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GSP teaches Lex Fridman how to street fight

In a street fight I would rather fight Francis and Gannou and fight the Bas Ruton in a street fight. Yeah, so very often people ask me the difference between a street fight and a fight and mixed martial art. The difference is in the street there is no referee and there is an instigator and there is the other person. The best in life for a street fight is always to not be the instigator because you have the element of surprise. So if you're in a heated argument with someone and then you feel that you potentially gonna be into a fight the best thing to do is to never show your center line. To always go on the side and put your hand up like this. You know that's one of the best thing to do. It's a self-defense tactic that it's used all around the world. Because from there the distance that I have to travel to cause a lot of damage to him is very minimal. You know it's very short. You know I can go boom, I can go boom and I'm protected because if he ever tried to do anything my hands are already up but I'm ready to respond at any aggression. So the first thing is if you're in an argument and you feel the heat is rising is to eat first. You don't want to fight but you want to eat first. You want to hit first you know. So it's either boom hit first depending the situation if you're someone who's much less physically strong than the aggressor you can use in the eyes, in the genitals, in the neck you know and then you can leave the scene. However if I'm like this and the minute he touched me like he declared war. Now I can go and perform a self-defense move. Striking not wrestling. Yes, yes. It's always striking first and leave the scene if you're for example a kid or someone who's not as physically doesn't have the physical strength of your aggressor. Of course I'm a UFC champion so that does not apply to me but the key is on a tactical we always use the element of surprise and when you strike, strike first and strike to cause the most damage as possible. The eyes, you can use the neck and do the genitals and then after you can leave the scene. That's the the the gold of having the element of surprise. Okay we were talking about knives. Yes. What about weapons are involved? Run faster? So weapons is very important if someone has a weapon and attack me for having my money I give him my money even if I'm Georges Saint-Pierre and I'm UFC champion. However if someone put a knife on my throat here and he's telling me to go in the trunk. No, I don't want to go in the trunk because I know it might it I've seen this movie and it's a bad ending. So things that I can do first it's always make sure that I try to make my hand as close as possible as the weapon and I try to be as close range as possible. If he's here I cannot do it because he's the distance is too far. If he's here that's idea so I can I can I can act like I want to look scared. Yeah please please please boom see here here I use my body and then I can go and break you know. So the idea is to use your entire body to deflect the weapon. So if the weapon is like this and the blade is coming out this way I use the element of surprise. You see I use my body not only grabbing him like this so if he tries to come back with the the knife it's solid then I can go and break. If he if it's the blade is pointing the other side it's same thing here here and here I can I can I can use my body always to smother the weapon. Controlling the wrist yeah but if it's out here. If it's out if it's out here you know and yes exactly it's too there's too much distance. You want to make sure you you you you get close to the weapon because that's what can cause the most damage. This is very important. There is other situation if the opponent if let's say you're a kid or someone come grab you by the body here you run by the body what I can do is grab the head and put my fingers inside the the eyes will with will make my opponent to release me immediately then I can I can go and leave. Yeah thumb in the eyes you you you push in the eyes. There is no rules. The eyes is always my favorite choice to go for because if you cannot see it's very hard to fight and normally the reflex for most people when they can't see they they they grab their eyes you know so it released the the the grip. I'm not gonna ask about the tie because I think you're wrong still. I think it's possible so like if you it's possible to use it as a same as for like a head smash like this kind of situation as opposed to a choke. I think it could be an advantage if it's a fake tie if it's if it's like something that can go like that can like a like a reptile that like a tail of a reptile that can go so if you try to pull my tie it goes out and now I know I get a head start. Exactly it's all about the element of surprise you want to to strike first the element of surprise in this street. George thank you so much for talking today. My pleasure. For looking for sharp men in black baby men in black.

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John Hopfield: Physics View of the Mind and Neurobiology | Lex Fridman Podcast #76

The following is a conversation with John Hopfield, professor at Princeton, whose life's work weaved beautifully through biology, chemistry, neuroscience, and physics. Most crucially, he saw the messy world of biology through the piercing eyes of a physicist. He's perhaps best known for his work on associative neural networks, now known as Hopfield networks, that were one of the early ideas that catalyzed the development of the modern field of deep learning. As his 2019 Franklin Medal in Physics Award states, he applied concepts of theoretical physics to provide new insights on important biological questions in a variety of areas, including genetics and neuroscience, with significant impact on machine learning. And as John says in his 2018 article titled, "'Now What?' His accomplishments have often come about by asking that very question, now what? And often responding by a major change of direction." This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do one or two minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is to me an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem that in the end provides an easy interface that takes a step up the next layer of abstraction over the stock market, making trading more accessible for new investors and diversification much easier. So again, if you get Cash App from the App Store or Google Play, and use code LEXPODCAST, you'll get $10, and Cash App will also donate $10 to Thirst, one of my favorite organizations that is helping advance robotics and STEM education for young people around the world. And now, here's my conversation with John Hopfield. What difference between biological neural networks and artificial neural networks is most captivating and profound to you? At the higher philosophical level, let's not get technical just yet. One of the things that very much intrigues me is the fact that neurons have all kinds of components, properties to them. And evolutionary biology, if you have some little quirk in how a molecule works or how a cell works, and it can be made use of, evolution will sharpen it up and make it into a useful feature rather than a glitch. And so you expect in neurobiology for evolution to have captured all kinds of possibilities of getting neurons, of how you get neurons to do things for you. And that aspect has been completely suppressed in artificial neural networks. So the glitches become features in the biological neural network? They can. Look, let me take one of the things that I used to do research on. If you take things which oscillate, they have rhythms which are sort of close to each other, under some circumstances, these things will have a phase transition and suddenly the rhythm will, everybody will fall into step. There was a marvelous physical example of that in the Millennium Bridge across the Thames River, about, built about 2001. And pedestrians walking across, pedestrians don't walk, synchronize, they don't walk in lockstep, but they're all walking about the same frequency. And the bridge could sway at that frequency and the slight sway made pedestrians tend a little bit to lock into step. And after a while, the bridge was oscillating back and forth and the pedestrians were walking in step to it. You could see it in the movies made out of the bridge. And the engineers made a simple, minor mistake. They assumed when you walk, it's step, step, step, and it's back and forth motion. But when you walk, it's also right foot, left foot, side to side motion. And it's the side to side motion for which the bridge was strong enough, but it wasn't stiff enough. And as a result, you would feel the motion and you'd fall into step with it. And people were very uncomfortable with it. They closed the bridge for two years while they built stiffening for it. Now, nerves, look, nerve cells produce action potentials. You have a bunch of cells which are loosely coupled together producing action potentials of the same rate. There'll be some circumstances under which these things can lock together. Other circumstances in which they won't. Well, they fire together, you can be sure that the other cells are gonna notice it. So you can make a computational feature out of this in an evolving brain. Most artificial neural networks don't even have action potentials, let alone have the possibility for synchronizing them. And you mentioned the evolutionary process. So the evolutionary process that builds on top of biological systems leverages the weird mess of it somehow. So how do you make sense of that ability to leverage all the different kinds of complexities in the biological brain? Well, look, at the biological molecule level, you'd have a piece of DNA which encodes for a particular protein. You could duplicate that piece of DNA and now one part of it can code for that protein, but the other one could itself change a little bit and thus start coding for a molecule which is slightly different. Now, if that molecule was just slightly different, had a function which helped any old chemical reaction was as important to the cell, it would go ahead and let that try and evolution would slowly improve that function. And so you have the possibility of duplicating and then having things drift apart. One of them retain the old function, the other one do something new for you. And there's evolutionary pressure to improve. Look, there is in computers too, but it's improvement has to do with closing some companies and opening some others. The evolutionary process looks a little different. Yeah, similar time scale perhaps. Much shorter in time scale. Companies close, yeah, go bankrupt and are born. Yeah, shorter, but not much shorter. Some companies last a century, but yeah, you're right. I mean, if you think of companies as a single organism that builds and you all know, yeah, it's a fascinating dual correspondence there between biological- And companies have difficulty having a new product competing with an old product. Yeah. And when IBM built its first PC, you probably read the book, they made a little isolated internal unit to make the PC. And for the first time in IBM's history, they didn't insist that you build it out of IBM components, but they understood that they could get into this market, which is a very different thing by completely changing their culture. And biology finds other markets in a more adaptive way. In a more adaptive way. Yeah, it's better at it. It's better at that kind of integration. So maybe you've already said it, but what to use the most beautiful aspect or mechanism of the human mind? Is it the adaptive, the ability to adapt as you've described or is there some other little quirk that you particularly like? Adaptation is everything when you get down to it, but the difference, there are differences between adaptation where you're learning goes on only over generations and over evolutionary time, where you're learning goes on at the time scale of one individual who must learn from the environment during that individual's lifetime. And biology has both kinds of learning in it. And the thing which makes neurobiology hard is that a mathematical system, as it were, built on this other kind of evolutionary system. What do you mean by mathematical system? Where's the math and the biology? Well, when you talk to a computer scientist about neural networks, it's all math. The fact that biology actually came about from evolution and the fact that biology is about a system which you can build in three dimensions. If you look at computer chips, computer chips are basically two-dimensional structures, maybe 2.1 dimensions, but they really have difficulty doing three-dimensional wiring. Biology is, the neocortex is actually also sheet-like and it sits on top of the white matter, which is about 10 times the volume of the gray matter and contains all what you might call the wires. But there's a huge, the effect of computer structure on what is easy and what is hard is immense. So. And biology does, it makes some things easy that are very difficult to understand how to do computationally. On the other hand, you can't do simple floating-point arithmetic, so it's awfully stupid. Yeah, and you're saying this kind of three-dimensional, complicated structure makes, it's still math. It's still doing math. The kind of math it's doing enables you to solve problems of a very different kind. That's right, that's right. So you mentioned two kinds of adaptation, the evolutionary adaptation and the adaptation or learning at the scale of a single human life. Which do you, which is particularly beautiful to you and interesting from a research and from just a human perspective? And which is more powerful? I find things most interesting that I begin to see how to get into the edges of them and tease them apart a little bit and see how they work. And since I can't see the evolutionary process going on, I'm in awe of it, but I find it just a black hole as far as trying to understand what to do. And so in a certain sense, I'm in awe of it, but I couldn't be interested in working on it. The human life's time scale is however thing you can tease apart and study. Yeah, you can do, there's the developmental neurobiology which understands how the connections and how the structure evolves from a combination of what the genetics is like and the real, the fact that you're building a system in three dimensions. And in just days and months, those early days of a human life are really interesting. They are, and of course, there are times of immense cell multiplication. There are also times of the greatest cell death in the brain is during infancy. It's turnover. So what is not effective, what is not wired well enough to use the moment, throw it out. It's a mysterious process. From, let me ask, from what field do you think the biggest breakthroughs in understanding the mind will come in the next decades? Is it neuroscience, computer science, neurobiology, psychology, physics? Maybe math, maybe literature? Well, of course, I see the world always through a lens of physics. I grew up in physics and the way I pick problems is very characteristic of physics and of an intellectual background, which is not psychology, which is not chemistry and so on and so on. Now, both of your parents are physicists. Both of my parents were physicists and the real thing I got out of that was a feeling that the world is an understandable place and if you do enough experiments and think about what they mean and structure things so you can do the mathematics of the relevant to the experiments, you also be able to understand how things work. But that was a few years ago. Did you change your mind at all through many decades of trying to understand the mind, of studying it different kinds of ways? Not even the mind, just biological systems. You still have hope that physics, that you can understand? There's a question of what do you mean by understand? Of course. When I taught freshman physics, I used to say, I wanted to give physics to understand the subject, to understand Newton's laws. I didn't want them simply to memorize a set of examples to which they knew the equations to write down to generate the answers. I had this nebulous idea of understanding so that if you looked at a situation, you could say, oh, I expect the ball to make that trajectory or I expect some intuitive notion of understanding. And I don't know how to express that very well and I've never known how to express it well. And you run smack up against it when you look at these simple neural nets, feedforward neural nets, which do amazing things and yet you know contain nothing of the essence of what I would have felt was understanding. Understanding is more than just an enormous lookup table. Let's linger on that. How sure you are of that? What if the table gets really big? So, I mean, ask another way, these feedforward neural networks, do you think they'll ever understand? Could answer that in two ways. I think if you look at real systems, feedback is an essential aspect of how these real systems compute. On the other hand, if I have a mathematical system with feedback, I know I can unlayer this and do it. But I have an exponential expansion in the amount of stuff I have to build if I can solve the problem that way. So feedback is essential. So we can talk even about recurrent neural nets, so recurrence. But do you think all the pieces are there to achieve understanding through these simple mechanisms? Like back to our original question, what is the fundamental, is there a fundamental difference between artificial neural networks and biological? Or is it just a bunch of surface stuff? Suppose you ask a neurosurgeon, when is somebody dead? Yeah. They'll probably go back to saying, well, I can look at the brain rhythms and tell you this is a brain which is never gonna function again. This one is, this other one is one which if we treat it well, is still recoverable. And then just do that by some electrodes looking at simple electrical patterns which don't look in any detail at all at what individual neurons are doing. These rhythms are utterly absent from anything which goes on at Google. Yeah, but the rhythms. But the rhythms what? So, well, that's like comparing, okay, I'll tell you, it's like you're comparing the greatest classical musician in the world to a child first learning to play. The question I'm at, but they're still both playing the piano. I'm asking, will it ever go on at Google? Do you have a hope? Because you're one of the seminal figures in launching both disciplines, both sides of the river. I think it's going to go on generation after generation the way it has where what you might call the AI computer science community says, let's take the following. This is our model of neurobiology at the moment. Let's pretend it's good enough and do everything we can with it. And it does interesting things. And after a while, it sort of grinds into the sand and you say, ah, something else is needed for neurobiology and some other grand thing comes in and enables you to go a lot further. But we'll go into the sand again. And I think it could be generations of this evolution. I don't know how many of them, and each one is going to get you further into what our brain does. In some sense, past the Turing test, longer and more broad aspects. And how many of these are good there are going to have to be before you say, I've made something, I've made a human, I don't know. But your sense is it might be a couple. My sense is it might be a couple more. Yeah. And going back to my brain waves as it were, from the AI point of view, they would say, ah, maybe these are an heavy phenomenon and not important at all. The first car I had, a real wreck of a 1936 Dodge, go above 45 miles an hour and the wheels would shimmy. Yeah. Good speedometer that. Now, nobody designed the car that way. The car is malfunctioning to have that. But in biology, if it were useful to know when are you going more than 45 miles an hour, you just capture that and you wouldn't worry about where it came from. Yeah. It's going to be a long time before that kind of thing, which can take place in large complex networks of things, is actually used in the computation. Look, how many transistors are there in your laptop these days? Actually, I don't know the number. It's- It's on the scale of 10 to the 10. I can't remember the number either. Yeah. And all the transistors are somewhat similar. And most physical systems with that many parts, all of which are similar, have collective properties. Yes. Sound waves in air, earthquakes, what have you, have collective properties. Whether, there are no collective properties used in artificial neural networks, in AI. Yeah, it's very- If biology uses them, it's going to take us to more generations of things for people to actually dig in and see how they are used and what they mean. See, you're very right. I might have to return several times to neurobiology and try to make our transistors more messy. Yeah, yeah. At the same time, the simple ones will conquer big aspects. And I think one of the most biggest surprises to me was how well learning systems, which are manifestly non-biological, how important they can be actually, and how important and how useful they can be in AI. So, if we can just take a stroll to some of your work, that is incredibly surprising, that it works as well as it does, that launched a lot of the recent work with neural networks. If we go to what are now called Hopfield networks, can you tell me what is associative memory in the mind for the human side? Let's explore memory for a bit. Okay, what you mean by associative memory is, ah, you have a memory of each of your friends. Your friend has all kinds of properties from what they look like, what their voice sounds like, where they went to college, where you met them, go on and on, what science papers they've written. If I start talking about a five foot 10, wire-aided cognitive scientist who's got a very bad back, it doesn't take very long for you to say, oh, he's talking about Jeff Hinton. I never mentioned the name or anything very particular, but somehow a few facts that are associated with a particular person enables you to get a hold of the rest of the facts, or not the rest of them, another subset of them. And it's this ability to link things together, link experiences together, which goes under the general name of associative memory. And a large part of intelligent behavior is actually just large associative memories that work, as far as I can see. What do you think is the mechanism of how it works in the mind? Is it a mystery to you still? Do you have inklings of how this essential thing for cognition works? What I made 35 years ago was, of course, a crude physics model to show the kind, to actually enable you to understand, my old sense of understanding as a physicist, because you could say, ah, I understand why this goes to stable states, it's like things going downhill. Right. And that gives you something with which to think in physical terms, rather than only in mathematical terms. So you've created these associative artificial networks. That's right. And now if you look at what I did, I didn't at all describe a system which gracefully learns. I described a system in which you could understand how learning could link things together, how very crudely it might learn. One of the things which intrigues me as I reinvestigate that system now to some extent is, look, I'll see you every second for the next hour or what have you. Each look at you is a little bit different. I don't store all those second by second images. I don't store 3000 images. I somehow compact this information. So I now have a view of you, which I can use. It doesn't slavishly remember anything in particular, but it compacts the information into useful chunks, which are somehow, it's these chunks, which are not just activities of neurons, bigger things than that, which are the real entities which are useful to you. Useful to you to describe, to compress this information. Coming at you. And you have to compress it in such a way that if the information comes in just like this again, I don't bother to rewrite it, or efforts to rewrite it, simply do not yield anything because those things are already written. And that needs to be not, look this up, have I written this, have I stored it somewhere already? That'd be something which is much more automatic in the machine hardware. Right, so in the human mind, how complicated is that process, do you think? So you've created, feels weird to be sitting with John Hopfield calling him Hopfield Networks, but. It is weird. Yeah, but nevertheless, that's what everyone calls him, so here we are. So that's a simplification, that's what a physicist would do. You and Richard Feynman sat down and talked about associative memory. Now if you look at the mind, where you can't quite simplify it so perfectly, do you think that. Let me backtrack just a little bit. Yeah, biology is about dynamical systems. Computers are dynamical systems. You can ask, if you want to model biology, if you want to model neurobiology, what is the time scale? There's a dynamical system in which, fairly fast time scale in which you could say, the synapses don't change much during this computation, so I'll think of the synapses fixed and just do the dynamics of the activity. Or you can say, the synapses are changing fast enough that I have to have the synaptic dynamics working at the same time as the system dynamics in order to understand the biology. Most, if you look at the feed-forward artificial neural nets, they're all done as learnings. First of all, I spend some time learning, not performing, then I turn off learning and I perform. Right. That's not biology. And so as I look more deeply at neurobiology, even as associative memory, I've got to face the fact that the dynamics of a synapse change is going on all the time. And I can't just get by by saying, I'll do the dynamics of activity with fixed synapses. So the synaptic, the dynamics of the synapses is actually fundamental to the whole system. Yeah, yeah. And there's nothing necessarily separating the time scales. When the time scales can be separated, it's neat from the physicist's or the mathematician's point of view, but it's not necessarily true in neurobiology. So you're kind of dancing beautifully between showing a lot of respect to physics and then also saying that physics cannot quite reach the complexity of biology. So where do you land? Or do you continuously dance between the two? I continuously dance between them because my whole notion of understanding is that you can describe to somebody else how something works in ways which are honest and believable and still not describe all the nuts and bolts in detail. Weather. I can describe weather as 10 to the 32 molecules colliding in the atmosphere. I can simulate weather that way, I have a big enough machine. I'll simulate it accurately. It's no good for understanding. I just want to understand things. I want to understand things in terms of wind patterns, hurricanes, pressure differentials, and so on. All things as they're collective. And the physicist in me always hopes that biology will have some things which can be said about it which are both true and for which you don't need all the molecular details as the molecules colliding. That's what I mean from the roots of physics by understanding. So what did, again, sorry, but Hopfield Networks help you understand what insight did it give us about memory, about learning? They didn't give insights about learning. They gave insights about how things having learned could be expressed. How having learned a picture of you reminds me of your name. That would, it didn't describe a reasonable way of actually doing the learning. Or at least that if you had previously learned the connections of this kind of pattern would now be able to behave in a physical way which is a, oh, if I put part of the pattern in here, the other part of the pattern will complete over here. I can understand that physics if the right learning stuff had already been put in. And it could understand why then putting in a picture of somebody else would generate something else over here. But it did not have a reasonable description of the learning process. But even, so forget learning. I mean, that's just a powerful concept that sort of forming representations that are useful to be robust for error correction kind of thing. So this is kind of what the biology does that we're talking about. Yeah, and what my paper did was simply enable you, there are lots of ways of being robust. If you think of a dynamical system, you think of a system where a path is going on in time. And if you think of a computer, there's a computational path, which is going on in a huge dimensional space of ones and zeros. And an error correction system is a system which if you get a little bit off that trajectory, will push you back onto that trajectory again. So you get to the same answer in spite of the fact that there were things, the computation wasn't being ideally done all the way along the line. And there are lots of models for error correction. But one of the models for error correction is to say, there's a valley that you're following flowing down. And if you push a little bit off the valley, just like water being pushed a little bit by a rock, it gets back and follows the course of the river. And that basically the analog in the physical system, which enables you to say, oh yes, error-free computation and an associative memory are very much like things that I can understand from the point of view of a physical system. The physical system can be under some circumstances, an accurate metaphor. It's not the only metaphor. There are other error correction schemes, which don't have a valley and energy behind them. But those are correction schemes, which a mathematician may be able to understand, but I don't. So there's the physical metaphor that seems to work here. That's right, that's right. So these kinds of networks actually led to a lot of the work that is going on now in neural networks, artificial neural networks. So the follow-on work with restricted Boltzmann machines and deep belief nets followed on from these ideas of the Hopfield network. So what do you think about this continued progress of that work towards now re-revigorated exploration of feed-forward neural networks and recurrent neural networks and convolutional neural networks and kinds of networks that are helping solve image recognition, natural language processing, all that kind of stuff? It's always intrigued me that one of the most long-lived of the learning systems is the Boltzmann machine, which is intrinsically a feedback network. And with the brilliance of Hinton and Sanofsky to understand how to do learning in that. And it's still a useful way to understand learning and understand, and the learning that you understand in that has something to do with the way that feed-forward systems work. But it's not always exactly simple to express that intuition. But it always amuses me to see Hinton going back to the will yet again on a form of the Boltzmann machine, because really that which has feedback and interesting probabilities in it is a lovely encapsulation of something computational. Something both computational and physical. Computational in the, it's very much related to feed-forward networks. Physical in that Boltzmann machine learning is really learning a set of parameters for a physics Hamiltonian or energy function. What do you think about learning in this whole domain? Do you think the aforementioned guy, Jeff Hinton, all the work there with backpropagation, all the kind of learning that goes on in these networks, how do you, if we compare it to learning in the brain, for example, is there echoes of the same kind of power that backpropagation reveals about these kinds of recurrent networks, or is it something fundamentally different going on in the brain? I don't think the brain is as deep as the deepest networks go, the deepest computer science networks. And I do wonder whether part of that depth of the computer science networks is necessitated by the fact that the only learning that's easily done on a machine is feed-forward. And so there's the question of to what extent has the biology, which has some feed-forward and some feed-back, been captured by something which has got many more neurons, but much more depth than the neurons in it. So part of you wonders if the feedback is actually more essential than the number of neurons or the depth, the dynamics of the feedback. The dynamics of the feedback, look, if you don't have feedback, it's a little bit like building a big computer and running it through one clock cycle, and then you can't do anything until you reload something coming in. How do you use the fact that there are multiple clocks? How do I use the fact that you can close your eyes, stop listening to me, and think about a chess board for a few minutes without any input whatsoever? Yeah, that memory thing, that's fundamentally a feedback kind of mechanism. You're going back to something. Yes, it's hard to understand. Talk about introspect, let alone consciousness. Is that so? Let alone consciousness, yes, yes. Because that's tied up in there too. You can't just put that on another shelf. Every once in a while, I get interested in consciousness, and then I go and I've done that for years, and ask one of my bettors, as it were, their view on consciousness. It's been interesting collecting them. What is consciousness? Let's try to take a brief step into that room. Well, I asked Marvin Minsky, his view on consciousness, and Marvin said, consciousness is basically overrated. It may be an epiphenomenon. After all, all the things your brain does, which are actually hard computations, you do non-consciously. And there's so much evidence that even the simple things you do, you can make committed decisions about them. The neurobiologist can say, he's now committed. He's going to move the hand left before you know it. So his view that consciousness is not, that's just like little icing on the cake, the real cake is in the subconscious. Yeah, yeah. Subconscious, non-conscious. Non-conscious, what's the better word, sir? It's only that Freud captured the other word. Yeah, it's a confusing word, subconscious. Nicholas Chater wrote an interesting book. I think the title of it is, The Mind is Flat. Flat, in a neural net sense, might be flat is something which is a very broad neural net without really any layers in depth, or the deep brain would be many layers and not so broad. In the same sense that if you push Minsky hard enough, he would probably have said, "'Consciousness is your effort to explain to yourself that which you have already done.'" Yeah. Yeah, it's the weaving of the narrative around the things that have already been computed for you. That's right, and so much of what we do for our memories of events, for example, if there's some traumatic event you witness, you will have a few facts about it correctly done. If somebody asks you about it, you will weave a narrative which is actually much more rich in detail than that, based on some anchor points you have of correct things, and pulling together general knowledge on the other, but you will have a narrative. And once you generate that narrative, you are very likely to repeat that narrative and claim that all the things you have in it are actually the correct things. There was a marvelous example of that in the Watergate slash impeachment era of John Dean. John Dean, you're too young to know, had been the personal lawyer of Nixon. And so John Dean was involved in the coverup, and John Dean ultimately realized the only way to keep himself out of jail for a long time was actually to tell some of the truths about Nixon. And John Dean was a tremendous witness. He would remember these conversations in great detail, and very convincing detail. And long afterward, some of the tapes, the secret tapes as it were, from which Jane was recalling these conversations were published, and one found out that John Dean had a good but not exceptional memory. What he had was an ability to paint vividly and in some sense accurately the tone of what was going on. By the way, that's a beautiful description of consciousness. Do you, like where do you stand in your, today? So perhaps it changes day to day, but where do you stand on the importance of consciousness in our whole big mess of cognition? Is it just a little narrative maker, or is it actually fundamental to intelligence? That's a very hard one. When I asked Francis Crick about consciousness, he launched forward in a long monologue about Mendel and the peas. Yeah. And how Mendel knew that there was something, and how biologists understood that there was something in inheritance, which was just very, very different, and the fact that inherited traits didn't just wash out into a gray, but were this or this, and propagated, that that was absolutely fundamental to biology, and it took generations of biologists to understand that there was genetics, and it took another generation or two to understand that genetics came from DNA. But very shortly after Mendel, thinking biologists did realize that there was a deep problem about inheritance. And Francis would have liked to have said, and that's why I'm working on consciousness. But of course, he didn't have any smoking gun in the sense of Mendel. And that's the weakness of his position. If you read his book, which he wrote with Koch, I think. Yeah, Christoph Koch, yeah. I find it unconvincing for the smoking gun reason. So I go on collecting views without actually having taken a very strong one myself, because I haven't seen the entry point. Not seeing the smoking gun, from the point of view of physics, I don't see the entry point. Whereas in neurobiology, once I understood the idea of a collective, an evolution of dynamics, which could be described as a collective phenomenon, I thought, ah, there's a point where what I know about physics is so different from any neurobiologist that I have something that I might be able to contribute. And right now, there's no way to grasp at consciousness from a physics perspective. From my point of view, that's correct. And of course, people, physicists like everybody else, think very muddily about things. You ask the closely related question about free will, do you believe you have free will? Physicists will give an offhand answer and then backtrack, backtrack, backtrack, where they realize that the answer they gave must fundamentally contradict the laws of physics. Naturally, answering questions of free will and consciousness naturally lead to contradictions from a physics perspective. Because it eventually ends up with quantum mechanics, and then you get into that whole mess of trying to understand how much, from a physics perspective, how much is determined, already predetermined, much is already deterministic about our universe. There's lots of different- And if you don't push quite that far, you can say essentially all of neurobiology, which is relevant, can be captured by classical equations of motion. Because in my view of the mysteries of the brain are not the mysteries of quantum mechanics, but the mysteries of what can happen when you have a dynamical system, driven system with 10 to the 14 parts. That that complexity is something which is, that the physics of complex systems is at least as badly understood as the physics of phase coherence in quantum mechanics. Can we go there for a second? You've talked about attractor networks, and just maybe you could say what are attractor networks, and more broadly, what are interesting network dynamics that emerge in these or other complex systems? You have to be willing to think in a huge number of dimensions, because in a huge number of dimensions, the behavior of a system can be thought of as just the motion of a point over time in this huge number of dimensions. Right. And an attractor network is simply a network where there is a line, and other lines converge on it in time. That's the essence of an attractor network. That's how you- In a highly dimensional space. And the easiest way to get that is to do it in a highly dimensional space where some of the dimensions provide the dissipation, which means, which, look, I have a physical system, trajectories can't contract everywhere. They have to contract in some places and expand in others. There's a fundamental classical theorem of statistical mechanics, which goes under the name of Liouville's theorem, which says you can't contract everywhere. You have to, if you contract somewhere, you expand somewhere else. And it's an interesting physical systems. You get driven systems where you have a small subsystem, which is the interesting part, and the rest of the contraction and expansion, the physicists would say is entropy flow in this other part of the system. But basically, attractor networks are dynamics funneling down, so you can't be any, so if you start somewhere in the dynamical system, you will soon find yourself on a pretty well-determined pathway, which goes somewhere. You start somewhere else, you'll wind up on a different pathway, but you don't have just all possible things. You have some defined pathways, which are allowed and onto which you will converge. And that's the way you make a stable computer, and that's the way you make a stable behavior. So in general, looking at the physics of the emergent stability in these networks, what are some interesting characteristics that, what are some interesting insights from studying the dynamics of such high-dimensional systems? Most dynamical systems, most driven dynamical systems, by driven, they're coupled somehow to an energy source, and so their dynamics keeps going because it's coupling to the energy source. Most of them, it's very difficult to understand at all what the dynamical behavior is going to be. You have to run it. You have to run it. There's a subset of systems which has what is actually known to the mathematicians as a Lyapunov function. And those systems, you can understand convergent dynamics by saying you're going downhill on something or other. And that's what I found with ever knowing what Lyapunov functions were in the simple model I made in the early 80s, was an energy function so you could understand how you could get this channeling onto pathways without having to follow the dynamics in infinite detail. You started rolling a ball off of a mountain that's going to wind up at the bottom of a valley. You know that's true without actually watching the ball roll down. There are certain properties of the system that when you can know that. That's right. And not all systems behave that way. Most don't, probably. Most don't, but it provides you with a metaphor for thinking about systems which are stable and who to have these attractors behave even if you can't find a Lyapunov function behind them or an energy function behind them. It gives you a metaphor for thought. Speaking of thought, if I had a glint in my eye with excitement and said, you know, I'm really excited about this, something called deep learning and neural networks, and I would like to create an intelligent system and came to you as an advisor, what would you recommend? Is it a hopeless pursuit to use neural networks to achieve thought? Is it, what kind of mechanisms should we explore? What kind of ideas should we explore? Well, you look at the simple networks, one-pass networks, they don't support multiple hypotheses very well. As I have tried to work with very simple systems which do something which you might consider to be thinking, thought has to do with the ability to do mental exploration before you make it take a physical action. Almost like we were mentioning, playing chess, visualizing, simulating inside your head, different outcomes. Yeah, yeah. And now you could do that in a feed-forward network because you've pre-calculated all kinds of things. But I think the way neurobiology does it, it hasn't pre-calculated everything. It actually has parts of a dynamical system in which you're doing exploration in a way which is... There's a creative element. Like there's an... There's a creative element. And in a simple-minded neural net, you have a constellation of instances from which you've learned. And if you are within that space, if a new question is a question within this space, you can actually rely on that system pretty well to come up with a good suggestion for what to do. If on the other hand, the query comes from outside the space, you have no way of knowing how the system is going to behave. There are no limitations on what could happen. And so with the artificial neural net world is always very much, I have a population of examples. The test set must be drawn from the equivalent population. If the test set has examples which are from a population which is completely different, there's no way that you could expect to get the answer right. Yeah. And so- What they call outside the distribution. That's right. That's right. And so if you see a ball rolling across the street at dusk, if that wasn't in your training set, the idea that a child may be coming close behind that is not going to occur to the neural net. And it is to our, there's something in your biology that allows that. Yeah. There's something in the way of what it means to be outside of the population of the training set. The population of the training set isn't just sort of this set of examples. There's more to it than that. And it gets back to my own question of what is it to understand something? Yeah. You know, in a small tangent, you've talked about the value of thinking of deductive reasoning in science versus large data collection. So sort of thinking about the problem. I suppose it's the physics side of you of going back to first principles and thinking. But what do you think is the value of deductive reasoning in the scientific process? Well, there are obviously scientific questions in which the route to the answer to it comes through the analysis of one hell of a lot of data. Right. Cosmology, that kind of stuff. And that's never been the kind of problem in which I've had any particular insight. Though I must say, if you look at, I mean, cosmology is one of those. If you look at the actual things that Jim Peebles, one of this year's Nobel Prize physics ones from the local physics department, the kinds of things he's done, he's never crunched large data. Never, never, never. He's used the encapsulation of the work of others in this regard. Right. But ultimately it boiled down to thinking through the problem. Like what are the principles under which a particular phenomenon operates? Yeah, yeah. And look, physics is always going to look for ways in which you can describe the system in a way which rises above the details. And to the hard-dyed-in-the-wool biologist, biology works because of the details. And physics, to the physicists, we want an explanation which is right in spite of the details. And there will be questions which we cannot answer as physicists because the answer cannot be found that way. There's, I'm not sure if you're familiar with the entire field of brain-computer interfaces. That's become more and more intensely researched and developed recently, especially with companies like Neuralink with Elon Musk. Yeah, I know there have always been the interest both in things like getting the eyes to be able to control things or getting the thought patterns to be able to move what had been a connected limb which is now connected through a computer. That's right. So in the case of Neuralink, they're doing a thousand plus connections where they're able to do two-way, activate and read spikes, neural spikes. Do you have hope for that kind of computer brain interaction in the near or maybe even far future of being able to expand the ability of the mind of cognition or understand the mind? It's interesting watching things go. When I first became interested in neurobiology, most of the practitioners thought you would be able to understand neurobiology by techniques which allowed you to record only one cell at a time. One cell, yeah. People like David Hubel very strongly reflected that point of view and that's been taken over by a generation, a couple of generations later by a set of people who says, not until we can record from 10 to the four or 10 to the five at a time, will we actually be able to understand how the brain actually works. And in a general sense, I think that's right. You have to begin to be able to look for the collective modes, collective operations of things. It doesn't rely on this action potential of that cell. It relies on the collective properties of this set of cells connected with this kind of patterns and so on. And you're not going to succeed in seeing what those collective activities are without recording many cells at once. The question is how many at once? What's the threshold? And that's the- Yeah, and look, it's being pursued hard in the motor cortex. The motor cortex does something which is complex and yet the problem you're trying to address is fairly simple. Now, neurobiology does it in ways that differ from the way an engineer would do it. An engineer would put in six highly accurate stepping motors controlling a limb rather than 100,000 muscle fibers, each of which has to be individually controlled. And so understanding how to do things in a way which is much more forgiving and much more neural, I think would benefit the engineering world in a way that I think would benefit the engineering world. The engineering world, ah, touch. Let's put in a pressure sensor or two, rather than an array of a gazillion pressure sensors, none of which are accurate, all of which are perpetually recalibrating themselves. So you're saying your hope is, your advice for the engineers of the future is to embrace the large chaos of a messy, error-prone system like those of the biological systems. Like that's probably the way to solve some of these. I think you'll be able to make better computations slash robotics that way than by trying to force things into a robotics where joint motors are powerful and stepping motors are accurate. But then the physicists, the physicists in you will be lost forever in such systems because there's no simple fundamentals to explore in systems that are so large and messy. Well, you say that, and yet there's a lot of physics, in the Navier-Stokes equations, the equations of nonlinear hydrodynamics, huge amount of physics in them. All the physics of atoms and molecules has been lost, but it's been replaced by this other set of equations, which is just as true as the equations at the bottom. Now those equations are going to be harder to find in general biology. But the physicist in me says there are probably some equations of that sort. They're out there. They're out there. And if physics is going to contribute to anything, it may contribute to trying to find out what those equations are and how to capture them from the biology. Would you say that's one of the main open problems of our age is to discover those equations? Yeah, if you look at, there's molecules and there's psychological behavior. And these two are somehow related. They're layers of detail. They're layers of collectiveness. And to capture that in some vague way, several stages on the way up to see how these things can actually be linked together. So it seems in our universe, there's a lot of elegant equations that can describe the fundamental way that things behave, which is a surprise. I mean, it's compressible into equations. It's simple and beautiful. But it's still an open question whether that link is equally between molecules and the brain is equally compressible into elegant equations. But your sense, you're both a physicist and a dreamer. You have a sense that- Yeah, but I can only dream physics dreams. Yeah, physics dreams. There was an interesting book called Einstein's Dreams, which alternates between chapters on his life and descriptions of the way time might have been, but isn't. The linking between these being, of course, ideas that Einstein might've had to think about the essence of time as he was thinking about time. So speaking of the essence of time and your biology, you're one human, famous impactful human, but just one human with a brain living the human condition, but you're ultimately mortal, just like all of us. Has studying the mind as a mechanism changed the way you think about your own mortality? It has really, because particularly as you get older and the body comes apart in various ways, I became much more aware of the fact that what is somebody is contained in the brain and not in the body that you worry about burying. And it is to a certain extent true that for people who write things down, equations, dreams, notepads, diaries, fractions of their thought does continue to live after they're dead and gone, after their body is dead and gone. And there's a sea change in that going on in my lifetime between when my father died, when except for the things which were actually written by him as it were, very few facts about him will have ever been recorded. And the number of facts which are recorded about each and every one of us forever now, as far as I can see, in the digital world. And so the whole question of what is death may be different for people a generation ago and a generation further ahead. Maybe we have become immortal under some definitions. Yeah, yeah. Last easy question, what is the meaning of life? Looking back, you've studied the mind, us weird descendants of apes, what's the meaning of our existence on this little earth? Oh, that word meaning is as slippery as the word understand. Interconnected somehow, perhaps. Is there, it's slippery, but is there something that you, despite being slippery, can hold long enough to express? I've been amazed at how hard it is to define the things in a living system in the sense that one hydrogen atom is pretty much like another, but one bacterium is not so much like another bacterium, even of the same nominal species. In fact, the whole notion of what is the species gets a little bit fuzzy. And the species exists in the absence of certain classes of environments. And pretty soon one winds up with a biology which the whole thing is living, but whether there's actually any element of it, which by itself would be said to be living, it becomes a little bit vague in my mind. Yeah. So in a sense, the idea of meaning is something that's possessed by an individual, like a conscious creature. And you're saying that it's all interconnected in some kind of way that there might not even be an individual, or all kind of this complicated mess of biological systems at all different levels where the human starts and when the human ends is unclear. Yeah, yeah, and we're in neurobiology where the, oh, you say the neocortex is the thinking, but there's lots of things that are done in the spinal cord. And so what is the essence of thought? Is it just gonna be neocortex? Can't be, can't be. Yeah, maybe to understand and to build thought, you have to build the universe along with the neocortex. It's all interlinked through the spinal cord. John, it's a huge honor talking today. Thank you so much for your time. I really appreciate it. Well, thank you for the challenge of talking with you. And it'll be interesting to see whether you can win five minutes out of this, just coherent sense to anyone. Beautiful. Thanks for listening to this conversation with John Hopfield. And thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, an organization that inspires and educates young minds to become science and technology innovators of tomorrow. If you enjoy this podcast, subscribe on YouTube, get five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words of wisdom from John Hopfield in his article titled, Now What, choosing problems is the primary determinant of what one accomplishes in science. I have generally had a relatively short attention span in science problems. Thus, I have always been on the look out for more interesting questions, either as my present ones get worked out, or as it get classified by me as intractable, given my particular talents. He then goes on to say, what I have done in science relies entirely on experimental and theoretical studies by experts. I have a great respect for them, especially for those who are willing to attempt communication with someone who is not an expert in the field. I would only add that experts are good at answering questions. If you're brash enough, ask your own. Don't worry too much about how you found them. Thank you for listening and hope to see you next time.

https://youtu.be/DKyzcbNr8WE

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Comma.ai Drive and Tour with George Hotz and Lex Fridman

George Hotz gave me a demo of the Kama 2 on a ride back to the Kama AI offices in San Diego. Then we took a quick tour of the office. I found both the Kama 2 system and the entire Kama AI team and operation very impressive. Plus I got a 3D printer named after me. As one robot to another, we're in this together my brother. And now on to the ride and tour with George Hotz. I'm here with uh driving with George Hotz and uh looking at the Kama 2. Trying to find a stretch of road where we can enable it. Okay just start looping back to the office. I mean I could enable it here but this isn't really where it shines. But yeah so we don't have we don't have red lights and stop signs yet. I don't want to ship it until we have a real uh holistic one. Until we have an end-to-end one. So you would be able to then like stop at a stop sign. So the longitudinal control. Did you just enable it? I just enabled it yeah. So this is the uh so we're gonna have to stop at this light. But um how do you enable it? Uh cruise control. So that's that's the the integrated knobs on the on the car. Yeah we have a good we'll go on the 163 a bit and that's that's that's a good test of uh whether your level two system's any good. Supercruise actually can't do it. Supercruise can't do it because they're they're not good enough with roll on the road. Autopilot can do it and we can do it. How's San Diego in terms of quality of roads and lane markings all that kind of stuff? Pretty mediocre like the rest of California. What's your favorite uh reason for using KAMA? Like when when do you find the most joy? Oh oh it's it's long trips. It's um you know driving from here to LA you'll do it without a disengagement almost. You can you can you know it's two hours to LA from here you could just go to LA uh get in your car and you just sit there and watch and it's it's a it's a great time. All right so we can we can engage here. So you know watch. So it doesn't technically require you to engage. It's just it's just it's just a little bit of a hassle. So it doesn't technically require perfect lane markings? No not at all. In fact you can do lane changes on roads that don't have lane markings because it's all end to end. So I have to get over three lanes. I'm just going to take control here to do it especially since there's a cop there. So let me just get over three lanes and then this road's a decent demo. Yeah so I think only us and Autopilot can do this road. Pretty curvy. Yeah and uh it's not just curvy it's also banked. And if you don't yeah if you don't do that well if you don't have a model that can detect that. So the longitudinal policy is actually just being done by the car. Hyundai has quite a competent ACC. Probably the best one. So we haven't really felt the urge to move to our gas and brakes. There's a few cute things where which ours will do better and more holistically than theirs. But um really it's about the turning. How hard is it to get it to be this smooth? Uh hard. Five years of engineering. All this end to end huh? We weren't detecting the lane lines. They're used but they're more used as uh see like right there. That's the stock system being too harsh on the brakes. If you're a human driving you would have been much more gradual on the brakes there. But we're really going to push to switch all the longitudinals to open pilot once we have end-to-end longitudinal and the same way we have end-to-end lateral. What's harder end-to-end longitudinal end-to-end lateral? We put a lot more work into end-to-end lateral because there's a lot more subtlety in that. The car companies have managed to build competent longitudinal. We have competent longitudinal using old school policies. But lateral there's so much subtlety. For example like when a lane splits out should you follow that split? Should you stay in the center? Should you stay to one side? Or so much subtlety there. And making it all smooth and not freak out. Yeah and this thing you know the reason I feel very confident keeping my hands off the wheel our torque limit is so much lower than Tesla's. So you can't can't do anything crazy? No. We do injection tests where one person sits in that seat with a joystick and the other person keeps their hands off the wheel and that person you can't look at them they're free to jam the joystick in any direction and if you don't feel you know safe in that maneuver they take back over here because we're getting off here. But um yeah. That stretch of road is a is a is a competent demonstration of open pilot. Yeah that was impressive. It's not the high end. Maybe when we get to the the city streets I'll engage on the city streets. Is uh city streets like a compelling use case or is that just kind of uh intuition builder? Without end-to-end longitudinal it's pretty uh like it's not really useful as product. So it's more just it's cool that it can do it and it's not really useful. Um so it's more just it's cool that it can do it and like we don't gate it off but most of open pilot uh is highways like most of the value real gain is is highways. Um but also well not just highways also like um like one lane each way kind of things like double yellow kind of roads. I was doing all like the mountains up in Colorado with this thing and just yeah you get to look at the mountains before it dries. Um so like I can engage it here. Nice um now remember the longitudinal policy is is Hyundai uh and it's not ideal for cities. But um so again we're going to go through this intersection with no lines. Oh yeah. See notice how there's no line there yet our placement is still almost human ideal. Yeah this is great. So there I mean there you see we did a stretch of you know a minute of city and perfectly human nothing sketchy. See places like that are where disengage on gas is really nice. Really easy to you know hand off you always know when that handoff is happening with the noise. It didn't like keep the ACC on or anything. God if it kept the ACC on and I make the turn and it's like trying to accelerate at a weird time you know just asking to have a bad time. I like the the sounds the visuals they clear when it's on and when it's off. Love it. Well done. Look at this. Let's stay on the bike. Damn that's impressive. That's really impressive. That's the intersections without thinking about it. Okay that was awesome. It's communicating the uncertainty with this movement a little bit. Yeah. I like it. Humans actually wobble a little more than you think too. You notice it a lot more in this. Yeah that's an interesting point. Yeah. Yeah true. I think Jesse Levinson mentioned this on one of his interviews. He's like so you know we have all these we have the safety driver sit in the car and mark every tiny mistakes it made and then we also had the safety driver who was like you know I think we have all these we have the safety driver sit in the car and mark every tiny mistakes it made and then we also had the safety driver sit in a car that was being human driven and mark all the little tiny mistakes it made. This is the Kama office in downtown. Kama office is right here. We're at Kama AI offices with Mr. George Hotz. Can you give us a little tour? It doesn't light up anymore. I don't know why. I think most of these dashboards are okay. We're almost at 30 million open pilot miles. Wow. It's a hell of a number. So here here's dailies, weeklies and uh so actually yeah dailies are like maybe not 2,000. 1.5. So those are used daily and then used weekly. Yeah. That's really cool. Weeklies are almost 2.5 and monthlies are a little over 3. This is how many devices are on our botnet in the last hour. Botnet last day, botnet last week. Is this all over the United States? This is no this is everywhere. So here's here's here's the maps. All right here's the map of the world. So we're everywhere in the world. So let's see. In the last 30 days we had 2,200 in the U.S. And then Korea, Canada, Taiwan. Japan's up there. This is our percent engaged. So percent of miles engaged is about 50 percent. Percent time engaged is about 30. Our disengagements are split pretty evenly between cancel, gas and break. Most of our segments are now coming from Comma 2s. Comma 2s. Comma 2s is the big the big breakout for this company. Yeah. Oh yeah, it's profitable. This is our live link to the Europe office. And come as a multinational corporation. George just erased a bunch of top secret things. Censorship, the censors came in. Yeah, yeah, yeah. Look the missions at the top of the board. Solve self-driving cars while delivering shippable intermediaries. Amen. What do we do badly? What can we do better? Right. Good questions. Open pilot 1.0, when is that coming up? When those things are done. PyTorch. Okay. I like how that's a bullet point. That's like move everything to PyTorch. Oh, sorry. It's not a data center, it's a compute cluster. For legal reasons, it's a compute cluster. It's a compute cluster, okay. That sounds sexier too. Data ingestion, multi-chain. Cool. So this is like a, This is the list of vision board for open pilot 1.0. It's not going to happen for a while. But the Comma 2 is going to get open pilot 1.0. It's like what I've said with the hardware. So this is all going to come to the Comma 2, just with OTAs. OTA, over the air. We're going to get it. Yeah. I mean, we're getting close on a lot of these. I'm going to start lowering the real touch timeout. Alex, you want to? This is Alex. Hi, nice to meet you. She's our COO. That's true. COO. Nice to meet you. She runs the back there stuff. What's the technical description of the back there stuff? You want to see? Yeah. I think it's more exciting than this stuff. It depends who you ask. We're ahead of all the secrets, right? Nick, do we have any secrets out? I'll blur it out. I think we have secrets right now. I'll blur the top secrets. This is production. Stress test. This is our final test. The Comma 2s hang out here for about 24 hours. We test them for their heat, their temperature, their light sensors. We do cosmetic checks, screen checks. Cool. Pretty exciting. You can see they all start over there as foams. Then they get retrofit. We have a beautiful house today. But you can see we have a class of 100 foams out right now. They're getting tested. Cool. It's kind of exciting, actually. Lex, this is Mitchell. He's the latest addition to our machine learning team. That's Chris, also known as Virtually Chris. He's a famous YouTuber. Oh, wow. How did fame change you? I introduced you as a famous YouTuber. Yes, I was the open pilot YouTuber. And then I got hired. Don't let it get to your head. Is that it? That's our head of hardware. Awesome. What's all the stuff that you guys are doing? What's that stage of the assembly? This is the final case. The case is going on. We have board testing. Then the retrofit foams get board put on them, soldered to them. We get the heat sink and the fan. And then we put the cases on them. Awesome. Yeah, they're taking the cases off. Screen's off here. Testing screens over here. We have an oven. 3D printer. I'm afraid to take it in there. It's very hot and loud. It's also the home of the compute cluster. It's not a data center. That's right. It's a compute cluster. Prepare yourself. The sound of productivity. Yeah. Oh my gosh, it's really hot. Fresh bag. This is what you see on the outside of the Comma 2's. I like how they have names. Meg. What's the purpose of the rings? They used to be for athletic activity. But now we have too many printers. We can't anymore. We just got about 20 printers in the last few months. They've come from all over the world. Literally. Poland, Germany, Peru. France. How long does it take to print a single one? We'll name number 49 for you. Thank you. We'll call him Lex. I told him he could be number 49. I can be. I'm working right now, but I promise 49 will work. It will be Lex number 49. I appreciate that. That would mean a lot to me. This is cool. Unfortunately, because we have to keep the bugs and dust out, they're covered, but... One U. I already forgot the original name. Compute cluster. These are our CPU machines. We have three racks that look like that. Two petabytes of spinning disks. We're in our 3080s. Our 3080s are in only desktop computers for non-business purposes. These are our GPU machines. What's in there? V100s. It's like a farm. Every day we have to go out and... 21st century farm. We have to hire a good farm-builder player to come farm us. I'm so proud of you. I farm the farmers every day. These are the ones that are ready to ship. These are all of our growing harnesses. These are all the cargo support. CAA, Bosch, Elevert, Subaru, Toyota, all the Hyundai's. All the way to J, Nissan, VW. All these are assembled by hand? That's cool. That's amazing. That's legit. That's awesome. That's the office. He took me for a ride. It was awesome. It was really surprising how well it worked. In the city a little bit too. It held up. He didn't show many secrets though. It means like, keep on driving, you know? That's why we replaced it with a heart. We're all big Elon fans. Elon's success is our success. If iOS succeeds, Android succeeds.

https://youtu.be/Lks97-GLElk

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Marcus Hutter: Universal Artificial Intelligence, AIXI, and AGI | Lex Fridman Podcast #75

The following is a conversation with Marcus Hutter, senior research scientist at Google DeepMind. Throughout his career of research, including with Juergen Schmidhuber and Shane Legge, he has proposed a lot of interesting ideas in and around the field of artificial general intelligence, including the development of AIXI, spelled A-I-X-I, model, which is a mathematical approach to AGI that incorporates ideas of Kolmogorov complexity, Solomonoff induction, and reinforcement learning. In 2006, Marcus launched the 50,000 Euro Hutter Prize for lossless compression of human knowledge. The idea behind this prize is that the ability to compress well is closely related to intelligence. This, to me, is a profound idea. Specifically, if you can compress the first 100 megabytes or one gigabyte of Wikipedia better than your predecessors, your compressor likely has to also be smarter. The intention of this prize is to encourage the development of intelligent compressors as a path to AGI. In conjunction with his podcast release just a few days ago, Marcus announced a 10x increase in several aspects of this prize, including the money, to 500,000 Euros. The better your compressor works relative to the previous winners, the higher fraction of that prize money is awarded to you. You can learn more about it if you Google simply Hutter Prize. I'm a big fan of benchmarks for developing AI systems, and the Hutter Prize may indeed be one that will spark some good ideas for approaches that will make progress on the path of developing AGI systems. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do one or two minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as one dollar. Brokerage services are provided by Cash App Investing, a subsidiary of Square, and member SIPC. Since Cash App allows you to send and receive money digitally, peer-to-peer, and security in all digital transactions is very important, let me mention the PCI Data Security Standard that Cash App is compliant with. I'm a big fan of standards for safety and security. PCI DSS is a good example of that, where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions. Now we just need to do the same for autonomous vehicles and AI systems in general. So again, if you get Cash App from the App Store or Google Play and use the code LEXPODCAST, you'll get $10 and Cash App will also donate $10 to FIRST, one of my favorite organizations that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Markus Hutter. Do you think of the universe as a computer or maybe an information processing system? Let's go with a big question first. Okay, I'll go with a big question first. I think it's a very interesting hypothesis or idea. And I have a background in physics, so I know a little bit about physical theories, the standard model of particle physics, and general relativity theory, and they are amazing and describe virtually everything in the universe. And they're all in a sense, computable theories. I mean, they're very hard to compute. And it's very elegant, simple theories which describe virtually everything in the universe. So there's a strong indication that somehow the universe is computable, but it's a plausible hypothesis. So what do you think, just like you said, general relativity, quantum field theory, why do you think that the laws of physics are so nice and beautiful and simple and compressible? Do you think our universe was designed, is naturally this way? Are we just focusing on the parts that are especially compressible? Are human minds just enjoy something about that simplicity and in fact, there's other things that are not so compressible? No, I strongly believe and I'm pretty convinced that the universe is inherently beautiful, elegant and simple and described by these equations. And we're not just picking that. I mean, if there were some phenomena which cannot be neatly described, scientists would try that, right? And you know, there's biology, which is more messy, but we understand that it's an emergent phenomena. And you know, it's complex systems, but they still follow the same rules, right, of quantum and electrodynamics. All of chemistry follows that and we know that. I mean, we cannot compute everything because we have limited computational resources. No, I think it's not a bias of the humans, but it's objectively simple. I mean, of course, you never know, you know, maybe there's some corners very far out in the universe or super, super tiny below the nucleus of atoms or, well, parallel universes which are not nice and simple, but there's no evidence for that. And we should apply Ockham's razor and, you know, choose the simplest tree consistent with it. But also, it's a little bit self-referential. So maybe a quick pause. What is Ockham's razor? So Ockham's razor says that you should not multiply entities beyond necessity, which sort of, if you translate it to proper English means, and you know, in the scientific context means that if you have two theories or hypotheses or models, which equally well describe the phenomenon, your study or the data, you should choose the more simple one. So that's just the principle? Yes. Sort of, that's not like a provable law, perhaps? Perhaps we'll kind of discuss it and think about it, but what's the intuition of why the simpler answer is the one that is likelier to be more correct descriptor of whatever we're talking about? I believe that Ockham's razor is probably the most important principle in science. I mean, of course, we need logical deduction and we do experimental design, but science is about understanding the world, finding models of the world, and we can come up with crazy complex models, which, you know, explain everything but predict nothing. But the simple model seemed to have predictive power, and it's a valid question why. And there are two answers to that. You can just accept it. That is the principle of science. And we use this principle and it seems to be successful. We don't know why, but it just happens to be. Or you can try, you know, find another principle which explains Ockham's razor. And if we start with the assumption that the world is governed by simple rules, then there's a bias towards simplicity. And applying Ockham's razor is the mechanism to finding these rules. And actually, in a more quantitative sense, and we come back to that later in case of some normal deduction, you can rigorously prove that. If you assume that the world is simple, then Ockham's razor is the best you can do in a certain sense. So I apologize for the romanticized question, but why do you think, outside of its effectiveness, why do we, do you think we find simplicity so appealing as human beings? Why does it just, why does E equals MC squared seem so beautiful to us humans? I guess mostly, in general, many things can be explained by an evolutionary argument. And, you know, there's some artifacts in humans which, you know, are just artifacts and not evolutionary necessary. But with this beauty and simplicity, it's, I believe, at least the core is about, like science, finding regularities in the world, understanding the world, which is necessary for survival, right? You know, if I look at a bush, right, and I just see noise, and there is a tiger, right, and eats me, then I'm dead. But if I try to find a pattern, and we know that humans are prone to find more patterns in data than they are, you know, like, you know, the Mars face and all these things, but this bias towards finding patterns, even if they are non, but, I mean, it's best, of course, if they are, yeah, helps us for survival. Yeah, that's fascinating. I haven't thought really about the, I thought I just loved science, but there, indeed, from, in terms of just for survival purposes, there is an evolutionary argument for why we find the work of Einstein so beautiful. Maybe a quick small tangent, could you describe what Solomonov induction is? Yeah, so that's a theory which I claim, and Ray Solomonov sort of claimed, you know, a long time ago, that this solves the big philosophical problem of induction. And I believe the claim is essentially true. And what it does is the following. So, okay, for the picky listener, induction can be interpreted narrowly and widely. Narrow means inferring models from data. And widely means also then using these models for doing predictions, or predictions also part of the induction. So I'm a little sloppy sort of with the terminology, and maybe that comes from Ray Solomonov, you know, being sloppy, maybe I shouldn't say that. He can't complain anymore. So let me explain a little bit this theory in simple terms. So assume you have a data sequence, make it very simple, the simplest one, say, 1, 1, 1, 1, 1, and you see 100 1s. What do you think comes next? The natural answer, I'm going to speed up a little bit, the natural answer is, of course, you know, 1. Okay? And the question is why? Okay, well, we see a pattern there, yeah, okay, there's a 1 and we repeat it. And why should it suddenly after 100 1s be different? So what we're looking for is simple explanations or models for the data we have. And now the question is, a model has to be presented in a certain language. In which language do we use? In science, we want formal languages, and we can use mathematics or we can use programs on a computer. So abstractly on a Turing machine, for instance, or it can be a general purpose computer. So, and there are, of course, lots of models of you can say maybe it's 100 1s and then 100 0s and 100 1s, that's a model, right? But there are simpler models. There's a model print one loop. Now that also explains the data. And if you push it to the extreme, you are looking for the shortest program, which if you run this program reproduces the data you have, it will not stop, it will continue, naturally. And this you take for your prediction. And on the sequence of 1s, it's very plausible, right? That the print one loop is the shortest program. We can give some more complex examples like 1, 2, 3, 4, 5. What comes next? The short program is again, you know, counter. And so that is, roughly speaking, how Solomonov induction works. The extra twist is that it can also deal with noisy data. So if you have, for instance, a coin flip, say a biased coin, which comes up head with 60% probability, then it will predict, it will learn and figure this out. And after a while it predicts, oh, the next coin flip will be head with probability 60%. So it's the stochastic version of that. But the goal is, the dream is always the search for the short program. Yes. Yeah. Well, in Solomonov induction, precisely what you do is, so you combine, so looking for the shortest program is like applying Opach's razor, like looking for the simplest theory. There's also Epicurus principle, which says, if you have multiple hypotheses, which equally well describe your data, don't discard any of them, keep all of them around, you never know. And you can put it together and say, okay, I have a bias towards simplicity, but I don't rule out the larger models. And technically what we do is, we weigh the shorter models higher and the longer models lower. And you use a Bayesian technique, you have a prior, which is precisely two to the minus the complexity of the program. And you weigh all this hypothesis and take this mixture, and then you get also the stochasticity in. Yeah, like many of your ideas, that's just a beautiful idea of weighing based on the simplicity of the program. I love that. That seems to me, maybe a very human-centric concept, seems to be a very appealing way of discovering good programs in this world. You've used the term compression quite a bit. I think it's a beautiful idea, sort of, we just talked about simplicity and maybe science, or just all of our intellectual pursuits is basically the attempt to compress the complexity all around us into something simple. So what does this word mean to you, compression? I essentially have already explained it. So compression means, for me, finding short programs for the data or the phenomenon at hand. You could interpret it more widely as finding simple theories, which can be mathematical theories, or maybe even informal, just in words. Compression means finding short descriptions, explanations, programs for the data. Do you see science as a kind of, our human attempt at compression? So we're speaking more generally, because when you say programs, you're kind of zooming in on a particular sort of, almost like a computer science, artificial intelligence focus. But do you see all of human endeavor as a kind of compression? Well, at least all of science, I see as an endeavor of compression, not all of humanity, maybe. And well, there are also some other aspects of science, like experimental design, right? I mean, we create experiments specifically to get extra knowledge, and that is then part of the decision-making process. But once we have the data, to understand the data is essentially compression. So I don't see any difference between compression, understanding, and prediction. So we're jumping around topics a little bit, but returning back to simplicity, a fascinating concept of Kolmogorov complexity. So in your sense, do most objects in our mathematical universe have high Kolmogorov complexity? And maybe what is, first of all, what is Kolmogorov complexity? Okay, Kolmogorov complexity is a notion of simplicity or complexity, and it takes the compression view to the extreme. So I explained before that if you have some data sequence, just think about a file on a computer, and best sort of, you know, just a string of bits. And if you, and we have data compressors, like we compress big files into zip files with certain compressors. And you can also produce self-extracting archives, that means as an executable, if you run it, it reproduces your original file without needing an extra decompressor. It's just a decompressor plus the archive together in one. And now there are better and worse compressors, and you can ask, what is the ultimate compressor? So what is the shortest possible self-extracting archive you could produce for a certain data set, yeah, which reproduces the data set? And the length of this is called the Kolmogorov complexity, and arguably, that is the information content in the data set. I mean, if the data set is very redundant or very boring, you can compress it very well, so the information content should be low, and, you know, it is low according to this definition. So it's the length of the shortest program that summarizes the data? Yes, yeah. And what's your sense of our sort of universe when we think about the different objects in our universe, concepts or whatever, at every level? Do they have high or low Kolmogorov complexity? So what's the hope? Do we have a lot of hope in being able to summarize as much of our world? That's a tricky and difficult question. So as I said before, I believe that the whole universe, based on the evidence we have, is very simple, so it has a very short description. Sorry, to linger on that, the whole universe, what does that mean? Do you mean at the very basic fundamental level in order to create the universe? Yes, yeah. So you need a very short program, and you run it. To get the thing going. You get the thing going, and then it will reproduce our universe. There's a problem with noise. We can come back to that later, possibly. Is noise a problem, or is it a bug or a feature? I would say it makes our life as a scientist really, really much harder. I mean, think about without noise, we wouldn't need all of the statistics. But that made me, we wouldn't feel like there's a free will. Maybe we need that for the... This is an illusion that noise can give you free will. That's, at least in that way, it's a feature. But also, if you don't have noise, you have chaotic phenomena, which are effectively like noise. So we can't get away with statistics even then. I mean, think about rolling a dice, and forget about quantum mechanics, and you know exactly how you throw it. But I mean, it's still so hard to compute the trajectory that effectively it is best to model it as coming out with a number, with probability one over six. But from this set of philosophical, Kolmogorov complexity perspective, if we didn't have noise, then arguably you could describe the whole universe as, well, as a standard model plus generativity. I mean, we don't have a theory of everything yet, but sort of assuming we are close to it or have it, plus the initial conditions, which may hopefully be simple. And then you just run it, and then you would reproduce the universe. But that's all by noise or by chaotic systems, or by initial conditions, which may be complex. So now, if we don't take the whole universe, but just a subset, just take planet Earth. Planet Earth cannot be compressed into a couple of equations. This is a hugely complex system. So interesting. So when you look at the window, like the whole thing might be simple, but when you just take a small window, then- It may become complex, and that may be counterintuitive, but there's a very nice analogy. The library of all books. So imagine you have a normal library with interesting books, and you go there, great, lots of information, and quite complex. So now I create a library, which contains all possible books, say, of 500 pages. So the first book just has A, A, A, A, A over all the pages. The next book, A, A, A, and ends with B, and so on. I create this library of all books. I can write a super short program, which creates this library. So this library, which has all books, has zero information content. And you take a subset of this library, and suddenly you have a lot of information in there. So that's fascinating. I think one of the most beautiful mathematical objects that, at least today, seems to be understudied or under-talked about is cellular automata. What lessons do you draw from sort of the game of life for cellular automata, where you start with the simple rules, just like you're describing with the universe, and somehow complexity emerges? Do you feel like you have an intuitive grasp on the fascinating behavior of such systems, where, like you said, some chaotic behavior could happen, some complexity could emerge, it could die out in some very rigid structures? Do you have a sense about cellular automata that somehow transfers maybe to the bigger questions of our universe? Yeah, the cellular automata, and especially the converse game of life, is really great, because these rules are so simple, you can explain it to every child, and even by hand you can simulate a little bit. And you see these beautiful patterns emerge, and people have proven that it's even Turing complete. You cannot just use a computer to simulate game of life, but you can also use game of life to simulate any computer. That is truly amazing. And it's the prime example, probably, to demonstrate that very simple rules can lead to very rich phenomena. And people sometimes, you know, how is chemistry and biology so rich? I mean, this can't be based on simple rules. But no, we know quantum electrodynamics describes all of chemistry. And we come later back to that, I claim intelligence can be explained or described in one single equation, this very rich phenomenon. You asked also about whether I understand this phenomenon. It's probably not. And there's this saying, you never understand really things, you just get used to them. And I think I'm pretty used to cellular automata. So you believe that you understand now why this phenomenon happens. But I give you a different example. I didn't play too much with this converse game of life, but a little bit more with fractals and with a Mandelbrot set and in this beautiful, you know, patterns, just look Mandelbrot set. And well, when the computers were really slow, and I just had a black and white monitor and programmed my own programs on a sampler to... Wow. Wow, you're legit. To get these fractals on the screen. And it was mesmerized and much later. So I returned to this, you know, every couple of years. And then I tried to understand what is going on. And you can understand a little bit. So I tried to derive the locations, you know, there are these circles and the apple shape. And then you have smaller Mandelbrot sets recursively in this set. And there's a way to mathematically by solving high order polynomials to figure out where these centers are and what size they are approximately. And by sort of mathematically approaching this problem, you slowly get a feeling of why things are like they are. And that sort of isn't, you know, first step to understanding why this rich phenomena. Do you think it's possible? What's your intuition? Do you think it's possible to reverse engineer and find the short program that generated these fractals sort of by looking at the fractals? Well, in principle, yes. Yeah. So, I mean, in principle, what you can do is you take, you know, any data set, you know, you take these fractals or you take whatever your data set, whatever you have, say a picture of Conway's Game of Life. And you run through all programs, you take a program size one, two, three, four, and all these programs, run them all in parallel in so-called dovetailing fashion, give them computational resources, first one 50%, second one half resources, and so on, and let them run, wait until they hold, give an output, compare it to your data. And if some of these programs produce the correct data, then you stop and then you have already some program. It may be a long program because it's faster. And then you continue and you get shorter and shorter programs until you eventually find the shortest program. The interesting thing, you can never know whether it's the shortest program, because there could be an even shorter program, which is just even slower. And you just have to wait, yeah? But asymptotically, and actually after finite time, you have the shortest program. So this is a theoretical but completely impractical way of finding the underlying structure in every data set. And that is what Solomon of Induction does and Kolmogorov complexity. In practice, of course, we have to approach the problem more intelligently. And then if you take resource limitations into account, there's, for instance, a field of pseudo-random numbers, yeah? And these are random numbers, so these are deterministic sequences, but no algorithm which is fast, fast means runs in polynomial time, can detect that it's actually deterministic. So we can produce interesting, I mean, random numbers, maybe not that interesting, but just an example. We can produce complex-looking data, and we can then prove that no fast algorithm can detect the underlying pattern. Which is unfortunately, that's a big challenge for our search for simple programs in the space of artificial intelligence, perhaps. Yes, it definitely is for artificial intelligence, and it's quite surprising that it's, I can't say easy, I mean, physicists worked really hard to find these theories, but apparently it was possible for human minds to find these simple rules in the universe. It could have been different, right? It could have been different. It's awe-inspiring. So let me ask another absurdly big question. What is intelligence? In your view? So I have, of course, a definition. I wasn't sure what you were going to say, because you could have just as easily said, I have no clue. Which many people would say, but I'm not modest in this question. So the informal version, which I worked out together with Shane Leck, who co-founded DeepMind, is that intelligence measures an agent's ability to perform well in a wide range of environments. So that doesn't sound very impressive, and these words have been very carefully chosen, and there is a mathematical theory behind that, and we come back to that later. And if you look at this definition by itself, it seems like, yeah, okay, but it seems a lot of things are missing. But if you think it through, then you realize that most, and I claim all of the other traits, at least of rational intelligence, which we usually associate with intelligence, are emergent phenomena from this definition. Like, you know, creativity, memorization, planning, knowledge, you all need that in order to perform well in a wide range of environments. So you don't have to explicitly mention that in a definition. Interesting. So yeah, so the consciousness, abstract reasoning, all these kinds of things are just emergent phenomena that help you in towards, can you say the definition again? So multiple environments. Did you mention the word goals? No, but we have an alternative definition. Instead of performing well, you can just replace it by goals. So intelligence measures an agent's ability to achieve goals in a wide range of environments. That's more or less equal. But it's interesting, because in there, there's an injection of the word goals. So we want to specify there should be a goal. Yeah, but perform well is sort of, what does it mean? It's the same problem. Yeah. There's a little bit of a gray area, but it's much closer to something that could be formalized. In your view, are humans, where do humans fit into that definition? Are they general intelligence systems that are able to perform in, like, how good are they at fulfilling that definition, at performing well in multiple environments? Yeah, that's a big question. I mean, the humans are performing best among all species on earth. All species we know of. Yeah. Depends. You could say that trees and plants are doing a better job. They'll probably outlast us. Yeah, but they are in a much more narrow environment, right? I mean, you just have a little bit of air pollutions and these trees die, and we can adapt, right? We build houses, we build filters, we do geoengineering. So the multiple environment part. Yeah, that is very important, yeah. So that's a distinguished narrow intelligence from wide intelligence, also in the AI research. So let me ask the Alan Turing question. Can machines think? Can machines be intelligent? So in your view, I have to kind of ask, the answer is probably yes, but I want to kind of hear your thoughts on it. Can machines be made to fulfill this definition of intelligence, to achieve intelligence? Yeah, I think the answer is yes, we can actually, I think we are. That's right. Yep. Yeah, well, of course, we could, I mean, even engineering isn't all about machines. Okay. We're not machine learning. But I think in the, we're determining the intelligence that they have, we are really just that. Yeah, that's the intelligence to really comment on, but yeah. was truly amazing. So reinforcement learning algorithm, which is able just by self-play to play chess and then also Go. And I mean, yes, they're both games, but they're quite different games. And you know, you don't feed them the rules of the game. And the most remarkable thing, which is still a mystery to me, that usually for any decent chess program, I don't know much about Go, you need opening books and end game tables and so on too. And nothing in there, nothing was put in there. Especially with AlphaZero, the self-play mechanism starting from scratch, being able to learn actually new strategies is- Yeah, it rediscovered, you know, all these famous openings within four hours by itself. What I was really happy about, I'm a terrible chess player, but I like Queen Gambi. And AlphaZero figured out that this is the best opening. Finally, somebody proved you correct. So yes, to answer your question, yes, I believe that general intelligence is possible. And it also, I mean, it depends how you define it. Do you say AGI, with general intelligence, artificial intelligence, only refers to if you achieve human level or a subhuman level, but quite broad, is it also general intelligence? So we have to distinguish, or it's only super human intelligence, general artificial intelligence. Is there a test in your mind, like the Turing test and natural language or some other test that would impress the heck out of you that would kind of cross the line of your sense of intelligence within the framework that you said? Well, the Turing test, well, it has been criticized a lot, but I think it's not as bad as some people think. Some people think it's too strong. So it tests not just for a system to be intelligent, but it also has to fake human- Deception. Deception, right, which is much harder. And on the other hand, they say it's too weak, because it just maybe fakes emotions or intelligent behavior. It's not real. But I don't think that's the problem or a big problem. So if it would pass the Turing test, so a conversation over terminal with a bot for an hour or maybe a day or so, and you can fool a human into not knowing whether this is a human or not, so that's the Turing test, I would be truly impressed. And we have this annual competitions in Lübna Prize. And I mean, it started with Eliza. That was the first conversational program. And what is it called? The Japanese Mitsuko or so, that's the winner of the last couple of years. A couple of years. And well- It's quite impressive. Yeah, it's quite impressive. And then Google has developed Mina, right? Just recently, that's an open domain conversational bot. Just a couple of weeks ago, I think. Yeah, I kind of like the metric that sort of the Alexa Prize has proposed. I mean, maybe it's obvious to you. It wasn't to me of setting sort of a length of a conversation. Like you want the bot to be sufficiently interesting that you'd want to keep talking to it for like 20 minutes. And that's a surprisingly effective in aggregate metric. Because you really, like nobody has the patience to be able to talk to a bot that's not interesting and intelligent and witty and is able to go on to different tangents, jump domains, be able to say something interesting to maintain your attention. And maybe many humans will also fail this test. Unfortunately, we set just like with autonomous vehicles, with chatbots, we also set a bar that's way too high to reach. I said, the Turing test is not as bad as some people believe. But what is really not useful about the Turing test, it gives us no guidance how to develop these systems in the first place. Of course, we can develop them by trial and error and do whatever and then run the test and see whether it works or not. But a mathematical definition of intelligence gives us an objective which we can then analyze by theoretical tools or computational and maybe even prove how close we are. And we will come back to that later with the Ixie model. So I mentioned the compression, right? So in natural language processing, they have achieved amazing results. And one way to test this, of course, you take the system, you train it, and then you see how well it performs on the task. But a lot of performance measurement is done by so-called perplexity, which is essentially the same as complexity or compression length. So the NLP community develops new systems and then they measure the compression length and then they have ranking and leaks because there's a strong correlation between compressing well and then the system's performing well at the task at hand. It's not perfect, but it's good enough for them as an intermediate aim. So you mean a measure, so this is kind of almost returning to the common ground of complexity. So you're saying good compression usually means good intelligence. Yes. So you mentioned you're one of the only people who dared boldly to try to formalize the idea of artificial general intelligence, to have a mathematical framework for intelligence, just like as we mentioned, termed AIXI, A-I-X-I. So let me ask the basic question. What is AIXI? Okay, so let me first say what it stands for because that's- What it stands for, actually, that's probably the more basic question. What it- The first question is usually how it's pronounced, but finally I put it on the website how it's pronounced, so you figured it out. Yeah. The name comes from AI, artificial intelligence, and the X-I is the Greek letter Xi, which are used for Solomonov's distribution for quite stupid reasons, which I'm not willing to repeat here in front of camera. Sure. So it just happened to be more or less arbitrary. It shows the Xi, but it also has nice other interpretations. So there are actions and perceptions in this model, where an agent has actions and perceptions, and over time. So this is A-index-I, X-index-I. So there's action at time I, and then followed by perception at time I. Yeah, we'll go with that. I'll edit out the first part. Yeah. I'm just kidding. I have some more interpretations. Yeah, go ahead. So at some point, maybe five years ago or 10 years ago, I discovered in Barcelona, it was on a big church, there was stone engraved, some text, and the word Aix appeared there a couple of times. I was very surprised and happy about it. And I looked it up. So it is Catalan language, and it means with some interpretation of that's it, that's the right thing to do. Yeah, Eureka. Oh, so it's almost like destined somehow came. Yeah. Yeah. Yeah. Came to you in a dream. So okay. And similarly, there's a Chinese word, Aixi, also written like Aixi, if you transcribe that to Pinyin. And the final one is that is AI crossed with induction, because that is, and that's going more to the content now. So good old fashioned AI is more about planning in known deterministic world, and induction is more about often, you know, IID data and inferring models. And essentially what this Aixi model does is combining these two. And I actually also recently, I think heard that in Japanese, AI means love. So if you can combine XI somehow with that, I think we can, there might be some interesting ideas there. So Aixi, let's then take the next step. Can you maybe talk at the big level of what is this mathematical framework? Yeah, so it consists essentially of two parts. One is the learning and induction and prediction part. And the other one is the planning part. So let's come first to the learning, induction, prediction part, which essentially I explained already before. So what we need for any agent to act well is that it can somehow predict what happens. I mean, if you have no idea what your actions do, how can you decide which actions are good or not? So you need to have some model of what your actions effect. So what you do is you have some experience, you build models like scientists of your experience, then you hope these models are roughly correct, and then you use these models for prediction. And the model is, sorry to interrupt, and the model is based on your perception of the world, how your actions will affect that world. That's not... So how do you think about the model? That's not the important part, but it is technically important, but at this stage we can just think about predicting, say, stock market data, weather data, or IQ sequences, one, two, three, four, five, what comes next, yeah? So of course our actions affect what we're doing, but I come back to that in a second. So, and I'll keep just interrupting. So just to draw a line between prediction and planning, what do you mean by prediction in this way? It's trying to predict the environment without your long-term action in that environment. What is prediction? Okay, if you want to put the actions in now, okay, then let's put in now, yeah? So- We don't have to put them now. Scratch it, scratch it, dumb question, okay. So the simplest form of prediction is that you just have data which you passively observe, and you want to predict what happens without interfering. As I said, weather forecasting, stock market, IQ sequences, or just anything, okay? And Solomonov's theory of induction based on compression, so you look for the shortest program which describes your data set, the shortest program which describes your data sequence, and then you take this program, run it, it reproduces your data sequence by definition, and then you let it continue running, and then it will produce some predictions, and you can rigorously prove that for any prediction task, this is essentially the best possible predictor. Of course, if there's a prediction task, or a task which is unpredictable, like, you know, fair coin flips, yeah, I cannot predict the next fair coin flip, Solomonov does it, says, okay, next head is probably 50%. It's the best you can do. So if something is unpredictable, Solomonov will also not magically predict it. But if there is some pattern and predictability, then Solomonov induction will figure that out eventually, and not just eventually, but rather quickly, and you can have proof convergence rates, whatever your data is. So that is pure magic in a sense. What's the catch? Well, the catch is that it's not computable, and we come back to that later. You cannot just implement it in even this Google resources here, and run it and predict the stock market and become rich. I mean, Ray Solomonov already tried it at the time. But so the basic task is you're in the environment, and you're interacting with an environment to try to learn a model of that environment, and the model is in the space of all these programs, and your goal is to get a bunch of programs that are simple. And so let's go to the actions now. But actually, good that you asked. Usually I skip this part, although there is also a minor contribution, which I did. So the action part, but I usually sort of just jump to the decision part. So let me explain to the action part now. Thanks for asking. So you have to modify it a little bit by now not just predicting a sequence which just comes to you, but you have an observation, then you act somehow, and then you want to predict the next observation based on the past observation and your action. Then you take the next action. You don't care about predicting it because you're doing it. Then you get the next observation, and you want, well, before you get it, you want to predict it, again, based on your past action and observation sequence. You just condition extra on your actions. There's an interesting alternative that you also try to predict your own actions. If you want. In the past or the future? Your future actions. That's interesting. Yeah. Wait, let me wrap. I think my brain is broke. We should maybe discuss that later after I've explained the ICSI model. That's an interesting variation. But that is a really interesting variation. And a quick comment. I don't know if you want to insert that in here, but you're looking at that in terms of observations, you're looking at the entire, the big history, the long history of the observations. Exactly. That's very important. The whole history from birth sort of of the agent. And we can come back to that also why this is important. Yeah, often in RL you have MDPs, macro decision processes, which are much more limiting. Okay, so now we can predict conditioned on actions. So even if we influence environment, but prediction is not all we want to do, right? We also want to act really in the world. And the question is how to choose the actions. And we don't want to greedily choose the actions. Just what is best in the next time step. And we first, I should say, what is, how do we measure performance? So we measure performance by giving the agent reward. That's the so-called reinforcement learning framework. So every time step, you can give it a positive reward or negative reward, or maybe no reward. It could be a very scarce, right? Like if you play chess, just at the end of the game, you give plus one for winning or minus one for losing. So in the IXE framework, that's completely sufficient. So occasionally you give a reward signal and you ask the agent to maximize reward, but not greedily sort of, you know, the next one, next one, because that's very bad in the long run if you're greedy. So, but over the lifetime of the agent. So let's assume the agent lives for M time steps, let's say dies in sort of a hundred years sharp. That's just, you know, the simplest model to explain. So it looks at the future reward sum and ask what is my action sequence? Or actually more precisely my policy, which leads in expectation, because I don't know the world, to the maximum reward sum. Let me give you an analogy. In chess, for instance, we know how to play optimally in theory. It's just a minimax strategy. I play the move which seems best to me under the assumption that the opponent plays the move which is best for him, so best, so worst for me, under the assumption that I play, again, the best move. And then you have this expected max three to the end of the game, and then you back propagate and then you get the best possible move. So that is the optimal strategy, which von Neumann already figured out a long time ago, for playing adversarial games. Luckily, or maybe unluckily for the theory, it becomes harder. The world is not always adversarial. So it can be, if there are other humans in cooperative, or nature is usually, I mean, the dead nature is stochastic. You know, things just happen randomly, or don't care about you. So what you have to take into account is the noise, and not necessarily adversariality. So you replace the minimum on the opponent's side by an expectation, which is general enough to include also adversarial cases. So now instead of a minimax strategy, you have an expectimax strategy. So far so good, so that is well known, it's called sequential decision theory. But the question is, on which probability distribution do you base that? If I have the true probability distribution, like say I play Begummin, right? There's dice, and there's certain randomness involved. I can calculate probabilities and feed it in the expectimax, or the sequential decision tree, come up with the optimal decision if I have enough compute. But for the real world, we don't know that. What is the probability the driver in front of me breaks? I don't know. So depends on all kinds of things, and especially new situations, I don't know. So this is this unknown thing about prediction, and there's where Solomonov comes in. So what you do is in sequential decision tree, you just replace the true distribution, which we don't know, by this universal distribution. I didn't explicitly talk about it, but this is used for universal prediction, and plug it into the sequential decision tree mechanism. And then you get the best of both worlds. You have a long-term planning agent, but it doesn't need to know anything about the world, because the Solomonov induction part learns. Can you explicitly try to describe the universal distribution, and how Solomonov induction plays a role here? I'm trying to understand. So what it does it, so in the simplest case, I said take the shortest program, describing your data, run it, have a prediction which would be deterministic. Yes. Okay? But you should not just take the shortest program, but also consider the longer ones, but keep it lower a priori probability. So in the Bayesian framework, you say a priori any distribution, which is a model or a stochastic program has a certain a priori probability, which is two to the minus, and why two to the minus length, you know, I could explain length of this program. So longer programs are punished, a priori. And then you multiply it with the so-called likelihood function, which is, as the name suggests, is how likely is this model given the data at hand. So if you have a very wrong model, it's very unlikely that this model is true, and so it is very small number. So even if the model is simple, it gets penalized by that. And what you do is then you take just the sum, but this is the average over it. And this gives you a probability distribution, so-called universal distribution, or Solomonov distribution. So it's weighed by the simplicity of the program and the likelihood. Yes. It's kind of a nice idea. Yeah. So, okay, and then you said there's, you're planning N or M, or I forgot the letter, steps into the future. So how difficult is that problem? What's involved there? Okay, so basic optimization problem, what are we talking? Yeah, so you have a planning problem up to horizon M, and that's exponential time in the horizon M, which is, I mean, it's computable, but intractable. I mean, even for chess, it's already intractable to do that exactly, and, you know, for Go. But it could be also discounted kind of framework where. Yeah, so having a hard horizon, you know, at 100 years, it's just for simplicity of discussing the model, and also sometimes the math is simple. But there are lots of variations. Actually, a quite interesting parameter. It's, there's nothing really problematic about it, but it's very interesting. So for instance, you think, no, let's let the parameter M tend to infinity, right? You want an agent which lives forever, right? If you do it naively, you have two problems. First, the mathematics breaks down because you have an infinite reward sum, which may give infinity, and getting reward 0.1 every time step is infinity, and giving reward one every time step is infinity, so equally good. Not really what we want. Other problem is that if you have an infinite life, you can be lazy for as long as you want for 10 years, and then catch up with the same expected reward. And, you know, think about yourself, or, you know, or maybe, you know, some friends or so. If they knew they lived forever, you know, why work hard now, you know, just enjoy your life, you know, and then catch up later. So that's another problem with infinite horizon. And you mentioned, yes, we can go to discounting, but then the standard discounting is so-called geometric discounting. So a dollar today is about worth as much as, you know, $1.05 tomorrow. So if you do this so-called geometric discounting, you have introduced an effective horizon. So the agent is now motivated to look ahead a certain amount of time effectively. It's like a moving horizon. And for any fixed effective horizon, there is a problem to solve, which requires larger horizon. So if I look ahead, you know, five time steps, I'm a terrible chess player, right? I need to look ahead longer. If I play go, I probably have to look ahead even longer. So for every problem, for every horizon, there is a problem which this horizon cannot solve. But I introduced the so-called near harmonic horizon, which goes down with one over T rather than exponentially T, which produces an agent which effectively looks into the future proportional to its age. So if it's five years old, it plans for five years. If it's a hundred years old, it then plans for a hundred years. Interesting. And it's a little bit similar to humans too, right? I mean, children don't plan ahead very long, but then we get adult, we play ahead more longer. Maybe when we get very old, I mean, we know that we don't live forever, and maybe then our horizon shrinks again. So that's really interesting. So adjusting the horizon, is there some mathematical benefit of that? Or is it just a nice, I mean, intuitively, empirically, it would probably be a good idea to sort of push the horizon back, extend the horizon as you experience more of the world. But is there some mathematical conclusions here that are beneficial? With Solomon's induction sort of prediction part, we have extremely strong finite time, but finite data results. So you have so and so much data, then you lose so and so much. So the theory is really great. With the Ixie model, with the planning part, many results are only asymptotic, which, well, this is- What does asymptotic mean? Asymptotic means you can prove, for instance, that in the long run, if the agent acts long enough, then it performs optimal or some nice thing happens. But you don't know how fast it converges. So it may converge fast, but we're just not able to prove it because of a difficult problem. Or maybe there's a bug in the model so that it's really that slow. So that is what asymptotic means, sort of eventually, but we don't know how fast. And if I give the agent a fixed horizon M, then I cannot prove asymptotic results, right? So I mean, sort of if it dies in 100 years, then 100 years is over. I cannot say eventually. So this is the advantage of the discounting that I can prove asymptotic results. So just to clarify, so, okay, I've built up a model. Well, now in the moment, I have this way of looking several steps ahead. How do I pick what action I will take? It's like with the playing chess, right? You do this minimax. In this case here, do expectimax based on the Solomonov distribution. You propagate back and then, while an action falls out, the action which maximizes the future expected reward under Solomonov distribution, and then you just take this action. And then repeat. And then you get a new observation and you feed it in this action observation, then you repeat. And the reward, so on. Yeah, so you're a row two, yeah. And then maybe you can even predict your own action. I love that idea. But okay, this big framework, what is it, I mean, it's kind of a beautiful mathematical framework to think about artificial general intelligence. What can you, what does it help you into it about how to build such systems? Or maybe from another perspective, what does it help us in understanding AGI? So when I started in the field, I was always interested in two things. One was AGI, the name didn't exist then, what's called general AI or strong AI. And the physics here of everything. So I switched back and forth between computer science and physics quite often. You said the theory of everything. The theory of everything, yeah. So basically, there's two biggest problems before all of humanity. Yeah, I can explain, if you want at some later time, why I'm interested in these two questions. Can I ask you, on a small tangent, if it was one to be solved, which one would you, if an apple fell on your head and there was a brilliant insight and you could arrive at the solution to one, would it be AGI or the theory of everything? Definitely AGI, because once the AGI problem is solved, I can ask the AGI to solve the other problem for me. Yeah, brilliantly put. Okay, so as you were saying about it. Okay, so, and the reason why I didn't settle, I mean, this thought about, you know, once you have solved AGI, it solves all kinds of other, not just the theory of every problem, but all kinds of more useful problems to humanity is very appealing to many people. And, you know, I had this thought also, but I was quite disappointed with the state of the art of the field of AI. There was some theory, you know, about logical reasoning, but I was never convinced that this will fly. And then there was this more holistic approaches with neural networks, and I didn't like these heuristics. So, and also I didn't have any good idea myself. So that's the reason why I toggled back and forth quite some while and even worked four and a half years in a company developing software, something completely unrelated. But then I had this idea about the IXE model. And so what it gives you, it gives you a gold standard. So I have proven that this is the most intelligent agents, which anybody could build in quotation mark, because it's just mathematical and you need infinite compute. But this is the limit. And this is completely specified. It's not just a framework. And, you know, every year, tens of frameworks are developed which discuss skeletons and then pieces are missing. And usually these missing pieces, you know, turn out to be really, really difficult. And so this is completely and uniquely defined, and we can analyze that mathematically. And we've also developed some approximations. I can talk about that a little bit later. That would be sort of the top-down approach, like say for Neumann's minimax theory, that's the theoretical optimal play of games. And now we need to approximate it, put heuristics in, prune the tree, blah, blah, blah. And so on. So we can do that also with the Ixia model, but for general AI. It can also inspire those, and most researchers go bottom-up, right? They have their systems, they try to make it more general, more intelligent. It can inspire in which direction to go. What do you mean by that? So if you have some choice to make, right? So how should I evaluate my system if I can't do cross-validation? How should I do my learning if my standard regularization doesn't work well? So the answer is always this, we have a system which does everything, that's Ixie. It's just completely in the ivory tower, completely useless from a practical point of view. But you can look at it and see, ah, yeah, maybe I can take some aspects, and instead of Kolmogorov complexity, they'll just take some compressors, which has been developed so far. And for the planning, well, we have UCT, which has also been used in Go. And at least it's inspired me a lot to have this formal definition. And if you look at other fields, like I always come back to physics because I have a physics background, think about the phenomenon of energy. That was a long time, a mysterious concept. And at some point it was completely formalized. And that really helped a lot. And you can point out a lot of these things which were first mysterious and vague, and then they have been rigorously formalized. Speed and acceleration has been confused, right, until it was formally defined. Yeah, there was a time like this. And people often don't have any background, still confuse it. So, and this Ixie model, or the intelligence definitions, which is sort of the dual to it, we come back to that later, formalizes the notion of intelligence uniquely and rigorously. So in a sense, it serves as kind of the light at the end of the tunnel. So for- Yes, yeah. So, I mean, there's a million questions I could ask her. So maybe kind of, okay, let's feel around in the dark a little bit. So there's been here at DeepMind, but in general, been a lot of breakthrough ideas, just like we've been saying around reinforcement learning. So how do you see the progress in reinforcement learning is different? Like which subset of Ixie does it occupy? The current, like you said, maybe the Markov assumption is made quite often in reinforcement learning. There's other assumptions made in order to make the system work. What do you see as the difference connection between reinforcement learning and Ixie? Yeah, so the major difference is that essentially all other approaches, they make stronger assumptions. So in reinforcement learning, the Markov assumption is that the next state or next observation only depends on the previous observation and not the whole history, which makes, of course, the mathematics much easier rather than dealing with histories. Of course, they profit from it also because then you have algorithms that run on current computers and do something practically useful. But for general AI, all the assumptions which are made by other approaches, we know already now they are limiting. So for instance, usually you need an ergodicity assumption in the MDP frameworks in order to learn. Ergodicity essentially means that you can recover from your mistakes and that there are no traps in the environment. And if you make this assumption, then essentially you can go back to a previous state, go there a couple of times and then learn what statistics and what the state is like, and then in the long run perform well in this state. But there are no fundamental problems. But in real life, we know there can be one single action, one second of being inattentive while driving a car fast can ruin the rest of my life. I can become quadriplegic or whatever. So there's no recovery anymore. So the real world is not ergodic, I always say. There are traps and there are situations where you are not recover from. And very little theory has been developed for this case. What about, what do you see in the context of AXA as the role of exploration? Sort of, you mentioned in the real world we can get into trouble when we make the wrong decisions and really pay for it. But exploration seems to be fundamentally important for learning about this world, for gaining new knowledge. So is exploration baked in? Another way to ask it, what are the parameters of this, of IAXE that can be controlled? Yeah, I say the good thing is that there are no parameters to control. Some other people try knobs to control, and you can do that. I mean, you can modify AXE so that you have some knobs to play with if you want to. But the exploration is directly baked in, and that comes from the Bayesian learning and the long-term planning. So these together already imply exploration. You can nicely and explicitly prove that for simple problems like so-called bandit problems, where you say, to give a real world example, say you have two medical treatments, A and B, you don't know the effectiveness, you try A a little bit, B a little bit, but you don't want to harm too many patients. So you have to sort of trade off exploring, and at some point you want to explore. And you can do the mathematics and figure out the optimal strategy. The so-called Bayesian agents, they're also non-Bayesian agents, but it shows that this Bayesian framework, by taking a prior over possible worlds, doing the Bayesian mixture, then the Bayes optimal decision with long-term planning, that is important, automatically implies exploration also to the proper extent, not too much exploration and not too little, in these very simple settings. In the IXE model, I was also able to prove that this is self-optimizing theorem or asymptotic optimality theorems, although they're only asymptotic, not finite time bounds. So it seems like the long-term planning is a really important, the long-term part of the planning is really important. Yes. And also, maybe a quick tangent, how important do you think is removing the Markov assumption and looking at the full history? Sort of intuitively, of course, it's important, but is it like fundamentally transformative to the entirety of the problem? What's your sense of it? Because we make that assumption quite often, just throwing away the past. I think it's absolutely crucial. The question is whether there's a way to deal with it in a more heuristic and still sufficiently well way. So I have to come up with an example on the fly, but you have some key event in your life, long time ago, in some city or something, you realize that's a really dangerous street or whatever, right? And you want to remember that forever, right? In case you come back there. Kind of a selective kind of memory. So you remember all the important events in the past, but somehow selecting the importance is... That's very hard, yeah. And I'm not concerned about just storing the whole history. Just, you can calculate human life, say, 30 or 100 years, doesn't matter, right? How much data comes in through the vision system and the auditory system. You compress it a little bit, in this case lossily, and store it. We are soon in the means of just storing it. But you still need to do the selection for the planning part and the compression for the understanding part. The raw storage, I'm really not concerned about. And I think we should just store, if you develop an agent, preferably just store all the interaction history. And then you build, of course, models on top of it, and you compress it, and you are selective. But occasionally you go back to the old data and reanalyze it based on your new experience you have. Sometimes you are in school, you learn all these things you think is totally useless, and much later you realize, oh, they were not so useless as you thought. I'm looking at you, linear algebra. Right, so maybe let me ask about objective functions, because that, or rewards. It seems to be an important part. The rewards are kind of given to the system. For a lot of people, the specification of the objective function is a key part of intelligence. The agent itself figuring out what is important. What do you think about that? Is it possible within the IXE framework to yourself discover the reward based on which you should operate? Okay, that will be a long answer. So, and that is a very interesting question, and I'm asked a lot about this question. Where do the rewards come from? And that depends. So, and I give you now a couple of answers. So if we want to build agents, now let's start simple. So let's assume we want to build an agent based on the IXE model, which performs a particular task. Let's start with something super simple, like, I mean, super simple, like playing chess or go or something. Then you just, you know, the reward is, you know, winning the game is plus one, losing the game is minus one, done. You apply this agent. If you have enough compute, you let itself play, and it will learn the rules of the game, will play perfect chess. After some while, problem solved. Okay, so if you have more complicated problems, then you may believe that you have the right reward, but it's not. So a nice, cute example is elevator control that is also in Rich Sutton's book, which is a great book, by the way. So you control the elevator and you think, well, maybe the reward should be coupled to how long people wait in front of the elevator. You know, long wait is bad. You program it and you do it. And what happens is the elevator eagerly picks up all the people, but never drops them off. So then you realize, maybe the time in the elevator also counts. So you minimize the sum. And the elevator does that, but never picks up the people in the 10th floor and the top floor because in expectation, it's not worth it. Just let them stay. Yeah. So even in apparently simple problems, you can make mistakes. Yeah, and that's what in more serious context, say, AI safety researchers consider. So now let's go back to general agents. So assume we have a general agent. So assume we want to build an agent which is generally useful to humans. Yes, we have a household robot. Yeah. And it should do all kinds of tasks. So in this case, the human should give the reward on the fly. I mean, maybe it's pre-trained in the factory and that there's some sort of internal reward for the battery level or whatever. Yeah, but so it does the dishes badly. You punish the robot, it does it good. You reward the robot and then to train it to a new task. Yeah, like a child, right? So you need the human in the loop if you want a system which is useful to the human. And as long as this agent stays sub-human level, that should work reasonably well, apart from these examples. It becomes critical if they become on a human level. It's the same as children, small children. You have reasonably well under control. They become older. The reward technique doesn't work so well anymore. So then finally, so this would be agents which are just, you could say slaves to the humans, yeah? So if you are more ambitious and just say, we want to build a new species of intelligent beings, we put them on a new planet and we want them to develop this planet or whatever. So we don't give them any reward. So what could we do? And you could try to come up with some reward functions like it should maintain itself, the robot. It should maybe multiply, build more robots, right? And maybe all kinds of things which you find useful, but that's pretty hard, right? What does self-maintenance mean? What does it mean to build a copy? Should it be exact copy, an approximate copy? And so that's really hard, but Laurent Assor, also at DeepMind, developed a beautiful model. So it just took the ICSI model and coupled the rewards to information gain. So he said the reward is proportional to how much the agent had learned about the world. And you can rigorously formally uniquely define that in terms of our catalog versions, okay? So if you put that in, you get a completely autonomous agent. And actually, interestingly, for this agent, we can prove much stronger result than for the general agent, which is also nice. And if you let this agent loose, it will be in a sense the optimal scientist. It is absolutely curious to learn as much as possible about the world. And of course, it will also have a lot of instrumental goals, right? In order to learn, it needs to at least survive, right? At that age, it's not good for anything. So it needs to have self-preservation. And if it builds small helpers acquiring more information, it will do that, yeah? If exploration, space exploration or whatever is necessary, right, to gathering information and develop it. So it has a lot of instrumental goals following on this information gain. And this agent is completely autonomous of us. No rewards necessary anymore. Yeah, of course, it could find a way to game the concept of information and get stuck in that library that you mentioned beforehand with a very large number of books. The first agent had this problem. It would get stuck in front of an old TV screen, which has just had white noise. Yeah, white noise, yeah. But the second version can deal with at least stochasticity. Well. Yeah, what about curiosity? This kind of word, curiosity, creativity, is that kind of the reward function being of getting new information? Is that similar to idea of kind of injecting exploration for its own sake inside the reward function? Do you find this at all appealing, interesting? I think that's a nice definition. Curiosity is reward, sorry, curiosity is exploration for its own sake. Yeah, I would accept that. But most curiosity, well, in humans, and especially in children, yeah, is not just for its own sake, but for actually learning about the environment and for behaving better. So I think most curiosity is tied in the end towards performing better. Well, okay, so if intelligence systems need to have this reward function, let me, you're an intelligence system, currently passing the Turing test quite effectively. What's the reward function of our human intelligence existence? What's the reward function that Marcus Hodder is operating under? Okay, to the first question, the biological reward function is to survive and to spread. And very few humans sort of are able to overcome this biological reward function. But we live in a very nice world where we have lots of spare time and can still survive and spread. So we can develop arbitrary other interests, which is quite interesting. On top of that. On top of that, yeah. But the survival and spreading sort of is, I would say the goal or the reward function of humans, the core one. I like how you avoided answering the second question, which a good intelligence system would. So my. Your own meaning of life and the reward function. My own meaning of life and reward function is to find an AGI to build it. Beautifully put. Okay, let's dissect Ix even further. So one of the assumptions is kind of infinity keeps creeping up everywhere. Which, what are your thoughts on kind of bounded rationality and sort of the nature of our existence in intelligence systems is that we're operating always under constraints, under limited time, limited resources. How does that, how do you think about that within the Ix framework within trying to create an AGI system that operates under these constraints? Yeah, that is one of the criticisms about Ix is simply that it ignores computation and completely and some people believe that intelligence is inherently tied to what's bounded resources. What do you think on this one point? Do you think it's, do you think the bounded resources are fundamental to intelligence? I would say that an intelligence notion which ignores computational limits is extremely useful. A good intelligence notion which includes these resources would be even more useful, but we don't have that yet. And so look at other fields outside of computer science. Computational aspects never play a fundamental role. You develop biological models for cells, something in physics, these theories, I mean, become more and more crazy and harder and harder to compute. Well, in the end, of course, we need to do something with this model, but there's more nuisance than a feature. And I'm sometimes wondering if artificial intelligence would not sit in a computer science department, but in a philosophy department, then this computational focus would be probably significantly less. I mean, think about the induction problem is more in the philosophy department. There's virtually no paper who cares about, you know, how long it takes to compute the answer. That is completely secondary. Of course, once we have figured out the first problem, so intelligence without computational resources, then the next and very good question is, could we improve it by including computational resources? But nobody was able to do that so far in an even halfway satisfactory manner. I like that, that in the long run, the right department to belong to is philosophy. That's actually quite a deep idea, or even to at least to think about big picture philosophical questions, big picture questions, even in the computer science department. But you've mentioned approximation, sort of, there's a lot of infinity, a lot of huge resources needed. Are there approximations to IXE that within the IXE framework that are useful? Yeah, we have developed a couple of approximations. And what we do there is that the Solomoff induction part, which was find the shortest program describing your data, we just replace it by standard data compressors. And the better compressors get, the better this part will become. We focus on a particular compressor called context-free weighting, which is pretty amazing, not so well known. It has beautiful theoretical properties, also works reasonably well in practice. So we use that for the approximation of the induction and the learning and the prediction part. And for the planning part, we essentially just took the ideas from a computer go from 2006. It was Java Zephyr Spary, also now at DeepMind, who developed the so-called UCT algorithm, upper confidence bound for trees algorithm, on top of the Monte Carlo tree search. So we approximate this planning part by sampling. And it's successful on some small toy problems. We don't want to lose the generality, right? And that's sort of the handicap, right? If you want to be general, you have to give up something. So, but this single agent was able to play, you know, small games like Hoon Poker and Tic-Tac-Toe and even Pac-Man. And it's the same architecture, no change. The agent doesn't know the rules of the game, virtually nothing, all by itself, or by player with these environments. So, Juergen Schmidhuber proposed something called Gate-On-Machines, which is a self-improving program that rewrites its own code. What sort of mathematically or philosophically, what's the relationship in your eyes, if you're familiar with it, between Aixi and the Gate-On-Machines? Yeah, familiar with it. He developed it while I was in his lab. Yeah, so the Girdle Machine, to explain it briefly, you give it a task. It could be a simple task as, you know, finding prime factors and numbers, right? You can formally write it down. There's a very slow algorithm to do that. Just try all the factors, yeah? Or play chess, right? Optimally, you write the algorithm to minimax to the end of the game. So, you write down what the Girdle Machine should do. Then it will take part of its resources to run this program, and other part of the resources to improve this program. And when it finds an improved version which provably computes the same answer, so that's the key part, yeah, it needs to prove by itself that this change of program still satisfies the original specification. And if it does so, then it replaces the original program by the improved program, and by definition, it does the same job, but just faster. Okay? And then, you know, it proves over it and over it. And it's developed in a way that all parts of this Girdle Machine can self-improve, but it stays provably consistent with the original specification. So, from this perspective, it has nothing to do with IXE. But if you would now put IXE as the starting axioms in, it would run IXE, but, you know, that takes forever. But then if it finds a provable, speed up of IXE, it would replace it by this, and this, and this, and maybe eventually it comes up with a model which is still the IXE model. It cannot be, I mean, just for the knowledgeable reader, IXE is incomputable, and I can prove that, therefore, there cannot be a computable exact algorithm computer. There needs to be some approximations, and this is not dealt with the Girdle Machine, so you have to do something about it. But there's the IXETL model, which is finitely computable, which we could put in. Which part of IXE is non-computable? The Solomonov induction part. The induction, okay, so. But there's ways of getting computable approximations of the IXE model, so then it's at least computable. It is still way beyond any resources anybody will ever have, but then the Girdle Machine could sort of improve it further and further in an exact way. So, is it theoretically possible that the Girdle Machine process could improve? Isn't IXE already optimal? It is optimal in terms of the reward collected over its interaction cycles, but it takes infinite time to produce one action. And the world continues whether you want it or not. So, the model is, assuming you had an oracle, which solved this problem, and then in the next 100 milliseconds or the reaction time you need gives the answer, then IXE is optimal. So, it's optimal in sense of data, also from learning efficiency and data efficiency, but not in terms of computation time. And then, yeah, the Girdle Machine, in theory, but probably not provably, could make it go faster. Yes. Okay. Interesting, those two components are super interesting. The sort of the perfect intelligence combined with self-improvement. Sort of provable self-improvement in the sense you're always getting the correct answer and you're improving. Beautiful ideas. Okay, so you've also mentioned that different kinds of things in the chase of solving this reward, sort of optimizing for the goal, interesting human things could emerge. So, is there a place for consciousness within IXE? Where does, maybe you can comment, because I suppose we humans are just another instantiation of IXE agents and we seem to have consciousness. You say humans are an instantiation of an IXE agent? Yes. Oh, that would be amazing, but I think that's not true even for the smartest and most rational humans. I think maybe we are very crude approximations. Interesting, I mean, I tend to believe, again, I'm Russian, so I tend to believe our flaws are part of the optimal. So, we tend to laugh off and criticize our flaws and I tend to think that that's actually close to an optimal behavior. Well, some flaws, if you think more carefully about it, are actually not flaws, yeah, but I think there are still enough flaws. I don't know, it's unclear. As a student of history, I think all the suffering that we've endured as a civilization, it's possible that that's the optimal amount of suffering we need to endure to minimize long-term suffering. That's your Russian background, I think. That's the Russian, whether humans are or not instantiations of an IXE agent, do you think there's a consciousness of something that could emerge in a computational form of framework like IXE? Let me also ask you a question. Do you think I'm conscious? Yeah, that's a good question. That tie is confusing me, but I think so. You think that makes me unconscious because it strangles me? If an agent were to solve the imitation game posed by Turing, I think they would be dressed similarly to you. That because there's a kind of flamboyant, interesting, complex behavior pattern that sells that you're human and you're conscious. But why do you ask? Was it a yes or was it a no? Yes, I think you're conscious, yes. Yeah, and you explained somehow why, but you infer that from my behavior, right? You can never be sure about that. And I think the same thing will happen with any intelligent way to develop if it behaves in a way sufficiently close to humans or maybe if not humans. I mean, maybe a dog is also sometimes a little bit self-conscious, right? So if it behaves in a way where we attribute typically consciousness, we would attribute consciousness to these intelligent systems and IXE probably in particular. That of course doesn't answer the question whether it's really conscious. And that's the big hard problem of consciousness. Maybe I'm a zombie. I mean, not the movie zombie, but the philosophical zombie. Is to you the display of consciousness close enough to consciousness from a perspective of AGI that the distinction of the hard problem of consciousness is not an interesting one? I think we don't have to worry about the consciousness problem, especially the hard problem for developing AGI. I think we progress. At some point we have solved all the technical problems and this system will behave intelligent and then super intelligent. And this consciousness will emerge. I mean, definitely it will display behavior which we will interpret as conscious. And then it's a philosophical question. Did this consciousness really emerge or is it a zombie which just fakes everything? We still don't have to figure that out although it may be interesting, at least from a philosophical point of view, it's very interesting, but it may also be sort of practically interesting. You know, there's some people say, if it's just faking consciousness and feelings, then we don't need to be concerned about rights. But if it's real conscious and has feelings, then we need to be concerned. I can't wait till the day where AI systems exhibit consciousness because it'll truly be some of the hardest ethical questions of what we do with that. It is rather easy to build systems which people ascribe consciousness. And I give you an analogy. I mean, remember, maybe it was before you were born, the Tamagotchi? Yeah. Before you were born. How dare you, sir? Why? That you're young, right? Yes, it's a good thing. Yeah, thank you. Thank you very much. But I was also in the Soviet Union. We didn't have any of those fun things. But you have heard about this Tamagotchi which was really, really primitive. Actually, for the time it was, and you could raise this, and kids got so attached to it and didn't want to let it die. And probably if we would have asked the children, do you think this Tamagotchi is conscious? They would have said yes. They would have said yes, I would guess. I think that's kind of a beautiful thing, actually, because that consciousness, ascribing consciousness seems to create a deeper connection, which is a powerful thing. But we have to be careful on the ethics side of that. Well, let me ask about the AGI community broadly. You kind of represent some of the most serious work on AGI, at least earlier. And DeepMind represents serious work on AGI these days. But why, in your sense, is the AGI community so small or has been so small until maybe DeepMind came along? Like, why aren't more people seriously working on human-level and superhuman-level intelligence from a formal perspective? Okay, from a formal perspective, that's sort of an extra point. So I think there are a couple of reasons. I mean, AI came in waves, right? You know, AI winters and AI summers, and then there were big promises which were not fulfilled. And people got disappointed. And that narrow AI, solving particular problems which seem to require intelligence, was always to some extent successful and there were improvements, small steps. And if you build something which is useful for society or industrially useful, then there's a lot of funding. So I guess it was in parts the money which drives people to develop specific systems, solving specific tasks. But you would think that at least in university, you should be able to do ivory tower research. And that was probably better a long time ago, but even nowadays, there's quite some pressure of doing applied research or translational research. And it's harder to get grants as a theorist. So that also drives people away. It's maybe also harder attacking the general intelligence problem. So I think enough people, I mean, maybe a small number were still interested in formalizing intelligence and thinking of general intelligence, but not much came up, right? Or not much great stuff came up. So what do you think, we talked about the formal, big light at the end of the tunnel, but from the engineering perspective, what do you think it takes to build an AGI system? I don't know if that's a stupid question or a distinct question from everything we've been talking about at IAXE, but what do you see as the steps that are necessary to take to start to try to build something? So you want a blueprint now and then you go off and do it? That's the whole point of this conversation. I'm trying to squeeze that in there. Now, is there, I mean, what's your intuition? Is it in the robotics space or something that has a body and tries to explore the world? Is in the reinforcement learning space, like the efforts with AlphaZero and AlphaStar that are kind of exploring how you can solve it through in the simulation, in the gaming world? Is there stuff in sort of all the transformer work in natural English processing, sort of maybe attacking the open domain dialogue? Like what, where do you see the promising pathways? Let me pick the embodiment maybe. So, embodiment is important, yes and no. I don't believe that we need a physical robot walking or rolling around, interacting with the real world in order to achieve AGI. And I think it's more of a distraction probably than helpful. It's sort of confusing the body with the mind. For industrial applications or near-term applications, of course we need robotics for all kinds of things, but for solving the big problem, at least at this stage, I think it's not necessary. But the answer is also yes, that I think the most promising approach is that you have an agent and that can be a virtual agent in a computer interacting with an environment, possibly a 3D simulated environment like in many computer games. And you train and learn the agent. Even if you don't intend to later put it sort of, this algorithm in a robot brain and leave it forever in the virtual reality, getting experience in a, although it's just simulated 3D world, is possibly, and I say possibly, important to understand things on a similar level as humans do, especially if the agent or primarily if the agent needs to interact with the humans, right? If you talk about objects on top of each other in space and flying and cars and so on, and the agent has no experience with even virtual 3D worlds, it's probably hard to grasp. So if you develop an abstract agent, say we take the mathematical path and we just want to build an agent which can prove theorems and becomes a better and better mathematician, then this agent needs to be able to reason in very abstract spaces. And then maybe sort of putting it into a 3D environment, simulated, or it is even harmful. It should sort of, you put it in, I don't know, an environment which it creates itself or so. It seems like you have an interesting, rich, complex trajectory through life in terms of your journey of ideas. So it's interesting to ask what books, technical, fiction, philosophical books, ideas, people had a transformative effect. Books are most interesting because maybe people could also read those books and see if they could be inspired as well. Yeah, luckily I asked books and not singular book. It's very hard and I try to pin down one book. And I can do that at the end. So the most, the books which were most transformative for me or which I can most highly recommend to people interested in AI. Both perhaps. Yeah, yeah, both, both, yeah, yeah. I would always start with Russell and Norvig, Artificial Intelligence, a Modern Approach. That's the AI Bible. It's an amazing book. It's very broad. It covers all approaches to AI. And even if you focus on one approach, I think that is the minimum you should know about the other approaches out there. So that should be your first book. Fourth edition should be coming out soon. Oh, okay, interesting. There's a deep learning chapter now, so there must be. Written by Ian Goodfellow, okay. And then the next book I would recommend, the Reinforcement Learning Book by Sutton and Bartow. That's a beautiful book. If there's any problem with the book, it makes RL feel and look much easier than it actually is. It's very gentle book. It's very nice to read, the exercises to do. You can very quickly get some RL systems to run. You know, on very toy problems, but it's a lot of fun. And in a couple of days, you feel, you know what RL is about. But it's much harder than the book. Come on now, it's an awesome book. Yeah, no, it is, yeah. And maybe, I mean, there's so many books out there. If you like the information theoretic approach, then there's Kolmogorov Complexity by Leon Vitani. But probably, you know, some short article is enough. You don't need to read a whole book, but it's a great book. And if you have to mention one all-time favorite book, so different flavor, that's a book which is used in the International Baccalaureate for high school students in several countries. That's from Nikolaus Altschul's Theory of Knowledge, second edition or first, not the third, please. The third one, they took out all the fun. So this asks all the interesting, or to me, interesting philosophical questions about how we acquire knowledge from all perspectives, you know, from math, from art, from physics, and ask how can we know anything? And the book is called Theory of Knowledge. From which, is this almost like a philosophical exploration of how we get knowledge from anything? Yes, yeah, I mean, can religion tell us, you know, about something about the world? Can science tell us something about the world? Can mathematics, or is it just playing with symbols? And, you know, it's open-ended questions. And I mean, it's for high school students, so they have then resources from Hitchhiker's Guide to the Galaxy and from Star Wars and the Chicken Crossed the Road, yeah? And it's fun to read, but it's also quite deep. If you could live one day of your life over again, has it made you truly happy? Or maybe like we said with the books, it was truly transformative. What day, what moment would you choose that something pop into your mind? Does it need to be a day in the past, or can it be a day in the future? Well, space-time is an emergent phenomena, so it's all the same anyway. Okay. Okay, from the past. You're really gonna say from the future, I love it. No, I will tell you from the future, yeah, okay? From the past. So from the past, I would say when I discovered my axiom model. I mean, it was not in one day, but it was one moment where I realized Kolmogorov complexity, I didn't even know that it existed, but I discovered sort of this compression idea myself, but immediately I knew I can't be the first one, but I had this idea. And then I knew about sequential decision tree, and I knew if I put it together, this is the right thing. And yeah, still when I think back about this moment, I'm super excited about it. Was there any more details and context that moment? Did an apple fall on your head? So if you look at Ian Goodfellow talking about GANs, there was beer involved. Is there some more context of what sparked your thought, or was it just? No, it was much more mundane. So I worked in this company, so in this sense, the four and a half years was not completely wasted. So, and I worked on an image interpolation problem, and I developed a quite neat new interpolation techniques, and they got patented. And then I, which happens quite often, I got sort of overboard and thought about, yeah, that's pretty good, but it's not the best. So what is the best possible way of doing interpolation? And then I thought, yeah, you want the simplest picture, which is if you core screen it, recovers your original picture. And then I thought about the simplicity concept more in quantitative terms, and yeah, then everything developed. And somehow the full beautiful mix of also being a physicist and thinking about the big picture of it then led you to probably think big with Ike. Yeah, yeah, so as a physicist, I was probably trained not to always think in computational terms, just ignore that and think about the fundamental properties which you want to have. So what about if you could really one day in the future, what would that be? When I solve the AGI problem. I don't think that- In practice, in practice. So in theory, I have solved it with the Ike-C model, but in practice. And then I ask the first question. What would be the first question? What's the meaning of life? I don't think there's a better way to end it. Thank you so much for talking today. It's a huge honor to finally meet you. Yeah, thank you too. It was a pleasure of mine, so I too. Thanks for listening to this conversation with Marcus Hutter and thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, an organization that inspires and educates young minds to become science and technology innovators of tomorrow. If you enjoy this podcast, subscribe on YouTube, get five stars on Apple Podcast, support on Patreon or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words of wisdom from Albert Einstein. The measure of intelligence is the ability to change. Thank you for listening and hope to see you next time.

https://youtu.be/E1AxVXt2Gv4

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Elon Musk Meme Review

And now for something completely different. Do you mind doing a bit of a meme review in the spirit of the great, the powerful PewDiePie? Let's say 1 to 11, just go over a few documents printed out. We can try. Let's try this. I present to you document numero uno. I don't know, okay. Vlad the Impaler discovers marshmallows. That's not bad. So you get it because he likes impaling things? Yes, I get it. I don't know, three, whatever. That's not very good. This is ground in some engineering, some history. Yeah, I give this an 8 out of 10. What do you think about nuclear power? I'm in favor of nuclear power. I think it's, in a place that is not subject to extreme natural disasters, I think it's, nuclear power is a great way to generate electricity. I don't think we should be shutting down nuclear power stations. Yeah, but what about Chernobyl? Exactly. So I think people, there's like a lot of fear of radiation and stuff. And it's, I guess, the problem is like a lot of people just don't understand, they didn't study engineering or physics. Sometimes the word radiation just sounds scary, so they can't calibrate what radiation means. But radiation is much less dangerous than you'd think. So like, for example, Fukushima, when the Fukushima problem happened due to the tsunami, I got people in California asking me if they should worry about radiation from Fukushima. I'm like, definitely not, not even slightly, not at all. That is crazy. And just to show, like, look, this is how, like, the dangers is so much overplayed compared to what it really is that I actually flew to Fukushima. I donated a solar power system for a water treatment plant. And I made a point of eating locally grown vegetables on TV in Fukushima. Like I'm still alive, okay. So it's not even that the risk of these events is low, but the impact of them is... Impact is greatly exaggerated. It's human nature. People don't know what radiation is. Like I've had people ask me, like, what about radiation from cell phones causing brain cancer? I'm like, when you say radiation, do you mean photons or particles? They're like, I don't know what you mean, photons, particles. Do you mean, let's say photons, what frequency or wavelength? And they're like, no, I have no idea. Like do you know that everything's radiating all the time? Like what do you mean? Like, yeah, everything's radiating all the time. Photons are being emitted by all objects all the time, basically. And if you want to know what it means to stand in front of nuclear fire, go outside. The sun is a gigantic thermonuclear reactor. You're staring right at it. Are you still alive? Yes. Okay, amazing. Yeah, I guess radiation is one of the words that can be used as a tool to fear monger by certain people. That's it. I think people just don't understand. I mean, that's the way to fight that fear, I suppose, is to understand, is to learn. Yeah, just say like, okay, how many people have actually died from nuclear accidents? It's like practically nothing. And say how many people have died from coal plants? And it's a very big number. So like, obviously, we should not be starting up coal plants and shutting down nuclear plants. Just doesn't make any sense at all. Coal plants like, I don't know, 100 to 1000 times worse for health than nuclear power plants. You want to go to the next one? This is really bad. So that 90, 180 and 360 degrees, everybody loves the math. Nobody gives a shit about 270. It's not super funny. I don't like 203. This is not, you know, LOL situation. Yeah. That's pretty good. The United States oscillating between establishing and destroying dictatorships. It's like a metric. Is that a metric? Yeah, metronome. Yeah, it's a 7 out of 10. It's kind of true. Oh, yeah. This is kind of personal for me. Next one. Oh, man, this is Laika? Yeah. Well, no. Or it's like referring to Laika or something? As Laika's husband. Husband. Yeah, yeah. Hello, yes, this is dog. Your wife was launched into space. And then the last one is him with his eyes closed and a bottle of vodka. Yeah, Laika didn't come back. No. They don't tell you the full story of, you know, what the impact they had on the loved ones. True. That one gets an 11 for me. Yeah, yeah. The Soviet shutout. Oh, yeah, this keeps going on the Russian theme. First man in space, nobody cares. First man on the moon. Well, I think people do care. I know, but... Yuri Gagarin's name will be forever in history, I think. There is something special about placing, like, stepping foot onto another totally foreign land. It's not the journey like people that explore the oceans. It's not as important to explore the oceans as to land on a whole new continent. Yeah. This is about you. Oh, yeah, I'd love to get your comment on this. Elon Musk, after sending $6.6 billion to the UN to end world hunger, you have three hours. Yeah, well, I mean, obviously $6 billion is not going to end world hunger. So I mean, the reality is at this point, the world is producing far more food than it can really consume. Like, we don't have a caloric constraint at this point. So where there is hunger, it is almost always due to like, Civil War, strife or some like... It's not a thing that is extremely rare for it to be just a matter of like, lack of money. It's like, you know, it's like some Civil War in some country and like one part of the country is literally trying to starve the other part of the country. So it's much more complex than something that money could solve. It's geopolitics. It's a lot of things. It's human nature. It's governments. It's money, monetary systems, all that kind of stuff. Yeah, food is extremely cheap these days. I mean, the US at this point, you know, among low-income families, obesity is actually another problem. It's not like, obesity is not hunger. It's like too much, you know, too many calories. So it's not that nobody's hungry anywhere. It's just, this is not a simple matter of adding money and solving it. What do you think that one gets? Just kidding. Two. Just going after Empires. World, where did you get those artifacts? The British Museum. Shout out to Monty Python. We found them. Yeah, the British Museum is pretty great. I mean, admittedly Britain did take these historical artifacts from all around the world and put them in London. But, you know, it's not like people can't go see them. So it is a convenient place to see these ancient artifacts is London for a large segment of the world. So I think, you know, on balance, the British Museum is a net good. Although I'm sure a lot of countries would argue about that. It's like you want to make these historical artifacts accessible to as many people as possible. And the British Museum, I think, does a good job of that. Even if there's a darker aspect to the history of Empire in general, whatever the Empire is, however things were done, it is the history that happened. You can't sort of erase that history, unfortunately. You could just become better in the future. That's the point. Yeah, I mean, it's like, well, how are we going to pass moral judgment on these things? Because if one is going to judge, say, the British Empire, you've got to judge what everyone was doing at the time and how were the British relative to everyone. And I think the British would actually get a relatively good grade, relatively good grade, not in absolute terms, but compared to what everyone else was doing, they were not the worst. Like I said, you got to look at these things in the context of the history at the time and say, what were the alternatives and what are you comparing it against? And I do not think it would be the case that Britain would get a bad grade when looking at history at the time. Now, if you judge history from what is morally acceptable today, you're basically going to give everyone a failing grade. I'm not clear, I don't think anyone would get a passing grade in their morality of like you go back 300 years ago, like who's getting a passing grade? Basically no one. And we might not get a passing grade from generations that come after us. What does that one get? Sure, six, seven, seven. For the Monty Python, maybe. I always love Monty Python, they're great. The Life of Brian and the Quest of the Holy Grail are incredible. Yeah, yeah. Damn, those serious eyebrows. Braj Neb. How important do you think is facial hair to great leadership? Well you got a new haircut, how does that affect your leadership? I don't know, hopefully not. It doesn't. Is that the second no one? Yeah, the second is no one. There is no one competing with Braj Neb. Those are like epic eyebrows. So sure. That's ridiculous. Give it a six or seven, I don't know. I like this like Shakespearean analysis of memes. Braj Neb had a flair for drama as well, like you know, showmanship. Yeah, yeah, it must come from the eyebrows. All right, invention, great engineering, look what I invented. That's the best thing since ripped up bread. Yeah. I invented sliced bread. Am I just explaining memes at this point? This is what my life has become. He's a meme lord, he's a meme explainer. Like a scribe that like runs around with the kings and just like writes down memes. I mean, when was the cheeseburger invention? That's like an epic invention. Like wow. Versus just like a burger? Or a burger, I guess a burger in general. Then there's like, what is a burger? What's a sandwich? And then you start getting, is a pizza a sandwich? And what is the original? It gets into an ontology argument. Yeah, but everybody knows like if you order like a burger or cheeseburger or whatever, and you like, you get like, tomato and some lettuce and onions and whatever, and mayo and ketchup and mustard, it's like epic. Yeah, but I'm sure they've had bread and meat separately for a long time, and it was kind of a burger on the same plate, but somebody who actually combined them into the same thing, and you bite it and hold it makes it convenient. It's a materials problem. Your hands don't get dirty and whatever. Yeah, it's brilliant. Well, that is not what I would have guessed. But everyone knows like if you order a cheeseburger, you know what you're getting, you know, it's not like some obtuse, like, I wonder what I'll get, you know. You know, fries are, I mean, great. I mean, they're the devil, but fries are awesome. And yeah, pizza is incredible. Food innovation doesn't get enough love. Yeah. I guess this is what we're getting at. Great. What about the Matthew McConaughey Austinite here? President Kennedy, do you know how to put men on the moon yet? NASA? No. President Kennedy, be a lot cooler if you did. Pretty much. Sure. Six, six or seven, I suppose. And this is the last one. That's funny. Someone drew a bunch of dicks all over the walls, Sistine Chapel, boys bathroom. Sure, I'll give it nine. It's really true. This is our highest ranking meme for today. I mean, it's true. Like, how did they get away with it? Lots of nakedness. I mean, dick pics are, I mean, just something throughout history. As long as people can draw things, there's been a dick pic. It's a staple of human history. It's a staple. It's a staple of human history.

https://youtu.be/oJHb5a3ggzE

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Niels Jorgensen: New York Firefighters and the Heroes of 9/11 | Lex Fridman Podcast #220

The following is a conversation with Niels Jorgensen, a New York firefighter for over 21 years who was there at Ground Zero on September 11, 2001. He was forced to retire because of the leukemia he contracted from cleaning up Ground Zero. This podcast tells his story and the story of other great men and women who were there that day. Some of the stories we talk about are part of a new limited podcast series that Niels hosts called 20 for 20 with 20 episodes for the 20 years since 9-11. To support this podcast, please check out our sponsors in the description. As a side note, please allow me to say a few words about the terrorist attacks on September 11, 2001. I was in downtown Chicago on that day, lost in the mundane busyness of an early Tuesday morning. At that time, I was already fascinated by human nature, the best and the worst of it, exploring it through the study of history and literature. In the years before, as a young boy growing up in Russia, I saw chaos, uncertainty, and desperation in the Soviet Union of the 1990s, wrapping up a century of war and suffering. But after coming to America, for me, there was a sense of hope, like all of it was behind us, a bad dream to be forgotten as we enter into the new century. On 9-11, when I saw the news of the second plane hitting the towers, my sense of hope had changed. I understood that the 21st century, like the century before, would too have its tragedies, its evildoers, its wars, and its suffering. And unlike the history books, these stories will involve all of us. They will involve me, in however small and insignificant a role, but one that nevertheless carries the responsibility to help. I became an American that day, a citizen of the world. I felt the common humanity in all of us. I felt the unity and the love and the days that followed, and I think most of the world shared in this feeling, that we are all in this together. Evil cannot defeat the human spirit. There were many heroes sung and unsung on that day and in the years after. Often, politicians fail to rightfully honor the service and sacrifice of these heroes. There is much I could say about that, but I don't want to waste my words on the failures of weak leaders. Instead, I want to say thank you to the men and women who rushed to ground zero to help, who put on a uniform to serve, who make me proud to be an American and a human being, and give me hope about the future of our civilization, here on a small spinning rock that despite the long odds, keeps kindling the fire of human consciousness and love. This is the Lex Friedman Podcast, and here is my conversation with Niels Jorgensen. Take me through the day of September 11th, 2001, as you experienced it, as you lived it. September 11th, 2001, it was a bright, beautiful, sunny Tuesday morning. It was late summer. There's a lot of folks who go to the beaches in New Jersey, call it the short summer. Everybody's left there for Labor Day, but it's still beautiful enough to enjoy the weather. I left my house about 6.30 in the morning, and my four and a half year old daughter said to me, Daddy, which truck are you driving today? The fire truck, the oil truck, or the Boar's Head truck? Because I had three jobs at the time. Most New York City firefighters and police officers, EMS, we don't make the most amount of money. So in order to live in that city, you have to hustle. My wife stayed at home raising the children. So my daughter said, oh, so you should be safe because you're on the oil truck. I told her I was going on the oil truck that day. So she said, you should be safe today, Daddy. So I left and worked for this great company on the North Shore, Staten Island, Quinlin Fuel, very nice people, treated me very well. And it was my first day back actually for the winter season. I usually get laid off a couple months in the summer because things are too hot to need oil. So I took the truck, started my route that day, and a plane hit the tower. So initially, I'm like, oh, it's probably some silly Learjet pilot, and he veered off track to get a better picture for a client, and he hit the building. So probably hit a bad turbulence, gust of wind. It's very windy down in that area, Manhattan. So that was my first thought. Can we pause there for a second? So 6.30 AM, you wake up, you leave, and then the plane hits at 8.45, 8.50, yeah. 8.45 AM. Yeah. It's just interesting how you phrase it. So how did you hear that a plane hit something? I'm a big news radio guy, news guy, bit of a buff. I've been that way since I was a kid, and I had the news radio on the local New York radio station. And as I was driving the truck, I heard an emergency report, this just in, aircraft has just struck the World Trade Center. And where Queensland is located, it's on the north rim of Staten Island, which is right on New York Harbor. And you could see Statue of Liberty a mile or two away in the distance, and then past that is the towers. So I just literally stopped the truck and looked out, and I saw the smoke. So there was smoke. Oh, it was dark black smoke. It was just, yeah, I mean, it was burning fully at that point. Did you have fear of what the hell happened? I was initially scared for anybody involved. I realized, I said, there's gonna be lots of fatalities, obviously, depending on the size of the aircraft. And the business day there had started probably at 8, 830. So those buildings should have been packed at that moment. So that was a thought that crossed my mind. But from our being responder perspective, if you're off duty, normally you do not go to a scene. They don't want you to because of accountability and safety. The on duty platoon will handle it. And if it's something very horrific, then they will have something called a recall, which is any police, firefighter, or EMS personnel is obligated to go to their command immediately, check in with their command, get their gear and stand by and await orders for deployment or to remain in that command for routine duties. Your routine duties. How often throughout history have there been recalls? I believe the one prior to that was like in the 1968 riots, possibly. And then maybe in the 70s, there was another blackout and riots. And I remember my dad talking about it. And he actually always said, just remember if something bad's going down, don't just rush in, you will wait the recall or at the very least, if there isn't a recall, you get to your firehouse. And because if you show up somewhere, there's a good chance that no one knows you're there. And now you, in your well-intended movements, you get lost or trapped or no one's looking for you. So that's the whole thing with checking in. And now you're with a squad or group of guys and everyone knows, hey, there's Nels, there's Lex. Okay. They're on this team. So I said, all right, they're not going to need us. It's probably going to be a fifth alarm and there'll be 250 firefighters there. They'll handle it. It's going to be a bad day for those guys, but our guys take on some heavy stuff and they'll be fine. A few minutes later, the second plane hit and I knew immediately, I'm like, okay, we're under attack. So I just flew the truck back in. I told my boss, I have to go. He understood, he knew something was way wrong and I just was flying. At the time, I actually had a yellow Volkswagen Beetle, kind of a goofy car to be driving, but I loved it. So for people who are just listening, you're kind of a big guy. Well, yeah, I definitely need to lose about 50 pounds. No, I don't mean in that way, your frame, big hands. As my beloved friend, Bobby Adams would say to me, I was driving around in a clown wagon and he also says I have a waving hairdo, waving bye-bye. So thanks, Bobby. You're good luck. Well, yeah, he's a great friend. Yeah, so I took the Volkswagen and I flew in and I was heading over to Verrazano Bridge and hit the Brooklyn Queens Expressway and my phone rang and my wife normally doesn't curse or raise a voice and she was yelling at me and she said, don't go in there, go to your firehouse. Well, first she asked where, she knew I was on the way, but she just wanted to know where. And I said, I'm on the curve, which is 65th Street on the Brooklyn Queens Expressway called Dead Man's Curve. We actually used to do a lot of car wrecks up there and I was hitting that curve pretty fast. And then right around the curve is the exit to the firehouse and I had to decide, well, am I driving right in to the battery tunnel to the city or am I going to the firehouse? And then I said, but I have no gear. I'm going to be ineffective. How do I show up with no gear, no protection? So she said, do what your dad would follow the recall, go to the firehouse. I hung up the phone, I love you, got to go. And I did, I went to the firehouse and I'm glad I listened to her. I had my father ringing in my ears, my dad, beautiful guy, he's 82, 34 years in New York City fire department. He came down on end stage non-hodgkin's lymphoma. He's 38, going on 39, 1978. And this guy, he's my hero. He was going to die, they sent him home. They said, there's really not much we can do. Go get your affairs and owner. And he says, but doc, I have three young kids. And she called him a couple hours later. She said, I got in touch with Sloan Kettering and they have a new drug. We want you to be a test pilot. And he said, hey doc, he's got a heavy Brooklyn accent. I'm a fireman, I'm a fireman, I'm not a pilot. And so she said, no, no, we want you to try this drug out. And if it works, we might have some success. But if not, he says, yeah, I'm going to die. So let's do it. So every two weeks for four years, he'd go for treatment, but he was assigned to a desk job after that, after the cancer tumor removal and the heavy treatments. And he'd get up every morning, four o'clock in the morning, and he'd walk down to the train station in Staten Island, take the train. And then he'd take the ferry across the Harbor and he'd get off looking at the towers. And then he'd take a subway into Brooklyn. And on every other Thursday, he'd leave at noon, do the same exact reverse route. And he'd get to the cancer center and my mom would meet him. And he'd get his infusion and within two hours, he'd be violently ill for a few days, a few days, really badly ill. And I just remember, I was 10 years old and he just had to have the room darkened out and he'd be so sick. And I just go in and wipe the vomit on his face, just try to give him a little water, but he couldn't take it down because he'd throw it up. And maybe on Saturday, he'd start coming around a little bit, drink down a little bit of tea. And on Sunday morning, he'd put his robe on, he'd go down, mom would make him black coffee and toast. He'd sit up, watch the news, watch a game. And then Monday morning, he'd go back to work. He did that for four years. And he's 82 and he's still here. You said that your dad's a man of a few words, but when he talks, they're profound. So what words were ringing in your ear when you were driving? I just always remember him saying, kid, they give the recall, you go to the firehouse, you don't go where you think you should, you go to the firehouse, you follow your orders. So do the smart thing, do your job. Yes, sir. And every time we'd hang up the phone, it's fireman talk. He'd say, I love you, keep low. My dad couldn't tell me he loved me until I told him when I first got on a fire department. I was 22 and my dad grew up in a tough household. My granddad was a good man, but a tormented man. He was sent away from home at 12 years old. He was from Denmark and I'm named after him, Grandpa Nils. And I think his demons took up a large part of his life, his anger, whatever it was, his fear. We got the sense that maybe when he was a child, he was an apprentice baker, living with strangers, working for them. And we think maybe he was abused and that's why he took it out on my dad and my grandma and my aunts. But they made it up to each other at the end of my granddad's life. My granddad turned out to be the best grandfather ever. I think he tried to heal and heal everyone by his change of behavior. So he's proof that you can change, you can improve if you work on it. But I know I'm going off track here, but- But you were a man enough, you say in your 20s to tell your dad- My dad, yeah. That you love him? I got on the job and he said, how'd it go, kid? How was the tour? We call it tour duty. I said, oh, dad, it was great. It was great. I love it. And he goes, just remember, you keep low. You always keep low. And keep low means you stay down below the flames. If a room flashes over and it's burning, if you stay up high, you're going to get burned badly. But if you get down on your belly and you crawl, you'll get out. So he'd always say that when you hang up the phone. And I said, well, I love you, pop. And he says, oh, well, thanks, kid. I said, well, you can say it too. And- Oh, nice. You pressured him. And he did. And he said it. And now every time we talk, he says it. So they talk about masculinity and whatnot. And my dad is one of those tough, tough guys with a soft edge. And that's how he brought me up, to be a protector. I hate bullies. I was bullied really badly as a kid. And I really hated it. And now I find myself sometimes throwing myself into situations to protect people that are being violated and hurt. And I just can't walk away from it. But that's my dad. My dad was that, just a great guy. But anyway, yeah. You still listen to, therefore, see, you probably wouldn't have rushed right to the towers, but you went- Yeah. So anyway, I did. I listened to him. I listened to my wife. I went to the firehouse. And it was really strange. It was eerie because the computer dispatch system was still beeping, which meant it sent a dispatch and the truck received it. Ladder 114, my truck company received it and they left. They were gone. So it was this beautiful old building built in the 1880s with a spiral staircase, just a narrow old brick garage. And it was empty. And I just heard the computer chirping. And I looked down on a ticket and it said, Ladder 114, respond. The Vessian West World Trade Center aircraft into building. And I said, oh God, I just hope they're not on a death ride because this now was two towers and they were burning. They were free burning. And I knew this was really, really bad. And I got on the phone and I called commands right away. I called the 40th battalion and chief's aide just said, look, get 12 guys, sign them in to the journal. There's a journal of daily events. Everything that takes place in the firehouse 24 seven has to be logged. And I logged myself as coming in, reporting for duty. And as the guys came in, I logged them in. And then one of our lieutenants took command. We grabbed up a bunch of gear and they basically told us, get 12 guys, get a city bus and get down to the battery tunnel. They said it would probably be closed. There was threats it was going to be blown up to get to the Brooklyn Bridge. And so we did. We got a city bus, we flagged it down and the bus driver said, I'm sorry, I can't give you the bus. I will drive you. And he took us and we stopped at engine 201, which is just about a quarter mile down the road from us. That's our affiliated engine company. And my childhood best friend here, Johnny Shard, he was assigned there and he was on shift. And then they went through the tunnel and we picked up those guys, the off-duty guys from 201. And then we kept going down 4th Avenue and we picked up 239's crew. And then we hightailed it down to the bridge and there's a lot of traffic. There's a lot of people fleeing, coming over the bridge and waves. So it affected the inbound. What was the mood like among the crew? It was somber because just prior to getting on the bus, the first tower went down. So we figured that I had heard 114, my lieutenant, Dennis Oberg, I heard him on the radio and he said, 114 to Manhattan, we're on your frequency. What do you need us? And they said, Tally Ho, which is our nickname, Tally Ho, respond in the Vessian West to the command post and receive your orders. And I heard Dennis say, Tally Ho, 10-4. And Dennis, a little while after that, they were proceeding to go into, I believe it was, I get this mixed up and I'm sorry, I should know this by the back of my hand, but sometimes it's just such a haze. But the second tower hit was the first one to go down and they were heading over to go in it. And all of a sudden he looked up and he saw what he thought to be disintegration and he turned the guys around. He said, run, just run. Don't look back. Don't look up, go. They sprinted as fast as they could and they dove under a fire truck. And the guys that were sprinting behind him 40 feet away were underneath a pile that was 10 stories deep. They were killed. And just further into that pile was his rookie son, who Dennis's rookie son, who was working in Ladder 105, which was my first command on the department. I worked for, proudly served for three years. And just beside them was my childhood best friend, John Shard and his crew from 201. And they were all killed. And the strange irony to that is that Dennis's son, Dennis Jr. was working under the wing of a senior man, as we say. A senior man is a guy with a lot of experience and he'll watch over you and make sure you don't veer off. Like I veer off a lot of talking and you don't veer off and you get yourself hurt. In the morning of the 1993 bombing, Henry Miller was my senior man. And I was the young guy under his wing and he protected me. And toward the end of the day, he looked around and he said, kid, it's a bad day. And he said, they didn't do it right. They blew it up in the middle. If they did it in a corner, they would have dropped this building half mile down at Canal Street. But don't kid yourself, they'll be back and they'll do it. And they'll do it right next time. And it's so strange and so prophetic because he was there with them. He died with Dennis. He knew it. And like 1994, we had a training manual, with a picture of the towers, with a target. And it said, not a matter of if, but a matter of when be prepared. And it's haunting. It was like people knew, right? And we didn't stop it. And so we got off the bus. But just prior to that coming over the bridge, the second tower is gone now. And we're just destroyed because we're like, our guys are there. They're all in there. Now, we're feeling like cowards because we got there late. And initially, we're thinking there's 500 guys that are gone because it was a 10th alarm assignment, which means 50, 60 fire trucks, five to six guys per, you're looking at at least, there was even more 10th alarm plus multiple alarms on top of it. It was a dispatch basically equivalent of five to 600 firefighters. We figured out they're all in there, all gone. All the police officers, Port Authority Police, NYPD Police, court officers just up the street from the courts, transit cops from the train tunnels. We knew everybody was going and now they're gone. So what you saw, what were we looking at? What did it look like? So you saw rubble and then you knew that many, that 105 and 201, many of those guys are in the, they're dead. Yeah. And we thought- What did you see? 114 was in there too. We didn't realize at that point, we didn't even realize that they had gotten under that truck. We thought they were all gone. But yeah, it looked like a movie scene with just end of the earth destruction. It's just massive piles of intertwined steel, what was left of the steel. And there was no cement, it was all just dust. And it was just a burning pile of dust and concrete and plastic. And it was just, everything was just pulverized. And it was truly hard to mentally compute that. It was like, what? And then there was just fighter jets, a couple of fighter jets just circling. And you just heard the flying by over your head. I mean, you literally see the guy banking a turn around the Brooklyn Bridge and just coming back. And I'm like, holy shoot, we're under attack. And we couldn't really get concrete intel as to what exactly, we knew planes, we knew planes, but then we kept hearing there was multiple devices. There was devices in a battery tunnel and there was devices on a George Washington Bridge and in the subways. And it was just chaos. I mean, we kept it together obviously, because that's kind of, we try, that's what we do. But the just constant barrage of different reports, it was like, holy shoot. And then as we were being deployed, it was a little frustrating, but they were trying to take command and send us in groups now because they realized we have to start searching this. You could hear the alarms on the Scott Airmasks, the packs we wear to go into the building. It has a motion alarm. And if you stop moving for 30 seconds, it just sounds like this whining, this screaming bell, it just keeps going and going. And you could hear multiple units of those going off. And you're like, wait a minute, there's guys with those, where are they? And it's emanating from underneath the pile. Wow. And it was just surreal and truly like a war zone. I mean, I was a soldier in the reserves and I never saw combat and I would never claim that I did, but we trained, we trained for a lot of situations and we trained in real life atmospheres and whatnot. And this was just beyond that by weeps and bounds. It was bizarre. Did you see the towers collapse? As we were coming over the bridge, the first one, as we were deploying from the firehouse, we had a television on and I saw it go down. And it just, it was just like, and we were so involved in getting gear together and getting, okay, team set up and okay, you're going to be with these two guys and these, and I just yelled, there's the guys and they're looking at me. I dropped to my knees and I started praying. They're like, what the hell's wrong? I said, I couldn't even say, it's like, I was like, 114, they're in there. And they're like, what? I said, the tower's gone. And all you saw on the TV was just this pile of dust. And I guess, because they didn't see it going down, they probably thought I truly lost it. And then the realization came, it was like, oh, wow, the tower's down. So now it was like, wow, this is really on. So we just took off and got that boss. And- So if you thought many of the guys on 114 were dead, if you thought that, did you think you're going to die? I mean, if you're rushing into the, towards the rubble. As crazy as it sounds, I never thought that the other tower would go down. I said, okay, maybe some freak chance that one went down, but no, the other one's not going to go. They're built so strong. I was in those towers so many times and I made dinner up in the top four restaurant windows on the world. And I'm saying, nah, there's no way. Like how the hell did this one happen? But I was having a hard time mentally processing that the building was gone. And believe me, if you don't have fear in this industry and police, fire, military, then you're kidding yourself or you're a danger to everyone. I don't care who it is, as tough as they are, this and that, everybody has a certain level of fear with doing this. And I don't care how long you do it, there's always that chance of something going bad. And everyone who does it has that certain amount of fear. But at that point, it was such a feeling of disbelief. That fear wasn't even kicking in. It was just like, what the hell just happened? And I honestly think it was almost like a shock and it just stayed that whole day. So the building is, before it collapses, is burning? It's just burning. I mean, upper floors, up in the 78th, up to the 80s. And then there's the way that the cut was from the plane. It wasn't just straight across. It was from the 78th then on up to maybe the 86th. And then the jet fuel had come down and was burning down. And there was people on the ground who were doused with jet fuel that was already burning, and they were lit on fire on the ground. It was just insane how vast the destruction path was. As a firefighter, what are you supposed to do with that scale of fire? I think the first bosses in, the first chiefs, were just going to do their best to get, as we get hose lines, what our whole theory is, or our tactics is, to get water at the fire, at the base of the fire, and get the truck company, which is the ladder company, they're the guys who break the doors down, put ladders up, this and that, to get them to where the life is most expected and get them out of there. So I think the chief's tactics at that point was, let me get multiple engine companies, let me get four, five, six hose lines fighting this fire, hose lines fighting this fire, this massive fire, and let me get 15, 20 truck companies up there, just yoking people out of there. Yeah, but you got to go up the stair, everything's not working. Yeah, guys had to walk up 80, 90, 100 flights of stairs, and there's audio of officers and firefighters speaking to each other on the radio channels. And unfortunately, at that point in time, we had very, very bad communication system. We'd been fighting for years to get radios that work properly. We couldn't, because it was a lot of money. We fought for years to get the full bunker firefighting suits, which is the pants and the coat. We used to have just coats and these roll-up rubber boots, and guys were burning to death. And we had to fight. And unfortunately, we lost three guys in one vicious, vicious fire in 1994. And then they finally said, enough's enough, give these guys the gear. So it's a strange phenomenon in the first responder world and in the military world. It's really one of the most important things that takes place in society, the most pertinent organizations, and we can't get the funding we need. It's crazy. They'll throw money at every nonsensical thing. But when it comes to gear, equipment, protective equipment, trucks, this, couldn't get it. Couldn't get it. Just all the ways you could take care of people. I saw since 9-11, the wars in the Middle East have cost America over $6 trillion. Yeah. And the amount of that money that was spent on the soldiers, in this case, the first responders, is minimal. Compared to it, yeah. Almost nothing. They, Lex, they closed down, I believe it's either seven or eight. In May of 2002, they closed down nine firehouses in New York City for budget reasons. We hadn't even finished cleaning up the World Trade Center site and they slashed the budget. And still to this day, have not reopened those firehouses. There's a million more people now living in New York City than there were in 2001. And the fire protection is way less than it was. And it's a sin. It's really a sin. Can I ask you a difficult question? So, there's this famous photograph of a falling man. So, many people had to decide when they're above the fire, in the fire, whether to jump out of the building or to burn to death. What do you make of that decision? What do you make of that situation? Those people who jumped, those were acts of sheer desperation. I've been in fires and just minor burns, but minor, you know, in situation. But I've been trapped, caught somewhat, ended up in a burn center for some, nothing serious at all. But I, for those brief seconds, half a minute, was, thank God, if I didn't have my fire gear on, I would have been burned to a very, very horrible level. Those people were burning alive. And they had the choice of either to stay there and burn alive or to launch themselves. And some of them, I don't fault them, but they had a few folks, they won't show it anymore because they say, I don't know why, I'd offend some people, but they had a couple folks that took umbrellas and they took garbage bags because they thought that it would slow down their acceleration rate to the ground and maybe, just maybe they wouldn't be killed. And that's, to me, a true sense of desperation for humanity to say, I'm going to die either way, but let me take my chance. And I don't know the exact number of those folks who did that, but our first member of the fire department killed, firefighter Daniel Serf from Engine 216, was struck by a jumper. And one of my dear friends was ordered to help take him, and they knew he was passed away because he was hit by a flying missile, I mean, 120 miles an hour, a body lands on you, those two bodies are now crushed. And they were ordered to take that firefighter and bring him across the street to Engine 10, Ladder 10, it was literally a firehouse, less than a hundred yards from the facade of the Trade Center, from the Trade Center complex, they were literally right there. And there was plane parts that went into that firehouse, landed into the front doors, onto the roof, but the building itself was not destroyed. So it was used as a mini command center for quite a while. So my friend was ordered to take Daniel's body in respect and bring it over to this firehouse and give it some semblance of dignity and lay it out on one of the bunk room, the bunks we have in the bunk house, and just cover it with a sheet and put a sign, please firefighter killed, do not disturb, and then we'll get to him later, because obviously this operation is going to go on for days. And my friend who's such a great, great, wonderful guy is so still to this day, filled with guilt, because if they weren't taking his body out with the respect and dignity that they did, it took a while because, you know, it's just, it's a tough situation. His ladder company was coming over the bridge, there's a famous picture of Ladder 118, you see this tractor trailer fire truck, it's the one where the guy in the back also drives. And it's a zoomed out shot, and you see the Brooklyn Bridge, and you see only the fire truck in the middle, and you see the two burning towers in the distance. Well, his engine company was just ahead of them on the bridge. And the only reason that engine company lived is their initial duty assignment was to take that firefighter and bring his body over. It's like the military, we don't leave anyone behind, these are our guys. As some guys say, it's all about the guy right next to you, and nothing else really matters. When that guy right next to you goes down, it stops, you get that guy to safety, or if he's dead, you get him out. So in that time frame, that saved his life. But that's a heavy burden to carry now for the rest of your life, because you say, if I wasn't helping my dead friend, I'm dead. Yeah. What did it look like at Ground Zero? What did it feel like? What did it smell like? You said there was a sense that it was almost like a war zone, but can you paint a picture of how much dust is in the air? How hot is it? How many people are there? And again, how did it feel like? It was just, it was a scene of control chaos. Control because there was a semblance of command, and we were just trying to do our jobs. But it was such a frantic pace, because we're now digging frantically, knowing that there's life underneath this pile. And this is throughout the afternoon of that evening? Yeah, I mean, this was nonstop, just nonstop really for days. But for my particular crew, we literally kept going. We initially were dispatched over towards number seven, had just gone down, and we were searching the post office that was there. There was reports of people trapped. And we painstakingly searched every single inch of that building to make sure no one was left in there. And then we were deployed to the pile. And the pile is sort of ambiguous, because it was just such a vast, vast pile. I mean, it went for city blocks. And we were assisting in the retrieval of two Port Authority police officers, were lucky enough to survive, but they were trapped. They were deep down into a crevasse, and they had to be physically dug out and extricated. So there was a couple hundred, few hundred guys involved in that process of bringing in equipment, jaws of life, airbags to lift steel, to cut pieces of steel. It was just a huge operation. And we were back toward the logistics end of it, shuttling in gear, and bringing in stretchers, bringing in oxygen, whatever was needed. And you were trying to climb over this jagged pile of debris. It wasn't like you just walked 100 feet on a street with something. You were trying to climb over this I-beam, and then down into this hole, and then back up that hole. I mean, just to run one piece of equipment took a half an hour to get 100 feet, 200 feet. Mind you, some of these pieces of equipment are 100 pounds. Generator for hearse tools, this massive motor on a frame. Unstable ground. Unstable ground. Just horrible conditions. Fires were still burning aside you, beneath you. And at one point, I veered off to the side, and I was with this other fireman from my father's old ladder company, 172. And it was strange, because we were down quite a bit down, like 70 feet down into this ravine of debris. And he says, Brother, what do you hear? And at the time, it was like dust. It was like sand just falling down a pile, and it was hissing from gas pipes and water pipes. And I said, I hear the gas lines. I hear the sand. I hear the concrete. He goes, No, no. What else do you hear? And just beside of us was a lady's pocketbook, and a high heel shoe, and someone's sneaker, but nobody with it. And I said, I don't know. I don't hear anything. He says, Me neither. He goes, No one's coming out of here. And I said, No, no, no. There's gotta be someone coming out of here. I mean, there's thousands of people in here, and they're coming out. He says, Brother, we would hear them calling for help. They're gone. And I still at that point thought there was a chance. And after about the fourth day, they just said, This is a recovery now. There's no more life. There's no more chance. And on that first night, we went full tilt till my crew, my specific crew of 12, 15 guys. And four in the morning, we just couldn't breathe anymore. We couldn't see. We were caked just with... It was like if you took flour and just kept dousing yourself. And the lieutenant just said, Look, guys, we're gonna go back. We're gonna get some medical aid, and then we'll come back in a few hours. And we took a city bus back through the battery tunnel. And unbeknownst to us, that morning, this off-duty firefighter, Steven Siller from Squad Company One, he raced down there with his pickup. And he couldn't go any further because the traffic was stopped up because they had a report of a bomb. So everything was held up. And he grabbed his fire gear and he put it on, stuff weighs about 60 pounds, and he ran through the tunnel. Two and a half miles, got to the end of the tunnel, fire truck was coming in from the other way. He hopped on the back, got him up to West Street, jumped off, tried to look for his company, where they were. And he was never seen again. He just ran through the tunnel. Ran through the tunnel. And he got there to help his team. It's all about the team, it's all about the guy right next to you. And he's the Tunnel to Towers Foundation, Steven. His brother, Frank, decided in his name, in perpetuity, he's got a fund that now builds a home for every Gold Star family, for every seriously battle-wounded warrior, for every seriously wounded first responder, or killed in a light and duty first responder. If they had a home, they're paid a mortgage. If they didn't have a home, they give them a home. And especially if it's a severely battle-wounded, they give them a smart home because these poor guys come home with no limbs. And so the beauty of Steven and his selfless act was that he's now helped thousands and thousands of people. I mean, Tunnel to Towers is incredible. That's part of our mission, is to bring awareness to these great people at Tunnel to Towers, what they do. They've raised $250 million to help protect the protectors, to rescue the rescuers, in a what's become, unfortunately, a somewhat ungrateful society. But they will not forget these great guys. So you tell Steven's story, he's one of the 20 people that you talk about in the new Iron Labs 20 for 20 podcast series. If you could just linger on his story a little longer, what does that tell you about the human spirit? That this guy, you know, the Tunnel couldn't drive through, so he just puts on that heavy pack and runs. What do you make of that? That shows the depth of a man's soul. He didn't have to do that. He could have turned around and went home to his family and nobody would have shamed him. But he's one of those beautiful, brave people that take a job that really doesn't pay a lot of money and you become a cop or a firefighter or a nurse or an EMT or a medic or soldier or marine or airman, sailor. When you take these jobs, you don't do it for fanfare. You definitely don't do it for money. I mean, those 13 brave souls we lost a week or two ago in Afghanistan, they're brand new soldiers and marines. They make $22,000 an hour, but they don't work 40 hours a week. They work 80, they work 90 hours a week. So they make it about six bucks an hour. And you know what? They sign up. And firefighters and cops and medics and EMTs, nurses, emergency room doctors, they don't really make a lot of money. I mean, they're starting salary right now for a New York cop. I was a New York cop for two years first. I made $12.25 an hour back in 1989 to get shot at during the crack wars. If you made $11 an hour with a family of four, you were entitled to welfare back then. So I was just above the welfare level, risking my life. And these are the guys that are getting ripped up now. And look, I won't get into any politics, but that says something about someone's soul, that they're willing to take a job like that and now get zero respect. So a guy like Steven, what that shows is the depth of that man's soul, and courage, and determination. It's hard to be selfless in this world anymore, but I still know a lot of selfless people that just put on equipment every day, bulletproof vests, fire bunker gear, stethoscopes, flak jackets, military helmets. And they go in and they do it smiling. That young Marine that passed last week, she was photographed and quoted as saying, I have my dream job, as she was holding a little Afghani baby. And she was dead a few days later. She was so thrilled to be making $7 an hour helping people. Isn't that huge? That to me says, that's a true sign of character right there. And it's important for our society to elevate those people as heroes. Let me ask you about firefighting. What do you think it means to be a great firefighter and a great man, a great human being in a situation like you were in in 9-11? You know, that's kind of a broad term. You can go to different firehouses and they might have a different definition of what they consider a great firefighter. But I think in the industry as a whole, if you're willing to put everyone else before you, especially your team, you know, as we say, there ain't no I in team, right? It's T-E-I-M. There's no I in there. It's all about those guys and girls next to you. If you can do that, that makes you pretty great. You put everything else second and you just run in and you run in with that team for strangers. You know, I've had the honor of, I spent almost 25 years of my adult life serving humanity, my country, my former city. And the people I worked with were giants. And I don't mean that in height, I mean, but I mean that in spirit and in soul. I saw some of the most heroic selfless acts. And then I saw some of the behind the scenes that were so impressive. You know, we'd go to a fire around Christmas and a family would lose everything. And even when I was a cop, same thing, you come back either to the police precinct or the firehouse or the EMS station. And someone would put together a collection and say, hey guys, hey Lex, 50 bucks a man. You know, the Smiths down the street just lost everything. We're going to go get some presents for the kids and some turkeys. And not one of those guys questioned that. And they were making 12, 25 an hour and they still came up with 50 bucks for that family. But see, that's the stuff the press won't show you, right? They don't want to show that humanity, that soft edge. See, when you're a warrior, you need to have this rough shield, this rough exterior. Because if you don't, you die. But a true great firefighter or responder or a cop or military personnel, they have that rough exterior, but that soft underbelly, that heart, right? I see it. It's there. And that's to me the true great ones. Some of them, they just have a hard time doing that. There's no shame in showing your soft side. Well, you got your dad to say, I love you back. No, that's right. That was huge, man. That took me 22 years, Lex. So you were a firefighter for 21, almost 22 years. Why did you become a firefighter? Oh, my dad. I was five years old and I went to his firehouse and there was these, at the time, they looked like giants to me with mustaches and the trucks smelled like smoke and the gear smelled like smoke and the tires and the diesel fuel. And I was like, this is what I'm going to do. And then they bring you in the kitchen and they stuff you with ice cream and cake and then I go home to my mom shaking with a sugar cone and she's mad at my dad. But yeah, it was just, oh, I was like, I got to do this. It was like, they were like a baseball team in a garage with a truck and these big tools and big coats and helmets and they were just laughing and having fun and I'm like, yeah, man, I'm doing this. And I knew. I was obsessed with it. I mean, I was so pissed that the fireman's test came out when I was 14 and I couldn't take it. You had to be 18. And it was done, the test was graded and whatever. So my dad, now there's a copy circulating because it's old now. And he goes, yeah, yeah, this is what you're in for. And I took it and I did it like it was real and I got a 99. I was so pissed. I said, I want to get hired. He goes, you can't, you're 14. But I just wanted to do it so bad. And I just wanted to help people. I just wanted to be like my dad. He'd come home smiling, as tired as he was. And he fought fires in the 60s and 70s when the city was burning. And he's still as exhausted as he was, he'd still be smiling. I wanted to smile at work. And I used to, I got paid to laugh and joke. I got paid to cry sometimes, but man, we laughed a lot. We really, it was the chop breaking. It's just unending and it's great. If you don't mind, can you tell me, you were really kind enough to give me one of these shirts with 114. Can you tell me the story of 114, of Tally Ho? I wear proudly, I served eight years in that command and I didn't finish my career there. I passed the lieutenant's test. And once you do, you have to leave. The story behind Tally Ho is back in World War II, there was this gentleman named Bad Jack Carroll. And Jack was an airborne ranger. And my father-in-law was also on the department and he knew Jack. And Jack came home, Jack jumped Normandy and stormed up through the Battle of the Bulge in Bastogne. And he came back, greatest generation as they all did. And they got jobs. They went right to work and they were treated better back then, vets. And he got on the New York City Fire Department and he got assigned a lot of 114. And they first got radios back then. And when Jack, he would drive the truck. You're up there with the officer, either lieutenant or captain. So the boss is off the truck, you operate the radio for them as the driver. So when they call them and they'd say, a lot of 114, respond in the 52nd Street, 3rd Avenue structure fire. You're supposed to get back and say, a lot of 114, 10-4. But he refused to do that. He'd say, a lot of 114, Tally Ho. Because that's what they'd yell when they jump out the plane. So all these years later, it's stuck. And it's a little bit of a bragging right. But out of 350 engine and truck companies in the whole New York City Fire Department, we're pretty much the only one that's called by their nickname on the radio, not their number. So it tweaks some guys off in other places. They may, hey, F you, Tally Ho. But it's just, yeah, it's a great, great heritage and we're really proud. And Shamrock was, he was Irish and a lot of the guys back then were Irish immigrants from the area, from the neighborhood. And they would actually take the fire truck to church on Sunday and park out front. And one guy would stay in it to hear the radio in case they got a call. So, yeah, that's the proud history. And you said that if I wear this around New York, I might get in a little bit of- You might get a guy from the Bronx, go ahead, Tally Ho, screw you. But I mean, it's all that good rivalry. We like to kid each other back and forth. Guys from Manhattan will say, yeah, you guys in Brooklyn, yeah, short buildings, tall stories. And we're like, yeah, but you guys in Manhattan, tall buildings, no stories. It's all that jocular ball breaking. It's good stuff. Let me ask, I guess, a difficult question. If we just step back in the events of 9-11, on the side of the people that flew into the towers, what do you take away from that day about human nature, about good and evil? How did that change your view of the world? I witnessed evil firsthand. I remember later on, well into that night when we were trying to help get those police officers out, I remember looking up at the building, Century 21, the store runs along the east side of the towers and it was still there. The debris had come down right almost to the edge. Century 21 is this old storied department store in New York City. And the sign was there and it was still lit up. Some of the neon was broken, but I think some of it was actually still lit up. And I just looked around and I was like, this is a war zone. We're at war. And we knew we were attacked. We heard the fighter planes. And back then it wasn't the extensive communication network. And we had cell phones, but they were the old school flip phones and there was no news on them. And so, plus we didn't have a signal down there anyway. I couldn't reach my family for 12, 13 hours. And then my dad had deployed down to the ferry terminal to retrieve bodies. He was retired, but he still went. And they deployed him to go be basically the morgue transport guys. They expected to be sending hundreds and thousands of bodies across on the ferry. And they set up these tractor trailers as a mobile morgue. And that never happened because there were no bodies to take. They were all buried. So, it's so evil firsthand. I don't know how someone can inflict such revenge or a vengeful act in the name of anything, in the name of a religion, in the name of a cause, in the name... Like what the hell? Were you ever able to make sense of that? Why men are able to commit such acts of terror in the days and the years after? No, Lex, I haven't. My mom's from Ireland and I still have a lot of family there. And my great uncles, one of them was dragged out and shot. He lived, but just based on a rumor that he was in the IRA. And I wasn't happy to see what happened to my mom's people because they were victimized and brutalized by England at that time. But blowing up bombs and killing innocents in the name of that, it doesn't make it right. I couldn't justify something like that. I can see, you know, I was a cop, I was a soldier and you never want to take life in those jobs, but sometimes you have to. But you don't do it with a vengeance. You don't do it with a thirst. You do it because it's necessary for survival. When you do it out of a bloodlust, out of a thirst, out of a cause, that's evil. There's something wrong with you. I have no... I respect life to the highest level. I mean, I'm very... Life is sacred to me. It's precious. It's beyond... It's not a commodity. It's a gift. But to take life just so randomly, so there's something way wrong with that person. And maybe I'm a conflicted soul, but I would have no problem seeing someone like that put to death because they do not deserve life. There's many children around this world that are being taught to hate someone who's different than them just because the person who's allegedly teaching them says so. I don't understand it. Well, that starts with just having a basic respect and appreciation of other human beings. And that starts with empathy. So, yes. And one of the reasons I love this country, while joking that I'm Russian, and maybe you could say the same as you being Irish, you're actually truly an American. And that's why I consider myself very much an American. And one of the reasons I love this country is it serves as a beacon. I still believe it serves as a beacon of hope and that empathy and love for the rest of the world that hate is not gonna get you far, that love will get you a lot farther. And I still think sometimes it's easy to see the press, mainstream media, you could see social networks, because you can make so much money on division, sometimes because it makes so much money, it's easy to think we're really divided. I honestly don't think we are. It's just like the very surface level thing that we see on Twitter and so on. It's that you're 100% right. There's people out there that are maximizing off this whole division. They want us divided. They want people angry because it sells. A lot of these people that are in charge of certain organizations, well, they all seem to have nice cars and nice houses and nice vacations. And they're constantly trying to convince everybody that we hate each other. Yeah. To me, I'll use a fireman analogy, right? It's like a little campfire. And if you just let the embers flutter, they'll go out. But if you take a little cup of gasoline with those embers, it'll blow right up in your face. And that's what a lot of these politicians and a lot of these media folks are doing, because there's something in it for them. And I think it's possible to defeat them with great leaders, with great spokespeople, with great human beings having a voice. One of the powerful things of the internet is more and more people have a voice. And I ultimately believe, certainly in America, but in the world, the good people outnumber the assholes. Oh, I agree. And there's days when I think the assholes are overrunning us. But you know what? I think what the downfall of the world is, is ego and arrogance and people that think they're better than that other guy. My parents raised me to be this way. My mom is such a sweet, gentle soul. She's an immigrant. She came here at 16 years old. She helps everybody but herself, right? She's just one of those people. She's sick. She's got Parkinson's. You'd never know it. And she's still flying around her condo complex helping everybody, because that's what she does. She loves to help people. But she's been in their shoes. She's been poor. She's sick. Her husband was sick. She's had all sorts of suffering and loss in her life. My granddad died when my mom was 10, and she was one of 10 children that survived out of 14. She knows hard times, but she so appreciates the good times and the goodness of this country. You know, the fire department and the police department, military, it taught me a lot about empathy and trying to really feel for someone and put yourself in their situation. I remember years back, I was a much younger fireman, probably five years on the job. And I was sent down to the next firehouse over to fill in. You know, we would get sent around randomly when they needed an extra guy. And someone came banging on the firehouse door. And in the tenement apartment next door, they said there was an older woman that was unconscious. So we dispatched ourselves, and we ran over with the medical kit. And it was an elderly woman laying there on the bed, on the bed. And she was obviously not breathing. She was obviously in cardiac arrest. And an older gentleman that was holding her hand, just inconsolably crying. And it turned out it was her husband, and they were married for 65 years. And normally, we would just respectfully ask the family members to just step aside and let us do our work. And I realized that he wouldn't leave her side. So I kind of gave the crew a wink, and they were doing CPR on what they had to. And I just let him keep holding her hand. And I said, sir, could you just come over just a little bit so we can work? And I held his hand as he held hers. And I said, sir, I said, do you have faith? And he did. And I said, would you like to pray with me for your wife? And he said, I would like to. So we said the Lord's Prayer. And I just asked God to protect her and bless her. And I think he realized that she didn't have a chance, but we still gave her that chance. And we got her in the ambulance. And maybe it was wrong to try to make it look like we could save her. But you can't really not try. But the one beautiful moment was he thanked me, and he was almost okay with it at that point. He wasn't as upset. He wasn't as distraught. Because I tried to just humanize that situation of what we were trying to do. We were trying to do our best, but we also tried to be compassionate to his sadness. And I walked away just feeling so good, even though it was a tragic situation and she did pass, that he came by to thank us days later. And just heartbreaking. But it just happens many, many times throughout the country every day. People get that opportunity as a responder to be that last bridge to the family and the loved one. And you only get that opportunity once sometimes. And you really have to... To me, it's like your moment to shine. You could just be very, very dismissive and very rude, or you could be compassionate and just show, hey, I have a mom, I have a grandma. And just in your mind, pretend that that's who you're working on and that's who you're with. So that moment of compassion, that moment of empathy, even if it's brief, can be the thing that saves the person from suffering, make the difference between suffering and overcoming in the face of tragedy. Yes. I felt that even though obviously his loss was still huge, it just made it a little more bearable and tried to just take his grief down to a lower level. And it made me feel, just feel really good about doing it. That's a powerful way to see the job of a first responder. Of course, you have to deal with certain aspects of the tragedy, but it's to provide somebody with that moment of compassion. Yeah. And I made it a little habit because sometimes with faith, it's a little bit of a tricky subject. So every time I had someone who died, which unfortunately was many, many times, I would just touch their hand and just say a little quick prayer and just say, look, I hope you're moving on to a better place. I hope if you did have faith that it's strong as you depart. And if you didn't have faith, I hope maybe at your last moment that you found some and you just found some closure. So that was just my little ritual. I think I just, I felt it was important that that person, even though they were a stranger, just had someone there just sort of hoping for the best for them in their last moments. You mentioned cancer. You had a rare leukemia due to all the work that you did at Ground Zero. Can you maybe talk to the experience of just breathing through those days and what that was like being unable to breathe, being overwhelmed by all of the dust in the air? Yes. The first day, especially, we didn't have equipment. We didn't have breathing apparatus. And then we were handed little 69 cent hardware store dust masks, those little thin paint masks that would just get sweated up and sticking to your face within 30 seconds. They were useless. And what you wound up feeling like was that you swallowed a box of razor blades because there was glass and there was cement and it was just so caustic. And I remember that night when we went back just to get some medical relief for the few hours, we were walking up the hill to the firehouse because they dropped us off like a block away down at Engine 201 and quarters. And one of the older firemen, as we're walking up the block, we're all struggling, we're all having a hard time breathing. I mean, I felt like I was dying, literally. It was pretty bad. And I just remember the one guy going, now we're all dead. And I said, no, no, we made it. We made it. He goes, no, you don't get it, kid. He said, we just breathed in poison after poison for hours. And then that went into days and then went into months. He says, we're all dead, man. This is going to take us all. And I thought he was crazy. And then now years later, like starting in 03, 04, guys just started coming down with these really rare and advanced cancers. And then it just stopped being a coincidence with the number of guys. And they were young. One of the first guys, John McNamara, he was 33 or 34 and he came down colon cancer and it took him quickly. He was in 2005. And I kind of said to friends and family, I said, I feel like I'm running through a minefield and I wonder when I'm going to step on my mine because everybody's going to get sick. And I wasn't feeling well from 2008 on. I couldn't put my finger on it, but I just wasn't right. And in 2011, I failed my medical. My bloods came back horrifically wrong and they pulled me off the truck, but they strung me out for a month. The doctors sniffed upon me and one of them said my spleen was engorged because there was probably drinking myself to death. Like as he said, most of the guys did after 9-11, which was pretty wrong of him and stereotypical, just to stereotype and to categorize. And guy couldn't have cared less. He just, he was so crude and nasty. And then my one doctor who was my doctor on the outside, my blood pressure was 240 over 140. My spleen was about to rupture. She didn't even show up for my appointment and I went down, I passed out. The paramedics responded. She got into an argument with a paramedic because for big ego and basically telling him there wasn't really anything wrong. And he's looking at my paperwork going, this guy's got leukemia. And he overrode her. He raced me out of there, down to Brooklyn Methodist. And the doctor, the charge physician, the ER physician, he says, you're not leaving. You're in a bad way. And I said, well, what is it? He said, I need a little while to figure it out. He goes, but you probably have one of a few different types of leukemia. He said, I'll drill into your hip, take your marrow and find out. And he said, but in the meantime, we'll get the swelling on the spleen down, I guess some sort of rapid medicines and whatnot, because my spleen was about to rupture. I had no blood platelets left, which is your clotter. So I basically would have bled to death. And I found out from my team of doctors that I had about 48 hours to live. And that really set me off. I was infuriated because I was telling him for a long time that I was sick. And- The doctors failed you. The few doctors in the beginning failed you. I felt very betrayed. And other guys had died. And I had it out with that one doctor. I basically told her she was fired from my case. And she's a pretty politically in charge person, and I didn't care. I jeopardized my job for it because it was my life. And I got the sense that she didn't really, it didn't really matter to her. She didn't have any empathy, as you say. It was exact. So why for her? Why for a few others? Was there not a special care, a special compassion for, first of all, humans, but human beings in your position, especially a firefighter, a first responder? You know, Alex, I think what it is in the department, their title is just to get us back to duty as quickly as possible when we are either injured or sick. Because what happens then is your replacement is now in overtime. So you're out being paid on medical leave, but then they need to replace your spot, and then that costs more money. So I think it just behooves them to get as many personnel back. And especially during the summertime, they look at it like, oh, maybe you want a few extra days off to go to the beach. And this one doctor, he tipped his hand back as if I was drinking an alcohol beverage. He says, hey, busy summer? Because I asked him to look at my spleen, which was sticking out of my abdomen like a football. And I said, excuse me, sir. I said, how dare you assume that I'm abusing alcohol? Because alcohol abuse sometimes will present itself as the spleen is engorged and having an issue. So you automatically just assume that that was my situation. Wouldn't even give me an exam. And I was horrified. I was so angry. I mean, I wanted to punch this guy out. And I literally was screaming at him. And an executive officer came in to diffuse it and sent me to another doctor. And when I showed her my paperwork, she was horrified. She was like, what did he say? And she said, oh, okay, go to your regular doctor tomorrow, who was one of the department doctors. And it was just an indifference. It was like, I don't know. I was shocked at the lack of compassion. But you know what? That being said, I'm past it. Life moves on. The team of doctors, I ended up with a Methodist and my subsequent oncologist, Dr. Peter Mencel, world-class, just incredible human being. My Dr. Pete is just, I love him. I love him like a friend, like a big brother, like a father, like my primary oncology care nurse, Mike Nunez, was just incredible human being. And he knew I was frightened because I had to get two and a half years of chemo compressed into seven days or I was dead. These massive bags of chemo that never stopped. And the minute they went into your body, you felt like you were burning to death from the inside out. And when Mike came in to hook me up, he said, look, I have to wear a hazmat suit. This stuff is so caustic that if it drips, it'll burn whenever it touches. And I was like, but Mike, you're going to put that in my body. How the hell is it not going to kill me? He says, no, no, this is exactly what it's supposed to do. Trust me. So when he prepped the IV tube to get it flowing, it spilled onto the tube and the tube started to smoke and burn. And I said, no effing way, Mike, you're not putting that in me. No way, no way. And he goes, listen, let me get another one. Let me start it over. And here he is wearing a hazmat suit looking at me. And I'm going, this is insane. And he goes, he looked at me, he took my hand and he says, Nels, if you don't take it, you're dead. He says, you got those three kids. I'm sorry, I have no other option. You're dead. And I said, all right, Mike. Okay. And he hooked me up. And you know what? It was like, if you do drink alcohol and you have like a shot or want strong type spirit and you start feeling that burn. Well, the minute he hit me in the vein, it just started going up my arm, burning, and then up my shoulder, across my neck, into my head, across the rest of my body, within a minute down to my feet. And I was writhing in pain for seven days. And I was praying to die. I was the seventh rescuer in six months to come down with the rarest leukemia there is. There's only 500 cases in all North America a year. And seven of us came down in six months. Two guys died during treatment. Seven responders, police, fire. Two guys died in the first couple of days of the treatment because it's so vicious, your liver, your heart, your kidneys, something will fail. And I was praying and I was praying, and I was praying, but I wanted to die. I was in so much pain. And I wouldn't take a painkiller because I know people with some issues and I just didn't want to go there. And finally, on the last day I gave in, I said, please, I can't do this anymore. I was literally like jumping out of my skin and they gave me something. But it had burned out my mind, it burned out my body. I couldn't hear, I could barely see. It was vicious, but it worked. And my nurses, especially, they just, they were so dedicated and devoted. And I was not an easy patient because I was in a lot of pain. It was bad. And it drove my friends, my family crazy. It was just, it wasn't good. But on that first night, I had a quick vision of all these people that I loved that were dead, that died. A lot of them in the trade center. And I saw Johnny, I saw friends I grew up with. The last one was my mother-in-law who had passed six months before and she died of, she was in a coma, she had a stroke. She had a horrible, horrible last six months of life. And it wasn't fair because she was so religious. She went to church every day, devout Catholic woman. And all of a sudden I see her and she's smiling. And we used to talk a lot. We used to talk a lot. It's the Irish thing, like the gab, the gift of gab. And she used to call me her boyfriend because we'd sit and talk for hours and talk about books and about movies and about food. And I loved her. She was my friend. And she'd say, my boyfriend's here. And all of a sudden she's smiling and she goes, hi, my boyfriend. And I says, dad, no, no, what are you doing? She goes, he's not ready. He doesn't want you. You got to go back. You got things to do. And I'm like, no, no, no, it hurts so much. Please, please take me. And she left. She goes, no, no, not yet. I'll see you. And she just faded away. And one of my doctors on my team, she had a problem with religion. And that's okay. I understand that. I'm not a preacher. I have a faith, but I don't preach it. I don't push it. I just live and let live. So she sent in this shrink to see me. And I was messed up from the chemo, but I knew what I was seeing. I knew what I was saying. And he was a Jewish gentleman. He was a rabbi also in a synagogue. And I actually had responded in that district. And he knew 114 would run into Borough Park. Oh yeah, I see Tally Ho, they come down the street. And he asked me to tell him the story. And I did. And he started laughing and he scared me now. I says, doc, am I really crazy? He says, no, no. He said, I believe you, my friend. He said, we share the same God. He goes, we work in the same corporation, but in different departments. And he says, you did see your mother-in-law. He says, your faith is that strong. He said, I've had many patients express the same sentiments. He said, so I want you to listen to her and fight and be strong. And he said, so what else do you want to talk about? I says, well, I don't know, doc, am I that messed up? He goes, no, no. He goes, they're paying me for an hour. It only took 20 minutes. So we watched the Yankee game together. But it was just, again, it showed the human condition. Here's these two men of two totally different faiths. And yet we shared that bond of faith. And he had empathy and he had sympathy. And he saw me in many other patients. So he just didn't assume. And he gave me a fair shake. And I will always be grateful to him for that. Through any of this, the pain you had to go through with the leukemia, but also the days of 9-11 and after, did your faith get challenged? You know, Lex, it was strange. There was times I was so angry. There's that range of emotions, the anger, the denial, the depression, the this, the that. And this is the weirdest thing. It was mostly, I knew my career was over. And they retired me out of the job. I got sick in August and that October, they told me I was out. And by the time I was processed and used up my leaves and whatever you want to say it was, I was officially retired in January of 02. And it was less than six months. And I'm there walking my dog one day, my rescue greyhound who I miss. She was such a soul, God, she lived to be almost 13, Katie. And we're walking in the snow and I got the call, I was retired. And I looked at her and I'm like, Katie, what am I going to do? And she just looked up and said, we're going to go on a lot more walks. And I was so sad. And I was so sad and so angry because I lost my priesthood. I loved helping people. I really, Lex, I would have done it for free. I would never tell Mayor Bloomberg that, right? He's all about the book, right? But like, honestly, I would have been a New York City fireman. I would have paid them to do it. And I wasn't allowed anymore. That's it. You have over 20 years and you have cancer. Back when my dad got sick, they'd let you hang around for 10, 12 years in an office, but not now. Now it's all about the bottom line. But I was more depressed about losing a job than almost losing my life, as crazy as that sounds. And it just- It's more than a job. I mean, it's a way of life. It's also is your family, your father, you're carrying torture, your father's- Oh, my friend. I love my friends. I love... We work 24 hour shifts together. You cook, you clean, you break each other's jobs relentlessly. I mean, I love those guys so much. I mean, I hope that my kids and anyone that I know and care about, I hope they can experience the bond of that brotherhood that I experienced in my life. It was so... God, I would give anything to have it back. Just, yeah. Can I ask you about New York? So when I've... Unfortunately, I've never lived in New York. I visit. I've always wanted to live there for a bit. Obviously, it's a very different experience to have really lived in New York for many, many years. But there's a few friends of mine that are from... They got similar accent as yours. Yeah. That are a little bit saddened, perhaps it's temporary, but perhaps not. They don't seem to think so of what New York has become, especially with COVID. It's losing some of the spirit of New York. Do you have that sense? Do you have a hope for the city that has been so defining to what is America? My heart's broken. I had moved to New Jersey many years ago, but I still have a close attachment to New York. My parents are still there, many, many family members. And I've since now moved to Tennessee. I needed to go somewhere quiet. I wanted to heal my fractured soul. And I'm in the middle of a beautiful farming rural area in middle Tennessee. And so they probably call me a sellout back in New York for leaving, but it's not the same city and it's sad. I'll refrain from the politics and the finger pointing, but it's a mess compared to what it was. And I did Broadway theater security for many years and I started to see it slide with stuff that was happening, like public urination and defecation and just like, you know, tourists don't want to see that. And I had an unfortunate incident two years ago. I was jumped by four teenagers coming off the subway and they were pissed off because I was wearing an American flag hat. And I don't know, I'm not really sure why, but it left me... I got out of it, okay. But I was taken back. They were literally videoing it and the kid was just throwing shadow punches at my face wanting to beat me up. And I finally looked him in the eyes and I was like, oh boy, I'm a little too old for this. And body's a little broken down for chemo. And I finally just said, all right, all right. I just had enough. I wanted to go home. I just worked a 17 hour shift as a stagehand. And I was so taken back. I was so insulted. I'm saying, you know, I spent my life protecting this city and now I'm getting attacked like for nothing. And I just, I gave up and maybe I should have given it a little more time, but it's, I don't know, it's turned into an angry place. It's turned into... I think there's a lot of people that aren't getting the resources they need in a sense. There's a lot of mental illness. There's a lot of homelessness. There's a lot of violent people just roaming around the streets and it's not good. It's not safe. And tourists are not going to come back. Even just leading up to the COVID, I had some tourists saying to me, I won't be back. And now I can only imagine that it's just gotten exponentially worse, but I hope there's a chance it'll swing back because it is, it's the gateway to the world. I mean, my grandfather came from Denmark. He landed in Ellis Island in the twenties. American success story, 25 bucks in his pocket, didn't speak the language, had a sponsor family in Bay Ridge, Brooklyn, and he made it. He ended up dying, owning a bakery at one point and then an apartment building. And he did pretty well for himself for an immigrant who was poor. And my mom, my Irish mother landed in the same neighborhood, Bay Ridge, Brooklyn, 16 years old, worked as a cashier 50, 60 hours a week in a supermarket and finished school at night, married my father, the fireman, and lived the American dream. And it was all from New York. And my father's mom was from Irish immigrants and they all landed in Ellis Island. Well, my mom didn't because it was closed at that point, but there's people breaking down the doors to come to this country. There's no one breaking down the doors to leave. And this is a problem I have with people that aren't grateful for being here. And this, again, it's not political, just straight down the middle fastball. If you don't like it here, I'll show you the door. I'll get you the plane ticket. I mean, would you want to live back in Russia compared to here? You might because of family ties, but I mean, if you had no ties to Russia, or would you want to go to China right now and possibly end up in a labor camp? There's people busting down the doors to get to this place. It's not perfect. It's got its flaws. It's got its blemishes, but it's a damn great place. It's the best country in the world. Yeah. And some of it, so first of all, I have hope for New York. I think that culture is very difficult to kill. I think it will persevere. And I think ultimately the same story with New York as with the rest of the United States, it has to do with leaders. And I'm always hopeful that great leaders will emerge. I agree. And the kind of leadership we see now and the kind of conversations we have now, I think has to do with prosperity and comfort. And in the face of hardship, I think great leaders will emerge. And I just think ultimately in the long arc of history, New York will show. Leaders shouldn't become rich. They shouldn't become rich in the process, right? You shouldn't go into political office as an alleged lunchbox kind of guy and then come out eating at the best steakhouse in the world. I mean, that's the problem with politics, right? My Irish grandmother, God rest her, used to say, those politicians, they're all like dirty diapers. They're full of shit and they stink. And it's true. I don't give a crap what party they're in. Yeah. Greed and power. We had to beg these guys, beg them for federal legislation to cover our medical bills, right? There's a gentleman, John Feal from the Feel Good Foundation. This guy is a lion of a man, a general, but with a soft, big, great heart. And John is a former construction worker who came to the 9-11 site the day after. He was one of those guys cutting the steel with torches and craning it out of there. One of those hard hats that just, that never got the credit and the praise that we did as responders. And I don't mean that as a knock to responders, right? I mean, we lost 37 Port Authority police officers, 23 NYPD officers, about a dozen emergency medical technicians and paramedics, three court officers from New York State courts and two federal agents and 343 New York City firefighters. We lost a ton of responders. But the recovery workers, recovery workers, thankfully weren't killed in that process, but there's hundreds of them now who are dead from illnesses because they came down to recover our people and the civilians and the poor lost souls that were killed at work that day. And John literally almost lost his foot in a construction accident at the site. An 8,000 pound I-beam tore off half of his foot, ended up with massive sepsis, six months in the hospital, hundreds of thousand dollars in medical bills, and then no one wanted to pay him. So here's a guy who's going to lose his house, lose his life, lose everything. And now the never forget, it started quick, right? And he went on a mission, formed his Feel Good Foundation. His last name is Feel, F-E-A-L, Feel Good Foundation. And this man literally went to Washington, DC with his army, as he called it. And I was honored and blessed to be with him only a couple of times. I wish I had dedicated some more time to it. And what it was with John is he set out on a mission to get, and initially what he did is he got funding to take care of responders who were in that limbo, who couldn't get their medical bills paid, who couldn't make their mortgages, who couldn't make their car payments, who couldn't make their childcare payments. And John just took it upon his own to get donations and take care of you while you were suffering, right? I got a call when I got out of the hospital. You okay? You need anything? I said, who is this? It's John Feel. I said, aren't you that constructor? Yeah. You need anything? I'm pretty good right now. I said, I appreciate it. Phone ring again a few weeks later. Hey, John Feel, you need anything? I'm like, this guy's incredible. But there's people who needed stuff and he was getting it done. Yeah. And he, with his army, had to chase these politicians through the halls of Congress to get funding to cover the medical bills. I was getting sued for $125,000 for my month stay in the cancer ward. And I couldn't believe it. I said, well, wait a minute, I have insurance. They're like, oh no, no, this is terrorism related. We don't cover that. So usually then workers comp will cover your on-duty injury or illness. Oh no, no, no. Leukemia is not covered under that. We don't cover that. So then the ping pong game starts and I'm literally have people showing up taking pictures of my kids in front of the house. And I went and grabbed the guy one day by the collar. I said, who the hell are you? Sir, I'm a private investigator. We're putting a lien on this property due to a non-payment of a bill. I said, okay, I understand. Do your job. Let me bring my kids inside. Take all the pictures you want. Don't step on my front lawn. And I went in the house. I closed my room, my door, my door in my room. And I cried. I said, I can't believe this. I spent my entire adult life trying to help people, give of myself. And I can't even get my medical bill paid. Well, John Field got my medical bill paid. He finally got these politicians with his team, firefighter Ray Pfeiffer, who has since died, fought with terminal cancer for nine years in a wheelchair. Literally at the end, came out of hospice to go finalize getting us this coverage. Detective Luis Alvarez, who testified days before he died in front of Congress. And a bunch of other guys that were really, really sick. And we had to shame these people into signing on. And luckily we had Jon Stewart come on and literally just hound these guys and shame them and embarrass them. And what it all stemmed from was in 2006, the first death that was determined to be linked to 9-11, there was others, but the first one that was officially linked was a New York City police detective who initially, the city said he died of advanced lung disease. His lungs were protruding out of his body and he was on painkillers. And it was so bad at the end that the doctor said, just grind them up, snort them, drink it, whatever you need to do to get instant relief. So when they found the talcum from the pill lining in his lungs, they said, oh no, this is opiate abuse. He didn't die of lung disease. So they said, and the mayor was quoted as saying, he is not a hero. Well, shame on you, Mr. Mayor. He was a hero. And his father, who was a retired police chief, married up with the Feel Good Foundation and Jon Stewart and Ray Pfeiffer, detective Alvarez. And they got us all covered, but it took so long. Lexi, it was so heartbreaking. These people who were lining up three deep, politicians, three deep to catch a picture with a responder so they can tweet, hashtag never forget and hashtag look at me and hey, how am I doing? All that bull crap. But they didn't know. They were nowhere to be freaking found. I literally witnessed them hiding in cloak rooms, running down hallways away from us, those freaking cowards. That's cowardice. Can I just linger on the Jon Stewart thing, the comedian, actor Jon Stewart, his testimony before Congress over the benefits for 9-11 first responders. I mean, there's a lot of important human beings in this story, but he has a big voice. And he spoke from the heart. What do you make of that testimony? Oh, it was heartfelt. I mean, he spoke, look, I mean, Jon was a polarizing guy, right? There's certain things like over the years he was cutting edge and I might not have agreed with all of his, you know, well, you know, some stuff, some not, right? You know, like we all, but I tell you, I found him as funny. I enjoyed his humor. I would love the two of you to have a conversation. No, but again, I love a guy where you can have a difference in opinions. That's the beautiful thing about the firehouse kitchen. I mean, it could get raucous and now I don't know, it's a little different situation, but I mean, back in the day, some funny stuff. But yeah, Jon literally just took his talents. You would think he was speaking from the heart of a fireman or a cop or a soldier or a Marine or, you know, someone who was there. But I think he especially got to know Ray so well. And Ray had this stack of mass cards from, you know, the funeral cards they give out. It looks like, you know, a larger business card that's laminated. And Ray had a stack of them he would carry around. I think it was close to a hundred cards. And Jon saw it and he said, what's that? He says, these are my cards. He said, for what? He says, for my brother's funerals. He was like, oh my God, you've been to that many funerals? He goes, yeah, this is just the ones I made. And Jon, I think was just stunned. And Jon actually had that stack of cards after Ray passed and said, look at these, there's going to be more of these cards. We have one guy a week or girl, one responder or recovery worker or someone who actually resided down there. There's more than one a week dying. It's one a day dying on average. And on average, two people are diagnosed with a 9-11 cancer or disease. Right now, the worst part is there's autoimmune diseases flying off the graph and they're not covered under the legislation. By the grace of God, my cancer is covered. If my cancer comes back, I mean, I'm in remission, it's technically incurable, but I've been blessed. I'm staying ahead of this stuff going on 10 years. But if it comes back with a vengeance tomorrow and takes me, at least my wife will get my pension and be able to live her life without fear. But my friends who are suffering from these advanced autoimmunes, their wives get nothing. Their pension dies with them. And we're hoping that Jon and his army can shame these politicians once again to have the kindness and decency to cover these autoimmunes. They're throwing a lot of money around at a lot of things lately, and this is one that they won't. And these are lives in the balance who really need it. And Jon had this strong line, they did their jobs, do yours, talking to the politicians. Yeah. And it's a strong wake-up call that it's not about the Twitter or the social media or all that kind of stuff. You have a job to do. And you have to, it's that compassion implemented in the form of money, of helping people that were there for you when you needed help. Well, we had a guy, I mean, I might get audited out of this one, I hope not. But we had a congressman from out west, I won't say where, but he prided himself on saying he was a retired cop. Busy cop, 22 years. He said no on the legislation. I witnessed a cop who was dying get out of his wheelchair and said, hey, brother, I got a half a million dollars in medical bills, and I'm a short timer. I got a few months to live. Who the F is going to pay him? Do the right thing. You say you're a cop, you show me you're a cop, and you sign that paper. And the guy started tearing up, the congressman, and he signed it. But he had to be freaking shamed. And you know what he said? Well, this doesn't really confront me. This is pork as far as my district's concerned. He goes, oh yeah? Do you know there's 10 guys from your district who came across the country to help us that are also dying? He had no idea. He had no idea. And that's the sad part about it, Alex. It's a failure in leadership. I think some people would vote for Mickey Mouse, just because if he ran. I mean, no offense against Mickey Mouse. I like him. He's a good guy. Allegedly. Allegedly, supposedly. We don't know. Yeah. But seriously, I look at some of the leadership sometimes and go, we're in trouble. And also you lose, I think the way government is structured is people who are senators or people who are in Congress, they start playing a game between each other and they lose track of the connection to the people, to basic humanity. So you forget, even when you think of yourself as a cop, you forget what are the cops and the other people servicing the community actually experiencing all the troubles they're going through and how they can actually be helped because you lose touch with that because you're not actually living, you're not talking to them, you're not living among them. And I mean, that's a natural part of the system, but I think that's why character and great leadership is important is you say, you leave the game of Congress and you go back to the people. I mean, that's what the country, it's like the George Washington ideal is you're not playing the game of power. You ultimately see yourself as somebody who's servicing this country, servicing the community. And that requires talking to the people in their time of hardship. Well, you have some people, some people serving in congressional districts don't even live in that district. I mean, so how are they going to empathize? They're not even driving through there on a daily basis. And again, when anything becomes lucrative from a financial standpoint, it blurries people's vision. You have to take the potential of becoming rich out of politics. Politics is public service. Police and fire and EMS are public service, but cops and firemen and medics don't walk out of their career with gazillion dollar contracts with this company and that company on that board of directors and this board of directors. They walk out with a pension and that's it. And you have to wonder the intentions of people getting into politics. Are they truly going into to help the human condition or are they trying to help their own damn condition with their wallet and their pocketbook? And I try to lean toward the latter lately with what I'm seeing out there. Well, some of them are the good ones and that's our job as a society is to elevate the good ones. That's it. And that has to do with the ideals that we elevate. There are a number of conspiracy theories around the events of 9-11. Do any of these hold true to you or do they just frustrate you, even anger you? I've been asked this by a few different people in my life. This is my take on it, right? You're a man of science and a man of education. So you- Allegedly. Allegedly, but yes. But you're a very, very intelligent man. And what I believe took place is this. Structural steel will fail at a sustained temperature of 1500 degrees Fahrenheit. And I don't know exactly how long that would have to be sustained, but that's the temp, right? Diesel fuel, kerosene fuel, kerosene-based jet fuel, which was the ignition there, burns at 2200 degrees Fahrenheit. So that continued burning of that diesel, that jet fuel, but kerosene-based, it's all kind of similar, exceeded the temperature needed for that steel in the structural members of the trade center to fail. In my heart of hearts, I would hate to ever think that somebody affiliated with our government, with some sort of agenda, would perpetrate that crime and that tragic just destruction of humanity and property for some other form of gain. Those planes rammed into those buildings at 450 miles an hour. They were loaded with thousands and thousands of gallons of jet fuel. Number seven trade center had the backup for the emergency management system for the city. And it was an emergency generator in that complex, which had a 25,000 gallon tank of diesel fuel to continually run for weeks to keep the 911 system, the backup system going in the case of a catastrophic event. Well, that tank in seven heated up from the fire that was already going on, from the aircraft debris coming into the building. So once that diesel became ignited in seven, now you had enough temperature to fail that steel in that building. So I would like to truly believe what I've learned from the minimal fire science knowledge I have from my career, that it was just a matter of it burned too long, it burned too hot, and it failed. I mean, if you look at the way it came down, it came down as it was designed to, in the God forbid event that it was to collapse. It came down pancaking upon itself. If it had failed horizontally and just sprayed out side to side, those buildings would have dropped for a quarter, half a mile up to Canal Street. But you know, Lex- The fire and the destruction that could have resulted from that is- Yeah. Oh my gosh, it could have been so much worse. I mean, you would have taken out every building from that point all the way up. But in my heart, I'd like to just believe that it was just a fire that burned too long and too hot. These planes cause structural damage upon impact in both buildings, and it was just a matter of time. And then you think about it, you add all the plastics, all the carpeting, all of the stuff that was burning on those floors, you add that to that fire load. I think it just had enough to collapse it. And you were in building seven for part of that day. I was just after it came down as well. We were aside it, and we weren't in it or next to it when it actually did come down. But moments after we were there, and again, I would like to believe that it was just that that fuel was going, and physics took its course, and it failed. So physics and science aside, it's hard. It's both I would like to believe, and it's hard to imagine that anybody would be so evil as to orchestrate parts of this from within the United States government. That's very difficult for me to imagine. You know what, though, Lex? There's people, and I won't elaborate, I won't get into it, any controversial subjects or what have you. There's some people that don't have any problem at all perpetrating any level of evil. People like you and I who have hearts and we have depth of soul, we couldn't imagine it. But there's other people, wouldn't even be a second thought. I mean, I've seen some horrific incidents in my career that I go home shaking my head at night going, human beings are just, they're not wired right. I mean, I look at animals, I love animals, I love dogs especially. And I see this dog park when I train to fly airplanes now, and something I wanted to do. And there's a dog park across from the airport, and there's 60 dogs, and there's bones flying up in the air, and chew toys, and sticks, and they're running around having a time of their life. And they're all getting along, and they're not hurting each other, they're not violating each other, they're not canceling each other. And I'm going, we really need to learn from these dogs. And I just, yeah, I mean, sometimes it sounds crazy, but I think they're a better species than people. Unless they're rabid, they don't hurt on purpose, they don't cut you off in traffic and throw you the middle finger. They just don't do these acts of humanity that sometimes are so vicious. Why do you think these conspiracy theories, of which there's a lot, take hold? Why do you think so many people believe some version of different conspiracy theories around 9-11? Well, you know, like many, many things in life, it leaves me a little conflicted. I have to say this, I am at the point now, I don't know who to believe anymore. So I could see that not lending a hand to someone who's already a doubter going, oh yeah, look, exactly, that's what they're doing. I mean, look at this whole virus, who do you believe? Where did it come from? And if you plant that seed, it's like that little campfire we were talking about earlier, you just toss a little gas into those embers, you got a fire now. I also think there's a lot of people with a hell of a lot of extra time on their hands, right? And they're really bored. And the two are combined. Alex, yeah, man. Look, I was a three job Charlie, right? One guy used to say to me, anything but home. I go, no, I got deadlines, responsibilities. That's what it comes down to, I mean, look, we all have our hobbies and things we like and little nuances, and that's what makes us special, we're unique. Every person is a unique being. But I also think some people just, they wanna cling to something. We all wanna feel accepted and belong to something. So all of a sudden you group up with these people and you all believe this fervently, like, yeah, yeah, yeah, you know, they did it, they took it down, they took it down. And now you start going, yeah. And I think what happens is when you're in company of people and you start telling each other the same thing often, you freaking believe it. I mean, if you keep telling me I got a gray head of hair, I'm gonna go, you know what, I do. But no, I don't. I mean, right, I got that waving bye-bye do. But I think when you start hearing something often, you start believing it. But I'm not gonna doubt their intelligence, I'm not gonna doubt their intentions, but I just don't see it as being plausible. It would be too big of an operation to successfully happen. I mean, look, there's other things that, I won't say it on the interview there, but I have my doubts with certain things that... I mean, conspiracy theories take hold for a reason, because some of them are true. No, yeah. The hard thing is just to know which ones is the problem. When you don't have facts, right? Or you don't know who to trust. Sometimes when you don't have facts, when you don't have figures and you don't have science, it's hard to take someone's word on it. I had a conversation with someone a while back, right? And the guy's like a just dedicated atheist, and he thinks I'm an idiot for believing in God. And he's like, yo, you're one of those jerks who believe in creation. And I said, well, I do. Well, what about the Big Bang Theory? He's going on his diatribe about the science and the gases and the chemistry. And I'm going, dude, I barely got through high school chemistry, slow down. And he went on a tangent. And all of a sudden I stopped and went, who created the gas and the molecules and the stuff you're talking about and the collisions? And he was furious and stomped off. And I got him. And again, I had no facts. I had no figure. He didn't either, but I stumped him. But sometimes when you can't show some, people need to see something tangible. They need to see it in their hand to believe it. And that's the real hard thing about faith. I see it in action. People restore my faith. And then I say to myself, well, there can't be that many dummies in this world if there's so many billions of us believing in this higher power, this higher, right? And you said earlier, you believe most people are good. And I do too. The bad outshine the good because the bad get the press, right? If it bleeds, it leads. That's just, think about it. How many more damn zombie apocalypse movies can we make, right? I didn't even know there was that many zombies. And it just seems like every other show is just guys like bashing each other's heads in with bats with nails in it. And it's like, after a while, it's like, oh, gosh, you got to get a new boogeyman here, right? But seriously, like- But meanwhile, human civilization is getting better and better. We just like making Hollywood movies that just- We're getting better and better, but we're treating each other worse and worse. You would think with all this technology and all the knowledge and all the... It's like, what the hell is going on sometimes? I really want to see the good. And I think maybe the level of bad that we're seeing was always existing. It's just now everything is instantaneous news and flashes and tweets and this and this. Like, you know- Well, with the technology we have, it's also come to the light. So you get to see all these fights. I think that's step one of dealing with the problem is revealing it in its full, beautiful light. Oh, yeah. How much of a bickering species we are. 50 years ago, a guy like me who loves to talk, how the hell would I have gotten an opportunity to have someone listen to me and have, right? I love this. This is amazing. I think it's cool, but you didn't have that arena. You didn't have all these things. My grandfather Nels, God rest him, he died in 1979. I mean, that dude didn't even want to have a checking account. He would walk to each store, each the phone company, the gas company, this company, and pay the bill in person. He didn't trust the bank. And it was like, now, ATMs, this, that, he would be overwhelmed. He'd be just like... I mean, I love my dad, but to watch him on his iPad is comical, right? He calls my niece's boyfriend, who's a tech guy, Matt. If you listen, he's the greatest. He'll have this poor guy on the phone for hours. The second you walk in to see my kids, hey, do me a favor, straighten out this pad. And it's comical because I'm looking at my dad, I'm going, he was born when Hitler started World War II. Yeah, wow. And I'm going, he's seen all of that. Oh, my wife's grandmother was born in 1900 in Czechoslovakia, and she died in 1998. And I'm going, holy, the stuff she saw in the span of her life, it's just incredible. But what troubles me sometimes is with all of these advances and all these devices, this is what I say to my kids. Look up from the phone and look up, right? Because we don't talk anymore. I saw a girl, literally, I shouldn't say girl, guy, whatever. I saw a person literally just about walk into an open manhole cover texting. And I'm going, that's scary because your awareness is gone. And I've been at restaurants with groups of people, and they're texting. They're texting each other, they're sitting on the other side of the table. I'm like, put the freaking thing down and have a conversation. And that's the thing, we've lost the art of conversation. My wife, she has this running joke, she goes, oh, there's a lot going on up there. And I'm like, yeah, because I really, I'm inquisitive, I'm excited about life. I love to meet people, I love to learn. And the only way you can do that is to have a conversation. The hilarious thing about this, so you're obviously very charismatic, you got great stories, you're a great human being. And you're talking to a guy who spent most of his life behind a computer hiding from people. No, no, and I don't- But we're trying to bridge this. Right, but I don't mean that as a rip, but I would never know that. It's real. I would never know that because you're very engaging, you're very, I would not know, you don't have any impediments to your social skills, your personal. And that's, and again, I don't mean it as a knock to you and these young people. Well, no, but this is me trying to look up from a smartphone, is having these conversations, talking to people. I think it's important. I mean, some of it could be, it's always hard to know. Some of it could be just you and I being old school. Like, cause you grew up before the internet. Maybe there is joy and deep human connection to be discovered inside the smartphone. We don't know. It doesn't seem that way, but because the smartphone is so new, maybe we just haven't figured out those things. Cause there's a globalizing aspect. There's a opportunity for you to connect with people from across the world in ways that- Oh yeah. I have cousins in Ireland and England. I love it. I get a FaceTime or a WhatsApp and it's like, holy crap, they're three, 4,000 miles away and I'm having a conversation now. I used to send my grandma in Ireland a letter. I adored her. She passed when I was 10. And no, I'm sorry, I was 11. And I'd send her a letter, airmail, and I'd wait and wait. And about two weeks later, this airmail letter would come back and she called me Master Nils William George. I would be so excited, open up that letter. Handwritten, just like- Yeah. And then I'd write her another one and I just couldn't wait for letters from granny. And now it's like, that's kind of faded away. Yeah. I still write letters, by the way, handwritten. I do too. The way this all came about was I wrote a letter to someone to say, thank you for cancer research. I'm blessed to be alive. My cancer, right? That's a good starting point for any story. I'm blessed to be alive. And my cancer was one that if I got it 15 years prior to 19, excuse me, 2011, I was a dead man. 15, 20 years before there was no drug to treat, I was gone, going home to see him. So there's this wonderful gentleman that donated hundreds of millions of dollars to cancer research, Mr. David Koch. He's since, God rest his soul, passed away. And he's a controversial guy, big time business titan. And the press was just brutalizing him one day over something to do with his politics. Now, I'm a union guy. I'm proudly served in unions, still in a union. And he was not, most business guys don't like unions, right? But most guys like me don't like working for $3 an hour. So we like our unions, right? And I reached out, crossed the table, so to speak, and I sent him a handwritten letter to thank him, to say, we may not agree on everything, but I can't thank you enough. There's just this regular dude out there who is now living his life, watching his kids grow. Thanks to generous people like you who believe enough in cancer research, you've saved my life. Maybe I can't say his exact dollars, but people like him. And he reached back out and his secretary said, oh, he'd like to talk to you on the phone. I go, well, he's kind of a busy guy. He wants to talk to me. He's a billionaire. And he got on the phone. He was like the greatest guy in the world. Invited me up to Sloan Kettering to dedicate a new cancer wing. It was like I was hanging out with my dad. And the sweetest man, just so kind, so empathy, because he was a cancer survivor. But now he's got the means to help people who've suffered his fate to a better place. And he was so real. And it was so beautiful just to get to know, say, hey, you know what? This guy is a big time guy, but yet he's just a regular human like you and I. I'm a guy who went to night college and I went to the army and I'm a blue collar kind of dude. And here's this guy who went to MIT like you. And he's a wildly successful billionaire, a genius. But yet he can sit down and mix it up with me and know that I was truly grateful. And that to me was just like one of the coolest little relationships I've ever had. It wasn't like we were hanging out having barbecues together. But it was just I was so touched by his decency. Well, the basics of the cancer reveals, you know, it's like fundamental to the human experience is trauma is tragedy. It's like money. Who gives a shit about money, education, all that is like weird new inventions. You know, life is short. You suffer with the various diseases. And that is a reminder that life is short and a reminder of the basic human connection. And that's why you can bridge that gap. Oh, yeah. All sparked by a handwritten letter, which just is makes for a hell of a story. And you know what, Lex, this is the commonality between us, a guy with three jobs to a billionaire. We both had that sense of a sledgehammer to the chest. Boom, you have cancer and you can't breathe for like 30 seconds. And then when your heart's just about to kick off and you take a breath and you go, I'm sorry, what'd you say, doc? You have cancer. And it don't matter what kind. One of my best buddies, Bobby's going through right now, prostate. And I got way too many of my buddies with cancer. Right. My buddy, Hugh, who became a vet since his first cancer, he was a fireman. He's now a veterinary. Right. He diagnosed me actually over the phone, by the way. When they couldn't figure out what was wrong with me, well, Dr. Hugh, he nailed it to the T. And we talk. And the same thing that the dozen of my close friends that have cancer, the same thing we say is the fear. So Mr. Koch and I, we shared that same sledgehammer to the chest and that same fear. And it didn't matter how much money he had and how much I didn't. And it's just like the morning of the trade center. There was big time brokers who went to their demise, right? Working in these firms, God rest them. And there was dishwashers up on the windows on the world restaurant, on 107th floor, making five bucks an hour. And they died together. It didn't matter. It didn't matter if you had an armored car loaded with bills, you were done that day. And that's, I think, where people need to humanize each other. Just because you're driving around in a nice car and you got your own jet and you got this and you got that, don't mean nothing. When you're in that vulnerable spot, you could have more money than the US reserves, Federal Reserve, or you could have a welfare check. You're going. I learned that in a cancer ward. I had people in my ward that died on me. I was going around as a little bit of an ambassador because I was trying to, I was putting on a fake, I was putting on a fake like I got this, I got this. I was so scared. But when I got past that, that seven days of torture and the days leading up to it, I'd go around and try to comfort the other cancer patients. I had this one older African-American gentleman, he couldn't talk because he had such advanced throat cancer. He was my roommate for a little while, but then he got worse. So they had to put him by himself. And you couldn't understand what he was saying because his throat was just so radiated from the radiation. But if you put your ear down to him, you could make out what he was saying. And I'm not faulting the nurses for maybe not wanting to do that. They're busy. They got a ton going on. They can't spend, so if he was in need, I'd put my ear down and I'd find out and I'd go get it for him. So when they moved me down the hall, they asked me to come down with my IV tower. He needed me. And I knew it was bad because he just, his look was gone. I said, sir, what do you need? And he whispered, call my sister, I'm going. He had only one survivor in his whole life. And she was in North Carolina and he wanted her to know she couldn't get up. She was elderly. And I got the nurse and I got on the phone and I called his sister and I said, ma'am, I explained who I was. And I said, he can't really verbalize too well right now, but he wants to say he loves you. And I put the phone down and he told her he loved her and he said, I'm going home. And that was it. And I hung the phone up and I said, ma'am, I'm so sorry. I said, they'll notify you. And I stayed with him for a while holding his hand and then they wanted him to rest and then I left and then I got the tap an hour later and they said, I'm sorry, he's gone. And then there was another girl and she was a young girl from one of the areas I work, young African-American girl where I used to respond. And I didn't know her, but I knew her neighborhood and she had what I had, but they weren't sure which one. Leukemia is there's an elusive beast. There's 49 of them. And each one of them is like, got their own little nuances, own specific treatments. So if they don't know what you have, they don't know what to do for you. And she refused to let him drill into her hip to take the marrow because it's vicious. It hurts so much. It's like someone's boring into your hip with a wood drill and it's no joke. And they asked me to try to convince her to let her, let them do that or she was going to die. Cause if they couldn't figure it out, it was advancing quickly. She was. So I talked to her and she said, I can't, I can't, I'm too scared. I said, but are you more scared to die? And she said, I am. I said, okay, I'll stay with you. I'll hold your hand. You squeeze it as hard as you want. And I said, if you want, they'll give you like a towel or something to bite on whatever I said, but you get that pain out, but you need to do this so you can get saved. And she said, okay. And they came in and they, this huge thick needle, they just bored into you. And she's screaming for her life and she's squeezing my fingers so hard and so hard. And I said, that's okay, hon, you keep going, you keep going. We got it. It's just 10 more seconds, 10 more seconds. They got it. They figured out her treatment and they got her onto her road to recovery. And then I spent a long time asking God, why, why do I have cancer? But then I stopped and I went, wait a minute. I didn't die that day with my friends. Shame on me for asking them why I have cancer. I had 10 years after 9-11 was such great years. And I got to watch my little girl being born when John never got to see his son. So it was all gravy after that. And I said, but now I know why I have my cancer. Because I can empathize with people who have it. And I can try to be their voice when they can't talk, be their shield to try to take that pain. Because I can understand, I can walk their walk. And now I thank God for my cancer. Because it's made me a better human being. It's made me, I'm not going to lie, it brought a lot of anger for a while and my family suffered it. But I really tried to go past that and heal. And part of living out in the country, it's very, very healing for the mind and the soul. But I now thank God for the cancer because it humbled me. I didn't really need humbling. I wasn't an arrogant, puffed up type of person at all. But maybe I was running away at myself a little bit. I'm working on a TV show. I'm fine, man. 30 at the time, I was 42. I got sick. Life was cruising, man. It was great. And then all of a sudden it was like a blowout on the highway in the middle of the night and you're just veering off towards the guardrail. Yeah. You remembered, you're reminded that you're mortal. And that's ultimately a connection to all the rest of us. Oh yeah. It's a good thing though. When you... Because that's the problem, I think. There's a lot of people running around and thinking they're immortal. When you look at it, Lex, you look at the heartache in a lot of segments of people. And anytime someone that's got fame and wealth and success and they die tragically, a lot of times it's from a substance abuse or just some horrible death. And I used to say to myself, how the hell would someone with that much money and that much fame and this freaking mansion and I love cars. My son and I are just big car heads. I'm like, this guy's got a collection of cars and he overdosed because he was sad. And I'm going, how the frig are you sad? But then I stop and I go, okay, because maybe he doesn't have any idea who loves him. He's got a lot of people clinging onto him because of his success. And he just, he can't fill that void. And then they fill the void with something destructive. And I'm not bashing people that have substance abuse problems or alcohol problems. I don't mean it that way. But what I mean is, it's just sad that their level of despair is so high. On the surface, they look like they just got everything going on. It's all great. They're still humans. Still got to deal with the same. Yep, exactly. Because they want love. They want love. And they can't really find it. Well, first of all, that's true for all of us. I think we're deeply lonely and looking for love and when we find it, that's what friendship is. That's what true. And then that's true for whether you're super rich or super poor. It's all the same journey. My dad said all the time, kid, you're going to end up working with hundreds of guys and you'll love a lot of them. But he says, when it's all said and done and you're all like me and if you still got two or three of them that you talk to and you love. And I tell you what, I have thanked the Lord more than two or three of them. And I have my six. I call it my six. Six guys that are going to carry my coffin when I'm gone. Because I know this cancer is going to come back. I know. We get multiples. My friend Yvette just got his second. My friend Mike's had five of them. The other Mike has two. But I wasn't ready to accept it in 2011. There was so much more to do and it was so much, I was so scared. I'm like, wow, who's going to take care of my kids? They were little, 9, 11 and 14. It's like, what the hell? I have two girls and a boy in between and they're beautiful kids. They're such good, good children. The adults now. But my wife's a drill sergeant. She coughs, she don't mess. She's this big. So you're the softie in the family. I'm just kidding. It's funny because my son said to me, my son's 21 now. He's a good kid. And he says to me, back when he's 12, he goes, dad, I don't want you to be offended, but I'm really scared of mom. I'm not really that scared of you. I cracked up because it's true. She's got to stand on a milk crate to reach him because she's tiny and he's tall. But it's true. But she was hard but fair, but loved. That's the thing. You take any child anywhere from any background, if you love them, you nurture them, you teach them and you guide them, you have a successful adult. And see, that's the problem in our society. It's not judgmental. I'm not judging anyone. But we need to try harder as parents, as siblings, as friends. But especially when we're blessed with a child, it's like, you got to put that child first. It's like being a military personal responder. It's not about you anymore. Now it's the team. So that little child is now the team and your wife or your significant other, it's not about you anymore. And see, that's the problem is people have a hard time not making it about them. Like now it's really weird. My kids are 19, 21, and 24 and they hardly want to hang with me because they're busy in their life. We love each other. They're probably tired of hearing me go on and preach and whatever, but they're adults. We did pretty much the crux of what we had to do to put them into adulthood. And I look back and I go, wow, I wish I didn't work so much. But then I say, no, but it was okay. My wife stayed home, good lessons, good... But ultimately, like you said, it's love. It is. It's the common... Love is the most important ingredient on this earth. And that's the problem what's going on right now. Take politics out of it. Take polarizing each other against each other. Take all that crap out of it and just airdrop a bunch of love. When I worked on Rescue Me, I love those people so much. We had such a great crew and they worked so hard. You're a celebrity. No, no, no, not at all. If I was, it didn't really work out so good. I went on to being a stagehand that way. I'm not pretty. And they don't want old guys waving bye-bye hairdos. But it was funny. The crew, we became really tight. We had like, shoot, like 80, 90 people on a set. And the first few episodes, everybody's trying to feel each other out because you work with different crews, different people. And this is going back, starting in 2004, so it was a different time. And I love to hug people. Because to me, a hug is a true expression of love and caring. You may not know a person a long time, but you say, I care about you with a hug. Can I just a tiny tangent? This is in the midst of COVID when I was in Boston and it was masks, like triple masks. And when I went to see Joe here, when he's trying to convince me to move to Austin, Joe Rogan. And then the first time I see him, he's like, ah, you motherfucking big ass hug. And it felt so good. People probably looked horrified. They're hugging. Well, it was just him. Oh, okay. I don't want to say it, but if you do it in public now, it's like you committed a crime. But that expression, because I was so... You forget how powerful that is. Oh, I got some of my buddies. I give them a huge hug and a big sloppy kiss on their cheek. And I mean, because I love them. These are my brothers. But on this set, I swear to God, it got to the point and I'm not trying to whatever, but there was people that would come up to me for the daily hug. And I said, what are you doing? And they said, come on, bring it in. And I give them the hug. And they said, you don't understand. It just makes me feel so good. It makes me feel like you give a crap about me. I said, I really do. I said, but it touched my heart that people were seeking me out to get that hug to start the day. And I remember there was a guy in Manhattan, he was selling hugs for like 50 cents. And I think he got arrested, right? It was just before COVID. But I wouldn't sell them if... Yeah, you're giving them away for free. Well, now I got leukemia. I'd be kind of concerned to get into COVID. I mean, but I really think we need that. We need hugging booths in each city or each town. Because there's so many people that just want to know someone gives a shit about them. And that's the problem. That's what I love about small little towns like where I am now in Tennessee. And I'm not knocking New York, I'm not knocking big towns, but I guess it's easier to do in a smaller area because it's just not this massive humanity. But they'll stop and check on you. Like you're out in the road and I'm cutting and cleaning or whatever. Occasionally I'll roll a lawnmower or a tractor into a ditch because I'm not a farmer too good, but it's easier to drive a fire truck in New York. But they literally, oh, I was worried, I haven't seen you. And I'm like, no, no, I'm okay. But they literally check on you, they're worried about you. And I'm going, people hardly know me, but yet they're so caring. And that's the problem. This is what I love about my life. I spent a lot of time, especially as a young boy, a lot of time in Ireland at my grandma's farm. And my mom comes from this tiny, tiny little village, she's out in the middle of nowhere. And the childhood home she grew up in still, my aunt and uncle live in it still. I just love it there so much because everyone waves. Tennessee is similar. They wave, drive by and they're like, who the hell is that? And I just wave. But my cousin will point it out, that's your third cousin, second removed by Johnny. Like, holy shoot, I'm related to everyone here. But everyone stops to say hello and how are you? And I have a problem doing that because my wife goes, people think you're crazy. Why are you talking to everybody? I said, I'll literally stop someone and say, how's your day going? I mean, I'm randomly on the sidewalk, then it looks a little nuts. But if I'm buying a cup of coffee. Oh, that happens here in Austin all the time. That's why I love it here. You're on the sidewalk randomly. Yeah, no, it's just so nice. They'll say hi to me, I thought they recognized me or something. They don't give a shit who you are. They're just being nice. I was on the road coming back, driving from my family up north down to Tennessee last week. I stopped in a bathroom and it was closed. The girl was cleaning it, whatever. She's working so hard, whatever. She goes, sir, she goes, if you go down the hall, there's a family restroom, feel free to use it. She didn't have to do that. And I went down and I'm old. You need a bathroom, you need a bathroom. And I walked back out and I said, ma'am, I said, I want to thank you for being here today. I says, bathroom was immaculate. It was, it was like my army bathroom in the barracks. It was spotless. And I gave her $10. I said, I'd really like you to buy lunch with me today. I said, you really didn't have to do me that favor. She goes, no, sir. I said, no, no, I want. And it was like I gave her a million bucks. Mm-hmm. And I say to my wife now, I've been praying to be a billionaire. She goes, that's a sin. I said, no, no, you don't understand. Right? And she goes, oh, you're Mr., you know, Mr., you know, God. I said, no, no, no. I said, you're getting it wrong. I said, I'm praying to be like a multi-gazillionaire because I want to give all away. We used to have a sign in ladder 114 until some other rival truck company stole it, right? Because that's what we do. You know, you get sent to cover your district when you're out of fire and now your stuff's missing. Yeah. And the old timer's had a sign that says, I am content because if you got to ladder 114, that was considered such a great place, such a great assignment, such great guys. You had to be vetted to get there. You couldn't just randomly go. And it was a little exclusionary, but they wanted good guys. And I said to myself, that's where I am in life right now. I am content, but I'm restless because I want to really do a lot more good. It's like this podcast. I want to make sure that it's not forgotten. And I want to make sure that these charities that are really, really helping people get recognized. But I'd like to take it a step further, right? A friend of mine runs this foundation for young folks suffering mental illness and in crisis. It's for someone that we love dearly. And he's on a mission now to get therapy dogs for really, really mentally wounded warriors, right? A lot of these young soldiers are having a really hard time. And now they could be out a while. They may have come back in country two, three years ago. Now it's just starting to set in. And there's a waiting list for thousands of therapy dogs. And he said that they can't get enough of them quick enough. But he said, when you see the response, the way these veterans just light up when they get these dogs, it just changes their life radically, immediately. And I said, that's it. God, I don't know how I'm going to do it, but I want to be a gazillionaire. And I don't want any picture, photo ops, this, that. I just want to go, there's a dog, there's a dog, there's a dog, there's a dog. And then I want to build veterans land for these vets who just need a nice clean place to live. So why don't we take these old army bases and marine bases and Navy bases that have been shut down? They're just sitting there rotting away. I was in the army in Alabama. My old Fort McClellan is three quarters vacant. It's sitting there. They just did a documentary on it. It just looks like zombie land going back to zombies. So why don't we take that and renovate it and say to vets who are struggling, hey guys, you're going to live here? And they take the old army, the place where they had all the supplies, there's massive buildings where you could just retrofit it and make light manufacturing within two weeks. Give these guys jobs. There they live, there they work, they'll take care of it. Military guys, they teach you how to take care of stuff, right? How the hell in this country should any vet come back home and be homeless? Because now they have to dedicate their lives for six, seven, 10, 12 years, five, six deployments making $750 an hour. And then they spend seven years or they get a whopping $16 an hour, right? They walk out making $35 grand. And now no one gives them a job. No one gives them a chance. So very quickly they end up homeless by no fault of their own. And I don't know how that's even possible. The people in this country who've given the very most and they're struggling, they're hurting. That's not fair. And my whole thing is if I can have this dream of succeeding, so to speak, I want to try to change it. So that's why I'm praying to be a billionaire. My Irish mother probably wouldn't agree either because you're not supposed to, right? Well, I'm the same with you. The more money you have, the more you're able to help people. You can put smiles on people's faces. I have to ask you, the US invaded Afghanistan in October, 2001 in response to the terror attacks. Now, 20 years later, we still had a presence and abruptly withdrew all troops. What do you think about this war across the world that was sparked by this tragedy? Whenever you do something quickly without thinking it through and planning, it doesn't succeed. I understand that we needed to exit. I mean, how long are we going to stay over there? And we've lost over 7,000 of our young souls over there. For sometimes people, I don't know if they're grateful for it or not, right? I mean, I don't know. So there's the other element, and sorry to interrupt this. One is the financial of $6 trillion. And that money is not just money, it's education, it's everything. It's money that could have gone towards, first of all, the first responders, but all the service men and women of all kinds throughout this country. And then there's the other side, which is the over 800,000 people who died in direct result of this conflict. So not just the American side of the troops, but just people who died, those humans. And those humans, many of them civilians, that's spreading hate, especially if you have leaders on the other side who frame the death of those civilians in certain ways, that just spreads hate throughout the world. And so you think about this kind of 20 year saga and think, what are the ways that money could have been spent better? And what was the way that we could have spread more love in the world versus hate? And you wonder. But then the other side, what is it? I'm not sure who says this line, but it's something like, we sleep at night because there's rough men out there ready to fight for you. There is some sense in which we have to make sure that there's strength coupled with the love. Otherwise, evil men will do evil onto the world. So it's a very difficult decision, but then you look at the final picture and say, what have we gotten for the $6 trillion? What have we gotten for this 20 years? The thousands of American soldiers who died, the hundreds of thousands of civilians who have died. It's a troubling subject for me. I'm a patriot. I love this country. I love it with my soul. And I was just about to head over to the first Iraqi war, and we went out for desert warfare training, and then it ended. I was at that time a combat medic assigned to an armored cavalry unit. So basically tanks driving around an armored personnel carrier, and when it gets hit, then you tend to that guy, try to save his life. I didn't want to go. I may sound like a coward. I did not want to go to war. I would have went willingly if I was sent to defend my country. I took my oath. I didn't join the military to kill, but if necessary, I would. I'll use the analogy of cancer. If you have a cancer and you're aware of its presence, and you don't annihilate those cells and take them out quickly, it's going to spread, it's going to spread, and it's going to kill you. Those evil bastards that flew those airplanes, one of those airplanes had a little three-year-old child in it from Ireland, where my mom's hometown. A friend of mine who's since died of a heart attack from 9-11 toxins, he found her shoe with human remains in it. And he thought someone was messing with us because we didn't know there was any kids in the building. He says, boss, there's a baby shoe, and it looks like there's something in it, but there's no kids in the Trade Center. I went, the plane, it's a little girl's shoe. I can never get that shoe out of my mind. The evil bastards who perpetrated that needed to have missiles strike and rain down upon them and annihilate them like a cancer that they are. What just fascinates me is they'll show videos of these guys flying around and pick up trucks with 50 cows on the back. It's like, well, wait a minute. If a camera crew can get this footage, you think all these freaking drones and planes and radar-assisted systems can't just go, goodnight, you're gone. So kill the cancer, kill the cells, get rid of it, get rid of it quickly, and go into remission. Like an undeniable show of force that sends a message that gets rid of most of the obvious centers of terrorism. On that note, that's the, because we offline mentioned a discussion with Jaco, and maybe a romanticized view and mentioning Brothers in Arms by Dire Straits and saying we're all brothers in arms, even when it's on the opposite side of fighting, which is more of a vision. And growing up in the Soviet Union, you saw about World War II, World War II, that it's all just kids thrown into the, kids sent to die in all sides. But then presenting that to Jaco, who was in Iraq, he did not see it as brothers in arms, which is, there's his basic statement is there's evil people, and some people don't deserve the compassion. You give them a few chances, they don't take the chances they have to go, because they're spreading evil onto the world. And so it's not, we're not, all of us deserve a chance. Oh no, absolutely. But the difference though, and believe me, Jaco, I am from a way, way minor league compared to him, right? I mean, this man was right there in the firing line. But I can understand his analogy, because when you think about it, right, those young conscripts back in Germany and Russia and all the countries where they were being drafted, even our guys were being drafted and thrown into this. They were gallantly and bravely defending their country. Now, I'm sure the young Germans felt, well, hey, Hitler must be right, right? And young Russians felt, hey, Stalin must be right. And the young Americans figured, hey, President Roosevelt must be right. So they were romantically, in a sense, defending the honor of their country, of their motherland. The difference between those, so they did have that commonality. If you and I were firing across each other from France to Germany, or from Germany to Russia, or whatever, we're just these two kids who got thrown into this. We didn't freaking ask for this, right? But the difference with Jocko's enemy is no one was attacking their country over there, right? No one was taking their country over. Maybe in their mind, they didn't want people trying to build their government, this and that. I don't know. I don't know enough about the history there to really elaborate. We didn't attack them. And if a soldier attacks a soldier, that's an understood concept amongst warriors. But when a soldier attacks a civilian, now you're after a different beast, and you've written that beast off, if that makes any sense. Yeah, and the enemy, I mean, as Jocko explains, the enemy in Iraq and just certain parts of the Middle East is essentially terrorists who are, who don't value the lives of the civilians of their own country. They don't. And so it becomes like this weird guerrilla warfare slash game of violence that ultimately allows them to gain more power within their country, but they don't care if they're playing with civilian lives as pawns. If you have a child who dies, that's a civilian in their country, that could be seen as a positive for them because they can use that to leverage for more and more power within that country. Well, absolutely. And so when you're fighting an enemy like that, that's a vicious, that's an evil enemy. Absolutely. It's like snakes are beautiful, but if you go pet a rattler, you're getting bit and you're getting dead, right? Yeah. And that's what terrorists, you've got to cut the head of the snake off. And I feel, no, don't commit our guys to me there anymore. But what we need to do is go with tech warfare. If we have intel from drones or planes or whatever it is that so-and-so and so-and-so and so-and-so are driving down in that pickup or whatever, take it out and do it again tomorrow and tomorrow and tomorrow. And maybe they'll get the message after a while, oh shit, these guys aren't messing around. Instead of throwing wave after wave of our brave warriors, brave seals, brave special ops guys, and God bless them for what they do. I couldn't do it. I could not have done it. But they have to be now sitting home going, what the hell? My friends, my body, myself, they must feel so betrayed because they passionately went over there to cure a cancer, the cancer of terrorism. And now the cancer is back. And I hate to say it, but I think the cancer might start running wild. We need to change our tactics up. This is just my opinion. I can't see committing all of our guys to a continuous eternal war. But I think what we need to do is hit surgically and hit hard at that cancer that is over there. We are never going to rebuild that region. It's just, it's thousands of years of traditions that you're not going to change. It's just some people are unchangeable because they don't want to. And we have so many social problems here in our country, I think that we need to fix first. You know, I heard this spoken in the past by many people. It's like the garden theory. You have your garden with a fence around it. You tend to your garden. There may be weeds on the outside of the fence, but as long as they're not inside your garden, your garden will prosper. And I know some people don't agree to that, America first. And you know, the whole thing care of our own, but it's like, how are we going to take in more people now? And I have a human feeling for them, but it's almost like the lifeboat theory. How many people can we take into the lifeboat before the lifeboat itself sinks as the ship is going down? So if we can't take care of our own homeless vets and our own homeless people, and we can't take care of our own homeless people, and it's just going to become worse. And it doesn't make any sense. It's just like we need to just take a timeout and I think switch our tactics a little bit. And invest into helping people here at home. Absolutely. Absolutely. There's very few as obvious of cases as the first responders in 9-11. One of the things that I really want to kind of talk about at least a little bit, we've already talked about the amazing project that you're doing, the 20 for 20 podcast that you host. We mentioned one story, Steven Siller. Is there other stories, or maybe you can speak out at a high level, what are you hoping to tell? And all these different stories that are weaved about that connect the tragedies and the triumphs, the heroism of that day and the days and the years that followed. You know, Lex, it seems like the common few themes, the common threads are being selfless, helping out others even though they might be a stranger, in acts of kindness, acts of love, and it seems to all be weaved together with faith. They all seem to have some sort of faith. I mean, we have one gentleman, Mark Hanna, and he's a Coptic Egyptian priest. And he's an immigrant to the United States. He was a Port Authority building engineer. And with his crew, who subsequently passed away, the crew did, he was effectively rescuing dozens of people on the upper floors. And his boss ordered him to assist an elderly gentleman who was 89 down 78 flights of stairs to get him out. And in stopping on the 21st floor, he figured they would just wait there for medics. He came across Captain Patty Brown of Ladder Company 3, who told him, no, sir, you need to evacuate. And Captain Brown picked his brain a little bit about the structure because he figured, found out he was an engineer. And Captain Patty Brown continued on to effect rescues, and he and his crew were killed. But he's now, Mark was able to effectively evacuate this gentleman. They were the two known last survivors to come out of the tower. He now has dedicated his life to becoming a Coptic priest in St. Mary's Church in East Brunswick, New Jersey. He did this for a total stranger. And he said he was inspired by his bosses who died and his friends. One of his best friends was an Italian man. The other man was a retired Navy SEAL, Hispanic man. And they were part of this melting pot. And no one looked at each other that day, what color, what race, what belief are you? They just said, hey, you're a human in need, let's go. And we have the story about John Feale and his mission to help the responders. We have a young lady, Mariah, whose birth father was on flight 93. She had not even met him. And she had this premonition that somebody in her family was killed that day. And her adopted mom said, no, everyone's fine. Well, three years later, when she was legally able to find out who her dad was, she found out that her dad, Tom, was actually on that plane as part of the Let's Roll team. And we have a gentleman, Robert Burke, who's an actor, sweetheart of a man. He's a gentleman. And he's a very, very popular actor in Hollywood. He was on Rescue Me, Blue Bloods, Gossip Girls. And Bobby, my friend, as I call him, is a volunteer fireman now. This man doesn't need to get out of bed at two o'clock in the morning and help people with a stroke or burning garage or a burning house, but he does because he wants to. Because his best friend was Captain Patty Brown. And his other best friend was Father Michael Judge, who was our chaplain, who was killed, literally blessing the victims at the site, had just given last rites to the firefighter I mentioned earlier, Danny, who was killed. And Father Judge was in the lobby of the building, giving a blessing, praying to God to please stop this. And he was struck by debris and he was killed. And then Bobby goes on to elaborate about Father Judge's story. Father Judge used to walk the streets of New York City helping AIDS patients just with whatever they needed. And he was a Franciscan friar. They wear sandals and a rope. They just live very humble lives. And it's just a common denominator is loving each other and helping each other, regardless of you know the person or not. And really when you think about it, that's how America was made. We fought for independence. Stranger fought next to stranger and fought tyranny because they wanted freedom. They wanted to be able to live, love, pray, and prosper. And they fought and died alongside of strangers. And it's sort of symbolic of what happened that day. And then strangers from around this great country just flocked in by the thousands to help. They didn't know who was in that pile, but they didn't care. That was another American. And what I ultimately am trying to do involved in this beautiful project is spread the message of doing the right thing. Look at these examples, these brave people who didn't have to, especially the civilians, they weren't paid to run back in there and help person after person. And they had no obligation. They could have just said, hey man, I'm out of here and just bolted, but they didn't. So we're just trying to say to people, let's bring back that unity and that feeling of 9-12. As strange as 9-12 of a day it was, it was so sad because it was the first dawn of the sun where we realized this wasn't a dream, this was real and it's not going away. But the beauty of it was there was thousands of people lined up along the West Side Highway with signs and American flags. And they were from every country and every race and every creed. And it didn't matter who they were, but they all shared one bond, love. And they were hugging and crying and thanking rescuers. And it brought the morale so high for a group of people that was so beaten down the day before. It just started lifting the morale and making us realize, you know what? People really do give a crap. They really do love each other. And now I'm going to be honest with you, I've been doubting that a little bit lately. I still have these examples of it. That lady who helped me last night with the phone and I know there's these shining little examples, but sometimes I think, I don't know, are we running out of them? Well, I got to give you some advice. So there's two words that were repeated often in the days and the years after 9-11, which is never forget. So might I remind you to never forget about 9-12. I mean, those words you talked about that, you know, there's people, what is it, college freshmen? Yeah, they weren't even born. They weren't even born. And there's people in the twenties that were too young to remember, to understand the events of that day. But I think what that day, as you're describing, means it's not about a terrorist attack. It's about the unity that followed. It was tremendous, Lex. I never felt so proud. I was always proud of this country. You know, I remember my grandpa Nails used to walk by, I'd see a flag or hear a star spangled banner and he'd tear up and I'd say, Grant, why are you crying? He said, I'm not crying, it's tears of joy. I love this country so much. And I just remember like feeling that way. I felt that way 9-10. I felt that way on 9-11, but then on 9-12, I was just so proud of just the people, the way they stepped up. And I just want to try to see if that can happen again. And I hope it's not necessary for us to have another tragedy to bring that about. Let's do that without the tragedy. Let's just stop and say, hey, you know what? Let me listen to what this guy has to say. And maybe he probably won't convince me, but maybe I'll go, well, you know, I never thought of it that way. Stop the finger pointing, the bickering, the tantrums, the fighting. It's just not necessary. It gets you nowhere. It's like, you know, I was two years old and I'd stomp around because I wanted a cookie or a piece of candy. I still didn't get it. Turned blue in the face and whatever, got a swat in the rear end, but it didn't get the candy. And that's what we got going on right now. Everybody's just stomping around, being a baby. Stop. Just stop. We're really lucky. Look, the country's not perfect, right? But it's damn good. It gives us all these opportunities. Like I said, no one's rushing out the gates to get out of here. I got a cousin of mine, I love him dearly, my cousin Tony in Ireland. And he said, he's just a little older than me, he's in his 50s. He said, man, I should have done it. I should have went to America. My dad said, go to America. I went to England. And he went back to Ireland. But he's happy in Ireland. This is home. But he said, wow, what a place of opportunity. And I said, it's never too late. He goes, yeah, but you know what, you get tied down. And I understand that. I thank God my mom came here at 16. I thank God my grandpa got on that ship in his 20s, 27, I think, with not a nickel to rub together. I thank God they did it. Because I don't know where else I would have ended up. There's no place else I want to be. And I thank God that there's people like you who rushed towards ground zero to help other human beings. And I believe that that human spirit ultimately represents the best of this country and the best of this world. Thank you for the stories you're telling, for your perseverance in that. And thank you for welcoming me to the crew. You're very welcome. I'm proud. And we'll take you any day. You look like you could do the job just fine. I love lifting heavy things and doing dangerous things. So I'm proud to be part of this country and part of the Detailio now. Well, you are definitely an attribute to America. And we're glad you chose to come here. Alex, it's such a beautiful place. It's a beautiful melting pot. If we were all the same, it would be kind of a boring place, right? Yeah, kind of boring. Let's keep it fun. It really would. But it's just such a great place. And I just want to say thanks. It's an honor. It's an honor to have someone to let me sound off. And it'll be even bigger honor if somebody will listen to me and just say, hey, let me just try to do something good today. And that's the tunnel to towers mantra is let us do good. And I just, I got a really big credit card with God, a big balance, right? I need to pay him back a lot and I need to pay him forward. And I'm just going to spend the rest of my days trying my best. I don't know where this is going to go, what it'll lead into, but I really would like to get those dogs for those vets, build them that village and just keep going on from project to project. Just say when my final day comes and I'm laying there and I say, you know what? I really made the most of that second chance God gave me way back in 2011. I hope it's 30, 40 years from now, but even if it's 30 months from now, giving it the best shot. So thank you, sir. I appreciate it. And wishing you blessings and success in your career. Keep up the good fight. And you're always welcome back to Texas. Oh, I love it. It's great food and a little hot, but I can deal with it. We don't do so good Irish in the sun, you know, but- Well, the barbecue and the people are worth it. No, they are. They're awesome. I was down here for some storm relief a few years ago. And I tell you what, I fell in love with it. The people are great. It's a great state. And yeah, I'll definitely be back again for sure. Thanks for talking to me, Neil. Thank you, sir. Appreciate it. Appreciate it. Thanks for listening to this conversation with Niels Jorgensen. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Franklin D. Roosevelt. Human kindness has never weakened the stamina or softened the fiber of a free people. A nation does not have to be cruel to be tough. Thank you for listening. I hope to see you next time.

https://youtu.be/hZenJc1fa70

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Matt Walker: Sleep | Lex Fridman Podcast #210

The following is a conversation with Matt Walker, sleep scientist, professor of neuroscience and psychology at Berkeley, author of Why We Sleep, and the host of a new podcast called The Matt Walker Podcast. It's 10 minute episodes a couple of times a month, covering sleep and other health and science topics. I love it and recommend it highly. It's up there with the greats, like the Huberman Lab Podcast with Andrew Huberman, and I think David Sinclair is putting out an audio series soon too. I can't wait to listen to it. I'm really excited by the future of science in the podcasting world. To support this podcast, please check out our sponsors, Stamps.com, Squarespace, Athletic Greens, BetterHelp, and Onnit. Their links are in the description. As a side note, let me say that to me, a healthy life is one in which you fall in love with the world around you, with ideas, with people, with small goals and big goals, no matter how difficult, with dreams you hold onto and chase for years. Life should be lived fully. That, to me, is the priority. That, to me, is a healthy life. Second to that is the understanding and the utilization of the best available science on diet, exercise, supplements, sleep, and other lifestyle choices. To me, science in the realm of health is a guide for we should try, not the absolute truth of how to live life. The goal is to learn to listen to your body and figure out what works best for you. All that said, a good night's sleep can be a great tool in making life awesome and productive, and Matt is a great advocate of the how and the why of sleep. We agree on some things and disagree on others, but he's a great human being, a great scientist, and is recently a friend with whom I enjoy having these wide-ranging conversations. This is the Lex Friedman Podcast, and here is my conversation with Matt Walker. You should try these shades on. Let's see what you look like. So they are now your shades, and that's not a question. It's the same thing as Putin took the Super Bowl ring and it's now his ring. Yeah, one wonders if he was offered it, but they are yours. When did you first fall in love with the dream of understanding sleep? Like where did the fascination with sleep begin? So back in the United Kingdom, you can sort of start doing medicine at age 18, and it's a five-year program. And I was at the Queen's Medical Center in the UK, and I remember just being fascinated by states of consciousness and particularly anesthesia. I was thinking, isn't that incredible? Within seconds, I can take a perfectly conscious human being and I can remove all existence of the mentality and their awareness within seconds. And that stunned me. So I started to get really interested in conscious states. I even started to read a lot about hypnosis. And all of these things, hypnosis, even sleep and dreams at the time, they were very esoteric. It was sort of charlatan science at that stage. And I think almost all of my colleagues and I are accidental sleep researchers. No one, as I recall, in the classroom when you're sort of five years old and the teacher says, what would you like to be when you grow up? No one's putting their hand up and saying, I would love to be a sleep researcher. And so when I was doing my PhD, I was trying to identify different forms of dementia very early on in the course. And I was using electrical brainwave recordings to do that. And I was failing miserably. It was a disaster, just no result after no result. And I used to go home to the doctor's residence with this sort of a little igloo of journals that at the weekend I would sort of sit in and read. And which I'm now thinking, do I really want to admit this? Cause it sounds like I had no social life, which I didn't. I was social leper. But, and I started to realize that some parts of the brain were sleep related areas. And some dementias were eating away those sleep related areas. Other dementias would leave them untouched. And I thought, well, I'm doing this all wrong. I'm measuring my patients while they're awake. Instead I should be measuring them while they're asleep. Started doing that, got some amazing results. And then I wanted to ask the question, is that sleep disruption that my patients are experiencing as they go into dementia, maybe it's not a symptom of the dementia. I wonder if it's a cause of the dementia. And at that point, which was, cough, cough, 20 years ago, no one could answer a very simple fundamental question. Why do we sleep? And I, at the time, didn't realize that some of the most brilliant minds in scientific history had tried to answer that question and failed. And at that point, I just thought, well, I'm going to go and do a couple of years of sleep research and I'll figure out why we sleep. And then I'll come back to my patients in this question of dementia. And as I said, that was 20 years ago. And what I realized is that hard questions care very little about who asks them. They will meter out their lessons of difficulty all the same. And I was schooled in the difficulty of the question, why do we sleep? But in truth, 20 years later, we've had to upend the question rather than saying, why do we sleep? And by the way, the answer then was that we sleep to cure sleepiness, which is like saying, we eat to cure hunger. That tells you nothing about the physiological benefits of food, same with sleep. Now we've actually have to ask the question, is there any physiological system in the body or any major operation of the mind that isn't wonderfully enhanced when we get sleep or demonstrably impaired when we don't get enough? And so far, for the most part, the answer seems to be no. So far, the answer seems to be no. So why does the body and the mind crave sleep then? Why do we sleep? How can we begin to answer that question then? So I think one of the ways that I think about this or one of the answers that came to me is the following. The reason that we implode so quickly and so thoroughly with insufficient sleep is because human beings seem to be one of the few species that will deliberately deprive themselves of sleep for no apparent good reason, biological. And what that led me then to was the following. Mother nature as a consequence. So no other species does what we do in that context. There are a few species that do undergo sleep deprivation, but for very obvious, clear biological reasons. One is when they're in a condition of severe starvation. The second is when they're caring for their newborn. So for example, killer whales will often deprive themselves. The female will go away from the pod, give birth, and then bring the calf back. And during that time, the mother will undergo sleep deprivation. And then the third one is during migration when birds are flying trans oceanographic 2,000, 3,000 miles. But for the most part, it's never seen in the animal kingdom which brings me back to the point. Therefore, mother nature in the course of evolution has never had to face the challenge of this thing called sleep deprivation. And therefore, she has never created a safety net in place to circumnavigate this common influence. And there is a good example where we have, which is called the adipose cell, the fat cell, because during our evolutionary past, we had famine and we had feast. And mother nature came up with a very clever recipe, which is how can I store caloric credit so that I can spend it when I go into debt? And the fat cell was born, brilliant idea. Where is the fat cell for sleep? Where is that sort of banking chip for sleep? And unfortunately, we don't seem to have one because she's never had to face that challenge. So even if there's not some kind of physics fundamental need for sleep, that physiologically or psychologically, the fact is most organisms are built such that they need it. And then mother nature never built an extra mechanism for sleep deprivation. So it's interesting that why we sleep might not have a good answer, but we need to sleep to be healthy is nevertheless true. Yeah, and we have many answers right now. In some ways, the question of why we sleep was the wrong question too. It's what are the pluripotent many reasons we sleep? We don't just sleep for one reason because from an evolutionary perspective, it is the most idiotic thing that you could imagine. When you're sleeping, you're not finding a mate, you're not reproducing, you're not caring for your young, you're not foraging for food, and worse still, you're vulnerable to predation. So on any one of those grounds, but especially as a collective, sleep should have been strongly selected against in the course of evolution. But in every species that we've studied carefully to date, sleep is present. Yeah, so it is important. So like, you're right. I think I've heard arguments from an evolutionary biology perspective that sleep is actually advantageous. You know, maybe like some kind of predator-prey relationships. Yeah. But you're saying, and it actually makes way more sense what you're saying, is it should have been selected against. Like, why close your eyes? Yeah, why? Because, and you know, there was an energy conservation hypothesis for a while, which is that we need to essentially go into low battery mode, you know, power down because it's unsustainable. But in fact, that actually has been blasted out the water because sleep is an incredibly active process. In fact, the difference between you just lying on the couch, but remaining conscious versus you lying on the couch and falling asleep, it's only a savings of about 140, 150 calories. In other words, you know, you just go out and club another baby seal or whatever it was, and you wouldn't worry, you know. So it has to be much more to it than energy conservation, much more to it than sharing, you know, ecosystem space and time, much more to it than simply predator-prey relationships. If sleep really did, and you know, looking back, even very old evolutionary organisms like earthworms, millions of years old, they have periods where they're active and periods where they're passively asleep. It's called lethargics. And so what that in some way suggested to me was sleep evolved with life itself on this planet, and then it has fought its way through heroically every step along the evolutionary pathway, which then leads to the sort of famous sleep statement from a researcher that if sleep doesn't serve an absolutely vital function or functions, then it's the biggest mistake the evolutionary process has ever made. And we've now realized mother nature didn't make a spectacular blunder with sleep. You've mentioned the idea of conscious states. Do you think of sleep as a fundamentally different conscious state than awakeness? And how many conscious states are there? So when you're into it, you're understanding of what the mind can do. Do you think awake state, sleep state, or is there some kind of continuum? There's a complicated state transition diagram. Like how do you think about this whole space? I think about it as a state space diagram. And I think it's probably more of a continuum than we have believed it to be or suggested it to be. So we used to think absent of anesthesia that there were really three main states of consciousness. There was being awake, being in non-rapid eye movement sleep or non-dream sleep, and then being in rapid eye movement sleep or dream sleep. And those were the three states within which your brain could percolate and be conscious. Conscious during non-REM sleep is maybe a stretch to say, but I still believe there is plenty of consciousness there. I don't believe that though anymore. And the reason is because we can have daydreams and we are in a very different wakeful state in those daydreams than we are when we are, as we are now together, present and extraceptively focused rather than interceptively focused. And then we also know that as you are sort of progressing into those different stages of sleep during non-REM sleep, you can also still dream. Depends on your definition of dreaming, but we seem to have some degree of dreaming in almost all stages of sleep. We've also then found that when you are sleep deprived, there are even individual brain cells will fall asleep. Despite the animal being, you know, behaviorally from best we can tell awake, individual brain cells and clusters of brain cells will go into a sleep-like state. And humans do this too. When we are sleep deprived, we have what are called micro-sleeps where the eyelid will partially close and the brain essentially falls lapses into a state of sleep, but behaviorally you seem to be awake. And the danger here is road traffic accidents. So these are the, what we call these sort of micro-sleep events at the wheel. Now, if you're traveling at 65 miles an hour in a two ton vehicle, you know, it takes probably around one second to drift from one lane to the next. And it takes two seconds to go completely off the road. So if you have one of these micro-sleeps at the wheel, you know, it could be the last micro-sleep that you ever have. But I don't now see it as a set of, you know, very binary distinct, you know, step function states. It's not a one or a zero. I see it more of a, as a continuum. Yeah, so I've for five, six years at MIT really focused on this human side of driving question. And one of the big concerns is the micro-sleeps, drowsiness, these kinds of ideas. And one of the open questions was, is it possible through computer vision to detect, or any kind of sensors? The nice thing about computer vision is you don't have to have direct contact to the person. Is it possible to detect increases in drowsiness? Is it possible to detect these kinds of micro-sleeps or actually just sleep in general? Among other things, like distraction. These are all words that have so many meanings and so many debates, like attention is a whole nother one. Just because you're looking at something doesn't mean you're loading in the information. Just because you're looking away doesn't mean your peripheral vision can't pick up the important information. There's so many complicated vision science things there. So I wonder if you could say something to, they say the eyes are the windows to the soul. Do you think the eyes can reveal something about sleepiness through computer vision, just looking at the video of the face? And Andrew Huberman and I, your friend, have talked about this. So I would love to work on this together. We should do. It's a fascinating problem. But drowsiness is a tricky one. So there's what kind of information? There's blinking and there's eye movement. And those are the ones that can be picked up with computer vision. Do you think those are signals that could be used to say something about where we are in this continuum? Yeah, I do. And I think there are a number of other features too. I think aperture of eye, so in other words, partial closures, full closures, duration of those closures, duration of those partial closures of the eyelid. I think there may be some information in the pupil as well, because as we're transitioning between those states, there are changes in what's called the automatic nervous system, or technically it's called the autonomic nervous system, part of which will control your pupillary size. So I actually think that there is probably a wealth of information. When you combine that probably with aspects of steering, angle steering maneuver, and if you can sense the pressure on the pedals as well, my guess is that there is some combinatorial feature that creates a phenotype of you are starting to fall asleep. And as the autonomous controls develop, it's time for them to kick in. Some manufacturers, auto manufacturers, sort of have something beta version, maybe an alpha version of this already starting to come online where they have a little camera in the wheel that I think tries to look at some features. Almost everybody doing this, and it's very alpha. So, you know, the thing that you currently have, some people have that in their car, there's a coffee cup or something that comes up that you might be sleepy. The primary signal that they're comfortable using is a steering wheel reversals. So basically using your interaction with the steering wheel and how much you're interacting with it as a sign of sleepiness. So if you have to constantly correct the car, that's a sign of you starting to drift into micro sleep. I think that's a very, very crude signal. It's probably a powerful one. There's a whole nother component to this, which is it seems like it's so driver and subject dependent. How our behavior changes as we get sleepy and drowsy seems to be different in complicated, fascinating ways where you can't just use one signal. It's kind of like what you're saying, there has to be a lot of different signals that you should then be able to combine. The hope is there's the searches for like universal signals that are pretty damn good for like 90% of people. But I don't think we need to take necessarily quite that approach. I think what we could do in some clever fashion is using the individual. So what you and I are perhaps suggesting here is that there is an array of features that we know provide information that is sensitive to whether or not you're falling asleep at the wheel. Some of those, let's say that there are 10 of them. For me, seven of them are the cardinal features. For you, however, six of them, and they're not all the same sort of overlapping are those for you. I think what we need is algorithms that can firstly understand when you are well slept. So let's say that people have sleep trackers at night and then your car integrates that information. And it understands when you are well slept. And then you've got the data of the individual behavior unique to that individual snowflake like when they are well slept. This is the signature of well-rested driving. Then you can look at deviations from that and pattern match it with the sleep history of that individual. And then I don't need to find the sort of, the one size fits all approach for 99% of the people. I can create a very bespoke tailor like set of features, a Savile Row suit of sleepiness features. That would be my, if you want to ask me about moonshots and crazy ideas, that's where I'd go. But to start with, I think your approach is a great one. Let's find something that covers 99% of the people because the worrying thing about microsleeps, of course, unlike drugs or alcohol, which certainly is a terrible thing to be behind the wheel, with those often you react too late. And that's the reason you get into an accident. When you fall asleep behind the wheel, you don't react at all. You know, at that point, there is a two-ton missile driving down the street and no one's in control. That's why those accidents can often be more dangerous. Yeah, and the fascinating thing is in the case of semi-autonomous vehicles like Tesla autopilot, this is where I've had disagreements with Mr. Elon Musk, and the human factors community, which is this community that one of the big things they study is human supervision over automation. So you have like pilots, you know, supervising an airplane that's mostly flying autonomously. The question is when we're actually doing the driving, how do microsleeps or general, how does drowsiness progress and how does it affect our driving? That question becomes more fascinating, more complicated when your task is not driving, but supervising the driving. So your task is to take over when stuff goes wrong. And that is complicated, but the basic conclusions from many decades is that humans are really crappy at supervising because they get drowsy and lose vigilance much, much faster. The really surprising thing with Tesla autopilot, it was surprising to me, surprising to the human factors community, and in fact, they still argue with me about it, is it seems that humans in Teslas with autopilot and other similar systems are not becoming less vigilant, at least with the studies we've done. So there's something about the urgency of driving. I can't, I'm not sure why, but there's something about the risk, I think the fact that you might die is still keeping people awake. The question is, as Tesla autopilot or similar systems get better and better and better, how does that affect increasing drowsiness? And that's when you need to have, that's where the big disagreement was, you need to have driver sensing, meaning driver facing camera that tracks some kind of information about the face that can tell you drowsiness. So you can tell the car if you're drowsy so that the car can be like, you should be probably driving or pull to the side. Right, or I need to do some of the heavy lifting here. Yeah, so there needs to be that dance of interaction of human and machine, but currently it's mostly steering wheel based. So this idea that your hands should be on the steering wheel that's a sign that you're paying attention is an outdated and a very crude metric. I agree, yeah. I think there are far more sophisticated ways that we can solve that problem if we invest. Can I ask you a big philosophical question before we get into fun details? On the topic of conscious states, how fundamental do you think is consciousness to the human mind? I ask this from almost like a robotics perspective. So in your study of sleep, do you think the hard question of consciousness, that it feels like something to be us, is that like a nice little feature, like a quirk of our mind, or is it somehow fundamental? Because sleep feels like we take a step out of that consciousness a little bit. So from all your study of sleep, do you think consciousness is like deeply part of who we are, or is it just a nice trick? I think it's a deeply embedded feature that I can imagine has a whole panoply of biological benefits. But to your point about sleep, what is interesting if you do a lot of dream research, and we've done some, it's very, very rare at all, in fact, for you to end up becoming someone other than who you are in your dreams. Now, you can have third-person perspective dreams where you can see yourself in the dream as if you've risen above your physical being. But for the most part, it's very rare that we lose our sense of conscious self. And maybe I'm sort of doing a sleight of hand because it's really what I'm saying is it's very rare that we lose our sense of who we are in dreams. We never do. Now, that's not to suggest that dreams aren't utterly bizarre and I mean, when you slept last night, which I know may have been perhaps a little less than me, but when you went into dreaming, you became flagrantly psychotic. And there are five essentially good reasons. Firstly, you started to see things which were not there, so you were hallucinating. Second, you believe things that couldn't possibly be true, so you were delusional. Third, you became confused about time and place and person, so you're suffering from what we would call disorientation. Fourth, you have wildly fluctuating emotions, something that psychiatrists will call being affectively labile. And then how wonderful, you woke up this morning and you forgot most, if not all of that dream experience, so you're suffering from amnesia. If you had to experience any one of those five things while you're awake, you would probably be seeking psychological help. So I place that as a backdrop against your astute question because despite all of that psychosis, there is still a present self nested at the heart of it, meaning that I think it's very difficult for us to abandon our conscious sense of self. And if it's that hard, it's the old adage in some ways that you can't outrun your shadow, but here it's more of a philosophical question, which is about the conscious mind and what the state of consciousness actually means in a human being. So I think that that to me, you become so dislocated from so many other rational ways of waking consciousness, but one thing that won't go away, that won't get perturbed or sort of, you know, manacled is this your sense of conscious self. Yeah, that's a strong sign that consciousness is fundamental to the human mind. Or we're just creatures of habit who've gotten used to having consciousness. Maybe it just takes a lot of either chemical substances or a lot of like mental work to escape that. I mean, it's like trying to launch a rocket. You know, the energy that has to be put in to create escape velocity from the gravitational pull of this thing called planet earth is immense. Well, the same thing is true for us to abandon our sense of conscious self. The amount of biological, the amount of substances, the amount of wacky stuff that you have to do to truly get escape velocity from your conscious self. What does that tell us about then the fundamental state of our conscious self? Yeah, it also probably says that it's quite useful to have consciousness for survival and for just operation in this world. And perhaps for intelligence. I'm one of the, on the AI side, people that think that intelligence requires consciousness. So like high levels of general intelligence requires consciousness. Most people in the AI field think like consciousness and intelligence are fundamentally different. You can build a computer that's super intelligent. It doesn't have to be conscious. I think that if you define super intelligence by being good at chess, yes. But if you define super intelligence as being able to operate in this living world of humans and be able to perform all kinds of different tasks, consciousness, it seems to be somehow fundamental to richly integrate yourself into the human experience, into society. It feels like you have to be a conscious being. But then we don't even know what consciousness is and we certainly don't know how to engineer it in our machines. I love the fact that there are still questions that are so embryonic because I suspect it's the same with you. Answers to me are simply ways to get to more questions. It's questions where, questions turn me on, answers less so. And I love the fact that we are still embryonic in our sense of arguing about even what the definition of consciousness is. But I also find it fascinating. I think it's thoroughly delightful to absorb yourself in the thought. Think about the brain and we can move back across the complexity of phylogeny from humans to mammals to sort of birds to reptiles, amphibians, fish, bacteria, whatever you want. And you can go through this and say, okay, where is the hard line of what we would define as consciousness? And I'm sure it's got something to do with the complexity of the neural system. Of that, I'm fairly certain. But to me, it's always been fascinating. So what is it then? Is it that I just keep adding neurons to a Petri dish and I just keep adding them and adding them and adding them. At some point when I hit a critical mass of interconnected neurons, that is the mass of the interconnected human brain, then bingo. All of a sudden it kicks into gear and we have consciousness. Like a phase shift, phase transition of some kind. Correct, yeah. But there is something about the complexity of the nervous system that I think is fundamental to consciousness. And the reason I bring that up is because when we're trying to then think about creating it in an artificial way, does that inform us as to the complexity that we should be looking at in terms of development? I also think that it's a missed opportunity in the sort of digital space for us to try to recreate human consciousness. We've already got human consciousness. What if we were to think about creating some other form of consciousness? Why do we have to think that the ultimate in the creation of an artificial intelligence is the replication of a human state of consciousness? Can we not think outside of our own consciousness and believe that there is something even more incredible or more complimentary, more orthogonal? So I'm sometimes perplexed that people are trying to mimic human consciousness rather than think about creating something that's different. I think of human consciousness or consciousness in general as this magic superpower that allows us to deeply experience the world. And just as you're saying, I don't think that superpower has to take the exact flavor as humans have. That's my love for robots. I would love to add the ability to robots that can experience the world and other humans deeply. I'm humbled by the fact that that idea does not necessarily need to look anything like how humans experience the world. But there's a dance of human to robot connection the same way human to dog or human to cat connection. There's a magic there to that interaction. And I'm not sure how to create that magic, but it's a worthy effort. I also love just exactly as you said, on the question of consciousness or engineering consciousness, the fun thing about this problem is it seems obvious to me that 100 years from now, no matter what we do today, people, if we're still here, will laugh at how silly our notions were. So it's almost impossible for me to imagine that we will truly solve this problem fully in my lifetime. And more than that, everything we'll do will be silly 100 years from now. But it's still a work that makes it fun to me because it's like you have the full freedom to not even be right. Just to try, just to try is freedom. And that's how I see- Can you get me that t-shirt please? I love that. So, and human robot interaction is fascinating because it's like watching dancing. I've been dancing tango recently. And just, it's like, there is no goal. The goal is to create something magical. And whether consciousness or emotion or elegance of movement, all of those things aid in the creation of the magic. And it's a free, it's an art form to explore how to make that, how to create that in a way that's compelling. Yeah, I love the line in Sense of a Woman with Al Pacino where he's speaking about the tango and he said, really, it's just freedom that if you get tangled up, you just keep tangoing on. I still to this day, I think, well, first or second time I talked to Joe Rogan on his podcast, I said, we got into this heated argument about whether Sense of a Woman is a better movie than John Wick. Because it's one of my favorite movies for many reasons. One is, Sense of a Woman. Sense of a Woman. Parsons didn't know that, by the way. You just tossed that out there. Yeah, I didn't know if you would actually know of the movie. Awesome, awesome. Yeah, I said, I love the tango scene. I love Al Pacino's performance. It's a wonderful movie. Then Joe was saying John Wick is better. So we to this day argue about this. I think it depends on what conscious state you're in that you would be ready and receptive to. But Sense of a Woman, I think it has one of the best monologues at the end of the movie that has ever been written or at least performed. When Al Pacino defends the younger. Yeah, I often think about that. There's been times in my life, I don't know about you, where I wish I had an Al Pacino in my life. Where integrity is really important in this life. It is. And sometimes you find yourself in places where there's pressure to sacrifice that integrity. And you want, what is it, Lieutenant Colonel or whatever he was. To come in. Slade. To come in on your side and scream at everyone and say, what the hell are we doing here? Being, you know, unfortunately British and sort of having that slightly awkward sort of Hugh Grant gene. It's very, very, very at the opposite end of the spectrum of the remarkable feat of Al Pacino at the end of that scene. But, and yeah, integrity is, it's a challenging thing and I value it much. And I think it can take 20 years to build a reputation and two minutes to lose it. And there is nothing more that I value than integrity. And, you know, if I'm ever wrong about anything, I truly don't want to be wrong for any longer than I have to be. You know, that's what being in some ways a scientist is. You're just driven by truth. And the irony relative to something like mathematics is that in science, you never find truth. What will you do in science is you discount the things that are likely to be untrue, leaving only the possibility of what could be true. But in math, you know, when you create, you know, a proof, it's a proof for, you know, from that point forward, there is truth in mathematics. And there's, I think there's a beauty in that, but I kind of like the messiness of science, because again, to me, it's less about the truth of the answer and it is more about the pursuit of questions. But their integrity becomes more and more important and it becomes more difficult. There's a lot of pressures, just like in the rest of the world, but there's a lot of pressures on a scientist. One is like funding sources. I've noticed this, that, you know, money affects everyone's mind, I think. I've been always somebody that I believe money can't, you can't buy my opinion. I don't care how much money, billions or trillions. But that pressure is there and you have to be very cognizant of it and make sure that your opinion is not defined by the funding sources. And then the other is just your own success of, you know, for a couple of decades, publishing an idea and then realizing at some point that that idea was wrong all along. And that's a tough thing for people to do, but that's also integrity is to walk away, is to say that you were wrong. That doesn't have to be in some big dramatic way. It could be in a bunch of tiny ways along the way. Right. Like reconfigure your intuition about a particular problem. That's, and all of that is integrity. When everybody in the room, you know, believes a certain thing, everybody in the community believes a certain thing to be able to still be open-minded in the face of that. Yeah, and I think it comes down in some ways to the issue of ego, that you bond your, you know, correctness or your rightness, your scientific theory with your sense of ego. You know, I've never found it that difficult to let go of theories in the face of counter evidence, in part because I have such low self-esteem. Well, I kind of like that. I've always liked that combination. I have the same. I'm like very self-critical, imposter syndrome, all those things, putting yourself below the podium, but at the same time, having the ego that drives the ambition to work your ass off. Like some kind of weird drive, maybe like drive to be better. Like thinking of yourself as not that great and always driving to be better. And at the same time, because that can be paralyzing and exhausting and so on, at the same time, just being grateful to be alive. But in the sciences, in the actual effort, never be satisfied, never think of yourself highly. It seems to be a nice combination. I very much hope that that is part of who I am. And I remain very quietly motivated and driven. And I, like you, love the idea of perfection. And I know I will never achieve it, but I will never stop trying to. So similar to you, which sounds weird, because there's all these videos of me on the internet. So I think I just naturally lean into the things I'm afraid of and I'm uncomfortable doing. Like I'm very afraid of talking to people. And just even before talking to you today, just a lot of anxiety and all those kinds of things. How about talking to me? Yeah, yeah. Oh, like some nervousness. Fear in some cases, self-doubt and all those kinds of things. But I do it anyway. So the reason I bring that up is you've launched a podcast. I have. Allow me to say, I think you're a great science communicator. So this challenge of being afraid or cautious of being in the public eye, and yet having a longing to communicate some of the things you're excited about in the space of sleep and beyond. What's your vision with this project? I think firstly to that question, like you, I am always more afraid of not trying than trying. Yeah. That to me frightens me more. But with the podcast, I think really, I have two very simple goals. I want to try and democratize the science of sleep. And in doing so, my goal would be to try and reunite humanity with the sleep that it is so desperately bereft of. And if I can do that through a number of different means, the podcast is a little bit different than this format. It's going to be short form monologues from yours truly, that will last usually less than just 10 minutes. And I see it as simply a little slice of sleep goodness that can accompany your waking day. It's hard to know what is the right way to do science communication. Like your friend of mine, Andrew Huberman, he's an incredible human being. Oh gosh. So he does like two hours of, I wonder how many takes he does, I don't know. But it looks like he doesn't do any. Yeah, I suspect he's that magnificent of a human being. When I talk to him in person, he always generates intelligent words, well-sighted, nonstop for hours. So I don't. He's a Gatlin gun of information and it's pristine. And passion and all those kinds of things. That's an interesting medium. I wouldn't have, it's funny because I wouldn't have done it the way he's doing it. I wouldn't advise him to do it the way he's doing it. Because I thought there's no way you could do what you're doing. Because it's a lot of work. But he is like doing an incredible job of it. I just think it's the same with like Dan Carlin and hardcore history. I thought that the way Andrew's doing it would crush him the way it crushes Dan Carlin. So Dan has so much pressure on him to do a good job that he ends up publishing like two episodes a year. So that pressure can be paralyzing. The pressure of like putting out like strong scientific statements, that can be overwhelming. Now, Andrew seems to be just plowing through anyway. If there's mistakes, he'll say there's corrections and so on. I just, I wonder, I actually haven't talked to him too much about it. Like psychologically, how difficult is it to put yourself out there for an hour or two a week of just nonstop dropping knowledge? Any one sentence of which could be totally wrong. It could be a mistake. And there will be mistakes. And I, in the first edition of my book, there were errors that, you know, we corrected in the second edition too. But there will be probabilistically, you know, if you've got, you know, 10 facts per page of a book and you've got 350 pages, odds are it's probably not going to be at a perfection out the gate. And it will be the same way for Andrew too. But having the reverence of a humble mind and simply accepting the things that are wrong and correcting them and doing the right thing, I know that that's his mentality. I do want to say that I'm just kind of honored to be, it's like, it's a cool group of like scientific people that I'm fortunate enough to now be interacting with. It's you and Andrew and David Sinclair has been thinking about throwing his hat in the ring. Oh, I hope so. David is another one of those very special people in the world. So it's cool because podcasts are, it's cool. It's such a powerful medium of communication. It's much freer than more constrained like publications and so on. Or it's much more accessible and inspiring than like, I don't know, conference presentations or lectures. So it's a really exciting medium to me. And it's cool that there's this like group of people that are becoming friends and putting stuff out there and supporting each other. So it's fun to also watch how that's going to evolve in your case, because I wonder, it'll be two a month. Or devolve. Devolve. Is the answer to that. Well, I mean, some of it is persistence through the challenges that we've been talking about, which is like- I think I've got a lot to learn. Yeah. But I will persist. Can I ask you some detailed stuff? You mentioned that one. Oh my goodness. Go anywhere you wish with sleep. So I'm a big fan of coffee and caffeine. And I've been, especially in the last few days, consuming a very large amount. And I'm cognizant of the fact that my body is affected by caffeine different than the anecdotal information that other people tell me. I seem to be not at all affected by it. It's almost, it feels more like a ritual than it is a chemical boost to my performance. Like I can drink several cups of coffee right before bed and just knock out anyway. I'm not sure if it's a biological chemical or it has to do with just the fact that I'm consuming huge amounts of caffeine. All that to say, what do you think is the relationship between coffee and sleep? Caffeine and sleep? There's an interesting distinction there. There is a distinction. So I think the first thing to say, which is going to sound strange coming from me, is drink coffee. The health benefits associated with drinking coffee are really quite well established now. But I think that the counterpoint to that, well, firstly, the dose and the timing make the poison. And I'll perhaps come back to that in just a second. But for coffee, it's actually not the caffeine. So, a lot of people have asked me about this rightful paradox between the fact that sleep provides all of these incredible health benefits and then coffee, which can have a deleterious impact on your sleep, has a whole collection of health benefits. Many of them, Venn diagram overlapping with those that sleep provides. How on earth can you reconcile those two? And the answer is that, well, the answer is very simple. It's called antioxidants. That it turns out that for most people in Western civilization, because of diet not being quite what it should be, the major source through which they obtain antioxidants is the coffee bean. So the humble coffee bean has now been asked to carry the astronomical weight of serving up the large majority of people's antioxidant needs. And you can see this if, for example, you look at the health benefits of decaffeinated coffee. It has a whole constellation of really great health benefits too. So it's not the caffeine, and that's why I liked what you said, this sort of separation of church and state between coffee and caffeine. It's not the caffeine, it's the coffee bean itself that provides those health benefits. But coming back to how it impacts sleep, it impacts sleep in probably at least three different ways. The first is that for most people, caffeine can make it obviously a little harder to fall asleep. Caffeine can make it harder to stay asleep. But let's say that you are one of those individuals, and I think you are, and you can say, look, I can have three or four espressos with dinner, and I fall asleep just fine, and I stay asleep soundly across the night, so there's no problem. The downside there is that even if that is true, the amount of deep sleep that you get will not be as deep. And so you will actually lose somewhere between 10 to 30% of your deep sleep if you drink caffeine in the evening. So to give you some context, to drop your deep sleep by let's say 20%, I'd probably have to age you by 15 years, or you could do it every night with a cup of coffee. I think the fourth component that is perhaps less well understood about coffee is its timing, and that's why I was saying the timing and the dose make the poison. The dose, by the way, once you get past about three cups of coffee a day, the health benefits actually start to turn down in the opposite direction. So there is a U-shaped function. It's sort of the Goldilocks syndrome, not too little, not too much, just the right amount. The second component is the timing, though. Caffeine has a half-life of about five to six hours, meaning that after five to six hours, 50% of that, on average, for the average adult, is still in the system, which means that it has a quarter-life of 10 to 12 hours. So in other words, if you have a coffee at noon, a quarter of that caffeine is still circulating in your brain at midnight. So having a cup of coffee at noon, one could argue, is the equivalent of tucking yourself into bed at midnight, and before you turn the light out, you swig a quarter of a cup of coffee. But that doesn't still answer your question as to why are you so immune? So I'm someone who is actually, unfortunately, very sensitive to caffeine, and if I have, you know, even two cups of coffee in the morning, I don't sleep as well that night. And I find it miserable because I love the smell of coffee. I love the routine. I love the ritual. I think I would love to be invested in it. It's just terrible for my sleep, so I switch to the decaf. There is a difference from one individual to the next, and it's controlled by a set of liver enzymes called cytochrome P450 enzymes. And there is a particular gene that if you have a different sort of version of this gene, it's called CYP1A2. That gene will determine the speed of the clearance of caffeine from your system. Some people will have a version of that gene that is very effective and efficient at clearing that caffeine. And so their half-life could be as short as two hours rather than five to six hours. Other people, hands up, Matt Walker, have a version of that gene that is not very effective at clearing out the caffeine, and therefore their half-life sort of sensitivity could be somewhere between eight to nine hours. So we understand that there are individual differences, but overall, I guess the top line here is drink coffee and understand that it's not the caffeine, it's the coffee that's the benefit, and the dose makes the poison. Is there some aspect to it that's, it's like a muscle in terms of all the combination of letters and numbers that you just said? Is there some aspect that if I can improve the quarter-life, the half-life, could decrease that number if I just practice? Like drink a lot of coffee, it's just like habit, you know, alters how your body's able to get rid of the caffeine. Not how the body is able to get rid of the caffeine, but it does alter how sensitive the body is to the caffeine. And it's not at the level of the enzyme degrading the caffeine. It's at the level of the receptors that caffeine will act upon. Now, it turns out that those are called adenosine receptors, and maybe we can speak about what adenosine is and sleep pressure and all of that good stuff. But as you start to drink more and more coffee, the body tries to fight back, and it happens with many different drugs, by the way, and it's called tolerance. And so one of the ways that your body becomes tolerant to a drug is that the receptors that the drug is binding to, these sort of welcome sites, these sort of, you know, picture myths, as it were, that receive the drug, those start to get taken away from the surface of the cell. And it's what we call receptor internalization. So the cell starts to think, gee whiz, you know, there's a lot of stimulation going on, this is too much. So I'm just going to, when normally I would, you know, coat my cell with, let's just say five of these receptors, for argument's sake, things are going a little bit too ballistic right now. I'm going to take away at least two of those receptors and downscale it to just having three of those. And now you need two cups of coffee to get the same effect that one cup of coffee got you before. And that's why then when you go cold turkey on coffee, all of a sudden the system has equilibrated itself to expecting X amount of stimulation. And now all of that stimulation is gone. So it's now got too few receptors and you have a caffeine withdrawal syndrome. And that's why, for example, with, you know, drugs of abuse, things like heroin, when people go into abstinence, you know, as they're sort of moving into their addiction, they will build up a progressive tolerance to that drug. So they need to take more of it to get the same high. But then if they go cold turkey for some period of time, the system goes back to being more sensitive again. It starts to repopulate the surface of the cell with these receptors. But now when they reuse and they fall off the wagon, if they go back to the same dose that they were using before, you know, 10 weeks ago or three months ago, that dose can kill them. They can have an overdose. Even though they were using the same amount at those two different times, the difference is that it's not the dose of the drug, it's the sensitivity of the system. And that's the same thing that we see with caffeine. In terms of training the muscle, as it were, is the system becomes less sensitive, can calibrate. Is there a time, the number of hours before bed, that's a safe bet to most people to recommend you shouldn't drink caffeine this many hours? Like, is there an average half-life that you should be aiming at? Or is this advice kind of impossible because there's so much variability? There is huge variability. And I think everyone themselves, you know, to a degree knows it, although I'll put a caveat on that too, because it's a slightly dangerous point. So the recommendation for the average adult and who, where is the average adult in society? There is no such thing, but for the average adult, it would be probably cutting yourself off maybe 10 hours, you know, before. So assuming a normative bedtime in society, I would say try to stop drinking caffeine, you know, before 2 p.m. and just keep an eye out, you know. And if you're struggling with sleep, dial down the caffeine and see if it makes a difference. Can I ask you about sleep and learning? So how does sleep affect learning? Sleep before learning, sleep after learning, which are both fascinating kind of dynamics of the mind's interaction with this extra conscious state. Yeah, sleep is profoundly and very intimately related to your memory systems and your informational systems. The first, as you just mentioned, is that sleep before learning will essentially prepare your brain almost like a dry sponge, ready to sort of, you know, initially soak up new information. In other words, you need sleep before learning to effectively imprint information into the brain, to lay down fresh memory traces. And without sleep, the memory circuits of the brain, and we know we've studied these memory circuits, will, you know, they essentially become waterlogged, as it were, for the sponge analogy, and you can't absorb the information as effectively. So you need sleep before learning, but you also need sleep, unfortunately, after learning too, to then take those freshly minted memories and effectively hit the save button on them. But it's nowhere near as quick as a digital system. It takes hours because it's a physical biological change that happens at the level of brain cells. But sleep after learning will cement and solidify that new memory into the neural architecture of the brain, therefore making it less likely to be forgotten. So, you know, I often think of sleep in that way as, it's almost sort of future-proofing information. In what way? Well, it means that it gives it a higher degree of assurance to be remembered in the future rather than go through the sort of degradation that we think of as forgetting. So the brain has, in some ways by default, you know, there is forget, and actually I would love to, I was going to say sleep is relevant for memory in three different ways, but I'm going to amend that and say this four different ways, which is learning, maintaining, memorizing, abstraction, assimilation, association, and then forgetting, which the last one sounds oxymoronic based on the former three, but I'll see if I can explain. So sleep after learning then sort of, you know, sets that information like amber in, you know, in solidification. The third benefit, however, is that sleep, we've learned more recently is much more intelligent than we ever gave it credit for. Sleep doesn't simply just take individual memories and strengthen them. Sleep will then intelligently integrate and cross-link and associate that information together. And it's almost like informational alchemy so that you wake up the next morning with a revised mind wide web of associations. And that's probably the reason that, you know, you've never been told to stay awake on a problem. You know, and in every language that I've inquired about that phrase or something very similar seems to exist, which means to me that this creative associative benefit of sleep transcends cultural boundaries. It is a common experience across humanity. Now, I should note that I think the French translation of that is much closer to, I think you sleep with a problem, whereas the British, you sleep on a problem. The French, you sleep with a problem. I think it says so much about the romantic difference between the British and the French, but let's not go there. That's brilliant. So- Such a subtle, but such a fundamental difference, yeah. Yeah, goodness me. You sleep with the problem. Yes, exactly. That's why I love the French. So, and we can just double click on any one of these and go into detail, but the fourth, I became really enchanted by about eight years ago in our research, which was this idea of forgetting. And I started to think that forgetting may be the price that we pay for remembering. And in that sense, there is an enormous benefit to letting go. And you may be thinking, that sounds ridiculous. I don't want to forget. In fact, my biggest problem is I keep forgetting things, but the brain has a, well, we believe, has a finite storage capacity. We can't prove it yet, but my suspicion is that that's probably true. It doesn't have an infinite storage capacity. It has constraints. If that's the case, we can't simply go through life being constantly informational aggregators, unless we are programmed to say we've got a hard drive space of about 85 to 90 years and we're good and we can do that. Maybe that's true. I don't think that's true. I think forgetting is an incredibly good and useful thing. So for example, it's not beneficial from an evolutionary perspective for me to remember where I parked my car three years ago. So it's important that I can remember today's parking spot, but I don't want to have the junk kind of DNA from a memory perspective of where I parked my car two years ago. Now, I actually have, in some ways, a problem with forgetting. I'm, and again, I'm not trying to sort of be laudatory, but I tend not to forget too many things. And I don't think that that's a good thing. And there's a wonderful neurologist, Luria, who wrote a book called The Mind of the Mnemonicist. And it was a brilliant book, both because it was written exquisitely, but he was studying these sort of memory savants who basically could remember everything that he gave them. And he tried to find a chink in their armor. And the first half of the book is essentially about him seeing how far he can push them before they fail. And he never found that place. He could never find a place where they stopped remembering. And then in his brilliance, he turned the question on its head. He said, not what is the benefit of constantly remembering, but instead, what is the detriment to never forgetting? And when you start to realize his descriptions of those individuals, it's probably a life that you would not want. But it's as fascinating, both from a human perspective, but also AI perspective. There's a big challenge in the machine learning community of how to build systems that are able to remember for prolonged periods of time, lifelong continuous learning. So where you build up information over time. So memory is one of the biggest open problems in AI and machine learning. But at the same time, the right way to formulate memory is actually forgetting, because you have to be exceptionally selective at which kind of stuff you remember. And that's where the step of assimilation, integration, that you're referring to is really important. I mean, we forget most of the things. And the question is exactly the cost of forgetting at the very edge of stuff that could be important or could not be. How do we remember or not those things? Like for example, I've, you know, doing a podcast, I've become cognizant of one feature of my forgetting that's been problematic, which is I forget names and titles of books and so on. So when I read, I remember ideas. I remember quotes. I remember statements and like, that's the space in which I'm thinking. But when you communicate to others, you have to say this person in this book said that. So it's the same thing with like Andrew Huberman is masterful at this. It's this important academia, remembering the authors of a paper and the title of the paper as part of remembering the idea. And I've been feeling the cost of not being able to naturally remember those things. And so that's something I need to sort of work on. But that's an example. You're good with faces? Yes, very good at faces. But not good with names. So I'm exactly like you. And there is, you know, an understanding of that in the brain too. We understand that there is partitioning of those in terms of the territory of the brain that takes care of faces and facts and places and they can be separate. So I will never forget a face, but you know, and as I said, I usually forget very little, but for some reason names are a struggle. I think in some ways because I'm probably just a slightly anxious person. So when you first meet someone, which is usually the time when a name is introduced, you know, you were saying you were sort of anxious maybe about sort of sitting down with me, but I find that a little bit, you know, activating. And so it's not as though there's anything wrong with my memory. It's just the emotional state I'm in when I'm first meeting someone. You know, it's a little bit disturbing, but I will never forget that face. I completely relate to that because I almost don't hear people's names when they tell me because I'm so anxious. Yeah, yeah. But I think there's certain quirks of social interaction that show that you care about the person, that you remember that person, that they matter to you, that they had an impact on you. And one of the ways to show that is you remember their name. But that's a quirk to me because there's a lot of people I meet have a deep impact on me, but I can't communicate that unless I know their name, unless I know some of the details that we humans seem to use to communicate that we remember each other. What I remember well is the feeling we shared, is the experience we shared. What I don't remember well is the detailed labels of those experiences. And I need to certainly work on that. I don't know. I think it's, you know, just allowing yourself to be innate and who you are is also a beautiful thing too. I'm not suggesting it's not important to try and better oneself. But I also sometimes worry about the misery that that puts us in. But like you, I will, I do struggle with it. But I know the first time when we met in the lobby, I know exactly what you look like. I know that you were wearing headphones. I know the shape and the size of those headphones. You didn't have your black jacket on. I know exactly what the weave of your shirt looked like. I know what your shoes look like. And I knew exactly the height of your, the end of your pants from the top of your shoes. And so those things I don't forget, you know, and I can remember when people, I met people, you know, two years ago and I'll say, oh yes, we met there. And I remember you had those fantastic, you know, boots on. I thought they were a bloody great pair of boots, you know. And they're like, how do you, I didn't even remember what I was wearing that day. It's fascinating. Yeah, I'm the exact same way, but you can't until we have Neuralink or something like that, we can't communicate that you remember all those things. I know, that's what I want. So you have to be able to use tricks of human communication for that. But so that, I mean, that's the, it's ultimately is a trick of like, which to remember, which to forget. Right. And the forgetting is so, it's so fascinating to say this. I mean, it seems to be deeply connected to that assimilation process. So forgetting, you try to fit all the new stuff into this big web of the old stuff and the things that don't fit, you throw out. I think the assimilation, the way I've been thinking about it with sleep, and it's particularly sort of dream sleep that we think can help with this assimilation, is that during wake, we have one version of associative processing. And what I mean by that is we see the most obvious connections. So I think of wakefulness as a Google search gone right. Whereas I see dream sleep as doing something very different. I think dream sleep is a little bit like group therapy for memories, that everyone gets a name badge and sleep gathers in all of the individual pieces of the day. And it sort of starts to get you to, forces you in fact, to speak to the people, not at the front of the room that you think you've got the most obvious connection with, but to speak with the people all the way at the back of the room, that at first you think, I've got no obvious connection with them at all. But once you get chatting with them, you learn that you do have a very distant non-obvious connection, but it's still a connection on the same. And it's almost as though you're doing a Google search where I input Lex Friedman and it doesn't take me to the first page of your home site. It takes me to page 20, which is about some like field hockey game in Utah. Now it turns out that there actually is a link if I look at it, it's a distant non-obvious one. And to me, I find that exciting because when you fuse things together that shouldn't normally go together, but when they do, they cause marked advances in evolutionary fitness, it sounds like the biological basis of creativity. And that's exactly what I think dream sleep and the algorithm of dream sleep is designed to do. You know, it's not a Boolean like system where you have, you know, the sort of assumptions of true and false, you know, maybe it's more fuzzy logic system. And I think REM sleep is a perfect environment within which we do, you know, it's almost like memory pinball. You know, you get the information that you've learned during the day and then you pull the lever back and you shoot it up into the attic of your brain. You know, this cortex filled with all of your past historical knowledge and you start to bounce it around and see where one of those things lights up and you build a new connection there and you build another one there too. You're developing schemas. And so in that way, I think you could argue, you know, we dream, therefore we are. Yeah. Yeah, so in terms of this line between learning and thinking through a new thing that seems to be deeply connected, there's this legendary engineer named Jim Keller who keeps yelling at me about this. He says it's very effective. He likes to, for difficult problems before bed, think about that difficult problem. We're not talking about like drama at work or all that kind of stuff. No, like a scientific for him, engineering problem. He likes to like intensely think about it as to prime his mind before sleep and then go to sleep. And then he finds that the next day, he's able to think much clearer and there's new ideas that come, but also just, I guess it's more well-integrated. And sometimes during the process of, like he's able to like wake up and like see new insights. That's right. If he's deeply sort of aggressively thinking through a problem. And there's many scientific, you know, demonstrations of this, you know, the Mendeleev with the periodic table of elements, you know, he was trying for months to understand. I mean, talk about an ecumenical problem of epic proportions. Here's your question today. You have to understand how all of the known elements in the universe fit together in a logical way. Good luck, take care. It was non-trivial at the time. And he would try and try. He was so obsessed with it. He created playing cards with all of the different elements on. And then he would go on these long train journeys around Europe and he would just sort of deal these cards in front of them. And he would shuffle them, shuffling and shuffling. And he would just try to see if he could find what the answer was. And then, so the story goes, you know, he fell asleep and he had a dream. And in that dream, you know, all of these elements started to dance and play around and they snapped into a logical grid, you know, atomic weights, et cetera, et cetera. And it wasn't his waking brain that solved the problem. It was his sleeping brain that solved the impenetrable problem that his waking brain could not. And there's been count, you know, even in the arts and in music, some wonderful dreams, you know, Frankenstein, Mary Shelley's epic Gothic novel came to her in a dream at Lord Byron's home. And then we've got, you know, Paul McCartney. Yesterday, the song came to him in a dream. He was filming, gosh, what was the movie? I don't recall it. I should be shot because I'm from Liverpool myself. But he was on Wimpole Street in London and filming. And he came up with that song, the melody in his sleep, not to be outdone by the Beatles. And by the way, Let It Be also came from a dream that McCartney had. People usually give it, you know, religious overtones. You know, Mother Mary comes to me speaking words of wisdom, let it be. If you've ever asked who Mother Mary is, it's not the, you know, the biblical content. It's his mother. It's Mary McCartney. And she came to him in a dream and gifted him the song. But the best story I've heard is not to be outdone by the Beatles, the Stones, Keith Richards, who I think once was suggested that, who was it? It was a comedian who was saying that in an interview with Rolling Stone, Keith Richards suggested or inferred that young kids should not do drugs. And they said, well, look, young kids can't do drugs because you've done all of the drugs. And I always thought that, but Keith Richards described, he would always go to bed with his guitar and a tape recorder. And then probably he would have a whole set of other things in the bed with him and who knows how many other people, but anyway. And then he said in his autobiography and I'm paraphrasing here, but one morning I woke up and I realized that the tape had recorded all the way to the end. So I rewound the tape and I hit play and there in some kind of ghostly form were the opening chords to Satisfaction, the most famous successful Rolling Stone song of all time. Followed by then 43 minutes of snoring. That's awesome. That riff came to him, one of the most famous riffs in all of rock and roll came to him by way of a dream inspired insight. So I think there is too many of those anecdotes and we've now got the science. I don't rely on anecdotes as science. We've now done the studies in the laboratory and we can reliably demonstrate that sleep inspires creativity, inspires problem solving capacity. Well, the interesting thing is, is it possible to some of the ideas that you talk about to turn them into a protocol that could be practiced rigorously? So what Jim Keller espouses is saying, not just the fact that sleep helps you increase the creativity, but turn it into a process. Like literally, like don't do it accidentally. Like an athlete does certain things to optimize their performance. They have a training routine, they have a regimen of like cycling and sprints and long distance stuff. In the same way, thinking about your job as an idea generator in the engineering space is like, this is good for my performance. So like for an hour before bed, think through a problem like every night and then use sleep to work through that problem. I mean, these are the first person that I heard like of the people I really respect that do like what I do, which is like programming engineering type work, like using sleep, not accidentally, but with a purpose, like using sleep. You know, that's just basically the difference between, as you said, a passive approach to it versus an active deterministic or hope for a deterministic approach to it. In other words, that you are actually trying to harness the power of sleep in a deliberate way rather than an unthoughtful way. I still think that mother nature, through the 3.6 million years of evolution has probably got it mostly figured out in terms of what information should be uploaded at night and worked through. I think her algorithm is probably pretty good at this stage. It's not to suggest though that, you know, we can't try to tweak it and nudge it. You know, it's a very light hand on the tiller is what he's doing. I don't think there's anything wrong with that. You know, just like, for example, for me, fasting has improved my ability to focus deeply and productivity significantly. And in that same way, you know, it's possible that playing with these ideas of thinking before bed or some hours before bed or some playing with different protocols will have a significant leap over what mother nature naturally does. So if you let your body do what it naturally does, you may not achieve the same level of performance because mother nature has not designed us to think deeply about chip design or programming artificial intelligence systems. Well, she's gifted us the architecture and the capacity to do that. What we do with that is, you know, is what life's experience dictates. She gives us the blueprint to do many, you know. Well, if I were to sort of introspect and self-analyze what mother nature wants me to do, I think given my current lifestyle that I have food in the fridge and a bed to sleep on, I think what mother nature wants me to do is to be lazy. And so I think I'm actually resisting mother nature because so many of my needs are satisfied. And so I have to resist some of the natural forces of the body and the mind when I do some of the things I do. So there's that dance, you know, like I've been thinking about doing a startup and that's obviously going against everything that my body and mind are telling me to do because it's going to be basically suffering. But the only reason I want- As you know, it will be over. Yes. But nevertheless, there's some kind of inner drive that wants me to do it. And then you start to ask the question, well, how do you optimize the things you can optimize like sleep, like diet, like the people that you surround yourself with in order to maximize happiness and performance and all those kinds of things without also over-optimizing. And that's such an interesting idea from an engineer. So as you may know, you don't often get those kinds of ideas from engineers. Engineers usually just don't read books about sleeping. They're usually like, they're not the healthiest of people. I think that's changing over time, especially Silicon Valley, especially the tech sector. People are starting to understand what's a healthy lifestyle but usually they're kind of on the insane side, especially programmers. But it's nice to hear somebody like that use sleep and use some of the things you talk about strategically, on purpose. You know, to that idea of not just trying to use what mother nature gave, but seeing if you can do something more or different. In a conservative mindset, I would then pose the question at what cost? Because when you do something perhaps that deviates from the typical pre-programmed, mother nature's program, I suspect it usually comes at the cost of something else. So maybe he is able to direct and focus his sleeping cognition on those particular topics that will gain him better problematic resolution the next day when he wakes up. The question is though, at what cost of the other things that didn't make it onto the menu of the finger buffet of sleep that night? And is it that you don't process the emotional difficulties or events and therefore you are less emotionally resolved the next day, but you are more problem resolved the following day. And so I always try to think, and I truly don't want to sound puritanical either about sleep. And I think I've come off that way many a times, especially when I started out in the public. The tone of the book in some ways, you know, I look back and think, could I have been a little softer? And the reason was I was that way back in, but when I started writing the book, which was probably something like 2014 or 15, sleep was the neglected step-sister in the health conversation of the day. And I was just so sad to see the amount of suffering and disease and sickness that was caused by insufficient sleep. And for years before I'd been, you know, doing public speaking and I'd tell people about the great things that happen when you get sleep, people would say, that's fascinating. And then they would go back and keep doing the same thing about not sleeping enough. And then I realized you can't really speak about the good things that happen. It's like the news, what bleeds leads. And if you speak about the alarmingly bad things that happen, people tend to have a behavioral change. And so the book as a consequence, I think probably came out a little bit on the strong side of, you know, trying to convince people. You were trying to help a lot of people and that's a powerful way to help a lot of people. I was genuinely trying to help people, but you know, certainly for some people for whom sleep does not come easy, then it was probably, you know, a tricky book to read too. And I think I feel more sensitive to those people now and empathetically connected to them. So I think, again, the point was simply that I don't mean to sound too puritanical in all of this. And the same way with, you know, caffeine and coffee. I am just a scientist and I am not here to tell anyone how to live their life. That is not my job at all. And life is to be lived to a degree. And life is to be lived if you want to do a startup. All I want to do is empower people with the understanding of the science of sleep. And then you can make an informed choice as to how you want to live your life. And I offer no judgment on how anyone wishes to live their life. I just want to try and see if the information that I have about sleep would alternatively change how you would think about your life decisions. And if it doesn't, no problem. And if it does, I hope it's been of use. Well, maybe this is me trying to justify my lifestyle to you. But Dr. Seuss said, you know you're in love when you can't fall asleep because reality's finally better than your dreams. I love that quote too. Okay. My sleeping schedule is complicated. And it has to do primarily with the fact that I love basically everything that I do. And that love takes a form that may not appear to be love from the external observer perspective. Because it often includes struggle. It often includes something that looks like stress, even though it's not stress. It's like this excitement, it's this turmoil and chaos of passion, of struggling with a problem, of being sad and down to the point even depressed of how difficult the problem is, the disappointment that the last few weeks and months have been a failure and self-doubt, all that mix. But I love it. And a part of that is sometimes staying up all night, working on a thing I'm really passionate about. And that means sleep schedules that are just like, you know, sometimes sleeping during the day, sometimes very often sleeping very little, but taking naps that are like an hour, two hours or so on, that kind of weird chaos. Now, also to try to give myself backup, I was trying to like research yesterday, is anybody else productive while like this? And there's of course a lot of anecdotal evidence and some of it could be just narratives that people have told to the public when in reality they sleep way more. But there's a bunch of people that, you know, have not, are famous for not sleeping much. So on the topic of naps, I read this a long time ago and I checked this, Churchill was big on big naps and is actually just reading more about Winston Churchill's sleep schedule is very much like mine. So I basically wanna give myself the opportunity to at night, to stay up all night if I want to. And a good nap is a big part of that in the late evening. Like I'll often, that's just destroy social life completely, but I'll often take a nap in the late afternoon or the evening and that sets me, if I want to stay up all night. And things like that, like I've read that Nikola Tesla slept only two hours a night, Edison, the same three hours, but he actually did the polyphasic sleep like where it's just a bunch of naps. What can you say about this madness of love and passion of loving everything you do and the chaos of sleep that might result in? I love the Seuss quote. And I've had that experience too, like you, I adore what I do. If someone gave you enough money to live the rest of your life, got a roof above my head, rice and beans on the table, and they said, you don't have to work anymore. I would do nothing different. I would do exactly, you know, the sounds a little crass and I hope it doesn't sound this way, but being a scientist is not what I do, it's who I am. When that's the case, sleep, working out, showering and eating are the things that I do in between my love affair with sleep. Yeah. I fell asleep like a blind roofer. And it was a love affair that started 20 years ago and I remain utterly besotted today. It's the most beguiling thing in the world to me. And I could easily, and I have, you know, it's kept me up at night. When my mind is fizzing with experimental ideas or I think I've got a new hypothesis or theory, I will struggle with sleep. I really will. It doesn't come easy to me because my mind is just so on fire with those ideas. So I understand the struggle. But, you know, I couldn't advocate from a scientific perspective, the schedule, because the science just doesn't, you know, I would feel as though I'm doing you a disservice to say it's okay, you know, that that won't come with some blast radius, some, you know, health consequences. You know, you can add Margaret Thatcher and Ronald Reagan to that list too. Both of them were very, you know, proud chess beaters of how little sleep that they get. Thatcher said four hours, Reagan, something similar, you know, and I, knowing the links that we now know between sleep and Alzheimer's disease, I've often wondered whether it was coincidental then that both of them died of the terrible disease of Alzheimer's meaning, you know, maybe it doesn't get you by way of, you know, being popped out of the gene pool in a car accident, because you had a microsleep at the wheel at age 32, or it doesn't get you at 42 with, you know, heart attack, or even 52 with cancer or a stroke, maybe it gets you in your 70s. I think the elastic band of sleep deprivation can stretch only so far before it snaps. And it ultimately seems to snap, you know, Nikola Tesla, I think he, Nikola Tesla, he, I think, died of a coronary thrombosis, I believe. And there was a wonderful study done out of Harvard where they took a group of people who had no signs of cardiovascular disease. And what they found is that when they track them for years afterwards, they were completely healthy to begin with. Those people who are getting less than six hours of sleep ended up having a 300% increased risk of developing calcification of the coronary artery, which is the major sort of corridor of life for your heart. When someone says, you know, he died of a massive coronary, it's because of a blockade of the coronary artery, you know, and Tesla, you know, passed away from a coronary thrombosis. We also know that insufficient sleep is linked to numerous mental health issues. We know that Churchill had a wicked battle with depression. Gosh, my goodness, he used to call it black dog that would come and visit him. And I think many of his paintings, he was exquisite painter, but some of them would depict his darkness with depression as well. You know, Edison is interesting. People have argued that he would short sleep and he didn't put much value in sleep, whether or not that's true, we don't know, but he was a habitual napper. You're right, during the day, I've got some great pictures of him on his inventor's bench taking a nap. And in fact, I believe he set up nap cots around his house so he could nap. But what we also know is that he, again, coming out of Harvard just a couple of months ago, demonstrated very clearly that polyphasic sleep is associated with worse physical outcomes, worse cognitive outcomes, and especially worse mood outcomes. So from that sense, you know, sleeping like a baby is not perfect for adults. There's a fascinating dance here of the mean and the extreme, like the average and the high performers. So I, I think this gets to like the meaning of life kind of discussion, but let's go there. So, well, and also happiness. So when studying sleep and when studying anything like diet and exercise, I think you have to really get a lot more data about individuals to make a conclusive statement. That's when people talk about like, is meat, red meat, good for you or bad for you, right? It's just so often correlated with other life decisions when you choose to eat meat or not. My sense is that whatever life decisions you make, if they reduce stress and lead to happiness, that's also going to be a big boost that needs to be integrated into the plots in the science, right? So I'll give you an example of somebody who's unarguably seen as unhealthy. My friend, Mr. David Goggins. So he's clearly obviously almost on purpose destroying his body. And to say that he's doing the wrong thing or the unhealthy thing feels wrong. But I'm not sure exactly in which way he feels wrong. One of the things I'm bothered by, and again, I apologize for the therapy sessions, a framework of this, but I'm bothered by the fact that a lot of people tell me or David that they're doing things wrong. A lot of people in my life, when they see me not sleep, they'll tell me to sleep more. Now they're correct, but one fundamental aspect that I'd like to complain about is not enough people, almost nobody, especially people that care for me, will come to me and say, you have a dream, work harder. It's like the healthy thing should be a component of a life well lived, but not everything. And I don't know what to do with that because you certainly don't want to espouse it. And just like you said, when you were working in your book, there is a belief that sleep was a secondary citizen in the full spectrum of what's a healthy life. But at the same time, I'm bothered by in Silicon Valley and all these kinds of work environments that I get to work with with engineers is there's, to me, too much focus on work-life balance. What that usually starts meaning is like, yeah, yeah, of course, it's good to have a social life, it's good to have a family, it's good to eat well and sleep well, but we should also discover our passion. We should also give ourself a chance to work our ass off towards a dream and make mistakes and take big risks that in the short term seem to sacrifice health. And I think, to come back to how you started about David Goggins, who I've never met, but who I admire incredibly and have an immense reverence for the man, you said two things. Is it wrong to do those things to yourself? And is it unhealthy to do those things to yourself? I disagree with the former and I agree with the latter. So from a health biological medicine perspective, sleeping in the way that you've described or that other people may be sleeping in terms of insufficient amounts, now to your point too about into individual differences, usually when I see a bar graph and a mean, I usually say, show me your variance. I want to see your variance. In other words, show me the distribution of that effect. How many people were below the mean? How many, is it all tightly clustered around this one thing? So it's a very robust effect or was this huge fan of effect where for some people, there was no effect at all and other people, there was a whopping effect and everything in between. So I don't discount into individual variability, but, and I will come back to those two points about, is it wrong and is it unhealthy in just a second? When it comes to sleep, we have found huge amounts of inter-individual differences in your response to a lack of sleep. But one of the fascinating things, so let's say that I take you and we're going to measure your attention, your emotion, your mood, your blood pressure, your blood sugar glucose regulation, your autonomic nervous system and your different gene expression. Let's say I'm just going to measure a whole, kaleidoscope of different outcomes, brain and body. And I find that on our measure of cognition, on your attentional ability to focus, you are very resilient. You just don't show any impairments at all, even after being awake for 36 hours straight. Does that mean that you are resilient in all of those other domains as well? The answer is no, you're not. So you can be resilient in one, but very vulnerable in another. And we've not found anyone who isn't at least vulnerable in one of those domains, meaning that it's somewhat safe to say that not getting sufficient sleep will lead to some kind of impairment in any one given individual. It may not be the same impairment, but it's likely to be an impairment. But to come back to the question, I think it's wrong to tell anyone that it's wrong to do what they're doing, even if they are compromising their sleep, even if they're compromising their mental health. You know, as long as they're not hurting anyone else, then I think the answer is that's that person's choice. Yeah, but that's that person's life. I'd like to push back further. So see, the way you kind of said it, yes, you're absolutely right. But I would like to say a stronger statement, which is you should let go of that judgment of somebody is wrong and allow yourself to be inspired by the great heights they have reached. So take yourself out of the seat of being a judger of what is healthy or not, and appreciate the greatness of a particular human. You watch the Olympics, the kind of things that some athletes do to reach the very heights. The Olympics are taking years off their life. They suffer depression after the Olympics often. Their physiology is disastrous. Everything, their personal life, their psychology, their physiology, everything. It's a giant mess. So the question is about life. And healthy now means longevity, quality of life over a prolonged period of time, optimum performance over a prolonged period of time. But to me, beauty is reaching great heights. And there's a dance there that sometimes reaching great heights requires sacrifice of health and not like a calculation where you sat down on a sheet of paper and say, I'm going to take seven years off my life for an Olympic gold medal. No, it requires more chaotic journey that doesn't do that kind of calculus. And I just want to kind of speak to the, in the culture that struggles of what is healthy and not, we want to be able to speak to what is healthy and at the same time be inspired by the great heights that humans reach no matter how healthy or unhealthy they live. Yeah, I agree with that. I think if that's a flag you're hoisting, I will definitely salute it because it really depends, you know, what are you trying to optimize for in your life? And if you are, I think the only danger potentially with that mindset is that if you look at many of the studies of old age and end of life, most people say I never look back on my life and wish I worked harder. I wish instead I'd spent more time with family, friends, and engaged in that aspect. Now I'm not saying though, coming back to your point, that that is the standard rubric for everyone. I don't believe it is too. And there are many things that you and I are both benefiting from today, even in the field of medicine, where people have sacrificed their own longevity for the quest of solving a particular medical problem. And they died quicker because of their commitment, because they wished to try and solve that problem in their pursuit of greatness scientifically. And I now benefit. Am I grateful that they did that? Incredibly grateful. You know, a simpler demonstration is this. If tonight at 4 a.m. in the morning, I have a ruptured appendix, I have an appendicitis, I am incredibly grateful that there is an emergency team that will take me to the hospital at 4 a.m. in the morning. They are awake, they're not sleeping, and they saved my life. And that's part of what their life's mission and quest is. And they saved another's life by, in some ways, shaving a little of their own off. So I don't take, I have no umbrage with that mentality at all. I think you just have to be very clear about what you're optimizing for. And my worry is that most people fall into the rat race, and they never actually ask the question, why am I doing this? If you're just working nine to five, and you allow that nine to five to stretch into much longer, but it's nevertheless a job that's kind of like wears you down, that's one thing. Another thing is when it is a, like, you're, it's a dream. Your life mission. It's a life mission. To accomplish. And for that, I think as long as you know what it is that you could be doing to yourself, and you are comfortable and A-okay with that, I have no problem with that at all. Again, as I said, as a scientist, I cannot, should not, and will not tell anyone what they should do with their life. All I want you to be able to do is say, okay, now I understand more about the, previously these would be known unknowns, and these were the unknown unknowns. And now I am slightly more cognizant. I have more knowns than I had before regarding my sleep and my health. Knowing that information, do I still choose to make this decision? And if that's what I offered, then I think I've done my job. That's all I want to offer is just added information into the decision algorithm, and what you end up choosing as an output of that algorithm has nothing to do with me. It's not my business, and I will never judge anyone for it. And as I said, I'm immensely grateful for people who have sacrificed much in their lives to give me what I have. So you're saying as long as the sacrifice, sort of grounded in knowledge of what the sacrifice is, that sleep is important, all those kinds of things. And that you're comfortable with it, that it is your conscious choice rather than feeling as though you're trapped or that you are just, you haven't thought about it. And you start that job at age 32, and then you wake up the next morning and you're 65, and you think, where did my life go? What was I doing? That to me, I would feel, I would want to hug you, and I would say, I'm just, and I'm not saying, I don't mean to sound belittling here at all. I would just not wish that for you. I would wish that you could have thought about what it was that you're doing and not have that regret. Yeah, so I guess I'm, this is for you, the listener. I'm coming out of the closet here a little bit. The fact that I enjoy the madness I live in, so please do not criticize me, embrace me. I understand the sacrifices I'm making. I enjoy sleeping on the floor when I'm passionately programming all night and just pass out on the carpet. I love this life, okay? So it's, but it's definitely something I think about that there's a balance to strike where- I just want you to have as much of it though. Of life. See, quality of life is important. I should have said, I want you to have as much high quality life. And if high quality of life means I spend five decades on this planet, but yet in that time I am thrilled every day. I'm turned on every day by what I do. And I reveled in this thing called my life's work. I think that that is a 50 year journey of absolute delight and fulfillment that you should take. I think about my death all the time. I meditate on death. I'm okay to die today. So to me, longevity is not a significant goal. I'm so happy to be alive. I don't even think it would suck to die today. I'm as afraid of it today as I will be in 50 years. I don't wanna die as much today as I will in 50 years. There's of course all these experiences I would like to have, but everything's already amazing. It's like that Lego movie. I don't know. To me, I just wanna keep doing this. And there's of course things that could affect, like you mentioned dementia and these deterioration of the mind or the body that can significantly affect the quality of life. And so you want to- I'm not sure you're aware of that. That's the price you pay for the entry into this magical kingdom that you are experiencing, which is a lovely thing. I feel privileged too. I can't believe the life that I live. It's incredible. And just like you, I think about mortality a great deal. I think a lot about death, but I don't worry about death. I probably, with the exception of the potential pain that comes before it, that some people, many people can suffer, that maybe concerns me, but I actually think about mortality as a tool, as I use it as a lens through which I can then retrospect. And by placing myself at the point of future mortality, I can then use it as a retrospective lens to focus and ask the following question, is there anything I feel I would regret and therefore change in the life that I currently have now? That's the way I meditate and use mortality as a question, is to try and course correct and focus my life. I worry not about dying, but I like to think about death as a way to prioritize my life, if that makes sense. I don't know if that makes sense. No, it makes total sense to decide how do you want to live today so that in the future you do not regret the way you've lived today. Right, and to place yourself in the future at your point of mortality is one way to, I think, as an exercise to retrospectively look back and not lose out on informed choices that you could otherwise lose out on if you weren't thinking about mortality. Yeah, it clarifies your thinking. So I mentioned I sleep on the floor, take naps and power naps and it's just kind of madness. Is there weirdnesses to your own sleep schedule as a scientist that does incredible work, has a lot of things going on, has to lead research, has to write research, has to be a science communicator, also have a social life, all those kinds of things. Is there certain patterns to your own sleep that you regret or you participate in that you find you enjoy? Is there some personal stuff, quirks, or things you're proud of that you do in terms of your sleep schedule? The funny thing about being a sleep researcher is that it doesn't make you immune to the ravages of a difficult night of sleep and I have battled my own periods of insomnia in my life too. And I think I've been fortunate in ways because I know how sleep works and I know how to combat insomnia, I know how to get it under control. Because insomnia in many ways is a condition where all of a sudden your sleep controls you rather than you control your sleep. Oh yeah, that's a beautiful way to put it, yeah. And I know when I'm starting to lose control and it's starting to take control, I understand how to regain. But it doesn't happen overnight, it takes a long time. So you've struggled with insomnia in your life? I have, not all of my life. I would say I've probably had three or four really severe bouts. And all of them usually triggered by emotional circumstances, by stress. Stress that's connected to actual events in life or stress that's unexplainable? Well, externally triggered, yeah. It's sort of what we would call reactive stress. And so that's sort of point number one about the idiosyncrasies. The point number two is that when you are having a difficult night of sleep, as a sleep researcher, you basically have become the Woody Allen neurotic of the sleep world. Because at that moment, I'm trying to fall asleep and I'm not, and I'm starting to think, okay, my dorsolateral prefrontal cortex is not shutting down, my noradrenaline is not ramping down, my sympathetic nervous system is not giving way to my parasympathetic. At that point, you are dead in the water for the next two hours and nothing is bringing you back. So there is some irony in that too. I would say for myself though, if there is something I'm not proud of, it has been at times railing against my chronotype. So your chronotype is essentially, are you a morning type, evening type, or somewhere in between? Yeah. And there were times because society is desperately biased towards the morning types. This notion of the early bird catches the worm. Maybe that's true, but I'll also tell you that the second mouse gets the cheese. Yeah, so I think one of the issues- That's a good line. Around, firstly, people don't really understand chronotype because I'll have some people when I'm sort of out in the public, they'll say, look, I struggle with terrible insomnia and I'll ask them, is it problems falling asleep or staying asleep? And they'll say falling asleep. And then I'll say, look, if you are on a desert island with nothing to wake up for, no responsibilities, what time would you normally go to bed and what time would you wake up? And they would say, I'd probably like to go to bed about midnight and wake up maybe eight in the morning. And then I'd say, so what time do you now go to bed? And they'd say, well, I've got to be up for work early, so I get into bed at 10. I'd say, well, you don't have insomnia, you have a mismatch between your biological chronotype and your current sleep schedule. And when you align those two, and I was fighting that for some time too, I'm probably mostly right in the middle. I am desperately vanilla, unfortunately, in many aspects of life, but this included, I'm neither a strong morning type nor a strong evening type. So ideally, I'd probably like to go to bed around 11, 10.30, 11, probably somewhere between 10.30 and 11 and wake up, I naturally wake up usually most days before my alarm at 7.04. And it's 7.04 because why not be idiosyncratic in terms of setting alarms? I love it. And so I- That's kind of awesome, I've never heard about that. That's amazing. I'm gonna start doing that now, setting alarms like a little bit off the- Yeah, I'm never quite sure why we all- It's a celebration of uniqueness. Yeah, and I am quite the odd snowflake in that sense too. So I would usually then try to force myself because I had that same mentality that if I wasn't up at 6.30 and in the gym by seven, that there was something wrong with me. And I quickly abandoned that. But if I look back, if there was a shameful act that I have around my sleep, I think it would be that for some years until I really started to get more detailed into sleep. And now I have no shame in telling people that I will probably usually wake up around 6.45 naturally, sometimes seven when people are looking at me thinking, you're a sloth, you're lazy. And I don't finish my daily workout until, I'm not working until probably nine o'clock in the morning. I'm thinking, what are you doing? Now I will work late into the day. If I could, I would work 16 hours. It's my passion just like yours. So I don't feel shame around that, but I have changed my mentality around that. It's complicated because I'm probably happiest going to bed, if I'm being honest, like at 5 a.m. That's fine, you're just an extreme evening type. But the problem is, it's not that I'm ashamed for it, I actually kind of enjoy it because I get to sleep through all the nonsense of the morning and the, isn't that a beautiful thing? Like people are busy with their emails and I just am happy as a cow. And I wake up, after all the drama has been resolved. Yeah, and cows are happy and the drama has been resolved. Exactly. But in society you do, especially, I mean, this is what I think about is, when you work on a larger team, especially with companies, you are, everybody's awake at the same time. So that's definitely been a struggle to try to figure out, just like you said, how to balance that, how to fit into society and yet be optimal for your current type. You said, yeah. You have to sleep in synchrony with it and harmony. Because normally what we know is that if you fight biology, you'll normally lose. And the way you know you've lost is through disease and sickness. You said you suffered through several bouts of insomnia. Is there, aside from embracing your chronotype, is there advice you can give how to overcome insomnia from your own experience? Right now, the best method that we have is something called Cognitive Behavioral Therapy for Insomnia or CBTI for short. And you work with, for people who don't know what it is, you work with a therapist for maybe six weeks, and you can do it online, by the way. I would recommend probably jumping online. It's just the easiest. And it will change your beliefs, your habits, your behaviors, and your general stress around this thing called sleep. And it is just as effective as sleeping pills in the short term. But what's great is that unlike sleeping pills, when you stop working with your therapist, those benefits last for years later. Whereas when you stop your sleeping pills, you typically have what's called rebound insomnia, where your sleep not only goes back to being as bad as it was before, it's usually even worse. For me, I think I found a number of things effective. The first is that I had to really address what was stressful and try to come up with some degree of meaningful rationality around it. Because I think one of the things that happens, there's something very, talking about conscious states, to come all the way back to, gosh, I don't know, I feel like we've only been chatting for like 20 minutes, but you're gonna tell me it's been a while. Yeah, it's been a while. Okay, I'm desperately, I feel terribly sorry. But let's come back to conscious states, which is where we started. There is something very strange about the night that thoughts and anxieties are not the same as they are in the waking day. They are worse, they are bigger. And I at least find that I am far more likely to catastrophize and ruminate at night about things that when I wake up the next day in the broad light of day, I think it's no one near that bad man. What were you doing? It's not that bad at all. So to gain firstly, some rational understanding of my emotional state that's causing that insomnia was very helpful. The second thing was to keep regularity, just going to bed at the same time waking up. And here's an unconventional piece of sleep advice. After a bad night of sleep, do nothing. Don't wake up any later. Don't go to bed any earlier. Don't nap during the day. And don't drink any more coffee than you would otherwise. Because if you end up sleeping later into the morning, you're then not going to be tired at your normal time at night. So then you're gonna get into bed thinking, well, I had a terrible night of sleep last night. And yes, I slept in this morning to try and compensate, but I'm still gonna get to bed at my normal time. But now you get into bed and you haven't been awake for as long as you normally would. So you're not as sleepy as you normally would be. And so now you sit there lying in bed and it's another bad night. And the same thing is, if you go to bed any earlier, so don't wake up any later, wake up at the same time, don't go to bed any earlier, because then you're just probably your chronotype, your biological rhythm doesn't want you to be asleep. And you think, well, terrible night, I'm gonna get into bed at 9 p.m. rather than my standard 10. I'm just gonna be lying in bed awake for that hour. Naps will take, are a double-edged sword. They can have wonderful benefits. And we've done lots of studies on naps for both the brain and the body. But they are a double-edged sword in the sense that napping will just take the edge off your sleepiness. It's a little bit like a valve on a pressure cooker. When you nap during the day, you can take some of that healthy sleepiness that you've been building up during the day. And for some people, not all people, but for some people, that can then make it harder for them to fall asleep at night and then stay asleep soundly across the night. So the advice would be, if you're struggling with sleep at night, don't nap during the day. But if you are not struggling with sleep, and you can nap regularly, naps are just fine. And we can play around with optimal durations depending on what you want. Just try not to nap too late into the day, because napping late into the day is like snacking before your main meal. It just takes the edge off your sleep hunger, as it were. But that would be, so that's my unconventional second piece of advice regarding insomnia. The third is meditation. I found meditation to be incredibly powerful. I started reading about meditation as I was researching that aspect of the book many years ago. And as a hard-nosed scientist, I thought this sounds very woo-woo. This is sort of, we all hold hands and sing Kumbaya and everything's going to be fine with sleep. I read the data and it was compelling. I couldn't ignore it. And I started meditating, and that was six years ago and I haven't stopped. And I find meditation before bed incredibly powerful. The meditation app companies were perplexed at this at first. They want people to meditate during the day. But when they looked at their usage statistics, they found that they would have people in the morning meditating. And then there's a huge number of people using the meditation app in the evening. What they were doing was self-medicating their insomnia. And they finally, rather than railing against it, they started to see it as a cash cow, rightly so. So I found meditation to be helpful. Having a wind-down routine is the other thing that's critical for me. I can't just go from, because when my mind is switched on, and I think you may be like this too, if I get into bed, that rolodex of thoughts and information and excitement and anxiety and worry is just whirling away, and it's not gonna be a good night for me. So I have to find a wind-down routine. And that makes sense when you realize what sleep is like. Sleep is not like a light switch. Sleep is much more like trying to land a plane. You know, it takes time to descend down onto the terra firma that we call sound sleep at night. And we have this for kids. You know, I don't have children, but a lot of parents will say, you know, we have to have the bedroom, sorry, the bedtime routine. You know, you bathe the kid, you put them in bed, you read them a story. You have to go through this routine, this wind-down routine for them, and then they fall asleep wonderfully. Why do we abandon that as adults? We need that same wind-down routine. So that's been the other thing that's been very helpful to me. So don't do anything different. If you have a bad night of sleep, keep doing the same thing. Manage your anxiety, understand it, rationalize it. Then meditation. And then finally having some kind of disengagement wind-down routine. Those are the four things that have been very helpful to me. That's brilliant. So the regularities really do a lot of work against insomnia. Is there, is it possible to have a healthy sleep life without the regularities? I say that because I'm all over the place and I've gotten good at being all over the place. So I'll often, like what happens, I'll go stretches of time, there'll be some times a month where I, my days are like, this is embarrassing to admit, but they're like- It's just you and I here, it's just you and I. It's like 28 hours or 30 hour days. Yeah. Like I'll just go all the way around, comfortably and happily, I love it. And then there'll be a nap. I mean, if you like add up the hours when I'm just like sleeping as much as I want, it'll probably be like six hour average per 24 hours. Like that kind of, so it works out nicely. Maybe even seven hours, I don't know. But that it's obviously irregular and there's chaos in the whole thing. Right. Like sometimes it's shorter sleep, sometimes it's longer. Is that totally not a good thing, do you think? The best evidence that we have to speak to this question is people who are doing rotating shifts. And unfortunately, the news is not good. They usually have a higher instance of many diseases such as depression, diabetes, cardiovascular disease, obesity, stroke. And again, that's just me communicating the data that we have and I'm not telling you that you should do anything different. The other thing is that there's nothing in your biology that suggests that that's how your body was designed to sleep. It is a system that loves habit. If your circadian clock in your brain is called the suprachiasmatic nucleus, sits in the middle of your brain, had a personality trait, it would be a creature of habit. It loves habit. That's how your biology is designed to work is through very archetypal, prototypical, expected cycles. And when we do something different to that, then you start to see some of the pressure, stress fractures in the system. But again, to your point, if that's something that you don't mind, adopting and understanding, and then I think you should keep doing what you're doing. Yeah, it's complicated. Of course, you have to be a student of your own body and explore it. One of the reasons I wanna have kids is kids enforce a stricter schedule. I think I definitely keep- So I've heard. I definitely feel that I'm not living the sort of data-wise, scientifically speaking, the optimal life. And me just living the way I wanna live day to day is perhaps not the optimal way. And there's certain things that I've seen, very successful people that I know in my life, when they have kids, they actually, their productivity goes up, they get their shit together. There's a lot of aspects that- Regularity, yeah. Yeah, the regularity. I mean, that creature's a habit. That's the thing, that's power. And then you start to optimally use the hours you have in the day. Let me ask you about- Actually, I just have one quick point on that too. We often think about sleep as a cost, but instead I think of sleep as an investment. And the reason is because your effectiveness and your efficiency when you're well-slept typically exceeds that when you're not. And to me, it's the idea of, if I'm going to boil a pot of water, why would I boil it on medium when I could boil it in half the time on high? And I sometimes worry that when I speak to Fortune 500 companies, and they're of this mentality of long hours, getting people to rise and grind. The first point is that after about 20 hours of being awake, a human being is as cognitively as impaired as they would be if they were legally drunk. And the reason I bring that point up is because I don't know any company or CEO who would say, I've got this great team, they're drunk all the time. But we often lord the airport warrior who's flown through three different time zones in the past two days is on email at 2 a.m. and then is in the office at six. And I think there is some aspect, not in all people, but there is sort of some aspect of that slight sleep machismo. And that's not what, you are very different. You are driven by a purity of passion and a very authentic, incredibly genuine goal of wanting to do something remarkable with your life. That's not the issue I think I'm speaking about. It's just simply that I think the, this notion of wanting to be awake for longer to try and get more done can sometimes be at odds with the fact that you can actually get so much more done if you're well slept. And it's this trade off. I actually admire people that take the big risk and work hard, whether that means staying up late at night, all those kinds of things, but it cannot be in the framework, in the context, like what Edison said, which is sleep feels like a waste of time. So like, if you're not sleeping because you think sleep is stupid, that's totally wrong. But if you're not sleeping because you're deeply passionate about something, that to me, it's a gray area, of course, but that to me is much more admirable. And everything you're espousing is saying like, whatever the hell you're doing, you better be aware that sleep, long-term and short-term is really good for you. So if you're not sleeping, you're sacrificing, just make sure you're sacrificing for the right thing. I see vodka and getting drunk the same way. I know it's not good for me. I know I'm not gonna feel good days after. I know it's gonna decrease my performance. And there's nothing positive about it, except it introduces chaos in my life that introduces beautiful experiences that I would not otherwise have. It creates like this turmoil of social interaction that ultimately makes me happy that I've experienced them in the moment. And later the stories, you get to meet new people. So like alcohol in this society is an incredible facilitator of that. So like, that's a good example of like not sleeping and drinking way too much vodka. Again, it's this notion of life is to be lived to a degree. But if you do have children, I think one of the other things that then maybe comes into the picture is the fact that now there are other people that you have to live for than yourself. Yeah, but come on, like once they're old enough, like if you can't defend for yourself, you're too weak, get stronger. It's gonna be that kind of fatherhood. I got it. I'm understanding so much more about like Screamin than I did. That's why you have to have, for me that'd be, my wife would be probably softer. It's good cop, bad cop, because I think I'm... But of course, actually, because I don't have kids, I've seen some tough dudes when they have kids become like the softies. They become like, they do everything for their kids. It becomes like, it totally transforms their life. I mean, Joe Rogan is an example of that. I've just seen so many tough guys completely become changed by having kids, which is fascinating to watch because it just shows you how meaningful having kids is for a lot of people. Although I would say having, you know, chatted with Joe for some time, I think he is a delightful, sweetheart, independent of children, I think. Don't get me wrong, I don't wanna be in a ring with him. He would face me five ways till Tuesday, but I think he's a desperately sweet man and a very, very smart individual. Yeah, I mean, but he talks about the compassion he's gained from realizing just watching kids grow up, that we were all kids at some point. You get a new perspective. I think just like me, I still get this with him. He's super competitive and like there's a certain way to approach life. Like you're striving to do great things and you're competitive against others and that intensity or that aggression, that can lack compassion sometimes and empathy. And when you have children, you get a sense like, oh, everybody was a child at some point. Everybody was a kid. And you see that whole development process. It can definitely enrich, expand your ability to be empathetic. Let me ask you about diet. So what's the connection between diet and sleep? So I do intermittent fasting, sometimes only one meal a day, sometimes no meals a day. Is there a good science on the interaction between fasting and sleep? We have some data, I would prefer more, but we have data both on time-restricted eating and then we have some data on fasting to a degree. On time-restricted eating, I think that it has some benefits, although the human replication studies have actually not borne out quite the same health benefit extent that the animal studies have. There've been some disappointing studies. One here close to where we are right now at UCSF recently. So I think time-restricted eating can be a good thing and there are many benefits of time-restricted eating. Is sleep one of them? No, it doesn't seem to be because there are probably at the time that we're recording this, three pretty decent studies that I'm aware of. Two out of the three were in obese individuals. One out of the three were in healthy weight individuals. And what they found was that time-restricted eating in all three of those studies didn't have any advantageous benefit to sleep. It didn't necessarily harm sleep, but it didn't seem to improve it. When it comes to fasting though, which is a different state, we don't have too many studies, experimental studies with long-term fasting. The best data that we have is probably from religious practices and probably the most data we have is during Ramadan where people will fast for 29 to 30 days from sunrise to sunset. And under those conditions, there are probably five distinct changes that we've seen. None of them seem to be particularly good for sleep. The first is that the amount of melatonin that you release, and melatonin is a hormone. It's often called the hormone of darkness or the vampire hormone, not because it makes you look longingly at people's necklines, but it's just because it comes out at night. Melatonin signals to your brain and your body that it's dark, it's nighttime, and it's time to sleep. Those individuals, when they were undergoing that regimen to fasting, the amount of melatonin that was released and when it was released, the amount of melatonin decreased and when it was released came later. That was the first thing. The second thing was that they ended up finding it harder to fall asleep as quickly as they normally would otherwise. The third thing was that the total amount of sleep that they were getting decreased. The fourth fascinating thing was that a wake-promoting chemical called orexin increased. And this is why a lot of people will say, when I'm fasting, it feels like I can stay awake for longer and I'm more alert, I'm more active. And I'll come back from an evolutionary perspective why we understand that to be the case. And then the fourth factor is that fasting didn't decrease the amount of deep sleep that seemed to be unaffected. It did, however, decrease the amount of REM sleep or dream sleep. And we know that REM sleep dreaming is essential for emotional first aid, mental health, it's critical for memory, creativity. It's also critical for several hormone functions. It's when, you know, if you, there's direct correlations between testosterone, you know, testosterone release peaks just before you go into REM sleep and during REM sleep too. So REM sleep is critical. But so those are the five changes that we've seen. None of them seem to be that advantageous for sleep. But the fourth point that I mentioned, which was orexin, which is this wake-promoting chemical and a good demonstration or a very sad demonstration of its power is when it becomes very deficient in the brain and it leads to a condition called narcolepsy. Where, you know, you're just unpredictable with your sleep and you, so orexin when it's in high concentrations keeps you awake when you lose it, it can, you know, it can put you very much into a state of narcolepsy where you're sleeping a lot of the time in unpredictable sleep. Why on earth when you are fasting would the brain release a wake-promoting chemical? And our answer is right now is the following. The one of the few times that I mentioned before that we see animals undergoing insufficient sleep or prolonged sleep deprivation is under conditions of starvation. And that is an extreme evolutionary pressure. And at that point, the brain will forego some, it won't forego all, but it will forego some of its sleep. And the reason is so that it can stay awake for longer because the sign of starvation is saying to the brain, you can't find food in your normal foraging perimeter. You need to stay awake for longer so you can travel outside of your perimeter for a further distance, and maybe you will find food and save the organism. So in other words, when we fast, it's giving our brain this evolutionary signal that you are under conditions of starvation. So the brain responds by saying, oh my goodness, I need to release the chemical that helps the organism stay awake for longer, which is orexin. So that they can forage for more food. Now, of course, your brain from evolutionary perspective doesn't know about this thing called Safeway that you could easily go to and break the fast. But that's how we understand fasting. And I think, you know, my dear friend, Peter Atiyah has done a lot of work in this area too. I think fasting and David Sinclair's brilliant work, goodness me, what an individual too. The work is pretty clear there that, you know, time-restricted eating and fasting have wonderful health benefits. Time, you know, fasting creates this thing called hormesis, just like exercise and low level stress and sauna, heat shock. And hormesis is a biological process, I think as David Sinclair has once said, in simple layman's terms is, what doesn't kill you makes you stronger. And I think there is certainly good data that fasting and time-restricted eating has many benefits. Is sleep one of them? It doesn't seem to be, it doesn't seem to enhance sleep. But it's interesting to understand its effects on sleep. I've like, I fasted, it's a study of NF2. Once fasted 72 hours and another time, 48 hours. And I found that I got much less sleep and was very restful though. I hesitate to say this, but this is how I felt, which is I needed less sleep. I wonder if my brain is deceiving me because it feels like I'm getting a whole extra amount of focus for free. And I wonder if there's long-term impacts of that. Because if I fast 24 hours, get the same amount of calories, one meal a day, there's a little bit of discomfort, like just maybe your body gets a little bit colder. Maybe there's just, I mean, hunger. But the amount of focus is crazy. And so I wonder, it's like, I'm a little suspicious of that. I feel like I'm getting something for free. I'm the same way with sweetener, like Splenda or something. It's like, it's gotta be really bad for you, right? Because why is it so tasty, right? And I think, yeah, as we said before, with biology, you don't get, if there's a gain, there's, yeah, there's often a cost too. So, but we at least understand the biological basis of what you're describing. It's not that you actually don't need less sleep. It's that this chemical is present that forces you more awake. And so subjectively you feel as though I don't need as much sleep because I'm wide awake. And those two things are quite different. It's not as though your sleep need has decreased. It's that your brain has hit the overdrive switch, the overboost switch to say, we need to keep you awake because food is in short supply. So you mentioned during sleep, there's a simulation, all those kinds of things for learning purposes. But there's also these, you mentioned the five ways in which we become psychotic in dreams. What do you think dreams are about? Why do you think we dream? What place do we go to when we dream? And why are they useful? Not just the simulation aspect, but just like all the crazy visuals that we get with dreams. Is there something you can speak to that's actually useful? Like why we have such fun experiences in that dream world? So one of the camps in the sleep field is that dreams are meaningless, that they are an epiphenomenal by-product of this thing called REM sleep, from which dreams come from as a physiological state. So the analogy would be, let's think of a light bulb, that the reason that you create the apparatus of a light bulb is to produce this thing called light in the same way that we've evolved to this thing called REM sleep to serve whatever functions REM sleep serves. But it turns out that when you create light in that way, you also produce something called heat. It was never the reason that you designed the light bulb, it's just what happens when you create light in that way. And the belief so too was that dreaming was essentially the heat of the light bulb, that REM sleep is critical, but when you have REM sleep with a complex brain like ours, you also produce this conscious epiphenomenon called dreaming. I don't believe that for a second. And from a simple perspective is that I suspect that dreaming is more metabolically costly as a conscious experience than not dreaming. So you could still have REM sleep, but absent the conscious experience of dreaming was probably less metabolically costly. And whenever mother nature burns the energy unit called ATP, which is the most valuable thing, there's usually a reason for it. So if it's more energetically demanding, then I suspect that there is a function to it. And we've now since discovered that dreams have a function. The first, as we mentioned, creativity. The second is that dreams provide a form of overnight therapy. Dreaming is a form of emotional first aid. And it's during dream sleep at night that we take these difficult, painful experiences that we've had during the day, sometimes traumatic. And dream sleep acts almost like a nocturnal soothing balm. And it sort of just takes the sharp edges off those difficult, painful experiences so that you come back the next day and you feel better about them. And so I think in that sense, dreaming, it's not time that heals all wounds. It's time during dream sleep that provides emotional convalescence. So dreaming is almost a form of, you know, emotional windscreen wipers. And I think, and by the way, it's not just that you dream. It's what you dream about that also matters. So for example, scientists have done studies with learning and memory where they have people learn a virtual maze. And what they discovered was that those people who then dreamed, but dreamed of the maze, were the only ones who, when they woke up, ended up being better at navigating the maze. Whereas those people who dreamed but didn't dream about the maze itself, they were no better at navigating the maze. So it's not just that you, it's not sort of necessary, but not sufficient. It's necessary that you dream, but it's not sufficient to produce the benefit. You have to be dreaming about certain things itself. And the same is true for mental health. What we've discovered is that people who are going through a very difficult experience, a trauma, for example, a very painful divorce, those people who are dreaming, but dreaming of that difficult event itself, they go on to gain resolution to their clinical depression one year later. Whereas people who were dreaming just as much, but not dreaming about the trauma itself, did not go on to gain as much clinical resolution to their depression. So I think to me, those are the lines of evidence that tell me dreaming is not epiphenomenal. And it's not just about the act of dreaming, it's about the content of the dreams, not just the fact of a dream itself. It's, first of all, it's fascinating. It makes a lot of sense, but then immediately takes my mind to, from an engineering perspective, how that could be useful in, for example, AI systems of, if you think about dreaming as an important part about learning and cognition and filtering previous memories of what's important, integrating them, maybe you can correct me, but I see dreaming as a kind of simulation of worlds that are not constrained by physics. So you get a chance to take some of your memories, some of your thoughts, some of your anxieties, and play with them, construct virtual worlds and see how it evolves, to play with those worlds in a safe environment of your mind, safe in quotes, because you could probably get into a lot of trouble with the places your mind will go. But this definitely is applied in much cruder ways in artificial intelligence. So one context in which this is applied is the process called self-play, which is reinforcement learning where agents play against itself or versions of itself. And it's all simulated of trying different versions of themselves and playing against each other to see what ends up being a good. The ultimate goal is to learn a function that represents what is good and what is not good in terms of how you should act in the world. Right, you create a set of decision weights based on experience, and you constantly update those weights based on ongoing learning. But the experience is artificially created versus actual real data. So it's a crude approximation of what dreams are, which is you're hallucinating a lot of things to see which things are actually true. No, I think it's been a theory that's been put forward, which is that dreaming is a virtual reality test space that is largely consequence-free. What an incredible gift to give a conscious mind each and every night. Now, the conscious mind, the human mind, is very good at constructing dreams that are nevertheless useful for you. Like, they're wild and crazy, but they're such that they are still grounded in reality to a degree where anything you learn in dreams might be useful in reality. This is a very difficult thing to do because it requires a lot of intelligence. It requires consciousness. This has been effectively recently being used in self-supervised learning for computer vision with the process of what's called data augmentation. That's a very crude version of dreams, which is you take data and you mess with it and you start to learn how a picture of a cat truly represents a cat by messing with it in different ways. Now, the crude methods currently are cropping, rotating, distorting, all that kind of stuff, but you can imagine much more complicated generative processes that start hallucinating different cats in order for you to understand deeply of what it means for something to look like a cat. Right, what is the prototype of a, the archetype of a cat? Yeah, the archetype. That's a very difficult process for computer vision to go from what are the pixels that are usually associated with a cat to what is a cat in the visual space? In the three-dimensional visual space that is projected on an image, on a two-dimensional image, what is a cat? Those are fundamentally philosophical questions that we humans don't know the answer to linguistically, but when we look at a picture of a cat and a dog, we can usually tell pretty damn well what's the difference. And I don't know what that is because you can't reduce that to pointy ears or non-pointy ears, furry or not furry, something about the eyes. It's been a longstanding issue in cognitive science, cognitive neuroscience too, is how does the brain create an archetype? How does it create schemas that have general applicability, but yet still obtain specificity? That's a very difficult challenge. And we can do it, we do it. It's rather bloody amazing. And it seems like part of the toolbox is this controlled hallucination, which is dreams. Well, it's a relaxing of the rigid constraints. I often think of dreaming as, from an information processing standpoint, the prison guards are away and the prisoners are running amok in a delightful way. And part of the reason is because when you go into dream sleep, the rational part of your brain called the prefrontal cortex, which is the part, it's like the CEO of the brain. It's very good at making high level, rational, top-down decisions and controlled actions. That part of the brain is shut down during REM sleep. But then emotional centers, memory centers, visual centers, motoric centers, all of those centers actually become more active. In fact, some of them are more active than when we're awake in the dream state. So your brain from a neural architecture perspective is radically different. Its network feature is not the same as wakefulness. And I think this is an immensely beneficial thing that we have at least two different rational and irrational conscious states that we do information processing in. The rational, the veritical, the page one of the Google search is wakefulness. The more irrational, illogical, hyper-associative Google page 20 is the REM sleep. Both I think are critical, both are necessary. That's fascinating. And again, fascinating to see how that could be integrated in the machines to help them learn better and to reason better. And in some ways, we also know it from a chemical perspective too. When you go into dream sleep, it is a neurochemical cocktail like no other that we see at the rest of the 24-hour state. There is a chemical called noradrenaline or norepinephrine in the brain. And you know of its sister chemical in the body called adrenaline. But upstairs in the brain, noradrenaline is very good at creating a very hyper-focused, attentive, narrow, it's sort of very convergent way of thinking to a point, sharp, focus, that's the only thing. The spotlight of consciousness is very narrow. That's noradrenaline. When you remove noradrenaline, then you go from a high SNR, high signal to noise ratio, where it's just you and I in this moment, I don't even know what's going on elsewhere. I am with you, noradrenaline is present. But when you go into REM sleep, it is the only time during the 24-hour period where your brain is devoid of any noradrenaline. It is completely shut off. And so the signal to noise ratio is very different. It's almost as though we're injecting a greater amount of noise into the neural architecture of the brain during dream sleep, as if it's chemically brute forced into this relaxed associative memory processing state. And then from an anatomical perspective, just as I described, the prefrontal cortex goes down and other regions light up. So it is a state that seems to be very, I mean, if you were to show me a brain scan of REM sleep and tell me that it's not REM sleep, just say, look, based on the pattern of this brain activity, what would you say is going on in this person's mind? I would say, well, they're probably not rational. They're probably not having logical thought because their prefrontal cortex is down. They're probably feeling very emotional because their amygdala is active, which is an emotional center of the brain. They're definitely going to be thinking visually because the back of the brain is lit up, the visual cortex. It's probably going to be filled with past experience and autobiographical memories because their memory centers are lighting up. And there's probably going to be movement because their motor cortex is very active. That to me sounds very much like a dream. And that's exactly what we see in brain scanners when we've put people inside of them. One of the things I notice sleep affects is my ability to see the beauty in the world. So what do you think is the connection between sleep and your emotional life? Your ability to love other human beings and love life? Yeah, I think it's very powerful and strong. So we've done a lot of work in the field of sleep and emotion and sleep and moods, and you can separate your emotions into two main buckets, positive and negative. And what's interesting is that when you are sleep deprived and the more hours that you go into being awake and the fewer hours that you've had to sleep, your negative mood starts to increase. And we know which individual types of emotions are changing. I've got a wonderful postdoc in my lab called Etty Ben-Simon, who's doing some incredible work on trying to understand the emotional, individual emotional tapestry of affective meltdown when you're not getting sufficient sleep. But let's just keep with two dimensions, positive and negative. The negative, most people would think, well, it's the negative that takes the biggest hit when I'm sleep deprived. It's not. By probably a log order magnitude larger is a hit on your positive emotions. In other words, you stop gaining pleasure from normally pleasurable things. And it's a state that we call anhedonia. And anhedonia is the state that we often call depression. So depression, to most people's surprise, isn't necessarily that you're always feeling negative emotions. It's often more about the fact that you lose the pleasure in the good things in life. That's what we call anhedonia. That's what we see in sleep and insufficient sleep. And it happens quite quickly. Yeah, it's kind of fascinating. I think I do, it's not depression, but it's a stroll into that direction, which is when I'm sleep deprived, I stop being able to see the meaning in life. The things that gave me meanings starts to lose meaning. It makes me realize how enjoyable everything is in my life because when I start to lose it, when I'm severely sleep deprived, you start to see how much life sucks when you lose it. But that said, I'm just cognizant enough that sleep fixes all of that. So I use those states for what they're worth. In fact, I personally like to pay attention to the things that bother me during that time because they also reveal important information to me. That's an interesting method to use, like a Rorschach. Yeah, I mean, so I find when I fast combine sleep deprivation, am clear to see with people, clear in identifying the things that are not going right in my life, or people that I'm working with are not doing as good of a job as they could be doing. Like people that are negative in my life, I'm more able to identify them. So I don't act on that. It's a very bad time to act on those decisions. But you- Good point, well made. I'm recording that information because I usually, when I'm well rested and happy, I see the beauty in everybody, which can get you into trouble. So you have to balance those two things. But yes, it's fascinating. But there's irony there too, which is the fact that when you're well rested and well slept, just as you said, you see the beauty in life and it sort of enlivens you and sort of gives you a quality of life that's emotionally very different. Yet then we are contrasting that against the need for not getting enough sleep because of the beautiful things that you want to accomplish in life. And I don't actually see them as, you know, sort of completely counterintuitive or paradoxical because I still think that you can strive for all of the brilliant things that you are striving for to have the monumental goals, the Herculean challenges that you wish to take on and solve. They can still enthrall you and excite you and stimulate you. But because of the insufficient sleep that they can or that goal can produce, it will shave off the beauty of life that you experience in between. And again, this is just about the trade-off. I will say though that, and this is not applicable to your circumstance, we do know that insufficient sleep is very strongly linked to suicide ideation, suicide attempts, and tragically suicide completion as well. And in fact, in 20 years of studying sleep, we have not been able to discover a single psychiatric condition in which sleep is normal. And I think that that is a profound state. I think it tells us so much about the role of sleep as a potential causal agent in psychiatric conditions. I also think it's a potential sign that we should be using sleep as a tool for the prevention of grave mental illness. Yeah, it's both a cause and a solution. So yeah, I mean, me personally, I've gone through a few dark periods quite recently, and it was almost always sleep is not the cause, but sleep is the catalyst from going to a bad time to a very bad time. Yeah. And so it's definitely true. And it's funny how sleep can just cure all of that. There's actually a beautiful quote by an American entrepreneur called E. Joseph Kosman, who once said that the best bridge between despair and hope is a good night's sleep. And I spilled so much ink and hundreds of pages inelegantly trying to say the same thing in my book, and he said it in one line, and it's beautiful. What do you think is, we've been talking about how to extend this life, how to make it a good life. We've been talking about love. What do you think is the meaning of this whole ride? Of life? Of life. Why do we wanna make it a good one? Do you think there's a meaning? Do you think there's an answer to the why? For me personally, I think the meaning of life is to eat, is to sleep, is to fall in love, is to cry, and then to die. Oh, and probably race cars in between. Race cars. Well, there's a whole topic of sex we didn't talk about, so that's probably in there somewhere. Should we do that? Maybe if you'll have me back, I would love to do it. Yeah, that's a fall. I will give a round two. Next time, we will do a round three. Next time, we will do another three hours on sex alone. Has it been, yeah. It has been over three hours, yeah. Gosh, okay. Matt, I'm a big fan of your work. I think you're doing really important work, even despite all the things I've been saying about the madness of my own sleep schedule. I think you're helping millions of people, so it's an honor that you spend your valuable time with me, and I can't wait until your podcast comes out. I'm a huge fan of podcasts, I'm a huge fan of you, and it's just an honor to know you, and to get a chance, hopefully in the future, to work together with you. You're a brilliant man, and you're doing amazing things, and I feel immensely honored to have met you, to now know you, and to start calling you a friend. Thank you for what you do for the world, and for me included. Thank you, Matt. Take care. Thanks for listening to this conversation with Matt Walker, and thank you to Stamps.com, Squarespace, Athletic Greens, BetterHelp, and Onnit. Check them out in the description to support this podcast. And now, let me leave you with some words from Nikola Tesla, who we discussed in this podcast as sleeping very few hours a night. "'All that was great in the past was ridiculed, "'condemned, combated, and suppressed, "'only to emerge all the more powerfully, "'all the more triumphantly from the struggle.'" Thank you for listening, and hope to see you next time.

https://youtu.be/Hc4XvHTlW3s

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Origin of the term AGI (Ben Goertzel) | AI Podcast Clips

Maybe it's good to step back a little bit. I mean, we've been using the term AGI. People often cite you as the creator, or at least the popularizer of the term AGI, artificial general intelligence. Can you tell the origin story of the term? Sure, sure. So yeah, I would say I launched the term AGI upon the world for what it's worth without ever fully being in love with the term. What happened is I was editing a book, and this process started around 2001 or two. I think the book came out 2005, finally. I was editing a book which I provisionally was titling Real AI. And I mean, the goal was to gather together fairly serious academicish papers on the topic of making thinking machines that could really think in the sense like people can, or even more broadly than people can, right? So then I was reaching out to other folks that I had encountered here or there who were interested in that, which included some other folks who I knew from the transhumanist and singularitarian world like Peter Vos, who has a company, AGI Incorporated still in California, and included Shane Legg, who had worked for me at my company WebMind in New York in the late 90s, who by now has become rich and famous. He was one of the co-founders of Google DeepMind. But at that time, Shane was, I think he may have just started doing his PhD with Markus Hutter, who at that time hadn't yet published his book Universal AI, which sort of gives a mathematical foundation for artificial general intelligence. So I reached out to Shane and Markus and Peter Vos and Pei Wang, who was another former employee of mine who had been Douglas Hofstadter's PhD student, who had his own approach to AGI, and a bunch of some Russian folks reached out to these guys and they contributed papers for the book. But that was my provisional title, but I never loved it because in the end, I was doing some, what we would now call narrow AI as well, like applying machine learning to genomics data or chat data for sentiment analysis. I mean, that work is real. In a sense, it's really AI, it's just a different kind of AI. Ray Kurzweil wrote about narrow AI versus strong AI. But that seemed weird to me because, first of all, narrow and strong are not antonyms. Right? That's right. But secondly, strong AI was used in the cognitive science literature to mean the hypothesis that digital computer AIs could have true consciousness like human beings. So there was already a meaning to strong AI, which was complexly different but related, right? So we were tossing around on an email list what title it should be, and so we talked about narrow AI, broad AI, wide AI, narrow AI, general AI, and I think it was either Shane Legg or Peter Vos on the private email discussion we had, he said, well, why don't we go with AGI, artificial general intelligence? Pei Wang wanted to do GAI, general artificial intelligence, because in Chinese it goes in that order. But we figured gay wouldn't work in US culture at that time, right? So we went with the AGI, we used it for the title of that book, and part of Peter and Shane's reasoning was you have the G factor in psychology, which is IQ, general intelligence, right? So you have a meaning of GI, general intelligence in psychology, so then you're looking like artificial GI. So then we- That makes a lot of sense, I think. Yeah, we used that for the title of the book, and so I think, maybe both Shane and Peter think they invented the term, but then later, after the book was published, this guy Mark Gubrid came up to me, and he's like, well, I published an essay with the term AGI in 1997 or something, and so I'm just waiting for some Russian to come out and say they published that in 1953, right? I mean, that term- For sure. That term is not dramatically innovative or anything. It's one of these obvious, in hindsight, things, which is also annoying in a way, because Joe Chabac, who you interviewed, is a close friend of mine. He likes the term synthetic intelligence, which I like much better, but it hasn't actually caught on, right? Because, I mean, artificial is a bit off to me, because artifice is like a tool or something, but not all AGIs are gonna be tools. I mean, they may be now, but we're aiming toward making them agents rather than tools, and in a way, I don't like the distinction between artificial and natural, because, I mean, we're part of nature also, and machines are part of nature. I mean, you can look at evolved versus engineered, but that's a different distinction. Then it should be engineered general intelligence, right? And then general, well, if you look at Markus Hutter's book, Universally, what he argues there is, within the domain of computation theory, which is limited but interesting, so if you assume computable environments, the computable reward functions, then he articulates what would be a truly general intelligence, a system called AIXI, which is quite beautiful. AIXI. AIXI, and that's the middle name of my latest child, actually. What's the first name? First name is QORXI, Q-O-R-X-I, which my wife came up with, but that's an acronym for quantum organized rational expanding intelligence. And his middle name is XIPHONES, actually. XIPHONES, which means the former principal underlying AIXI. In any case- You're giving Elon Musk's new child a run for his money. Well, I did it first. He copied me with this new freakish name. But now, if I have another baby, I'm gonna have to outdo him. Outdo him. It's become an arms race of weird, geeky baby names. We'll see what the babies think about it, right? Yeah. But, I mean, my oldest son, Zarathustra, loves his name, and my daughter, Sherazade, loves her name. So, so far, basically, if you give your kids weird names- They live up to it. Well, you're obliged to make the kids weird enough that they like the names, right? It directs their upbringing in a certain way. But, yeah, anyway, I mean, what Marcus showed in that book is that a truly general intelligence, theoretically, is possible, but would take infinite computing power. So then, the artificial is a little off. The general is not really achievable within physics, as we know it. And, I mean, physics, as we know it, may be limited, but that's what we have to work with now. Intelligence- Infinitely general, you mean, like, from an information processing perspective, yeah. Yeah, intelligence is not very well-defined, either. I mean, what does it mean? I mean, in AI now, it's fashionable to look at it as maximizing an expected reward over the future, but that sort of definition is pathological in various ways. And my friend David Weinbaum, aka Weaver, he had a beautiful PhD thesis on open-ended intelligence, trying to conceive intelligence in a- Without a reward. Without an objective function. Yeah, he's just looking at it differently. He's looking at complex self-organizing systems and looking at an intelligence system as being one that revises and grows and improves itself in conjunction with its environment without necessarily there being one objective function it's trying to maximize. Although, over certain intervals of time, it may act as if it's optimizing a certain objective function. Very much Solaris from Stanislav Lom's novels, right? So yeah, the point is, artificial general and intelligence- Don't work. They're all bad. On the other hand, everyone knows what AI is, and AGI seems immediately comprehensible to people with a technical background. So I think that the term has served as sociological function. Now it's out there everywhere, which baffles me. It's stuck. Yeah, I agree. I mean, that's it. We're stuck with AGI probably for a very long time until AGI systems take over and rename themselves. Yeah, and then we'll be biological- We're stuck with GPUs too, which mostly have nothing to do with graphics anymore. I wonder what the AGI system will call us humans. That was maybe- Grandpa. Yeah. Yeah. GPs. Yeah. Grandpa processing unit. Biological grandpa processing unit.

https://youtu.be/4X2xYyIk5x0

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Dava Newman: Reusable Rockets

Is there something else that you've been excited about and like reusable rockets perhaps that you've seen in the last few years? Yeah, well, the reusability, you had the reusability is awesome. I mean, it's just the best. Now we have to remember the shuttle was a reusable vehicle. Yes. Which shuttle is an amazing, it's narrow space engineer. You know, I mean, the shuttle is still, this is the most gorgeous, elegant, extraordinary design of a space vehicle. It was reusable, it just wasn't affordable. But the reusability of it was really critical because we flew it up, it did come back. So the notion of reusability, I think absolutely. Now what we're doing with we, you know, like global we, but with SpaceX and Virgin, sending the rockets up, recovering the first stages where if they can regain 70% cost savings, that's huge. And just seeing the control, you know, being in control and dynamics, just seeing that rocket come back and land. Oh yeah, that's- It never gets old. It's exciting every single time you look at it and you say, that's magic. So it's so cool. To me, the landing is where I stand up, start clapping, just the control. Yeah, just the algorithm, just the control algorithms. And hitting that landing, it's, you know, it's gymnastics for rocket ships. But to see these guys stick a landing, it's just wonderful. So every time, like I say, every time I see, you know, the reusability and the rockets coming back and landing so precisely, it's really exciting. So it is, actually, that's a game changer. We are in a new era of lower costs and a lot, the higher frequency. And it's the world, not just NASA. It's many nations are really upping their frequency of launches.

https://youtu.be/8libSL9vc1U

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Keoki Jackson: Lockheed Martin | Lex Fridman Podcast #33

The following is a conversation with Kiyoki Jackson. He's the CTO of Lockheed Martin, a company that through its long history has created some of the most incredible engineering marvels human beings have ever built, including planes that fly fast and undetected, defense systems that intersect nuclear threats that can take the lives of millions, and systems that venture out into space, the moon, Mars, and beyond. And these days, more and more, artificial intelligence has an assistive role to play in these systems. I've read several books in preparation for this conversation. It is a difficult one, because in part, Lockheed Martin builds military systems that operate in a complicated world that often does not have easy solutions in the gray area between good and evil. I hope one day this world will rid itself of war in all its forms. But the path to achieving that in a world that does have evil is not obvious. What is obvious is good engineering and artificial intelligence research has a role to play on the side of good. Lockheed Martin and the rest of our community are hard at work at exactly this task. We talk about these and other important topics in this conversation. Also, most certainly, both Kiyoki and I have a passion for space. Us humans venturing out toward the stars. We talk about this exciting future as well. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Kiyoki Jackson. I read several books on Lockheed Martin recently. My favorite in particular is by Ben Rich, Carlos Conkworx's personal memoir. I think it's a little edgy at times, but from that, I was reminded that the engineers at Lockheed Martin have created some of the most incredible engineering marvels human beings have ever built throughout the 20th century and the 21st. Do you remember a particular project or system at Lockheed or before that at the Space Shuttle Columbia that you were just in awe at the fact that us humans could create something like this? You know, that's a great question. There's a lot of things that I could draw on there. When you look at the Conkworx and Ben Rich's book in particular, of course, it starts off with basically the start of the jet age and the P-80. I had the opportunity to sit next to one of the Apollo astronauts, Charlie Duke, recently at dinner. And I said, hey, what's your favorite aircraft? And he said, well, it was by far the F-104 Starfighter, which was another aircraft that came out of Lockheed there. It was the first Mach 2 jet fighter aircraft. They called it the missile with a man in it. And so those are the kinds of things that I grew up hearing stories about. Of course, the SR-71 is incomparable as kind of the epitome of speed, altitude, and just the coolest looking aircraft ever. So there's a- And that's a reconnaissance, that's a plane- That's a, yeah, intelligence surveillance and reconnaissance aircraft that was designed to be able to outrun, basically go faster than any air defense system. But I'll tell you, I'm a space junkie. That's why I came to MIT. That's really what took me ultimately to Lockheed Martin. And I grew up, and so Lockheed Martin, for example, has been essentially at the heart of every planetary mission, like all the Mars missions we've had a part in. And we've talked a lot about the 50th anniversary of Apollo here in the last couple of weeks, right? But remember 1976, July 20th, again, National Space Day. So the landing of the Viking, the Viking lander on the surface of Mars, just a huge accomplishment. And when I was a young engineer at Lockheed Martin, I got to meet engineers who had designed various pieces of that mission as well. So that's what I grew up on, is these planetary missions, the start of the space shuttle era, and ultimately had the opportunity to see Lockheed Martin's part. And we can maybe talk about some of these here, but Lockheed Martin's part in all of these space journeys over the years. Do you dream, and I apologize for getting philosophical at times, or sentimental. I do romanticize the notion of space exploration. So do you dream of the day when us humans colonize another planet like Mars, or a man, a woman, a human being steps on Mars? Absolutely. And that's a personal dream of mine. I haven't given up yet on my own opportunity to fly into space. But from the Lockheed Martin perspective, this is something that we're working towards every day. And of course, we're building the Orion spacecraft, which is the most sophisticated human rated spacecraft ever built. And it's really designed for these deep space journeys, starting with the moon, but ultimately going to Mars and being the platform from a design perspective, what we call the Mars Base Camp, to be able to take humans to the surface. And then after a mission of a couple of weeks, bring them back up safely. And so that is something I want to see happen during my time at Lockheed Martin. So I'm pretty excited about that. And I think once we prove that's possible, colonization might be a little bit further out, but it's something that I'd hope to see. So maybe you can give a little bit of an overview of... So Lockheed Martin has partnered with a few years ago with Boeing to work with the DOD and NASA to build launch systems and rockets with the ULA. What's beyond that? What's Lockheed's mission timeline, timeline and long-term dream in terms of space? You mentioned the moon. I've heard you talk about asteroids as Mars. What's the timeline? What's the engineering challenges and what's the dream long-term? Yeah, I think the dream long-term is to have a permanent presence in space beyond low earth orbit, ultimately with a long-term presence on the moon and then to the planets, to Mars. And... Sorry to interrupt on that. So long-term presence means... Sustained and sustainable presence in an economy, a space economy that really goes alongside that. With human beings and being able to launch perhaps from those... So like hop? There's a lot of energy that goes in those hops, right? So I think the first step is being able to get there and to be able to establish sustained basis, right? And build from there. And a lot of that means getting, as you know, things like the cost of launch down. And you mentioned United Launch Alliance. And so I don't want to speak for ULA, but obviously they're working really hard to... On their next generation of launch vehicles to maintain that incredible mission success record that ULA has, but ultimately continue to drive down the cost and make the flexibility, the speed and the access ever greater. So what's the missions that are on the horizon that you could talk to? Is there a hope to get to the moon? Absolutely. Absolutely. I mean, I think you know this or you may know this. There's a lot of ways to accomplish some of these goals. And so that's a lot of what's in discussion today. But ultimately, the goal is to be able to establish a base, essentially in cislunar space that would allow for ready transfer from orbit to the lunar surface and back again. And so that's sort of that near term, I say near term in the next decade or so vision. Starting off with a stated objective by this administration to get back to the moon in the 2024, 2025 timeframe, which is right around the corner here. How big of an engineering challenge is that? I think the big challenge is not so much to go, but to stay. And so we demonstrated in the 60s that you could send somebody up, do a couple of days of mission and bring them home again successfully. Now we're talking about doing that, I'd say more to, I don't want to say an industrial scale, but a sustained scale, right? So permanent habitation, regular reuse of vehicles, the infrastructure to get things like fuel, air, consumables, replacement parts, all the things that you need to sustain that kind of infrastructure. So those are certainly engineering challenges. There are budgetary challenges. And those are all things that we're going to have to work through. The other thing, and I shouldn't, I don't want to minimize this. I mean, I'm excited about human exploration, but the reality is our technology and where we've come over the last 40 years essentially has changed what we can do with robotic exploration as well. And to me, it's incredibly thrilling. And this seems like old news now, but the fact that we have rovers driving around the surface of Mars and sending back data is just incredible. The fact that we have satellites in orbit around Mars that are collecting weather, they're looking at the terrain, they're mapping, all of these kinds of things on a continuous basis, that's incredible. And the fact that you got the time lag, of course, going to the planets, but you can effectively have virtual human presence there in a way that we have never been able to do before. And now with the advent of even greater processing power, better AI systems, better cognitive systems and decision systems, you put that together with the human piece and we really opened up the solar system in a whole different way. And I'll give you an example. We've got OSIRIS-REx, which is a mission to the asteroid Bennu. So the spacecraft is out there right now on basically a year mapping activity to map the entire surface of that asteroid in great detail, all autonomously piloted. But the idea then that, and this is not too far away, it's going to go in, and it's got a sort of a fancy vacuum cleaner with a bucket. It's going to collect the sample off the asteroid and then send it back here to earth. And so we have gone from sort of those tentative steps in the 70s, early landings, video of the solar system, to now we've sent spacecraft to Pluto, we have gone to comets and intercepted comets, we've brought stardust material back. So we've gone far and there's incredible opportunity to go even farther. So it seems quite crazy that this is even possible. Can you talk a little bit about what it means to orbit an asteroid and with a bucket to try to pick up some soil samples? Yeah. So part of it is just kind of the, these are the same kinds of techniques we use here on earth for high speed, high accuracy imagery, stitching these scenes together and creating essentially high accuracy world maps. And so that's what we're doing obviously on a much smaller scale with an asteroid. But the other thing that's really interesting, you put together sort of that neat control and data and imagery problem. But the stories around how we designed the collection, I mean, as essentially, this is the sort of the human ingenuity element, right? That essentially had an engineer who had a, one day he's like, well, starts messing around with parts, vacuum cleaner, bucket, maybe we could do something like this. And that was what led to what we call the pogo stick collection, right? Where basically a thing comes down, it's only there for seconds, does that collection, grabs the, essentially blows the regolith material into the collection hopper and off it goes. It doesn't really land almost. It's a very short landing. Wow, that's incredible. So what is, in those, we talk a little bit more about space, what's the role of the human in all of this? What are the challenges? What are the opportunities for humans as they pilot these vehicles in space and for humans that may step foot on either the moon or Mars? Yeah, it's a great question because I just have been extolling the virtues of robotic and, you know, rovers, autonomous systems, and those absolutely have a role. I think the thing that we don't know how to replace today is the ability to adapt on the fly to new information. And I believe that will come, but we're not there yet. There's a ways to go. And so, you know, you think back to Apollo 13 and the ingenuity of the folks on the ground and on the spacecraft to essentially cobble together a way to get the carbon dioxide scrubbers to work. Those are the kinds of things that ultimately, you know, and I'd say not just from dealing with anomalies, but, you know, dealing with new information. You see something and rather than waiting 20 minutes or half an hour, an hour to try to get information back and forth, but be able to essentially re-vector on the fly, collect, you know, different samples, take a different approach, choose different areas to explore. Those are the kinds of things that human presence enables that is still a ways ahead of us on the AI side. Yeah, there's some interesting stuff we'll talk about on the teaming side here on Earth that's pretty cool to explore. And in space, let's not leave the space piece out. So, what is teaming, what is AI and humans working together in space look like? Yeah, one of the things we're working on is a system called Maya, which is, you can think of it, so it's an AI assistant. In space. In space, exactly. And you think of it as the Alexa in space, right? But this goes hand in hand with a lot of other developments. And so, today's world, everything is essentially model-based, model-based systems engineering to the actual digital tapestry that goes through the design, the build, the manufacture, the testing, and ultimately the sustainment of these systems. And so, our vision is really that, you know, when our astronauts are there around Mars, you're going to have that entire digital library of the spacecraft, of its operations, all the test data, all the test data and flight data from previous missions to be able to look and see if there are anomalous conditions and tell the humans and potentially deal with that before it becomes a bad situation and help the astronauts work through those kinds of things. And it's not just dealing with problems as they come up, but also offering up opportunities for additional exploration capability, for example. So, that's the vision is that, you know, these are going to take the best of the human to respond to changing circumstances and rely on the best of AI capabilities to monitor this almost infinite number of data points and correlations of data points that humans, frankly, aren't that good at. So, how do you develop systems in space like this, whether it's Alexa in space or in general, any kind of control systems, any kind of intelligent systems when you can't really test stuff too much out in space? It's very expensive to test stuff. Yeah. So, how do you develop such systems? Yeah, that's the beauty of this digital twin, if you will. And of course, with Lockheed Martin, we've over the past, you know, five plus decades been refining our knowledge of the space environment, of how materials behave, dynamics, the controls, the, you know, radiation environments, all of these kinds of things. So, we're able to create very sophisticated models. They're not perfect, but they're very good. And so, you can actually do a lot. I spent part of my career, you know, simulating communication spacecraft, you know, missile warning spacecraft, GPS spacecraft in all kinds of scenarios and all kinds of environments. So, this is really just taking that to the next level. The interesting thing is that now you're bringing into that loop a system, depending on how it's developed, that may be non-deterministic. It may be learning as it goes. In fact, we anticipate that it will be learning as it goes. And so, that brings a whole new level of interest, I guess, into how do you do verification and validation of these non-deterministic learning systems in scenarios that may go out of the bounds or the envelope that you have initially designed them to. So, this system and its intelligence has the same complexity, some of the same complexity a human does. And it learns over time. It's unpredictable in certain kinds of ways. So, you also have to model that when you're thinking about it. So, in your thoughts, it's possible to model the majority of situations, the important aspects of situations here on Earth and in space enough to test stuff? Yeah. This is really an active area of research. And we're actually funding university research in a variety of places, including MIT. This is in the realm of trust and verification and validation of, I'd say, autonomous systems in general, and then as a subset of that, autonomous systems that incorporate artificial intelligence capabilities. And this is not an easy problem. We're working with startup companies. We've got internal R&D. But our conviction is that autonomy and more and more AI-enabled autonomy is going to be in everything that Lockheed Martin develops and fields. And it's going to be retrofit. Autonomy and AI are going to be retrofit into existing systems. They're going to be part of the design for all of our future systems. And so, maybe I should take a step back and say the way we define autonomy. So, we talk about autonomy, essentially, system that composes, selects, and then executes decisions with varying levels of human intervention. And so, you could think of no autonomy. So, this is essentially the human doing the task. You can think of effectively partial autonomy where the human is in the loop. So, making decisions in every case about what the autonomous system can do. Either in the cockpit or remotely. Or remotely, exactly. But still in that control loop. And then there's what you'd call supervisory autonomy. So, the autonomous system is doing most of the work. The human can intervene to stop it or to change the direction. And then ultimately, full autonomy where the human is off the loop altogether. And for different types of missions, want to have different levels of autonomy. So, now take that spectrum and this conviction that autonomy and more and more AI are in everything that we develop. The kinds of things that Lockheed Martin does, a lot of times are safety of life critical kinds of missions. Think about aircraft, for example. And so, we require and our customers require an extremely high level of confidence. One, that we're going to protect life. Two, that we're going to... That these systems will behave in ways that their operators can understand. And so, this gets into that whole field. Again, being able to verify and validate that the systems have been... That they will operate the way they're designed and the way they're expected. And furthermore, that they will do that in ways that can be explained and understood. And that is an extremely difficult challenge. Yeah. So, here's a difficult question. I don't mean to bring this up, but I think it's a good case study that people are familiar with. Boeing 737 Max commercial airplane has had two recent crashes where their flight control software system failed. And it's software, so I don't mean to speak about Boeing. But broadly speaking, we have this in the autonomous vehicle space too, semi-autonomous. We have millions of lines of code software making decisions. There is a little bit of a clash of cultures because software engineers don't have the same culture of safety often that people who build systems like Lockheed Martin do where it has to be exceptionally safe. You have to test this on. So, how do we get this right when software is making so many decisions? Yeah. And this... There's a lot of things that have to happen. And by and large, I think it starts with the culture, which is not necessarily something that A, is taught in school or B, is something that would come... Depending on what kind of software you're developing, it may not be relevant if you're targeting ads or something like that. And by and large, I'd say not just Lockheed Martin, but certainly the aerospace industry as a whole has developed a culture that does focus on safety, safety of life, operational safety, mission success. But as you note, these systems have gotten incredibly complex. And so, they're to the point where it's almost impossible. State space has become so huge that it's impossible to, or very difficult to do a systematic verification across the entire set of potential ways that an aircraft could be flown, all the conditions that could happen, all the potential failure scenarios. Now, maybe that's soluble one day, maybe when we have our quantum computers at our fingertips, we'll be able to actually simulate across an entire, almost infinite state space. But today, there's a lot of work to really try to balance to really try to bound the system to make sure that it behaves in predictable ways, and then have this culture of continuous inquiry and skepticism and questioning to say, did we really consider the right realm of possibilities? Have we done the right range of testing? Do we really understand, in this case, human and machine interactions, the human decision process alongside the machine processes? And so, that's that culture, that we call it the culture of mission success at Lockheed Martin, that really needs to be established. And it's not something, it's something that people learn by living in it. Right. And it's something that has to be promulgated, and it's done from the highest levels at a company of Lockheed Martin, like Lockheed Martin. Yeah. And the same is being faced, it's certainly autonomous vehicle companies where that culture is not there, because it's started mostly by software engineers. So, that's what they're struggling with. Is there lessons that you think we should learn as an industry and a society from the Boeing 737 MAX crashes? These crashes, obviously, are either tremendous tragedies, they're tragedies for all of the people, the crew, the families, the passengers, the people on the ground involved. And it's also a huge business and economic setback as well. I mean, we've seen that it's impacting, essentially, the trade balance of the US. So, these are important questions. And these are the kinds that we've seen similar kinds of questioning at times, go back to the Challenger accident. And it is, I think, always important to remind ourselves that humans are fallible, that the systems we create, as perfect as we strive to make them, we can always make them better. And so, another element of that culture of mission success is really that commitment to continuous improvement. If there's something that goes wrong, a real commitment to root cause, to root cause and true root cause understanding, to taking the corrective actions and to making the system, future systems better. And certainly, we want to, we strive for no accidents. And if you look at the record of the commercial airline industry as a whole and the commercial aircraft industry as a whole, there's a very nice decaying exponential to years now where we have no commercial aircraft accidents at all, right? Or fatal accidents at all. So, that didn't happen by accident. It was through the regulatory agencies, FAA, the airframe manufacturers, really working on a system to identify root causes and drive them out. So, maybe we can take a step back, and many people are familiar, but Lockheed Martin broadly, what kind of categories of systems are you involved in building? Lockheed Martin, we think of ourselves as a company that solves hard mission problems. And the output of that might be an airplane or a spacecraft or a helicopter or a radar or something like that. But ultimately, we're driven by these, what is our customer? What is that mission that they need to achieve? And so, that's what drove the SR-71, right? How did it get to SR-71, right? How do you get pictures of a place where you've got sophisticated air defense systems that are capable of handling any aircraft that was out there at the time, right? So, that's what yielded an SR-71. Let's build a nice flying camera. Exactly. And make sure it gets out and it gets back, right? Got it. And that led ultimately to really the start of the space program in the US as well. So, now take a step back to Lockheed Martin of today. And we are on the order of 105 years old now between Lockheed and Martin, the two big heritage companies, which were made up of a whole bunch of other companies that came in as well. General Dynamics, kind of go down the list. Today, you can think of us in this space of solving mission problems. So, obviously, on the aircraft side, tactical aircraft, building the most advanced fighter aircraft that the world has ever seen. We're up to now several hundred of those delivered, building almost 100 a year. And of course, working on the things that come after that. On the space side, we are engaged in pretty much every venue of space utilization and exploration you can imagine. So, I mentioned things like navigation, timing, GPS, communication satellites, missile warning satellites. We've built commercial surveillance satellites. We've built commercial communication satellites. We do civil space. So, everything from human exploration to the robotic exploration of the outer planets. And keep going on the space front. But a couple of other areas I'd like to put out, we're heavily engaged in building critical defensive systems. And so, a couple that I'll mention, the Aegis Combat System. This is basically the integrated air and missile defense system for the US and allied fleets. And so, protects carrier strike groups, for example, from incoming ballistic missile threats, aircraft threats, cruise missiles, ballistic missile threats, aircraft threats, cruise missile threats, and kind of go down the list. So, the carriers, the fleet itself is the thing that is being protected. The carriers aren't serving as a protection for something else. Well, that's a little bit of a different application. We've actually built a version called Aegis Ashore, which is now deployed in a couple of places around the world. So, that same technology, I mean, basically can be used to protect either an ocean-going fleet or a land-based activity. Another one, the THAAD program. So, THAAD, this is the Theater High Altitude Area Defense. This is to protect, you know, relatively broad areas against sophisticated ballistic missile threats. And so, now, you know, it's deployed with a lot of US capabilities. And now, we have international customers that are looking to buy that capability as well. And so, these are systems that defend, not just defend militaries and military capabilities, but defend population areas. We saw, you know, maybe the first public use of these back in the first Gulf War with the Patriot systems. And these are the kinds of things that Lockheed Martin delivers. And there's a lot of stuff that goes with it. So, think about the radar systems and the sensing systems that cue these, the command and control systems that decide how you pair a weapon against an incoming threat. And then, all the human and machine interfaces to make sure that they can be operated successfully in very strenuous environments. Yeah, there's some incredible engineering that at every front, like you said. So, maybe if we just take a look at Lockheed history broadly, maybe even looking at Skunk Works. What are the biggest, most impressive milestones of innovation? So, if you look at stealth, I would have called you crazy if you said that's possible at the time. And supersonic and hypersonic. So, traveling at, first of all, traveling at the speed of sound is pretty damn fast. And the supersonic and hypersonic, three, four, five times the speed of sound. That seems, I would also call you crazy if you say you can do that. So, can you tell me how it's possible to do these kinds of things? And is there other milestones and innovation that's going on that you can talk about? Yeah. Well, let me start on the Skunk Works saga. And you kind of alluded to it in the beginning. Skunk Works is as much an idea as a place. And so, it's driven really by Kelly Johnson's 14 principles. And I'm not going to list all 14 of them off. But the idea, and this I'm sure will resonate with any engineer who's worked on a highly motivated small team before, the idea that if you can essentially have a small team of very capable people who want to work on really hard problems, you can do almost anything. Especially if you kind of shield them from bureaucratic influences, if you create very tight relationships with your customers so that you have that team and shared vision with the customer. Those are the kinds of things that enable the Skunk Works to do these incredible things. And we listed off a number that you brought up stealth. And I mean, this whole, I wish I could have seen Ben Rich with a ball bearing, rolling it across the desk to a general officer and saying, would you like to have an aircraft that has the radar cross section of this ball bearing? Probably one of the least expensive and most effective marketing campaigns in the history of the industry. So just for people that are not familiar, I mean, the way you detect aircraft, because I mean, I'm sure there's a lot of ways, but radar for the longest time, there's a big blob that appears in the radar. How do you make a plane disappear so it looks as big as a ball bearing? What's involved in technology-wise there? What's broadly, sort of the stuff you can speak about? I'll stick to what's in Ben Rich's book, but obviously the geometry of how radar gets reflected and the kinds of materials that either reflect or absorb are kind of the couple of the critical elements there. And it's a cat and mouse game, right? I mean, radars get better, stealth capabilities get better. And so it's a really a game of continuous improvement and innovation there. I'll leave it at that. Yeah. So the idea that something is essentially invisible is quite fascinating. But the other one is flying fast. So speed of sound is 750, 60 miles an hour. So supersonic is Mach 3, something like that. Yeah. We talk about the supersonic, obviously, and we kind of talk about that as that realm from Mach 1 up through about Mach 5. And then hypersonic, so high supersonic speeds would be past Mach 5. And you got to remember Lockheed Martin and actually other companies have been involved in hypersonic development since the late 60s. You think of everything from the X-15 to the space shuttle as examples of that. I think the difference now is if you look around the world, particularly the threat environment that we're in today, you're starting to see publicly folks like the Russians and the Chinese saying they have hypersonic weapons capability that could threaten US and allied capabilities. And also basically the claims are these could get around defensive systems that are out there today. And so there's a real sense of urgency. You hear it from folks like the Undersecretary of Defense for Research and Engineering, Dr. Mike Griffin, and others in the Department of Defense that hypersonics is something that's really important to the nation in terms of both parity, but also defensive capabilities. And so that's something that we're pleased. It's something that Lockheed Martin's had a heritage in. We've invested R&D dollars on our side for many years. And we have a number of things going on with various US government customers in that field today that we're very excited about. So I would anticipate we'll be hearing more about that in the future from our customers. And I've actually haven't read much about this. Probably you can't talk about much of it at all, but on the defensive side, it's a fascinating problem of perception, of trying to detect things that are really hard to see. Can you comment on how hard that problem is and how hard is it to stay ahead, even if we're going back a few decades, stay ahead of the competition? Well, maybe I'd, again, you got to think of these as ongoing capability development. And and so think back to the early days of missile defense. So this would be in the 80s, the SDI program. And in that timeframe, we proved, Lockheed Martin proved that you could hit a bullet with a bullet, essentially, and which is something that had never been done before to take out an incoming ballistic missile. And so that's led to these incredible hit to kill kinds of capabilities, PAC-3, that's the Patriot Advanced Capability, Model 3 that Lockheed Martin builds, the THAAD system that I talked about. So now hypersonics, they're different from ballistic systems. And so we got to take the next step in defensive capability. I can, I'll leave that there, but I can only imagine. Now, let me just comment. So as an engineer, it's sad to know that so much that Lockheed has done in the past is classified, or today, you know, and it's shrouded in secrecy. It has to be by the nature of the application. So like what I do, so what we do here at MIT, we'd like to inspire young engineers, young scientists, and yet in the Lockheed case, some of that engineer has to stay quiet. How do you think about that? How does that make you feel? Is there a future where more can be shown, or is it just the nature of this world that it has to remain secret? It's a good question. I think, you know, the public can see enough of, and including students who may be in grade school, high school, college today, to understand the kinds of really hard problems that we work on. And I mean, look at the F-35, look at the F-35, right? And, you know, obviously a lot of the detailed performance levels are sensitive and controlled. But, you know, we can talk about what an incredible aircraft this is, you know, supersonic, super cruise, kind of a fighter, a, you know, stealth capabilities. It's a flying information system in the sky with data fusion, sensor fusion capabilities that have never been seen before. So these are the kinds of things that I believe, you know, these are the kinds of things that got me excited when I was a student. I think these still inspire students today. And the other thing I'd say, I mean, you know, people are inspired by space. People are inspired by aircraft. Our employees are also inspired by that sense of mission. And I'll just give you an example. I had the privilege to work and lead our GPS programs for some time. And that was a case where, you know, I actually worked on a program that touches billions of people every day. And so when I said I worked on GPS, everybody knew what I was talking about, even though they didn't maybe appreciate the technical challenges that went into that. But I'll tell you, I got a briefing one time from a major in the Air Force. And he said, I go by call sign GIMP. GPS is my passion. I love GPS. And he was involved in the operational test of the system. He said, I went, I was out in Iraq and I was on a helicopter, Black Hawk helicopter, and I was bringing back, you know, a sergeant and a handful of troops from a deployed location. And, you know, he said, my job is GPS. So I asked that sergeant and he's, you know, beaten down and kind of half asleep. And I said, what do you think about GPS? And he brightened up, his eyes lit up and he said, well, GPS, that brings me and my troops home every day. I love GPS. And that's the kind of story where it's like, okay, I'm really making a difference. Okay. I'm really making a difference here in the kind of work. So that mission piece is really important. The last thing I'll say is that, and this gets to some of these questions around advanced technologies. It's not, you know, they're not just airplanes and spacecraft anymore for people who are excited about advanced software capabilities, about AI, about bringing machine learning. These are the things that we're doing to exponentially increase the mission capabilities. That go on those platforms. And those are the kinds of things that I think are more and more visible to the public. Yeah. I think autonomy, especially in flight is super exciting. Do you, do you see if a day here we go back into philosophy, a future when most fighter jets will be highly autonomous to a degree where a human doesn't need to be in the cockpit in almost all cases? Well, I mean, that's a world that to a certain extent we're in today. Now, these are remotely piloted aircraft to be sure, but we have hundreds of thousands of flight hours a year now in remotely piloted aircraft. And then if you take the F-35, there are huge layers, I guess, in levels of autonomy built into that aircraft so that the pilot is essentially more of a mission manager rather than doing the data, you know, the second to second elements of flying the aircraft. So in some ways it's the easiest aircraft in the world to fly. And kind of a funny story on that. So I don't know if you know how aircraft carrier landings work, but basically there's what's called a tail hook and it catches wires on the deck of the carrier. And that's what brings the aircraft to a screeching halt. And there's typically three of these wires. So if you miss the first, the second one, you catch the next one. Right. And we got a little criticism. I don't know how true this story is, but we got a little criticism. The F-35 is so perfect. It always gets the second wires. We're wearing out the wire because it always hits that one. But that's the kind of autonomy that just makes these, that essentially up levels what the human is doing to more of that mission manager. So much of that landing by the F-35 is autonomous. Well, it's just, you know, the control systems are such that you really have dialed out the variability that comes with all of the environmental conditions. You're wearing it out. So my point is to a certain extent, that world is here today. Do I think that we're going to see a day anytime soon when there are no humans in the cockpit? I don't believe that, but I do think we're going to see much more human machine teaming and we're going to see that much more at the tactical edge. And we did a demo. You asked about what the skunk works is doing these days. And so this is something I can talk about, but we did a demo with the air force research laboratory, our laboratory. We called it have radar. And so using an F-16 as an autonomous wingman, and we demonstrated all kinds of maneuvers and various mission scenarios with the autonomous F-16 being that so-called loyal or trusted wingman. And so those are the kinds of things that, you know, we've shown what is possible now, given that you've up leveled that pilot to be a mission manager. Now they can control multiple other aircraft. Think of them almost as extensions of your own aircraft flying alongside with you. So that's another example of how this is really coming to fruition. And then, yeah, I mentioned the landings, but think about just the implications for humans and flight safety. And this goes a little bit back to the discussion we were having about how do you continuously improve the level of safety through automation while working through the complexities that automation introduces. So one of the challenges that you have in high performance fighter aircraft is what's called G-lock. So this is G-induced loss of consciousness. So you pull nine Gs, you're wearing a pressure suit. That's not enough to keep the blood going to your brain. You blackout. And of course, that's bad if you happen to be flying low, you know, near the deck and, you know, or an obstacle or terrain environment. And so we developed a system at our aeronautics division called Auto GCAS, so Autonomous Ground Collision Avoidance System. And we built that into the F-16. It's actually saved seven aircraft, eight pilots already in the relatively short time it's been deployed. It was so successful that the Air Force said, hey, we need to have this in the F-35 right away. So we've actually done testing of that now on the F-35. And we've also integrated an autonomous air collision avoidance system. So think the air to air problem. So now it's the integrated collision avoidance system. But these are the kinds of capabilities, you know, I wouldn't call them AI. I mean, they're very sophisticated models, you know, of the aircraft dynamics coupled with the terrain models to be able to predict when essentially, you know, the pilot is doing something that is going to take the aircraft into or the pilots not doing something in this case. But those just gives you an example of how autonomy can be really a lifesaver in today's world. It's like autonomous, automated emergency braking in cars. But is there any exploration of perception of, for example, detecting G-LOC that the pilot has is out? So as opposed to perceiving the external environment to infer that the pilot is out, but actually perceiving the pilot directly? Yeah, this is one of those cases where you'd like to, you know, not take action if you think the pilots there. And it's almost like systems that try to detect if a driver is falling asleep on the road, right? With limited success. Yeah. So, I mean, this is what I call the system of last resort, right? Where if the aircraft has determined that it's going into the terrain, get it out of there. And this is not something that we're just doing in the aircraft world. And I wanted to highlight, we have a technology we call Matrix, but this is developed at Sikorsky Innovations. The whole idea there is what we call optimal piloting. So not optional piloting or unpiloted, but optimal piloting. So an FAA certified system. So you have a high degree of confidence. It's generally pretty deterministic. So we know that it'll do in different situations, but effectively be able to fly a mission with two pilots, one pilot, no pilots. And you can think of it almost as like a dial of the level of autonomy that you want, but able, so it's running in the background at all times and able to pick up tasks, whether it's, you know, sort of autopilot kinds of tasks or more sophisticated path planning kinds of activities to be able to do things like, for example, land on an oil rig, you know, in the North Sea in bad weather, zero, zero conditions. And you can imagine, of course, there's a lot of military utility to capability like that. You could have an aircraft that you want to send out for a crewed mission, but then at night, if you want to use it to deliver supplies in an unmanned mode, that could be done as well. And so there's clear advantages there. But think about on the commercial side, you know, if you're an aircraft taken, and you're going to fly out to this oil rig, and if you get out there and you can't land, then you got to bring all those people back, reschedule another flight, pay the overtime for the crew that you just brought back because they didn't get where they were going, pay for the overtime for the folks that are out there in the oil rig. This is real economic, you know, these are dollars and cents kinds of advantages that we're bringing in the commercial world as well. So this is a difficult question from the AI space that I would love it if we're able to comment. So a lot of this autonomy in AI you've mentioned just now has this empowering effect. One is the last resort, it keeps you safe. The other is there's a, with the teaming and in general assistive, assistive AI. And I think there's a, there's always a race. So the world is full of, the world is complex, it's full of bad actors. So there's often a race to make sure that we keep this country safe, right? But with AI, there is a concern that it's a slightly different race. There's a lot of people in the AI space that are concerned about the AI arms race, that as opposed to the United States becoming, you know, having the best technology and therefore keeping us safe, we even, we lose ability to keep control of it. So this, the AI arms race, getting away from all of us humans. So do you share this worry? Do you share this concern when we're talking about military applications that too much control and decision-making capabilities given to software or AI? Well, I don't see it happening today. And in fact, this is something from a policy perspective, you know, it's obviously a very dynamic space, but the Department of Defense has put quite a bit of thought into that. And maybe before talking about the policy, I'll just talk about some of the why, and you alluded to it being a sort of a complicated and a little bit scary world out there, but there's some big things happening today. You hear a lot of talk now about a return to great powers competition, particularly around China and Russia with the US, but there are some other big players out there as well. And what we've seen is the deployment of some very, I'd say concerning new weapon systems, you know, particularly with Russia and breaching some of the IRBM, Intermediate-Range Ballistic Missile Treaties, that's been in the news a lot. You know, the building of artificial islands in the South China Sea by the Chinese and then arming those islands, the annexation of Crimea by Russia, the invasion of Ukraine. So there's some pretty scary things. And then you add on top of that, the North Korean threat has certainly not gone away. There's a lot going on in the Middle East with Iran in particular. And we see this global terrorism threat has not abated, right? So there are a lot of reasons to look for technology to assist with those problems, whether it's AI or other technologies like hypersonics, which we discussed. So now let me give just a couple of hypotheticals. So people react sort of in the second timeframe, right? You know, a photon hitting your eye to, you know, a movement is, you know, on the order of a few tenths of a second kinds of processing time. Roughly speaking, you know, computers are operating in the nanosecond timescale, right? So just to bring home what that means, a nanosecond to a second is like a second to 32 years. So seconds on the battlefield in that sense, literally are lifetimes. And so if you can bring an autonomous or AI enabled capability that will enable the human to shrink, maybe you've heard the term the OODA loop. So this whole idea that a typical battlefield decision is characterized by observe. So information comes in, orient, what does that mean in the context? Decide, what do I do about it? And then act, take that action. If you can use these capabilities to compress that OODA loop to stay inside what your adversary is doing, that's an incredible, powerful force on the battlefield. That's a really nice way to put it. That the role of AI and computing in general has a lot to benefit from just decreasing from 32 years to one second, as opposed to on the scale of seconds and minutes and hours making decisions that humans are better at making. And it actually goes the other way too. So that's on the short time scale. So humans kind of work in the one second, two seconds to eight hours. After eight hours, you get tired, you got to go to the bathroom, whatever the case might be. So there's this whole range of other things. Think about surveillance and guarding facilities. Think about moving material, logistics, sustainment. A lot of these, what they call dull, dirty and dangerous things that you need to have sustained activity, but it's sort of beyond the length of time that a human can practically do as well. So there's this range of things that are critical in military and defense applications that AI and autonomy are particularly well suited to. Now, the interesting question that you brought up is, okay, how do you make sure that stays within human control? And so that was the context for now the policy. And so there is a DOD directive called 3000.09, because that's the way we name stuff in this world. And I'd say it's well worth reading. It's only a couple of pages long, but it makes some key points. And it's really around making sure that there's human agency and control over use of semi-autonomous and autonomous weapon systems. Making sure that these systems are tested, verified, and evaluated in realistic, real-world type scenarios. Making sure that the people are actually trained on how to use them. Making sure that the systems have human machine interfaces that can show what state they're in and what kinds of decisions they're making. Making sure that you establish doctrine and tactics and techniques and procedures for the use of these kinds of systems. And by the way, none of this is easy, but I'm just trying to lay the picture of how the US has said, this is the way we're going to treat AI and autonomous systems. That it's not a free for all. And like there are rules of war and rules of engagement with other kinds of systems, think chemical weapons, biological weapons, we need to think about the same sorts of implications. And this is something that's really important for Lockheed Martin. I mean, obviously we are a hundred percent complying with our customer and the policies and regulations. But I mean, AI is an incredible enabler, say within the walls of Lockheed Martin in terms of improving production efficiency, helping engineers doing generative design, improving logistics, driving down energy costs. I mean, there are so many applications, but we're also very interested in some of the elements of ethical application within Lockheed Martin. So we need to make sure that things like privacy is taken care of, that we do everything we can to drive out bias in AI enabled kinds of systems. That we make sure that humans are involved in decisions that we're not just delegating accountability to algorithms. And so for us, it all comes back, I talked about culture before, and it comes back to sort of the Lockheed Martin culture and our core values. And so it's pretty simple for us to do what's right, respect others, perform with excellence. And now how do we tie that back to the ethical principles that will govern how AI is used within Lockheed Martin? And we actually have a world, so you might not know this, but there are actually awards for ethics programs. Lockheed Martin's had a recognized ethics program for many years. And this is one of the things that our ethics team is working with our engineering team on. One of the miracles to me, perhaps a layman, again, I was born in the Soviet Union. So I have echoes, at least in my family history of World War II and the Cold War. Do you have a sense of why human civilization has not destroyed itself through nuclear war, so nuclear deterrence? And thinking about the future, does technology have a role to play here? And what is the long-term future of nuclear deterrence look like? Yeah, this is one of those hard, hard questions. And I should note that Lockheed Martin is both proud and privileged to play a part in multiple legs of our nuclear and strategic deterrent systems like the Trident submarine-launched ballistic missiles. You talk about, is there still a possibility that the human race could destroy itself? I'd say that possibility is real, but interestingly, in some sense, I think the strategic deterrents have prevented the kinds of incredibly destructive world wars that we saw in the first half of the 20th century. Now, things have gotten more complicated since that time and since the Cold War. It is more of a multipolar great powers world today. Just to give you an example, back then, there were, in the Cold War timeframe, just a handful of nations that had ballistic missile capability by last count. And this is a few years old. There's over 70 nations today that have that, the similar kinds of numbers in terms of space-based capabilities. So the world has gotten more complex and more challenging, and the threats, I think, have proliferated in ways that we didn't expect. The nation today is in the middle of a recapitalization of our strategic deterrent. I look at that as one of the most important things that our nation can do. What is involved in deterrence? Is it being ready to attack, or is it the defensive systems that catch attacks? A little bit of both. And so it's a complicated game theoretical kind of program. But ultimately, we are trying to prevent the use of any of these weapons. And the theory behind prevention is that even if an adversary uses a weapon against you, you have the capability to essentially strike back and do harm to them that's unacceptable. And so that will deter them from making use of these weapon systems. The deterrence calculus has changed, of course, with more nations now having these kinds of weapons. But I think, from my perspective, it's very important to maintain a strategic deterrent. You have to have systems that you know will work when they're required to work. You know that they are required to work. You know that they have to be adaptable to a variety of different scenarios in today's world. And so that's what this recapitalization of systems that were built over previous decades, making sure that they are appropriate not just for today, but for the decades to come. So the other thing I'd really like to note is strategic deterrence has a very different character today. We used to think of weapons of mass destruction in terms of nuclear, chemical, biological. And today we have a cyber threat. We've seen examples of the use of cyber weaponry. And if you think about the possibilities of using cyber capabilities or an adversary attacking the US to take out things like critical infrastructure, electrical grids, water systems, those are scenarios that are strategic in nature to the survival of a nation as well. So that is the kind of world that we live in today. And part of my hope on this is one that we can also develop technical or technological systems, perhaps enabled by AI and autonomy, that will allow us to contain and to fight back against these kinds of new threats that were not conceived when we first developed our strategic deterrence. Yeah, I know that Lockheed is involved in cyber. I saw that you mentioned that. Nuclear almost seems easier than cyber because there's so many attack, there's so many ways that cyber can evolve in such an uncertain future. But talking about engineering with a mission, I mean, in this case, you're engineering systems that basically save the world. Like I said, we're privileged to work on some very challenging problems for very critical customers here in the US and with our allies abroad as well. Lockheed builds both military and non-military systems. And perhaps the future of Lockheed may be more in non-military applications if you talk about space and beyond. I say that as a preface to a difficult question. So President Eisenhower in 1961, in his farewell address, talked about the military industrial complex and that it shouldn't grow beyond what is needed. So what are your thoughts on those words, on the military industrial complex, on the concern of growth of their developments beyond what may be needed? That where it may be needed is a critical phrase, of course. And I think it is worth pointing out, as you noted, that Lockheed Martin, we're in a number of commercial businesses from energy to space to commercial aircraft. And so I wouldn't neglect the importance of those parts of our business as well. I think the world is dynamic. And there was a time, it doesn't seem that long ago to me, I was a graduate student here at MIT and we were talking about the peace dividend at the end of the Cold War. If you look at expenditure on military systems as a fraction of GDP, we're far below peak levels of the past. And to me, at least, it looks like a time where you're seeing global threats changing in a way that would warrant relevant investments in defensive capabilities. The other thing I'd note, for military and defensive systems, it's not quite a free market, right? We don't sell to people on the street. And that warrants a very close partnership between, I'd say, the customers and the people that design, build, and maintain these systems because of the very unique nature, the very difficult requirements, the very great importance on safety and on operating the way they're intended every time. And so that does create, and frankly, it's one of Lockheed Martin's great strengths, is that we have this expertise built up over many years in partnership with our customers to be able to design and build these systems that meet these very unique mission needs. Yeah, because building those systems is very costly. There's very little room for mistake. I mean, it's just Ben Rich's book and so on just tells the story. It's nerve-wracking just reading it. If you're an engineer, it reads like a thriller. Okay. Let's go back to space for a second. I guess... I'm always happy to go back to space. So a few quick, maybe out there, maybe fun questions. It may be a little provocative. What are your thoughts on the efforts of the new folks, SpaceX and Elon Musk? What are your thoughts about what Elon is doing? Do you see him as competition? Do you enjoy competition? What are your thoughts? Yeah. First of all, certainly Elon, I'd say SpaceX and some of his other ventures are definitely a competitive force in the space industry. And do we like competition? Yeah, we do. And we think we're very strong competitors. I think competition is what the US is founded on in a lot of ways and always coming up with a better way. And I think it's really important to continue to have fresh eyes coming in, new innovation. I do think it's important to have level playing fields. And so you want to make sure that you're not giving different requirements to different players. But I tell people, I spent a lot of time at places like MIT. I'm going to be at the MIT Beaverworks Summer Institute over the weekend here. And I tell people, this is the most exciting time to be in the space business in my entire life. And it is this explosion of new capabilities that have been driven by things like the massive increase in computing power, things like the massive increase in comms capabilities, advanced and additive manufacturing are really bringing down the barriers to entry in this field. And it's driving just incredible innovation. And it's happening at startups, but it's also happening at Lockheed Martin. You may not realize this, but Lockheed Martin working with Stanford actually built the first CubeSat that was launched here out of the US that was called Quakesat. And we did that with Stellar Solutions. This was right around just after 2000, I guess. And so we've been in that from the very beginning. And I talked about some of these like Maya and Orion, but we're in the middle of what we call smartsats and software-defined satellites that can essentially restructure and remap their purpose, their mission on orbit to give you almost unlimited flexibility for these satellites over their lifetimes. So those are just a couple of examples, but yeah, this is a great time to be in space. Absolutely. So Wright Brothers flew for the first time 116 years ago. So now we have supersonic stealth planes and all the technology we've talked about. What innovations, obviously you can't predict the future, but do you see Lockheed in the next 100 years? If you take that same leap, how will the world of technology and engineering change? I know it's an impossible question, but nobody could have predicted that we could even fly 120 years ago. So what do you think is the edge of possibility that we're going to be exploring in the next 100 years? I don't know that there is an edge. We've been around for almost that entire time, right? The Lockheed Brothers and Glenn L. Martin starting their companies in the basement of a church and an old service station. We're very different companies today than we were back then, right? And that's because we've continuously reinvented ourselves over all of those decades. I think it's fair to say, I know this for sure, the world of the future, it's going to move faster. It's going to be more connected. It's going to be more autonomous, and it's going to be more complex than it is today. And so this is the world as a CTO at Lockheed Martin that I think about, what are the technologies that we have to invest in? Whether it's things like AI and autonomy, you can think about quantum computing, which is an area that we've invested in to try to stay ahead of these technological changes. And frankly, some of the threats that are out there. I believe that we're going to be out there in the solar system, that we're going to be defending and defending well against probably military threats that nobody has even thought about today. We're going to use these capabilities to have far greater knowledge of our own planet, the depths of the oceans, all the way to the upper reaches of the atmosphere and everything out to the sun and to the edge of the solar system. So that's what I look forward to. And I'm excited, I mean, just looking ahead in the next decade or so to the steps that I see ahead of us in that time. I don't think there's a better place to end, Keokuk. Thank you so much. Lex, it's been a real pleasure. And sorry it took so long to get up here, but I'm glad we were able to make it happen.

https://youtu.be/anXep8kBOCg

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Tomaso Poggio: Brains, Minds, and Machines | Lex Fridman Podcast #13

The following is a conversation with Tommaso Poggio. He's a professor at MIT and is a director of the Center for Brains, Minds, and Machines. Cited over 100,000 times, his work has had a profound impact on our understanding of the nature of intelligence in both biological and artificial neural networks. He has been an advisor to many highly impactful researchers and entrepreneurs in AI, including Demis Hassabis of DeepMind, Amnon Shashua of Mobileye, and Christoph Koch of the Allen Institute for Brain Science. This conversation is part of the MIT course on artificial general intelligence and the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, iTunes, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D. And now, here's my conversation with Tommaso Poggio. You've mentioned that in your childhood, you've developed a fascination with physics, especially the theory of relativity, and that Einstein was also a childhood hero to you. What aspect of Einstein's genius, the nature of his genius, do you think was essential for discovering the theory of relativity? You know, Einstein was a hero to me and I'm sure to many people because he was able to make, of course, a major, major contribution to physics with simplifying a bit just a Gedanken experiment, a thought experiment. You know, imagining communication with lights between a stationary observer and somebody on a train. And I thought, you know, the fact that just with the force of his thought, of his thinking, of his mind, he could get to something so deep in terms of physical reality, how time depends on space and speed. It was something absolutely fascinating. It was the power of intelligence, the power of the mind. Do you think the ability to imagine, to visualize as he did, as a lot of great physicists do, do you think that's in all of us human beings? Or is there something special to that one particular human being? I think, you know, all of us can learn and have, in principle, similar breakthroughs. There are lessons to be learned from Einstein. He was one of five PhD students at ETH, the Eidgenossische Technische Hochschule in Zürich in physics. And he was the worst of the five. The only one who did not get an academic position when he graduated, when he finished his PhD, and he went to work, as everybody knows, for the patent office. And so it's not so much that he worked for the patent office, but the fact that obviously he was smart, but he was not a top student, obviously was the anti-conformist, was not thinking in the traditional way that probably his teachers and the other students were doing. So there is a lot to be said about, you know, trying to be, to do the opposite or something quite different from what other people are doing. That's certainly true for the stock market. Never buy if everybody's buying. And also true for science. Yes. So you've also mentioned, staying on the theme of physics, that you were excited at a young age by the mysteries of the universe that physics could uncover. Such, as I saw mentioned, the possibility of time travel. So the most out of the box question I think I'll get to ask today, do you think time travel is possible? Well, it would be nice if it were possible right now. You know, in science you never say no. But your understanding of the nature of time. Yeah. It's very likely that it's not possible to travel in time. You may be able to travel forward in time if we can, for instance, freeze ourselves or, you know, go on some spacecraft traveling close to the speed of light. But in terms of actively traveling, for instance, back in time, I find probably very unlikely. So do you still hold the underlying dream of the engineering intelligence that we'll build systems that are able to do such huge leaps, like discovering the kind of mechanism that would be required to travel through time? Do you still hold that dream or echoes of it from your childhood? Yeah. You know, I don't think whether there are certain problems that probably cannot be solved, depending what what you believe about the physical reality, like, you know, maybe totally impossible to create energy from nothing or to travel back in time. But about making machines that can think as well as we do or better or more likely, especially in the short and midterm, help us think better, which is in a sense is happening already with the computers we have. And it will happen more and more. But that I certainly believe. And I don't see in principle why computers at some point could not become more intelligent than we are, although the word intelligence is a tricky one and one who should discuss what I mean with that. And intelligence, consciousness, words like love is all these are very, you need to be disentangled. So you've mentioned also that you believe the problem of intelligence is the greatest problem in science, greater than the origin of life and the origin of the universe. You've also in the talk I've listened to said that you're open to arguments against you. So what do you think is the most captivating aspect of this problem of understanding the nature of intelligence? Why does it captivate you as it does? Well, originally, I think one of the motivation that I had as a, I guess, a teenager when I was infatuated with theory of relativity was really that I, I found that there was the problem of time and space and general relativity. But there were so many other problems of the same level of difficulty and importance that I could, even if I were Einstein, it was difficult to hope to solve all of them. So what about solving a problem or solution and allow me to solve all the problems? And this was what if we could find the key to an intelligence, you know, 10 times better or faster than Einstein. So that's sort of seeing artificial intelligence as a tool to expand our capabilities. But is there just an inherent curiosity in you and just understanding what it is in our, in here that makes it all work? Yes, absolutely. You're right. So I was starting, I started saying this was the motivation when I was a teenager, but, you know, soon after, I think the problem of human intelligence became a real focus of, you know, of my, of my science and my research, because I think he's, for me, the most interesting problem is really asking who we are, right? Is asking not only a question about science, but even about the very tool we are using to do science, which is our brain. How does our brain work? From where does it come from? What are its limitation? Can we make it better? Can we make it better? And that in many ways is the ultimate question that underlies this whole effort of science. So you've made significant contributions in both the science of intelligence and the engineering of intelligence. In a hypothetical way, let me ask, how far do you think we can get in creating intelligence systems without understanding the biological, the understanding how the human brain creates intelligence? Put another way, do you think we can build a strong AI system without really getting at the core, the functional, understanding the functional nature of the brain? Well, this is a real difficult question. You know, we did solve problems like flying flying without really using too much our knowledge about how birds fly. It was important, I guess, to know that you could have things heavier than air being able to fly like birds. But beyond that, probably we did not learn very much. You know, some, you know, the brothers Wright did learn a lot of observation about birds and designing their aircraft. But, you know, you can argue we did not use much of biology in that particular case. Now, in the case of intelligence, I think that it's a bit of a bet right now. If you are if you ask, OK, we we all agree we'll get at some point, maybe soon, maybe later to a machine that is indistinguishable from my secretary's in terms of what I can ask the machine to do. I think we'll get there. And now the question is, you can ask people, do you think we'll get there without any knowledge about, you know, the human brain or that the best way to get there is to understand better the human brain? Yeah. OK. This is, I think, an educated bet that different people with different background will decide in different ways. The recent history of the progress in AI in the last, I would say, five years or 10 years has been the main breakthroughs, the main recent breakthroughs. I really start from neuroscience. I can mention reinforcement learning as one is one of the algorithms at the core of AlphaGo, which is the system that beat the kind of an official world champion of Go, Lee Sedol, two or three years ago in Seoul. That's one. And that started really with the work of Pavlov in 1900, Marvin Minsky in the 60s, many other neuroscientists later on. And deep learning started, which is at the core again of AlphaGo and systems like autonomous driving systems for cars, like the systems that Mobili, which is a company started by one of my ex-postdocs, Amnon Shashua. So that is at the core of those things. And deep learning, really the initial ideas in terms of the architecture of this layered hierarchical networks started with the work of Torsten Wiesel and David Hubel at Harvard up the river in the 60s. So recent history suggests that neuroscience played a big role in these breakthroughs. My personal bet is that there is a good chance they continue to play a big role maybe not in all the future breakthroughs, but in some of them. Leaves an inspiration. At least in an inspiration, absolutely, yes. So you studied both artificial and biological neural networks. You said these mechanisms that underlie deep learning and reinforcement learning. But there is nevertheless significant differences between biological and artificial neural networks as they stand now. So between the two, what do you find is the most interesting, mysterious, maybe even beautiful difference as it currently stands in our understanding? I must confess that until recently I found that the artificial networks too simplistic relative to real neural networks. But recently I've been starting to think that yes, they're a very big simplification of what you find in the brain. But on the other hand, are much closer in terms of the architecture to the brain than other models that we had, that computer science used as model of thinking, which were mathematical logics, you know, Lisp, prologue, and those kinds of things. So in comparison to those, they're much closer to the brain. You have networks of neurons, which is what the brain is about. The artificial neurons in the models, as I said, caricature of the biological neurons, but they're still neurons, single units communicating with other units, something that is absent in the traditional computer type models of mathematics, reasoning, and so on. So what aspect would you like to see in artificial neural networks added over time as we try to figure out ways to improve them? So one of the main differences and, you know, problems in terms of deep learning today, and it's not only deep learning, and the brain is the need for deep learning techniques to have a lot of labeled examples. You know, for instance, for ImageNet, you have like a training set, which is 1 million images, each one labeled by some human in terms of which object is there. And it's clear that in biology, a baby may be able to see a million of images in the first years of life, but will not have a million of labels given to him or her by parents or caretakers. So how do you solve that? You know, I think there is this interesting challenge that today, deep learning and related techniques are all about big data, big data meaning a lot of a lot of examples labeled by humans. Whereas in nature, you have so that this big data is n going to infinity, that's the best, you know, n meaning labeled data. But I think the biological world is more n going to 1. A child can learn. It's a beautiful way to put it. Very small number of, you know, labeled examples. Like you tell a child, this is a car. You don't need to say like in ImageNet, you know, this is a car, this is a car. This is not a car. This is not a car. 1 million times. So and of course, with AlphaGo and or at least the AlphaZero variants, there's because of the world of Go is so simplistic that you can actually learn by yourself through self play. You can play against each other. And the real world, I mean, the visual system that you've studied extensively is a lot more complicated than the game of Go. So on the comment about children, which are fascinatingly good at learning new stuff. How much of it do you think is hardware? How much of it is software? Yeah, that's a good, deep question is in a sense is the old question of nurture and nature. How much is in the gene and how much is in the experience of an individual? Obviously, it's both that play a role. And I believe that the way evolution gives put prior information, so to speak, hardware is not really hardware. But that's essentially an hypothesis. I think what's going on is that evolution has, you know, almost necessarily, if you believe in Darwin is very opportunistic. And and think about our DNA and the DNA of Drosophila. Our DNA does not have many more genes than Drosophila. The fly. The fly. The fruit fly. Now, we know that the fruit fly does not learn very much during its individual existence. It looks like one of this machinery that it's really mostly not 100 percent, but, you know, 95 percent hard coded by the genes. But since we don't have many more genes than Drosophila, evolution could encode in us a kind of general learning machinery and then had to give very weak priors, like, for instance, let me give a specific example, which is a recent work by a member of our Center for Brains, Minds and Machines. We know because of work of other people in our group and other groups that there are cells in a part of our brain neurons that are tuned to faces. They seem to be involved in face recognition. Now, this face area exists, seems to be present in young children and adults. And one question is, is there from the beginning, is hardwired by evolution or, you know, somehow is learned very quickly? Lexer So what's your, by the way, a lot of the questions I'm asking, the answer is we don't really know. But as a person who has contributed some profound ideas in these fields, you're a good person to guess at some of these. So, of course, there's a caveat before a lot of the stuff we talked about. But what is your hunch? Is the face, the part of the brain that seems to be concentrated on face recognition, are you born with that? Or you just, is designed to learn that quickly, like the face of the mother? And so... Kahneman My hunch, my bias was the second one, learned very quickly. And it turns out that Marge Livingstone at Harvard has done some amazing experiments in which she raised baby monkeys, depriving them of faces during the first weeks of life. So they see technicians, but the technician have a mask. And so when they looked at the area in the brain of these monkeys, that usually you find faces, they found no face preference. So my guess is that what evolution does in this case is there is a plastic area, which is plastic, which is kind of predetermined to be imprinted very easily. But the command from the gene is not a detailed circuitry for a face template. Could be, but this will require probably a lot of bits, you have to specify a lot of connection of a lot of neurons. Instead, the command from the gene is something like imprint, memorize what you see most often in the first two weeks of life, especially in connection with food. And maybe nipples, I don't know. Right. Well, source of food. And so in that area is very plastic at first and then solidifies. It'd be interesting if a variant of that experiment would show a different kind of pattern associated with food than a face pattern, whether that could stick. There are indications that during that experiment, what the monkeys saw quite often were the blue gloves of the technicians that were giving to the baby monkeys the milk. And some of the cells, instead of being face sensitive in that area, are hand sensitive. That's fascinating. Can you talk about what are the different parts of the brain and in your view, sort of loosely, and how do they contribute to intelligence? Do you see the brain as a bunch of different modules and they together come in the human brain to create intelligence? Or is it all one mush of the same kind of fundamental architecture? Yeah, that's an important question. And there was a phase in neuroscience back in the 1950s or so in which it was believed for a while that the brain was equipotential. This was the term you could cut out a piece and nothing special happened apart a little bit less performance. There was a surgeon, Lashley, who did a lot of experiments of this type with mice and rats and concluded that every part of the brain was essentially equivalent to any other one. It turns out that that's really not true. There are very specific modules in the brain, as you said, and people may lose the ability to speak if you have a stroke in a certain region or may lose control of their legs in another region. So they're very specific. The brain is also quite flexible and redundant, so often it can correct things and kind of take over functions from one part of the brain to the other. But really, there are specific modules. So the answer that we know from this old work, which was basically based on lesions, either on animals or very often there was a mine of very interesting data coming from the war, from different types of different types of injuries that soldiers had in the brain. And more recently, functional MRI, which allow you to check which part of the brain are active when you are doing different tasks, can replace some of this. You can see that certain parts of the brain are involved, are active. In vision, language. Yeah, that's right. But sort of taking a step back to that part of the brain that discovers, that specializes in the face and how that might be learned, what's your intuition behind, is it possible that from a physicist's perspective, when you get lower and lower, that it's all the same stuff and it just, when you're born, it's plastic and quickly figures out this part is going to be about vision, this is going to be about language, this is about common sense reasoning. Do you have an intuition that that kind of learning is going on really quickly or is it really kind of solidified in hardware? That's a great question. So there are parts of the brain like the cerebellum or the hippocampus that are quite different from each other. They clearly have different anatomy, different connectivity. Then there is the cortex, which is the most developed part of the brain in humans. And in the cortex, you have different regions of the cortex that are responsible for vision, for audition, for motor control, for language. Now, one of the big puzzles of this is that in the cortex, is the cortex, is the cortex, looks like it is the same in terms of hardware, in terms of type of neurons and connectivity across these different modalities. So for the cortex, I think aside this other parts of the brain like spinal cord, hippocampus, cerebellum and so on, for the cortex, I think your question about hardware and software and learning and so on, it's, I think is rather open. And I find very interesting, for instance, to think about an architecture, computer architecture that is good for vision and at the same time is good for language. Seems to be, you know, so different problem areas that you have to solve. But the underlying mechanism might be the same and that's really instructive for It may be. artificial neural networks. So you've done a lot of great work in vision, in human vision, computer vision. And you mentioned the problem of human vision is really as difficult as the problem of general intelligence. And maybe that connects to the cortex discussion. Can you describe the human visual cortex and how the humans begin to understand the world through the raw sensory information? What's, for folks enough, familiar, especially in on the computer vision side, we don't often actually take a step back except saying with a sentence or two that one is inspired by the other. What is it that we know about the human visual cortex? That's interesting. We know quite a bit. At the same time, we don't know a lot. But the bit we know, you know, in a sense, we know a lot of the details and many we don't know. And we know a lot of the top level, the answer to the top level question, but we don't know some basic ones, even in terms of general neuroscience, forgetting vision. You know, why do we sleep? It's such a basic question. And we really don't have an answer to that. Do you think, so taking a step back on that, so sleep, for example, is fascinating. Do you think that's a neuroscience question? Or if we talk about abstractions, what do you think is an interesting way to study intelligence or most effective on the levels of abstractions? Is it chemical? Is it biological? Is it electrophysical? Mathematical, as you've done a lot of excellent work on that side. Which psychology, sort of like, at which level of abstraction do you think? Well, in terms of levels of abstraction, I think we need all of them. It's one, you know, it's like if you ask me, what does it mean to understand the computer, right? And that's much simpler. But in a computer, I could say, well, I understand how to use PowerPoint. That's my level of understanding a computer. It's, it is reasonable, you know, it gives me some power to produce slides and beautiful slides. And now you can ask somebody else, he says, well, I know how the transistor work that are inside the computer. I can write the equation for, you know, transistor and diodes and circuits, logical circuits. And I can ask this guy, do you know how to operate PowerPoint? No idea. Right? So do you think if we discovered computers walking amongst us full of these transistors that are also operating under Windows and have PowerPoint, do you think it's digging in a little bit more? How useful is it to understand the transistor in order to be able to understand PowerPoint and these higher level intelligent processes? So I think in the case of computers, because they were made by engineers by us, this different level of understanding are rather separate on purpose. You know, they are separate modules so that the engineer that designed the circuit for the chips does not need to know what is inside PowerPoint and somebody can write to the software translating from one to the other. So in that case, I don't think understanding the transistor help you understand PowerPoint or very little. If you want to understand the computer, this question, you know, I would say you have to understand it at different levels if you really want to build it. But for the brain, I think these levels of understanding, so the algorithms, which kind of computation, you know, the equivalent PowerPoint and the circuits, you know, the transistors, I think they are much more intertwined with each other. There is not, you know, a neatly level of the software separate from the hardware. And so that's why I think in the case of the brain, the problem is more difficult and more than for computers requires the interaction, the collaboration between different types of expertise. So the brain is a big hierarchical mess, so you can't just disentangle levels? I think you can, but it's much more difficult and it's not completely obvious. And as I said, I think he's one of the person I think is the greatest problem in science. So, you know, I think it's fair that it's difficult. That's a difficult one. That said, you do talk about compositionality and why it might be useful. And when you discuss why these neural networks in artificial or biological sense, learn anything, you talk about compositionality. See, there's a sense that nature can be disentangled. Well, all aspects of our cognition could be disentangled a little to some degree. So why do you think, what, first of all, how do you see compositionality and why do you think it exists at all in nature? I spoke about, I use the term compositionality when we looked at deep neural networks, multi layers, and trying to understand when and why they are more powerful than more classical one layer networks like linear classifier, kernel machines, so-called. And what we found is that in terms of approximating or learning or representing a function, a mapping from an input to an output, like from an image to the label in the image, if this function has a particular structure, then deep networks are much more powerful than shallow networks to approximate the underlying function. And the particular structure is a structure of compositionality. If the function is made up of functions of functions, so that you need to look on when you are interpreting an image, classifying an image, you don't need to look at all pixels at once, but you can compute something from small groups of pixels, and then you can compute something on the output of this local computation and so on. It is similar to what you do when you read the sentence, you don't need to read the first and the last letter, but you can read syllables, combine them in words, combine the words in sentences. So this is this kind of structure. So that's as part of a discussion of why deep neural networks may be more effective than the shallow methods. And is your sense for most things we can use neural networks for, those problems are going to be compositional in nature, like language, like vision, how far can we get in this kind of way? Right. So here is almost philosophy. Well, let's go there. Yeah, let's go there. So a friend of mine, Max Tegmark, who is a physicist at MIT. I've talked to him on a few occasions. I've talked to him on this thing. Yeah. And he disagrees with you, right? A little bit. Yeah, we agree on most, but the conclusion is a bit different. His conclusion is that for images, for instance, the compositional structure of this function that we have to learn or to solve these problems comes from physics, comes from the fact that you have local interactions in physics between atoms and other atoms, between particle of matter and other particles, between planets and other planets, between stars and other, it's all local. Yeah. And that's true, but you could push this argument a bit further. Not this argument, actually, you could argue that, you know, maybe that's part of the truth, but maybe what happens is kind of the opposite, is that our brain is wired up as a deep network. So it can learn So it can learn, understand, solve problems that have this compositional structure. And it cannot do, it cannot solve problems that don't have this compositional structure. So the problems we are accustomed to, we think about, we test our algorithms on, are this compositional structure because our brain is made up. And that's in a sense an evolutionary perspective that we've, so the ones that didn't have, that weren't dealing with a compositional nature of reality died off? Yes, but also could be maybe the reason why we have this local connectivity in the brain, like simple cells in cortex looking only at the small part of the image, each one of them, and then other cells looking at the small number of these simple cells and so on. The reason for this may be purely that it was difficult to grow longer range connectivity. So suppose it's, you know, for biology, it's possible to grow short range connectivity, but not longer range also, because there is a limited number of longer range. And so you have this limitation from the biology. And this means you build a deep convolutional network. This would be something like a deep convolutional network. And this is great for solving certain class of problems. These are the ones we find easy and important for our life. And yes, they were enough for us to survive. And you can start a successful business on solving those problems, right? Like with Mobileye, driving is a compositional problem. So on the learning task, I mean, we don't know much about how the brain learns in terms of optimization. So the thing that's stochastic gradient descent is what artificial neural networks use for the most part to adjust the parameters in such a way that it's able to deal based on the label data, it's able to solve the problem. So what's your intuition about why it works at all? How hard of a problem it is to optimize a neural network, artificial neural network? Is there other alternatives? Just in general, your intuition is behind this very simplistic algorithm that seems to do pretty good, surprising. Yes, yes. So I find neuroscience, the architecture of cortex is really similar to the architecture of deep networks. So there is a nice correspondence there between the biology and this kind of local connectivity, hierarchical architecture. The stochastic gradient descent, as you said, is a very simple technique. It seems pretty unlikely that biology could do that from what we know right now about cortex and neurons and synapses. So it's a big question open whether there are other optimization learning algorithms that can replace stochastic gradient descent. And my guess is yes, but nobody has found yet a real answer. I mean, people are trying, still trying, and there are some interesting ideas. The fact that stochastic gradient descent is so successful, this has become clearly not so mysterious. And the reason is that it's an interesting fact, you know, is a change in a sense in how people think about statistics. And this is the following, is that typically when you had data and you had, say, a model with parameters, you are trying to fit the model to the data, you know, to fit the parameter. Typically the kind of crowd wisdom type idea was you should have at least twice the number of data than the number of parameters. Maybe 10 times is better. Now, the way you train neural network these days is that they have 10 or 100 times more parameters than data, exactly the opposite. And which, you know, it has been one of the puzzles about neural networks. How can you get something that really works when you have so much freedom in, you know. From that little data you can generalize somehow. Right, exactly. Do you think the stochastic nature of it is essential, the randomness? So I think we have some initial understanding why this happens. But one nice side effect of having this overparameterization, more parameters than data, is that when you look for the minima of a loss function, like stochastic gradient descent is doing, you find, I made some calculations based on some old basic theorem of algebra called the Bezout theorem, and that gives you an estimate of the number of solution of a system of polynomial equation. Anyway, the bottom line is that there are probably more minima for a typical deep networks than atoms in the universe. Just to say there are a lot. Because of the overparameterization. More global minima, zero minima, good minima. More global minima. Yeah, a lot of them. So you have a lot of solutions. So it's not so surprising that you can find them relatively easily. And this is because of the overparameterization. The overparameterization sprinkles that entire space with solutions that are pretty good. Yeah, it's not so surprising, right? It's like, you know, if you have a system of linear equation and you have more unknowns than equations, then you have, we know, you have an infinite number of solutions. And the question is to pick one. That's another story. But you have an infinite number of solutions. So there are a lot of value of your unknowns that satisfy the equations. But it's possible that there's a lot of those solutions that aren't very good. What's surprising is that they're pretty good. Why can you pick one that generalizes well? Yeah, exactly. But that's a separate question with separate answers. One theorem that people like to talk about that kind of inspires imagination of the power of neural networks is the universal approximation theorem. That you can approximate any computable function with just a finite number of neurons in a single hidden layer. Do you find this theorem one surprising? Do you find it useful, interesting, inspiring? No, this one, you know, I never found it very surprising. It was known since the 80s, since I entered the field, because it's basically the same as Weierstrass theorem, which says that I can approximate any continuous function with a polynomial of sufficiently, with a sufficient number of terms, monomials. It's basically the same and the proofs are very similar. So your intuition was there was never any doubt that neural networks in theory could be very strong approximators. Right. The question, the interesting question is that if this theorem says you can approximate fine, but when you ask how many neurons, for instance, or in the case of polynomial, how many monomials I need to get a good approximation, then it turns out that that depends on the dimensionality of your function, how many variables you have. But it depends on the dimensionality of your function in a bad way. It's, for instance, suppose you want an error, which is no worse than 10%. In your approximation, you come up with a network that approximates your function within 10%. Then it turns out that the number of units you need are in the order of 10 to the dimensionality d, how many variables. So if you have, you know, two variables, these two, you have 100 units and okay. But if you have say 200 by 200 pixel images, now this is, you know, 40,000, whatever. We again go to the size of the universe pretty quickly. Yeah, exactly. 10 to the 40,000 or something. And so this is called the curse of dimensionality. Not, you know, quite appropriately. And the hope is with the extra layers, you can remove the curse. What we proved is that if you have deep layers, hierarchical architecture with local connectivity of the type of convolutional deep learning, and if you're dealing with a function that has this kind of hierarchical architecture, then you avoid completely the curse. You've spoken a lot about supervised deep learning. Yeah. What are your thoughts, hopes, views on the challenges of unsupervised learning with GANs, with generative adversarial networks? Do you see those as distinct, the power of GANs, the power of GANs, do you see those as distinct from supervised methods and neural networks? Are they really all in the same representation ballpark? GANs is one way to get estimation of probability densities, which is somewhat new way that people have not done before. I don't know whether this will really play an important role in, you know, in intelligence or it's interesting. I'm less enthusiastic about it to many people in the field. I have the feeling that many people in the field are really impressed by the ability of producing realistic looking images in this generative way. Which describes the popularity of the methods, but you're saying that while that's exciting and cool to look at, it may not be the tool that's useful for it. So you describe it kind of beautifully. Current supervised methods go end to infinity in terms of number of labeled points, and we really have to figure out how to go to end to one. And you're thinking GANs might help, but they might not be the right. I don't think for that problem, which I really think is important, I think they may help. They certainly have applications, for instance, in computer graphics. And, you know, I did work long ago, which was a little bit similar in terms of saying, okay, I have a network and I present images and I can input its images and output is, for instance, the pose of the image, you know, a face, how much is smiling, is rotated 45 degrees or not. What about having a network that I train with the same data set, but now I invert input and output. Now the input is the pose or the expression, a number, set of numbers, and the output is the image and I train it. And we did pretty good, interesting results in terms of producing very realistic looking images. It was, you know, a less sophisticated mechanism, but the output was pretty less than GANs, but the output was pretty much of the same quality. So I think for a computer graphics type application, yeah, definitely GANs can be quite useful and not only for that, but for, you know, helping, for instance, on this problem of unsupervised example of reducing the number of labeled examples. I think people, it's like they think they can get out more than they put in. You know, it's- There's no free lunches. Yeah, right. So what do you think, what's your intuition? How can we slow the growth of end to infinity in supervised, end to infinity in supervised learning? So for example, Mobileye has very successfully, I mean, essentially annotated large amounts of data to be able to drive a car. Now, one thought is, so we're trying to teach machines, a school of AI, and we're trying to, so how can we become better teachers maybe? That's one way. No, you're, you know, I like that because one, again, one caricature of the history of computer science, you could say, is, begins with programmers, expensive. Continuous labelers, cheap. And the future will be schools like we have for kids. Currently, the labeling methods, we're not selective about which examples we teach networks with. So I think the focus of making one-shot networks that learn much faster is often on the architecture side. But how can we pick better examples with which to learn? Do you have intuitions about that? Well, that's part of the problem. But the other one is, you know, if we look at biology, a reasonable assumption, I think, is in the same spirit that I said, evolution is opportunistic and has weak priors. You know, the way I think the intelligence of a child, a baby may develop is by bootstrapping weak priors from evolution. For instance, in, you can assume that you have in most organisms, including human babies, built in some basic machinery to detect motion and relative motion. And in fact, there is, you know, we know all insects from fruit flies to other animals, they have this. Even in the retinas, in the very peripheral part, it's very conserved across species, something that evolution discovered early. It may be the reason why babies tend to look, in the first few days, to moving objects and not to not moving objects. Now, moving objects means, okay, they're attracted by motion. But motion also means that motion gives automatic segmentation from the background. So because of motion boundaries, you know, either the object is moving, or the eye of the baby is tracking the moving object and the background is moving, right? Lex Massimino Yeah, so just purely on the visual characteristics of the scene, that seems to be the most useful. Fabrizio D'Agostino Right. So it's like looking at an object without background. It's ideal for learning the object. Otherwise, it's really difficult, because you have so much stuff. So suppose you do this at the beginning, first weeks, then after that, you can recognize object. Now they are imprinted a number of them, even in the background, even without motion. Lex Massimino So that's the, by the way, I just want to ask on the object recognition problem. So there is this being responsive to movement and doing edge detection, essentially. What's the gap between being effectively effective at visually recognizing stuff, detecting where it is, and understanding the scene? Is this a huge gap in many layers? Fabrizio D'Agostino Or is it? Are we? Is it close? Lex Massimino No, I think that's a huge gap. I think present algorithms with all the success that we have, and the fact that there are a lot of very useful, I think we are in a golden age for applications of low level vision and low level speech recognition and so on, you know, Alexa and so on. There are many more things of similar level to be done, including medical diagnosis and so on. But we are far from what we call understanding of a scene, of language, of actions of people. That is, despite the claims, that's, I think, very far. Lex Massimino We're a little bit off. So in popular culture, and among many researchers, some of which I've spoken with, the Stuart Russell and Elon Musk, in and out of the AI field, there's a concern about the existential threat of AI. And how do you think about this concern? And is it valuable to think about large scale, long term unintended consequences of intelligence systems we try to build? Lex Massimino I always think it's better to worry first, you know, early rather than late. So, Peter Robinson So worry is good. Lex Massimino Yeah, I'm not against worrying at all. Peter Robinson Yeah. Lex Massimino Personally, I think that, you know, it will take a long time before there is a real reason to be worried. But as I said, I think it's good to put in place and think about possible safety against what I find a bit misleading, things like that have been said by people I know, like Elon Musk, and what is Bostrom in particular, and what is his first name? Peter Robinson Nick. Lex Massimino Nick Bostrom, right. You know, and a couple of other people that for instance, AI is more dangerous than nuclear weapons. Peter Robinson Right. Lex Massimino Yeah, I think that's really wrong. That can be misleading, because in terms of priority, we should still be more worried about nuclear weapons and, you know, what people are doing about it and so on than AI. Peter Robinson And you've spoken about Demos Hesavis and yourself saying that you think it'll be about 100 years out before we have a general intelligence system that's on par with a human being. Do you have any updates for those predictions? Lex Massimino Well, I think he said, Peter Robinson He said 20, I think. Lex Massimino He said 20, right. This was a couple of years ago. I have not asked him again. So should I? Peter Robinson Your own prediction. What's your prediction about when you'll be truly surprised? And what's the confidence interval on that? Lex Massimino You know, it's so difficult to predict the future and even the presence of it. Peter Robinson It's pretty hard to predict. Lex Massimino But I would be, as I said, this is completely, it would be more like Rod Brooks. I think he's about 200 years. Peter Robinson 200 years. Lex Massimino When we have this kind of AGI system, artificial general intelligence system, and you're sitting in a room with her, him, it, do you think it will be the underlying design of such a system is something we'll be able to understand? It'll be simple. Do you think it'll be explainable, understandable by us? Your intuition again, we're in the realm of philosophy a little bit. Peter Robinson Well, probably no. But again, it depends what you really mean for understanding. So I think, you know, we don't understand how deep networks work. I think we're beginning to have a theory now. But in the case of deep networks, or even in the case of the simpler kernel machines or linear classifier, we really don't understand the individual units also. But we understand what the computation and the limitations and the properties of it are. It's similar to many things. You know, what does it mean to understand how a fusion bomb works? How many of us, many of us understand the basic principle. And some of us may understand deeper details. Lex Mosser And that sense understanding is as a community, as a civilization, can we build another copy of it? And in that sense, do you think there'll be, there'll need to be some evolutionary component where it runs away from our understanding? Or do you think it could be engineered from the ground up? The same way you go from the transistor to PowerPoint? Fabio Pino All right. So many years ago, this was actually 40, 41 years ago, I wrote a paper with David Marr, who was one of the founding father of computer vision, computational vision. I wrote a paper about levels of understanding, which is related to the question I discussed earlier about understanding PowerPoint, understanding transistors, and so on. And, you know, in that kind of framework, we had the level of the hardware and the top level of the algorithms. We did not have learning. Recently, I updated adding levels, and one level I added to those three was learning. So, and you can imagine, you could have a good understanding of how you construct a learning machine, like we do. But being unable to describe in detail what the learning machines will discover, right? Now, that would be still a powerful understanding if I can build a learning machine, even if I don't understand in detail every time I need to learn something. Luke Simon Just like our children, if they start listening to a certain type of music, I don't know, Miley Cyrus or something, you don't understand why they came to that particular preference, but you understand the learning process. That's very interesting. So, on learning for systems to be part of our world, it has a certain, one of the challenging things that you've spoken about is learning ethics, learning morals. And how hard do you think is the problem of, first of all, humans understanding our ethics? What is the origin and the neural and low level of ethics? What is it at the higher level? Is it something that's learnable for machines in your intuition? Miley Cyrus I think, yeah, ethics is learnable, very likely. I think it's one of these problems where I think understanding the neuroscience of ethics, you know, people discuss there is an ethics of neuroscience. You know, how a neuroscientist should or should not behave. You can think of a neurosurgeon and the ethics rule he has to obey or she has to obey. But I'm more interested in the neuroscience of ethics. Matthew Feeney You're blowing my mind right now. The neuroscience of ethics is very meta. Miley Cyrus Yeah, and, you know, I think that would be important to understand also for being able to design machines that are ethical machines in our sense of ethics. Matthew Feeney And you think there is something in neuroscience, there's patterns, tools in neuroscience that can help us shed some light on ethics? Or is it mostly on the psychologists of sociology and which higher level? Miley Cyrus No, there is psychology, but there is also in the meantime, there is evidence, fMRI, of specific areas of the brain that are involved in certain ethical judgment. And not only this, you can stimulate those area with magnetic fields and change the ethical decisions. Matthew Feeney Yeah. Wow. Miley Cyrus So that's work by a colleague of mine, Rebecca Sachs, and there is other researchers doing similar work. And I think, you know, this is the beginning. But ideally, at some point, we'll have an understanding of how this works, and why it evolved, right? Matthew Feeney The big why question. Yeah, it must have some purpose. Miley Cyrus Yeah, obviously, it has, you know, some social purposes, probably. Matthew Feeney If neuroscience holds the key to at least eliminate some aspect of ethics, that means it could be a learnable problem. Miley Cyrus Yeah, exactly. Matthew Feeney And as we're getting into harder and harder questions, let's go to the hard problem of consciousness. Is this an important problem for us to think about and solve on the engineering of intelligence side of your work of our dream? Miley Cyrus You know, it's unclear. So, you know, again, this is a deep problem, partly because it's very difficult to define consciousness. And there is a debate among neuroscientists about whether consciousness and philosophers, of course, whether consciousness is something that requires flesh and blood, so to speak, or could be, you know, that we could have silicon devices that are conscious, or up to statement like everything has some degree of consciousness and some more than others. This is like, you know, like Giulio Tognoni and Fee. Matthew Feeney We just recently talked to Christoph Koch. Miley Cyrus Okay. Matthew Feeney So he's Miley Cyrus Christoph was my first graduate student. Matthew Feeney Yeah. Do you think it's important to illuminate aspects of consciousness in order to engineer intelligence systems? Do you think an intelligence system would ultimately have consciousness? Are they interlinked? Christoph Koch You know, most of the people working in artificial intelligence, I think, would answer, we don't strictly need consciousness to have an intelligent system. Miley Cyrus That's sort of the easier question, because it's a very engineering answer to the question. Pass the Turing test, we don't need consciousness. But if you were to go, do you think it's possible that we need to have that kind of self-awareness? Christoph Koch We may, yes. So for instance, I personally think that when test a machine or a person in a Turing test, in an extended Turing test, I think consciousness is part of what we require in that test, you know, implicitly, to say that this is intelligent. Christoph disagrees. Miley Cyrus Yes, he does. Despite many other romantic notions he holds, he disagrees with that one. Christoph Koch Yes, that's right. So, you know, we'll see. Miley Cyrus Do you think, as a quick question, Ernest Becker, fear of death, do you think mortality and those kinds of things are important for consciousness and for intelligence? The finiteness of life, finiteness of existence, or is that just a side effect, an evolutionary side effect that's useful for natural selection? Do you think this kind of thing that we're going to, this interview is going to run out of time soon, our life will run out of time soon. Do you think that's needed to make this conversation good and life good? Christoph Koch You know, I never thought about it. It's a very interesting question. I think Steve Jobs in his commencement speech at Stanford argued that, you know, having a finite life was important for stimulating achievements. So it was a different… Miley Cyrus You live every day like it's your last, right? Christoph Koch Yeah, yeah. So, rationally, I don't think strictly you need mortality for consciousness, but… Miley Cyrus Who knows? They seem to go together in our biological system, right? Christoph Koch Yeah, yeah. Miley Cyrus You've mentioned before, and the students are associated with, AlphaGo immobilized the big recent success stories in AI. I think it's captivated the entire world of what AI can do. So what do you think will be the next breakthrough? And what's your intuition about the next breakthrough? Christoph Koch Of course, I don't know where the next breakthrough is. I think that there is a good chance, as I said before, that the next breakthrough would also be inspired by, you know, neuroscience. But which one, I don't know. Miley Cyrus And there's… so MIT has this quest for intelligence. And there's a few moonshots, which, in that spirit, which ones are you excited about? Which projects kind of… Christoph Koch Well, of course, I'm excited about to one of the moonshots with which is our Center for Brains, Minds and Machines, which is the one which is fully funded by NSF. And it's a, it is about visual intelligence. Miley Cyrus And that one is particularly about understanding. Christoph Koch Visual intelligence, so the visual cortex and, and visual intelligence in the sense of how we look around ourselves and understand the world around ourselves, you know, meaning what, what is going on, how we could go from here to there without hitting obstacles. You know, whether there are other agents, people in the environment, these are all things that we perceive very quickly. And, and it's something actually quite close to being conscious, not quite. But, you know, there is this interesting experiment that was run at Google X, which is in a sense is just a virtual reality experiment, but in which they had subjects sitting, say, in a chair with goggles like Oculus and so on, earphones, and they were seeing through the eyes of a robot nearby, two cameras, microphones for receiving. So their sensory system was there. And the impression of all the subject very strong, they could not shake it off, was that they were where the robot was. They could look at themselves from the robot and still feel they were, they were where the robot is. They were looking at their body. Their self had moved. Lex Well, so some aspect of seeing understanding has to have ability to place yourself, have a self-awareness about your position in the world and what the world is. So, so we may have to solve the hard problem of consciousness to solve it. Christof Koch On their way. Yes. Lex Well, it's quite, quite a moonshot. So you've been an advisor to some incredible minds, including Demis Hassabis, Christof Koch, Amnon Shashua, like you said, all went on to become seminal figures in their respective fields. From your own success as a researcher and from perspective as a mentor of these researchers, having guided them, in the way of advice, what does it take to be successful in science and engineering careers? Whether you're talking to somebody in their teens, 20s and 30s, what does that path look like? Christof Koch It's curiosity and having fun. And I think it's important also having fun with other curious minds. Lex It's the people you're surrounded with too. Christof Koch Yeah. Lex Fun and curiosity. Is there, you mentioned Steve Jobs, is there also an underlying ambition that's unique that you saw or is it really does boil down to insatiable curiosity and fun? Christof Koch Well, of course, it's being curious in an active and ambitious way. Yes. Definitely. But I think sometimes in science, there are friends of mine who are like this, you know, there are some of the scientists like to work by themselves and kind of communicate only when they completed their work or discover something. I think I always found the actual process of, you know, discovering something. It's more fun if it's together with other intelligent and curious and fun people. Lex So if you see the fun in that process, the side effect of that process will be that you'll actually end up discovering some interesting things. So as you've led many incredible efforts here, what's the secret to being a good advisor, mentor, leader in a research setting? Is it a similar spirit or yeah, what advice could you give to people, young faculty and so on? Christof Koch It's partly repeating what I said about an environment that should be friendly and fun and ambitious. And, you know, I think I learned a lot from some of my advisors and friends and some were physicists. And there was, for instance, this behavior that was encouraged of when somebody comes with a new idea in the group, you're, unless it's really stupid, but you are always enthusiastic. And then you're enthusiastic for a few minutes, for a few hours, then you start, you know, asking critically a few questions, testing this. But, you know, this is a process that is, I think it's very, very good. You have to be enthusiastic. Sometimes people are very critical from the beginning. That's not... Lex Yes, you have to give it a chance. Christof Koch Yes. Lex That seed to grow. That said, with some of your ideas, which are quite revolutionary, so there's a witness, especially in the human vision side and neuroscience side, there could be some pretty heated arguments. Do you enjoy these? Is that a part of science and academic pursuits that you enjoy? Is that something that happens in your group as well? Christof Koch Yeah, absolutely. I also spent some time in Germany. Again, there is this tradition in which people are more forthright, less kind than here. So, you know, in the US, when you write a bad letter, you still say, this guy is nice. Lex Yes, yes. Yeah, here in America, it's degrees of nice. Christof Koch Yes. Lex It's all just degrees of nice. Christof Koch Right, right. So as long as this does not become personal, and it's really like, you know, a football game with its rules, that's great. Lex That's fun. So if you somehow find yourself in a position to ask one question of an oracle, like a genie, maybe a god, and you're guaranteed to get a clear answer, what kind of question would you ask? What would be the question you would ask? Christof Koch In the spirit of our discussion, it could be, how could I become 10 times more intelligent? Lex And so, but see, you only get a clear, short answer. So do you think there's a clear, short answer to that? Christof Koch No. Lex And that's the answer you'll get. So you've mentioned Flowers of Elgar'nan. Christof Koch Oh, yeah. Lex There's a story that inspired you in your childhood, as this story of a mouse, a human achieving genius level intelligence, and then understanding what was happening while slowly becoming not intelligent again in this tragedy of gaining intelligence and losing intelligence. Do you think in that spirit, in that story, do you think intelligence is a gift or a curse from the perspective of happiness and meaning of life? You try to create an intelligent system that understands the universe, but on an individual level, the meaning of life, do you think intelligence is a gift? Christof Koch It's a good question. I don't know. Lex As one of the, as one people consider the smartest people in the world, in some dimension, at the very least, what do you think? Christof Koch I don't know. It may be invariant to intelligence, that degree of happiness. It would be nice if it were. Lex That's the hope. Christof Koch Yeah. Lex You could be smart and happy and clueless and happy. Christof Koch Yeah. Lex As always, on the discussion of the meaning of life, it's probably a good place to end. Tomasso, thank you so much for talking today. Tomasso Thank you. This was great.

https://youtu.be/aSyZvBrPAyk

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John Abramson: Big Pharma | Lex Fridman Podcast #263

The jury found Pfizer guilty of fraud and racketeering violations. How does Big Pharma affect your mind? Everyone's allowed their own opinion. I don't think everyone's allowed their own scientific facts. Does Pfizer play by the rules? Pfizer isn't battling the FDA. Pfizer has joined the FDA. The following is a conversation with John Abramson, faculty at Harvard Medical School, a family physician for over two decades, and author of the new book, Sickening, about how Big Pharma broke American healthcare and how we can fix it. This conversation with John Abramson is a critical exploration of the pharmaceutical industry. I wanted to talk to John in order to provide a countervailing perspective to the one expressed in my podcast episode with the CEO of Pfizer, Albert Bourla. And here, please allow me to say a few additional words about this episode with the Pfizer CEO, and in general, about why I do these conversations and how I approach them. If this is not interesting to you, please skip ahead. What do I hope to do with this podcast? I want to understand human nature, the best and the worst of it. I want to understand how power, money, and fame changes people. I want to understand why atrocities are committed by crowds that believe they're doing good. All this, ultimately, because I want to understand how we can build a better world together, to find hope for the future, and to rediscover each time through the exploration of ideas, just how beautiful this life is. This, our human civilization, in all of its full complexity, the forces of good and evil, of war and peace, of hate and love. I don't think I can do this with a heart and mind that is not open, fragile, and willing to empathize with all human beings, even those in the darkest corners of our world. To attack is easy. To understand is hard. And I choose the hard path. I have learned over the past few months that this path involves me getting more and more attacked from all sides. I will get attacked when I host people like Jay Bhattacharya or Francis Collins, Jamie Mertzl or Vincent Reconiello, when I stand for my friend Joe Rogan, when I host tech leaders like Mark Zuckerberg, Elon Musk, and others, when I eventually talk to Vladimir Putin, Barack Obama, and other figures that have turned the tides of history. I have and I will get called stupid, naive, weak, and I will take these words with respect, humility, and love, and I will get better. I will listen, think, learn, and improve. One thing I can promise is there's no amount of money or fame that can buy my opinion or make me go against my principles. There's no amount of pressure that can break my integrity. There's nothing in this world I need that I don't already have. Life itself is the fundamental gift. Everything else is just a bonus. That is freedom. That is happiness. If I die today, I will die a happy man. Now, a few comments about my approach and lessons learned from the Albert Bourla conversation. The goal was to reveal as much as I could about the human being before me, and to give him the opportunity to be a part of the conversation. I was able to do that, to give him the opportunity to contemplate in long form the complexities of his role, including the tension between making money and helping people, the corruption that so often permeates human institutions, the crafting of narratives through advertisements, and so on. I only had one hour, so this wasn't the time to address these issues deeply, but to show if Albert struggled them in the privacy of his own mind, and if he would let down the veil of political speak for time to let me connect with a man who decades ago chose to become a veterinarian, who wanted to help lessen the amount of suffering in the world. I had no pressure placed on me. There were no rules. The questions I was asking were all mine and not seen by Pfizer folks. I had no care whether I ever talked to another CEO again. None of this was part of the calculation in my limited brain computer. I didn't want to grill him the way politicians grill CEOs in Congress. I thought that this approach is easy, self-serving, dehumanizing, and it reveals nothing. I wanted to reveal the genuine intellectual struggle, vision, and motivation of a human being, and if that fails, I trusted the listener to draw their own conclusion and insights from the result, whether it's the words spoken, or the words left unspoken, or simply the silence. And that's just it. I fundamentally trust the intelligence of the listener. You. In fact, if I criticize the person too hard or celebrate the person too much, I feel I fail to give the listener a picture of the human being that is uncontaminated by my opinion or the opinion of the crowd. I trust that you have the fortitude and the courage to use your own mind, to empathize, and to think. Two practical lessons I took away. First, I will more strongly push for longer conversations of three, four, or more hours versus just one hour. 60 minutes is too short for the guest to relax and to think slowly and deeply, and for me to ask many follow-up questions or follow interesting tangents. Ultimately, I think it's in the interest of everyone, including the guests, that we talk in true long form for many hours. Second, these conversations with leaders can be aided by further conversations with people who wrote books about those leaders or their industries, those that can steel man each perspective and attempt to give an objective analysis. I think of Teddy Roosevelt's speech about the man in the arena. I want to talk to both the men and women in the arena and the critics and the supporters in the stands. For the former, I lean toward wanting to understand one human being's struggle with the ideas. For the latter, I lean towards understanding the ideas themselves. That's why I wanted to have this conversation with John Abramson, who is an outspoken critic of the pharmaceutical industry. I hope it helps add context and depth to the conversation I had with the Pfizer CEO. In the end, I may do worse than I could have or should have. Always, I will listen to the criticisms without ego, and I promise I will work hard to improve. But let me say finally that cynicism is easy. Optimism, true optimism, is hard. It is the belief that we can and we will build a better world and that we can only do it together. This is the fight worth fighting. So here we go. Once more into the breach, dear friends. I love you all. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with John Abramson. Your faculty at Harvard Medical School, your family physician for over two decades, rated one of the best family physicians in Massachusetts. You wrote the book Overdose America and the new book coming out now called Sickening about how Big Pharma broke American healthcare, including science and research, and how we can fix it. First question, what is the biggest problem with Big Pharma that if fixed would be the most impactful? So if you can snap your fingers and fix one thing, what would be the most impactful, you think? The biggest problem is the way they determine the content, the accuracy, and the completeness of what doctors believe to be the full range of knowledge that they need to best take care of their patients. So that with the knowledge having been taken over by the commercial interests, primarily the pharmaceutical industry, the purpose of that knowledge is to maximize the profits that get returned to investors and shareholders and not to optimize the health of the American people. So rebalancing that equation would be the most important thing to do to get our healthcare back aimed in the right direction. Okay, so there's a tension between helping people and making money. So if we look at particularly the task of helping people in medicine, in healthcare, is it possible if money is the primary sort of mechanism by which you achieve that as a motivator, is it possible to get that right? I think it is, Lex, but I think it is not possible without guardrails that maintain the integrity and the balance of the knowledge. Without those guardrails, it's like trying to play a professional basketball game without referees and having players call their own fouls. But the players are paid to win, and you can't count on them to call their own fouls. So we have referees who are in charge. We don't have those referees in American healthcare. That's the biggest way that American healthcare is distinguished from healthcare in other wealthy nations. Okay, so you mentioned Milton Friedman, and you mentioned his book called Capitalism and Freedom. He writes that there are only three legitimate functions of government to preserve law and order, to enforce private contracts, and to ensure that private markets work. You said that that was a radical idea at the time, but we're failing on all three. How are we failing? And also maybe the bigger picture is, what are the strengths and weaknesses of capitalism when it comes to medicine and healthcare? Can we separate those out? Because those are two huge questions. So how we're failing on all three, and these are the minimal functions that our guru of free market capitalism says capitalism said the government should perform. So this is the absolute baseline. On preserving law and order, the drug companies routinely violate the law in terms of their marketing and in terms of their presentation of the results of their trials. I know this because I was an expert in litigation for about 10 years. I presented some of what I learned in civil litigation to the FBI and the Department of Justice, and that case led to the biggest criminal fine in US history as of 2009. And I testified in a federal trial in 2010, and the jury found Pfizer guilty of fraud and racketeering violations. In terms of violating the law, it's a routine occurrence. The drug companies have paid $38 billion worth of fines from, I think, 1991 to 2017. It's never been enough to stop the misrepresentation of their data, and rarely are the fines greater than the profits that were made. See, executives have not gone to jail for misrepresenting data that have involved even tens of thousands of deaths in the case of Vioxx, OxyContin as well. And when companies plead guilty to felonies, which is not an unusual occurrence, the government usually allows the companies, the parent companies, to allow subsidiaries to take the plea so that they are not one step closer to getting disbarred from Medicare, not being able to participate in Medicare. So in that sense, there is a mechanism that is appearing to impose law and order on drug company behavior, but it's clearly not enough. It's not working. Can you actually speak to human nature here? Are people corrupt? Are people malevolent? Are people ignorant that work at the low level and at the high level at Pfizer, for example, at big pharma companies? How is this possible? So I believe, just on a small tangent, that most people are good. And I actually believe if you join big pharma, so a company like Pfizer, your life trajectory often involves dreaming and wanting and enjoying helping people. Yes. And so, and then we look at the outcomes that you're describing, and it looks, and that's why the narrative takes hold, that like Pfizer CEO Albert Bourla, who I talked to, is malevolent. Malevolent. The sense is like these companies are evil. So if the different parts, the people are good and they want to do good, how are we getting these outcomes? Yeah. I think it has to do with the cultural milieu that this is unfolding in. And we need to look at sociology to understand this, that when the cultural milieu is set up to maximize the returns on investment for shareholders and other venture capitalists and hedge funds and so forth, when that defines the culture and the higher up you are in the corporation, the more you're in on the game of getting rewarded for maximizing the profits of the investors. That's the culture they live in. And it becomes normative behavior to do things with science that look normal in that environment and are shared values within that environment by good people whose self-evaluation becomes modified by the goals that are shared by the people around them. And within that milieu, you have one set of standards, and then the rest of good American people have the expectation that the drug companies are trying to make money, but that they're playing by rules that aren't part of the insider milieu. That's fascinating. The game they're playing modifies the culture of inside the meetings, inside the rooms, day to day, that there's a bubble that forms. We're all in bubbles of different sizes. And that bubble allows you to drift in terms of what you see as ethical and unethical, because you see the game as just part of the game. So marketing is just part of the game. Paying the fines is just part of the game of science. Yep. And without guardrails, it becomes even more part of the game. You keep moving in that direction if you're not bumping up against guardrails. And I think that's how we've gotten to the extreme situation we're in now. So, like I mentioned, I spoke with Pfizer CEO Albert Bourla, and I'd like to raise with you some of the concerns I raised with him. So one, you already mentioned, I raised the concern that Pfizer's engaged in aggressive advertising campaigns. As you can imagine, he said no. What do you think? I think you're both right. I agree with you that the aggressive advertising campaigns do not add value to society. And I agree with him that they're, for the most part, legal, and it's the way the game is played. Right. So sorry to interrupt, but oftentimes his responses are, especially now, he's been CEO for only like two years, three years, he says Pfizer was a different company, we've made mistakes, right, in the past. We don't make mistakes anymore. That there's rules, and we play by the rules. So like, with every concern raised, there's very, very strict rules, as he says. In fact, he says sometimes way too strict, and we play by the rules. And so in that sense, advertisement, it doesn't seem like it's too aggressive, because it's playing by the rules. And relative to the other, again, it's the game, relative to the other companies, it's actually not that aggressive. Relative to the other big pharma companies. Yes, yes. I hope we can quickly get back to whether or not they're playing by the rules, but in general. But let's just look at the core of the problem. Whether or not they're playing by the rules, but in general. But let's just look at the question of advertising specifically. I think that's a good example of what it looks like from within that culture, and from outside that culture. He's saying that we follow the law on our advertising. We state the side effects, and we state the FDA approved indications, and we do what the law says we have to do for advertising. And I have not, I've not been an expert in litigation for a few years, and I don't know what's going on currently, but let's take him at his word. It could be true. It might not be, but it could be. But if that's true in his world, in his culture, that's ethical business behavior. From a common sense person's point of view, a drug company paying highly skilled media folks to take the information about the drug and create the illusion, the emotional impact, and the takeaway message for viewers of advertisements that grossly exaggerate the benefit of the drug and minimize the harms, it's sociopathic behavior. Sociopathic behavior to have viewers of ads leave the ad with an unrealistic impression of the benefits and harms of the drug. And yet he's playing by the rules. He's doing his job as CEO to maximize the effect of his advertising. And if he doesn't do it, this is a key point, if he doesn't do it, he'll get fired and the next guy will. So the people that survive in the company, the people that get raises in the company and move up in the company are the ones that play by the rules, and that's how the game solidifies itself. But the game is within the bounds of the law. Sometimes, most of the time, not always. We'll return to that question. I'm actually more concerned about the effect of advertisement in a kind of much larger scale on the people that are getting funded by the advertisement in self-censorship. Just like more subtle, more passive pressure to not say anything negative. Because I've seen this, and I've been saddened by it, that people sacrifice integrity in small ways in small ways when they're being funded by a particular company. They don't see themselves as doing so, but you could just clearly see that the space of opinions that they're willing to engage in, or a space of ideas they're willing to play with, is one that doesn't include negative, anything that could possibly be negative about the company. They just choose not to, because, you know, why? And that's really sad to me, that, you know, if you give me a hundred bucks, I'm less likely to say something negative about you. That makes me sad. Because the reason I wouldn't say something negative about you, I prefer, is the pressure of friendship and human connection, those kinds of things. So I understand that. That's also a problem, by the way. So they start having dinners and shaking hands, and, oh, aren't we friends? But the fact that money has that effect is really sad to me. On the news media, on the journalists, on scientists, that's scary to me. But of course, the direct advertisement to consumers, like you said, is potentially a very negative effect. I wanted to ask if, what do you think is the most negative impact of advertisement? Is it that direct to consumer on television? Is it advertisement to doctors? Which I'm surprised to learn, I was vaguely looking at, is more than the advertisement, more spent on advertising to doctors than to consumers. That's really confusing to me. It's fascinating, actually. And then also, obviously, the law side of things is the lobbying dollars, which I think is less than all of those. But anyway, it's in the ballpark. What concerns you most? Well, it's the whole nexus of influence. There's not one thing, and they don't invest all their, they don't put all their eggs in one basket. It's a whole surround sound program here. But in terms of advertisements, let's take the advertisement. Trulicity is a diabetes drug, a type two diabetes, an injectable drug. And it lowers blood sugar just about as well as metformin does. Metformin costs about $4 a month. Trulicity costs, I think, $6,200 a year. So $48 a year versus 6,200. Trulicity has distinguished itself because it did, the manufacturer did a study that showed that it significantly reduces the risk of cardiovascular disease in diabetics. And they got approval on the basis of that study, that very large study being statistically significant. And what the, so the ad, the ads obviously extol the virtues of trulicity because it reduces the risk of heart disease and stroke. And that's one of the major morbidities risks of type two diabetes. What the ad doesn't say is that you have to treat 323 people to prevent one non-fatal event at a cost of $2.7 million. And even more importantly than that, what the ad doesn't say is that the evidence shows that engaging in an active, healthy lifestyle program reduces the risk of heart disease and strokes far more than trulicity does. Now there's, to be fair to the company, the sponsor, there's never been a study that compared trulicity to lifestyle changes. But that's part of the problem of our advertising. You would think in a rational society that was way out on a limb as a lone country besides New Zealand that allows direct-to-consumer advertising, that part of allowing direct-to-consumer advertising would be to mandate that the companies establish whether their drug is better than, say, healthy lifestyle adoption to prevent the problems that they claim to be preventing. But we don't require that. So the companies can afford to do very large studies so that very small differences become statistically significant. And their studies are asking the question, how can we sell more drug? They're not asking the question, how can we prevent cardiovascular disease in people with type 2 diabetes? And that's how we get off in this. We're now in the extreme arm of this distortion of our medical knowledge, of studying how to sell more drugs than how to make people more healthy. That's a really great thing to compare to is lifestyle changes. Because that should be the bar. If you do some basic diet, exercise, all those kinds of things, how does this drug compare to that? Right. Right. And that study was done, actually, in the 90s. It's called the Diabetes Prevention Program. It was federally funded by the NIH so that there wasn't this drug company imperative to just try to prove your drug was better than nothing. And it was a very well-designed study, randomized, controlled trial in people who were at high risk of diabetes, so-called pre-diabetics. And they were randomized to three different groups, a placebo group, a group that got treated with metformin, and a group that got treated with intensive lifestyle counseling. So this study really tested whether you can get people in a randomized controlled trial assigned to intensive lifestyle changes, whether that works. Now, the common wisdom amongst physicians, and I think in general, is that you can't get people to change. You can do whatever you want. You can stand on your head. You can beg and plead. People won't change. So give it up and let's just move on with the drugs and not waste any time. Except this study that was published in the New England Journal, I think, in 2002 shows that's wrong, that the people who were in the intensive lifestyle group ended up losing 10 pounds, exercising five times a week, maintaining it, and reduced their risk of getting diabetes by 58% compared to the metformin group, which reduced its risk of getting diabetes by 31%. So that exact study was done, and it showed that lifestyle intervention is the winner. Who, as a small tangent, is the leader? Who is supposed to fight for the side of lifestyle changes? Where's the big pharma version of lifestyle changes? Who's supposed to have the big bully pulpit, the big money behind lifestyle changes? In your sense, because that seems to be missing in a lot of our discussions about health policy. Right, that's exactly right. And the answer is that we assume that the market has to solve all of these problems. And the market can't solve all of these problems. There needs to be some way of protecting the public interest for things that aren't financially driven, so that the overriding question has to be how best to improve Americans' health, not companies funding studies to try and prove that their new inexpensive drug is better and should be used. Well, some of that is also people sort of like yourself. I mean, it's funny, you spoke with Joe Rogan. He constantly espouses lifestyle changes. So some of it is almost like, understanding the problems that big pharma is creating society, and then sort of these influential voices speaking up against it. So whether they're scientists or just regular communicators. Yeah, I think you got to tip your hat to Joe for getting that message out. And he clearly believes it and does his best. But it's not coming out in the light of the day. It's not coming out in the light of compelling concrete test. But it's not coming out in the legitimate avenues, in the legitimate channels that are evidence-based medicine from the sources that the docs are trained to listen to and modify their patient care on. Now, it's not a 100%. I mean, there are articles in the big journals about the benefits of lifestyle. as the randomized controlled trials that test this drug against placebo or this drug against another drug. So the Joe Rogans of the world keep going. You know, I tip my hat. But it's not gonna carry the day for most of the people until it has the legitimacy of the medical establishment. Yeah, like something that the doctors really pay attention to. Well, there's an entire mechanism established for testing drugs. There's not an entire mechanism established for in terms of scientific rigor of testing lifestyle changes. I mean, it's more difficult. I mean, everything's difficult in science. Science that involves humans, especially. But it's just, these studies are very expensive. They're difficult. It's difficult to find conclusions to control all the variables. And so it's very easy to dismiss them unless you really do a huge study that's very well funded. And so maybe the doctors just lean towards the simpler studies over and over, which is what the drug companies fund. They can control more variables. See, but the control there is sometimes by hiding things too, right? So sometimes you can just say that this is a well-controlled study by pretending there's a bunch of other stuff, just ignoring the stuff that could be correlated, it could be the real cause of the effects you're seeing, all that kind of stuff. So money can buy ignorance, I suppose, in science. It buys the kind of blinders that are on, that don't look outside the reductionist model. And that's another issue is that we kind of, nobody says to doctors in training, only listen to reductionist studies and conclusions and methods of promoting health. Nobody says that explicitly, but the respectable science has to do with controlling the factors. And I mean, it just doesn't make sense to me. I'm gonna pick on Trulicity because it's such an obvious example, but it's not more egregious than many others. It doesn't make sense to me to allow a drug to be advertised as preventing cardiovascular disease when you haven't included lifestyle changes as an arm in the study. It's just so crystal clear that the purpose of that study is to sell Trulicity. It's not to prevent cardiovascular disease. If we were in charge, I would try to convince you that anywhere that study, the results of that study were presented to physicians, it would be stamped in big red letters, this study did not compare Trulicity to lifestyle changes. They need to know that. And the docs are kind of trained, these blinders get put on, and they're trained to kind of forget that that's not there. Do you think, so first of all, that's a small or big change to advertisement that seems obvious to say, like in force that it should be compared to lifestyle changes. Do you think advertisements, period, in the United States for pharmaceutical drugs should be banned? I think they can't be banned, so it doesn't matter what I think. Okay, let's say you were a dictator, and two, why can't they be banned? Okay. Answer either one. I believe, I've been told by lawyers who I trust, that the freedom of speech in the US Constitution is such that you can't ban them, that you could ban cigarettes and alcohol, which have no therapeutic use, but drugs have a therapeutic use, and advertisements about them can't be banned. Let's assume that they can't be, because we know they won't be anyway. But let's assume they can't be, and especially our Supreme Court now would be unlikely to take that seriously. But that's not the issue. The issue is that if the drug companies wanna spend their money advertising, they should have to have independent analysis of the message that the viewers are left with about the drug, so that it's realistic. What's the chance the drug will help them? Well, in trulicity, it's one out of 323. 322 people aren't gonna benefit from the cardiovascular risk reduction. What's the true cost? When drugs advertise that you may be able to get this for a $25 copay or something, tens of thousands of dollars a year drug for a $25 copay, what an enormous disservice that is to misrepresent the cost to society. That should not be allowed. So you should have to make it clear to the viewers how many people are gonna benefit, what's your chance of benefiting, how does it compare to lifestyle changes or less expensive therapies, what do you give up if you use a less expensive therapy or gain, perhaps? And how much it costs. How much it costs. Now, that can go either way, because if you say Humira costs $72,000 and it's no more effective as a first-line drug than methotrexate, which costs $480, people might say, I want the expensive drug, because I can get it for a $25 copay. So you'd have to temper that a little bit. Oh, you mean people are so, they don't care. They don't care, their insurance is gonna cover it and it's a $25 copay, but we could figure out how to deal with that. The main point is that if we assume that advertisements are gonna keep going, and they are, we could require that there be outside evaluation of the message that reasonable, unbiased viewers take away from the ads, and the ads would have to tell the truth about the drug. And the truth should have like sub-truth guardrails, meaning like the cost that we talked about, the effects compared to things that actually, you know, lifestyle changes, to just these details, very strict guardrails of what actually has to be specified. And I would make it against the law to have family picnics or dogs catching Frisbees in the ads. So, you mean 95% of the ads, yes. I mean, there's something dark and inauthentic about those advertisements, but they seem, I mean, I'm sure they're being done because they work for the target audience. And then the doctors too. Can you really buy a doctor's opinion? Why does it have such an effect on doctors, advertisement to doctors? Like you as a physician, again, like from everything I've seen, people love you. People should definitely look you up from, there's a bunch of videos of you giving talks on YouTube, and it's just so refreshing to hear just the clarity of thought about health policy, about healthcare, just the way you think throughout the years. Thank you. So, it's easy to think about, maybe you're criticizing Big Pharma, that's one part of the message that you're talking about, but that's not, your brilliance actually shines in the positive, in the solutions and how to do it. So, as a doctor, what affects your mind? And how does Big Pharma affect your mind? Number one, the information that comes through legitimate sources that doctors have been taught to rely on, evidence-based medicine, the articles in peer-reviewed journals, the guidelines that are issued. Now, those are problematic, because when an article is peer-reviewed and published in a respected journal, people and doctors obviously assume that the peer reviewers have had access to the data, and they've independently analyzed the data, and they corroborate the findings in the manuscript that was submitted, or they give feedback to the authors and say, we disagree with you on this point, and would you please check our analysis, and if you agree with us, make it. That's what they assume the peer-review process is, but it's not. The peer reviewers don't have the data. The peer reviewers have the manuscript that's been submitted by the, usually in conjunction with, or by the drug company that manufactures the drug. So peer reviewers are unable to perform the job that doctors think they're performing to vet the data to assure that it's accurate and reasonably complete. They can't do it. And then we have the clinical practice guidelines, which are increasingly more important as the information, the flow of information keeps getting brisker and brisker, and docs need to get to the bottom line quickly. Clinical practice guidelines become much more important, and we assume that the authors of those clinical practice guidelines have independently analyzed the data from the clinical trials and make their recommendations that set the standards of care based on their analysis. That's not what happens. The experts who write the clinical trials rely almost entirely on the publications presenting the results of the clinical trials, which are peer reviewed, but the peer reviewers haven't had access to the data. So we've got a system of the highest level of evidence that doctors have been trained over and over again to rely on to practice evidence-based medicine to be good doctors that has not been verified. Do you think that data that's coming from the pharma companies, do you think they're, what level of manipulation is going on with that data? Is it at the study design level? Is it at literally there's some data that you just keep off, you know, keep out of the charts, keep out of the aggregate analysis, then you then publish? Or is it the worst case, which is just change some of the numbers? It happened. All three happened. I can't, I don't know what the denominator is, but I spent about 10 years in litigation. And for example, in Vioxx, which was withdrawn from the market in 2004 in the biggest drug recall in American history, the problem was that it got recalled when a study that Merck sponsored showed that Vioxx doubled the risk, more than doubled the risk of heart attacks, strokes, and blood clots, serious blood clots. It got pulled then. But there was a study, a bigger study that had been published in 2000 in the New England Journal of Medicine that showed that Vioxx was a better drug for arthritis and pain, not because it was more effective. It's no more effective than Aleve or Advil, but because it was less likely to cause serious GI complications, bleeds and perforations in the gut. Now, in that study that was published in the New England Journal that was never corrected, it was a little bit modified 15 months after the drug was taken off the market, but never corrected, Merck left out three heart attacks. And the FDA knew that Merck left out three heart attacks. And the FDA's analysis of the data from that study said that the FDA wasn't gonna do the analysis without the three heart attacks in it. And the important part of this story is that there were 12 authors listed on that study in the New England Journal. Two were Merck employees. They knew about the three heart attacks that had been omitted. The other 10 authors, the academic authors, didn't know about it. They hadn't seen that data. So Merck just, they had an excuse, it's complicated, and the FDA didn't accept it, so there's no reason to go into it. But Merck just left out the three heart attacks. And the three heart attacks, it may seem three heart attacks in a 10,000-person study may seem like nothing, except they completely changed the statistics so that had the three heart attacks been included, the only conclusion that Merck could have made was that Vox significantly increased the risk of heart attack. And they abbreviated their endpoint from heart attacks, strokes, and blood clots to just heart attacks. Yeah. So those are maybe, in their mind, they're also playing by the rules because of some technical excuse that you mentioned that was rejected. How can this, because this is crossing the- No, no, let me interrupt. No, that's not true. The study was completed, the blind was broken, meaning they looked at the data. In March of 2000, the article was published in the New England Journal in November of 2000. In March of 2000, there was an email by the head scientist that was published in the Wall Street Journal that said the day that the data were unblinded that it's a shame that the cardiovascular events are there, but the drug will do well and we will do well. But removing the three heart attacks, how does that happen? Like, who has to convince themselves, is this pure malevolence? You have to be the judge of that, but the person who was in charge of the Data Safety Monitoring Board issued a letter that said they'll stop counting cardiovascular events a month before the trial is over, and they'll continue counting GI events. And that person got a contract to consult with Merck for $5,000 a day, I think for 12 days a year, for one or two years, that was signed, that contract was signed within two weeks of the decision to stop counting heart attacks. I wanna understand that man or woman. I wanna, I want, it's the, been reading a lot about Nazi Germany and thinking a lot about the good Germans. Because I want to understand so that we can each encourage each other to take the small heroic actions that prevents that. Because it feels to me, removing malevolence from the table, where it's just a pure psychopathic person, that there's just a momentum created by the game, like you mentioned. And so it takes reversing the momentum within a company, I think requires many small acts of heroism. Not gigantic, I'm going to leave and become a whistleblower and publish a book about it. But small, quiet acts of pressuring against this. Like, what are we doing here? We're trying to help people. Is this the right thing to do? Looking in the mirror constantly and asking, is this the right thing to do? I mean, that's how, that's what integrity is. Acknowledging the pressures you're under and then still be able to zoom out and think, what is the right thing to do here? But the data, hiding the data, makes it too easy to live in ignorance. So like within those, inside those companies. So your idea is that the reviewers should see the data. That's one step. So to even push back on that idea is, I assume you mean that data remains private except to the peer reviewers. The problem, of course, as you probably know, is the peer review process is not perfect. You know, it's individuals. It feels like there should be a lot more eyes on the data than just the peer reviewers. Yes, this is not a hard problem to solve. When a study is completed, a clinical study report is made, and it's usually several thousand pages. And what it does is it takes the raw patient data and it tabulates it in the ways, it's supposedly and usually, in the ways that the company has pre-specified. So that you then end up with a searchable, let's say 3,000 page document. And as I became more experienced as an expert in litigation, I could go through those documents pretty quickly. Quickly may mean 20 hours or 40 hours, but it doesn't mean three months of my work. And see if the companies, if the way the company has analyzed the data is consistent with their statistical analysis plan and their pre-specified outcome measures. It's not hard. And I think you're right. Peer reviewers, I don't peer review clinical trials, but I peer review other kinds of articles. I have to do one on the airplane on the way home. And it's hard. I mean, we're just ordinary mortal people volunteering to- Unpaid, the motivation is not clear. The motivation is to keep, to be a good citizen in the medical community and to be on friendly terms with the journals so that if you want to get published, there's sort of an unspoken incentive. As somebody who enjoys game theory, I feel like that motivation is good, but could be a lot better. Yes, you should get more recognition or in some way academic credit for it. It should go to your career advancement. If it's an important paper and you recognize it's an important paper as a great peer reviewer, that this is not in that area where it's clearly a piece of crap paper or clearly an awesome paper that doesn't have controversial aspects to it and it's just a beautiful piece of work. Okay, those are easy. And then there's the very difficult gray area, which may require many, many days of work on your part as a peer reviewer. So it's not just a couple hours, but really seriously reading. Like some papers can take months to really understand. So if you really want to struggle, there has to be an incentive for that struggle. Yes, and billions of dollars ride on some of these studies. And lies. Yeah. Right? Not to mention. Right, but it would be easy to have full-time statisticians hired by the journals or shared by the journals who were independent of any other financial incentive to go over these kind of methodological issues and take responsibility for certifying the analyses that are done and then pass it on to the volunteer peer reviewers. See, I believe even in this, in sort of capitalism or even social capital, after watching Twitter in the time of COVID and just looking at people that investigate themselves, I believe in the citizenry. People, if you give them access to the data, like these citizen scientists arise. A lot of them on the, it's kind of funny. A lot of people are just really used to working with data. They don't know anything about medicine and they don't have actually the biases that a lot of doctors and medical and a lot of the people that read these papers, they'll just go raw into the data and look at it with, like they're bored almost and they do incredible analysis. So I, you know, there's some argument to be made for a lot of this data to become public. Like de-anonymized, no, sorry, anonymized, all that kind of stuff, but for a lot of it to be public, especially when you're talking about things as impactful as some of these drugs. I agree 100%, so let's turn the micro, let's get a little bit more granular. On the peer review issue, we're talking about pre-publication transparencies and that is critically important. Once a paper is published, the horses are out of the barn and docs are gonna read it, take it as evidence-based medicine. The economists call what then happens as stickiness, that the docs hold on to their beliefs. And my own voice inside says, once doctors start doing things to their patients' bodies, they're really not too enthusiastic about hearing it was wrong. Yeah, that's the stickiness of human nature. Wow, so that bar, once it's published, the doctors, that's when the stickiness emerges, wow. Yeah, it's hard to put that toothpaste back in the tube. Now, that's pre-publication transparency, which is essential. And you could have, whoever saw that data pre-publication could sign confidentiality agreements so that the drug companies couldn't argue that we're just opening the spigots of our data and people can copy it and blah, all the excuses they make. You could argue that you didn't have to, but let's just let them do it. Let the peer reviewers sign confidentiality agreements and they won't leak the data. But then you have to go to post-publication transparency, which is what you were just getting at, to let the data free and let citizens and citizen scientists and other doctors who are interested have at it. Kind of like Wikipedia, have at it. Let it out and let people criticize each other. Okay, so speaking of the data, the FDA asked 55 years to release Pfizer vaccine data. This is also something I raised with Albert Bourla. The Pfizer. There's several things I didn't like about what he said. So some things are expected and some of it is just revealing the human being, which is what I'm interested in doing. But he said he wasn't aware of the 75 and the 55. I'm sorry, wait a minute. He wasn't aware of? The how long, so here, I'll explain what he. Do you know that since you spoke to him, Pfizer has petitioned the judge to join the suit in behalf of the FDA's request to release that data over 55 or 75 years? Pfizer's fully aware of what's going on. He's aware. I'm sure he's aware in some formulation. The exact years, he might have not been aware. But the point is that there is, that is the FDA, the relationship with Pfizer and the FDA in terms of me being able to read human beings was the thing he was most uncomfortable with, that he didn't wanna talk about the FDA. And that, it was clear that there was a relationship there that if the words you use may do a lot of harm, potentially because like you're saying, there might be lawsuits going on, there's litigation, there's legal stuff, all that kind of stuff. And then there's a lot of games being played in this space. So I don't know how to interpret it, if he's actually aware or not, but the deeper truth is that he's deeply uncomfortable bringing light to this part of the game. Yes, and I'm gonna read between the lines, and Albert Bourla certainly didn't ask me to speak for him. But I think, when did you speak to him? How long ago? Wow, time flies when you're having fun. Two months ago. Two months ago. So that was just recently, it's come out, just in the past week, it's come out, that Pfizer isn't battling the FDA. Pfizer has joined the FDA in the opposition to the request to release these documents in the same amount of time that the FDA took to evaluate them. Yeah. So Pfizer is offering to help the FDA to petition the judge to not enforce the timeline that he seems to be moving towards. So for people who are not familiar, we're talking about the Freedom of Information Act request to release the Pfizer vaccine study data, to release as much of the data as possible, like the raw data, the details, or actually not even the raw data, it's data. Doesn't matter, there's details to it. And I think the response from the FDA is that, yes, of course, but we can only publish like some X number of pages a day. 500 pages. 500 pages of data. It's not a day though, it's a week, I think. Whatever. The point is, whatever they're able to publish is ridiculous. It's like, my printer can only print three pages a day and we cannot afford a second printer. So it's some kind of bureaucratic language for, you know, there's a process to this, and now you're saying that Pfizer is obviously more engaged in helping this kind of bureaucratic process prosper in its full absurdity, Kafka-esque absurdity. So what is this? This really bothered people. This really- This is really troublesome. And just to put it in just plain English terms, Pfizer's making the case that it can't- The FDA and Pfizer together are making the case that they can't go through the documents. It's gonna take them some number of hundredfold, hundreds of folds more time to go through the documents than the FDA required to go through the documents to approve the vaccines, to give the vaccines full FDA approval. And the FDA's argument, talk about Kafka-esque, is that to do it more rapidly would cost them $3 million. $3 million equals one hour of vaccine sales over two years. One hour of sales. And they can't come up with the money. And now Pfizer has joined the suit to help the FDA fight off this judge, this mean judge who thinks they ought to release the data. But evidently Pfizer isn't offering to come up with the $3 million either. So, but for $3 million, I mean, maybe, maybe the FDA should do a GoFundMe campaign. Well, obviously the money thing, I mean, I'm sure if Elon Musk comes along and says, I'll give you a hundred million, publish it now, I think they'll come up with another. So, I mean, it's clear that there is cautiousness. I don't know the source of it from the FDA. There's only one explanation that I can think of, which is that the FDA and Pfizer don't wanna release the data. They don't wanna release the three or 500,000 pages of documents. And I don't know what's in there. I wanna say one thing very clearly. I am not an anti-vaxxer. I believe the vaccines work. I believe everybody should get vaccinated. The evidence is clear that if you're vaccinated, you reduce your risk of dying of COVID by 20 fold. And we've got new sub-variants coming along. And I just wanna be very clear about this. That said, there's something I would give you 10 to one odds on a bet that there's something in that data that is gonna be embarrassing to either FDA or Pfizer or both. So, there's two options. I agree with you a hundred percent. One is they know of embarrassing things. That's option one. And option two, they haven't invested enough to truly understand the data. Like, I mean, it's a lot of data. That they have a sense there might be something embarrassing in there. And if we release it, surely the world will discover the embarrassing. And to do a sort of, to steel man their argument, they'll take the small, the press, the people will take the small embarrassing things and blow them up into big things. Yes, and support the anti-vax campaign. I think that's all possible. Nonetheless, the data are about the original clinical trial. And the emergency use authorization was based on the first few months of the data from that trial. And it was a two year trial. The rest of that data has not been opened up. And there was not an advisory committee meeting to look at that data when the FDA granted full authorization. Again, I am pro-vaccine. I am not making an anti-vax argument here. But I suspect that there's something pretty serious in that data. And the reason why I'm not an anti-vaxxer, having not been able to see the data that the FDA and Pfizer seem to willing, not just to put effort into preventing the release of, but seem to have quite a bit of energy into preventing, invest quite a bit of energy in not releasing that data. The reason why that doesn't tip me over into the anti-vaxxer side is because that's clinical trial data, early clinical trial data that involved several thousand people. We now have millions of data points from people who have had the vaccine. This is real world data showing the efficacy of the vaccines. And so far, knock on wood, there aren't side effects that overcome the benefits of vaccine. So I'm with you. I'm now, I guess, three shots of the vaccine. But there's a lot of people that are kind of saying, well, even the data on the real world use, large scale data, is messy. The way it's being reported, the way it's being interpreted. Well, one thing is clear to me that it is being politicized. I mean, if you just look objectively, don't have to go to, at the shallow surface level, it seems like there's two groups that, I can't even put a term to it because it's not really pro-vaccine versus anti-vaccine because it's pro-vaccine, triple mask, Democrat, liberal, and then anti-mandate, whatever those groups are. I can't quite, because they're changing. Anti-mask, but not really, but kind of. So those two groups that feel political in nature, not scientific in nature, they're bickering. And then it's clear that this data is being interpreted by the different groups differently. And it's very difficult for me as a human being to understand where the truth lies, especially given how much money is flying around on all sides. So the anti-vaxxers can make a lot of money too. Let's not forget this. From the individual perspective, you can become famous being an anti-vaxxer. And so there's a lot of incentives on all sides here. And there's real human emotion and fear and also credibility. Scientists don't wanna ruin their reputation if they speak out in whatever, like speak their opinion or they look at some slice of the data and begin to interpret it in some kind of way. They're very, it's clear that fear is dominating the discourse here, especially in the scientific community. So I don't know what to make of that. And the only happy people here is Pfizer. It's just plowing all ahead. I mean, with every single variant, I would say, outside of arguably a very flawed system, there's a lot of incredible scientific and engineering work being done in constantly developing new antiviral drugs, new vaccines to deal with the variants. So they're happily being a capitalist machine. And it's very difficult to know what to do with that. And let's just put this in perspective for folks. The best-selling drug in the world has been Humira for a number of years. It's approved for the treatment of rheumatoid arthritis and eight other indications. And it's sold about $20 billion globally over the past few years. It leveled out, it peaked at that level. Pfizer expects to sell $65 billion of vaccine in the first two years of the pandemic. So this is by far the biggest selling and most profitable drug that's ever been come along. So can I ask you a difficult question here? In the fog that we're operating in here, on the Pfizer-BioNTech vaccine, what was done well and what was done badly that you can see now? It seems like we'll know more decades from now. Yes, but now in the fog of today with the $65 billion flying around, where do you land? So we're gonna get to what I think is one of the key problems with the pharmaceutical industry model in the United States about being profit-driven. So in 2016, the NIH did the key infrastructure work to make mRNA vaccines. That gets left out of the discussion a lot. And Pfizer-BioNTech actually paid royalties voluntarily to the NIH. I don't know how much it was. I don't think it was a whole lot of money, but I think they wanted to avoid the litigation that Moderna got itself into by just taking that 2016 knowledge and having that be the foundation of their product. So Pfizer took that and they did their R&D. They paid for their R&D having received that technology. And when they got the genetic code from China about the virus, they very quickly made a vaccine and the vaccine works. And President Trump, to his credit, launched Operation Warp Speed and just threw money at the problem. They just said, we spent five times more per person than the EU early on. Just pay them whatever they want. Let's just get this going. And Americans were vaccinated more quickly. We paid a lot of money. The one mistake that I think the federal government made was they were paying these guaranteed fortunes and they didn't require that the companies participate in a program to do global vaccinations. So the companies doing their business model distributed the vaccines where they would make the most money. And obviously they would make the most money in the first world. And almost, I think, 85% of the vaccines early on went to the first world. And very, very few vaccinations went to the third world. So what happened is there was such a low vaccination rate. In May of 2021, there was all hands on deck cry for help from the World Trade Organization, the World Health Organization, the IMF and the World Bank made a plea for $50 billion so that we could get to 40% vaccination rate in the third world by the end of 2021. And it was unrequited. Nobody answered. And now Africa has about a 8.9% vaccination rate. India is coming up, but it's been very low. The problem with all this is I believe those mRNA vaccines are excellent vaccines. But if we leave the third world unvaccinated, we're gonna have a constant supply of variants of COVID that are gonna come back into the United States and harm Americans exactly like Delta and Omicron have. So we've made a great drug. It reduces the risk of mortality in Americans who get it by a lot, but we're not doing what we need to do to protect Americans from Omicron. You don't have to be an idealist and worry about global vaccine equity. If you're just ordinary selfish people like most of us are, and you're worried about the health of Americans, you would ensure global vaccine distribution. Let me just make one more point. That $50 billion that was requested by the four organizations back in May of 2021, 32 billionaires made $50 billion from the vaccines at that point, took it into their private wealth. So what had been taken, this enormous amounts of money that had been taken into private wealth was enough to do what those organizations said needed to be done to prevent the sub-variants from coming back and doing what they're doing. The money was there, but how does the motivation, the money-driven motivation of Big Pharma lead to that kind of allocation of vaccines? Allocation of vaccines? Because they can make more money in the United States. They're gonna distribute their vaccines where they can make the most money. Right. Is there a malevolent aspect to this where, boy, I don't like saying this, but that they don't see it as a huge problem that variants will come back to the United States? I think it's the issue we were talking about earlier on where they're in a different culture and their culture is that their moral obligation, as Milton Friedman would say, is to maximize the profits that they return to shareholders. And don't think about the bigger picture. The collateral damage. Don't think about the collateral damage. And also kind of believe, convince yourself that if we give into this capitalist machine in this very narrow sense of capitalism, that in the end, they'll do the most good. This kind of belief that if we just maximize profits, we'll do the most good. Yeah, that's an orthodoxy of several decades ago. And I don't think people can really say that in good faith. When you're talking about vaccinating the third world so we don't get hurt, it's a little bit hard to make the argument that the world's a better place because the profits of the investors went up. Yeah, but at the same time, I think that's a belief you can hold. I mean, I've interacted with a bunch of folks that kind of, it's the, I don't want to mischaracterize Ayn Rand, okay? I respect a lot of people, but there's a belief that can take hold. If I just focus on this particular maximization, it will do the most good for the world. The problem is when you choose what to maximize and you put blinders on, it's too easy to start making gigantic mistakes that have a big negative impact on society. So it really matters what you're maximizing. Right, and if we had a true democracy and everybody had one vote, everybody got decent information and had one vote, Ayn Rand's position would get some votes, but not many. And it would be way outvoted by the common people. Let me ask you about this very difficult topic. I'm talking to Mark Zuckerberg of Meta, the topic of censorship. I don't know if you've heard, but there's a guy named Robert Malone and Peter McCullough that were removed from many platforms for speaking about the COVID vaccine as being risky. They were both on Joe Rogan's program. What do you think about censorship in this space, in this difficult space where so much is controlled by, not controlled, but influenced by advertisements from big pharma, and science can even be influenced by big pharma? Where do you lean on this? Should we allow, should we lean towards freedom and just allow all the voices, even those that go against the scientific consensus? Is that one way to fight the science that is funded by big pharma? Or is that do more harm than good, having too many voices that are contending here? Should the ultimate battle be fought in the space of scientific publications? And particularly in the era of COVID, where there are large public health ramifications to this public discourse, the ante is way up. So I don't have a simple answer to that. I think everyone's allowed their own opinion. I don't think everyone's allowed their own scientific facts. And how we develop a mechanism that's other than an open internet where whoever is shouting the loudest gets the most clicks and the rage creates value on the internet. I think that's not a good mechanism for working this out. And I don't think we have one. I don't have a solution to this. I mean, ideally, if we had a philosopher king, we could have a panel of people who were not conflicted by rigid opinions decide on what the boundaries of public discourse might be. I don't think it should be fully open. I don't think people who are making, who are committed to an anti-vaccine position and will tailor their interpretation of complex scientific data to support their opinion, I think that can be harmful. Constraining their speech can be harmful as well. So I don't have an answer here, but yeah. I tend to believe that it's more dangerous to censor anti-vax messages. The way to defeat anti-vax messages is by being great communicators, by being great scientific communicators. So it's not that we need to censor the things we don't like. We need to be better at communicating the things we do like or the things that we do believe represent a deep scientific truth. Because I think if you censor, you get worse at doing science and you give the wrong people power. So I tend to believe that you should give power to the individual scientists and also give them the responsibility of being better educators, communicators, expressors of scientific ideas, put pressure on them to release data, to release that data in a way that's easily consumable, not just like very difficult to understand, but in a way that can be understood by a large number of people. So the battle should be fought in the open space of ideas versus in the quiet space of journals. I think we no longer have that comfort, especially at the highest of stakes. So this kind of idea that a couple of peer reviewers decide the fate of billions doesn't seem to be sustainable, especially given a very real observation now that the reason Robert Malone has a large following is there's a deep distrust of institutions, deep distrust of scientists, of science as an institution, of power centers, of companies, of everything, and perhaps rightfully so. But the way to defend against that is not for the powerful to build a bigger wall, it's for the powerful to be authentic and maybe a lot of them to get fired, and for new minds, for new fresh scientists, ones who are more authentic, more real, better communicators to step up. So I fear censorship because it feels like censorship is an even harder job to do it well than being good communicators. And it seems like it's always the C students that end up doing the censorship. That it's like, it's always the incompetent people, and not just the incompetent, but the biggest whiners. So like what happens is the people that get the most emotional and the most outrage will drive the censorship. And it doesn't seem like reason drives the censorship. That's just objectively observing how censorship seems to work in this current, so there's so many forms of censorship. You look at the Soviet Union with the propaganda or Nazi Germany, it's a very different level of censorship. People tend to conflate all of these things together. Social media trying desperately to have trillions or hundreds of billions of exchanges a day, and try to make sure that their platform has some semblance of like, quote, healthy conversations. People just don't go insane, they actually like using the platform, and they censor based on that. That's a different level of censorship, but even there, you can really run afoul of the people that get, the whiny C students controlling too much of the censorship. I believe that you should actually put the responsibility on the self-proclaimed holders of truth, aka scientists, at being better communicators. I agree with that, I'm not advocating for any kind of censorship, but Marshall McLuhan was very influential when I was in college, and his, that meme, the medium is the message. It's a little bit hard to understand when you're comparing radio to TV, and saying radio's hotter, or TV's hotter, or something, but we now have the medium as the message in a way that we've never seen, we've never imagined before, where rage and anger and polarization are what drives the traffic on the internet. And we don't, it's a question of building the commons. Ideally, I don't know how to get there, so I'm not pretending to have a solution, but the commons of discourse about this particular issue, about vaccines, has been largely destroyed by the edges, by the drug companies and the advocates on the one side, and the people who just criticize and think that even though the data are flawed, that there's no way vaccines can be beneficial. And to have those people screaming at each other does nothing to improve the health of the 95% of the people in the middle who want to know what the rational way to go forward is and protect their families from COVID and live a good life and be able to participate in the economy. And that's the problem. I don't have a solution. Well, there's a difficult problem for Spotify and YouTube. I don't know if you heard, this is a thing that Joe Rogan is currently going through, as a platform, whether to censor the conversation that, for example, Joe was having. So I don't know if you heard, but Neil Young and other musicians have kind of spoke out and saying they're going to leave the platform because Joe Rogan is allowed to be on this platform having these kinds of conversations with the likes of Robert Malone. And it's clear to me that Spotify and YouTube are being significantly influenced by these extreme voices, like you mentioned, on each side. And it's also clear to me that Facebook is the same, and it was going back and forth. In fact, that's why Facebook has been oscillating on the censorship, is like one group gets louder than the other, depending on whether it's an election year. There's several things to say here. So one, it does seem, I think you put it really well, it would be amazing if these platforms could find mechanisms to listen to the center, to the big center that's actually going to be affected by the results of our pursuit of scientific truth, right? And listen to those voices. I also believe that most people are intelligent enough to process information and to make up their own minds. Like they're not in terms of, it's complicated, of course, because we've just been talking about advertisement and how people can be influenced. But I feel like if you have raw, long form, podcasts or programs where people express their mind and express their argument in full, I think people can hear it to make up their own mind. And if those arguments have a platform on which they can live, then other people could provide better arguments if they disagree with it. And now we as human beings, as rational, as intelligent human beings, can look at both and make up our own minds. And that's where social media can be very good at this collective intelligence. We together listen to all of these voices and make up our own mind. Humble ourselves actually often. You think you know, like you're an expert, say you have a PhD in a certain thing, so there's this confidence that comes with that. And the collective intelligence, uncensored, allows you to humble yourself eventually. Like as you discovery, all it takes is a few times looking back five years later, realizing I was wrong. And that's really healthy for a scientist, that's really healthy for anybody to go through. And only through having that open discourse can you really have that. That said, Spotify also, just like Pfizer is a company, which is why this podcast, I don't know if you know what RSS feeds are, but podcasts can't be censored. So Joe's in the unfortunate position, he only lives on Spotify. So Spotify's been actually very good at saying we're staying out of it for now. But RSS, this is pirate radio. Nobody can censor, it's the internet. So financially, in terms of platforms, this cannot be censored, which is why podcasts are really beautiful. And so if Spotify or YouTube wants to be the host of podcasts I think where they flourish is free expression, no matter how crazy. Yes, but I do wanna push back a little bit on what you're saying. Because I have anti-fax friends who I love. I mean, they're dear, cherished friends. And they'll send me stuff. And it'll take me an hour to go through what they sent to see if it is credible. And usually it's not. It's not a random sample of the anti-vax argument. I'm not saying I can disprove the anti-vax argument, but I am saying that it's almost like we were talking about how medical science, clinical trials, the presentation of clinical trials to physicians could be improved. And the first thing we came up with is to have pre-publication transparency in the peer review process. So bad information, biased information, doesn't get out as if it's legitimate and you can't put it back, recapture it once it gets out. I think there's an element of that in the arguments that are going on about vaccines. And they're on both sides, but I think the anti-vax side puts out more units of information claiming to show that the vaccines don't work. And I guess in an ideal situation, there would be real-time fact-checking by independent people not to censor it, but to just say that study was set up to do this, and this is what the conclusions were. So the way it was stated is on one side of this argument. But that's what I'm arguing, I agree with you. What I'm arguing is that this big network of humans that we have that is the collective intelligence can't do that real-time if you allow it to, if you encourage people to do it. And the scientists, as opposed to, listen, I interact with a lot of colleagues, a lot of friends that are scientists, they roll their eyes. Their response is like, ugh. Like they don't want to interact with this. But that's just not the right response. When a huge number of people believe this, it is your job as communicators to defend your ideas. It is no longer the case that you go to a conference and defend your ideas to two other nerds that have been working on the same problem forever. I mean, sure, you can do that, but then you're rejecting the responsibility you have explicitly or implicitly accepted when you go into this field, that you will defend the ideas of truth. And the way to defend them is in the open battlefield of ideas, and you become a better communicator. And I believe that when you have a large, you said you invested one or two hours in this particular, but that's little ants interacting at scale, I think that allows us to progress towards truth, at least, you know, at least I hope so. I think you're an optimist. I wanna work with you a little bit on this. Let's say a person like Joe Rogan, who, by the way, had me on his podcast, and let me- It was an amazing conversation. I really enjoyed it. Well, thank you. I did too. And I didn't know Joe. I didn't know much about his podcast. He pushed back on Joe a bunch, which is great. And he was- I love it. He was a gentleman, and we had it out. In fact, he put one clip, at one point he said something that was a little bit wrong, and I corrected him. And he had the guy who- Jamie. Jamie. He had Jamie check it, and was very forthright in saying, you know, John's got it right here. We gotta modify this. In any event, in any event- You got him. Well, I wasn't trying to get him. I was just trying to- No, no, no, no, no. You totally, it was a beautiful exchange. There was so much respect in the room, pushing back and forth, it was great. Yeah, so I respect him. And I think when he has somebody on who's a dyed-in-the-wool anti-vaxxer, the question is, how can you balance, if it needs balance, in real time? I'm not talking about afterwards. I'm talking in real time. Maybe you record- Well, he does record it, obviously. But maybe when there's a statement made that is made as if it's fact-based, maybe that statement should be checked by some folks who, imaginary folks who are trustworthy. And in real time, as that discussion is being played on the podcast, to show what independent experts say about that claim. That's a really interesting idea. By the way, for some reason, this idea popped into my head now is, I think real time is very difficult. And it's not difficult, but it kind of ruins the conversation, because you want the idea to breathe. Yeah. I think what's very possible is before it's published, it's the pre-publication, before it's published, you let a bunch of people review it, and they can add their voices in post, before it's published. They can add arguments, arguments against certain parts. That's very interesting, to sort of, as one podcast, publish addendums. Publish the peer review together with the publication. Yes. That's very interesting. I might actually do that. That's really interesting. Because I've been doing more debates, where at the same time, have multiple people, which has a different dynamic, because both people, I mean, it's really nice to have the time to pause, just by yourself, to fact check, to look at the study that was mentioned, to understand what's going on. So the peer review process, to have a little bit of time. That's really interesting. I actually would, I'd like to try that. To agree with you on some point, in terms of anti-vax, I've been fascinated by listening to arguments from this community of folks, that's been quite large, called the Flat Earthers. They're the people that believe the Earth is flat. And I don't know if you've ever listened to them, or read their arguments, but it's fascinating how consistent and convincing it all sounds, when you just kind of take it in. Just like, just take it in like listening normally, it's all very logical. Like if you don't think very, well, no. So the thing is, the reality is, at the very basic human level, with our limited cognitive capabilities, the Earth is pretty flat, when you go outside, and you look, it's flat. So like, when you use common sense reasoning, it's very easy to play to that, to convince you that the Earth is flat. Plus there's powerful organizations that want to manipulate you, and so on. But then there's the whole progress of science and physics of the past, but that's difficult to integrate into your thought process. So it's very true that people should listen to Flat Earthers, because it was very revealing to me how easily it is, how easy it is to be convinced of basically anything, by charismatic arguments. Right, and if we're arguing about whether the Earth is flat or not, as long as we're not navigating airplanes and doing other kinds of things, trying to get satellites to do transmission, it's not that important, what I believe. But if we're arguing about how we approach the worst public health crisis in, I don't know how long, I think we're getting worse than the Spanish flu now, I don't know what the total global deaths with Spanish flu were, but in the United States, we certainly have more deaths than we had from Spanish flu. Plus the economic pain and suffering. Yes, yes, and the damage to the kids, school and so forth. We got a problem, and it's not going away, unfortunately. So when we get a problem like that, it's not just an interesting bar room conversation about whether the Earth is flat, there are millions of lives involved. Let me ask you yet another question, that issue I raised with Pfizer CEO Albert Bourla. It's the question of revolving doors. That there seems to be a revolving door between Pfizer, FDA, and CDC. People that have worked at the FDA, now work at Pfizer, and vice versa, including the CDC and so on. What do you think about that? So first of all, his response, once again, is there's rules, there's very strict rules, and we follow them. Do you think that's a problem? Hoo-ha. And also, maybe this is a good time to talk about this Pfizer play by the rules. One at a time. One at a time. Okay, and this isn't even about Pfizer, but it's an answer to the question. Yes. So there's this drug, Adjahilm, that was approved by the FDA maybe six months ago. It's a drug to prevent the progression of low-grade Alzheimer's disease. The target for drug development for Alzheimer's disease has been the amyloid, reducing the amyloid plaques in the brain, which correlate with the progression of Alzheimer's. And Biogen showed that its drug, Adjahilm, reduces amyloid plaques in the brain. They did two clinical trials to determine the clinical efficacy, and they found that neither trial showed a meaningful benefit. And in those two trials, 33% more people in the Adjahilm group developed symptomatic brain swelling and bleeding than people in the placebo group. There was an advisory committee convened to debate and determine how they felt about the approvability of Adjahilm, given those facts. And those facts aren't in dispute. They're in Biogen slides, as well as FDA documents. The advisory committee voted 10 against approval and one abstain. So that's essentially universal, a unanimous vote against approving Adjahilm. Now, the advisory committees have been pretty much cleansed of financial conflicts of interest. So this advisory committee votes 10 no, one abstention, and the FDA overrules the unanimous opinion of its advisory committee and approves the drug. Three of the members of the advisory committee resign. They say, we're not gonna be part, if the FDA's not gonna listen to a unanimous vote against approving this drug, which shows more harm than benefit, undisputed. We're not gonna participate in this. And the argument against approval is that the surrogate endpoint, the reduction of amyloid, the progression of amyloid plaques, is known by the FDA not to be a valid clinical indicator. It doesn't correlate. 27 studies have shown it doesn't correlate with clinical progression. Interrupting the amyloid plaques doesn't mean that your Alzheimer's doesn't get worse. So it seems like it's a slam dunk and the FDA made a mistake and they should do whatever they do to protect their bureaucratic reputation. So the head of the Bureau of the FDA, the Center for Drug Evaluation and Research that approves new drugs, who had spent 16 years as an executive in the pharmaceutical industry, issued a statement and said, what we should do in this situation is to loosen the prohibition of financial ties of interest with the drug companies so we get less emotional responses. Said this, it's in print. People are just too emotional about this. People were just too emotional. The 10 people who voted against it and the no people who voted for it, it's all too emotional. So this gets back, this is a long answer to your short question. I think this is a wonderful window into the thinking of the FDA that financial conflicts of interest don't matter in a situation when I think it's obvious that they would matter. But there's not a direct financial conflict of interest. It's kind of, like it's not, like Albert said, there's rules. I mean, you're not allowed to have direct financial conflicts of interest. It's indirect. Right, but what I'm saying is, I'm not denying what he said is true, but the FDA, a high official in the FDA is saying that we need to allow conflicts of interest in our advisory committee meetings. Ah. And that, she wants to change the rules. Right. So Albert Bourla would still be playing by the rules, but it just shows how one-sided the thinking here is. But you think that's influenced by the fact that there were pharmaceutical executives working at the FDA and vice versa. And they think that's a great idea. Who gets to fix this? Do you think it should be just banned? Like if you worked. I don't know. Two separate questions. Yeah. One is, should the officials at the FDA come from pharma and vice versa? Yes. That's one question. And the other question is, should advisory committee members be allowed to have financial conflicts of interest? Yes. I think, in my opinion, and people might say I'm biased, I think advisory committee people should not have conflicts of interest. I think their only interest ought to be the public interest. And that was true from my understanding of the situation. It's the afterward in my book. I spent some time studying it about Adjahilm. I think it's a slam dunk that there ought to be no conflicts of interest. Now, the head of CDER, Center for Drug Evaluation Research, thinks that that's gonna give you a biased result because we don't have company influence. And that, I think, shows how biased their thinking is, that not having company influence is a bias. Let me try to load that in. I'm trying to empathize with the belief that companies should have a voice at the table. I mean, yeah, it's part of the game. They've convinced themselves that this is how it should be played. But they have a voice at the table. They've designed the studies. Right, that's their voice. They've analyzed the data. I mean, what bigger voice do you deserve? But I do also think, on the more challenging question, I do think that there should be a ban. If you work at a pharmaceutical company, you should not be allowed to work at any regulatory agency. Yes. You should not. I mean, that, going back and forth, it's just, even if it's 30 years later. Yeah, I agree. And I have another nomination for a ban. We're in this crazy situation where Medicare is not allowed to negotiate the price of drugs with the drug companies. So the drug companies get a patent on a new drug. Unlike every other developed country, they can charge whatever they want. So they have a monopoly on a utility because no one else can make the drug. Charge whatever they want, and Medicare has to pay for it. And you say, how did we get in this crazy situation? So how we got here is that in 2003, when Medicare Part D was passed, Billy Towson was head of the Ways and Means Committee in the House, played a key role in ushering this through with the non-negotiation clause of it. And after it was passed, Billy Towson did not finish out his term in Congress. He went to pharma for a $2 million a year job. This is, this is incredible. You might think that a ban on that would be a good idea. I spoke with Francis Collins, head of the NIH, on this podcast. He and NIH have a lot of power over funding in science. What are they doing right? What are they doing wrong? In this interplay with big pharma, how connected are they? Again, returning to the question, what are they doing right? What are they doing wrong, in your view? Yeah, so my knowledge of the NIH is not as granular as my knowledge of pharma. That said, in broad brushstrokes, the NIH is doing the infrastructure work for all drug development. I think they've participated in 100% of the drugs that have been approved by the FDA over the past 10 years or so. They've done infrastructure work. And what they do is not work on particular drugs, but they develop work on drug targets, on targets in the human body that can be affected by drugs and might be beneficial to turn on or off. And then the drug companies can, when they find a target that is mutable and potentially beneficial, then the drug companies can take the research and choose to invest in the development of the drugs, specific drug. That's our model. Now, 96% of the research that's done in clinical trials in the United States is about drugs and devices. And only a fraction of the 4% that's left over is about preventive medicine and how to make Americans healthier. I think, again, from the satellite view, the NIH is investing more in science that can lead to commercial development rather than, as you said at the beginning of the podcast, there's no big fitness and lifestyle industry that can counter pharma. So I think at the NIH level, that countering can be done. And the Diabetes Prevention Program study that we talked about before, where lifestyle was part of a randomized trial and was shown to be more effective than metformin at preventing the development of diabetes, that is absolute proof positive that investing in that kind of science can produce good results. So I think that we're aimed at drug development and what we ought to be aimed at is an epidemiological approach to improving the health of all Americans. We rank 68th in the world in healthy life expectancy. Despite spending an extra trillion and a half dollars a year. And I believe strongly that the reason why we've gotten in this crazy position is because the knowledge that we're producing is about new drugs and devices and it's not about improving population health. In this problem, the NIH is the perfect institution to play a role in rebalancing our research agenda. And some of that is on the leadership side with Francis Collins and Anthony Fauci, not just speaking about basically everything that just leads to drug development, vaccine development, but also speaking about healthy lifestyles and speaking about health, not just sickness. Yes, and investing. Investing in health. I mean, it's like one fee is the other. One, you have to communicate to the public the importance of investing in health and that leads to you getting props for investing in health and then you can invest in health more and more and that communicates, I mean, everything that Anthony Fauci says or Francis Collins says has an impact on scientists. I mean, it sets the priorities. I don't think they, it's the sad thing about leaders. Forgive me for saying the word, but mediocre leaders is they don't see themselves as part of a game. They don't see the momentum. It's like a fish in the water. They don't see the water. Great leaders stand up and reverse the direction of how things are going and I actually put a lot of responsibility, some people say too much, but whatever. I think leaders carry the responsibility. I put a lot of responsibility on Anthony Fauci and Francis Collins for not actually speaking a lot more about health, not, and bigger, inspiring people in the power and the trustworthiness of science. You know, that's on the shoulders of Anthony Fauci. I'm gonna abstain from that because I'm not expert enough, but. Neither am I, but I'm opinionated. I am too, but not on camera. Yes. No, but seriously, the problem is pretty simple, that we're investing 96% of our funding of clinical research in drugs and devices and 80% of our health is determined by how we live our lives. Yes. And this is ridiculous. The United States is going further and further behind the other wealthy countries in terms of our health. We ranked 38th in healthy life expectancy in 2000 and now we're spending a trillion and a half dollars extra and we rank 68th. We've gone down. You have this excellent, there's a few charts that I'll overlay that tell the story in really powerful ways. So one is the healthcare spending as percentage of GDP that on the x-axis is years and the y-axis is percentage. And the United States, as compared to other countries on average, has been much larger and growing. Right, we are now spending 7% more of our GDP, 17.7% versus 10.7% on healthcare. 7%, and I think GDP is the fairest way to compare healthcare spending. Per person in dollars, we're spending even, the difference is even greater. But other costs vary with GDP. So let's stick with the conservative way to do it. 17.7 or 18% of GDP. 18% of GDP spent on healthcare. 7% higher than the comparable country average. 17.7% versus 10.7. 7% higher. Right, and 7% of $23 trillion GDP is more than $1.5 trillion a year in excess. And then you have another chart that shows healthcare system performance compared to spending. And there's a point cloud of different countries, the x-axis being healthcare spending as a percentage of GDP, which we just talked about. That US is 7% higher than everyone, the average. And then on the y-axis is performance. So x-axis spending, y-axis performance. And there's a point cloud, we'll overlay this if you're watching on YouTube, of a bunch of countries that have high performance for what they're spending. And then US is all alone on the right bottom side of the chart where it's low performance and high spending. Correct. So this is a system that is abiding by spending that is directed by the most profitable ways to deliver healthcare. So you put that in the hands of big pharma. As you maximize for profit, you're going to decrease performance and increase spending. Yes, but I want to qualify that and say it's not all big pharma's fault. They're not responsible for all the problems in our healthcare system. They're not responsible for the administrative costs, for example. But they are the largest component of our rising healthcare costs. And it has to do with this knowledge issue. Controlling the knowledge that doctors have makes it so that doctors can live with this situation, believing that it's optimal, when it's a wreck. Yeah. Let me ask you the big, so as a physician, so everything you've seen, we've talked about 80% of the impact on health is lifestyle. How do we live longer? What advice would you give to general people? What space of ideas result in living longer and higher quality lives? Right, this is a very simple question to answer. Exercise for at least a half hour, at least five times a week, number one. Number two, don't smoke. Number three, maintain a reasonably healthy body weight. Some people argue that being lower than a BMI of 25 is healthy. I think that may be true, but I think getting above 30 is unhealthy, and that ought to be. Now, that's largely impacted by socioeconomic status, and we don't wanna blame the victims here. So we gotta understand that when we talk about all of these things, not cigarettes, but exercise and a good diet, and maintaining a healthy body weight, we have to include in doing those things the impediments to people of lower socioeconomic status being able to make those changes. We've got to understand that personal responsibility accounts for some of this, but also social circumstances accounts for some of it. And back to your fishbowl analogy, if you're swimming in a fishbowl, if you live in a fish tank that's not being properly maintained, the approach wouldn't be to treat individual sick fish. It would be to fix your fish tank to get the bacteria out of it and whatever bad stuff is in there, and make your fish tank healthier. Well, we invest far less than the other wealthy countries do. We're flipped. We have the mirror image in the spending on social determinants of health and medical determinants of health. We have exactly the wrong order. And not only does that choke off social determinants of health, which are very important, but actually just the ratio, even if you were spending, if we raise the social spending and raise our medical spending in proportion, it's the ratio of social spending to medical spending that's the problem. So, and why do we do that? Well, the answer is perfectly obvious that the way to transfer money from working Americans to investors is through the biomedical model, not through the social health model. And that's the problem. And I'd like to discuss this because the market isn't gonna get us to a reasonable allocation. All the other wealthy countries that are so much healthier than we are and spending so much less than we are have some form of government intervention in the quality of the health data that's available, in the budgeting of health and social factors. And we don't, we're kind of the Wild West and we let the market determine those allocations. And it's an awful failure. It's a horrendous failure. So one argument against government, or I'm sorry, an alternative to the government intervention is the market can work better if the citizenry has better information. So one argument is that, you know, communicators like podcasts and so on, but other channels of communication will be the way to fight big pharma. Your book is the way to, by providing information. The alternative to the government intervention on every aspect of this, including communication with the doctors, is to provide them other information and not allow the market to provide that information by basically making it exciting to buy books, to make better and better communicators on Twitter, through books, through op-eds, through podcasts, through so on. So basically, because there's a lot of incentive to communicate against the messages of big pharma. There is incentive, because people want to understand what's good for their lives, and they're willing to listen to charismatic people that are able to clearly explain what is good for them. And they do. And more than 80% of people think that drugs cost too much, and the drug industry is too interested in profits. But they still get influenced. They can't, you can't get the vote through Congress. You know, Democrats and Republicans alike are taking money from Congress. And somehow, it just doesn't work out that these even small changes. I mean, the pared down part of Medicare, the plan for increasing Medicare negotiation drug costs in Build Back Better, it's literally gonna reduce the number of new drugs that are beneficial, uniquely beneficial, by about one new drug, or two new drugs over 30 years. It will have virtually an indecipherable impact. And yet, pharma is talking about the impact on innovation. And if you vote for this, if you let your congressman vote for this, you're gonna severely slow down drug innovation, and that's gonna affect the quality of your life. Let me ask you about over-medication that we've been talking about from different angles. But one difficult question for me, I'll just, I'll pick one of the difficult topics, depression. So depression is a serious, painful condition that leads to a lot of people suffering in the world. And yet, it is likely they were over-prescribing antidepressants. So as a doctor, as a patient, as a healthcare system, as a society, what do we do with that fact? That people suffer, there's a lot of people suffering from depression, and there's also people suffering from over-prescribing of antidepressants. Right. So a paper in the New England Journal by Eric Turner showed that the data, if you put all the data together from antidepressants, you find out that antidepressants are not effective for people who are depressed but don't have a major depression. Major depression is a serious problem. People can't function normally, they have a hard time getting out, performing their normal social roles. But what's happened is that the publicity, I mean, Prozac Nation was a good example of making the argument that why should people settle for normal happiness when they can have better than normal happiness? And if you're not having normal happiness, you should take a drug. Well, that concept that serotonin metabolism is the root cause of depression is really a destructive one. We have drugs that change serotonin metabolism, but we don't know if that's why antidepressants work on major depression. And they certainly don't work on everybody with major depression. I forget what the number needed to treat is. I think it's around four. One out of four people have significant improvement. But the people without major depression don't get better. And the vast majority of these drugs are used for people without major depression. So what's happened is that the feelings of life satisfaction, of happiness and not sadness have been medicalized. The normal range of feelings have been medicalized. And that's not to say that they shouldn't be attended to, but the evidence shows that attending to them by giving somebody a medicine doesn't help except that they feel like somebody cares about them and believes that they're suffering. But there are problems in living that give rise to much of this symptomatology of less than major depression and let's call it what it is and figure out a way to help people, individual therapy, group therapy, maybe lifestyle modification would work. We gotta try that. But let's call it what it is instead of saying, oh, you're in this vast basket of people who are depressed so we'll give you an antidepressant, even though the evidence shows that people who are suffering from your level of depression don't get better. And that's a consequence of not focusing on preventative medicine, the lifestyle changes, all that kind of stuff. Well, yes, but it's really a consequence of the drug companies creating the impression that if you're sad, take a pill. If you're non-major depression, how do you overcome depression? Well, you have to talk about what the problem is. So talk therapy, lifestyle changes. Well, no, I'm not jumping to that. I'm saying that you ought to, A, the way you feel must be respected. Yeah, acknowledge that you're suffering. Acknowledge that you're suffering and deal with healthcare providers who acknowledge that you're suffering. So let's take that first step. And then- Big first step also. Big first step, yeah. Family docs are pretty good at that. That's kind of the arena that caused me to go into family medicine, the subjective experience of the patient. Okay, so you're a person who is not getting the enjoyment out of their life that they feel they ought to be getting. Now let's figure out why and whether that means some time with a social worker, some time with a psychiatrist, some time with a psychiatric nurse. I'm not sure how you'd best do that, most effectively and efficiently, but that's what you need to do. And it may be that there's a marital problem and there's something going on and one of the spouses can't find satisfaction in the life they have to live within the relationship. Maybe there's a past history of trauma or abuse that somebody is projecting onto their current situation. Maybe there's socioeconomic circumstances where they can't find a job that gives them self-respect and enough money to live. All, an infinite range of things. But let's figure out, make a diagnosis first. The diagnosis isn't that the person feels sadder than they want to feel. The diagnosis is why does the person feel sadder than they want to feel? You mentioned this is what made you want to get into family medicine. As a doctor, what do you think about the saying, save one life, save the world? This was always moving to me about doctors because you have this human in front of you and your time is worth money. Your, what you prescribe and your efforts after the visit are worth money. And it seems like the task of the doctor is to not think about any of that. Or, not the task, but it seems like a great doctor despite all that just forgets it all and just cares about the one human. And somehow that feels like the love and effort you put into helping one person is the thing that will save the world. It's not like some economic argument or some political argument or financial argument. It's a very human drive that ultimately is behind all of this that will do good for the world. Yes, I think that's true. And at the same time, I think it's equally true that all physicians need to have a sense of responsibility about how the common resources are allocated to serve the whole population's interest best. That's a tension that you have as a physician. Let's take the extreme example. Let's say you had a patient in front of you who if you gave a $1, 10 billion pill to, you would save their life. I would just be tortured by that as a physician because I know that $10 billion spent properly in an epidemiologically guided way is gonna save a whole lot more lives than one life. So it's also your responsibility as a physician to walk away from that patient. I wouldn't say that. I think it's your responsibility. To be tortured by it. That's exactly right. The human condition. Yeah. That's a tough job. But yeah, yeah, to maintain your humanity through it all. But you've been asking at different points in this conversation, why are doctors so complacent about the tremendous amount of money we're spending? Why do they accept knowledge from different sources that may not pan out when they really know the truth? And the answer is that they're trying to do their best for their patients. And it's the same kind of torture to figure out what the hell is going on with the data. And that's a sort of future project. And maybe people will read my book and maybe they'll get a little more excited about it, become more legitimate in practice. I would feel like my life was worthwhile if that happened. But at the same time, they've gotta do something with the patient in front of them. They've got to make a decision. And they probably, there are not many weirdos like me who invest their life in figuring out what's behind the data. They're trying to get through the day and do the right thing for their patient. So they're tortured by that decision too. And so if you're not careful, big pharma can manipulate that drive to try to help the patient, that humanity of dealing with the uncertainty of it all. Like what is the best thing to do? Big pharma can step in and use money to manipulate that humanity. Yeah, I would state it quite differently. It's sort of an opt out rather than an opt in. Big pharma will do that. And you need to opt out of it. What advice would you give to a young person today in high school or college stepping into this complicated world full of advertisements, of big powerful institutions, of big rich companies, how to have a positive impact in the world, how to live a life they can be proud of? I would say should that person who has only good motives go into medicine. They have an inclination to go into medicine and they've asked me what I think about that given what I know about the undermining of American healthcare at this point. And my answer is if you got the calling, you should do it. You should do it because nobody's gonna do it better than you. And if you don't have the calling and you're in it for the money, you're not gonna be proud of yourself. How do you prevent yourself from doing, from letting the system change you over years and years? Like letting the game of pharmaceutical influence affect you? It's a very hard question because the sociologic norms are to be affected and to trust the sources of information that are largely controlled by the drug industry. And that's why I wrote Sickening is to try and help those people in the medical profession to understand that what's going on right now looks normal but it's not. The health of Americans is going downhill. Our society is getting ruined by the money that's getting pulled out of other social, socially beneficial uses to pay for healthcare that is not helping us. So fundamentally, the thing that is normal, not question the normal, don't, if you conform, conform hesitantly. Well, you have to conform. You can't become a doctor without conforming. I just made it through. But there aren't many and it's hard work. But you have to conform. And even with my colleagues in my own practice, I couldn't convince them that some of the beliefs they had about how best to practice weren't accurate. There's one scene, a younger physician had prescribed hormone replacement therapy. This is back in 2000, 2001, had prescribed hormone replacement therapy for one of my patients who happened to be a really good personal friend. And I saw that patient covering for my colleague at one point and I saw that her hormone replacement therapy had been renewed and I said, are you having hot flashes or any problem? No, no, no, no. But Dr. So-and-so said it's better for my health. And I said, no, no, it's not. The research is showing that it's not. It's harmful for your health and I think you should stop it. So my colleague approached me when she saw the chart and said, wait a minute, that's my patient. Maybe your friend, but it's my patient. And I went to a conference from my alma mater, medical school, and they said that healthy people should be given hormone replacement. And I said, there's gotta be drug companies involved in this. And she said, no, no, no, it was at my university. It was not a drug company thing. We didn't go to a Caribbean island. I said, do you have the syllabus? She said, yeah. And she went and got the syllabus and sure enough, it was sponsored by a drug company. They're everywhere. They're everywhere. And it's back to Kuhn that groups of experts share unspoken assumptions and in order to be included in that group of experts, you have to share those unspoken assumptions. And what I'm hoping to do with my book, Sickening, and being here, having this wonderful conversation with you is to create an alternative to this normal that people can pursue and practice better medicine and also prevent burnout. I mean, about half the doctors complain that they're burned out and they've had it. And I think that this is a subject, but I don't have data on this. This is just my opinion. But I think that a lot of that burnout is so-called moral injury from practicing in a way that the docs know isn't working. It's not actually providing an alternative to the normal. It's expanding the normal, it's shifting the normal, just like with Kuhn. I mean, you're basically looking for, to shift the way medicine is done to the original, I mean, to the intent that it represents, the ideal of medicine, of healthcare. Yeah, in Kuhnian terms, to have a revolution. And that revolution would be to practice medicine in a way that will be epidemiologically most effective, not most profitable for the people who are providing you with what's called knowledge. You helped a lot of people as a doctor, as an educator, live better lives, live longer, but you yourself are a mortal being. Do you think about your own mortality? Do you think about your death? Are you afraid of death? I'm not, I've faced it. Been close. Yourself? Yeah, yeah. How do you think about it? What wisdom do you gain from having come close to death, the fact that the whole thing ends? It's liberating. It's very liberating. I mean, I'm serious. I was close, and not too long ago. And it was a sense of, you know, this may be the way it ends, and I've done my best. It's not been perfect, and if it ends here, it ends here. The people around me are trying to do their best, and in fact, I got pulled out of it, but it didn't look like I was gonna get pulled out of it. Are you ultimately grateful for the ride, even though it ends? Well, it's a little, I think so. If I know, you know, you can't take the ride if you know it's gonna end well. It's not the real ride, it's just a ride. But I, having gone through the whole thing, I definitely freed me of a sense of anxiety about death, and it said to me, do your best every day, because it's gonna end sometime. I apologize for the ridiculously big question, but what do you think is the meaning of life, of our human existence? I think it's to care about something and do your best with it, whether it's being a doctor and trying to make sure that the greatest number of people get the best healthcare, or it's a gardener who wants to have the most beautiful plants, or it's a grandparent who wants to have a good relationship with their grandchildren. But whatever it is that gives you a sense of meaning, as long as it doesn't hurt other people, to really commit yourself to it. That commitment, being in that commitment, for me, is the meaning of life. Put your whole heart and soul into the thing. Yep. What is it, the Bukowski poem, Go All the Way. Hmm, John, you're an incredible human being, incredible educator. Like I said, I recommend people listen to your lectures. It's so refreshing to see that clarity of thought and brilliance. And obviously, your criticism of Big Pharma, or your illumination of the mechanisms of Big Pharma is really important at this time. So I really hope people read your book, Sickening, that's out today, or depending on when this comes out. Thank you so much for spending your extremely valuable time with me today. It was amazing. Well, Lex, I wanna back to you. Thanks for engaging in this conversation, for creating the space to have it, and creating a listenership that is interested in understanding serious ideas. And I really appreciate the conversation. And I should mention that offline, you told me you listened to the Gilbert Strang episode. So for anyone who don't know Gilbert Strang, another epic human being that you should check out. If you don't know anything about mathematics or linear algebra, go look him up. He's one of the great mathematics educators of all time. Of all the people you mentioned to me, I appreciate that you mentioned him, because he is a rock star of mathematics. John, thank you so much for talking to me. This was awesome. Great, thank you. Thanks for listening to this conversation with John Abramson. To support this podcast, please check out our sponsors in the description. And now let me leave you some words from Marcus Aurelius. Waste no time arguing about what a good man should be. Be one. Thank you for listening and hope to see you next time.

https://youtu.be/arrokG3wCdE

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Nic Carter: Bitcoin Core Values, Layered Scaling, and Blocksize Debates | Lex Fridman Podcast #173

The following is a conversation with Nick Carter, who is a partner at Castle Island Ventures, co-founder of CoinMetrics.io, and previously a crypto asset research analyst at Fidelity Investments. He's a prominent writer, speaker, and podcaster on topics around decentralized finance and especially Bitcoin. Quick mention of our sponsors, The Information, Athletic Greens, Four Sigmatic, and Blinkist. Check them out in the description to support this podcast. This conversation with Nick Carter is part of a series of episodes on cryptocurrency that is a small journey of exploration I'm on because I find decentralized finance, and especially Bitcoin, fascinating, technically and philosophically, especially because it may be the very mechanism that achieves a global decentralization of power, giving more sovereignty to the individual, and making our systems more resilient to corruption, manipulation, and in general, to the darker sides of human nature. Please let me also address something for a few minutes that happened recently that's been weighing heavy on me. If you find me annoying to listen to, please skip to the actual conversation with Nick. I had a recent podcast episode with Anthony Pompliano where we spoke about Bitcoin and life in general for three hours. I was curious, inspired, positive, or at least I tried to be as I usually do. Someone clipped out, out of context, a short segment of me mumbling something about having a PhD, and I started getting mocked online because that made it convenient for people to mock me for being yet another quote-unquote expert who learns about Bitcoin and thinks he knows everything. I almost never mention that I have a PhD, except to make fun of myself, as I was doing, or at least trying to do in the full context of the conversation. I brought up grad school as a random example of one of the many journeys I've taken that was hard, but where the destination was in itself not very useful. I was saying I enjoy exploring with a curious mind, and I'm willing to be patient, to learn, to listen, to humble myself with knowledge for the sake of knowledge itself. Grad school was an example of that. The PhD means nothing, at least to me. I never call myself an expert, or at least try not to, because that would be dumb, because I know how little I know. I'm not an influencer, or a thought leader, or whatever else silly, self-aggrandizing label people put on their LinkedIn. I try to be the opposite of what I was mocked for. I try to think deeply about the world, to look for the beautiful ideas in the minds of others, and to be inspired by them. I wanted to say all this because psychologically, it struck a bit of a blow. It made me realize that even when I approach things with love, I may be mocked, I may be derided, I may be taken out of context, or even lied about. With the growing platform, this is sadly only increasing. I now have learned that there's people who are waiting for my missteps, so they can point the finger, laugh, and say, see, I told you so. That guy's a joke. He's a fraud. As a fellow human being, the knowledge of this is painful. Yes, I know, people tell me to toughen up, and my life has been about strengthening my mind in the face of my limits, but I refuse to not be fragile and wear my heart on my sleeve. It's who I am. In some sense, this is the immune system of the internet, but let us be careful not to destroy the good ones in the process. The Bitcoin community had to endure many years of attacks from quote-unquote experts, and also fraudulent cryptocurrency efforts that scammed people out of their money. This created a powerful immune system that fought the attackers and the scammers. I understand this, and I also understand that one of the beautiful aspects of Bitcoin is its community of humans is decentralized. But some small part of this community has come to enjoy the us versus them battles, sometimes for the sake of the battle in itself. This happens in political discourse as well. I understand this, but to my limited mind, it sounds like groupthink, which has powerful defense mechanisms against bad ideas, but has dangerous consequences if taken too far, as in many periods of human history that I often talk about, where the us versus them thinking has led to the suffering of many. Again, I understand the value of this as many Bitcoiners explained to me, but it's not the way I, as a sovereign individual, choose to walk in this life. By the way, none of this podcast should be treated as financial advice. Before Nick kindly gifted me with $100 worth of Bitcoin in hardware form, I didn't own any. I'll probably buy some Bitcoin on Cash App, Coinbase, and other platforms, and also transfer to a hardware wallet just to learn how to do it. But other than that, I don't necessarily make wise investment decisions. Money is not a motivation for me personally. I try to avoid it, actually. I'm grateful for every day I'm alive, no matter how much money is in my bank account. For long stretches of my life, that number was very close to zero, and I was always fortunate to be free and happy. So I encourage you to listen to people much smarter than me for actual good financial advice. Here, I'm just exploring ideas. And as if this has not already gone on too long, let me please make another comment on the style of discourse among some Bitcoin maximalists on platforms like Twitter, that in my humble view, I may be wrong, but I believe is not conducive to the nuanced, empathetic exchange of ideas I very much look for and enjoy. Again, I appreciate their style of discourse. I think I understand the value of it, but it's not my thing, so I don't want to engage in it. I want to hear the quiet voices in the room. I look for people to inspire each other, and when we disagree, I look for disagreement that is grounded in respect and empathy. I think that mockery and derision destroys the possibility of those nuanced conversations. It drives away the quiet, thoughtful, empathetic voices, and I try to give those voices space to be heard, to shine, to exchange ideas, whether we agree or disagree. So, if I happen to block you on Twitter, I block you with love. Honestly, I will never speak poorly of you or even think poorly of you. I would love to hang out in person, give you a big old hug, and talk about life over some beers. If you see or hear me say something stupid, which I'm sure I do often, or something you disagree with, and you still respect me as a human being, please show your love, as I always do to you, but also send me some links to blogs, books, videos, podcasts, where people describe why my stated idea may be totally wrong. I love this kind of long-form disagreement. I humble myself every day by reading books and blogs by people much smarter than me. Sometimes it strengthens my ideas, sometimes it totally changes them, but I always learn. This is a too long way of saying that I'm here trying to walk with grace and with an open mind, a bit of patience, and always love. If I make mistakes, cut me some slack. Like you, I'm only human, allegedly. This is the Lex Freeman podcast, and here is my conversation with Nick Carter. What philosopher or philosophical idea had a big impact on your life, not just in the space of cryptocurrency, but in general? Oh, so we're going now. We're rolling. We're going right in. We're rolling. Because you majored philosophy. I did. I majored in philosophy. I didn't know what to do with my life, and my parents said, do whatever you find interesting. It's like, okay, philosophy, great. I find that interesting. Yeah. And it had way more of an impact on my career, actually, than I thought it might. Typically, I guess, if you do philosophy, you go into law or finance, so it sort of makes sense. But there are a number of philosophers I really admire. One of my favorites would be Descartes, probably, the notion of skepticism. It's sort of a rabbit hole. It's kind of hard to pull yourself out of it. Basically, the brain and the VAT theory, pulling yourself out of that. But yeah, I really like epistemology, questioning what it is to have knowledge. So, Descartes was one of my gateways to that. Do you think everything is knowable? Like, we humans can know fully the objective reality? Oh, definitely not. No, I mean, reality is very much processed through your own subjective lens. So, how much do you think do we understand about this world? Because a lot of your ideas, a lot of things we might talk about today are kind of trying to figure out human civilization, how human behavior works at scale, all those kinds of things. That kind of assumes that we have it or we're able to somehow figure most of it out, right? So, when you step way back, how much of it have we really figured out? Well, I think that's the conceit of economics is thinking that you can model human behavior in these unbelievably complex systems. And then I think that's the modern critique of economics, like the sort of Talebian critique, is that you can't have true knowledge and they're much less predictable than we think they are. And we behave according to our accumulated assumptions, and we're using tiny sort of data sets trained on the last 50, 100 years, and they turn out to be horribly askew. And that's when we have our gray swans and our black swans. So, reality is much less knowable than we think side of things. But it is nice to have very concrete things like Bitcoin, that's for sure. Oh, so you think, so most of it is shaky ground, but there are some things, there's like islands of sturdiness. Yeah. That's a good way to put it. Yeah. I mean, look at the dollar system, not to pivot this into the dollar right away, but the dollar is like... That's the shaky ground. Who truly understands the dollar system? I mean, the totality of it, the Eurodollar system, the way that monetary policy interacts with the economy, is monetary issuance inflationary? What's the relationship between unemployment and inflation? Even policymakers don't understand these things. Economists don't seem to understand them. What is inflation? How do you define inflation? None of these things are really known or knowable. So, a lot of people kind of make a claim that there's a lot of manipulation possible with the dollar, with those currencies. If you couple that with the fact that people don't understand it, and yet there's claims that it's being manipulated by centralized power, how do you bring those two ideas together? If no one understands it, how can you manipulate it? I think what we don't understand are the long-term consequences of our structures. So, like the Fed's mandate to target unemployment and steady exchange rates or low inflation. You know, what we don't understand is, okay, what is the result of doing that continuously for 40 years? What is the net effect of that? What is the consequence of the long-term accumulation of debt and, you know, basement interest rates? What is the net effect of that on society? We might understand there's much short-term features of the system, but I think it's the longer-term features we don't understand. Do you think there's like malevolent people, people that don't have good intent in central banks, like in the system? You know, when you have centralized power in any forms, it's susceptible to somebody hacking the system, taking the power, and in the shadows, this is where conspiracy theories come in, right? In the shadows, be able to, you know, act out things that have a lot of negative impacts on a large percent of the population in greedy self-interest. Do you think there's people like that, or do you think fundamentally most people are good, even those associated with the sort of central banking? I mean, I don't villainize those people. I think everyone is the hero of their own story, right? So, they all believe that their force are good in the world, you have to. Are there any true villains? I don't think so. I think they get socialized into a world where they believe their particular skills and their mandate is what they should be doing. I think they might be presumptuous or arrogant in some cases. And I think it's more of a systemic issue where you have a small handful of very homogenous types of people with PhDs from the same institutions that are brought up in the same cultural context that, you know, set policy and wield a tremendous amount of control over society. And I think they have this notion that you can tinker society, you can play with a few key variables and tinker society into a state that is desirable or good. And that's what they're trying to do. And I think the consequences of that can be pretty bad. But no, I don't think it's born out of malevolence. There's an interesting idea. I think Michael Malice brought it up as a test whether you're on the left or the right. The question he asks, which is, do you think some people are better than others? If you say yes, he claims you're on the right. If you start answering, if you start like saying a lot of things like you're on the left. So if you start explaining yourself, well, equivocating, yeah, it's a good term for it. I was really, so in this test, I suppose I would be on the left because I'm uncomfortable with the idea that some people are better than others as a basic feeling, as a starting point in the way you think about the world. Because as we're talking about, everybody's a hero of their own story. When you start to think some people are better than others, as a starting axiom, it's like a slippery slope to where you think you're way better than others. And then you start to like, basically, it's okay to take advantage of a large percent of the population for the greater good. And then you go into Stalin mode and Hitler mode, where it's okay to murder a large part of the population for the greater good. So it's this very dangerous, slippery slope of my mind. So I try to not, yeah, I was always uncomfortable with that kind of test or even that kind of thought. And yes, the same applies in suppose in government, in central banking is, if you think some people are better than others, applying your idea of what is good can have large scale detrimental effects. Of course. Yeah. I'm glad you didn't pose me the question. I mean, I think it maybe not the left-right axiom isn't, the disjunction isn't the way I would sort of put it. But to me, it's just, if you reason in a consequentialist way, that lends itself to authoritarianism, whereby you think you can shape society and only you can shape society in a positive direction according to your specific objectives. So let's step onto the land of sturdiness that is Bitcoin. What is Bitcoin? And in your view, what are the principles, the philosophical foundations of Bitcoin? Well, Bitcoin, the term I think refers to two things specifically. So one is the protocol for conveying value through a communications channel. So just a set of rules that we collectively opt into in order to transact online or just at a distance. And then the other thing is the name of the asset, the sort of monetary unit which circulates within the system. And that always confused people a lot because it's like, well, you've got uppercase Bitcoin, lowercase Bitcoin. Why didn't Satoshi just give them different names? Like in Ethereum, you've got Ethereum, the system, and then Ether. Although people don't really talk about Ether very much, but they chose to distinguish them. In Bitcoin, for whatever reason, they're not distinct. So the two Bitcoins get co-mingled all the time in the explanations. Did you find that's a problem that confuses things? I mean, what's really a distinction between the protocol and the currency? Well, they are sometimes distinguished practically. Like you can transact with Bitcoin outside of the Bitcoin protocol, for instance. So you can transact with Bitcoin on Ethereum or I have Bitcoin on an open dime here. This would be a Bitcoin transaction. It wouldn't settle on the Bitcoin network. Do you mind explaining what you have on the table before us? Yeah. So I brought you some presents. That's awesome. This isn't a bribe. This is just a proof of concept. So this is basically a Bitcoin bearer instrument. So I put a hundred bucks of Bitcoin on here. And to spend it, you have to basically physically destroy part of the device. You have to poke a hole and poke off one of the little transistors on this. So it can only be spent once. And you can't extract the private key from this device. So the private key was generated on device, always stays on the device. So what it means without breaking off a small part. So this basically is a way to physically instantiate Bitcoin. So it's kind of clever. It's basically gold. Yeah, effectively. So here. Thank you so much. This one's limited edition. It's orange. So what is it called again? OpenDime. The point is, if you wanted to settle a Bitcoin transaction instantly, the kind of same way that a cash transaction is instant final settlement, right? You would do it with a device like this. So if I was buying a house from you, you might prefer to do it with a physical bearer instrument as opposed to waiting for a confirmation on the Bitcoin blockchain. So the moment I hand that over to you, goes in your possession, you're the owner. There's no way for me to have retained the private key. I could have created a Bitcoin paper wallet and given that to you, but you have no assurance that I didn't copy down the key elsewhere. So this solves that problem. So this is a physical instantiation of the Bitcoin transaction outside the Bitcoin protocol. That's right. So you're transacting the currency outside of the protocol. So it's analog Bitcoin. We're running it analog, which I always like because Bitcoin is this immaterial thing. And so it's nice to have physical totems. How much does it cost to manufacture this, do you know? Like 15 bucks or something. So this is just kind of almost like a philosophical statement versus something that's scalable for use. The point of Bitcoin is to be in the digital space, right? But this shows like Bitcoin can be anywhere. It's useful for gifts. I don't know if it would be a suitable foundation for a physical Bitcoin economy. In theory, these would be like cash like instruments that you could use to transact. Well, I just mean post-apocalypse. Yeah, yeah. You still need to plug it into your laptop to actually verify that there's coins on there. So you still need the internet. So I have to take your word for how much money is on here. No, I mean, you can plug it into your laptop and check. But to transact, to extract Bitcoin from this, I need to break. Yeah, you have to poke a hole through the little hole and that renders it spendable. So that's protection against you spending it and then representing that it's still loaded. That's fascinating. Yeah. So the other thing I brought here, basically dice, 12 sided. They don't have any Bitcoin on them. So they just have a bunch of different critiques of Bitcoin on each side. We'll go through them then. This is awesome. I don't know if we have time to do all 11 because there's one with my phone's logo on it. But it's just basically a tongue in cheek joke that the critiques of Bitcoin are so formulaic at this point that you can just put them on dice. It's silly. Well, some of them might be topics for interesting conversations. Oh, yeah. We can even arrange the conversation that way. You can roll the dice and see what you get. All right. But first, the philosophical foundations of Bitcoin, like how do you see Bitcoin outside of just a basic protocol and a basic currency? It seems to be, like you said, it seems like sturdy ground. So what do you mean by that? Yeah. So it's not just any protocol for moving value around. It's not just any currency. It's got specific rules and values that are embedded in it. And this is an important point, is that Bitcoin is the encoding of certain values, which are often misunderstood or not acknowledged necessarily. And so it's sort of impregnated with values. And what they are specifically is a topic of debate. And there have been civil wars fought over the values inherent in Bitcoin. One of them was, should Bitcoin be this cheap, scalable, the base layer, low fee payment system with an emphasis on P2P payments? Or should it be more of this gold-like digital commodity that would eventually settle infrequently and mainly between institutions? So that's fundamentally a conflict of visions. So keep in mind that this is just one man's opinion. I don't speak for Bitcoin. So I would say the key number one value that's embedded in Bitcoin is the notion of non- discretionary monetary policy. So algorithmic monetary policy as opposed to human-based monetary policy. Satoshi was very clear about that. Bitcoin is an alternative to modern central banking, where you have constant tweaking, constant intervention, which Satoshi felt leads to credit bubbles and so on. So Bitcoin proposes a completely non-discretionary monetary policy, sort of decays over time. 50% of the coins were issued in the first four years, and then the next 25% in the next four years, then 12.5% in the next four years, until you get to 21 million units. And none of those numbers really matter. It could have been 25 million units, and it could have been a more aggressive slope or a more gradual slope. But what matters is that this schedule was proposed even before the code was public. The schedule was proposed, and then we all collectively agreed to stick to it. And that is kind of a first for a monetary system. I mean, gold kind of has that property, right? Because the supply of gold above ground only really increases at 1% to 2% a year. So it's sort of inhuman, which is a good feature, right? You don't want to give humans that much control over it. Bitcoin is a much more fastidious approach to that. It really is super concrete about what the supply schedule is, and the fact, crucially, that it can't change. So we can't have a bailout of debtors. Let's say a lot of people had debts denominated in Bitcoin, and we needed loose, accommodative monetary policy to bail them out. That's not possible. We couldn't have a jubilee denominated in Bitcoin, because the social contract we've all had, that we've all bought into and committed to, is that it's non-discretionary. So that's sort of one of the first things. And I think ultimately that comes back to basically a strong respect for property rights. Because if we were to have unanticipated inflation, let's say a really charismatic leader somehow commandeered Bitcoin and convinced everyone that we should have 30 million units and not 21 million, that would basically be dilutive on everybody that held Bitcoin and had opted into the 21 million set of coins. An additional 9 million unanticipated would have a dilutive effect on everyone else, and that would be a covert way of effectively stealing their purchasing power through inflation. Is that possible, that kind of thing? I mean, what's the mechanism of Bitcoin that resists that kind of charismatic leader? Well, we've had people that have had a lot of influence in Bitcoin in the past, and they've tried to make changes to the protocol. Not as dramatic as that, but Bitcoiners have generally resisted those individuals, institutions. And they, you know, Bitcoiners have a good track record of sort of staying true to those core values. So that, you know, you mentioned values and like sticking to the monetary thing, but there's bigger values. There's almost like psychological values that are instilled in Bitcoin. You make a point that Bitcoin for many is a vessel, quote, for their expectations, hopes, and dreams. Can the Bitcoin protocol support this kind of complexity of the human condition? So like, there's ideas of freedom that seem to be spoken about. There's a sort of ideas of, I mean, even love. I mean, some people kind of use it as a meme, like, you know, Bitcoin is love or something like that, you know, mostly to troll me because I talk about love all the time. But, you know, these bigger ideas than just the exchange of currencies. PBR Yeah, I mean, Bitcoin itself is very simple, I would say, like ultimately, it doesn't, you know, pretend to do very much. It really just settles transactions. But people do superimpose their own views on it, for sure. And Bitcoin's qualities give rise to these perceptions of it having censorship resistance or giving you transactional freedom or a measure of transactional privacy. So because anyone can operate a node and join the consensus process, and because mining is a competitive free market process, that means that it's likely that you can't be censored by the miners. So that means you have transactional freedom. So you have these computer science, technical features of the system that cause it to have these political qualities, which is, it's very hard or impossible to censor a specific individual. So it's interesting to see that flow. But so that's one of the core values, for sure, is the censorship resistance. Then you have the fact that it's a cryptographic based system. And you can hold value in your brain by memorizing 12 words, for instance, that gives it seizure resistance, which is, again, a political concept. If you wanted to desert your jurisdiction with your wealth intact in your brain, that cryptographic feature of the system, the fact that it's built on public key cryptography, and that you can encode a Bitcoin private key in 12 words, that gives it this political salience that you're now empowered relative to a despot, basically. Yeah, I mean, there's so many beautiful concepts behind cryptocurrency, behind Bitcoin, that stand for sort of freedom. Some of the basic things at the founding of this country. The one thing I don't like personally behind Bitcoin and cryptocurrencies is that money's involved. And it's like people's life savings sometimes are involved. So there is naturally a kind of fear, a self preservation, instinctual kind of dogmatic thing that comes in, where you're not the best of human nature. You stop being a George Washington, and you lose touch of the foundational principles, which I think are beautiful, just like the founding principles of this country. So that's just like... So I like staying on the level of the philosophy versus the level of like, all my money is invested in Bitcoin. And that becomes very tricky territory to have principal discussions about ideas. It's an interesting tension. Well, I try to stay balanced despite being very exposed to Bitcoin. Let me ask the ridiculous question, just in case. Who is Satoshi Nakamoto? And is it you? We don't know. It's probably not me because I was like 17 when Satoshi invented Bitcoin. 16. So unlikely. And also not really a programmer. So there's a lot of theories, but honestly, it's one of the greatest mysteries of all time. Because even Bitcoiners that have been around since day one, really, people that were around before Bitcoin came out, they're on the mailing list, they were active in the cypherpunk community. You ask them and they sincerely will not know. And they may not even have a good guess as to who Satoshi is. Is it important to know? Or is it like actually important not to know? Do you think that's a feature or bug that you don't know? Some people don't like the uncertainty, especially folks on Wall Street, they really want to know. And if you read the Coinbase S1, their disclosure pre-IPO, that's a risk factor. That Satoshi could come back. So the risk management crowd wants to know, because they want to know if maybe Satoshi had undesirable political opinions or something that would forever taint the project. Do you think they were just trolling with Satoshi's identity being a risk factor? Or was there an actual meeting and a discussion of that being a risk factor? I think in the risk factor sections of the prospectus, it's really just the lawyers doing a total brain dump to cover absolutely everything they can think of. So it's just lawyers, it's not like... I think Elon was somewhere in the legal documents for SpaceX mentioned that Earth governments have no jurisdiction on Mars. They threw that in there. And it feels like, yeah, that could be lawyers, but it could also just be Elon trolling. Yeah. So I wonder if it's the Coinbase folks trolling or if it's lawyers. I hope it's the trolling, not the lawyers. The Coinbase leadership, they're not as big trolls as Elon is. But it's a risk for sure from their perspective, because let's say Satoshi returned, doesn't seem likely. And let's say they decided to spend all their coins, which also seems very unlikely. That's rumored to be, or estimates have it, at 1 to 1.2 million Bitcoin, which is like 50, $60 billion worth. So some people consider that to be a risk. You think it's... This is almost like a topic of leadership. It doesn't feel like anybody, any one person speaks for Bitcoin. There's not even like prominent figures. Like you have for like Ethereum, you have Vitalik Buterin. There's a lot of like top minds talking about it like yourself, but it's not like one or two. Do you think again, is that a feature or a bug? Like, do you think for effective, for Bitcoin to effectively have a role in society that like is as large or larger than the dollar, there needs to be like leadership that represents it, almost like democratic kind of thing? Well, that's a real counterintuitive point, because most Bitcoiners, including myself, would say, no, the lack of leadership is a great quality to have. Because if you have a charismatic leader and a foundation or corporation that controls it, maybe they can control the features of the protocol, and maybe they can expropriate holders of the coin or, you know, build in an endowment that pays them off and gives them privileged access to the units of the coin, for instance. So, you know, we call people that have privileged access to the money spigot, Cantillon insiders, which is there's this economist that pointed out that as, you know, I think Richard Cantillon, that as money enters the economy, it has an uneven flow. Right? And so you see this in last decade or so before that too, the consequence of money printing in this country is people that own financial assets made a lot of money and people that didn't, didn't. So you see that Cantillon insider, Cantillon outsider effect. And it's the same with a cryptocurrency. In many other alternative cryptocurrencies that do have these corporate entities, or these leaders and CEOs, they're able to make specific decisions regarding the protocol and the currency of the asset, the benefit themselves, their cronies, etc. And that's not a good feature to have. I mean, it does grant you, you know, the ability to orchestrate decisions in a faster and more efficient way. But long term, what you're trying to optimize for, if you're creating a money is monetary credibility and soundness. So you don't really want it changing all that often. And you don't want to have the appearance of, you know, these elites that are engaging in rent seeking or anything like that. So there's definitely people that are influential in Bitcoin. There's core developers that people listen to because it's, I would say, meritocracy largely. And they're sort of self-appointed high priests of the protocol. I write a lot about Bitcoin, people listen to me, but it's a completely free market of ideas, right? I don't have any authority within Bitcoin whatsoever. I'm just a scribbler, you know? You're just a scribbler. Just a scribbler. Just a scribbler. Well, so was Aristotle and Socrates and Nietzsche. Okay. At the high level, technically, how does Bitcoin work? Is there interesting things you could say? Like, what are miners? What are nodes, full nodes? What are blocks? What's proof of work? Is there a nice way to wrap up a clean explanation of the protocol? Oh man, that could be another five hours. Is there interesting, because I'd love to talk to you about block size wars and sort of the politics, psychology, the principles around that. But sort of building up to that, it'd be nice to talk about how the thing works. That's fair. I mean, and the block size wars are a really fascinating discussion of how governance debates intersect with technical features. So I guess we can, yeah, so basically at the highest possible level, Bitcoin is a globally shared, it's really a replicated ledger that any participant that wants to be an equal peer on that ledger, they want to maintain that ledger and they want to stay up to date with the global state of the ledger. And really any monetary system is just a ledger with physical cash. We benefit from the physical instantiation of the money. So the physics is the ledger. The physics is the ledger, right? Same with gold, right? You can't just produce new units of gold. So we trust that gold atoms are hard to create, although not impossible, right? You could fire a bunch of protons and whatever is the adjacent metal and create gold atoms would be expensive. And the same with dollars, we trust that it's hard to counterfeit a dollar. So we trust the physical analog world to help maintain the state of that ledger with digital money, like the money in your bank account, your checking account. We basically trust our institutions or banking institutions to keep a faithful record. And then ultimately, we trust the central bank to administer that system. So there's kind of a handful of nodes. In Bitcoin, we trust that the economic incentives of the system are carefully poised, basically. So we trust that the free market mining competition will lead to the miners assembling transactions into blocks in a faithful and correct way, and that we are going to converge on a global state of the ledger continuously, which updates every 10 minutes or so with some variance. And then the miners aren't the sole entities that control the system. To really participate, if you are a merchant and you're accepting Bitcoin, you really want to run your own full node and check the whole history of transactions, sort of something like, I want to say five to 600 million transactions that have ever occurred on Bitcoin. LUIS So a full node contains all the transactions ever transacted on the Bitcoin blockchain, and that's, I saw it's like 200 gigs or something like that. PATRICK Like 350, something like that. It's doable on a regular consumer laptop, and that is going to be really key later on in the discussion. LUIS Sure. PATRICK But so, you know, that's really the ultimate trust models. First of all, we trust that the miners that assemble transactions into blocks, and they are the archivists, you know, they inscribe those transactions onto the ledger, and they have an economic incentive to sort of behave correctly because they're getting paid in no units of Bitcoin. That's part of it. But then really, you are also, you're not fully trusting them. You're actually, if you want to run a node, you replay every single transaction in the history of Bitcoin from the beginning to the current day, and you arrive at the present state that way. So you don't really have to trust too many people or entities. You can validate the correctness of that all the rules have been followed, that all the Bitcoins that were created were done so in the valid way, that the inflation rate was adhered to, and that there's no covert inflation. You know, that if you're spending 50 units of Bitcoin, you had that Bitcoin to spend in the first place. So it's sort of delicately poised between node operators who, you know, engage in this validity checking, kind of anti-counterfeiting checking, and then also the miners, which are an industrial entity, and they basically produce block space and assemble transactions into blocks. And everybody, so the miners are incentivized to not mess with the system because they're gaining value from the system. So if they mess with it, it's going to decrease the value of their physical work investment. Yeah, so they have to incur real physical cost to produce a block, right? So right now you get 6.25 Bitcoins in a block at a minimum, and then maybe some fees as well. How hard is it to produce a block now? Well, challenging. I mean, you need 6.25 Bitcoins, and a Bitcoin's worth $55,000 or so. So it's probably going to cost you about that amount to produce it, because it's a free market competition, and miners have very thin margins. So it's like if I auction off a dollar, you would pay up to 99 cents to buy that dollar from me. It's exactly what happens with miners. They're, you know, basically competing for the right to obtain new units of money. So logically speaking, they would pay up to the value of that money in order to earn it. And for people who are not familiar, the process of mining is solving a difficult cryptographic problem. That's a computational problem. I would say it's not like, people sometimes represent it as like a really challenging puzzle. Like the individual puzzle is very simple. Like you can do it with pen and paper if you wanted, you know, like SHA-256. It's just that you're searching through the big mathematical space to find the needle in the haystack. You're just doing lots of iterations of a simple puzzle. It's just brute force, hence like the stability of the whole idea of the proof of work. If there was a shortcut, it wouldn't work. Exactly. So let's hope nobody solves SHA-256. Yeah, there's a lot of discussions from the quantum computing space, but everybody I talk to, all my colleagues that work in quantum computers say that we're quite a long way away from that being an issue in cryptography and certainly an issue in cryptocurrency. That should have been one of the sides on these dice. It should have been quantum. Quantum. Because I don't think it is. I forgot to put it on this edition. People should check out Scott Aronson. There's a lot of people that are kind of selling quantum snake oil. So you should be very careful. I think it is a really exciting space that might change the world in the next decade or a couple hundred years, especially for simulating quantum mechanical systems. But in quantum machine learning, people should check out TensorFlow Quantum. It's a nice way to sort of educate yourself about the space. And actually, if you're pragmatically minded to, you know, through software engineering, explore how you simulate quantum circuits, how you run machine learning on those quantum circuits. The main point that Scott makes, Scott Aronson, people should check out his blog too, is that like there's not yet a single machine learning application that doesn't do almost as well on a classical computer. So it doesn't, like, yes, the dream is somehow quantum computers will change the nature of artificial intelligence, but there's yet to be an actual algorithm that, or a problem set or a data set where that would be the case. So skepticism is good in this space. Anyway, that said, so you kind of explained how Bitcoin works. You also wrote a blog post recently giving a shout out to the new book, The Block Size Wars. What is a block size? What are the block size wars? It's history, it's importance, it's philosophical foundations. Yeah, I mean, Bitcoin at this point, we have our own civil wars, if you're wondering about how politically intense it gets. It's currently not hot, it's cold. It's, oh yeah, we're in a detente right now. There's no tanks or missiles, at least not yet, hopefully. It can get a little violent, I guess. I think one of the Bitcoin core developers, or one of the participants in the war got swatted at one point. What's swatted means? When someone does a fake phone call saying that you're holding someone hostage at your house, and the SWAT team goes, it's pretty scary. Oh, wow. Internet warfare tactic, yeah. But the block size war, I would say effectively ended, although we're definitely going to have more civil wars in Bitcoin for sure. But basically, the core argument was a technical one on its surface, but a very deep political one at its core. The technical question is, how many megabytes should be in each successive block? So, Satoshi basically installed a limit of one megabyte per block. So, we should backtrack. There was no limit in the beginning. And it seems like Satoshi, what is this, 2000? The war started in what, 2017 or something like that? I don't know when the- 2015 was when the battle cry began. What was the first battle in the civil war? I don't remember. But Satoshi, I don't know if you can comment on it. Why did Satoshi set the limit to one megabyte all of a sudden, almost secretively? And in the beginning, there was no limit whatsoever. Yeah, we can get into, and people have spent thousands of hours pouring over Satoshi's writings to find which side Satoshi was on. And you can find, like any textual exegesis, you can find evidence for either side. But yeah, I mean, effectively, when Bitcoin was launched, there was a block size. Because if you made a block over a certain size with the first edition of the code, it would have crashed nodes. But then, yeah, in 2010, Satoshi added the one megabyte limit in a covert way with no comments or anything. And that stuck, basically. And then Bitcoin blocks filled up. And people that had been socialized into this vision of Bitcoin as an effectively free transactional network, like why pay a transaction fee if you're not at congestion? If the block isn't full, the miner will mine your transaction for free, right? People that had been brought up in that status quo from 2009 to kind of 2015, they noticed the blocks started to fill up and they're like, okay, well, let's just remove this arbitrary limit, right? What could possibly be the harm? And then a whole other faction said, no, you need to cap the data throughput of the system because if you increase it, it's going to be highly exclusionary. And ultimately, regular folks are not going to be able to run a full node. So there's a fixed frequency of blocks, and so if you want to increase the number of transactions per second, you want to increase the size of the block. So huge blocks allow you to shove in a lot of transactions. Small blocks don't. So that's what you mean by constraining the system. So what's the benefit of a small block size where you can squeeze in only a small number of transactions, and what's the benefit of a huge block size where you can squeeze in a lot of transactions? Well, it really comes down to the way you think about the system. So a lot of people wanted Bitcoin to be Visa scale. So do you have blocks sufficiently large that you could accommodate a Visa level scale of transactions? Which is many orders of magnitude more transactions. That's right. I mean, preposterously larger in terms of data throughput than a Visa scale. And, you know, Bitcoin offers up, or at least it used to, 144 megabytes of space per day, and your average transaction is 350 bytes. So, you know, you could, at a push, do four or five hundred thousand transactions a day, which is not many. So if you wanted to get to Visa scale, you'd have to increase blocks obnoxiously large. The small blockers claim that this would overwhelm the ability of any regular person to ingest that data and stay current at the state of the ledger to replay all those transactions to ensure that the protocol rules were valid. So basically, the small blocker contention is that you eliminate the trustlessness of the system by pushing a ton of data through the system because only one or two industrial heavy duty nodes would ever be able to run the protocol at that point. So, by the way, in the civil war, the two sides, as you're calling them, the small blocker and the big blocker sides. And so that takes us back to the thing that you mentioned that a regular computer could be a node. And with big blocks, that's no longer going to be the case. So just the number of transactions is going to blow up the size of the blockchain that every full node has to store. And so then as opposed to a regular mom and pop type of node, you're going to have to have data centers. So they're going to have to be owned by large organizations. There's going to have to be very few of them. And that's how you centralize the control over this whole operation. So the big blocker, yes, it allows you to be Visa and do a huge number of transactions, but it becomes centralized. And then the small blockers, you cannot actually do kind of merchant style transactions, but you get the decentralized benefit. Well, I don't even think the big block approach would allow you to be Visa, frankly, because there's effectively one node in the Visa network, right? So you don't really need to maintain this peer to peer architecture at all. And the amount of data you'd have to push through the network to reach Visa scale is a really preposterous amount. I mean, and we have now evidence for what happens when you try and scale up as a blockchain and do 10 million transactions a day, which is still not Visa scale, right? You know, I've seen what it's like to operate those nodes and it's not pretty. So there are totally genuine computer science physical limits, because it's a broadcast network. Everyone has to be aware of every transaction. And that model, which gives you the trustlessness, the nice guarantees where everyone's an equal peer on the network, everyone has audited the full history of the transactions, that model falls apart under stress. So the small blocker vision is that ultimately you would scale in a layered approach with the base layer transactions being settlement style transactions and, you know, payments happening at the other layers, basically. Is that universally agreed upon or like to a large degree agreed upon that the small blockers have won in this debate? Well, where would you put the current state of affairs? There was a wave of competing Bitcoin implementations starting in 2015 with Bitcoin XT. Actually, Gavin Anderson, who is the guy that Satoshi handed the reins to when Satoshi left, Gavin supported this large block proposal. And so that didn't achieve consensus. And then there was Bitcoin Unlimited. And then later on, there was a genuine hard fork where the small blockers couldn't or the large blockers couldn't push through their proposals on Bitcoin itself. So they just created a competing version of Bitcoin. So by the way, maybe you can comment on, but sort of hard fork versus a soft fork, a hard fork is when it's not no longer compatible. What's the right way to put it? They can't operate on the same blockchain, the same with the same protocol. Yeah. So there's a few ways to define them. And it's pretty, it gets controversial as well. But one way to define it as a hard fork is a expansion of protocol rules and a soft fork is a shrinking of protocol rules. That's an interesting way to find it. It's not very intuitive. So I don't like that way. Another way is that a hard fork is backwards and compatible, whereas soft fork is in theory, backwards compatible. So in August 2017, basically the large blockers had had enough and they said, we're going to hard fork Bitcoin. We're going to create a clone, an alternative version of Bitcoin, which has a shared history as Bitcoin itself, but you completely fork it and you create a new future. And, but, you know, everybody that had a balance on Bitcoin at the time also had a balance on the alternative coin, Bitcoin Cash. And so that was really... That's what it's called, Bitcoin Cash is the hard fork. That was one of them. There were more actually. I mean... What the heck is Bitcoin Satoshi's vision BSV, Bitcoin SV? So this is all talking about increasing the max, the limit of the block size more and more and more. Yeah. That was one of the changes they wanted to push through. But BSV was a fork of Bitcoin Cash. So hard fork of Bitcoin Cash. Yeah. So, and so now there's multiple big blocker blockchains floating around. It's like... What are your thoughts about them? Well, I was... Because they're pretty popular. Sorry to interrupt. Are they popular? I mean, if you look at the metrics, they're not. And they don't trade. They, I think each trade below 1% of the value of Bitcoin itself. I see. So measuring popularity is like how much they actually... Oh, value, frequency of trade. Oh, no, no. I mean, they do like a fair number of transactions, but there's no way to know that that is genuine or just contrived. So, ultimately the true measure, I think, in my mind is just where the market prices these protocols relative to Bitcoin. Because that's like a prediction market. If Bitcoin Cash was being priced at 50% of Bitcoin, you could say the market has given it a 50% chance of unseating Bitcoin, right? But both Bitcoin Cash and Bitcoin SV, which was a hard fork from Bitcoin Cash itself, are well, I believe at this point, well below 1% of the value of Bitcoin. And in the, so in like the ranking of different cryptocurrencies, what is it? Bitcoin, Ethereum? Is Ethereum in value? Yeah, somewhere. Yeah, somewhere too. And then Bitcoin Cash is the one that, it's in the top five, right? But it's just a fast drop off. You know, I haven't checked lately, but I think it's reached kind of morbidity. You know, it doesn't really have much traction. The blocks aren't full. So the whole value proposition was, you know, we will get all this merchant adoption if we increase the block size. That just didn't materialize. In my view, they had a flawed vision of how adoption works and what blockchain should optimize for. Maybe you get a Bitcoin Cash supporter on the show, they'll give you a different answer. But yeah, full disclosure, you know, I have my sympathies and I think the small blockers, one, that's gurmish for sure. So at this time, there's no merchant adoption and so on. So it's kind of, it's vision, the whole reason for existence, at least for now, hasn't materialized. And so that's an indication as possible that, well, it's a sign that perhaps that's the wrong way to accomplish the scalability. Well, you know, first of all, I think the layered scaling model is definitely, definitely correct. I mean, that's absolutely the way these things have to work, given the constraints of blockchains. What is the layered scaling model? It's really how all payment systems scale, blockchain or otherwise. And I think a lot of people don't understand this, is that there is no equivalent to scaling of the base layer in the regular payment space. That totally doesn't happen. All of them are built on layers. So Visa is like the fifth layer in the payment stack that ultimately depends on these utility scale settlement systems like Fedwire, Chips, ACH, basically interbank settlement systems. So you've got these slow moving but high assurance settlement systems. Fedwire is probably the number one, you know, like when you send a wire that's using the Fedwire system typically. On top of that, you know, you have banks and then you have payment processors, and then you build up these layers and layers and layers. And then you have these fast payments, you know, Venmo, PayPal, credit, debit, Visa, you name it. Those payments are not final when they occur, you know, a credit card transaction will not be final for 90 to 120 days. So you've decoupled the payment, the financial message, and the settlement. Those are distinct concepts. And the settlement happens on a deferred basis. So that's how you get scalability, is you have lots and lots of messages, but that they don't settle for a long time. They might settle on a net basis on an end of day basis. But so that's really how it works. And then you have Fedwire where your average transactions in the millions of dollars, and there's only a few hundred thousand transactions a day. It's sort of an interbank settlement network. So that's my vision for how I think Bitcoin will develop to Bitcoin itself on the base layer is the slow moving high assurance final settlement network where if you're sending money to the other side of the globe to someone you don't trust, where you want that payment to be final in a short period of time, and both counterparties know it's final, then you would use that. But if you wanted to buy coffee, you could do it on a second, you know, second layer. Lightning would be one way. There's a bunch of side chains now. Or you could use, you know, a more centralized solution if you wanted. It's kind of a profound idea that in the space of transactions, when you're buying coffee or buying anything really from a merchant or exchanging goods and all those kinds of things, that most of the time, like basic, honest behavior, human behavior, which it does appear that most of our society is based on the fact that we're all, most of us are honest, is like stuff is not going to go wrong when you do this transaction. And you only need like the base layer, whether it's Bitcoin, whether it's, I forget the terms you use for the credit card version, but you need that just to verify, just to like resolve any disagreements or shady shit. Yeah. And that's a really rare occurrence. So it's okay for that to be handled in this, in a small block debate, handled at a rate that's much, much lower than the rate of the transactions. That's a kind of, that's a really interesting idea that when we spend money, we didn't actually exchange the money most of the time. Yeah. Most of the time you're not getting final settlement when you do a transaction. And oftentimes that causes there's pluses and minuses on the plus side, you have huge efficiency if you use a credit network like Visa, but it's in the name credit, right? Visa is extending you credit, right? They're kind of guaranteeing your reputation to the merchant, but fraud happens all the time, right? There's always fraud because you have this reversibility, right? And so you can engage in fraud against the merchant. If you have a final settlement, there's no possibility for fraud. So that's one reason merchants kind of like accepting Bitcoin, because once you receive an inbound Bitcoin payment and you deliver some good or service, that payment can't be reversed. But frankly, most of the transactions we undertake on a daily basis do not require those strong assurances of final settlement. There's one exception, which is physical cash. With physical cash or the open dime, a cash-like product, you actually are getting final settlement. But most online banking transactions, most P2P, digital wallet transactions in the dollar system, they're not really final at all. You mentioned Lightning, Lightning Network. What is it, what are your thoughts on it, and what are your thoughts about any kind of alternatives? So Lightning is one potential payment solution built on top of Bitcoin, where you have different assurances, different transactional assurances, but ultimately it's very proximate to the base layer. So if something goes wrong, you can always basically settle to the base layer. Just layer two. Yeah, layer two, you could say. And basically the intuition is, it's kind of like opening a bar tab. So you go to the bar and you might drink a dozen beers over the course of the night, maybe half a dozen. And, well, I guess nobody goes to the bar these days, but let's say you did. Yeah. You open a tab, and at the end of the night you settle up once. You're not necessarily paying each time you get another beer. So it's the same idea. You're opening a channel, an ongoing relationship with your counterparty. And so Lightning has you open a channel with a counterparty, and you're sort of sending back and forth these cryptographic commitments saying, you know, I agree to send you some Bitcoin, but you don't necessarily settle each time you make a transaction. So you do hundreds of thousands of transactions in a channel. The other thing Lightning proposes is saying, okay, well, now that we have channels established, what if we interlocked a number of channels together? So if you and I have a channel, and me and my buddy have a channel, my buddy can now pay you because you have a relationship through me, basically. And so Lightning is this network, this overlay network that sits on top of Bitcoin and allows people to transact in a much faster and less frictional way without the need for Bitcoin's kind of slow periodic settlement, assuming that everything sort of goes well. Do you see any downsides to this? Like, have you seen flaws in the whole system from a security perspective, from a scaling perspective, any of that? Or is Lightning working well? It works. I use it. When I initially sold those dice, I sold them on Lightning. I was one of the first merchants to use Lightning back in the day, the first edition of the dice. So people could buy these dice somewhere? Well, they used to be able to. I haven't made a new edition recently. They're very scarce and very special. They're like physical NFTs. Physical NFTs? Yeah. I mean, the flaw with Lightning is really that you – and this can be remediated in a number of ways – but you have to sort of pre-fund these channels. So it's a weird concept to have to inject liquidity into a channel in order to accept a payment. So I'm sure those user experience problems can be solved, but it's still in a state of relative immaturity. So we'll see. In terms of other ideas that are sidechains or soft forks of Bitcoin, you've mentioned something about Schnorr and Taproot. What are your thoughts about this update to Bitcoin in terms of its promise to improve privacy and scaling and so on? And what other things are you interested, excited about in terms of the development of Bitcoin? Well, Schnorr and Taproot, that's the first new protocol upgrade since Segwit in 2017, which was what laid the groundwork for Lightning to be developed, basically. And Schnorr and Taproot is really the first protocol change in three, almost four years now. So we're very excited about it. Is there something interesting to say technically about what are the things that's actually going to improve? And maybe on the politics side, bringing a protocol change on Bitcoin, what does that actually involve? Yeah, I mean, it's a huge deal because the last time we tried to make a change to the protocol, we had a whole civil war over it. And it was incredibly difficult to get Segwit activated in 2017. And it took all this brinksmanship and threats and all these campaigns. And it was this whole thing. Luckily, I think things have quieted down and there's much more consensus that Schnorr and Taproot is a good change to Bitcoin and everyone generally supports it. But everyone kind of has PTSD over the last time when we tried to change Bitcoin. And so we're sort of really dithering over how we actually want to implement it. So it's taking forever because we're trying to set the protocol for how do you change Bitcoin itself. And all of our assumptions went out the window last time. So we're trying to reset and decide what is a legitimate way to institute a change to Bitcoin. So that's actually the big question right now. It's not should we implement these changes? We basically all agree that we should. It's a meta question is what's the valid way to implement new changes to Bitcoin? What's a way that is scalable in the long term and will last and people will consider credible, even if this one isn't controversial at all? So that's where we're at. We're basically debating over how do we implement this change that we all want to get a feeling of how slow Bitcoin governance is and how deliberate it is. Everybody collectively wants the change, but we haven't fully agreed on how we're going to put it into Bitcoin. So it's a classic sort of Bitcoin situation. But what it is, is I mean, Schnorr is an alternative signature scheme. I think it was encumbered by a patent and it had only just been unencumbered when Satoshi created Bitcoin. I believe it's a better signature scheme than elliptic curves, which is what then ECDSA, which is what Bitcoin uses. And so it's been long enough that we now trust it, you know, kind of in cryptography. It's meant to be Lindi, you know, it's sort of you want to test it over time and then it's considered safe to use. So Schnorr has been around for long enough that we've decided to rip out ECDSA and insert Schnorr, which is just a different signature scheme, which is more efficient and it has better properties. Like if you want to do a multi signature transaction where many people collectively sign in order to permission a spend, that would be more efficient in a bytes sense than ECDSA, for instance. So it's pretty incremental. And then Taproot is all about having transactional conditions that are sort of withheld from final entry onto the blockchain. So it's kind of a way to have more private conditional transactions on Bitcoin. So both of them, I would say, are incremental changes. Is this an over exaggeration that Schnorr Taproot might improve privacy and scaling, which is like at the high level things that people mention? Is that just like a dramatic way of trying to frame what's fundamentally an incremental improvement? Yes, but incremental is the word, right? It's not, we're not going to get an order of magnitude enhancement to either privacy or scaling, but we will get a considerable enhancement. But privacy and scaling are actually two sides of the same coin, because you get more transactional privacy by removing data from the ledger so that there's less metadata for people to surveil and analyze. And that's also how you scale, by compressing and being really space efficient with transactions. And the more parsimonious you are, the more economically dense each byte that everyone has to retain on the ledger is. And so those are very closely allied concepts. So do you mind if we go through some potential criticisms of Bitcoin? Totally. I spent the last five years tackling these every day. Are the dice the same? Those two are the same, yeah. There are three editions. So let's go with the dice. What do we got? Silk Road. What does that mean? Silk Road, classic. Classic situation. So I mean, that was the Darknet marketplace set up by Ross Ulbricht in the early days of Bitcoin. That's one of the first killer apps for Bitcoin was being the payments network behind this Darknet marketplace, where you'd go to buy drugs and things. And so that became associated with Bitcoin, if you remember the press coverage from back then. But over time that faded and it became less of a critique. But so like the critique is that Bitcoin is something you would use for illegal activity, for drugs, for crimes, all those kinds of things, as opposed to any kind of legitimate transactions and merchant transactions. And today Bitcoin settles $10 billion a day and the vast, vast majority of it is completely legitimate. It's just a useful alternative system. But back then a huge fraction of all Bitcoin transactions were related to the basically illicit marketplaces. And if you're just tuning in, this incredible tall-sided guy has 11 common criticisms of Bitcoin that Nick, in a genius way, has put together. Maybe you could do a couple more. Oh, it was Satoshi something. Satoshi coins. Satoshi coins. We touched on that early in the episode. What if Satoshi returns and sells all of their coins? So we don't know for sure how many coins Satoshi actually mined or produced, because there's a degree of probabilistic analysis that you would do. There's a few thousand blocks that were mined by what we think is a single entity in sort of 2009. And so if you add them all up, you get to about a million. So people think that Satoshi mined a million coins, and then they're worried that Satoshi would return and market sell all the coins, thus crushing the price of Bitcoin. So looking at some of these, no CEO, I think we touched on that. We do, we see. We've already hit on the dice. No merchants. That's no longer true. We've already talked about that, yeah. There's a scalability one, and I think that one has addressed the idea that you're mentioning with the block size debates and the lightning network that by adding extra layers on top, you can achieve scalability. That's my vision. That's my theory. And you can do it in a permissionless and a permissioned way. Like Coinbase is a big Bitcoin exchange. They provide scalability. They're a financial institution. And you can settle up internally on their own database and then periodically settle to Bitcoin. So they do something like the lighting network internally, something like this, some kind of mechanism. Well, honestly, I'm not sure exactly how it works. They might have that built in. But just generally speaking, institutional scaling is a model for scaling, right? Where you could have banks holding Bitcoin, and they issue notes against Bitcoin, and those are your payments, and then the base layer is the settlement layer. I think that's what you're getting with the boiling oceans, is this is like the impact on weather, I suppose. On the environment. On the environment. So that is a concern that people have in terms of like the proof of work requires that there's a lot of computational resources being used, and that requires a lot of energy and some large percentage of the world's energy is used to mine Bitcoin. What's, how would you respond to that criticism? Yeah, I mean, that's been the loudest critique of Bitcoin this year in the press. This year, really? Yeah. So, I mean, it's not like a new criticism, but Bitcoin is consuming more energy than ever. So as the price rises, the electricity consumption rises. And so we've heard renewed, you know, bellyaching over this, for sure. I mean, it's, if you don't believe that Bitcoin is useful, then you're inclined to think that all the energy consumption is a waste. So that's, you know, it's something that's sort of unrebuttable if you fundamentally contest the validity of the Bitcoin system. So if Bitcoin is like a thing that will take over, will become like the main mechanism of financial transactions or transactions period in the world, then you say, well, the cost of energy use is actually quite low relative to the benefit it provides. If you think it's not going to be, if it's just a volatile way to make a little money in the short term, then you see the energy use as really wasteful. That's totally spurious. Yeah. Yeah. So. So then there's no really response, I suppose. That's so I can totally, you know, get into the details of Bitcoin's energy mix and things like that, but that's like at a high level, what the debate is. It's this normative question, like, does Bitcoin have an entitlement to consume any of the world's resources? And that's actually where the debate should end much of the time, because a lot of people fundamentally dispute the validity or usefulness of Bitcoin as a system. And so, of course, they're going to consider the energy usage illegitimate. Now, there's a lot of mitigating factors if you think that Bitcoin is potentially a useful system, which is Bitcoin consumes energy in a very peculiar way, which virtually no other industry does, which is that Bitcoin is a geography independent buyer of energy, which is not how we humans typically consume energy. Like we need energy to be produced near to population centers, and we need it to be produced at the, you know, corresponding to the peaks and troughs of our consumption, right? Because we have to 100% match the demand and the supply at all times, right? Otherwise, we have blackouts. So Bitcoin doesn't care about any of that. It just buys energy on a constant basis. And so it's, you know, indifferent to where it's being produced. And so the consequence of all that is that Bitcoin will buy energy that's otherwise being wasted, basically. So it will buy so-called stranded energy assets that would not make it to a population center. And in fact, most energy produced ultimately does not sort of make it to, you know, your socket in your wall. And so this is why so much Bitcoin is mined in China, for instance. It's not because, you know, Chinese industrialists had a special affinity for Bitcoin. It's because the Chinese grid had a massive overabundance of energy, and particularly in four provinces, Sichuan, Yunnan, Inner Mongolia, and Xinjiang. So in those four provinces, those are all pretty distant from major population centers. So because of that, you can't really transport the energy that easily. And so huge amounts of energy are curtailed or basically wasted in all those provinces. And so miners set up shop there because they could mine Bitcoin with the excess energy. They could monetize this thing that otherwise was going to go to waste. So, you know, there's things like that, which, you know, I think mitigate the reality. Bitcoin is not really rival with our consumption of electricity. It's not depriving anyone of electricity. It's mostly these stranded assets that are going into supporting the Bitcoin network. So maybe let's do a last one since you mentioned China. It says China control. So if so much mining is happening in China, how do we prevent nation states from controlling much of Bitcoin? Yeah, that's the flip side of a large portion of the blocks being mined in China due to this energy feature, which I discussed, which is that there's a lot of Chinese miners for sure. Now, the question ultimately is what degree of control do miners have over the Bitcoin system? Right. And that was part of the block size debate. I mean, the miners there when we implemented segregated witness in 2017, the miners just didn't want to do it. Eventually, the users, the regular folks running nodes rebelled and basically said, look, we're going to implement this whether or not you do it. And it was a threat to the value of Bitcoin because if this threat had gone through, it could have split Bitcoin and it would have been really messy. So the miners sort of capitulated. So I think the current consensus is that miners do not have unilateral control over Bitcoin and that governance is more poised between people that run nodes, developers and miners. It's sort of a triumvirate where neither of them has total control. So that's my current model for controlling Bitcoin. I think if you asked a miner, they would tell you they didn't feel that they had sort of unilateral control over Bitcoin either. Almost as a thought experiment, can I ask you to think about if some of your predictions some of your analysis, some of your understanding of Bitcoin is wrong in the following sense where it will not have the impact that you have a vision for it, that it will not have the scale of impact and perhaps in terms of value will go to zero to something very low and other cryptocurrency or other financial systems will overtake it. What would be the reason for that in your mind? Like why might you be wrong? If you look back at it in the future, what did you not understand about Bitcoin that will result in that? Yeah, that's a great question. I think for that to happen, one of two things would have to obtain, one of two things would have to happen for Bitcoin to just be irrelevant basically. Either central banks totally clean up their act and stop engaging in rampant money printing, which I don't expect that to happen anytime soon. I mean, it looks like we're normalizing this new regime of inflation, pro-inflation to remediate the debt issues we have. So that would be one thing that would make Bitcoin cryptocurrency much less relevant as if everyone becomes totally assured of the soundness of sovereign currencies basically, namely the dollar, like the dollar being the main one. It seems like we're going completely opposite direction, but most people seem to be noticing the stirrings of inflation in society. I mean, you might have noticed that too. It's showing up in commodity prices, lumber prices, in food, obviously in financial assets, and it'll show up in consumer prices generally soon. So that would be one way for Bitcoin to basically become irrelevant, because it's a dialectical thing. Bitcoin is held in opposition to the established monetary regime. So if they completely reform themselves and the dollar becomes super sound once again, and the Fed stops tinkering the way they constantly do, then we wouldn't need cryptocurrency as much. The other thing would be if a completely superior design for a new sort of state-independent monetary system emerged, but it's really hard to even imagine how that would come to emerge. And there's good reasons to think that Bitcoin, the conditions of its launch were extremely favorable and hard to replicate. Can you speak to some of those conditions? Why it's a unique timing-wise moment for Bitcoin to emerge? Yeah, so obviously Bitcoin was born in the depths of the financial crisis, which gives it a nice historical element, but that was kind of a coincidence. Honestly, we know that Satoshi had been working on it earlier, in 2017. The really special thing about Bitcoin was that it was launched anonymously by an entity that did not seek any glory or credit for what they did, and apparently never monetized it at all. So they never really moved any of their coins. Satoshi sent one test transaction to Hal Finney, who's one of the earliest Bitcoiners. Aside from that, as far as we know, Satoshi never spent any of their coins. So you have this wonderful Promethean quality, whereby it's almost self-sacrificial. I mean, it's like this borderline godlike figure in terms of their restraint finds this monetary technology and releases it to the world and pays the price. They never took advantage of their filthy lucre. You know, they never recognized any of the $50 billion that they made from Bitcoin. Satoshi also didn't assign themselves any privileged access to the coins. You know, Satoshi could have just written in the code, I own 10% of the coins. But they didn't. They just mined in the open free market competition like everyone else. It's just that Satoshi is an early miner to support the network, accumulate a lot of coins, for sure. But they didn't have any privileged special access. So that's one thing that's extremely special about the launch, is that we'd have a lot of people that were truly committed to the monetary protocol and didn't seek either recognition or financial spoils, and then also left. You know, Satoshi left in 2010, 2011, and hasn't really been heard from since. It's a very George Washington move, gangster move, where he didn't want power, and once he got power, he let go of it. Precisely. That was a key, actually, move. That was probably one of the most important moves at the founding of this country. That's right. George Washington could have been a king, probably if he'd wanted. And Satoshi could have been Jerome Powell if he'd wanted. And Satoshi could have held on to power indefinitely, but chose to leave. The other thing is that Bitcoin circulated for a long period of time, from January 2009 to about July 2010, without really having a financial value. So there weren't really any marketplaces, it didn't have a value. And so that gave it this really great distribution among a broad set of stakeholders. And there were no venture funds or hedge funds trying to aggressively buy up all the supply back then. Now, when you have new cryptocurrencies launched, they're aggressively pre-mined, and some gigantic Silicon Valley venture fund is going to own 30% of it. And so it's sort of impossible to conceive of how that could become a global money. Because how could a Silicon Valley investment firm own 30% of the money supply? That doesn't make sense. That's just so oligarchical, right? It's unbelievable. So Bitcoin, by contract, is a very bottom-up thing. It was the early enthusiasts, people that were really excited about the technology, they're the ones that obtained those early coins. And so there was a real element of fairness and just an organic nature to its launch, which would be incredibly hard to recapture today. Let's say Satoshi came back and they said, okay, I made Bitcoin 2.0, I'm going to release it. There would be the most aggressive land grab ever by gigantic pools of capital to get favorable allocations of the new system, right? Can Satoshi with Bitcoin 2.0 build in a resistance mechanism or a prevention mechanism for the land grab? It would be hard to because if you have capital and resources, I mean, if it was a proof of work chain, you'd just have people that would invest a ton of money in mining, for instance. But most new blockchains, cryptocurrencies are just sold, basically. They're issued in token offerings kind of thing. So it's hard to enforce through the protocol the decentralization of control power. It'd be challenging too. And people have tried to do airdrops where they distribute coins to a large number of people. It basically doesn't work. Most people don't care about the airdrop. So it's hard to have an equitable distribution. I think the conditions of Bitcoin's launch were so lucky and favorable that they're very unlikely to be replicated. So I do think it's going to be a real challenge to ever have a new competitor that's as decentralized, as leaderless, as dispersed, sort of distributed as Bitcoin has its credibility. I don't know how you could overrule it on those important features. Luke What about Bitcoin's comparison to other current cryptocurrencies? So Bitcoin versus Ethereum, for example. Why is it possible that Ethereum overtakes Bitcoin? Josh That's certainly possible. Yeah, I'm not ruling it out. Ethereum leadership is sort of wise enough to understand that they shouldn't compete with Bitcoin on those most profound qualities. Like Ethereum doesn't really aspire to be more sound from a monetary perspective than Bitcoin. In fact, the Ethereum leadership are sort of constantly tweaking the monetary policy. So they went for a completely different trade-off. They also don't compete to be as decentralized from a governance perspective, right? Because there's leadership. There's an ETH foundation. There's a charismatic leader, Vitalik. And Ethereum has this policy of hard forks. So in Bitcoin, hard forks are extremely rare. In Ethereum, it's the default way to change things. So it's a much more adaptive system, and it changes more frequently. But that also means that it's sort of they're incurring more risk when they introduce those changes. There's much more complexity. So Ethereum is smart because they sort of understood Bitcoin as the top dog when it comes to a sound money, a digital gold type thing. And they went for all of the different trade-offs. They wanted to be more of a platform. They wanted to have more complexity of the transactional layer. They wanted to take on more risk in terms of changing the protocol. They wanted to change more quickly. They wanted to make the monetary policy more mutable. So Ethereum takes that completely different tack. Of course, you know, I'm not ruling out that it could take over Bitcoin from a market cap perspective. It's just a very different system. And I tend to think that Bitcoin is the most disruptive one because it's the most equipped to challenge sovereign currencies in the grand scheme. Do you think they can coexist? So like in the future, do you see a world where, you know, Ethereum captures some large percent of the market, but nevertheless the minority? A hundred percent, a hundred percent. Bitcoin has already been tokenized and put onto Ethereum, many units of Bitcoin, I think over a billion dollars worth. So not only do they coexist, they are actually mutualistic. So they're like two creatures that have this, you know, it's like the rhino and like the bird that pecks the parasites off the rhino's back or whatever. Yeah. Right. So I don't know which is which in the analogy, but yeah, I don't know who the parasites are. Or, you know, the alligator and the teeth cleaning fish or whatever. Right. So, you know, I always wonder why the alligator doesn't just eat the fish, but I guess they're brushing its teeth basically. So Ethereum is, it gives you more transactional flexibility. There's much more experimentation happening there. It has this whole decentralized finance element. There's a huge number of Bitcoins that circulate on the Ethereum protocol, right? Because Ethereum is open to other asset types, basically. So I think that's actually accretive to both systems because Ethereum gets to have this good form of collateral Bitcoin on the system, which has good volatility characteristics. And then it's a supply sink for Bitcoins, which are sort of now they're injected into this third party protocol. And that, I think, reduces the velocity of Bitcoin overall, and it's probably good for the valuation. So you see, it quite possibly could be a symbiotic relationship. That's really interesting. I think so. I think so. What are your thoughts about Vitalik, Buterin? What are your thoughts about some of the other figures in the space outside of Bitcoin? I think Vitalik made some mistakes with Ethereum. Ultimately, I disagree with some of the decisions that were made along the way. Like there's this infamous case of this bailout where 14% of Ether was lost in the smart contract, or really this smart contract that a lot of Ethereum leadership were sort of backing and supporting was hacked. And then the foundation with Vitalik's support chose to make a change to the underlying protocol to undo the hack. Right? So to me, that was not the most prudent approach, because you're basically violating the core protocol rules in order to undo, you know, to bail out a specific contract, which has failed. Granted, there was a lot of Ether in there, but I think that shook the credibility of the Ethereum system. That happened back in 2016, I think. That was one reason why I became disenchanted with Ethereum. So basically, even if in that case, that might fix an important problem that opens the door to centralized, like, manipulation of the protocol in the future. Yeah, it basically demonstrates that there's certain elites at the protocol level that can exercise specific control over the system. And, you know, a lot of people have lost money in hacks on Ethereum, and a lot of contracts have gone south. Huge amount of value. But they didn't get a bailout. And it was just when, you know, this specific contract called the DAO, D-A-O, was hacked, that, you know, the leadership intervened. And, you know, to their credit, they haven't had a significant intervention or bailout since then. But it did normalize the practice, and I think it weakened the social contract. So I would prefer that you sort of bite the bullet in that situation, and you accept the failure of that contract. That would be a ballsy move to bite that bullet. Yeah. I mean, and then you would have had, like, what they thought was a malicious entity in control of a lot of coins. I think the real reason they sort of felt that they had to undo it was because they'd always planned to move to this proof of stake world, where your political control over the system is a function of your wealth in the system. And they didn't want this attacker, which would have inherited all this significant wealth, to have influence over that future proof of stake version. That's sort of my theory. Yeah, I mean, that makes sense. It kind of reminds me of the bailout of car companies. You know, this is difficult. There's a lot of people that criticize the bailout of these large companies, you know. Yeah, creative destruction. I mean, I was critical of the bailouts that happened during COVID. I mean, I generally think that it's healthier for society for bad firms that aren't making money to fail or be reorganized under the various forms of bankruptcy. And you saw what happens. You see the corporate sector in Japan in the 90s, there was this slow motion insolvency where basically firms weren't allowed to fail. And the Japanese corporate sector lost competitiveness because bad firms did not fail. And so, you know, the process of actual capitalism for the market clearing didn't occur. So I'm always in support of, you know, of the free market being allowed to clear for non-profitable firms to fail. It's complicated, man, because creative destruction seems to be in the long term a positive. But human civilization is such that short-term pain has real impact on people, you know? Yeah, policy makers don't ever want to incur that short-term pain because they have a short-term outlook and term limits often. So... But, and also just it's short-term pain. Forget policy makers, forget politicians. It sucks to lose a job for an individual, you know? You could say the company, you know, creative destruction of a company means the company was inefficient and that's going to have a ripple effect of teaching everybody else what an efficient operation looks like. But like there's jobs that are being lost. There's families that have to suffer because of that. I mean, that's the tension we live in society is having a basic safety net for our world. Because there's a level beyond which, like, if through creative destruction that you have some percent of the population that dips below a certain level that you would call like suffering. We don't want that. And that's a difficult thing to live with. Like, yes, in the long term, you want inefficiency to be destroyed and efficiency to be rewarded. But there does seem to be a base level of like quality of life that we want to uphold. That's a difficult thing to think about. I think about that a lot. There's a doctor called Paul Farmer that, you know, there's like in Haiti or in Africa, there's a child who's dying. And as a doctor, you want to give everything you have, all the money you have to save that one child. But, you know, and you do actually. But that's a very human action. It's not an economic, it's not a rational action from a game theoretic perspective because there's no way you can take that action for every child who is suffering. But there's something deeply human about doing that for that one particular child. In that same sense, creative destruction is an important part of life. Destruction is an economic principle. But it's not necessarily that same kind of human principle. And there's a tension there. I see it. I mean, I think that's the issue with modern central banking really is that the central bank always has an incentive to lower interest rates. And they've been doing that from the 70s towards today on this, you know, well, 80s really on this slow march down. Because whenever there was a hint of a crisis in the economy or financial asset prices started to fall, their reaction is, okay, we'll inject more capital into the economy, we'll save it. But my view is that these palliative short-term measures cause the buildup of a huge amount of fragility in the long term. And then the ultimate collapse is much worse than the counterfactual situation where you raised interest rates, you took your medicine, and the economy was healthier. So, and that's sort of, that's why people like Ray Dalio point out that you have these long-term debt cycles, and we're sort of at the end of one now, is because we couldn't take our medicine, we couldn't let interest rates clear. We constantly wanted to ward off any difficulty, and we didn't ever want to deleverage, truly. And then when the debt crisis happens and it hits, it's, you know, horrendously bad. So do you think Bitcoin might reach a million dollars in value? It's having a current resurgence, a crazy one in 2021, in the recent months of over 60,000, I guess it is now. Do you think it's possible it goes over 100,000? Do you think it's possible it goes to a million? You can't rule anything out with Bitcoin. So, I mean, I'm not, you know, one to put price targets on it, but one way it could reach a million dollars is Bitcoin's value stays unchanged in real terms. A dollar depreciates. A dollar depreciates against it. Not that I expect hyperinflation, but yeah, I mean, look, Bitcoin is worth about one-tenth, slightly under one-tenth the value of all the gold in the world. And, you know, gold is worth 10 trillion, 11 trillion dollars in the aggregate. Do I think Bitcoin can be more culturally and economically salient than gold in two decades' time? 100%. Bitcoin was unknown 12 years ago, and today 100 million people worldwide own Bitcoin. So just extrapolate that. What is the level of penetration you think we'll get? 500 million, a billion? You know, you can easily tune these adoption curves however you like. I don't think it's done, you know, monetizing and being adopted globally. You think it can become like the base layer for a lot of our financial operation, like to become the main base layer for all our transactions? So, like, even banks will use Bitcoin, essentially, and like Visa would use Bitcoin as the base layer. Like, it would actually operate very similarly at the surface layer, but at the base layer would all be Bitcoin. That's precisely what I expect. And banks and Visa are already using Bitcoin. So Visa has embraced Bitcoin in a really big way, actually. And it's always funny to the people saying Bitcoin has to change in a certain way so it can compete with Visa. No. Visa adopted Bitcoin, right? PayPal adopted Bitcoin. Square adopted Bitcoin. Obviously, they're not tearing out all of their existing infrastructure, but they're totally engaging with this thing. Banks have now begun, they got the green light to provide custody for Bitcoin for their depositors. That's the first step. Eventually, you know, it'll happen one of two ways. Either Bitcoin native financial institutions will become banks. That's already happening. There's Bitcoin exchanges that have gotten banking licenses. Or banks themselves will start to engage with Bitcoin as a reserve asset. It'll converge either way. That's totally happening. And yes, I mean, I don't think Bitcoin is going to power every financial transaction. I think it'll coexist alongside sovereign currencies. But I think it's a great reserve asset. It's a very powerful asset to build a financial system on top of because it's highly, highly auditable. It's something that you can take physical delivery of very cheaply. And those are great qualities. If you're a depositor in a bank, they can prove to you how much Bitcoin they have. They can't really easily prove, you know, in the old system, how much gold they held on deposit. And you can easily conduct a run on the bank. You can hold them accountable because you can withdraw it because, you know, making a Bitcoin transaction is pretty easy at the end of the day. Unlike fiat currency, it's like kind of you can't really withdraw all your dollars from the bank. I mean, you sort of can, but you're not going to want to take delivery of pounds of cash or anything like that. So it's a good modern asset upon which to build a financial system, basically. You mentioned Square and Visa sort of investing in Bitcoin. What do you make of probably one of the higher profile big investments in Bitcoin, which is Tesla and Elon Musk, but there's also a few billionaires like Chamath and all of them investing. What do you make of this whole movement? Why do you think they're doing it? I mean, Tesla is an interesting case. Why do you think Tesla is buying so much Bitcoin? I honestly don't know. And I would love to truly know Elon's genuine thoughts on Bitcoin because he's kind of sending us mixed messages, honestly, with his embrace of Dogecoin, which is sort of playful, not exactly sure what point he's trying to make there. So you were involved with Dogecoin, you mentioned offline a little bit in the early days, or at least played around with it. What do you make of Dogecoin? What do you make of Elon and Doge? What do you make of this particular meme coin? Is it one, like a legitimate cryptocurrency, or is it two, like a funny internet way of saying F you to the man? Yeah, it's a good question. I mean, so I wasn't like a figurehead in Dogecoin or anything, but that was totally my introduction to crypto, was mining Dogecoin in my dorm room, and then tipping people online in Dogecoin, which I just thought was the funniest thing. So I guess I was really easy to entertain back in 2013. But it was very playful at the time. There was a culture around Dogecoin, and the people liked it because it was in opposition to the Bitcoin culture, which was really serious and involved lots of Austrian economics and Rothbard and Hayek and stuff like that. So that was my introduction to cryptocurrency, was because I thought the Bitcoin people were pretty lame, and they were like way too serious about all this stuff. And I was like, okay, I'll just be a part of the Dogecoin community. And they did all these funny publicity stunts, like they paid to send the Jamaican bobsled team to the Olympics. Great stuff. They put the Dogecoin logo on top of a NASCAR car. And that tickled me so much, because it's like this made-up internet coin. This was back when crypto was pretty novel and still kind of funny and stuff. And that was really entertaining. Fast forward seven, eight years, Dogecoin is way less entertaining now, frankly, because the leadership left, the community spirit evaporated. The meme didn't persist. I mean, Doge itself is not really a contemporary meme, right? I mean, it's an old meme. Although that new refresh of the meme, like Doge, I haven't heard that name in a long time, where Doge is in a hat smoking a cigarette. I mean, there's some sense where Elon is reinvigorating the meme. And it's funny, because one influential figure could do just that, which just speaks to the tension that you're talking about. Like Tesla is investing Bitcoin, and yet Elon, he also tweets about Bitcoin, but he's... I mean, who am I to question the meme, right? I can't dissect internet culture and panandically sit here and tell you it's an invalid meme. If people believe in it, then it's real. Is there a space for meme coins at this time, like Doge or somebody else to almost like... It does serve a lot of purposes, which is, like you said, it pulls in people into this whole space of digital currency, into cryptocurrency, allow them to explore, allow them to have fun as opposed to taking everything very seriously. Is there still space for that? Yeah. I mean, the crypto landscape is very broad today. So whatever cultural element you seek to find within crypto, you will find. It was a bit different in 2013, because Bitcoin was kind of the only game in town. There were a couple altcoins. And so Dogecoin made a lot of sense as a counterpart to Bitcoin, as a less serious counterpart. Today crypto is just this like gigantic cultural and economic trend. So it's very multifaceted. Dogecoin is one of the many ways that people have to engage with it. I think a lot of people that buy Dogecoin based on Elon's implied guidance are going to lose money, because fundamentally there's nothing enduring about Dogecoin. It's an ancient fork of Bitcoin. It's unmaintained. It's probably at risk, actually, from a protocol perspective. It's merge-mined with Litecoin, I think. If there was an inflation bug on Dogecoin, it's unclear who would be able to remediate that. So it's not technologically very sound. So I wouldn't recommend that anyone stores wealth in it. Yes, it's funny, because cryptocurrency, like my interest in cryptocurrency, is in the exploration of technical ideas. But cryptocurrency is also, like in the case of Dogecoin, for LOLs, at least originally, like a meme coin. But it's also a mechanism for investment. And so those are sometimes a tension. 100%. And it's unclear. The meme with Doge has almost become to take it to, I guess, a dollar, trying to drive the value up to a dollar. But implied in that is this overlap of the meme coin and legitimate investment. And so you have a lot of young people, I think, who almost start getting greedy and want to make money, as opposed to having fun. And that becomes a different beast then, because you're essentially making financial decisions that can have a long-lasting... Like, you know, money is freedom. And if you make stupid financial decisions, you can remove freedom from your life. And it can be detrimental in that sense. So I don't... It's difficult. I don't know what to do with that set of ideas, because a lot of cryptocurrency, including Bitcoin, is very volatile, because it's new. So you're trying to figure out the space of what's actually going to be a large part of, like you speak of network effects. What's going to take over the world? And through that process, there's going to be a lot of volatility. And if you're talking about cryptocurrency as an investment mechanism, then it can have real detrimental effects on people's lives. Yeah. And that's really the challenge with operating in the crypto space, talking about it. Overlaid on top of everything that's interesting politically or culturally about it is the financial incentive. And so, you know, it's not all fun and games, because there are literally billions, over a trillion dollars at stake now. So if you buy Dogecoin, because some influencer on TikTok said so, you've now made a financial decision, right? So I'm not going to scold any Dogecoin buyers or any crypto asset buyer for that matter, but be aware that there are like billions of dollars of really elite hedge funds that are trying to front run all of your decisions and evaluate social sentiment, things like that. So it's a water full of sharks, basically. And by the way, if you're listening to this, don't take this podcast or anything I ever say as financial advice. That's definitely not my interest or expertise level. The interest here is to explore different ideas. Speaking of which, you've written a little bit about NFTs. I'd be interested to hear your opinions on this space of ideas, these non-fungible tokens. They seem to have a cultural impact currently, but do they have a long lasting technical, financial, or cultural impact, or is this just the Fed? What do you think of NFTs? Yeah, I think the current enthusiasm for NFTs and the financial metrics you see, the growth there in that sector, is partially a function of where we are in the actual credit cycle. So oftentimes when inflationary events occur, you have correspondence speculative manias that occur at the same time because people intuitively feel that the fiat currency that they hold is being debased. And so they frantically look around for other places to put it. So stocks, property, commodities, and then other asset classes, NFTs are an asset class. And this is a case with any inflation you look at in history, you saw these correspondence speculative manias basically, speculative episodes. So a lot of us feel that inflation is occurring, whether it's in CPI or not, that basically lots of dollars are being injected into the economy. We have all seen stocks massively appreciate even as GDP contracted. And so a lot of people sort of got caught on to this notion that, wow, is the Fed, you know, lowers interest rates and Congress spends a huge amount of stimulus dollars into the economy, financial assets are going to go up, so I better have exposure to all that stuff. And so you see virtually every asset class is awash with cash right now. People are investing like their lives depend on it, investing, trading, whatever. Whether it's options, volumes, on Robinhood, you know, like kind of retail brokerages, things like that, whether it's stocks, whether it's crypto and then other collectibles, baseball cards, their valuations have been skyrocketing. And so I think NFTs are part of that. It's a new asset class. It's basically an opportunity to invest in sort of art or collectibles, in-game items, things like that. I think that explains a large degree of the enthusiasm, the excitement is that it's a novel asset class that people can trade and right as, you know, these inflationary tailwinds pick up. Now as for the sort of virtues of the actual technical phenomenon, NFTs are actually not a new idea at all. So you've had NFTs, I didn't call them NFTs, but in 2016 built on Bitcoin, for instance. So it's been around for a while. What it is, is a serial code, basically a string of data that is inserted onto a public blockchain and then circulates as a unique token. And then the question is, okay, well, what does that data refer to? What's the external reference? And that has to be defined. There has to be some entity which says, oh yeah, this unique string refers to like this piece of art or digital content or, you know, trading card or whatever. So NFT, the concept itself is like an incredibly broad idea. It's just, well, what if we took, you know, barcodes and put them on chain so that they could be traded and so they could circulate freely on a peer to peer basis and plugged into exchanges and things like that. So that concept is super valid, clearly has protocol market fit, right? People are using it for a really wide array of purposes. It's completely going to exist. May the valuations contract of NFTs in the aggregate? Definitely possible, probably likely. But I think the notion of creating enduring collectibles or artworks that have accompanying signatures, basically autographed art on the blockchain, that has totally been validated. I think that won't go away. I wonder if there's ideas like BitCloud, for example. I don't know if you saw that. If there's ideas built on top of this concept, it doesn't have to be like Ethereum, NFT, it could be just the concept of non-fungible tokens, whether those kinds of things could take hold. And it's less about financial transactions and more about almost like, I don't know how to put it, but like staking identity in some way, whether it's BitCloud or identity of objects, like there might be some way of connecting physical reality and digital reality in some interesting ways. So just the financial aspect is a way to put some validity behind the identity. I wonder if there's ideas there that are yet to be discovered or ideas that are yet to take hold. Like BitCloud, it seems interesting. It seems shady as hell. It seems a little scammy. I don't know if I like the idea that you can bet on people, essentially. Right. Yeah, I think my market cap on BitCloud is like $90,000 and I haven't done anything there. Did you verify yourself or whatever? I have not. I think people would yell at me on Twitter if I did. And it's unclear whether it's a scam yet or not, right? It's unclear where it's coming from. Well, there are some details about the investors. It's backed by some pretty big name investors. So I probably wouldn't use the word scam to describe it, but it's got Ponzi-like dynamics, like everything in crypto. So there's very questionable. And then also, is it using people's likeness without their permission, which is, I think, a legal question. So there's open questions around it. But is our public blockchains and that sort of architecture, is that going to be useful for decentralized or alternative forms of social media? 100% yes. I'm super, super bullish on that idea. Basically creating open protocols, open namespaces, ways to organize without the dependence on a single node, effectively, in Silicon Valley, the Twitter node or the Facebook node. I think it's a matter of urgency that we create digital gathering spaces where you have strong property rights. You have a claim on your identity. You have a claim on your data. And open architecture is our way to do that. I don't know if it'll be a blockchain, but certainly I think the general concept introduced by blockchains is a good template for how to organize these systems. Yeah. Value, freedom, value decentralization of power, whatever the mechanism. Let me ask you about love. So there is a Bitcoin maximalist community that sometimes, so those folks in general have a strong belief that Bitcoin is good for the world and it's almost an ethical imperative to sort of help Bitcoin succeed, which I think as a member of any community, I think it's beautiful to believe in the vision of the community. There does seem to be some properties of what some may call like toxicity or derision and mockery and those kinds of things. Some folks have criticized this, right? That Bitcoin maximalism is not necessarily good for the world, even if Bitcoin is good for the world. What are your thoughts about this kind of approach philosophically or practically to the spread of Bitcoin? And is there a way that we can add more love to the world while we add more Bitcoin to the world? That's a great question. I mean, you know, Bitcoin is sort of what you make of it. So you can define your own path as you advocate for Bitcoin or don't for that matter. So my chosen approach is the approach you see here, which I try to minimize the amount of sort of harshness or mockery, although I've been known to be mean on Twitter too. Well, Twitter is a specific, sorry to interrupt, is a specific media where this takes its worst form. So I'm learning, listen, I'm actually, because of this podcast, but in general, I'm part of different communities. And some are full of like unabashed love and some are like, what I experienced on Twitter, the Bitcoin community, at first I was off put in terms of the intensity, the mockery, I bet, the layers of lull, like the layers of not taking anything seriously. And I think there's power to that. There's freedom to that. I appreciate it. I have respect for it, but it's not my thing on Twitter. It's just not the way I enjoy communicating on Twitter. I retired from Twitter. I hit a hundred thousand followers and then I retired. I'm free now. I don't have to tweet anymore. It's great. But I totally can see the point. I wish that Bitcoiners were gentler in their approach. Not all Bitcoiners are like that, of course. There's 50 to 100 million of them worldwide and a few tens of thousands on Twitter. So I'm not going to claim that they're necessarily representative. The toxicity, though, is kind of a learned habit because Bitcoin has had so many episodes where strong-willed institutions, billionaires, the dice are pretty toxic, you could say, right? I'm basically mocking critics of Bitcoin. But at the same time, you're saying that the criticism has been predictable and repeatable and it's been the same throughout. Yeah, and that's a pretty dismissive thing to say, right? That I can reduce you to an algorithm with 11 permutations. But the thing to remember, I guess, is that some of the best-funded companies in the Bitcoin space, the most powerful miners, billionaires, have tried to change and co-opt and alter Bitcoin to shape it to their liking. And without these incredibly hardcore high priests of the Bitcoin protocol, it would have been hopelessly malleated in all number of ways. And so there is a reason why someone would be incredibly protective of Bitcoin. Does that justify immense toxicity on social media? Probably not. But it's a leaderless protocol, so the whole point is that it's money for enemies. And you know, some of the Bitcoin maximalists came for me, too, when I made suggestions that they didn't like. But I'm happy to use it, the protocol, because I know that that transaction will be final, regardless of how odious my counterparty is or how politically disfavored their opinions are. I mean, and this is where there could be disagreements, but I think you have to think about what's effective as a defense mechanism of strong ideas. And I personally think that kindness and thoughtfulness is much more effective because it lets the idea shine, as opposed to the personality of the individual humans overriding it. But there's debates on this, you know. I mean, I take your side on that. I think a patient and careful approach is the way to go. Now do all critics deserve good faith engagement? No, I would say. A lot of critics of Bitcoin operate in extreme bad faith. And the reason why is because we're not just talking about technical questions. In fact, most of this conversation has not been technical. It's been political. Because Bitcoin is an intensely political idea. And so a lot of people are predisposed to totally hate it and to wish death on Bitcoiners. I mean, there was a professor at GW I saw earlier this week that was musing about getting all the Bitcoiners on a boat and sinking it. It's like, in what other context would an upstanding professor muse about mass murder? But in the context of Bitcoin, it's sort of okay within his peers, because you're talking about something that most people don't like. It's a concept that's alien to them, that doesn't jive with the way they see the world. And so because it's so pitched from a political perspective, there's a lot of critics as well as defenders that operate in bad faith, I would say. But that's the nature of the beast. Because we're proposing a very disruptive thing. And there are people that would be disrupted by it. You wrote a blog post titled On Writing. You're I think an excellent writer. So let me ask, what does it take to be a good writer? What does it take to write some of the blog posts you've written, sort of condense a set of ideas in your head, the mess that's probably in your head and putting down on paper in a way that communicates the idea clearly and powerfully? So that was basically the point of the blog post, is that being an impressive writer is different from being an effective writer. So I think the answer to your question is humility, basically. So I think if you let pride and vanity seep into your writing, then you risk creating a very noisy signal, creating a very inefficient channel for communicating literal neural arrangements from your brain to someone else's brain. And that's what I think about when I write, is like, wow, I have the power to at scale change the literal physical composition of people's brains, to rewire them. If I make an idea that's so persuasive, that's so sticky, if I coin a phrase that is so pithy, then I can alter their brain. That's crazy. I mean, you're letting someone reach into your head and mess with it a little bit. That's unbelievable. And that's like a superpower. And if you could do that to 100,000 people at once, how powerful is that? And you mentioned Descartes, I think, therefore I am. That's like literally rewired millions of brains throughout history. Right. I mean, that's one of the most powerful, like, Koguta Urgo Sum, one of the most powerful phrases ever written. And that sent a zillion philosophy undergraduates down a rabbit hole of skepticism that some of them didn't make it out of. And they're convinced that the brain in the VAT theory is true, and there's no way to know what are tangible experiences. But yeah, so that's the beauty of writing. And the thing that interferes with that is our pride, our desire to impress people and look good to them and show off our vocab and stuff. And that was the point of that piece, is that I went on this journey where I eventually realized that I don't know if I'm any better of a writer for having realized it, but I think that is a necessary condition. So does that mean there is a value to striving for simplicity in the words as opposed to, I mean, complexity? I think so, for sure. And we deal with complex topics all the time in crypto, and that's always a huge red flag for me. If you can't explain something simply, do you understand it? So if you're talking about something complex, if you can't find simple ways to discuss it, my presumption is that you're actually obfuscating the truth. And this is what Orwell railed against with political language. He really hated political language because he felt that its authors were using deliberate obfuscation. And he hated euphemisms. And I hate euphemisms, too. I much prefer forthrightness and clarity of thought. But most people, when they write, don't really endeavor to be particularly clear. They might be writing to show off their startup or to demonstrate to people how cool they are or how well-read they are. They're displaying. It's like a peacock-style display. What fraction of people write to actually communicate meaning? Small fraction. It's especially difficult because what I've detected is something in us humans as readers assign more credibility to people that obfuscate. So like simple, clear communication of an idea is not like the immediate reaction is not one where we assign credibility to the person. Like that was brilliant. There's a lot of people that I kind of listen to without really understanding what the heck they're talking about. But it sounds musical and smart. And then I see a lot of folks assigning credibility to that person. And it's unfortunate. It's unfortunate that there's that tension as a reader, that we appreciate the beauty and power of complex weaving of words without assigning as much value to actual clear communication of an idea. And I'm always skeptical in speech as well. When someone will describe someone as articulate, I'm always immediately skeptical of the value of what that person is saying. Because if you articulate, you can make bad ideas sound very acceptable. Noam Chomsky has said this before. As a way to defend the way he speaks, he said that he's suspicious of charismatic people because they can basically sell any kind of idea. He speaks in a very monotone and boring way so that whatever the value his ideas have, it'll shine through. There's something to that. There's something to that. But it's a difficult journey. It's a difficult path. Because then, I think it's the right path because ultimately you focus on the quality of your ideas. And in the long term, that wins. I agree. Just by way of advice, is there, if people are interested in Bitcoin or cryptocurrency in your work, what are good books or resources on Bitcoin from you and from others that you can recommend that were in your own journey helped you or you've seen help others? Well, it's very easy. It's much easier today to make the Bitcoin journey because the quality of content is so much better than it was when I started. When I learned about Bitcoin, there was the Bitcoin Wiki and the Bitcoin Stack Exchange and the subreddit, and that was kind of it. And you had to just pick up everything. The economic theory hadn't really been worked out very much, so you had to pick everything up from scratch. The good news is that there's a huge abundance of content, and that's actually one of Bitcoin's greatest strengths, is that people are totally inspired to write about it. And it's almost a rite of passage at this point if you're a Bitcoin thinker to have your book. I don't have a book yet. I would love to recommend my book. I haven't written one. Do you think about writing a book? Yeah, I think it's my duty, 100%. Everyone that has created a lot of Bitcoin content probably should condense it into a book to give it an enduring status. It's interesting because you mentioned Block Size Wars, and you've written on a lot of different topics, so you could both write a big, sapien-style book about Bitcoin or cryptocurrency, right? But you can also write a book on each specific thing. And now that you put pressure on yourself in talking about simplicity, where do you lean on those different book journeys that you might take on? Do you have in you eventually a Bitcoin book? I mean, I tallied up the words that I wrote in the last couple years on Bitcoin. It's over 100,000 words a year, so that's two novels there. But yeah, I think I do. I think there's so much underexplored space in Bitcoin. I mean, a systematic interpretation of Satoshi's writings, for instance. And a lot of people don't want anyone to do that because they don't want it to have these religious overtones where you're engaging in interpretation, you know? But that's something that should be done. There's a lot of Bitcoin histories that haven't been written. There was a great Bitcoin history recently published. This is one of my recommendations, is On the Block Size War by Jonathan Beer, who runs probably the best research desk in the industry. So there's huge amounts of history that has transpired that hasn't been chronicled. And some of the accounts are indifferent. They're often written by outsiders, journalists that maybe don't fully engage with the Bitcoin system. Do you think the humans are interesting in the story, too? Of course, they're the most interesting thing. You know, I mean, Bitcoin itself doesn't really change that much. It's kind of this cold protocol that just sort of takes along. But the characters are just fascinating. And there's so many unbelievable characters in the Bitcoin story. Unbelievable. Yeah, that's the cool thing about Bitcoin and cryptocurrency and just internet is the weirdos, the brilliant weirdos. All the people in the stuff that's already established are boring. Like economics professors are all boring. But the interesting people, the wild ones, are the ones that are innovating in the crypto space, which is, you know, that's where the dangerous weirdos are and the exciting brilliant weirdos. Well, you had to be kind of crazy to adopt Bitcoin in the first sort of five years of its life. So there's an adverse selection element there. I don't know if that's an uncharitable way to put it, but like some of Bitcoin's earliest evangelists are not the evangelists I would have chosen, but they were the ones that we got. So it's the one we got. But is there is there resources? You're basically saying just throw a dart and most books are going to be good? Or is there something that stands out to you? I mean, your average book is, you know, terrible for sure, but not on Bitcoin specifically, but just in general. It depends whether you like the computer science, the economics or the history. But my recommendations would be, you know, obviously the Bitcoin white paper, that's and Satoshi's complimentary writings. That's very important is to try and understand the intentions behind the system and also to understand the system without having your view colored by some third party's description of it. Most descriptions of Bitcoin are really bad. So just go to the originals, go to the Hal Finney's posts, Satoshi's posts on Bitcoin talk. There's a huge amount of lucidity there. And actually, most of our questions about Bitcoin today that we have a decade later, were really answered in those earliest days. People just don't know it. The canonical economic work relating to Bitcoin, a lot of people don't like it. I think it's fine, would be the Bitcoin standard. A lot of people don't like it. I just read it. I like it. I think it's a good description of sort of the Austrian perspective and then how it relates to Bitcoin. There isn't that much about Bitcoin in there. But I think the point is, once you've understood, you know, Seyfriedin's view of monetary policy, Bitcoin makes a ton of sense. You don't actually need to argue for it that much. So the Bitcoin standard is a good introduction to sort of the orthodox thought in Bitcoin. There's a more recent book called Layered Money, which I liked by Nick Batia, which goes into more depth about what I was talking about earlier in the conversation, the layered approach to scaling. And that's a really critical thing to understand. Then technical books about Bitcoin. I like Grokking Bitcoin, which is a very computer science heavy one. There's a good textbook called Bitcoin and Cryptocurrency Technologies by Arvind Narayan. I think he's a Princeton computer science professor, which is really good at building intuition. Antonopoulos' books, Mastering Bitcoin, are good. Then there's like simpler intuition building books that aren't hardcore on the economics or the protocol design. So you have Inventing Bitcoin by Jan Pritzker, which is good. You have Bitcoin Clarity by Kjaer Bakkers. As you can tell, my bookshelf is mostly Bitcoin books. Well, that's a good selection. And of course, like you said, your writing and your book, that comes out this year or next year? I think I'm going to need 18 months. But most of the good Bitcoin content is just online, on Medium, on Twitter. So it's a decentralized consensus kind of thing. What about book recommendations that you could give people who love these outside of the world of crypto that maybe had an impact on your life? Fiction, sci-fi, maybe technical, philosophical. Is there something you would recommend that people might read? I really liked the three-body problem, but that's a really hackneyed recommendation. But it really made me think, and I like the hard sci-fi, the commitment to science and science fiction. So I thought it was very clever. Is there one, is there something that really annoys you in terms of the opposite of hard sci-fi, like that doesn't get stuff right? Movies or... I mean, I have issues when I watch ostensibly sci-fi or fantasy films that are not consistent about the rules for the universe that they've laid out, or where they're just impossible to comprehend. Like Christopher Nolan's latest film. You needed a spreadsheet to understand that. I trust that maybe he was consistent about the rules of his universe, I just did not understand it at all. In that sense, probably one of my favorites is 2001 Space Odyssey. It's so, obviously it's many, many decades ago, but it's quite brilliant in both its consistency and the depth of thought put into what the technology would actually be. Not in visually, not in silly graphical ways, but in terms of function and its impact on humanity. But that takes care, that takes a lot of work, and that takes genius actually, which is why Kubrick is regarded for what he is. What advice, you've taken an interesting journey through your life, you were at Fidelity, a philosophy major, you're now one of the seminal minds in the world of Bitcoin and cryptocurrency. Who the hell knows what the next five, ten years looks for you? If you were to give advice to somebody young today, making their way through life, making a career, what kind of advice would you give? See, the problem with advice is that in a world where so much of success is defined by luck and serendipity, is that the advice givers often don't know why they've been successful. They might say, you know, I was wearing a green tie on the day of my job interview, and so you should go out and wear green ties. And so they might just get the causality completely wrong. I mean, I'm not going to claim that I'm super successful yet, but see, that's the problem is that I don't think my journey is replicable necessarily. So who am I to give advice? So the one thing I will say is that the thing I did right was to become completely obsessed with a domain I found really interesting and held promise. Like if I had been really interested in like Magic the Gathering, I wouldn't have been able to like do much with that, aside from build like a killer, you know, card pack or whatever. And I wasn't afraid to, you know, really put myself out there and, you know, float my thoughts online and see how people reacted to them. Even if I said stuff that was completely erroneous or wrong all the time, the rewards to writing and just publishing content are immense, as you know, obviously. It's the most high leverage activity I think most young people have available to them. And I was very lucky and I benefited from a lot of favorable coincidences, a lot of people that took a chance on me. And if I had more time, I would sit here and name them. Is there something in your actions that made you more open to the benefits of luck? Sort of, you know, luck can bring you a lot of positive and negative things. So saying you're lucky means you were able to ride the wave of whatever positive stuff luck brought you. Well that's right, you have to put yourself in a position to be lucky, and most people don't. So you just have to get as many shots on goal as possible. And of course luck plays an undeniable role in any career path, for sure. But you do have to make yourself available to it, and you have to take a ton of chances. But yeah, that's the problem with advice. It's just so hard to replicate it, so I find it illegitimate most of the time. You heard it here, kids, don't listen to anything Nick just said. Exactly. Wear a green tie to your interviews, it'll work out well. Do you think there's a meaning or reason to any of this, this existence, this life? Well we make our own meaning, for sure. I find a huge amount of meaning in what I do. I find it beautiful, I feel very lucky and blessed to be in the line of work that I'm in. You know, to have your hobby and your passion and your job just be a completely integrated thing. So that's where I find meaning. If you're just a bag of cells and bacteria that eventually dissipates, dies, and goes into the ground and disappears back into the universe, that doesn't make any sense. Well that may be true, but I find the sublime in things like Bitcoin. I find it incredibly inspiring to work on it. I believe it's a hundred year plus project and it stirs those aesthetic emotions in you, as I'm sure your work does. So you find it beautiful. Absolutely, absolutely. And inspiring more than just beautiful. So you have hope for human civilization and Bitcoin is part of that hope? Yeah, it's a very optimistic view. And people accuse us of being pessimists and saying that we are rooting for the collapse of civilization, completely false. Bitcoiners are wildly optimistic because they believe that you can monetize a completely new system from scratch and compete with the strongest superpower in the military and the dollar and everything that goes with that. That's the craziest, most ludicrously optimistic proposition imaginable. So I think Bitcoiners are the most optimistic people out there. I don't think there's a better way to end it on that hopeful vision of human civilization, Nick. I've heard a lot of amazing things about you. I was binge watching your interviews, binge reading your blogs. Fell in love with your work. You're a good dude. Inspiring, brilliant. Thank you so much for wasting all your valuable time with me today. My absolute pleasure. Thanks for listening to this conversation with Nick Carter. And thank you to The Information, Athletic Greens, Four Sigmatic, and Blinkist. Check them out in the description to support this podcast. And now let me leave you with some words about freedom and beauty from Stephen King. Some birds are not meant to be caged, that's all. Their feathers are too bright, their songs too sweet and wild. So you let them go. Or when you open the cage to feed them, they somehow fly out past you. And the part of you that knows it was wrong to imprison them in the first place rejoices. But still, the place where you live is that much more drab and empty for their departure. Thank you for listening, and hope to see you next time.

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Nick Bostrom on the Joe Rogan Podcast Conversation About the Simulation | AI Podcast Clips

So part three of the argument says that, so that leads us to a place where eventually somebody creates a simulation. That I think you had a conversation with Joe Rogan, I think there's some aspect here where you got stuck a little bit. How does that lead to we're likely living in a simulation? So this kind of probability argument, if somebody eventually creates a simulation, why does that mean that we're now in a simulation? What you get to if you accept alternative three first is there would be more simulated people with our kinds of experiences than non-simulated ones. Like if, kind of, if you look at the world as a whole, by the end of time, a situation where you just count it up, there would be more simulated ones than non-simulated ones. Then there is an extra step to get from that. If you assume that, suppose for the sake of the argument that that's true, how do you get from that to the statement, we are probably in a simulation? So here you're introducing an indexical statement, like it's that this person right now is in a simulation. There are all these other people that are in simulations and some that are not in a simulation. But what probability should you have that you yourself is one of the simulated ones? Right, in this setup. So yeah, so I call it the bland principle of indifference, which is that in cases like this, when you have two, I guess, sets of observers, one of which is much larger than the other, and you can't from any internal evidence you have, tell which set you belong to, you should assign a probability that's proportional to the size of these sets. So that if there are 10 times more simulated people with your kinds of experiences, you would be 10 times more likely to be one of those. Is that as intuitive as it sounds? I mean, that seems kind of, if you don't have enough information, you should rationally just assign the same probability as the size of the set. It seems pretty plausible to me. Where are the holes in this? Is it at the very beginning, the assumption that everything stretches, sort of you have infinite time, essentially? You don't need infinite time. You just need, how long does the time- Well, however long it takes, I guess, for a universe to produce an intelligent civilization that then attains the technology to run some ancestry simulations. Gotcha. At some point, when the first simulation is created, that stretch of time, just a little longer than they'll all start creating simulations. Kind of like order of magnitude. Yeah, well, I mean, there might be different, it might, if you think of there being a lot of different planets, and some subset of them have life, and then some subset of those get to intelligent life, and some of those maybe eventually start creating simulations. They might get started at quite different times. Like maybe on some planet, it takes a billion years longer before you get monkeys, or before you get even bacteria than on another planet. So this might happen kind of at different cosmological epochs. Is there a connection here to the doomsday argument and that sampling there? Yeah, there is a connection in that they both involve an application of anthropic reasoning, that is reasoning about these kind of indexical propositions. But the assumption you need in the case of the simulation argument is much weaker than the assumption you need to make the doomsday argument go through. What is the doomsday argument, and maybe you can speak to the anthropic reasoning in more general. Yeah, that's a big and interesting topic in its own right, anthropics. But the doomsday argument is this really first discovered by Brandon Carter, who was a theoretical physicist and then developed by philosopher John Leslie. I think it might have been discovered initially in the 70s or 80s, and Leslie wrote this book, I think, in 96. And there are some other versions as well by Richard Gott, who's a physicist, but let's focus on the Carter-Leslie version, where it's an argument that we have systematically underestimated the probability that humanity will go extinct soon. Now, I should say most people probably think at the end of the day, there is something wrong with this doomsday argument that it doesn't really hold. It's like there's something wrong with it, but it's proved hard to say exactly what is wrong with it. And different people have different accounts. My own view is it seems inconclusive. And I can say what the argument is. Yeah, that would be great. Yeah, so maybe it's easiest to explain via an analogy to sampling from urns. So imagine you have a big, imagine you have two urns in front of you and they have balls in them that have numbers. The two urns look the same, but inside one there are 10 balls, ball number one, two, three, up to ball number 10. And then in the other urn, you have a million balls numbered one to a million. And somebody puts one of these urns in front of you and ask you to guess what's the chance it's the 10 ball urn. And you say, well, 50-50, I can't tell which urn it is. But then you're allowed to reach in and pick a ball at random from the urn. And let's suppose you find that it's ball number seven. So that's strong evidence for the 10 ball hypothesis. Like it's a lot more likely that you would get such a low numbered ball if there are only 10 balls in the urn, like it's in fact 10% done, right? Then if there are a million balls, it would be very unlikely you would get number seven. So you perform a Bayesian update. And if your prior was 50-50, that it was the 10 ball urn, you become virtually certain after finding the random sample was seven, that it only has 10 balls in it. So in the case of the urns, this is uncontroversial, just elementary probability theory. The Doomsday Argument says that you should reason in a similar way with respect to different hypotheses about how many balls there will be in the urn of humanity, I said, for how many humans there will ever be by the time we go extinct. So to simplify, let's suppose we only consider two hypotheses, either maybe 200 billion humans in total or 200 trillion humans in total. You could fill in more hypotheses, but it doesn't change the principle here. So it's easiest to see if we just consider these two. So you start with some prior based on ordinary empirical ideas about threats to civilization and so forth. And maybe you say it's a 5% chance that we will go extinct by the time there will have been 200 billion only. You're kind of optimistic, let's say. You think probably we'll make it through, colonize the universe. But then according to this Doomsday Argument, you should take off your own birth rank as a random sample. So your birth rank is your sequence in the position of all humans that have ever existed. It turns out you're about a human number of 100 billion, give or take. That's like roughly how many people have been born before you. That's fascinating, because I probably, we each have a number. We would each have a number in this. I mean, obviously the exact number would depend on where you started counting, like which ancestors was human enough to count as human. But those are not really important. There are relatively few of them. So yeah, so you're roughly 100 billion. Now, if there are only gonna be 200 billion in total, that's a perfectly unremarkable number. You're somewhere in the middle, right? It's run-of-the-mill human, completely unsurprising. Now, if there are gonna be 200 trillion, you would be remarkably early. It's like, what are the chances out of these 200 trillion that you should be human number 100 billion? That seems it would have a much lower conditional probability. And so analogously to how in the urn case, you thought after finding this low-numbered random sample, you updated in favor of the urn having few balls. Similarly, in this case, you should update in favor of the human species having a lower total number of members. That is doom soon. You said doom soon? Yeah, well, that would be the hypothesis in this case, that it will end after 200 billion. I just like that term for that hypothesis, yeah. So what it kind of crucially relies on, the doomsday argument, is the idea that you should reason as if you were a random sample from the set of all humans that will ever have existed. If you have that assumption, then I think the rest kind of follows. The question then is why should you make that assumption? In fact, you know you're 100 billion, so where do you get this prior? And then there's like a literature on that with different ways of supporting that assumption. That's just one example of a theropic reasoning, right? That seems to be kind of convenient when you think about humanity. When you think about sort of even like existential threats and so on, is it seems that quite naturally that you should assume that you're just an average case? Yeah, that you're a kind of a typical or randomly sampled. Now, in the case of the doomsday argument, it seems to lead to what intuitively we think is the wrong conclusion, or at least many people have this reaction, that there's gotta be something fishy about this argument, because from very, very weak premises, it gets this very striking implication that we have almost no chance of reaching size 200 trillion humans in the future. And how could we possibly get there just by reflecting on when we were born? It seems you would need sophisticated arguments about the impossibility of space colonization, blah, blah. So one might be tempted to reject this key assumption. I call it the self-sampling assumption. The idea that you should reason as if you were a random sample from all observers or in some reference class. However, it turns out that in other domains, it looks like we need something like this self-sampling assumption to make sense of bona fide scientific inferences. In contemporary cosmology, for example, you have these multiverse theories. And according to a lot of those, all possible human observations are made. So I mean, if you have a sufficiently large universe, you will have a lot of people observing all kinds of different things. So if you have two competing theories, say about the value of some constant, it could be true according to both of these theories that there will be some observers observing the value that corresponds to the other theory because there will be some observers that have hallucinations or there's a local fluctuation or a statistically anomalous measurement. These things will happen. And if enough observers make enough different observations, there will be some that sort of by chance make these different ones. And so what we would wanna say is, well, many more observers, a larger proportion of the observers will observe as it were the true value. And a few will observe the wrong value. If we think of ourselves as a random sample, we should expect with a probability to observe the true value. And that will then allow us to conclude that the evidence we actually have is evidence for the theories we think are supported. It kind of then is a way of making sense of these inferences that clearly seem correct that we can make various observations and infer what the temperature of the cosmic background is and the fine structure constant and all of this. But it seems that without rolling in some assumption similar to the self-sampling assumption, this inference just doesn't go through. And there are other examples. So there are these scientific contexts where it looks like this kind of anthropic reasoning is needed and makes perfect sense. And yet in the case of the doomsday argument, it has this weird consequence and people might think there's something wrong with it there. So there's then this project that would consistent try to figure out what are the legitimate ways of reasoning about these indexical facts when observer selection effects are in play. In other words, developing a theory of anthropics. And there are different views of looking at that. And it's a difficult methodological area. But to tie it back to the simulation argument, the key assumption there, this bland principle of indifference, is much weaker than the self-sampling assumption. So if you think about in the case of the doomsday argument, it says you should reason as if you are a random sample from all humans that will ever have lived. Even though in fact, you know that you are about number 100 billionth human and you're alive in the year 2020. Whereas in the case of the simulation argument, it says that, well, if you actually have no way of telling which one you are, then you should assign this kind of uniform probability. Yeah, yeah. Your role as the observer in the simulation argument is different, it seems like. Like, who is the observer? I mean, I keep assigning the individual consciousness. Yeah, I mean, well, a lot of observers in the simulation, in the context of the simulation argument, but they're all observers. The relevant observers would be, A, the people in original histories, and B, the people in simulations. So this would be the class of observers that we need. I mean, there are also maybe the simulators, but we can set those aside for this. So the question is, given that class of observers, a small set of original history observers and a large class of simulated observers, which one should you think is you? Where are you amongst this set of observers? I'm maybe having a little bit of trouble wrapping my head around the intricacies of what it means to be an observer in the different instantiations of the anthropic reasoning cases that we mentioned. I mean, does it have to be- It's like the observer, no, I mean, it may be an easier way of putting it. It's just like, are you simulated or are you not simulated, given this assumption that these two groups of people exist? Yeah, in the simulation case, it seems pretty straightforward. Yeah, so the key point is the methodological assumption you need to make to get the simulation argument to where it wants to go is much weaker and less problematic than the methodological assumption you need to make to get the doomsday argument to its conclusion. Maybe the doomsday argument is sound or unsound, but you need to make a much stronger and more controversial assumption to make it go through. In the case of the simulation argument, I guess one maybe way intuition popped to support this bland principle of indifference is to consider a sequence of different cases where the fraction of people who are simulated to non-simulated approaches one. So in the limiting case where everybody is simulated, obviously you can deduce with certainty that you are simulated. If everybody with your experiences is simulated then you know you're gotta be one of those. You don't need the probability at all. You just kind of logically conclude it, right? Right. So then as we move from a case where say 90% of everybody is simulated, 99%, 99.9%, it should seem plausible that the probability assigned should sort of approach one certainty as the fraction approaches the case where everybody is in a simulation. Yeah, that's a good one. And so you wouldn't expect that to be a discrete. Well, if there's one non-simulated person, then it's 50-50, but if we'd move that, then it's 100%, like it should kind of... There are other arguments as well one can use to support this bland principle of indifference, but that might be enough to... But in general, when you start from time equals zero and go into the future, the fraction of simulated, if it's possible to create simulated worlds, the fraction of simulated worlds will go to one. Well, it won't probably go all the way to one. In reality, there would be some ratio, although maybe a technologically mature civilization could run a lot of simulations using a small portion of its resources. It probably wouldn't be able to run infinitely many. I mean, if we take, say, the physics in the observed universe, if we assume that that's also the physics at the level of the simulators, that would be limits to the amount of information processing that any one civilization could perform in its future trajectory. Right, I mean, that's... Well, first of all, there's a limited amount of matter you can get your hands off because with a positive cosmological constant, the universe is accelerating. There's like a finite sphere of stuff, even if you travel with the speed of light that you could ever reach, you have a finite amount of stuff. And then if you think there's like a lower limit to the amount of loss you get when you perform an erasure of a computation, or if you think, for example, just matter gradually over cosmological timescales, decay, maybe protons decay, other things, and you radiate out gravitational waves, like there's all kinds of seemingly unavoidable losses that occur. So eventually we'll have something like a heat death of the universe, or a cold death or whatever, but yeah. So it's finite, but of course we don't know which, if there's many ancestral simulations, we don't know which level we are. So that could be, couldn't there be like an arbitrary number of simulation that spawned ours, and those had more resources in terms of physical universe to work with? So what do you mean that that could be? So sort of, okay, so if simulations spawn other simulations, it seems like each new spawn has fewer resources to work with. Yeah, but we don't know at which step along the way we are at. Right. Any one observer doesn't know whether we're in level 42, or 100, or one, or does that not matter for the resources? I mean, it's true that there would be uncertainty as, you could have stacked simulations. Yes, that's right. And that could then be uncertainty as to which level we are at. As you remarked also, all the computations performed in a simulation within a simulation also have to be expanded at the level of the simulation. Right. So the computer in basement reality where all the simulations within simulations within simulations are taking place, like that computer ultimately, it's CPU or whatever it is, like that has to power this whole tower, right? So if there is a finite compute power in basement reality, that would impose a limit to how tall this tower can be. And if each level kind of imposes a large extra overhead, you might think maybe the tower would not be very tall, that most people would be low down in the tower. I love the term basement reality.

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David Sinclair: Extending the Human Lifespan Beyond 100 Years | Lex Fridman Podcast #189

The following is a conversation with David Sinclair. He's a professor in the Department of Genetics at Harvard and co-director of the Paul F. Glenn Center for the Biology of Aging at Harvard Medical School. He's the author of the book, Lifespan and co-founder of several biotech companies. He works on turning age into an engineering problem and solving it, driven by a vision of a world where billions of people can live much longer and much healthier lives. Quick mention of our sponsors, Onnit, Clear, National Instruments, and I, SimpliSafe and Linode. Check them out in the description to support this podcast. As a side note, let me say that longevity research challenges us to think how science and engineering will change society. Imagine if we can live 100,000 years, even under controlled conditions, like in a spaceship, say, then suddenly a trip to Alpha Centauri that is 4.37 light years away, takes a single human lifespan. And on the psychological, maybe even philosophical level, as the horizons of death drifts farther into the distance, how will our search for meaning change? Does meaning require death or does it merely require struggle? Reprogramming our biology will require us to delve deeper into understanding the human mind and the robot mind. Both of these efforts are as exciting of a journey as I can imagine. This is the Lex Friedman Podcast and here is my conversation with David Sinclair. I usually feel like the same person when I was 12. Like when I, right now, as I think about myself, I feel like exactly the same person that I was when I was 12. And yet, I am getting older, both body and mind, and still feel like time hasn't passed at all. Do you feel this tension in yourself that you're the same person and yet you're aging? Yeah, I have this tension that I'm still a kid, but that helps in my career. Scientists need to have a wonder about the world and you don't wanna grow up. 12-year-olds, and even younger, I would say six, seven-year-olds, I've still got that boy in me and I can look at things. It's a gift, I think, that I can see things for the first time if I choose to, and then explain them as I would to a six-year-old, because I am that mentally. But on the other hand, I'm getting older. I run a lab of 20 people at Harvard. I've got a book, I've got science to do, companies to run. And so I have to, on most days, just pretend to be a grown-up and be mature, but I definitely don't feel that way. There's something I really appreciated in the opening of your book. You talked about your grandmother. And on this kind of theme, on this kind of topic, she, first of all, had a big influence on you. My grandmother had a big influence on me. And you also mentioned this poem by the author of Winnie the Pooh, Alan Alexander Milne. Maybe I can read it real quick, because I love it. On the topic of being children, when I was one, I had just begun. When I was two, I was nearly new. When I was three, I was hardly me. When I was four, I was not much more. When I was five, I was just alive. But now I am six. I am as clever as clever, so I think I'll be six, now, forever and ever. So this idea of being six and staying six forever, being youthful, being curious, being childlike, this and other things, what influence has your grandmother had on your thinking about life, about death, about love? Yeah, I was getting misty-eyed as you read that, because that poem was read to me very often, if not every day, by my grandmother, who partially raised me. And she was as much a bohemian as an artist, philosopher. And she's one of those people that wouldn't talk about the little things. She said, I hate small talk. Don't talk to me about politics or the weather. Yeah, talk to me about human beings and culture. So I was raised on that. And this poem was one that she read to me often, because she knew that the mind of a child is precious, it's honest, it's pure. And she grew up during the Second World War and in Hungary, in Budapest, witnessed the worst of humanity. She was trying to save a whole group of Jewish friends in her apartment. Saw what happened after the World War, which was, there was, the Russians were in control and locals weren't necessarily treated well if they were rebellious, which she was. And then there was the revolution in 56, which she was part of and had to escape the country. So she saw what can happen when humans do their worst. And her words to me, expressed in part through that poem, was, David, always stay young and innocent and have wonder about the world, and then do your best to make humanity the best it can be. And that's who I am. That's what I live for. That's what I get up in the morning to do, is to leave the world a better place and show to whoever's watching us, whether it's aliens or some future human historian, that we can do better than we did in the 20th century. You know, we mentioned offline this idea of bringing people back to life through artificial intelligence. Sort of, I don't know if you've seen videos of basically animating people back to life. Meaning, whether it's, for me personally, I've been working on specifically about Albert Einstein, but also Alan Turing, Isaac Newton, and Richard Feynman. And it's an opportunity to bring people that meant a lot to others in the world and animate them and be able to have a conversation with them. At first, to try to visually explore the full richness of character that they had as they struggle with the ideas of the modern age. Sort of, it's less about bringing back their mind and more bringing back the visual quirks that made them who they are. And then maybe in the future, it's using the textual, the visual, the video, the audio data to actually compress down the person for who they are and be able to generate text. There's a few companies, there's Replica, which is a chat engine that was born out of the idea of bringing, the founder lost her friend to, he got ran over by a car. And the initial reason she founded the company was trying to just have a conversation with her friend. She trained a machine learning, natural language system on the text that they exchanged with each other and try, she had a conversation with him sort of after he was gone. And it's very, the conversation was very trivial. It was obvious that it's, you know, AI agent, but it gave her solace. It made her actually feel really good. And that's the way I wonder if it's possible to bring back people that are, that mean something to us personally, not just Einstein, but people that we've lost and in that way achieve a kind of small artificial immortality. I don't know if you think about this kind of stuff. Well, I definitely think about a lot of things. That one's a really good one. There's a great black mirror episode about the wife who brings back the boyfriend or husband. I think one of the challenges with bringing back Richard Feynman would be to capture his sense of humor, but that would be awesome. But yeah, bringing back loved ones would be great, especially if it's, you know, they're young and they die early, though it may hold you back from moving on. That's another thing that could happen as a negative. But I think that's great. And I also think that it's going to be possible, especially when we're recording some of us, every aspect of our lives, whether it's our face or things we see, right? Eventually one day, everything we see can be recorded. And then you can build somebody's experience and thoughts, speech, and you will have replicas of everybody, at least digitally. And physically you could do that too one day. But that's a good idea, especially because there are people that I'd like to meet. And I think it's easier than building a time machine. One person I'd love to meet is Benjamin Franklin. Really? Well, I wouldn't go back in time. I would, but I'd prefer to bring him into the future and say, can you believe we have this thinking machine in our pockets now? And just see the look on his face as to where humanity has come. Because I think of him as a modern guy that just was before his time. Yeah, so you're thinking Benjamin Franklin is a scientist, not Benjamin Franklin, the political thing. Because he'd be very upset with Congress right now. Right. So maybe talk to him about science and technology, not politics. Or maybe just don't get him on Twitter because he'll be very upset with human civilization. You know, I wonder what their personalities are like. Isaac Newton, it does seem complicated to figure out what their personality is like. Even Friedrich Nietzsche, who I also thought about. Feynman is, we just have enough video where we get the full kind of, I mean, it shows you how important it is to get not the official kind of book level presentation of a human, but the authentic, the full spectrum of humanity. You mentioned collecting data about a person, collecting the whole thing, the whole of life, the ups and downs, the embarrassing stuff, the beautiful stuff, not just the things that's condensed into a book. And then with Feynman, you start to see that a little bit. Through conversations, you start to see peaks of like that genius. And then through stories about him from others. And then certainly you, the sad thing about Alan Turing, for example, is there's very little, if any, recording of him. In fact, I haven't been able to find recording allegedly there's supposed to be a recording of him doing some kind of radio broadcast, but I haven't been able to find anything. And so that's truly sad. That it feels like it makes you realize how the upside, how nice it is to collect data about a person, to capture that person. There's, that's the upside of the modern internet age, the digital age, that that information, yeah, creates a kind of immortality. And then you can choose to highlight the best parts of the person, maybe throw away the ugly parts and celebrate them even after they're gone. So that's a really interesting opportunity. You've also mentioned to me offline that you're really excited about all the different wearables and all the different ways we can collect information about our bodies, about, well, the whole thing. Is what's most exciting to you in terms of collecting the biological data about a human being? Well, so I'm a biologist. I find animals and humans as machines very interesting. It's one of the reasons I didn't become an engineer or a surgeon, I wanted to understand how we actually are built. And so I think a lot about machines merging with humans. And the first of that are the bio-wearables. And so I talked a lot about this, I wrote about it in Lifespan, the book, and pictured a future where you would be monitored constantly so that you wouldn't suddenly have a heart attack, you'd know that was coming, or you wouldn't go to the doctor and they don't know if you need an antibiotic or not. Long-term, how old are you, how to fix things, what should you eat, what should you take, what should your doctor do? These devices, I predicted, would be smarter, better educated than your physician and would augment them, and then there'd be a human that would just tick off to see if it's correct and they approve. I also was predicting in the book that we would have video conferences with our doctors and that medicines would be delivered, initially by courier, but eventually by drones and get it to you, sometimes in an emergency. And that we could even have pills that were synthesized or delivered in your kitchen and combined, certainly. What's amazing about that is that, what are we now, two years since the book came out, even less, and that future is basically here already. COVID-19 accelerated that incredibly. So where we're at now in society is, if you want to pay for it, you can have a blood test that will detect cancer 10, 20 years earlier than it would before it forms a tumor. You can, of course, do your genome very cheaply for less than $100 now. There are bio-wearables already. I wear this ring from Aura that I have a number of years of data. I've been doing blood tests for the last 12 years with a company called Inside Tracker, which I consult for. And so I have all of that data as well. And there's 34 different parameters on my testosterone, my blood glucose, my inflammation. And I use all that data to, of course, I wear a watch that measures things as well. I use that data to keep my body in optimal shape. So I'm now 51. And according to those parameters, I'm at least as good as someone in their early 40s. And if I really work at it, I can get my biochemistry down to mid 30s. Though I like to now eat a little dessert once in a while. So that's the future we're in right now. Anyone can do what I just said. But in the very near future, just in the next few years, you can be wearing wearables. So I'm currently wearing a little, what's called a bio sticker. This one I just put on last night. It's about an inch long, a few millimeters. Yeah, for people just listening, it's on David's chest. It's just the, how does it attach? It's just kinda. It sticks on. It sticks on. Yeah, so on one side you have an on button that you press. The lights come on, flashes four times, it's good to go. It immediately syncs to your phone. And this one, it's called a bio button, nice name. And there's another one that I have that I haven't tried yet that does EKG on your heart. This is mainly for doctors to monitor patients that go home after a heart attack or surgery. But that's medical grade, FDA approved device. So there will be a day, in fact it's already here, that doctors are using these to get patients to go home and save a week in hospital, $2,000 at least for each patient. That's massive savings for the hospital. But ultimately what I'm excited about is a future that isn't that far off where everybody, certainly in developed countries, eventually these will cost a few cents and rechargeable. The only cost will be the software subscription that can be monitored constantly. And to give you an idea what this is measuring me at a thousand times a second is my vibrations as I speak, my orientation, it already has told me this morning how I slept, where I slept, what side I slept on. We've got sneezing, coughing, body temperature, heart rate, heart, other parameters of the heart that would indicate heart health. These data are being used now to predict sickness. So eventually we'll have, just in the next year or so, the ability to predict whether something, or diagnose whether something is pneumonia or just a rhinovirus that can be treated or not. This is really going to not just revolutionize medicine, but I think extend lives dramatically. Because if I'm gonna have a heart attack next week, and that's possible, this device should know that and I'll be in hospital before I even have it. Maybe you can talk a little bit about InsideTracker because I saw that there's some really cool things in there. Like it actually, maybe you can talk about, I guess that you're collecting blood to give it the data. So, and it has like basic recommendations on how to improve your life. We're not just talking about diseases, right? Like anticipating having a particular disease, but it's almost like guiding your trajectory to life, how to, whether it's extend your life or just live a more fulfilling, like improve the quality of life, I suppose this is the right way to say it. How does InsideTracker work? What the heck is it? Because I saw there was also pretty cool. Yeah. What is it? Is it something other people can use? You can definitely use it. You can sign up, it's consumer. It's like a company, consumer-facing company? It is, yeah. And I also want to democratize the ability to just take a mouth swab eventually. We don't need to have a blood test necessarily, but for now it's a blood test and you'd go to a lab core request in the US. It's also available overseas. You can upload your own data for minimal cost and get the algorithms, the AI in the background to take that data, plot where you are against others in your age group in terms of health and longevity, bio age, they call it, no, inner age. But also it provides recommendations. And this isn't just a bunch of BS. It sounds like it might be to say, I'll go eat this or go to that restaurant and order that, but it's actually based on, they basically, this company has entered hundreds, now it would be thousands of scientific papers into their database, and hundreds of thousands of human data points. And they have tens of thousands of individuals that have been tracked over time. And anonymously, that data is used to say what works and what doesn't. If you eat that, what works? If you take that supplement, what works? And I was a co-author on a paper that showed that the recommendations for food and supplements was better than the leading drug for type two diabetes. That's so cool. The idea that you can connect, like skipping the human having to do this work, you can connect the scientific papers, almost like meta-analysis of the science connected to the individual data. And then based on that, connect your data to whatever the proper group is within whatever the scientific paper is to make the suggestion of how that work applies to your life. And then that ultimately maps to a recommendation of what you should do with your life. It all, like this giant system that ultimately recommends you should drink more coffee or less. Right, and we'll have the genome in there as well. You can upload that. And so these programs will know us way better than we do and our doctors as well. The idea of going to a doctor once a year for an annual checkup and having males get a finger up their butt and you cough, that to me is a joke. That's medieval medicine. And that's very soon going to be seen as medieval. Yeah, to me as a computer science person, it's always upsetting to go to the doctor and just look at him and realize you know nothing about me. You're making your opinions based on, it is very valuable, years of intuition building about basic symptoms, but you're just like, it is medieval. They're very good at it. In fact, doctors in medieval times were probably damn good at working with very little. But the thing is, I'd rather prefer a doctor that doesn't really know what they're doing but has a huge amount of data to work with. Well, you're right. And many of my good friends are doctors. I work at Harvard. So I'm not against the profession at all. But I think that they need just as much help as anyone else does. We wouldn't drive a car without a dashboard. We wouldn't think of it. So why would doctors do the same? If we could, can we step back to the big profound philosophical, both tragic and beautiful question about age? How and why do we age? Is it, from an engineering perspective, you said you like the biological machine. Is that a feature or a bug of the biological machine? It is both a bug and a feature. Evolutionary speaking, we only live as long as we need to to replace ourselves efficiently. If you're a mouse, you're only gonna live two and a half years, three years. You're probably gonna die of starvation, predation, freezing in the winter. So they divert most of their resources to reproducing rapidly, but they don't put a lot of energy into preserving their soma, which is their body. Conversely, a baleen type of whale, a bowhead whale in particular, will live hundreds of years because they're at the top of the food chain and they can live as long as they want. So they breed slowly and build a body that lasts. We're somewhere in between because we've really only just come out of the savannas where we could be picked off by a cat. We were pretty wimpy going back six million years ago. So we actually need to evolve quicker than evolution will. And that's why we can use our oversized brains and intuition to give us what evolution not only didn't give us, but took away from us. Now we're pathetic. Look at our bodies. These arms, if any of us, even the strongest person in the world went in a cage with a chimpanzee, the chimp could knock that person's head off, no question. So we're pathetic. So we need to engineer ourselves to be healthier and longer lived. So getting to aging, we can do better. Whales do way better. We're trying to learn how whales do that. And if you ask really anybody in the field now, professor, they'll say there are eight or nine hallmarks of aging, which are really, it's a word for causes of aging. So you probably have heard of some of these. Your listeners will have loss of telomeres, the ends of the chromosomes, like the little ends of shoelaces, that kind of thing. They get too short, cells stop dividing, become senescent. They become, they put out what are called mitogens that cause cancer and inflammatory molecules. So that's another aspect of aging, cellular senescence. Another one is loss of the energetics, so mitochondria, the battery packs wind down. There's a whole bunch, stem cells, proteostasis. Well, these are our Achilles heels that I'm talking about that are common amongst all life forms, really. But if you want me to jump to the chasers to what is the upstream defining factor, if we boil it down, what do we get? So most biologists would say you can't boil it down. It's too complex. I would say you can boil it down to an equation, which is the preservation of information and loss due to entropy, i.e. noise. And that is the basis of my research. It originally came out of discoveries in yeast cells where I went to MIT in the 1990s. You studied bread. I kind of did. I studied the makers of bread, a little yeast called Saccharomyces cerevisiae, which at the time was one of the hottest, excuse the pun, organisms to work on. But we figured out in the lab why yeast cells get old and found genes that control that process and made them live longer, which was an amazing four years of my life. One of those genes had a name with an acronym SIR2. Now the two is irrelevant. The SIR is important. And the most important letter out of all of those three is I, which stands for information. Silent information regulator number two, when you put more copies of that gene in, just put in one more copy, the yeast cells live 30% longer and suppress the cause of aging, which was the dysregulation of information in the cell. And then, so fast forward to now, I've been looking in humans and mice, because they live shorter and cheaper to study, where the loss of information in our bodies is a root cause of aging. And I think it is. Your boldness in viewing biology in this way is fascinating because that also leads to a kind of, it's almost like allows for a theory of aging, like you could boil it down to a single equation. And it leads to perhaps a metric that allows you to optimize aging, sort of in the fight against entropy. I had to figure out which mechanisms, like you said, the silent information regulator, which mechanisms allow you to preserve information without injecting noise, without creating entropy, without creating degradation of that information. For some reason, converting biology, which I thought was mostly impossible, into an engineering problem feels like it makes it amenable to optimization, to solving problems, to creating technology that can, whether that's genetic engineering or AI, it makes it possible to create the technology that would improve the degradation of information and aging. Is there more concrete ways you think about the kind of information we want to preserve? And also, is there good ideas about regulators of that information, about ways to prevent the distortion, the degradation of that information? Right, so we have silent information regulator genes in our bodies, we have seven of them, SIRT1 through seven, they're called. And we found in mice, one way to slow down the loss of information is to just give more of these, to upregulate these genes. So we made a mouse that has more of this SIRT1 gene, turned it on, and that slowed down the aging of the brain and preserved their information. Now, what information am I talking about, you might ask? Well, again, you can simplify biology. There are two types of information in the cell, primarily. The one we all read about and know about is the DNA, the genome, and that's base four information, ATCG, the four chemicals that make up the various sequences of the genome, billions of letters. And that also degrades over time, but what's been fascinating is that we find that that information is pretty much intact in old animals and people. You can clone a dog, one of my friends in LA just cloned his dog three times. So this is doable, right? It means that the genome can be intact. But what's the other type of information? It's the epigenome, the regulators of the genetic information. And physically, that's really just how the DNA is wrapped up or looped out for the cell to access it and read it. So it's similar to, and excuse this analogy, but it's a good one, a compact disc or a DVD. Those pits in the foil are the digital information, that's the genome, and the epigenome is the reader of that information. And in a different cell, you'd read different music, different songs, different symphonies. And that's what gets laid down when we're in the womb and that makes a skin cell forever a skin cell and not a brain cell tomorrow. Thank God, otherwise our brains wouldn't work very well. But over time, what we see is that the brain cells start to look more like skin cells and the kidney cells start to look more like liver cells. And they, what we call X differentiate, this is a term that we use in my lab that isn't yet widely used. But we needed a term to explain this. And that process of X differentiation, the loss of the reader of the CD or the DVD, we liken that to scratches on the DVD so that the reader cannot fully access the information. Now we can slow down the scratches, as I mentioned. We can turn on these genes, we can even put in molecules into the cell or even eat them and turn on those pathways, which my father and I have been trying to do for about a decade to slow things down. But the question that I've had is, is there a repository of information still in the body? Because anyone who knows anything about the loss of information or even has tried to copy a cassette tape or photocopy or Xerox anything knows that over time you lose that information irreparably. So I've been looking for a backup copy inspired largely by Claude Shannon's work at MIT as well in the 1940s. His mathematical theory of communication is just brilliant. And so I've been looking for what he called the observer, which is the backup copy. We today might call that the TCPIP protocol of the internet that stores information in case it doesn't make it to your computer, it will fill in the gaps. And we've been spending about the last five years to try and find if there really is a backup copy in the body to reset the epigenome and polish those scratches away. That's incredible, so finding the backup, so whenever there are too many scratches pile up, you can just write a new version. Like write, not a new version, but go to the backup and restore it. Right, that's really all we're talking about. It's not that hard once you know the trick. And for people that actually remember like DVDs and scratches on them, how frustrating it is, that's a brilliant metaphor for aging. And then the reader is the thing that skips and then it could destroy your experience, the richness of the experience that is listening to your favorite song. Right, but in biology, it's even worse because you'll lose your memory, your kidneys will fail, you'll get diabetes, your heart will fail. And we call that aging and age-related diseases. So most people forget that diseases that we get when we get old are 80 to 90% caused by aging. And we've been trying to fix things with Band-Aids after they occur without even generally talking about the root cause of the problem. Is there the scratches, do those come from, are those programmed or are they failures? Meaning is it, so if it's by design, then there's like a encoded timeline schedule that the body's just on purpose degrading the whole thing. And then there's the just the wear and tear of like the scratches on a disc that happen through time. Which one is it that's the source of aging? It's more akin to wear and tear, there isn't a program. Getting back to evolution, there's no selection for aging. We're not designed to age, we just live as long as we need to and then we're at the whim of entropy, basically, second law of thermodynamics, stuff falls apart. We live a bit longer than age 40, only because there are robust, resilient systems, but eventually they fail as well. Current limit to the human lifespan where they completely fail is 122. But I don't like to think of it as wear and tear because there's two aspects to it. There's a system that's built to keep us alive when we're young, but actually comes back to bite us as we get older. And we call this issue antagonistic pleiotropy. What's good for you when you're young can cause problems when you're older. So we've been looking, what is the cause of, the main causes of the noise? And we've found two of them definitively. The first one is broken chromosomes. When a chromosome breaks, the cell has to panic because that's either going to cause a cancer or kill the cell. There's only two outcomes, it's pretty much a problem. And so what the cell does is it reorganizes the epigenome in a massive way. What that leads to is, think of it as a tennis match or a ping pong game. The proteins are the balls and they now leave where they should be, which is regulating the genes that make the cell type, whatever it is. And they have a dual function, they actually go to the break, the chromosome will break and fix that. And then they come back. You might ask, well, why is it set up that way? Well, it's a beautiful system, it coordinates gene expression, the control systems with the repair. You want them coordinated. Problem is as we get older, this ping pong game, some of the balls get lost. They don't come back to where they originally started. And that's what we think is the main noise for aging. And we've also, the other cause of aging that we found is cell stress, we damage nerves and they age rapidly. So that's the other issue. There's probably others. Smoking chemicals, for example, we know accelerates biological age pretty dramatically. But the question is, can you slow that down or can you reset them to get those ping pong balls to go back to where they originally started in the game? And we think we found a way to do that. What can you give me hints? Whose fault is it in the balls not coming back? Is it the proteins themselves? Are they starting? Again, I've been obsessed with the protein folding problem from the AI perspective. So is it the proteins or is it something else? Well, we know who hits the balls and recruits them so that the break is recognized by proteins who send out a signal through phosphorylation is typical way cells talk to other proteins. And that recruits those repair factors, those ping pong balls to the break. So the cell's actively doing this to try and help itself. But we don't know who's to blame for them not coming back. That could just be a flaw in the quote unquote design. I don't think that there's something saying, well, 1% of you balls proteins never go back. I just think it's hard to reset a system that's constantly changing. We have in our bodies close to a trillion DNA breaks every day. And imagine that over 80 years, what damage that does to our epigenomic information. Now we know that this is, well, we never know anything in biology, but we have strong evidence that this is true because we can mess with animals, we can create DNA breaks and tickle them with a few breaks, maybe raise it by threefold over background levels of normal breakage. And if we're right, those mice should get old. And they do. We can actually, we've created these breaks in a way that's titratable. We can, it's like a rheostat, we can send it to 11. I drove my Tesla here, I'm a big fan of Spinal Tap 2, going to 11. If we go to 11, we can make a mouse old in a matter of months. We prefer to go to a level of about four and it gets old in 10 months. But it's definitely old. It's got all of the hallmarks of aging, it's got diseases, it looks old, its skin is old, it's got gray hair. But importantly, we can now measure age by looking at the scratches. We can look at the epigenome, we can measure it and use machine learning to give us a number. And those mice are 50% older than normal. So you can replicate the aging process in a controlled way. You can, I mean, in a way that you, I mean, you could accelerate it in a controlled way and measure how much exactly it's aging. And that gives you step one of a two-step process to when you can then figure out, well, how can we reverse this? And now we're reversing those mice. Is there a good, I love what you said. I mean, in biology, you really don't know. It's such a beautiful mess. Is there ideas how to do that? Is that on the genetic engineering level? Is it like, what can you mess with? Is it going to the, trying to discover the backup copies and restoring from them? Like what's, if it's possible to convert it to natural language words, what are the ideas here? What is the observer and how do we contact it? Exactly, what's the observer and how do you contact it? Or if there's other ideas, how to reverse the balls getting lost process. Yeah, well, you can slow it down. Slow it. But we found that a reset switch recently, we just published this in the December 2020 issue of Nature. And what we found is that there are three embryonic genes that we could put into the adult animal to reset the age of the tissues. And it only takes four to eight weeks to work well. And we can take a blind mouse that's lost its vision due to aging. Neurons aren't working well towards the brain. Reset those neurons back to a younger age. And now the mice can see again. These three genes are famous actually because they're a set of four genes discovered by Shinya Yamanaka, who won the Nobel Prize in 2016 for discovering that those four genes when turned on at high levels in adult cells can generate stem cells. And this is, I think, well known now that we can create stem cells from adult tissue. But what wasn't known is can you partially take age back without becoming a tumor or generating a stem cell in the eye, which would be a disaster? And the answer is yes. There is a system in the body that can take the age of a cell back to a certain point, but no further, safely, and reset the age. And we're now using that to reset the age of the brain of those mice that we aged prematurely. And they're getting their ability to learn back. This is really exciting, right? Like what's the downside of this? Well, the downside is if you overdo it and you don't get it right, you might cause tumors. But we do it very carefully. And we also know that in the eye, it's very safe. We also injected these, we deliver them by viruses. So we can control where and when they get turned on. And in this paper, we've published that if we put high levels in the mouse, into their veins, throughout the body, they don't get cancer for over a year. So I'm so optimistic that we're going into human studies in less than two years from now. Is there a place where AI can help? Sorry to inject one of the things I'm very excited about and passionate about. So Google DeepMind recently had a big breakthrough with AlphaFold2, but also AlphaFold two years ago with achieving sort of state of the art performance on the protein folding problem, single protein folding. But it also paints a hopeful picture of what's possible to do in terms of simulating the folding of proteins, but also simulating biological systems through AI. Is there something to you combined with this brilliant work on the biology side that you're hopeful about where AI can be a tool to help? Where isn't that a tool? I mean, if you're not using AI right now in biology, you're getting left behind. We use it all the time. We're using it to generate these biological clocks to be able to read those scratches. We're using it to predict the folding of proteins so we can target molecules and modulate their activity. We're using it to assemble genomes of different species. What else? We use it to predict the longevity of a mouse based on how it reacts to certain things, hearing, eyesight, generally frailty. So we just put out a paper last year on that. The other thing we can use it for, which is a little off the track here, but we use it for predicting which microorganisms are in your body. Actually, not predicting, telling you. So our daughter, Natalie, was infected with Lyme disease a few years ago, almost went blind from it. And the test took four days. And I thought, just give me the DNA from her spinal fluid. I'll go tell you what's in it, if it's Lyme disease or not. They refused. And so at that point I said, this has to be done better. So I've started a company that now can take a sample of any part of your body. It's typically done now with liver transplant patients to detect viruses that come out of their organs. But that's another area that AI is extremely important for. I think if you're not, in five years, if you're not using deep learning, you've got a problem. Because the amount of data that we generate now as biologists is just terabytes. It can be terabytes per week, it'll eventually be terabytes per day. And then we just go from there. And I actually have trouble recruiting enough bioinformaticians. A lot of our work is now just number crunching. A part of that is collecting the data, which is kind of something we've talked a little bit about. But is there something you can say about how we can collect more and more data? Not just on the one person level, like for you to understand your various markers, but to create huge data sets, to understand how we can detect certain pathogens, detect certain properties, characteristics of, whether it's aging or all the other ways that the human body can fail. It seems like with biology, there's a kind of privacy concerns that, well, actually not privacy concerns, it's almost like regulation that kind of prevents like hospitals and sharing data. I'm not sure exactly how to say it, but it seems like when you look at autonomous vehicles, people are much more willing to share data. When you look at human biology system, people are much less willing to share data. Is there a hopeful path forward where we can share more and more data at a large scale that ultimately ends up helping us understand the human body and then treat problems with the human body? So we are right in the middle. We're living through what's gonna be seen as one of the biggest revolutions in human health through the gathering of data about our bodies. And 20 years ago, people didn't wanna go on social media. They're worried about it. Now you have to, if you're a kid, that's for sure. Same with medical records. These are becoming all digitized and expanded. Ultimately, we're going to, even if we don't want to, have to be monitored. There's gonna be a court case that, I bet two, three years from now, someone's gonna say, how come my father died from a heart attack? You had these biosensors, 20 bucks, and you didn't use it. Lawsuit right there. And suddenly, all hospitals have to give you one of these. There'll be a reversal, like to where, it's your fault if you don't collect the data. That's brilliant. And that's absolutely right. I mean, that's absolutely right. That's the frustration I feel on going to the doctor is like, it's almost negligent to not collect the data because you're making, if there's something really wrong with me and you're making decisions based on very few tests, that's almost negligent when you have the opportunity to collect a huge amount more data. Well, let me tell you something, Lex. I've got this inside track of data for myself over a decade. And you'd think my doctor would roll his eyes at this oh, he's gone to a consumer company, blah, blah, blah. I had my first checkup in a year with him through video conference. And he was running blind. He really didn't know what was going on with me. He asked the usual things. How am I sleeping? How am I eating? These kinds of usual things. And I said, well, I've got new tests back from inside tracker. And he said, great, I'd love to see them. So I share screen and we look at the graphs, look at the data, and he's loving it. Because he cannot order these tests willy-nilly. So I said, well, let's order a HbA1c blood glucose levels, because I'm very interested in that. That tracks with longevity. And he said, well, I have no reason to order that. Do you have a family history? No. Do you have any symptoms of diabetes? No, well, I can't order the test. I almost wanted to reach through the computer and strangle him. But instead, I pay a little bit to get these tests done. And then he looks at them. So that's now the way consumer health is going, is that you can get better data than your doctor can, but they like you to do that. Quick human question, maybe you can educate me. I think doctors sometimes have a bit of an ego. I understand that the doctor is super experienced with a lot of things, but this is a fundamental question of human variability. Like I know a lot of specific details about like, I mean, it depends, of course, what we're talking about. But I bring a lot of knowledge and if I have data with me, then I have like several orders of magnitude more knowledge. And I think there's an aspect to it where the doctor has to put their expert hat, like take it off and actually be a curious, open-minded person and study and look at that data. Do you think it's possible to sort of change the culture of the medical system to where the doctors are almost, as you said, are excited to see the data? Or is that already happening? It's really happening. Now, we've probably lost the last generation, they're no hopers. So I teach at Harvard Medical School and they're excited about this. They're excited about aging, which is a new aspect to medicine. Oh, wow, we can do something about that. And then, yeah, all this data, what do we do with it? There's still the traditional pathology and all that stuff, which they need to know. But time will change their mindset. I'm not worried about that. And like we were discussing, this isn't a question of if, it's just a matter of when. And I have a front row seat on all of this. I had breakfast with a CEO who is making this happen just yesterday. I can tell you for sure that most people have no idea that this revolution is occurring and is happening so quickly. If you're running a hospital and you can save $2,000 per cardiac patient, what are you gonna do? You have to use it. Otherwise, the hospital down the road is gonna be beating you. And there are large hospital aggregations, so there's Ascension and others, that just have to go this way for budgetary reasons. And right now, the US spends, what is it, 17% of their GDP on healthcare. Let's say one of these buttons on my chest costs 20 bucks, it's rechargeable, and it can predict people's health and save on antibiotics, prevent heart attacks. How many billions, if not trillions of dollars will that save over the next decade? Yeah, so when the public wakes up to this, they'll almost demand it. Like, this should be accepted everywhere, this is obvious, it's gonna save a lot of money, it's gonna improve the quality of life. Well, and the CFOs of hospital groups will have to. And insurance companies are gonna wanna get in on this. So now that gets to privacy, right? Should an insurance company have access to your data? I would say no, but you could voluntarily show them some of it if they give you a discount, and that's also being worked on right now. I hope that we do create kind of systems where I can volunteer to share my data and I can also take the data back, meaning like delete the data, request deletion of data, and then maybe policy creates rules to where you can share data, you could delete the data. And I think if I have the option to delete all my data that a particular company has, then I'll share my data with everyone. I feel like if, because that gives me the tools to be a consumer, an intelligent consumer, of awarding my data to a company that deserves it and taking it back when the company's misbehaving. And in that way, encourage, as a consumer in the capitalist system, encourage the companies that are doing great work with that data. Well, yeah, healthcare data security is number one. On my mind, InsideTracker made sure that that was true. These buttons on your chest, there's very private stuff. They can probably tell if you're having sex one night, right? So this is not the kind of stuff you want leaked. So I don't know whether it's blockchain or something. Speak for yourself, I don't want this public. Yeah. The live stream. Well, I guess it depends on how you go, but. Yeah. But there's a lot of stuff you don't want out there and this definitely has to be number one because it's one thing to have your credit card information stolen, it's another thing your health records are permanently out there. Yeah. So there's, on the biology side, super exciting ways to slow aging, but there's also on the lifestyle side. I recently did a 72 hour fast. Just an opportunity to take a pause and appreciate life. Think about, there's something about fasting that encourages you to reflect deeper than you otherwise might. The time kind of slows and you also realize that you're human because your body needs food and you start to see your body's almost as a machine that takes food and produces thoughts. And then ends briefly. I mean, you start to, depending who you are, if you're like engineering minded, you start to think of this whole thing as a kind of, yeah, as a machine. And then also feelings fill this machine. Feelings of gratitude, of love, but also the uglier things of jealousy and greed and hate and all those kinds of things. You start to think, okay, how do I manage this body to create a rich experience? All of that comes from fasting for me. Anyway, but there's also health benefits to fasting. I intermittent fast a lot. I eat just one meal a day most of the time. Is there something you could say about the benefits of fasting in your own life and in general the anti-aging process? Wow, you're a philosopher too. Sorry, I apologize. No, I'm impressed. True renaissance man. It's a joy to be here. So when it comes to fasting, this is, being abstemious is one of the oldest ways to improve health. Probably they knew this 5,000 plus years ago. So that's not new. But what we're figuring out is what is optimal and how does it work? And one of the things we help contribute to, which I can speak to with some authority, is that these longevity genes we work on, we showed back in the early 2000s, are turned on by fasting. And at least in yeast, we were the first to show that how calorie restriction fasting works to extend lifespan. And that was the first for any species. Something similar happens in our bodies. When we're hungry or put our bodies under any other perceived adversity, such as running, our bodies think, wow, we're getting run, chased by a sabertooth cat or something. If we're really hot or cold, these probably also work. To put our bodies in this defensive state, to activate these genes in the way that whales do and mice don't. And so hunger is the best way to do that. In fact, I don't think you have to feel hungry. You can get used to it. But if there was one thing I would recommend to anybody to slow down aging would be to skip a meal or two a day. Now it doesn't mean you don't have to live well. You can go out. I go to restaurants, I eat regular food. I try to be as healthy as possible. But I've gone from skipping breakfast most of my life, now to skipping lunch as well. And I have my physique back that I had when I was 20. I feel 20 mentally. I'm much sharper. I don't feel tired anymore. I sleep well. So I'm a huge fan of the one meal a day thing. Where I'm not good at is going beyond one day. But if you do three days- Have you ever fasted longer than 24 hours? I tried doing two days. I might've made it to the third and given up. I just find that I don't have a lot of willpower. I also hate exercise. So I'm not sure how long I'm gonna live. But I've managed to do one meal a day. So if I can do that, seriously, anybody can do that. To your listeners and viewers, I would say, don't try to do it all at once. You can't go from snacking and eating three meals a day to what I do easily. Work your way up to it, but also compensate with drinking. If you like tea, if you like coffee, put some milk in it. That's fine. You can fill your stomach up with liquids, diet sodas. I get criticized for drinking, but I'm gonna continue to have those. But then I power through the day. I definitely don't feel tired. I don't have a lag anymore. But also give it at least two weeks because there's a habit as well. Having something in your mouth, chewing, feeling that fullness, you can break that habit. And within two, three weeks, you'll have done it. Absolutely. So I'm not actually even that strict about it. You said diet soda. Yeah, people are very kind of weirdly strict about fasting, the rules and fasting. Like for example, I drank Element Electrolytes when I was fasting, and that has like five calories. And so technically it's not fasting. Or people will say like, if you drink coffee, there's caffeine and they'll say that's technically not fasting because there's some kind of biological effects of caffeine, but whatever. Of course, there's like biological benefits that you can argue about, but there's also just experiential benefits. Just calorie restriction broadly has a certain experience to it that, like for me personally, just as you said, has made me feel really good. That said, like especially, I've gained quite a bit of weight, like maybe even like 15 pounds, something like that, since I moved to Austin, Texas. And I still keep the same diet, but I eat a lot of meat in that one, just because it's delicious, because it's also the amazing people I met in Texas. It's just there's like a camaraderie, a friendship, a love to the people that like makes you really enjoy the atmosphere of eating the brisket and the meat. Is this Joe Rogan insisting? Joe is, I mean, he's very different. Joe loves bread and pasta. Like he knows that his body feels best doing keto or carnivore. So that's what he usually tries to stick to, but he also does not hold back and he'll just eat pasta when he does pasta. And he sort of enjoys life in that way. I can't, I don't know how to enjoy life in that way. I also love pasta, but I'm just not going to enjoy it because I know my body ultimately does not feel good with pasta. So it's a funny kind of dichotomies. I would like to cheat, I guess, by eating more meat than I, you know, like overeating on the things that I know my body feels good on, as opposed to eating stuff I shouldn't, like cake and all those kinds of things. I tend to find happiness in overeating the good stuff versus eating the bad stuff. And that's the kind of balance. Him, he's like, fuck it. Every once in a while, you gotta enjoy it. And then also coupled with that for him is just exercise, like then faces demons the next day and just like burn a huge amount of calories, which is, I mean, whatever's up with that guy's mind, there's an ability to fully experience life, which is represented by the pasta, and the ability to just like fight the demons, which is represented by all the crazy kettleballs and running the hills and all this kind of stuff that he does. That takes a lot out of you doing that kind of insane exercise. And I think I'm more like you, or at least towards your direction is like, I really hate exercise. So I do it, but I really hate it. And so it's a balance that you have to strike. Is there something you could say about the diet side of that for you personally, but in general, in order to achieve calorie restriction, like for me eating, I know it may not sound healthy, but eating carnivore, eating mostly meat has made me feel really good, both mentally and physically. Is there something you could say about the kinds of diets that may improve longevity, but also enable calorie restriction? Well, sure. I mean, the first thing that's important to know is that while many people are interested slash obsessed with what they eat, the data that's come out of animal studies at least is it's far more important when you eat than what you eat. And this was a fantastic study a few years ago by my friend, Rafael de Cabo at the National Institutes of Health in Bethesda. And he had 10,000 mice on different diets, hoping to find the perfect mix of carbs, protein, and fat. And it turns out that the only ones that lived longer were the ones that only ate once a day. And so that, we're not mice, but I think that we're close enough to mice that this tells us a lot. But okay, but I still think the best bang for the longevity buck is to do both well, eat less often and eat the right things. Now I'll preface this to say, I'm not a nut about this. I will eat very occasionally a dessert. Usually I steal from others, which doesn't count, right? But you got to live life, right? What's a long life if it's not enjoyable anyway? But what I also found, and this is, I'll get to your question in a second, but my microbiome right now and stomach is at a point where if I try to overeat on a steak, which I did a couple of days ago, I actually had a chicken, a fried chicken specifically, for two days, I felt terrible. I couldn't sleep, it wouldn't go down. So I'm now at a point where even if I want to binge on meat and fried foods, I just can't, it just feels bad. But what do I recommend? Well, what the data says, which I try to follow, is that plant-based foods will be better than meat-based foods. And I know that there are a lot of people who disagree, but one of the facts is, well, there's a few facts. One is that people who live a long time tend to eat those type of diets, Mediterranean, Okinawa diet. They're eating mostly plants with a little bit of meat and not a lot of red meat. And the other fact is that in animals, we know that there's a mechanism that's called mTOR, little m, capital T-O-R, that responds to certain amino acids that are found in more abundance in meat. And when it responds, it actually shortens lifespan. And the converse, if you starve it of those three amino acids mostly in meat, then it extends lifespan. And there's a drug called rapamycin, which some people are experimenting with, that does that. So you might be able to, I'm just saying this here from all my colleagues, we don't know the results here, but you could potentially take a rapamycin-like drug and counteract the effects of meat in the long run. Don't know, we should try that, actually. We could do that in the lab. But getting to the bottom of this, what I think is going on is that just like testosterone and growth hormone, you will get temporary, maybe not temporary, immediate health benefits. You'll feel great, you'll get more muscle, energy. But the problem is, I think it's at the expense of long-term health and longevity. Well, this is actually something I worry about in terms of long-term effects or the cost in terms of longevity. It's very difficult to know how your choices affect your longevity because the impact is down the line. Just because something makes me feel good now, like eating only meat makes me feel good now, I wonder what are the costs down the line. Well, think about what I was saying about the trade-offs between growth and reproduction, which is what a mouse does, and a whale that grows slowly, reproduces slowly, lives a long time. It's called the disposable soma theory. Koch would just propose that in the 70s. What meat probably does is put you in the mouse category, super fertile, grow fast, heal fast. And then if you wanna be a whale, you should restrict meat and do things that promote the preservation of your body. Is it difficult to eat a plant-based diet that you perform well under, so mentally and physically? Just almost, I'm asking almost like an anecdotal question, or unless you know the science. Well, the science is still being worked out, but from the synthesis of everything that I've read, I try to eat a diet that's definitely full of leafy greens, particularly spinach is great because it's got the iron that we need, plenty of vitamins. I also try to avoid too much fruit and berries, particularly fruit juice, definitely avoid that sugar high. Spiking your sugar is not healthy in the long run. The other thing that's interesting is we discovered what we called xenohormetic molecules. Let me unpack that, because it's a terrible name, and I take full responsibility with my friend Conrad Howitz. The xeno means cross species, and hormesis is the term that what doesn't kill you makes you live longer and be healthier. And so we're getting cross species health improvements by molecules that plants make. And plants make these molecules when they're also under adversity or perceived adversity. For instance, I understand if you want really healthy or good oranges, you can drive nails into the bark of the tree before you harvest. Same with wine, you typically want them to be dry before you harvest or covered in fungus. And that's because these plants make these colorful and xenohormetic molecules that make themselves stress resistant, turn on their sirtuin defenses, the sirt genes, remember? And when we eat them, we get those same benefits. That's the idea, and we've evolved to do so. This isn't a coincidence. It's my theory, our theory, that we want to know when our food supply is under adversity because we need to get ready for a famine. And so we hunker down and preserve our body. And by eating these colored foods, so practically speaking, if it's full of color, or if there's been some chewing by a caterpillar, organic, grown locally in local farms, I'll eat that versus a watery, insipid, light colored lettuce that's been grown in California. So you want vegetables that have suffered. You went to David Goggins' vegetables. That's the xenohormetic molecules. I love that term, I'm gonna take that one with me. Thank you. Yeah, I follow him on Instagram, it's always screaming. You want the, that he's basically the xenohormetic version of a human. I like it. So these are the molecules that are representative of the stress that's been, that a plant has been under. Yeah, the best example of that is resveratrol, which many people, including myself, take as a supplement. Grapes, grapevines produce that in abundance when they're dried out or they have too much light or fungus. And that, we've shown, activates the SO2 enzyme in our bodies, which, remember, is what extends lifespan in yeast and slows down aging in the brain. That's beautiful. Yeah, I tend to avoid fruit as well. So green veggies, anything that's not very sweet. So I would just say you're relatively low, like you try to avoid sugary things as well. Yeah, I'm fairly militant about that. I rarely would add sugar to anything. Occasionally I would eat a slice of cheesecake, but that would be maybe once or twice a year. You have to give in occasionally. But yeah, anything that's sweet, I would rather substitute something like stevia if I need a sugar hit. What about exercise? Your favorite topic. I don't like talking about it. Okay, great. Is there benefits to longevity from exercise? Well, no doubt. That's proven. Just like fasting, it's pretty clear that that works. For example, there are studies of cyclists. It was something like people that cycle over 80 miles a week have a 40% reduction in a variety of diseases, certainly heart disease. So that's not even a question. But what's interesting is that we're learning that you don't need much to have a big benefit. It's an asymptotic curve. And in fact, if you overdo it, you probably have reduced benefits, particularly if you start to wear out joints, that kind of thing. But just 10 minutes on a treadmill a few times a week, getting you to lose your breath, get hypoxic, as it's called, seems to be very beneficial for long-term health. And that's the kind of exercise that I like to do, aerobic. Though I do enjoy lifting weights, so that is what I call my exercise, which has other benefits, including maintaining hormone levels, male hormone levels. But also, really why I do it is I want to be able to counteract the effect of sitting for most of the day. And as you get older, you lose muscle mass. It's a percent or so a year. And I don't want to be frail when I'm older and fall over and break my hip, which happens every 20 seconds in this country. So maintaining that strength, but also doing the cardio for the longevity, for avoiding the heart disease. Yeah, I definitely, just like with fasting, have the philosophical benefit of running long and running slow. I enjoy it because it kind of clears the mind and allows you to think. I actually listen to brown noise as I run. It really helps remove myself from the world and just like zoom in on particular thoughts. What is brown noise? It's like white noise, but deeper. So like white noise is like shh, and then brown noise is more like, shh, like ocean. That sounds great. I might try that. Yeah, yeah, it's a- It's more soothing probably. I'm not sure. There could be science to this. I need to look this up. I've been meaning to. But when I started, this is maybe like five years ago, I started listening to brown noise when I work. And the first time I listened to it, something happened to my mind where it just went like zoomed in to like in a way that it felt like really weird. Like how precisely it was able to sort of remove the distractions of the world and really help my mind. Obviously, like the mind is trying to focus and then it just enabled that process of trying to focus on a particular problem. I don't know if this is generalizable to others. People should definitely try it if you're listening to this. Maybe it's just my own mind, but it's funny. It made me, brown noise made me realize that there's probably hacks out there that work for me that I should be constantly looking for. It's almost like an encouraging and motivating event that maybe there's other stuff out there. Maybe there's other brown noise like things out there that truly like almost immediately make me feel better. I don't know if it's generalizable to others, but it does seem that it's the case that there's probably for many others, things like that that could be discovered. And so it's always disappointing when I find things in life that I wish I would found earlier. I got LASIK eye surgery a few years ago. And the first thought I had like the next day when I woke up is like, damn it, why didn't I do this way earlier? There's all this stuff of that nature that are yet to be discovered. So it pays to explore. Yeah, you have a different mind. You have quite a beautiful mind. So I suspect brown noise helps you focus and cause you're probably all over the place if you don't control it. Yeah, exactly. I mean, it's something about it. It's a programmer thing. A programming is a really difficult mental journey because you have to keep a lot of things in mind. So you're constantly designing things and you have to be extremely precise by making those things concrete in code. You also have to look stuff up on the internet to sort of feed like information and looking up stuff on the internet. Internet is full of like distracting things. So you have to be really focused in the way you look stuff up in pulling that information in. So it requires a certain discipline and a certain focus that I've been very much exploring how to do. Like I do it really well in the morning, coffee's involved, all those kinds of things. You're trying to optimize, keeping very positive, inspired, no social media, all those kinds of things and trying to optimize for. And everybody has their own kind of little journey that they try to understand. You get this from like writers. When you read about the habits of writers, like the habits they do in the morning, they usually write like two, three, four hours a day and that's it. It's like they optimize that ritual. And then there's always Hunter Stompson. So sometimes it pays off to be wild. What about sleep? How important is sleep for longevity? I would guess based on the evidence that it's really important and because we don't know for sure. But what we know from animal studies is the following. If you restrict sleep from a rat for just two weeks, it'll develop type two diabetes. It's that important. So that's the main thing. What we also know is at the molecular level that if you disrupt your sleep-wake cycle, so we actually have proteins that go up and down that control our sleep-wake. All of us, most of our cells do that. If you disrupt that, you'll get premature aging. And guess what? The opposite is true. That as you get older, that cycle, the amplitude becomes diminished. And this is why it's harder to get to sleep as you get older and then you got all sorts of problems. And I think what's going on is there's a positive feedback loop, which is a disaster in your old age, which is, right, you're aging. You can't at this moment totally prevent that. And then it's disrupting your sleep and you get not enough sleep and then that's gonna accelerate your aging process. And so it's known that people who are shift workers are more susceptible to certain age-related diseases. So your bottom line, you definitely wanna work on that. It's one of the reasons I have this ring on my finger which helps me optimize my sleep and learn what I do the day before if it was a bad idea and I'll stop doing that, like eating a fried chicken. I see you're still carrying the burdens of that decision. But is, yeah, you know, sleep is one of those things that's making me wonder about the variability between humans a little bit and how science is often focused on, like it's not often focused on high performers in a particular way. And it's looking at the aggregate versus the individual cases. For example, like for me, I don't know what the exact hours are, but like power naps are incredible. I tend to look at the metric of stress and happiness and joy and try to optimize those. So decreasing stress, increasing happiness and using sleep as just one of the tools to do that because like hitting the five, six, seven, eight, nine hour mark or whatever the correct mark is, I find that to be stress inducing for me versus stress relieving. Like thinking about that, I feel best if I sleep sometimes for eight hours, sometimes for four hours in the power nap. And as long as I have a stupid, private usually, smile on my face, that's when I'm doing good as opposed to getting a perfect amount of sleep according to whatever the latest blog post is. And I also pull all nighters still. I also think there's something about the body, like as long as you do it regularly, it's not as stress inducing. Like you know what it is. The reason I pull all nighters isn't for like I'm playing Diablo three or something is because I'm doing something I'm truly passionate about. Well, I'm also love video games, but I'm doing something I'm truly passionate about. And it's almost like there's the Jocko Willink feeling of when I'm up at 7 a.m. and I haven't slept all night and still I'm working on it. There's a kind of a celebration of the human spirit that I really enjoy it. And that's happiness. And to sort of then, and I usually don't tell that kind of stuff to people because their first statement will be like, you should get more sleep. It's like, no, I'm doing stuff I love. You should get more love in your life, bro. That's right. So, but that said in aggregate, when you look at the full span of life is probably you should be getting a consistent amount of sleep. And it seems like it's in that seven, eight hour range. Yeah, but it's similar to food. It's the quality, not the quantity. And when you get it. So I look at my data pretty often and what makes a difference to me is not the amount of hours, but the quality, the depth and the deep sleep is what will do it. So if I have a lot of alcohol before going to sleep and I can see my heart rate being different, but what really kills me is that I don't get a lot of that deep sleep and I wake up, barely remembering stuff. So that, like you say, if you're happy and contented and you're not gonna have these cortisol chemicals going through your body, you will more naturally get into that deep state. And even if you just get four hours, way better than eight hours of none of that. Yeah, that's beautiful. And some of that could be genetic. For me, I just fall asleep like this. If you want me to fall asleep right now, I can do it. I have no problem with it combined with coffee. I just had two energy drinks. I can probably sleep. So I don't know if that's genetics or it's kind of, I don't know what it is. Or maybe that I don't have kids and I'm single. So I don't have, I'm almost listening to some kind of biological signal versus societal signal. I'm not supposed to go to sleep. So I just go to sleep whenever I feel like going to sleep. Well, that's because you're self-employed. Self-employed. Most people don't have that luxury, but we're lucky, the two of us, that we can make our own hours. But yeah, it's super important. And those people who have the shift work, I mean, they really need to change the way that works because they're literally killing those people. Is there something you could say about the mind and stress in terms of the effect on longevity? Because I don't know if you think about it this way, but when you talk about the biological machine, it's always these mechanisms that are not necessarily directly connected to the brain or the operation of the brain. Like what's the role about stress and happiness and yeah, the sort of higher cognitive things going on in the brain on longevity? Right, well, that's a great point. The brain is the center for longevity, actually. We do know that. First off, when I'm stressed, I can see, mentally stressed, then I can see it in my body. Heart rate, hormones, it's clear. That's no true surprise. So you've got to work on your brain first and foremost. If you are totally freaked out, agitated all the time, you will live shorter. I'm certain of it. I keep fish. I'm a big aquarium guy. And you can see the difference between the fish that's having a good time and dominant and the one that gets picked on. It just looks like crap. You don't want to be the little fish getting picked on if you can help it. So I used to be extremely stressed as a kid. I was a perfectionist, very shy, always worried about being a failure. If I didn't get an A+, I was crying in my bedroom, that kind of sad existence. I got into my 20s, then in my 30s, and realized that's not the way to live. So I've worked very hard to get to this point where I almost never get stressed, never. There's nothing that, I've never gotten angry in my lab. I've got 20 kids. Sometimes it's like a, most of the time it's like a kindergarten. I haven't lost my temper. I'm very calm, but that's intentional. And I don't worry about stuff. Millions of dollars, billions of dollars at stake sometimes. Keep it cool. It's only life. We're all headed to the same place anyway. Don't worry about it. But to answer your question, I think in a better way, if you manipulate the brain of an animal, I'll give you an example. If we turn on this SIRT gene that I mentioned, SIRT1, we, a good friend of mine at Wash U, she and I did this. They upregulated that gene just in the neurons of the animal. It lived longer. So that's sufficient to extend lifespan. We also know that you can manipulate the part of the brain called the hypothalamus, which leeches a lot of chemicals into the body and proteins, most of which we don't know yet. But just changing the inflammation of that little organ or part of the brain is sufficient to make animals live longer as well. So get your brain in order first before you tackle anything else, I would say. So you kind of mentioned this. With the Insight Tracker, there's ability to take blood measurement and then infer from that a bunch of different things about your body and how you can improve the longevity. And you've also mentioned saliva and more efficient ways to get data. What does that involve? What's the future of data collection look like for the human biological system? Right, well, yeah, the issue with blood is you need someone to take it. Or you prick your finger, which hurts. So you've got to have something better. So I think what the future looks like is that you'll spit onto a little piece of paper and stick it in a machine, and it'll do that for you. But we're not there yet. So the intermediate future that I'm building right now is that you would take a swab of the inside of your mouth, which is the easiest way to take cells out of your body, and just ship them off. Okay, so it's called a buccal swab. I think we became very used to that. Right now, because of COVID, people don't like going to the doctor as much. They don't like going out. They just want to have home tests. And so that, I think, is the next 10 years where you'll get a kit in the mail, you'll swab your cheeks, stick it back in an envelope, send it off, and a week later, you have either a doctor's report or a health recommendation. And what can you get off a cheek swab? Well, you can get anything. You can get hormones, stress hormones, blood glucose levels. You can also tell your age reasonably accurately doing that, actually quite accurately. And those clocks cannot just tell you how you're doing over time, but can be used to give you recommendations to slow that process down. Because some people sometimes are 10 years older biologically than their actual chronological age. I mean, why does it matter how many times the Earth's gone around the sun, seriously? Who cares about birthdays? It's how long your body's clock has been ticking and how fast. So I could take a cheek swab from you today, Lex, take it back to my lab, and we then, by tomorrow, tell you how old you are biologically based on what we call the epigenetic clock. And you might be freaked out, you might be happy, but either way, we can advise you on how to improve the trajectory. Because we know that smoking increases the speed of that clock. We also know that fasting and people who eat the right foods have a slower clock. Without that knowledge, you're flying blind. But I like the idea of a swab because it's just so easy. A lot of us have done something like that for COVID tests. It's not a big deal. Yeah, I've been doing nonstop rapid antigen tests. So let me say, that particular one, rapid antigen test, they've been a source of frustration for me because everybody should be doing it. It's so easy. We've also been working in my lab on democratizing these tests to bring them down from a few hundred bucks to a dollar. So just to clarify, you're talking about not research, you're talking about company stuff, like actual consumer-facing things? Well, right. The research on bringing the price down has occurred in my lab at Harvard. And then that intellectual property is being licensed and has been licensed out to a company that will be consumer-facing. So anybody for a small amount of money can do this. Well, you got subscriber number one obsessed. I think that's a beautiful, beautiful idea. So somebody who, maybe I would have been more hesitant about it until COVID, but home tests are super easy. I almost wanted to share that data with the world, like in some way, not the entirety of the data, but like some visualization of like how I'm doing. Like, it's almost like, you know, when you share, if you had like a long run or something like that, I wish I could share because it inspires others. And then you can have a conversation about like, well, what are the hacks that you've tried and have a conversation about like how to improve lifestyle and those kinds of things that's grounded in data. That's exactly, that's what's gonna happen. Now, everything's anonymous, of course. We talked about security there, but once it's anonymized, you can then plot these numbers. And I've plotted my epigenetic age versus hundreds of other people who have taken this test now. And I can tell you where I fit relative to others in terms of my biological age. And I'm happy to share that with you all because it's been pretty low. You can choose to share it, of course. Not everyone wants to share that. But when you go to the doctor, first of all, your doctor does treat you as though you're an average person and none of us are average, there's no such thing. But second of all, we never know how we're doing relative to others because we all, most of us, we don't share our information. So we might have this number and that number, but do you know that your numbers are good for your age or not? You have no idea. Even your doctor probably doesn't even know. So this graph that I'm talking about is the beginning of a world where you can say, how am I doing? I'm a, for the two of us, we're white and we're male and we're this age and we do this. Are we good? Are we doing the right things or the wrong things? Do we need to fix certain things? And this is what the future is. It's forget about just experimenting and not knowing the result. I mean, who doesn't experiment and doesn't look at the data? No one, it makes no sense. So we're gonna enter a world where we have a dashboard on our body, the swabs, the blood tests, the biosensors where our doctors can look at that, but we can also look at it and they can recommend, go to this restaurant down the road. They've got this great meal. It's high in whatever you need today because you're lacking vitamin D and vitamin K2, go for it. Ridiculous question or perhaps not. If you look maybe 50 years from now or a hundred years from now, a person born then, what do you think is a good goal in terms of how long a person would live? Like what is the maximum longevity that we can achieve through the methods that we have today or are developing some of the things we've been talking about in terms of genetics, in terms of biology? Is there a number? Right, well, so it changes all the time because technology's changing so quickly. I keep revising the number upward, but I would say that if you do the right things during your life and start at an early age, let's say 25, we don't want malnutrition, starvation. That's not what I'm talking about. But in your 20s, start eating the kind of diets that I talked about, skipping meals. In animals, that gives you an extra 20 to 30%. We don't know if that's true for humans and that would, even 5% more would be a good, a big deal for the planet. I think that we should all aim to at least reach a century. I'm a little bit behind. I was born too early to benefit the most from all of this discovery. Those of you who are in your 20s, you should definitely aim to reach 100. I don't see why not. Consider this, this is really important. The average lifespan of a human that looks after themselves but doesn't pay attention is about 80, okay? Japan, that's the average age for a male, a bit higher. If you do the right things in your life, which is eat healthy food, don't overeat, don't become obese, do a bit of exercise, get good sleep and don't stress, that gives you on average 14 extra years. That gets you to 94. So getting to 100, if you just focus on what I'm talking about, it's not a big deal. So what's the maximum? Well, we know that one human made it to 122 and a number of them make it into their teens. I think that's also the next level of where we can get to with the types of technologies that I'm talking about. Medicines, like I mentioned rapamycin, there's one called metformin, which is the diabetes drug, which I take, that in combination with these lifestyle changes should get us beyond 100. How long can we ultimately live? Well, there's no maximum limit to human lifespan. Why can a whale live 300 years but we cannot? We're basically the same structure. We just need to learn from them. So anyone who says, oh, you max out at X, I think is full of it. There's nothing that I've seen that says biological organisms have to die. There are trees that live for thousands of years and their biochemistry is pretty close to ours. What do you think it means to live for a very long time? Let's say if it's 200 years we're talking about or a thousand years. There's some sense, you could argue that there is immortal organisms already living on Earth. Like there's bacteria, so there's certain living organisms that in some fundamental way do not die because they keep replicating their genetic, they keep like cloning themselves. Is it the same human if we can somehow persist the human mind and like copy clone certain aspects and just keep replacing body parts? Do you think that's another way to achieve immortality, to achieve a prolonged sort of increased longevity is to replace the parts that break easily and keep, because actually from your theory of aging as a degradation of information, so an information theory view of aging, like what is the key information that makes a human? Can we persist that information and just replace the trivial parts? Yeah, I mean the short answer is yes. We're already replacing body parts but what makes us human is our brain. Everything else is suboptimal except our brain. The ability to replace actual neurons is really hard. I think it might be easy to upload rather than replace neurons because they're so tight, it's such a network and just perturbing the system. It's Frodringer's cat, you change everything once you get in there. The problem is, well I guess the solution, let me go to the solution that's more interesting. What we're learning is that if you reverse the age of nerve cells, it looks like they get their memories back. So the memories are not lost, they're just that the cells don't know how to interpret them and function correctly. And this is one of the things we're studying in my lab, if you take an old mouse that has learned something when it was young but forgotten, does it get that back? And all evidence points to that being true. So I'd rather go in and rejuvenate the brain as it sits rather than replace individual cells which would be really hard. What do you think about efforts like Neuralink, which basically you mentioned uploading, are trying to figure out, so creating brain-computer interfaces that are trying to figure out how to communicate with the brain. But one of the features of that is trying to record the human brain more and more accurately. Do you have hope for that to, of course it will lead to us better understanding from a neuroscience perspective, the human mind, but do you have hope for it increasing longevity in terms of how it's used? I think that it can help with certain diseases. But I see at least within our lifetime that's the best use of it, is to be able to replace parts of the body that are not functioning, such as the retina and other parts, the visual cortex back here. That's going to be doable. In terms of longevity, maybe we could put something on the hypothalamus and start secreting those hormones and get that back. Ultimately, I think the best way to preserve the brain is going to be to record it, but also I think it's going to require death, unfortunately, to then do very detailed scans, even if you have enough time and money, atomic microscopy, and rebuild the brain from scratch. Rebuild from scratch, yeah. I mean, we are living more and more in a digital world. I wonder if the scanning is good enough for the critical things in terms of memories, in terms of the particular quirks of your cognitive processes. They're not. We're not close, yes, but we've made quite a bit of progress. So if you're an exponential type of person. Well, let's dream a little here. Yes, that's the point. The way it would work, that I could see it working, is you take a single cell slice through your dead brain, and we can now, the problem with the engineering aspect is that the engineering is, the physical aspect of the brain is not even half the problem. The problem is which genes are switched on and off. This experience that we're having here is altering certain genes in neurons that will be preserved, hopefully, for a number of decades, but you cannot see that with a microscope easily, but there are technologies invented, actually, just down the hall in the building I'm at, George Church invented a way, his lab invented a way to look at which genes are switched on and off, not only in a single cell, which any lab can do these days, but in situ, where it's situated in the brain. So you can say, okay, this nerve cell had these genes switched on and these switched off, we can recreate that, but just scanning the brain and looking how the nerves are touching each other is not gonna do it. Wow, okay, so you have to scan the full biology, the full details of the- And look at the epigenome. At the epigenome, too. Yeah, which genes are on and off. It's just easier to reset the epigenome and get them to work like they used to. True, true, use- We're doing that now. Use the hardware we already have, just figure out how to make that hardware last longer. Right, ultimately, information will be lost, even genetic information degrades slowly through mutation. So immortality is not achievable through that means, though I think we could potentially reset the body hundreds of times and live for thousands of years. Okay, so we talked about biology. Let's, forgive me, but let's talk about philosophy for just a brief moment. So somebody I've enjoyed reading, Ernest Becker wrote The Denial of Death. There's also Martin Heidegger. There's a bunch of philosophers who claim that most people live life in denial of death. Sort of, we don't fully internalize the idea that we're going to die. Because if we did, as they say, there will be a kind of terror of, I mean, a deep fear of death. The fact that we don't know what's, like we almost don't know what to do with non-existence, with disappearing. Like our, the way we draw meaning from life seems to be grounded in the fact that we exist and that we, at some point, will not exist is terrifying. And so we live in an illusion that we're not going to die and we run from that terror. That's what Ernest Becker would say. Do you think there's any truth to that? Oh, I know there's truth to that. I experience it every day when I talk to people. We have to live that way, although unfortunately I can't. But for most people, it's extremely distressing to think about their own mortality. We think about it occasionally. And if we really thought about it every day, we'd probably be brought to tears. How much we'd not just miss ourselves, but miss our family, our friends. We are, all living life forms have evolved to not want to die. And when I mean want, biochemically, genetically, physically. That yeast cell, the cells that I studied at MIT, they were fighting for their lives. They didn't think. But our brain has evolved the same survival aspect. Of course, we don't want to die. But the problem for us, unfortunately, it's a curse and a blessing, is that we're now conscious. We know that we're going to die. Most species that have ever existed don't. That's a burden, that's a curse. And so what I think's happened is, we've evolved certainly to want to live for a long time, perhaps never want to die. But the thought about dying is so traumatic that there is an innate part of our brains, and it's probably genetically wired, to not think about it. I really think that's part of being human. Because, you know, think about tribes that obsessed with longevity every day and that were going to die. They probably didn't make much technological progress because they were just crying in their huts every day, or, you know, on the savanna. So I really think that we've evolved to naturally deny aging. And it's one of the problems that I face in my career, and, you know, when I speak publicly and on social media, is that it's shocking. People don't want to think about their age. But I think it's getting better. I think my book has helped. These tests that we're developing should help people understand it's not a problem to think about your long-term health. In fact, if you don't, you're going to reach 80 and really regret it. And the other side of it, so again, Ernest Becker, but also Victor Frankl, I recommend highly, Man's Search for Meaning. Bernard Williams is a moral philosopher. They kind of argue that this knowledge of death, even if we often don't contemplate it, we do at times. And the very, what you call the curse, which I agree with you, it's a curse and a blessing that we're able to contemplate our own mortality. That gives meaning to life. So death gives meaning to life. As what Victor Frankl argues, I would probably argue the same. There's something about the scarcity of life and contemplating that, that makes each moment that much sweeter. Is there something to that? I think it's individual. In my case, it's completely wrong. I appreciate you saying that. I don't get joy out of every day because I think I'm going to die. I get joy out of every day because every day is joyous and I make it that way. And even if I thought I was going to live forever, I would still be enjoying this moment just as much. And I bet you would too. Well, I think about that a lot. I think it's very difficult to know. I'm almost afraid that I wouldn't enjoy it as much if I was immortal. I'm almost afraid to want to be immortal or to live longer because it perhaps is a kind of justification for me to accept that I'm going to die. It's saying like, oh, if I was immortal, I wouldn't be able to enjoy life as much as I do. But it's very possible that I would enjoy just as much. Of course, enjoying life, whether you're mortal or not, takes work. Like it requires you to have the right kind of frame of mind. You can discover, you can focus your mind on the ugliness of life. There's plenty of ugly things in this world and you can focus on them. You can complain. Whenever like, if it's raining outside, you can focus on the fact that you have shelter and enjoy the hell out of it. Or you can enjoy running in the rain when it's warm and like the beauty of nature, just being one with nature. Or you can just complain, this fucking weather again in Boston. And then it's either always raining or freezing, damn it. And like the same thing with like wifi going out on airplanes. Like you can either complain about like stupid wifi and JetBlue or something. Or you could say like how incredible it is that I can fly through the sky and in a matter of hours be anywhere else in the world. And then I could also on occasion watch like check email and even watch movies while connecting through satellites that are flying through space. So it's a matter of perspective. And perhaps there's an extra level of work required when you're a mortal. Because it's easier when you're a mortal or live longer to be lazy, to delay stuff. But if you're not, you can still derive the same amount of joy. So it's possible, it's possible. It's definitely possible. In my life, I went from being the, nothing's working to every day's great to wake up to. And I think even if you live, think you're gonna live forever, you can enjoy every day. What I do is everything's relative. We can compare ourselves to our neighbor who has more money or to the flight that should have had wifi. Or which is what I do, I'm still six years old remember. What a six year old does says, look, I can, when I tell my fingers to form a fist, they actually do that. That's really cool. That's how I live my life. I can pick up on your desk here, this metal object. It's a metal cube about an inch by an inch by an inch. And I tell myself not about cubes, but about inanimate objects. Probably once a day I'll say, I'm a living thing. I can think, I can move, I can eat. I am full of energy. And there's that leaf or this cube here that will never be alive. That's what I look at and compare myself to. And for as long as I live, if it's forever, of course it won't be, but even if it was forever, the relative to this lump of metal on this table here, we are wondrous things in the universe. And probably the most wondrous things in the universe. Yeah, we're able to deeply appreciate the leaf or the cube and deeply appreciate ourselves, which is, it can be a curse, but it's mostly a gift. Especially when you're, it's such a beautiful poem. Now I'm six, I'm as clever as clever. So I think I'll be six now forever and ever. That's a good thing to aspire to. Your grandmother was onto something. David, this was an incredible conversation. I'm a huge fan of your work. So thank you for wasting your valuable time with me today. I really, really appreciate it. This was awesome. Thank you for having me on, Lex, appreciate it. Thanks for listening to this conversation with David Sinclair. And thank you to Onnit, Clear, National Instruments, Simply Safe, and Linode. Check them out in the description to support this podcast. And now let me leave you with some words from Arthur Schopenhauer. All truth passes through three stages. First, it is ridiculed. Second, it is violently opposed. Third, it is accepted as being self-evident. Thank you for listening and hope to see you next time.

https://youtu.be/jhKZIq3SlYE

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Mark Normand: Comedy! | Lex Fridman Podcast #255

The following is a conversation with Mark Normand, a New York comedian who has a way with words that is often both dark and hilarious. Let that be a warning, dear friends, to proceed with caution and to wear protection. You may, in fact, need it. He has a special on his YouTube called Out to Lunch and a new special on Netflix as part of the Stand Up Season 3 series I recommend you watch. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Mark Normand. I asked Tim Dillon about Bukowski first, so let me continue on that tradition and ask you about something that Charles Bukowski said about love. Wait, are we rolling? Yes. Oh, geez, no hello, no nothing. Nope. I thought I was robotic. Bukowski said, love is a fog that burns away with the first daylight of reality. So, Mark Normand, let me first ask you about love. What are your thoughts about love? You talk about your relationships quite a bit. Do you think love can last? I do, but I think it's work. Everybody wants love to be this pre-packaged, perfect, euphoric thing, but you gotta... It's like a good body, you know? We're all born with a good body, but you gotta keep it in shape, and it's the same with a loving relationship. I think you... Nobody wants to do the work, that's the problem. You talked about... I think you told a story about being unfaithful to a previous girlfriend or something like that. I think the story goes that you were drifting apart. Who were you talking to? Bert Kreischer, maybe, or something like that? Yeah, we were high school sweethearts, dated for 12 years, and then... So, that wasn't love anymore. That was more like relationship. It was comfort. It was routine. And we just slipped into that married life, autopilot world. I tried to break up, I think, and it didn't take. It was one of those things. Our lives are just so baked in. And then I think I cheated, and she caught me, and it was ugly, and then we went to therapy to try to work it out, but it's much like a car that gets into a wreck. The door just never closes the same. You know what I mean? Yeah. So, what are your thoughts about, then, commitment, like outside of love, marriage? I think it's an antiquated idea. I think it's kind of silly and unrealistic, and I think we're coming out of that as we get all polyamorous, and non-binary, and queefy, and all this stuff. I think we're slowly moving away from that, but I think a lot of the ladies, more majority women, like marriage, like the idea of it. I'm a fiancé now, or whatever you call it. I'm engaged. And she is just, woo-wee, going hog wild. She's loving it. She's got the dress thing, pick a venue, flower, and she's deep in, whereas I feel guilty, because I'm just like, ah, jeez. Is it planned already? When's the wedding? You see Squid Game? I'm just living life. Yeah. It's planned. It's in New Orleans. I'm from there, and it's next year. Are you married? No, single. Virgin? Of course, yeah. I can't imagine. I bet you'd be great in bed. You're ripped. You'd be the best hairline in podcasting. Yeah, I don't know. I haven't tried yet, so we'll have to see. All right, well, let me know. Pretty big hog on you? Yeah, I could see you packing a crazy, crazy tool downtown. That matters for girls? Apparently, yeah. That's all I hear about. Okay, New Orleans. You grew up in New Orleans? Yeah, born and raised. Treme, outside the French Quarter. You ever been? Yeah, don't remember it. Oh, you drink? Yeah, I drink. Of course, I drink. I don't know. I can't tell if you have fun. No, not really, but Russian, of course, I drink vodka, all that kind of stuff. Oh, I know Russian. Yeah, yeah, yeah. Gotta know. Vodka. Beer was just labeled an alcoholic beverage in 2011. Fun fact. What do you mean? In Russia. It was just drinks. It was just like apple juice before. It finally got declared legally as an alcoholic beverage. Which means you can regulate it, that kind of thing. I guess so. Yeah. See, that's where your brain goes. Yeah, yeah, yeah. I just go, oh, these fucking Ruskies are- I didn't even know there's rules about drinking. This is good. I'm learning about Russia from you. Thank you. What's the difficult memory experience from childhood in New Orleans that made you the man you are today? I don't know if it made me the man, but, geez, I had a lot of scuffles in the neighborhood. I was the white kid in the neighborhood, so I was automatically the odd man out, the minority, the weirdo, the dork, the dweeb, the honky. So just a lot of memories of getting slapped in the face by guys and just having to take it, because there's five guys there. And they'd be like, oh, look, you didn't even fight back. And you're like, well, what am I going to do? Hit you and then get beat up by these guys? So a lot of that stuff was a big bummer growing up. Got robbed all the time. Lost a lot of bicycles. Had a bicycle taken from under me. That was pretty brutal. These kids pulled up. They're like 17, and I was 13, and I had a face paint on. I had a not black face, but I was at a summer camp, and I had a rainbow face painted on me. We were helping kids that day. So I let them put paint on me. So now I'm riding home. What a mark. What a goober I am. I'm riding home, and these guys see me a mile away. I'm a sitting duck, and they go, we can take his bike. He's got a fucking rainbow on his cheek. So they just go, hey. Cut in front of you. They go, let me try your bike. I go, I'm good. I'm good. I knew what they wanted. And they go, let me try the bike, and then they just pushed me and took the bike. So stuff like that was really shaping the insecurity, the self-worth. They did, because I've been mugged when I was younger, too. Really? Yeah. It changes your view of human nature a little bit. For sure. You go, wow, I didn't know people could be this mean, this cruel, inconsiderate. I'm always worried about it. Did I fart too much? Am I annoying? Am I pissing this guy off? But what a way to live. Just I want the bike. I'm taking it. Fuck his feelings. For me, that quickly turned into realizing that that's just a temporary phase that those folks are in. They have a capacity to be good. Sure. For some reason, for me, that was a motivation to see, can we discover, can we incentivize them to find a better path in life? I wasn't all, I don't know, Gandhi about it. Of course, I was pissed and all those kinds of things, but I don't know, it seemed like just the kind of thing you might do when you're younger. You hope. But this is adult crime, obviously. Yeah, I know. But yeah, exactly. And then it solidifies, and then you're beyond saving at some point. But there's always an opportunity to make a better life for yourself, to become a better version of yourself. Yeah, and I remember coming home crying with no bike, and my mom, my parents are liberal to a fault, where they were like, oh, well, they need it. They're poor kids in the neighborhood. And you're like, all right. But I also have a bicycle that I ride around, and I also like to live in an area that's not just riddled with theft and vandalism. But they were just like, oh, they need it. And then it was a moot point, we just moved on. So I remember very young being like, all right, I gotta figure my shit out. Okay, so you said you were beat up quite a bit, like bullying and stuff? Pushed around. I was never hospitalized or anything. But you get a black guy here and there, and a bloody nose, stuff like that. And it was just the outnumbered thing. The violence didn't really bother me, because you're just kids, you're boys. But it was the predatory, let's get him, you know, we can take him down. He's, you know, he's an easy target. That's what kills you, the mental part. Yeah, until you actually said that, I didn't realize. I've been in, what do you call them, scuffles. And there's just one that stands out to me where, yeah. Let's hear it, fatty. Bring it on. And you do jujitsu and all that stuff, right? Yeah, I can see the guns through the suit, you're like John Wick. All right. Well, I used to have, now you're gonna start making fun of me. I used to have long hair for like a couple of years. I was in a band, playing music and stuff like that. And there was, like, most of the fights I've been in were basically one-on-one, maybe a little bit like a little extra stuff, but not outnumbered. And this one particular time, I've learned a lot of lessons, but one of them was, there was a fight started between me and this other person, and then his buddies, I guess, were there. And they, as opposed to breaking it up or letting it happen, one of them grabbed my hair. It's the first time anybody grabbed, like, used my hair in a fight, which I've since then realized that that's actually a really powerful grip and a powerful weapon. Oh, yeah. Oh, very vulnerable of you. And then my head got pulled back and they pulled me down to the ground. Like, I couldn't do anything. It was so, I remember being exceptionally frustrated. Yes. Like, that was the feeling like, I can't do anything here. I'm, like, trapped. And then they were just, like, kicking me and hitting me and stuff like that. And the outnumbered part of it, because I always kind of remember the trapped part, because I just hated from a fighting grappling perspective, how, like, the feeling was, this isn't fair. Yes, that's what it is. It's a deep, deep unfairness. Yeah. That you just can't, you can't win. The mob wins. Yeah, the mob wins. Scary stuff. But it makes a man out of you in a weird way. It builds character. You realize life isn't fair early and you go on from there. So, there's something there. And look at you today. They're probably, you know, eating out of a dumpster at a Krispy Kreme and you're here. Got eight podcasts. You're doing great. Talking to giant titans of the industry. No, I do remember returning home that night. I mean, that you said you were crying. That's really formative. Like, that's the point at which you get to decide, what do I make of this moment? I mean, especially when you're younger, maybe it's not presented to you that way. But, like, some of the greatest people in history were bullied in these kinds of ways. And they made something of themselves in this moment. Like, bullied by life in some kind of way. It's, like, an opportunity for growth. It's weird. But, like, hardship, even in small doses, is, like, an opportunity for growth. Totally. I mean, look at Richard Pryor. They say he's labeled as the best comedian of all time. Grew up in a whorehouse. Watched his mom get plowed by these guys in the middle of Indiana, I want to say. And just, who had a harder life? Who would suck dick for drugs? All this stuff growing up, beat up. And then the weird thing is, oops, sorry, that's my birth control alarm. And then the whole world is, like, trying to get rid of bullying. But we still do bullying, but now it's accepted bullying. It's very strange. So, you're a proponent of beating kids up? Is that what you're saying? Yes, and sex with them. All right. But no, I just think it's part of life, and it's horrible. It's like rain. You gotta have it. Look, a rainy day is a bummer, you know, but you need it. And I think it's similar to that. What was your relationship like with your mom and your dad? What are some memorable moments with them? What did you learn from them? Good parents. They're giving, thoughtful. A little out to lunch, you know. They were workaholics, so it was hard to get a lot out of them. And my dad was kind of an angry dad. I think he just had, like, a weird childhood, and he's just trying to make it, and he's trying to provide, but it's hard, and we live in this horrible neighborhood, and we're getting robbed all the time. So, life was kind of coming down on him all the time. So, then he'll take it out on you or whoever, or he would snap. But great parents. They cared. They put us first. But there wasn't a lot of... I don't know, you ever go to a friend's house as a kid, and there's a picture of a ski trip, and you're like, ski trip? What the hell is that about? It wasn't a lot of that. And smart, very smart people, but I don't know how well they were at socializing. So, you never bonded with them on a deep human level? Some bonding, but rarely deep. Yeah, it was just almost coworker. Hey, cold out, huh? What? It's cold out, huh? Oh, yeah, like that kind of stuff. Yeah, yeah, yeah. Gotcha. Get there a little bit, but my parents would... I hope they never say this, but they would do a thing where... My dad especially would do a thing where he would... He knew how to cut you down right to the bone. And so, after a while, you're like, I'm not even gonna interact with this guy, because he can get you so well. One time, we were at a Thanksgiving, some kind of family event, and all the cousins are there. And I remember I was holding court. I was a young boy finding my comedic legs in this weird, tumultuous sea we call a family, and I was killing. And my dad comes out, and he goes, what are you, holding court? And I was like, and I felt like I was this big. I just shrunk down. He just nailed it, because in my head, I'm like, I'm holding court. Look at me. I got the whole room. And he goes, what are you? What are you, holding court here? Like, who the hell do you think you are? And I was like, he's right. I shouldn't be holding court. Who the fuck am I? I'm nobody. So, stuff like that. Stuff like that. Was he aware of that, you think? He wasn't. He wasn't. I don't think he was, but... Do you give parents a pass when they're unaware of the destructive? Is it better when they're unaware? Because it seems like that's the way. That's true. That's the way parents often fail, is they're not intentionally malevolent. They're just like, clueless. Yeah. It's a bittersweet thing, because you're like, well, okay, he's not malicious. He's not trying to hurt me. But also, he doesn't know he hurt me. I don't know. It's tough, because if he was trying to hurt you, I guess that would be worse. So, you're the fully baked Mark Norman cake at this point. Yeah, it's a shitty cake. Do you... Fruit salad. You know, the sense of self-worth you mentioned. I think in your comedy, there's a sense like you hate yourself. You think? I didn't know if that came through. Shit, I was trying to hide that part. God damn it. I mean, when you, in the privacy of your own mind, are you able to love yourself, or is it mostly self-hate? Jeez. What happened to this podcast? I didn't know it was on Dr. Phil. Dr. Phil. I thought we were going to talk about engineering and climate change and rockets. We'll get there. Okay. Starts with love, goes to rockets. All right, I like that. I like that's a t-shirt. What's the question? Sorry. Do I feel love? No, no. I love myself. Yeah, yeah, yeah. So, are you... This engine of being self-critical, of just being constantly anxious about how the world perceives you, these kinds of things, is this something that you just go to for comedy, or is this who you are as a human being? I think I don't want to explore it. I think I get around it. I tap dance around it, but I get it out a little with my act, maybe, because I can't do it. I'm not doing it in real life, so I'll get out this no love, not loving myself. I don't know. Who wants to love themself? Everybody always like, you got to love yourself, and then when you meet somebody who does love yourself, you're like, I fucking hate this guy. Don't you hate the guy who's upset? I'm great. I'm awesome. Life is good. You're like, ah, this guy sucks. I'd rather an insecure guy. So, maybe I want to stay insecure. Maybe I don't want to find this love for myself. Well, okay. So, self-love, just appreciating who you are, or appreciating the moment, or being grateful, doesn't have to express itself by the guy saying, I'm awesome. True. It's more just like humility. It's just like walking calmly through the world, and just being grateful to be alive, that kind of thing. That's good. And being appreciative of all the accomplishments you made so far. I say all this because mostly I'm extremely self-critical in everything I do. Yeah. And I kind of enjoy it. I think it's a nice little engine that it makes it fun. It makes life fun, because it's like, if you hate everything you do, like you've done in the past, that gives you like, all right, we can do better. Yes. But that's the key, is making yourself critical. Always trying to get better. I could change this. I could tweak this. I could improve this. When you just go, I hate that I do this, I suck, you just shut down. So, that's the key, is always being productive with the criticism. Yeah. And the basics of life, I'm just like grateful for it, to be alive. That's nice to be a couple of that with self-criticism. Two legs, again, the hairline, the hog, the muscles, the world. You got a good brain on you. I mean, you're lucky. You're in the top, you know, most people are fat as shit at Burger King right now, hitting their kids. You're in a Ramada hotel, sitting with a low-level comedian. For the record, I ate McDonald's last night. Oh, all right, well, you're human. Well, just so you know, this is not me defending, I'm not sponsored by McDonald's, but I mostly eat meat, and there's nothing wrong with the beef they have. It's actually one of the easiest ways late at night to— I think it's horse. I don't know if it's actually cow. It's actually rats, yeah, you're right. But hey, it's just meat. I'm a meat guy myself. They say in 20 years we're going to look back and go, can you believe people ate meat? It's going to look like somebody like slavery. Yeah, there's some ethical, difficult things with factory farming. Yeah, so let's ride it out now while we still got it. And now it's on record. Tom Waits said something about New York. You like Tom Waits? I think he's underrated. I think he's got great quips and quotes. Check him out on YouTube. He's got some montages and super cuts of him being hilarious. What does he say about, I'd rather have a bottle in front of me than a frontal lobotomy. That was the one. That was the one that sold me. I was like, this guy's awesome. Yeah, but his music, because he's just a genius musician. Yeah. Anyway, he was talking about New York, and I was walking around these— I'm in New York right now, we're in New York right now. It's still a magical city to me. A lot of people are quite cynical about it, about the state of things, but— Rogan. Not like Michael Malice, like a lot of friends of mine. They're just, a lot of folks, I mean, San Francisco, New York, there's something about the pandemic where people have become quite cynical about the place they are, and they try to escape. It's interesting. I mean, they're asking some difficult questions about what they are in life. They're having like a self-imposed midlife crisis. It's good, I think, for everybody to go through this process, but I think, I hope New York reemerges— It will. —as the flourishing place for the weirdos. Anyway, Tom Waits said, New York, of course, is to be in endless surreal situations where a $50,000 gunmetal Mercedes pulls up in a puddle of blood and outsteps a 25-carat blonde with a $2 wristwatch. Woo! And he keeps going on. So it's like a— That's like bars. He's like a rapper. Yeah, yeah, yeah. He's good. But basically, just the absurdity of it all. Lots of money, lots of weirdos, degenerates, and dreamers, and the whole mix of it. Do you think, do you think that's an accurate description of what New York is today? Like, is there still a place for the weirdos and just the interesting artists, the edgy, the comedians, the creators, the entrepreneurs, as opposed to Wall Street, as opposed to rich folk, and then hopeless folk? Yeah, I think it's definitely changed a lot. There's a tiny corner for us weirdo artists. New York used to be where you went to make it as a painter or whatever, a comedian or a singer, and there were all these dives and shitboxes and all these places you could go. And now it's more Pink Berries and Subway sandwiches and Chase Banks. So it's definitely lost a lot of its creative edge. It's just money. Money keeps coming in, and now you see all these comedians move to Nashville, Austin, Denver, whatever. So it doesn't have the power it used to have of like, you gotta be here if you wanna make it. That's definitely gone. So that hurt the city a lot. The city is way more soulless. When I moved here in 07, I mean, not only did I get mugged three times in the first year, but it was a hub of like, it felt like things were happening here. It was an energy, it was electricity. And we still have the electricity, but it's also maybe just because there's Times Square, there's Soho, there's Wall Street. So we got the staples, but there is a little bit of that. It's almost like a marriage. Like, yeah, we're in love, but it's not as passionate as it once was. That's how I would equate New York. What gives you hope? You're pretty hopeful about it, though. I'm hopeful just because I know it's magical, and I think it has to be. I mean, it's the epicenter of America. This is where the immigrants came, and this is where the stock market is, and the entertainment industry, a lot of it is here. So I think it's gonna happen, but something like the bottom has to fall out, and then people have to move back here and all that. So something, the corporations are kind of fucking us. They're just buying everything. Well, that's true for everything. It's true for Austin probably as well. People are just buying out land and all that kind of stuff. You always hear of Hemingway and Dali, and all these guys went to Paris in the 20s or whatever that was. I get it now. I just feel like, why do these guys go to Paris? Why do these artists? And now I get it, because it's freer there. That's why Austin became that Paris, where everybody's like, I gotta get out of LA. I'm going there. But we came back from that. The 70s were wild, and 90s were cool. So maybe it'll come back. Might just take a decade. Well, that's how stories are told. There's always pockets of Paris within New York. True. There's just an opportunity to let your weird flourish is there in New York, I'm sure. It's there. You gotta find it. Before it was front and center. What's your favorite thing about New York? What kind of things just like... I mean, how long is this pod? I could go on. It's too much to put into one hour. We've got other questions. But I love that one neighborhood is wildly different than the next. I'm in Little Italy, and then you take four steps, now I'm in Chinatown. And then the history there, and then the stories, and the food, and the culture, and all that. And then you go 10 feet over here, and now you're in Brooklyn, and this is insane. It's a whole other world. And it's almost like a little America in one city. And it's great. And just the fact that they pulled it off. Fifth Avenue goes way up, and you're like, there's a billionaire's house next to a hobo. And then this is a black guy who's fighting with a Cuban guy, and an Asian guy's trying to get in the middle of them, and the cabbies from the Middle East. And there's so many beautiful women here, and there's so many brilliant minds here. And the pace is great. It keeps you moving. I mean, it just, you can't beat it. And the city will fuck you in the ass, too. Don't get me wrong. You land at JFK, and you're like, oh, God, I got mugged. My Uber driver called me a homo. I stepped in human shit. Where the fuck am I? So yeah, it's bad news. But that bad news, it's almost like the bullying. It kills you in a weird way, but it makes you stronger, and you build more layers, and layers, and layers. That's why some new guy, some hayseed from Milwaukee shows up. You've been here 10 years, and you go, let me help you out, because you got addressed. You're going to get your ass kicked for six months. But I know the rope's a little, and I think you need a little of that. If the treadmill's not on, you're not going to run. New York, the treadmill's on. So it just makes you run, and it makes you better. And look, it wears on you. You probably lose 10 years of your life living in New York versus Indianapolis, but it's a better life. Have you seen 25th Hour? Yeah, it's been a while. Spike Lee joint. Yeah, Spike Lee joint. I mean, Ed Norton, there's a whole monologue there about New York. Oh, that's right. They're talking about just, he has a mix. There's melancholy music, I think, or just a melancholy feel to the whole thing, but there's an anger and a disgust with the city. But through the anger and the disgust comes out a love for the city. Same with, was Taxi Driver in New York? Oh, yeah. It's gorgeous. Crazy. Yeah, so there's something about that. What is that? What is that grit of the city that pushes you down? Well, that's the beauty of the city is it's this tribal human nature, like the sex shops and fistfights and racism and all this tension, but yet it's the epicenter of technology and finance and sophistication on Fifth Avenue. So you get that juxtaposish. It's kind of like in Boston. You go to Boston, they got MIT, they got Harvard, they got all this shit. And then they got the fishermen, the blue collar douchebags, the Irish guys, the immigrants, you know, and you get that mix of like insanely smart with wicked pisser and these two worlds and that's a good thing. It's like when a black guy fucks an Asian lady, that's a good looking kid. You get a mix. You know, we're mixing two totally different things are coming together and it makes it like peanut butter and chocolate. Peanut butter and chocolate. I've never tried that. What? Maybe I have. What's that about? I'm talking about Reese's. Like Reese's, yeah. Oh, it's the best candy. Yeah. Without the fakeness of LA, without the kind of without the kind of, the facade. Yeah, LA's tough. What's the difference between LA comedy and New York comedy to you? I think one place you kind of go to make it and be discovered and be loved and one place you go, you can get all that in New York too, but I think in New York, it's more of a school, a bootcamp of comedy. Let's make great comedy. Let's make original comedy. Let's watch the other guys and gals who are at the show at the clubs and learn from them and try to hang out with them and absorb some of them. In LA, it's like, when am I on? I'm next. Get out of my way. I'm the star here. I'm a bigger star than you. Oh, this guy's actually a big star. I got to outwork. It's a lot of that instead of like, damn, that was funny. I got to be that funny. Damn, I wish I had a joke. And look, I don't want to speak for LA comics because there's Bill Burr, Anthony Jelzilek, these brilliant LA comics, but they all cut their teeth in New York, just saying. Then they moved to LA. That's a good point. Ali Wong, all these people, killer comics, but New York, started New York, moved to New York. There is something about comics that stay in New York for a long time, though, like Dave Vitello. Oh, you know about Dave? Yeah, yeah. He wants to do this podcast. He does? Yeah, I'm a huge fan of Dave Vitello. Wow. Yeah, he's the king. He almost like he doesn't want to make it. I don't know. I mean, you probably know him, but it feels like you just, maybe it's romanticizing it, but you're like, you almost just love the art of comedy, of like becoming funnier, crafting the jokes, becoming funnier than the other comics, like competing with each other kind of thing. Not over like money or fame or any of that, just purely the comedy of it. Totally. That's Dave. That's him in a nutshell. He's like that guy in the movies in the 80s, action movies, where they're like, they go up to a creek in Montana and some guy's living in a cabin and he's sharpening a stick and they go, the Russians are coming, they're invading, we need you, you're the best commando. And he's like, I gave that up, man. I'm done with that lifestyle. But you're the best, we need you. And he has to suit up eventually. He looks at a picture of his dead wife and he goes, fuck it, I'm going. And then they fight the Ruskies. But he's that guy. He just is gifted. He's got a gift from Allah and he's the best. Yeah, a lot of comics give him props. It's always surprising to me. It's surprising to me because he hasn't really made it big. He did. In the 90s, he was huge. He had his own TV show. He was the boy. Yeah, yeah, that show was awesome. But I mean, as big as I think he deserves to be. Well, that's art. The mainstream shit is always the worst. It's like McDonald's versus some hole in the wall. I know I'm shitting on McDonald's again, but it's good. And you know, certain comics we could name are good, but the delicacy is going to be less talked about and less household namey than the mainstream hacky shit. Yeah, it's funny because he hasn't, I think he was on Joe Rogan's show once, maybe? Yeah, once or twice. And he was with somebody else. Jeff Ross? Yeah, he met him with Jeff Ross. Oh yeah, because they did that like two mics thing. Oh, with mics, yeah. But he's the quickest guy. There's no one funnier. Yeah, yeah, him and you, you're super quick. Your recent appearance on Rogan was hilarious. Oh, thanks. Just so fast. You were on with Ari and... Shane Gillis. Shane Gillis. Yeah, that was fun. We're going back in January. I don't know when this comes out. This has never come out. Neither will you. We're having fun. Yep. All right. So what does it feel like to bomb in stand-up comedy? Like to fail? Maybe the psychology of it first. Like, just take me through it. Because you were talking about being outnumbered in a fight, just being beat up. Very similar. By the way, this is like a no eye contact off. Yeah. We're both uncomfortable with the cat. Yeah, it's great. It's kind of nice to be with my people. But yeah, it's fun. Do you need a sheet of paper to look at? I'm going, I got a good sweet spot right there. Nice. Yeah, it's a nightmare, but it's part of it. It's the validation too is the worst part. Because whenever you do comedy and kill, you can be a great comic. But even David Tell, these brilliant guys, you feel like you're getting away with something. I don't have a day job. I'm telling jokes for a living. I'm talking about my dick up here and they're fucking loving me and they call me a genius and all this. I'm talking about my sack. And it's great. It makes people happy and it's funny. But that bombing, when you bomb, your first thought is like, yeah, you're right. At first you're like, fuck you guys. What, you don't like this shit? And then you just start going in. You're like, yeah, maybe it isn't that good. Maybe they're right. I do suck. I knew I sucked. I should become a mailman, you know, and it stinks and you feel alone and you feel like you wasted their time. And then you're like, what was I thinking? I could be a comedian. What the fuck? Who am I? Eddie Murphy? What am I doing here? So it's a lot of just spiraling out of horrible thoughts. But I also love that it hurts so bad. Bombing fucking hurts because now everybody doesn't do it. I think a lot more people could do comedy probably and figure it out. But the bombing is so brutal that it keeps... One time I went to Minneapolis. I was like, this is a great city. I mean, it's sun is shining. Why isn't this city packed? And they're like, because the winters are so bad and we love it because it keeps everybody out. And I feel the same about comedy. The bombs are so brutal. I've had bombs where I'm in bed. I'm just staring at the ceiling like, what the fuck was that? Like you have PTSD. I bombed at an arena once, 20,000 people. I did 30 minutes to silence. I guess it's not just like one joke, fails. It's like they start piling on like it's irrecoverable. Yes. And one joke failing is very common. Like a lot of audience don't even notice that bomb because you get so many jokes in a row, you can sandwich a good one, then a bad one, then a good one. But when you bomb, it's almost like they chose, we don't like you. Nothing you say will redeem yourself. And it's hard to get out of. It's like being pulled down by your hair. You can't get back. I can't win this fight no matter what. Can you like get him back by acknowledging like the elephant in the room? That helps, but they're still going to go, that was funny when he made fun of it, but he sucks. He still sucks. He still sucks. That's the worst part. You're going, no, this is good. You guys just don't like me. Just because you don't like me doesn't mean I'm bad. Yeah. I like going to open mics a lot. Just listening because first of all, I think the audience in the open mic, at least the ones I've been to, is mostly I guess other comedians or at least people who don't seem to want to laugh at anything. And so I just love it because it's human nature and perseverance that is best. But here's comedians, like clearly, this is mostly in Austin, they have a dream. Like why would you get up there? Right. Maybe some weird New Year's resolution bullshit, but for the most part, it's people who want to be comedians. Like a lot of the open micers are people who clearly have done this for quite a long time already, like at least a year or two, maybe five years. And they're often not very funny. And just bombing in front of an audience of like 20, where they're just sitting there, like almost like mocking them with their eyes, or maybe, and I don't know. And they still push through. They still like as if they're doing an arena and everybody's laughing. They still got that energy trying, almost like to an audience that doesn't exist, like an audience of their dreams. Because I guess you have to do that to keep the energy of the act going. And it's just so beautiful to watch them try it. And also what happens, open mic, I don't know, five minutes, whatever they do, they walk off and then walk back offstage. Oh, nightmare. And like you can't, who do they look at? Like what do you look, do you make eye contact with people? Do you- You look at your phone, you look at your feet, you just zone out. You kind of go white. You just hear white noise and go out. It's tough. But you need a little delusion to be a comedian. To get into it, it takes a little bit of delusion. Like you think you can do this? You got 10 years ahead of you of hell and you're up for this? And most comics, we see a horrible crowd and we see our friend bomb and we go, yeah, he's bombing, but I'll get him. I'll get him. And then you don't get him. But that's human nature too, is like, they don't like him, but they'll like me. And you need a little of that to keep going as a comedian. But you don't want too much delusion because then you're a psycho, but you need a little. Well, the psycho could be good for a comedy. That's true too. I love psychos. I mentioned to you offline that I talked to Elon and we talked about doing standup that he's thinking maybe do a few minutes of standup. I was going to say, if you need a coach, Elon, I got you. Well, maybe you should move to Austin to coach him full time. Ah, hopefully he can fly me in. So what advice would you give to somebody who wants to try to do five minutes? Like the early steps of trying to go to an open mic and say something funny? Well, that's the irony of comedy is, I don't know if it's irony, but it's like the beginning is the hardest part. Usually the beginning is the easy part. Hey, I'm playing this level of Mario. I'd start, I'd jump over one Koopa Troopa, whatever. And then the end is like, Jesus Christ, I got 30 guys coming at me. Comedy is the opposite. The beginning is like, it's a gauntlet. It's just obstacles. And it's like you said, open mics. I watch these famous comedians on Netflix and you go, this would all bomb at open mic. They're killing in Radio City. This would bomb at open mic. That's the weird part. So it's almost like you have to go through hell just to get to the promised land. And I would say, rehearse the shit out of it because you're going to get frazzled up there. Everybody thinks, oh, this is good material. But you also forget about the other part of delivering it, having confidence, being likable, having timing, having a cadence, figuring out who you are, figure out what the audience thinks you are or how they perceive you. Because you can go up there and say all this, but they go, that's the guy, he's clearly gay. Why is he acting like he's not gay? That's all. Now they're not listening to the joke. So you got to know how you look. And it's just repetition, repetition. And bombing is not failure. That's what you got to remember. I mean, look, if you do a killer hour and then you take it to Netflix and bomb, you fucked up. But bombing is not failure. It's just data. It's going, oh, okay, I got to retool that. That didn't work. Something's wrong there. I missed a word there. So you got to treat the act almost like ingredients in a cooking, in a dish. Oh, I put too many eggs in. Take an egg out. You got to treat it like that. And look, when you pull a bad cake out of an oven, you go, I fucked up. But it doesn't hurt your feelings. But when you bomb and fuck up, it hurts your feelings. So you got to factor that in too. Your feelings are going to be hurt. And just almost be a robot and just keep going towards that open mic. You know how scary an open mic is? Bombing sucks, but bombing in front of other comedians is way worse. Because they know what just happened. And they could have saved you and they didn't. So it's way worse. And they're going to be your quote unquote friends for this journey. Yeah, no, these are evil people. Twisted, fucked up people. Can you tell, like, in those early days, let's just talk about that, like, the open mic level, that a joke is going to be good on paper? Like, I'll give you my experience, because maybe you could be my coach in this particular moment. So like Larry Nassar. That's fun, huh? Joking, everybody. I hope nobody takes it seriously. I now have an amazing team of folks who help me with editing, and they're now currently sweating. You got to leave that one in. That was quick. Yeah, that's pretty good. I'll eat that one. That was good. All right. So, you know, going in front of an audience, just even to give a lecture terrifies me, which I've done. But open mic, I mean, that to me, perhaps that's why I like going to open mics and listening, is because I just, it terrifies me so much, that idea of going up there and bombing, I mean, it's scary. And to do even like one minute, to be honest, is scary, and five minutes. I'm also, I've watched enough open mics to realize that five minutes is a long time. I mean, it depends on your comedy, but if you're doing fast stuff, five minutes is a really long time. Oh, it's eternity. I guess with a long story, two is a long time, because if the story's not working, you're building up to something. If the story's going to fail, you just spent all that time telling the story that completely went flat. Completely. Got nothing. I guess if you have a series of jokes, you can at least try to recover and do the Mitch Hedberg thing where like, all right, I'll cross that off. Yeah, yeah. Well, I'm able to, I've tried to write a few things, and I'm able to tell that it's really bad. Well, that's better than most. Most people's egos kick in and go, no, this is good. No, see, I'm able to introspect that. It seems funny. I mean, I guess the thing I'm looking for is original. There's easy stuff that you think is funny, but to me, originality is the thing you should be looking for, because then that's what actually becomes funny. Or rather, if it's original, even if it bombs, that feels like more a beautiful art creation that you did. At least you swung for it. You did something unique. Even with open mic, your first five minutes, there's so many, just go to enough open mics, you'll hear all the, there's a list of jokes that you can just go to. First of all, you can make fun of the fact that you're at an open mic, that you're doing this the first time and so on. You could do a lot of stuff where you make fun of your appearance in some way and so on. But yeah, you could do that. That takes actually, that's way harder than people realize to do in an original way. Yes. To present who you are as a person very quickly, enough to then put that person down in front of everybody else. So you have to reveal the- The audience is like that, because they go, he knows what we're thinking. Yeah, exactly. But do it again in an original way. And so when I'm trying to write stuff, not that I've tried long, it's like 30 minutes, but enough to see like, oh shit, to write something original is really difficult. It is. But do you got a bit? Anything? No. You didn't write any one line or anything? For this? No. Well, just in general, ever in your life, ever written a joke? Oh yeah, yeah, yeah, yeah, yeah. Oh, okay. No, but I don't have anything in my mind popped up. So the jokes that I've written have more to do, like, for some reason my mind goes to like dark places. So, you know, and not actually dark in the Mark Norman dark, because you go really dark to where it's like almost absurd. My natural inclination is to go to like a dark historical place like Hitler and Stalin. And almost go to that place and then talk about something absurd there. So like, don't go all the way, I don't know, I don't want to give examples because it'll be clipped, but the Mark Norman style, look it up, he has a special on his YouTube, that kind. I want to almost explore the dark aspects of human nature more kind of connected to actual historical figures. That's the inclination. Like, I don't know, Nature's Metal, the Instagram channel that explores like the darkness of nature, like something there. See, that's good that you already know that you've kind of gotten to the core of your comedy already, and that's interesting. That's a step ahead. Yeah, I can hear, with most things I do in life, I can like hear the music from a distance, like in myself, like, okay, if you have anything, this is the direction it'll be, without actually knowing exactly all the steps. And that's a nice motivation to be like, all right, well, if you do this for a long time, maybe you'll have a chance to get there. But you have to, that's where it's a feature to be super self-critical, I think. Yes. But then that's why it's fucking terrifying to walk up to a stage, stand there, and probably forget everything. Yeah, that's the other part nobody thinks about. Just goes right out of your head. You go fight or flight. It's ugly. My first years were horrific bombing, horrific stammering, horrific not remembering the punchline. Like, you got to, maybe you got a setup going and they're kind of on board and you're like, ah, how's that? Camera out goes, and you just hate yourself. It's a nightmare. But you've already kind of, maybe if you haven't done standup or whatever, but you kind of know your voice. And that's pretty advanced. So you're not trying to be somebody else. I guess, yeah, just for having done like podcasts and lecture and so on. That helps. I've already done some of the work of the standups do, which is embarrass yourself in front of others for prolonged periods of time. Yes. Yeah. So I'd done that without actually developing the funny. Right, right, right. But maybe the funny just is not that difficult to develop. No, it's super difficult, of course, but I mean, maybe the essential work of a standup comedian is just the embarrassment of like finding who you are. Yeah, that's a part of it for sure. You know, in the beginning, you're like, water bottle. What's funny about water bottle? I'm a funny guy. I can make this funny, but that's not it. You know, it's your shit, your shit, like your dark stuff. For me, I tend to gravitate towards dark, but in a weird way where, you know, people say like, hey, don't objectify women. But then they go, Caitlyn Jenner's beautiful. And you're like, well, wait, I know something's off here. Why can you objectify her, but not the supermodel? So what's going on there? And I like to play with that. So I have this joke where I say, Caitlyn Jenner. Oh, women go, Caitlyn Jenner's beautiful, beautiful woman. I go, well, you look like her. And they go, fuck you. And you're like, there's a lot of truth there. But I like exploring that kind of, oh, you're trying to get one over on me, or you're lying to yourself, or what are we doing here? And I like that kind of comedy. I don't see color. Well, I'm black. No, you're not. You know, that's fun, because you're lying. Yeah, okay. So like, big time comedians, such as yourself, don't like to think of yourself in this way. But yeah, this is like, where you over philosophize comedy. But yeah, definitely. It seems like comedians. Don't say important. Nothing worse than a comedian who thinks they're important. Yeah. So I was going, I was trying to find, as I was trying to say these words, I realized how cliche it is and how uninteresting it is. So I'm going to just, but there is something. I'm worried this whole thing is uninteresting. I'm like, who cares about comedy? There's like six comics on the planet. Nobody cares. Okay. I trust you in the pilots, see? You know what you're doing. You got listeners. They've tuned out long ago. Oh, we gotta get Dan Carlin on here, huh? Is he around? Yeah. We're just going back and forth on Twitter just now. He's a huge fan. He was on here before. He'll be back. I've been actually really trying to volunteer myself aggressively with Dan Carlin for like a Russian episode where I could speak Russian. There's certain documents, I talked with Jaco about this too, certain things. I mean, I just love the challenge of bringing Russian documents that I can read in Russian and then can translate and can try to capture the depth of the writing in the Russian language and communicate to an American audience. So much is lost in translation. Like there's so much pain and poetry in the Russian language. It's just connected to the culture. Every language, not every language, but many languages are uniquely able to capture the culture of the people. I mean, in some way, they're the representation of the culture of the people. And so Russian is definitely that. It represents the full history and culture of the 20th century with all the atrocities, all the broken promises, all those kinds of things. Norm says Russian literature is the most tapped into human existence than anything else. Norm. McDonald. Yeah. Big Russian literature guy. Dostoevsky, all that shit. It's funny that there is a gap with comedians too. There's a culture of Russian comedy, like standup comedians that are totally- I don't know these Russians. I mean, I don't know today. I mean more from the 80s and 90s. Yakov. That's all I know. So there's like a forced- I've never seen you that offended. No, no, no. There's a different... There's like the kinesiologist, and there's like the kinesins, and there's the edgy- Is that Russian? What do you mean? Wait, I thought you said there was Russian comics. Yeah, Russian comics. I'm comparing- Or style. I'm giving you like a style, a darkness, like that's the kind of people that kind of challenge. They give, again, this is to how important comedians are, is they give a voice to people where in the Soviet Union you really can't express your opposition to the government. And so comedians are exceptionally important there for just, I don't know, channeling the anger, even when sometimes it's not the actual opposition to the government. They're just channeling the anger, the frustration with the absurdity of life. When there's a shortage of food, shortage of jobs, the absurdity of the bureaucracy, like a top-heavy government, just all of that can only sometimes be expressed with dark, absurd humor. And that actually, why there's a culture of that kind of humor, you gather around the table with vodka, and all you can do is just talk shit and just- Be offensive, say horrible shit, ball bust. I mean, I make school shooting jokes, and people go, how do you do that? I'm like, well, maybe that's how I deal with it. How come I gotta empathize the way you do? Maybe we're different. All right, so now let's skip the whole open mic thing and crafting jokes. Oh, yeah, that's tough. Kerouac said, one day I will find the right words and they will be simple. When do you know the joke is done? It's perfect. You're somebody that does really sharp, fast jokes well. Oh, thanks. So there's somebody, I don't know who you see yourself in the same school as. You're darker and faster than Hedberg, I think, in terms of just, I don't know, the turns you take. Hey, thanks, I appreciate it. I think I got some Norm MacDonald and maybe- Oh, Norm, that's right, Norm. You know, obviously Norm, but Chris Rock was huge for me. Old, like, 90s Chris Rock was like, I didn't know you could do jokes like that. I always loved George Carlin and Groucho Marx and Bill Murray. There's so many different types of comedy, but when I saw the bigger and blacker bring the pain, I was like, oh my God, this is like, it hit me. So that was big. And then Norm's just like the funniest guy on the planet. So him being the smartest guy in the room, but acting dumb was great. So yeah, Chris Rock has that way of cutting to the bullshit, which I mentioned earlier. I like that cutting through the bullshit kind of style of comedy, because you kind of go, oh, I'm not crazy. That's what I thought, too. I was too scared to say it, but I thought that, and he's saying it in a room of people are laughing. Maybe I'm not an idiot. So that helped me. So it's observational, but not Jerry Seinfeld observational. It's like, look, going to the darker thing within society. Yeah, it's great, but I like him too, but seeing it, doing it about stuff like in your life, society. Yeah, race, gender, government, politics, all that kind of stuff. Exactly, exactly. Sex, human emotions, jealousy, whatever it is, that's the good stuff. How'd you feel when Norm passed away? Ah, that was a bummer, because he was, what, 61? And I just didn't see it coming. I watched so many hours of his stuff, and I met him, and he was like this comedic bar, like, hey, we got Norm. There's so much shit comedy. Then you see Norm, and you're like, this is next level. This is savant-type shit, and then to lose him is like, ah. Norm had 20 more years at least of just content and content and thoughts and his point of view, and we'll never get that, and that sucks. Yeah, there is something about artists. Like, Jimi Hendrix dying too early, it's like, you wonder. What was next? Yeah, what was next? But then part of it is like, it all ends for all of us, and it's like, walking away early is kind of admirable. It's almost like, I did a pretty good job. Yeah. I'm good with that, and especially the way he did, which is not telling anybody. I know! Nine years, his best friends didn't even know, and in this world of, like, victimhood, and I need clicks, and I need people to love me, he could have got, you know, canceled and yelled at and in trouble, and he could have pulled that cancer card, and he never did. I mean, the integrity on this motherfucker. Did you get a chance to interact with him? Like, what, how often did you meet him? I met him once at the Comedy Cellar, and we chatted for five minutes, and then he went on and did the Letterman set that he did, he was running the Letterman set, and sweet guy, nice guy, didn't know him that well, but I mean, he's just brilliant. And I also love a brilliant guy who does stupid stuff. That's a fun, fun little combo there. Like, silly guys who are actually brilliant also. You know, like, Louis C.K. is a brilliant comic, and he'll do a joke about farting on a kid, and you're like, that's great that he still finds farts funny, and he's also this comedic genius guy. I like that. Yeah. And doesn't really acknowledge the genius. Yeah, yeah. That's, yeah. I like smart people, they're silly. Yes, that's a good combo. Like, you said Elon is silly. Yeah, super silly. Yeah, that's great. Because we teach kids, like, hey, put that down, stop that, quit cutting up, quit horsing around. But maybe that's some kind of sign of brilliance there. Yeah. Being, like, childlike and silly is a kind of wisdom. I feel like those people are way wiser than the people that, no offense to me, wear a suit and take themselves way too seriously. No, but you got a spark in you. A little bit. You got a little, what's the word? Not elf. Imp. A little imp in you. Give that a go. You know what imp? Old Mischievous. It's like a little... Is that a Tolkien character? Imp. Yeah, might be. An imp is a European mythological being similar to a fairy or a demon. You call me a fairy? Well... Frequently. No, okay. Similar to a fairy or a demon. I feel like that's a big leap. Big leap. Yeah, that's not a great info bio there. Frequently described in folklore and superstition, the word may perhaps derive from the term imp, spelled with a Y, used to denote a young grafted tree. It's a little mischievous. You got a twinkle. You're this serious buttoned up guy, but there's a twinkle. There's a twinkle. Wow. And the audience can see the twinkle, and that's why you resonate, I think. I'm sorry. Deep analysis by Mark Norman. Psychological analysis. Okay, but then back to the crafting of the joke. You said Chris Rock and Norman McDonald. What, for you, how do you know when the joke is done? Are there some jokes that you're proud of? Wow, that's well done. Yeah, the joke is done. It's a tough question because there's so many different kinds of jokes. There's what we call a chunk, which is a big idea with a bunch of jokes in the middle of it, and then a big crescendo at the end. Or there's a one-liner. Or there's a tag of a joke that's also a joke. So the jokes come in different... Like I have a joke where I say, I met my girl on that Jewish app. What's that Jewish app called? PayPal. Nice. That's the hell. That's what the reaction you want from the crowd. But it's a fun turn, because you say your thing, and then I hit you with a misdirect. And that's what a joke is. A joke is basically me saying something that makes sense, but you didn't see it coming. And that's a perfect example of that. So that joke took forever to figure out, by the way. You had to go to different services like PayPal. What's funniest? Exactly. And I figured PayPal is funny because it has the word pay in it. It's also not really a good word. Venmo, PayPal. It just hits better. Yeah, PayPal is funnier somehow. It's funnier somehow. And that's the beauty of comedy. There's a weird little magic into it. You can get technical all day and formulaic, but there's still that little bit of fairy dust that you don't know why this is funnier. Or imp dust. Imp dust. Yes. With a Y. Okay. So you know a joke is done when it kills. And there's a roundness to a joke when you feel like this is buttoned up. This is done here. Is simplicity the right word there? Yeah. Is it like you're chopping stuff away, or are you adding stuff? What does it feel like? Simplicity is always the best angle. I mean, you can get real high concept with a joke and still make it work, but the simpler the better. I saw Dave Chappelle on stage once, and Chris Rock and Demetri Martin were in the back watching in awe. And Dave Chappelle, I can't remember the joke, but he said something about sex or women. And Demetri Martin goes, eh, it's a little easy. And Chris Rock goes, that's why it's good. And I remember hearing that as a young comic, like, ah, I'm getting this comedy lesson right here for these two titans. And so that was fun. Simple is key. So the easy is okay. That's such a weird... I think I remember reading or hearing Eminem say something about maybe the song Slim Shady. One of the songs, he's like, I knew it was going to be good because it got really repetitive and annoying very quickly, or something like that. I mean, that's the sort of the music equivalent of it's too easy. Like, if it's like super catchy, as a musician, you might get very quickly bored of it. Or like, as you're creating it, no, it's too easy. It's like, there needs to be some more complexity to it. I like complexity, but the best guys who are the ones who make complex shit look simple. Like, you ever heard that Ben Franklin story, where he's talking to his friend, his friend's like, I'm going to start a hat store. So he puts a sign out, says, hats for sale, $12. And Ben Franklin looks at it, goes, well, you don't need the $12, because all they need to know is that you got hats for sale. He's like, all right. So he loses the $12, makes a new sign, hats for sale. And he goes, you don't really need for sale, because it's a business. People can put that together. So he just goes, all right, he makes a new sign, it says hats. And then Ben Franklin's like, you know, you don't really need the word hat. You can just put a picture of a hat. And he made a new sign, which is a picture of a hat, and it helped the business or something. That's like some old wives' tale or whatever. But I think about that all the time when I'm writing. I thought this was going to like, there was no sign, it went like super nihilistic. Oh, maybe, maybe, that could work too. Like, as a comedian, so I'm a fan of yours, I enjoy, I really enjoy you in conversations. Wow, now? I'm getting nothing out of you. No, this is... All right, I can't tell. Oh, like emotion? You're tough not to read. I'm cold inside. I mean, just the quickness you have. Obviously, you're also a great standup comedian. What's your favorite medium to shine in? So you have a podcast yourself, an excellent podcast. Thanks. You're often the podcast guest. Yeah. Which is always fun to listen to, how you're going to deal with the different people. You're great on Rogan. Oh, thanks. What do you enjoy most? Podcasts are great because you can stretch out a little more, you can breathe a little. You know, with a standup set, I like to be like, boom, boom, boom, boom, boom. But podcasts are great because it's conversational. So you can be, it's almost like you're being funny with your friends. Whereas a stage is like, this is a piece, this is a presentation. But I think the podcast is great, but you don't get the reaction. Unless the host is laughing, you can't hear the guy in his car in New Jersey driving to work going, ah! Every now and then, I'll read a comment like, I spit out my coffee when you said this. And I'm like, but it's not immediate. You want the immediate. So standup will always be number one, but there's no better feeling than killing in a room of people who don't know who you are, strangers. You're in the middle of nowhere. You left your wife at home. You left your kids. You left your house. You're in the middle of bumfuck Dickville and murdering for these hillbilly nobody, whatever it is. And they're slinging their beers and cheering you on and they carry out and you fucked some fat lady and you leave and you get back to your hotel and you go, holy shit, what was that? No one will ever know about it. Just lost in the ether. That's the best feeling. Yeah. Killing in obscurity, as Bill Burr would say. Yeah, this is one of the things that sucks about giving lectures at universities or giving lectures in general is when you look at the audience, several hundred students, they all have a bored look on their face. My face now probably looks bored, but I'm actually excited to be talking to you. But there's something about a comedy called, maybe this is the contingent of laughter, but it gives people the freedom to just laugh, to remove that facade of, you don't have to pretend like you don't care. If you care, you can show it and you can have fun with it. Probably liquor helps a lot too. It helps, for sure. But there is a, especially, and that's why comedy I think is so popular right now, because HR is up our ass. We're scared of old tweets that might come back to haunt us. What did I say on that interview? Even people at offices are like, I put something on Facebook in 1999 that was about fat tits that I liked. Should I get rid of that? Even people say, there's no cancel, whatever. There is something in the air right now that wasn't there before. It's the video, I'm a Karen, I got caught at Trader Joe, whatever it is. People rat on each other now, everybody's tattletaling because they want the clicks. It's a horrible society we've crafted. But stand-up comedy gets you to come out, and now people do it at stand-up shows too, sadly, but it gets you to come out and let that inhibition down. Because we're all human, we've all had the fucked up thoughts like, man, that guy's fat as shit. It doesn't mean you hate the guy, it doesn't mean you hate fat people, it doesn't mean you're fat shaming, but you can't say that at the office. You can't go, Bob, you're fat as shit. You'll get fired for body shaming. But at the club, you go, that guy's fat as shit. And the crowd goes, he is fat as shit. And it's this weird cathartic thing, because all we do is tamp shit down. It's kind of like you ever meet a girl who's all prim and proper in the bedroom, she's like, put a lamp up my ass, whatever it is. It's because we got to get it out, we're all repressed in some way. So I guess what you're saying is comedy's important. Yes, callback. Well played, sir. What do you think about Austin? What do you think about the comedy scene in Austin? We'll talk about LA and New York. What do you think about what Joe's trying to create there? So I should say that the reason I moved to Austin, I have this dream of, it wouldn't be funny if I said this dream of becoming a comedian. In an audience, at least. Yeah, that's true. You know how I always said you can hear the music in the distance? I have this dream around robotics and artificial intelligence, whether it's a company, whether it's something else that was just pulling me to, I actually wanted to move to San Francisco and then all my friends in San Francisco said, no, it's the wrong place. At this time, the cynicism there is just not conducive to taking big leaps into the unknown, excited about the future kind of thing. And Austin was that, for me in particular with Elon Musk, but also just the energy that everybody had, including Joe, the excitement about the future. I don't care if Austin burns to the ground and it actually is a complete failure. Being excited about the future seems to be, like optimism about the future seems to be the thing that actually makes that future happen, makes a great future happen. So it's always cool for me to see Joe super excited about creating a culture in Austin, making it a comedy hub. I don't want to overstate it, but I think he really believes it'll be a very big place for comedy in the United States in general, in the world. And so just even believing that, that's powerful. You start to make it happen, that energy is there. Anyway, but that's for me from just an outsider watching. I should also mention for less of an outsider, more insider in the martial arts world, partially probably because of Joe, I'm not sure, like John Donahar, Gordon Ryan, the B Team, all those folks, those are, that might be gibberish to you, but those are like some of the greatest grapplers and martial artists of all time. So it's also becoming this hub of martial arts. I love that. The whole thing is just beautiful. Anyway, what are your thoughts about that scene? Well, there's a lot here, a lot of things to mention. One, I think Joe did do that to a degree. All these people, Segura lives there now, a lot of comics live there. He's opening clubs, other clubs are opening. I think it's happening. That's the other thing is people go, everybody's moving to Austin, Austin's the new hub. And then they look at their watch and they go, five minutes went by, nothing changed. It's going to take years, but everybody wants it now, now, now. What, Austin, there's no industry there? There's no Netflix, whatever. And you're like, yeah, I know, but it needs a minute. You can't just do this overnight. So people forget that. So it could happen huge, just give it some time. I mean, he's opening a club. I went and saw it. It's incredible. It's so perfect for comedy. It's every detail, it's incredible. But so it could happen still. I do think there's a little biting off more than they can chew with Austin because it's not that big. And it's spread out. I mean, yeah, it's not big. And the infrastructure is not quite there to support it. But it has a lot of, I'm comparing from the tech side, it has a lot of land to expand into. So it might become this... That helps. Like you're basically establishing, it's kind of like New York, you're establishing these whole neighborhoods. And you have the freedom to do that because there's a lot of space on all sides. Yes. Okay. So that helps. So again, maybe some time. I do agree with this, that new hope that's kind of built into human beings of like, let's go to America. Let's go to Utopia. We even have it with space. Let's go to Mars. We got to see what's over there. And it's just red, dusty bullshit, but you still got to go. So I'm with you on that about this new hope, this new land. And I think that is beautiful. And I think there's a lot of haters. I think there's a lot of naysayers who hate change, who hate anything new. And then I think you got to go, hey, that hurts. That sucks. But blow me, Dickless. I'm trying something. You're a loser. Stop hating on me. I mean, how many people hate Elon Musk? Yeah, it's hilarious. I mean, there's some of the criticism on Austin would be, it's like a fad. Like a lot of people are really people are excited about Austin. And somehow that's like, it's like when Green Day became famous, you no longer want to be a fan of Green Day. But to me, like this... Austin was already a cool town. Like every comic five years ago, it's like, oh, I got Austin this weekend. I can't wait. So it already had a buzz. But some people think maybe the buzz was the cool part. The fact that it was like this off the beaten path city. And now I get to visit it and then leave. But I think it could still be this comedy tech booming place. It just will take some time and people want it right now. Well, on the tech side, it's... It's already there? It's getting there very fast. So I mean, Elon's really pushing that with the factory. It's just a huge number of people are moving there with jobs. Like you're already starting. And then the opportunities to launch new companies is just incredible. I guess it's not right now. It's like within months, within a year, that kind of thing. But like, it's an opportunity to just start to build shit in a new place. And it's cool. It's kind of like, you know, go to Mars. It's like you get to start over. Yeah. And I like the hope aspect. I think that's huge for people. And I'm all for it. I hope it works out. I don't know if it will. But I don't know anything about economies and city planning and all that shit. So it might be too early to say, but I hope it works. Are you still talking about Austin or Mars? Austin. Mars is... There's nothing there. There's no vagina there. There's no food there. There's no water there. I don't know. It seems... I get space travel. I think it's important. But I don't know Mars is really going to move the needle. So what are your thoughts about Elon Musk and SpaceX and launching rockets into space? I mean, it's all good. Because you could say, hey, we could just feed everybody. And it's like, yeah, that's true. By the way, these guys give a ton of money to like philanthropy shit that nobody cares about. By the way, you know, it's weird. Like he can feed the Nigeria and with pocket change of his and you're like, well, maybe he has. You know, like I heard Bill Gates gave back so much money, he saved 6 million lives. But that's a reverse Holocaust, by the way. That's pretty good. What have you done? You're a barista. So, you know, I just think space travel is good because you learn about the place you're living in from going to space. It kind of helps you learn about this more. You could say, what's the point of going to this other there? But it does help, I think. Yeah, doing difficult things in the engineering space seems to be a way to develop like as a as almost like an accident as a side effect of doing a really difficult thing in a team of brilliant people. You develop things like the Internet. And you could argue that the Internet maybe is not so good for society. No, I'm just kidding. It's good and bad. Yeah. But it's like a pull up. You're trying to get your bicep going. But hey, before you know, you got decent forearms. But you weren't working on the forearms. You wanted to buy, but you got the fore. And I think that's kind of what space travel is. I like how this like pivoted into a workout routine advice. I'm trying to get an analogy going here. All right, they work pretty well. I'll take it. All right. What are your thoughts about, since I'm a robotics person, I'd be curious to see like what do you think about the space at all about, first of all, autonomous vehicles with Tesla Autopilot and Waymo self-driving car. I'm not sure if you're familiar with all the autonomous vehicles and so on. So those are robots on wheels. And then there's also legged robots. So next time you're in Austin, you get to meet some of the legged robots I've been working on. And I find those kind of a fascinating way to explore the nature of intelligence in our computers, but also explore our own intelligence and also explore our own, like what makes us connect to other living beings, whether it's dogs, cats, or other humans. Like there's some magic there that's beyond just intelligence. And like when I have the robot dog, there's some aspect to it that, I don't know, brings me joy in a way that a dog does, in a way that a good friend does. Really? Oh, that's interesting. And I'm not sure if that's some kind of anthropomorphism, like where I'm projecting my hopes for what this thing is. Maybe a little of that. But it's kind of built in. I mean, it's just a source of joy. Maybe it's connected to the fact that there's just like a loneliness within all of us, within me, and it's just nice to have other things in your life that move, that recognize you, that kind of thing. I mean, I suppose it's nice to even just have a plant. Yeah, it is. Plant goes a long way. You see a guy with plants in his apartment, it changes the apartment, because they're alive. You gotta water them. You gotta put sun on them. So yeah, I think there's something there. And I think you can see people's reactions when you show them advanced technology, like these dog robots or these robots that dance and shit. People are like, what the fuck? It hits home in some way, whether it's fear or you want to fuck them, clearly, whatever it is. But it does connect with you in some way. So I'm with you. And I think, this is why I don't think robots will take over. You always hear that, robot, they're making them too advanced. They're going to wipe us out, blah, blah, blah. If robots get at human emotions, that is scary, because they could get mad at us and kill us, and they're stronger, and they don't need sleep, they don't need food, they don't need water, they don't get jealous. But if they have emotions, then I think we can dominate them. Because who knows emotions better than us? We've got thousands of years of evolutionary, emotional bullshit. We can go, hey, robot, I heard your wife fucked that blackened decker, huh? They're going to crumble. We can bully them. Emotionally manipulated robots. Yes, that's when we'll win. Right now, they could kill us. They could just, we'd all die, then we shoot them back, bing, bing, bing, bing. That's no good. But if they do get emotions, then we can go, hey, you look like hell. What is that, a rusty bolt? Hey, you're dropping some oil there, you know, you loser. I think we can win if they do get emotions. This goes back to your father being able to undercut you with a single word. You're right. Yeah. So we're the creators of the robots, and then the robots will just, you would say the exact thing where the robot would be like, that son of a bitch. And then it goes back to his hole and just sits there miserable. Right. Yeah, hardware looks more like software to me. You can't get it up. Yada, yada, yada. Yeah. But I'm not worried about robots. And I think self, what do you think about the self-driving cars? Is that just wiping out the horse and buggy? Isn't that just progression of technology? Yeah. So I don't know if you've driven in a Tesla, for example. I have. I rode in the past year. I didn't drive it. Yeah, there's several stages in that. I think the problem is way harder than people realize. And for quite a while, it'll just make driving more pleasant. It'll make it less stressful. It'll take over some of the boring bits for you. It'll make it easier. Like, there's something that happens actually when the car is driving for you in the following way. Like, it's staying in the lane. It's keeping distance to the car in front of you. Maybe it's changing lanes. It allows you to relax a little bit. You still have to be alert, but you become like a passenger and you get to take in the world. I mean, somehow that's more relaxing without making you necessarily bored more. It energizes you more. So I just think it makes the driving experience more pleasant. But when you actually fully automate cars, when you can just completely tune out and start reading a book or go to sleep, that might change society in ways we don't even understand. Because you'll have... I mean, it'll probably change the nature of roads because the cars... Because now you can be super productive. And so it no longer quite matters to you as much how long it takes to get from point A to point B because you're not wasting that time. You just continue working. It's like public transit that comes to you. Exactly. And so there will be maybe less roads and bigger roads, and it'll just change the nature of how we get from point A to point B. I think you're right. But then couple that also with the fact that we seem to be more and more comfortable existing in the digital world. Yeah. So maybe we won't want to go outside more and more. We'll just interact with each other virtually. And I don't mean Zoom meetings. I mean just in other ways that's more fulfilling than a Zoom meeting. But then maybe not because there's something deeply uncompelling about Zoom meetings. Podcasts that are remote, unless they're super information dense, at least to me as a podcast fan, kind of suck. They suck. There's no connection. It goes back to the dog thing. With the Zoom, there's no connection. Yeah, and we're not... I don't understand why we're not even making eye contact. I know. But it's something there. It's in the room. There's pheromones. And that's out of our understanding probably. It's just some kind of weird biological... You ever have Cheerios in a bowl? The Cheerios tend to go together. You see a cluster of Cheerios. They're never really hanging out on the other side. And that's kind of how people are in real life. I wonder what the physics of that is. So they come together and they stick. It's something with molecules. I don't know. I can't remember what it was. But it was fascinating. And I think that's how people are. And I think you try to write a TV show or craft a movie with your team. Zoom, nothing there. It's like phone sex versus penetration. One day you'll learn that. I know nothing of either. I look forward because I think there's a phone sex Netflix documentary that... There's a show or something like that that is really popular. I don't want to go watch. At least I can learn about that. I could send you some links. Oh, on the internet? Yeah, yeah. But yeah, self-driving car, I think it's just inevitable. It's coming and these truckers are going to have to figure something out. Yeah. I mean, that's an under-understood industry, actually, because there's a lot of trucking jobs. Oh, yeah. And people don't want to... Well, people don't want to actually take them anymore because it's such a difficult job. So it won't have, or a lot of people believe it won't have as big of a negative impact as folks anticipate. There'll be other automation. I think they'll have a huge impact. Yeah, for sure. I mean, you already see it in McDonald's. You go to the beep, beep, beep. Why do you want to get yelled at by the heavyset woman of color for making a bad order when you can just hit the screen? But those interactions, I think, are human. I mean, that's part of life. So it is scary taking away everything. How long till we're not fucking? That's coming, too. Yeah. Then there's going to have two types of people. Are you a fuck in real life or are you a digital fuck person? I'm a digital. I like real fucking. Sorry, we can't date. That's coming. Well, there's also the reproduction side of sex, which is like with genetic engineering, you'll be able to specify a little bit of details. I talked to Jamie Marzo about that, like where you can specify, like, you know, it'll start with, like, I want my child not to have like a high likelihood of diabetes or something like that. And then you get to specify, like, intelligence, you get to specify those kinds of parameters until you're, like, basically trying to create a perfect human and you lose some of the magic of the flaws that make us who we are. Yes. And, you know, I'm pretty sure in the full lineup of humans, like, so let me give you some information. Lay it off a bit. Break it down. I'm sure you researched this thoroughly, but a male of the human species, the Homo sapien, produces 500 billion sperm cells in a lifetime. So that's all, some more than others, that's all uniquely, genetically unique humans that you could produce. So even across those 500 billion, you can select. And so- You mean like abort some? Or- No, you can choose which of them you want. I mean, just imagine all the genetic possibilities that are there, like, all the possible, like, you won the race. Yes. Shocking. This is a winner. Yeah, this is a winner. You won out of all the 500 billion? You have to imagine what the competition was. Oh, just tards all day long. Handicap. Well, so it's not actually the fastest sperm, or like, it's, I think a lot of it is timing and luck. Ah. What it seems like. There's actual papers on this, and I've actually been reading them. I hope so. So it's not just like the fastest sperm to the egg. Okay. There's a timing thing. So you were just lucky. All right. I believe that. So it's interesting to think about, like, once you're able to specify some parameters of what your child is like, how that changes the nature of, even just like the intimacy of two humans getting together and making, creating together a child. Yeah. I mean, it changes it. It's almost like, I don't know, it becomes like a factory line of some kind. If you don't meet naturally. Yeah, if you don't meet naturally, and then you don't, and you get to optimize your child, then it's, then it's something like you have to consider utilitarian type of things, like, what's good for society, and then it'll probably be regulation about what kind of children you can have and not, like, your child cannot have an IQ below this or above this, or something like that. Yeah. Your child cannot. We already kind of do that with, you know, VIP clubs, like, ah, you're kind of ugly, or women go, hey, he's not tall enough. We kind of do it a little, especially sexually. Yeah. We do. Can't get on the roller coaster, be this short, whatever it is, you know, we do it in some capacity. But here, this would be, like, fully transparent, and to a degree that it's hard to imagine. Like, the way we currently do it, you can at least get around it. Yes. You can at least, like, trick your way onto the roller coaster, even if you're short. Right. Or the fat guy can get rich so he can get laid, you know, there's other ways. At the risk of asking the totally wrong person this question, what advice would you give to young people today in high school and college about how to have a successful career, or career they're proud of, or maybe have a life that they're proud of? Well, first of all, you gotta be, you gotta want a life you're proud of. Not everybody has any integrity. A lot of people just want short money. I wanna feel good, look good, right now. I wanna do Molly, boom, I'll feel good, you know? But you should space it out. It's almost like saving money so you can use it later. Nobody wants to save money. What do they say, like, 11% of America actually has money saved? A thousand dollars or some shit? It's wildly low. Everybody wants it now, now, what do you call it, immediate gratification. I think the key to happiness and satisfaction is working for something. Even if it's, it's like a baby. If you could have a baby in five minutes, if a woman, you got her, you jizzed in her, and she had a baby, five minutes, boom, newborn, healthy, I think you'd be more likely to throw it away, if you could make it that quick. It's the fact that you spent nine months backbreaking the labor, the lactating, the ripped placenta, and the hymen, or whatever the fuck, that's what makes you love it. And I think it's the same with comedy or making money or whatever. Look at these kids who like child stars. They all become heroin addicts at like 22 because they've just, their sensors are burned out, their pleasure sensors. You didn't have to earn it. I think earning it is a big part of life. And always try to do better, try to do more, try to learn new things. Hey, I'm bored. Life sucks. Play the piano then, you chooch. But you won't do it because it takes effort and failure and all that. But that's the good part. And I know it's hard to see. So I think that's a good key to life is work hard at something you care about and then love the result. The hard work, the journey is actually way more important than just getting something. Everybody wants to go on Amazon, I got a package, then you feel good for 10 seconds and all right, let's go on Amazon again. And then it's just a dumb cycle of you being disgusting and gluttonous. So work for it. Everybody wants to take steroids and just, boop, I'm buff. Why'd you point at me? Well, I'm just saying. Because I'm Russian or what? Well, I saw the Icarus. Yeah. But no, I'm not saying you're on Roids. I'm just saying you'd be way bigger. But I'm just saying, work for something. And then I would also, young people, eat shit early. Eat shit early. I know a guy who kind of got canceled or whatever, and he had an out early, but he tried to get by and he tried to ride it. And it all came crumbling down. But if he had eaten it early, like, yeah, I fucked up, I did that, whatever it was, he would have just kind of been shit on for a month and then it would have gone away. But now it's his whole identity. And that sucks. So eat shit early. And I know it's hard to see. What do I mean early? I'm in the present. But look ahead, look back, this time will pass. I mean, look at high school. High school was the biggest thing in our lives. Oh my God, this exam, Susie Q hates me, the football player beat me up. I'll never recover. Now you don't even think about high school. It's just a blip in your dumb life, you know? And that's what this is now. This will just be a blip. So remember that and work towards something and work hard and care about the result. If the result isn't good, try it again. And failure is not always bad. We look at failure as this end all, be all. My life's over, I failed. But failure is really just learning. So that's something. So in summary, eat shit early and eat shit often. Yes. All right. Mark Norman. Eat ass. That's escalated quickly. All right. I have a list of random questions for you. What activities make you lose track of time? Just have that, go into that zone. You have this happiness, contentment about you that you just truly enjoy. Yeah, I think a good conversation, like I'll sit at the comedy cellar with friends, maybe a little whiskey's flowing. And when you're really just vibing and inhib... Inhib... Inhibity? You can do it. What is it? Inhibited. Inhibited. Uninhibited. Uninhibited. When you're just vibing and you're uninhibited, you're saying crazy shit and you're laughing and you're not worried, am I seeming cool right now? Am I seeming likable? When you're just you 100% and it's all coming out of you and then they're saying stuff and you go back and forth and you feel that excitement. Oh, they're talking, but I want to say my thing. And you get all keyed up. I love that. And I look at my watch, I'm like, fuck, it's three in the morning. We've been talking for five hours. So I love that. That makes the time fly by. Also, I bought a... Speaking of self-driving cars, I bought a 1973 BMW car and it's classic and it's stick shift and it's grizzly and gritty and rusty and it's a bucket of bolts, but I love driving it. Bucket of bolts. Yeah. You and Tom Waits are poets. Have you taken like a long trip anywhere, like road trip in your life or with this BMW? Not with it. It's pretty new, but I will. It's a new 1973. Yeah. It's new to me. And it just, it goes in the face of everything we're doing now. Everything is digital. Everything is automated. Everything is hands off. Everything is delivered. And this is the most hands-on thing in the world. And I am dialed in, man. I got the tachometer. I keep an eye on that. Oh, I put the wrong gear in. Shit. Oh, it's about to stall. Put some gas, put some clutch. And it's all just brain power and staying in focus and all that. And it's the opposite of tweeting and texting and watching porn or whatever. So I almost needed that in my life. So I bought this car just to have this little exercise. I hope you don't mind that I'm just trying out random questions I wrote on you that are completely, they're like completely insane. I'm a guinea pig, jizz in my face. Bring it on, baby. This would be edited down to five minutes. If everyone on earth disappeared and it was just you left, what would your days look like? What would you do? That's tough because I'm already an introvert and I try to avoid people mostly. I like a one-on-one, but crowds and all that is tough. So basically unchanged? Yeah, that's what I was going to say. But then that's the irony is I would be so sad to not talk to anybody. So it's this weird, bittersweet thing. But I don't know what I would do, man. I guess it's kind of like when you're hungover, you just go into the primal survival mode. I got to get food. I need water. I'm horny. Jerk off. You just go. You're not like playing the piano or painting or at the gym. So I think I would just go into urges, man. Primal urges. Find food. Store food. Am I safe? Make weapons. Build a shelter that I can't get attacked in. I would go all survival mode. And then once I maybe realized if I was safe or not, there's no wild roaming dogs, I would start exploring and maybe somehow get a vehicle and I would try to expand and that would be it. And maybe I'd journal. Exploring to what? To try to find new experiences? New life. Maybe there is another guy out there. Oh, so always there's a possibility. Yeah, hope. And then maybe there's a better place I could live. Let's find that. And then moving on. Maybe there's more food over here. So yeah, the hope would drive me. But it would be bleak and sad and horrible also. So what you're saying is you really want other people to be there so you can hide from them. Yes. Yes. Well said. All right. What's an item on your bucket list that you haven't done yet? Think about something you'd be very upset if you died and you haven't done. Well, I'm terrified of having kids, you know, just because I'm a child myself and I'm selfish and lazy in a way. So kids are like, this is your whole life now. This is it. You gotta not let this thing die. You gotta love it. You gotta raise it. So kids scare the shit out of me. But I also feel like if I don't have them, I'll regret it. Well, you've seen so many people like you who are fundamentally changed by kids. Like it's a source of, like a deep source of happiness, even though you didn't anticipate it. Yeah. So you like, you penciled it into your bucket list. Yes. Yes. It might be on there. Okay. Do you want kids? Yeah. Well, I want kids. I want to get married. I want to have kids. I kind of, I don't like choice. So in the following way, like, I appreciate the value of scarcity and the power of scarcity. Like I don't like the modern dating culture. It's not some religious thing or whatever. I just like one girl for a long time, or at least swinging for that always, like swinging for the fences. But you could be swinging right now. I mean, you're- There's a different use of the word swinging. Sure, sure. But I'm saying, you could be, you look great. You're handsome. Yeah, thank you. Muscular. Thank you. You get the job done. So I feel like you wouldn't leave without an orgasm on her. Yeah. But I just like to, you know, about furries, I like to dress up as animals and I just have trouble finding others who like the same- Ah, they're up there. I could show you some chat rooms. You're also my coach for the internet. Okay. What are you most afraid of? I guess on unlived life, I'm a, I was a big fan growing up of like wild guys, you know, like these Teddy Roosevelt's who would go out and hunt lions and like bar fighting guys. I was obsessed with Hunter S Thompson types. And look, this is what I love about guys like, who's a good example? Like Hemingway. Hemingway was the manliest guy. He had the rifle and the elephant gun and the whiskey and the writing and the women and the fistfights. But people forget that the other side of that coin is I'm sure he was in a lot of hotel rooms weeping. I'm sure he was lonely as fuck. I'm sure he had some wicked hangovers. I mean, he killed himself for Christ's sake. So obviously he was dealing with something. So the key to me is having this adventurous life, living to the fullest, doing crazy shit, scaring yourself, but also not killing yourself. Like also not hating, cause I used to party a lot hard. I used to bang a lot of gals. And this is the flip side is like, this girl hates you now, or you got herpes or you're hungover or your mom is like, where are you? You never call me anymore. And you're like, oh, my mom, I let Ty's go with my mom. I got to connect. So there's a horrible side to the party animal. The Keith Richards we don't see is not pretty. I mean, he's already weird looking, but he's partying, he's smoking, he's living, but there's another side of that coin. And I think the key to life is living that fucking crazy, awesome, badass life and also having some meaning and a little bit of a, what's the word? Not just not killing yourself, not going sad, not being depressed. There's a medium there, a sweet spot. Does that make sense? Yeah, yeah, yeah. So taking big leaps and Hemingway grabbing life by the balls, but at the same time not crushing the balls. Does that metaphor work at all? Perfect. Evil Knievel, we all know him. What a badass, fearless, oh man, what a cool dude. He's got balls of steel, but he also lived the back half of his life in a fucking Barker lounger where his legs were made of steel and he couldn't see straight and his dick didn't work. So you know what I mean? You've got to have a balance, but you still want the balance. I'm willing to take a little bit of shit for a little bit of fun, but you don't want to go too hard. But you've got to still risk it. I mean, Hunter S. Thompson, it didn't end well. Yeah. But it was quite a ride. Quite a ride. What small act of kindness were you once shown that you will never forget? Wow, that's a great question. I just wrote these for the guinea pig. You're the guinea pig. That's great. That's a keeper. Keep that question. This is where we're workshopping questions here. All right, I'll take it. Now you're open biking. This is your version. Let's see. There's a couple ladies in high school who were kind enough to hand job me. That was nice, which I really appreciate. I don't think women know how much that means to us. Women are like, oh, I'm not a piece of meat or whatever. And you're like, I know, but if you just gave me a hand job, it would make my world. It's like telling a kid he's smart or loved. See, most people mention like a math teacher, middle school that was inspired them to get into science. Give a shout out to the. Well, that's part of it. That's not the nicest, but I'm just saying that goes a long way. All right. Let's see. Kindness. That's a great question. I want to give you a good answer. I got lost when I was like six. I was walking around my dad and I zoned out and went away. And next thing you know, I don't know where I am. I'm in a neighborhood. This old guy finds me crying on a lawn somewhere and he goes, come inside. And he tried to call my parents and nothing came of it. Eventually, they found me after like nine hours. Cops were there. The FBI is out there, fucking helicopters. And I guess, you know, that's nice. This old guy took me in for a couple hours and just sat me down and kept me safe. That's something. Yeah. Oh, how about Enos, my transvestite nanny? Very kind. He did you hear about this? No. Okay. We had this transvestite nanny. He was like a drag queen, but it was in the 90s. It was weird. It was new. And my bike got stolen and he, you know, my parents like, what are you going to do? They're poor kids, you know? And he was like, fuck it, we're going to go get that bike. And I was like, this guy's in a wig and high heels, big black guy. And I'm like, ah, what are you going to do? You know, it's gone. And he's like, no, we're going to go get it. So we got in the van and drove around my neighborhood, saw the kids, fuck with the bike, you know, five street toughs. And he goes, all right, you want to come out or should I just do this? And I was like, you do it. I'm terrified. What are you crazy? And he got out of the van in full, you know, heels and wig. And he went up to these guys and they went off. Oh my God, look at this fucking guy, homo, faggot, all this shit. You know, it's the 90s. And he just stared at them long enough to where they were kind of like, all right, well, I guess we're going to fight you now. And he goes, that's not your bike. And they go, what are you going to do about it? And he puts his hand on the middle of the bike and they didn't do anything. And he just picked it up and said, that's what I thought. Put the bike over shoulder, slid the van door open, threw the bike in and we drove off. Somebody stuck up for you. Yeah. And you know, I mean, he could have got, I mean, they're tools. They could have fucking tuned him up. Two seconds. That actually like takes courage. Oh yeah. Real courage. And then that, the reason you do and act like that is that makes a kid like you feel like there's somebody on your side. Yes. That's powerful. Someone on your side is big. It's big. That goes a long way. Especially when they have the risk of getting their ass kicked or their job taken away or whatever it is. Now we're going to get philosophical, maybe a little bit emotional. Would you rather lose all your old memories or never be able to make new ones? It's a tough one, but I'd go easy answer, make new ones. But don't you think all the shitty things that happened to you? Oh, so my hard drive is wiped clean. It's not, is it memories or is it how every memory affected me too? I mean, this is a very- Why do they go hand in hand? I think the reality about memories is you replay them often. You go back to them, even when you're not aware of it. You really go back often. And they change. You change them too. Yeah, you change them to suit your understanding of the world. Yes. So the dark view you have, both the hope and the cynicism you have about the world is so deeply grounded in the memories that you're basically, I would say if you erase all memories, I think you're really starting over with maybe the wisdom of how the world works, but not your, so much of your personality is gone. You would really, it'd be interesting how your comedy would change. Maybe you would have a good sense of timing, you have a good sense of like the writing process maybe, but like- Now you're making some good points, but let me ask you this. Let's say I go to Lake Cuomo with my girlfriend now. I wipe the memory, or I keep my old memories. Let's say I go to the Tuscany with the lady. Yeah. I just won't remember that? Yeah, but you get to experience it in the moment. Okay. You get to enjoy it. Can I look at a photo of it? Yes. But I was, what the hell is this? Yeah, exactly. Oh, fascinating. It's exact. The rules are pretty simple. I think everyone knows how the rules go. So, but you would, yeah, so what- Well, I was going to say start new ones, but then I realized I wouldn't be who I was without them. That's what you're saying. So, I guess I'd keep them, because I am 38, so I've gotten a good chunk out of life. Yeah. And let's be honest, how many years do you have left? I know, right? I got AIDS. Is it better to have loved, okay, this question is ridiculous. Is it better to have loved and lost, or to have never loved at all? It sounds cliche, but there's a question. Definitely better to loss. So, you enjoy the ups and downs? The roll of the dice? Yeah, that's life. Sun and rain, baby. I kind of like both, the whole thing. The loss, every time you lose something, it really makes you distinctly realize how much you valued it. Yes. When I'm sad, when I'm feeling alone, and I'm sitting there alone at home, and I wish I could hang out with somebody, that's a realization how awesome people are. Yeah. So, it's like the missing, the, yeah. We don't have a lot of that in life anymore, because we can have anything we want immediately. So, the missing has gone away, which again, drives down the joy of having it. So, I think you're right, you need both. So, like you said, you have a condition that, a terminal condition, not many years left. Do you think about your mortality? You think about that? All day, every day. Are you afraid? Not afraid, because it's inevitable. So, it's more like, how are we going to handle this? It's like, the winter is coming, let's stock up on some fucking nuts. But the existential nature of it, like, the fact that this ride ends, like, what the hell are you doing any of this for? Like, is it your... Satisfaction, happiness. Short term, but like, there is a presumption there that it kind of goes on forever. I think if you truly think about the fact that it ends... Your brain almost shuts it down. Yeah, yeah. There's some kind of like, protective switch that just goes off. I mean, that's why the Stoics, you know, encourage people to meditate on death, because it somehow reorganizes your priorities. It helps you, like, holy shit, this ends, make the most of the day. Yes. It's just a nice thing, but still, you can't quite comprehend that the thing ends. Little things too, you know, people go like, oh, we got a layover between our flights, it's an hour, what are we gonna do for an hour? It's like, what do you mean, what are you gonna do for an hour? You're gonna kill an hour, let's kill, how are we gonna kill this hour? This is part of your life. You're just trying to get rid of it, you're just trying to kill it. That always blew my mind, like, hey, fuck it, let's hit the airport bar, let's get a, you know, a candy bar, something. Anything with bar. But it just... You gotta live. I hate this, like, how are we gonna burn... Oh, the bar didn't open for 15 minutes, what are we gonna do? Well, we got 15 minutes, we got the world is our oyster. Yeah, make the most of it. And like you said, in modern day, actually, the boredom is a gift. When you're waiting for something, that's a gift. You get to be with your thoughts. Yeah. Those are the same thoughts you'll have when you're in your deathbed. There won't be a... You won't be scrolling TikTok on your deathbed. I hope not, Jesus. You'll be a lot more, actually, maybe you would be. What a sad existence. Because it would be a good, like, content creators would be like, oh, I'm dying, this would be good content. Yeah, I want to be able to film the exact moment it goes, beeep. Last words, I wonder what my last words will be. Yeah. A good way to, like, end the account with a bang. Yep, I like that. Well, you know, have you ever seen that meme where the old guy in bed goes, I wish I had tweeted more, you know, and then he dies. It's so true. Could be the future. What do you think is the meaning of life? I don't think there is one. Everybody always throws that out there. There isn't a meaning. I think we're here, we're lucky to be here. I think there's no afterlife, there's no heaven, that's all shit we tell ourselves to feel better. And I think you gotta just... It's like saying, what is the meaning of this food I made? Well, it's just you enjoy the food, you try to get the most out of it, you built the food, you prepared it, so just get what you can out of it, don't die, and try to make it last as long as possible. Yeah, but you look at Earth, it's like four billion years old, and life started early on, like simple cell bacteria life, like one billion years in, and then it started like having lots of aggressive interaction. Eventually, there's predator and prey, and there's sex, lots of sex, lots of sex, lots of violence. And then through natural selection, there's just a whole evolutionary process of animals that have loved and lost and murdered and gotten murdered and all that kind of stuff, and it's somehow led to human civilization. We're super busy trying to create things and trying to create things and creating beautiful art, creating beautiful comedy, just always creating something new. It feels like it's tending towards something. It's not dying. If you die tomorrow, you still have all these hours of pods. So it's kind of, you think you're cheating death in a subconscious way, I think. Right. You know who Ernest Becker is? I've heard the name. It's a book called The Noul of Death, this idea that... Oh, yeah. That if you don't acknowledge... Books on my show. Girls love it. Really? Like Dostoevsky, no, I'm just saying, you want to bring Tolstoy, Dostoevsky, Russian literature, back to norm, it's good to bring to... Because no American has read any Russian literature, but they all appreciate it if you bring it, and it's not like they're going to ask you any legitimate questions because they haven't read it, so you can always pretend like you've read it. So it's a... It's a little dense. Can we get a shortened version? Cliff notes. Yes, or make a movie with Ben Stiller that I can just go, oh, this is based on, what is it, Life and Death? No, what's the one? War and Peace. War and Peace. Yeah. Yeah, so Ernest Becker's theory, and there's this whole terror management theory that basically says that, like, our terror of death, our fear of death is one of the central creative forces... I agree....of the human condition. It's the reason we're trying to, yeah, cheat death. We're trying to delude ourselves that somehow we can become immortal through our art. That's why you've uploaded your special to YouTube, because you think your special will outlive all of human civilization. You think YouTube will outlive all of human civilization. Right. That could go away tomorrow. That can go away tomorrow. All of this can go away, so I'm truly grateful, Mr. Mark Norman, that you would spend your very valuable time with me today, even though it could all go away. This could be the last day of our lives, and won't you be quite upset this is how you spent it? Ah, yeah, in your hotel room. What am I doing? You're like Harvey Weinstein here. You heard me up, and now I feel fucked. Just wait what we have ready for you after the podcast is over. All right, brother, thanks so much for talking today. Thank you. That was great. Comedy. Thanks for listening to this conversation with Mark Norman. To support this podcast, please check out our sponsors in the description. Now, let me leave you with some words from Mark Norman himself on his Twitter, which you should definitely follow because it's hilarious. The worst thing about getting Omicron for Christmas is you know it was regifted. Thank you for listening, and hope to see you next time.

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Manolis Kellis: Human Genome and Evolutionary Dynamics | Lex Fridman Podcast #113

The following is a conversation with Manolis Kellis. He's a professor at MIT and head of the MIT Computational Biology Group. He's interested in understanding the human genome from a computational, evolutionary, biological, and other cross-disciplinary perspectives. He has more big, impactful papers and awards than I can list, but most importantly, he's a kind, curious, brilliant human being and just someone I really enjoy talking to. His passion for science and life in general is contagious. The hours honestly flew by, and I'm sure we'll talk again on this podcast soon. Quick summary of the ads. Three sponsors, Blinkist, 8sleep, and Masterclass. Please consider supporting this podcast by going to blinkist.com slash lex, 8sleep.com slash lex, and signing up at masterclass.com slash lex. Click the links, buy the stuff, get the discount. It's the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars and Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This episode is supported by Blinkist, my favorite app for learning new things. Get it at blinkist.com slash lex for a seven-day free trial and 25% off afterwards. Blinkist takes the key ideas from thousands of nonfiction books and condenses them down into just 15 minutes that you can read or listen to. I'm a big believer in reading at least an hour every day. As part of that, I use Blinkist every day to try out a book I may otherwise never have a chance to read. And in general, it's a great way to broaden your view of the idea landscape out there and find books that you may want to read more deeply. With Blinkist, you get unlimited access to read or listen to a massive library of condensed nonfiction books. Go to blinkist.com slash lex to try it free for seven days and save 25% off your new subscription. That's blinkist.com slash lex, Blinkist spelled B-L-I-N-K-I-S-T. This show is also sponsored by Eight Sleep and its Pod Pro mattress. You can check out at eightsleep.com slash lex to get $200 off. It controls temperature with an app and can cool down to as low as 55 degrees on each side of the bed separately. Research shows that temperature has a big impact on the quality of our sleep. Anecdotally, it's been true for me, it's truly been a game changer. I love it. The Pod Pro is packed with sensors that track heart rate, heart rate variability and respiratory rate, showing it all in their app. The app's health metrics are amazing, but the cooling alone is honestly worth the money. Check it out at eightsleep.com slash lex to get $200 off. This show is also sponsored by Masterclass. Sign up at masterclass.com slash lex to get a discount and to support this podcast. When I first heard about Masterclass, I thought it was too good to be true. For 180 bucks a year, you get an all access pass to watch courses from, to list some of my favorites, Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking and communication, Will Wright, one of my favorite game designers, Carlos Santana, one of my favorite guitar players, Garry Kasparov, of course, the greatest chess player of all time, I'm not biased, Daniel Negrano on poker and many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. By the way, you can watch it on basically any device. Once again, sign up at masterclass.com slash lex to get a discount and to support this podcast. And now here's my conversation with Manolis Callas. What to you is the most beautiful aspect of the human genome? Don't get me started. So, we got time. The first answer is that the beauty of genomes transcends humanity. So it's not just about the human genome. Genomes in general are amazingly beautiful. And again, I'm obviously biased. So in my view, the way that I like to introduce the human genome and the way that I like to introduce genomics to my class is by telling them, you know, we're not the inventors of the first digital computer. We are the descendants of the first digital computer. Basically, life is digital. And that's absolutely beautiful about life. The fact that at every replication step, you don't lose any information because that information is digital. If it was analog, if it was just brought in concentrations, you'd lose it after a few generations. It would just dissolve away. And that's what the ancients didn't understand about inheritance. The first person to understand digital inheritance was Mendel, of course. And his theory, in fact, stayed in a bookshelf for like 50 years, while Darwin was getting famous about natural selection. But the missing component was this digital inheritance, the mechanism of evolution that Mendel had discovered. So that aspect, in my view, is the most beautiful aspect, but it transcends all of life. And can you elaborate maybe the inheritance part? What was the key thing that the ancients didn't understand? So the very theory of inheritance as discrete units, throughout the life of Mendel, and well after his writing, people thought that his pea experiments were just a little fluke, that they were just a little exception that would normally not even apply to humans. That basically what they saw is this continuum of eye color, this continuum of skin color, this continuum of hair color, this continuum of height. And all of these continuums did not fit with a discrete type of inheritance that Mendel was describing. But what's unique about genomics and what's unique about the genome is really that there are two copies and that you get a combination of these, but for every trait, there are dozens of contributing variables. And it was only Ronald Fisher in the 20th century that basically recognized that even five Mendelian traits would add up to a continuum-like inheritance pattern. And he wrote a series of papers that still are very relevant today about sort of this Mendelian inheritance of continuum-like traits. And I think that was the missing step in inheritance. So well before the discovery of the structure of DNA, which is again another amazingly beautiful aspect, the double helix, what I like to call the most noble molecule of our time, holds within it the secret of that discrete inheritance, but the conceptualization of discrete elements is something that precedes that. So even though it's discrete, when it materializes itself into actual traits that we see, it can be continuous. It can basically arbitrarily rich and complex. So if you have five genes that contribute to human height, and there aren't five, there's a thousand. If there's only five genes and you inherit some combination of them and everyone makes you two inches taller or two inches shorter, it'll look like a continuum trait, a continuous trait. But instead of five, there are thousands and every one of them contributes to less than one millimeter. We change in height more during the day than each of these genetic variants contributes. So by the evening, you're shorter than you were, you woke up with. Isn't that weird then that we're not more different than we are? Why are we all so similar if there's so much possibility to be different? Yeah, so there are selective advantages to being medium. If you're extremely tall or extremely short, you run into selective disadvantages. So you have trouble breathing, you have trouble running, you have trouble sitting if you're too tall. If you're too short, you might, I don't know, have other selective pressures acting against that. If you look at natural history of human population, there's actually selection for height in Northern Europe and selection against height in Southern Europe. So there might actually be advantages to actually being not super tall. And if you look across the entire human population, for many, many traits, there's a lot of push towards the middle. Balancing selection is the usual term for selection that sort of seeks to not be extreme and to sort of have a combination of alleles that sort of keep recombining. And if you look at mate selection, super, super tall people will not tend to sort of marry super, super tall people. Very often you see these couples that are kind of compensating for each other. And the best predictor of the kid's age is very often just take the average of the two parents and then adjust for sex and boom, you get it. It's extremely heritable. Let me ask, you kind of took a step back to the genome outside of just humans, but is there something that you find beautiful about the human genome specifically? So I think the genome, if more people understood the beauty of the human genome, there would be so many fewer wars, so much less anger in the world. I mean, what's really beautiful about the human genome is really the variation that teaches us both about individuality and about similarity. So any two people on the planet are 99.9% identical. How can you fight with someone who's 99.9% identical to you? It's just counterintuitive. And yet any two siblings of the same parent differ in millions of locations. So every one of them is basically two to the million unique from any pair of parents, let alone any two random parents on the planet. So that's, I think, something that teaches us about sort of the nature of humanity in many ways, that every one of us is as unique as any star and way more unique in actually many ways. And yet we're all brothers and sisters. Yeah, just like stars, most of it is just fusion reactions. Yeah, you only have a few parameters to describe stars. Yeah, exactly. Mass size, initial size, and stage of life. Whereas for humans, it's thousands of parameters scattered across our genome. So the other thing that makes humans unique, the other things that makes inheritance unique in humans is that most species inherit things vertically. Basically, instinct is a huge part of their behavior. The way that, I mean, with my kids, we've been watching this nest of birds with two little eggs outside our window for the last few months, for the last few weeks as they've been growing. And there's so much behavior that's hard-coded. Birds don't just learn as they grow. They don't, there's no culture. Like a bird that's born in Boston will be the same as a bird that's born in California. So there's not as much inheritance of ideas, of customs. A lot of it is hard-coded in their genome. What's really beautiful about the human genome is that if you take a person from today and you place them back in ancient Egypt, or if you take a person from ancient Egypt and you place them here today, they will grow up to be completely normal. That is not genetics. This is the other type of inheritance in humans. So on one hand, we have genetic inheritance, which is vertical, from your parents down. On the other hand, we have horizontal inheritance, which is the ideas that are built up at every generation are horizontally transmitted. And the huge amount of time that we spend in educating ourselves, a concept known as neoteny, neo for newborn and then teny for holding. So if you look at humans, I mean, the little birds that were eggs two weeks ago, and now one of them has already flown off, the other one's ready to fly off. In two weeks, they're ready to just fend for themselves. Humans, 16 years. 18 years, 24, getting out of college. I'm still learning. So that's so fascinating, this picture of a vertical and a horizontal. When you talk about the horizontal, is it in the realm of ideas? Exactly. Okay, so it's the actual social interactions. That's exactly right. So basically, the concept of neoteny is that you spend acquiring characteristics from your environment in an extremely malleable state of your brain and the wiring of your brain for a long period of your life. Compared to primates, we are useless. You take any primate at seven weeks and any human at seven weeks, we lose the battle. But at 18 years, all bets are off. Basically, our brain continues to develop in an extremely malleable form till very late. And this is what allows education. This is what allows the person from Egypt to do extremely well now. And the reason for that is that the wiring of our brain and the development of that wiring is actually delayed. So the longer you delay that, the more opportunity you have to pass on knowledge, to pass on concepts, ideals, ideas from the parents to the child. And what's really absolutely beautiful about humans today is that that lateral transfer of ideas and culture is not just from uncles and aunts and teachers at school, but it's from Wikipedia and review articles on the web and thousands of journals that are sort of putting out information for free and podcasts and video casts and all of that stuff where you can basically learn about any topic, pretty much everything that would be in any super advanced textbook in a matter of days, instead of having to go to the Library of Alexandria and sail there to read three books and then sail for another few days to get to Athens and et cetera, et cetera, et cetera. So the democratization of knowledge and the spread, the speed of spread of knowledge is what defines, I think, the human inheritance pattern. So you sound excited about it. Are you also a little bit afraid or are you more excited by the power of this kind of distributed spread of information? So you put it very kindly that most people are kind of using the internet and looking Wikipedia, reading articles, reading papers and so on. But if we're honest, most people online, especially when they're younger, probably looking at five second clips on TikTok or whatever the new social network is, are you, given this power of horizontal inheritance, are you optimistic or a little bit pessimistic about this new effect of the internet and democratization of knowledge on our, what would you call this? This genome, like would you use the term genome, by the way, for this? Yeah, yeah, I think, you know, we use the genome to talk about DNA, but very often we say, you know, I mean, I'm Greek, so people ask me, hey, what's in the Greek genome? And I'm like, well, yeah, what's in the Greek genome is both our genes and also our ideas and our ideals and our culture, so. The poetic meaning of the word. Exactly, exactly, yeah. So I think that there's a beauty to the democratization of knowledge, the fact that you can reach as many people as any other person on the planet and it's not who you are, it's really your ideas that matter, is a beautiful aspect of the internet. The, I think there's of course a danger of my ignorance is as important as your expertise. The fact that with this democratization comes the abolishment of respecting expertise. Just because you've spent, you know, 10,000 hours of your life studying, I don't know, human brain circuitry, why should I trust you? I'm just gonna make up my own theories and they'll be just as good as yours, is an attitude that sort of counteracts the beauty of the democratization. And I think that within our educational system and within the upbringing of our children, we have to not only teach them knowledge, but we have to teach them the means to get to knowledge. And that, you know, it's very similar to sort of, you fish, you catch a fish for a man for one day, you fed them for one day, you teach them how to fish, you fed them for the rest of their life. So instead of just gathering the knowledge they need for any one task, we can just tell them, all right, here's how you Google it. Here's how to figure out what's real and what's not. Here's how you check the sources. Here's how you form a basic opinion for yourself. And I think that inquisitive nature is paramount to being able to sort through this huge wealth of knowledge. So you need a basic educational foundation based on which you can then add on the sort of domain specific knowledge. But that basic educational foundation should not just be knowledge, but it should also be epistemology, the way to acquire knowledge. I'm not sure any of us know how to do that in this modern day. We're actually learning. One of the big surprising thing to me about the coronavirus, for example, is that Twitter has been one of the best sources of information. Basically, like building your own network of experts, as opposed to the traditional centralized expertise of the WHO and the CDC, or maybe any one particular respectable person at the top of a department, some kind of institution. You instead look at 10, 20, hundreds of people, some of whom are young kids that are incredibly good at aggregating data and plotting and visualizing that data. That's been really surprising to me. I don't know what to make of it. I don't know how that matures into something stable. I don't know if you have ideas. If you were to try to explain to your kids where should you go to learn about coronavirus, what would you say? It's such a beautiful example, and I think the current pandemic and the speed at which the scientific community has moved in the current pandemic, I think exemplifies this horizontal transfer and the speed of horizontal transfer of information. The fact that the genome was first sequenced in early January, the first sample was obtained December 29, 2019, a week after the publication of the first genome sequence. Moderna had already finalized its vaccine design and was moving to production. I mean, this is phenomenal. The fact that we go from not knowing what the heck is killing people in Wuhan to, wow, it's SARS-CoV-2, and here's a set of genes, here's the genome, here's the sequence, here are the polymorphisms, et cetera, in the matter of weeks is phenomenal. In that incredible pace of transfer of knowledge, there have been many mistakes. So, you know, some of those mistakes may have been politically motivated, or other mistakes may have just been innocuous errors. Others may have been misleading the public for the greater good, such as don't wear masks because we don't want the masks to run out. I mean, that was very silly in my view and a very big mistake. But the spread of knowledge from the scientific community was phenomenal, and some people will point out to bogus articles that snuck in and made the front page. Yeah, they did, but within 24 hours, they were debunked and went out of the front page. And I think that's the beauty of science today, the fact that it's not, oh, knowledge is fixed. It's the ability to embrace that nothing is permanent when it comes to knowledge, that everything is the current best hypothesis and the current best model that best fits the current data, and the willingness to be wrong, the expectation that we're gonna be wrong, and the celebration of success based on how long was I not proven wrong for, rather than, wow, I was exactly right, because no one is gonna be exactly right with partial knowledge. But the arc towards perfection, I think is so much more important than how far you are in your first step. And I think that's what sort of the current pandemic has taught us, the fact that, yeah, no, of course, we're gonna make mistakes, but at least we're gonna learn from those mistakes and become better and learn better and spread information better. So if I were to answer the question of where would you go to learn about coronavirus? First, textbook. It all starts with a textbook. Just open up a chapter on virology and how coronaviruses work. Then some basic epidemiology and sort of how pandemics have worked in the past. What are the basic principles surrounding these first wave, second wave? Why do they even exist? Then understanding about growth, understanding about the R naught and RT at various time points. And then understanding the means of spread, how it spreads from person to person. Then how does it get into your cells from when it gets into the cells? What are the paths that it takes? What are the cell types that express the particular ACE2 receptor? How is your immune system interacting with the virus? And once your immune system launches a defense, how is that helping or actually hurting your health? What about the cytokine storm? What are most people dying from? Why are the comorbidities and these risk factors even applying? What makes obese people respond more or elderly people respond more to the virus while kids are completely, you know, you know, very often not even aware that they're spreading it? So the, you know, I think there's some basic questions that you would start from, and then I'm sorry to say, but Wikipedia is pretty awesome. Google is pretty awesome. So- It used to be a time, maybe five years ago, I forget when, but people kind of made fun of Wikipedia for being an unreliable source. I never quite understood it. I thought from the early days, it was pretty reliable or better than a lot of the alternatives. But at this point, it's kind of like a solid accessible survey paper on every subject ever. There's an ascertainment bias and a writing bias. So I think this is related to sort of people saying, oh, so many nature papers are wrong. And they're like, why would you publish in nature? So many nature papers are wrong. And my answer is, no, no, no. So many nature papers are scrutinized. And just because more of them are being proven wrong than in other articles is actually evidence that they're actually better papers overall because they're being scrutinized at a rate much higher than any other journal. So if you basically judge Wikipedia by not the initial content, but by the number of revisions, then of course it's gonna be the best source of knowledge eventually. It's still very superficial. You then have to go into the review papers, et cetera, et cetera, et cetera. But I mean, for most scientific topics, it's extremely superficial. But it is quite authoritative because it is the place that everybody likes to criticize as being wrong. You say that it's superficial. On a lot of topics that I've studied a lot of, I find it, I don't know if superficial is the right word. Because superficial kind of implies that it's not correct. No, no. I don't mean any implication of it not being correct. It's just superficial. It's basically only scratching the surface. For depth, you don't go to Wikipedia. You go to the review articles. But it can be profound in the way that articles rarely, one of the frustrating things to me about certain computer science, like in the machine learning world, articles, they don't as often take the bigger picture view. There's a kind of data set and you show that it works and you kind of show that here's an architectural thing that creates an improvement and so on and so forth. But you don't say, well, what does this mean for the nature of intelligence for future data sets we haven't even thought about? Or if you were trying to implement this, like if we took this data set of 100,000 examples and scaled it to 100 billion examples with this method, like look at the bigger picture, which is what a Wikipedia article would actually try to do, which is like, what does this mean in the context of the broad field of computer vision or something like that? Yeah, I agree with you completely, but it depends on the topic. I mean, for some topics, there's been a huge amount of work. For other topics, it's just a stub. So, you know. I got it. Well, yeah, actually, which we'll talk on, genomics was not great. Yeah, it's very shallow. Yeah, yeah. It's not wrong, it's just shallow. It's shallow. Every time I criticize something, I should feel partly responsible. Basically, if more people from my community went there and edited, it would not be shallow. It's just that there's different modes of communication in different fields. And in some fields, the experts have embraced Wikipedia. In other fields, it's relegated. And perhaps the reason is that if it was any better to start with, people would invest more time. But if it's not great to start with, then you need a few initial pioneers who will basically go in and say, ah, enough, we're just gonna fix that. And then I think it'll catch on much more. So if it's okay, before we go on to genomics, can we linger a little bit longer on the beauty of the human genome? You've given me a few notes. What else do you find beautiful about the human genome? So the last aspect of what makes the human genome unique, in addition to the similarity and the differences and the individuality, is that, so very early on, people would basically say, oh, you don't do that experiment in human. You have to learn about that in fly. Or you have to learn about that in yeast first, or in mouse first, or in a primate first. And the human genome was in fact relegated to sort of, oh, the last place that you're gonna go to learn something new. That has dramatically changed. And the reason that changed is human genetics. We are the species in the planet that's the most studied right now. It's embarrassing to say that, but this was not the case a few years ago. It used to be first viruses, then bacteria, then yeast, then the fruit fly and the worm, then the mouse, and eventually, human was very far last. So it's embarrassing that it took us this long to focus on it, or the, what do you? It's embarrassing that the model organisms have been taken over because of the power of human genetics. That right now, it's actually simpler to figure out the phenotype of something by mining this massive amount of human data than by going back to any of the other species. And the reason for that is that if you look at the natural variation that happens in a population of seven billion, you basically have a mutation in almost every nucleotide. So every nucleotide you wanna perturb, you can go find a living, breathing human being and go test the function of that nucleotide by sort of searching the database and finding that person. Wait, why is that embarrassing, it's a beautiful dataset. It's a beautiful dataset. It's embarrassing for the model organism. For the flies? Yeah, exactly. I mean, do you feel, on a small tangent, is there something of value in the genome of a fly and other of these model organisms that you miss that we wish we would be looking at deeper? So directed perturbation, of course. So I think the place where humans are still lagging is the fact that in an animal model, you can go and say, well, let me knock out this gene completely and let me knock out these three genes completely. And the moment you get into combinatorics, it's something you can't do in the human because there just simply aren't enough humans on the planet. And again, let me be honest, we haven't sequenced all seven billion people. It's not like we have every mutation, but we know that there's a carrier out there. So if you look at the trend and the speed with which human genetics has progressed, we can now find thousands of genes involved in human cognition, in human psychology, in the emotions and the feelings that we used to think are uniquely learned. Turns out there's a genetic basis to a lot of that. So the human genome has continued to elucidate through these studies of genetic variation so many different processes that we previously thought were something that, like free will. Free will is this beautiful concept that humans have had for a long time. You know, in the end, it's just a bunch of chemical reactions happening in your brain. And the particular abundance of receptors that you have this day based on what you ate yesterday or that you have been wired with based on your parents and your upbringing, et cetera, determines a lot of that quote unquote free will component to sort of narrower and narrower slices. So how much, on that point, how much freedom do you think we have to escape the constraints of our genome? You're making it sound like more and more we're discovering that our genome actually has a lot of the story already encoded into it. How much freedom do we have? So let me describe what that freedom would look like. That freedom would be my saying, ooh, I'm gonna resist the urge to eat that apple because I choose not to. But there are chemical receptors that made me not resist the urge to prove my individuality and my free will by resisting the apple. So then the next question is, well, maybe now I'll resist the urge to resist the apple and I'll go for the chocolate instead to prove my individuality. But then what about those other receptors that, you know. That might be all encoded in there. So it's kicking the bucket down the road and basically saying, well, your choice will may have actually been driven by other things that you actually are not choosing. So that's why it's very hard to answer that question. It's hard to know what to do with that. I mean, if the genome has, if there's not much freedom, it's a. It's the butterfly effect. It's basically that in the short term, you can predict something extremely well by knowing the current state of the system. But a few steps down, it's very hard to predict based on the current knowledge. Is that because the system is truly free? When I look at weather patterns, I can predict the next 10 days. Is it because the weather has a lot of freedom and after 10 days, it chooses to do something else? Or is it because, in fact, the system is fully deterministic and there's just a slightly different magnetic field of the earth, slightly more energy arriving from the sun, a slightly different spin of the gravitational pull of Jupiter that is now causing all kinds of tides and slight deviation of the moon, et cetera. Maybe all of that can be fully modeled. Maybe the fact that China is emitting a little more carbon today is actually gonna affect the weather in Egypt in three weeks. And all of that could be fully modeled. In the same way, if you take a complete view of a human being now, I model everything about you, the question is, can I predict your next step? Probably. But at how far? And if it's a little further, is that because of stochasticity and sort of chaos properties of unpredictability of beyond a certain level, or was that actually true free will? Yeah, so the number of variables might be so, you might need to build an entire universe to be able to model. To simulate a human, and then maybe that human will be fully simulatable, but maybe aspects of free will will exist, and where's that free will coming from? It's still coming from the same neurons, or maybe from a spirit inhabiting these neurons. But again, it's very difficult empirically to sort of evaluate where does free will begin, and sort of chemical reactions and electric signals. So on that topic, let me ask the most absurd question that most MIT faculty rolled their eyes on. But what do you think about the simulation hypothesis and the idea that we live in a simulation? I think it's complete BS. Okay. There's no empirical evidence. No, there's not. Absolutely not. Not in terms of empirical evidence, there's not, but in terms of a thought experiment, does it help you think about the universe? I mean, so if you look at the genome, it's encoding a lot of the information that is required to create some of the beautiful human complexity that we see around us. It's an interesting thought experiment. How much parameters do we need to have in order to model this full human experience? Like if we were to build a video game, how hard it would be to build a video game that's convincing enough and fun enough, and has consistent laws of physics, all that stuff? It's not interesting to you as a thought experiment? I mean, it's cute, but it's Occam's razor. I mean, what's more realistic, the fact that you're actually a machine or that you're a person? What's the fact that all of my experiences exist inside the chemical molecules that I have, or that somebody's actually simulating all that? Well, you did refer to humans as a digital computer earlier. Of course, of course, but that does not- It's a kind of a machine, right? I know, I know, but I think the probability of all that is nil, and let the machines wake me up and just terminate me now if it's not. I challenge you, machines. They're gonna wait a little bit to see what you're gonna do next. It's fun, it's fun to watch, especially the clever humans. What's the difference to you between the way a computer stores information and the human genome stores information? So you also have roots and your work. Would you say when you introduce yourself at a bar- It depends who I'm talking to. Would you say it's computational biology? Do you reveal your expertise in computers? It depends who I'm talking to, truly. I mean, basically, if I meet someone who's in computers, I'll say, oh, I'm a professor in computer science. If I meet someone who's in engineering, I say, computer science and electrical engineering. If I meet someone in biology, I'll say, hey, I work in genomics. If I meet someone in medicine, I'm like, hey, I work on genetics. You're a fun person to meet at a bar, I got you. No, no, but what I'm trying to say is that I don't, I mean, there's no single attribute that I will define myself as. There's a few things I know, there's a few things I study, there's a few things I have degrees on, and there's a few things that I grant degrees in. I publish papers across the whole gamut, the whole spectrum of computation to biology, et cetera. I mean, the complete answer is that I use computer science to understand biology. So I'm a, you know, I develop methods in AI, in machine learning, statistics, in algorithms, et cetera, but the ultimate goal of my career is to really understand biology. If these things don't advance our understanding of biology, I'm not as fascinated by them. Although there are some beautiful computational problems by themselves, I've sort of made it my mission to apply the power of computer science to truly understand the human genome, health, disease, you know, and the whole gamut of how our brain works, how our body works, and all of that, which is so fascinating. So the dream, there's not an equivalent sort of complimentary dream of understanding human biology in order to create an artificial life, or an artificial brain, or artificial intelligence that supersedes the intelligence and the capabilities of us humans. It's an interesting question. It's a fascinating question. So understanding the human brain is undoubtedly coupled to how do we make better AI, because so much of AI has in fact been inspired by the brain. It may have taken 50 years since the early days of neural networks till we have all of these amazing progress that we've seen with deep belief networks and all of these advances in Go, in chess, in image synthesis, in deep fakes, in you name it. But the underlying architecture is very much inspired by the human brain, which actually posits a very, very interesting question. Why are neural networks performing so well? And they perform amazingly well. Is it because they can simulate any possible function? And the answer is no, no. They simulate a very small number of functions. Is it because they can simulate every possible function in the universe? And that's where it gets interesting. The answer is actually yeah, a little closer to that. And here's where it gets really fun. If you look at human brain and human cognition, it didn't evolve in a vacuum. It evolved in a world with physical constraints like the world that inhabits us. It is the world that we inhabit. And if you look at our senses, what do they perceive? They perceive different parts of the electromagnetic spectrum. The hearing is just different movements in air. The touch, et cetera. I mean, all of these things, we've built intuitions for the physical world that we inhabit. And our brains and the brains of all animals evolved for that world. And the AI systems that we have built happen to work well with images of the type that we encounter in the physical world that we inhabit. Whereas if you just take noise and you add random signal that doesn't match anything in our world, neural networks will not do as well. And that actually basically has this whole loop around this, which is this was designed by studying our own brain, which was evolved for our own world, and they happen to do well in our own world. And they happen to make the same types of mistakes that humans make many times. And of course you can engineer images by adding just the right amount of sort of pixel deviations to make a zebra look like a bamboo and stuff like that, or like a table. But ultimately the undoctored images at least are very often mistaken, I don't know, between muffins and dogs, for example, in the same way that humans make those mistakes. So there's no doubt in my view that the more we understand about the tricks that our human brain has evolved to understand the physical world around us, the more we will be able to bring new computational primitives in our AI systems to again better understand not just the world around us, but maybe even the world inside us, and maybe even the computational problems that arise from new types of data that we haven't been exposed to, but are yet inhabiting the same universe that we live in with a very tiny little subset of functions from all possible mathematical functions. Yeah, and that small subset of functions, all that matters to us humans really. That's what makes. It's all that has mattered so far, and even within our scientific realm, it's all that seems to continue to matter. But I mean, I always like to think about our senses and how much of the physical world around us we perceive. And if you look at the LIGO experiment over the last year and a half has been all over the news. What did LIGO do? It created a new sense for human beings, a sense that has never been sensed in the history of our planet. Gravitational waves have been traversing the earth since its creation a few billion years ago. Life has evolved senses to sense things that were never before sensed. Light was not perceived by early life. No one cared. And eventually photoreceptors evolved and the ability to sense colors by sort of catching different parts of that electromagnetic spectrum. And hearing evolved and touch evolved, et cetera. But no organism evolved a way to sense neutrinos floating through earth or gravitational waves flowing through earth, et cetera. And I find it so beautiful in the history of not just humanity, but life on the planet, that we are now able to capture additional signals from the physical world than we ever knew before. And axioms, for example, have been all over the news in the last few weeks. The concept that we can capture and perceive more of that physical world is as exciting as the fact that we were blind to it is traumatizing before. Because that also tells us, you know, we're in 2020. Picture yourself in 3020 or in 20, you know. What new senses might we discover? Is it, you know, could it be that we're missing 9 10ths of physics? That like there's a lot of physics out there that we're just blind to, completely oblivious to it. And yet they're permeating us all the time. Yeah, so it might be right in front of us. So when you're thinking about premonitions, yeah, a lot of that is ascertainment bias. Like, yeah, you know, every now and then you're like, oh, I remember my friend, and then my friend doesn't appear and I'll forget that I remembered my friend. But every now and then my friend will actually appear. I'm like, oh my God, I thought about you a minute ago. You just called me, that's amazing. So, you know, some of that is this, but some of that might be that there are, within our brain, sensors for waves that we emit that we're not even aware of. And this whole concept of when I hug my children, there's such an emotional transfer there that we don't comprehend. I mean, sure, yeah, of course, we're all like hardwire for all kinds of touchy feely things between parents and kids is beautiful, between partners is beautiful, et cetera. But then there are intangible aspects of human communication that I don't think it's unfathomable that our brain has actually evolved ways and sensors for it that we just don't capture. We don't understand the function of the vast majority of our neurons. And maybe our brain is already sensing it, but even worse, maybe our brain is not sensing it at all. And we're oblivious to this until we build a machine that suddenly is able to sort of capture so much more of what's happening in the natural world. So what you're saying is we're going, physics is going to discover a sensor for love. And maybe dogs are off scale for that. And we've been oblivious to it the whole time because we didn't have the right sensor. And now you're gonna have a little wrist that says, oh my God, I feel all this love in the house. I sense a disturbance in the forest. It's all around us and cats will have zero. None. None. It's just, nothing. But let's take a step back to our unfortunate place. To one of the 400 topics that we had actually planned for. Well, but to our sad time in 2020 when we only have just a few sensors and very primitive early computers. So in your, you have a foot in computer science and a foot in biology. In your sense, how do computers represent information differently than like the genome or biological systems? So first of all, let me correct that, no, we're in an amazing time in 2020. Computer science is totally awesome and physics is totally awesome. And we have understood so much of the natural world than ever before. So I am extremely grateful and feeling extremely lucky to be living in the time that we are. Because first of all, who knows when the asteroid will hit. And second, of all times in humanity, this is probably the best time to be a human being and this might actually be the best place to be a human being. So anyway, for anyone who loves science, this is it. This is awesome, it's a great time. At the same time, just a quick comment. All I meant is that if we look several hundred years from now and we end up somehow not destroying ourselves, people will probably look back at this time in computer science and at your work of Manos at MIT. As infantile. As infantile and silly and how ignorant it all was. I like to joke very often with my students that we've written so many papers, we've published so much, we've been cited so much and every single time I tell my students, you know, the best is ahead of us. What we're working on now is the most exciting thing I've ever worked on. So in a way, I do have this sense of, yeah, even the papers I wrote 10 years ago, they were awesome at the time, but I'm so much more excited about where we're heading now. And I don't mean to minimize any of the stuff we've done in the past, but there's just this sense of excitement about what you're working on now that as soon as a paper is submitted, it's like, ugh, it's old. Like, you know, I can't talk about that anymore. I'm not gonna talk about it. At the same time, you're not, you probably are not going to be able to predict what are the most impactful papers and ideas. When people look back 200 years from now at your work, what would be the most exciting papers? And it may very well be not the thing that you expected. Or the things you got awards for or, you know, that kind of. This might be true in some fields. I don't know, I feel slightly differently about it in our field. I feel that I kind of know what are the important ones. And there's a very big difference between what the press picks up on and what's actually fundamentally important for the field. And I think for the fundamentally important ones, we kind of have a pretty good idea what they are. And it's hard to sometimes get the press excited about the fundamental advances, but, you know, we take what we get and celebrate what we get. And sometimes, you know, one of our papers, which was in a minor journal, made the front page of Reddit and suddenly had like hundreds of thousands of views. Even though it was in a minor journal, because, you know, somebody pitched it the right way that it suddenly caught everybody's attention. Whereas other papers that are sort of truly fundamental, you know, we have a hard time getting the editors even excited about them when so many hundreds of people are already using the results and building upon them. So I do appreciate that there's a discrepancy between the perception and the perceived success and the awards that you get for various papers. But I think that fundamentally, I know that, you know, some paper, I'm, so, so. So is there a paper that you're most proud of? See, now you just, you trapped yourself. No, no, no, no. I mean, is there a line of work that you have a sense is really powerful that you've done to date? You've done so much work in so many directions, which is interesting. Is there something where you think is quite special? I mean, it's like asking me to say which of my three children I love best. I mean. I mean. I mean. I mean. I mean. I mean. I mean, and it's such a gimme question that is so, so difficult not to brag about the awesome work that my team and my students have done. And I'll just mention a few off the top of my head. I mean, basically there's a few landmark papers that I think have shaped my scientific path. And I like to somehow describe it as a linear continuation of one thing led to another, led to another, led to another. And it kind of all started with, skip, skip, skip, skip, skip. Let me try to start somewhere in the middle. So my first PhD paper was the first comparative analysis of multiple species. So multiple complete genomes. So for the first time, we basically developed a concept of genome-wide evolutionary signatures. The fact that you could look across the entire genome and understand how things evolve. And from these signatures of evolution, you could go back and study any one region and say, that's a protein coding gene. That's an RNA gene. That's a regulatory motif. That's a binding site and so on and so forth. So. Oh, sorry, so comparing different species. Species of the same. So take human, mouse, rat, and dog. You know, they're all animals. They're all mammals. They're all performing similar functions with their heart, with their brain, with their lungs, et cetera, et cetera, et cetera. So there's many functional elements that make us uniquely mammalian. And those mammalian elements are actually conserved. 99% of our genome does not code for protein. 1% codes for protein. The other 99%, we frankly didn't know what it does until we started doing this comparative genomic studies. So basically, these series of papers in my career have basically first developed that concept of evolutionary signatures and then applied them to yeast, applied them to flies, applied them to four mammals, applied them to 17 fungi, applied them to 12 Drosophila species, applied them to then 29 mammals, and now 200 mammals. So sorry, so can we, so the evolutionary signatures, it seems like such a fascinating idea. I'm probably gonna linger on your early PhD work for two hours. But what is, how can you reveal something interesting about the genome by looking at the multiple species and looking at the evolutionary signatures? Yeah, so you basically align the matching regions. So everything evolved from a common ancestor way, way back. And mammals evolved from a common ancestor about 60 million years back. So after the meteor that killed off the dinosaurs landed near Machu Picchu, we know the crater. It didn't allegedly land. That was the aliens, okay. No, just slightly north of Machu Picchu in the Gulf of Mexico, there's a giant hole that that meteor impact. Sorry, is that definitive to people? Have people conclusively figured out what killed the dinosaurs? I think so. So it was a meteor? Well, you know, for volcanic activity, all kinds of other stuff is coinciding. But the meteor is pretty unique. And we now have- That's also terrifying. I wouldn't, if I, we still have a lot of 2020 left. So if anything comes- No, no, but think about it this way. So the dinosaurs ruled the earth for 175 million years. We humans have been around for what? Less than 1 million years, if you're super generous about what you call humans. And you include chimps basically. So we are just getting warmed up. And we've ruled the planet much more ruthlessly than Tyrannosaurus Rex. T-Rex had much less of an environmental impact than we did. And if you give us another 174 million years, humans will look very different if we make it that far. So I think dinosaurs basically are much more of life history on earth than we are in all respects. But look at the bright side. When they were killed off, another life form emerged, mammals. And that's that whole evolutionary branching that's happened. So you kind of have, when you have these evolutionary signatures, is there basically a map of how the genome changed? Yeah, exactly. So now you can go back to this early mammal that was hiding in caves, and you can basically ask what happened after the dinosaurs were wiped out. A ton of evolutionary niches opened up. And the mammals started populating all of these niches. And in that diversification, there was room for expansion of new types of functions. So some of them populated the air with bats flying, a new evolution of light. Some populated the oceans with dolphins and whales going off to swim, et cetera. But we all are fundamentally mammals. So you can take the genomes of all these species and align them on top of each other and basically create nucleotide resolution correspondences. What my PhD work showed is that when you do that, when you line up species on top of each other, you can see that within protein coding genes, there's a particular pattern of evolution that is dictated by the level at which evolutionary selection acts. If I'm coding for a protein and I change the third codon position of a triplet that codes for that amino acid, the same amino acid will be encoded. So that basically means that any kind of mutation that preserves that translation, that is invariant to that ultimate functional assessment that evolution will give, is tolerated. So for any function that you're trying to achieve, there's a set of sequences that encode it. You can now look at the mapping, the graph isomorphism, if you wish, between all of the possible DNA encodings of a particular function and that function. And instead of having just that exact sequence at the protein level, you can think of the set of protein sequences that all fulfill the same function. What's evolution doing? Evolution has two components. One component is random, blind, and stupid mutation. The other component is super smart, ruthless selection. That's my mom calling from Greece. Yes, I might be a fully grown man, but I am a Greek. Did you just cancel the call? Wow, you're in trouble. I know, I'm in trouble. No, she's gonna be calling the cops. I'm gonna edit this clip out and send it to her. Honey, are you okay? So there's a lot of encoding for the same kind of function. Yeah, so you now have this mapping between all of the set of functions that could all encode the same, all of the set of sequences that can all encode the same function. What evolutionary signatures does is that it basically looks at the shape of that distribution of sequences that all encode the same thing. And based on that shape, you can basically say, ooh, proteins have a very different shape than RNA structures, than regulatory motifs, et cetera. So just by scanning a sequence, ignoring the sequence, and just looking at the patterns of change, I'm like, wow, this thing is evolving like a protein, and that thing is evolving like a motif, and that thing is evolving. So that's exactly what we just did for COVID. So our paper that we posted in bioRxiv about coronavirus basically took this concept of evolutionary signatures and applied it on the SARS-CoV-2 genome that is responsible for the COVID-19 pandemic. And comparing it to- To 44 Cervicovirus species, so this is the beta. What word did you just use? Cervicovirus. Cervicovirus, so SARS-related beta coronavirus. It's a portmanteau of a bunch. So that family of viruses. Yeah, so- How big is that family, by the way? We have 44 species that- 44 species in the family? Yeah. Virus is a clever bunch. No, no, but there's just 44, and again, we don't call them species in viruses, we call them strains, but anyway, there's 44 strains, and that's a tiny little subset of maybe another 50 strains that are just far too distantly related. Most of those only infect bats as the host, and a subset of only four or five have ever infected humans. And we basically took all of those and we aligned them in the same exact way that we've aligned mammals, and then we looked at what proteins are, which of the currently hypothesized genes for the coronavirus genome are in fact evolving like proteins and which ones are not. And what we found is that ORF10, the last little open reading frame, the last little gene in the genome, is bogus. That's not a protein at all. What is it? It's an RNA structure. That doesn't have a- It doesn't get translated into amino acids. And that, so it's important to narrow down to basically discover what's useful and what's not. Exactly. Basically, what is even the set of genes? The other thing that these evolutionary signatures showed is that within ORF3A lies a tiny little additional gene encoded within the other gene. So you can translate a DNA sequence in three different reading frames. If you start in the first one, it's, you know, ATG, et cetera. If you start on the second one, it's TGC, et cetera. And there's a gene within a gene. So there's a whole other protein that we didn't know about that might be super important. So we don't even know the building blocks of SARS-CoV-2. So if we want to understand coronavirus biology and eventually fight it successfully, we need to even have the set of genes. And these evolutionary signatures that I developed in my PhD work- Are you really- We just recently used. You know what, let's run with that tangent for a little bit, if it's okay. Can we talk about the COVID-19 a little bit more? Like, what's your sense about the genome, the proteins, the functions that we understand about COVID-19? Where do we stand in your sense? What are the big open problems? And also, you know, you kind of said it's important to understand what are the, like, the important proteins, and like, why is that important? So what else does the comparison of these species tell us? What it tells us is how fast are things evolving? It tells us about at what level is the acceleration or deceleration pedal set for every one of these proteins. So the genome has, you know, 30 some genes. Some genes evolve super, super fast. Others evolve super, super slow. If you look at the polymerase gene that basically replicates the genome, that's a super slow evolving one. If you look at the nucleocapsid protein, that's also super slow evolving. If you look at the spike one protein, this is the part of the spike protein that actually touches the ACE2 receptor and then enables the virus to attach to your cells. That's the thing that gives it that visual- Yeah, the corona look, basically. The corona look, yeah. So basically, the spike protein sticks out of the virus, and there's a first part of the protein, S1, which basically attaches to the ACE2 receptor. And then S2 is the latch that sort of pushes and channels the fusion of the membranes and then the incorporation of the viral RNA inside our cells, which then gets translated into all of these 30 proteins. So the S1 protein is evolving ridiculously fast. So if you look at the stop versus gas pedal, the gas pedal is all the way down. Orf8 is also evolving super fast, and Orf6 is evolving super fast. We have no idea what they do. We have some idea, but nowhere near what S1 is. So what the- Isn't that terrifying that S1 is evolving? That means that's a really useful function. And if it's evolving fast, doesn't that mean new strains could be created or it does something? That means that it's searching for how to match, how to best match the host. So basically, anything in general, in evolution, if you look at genomes, anything that's contacting the environment is evolving much faster than anything that's internal. And the reason is that the environment changes. So if you look at the evolution of the Cerbicoviruses, the S1 protein has evolved very rapidly because it's attaching to different hosts each time. We think of them as bats, but there's thousands of species of bats. And to go from one species of bat to another species of bat, you have to adjust S1 to the new S2 receptor that you're gonna be facing in that new species. Sorry, quick tangent. Is it fascinating to you that viruses are doing this? I mean, it feels like they're this intelligent organism. I mean, does it give you pause how incredible it is that the evolutionary dynamics that you're describing is actually happening and they're figuring out how to jump from bats to humans all in this distributed fashion? And then most of us don't even say they're alive or intelligent or whatever. So intelligence is in the eye of the beholder. You know, stupid is as stupid does, as Forrest Gump would say. And intelligent is as intelligent does. So basically, if the virus is finding solutions that we think of as intelligent, yeah, it's probably intelligent. But that's again in the eye of the beholder. Do you think viruses are intelligent? Of course not. Really? No. It's so incredible. So remember when I was talking about the two components of evolution? One is the stupid mutation, which is completely blind, and the other one is the super smart selection, which is ruthless. So it's not viruses who are smart. It's this component of evolution that's smart. So it's evolution that sort of appears smart. And how is that happening? By huge parallel search across thousands of parallel infections throughout the world right now. Yes, but so to push back on that, so yes, so then the intelligence is in the mechanism. But then by that argument, viruses would be more intelligent because there's just more of them. So the search, they're basically the brute force search that's happening with viruses, because there's so many more of them than humans, then they're taken as a whole are more intelligent. I mean, so you don't think it's possible that, I mean, who runs, would we even be here if viruses weren't, I mean, who runs this thing? So humans or viruses? So let me answer, yeah, let me answer your question. So we would not be here if it wasn't for viruses. And part of the reason is that if you look at mammalian evolution early on in this mammalian radiation that basically happened after the death of the dinosaurs, is that some of the viruses that we had in our genome spread throughout our genome and created binding sites for new classes of regulatory proteins. And these binding sites that landed all over our genome are now control elements that basically control our genes and sort of help the complexity of the circuitry of mammalian genomes. So everything's co-evolution. And- We're working together. Yeah. And yet you say they're dumb. We've co-opted them. No, I never said they're dumb. They just don't care. They don't care. Another thing, oh, is the virus trying to kill us? No, it's not. The virus is not trying to kill you. It's actually actively trying to not kill you. So when you get infected, if you die, Palmer, I killed him, is what the reaction of the virus will be. Why? Because that virus won't spread. Many people have a misconception of, oh, viruses are smart, or, oh, viruses are mean. They don't care. It's like you have to clean yourself of any kind of anthropomorphism out there. I don't know. Oh, yes. So there's a sense when taken as a whole that there's a- It's in the eye of the beholder. Stupid is as stupid does. Intelligent is as stupid as intelligent does. So if you want to call them intelligent, that's fine. Then I- Because the end result is that they're finding amazing solutions. Right. I mean, I am in awe. They're so dumb about it. They're just doing dumb- They don't care. They're dumb and they're not- They just don't care. They don't care. The care word is really interesting. Exactly. I mean, there could be an argument that they're conscious. They're just dividing. They're not. They're just dividing. They're just a little entity which happens to be dividing and spreading. It doesn't want to kill us. In fact, it prefers not to kill us. It just wants to spread. And when I say wants, again, I'm anthropomorphizing, but it's just that if you have two versions of a virus, one acquires a mutation that spreads more, that's gonna spread more. One acquires a mutation that spreads less, that's gonna be lost. One acquires a mutation that enters faster, that's gonna be kept. One acquires a mutation that kills you right away, it's gonna be lost. So over evolutionary time, the viruses that spread super well but don't kill the host are the ones that are gonna survive. Yeah, but so you brilliantly described the basic mechanisms of how it all happens, but when you zoom out and you see the, you know, the entirety of viruses, maybe across different strains of viruses, it seems like a living organism. I am in awe of biology. I find biology amazingly beautiful. I find the design of the current coronavirus, however lethal it is, amazingly beautiful. The way that it is encoded, the way that it tricks your cells into making 30 proteins from a single RNA. Human cells don't do that. Human cells make one protein from each RNA molecule. They don't make two, they make one. We are hardwired to make only one protein from every RNA molecule, and yet this virus goes in, throws in a single messenger RNA. Just like any messenger RNA, we have tens of thousands of messenger RNAs in our cells in any one time, in every one of our cells. It throws in one RNA, and that RNA is so, I'm gonna use your word here, not my word, intelligent, that it hijacks the entire machinery of your human cell. It basically has, at the beginning, a giant open reading frame. That's a giant protein that gets translated. Two thirds of that RNA make a single giant protein. That single protein is basically what a human cell would make. It's like, oh, here's a start codon. I'm gonna start translating here. Human cells are kind of dumb, I'm sorry. Again, this is not the word that we'd normally use, but the human cell basically is, oh, this is an RNA, must be mine, let me translate, and it starts translating it, and then you're in trouble. Why? Because that one protein, as it's growing, gets cleaved into about 20 different peptides. The first peptide and the second peptide start interacting, and the third one and the fourth one, and they shut off the ribosome of the whole cell to not translate human RNAs anymore. So the virus basically hijacks your cells, and it cuts, it cleaves every one of your human RNAs to basically say to the ribosome, don't translate this one, junk. Don't look at this one, junk. And it only spares its own RNAs because they have a particular mark that it spares. Then all of the ribosomes that normally make protein in your human cells are now only able to translate viral RNAs and make more and more and more and more of them. That's the first 20 proteins. In fact, halfway down about protein 11, between 11 and 12, you basically have a translational slippage where the ribosome skips reading frame, and it translates from one reading frame to another reading frame. That means that about half of them are gonna be translated from one to 11, and the other half are gonna be translated from 12 to 16. Wow, it's gorgeous. And then, then you're done. Then that mRNA will never translate the last 10 proteins, but spike is the one right after that one. So how does spike even get translated? This positive strand RNA virus has a reverse transcriptase, which is an RNA-based reverse transcriptase. So from the RNA on the positive strand, it makes an RNA on the negative strand. And in between every single one of these genes, these open reading frames, there's a little signal, AACGCA or something like that, that basically loops over to the beginning of the RNA. And basically, instead of sort of having a single full negative strand RNA, it basically has a partial negative strand RNA that ends right before the beginning of that gene, and another one that ends right before the beginning of that gene. These negative strand RNAs now make positive strand RNAs that then loop to the human host cell, just like any other human mRNA. It's like, ooh, great, I'm gonna translate that one, because it doesn't have the cleaving that the virus has now put on all your human genes. And then you've lost the battle. That cell is now only making proteins for the virus that will then create the spike protein, the envelope protein, the membrane protein, the nucleocapsid protein that will package up the RNA, and then sort of create new viral envelopes. And these will then be secreted out of that cell in new little packages that will then infect the rest of the cells. Repeat the whole process again. It's beautiful, right? It's mind-boggling. It's hard not to anthropomorphize it. I know, but it's so gorgeous. So there is a beauty to it. Of course. Is it terrifying to you? So this is something that has happened throughout history. Humans have been nearly wiped out over and over and over again, and yet never fully wiped out. So I'm not concerned about the human race. I'm not even concerned about the impact on sort of our survival as a species. This is absolutely something, I mean, human life is so invaluable, and every one of us is so invaluable, but if you think of it as sort of, is this the end of our species? By no means, basically. So let me explain. The Black Death killed what, 30% of Europe? That has left a tremendous imprint, a huge hole, a horrendous hole in the genetic makeup of humans. There's been series of wiping out of huge fractions of entire species or just entire species altogether, and that has a consequence on the human immune repertoire. If you look at how Europe was shaped and how Africa was shaped by malaria, for example, all the individuals that carry a mutation that protects you from malaria were able to survive much more. And if you look at the frequency of sickle cell disease and the frequency of malaria, the maps are actually showing the same pattern, the same imprint on Africa, and that basically led people to hypothesize that the reason why sickle cell disease is so much more frequent in Africa than in Americans of African descent is because there was selection in Africa against malaria, leading to sickle cell, because when the cells sickle, malaria is not able to replicate inside your cells as well, and therefore you protect against that. So if you look at human disease, all of the genetic associations that we do with human disease, you basically see the imprint of these waves of selection killing off gazillions of humans. And there's so many immune processes that are coming up as associated with so many different diseases. The reason for that is similar to what I was describing earlier, where the outward facing proteins evolve much more rapidly because the environment is always changing. But what's really interesting, the human genome is that we have co-opted many of these immune genes to carry out non-immune functions. For example, in our brain, we use immune cells to cleave off neuronal connections that don't get used. This whole use it or lose it, we know the mechanism. It's microglia that cleave off neuronal synaptic connections that are just not utilized. When you utilize them, you mark them in a particular way that basically when the microglia come, tell it, don't kill this one, it's used now. And the microglia will go off and kill the ones you don't use. This is an immune function, which is co-opted to do non-immune things. If you look at our adipocytes, M1 versus M2 macrophages inside our fat will basically determine whether you're obese or not. And these are again immune cells that are resident and living within these tissues. So many disease associations. That's fascinating that we co-opt these kinds of things for incredibly complicated functions. Exactly, evolution works in so many different ways, which are all beautiful and mysterious. But not intelligent. Not intelligent, it's in the eye of the beholder. But the point that I'm trying to make is that if you look at the imprint that COVID will have, hopefully it will not be big. Hopefully the US will get attacked together and stop the virus from spreading further. But if it doesn't, it's having an imprint on individuals who have particular genetic repertoires. So if you look at now the genetic associations of blood type and immune function cells, et cetera, there's actually association, genetic variation that basically says how much more likely am I or you to die if we contact the virus. And it's through these rounds of shaping the human genome that humans have basically made it so far. And selection is ruthless and it's brutal and it only comes with a lot of killing. But this is the way that viruses and environments have shaped the human genome. Basically when you go through periods of famine, you select for particular genes. And what's left is not necessarily better, it's just whatever survived. And it may have been the surviving one back then, not because it was better, maybe the ones that ran slower survived. I mean, again, not necessarily better. But the surviving ones are basically the ones that then are shaped for any kind of subsequent evolutionary condition and environmental condition. But if you look at, for example, obesity, obesity was selected for, basically the genes that now predisposes to obesity were at 2% frequency in Africa. They rose to 44% frequency in Europe. Wow, that's fascinating. Because you basically went through the ice ages and there was a scarcity of food. So there was a selection to being able to store every single calorie you consume. Eventually, environment changes. So the better allele, which was the fat storing allele, became the worst allele, because it's the fat storing allele. It still has the same function. So if you look at my genome, speaking of mom calling, mom gave me a bad copy of that gene, this FTO locus. Basically makes me- The one that has to do with- Obesity. With obesity. Yeah, I basically now have a bad copy from mom that makes me more likely to be obese. And I also have a bad copy from dad that makes me more likely to be obese. So I'm homozygous. And that's the allele, it's still the minor allele, but it's at 44% frequency in Southeast Asia, 42% frequency in Europe, even though it started at 2%. It was an awesome allele to have 100 years ago. Right now, it's a pretty terrible allele. So the other concept is that diversity matters. If we had 100 million nuclear physicists living the earth right now, we'd be in trouble. You need diversity, you need artists, and you need musicians, and you need mathematicians, and you need politicians, yes, even those. And you need- Well, let's not get crazy. But because then if a virus comes along or whatever- Exactly, exactly. So no, there's two reasons. Number one, you want diversity in the immune repertoire, and we have built in diversity. So basically, they are the most diverse. Basically, if you look at our immune system, there's layers and layers of diversity. Like the way that you create your cells generates diversity because of the selection for the VDJ recombination that basically eventually leads to a huge number of repertoires. But that's only one small component of diversity. The blood type is another one. The major histocompatibility complex, the HLA alleles, are another source of diversity. So the immune system of humans is by nature incredibly diverse. And that basically leads to resilience. So basically what I'm saying that I don't worry for the human species. Because we are so diverse immunologically, we are likely to be very resilient against so many different attacks like this current virus. So you're saying natural pandemics may not be something that you're really afraid of because of the diversity in our genetic makeup. What about engineered pandemics? Do you have fears of us messing with the makeup of viruses? Well, yeah, let's say with the makeup of viruses to create something that we can't control and would be much more destructive than it would come about naturally. Remember how we were talking about how smart evolution is? Humans are much dumber. So. You mean like human scientists, engineers? Yeah, humans, humans just like. Humans overall? Yeah, humans overall. Okay. But I mean, even the sort of synthetic biologists. You know, basically, if you were to create, you know, virus like SARS that will kill a lot of people, you would probably start with SARS. So whoever, you know, would like to design such a thing would basically start with a SARS tree or at least some relative of SARS. The source genome for the current virus was something completely different. It was something that has never infected humans. No one in their right mind would have started there. But when you say source, it's like the nearest. The nearest relative. Relative. Is in a whole other branch. No species of which has ever infected humans in that branch. So, you know, let's put this to rest. This was not designed by someone to kill off the human race. So you don't believe it was engineered? The. More likely. Yeah, the path to engineering a deadly virus would not come from this strain that was used. Moreover, there's been various claims of, ha ha, this was mixed and matched in a lab because the S1 protein has three different components, each of which has a different evolutionary tree. So, you know, a lot of popular press basically said, aha, this came from pangolin and this came from, you know, all kinds of other species. This is what has been happening throughout the coronavirus. So basically the S1 protein has been recombining across species all the time. Remember when I was talking about the positive strand, the negative strand, subgenomic RNAs? These can actually recombine. And if you have two different viruses infecting the same cell, they can actually mix and match between the positive strand and the negative strand and basically create a new hybrid virus with recombination that now has the S1 from one and the rest of the genome from another. And this is something that happens a lot in S1, in Orphate, et cetera. And that's something that's true of the whole tree. For the whole family of coronaviruses. So it's not like someone has been messing with this for millions of years and, you know, changing the species. Because it happens naturally. That's, again, beautiful that that somehow happens, that they recombine. So two different strands can infect the body and then recombine. So all of this actually magic happens inside hosts. Like all, like the- Yeah, yeah. That's why classification-wise, virus is not thought to be alive because it doesn't self-replicate, it's not autonomous. It's something that enters a living cell and then co-opts it to basically make it its own. But by itself, people ask me, how do we kill this bastard? I'm like, you stop it from replicating. It's not like a bacterium that will just live in a, you know, puddle or something. It's a virus. Viruses don't live without their host. And they only live without their host for very little time. So if you stop it from replicating, it'll stop from spreading. I mean, it's not like HIV, which can stay dormant for a long time. Basically, coronaviruses just don't do that. They're not integrating genomes. They're RNA genomes. So if it's not expressed, it degrades. RNA degrades. It doesn't just stick around. Well, let me ask also about the immune system you mentioned. A lot of people kind of ask, you know, how can we strengthen the immune system to respond to this particular virus, but in viruses in general? Do you have, from a biological perspective, thoughts on what we can do as humans to strengthen our immune system? If you look at the death rates across different countries, people with less vaccination have been dying more. If you look at North Italy, the vaccination rates are abysmal there. And a lot of people have been dying. If you look at Greece, very good vaccination rates. Almost no one has been dying. So yes, there's a policy component. So Italy reacted very slowly. Greece reacted very fast. So yeah, many fewer people died in Greece. But there might actually be a component of genetic immune repertoire. Basically, how did people die off, you know, in the history of the Greek population versus the Italian population. There's a- That's interesting to think about. And then there's a component of what vaccinations did you have as a kid and what are the off-target effects of those vaccinations? So basically, a vaccination can have two components. One is training your immune system against that specific insult. The second one is boosting up your immune system for all kinds of other things. If you look at allergies, Northern Europe, super clean environments, tons of allergies. Southern Europe, my kids grew up eating dirt, no allergies. So growing up, I never had even heard of what allergies are. Like, really, allergies? And the reason is that I was playing in the garden. I was putting all kinds of stuff in my mouth from all kinds of dirt and stuff. Tons of viruses there, tons of bacteria there. You know, my immune system was built up. So the more you protect your immune system from exposure, the less opportunity it has to learn about non-self repertoire in a way that prepares it for the next insult. So- So it's a horizontal thing, too? Like, so it's throughout your lifetime and the lifetime of the people that, your ancestors? That kind of thing? Yeah, absolutely. What about the, so again, it returns against free will. On the free will side of things, is there something we could do to strengthen our immune system in 2020? Is there, you know, exercise, diet, all that kind of stuff? So it's kind of funny. There's a cartoon that basically shows two windows with a teller in each window. One has a humongous line and the other one has no one. The one that has no one above says health. No, it says exercise and diet. And the other one says pill. Yeah. And there's a huge line for pill. So we're looking basically for magic bullets for sort of ways that we can, you know, beat cancer and beat coronavirus and beat this and beat that. And it turns out that the window with like, just diet and exercise is the best way to boost every aspect of your health. If you look at Alzheimer's, exercise and nutrition. I mean, you're like, really? For my brain, neurodegeneration? Absolutely. If you look at cancer, exercise and nutrition. If you look at coronavirus, exercise and nutrition. Every single aspect of human health gets improved. And one of the studies we're doing now is basically looking at what are the effects of diet and exercise? How similar are they to each other? We basically take in diet intervention and exercise intervention in human and in mice. And we're basically doing single cell profiling of a bunch of different tissues to basically understand how are the cells, both the stromal cells and the immune cells of each of these tissues, responding to the effect of exercise. What are the communication networks between different cells where the muscle that exercises sends signals through the bloodstream, through the lymphatic system, through all kinds of other systems that give signals to other cells that I have exercised and you should change in this particular way, which basically reconfigure those receptor cells with the effect of exercise. Again- How well understood is those reconfigurations? Very little. We're just starting now, basically. Is the hope there to understand the effect on, so like the effect on the immune system? On the immune system, the effect on brain, the effect on your liver, on your digestive system, on your adipocytes? Adipo is the most misunderstood organ. Everybody thinks, oh, fat, terrible. No, fat is awesome. Your fat cells is what's keeping you alive because if you didn't have your fat cells, all those lipids and all those calories would be floating around in your blood and you'd be dead by now. Your adipocytes are your best friend. They're basically storing all these excess calories so that they don't hurt all of the rest of the body. And they're also fat-burning in many ways. So, again, when you don't have the homozygous version that I have, your cells are able to burn calories much more easily by sort of flipping a master metabolic switch that involves this FTO locus that I mentioned earlier and its target genes, RX3 and RX5, that basically switch your adipocytes during their three first days of differentiation as they're becoming mature adipocytes to basically become either fat-burning or fat-storing fat cells and the fat-burning fat cells are your best friend. They're much closer to muscle than they are to white adipocytes. Is there a lot of difference between people like that you could give, science could eventually give advice that is very generalizable or is our differences in our genetic makeup, like you mentioned, is that going to be basically something we have to be very specialized individuals? Any advice we give in terms of diet, like what we were just talking about? Believe it or not, the most personalized advice that you give for nutrition don't have to do with your genome. They have to do with your gut microbiome, with the bacteria that live inside you. So, most of your digestion is actually happening by species that are not human inside you. You have more non-human cells than you have human cells. You're basically a giant bag of bacteria with a few human cells along. And those do not necessarily have to do with your genetic makeup? They interact with your genetic makeup. They interact with your epigenome. They interact with your nutrition. They interact with your environment. They're basically an additional source of variation. So, when you're thinking about sort of personalized nutritional advice, part of that is actually how do you match your microbiome and part of that is how do we match your genetics? But again, this is a very diverse set of contributors and the effect sizes are not enormous. So, I think the science for that is not fully developed yet. Speaking of diets, because I've wrestled in combat sports, sports my whole life, where weight matters. So, you have to cut and all that stuff. One thing I've learned a lot about my body and it seems to be, I think, true about other people's bodies is that you can adjust to a lot of things. That's the miraculous thing about this biological system is like I fast often. I used to eat like five, six times a day and thought that was absolutely necessary. How could you not eat that often? And then when I started fasting, your body adjusts to that and you learn how to not eat. And it was, if you just give it a chance for a few weeks, actually, over a period of a few weeks, your body can adjust to anything. And that's such a beautiful thing. So, I'm a computer scientist and I've basically gone through periods of 24 hours without eating or stopping. And then I'm like, ooh, must eat. And I eat a ton. I used to order two pizzas just with my brother. So, I've gone through these extremes as well and I've gone the whole intermittent fasting thing. So, I can sympathize with you both on the seven meals a day to the zero meals a day. So, I think when I say everything with moderation, I actually think your body responds interestingly to these different changes in diet. I think part of the reason why we lose weight with pretty much every kind of change in behavior is because our epigenome and the set of proteins and enzymes that are expressed and our microbiome are not well suited to that nutritional source. And therefore, they will not be able to sort of catch everything that you give them. And then a lot of that will go undigested and that basically means that your body can then lose weight in the short term, but very quickly will adjust to that new normal and then will be able to sort of perhaps gain a lot of weight from the diet. So, anyway, I mean, there's also studies in factories where basically people dim the lights and then suddenly everybody started working better. It was like, wow, that's amazing. Three weeks later, they made the lights a little brighter. Everybody started working better. So, any kind of intervention has a placebo effect of wow, now I'm healthier and I'm gonna be running more often, et cetera. So, it's very hard to uncouple the placebo effect of wow, I'm doing something to intervene on my diet from the wow, this is actually the right thing for me. So, you know. Yeah, from the perspective from a nutrition science, psychology, both things I'm interested in, especially psychology, it seems that it's extremely difficult to do good science because there's so many variables involved. It's so difficult to control the variables, so difficult to do sufficiently large scale experiments, both sort of in terms of number of subjects and temporal, like how long you do the study for, that it just seems like it's not even a real science for now, like nutrition science. I wanna jump into the whole placebo effect for a little bit here and basically talk about the implications of that. If I give you a sugar pill and I tell you it's a sugar pill, you won't get any better. But if I tell you a sugar pill and I tell you, wow, this is an amazing drug, it actually will stop your cancer, your cancer will actually stop with much higher probability. What does that mean? That's so amazing. That means that if I can trick your brain into thinking that I'm healing you, your brain will basically figure out a way to heal itself, to heal the body. And that tells us that there's so much that we don't understand in the interplay between our cognition and our biology that if we were able to better harvest the power of our brain to sort of impact the body through the placebo effect, we would be so much better in so many different things. Just by tricking yourself into thinking that you're doing better, you're actually doing better. So there's something to be said about sort of positive thinking, about optimism, about sort of just getting your brain and your mind into the right mindset that helps your body and helps your entire biology. Yeah, from a science perspective, that's just fascinating. Obviously, most things about the brain is a total mystery for now, but that's a fascinating interplay that the brain can reduce. The brain can help cure cancer. I don't even know what to do with that. I mean, the way to think about that is the following. The converse of the equation is something that we are much more comfortable with. Like, oh, if you're stressed, then your heart rate might rise and all kinds of sort of toxins might be released and that can have a detrimental effect in your body, et cetera, et cetera, et cetera. So maybe it's easier to understand your body healing from your mind by your mind is not killing your body, or at least it's killing it less. So I think that aspect of the stress equation is a little easier for most of us to conceptualize, but then the healing part is perhaps the same pathways, perhaps different pathways, but again, something that is totally untapped scientifically. I think we tried to bring this question up a couple of times, but let's return to it again. Is what do you think is the difference between the way a computer represents information, the human genome represents and stores information? And maybe broadly, what is the difference between how you think about computers and how you think about biological systems? So I made the very provocative claim earlier that we are a digital computer, like I said, at the core lies a digital code, and that's true in many ways, but surrounding that digital core, there's a huge amount of analog. If you look at our brain, it's not really digital. If you look at our sort of RNA and all of that stuff inside our cells, it's not really digital. It's really analog in many ways, but let's start with the code and then we'll expand to the rest. So the code itself is digital. So there's genes. You can think of the genes as, I don't know, the procedures, the functions inside your language. And then somehow you have to turn these functions on. How do you call a gene? How do you call that function? The way that you would do it in old programming languages is go to address whatever in your memory, and then you'd start running from there. And modern programming languages have encapsulated this into functions and objects and all of that, and it's nice and cute, but in the end, deep down, there's still an assembly code that says go to that instruction, and it runs that instruction. If you look at the human genome and the genome of pretty much most species out there, there's no go-to function. You just don't start transcribing in position 13, 13,527 in chromosome 12. You instead have content-based indexing. So at every location in the genome, in front of the genes that need to be turned on, I don't know, when you drink coffee, there's a little coffee marker in front of all of them. And whenever your cells that metabolize coffee need to metabolize coffee, they basically see coffee and they're like, ooh, let's go turn on all the coffee-marked genes. So there's basically these small motifs, these small sequences that we call regulatory motifs. They're like patterns of DNA. They're only eight characters long or so, like GAT, GCA, et cetera. And these motifs work in combinations, and every one of them has some recruitment affinity for a different protein that will then come and bind it, and together collections of these motifs create regions that we call regulatory regions that can be either promoters near the beginning of the gene, and that basically tells you where the function actually starts, where you call it, and then enhancers that are looping around of the DNA that basically bring the machinery that binds those enhancers, and then bring it onto the promoter, which then recruits the right, sort of the ribosome and the polymerase and all of that thing, which will first transcribe and then export and then eventually translate in the cytoplasm, you know, whatever, RNA molecule. So the beauty of the way that the digital computer, that's the genome, works is that it's extremely fault-tolerant. If I took your hard drive and I messed with 20% of the letters in it, of those zeros and ones, and I flipped them, you'd be in trouble. If I take the genome and I flip 20% of the letters, you probably won't even notice. And that resilience- That's fascinating, yeah. Is a key design principle, and again, I'm thermomorphizing here, but it's a key driving principle of how biological systems work. They're first resilient and then anything else. And when you look at this incredible beauty of life from the most, I don't know, beautiful, I don't know, human genome, maybe, of humanity and all of the ideals that should come with it, to the most terrifying genome, like, I don't know, COVID-19, SARS-CoV-2, and the current pandemic, you basically see this elegance as the epitome of clean design, but it's dirty, it's a mess, it's, you know, the way to get there is hugely messy. And that's something that we as computer scientists don't embrace. We like to have clean code. Like, in engineering, they teach you about compartmentalization, about sort of separating functions, about modularity, about hierarchical design. None of that applies in biology. Testing. Testing, sure, yeah, biology does plenty of that, but I mean, through evolutionary exploration. But if you look at biological systems, first, they are robust, and then they specialize to become anything else. And if you look at viruses, the reason why they're so elegant, when you look at the design of this genome, it seems so elegant, and the reason for that is that it's been stripped down from something much larger because of the pressure to keep it compact. So many compact genomes out there have ancestors that were much larger. You don't start small and become big. You go through a loop of add a bunch of stuff, increase complexity, and then slim it down. And one of my early papers was, in fact, on genome duplication. One of the things we found is that baker's yeast, which is the yeast that you use to make bread, but also the yeast that you use to make wine, which is basically the dominant species when you go in the fields of Tuscany and you say, you know, what's out there, is basically Saccharomyces cerevisiae, or the way my Italian friends say, Saccharomyces cerevisiae. So, so. Which means what? Oh, Saccharomyces, okay, I'm sorry, I'm Greek. So yeah, zaharo, mykis, zaharo is sugar, mykis is fungus. Yes. Cerevisiae, cerveza, beer. So it means the sugar fungus of beer. Yeah. You know, less, less, less sounding to the ear. Still poetic, yep. So anyway, Saccharomyces cerevisiae, basically the major baker's yeast out there, is the descendant of a whole genome duplication. Why would a whole genome duplication even happen? When it happened is coinciding with about a hundred million years ago and the emergence of fruit-bearing plants. Why fruit-bearing plants? Because animals would eat the fruit, would walk around and poop huge amounts of nutrients along with a seed for the plants to spread. Before that, plants were not spreading through animals, they were spreading through wind and all kinds of other ways. But basically the moment you have fruit-bearing plants, these plants are basically creating this abundance of sugar in the environment. So there's an evolutionary niche that gets created. And in that evolutionary niche, you basically have enough sugar that a whole genome duplication, which initially is a very messy event, allows you to then, you know, relieve some of that complexity. So I had to pause. What does genome duplication mean? That basically means that instead of having eight chromosomes, you can now have 16 chromosomes. So, but with the duplication, at first when you go to 16, you're not using that. Oh yeah, you are. Yeah, so basically from one day to the next, you went from having eight chromosomes to having 16 chromosomes. Probably a non-disjunction event during a duplication, during a division. So you basically divide the cell instead of half the genome going this way and half the genome going the other way after duplication of the genome. You basically have all of it going to one cell. And then there's sufficient messiness there that you end up with slight differences that make most of these chromosomes be actually preserved. It's a long story short to me. But it's a big upgrade, right? So that's- Not necessarily, because what happens immediately thereafter is that you start massively losing tons of those duplicated genes. So 90% of those genes were actually lost very rapidly after whole genome duplication. And the reason for that is that biology is not intelligent. It's just ruthless selection, random mutation. So the ruthless selection basically means that as soon as one of the random mutations hit one gene, ruthless selection just kills off that gene. It's just, you know, if you have a pressure to maintain a small compact genome, you will very rapidly lose the second copy of most of your genes. And a small number, 10%, were kept in two copies. And those had to do a lot with environment adaptation, with the speed of replication, with the speed of translation, and with sugar processing. So I'm making a long story short to basically say that evolution is messy. The only way- Like so, you know, the example that I was giving of messing with 20% of your bits in your computer, totally bogus. Duplicating all your functions and just throwing them out there in the same, you know, function, just totally bogus. Like this would never work in an engineer system. But biological systems, because of this content-based indexing and because of this modularity that comes from the fact that the gene is controlled by a series of tags, and now if you need this gene in another setting, you just add some more tags that will basically turn it on also in those settings. So this gene is now pressured to do two different functions. And it builds up complexity. I see a whole genome duplication and gene duplication in general as a way to relieve that complexity. So you have this gradual buildup of complexity as functions get sort of added onto the existing genes. And then boom, you duplicate your workforce and you now have two copies of this gene. One will probably specialize to do one and the other one will specialize to do the other, or one will maintain the ancestral function, the other one will sort of be free to evolve and specialize while losing the ancestral function and so on and so forth. So that's how genomes evolve. They're just messy things, but they're extremely fault tolerant and they're extremely able to deal with mutations because that's the very way that you generate new functions. So new functionalization comes from the very thing that breaks it. So even in the current pandemic, many people are asking me, which mutations matter the most? And what I tell them is, well, we can study the evolutionary dynamics of the current genome to then understand which mutations have previously happened or not and which mutations happen in genes that evolve rapidly or not. And one of the things we found, for example, is that the genes that evolved rapidly in the past are still evolving rapidly now in the current pandemic. The genes that evolved slowly in the past are still evolving slowly. Which means that they're useful. Which means that they're under the same evolutionary pressures. But then the question is, what happens in specific mutations? So if you look at the D614 gene mutation that's been all over the news, so in position 614, in the amino acid 614, of the S protein, there's a D2G mutation that sort of has creeped over the population. That mutation, we found out through my work, disrupts a perfectly conserved nucleotide position that has never been changed in the history of millions of years of equivalent mammalian evolution of these viruses. That basically means that it's a completely new adaptation to human. And that mutation has now gone from 1% frequency to 90% frequency in almost all outbreaks. So there's a mutation, I like how you say it, in the 416, what was it? Yeah, 614, sorry. 614, all right. D614G. D6, so literally, so what you're saying is this is like a chess move. So it just mutated one letter to another. Exactly. And that hasn't happened before. Yeah, never. And this somehow, this mutation is really useful. It's really useful in the current environment of the genome, which is moving from human to human. When it was moving from bat to bat, it couldn't care less for that mutation. But it's environment specific, so now that it's moving from human to human, hoo-hoo, it's moving way better, like by orders of magnitude. So what do you, okay, so you're like tracking this evolutionary dynamics, which is fascinating, but what do you do with that? So what does that mean? What does this mean, what do you make, what do you make of this mutation in trying to anticipate, I guess? Is one of the things you're trying to do is anticipate where, how this unrolls into the future, this evolutionary dynamic? Such a great question. So there's two things. Remember when I was saying earlier, mutation is the path to new things, but also the path to break old things. So what we know is that this position was extremely preserved through gazillions of mutations. That mutation was never tolerated when it was moving from bat to bat. So that basically means that that mutation, that position is extremely important in the function of that protein. That's the first thing it tells. The second one is that that position was very well suited to bat transmission, but now is not well suited to human transmission, so it got rid of it. And it now has a new version of that amino acid that basically makes it much easier to transmit from human to human. So in terms of the evolutionary history teaching us about the future, it basically tells us here's the regions that are currently mutating, here's the regions that are most likely to mutate going forward. As you're building a vaccine, here's what you should be focusing on in terms of the most stable regions that are the least likely to mutate, or here's the newly evolved functions that are the most likely to be important because they've overcome this local maximum that it had reached in the bat transmission. So anyway, it's a tangent to basically say that evolution works in messy ways, and the thing that you would break is the thing that actually allows you to first go through a lull and then reaching new local maximum. And I often like to say that if engineers had basically designed evolution, we would still be perfectly replicating bacteria because it's by making the bacterium worse that you allow evolution to reach a new optimum. That's just a pause on that. That's so profound. That's so profound for the entirety of this scientific and engineering disciplines. Exactly. We as engineers need to embrace breaking things. We as engineers need to embrace robustness as the first principle beyond perfection because nothing's gonna ever be perfect. And when you're sending a satellite to Mars, when something goes wrong, it'll break down as opposed to building systems that tolerate failure and are resilient to that, and in fact, get better through that. So the SpaceX approach versus NASA for the- For example. Is there something we can learn about the incredible, take lessons from the incredible biological systems in their resilience, in the mushiness, the messiness to our computing systems, to our computers? It would basically be starting from scratch in many ways. It would basically be building new paradigms that don't try to get the right answer all the time, but try to get the right answer most of the time, or a lot of the time. Do you see deep learning systems in the whole world or machine learning as kind of taking a step in that direction? Absolutely, absolutely. Basically by allowing this much more natural evolution of these parameters, you basically, and if you look at sort of deep learning systems, again, they're not inspired by the genome aspect of biology, they're inspired by the brain aspect of biology. And again, I want you to pause for a second and realize the complexity of the entire human brain with trillions of connections within our neurons, with millions of cells talking to each other, is still encoded within that same genome. That same genome encodes every single freaking cell type of the entire body. Every single cell is encoded by the same code. And yet specialization allows you to have the single viral-like genome that self-replicates, the single module, modular automaton, work with other copies of itself. It's mind-boggling. Create complex organs through which blood flows. And what is that blood? The same freaking genome. Create organs that communicate with each other. And what are these organs? The exact same genome. Create a brain that is innervated by massive amounts of blood pumping energy to it, 20% of our energetic needs, to the brain, from the same genome. And all of the neuronal connections, all of the auxiliary cells, all of the immune cells, the astrocytes, the ligandrocytes, the neurons, the excitatory, the inhibitory neurons, all of the different classes of pericytes, the blood-brain barrier, all of that, same genome. One way to see that in a sad, this one is beautiful, the sad thing is thinking about the trillions of organisms that died to create that. You mean on the evolutionary path? On the evolutionary path to humans. It's crazy, there's two descendant of apes just talking on a podcast, okay. So mind-boggling. Just to boggle our minds a little bit more, us talking to each other, we are basically generating a series of vocal utterances through our pulsating of vocal cords received through this. The people who listen to this are taking a completely different path to that information transfer, yet through language. But imagine if we could connect these brains directly to each other. The amount of information that I'm condensing into a small number of words is a huge funnel, which then you receive and you expand into a huge number of thoughts from that small funnel. In many ways, engineers would love to have the whole information transfer, just take the whole set of neurons and throw them away. I mean, throw them to the other person. This might actually not be better because in your misinterpretation of every word that I'm saying, you are creating new interpretation that might actually be way better than what I meant in the first place. The ambiguity of language perhaps might be the secret to creativity. Every single time you work on a project by yourself, you only bounce ideas with one person and your neurons are basically fully cognizant of what these ideas are. But the moment you interact with another person, the misinterpretations that happen might be the most creative part of the process. With my students, every time we have a research meeting, I very often pause and say, let me repeat what you just said in a different way. And I sort of go on and brainstorm with what they were saying, but by the third time, it's not what they were saying at all. And when they pick up what I'm saying, they're like, oh, well, da-da-da, now they've sort of learned something very different from what I was saying. And that is the same kind of messiness that I'm describing in the genome itself. It's sort of embracing the messiness. And that's a feature, not a book. Exactly. And in the same way, when you're thinking about sort of these deep learning systems that will allow us to sort of be more creative perhaps, or learn better approximations of these complex functions, again, tuned to the universe that we inhabit, you have to embrace the breaking. You have to embrace the, how do we get out of these local optima? And a lot of the design paradigms that have made deep learning so successful are ways to get away from that, ways to get better training by sort of sending long range messages, these LSTM models and the sort of feed forward loops that sort of jump through layers of a convolutional neural network. All of these things are basically ways to push you out of these local maxima. And that's sort of what evolution does, that's what language does, that's what conversation and brainstorming does, that's what our brain does. So this design paradigm is something that's pervasive and yet not taught in schools, not taught in engineering schools where everything's minutely modularized to make sure that we never deviate from whatever signal we're trying to emit, as opposed to let all hell breaks loose because that's the path to paradise. The path to paradise. Yeah, I mean, it's difficult to know how to teach that and what to do with it. I mean, it's difficult to know how to build up the scientific method around messiness. I mean, it's not all messiness, we need some cleanness. And going back to the example with Mars, that's probably the place where I want to sort of moderate error as much as possible and sort of control the environment as much as possible. But if you're trying to repopulate Mars, well, maybe messiness is a good thing then. On that, you quickly mentioned this in terms of us using our vocal cords to speak on a podcast. So Elon Musk and Neuralink are working on trying to plug, as per our discussion with computers and biological systems, to connect the two. He's trying to connect our brain to a computer to create a brain-computer interface where they can communicate back and forth. On this line of thinking, do you think this is possible to bridge the gap between our engineered computing systems and the messy biological systems? My answer would be absolutely. There's no doubt that we can understand more and more about what goes on in the brain and we can sort of train the brain. I don't know if you remember the Palm Pilot. Yeah, Palm Pilot, yeah. Remember this whole sort of alphabet that they had created? Am I thinking of the same thing? It's basically, you had a little pen and for every character, you had a little scribble that was unique that the machine could understand and that instead of trying the machine, trying to teach the machine to recognize human characters, you had basically, they figured out that it's better and easier to train humans to create human-like characters that the machine is better at recognizing. So in the same way, I think what will happen is that humans will be trained to be able to create the mind pattern that the machine will respond to before the machine truly comprehends our thoughts. So the first human brain interfaces will be tricking humans to speak the machine language where with the right set of electrodes, I can sort of trick my brain into doing this. And this is the same way that many people teach like learn to control artificial limbs. You basically try a bunch of stuff and eventually you figure out how your limbs work. That might not be very different from how humans learn to use their natural limbs when they first grow up. Basically, you have these neoteny period of this puddle of soup inside your brain, trying to figure out how to even make neural connections before you're born and then learning sounds in utero of all kinds of echoes and eventually getting out in the real world. And I don't know if you've seen newborns, but they just stare around a lot. One way to think about this as a machine learning person is, oh, they're just training their edge detectors. And eventually they figure out how to train their edge detectors. They work through the second layer of the visual cortex and the third layer and so on and so forth. And you basically have this learning how to control your limbs that probably comes at the same time. You're sort of throwing random things there and you realize that, ooh, wow, when I do this thing, my limb moves. Let's do the following experiment. Take a breath. What muscles did you flex? Now take another breath and think what muscles do I flex? The first thing that you're thinking when you're taking a breath is the impact that it has on your lungs. You're like, oh, I'm now gonna increase my lungs or I'm now gonna bring air in. But what you're actually doing is just changing your diaphragm. That's not conscious, of course. You never think of the diaphragm as a thing. And why is that? That's probably the same reason why I think of moving my finger when I actually move my finger. I think of the effect instead of actually thinking of whatever muscle is twitching that actually causes my finger to move. So we basically in our first years of life build up this massive lookup table between whatever neuronal firing we do and whatever action happens in our body that we control. If you have a kid grow up with a third limb, I'm sure they'll figure out how to control them probably at the same rate as their natural limbs. And a lot of the work would be done by the, if a third limb is a computer, you kind of have a, not a faith, but a thought that the brain might be able to figure out, like the plasticity would come from the brain. Like the brain would be cleverer than the machine at first. When I talk about a third limb, that's exactly what I'm saying, an artificial limb that basically just controls your mouse while you're typing. Perfectly natural thing. I mean, again, in a few hundred years. Maybe sooner than that. But basically there's, as long as the machine is consistent in the way that it will respond to your brain impulses, you'll figure out how to control that and you could play tennis with your third limb. And let me go back to consistency. People who have dramatic accidents that basically take out a whole chunk of their brain can be taught to co-opt other parts of the brain to then control that part. You can basically build up that tissue again and eventually train your body how to walk again and how to read again and how to play again and how to think again, how to speak a language again, et cetera. So there's a massive amount of malleability that happens naturally in our way of controlling our body, our brain, our thoughts, our vocal cords, our limbs, et cetera and human-machine interfaces are all inevitable if we sort of figure out how to read these electric impulses but the resolution at which we can understand human thought right now is nil, is ridiculous. So how are human thoughts encoded? It's basically combinations of neurons that co-fire and these create these things called engrams that eventually form memories and so on and so forth. We know nothing of all that stuff. So before we can actually read into your brain that you wanna build a program that does this and this and this and that, we need a lot of neuroscience. Well, so to push back on that, do you think it's possible that without understanding the functionally about the brain or from the neuroscience or the cognitive science or psychology, whichever level of the brain we'll look at, do you think if we just connect them, just like per your previous point, if we just have a high enough resolution between connection between Wikipedia and your brain, the brain will just figure it out with less understanding because that's one of the innovations of Neuralink is they're increasing the number of connections to the brain to several thousand, which before was in the dozens or whatever. You're still off by a few orders of magnitude, only order of seven. So. Right, but the thing is, the hope is if you increase that number more and more and more, maybe you don't need to understand anything about the actual, how human thought is represented in the brain. You can just let it figure it out by itself. Yeah, people, Keanu Reeves waking up and saying, I know cook food. Yeah, exactly. Exactly. So yeah, sure. You don't have faith in the plasticity of the brain to that degree. It's not about brain plasticity. It's about the input aspect. Basically, I think on the output aspect, being able to control a machine is something that you can probably train your neural impulses that you're sending out to sort of match whatever response you see in the environment. If this thing moved every single time I thought a particular thought, then I could figure out, I could hack my way into moving this thing with just a series of thoughts. I could think guitar, piano, tennis ball. And then this thing would be moving. And then I would just have the series of thoughts that would sort of result in the impulses that will move this thing the way that I want. And then eventually it'll become natural because I won't even think about it. I mean, the same way that we control our limbs in a very natural way. But babies don't do that. Babies have to figure it out. And some of it is hard-coded, but some of that is actually learned based on whatever soup of neurons you ended up with, whatever connections you pruned them to, and eventually you were born with. A lot of that is coded in the genome, but a huge chunk of that is stochastic. And sort of the way that you sort of create all these neurons, they migrate, they form connections, they sort of spread out, they have particular branching patterns, but then the connectivity itself, unique in every single new person. All this to say that on the output side, absolutely, I'm very, very hopeful that we can have machines that read thousands of these neuronal connections on the output side, but on the input side, oh boy. I don't expect any time in the near future we'll be able to sort of send a series of impulses that will tell me, oh, Earth to sun distance, 7.5 million, et cetera, like nowhere. I mean, I think language will still be the input way rather than sort of any kind of more complex. It's a really interesting notion that the ambiguity of language is a feature. And we evolved for millions of years to take advantage of that ambiguity. Exactly. And yet no one teaches us the subtle differences between words that are near cognates, and yet evoke so much more than one from the other. And yet, when you're choosing words from a list of 20 synonyms, you know exactly the connotation of every single one of them. And that's something that is there. So yes, there's ambiguity, but there's all kinds of connotations. And in the way that we select our words, we have so much baggage that we're sending along, the way that we're emoting, the way that we're moving our hands every single time we speak, the pauses, the eye contact, et cetera, so much higher baud rate than just a vocal, you know, string of characters. Well, let me just take a small tangent on that. Oh, tangent, we haven't done that yet. That's a good idea, let's do a tangent. We'll return to the origin of life after. So, I mean, you're Greek, but I'm going on this personal journey. I'm going to Paris for the explicit purpose of talking to one of the most famous, a couple who's a famous translators of Russian literature, Dostoevsky, Tolstoy, and they go, that's their art, is the translation. And everything I've learned about the translation art, it makes me feel, it's so profound in a way that's so much more profound than the natural language processing papers I read in the machine learning community, that there's such depth to language that I don't know what to do with. I don't know if you've experienced that in your own life with knowing multiple languages. I don't know what to, I don't know how to make sense of it, but there's so much loss in translation between Russian and English, and getting a sense of that. Like, for example, there's like, just taking a single sentence from Dostoevsky, and there's a lot of them. You could talk for hours about how to translate that sentence properly. That captures the meaning, the period, the culture, the humor, the wit, the suffering that was in the context of the time, all of that could be a single sentence. You could talk forever about what it takes to translate that correctly. I don't know what to do with that. So, being Greek, it's very hard for me to think of a sentence, or even a word, without going into the full etymology of that word, breaking up every single atom of that sentence, and every single atom of these words, and rebuilding it back up. I have three kids, and the way that I teach them Greek is the same way that, you know, the documentary I was mentioning earlier about sort of understanding the deep roots of all of these words. And it's very interesting that every single time I hear a new word that I've never heard before, I go and figure out the etymology of that word, because I will never appreciate that word without understanding how it was initially formed. Interesting. But how does that help? Because that's not the full picture. No, no, of course, of course. But what I'm trying to say is that knowing the components teaches you about the context of the formation of that word, and sort of the original usage of that word. And then, of course, the word takes new meaning as you create it, you know, from its parts. And that meaning then gets augmented, and two synonyms that sort of have different roots will actually have implications that carry a lot of that baggage of the historical provenance of these words. So before working on genome evolution, my passion was evolution of language, and sort of tracing cognates across different languages through their etymologies. And- That's fascinating that there's parallels between, I mean- Of course, a huge amount. There's evolutionary dynamics to our language. Yeah. In every single word that you utter, parallels, parallels. What does parallels mean? Para means side by side, alleles from alleles, which means identical twins. Parallels. I mean, name any word, and there's so much baggage, so much beauty in how that word came to be, and how this word took a new meaning than the sum of its parts. Yeah, and they're just words. They don't have any physical grounding. Exactly, and now you take these words, and you weave them into a sentence. Ah, the emotional invocations of that weaving are fathomless. And all of those emotions all live in the brains of humans. In the eye of the beholder. In the eye of, no, seriously, you have to embrace this concept of the eye of the beholder. It's the conceptualization that nothing takes meaning with one person creating it. Everything takes meaning in the receiving end. And the emergent properties of these communication networks, where every single, you know, if you look at the network of our cells and how they're communicating with each other, every cell has its own code. This code is modulated by the epigenome. This creates a bunch of different cell types. Each cell type now has its own identity, yet they all have the common root of the stem cells that sort of led to them. Each of these identities is now communicating with each other. They take meaning in their interaction. There's an emergent property that comes from a bunch of cells being together that is not in any one of the parts. If you look at neurons communicating, again, these engrams don't exist in any one neuron. They exist in the connection, in the combination of neurons. And the meaning of the words that I'm telling you is empty until it reaches you and it affects you in a very different way than it affects whoever's listening to this conversation now. Because of the emotional baggage that I've grown up with, that you've grown up with, and that they've grown up with. And that's, I think, the magic of translation. If you start thinking of translation as just simply capturing that emotional set of reactions that you evoke, you need a different set of words to evoke that same set of reactions to a French person than to a Russian person, because of the baggage of the culture that we grew up in. Yeah, I mean, there's- So basically, you shouldn't find the best word. Sometimes it's a completely different sentence structure that you will need, matched to the cultural context of the target audience that you have. Yeah, I mean, you're just, I usually don't think about this, but right now there's this feeling, as a reminder, there's just you and I talking, but there's several hundred thousand people will listen to this. There's some guy in Russia right now running, like in Moscow, listening to us. And there's somebody in India, I guarantee you, there's somebody in China and South America, there's somebody in Texas, and they all have different- Emotional baggage. They probably got angry earlier on about the whole discussion about coronavirus and about some aspect of it. Yeah, and there's that network effect. Yeah, yeah, yeah. It's a beautiful thing. And this lateral transfer of information, that's what makes the collective, quote-unquote, genome of humanity so unique from any other species. So you somehow miraculously wrapped it back to the very beginning of when we were talking about the beauty of the human genome. So I think this is the right time, unless we wanna go for a six to eight hour conversation. We're gonna have to talk again, but I think for now, to wrap it up, this is the right time to talk about the biggest, most ridiculous question of all, meaning of life. Off mic, you mentioned to me that you had your 42nd birthday, 42nd being a very special, absurdly special number, and you had a kind of get together with friends to discuss the meaning of life. So let me ask you, as a biologist, as a computer scientist, and as a human, what is the meaning of life? I've been asking this question for a long time, ever since my 42nd birthday, but well before that, in even planning the Meaning of Life Symposium. And symposium, sym means together, posy actually means to drink together. So a symposium is actually a drinking party. So the meaning. Can you actually elaborate about this Meaning of Life Symposium that you put together? It's like the most genius idea I've ever heard. So 42 is obviously the answer to life, the universe, and everything, from the Hitchhiker's Guide to the Galaxy. And as I was turning 42, I've had the theme for every one of my birthdays. When I was turning 32, it's one, zero, zero, zero, zero, zero in binary. So I celebrated my 100,000th binary birthday, and I had a theme of going back 100,000 years, let's dress something in the last 100,000 years. Anyway, I've always had these. You're such an interesting human being. Okay, that's awesome. I've always had these sort of numerology-related announcements for my birthday parties. So what came out of that Meaning of Life Symposium is that I basically asked 42 of my colleagues, 42 of my friends, 42 of my collaborators, to basically give seven-minute speeches on the meaning of life, each from their perspective. And I really encourage you to go there, because it's mind-boggling that every single person said a different answer. Every single person started with, I don't know what the meaning of life is, but, and then gave this beautifully, eloquently answer, eloquent answer. And they were all different, but they all were consistent with each other and mutually synergistic, and together forming a beautiful view of what it means to be human in many ways. Some people talked about the loss of their loved one, their life partner for many, many years, and how their life changed through that. Some people talked about the origin of life. Some people talked about the difference between purpose and meaning. I'll, you know, maybe quote one of the answers, which is this linguistics professor, friend of mine at Harvard, who basically said that she was gonna, she's Greek as well, and she said, I will give a very Pythian answer. So Pythia was the Oracle of Delphi, who would basically give these very cryptic answers, very short, but interpretable in many different ways. There was this whole set of priests who were tasked with interpreting what Pythia had said, and very often you would not get a clean interpretation, but she said, I will be like Pythia and give you a very short and multiply interpretable answer, but unlike her, I will actually also give you three interpretations. And she said, the answer to the meaning of life is become one. And the first interpretation is like a child, become one year old with the excitement of discovering everything about the world. Second interpretation, in whatever you take on, become one, the first, the best, excel, drive yourself to perfection for every one of your tasks. And become one when people are separate, become one, come together, learn to understand each other. Damn, that's an answer. And one way to summarize this whole meaning of life symposium is that the very symposium was illustrating the quest for meaning, which might itself be the meaning of life. This constant quest for something sublime, something human, something intangible, some aspect of what defines us as a species and as an individual, both the quest of me as a person through my own life, but the meaning of life could also be the meaning of all of life. What is the whole point of life? Why life? Why life itself? Because we've been talking about the history and evolution of life, but we haven't talked about why life in the first place? Is life inevitable? Is life part of physics? Does life transcend physics? By fighting against entropy, by compartmentalizing and increasing concentrations rather than diluting away? Is life a distinct entity in the universe beyond the traditional, very simple physical rules that govern gravity and electromagnetism and all of these forces? Is life another force? Is there a life force? Is there a unique kind of set of principles that emerge, of course, built on top of the hardware of physics, but is it sort of a new layer of software or a new layer of a computer system? So that's at the level of big questions. There's another aspect of gratitude, of basically, what I like to say is, during this pandemic, I've basically worked from 6 a.m. until 7 p.m. every single day, nonstop, including Saturday and Sunday. I've basically broken all boundaries of where personal life begins and work life ends. And that has been exhilarating for me, just the intellectual pleasure that I get from a day of exhaustion, where at the end of the day, my brain is hurting, I'm telling my wife, wow, I was useful today. And there's a certain pleasure that comes from feeling useful. And there's a certain pleasure that comes from feeling grateful. So I've written this little sort of prayer for my kids to say at bedtime every night, where they basically say, thank you, God, for all you have given me and give me the strength to give on to others with the same love that you have given on to me. We as a species are so special. The only ones who worry about the meaning of life. And maybe that's what makes us human. And what I like to say to my wife and to my students during this pandemic work extravaganza, is every now and then they ask me, but how do you do this? And I'm like, I'm a workaholic. I love this. This is me in the most unfiltered way. The ability to do something useful, to feel that my brain's being used, to interact with smartest people on the planet day in, day out, and to help them discover aspects of the human genome, of the human brain, of human disease and the human condition that no one has seen before. With data that we're capturing that has never been observed. And there's another aspect, which is on the personal life. Many people say, oh, I'm not gonna have kids. Why bother? I can tell you as a father, they're missing half the picture, if not the whole picture. Teaching my kids about my view of the world and watching through their eyes the naivete with which they start and the sophistication with which they end up. The understanding that they have of not just the natural world around them, but of me too. The unfiltered criticism that you get from your own children that knows no bounds of honesty. And I've grown components of my heart that I didn't know I had until you sense that fragility, that vulnerability of the children, that immense love and passion, the unfiltered egoism that we as adults learn how to hide so much better. It's just this back of emotion that tell me about the raw materials that make a human being and how these raw materials can be arranged with more sophistication that we learn through life to become truly human adults. But there's something so beautiful about seeing that progression between them, the complexity of the language growing as more neural connections are formed, to realize that the heart is not just a physical body, the hardware is getting rearranged as their software is getting implemented on that hardware, that their frontal cortex continues to grow for another 10 years. There's neuronal connections that are continuing to form, new neurons that actually get replicated and formed. And it's just incredible that we have this, not just you grow the hardware for 30 years and then you feed it all of the knowledge. No, no, the knowledge is fed throughout and is shaping these neural connections as they're forming. So seeing that transformation from either your own blood or from an adopted child is the most beautiful thing you can do as a human being. And it completes you, it completes that path, that journey. The create life, oh sure, that's at conception, that's easy. But create human life to add the human part, that takes decades of compassion, of sharing, of love and of anger and of impatience and patience. And as a parent, I think I've become a very different kind of teacher. Because again, I'm a professor, my first role is to bring adult human beings into a more mature level of adulthood, where they learn not just to do science, but they learn the process of discovery and the process of collaboration, the process of sharing, the process of conveying the knowledge, of encapsulating something incredibly complex and sort of giving it up in sort of bite-sized chunks that the rest of humanity can appreciate. I tell my students all the time, like when an apple falls, when a tree falls in the forest and no one's there to listen, has it really fallen? The same way you do this awesome research, if you write an impenetrable paper and no one will understand, it's as if you never did the awesome research. So conveying of knowledge, conveying this lateral transfer that I was talking about at the very beginning of sort of humanity and sort of the sharing of information, all of that has gotten so much more rich by seeing human beings grow in my own home, because that makes me a better parent and that makes me a better teacher and a better mentor to the nurturing of my adult children, which are my research group. First of all, beautifully put, connects beautifully to the vertical and the horizontal inheritance of ideas that we talked about at the very beginning. I don't think there's a better way to end it on this poetic and powerful note. Manolis, thank you so much for talking to us. A huge honor, we'll have to talk again about the origin of life, about epigenetics, epigenomics, and some of the incredible research you're doing. Truly an honor, thanks so much for talking today. Thank you, such a pleasure. It's such a pleasure. I mean, your questions are outstanding. I've had such a blast here. I can't wait to be back. Awesome. Thanks for listening to this conversation with Manolis Kellis, and thank you to our sponsors, Blinkist, Eight Sleep, and Masterclass. Please consider supporting this podcast by going to blinkist.com slash Lex, eightsleep.com slash Lex, and masterclass.com slash Lex. Click the links, buy the stuff, get the discount. It's the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review Five Stars on Apple Podcast, support on Patreon, or connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Charles Darwin that I think Manolis represents quite beautifully. If I had my life to live over again, I would have made a rule to read some poetry and listen to some music at least once every week. Thank you for listening, and hope to see you next time.

https://youtu.be/brslF-Cy3HU

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7 Levels of Coronavirus Attack on Our Society and How We Can Fight Back

The coronavirus pandemic is a global crisis, but I think it's also a moment that unites us, that gives us an opportunity to show the strength of our community, to be compassionate to our fellow human beings, and to work hard to fight this thing. And I think we will, and I think we'll beat it. So I wanted to make a video about, in my view, seven different levels at which the coronavirus is attacking the fundamental nature of our society, and how we can fight back, and how we can emerge stronger together. The seven levels of attack are biological, medical, level number one, that attacks the individual human life and death, and the biology, the wellbeing, the health of an individual human being. Psychological, which is attacking the emotional stability, the fear, and the ability to love and be compassionate towards our fellow human beings in the individual psychology of a person. Level number three is social, which is attacking the collective cognition, the collective intelligence of our species, instilling panic, the spread of misinformation, the spread of conspiracies. Level number four is economic, attacking the financial stability of our global markets, the employment of individuals, productivity, and generally the financial burden, especially the imbalance of the financial burden carried by individuals. Level number five is political, exacerbating the partisanship and the ability to make effective policy and respond to the virus at the federal, at the global scale. Level number six is existential, which is taking perhaps a step back from the concerns of the current natural pandemic and looking at civilization level extinction, looking at existential threats that may be among us today and may be posed to us in this coming century, from artificial intelligence, to nanotechnology, to engineered pandemics and other concerns. And level seven is really taking a step back and looking at the philosophical. The test the virus presents to us to consider the fundamental fabric of the human condition at the individual level and the societal level. What are we supposed to be together? How are we supposed to live? What is the meaning of it all? And what is the best path forward for us as a society in the coming decades, in the coming centuries? The meaning of life as silly perhaps and unanswerable the question is, is also perhaps the most important question of all. And if there's ever a time to consider, to ponder, to try to answer that question, it is now. It's an opportunity that the virus presents. So if you allow me, I'd like to talk to the seven different levels of attack from coronavirus in a video that's a little bit different, perhaps than some of the videos out there. And certainly from the videos that I'm used to making, I've been doing a lot of data aggregation and analysis, a lot of simulation for forecasting purposes, even simulation for revealing the mathematical patterns in the spread of a pandemic. There's a lot of interesting ideas there that I hope to explore either privately or publicly through the video format or blogs or even papers. But this video is higher level. It's thinking of the big picture of this virus. So if you allow me, I'd like to talk about three things for each of the levels. One is the pain we're likely to feel. Two is the challenge for us to overcome. And three is the hope, the silver lining, the light at the end of the tunnel. It's really important to mention that if there's any errors or expansions possible on something I say in this video, please let me know. I will add corrections and expansions into the description. So please also read the description to this video. The burden I carry with making a video like this and future videos on the coronavirus is mistakes here could cost lives. So I'm very cognizant of that. I'm very careful. Please read the description and please let me know if there's any errors in the data or just even the wording of the things I say. So looking at level one first, at the biological and the medical, the direct attack of the virus on the human body, it's very difficult to make projections about the number of cases that we're likely to observe, at least in the first wave, and the number of deaths that we're likely to observe. Many people, including myself, are carefully looking at the data, aggregating it, analyzing it, but it's still not a good time to make a good projection. It is perhaps a good hopeful message to consider the best case scenario. If the governments respond swiftly, if we all do our part, if the hospital resources don't become overwhelmed, it's possible that the level of deaths that we observe is at or below the levels of annual influenza deaths, which is still a tragic, a tragic number. Now, if the response is not swift from governments and individuals doing our part, then the worst case number of deaths could count in the millions. Still too difficult to tell, but this virus from everything we see on the biological side is much more dangerous than the influenza virus, than the flu. So this level is one that there's already been a lot of great information on, blogs, papers, videos, CDC. You should make sure you're paying attention, but the message is clear. For individuals, you should stay home, social isolation, social distancing, wash hands, don't get infected, and don't infect others. For the medical infrastructure, the people really fighting, really heroes fighting on the front lines are the healthcare workers and the service workers, making sure our society still runs, making sure people who are sick are getting help. The thing that I've seen is I understand that works really well is the testing quickly, testing early, and treating when treatment is needed. And also for people who are sick, tracing to see who are the other individuals they interacted with, so they can be properly socially isolated. Of course, on the science side, a lot of brilliant people are working on a treatment on antiviral drugs, on vaccines, and on the engineering, manufacturer, logistics side, people are working to manufacture ventilators, test kit, protective equipment like masks. This is a huge global effort. Now, the hope is we, in this immediate response, we flatten the curve, we don't overwhelm healthcare resources, and we minimize the loss of life. One of the most difficult things here is for doctors to make life and death decisions. I would like to recommend a book called Mountains Beyond Mountains by Tracy Kidder, which tells the story of Paul Farmer. It's the first time I realized, and it might be cliche to say, but it really is true that doctors, nurses, and healthcare workers are heroes. And that book was the first time I realized that many of the decisions we make are beyond reason. They're some of the most complicated ethical decisions you have to make. You have to listen to your heart, and those are the decisions, deeply human decisions that doctors have to make. And at this biological, this medical level of life, of human life and human death, doctors are really, and nurses and health workers are really at the front lines of making those most difficult decisions. That is such an important fight. They truly are heroes. I recommend the book highly to highlight the burden that these folks have to carry. Now, the hope is if the response is swift, and we all do our part, that this turns out to be as close to the best case as possible. And then it serves as a dress rehearsal for a much worse pandemic that could cost a lot more, both economic impact and the loss of human life. And that means we can now look into the future and invest in science, invest in the healthcare infrastructure, such that future responses can be much more swift, and we're much more prepared for something catastrophic, truly catastrophic. And finally, the hope is that we can discuss the role of technology in all of this in the years to come. Information truly is power in controlling the spread of a pandemic, but information, data, is something that requires that we strike a balance between privacy and health. And that requires a discussion about who controls, who manages, who regulates the technology in terms of how privacy is preserved. The second level at which the virus is attacking our society is the individual human emotion. Fear is real. Fear of losing your job, fear of losing your health or the health of the loved ones, fear of losing basic resources like water and food and power. And there also could just be fundamentally a fear of uncertainty, which can lead to tensions within the family and within the small inner social circle. Now, the key there is to stay calm. It's so important for reason to override emotion, especially in decision-making. So stay calm, stay informed. This might be difficult to say, but this is also a good time to reevaluate your life journey to ask the question, am I living my dream? Am I living my passion? This is a good time as any for a personal revolution to start over, to do the thing you've always wanted to do, to start writing, to start reading, to learn, take an online class, to pivot in your own personal journey. Or if you're a business owner, to pivot the structure of your business, the thing it's doing, the underlying ideas behind the business, the scale of the business, rethink everything. This is a good time for a personal revolution. Now, this can be extremely painful, especially for people living paycheck to paycheck who have to support a family. But this is the time. If there's ever a time, this is the time to do it, to rethink what are the coming days, weeks and months look like? How can you change your life so you can truly live your dream, your passion, and provide for your family, provide for yourself, provide for your family, and be the best person you can be? This is the time for that personal revolution. Again, it might be very painful, but this is the time for it. My hope at this level, at the psychological level of the individual, is that we use this opportunity to reevaluate our lives, to take a leap forward on something you've always wanted to do. And in general, my hope is that we overcome fear, the natural fear of uncertainty, and lean in, lean into love, compassion for our fellow human beings. Resist the desire to be afraid. Lean in to being compassionate towards others. Level three is social. Social distancing, really should be called physical distancing, that we're all practicing, has led us to lean in to rely on social media for connection, for basic human connection, and for information. So it has served as a gradual replacement of our own individual thinking, which is much easier to practice in the physical world, and more reliance on the kind of collective cognition, the hive mind that's represented by social networks. And what that results is, is a magnification of level two attack of the virus, on the fear and panic that can spread, like contagion on social networks. So social networks are much more effective at spreading an individual human emotion, such that it becomes a mass human emotion of our collective cognition, of our collective mind. And again, that also applies to not just fear and emotion, it applies to misinformation, non-scientific, anti-scientific information, and of course, conspiracy theories. So that's another level at which the virus attacks our society, and due to the efficiency of social media, is perhaps one of the most novel aspects of this pandemic. Now, the challenge for us at the individual human level is self-reflection meditation. Detach yourself. Yuval Harari in 21 Lessons for the 21st Century talks about this in the last chapter for meditation, is to detach ourselves from this hive mind, to think on ourselves, to do the self-reflection, to hear our own inner voice, inner thoughts. Not allow the wave of information, of panic, that can travel through social media, to impact us fully. It should be something we can simply observe, as opposed to deeply internalize. Again, the really important thing here is looking, finding, digging for facts. That means looking at source information, source scientific information, as opposed to derived opinion pieces on that information. And most importantly, think critically on your own. Just because the group that you're supposed to belong to, whether that's political or social, thinks a certain way, doesn't mean you should think that way. Remove the power of the hive mind by thinking on your own. Now, my hope is that this level, this becomes a jarring wake-up call of how we use social media as a society. One, in terms of controlling the spread of misinformation, and two, in terms of the way we connect with other human beings on social media. As opposed to giving in to the drug, the dopamine-fueled drama of social media, of clicking likes and tracking likes, and getting angry at the drama and the tension, and so on. More seeing it as another medium in which we can encourage deep connection with other human beings, friendships, real, positive, good vibes. It might be naive to say, but I think it's actually possible. It's both a technology problem, and it's a society problem of how we define the standards of how we behave in the social world. And this is a good wake-up call to look at that. In a time of panic, we come together, and there's no reason we can't stay together in this kind of way online. Now, level four is economic, and this could be the most painful of the impacts of the virus. Day by day, the projections are getting worse and worse from the economists. Some economists, more and more, are predicting double-digit drops in GDP in the second quarter. The real pain that people are already feeling, and will feel more and more, is the loss of jobs. Many economists are predicting millions, three to seven millions of US jobs lost before the summer. Now, these are jobs in the service industry, hotel, travel, restaurants. Many folks who are already living paycheck to paycheck. This is real pain and burden that a lot of families will have to carry. And on the small business side, this is difficult to measure, but surveys of business owners are saying that in just three months, 50% of them do not see a way to avoid bankruptcy. So that's a much longer lasting impact on the fabric of our, the United States capitalist society, where small business is in many ways at the backbone of our society. The challenge for us as a citizen is to hold politicians accountable as they develop a fiscal stimulus package. It's really important, drawing lessons from the 2008 financial crisis, that the bailout, that the fiscal stimulus that passes, is one that benefits the people that need it. The workers who lose their job, the small businesses on the verge of bankruptcy. As a consumer, at least in the United States, consumer spending is a big part of the US economy. The 70%. So if you can afford it, continuing spending money on things you need, especially to support local and small businesses. And finally, as a business, as a small business, this is an opportunity to reinvent, to add an online component, to diversify, to pivot. Now that might be really painful, difficult to say. I recently left my job. I was facing a bank account with nothing in it, and there's a lot of reinvention and pivoting that was required to do. I'm working on building a startup that brings in no money, so I had to figure out how can I make money in the meantime. Now that kind of thing could be exceptionally painful, especially if it requires learning skills that you don't have. But I think if you face this fear, taking this step where you reinvent the business could be the best decision you've ever made. It could be very painful in the short term, but exceptionally profitable and liberating in the long term. So this is the time, as I mentioned before, for if you're a small business owner, for a personal revolution. Now my hope is, as it is for everybody else, that once we reopen our society, that the fiscal stimulus not just carries us through, but allows us to resume consumer spending as quickly as possible, so that the recovery is, as they say, a V versus a U, that it's an immediate and aggressive and quick recovery. And also, it's a very dark and perhaps a little bit Russian of me to think of the silver lining of this, but one of the positive aspects of the pain that people are feeling is that a lot of people are feeling that pain together. We're in this together. Majority of the lower class and the middle class will be feeling the pain of shutting down the economy. We're in this together. There's something, if just a little bit comforting, that the pain you feel is the pain that's also felt by your neighbors. Again, the hope is that it brings us together. Level five is political. I think it's not an exaggeration to say we're living in one of the most divided times, politically, in the history of the United States, of our country, and especially on the heels of the United States president being impeached and an election coming up. It leads to the politicization of everything, including the virus, and that's a huge pain, and that's a really damaging attack vector along which the virus can exploit our society, at least this nation. And also, outside of the partisanship, this is a time for the government to pass policy, to respond to the virus, and there is, as always through history, through wars, through pandemics, through big global crises, there's a diminishment of our rights and freedoms, and that is another attack of the virus on the fabric of our society. The challenge for a citizen is to not let charlatans in the government of any party affiliation capitalize on our fear, as I described in level two, the psychological, the emotional, by overreaching power. So this could look like anything. It could look like mass surveillance. It could look like martial law, individual cities, states, federal. It could look like detaining people without trial, which we're already starting to see, and God forbid, canceling elections, so really attacking the fundamental nature of democracy. We have seen this throughout history. As citizens of this democratic nation, we have to stay vigilant to this threat. On the scientific front, I think it's really, really important that we do not look at the coronavirus through a political lens. It should not be a red and blue issue. It should be something where we trust the expert, the scientific information, the best data available. Should not be seen through a lens of the partisan divide that has driven so much of our public discourse about federal policy, because the one plus trillion dollar stimulus package that Congress is trying to pass is something that can make or break this economy, or rather, it can make the difference between the V and the U shape recovery, fast recovery or delayed multi-month recovery where a lot of people will suffer. It's exceptionally important to get this right, and politics should not come at all into play into the decisions being made by our policymakers. So the hope is, once we beat this thing, is that we rethink the federal infrastructure, the response to global threats, really invest back into it, try to see government in this one regard as something that could really unite the people in an effective, timely, quick response. The hope is we're reminded of the importance of government, and then reinvigorate the basic unit of a democracy, which is the citizen, and remind us that we can accomplish a lot of things if we work together, so not through divisiveness, but on really big, important issues and things we really should all agree on working together. This is a good reminder. Just like going to the moon was a good reminder of what science and engineering could do at a large scale, this is what's needed now. This virus perhaps should serve as a good reminder that good science, good engineering at scale is essential for us to work together on to respond to these kinds of things in the future, and just to create, progress forward to make a better world in a lot of different dimensions. It continues to be a huge surprise to me that science not always, but sometimes, enters the world of politics, and politicians play games with scientific facts. They question the validity of findings of individual personalities in science. I think people, my hope is that they understand that on especially the most important questions, there's thousands of scientists trying to disprove each other. This kind of collective mechanism is really good at cutting out all the BS and getting to the core, the truth of things. Science cannot answer all questions. There's, to me, some of the most important questions about ethics is impossible for science to answer, but the basic questions of the mechanism that threaten our well-being, especially in the biological, chemical, and physical world, science is really well-equipped to answer, and we should not politicize that extremely powerful mechanism that can protect us, that can build big, amazing, cool things that make our life easier, better, just create a better world. And I hope that we emerge as a society that can bicker and politicize everything else, but science and scientific experts is something we trust. Level six is existential. You can say evolutionary, even. The human species has not always existed, and there's no guarantee it will always exist. Perhaps this is not the right time to be deeply thinking about this question. We wanna deal with the threat at hand, but I recommend a lot of excellent work been written on existential risks from Nick Bostroms and others at the Future of Humanity Institute and other institutions in general, considering what are the different threats that our human civilization is facing in the next hundred years that could lead to extinction or lead to a large number of people being either displaced or killed. Now, this goes everything from global warming to nuclear war to nanotechnology accident to molecular nanotechnology weapons, so different kinds of weapons, to things that I've spoken a lot about, think a lot about, is superintelligent AI, artificial general intelligence systems, and then there's pandemics, the natural pandemic of coronavirus that we're experiencing now, and then there's a lot of concern about engineering pandemics, the kind of risk they pose to our civilization. The pandemic we're experiencing now is unlikely to be a species extinction level event, but it serves as a dress rehearsal, something that reveals the fragility of our species, things that feel in the moment totally unexpected, and yet are completely expected if you listen to the experts. Experts on pandemics are predicting that there will be a much worse one coming for sure. For me personally, I work in artificial intelligence. I embody a lot of different views, but certainly because I program and build a lot of systems, what you call narrow AI systems, there's a clear awareness of how far we are from creating superintelligent AI systems and I can talk at length about why I see that as an exceptionally difficult problem on many levels, especially the kind of AI systems that could destroy human civilization. But I think at this level, the coronavirus pandemic has really changed my mind. It's given me a wake-up call to think, think more clearly about the unexpected, that the things that threaten us may come in ways we don't expect, so we have to be exceptionally careful, especially when we work in that particular field. I'm not an expert in pandemics. I'm not an expert in molecular nanotechnology, nor nuclear terrorism, but I am, I hate the word expert, but I'm somewhat knowledgeable in the world of AI, and so it's my responsibility to look bigger, to think bigger about the things that are totally unexpected, that may threaten the wellbeing of many of our, especially most vulnerable members of our society, but really everybody. And so the challenge for us as a society as we emerge from this pandemic is to invest in scientific research on all these avenues, to be prepared way ahead of time to some of the threats posed here, especially what research does is it doesn't only reveal mechanism of how we can protect us, but it reveals the possible vectors of attack that could be expected. So just investing in research, getting more people to think about this problem, I think is exceptionally important to prepare society, to prepare scientific minds, and the tooling, the engineering, the infrastructure required to respond to a problem before it kills a billion or more people. And finally, level seven, philosophical, really taking a step back. It's much more difficult to be eloquent about this, so I'll mention a book that had a big impact on my life and rings true in many of its lessons is The Plague by Albert Camus. Now, in the world that Camus paints in The Plague, suffering seems to be something that's just a part of life. And the question that life poses to us is how do we respond to that suffering? How do we deal with that suffering? And at least to me, the lessons I draw from it is that love for our fellow human beings, compassion for others, is the way we conquer that suffering. The natural inclination, perhaps, at first, is to turn into yourself, because everything in life, in your existence, is going to be a source of pain, a source of loss, a source of suffering. And so you want to isolate yourself, you want to separate yourself, you want to run away from that. But the reality is, somehow, that seems to be part of the human condition is that going into yourself, hiding from life, running away from life, from others, from society, is actually not a way to remove suffering from your life. That somehow stokes the fire of pain, of dread. And so the way to overcome that, the meaning of life, I guess you could say, for Camus, is to love others. And the book itself serves as an allegory for World War II, and my relatives, the society of the Soviet Union in which I was born in, raised in, is so deeply grounded in the story of World War II and the pain of World War II. And the lessons that emerge there is that, as painful as it is to say, all that suffering, all that death, what emerges is that love for each other conquers all. Love of community. And that's my hope, is that we emerge from this at the highest level, from this virus, with a greater sense of community, with a greater sense for the value of community, for the love of our fellow human beings, for the compassion for our fellow human beings. My hope is that this virus is a reminder that love is the meaning of life. Thank you for watching this video. I hope it's of value for some people. I hope it helps. And again, I love you all.

https://youtu.be/jAYTogd38m4

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Sergey Levine: Robotics and Machine Learning | Lex Fridman Podcast #108

The following is a conversation with Sergei Levine, a professor at Berkeley and a world-class researcher in deep learning, reinforcement learning, robotics, and computer vision, including the development of algorithms for end-to-end training of neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and, in general, deep RL algorithms. Quick summary of the ads. Two sponsors, Cash App and ExpressVPN. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST and signing up at expressvpn.com slash lex pod. Click the links, buy the stuff. It's the best way to support this podcast and, in general, the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as one dollar. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is an algorithmic marvel. So big props to the Cash App engineers for taking a step up to the next layer of abstraction over the stock market, making trading more accessible for new investors and diversification much easier. So again, if you get Cash App from the App Store or Google Play and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. This show is also sponsored by ExpressVPN. Get it at expressvpn.com slash LEXPOD to support this podcast and to get an extra three months free on a one-year package. I've been using ExpressVPN for many years. I've been using it for a long time. I love it. I think ExpressVPN is the best VPN out there. They told me to say it, but it happens to be true in my humble opinion. It doesn't log your data, it's crazy fast, and it's easy to use, literally just one big power on button. Again, it's probably obvious to you, but I should say it again. It's really important that they don't log your data. It works on Linux and every other operating system, but Linux, of course, is a little bit more expensive. Shout out to my favorite flavor, Ubuntu Mate 2004. Once again, get it at expressvpn.com slash LEXPOD to support this podcast and to get an extra three months free on a one-year package. And now, here's my conversation with Sergey Levine. What's the difference between a state-of-the-art human, such as you and I? Well, I don't know if you've ever heard of robots, but a state-of-the-art human and a state-of-the-art robot. That's a very interesting question. Robot capability is, it's kind of a, I think it's a very tricky thing to understand because there are some things that are difficult that we wouldn't think are difficult, and some things that are easy that we wouldn't think are easy. And there's also a really big gap between capabilities of robots in terms of hardware and their physical capability and capabilities of robots in terms of what they can do autonomously. There is a little video that I think robotics researchers really like to show, especially robotics learning researchers like myself from 2004 from Stanford, which demonstrates a prototype robot called the PR1. And the PR1 was a robot that was designed as a home assistance robot. And there's this beautiful video showing the PR1 tidying up a living room, putting away toys, and at the end bringing a beer to the person sitting on the couch, which looks really amazing. And then the punchline is that this robot is entirely controlled by a person. So, you can, so in some ways the gap between a state-of-the-art human and a state-of-the-art robot, if the robot has a human brain, is actually not that large. Now, obviously, like human bodies are sophisticated and very robust and resilient in many ways, but on the whole, if we're willing to like spend a bit of money and do a bit of engineering, we can kind of close the hardware gap almost. But the intelligence gap, that one is very wide. LUIS So, when you say hardware, you're referring to the physical, sort of the actuators, the actual body of the robot, as opposed to the hardware on which the cognition, the nervous, the hardware of the nervous system. DAVE Yes, exactly. I'm referring to the body rather than the mind. LUIS So, what's- DAVE So, that means that the kind of the work is cut out for us. Like, while we can still make the body better, we kind of know that the big bottleneck right now is really the mind. LUIS And how big is that gap? How big is the difference in your sense of ability to learn, ability to reason, ability to perceive the world between humans and our best robots? DAVE The gap is very large, and the gap becomes larger the more unexpected events can happen in the world. So, essentially, the spectrum along which you can measure the size of that gap is the spectrum of how open the world is. If you control everything in the world very tightly, if you put the robot in like a factory, and you tell it where everything is, and you rigidly program its motion, then it can do things, you know, one might even say in a superhuman way. It can move faster, it's stronger, it can lift up a car and things like that. But as soon as anything starts to vary in the environment, now it'll trip up. And if many, many things vary like they would like in your kitchen, for example, then things are pretty much like wide open. LUIS Now, again, we're going to stick a bit on the philosophical questions, but how much on the human side of the cognitive abilities in your sense is nature versus nurture? So, how much of it is a product of evolution, and how much of it is something we'll learn from sort of scratch from the day we're born? DAVE I'm going to read into your question as asking about the implications of this for AI. I'm not a biologist, I can't really like speak authoritatively about stuff. LUIS So, in Tlingit, if it's all about learning, then there's more hope for AI. DAVE Yeah. So, the way that I look at this is that, you know, well, first, of course, biology is very messy. And if you ask the question, how does a person do something, or how does a person's mind do something, you can come up with a bunch of hypotheses. And oftentimes, you can find support for many different, often conflicting hypotheses. One way that we can approach the question of what the implication of this for AI are, is we can think about what's sufficient. So, you know, maybe a person is from birth very, very good at some things, like, for example, recognizing faces, there's a very strong evolutionary pressure to do that. If you can recognize your mother's face, then you're more likely to survive, and therefore people are good at this. But we can also ask, like, what's the minimum sufficient thing? And one of the ways that we can study the minimal sufficient thing is we could, for example, see what people do in unusual situations, if you present them with things that evolution couldn't have prepared them for. You know, our daily lives actually do this to us all the time. We didn't evolve to deal with, you know, automobiles and space flight and whatever. So, there are all these situations that we can find ourselves in, and we do very well there. Like, I can give you a joystick to control a robotic arm, which you've never used before, and you might be pretty bad for the first couple of seconds. But if I tell you, like, your life depends on using this robotic arm to, like, open this door, you'll probably manage it. Even though you've never seen this device before, you've never used the joystick control, and you'll kind of muddle through it. And that's not your evolved natural ability, that's your flexibility, your adaptability. And that's exactly where our current robotic systems really kind of fall flat. But I wonder how much general, almost what we think of as common sense, pre-trained models underneath all of that. So, that ability to adapt to a joystick requires you to have a kind of, you know, I'm human, so it's hard for me to introspect all the knowledge I have about the world, but it seems like there might be an iceberg underneath of the amount of knowledge we actually bring to the table. That's kind of the open question. I think there's absolutely an iceberg of knowledge that we bring to the table, but I think it's very likely that iceberg of knowledge is actually built up over our lifetimes. Because we have, you know, we have a lot of prior experience to draw on, and it kind of makes sense that the right way for us to, you know, to optimize our efficiency, our evolutionary fitness and so on, is to utilize all that experience to build up the best iceberg we can get. And that's actually one of, you know, while that sounds an awful lot like what machine learning actually does, I think that for modern machine learning, it's actually a really big challenge to take this unstructured mass of experience and distill out something that looks like a common sense understanding of the world. And perhaps part of that is, it's not because something about machine learning itself is broken or hard, but because we've been a little too rigid in subscribing to a very supervised, very rigid notion of learning, you know, kind of the input, output, X's go to Y's sort of model. And maybe what we really need to do is to view the world more as like a massive experience that is not necessarily providing any rigid supervision, but sort of providing many, many instances of things that could be. And then you take that and you distill it into some sort of common sense understanding. I see. Well, you're painting an optimistic, beautiful picture, especially from the robotics perspective, because that means we just need to invest and build better learning algorithms, figure out how we can get access to more and more data for those learning algorithms to extract signal from, and then accumulate that iceberg of knowledge. It's a beautiful picture. It's a hopeful one. I think it's potentially a little bit more than just that. And this is where we perhaps reach the limits of our current understanding. But one thing that I think that the research community hasn't really resolved in a satisfactory way is how much it matters where that experience comes from. Like, you know, do you just like download everything on the internet and cram it into essentially the 21st century analog of the giant language model and then see what happens? Or does it actually matter whether your machine physically experiences the world or, in the sense that it actually attempts things, observes the outcome of its actions, and kind of augments its experience that way? That it chooses which parts of the world it gets to interact with and observe and learn from. Right. It may be that the world is so complex that simply obtaining a large mass of sort of IID samples of the world is a very difficult way to go. But if you are actually interacting with the world and essentially performing this sort of hard negative mining by attempting what you think might work, observing the sometimes happy and sometimes sad outcomes of that, and augmenting your understanding using that experience, and you're just doing this continually for many years, maybe that sort of data in some sense is actually much more favorable to obtaining a common sense understanding. One reason we might think that this is true is that, you know, what we associate with common sense or lack of common sense is often characterized by the ability to reason about kind of counterfactual questions. Like, you know, if I were to, here I'm this bottle of water sitting on the table, everything is fine if I were to knock it over, which I'm not going to do, but if I were to do that, what would happen? And I know that nothing good would happen from that, but if I have a bad understanding of the world, I might think that that's a good way for me to like, you know, gain more utility. If I actually go about my daily life doing the things that my current understanding of the world suggests will give me high utility, in some ways I'll get exactly the right supervision to tell me not to do those bad things and to keep doing the good things. So there's a spectrum between IID, random walk through the space of data, and then there's, and what we humans do. I don't even know if we do it optimal, but that might be beyond. So this open question that you raised, where do you think systems, intelligent systems that would be able to deal with this world fall? Can we do pretty well by reading all of Wikipedia, sort of randomly sampling it like language models do, or do we have to be exceptionally selective and intelligent about which aspects of the world we interact with? So I think this is first an open scientific problem, and I don't have like a clear answer, but I can speculate a little bit. And what I would speculate is that you don't need to be super, super careful. I think it's less about like being careful to avoid the useless stuff, and more about making sure that you hit on the really important stuff. So perhaps it's okay if you spend part of your day just guided by your curiosity, visiting interesting regions of your state space, but it's important for you to, every once in a while, make sure that you really try out the solutions that your current model of the world suggests might be effective and observe whether those solutions are working as you expect or not. And perhaps some of that is really essential to have kind of a perpetual improvement loop. Like this perpetual improvement loop is really like, that's really the key, the key that's going to potentially distinguish the best current methods from the best methods of tomorrow in a sense. How important do you think is exploration or total out of the box thinking exploration in this space as you jump to totally different domains? So you kind of mentioned there's an optimization problem, you kind of explore the specifics of a particular strategy, whatever the thing you're trying to solve. How important is it to explore totally outside of the strategies that have been working for you so far? What's your intuition there? Yeah, I think it's a very problem dependent kind of question. And I think that that's actually, you know, in some ways that question gets at one of the big differences between sort of the classic formulation of a reinforcement learning problem and some of the sort of more open-ended reformulations of that problem that have been explored in recent years. So classically, reinforcement learning is framed as a problem of maximizing utility, like any kind of rational AI agent, and then anything you do is in service to maximizing the utility. But a very interesting kind of way to look at, I'm not necessarily saying this is the best way to look at it, but an interesting alternative way to look at these problems is as something where you first get to explore the world however you please, and then afterwards you will be tasked with doing something. And that might suggest a somewhat different solution. So if you don't know what you're going to be tasked with doing, and you just want to prepare yourself optimally for whatever your uncertain future holds, maybe then you will choose to attain some sort of coverage, build up sort of an arsenal of cognitive tools, if you will, such that later on when someone tells you, now your job is to fetch the coffee for me, you'll be well prepared to undertake that task. And you see that as the modern formulation of the reinforcement learning problem, as a kind of, the more multitask, the general intelligence kind of formulation. I think that's one possible vision of where things might be headed. I don't think that's by any means the mainstream or standard way of doing things, and it's not like if I had to- But I like it. It's a beautiful vision. So maybe actually take a step back a step back. What is the goal of robotics? What's the general problem of robotics we're trying to solve? You actually kind of painted two pictures here, one of sort of the narrow, one of the general. What in your view is the big problem of robotics? Again, ridiculously philosophical, high level questions. I think that, you know, maybe there are two ways I can answer this question. One is there's a very pragmatic problem, which is like, what would make robots, what would sort of maximize the usefulness of robots? And there, the answer might be something like a system where, a system that can perform whatever task a human user sets for it, you know, within the physical constraints, of course, if you tell it to teleport to another planet, it probably can't do that. But if you ask it to do something that's within its physical capability, then potentially with a little bit of additional training or a little bit of additional trial and error, it ought to be able to figure it out in much the same way as like a human teleoperator ought to figure out how to drive the robot to do that. That's kind of the very pragmatic view of what it would take to kind of solve the robotics problem, if you will. But I think that there is a second answer. And that answer, that answer is a lot closer to why I want to work on robotics, which is that I think it's less about what it would take to do a really good job in the world of robotics, but more the other way around, what robotics can bring to the table to help us understand artificial intelligence. Lex Dressel So your dream, fundamentally, is to understand intelligence. Peter T. Leeson Yes, I think that's the dream for many people who actually work in this space. I think that there's something very pragmatic and very useful about studying robotics. But I do think that a lot of people that go into this field, actually, you know, the things that they draw inspiration from are the potential for robots to like help us learn about intelligence and about ourselves. Lex Dressel So that's fascinating that robotics is basically the space by which you can get closer to understanding the fundamentals of artificial intelligence. So what is it about robotics that's different from some of the other approaches? So if we look at some of the early breakthroughs in deep learning, or in the computer vision space, and the natural language processing, there's really nice, clean benchmarks that a lot of people competed on and thereby came up with a lot of brilliant ideas. What's the fundamental difference to you between computer vision, purely defined and ImageNet and kind of the bigger robotics problem? Peter T. Leeson So there are a couple of things. One is that with robotics, you kind of have to take away many of the crutches. So you have to deal with both the particular problems of perception, control, and so on, but you also have to deal with the integration of those things. And, you know, classically, we've always thought of the integration as kind of a separate problem. So a classic kind of modular engineering approach is that we solve the individual sub problems, then wire them together, and then the whole thing works. And one of the things that we've been seeing over the last couple of decades is that, well, maybe studying the thing as a whole might lead to just like very different solutions than if we were to study the parts and wire them together. So the integrative nature of robotics research helps us see, you know, different perspectives on the problem. Another part of the answer is that with robotics, it casts a certain paradox into very clever relief. So this is sometimes referred to as a Moravic's paradox, the idea that in artificial intelligence, things that are very hard for people can be very easy for machines and vice versa, things that are very easy for people can be very hard for machines. So, you know, integral and differential calculus is pretty difficult to learn for people, but if you program a computer, do it, it can derive derivatives and integrals for you all day long without any trouble. Whereas some things like, you know, drinking from a cup of water, very easy for a person to do, very hard for a robot to deal with. And sometimes when we see such blatant discrepancies that give us a really strong hint that we're missing something important. So if we really try to zero in on those discrepancies, we might find that little bit that we're missing. And it's not that we need to make machines better or worse at math and better at drinking water, but just that by studying those discrepancies, we might find some new insight. So that could be in any space, it doesn't have to be robotics, but you're saying, I mean, it's kind of interesting that robotics seems to have a lot of those discrepancies. So the Hans-Marvik paradox is probably referring to the space of the physical interaction, like you said, object manipulation, walking, all the kind of stuff we do in the physical world. So how do you make sense, if you were to try to disentangle the Marvik paradox, like why is there such a gap in our intuition about it? Why do you think manipulating objects is so hard from everything you've learned from applying reinforcement learning in this space? Yeah, I think that one reason is maybe that for many of the other problems that we've studied in AI and computer science and so on, the notion of input output and supervision is much, much cleaner. So computer vision, for example, deals with very complex inputs, but it's comparatively a bit easier, at least up to some level of abstraction to cast it as a very tightly supervised problem. It's comparatively much, much harder to cast robotic manipulation as a very tightly supervised problem. You can do it, it just doesn't seem to work all that well. So you could say that, well, maybe we get a label data set where we know exactly which motor commands to send and then we train on that. But for various reasons, that's not actually such a great solution. And it also doesn't seem to be even remotely similar to how people and animals learn to do things because we're not told by our parents, here's how you fire your muscles in order to walk. We do get some guidance, but the really low level detailed stuff, we figure out mostly on our own. And that's what you mean by tightly coupled, that every single little sub action gets a supervised signal of whether it's a good one or not. Right. So while in computer vision, you could imagine up to a level of abstraction that maybe somebody told you this is a car and this is a cat and this is a dog, in motor control, it's very clear that that was not the case. If we look at sort of the sub spaces of robotics, that again, as you said, robotics integrates all of them together and we'll get to see how this beautiful mess interplays. But so there's nevertheless still perception. So it's the computer vision problem, broadly speaking, understanding the environment. Then there's also, maybe you can correct me on this kind of categorization of the space, then there's prediction in trying to anticipate what things are going to do into the future in order for you to be able to act in that world. And then there's also this game theoretic aspect of how your actions will change the behavior of others. In this kind of space, what's, and this is bigger than reinforcement learning, this is just broadly looking at the problem of robotics, what's the hardest problem here? Or is there, or is what you said true that when you start to look at all of them together, that's a whole nother thing. Like you can't even say which one individually is harder because all of them together, you should only be looking at them all together. I think when you look at them all together, some things actually become easier. And I think that's actually pretty important. So we had, you know, back in 2014, we had some work, basically our first work on end to end reinforced learning for robotic manipulation skills from vision, which, you know, at the time was something that seemed a little inflammatory and controversial in the robotics world. But other than the inflammatory and controversial part of it, the point that we were actually trying to make in that work is that for the particular case of combining perception and control, you could actually do better if you treat them together than if you try to separate them. And the way that we tried to demonstrate this is we picked a fairly simple motor control task where a robot had to insert a little red trapezoid into a trapezoidal hole. And we had our separated solution, which involved first detecting the hole using a pose detector and then actuating the arm to put it in. And then our intent solution, which just mapped pixels to the torques. And one of the things we observed is that if you use the intent solution, essentially the pressure on the perception part of the model is actually lower. Like it doesn't have to figure out exactly where the thing is in 3D space. It just needs to figure out where it is, you know, distributing the errors in such a way that the horizontal difference matters more than the vertical difference because vertically it just pushes it down all the way until it can't go any further. And their perceptual errors are a lot less harmful, whereas perpendicular to the direction of motion, perceptual errors are much more harmful. So the point is that if you combine these two things, you can trade off errors between the components optimally to best accomplish the task. And the components can actually be weaker while still leading to better overall performance. That's a profound idea. I mean, in the space of pegs and things like that, it's quite simple. It almost is tempting to overlook, but that seems to be at least intuitively an idea that should generalize to basically all aspects of perception and control. Of course. That one strengthens the other. Yeah. And people who have studied sort of perceptual heuristics in humans and animals find things like that all the time. So one very well-known example of this is something called the gaze heuristic, which is a little trick that you can use to intercept a flying object. So if you want to catch a ball, for instance, you could try to localize it in 3D space, estimate its velocity, estimate the effect of wind resistance, solve a complex system of differential equations in your head. Or you can maintain a running speed so that the object stays in the same position as in your field of view. So if it dips a little bit, you speed up. If it rises a little bit, you slow down. And if you follow the simple rule, you'll actually arrive at exactly the place where the object lands and you'll catch it. And humans use it when they play baseball. Human pilots use it when they fly airplanes to figure out if they're about to collide with somebody. Frogs use this to catch insects and so on and so on. So this is something that actually happens in nature. And I'm sure this is just one instance of it that we were able to identify just because scientists were able to identify because it's so prevalent, but there are probably many others. Do you have a, just so we can zoom in as we talk about robotics, do you have a canonical problem, sort of a simple, clean, beautiful, representative problem in robotics that you think about when you're thinking about some of these problems? We talked about robotic manipulation. To me, that seems intuitively, at least the robotics community has converged towards that as a space. That's the canonical problem. If you agree, then maybe do you zoom in in some particular aspect of that problem that you just like? Like if we solve that problem perfectly, it'll unlock a major step in towards human level intelligence. I don't think I have like a really great answer to that. And I think partly the reason I don't have a great answer kind of has to do with the, it has to do with the fact that the difficulty is really in the flexibility and adaptability rather than in doing a particular thing really, really well. So it's hard to just say like, oh, if you can, I don't know, like shuffle a deck of cards as fast as like a Vegas casino dealer, then you'll be very proficient. It's really the ability to quickly figure out how to do some arbitrary new thing well enough to like, you know, to move on to the next arbitrary thing. But the source of newness and uncertainty, have you found problems in which it's easy to generate new newness-ness-nesses? Yeah. New types of newness. Yeah. So a few years ago, so if you'd asked me this question around like 2016, maybe, I would have probably said that robotic grasping is a really great example of that because it's a task with great real world utility. Like you will get a lot of money if you can do it well. What is robotic grasping? Picking up any object. With a robotic hand. Exactly. So you will get a lot of money if you do it well, because lots of people want to run warehouses with robots. And it's highly non-trivial because very different objects will require very different grasping strategies. But actually, since then, people have gotten really good at building systems to solve this problem. To the point where I'm not actually sure how much more progress we can make with that as like the main guiding thing. But it's kind of interesting to see the kind of methods that have actually worked well in that space because robotic grasping classically used to be regarded very much as almost like a geometry problem. So people who have studied the history of computer vision will find this very familiar. That it's kind of in the same way that in the early days of computer vision, people thought of it very much as like an inverse graphics thing. In robotic grasping, people thought of it as an inverse physics problem, essentially. You look at what's in front of you, figure out the shapes, then use your best estimate of the laws of physics to figure out where to put your fingers on, you pick up the thing. And it turns out that what works really well for robotic grasping, instantiated in many different recent works, including our own, but also ones from many other labs, is to use learning methods with some combination of either exhaustive simulation or like actual real world trial and error. And it turns out that those things actually work really well. And then you don't have to worry about solving geometry problems or physics problems. So what are, just by the way, in the grasping, what are the difficulties that have been worked on? So one is like the materials of things, maybe occlusions on the perception side. Why is it such a difficult, why is picking stuff up such a difficult problem? Yeah. It's a difficult problem because the number of things that you might have to deal with, or the variety of things that you have to deal with is extremely large. And oftentimes things that work for one class of objects won't work for other classes of objects. So if you get really good at picking up boxes and now you have to pick up plastic bags, you just need to employ a very different strategy. And there are many properties of objects that are more than just their geometry. It has to do with the bits that are easier to pick up, the bits that are harder to pick up, the bits that are harder to pick up, the bits that are more flexible, the bits that will cause the thing to pivot and bend and drop out of your hand versus the bits that result in a nice secure grasp, things that are flexible, things that if you pick them up the wrong way, they'll fall upside down and the contents will spill out. So there's all these little details that come up, but the task is still kind of can be characterized as one task. Like there's a very clear notion of you did it or you didn't do it. So in terms of spilling things, there creeps in this notion that starts to sound and feel like common sense reasoning. Do you think solving the general problem of robotics requires common sense reasoning, requires general intelligence, this kind of human level capability of, you know, like you said, be robust and deal with uncertainty, but also be able to sort of reason and assimilate different pieces of knowledge that you have? Yeah. What are your thoughts on the needs of common sense reasoning in the space of the general robotics problem? So I'm going to slightly dodge that question and say that I think maybe actually it's the other way around is that studying robotics can help us understand how to put common sense into our AI systems. One way to think about common sense is that, and why our current systems might lack common sense, is that common sense is a property, is an emergent property of actually having to interact with a particular world, a particular universe and get things done in that universe. So you might think that, for instance, like an image captioning system, maybe it looks at pictures of the world and it types out English sentences. So it kind of deals with our world. And then you can easily construct situations where image captioning systems do things that defy common sense, like give it a picture of a person wearing a fur coat and we'll say it's a teddy bear. But I think what's really happening in those settings is that the system doesn't actually live in our world. It lives in its own world that consists of pixels and English sentences and doesn't actually consist of like, you know, having to put on a fur coat in the winter so you don't get cold. So perhaps the reason for the disconnect is that the systems that we have now simply inhabit a different universe. And if we build AI systems that are forced to deal with all of the messiness and complexity of our universe, maybe they will have to acquire common sense to essentially maximize their utility. Whereas the systems we're building now don't have to do that. They can take some shortcut. That's fascinating. You've a couple of times already sort of reframed the role of robotics in this whole thing. And for some reason, I don't know if my way of thinking is common, but I thought like, we need to understand and solve intelligence in order to solve robotics. And you're kind of framing it as, no, robotics is one of the best ways to just study artificial intelligence and build sort of like, robotics is like the right space in which you get to explore some of the fundamental learning mechanisms, fundamental sort of multimodal, multitask aggregation of knowledge mechanisms that are required for general intelligence. That's really interesting way to think about it. But let me ask about learning. Can the general sort of robotics, the epitome of the robotics problem be solved purely through learning, perhaps end to end learning, sort of learning from scratch as opposed to injecting human expertise and rules and heuristics and so on? I think that in terms of the spirit of the question, I would say yes. I mean, I think that though in some ways it's maybe like an overly sharp dichotomy. Like, you know, I think that in some ways when we build algorithms, we, you know, at some point a person does something. Yeah, hyper parameters. There's always- A person turned on the computer, a person, you know, implemented TensorFlow. But yeah, I think that in terms of the point that you're getting at, I do think the answer is yes. I think that we can solve many problems that have previously required meticulous manual engineering through automated optimization techniques. And actually one thing I will say on this topic is, I don't think this is actually a very radical or very new idea. I think people have been thinking about automated optimization techniques as a way to do control for a very, very long time. And in some ways what's changed is really more the name. So, you know, today we would say that, oh, my robot does machine learning. It does reinforcement learning. Maybe in the 1960s, you'd say, oh, my robot is doing optimal control. And maybe the difference between typing out a system of differential equations and doing feedback linearization versus training a neural net, maybe it's not such a large difference. It's just, you know, pushing the optimization deeper and deeper into the thing. Well, it's interesting you think that way, but with, especially with deep learning, that the accumulation of sort of experiences in data form to form deep representations starts to feel like knowledge as opposed to optimal control. So, this feels like there's an accumulation of knowledge through the learning process. Yes. Yeah. So, I think that is a good point that one big difference between learning-based systems and classic optimal control systems is that learning-based systems in principle should get better and better the more they do something. And I do think that that's actually a very, very powerful difference. So, if we look back at the world of expert systems, the symbolic AI and so on, of using logic to accumulate expertise, human expertise, human encoded expertise, do you think that will have a role at some point? So, the, you know, deep learning, machine learning, reinforcement learning has shown incredible results and breakthroughs and just inspired thousands, maybe millions of researchers. But, you know, there's this less popular now, but it used to be popular idea of symbolic AI. Do you think that will have a role? I think in some ways, the kind of the descendants of symbolic AI actually already have a role. So, you know, this is the highly biased history from my perspective. You say that, well, initially we thought that rational decision-making involves logical manipulation. So, you have some model of the world expressed in terms of logic. You have some query, like what action do I take in order to, for X to be true? And then you manipulate your logical symbolic representation to get an answer. What that turned into somewhere in the 1990s is, well, instead of building kind of predicates and statements that have true or false values, we'll build probabilistic systems where things have probabilities associated and probabilities of being true and false, and that turned into Bayes nets. And that provided sort of a boost to what were really, you know, still essentially logical inference systems, just probabilistic logical inference systems. And then people said, well, let's actually learn the individual probabilities inside these models. And then people said, well, let's not even specify the nodes in the models. Let's just put a big neural net in there. But in many ways, I see these as actually kind of descendants from the same idea. It's essentially instantiating rational decision-making by means of some inference process and learning by means of an optimization process. So, in a sense, I would say, yes, that it has a place. And in many ways, that place is, you know, it already holds that place. It's already in there. Yeah, it's just by different, it looks slightly different than it was before. Yeah. But there are some things that we can think about that make this a little bit more obvious. Like if I train a big neural net model to predict what will happen in response to my robot's actions, and then I run probabilistic inference, meaning I invert that model to figure out the actions that lead to some plausible outcome. Like, to me, that seems like a kind of logic. You have a model of the world that just happens to be expressed by a neural net, and you are doing some inference procedure, some sort of manipulation on that model to figure out, you know, the answer to a query that you have. It's the interpretability, it's the explainability, though, that seems to be lacking more so. Because the nice thing about sort of expert systems is you can follow the reasoning of the system. That to us mere humans is somehow compelling. It's just, I don't know what to make of this fact that there's a human desire for intelligent systems to be able to convey in a poetic way to us why it made the decisions it did. Like tell a convincing story. And perhaps that's like a silly human thing. Like we shouldn't expect that of intelligent systems. Like we should be super happy that there's intelligent systems out there. But if I were to sort of psychoanalyze the researchers at the time, I would say expert systems connected to that part, that desire of AI researchers for systems to be explainable. I mean, maybe on that topic, do you have a hope that sort of inference systems, so learning-based systems will be as explainable as the dream was with expert systems, for example? I think it's a very complicated question because I think that in some ways the question of explainability is kind of very closely tied to the question of performance. Like, you know, why do you want your system to explain itself? Well, so that when it screws up, you can kind of figure out why it did it. But in some ways that's a much bigger problem, actually. Like your system might screw up and then it might screw up in how it explains itself, or you might have some bug somewhere so that it's not actually doing what it was supposed to do. So, you know, maybe a good way to view that problem is really as a bigger problem of verification and validation of which explainability is sort of one component. I see. I just see it differently. I see explainability, you put it beautifully, I think you actually summarize the field of explainability. But to me, there's another aspect of explainability, which is like storytelling that has nothing to do with errors or with, like, it doesn't, it uses errors as elements of its story, as opposed to a fundamental need to be explainable when errors occur. It's just that for other intelligence systems to be in our world, we seem to want to tell each other stories. And that's true in the political world, that's true in the academic world, and that, you know, neural networks are less capable of doing that, or perhaps they're equally capable of storytelling and storytelling. Maybe it doesn't matter what the fundamentals of the system are, you just need to be a good storyteller. Maybe one specific story I can tell you about in that space is actually about some work that was done by my former collaborator, who's now a professor at MIT named Jacob Andreas. Jacob actually works in natural language processing, but he had this idea to do a little bit of work in reinforcement learning, and how natural language can basically structure the internals of policies trained with RL. And one of the things he did is he set up a model that attempts to perform some task that's defined by a reward function, but the model reads in a natural language instruction. So this is a pretty common thing to do in instruction following. So you tell it, like, you know, go to the red house, and then it's supposed to go to the red house. But then one of the things that Jacob did is he treated that sentence not as a command from a person, but as a representation of the internal kind of state of the mind of this policy, essentially. So that when it was faced with a new task, what it would do is it would basically try to think of possible language descriptions, attempt to do them, and see if they led to the right outcome. So it would kind of think out loud, like, you know, I'm faced with this new task, what am I going to do? Let me go to the red house. Oh, that didn't work. Let me go to the blue room or something. Let me go to the green plant. And once it got some reward, it would say, oh, go to the green plant. That's what's working. I'm going to go to the green plant. And then you could look at the string that it came up with, and that was a description of how it thought it should solve the problem. So you could basically incorporate language as internal state, and you can start getting some handle on these kinds of things. And then what I was kind of trying to get to is that also, if you add to the reward function, the convincingness of that story. So I have another reward signal of, like, people who review that story, how much they like it. So that, you know, initially that could be a hyperparameter, sort of hard-coded heuristic type of thing, but it's an interesting notion of the convincingness of the story becoming part of the reward function, the objective function, the explainability. It's, in the world of sort of Twitter and fake news, that might be a scary notion, that the nature of truth may not be as important as the convincingness of the, how convinced you are in telling the story around the facts. Well, let me ask the basic question. You're one of the world-class researchers in reinforcement learning, deep reinforcement learning, certainly in the robotics space. What is reinforcement learning? I think that what reinforcement learning refers to today is really just the kind of the modern incarnation of learning-based control. So classically, reinforcement learning has a much more narrow definition, which is that it's, you know, literally learning from reinforcement, like, the thing does something and then it gets a reward or punishment. But really, I think the way the term is used today is it's used to refer more broadly to learning-based control. So some kind of system that's supposed to be controlling the system, but it's not. So it's not a system that is actually controlling something, and it uses data to get better. And what does control mean? So is action is the fundamental element there? It means making rational decisions. And rational decisions are decisions that maximize a measure of utility. And sequentially, so you make decisions time and time and time again. Now, like, it's easier to see that kind of idea in the space of maybe games and the space of robotics. Do you see it bigger than that? Is it applicable? Like, where are the limits of the applicability of reinforcement learning? Yeah, so rational decision making is essentially the encapsulation of the AI problem viewed in through a particular lens. So any problem that we would want a machine to do, an intelligent machine can likely be represented as a decision making problem. Classifying images is a decision making problem, although not a sequential one, typically. You know, controlling a chemical plant is a decision making problem. Deciding what videos to recommend on YouTube is a decision making problem. And one of the really appealing things about reinforcement learning is, if it does encapsulate the range of all these decision making problems, perhaps working on reinforcement learning is, you know, one of the ways to reach a very broad swath of AI problems. But what is the fundamental difference between reinforcement learning and maybe supervised machine learning? So reinforcement learning can be viewed as a generalization of supervised machine learning. You can certainly cast supervised learning as a reinforcement learning problem. You can just say your loss function is the negative of your reward. But you have stronger assumptions. You have the assumption that someone actually told you what the correct answer was, that your data was IID and so on. So you could view reinforcement learning as essentially relaxing some of those assumptions. Now, that's not always a very productive way to look at it, because if you actually have a supervised learning problem, you'll probably solve it much more effectively by using supervised learning methods, because it's easier. But you can view reinforcement learning as a generalization of that. No, for sure. But they're fundamentally different. That's a mathematical statement that's absolutely correct. But it seems that reinforcement learning, the kind of tools we bring to the table today, of today, so maybe down the line, everything will be a reinforcement learning problem, just like you said, image classification should be mapped to a reinforcement learning problem. But today, the tools and ideas, the way we think about them are different. Sort of supervised learning has been used very effectively to solve basic, narrow AI problems. Reinforcement learning kind of represents the dream of AI. It's very much so in the research space now, in sort of captivating the imagination of people of what we can do with intelligent systems. But it hasn't yet had as wide of an impact as the supervised learning approaches. So that, sort of, my question comes from the more practical sense. Like, what do you see is the gap between the more general reinforcement learning and the very specific, yes, sequential decision making with one step in the sequence of the supervised learning? So from a practical standpoint, I think that one thing that is, you know, potentially a little tough now, and this is, I think, something that we'll see, this is a gap that we might see closing over the next couple of years, is the ability of reinforcement learning algorithms to effectively utilize large amounts of prior data. So one of the reasons why it's a bit difficult today to use reinforcement learning for all the things that we might want to use it for is that in most of the settings where we want to do rational decision making, it's a little bit tough to just deploy some policy that does crazy stuff and learns purely through trial and error. It's much easier to collect a lot of data, a lot of logs of some other policy that you've got. And then maybe you, you know, if you can get a good policy out of that, then you deploy it and let it kind of fine tune a little bit. But algorithmically, it's quite difficult to do that. So I think that once we figure out how to get reinforcement learning to bootstrap effectively from large data sets, then we'll see very, very rapid growth in applications of these technologies. So this is what's referred to as off-policy reinforcement learning or offline RL or batch RL. And I think we're seeing a lot of research right now that's bringing us closer and closer to that. Can you maybe paint the picture of the different methods? So you said off-policy, what's value-based reinforcement learning, what's policy-based, what's model-based, what's off-policy, on-policy? What are the different categories of reinforcement learning? Yeah. So one way we can think about reinforcement learning is that it's, in some very fundamental way, it's about learning models that can answer kind of what-if questions. So what would happen if I take this action that I hadn't taken before? And you do that, of course, from experience, from data. And oftentimes you do it in a loop. So you build a model that answers these what-if questions, use it to figure out the best action you can take, and then go and try taking that and see if the outcome agrees with what you predicted. So the different kinds of techniques basically refer to different ways of doing it. So model-based methods answer a question of what state you would get, basically what would happen to the world if you were to take a certain action. Value-based methods, they answer the question of what value you would get, meaning what utility you would get. But in a sense, they're not really all that different because they're both really just answering these what-if questions. Now, unfortunately for us, with current machine learning methods, answering what-if questions can be really hard because they are really questions about things that didn't happen. If you wanted to answer what-if questions about things that did happen, you wouldn't need a learned model. You would just repeat the thing that worked before. And that's really a big part of why RL is a little bit tough. So if you have a purely on-policy kind of online process, then you ask these what-if questions, you make some mistakes, then you go and try doing those mistaken things, and then you observe kind of the counter examples that will teach you not to do those things again. If you have a bunch of off-policy data and you just want to synthesize the best policy you can out of that data, then you really have to deal with the challenges of making these counterfactual. First of all, what's a policy? Yeah. A policy is a model or some kind of function that maps from observations of the world to actions. So in reinforcement learning, we often refer to the current configuration of the world as the state. So we say the state kind of encompasses everything you need to fully define where the world is at at the moment. And depending on how we formulate the problem, we might say you either get to see the state or you get to see an observation, which is some snapshot, some piece of the state. So policy just includes everything in it in order to be able to act in this world. Yes. And so what does off-policy mean? Yeah. So the terms on-policy and off-policy refer to how you get your data. So if you get your data from somebody else who was doing some other stuff, maybe you get your data from a company, maybe you get your data from some manually programmed system that was just running in the world before, that's referred to as off-policy data. But if you got the data by actually acting in the world based on what your current policy thinks is good, we call that on-policy data. And obviously, on-policy data is more useful to you because if your current policy makes some bad decisions, you will actually see that those decisions are bad. Off-policy data, however, is more useful to you because maybe that's all the log data that you have from before. So we talked about offline, talked about autonomous vehicles, so you can envision off-policy kind of approaches in robotic spaces where there's already a ton of robots out there, but they don't get the luxury of being able to explore based on reinforcement learning framework. So how do we make, again, open question, but how do we make off-policy methods work? So this is something that has been kind of a big open problem for a while. And in the last few years, people have made a little bit of progress on that. I can tell you about it, and it's not by any means solved yet, but I can tell you some of the things that, for example, we've done to try to address some of the challenges. It turns out that one really big challenge with off-policy reinforcement learning is that you can't really trust your models to give accurate predictions for any possible action. So if in my data set, I never saw somebody steering the car off the road onto the sidewalk, my value function or my model is probably not going to predict the right thing if I ask what would happen if I were to steer the car off the road onto the sidewalk. So one of the important things you have to do to get off-policy RL to work is you have to be able to figure out whether a given action will result in a trustworthy prediction or not. And you can use kind of distribution estimation methods, kind of density estimation methods to try to figure that out. So you could figure out that, well, this action, my model is telling me that it's great, but it looks totally different from any action I've taken before, so my model is probably not correct. And you can incorporate regularization terms into your learning objective that will essentially tell you not to ask those questions that your model is unable to answer. Lex Dems What would lead to breakthroughs in this space, do you think? Like what's needed? Is this a data set question? Do we need to collect big benchmark data sets that allow us to explore the space? Is it a new kinds of methodologies? Like what's your sense? Or maybe coming together in a space of robotics and defining the right problem to be working on? Peter T. Leeson Yeah. I think for off-policy reinforcement learning in particular, it's very much an algorithms question right now. And this is something that I think is great because an algorithms question is that that just takes some very smart people to get together and think about it really hard. Whereas if it was like a data problem or hardware problem, that would take some serious engineering. So that's why I'm pretty excited about that problem, because I think that we're in a position where we can make some real progress on it just by coming up with the right algorithms. In terms of which algorithms they could be, the problems at their core are very related to problems in things like causal inference, right? Because what you're really dealing with is situations where you have a model, a statistical model, that's trying to make predictions about things that it hadn't seen before. And if it's a model that's generalizing properly, that'll make good predictions. If it's a model that picks up on spurious correlations, that will not generalize properly. And then you have an arsenal of tools you could use. You could, for example, figure out what are the regions where it's trustworthy. Or on the other hand, you could try to make it generalize better somehow, or some combination of the two. Is there room for mixing, sort of, where most of it, like 90, 95 percent, is off policy, you already have the data set, and then you get to send the robot out to do a little exploration? Like, what's that role of mixing them together? Yeah, absolutely. I think that this is something that you actually meant to describe very well at the beginning of our discussion when you talked about the iceberg. Like, this is the iceberg. The 99 percent of your prior experience, that's your iceberg. You use that for off-policy reinforcement learning. And then, of course, if you've never, you know, opened that particular kind of door with that particular lock before, then you have to go out and fiddle with it a little bit. And that's that additional one percent to help you figure out a new task. And I think that's actually, like, a pretty good recipe going forward. Is this, to you, the most exciting space of reinforcement learning now? Or is there, what's, and maybe taking a step back, not just now, but what's, to you, is the most beautiful idea? I apologize for the romanticized question, but the beautiful idea or concept in reinforcement learning? In general, I actually think that one of the things that is a very beautiful idea in reinforcement learning is just the idea that you can obtain a near-optimal control or near-optimal policy without actually having a complete model of the world. This is, you know, it's something that feels perhaps kind of obvious if you just hear the term reinforcement learning or you think about trial and error learning. But from a controls perspective, it's a very weird thing because classically, you know, we think about engineered systems and controlling engineered systems as the problem of writing down some equations and then figuring out, given these equations, you know, basically like solve for x, figure out the thing that maximizes its performance. And the theory of reinforcement learning actually gives us a mathematically principled framework to think, to reason about, you know, optimizing some quantity when you don't actually know the equations that govern that system. And that, I don't know, to me that actually seems kind of, you know, very elegant. Not something that sort of becomes immediately obvious, at least in the mathematical sense. Does it make sense to you that it works at all? Well, I think it makes sense when you take some time to think about it, but it is a little surprising. Well, then taking a step into the more deeper representations, which is also very surprising of the sort of the richness of the state space, the space of environments that this kind of approach can operate in. Can you maybe say what is deep reinforcement learning? Well, deep reinforcement learning simply refers to taking reinforcement learning algorithms and combining them with high capacity neural net representations, which is, you know, kind of, it might at first seem like a pretty arbitrary thing, just take these two components and stick them together. But the reason that it's something that has become so important in recent years is that reinforcement learning, it kind of faces an exacerbated version of a problem that has faced many other machine learning techniques. So if we go back to like, you know, the early 2000s or the late 90s, we'll see a lot of research on machine learning methods that have some very appealing mathematical properties, like they reduce the convex optimization problems, for instance, but they require very special inputs. They require a representation of the input that is clean in some way, like for example, clean in the sense that the classes in your multi-class classification problems separate linearly. So they have some kind of good representation, and we call this feature representation. And for a long time, people were very worried about features in the world of supervised learning because somebody had to actually build those features. So you couldn't just take an image and plug it into your logistic regression or your SVM or something. Someone had to take that image and process it using some handwritten code. And then neural nets came along and they could actually learn the features. And suddenly we could apply learning directly to the raw inputs, which was great for images, but it was even more great for all the other fields where people hadn't come up with good features yet. And one of those fields was actually reinforcement learning, because in reinforcement learning, the notion of features, if you don't use neural nets and you have to design your own features, is very, very opaque. It's very hard to imagine, let's say I'm playing chess or Go. What is a feature with which I can represent the value function for Go or even the optimal policy for Go linearly? I don't even know how to start thinking about it. And people tried all sorts of things. They would write down, an expert chess player looks for whether the knight is in the middle of the board or not. So that's a feature. Is knight in middle of board? And they would write these long lists of arbitrary made up stuff. And that was really getting us nowhere. And chess is a little more accessible than the robotics problem. Absolutely. Right? There's at least experts in the different features for chess. But still, the neural network there, to me, that's, I mean, you put it eloquently and almost made it seem like a natural step to add neural networks. But the fact that neural networks are able to discover features in the control problem, it's very interesting. It's hopeful. I'm not sure what to think about it, but it feels hopeful that the control problem has features to be learned. Like, I guess my question is, is it surprising to you how far the deep side of deep reinforcement learning was able to, like what the space of problems has been able to tackle from, especially in games with the alpha star and alpha zero and just the representation power there and in the robotics space. And what is your sense of the limits of this representation power and the control context? I think that in regard to the limits bit here, I think that one thing that makes it a little hard to fully answer this question is because in settings where we would like to push these things to the limit, we encounter other bottlenecks. So like the reason that I can't get my robot to learn how to like, I don't know, do the dishes in the kitchen, it's not because it's neural net is not big enough. It's because when you try to actually do trial and error learning, reinforcement learning directly in the real world, where you have the potential to gather these large, very highly varied and complex datasets, you start running into other problems. Like one problem you run into very quickly, it'll first sound like a very pragmatic problem, but it actually turns out to be a pretty deep scientific problem. Take the robot, put it in your kitchen, have it try to learn to do the dishes with trial and error. It'll break all your dishes and then we'll have no more dishes to clean. Now you might think this is a very practical issue, but there's something to this, which is that if you have a person trying to do this, a person will have some degree of common sense. They'll break one dish, they'll be a little more careful with the next one. And if they break all of them, they're going to go and get more or something like that. So there's all sorts of scaffolding that comes very naturally to us for our learning process. Like if I have to learn something through trial and error, I have the common sense to know that I have to try multiple times. If I screw something up, I ask for help or I reset things or something like that. And all of that is kind of outside of the classic reinforcement learning problem formulation. There are other things that can also be categorized as kind of scaffolding, but are very important. Like for example, where do you get your reward function? If I want to learn how to pour a cup of water, well, how do I know if I've done it correctly? Now that probably requires an entire computer vision system to be built just to determine that. And that seems a little bit inelegant. So there are all sorts of things like this that start to come up when we think through what we really need to get reinforcement learning to happen at scale in the real world. And I think that many of these things actually suggest a little bit of a shortcoming in the problem formulation and a few deeper questions that we have to resolve. Lexay That's really interesting. I talked to like David Silver about AlphaZero and it seems like there's no, again, we haven't hit the limit at all in the context when there is no broken dishes. So in the case of Go, you can, it's really about just scaling compute. So again, like the bottleneck is the amount of money you're willing to invest in compute and then maybe the different, the scaffolding around how difficult it is to scale compute maybe. But there, there's no limit. And it's interesting. Now we move to the real world and there's the broken dishes, there's all the, and the reward function like you mentioned, that's really nice. So what, how do we push forward there? Do you think, there's this kind of sample efficiency question that people bring up of, you know, not having to break 100,000 dishes. Is this an algorithm question? Is this a data selection like question? What do you think? How do we, how do we not break too many dishes? Yeah. Well, one way we can think about that is that maybe we need to be better at reusing our data, building that iceberg. So perhaps it's too much to hope that you can have a machine that in isolation, in the vacuum without anything else can just master complex tasks in like in minutes, the way that people do. But perhaps it also doesn't have to, perhaps what it really needs to do is have an existence, a lifetime where it does many things and the previous things that it has done, prepare it to do new things more efficiently. And, you know, the study of these kinds of questions typically falls under categories like multitask learning or meta learning. But they all fundamentally deal with the same general theme, which is use experience for doing other things to learn to do new things efficiently and quickly. So what do you think about if you just look at the one particular case study of Tesla autopilot that has quickly approaching towards a million vehicles on the road, where some percentage of the time, 30, 40% of the time is driven using the computer vision, multitask, HydroNet, right? And then the other percent, that's what they call it, HydroNet. The other percent is human controlled. From the human side, how can we use that data? What's your sense? So like, what's the signal? Do you have ideas in this autonomous vehicle space when people can lose their lives? You know, it's a safety critical environment. So how do we use that data? So I think that actually the kind of problems that come up when we want systems that are reliable and that can kind of understand the limits of their capabilities, they're actually very similar to the kind of problems that come up when we're doing off policy reinforcement learning. So as I mentioned before, in off policy reinforcement learning, the big problem is you need to know when you can trust the predictions of your model. Because if you're trying to evaluate some pattern of behavior for which your model doesn't give you an accurate prediction, then you shouldn't use that to modify your policy. And it's actually very similar to the problem that we're faced when we actually then deploy that thing and we want to decide whether we trust it in the moment or not. So perhaps we just need to do a better job of figuring out that part. And that's a very deep research question, of course, but it's also a question that a lot of people are working on. So I'm pretty optimistic that we can make some progress on that over the next few years. What's the role of simulation in reinforcement learning, deep reinforcement learning, reinforcement learning? Like how essential is it? It's been essential for the breakthroughs so far, for some interesting breakthroughs. Do you think it's a crutch that we rely on? I mean, again, this connects to our off policy discussion, but do you think we can ever get rid of simulation? Or do you think simulation will actually take over? We'll create more and more realistic simulations that will allow us to solve actual real world problems, like transfer the models we learn in simulation to real world problems? Yeah. I think that simulation is a very pragmatic tool that we can use to get a lot of useful stuff to work right now. But I think that in the long run, we will need to build machines that can learn from real data, because that's the only way that we'll get them to improve perpetually. Because if we can't have our machines learn from real data, if they have to rely on simulated data, eventually the simulator becomes the bottleneck. In fact, this is a general thing. If your machine has any bottleneck that is built by humans and that doesn't improve from data, it will eventually be the thing that holds it back. And if you're entirely reliant on your simulator, that'll be the bottleneck. If you're entirely reliant on a manually designed controller, that's going to be the bottleneck. So simulation is very useful. It's very pragmatic, but it's not a substitute for being able to utilize real experience. And this is, by the way, this is something that I think is quite relevant now, especially in the context of some of the things we've discussed, because some of these kind of scaffolding issues that I mentioned, things like the broken dishes and the unknown reward function, like these are not problems that you would ever stumble on when working in a purely simulated kind of environment. But they become very apparent when we try to actually run these things in the real world. To throw a brief wrench into our discussion, let me ask, do you think we're living in a simulation? Oh, I have no idea. Do you think that's a useful thing to even think about, about the fundamental physics nature of reality? Or another perspective, the reason I think the simulation hypothesis is interesting is to think about how difficult is it to actually create sort of a virtual reality game type situation that will be sufficiently convincing to us humans or sufficiently enjoyable that we wouldn't want to leave? I mean, that's actually a practical engineering challenge. And I personally really enjoy virtual reality, but it's quite far away. But I kind of think about what would it take for me to want to spend more time in virtual reality versus the real world? And that's a sort of a nice, clean question, because at that point, we've reached, if I want to live in a virtual reality, that means we're just a few years away, we're a majority of the population lives in a virtual reality, and that's how we create the simulation, right? You don't need to actually simulate the quantum gravity and just every aspect of the universe. And that's an interesting question for reinforcement learning too, is if we want to make sufficiently realistic simulations that may, it blend the difference between sort of the real world and the simulation, thereby just some of the things we've been talking about, kind of the problems go away, if we can create actually interesting, rich simulations. It's an interesting question. And actually, I think your question casts your previous question in a very interesting light, because in some ways, asking whether we can, well, the more kind of practical version of this, like, you know, can we build simulators that are good enough to train, essentially, AI systems that will work in the world? And it's kind of interesting to think about this, about what this implies. If true, it kind of implies that it's easier to create the universe than it is to create a brain. And that seems like, put this way, it seems kind of weird. The aspect of the simulation most interesting to me is the simulation of other humans. That seems to be a complexity that makes the robotics problem harder. Now, I don't know if every robotics person agrees with that notion. Just as a quick aside, what are your thoughts about when the human enters the picture of the robotics problem? How does that change the reinforcement learning problem, the learning problem in general? Yeah, I think that's a, it's a kind of a complex question. And I guess my hope for a while had been that if we build these robotic learning systems that that are multitask, that utilize lots of prior data, and that learn from their own experience, the bit where they have to interact with people will be perhaps handled in much the same way as all the other bits. So if they have prior experience of interacting with people, and they can learn from their own experience of interacting with people for this new task, maybe that'll be enough. Now, of course, if it's not enough, there are many other things we can do, and there's quite a bit of research in that area. But I think it's worth a shot to see whether the multi-agent interaction, the ability to understand that other beings in the world have their own goals, intentions, and thoughts, and so on, whether that kind of understanding can emerge automatically from simply learning to do things with and maximize utility. That information arises from the data. You've said something about gravity, sort of, that you don't need to explicitly inject anything into the system, they can be learned from the data. And gravity is an example of something that could be learned from data, sort of like the physics of the world. What are the limits of what we can learn from data? Do you really, do you think we can, so a very simple, clean way to ask that is, do you really think we can learn gravity from just data? The idea, the laws of gravity? So something that I think is a common kind of pitfall when thinking about prior knowledge and learning is to assume that just because we know something, that it's better to tell the machine about that rather than have it figure it out on its own. In many cases, things that are important, that affect many of the events that the machine will experience are actually pretty easy to learn. Like, if things, if every time you drop something, it falls down, like, yeah, you might not get the, you might get kind of the Newton's version, not Einstein's version, but it'll be pretty good. And it will probably be sufficient for you to act rationally in the world because you see the phenomenon all the time. So things that are readily apparent from the data, we might not need to specify those by hand. It might actually be easier to let the machine figure them out. It just feels like that there might be a space of many local, a local minima in terms of theories of this world that we would discover and get stuck on. Yeah, of course. That Newtonian mechanics is not necessarily easy to come by. Yeah, and well, in fact, in some fields of science, for example, human civilizations that sell full of these local optimums. So for example, if you think about how people try to figure out biology and medicine, you know, for the longest time, the kind of rules, the kind of principles that serve us very well in our day-to-day lives actually serve us very poorly in understanding medicine and biology. We had kind of very superstitious and weird ideas about how the body worked until the advent of the modern scientific method. So that does seem to be, you know, a failing of this approach, but it's also a failing of human intelligence, arguably. Yeah, maybe a small aside, but some, you know, the idea of self-play is fascinating in reinforcement learning, sort of these competitive, creating a competitive context in which agents can play against each other in a, sort of at the same skill level and thereby increasing each other's skill level. It seems to be this kind of self-improving mechanism is exceptionally powerful in the context where it could be applied. First of all, is that beautiful to you that this mechanism work as well as it does, and also can it be generalized to other contexts, like in the robotic space or anything that's applicable to the real world? I think that it's a very interesting idea, but I suspect that the bottleneck to actually generalizing it to the robotic setting is actually going to be the same as the bottleneck for everything else, that we need to be able to build machines that can get better and better through natural interaction with the world. And once we can do that, then they can go out and play with, they can play with each other, they can play with people, they can play with the natural environment. But before we get there, we've got all these other problems we've got, we have to get out of the way. So there's no shortcut around that, you have to interact with a natural environment that... Well, because in a self-play setting, you still need a mediating mechanism. So the reason that, you know, self-play works for a board game is because the rules of that board game mediate the interaction between the agents. So the kind of intelligent behavior that will emerge depends very heavily on the nature of that mediating mechanism. So on the side of reward functions, that's coming up with good reward functions seems to be the thing that we associate with general intelligence. Like, human beings seem to value the idea of developing our own reward functions of, you know, at arriving at meaning and so on. And yet for reinforcement learning, we often kind of specify that's the given. What's your sense of how we develop reward, you know, good reward functions? Yeah, I think that's a very complicated and very deep question. And you're completely right that classically in reinforcement learning, this question has kind of been treated as a non-issue, that you sort of treat the reward as this external thing that comes from some other bit of your biology, and you kind of don't worry about it. And I do think that that's actually, you know, a little bit of a mistake that we should worry about it. And we can approach it in a few different ways. We can approach it, for instance, by thinking of reward as a communication medium. We can say, well, how does a person communicate to a robot what its objective is? You can approach it also as a sort of more of an intrinsic motivation medium. You could say, can we write down kind of a general objective that leads to good capability? Like, for example, can you write down some objective such that even in the absence of any other task, if you maximize that objective, you'll sort of learn useful things. This is something that has sometimes been called unsupervised reinforcement learning, which I think is a really fascinating area of research, especially today. We've done a bit of work on that recently. One of the things we've studied is whether we can have some notion of unsupervised reinforcement learning by means of information theoretic quantities, like, for instance, minimizing a Bayesian measure of surprise. This is an idea that was pioneered, actually, in the computational neuroscience community by folks like Carl Friston. And we've done some work recently that shows that you can actually learn pretty interesting skills by essentially behaving in a way that allows you to make accurate predictions about the world. It seems a little circular, like do the things that will make you think about the world. But it's not the things that will lead to you getting the right answer for prediction. But you can, you know, by doing this, you can sort of discover stable niches in the world. You can discover that if you're playing Tetris, then correctly, you know, clearing the rows will let you play Tetris for longer and keep the board nice and clean, which sort of satisfies some desire for order in the world. And as a result, get some degree of leverage over your domain. So, we're exploring that pretty actively. Is there a role for a human notion of curiosity in itself being the reward, sort of discovering new things about the world? So, one of the things that I'm pretty interested in is actually whether discovering new things can actually be an emergent property of some other objective that quantifies capability. So, new things for the sake of new things, maybe it's not, maybe it might not by itself be the right answer, but perhaps we can figure out an objective for which discovering new things is actually the natural consequence. That's something we're working on right now, but I don't have a clear answer for you there yet that's still a work in progress. You mean just that it's a curious observation to see sort of creative patterns of curiosity on the way to optimize for a particular... On the way to optimize for a particular measure of capability. Is there ways to understand or anticipate unexpected, unintended consequences of particular reward functions? Sort of anticipate the kind of strategies that might be developed and try to avoid highly detrimental strategies? Yeah. So, classically, this is something that has been pretty hard in reinforcement learning because it's difficult for a designer to have good intuition about what a learning algorithm will come up with when they give it some objective. There are ways to mitigate that. One way to mitigate it is to actually define an objective that says, like, don't do weird stuff. You can actually quantify it and say just like, don't enter situations that have low probability under the distribution of states you've seen before. It turns out that that's actually one very good way to do off-policy reinforcement learning, actually. So, we can do some things like that. If we slowly venture in speaking about reward functions into greater and greater levels of intelligence, there's... I mean, Stuart Russell thinks about this, the alignment of AI systems with us humans. So, how do we ensure that AGI systems align with us humans? It's kind of a reward function question of specifying the behavior of AI systems such that their success aligns with the broader intended success interest of human beings. Do you have thoughts on this? Do you have kind of concerns of where reinforcement learning fits into this? Or are you really focused on the current moment of us being quite far away and trying to solve the robotics problem? I don't have a great answer to this, but... And I do think that this is a problem that's important to figure out. For my part, I'm actually a bit more concerned about the other side of this equation that maybe rather than unintended consequences for objectives that are specified too well, I'm actually more worried right now about unintended consequences for objectives that are not optimized well enough, which might become a very pressing problem when we, for instance, try to use these techniques for safety critical systems like cars and aircraft and so on. I think at some point we'll face the issue of objectives being optimized too well, but right now I think we're more likely to face the issue of them not being optimized well enough. But you don't think unintended consequences can arise even when you're far from optimality, sort of like on the path to it? Oh, no, I think unintended consequences can absolutely arise. It's just, I think right now, the bottleneck for improving reliability, safety, and things like that is more with systems that need to work better, that need to optimize their objective better. Do you have thoughts, concerns about existential threats of human level intelligence? If we put on our hat of looking in 10, 20, 100, 500 years from now, do you have concerns about existential threats of AI systems? I think there are absolutely existential threats for AI systems, just like there are for any powerful technology. But I think that these kinds of problems can take many forms and some of those forms will come down to people with nefarious intent. Some of them will come down to AI systems that have some fatal flaws, and some of them will, of course, come down to AI systems that are too capable in some way. But among this set of potential concerns, I would actually be much more concerned about the first two right now, and principally the one with nefarious humans, because just through all of human history, actually, it's the nefarious humans that have been the problem, not the nefarious machines, than I am about the others. And I think that right now, the best that I can do to make sure things go well is to build the best technology I can, and also hopefully promote responsible use of that technology. Do you think RL systems have something to teach us humans? You said nefarious humans getting us in trouble. I mean, machine learning systems have in some ways have revealed to us the ethical flaws in our data. In that same kind of way, can reinforcement learning teach us about ourselves? Has it taught something? What have you learned about yourself from trying to build robots and reinforcement learning systems? I'm not sure what I've learned about myself, but maybe part of the answer to your question might become a little bit more apparent once we see more widespread deployment of reinforcement learning for decision-making support in domains like healthcare, education, social media, et cetera. And I think we will see some interesting stuff emerge there. We will see, for instance, what kind of behaviors these systems come up with in situations where there is interaction with humans and where they have possibility of influencing human behavior. I think we're not quite there yet, but maybe in the next few years, we'll see some interesting stuff come out in that area. I hope outside the research space, because the exciting space where this could be observed is there are large companies that deal with large data, and I hope there's some transparency. One of the things that's unclear when I look at social networks and just online is why an algorithm did something or whether even an algorithm was involved. And that'd be interesting from a research perspective just to observe the results of algorithms to open up that data or to at least be sufficiently transparent about the behavior of these AI systems in the real world. What's your sense, I don't know if you looked at the blog post, Bit of Lesson by Rich Sutton, where it looks at sort of the big lesson of researching AI and reinforcement learning is that simple methods, general methods that leverage computation seem to work well. So basically don't try to do any kind of fancy algorithms, just wait for computation and get fast. Do you share this kind of intuition? I think the high level idea makes a lot of sense. I'm not sure that my takeaway would be that we don't need to work on algorithms. I think that my takeaway would be that we should work on general algorithms. And actually, I think that this idea of needing to better automate the acquisition of experience in the real world actually follows pretty naturally from Rich Sutton's conclusion. So if the claim is that automated general methods plus data leads to good results, then it makes sense that we should build general methods and we should build the kind of methods that we can deploy and get them to go out there and collect their experience autonomously. I think that one place where I think that the current state of things falls a little bit short of that is actually the going out there and collecting the data autonomously, which is easy to do in a simulated board game, but very hard to do in the real world. Yeah, it keeps coming back to this one problem, right? So your mind is focused there now in this real world. It just seems scary, this step of collecting the data. And it seems unclear to me how we can do it effectively. Yeah, well, you know, seven billion people in the world, each of them have to do that at some point in their lives. And we should leverage that experience that they've all done. We should be able to try to collect that kind of data. Okay, big questions. Maybe stepping back through your life, would book or books, technical or fiction or philosophical, had a big impact on the way you saw the world and the way you thought about in the world, your life in general? And maybe what books, if it's different, would you recommend people consider reading on their own intellectual journey? It could be within reinforcement learning, but it could be very much bigger. I don't know if this is like a scientifically, like, particularly meaningful answer. But like, the honest answer is that I actually found a lot of the work by Isaac Asimov to be very inspiring when I was younger. I don't know if that has anything to do with AI necessarily. You don't think it had a ripple effect in your life? Maybe it did. But yeah, I think that a vision of a future where, well, first of all, artificial, I might say artificial intelligence system, artificial robotic systems have a big place, a big role in society. And where we try to imagine the limiting case of technological advancement and how that might play out in our future history. But yeah, I think that that was in some way influential. I don't really know how, but I would recommend it. I mean, if nothing else, you'd be well entertained. When did you first, yourself, like fall in love with the idea of artificial intelligence, captivated by this field? So, my honest answer here is actually that I only really started to think about it as something that I might want to do actually in graduate school pretty late. And a big part of that was that until somewhere around 2009, 2010, it just wasn't really high on my priority list because I didn't think that it was something where we're going to see very substantial advances in my lifetime. And maybe in terms of my career, the time when I really decided I wanted to work on this was when I actually took a seminar course that was taught by Professor Andrew Ng. And at that point, I, of course, had some, had like a decent understanding of the technical things involved. But one of the things that really resonated with me was when he said in the opening lecture, something to the effect of like, well, he used to have graduate students come to him and talk about how they want to work on AI, and he would kind of chuckle and give them some math problem to deal with. But now he's actually thinking that this is an area where we might see like substantial advances in our lifetime. And that kind of got me thinking, because, you know, in some abstract sense, yeah, like you can kind of imagine that. But in a very real sense, when someone who had been working on that kind of stuff their whole career suddenly says that, yeah, like that had some effect on me. Yeah, this might be a special moment in the history of the field, that this is where we might see some interesting breakthroughs. So in the space of advice, somebody who's interested in getting started in machine learning or reinforcement learning, what advice would you give to maybe an undergraduate student or maybe even younger? How, what are the first steps to take? And further on, what are the steps to take on that journey? So something that I think is important to do is to not be afraid to like spend time imagining the kind of outcome that you might like to see. So, you know, one outcome might be a successful career, a large paycheck or something, or state of the art results on some benchmark. But hopefully, that's not the thing that's like the main driving force for somebody. But I think that if someone who's a student considering a career in AI, like takes a little while, sits down and thinks like, what do I really want to see? What I want to see a machine do? What do I want to see a robot do? What do I want to do? And what I want to see a natural language system, just like imagine, you know, imagine it almost like a commercial for a future product or something, or like something that you'd like to see in the world, and then actually sit down and think about the steps that are necessary to get there. And hopefully, that thing is not the thing that you want to see in the world, but it's a thing that you want to see in the world. And hopefully, that thing is not a better number on image net classification. It's like, it's probably like an actual thing that we can't do today, that would be really awesome, whether it's a robot butler or a, you know, a really awesome healthcare decision making support system, whatever it is that you find inspiring. And I think that thinking about that, and then backtracking from there and imagining the steps needed to get there will actually lead to much better research, it'll lead to much better work on the bottlenecks that other people aren't working on. And then naturally to turn to you, we've talked about reward functions, and you just give an advice on looking forward to how you'd like to see what kind of change you would like to make in the world. What do you think, ridiculous, big question, what do you think is the meaning of life? What is the meaning of your life? What gives you fulfillment, purpose, happiness, and meaning? That's a very big question. What's the reward function under which you are operating? Yeah, I think one thing that does give, you know, if not meaning, at least satisfaction is some degree of confidence that I'm working on a problem that really matters. I feel like it's less important to me to like, actually solve a problem, but it's quite nice to take things to spend my time on that I believe really matter. And I try pretty hard to look for that. I don't know if it's easy to answer this, but if you're successful, what does that look like? What's the big dream? Now, of course, success is built on top of success and you keep going forever, but what is the dream? Yeah, so one very concrete thing, or maybe as concrete as it's going to get here is to see machines that actually get better and better the longer they exist in the world. And that kind of seems like on the surface, one might even think that that's something that we have today, but I think we really don't. I think that there is an unending complexity in the universe. And to date, all of the machines that we've been able to build don't sort of improve up to the limit of that complexity. They hit a wall somewhere. Maybe they hit a wall because they're in a simulator that is only a very limited, very pale imitation of the real world, or they hit a wall because they rely on a labeled dataset, but they never hit the wall of like running out of stuff to see. So, you know, I'd like to build a machine that can go as far as possible in that regard. Runs up against the ceiling of the complexity of the universe. Yes. Well, I don't think there's a better way to end it, Sergey. Thank you so much. It's a huge honor. I can't wait to see the amazing work that you have to publish. And in the education space, in terms of reinforcement learning, thank you for inspiring the world. Thank you for the great research you do. Thank you. Thanks for listening to this conversation with Sergey Lavin, and thank you to our sponsors, Cash App and ExpressVPN. Please consider supporting this podcast by downloading Cash App and using code LEXPODCAST and signing up at expressvpn.com slash lexpod. Click all the links, buy all the stuff. It's the best way to support this podcast and the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with Firestarz and Apple Podcast, support on Patreon, or connect with me on Twitter at Lex Friedman, spelled somehow, if you can figure out how, without using the letter E, just F-R-I-D-M-A-N. And now let me leave you with some words from Salvador Dali. Intelligence without ambition is a bird without wings. Thank you for listening and hope to see you next time.

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Ilya Sutskever: Deep Learning | Lex Fridman Podcast #94

The following is a conversation with Ilya Sutskever, co-founder and chief scientist of OpenAI, one of the most cited computer scientists in history with over 165,000 citations, and to me one of the most brilliant and insightful minds ever in the field of deep learning. There are very few people in this world who I would rather talk to and brainstorm with about deep learning, intelligence, and life in general than Ilya, on and off the mic. This was an honor and a pleasure. This conversation was recorded before the outbreak of the pandemic. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with 5 Stars and Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend Ascent of Money as a great book on this history. Both the book and audiobook are great. Debits and credits on ledgers started around 30,000 years ago, the US dollar created over 200 years ago, and Bitcoin, the first decentralized cryptocurrency, released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to, and just might, redefine the nature of money. So again, if you get Cash App from the App Store or Google Play and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping advance robotics and STEM education for young people around the world. And now, here's my conversation with Ilya Sutskever. You were one of the three authors with Alex Kuchevsky, Jeff Hinton of the famed Alex Ned paper that is arguably the paper that marked the big catalytic moment that launched the deep learning revolution. At that time, take us back to that time, what was your intuition about neural networks, about the representational power of neural networks? And maybe you could mention how did that evolve over the next few years, up to today, over the 10 years? Yeah, I can answer that question. At some point in about 2010 or 2011, I connected two facts in my mind. Basically, the realization was this. At some point, we realized that we can train very large, I shouldn't say very, you know, they were tiny by today's standards, but large and deep neural networks, end to end with back propagation. At some point, different people obtained this result. I obtained this result. The first moment in which I realized that deep neural networks are powerful was when James Martens invented the Hessian free optimizer in 2010. And he trained a 10-layer neural network, end to end, without pre-training, from scratch. And when that happened, I thought, this is it. Because if you can train a big neural network, a big neural network can represent very complicated function. Because if you have a neural network with 10 layers, it's as though you allow the human brain to run for some number of milliseconds. Neuron firings are slow. And so in maybe 100 milliseconds, your neurons only fire 10 times. So it's also kind of like 10 layers. And in 100 milliseconds, you can perfectly recognize any object. So I thought, so I already had the idea then that we need to train a very big neural network on lots of supervised data. And then it must succeed, because we can find the best neural network. And then there's also theory that if you have more data than parameters, you won't overfit. Today, we know that actually this theory is very incomplete, and you won't overfit even if you have less data than parameters. But definitely, if you have more data than parameters, you won't overfit. So the fact that neural networks were heavily over-parameterized wasn't discouraging to you? So you were thinking about the theory that the number of parameters, the fact there's a huge number of parameters is okay, is going to be okay? I mean, there was some evidence before that it was okay-ish. But the theory was that if you had a big data set and a big neural net, it was going to work. The over-parameterization just didn't really figure much as a problem. I thought, well, with images, you're just going to add some data augmentation, and it's going to be okay. So where was any doubt coming from? The main doubt was, can we train a big... Will we have enough compute to train a big enough neural net? With backpropagation? Backpropagation, I thought, would work. The thing which wasn't clear was whether there would be enough compute to get a very convincing result. And then at some point, Alex Kirzhevsky wrote these insanely fast OODA kernels for training convolutional neural nets. And that was, bam, let's do this. Let's get an image in that, and it's going to be the greatest thing. Was most of your intuition from empirical results by you and by others? So just actually demonstrating that a piece of program can train a 10-layer neural network? Or was there some pen and paper or marker and whiteboard thinking, intuition? Because you just connected a 10-layer large neural network to the brain. So you just mentioned the brain. So in your intuition about neural networks, does the human brain come into play as an intuition builder? Definitely. I mean, you've got to be precise with these analogies between artificial neural networks and the brain. But there's no question that the brain is a huge source of intuition and inspiration for deep learning researchers since all the way from Rosenblatt in the 60s. If you look at the whole idea of a neural network is directly inspired by the brain. You had people like McCallum and Pitts who were saying, hey, you got these neurons in the brain. And hey, we recently learned about the computer and automata. Can we use some ideas from the computer and automata to design some kind of computational object that's going to be simple, computational, and kind of like the brain? And they invented the neuron. So they were inspired by it back then. Then you had the convolutional neural network from Fukushima and then later Jan Lekan who said, hey, if you limit the receptive fields of a neural network, it's going to be especially suitable for images, as it turned out to be true. So there was a very small number of examples where analogies to the brain were successful. And I thought, well, probably an artificial neuron is not that different from the brain if it's screened hard enough. So let's just assume it is and roll with it. So we're now at a time where deep learning is very successful. So let us squint less and say, let's open our eyes and say, what to you is an interesting difference between the human brain? Now, I know you're probably not an expert, neither a neuroscientist or a neurobiologist, but loosely speaking, what's the difference between the human brain and artificial neural networks that's interesting to you for the next decade or two? That's a good question to ask. What is an interesting difference between the brain and our artificial neural networks? So I feel like today, artificial neural networks, so we all agree that there are certain dimensions in which the human brain vastly outperforms our models. But I also think that there are some ways in which our artificial neural networks have a number of very important advantages over the brain. Look, looking at the advantages versus disadvantages is a good way to figure out what is the important difference. So the brain uses spikes, which may or may not be important. Yes, that's a really interesting question. Do you think it's important or not? That's one big architectural difference between artificial neural networks. It's hard to tell, but my prior is not very high and I can say why. You know, there are people who are interested in spiking neural networks. And basically what they figured out is that they need to simulate the non-spiking neural networks in spikes. And that's how they're going to make them work. If you don't simulate the non-spiking neural networks in spikes, it's not going to work because the question is why should it work? And that connects to questions around back propagation and questions around deep learning. You've got this giant neural network. Why should it work at all? Why should the learning rule work at all? It's not a self-evident question, especially if you, let's say if you were just starting in the field and you read the very early papers, you can say, Hey, people are saying, let's build neural networks. That's a great idea because the brain is a neural network. So it would be useful to build neural networks. Now let's figure out how to train them. It should be possible to train them probably, but how? And so the big idea is the cost function. That's the big idea. The cost function is a way of measuring the performance of the system according to some measure. By the way, that is a big, actually, let me think. Is that one, a difficult idea to arrive at? And how big of an idea is that? That there's a single cost function. Sorry, let me take a pause. Is supervised learning a difficult concept to come to? I don't know. All concepts are very easy in retrospect. Yeah, that's what, it seems trivial now, but I, because the reason I asked that and we'll talk about it, because is there other things, is there things that don't necessarily have a cost function, maybe have many cost functions, or maybe have dynamic cost functions, or maybe a totally different kind of architectures? Because we have to think like that in order to arrive at something new, right? So the only, so the good examples of things which don't have clear cost functions are GANs. In a GAN you have a game. So instead of thinking of a cost function, where you want to optimize, where you know that you have an algorithm gradient descent, which will optimize the cost function. And then you can reason about the behavior of your system in terms of what it optimizes. With a GAN you say, I have a game and I'll reason about the behavior of the system in terms of the equilibrium of the game. But it's all about coming up with these mathematical objects that help us reason about the behavior of our system. Right, that's really interesting. Yeah, so GAN is the only one, it's kind of a, the cost function is emergent from the comparison. It's, I don't know if it has a cost function. I don't know if it's meaningful to talk about the cost function of a GAN. It's kind of like the cost function of biological evolution, or the cost function of the economy. It's, you can talk about regions to which it will go towards, but I don't think, I don't think the cost function analogy is the most useful. So evolution doesn't, that's really interesting. So if evolution doesn't really have a cost function, like a cost function based on its, something akin to our mathematical conception of a cost function, then do you think cost functions in deep learning are holding us back? Yeah, so you just kind of mentioned that cost function is a nice first profound idea. Do you think that's a good idea? Do you think it's an idea we'll go past? So self-play starts to touch on that a little bit in reinforcement learning systems. That's right. Self-play and also ideas around exploration, where you're trying to take action that surprise a predictor. I'm a big fan of cost functions. I think cost functions are great and they serve us really well. And I think that whenever we can do things with cost functions, we should. And you know, maybe there is a chance that we will come up with some yet another profound way of looking at things that will involve cost functions in a less central way. But I don't know. I think cost functions are, I mean, I would not bet against cost functions. Is there other things about the brain that pop into your mind that might be different and interesting for us to consider in designing artificial neural networks? So we talked about spiking a little bit. I mean, one thing which may potentially be useful, I think people, neuroscientists have figured out something about the learning rule of the brain, or I'm talking about spike time independent plasticity, and it would be nice if some people would just study that in simulation. Wait, sorry, spike time independent plasticity? Yeah, that's right. What's that? STD. It's a particular learning rule that uses spike timing to figure out how to, to determine how to update the synapses. So it's kind of like if the synapse fires into the neuron before the neuron fires, then it's strengthen the synapse. And if the synapse fires into the neurons shortly after the neuron fired, then it weakens the synapse. Something along this line. I'm 90% sure it's right, so if I said something wrong here, don't, don't get too angry. But you sound brilliant while saying it. But the timing, that's one thing that's missing. The temporal dynamics is not captured. I think that's like a fundamental property of the brain, is the timing of the signals. Well, your recurrent neural networks. But you think of that as this, I mean, that's a very crude, simplified, what's that called? There's a clock, I guess, to recurrent neural networks. It's, this, this seems like the brain is the general, the continuous version of that, the generalization where all possible timings are possible, and then within those timings is contained some information. You think recurrent neural networks, the recurrence in recurrent neural networks can capture the same kind of phenomena as the timing that seems to be important for the brain, in the firing of neurons in the brain? I, I mean, I think, I think recurrent neural networks are amazing, and they can do, I think they can do anything we'd want them to, we'd want a system to do. Right now, recurrent neural networks have been superseded by transformers, but maybe one day they'll make a comeback, maybe they'll be back, we'll see. Let me, on a small tangent, say, do you think they'll be back? So, so much of the breakthroughs recently that we'll talk about on natural language processing and language modeling has been with transformers that don't emphasize recurrence. Do you think recurrence will make a comeback? Well, some kind of recurrence, I think, very likely. Recurrent neural networks for process, as they're typically thought of for processing sequences, I think it's also possible. What is, to you, a recurrent neural network? And generally speaking, I guess, what is a recurrent neural network? You have a neural network which maintains a high-dimensional hidden state, and then when an observation arrives, it updates its high-dimensional hidden state through its connections in some way. So do you think, you know, that's what like expert systems did, right? Symbolic AI, the knowledge-based, growing a knowledge base is maintaining a hidden state, which is its knowledge base, and is growing it by sequentially processing. Do you think of it more generally in that way, or is it simply, is it the more constrained form of a hidden state with certain kind of gating units that we think of as today with LSTMs and that? I mean, the hidden state is technically what you described there, the hidden state that goes inside the LSTM or the RNN or something like this. But then what should be contained, you know, if you want to make the expert system analogy, I'm not... I mean, you could say that the knowledge is stored in the connections, and then the short-term processing is done in the hidden state. Yes. Could you say that? Yes. So sort of, do you think there's a future of building large-scale knowledge bases within the neural networks? Definitely. So we're going to pause on that confidence, because I want to explore that. Well, let me zoom back out and ask, back to the history of ImageNet, neural networks have been around for many decades, as you mentioned. What do you think were the key ideas that led to their success, that ImageNet moment and beyond, the success in the past 10 years? Okay, so the question is, to make sure I didn't miss anything, the key ideas that led to the success of deep learning over the past 10 years. Exactly. Even though the fundamental thing behind deep learning has been around for much longer. So the key idea about deep learning, or rather, the key fact about deep learning before deep learning started to be successful, is that it was underestimated. People who worked in machine learning simply didn't think that neural networks could do much. People didn't believe that large neural networks could be trained. People thought that, well, there was a lot of debate going on in machine learning about what are the right methods and so on. And people were arguing because there was no way to get hard facts. And by that I mean, there were no benchmarks which were truly hard, that if you do really well on them, then you can say, look, here's my system. That's when you switch from... That's when this field becomes a little bit more of an engineering field. So in terms of deep learning, to answer the question directly, the ideas were all there. The thing that was missing was a lot of supervised data and a lot of compute. Once you have a lot of supervised data and a lot of compute, then there is a third thing which is needed as well, and that is conviction. Conviction that if you take the right stuff, which already exists, and apply and mix it with a lot of data and a lot of compute, that it will in fact work. And so that was the missing piece. It was, you had the... You needed the data, you needed the compute, which showed up in terms of GPUs, and you needed the conviction to realize that you need to mix them together. So that's really interesting. So I guess the presence of compute and the presence of supervised data allowed the empirical evidence to do the convincing of the majority of the computer science community. So I guess there's a key moment with Jitendra Malik and Alex, Alyosha Efros, who were very skeptical, right? And then there's Jeffrey Hinton that was the opposite of skeptical. And there was a convincing moment, and I think ImageNet served as that moment. And they represented this kind of, or the big pillars of computer vision community, kind of the wizards got together, and then all of a sudden there was a shift. And it's not enough for the ideas to all be there and the compute to be there, it's for it to convince the cynicism that existed. That's interesting, that people just didn't believe for a couple of decades. Yeah, well, but it's more than that. It's kind of, when put this way, it sounds like, well, you know, those silly people who didn't believe what were they missing. But in reality, things were confusing because neural networks really did not work on anything. And they were not the best method on pretty much anything as well. And it was pretty rational to say, yeah, this stuff doesn't have any traction. And that's why you need to have these very hard tasks, which produce undeniable evidence. And that's how we make progress. And that's why the field is making progress today, because we have these hard benchmarks, which represent true progress. And this is why we are able to avoid endless debate. So incredibly, you've contributed some of the biggest recent ideas in AI, in computer vision, language, natural language processing, reinforcement learning, sort of everything in between. Maybe not GANs. There may not be a topic you haven't touched. And of course, the fundamental science of deep learning. What is the difference to you between vision, language, and as in reinforcement learning, action, as learning problems? And what are the commonalities? Do you see them as all interconnected? Are they fundamentally different domains that require different approaches? Okay, that's a good question. Machine learning is a field with a lot of unity, a huge amount of unity. In fact- What do you mean by unity? Like overlap of ideas? Overlap of ideas, overlap of principles. In fact, there's only one or two or three principles, which are very, very simple. And then they apply in almost the same way, in almost the same way to the different modalities, to the different problems. And that's why today, when someone writes a paper on improving optimization of deep learning and vision, it improves the different NLP applications and it improves the different reinforcement learning applications. Reinforcement learning- So I would say that computer vision and NLP are very similar to each other. Today, they differ in that they have slightly different architectures. We use transformers in NLP and we use convolutional neural networks in vision. But it's also possible that one day this will change and everything will be unified with a single architecture. Because if you go back a few years ago in natural language processing, there were a huge number of architectures for every different tiny problem had its own architecture. Today, there's just one transformer for all those different tasks. And if you go back in time even more, you had even more and more fragmentation and every little problem in AI had its own little subspecialization and sub- little set of collection of skills, people who would know how to engineer the features. Now it's all been subsumed by deep learning. We have this unification. And so I expect vision to become unified with natural language as well. Or rather, I shouldn't say expect. I think it's possible. I don't want to be too sure because I think on the convolutional neural net, it's very computationally efficient. RL is different. RL does require slightly different techniques because you really do need to take action. You really do need to do something about exploration. Your variance is much higher. But I think there is a lot of unity even there. And I would expect, for example, that at some point there will be some broader unification between RL and supervised learning, where somehow the RL will be making decisions to make the supervised learning go better. And there will be, I imagine, one big black box and you just throw every- you know, you shovel things into it and it just figures out what to do with whatever you shovel in it. I mean, reinforcement learning has some aspects of language and vision combined almost. There's elements of a long-term memory that you should be utilizing and there's elements of a really rich sensory space. So it seems like the- it's like the union of the two or something like that. I'd say something slightly differently. I'd say that reinforcement learning is neither, but it naturally interfaces and integrates with the two of them. You think action is fundamentally different? So yeah, what is interesting about- what is unique about policy of learning to act? Well, so one example, for instance, is that when you learn to act, you are fundamentally in a non-stationary world, because as your actions change, the things you see start changing. You experience the world in a different way. And this is not the case for the more traditional static problem where you have some distribution and you just apply a model to that distribution. You think it's a fundamentally different problem or is it just a more difficult general- it's a generalization of the problem of understanding? I mean, it's a question of definitions almost. There is a huge- I mean, no, there's a huge amount of commonality for sure. You take gradients, you try- you take gradients, you try to approximate gradients in both cases. In the case of reinforcement learning, you have some tools to reduce the variance of the gradients. You do that. There's lots of commonality. You use the same neural net in both cases. You compute the gradient, you apply Adam in both cases. So, I mean, there's lots in common for sure, but there are some small differences which are not completely insignificant. It's really just a matter of your point of view, what frame of reference you- how much do you want to zoom in or out as you look at these problems. Which problem do you think is harder? So people like Noam Chomsky believe that language is fundamental to everything. So it underlies everything. Do you think language understanding is harder than visual scene understanding or vice versa? I think that asking if a problem is hard is slightly wrong. I think the question is a little bit wrong and I want to explain why. So what does it mean for a problem to be hard? Okay, the non-interesting, dumb answer to that is there's a benchmark and there's a human level performance on that benchmark. And how is the effort required to reach the human level benchmark? So from the perspective of how much until we get to human level on a very good benchmark? Yeah, I understand what you mean by that. So what I was going to say that a lot of it depends on, you know, once you solve a problem, it stops being hard. And that's always true. And so, but if something is hard or not depends on what our tools can do today. So, you know, say today, true human level, language understanding and visual perception are hard in the sense that there is no way of solving the problem completely in the next three months. Right? So I agree with that statement. Beyond that, I'm just, I'd be, my guess would be as good as yours. I don't know. Oh, okay. So you don't have a fundamental intuition about how hard language understanding is? I think I know I changed my mind. I'd say language is probably going to be harder. I mean, it depends on how you define it. Like if you mean absolute top notch, 100% language understanding, I'll go with language. But then if I show you a piece of paper with letters on it, is that, you see what I mean? So you have a vision system, you say it's the best human level vision system. I show you, I open a book and I show you letters. Will it understand the language? Will it understand the language? Will it understand how these letters form into word and sentences and meaning? Is this part of the vision problem? Where does vision end and language begin? Yeah. So Chomsky would say it starts at language. So vision is just a little example of the kind of structure and, you know, fundamental hierarchy of ideas that's already represented in our brain somehow that's represented in language. But where does vision stop and language begin? That's a really interesting question. So one possibility is that it's impossible to achieve really deep understanding in either images or language without basically using the same kind of system. So you're going to get the library. I think it's pretty likely that, yes, if we can get one, our machine learning is probably that good that we can get the other. But it's not one hundred percent sure. And also I think a lot of it really does depend on your definitions. Definitions of? Of like perfect vision. Because reading is vision, but should it count? Yeah, to me, so my definition is if a system looked at an image and then a system looked at a piece of text and then told me something about that and I was really impressed. That's relative. You'll be impressed for half an hour and then you're gonna say, well, I mean, all the systems do that, but here's the thing they don't do. Yeah, but I don't have that with humans. Humans continue to impress me. Is that true? Well, the ones, okay, so I'm a fan of monogamy, so I like the idea of marrying somebody, being with them for several decades. So I believe in the fact that, yes, it's possible to have somebody continuously giving you pleasurable, interesting, witty, new ideas, friends, yeah. I think so, they continue to surprise you. The surprise, it's, you know, that injection of randomness seems to be a nice source of, yeah, continued inspiration, like the wit, the humor. I think, yeah, that would be, it's a very subjective test, but I think if you have enough humans in the room. Yeah, I understand what you mean. Yeah, I feel like I misunderstood what you meant by impressing you. I thought you meant to impress you with its intelligence, with how well it understands an image. I thought you meant something like, I'm gonna show it a really complicated image and it's gonna get it right, and you're gonna say, wow, that's really cool, a systems of, you know, January 2020 have not been doing that. Yeah, no, I think it all boils down to, like, the reason people click like on stuff on the internet, which is like, it makes them laugh. So it's like humor or wit or insight. I'm sure we'll get that as well. So forgive the romanticized question, but looking back to you, what is the most beautiful or surprising idea in deep learning, or AI in general, you've come across? So I think the most beautiful thing about deep learning is that it actually works. And I mean it, because you got these ideas, you got the little neural network, you got the back propagation algorithm, and then you got some theories as to, you know, this is kind of like the brain, so maybe if you make it large, if you make the neural network large and you train it on a lot of data, then it will do the same function that the brain does. And it turns out to be true, that's crazy. And now we just train these neural networks and you make them larger and they keep getting better. And I find it unbelievable. I find it unbelievable that this whole AI stuff with neural networks works. Have you built up an intuition of why? Are there little bits and pieces of intuitions, of insights of why this whole thing works? I mean, some, definitely. While we know that optimization, we now have good, you know, we've had lots of empirical, huge amounts of empirical reasons to believe that optimization should work on most problems we care about. Do you have insights of why? So you just said empirical evidence. Is most of your, sort of empirical evidence kind of convinces you, it's like evolution is empirical, it shows you that, look, this evolutionary process seems to be a good way to design organisms that survive in their environment. But it doesn't really get you to the insights of how the whole thing works. I think it's, a good analogy is physics. You know how you say, hey, let's do some physics calculation and come up with some new physics theory and make some prediction. But then you got around the experiment. You know, you got around the experiment, it's important. So it's a bit the same here, except that maybe sometimes the experiment came before the theory, but it still is the case. You know, you have some data and you come up with some prediction. You say, yeah, let's make a big neural network, let's train it, and it's going to work much better than anything before it. And it will in fact continue to get better as you make it larger. And it turns out to be true. That's amazing when a theory is validated like this. You know, it's not a mathematical theory, it's more of a biological theory almost. So I think there are not terrible analogies between deep learning and biology. I would say it's like the geometric mean of biology and physics, that's deep learning. The geometric mean of biology and physics. I think I'm gonna need a few hours to wrap my head around that. Because just to find the geometric, just to find the set of what biology represents. Well, in biology things are really complicated. The theories are really, really, it's really hard to have good predictive theory. And in physics, the theories are too good. In physics, people make these super precise theories which make these amazing predictions. And in machine learning, we're kind of in between. Kind of in between, but it'd be nice if machine learning somehow helped us discover the unification of the two, as opposed to sort of the in between. But you're right, you're kind of trying to juggle both. So do you think there are still beautiful and mysterious properties in neural networks that are yet to be discovered? Definitely. I think that we are still massively underestimating deep learning. What do you think it'll look like? Like what, if I knew I would have done it, yeah? So, but if you look at all the progress from the past 10 years, I would say most of it, I would say there've been a few cases where some, where things that felt like really new ideas showed up. But by and large, it was every year we thought, okay, deep learning goes this far. Nope, it actually goes further. And then the next year, okay, now, now this is big deep learning. We are really done. Nope, it goes further. It just keeps going further each year. So that means that we keep underestimating, we keep not understanding it. It has surprising properties all the time. Do you think it's getting harder and harder to make progress? Need to make progress? It depends on what you mean. I think the field will continue to make very robust progress for quite a while. I think for individual researchers, especially people who are doing research, it can be harder because there is a very large number of researchers right now. I think that if you have a lot of compute, then you can make a lot of very interesting discoveries, but then you have to deal with the challenge of managing a huge compute cluster to run your experiments. It's a little bit harder. So I'm asking all these questions that nobody knows the answer to, but you're one of the smartest people I know, so I'm gonna keep asking. So let's imagine all the breakthroughs that happen in the next 30 years in deep learning. Do you think most of those breakthroughs can be done by one person with one computer? Sort of in the space of breakthroughs, do you think compute and large efforts will be necessary? I mean, I can't be sure. When you say one computer, you mean how large? You're clever. I mean, one GPU. I see. I think it's pretty unlikely. I think it's pretty unlikely. I think that there are many... The stack of deep learning is starting to be quite deep. If you look at it, you've got all the way from the ideas, the systems to build the datasets, the distributed programming, the building the actual cluster, the GPU programming, putting it all together. So the stack is getting really deep, and I think it can be quite hard for a single person to be world-class in every single layer of the stack. What about what Vladimir Vapnik really insists on is taking MNIST and trying to learn from very few examples. So being able to learn more efficiently. Do you think there'll be breakthroughs in that space that may not need a huge compute? I think there will be a large number of breakthroughs in general that will not need a huge amount of compute. So maybe I should clarify that. I think that some breakthroughs will require a lot of compute. And I think building systems which actually do things will require a huge amount of compute. That one is pretty obvious. If you want to do X, and X requires a huge neural net, you gotta get a huge neural net. But I think there will be lots of... I think there is lots of room for very important work being done by small groups and individuals. Can you maybe sort of on the topic of the science of deep learning, talk about one of the recent papers that you released, Deep Double Descent, where bigger models and more data hurt. I think it's a really interesting paper. Can you describe the main idea? Yeah, definitely. So what happened is that over the years, some small number of researchers noticed that it is kind of weird that when you make the neural network larger, it works better, and it seems to go in contradiction with statistical ideas. And then some people made an analysis showing that actually you got this double descent bump. And what we've done was to show that double descent occurs for pretty much all practical deep learning systems. And that it'll be also... So can you step back? What's the X axis and the Y axis of a double descent plot? Okay, great. So you can look, you can do things like, you can take a neural network, and you can start increasing its size slowly while keeping your dataset fixed. So if you increase the size of the neural network slowly, and if you don't do early stopping, that's a pretty important detail, then when the neural network is really small, you make it larger, you get a very rapid increase in performance. Then you continue to make it larger, and at some point performance will get worse, and it gets the worst exactly at the point at which it achieves zero training error, precisely zero training loss. And then as you make it larger, it starts to get better again. And it's kind of counterintuitive because you'd expect deep learning phenomena to be monotonic. And it's hard to be sure what it means, but it also occurs in the case of linear classifiers, and the intuition basically boils down to the following. When you have a large dataset and a small model, then small, tiny, random... So basically what is overfitting? Overfitting is when your model is somehow very sensitive to the small, random, unimportant stuff in your dataset. In the training dataset. In the training dataset, precisely. So if you have a small model and you have a big dataset, and there may be some random thing, some training cases are randomly in the dataset and others may not be there, but the small model is kind of insensitive to this randomness because it's the same, there is pretty much no uncertainty about the model when the dataset is large. So, okay, so at the very basic level, to me, it is the most surprising thing that neural networks don't overfit every time, very quickly, before ever being able to learn anything. There are a huge number of parameters. So here is, so there is one way, okay, so maybe, so let me try to give the explanation and maybe that will be, that will work. So you've got a huge neural network. Let's suppose you've got a, you have a huge neural network, you have a huge number of parameters, and now let's pretend everything is linear, which is not, let's just pretend. Then there is this big subspace where your neural network achieves zero error. And SGD is going to find approximately the point, that's right, approximately the point with the smallest norm in that subspace. Okay. And that can also be proven to be insensitive to the small randomness in the data when the dimensionality is high. But when the dimensionality of the data is equal to the dimensionality of the model, then there is a one-to-one correspondence between all the datasets and the models. So small changes in the dataset actually lead to large changes in the model, and that's why performance gets worse. So this is the best explanation, more or less. So then it would be good for the model to have more parameters, so to be bigger than the data. That's right, but only if you don't early stop. If you introduce early stop in your regularization, you can make the double descent bump almost completely disappear. What is early stop? Early stopping is when you train your model and you monitor your validation performance. And then if at some point validation performance starts to get worse, you say, okay, let's stop training. We are good, we are good, we are good enough. So the magic happens after that moment, so you don't want to do the early stopping. Well, if you don't do the early stopping, you get the very pronounced double descent. Do you have any intuition why this happens? Double descent? Oh, sorry, early stopping? No, the double descent. Well, yeah, so I try, let's see. The intuition is basically, is this, that when the dataset has as many degrees of freedom as the model, then there is a one-to-one correspondence between them. And so small changes to the dataset lead to noticeable changes in the model. So your model is very sensitive to all the randomness. It is unable to discard it. Whereas it turns out that when you have a lot more data than parameters, or a lot more parameters than data, the resulting solution will be insensitive to small changes in the dataset. Oh, so it's able to, let's nicely put, discard the small changes, the randomness. The randomness, exactly. The spurious correlation, which you don't want. Jeff Hinton suggested we need to throw back propagation. We already kind of talked about this a little bit, but he suggested that we need to throw away back propagation and start over. I mean, of course, some of that is a little bit wit and humor, but what do you think, what could be an alternative method of training neural networks? Well, the thing that he said precisely is that to the extent that you can't find back propagation in the brain, it's worth seeing if we can learn something from how the brain learns. But back propagation is very useful and we should keep using it. Oh, you're saying that once we discover the mechanism of learning in the brain or any aspects of that mechanism, we should also try to implement that in neural networks? If it turns out that we can't find back propagation in the brain. If we can't find back propagation in the brain. Well, so I guess your answer to that is back propagation is pretty damn useful. So why are we complaining? I mean, I personally am a big fan of back propagation. I think it's a great algorithm because it solves an extremely fundamental problem, which is that we can't find back propagation in the brain. It's a very fundamental problem, which is finding a neural circuit subject to some constraints. I don't see that problem going away. So that's why I really, I think it's pretty unlikely that we'll have anything which is going to be dramatically different. It could happen, but I wouldn't bet on it right now. So let me ask a sort of big picture question. Do you think neural networks can be made to reason? Why not? Well, if you look, for example, at AlphaGo or AlphaZero, the neural network of AlphaZero plays Go, which we all agree is a game that requires reasoning, better than 99.9% of all humans. Just the neural network, without the search, just the neural network itself. Doesn't that give us an existence proof that neural networks can reason? To push back and disagree a little bit, we all agree that Go is reasoning. I think I agree. I don't think it's a trivial. So obviously, reasoning, like intelligence, is a loose, gray area term, a little bit. Maybe you disagree with that. But yes, I think it has some of the same elements of reasoning. Reasoning is almost akin to search, right? There's a sequential element of stepwise consideration of possibilities and sort of building on top of those possibilities in a sequential manner until you arrive at some insight. So yeah, I guess playing Go is kind of like that. And when you have a single neural network doing that without search, it's kind of like that. So there's an existence proof in a particular constrained environment that a process akin to what many people call reasoning exists but more general kind of reasoning. So off the board. There is one other existence proof. Oh boy, which one? Us humans? Yes. Okay. All right, so do you think the architecture that will allow neural networks to reason will look similar to the neural network architectures we have today? I think it will. I think, well, I don't wanna make too overly definitive statements. I think it's definitely possible that the neural networks that will produce the reasoning breakthroughs of the future will be very similar to the architectures that exist today. Maybe a little bit more recurrent, maybe a little bit deeper. But these neural nets are so insanely powerful. Why wouldn't they be able to learn to reason? Humans can reason, so why can't neural networks? So do you think the kind of stuff we've seen neural networks do is a kind of just weak reasoning? So it's not a fundamentally different process? Again, this is stuff nobody knows the answer to. So when it comes to our neural networks, the thing which I would say is that neural networks are capable of reasoning. But if you train a neural network on a task which doesn't require reasoning, it's not going to reason. This is a well-known effect where the neural network will solve exactly the, it will solve the problem that you pose in front of it in the easiest way possible. Right, that takes us to the, to one of the brilliant sort of ways you've described neural networks, which is you've referred to neural networks as the search for small circuits, and maybe general intelligence as the search for small programs, which I found as a metaphor very compelling. Can you elaborate on that difference? Yeah, so the thing which I said precisely was that if you can find the shortest program that outputs the data at your disposal, then you will be able to use it to make the best prediction possible. And that's a theoretical statement which can be proved mathematically. Now, you can also prove mathematically that it is, that finding the shortest program which generates some data is not a computable operation. No finite amount of compute can do this. So then with neural networks, neural networks are the next best thing that actually works in practice. We are not able to find the best, the shortest program which generates our data, but we are able to find, you know, a small, but now that statement should be amended, even a large circuit which fits our data in some way. Well, I think what you meant by the small circuit is the smallest needed circuit. Well, the thing which I would change now, back then I really haven't fully internalized the over-parameterized results. The things we know about over-parameterized neural nets, now I would phrase it as a large circuit whose weights contain a small amount of information, which I think is what's going on. If you imagine the training process of a neural network as you slowly transmit entropy from the data set to the parameters, then somehow the amount of information in the weights ends up being not very large, which would explain why they generalize so well. So that's, the large circuit might be one that's helpful for the generalization. Yeah, something like this. But do you see it important to be able to try to learn something like programs? I mean, if we can, definitely. I think it's kind of, the answer is kind of yes, if we can do it, we should do things that we can do it. It's the reason we are pushing on deep learning, the fundamental reason, the root cause is that we are able to train them. So in other words, training comes first. We've got our pillar, which is the training pillar. And now we are trying to contort our neural networks around the training pillar. We gotta stay trainable. This is an invariant we cannot violate. And so being trainable means starting from scratch, knowing nothing, you can actually pretty quickly converge towards knowing a lot, or even slowly. But it means that given the resources at your disposal, you can train the neural net and get it to achieve useful performance. Yeah, that's a pillar we can't move away from. That's right, because if you can, and whereas if you say, hey, let's find the shortest program, well, we can't do that. So it doesn't matter how useful that would be, we can't do it, so we won't. So do you think, you kind of mentioned that the neural networks are good at finding small circuits or large circuits. Do you think then the matter of finding small programs is just the data? No. So, sorry, not the size or character, the type of data. Sort of ask giving it programs. Well, I think the thing is that right now, finding, there are no good precedents of people successfully finding programs really well. And so the way you'd find programs is you'd train a deep neural network to do it basically. Right. Which is the right way to go about it. But there's not good illustrations of that. It hasn't been done yet, but in principle, it should be possible. Can you elaborate a little bit? What's your insight in principle? Put another way, you don't see why it's not possible. Well, it's kind of like more, it's more a statement of, I think that it's unwise to bet against deep learning. And if it's a cognitive function that humans seem to be able to do, then it doesn't take too long for some deep neural net to pop up that can do it too. Yeah, I'm there with you. I've stopped betting against neural networks at this point because they continue to surprise us. What about long-term memory? Can neural networks have long-term memory or something like knowledge basis? So being able to aggregate important information over long periods of time that would then serve as useful sort of representations of state that you can make decisions by. So have a long-term context based on what you make in the decision. So in some sense, the parameters already do that. The parameters are an aggregation of the day of the neural, of the entirety of the neural experience. And so they count as long-term knowledge. And people have trained various neural nets to act as knowledge basis and, you know, investigated with people have investigated language models as knowledge basis. So there is work there. Yeah, but in some sense, do you think in every sense, do you think there's a, it's all just a matter of coming up with a better mechanism of forgetting the useless stuff and remembering the useful stuff? Because right now, I mean, there's not been mechanisms that do remember really long-term information. What do you mean by that precisely? Precisely, I like the word precisely. So I'm thinking of the kind of compression of information the knowledge bases represent, sort of creating a, now I apologize for my sort of human-centric thinking about what knowledge is, because neural networks aren't interpretable necessarily with the kind of knowledge they have discovered. But a good example for me is knowledge bases, being able to build up over time something like the knowledge that Wikipedia represents. It's a really compressed, structured knowledge base. Obviously not the actual Wikipedia or the language, but like a semantic web, the dream that semantic web represented. So it's a really nice compressed knowledge base, or something akin to that in a non-interpretable sense as neural networks would have. Well, the neural networks would be non-interpretable if you look at their rates, but their outputs should be very interpretable. Okay, so how do you make very smart neural networks, like language models, interpretable? Well, you ask them to generate some text, and the text will generally be interpretable. Do you find that the epitome of interpretability, like can you do better? Because you can't, okay, I would like to know what does it know and what doesn't it know? I would like the neural network to come up with examples where it's completely dumb, and examples where it's completely brilliant. And the only way I know how to do that now is to generate a lot of examples and use my human judgment. But it would be nice if a neural network had some self-awareness about it. Yeah, 100%. I'm a big believer in self-awareness, and I think neural net self-awareness will allow for things like the capabilities, like the ones you described, like for them to know what they know and what they don't know, and for them to know where to invest to increase their skills most optimally. And to your question of interpretability, there are actually two answers to that question. One answer is, you know, we have the neural net so we can analyze the neurons, and we can try to understand what the different neurons and different layers mean. And you can actually do that, and OpenAI has done some work on that. But there is a different answer, which is that, I would say, that's the human-centric answer, where you say, you know, you look at a human being, you can't read, you know, how do you know what a human being is thinking? You ask them, you say, hey, what do you think about this? What do you think about that? And you get some answers. The answers you get are sticky, in the sense you already have a mental model. You already have an, yeah, a mental model of that human being. You already have an understanding of, like a big conception of what it, of that human being, how they think, how what they know, how they see the world, and then everything you ask, you're adding onto that. And that stickiness seems to be, that's one of the really interesting qualities of the human being, is that information is sticky. You don't, you seem to remember the useful stuff, aggregate it well, and forget most of the information that's not useful. That process, but that's also pretty similar to the process that neural networks do. It's just that neural networks are much crappier at this time. It doesn't seem to be fundamentally that different. But just to stick on reasoning for a little longer, you said, why not? Why can't I reason? What's a good, impressive feat, benchmark to you of reasoning that you'll be impressed by if neural networks were able to do? Is that something you already have in mind? Well, I think writing really good code. I think proving really hard theorems. Solving open-ended problems with out-of-the-box solutions. And sort of theorem-type mathematical problems. Yeah, I think those ones are a very natural example as well. If you can prove an unproven theorem, then it's hard to argue, don't reason. And so by the way, and this comes back to the point about the hard results. If you have machine learning, deep learning as a field is very fortunate because we have the ability to sometimes produce these unambiguous results. And when they happen, the debate changes, the conversation changes. We have the ability to produce conversation-changing results. Conversation, and then of course, just like you said, people kind of take that for granted, say that wasn't actually a hard problem. Well, I mean, at some point, we'll probably run out of hard problems. Yeah, that whole mortality thing is kind of a sticky problem that we haven't quite figured out. Maybe we'll solve that one. I think one of the fascinating things in your entire body of work, but also the work at OpenAI recently, one of the conversation changers has been in the world of language models. Can you briefly kind of try to describe the recent history of using neural networks in the domain of language and text? Well, there's been lots of history. I think the Elman network was a small, tiny recurrent neural network applied to language back in the 80s. So the history is really fairly long, at least. And the thing that started, the thing that changed the trajectory of neural networks and language is the thing that changed the trajectory of all deep learning, and that's data and compute. So suddenly you move from small language models, which learn a little bit, and with language models in particular, there's a very clear explanation for why they need to be large to be good, because they're trying to predict the next word. So when you don't know anything, you'll notice very, very broad strokes, surface level patterns, like sometimes there are characters and there is a space between those characters. You'll notice this pattern. And you'll notice that sometimes there is a comma and then the next character is a capital letter. You'll notice that pattern. Eventually you may start to notice that there are certain words occur often. You may notice that spellings are a thing. You may notice syntax. And when you get really good at all these, you start to notice the semantics. You start to notice the facts. But for that to happen, the language model needs to be larger. So that's, let's linger on that, because that's where you and Noam Chomsky disagree. So you think we're actually taking incremental steps, a sort of larger network, larger compute, we'll be able to get to the semantics, to be able to understand language without what Noam likes to sort of think of as a fundamental understandings of the structure of language, like imposing your theory of language onto the learning mechanism. So you're saying the learning, you can learn from raw data, the mechanism that underlies language. Well, I think it's pretty likely. But I also want to say that I don't really know precisely what Chomsky means when he talks about, you said something about imposing your structure on language. I'm not 100% sure what he means, but empirically, it seems that when you inspect those larger language models, they exhibit signs of understanding the semantics, whereas the smaller language models do not. We've seen that a few years ago when we did work on the sentiment neuron. We trained a small, you know, smallish LSTM to predict the next character in Amazon reviews. And we noticed that when you increase the size of the LSTM from 500 LSTM cells to 4,000 LSTM cells, then one of the neurons starts to represent the sentiment of the article, of, sorry, of the review. Now, why is that? Sentiment is a pretty semantic attribute. It's not a syntactic attribute. And for people who might not know, I don't know if that's a standard term, but sentiment is whether it's a positive or a negative review. That's right. Like, is the person happy with something or is the person unhappy with something? And so here we had very clear evidence that a small neural net does not capture sentiment while a large neural net does. And why is that? Well, our theory is that at some point you run out of syntax to models, you start to gotta focus on something else. And with size, you quickly run out of syntax to model, and then you really start to focus on the semantics is would be the idea. That's right. And so I don't wanna imply that our models have complete semantic understanding because that's not true, but they definitely are showing signs of semantic understanding, partial semantic understanding, but the smaller models do not show that those signs. Can you take a step back and say, what is GPT-2, which is one of the big language models that was the conversation changer in the past couple of years? Yeah, so GPT-2 is a transformer with one and a half billion parameters that was trained on about 40 billion tokens of text, which were obtained from web pages that were linked to from Reddit articles with more than three upvotes. And what's a transformer? The transformer, it's the most important advance in neural network architectures in recent history. What is attention maybe too? Because I think that's an interesting idea, not necessarily sort of technically speaking, but the idea of attention versus maybe what recurrent neural networks represent. Yeah, so the thing is the transformer is a combination of multiple ideas simultaneously of which attention is one. Do you think attention is the key? No, it's a key, but it's not the key. The transformer is successful because it is the simultaneous combination of multiple ideas. And if you were to remove either idea, it would be much less successful. So the transformer uses a lot of attention, but attention existed for a few years. So that can't be the main innovation. The transformer is designed in such a way that it runs really fast on the GPU. And that makes a huge amount of difference. This is one thing. The second thing is that transformer is not recurrent. And that is really important too, because it is more shallow and therefore much easier to optimize. So in other words, it uses attention. It is a really great fit to the GPU and it is not recurrent. So therefore less deep and easier to optimize. And the combination of those factors make it successful. So now it makes great use of your GPU. It allows you to achieve better results for the same amount of compute. And that's why it's successful. Were you surprised how well transformers worked and GPT-2 worked? So you worked on language. You've had a lot of great ideas before transformers came about in language. So you got to see the whole set of revolutions before and after. Were you surprised? Yeah, a little. A little? Yeah. I mean, it's hard to remember because you adapt really quickly, but it definitely was surprising. It definitely was. In fact, you know what? I'll retract my statement. It was pretty amazing. It was just amazing to see generate this text of this. And you know, you got to keep in mind that at that time we've seen all this progress in GANs in improving the samples produced by GANs were just amazing. You have these realistic faces, but text hasn't really moved that much. And suddenly we moved from, you know, whatever GANs were in 2015 to the best, most amazing GANs in one step. And that was really stunning. Even though theory predicted, yeah, you train a big language model, of course you should get this. But then to see it with your own eyes, it's something else. And yet we adapt really quickly and now there's a sort of some cognitive scientists write articles saying that GPT-2 models don't truly understand language. So we adapt quickly to how amazing the fact that they're able to model the language so well is. So what do you think is the bar? For what? For impressing us that it. I don't know. Do you think that bar will continuously be moved? Definitely. I think when you start to see really dramatic economic impact, that's when. I think that's in some sense the next barrier. Because right now, if you think about the work in AI, it's really confusing. It's really hard to know what to make of all these advances. It's kind of like, okay, you got an advance and now you can do more things and you got another improvement and you got another cool demo. At some point, I think people who are outside of AI, they can no longer distinguish this progress anymore. So we were talking offline about translating Russian to English and how there's a lot of brilliant work in Russian that the rest of the world doesn't know about. That's true for Chinese. That's true for a lot of scientists and just artistic work in general. Do you think translation is the place where we're going to see sort of economic big impact? I don't know. I think there is a huge number of applicants. I mean, first of all, I wanna point out that translation already today is huge. I think billions of people interact with big chunks of the internet primarily through translation. So translation is already huge and it's hugely, hugely positive too. I think self-driving is going to be hugely impactful and that's, you know, it's unknown exactly when it happens, but again, I would not bet against deep learning. So I- So that's deep learning in general, but you think- Deep learning for self-driving. Yes, deep learning for self-driving. But I was talking about sort of language models. I see. Just to check. I veered off a little bit. Just to check. So you're not seeing a connection between driving and language No, no. Okay. Or rather both use neural nets. That'd be a poetic connection. I think there might be some, like you said, there might be some kind of unification towards a kind of multitask transformers that can take on both language and vision tasks. That'd be an interesting unification. Now, let's see, what can I ask about GPT-2 more? It's simple. So not much to ask. It's- You take a transform, you make it bigger, give it more data, and suddenly it does all those amazing things. Yeah, one of the beautiful things is that GPT, the transformers are fundamentally simple to explain, to train. Do you think bigger will continue to show better results in language? Probably. Sort of like, what are the next steps with GPT-2, do you think? I mean, I think for sure seeing what larger versions can do is one direction. Also, I mean, there are many questions. There's one question which I'm curious about, and that's the following. So right now, GPT-2, so we feed it all this data from the internet, which means that it needs to memorize all those random facts about everything in the internet. And it would be nice if the model could somehow use its own intelligence to decide what data it wants to accept and what data it wants to reject. Just like people. People don't learn all data indiscriminately. We are super selective about what we learn. And I think this kind of active learning, I think, would be very nice to have. Yeah, listen, I love active learning. So let me ask, does the selection of data, can you just elaborate that a little bit more? Do you think the selection of data is, like, I have this kind of sense that the optimization of how you select data, so the active learning process, is going to be a place for a lot of breakthroughs, even in the near future, because there hasn't been many breakthroughs there that are public. I feel like there might be private breakthroughs that companies keep to themselves, because it's a fundamental problem that has to be solved if you wanna solve self-driving, if you wanna solve a particular task. What do you think about the space in general? Yeah, so I think that for something like active learning, or in fact for any kind of capability, like active learning, the thing that it really needs is a problem. It needs a problem that requires it. It's very hard to do research about the capability if you don't have a task, because then what's going to happen is that you will come up with an artificial task, get good results, but not really convince anyone. Right, like, we're now past the stage where getting a result, an MNIST, some clever formulation of MNIST will convince people. That's right, in fact, you could quite easily come up with a simple active learning scheme on MNIST and get a 10x speedup, but then so what? And I think that with active learning, active learning will naturally arise as problems that require it pop up. That's my take on it. There's another interesting thing that OpenAI has brought up with GPT-2, which is when you create a powerful artificial intelligence system, and it was unclear what kind of detrimental, once you release GPT-2, what kind of detrimental effect it'll have, because if you have a model that can generate pretty realistic text, you can start to imagine that it would be used by bots in some way that we can't even imagine. So there's this nervousness about what it's possible to do. So you did a really kind of brave and I think profound thing, which is start a conversation about this. Like how do we release powerful artificial intelligence models to the public? If we do it all, how do we privately discuss with other, even competitors, about how we manage the use of the systems and so on? So from this whole experience, you released a report on it, but in general, are there any insights that you've gathered from just thinking about this, about how you release models like this? I mean, I think that my take on this is that the field of AI has been in a state of childhood, and now it's exiting that state and it's entering a state of maturity. What that means is that AI is very successful and also very impactful, and its impact is not only large, but it's also growing. And so for that reason, it seems wise to start thinking about the impact of our systems before releasing them, maybe a little bit too soon, rather than a little bit too late. And with the case of GPT-2, like I mentioned earlier, the results really were stunning. And it seemed plausible. It didn't seem certain. It seemed plausible that something like GPT-2 could easily use to reduce the cost of disinformation. And so there was a question of what's the best way to release it? And a staged release seemed logical. A small model was released, and there was time to see the... Many people use these models in lots of cool ways. There've been lots of really cool applications. There haven't been any negative application we know of, and so eventually it was released. But also other people replicated similar models. That's an interesting question, though, that we know of. So in your view, staged release is at least part of the answer to the question of how do we... What do we do once we create a system like this? It's part of the answer, yes. Is there any other insights? Like, say you don't wanna release the model at all because it's useful to you for whatever the business is. Well, plenty of people don't release models already. Right, of course. But is there some moral, ethical responsibility when you have a very powerful model to sort of communicate? Just as you said, when you had GPT-2, it was unclear how much it could be used for misinformation. It's an open question. And getting an answer to that might require that you talk to other really smart people that are outside of your particular group. Please tell me there's some optimistic pathway for people across the world to collaborate on these kinds of cases? Or is it still really difficult from one company to talk to another company? So it's definitely possible. It's definitely possible to discuss these kind of models with colleagues elsewhere and to get their take on what to do. How hard is it though? I mean... Do you see that happening? I think that's a place where it's important to gradually build trust between companies. Because ultimately, all the AI developers are building technology which is going to be increasingly more powerful. And so it's... The way to think about it is that ultimately we all need it together. Yeah, it's... I tend to believe in the better angels of our nature, but I do hope that when you build a really powerful AI system in a particular domain, that you also think about the potential negative consequences of... Yeah. It's an interesting and scary possibility that there'll be a race for AI development that would push people to close that development and not share ideas with others. I don't love this. I've been a pure academic for 10 years. I really like sharing ideas and it's fun, it's exciting. What do you think it takes to... Let's talk about AGI a little bit. What do you think it takes to build a system of human level intelligence? We talked about reasoning, we talked about long-term memory, but in general, what does it take, do you think? Well, I can't be sure. But I think that deep learning, plus maybe another small amount of AI is a small idea. Do you think self-play will be involved? Sort of like you've spoken about the powerful mechanism of self-play where systems learn by sort of exploring the world in a competitive setting against other entities that are similarly skilled as them and so incrementally improve in this way. Do you think self-play will be a component of building an AGI system? Yeah. So what I would say to build AGI, I think it's going to be deep learning plus some ideas. And I think self-play will be one of those ideas. I think that that is a very... Self-play has this amazing property that it can surprise us in truly novel ways. For example, like we, I mean, pretty much every self-play system, both our Dota bot, I don't know if OpenAI had a release about multi-agent where you had two little agents who were playing hide and seek. And of course, also AlphaZero. They will all produce surprising behaviors. They all produce behaviors that we didn't expect. They are creative solutions to problems. And that seems like an important part of AGI that our systems don't exhibit routinely right now. And so that's why I like this area. I like this direction because of its ability to surprise us. To surprise us. And an AGI system would surprise us fundamentally. Yes, and to be precise, not just a random surprise, but to find a surprising solution to a problem is also useful. Right. Now, a lot of the self-play mechanisms have been used in the game context, or at least in the simulation context. How much, how far along the path to AGI do you think will be done in simulation? How much faith, promise do you have in simulation versus having to have a system that operates in the real world? Whether it's the real world of digital real-world data or real world, like actual physical world of robotics? I don't think it's an either or. I think simulation is a tool and it helps. It has certain strengths and certain weaknesses and we should use it. Yeah, but, okay. I understand that. That's true, but one of the criticisms of self-play, one of the criticisms of reinforcement learning is one of the, its current power, its current results, while amazing, have been demonstrated in a simulated environments or very constrained physical environments. Do you think it's possible to escape them, escape the simulated environments and be able to learn in non-simulated environments? Or do you think it's possible to also just simulate in a photorealistic and physics realistic way the real world in a way that we can solve real problems with self-play in simulation? So, I think that transfer from simulation to the real world is definitely possible and has been exhibited many times in by many different groups. It's been especially successful in vision. Also, open AI in the summer has demonstrated a robot hand which was trained entirely in simulation in a certain way that allowed for seem-to-real transfer to occur. Is this for the Rubik's Cube? Yes, right. I wasn't aware that was trained in simulation. It was trained in simulation entirely. Really, so it wasn't in the physical, the hand wasn't trained? No, 100% of the training was done in simulation. And the policy that was learned in simulation was trained to be very adaptive. So adaptive that when you transfer it, it could very quickly adapt to the physical world. So the kind of perturbations with the giraffe or whatever the heck it was, were those part of the simulation? Well, the simulation was generally, so the simulation was trained to be robust to many different things, but not the kind of perturbations we've had in the video. So it's never been trained with a glove, it's never been trained with a stuffed giraffe. So in theory, these are novel perturbations. Correct, it's not in theory, in practice. That those are novel perturbations? Well, that's okay. That's a clean, small scale, but clean example of a transfer from the simulated world to the physical world. Yeah, and I will also say that I expect the transfer capabilities of deep learning to increase in general. And the better the transfer capabilities are, the more useful simulation will become. Because then you could take, you could experience something in simulation and then learn a moral of the story, which you could then carry with you to the real world. As humans do all the time when they play computer games. So let me ask sort of a embodied question, staying on AGI for a sec. Do you think AGI says that we need to have a body? We need to have some of those human elements of self-awareness, consciousness, sort of fear of mortality, sort of self-preservation in the physical space, which comes with having a body. I think having a body will be useful. I don't think it's necessary, but I think it's very useful to have a body for sure, because you can learn a whole new, you can learn things which cannot be learned without a body. But at the same time, I think that you can, if you don't have a body, you could compensate for it and still succeed. You think so? Yes, well, there is evidence for this. For example, there are many people who were born deaf and blind, and they were able to compensate for the lack of modalities. I'm thinking about Helen Kaler specifically. So even if you're not able to physically interact with the world, and if you're not able to, I mean, I actually was getting at, maybe let me ask on the more particular, I'm not sure if it's connected to having a body or not, but the idea of consciousness, and a more constrained version of that is self-awareness. Do you think an AGI system should have consciousness? We can't define consciousness, whatever the heck you think consciousness is. Yeah, hard question to answer, given how hard it is to define it. Do you think it's useful to think about? I mean, it's definitely interesting. It's fascinating. I think it's definitely possible that our systems will be conscious. Do you think that's an emergent thing that just comes from, do you think consciousness could emerge from the representation that's stored within your networks? So like that, it naturally just emerges when you become more and more, you're able to represent more and more of the world? Well, I'd say, I'd make the following argument, which is humans are conscious, and if you believe that artificial neural nets are sufficiently similar to the brain, then there should at least exist artificial neural nets you should be conscious to. You're leaning on that existence proof pretty heavily. Okay. But that's the best answer I can give. No, I know, I know, I know. There's still an open question if there's not some magic in the brain that we're not, I mean, I don't mean a non-materialistic magic, but that the brain might be a lot more complicated and interesting that we give it credit for. If that's the case, then it should show up, and at some point, we will find out that we can't continue to make progress. But I think it's unlikely. So we talk about consciousness, but let me talk about another poorly defined concept of intelligence. Again, we've talked about reasoning, we've talked about memory. What do you think is a good test of intelligence for you? Are you impressed by the test that Alan Turing formulated with the imitation game with natural language? Is there something in your mind that you would be deeply impressed by if a system was able to do? I mean, lots of things. There's a certain frontier of capabilities today, and there exist things outside of that frontier, and I would be impressed by any such thing. For example, I would be impressed by a deep learning system which solves a very pedestrian task, like machine translation or computer vision task or something which never makes mistake a human wouldn't make under any circumstances. I think that is something which have not yet been demonstrated, and I would find it very impressive. Yeah, so right now, they make mistakes in different, they might be more accurate than human beings, but they still, they make a different set of mistakes. So my, I would guess that a lot of the skepticism that some people have about deep learning is when they look at their mistakes and they say, well, those mistakes, they make no sense. Like if you understood the concept, you wouldn't make that mistake. And I think that changing that would be, that would inspire me, that would be, yes, this is progress. Yeah, that's a really nice way to put it. But I also just don't like that human instinct to criticize a model as not intelligent. That's the same instinct as we do when we criticize any group of creatures as the other, because it's very possible that GPT-2 is much smarter than human beings at many things. And that's definitely true. It has a lot more breadth of knowledge. Yes, breadth of knowledge, and even perhaps depth on certain topics. It's kind of hard to judge what depth means, but there's definitely a sense in which humans don't make mistakes, these models do. The same is applied to autonomous vehicles. The same is probably gonna continue being applied to a lot of artificial intelligence systems. We find, this is the annoying, this is the process of, in the 21st century, the process of analyzing the progress of AI is the search for one case where the system fails in a big way where humans would not, and then many people writing articles about it, and then broadly as the public generally gets convinced that the system is not intelligent. And we pacify ourselves by thinking it's not intelligent because of this one anecdotal case. And this seems to continue happening. Yeah, I mean, there is truth to that, although I'm sure that plenty of people are also extremely impressed by the systems that exist today. But I think this connects to the earlier point we discussed that it's just confusing to judge progress in AI. And you have a new robot demonstrating something. How impressed should you be? And I think that people will start to be impressed once AI starts to really move the needle on the GDP. So you're one of the people that might be able to create an AGI system here, not you, but you and OpenAI. If you do create an AGI system and you get to spend sort of the evening with it, him, her, what would you talk about, do you think? The very first time? First time. The first time I would just ask all kinds of questions and try to get it to make a mistake. And I would be amazed that it doesn't make mistakes and just keep asking broad questions. What kind of questions do you think, would they be factual or would they be personal, emotional, psychological? What do you think? All of the above. Would you ask for advice? Definitely. I mean, why would I limit myself talking to a system like this? Now, again, let me emphasize the fact that you truly are one of the people that might be in the room where this happens. So let me ask sort of a profound question about, I just talked to a Stalin historian. I've been talking to a lot of people who are studying power. Abraham Lincoln said, nearly all men can stand adversity, but if you want to test a man's character, give him power. I would say the power of the 21st century, maybe the 22nd, but hopefully the 21st, would be the creation of an AGI system and the people who have control, direct possession and control of the AGI system. So what do you think, after spending that evening having a discussion with the AGI system, what do you think you would do? Well, the ideal world I'd like to imagine is one where humanity, I like the board members of a company where the AGI is the CEO. So it would be, I would like, the picture which I would imagine is you have some kind of different entities, different countries or cities, and the people that leave their vote for what the AGI that represents them should do, and then AGI that represents them goes and does it. I think a picture like that, I find very appealing. You could have multiple, you would have an AGI for a city, for a country, and it would be trying to, in effect, take the democratic process to the next level. And the board can always fire the CEO. Essentially, press the reset button, say. Press the reset. Rerandomize the parameters. Well, let me sort of, that's actually, okay, that's a beautiful vision, I think, as long as it's possible to press the reset button. Do you think it will always be possible to press the reset button? So I think that it's definitely will be possible to build. So you're talking, so the question that I really understand from you is, will humans or, humans, people have control over the AI systems that they build? Yes, and my answer is, it's definitely possible to build AI systems which will want to be controlled by their humans. Wow, that's part of their, so it's not that just they can't help but be controlled, but that's, they exist, one of the objectives of their existence is to be controlled. In the same way that human parents generally want to help their children, they want their children to succeed. It's not a burden for them. They are excited to help the children and to feed them and to dress them and to take care of them. And I believe with high conviction that the same will be possible for an AGI. It will be possible to program an AGI, to design it in such a way that it will have a similar deep drive, that it will be delighted to fulfill, and the drive will be to help humans flourish. But let me take a step back to that moment where you create the AGI system. I think this is a really crucial moment. And between that moment and the Democratic board members with the AGI at the head, there has to be a relinquishing of power. So as George Washington, despite all the bad things he did, one of the big things he did is he relinquished power. He, first of all, didn't want to be president. And even when he became president, he didn't keep just serving as most dictators do for indefinitely. Do you see yourself being able to relinquish control over an AGI system, given how much power you can have over the world? At first, financial, just make a lot of money, right? And then control by having possession of this AGI system. I'd find it trivial to do that. I'd find it trivial to relinquish this kind of power. I mean, the kind of scenario you are describing sounds terrifying to me. That's all. I would absolutely not want to be in that position. Do you think you represent the majority or the minority of people in the AI community? Well, I mean- It's an open question and an important one. Are most people good is another way to ask it. So I don't know if most people are good, but I think that when it really counts, people can be better than we think. That's beautifully put, yeah. Are there specific mechanism you can think of of aligning AI gene values to human values? Is that, do you think about these problems of continued alignment as we develop the AI systems? Yeah, definitely. In some sense, the kind of question which you are asking is, so if I were to translate the question to today's terms, it would be a question about how to get an RL agent that's optimizing a value function which itself is learned. And if you look at humans, humans are like that because the reward function, the value function of humans is not external, it is internal. That's right. And there are definite ideas of how to train a value function. Basically an objective, and as objective as possible perception system that will be trained separately to recognize, to internalize human judgments on different situations. And then that component would then be integrated as the base value function for some more capable RL system. You could imagine a process like this. I'm not saying this is the process, I'm saying this is an example of the kind of thing you could do. So on that topic of the objective functions of human existence, what do you think is the objective function that's implicit in human existence? What's the meaning of life? Oh, I think the question is wrong in some way. I think that the question implies that there is an objective answer, which is an external answer. You know, your meaning of life is X. I think what's going on is that we exist, and that's amazing. And we should try to make the most of it and try to maximize our own value and enjoyment of our very short time while we do exist. It's funny, because action does require an objective function. It's definitely there in some form, but it's difficult to make it explicit, and maybe impossible to make it explicit, I guess is what you're getting at. And that's an interesting fact of an RL environment. Well, I was making a slightly different point, is that humans want things, and their wants create the drives that cause them to, you know, our wants are our objective functions, our individual objective functions. We can later decide that we want to change, that what we wanted before is no longer good, and we want something else. Yeah, but they're so dynamic. There's gotta be some underlying sort of Freud, there's things, there's like sexual stuff, there's people who think it's the fear of death, and there's also the desire for knowledge, and you know, all these kinds of things, or procreation, the sort of all the evolutionary arguments. It seems to be, there might be some kind of fundamental objective function from which everything else emerges. But it seems like that's very difficult to make explicit. I think that probably is an evolutionary objective function, which is to survive and procreate, and make your children succeed. That would be my guess, but it doesn't give an answer to the question of what's the meaning of life. I think you can see how humans are part of this big process, this ancient process, we exist on a small planet, and that's it. So given that we exist, try to make the most of it, and try to enjoy more, and suffer less as much as we can. Let me ask two silly questions about life. One, do you have regrets? Moments that if you went back, you would do differently. And two, are there moments that you're especially proud of, that made you truly happy? So I can answer both questions. Of course, there's a huge number of choices and decisions that I've made that with the benefit of hindsight, I wouldn't have made them. And I do experience some regret, but I try to take solace in the knowledge that at the time I did the best I could. And in terms of things that I'm proud of, I'm very fortunate to have done things I'm proud of, and they made me happy for some time, but I don't think that that is the source of happiness. So your academic accomplishments, all the papers, you're one of the most cited people in the world. All of the breakthroughs I mentioned, in computer vision and language and so on, what is the source of happiness and pride for you? I mean, all those things are a source of pride, for sure. I'm very grateful for having done all those things, and it was very fun to do them. But happiness comes, but you know, you can, happiness, well, my current view is that happiness comes from our, to a very large degree, from the way we look at things. You know, you can have a simple meal and be quite happy as a result, or you can talk to someone and be happy as a result as well. Or conversely, you can have a meal and be disappointed that the meal wasn't a better meal. So I think a lot of happiness comes from that, but I'm not sure, I don't wanna be too confident. I... Being humble in the face of the uncertainty seems to be also a part of this whole happiness thing. Well, I don't think there's a better way to end it than meaning of life and discussions of happiness. So, Ilya, thank you so much. You've given me a few incredible ideas. You've given the world many incredible ideas. I really appreciate it, and thanks for talking today. Yeah, thanks for stopping by. I really enjoyed it. Thanks for listening to this conversation with Ilya Sutskever, and thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using the code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review it with five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Alan Turing on machine learning. Instead of trying to produce a program to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education, one would obtain the adult brain. Thank you for listening, and hope to see you next time.

https://youtu.be/13CZPWmke6A

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Jeff Hawkins: The Thousand Brains Theory of Intelligence | Lex Fridman Podcast #208

The following is a conversation with Jeff Hawkins, a neuroscientist seeking to understand the structure, function, and origin of intelligence in the human brain. He previously wrote a seminal book on the subject titled On Intelligence, and recently a new book called A Thousand Brains, which presents a new theory of intelligence that Richard Dawkins, for example, has been raving about, calling the book, quote, brilliant and exhilarating. I can't read those two words and not think of him saying it in his British accent. Quick mention of our sponsors, Codecademy, BioOptimizers, ExpressVPN, Asleep, and Blinkist. Check them out in the description to support this podcast. As a side note, let me say that one small but powerful idea that Jeff Hawkins mentions in his new book is that if human civilization were to destroy itself, all of knowledge, all our creations would go with us. He proposes that we should think about how to save that knowledge in a way that long outlives us, whether that's on Earth, in orbit around Earth, or in deep space, and then to send messages that advertise this backup of human knowledge to other intelligent alien civilizations. The main message of this advertisement is not that we are here, but that we were once here. This little difference somehow was deeply humbling to me, that we may with some non-zero likelihood destroy ourselves, and that an alien civilization thousands or millions of years from now may come across this knowledge store, and they would only with some low probability even notice it, not to mention be able to interpret it. And the deeper question here for me is what information in all of human knowledge is even essential? Does Wikipedia capture it, or not at all? This thought experiment forces me to wonder what are the things we've accomplished and are hoping to still accomplish that will outlive us? Is it things like complex buildings, bridges, cars, rockets? Is it ideas like science, physics, and mathematics? Is it music and art? Is it computers, computational systems, or even artificial intelligence systems? I personally can't imagine that aliens wouldn't already have all of these things, in fact much more and much better. To me, the only unique thing we may have is consciousness itself, and the actual subjective experience of suffering, of happiness, of hatred, of love. If we can record these experiences in the highest resolution directly from the human brain such that aliens would be able to replay them, that is what we should store and send as a message. Not Wikipedia, but the extremes of conscious experiences, the most important of which, of course, is love. This is the Lex Friedman Podcast, and here is my conversation with Jeff Hawkins. We previously talked over two years ago. Do you think there's still neurons in your brain that remember that conversation, that remember me and got excited? There's a Lex neuron in your brain that just finally has a purpose? I do remember our conversation, or I have some memories of it, and I formed additional memories of you in the meantime. I wouldn't say there's a neuron or neurons in my brain that know you. There are synapses in my brain that have formed that reflect my knowledge of you and the model I have of you and the world. Whether the exact same synapses were formed two years ago, it's hard to say because these things come and go all the time. One thing to know about brains is that when you think of things, you often erase the memory and rewrite it again. So yes, but I have a memory of you, and that's instantiated in synapses. There's a simpler way to think about it. We have a model of the world in your head, and that model is continually being updated. I updated this morning. You offered me this water. You said it was from the refrigerator. I remember these things. And so the model includes where we live, the places we know, the words, the objects in the world. It's a monstrous model and it's constantly being updated, and people are just part of that model. So are animals, so are other physical objects, so are events we've done. So it's no special, in my mind, special place for the memories of humans. I mean, obviously, I know a lot about my wife and friends and so on, but it's not like a special place for humans or over here, but we model everything, and we model other people's behaviors too. If I said there's a copy of your mind in my mind, it's just because I know how humans, I've learned how humans behave, and I've learned some things about you, and that's part of my world model. Well, I just also mean the collective intelligence of the human species. I wonder if there's something fundamental to the brain that enables that. So modeling other humans with their ideas. We're actually jumping into a lot of big topics, like collective intelligence is a separate topic that a lot of people like to talk about. We can talk about that. But so that's interesting. We're not just individuals. We live in society and so on. But from our research point of view, and so again, let's just talk, we studied the neocortex. It's a sheet of neural tissue. It's about 75% of your brain. It runs on this very repetitive algorithm. It's a very repetitive circuit, and so you can apply that algorithm to lots of different problems, but it's all underneath. It's the same thing. We're just building this model. So from our point of view, we wouldn't look for these special circuits someplace buried in your brain that might be related to understanding other humans. It's more like, how do we build a model of anything? How do we understand anything in the world? And humans are just another part of the things we understand. So there's nothing to the brain that knows the emergent phenomenon of collective intelligence. Well I certainly know about that. I've heard the terms. I've read. No, but that's an idea. Well, okay. Well, I think we have language, which is sort of built into our brains, and that's a key part of collective intelligence. So there are some prior assumptions about the world we're going to live in when we're born. We're not just a blank slate. And so did we evolve to take advantage of those situations? Yes. But again, we study only part of the brain, the neocortex. Other parts of the brain are very much involved in societal interactions and human emotions and how we interact and even societal issues about how we interact with other people, when we support them, when we're greedy, and things like that. I mean, certainly the brain is a great place where to study intelligence. I wonder if it's the fundamental atom of intelligence. Well I would say it's absolutely an essential component, even if you believe in collective intelligence as, hey, that's where it's all happening. That's what we need to study. Which I don't believe that, by the way. I think it's really important, but I don't think that is the thing. But even if you do believe that, then you have to understand how the brain works in doing that. It's more like we are intelligent individuals, and together we are much more magnified, our intelligence. We can do things which we couldn't do individually. But even as individuals, we're pretty damn smart. And we can model things and understand the world and interact with it. So to me, if you're going to start someplace, you need to start with the brain. Then you could say, well, how do brains interact with each other? And what is the nature of language? And how do we share models that I've learned something about the world, how do I share it with you? Which is really what communal intelligence is. I know something, you know something. We've had different experiences in the world. I've learned something about brains, maybe I can impart that to you. You've learned something about physics, and you can impart that to me. But it all comes down to, even just the epistemological question of, well, what is knowledge? And how do you represent it in the brain? That's where it's going to reside, right? Or in our writings. It's obvious that human collaboration, human interaction is how we build societies. But some of the things you talk about and work on, some of those elements of what makes up an intelligent entity is there with a single person. Absolutely. I mean, we can't deny that the brain is the core element here in, at least I think it's true, because the brain is the core element in all theories of intelligence. It's where knowledge is represented, it's where knowledge is created. We interact, we share, we build upon each other's work, but without a brain you'd have nothing. There would be no intelligence without brains. So that's where we start. I got into this field because I just was curious as to who I am. How do I think? What's going on in my head when I'm thinking? What does it mean to know something? I can ask what it means for me to know something independent of how I learned it from you or from someone else or from society. What does it mean for me to know that I have a model of you in my head? What does it mean to know I know what this microphone does and how it works physically, even though I can't see it right now? How do I know that? What does it mean? How do the neurons do that at the fundamental level of neurons and synapses and so on? Those are really fascinating questions, and I'm happy to, just happy to understand those if I could. So in your new book, you talk about our brain, our mind as being made up of many brains. So the book is called A Thousand Brain Theory of Intelligence. What is the key idea of this book? The book has three sections, and it has sort of maybe three big ideas. So the first section is all about what we've learned about the neocortex, and that's the thousand brains theory. Just to complete the picture, the second section is all about AI, and the third section is about the future of humanity. So the thousand brains theory, the big idea there, if I had to summarize into one big idea is that we think of the brain, the neocortex as learning this model of the world, but what we learned is actually there's tens of thousands of independent modeling systems going on. And so each, what we call a column in the cortex, there's about 150,000 of them, is a complete modeling system. So it's a collective intelligence in your head in some sense. So the thousand brains theory says, well, where do I have knowledge about this coffee cup or where's the model of this cell phone? It's not in one place. It's in thousands of separate models that are complementary and they communicate with each other through voting. So this idea that we have, we feel like we're one person. That's our experience. We can explain that. But reality, there's lots of these, it's almost like little brains, but they're sophisticated modeling systems, about 150,000 of them in each human brain. And that's a total different way of thinking about how the neocortex is structured than we or anyone else thought of even just five years ago. So you mentioned you started this journey just looking in the mirror and trying to understand who you are. So if you have many brains, who are you then? So it's interesting, we have a singular perception, right? We think, oh, I'm just here, I'm looking at you, but it's composed of all these things. There's sounds and there's vision and there's touch and all kinds of inputs. Yet we have the singular perception. And what the thousand brains theory says, we have these models that are visual models. We have models that are auditory models, models that talk to models and so on, but they vote. And so in the cortex, you can think about these columns as like little grains of rice, 150,000 stacked next to each other. And each one is its own little modeling system, but they have these long range connections that go between them. And we call those voting connections or voting neurons. And so the different columns try to reach a consensus, like what am I looking at? Okay, each one has some ambiguity, but they come to a consensus. Oh, there's a water bottle I'm looking at. We are only consciously able to perceive the voting. We're not able to perceive anything that goes under the hood. So the voting is what we're aware of. The results of the vote. Yeah, the result. Well, you can imagine it this way. We were just talking about eye movements a moment ago. So as I'm looking at something, my eyes are moving about three times a second. And with each movement, a completely new input is coming into the brain. It's not repetitive. It's not shifting it around. It's completely new. I'm totally unaware of it. I can't perceive it. But yet, if I looked at the neurons in your brain, they're going on and off, on and off, on and off, on and off. But the voting neurons are not. The voting neurons are saying, we all agree, even though I'm looking at different parts of this, this is a water bottle right now. And that's not changing. And it's in some position and pose relative to me. So I have this perception of the water bottle about two feet away from me at a certain pose to me. That is not changing. That's the only part I'm aware of. I can't be aware of the fact that the inputs from the eyes are moving and changing and all this other stuff. So these long range connections are the part we can be conscious of. The individual activity in each column doesn't go anywhere else. It doesn't get shared anywhere else. There's no way to extract it and talk about it or extract it and even remember it to say, oh, yes, I can recall that. But these long range connections are the things that are accessible to language and to our hippocampus, our short term memory systems and so on. So we're not aware of 95 percent or maybe it's even 98 percent of what's going on in your brain. We're only aware of this sort of stable, somewhat stable voting outcome of all these things that are going on underneath the hood. So what would you say is the basic element in the thousand brains theory of intelligence of intelligence? What's the atom of intelligence when you think about it? Is it the individual brains? Then what is a brain? Well, let's let's can we just talk about what intelligence is first and then and then we can talk about the elements are. So in my in my book, intelligence is the ability to learn a model of the world, to build internal to your head. A model that represents the structure of everything, you know, to know what this is, a table and that's a coffee cup and this is a gooseneck lamp and all this to know these things. I have to have a model in my head. I just don't look at him and go, what is that? I already have internal representations of these things in my head and I had to learn them. I wasn't born to any of that knowledge. You were, you know, we have some lights in the room here. I, you know, that's not part of my evolutionary heritage, right? It's not in my genes. So we have this incredible model and the model includes not only what things look like and feel like, but where they are relative to each other and how they behave. I've never picked up this water bottle before, but I know that if I took my hand on that blue thing and I turn it, it'll probably make a funny little sound as the little plastic things detach and then it'll rotate and it'll rotate a certain way and it'll come off. How do I know that? Because I have this model in my head. So the essence of intelligence is our ability to learn a model and the more sophisticated our model is, the smarter we are. Not that there is a single intelligence because you can know about, you know a lot about things that I don't know and I know about things you don't know and we can both be very smart, but we both learned a model of the world through interacting with it. So that is the essence of intelligence. Then we can ask ourselves what are the mechanisms in the brain that allow us to do that and what are the mechanisms of learning, not just the neural mechanisms, what are the general process by how we learn a model? So that was a big insight for us. It's like what are the actual things that, how do you learn this stuff? It turns out you have to learn it through movement. You can't learn it just by, that's how we learn. We learn through movement. We learn, so you build up this model by observing things and touching them and moving them and walking around the world and so on. So either you move or the thing moves. Somehow. Obviously you can learn things just by reading a book, something like that, but think about if I were to say, oh, here's a new house. I want you to learn, what do you do? You have to walk from room to room. You have to open the doors, look around, see what's on the left, what's on the right. As you do this, you're building a model in your head. It's just, that's what you're doing. You can't just sit there and say, I'm going to grok the house. No. Or you don't even want to just sit there and read some description of it, right? You literally physically interact. And the same with like a smartphone. If I'm going to learn a new app, I touch it and I move things around and I see what happens when I do things with it. So that's the basic way we learn in the world. And by the way, when you say model, you mean something that can be used for prediction in the future. It's used for prediction and for behavior and planning. And does a pretty good job at doing so. Yeah. Here's the way to think about a model. A lot of people get hung up on this. So you can imagine an architect making a model of a house, right? So there's a physical model. It's small. And why do they do that? Well, we do that because you can imagine what it would look like from different angles. Okay. Look at them here, look at them there. And you can also say, well, how far to get from the garage to the swimming pool or something like that, right? You can imagine looking at this. And you can say, what would you view from this location? So we build these physical models to let you imagine the future and imagine behaviors. Now we can take that same model and put it in a computer. So we now, today, they'll build models of houses in a computer and they do that using a set of, we'll come back to this term in a moment, reference frames. But basically you assign a reference frame for the house and you assign different things for the house in different locations. And then the computer can generate an image and say, okay, this is what it looks like in this direction. The brain is doing something remarkably similar to this. Surprising. It's using reference frames. It's building these, it's similar to a model in a computer, which has the same benefits of building a physical model. It allows me to say, what would this thing look like if it was in this orientation? What would likely happen if I pushed this button? I've never pushed this button before. Or how would I accomplish something? I want to convey a new idea I've learned. How would I do that? I can imagine in my head, well, I could talk about it. I could write a book. I could do some podcasts. I could maybe tell my neighbor. And I can imagine the outcomes of all these things before I do any of them. That's what the model lets you do. It lets us plan the future and imagine the consequences of our actions. Prediction, you asked about prediction. Prediction is not the goal of the model. Prediction is an inherent property of it. And it's how the model corrects itself. So prediction is fundamental to intelligence. It's fundamental to building a model and the model's intelligent. And let me go back and be very precise about this. Prediction, you can think of prediction two ways. One is like, hey, what would happen if I did this? That's a type of prediction. That's a key part of intelligence. But here's some predictions like, oh, what's this water bottle going to feel like when I pick it up? And that doesn't seem very intelligent. But one way to think about prediction is it's a way for us to learn where our model is wrong. So if I picked up this water bottle and it felt hot, I'd be very surprised. Or if I picked it up and it was very light, I'd be surprised. Or if I turned this top and it didn't, I had to turn it the other way, I'd be surprised. And so all those might have a prediction like, okay, I'm going to do it. I'll drink some water. I'm going to go, okay, I do this. There it is. I feel opening, right? What if I had to turn it the other way? Or what if it's split in two? Then I say, oh my gosh, I misunderstood this. I didn't have the right model. This thing, my attention would be drawn to it. I'd be looking at it going, well, how the hell did that happen? Why did it open up that way? And I would update my model by doing it. Just by looking at it and playing around with it, I'd update it and say, this is a new type of water bottle. But you, so you're talking about sort of complicated things like a water bottle, but this also applies for just basic vision, just like seeing things. It's almost like a precondition of just perceiving the world is predicting. Everything that you see is first passed through your prediction. Everything you see and feel. In fact, this is the insight I had back in the late 80s. No, excuse me, early 80s. And I know that people have reached the same idea, is that every sensory input you get, not just vision, but touch and hearing, you have an expectation about it and a prediction. Sometimes you can predict very accurately, sometimes you can't. I can't predict what next word's going to come out of your mouth, but as you start talking, I'll get better and better predictions. And if you talked about some topics, I'd be very surprised. So I have this sort of background prediction that's going on all the time for all of my senses. Again, the way I think about that is this is how we learn. It's more about how we learn. It's a test of our understanding. Our predictions are a test. Is this really a water bottle? If it is, I shouldn't see a little finger sticking out the side. And if I saw a little finger sticking out, I was like, what the hell's going on? That's not normal. I mean, that's fascinating that, let me linger on this for a second. It really honestly feels that prediction is fundamental to everything, to the way our mind operates, to intelligence. So it's just a different way to see intelligence, which is like everything starts at prediction. And prediction requires a model. You can't predict something unless you have a model of it. But the action is prediction. The thing the model does is prediction. But you can then extend it to things like, what would happen if I took this today? I went and did this. What would be the likelihood? You can extend prediction to like, oh, I want to get a promotion at work. What action should I take? And you can say, if I did this, I predict what might happen. If I spoke to someone, I predict what might happen. So it's not just low-level predictions. Yeah, it's all predictions. It's all predictions. It's like this black box that you can ask basically any question, low-level or high-level. So we start off with that observation. It's this nonstop prediction. And I write about this in the book. And then we ask, how do neurons actually make predictions physically? Like, what does the neuron do when it makes a prediction? Or the neural tissue does when it makes a prediction. And then we ask, what are the mechanisms by how we build a model that allows you to make prediction? So we started with prediction as sort of the fundamental research agenda, in some sense. And say, well, we understand how the brain makes predictions, we'll understand how it builds these models and how it learns. And that's the core of intelligence. So it was the key that got us in the door to say, that is our research agenda, understand predictions. So in this whole process, where does intelligence originate, would you say? So if we look at things that are much less intelligent than humans, and you start to build up a human through the process of evolution, where is this magic thing that has a prediction model or a model that's able to predict that starts to look a lot more like intelligence? Is there a place where... Richard Dawkins wrote an introduction to your book, an excellent introduction. It puts a lot of things into context. It's funny just looking at parallels for your book and Darwin's Origin of Species. Darwin wrote about the origin of species. So what is the origin of intelligence? Yeah. Well, we have a theory about it, and it's just that, it's a theory. Theory goes as follows. As soon as living things started to move, they're not just floating in the sea, they're not just a plant grounded someplace. Soon as they started to move, there was an advantage to moving intelligently, to moving in certain ways. And there's some very simple things you can do, bacteria or single cell organisms can move towards a source of gradient of food or something like that. But an animal that might know where it is and know where it's been and how to get back to that place, or an animal that might say, oh, there was a source of food someplace, how do I get to it? Or there was a danger, how do I get to it? There was a mate, how do I get to them? There was a big evolution advantage to that. So early on, there was a pressure to start understanding your environment, like where am I and where have I been? And what happened in those different places? So we still have this neural mechanism in our brains. It's in the mammals, it's in the hippocampus and entorhinal cortex, these are older parts of the brain, and these are very well studied. We build a map of our environment. So these neurons in these parts of the brain know where I am in this room and where the door was and things like that. So a lot of other mammals have this kind of capability. All mammals have this. And almost any animal that knows where it is and can get around must have some mapping system, must have some way of saying, I've learned a map of my environment, I have hummingbirds in my backyard. And they go to the same places all the time, they must know where they are. They just know where they are when they're flying. They're not just randomly flying around. They know particular flowers they come back to. So we all have this. And it turns out it's very tricky to get neurons to do this, to build a map of an environment. And so we now know, there's these famous studies that's still very active about place cells and grid cells and these other types of cells in the older parts of the brain, and how they build these maps of the world. It's really clever. It's obviously been under a lot of evolutionary pressure over a long period of time to get good at this. So animals now know where they are. What we think has happened, and there's a lot of evidence to suggest this, is that mechanism we learned to map like a space, was repackaged, the same type of neurons was repackaged into a more compact form, and that became the cortical column. And it was in some sense genericized, if that's a word. It was turned into a very specific thing about learning maps of environments to learning maps of anything, learning a model of anything, not just your space, but coffee cups and so on. And it got sort of repackaged into a more compact version, a more universal version, and then replicated. So the reason we're so flexible is we have a very generic version of this mapping algorithm, and we have 150,000 copies of it. Sounds a lot like the progress of deep learning. How so? So take neural networks that seem to work well for a specific task, compress them, and multiply it by a lot, and then you just stack them on top of it. It's like the story of Transformers in Natural Language Processing. But in deep learning networks, they end up, you're replicating an element, but you still need the entire network to do anything. Here what's going on is each individual element is a complete learning system. This is why I can take a human brain, cut it in half, and it still works. It's pretty amazing. It's fundamentally distributed. It's fundamentally distributed, complete modeling systems. But that's our story we like to tell. I would guess it's likely largely right, but there's a lot of evidence supporting that story, this evolutionary story. The thing which brought me to this idea is that the human brain got big very quickly. That led to the proposal a long time ago that, well, there's this common element. Instead of creating new things, it just replicated something. We also are extremely flexible. We can learn things that we had no history about. That tells us that the learning algorithm is very generic. It's very universal because it doesn't assume any prior knowledge about what it's learning. You combine those things together and you say, okay, well, how did that come about? Where did that universal algorithm come from? It had to come from something that wasn't universal. It came from something that was more specific. This led to our hypothesis that you would find grid cells and place cell equivalents in the neocortex. When we first published our first papers on this theory, we didn't know of evidence for that. We did know of some, but we didn't know about it. Then we became aware of the evidence for grid cells and for parts of the neocortex. Now there's been new evidence coming out. There's some interesting papers that came out just January of this year. One of our predictions was if this evolutionary hypothesis is correct, we would see grid cell place cell equivalents, cells that work like them, through every column in the neocortex. That's starting to be seen. What does it mean? Why is it important that they're present? Because it tells us... We're asking about the evolutionary origin of intelligence. Our theory is that these columns in the cortex are working on the same principles. They're modeling systems. It's hard to imagine how neurons do this. We said, hey, it's really hard to imagine how neurons could learn these models of things. We can talk about the details of that if you want. There's this other part of the brain we know that learns models of environments. Could that mechanism to learn to model this room be used to learn to model the water bottle? Is it the same mechanism? We said it's much more likely the brain's using the same mechanism, which case it would have these equivalent cell types. It's basically the whole theory is built on the idea that these columns have reference frames and are learning these models and these grid cells create these reference frames. It's basically the major, in some sense, the major predictive part of this theory is that we will find these equivalent mechanisms in each column in the inner cortex, which tells us that that's what they're doing. They're learning these sensory motor models of the world. We're pretty confident that would happen, but now we're seeing the evidence. The evolutionary process nature does a lot of copy and paste and see what happens. Yeah. There's no direction to it, but it just found out, hey, if I took these elements and made more of them, what happens? I took them up to the eyes and I took them to ears. That seems to work pretty well for us. Again, just to take a quick step back to our conversation of collective intelligence, do you sometimes see that as just another copy and paste aspect? Is copying and pasting these brains in humans and making a lot of them and then creating social structures that then almost operate as a single brain? I wouldn't have said it, but you said it sounded pretty good. To you, the brain is its own thing. Our goal is to understand how the neural cortex works. We can argue how essential that is to understanding the human brain, because it's not the entire human brain. You can argue how essential that is to understanding human intelligence. You can argue how essential this is to communal intelligence. Our goal was to understand the neural cortex. What is the neural cortex and where does it fit in the various aspects of what the brain does? How important is it to you? Well, obviously, again, I mentioned again in the beginning, it's about 70 to 75% of the volume of a human brain. It dominates our brain in terms of size. Not in terms of number of neurons, but in terms of size. Size isn't everything, Jeff. I know. But it's nothing to be... It's not that. We know that all high level vision, hearing, and touch happens in the neural cortex. We know that all language occurs and is understood in the neural cortex, whether that's spoken language, written language, sign language, language of mathematics, language of physics, music. We know that all high level planning and thinking occurs in the neural cortex. If I were to say, what part of your brain designed a computer and understands programming and creates music? It's all the neural cortex. So then, that's just an undeniable fact. But then there's other parts of our brain are important too, right? Our emotional states, our body regulating our body. So the way I like to look at it is, can you understand the neural cortex without the rest of the brain? And some people say you can't, and I think absolutely you can. It's not that they're not interacting, but you can understand it. Can you understand the neural cortex without understanding the emotions of fear? Yes, you can. You can understand how the system works. It's just a modeling system. I make the analogy in the book that it's like a map of the world, and how that map is used depends on who's using it. So how our map of our world in our cortex, how we manifest as a human, depends on the rest of our brain. What are our motivations? What are my desires? Am I a nice guy or not a nice guy? Am I a cheater or not a cheater? How important different things are in my life? So but the neural cortex can be understood on its own. And I say that as a neuroscientist, I know there's all these interactions, and I want to say I don't know them, and we don't think about them. But from a layperson's point of view, you can say it's a modeling system. I don't generally think too much about the communal aspect of intelligence, which you've brought up a number of times already. So that's not really been my concern. I just wonder if there's a continuum from the origin of the universe, like this pockets of complexities that form living organisms. I wonder if we're just, if you look at humans, we feel like we're at the top. But I wonder if there's like just where everybody probably, every living type pocket of complexity is probably thinks they're the, pardon the French, they're the shit. They're at the top of the pyramid. Well, if they're thinking. Well, then what is thinking? In a sense, the whole point is in their sense of the world, their sense is that they're at the top of it. Like what does a turtle think? But you're bringing up, the problems of complexity and complexity theory are, it's a huge, interesting problem in science. And I think we've made surprisingly little progress in understanding complex systems in general. And so, the Santa Fe Institute was founded to study this. And even the scientists there will say, it's really hard. We haven't really been able to figure out exactly, that science isn't really congealed yet. We're still trying to figure out the basic elements of that science. What, where does complexity come from and what is it and how you define it, whether it's DNA creating bodies or phenotypes or it's individuals creating societies or ants and markets and so on. It's a very complex thing. I'm not a complexity theorist person. I think you need to ask, well, the brain itself is a complex system. So can we understand that? I think we've made a lot of progress understanding how the brain works. But I haven't brought it out to like, oh, well, where are we on the complexity spectrum? It's like, it's a great question. I prefer for that answer to be, we're not special. It seems like if we're honest, most likely we're not special. So if there is a spectrum, we're probably not in some kind of significant place. I think there's one thing we could say that we are special. And again, only here on earth. I'm not saying that. Is that if we think about knowledge, what we know, we clearly, human brains are the only brains that have a certain types of knowledge. We're the only brains on this earth to understand what the earth is, how old it is, that the universe is a picture as a whole. We're the only organisms to understand DNA and the origins of species. No other species on this planet has that knowledge. So if we think about, I like to think about, one of the endeavors of humanity is to understand the universe as much as we can. I think our species is further along in that, undeniably. Whether our theories are right or wrong, we can debate, but at least we have theories. We know what the sun is and how its fusion is and what black holes are. We know general theory of relativity and no other animal has any of this knowledge. So in that sense, we're special. Are we special in terms of the hierarchy of complexity in the universe? Probably not. Can we look at a neuron? You say that prediction happens in the neuron. What does that mean? So the neuron traditionally is seen as the basic element of the brain. So I mentioned this earlier, that prediction was our research agenda. We said, okay, how does the brain make a prediction? I'm about to grab this water bottle and my brain is predicting what I'm gonna feel on all my parts of my fingers. If I felt something really odd on any part here, I'd notice it. So my brain is predicting what it's gonna feel as I grab this thing. So how does that manifest itself in neural tissue? Brain's made of neurons and there's chemicals and there's neurons and there's spikes and they're connected. Where is the prediction going on? And one argument could be that, well, when I'm predicting something, a neuron must be firing in advance. It's like, okay, this neuron represents what you're gonna feel and it's firing. It's sending a spike. And certainly that happens to some extent. But our predictions are so ubiquitous that we're making so many of them, which we're totally unaware of. Just the vast majority of them, you have no idea that you're doing this. That it wasn't really, we were trying to figure out how could this be? Where are these happening? And I won't walk you through the whole story unless you insist upon it, but we came to the realization that most of your predictions are occurring inside individual neurons, especially the most common neuron, the pyramidal cells. And there's a property of neurons. Everyone knows, or most people know, that a neuron is a cell and it has this spike called an action potential and it sends information. But we now know that there's these spikes internal to the neuron, they're called dendritic spikes. They travel along the branches of the neuron and they don't leave the neuron, they're just internal only. There's far more dendritic spikes than there are action potentials, far more. They're happening all the time. And what we came to understand that those dendritic spikes, the ones that are occurring, are actually a form of prediction. They're telling the neuron, the neuron is saying, I expect that I might become active shortly. And that internal, so the internal spike is a way of saying, you might be generating external spikes soon. I predicted you're going to become active. And we wrote a paper in 2016 which explained how this manifests itself in neural tissue and how it is that this all works together. But the vast majority, we think there's a lot of evidence supporting it. So that's where we think that most of these predictions are internal, that's why you can't be, they're internal to the neuron, you can't perceive them. From understanding the prediction mechanism of a single neuron, do you think there's deep insights to be gained about the prediction capabilities of the many brains within the bigger brain and the brain? Oh yeah, yeah, yeah. So having a prediction inside an individual neuron is not that useful. So what? The way it manifests itself in neural tissue is that when a neuron emits these spikes, a very singular type of event, if a neuron is predicting that it's going to be active, it emits its spike a little bit sooner, just a few milliseconds sooner than it would have otherwise. I give the analogy in the book, it's like a sprinter on a starting block in a race. And if someone says, get ready, set, you get up and you're ready to go. And then when your race starts, you get a little bit earlier start. So that ready, set is like the prediction, and the neuron's ready to go quicker. And what happens is when you have a whole bunch of neurons together, and they're all getting these inputs, the ones that are in the predictive state, the ones that are anticipating to become active, if they do become active, they happen sooner, they disable everything else and it leads to different representations in the brain. So you have to, it's not isolated just to the neuron. The prediction occurs within the neuron, but the network behavior changes. So what happens under different predictions, different inputs have different representations. So what I predict is gonna be different under different contexts. What my input will be is different under different contexts. So this is a key little theory, how this works. So the theory of the thousand brains, if you were to count the number of brains, how would you do it? The thousand brain theory says that basically every cortical column in your neocortex is a complete modeling system. And that when I ask where do I have a model of something like a coffee cup, it's not in one of those models, it's in thousands of those models. There's thousands of models of coffee cups. That's what the thousand brains. And there's a voting mechanism. And there's a voting mechanism, which is the thing which you're conscious of, which leads to your singular perception. That's why you perceive something. So that's the thousand brains theory. The details of how we got to that theory are complicated. It wasn't that we just thought of it one day. And one of those details is we had to ask how does a model make predictions? And we've talked about just these predictive neurons. That's part of this theory. It's like saying, oh, it's a detail. But it was like a crack in the door. It's like, how are we gonna figure out how these neurons build through this? What is going on here? So we just looked at prediction as like, well, we know that's ubiquitous. We know that every part of the cortex is making predictions. Therefore whatever the predictive system is, it's gonna be everywhere. We know there's a gazillion predictions happening at once. So this is where we can start teasing apart, ask questions about how could neurons be making these predictions? And that sort of built up to now what we have, this thousand brains theory, which is complex. I can state it simply, but we just didn't think of it. We had to get there step by step. It took years to get there. And where does reference frames fit in? So yeah. Okay. So again, a reference frame, I mentioned earlier about the model of a house. And I said, if you're gonna build a model of a house in a computer, they have a reference frame. And you can think of reference frame like a Cartesian coordinates, like X, Y, and Z axes. So I could say, oh, I'm gonna design a house. I can say, well, the front door is at this location, X, Y, Z, and the roof is at this location, X, Y, Z, and so on. That's a type of reference frame. So it turns out for you to make a prediction, and I walk you through the thought experiment in the book where I was predicting what my finger was gonna feel when I touch the coffee cup. It was a ceramic coffee cup, but this one will do. And what I realized is that to make a prediction of what my finger's gonna feel, like, it's gonna feel different than this, what's it feel different if I touch the hole or this thing on the bottom? Make that prediction. The cortex needs to know where the finger is, the tip of the finger, relative to the coffee cup. And exactly relative to the coffee cup. And to do that, I have to have a reference frame for the coffee cup. It has to have a way of representing the location of my finger to the coffee cup. And then we realized, of course, every part of your skin has to have a reference frame relative to the things it touches. And then we did the same thing with vision. So the idea that a reference frame is necessary to make a prediction when you're touching something or when you're seeing something, and you're moving your eyes, you're moving your fingers. It's just a requirement to know what to predict. If I have a structure, I'm gonna make a prediction. I have to know where it is I'm looking or touching it. So then we said, well, how do neurons make reference frames? It's not obvious. X, Y, Z coordinates don't exist in the brain. It's just not the way it works. So that's when we looked at the older part of the brain, the hippocampus and the adrenal cortex, where we knew that in that part of the brain, there's a reference frame for a room or a reference frame for an environment. Remember I talked earlier about how you could make a map of this room. So we said, oh, they are implementing reference frames there. So we knew that reference frames needed to exist in every quarter of a column. And so that was a deductive thing. We just deduced it. It has to exist. So you take the old mammalian ability to know where you are in a particular space, and you start applying that to higher and higher levels. Yeah. First you apply it to where your finger is. So here's the way I think about it. The old part of the brain says, where's my body in this room? The new part of the brain says, where's my finger relative to this object? Where is a section of my retina relative to this object? I'm looking at one little corner. Where is that relative to this patch of my retina? And then we take the same thing and apply it to concepts, mathematics, physics, humanity, whatever you want to think about. And eventually you're pondering your own mortality. Well, whatever. But the point is, when we think about the world, when we have knowledge about the world, how is that knowledge organized, Lex? Where is it in your head? The answer is, it's in reference frames. So the way I learned the structure of this water bottle, where the features are relative to each other, when I think about history or democracy or mathematics, the same basic underlying structures happen. There's reference frames for where the knowledge that you're assigning things to. So in the book, I go through examples like mathematics and language and politics. But the evidence is very clear in the neuroscience. The same mechanism that we use to model this coffee cup, we're going to use to model high-level thoughts. Your, the demise of humanity, whatever you want to think about. It's interesting to think about how different are the representations of those higher dimensional concepts, higher level concepts, how different the representation there is in terms of reference frames versus spatial. But interesting thing, it's a different application, but it's the exact same mechanism. But isn't there some aspect to higher level concepts that they seem to be hierarchical? Like they just seem to integrate a lot of information into them. So is our physical objects. So take this water bottle. I'm not particular to this brand, but this is a Fiji water bottle. And it has a logo on it. I use this example in my book, our company's coffee cup has a logo on it. But this object is hierarchical. It is, it's got like a cylinder and a cap, but then it has this logo on it. The logo has a word, the word has letters, the letters have different features. And so I don't have to remember, I don't have to think about this. I say, oh, there's a Fiji logo on this water bottle. I don't have to go through and say, oh, what is the Fiji logo? It's the F and I and a J and I, and there's a hibiscus flower. And oh, it has the stamen on it. I don't have to do that. I just incorporate all of that in some sort of hierarchical representation. I say, put this logo on this water bottle. And then the logo has a word and the word has letters. All hierarchical. All that stuff is big. It's amazing that the brain instantly just does all that. The idea that there's water, it's liquid, and the idea that you can drink it when you're thirsty, the idea that there's brands. And then there's like all of that information is instantly built into the whole thing once you proceed. So I wanted to get back to your point about hierarchical representation. The world itself is hierarchical, right? And I can take this microphone in front of me. I know inside there's gonna be some electronics. I know there's gonna be some wires and I know there's gonna be a little diaphragm that moves back and forth. I don't see that, but I know it. So everything in the world is hierarchical. Just go into a room, it's composed of other components. The kitchen has a refrigerator. The refrigerator has a door. The door has a hinge. The hinge has screws and pins. So anyway, the modeling system that exists in every cortical column learns the hierarchical structure of objects. So it's a very sophisticated modeling system in this grain of rice. It's hard to imagine, but this grain of rice can do really sophisticated things. It's got 100,000 neurons in it. It's very sophisticated. So that same mechanism that can model a water bottle or a coffee cup can model conceptual objects as well. That's the beauty of this discovery that this guy Vernon Mouncastle made many, many years ago, which is that there's a single cortical algorithm underlying everything we're doing. So common sense concepts and higher level concepts are all represented in the same way? They're set in the same mechanisms. It's a little bit like computers. All computers are universal Turing machines. Even the little teeny one that's my toaster and the big one that's running some cloud server someplace. They're all running on the same principle. They can apply different things. So the brain is all built on the same principle. It's all about learning these models, structured models using movement and reference frames. And it can be applied to something as simple as a water bottle and a coffee cup. And it can be applied to thinking like what's the future of humanity and why do you have a hedgehog on your desk? I don't know. Nobody knows. Well, I think it's a hedgehog. That's right, it's a hedgehog in the fog. It's a Russian reference. Does it give you any inclination or hope about how difficult it is to engineer common sense reasoning? So how complicated is this whole process? So looking at the brain, is this a marvel of engineering or is it pretty dumb stuff stacked on top of each other over and over? A pretty extensive copy. Can it be both? Can it be both, right? I don't know if it can be both because if it's an incredible engineering job, that means it's, so evolution did a lot of work. Yeah, but then it just copied that. So as I said earlier, figuring out how to model something, like a space, is really hard. And evolution had to go through a lot of trick. And these cells I was talking about, these bridge cells and place cells, they're really complicated. This is not simple stuff. This neural tissue works on these really unexpected, weird mechanisms. But it did it. It figured it out. But now you can just make lots of copies of it. But then finding, yeah, so it's a very interesting idea that it's a lot of copies of a basic mini brain. But the question is how difficult it is to find that mini brain that you can copy and paste effectively. Today, we know enough to build this. I'm sitting here with, I know the steps we have to go. There's still some engineering problems to solve, but we know enough. And this is not like, oh, this is an interesting idea. We have to go think about it for another few decades. No, we actually understand it pretty well details. So not all the details, but most of them. So it's complicated, but it is an engineering problem. So in my company, we are working on that. We are basically laid out a roadmap, how we do this. It's not gonna take decades. It's better a few years, optimistically, but I think that's possible. It's complex things. If you understand them, you can build them. So in which domain do you think it's best to build them? Are we talking about robotics, like entities that operate in the physical world that are able to interact with that world? Are we talking about entities that operate in the digital world? Are we talking about something more specific, like is done in the machine learning community, where you look at natural language or computer vision? Where do you think is easiest to- It's the first two more than the third one, I would say. Again, let's just use computers as an analogy. The pioneers in computing, people like John van Norman on Turing, they created this thing, we now call the universal Turing machine, which is a computer, right? Did they know how it was gonna be applied, where it was gonna be used? Could they envision any of the future? No, they just said, this is a really interesting computational idea about algorithms and how you can implement them in a machine. And we're doing something similar to that today. We are building this universal learning principle that can be applied to many, many different things. But the robotics piece of that, the interactive elements. Let's be specific. You can think of this cortical column as what we call a sensory motor learning system. It has the idea that there's a sensor, and then it's moving. That sensor can be physical. It could be like my finger, and it's moving in the world. It could be like my eye, and it's physically moving. It can also be virtual. So it could be, an example would be, I could have a system that lives in the internet that actually samples information on the internet and moves by following links. That's a sensory motor system. So. Something that echoes the process of a finger moving along a cortical column. But in a very, very loose sense. It's like, again, learning is inherently about discovering the structure of the world and discovering the structure of the world, you have to move through the world. Even if it's a virtual world. Even if it's a conceptual world. You have to move through it. You don't, it doesn't exist in one, it has some structure to it. So, here's a couple of predictions of getting what you're talking about. In humans, the same algorithm does robotics, right? It moves my arms, my eyes, my body, right? And so, in the future, to me, robotics and AI will merge. They're not gonna be separate fields, because they're gonna, algorithms for really controlling robots are gonna be the same algorithms we have in our brain, at these sensory motor algorithms. Today we're not there, but I think that's gonna happen. And then, so, but not all AI systems will be robotics. You can have systems that have very different types of embodiments. Some will have physical movements, some will not have physical movements. It's a very generic learning system. Again, it's like computers, the Turing machine is like, doesn't say how it's supposed to be implemented, doesn't tell you how big it is, doesn't tell you what you can apply it to, but it's an interesting, it's a computational principle. Cortical column equivalent is a computational principle about learning, it's about how you learn, and it can be applied to a gazillion things. This is what, I think this is, I think this impact of AI is gonna be as large, if not larger, than computing has been in the last century, by far. Because it's getting at a fundamental thing. It's not a vision system or a learning system. It's a, it's not a vision system or a hearing system. It is a learning system. It's a fundamental principle, how you learn to structure in the world, how you can gain knowledge and be intelligent. And that's what the thousand brains says is going on. And we have a particular implementation in our head, but it doesn't have to be like that at all. Do you think there's going to be some kind of impact? Okay, let me ask it another way. What do increasingly intelligent AI systems do with us humans in the following way? Like, how hard is the human in the loop problem? How hard is it to interact the finger on the coffee cup equivalent of having a conversation with a human being? So how hard is it to fit into our little human world? I think it's a lot of engineering problems. I don't think it's a fundamental problem. I could ask you the same question. How hard is it for computers to fit into a human world? Right, I mean, that's essentially what I'm asking. Like, how much are we elitist, are we as humans? Like, we try to keep out systems. I don't know. I'm not sure I think, I'm not sure that's the right question. Let's look at computers as an analogy. Computers are a million times faster than us. They do things we can't understand. Most people have no idea what's going on when they use computers, right? How do we integrate them in our society? Well, we don't think of them as their own entity. They're not living things. We don't afford them rights. We rely on them. Our survival as a seven billion people or something like that is relying on computers now. Don't you think that's a fundamental problem that we see them as something we don't give rights to? So like, yeah, computers. So robots, computers, intelligent systems, it feels like for them to operate successfully, they would need to have a lot of the elements that we would start having to think about, like, should this entity have rights? I don't think so. I think it's tempting to think that way. First of all, I don't think anyone, hardly anyone thinks that's for computers today. No one says, oh, this thing needs a right. I shouldn't be able to turn it off or if I throw it in the trash can and hit it with a sledgehammer, I might form a criminal act. No, no one thinks that. And now we think about intelligent machines, which is where you're going, and all of a sudden, like, well, now we can't do that. I think the basic problem we have here is that people think intelligent machines will be like us. They're gonna have the same emotions as we do, the same feelings as we do. What if I can build an intelligent machine that absolutely could care less about whether it was on or off or destroyed or not? It just doesn't care. It's just like a map. It's just a modeling system. It has no desires to live, nothing. Is it possible to create a system that can model the world deeply and not care about whether it lives or dies? Absolutely, no question about it. To me, that's not 100% obvious. It's obvious to me, so we can debate it if you want. Where does your desire to live come from? It's an old evolutionary design. I mean, we could argue, does it really matter if we live or not? Objectively, no, right? We're all gonna die eventually. But evolution makes us wanna live. Evolution makes us wanna fight to live. Evolutionists wanna care and love one another and to care for our children and our relatives and our family and so on. And those are all good things. But they come about not because we're smart, because we're animals that grew up. The hummingbird in my backyard cares about its offspring. Every living thing in some sense cares about surviving. But when we talk about creating intelligent machines, we're not creating life. We're not creating evolving creatures. We're not creating living things. We're just creating a machine that can learn really sophisticated stuff. And that machine, it may even be able to talk to us. But it's not gonna have a desire to live unless somehow we put it into that system. Well, there's learning, right? The thing is. But you don't learn to wanna live. It's built into you. It's hard to explain. People like Ernest Becker argue, so okay, there's the fact of finiteness of life. The way we think about it is something we learn, perhaps. So, okay. Yeah, and some people decide they don't wanna live. And some people decide, you know, you can. But the desire to live is built in DNA, right? But I think what I'm trying to get to is in order to accomplish goals, it's useful to have the urgency of mortality. So what the Stoics talked about is meditating in your mortality. It might be a very useful thing to do to die and have the urgency of death and to realize that to conceive yourself as an entity that operates in this world that eventually will no longer be a part of this world and actually conceive of yourself as a conscious entity might be very useful for you to be a system that makes sense of the world. Otherwise, you might get lazy. Well, okay. We're gonna build these machines, right? So are we talking about building AI? But we're building the equivalent of the cortical columns, the- The neocortex. The neocortex. And the question is, where do they arrive at? Because we're not hard coding everything in. Well, in terms of, if you build the neocortex equivalent, it will not have any of these desires or emotional states. Now, you can argue that that neocortex won't be useful unless I give it some agency, unless I give it some desire, unless I give it some motivation. Otherwise, you'll be as lazy and do nothing, right? You could argue that. But on its own, it's not gonna do those things. It's just not gonna sit there and say, I understand the world, therefore, I care to live. No, it's not gonna do that. It's just gonna say, I understand the world. Why is that obvious to you? Why don't, do you think it's, okay, let me ask it this way. Do you think it's possible it will at least assign to itself agency and perceive itself in this world as being a conscious entity as a useful way to operate in the world and to make sense of the world? I think intelligent machine can be conscious, but that does not, again, imply any of these desires and goals that you're worried about. We can talk about what it means for an intelligent machine to be conscious. And by the way, not worry about, but get excited about. It's not necessarily that we should worry about it. So I think there's a legitimate problem, or not problem, a question to ask. If you build this modeling system, what's it gonna model? Yes. Right, what's its desire? What's its goal? What are we applying it to, right? So that's an interesting question. One thing, and it depends on the application. It's not something that's inherent to the modeling system. It's something we apply to the modeling system in a particular way. So if I wanted to make a really smart car, it would have to know about driving and cars and what's important in driving and cars. It's not gonna figure that out on its own. It's not gonna sit there and say, you know, I've understood the world, and I've decided, no, no, no, no. We're gonna have to tell it. We're gonna have to say, so imagine I make this car really smart. It learns about your driving habits. It learns about the world. And it's just, is it one day gonna wake up and say, you know what, I'm tired of driving and doing what you want. I think I have better ideas about how to spend my time. Okay. No, it's not gonna do that. Well, part of me is playing a little bit of devil's advocate but part of me is also trying to think through this because I've studied cars quite a bit and I've studied pedestrians and cyclists quite a bit. And there's part of me that thinks that there needs to be more intelligence than we realize in order to drive successfully. That game theory of human interaction seems to require some deep understanding of human nature. Okay, when a pedestrian crosses the street, there's some sense, they look at a car usually, and then they look away. There's some sense in which they say, I believe that you're not going to murder me. You don't have the guts to murder me. This is the little dance of pedestrian car interaction is saying, I'm gonna look away and I'm gonna put my life in your hands because I think you're human, you're not gonna kill me. And then the car, in order to successfully operate in Manhattan streets, has to say, no, no, no, no, I am going to kill you, like a little bit. There's a little bit of this weird inkling of mutual murder and that's the dance and we somehow successfully operate through that. Do you think you were born with that or how did you learn that social interaction? I think it might have a lot of the same elements that you're talking about, which is we're leveraging things we were born with and applying them in the context that- I would have said that that kind of interaction is learned because people in different cultures to have different interactions like that. If you cross the street in different cities and different parts of the world, they have different ways of interacting. I would say that's learned and I would say an intelligence system can learn that too. But that does not lead, and the intelligence system can understand humans. It could understand that, just like I can study an animal and learn something about that animal. I could study apes and learn something about their culture and so on. I don't have to be an ape to know that. I may not be completely, but I can understand something. So intelligence machine can model that. That's just part of the world. It's just part of the interactions. The question we're trying to get at, will the intelligence machine have its own personal agency that's beyond what we assigned to it or its own personal goals, or will it evolve and create these things? My confidence comes from understanding the mechanisms I'm talking about creating. This is not hand-wavy stuff. It's down to the details. I'm gonna build it and I know what it's gonna look like and I know what's it gonna behave. I know what the kind of things it could do and the kind of things it can't do. Just like when I build a computer, I know it's not gonna on its own decide to put another register inside of it. It can't do that. No way. No matter what your software does, it can't add a register to the computer. So in this way, when we build AI systems, we have to make choices about how we embed them. So I talk about this in the book. I said, you know, intelligence system is not just the neocortex equivalent. You have to have that, but it has to have some kind of embodiment, physical or virtual. It has to have some sort of goals. It has to have some sort of ideas about dangers, about things it shouldn't do. Like, you know, like we build in safeguards into systems. We have them in our bodies. We have put them in the cars, right? My car follows my directions until the day it sees I'm about to hit something and it ignores my directions and puts the brakes on. So we can build those things in. So that's a very interesting problem, how to build those in. I think my differing opinion about the risks of AI for most people is that people assume that somehow those things will just appear automatically or they'll evolve. And intelligence itself begets that stuff or requires it, but it's not. Intelligence of the neocortex equivalent doesn't require this. The neocortex equivalent just says, I'm a learning system. Tell me what you want me to learn. And I'll tell you, ask me questions. I'll tell you the answers. But in that, again, it's again like a map. It doesn't, a map has no intent about things, but you can use it to solve problems. Okay, so the building engineering the neocortex in itself is just creating an intelligent prediction system. Modeling system. Sorry, a modeling system. Yeah. You can use it to then make predictions, but you can also put it inside a thing that's actually acting in this world. You have to put it inside something. Again, think of the map analogy, right? A map on its own doesn't do anything. Right. It's just inert. It's just that you can learn, but it's just inert. So we have to embed it somehow in something to do something. So what's your intuition here? You had a conversation with Sam Harris recently that was sort of, you've had a bit of a disagreement and you're sticking on this point. You know, Elon Musk, Stuart Russell kind of have us worry existential threats of AI. What's your intuition? Why, if we engineer increasingly intelligent neocortex type of system in the computer, why that shouldn't be a thing that we worry about? It was interesting, you used the word intuition and Sam Harris used the word intuition too. And when he used that word, I immediately stopped and said, oh, that's the cusp of the problem. He's using intuition. I'm not speaking about my intuition. I'm speaking about something I understand, something I'm gonna build, something I am building, something I understand completely, or at least well enough to know what I'm guessing. I know what this thing's gonna do. And I think most people who are worried, they have trouble separating out, they don't have the knowledge or the understanding about like what is intelligence? How's it manifest in the brain? How's it separate from these other functions in the brain? And so they imagine it's gonna be human-like or animal-like. It's gonna have the same sort of drives and emotions we have, but there's no reason for that. That's just because there's an unknown. If the unknown is like, oh my God, I don't know what this is gonna do. We have to be careful. It could be like us, but really smarter. I'm saying, no, it won't be like us. It'll be really smart, but it won't be like us at all. But I'm coming from that not because I'm just guessing. I'm not using intuition. I'm basing it on like, okay, I understand this thing works. This is what it does. Let me explain it to you. Okay, but to push back, so I also disagree with the intuitions that Sam has, but I also disagree with what you just said, which what's a good analogy? So if you look at the Twitter algorithm in the early days, just recommender systems, you can understand how recommender systems work. What you can't understand in the early days is when you apply that recommender system at scale to thousands and millions of people, how that can change societies. So the question is, yes, you're just saying this is how an engineer in your cortex works, but when you have a very useful TikTok type of service that goes viral, when your neural cortex goes viral and then millions of people start using it, can that destroy the world? No, well, first of all, this is back, one thing I want to say is that AI is a dangerous technology. I'm not denying that. All technology is dangerous. Well, and AI maybe particularly so. Okay, so am I worried about it? Yeah, I'm totally worried about it. The thing where, the narrow component we're talking about now is the existential risk of AI, right? So I want to make that distinction because I think AI can be applied poorly. It can be applied in ways that people are going to understand the consequences of it. These are all potentially very bad things, but they're not the AI system creating this existential risk on its own. And that's the only place I disagree with other people. Right, so I think the existential risk thing is, humans are really damn good at surviving. So to kill off the human race, it'd be very, very difficult. Yes, but you can even, I'll go further. I don't think AI systems are ever going to try to. I don't think AI systems are ever going to like say, I'm going to ignore you, I'm going to do what I think is best. I don't think that's going to happen, at least not in the way I'm talking about it. So the Twitter recommendation algorithm is an interesting example. Let's use computers as an analogy again, right? I build a computer, it's a universal computing machine. I can't predict what people are going to use it for. They can build all kinds of things. They can even create computer viruses. It's all kinds of stuff. So there's some unknown about its utility and about where it's going to go. But on the other hand, I pointed out that once I build a computer, it's not going to fundamentally change how it computes. It's like, I used the example of a register, which is an internal part of a computer. I say it can't just sit there, because computers don't evolve. They don't replicate, they don't evolve. The physical manifestation of the computer itself is not going to, there's certain things it can't do. So we can break into things like, things that are possible to happen we can't predict, and things that are just impossible to happen. Unless we go out of our way to make them happen, they're not going to happen unless somebody makes them happen. Yeah, so there's a bunch of things to say. One is the physical aspect, which you're absolutely right. We have to build a thing for it to operate in the physical world, and you can just stop building them the moment they're not doing the thing you want them to do. Or just change the design. Or change the design. The question is, I mean, it's possible in the physical world, this is probably longer term, is you automate the building. It makes a lot of sense to automate the building. There's a lot of factories that are doing more and more and more automation to go from raw resources to the final product. It's possible to imagine that it's obviously much more efficient to create a factory that's creating robots that do something, that do something extremely useful for society. It could be personal assistants, it could be your toaster, but a toaster that has deeper knowledge of your culinary preferences. And that could get destroyed. I think now you've hit on the right thing. The real thing we need to be worried about, Lex, is self-replication. Right. That is the thing that we're worried about. In the physical world. Yeah, or even the virtual world. Self-replication, because self-replication is dangerous. It's probably more likely to be killed by a virus, or a human-engineered virus. Anybody can create, the technology's getting to almost anybody, well, not anybody, but a lot of people could create a human-engineered virus that could wipe out humanity. That is really dangerous. No intelligence required. Just self-replication. So we need to be careful about that. So when I think about AI, I'm not thinking about robots building robots. Don't do that. Don't build a, you know, just. Well, that's because you're interested in creating intelligence. It seems like self-replication is a good way to make a lot of money. Well, fine, but so is, maybe editing viruses is a good way too. I don't know. The point is, as a society, when we want to look at existential risks, the existential risks we face that we can control almost all evolve around self-replication. Yes. The question is, I don't see a good way to make a lot of money by engineering viruses and deploying them on the world. There could be applications that are useful. But let's separate out, let's separate out, I mean, you don't need to. You only need some, you know, terrorists who want to do it, because it doesn't take a lot of money to make viruses. Let's just separate out what's risky and what's not risky. I'm arguing that the intelligence side of this equation is not risky. It's not risky. It's not risky at all. It's the self-replication side of the equation that's risky. And I'm not dismissing that. I'm scared as hell. It's like the paperclip maximizer thing. Those are often talked about in the same conversation. I think you're right. Like creating ultra-intelligent, super-intelligent systems is not necessarily coupled with a self-replicating, arbitrarily self-replicating systems. Yeah, and you don't get evolution unless you're self-replicating. Yeah. And so I think that's the gist of this argument, that people have trouble separating those two out. They just think, oh, yeah, intelligence looks like us. And look at the damage we've done to this planet. Look how we've, you know, destroyed all these other species. Yeah, well, we replicate. We have eight billion of us or seven billion of us now. I think the idea is that the more intelligent we're able to build systems, the more tempting it becomes from a capitalist perspective of creating products, the more tempting it becomes to create self-reproducing systems. All right, so let's say that's true. So does that mean we don't build intelligent systems? No, that means we regulate, we understand the risks. We regulate them. You know, look, there's a lot of things we could do to a society which have some sort of financial benefit to someone which could do a lot of harm. And we have to learn how to regulate those things. We have to learn how to deal with those things. I will argue this. I would say the opposite. I would say having intelligent machines at our disposal will actually help us in the end more because it'll help us understand these risks better. It'll help us mitigate these risks better. There might be ways of saying, oh, well, how do we solve climate change problems? You know, how do we do this or how do we do that? That just like computers are dangerous in the hands of the wrong people, but they've been so great for so many other things, we live with those dangers. And I think we have to do the same with intelligent machines, but we have to be constantly vigilant about this idea of A, bad actors doing bad things with them, and B, don't ever, ever create a self-replicating system. And by the way, I don't even know if you could create a self-replicating system that uses a factory that's really dangerous. You know, nature's way of self-replicating is so amazing. You know, it doesn't require anything. It just, you know, the thing and resources and it goes, right? Yeah. If I said to you, you know what, we have to build, our goal is to build a factory that can make, that builds new factories, and it has to end to end supply chain. It has to mine the resources, get the energy. I mean, that's really hard. You know, no one's doing that in the next, you know, a hundred years. I've been extremely impressed by the efforts of Elon Musk and Tesla to try to do exactly that. Not from raw resource. Well, he actually, I think states, the goal is to go from raw resource to the final car in one factory. Yeah. And that's the main goal. Of course, it's not currently possible, but they're taking huge leaps. Well, he's not the only one to do that. This has been a goal for many industries for a long, long time. It's difficult to do. Well, a lot of people, what they do is instead, they have like a million suppliers and then they like, there's everybody's manufacturing. Co-locate them and they tie the systems together. It's a fundamentally distributed system. I think that's, that also is not getting at the issue I was just talking about, which is self-replication. It's, I mean, self-replication means there's no entity involved other than the entity that's replicating. Right. And so if there are humans in the loop, that's not really self-replicating, right? It's unless somehow we're duped into doing it. But it's also, I don't necessarily agree with you because you've kind of mentioned that AI will not say no to us. I just think. They will, yeah. So like, I think it's a useful feature to build in. I'm just trying to like put myself in the mind of engineers to sometimes say no. You know, if you. Yeah, well, I mean, I gave the example earlier, right? I gave the example of my car. Yeah. Right, my car turns the wheel and applies the accelerator and the brake, as I say, until it decides there's something dangerous. Yes. And then it doesn't do that. Yeah. Now, that was something it didn't decide to do. It's something we programmed into the car. And so good, it's a good idea, right? The question again isn't like, well, if we create an intelligent system, will it ever ignore our commands? Of course it will sometimes. Is it gonna do it because it came up with its own goals that serve its purposes and it doesn't care about our purposes? No, I don't think that's gonna happen. Okay, so let me ask you about these super intelligent cortical systems that we engineer and us humans. Do you think with these entities operating out there in the world, what does the future, most promising future look like? Is it us merging with them? Or is it us, like how do we keep us humans around when we have increasingly intelligent beings? Is it one of the dreams is to upload our minds in the digital space? So can we just give our minds to these systems so they can operate on them? Is there some kind of more interesting merger or is there more just communication? So in the third part of my book, I talked about all these scenarios and let me just walk through them. Sure. The uploading the mind one. Yes. Extremely, really difficult to do. Like we have no idea how to do this even remotely right now. So it would be a very long way away, but I make the argument you wouldn't like the result. And you wouldn't be pleased with the result. It's really not what you think it's gonna be. Imagine I could upload your brain into a computer right now. And now the computer's sitting there going, hey, I'm over here. Great, get rid of that old bio person. I don't need him. You're still sitting here. Yeah. What are you gonna do? No, no, that's not me. I'm here, right? Yeah. Are you gonna feel satisfied in that? Then you, but people imagine, look, I'm on my deathbed and I'm about to expire and I push the button and I'm uploaded. But think about it a little differently. And so I don't think it's gonna be a thing because people, by the time we're able to do this, if ever, because you have to replicate the entire body, not just the brain. It's really, I walked through the issues. It's really substantial. Do you have a sense of what makes us us? Is there a shortcut to what can only save a certain part that makes us truly us? No, but I think that machine would feel like it's you too. Right. Right? You have two people, just like I have a child, right? I have two daughters. They're independent people. I created them, well, partly. Yeah. I don't, just because they're somewhat like me, I don't feel on them and they don't feel like on me. So if you split them apart, you have two people. So we can come back to what makes, what consciousness do you want? We can talk about that. But we don't have a remote consciousness. I'm not sitting there going, oh, I'm conscious of that. I'm in that system over there. So let's stay on our topic here. One was uploading a brain. Ain't gonna happen in a hundred years, maybe a thousand, but I don't think people are gonna want to do it. The merging your mind with the neural link thing, right? Like, again, really, really difficult. It's one thing to make progress to control a prosthetic arm. It's another to have like a billion or several billion things and understanding what those signals mean. Like it's the one thing that like, okay, I can learn to think some patterns to make something happen. It's quite another thing to have a system, a computer, which actually knows exactly which cells it's talking to and how it's talking to them and interacting in a way like that. Very, very difficult. We're not getting anywhere closer to that. Interesting. Can I ask a question here? Yeah. So for me, what makes that merger very difficult practically in the next 10, 20, 50 years is like literally the biology side of it, which is like, it's just hard to do that kind of surgery in a safe way. But your intuition is even the machine learning part of it, where the machine has to learn what the heck it's talking to, that's even hard. I think it's even harder. And it's not, it's easy to do when you're talking about hundreds of signals. It's a totally different thing to say, talking about billions of signals. So you don't think it's the raw, it's a machine learning problem. You don't think it could be learned? Well, I'm just saying, no, I think you'd have to have detailed knowledge. You'd have to know exactly what the types of neurons you're connecting to. I mean, in the brain, there's these, the neurons do all different types of things. It's not like a neural network. It's a very complex organism system up here. We talked about the grid cells and the place cells. You have to know what kind of cells you're talking to and what they're doing and how their timing works and all this stuff, which you can't, today there's no way of doing that. But I think it's, I think the problem, you're right that the biological aspect of it, like who wants to have a surgery and have this stuff inserted in your brain, that's a problem. But let's assume we solve that problem. I think the information coding aspect is much worse. I think that's much worse. It's not like what they're doing today. Today, it's simple machine learning stuff because you're doing simple things. But if you want to merge your brain, like I'm thinking on the internet, I'm merge my brain with the machine and we're both doing, that's a totally different issue. That's interesting. I tend to think if, okay, yeah, if you have a super clean signal from a bunch of neurons, at the start, you don't know what those neurons are. I think that's much easier than the getting of the clean signal. I think if you think about today's machine learning, that's what you would conclude. I'm thinking about what's going on in the brain and I don't reach that conclusion. So we'll have to see. But I don't think, even then, I think there's kind of a sad future. Do I have to plug my brain into a computer? I'm still a biological organism. I assume I'm still gonna die. So what have I achieved? What have I achieved in doing some sort of? Oh, I disagree. We don't know what those are, but it seems like there could be a lot of different applications. It's like virtual reality. Is to expand your brain's capability to read Wikipedia. Yeah, but fine, but you're still a biological organism. Yes, yes. You're still mortal. You're still all of that, all of those things. What are you accomplishing? You're making your life in this short period of time better, right? Just like having the internet made our life better. Yeah, yeah. Yeah, okay. I think that's, if I think about all the possible gains we can have here, that's a marginal one. It's an individual, hey, I'm better. You know, I'm smarter. But you'll find, I'm not against it. I just don't think it's earth-changing. But, so this is the truth of the internet. When each of us individuals are smarter, we get a chance to then share our smartness. We get smarter and smarter together as a collective. This is kind of like this ant colony of intelligence. But why don't I just create an intelligent machine that doesn't have any of this biological nonsense? That has all the same, it's everything except don't burden it with my brain. Yeah. Right, it has a brain. It is smart. It's like my child, but it's much, much smarter than me. So I have a choice between doing some implant, doing some hybrid weird biological thing that's bleeding and all these problems and limited by my brain, or creating a system which is super smart that I can talk to that helps me understand the world, that can read Wikipedia and talk to me. I guess the open questions there are what does the manifestation of super intelligence look like? So what are we going to, you talked about why do I want to merge with AI. What's the actual marginal benefit here? If we have a super intelligent system, how will it make our life better? So that's a great question, but let's break it down to little pieces. On the one hand, it can make our life better in lots of simple ways. You mentioned a care robot or something that helps me do things. A cook, I don't know what it does, right? Little things like that. We can have better, smarter cars. We can have better agents, aides helping us in our work environment and things like that. To me, that's the easy stuff, the simple stuff in the beginning. And so in the same way that computers made our lives better in ways, many, many ways, we'll have those kind of things. To me, the really exciting thing about AI is sort of its transcendent quality in terms of humanity. We're still biological organisms. We're still stuck here on earth. It's going to be hard for us to live anywhere else. I don't think you and I are going to want to live on Mars anytime soon. And we're flawed. We may end up destroying ourselves. It's totally possible. If not completely, we could destroy our civilizations. Let's face the fact, we have issues here, but we can create intelligent machines that can help us in various ways. For example, one example I gave, and that sounds a little sci-fi, but I believe this. If we really wanted to live on Mars, we'd have to have intelligent systems that go there and build the habitat for us, not humans. Humans are never going to do this. It's just too hard. But could we have 1,000 or 10,000 engineering workers up there doing this stuff, building things, terraforming Mars? Sure, maybe we can move to Mars. Maybe we can move to Mars. But then if we want to go around the universe, should I send my children around the universe or should I send some intelligent machine, which is like a child, that represents me and understands our needs here on Earth that could travel through space? So it's sort of, in some sense, intelligence allows us to transcend the limitations of our biology. And don't think of it as a negative thing. It's in some sense, my children transcend my biology too, because they live beyond me. And they represent me, and they also have their own knowledge, and I can impart knowledge to them. So intelligent machines will be like that too, but not limited like us. But the question is, there's so many ways that transcendence can happen. And the merger with AI and humans is one of those ways. So you said intelligent, basically, beings or systems propagating throughout the universe, representing us humans. They represent us humans in the sense they represent our knowledge and our history, not us individually. Right, right. But I mean, the question is, is it just a database with a really damn good model? No, no, they're conscious just like us. Okay, but just different. They're different, just like my children are different. They're like me, but they're different. These are more different. I guess maybe I've already, I kind of, I take a very broad view of our life here on Earth. I say, you know, why are we living here? Are we just living because we live? Are we surviving because we can survive? Are we fighting just because we want to just keep going? What's the point of it? Right? So to me, the point, if I were to ask myself, what's the point of life? What transcends that ephemeral sort of biological experience is, to me, this is my answer, is the acquisition of knowledge, to understand more about the universe and to explore. And that's partly to learn more, right? I don't view it as a terrible thing if the ultimate outcome of humanity is we create systems that are intelligent, that are our offspring, but they're not like us at all. And we stay here and live on Earth as long as we can, which won't be forever, but as long as we can, but that would be a great thing to do. It's not like a negative thing. Well, would you be okay then if the human species vanishes, but our knowledge is preserved and keeps being expanded by intelligent systems? I want our knowledge to be preserved and expanded. Yeah. Am I okay with humans dying? No, I don't want that to happen. But if it does happen, what if we were sitting here and we were the last two people on Earth and we're saying, Lex, we blew it, it's all over, right? Wouldn't I feel better if I knew that our knowledge was preserved and that we had agents that knew about that, that left Earth? I would want that. It's better than not having that. I make the analogy of the dinosaurs. The poor dinosaurs, they lived for tens of millions of years. They raised their kids. They fought to survive. They were hungry. They did everything we do, and then they're all gone. Yeah. And if we didn't discover their bones, nobody would ever know that they ever existed, right? Do we wanna be like that? I don't wanna be like that. There's a sad aspect to it, and it's kinda, it's jarring to think about that it's possible that a human-like intelligent civilization has previously existed on Earth. Oh, yeah. The reason I say this is like, it is jarring to think that we would not, if they went extinct, we wouldn't be able to find evidence of them. After a sufficient amount of time. After a sufficient amount of time. Of course, there's like, like basically humans, like if we destroy ourselves now, human civilization destroy ourselves now, after a sufficient amount of time, we would not be, we'd find evidence of the dinosaurs. We would not find evidence of us humans. Yeah, that's kind of an odd thing to think about, although I'm not sure if we have enough knowledge about species going back for billions of years, but we might be able to eliminate that possibility. But it's an interesting question. Of course, this is a similar question to, you know, there were lots of intelligent species throughout our galaxy that have all disappeared. Yeah, that's super sad that they're, exactly, that there may have been much more intelligent alien civilizations in our galaxy that are no longer there. Yeah. You actually talked about this, that humans might destroy ourselves and how we might preserve our knowledge and advertise that knowledge to other. Advertise is a funny word to use. From a PR perspective. There's no financial gain in this. You know, like make it like, from a tourism perspective, make it interesting. Can you describe how you think about this problem? I broke it down into two parts, actually three parts. One is, you know, there's a lot of things we know that, what if we ended, what if our civilization collapsed? Yeah, I'm not talking tomorrow. Yeah, we could be a thousand years from now, like, so, you know, we don't really know. But historically, it would be likely at some point. Time flies when you're having fun. Yeah, that's a good way to put it. You know, could we, and then intelligent life evolved again on this planet. Wouldn't they want to know a lot about us and what we knew? Wouldn't they be able to ask us questions? So one very simple thing I said, how would we archive what we know? That was a very simple idea. I said, you know what, that wouldn't be that hard. Put a few satellites, you know, going around the sun and we'd upload Wikipedia every day and that kind of thing. So, you know, if we end up killing ourselves, well, it's up there and the next intelligence piece will find it and learn something. They would like that. They would appreciate that. So that's one thing. The next thing I said, well, what if, you know, how outside of our solar system? We have the SETI program. We're looking for these intelligence signals from everybody. And if you do a little bit of math, which I did in the book, and you say, well, what if intelligent species only live for 10,000 years before, you know, technologically intelligent species, like ones are really able to do the stuff we're just starting to be able to do. Well, the chances are we wouldn't be able to see any of them because they would have all been disappeared by now. They've lived for 10,000 years and now they're gone. And so we're not gonna find these signals being sent from these people because, but I said, what kind of signal could you create that would last a million years or a billion years? That someone would say, damn it, someone smart lived there. We know that. That would be a life-changing event for us to figure that out. Well, what we're looking for today in the SETI program isn't that. We're looking for very coded signals in some sense. And so I asked myself, what would be a different type of signal one could create? I've always thought about this throughout my life. And in the book, I gave one possible suggestion, which was we now detect planets going around other suns, other stars, excuse me. And we do that by seeing this slight dimming of the light as the planets move in front of them. That's how we detect planets elsewhere in our galaxy. What if we created something like that, that just rotated around the sun and it blocked out a little bit of light in a particular pattern that someone said, hey, that's not a planet. That is a sign that someone was once there. You can think, what if it's beating up pi, you know, three point whatever. So I did- From a distance, you can- From a distance, broadly broadcast, takes no continual activation on our part. This is the key, right? No one has to be sitting there running a computer and supplying it with power. It just goes on. So we go, it's continuous. And I argued that part of the SETI program should be looking for signals like that. And to look for signals like that, you ought to figure out how would we create a signal? Like, what would we create that would be like that, that would persist for millions of years, that would be broadcast broadly, that you could see from a distance, that was unequivocal, came from an intelligent species. And so I gave that one example, because they don't know what I know of, actually. And then finally, right, if ultimately our solar system will die at some point in time, how do we go beyond that? And I think it's possible, if at all possible, we'll have to create intelligent machines that travel throughout the solar system or throughout the galaxy. And I don't think that's gonna be humans. I don't think it's gonna be biological organisms. So these are just things to think about. What's the, I don't wanna be like the dinosaur. I don't wanna just live and, okay, that was it, we're done. Well, there is a kind of presumption that we're gonna live forever, which I think it is a bit sad to imagine that the message we send as you talk about is that we were once here instead of we are here. Well, it could be we are still here, but it's more of an insurance policy in case we're not here. I don't know, but there is something, I think about, we as humans don't often think about this, but it's like whenever I record a video, I've done this a couple of times in my life, I've recorded a video for my future self, just for personal, just for fun. And it's always just fascinating to think about that, preserving yourself for future civilizations. For me, it was preserving myself for a future me, but that's a little fun example of archival. Well, these podcasts are preserving you and I for future, hopefully well after we're gone. But you don't often, we're sitting here talking about this. You are not thinking about the fact that you and I are going to die, and there'll be like 10 years after, somebody watching this, and we're still alive. You know, in some sense I do. I'm here because I wanna talk about ideas. And these ideas transcend me, and they transcend this time on our planet. We're talking here about ideas that could be around 1,000 years from now, or a million years from now. When I wrote my book, I had an audience in mind, and one of the clearest audiences was people. Aliens. No, were people reading this 100 years from now. Yes. I said to myself, how do I make this book relevant to someone reading this 100 years from now? What would they wanna know that we were thinking back then? What would make it like that was an interesting, it's still an interesting book. I'm not sure I could achieve that, but that was how I thought about it, because these ideas, like especially in the third part of the book, the ones we were just talking about, you know, these crazy, what sounds like crazy ideas about storing our knowledge, and merging our brains with computers, and sending our machines out into space. These are not gonna happen in my lifetime. And they may not, and they may not happen in the next 100 years. They may not happen for 1,000 years, who knows? But we have the unique opportunity right now, we, you, me, and other people like this, to sort of at least propose the agenda that might impact the future like that. That's a fascinating way to think, both writing or creating. Try to make, try to create ideas, try to create things that hold up in time. Yeah. You know, understanding how the brain works, we're gonna figure that out at once. That's it, it's gonna be figured out at once. And after that, that's the answer. And people will study that thousands of years now. We still, you know, venerate Newton and Einstein. And, you know, because ideas are exciting even well into the future, you know? Well, the interesting thing is like big ideas, even if they're wrong, are still useful. Like. Yeah, especially if they're not completely wrong. Like, right, right, right. Newton's laws are not wrong, they're just Einstein's, they're better. Right, so. So yeah, I mean, but we're talking with Newton and Einstein, we're talking about physics. I wonder if we'll ever achieve that kind of clarity about understanding like complex systems and this particular manifestation of complex systems, which is the human brain. Oh, I'm totally optimistic we can do that. I mean, we're making progress at it. I don't see any reason why we can't completely. I mean, completely understand in the sense, you know, we don't really completely understand what all the molecules in this water bottle are doing, but, you know, we have laws that sort of capture it pretty good. And so we'll have that kind of understanding. I mean, it's not like you're gonna have to know what every neuron in your brain is doing. But enough to, first of all, to build it. And second of all, to do, you know, do what physics does, which is like have concrete experiments where we can validate. We're, this is happening right now. It's not, this is not some future thing. You know, I'm very optimistic about it. I know about our work and what we're doing. We'll have to prove it to people. But I consider myself a rational person. And, you know, until fairly recently, I wouldn't have said that. But right now, where I'm sitting right now, I'm saying, you know, this is gonna happen. There's no big obstacles to it. We finally have a framework for understanding what's going on in the cortex. And that's liberating. It's like, oh, it's happening. So I can't see why we wouldn't be able to understand it. I just can't. Okay. So, I mean, on that topic, let me ask you to play devil's advocate. Is it possible for you to imagine, look 100 years from now, and looking at your book, in which ways might your ideas be wrong? Oh, I worry about this all the time. Yeah. It's still useful. Yeah. Yeah. I think there's, you know, well, I can best relate it to like things I'm worried about right now. So we talk about this voting idea, right? It's happening. There's no question it's happening. But it could be far more, there's enough things I don't know about it that it might be working in ways differently than I'm thinking about. What's voting, who's voting, you know, where are representations? I talked about, like, you have a thousand models of a coffee cup like that. That could turn out to be wrong, because it may be, maybe there are a thousand models that are sub-models, but not really a single model of the coffee cup. I mean, there's things, these are all sort of on the edges, things that I present as like, oh, it's so simple and clean. Well, it's not that. It's always gonna be more complex. And there's parts of the theory which I don't understand the complexity well. So I think the idea that the brain is a distributed modeling system is not controversial at all, right? It's not, that's well understood by many people. The question then is, are each cortical column an independent modeling system? Right. I could be wrong about that. I don't think so, but I worry about it. My intuition, not even thinking why you could be wrong, is the same intuition I have about any sort of physicist, like string theory, that we as humans desire for a clean explanation. And 100 years from now, intelligent systems might look back at us and laugh at how we try to get rid of the whole mess by having simple explanation when the reality is it's way messier. And in fact, it's impossible to understand. You can only build it. It's like this idea of complex systems and cellular automata. You can only launch the thing. You cannot understand it. Yeah, I think that the history of science suggests that's not likely to occur. The history of science suggests that, as a theorist, and we're theorists, you look for simple explanations, right? Fully knowing that whatever simple explanation you're gonna come up with is not gonna be completely correct. I mean, it can't be. I mean, it's just more complexity. But that's the role of theorists play. They give you a framework on which you now can talk about a problem and figure out, okay, now we can start digging more details. The best frameworks stick around while the details change. Again, the classic example is Newton and Einstein, right? You know, Newton's theories are still used. They're still valuable. They're still practical. They're not like wrong. Just they've been refined. Yeah, but that's in physics. It's not obvious, by the way. It's not obvious for physics either that the universe should be such that it's amenable to these simple. But it's so far it appears to be. As far as we can tell. Yeah, I mean, but as far as we could tell. But it's also an open question whether the brain is amenable to such clean theories. That's the, not the brain, but intelligence. Well, I don't know. I would take intelligence out of it. I would just say, you know, well, okay. The evidence we have suggests that the human brain is, A, at the one time, extremely messy and complex, but there's some parts that are very regular and structured. That's why we started the neocortex. It's extremely regular in its structure. And unbelievably so. And then I mentioned earlier, the other thing is it's universal abilities. It is so flexible to learn so many things. We haven't figured out what it can't learn yet. We don't know, but we haven't figured out yet. But it can learn things that it never was evolved to learn. So those give us hope. That's why I went into this field. Because I said, you know, this regular structure, it's doing this amazing number of things. There's gotta be some underlying principles that are common, and other scientists have come up with the same conclusions. And so. It's promising. It's promising. And whether the theories play out exactly this way or not, that is the role that theorists play. And so far, it's worked out well, even though maybe we don't understand all the laws of physics. But so far, it's been pretty damn useful. The ones we have, our theories are pretty useful. You mentioned that we should not necessarily be, at least to the degree that we are, worried about the existential risks of artificial intelligence, relative to human risks from human nature being an existential risk. What aspect of human nature worries you the most, in terms of the survival of the human species? I have to admit, I'm disappointed in humanity, in humans. I mean, all of us. I'm one, so I'm disappointed in myself, too. It's kind of a sad state. There's two things that disappoint me. One is how it's difficult for us to separate our rational component of ourselves from our evolutionary heritage, which is not always pretty. Rape is an evolutionary good strategy for reproduction. Murder can be at times, too. Making other people miserable at times is a good strategy for reproduction. Now that we know that, and yet we have this sort of, you and I can have this very rational discussion, talking about intelligence and brains and life and so on. It seems like it's so hard. It's such a big transition to get humans, all humans, to make the transition from, let's pay no attention to all that ugly stuff over here. Let's just focus on the interesting. What's unique about humanity is our knowledge and our intellect. But the fact that we're striving is in itself amazing. The fact that we're able to overcome that part, and it seems like we are more and more becoming successful at overcoming that part. That is the optimistic view, and I agree with you. But I worry about it. I'm not saying, I'm worrying about it. I think maybe that was your question. I still worry about it. It could end tomorrow because some terrorists could get nuclear bombs and blow us all up. Who knows, right? The other thing I'm disappointed is, and I understand it. I guess you can't really be disappointed. It's just a fact is that we're so prone to false beliefs. We have a model in our head. The things we can interact with directly, physical objects, people, that model's pretty good. And we can test it all the time. I touch something, I look at it, I talk to you, see if my model's correct. But so much of what we know is stuff I can't directly interact with. I only know because someone told me about it. And so we're prone, inherently prone, to having false beliefs because if I'm told something, how am I gonna know it's right or wrong, right? And so then we have the scientific process which says we are inherently flawed. So the only way we can get closer to the truth is by looking for contrary evidence. Yeah, like this conspiracy theory, this theory that scientists keep telling me about that the Earth is round. As far as I can tell, when I look out, it looks pretty flat to me. So yeah, there is a tension. But it's also, I tend to believe that we haven't figured out most of this thing, right? Most of nature around us is a mystery. But does that worry you? I mean, it's like, oh, that's like a pleasure. More to figure out, right? Yeah, that's exciting. But I'm saying there's going to be a lot of, quote unquote, wrong ideas. I mean, I've been thinking a lot about engineering systems like social networks and so on, and I've been worried about censorship and thinking through all that kind of stuff because there's a lot of wrong ideas. There's a lot of dangerous ideas. But then I also read history and see when you censor ideas that are wrong, now this could be small-scale censorship, like a young grad student who comes up, who raises their hand and says some crazy idea. A form of censorship could be, I shouldn't use the word censorship, but. I don't know what you mean. Just like. Like de-incentivize them from, no, no, no, no. This is the way it's been. Yeah, yeah, you're foolish, kid. Don't think that makes sense. Yeah, you're foolish. So in some sense, those wrong ideas most of the time end up being wrong, but sometimes end up being foolish. I agree with you. So I don't like the word censorship. At the very end of the book, I ended up with sort of a plea or a recommended force of action. And the best way I know how to deal with this issue that you bring up is if everybody understood as part of your upbringing in life something about how your brain works, that it builds a model of the world, how it works, how basically it builds that model of the world, and that the model is not the real world. It's just a model. And it's never gonna reflect the entire world. And it can be wrong. And it's easy to be wrong. And here's all the ways you can get a wrong model in your head, right? It's not to prescribe what's right or wrong. It's just to understand that process. If we all understood the process, and then I get together and you say, I disagree with you, Jeff. And I say, Lex, I disagree with you. That at least we understand that we're both trying to model something. We both have different information which leads to our different models. And therefore I shouldn't hold it against you, and you shouldn't hold it against me. And we can at least agree that, well, what can we look for that's common ground to test our beliefs? As opposed to so much, we raise our kids on dogma, which is this is a fact, and this is a fact, and these people are bad. And if everyone knew just to be skeptical of every belief and why and how their brains do that, I think we might have a better world. Do you think the human mind is able to comprehend reality? So you talk about creating models that are better and better. How close do you think we get to reality? So the wildest ideas is like Donald Hoffman saying, we're very far away from reality. Do you think we're getting close to reality? Well, I guess it depends on what you define reality. We have a model of the world that's very useful. For basic goals of survival. Well, for our survival and our pleasure, whatever, right? So that's useful. I mean, it's really useful. Oh, we can build planes, we can build computers, we can do these things, right? I don't know the answer to that question. I think that's part of the question we're trying to figure out, right? Like, obviously if you end up with a theory of everything, that really is a theory of everything, and all of a sudden everything comes into play and there's no room for something else, then you might feel like we have a good model of the world. Yeah, but if we have a theory of everything and somehow, first of all, you'll never be able to really conclusively say it's a theory of everything, but say somehow we are very damn sure it's a theory of everything, we understand what happened at the Big Bang and how just the entirety of the physical process, I'm still not sure that gives us an understanding of the next many layers of the hierarchy of abstractions that form. Well, also, what if string theory turns out to be true? And then you say, well, we have no reality, no modeling of what's going on in those other dimensions that are wrapped into it on each other, right? Or the multiverse, you know? I honestly don't know how, for us, for human interaction, for ideas of intelligence, how it helps us to understand that we're made up of vibrating strings that are like 10 to the whatever times smaller than us. You could probably build better weapons and better rockets, but you're not gonna be able to understand intelligence. Maybe better computers. No, you won't be able, I think it's just more purely knowledge. You might lead to a better understanding of the beginning of the universe, right? It might lead to a better understanding of, I don't know. I guess, I think the acquisition of knowledge has always been one where you pursue it for its own pleasure and you don't always know what is gonna make a difference. Yeah, you're pleasantly surprised by the weird things you find. Do you think, for the neocortex in general, do you think there's a lot of innovation to be done on the machine side? You use the computer as a metaphor quite a bit. Is there different types of computer that would help us build intelligence? I mean, what are the physical manifestations of intelligent machines? Yeah, or is it- Oh, no, it's gonna be totally crazy. We have no idea how this is gonna look out yet. You can already see this. Today, of course, we model these things on traditional computers. And now, GPUs are really popular with neural networks and so on. But there are companies coming up with fundamentally new physical substrates that are just really cool. I don't know if they're gonna work or not. But I think there'll be decades of innovation here. Yeah. Totally. Do you think the final thing will be messy, like our biology is messy? Or do you think, it's the old bird versus airplane question. Or do you think we could just build airplanes that fly way better than birds in the same way we can build electrical neural cortex? Yeah. You know, can I riff on the bird thing a bit? Because I think it's interesting. People really misunderstand this. The Wright brothers, the problem they were trying to solve was controlled flight, how to turn an airplane, not how to propel an airplane. They weren't worried about that. Interesting, yeah. They already had, at that time, there was already wing shapes, which they had from studying birds. There was already gliders that carry people. The problem was, if you put a rudder on the back of a glider and you turn it, the plane falls out of the sky. So the problem was, how do you control flight? And they studied birds. And they actually had birds in captivity. They watched birds in wind tunnels. They observed them in the wild. And they discovered the secret was the birds twist their wings when they turn. And so that's what they did on the Wright brothers' flyer. They had these sticks that you would twist the wing. And that was their innovation, not their propeller. And today, airplanes still twist their wings. We don't twist the entire wing. We just twist the tail end of it, the flaps, which is the same thing. So today's airplanes fly on the same principles as birds, which is observed by, so everyone get that analogy wrong. But let's step back from that, right? Once you understand the principles of flight, you can choose how to implement them. No one's gonna use bones and feathers and muscles, but they do have wings. And we don't flap them, we have propellers. So when we have the principles of computation that goes on to modeling the world in a brain, we understand those principles very clearly. We have choices on how to implement them. And some of them will be biological-like and some won't. But I do think there's gonna be a huge amount of innovation here. Just think about the innovation went into computers. They had to invent the transistor. They invented the silicon chip. They had to invent, you know, then just software. I mean, there's millions of things they had to do. Memory systems. We're gonna do, it's gonna be similar. Well, it's interesting that the deep learning, the effectiveness of deep learning for specific tasks is driving a lot of innovation in the hardware, which may have effects for actually allowing us to discover intelligence systems that operate very differently, or at least much bigger than deep learning. Yeah, interesting. So ultimately, it's good to have an application that's making our life better now, because the capitalist process, if you can make money, that works. I mean, the other way, I mean, Neil deGrasse Tyson writes about this, is the other way we fund science, of course, is through military conquests. So here's an interesting thing that we're doing on this regard. So we've decided, we used to have a series of these biological principles, and we can see how to build these intelligent machines, but we've decided to apply some of these principles to today's machine learning techniques. So one of the, we didn't talk about this principle, one is sparsity in the brain. Most of the neurons are inactive at any point in time, it's sparse, and the connectivity is sparse, and that's different than deep learning networks. So we've already shown that we can speed up existing deep learning networks, anywhere from 10 to a factor of 100, I mean, literally 100, and make it more robust at the same time. So this is commercially very, very valuable. And so, if we can prove this actually in the largest systems that are commercially applied today, there's a big commercial desire to do this. Well, sparsity is something that doesn't run really well on existing hardware, it doesn't really run really well on GPUs and on CPUs. And so that would be a way of sort of bringing more, more brain principles into the existing system on a commercially valuable basis. Another thing we can think we can do is we're gonna use the dendrites, models of, I talked earlier about the prediction occurring inside a neuron. That basic property can be applied to existing neural networks, and allow them to learn continuously, which is something they don't do today. And so they saw the- The dendritic spikes that you were talking about. Yeah, well, we wouldn't model them as spikes, but the idea that you have, that today's neural networks have something called a point neuron, which is a very simple model of a neuron. And by adding dendrites to them, at just one more level of complexity that's in biological systems, you can solve problems in continuous learning and rapid learning. So we're trying to take, we're trying to bring the existing field, and we'll see if we can do it. We're trying to bring the existing field of machine learning commercially along with us. You brought up this idea of keeping, paying for it commercially along with us as we move towards the ultimate goal of a true AI system. Even small innovations on neural networks are really, really exciting. Yeah. It seems like such a trivial model of the brain and applying different insights that just, even like you said, continuous learning, or making it more asynchronous, or maybe making more dynamic, or like incentivizing, making it- Or more robust, even just more robust, you know? And making it somehow much better, incentivizing sparsity somehow. Yeah. Well, if you can make things 100 times faster, then there's plenty of incentive. That's true. People are spending millions of dollars just training some of these networks now, these transformer networks. Let me ask you the big question. How, for young people listening to this today, in high school and college, what advice would you give them in terms of which career path to take, and maybe just about life in general? Well, in my case, I didn't start life with any kind of goals. When I was going to college, it was like, oh, what did I study? Well, maybe I'll do some electrical engineering stuff. I wasn't like, today you see some of these young kids are so motivated, they're gonna change the world. I was like, I'll do that, whatever. But then I did fall in love with something. Besides my wife. But I fell in love with this, like, oh my God, it would be so cool to understand how the brain works. And then I said to myself, that's the most important thing I could work on. I can't imagine anything more important, because if you understand how the brains work, you can build intelligent machines, and they could figure out all the other big questions of the world. And then I said, but I wanna understand how I work. So I fell in love with this idea, and I became passionate about it. This is a trope, people say this, but it's true. Because I was passionate about it, I was able to put up with almost so much crap. I was in that, I was that person who said, you can't do this. I was a graduate student at Berkeley when they said, you can't study this problem. No one's gonna solve this, or you can't get funded for it. Then I went in to do mobile computing, and it was like, people say, you can't do that, you can't build a cell phone. But all along, I kept being motivated, because I wanted to work on this problem. I said, I wanna understand how the brain works. I got myself, I got one lifetime, I'm gonna figure it out, do the best I can. So by having that, as you point out, Lex, it's really hard to do these things. There's so many downers along the way. So many obstacles that get in your way. I'm sitting here happy all the time, but trust me, it's not always like that. That's, I guess, the happiness, the passion is a prerequisite for surviving the whole thing. Yeah, I think so, I think that's right. And so I don't wanna sit to someone and say, you need to find a passion and do it. No, maybe you don't. But if you do find something you're passionate about, then you can follow it as far as your passion will let you put up with it. Do you remember how you found it, how the spark happened? Why, specifically for me? Yeah, like, because you said, it's such an interesting, so like, almost like later in life, by later, I mean like, not when you were five, but you didn't really know, and then all of a sudden you fell in love with it. Yeah, yeah, there was two separate events that compounded one another. One, when I was probably a teenager, might've been 17 or 18, I made a list of the most interesting problems I could think of. First was, why does the universe exist? Seems like not existing is more likely. The second one was, well, given it exists, why does it behave the way it does? You know, laws of physics, why is it equal to MC squared, not MC cubed? You know, that's an interesting question. Third one was like, what's the origin of life? And the fourth one was, what's intelligence? And I stopped there. I said, well, that's probably the most interesting one. And I put that aside as a teenager. But then when I was 22, and I was reading the, no, excuse me, I was 70, it was 1979, excuse me, 1979. I was reading, so I was, at that time I was 22. I was reading the September issue of Scientific American, which is all about the brain. And then the final essay was by Francis Crick, who of DNA fame, and he had taken his interest to studying the brain now. And he said, you know, there's something wrong here. He says, we got all this data, all this fact, this is 1979, all these facts about the brain, tons and tons of facts about the brain. Do we need more facts? Or do we just need to think about a way of rearranging the facts we have? Maybe we're just not thinking about the problem correctly. You know, he says, this shouldn't be like this, you know? So I read that and I said, wow. I said, I don't have to become like an experimental neuroscientist. I could just look at all those facts and try to, and become a theoretician and try to figure it out. And I said, that I felt like it was something I would be good at. I said, I wouldn't be a good experimentalist. I don't have the patience for it. But I'm a good thinker and I love puzzles. And this is like the biggest puzzle in the world. It's the biggest puzzle of all time. And I got all the puzzle pieces in front of me. Damn, that was exciting. And there's something, obviously, you can't convert into words, that just kind of sparked this passion. And I have that a few times in my life, just something, just like you, it grabs you. Yeah, I thought it was something that was both important and that I could make a contribution to. And so all of a sudden, I felt like, oh, it gave me purpose in life. You know? I honestly don't think it has to be as big as one of those four questions. No, no, but- I think you can find those things in the smallest. Oh, absolutely, absolutely. I'm with, David Foster Wallace said, like, the key to life is to be unboreable. I think it's very possible to find that intensity of joy in the smallest of things. Absolutely. I'm just, you asked me my story. Yeah, yeah. No, but I'm actually speaking to the audience. It doesn't have to be those four. You happen to get excited by one of the bigger questions of- Yeah. I mean, the universe, but even the smallest things. I'm watching the Olympics now. Oh, yeah. Just giving yourself life, giving your life over to the study and the mastery of a particular sport is fascinating. And if it sparks joy and passion, you're able to, in the case of the Olympics, basically suffer for like a couple of decades to achieve perfection. I mean, you can find joy and passion just being a parent. I mean, it's- Yeah, the parenting one is funny. So I was, not always, but for a long time, wanted kids and get married and stuff. And especially it has to do with the fact that I've seen a lot of people that I respect get a whole nother level of joy from kids. And at first it's like, you're thinking is, well, I don't have enough time in the day, right? If I have this passion to solve- Which is true. Which is true. Yeah, yes. But like, if I want to solve intelligence, how's this kid situation going to help me? But then you realize that, like you said, the things that sparks joy, and it's very possible that kids can provide even a greater or deeper, more meaningful joy than those bigger questions. When they enrich each other. And that seemed like, obviously when I was younger, it's probably a counterintuitive notion because there's only so many hours in the day. But then life is finite and you have to pick the things that give you joy. Yeah, but you can also, understand you can be patient too. I mean, it's finite, but we do have, whatever, 50 years or something. It's also long, yeah. So in my case, I had to give up on my dream of the neuroscience because I was a graduate student at Berkeley and they told me I couldn't do this and I couldn't get funded. And so I went back in the computing industry for a number of years. I thought it would be four, but it turned out to be more. But I said, I'll come back. I'm definitely gonna come back. I know I'm gonna do this computer stuff for a while, but I'm definitely coming back. Everyone knows that. And it's the same as like raising kids. Well, yeah, you have to spend a lot of time with your kids. It's fun, enjoyable. But that doesn't mean you have to give up on other dreams. It just means that you may have to wait a week or two to work on that next idea. Well, you talked about the darker side of me and the disappointing sides of human nature that we're hoping to overcome so that we don't destroy ourselves. I tend to put a lot of value in the broad general concept of love, of the human capacity of compassion towards each other, of just kindness, whatever that longing of just the human to human connection. It connects back to our initial discussion. I tend to see a lot of value in this collective intelligence aspect. I think some of the magic of human civilization happens when there's, a party's not as fun when you're alone. Yeah, I totally agree with you on these issues. Do you think, from a neocortex perspective, what role does love play in the human condition? Well, those are two separate things. From a neocortex point of view, I don't think it doesn't impact our thinking about the neocortex. From a human condition point of view, I think it's core. I mean, we get so much pleasure out of loving people and helping people. So, I'll rack it up to old brain stuff and maybe we can throw it under the bus of evolution if you want. That's fine. It doesn't impact how we think about how we model the world. But from a humanity point of view, I think it's essential. Well, I tend to give it to the new brain. And also, I tend to think that some aspects of that need to be engineered into AI systems, both in their ability to have compassion for other humans and their ability to maximize love in the world between humans. So, I'm more thinking about the social network. So, whenever there's a deep integration between AI systems and humans, so specific applications where it's AI and humans, I think that's something that's often not talked about in terms of metrics over which you try to maximize, like which metric to maximize in a system. It seems like one of the most powerful things in societies is the capacity to love. It's fascinating. I think it's a great way of thinking about it. I have been thinking more of these fundamental mechanisms in the brain as opposed to the social interaction between humans and AI systems in the future, which is, and I think if you think about that, you're absolutely right. But that's a complex system. I can have intelligence systems that don't have that component, but they're not interacting with people. You know, they're just running something or building some place or something, I don't know. But if you think about interacting with humans, yeah. But it has to be engineered in there. I don't think it's gonna appear on its own. That's a good question. Yeah, well, we could, we'll look at it. In terms of, from a reinforcement learning perspective, whether the darker sides of human nature or the better angels of our nature win out, statistically speaking, I don't know. I tend to be optimistic and hope that love wins out in the end. You've done a lot of incredible stuff and your book is driving towards this fourth question that you started with on the nature of intelligence. What do you hope your legacy, for people reading 100 years from now, how do you hope they remember your work? How do you hope they remember this book? Well, I think as an entrepreneur or a scientist or any human who's trying to accomplish some things, I have a view that really all you can do is accelerate the inevitable. It's like, if we didn't study the brain, someone else would study the brain. If Elon Musk didn't make electric cars, someone else would do it eventually. And if Thomas Edison didn't invent a light bulb, we wouldn't be using candles today. So what you can do as an individual is you can accelerate something that's beneficial and make it happen sooner than whatever. That's really it, that's all you can do. You can't create a new reality that it wasn't gonna happen. So from that perspective, I would hope that our work, not just me, but our work in general, people would look back and said, hey, they really helped make this better future happen sooner. They helped us understand the nature of false beliefs sooner than make Ryan Rudd up. Now we're so happy that we have these intelligent machines doing these things, helping us, that maybe that solved the climate change problem and they made it happen sooner. So I think that's the best I would hope for. Some would say those guys just moved the needle forward a little bit in time. Well, it feels like the progress of human civilization is not, there's a lot of trajectories. And if you have individuals that accelerate towards one direction that helps steer human civilization. So I think in a long stretch of time, all trajectories will be traveled. But I think it's nice for this particular civilization on earth to travel down one that's not. Yeah, well, I think you're right. I mean, look, we have to take the whole period of, you know, World War II, Nazism or something like that. Well, that was a bad sidestep, right? We've been over there for a while. But you know, there is the optimistic view about life that ultimately it does converge in a positive way. It progresses ultimately, even if we have years of darkness. So yeah, so I think you could perhaps, that's accelerating the positive, it could also mean eliminating some bad missteps along the way too. But I'm an optimistic in that way. I'd say, you know, despite we talking about the end of civilization, you know, I think we're gonna live for a long time. I hope we are. I think our society in the future is gonna be better. We're gonna have less discord. We're gonna have less people killing each other. You know, we'll make them live in some sort of way that's compatible with the carrying capacity of the earth. I'm optimistic these things will happen. And all we can do is try to get there sooner. And at the very least, if we do destroy ourselves, we'll have a few satellites orbiting. Hopefully, yeah. That will tell alien civilization that we were once here. Or maybe our future, you know, future inhabitants of earth. You know, imagine the planet of the apes in here. You know, we kill ourselves, you know, a million years from now or a billion years from now, there's another species on the planet. Curious creatures who were once here. Yeah. Jeff, thank you so much for your work. And thank you so much for talking to me once again. Well, actually, it's great. I love what you do. I love your podcast. You have the most interesting people, me aside. So it's a real service, I think, you do for, in a very broader sense for humanity, I think. Thanks, Jeff. All right, pleasure. Thanks for listening to this conversation with Jeff Hawkins. And thank you to Code Academy, Bio-Optimizers, ExpressVPN, Asleep, and Blinkist. Check them out in the description to support this podcast. And now let me leave you with some words from Albert Camus. An intellectual is someone whose mind watches itself. I like this because I'm happy to be both halves, the watcher and the watched. Can they be brought together? This is a practical question we must try to answer. Thank you for listening. I hope to see you next time.

https://youtu.be/Z1KwkpTUbkg

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Peter Wang: Python and the Source Code of Humans, Computers, and Reality | Lex Fridman Podcast #250

The following is a conversation with Peter Wang, one of the most impactful leaders and developers in the Python community, former physicist, current philosopher, and someone who many people told me about and praised as a truly special mind that I absolutely should talk to. Recommendations ranging from Travis Oliphant to Eric Weinstein. So, here we are. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Peter Wang. You're one of the most impactful humans in the Python ecosystem. So, you're an engineer, leader of engineers, but you're also a philosopher. So, let's talk both in this conversation about programming and philosophy. First, programming. What to you is the best or maybe the most beautiful feature of Python, or maybe the thing that made you fall in love or stay in love with Python? Well, those are three different things. What I think is the most beautiful, what made me fall in love, what made me stay in love, when I first started using it was when I was a C++ computer graphics performance nerd. In the 90s? Yeah, in the late 90s. And that was my first job out of college. And we kept trying to do more and more abstract and higher order programming in C++, which at the time was quite difficult. With templates, the compiler support wasn't great, et cetera. So, when I started playing around with Python, that was my first time encountering really first class support for types, for functions, and things like that. And it felt so incredibly expressive. So, that was what kind of made me fall in love with it a little bit. And also, once you spend a lot of time in a C++ dev environment, the ability to just whip something together that basically runs and works the first time is amazing. So, really productive scripting language. I mean, I knew Perl, I knew Bash, I was decent at both, but Python just made everything, it made the whole world accessible. I could script this and that and the other network things, little hard drive utilities, I could write all of these things in the space of an afternoon. And that was really, really cool. So, that's what made me fall in love. Is there something specific you could put your finger on that you're not programming in Perl today? Like, why Python for scripting? I think there's not a specific thing as much as the design motif of both the creator of the language and the core group of people that built the standard library around him. There was definitely, there was a taste to it. I mean, Steve Jobs used that term in somewhat of an arrogant way, but I think it's a real thing, that it was designed to fit. A friend of mine actually expressed this really well. He said, Python just fits in my head. And there's nothing better to say than that. Now, people might argue modern Python, there's a lot more complexity, but certainly as of version 152, I think was my first version, that fit in my head very easily. So, that's what made me fall in love with it. Okay, so the most beautiful feature of Python that made you stay in love. It's like over the years, what has like, you do a double take and you return too often as a thing that just brings you a smile. I really still like the ability to play with metaclasses and express higher order of things. When I have to create some new object model to model something, right? It's easy for me, because I'm pretty expert as a Python programmer. I can easily put all sorts of lovely things together and use properties and decorators and other kinds of things and create something that feels very nice. So that to me, I would say that's tied with the NumPy and vectorization capabilities. I love thinking in terms of the matrices and the vectors and these kind of data structures. So, I would say those two are kind of tied for me. So, the elegance of the NumPy data structure, like slicing through the different multi-dimensional. Yeah, there's just enough things there. It's like a very, it's a very simple, comfortable tool. Just, it's easy to reason about what it does when you don't stray too far afield. Can you put your finger on how to design a language such that it fits in your head? Certain things like the colon or the certain notation aspects of Python that just kind of work. Is it something you have to kind of write out on paper, look and say, it's just right? Is it a taste thing or is there a systematic process? What's your sense? I think it's more of a taste thing. But one thing that should be said is that you have to pick your audience, right? So, the better defined the user audience is or the users are, the easier it is to build something that fits in their minds because their needs will be more compact and coherent. It is possible to find a projection, right? A compact projection for their needs. The more diverse the user base, the harder that is. And so, as Python has grown in popularity, that's also naturally created more complexity as people try to design any given thing. There'll be multiple valid opinions about a particular design approach. And so, I do think that's the downside of popularity. It's almost an intrinsic aspect of the complexity of the problem. Well, at the very beginning, aren't you an audience of one? Isn't ultimately, aren't all the greatest projects in history were just solving a problem that you yourself had? Well, so Clay Shirky in his book on crowdsourcing or in his kind of thoughts on crowdsourcing, he identifies the first step of crowdsourcing is me first collaboration. You first have to make something that works well for yourself. It's very telling that when you look at all of the impactful big project, well, they're fundamental projects now in the SciPy and PyData ecosystem, they all started with the people in the domain trying to scratch their own itch. And the whole idea of scratching your own itch is something that the open source or the free software world has known for a long time. But in the scientific computing areas, these are assistant professors or electrical engineering grad students. They didn't have really a lot of programming skill necessarily, but Python was just good enough for them to put something together that fit in their domain, right? So it's almost like it's a necessity of the mother of invention aspect. And also it was a really harsh filter for utility and compactness and expressiveness. Like it was too hard to use, then they wouldn't have built it because there was just too much trouble, right? It was a side project for them. And also necessity creates a kind of deadline. It seems like a lot of these projects are quickly thrown together in the first step. And that even though it's flawed, that just seems to work well for software projects. Well, it does work well for software projects in general. And in this particular space, one of my colleagues Stan Sieber identified this, that all the projects in the SciPy ecosystem, if we just rattle them off, there's NumPy, there's SciPy, built by different collaborations of people, although Travis is the heart of both of them. But NumPy coming from Numeric and NumRay, these are different people. And then you've got Pandas, you've got Jupyter or IPython, there's Matplotlib, there's just so many others I'm not gonna do justice, if I try to name them all. But all of them are actually different people. And as they rolled out their projects, the fact that they had limited resources meant that they were humble about scope. A great famous hacker, Jamie Zawiski, once said that every geek's dream is to build the ultimate middleware, right? And the thing is with these scientists turned programmers, they had no such thing. They were just trying to write something that was a little bit better for what they needed, the MATLAB, and they were gonna leverage what everyone else had built. So naturally, almost in kind of this annealing process or whatever, we built a very modular cover of the basic needs of a scientific computing library. If you look at the whole human story, how much of a leap is it? We've developed all kinds of languages, all kinds of methodologies for communication, and just kind of like grew this collective intelligence, civilization grew, it expanded, wrote a bunch of books, and now we tweet, how big of a leap is programming if programming is yet another language? Is it just a nice little trick that's temporary in our human history, or is it like a big leap in the, almost us becoming another organism at a higher level of abstraction, something else? I think the act of programming or using grammatical constructions of some underlying primitives, that is something that humans do learn, but every human learns this. Anyone who can speak learns how to do this. What makes programming different has been that up to this point, when we try to give instructions to computing systems, all of our computers, well, actually, this is not quite true, but I'll first say it, and then I'll tell you why it's not true. But for the most part, we can think of computers as being these iterated systems. So when we program, we're giving very precise instructions to iterated systems that then run at incomprehensible speed and run those instructions. In my experience, some people are just better equipped to model systematic iterated systems, well, whatever, iterated systems in their head. Some people are really good at that, and other people are not. And so when you have, like, for instance, sometimes people have tried to build systems that make programming easier by making it visual drag and drop. And the issue is you can have a drag and drop thing, but once you start having to iterate the system with conditional logic, handling case statements and branch statements and all these other things, the visual drag and drop part doesn't save you anything. You still have to reason about this giant iterated system with all these different conditions around it. That's the hard part, right? So handling iterated logic, that's the hard part. The languages we use then emerge to give us ability and capability over these things. Now, the one exception to this rule, of course, is the most popular programming system in the world, which is Excel, which is a data flow and a data-driven, immediate mode data transformation-oriented programming system. And it's actually not an accident that that system is the most popular programming system because it's so accessible to a much broader group of people. I do think as we build future computing systems, you're actually already seeing this a little bit, it's much more about composition of modular blocks. They themselves actually maintain all their internal state and the interfaces between them are well-defined data schemas. And so to stitch these things together using like IFTTT or Zapier or any of these kinds of, I would say compositional scripting kinds of things, I mean, HyperCard was also a little bit in this vein. That's much more accessible to most people. It's really that implicit state that's so hard for people to track. Yeah, okay, so that's modular stuff, but there's also an aspect where you're standing on the shoulders of giants. So you're building higher and higher levels of abstraction. You do that a little bit with language. So with language, you develop sort of ideas, philosophies from Plato and so on. And then you kind of leverage those philosophies as you try to have deeper and deeper conversations. But with programming, it seems like you can build much more complicated systems. Like without knowing how everything works, you can build on top of the work of others. And it seems like you're developing more and more sophisticated expressions, ability to express ideas in a computational space. I think it's worth pondering the difference here between complexity and complication. Okay, right? Back to Excel. Well, not quite back to Excel, but the idea is when we have a human conversation, all languages for humans emerged to support human relational communications, which is that the person we're communicating with is a person and they would communicate back to us. And so we sort of hit a resonance point, right? When we actually agree on some concepts. So there's a messiness to it and there's a fluidity to it. With computing systems, when we express something to the computer and it's wrong, we just try again. So we can basically live many virtual worlds of having failed at expressing ourselves to the computer until the one time we expressed ourselves right. Then we kind of put in production and then discover that it's still wrong, a few days down the road. So I think the sophistication of the things that we build with computing, one has to really pay attention to the difference between when an end user is expressing something onto a system that exists versus when they're extending the system to increase the system's capability for someone else to then interface with. And we happen to use the same language for both of those things. And in most cases, but it doesn't have to be that. And Excel is actually a great example of this, of kind of a counterpoint to that. Okay, so what about the idea of, you said messiness. Wouldn't you put the Softrip 2.0 idea, this idea of machine learning into the further and further steps into the world of messiness? The same kind of beautiful messiness of human communication. Isn't that what machine learning is? Is building on levels of abstraction that don't have messiness in them, that at the operating system level, then there's Python, the programming languages that have more and more power. But then finally, there's neural networks that ultimately work with data. And so the programming is almost in the space of data and the data is allowed to be messy. Isn't that a kind of program? So the idea of Softrip 2.0 is a lot of the programming happens in the space of data. So back to Excel, all roads lead back to Excel. In the space of data and also the hyperparameters of the neural networks. And all of those allow the same kind of messiness that human communication allows. It does, but my background is in physics. I took like two CS courses in college. So I don't have, now I did cram a bunch of CS in prep when I applied for grad school, but still I don't have a formal background in computer science. But what I have observed in studying programming languages and programming systems and things like that, is that there seems to be this triangle. It's one of these beautiful little iron triangles that you find in life sometimes. And it's the connection between the code correctness and kind of expressiveness of code, the semantics of the data, and then the kind of correctness or parameters of the underlying hardware compute system. So there's the algorithms that you wanna apply. There's what the bits that are stored on whatever media actually represent. So the semantics of the data within the representation, and then there's what the computer can actually do. And every programming system, every information system ultimately find some spot in the middle of this little triangle. Sometimes some systems collapse them into just one edge. Are we including humans as a system in this? No, no, I'm just thinking about computing systems here. And the reason I bring this up is because I believe there's no free lunch around this stuff. So if we build machine learning systems to sort of write the correct code that is at a certain level of performance, so it'll sort of select, right? With the hyperparameters, we can tune kind of how we want the performance boundary and SLA to look like for transforming some set of inputs into certain kinds of outputs. That training process itself is intrinsically sensitive to the kinds of inputs we put into it. It's quite sensitive to the boundary conditions we put around the performance. So I think even as we move to using automated systems to build this transformation, as opposed to humans explicitly from a top-down perspective, figuring out, well, this schema and this database and these columns get selected for this algorithm. And here we put a Fibonacci heap for some other thing. Human design or computer design, ultimately what we hit, the boundaries that we hit with these information systems is when the representation of the data hits the real world is where there's a lot of slop and a lot of interpretation. And that's where actually I think a lot of the work will go in the future is actually understanding kind of how to better in the view of these live data systems, how to better encode the semantics of the world for those things. There'll be less of the details of how we write a particular SQL query. Okay, but given the semantics of the real world and the messiness of that, what does the word correctness mean when you're talking about code? There's a lot of dimensions to correctness. Historically, and this is one of the reasons I say that we're coming to the end of the era of software, because for the last 40 years or so, software correctness was really defined about functional correctness. I write a function, it's got some inputs, does it produce the right outputs? If so, then I can turn it on, hook it up to the live database and it goes. And more and more now we have, I mean, in fact, I think the bright line in the sand between machine learning systems or modern data-driven systems versus classical software systems is that the values of the input actually have to be considered with the function together to say this whole thing is correct or not. And usually there's a performance SLA as well. Like, did it actually finish making this- What's SLA? Sorry, service level agreement. So it has to return within some time. You have a 10 millisecond time budget to return a prediction of this level of accuracy, right? So these are things that were not traditionally in most business computing systems for the last 20 years at all, people didn't think about it. But now we have value dependence on functional correctness. So that question of correctness is becoming a bigger and bigger question. What does that map to the end of software? We've thought about software as just this thing that you can do in isolation with some test trial inputs and in a very sort of sandboxed environment. And we can quantify how does it scale? How does it perform? How many nodes do we need to allocate if we want to scale this many inputs? When we start turning this stuff into prediction systems, real cybernetic systems, you're going to find scenarios where you get inputs that you're gonna want to spend a little more time thinking about. You're gonna find inputs that are not, it's not clear what you should do, right? So then the software has a varying amount of runtime and correctness with regard to input. And that is a different kind of system altogether. Now it's a full-on cybernetic system. It's a next generation information system that is not like traditional software systems. Can you maybe describe what is a cybernetic system? Do you include humans in that picture? So is it human in the loop kind of complex mess of the whole kind of interactivity of software with the real world, or is it something more concrete? Well, when I say cybernetic, I really do mean that the software itself is closing the observe, orient, decide, act loop by itself. So humans being out of the loop is the fact what for me makes it a cybernetic system. So humans are out of that loop. When humans are out of the loop, when the machine is actually sort of deciding on its own what it should do next to get more information, that makes it a cybernetic system. So we're just at the dawn of this, right? I think everyone talking about MLAI, it's great, but really the thing we should be talking about is when we really enter the cybernetic era and all of the questions of ethics and governance and correctness and all these things, they really are the most important questions. Okay, can we just linger on this? What does it mean for the human to be out of the loop in a cybernetic system? Because isn't the cybernetic system that's ultimately accomplishing some kind of purpose that at the bottom, the turtle's all the way down, at the bottom, turtle's a human. Well, the human may have set some criteria, but the human wasn't precise. So for instance, I just read the other day that earlier this year, or maybe it was last year at some point, the Libyan army, I think, sent out some automated killer drones with explosives. And there was no human in the loop at that point. They basically put them in a geo-fenced area, said, find any moving target, like a truck or vehicle, it looks like this, and boom. That's not a human in the loop, right? So increasingly, the less human there is in the loop, the more concerned you are about these kinds of systems, because there's unintended consequences, like less the original designer and engineer of the system is able to predict, even one with good intent is able to predict the consequences of such a system. Is that- That's right. There are some software systems, right, that run without humans in the loop that are quite complex. And that's like the electronic markets. And we get flash crashes all the time. We get, you know, in the heyday of high-frequency trading, there was a lot of market microstructure, people doing all sorts of weird stuff that the market designers had never really thought about, contemplated, or intended. So when we run these full-on systems with these automated trading bots, now they become automated, you know, killer drones, and then all sorts of other stuff. We are, that's what I mean by we're at the dawn of the cybernetic era, and the end of the era of just pure software. Are you more concerned, if you're thinking about cybernetic systems, or even like self-replicating systems, so systems that aren't just doing a particular task, but are able to sort of multiply and scale in some dimension, in the digital, or even the physical world, are you more concerned about, like, the lobster being boiled, so a gradual, with us not noticing, collapse of civilization, or a big explosion? Like, oops, kind of a big thing where everyone notices, but it's too late. I think that it will be a different experience for different people. I do share a common point of view with some of the climate, you know, people who are concerned about climate change, and just the big existential risks that we have, but unlike a lot of people who share my level of concern, I think the collapse will not be quite so dramatic as some of them think. And what I mean is that I think that for certain tiers of, let's say, economic class, or certain locations in the world, people will experience dramatic collapse scenarios. But for a lot of people, especially in the developed world, the realities of collapse will be managed. There will be narrative management around it, so that they essentially insulate, the middle class will be used to insulate the upper class from the pitchforks and the flaming torches and everything. It's interesting, because, so my specific question wasn't as general. My question was more about cybernetic systems or software. Okay. It's interesting, but it would nevertheless perhaps be about class, so the effect of algorithms might affect certain classes more than others. Absolutely. I was more thinking about whether it's social media algorithms or actual robots, is there going to be a gradual effect on us where we wake up one day and don't recognize the humans we are? Or is it something truly dramatic where there's like a meltdown of a nuclear reactor kind of thing, Chernobyl, like catastrophic events that are almost bugs in a program that scaled itself too quickly? Yeah, I'm not as concerned about the visible stuff. And the reason is because the big visible explosions, I mean, this is something I said about social media is that, at least with nuclear weapons, when a nuke goes off, you can see it and you're like, well, that's really, wow, that's kind of bad, right? I mean, Oppenheimer was reciting the Bhagavad Gita, right? When he saw one of those things go off. So we can see nukes are really bad. He's not reciting anything about Twitter. Well, but right, but then when you have social media, when you have all these different things that conspire to create a layer of virtual experience for people that alienates them from reality and from each other, that's very pernicious. It's impossible to see, right? And it kind of slowly gets in there. So. You've written about this idea of virtuality on this topic, which you define as the subjective phenomenon of knowingly engaging with virtual sensation and perception and suspending or forgetting the context that it's a simulacrum. So let me ask, what is real? Is there a hard line between reality and virtuality? Like perception drifts from some kind of physical reality. We have to kind of have a sense of what is the line that's we've gone too far. Right, right. For me, it's not about any hard line about physical reality as much as a simple question of, does the particular technology help people connect in a more integral way with other people, with their environment, with all of the full spectrum of things around them? So it's less about, oh, this is a virtual thing and this is a hard real thing, more about when we create virtual representations of the real things, always some things are lost in translation. Usually many, many dimensions are lost in translation. Right, we're now coming to almost two years of COVID, people on Zoom all the time. You know, it's different when you meet somebody in person than when you see them on, I've seen you on YouTube lots, right? But the seeing a person is very different. And so I think when we engage in virtual experiences all the time, and we only do that, there is absolutely a level of embodiment. There's a level of embodied experience and participatory interaction that is lost. And it's very hard to put your finger on exactly what it is. It's hard to say, oh, we're gonna spend $100 million building a new system that captures this 5% better, higher fidelity human expression. No one's gonna pay for that, right? So when we rush madly into a world of simulacrum and virtuality, you know, the things that are lost are, it's difficult, once everyone moves there, it can be hard to look back and see what we've lost. So is it irrecoverably lost, or rather when you put it all on the table, is it possible for more to be gained than is lost? If you look at video games, they create virtual experiences that are surreal and can bring joy to a lot of people, can connect a lot of people, and can get people to talk a lot of trash. So it can bring out the best and the worst in people. So is it possible to have a future world where the pros outweigh the cons? It is, I mean, it's possible to have that in the current world, but when literally trillions of dollars of capital are tied to using those things to groom the worst of our inclinations and to attack our weaknesses in the limbic system to create these things into id machines versus connection machines, then those good things don't stand a chance. Can you make a lot of money by building connection machines? Is it possible, do you think, to bring out the best in human nature to create fulfilling connections and relationships in the digital world and make a shit ton of money? If I figure it out, I'll let you know. But what's your intuition without concretely knowing what's the solution? My intuition is that a lot of our digital technologies give us the ability to have synthetic connections or to experience virtuality. They have co-evolved with sort of the human expectations. It's sort of like sugary drinks. As people have more sugary drinks, they need more sugary drinks to get that same hit, right? So with these virtual things and with TV and fast cuts and TikToks and all these different kinds of things, we're co-creating essentially humanity that sort of asks and needs those things. And now it becomes very difficult to get people to slow down. It gets difficult for people to hold their attention on slow things and actually feel that embodied experience, right? So mindfulness now more than ever is so important in schools and as a therapy technique for people because our environment has been accelerated. And McLuhan actually talks about this in the electric environment of the television. And that was before TikTok and before front-facing cameras. So I think for me, the concern is that it's not like we can ever switch to doing something better, but more of the humans and technology, they're not independent of each other. The technology that we use kind of molds what we need for the next generation of technology. Yeah, but humans are intelligent and they're introspective and they can reflect on the experiences of their life. So for example, there's been many years in my life where I ate an excessive amount of sugar. And then a certain moment I woke up and said, why do I keep doing this, this doesn't feel good. Like long-term. And I think, so going through the TikTok process of realizing, okay, when I shorten my attention span, actually that does not make me feel good longer term. And realizing that and then going to platforms, going to places that are away from the sugar. So in so doing, you can create platforms that can make a lot of money to help people wake up to what actually makes them feel good long-term. Develop, grow as human beings. And it just feels like humans are more intelligent than mice looking for cheese. They're able to sort of think, I mean, we can contemplate our own mortality, we can contemplate things like long-term love and we can have a long-term fear of certain things like mortality. We can contemplate whether the experiences, the sort of the drugs of daily life that we've been partaking in is making us happier, better people. And then once we contemplate that, we can make financial decisions in using services and paying for services that are making us better people. So it just seems that we're in the very first stages of social networks that just were able to make a lot of money really quickly. But in bringing out sometimes the bad parts of human nature, they didn't destroy humans, they just fed everybody a lot of sugar. And now everyone's gonna wake up and say, hey, we're gonna start having like sugar-free social media. Right, right. Well, there's a lot to unpack there. I think some people certainly have the capacity for that. And I certainly think, I mean, it's very interesting even the way you said it. You woke up one day and you thought, well, this doesn't feel very good. Well, that's still your limbic system saying this doesn't feel very good. You have a cat brain's worth of neurons around your gut. And so maybe that saturated and that was telling you, hey, this isn't good. Humans are more than just mice looking for cheese or monkeys looking for sex and power. Let's slow down. Now a lot of people would argue with you on that one. But yes. Well, we're more than just that, but we're at least that. And we're very, very seldom not that. So I don't actually disagree with you that we could be better and that better platforms exist. And people are voluntarily noping out of things like Facebook and noping out of it. Yeah. That's an awesome verb. It's a great term. Yeah, I love it. I use it all the time. You're welcome, Mike. I'm gonna have to nope out of that. I'm gonna nope out of that, right? That's gonna be a hard pass. And that's great. But that's again, to your point, that's the first generation of front-facing cameras, of social pressures. And you as a self-starter, self-aware adult have the capacity to say, yeah, I'm not gonna do that. I'm gonna go and spend time on long-form reads. I'm gonna spend time managing my attention. I'm gonna do some yoga. If you're a 15-year-old in high school and your entire social environment is everyone doing these things, guess what you're gonna do? You're gonna kind of have to do that because your limbic system says, hey, I need to get the guy or the girl or the whatever. And that's what I'm gonna do. And so one of the things that we have to reason about here is the social media systems or social media, I think, is our first encounter with a technological system that runs a bit of a loop around our own cognition and attention. It's not the last. It's far from the last. And it gets to the heart of some of the philosophical Achilles heel of the Western philosophical system, which is each person gets to make their own determination. Each person is an individual that's sacrosanct in their agency and their sovereignty and all these things. The problem with these systems is they come down and they are able to manage everyone en masse. And so every person is making their own decision, but together the bigger system is causing them to act with a group dynamic that's very profitable for people. So this is the issue that we have is that our philosophies are actually not geared to understand what is it for a person to have a high trust connection as part of a collective and for that collective to have its right to coherency and agency. That's something like when a social media app causes a family to break apart, it's done harm to more than just individuals, right? So that concept is not something we really talk about or think about very much, but that's actually the problem is that we're vaporizing molecules into atomic units and then we're hitting all the atoms with certain things that it's like, yeah, well, that person chose to look at my app. So our understanding of human nature is at the individual level, it emphasizes the individual too much because ultimately society operates at the collective level. And these apps do as well. And the apps do as well. So for us to understand the progression and the development of this organism we call human civilization, we have to think at the collective level too. I would say multi-tiered. Multi-tiered. Multi-tiered. So individual as well. Individuals, family units, social collectives, and all the way up. Okay. So you've said that individual humans are multi-layered, susceptible to signals and waves and multiple strata. The physical, the biological, social, cultural, intellectual. So sort of going along these lines, can you describe the layers of the cake that is a human being? And maybe the human collective, human society? So I'm just stealing wholesale here from Robert Persig, who is the author of Zen and the Art of Motorcycle Maintenance. And his follow-on book has a sequel to it called Lila. He goes into this in a little more detail. But it's a crude approach to thinking about people, but I think it's still an advancement over traditional subject-object metaphysics. Where we look at people as a dualist would say, well, is your mind, your consciousness, is that just merely the matter that's in your brain? Or is there something kind of more beyond that? And they would say, yes, there's a soul, sort of ineffable soul beyond just merely the physical body. And I'm not one of those people. I think that we don't have to draw a line between are things only this or only that? Collectives of things can emerge structures and patterns that are just as real as the underlying pieces. But they're transcendent, but they're still of the underlying pieces. So your body is this way. I mean, we just know physically you consist of atoms and whatnot. And then the atoms are arranged into molecules which then arrange into certain kinds of structures that seem to have a homeostasis to them, we call them cells. And those cells form sort of biological structures. Those biological structures give your body its physical ability and biological ability to consume energy and to maintain homeostasis. But humans are social animals. I mean, human by themselves is not very long for the world. So we also, part of our biology is why are two connect to other people? From the mirror neurons to our language centers and all these other things. So we are intrinsically, there's a layer, there's a part of us that wants to be part of a thing. If we're around other people, not saying a word, but they're just up and down, jumping and dancing, laughing, we're gonna feel better. And there was no exchange of physical anything. They didn't give us like five atoms of happiness. But there's an induction in our own sense of self that is at that social level. And then beyond that, Persick puts the intellectual level kind of one level higher than social. I think they're actually more intertwined than that. But the intellectual level is the level of pure ideas that you are a vessel for memes. You're a vessel for philosophies. You will conduct yourself in a particular way. I mean, I think part of this is if we think about it from a physics perspective, you're not, there's the joke that physicists like to approximate things. And we'll say, well, approximate a spherical cow. You're not a spherical cow, you're not a spherical human. You're a messy human. And we can't even say what the dynamics of your emotion will be unless we analyze all four of these layers. If you're Muslim at a certain time of day, guess what? You're gonna be on the ground, kneeling and praying. And that has nothing to do with your biological need to get on the ground or physics of gravity. It is an intellectual drive that you have. It's a cultural phenomenon and an intellectual belief that you carry. So that's what the four layered stack is all about. It's that a person is not only one of these things. They're all of these things at the same time. It's a superposition of dynamics that run through us, that make us who we are. So no layer is special. Not so much no layer is special. Each layer is just different. But we are- Each layer gets the participation trophy. Yeah, each layer is a part of what you are. You are a layer cake, right, of all these things. And if we try to deny, right, so many philosophies do try to deny the reality of some of these things, right? Some people will say, well, we're only atoms. Well, we're not only atoms because there's a lot of other things that are only atoms. I can reduce a human being to a bunch of soup and they're not the same thing, even though it's the same atoms. So I think the order and the patterns that emerge within humans to understand, to really think about what a next generation of philosophy would look like, that would allow us to reason about extending humans into the digital realm or to interact with autonomous intelligences that are not biological in nature. We really need to appreciate these, that human, what human beings actually are, is the superposition of these different layers. You mentioned consciousness. Are each of these layers of cake conscious? Is consciousness a particular quality of one of the layers? Is there like a spike, if you have a consciousness detector at these layers? Or is something that just permeates all of these layers and just takes different form? I believe what humans experience as consciousness is something that sits on a gradient scale of a general principle in the universe that seems to look for order and reach for order when there's an excess of energy. You know, it would be odd to say a proton is alive, right? It'd be odd to say that this particular atom or molecule of hydrogen gas is alive. But there's certainly something we can make assemblages of these things that have autopoetic aspects to them, that will create structures, that will, you know, crystalline solids will form very interesting and beautiful structures. This gets kind of into weird mathematical territories. You start thinking about Penrose and Game of Life stuff about the generativity of math itself, like the hyperreal numbers, things like that. But without going down that rabbit hole, I would say that there seems to be a tendency in the world that when there is excess energy, things will structure and pattern themselves. And they will then actually furthermore try to create an environment that furthers their continued stability. It's the concept of externalized extended phenotype or niche construction. So this is ultimately what leads to certain kinds of amino acids forming certain kinds of structures and so on and so forth until you get the ladder of life. So what we experience as consciousness, no, I don't think cells are conscious of that level. But is there something beyond mere equilibrium state biology and chemistry and biochemistry that drives what makes things work? I think there is. So Adrian Bajan has his constructual law. There's other things you look at. When you look at the life sciences and you look at any kind of statistical physics and statistical mechanics, when you look at things far out of equilibrium, when you have excess energy, what happens then? Life doesn't just make a hot herb soup. It starts making structure. There's something there. The poetry of reaches for order when there's an excess of energy because you brought up Game of Life. You did it, not me. I love cellular automata, so I have to sort of linger on that for a little bit. So cellular automata, I guess, or Game of Life is a very simple example of reaching for order when there's an excess of energy or reaching for order and somehow creating complexity. It's explosion of just turmoil somehow trying to construct structures. And in so doing, creates very elaborate organism-looking type things. What intuition do you draw from this simple mechanism? Well, I like to turn that around its head and look at it as what if every single one of the patterns created life or created, not life, but created interesting patterns? Because some of them don't. And sometimes you make cool gliders. And other times you start with certain things and you make gliders and other things that then construct like AND gates and NOT gates, right? And you build computers on them. All of these rules that create these patterns that we can see, those are just the patterns we can see. What if our subjectivity is actually limiting our ability to perceive the order in all of it? What if some of the things that we think are random are actually not that random? We're simply not integrating at a final level across a broad enough time horizon. And this is again, I said, we go down the rabbit hole, some of the Penrose stuff or like Wolfram's explorations on these things. There is something deep and beautiful in the mathematics of all this. That is hopefully one day I'll have enough money to work and retire and just ponder those questions. But there's something there. But you're saying there's a ceiling to when you have enough money and you retire and you ponder, there's a ceiling to how much you can truly ponder because there's cognitive limitations in what you're able to perceive as a pattern. Yeah. And maybe mathematics extends your perception capabilities, but it's still finite. It's just like. Yeah, the mathematics we use is the mathematics that can fit in our head. Yeah. Did God really create the integers? Or did God create all of it and we just happen at this point in time to be able to perceive integers? Well, he just did the positive in it. She, I think she created all of it. And then we. She just created the natural numbers and then we screwed all up with zero and then I guess, okay. But we did, we created mathematical operations so that we can have iterated steps to approach bigger problems, right? I mean, the entire point of the Arabic numeral system, and it's a rubric for mapping a certain set of operations, of folding them into a simple little expression. But that's just the operations that we can fit in our heads. There are many other operations besides, right? The thing that worries me the most about aliens and humans is that they're, aliens are all around us and we're too dumb to see them. Oh, certainly, yeah. Or life, let's say just life. Life of all kinds of forms or organisms. You know what, just even the intelligence of organisms is imperceptible to us because we're too dumb and self-centered. That worries me. Well, we're looking for a particular kind of thing. When I was at Cornell, I had a lovely professor of Asian religions, Jane Marie Law, and she would tell this story about a musical, a musician, a Western musician who went to Japan and he taught classical music and could play all sorts of instruments. He went to Japan and he would ask people, he would basically be looking for things in the style of, Western chromatic scale and these kinds of things. And then finding none of it, he would say, well, there's really no music in Japan. But they're using a different scale. They're playing different kinds of instruments. The same thing she was using as a sort of a metaphor for religion as well. In the West, we center a lot of religion, certainly the religions of Abraham, we center them around belief. And in the East, it's more about practice, spirituality and practice rather than belief. So anyway, the point is here, to your point, life, I think so many people are so fixated on certain aspects of self-replication or homeostasis or whatever. But if we kind of broaden and generalize this thing of things reaching for order, under which conditions can they then create an environment that sustains that order, that allows them, the invention of death is an interesting thing. There are some organisms on earth that are thousands of years old. And it's not like they're incredibly complex, they're actually simpler than the cells that comprise us, but they never die. So at some point, death was invented, somewhere along the eukaryotic scale, I mean, even the protists, right? There's death. And why is that? Along with the sexual reproduction, right? There is something about the renewal process, something about the ability to respond to a changing environment, where it just becomes, you know, just killing off the old generation and letting new generations try, seems to be the best way to fit into the niche. You know, human historians seems to write about wheels and fires, the greatest inventions, but it seems like death and sex are pretty good. And they're kind of essential inventions at the very beginning. At the very beginning, yeah. Well, we didn't invent them, right? Well, broad, we, you didn't invent them. I see us as one, you, particular homo sapien, did not invent them, but we together, it's a team project, just like you're saying. I think the greatest homo sapien invention is collaboration. So when you say collaboration, Peter, where do ideas come from? And how do they take hold in society? What's, is that the nature of collaboration? Is that the basic atom of collaboration is ideas? It's not not ideas, but it's not only ideas. There's a book I just started reading called Death From a Distance. Have you heard of this? No. It's a really fascinating thesis, which is that humans are the only conspecific, the only species that can kill other members of the species from range. And maybe there's a few exceptions, but if you look in the animal world, you see like pronghorns, butting heads, right? You see the alpha lion and the beta lion, and they take each other down. Humans, we develop the ability to chuck rocks at each other, well, at prey, but also at each other. And that means the beta male can chunk a rock at the alpha male and take them down. And he can throw a lot of rocks, actually, miss a bunch of times, but just hit once and be good. So this ability to actually kill members of our own species from range without a threat of harm to ourselves, create essentially mutually assured destruction, where we had to evolve cooperation. If we didn't, then if we just continue to try to do, like I'm the biggest monkey in the tribe, and I'm gonna own this tribe and you have to go, if we do it that way, then those tribes basically failed. And the tribes that persisted and that have now given rise to the modern Homo sapiens are the ones where respecting the fact that we can kill each other from range without harm, like there's an asymmetric ability to snipe the leader from range, that meant that we sort of had to learn how to cooperate with each other. Right, come back here, don't throw that rock at me. Let's talk our differences out. So violence is also part of collaboration. The threat of violence, let's say. Well, the recognition, maybe the better way to put it, is the recognition that we have more to gain by working together than the prisoner's dilemma of both of us defecting. So mutually assured destruction in all its forms is part of this idea of collaboration. Well, and Eric Weinstein talks about our nuclear peace. I mean, it kind of sucks if thousands of warheads aimed at each other, we mean Russia and the US, but it's like, on the other hand, we only fought proxy wars. We did not have another World War III of hundreds of millions of people dying to machine gun fire and giant guided missiles. So the original nuclear weapon is a rock that we learned how to throw, essentially? Yeah, well, the original scope of the world for any human being was their little tribe. I would say it still is for the most part. Eric Weinstein speaks very highly of you, which is very surprising to me at first, because I didn't know there's this depth to you, because I knew you as an amazing leader of engineers and an engineer yourself and so on. So it's fascinating. Maybe just as a comment, a side tangent that we can take, what's the nature of your friendship with Eric Weinstein? How did such two interesting paths cross? Is it your origins in physics? Is it your interest in philosophy and the ideas of how the world works? What is it? It's actually, it's very random. Eric found me. He actually found Travis and I. Travis Oliphant. Oliphant, yeah. We were both working at a company called Enthought back in the mid-2000s, and we were doing a lot of consulting around scientific Python. And we'd made some tools, and Eric was trying to use some of these Python tools to visualize that he had a fiber bundle approach to modeling certain aspects of economics. He was doing this, and that's how he kind of got in touch with us. And so- This was in the early- This was in the mid-2000s. 07 timeframe, 06, 07 timeframe. Eric Weinstein trying to use Python to visualize fiber bundles. Right, to visualize fiber bundles, using some of the tools that we'd build in the open source. That's somehow entertaining to me, the thought of that. It's pretty funny. But then, we met with him a couple of times, a really interesting guy. And then in the wake of the 07, 08 kind of financial collapse, he helped organize with Lee Smolin a symposium at the Perimeter Institute about, okay, well, clearly, big finance can't be trusted, government's in its pockets with regulatory capture. What the F do we do? And all sorts of people, Nassim Tlaib was there, and Andy Lo from MIT was there, and Bill Janeway, just a lot of top billing people were there, and he invited me and Travis and another one of our coworkers, Robert Kern, who is anyone in the SciPy, NumPy community knows Robert, really great guy. So the three of us also got invited to go to this thing. And that's where I met Brett Weinstein for the first time as well. Yeah, I knew him before he got all famous for unfortunate reasons, I guess. But anyway, so we met then and kind of had a friendship throughout since then. You have a depth of thinking that kind of runs with Eric in terms of just thinking about the world deeply and thinking philosophically. And then there's Eric's interest in programming. I actually have never, he'll bring up programming to me quite a bit as a metaphor for stuff. But I never kind of pushed the point of like, what's the nature of your interest in programming? I think he saw it probably as a tool. Yeah, absolutely. That to visualize, to explore mathematics and explore physics. But I was wondering like, what's his depth of interest and also his vision for what programming would look like in the future? Have you had interaction with him, like discussion in the space of Python and programming? Well, in the sense of sometimes he asks me, why is this stuff still so hard? Yeah, you know, everybody's a critic, but actually no, Eric- Programming you mean like in general? Yes, yes. Well, not programming in general, but certain things in the Python ecosystem. But he actually, I think what I find in listening to some of his stuff is that he does use programming metaphors a lot, right? He'll talk about APIs or object oriented and things like that. So I think that's a useful set of frames for him to draw upon for discourse. I haven't pair programmed with him in a very long time. You've previously pair coded with Eric Weinstein. Trying to help like put together some of the visualizations around these things, but it's been a very, not really pair program, but like even looked at his code, right? I mean- How legendary would be is that like a Git repo with Peter Wang and Eric Weinstein? Well, honestly, Robert Kern did all the heavy lifting. So I have to give credit where credit is due. Robert is the silent, but incredibly deep, quiet, not silent, but quiet, but incredibly deep individual at the heart of a lot of those things that Eric was trying to do. But we did have, you know, in the, as Travis and I were starting our company in 2012 timeframe, we went to New York. Eric was still in New York at the time. He hadn't moved to, this was before he joined Teal Capital. We just had like a steak dinner somewhere. Maybe it was Keene's, I don't know, somewhere in New York. So it was me, Travis, Eric, and then Wes McKinney, the creative pandas. And then Wes's then business partner, Adam. The five of us sat around having this, just a hilarious time, amazing dinner. I forget what all we talked about, but it was one of those conversations, which I wish as soon as COVID is over, maybe Eric and I can sit down- Recreate. Recreate it somewhere in LA, or maybe he comes here. Cause a lot of cool people are here in Austin, right? Exactly. Yeah, we're all here. He should come here. Yeah. So he uses the metaphor source code sometimes to talk about physics. We figure out our own source code. So you with the physics background and somebody who's quite a bit of an expert in source code, do you think we'll ever figure out our own source code in the way that Eric means? Do you think we'll figure out the nature of reality? Well, I think we're constantly working on that problem. I mean, I think we'll make more and more progress. For me, there's some things I don't really doubt too much. Like I don't really doubt that one day we will create a synthetic, maybe not fully in silicon, but a synthetic approach to cognition that rivals the biological 20 watt computers in our heads. What's cognition here? Cognition. Which aspect? Perception, attention, memory, recall, asking better questions. That for me is a measure of intelligence. Doesn't Roomba Vacuum Cleaner already do that? Or do you mean, oh, it doesn't ask questions. I mean, no. It's, I mean, I have a Roomba, but it's, well, it's not even as smart as my cat, right? So. It's asking questions about what is this wall? It now, new feature asks, is this poop or not, apparently. Yes, a lot of our current cybernetic system, it's a cybernetic system. It will go and it will happily vacuum up some poop, right? The older generations would. A new one, just released, does not vacuum up the poop. This is a commercial for Roomba. I wonder if it still gets stuck under my first rung of my stair. In any case, these cybernetic systems we have, they are mold, they're designed to be sent off into a relatively static environment. And whatever dynamic things happen in the environment, they have a very limited capacity to respond to. A human baby, a human toddler of 18 months of age, has more capacity to manage its own attention and its own capacity to make better sense of the world than the most advanced robots today. So again, my cat, I think, can do a better job of my two, and they're both pretty clever. So I do think though, back to my kind of original point, I think that for me, it's not a question at all that we will be able to create synthetic systems that are able to do this at an equal level or better than the human mind. It's also for me, not a question, that we will be able to put them alongside humans so that they capture the full broad spectrum of what we are seeing as well, and also looking at our responses, listening to our responses, even maybe measuring certain vital signs about us. So in this kind of sidecar mode, a greater intelligence could use us in our whatever, 80 years of life, to train itself up, and then be a very good simulacrum of us moving forward. So who is in the sidecar in that picture of the future exactly? The baby version of our immortal selves. Okay, so once the baby grows up, is there any use for humans? I think so. I think that out of epistemic humility, we need to keep humans around for a long time. And I would hope that anyone making those systems would believe that to be true. Out of epistemic humility. What's the nature of the humility that- That we don't know what we don't know. So we don't- Right? So we don't know- First, we have to build systems that help us do the things that we do know about, that can then probe the unknowns that we know about, but the unknown unknowns, we don't know. Nature is the one thing that is infinitely able to surprise us. So we should keep biological humans around for a very, very, very long time, even after our immortal selves have transcended, have gone off to explore other worlds, gone to go communicate with the lifeforms living in the sun or whatever else. So I think that's, for me, these seem like things that are going to happen. Like I don't really question that, that they're gonna happen. Assuming we don't completely, you know, destroy ourselves. Is it possible to create an AI system that you fall in love with, and it falls in love with you, and you have a romantic relationship with it? Or a deep friendship, let's say. I would hope that that is the design criteria for any of these systems. If we cannot have a meaningful relationship with it, then it's still just a chunk of silicon. So then what is meaningful? Because back to sugar. Well, sugar doesn't love you back, right? So the computer has to love you back. And what does love mean? Well, in this context, for me, love, I'm gonna take a page from Alain de Botton, love means that it wants to help us become the best version of ourselves. Yes. That's beautiful. That's a beautiful definition of love. So what role does love play in the human condition at the individual level and at the group level? Because you were kind of saying that humans, we should really consider humans both at the individual and the group and the societal level. What's the role of love in this whole thing? We talked about sex, we talked about death, thanks to the bacteria that invented it. At which point did we invent love, by the way? I mean, is that also- No, I think love is the start of it all. And the feelings of, and this gets, this is sort of beyond just romantic, sensual, whatever kind of things, but actually genuine love as we have for another person, love as it would be used in a religious text, right? I think that capacity to feel love, more than consciousness, that is the universal thing. Our feeling of love is actually a sense of that generativity. When we can look at another person and see that they can be something more than they are, and more than just what we, a pigeonhole we might stick them in. We see, I mean, I think there's, in any religious text you'll find voiced some concept of this, that you should see the grace of God in the other person. Right, that they're made in the spirit of what, the love that God feels for his creation or her creation. And so I think this thing is actually the root of it. So I would say before, I don't think molecules of water feel consciousness, have consciousness, but there is some proto micro quantum thing of love. That's the generativity when there's more energy than what they need to maintain equilibrium. And that, when you sum it all up, is something that leads to, I mean, I had my mind blown one day as an undergrad at the physics computer lab. I logged in and when you log into bash for a long time, there was a little fortune that would come out. And it said, man was created by water to carry itself uphill. And I was logging in to work on some problem set and I logged in and I saw that and I just said, son of a bitch, I just, I logged out and I went to the coffee shop and I got a coffee and I sat there on the quad and like, you know, it's not wrong and yet WTF, right? So when you look at it that way, it's like, yeah, okay. Non-equilibrium physics is a thing. And so when we think about love, when we think about these kinds of things, I would say that in the modern day human condition, there's a lot of talk about freedom and individual liberty and rights and all these things, but that's very Hegelian, it's very kind of following from the Western philosophy of the individual as sacrosanct, but it's not really couched, I think the right way because it should be how do we maximize people's ability to love each other, to love themselves first, to love each other, their responsibilities to the previous generation, to the future generations. Those are the kinds of things that should be our design criteria, right? Those should be what we start with to then come up with the philosophies of self and of rights and responsibilities. But that love being at the center of it, I think when we designed systems for cognition, it should absolutely be built that way. I think if we simply focus on efficiency and productivity, these kinds of very industrial era, all the things that Marx had issues with, right? That's a way to go and really I think go off the deep end in the wrong way. So one of the interesting consequences of thinking of life in this hierarchical way of an individual human, and then there's groups and there's societies is I believe that you believe that corporations are people. So this is kind of a politically dense idea, all those kinds of things. If we just throw politics aside, if we throw all of that aside, in which sense do you believe that corporations are people? And how does love connect to that? Right, so the belief is that groups of people have some kind of higher level, I would say mesoscopic claim to agency. So where do I, let's start with this. Most people would say, okay, individuals have claims to agency and sovereignty. Nations, we certainly act as if nations, sort of very large, large scale, nations have rights to sovereignty and agency. Like everyone plays the game of modernity as if that's true, right? We believe France is a thing, we believe the United States is a thing. But to say that groups of people at a smaller level than that, like a family unit is the thing. Well, in our laws, we actually do encode this concept. I believe that in a relationship, in a marriage, right? One partner can sue for loss of consortium, right? If someone breaks up the marriage or whatever. So these are concepts that even in law, we do respect that there is something about the union and about the family. So for me, I don't think it's so weird to think that groups of people have a right to, a claim to rights and sovereignty of some degree. I mean, we look at our clubs, we look at churches. These are, we talk about these collectives of people as if they have a real agency to them. And then they do. But I think if we take that one step further, and say, okay, they can accrue resources. Well, yes, check, by law they can. They can own land, they can engage in contracts, they can do all these different kinds of things. So we, in legal terms, support this idea that groups of people have rights. Where we go wrong on this stuff is that the most popular version of this is the for-profit absentee owner corporation that then is able to amass larger resources than anyone else in the landscape, anything else, any other entity of equivalent size. And they're able to essentially bully around individuals, whether it's laborers, whether it's people whose resources they want to capture. They're also able to bully around our system of representation, which is still tied to individuals, right? So I don't believe that's correct. I don't think it's good that they, they're people, but they're assholes. I don't think that corporations as people acting like assholes is a good thing. But the idea that collectives and collections of people, that we should treat them philosophically as having some- Agency. Some agency and some mass at a mesoscopic level. I think that's an important thing, because one thing I do think we underappreciate sometimes is the fact that relationships have relationships. So it's not just individuals having relationships with each other. But if you have eight people seated around a table, right? Each person has a relationship with each of the others, and that's obvious. But then if it's four couples, each couple also has a relationship with each of the other couples, right? The dyads do. And if it's couples, but one is the father and mother older, and then one of their children and their spouse, that family unit of four has a relationship with the other family unit of four. So the idea that relationships have relationships is something that we intuitively know in navigating the social landscape, but it's not something I hear expressed like that. It's certainly not something that is, I think, taken into account very well when we design these kinds of things. So I think the reason why I care a lot about this is because I think the future of humanity requires us to form better sense-make, collective sense-making units at something around Dunbar number, half to 5X Dunbar. And that's very different than right now where we defer sense-making to massive aging zombie institutions. Or we just do it ourselves. We go it alone. Go to the dark force of the internet by ourselves. So that's really interesting. So you've talked about agency, I think maybe calling it a convenient fiction at all these different levels. So even at the human individual level, it's kind of a fiction, we all believe, because we are, like you said, made of cells and cells are made of atoms. So that's a useful fiction. And then there's nations. That seems to be a useful fiction. But it seems like some fictions are better than others. There's a lot of people that argue the fiction of nation is a bad idea. One of them lives two doors down from me, Michael Malice, he's an anarchist. I'm sure there's a lot of people who are into meditation that believe the idea, this useful fiction of agency of an individual is troublesome as well. We need to let go of that in order to truly, like to transcend, I don't know, I don't know what words you wanna use, but suffering or to elevate the experience of life. So you're kind of arguing that, okay, so we have some of these useful fictions of agency. We should add a stronger fiction that we tell ourselves about the agency of groups in the hundreds of the half of Dunbar's number, five X Dunbar's number. Yeah, something on that order. And we call them fictions, but really they're rules of the game, right? Rules that we feel are fair or rules that we consent to. I always question the rules when I lose, like a monopoly. That's when I usually question, when I'm winning, I don't question the rules. We should play a game of Monopoly someday. There's a trippy version of it that we could do. What kind? Contract Monopoly is introduced by a friend of mine to me, where you can write contracts on future earnings or landing on various things. And you can hand out, like, you can land the first three times you land a park place is free or whatever, just, and then you can start trading those contracts for money. And then you create a human civilization and somehow Bitcoin comes into it. Okay, but some of these- Actually, I bet if me and you and Eric sat down to play a game of Monopoly and we were to make NFTs out of the contracts we wrote, we could make a lot of money. Now it's a terrible idea. I would never do it, but I bet we could actually sell the NFTs around. I have other ideas to make money that I could tell you, and they're all terrible ideas, including cat videos on the internet. Okay, but some of these rules of the game, some of these fictions are, it seems like they're better than others. They have worked this far to cohere human, to organize human collective action. But you're saying something about, especially this technological age requires modified fictions, stories of agency. Why the Dunbar number? And also, how do you select the group of people? Dunbar numbers, I think, I have the sense that it's overused as a kind of law that somehow we can have deep human connection at this scale. Like some of it feels like an interface problem too. It feels like if I have the right tools, I can deeply connect with a larger number of people. It just feels like there's a huge value to interacting just in person, getting to share traumatic experiences together, beautiful experiences together. There's other experiences that in the digital space that you can share. It just feels like Dunbar's number could be expanded significantly, perhaps not to the level of millions and billions, but it feels like it could be expanded. So how do we find the right interface, you think, for having a little bit of a collective here that has agency? You're right that there's many different ways that we can build trust with each other. My friend, Joe Edelman, talks about a few different ways that mutual appreciation, trustful conflict, just experiencing something. There's a variety of different things that we can do, but all those things take time, and you have to be present. The less present you are, I mean, there's just, again, a no free lunch principle here. The less present you are, the more of them you can do, but then the less connection you build. So I think there is sort of a human capacity issue around some of these things. Now, that being said, if we can use certain technologies, so for instance, if I write a little monograph on my view of the world, you read it asynchronously at some point, and you're like, wow, Peter, this is great. Here's mine. I read it, I'm like, wow, Lex, this is awesome. We can be friends without having to spend 10 years figuring all this stuff out together. We can just read each other's thing and be like, oh yeah, this guy's exactly in my wheelhouse, and vice versa, and we can then connect just a few times a year and maintain a high trust relationship. It can be expanded a little bit, but it also requires, these things are not all technological in nature, it requires the individual themselves to have a certain level of capacity, to have a certain lack of neuroticism. If you wanna use the ocean big five sort of model, people have to be pretty centered. The less centered you are, the fewer authentic connections you can really build for a particular unit of time. It just takes more time. Other people have to put up with your crap. There's just a lot of the stuff that you have to deal with if you are not so well-balanced. So yes, we can help people get better to where they can develop more relationships faster, and then you can maybe expand Dunbar number by quite a bit, but you're not gonna do it, I think it's gonna be hard to get it beyond 10X, kind of the rough swag of what it is. Well, don't you think that AI systems could be an addition to Dunbar's number? So like why- Do you count as one system or multiple AI systems? Multiple AI systems. So I do believe that AI systems, for them to integrate into human society as it is now, have to have a sense of agency. So there has to be a individual, because otherwise we wouldn't relate to them. We could engage certain kinds of individuals to make sense of them for us and be almost like, did you ever watch Star Trek? Like Voyager, like there's the Volta who are like the interfaces, the ambassadors for the Dominion. We may have ambassadors that speak on behalf of these systems. They're like the Mentats of Dune maybe, or something like this. I mean, we already have this to some extent. If you look at the biggest sort of, I wouldn't say AI system, but the biggest cybernetic system in the world is the financial markets. It runs outside of any individual's control. And you have an entire stack of people on Wall Street, Wall Street analysts, to CNBC reporters, whatever. They're all helping to communicate what does this mean? You know, Jim Cramer, like run around and yell and stuff. Like all of these people are part of that lowering of the complexity there to meet sense, to help do sense-making for people at whatever capacity they're at. And I don't see this changing with AI systems. I think you would have ringside commentators talking about all this stuff that this AI system is trying to do over here, over here. Because it's actually a super intelligence. So if you wanna talk about humans interfacing, making first contact with the super intelligence, we're already there. We do it pretty poorly. And if you look at the gradient of power and money, what happens is the people closest to it will absolutely exploit their distance for personal financial gain. So we should look at that and be like, oh, well, that's probably what the future will look like as well. But nonetheless, I mean, we're already doing this kind of thing. So in the future, we can have AI systems, but you're still gonna have to trust people to bridge the sense-making gap to them. See, I just feel like there could be of like millions of AI systems that have agencies. When you say one super intelligence, super intelligence in that context means it's able to solve particular problems extremely well. But there's some aspect of human-like intelligence that's necessary to be integrated into human society. So not financial markets, not sort of weather prediction systems, or I don't know, logistics optimization. I'm more referring to things that you interact with on the intellectual level. And that I think requires, there has to be a backstory. There has to be a personality. I believe it has to fear its own mortality in a genuine way. Like there has to be all, many of the elements that we humans experience that are fundamental to the human condition, because otherwise we would not have a deep connection with it. But I don't think having a deep connection with it is necessarily going to stop us from building a thing that has quite an alien intelligence aspect to it. So the other kind of alien intelligence on this planet is octopuses or octopodes or whatever you wanna call them. Octopi, yeah, there's a little controversy as to what the plural is, I guess. But an octopus. An octopus. Yeah, an octopus, it really acts as a collective intelligence of eight intelligent arms, right? Its arms have a tremendous amount of neural density to them. And I see if we can build, I mean, just let's go with what you're saying. If we build a singular intelligence that interfaces with humans, that has a sense of agency so it can run the cybernetic loop and develop its own theory of mind, as well as it's a theory of action, all of these things, I agree with you, that that's the necessary components to build a real intelligence, right? There's gotta be something at stake. It's gotta make a decision. It's gotta then run the OODA loop. Okay, so we build one of those. Well, if we can build one of those, we can probably build 5 million of them. So we build 5 million of them. And if their cognitive systems are already digitized and already kind of there, we stick a antenna on each of them, bring it all back to a hive mind that maybe doesn't make all the individual decisions for them, but treats each one as almost like a neuronal input of a much higher bandwidth and fidelity, going back to a central system that is then able to perceive much broader dynamics that we can't see. In the same way that a phased array radar, right? You think about how phased array radar works. It's just sensitivity. It's just radars, and then it's hypersensitivity and really great timing between all of them. And with a flat array, it's as good as a curved radar dish, right? So with these things, it's a phased array of cybernetic systems that'll give the centralized intelligence much, much better, much higher fidelity understanding of what's actually happening in the environment. But the more power, the more understanding the central superintelligence has, the dumber the individual fingers of this intelligence are, I think. I think- Not necessarily. In my sense, this is- I don't see what it has to be. This argument, there has to be, the experience of the individual agent has to have the full richness of the human-like experience. You have to be able to be driving the car in the rain, listening to Bruce Springsteen, and all of a sudden break out in tears because remembering something that happened to you in high school or something. You can't plant those memories if that's really needed. But no, I'm- No, but the central agency, I guess I'm saying, in my view, for intelligence to be born, you have to have a decentralization. Each one has to struggle and reach. So each one, in excess of energy, has to reach for order, as opposed to a central place doing so. Have you ever read some sci-fi where there's hive minds? The Werner Wenz, I think, has one of these, and then some of the stuff from, yes, from the Commonwealth Saga. The idea that you're an individual, but you're connected with a few other individuals telepathically as well, and together you form a swarm. So if you are, I ask you, what do you think is the experience of, if you are, well, a Borg, right? If you are one, if you're part of this hive mind, outside of all the aesthetics, forget the aesthetics, internally, what is your experience like? Because I have a theory as to what that looks like. The one question I have for you about that experience is, how much is there a feeling of freedom, of free will? Because I, obviously, as a human, very unbiased, but also somebody who values freedom and biased, it feels like the experience of freedom is essential for trying stuff out, to being creative and doing something truly novel, which is at the core of what you do. Yeah, well, I don't think you have to lose any freedom when you're in that mode, because I think what happens is we think, we still think, I mean, you're still thinking about this in a sense of a top-down command and control hierarchy, which is not what it has to be at all. I think the experience, so I'll just show my cards here. I think the experience of being a robot in that robot swarm, a robot who has agency over their own local environment, that's doing sense-making and reporting it back to the hive mind, I think that robot's experience would be, one, when the hive mind is working well, it would be an experience of talking to God, that you essentially are reporting to, you're sort of saying, here's what I see, I think this is what's gonna happen over here, I'm gonna go do this thing, because I think if I'm gonna do this, this will make this change happen in the environment, and then God, she may tell you, that's great, and in fact, your brothers and sisters will join you to help make this go better, and then she can let your brothers and sisters know, hey, Peter's gonna go do this thing, would you like to help him? Because we think that this will make this thing go better, and they'll say, yes, we'll help him. So the whole thing could be actually very emergent, that the sense of, what does it feel like to be a cell in a network that is alive, that is generative? And I think actually the feeling is serendipity, that there's random order, not random disorder or chaos, but random order, just when you need it, you hear Bruce Springsteen, you turn on the radio, and bam, it's Bruce Springsteen. That feeling of serendipity, I feel like, this is a bit of a flight of fancy, but every cell in your body must have, what does it feel like to be a cell in your body? When it needs sugar, there's sugar, when it needs oxygen, there's just oxygen. Now, when it needs to go and do its work, and pull as one of your muscle fibers, it does its work, and it's great, it contributes to the cause. So this is all, again, a flight of fancy, but I think as we extrapolate up, what does it feel like to be an independent individual with some bounded sense of freedom? All sense of freedom is actually bounded, but with a bounded sense of freedom that still lives within a network that has order to it? And I feel like it has to be a feeling of serendipity. So the cell, there's a feeling of serendipity, even though- It has no way of explaining why it's getting oxygen and sugar when it gets it. So you have to, each individual component has to be too dumb to understand the big picture. No, the big picture's bigger than what it can understand. But isn't that an essential characteristic of the individual, is to be too dumb to understand the bigger picture? Like, not dumb necessarily, but limited in its capacity to understand. Because the moment, okay. The moment you understand, I feel like that leads to, if you tell me now that there's some bigger intelligence controlling everything I do, intelligence broadly defined, meaning like, you know, even the Sam Harris thing, there's no free will. If I'm smart enough to truly understand that that's the case, that's gonna, I don't know if I- We have a philosophical breakdown, right? Because we're in the West and we're pumped full of this stuff of like, you are a golden, fully free individual with all your freedoms and all your liberties and go grab a gun and shoot whatever you want to. No, it's actually, you don't actually have a lot of these. You're not unconstrained, but the areas where you can manifest agency, you're free to do those things. You can say whatever you want on this podcast. You can create a podcast, right? You're not, I mean, you have a lot of this kind of freedom, but even as you're doing this, you are actually, I guess where the denouement of all this is that we are already intelligent agents in such a system, right? In that one of these like robots of one of 5 million little swarm robots or one of the Borg, they're just posting an internal bulletin board. I mean, maybe the Borg cube is just a giant Facebook machine floating in space and everyone's just posting on there. They're just posting really fast and like, oh yeah. It's called the metaverse now. The net's called the metaverse. That's right. Here's the enterprise. Maybe we should all go shoot it. Yeah, everyone upvotes and they're gonna go shoot it. But we already are part of a human online collaborative environment and collaborative sense-making system. It's not very good yet. It's got the overhangs of zombie sense-making institutions all over it, but as that washes away and as we get better at this, we are going to see humanity improving at speeds that are unthinkable in the past. And it's not because anyone's freedoms were limited. In fact, the open-source, I mean, we started this with open-source software, right? The collaboration, what the internet surfaced was the ability for people all over the world to collaborate and produce some of the most foundational software that's in use today, right? That entire ecosystem was created by collaborators all over the place. So these online kind of swarm kind of things are not novel. It's just, I'm just suggesting that future AI systems, if you can build one smart system, you have no reason not to build multiple. If you build multiple, there's no reason not to integrate them all into a collective sense-making substrate. And that thing will certainly have emergent intelligence that none of the individuals and probably not any of the human designers will be able to really put a bow around and explain. But in some sense, would that AI system still be able to go like rural Texas, buy a ranch, go off the grid, go full survivalist? Can you disconnect from the hive mind? You may not want to. So to be ineffective, to be intelligent. You have access to way more intelligence capability if you're plugged into 5 million other really, really smart cyborgs. Why would you leave? So like there's a word control that comes to mind. So it doesn't feel like control, like overbearing control. It's just- I think systems, well, this is to your point. I mean, look at how uncomfortable you are with this concept, right? I think systems that feel like overbearing control will not evolutionarily win out. I think systems that give their individual elements the feeling of serendipity and the feeling of agency, that those systems will win. But that's not to say that there will not be emergent higher level order on top of it. And that's the thing. That's the philosophical breakdown that we're staring right at, which is in the Western mind, I think there's a very sharp delineation between explicit control, Cartesian, like what is the vector? Where is the position? Where is it going? It's completely deterministic. And kind of this idea that things emerge. Everything we see is the emergent patterns of other things. And there is agency when there's extra energy. So you have spoken about a kind of meaning crisis that we're going through. But it feels like since we invented sex and death, we broadly speaking, we've been searching for a kind of meaning. So it feels like a human civilization has been going through a meaning crisis of different flavors throughout its history. Why is, how is this particular meaning crisis different? Or is it really a crisis and it wasn't previously? What's your sense? A lot of human history, there wasn't so much a meaning crisis. There was just a like food and not getting eaten by bears crisis, right? Once you get to a point where you can make food, there was the like not getting killed by other humans crisis. So sitting around wondering what is it all about is actually a relatively recent luxury. And to some extent, the meaning crisis coming out of that is precisely because, well, it's not precisely because I believe that meaning is the consequence of when we make consequential decisions, it's tied to agency, right? When we make consequential decisions, that generates meaning. So if we make a lot of decisions, but we don't see the consequences of them, then it feels like what was the point, right? But if there's all these big things happening, but we're just along for the ride, then it also does not feel very meaningful. Meaning, as far as I can tell, this is my working definition of circa 2021, is generally the result of a person making a consequential decision, acting on it, and then seeing the consequences of it. So historically, just when humans are in survival mode, you're making consequential decisions all the time. So there's not a lack of meaning because like you either got eaten or you didn't, right? You got some food and that's great, you feel good. Like these are all consequential decisions. Only in the post fossil fuel and industrial revolution, could we create a massive leisure class. I could sit around not being threatened by bears, not starving to death, making decisions somewhat, but a lot of times not seeing the consequences of any decisions they make. The general sort of sense of anomie, I think that's the French term for it, in the wake of the consumer society, in the wake of mass media telling everyone, hey, choosing between Hermes and Chanel is a meaningful decision. No, it's not. It's kind of- I don't know what either of those mean. Oh, they're high end luxury purses and crap like that. But the point is that we give people the idea that consumption is meaning, that making a choice of this team versus that team, spectating has meaning. So we produce all of these different things that are as if meaning, right? But really making a decision that has no consequences for us. And so that creates the meaning crisis. Well, you're saying choosing between Chanel and the other one has no consequence. I mean, why is one more meaningful than the other? It's not that it's more meaningful than the other, it's that you make a decision between these two brands and you're told this brand will make me look better in front of other people. If I buy this brand of car, if I wear that brand of apparel, right? A lot of decisions we make are around consumption, but consumption by itself doesn't actually yield meaning. Gaining social status does provide meaning. So that's why in this era of abundant production, so many things turn into status games. The NFT kind of explosion is a similar kind of thing. Everywhere there are status games because we just have so much excess production. But aren't those status games a source of meaning? Do the games we play have to be grounded in physical reality like they are when you're trying to run away from lions? Why can't we in this virtuality world on social media, why can't we play the games on social media, even the dark ones? Right, we can. But you're saying that's creating a meaning crisis. Well, there's a meaning crisis in that there's two aspects of it. Number one, playing those kinds of status games oftentimes requires destroying the planet because it ties to consumption, consuming the latest and greatest version of a thing, buying the latest limited edition sneaker and throwing out all the old ones. Maybe it keeps in the old ones, but the amount of sneakers we have to cut up and destroy every year to create artificial scarcity for the next generation, right? This is kind of stuff that's not great. It's not great at all. So conspicuous consumption fueling status games is really bad for the planet, not sustainable. The second thing is you can play these kinds of status games but then what it does is it renders you captured to the virtual environment. The status games that really wealthy people are playing are all around the hard resources where they're gonna build the factories, they're gonna have the fuel and the rare earths to make the next generation of robots. They're then going to run games, run circles around you and your children. So that's another reason not to play those virtual status games. So you're saying ultimately the big picture game is won by people who have access or control over actual hard resources. So you don't see a society where most of the games are played in the virtual space. They'll be captured in the physical space. It all builds. It's just like the stack of human being, right? If you only play the game at the cultural and then intellectual level, then the people with the hard resources and access to layer zero physical are going to own you. But isn't money not connected to or less and less connected to hard resources and money still seems to work? It's a virtual technology. There's different kinds of money. Part of the reason that some of the stuff is able to go a little unhinged is because the big sovereignties where one spends money and uses money and plays money games and inflates money, their ability to adjudicate the physical resources and hard resources and land and things like that, those have not been challenged in a very long time. So, you know, we went off the gold standard. Most money is not connected to physical resources. It's an idea. And that idea is very closely connected to status. But it's also tied to, like, it's actually tied to law. It is tied to some physical hard things, so you have to pay your taxes. Yes, so it's always at the end going to be connected to the blockchain of physical reality. So in the case of law and taxes, it's connected to government. And government is what violence is the, I'm playing on the stacks of devil's advocates here. I'm popping one devil off the stack at a time. Isn't ultimately, of course, it'll be connected to physical reality, but just because people control the physical reality, it doesn't mean the status. LeBron James, in theory, could make more money than the owners of the teams, in theory. And to me, that's a virtual idea. So somebody else constructed a game, and now you're playing in the virtual space of the game. And so it just feels like there could be games where status, we build realities that give us meaning in the virtual space. Like, I can imagine such things being possible. Oh, yeah, okay, so I see what you're, I think I see what you're saying there. With the idea there, I mean, we'll take the LeBron James side and put in some YouTube influencer. Yes, sure. So the YouTube influencer, it is status games, but at a certain level, it precipitates into real dollars. And into, well, you look at Mr. Beast, right? He's like sending off half a million dollars worth of fireworks or something on a YouTube video. And also like saving trees and so on. Sure, right, and trying to plant a million trees with Mark Rober or whatever it was. Yeah, it's not that those kinds of games can't lead to real consequences. It's that for the vast majority of people in consumer culture, they are incented by the, I would say mostly I'm thinking about middle-class consumers. They're incented by advertisements, they're scented by their mimetic environment to treat the purchasing of certain things, the need to buy the latest model of whatever, the need to appear however, the need to pursue status games as a driver of meaning. And my point would be that it's a very hollow driver of meaning, and that is what creates a meaning crisis. Because at the end of the day, it's like eating a lot of empty calories, right? Yeah, it tasted good going down, a lot of sugar, but man, it was not enough protein to help build your muscles. And you kind of feel that in your gut. And I think that's, I mean, so all this stuff aside, and setting aside our discussion on currency, which I hope we get back to, that's what I mean about the meaning crisis, part of it being created by the fact that we don't, we're not encouraged to have more and more direct relationships. We're actually alienated from relating to, even our family members sometimes, right? We're encouraged to relate to brands. We're encouraged to relate to these kinds of things that then tell us to do things that are really of low consequence. And that's where the meaning crisis comes from. So the role of technology in this, so there's somebody you mentioned who's Jacques Eliel, his view of technology, he warns about the towering piles of technique, which I guess is a broad idea of technology. Yes. So I think, correct me if I'm wrong, for him, technology is bad, it moving away from human nature, and it's ultimately is destructive. My question broadly speaking, this meaning crisis, can technology, what are the pros and cons of technology? Can it be a good? Yeah, I think it can be. I certainly draw on some of the Lowell's ideas, and I think some of them are pretty good. But the way he defines technique is, well, also Simondon as well. I mean, he speaks to the general mentality of efficiency. Homogenized processes, homogenized production, homogenized labor to produce homogenized artifacts, that then are not actually, they don't sit well in the environment. So it's essentially, you can think of it as the antonym of craft. Whereas a craftsman will come to a problem, maybe a piece of wood, and they make into a chair, it may be a site to build a house, or build a stable, or build whatever. And they will consider how to bring various things in to build something well contextualized, that's in right relationship with that environment. But the way we have driven technology over the last 100, 150 years, is not that at all. It is, how can we make sure the input materials are homogenized, cut to the same size, diluted and doped to exactly the right alloy concentrations? How do we create machines that then consume exactly the right kind of energy to be able to run at this high speed, to stamp out the same parts, which then go out the door, everyone gets the same tickle me Elmo. And the reason why everyone wants it is because we have broadcasts that tells everyone this is the cool thing. So we homogenize demand, right? And we're like Baudrillard, and other critiques of modernity coming from that direction, you know, the situation list as well. It's that their point is that at this point in time, consumption is the thing that drives a lot of the economic stuff, not the need, but the need to consume and build status games on top. So we have homogenized, when we discovered, I think this is really like Bernays and stuff, right? In the early 20th century, we discovered we can create, we can create demand, we can create desire in a way that was not possible before because of broadcast media. And not only do we create desire, we don't create desire for each person to connect to some bespoke thing to build a relationship with their neighbor or their spouse. We are telling them, you need to consume this brand, you need to drive this vehicle, you gotta listen to this music, have you heard this, have you seen this movie, right? So creating homogenized demand makes it really cheap to create homogenized product. And now you have economics of scale. So we make the same Tickle Me Elmo, give it to all the kids, and all the kids are like, hey, I got a Tickle Me Elmo, right? So this is, ultimately, where this ties in then to runaway hyper-capitalism is that we then, capitalism is always looking for growth. It's always looking for growth, and growth only happens at the margins. So you have to squeeze more and more demand out, you gotta make it cheaper and cheaper to make the same thing, but tell everyone they're still getting meaning from it. You're still like, this is still your Tickle Me Elmo, right? And we see little bits of this dripping, critiques of this dripping in popular culture. You see it sometimes, it's when Buzz Lightyear walks into the thing, he's like, oh my God, at the toy store, I'm just a toy. Like there's millions of other, or there's hundreds of other Buzz Lightyears, just like me, right? That is, I think, a fun Pixar critique on this homogenization dynamic. I agree with you on most of the things you're saying, so I'm playing devil's advocate here, but this homogenized machine of capitalism is also the thing that is able to fund, if channeled correctly, innovation, invention, and development of totally new things that, in the best possible world, create all kinds of new experiences that can enrich lives, the quality of lives for all kinds of people. So isn't this the machine that actually enables the experiences and more and more experiences that will then give meaning? It has done that to some extent. I mean, it's not all good or bad, in my perspective. You know, we can always look backwards and offer a critique of the path we've taken to get to this point in time, but that's a different, that's somewhat different and informs the discussion, but it's somewhat different than the question of where do we go in the future, right? Is this still the same rocket we need to ride to get to the next point? Will it even get us to the next point? Well, how does this, so you're predicting the future, how does it go wrong, in your view? We have the mechanisms, we have now explored enough technologies to where we can actually, I think, sustainably produce what most people in the world need to live. We have also created the infrastructures to allow continued research and development of additional science and medicine and various other kinds of things. The organizing principles that we use to govern all these things today have been, a lot of them have been just inherited from, honestly, medieval times. Some of them have refactored a little bit in the industrial era, but a lot of these modes of organizing people are deeply problematic, and furthermore, they're rooted in, I think, a very industrial mode perspective on human labor. And this is one of those things, I'm gonna go back to the open source thing. There was a point in time when, well, let me ask you this. If you look at the core SciPy sort of collection of libraries, that's SciPy, NumPy, Matplotlib, right? There's IPython Notebook, let's throw Pandas in there, Scikit-learn, a few of these things. How much value do you think, economic value, would you say they drive in the world today? That's one of the fascinating things about talking to you and Travis, it's like, it's a measure, it's like- At least a billion dollars a day, maybe? Billion dollars, sure. I mean, it's like, it's a similar question of like, how much value does Wikipedia create? Right. It's like, all of it, I don't know. Well, I mean, I think, all of it, I don't know. Well, I mean, if you look at our systems, when you do a Google search, right? Now, some of that stuff runs through TensorFlow, but when you look at, you know, Siri, when you do credit card transaction, fraud, like just everything, right? Every intelligence agency under the sun, they're using some aspect of these kinds of tools. So I would say that these create billions of dollars of value. Oh, you mean like direct use of tools that leverage- Yeah, direct, yeah. Yeah, even that's billions a day, yeah. Yeah, right, easily, I think. Like the things they could not do if they didn't have these tools, right? Yes. So that's billions of dollars a day, great. I think that's about right. Now, if we take how many people did it take to make that? Right, and there was a point in time, not anymore, but there was a point in time when they could fit in a van. I could have fit them in my Mercedes Spinter, right? And so if you look at that, like, holy crap, literally a van of maybe a dozen people could create value to the tune of billions of dollars a day. What lesson do you draw from that? Well, here's the thing. What can we do to do more of that? Like that's open source. The way I've talked about this in other environments is when we use generative participatory crowdsourced approaches, we unlock human potential at a level that is better than what capitalism can do. I would challenge anyone to go and try to hire the right 12 people in the world to build that entire stack the way those 12 people did that, right? They would be very, very hard pressed to do that. If a hedge fund could just hire a dozen people and create like something that is worth billions of dollars a day, every single one of them would be racing to do it, right? But finding the right people, fostering the right collaborations, getting it adopted by the right other people to then refine it, that is a thing that was organic in nature. That took crowdsourcing, that took a lot of the open source ethos, and it took the right kinds of people, right? None of those people who started that said, I need to have a part of a multi-billion dollar a day sort of enterprise. They're like, I'm doing this cool thing to solve my problem for my friends, right? So the point of telling the story is to say that our way of thinking about value, our way of thinking about allocation of resources, our ways of thinking about property rights and all these kinds of things, they come from finite game, scarcity mentality, medieval institutions. As we are now entering, to some extent, we are sort of in a post-scarcity era, although some people are hoarding a whole lot of stuff. We are at a point where, if not now, soon, we'll be in a post-scarcity era. The question of how we allocate resources has to be revisited at a fundamental level, because the kind of software these people built, the modalities that those human ecologies that built that software, it treats software as unproperty. Actually, sharing creates value. Restricting and forking reduces value. So that's different than any other physical resource that we've ever dealt with. It's different than how most corporations treat software IP, right? So if treating software in this way created this much value so efficiently, so cheaply, because feeding a dozen people for 10 years is really cheap, right? That's the reason I care about this right now, is because looking forward, when we can automate a lot of labor, where we can, in fact, the programming for your robot in your part of the neck of the woods and your part of the Amazon to build something sustainable for you and your tribe to deliver the right medicines, to take care of the kids, that's just software, that's just code. That could be totally open-sourced, right? So we can actually get to a mode where all of this additional generative things that humans are doing, they don't have to be wrapped up in a container and then we charge for all the exponential dynamics out of it. That's what Facebook did. That's what modern social media did, right? Because the old internet was connecting people just fine. So Facebook came along and said, well, anyone can post a picture, anyone can post some text, and we're gonna amplify the crap out of it to everyone else. And it exploded this generative network of human interaction. And then I said, how do I make money off that? Oh yeah, I'm gonna be a gatekeeper on everybody's attention. And that's how we make money. So how do we create more than one van? How do we have millions of vans full of people that create NumPy, SciPy, that create Python? So, you know, the story of those people is often they have some kind of job outside of this. This is what they're doing for fun. Don't you need to have a job? Don't you have to be connected, plugged in to the capitalist system? Isn't that what, like, isn't this consumerism, the engine that results in the individuals that kind of take a break from it every once in a while to create something magical? Like at the edges is where the innovation happens. Right, the question of surplus, right? This is the question. Like if everyone were to go and run their own farm, no one would have time to go and write NumPy, SciPy, right? Maybe, but that's what I'm talking about when I say we're maybe at a post-scarcity point for a lot of people. The question that we're never encouraged to ask in a Super Bowl ad is how much do you need? How much is enough? Do you need to have a new car every two years, every five? If you have a reliable car, can you drive one for 10 years, is that all right? I had a car for 10 years and it was fine. You know, your iPhone, do you have to upgrade every two years? I mean, it's sort of, you're using the same apps you did four years ago, right? This should be a Super Bowl ad. This should be a Super Bowl ad, that's great. Maybe somebody- Do you really need a new iPhone? Maybe one of our listeners will fund something like this of like, no, but just actually bringing it back, bringing it back to actually the question of what do you need? How do we create the infrastructure for collectives of people to live on the basis of providing what we need, meeting people's needs with a little bit of excess to handle emergencies and things like that, pulling our resources together to handle the really, really big emergencies, somebody with a really rare form of cancer or some massive fire sweeps through half the village or whatever, but can we actually unscale things and solve for people's needs and then give them the capacity to explore how to be the best version of themselves? And for Travis, that was throwing away his shot of tenure in order to write NumPy. For others, there is a saying in the Sci-Fi community that Sci-Fi advances one failed postdoc at a time. And that's, we can do these things. We can actually do this kind of collaboration because code, software, information organization, that's cheap. Those bits are very cheap to fling across the oceans. So you mentioned Travis. We've been talking and we'll continue to talk about open source. Maybe you can comment. How did you meet Travis? Who is Travis Alphont? What's your relationship been like through the years? Where did you work together? How did you meet? What's the present and the future look like? Yeah, so the first time I met Travis was at a Sci-Fi conference in Pasadena. Do you remember the year? 2005. I was working at, again, at Nthought, working on scientific computing, consulting. And a couple of years later, he joined us at Nthought, I think 2007. And he came in as president, one of the founders of Nthought was the CEO, Eric Jones. And we were all very excited that Travis was joining us. And that was great fun. And so I worked with Travis on a number of consulting projects and we worked on some open source stuff. I mean, it was just a really, it was a good time there. And then- It was primarily Python related? Oh yeah, it was all Python, NumPy, Sci-Fi consulting kind of stuff. Towards the end of that time, we started getting called into more and more finance shops. They were adopting Python pretty heavily. I did some work on like a high frequency trading shop, working on some stuff. And then we worked together on some, a couple of investment banks in Manhattan. And so we started seeing that there was a potential to take Python in the direction of business computing. More than just being this niche like MATLAB replacement for big vector computing, what we were seeing was, oh yeah, you could actually use Python as a Swiss army knife to do a lot of shadow data transformation kind of stuff. So that's when we realized the potential is much greater. And so we started Anaconda, I mean, it was called Continuum Analytics at the time, but we started in January of 2012 with a vision of shoring up the parts of Python that needed to get expanded to handle data at scale, to do web visualization, application development, et cetera. And that was that, yeah. So he was CEO and I was president for the first five years. And then we raised some money and then the board sort of put in a new CEO. They hired a kind of professional CEO. And then Travis, you laugh at that. I took over the CTO role. Travis then left after a year to do his own thing, to do QuantSite, which was more oriented around some of the bootstrap years that we did at Continuum, where it was open source and consulting. It wasn't sort of like gung-ho product development and it wasn't focused on, we accidentally stumbled into the package management problem at Anaconda, but then we had a lot of other visions of other technology that we built in the open source. And Travis was really trying to push, again, the frontiers of numerical computing, vector computing, handling things like auto differentiation and stuff intrinsically in the open ecosystem. So I think that's the, that's kind of the direction he's working on in some of his work. We remain great friends and colleagues and collaborators, even though he's no longer day-to-day working at Anaconda, but he gives me a lot of feedback about this and that and the other. What's a big lesson you've learned from Travis about life or about programming or about leadership? Wow, there's a lot. There's a lot. Travis is a really, really good guy. He really, his heart is really in it. He cares a lot. I've gotten that sense having to interact with him. It's so interesting. Such a good human being. He's a really good dude. And he and I, it's so interesting. We come from very different backgrounds. We're quite different as people, but I think we can not talk for a long time and then be on a conversation and be eye-to-eye on like 90% of things. And so he's someone who I believe, no matter how much fog settles in over the ocean, his ship, my ship are pointed sort of in the same direction to the same star. Wow, that's a beautiful way to phrase it. No matter how much fog there is, we're pointed at the same star. Yeah, and I hope he feels the same way. I mean, I hope he knows that over the years now. We both care a lot about the community. For someone who cares so deeply, I would say this about Travis that's interesting. For someone who cares so deeply about the nerd details of like type system design and vector computing and efficiency of expressing this and that and the other, memory layouts and all that stuff, he cares even more about the people in the ecosystem, the community. And I have a similar kind of alignment. I care a lot about the tech. I really do. But for me, the beauty of what this human ecology has produced is I think a touchstone. It's an early version. We should look at it and say, how do we replicate this for humanity at scale? What this open source collaboration was able to produce, how can we be generative in human collaboration moving forward and create that as a civilizational kind of dynamic? Like, can we seize this moment to do that? Because like a lot of the other open source movements, it's all nerds nerding out on code for nerds. And this, because it's scientists, because it's people working on data, that all of it faces real human problems. I think we have an opportunity to actually make a bigger impact. Is there a way for this kind of open source vision to make money? Absolutely. To fund the people involved? Is that an essential part of it? It's hard, but we're trying to do that in our own way at Anaconda, because we know that business users, as they use more of the stuff, they have needs that like business specific needs around security, provenance. They really can't tell their VPs and their investors, hey, we're having, our data scientists are installing random packages from who knows where and running on customer data. So they have to have someone to talk to you. And that's what Anaconda does. So we are a governed source of packages for them. And that's great. That makes some money. We take some of that and we just take that as a dividend. We take a percentage of our revenues and write that as a dividend for the open source community. But beyond that, I really see the development of a marketplace for people to create notebooks, models, data sets, curation of these different kinds of things, and to really have a long tail marketplace dynamic with that. Can you speak about this problem that you stumbled into of package management, Python package management? What is that? A lot of people speak very highly of Conda, which is part of Anaconda, which is a package manager. There's a ton of packages. So first, what are package managers? And second, what was there before? What is pip? And why is Conda more awesome? The package problem is this, which is that in order to do numerical computing efficiently with Python, there are a lot of low-level libraries that need to be compiled, compiled with a C compiler or C++ compiler or Fortran compiler. They need to not just be compiled, but they need to be compiled with all of the right settings. And oftentimes those settings are tuned for specific chip architectures. And when you add GPUs to the mix, when you look at different operating systems, you may be on the same chip, but if you're running Mac versus Linux versus Windows on the same x86 chip, you compile and link differently. All of this complexity is beyond the capability of most data scientists to reason about. And it's also beyond what most of the package developers want to deal with too. Because if you're a package developer, you're like, I code on Linux, this works for me, I'm good. It is not my problem to figure out how to build this on an ancient version of Windows. That's just simply not my problem. So what we end up with is we have a creator, or create a very creative crowdsourced environment where people want to use this stuff, but they can't. And so we ended up creating a new set of technologies like a build recipe system, a build system, and an installer system that is able to, well, to put it simply, it's able to build these packages correctly on each of these different kinds of platforms and operating systems, and make it so when people want to install something, they can, it's just one command. They don't have to set up a big compiler system and do all these things. So when it works well, it works great. Now, the difficulty is we have literally thousands of people writing code in the ecosystem, building all sorts of stuff. And each person writing code, they may take a dependence on something else. And so all this web, incredibly complex web of dependencies. So installing the correct package for any given set of packages you want, getting that right subgraph is an incredibly hard problem. And again, most data scientists don't want to think about this. They're like, I want to install NumPy and Pandas. I want this version of some like geospatial library. I want this other thing. Like, why is this hard? These exist, right? And it is hard because it's, well, you're installing this on a version of Windows, right? And half of these libraries are not built for Windows. Or the latest version isn't available, but the old version was. If you go to the old version of this library, that means you need to go to a different version of that library. And so the Python ecosystem, by virtue of being crowdsourced, we were able to fill a hundred thousand different niches. But then we also suffer this problem that because it's crowdsourced and no one, it's like a tragedy of the commons, right? No one really wants to support their thousands of other dependencies. So we end up sort of having to do a lot of this. And of course the Conda Forge community also steps up as an open source community that maintains some of these recipes. That's what Conda does. Now, Pip is a tool that came along after Conda to some extent. It came along as an easier way for the Python developers writing Python code that didn't have as much compiled stuff. They could then install different packages. And what ended up happening in the Python ecosystem was that a lot of the core Python and web Python developers, they never ran into any of this compilation stuff at all. So even we have, on video, we have Guido van Rossum saying, you know what, the scientific community's packaging problems are just too exotic and different. I mean, you're talking about Fortran compilers, right? Like you guys just need to build your own solution, perhaps, right? So the core Python community went and built its own sort of packaging technologies, not really contemplating the complexity of this stuff over here. And so now we have the challenge where you can Pip install some things, some libraries, if you just want to get started with them, you can Pip install TensorFlow, and that works great. The instant you want to also install some other packages that use different versions of NumPy or some like graphics library or some OpenCV thing or some other thing, you now run into dependency hell. Because you cannot, you know, OpenCV can't have a different version of libjpeg over here than PyTorch over here. Like they actually, and they all have to use the, if you want to use GPU acceleration, they have to all use the same underlying drivers and same GPU CUDA things. So it gets to be very gnarly, and it's a level of technology that both the makers and the users don't really want to think too much about. And that's where you step in and try to solve this- We try to solve it. Subgraph problem. How much is that, I mean, you said that you don't want to think, they don't want to think about it, but how much is it a little bit on the developer and providing them tools to be a little bit more clear of that subgraph of dependency that's necessary? It is getting to a point where we do have to think about, look, can we pull some of the most popular packages together and get them to work on a coordinated release timeline, get them to build against the same test matrix, et cetera, et cetera, right? And there is a little bit of dynamic around this, but again, it is a volunteer community. Yeah. You know, people working on these different projects have their own timelines and their own things they're trying to meet. So we end up trying to pull these things together and then it's this incredibly, and I would recommend just as a business tip, don't ever go into business where when your hard work works, you're invisible. And when it breaks because of someone else's problem, you get flack for it. Because that's in our situation, right? When something doesn't conda install properly, usually it's some upstream issue, but it looks like conda is broken. It looks like, you know, Anaconda screwed something up. When things do work though, it's like, oh yeah, cool. It's worked. Assuming naturally, of course, that's very easy to make that work, right? So we end up in this kind of problematic scenario, but it's okay because I think we're still, you know, our heart's in the right place. We're trying to move this forward as a community sort of affair. I think most of the people in the community also appreciate the work we've done over the years to try to move these things forward in a collaborative fashion, so. One of the sub graphs of dependencies that became super complicated is the move from Python 2 to Python 3. So there's all these ways to mess with these kinds of ecosystems of packages and so on. So I just want to ask you about that particular one. What do you think about the move from Python 2 to 3? Why did it take so long? What were, from your perspective, just seeing the packages all struggle and the community all struggle through this process, what lessons do you take away from it? Why did it take so long? Looking back, some people perhaps underestimated how much adoption Python 2 had. I think some people also underestimated how much, or they overestimated how much value some of the new features in Python 3 really provided. Like the things they really loved about Python 3 just didn't matter to some of these people in Python 2. Because this change was happening as Python, SciPy, was starting to take off really like past like a hockey stick of adoption in the early data science era, in the early 2010s. A lot of people were learning and onboarding in whatever just worked. And the teachers were like, well, yeah, these libraries I need are not supported in Python 3 yet, I'm going to teach you Python 2. Took a lot of advocacy to get people to move over to Python 3. So I think it wasn't any particular single thing, but it was one of those death by a dozen cuts, which just really made it hard to move off of Python 2. And also Python 3 itself, as they were kind of breaking things and changing things around and reorganizing the standard library, there's a lot of stuff that was happening there that kept giving people an excuse to say, I'll put off till the next version. 2 is working fine enough for me right now. So I think that's essentially what happened there. And I will say this though, the strength of the Python data science movement, I think is what kept Python alive in that transition. Because a lot of languages have died and left their user bases behind. If there wasn't the use of Python for data, there's a good chunk of Python users that during that transition would have just left for go and rust and stayed. In fact, some people did. They moved to go and rust and they just never looked back. The fact that we were able to grow by millions of users, the Python data community, that is what kept the momentum for Python going. And now the usage of Python for data is over 50% of the overall Python user base. So I'm happy to debate that on stage somewhere if I was someone that they really want to take issue with that statement. But from where I sit, I think that's true. The statement there, the idea is that the switch from Python 2 to Python 3 would have probably destroyed Python if it didn't also coincide with Python for whatever reason, just overtaking the data science community, anything that processes data. So like the timing was perfect, that this maybe imperfect decision was coupled with a great timing on the value of data in our world. I would say the troubled execution of a good decision. It was a decision that was necessary. It's possible if we had more resources, we could have done in a way that was a little bit smoother, but ultimately, the arguments for Python 3, I bought them at the time and I buy them now, right? Having great text handling is like a non-negotiable table stakes thing you need to have in a language. So that's great. But the execution, Python is the, it's volunteer driven. It's like now the most popular language on the planet, but it's all literally volunteers. So the lack of resources meant that they had to really, they had to do things in a very hamstrung way. And I think to carry the Python momentum in the language through that time, the data movement was a critical part of that. So someone was carrot and stick. I actually have to shamefully admit that it took me a very long time to switch from Python 2 and Python 3 because I'm a machine learning person. It was just for the longest time, you could just do fine with Python 2. Right. But I think the moment where I switched everybody I worked with and switched myself for small projects and big is when finally, when NumPy announced that they're going to end support like in 2020 or something like that. Right. So like when I realized, oh, this is going to end. Right. So that's the stick. That's the stick. That's not a carrot. So for the longest time it was carrots. It was like all of these packages were saying, okay, we have Python 3 support now, come join us. We have Python 2 and Python 3. But when NumPy, one of the packages I sort of love and depend on said like, nope, it's over. That's when I decided to switch. I wonder if you think it was possible much earlier for somebody like NumPy or some major package to step into the cold and say like, we're an anus. Well, it's a chicken and egg problem too, right? You don't want to cut off a lot of users unless you see the user momentum going too. So the decisions for the scientific community for each of the different projects, you know, there's not a monolith. Some projects are like, we'll only be releasing new features on Python 3. Yeah. NumPy is more of a sticky carrot, right? A firm carrot, if you will, a firm carrot. A stick-shaped carrot. But then for others, yeah, NumPy in particular, because it's at the base of the dependency stack for so many things, that was the final stick. That was a stick-shaped stick. People were saying, look, if I have to keep maintaining my releases for Python 2, that's that much less energy that I can put into making things better for the Python 3 folks or in my new version, which is of course going to be Python 3. So people were also getting kind of pulled by this tension. So the overall community sort of had a lot of input into when the NumPy core folks decided that they would end of life on Python 2. So as these numbers are a little bit loose, but there are about 10 million Python programmers in the world. You could argue that number, but let's say 10 million. It's actually where I was looking, it said 27 million total programmers, developers in the world. You mentioned in a talk that changes need to be made for there to be 100 million Python programmers. So first of all, do you see a future where there's 100 million Python programmers? And second, what kind of changes need to be made? So Anaconda, Miniconda get downloaded about a million times a week. So I think the idea that there's only 10 million Python programmers in the world is a little bit undercounting. There are a lot of people who escape traditional counting that are using Python and data in their jobs. I do believe that the future world for it to, well, the world I would like to see is one where people are data literate. So they are able to use tools that let them express their questions and ideas fluidly. And the data variety and data complexity will not go down. It will only keep increasing. So I think some level of code or code-like things will continue to be relevant. And so my hope is that we can build systems that allow people to more seamlessly integrate Python kinds of expressivity with data systems and operationalization methods that are much more seamless. And what I mean by that is, right now you can't punch Python code into an Excel cell. I mean, there's some tools you can do to kind of do this. We didn't build a thing for doing this back in the day, but I feel like the total addressable market for Python users, if we do the things right, is on the order of the Excel users, which is a few hundred million. So I think Python has to get better at being embedded, being a smaller thing that pulls in just the right parts of the ecosystem to run numerics and do data exploration, meeting people where they're already at with their data and their data tools. And then I think also it has to be easier to take some of those things they've written and flow those back into deployed systems or little apps or visualizations. I think if we don't do those things, then we will always be kept in a silo as sort of an expert users tool and not a tool for the masses. You know, I work with a bunch of folks in the Adobe Creative Suite, and I'm kind of forcing them or inspiring them to learn Python to do a bunch of stuff that helps them. And it's interesting, because they probably wouldn't call themselves Python programmers, but they're all using Python. I would love it if the tools like Photoshop and Premiere and all those kinds of tools that are targeted towards creative people, I guess that's where Excel, Excel is targeted towards a certain kind of audience that works with data, financial people, all that kind of stuff, if there would be easy ways to leverage, to use Python for quick scripting tasks. And, you know, there's an exciting application of artificial intelligence in this space that I'm hopeful about looking at now OpenAI Codex with generating programs. So almost helping people bridge the gap from kind of visual interface to generating programs to something formal, and then they can modify it and so on, but kind of without having to read the manual, without having to do a Google search and stack overflow, which is essentially what a neural network does when it's doing code generation, is actually generating code and allowing a human to communicate with multiple programs, and then maybe even programs to communicate with each other via Python. So that to me is a really exciting possibility, because I think there's a friction to kind of, like, how do I learn how to use Python in my life? There's oftentimes you kind of, what, start a class, you start learning about types, I don't know, functions. Like, this is, you know, Python is the first language with which you start to learn to program. But I feel like that's going to take a long time for you to understand why it's useful. You almost want to start with a script. Well, you do, in fact. I think starting with the theory behind programming languages and types and all that, I mean, types are there to make the compiler writer's jobs easier. Types are not, I mean, heck, do you have an ontology of types for just the objects on this table? No. So types are there because compiler writers are human and they're limited in what they can do. But I think that the beauty of scripting, like, there's a Python book that's called Automate the Boring Stuff, which is exactly the right mentality. I grew up with computers in a time when I could, when Steve Jobs was still pitching these things as bicycles for the mind. They were supposed to not be just media consumption devices, but they were actually, you could write some code. You could write basic, you could write some stuff to do some things. And that feeling of a computer as a thing that we can use to extend ourselves has all but evaporated for a lot of people. So you see a little bit in parts in the generation of youth around Minecraft or Roblox. And I think Python, CircuitPython, these things could be a renaissance of that, of people actually shaping and using their computers as computers, as an extension of their minds and their curiosity, their creativity. So, you talk about scripting the Adobe suite with Python in the 3D graphics world. Python is a scripting language that some of these 3D graphics suites use. And I think that's great. We should better support those kinds of things. But ultimately, the idea that I should be able to have power over my computing environment if I want these things to happen repeatedly all the time, I should be able to say that somehow to the computer, right? Now, whether the operating systems get there faster by having some Siri backed with open AI with whatever. So you can just say, Siri, make this do this, do this, and every other Friday, right? We probably will get there somewhere. And Apple's always had these ideas. There's the Apple script in the menu that no one ever uses. But you can do these kinds of things. But when you start doing that kind of scripting, the challenge isn't learning the type system or even the syntax of the language. The challenge is all of the dictionaries and all the objects of all their properties and attributes and parameters. Like who's got time to learn all that stuff, right? So that's when then programming by prototype or by example becomes the right way to get the user to express their desire. So there's a lot of these different ways that we can approach programming. But I do think when, as you were talking about the Adobe scripting thing, I was thinking about, you know, when we do use something like NumPy, when we use things in the Python data and scientific, let's say, expression system, there's a reason we use that, which is that it gives us mathematical precision. It gives us actually quite a lot of precision over precisely what we mean about this dataset, that dataset. And it's the fact that we can have that precision that lets Python be powerful over as a duct tape for data. You know, you give me a TSV or a CSV, and if you give me some massively expensive vendor tool for data transformation, I don't know I'm gonna be able to solve your problem. But if you give me a Python prompt, you can throw whatever data you want at me. I will be able to mash it into shape. So that ability to take it as sort of this like, you know, machete out into the data jungle is really powerful. And I think that's why at some level, we're not gonna get away from some of these expressions and APIs and libraries in Python for data transformation. You've been at the center of the Python community for many years. If you could change one thing about the community to help it grow, to help it improve, to help it flourish and prosper, what would it be? I mean, you know, it doesn't have to be one thing, but what kind of comes to mind? What are the challenges? Humility is one of the values that we have at Anaconda, the company, but it's also one of the values that we have in the community that it's been breached a little bit in the last few years, but in general, people are quite decent and reasonable and nice. And that humility prevents them from seeing the greatness that they could have. I don't know how many people in the core Python community really understand that they stand perched at the edge of an opportunity to transform how people use computers. And actually PyCon, I think it was the last physical PyCon I went to, Russell Keith-Magee gave a great keynote about very much along the lines of the challenges I have, which is Python for a language that doesn't actually, that can't put an interface up on like the most popular computing devices, it's done really well as a language, hasn't it? You can't write a web front end with Python, really. I mean, everyone uses JavaScript. You certainly can't write native apps. So for a language that you can't actually write apps in any of the front end runtime environments, Python's done exceedingly well. And so that wasn't to pat ourselves on the back. That was to challenge ourselves as a community to say, we, through our current volunteer dynamic, have gotten to this point. What comes next and how do we seize, you know, we've caught the tiger by the tail. How do we make sure we keep up with it as it goes forward? So that's one of the questions I have about sort of open source communities is at its best, there's a kind of humility. Is that humility prevent you to have a vision for creating something like very new and powerful? And you've brought us back to consciousness again. The collaboration is a swarm emergent dynamic. Humility lets these people work together without anyone trouncing anyone else. How do they, you know, in consciousness, there's the question of the binding problem. How does a singular, our attention, how does that emerge from, you know, billions of neurons? So how can you have a swarm of people emerge a consensus that has a singular vision to say, we will do this. And most importantly, we're not gonna do these things. Emerging a coherent, pointed, focused leadership dynamic from a collaboration, being able to do that kind of, and then dissolve it so people can still do the swarm thing. That's a problem, it's a question. So do you have to have a charismatic leader? For some reason, Linus Torvald comes to mind, but you know, there's people who criticize. He rules with an iron fist, man. But there's still charisma. There is charisma, right? There's a charisma to that iron fist. There's, every leader is different, I would say, in their success. So he doesn't, I don't even know if you can say he doesn't have humility. There's such a meritocracy of ideas that like, this is a good idea and this is a bad idea. There's a step function to it. Once you clear a threshold, he's open. Once you clear the Bozo threshold, he's open to your ideas, I think. But see, the interesting thing is, obviously that will not stand in an open source community if that threshold that is defined by that one particular person is not actually that good. So you actually have to be really excellent at what you do. So he's very good at what he does. And so there's some aspect of leadership where you can get thrown out, people can just leave. That's how it works with open source, the fork. But at the same time, you want to sometimes be a leader, like with a strong opinion. Because people, I mean, there's some kind of balance here for this hive mind to get behind. Leadership is a big topic. And I didn't, I'm not one of these guys that went to MBA school and said, I'm gonna be an entrepreneur and I'm gonna be a leader and I'm gonna read all these Harvard Business Review articles on leadership and all this other stuff. I was a physicist turned into a software nerd who then really like nerded out on Python. And now I am entrepreneurial, right? I saw a business opportunity around the use of Python or data, but for me, what has been interesting over this journey with the last 10 years is how much I started really enjoying the understanding and thinking deeper about organizational dynamics and leadership. And leadership does come down to a few core things. Number one, a leader has to create belief or at least has to dispel disbelief. Leadership also, you have to have vision, loyalty and experience. So can you say belief in a singular vision? Like what does belief mean? Yeah, belief means a few things. Belief means here's what we need to do and this is a valid thing to do and we can do it. That you have to be able to drive that belief. And every step of leadership along the way has to help you amplify that belief to more people. I mean, I think at a fundamental level, that's what it is. You have to have a vision, you have to be able to show people that, or you have to convince people to believe in the vision and to get behind you. And that's where the loyalty part comes in and the experience part comes in. There's all different flavors of leadership. So if we talk about Linus, we could talk about Elon Musk and Steve Jobs, there's Sunder Pichai, there's people that kind of put themselves at the center and are strongly opinionated and some people are more like consensus builders. What works well for open source? What works well in the space of programmers? So you've been a programmer, you've led many programmers and are now sort of at the center of this ecosystem. What works well in the programming world, would you say? It really depends on the people, what style of leadership is best. And it depends on the programming community. I think for the Python community, servant leadership is one of the values. Like at the end of the day, the leader has to also be the high priest of values. So any collection of people has values of their living. And if you want to maintain certain values and those values help you as an organization become more powerful, then the leader has to live those values unequivocally and has to hold the values. So in our case, in this collaborative community around Python, I think that the humility is one of those values, servant leadership. You actually have to kind of do the stuff. You have to walk the walk, not just talk the talk. I don't feel like the Python community really demands that much from a vision standpoint. And they should. And I think they should. This is the interesting thing is like so many people use Python. From where comes the vision? You have a Elon Musk type character who makes bold statements about the vision for particular companies he's involved with. And it's like, I think a lot of people that work at those companies kind of can only last if they believe that vision. And some of it is super bold. So my question is, and by the way, those companies often use Python, how do you establish a vision? Get to 100 million users, right? Get to where, you know, Python is at the center of the machine learning and was it data science, machine learning, deep learning, artificial intelligence revolution, right? Like in many ways, perhaps the Python community is not thinking of it that way, but it's leading the way on this. Like the tooling is like essential. Right, well, you know, for a while PyCon people in the scientific Python and the PyData community, they would submit talks. Those are early 2010s, mid 2010s. They would submit talks for PyCon and the talks would all be rejected because there was the separate sort of PyData conferences. And they're like, well, these probably belong more to PyData. And instead there'd be yet another talk about, you know, threads and, you know, whatever, some web framework. And it's like, that was an interesting dynamic to see that there was, I mean, at the time it was a little annoying because we wanted to try to get more users and get more people talking about these things. And PyCon is a huge venue, right? It's thousands of Python programmers, but then also came to appreciate that, you know, parallel, having an ecosystem that allows parallel innovation is not bad, right? There are people doing embedded Python stuff. There's people doing web programming, people doing scripting, there's cyber uses of Python. I think the, ultimately at some point, if your slide mode mold covers so much stuff, you have to respect that different things are growing in different areas and different niches. Now, at some point that has to come together and the central body has to provide resources. The principle here is subsidiarity. Give resources to the various groups to then allocate as they see fit in their niches. That would be a really helpful dynamic. But again, it's a volunteer community. It's not like they had that many resources to start with. What was or is your favorite programming setup? What operating system, what keyboard, how many screens, what are you listening to, what time of day, are you drinking coffee, tea? Tea, sometimes coffee, depending on how well I slept. I used to have- How much sleep do you get, are you a night owl? I remember somebody asked you somewhere a question about work-life balance, and like not just work-life balance, but like a family, you know, you lead a company, and your answer was basically like, I still haven't figured it out. Yeah, I think I've gotten a little bit better balance. I have a really great leadership team now supporting me, and so that takes a lot of the day-to-day stuff off my plate, and my kids are getting a little older, so that helps. So, and of course I have a wonderful wife who takes care of a lot of the things that I'm not able to take care of, and she's great. I try to get to sleep earlier now, because I have to get up every morning at six to take my kid down to the bus stop. So there's a hard thing. For a while, I was doing polyphasic sleep, which is really interesting. Like I go to bed at nine, wake up at like 2 a.m., work till five, sleep three hours, wake up at eight. Like that was actually, it was interesting. It wasn't too bad. How did it feel? It was good. I didn't keep it up for years, but once I have travel, then it just, everything goes out the window, right? Because then you're like time zones and all these things. Socially, was it, except like, were you able to live outside of how you felt? Were you able to live normal society? Oh yeah, because like on the nights that I wasn't out hanging out with people or whatever, going to bed at nine, no one cares. I wake up at two, I'm still responding to their Slacks, emails, whatever, and shit posting on Twitter or whatever at two in the morning is great. Right? And then you go to bed for a few hours and you wake up, it's like you had an extra day in the middle. And I'd read somewhere that humans naturally have biphasic sleep or something, I don't know. But- I read basically everything somewhere. So every option of everything is a good option. Every option of everything. I will say that that worked out for me for a while, although I don't do it anymore. In terms of programming setup, I had a 27 inch high DPI setup that I really liked, but then I moved to a curved monitor just because when I moved to the new house, I want to have a bit more screen for Zoom plus communications, plus, you know, like various kinds of things. So it's like one large monitor. One large curved monitor. What operating system? Mac. Okay. Yeah. Is that what happens when you become important? Is you stop using Linux and Windows? No, I actually have a Windows box as well on the next table over, but I have three desks, right? Yes. So main one is the standing desk so that I can, you know, whatever, when I'm like, I have a teleprompter set up and everything else. And then I've got my iMac and then eGPU and then Windows PC. The reason I moved to Mac was it's got a Linux prompt or no, sorry, it's got a Unix prompt. It's got a Unix prompt so I can do all my stuff. But then I don't have to worry. Like when I'm presenting for clients or investors, whatever, like it, I don't have to worry about any like ACPI related F-sick things in the middle of a presentation, like none of that. It just, it will always wake from sleep and it won't kernel panic on me. And this is not a dig against Linux, except that I just, I feel really bad. I feel like a traitor to my community saying this, right? But in 2012, I was just like, okay, start my own company, what do I get? And Linux laptops were just not quite there. Yes. I'm stuck with Maxon. Can I just defend something that nobody respectable seems to do, which is, so I do a boot on Linux Windows, but in Windows, I have a Windows subsystems for Linux or whatever, WSL. And I find myself being able to handle everything I need and almost everything I need in Linux for basic sort of tasks, scripting tasks within WSL and it creates a really nice environment. So I've been, but like whenever I hang out with like especially important people, like they're all on iPhone and a Mac. And it's like, yeah, like what there is a messiness to Windows and a messiness to Linux that makes me feel like you're still in it. Well, the Linux stuff, Windows subsystem for Linux is very tempting, but there's still the Windows on the outside where I don't know where, and I've been, okay, I've been, I've used DOS since version 1.11 or 1.21 or something. So I've been a long time Microsoft user. And I will say that like, like it's really hard for me to know where anything is, how to get to the details behind something when something screws up as invariably does. And just things like changing group permissions on some shared folders and stuff, just everything seems a little bit more awkward, more clicks than it needs to be. Not to say that there aren't weird things like hidden attributes and all this other happy stuff on Mac, but for the most part, and well, actually, especially now with the new hardware coming out on Mac, it'll be very interesting, with the new M1, there were some dark years the last few years when I was like, I think maybe I have to move off of Mac as a platform. But this, I mean, like my keyboard was just not working. Like literally my keyboard just wasn't working, right? I had this touch bar, didn't have a physical escape button like I needed to, because I used Vim. And now I think we're back. So. So you use Vim and you have a, what kind of keyboard? So I use a Realforce 87U. It's a mechanical, it's a topro key switch. It's a weird shape, there's a normal shape. Normal shape. Oh no, because I say that because I use a Kinesis and I had, you said some dark, you said you had dark moments. I have, I recently had a dark moment, it's like, what am I doing with my life? So I remember sort of flying in a very kind of tight space and as I'm working, this is what I would do on an airplane. I pull out a laptop and on top of the laptop, I'll put a Kinesis keyboard. That's hardcore, man. I was thinking, is this who I am? Is this what I'm becoming? Will I be this person? Because I'm on Emacs with this Kinesis keyboard sitting like with everybody around. Emacs on Windows. On WSL, yeah. Yeah, Emacs on Linux on Windows. Yeah, on Windows. And like everybody around me is using their iPhone to look at TikTok. So I'm like in this land and I thought, you know what? Maybe I need to become an adult and put the nineties behind me and use like a normal keyboard. And then I did some soul searching and I decided like, this is who I am. This is me like coming out of the closet to saying, I'm Kinesis keyboard all the way. I'm going to use Emacs. You know who else is a Kinesis fan? Wes McKinney, the creator of Pandas. Oh. He just, he banged out Pandas on a Kinesis keyboard, I believe. I don't know if he's still using one, maybe, but certainly 10 years ago, like he was. If anyone's out there, maybe we need to have a Kinesis support group. Please reach out. Isn't there already one? Is there one? I don't know. There's gotta be an IRC channel, man. Oh no. And you access it through Emacs. Okay. Do you still program these days? I do a little bit. Honestly, the last thing I did was I had written, I was working with my son to script some Minecraft stuff. So I was doing a little bit of that. That was the last, literally the last code I wrote. Oh, you know what? Also I wrote some code to do some cap table evaluation, waterfall modeling kind of stuff. What advice would you give to a young person, say your son, today in high school, maybe even college about career, about life? This may be where I get into trouble a little bit. We are coming to the end. We're rapidly entering a time between worlds. So we have a world now that's starting to really crumble under the weight of aging institutions that no longer even pretend to serve the purposes they were created for. We are creating technologies that are hurtling billions of people headlong into philosophical crises who they don't even know the philosophical operating systems in their firmware. And they're heading into a time when that gets vaporized. So for people in high school, and certainly I tell my son this as well, he's in middle school, people in college, you are going to have to find your own way. You're going to have to have a pioneer spirit, even if you live in the middle of the most dense urban environment. All of human reality around you is the result of the last few generations of humans agreeing to play certain kinds of games. A lot of those games no longer operate according to the rules they used to. Collapse is nonlinear, but it will be managed. And so if you are in a particular social caste or economic caste, and it's not, I think it's not kosher to say that about America, but America is a very stratified and classist society. There's some mobility, but it's really quite classist. And in America, unless you're in the upper middle class, you are headed into very choppy waters. So it is really, really good to think and understand the fundamentals of what you need to build a meaningful life for you, your loved ones, with your family. And almost all of the technology being created that's consumer facing is designed to own people, to take the four stack of people, to delaminate them and to own certain portions of that stack. And so if you want to be an integral human being, if you want to have your agency and you want to find your own way in the world, when you're young would be a great time to spend time looking at some of the classics around what it means to live a good life, what it means to build connection with people. And so much of the status game, so much of the stuff, one of the things that I sort of talk about as we create more and more technology, there's a gradient technology, and a gradient technology always leads to a gradient in power. And this is Jacques Allure's point to some extent as well. That gradient in power is not going to go away. Technologies are going so fast that even people like me who helped create some of the stuff I'm being left behind. That's some cutting edge research. I don't know what's going on in GANs today. You know, I'll go read some proceedings. So as the world gets more and more technological, it'll create more and more gradients where people will seize power, economic fortunes. And the way they make the people who are left behind okay with their lot in life is they create lottery systems. They make you take part in the narrative of your own being trapped in your own economic sort of zone. So avoiding those kinds of things is really important, knowing when someone is running game on you basically. So these are the things I would tell young people. It's a dark message, but it's realism. I mean, that's what I see. So after you gave some realism, you sit back, you sit back with your son, you're looking out at the sunset. What to him can you give as words of hope? And to you, from where do you derive hope for the future of our world? So you said at the individual level, you have to have a pioneer mindset to go back to the classics to understand what is in human nature you can find meaning. But at the societal level, what trajectory, when you look at possible trajectories, what gives you hope? What gives me hope is that we have little tremors now, shaking people out of the reverie of the fiction of modernity that they've been living in, kind of a late 20th century style modernity. That's good, I think, because, and also to your point earlier, people are burning out on some of the social media stuff. They're sort of seeing the ugly side, especially the latest news with Facebook and the whistleblower, right? It's quite clear these things are not all they're cracked up to be. So- Do you believe, like, I believe better social media can be built because they are burning out and they'll incentivize other competitors to be built. Do you think that's possible? Well, the thing about it is that when you have extractive return on returns, you know, capital coming in and saying, look, you own a network, give me some exponential dynamics out of this network. What are you gonna do? You're gonna just basically put a toll keeper at every single node and every single graph edge, every node, every vertex, every edge. But if you don't have that need for it, if no one's sitting there saying, hey, Wikipedia monetize every character, every byte, every phrase, then generative human dynamics will naturally sort of arise assuming we do, we respect a few principles around online communications. So the greatest and biggest social network in the world is still like email, SMS, right? So we're fine there. The issue with the social media, as we call it now, is they're actually just new amplification systems, right? Now it's benefit of certain people like yourself who have interesting content to be amplified. So it's created a greater economy and that's cool. There's a lot of great content out there, but giving everyone a shot at the fame lottery, saying, hey, you could also have your, if you wiggle your butt the right way on TikTok, you can have your 15 seconds of micro fame. That's not healthy for society at large. So I think if we can create tools that help people be conscientious about their attention, spend time looking at the past and really retrieving memory and calling, not calling, but processing and thinking about that, I think that's certainly possible and hopefully that's what we get. So the bigger picture, the bigger question that you're asking about what gives me hope is that these early shocks of COVID lockdowns and remote work and all these different kinds of things, I think it's getting people to a point where they are looking, they're sort of no longer in the reverie. As my friend, Jim Rutt says, there's more people with ears to hear now. With pandemic and education, everyone's like, wait, wait, what have you guys been doing with my kids? Like, how are you teaching them? What is this crap you're giving them as homework? So I think these are the kinds of things that are getting in the supply chain disruptions, getting more people to think about how do we actually just make stuff? This is all good, but the concern is that it's still gonna take a while for these things, for people to learn how to be agentic again and to be in right relationship with each other and with the world. So the message of hope is still people are resilient and we are building some really amazing technology. And I also, like, to me, I derive a lot of hope from individuals in that van. The power of a single individual to transform the world, to do positive things for the world is quite incredible. Now you've been talking about, it's nice to have as many of those individuals as possible, but even the power of one, it's kind of magical. It is, it is. We're in a mode now where we can do that. I think also, part of what I try to do is, in coming to podcasts like yours and then spamming you with all this philosophical stuff that I've got going on, there are a lot of good people out there trying to put words around the current technological, social, economic crises that we're facing. And in the space of a few short years, I think there has been a lot of great content produced around this stuff for people who wanna see, wanna find out more or think more about this. We're popularizing certain kinds of philosophical ideas that move people beyond just the, oh, you're communist, oh, you're capitalist kind of stuff. Like it's sort of, we're way past that now. So that also gives me hope that I feel like I myself am getting a handle on how to think about these things. It makes me feel like I can hopefully affect change for the better. We've been sneaking up on this question all over the place. Let me ask the big, ridiculous question. What is the meaning of life? Wow. The meaning of life. Yeah, I don't know. I mean, I've never really understood that question. When you say meaning crisis, you're saying that there is a search for a kind of experience that's, could be described as fulfillment, as like the aha moment of just like joy and maybe when you see something beautiful or maybe you have created something beautiful, that experience that you get, it feels like it all makes sense. So some of that is just chemicals coming together in your mind and all those kinds of things. But it seems like we're building a sophisticated collective intelligence that's providing meaning in all kinds of ways to its members. And there's a theme to that meaning. So for a lot of history, I think faith played an important role. Faith in God, sort of religion. I think technology in the modern era is kind of serving a little bit of a source of meaning for people, like innovation of different kinds. I think the old school things of love and the basics of just being good at stuff. But you were a physicist, so there's a desire to say, okay, yeah, but these seem to be like symptoms of something deeper. Right. Like why? What's capital M meaning? Yeah, what's capital M meaning? Why are we reaching for order when there is excess of energy? I don't know if I can answer the why. Any why that I come up with, I think, is gonna be, I'd have to think about that a little more, maybe get back to you on that. But I will say this. We do look at the world through a traditional, I think most people look at the world through what I would say is a subject-object metaphysical lens, that we have our own subjectivity, and then there's all of these object things that are not us. So I'm me, and these things are not me, right? And I'm interacting with them, I'm doing things to them. But a different view of the world that looks at it as much more connected, that realizes, oh, I'm really quite embedded in a soup of other things, and I'm simply almost like a standing wave pattern of different things, right? So when you look at the world in that kind of connected sense, I've recently taken a shine to this particular thought experiment, which is, what if it was the case that everything that we touch with our hands, that we pay attention to, that we actually give intimacy to, what if there's actually, all the mumbo jumbo, like people with the magnetic healing crystals and all this other kind of stuff and quantum energy stuff, what if that was a thing? What if, literally, when your hand touches an object, when you really look at something and you concentrate and you focus on it and you really give it attention, you actually give it, there is some physical residue of something, a part of you, a bit of your life force that goes into it. Okay, now this is of course completely mumbo jumbo stuff. This is not, like I don't actually think this is real, but let's do the thought experiment. What if it was? What if there actually was some quantum magnetic crystal and energy field thing that just by touching this can, this can has changed a little bit somehow. And it's not much unless you put a lot into it and you touch it all the time, like your phone, right? These things gained, they gain meaning to you a little bit, but what if there's something that technical objects, the phone is a technical object. It does not really receive attention or intimacy and then allow itself to be transformed by it. But if it's a piece of wood, if it's the handle of a knife that your mother used for 20 years to make dinner for you, right? What if it's a keyboard that you banged out your world transforming software library on? These are technical objects and these are physical objects, but somehow there's something to them. We feel an attraction to these objects as if we have imbued them with life energy, right? So if you walk that thought experiment through, what happens when we touch another person, when we hug them, when we hold them? And the reason this ties into my answer for your question is that there's, if there is such a thing, if we were to hypothesize, you know, hypothesize it's such a thing, it could be that the purpose of our lives is to imbue as many things with that love as possible. That's a beautiful answer and a beautiful way to end it. Peter, you're an incredible person. Thank you. Spending so much in the space of engineering and in the space of philosophy, I'm really proud to be living in the same city as you. And I'm really grateful that you would spend your valuable time with me today. Thank you so much. Well, thank you. I appreciate the opportunity to speak with you. Thanks for listening to this conversation with Peter Wang. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Peter Wang himself. We tend to think of people as either malicious or incompetent. But in a world filled with corruptible and unchecked institutions, there exists a third thing, malicious incompetence. It's a social cancer and it only appears once human organizations scale beyond personal accountability. Thank you for listening and hope to see you next time.

https://youtu.be/X0-SXS6zdEQ

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David Patterson: Computer Architecture and Data Storage | Lex Fridman Podcast #104

The following is a conversation with David Patterson, Turing Award winner and professor of computer science at Berkeley. He's known for pioneering contributions to risk processor architecture used by 99% of new chips today and for co-creating RAID storage. The impact that these two lines of research and development have had in our world is immeasurable. He's also one of the great educators of computer science in the world. His book with John Hennessy is how I first learned about and was humbled by the inner workings of machines at the lowest level. Quick summary of the ads. Two sponsors, the Jordan Harbinger Show and Cash App. Please consider supporting the podcast by going to jordanharbinger.com slash Lex and downloading Cash App and using code LexPodcast. Click on the links, buy the stuff. It's the best way to support this podcast and in general, the journey I'm on in my research and startup. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it, the five stars on Apple Podcast, support it on Patreon or connect with me on Twitter at Lex Friedman, spelled without the E, just F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This episode is supported by the Jordan Harbinger Show. Go to jordanharbinger.com slash Lex. It's how he knows I sent you. On that page, there's links to subscribe to it on Apple Podcast, Spotify and everywhere else. I've been binging on this podcast. It's amazing. Jordan is a great human being. He gets the best out of his guests, dives deep, calls them out when it's needed and makes the whole thing fun to listen to. He's interviewed Kobe Bryant, Mark Cuban, Neil deGrasse Tyson, Garry Kasparov and many more. I recently listened to his conversation with Frank Abagnale, author of Catch Me If You Can and one of the world's most famous con men. Perfect podcast length and topic for a recent long distance run that I did. Again, go to jordanharbinger.com slash Lex. To give him my love and to support this podcast, subscribe also on Apple Podcast, Spotify and everywhere else. This show is presented by Cash App, the greatest sponsor of this podcast ever and the number one finance app in the App Store. When you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin and invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend The Scent of Money as a great book on this history. Also, the audio book is amazing. Debits and credits on Ledger started around 30,000 years ago. The US dollar created over 200 years ago and the first decentralized cryptocurrency released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the App Store or Google Play and use the code LexPodcast, you get $10 and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with David Patterson. Let's start with the big historical question. How have computers changed in the past 50 years at both the fundamental architectural level and in general, in your eyes? Well, the biggest thing that happened was the invention of the microprocessor. So computers that used to fill up several rooms could fit inside your cell phone. And not only did they get smaller, they got a lot faster. So they're a million times faster than they were 50 years ago, and they're much cheaper and they're ubiquitous. There's 7.8 billion people on this planet. Probably half of them have cell phones right now, just remarkable. That's probably more microprocessors than there are people. Sure, I don't know what the ratio is, but I'm sure it's above one. Maybe it's 10 to one or some number like that. What is a microprocessor? So a way to say what a microprocessor is is to tell you what's inside a computer. So a computer forever has classically had five pieces. There's input and output, which kind of naturally, as you'd expect, is input is like speech or typing, and output is displays. There's a memory, and like the name sounds, it remembers things. So it's integrated circuits whose job is you put information in, then when you ask for it, it comes back out. That's memory. And the third part is the processor, where the term microprocessor comes from. And that has two pieces as well. And that is the control, which is kind of the brain of the processor. And what's called the arithmetic unit, it's kind of the brawn of the computer. So if you think of as a human body, the arithmetic unit, the thing that does the number crunching is the body and the control is the brain. So those five pieces, input, output, memory, arithmetic unit, and control have been in computers since the very dawn. And the last two are considered the processor. So a microprocessor simply means a processor that fits on a microchip. And that was invented about 40 years ago, was the first microprocessor. It's interesting that you refer to the arithmetic unit as the, like you connect it to the body and the controller's the brain. So I guess, I never thought of it that way. It's a nice way to think of it because most of the actions the microprocessor does in terms of literally sort of computation, but the microprocessor does computation. It processes information. And most of the thing it does is basic arithmetic operations. What are the operations, by the way? It's a lot like a calculator. So there are add instructions, subtract instructions, multiply and divide. And kind of the brilliance of the invention of the computer or the processor is that it performs very trivial operations, but it just performs billions of them per second. And what we're capable of doing is writing software that can take these very trivial instructions and have them create tasks that can do things better than human beings can do today. Just looking back through your career, did you anticipate the kind of how good we would be able to get at doing these small basic operations? How many surprises along the way where you just kind of sat back and said, wow, I didn't expect it to go this fast, this good? Well, the fundamental driving force is what's called Moore's Law, which was named after Gordon Moore, who's a Berkeley alumnus. And he made this observation very early in what are called semiconductors. And semiconductors are these ideas you can build these very simple switches and you can put them on these microchips. And he made this observation over 50 years ago. He looked at a few years and said, I think what's going to happen is the number of these little switches called transistors is going to double every year for the next decade. And he'd said this in 1965. And in 1975, he said, well, maybe it's gonna double every two years. And that, what other people since named that Moore's Law, guided the industry. And when Gordon Moore made that prediction, he wrote a paper back in, I think, in the 70s and said, not only did this gonna happen, he wrote, what would be the implications of that? And in this article from 1965, he shows ideas like computers being in cars and computers being in something that you would buy in the grocery store and stuff like that. So he kind of not only called this shot, he called the implications of it. So if you were in the computing field, and if you believed Moore's prediction, he kind of said what would be happening in the future. So it's not kind of, it's at one sense, this is what was predicted. And you could imagine, it was easy to believe that Moore's Law was gonna continue. And so this would be the implications. On the other side, there are these shocking events in your life. Like I remember driving in a Marine across the bay in San Francisco and seeing a bulletin board at a local civic center and it had a URL on it. And it was like, for the people at the time, these first URLs, and that's the, you know, WWW select stuff with the HTTP, people thought it looked like alien writing, right? They'd see these advertisements and commercials or bulletin boards that had this alien writing on it. So for the lay people, it's like, what the hell is going on here? And for those people in industry, it was, oh my God, this stuff is getting so popular, it's actually leaking out of our nerdy world into the real world. So that, I mean, there was events like that. I think another one was, I remember in the early days of the personal computer, when we started seeing advertisements in magazines for personal computers, like it's so popular that it's made the newspapers. So at one hand, you know, Gordon Moore predicted it and you kind of expected it to happen, but when it really hit and you saw it affecting society, it was shocking. So maybe taking a step back and looking both engineering and philosophical perspective, what do you see as the layers of abstraction in a computer? Do you see a computer as a set of layers of abstractions? Yeah, I think that's one of the things that computer science fundamentals is these things are really complicated and the way we cope with complicated software and complicated hardware is these layers of abstraction. And that simply means that we suspend disbelief and pretend that the only thing you know is that layer and you don't know anything about the layer below it. And that's the way we can make very complicated things. And probably it started with hardware, that's the way it was done, but it's been proven extremely useful. And I would think in a modern computer today, there might be 10 or 20 layers of abstraction and they're all trying to kind of enforce this contract is all you know is this interface, there's a set of commands that you are allowed to use and you stick to those commands and we will faithfully execute that. And it's like peeling the layers of an onion, you get down, there's a new set of layers and so forth. So for people who wanna study computer science, the exciting part about it is you can keep peeling those layers. You take your first course and you might learn to program in Python and then you can take a follow-on course and you can get it down to a lower level language like C and you can go and then you can, if you want to, you can start getting into the hardware layers and you keep getting down all the way to that transistor that I talked about that Gordon Moore predicted and you can understand all those layers all the way up to the highest level application software. So it's a very kind of magnetic field. If you're interested, you can go into any depth and keep going. In particular, what's happening right now or it's happened in software last 20 years and recently in hardware, there's getting to be open source versions of all of these things. So what open source means is what the engineer, the programmer designs, it's not secret, the belonging to a company, it's out there on the worldwide web so you can see it. So you can look at, for lots of pieces of software that you use, you can see exactly what the programmer does if you want to get involved. That used to stop at the hardware. Recently, there's been an efforts to make open source hardware in those interfaces open so you can see that. So instead of before you had to stop at the hardware, you can now start going layer by layer below that and see what's inside there. So it's a remarkable time that for the interested individual can really see in great depth what's really going on in the computers that power everything that we see around us. Are you thinking also when you say open source at the hardware level, is this going to the design, architecture, instruction set level or is it going to literally the manufacturer of the actual hardware, of the actual chips, whether that's ASICs specialized to a particular domain or the general? Yeah, so let's talk about that a little bit. So when you get down to the bottom layer of software, the way software talks to hardware is in a vocabulary. In what we call that vocabulary, we call that the words of that vocabulary are called instructions. And the technical term for the vocabulary is instruction set. So those instructions are like what we talked about earlier. There can be instructions like add, subtract, and multiply, divide. There's instructions to put data into memory, which is called a store instruction and to get data back, which is called a load instructions. And those simple instructions go back to the very dawn of computing. In 1950, the commercial computer had these instructions. So that's the instruction set that we're talking about. So up until I'd say 10 years ago, these instruction sets were all proprietary. So a very popular one is owned by Intel, the one that's in the cloud and in all the PCs in the world. Intel owns that instruction set. It's referred to as the x86. There've been a sequence of ones that the first number was called 8086. And since then, there's been a lot of numbers, but they all end in 86. So there's been that kind of family of instruction sets. And that's proprietary. And that's proprietary. The other one that's very popular is from ARM. That kind of powers all the cell phones in the world, all the iPads in the world, and a lot of things that are so-called internet of things devices. ARM and that one is also proprietary. ARM will license it to people for a fee, but they own that. So the new idea that got started at Berkeley kind of unintentionally 10 years ago is early in my career, we pioneered a way to do these vocabularies instruction sets that was very controversial at the time. At the time in the 1980s, conventional wisdom was these vocabularies instruction sets should have powerful instructions. So polysyllabic kind of words, you can think of that. And so that instead of just add, subtract, and multiply, they would have polynomial divide or sort a list. And the hope was of those powerful vocabularies that make it easier for software. So we thought that didn't make sense for microprocessors. There was people at Berkeley and Stanford and IBM who argued the opposite. And we called that was a reduced instruction set computer and the abbreviation was RISC and typical for computer people, we use the abbreviations that are pronouncing it. So RISC was the thing. So we said for microprocessors, which with Gordon's more is changing really fast, we think it's better to have a pretty simple set of instructions, reduced set of instructions, that that would be a better way to build microprocessors since they're gonna be changing so fast due to Moore's law. And then we'll just use standard software to generate more of those simple instructions. And one of the pieces of software that's in that software stack going between these layers of abstractions is called a compiler. And it's basically translates, it's a translator between levels. We said the translator will handle that. So the technical question was, well, since there are these reduced instructions, you have to execute more of them. Yeah, that's right. But maybe you execute them faster. Yeah, that's right. They're simpler so they could go faster, but you have to do more of them. So what's that trade off look like? And it ended up that we ended up executing maybe 50% more instructions, maybe a third more instructions, but they ran four times faster. So this controversial RISC ideas proved to be maybe factors of three or four better. I love that this idea was controversial and almost kind of like rebellious. So that's in the context of what was more conventional is the complex instructional set computing. So how would you pronounce that? CISC. CISC. Right, so RISC versus CISC. And believe it or not, this sounds very, who cares about this, right? It was violently debated at several conferences. It's like, what's the right way to go? And people thought RISC was de-evolution. We're gonna make software worse by making those instructions simpler. And there were fierce debates at several conferences in the 1980s. And then later in the 80s, it kind of settled to these benefits. It's not completely intuitive to me why RISC has, for the most part, won. Yeah, so why did that happen? Yeah, yeah, and maybe I can sort of say a bunch of dumb things that could lay the land for further commentary. So to me, this is kind of an interesting thing. If you look at C++ versus C, with modern compilers, you really could write faster code with C++. So relying on the compiler to reduce your complicated code into something simple and fast. So to me, comparing RISC, maybe this is a dumb question, but why is it that focusing the definition, the design of the instruction set on very few simple instructions in the long run provide faster execution versus coming up with, like you said, a ton of complicated instructions that over time, years, maybe decades, you come up with compilers that can reduce those into simple instructions for you? Yeah, so let's try and split that into two pieces. So if the compiler can do that for you, if the compiler can take a complicated program and produce simpler instructions, then the programmer doesn't care, right? Programmer, I don't care just how fast is the computer I'm using, how much does it cost? And so what happened kind of in the software industry is right around before the 1980s, critical pieces of software were still written not in languages like C or C++. They were written in what's called assembly language, where there's this kind of humans writing exactly at the instructions at the level that a computer can understand. So they were writing add, subtract, multiply instructions. It's very tedious. But the belief was to write this lowest level of software that people use, which are called operating systems, they had to be written in assembly language because these high level languages were just too inefficient. They were too slow or the programs would be too big. So that changed with a famous operating system called Unix, which is kind of the grandfather of all the operating systems today. So Unix demonstrated that you could write something as complicated as an operating system in a language like C. So once that was true, then that meant we could hide the instruction set from the programmer. And so that meant then it didn't really matter. The programmer didn't have to write lots of these simple instructions. That was up to the compiler. So that was part of our arguments for risk is if you were still writing an assembly language, there's maybe a better case for CISC instructions. But if the compiler can do that, it's gonna be, that's done once, the computer translates it once. And then every time you run the program, it runs at this potentially simpler instructions. And so that was the debate, right? And people would acknowledge that the simpler instructions could lead to a faster computer. You can think of monosyllabic instructions. You could say them, if you think of reading, you could probably read them faster or say them faster than long instructions. The same thing, that analogy works pretty well for hardware. And as long as you didn't have to read a lot more of those instructions, you could win. So that's the basic idea for risk. But it's interesting that in that discussion of UNIX and C, that there's only one step of levels of abstraction from the code that's really the closest to the machine to the code that's written by human. At least to me, again, perhaps a dumb intuition, but it feels like there might have been more layers, sort of different kinds of humans stacked on top of each other. So what's true and not true about what you said is several of the layers of software, so if you, two layers would be, suppose we just talk about two layers. That would be the operating system, like you get from Microsoft or from Apple, like iOS or the Windows operating system. And let's say applications that run on top of it, like Word or Excel. So both the operating system could be written in C and the application could be written in C. But you could construct those two layers and the applications absolutely do call upon the operating system. And the change was that both of them could be written in higher level languages. So it's one step of a translation, but you can still build many layers of abstraction of software on top of that. And that's how things are done today. So still today, many of the layers that you'll deal with, you may deal with debuggers, you may deal with linkers. There's libraries, many of those today will be written in C++, say, even though that language is pretty ancient. And even the Python interpreter is probably written in C or C++. So lots of layers there are probably written in these some old fashioned efficient languages that still take one step to produce these instructions, produce RISC instructions, but they're composed, each layer of software invokes one another through these interfaces, and you can get 10 layers of software that way. So in general, RISC was developed here at Berkeley? It was kind of the three places that were these radicals that advocated for this against the rest of the community were IBM, Berkeley, and Stanford. You're one of these radicals. And how radical did you feel? How confident did you feel? How doubtful were you that RISC might be the right approach? Because you can also intuit that it's kind of taking a step back into simplicity, not forward into simplicity. Yeah. No, it was easy to make, yeah. It was easy to make the argument against it. Well, this was my colleague, John Hennessy at Stanford. Now, we were both assistant professors. And for me, I just believed in the power of our ideas. I thought what we were saying made sense. Moore's law is gonna move fast. The other thing that I didn't mention is one of the surprises of these complex instruction sets. You could certainly write these complex instructions if the programmer is writing them themselves. It turned out to be kind of difficult for the compiler to generate those complex instructions. Kind of ironically, you'd have to find the right circumstances that just exactly fit this complex instruction. It was actually easier for the compiler to generate these simple instructions. So not only did these complex instructions make the hardware more difficult to build, often the compiler wouldn't even use them. And so it's harder to build. The compiler doesn't use them that much. The simple instructions go better with Moore's law. The number of transistors is doubling every two years. So we're gonna have, you wanna reduce the time to design the microprocessor. That may be more important than the number of instructions. So I think we believed that we were right, that this was the best idea. Then the question became in these debates, well, yeah, that's a good technical idea. But in the business world, this doesn't matter. There's other things that matter. It's like arguing that if there's a standard with the railroad tracks, and you've come up with a better with, but the whole world is covered in railroad tracks, so your ideas have no chance of success. Commercial success. It was technically right, but commercially, it'll be insignificant. Yeah, it's kind of sad that this world, the history of human civilization is full of good ideas that lost because somebody else came along first with a worse idea. And it's good that in the computing world, at least some of these have, well, you could argue, I mean, there's probably still CISC people that say, yeah, there still are. And what happened was, what was interesting, Intel, a bunch of the CISC companies with CISC instruction sets of vocabulary, they gave up, but not Intel. What Intel did, to its credit, because Intel's vocabulary was in the personal computer, and so that was a very valuable vocabulary because the way we distribute software is in those actual instructions. It's in the instructions of that instruction set. So you don't get that source code, what the programmers wrote. You get, after it's been translated into the lowest level, that's, if you were to get a floppy disk or download software, it's in the instructions of that instruction set. So the x86 instruction set was very valuable. So what Intel did cleverly and amazingly is they had their chips in hardware do a translation step. They would take these complex instructions and translate them into essentially in RISC instructions in hardware on the fly, at gigahertz clock speeds, and then any good idea that RISC people had, they could use and they could still be compatible with this really valuable PC software base, which also had very high volumes, 100 million personal computers per year. So the CISC architecture in the business world was actually one in this PC era. So just going back to the time of designing RISC, when you design an instruction set architecture, do you think like a programmer? Do you think like a microprocessor engineer? Do you think like a artist, a philosopher? Do you think in software and hardware? I mean, is it art, is it science? Yeah, I'd say, I think designing a good instruction set is an art, and I think you're trying to balance the simplicity and speed of execution with how well easy it will be for compilers to use it. You're trying to create an instruction set that everything in there can be used by compilers. There's not things that are missing that'll make it difficult for the program to run, that run efficiently, but you want it to be easy to build as well. So it's that kind of, so you're thinking, I'd say you're thinking hardware, trying to find a hardware, software compromise that'll work well. And it's a matter of taste, right? It's kind of fun to build instruction sets. It's not that hard to build an instruction set, but to build one that catches on and people use, you have to be fortunate to be the right place in the right time, or have a design that people really like. Are you using metrics? So is it quantifiable? Because you kind of have to anticipate the kind of programs that people write ahead of time. So is that, can you use numbers, can you use metrics, can you quantify something ahead of time, or is this, again, that's the art part where you're kind of anticipating? No, it's a big change, kind of what happened, I think from Hennessy's and my perspective in the 1980s, what happened was going from kind of really, you know, taste and hunches to quantifiable. And in fact, he and I wrote a textbook at the end of the 1980s called Computer Architecture, A Quantitative Approach. I heard of that. And it's the thing, it had a pretty big impact in the field because we went from textbooks that kind of listed, so here's what this computer does, and here's the pros and cons, and here's what this computer does and pros and cons, to something where there were formulas, and equations where you could measure things. So specifically for instruction sets, what we do and some other fields do is we agree upon a set of programs, which we call benchmarks, and a suite of programs, and then you develop both the hardware and the compiler, and you get numbers on how well your computer does given its instruction set, and how well you implemented it in your microprocessor, and how good your compilers are. And in computer architecture, using professors' terms, we grade on a curve rather than grade on an absolute scale. So when you say, these programs run this fast, well, that's kind of interesting, but how do you know it's better? Well, you compare it to other computers at the same time. So the best way we know how to make, turn it into a kind of more science, and experimental, and quantitative, is to compare yourself to other computers of the same era that have the same access, the same kind of technology, on commonly agreed benchmark programs. So maybe to toss up two possible directions we can go, one is what are the different trade-offs in designing architectures? We've been already talking about CISC and RISC, but maybe a little bit more detail in terms of specific features that you were thinking about. And the other side is, what are the metrics that you're thinking about when looking at these trade-offs? Yeah, let's talk about the metrics. So during these debates, we actually had kind of a hard time explaining, convincing people the ideas, and partly we didn't have a formula to explain it. And a few years into it, we hit upon a formula that helped explain what was going on. And I think if we can do this, see how it works orally to do this. So, let's see if I can do a formula orally. So fundamentally, the way you measure performance is how long does it take a program to run? Program, if you have 10 programs, and typically these benchmarks were sweet because you'd want to have 10 programs so they could represent lots of different applications. So for these 10 programs, how long did it take to run? Well, now, when you're trying to explain why it took so long, you could factor how long it takes a program to run into three factors. So, one of the first one is how many instructions did it take to execute? So that's what we've been talking about, the instructions of a chemi. How many did it take? All right. The next question is how long did each instruction take to run on average? So you'd multiply the number of instructions times how long it took to run, and that gives you a time. Okay, so that's, but now let's look at this metric of how long did it take the instruction to run? Well, it turns out the way we could build computers today is they all have a clock. And you've seen this when you, if you buy a microprocessor, it'll say 3.1 gigahertz or 2.5 gigahertz and more gigahertz is good. Well, what that is, is the speed of the clock. So 2.5 gigahertz turns out to be four billionths of instruction or four nanoseconds. So that's the clock cycle time. But there's another factor, which is what's the average number of clock cycles it takes per instruction? So it's number of instructions, average number of clock cycles, and the clock cycle time. So in these risk-sys debates, we would, they would concentrate on, but risk needs to take more instructions. And we'd argue what, maybe the clock cycle is faster, but what the real big difference was, was the number of clock cycles per instruction. Per instruction, that's fascinating. What about the mess of, the beautiful mess of parallelism in the whole picture? Parallelism, which has to do with say, how many instructions could execute in parallel and things like that. You could think of that as affecting the clock cycles per instruction, because it's the average clock cycles per instruction. So when you're running a program, if it took a hundred billion instructions and on average, it took two clock cycles per instruction, and they were four nanoseconds, you could multiply that out and see how long it took to run. And there's all kinds of tricks to try and reduce the number of clock cycles per instruction. But it turned out that the way they would do these complex instructions is they would actually build what we would call an interpreter in a simpler, a very simple hardware interpreter. But it turned out that for the CISC instructions, if you had to use one of those interpreters, it would be like 10 clock cycles per instruction, where the risk instructions could be two. So there'd be this factor of five advantage in clock cycles per instruction. We have to execute say 25 or 50% more instructions. So that's where the risk comes in. And then you could make an argument whether the clock cycle times are the same or not. But pointing out that we could divide the benchmark results time per program into three factors, and the biggest difference in risk and CISC was the clock cycles per, you execute a few more instructions, but the clock cycles per instruction is much less. And that was what this debate, once we made that argument, then people say, oh, okay, I get it. And so we went from, it was outrageously controversial in 1982 that maybe probably by 1984 or so, people said, oh yeah, technically they've got a good argument. What are the instructions in the risk instruction set? Just to get an intuition. Okay, 1995, I was asked to sign to predict the future of what microprocessor like a future. So I, and I'd seen these predictions and usually people predict something outrageously. They predict something outrageous just to be entertaining, right? And so my prediction for 2020 was, things are gonna be pretty much, they're gonna look very familiar to what they are. And they are, if you were to read the article, the things I said are pretty much true. The instructions that have been around forever are kind of the same. And that's the outrageous prediction actually. Yeah. Given how fast computers have been growing. Well, and Moore's law was gonna go on, we thought for 25 more years, who knows? But kind of the surprising thing, in fact, Hennessy and I won the ACM AM Turing Award for both the risk instruction set contributions and for that textbook I mentioned. But we are surprised that here we are 35, 40 years later after we did our work and the conventional wisdom of the best way to do instruction sets is still those risk instruction sets that look very similar to what we looked like we did in the 1980s. So those, surprisingly, there hasn't been some radical new idea, even though we have a million times as many transistors as we had back then. But what are the basic instructions and how did they change over the years? So are we talking about addition, subtraction, these are the- Okay, so the things that are in a calculator are in a computer. So any of the buttons that are in the calculator in the computer. So the- Nice way to put it. So if there's a memory function key and like I said, those are turns into putting something in memories called a store, bring something back, it's gonna load. Just a quick tangent, when you say memory, what does memory mean? Well, I told you there were five pieces of a computer. And if you remember in a calculator, there's a memory key. So you wanna have intermediate calculation and bring it back later. So you'd hit the memory plus key, M plus maybe, and it would put that into memory. And then you'd hit an RM like recurrent instruction and it'd bring it back into the display. So you don't have to type it. You don't have to write it down and bring it back again. So that's exactly what memory is. You can put things into it as temporary storage and bring it back when you need it later. So that's memory and loads and stores. But the big thing, the difference between a computer and a calculator is that the computer can make decisions. And amazingly decisions are as simple as, is this value less than zero? Or is this value bigger than that value? So there's, and those instructions, which are called conditional branch instructions is what give computers all its power. If you were in the early days of computing before what's called the general purpose microprocessor, people would write these instructions kind of in hardware, but it couldn't make decisions. It would just, it would do the same thing over and over again. With the power of having branch instructions, it can look at things and make decisions automatically. And it can make these decisions, billions of times per second. And amazingly enough, we can get, thanks to advanced machine learning, we can create programs that can do something smarter than human beings can do. But if you go down that very basic level, which the instructions are the keys on the calculator, plus the ability to make decisions, these conditional branch instructions. And all decisions fundamentally can be reduced down to these branch instructions. Yeah, so in fact, and so, going way back in the stack, back to, we did four risk projects at Berkeley in the 1980s. We did a couple at Stanford in the 1980s. In 2010, we decided we wanted to do a new instruction set, learning from the mistakes of those risk architectures in the 1980s. And that was done here at Berkeley almost exactly 10 years ago. And the people who did it, I participated, but other, Krzysztof Sanovic and others drove it. They called it Risk 5 to honor those risk, the four risk projects of the 1980s. So what does Risk 5 involve? So Risk 5 is another instruction set of vocabulary. It's learned from the mistakes of the past, but it still has, if you look at the, there's a core set of instructions that's very similar to the simplest architectures from the 1980s. And the big difference about Risk 5 is it's open. So I talked earlier about proprietary versus open, kind of soft software. So this is an instruction set, so it's a vocabulary. It's not hardware, but by having an open instruction set, we can have open source implementations, open source processors that people can use. Where do you see that going? It's a really exciting possibilities, but you're just like in the scientific American, if you were to predict 10, 20, 30 years from now, that kind of ability to utilize open source instruction set architectures like Risk 5, what kind of possibilities might that unlock? Yeah, and so just to make it clear, because this is confusing, the specification of Risk 5 is something that's like in a textbook, there's books about it. So that's defining an interface. There's also the way you build hardware is you write it in languages. They're kind of like C, but they're specialized for hardware that gets translated into hardware. And so these implementations of this specification are what are the open source. So they're written in something that's called Verilog or VHDL, but it's put up on the web, just like you can see the C++ code for Linux on the web. So that's the open instruction set enables open source implementations of Risk 5. So you can literally build a processor using this instruction set. People are, people are. So what happened to us, the story was, this was developed here for our use to do our research. And we made it, we licensed under the Berkeley Software Distribution License, like a lot of things get licensed here. So other academics use it, they wouldn't be afraid to use it. And then about 2014, we started getting complaints that we were using it in our research and in our courses. And we got complaints from people in industries, why did you change your instruction set between the fall and the spring semester? And well, we get complaints from industrial time. Why the hell do you care what we do with our instruction set? And then when we talked to them, we found out there was this thirst for this idea of an open instruction set architecture. And they had been looking for one, they stumbled upon ours at Berkeley, thought it was, boy, this looks great. We should use this one. And so once we realized there is this need for an open instruction set architecture, we thought that's a great idea. And then we started supporting it and tried to make it happen. So this was, we accidentally stumbled into this, into this need and our timing was good. And so it's really taking off. There's, universities are good at starting things, but they're not good at sustaining things. So like Linux has a Linux foundation, there's a RISC-V foundation that we started. There's an annual conferences. And the first one was done, I think, January of 2015. And the one that was just last December, and it had 50 people at it. And the one last December had 1,700 people were at it and the company's excited all over the world. So if predicting into the future, if we were doing 25 years, I would predict that RISC-V will be possibly the most popular instruction set architecture out there, because it's a pretty good instruction set architecture and it's open and free. And there's no reason lots of people shouldn't use it. And there's benefits just like Linux is so popular today compared to 20 years ago. And the fact that you can get access to it for free, you can modify it, you can improve it for all those same arguments. And so people collaborate to make it a better system for everybody to use and that works in software. And I expect the same thing will happen in hardware. So if you look at ARM, Intel, MIPS, if you look at just the lay of the land, and what do you think, just for me, because I'm not familiar how difficult this kind of transition would, how much challenges this kind of transition would entail, do you see, let me ask my dumb question in another way. No, that's, I know where you're headed. Well, there's a bunch, I think the thing you point out, there's these very popular proprietary instruction sets, the x86 and ARM. And so how do we move to RISC-V potentially in the span of five, 10, 20 years, a kind of unification, given that the devices, the kind of way we use devices, IoT, mobile devices, and the cloud just keeps changing? Well, part of it, a big piece of it is the software stack. And what right now looking forward, there seem to be three important markets. There's the cloud, and the cloud is simply companies like Alibaba and Amazon and Google, Microsoft, having these giant data centers with tens of thousands of servers and maybe a hundred of these data centers all over the world. And that's what the cloud is. So the computer that dominates the cloud is the x86 instruction set. So the instruction or the instruction sets used in the cloud are the x86, almost 100% of that today is x86. The other big thing are cell phones and laptops. Those are the big things today. I mean, the PC is also dominated by the x86 instruction set, but those sales are dwindling. You know, there's maybe 200 million PCs a year, and there's, is there one and a half billion phones a year? There's numbers like that. So for the phones, that's dominated by ARM. And now, and a reason that, I talked about the software stacks, and the third category is internet of things, which is basically embedded devices, things in your cars and your microwaves, everywhere. So what's different about those three categories is for the cloud, the software that runs in the cloud is determined by these companies, Alibaba, Amazon, Google, Microsoft. So they control that software stack. For the cell phones, there's both, for Android and Apple, the software they supply, but both of them have marketplaces where anybody in the world can build software. And that software is translated or, you know, compiled down and shipped in the vocabulary of ARM. So that's what's referred to as binary compatible because the actual, it's the instructions are turned into numbers, binary numbers, and shipped around the world. So- And so just a quick interruption. So ARM, what is ARM? Is ARM is an instruction set, like a risk-based? Yeah, it's a risk-based instruction set. It's a proprietary one. ARM stands for Advanced Risk Machine. ARM is the name where the company is. So it's a proprietary risk architecture. So, and it's been around for a while, and it's, you know, surely the most popular instruction set in the world right now. They, every year, billions of chips are using the ARM design in this post-PC era. Was it one of the early risk adopters of the risk idea? Yeah, the first ARM goes back, I don't know, 86 or so. So Berkeley instead did their work in the early 80s. Their ARM guys needed an instruction set, and they read our papers, and it heavily influenced them. So getting back to my story, what about Internet of Things? Well, software's not shipped in Internet of Things. It's the embedded device. People control that software stack. So the opportunities for RISC-V, everybody thinks, is in the Internet of Things embedded things, because there's no dominant player like there is in the cloud or the smartphones. And, you know, it doesn't have a lot of licenses associated with, and you can enhance the instruction set if you want, and people have looked at instruction sets and think it's a very good instruction set. So it appears to be very popular there. It's possible that in the cloud, people, those companies control their software stacks. So it's possible that they would decide to use RISC-V, if we're talking about 10 and 20 years in the future. The one that would be harder would be the cell phones, since people ship software in the ARM instruction set. That, you'd think, would be the more difficult one. But if RISC-V really catches on, and, you know, in a period of a decade, you can imagine that's changing over, too. Do you have a sense why RISC-V or ARM has dominated? You mentioned these three categories. Why did ARM dominate? Why does it dominate the mobile device space? And maybe my naive intuition is that there's some aspects of power efficiency that are important that somehow come along with RISC. Well, part of it is, for these old CISC instruction sets, like in the x86, it was more expensive to these, for, you know, they're older, so they have disadvantages in them because they were designed 40 years ago. But also, they have to translate in hardware from CISC instructions to RISC instructions on the fly. And that costs both silicon area, the chips are bigger to be able to do that, and it uses more power. So ARM has, which has, you know, followed this RISC philosophy, is seen to be much more energy efficient. And in today's computer world, both in the cloud and the cell phone and, you know, things, it isn't, the limiting resource isn't the number of transistors you can fit in the chip, it's what, how much power can you dissipate for your application. So by having a reduced instruction set, that's possible to have a simpler hardware, which is more energy efficient. And energy efficiency is incredibly important in the cloud. When you have tens of thousands of computers in a data center, you wanna have the most energy efficient ones there as well. And of course, for embedded things running off of batteries, you want those to be more energy efficient, and the cell phones too. So I think it's believed that there's a energy disadvantage of using these more complex instruction set architectures. So the other aspect of this is, if we look at Apple, Qualcomm, Samsung, Huawei, all use the ARM architecture, and yet the performance of the systems varies. I mean, I don't know whose opinion you take on, but, you know, Apple, for some reason, seems to perform better in terms of these implementations, these architectures. So where's the magic enter the picture? How's that happen? So what ARM pioneered was a new business model. As they said, well, here's our proprietary instruction set, and we'll give you two ways to do it. We'll give you one of these implementations written in things like C called Verilog, and you can just use ours. You have to pay money for that. Not only will give you their, you know, we'll license you to do that, or you could design your own. And so we're talking about numbers like tens of millions of dollars to have the right to design your own, since the instruction set belongs to them. So Apple got one of those, the right to build their own. Most of the other people who build like Android phones just get one of the designs from ARM to do it themselves. So Apple developed a really good microprocessor design team. They, you know, acquired a very good team that was building other microprocessors and brought them into the company to build their designs. So the instruction sets are the same, the specifications are the same, but their hardware design is much more efficient than I think everybody else's. And that's given Apple an advantage in the marketplace in that the iPhones tend to be faster than most everybody else's phones that are there. It'd be nice to be able to jump around and kind of explore different little sides of this, but let me ask one sort of romanticized question. What to you is the most beautiful aspect or idea of RISC instruction set or instruction sets or this work that you've done? You know, I was always attracted to the idea of, you know, small is beautiful, is that the temptation in engineering, it's kind of easy to make things more complicated. It's harder to come up with a, it's more difficult, surprisingly, to come up with a simple, elegant solution. And I think that there's a bunch of small features of RISC in general that, you know, where you can see this examples of keeping it simpler makes it more elegant. Specifically in RISC-V, which, you know, I was kind of the mentor in the program, but it was really driven by Krzysztof Sanovic and two grad students, Andrew Waterman and Yansip Li, is they hit upon this idea of having a subset of instructions, a nice simple subset instructions, like 40-ish instructions that all software, the software stack for RISC-V can run just on those 40 instructions. And then they provide optional features that could accelerate the performance instructions that if you needed them could be very helpful, but you don't need to have them. And that's a new, really a new idea. So RISC-V has, right now, maybe five optional subsets that you can pull in, but the software runs without them. If you just want to build the, just the core 40 instructions, that's fine. You can do that. So this is fantastic educationally is that you can explain computers. You only have to explain 40 instructions and not thousands of them. Also, if you invent some wild and crazy new technology, like, you know, biological computing, you'd like a nice, simple instruction set. And you can, RISC-V, if you implement those core instructions, you can run, you know, really interesting programs on top of that. So this idea of a core set of instructions that the software stack runs on, and then optional features that if you turn them on, the compilers will use, but you don't have to, I think is a powerful idea. What's happened in the past for the proprietary instruction sets is when they add new instructions, it becomes required piece. And so that all microprocessors in the future have to use those instructions. So it's kind of like, for a lot of people as they get older, they gain weight, right? The weight and age are correlated. And so you can see these instruction sets get getting bigger and bigger as they get older. So RISC-V, you know, lets you be as slim as you're as a teenager, and you only have to add these extra features if you're really gonna use them, rather than you have no choice, you have to keep growing with the instruction set. I don't know if the analogy holds up, but that's a beautiful notion. That there's, it's almost like a nudge towards, here's the simple core, that's the essential. Yeah, I think the surprising thing is still, if we brought back, you know, the pioneers from the 1950s and showed them the instruction set architectures, they'd understand it. They'd say, wow, that doesn't look that different. Well, you know, I'm surprised. And it's, there's, it may be something, you know, to talk about philosophical things. I mean, there may be something powerful about those, you know, 40 or 50 instructions that all you need is these commands, like these instructions that we talked about. And that is sufficient to build, to bring about, you know, artificial intelligence. And so it's a remarkable, surprising to me that as complicated as it is to build these things, you know, a microprocessors where the line widths are narrower than the wavelength of light, you know, is this amazing technologies at some fundamental level, the commands that software executes are really pretty straightforward and haven't changed that much. And in decades, which what a surprising outcome. So underlying all computation, all Turing machines, all artificial intelligence systems, perhaps might be a very simple instruction set, like a RISC-V or it's, yeah. I mean, that's kind of what I said. I was interested to see, I had another more senior faculty colleague and he had written something in Scientific American and, you know, his 25 years in the future and his turned out about when I was a young professor and he said, yep, I checked it. And so I was interested to see how that was gonna turn out for me. And it's pretty, held up pretty well. But yeah, so there's probably, there's some, you know, there must be something fundamental about those instructions that were capable of creating, you know, intelligence from pretty primitive operations and just doing them really fast. You kind of mentioned a different, maybe radical computational medium like biological and there's other ideas. So there's a lot of spaces in ASIC, so it's domain specific and then there could be quantum computers and so we can think of all of those different mediums and types of computation. What's the connection between swapping out different hardware systems in the instruction set? Do you see those as disjoint or are they fundamentally coupled? Yeah, so what's, so kind of if we go back to the history, you know, when Moore's Law is in full effect and you're getting twice as many transistors every couple of years, you know, kind of the challenge for computer designers is how can we take advantage of that? How can we turn those transistors into better computers, faster typically? And so there was an era, I guess, in the 80s and 90s where computers were doubling performance every 18 months and if you weren't around then, what would happen is you had your computer and your friend's computer, which was like a year, year and a half newer and it was much faster than your computer and he or she could get their work done much faster than your computer because you were. So people took their computers, perfectly good computers, and threw them away to buy a newer computer because the computer one or two years later was so much faster. So that's what the world was like in the 80s and 90s. Well, with the slowing down of Moore's Law, that's no longer true, right? Now with, you know, not desk-side computers, but the laptops, I only get a new laptop when it breaks, right, oh, damn, the disc broke or this display broke, I gotta buy a new computer, but before you would throw them away because they were just so sluggish compared to the latest computers. So that's, you know, that's a huge change of what's gone on. So, but since this lasted for decades, kind of programmers and maybe all of society is used to computers getting faster regularly. We now believe, those of us who are in computer design, it's called computer architecture, that the path forward is instead is to add accelerators that only work well for certain applications. So since Moore's Law is slowing down, we don't think general purpose computers are gonna get a lot faster. So the Intel processors of the world are not gonna, haven't been getting a lot faster. They've been barely improving, like a few percent a year. It used to be doubling every 18 months and now it's doubling every 20 years. So it's just shocking. So to be able to deliver on what Moore's Law used to do, we think what's gonna happen, what is happening right now is people adding accelerators to their microprocessors that only work well for some domains. And by sheer coincidence, at the same time that this is happening, has been this revolution in artificial intelligence called machine learning. So with, as I'm sure your other guests have said, AI had these two competing schools of thought, is that we could figure out artificial intelligence by just writing the rules top down, or that was wrong. You had to look at data and infer what the rules are of the machine learning, and what's happened in the last decade or eight years is machine learning has won. And it turns out that machine learning, the hardware you build for machine learning is pretty much multiply. The matrix multiply is a key feature for the way machine learning is done. So that's a godsend for computer designers. We know how to make matrix multiply run really fast. So general purpose microprocessors are slowing down. We're adding accelerators for machine learning that fundamentally are doing matrix multiplies much more efficiently than general purpose computers have done. So we have to come up with a new way to accelerate things. The danger of only accelerating one application is how important is that application. Turns out machine learning gets used for all kinds of things. So serendipitously, we found something to accelerate that's widely applicable. And we don't even, we're in the middle of this revolution of machine learning. We're not sure what the limits of machine learning are. So this has been a kind of a godsend. If you're gonna be able to deliver on improved performance, as long as people are moving their programs to be embracing more machine learning, we know how to give them more performance even as Moore's Law is slowing down. And counterintuitively, the machine learning mechanism, you can say is domain specific, but because it's leveraging data, it's actually could be very broad in terms of the domains it could be applied in. Yeah, that's exactly right. Sort of, it's almost, sort of people sometimes talk about the idea of software 2.0. We're almost taking another step up in the abstraction layer in designing machine learning systems, because now you're programming in the space of data, in the space of hyperparameters. It's changing fundamentally the nature of programming. And so the specialized devices that accelerate the performance, especially neural network based machine learning systems, might become the new general. Yeah, so the thing that's interesting to point out, these are not tied together. The enthusiasm about machine learning, about creating programs driven from data that we should figure out the answers from data rather than kind of top down, which classically the way most programming is done and the way artificial intelligence used to be done, that's a movement that's going on at the same time. Coincidentally, and the first word in machine learning is machines, right? So that's going to increase the demand for computing, because instead of programmers being smart, writing those things down, we're gonna instead use computers to examine a lot of data to kind of create the programs. That's the idea. And remarkably, this gets used for all kinds of things very successfully. The image recognition, the language translation, the game playing, and it gets into pieces of the software stack like databases and stuff like that. We're not quite sure how general purpose is, but that's going on independent of this hardware stuff. What's happening on the hardware side is Moore's law is slowing down right when we need a lot more cycles. It's failing us right when we need it, because there's gonna be a greater increase in computing. And then this idea that we're gonna do so-called domain specific, here's a domain that your greatest fear is you'll make this one thing work, and that'll help 5% of the people in the world. Well, this looks like it's a very general purpose thing. So the timing is fortuitous that if we can, perhaps if we can keep building hardware that will accelerate machine learning, the neural networks, the timing will be right, that neural network revolution will transform software, the so-called software 2.0. And the software of the future will be very different from the software of the past. And just as our microprocessors, even though we're still gonna have that same basic RISC instructions to run a big pieces of the software stack like user interfaces and stuff like that, we can accelerate the kind of the small piece that's computationally intensive. It's not lots of lines of code, but it takes a lot of cycles to run that code, that that's gonna be the accelerator piece. So that's what makes this, from a computer designers perspective, a really interesting decade. What Hennessy and I talked about in the title of our Turing-Warren speech is a new golden age. We see this as a very exciting decade, much like when we were assistant professors and the RISC stuff was going on, that was a very exciting time, was where we were changing what was going on. And we see this happening again. Tremendous opportunities of people because we're fundamentally changing how software is built and how we're running it. So which layer of the abstraction do you think most of the acceleration might be happening? If you look in the next 10 years, sort of Google is working on a lot of exciting stuff with the TPU, sort of there's a closer to the hardware, there could be optimizations around the, a route closer to the instruction set. There could be optimization at the compiler level. It could be even at the higher level software stack. Yeah, it's gotta be, if you think about the old RISC-Sys debate, it was both, it was software hardware. It was the compilers improving as well as the architecture improving. And that's likely to be the way things are now. With machine learning, they're using domain-specific languages, the languages like TensorFlow and PyTorch are very popular with the machine learning people that those are the raising the level of abstraction. It's easier for people to write machine learning in these domain-specific languages like PyTorch and TensorFlow. So where the most optimization might be happening? And so there'll be both the compiler piece and the hardware piece underneath it. So as you kind of, the fatal flaw for hardware people is to create really great hardware, but not have brought along the compilers. And what we're seeing right now in the marketplace, because of this enthusiasm around hardware for machine learning is getting, probably billions of dollars invested in startup companies. We're seeing startup companies go belly up because they focus on the hardware, but didn't bring the software stack along. We talked about benchmarks earlier. So I participated in machine learning, didn't really have a set of benchmarks. I think just two years ago, they didn't have a set of benchmarks. And we've created something called MLPerf, which is machine learning benchmark suite. And pretty much the companies who didn't invest in the software stack couldn't run MLPerf very well. And the ones who did invest in the software stack did. And we're seeing, like kind of in computer architecture, this is what happens. You have these arguments about risk versus sys. People spend billions of dollars in the marketplace to see who wins. And it's not a perfect comparison, but it kind of sorts things out. And we're seeing companies go out of business and then companies like, there's a company in Israel called Habana, they came up with machine learning accelerators. They had good MLPerf scores. Intel had acquired a company earlier called Nirvana a couple of years ago. They didn't reveal their MLPerf scores, which was suspicious. But a month ago, Intel announced that they're canceling the Nirvana product line and they bought Habana for $2 billion. And Intel's gonna be shipping Habana chips, which have hardware and software and run the MLPerf programs pretty well. And that's gonna be their product line in the future. Brilliant, so maybe just to linger briefly on MLPerf. I love metrics, I love standards that everyone can gather around. What are some interesting aspects of that portfolio of metrics? Well, one of the interesting metrics is what we thought. It was, I was involved in the start, that Peter Mattson is leading the effort from Google. Google got it off the ground, but we had to reach out to competitors and say, there's no benchmarks here. We think this is bad for the field. It'll be much better if we look at examples like in the risk days, there was an effort to create a, for the people in the risk community got together, competitors got together, we're building risk microprocessors to agree on a set of benchmarks that were called spec. And that was good for the industry. It's rather before the different risk architectures were arguing, well, you can believe my performance, others, but those other guys are liars. And that didn't do any good. So we agreed on a set of benchmarks, and then we could figure out who was faster between the various risk architectures, but it was a little bit faster, but that grew the market rather than, people were afraid to buy anything. So we argued the same thing would happen with MLPerf. Companies like Nvidia were maybe worried that it was some kind of trap, but eventually we all got together to create a set of benchmarks and do the right thing. And we agree on the results. And so we can see whether TPUs or GPUs or CPUs are really faster and how much the faster. And I think from an engineer's perspective, as long as the results are fair, you can live with it. Okay, you kind of tip your hat to your colleagues at another institution, boy, they did a better job than us. What you hate is if it's false. They're making claims and it's just marketing bullshit, and that's affecting sales. So from an engineer's perspective, as long as it's a fair comparison and we don't come in first place, that's too bad, but it's fair. So we wanted to create that environment for MLPerf. And so now there's 10 companies, I mean, 10 universities and 50 companies involved. So pretty much MLPerf is the way you measure machine learning performance. And it didn't exist even two years ago. One of the cool things that I enjoy about the internet, it has a few downsides, but one of the nice things is people can see through BS a little better with the presence of these kinds of metrics. So it's really nice, companies like Google and Facebook and Twitter, now it's the cool thing to do is to put your engineers forward and to actually show off how well you do on these metrics. There's not sort of, there's less of a desire to do marketing, less so. Am I sort of naive? No, I think, I was trying to understand that what's changed from the 80s in this era. I think because of things like social networking, Twitter and stuff like that, if you put up bullshit stuff, right, that's just purposely misleading, you can get a violent reaction in social media pointing out the flaws in your arguments, right? And so from a marketing perspective, you have to be careful today that you didn't have to be careful that there'll be people who put out the flaw. You can get the word out about the flaws and what you're saying much more easily today than in the past. It used to be easier to get away with it. And the other thing that's been happening in terms of showing off engineers is just, in the software side, people have largely embraced open source software. It was 20 years ago, it was a dirty word at Microsoft. And today, Microsoft is one of the big proponents of open source software. The kind of that's the standard way most software gets built, which really shows off your engineers because you can see, if you look at the source code, you can see who are making the commits, who's making the improvements, who are the engineers at all these companies who are really great programmers and engineers and making really solid contributions, which enhances their reputations and the reputation of the companies. But that's, of course, not everywhere. Like in the space that I work more in is autonomous vehicles and there's still, the machinery of hype and marketing is still very strong there and there's less willingness to be open in this kind of open source way and sort of benchmark. So MLPerf represents the machine learning world is much better at being open source about holding itself to standards of different, the amount of incredible benchmarks in terms of the different computer vision, natural lingo processing tasks is incredible. Historically, it wasn't always that way. I had a graduate student working with me, David Martin. So in computer, in some fields, benchmarking has been around forever. So computer architecture, databases, maybe operating systems, benchmarks are the way you measure progress. But he was working with me and then started working with Chetender Malik and he's, Chetender Malik in computer vision space, I guess you've interviewed Chetender. And David Martin told me, they don't have benchmarks. Everybody has their own vision algorithm and the way, here's my image, look at how well I do and everybody had their own image. So David Martin, back when he did his dissertation, figured out a way to do benchmarks. He had a bunch of graduate students identify images and then ran benchmarks to see which algorithms run well. And that was, as far as I know, kind of the first time people did benchmarks in computer vision and which was predated all, the things that eventually led to ImageNet and stuff like that. But then the vision community got religion and then once we got as far as ImageNet, then that let the guys in Toronto be able to win the ImageNet competition and then that changed the whole world. It's a scary step actually because when you enter the world of benchmarks, you actually have to be good to participate as opposed to, yeah, you can just, you just believe you're the best in the world. Yeah. And I think the people, I think they weren't purposely misleading. I think if you don't have benchmarks, I mean, how do you know? You could have, your intuition, it's kind of like the way we did used to do computer architecture. Your intuition is that this is the right instruction set to do this job. I believe in my experience, my hunch is that's true. We had to get to make things more quantitative to make progress. And so I just don't know how, in fields that don't have benchmarks, I don't understand how they figure out how they're making progress. So we're kind of in the vacuum tube days of quantum computing. What are your thoughts in this wholly different kind of space of architectures? I actually, quantum computing idea's been around for a while and I actually thought, well, I sure hope I retire before I have to start teaching this. I'd say because I talk about, give these talks about the slowing of Moore's law and we need to change by doing domain specific accelerators. Common questions say, what about quantum computing? The reason that comes up, it's in the news all the time. So I think the key, the third thing to keep in mind is quantum computing is not right around the corner. There've been two national reports, one by the National Academy of Engineering, another by the Computing Consortium, where they did a frank assessment of quantum computing. And both of those reports said, as far as we can tell, before you get error corrected quantum computing, it's a decade away. So I think of it like nuclear fusion, right? There've been people who've been excited about nuclear fusion a long time. If we ever get nuclear fusion, it's gonna be fantastic for the world. I'm glad people are working on it, but it's not right around the corner. Those two reports to me say probably it'll be 2030 before quantum computing is something that could happen. And when it does happen, this is gonna be big science stuff. This is micro Kelvin, almost absolute zero things that if they vibrate, if a truck goes by, it won't work. So this'll be in data center stuff. We're not gonna have a quantum cell phone. And it's probably a 2030 kind of thing. So I'm happy that people are working on it, but just it's hard with all the news about it, not to think that it's right around the corner. And that's why we need to do something as Moore's law is slowing down to provide the computing, keep computing getting better for this next decade. And we shouldn't be betting on quantum computing or expecting quantum computing to deliver in the next few years. It's probably further off. I'd be happy to be wrong. It'd be great if quantum computing is gonna commercially viable, but it will be a set of applications. It's not a general purpose computation. So it's gonna do some amazing things, but there'll be a lot of things that probably, you know, the old fashioned computers are gonna keep doing better for quite a while. And there'll be a teenager 50 years from now watching this video saying, look how silly David Patterson was saying. No, I just said, I said 2030. I didn't say never. We're not gonna have quantum cell phones. So he's gonna be watching it in a quantum cell. I mean, I think this is such a, you know, given that we've had Moore's law, I just, I feel comfortable trying to do projects that are thinking about the next decade. I admire people who are trying to do things that are 30 years out, but it's such a fast moving field. I just don't know how to, I'm not good enough to figure out what's the problem's gonna be in 30 years. You know, 10 years is hard enough for me. So maybe if it's possible to untangle your intuition a little bit, I spoke with Jim Keller. I don't know if you're familiar with Jim. And he is trying to sort of be a little bit rebellious and to try to think that- Yes, he quotes me as being wrong. Yeah, so this is- What are you, wait, wait, wait, for the record. Jim talks about that he has an intuition that Moore's law is not in fact dead yet and that it may continue for some time to come. What are your thoughts about Jim's ideas in this space? Yeah, this is just marketing. So what Gordon Moore said is a quantitative prediction. We can check the facts, right? Which is doubling the number of transistors every two years. So we can look back at Intel for the last five years and ask him, let's look at DRAM chips six years ago. So that would be three two-year periods. So then our DRAM chips have eight times as many transistors as they did six years ago. We can look up Intel microprocessors six years ago. If Moore's law is continuing, it should have eight times as many transistors as six years ago. The answer in both those cases is no. The problem has been because Moore's law was kind of genuinely embraced by the semiconductor industry is they would make investments in similar equipment to make Moore's law come true. Semiconductor improving and Moore's law in many people's mind are the same thing. So when I say, and I'm factually correct, that Moore's law is no longer holds, we are not doubling transistors every year's years, the downside for a company like Intel is people think that means it's stopped, that technology has no longer improved. And so Jim is trying to counteract the impression that semiconductors are frozen in 2019, are never gonna get better. So I never said that. All I said was Moore's law is no more. And I'm- Strictly look at the number of transistors. That's what Moore's law is. There's the, I don't know, there's been this aura associated with Moore's law that they've enjoyed for 50 years about look at the field we're in, we're doubling transistors every two years, what an amazing field, which is amazing thing that they were able to pull off. But even as Gordon Moore said, no exponential can last forever. It lasted for 50 years, which is amazing. And this is a huge impact on the industry because of these changes that we've been talking about. So he claims, because he's trying to act, he claims, Patterson says, Moore's law is no more and look at it, it's still going. And TSMC, they say it's no longer, but there's quantitative evidence that Moore's law is not continuing. So what I say now to try and, okay, I understand the perception problem when I say Moore's law has stopped. Okay, so now I say Moore's law is slowing down and I think Jim, which is another way of, if it's predicting every two years and I say it's slowing down, then that's another way of saying it doesn't hold anymore. And I think Jim wouldn't disagree that it's slowing down because that sounds like it's, things are still getting better, just not as fast, which is another way of saying Moore's law isn't working anymore. It's still good for marketing. But what's your, you're not, you don't like expanding the definition of Moore's law. Sort of naturally. Well, as an educator, it's just like modern politics. Does everybody get their own facts? Or do we have, Moore's law was a crisp, Carver Mead looked at his Moore's conservations drawing on a log-log scale, a straight line, and that's what the definition of Moore's law is. There's this other, what Intel did for a while, interestingly, before Jim joined them, they said, oh no, Moore's law isn't the number of doubling, isn't really doubling transistors every two years. Moore's law is the cost of the individual transistor going down, cutting in half every two years. Now, that's not what he said, but they reinterpreted it because they believed that the cost of transistors was continuing to drop, even if they couldn't get twice the main chips. Many people in industry have told me that's not true anymore. That basically, in more recent technologies, it got more complicated, the actual cost of transistor went up. So even a corollary might not be true, but certainly, Moore's law, that was the beauty of Moore's law. It was a very simple, it's like equals MC squared, right? It was like, wow, what an amazing prediction. It's so easy to understand, the implications are amazing, and that's why it was so famous as a prediction, and this reinterpretation of what it meant and changing is revisionist history, and I'd be happy, and they're not claiming there's a new Moore's law. They're not saying, by the way, it's instead of every two years, it's every three years. I don't think they wanna say that. I think what's gonna happen is new technology revisions, each one's gonna get a little bit slower. So it is slowing down, the improvements won't be as great, and that's why we need to do new things. Yeah, I don't like that the idea of Moore's law is tied up with marketing. It would be nice if- Whether it's marketing or it's, well, it could be affecting business, but it could also be affecting the imagination of engineers. If Intel employees actually believe that we're frozen in 2019, well, that would be bad for Intel. Not just Intel, but everybody. Moore's law is inspiring to everybody. What's happening right now, talking to people who have working in national offices and stuff like that, a lot of the computer science community is unaware that this is going on, that we are in an era that's gonna need radical change at lower levels that could affect the whole software stack. This, if Intel, if you're using cloud stuff and the servers that you get next year are basically only a little bit faster than the servers you got this year, you need to know that, and we need to start innovating to start delivering on it. If you're counting on your software, your software gonna have a lot more features, assuming the computers can get faster, that's not true. So are you gonna have to start making your software stack more efficient? Are you gonna have to start learning about machine learning? So it's a warning or call for arms that the world is changing right now. And a lot of people, a lot of computer science PhDs are unaware of that. So a way to try and get their attention is to say that Moore's law is slowing down and that's gonna affect your assumptions. And we're trying to get the word out. And when companies like TSMC and Intel say, oh, no, no, no, Moore's law is fine. Then people think, okay, I don't have to change my behavior. I'll just get the next servers. And if they start doing measurements, they'll realize what's going on. It'd be nice to have some transparency and metrics for the lay person to be able to know if computers are getting faster. Yeah, there are a bunch of, most people kind of use clock rate as a measure of performance. It's not a perfect one, but if you've noticed clock rates are more or less the same as they were five years ago. Computers are a little better than they aren't. They haven't made zero progress, but they've made small progress. So there's some indications out there. And then our behavior, right? Nobody buys the next laptop because it's so much faster than the laptop from the past. For cell phones, I think, I don't know why people buy new cell phones because a new one's announced. The cameras are better, but that's kind of domain specific, right? They're putting special purpose hardware to make the processing of images go much better. So that's the way they're doing it. They're not particularly, it's not that the ARM processor in there is twice as fast as much as they've added accelerators to help the experience of the phone. Can we talk a little bit about one other exciting space, arguably the same level of impact as your work with RISC is RAID. In 1988, you co-authored a paper, A Case for Redundant Arrays of Inexpensive Disks, hence RAID, R-A-I-D, RAID. So that's where you introduced the idea of RAID. Incredible that that little, I mean little, that paper kind of had this ripple effect and had really a revolutionary effect. So first, what is RAID? What is RAID? So this is work I did with my colleague, Randy Katz, and a star graduate student, Garth Gibson. So we had just done the fourth generation RISC project and Randy Katz, which had an early Apple Macintosh computer, at this time, everything was done with floppy disks, which are old technologies that could store things that didn't have much capacity. And you had to, to get any work done, you're always sticking your little floppy disk in and out because they didn't have much capacity. But they started building what are called hard disk drives, which is magnetic material that can remember information storage for the Mac. And Randy asked the question when he saw this disk next to his Mac, gee, these are brand new small things. Before that, for the big computers, the disk would be the size of washing machines. And here's something the size of a book or so. He says, I wonder what we could do with that. Well, Randy was involved in the fourth generation RISC project here at Berkeley in the 80s. So we figured out a way how to make the computation part, the processor part go a lot faster. But what about the storage part? Can we do something to make it faster? So we hit upon the idea of taking a lot of these disks developed for personal computers and Macintoshes and putting many of them together instead of one of these washing machine size things. And so we wrote the first draft of the paper and we'd have 40 of these little PC disks instead of one of these washing machine size things. And they would be much cheaper because they're made for PCs. And they could actually kind of be faster because there was 40 of them rather than one of them. And so we wrote a paper like that and sent it to one of our former Berkeley students at IBM. And he said, oh, this is all great and good, but what about the reliability of these things? Now you have 40 of these devices, each of which are kind of PC quality. So they're not as good as these IBM washing machines. IBM dominated the storage canisters. So the reliability is gonna be awful. And so when we calculated it out, instead of it breaking on average once a year, it would break every two weeks. So we thought about the idea and said, well, we gotta address the reliability. So we did it originally performance, but we had to do reliability. So the name, Redundant Array of Inexpensive Disks, is array of these disks, inexpensive like for PCs, but we have extra copies. So if one breaks, we won't lose all the information. We'll have enough redundancy that we could let some break and we can still preserve the information. So the name is an Array of Inexpensive Disks. This is a collection of these PCs. And the R part of the name was the redundancy so they'd be reliable. And it turns out if you put a modest number of extra disks in one of these arrays, it could actually not only be as faster and cheaper than one of these washing machine disks, it could be actually more reliable because you could have a couple of breaks even with these cheap disks, whereas one failure with the washing machine thing would knock it out. Did you have a sense just like with risk that in the 30 years that followed, RAID would take over as a mechanism for storage? I'd say, I think I'm naturally an optimist, but I thought our ideas were right. I thought kind of like Moore's law, it seemed to me if you looked at the history of the disk drives, they went from washing machine size things and they were getting smaller and smaller. And the volumes were with the smaller disk drives because that's where the PCs were. So we thought that was a technological trend that disk drives, the volume of disk drives was gonna be getting smaller and smaller devices, which were true, they were the size of a, I don't know, eight inches diameter, then five inches, then three inches diameters. And so that it made sense to figure out how to deal things with an array of disks. So I think it was one of those things where logically, we think the technological forces were on our side, that it made sense. So we expected it to catch on, but there was that same kind of business question. IBM was the big pusher of these disk drives. In the real world, where the technical advantage get turned into a business advantage or not. It proved to be true, it did. And so we thought we were sound technically and it was unclear whether the business side, but we kind of, as academics, we believe that technology should win and it did. And if you look at those 30 years, just from your perspective, are there interesting developments in the space of storage that have happened in that time? Yeah, the big thing that happened, well, a couple of things that happened. What we did had a modest amount of storage, so as redundancy, as people built bigger and bigger storage systems, they've added more redundancy, so they could add more failures. And the biggest thing that happened in storage is for decades, it was based on things physically spinning called hard disk drives, where you used to turn on your computer and it would make a noise. What that noise was, was the disk drive spinning and they were rotating at like 60 revolutions per second. And it's like, if you remember the vinyl records, if you've ever seen those, that's what it looked like. And there was like a needle like on a vinyl record that was reading it. So the big drive change is switching that over to a semiconductor technology called flash. So within the last, I'd say about decade, is increasing fraction of all the computers in the world are using semiconductor for storage. The flash drive, instead of being magnetic, they're optical, well, they're semiconductor writing of information very densely. And that's been a huge difference. So all the cell phones in the world use flash. Most of the laptops use flash. All the embedded devices use flash instead of storage. Still in the cloud, magnetic disks are more economical than flash, but they use both in the cloud. So it's been a huge change in the storage industry. The switching from primarily disk to being primarily semiconductor. For the individual disk, but still the RAID mechanism applies to those different kinds of disks. Yes, the people will still use RAID ideas because it's kind of what's different, kind of interesting, kind of psychologically, if you think about it. People have always worried about the reliability of computing since the earliest days. So kind of, but if we're talking about computation, if your computer makes a mistake and the computer says, the computer has ways to check and say, oh, we screwed up, we made a mistake. What happens is that program that was running, you have to redo it, which is a hassle. For storage, if you've sent important information away and it loses that information, you go nuts. This is the worst, oh my God. So if you have a laptop and you're not backing it up on the cloud or something like this, and your disk drive breaks, which it can do, you'll lose all that information and you just go crazy, right? So the importance of reliability for storage is tremendously higher than the importance of reliability for computation because of the consequences of it. So yes, so RAID ideas are still very popular, even with the switch of the technology. Although flash drives are more reliable. If you're not doing anything like backing it up to get some redundancy so they handle it, you're taking great risks. You said that for you and possibly for many others, teaching and research don't conflict with each other as one might suspect, and in fact, they kind of complement each other. So maybe a question I have is how has teaching helped you in your research or just in your entirety as a person who both teaches and does research and just thinks and creates new ideas in this world? Yes, I think what happens is, is when you're a college student, you know there's this kind of tenure system in doing research. So kind of this model that is popular in America, I think America really made it happen, is we can attract these really great faculty to research universities because they get to do research as well as teach. And that, especially in fast moving fields, this means people are up to date and they're teaching those kinds of things. But when you run into a really bad professor, a really bad teacher, I think the students think, well this guy must be a great researcher because why else could he be here? So as I, you know, after 40 years at Berkeley, we had a retirement party and I got a chance to reflect and I looked back at some things. That is not my experience. There's a, I saw a photograph of five of us in the department who won the Distinguished Teaching Award from campus, a very high honor. You know, I've got one of those, one of the highest honors. So there are five of us on that picture. There's Manuel Blum, Richard Karp, me, Randy Kass and John Osterhout, contemporaries of mine. I mentioned Randy already. All of us are in the National Academy of Engineering. We've all run the Distinguished Teaching Award. Blum, Karp and I all have Turing Awards. Turing Awards, right. You know, the highest award in computing. So that's the opposite, right? What's happened is they're highly correlated. So probably, the other way to think of it, if you're very successful people, or maybe successful at everything they do, it's not an either or. And even- But it's an interesting question whether specifically, that's probably true, but specifically for teaching. If there's something in teaching that, it's the Richard Feynman, right, idea. Is there something about teaching that actually makes your research, makes you think deeper and more outside the box and more insightful? Yeah, absolutely. I was gonna bring up Feynman. I mean, he criticized the Institute of Advanced Studies. So the Institute of Advanced Studies was this thing that was created near Princeton where Einstein and all these smart people went. And when he was invited, he thought it was a terrible idea. This is a university. It was supposed to be heaven, right? A university without any teaching. But he thought it was a mistake. It's getting up in the classroom and having to explain things to students and having them ask questions. Like, well, why is that true? Makes you stop and think. So he thought, and I agree, I think that interaction between a research university and having students with bright young minds asking hard questions the whole time is synergistic. And a university without teaching wouldn't be as vital and exciting a place. And I think it helps stimulate the research. Another romanticized question, but what's your favorite concept or idea to teach? What inspires you or you see inspire the students? Is there something that pops to mind or puts the fear of God in them? I don't know, whichever is most effective. I mean, in general, I think people are surprised. I've seen a lot of people who don't think they like teaching come give guest lectures or teach a course and get hooked on seeing the lights turn on, right? Is people, you can explain something to people that they don't understand, and suddenly they get something that's not, that's important and difficult. And just seeing the lights turn on is a real satisfaction there. I don't think there's any specific example of that. It's just the general joy of seeing them understand. I have to talk about this, because I've wrestled, I do martial arts. Yeah, of course, I love wrestling. I'm Russian, so I've talked to Dan Gable on the podcast. Dan Gable's my era kind of guy. So you wrestled at UCLA, among many other things you've done in your life, competitively in sports and science, so on, you've wrestled. Maybe, again, continuing with the romanticized questions, but what have you learned about life and maybe even science from wrestling or from? Yeah, in fact, I wrestled at UCLA, but also at El Camino Community College. And just right now, we were, in the state of California, we were state champions at El Camino. And in fact, I was talking to my mom, and I got into UCLA, but I decided to go to the community college, which is, it's much harder to go to UCLA than the community college. And I asked, why did I make that decision? Because I thought it was because of my girlfriend. She said, well, it was the girlfriend, and you thought the wrestling team was really good. And we were right, we had a great wrestling team. We actually wrestled against UCLA at a tournament, and we beat UCLA. It's a community college, which is just freshmen and sophomores. And part of the reason I brought this up is I'm gonna go, they've invited me back at El Camino to give a lecture next month. And so, my friend who was on the wrestling team, that we're still together, we're right now reaching out to other members of the wrestling team, so we can get together for a reunion. But in terms of me, it was a huge difference. I was both, I was kind of, the age cutoff, it was December 1st, and so I was almost always the youngest person in my class. And I matured later on, our family matured later, so I was almost always the smallest guy. So, I took kind of nerdy courses, but I was wrestling. So wrestling was huge for my self-confidence in high school. And then I kind of got bigger at El Camino and in college. And so, I had this kind of physical self-confidence. And it's translated into research self-confidence. And also kind of, I've had this feeling, even today in my 70s, if something going on in the streets that is bad physically, I'm not gonna ignore it, right? I'm gonna stand up and try and straighten that out. And that kind of confidence just carries through the entirety of your life. Yeah, and the same things happens intellectually. If there's something going on or people are saying something that's not true, I feel it's my job to stand up, just like I would in the street. If there's something going on, somebody attacking some woman or something, I'm not standing by and letting that get away. So, I feel it's my job to stand up. So it kind of ironically translates. The other things that turned out, for both, I had really great college and high school coaches and they believed, even though wrestling's an individual sport, that we'd be more successful as a team if we bonded together, we'd do things that we would support each other, rather than everybody, you know, in wrestling it's a one-on-one, and you could be everybody's on their own. But he felt if we bonded as a team, we'd succeed. So I kind of picked up those skills of how to form successful teams from wrestling. And so I think, most people would say, one of my strengths is I can create teams of faculty, large teams of faculty, grad students, pool all together for a common goal and often be successful at it. But I got both of those things from wrestling. Also, I think, I heard this line about if people are in kind of, you know, collision, you know, sports with physical contact, like wrestling or football and stuff like that, people are a little bit more, you know, assertive or something. And so I think that also comes through, is, you know, and I didn't shy away from the risk-assist debates, you know, I enjoyed taking on the arguments and stuff like that. So it was, I'm really glad I did wrestling. I think it was really good for my self-image and I learned a lot from it. So I think that's, you know, sports done well, you know, there's really lots of positives you can take about it, of leadership, you know, how to form teams and how to be successful. So we've talked about metrics a lot. There's a really cool, in terms of bench press and weightlifting pound years metric that you developed that we don't have time to talk about, but it's a really cool one that people should look into. It's rethinking the way we think about metrics and weightlifting. But let me talk about metrics more broadly, since that appeals to you in all forms. Let's look at the most ridiculous, the biggest question of the meaning of life. If you were to try to put metrics on a life well-lived, what would those metrics be? Yeah, a friend of mine, Randy Katz said this, he said, you know, when it's time to sign off, it's, the measure isn't the number of zeros in your bank account, it's the number of inches in the obituary in the New York Times, was he said it. I think, you know, having, and you know, this is a cliche, is that people don't die wishing they'd spent more time in the office, right? As I reflect upon my career, there've been, you know, a half a dozen, a dozen things say I've been proud of. A lot of them aren't papers or scientific results. Certainly my family, my wife, we've been married more than 50 years, kids and grandkids, that's really precious. Education things I've done, I'm very proud of, you know, books and courses. I did some help with underrepresented groups that was effective. So it was interesting to see what were the things I reflected, you know, I had hundreds of papers, but some of them were the papers, like the risk and rate stuff that I'm proud of, but a lot of them were not those things. So people who are just spend their lives, you know, going after the dollars or going after all the papers in the world, you know, that's probably not the things that are afterwards you're gonna care about. When I was, just when I got the offer from Berkeley but before I showed up, I read a book where they interviewed a lot of people in all works of life. And what I got out of that book was the people who felt good about what they did was the people who affected people, as opposed to things that were more transitory. So I came into this job assuming that it wasn't gonna be the papers, it was gonna be relationships with the people over time that I would value, and that was a correct assessment. Right, it's the people you work with, the people you can influence, the people you can help, is the things that you feel good about towards the end of your career. It's not the stuff that's more transitory. I don't think there's a better way to end it than talking about your family, the over 50 years of being married to your childhood sweetheart. What I think I could add is how to, when you tell people you've been married 50 years, they wanna know why. How, why? Yeah, I can tell you the nine magic words that you need to say to your partner to keep a good relationship. And the nine magic words are, I was wrong, you were right, I love you. And you gotta say all nine. You can't say, I was wrong, you were right, you're a jerk. You can't say that. So freely acknowledging that you made a mistake, the other person was right, and that you love them really gets over a lot of bumps in the road. So that's what I pass along. Beautifully put. David, it is a huge honor. Thank you so much for the book you've written, for the research you've done, for changing the world. Thank you for talking today. Oh, thanks for the interview. Thanks for listening to this conversation with David Patterson. And thank you to our sponsors, the Jordan Harbinger Show and Cash App. Please consider supporting this podcast by going to jordanharbinger.com slash Lex and downloading Cash App and using code LexPodcast. Click the links, buy the stuff. It's the best way to support this podcast and the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with 5,000 of the podcast, support it on Patreon, or connect with me on Twitter at Lex Friedman, spelled without the E. Try to figure out how to do that. It's just F-R-I-D-M-A-N. And now let me leave you with some words from Henry David Thoreau. "'Our life is ferreted away by detail. "'Simplify, simplify.'" Thank you for listening and hope to see you next time.

https://youtu.be/naed4C4hfAg

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Chris Duffin: The Mad Scientist of Strength | Lex Fridman Podcast #207

The following is a conversation with Chris Duffin, the mad scientist of strength. He's one of the strongest people in the world, but is also an engineer of some of the most innovative strength equipment I've ever seen. Check out his company Kabuki Strength. He's the only person who squatted and deadlifted 1,000 pounds for multiple reps and achieved many other amazing feats of strength. He has lived one hell of a life of hardship and triumph, as he writes about in his book called The Eagle and the Dragon. Quick mention of our sponsors, Headspace, Magic Spoon, Sun Basket, and Ladder. Check them out in the description to support this podcast. As a side note, let me say that I was always a fan of strength, both powerlifting and Olympic weightlifting, both as a fan and practitioner. Mostly, I'm a fan of people who are willing to put in years of hard work towards finding out what the limits of their body is and then smashing past those limits. People like Chris Duffin, or on the Olympic weightlifting side, people like Dmitry Klokov. That guy's great. This is why I love watching the Olympics, both the heartbreaks and the triumphs. They all reveal the incredible heights that the human mind and the human body can reach. This is the Lex Friedman Podcast, and here is my conversation with Chris Duffin. You've been a part of several incredible feats of strength. Which was the hardest, or maybe one you're most proud of? Definitely the one I'm most proud of is that journey for the grand goals. It was a five-year scope that I chased this. When you think about training, it took more than five years, obviously. By that point, I'd been training for over 25 years. There were three distinct things that I wanted to accomplish out of this. It was really thought out. This was my exit from being a competitive lifter and basically saying, hey, I'm going to be an Instagram lifter, an exhibition lifter, or whatever. I've done this for 16 years. I was number one in the world for eight years straight, all-time world records. I'm like, I'm not going to do that anymore. What I want to do is just something deep down to me that is really important. There's three things that were driving this. This is a five-year journey that I went through to do this. I really wanted to showcase that you could do something that is well beyond the scope of what people think is humanly possible. Just this inspiration thing, this grand over the top. If you set your mind to a single-minded goal, you can go so much further. I didn't even say what the goal was up front because it was so far out there, I would have been laughed at. I think big goals should be kept pretty damn close to start with for that reason too. Then the second piece was to walk the walk, to show the principles of what I believed in around human movement, the ability to manage and control the spinal mechanics and the output that can have on the body. I wanted to take the two most basic movements that every able-bodied person should be able to do. Fundamental movement patterns, the squat, which is in the developmental approach is around nine months as a baby from a developmental kinesiology standpoint and a really basic pattern that every able-bodied person should be able to master. The other one being the hip hinge, being able to pick something up off the ground, a deadlift. I wanted to do those two, not just one, because I wanted to show the principles that I wasn't built for one. I wasn't a specialist because of my lever links, torso links, all that, all that, any outliers, because nobody had ever done a thousand pound squat. This is it, and a thousand pound deadlift. It was outside of the scope of what anybody's, there's like half a dozen people that have done one or the other, but nobody's ever done both. I wanted to do something unique. I wanted to do them, not only do it, but do them for reps to leave literally no question out there. There's no competition for that. This is what I'm going to go do. To pull it off, I had some past issues with my elbows and stuff that I couldn't work around, so I had to wear straps, which was another reason I couldn't do it in the competition setting. The first year I worked up and I did a thousand and two pound deadlift. Plates were weighed afterwards. It was a little bit over. I did it for almost three reps. That still stands as a Guinness World Record, just the one rep does, as the most weight ever sumo deadlifted. One other person has deadlifted a thousand for reps at this point, and that was Thor Bjornsson from Game of Thrones. He's done a thousand for a double as well. Then the next four years, and I did a bunch of feats of strength on the way, but it was all about building that axial loading capacity, the strength that, because now I'm moving the weight from my hands up to my shoulders. To do it for reps is so much harder than a single, like five to 10 seconds versus 30 plus seconds to be able to buffer and manage all that with that kind of load is just crazy. It's literally about the duration that your body is carrying the load. Yeah, that's a big part of it. Yeah, because you're using the resource of the diaphragm for stabilization, and so it's also responsible for respiration and all this other stuff. Even when you're not squatting, you've got to be handling those loads. Just holding that weight is fascinating. It's fascinating that the human body can do that, can maintain that structure, just everything working together, that the biology, the skeletal structure, the musculature on top of that can hold the weight. It's fascinating to watch. Everything is very intentful about positioning and how you're creating pressure and all this sort of stuff, especially for me. When I mentioned that half a dozen people have squatted it and half a dozen people have deadlifted it, understand those people all weigh 380 to 440 pounds. I weighed 265 to 285 depending on where I was between the two. There's that as well, right? Big, big difference. Over the course of that, I did a lot of other feats of strength that fit in that capacity. We can skip over those, but that was hugely invested as far as what I put into being able to accomplish that because it's over the top, which means the other stuff had to shift. There's so many things that came into place to pull that off. Last March, two days before the world shut down, I did it. It was supposed to be at the largest equipment exhibition in the world down in San Diego as an event. That got shut down a week beforehand, obviously. We moved to let's do it in my gym and invite people. That was on a Saturday. Thursday or Friday, they limited it to 25 people for gatherings. I did it on Saturday. Then Monday, everything shut down. It was surreal for timing-wise. If I hadn't done it, it would have never got done because I'd pushed to the limit. I couldn't come back and do it. It was at the total limitation of my capabilities. I'm pretty proud of it. The last piece was every one of these feats along the way, I collaborated with a charity that I believed in. There was a lot of those tied to my life story, which we probably will get into. It was threefold. That inspiration piece, inspiration, motivation, walking the walk and showing just these methodologies that a guy that had to learn to walk again can do something like this with no back pain. There is a way. The third one is to provide awareness and recognition around a lot of key charities. So your heart was in this journey, but also your mind. You're like a scholar of strength, a scientist of strength, an engineer of strength. For reps, do 1,000 pounds of squat and deadlift. Let's first talk through the actual day you did it. What does it take to lift that much for reps? The day of is really easy. Really? The lift itself, other than a few seconds, is really easy and not challenging. People always ask me, what was it like? How beat up were you after that and the deadlift? The simple fact is it was easy. The work to get there was horrendous. So even the psychology of the day, there was not a fear, there was not a nervousness, there was not a doubt in your mind? There were certainly doubts on that day from some training history. So there was some major breaks to my confidence in the couple months leading up where I had issues with passing out under the bar, so completely losing consciousness. And this was on weight less than 1,000 pounds even. So that was all this buildup in me going, what if? I think I have this resolved, but what if I get up there and I can't even do a rep? How embarrassing will this be that I've been talking about this and planning for this for so long? But outside of that, I knew I could do it. In fact, I wanted to do even more, even up to the second rep. Training is about working into a fatigue state. So you're building an amount of fatigue in your system. And then when you let off of it, that's when you get a compensation. And that's how you stair-step training. This is periodization. But leading into a big event, you're accumulating this massive amount of fatigue. And so I was performing at a level that I could do it. And so I knew I was going to be able to on meat because then you give yourself that window to be able to recover and supercompensate and be able to do a little bit more. So that first rep when I did it, strength-wise, I went, I could do this for five reps. It went through my head. I'm like, I mean, it was easy and it was fast and it felt amazing. And I'm like, I'm going to crush this. And then set rep two, the realization kicked in. It's like, oh, this is for reps with 1,000 pounds on your back and you're fatiguing just like, and then the third one was every last thing I could muster to just finish. I mean, and I just barely got it done because it's the strength is like there, but like that capacity to be able to manage all those resources for that amount of time. Cause it's not just leg strength when we're talking about this stuff. So what does it take to go from the, from, I don't know what, like from 500 to a thousand that feels like a journey that's like exponential. It's much, it is. It gets exponentially harder. It does. In the early two thousands, like I said, I started lift in 1988. But my first meet in the early two thousands, my, my max deadlift was 523 and my first squat was 550. So, uh, that's a heck of a journey. That is a journey for people that like to lift. What should they understand about the difference between doing 500 and a thousand in terms of the actual lift that you were experiencing that day in terms of the mechanics, in terms of all the things you have to be like the neurological adaptation, you mentioned the breathing, the core strength, what like techniques, like little tricks, psychological tricks, anything that kind of stands out to you. The level of intent and the opportunity for air are at a different level. So just the minutest changes of position by quarter inch, half inch can be make or break at that level. So these things, everything gets amplified. So the ability to, to start with having the pelvis just in the right orientation to the diaphragm, before we start initiating what we call the, the eccentric loading of the abdominal cavity to create this intra abdominal pressure of working against this outward expansion, working against the outer sheath of abdominal thoracolumbar musculature, obliques, um, causing the co-contraction at the pelvic floor, all this stuff and how you cue that. Cause you can't think about all this stuff. You need to break it down and distill in practice to like, it's one simple cue that we now lock down and control this torso stability, because this is what these fundamental movements are about as being able to control our spinal mechanics. And then now be able to maintain that while articulating the joints around that through a range of motion, uh, and then using the main power drivers. So in this instance, both instances, it's the, you know, the hip complex to generate that power and transfer it from how we're rooted and connected to the floor through to the distal end, you know, which would be the barbell on the shoulder. You know, there's a couple of key concepts. So one is that what we just talked through is how to actually maintain that stability. So if you have either the diaphragm, so, uh, which is connected at the rib cage. So out of alignment in any position, it needs to be in alignment with the pelvic, uh, the pelvis. So those two in opposition. So this is simple engineering here, um, because what we're going to do is eccentrically load this. We're going to use the diaphragm, just like you would in a diaphragm pump, where it's going to press down on all the tissue in there. So we're not using breath. So our breath was actually a lot of times a default pattern when people do that, because they'll bring it into their chest and raise, uh, their rib cage. So, um, what we want to do is just initiate the diaphragm air can be used as well over the top at the final to create just a little bit more downward pressure. But if we have out of alignment there, we have, uh, a pressure leak where it's going to be pushed out the front or the rear, if you're either inflection or extension. All right. And then that causes this co-contraction and all this pressure of, of, uh, the organs essentially against outward, against all those tissue for the co-contraction, as well as surrounding the spine to be able to stabilize that. And then it puts all the muscles on both sides of the body in what we call the, the, the best length tension relationship. So if you think about a curl and we reach our arm out at the extended length, our bicep is not as strong and then all the way in the curl position, it's not in strong. There's somewhere in here that's this control of both. And so when you're sitting there arched or bent over, we have muscles that are past either one of those ranges. So they've got a lot of tension, which then will create relaxation on the other side. Right? So we want to have an, all of that needs to be working. And now the next important thing is the foot. So it's actually this connection to the ground and how we're actually using the foot and ankle complex to grab and grip this connection to the ground and elicit, uh, an effect. And because of this, and then the everything between will naturally kind of do what it needs to do. So people like to focus on knee, knee position or how far out their hips are, all this other stuff, which is outputs of this. So if we control the torso and the knee, the only thing that can happen from that point is for the squat to happen. All right. Um, so this allows us to use this massive foot, you know, the hip complex for all the muscles around that, that are built to drive through hip extension to complete the squat. I did actually miss one thing in there. So this torso people will often miss, uh, the lat is a spinal stabilizer as well. So that's key in controlling a function at the, the, uh, TL junction, um, which is, um, just above the lumbar spine. So kind of right opposite where your sternum is, and you'll see people kind of roll over sometimes like in an Olympic squad or something like that, where they lose position. Um, and that's often because they're close grip because you can't engage the lats very well that way. And they're pushing up in the bar, but you want to be able to drive and pull the bar to your center. And that's going to create and use the lats now to drive and connect the shoulder into this. And we're kind of congressing and tightening all this stuff towards that center to create that entire torso stability. That's why I was using torso stability, not just core stability, uh, in my conversation earlier. Torso stability. Okay. So there's all these like modules of the body, then connected to the grounding with like your feet on the ground, everything you're speaking to, how do you work each of those modules? Is this over time, you kind of develop the feel that ultimately boils onto this one simple cue that you mentioned, or do you, can you like literally study each particular module in yourself and see how it affects the lift? So the best way, and I'm big believer, cause I hate just like people getting out and just doing just movement stuff and not actually adding load because we only adapt when there's load, maybe we can get some, you know, some proprioception or awareness of position and other stuff, doing some, some corrective patterns and other stuff. But this is basic physiology is that there must be an imposed demand for us to have adaptation. And this is mental, this is emotional, this is all these areas. Um, but, and people miss that so much. So miss that. So I prefer to be able to look at a person and this is our methodology and do the assessment in any basic loaded movement. So with developing an eye for that, you can actually see and go, okay, we've got a fault pattern right here in the foot and use a cue or a set of cues. It doesn't really matter till we find the one that works and bring that. And now we know we want to simplify this stuff. I just walked through. That sounds really complicated. And it, it is, if we try to break down and distill it all, but like, let's just find the basic stuff that gets us in the range, start working and then find the next, as we add load. Now we find where's our next area that we're starting to fault that and then go there again next. So this is what we do, what we teach in our educational platform. So we are the only, I believe everybody wants to do a lot of these like, uh, assessments, you know, on a bench, on a table body. And it's like, no, let's, let's go squat. Let's go deadlift. If you do strong men and it's a yoke carry, let's go carry. Cause these are basic human fundamentals. It's not powerlifting. Like this is how we function. This is why we, we work with 29 of the 30 major league baseball teams and 90% of all professional sports out there in North America. Sorry. Although we do some work with tour de France and other stuff as well. And, uh, North America, I do mean hockey too. Uh, but, uh, these principles like, you know, if, if the Dodgers won't bring us in, they're not learning how to power lift, you know, we're going to, obviously we'll probably be do we do a little bit more, uh, shoulder focus than hip focus with their athletes or their coaches. We're usually working with the coaches, not the athletes. And so you help them. And then the same thing on yourself to understand the role that these different muscle groups have on the holistic. Yeah. So it's all about getting the joints in the appropriate position so that we can, that we can manage loads so that we're not putting undue stress in the joint. We're getting the proper link tension. We're getting these basic fundamental things with the body. And so the, the largest global impact that you will have is through spinal mechanics. I can't look at a shoulder if I'm not managing this, cause it's your spine. So for those that are just listening, like I'm arching and then, and then flexing, um, that's going to affect shoulder extension, flexion, all these sorts of things. So it could even affect things down to what's looking at dorsiflexion issues on the foot. Like, and then that's why I go to the foot next because it has the second largest global impact. And then from there, now I'm going to look at the big energy drivers, which is be hip complex, shoulder complex. And then we can start looking at kind of the peripheral things, but usually that's some sort of output of the other, but the knees, the elbows, the things like that. So it's all about getting the stack, which affects neurology. So let's talk to engineering terms. You get in a car, modern car today, and a lot of them will have this traction control button in there. And there's a big misconception that, you know, I'm, I'm out and it's, it's snowy or snowy or here in Austin, only rainy. Well, it probably doesn't rain much, but you're going around a corner, start slipping. It's like, Oh, it's going to send the powers from the wheels that are slipping to the ones that are gripping and keep me from crashing and dying a fiery death. Well, that's not how it works. It's the exact same. We've got, we've got the, we've got the tires, which are our foot, you know, the connection to the ground, right? We've got the power driver, which is, you know, the, the engine, the transmission delivering, you know, the power through it. And we've got the stability or suspension, and then we have the neurology and what the neurology is doing. It's sensing that we don't have good stability or a loss of connection somewhere. And so I need to save you from crashing and hurting yourself. And so it goes to the engine and says, let's retard the timing. Let's reduce the shift patterns. And we're just reducing the power output. And that's straight how the human body works. So when I do this stuff, it's actually affecting that. I mean, I can take somebody and do some minute changes with the neck position at the thoracic outlet. Okay. And immediately see an enhancement in power output. And I can measure it. We measure this stuff with velocity devices and see like a 10% boom jump. And so think about that. What about all your training through the years where you actually had additional capacity, but you weren't using it because your traction control was on. Now you figure this out stuff, and now you start stacking it. Now you can see so much greater. So it's not just injury prevention. This is performance and additive performance over time. This is huge. And people don't really think about this stuff, but we can turn that stuff off, which is actually going to also, again, make us safer. But what we want to do is the performance tuned race car. Do they have a traction control button? No, they got some amazing tires to grip the ground, a performance tuned suspension, and that driver's going to put what his foot to the metal. He's going to put it to the floor. Okay. That's a performance vehicle. That's what we want to be. I want to continue on that line. But first I have to ask, like, how did it feel to accomplish the grand goal? Oh my God. Okay. When you just stand back, oh my thousand pounds for reps. What did it feel like? Anybody can go watch the video online. 12th film, by the way, got me all like excited. Oh, well, the movies. So we actually have the final footage of that. The good footage not posted yet. So it's literally just an Instagram video or a phone video right now. The only one online. Yeah. It's on your YouTube channel. It's dramatic. Yes, it is. Yeah. Came out just timed to the music perfectly too, which is I listened to some odd music, which there's some reason behind that. Okay. I liked it though. It was great. It does work. You're saying there's full length footage? There's a documentary that's, it's got a little slowed because of COVID, because it's also a backstory of the Eagle and the Dragon, my book, about why I do kind of the things that I've done in my life. Or that's what I'm assuming the director's working on. I don't really have the control of the movie, right? But, but okay. But the video is incredible. How did it feel? How did it feel? I started crying. It was overwhelming to have worked so intensely and so long and hard at something that pushed every ounce of me to the limit. But, and, and I did it. I'm getting a little emotional. I did exactly what I said I was going to fucking do. And it was, it was overpowering. I mean, I was just crying uncontrollably, just with a mixture of, I don't know what the mixture of emotions is hard to explain. Cause it was the completion of something. It was a new phase of my life. I mean, there's so many things here. So one, you set an impossible goal and you accomplished it. One. Two is like on the broader humanity aspect, like how many humans in this world accomplish perfection in a particular direction required to do this? So like, you're basically representing like one little, like, like little glimmer of excellence of the human spirit. There's always more. So understand this. This is a basic fundamental. You can always do better. There is no such thing as perfection. You could always, there is always more. So anytime you reach something, any amazing workout or accomplishment in life, could you have put more into it? Could you? Yes. But here's the thing. I left on my terms. I said, this is it. I'm going to work towards, I've been training for 30 years. I'm going to do this thing that is like, I couldn't even say that I was going to do it years before. I'm going to do it. And then I'm done. I didn't leave from an injury. I wasn't forced. I wasn't, I left on, I did exactly what I said. I went to a level that I, I left on my terms and that's unique because that's usually not the case. Usually you kind of either taper out or it doesn't matter. I'm talking like anything in life in general. You taper out, you fail, you hurt, you lose, something, you roll into retirement. You accomplished something truly great and you walked away on your own terms. Is there a sadness completing something like that? Because it's in one perspective, the greatest thing you'll ever do. And like when you accomplish such a great height, in some sense, you have to face your mortality at that point. So good question, but it is certainly not the greatest thing that I'll ever do. The greatest physical strength I'll ever do. The greatest physical, yes. But that was an expression of some of my values and the way that I want to live. It was a way of expressing it. So understanding that is hugely fundamental because we do see so many athletes get to the end of a career and then they fall into a depressive state and struggle with drugs, alcohol, depression, so on, because they lost how they identified themselves and trying to figure out where to turn, what to do, but a big central component of their identity is lost. So I knew that this was one way to express that and my grand goals have shifted. They're shifted to other outlets that allow me to express that. Like my companies, Kabuki Strength, I'm going to change the face of fitness as well as all the way through with its integration with clinical medicine and telemedicine and I got another five years before even people see what I'm working on. I'm five years in right now because I had to invent equipment. I have to develop methodologies that we're talking. I had to do this stuff that Ground Layer wasn't done to create a cohesive ecosystem of training methodology tied to the tools that we're using, to the environment tied to the clinical practice assessment tied to the interaction between all those and how that actually needs to be reframed because so much of this is broken. But there is sadness. I won't deny that. And the sadness comes in the singularity of focus that I had at that time, the being in the process. Not necessarily do it, but like being in this place that the rest of the world kind of fell away from me in those final phases to have something so intense, to have a team around me so focused on supporting. It took me a couple months after that squat. I finally one day I woke up and I was like, oh, welcome back to the world. I was in such a mental fog. It took me a while to climb out of that. But that space, that level of intensity and drive and living and being in that space, I do miss that. But I also I can't continue that. I couldn't continue. There's a point of you push it so hard, the level to try to go from there is not acceptable for the impacts that it'll have on your life or how you want to live. And it was taking away those final like I had to do extreme things and live in an extreme way to get there. You're just a genius in this whole space of strength and health and almost like biology that the strength feat is just one representation of that. But this particular strength feat required that kind of singular focus, which I think, I don't know, there's something beautiful about that singular focus. There is. Often only truly perfected in athletics. I see it with the greatest Olympic athletes as well. The kind of singular focus required there is incredible. It's somehow some of the most beautiful things that humans can do. And it's not just that thing. So that's the thing. It's like, oh, that must be it. When we say singularity of focus, it's not like, here's it because it covers a vast array of stuff. Like I was working with people all around North America, I wouldn't say anybody around the globe, but professionals coming in, working on different aspects of rehab and recovery. And like, I mean, I'm tapping all sorts of stuff in so many platforms from nutrition to drugs to, again, various Chinese medicine, as far as- But also the humans in your life, just love and positivity and just inspiration, all those kinds of aspects. I mean, you probably would have done much more if you went outside North America and talked to some Russians, just between you and I. Some Russians. Possibly. Like they give you some, I don't know, there's some incredible strength athletes in Eastern Europe. Absolutely. I've got the best one coming in September to get fixed. So what do you mean by fixed? So I'm not sure what his particular issues are, but he has held the all-time world record repeatedly for a long time, and he hasn't competed for some time. And he just reached out saying he would like to come and have me take a look and see if I can get him fixed because he needs to return. So, okay. So it's more injury-centric versus like form and fundamental-centric combination of everything. Everybody always wants to focus on the output. How do you give me the fix for that? But it ties right back into all those other things. Right? So, but yeah, the Eastern, the Eastern Bloc continued to be a dominant force in regards to athletics and strength athletics, without a doubt. Some of my big rivals in my competitive days were, that's who it was. Rivalry brings out the best in us. Can you tell me the story of your childhood? It's definitely outside the scope of the norm. Well, today, maybe not 150 or 200 years ago, but my parents, highly intelligent people coming out of the Bay Area. My mom was going to school to be a chemical engineer. She was a top student athlete, graduated out of her school. My father was a member of Mensa. My stepfather was just a genius, but not able to really function in society. But my mom was, she had some demons and some other stuff. And just, she just said one day, she's like, I just don't want to be part of society. She still isn't. Lives out in the desert, but has her minds. But she wanted to figure out a way to make a life outside of that. And so that's where we ended up is up in the mountains in Northern California. And a lot of that was them trying to get into successfully growing marijuana, which back in that, it wasn't legal back then, highly illegal. And in fact, those areas were, some of the areas where I lived were quite dangerous. So there's a documentary, Murder Mountain, that came out recently. If you watch that, you'll tie into my book, just the understanding of the stuff that I was talking about, dealing with serial killers, human trafficking, police corruption, murderers, like just how real that stuff is if it doesn't capture you from the book. The book, by the way, is The Eagle and the Dragon. Yeah. Thank you. Yeah. I'm a terrible salesperson, like I told you. But it's a good title. I don't know if you came up with it, but- I did. Yeah. So yeah, we'll talk about that anyway. Yeah. We're living by a stream off a meadow. There's no roads into where you have to hike in. And we've got beams lashed into the trees up above us because that's where our bedding is, because there's rattlesnake dens all around. And six years old, I'm being taught how to capture and handle live rattlesnakes, because that's what I need to do to be safe. And you can imagine, six years old, sitting there with a live rattlesnake in your hand, grabbing it by the side of the head, controlling so it can't bite you. And it's just wrapping itself around your arm and you're staring. Its only intent is, right then, is to kill you. Like, that's it, right? You want to take a bath, it's filling up the jug in the stream and setting it out on the rocks during the sun so you can dump it over your head. And not all the living was that way. Good part was similar to that, tent living, living in a 16-foot trailer with a family, a six, which is not much bigger than the space that we're sitting here. So we're talking hard winters with feet of snow on the ground, nowhere to go. I'm living in the back of the pickup truck in just a standard sleeping bag that we get from the Salvation Army, not the Blow Zero. So I'm not sleeping well. There's living in homes that were maybe condemned. There's no doors even on them, no electricity or running water, or one or the other, or both, and sometimes a little bit better. By the time we got to high school, we had a mobile home. So my stepfather had won a disability payment because he had a broken arm that whole time from an accident a long time ago and finally got an award and got a down payment on this mobile home that didn't have, again, doors on the inside. It did have running water, did have electricity, didn't have a kitchen. The windows would crank closed and open, but they wouldn't close all the way. So they'll trim them in with plastic to be able to try to protect from the elements. That was my environment, learning how to forage for mushrooms. I mean, there were summers I would send and my parents would be out. They were in the drug trade earlier. We got taken by the police and put into foster care for a while, which ties into some of the stories with human trafficking. Honestly, it's in my book, but it's really hard for me to talk about that stuff. Obviously, not all that's in the book. But they got us back, moved to Oregon, and they stayed out of the drug trade from that time to ensure that they didn't lose us again. But quickly, we fell back into the same thing. So at that point, it was learning about geology and starting to do mining and firewood cutting, but mostly the mining because Pat's broken arm chainsaw made a little tough. If you remember just the sequence of moments, are you haunted by the darker moments of your childhood? Do you remember moments of simple joy and happiness? Outside of the living around dangerous people and the interactions that came from that, we were a family. We were a cohesive unit battling against the world together. We spent all our time together, work, play. I was there. I was helping raise my siblings or I was working with them. It was a constant. Like I said, we were very physically active. So I had that in my upbringing. I had a plug for my shoe company, Barefoot, B-E-A-R. I ran around the wilderness and bare feet all the time. I had a lot of great moments. I'm thankful for a lot of that childhood once we take out the trauma and the other stuff associated with it. So the connection that I have with my sisters is huge. That goes a bit further because I am a little bit of a father figure because I was at home raising them. Then later, I took custody of them while I was going to school because the environment at home deteriorated further. Their stepfather, like I said, he wasn't capable of managing life. My mom had a mental breakdown and took off to Montana. He descended into madness even worse. I actually took my 13-year old sister and kicked her out in the middle of winter, a couple feet of snow on the ground because he thought she stole his favorite cereal bowl type. So that's when I took in and was going to college, putting myself through college, and I started taking custody of my sisters and raising them. So anyway, we're still like very, very tight family. There was a few years later in life that the connection with my mother was kind of broken. I didn't speak to her for years because of her basically abandoning my sisters and me having to come in, but we've worked through that as best we can. So you anger on your part? It wasn't, there might've been some anger. Did you always love her? Yes, and I still do. She's taught me basically everything I know about strength and perseverance and living life on your terms and being able to create that. So much of what I am is from that. That we've all had to learn to be okay with the way she is because she is just blunt, but she's the one that figured out that the human trafficking situation and got the DA involved and got all the, she's the one that I've learned a lot from her. Did you inherit some of the demons? Oh, most certainly. And it's something I've continued, and my father's side has been really tough on that because some of it is just based genetic as well. So my stepfather made, I think six or seven attempts on his life during his lifetime. One of those in front of me, his mother blew her head off with a shotgun. Her brother jumped out a window in LA. Their father did something similar. And I don't know how far back it goes because there is no family except for me and my children. You spoke about going through depression yourself. Yeah. Can you talk about some of the darker moments of that? Have you ever, like many in your family, have you ever considered suicide? Yes, I have. Yes, I have. You've achieved a lot of exceptional things in your life. Can you talk about those early days of depression and how you overcame it? Yeah. So the things that I did that people give me accolades for are the things that I did selfishly to save myself. The things like taking custody of my sisters, being the person that everybody around, the important people relied on, the fact that I had to step to the plate and be present and be that person. Because if I failed, they failed. They would be like the people that I grew up with that are dead or in prison or on drugs and they're either way to one of those. That's where everybody ended. And I wasn't going to let that happen. What about saving yourself? Right. And so that's how in those early days, that's how I did it. Not saying it's the best approach, but it was survivor mentality. It was, I can't selfishly do that because I have them to take care of. Right. And then that continued where I would keep putting myself in these leadership roles or other things and just always being this person that was at the center, at the hub that forced me to be there. And so it's only in the more recent last decade or so that I have had to really learn how to come and start confronting some of those demons. And you think, man, why is the guy so successful? I mean, and we haven't talked about all the stuff that I've done, but I've seen a lot of success in both business leadership, athletics, academics, entrepreneurship, all these sorts of things. But if it wasn't for having kids and the same being in the position, I wouldn't be here. And that's the reality of it. And I'm learning to come and manage those as best I can, learning to meditate into those things and really feel what the driver is so I can get to those root understanding and having some guidance doing so. If you've got mental health issues, this isn't something that you need to tackle on your own. Having a professional that can help guide you on that introspective journey is something like, it's not like, hey, I'm a big tough guy, I can handle everything. You know, that's fascinating that you saved yourself. That's quite powerful to save yourself by having others depend on you. And so you can't fail, you can't fuck it up. And that's a reason to keep moving forward. But on the flip side, that's not addressing the darkness. It's not. And it's probably not a sustainable strategy either. Right. So I recognize these. I don't know. And perhaps it is sustainable. Perhaps. I mean, there's something beautiful about giving yourself basically in service of others and thereby creating purpose. And then like, it's almost like fake it to the point where you're like, I'm gonna give it to you. And then you make it eventually. That is purpose though. That is purpose. I mean, you have to, to me, life is about taking your cup and how you choose to pour it out, how you choose to give, what is your purpose? What is that connection with everybody around you? That's the intent. That's the life. That's what life is about. How are you going to help those around you? How are you going to help the world? Your purpose is right here, figuring out what this is and then how to do that. But at the same time, you can't let that run dry. So you have to make sure that you're filling that up. That's the other side. That's the other side. That's the other side. Yeah. We'll return to your engineering degree, which you're obviously scientifically engineering minded, which is fascinating. Your book is titled The Eagle and the Dragon. What do the eagle and the dragon symbolize? They're pretty big symbols for me. In fact, that covers my entire body as a tattoo. So the first one I had done at around 19 years old. And so this is, or started at 19. It's an eagle that an eagle that covers my entire front, my stomach, rib cage, and one that was on my back that covered most of my back. And there's chained at the, well, at the claw, I guess. And the chain wraps down around and attaches to my ankle and there's a shackle there. And so this was something that I had done at that age because it was, to me, it was a representation of your potential, your strengths, your abilities, that you can fly to whatever height that you want in this world. The only thing holding you back at the end of the day is yourself. And this was, I hadn't necessarily accomplished a whole lot at that time. I mean, I was valedictorian for high school, small high school. Does that even count? I was a state level wrestler. This was my belief. You sensed that there was a potential in you and the only thing that could stop you from realizing that potential was yourself. That's right. That's a heck of a tattoo to get, by the way, at 19. But yeah, 40 hours went into that thing. It shows you got some guts. And then the next tattoo, so I only have two, I had done in 2015, 2016, at this point in my life. So I had done that. I had flown to whatever heights. So I had proven to myself and maybe done what I thought I needed to do to show the world that this poor kid from the sticks, this kid growing up in the mountains with nothing could achieve the American dream. I was a corporate executive sought after that I'd come in, I'd fix companies, I'd turn around and prep them for sale. I'd take a company and grow it from a regional to a national to a global presence. I did this in the automotive manufacturing, aerospace manufacturing, high tech, heavy industry. And I had a house with a white picket fence. I was a successful athlete with all time world records. I owned a gym on the side where I coached people and had a comfortable marriage that everything was hunky dory with no arguments at home. And I walked away from all of it. I left everything behind except for my kids. I wanted to chase what I was meant to do and chase what I was capable of doing. I wanted to become a better version of myself, but very intentfully. And that's what I did. I sold, I had multiple homes, sold my homes. I cashed in all my retirement that I'd earned for 20, nearly 20 years. And I lost all that. I leveraged myself millions of dollars of personal debt so that if I failed, there was no way out. Even going back to that old career that I did well, I'd be living in an apartment the rest of my life, paying it off. People questioned, people questioned me at the time. I was a good guy. I was a good guy. I was a good guy. People questioned, people questioned me at the time because I had a comfortable, easy marriage. And I chose to ask for a divorce. And I ended up living in an apartment for a couple of years with no income, selling off every last thing that I had except for my two vehicles that I built and with my kids. And I started my businesses to help people live a better quality of life, to get them out of pain, to help them live better through strength, to realize that stress, demand, those things, they don't have to be the thing that, if you look back, made you had the bad back, made you have the bad Ds, but they do the opposite. They get you out of pain. And then I started working on my book to hit on those other things, the mental, the emotional, maybe even spiritual. I don't touch on that one too much in there, but it's all the same. That things that happen around you to you, maybe they're bad. I can't take away that, but why can't you use what you have of it to become a stronger and better person, to become more resilient, to be able to take the things that you don't know that are coming in the future? And so this is very intentful. And that's what the second long-winded answer in your question here. The dragon. The dragon. The dragon is an Ouroboros. And so it circles my entire upper body, my shoulders, my back, my chest, everything. It's right here. There's this big dragon head and its tail is right there in its mouth. That's eating itself. And it may sound a bit graphic or whatever, but it is, it's the eating of the old, becoming the new. It is the purposeful reinvention of oneself. It is the deciding, not realizing just your potential, but deciding specifically who you want to be in this fucking world and becoming that person. Can you comment on the value and the power of putting a flame to your old life, your old self, just destroying all of it as you walk into the new life? Did you have to do that? I don't recommend this, by the way, because when you put yourself in no way out, there is no way out. Okay. Like you got to really, but I can be an overconfident individual at times. And I live through extremes. I think it's a great way of actually finding your real values and how you want to live, honestly, to chase the the having absolutely perfect squat technique, but chase putting every freaking thing that you've got in it, which most people would say those are, those are opposite. Those are diametrically opposed. I wanted a better home life. I wanted to do more in the world through my work. And the burning the bridges mentality is not necessarily, you know, the best. There was some temperament in that though, because I, I was not, I was slow to make the shift for a long time because I'd been thinking about doing it, but I was thinking about doing it in a healthcare perspective. I'm going to go back to school to be a surgeon or a physical therapist or a Cairo, because that's where like all my research and stuff was in this, this human movement and rehab and recovery. This is the mentors that I've been developing were the best in the world in these things, in these disciplines, those were my, my friends. And, and, but I wasn't able to compromise my family's certain quality of life. I wanted to, to keep that. So it was, it was slow and hard for me to make that transition, but I didn't do it until I had a platform built enough that those first few years I did have an income. I was able to make enough from the business until it grew so fast that I needed so much more needed to come in the living in the apartment piece and doing all that. That was actually a couple of years into into that process, maybe like two years. I'm with you on that. So I, I'm actually going through that very process now. I put, I, I put everything, I quit everything, gave away everything and starting a new. And unfortunately, or fortunately this podcast somehow became quite popular. So it's getting in, in the way of my burning everything to the ground, but in that it's a source of joy. But the main thing I'm after is is a similar project as you is building a business. Sense of joy. So this, this is the point I want to drive home right now, right now, because when I say burn, I learned the burning the bridges works because that's how I had to succeed when I was earlier, the bridges weren't burnt, they didn't exist. There was no couch to go home to. There was no, there was no fallback plan and it forced me and gave me the confidence to know that I can pull it off. But I don't encourage people because there's so much out there of this hustle porn and other stuff going, just grind, just go after it, get in and start your, like, you'll get there. And it's all about the output to make money, to be somebody, to do this. And I'll tell you what, that is some short-term motivation right there. I feel like dropping a few swear words, but. You're always welcome. This is, we've already done a few, so we'll, uh. All right, we'll balance it out. That is short term. That is not going to keep you going. This need, if you're going to go that approach, it needs to be because this is your North star. There's going to be so much hard work. There's going to be years of just pushing through where your quest, not only is everybody around you questioning you and your family's questioning you, you're questioning yourself going, man, I don't know if I can pull this off. You're going to be stressed. You're going to be pulled to the max. If somebody comes up to me and says, should I start a business? I'm going to say no. And then people are like, oh, you're supposed to motivate me. If you need me to motivate you, this is the wrong damn approach for you. This is going to be hard. This is going to be harder than you expect, even with me telling you this. And so it better damn well be worth it. This better be your North fucking star. This better live and be a way for you to be able to articulate or realize those values that you want to live. This isn't something to make money. This is a way for you to live the life and be able to share the values that you have with the world. And that's what it is. And if you don't have that, which is going to give you joy, then freaking walk away. Yeah. This is not some way to make some money and be known. I mean, this includes both like simple day to day joy and also deep meaning. The whole thing. And then that allows you to overcome all the pain along the way. But I got to say, I mean, it's a difficult thing because you run a business. This podcast and a lot of things I do research wise is full of joy, but it's simple. Running a business is hard. So it's something that I'm very hesitant about in that to almost push back a little bit. I think if I do get the guts to start the business, it will not be because I'm not choosing a more joyful life because I'm already truly happy. The reason I'll choose is because I just can't help it. I've always had this dream and I know it's going to lead to suffering and I know it's going to be a life that has less happiness in it. As sad as this to say. But it won't be. It won't be less happiness. Because we talk about this cup and where you choose to pour it and what you choose to do with it. And when you look back on things, the things that are going to give you the most joy, the most proud, the things that are going to stand out in your life that you really remember are going to be those days. And those years you struggle, you're going to look back on 10 years later and go, fuck, those were the glory days. Those were the glory days. Yeah. And it won't feel like it at the time. That's what life's made of. And so this is your opportunity. You feel that. So right now, you got this, when you think about it, you got this little thing twisting up in your gut, right? It's a mixture of anxiety and fear as well as excitement. And that is, that's your signal that this is your opportunity for that personal growth to challenge yourself. This is your going for a run or working out in the heat. It's those things. It is your opportunity to go, heck, maybe it even fails. Maybe it even fails. But by turning into that, you're going to learn so much and it's going to make you so much better. And it's the path that you should take when you have this stuff rolling around in there. And I don't, it could just be a hard conversation with your partner or your boss. It could be taking on a project that your boss has thrown out to the team and you're like, oh, I'm going to hide in the back. I don't want that one. And it's like, maybe you do. Maybe it's going back to school. Maybe it's making that career move that you always wanted, but you're just afraid of. All these things are your opportunity for you to turn into that. It is your workout. It is your practice. Because if you don't, you'll get soft and who knows what's coming and you're not going to be ready for it. And it's going to run right over the top of you because you're going to be weak. You're going to be soft. There's some aspect in which choosing that hard path is actually the way to arrive at the richest kind of happiness, the greatest fulfillment. That's the funny thing about just the human. But just make sure you're filling the cup as you're going through it, not pouring it all out. So that's the part to figure out, right? Sure. Well, life is short anyway. Eventually the cup will be empty. So maybe time the refilling of the cup correctly so you maximize the little time you got. Let me talk to you about strength a little bit. First, high level. What are the differences in the different disciplines of strength? So powerlifting we talked about. Maybe just to clarify for people, powerlifting, Olympic lifting, just regular gym fitness, bodybuilding, doing curls in front of the mirror for hours like I do. What's the difference between all of these? Oh, and also strongman. Strongman, every one of those as far as the athletic disciplines are different qualities. So we want to think about things as terms of quality. So there's strength, there's power, there's endurance, there's the ability to be coordinated and athletic. There's all these things and they're different qualities. So your training as it relates to that is how you cycle in the development of those qualities. What we want to think about is there's a lot of different frames of thought. Some very classical, maybe not classical Russian approach because there's a lot of different approach from the Eastern block. But one of the ones is developing all the qualities at once, focusing on building those. More of a periodization effect would be focusing on one quality at a time or one quality while maintaining other qualities and then shifting that around. So it's just going to be a little different based on what the output is and what the desired. So like powerlifting is actually, power is the wrong word. There's actually no power in it. It's just brute. It's strength. Application of force. Olympic lifting would actually be a better name for powerlifting because that is more explosive development. Strongman is again, now we're getting a little bit more athletic. It's equipment based on the implements and stuff that are used, how fast you can move your feet and run, mixed with more endurance, but still very strength focused. And there's some things with strongman that is straight. Each one of these is very also focused on different genetic dispositions. So actually, if you look at the history of sports, you'll find that they're a lot of times based on different populations. And it sounds like it's very un-PC, but like a Highland Games, they've got deeper hip sockets that are shallow. So you're going to see a lot of short hip hinge movements, like the caber toss and things like that. Muay Thai wrestling, they've got a completely different hip joint. And so strongman itself is going to be for very large frame individuals. If you're not well over six foot and a large person, you're probably not going to perform well. Very few people at sub six foot have ever done well at strongman just because it's leverage based, right? Olympic lifting, we see consistently in Europe, the history tells us a high level of hip and back issues because of the depth that that hip socket has to go in to be able to complete that lift. And so you're going to see issues with populations that don't have the ability to do that. So we've talked a little bit about training as well as disposition. Yeah. And also cross-fits into that, that's more like strongman, but for a wider variety of bodies, I suppose. Yep. And definitely more metabolic conditioning focused than the strength aspect of it. And conditioning is an interesting thing too. So that quality, in my opinion, can be developed a lot faster, but kind of peaks much faster as well. So where strength, we can continue to add and add and add over time. So it's, for me, like for conditioning with any strength athlete, I don't like to spend as much time on that. So I'll cycle the conditioning work for our strength athletes and then taper that off leading into meet. So the more metabolic work, that means the more capacity in strength training that you can accomplish, which is the goal, and recover from. But then as we lead to a competition, we want to spend more time on recovering from that. So we have to pull things out, so we'd pull out less. So a typical approach would be taking a six-week cycle for conditioning and ramping up over three weeks periods time, then dropping back down again and ramping up and being slightly offset by a week or two from your strength peaks, so that you've actually tapered the week prior in your conditioning work to your strength work. But that way, we're not hitting conditioning hard all the time, which is a common misstep that people make, is going, well, I need conditioning. So they just hammer that at a base level over the top instead of cycling that. If we talk about powerlifting, in terms of regimen, in terms of exercise, in terms of the process, the wood consistent with what, is there something to be said about general qualities of the consistency of the regimen required to get strong? Yes. So let's talk about some training principles as a whole. And this will, I think this will break down what you're wanting. The more work that we can fit into a given time, the more progress we're going to make. But that doesn't mean doing the max amount of work possible at any given time. So we know that we're always, to accomplish more, to accomplish more, we're always going to have more. And there's a certain ceiling that you're going to hit that you're not going to be able to add more. So you want to start and get the most amount of results that you can with the least amount of work, because you're going to have to do it again, like this stair step over and over, year, decade, so on. So when people, this is a big miss people got, they look at a Chico program from Russia or so on, and they go, I'm going to follow this. And it's like, that was specifically written for somebody with 20 years of experience, that's already built the capacities to be at that level. So it's all about building that work capacity. So how much work can you give in a given time? So now we want to look at some research as it relates to injuries, because injuries are going to be a big driver over time of what holds you back. So when we talk consistency, training hard for three years, five years, it's gonna be really good. But what we find is a lot of people train really hard for nine months, have to slow back for a month, get back into it, then miss another week, because and so on, they're always like this little nagging that little nagging. And so it's pretty clear in the research, we want to we're looking at when we're stair stepping this stuff, we're looking at acute and chronic loading. So some fancy words for average and like what's happening right now. So this given week would be our acute, chronic would be what is our average loading, let's say over the last six months. So the more that we can move the chronic loading up, the more work we're getting done on as a whole, over time, we're gonna get stronger. The way that we build the capacity to do that is having spikes in acute loading. Now, as we do this, the acute loading, if it spikes more than 10, maybe 15% from what the chronic loading has been, that accounts for 80% of injuries out there. So it's not actually the movement quality or this misstep or the other, me usually happens about four or five, six weeks later, it's like, oh, this nagging, and then it gets worse. And then now you got to, you got to do some rehab, your training sessions aren't as good and so on. So now we're starting to look at this, okay, it's like, I want to do the least amount of work where I can still progress. I want to be able to have spikes in my weekly demand that don't go above 10 to 15% of what I've been averaging for the last month. But every time I do a spike, my average goes up, right? Boom, boom, boom. And then that becomes very particular also when you do take planned time off. So a lot of people, training session, maybe they're doing a five week block with a deload week, or you go on vacation for a week, or any of those things that were a downward, what does that do to your average and chronic loading? It brings it down. And then what does the person want to do when they come back? Make up for it. Now they have a huge spike above, five weeks later, we're dealing with, ah, this elbow, this wrist, whatever's kind of bothering me, and now you're not performing as much. So these are some really fundamental pieces of training. And then now we can start overlaying the qualities that we're trying to develop that we were talking about earlier. So now it's, let's talk about my deadlift, my thousand pound deadlift. We'll talk about the training cycles for both the thousand deadlift and squat. So backing up a year out from the deadlift, knowing I was training at the time, heavy deadlifts once a week. And usually it was two of those sessions a month were really heavy and the others weren't. And it's like, okay, how can we get this up to where I'm deadlifting twice a week? And I'm like, well, I'm going to start deadlifting twice a week because that's where I want to be. To be able to accomplish this, I need to be loading about that much with frequency with a certain volume to be able to accomplish this goal. We're not going to go through all the math and stuff like that and how that's arrived, but there is math behind this. And so instead of just like, oh, well, let's start deadlifting twice a week. No. So we start and we take the one session a week and we split it, part of it, take part of it away and put it in the second half of the week. So the total volume is still the same. And then we start adding some volume, but I'm doing it at a, off a block so that the actual load is, the cumulative load is less because I have less range of motion. And then we start building that closer to the ground, closer to the ground, and so on. And now we start getting to where I'm almost doing two sessions, full sessions a week. And then we start adding a little bit of load. And so at my level, this isn't talking about adding another set or another day a week. We're talking like in my squat, it might be one rep instead of doing three sets of three at one week, I do two doubles or two triples, then two doubles to give me one more rep. That's it. And so we're doing that from one week to the next. And that's a cycle, training cycle. It might be five, six weeks and then so on and the next one, and slowly bringing that average load up. So the last phases of the squat, for example, we took the average loading every week. So my, of my heavy sets. So once we developed all this stuff over the last year to get to this point, now it is taking and going, okay, my average load this week is eight reps at 955 pounds. And then the next week, let's get it to nine, 957, 963. And this was pretty aggressive working up to where my average loading the final that at the final was 985 pounds average load for eight to nine reps. And that's why I said, this is the intense part. That was why it was the day of was much easier. That week over week is pretty brutal. They not sound, oh, you're just squatting. And now let's back up. Let's look at the quality development. So a year out from the squat, obviously they've been working on developing axial load capacity, my capacity to withstand load from top to bottom. So I like thinking about things in movement vectors. So this vector is an axial loaded vector is the hardest to recover from. So what's axial? So like is deadlift, are they both? They're both. Yep. So a horizontal, a front to back would be like a row or a press. Why is the axial hardest to recover from? Because it's the entire body, the entire- Entire body, just anything that is, that taxes the spinal mechanics. I don't, I could tell you my beliefs. It's studied. It is. Okay. We can just keep the discussion on that, but short like that. So we start looking at those different vectors that we're training in. So this is why this is important to understand. So I'm not just getting into nuance here. So, hey, squatting is going to make me, make me jump further because it's legs. Well, squatting is an axial load vector and jumping is a vector this way. So actually hip thrusts would help with your, and this is proven in science, with your forward jumping ability. They're both working similar muscles, the glute extension, but they're working it in those different platforms. So it's really important to understand because people don't understand. I'm building my work capacity by doing sled pushes. You're not developing your work capacity for squatting. Most movements, even ones as holistic as a squat require specialization. Yeah. You can't get strong at the squat by doing- You're going to have some carry over, right? Obviously, but because taking an untrained person that hasn't done it is still not going to do as good as somebody that's done non-specific work, but done work. So, but yes, for the most part. To get truly strong, you need to specialize. So, but not all the time. So now we talk about quality. So, and if we specialize in the same thing too long, we stagnate because the body adapts to a certain point and just can't make progress. So we wanted to save the actual squatting in the pattern with the bar that I was doing for the very end. So starting a year out, I started doing work front squatting, like a squat, axial loaded pattern, and worked on maximizing that up. Then I started shifting to doing transformer bar squat. It's this bar I developed that actually change manipulates spinal mechanics. So I started loading in these more forward positions and being able, again, so now I'm getting closer than a front squat, but not quite squatting. And then I would start adjusting that bar every training cycle to closer to a squat, toser to a squat till it finally was, right? What's the difference between a front squat and a regular back squat, in terms of the stress on the body, the mechanics? Was there something interesting to be said about, like how fundamentally different are they? So what's interesting, people think about the weight in position to them like, oh, the bar's in front of me, the bar's behind me, which is not the case. The bar is above your midfoot. The load is above your midfoot. So we're actually manipulating the spine behind the bar. So we're causing spinal uprighting behind the bar, getting in a more erect position, which is gonna change the relationship of the hip angle. It's gonna change our ability to maintain the spine. It's going to change how much the core comes in, how hard it is to maintain that sternum to diaphragm relationship that we talked about. All this stuff starts changing. So the bar stays in the same place. Bar's still behind you, but the load moves around. But we're actually manipulating the spine around the load. Yeah. That's incredible. We can tailor it to an athlete, which is great when you got a seven foot plus tall baseball player or a basketball player. That's why we work with all these teams. Anyway, so it's like you're taking something and getting closer and closer to it. At the same time, we're looking at the quality. So like I needed to be able to really hold this torso position with the weight moving up here. Now, unlike the deadlift, the ability to manage this TL position becomes much more challenging. So that was also why I was choosing the transformer bar, because it actually challenges that more in those big forward positions. I was also working on my back strength tremendously to be able to hold and maintain position. So there was a lot of like, I chose a bent over rows. So bent over row is a mixed vector. So it's a forward to back. So it wouldn't have as much carrier, but it's also got some axial loading component in it as well. So we're working on that. And then as we get closer and closer to competition, I'm developing those strengths, but now I need to start tapering those out. So all of my recovery needs can now go into the more specific that I'm actually ramping the load up. So as I'm ramping the load on the weight, I'm able to ramp it a lot faster because I'm tapering out the other stuff. So I can still keep my total load high, but now get it very, very specific. So everything that I've done has always been kind of an annual training cycle. And then again, this was like a, this was a five-year training cycle, but we just kind of walked through the last year of each and you can see how these concepts play out in reality. So in the cycling, so this is both for you, but also for more recreational strength athletes, let's say there's variety injected into this. You need variety. Yeah. Yeah. Because you will basically stagnate at some level, right? So you should, should always be kind of shifting a little bit. So three to four month blocks in general for an average, you know, just a gen pop fitness is pretty good where you're going to spend more time, maybe in a higher rep range or lower rep range, a little bit more work on endurance capacity, or maybe some more time, Hey, I'm playing around with boxing or jujitsu or something like that. Bring that a little bit more to the front forefront for awhile and bring the other out. But like mixing, mixing those variables up, but trying to keep the total load the same and always kind of like, no, do we add a little more again? It doesn't have to be major and it shouldn't be major. You don't want these big jumps. You don't go, Oh my God, let's move. Let's jump into squatting every day. You've got to build the capacity to do that. It's simple. What role would you say strength has in sports that combine skill and strength? So for me personally, maybe I'll just ask it selfishly, which is a grappling wrestling MMA. Yeah. How about I start with baseball? Please. No, I, I will. Okay. The sport, okay. Baseball and golf are two of my favorite sports. No, I don't. You don't have to be in shape at all to excel at those sports. Well, here's the thing. There we go. We're going to get this argument. Well, I've got a perfect example because this is, this is why I sell so many transformer bars into the major league baseball. So they get these people that come in, these athletes that have been baseball their whole life. It is part of the culture. And so they're great athletes. They've got all the skill. The only thing they have to do is develop a little bit more resilience so that they don't have the injury. They can push their training a little bit more that we can add a little bit more force output and be able to recover from it. So the only thing they've got to do is add some training, but there's no training culture there. So they don't have any experience, which is why they love the transformer bar because they don't have to worry about teaching the technique. We can actually set the bar on a setting that makes their squats perfect, like queuing all the stuff with actually not having to coach it. Because when you're coaching a room full of athletes, it's really hard to teach the nuance of all this and not sure that all that. But that's all that they have to do with these players with a huge level of skill. So once you reach a certain level of skill, adding strength is the only real forward path. So that's the basic simple answer to that. So one of the benefits there being like injury prevention, actually. Injury prevention, resilience, because especially fighting sports, you're going to be challenged and thrown and other things happen to you. And the more resilient you can make your structures, the better you're going to be. Even a cyclist, mountain biking, why would they need it? Why would they need to do upper body training? Take a crash, your shoulder's gone. You're done. Your career is over, unless you've done a little training. Right? So there's value in all this stuff, but the resilience is like, that's huge. And then we can overlay strength. Where we miss is this focus on strength when we haven't developed quality motor patterns first. So this is a huge thing with children, because people want to know what's the appropriate training age. I'd have had my daughter training before my son, because she developed movement patterns that are better quality earlier. There's no age, because it's going to be very dependent on the individual. There's no point in having adaptation if we don't have the right thing to adapt to yet. And that applies to general movement, but also to sport. So you're saying the skills should be developed first and then the strength applied on top of that. Yep. Maybe you can educate me, but I actually quit lifting and powerlifting for a long time after I started judo, jiu-jitsu, grappling, all this sort of combat sports, because I found that it was preventing me from relaxing my body enough to load in the skill. So this isn't a problem with the training. This is a problem with you. Yeah. This is a theme here. So this is actually really, really important. The first product I ever released was a loadable mace, a swinging mace. And because every powerlifter and body, well, not every, but most serious powerlifters and bodybuilders, shoulders mobility is pretty limited. And most of them really, really struggle with this. The problem is they've been taught to have tension all the time. And that's not good. So when we talk about the joint positions that we were talking about earlier and having those and the muscles in the right length and tension relationship, athleticism is the speed to relaxation because the counter is speed to contraction. Float like a butterfly, sting like a bee. And so what a mace can do is use that, because this ties back into developmental kinesiology, because a lot of reset patterns are getting back into these basic movements, but it's as much about relaxation as it is contraction. So a mace, we have this weight on a big long lever. So if I grab a kettlebell, and this will be like, that's the same movement as a kettlebell halo. It is the same movement as a kettlebell. But here in the halo, I'm on the whole time. With the mace at the proper length with the right distribution, you cannot do the movement. You could not move, force your way through it. The only way that you can accomplish that is by relaxing. And then now we can contract all the muscles related around that shoulder girdle all at once. We're working on off, on off, on off with moving and contracting. And now, so what happens a lot of times as this stiffness and tightness happens, if we're in poor positions, we start using stabilizer muscles to do the movement. And then that's where this stiffness come from. So it means that in some of whatever training that you're doing, there's a deficit in the movement quality. Okay. Or there's a deficit in the training program and you're not recovering from. And 80% of the time, that's the right answer, right? But yeah, that's where the gap is and learning how to relax. And the way a lot of the exercises are taught and have been taught for a long time, which is why there's a big gap. And this is why both clinical rehab and all these other components are mixed in my philosophy and what I'm trying to do with Kabuki strength, because I'm looking at holistic movement. I'm not looking at power lifting base movements are what I want to load and be able to assess on, but this affects all sports, all activities and strength doesn't have to be that. I mean, I I'm freaking a thousand pound squatter and deadlifter. If you, if you watch any of my videos where I do like complete quad fall backs, I don't stretch at all. I can usually get close to a full split. Like if I want to. What? No, I did not see those videos. Okay. That's hard to believe. Wow. Okay. Well, actually I do. I just did one recently, a quad fall back with my, with my mace loaded way out to the end, torsioning on both ends of the other. And like, I do a lot of, I do a lot of weird stuff. That's awesome. Okay. Squatting doesn't make your hips tight. Squatting like shit makes your hips tight. And so, but there is no perfect world. We're always, our training program isn't quite perfect. Our movement isn't necessarily perfect. Like, so you're going to have the needs for this stuff. But if you're always have to do some soft tissue work to loosen up the same one for that exercise, to be able to get a joint in position, there is a problem. And I'm not saying don't do it, do it because I don't want you to have a joint. Like if I can't get my shoulders in a position, I can't do overhead presses because I'm going to compromise my spine position. Then I'm going to end up with some other problems, right? So go ahead and clean that up so you can get in position, but go figure out why it is and fix it. And then maybe next, you know, three, four months from now, they're going to get a little something else going on. Fix it, but understand the deeper root reason of why. So I don't know. I believe I am the only company manufacturing and selling, you know, fascial soft tissue tools. And I'll tell you, I don't want you to use them. Because it's not helping you get to the why, why it was caused in the first place. Yeah. The goal, the goal, the perfect state is not having to use them. Reality is you're going to have to use them from time to time because the world's not perfect. Yeah. So your discovery is 100% on point. Well, there's another side to combat sports. When you're beginning a particular combat sport, strength can be a negative because human psychology, because you can get away with a lot when you're strong. Uh-huh. Yes, you can. So if your mind is strong enough to where you can just turn off that advantage and be a beginner, truly, in a particular art, that's probably the best way to do it. But you can get away and then you don't learn. Yeah. Yeah. It's hard. It's hard to get away from that. Yeah. It's hard. It's hard not to use the little advantages you have because like jiu-jitsu is a big hit on the ego for, you know, especially guys, you know, when like a smaller person just destroys you, dominates you, when you can, I don't know, deadlift whatever number of pounds. And it's hard not to use that strength to then resist the, slow the ultimate destruction by like 120 pounds. And that's why I recommend developing the skill quality first, but it doesn't mean that you can't. You can't. That's right. You can still do it. So don't take it as a like, oh, I can't go that direction. That's fine. But understand those things. And then also understand that jiu-jitsu is additional load on the body. So you have to, you can't just add it on top. Yeah. You've got to taper back the other, you're going to have to make a, I'm sorry, you may not want to hear it, but you're not going to be able to do as much and add that here. Yeah. It's a compromise because your total volume still has to be there. And there's not, unfortunately not really a way to measure what the jiu-jitsu volume is with this. So you've got to take a look at that. And that's where like measuring like heart rate variability or other stuff can be useful. So you can see what is happening for me from a sympathetic versus parasympathetic nervous system standpoint. Yeah. Making sure your body recovers efficiently and trying to put numbers to it. Yeah. You mentioned Kabuki Strength. You run the Kabuki Strength Lab, previously called the Elite Performance Center in Oregon. You called it the perfect gym. What makes for the perfect strength training gym? I don't know where I called it the perfect gym. In a video somewhere I watched. Oh man. I mean, that's where my testing grounds for developing all this stuff was through the years. And so this is, like I said, I started developing relationships with the best developmental kinesiologist in the US, the best, arguably the best or most well-known physical therapist in the world, the best spine biomechanist in the world. I started doing continuing education with these clinical courses and learning this stuff and going, but how does it work in my world? Right. And then I started lecturing with them and all this other stuff. But the lab was like, where do we test this stuff? And so let me get to a point. There's three things. There's always three things. So to be a success, to achieve success, I believe there's three things that really, really come into place. And it's the right methodology, the right tools, and the right environment. And so it was all about building that. And so the methodologies came from a lot of that different, that gray area, interaction of clinical with sports science. And then the tools I had to start creating and designing. And then the environment is having this focused environment of people that want to do better and push each other and having community and culture. I end up building these connections, this network. Everything that I'm doing with my businesses is trying to create that into a scalable fashion. And so I'm building the groundwork because to have a system that like, yeah, I had clinicals on site that knew exactly what we were doing. And when it's me and a few people in a small team and all this stuff, we're all just like easy to manage. And you can see these, there's other models around this. So I've been other areas since maybe whenever it was, I filmed that video that said that, that they have that same model. And it's taken probably about a decade usually to develop that. And having the right people in this community, they can create this network and the tool and all this stuff. Except they still don't have the best tools because Kabuki strength didn't exist. And so out of that was, is essentially I started building this business and people like, when did you know how all this stuff was connected? And I'm like, I don't know. I didn't, I just started creating on the outset, the things that worked until finally, I'm like, Oh, I'm recreating a scalable version of this stuff. Here's the methodologies and a coaching platform that we can manage clients around the globe and see what's working and not based on the scientific principles of training, right? How do we create that into a database that now we can train new coaches and they can use those same metrics and tools to create programs that are tailored to fit person's individual needs, right? Now, how do we integrate that with assessment and clinical care assessment and all these other pieces? So there's a lot of work in that. And so that's where Kabuki strength is the Genesis, but we have, we call our gym, the Kabuki strength lab. Literally people find about our gym in the neighborhood and they're like, how long have you been here? Why, why do I not know about this? We don't advertise our gym at all. They're like, that makes no sense. Well, that's because the only reason is to have a testing environment for the tools and methodology and having enough people to have the culture and fit and to be able to be part of the experiment. Mm-hmm. What about the environment of the, the feel of it? The actual gym? There's a, I don't know, a grunginess to it. I've recently became a member of planet fitness for reasons that have to do more with the heat in Austin that sometimes I need to put in time on the treadmill. I don't like that. I don't have any judgment on this. I don't. The best gyms I've been in are kind of dirty. You walk in and you know that work is to be done. Yes. There's not another reason to do there. It is, the environment is tight. There's a big piece of that. I know it's studied sociologically, I believe. I just, I just bitched that word too. But the intensity, when you start growing a space, the intensity drops. And so I, I had that experience when we grew, we went from a 4,000 foot to a 9,000 square foot gym at one time. And everybody's like, it doesn't feel the same. Like if people are complaining for years, we've shrunk it back down. Well, we're down to 3,500 square feet and it creates that tension. And it's not a 5,000 square feet. It's down to 3,500 square feet. And it creates that intensity. It creates the closest, the connection with the people around you. And then, like I said, the grunginess, like you go in, you know, the intention when you walk in, that environment creates that tension. But when I speak environment, it's not just the, it's not the physical, it's the people. But you know, when the gym is a little bit beat up. Yes. It also tells a story, like history to it. You could tell that not only is there work to be done, that work has been done here. Yes. Like battles have been fought. There's something to that where you're just in a long line of people, you know, that fought and won. And we could get into a whole nother space. So there'd be a whole nother topic, but that existing energy of a space. I mean, we mentioned offline, Joe Rogan, he talks about the same with comedy clubs. There's certain, there's certain clubs that just have a history. There's an energy there. You can get all woo woo, but you know, there is there. It's a real thing, I think. You walk in and you can feel it. And you feel it. You feel it. Yeah. That makes me feel that somehow all of us humans are connected in ways that's hard to describe, even the ones who are no longer here. Just the greatness that once was is still in the walls, in the space present there. And we somehow can plug into that energy. Yeah. We can go down a path there. There's something really powerful there. You've also mentioned a bunch of cool equipment that you've developed as part of Kabuki Strength. Probably a little bit of that has to do with your engineering education, but also just generally with the spirit of the innovator that you are. What are some cool, maybe revolutionary pieces of equipment that you're particularly proud of, or just you've been obsessed with recently? Love to talk about that. So we've got some wild, crazy stuff that just came out and is coming out too. So everything that we create and release at Kabuki Strength, the industry hasn't seen before. There's stuff that's basic foundational that's been around forever because it works, but there's always more. It could be better. And why are we not looking at these things, these foundational things? So when people are coming up with novel things, they end up being way different outside the perspective. And I'm coming up with things that are way different, that are plays on what we already know works. So we talked about the transform bar, the only bar in the world. We can manipulate spinal mechanics. So everything for me from a design concept that we develop is all about creating products that can rapidly accommodate to the variability of an individual's leverages, mobility, and training needs. And that's going to also create and distill down the size and scope of space that we need, which is going to continue to be an ongoing thing. Check out my Instagram after this and you'll see, I put an entire gym on the bed of my truck and went on vacation last week, drove to the desert. And by entire gym, I mean squat rack, full complement of our specialty bars, a horizontal and vertical pulley system, handheld weights, shoulder, like a complete an entire gym in product that took up the space, the size of this bed right here. That's incredible. Because of the design scope of what we have. So the cool thing is that we're not just talking about the design scope of what we have. So the cool thing is that there's two other bars that fit our biomechanically sound barbell lines. We talked about the transformer bar. The other two are built on this thing I called playground physics. So we have these bars with handles that are off parallel with the axis. So they've been around the market for a long time. One is a hex bar or a trap bar. Another one is a pressing bar with the handles turned as well. And both of them suck. They're horrible. Anytime any lifter knows if you pick it up, it's going to break your wrist and crush into your face. And it just doesn't feel good pressing, but it alleviates the strain on the wrist. So people use it for that reason. And the trap bar, same thing. It's always diving forward in your hand. So it's kind of limited. It's also limited in use because you could do a lot more with it. So these bars are really cool. Playground physics. So as soon as the center of rotation is on the same axis as the center of mass and the handle is off center, you have a teeter totter. So a teeter totter has a balance point, but it's infinitely perfect. So technically you can never find it. So it's always going to be sitting on one side or the other in a playground. And that's what these bars are designed. So you got instability right here. You can't find the center. The bar is always trying to tip in your hands on the trap bar. So you can't do carries with it because you're doing for momentum and it wants to dip on you. The Swiss bar wants to crush your face. Well, what do we do? We just make a swing. Put center of mass below center of rotation. And what does it do? Oh, it always finds center. So the handles on our pressing bar, it's arced so that the handles are above center of rotation. And then every angle, instead of just being a certain fixed angles, each angle is based on the width, the average width of an individual. So the internal and external rotational bias is based of the shoulder is based on the width, leaving just a little bit left because we talked about the lap being a stabilizer. You still need to have a little bit of cue of external rotation to engage that as a stabilizer. Boom. Now, all of a sudden you have a bar and I kid you not, this is a great story. Major league baseball, when I presented it, every head strength coach for a major league baseball team, maybe not every, but damn near most of them have bad shoulders. They can't press, they've got shoulder surgeries, so on. And so we're showing, they love all our stuff. And I'm like, Hey, I've got this cool prototype I want to show you. It's a pressing bar. And they're like, Oh, you know, major league baseball is a little hesitant on pressing because the dangers for the shoulder. And I can't, I haven't been able to take a bar to my chest. I mean, I really love to, it's been five years since I've been able to XX train and I'm like, just try it. Like I can't even get a bar to my chest without pain. Like, just try it. That feels good. Now the arc makes it actually three inches deeper. So people are automatically scared. I can't do that. Cause that's an extra range of motion. Right? Like, Oh, put a plate on there. They're doing it by that time. The staff's like, they're all standing around. You see like, what's going on? Put two plates on. You see the, just like, he gets up. How do you feel? Like, I feel fine. No pain at all. I did this with five teams with five of the happening repeatedly five times and that they, and every one of them worked up to two plates and did reps varied with zero pain to a three inch range or greater range of motion. Cause what did we do? We stacked all the joints and we provided stability at the end that we balanced internal and external rotation. I mean, just basic playground physics and it changed the game. Now we get a greater range of motion with a greater training effect with the negative stresses removed. Our trap bar opened up one side, which there was already something like that out there created. It pops up so you can pick up, take the weights on and off. It's got a built in Jack and then created the high handle position, which already did. Everybody uses the high handle on a trap bar. They just don't know why they like it. The handle that's on center. We offset just a little bit, not enough to make a difference on the range of motion lift or even notice visibly, but it still has the same effect. So both handles now have that. We added the option of different handle sizes based on whatever your needs are, even a one that rolls to develop a grip and then different widths that you could choose from based on whether you're training a teen athlete or a seven foot six NBA player or a NFL lineman so that we can accommodate for all these differences. And so, and then now it becomes the most functional all around bar around because now you can do carries with it. You can do split squats with it. You could do curls with it because it goes around the body. You can do overhead presses because you don't have a thing that gets in your way and you can flip it up into position. You can do bent over rows and not run into your shins. You can do seal rows off of a bench. You can do ab rollouts. You could, should I go on? Yeah. So you could use it as like the main bar. The best multi-purpose bar around. You got a home gym, one bar. Like how do you develop totally new equipment like this? I scratch it on paper. Maybe, maybe weld some cut up and weld up a prototype. But usually I just hand the scratched up paper to my engineering manager. And that's what he says his job is to distill my chicken scratch into something real. And then that team picks it up. But in the old days, starting out, I just walk out. I just walk out and do it. I, you talk about engineering. I'm actually more, I work more of an artist fashion. It's in my head. And I just go create with no plans. And so they have to pick that up and actually do the engineering and testing and all that. And then we got two other products came out this year. Freaking wild. They're, are you familiar with training with a flywheel? No, no, it's a flywheel. Maybe a flywheel is a spinning object that creates an inertial mass and then it reverses direction. So whatever you put into it and there's ones out there. But ours is the first patent pending. That's all, everything all in one unit. So it's a floor-based as well as a horizontal. So you can basically do any pulley movement in the world. And now everything that you put into it on a concentric force, it whips right back as a, as a centric load. Gotcha. So there's an accelerating whipping motion. It just, yeah, basically. Yeah. I mean, okay. I have to, I'm, I have trouble imagining exactly many of the things you're describing, I suppose have to be experienced, right? Yes. Because there's a magic. And there's a lot of research they've been around. They're adopted more heavily in Europe, quite heavily in Europe, but not as much in the U S because they sell them as a be all end all tool, which they're not. They're crazy for what they do, but it's not the, it's another tool. And so we have a very high quality unit now that is half the cost of everybody else's because the innovation of a movable mount point that you, for them, you have to have two pieces of equipment. We have one. So and then a few other things, better platform to be able to do things and that we can do what we call app off platform work, which allows us to do movements like punches and standups, things like that. And then I've got a handheld weight coming out next month that we can actually play with. So I'm varying the load with it, never leaving your hand by changing the leverage point. And so what are we, what exercises we're talking about here? Anything that would be a dumbbell or a kettlebell movement. So it functions, it does the function of a kettlebell, a dumbbell, and what we call a center mass bell, as well as provides variable loading within a range. So how can you change, like, how can you change the load? Because load, well, we don't actually change the load. We change the torque on the, on the joint that we're working, which is the same. That's actually what is creating the force, right? So if I'm doing a front raise, it's where this, this downward forces times the distance away, right? Which also then makes it no force when I've got at the bottom of the front ways, which is why it's so easy with this. It's like a kettlebell. It's offset, except it has three different handles. But it's offset just at a kettlebell. You can't do it because the offset so far, it becomes a wrist movement. So ours has three different sizes and the offset just enough so that you can pick, if I put it in the front race position or curl position, I could put it in outward position and the force is almost what it is at the, at the top. But then I get to the top and it's the same exact or the curl. So I can actually change the force curve in the movement. And then I can just release the pressure a little bit and let it swing into position and keep doing a drop set with never letting it go. Yeah. So it's got a really nice texture grip that allows you to hold it in different positions. And then the load offset is just enough that it doesn't overpower the wrist. And then you've got different hand sizes so that you can maximize this relationship and hit whatever joint that you're applying. So it sounds incredible. It's really freaking awesome because you can, because the variable load now I could go straight from front raises to side raises or rear or curl because without like, because I don't have to put it down. So now my time under tension goes through the roof. And by the way, same effect with a flywheel trainer, because the variable, whatever you put into it is what it kicks back. So you have an constant time under tension because there's no rest points either. So all this stuff is working on maximizing time under tension, which anyway, it's cool stuff. Anyway, I get excited. Well, let me ask you about another thing you've already mentioned, but I find this really interesting, which is barefoot running and your sort of company, Barefoot Athletics. Yeah. BEAR. And the tagline is optimizing the human to ground interface. We've talked about this a little bit with the powerlifting. How do you think about the foot ground interface? It's interesting that we know that we should be able to train all these parts of our body to be able to be stronger, be more resilient, like, but we think that the foot is different, that we need to package it and modify it. And somehow that that's the science of making it healthy where I challenge people. Think about that. Like first thing you do in the morning is roll out of bed and put your weightlifting belt on and wrap it on tight and wear it till you go to bed at night. Do it with your shoulders, your knees, put it, wake up and put some knee wraps on. Okay. And elbow wraps and see what happens. One, you'll get weaker. You'll lose movement capacity and you'll start affecting other areas of the body very negatively because they will start picking up the compensation for those joints that are not moving properly. This is it. What shoes are for is to protect you from the environment, from cuts and abrasions and heat and things like that. But the foot, all I mean, the mind blowing is like every other area of the body, you need to use it and you need to strengthen it and you need to learn to control it. That's it. That's all I have to say about the subject. Okay. It's that simple, but somehow we have been sold entire industries like the orthotics industry. It's completely false. Meta analysis of the data shows that orthotics do nothing beyond temporary relief from pain over a six, eight week period of time and provide no long-term benefit. And I can't tell you how many people I've eliminated back or knee or hip pain from working on strengthening and controlling the foot and ankle complex. We believe we've villainized and said a low arch is a condition that needs fixed. Like when it really is just controlling the foot and ankle complex and how they relate to each other and how we use that. Is it like go put on boxing gloves in the morning and do that for the next 20 years and see what happens. It's not about finding the right shoe that fits because your foot has been deformed. And so I'm not like some wacky, like, oh, you got to be barefoot forever. Do this. Like, no, I'm just saying go spend some time using it, strengthen it, learn to control it. And you'll work better in a shoe, but the whole running shoe movement with the raised heel, that was the person that suggested that to Nike way back when they were trying to figure out what to do, the reason. And he says it's the worst thing that he ever did because we were coming from an era of people wearing heeled shoes, which by the way came from stirrups way back in the day. That's where the whole heel came from. And so he's like, well, I'm going to do a heeled shoe. That's where the whole heel came from is to go into stirrup. But then it went into fashion. And then the running craze started coming around in the seventies. They're, they're starting to push this, the general mass population. And they realized that they were causing injuries and like, what are we going to do? Well, that's because everybody was in this position and had a shortened, shortened calf muscle. And it's like, well, the workaround, let's just put a heel on it. So we don't injure them. That's it. And now because the raised heel, you got to raise the toe. And then now with that, if you go stand on something and pull your inner toe in and in a squat position, just reach down and do it, you'll see that you have no control over internal and external rotation of your, of your leg. You don't. And, or your foot. And you actually have to put a support in for the arch to be able to passively control those structures. It's just bandaid on top of bandaid on top of bandaid. Use it, strengthen it. If you want to wear some shoes, cause they look good or fancy. I'm like, I have no problem. I mean, I go out on a wife. My wife will put on some high heels every now and again. But all I'm saying is use your foot. My thousand pound squat, my thousand pound deadlift were done barefoot. I'm not trying to sell you shoes. Go do it with no shoe. That's what I've been promoting. I did that for six years and I promoted it. But people ask me like, well, what do I do? Because my gym requires shoes. Okay. What do I go? And, uh, and then I go, well, you know, you could pick up these other finger shoes or whatever. And they go, man, my wife won't have sex with me. And I go, I know mine either. Like, trust me, I'm not making this up. Everybody in that market markets to one segment and they're still missing some gaps because they, they still have a little bit too narrow of a toe box. And if you're lifting, you have the opportunity to really get that splay and start working on this stuff better. So, um, I just wanted to create a shoe that create a shoe. These ones are odd colored because it's a partnership with Kabuki. Normally we've got a black or a gray, a low top, high top sticks to the ground for lifting. So we can do that. And very pliable. It's a moccasin. It's a modern day box. But looks okay that you can wear it around in other areas. If you, if you so choose, like, you know what the number one healthcare cost in America is? Diabetes, heart disease, cancer, low back pain. Hmm. Now, what do you attribute low back pain to? Well, it's attributed to a lot of things, but inability to control spinal position, which starts happening from some breathing issues. It also happens from the foot. So there's a lot of stuff, but everything that I do actually focus on improving this. Yeah. And it all starts with the feet. This is one thing, like this doesn't affect breathing, but, um, so it does actually affect breathing to some extent and spinal stabilization. So the raised heel and toe will make you stride further, because of just how it operates. But that overstride is a result of opening this. So we open the pelvis and diaphragm. Did we talk about that and the impact that that has for controlling and spine? Yeah, I think we touched on that. But it's all this stuff plays together. So the gait affects that. And so the shoe affects the gait. And then so it's all connected. All connected. Let me be very purposeful with some conversation here, though. We've talked about periodization. This was a big gap. So people go, yeah, well, when people started running with those, they started having injuries back when the finger company produced those and didn't do the education around this very simple concept. You do not walk into the gym if you haven't squatted and start squatting 225 from for max rex every week day or every day over day. And that's what people did because they weren't told that you need to build the capacity to do this. You go wear these and walk around in your office or wherever all day long, your feet are going to hurt. They're going to be sore. Do it for 10% of your time. Do that for a month, then add some. That will build the capacity to do this. And then that's going to start having the ability to strengthen, manage the foot. And there's a whole lot of other stuff. I've got videos on things that you can do. Buy whatever you want or just spend some time out of them. Like that's all that I want people to do because it is so simple and it has such a profound impact. Yeah, it does. What I did- I noticed when I walked in. I was like, oh, hey, you're spending some time without shoes on. Well, what I did, I think it's already now two years ago when I was doing a lot of running, I do like a 10 mile run. I would take my shoes off for the last like half mile and I run like that. And that was for me really helpful to ensure that I have proper form. Form that minimizes pain on the way I run. I still like shoes. I benefit a lot from shoes, the protection they provide, but it's for running we're referring to, especially trail running and so on. And in the city when there's glass and all those kinds of things, but it's really important to have minimal sort of protection on your feet. For me, at least it was to figure out the ways that my form basic movement and like the positioning in the foot, the impact of the foot and everything, you know, the lower leg, the entirety of the torso really, how it's improperly positioned in terms for the objective of minimizing pain. And the barefoot running really helped fix that for me. Because I figured out that I need to take shorter steps, more frequent, you know, all those kinds of things. And that really helps you figure that out. Like, let's be realist about stuff, like, spend some time using it, strengthen it. And I've got some great ways to do that and learn how to do that. So yeah. What is a good diet for strength development? I've just to give you some context, I've been eating mostly meat, not for strength, mostly for mental performance. I just enjoy it. I just enjoy it. Yes, you need to have a base level of protein building blocks for tissue, right? We need to have enough fats to be able to have hormones work and key processes in the body. We need to have, well, you don't need to have from a performance aspect carbohydrates necessarily, because the other ones can convert into injury sources. But for a performance athlete, carbohydrates can be very beneficial as well. So I look at it as you need a base level fats, you need a base level of proteins, and then you adjust the carbohydrate intake based on the needs. I'm not anti-carbohydrate by any means. Because a lot of people, well, they look at me now when they see like how lean I am, and they jump to a conclusion, you must be keto, you must be carnivore, you must be whatever. And it's like, so losing and gaining weight is simply eating less or eating more. I mean, it's, and we get so complicated. Oh, that my fat, like, what's your fasting window? If I'm doing fasting, it's just because it works with my environment. Sometimes I do it, sometimes I don't. All that does is control how much calories that you take. Big success with keto and carnivore diets. It's hard to eat a lot and put on weight with those diets. Protein actually has a thermogenic effect. And so you have to have a massive amount of fats if you have a only meat diet, because you can literally starve to death. There's a show where they put people out in the wilderness. And this guy, the one that won, one of the ones I looked at, they threw him way like up in the, up past the way out there, there was nothing, but he somehow got a caribou and killed it. And he still lost a pound a day for 30 days with a caribou because his fat was stolen by a, and he could eat all the meat he wanted. And then he almost got pulled because his weight loss. But that isn't actually a performance. So those type of keto and carnivore are not performance diets. So they're not going to be as effective at supplying the energy needs for high capacity training. So don't get me wrong. You can do training, but like you can be a successful, like elite athlete with a, with a vegan diet, but it's not as easy to do it with other diets. So, and you're missing some base nutrients, so many nutrients and meat. I believe having greens in your diet is really beneficial, lots of research, but there's people in the other worlds that argue that you don't need them, but they help clear organs, provide micronutrients, all this sort of stuff. So I eat simply a whole well-rounded diet and I've gone from, I can go from 285 pounds squatting a ton of weight to eating less and dropping all the way down to, you know, seven, 8% body fat with veins standing out everywhere without a tissue on me, just with amazing, great tasting food. To lose weight or be healthy does not mean that you need to eat flavorless, bland food. So that's the main thing I try to get across. It's eat less to lose weight, eat more to gain weight. Yep. Make sure that you've got enough protein, make sure that you've got your micronutrients covered, which is going to cover by eating real food. Don't go low fat, no fat. If you want a performance, don't go no carb, but if it works, any of those things. So diet approach, when you look at diets, understand that they're, how aggressive they are. So like keto can make you lose a lot of weight. Carnivore can make you lose a lot of weight. A lot of that upfront is actually dropping glycogen stores. So you're actually just reducing water in your muscle and fat tissue. So, which is why it doesn't, isn't as great for a performance diet, but understand that every diet also has a level of discipline and does it fit your lifestyle? So I suggest people don't find a diet. You need to find a lifestyle because that's what's sustainable. I hate the word diet to begin with. What behaviors are sustainable and then do that. And then over time, the things you'll get to where you need to get. Diet itself, just by the name of it is not sustainable because it is a short-term thing to get somewhere. Yeah. I tend to try to measure it because I definitely have a love-hate relationship with food. I tend to look back and say like, by following this particular protocol, lifestyle, whatever, what was the level of happiness? Yes. So not like weight loss or weight gain, all those kinds of things. It's the entirety of the picture. Productivity, just feeling good throughout the day. Socially also, like interacting with people because so much of a human connection, like I mentioned before, is over food. And if you're going to limit yourself in that regard, you're limiting a certain fundamental aspect of life. A number of years ago, I did like 20 to 22 hour fasts every day. And I'm like, well, this doesn't work. I can't do business lunches and stuff like that. So when I was in my fasting thing, I went to a 16 so I could have a light lunch just for the social aspect of it and perform that. And then that's why I like the typical bodybuilding, like the eight meal a day diet has never worked for me because I've always been a very bit like trying to fit that between meetings and other stuff. What that diet provides is that just you get less bloat and distention of a larger meal. But at the end of the day, you get the same exact results. Pick a lifestyle, live that. You can have really great tasting food. And that to me is the same thing. And this is why I'm like really hitting this point because also with the dieting and like the approach like, oh, I'm going to do this. And people pick these chicken and broccoli recipes and guess what? You're going to break. If you do not enjoy it, you will break. So it is a very important point. Well, I also slightly push back or maybe to elaborate, if you don't enjoy moderation, for me particularly, I have trouble moderating certain things, most foods, I would say. So my source of happiness comes with foods, even if they're bland, the ones that can enjoy, but enjoy moderation. So there's, I mean, I enjoy every piece of food. So it's like, if you can enjoy the full lifestyle, it's not just the particular experience, but like the full journey. Yep. Does it fit your lifestyle? Yeah. Yep. So let me ask about a complicated topic that's sometimes a bit controversial, which is steroids and maybe TRT, testosterone replacement therapy. What role does that play in strength training? All right. We're going to go there. Yeah. But it's an important discussion to have. I think that it's something that I can be more transparent on. In my past, I wasn't able to due to the career that I had. So just like covering that stuff in a public forum, when you're highly looked at being an executive for recruiting and other stuff, it was an area I had to just kind of pass on, right? Now, I've used steroids. I've used them since I was 33. And I basically just use TRT now after my big squat. So for 10 years, I used them. And there's some interesting components to this. So one is just the gray area of what we call performance enhancing supplements. So performance, was it PEDs? That the line of what defines a PED is ever shifting. And it's shifting based on society norms, cultural norms, government bodying agencies, all these sorts of stuff. So I'm not making excuses here. So I just want to elaborate before I actually start digging into the details here. Because performance enhancing, I could take sodium bicarbonate and enhance my ability to perform deadlifts for reps. Guess what? I did that for my Guinness World Record for deadlifts in a minute. Okay? People do it for rowing or other, they use high capacity type stuff. It is performance enhancing. It is a chemical. It is baking soda. All right? They're not able to make it illegal because everybody eats bread. Well, not everyone. And so it's a little hard to test for. No matter what you do at any level. So that's an extreme example. But other examples, you're drinking an energy drink in that cup there a little while ago. And in America, you can get an energy drink with 240 milligrams of caffeine in it. In Canada, that's too dangerous. You can only get 140, but you can go buy a Fedra. And a Fedra is illegal in America. And so these things bounce back and forth all the time. I could take Yohembi and in Europe or Australia, it is a drug and classified. And in America, it is not. It's an herbal root. And a lot, I actually haven't won one of my supplements except for the overseas version. Anyway, the point I'm getting is no matter what you do at some point, there's by some point, no matter what you do at some point, there's by someone's standards, you are cheating. And because it is, you're taking something that, but you could work around these things with nutritional ways or other ways versus taking a chemical. And there's whole lots of ways to do this, but it's like, oh no, it's steroids. It's not. It's injectable. It's not. Well, somewhere there's a culture or a person that will say you're cheating no matter what. So it's a self-defined, you need to define it for yourself unless you're competing in an organization that has testing, then it's a straight ethical thing. And it's either right or wrong, in my opinion. That's kind of the overall dilemma of it is if you want to see what you're totally capable of, you have to decide yourself what's okay or not to that level. There is no body that can say something yes or no. Yeah. When there's an event like the Olympics, maybe then you have a standard that you're all trying to adhere to. And then it makes sense to keep a certain, like to be within, there's an ethical imperative. So yeah, I'm not talking about that. I'm agreeing to compete in this by these rules. Yeah. But when you're trying to maximize your own performance, whatever that journey is, whatever that goal is, that's a different story. And it's not easy to figure that out. You go, oh, you're just like dancing around the subject, whatever. Well, guess what? I've got a prescription for growth hormone and testosterone. It's legal for me to take. And you know what? A lot of the people that are in front of the camera in the media, politicians and news people, and the people that are there saying the no-drug stuff, they're going to anti-aging clinics to look better, and they have a prescription for growth hormone and testosterone themselves. But in their eyes, it's okay. It is a prescription from their doctor because they have the money to do it. So it's legal and it's fine. If I, it's interesting in Oregon, anybody, and I don't know what other states, over the age of 16 can, without parents' permission, by the way, walk into a gender clinic as a female and get a prescription for testosterone. But as an athlete, if I've got low testosterone, I'm so low, I've got depression, I can't have sex with my wife, it's affecting my quality of life, I will have to fight tooth and nail to get testosterone just as a prescription, and then I will get kicked out of my organization for competing. Like, so you understand how gray this stuff gets? Do you think the stigma on testosterone is the reason we're not having a healthy conversation about when it's proper? Like, what are the proper uses of testosterone in an athlete's life and just the regular human life? Yeah, absolutely. And it's just, it's like anything. It's like I said, it is lines that we pick and draw. Anytime you put that out there, people are going to have different opinions where those lines are. So now when it comes to strength, here's an interesting thing. In powerlifting, there's tested federations and non-tested federations. So we can literally look at the statistical data and actually find out what do steroids do. And so it's pretty clear that steroids provide about a 10% increase in strength on average over not. Now, that does take out the fact that steroids will put you in, allow you to put on more mass, so you'll go up a weight class a lot of times. So as a whole, you could definitely lift more probably than the 10% over time. And then we think about steroids as the ability to just put on muscle. And here's where things get a little interesting, even with people that use steroids, is not understanding the neurological impacts that steroids have. Because you could take some steroids right now and be stronger in 10 minutes. That's clearly not done anything from a physiology standpoint to make you stronger, but we have tapped in neurologically to elicit those gains. And there's a whole lot that happens neurologically. Like how much science is there in terms of all the different ways you could take steroids, which kinds of steroids, the timing, the dose, all of those things to develop the neurological, the physical, the skeletal, like all the... You've talked with such depth about the science of strength building in terms of form, in terms of the equipment that you use. It seems like a component, the use of steroids should be an equal level of scientific rigor when applying them. It is. Now, the research is harder to get because of what it is. But there is a lot of research that was done when they were legal. So they were legal up in through, I think, the mid 80s. And so a lot of the classical high benefit to low risk steroids were studied. And then since then, there's a lot of designer steroids or new steroids that have come up that don't have a lot of research around safety and risk and things of that nature. And we can't do that because of the legality around these things. But some of the stuff on the neurological function is really just understanding how that chemical structure works and what it's doing to the neurotransmitters, what it's doing. And so some of it is really talking to people that have experience with it. And the other is understanding those structures and what they do. The neurological component, I think, is more interesting than most because most steroids act through increasing muscle protein synthesis. That's how you add more muscle is they have an anti-catabolic effect and they have a muscle protein synthesis enhancing effect. So it reduces the amount of muscle that you waste and increases the amount of muscle that you put on. But the neurological component is tremendously valuable for what it can do for your training workout. Like if I handle more load over time, I'm going to make more progress. If I can actually just stimulate more neurological effects for a specific event, it's going to have an impact. But there's other ways that you can tap into this too. Things that you can tap into mentally with great practice with meditation and other stuff that will have the same effect. People probably think I'm over speaking, especially steroid users that are listening to this. Well, at least I'm talking out my ass, but I'm not. Because I have experience with this stuff on both ends. And some of those areas, a lot of people don't have the experience with that. What I've kind of heard from people is the confidence that comes with steroids. It feels like, not to call it placebo, but it seems like the psychological benefits of steroids is huge. And that you feel like there's a confidence that seems to be coupled with the actual biological and chemical effects. I have actually a neurological condition. So I actually don't feel a lot of that stuff that people, because there's certain steroids that like people will like, your like very extreme ones, like that would make somebody bite someone's ear off in a fight, for example. Almost like aggression. And they literally do nothing. I'm like, always just chilling. I don't like have an effect. That's great. But neurologically, they're still having those effects, but I don't get those feels that other people have from those. But yes, there's that immediate boost in aggression and a confidence and stuff that come with a lot of those ones that deal on the neurological. Overall, a good sense of well-being, just like from being on testosterone, like it's going to affect your mood. And it's interesting. So testosterone replacement therapy, if we walk down that path now and kind of switch gears, we find that men today have declining testosterone over what has historically been in the past. So right now, I think a 35-year-old testosterone is shown to be about half what it was just 50 years ago. So I don't know if we could argue the point. We don't really have the science to validate any of it, but it could be society as far as the impact that it's having on the mental health. For men, it could be the estrogens floating around in the water from all the chemicals and birth control and all this sort of stuff. Could be a lot of things. But it is a fact that average testosterone is significantly lower. And that is going to end up affecting life, quality of life, as well as your longevity, because it will affect those things. But on the other end, steroids and TRT, particularly steroids, come with a lot of negative health benefits. Not benefits, a lot of negative health ramifications. And so if I knew what I know now, I don't know that I would have gone that path. I didn't until I was 33, which is kind of an outlier for a strength athlete. I was a four times body weight deadlifter, 800 plus pounds at 198. It was pretty dang strong before I went down that path. And that's because I wanted to see what I was capable of. But I was reaching a point that it was either I need to do that or not. My testosterone, my natural testosterone levels were actually I think below 300 is actually the threshold. So I was being told to go on TRT for the last couple of years, probably just because I was pushing so hard. And the stress level was driving my test down. So it was self-imposed, more than likely. But I put it off because I wanted to set all the drug-free records. And I set the ones that I wanted. And then it was 33, I'm entering the age category. And I'm like, I'm going to go on TRT. I did not feel like I should be with TRT. Personally, my ethical standard was I shouldn't be competing in tested events anymore. There are federations that will allow you with your, you show up with your script and you do your test and you're below a certain level, but you're still on. But for me, I'm like, that's not okay. So I'm like, I may as well at this point, use steroids. But since then, understanding all those ramifications, I might not have gone down that route quite so fast and easily. But I continued because I also have a lot of resources that other people don't and being able to assess and understand and put things in place to mitigate that. So you need to be. And the other thing is, once you go on, it's literally a decision for life. But realistically is, because your quality of life, your feeling is going to be enhanced quite a bit. And you're not going to want to go back. And if you go back, it's going to be less than it was before. That's how the endocrine system works. There are ways to try to recover and bring that up, but it might be a while. And if you've been on for a while, it definitely is not an option. So those are big things that people need to understand that you're going to have some things in there. And even TRT has some potential, especially at higher levels, that it's going to increase the risk for prostate cancer. It's going to potentially cause some hypertrophy of the left ventricle of the heart and some potential plaque buildup of some of those key arteries around there that's going to have an impact on your cardiovascular health. There's things that you can do again, but everything is like the shoe story, right? Where I'm anti-shoe, but I'm going, well, we could put Band-Aids on this. So it's- Yeah. But there's a quality of life that comes with it, the increasing quality of life. And if you do it correctly, I think- For me, I definitely would not live without TRT, even with knowing what I know now, at this age and the quality of life and being able to be there, have the energy, the recovery. That's a big thing where all this, so I talked about muscle protein synthesis and anti-catabolism as being big drivers, but recovery is the other big aspect that they offer, probably as a result of those, but those are going to be the big enhancements. So just doing steroids, steroids is going to increase all the other stuff that you do. So if you have good training, you have good diet, good quality of sleep, like all this other stuff, then you can take advantage of that. But you could shoot steroids and nobody would know. And honestly, you go down to 24-hour fitness and you'll see a bunch of late 19 to 21 year old kids that are all kind of red and 150 pounds that don't look like anything. And a bunch of them will be using steroids because they're not, so it's not going to make a champion. Like you said, 10% at most. It's not going to, guess what? I was already at an elite level. I was one of the best in the world before I started using. It doesn't do that. It does a 10% increase at best. And that's proven in the statistics, which is interesting because most people don't know this. The data is right there. Yeah. And that's why I'm often saddened by maybe the negative view of somebody like Lance Armstrong, who was one of the greatest athletes in history. And everybody else that he was competing against, I'm sorry. I hate to blow anybody's bubble, but regardless of I told you my ethical pieces with saying that you're going to be at something at an elite level, you look at a lot of those big figures out there, when their income and your life relies on it, you're going to push those limits. So maybe my ethical would change if I was in that position too, because here's the thing where I believe. Like someone is, I think people should avoid steroids. TRT, probably something worth taking a look at what your levels are when you're in the 35 to 45 range and see what decision you decide to make from there. And that's a decision that you make for the rest of your life. The only times that you should be taking a look at steroids is if it's funding your life, it's creating that it is your job and it's doing like, and honestly it was for me. So was it the only thing? No. No. If you want to get into neurology, neurotransmitters and alcohol, there's a really interesting discussion on performance enhancement. So when I lift heavy, and so I always promote it not more than a drink or two, like once or twice a month is what all I'm talking about when I'm saying this. What's the timing of the drink that we're talking about? It's about three to five minutes. Before? Yes. And then we're talking about beer. It doesn't matter the source. So shots are the easiest. You want something that is not going to have some sort of regurgitory effect or bloating effect or anything like that. But you want to have the quick hit of energy. So it's a preferential energy source moves above ketones, carbs, everything. It's seven calories per gram, but then there's some really interesting things that happen. Spikes blood pressure, which is going to make weights feel lighter. So when you're in your early 20s and you're trying to hit up some attractive person at the bar, you're with your buddies and you're like, ah, and you got second guess, oh, should I, should I? And they go, have a shot of liquid courage. And you have one. And all of a sudden, the second thoughts, the second guessing, all that drops away. You're focused in the moment and you walk over and you actually perform a little better, like conversation wise than you normally would. Now, if you have five or six and then go over, you're gonna make a fool of yourself. So it's all about timing and amount, but there is a reason that that happens. So anyway, I'm known for promoting this whiskey and deadlift concept. I love this, but it works. Like the Eastern block. That's where I stole it from because I was watching all these Russian lifters would have a shot of vodka or something before they go lift. And I'm like, there's something here. So I started experimenting with it and I'm like, that works. And then I started researching, nobody talks about this stuff. So it takes a while to start piecing together all the stuff that actually happens to make that happen. But it moves away the things that you're going to, the concerns about the ramifications in the future and the other stuff. So the, um, but brings you into the moment and then the, the, the dopamine hit and the other, and then it, uh, enhances whatever mood that you're in. But all of a sudden you get in the state much easier. And so it's really, really interesting, but it's very, it's a very small amount needed and very time sensitive, but it can be so much more powerful than like drugs people use for this stuff. It ties really together with meditative state and other pieces to, to, to get you into that flow state, those thoughts about failure, what if, what, like all that you, you get into that zone, that moment, that time. Mm-hmm. Um, so anyway, so interesting, an alcoholic is promoting out, you know, uh, No, but there's an important point here. It's not often talked about. I think it is fascinating that because you can get into so much trouble with alcohol when using excess, people don't often talk about the, the positive aspects of alcohol, even in your college years. It had a, it had a lasting effect on who I am as a person. I don't think people give enough credit to the positive aspect. See, you could have accomplished a lot of those same things with a little more moderation, which I think people should talk about more, which is like the, the way to open up a personality, like the flowering of the full character and the weirdness and the, the, the, like, the beauty of who you are as a human being could be opened up with alcohol. And that's really interesting to think about. You should try some podcasts with a, with a shot and, and these. Yeah. Actually, I, I do this sometimes with myself and guests and it will change the conversation, lubricates the conversation. Definitely not the excess, which is what I learned, because I went all the way in because I do everything at extremes. Yeah. So it was a really hard lesson that took me a lot of time to unwind, but it is interesting and people don't discuss those things because it's, it's either this or this. You're one of the greatest strength athletes of all time. So it's worthwhile to consider how you optimize the, the feats of strength that you reach for with things like steroids. It's, it makes perfect sense. And I think that was a, from my perspective, I think it was probably the right decision. You've achieved something incredible that inspires a huge number of people. That's it. And you've shown to yourself and to the world, but what the human body can accomplish. Yep. That's incredible. And no matter if I push to a less weight and if I disclosed everything that I did and I didn't, when I wasn't using steroids, in my opinion, if we went through everything, there would people that would say you're using performance enhancing. Yeah. No matter what, like it is, it's straight up. So you just need to be okay with it yourself. And so I had to make the call. I want to see what the true potential is of every, let's throw everything out the window that I feel, unless I feel it's a risk from a, from a health standpoint that I'm not willing to take on. And because that's how do I like, it's just picking and choosing. Yeah. And it's just picking and choosing. I, here's what I want to know. This is what I want to be able to try to achieve. And so, yeah, yeah, that's what I did. And what you did is incredible. Like it's, it's just all inspiring. And what Lance Armstrong did was incredible. Yeah. And that, And that, and that eats me up. And what's funny is the people that bash him are like on the media or politicians or maybe some actors and guess what? A ton of them are doing the same thing. It's hypocrisy at its finest. Trust me. But How many, how many of those figures you're watching in movies that love to talk, you know, be, you know, be political and do this and the news and all this, I'm telling you, they're, they're anti-aging clinics, like all over California and everywhere else. Who do you think is, keeps them in business? Well, It's not the competitive lifter. I'll tell you that. Well, that's, you're speaking, And they're using peptides and SARMs and all sorts of like, Wait, you're speaking to the hypocrisy. I also want to speak to the, the fact, you know, somebody who's a friend of mine, David Goggins. I don't know if you know who that is. Ultra marathon runner, Navy seal. He gets Pretty incredible person. Yeah. Incredible human being. And he gets criticism like, you know, what you're doing is, is bad for the body. You know, you're, you're pushing yourself too far. I find that the people that criticize are often people that haven't truly pushed themselves to the limit. They haven't actually worked hard in their life. When you work hard, you realize how incredible it is that a human being can dedicate themselves so fully to an effort the way you did the way David Goggins does the way, the way the greatest athletes do. And there's nothing that should be said beyond just sitting back in awe that humans can achieve that. And that inspires me to do the best, whatever the hell I do to be the best version of that. There's something about like athletic feats, especially like strength that just inspire us to do the best, to be the best version of ourselves. I don't know. That's the only thing you should be saying as opposed to criticizing some little detail of this and that. It's just awe inspiring that you push yourself to the limit. Anybody that is at that level. And this is funny, like in competitive sports, like you go online and people, it's just bash, bash, bash, bash, bash, bash, bash. You go talk to anybody, anybody, anybody that's a high level athlete within that field. And nobody has a single bad thing to say about each other. But all this chitter chatter down there. I mean, I know exactly what you're saying. So if you, I would say, cause I have love for all those folks, especially when you're younger, you have a little bit of that desire to criticize others. Like, I think that should be channeled in improving your own life. Anytime that you feel that way, that is when you need to turn inward. And it's hard to do, but there is a reason that you have those emotions around someone else and what they're doing, that you have an opportunity to look at yourself and know why you feel that way. And that, guess what? That's going to be the hard thing to do. That's going to be the thing, again, that's stirring you a little bit, cause it's so much easier to sit there and, or talk to your confidant or whatever, instead of go, why does that bother me? Why does what that person doing or what that person's achieving bother me? It's a good, difficult question that I often ask others, whether it's better to work hard or work smart. I like to ask that question because it helps me get a sense of the human being. And I think I, let me just say, like, I often, I often like people that answer that with work hard. Even though the quote unquote right answer is work smart, meaning like finding the optimal, efficient way to achieve a certain goal. I find that people that answer work smart don't actually find the optimal, efficient way to achieve a goal. It seems like the people that at least, certainly early in life, strive to work their ass off, even that means doing the inefficient, the dumb thing, just to learn the mistake. The spirit behind, the human spirit behind the person that says, or a card, is the one that I connect with. But I'm torn, especially in the war culture, in the tech sector where people answer work smart. What would you say about that tension? This definitely encompasses like, I'm the intellectual and I'm the meathead. I'm the work around the clock and go fix the processes and make it so much better type person. That's me and that's everything, that's my life story. Busting your ass to find the easiest way possible. To both. So like, I will build a custom hydraulic cart that will lift my plates up to the height of my squat so that I can minimize, roll it over next to it and then minimize the effort of it going on and off. Yeah. To be able to lift the most amount of weight as possible. Yeah. So that I can save the energy from here, from lifting those up and the fatigue of my back being in a bad position, so I can nearly kill myself over here. Yes. Right? My wife, anybody will say, I'm a workaholic. Yeah. And the first thing that I would do when it would be doing a company turnaround, they'd hire me, come in, and I would be taking over for someone that wasn't successful. But it was usually, hardly ever for lack of want or trying. So a lot of times, they knew they were unsuccessful and they were running around working six, seven days a week, 12 hour days, doing so much. And it'd be like, well, you need to do this. And they'd train me on all the reports and this and all the things and like, good luck. Good luck, I couldn't do it. And the first thing I would do is nothing. I would do nothing. Because then I would find what actually keeps coming back, the things that I need to do and how much of it was filling the space. Because so much of human nature, when you're failing, is to make yourself feel like you're accomplishing things. This is when things go on your list, on your checklist, and you start like rolling up. So you're running around just getting shit done. Yeah, being busy. Right? Yeah. But at the same time, find somewhere in my career something I've done where I haven't outworked everybody. Just so much on distilling things down to what's important. Yeah. And you've got to make time to sit back and assess and think and be introspective. You have to make time for this. Because if not, you're going to waste so much time sitting there walking sideways when all you got to do is move just one step in front of the other each day. Just one. That's all I say. Because it's going to add up. But you could spend six months knocking shit out, doing your routine, busting your ass, and not take that one step. So you've got to distill stuff down. You've got to really understand what's important to you in life and where you're going. And when you're looking at anything in your life, the first thing that you need to do is figure out, do I need to do it? And just quit doing it. Just quit doing things in your life. And you'll see that a lot of stuff that you think has to be done doesn't have to be done. You'd be surprised. And then from there, it's the tech. Okay. And then of that, what can I automate? What can I not have to do in a repeated fashion? And then the last one, yeah, wherever possible. If it's not something that I'm adding tremendous value to, like my uniqueness, people are like, oh, you must do the automation on your vehicles because you love working. I'm like, fuck that. I don't. And they're like, what? That doesn't make any sense. And I'm like, no, I love creating things. But I don't want to do that stuff. So you could use delegating if you're a manager position, but it's outsourcing, whatever it is. But there are also so many things. And this ties back to your point around just doing it. There's a point to like, I'm going to do this, I'm going to do that. There's a point to like experiencing all levels to really understand things. You need to spend time at the same time doing all those things because there could be good, huge, massive gaps in there that you're not aware of that are key for you or key to be having done different or so on. So like in my company days, I was one of the few executives that came in that could do anything on the floor from code to machine, run a lathe, mill, weld, step into engineering. And that added tremendous value to me to having had spent time being a doer and not enough people want to be, you've got to just go do shit. You need to spend time in your life chopping wood. Yeah, get a lot of shit done. Doesn't matter what the shit is. You've got to have experience trying and doing all these things that you would never... My skill set is massive because I want to know... You need to have those touch points. My job, my title is chief visionary, but I've spent time doing everything. It's not about just creating this amazing strategy or vision and I'm just going to be there and this person that directs and like... You can't be effective. You cannot connect the dots unless you've been in the moment with everything. Yeah. Low level stuff. Sometimes it's doing stupid shit that you're not uniquely qualified to do that anybody could do, but you did it anyway. Just the training environment. People hit me up at a school or wherever like, hey, how do I get into... I want to grow my brand online. I want to do this. Where do I start? I'm like, go get a job at Planet Fitness or 24-Hour Fitness. They're like, but I want to... How do I get recognized and write articles and be an online coach? I'm like, you need to go spend a few years one-on-one training people to learn the interaction, how people... There's base levels you have to do. You've got to go work your way up from the ground. Yeah. I truly believe it. Well, I think that's the hard work piece that I'm speaking to that I like it when people have been humbled by the hardness of life. Like how difficult it is to do stuff and it does... Like, oh, I went and got my MBA. I went to MIT. I don't need to do that stuff. I'm above that. Yeah. Yeah. Once you've been humbled by doing those things, I feel like you can truly explore the optimization that you're talking to, finding the ways where you're uniquely capable to add value to the world. And then again, work your ass off to be the best in the world at that thing. Yes. So it's always... But then don't waste your time on shit that's not a line. That's the only... So that's... I guess there's a lot of context I put around that. But... But yeah, that was like a long answer to a long, beautiful answer to an unanswerable question. Do you have advice outside of all this discussion to young people today about career, about life? Since you've done so many things, you've overcome a lot of things. Think high school, college student, thinking about what to do in their life. Do you have advice for those guys and girls? Yeah. Yeah. First is, you don't have it figured out. So don't worry, just jump in. Yeah. We talked a lot about understanding your values and aligning all that stuff, but you gotta have a base level of start exploring and learning. And just spending the time doing like, pick something. Let me elaborate a little bit. No, you know what? A lot of people struggle with that aspect now because the choice, there's so much choice, it's difficult to pick something. But I think it does boil down to, you should pick something and don't worry about it. And then, but within that, you can start discovering the things that are there for you. Like I talked about, I made this huge shift, I threw away my whole life, but I don't regret anything about that. I wouldn't be where I was if I didn't walk through and learn those things. And in fact, in the course of that, I learned just how much that inspiring people and helping them realize the potential far beyond what they thought was capable. And guess what? That was leadership 101 in managing people base level, floor level. And I got a lot out, it was perfectly aligned with, and that's what I realized, it didn't matter what industry I was in or any of those other things. But I was able, you can see so many things, there's so many paths that you can go down to help you realize what those things are. And you're going to be able to find a lot of those nuggets and develop those. Do you think that I could have just gone to school and got out and started a globally recognized brand within a few years without having been schooled in business while getting paid for it by others for years? And in fact, that entire time I knew that that's what I wanted to do, but I didn't go out on it. I mentored some of my friends along the same path to go, no, they're like, I'm ready, I'm ready to go do this. And I'm like, no, now you need to go get a job. Yeah, you know, engineering, management, design, all that stuff, go get a job as a manager now. Like, oh, that's a step down. I can't do that. I'm like, go try it. A couple of years later, oh my God, that was such a good move. I didn't know what I didn't know. And now they're an executive for freaking a Fortune 500 company. And the same thing, like I sat there knowing that I was getting a free education. Don't stress yourself out, that's my advice. Don't stress yourself out that you've got to have this perfect thing because this process of understanding your values and the interest, that takes time. You can get a job where you're getting paid to learn. Exactly. That's a good deal before you launch on your own. You mentioned going back to darkness. I'm Russian, so I like going back to darkness. You suffered from depression, you considered suicide. Do you ponder your own death these days? Do you think about your mortality? Are you afraid of death? I definitely think about mortality. And am I afraid of my own death? It depends on the moment. If I'm in the middle of a project, I definitely want to finish that project, man. But I don't fear it so much. I fear leaving my kids or my wife and not being able to be there for them. That bothers me. Outside of that, I know that I put everything into the life that I've lived. Like you said, there's always more, but I've lived hard. I've loved and I've been through a lot. I've been through a lot. I've lived hard. I've loved hard. Every moment in my life, I've made connections and impacted people around me for the better. And this tracks back, which is crazy when we were doing the documentary and they're interviewing people through my whole life and the consistency of the themes of anyone, like anything for Duffin. Like just, sure, I'll fly in from Boston. And all of them, like these people, like all of like, it was crazy. Like everybody had a story about me giving, like just over and over. And I didn't even really... It's just the way you were. But I've been all in. I don't have, like, I have a lot more I want to do, but I don't have things that regret have not done in, like, I don't fear it. I don't fear it. Yeah. It's like the, I don't know if you know, the Bukowski poem, Go All the Way. Otherwise, Don't Even Try. It seems like you embody that poem and you've accomplished some incredible things and serve as an inspiration to a huge number of people. Chris, you're an amazing human being. I'm really honored that you would spend your valuable time with me. Thank you so much for talking with me today. It was incredible. I can't wait to check out all the cool stuff you've engineered with Kabuki Strength. So I'm obviously, I love the, I love strength. I love strength training. I love the idea of strength. I love the equipment and the engineering approach that you take to strength. You're an incredible human, both on the things you've accomplished in terms of your own strength feats and the kind of science and engineering you bring to the field that many others could use. So thank you so much for talking today. Thanks for having me on. That was quite the final. Thank you. Thanks for listening to this conversation with Chris Duffin. And thank you to Headspace, Magic Spoon, Sun Basket, and Ladder. Check them out in the description to support this podcast. And now let me leave you with some words from Arnold Schwarzenegger. Strength does not come from winning. Your struggles develop your strengths. When you go through the hardship and decide not to surrender, that is strength. Thank you for listening and hope to see you next time.

https://youtu.be/e4Bet29PVPY

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Robert Crews: Afghanistan, Taliban, Bin Laden, and War in the Middle East | Lex Fridman Podcast #244

The following is a conversation with Robert Cruz, a historian at Stanford, specializing in the history of Afghanistan, Russia, and Islam. This is the Alex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Robert Cruz. Was it a mistake for the United States to invade Afghanistan in 2001, 20 years ago? Yes. As simple as yes, why was it a mistake? I'm a historian, so I say this with some humility about what we can know. I think I'd still like to know much more about what was going on in the White House, in the hours, days, weeks, after 9-11. But I think the George W. Bush administration acted in a state of panic. And I think they wanted to show a kind of toughness. They wanted to show some kind of resolve. This was a horrific act that played out on everyone's television screens. And I think it was really a, fundamentally a crisis of legitimacy within the White House, within the Oval Office. And I think they felt like they had to do something, and something dramatic. I think they didn't really think through, you know, who they were fighting, you know, who the enemy was, what this geography had to do with 9-11. I think looking back at it, I mean, some of us, not to say I was, you know, clairvoyant or could see into the future, but I think many of us were, even from that morning, skeptical about the connections that people were drawing between Afghanistan as a state, as a place, and the actions of Al-Qaeda in Washington, and New York, and Pennsylvania. So as you watch the events of 9-11, the things that our leaders were saying in the minutes, hours, days, weeks that followed, maybe you can give a little bit of a timeline of what was being said, when was the actual invasion of Afghanistan, and also what were your feelings in the minutes, weeks after 9-11? I was in DC, I was, you know, on the way to American University, hearing on NPR what had happened, and I thought of the American University logo, which is red, white, and blue, it's an eagle, and I thought, you know, Washington is under attack, and symbols of American power are under attack, and so, you know, I was quite concerned, and at the time lived, you know, just a few miles from the capital, and so, you know, I felt that, you know, it was real, so I appreciate the, you know, the sense of anxiety, and fear, and panic, and four, two, three years later, in DC, we were constantly getting reports, you know, mostly rumors, and unconfirmed about all kinds of attacks that would fall on the city, so I definitely appreciate the sense of being under assault, but in watching television, including Russian television that day, because I just installed a satellite thing, so I was trying to watch world news, and get different points of view, and that was quite useful to have an alternative, you know, set of eyes. In Russian? Yeah, in Russian, yeah. Okay, so your Russian is good enough to understand Russian television. The news, yeah, the news, and the visuals that were coming that were not shown on American television. I don't know how they had it, but they had, they were not filtering anything in the way that the major networks and cable televisions were doing here, so it was a very unvarnished view of the violence of the moment, you know, in New York City, of people diving from the towers, or being, you know, and it was really, they didn't hold back on that, which was quite, you know, fascinating. I think much of the world saw much more than actually the American public saw, but to your question, you know, amid that feeling of imminent doom, I watched commentators start to talk about Al-Qaeda, and then talk about Afghanistan, and one of the experts was Barnett Rubin, who's at NYU, who's a, you know, kind of long, very learned Afghanistan hand, and he's brought on Peter Jennings on ABC News to kind of lay this out for everyone, and I thought, you know, he did a fine job, but I think it was formative in cementing the view that somehow Al-Qaeda was synonymous with this space, Afghanistan, and I think, again, I was no Al-Qaeda expert then, and I'm not now, but I think my immediate thought went to war, and because my background had been with, at that point, mostly Afghans who had been displaced from decades of war, who I encountered in Uzbekistan, who were refugees, and so on, I thought immediately, you know, my mind went to the suffering of Afghan people, that this war was going to sweep up, of course, the defenseless people who have nothing to do with these politics. So we should give maybe a little bit of context that you can speak to. So assume nobody's an expert at anything. So let's just say you and I are not experts at anything. What, as a historian, were you studying at the time and thinking about, say, is it the full global history of Afghanistan, is it the region? Were you thinking about the Mujahideen and Al-Qaeda and Taliban? Were you thinking about the Soviet Union, the proxy war through Afghanistan? Were you thinking about Iraq and oil? Like, what's the full space of things in your heart, in your mind at the time? I mean, just at the moment, of course, it was, you know, there's the sense of, you know, the suffering and the tragedy of the moment of the deaths. And that was, I think, I was preoccupied by the violence of the moment. But as the conversation turned to Afghanistan as a kind of theater, to somehow respond to this moment, I think immediately what came to mind was that the little I knew about Al-Qaeda at the time suggested that the geography was inaccurate, that this was a global network, a global threat, that this was a kind of, you know, a movement that went beyond borders. And I think that it felt early on that Afghanistan was gonna be used as a scapegoat. And just intellectually at the time, you know, I was teaching at American University, my courses, you know, touched on a range of subjects, but I was trying to complete a book on Islam and the Russian Empire, actually. But in doing that research, which took me across Russia and Central Asia, purely by accident, I had developed an interest in Afghanistan because, just again, a series of coincidences, I found myself in Tashkent, the capital of Uzbekistan, without housing, through an American friend who was like the king of the market in Tashkent. He knew everyone, he run into some Afghan merchants there. They found out I didn't have a place to live. I didn't know where Afghanistan was, honestly. This was 1997, I had a vague idea it was next door. Well, you lived in Uzbekistan? Yeah, in Tashkent, doing dissertation research, yeah. Because it was, you know, hub of the Russian Empire in Central Asia. Yeah. So by accident, I met with these young Afghans who took me in as roommates. And that, I think, the sense of that community shaped my idea of what Afghanistan is. It was my first exposure to them. They were part of a trading diaspora. They brought, they had brought matches from Riga, Latvia. They had somehow brought flour and some agricultural products from Egypt. And they were sitting in enclosed containers in Tashkent, waiting for the Uzbekistani state to permit them to trade. So these guys are mostly hanging out during the day. They would get dressed up, they'd put on suits and ties, like you're wearing. They'd polish their shoes, and they would sit around offices, drink tea, pistachios. Then they'd feast at lunch, and then at night we would go out. So part of my research, because I also had a bottleneck in my research, I was going to the state archives in Tashkent. And because of the state of Uzbekistan, that was a very kind of suspicious thing to do. So it took a while to get in. So I had downtime in Tashkent, just like these guys. So I got to know them pretty well. And it was really just an accidental kind of thing, but grew quite close to them. And I developed an appreciation of, which now I think, again, thinking of the seeds of all this, these people had already lived, young guys, in their 20s, they'd already lived in 67 countries. They all spoke half a dozen languages. One of my best friends there had been a kickboxer and break dancer, trained in Tehran. His father was a theater person in Afghanistan. He told stories of escaping death in Afghanistan during the civil war, going to Uzbekistan, escaping death there. And these were very real stories. Can you also just briefly mention, geographically speaking, Afghanistan, Uzbekistan, Tajikistan, you mentioned Iran. Right. Who are the neighbors of all of this? What are we supposed to be thinking about for people? I was always terrible at geography and spatial information. So can you lay it out? Yeah, yeah, sure, sure. So Tashkent is the capital of Uzbekistan. It was a hub of Russian imperial power in the 19th century. The Russians take the city from a local kind of Muslim dynasty in 1865. It becomes the city, the kind of hub of Soviet power in Central Asia after 1917. It becomes the center of the Soviet Republic of Uzbekistan, which becomes independent finally in 1991 when the Soviet Union collapses. So these are all like, these republics are the fingertips of Soviet power in Central Asia. That's right. And they've been independent since 1991, but they have struggled to disentangle themselves from Moscow, from one another. And now they face very serious pressure from China to form a kind of periphery of the great machine that is the Chinese economy and its ambitions to stretch across Asia. For Afghanistan, where my roommates, my friends hailed from, Afghanistan had fallen into civil war in the late 1970s when leftists tried to seize power there in 1978. The Soviet Union then extended from Uzbekistan, crossing the border with its forces in 1979 to try to shore up this leftist government that had seized power in 1978. And so for Central Asians in the wider region, their fate had for some decades been tied to Afghanistan in a variety of ways, but it became much more connected in 1980s when Soviet Red Army occupied Afghanistan for 10 years. And here I refer your listeners and viewers to Rainbow Three as the guide to- The historically accurate guide. The historically accurate, the Bible. The Bible of Afghan history in Rainbow Three, yeah. As a fantastic window onto the American view of the war. But for most Afghans, there are people who fought against the Soviet Army, but of a certain generation, the guys I knew, their mission was to survive. And so they fled in waves by the millions to Pakistan, to Iran. Some went north into Soviet Central Asia later in the 1990s and some were displaced across the planet. So California, where we're sitting today, has a large community that came in the 80s and 90s in the East Bay. Can I ask a quick question that's a little bit of a tangent? Yeah. What is the correct or the respectful way to pronounce Afghanistan, Afghanistan, Iran, Iran? So as a Russian speaker, Afghanistan. Yeah. The on versus the an. Yeah. Is it a different country by country? As an English speaker in America, is it pretentious and disrespectful to say Afghanistan or is it the opposite, respectful to say it that way? What are your thoughts on this? That's a fascinating question. I defer to the people from those countries to of course sort out those politics. I think one of the fascinating things about the region broadly is that it is a place of so many cultures and are really quite cosmopolitan. So I think people are mostly quite forgiving about how you say Afghanistan, Afghanistan. It's not like Paris. Yeah, yeah, right, right. The French are not forgiving. No, no, no, exactly. I think people are very, very forgiving. And I think that Iranians are a bit more instructive in suggesting Iran rather than Iran, right? Iraq, Iraq. You know, I think there's come to be a fit between certain ways of pronouncing these places and the position that Americans take about them, right? So it's more jarring when people say Iraq and it comes with a claim that a certain kind of person should be the victim of violence or, right? So does that, yeah. It's kind of like talking about the Democratic Party or the Democrat Party. It's sometimes using certain kind of terminology to make a little bit of a sort of implied statement about your beliefs. That's fascinating. Yeah, I mean, I think when I hear Iraq and Iran, I mean, I think it, yeah, is it intentional in the case of a Democrat or is it just a, you know, and it's a whatever. I think, again, I think most Iranians and Afghans people I know have been very cool about that. What annoys Afghans now, I can say, I think it's fair to say, I don't mean to speak for millions of people, for a tiger of people, but I can just share with our non-Afghan friends. The term Afghani is a kind of term of offense because that's the name of the currency. And so lots of people ask, you know, why having, especially, again, it's more directed at Americans because, you know, we've been so deeply involved in that country, obviously for the last 20 years, right? So Afghans ask why after 20 years are you still calling us the wrong name? What is the right name? Somebody who is- They prefer Afghans. Afghans. Yeah, and Afghani is the name of the currency. And so- I just dodged the bullet because I was gonna say Afghani. That's cool, no, no, yeah, I hear you. That's really great to know. Yeah, yeah, and it's, again, I think, but I would emphasize that people are quite open and, you know, it's a whole region of incredible diversity and respect for linguistic pluralism, actually. So I think that, you know, but I also appreciate that in this context, when there's a lot of pain, you know, in the Afghan diaspora community in particular, you know, being called the wrong name after 20 years when they already feel so betrayed at this moment, you know, just kind of, if one follows us on social media, that is one kind of hot wire, right? Yeah, so the reason I ask about pronunciation is because, yes, it is true that there are certain things when mispronounced kind of reveal that you don't care enough to pronounce correctly. So you don't know enough to pronounce correctly and you dismiss the culture and the people, which I think, as per your writing, is something that, if it's okay, I'll go with Afghanistan, just because I'm used to it. I say Iraq, Iran, but I say Afghanistan. Yeah, that's great. As you do in your writing, Afghanistan suffers from much misunderstanding from the rest of the world. But back to our discussion of Uzbekistan, Tajikistan, the whole region that gives us context for the events of 9-11. Right, right. So yeah, if we go back to that day and the weeks, you know, that followed, in my mind went to the community I knew in Tashkent, which is interesting. It was, I mean, they were, so Islam was the focal point of our conversation in the US about 9-11, right? Everyone wanted to know what was the relationship between the Serbic violence and that religious tradition with its, you know, 1 billion plus followers across the globe, right? That became the issue, of course, for American security institutions, for local state and police institutions, right? I mean, it became the, I think it was the question that most Americans had on their mind. So again, I didn't imagine myself as someone who had all the answers, of course, but given my background and coming at this from Russian history, coming at this from studying empire and trying to think about the region broadly, you know, I was very alarmed at the way that the conversation went. Can I ask you a question? What was your feeling on that morning of 9-11? Who did this? Isn't that a natural feeling? It's coupled with fear of what's next, especially when you're in DC, but also who is this? Is this an accident? Is this a deliberate terrorist attack? Is this domestic? What were your thoughts of the options and the internal ranking given here by expertise? I mean, I suppose I was taken by the narrative that this was international. I mean, I'd also lived in New York during one of the first bombings in 94 of the World Trade Center. So it was clear to me that a radical community had really fixed New York as part of their imagination of, and I immediately thought it was a kind of blow to American power. And I was drawn by the symbolism of, if you think of it as an act, it was a kind of an act of speech, if you will, kind of a way of speaking to, from a position of relative weakness, speaking to an imperial power. And I saw it as a kind of symbolic speech act of that with horrific real world consequences for all those innocent victims, for the firemen, for the police, and just the horror of the moment. So I did see it as transcending the United States, but I did not see it as really having anything necessarily to do fundamentally about Afghanistan and the history of the region that I'd been studying and the community people that I knew who were not particularly religious, right? The guys I hung out with actually wore me out because they wanted to go out every night. They wanted to party every night. Drinking? Yep. We had discussions about alcohol. I mean, Uzbekistan is famous for its- Drinking. It's drinking. You know, it's- That's something to look forward to. So I do wanna travel to that part of the world. When was the last time you were in that part of the world? Early 2000s. Well, in the mid 2000s, 2010s. So wait, so by the way, we're drinking vodka. What's the weapon of choice? Uzbekistan has incorporated vodka as the choice. And it informs, you know, and it's, but the fascinating thing, you know, and as a student is what you're observing as a non-Muslim, you know, I'm a non-Russian. This is all, you know, culturally new to me. And I'm, you know, a student of all that, right? As a grad student, doing my work there. So you're like the Jane Goodall of vodka and Russia. That's right. You're just observing. That's right, yeah, yeah, yeah. And then you get the psalmogon, the grass vodka. You get, you know, I have, I've had some long nights on the Kazakhstan frontier that I'm not proud of, you know. But you got to know the people and some of them from Afghanistan. Yeah, yeah, yeah, but intellectually. So the thing, I mean, the fascinating thing there was that, and just as a, I mean, there's a whole, you know, I'm a historian, right? But there are great contributions by, you know, anthropologists and ethnographers who've gone across the planet and try to understand how Muslims understand the tradition at different contexts. So many Uzbeks will say, you know, this is part of our national culture to drink and eat as we please, right? And yet I'm a very devout Muslim. And so, of course, you can encounter other Muslim communities who won't touch alcohol, right? But it's become kind of, I think it's very much, you know, Soviet culture left a deep impression in each of these places. And so there are ways of thinking, ways of performing, ways of enjoying oneself that are shared across Soviet, in a form of Soviet space to this day, right? And you've written also about Muslims in the Soviet Union. That's right. There's an article that there's a paywall, so I couldn't read it. And I really wanna read it. Is- Happy to share with you, yeah. Moscow and the mosque or something like that. Right, right. By the way, just another tangent on a tangent. Yeah. So I bought all your books. I love them very much. One of the reasons I bought them and read many parts is because they're easy to buy. Unlike articles, every single website has a paywall. So it's very frustrating to read brilliant scholars such as yourself. No, no. I wish there was one fee I could pay everywhere. I don't care what that fee is. Where it gives, allows me to read some of your brilliant writing. No, no, thank you. I think moving toward more kind of open source formatting stuff, I think is what a lot of journals are thinking about now. And I think it's definitely for the kind of democratization of knowledge and scholarship, that's definitely an important thing that we should all think about. And I think we need to exert pressure on these publishers to do that. So I appreciate that. This is what I'm doing here. Yeah, yeah, yeah. Good, good. I appreciate it. So your thought was Afghanistan is not going to be the center, the source of where. It's not the center of this. And invading that country isn't gonna fix the toxic milestone of politics that produced 9-11. I think I'm just thinking of some of the personalities just thinking about going back to the Tashkent story, which I'll end with. I mean, just observing real Muslims doing things and then asking questions about it and trying to understand through their eyes what the tradition means to them. And then we had a very narrow conversation about what Islam is that immediately exploded on the day of 9-11. And then of course, I think the antipathy toward Islam and Muslims was informed by racism, informed by xenophobia. So it became a perfect storm, I think, of demonization that didn't sit with what I knew about the tradition and with the actual people that I had known. Because then going back to, I mean, there were other friends and encounters and so on, but just thinking about Afghanistan and Tashkent for a moment, I mean, just thought about my friends who had been, who had suffered a great deal in their short lives, who had been cast aside from country to country, but had found a place in Tashkent with some relative stability. And they wanted to go out every night. And they explained, one friend, we talked about it with the alcohol and all that, and he didn't get crazy, but he was like, you can drink, but just don't get drunk. That's permissible within Islam, right? And he was, I think, Pashtun. I think Uzbeks had a different view. Often, the more vodka, the better. And it doesn't violate, as I understand, Islam. So even, it's kind of a silly example, but it's just an illustration of the ways in which different communities, different generations, different people can come at this very complex, rich tradition in so many different ways. So obviously, whatever kind of scholar you are, any kind of expert, whatever, it's always disconcerting to see your field of specialization be flattened, right? And then be flattened, and then be turned to arguments for violence. Mixed up with natural human feelings of hate. Yeah, and hurt at that moment. And pain. So I mean, that day, I vividly remember, I sat with other PhD historians in different fields. We, oddly enough, had lunch that day, and it kind of deserted Washington. Some place was open, we went. And we just thought, this is gonna kind of open up like a great mall of destruction. And the American state is going to destroy, and it's gonna destroy in this geography. And I thought that was misplaced for lots of reasons. And then I think, if one, I'd been doing some research on Afghanistan then, I was kind of shifting to the South, and I'd been looking at the Taliban from afar for some years, and I think it's clear now that in retrospect, there were opportunities for alternative policies at that moment. So what should the conversation have been like? What should we have done differently? Because from a perspective of the time, the United States was invaded by a foreign force. What is the proper response, or what is the proper conversation about the proper response at the time, you think? I know my colleague at Stanford, Condoleezza Rice, would tell me this is above my pay grade. And she makes a point in her classes to talk about how difficult decision-making is under such intense pressure. And I appreciate that. I am a historian who sits safely in my office. I don't like battlefields. I don't like taking risks. So I can see all those limits. I'm not a military expert. I've been accused of being a spy wherever I've gone because of the way I look and because of my nationality and so on, but I'm not a spy, so I defer. Yeah, I respect the expertise of all those communities, but I think they acted out of ignorance. They acted, I think, because, I mean, you think of the, in a way, there was a compensatory aspect of this decision-making. I mean, the Bush administration failed. This was an extraordinary failure, right? So if we start- In which way? If we're gonna break down the- The intelligence, I mean, if you follow the story of Richard Clark- Who's Richard Clark? He was a national security expert who was tasked with following Al-Qaeda, who had produced a dossier under the Clinton administration that he passed on to the George W. Bush administration. And if you look at the work of Connie Lisa Rice, she wrote a very famous, I think, unpaywalled foreign affairs article that you can read, announcing the George W. Bush foreign policy kind of outlook. And it was all about great powers. It was about the rise of China. It was about Russia. I mean, there's definitely a kind of hangover of those who missed having Russia as the boogeyman, who spoke, you know, the Clinton administration repeated again and again the idea of making sure the bear stayed in his cage, which is why the United States threw a lifeline to the Central Asian states, hoping to have pipelines, hoping to shore up their national sovereignty as a way of containing Russia initially, but also Iran, you know, which sits to the south and west, and then peripherally looking down the road to China, to the east. So the bear is what, like Russia, or is it kind of like some weird combination of Russia, Iran, and China? The bear is Russia and Russia is this, I'm trying to characterize the imagination of some of these national security figures. This is an image formed in the Cold War. I mean, it has deeper seeds in European and Western intellectual thought that go back at least to the 1850s in the reign of Tsar Nicholas I. When we first get this language about the Russian empire as this kind of evil polity. Obviously, this was a kind of pillar of Reaganism, but the Clinton folks kept that alive. They wanted to make sure that American power would be unmatched, and they, being creatures of the Cold War themselves, they looked to Russia as a resurgent power well before Putin was even thought of. Yeah, I mean, this is, you mentioned one deep, profound historical piece in Rambo. It's probably, this conflict has to do with another Celestinian film, a movie, Iraqi Four, which is also historically accurate and based on, it's basically a documentary. So there is something about the American power, even at the level of Condoleezza Rice, these respected, deep kind of leaders and thinkers about history and the future, where they like to have competition with other superpowers and almost conjure up superpowers, even when those countries don't maybe, at the time, at least deserve the label of superpower. That's right, great point. Yeah, they're all excellent points. So yeah, I mean, Russia was, I think, many experts. I mean, my mentor at Princeton, Stephen Kalkin, was then writing great things about how, if you look at Russia's economy, the scale of its GDP, its capacity to actually act globally, it's all quite limited. But Condoleezza Rice and the people around her came into power with George W. Bush, thinking that the foreign policy challenges of her era would be those of the past, right? Richard Clarke and others within the administration warned that, in fact, there is this group that has declared war against the United States and they are coming for us. The FBI had been following these people around for many months. So by the time George W. Bush comes to power, lots of Al-Qaeda activists, well, not lots, but perhaps a dozen or so, are already training in the United States, right? And what we knew immediately from the biographies of some of the characters of the attackers of 9-11, it was a hodgepodge of people from across the planet, but most of them were Saudi, right? And that was known very early on, or presumed very early on. So again, if we go back to your big question about the geography, why Afghanistan, it didn't add up, it seemed to me that Afghanistan was a kind of soft target. It was a place to have explosions, to seemingly recapture American supremacy. And also I think there was, in many quarters, there was a deep urge for revenge. And this was a place to have some casualties, have some explosions. And then I think, restore the legitimacy of the Bush administration by showing that we're in charge, we'll pay. And I think that was a very old-fashioned, punitive dimension, which rests upon the presumption that if we intimidate these people, they'll know not to try us again, right? All these, I would suggest, are all misreadings of an organization that was always global. It had no real center. I mean, it called itself the center, that's one way to translate Al-Qaeda. But that center was really in the imagination. Bin Laden bounced around from country to country. And crucially, I think a dimension that I don't claim to know anything new about, but has endured as a kind of doubt, is the role of Saudi Arabia, and the fact that the muscle in that operation of 9-11 was Saudi, right? I mean, this was a Saudi operation with, if one thinks again, just on the basis of nationalities, Saudis, an Egyptian or two, a Lebanese guy, and the Egyptian guy had been studying in Germany. He was an urban planner, right? So if one thinks of the imagination of this, I mean, and in fact, if you look at the kind of typology of the figures who have led this radical movement, I mean, if you think of the global jihadists, they are mostly not religious scholars, right? Bin Laden was not a religious scholar. His training was an engineer. Some biographers claim that he was a playboy for much of his youth. But really, these ideas, I think that's probably why they chose the Twin Towers. I mean, this is an imagination fueled by training and engineering. I mean, a lot of the sociology, if you do a kind of post-pacography of a lot of these leading jihadists, their backgrounds are not in Islamic scholarship, but actually in engineering and kind of practical sciences and professions. Medical doctors are among their ranks. And so there's long been a tension between Islamic scholars who devote their whole lives to study of texts and commentary and interpretation. And then what some scholars call kind of new intellectuals, new Muslim authorities, who actually have secular university educations, often in the natural sciences or engineering and technical fields, who then bring that kind of mindset, if you will, to what Muslim scholars call the religious sciences, which are a field of kind of ambiguity and of gradation and of subtlety and nuance and really of decades of training before one becomes authoritative to speak about issues like whether or not it's legitimate to take someone else's life. With the relation to Afghanistan, who was bin Laden? Bin Laden was a visitor. If you look at his whole life course, part of it is an enigma still. You know, he is from a Saudi elite family, but a family that kind of has a Yemeni Arabian sea kind of genealogy. So the family has no relationship to Afghanistan past or present, except at some point in 1980s, when he went like thousands of other young Saudis, first to Pakistan, to places like Peshawar on the border, where they wanted to aid the jihad in some capacity. And for the most part, the Arabs who went opened up hospitals, some opened up schools. The bin Laden family had long been based in engineering construction. So it's thought that he used some of those skills and resources and connections to build things. You know, we have images of him firing a gun for show. Right? It's not clear that he ever actually fired a gun in what we would call combat. Again, I could be corrected by this. And I think there are competing accounts of who he was. So he's kind of a, I mean, these figures that he said at the pinnacle of this world are, you know, fictive heroes that people map their aspirations onto. Right? And so people like Mullah Omar, who was then head of the Taliban, was rarely seen in public. The current head of the Taliban is almost never seen in public. I mean, there's a kind of studied Arab mystery that they've cultivated to make themselves available for all kinds of fantasies. Right? Do you think he believed, so his religious beliefs, do you think he believed some of the more extreme things that enable him to commit terrorist acts? Maybe put another way, what makes a man want to become a terrorist? And what aspect of bin Laden made him want to be a terrorist? Right. Right. I mean, let me offer some observations. I think, you know, there are others who know more about bin Laden and have far more expertise in Al-Qaeda. So I'm coming at this in an adjacent way, kind of from Afghanistan and from my historical training. So this is my two cents. So, you know, bear with me. I don't have the authoritative account. Which in itself is fascinating because you're a historian of Afghanistan and the fact that bin Laden isn't a huge part of your focus of study just means that bin Laden is not a key part of the history of Afghanistan, except that America made him a key part of the history of Afghanistan. I would endorse that. Definitely, that's it. I mean, you've put it in a very pithy way. Yeah, so listen, he was an engineer. He was said to be a playboy. He spent a lot of cash from his family. You know, like many young Saudis and from some other countries, he was inspired by this idea that there was jihad in Afghanistan. It was gonna take down one of the two superpowers, the Soviet Union, who, you know, the Red Army did murder hundreds of thousands, perhaps as many as 2 million Afghan civilians during that conflict. It's very, you know, plausible and very, you know, completely understandable that many young people would see that cause as, you know, the righteous, pious fighters for jihad who call themselves mujahideen, arrayed against this evil empire, right, of a godless Soviet empire that, I mean, there's even confusion about what the Soviets wanted. Right now, we know much more about, like, what the Kremlin wanted, what Brezhnev wanted, and how the Soviet elite thought about it because we have many more of their records. But from the outside, you know, for Jimmy Carter and then for Reagan, it looked like the Soviets were making a move on South Asia because they wanted to get to the warm water ports, you know, which Russians always want, supposedly, right? And it was kind of a move to take over our oil and, you know, to assert world domination, right? So there are lots of ways in which this looked like good versus evil. In Congress, it looked like, you know, kind of Vietnam again, but this time, this is our chance to get them. And there are lots of great quotes, I mean, disturbing, but really revealing quotes that American policymakers made about wanting to give the Soviets their Vietnam. And so the CIA funneled, you know, hundreds of millions of dollars into this project to back the mujahideen, you know, who Reagan called freedom fighters. And so Bin Laden was part of that universe. He's part of that, you know, he's swimming in the ocean of these Afghan mujahideen who out of size, you know, did 95% of the fighting. They're the ones who died. They're the ones who defeated the Red Army, right? The Arabs who were there did a little bit of fighting, but a lot of it was for, you know, their purposes. It was to get experience. It was to kind of create their reputations. Like Bin Laden began to force for himself of being spokesman for a global project because by the late 80s, when Bin Laden, I think was more active and began conspiring with people from other Arab countries, the idea that, you know, Gorbachev came to power in 85. He's like, let's get out of here. This is draining the Soviet budget. It's an embarrassment. We didn't think about this properly. Let's focus on restoring the party and strengthening the Soviet Union. Let's get out of this costly war. You know, it's a waste. It's not worth it. We're gonna lose anything by getting out of Afghanistan. And so their retreat was quite effective and successful from the Soviet point of view, right? It's not what we're seeing now. What year was the retreat? I mean, it began, so Mikhail Gorbachev came to power in 85. You know, he was a generation younger than the other guys. He was a critic of the system. He didn't wanna abolish it. He wanted to reform it. He was a true believer in Soviet socialism and in the party as a monopolist, right? But he was critical of the old guard and recognized that the party had to change and the whole system had to change to continue to compete. And so Afghanistan was one element of this. And so he pushed the Afghan elites that Moscow was backing to basically say, listen, we're gonna share power. And so a figure named Najibullah, who was a Soviet trained intelligence specialist sitting in Kabul agreed. And he said, we need to have a more kind of pluralistic accommodations approach to our enemies who are backed by the US mainly, sitting in Pakistan, sitting in Iran, backed by these Arabs to a degree, getting money from Saudi. And he said, let's draw some of them into the government and basically have a kind of unity government that would make some space to the opposition. And for the most part, with US backing, with Pakistani backing, with Iranian backing, and with Saudi backing, the opposition said, no, we're not going to reconcile. We're gonna push you off the cliff. And so that story goes on from at least 1987. The last Soviet Red Army troops leave early 1989. But the Najibullah government holds on for three more years. It is the, I mean, they're still getting some help from the Soviet Union. Its enemies are still getting help from the US mainly. And it's not until 1992 that they lose. And then Mujahideen come to power. They immediately, they're deeply fractured. And that's where Bin Laden is watching all of this unroll. That's right, and he's part of the mix, but he's also mobile. So he at one point goes, is in Sudan. He's moving from place to place. His people are all over the world. In fact, I mean, if you think of the, once the Mujahideen take power, they have difficulties with Arab fighters too. And they don't want them coming in and messing with, the Mujahideen regard this as like, this is an Afghan national state that we're gonna build. It's gonna be Islamic. It's gonna be an Islamic state, but you can't interfere with us. And so there are always tensions. And so the Arabs are always kind of, I would say they were, the Arab fighters were always interlopers. Yes, the Afghans are happy to take their money, send patients to their hospitals, take their weapons, but they're never gonna let this be like a Saudi or Egyptian or whatever project. But then many of those fighters went home. They went back to Syria. They went back to Egypt. Some wanted to go back to Saudi Arabia, but the Saudis were very careful. I mean, the Saudis always used Afghanistan as a kind of safety valve. In fact, they had fundraisers on television. They chartered jets. They filled them with people to fly to Pakistan, get out in the shower and say, go fight. And it was one way that the monarchy, the Saudi monarchy, very cleverly, I think, created a kind of escape valve for would-be dissidents in Saudi Arabia. Just send them abroad. You wanna fight Jihad, go do that somewhere else. Don't bother the kingdom. But all this became dicier in the early 90s when some of these guys came back home and some of the scholars around them said, let's, we've defeated the Soviet Union, which is a huge, huge boost. And I think part of the dynamic we see today is that the Taliban victory is a renewed inspiration for people who think, look, we beat the Soviets, now we beat the Americans. And so already watching the Soviet retreat across this bridge back into Uzbekistan, if you see these dramatic images of the tanks moving, a lot of people interpreted this as like, we are going to change the world. And now we're turning to the Americans. And our local national governments are backed by the Americans. So let's start with those places. And then let's go strike the belly of the beast, which is America, which is New York. And going back to Bin Laden, your question about what motivates him, what motivated him, again, he was not a rigorously trained Islamic scholar. And that, I think, when this comes up in our classes, I think, especially young people, I mean, people who weren't even born on 9-11, I mean, they're shocked. They see his appearance. They see him pictured in front of a giant bookshelf of Arabic books. He's got the Kalashnikov. He's got what looks like a religious scholars library behind him, right? But if you look at his words, I mean, one fascinating thing about just our politics and just one thing that kind of sums all this up, I mean, the fact that on 9-11, we had to have a few people, a few experts, people like Barnett Rubin, who was an Afghanistan expert. So that was one way in which I think, I'm not faulting him personally, but it's just one way in which that relationship appeared to be formed, right, of linking Afghanistan to that moment. If one looks actually at what Bin Laden was saying and doing, people like Richard Clarke were studying this. There were Arab leaders. The Arab press was watching this because he gave some of his first interviews to a few Arab newspaper outlets. But speaking of our American kind of monolingualism, a lot of what he was saying wasn't known. And so I think for several years, people weren't reading what Bin Laden said. I mean, experts are reading it in Arabic, but there was great anxiety around translating his works. So we have Manconf, we have all this other stuff. You can buy the collected works of Lenin, Stalin, Mao, whatever you want in whatever language you want. But Bin Laden was taboo for American publishing. And so it was only Verso in the UK that published a famous volume called Messages to the World, which was the first compendium of Bin Laden's writings. So he has a Manconf. He has a type, does he have a thing where he- I mean, it's a kind of collected works. It's a collected works of his- Okay, so he had like a blog. Yeah, yeah, yeah. It's a collection of articles versus- Yeah, these are interviews. These are his missives, his declarations, his decrees, right? But I think just in terms of, if we zoom out for a second about American policy choices and so on, the powers that be didn't trust us to know what he was really about. I put it that way. And I don't say that in a conspiratorial sense. I just think that it was a taboo. I think people, there was a kind of consensus that, trust us, we know how to fight Al Qaeda. And you don't need to know what they're about because they're crazy. They're fanatics, they're fundamentalists. They hate us. Remember that language? Yeah. Us versus them. But if you read Bin Laden, that's when it gets messy. That's where Bin Laden's argumentation is not fundamentally about Islam. And if you're sitting here with an Islamic scholar, he would say, depending on which Islamic scholar, they would tend to go through and dissect and negate 99% of the arguments that Bin Laden claimed was in Islam, right? But what strikes me as an historian, who's again, looking at this adjacently, if you read Bin Laden, I mean, the arguments that he make are, first of all, they're sophisticated. They reflect a mind that is about geopolitics. He uses terms like imperialism. He knows something about world history. He knows something about geography. So imperialism is the enemy for him? Or what's the nature of the enemy? It's an amalgam, and like a good politician, which is what I would call him, he is adept at speaking in different ways to different audiences. So if you look at the context in which he speaks, if you look at messages to the world, if you look at his writings, and you can zoom out now, and we now have compendia of the writings of Al-Qaeda more broadly. You can purchase these. They're basically primary source collections. We now have that for the Taliban. I mean, what's fascinating about, I think, if you'd like this culture, acknowledging it's very diverse internally, is that these people are representatives of political movements who seek followers. They speak. They often are very, I'd say, skilled at visual imagery. And especially now, I mean, what's fascinating is that, I mean, the Taliban used to shoot televisions. They used to blow up VCR, videotapes. They used to string audio and video cassettes from trees and kind of ceremonial hangings, right? That were killing this nefarious, infidel technology that is doing the work of Satan. And yet today, one of the keys to the Taliban's success is that they got really good at using media. I mean, brilliant at using the written word, the spoken word, music, actually. And Hollywood, Hollywood is the gold standard. And these guys have studied how to create drama, how to speak to modern users. I mean, Islamic State did this. I mean, the role of media, new media. I mean, I follow and I am followed by senior Taliban leaders, which is bizarre on Twitter. On Twitter? I don't know why they care about me. I'm nothing. They follow you on Twitter. I don't know why. This is no joke, this is no joke. They are part of our modern world. It's how they talk and it's how they recruit. And this is part of the, this is why they are. So Bin Laden, if you read Bin Laden, he speaks multiple languages, I would say. It's environmentalism. The West is bad because we destroyed the planet. The West is bad because we abuse women. So in class, especially female students are very surprised to learn, and actually say, this feminist argument is not, we start with, this is a murderer. This is a person who has taken human life, innocent life over and over again. And he is aspirationally genocidal. But let's try to understand what he's about. So we walk through the texts, read them, and people are shocked to learn that it's not just about quotations from the Quran strung together in some irrational fashion. He knows, I mean, at the core, I'd say is the problem of human suffering. And he has a geography of that that is mostly Muslim, but he talked about the suffering of Kashmir. All right, so if you have a student in your class who's from South Asia and knows about Kashmir, you know, he or she will say, that's not entirely inaccurate. The Indian state commits atrocities in Kashmir. Pakistanis have done that too. Palestine is an issue, right? So you have, in the American university setting, people across the spectrum who get that, you know, Palestinians have had a raw deal. And so it's a, victimhood is essential, and it's Muslim victimhood, which is primary, but as a number of scholars have written, and I'm, you know, I definitely think this is a framework for what this useful, I mean, in this kind of vocabulary, in this framing, this narrative, today, in today's world, if we think of today's world being post-Cold War, 91 to the present, looking at the series of Gulf Wars, and seeing the visuals of that, I think that, you know, I think the American public has been shielded from some of this, but if you look at just the carnage of the Iraqi army that George H.W. Bush produced, right? Or you think of, you know, the images of the suffering of Iraqi children under George H.W. Bush's sanctions, US-British airstrikes, then you have Madeleine Albright answer a question on 60 Minutes saying, do you think, you know, the deaths of half a million Iraqi kids is worth it? You know, is that justified to contain Saddam Hussein? And she says on camera, yes, it's worth it to me. If you put that all together, I mean, American kids, and of course, the American public, they're not always aware of those facts of global history, but these guys are, and they very capably use these images, use these tropes, and use facts. I mean, so many things are not deniable. I mean, these estimates about the number of Iraqi civilian children dead, you know, that came from, I think, the Lancet, and it came from, those are estimates. But looking at this from the point of view of Amman, of, you know, Jaffa, of Nairobi, you know, just think around the planet. If you see yourself as the victim of this great imperial power, you know, you see why, especially young men, would be drawn to a road of self-sacrifice, and the idea is that in killing others, you are making them feel how you feel. Because they won't listen to your arguments reasonably, because they won't, you know, recognize Palestinian suffering, Bosnian suffering, right? Chechen suffering. You go across the planet, right? Because they won't recognize our suffering, we're gonna speak to you in the only language that you understand, and that's violence. And look at the violence of the post-1991 world, right? In which American air power really becomes a global, you know, kind of fact in the lives of so many people. And then the big mistake after 9-11, among many, I mean, fundamentally was taking the war on terror to some, you know, 30 or 40 countries, right? So that you have more and more of the globe feel like they're under attack, right? And the logic is that essentially it's not, it's free bin Laden, it's not we're going to convert you and turn you into Muslims, and that's why we're doing this. That appears, that claim does appear at times. But it's, if you look at any given bin Laden text, I mean, there are 40 claims in each text. I mean, it's kind of, it's dizzying, but he's a modern politician, he knows the language of social equality, you know, that there's a class dimension to it, there is an environmental dimension to it, there's a gender dimension to it. And yes, there are chronic quotes sprinkled in. And when he wants to speak that language, he knew that, you know, he's not a scholar. So he would often get a few recognized scholars to sign on. So some of his declarations of jihad had his signature kind of sprinkled in with like a dozen other signatures from people who are somewhat known or at least, you know, with titles, right? So as a kind of intellectual exercise, it's fascinating to see that he is throwing everything at the wall in one level. That's one way to see that it's a, these are kind of testaments toward recruitment of people who, yes, they're angry, yes, they're unhappy. And this is what, you know, I think for our broader public, it's hard to get, you're like, well, bin Laden didn't suffer. He wasn't poor. Like, yeah, I mean, Lenin, Pol Pot. I mean, they're speaking to, they're empathetic to the suffering, the landscape, the full landscape of suffering. It's interesting to think about suffering, you know, America, the American public, American politicians and leaders, when they see what is good and evil, they're often not empathetic to the suffering of others. And what you're saying is bin Laden perhaps accurately could speak to the ignorance of America, maybe the Soviet Union, to the suffering of their people. That's right. And I mean, if you look at the speeches and the ideas that are public of Hitler in the 1930s, he spoke quite accurately to the injustice and maybe the suffering of the German people. It, I mean, charismatic politicians are good at telling accurate stories. It's not all fabricated, but they emphasize certain aspects. And then the problem part is the actions you should take based on that. Right, right. So the narratives and the stories may be grounded in historical accuracy. The actions then cross the line, the ethical line. I thought that too. I mean, it's a, again, if you pick up just one of these texts I mean, it's a kaleidoscope. So the Hitler analogy is interesting because it's, you know, Hitler spoke to, he could speak to things like inflation, right? Which really existed. But he also appealed to the irrational emotions of Germans, right? He sought out scapegoats, you know, Jews, Roma, disabled people, homosexuals, and so on, right? That's also there in bin Laden too. I mean, the idea of, you know, an anti-Semitism, the constant flagging of Zionists and crusaders. It's a kind of shotgun approach to a search for followers. But I also hasten to add that it's, for all of the things that we could tick off saying, well, yes, Kashmiris have suffered, Chechens have suffered and so on. Bin Ladenism never became a mass movement. I mean, it never really, I think that, I mean, this is the encouraging thing, right? About ideology. I mean, I think the blood on his hands always limited his appeal among Muslims and others. But bin Laden did have, I mean, he had a, there's a great book by a great scholar at UC San Diego, Jeremy Prestholt, who wrote a great book about global icons in which he has bin Laden, he has Bob Marley, he has Tupac, you know, he asked why, you know, when he was doing research in East Africa, why did he see young kids wearing bin Laden shirts? They're also wearing like Tupac shirts. They're wearing bin Bob Marley shirts. And basically it's a way of looking at a kind of partial embrace of some aspects of the rebelliousness of some of these figures, some of the time by some people under certain conditions. Well, the terrifying thing to me, so yeah, there is a longing in the human heart to belong to a group and a charismatic leader somehow, especially when you're young, just a catalyst for all of that. And I tend to think that perhaps it's actually hard to be Hitler. So a leader so charismatic that he can rile a nation to war. And bin Laden, perhaps we're lucky, was not sufficiently charismatic. I feel like if his writing was better, if his speeches were better, if his ideas were stronger, better, it's like more viral, and then there would be more people, kind of young people uniting around him. So in some sense, it's almost like accidents of history of just how much charisma, how much charisma a particular evil person has, a person like bin Laden. I think it's fair, evil works, I think. Do you think bin Laden is evil? Oh yeah, yeah, yeah. I mean, he was a mass murderer. I'm just saying that his ideas were, they're more complex than we've tended to acknowledge. They have a wider potential resonance than we would acknowledge. I mean, and also I guess just one fundamental point is that thinking about the complexity of bin Laden is also a way of removing him from Islam. He is not an Islamic thinker. He is a cosmopolitan thinker who plays in all kinds of modern ideologies, which have proven to mobilize people in the past, right? So anti-Semitism, populism, environmentalism, and the urging to do something about humanity, do something about suffering. That's why I think the actual, you asked about what motivates people to do this kind of stuff. I think that's why if one goes below the level of leadership and this is being reported, if you look at the trial ongoing now in Paris of the Baraklan murders, I think, the court allowed some discussion of the backgrounds of the accused and they come from different backgrounds, but if there's any common bond, it's kind of that they had some background in petty crime. Famously in the 7-7 bombings in London, the Metropolitan Police, UK authorities looked at all those guys and what people want is this idea that they must be very pious. They must be super Islamic to do this kind of stuff. They must be fanatical true believers, but what they found with those guys was that some were nominally Muslim, some went to mosques, some didn't. Some were single, young guys with criminal backgrounds. Some were like, sorry, they were kind of misfits who never succeeded in anything, but others had, at least one of them had a wife and family who he widowed and orphaned. And so there's no, I mean, for policing, I mean, if you're looking at it through that lens, there is no kind of typology that will predict who will become violent. And that's why I think we have to move beyond thinking about religious augmentation narrowly or by itself and think about things like geopolitics, think about how people respond to inequality, the existential threat of climate crisis, of a whole host of matters, and think about this is a mode of political contestation. I mean, it's a violent one, it's one I condemn, it is evil, right? But these are people that are, they're trying to be political, they're trying to change things in some way. It's not narrowly about like, I'm gonna impose Sharia law on you, you must wear a veil, you must eat this kind of food. It's not that parochial. But another quick thought about your interesting claim about charisma in this, I think that the one self-limiting feature of this subculture is that definitely, I mentioned the enigma of not wanting to be seen and that the kind of invisibility is a productive force of a power, which a colleague of mine who knows ancient history far better than I, said this is when she looked at Mullah Omar initially, or we come up in Laden, I mean, this kind of studied posture of staying in the shadows, is also a source of authority potentially, because it invites the idea, and it's partly dictatorships do this well, I mean, it invites the idea that someone's working, and maybe it's the basis for a lot of QAnon or other conspiracy today, that someone's working behind the scenes and things are gonna go the right way, you can't see it. That's almost preferable because you can kind of feel it. And so not having someone out front can maybe be more effective than having someone out in front constantly. Then the whole- Maybe, maybe. And then the whole Bin Laden, Mullah Omar thing like you can't see me, or if you look at Bin Laden's photographs and his video stuff, I mean, he's coy. Some observers have noted that he's kind of effeminate. He doesn't strike this kind of masculine, he's not a Mussolini, he's not a Hitler, macho, I'm standing, dumping my chest, he's not doing the theatrical chin, the theater people tell us is so aggressive. Oh, a chin? Just what, bringing your chin up? I saw a great BBC theater person, it was kind of a makeover show about how to become- A better hitter? Oh no, a powerful leader, authoritarian figure? No, just how to get ahead in life. And then- Oh, okay, cool. Just about acting, how you can act differently, right? So it was a BBC thing. And this woman claimed that sticking your chin out like a wrestler does, right, is the most, like middle to middle- I love this kind of- Most aggressive. Hilarious analysis that people have about power. But watch the chin, watch the chin. It's the same as analyzing in wrestling, styles that win, or fighting, or so on. There's so many ways to- Well, the chin, I mean, the chin is a, could be interesting in verbal gesture. And I've watched enough Mussolini footage from my classes to try to pick the right moment. And the chin is, Mussolini's all about the chin, so. And I have watched human beings and human nature enough to know that there's more to a man, a powerful man, than a chin. Yeah, no, no, no, I'm saying it's an act of aggression. I'm not saying it's- It's one of the many tools in the toolkit. Yeah, yeah, sure, yeah. So she definitely- It's not all about the chin, but it's a- But that's what I'm trying to tell you about Bin Laden. I don't think he was deliberate enough with the way he presents himself. What I'm saying about Bin Laden that makes him different from these other characters is that because he played it being the scholar, he played it being a figure of modesty and humility. And that meant that he was often, again, if you watch his visuals, I mean, yes, there's one video of him firing a gun, but if you watch how he moved, how he wouldn't look at people directly, how his face was almost, I mean, he appears to be incredibly shy. He's all spoken, his voice was low. He attempted to be poetic, right? So it wasn't a warrior kind of image that he tried to project of like a tough guy. It was, I'm demure, I'm humble, I'm offering you this message. And the appeal that he was going for was to see, to project himself as a scholar whose knowledge and humility, the whole package, carried with it an authenticity and a valor that would animate, inspire people to commit acts of violence, right? So it's a different kind of logic of like go and kill, right? So he presented himself in contrast to the imperialist kind of macho power. Bombastic, whatever, yeah. So that's just yet another way of, and you have to have facial hair or hair of different kinds that's recognized. We had a very recognizable look too, or at least later in life. So yeah, no, he tried to look the part. Yeah, yeah, yeah. But I'm saying we're fortunate that whatever calculation that he was making, he was not more effective. Yeah. I mean, there's, the world is full of terrorist organizations and we're fortunate to the degree, any one of them does not have an incredibly charismatic leader that attains the kind of power that's very difficult to manage at the geopolitical level. Yeah, and we credit the publics, you know, who don't buy into that, right? Who see through this. We credit the critics, you know? Fairly on, going back to 9-11 itself, one of the problems was that US government officials kept kind of leaning on Muslims to condemn this as if all Muslims shared some collective responsibility or culpability. And in fact, dozens of scholars and organizations, hundreds condemned this, but their condemnations never quite made it out. But it created a tension where, you know, if you wore a veil, you must've been one of them and you must be on team Bin Laden. And so a lot of the, you know, I think a lot of the popular violence and discrimination and profiling came out of that urge to see a oneness, which, you know, Bin Laden projected, right? He wanted to say, we are one community, you know, if you are a Muslim, you must be with me, right? But I think that's where the diversity of Muslim communities became important because outside of small pockets, I mean, they didn't accept his leadership, right? People wore t-shirts in some countries. I mean, non-Muslims wore t-shirts because he was like, he stuck it to the Americans. So in Latin America, people were like, yeah, that was sad, but, you know, finally, I mean, there was a kind of schadenfreude in that moment internationally. It's like Che Guevara or somebody like that. Che, yeah, Che's the other character in Pissol's book. Yeah, yeah, that's right, that's right. It's just as simple. It's not exactly what he believed or the cruelty of actions he took. It's more like he stood for an idea of revolution versus authority. That's right. And that's a great way to understand Bin Ladenism and the whole phenomenon, but I think looking at the big picture, it's also, you wonder, will that ever end, right? I mean, is that, I mean, that's the risk of being a kind of hyperpower like the US where you, in insisting on a kind of unipolar world in 2001, 2002, 2003, I think that created an almost irresistible target, you know, wherever the US wanted to exert itself militarily. Before we go to the history of Afghanistan, the people, and I just wanna talk to you about just some fascinating aspect of the culture. Let's go to the end, withdrawal of US troops from Afghanistan. What are your thoughts on how that was executed? How could it have been done better? Yeah, an important question. I mean, I would preface all this by saying, you know, as I noted, I think the war was a mistake. I had hoped the war would end sooner. I think there were different exit routes all along the way. Again, I think there were lots of policy choices in September, in October, when the war began. There were choices in December, 2001. So we could look at almost every six-month stopping point and say, we could have done differently. As it turns out, though, I mean, the way it played out, you know, it's been catastrophic. And I think the Biden administration has remained unaccountable for the scale of the strategic and humanitarian and ethical failure that they're responsible for. Well, okay, let's lay out the full. There's George W. Bush. There's Barack Obama. There's Donald Trump. That's right. There's Biden. Yeah. So they're all driving this van and there's these exits and they keep not taking the exits and they're running out of gas. I do this all the time, thinking, where am I gonna pull off? I'll go to the frictalus empty. How could it have been done better? And what exactly, how much suffering have all the decisions along the way caused? What are the long-term consequences? What are the biggest things that concern you about the decisions we've made in both invading Afghanistan and staying in Afghanistan as long as we have? I mean, if we start at the end, as you proposed, you know, the horrific scenes of the airport, you know, that was just one dimension. I think in the weeks to come, I mean, we're gonna see Afghanistan implode. There are lots of signs that malnutrition, hunger, starvation are going to claim tens of thousands, maybe hundreds of thousands of lives this winter. And I think there is really nothing, there's no framework in place to foresaw that. What is the government, what is currently the system there? What's the role of the Taliban? So there could be tens of thousands, hundreds of thousands that starve, either just almost a famine or starve to death. So this is economic implosion, this is political implosion. What's the system there like? And what could be the one, you know, some inkling of hope? Right, right. The Taliban sit in control. That's unique. When they were in power in the 1990s, from 1996, 2001, they controlled some 85 to 90% of the country. Now they own it all, but they have no budget. The Afghan banking system is frozen. So the financial system's a mess. And it's frozen by the US, because the US is trying to use that lever to exert pressure on the Taliban. And so the ethical quandaries are, of course, legion, right? Do you release that money to allow the Taliban to shore up their rule, right? The Biden administration has said no, but the banks aren't working. If you're in California, you wanna send $100 to your cousin so she can buy bread. You can't do that now. It's almost impossible. There are some informal networks, they're moving some stuff, but there are bread lines. The Taliban government is incapable, fundamentally, of ruling. I mean, they can discipline people on the street, they can force people into the mosque, they can shoot people, they can beat protesters, they can put out a newspaper, they can have, they're great at diplomacy, it turns out, but they can't rule this country. So essentially, the hospitals and the kind of healthcare infrastructure is being managed by NGOs that are international. But most people had to leave, and the Taliban have impeded some of that work. They've told adult women, essentially, to stay home, right? So a big part of the workforce isn't there. So, I mean, the supply chain is kind of crawling to a halt. Trade with Pakistan and its neighbors, I mean, it's kind of a transit trade economy. It exports fruits. Pakistan has been closing the border because they're anxious about refugees. They wanna exert pressure on it, the national community, to recognize the Taliban, because the Pakistan want the Taliban to succeed in power, because they see that in Pakistan's national interest, especially through the lens of its rivalry with India. So the Pakistani security institutions are playing a double game. Essentially, the Afghan people are being held hostage. And so the Taliban are also saying, if you don't recognize us, you're gonna let tens of millions of Afghans starve. So to which degree is Taliban, like, who are the Taliban? What do they stand for? What do they want? Obviously, year by year, this changes. So what is the nature of this organization? Can they be a legitimate, peaceful, kind, respectful government, sort of holder of power, or are they fundamentally not capable of doing so? Yeah, I mean, the briefest answer would be that they are a clerical slash military organization. They have, this is kind of a imperfect metaphor, but years ago, a German scholar used the term caravan to describe them. And that has some attractive elements, because different people who joined the Taliban for different purposes at different times. But today, and people tell us, scholars who know more about the movement than I have said, listen, the Taliban is this kind of hodgepodge of different actors and people and competing interests. And I think, so we have a lot of scholars that say, listen, it's polycentric. It's got people in this city and that city and so on. I think actually, I was always very skeptical. How do they know this? I mean, this is an organization that doesn't want you to know where that money comes from and so on. But I would say, now that we have a clear picture of what has happened, I'd say they were a astoundingly well-organized clerical military organization that has a very cohesive and enduring ideology, which is quite idiosyncratic if we zoom out and continue the conversation we're having about Islam and how we think about radicalism and who's drawn to what. People throw different terms around to describe the Taliban. Some use a term that links it to a kind of school of thought born in the 19th century in India, the Doobandi school. But if you look at their teachings, it's very clear now, I think that these labels, it's like saying, you're an MIT guy. Well, what does that mean? I mean, MIT is home to dozens of different potentially kinds of intellectual orientations, right? I mean, attaching the name of a school doesn't quite capture, I mean, university. It's complicated. I mean, actually, MIT is interesting because I would say MIT is different than Stanford, for example. I think MIT has a more kind of narrow. Yeah, I hear you. Bad analogy on my part, maybe. Well, no, it's interesting because I would argue that there's some aspect of a brand like Taliban or MIT, no relation, that has a kind of interact, like the brand results in the behavior of the, like enforces a kind of behavior in the people and the people feed the brand. And like, there's a loop. I think Stanford is a good example of something that's more distributed. There's sufficient amount of diversity in like all kinds of like centers and all that kind of stuff that the brand doesn't become one thing. And MIT is so engineering. It's so good in that. Okay, scratch MIT, scratch Stanford too, because I think Stanford's more like MIT than you might imagine. But isn't Taliban, isn't it pretty, I don't think there's a diversity. So yeah, sorry, so just to rephrase. So people say, oh, the Deobandi school. I'm like, what is that? I mean, the Taliban are, they're an ethnic movement. They represent a vision of Pashtun power, right? Pashtuns are people who are quite internally diverse, who actually speak multiple dialects of Pashto, who reside across the frontier of Pakistan and Afghanistan. There are Pashtuns who live all over the planet, right? There's a community in Moscow, California, everywhere, right? So it's a global diaspora of sorts. Pashtuns have a kind of genealogical imagination so that lots of Pashtuns can tell you the names of their grandparents, great-grandparents and so on. And that's kind of a, there's a sense of pride in that. Pashto language is a kind of core element of that identity, but it's not universal. So for example, you can meet people who say, I am Pashtun, but I don't know Pashto. So as you claw away at this idea, it's amorphous. It also means different things to different people at different times. So saying the Taliban are Pashtun requires lots of qualifiers because lots of Pashtuns will say, no, no, I have nothing to do with Taliban. I hate those people. So the Taliban tried to mobilize other Pashtuns with limited success, but their core membership is almost exclusively Pashtun. And they say, no, no, we represent Afghans. We represent pious Muslims. And so in recent two, three years, they've gone further to say, no, we have other groups. We have Uzbeks, we have Tajiks, we have Hazaras. And in the north of Afghanistan, in recent years, they did do a bit better at drawing in people who were very disrespected because of the government and they were able to diversify their ranks somewhat. But if you watch this at August 15 and who they've appointed, what language they've used, how they've presented themselves, it's clear that they are Pashtun, they are male, and they are extremely ideologically cohesive and disciplined, I'd say. So I think that a lot of the polycentrism, blah, blah, some of that stuff was a way to fight a war. They are fundamentally a guerrilla movement. They see themselves as kind of pious Robin Hoods. The rhetoric is very much about taking from the rich, taking from the privileged, giving to the poor, being on the side of the underdog, fighting against evil. And so, I mean, their bag, if you like, their thing, their central theme, their brand is about public morality. And so their origin story, going back to 1994, is that they interceded, they broke up a gang of criminals who were trying to rape people. And so there's a very interesting kind of like, if this is on like sexuality and on public morality, it really being the core of like, we're gonna restore order and public morality. And how that translates into governance is something they've never sorted out. I mean, how do you run a banking system? If your intellectual priorities are really about, you know, the length of a beard. And then their path to power, in a kind of abstract sense, I mean, a lot of that was very much driven by, if you like, propagating the promise of martyrdom. And that sounds, I don't mean to say that in a way that, to make it sound ridiculous, to make it sound like it's a moral judgment. It's simply, I think, a fact. It's a fact of their appeal that they promised young men who have known nothing else but studying in certain schools, if at all, but they've known fighting and they've known victimization. And this isn't, I'm not asking for like sympathy for them, but I think the reality is that a lot of the, we know about the kind of foot soldiers is that they, they lost families in bombings, in airstrikes, in night raids, you know, I mean, orphans have always been a stream, living in all-male society, not knowing girls, not knowing women, hearing things from outside about places like Kabul. And so there's always been this kind of urban-rural dimension. It's not just that, but I think there's a whole imagination that being Taliban captures. And the whole margin thing is really, it's, yeah, I think to any religious person, I mean, it's not a bizarre idea. I mean, it animates, I mean, so many global traditions, you know, but I think the, but you try to tell like an army colonel, right, if you were to have a conversation with, you know, a US Marine about this, I mean, some would get it from their own religious backgrounds, but I think the, it's an alien idea, but I think it is essential to kind of stretch our imagination and understand that's attractive. And now one of the dilemmas going forward is that they've got to pivot from martyrdom. And some have been, some have told foreign journalists, I mean, it's good that we're in charge now. We're gonna build a proper state, but I, it's kind of boring. I want to keep fighting. Maybe I'll do that in Pakistan. Yeah, I mean, it's nice that they are expressing that thought, some are not even honest sufficiently with themselves to express that kind of thought. If you're a fighter, you see that with a bunch of fighters or professional athletes once they retire. They don't know, it's very, it's boring. And so like if the spirit of the Taliban, even the best version of the Taliban is to fight, is to be martyrs, is to, and paint the world as good and evil and you're fighting evil and all that kind of stuff that's difficult to imagine how they can run an education system, a banking system, respect all kinds of citizens with different backgrounds and religious beliefs and women and all that kind of stuff. So. Yeah, and they've walked into Kabul and other major cities. If someone are young, they didn't know those places, but also the very important obstacle for them is that Afghan society has changed. I mean, it's not what, even for the older guys, it's not what they knew in the 1990s. Some always had some ambivalence about the capital, but now it's totally different. I mean, they've been shocked to see, I think to me, one of the most striking features of the last few weeks has been that women have come out on the streets and have stood in their faces and said, we demand rights, we demand education, we demand employment. And these foot soldiers are paralyzed. They're not sure. They don't know what to do with women, period. Yeah, yeah. And they don't know what to do with being yelled at and having someone stick their fingers in their faces. I mean, this is not what they've imagined. And so I think, and at this juncture, there are still foreign cameras around. So they have committed acts of violence against women, against journalists. They've beaten people. They've disappeared people. Even with cameras around, even in this tense period. Yeah, but I think that when the cameras retreat and that's not gonna happen, it's gonna get much worse, I think. So the challenge now is, can the Taliban rule? And then this is where the diplomacy is so important because the Taliban can't rule in isolation. And they know that. And part of the success is due to the fact that they were, they became very good at talking to other people in the last, I mean, it's been building for the last decade, but as the last five years, and they always had Pakistan's backing. And so the Taliban are, we noted they're a military force, very effective guerrilla force. They beat NATO. I mean, this is, still hasn't sunk in. I mean, the fact that they, with light arms, using suicide attacks, using mines, improvised explosive devices, machine guns. In some, in recent years, they got sniper rifles. And from the summer, they got American equipment on a broad scale, right? They have airplanes. There's a lot that they will be able to use eventually. So, but still, basically it's a story of AK-47s, some American small arms and mines. So it's very Ho Chi Minh, very old school guerrilla fighting, right? And they defeated the most powerful military alliance in world history, probably. So that has not yet sunk in and what that means for American and global politics. And now they're trying to rule, right? They know they need international support. And their most consistent backer has been Pakistan, who sees them as an extension of Pakistani power. You know, and this is very important for a Pakistani elite that of course is looking toward India. They want to have their rear covered, right? They want to make sure that these postures don't cause trouble for Pakistan. And they like, I mean, for some of the security forces, they like this vision of the Islamic State that the Taliban are building there, because they, those are not citizen from their views of what Pakistan should be. But the Taliban have been smart enough to kind of diversify their potential allies. So everyone in the neighborhood has wanted the US to leave, right? If we go back to 2001, there were Iranian and American special forces in the North working together against the Taliban to displace them using Iranian, American, and then Afghan resistance forces against the Taliban. And that was a real moment of rapprochement if we go back to the missed exits. The relationship with Iran could have been different at that moment, but the US under George W. Bush, you know, devised this axis of evil language, put them together with their enemy Iraq and then North Korea all that went South. That was the most opportunity. But in recent years, the Taliban and Iran have kind of papered over the differences. They allowed the Taliban to open some offices on Iranian territory, likely shared some resources, some intelligence, some sophisticated weaponry. And then the Taliban went to Moscow. And for the Putin administration, they've long been worried that, they see the Taliban as a kind of disease that will potentially move North, infect Uzbekistan, Tajikistan, Kyrgyzstan, Turkmenistan, Kazakhstan, and maybe creep into Russia's sphere of influence. Maybe that's why they have, much troops sitting in Tajikistan. I mean, the one forward base that Russia still has in Central Asia is in Tajikistan. And so the Taliban were always a worrying point, but also useful because they could say, well, you know, in case the Taliban get out of control, we need to be here. And so Tajikistan said, okay, you're helping secure us. And yes, it impinges upon our sovereignty, but it's okay. So Putin said, let's give another black eye to the Americans and let's treat the Taliban as if they're the kind of government in waiting. Let's have them come to Moscow multiple times. This summer, for the last year or two, they've been talking to China. So the photographs of senior Taliban figures going from their office in Qatar, which was a major blow to the Uzbek government, the fact that they were able to open up an office in Qatar that at one point began to fly a flag of the Islamic Emirate of Afghanistan. That basically said we're a state in the waiting. And as the US backed Afghan government failed and failed and failed at ruling too, right? As they showed how corrupt they were. And as they really alienated more and more Afghans by committing acts of violence against them, by stealing from them, by, you know, basically creating a kind of kleptocracy, right? The Taliban said, we are pure, we are not corrupt. And look at us, we're winning on the battlefield. And internationally, look, we're talking to China. We're talking to Putin, we're talking to China. Yeah. We're a legitimate, powerful center of Central Asia. And also kind of, you know, hinting that, you know, we, oh, we have a website. I mean, the whole digital angle is amazing because they began to, and this is important actually, that they had a website which grew more and more sophisticated again, after having, you know, shot televisions and these kind of ceremonial killings of these infidel devices, right? They said, we have a government, we have commissions, we have a complaint line. They lifted all this technocratic language that you get from any UN document, you know, about good governance and all that kind of, you know, generic language that the NGO world has produced for us, right, in English. They reproduced that in five languages on their top-down website. And of course, I'm not saying anyone believed this, but it was like, you know, just put me in, coach. You know, I know the playbook. I know how to run a government. And look, we have an agricultural commission. We have, you know, a taxation system. And again, this idea, and then on the ground, they had their own law courts. And they would creep into a district, assassinate some people, the local authority figures, men of influence, talk to local clerics, either get them on board or kill them and say, you know, this state is corrupt, but we're bringing you justice. This is our calling card. We're bringing public morality and justice. And then to a broader world, they said, you know, yeah, things didn't go perfectly, a whole Al Qaeda thing, you know, we should be kind of do over on that. We're not gonna let anyone hurt you from our territory. We just want to rule and people like us and look. And so if we look at the neighborhood, Iran, even Central Asian states after a while, recognizing they can make some money. I mean, one of the, one thing that Uzbekistan likes about the current arrangement, or they're not hostile to, is that they have all these contracts. They can potentially make some money from, you know, the pipeline dream remains alive, running natural gas, oil to, you know, it was to the Indian Ocean to markets, you know, beyond Central Asia. It's sitting on a couple trillion dollars, probably in mineral resources that China would love to have, of course. And so people are looking at Afghanistan now, after 20 years saying, you know, under American rule, it was a basket case, right? There was immense human suffering, incredibly violent. The world did not start counting civilian casualties in Afghanistan until 2009. I mean, think about that, the war went on for eight years. The Taliban were never really defeated. They just went to Pakistan. They went to the mountains, they went to the woods. And so all these different American operations, as you noted, under Bush, Obama, Trump, and so on, killed countless civilians. The US never accounted for that. We never even counted. Trump escalated the civilian casualties by escalating the air war. But a lot of this was like very ugly on the ground, you know, night raid stuff, where you drop into a Hamlet and massacre people. And then you're not honest about what happened, right? So that dynamic continued to fuel the growth of Taliban from below. So the foot soldiers, they never ran out of foot soldiers. I mean, the US and its allies killed tens of thousands, maybe hundreds of thousands of Taliban fighters over the last 20 years, but they just sprouted up again. And part of that was the kind of solidarity culture, the male bonding of martyrology, of martyrdom, and of revenge, and a sense of the foreign invader. And I haven't taught a ton of US military people, but through the Hoover, they put officers in our classes sometimes, and met a few wonderful army and marine officers who I really enjoyed. You know, we came from the South like me, always had great rapport with them. And they expressed a range of opinions about this. I think that I learned a lot from someone who said, yeah, I mean, I get why they hate us. I get why they're still fighting, because last week we just killed 14 of their fellow villagers. So the officers, the guys on the ground fighting this war, we're not stupid about that. I mean, they got the human dimension of that, and yet no one got off the exit, as you said. People kept driving. But going forward now, internationally, it's critical that they have, I mean, they've had meetings. I mean, what the Taliban have done since August 15th is a lot of diplomacy. They've had meetings, they've had people, they've had Tashkent come, they've had Beijing come, they've had Moscow come. I mean, they've had major visits from Islamabad, from security people, from diplomatic circles. And they're counting on things being different this time. I mean, the first time around, the only people who backed the Taliban by recognition, giving them diplomatic recognition, were the Saudis, Pakistanis, and the UAE. And because of Al-Qaeda, because of opium, because of some of the human rights stuff, you know, the US pushed everyone to like, let's not recognize this state. Even though the US did, I mean, Colin Powell famously, in the summer of 2001, you know, we did give a few grants and aid to the Taliban. As I kind of like massaging negotiations, they kept talking about Bin Laden, but they also wanted them to stop opium production. I mean, Afghanistan throughout all this period we've talked about is the global center of opium production. I mean, over the years, more and more of the Afghan economy continued to today is devoted to the opium trade. Opium, which is the thing that leads to heroin, some of the painkillers. And even if Afghan poppies don't make it to Hoboken, you know, they are not the source of American deaths. You know, they are part of a universal market, a global market, which, you know, I think any economist will tell you is part of the story of our opium problem. Something I read maybe a decade ago now, and I just kind of looked it up again to bring it up to see your opinion on this, is a 2010 report by the International Council on Security and Development that showed that 92% of Afghans in Helmand and Kandahar Province know nothing of the 9-11 attacks on US in 2001. Is this at all representative of what you know? Is this possible? So basically, put another way, is it possible that a lot of Afghans don't even know the reason why there may be troops or the sort of American provided narrative for why there's troops, American soldiers and American drones overhead in Afghanistan? Right. I mean, my gut response, not knowing the details of this actual poll, is that that's a very unhelpful way to think about how Afghans relate to the world. And I think, you know, it could be, you know, if you go to my hometown in North Carolina, if you knock on some doors, you may meet people who don't know all kinds of things. I could probably walk around this neighborhood here in California and there'd be all kinds of people who don't know all kinds of things. You know, Kyrie Irving apparently thinks the earth is flat. I mean, you know, so we could make a lot of certain kinds of ignorance, I think. But I think what I would say, and then there's also, I mean, a companion point may be that in thinking about the withdrawal, the collapse, the return of the Taliban, there's been a big conversation about, you know, what do Afghans think of us really? And this famous piece in the New Yorker was about how, you know, many people liked the Taliban, you know, that many women interviewed, supposedly, in this piece, you know, were sympathetic because they'd lost family members and all the violence. And the idea kind of was that, you know, we haven't thought about that at all when in fact, you know, of course we have and lots of people have, but I think if you're just dropping into the conversation, if you look at like an immediate arc of coverage of Afghanistan and the United States, I mean, the arc went from lots of coverage during, of course, 9-11 and its aftermath, lots of coverage during Obama's surge, and then quickly dropped down. The last decade has been almost nothing. So if you ask the same question about Americans, or other Americans, I'm not sure what they would say to you, what percentage would actually know why the US is in X, Y, or Z either, right? But again, the Afghan side, just to return to that for a moment, I think that, you know, we can fetishize these provinces. They are a kind of, you know, a place where Taliban support has been greatest. Also where there's been the most violence, where the Americans have been most committed to trying to root out the Taliban movement. Where- This is Helmand and Kanawha. Exactly, in the South. What are the other parts, in the South of Afghanistan? Yeah, and it's mostly Pashtun, not exclusively, but mostly Pashtun, mostly rural. What is Pashtun? That's the other group, you know, that the Taliban claim to represent, right? So they are this group- What other groups are there? Okay, sorry, yeah, yeah, sorry. So in cities, you'll find everything, right, that is in Afghanistan. You'll find Uzbeks, Tajiks, Hazaras. These are people who, you know, Uzbek is a Turkic language, right? Most Uzbeks live in what is now Uzbekistan, but they form majorities in some northern parts of the city. I'm sorry, of the country of Afghanistan. But what I emphasize is that, and you can find online an ethnographic map of Afghanistan, and you'll see green where Pashtuns live, red where Hazaras live, orange where Uzbeks live, you know, purple where Tajiks live. Then there are a bunch of other smaller groups of different kinds. You know, there are Noristani, there are Baluch, there are, in different religious communities, there are Sunni, Shia, different kinds of Shia. What are the key differences between them? Is it religious basis from the origins of where they immigrated from? And how different are they? So they're all, I mean, they're all indigenous, I think. I mean, there's a kind of mythology that some groups have been there longer, right? So they have a greater claim to power. But historically, I mean, it's like, you know, ethnic groups anywhere, people have different narratives about themselves. But many Pashtuns would tell you, not all, but many would say, we are the kind of state builders of Afghanistan, the dynasty that ruled much of the space, that was born in the mid 18th century, that ruled until 1973, more or less, generalizing, you know, it was a Pashtun dynasty. The Taliban have definitely said, to some audiences, we are the rightful rulers because we are Pashtun. The trick though is, I don't mean to be evasive, but just to get away from the complexity, one quick answer as well, they're majorities and minorities. I mean, one finds that a lot along with those maps, but I would say, suspend any firm belief in that because that could be entirely wrong. In fact, there's never been a modern census of Afghanistan. So when journalists say Pashtuns are the majority, or they're the biggest group, I would say not so fast. I would say not so fast because of migration is one major issue. No major modern census. Actually, the Soviets got pretty close, but didn't quite, you know, find something comprehensive and didn't publicize it, knowing that it was, you know, modern times, ethnicity can be the source of political mobilization. It's not innately so, but it's been part of the story. But then you have mixed families, right? So a lot of people you'll meet, you'll encounter in the diaspora and around. I mean, well, I am, you know, my one parent is Tajik, one is Pashtun, right? Or I'm Pashtun, as I mentioned before, but I don't speak Pashto, right? Or I am Hazara, but you read about us as Shi'i Hazaras. In fact, I'm a Sunni Hazara. Or I'm a secular Hazara, or I'm an atheist Hazara. I mean, everything's possible, right? One of my friends, if he were here, he'd say I'm Kabuli, you know, I'm from Kabul. So if you think about it in Russian terms, you know, it means a lot if you're a Muscovite, you know, if you're from Bizer or Moscow, I mean, you know. Yeah, well, even here, there's Bostonians, Texans, Californians. Yeah, yeah, East Coast, West Coast, all that stuff. Those are all part of the mix here. So you asked about Kandahar and Helmand, then I would say, yeah, if you go out to, you know, a pomegranate field, you'll meet a guy who may reckon time differently from you and me, who may not be literate, he may not have ever had a geography lesson, but if you go one door over, you may meet a guy who, you know, whose life path has taken him to live in, you know, six countries. He may speak five languages. And these are all things I'm not saying, they're all, these are just because people have money can go fly around. I mean, there are people who are displaced by war from late 1970s, right? Even already in the early 70s, people were traveling by the tens of thousands to Iran, you know, as labor migrants. And once you get to Iran, once you get to Pakistan, once you get to Uzbekistan, you then connect to all kinds of cosmopolitan cultures. And in fact, I think one of the themes of the book, you know, that you may have read, it may put you to sleep, you know, Afghan modern was about, you know, conceptualizing Afghanistan as a cosmopolitan place where for centuries people went on the move and trade in this area. You think of, you know, I think this mischaracterization of places like Helmand and Kandahar, you know, you fly in or you're part of a Marine battalion and you see people there and they look different. And I think in our imagination, if I can generalize, you know, they look like they've been there for millennia, right, the dress, the whatever, right? You think of technology, you think of the mud compounds and so on. You think of, you know, animal drawn transportation, that kind of stuff, right? Or the motorbike, right, at most is what they have. But in fact, if you, all those families, their trade has taken them to Northern India for centuries, right? The trade has connected them to cosmopolitan centers. You know, say they have a scholar in the family, that scholar may have studied all over the Middle East, South Asia, right? You know, their ancestors may have been horse traders who went all the way to Moscow, right? I mean, we have historical records of all these people traveling across Eurasia, pursuing all kinds of livelihoods. And so Afghanistan is this paradox of visually looking remote and looking like it's kind of stuck in time, but the family trajectories and the current trajectories are astoundingly cosmopolitan and mobile. And so, and a conception of being a world center is also quite strong. So, you know, another way to frame that question about like, do they know about 9-11 would be like, why should we know about 9-11? Because we are at the center of something important, right? We are the center of Asia, we are the heart of Asia. We have a kind of historic greatness. We are, you know, a proud culture of our own achievements. Right, so we're not worried about that, right? That said, I mean, sure, there are different narratives about why Americans are there, why people are being killed. You know, of course you'd find, you know, they want to convert us, you know, they want our gold, they want our opium, they want X, Y, and Z, right? There was a recent story about a Taliban official sitting in an office in Kabul, and a journalist asked him, can you find in this rotating globe, find your country, find where we're sitting right now. And he was filmed not being able to do it. And so a lot of, you know, race-fiscated Afghans in the diaspora were saying, you know, ha ha, look at this. And that exists. I mean, I think I could go to my Stanford classroom and there'd be a lot of kids who wouldn't know where Afghanistan is too, right? But I guess I wouldn't use those metrics to suggest that this is a place that doesn't have a sense of its place in the world and of geopolitics. I think if anything, being a relatively small country in a very complicated neighborhood, I mean, everybody, every cab driver, I mean, people have a, I mean, you know, this is where America is different because I don't think Americans have this sense. You know, we're talking about Moscow and stuff. I think, you know, Moscow cab drivers, I think a lot of them are gonna tell you, like, what's happening in the world and why, right? And it's just part of, it's part of their thing, right? You can find that in Ghana, you can find that in Mexico City, right? You find that lots of places. So I think Afghans are part of a very sophisticated kind of mapping of the world and where they fit in. And a lot of them remarkably had done it firsthand, which is what struck me so much. And, you know, really my experiences from the 1990s in Tashkent places that these guys had already lived in more countries than I'd ever been. They already knew half those languages. I mean, this one friend's Russian was impeccable. And of course it helped, they had Russian girlfriends. They had, you know, they mixed with the police, they had run-ins, I mean, this wasn't something you got from a book, right? This was like hard knock life. I mean, one friend was from a wealthy family in the trading diaspora and he was imprisoned. I mean, they sent him to prison in Pakistan and he talks about how he started like running the jail, you know, taking cigarettes to people, doing little things and kind of, you know, these are not stories of like, oh, I went to Harvard and so I'm so learned because of this. I mean, it's a whole range of experiences. The interesting thing is the survey is a survey and it doesn't reflect ignorance, as you're saying perhaps, but it may reflect a different geopolitical view of the world than the West has. So if, you know, for a lot of the world, 9-11 was one of the most important moments of recent human history. And for Afghanistan to not to know that, especially when they're part of that story, means they have a very different, like there could be a lot of things said. One is the spread of information is different. The channels of the way information is spread and two, the things they care about. Maybe they see themselves as part of a longer arc of history with the bickering of these superpowers that seem to wanna go to the moon are not as important as the big sort of arc that's been the story of Afghanistan. That's an interesting idea, but it's still a bit, if at all representative of the truth. It's heartbreaking that they're not, do not see themselves as active player in this game between the United States and Central Asia, because there's such a critical player. And I feel, and obviously in many ways, get the short end of the stick in this whole interaction with the, you know, invasion of Afghanistan for many years. And then this rushed withdrawal of troops and now the economic collapse. And it's sad in some ways. No, it's very, I mean, you know, another way to put it is this. I mean, yeah, there's a range of knowledge and you're right, the information flows are peculiar to particular geographies and histories and stuff. I think that, you know, plucking out one sample from some fairly remote area, from one like follow the agricultural products. I mean, and this is where, you know, I think urban rural divides used to mean a lot more in the 19th century, right? So a lot of like nuts and bolts of history is about conceiving of these kinds of distinctions, you know, but I think that if one has the privilege of traveling a bit, you see that like urban areas are fed by rural hinterlands. And if you look, think of who actually, you know, brings the bread, the milk, you know, the pomegranates and so on, it creates these networks and then, you know, mobility channels, information and so on. But yeah, but your broader point about like the tragedy of this, I mean, I guess if I can quote a brilliant student of mine, an Afghan American woman who just received her PhD, who's now, you know, doctor, he's a great scholar. You know, we've done several events now trying to just think through what's happened. And of course she's very emotionally affected by it. And she continues to ask a really great question. If I can get her phrasing right, you know, if you think of the cycle of like the Taliban being in power in 2001, in the way in which that affected women in particular, you know, half Afghan, half of the society, right? Then you think of this 20 year period of violence and, you know, missed exits, right? And repeated tragedy, but also it created a space. I mean, it created a space for a whole, I'd say generationally, it created a sense, a space for people to realize something new. I think, so we have to attend to the dynamism of the society, right? So yeah, this happened mostly in Kabul, other big cities, Mazar-e-Sharif, Herat, Kandahar. But you can't limit your analysis to that because things like radio, television, everyone got a TV channel. There's a wonderful documentary called Afghan Star that I recommend to your listeners and viewers that it's about a singing show, a singing contest show. But you see just for some of these things about like connections, I mean, it's a show by an independent television network that did drama, it did kind of infomercials for the government and huge American investment in it. So it wasn't politically neutral, but it did talk shows, did all this kind of stuff. But it did a singing show that became incredibly popular, modeled upon the British American, you know, American Idol kind of stuff, you know, and you could vote. So it had a kind of democratic practice element. But it's fascinating to see that, you know, people hooked up generators to televisions and watch this, you know, you think of like literacy rates. Literacy rates are imperfect and, you know, people who study, you know, medieval or modern Europe talk about how, yeah, no one could read and there weren't many books, but if someone had a book, it'd be read aloud to a whole village potentially or a gathering. So there was, you know, some of these metrics don't get what people actually perceive as information or exposure because there's a magnifying power of open spaces and hearing radio in group settings, seeing television group settings, having telephone, you know, cheap telephones, which then become an access point to the world and social media, right? So all this stuff swept across African society as it did elsewhere, you know, in the last decade or more. So African society became, you know, in important ways, really connected to everything going on. And so you see that reflected politically in what people wanted. So you had some people obviously back to return to the Taliban. Some people wanted status quo, but increasingly many more people wanted something else. And one of the great failures was to expose people to democracy, but only give them the rigged version. And so the US and the State Department in particular continued to double down on faked elections for the parliament and for the presidency in Afghanistan. What kind of elections? Faked, fraudulent elections for parliament and for president in Afghanistan again and again, from the very beginning. And those elections were partly theater for the US, like for remaining on the road that you're describing, right, for not deviating, for not exiting, because we were building democracy there. In reality, the US government knew it was never really building democracy there. It was establishing control. And elections were one means to gather control, right? But then you had on the ground, especially among young people, going to university, you know, having experiences that were denied to them before, you know, they took these problems as seriously. So part of the disillusionment that we see today is that, you know, they believed what the US told them, that they're constructing democracy. And of course, you know, setting psychos, maybe thinking, well, you know, you're not really doing that, you're backing fraud. They believed it when they were younger, and now they're actually smart enough to understand that it's a farce. Yeah. But in so indirectly had the consequence of actually working. Yeah. And that it taught the young, for over a period of 20 years, young folks to believe that democracy is possible and then to realize what democracy is not. Exactly. Just the current system. That's beautifully said. And so, but now look at us, now it's, you know, it's now November. And so this whole period, and I wouldn't say like, you know, I wouldn't cast the last 20 years, if we're looking at all the achievements, you know, I wouldn't put them in an American tally sheet, like, oh, this is something we should pat ourselves on the back for. I think that much has happened actually against what the Americans wanted. I mean, that the kind of free thinking, democracy wanting, I mean, even like, you know, we could point out on the religious, go back to the religious sphere. I mean, the African religious landscape became very pluralistic. Lots of young people wanted a different kind of secular politics. But the old guard who wanted the status quo and wanted something that they'd fought for in 1980s tended to still get American backing as the political elites, who still tended to monopolize political power. So all that stuff was happening in different ways. I mean, the Americans established this American University of Afghanistan, which is I think one of the best things the US did there. And I regret that the US didn't fund 20 more, you know, sprinkling them across the country, making them accessible people. Because it was, you know, again, it wasn't an engine of Americanization. It was just opportunity. And so the thirst for higher education is really extraordinary. It was never really met. The US tended to put money in primary education, which much of that too was fraudulent. But so you have all this interesting dynamism. You have, you know, the arts, you have a critical space. I mean, I call it a public sphere in the classic European sense. You know, the Afghans made it their own. And again, it wasn't Americanization. It wasn't imposed. It was something that Afghans built across generations, but really with a firm foundation among youth who wanted importantly, a multi-ethnic Afghan society. You asked about postings and that kind of stuff. And a lot of that language in recent years was they were aware that the US-backed government was playing ethnic politics and trying to kind of put people in the blocks and mobilize people based on their ethnic identity. And there was a younger cohort of people who said, you know, we are Afghan. And then there's interesting social media stuff where people would say, I am Hazara, but I'm also Tajik, I'm also Uzbek. And I mean, it was a way of creating a multi-ethnic Afghan national identity that embraced everything. I mean, very utopian, you know, super utopian, right? But symbolically it was very important that they rejected being mobilized politically, you know, voting as a Hazara or voting as whatever. And of course there were communities who wanted to, you know, vote as that ethnic community. But there were also people who said, you know, let's put a kind of civic nationalism first, one that accommodates ethnic pluralism in a way that rejected a kind of majoritarian politics of one ethnic group dominating the thing. So all this stuff was quite interesting. I mean, women were asserting themselves in across multiple spheres. Of course it remained patriarchal. Of course there were struggles. Of course there was violence. Of course, you know, there's no utopia. But the door on all that shut on August 15. So to go back to the quote that I wanted to offer from the student, now professor, was that, you know, in trying to make sense of this, and you mentioned the tragic arc here, you think of the 20 years, like she asked, you know, why did you go to war in our country? Basically, why did you do this to us for 20 years when this was never about us? You know, you never asked us if you wanted to come. You never asked us what you wanted to build here. You didn't ask us when you were coming and you didn't ask us when you were leaving. You just did this all on your own. And we tried to make the most of it. And then you pulled the rug out from under us, you know, at the 11th hour and returned to power, partly by diplomacy. It wasn't at the end, just a military loss. I mean, it was a series of diplomatic decisions. I mean, the idea, you asked about alternatives. I mean, giving up Bagram, I mean, holding to the timeline. I mean, the Biden people did not need to hold to the Doha agreement that Trump had signed. I mean, every American president writes his or her own foreign policy, right? So the Biden administration acted as if, and they tried to convince us that their hands were tied and that it was either this or 20 more years of war or some absurd kind of, you know, false alternative. And so, but I think that's important for American audiences to hear that, you know, they're like, you came to here to experiment. You came here to punish. You came here to kind of reassert, you know, your dominance, the world stage, you know, to work out the fear and hurt of 9-11 that we talked about, which was so real, you know, and palpable and so important for American politics since then, like you worked out your problems, you know, on us, on our territory, and now what do we have for it? You know, and then the people who had a stake in that system, imperfect as it was, have been desperate to leave. And so this, I don't know how much people are aware of this, but, you know, I'm a scholar. I work in California, you know, I have friends. I edit a journal on Afghanistan and, you know, but I'm not a politician, I'm not a soldier, but people assume that, you know, Afghans have been desperately trying to reach me and anyone who is kind of on the radar as an American to help get them out. You know, that's the kind of like, you know, the symbol of voting with your feet, you know, is quite powerful. I mean, there's a huge swath of society that doesn't want the system and is literally living in terror about it. Naturally, women, you know, I mean, especially women of a certain age, I mean, they feel like their lives are over. I mean, there is an epidemic of suicide. They feel betrayed and some people have done some good things in getting people out. You know, I mean, some, you know, the US military vets have been, you know, at the forefront of working to get out people, you know, that they know they owe, but the US government doesn't want these people. I mean, they have created all these obstacles to allowing a safety valve for people to leave. Looking forward from a perspective of leadership, how do we avoid these kinds of mistakes? So obviously some interests, some aspects of human nature led to this war. How do we resist that in the future? I guess beyond my moral and intellectual capacity, I'll just say this. I mean, looking at it again, looking at it from my home ground is the university. And I think of the intellectual, you know, ways of thinking that I think students should develop for themselves as citizens, right? And maybe that's where to start is like, you know, historical thinking. I mean, these are all, you know, I try to tell people, you know, if you want to do robotics, computer science, you'd be a doctor or whatever. You should study history. Yeah, I mean, you don't have to be a historian like me. And it's, you know, my job isn't perfect. My profession is deeply flawed, right? But as I get older, I'm like, there are fewer and fewer historians actually like, you know, I want to hang out with and stuff. So it's like, I'm not offering myself as like a model for anything, but you know, whether you're a, you know, you carry the mail or you're a brain surgeon, whatever. I mean, I think it's a way of civic engagement and a way of like, you know, ethical being in the world that we need to familiarize ourselves with. Because if you're an American or if you're from a rich country, you know, you need to be aware of your effect on an integrated world. You can't say anymore that you don't know or care what's happening in Afghanistan or really circle the globe and point to a place. I mean, we're all connected and we're all, we have ethical obligations. That's one place to start. I would just say this, and this is a, I'll offer a self critique. And that is so much of my teaching and like the themes of my research have been about empire. You know, how big states work, not only on big territories like the Russian empire and Soviet Union and stuff, but the way in which power often, you know, is projected beyond those boundaries in ways that we don't see. So this is where things like neoliberalism or just, you know, if you want to take capitalism or just things that, you know, the idea of humanity or of liberalism or of humanitarianism, ideas that move beyond state boundaries are all things that we think about as affecting power in some ways that often harm people, right? So I think part of, as I've seen my job so far is to think about, you know, building upon the work of my people in grad school and, you know, scholars that have affected me. I mean, you know, we're all concerned with how power works and its effects and trying to be attuned to understanding things that aren't visible, right? That we should be thinking about, that should be known to us. And as scholars, we can hopefully play some useful role in showing effects that aren't, you know, obvious initially. So empire is a framework to think about this. And so you think about evading foreign countries. Obviously, if you're a scholar of empire, you've seen what that looks like and that's horrific, right? You look at things like racism as one of the ideological pillars of empire. You know, that's horrific. It must be critiqued. It must be, you know, we must be educated against. Some of the, you know, gender exploitation of empire is also something to highlight, you know, to rectify and so on. You know, to be moral beings, we need to think about past inequality and the legacies of violence and destruction that live on. I mean, living in the Americas. I mean, look at, you know, we're all on stolen land. We're all in the sense, living with the fruits of genocide and slavery and all those things that are hard to come to terms with. Right? But the last few months in Afghanistan and thinking about empire, I think made me more humble when I read people who say, to put it simply, have taken some joy in this moment, saying like, well, the Americans got kicked out of Afghanistan. You know, if you're against empire, this is a good thing. This is a kind of victory of anti-colonial. You could see from the perspective of Afghanistan that America is not some kind of place that has an ideal of freedom and all the kinds of things that we American tell ourselves. But it's more America has the ideal of empire, that there's one place that has the truth and everybody else must follow this truth. And so from a perspective of Afghanistan, it could be a victory against this idea of centralized truth of empire. That's another way to tell this story. And then in that sense, it's a victory. And in that sense also, I mean, you push back against this somewhat, this idea of Afghanistan as the graveyard of empires. Right, right. And I would say this, I'd say, you know, I mean, I'm a critic of empire. I mean, you know, colonialism is a political phenomenon that stays with us. And I think, you know, we need scholars to point to the way in which it still works and still does harm. But it's part of being an empire that you can just get up and leave a place, right? That you can remake its politics on one day. And then because it fails to advance your agenda at one moment, you simply walk away. I mean, you know, we can point to other moments. I mean, 1947 on the subcontinent, you know, the way that the British withdrew played a significant role in mass violence, you know, that accompanied partition. It wasn't all the actions of the British that, you know, dictated that, right? There were lots of actors who chose to pick up, you know, the knife to kill their neighbor and so on. I mean, there's lots of agency in that moment as there is now in what's happening in Afghanistan. But I think the capriciousness, I mean, the ability to act as if your political decisions about other people's lives, you know, or something that can be made, you know, in secret, that can be made willy-nilly, that really are beyond the accountability, you know, of those who are actually going to live with the consequences of shifting the cards on a deck in a way that decides who rules and who doesn't. I would love to hear your conversation with somebody I just talked to, which is Neil Ferguson, who argues on the topic of empire that you can also zoom out even further and say, weigh the good and the bad of empire. And he argues, I think he gets a lot of flack for this from other historians, that like the British empire did more good than bad in certain moments of history. And that's an uncomfortable truth. There's like levels, it's a cake with layers of uncomfortable truths, and it's not a cake at all because none of it tastes good. Right, I mean, I would continue to disagree with Neil Ferguson, so I'm still working out where I am and what this moment does to kind of, I think, qualify my understanding of the past into, I think, in a moment of humility, you know, I do, and I'm partly reacting to the kind of, you know, as you put it, I mean, the idea that this is like a good thing that American power has been defeated here. I mean, I do think American power should contract, and I don't think, and again, if I had to create a tally sheet of what the Americans did in the US, I mean, I mentioned the American University of Afghanistan, right, it could have done that without invading the country and killing people, you know, I've not now become an apologist for empire, I'm not now a mini Neil Ferguson, but, you know, ending empire is, I mean, it does, how you, those decisions you make are, in some ways, a continuation of imperial hubris, right? So you're not really out of empire yet, you're not really contracting empire for those who are living it, you know? But I think it's also, I mean, maybe I put it this way, it's be careful what you ask for, you know, I mean, I wanted the US out of Afghanistan, but I wanted there to be a political settlement, I wanted, you know, I wanted my cake and I wanted to eat it too, right? I wanted all kinds of things to be different, right? But why is going to Afghanistan even needed for that? You can play all those games of geopolitics without ever invading and taking ownership of the place. It feels like the war. Yeah, I mean. It feels like, I mean, I'm not exactly sure what military force is necessary for, except for targeted intense attacks. It feels like to me, the right thing to do after 9-11 was to show, was a display of force unlike anything the world has ever seen for a very short amount of time, targeted at, sure, at terrorists, at certain strongholds and so on. Yeah. And then in and out, and then focus on education, on empowering women into the education system, all those kinds of things that have to do with supporting the culture, the education, the flourishing of the place. That has nothing to do with military policing, essentially. No, I mean, I think, yeah, if you look at it through that lens, I mean, invading Afghanistan and then invading Iraq didn't end Al-Qaeda, it didn't end terrorism, right? It didn't really deflate these ideologies entirely. There were, if you like, you could say there were, you know, some limited discrediting of certain kinds of ideas. But in fact, I mean, look at the phenomenon of suicide bombing. I mean, it spread. I mean, it was never an Islamic thing. It was never, you know, a Muslim thing. Some Muslims adopted it in some places, but the circuits of knowledge about how to do these kind of things only expanded with the insurgencies that emerged in Afghanistan and Iraq, and then they kind of became connected. And then they became to the present. I mean, the Islamic State is, it's the best thing that happened to the Taliban ever, because it's on the basis of its supposed new stance as a counter-terrorism outfit, that it will get recognition from all its neighbors. It will get recognition in Russia. I mean, already with the evacuation of the airport, the United States was collaborating with the Taliban against the Islamic State and openly talking about the Taliban as if they were partners in the security operation. So, and then Al-Qaeda remains present in Afghanistan. So- Trillions of dollars spent. Yeah. The drones up above bombing places that result in civilian death, the death of children, the death of fathers and mothers, and those stories, even at the individual level, propagate virally across the land, creating potentially more terrorists. And a cynical view of the trillions of dollars is the military-industrial complex, where there's just a momentum, where after 9-11, the feeling like we should do something led to us doing something. And then a lot of people realizing they can make money from doing more of that something. And then it's just the momentum, where no one person is sitting there petting a cat in an evil way, saying, we're going to spend all of this money and create more suffering and create more terrorism. But it's just something about that momentum that leads to that. And to me, honestly, I'm still a sucker. I believe in leadership. I believe in great charismatic leaders and the power of that one to do evil and to do good. And it felt like I honestly put the blame on George Bush, Obama, Trump, and Biden for the lack of leadership in this. Yeah, definitely, definitely. I agree, and yeah, there is the military-industrial complex component, which is huge. And there's also, I mean, speaking of government leadership, it's also, I'd say, the imbalance of power within Washington. I mean, the Pentagon used this moment, well, beginning in 2001, I think, to assert its authority at the expense of other institutions of national government. I mean, the State Department diplomacy has become a shadow of what it was once capable of doing. And of course, I mean, other historians, US historians, which I'm not, formally a historian of the United States, but we can go back to talk about Vietnam. We talk about lots of Cold War and post-Cold War engagements. And I think we need a reckoning about how the United States uses military power, why we devote so much to our military budget and what could be available to us if we had a more sensible view of the value of military power, of its effectiveness. And I think we're willing to hammer home that this was a defeat. I mean, I think there should be accountability. And if you, and this could be a kind of opening for a kind of bipartisan conversation, because if you are a kind of American militarist, I mean, you have to look at the leadership that got you to a place where you were defeated by men wearing sandals, firing AK-47s, right? Yeah, there should be a humility with that. Yeah. I mean, we should actually say that, like literally the- Oh, we lost. You should say we lost. It wasn't just, you know. The American military lost. Yeah, and I feel I have very mixed feelings and it's, I don't know a ton of veterans, but I've mentioned I've topped my share and have a student now and they are suffering because they look at the sacrifices that they made that I didn't make. I mean, American society didn't make the sacrifices. I mean, men and women lost limbs, they lost eyes, they lost lives. There's been this, of course, quiet epidemic of suicide among veterans. And I've heard some stories, the fact that the State Department is seeing a similar surge of suicides because they see their adult life's work collapse. They've seen their relationships. I mean, they've seen, they were seeing phone calls in the middle of the night from people who they trusted with their lives, who they know are gonna be targeted. I mean, some have already been killed. They've seen the, I mean, I think just, I'd imagine just ideologically and professionally what they believed in and what they sacrificed for has vanished. And I think that's bad. I mean, historically, thinking of some of the precedents you were thinking of, I mean, if you think of, first of all, at a human level, I feel horrible for those people who, I may not have agreed with everything they had done and their choices in life, but I respect the fact that many good people went out of the best intentions as young people to do the right thing and make things right. And I respect that. And I've met enough to know that there were people who saw the gray in complexity and that's all you can hope for. But we don't want a generation of disillusioned veterans. If we look at the other post-war moments, and this is kind of a post-war moment where, I think we need a conversation with American veterans about what they've gone through and what they're feeling. And they still have skin in the game because their personal connections and of their histories- And they're also gonna be future leaders. I mean, veterans- Already, yeah. People who have served are often great men and women. That's- That's true. And, you know, throughout history, whether you sacrifice you served in fighting World War II, in fighting Vietnam, that's going to mold you in different ways. That's going to mold how you are as a leader that leads this country forward. And so you have to have an honest conversation about what was the role of the war in Afghanistan, the war in the Middle East, the war on terror in the history of America. If we just look at the full context at the end of this 21st century, how we're going to remember this and how that's going to result in our future interactions with small and large countries, with China or some proxy war with China, with Russia or some proxy war with Russia. What's the role of oil and natural resources and opium and all those kinds of things? What's the role of military power in the world? And now with COVID, you know, it's like, it's almost like because of the many failures of the US government and many leaders in science and politics to respond effectively and quickly to COVID, we kind of forget that we fumbled this other thing too. And it's hard to know which is going to be more expensive. They seem to be symptoms of something of a same kind of source problem of leadership, of bureaucracy, of the way information and intelligence flows throughout the US government, all those kinds of things. And that hopefully motivates young leaders to fix things. Definitely. I mean, I think if there's one theme that jumps out to me in thinking about this moment, I mean, if we recognize that we live in a kind of crisis of democracy in the United States and in other countries that have long been part of their democratic traditions, if we see them be under assault from certain quarters, I think military defeat is yet another addition to all the aspects of this that you mentioned. I mean, the fact that military defeat is a giant match that you're throwing on this fire, potentially if we think of its legacies and other post-war environments when, you know, the veteran angle, you know, is one, when you have people who feel betrayed. I mean, they have been fodder for the far right in other settings. I mean, interwar Europe is very much about mobilizing disillusioned veterans in the name of right-wing fascist politics. If one thinks too of this moment of really increasing xenophobia, you know, our immigration debate is now talking about whether or not Afghans should be permitted at all in the United States, you know, after 20 years. And I think immediately the response in Europe, which I follow to some extent, you know, focusing on Germany, because it was really ramping up deportations of Afghans leading up to this collapse. And now they have been, you know, a lot of right-wing center-right politicians in Germany have been watching all this with an eye to, I think, using it to their advantage for a domestic German audience to say, you know, in the context of recent elections that, you know, we're the party who will defend you against these Afghans who are gonna be coming from this. So, you know, what I've tried to emphasize in talking to different groups about this moment is that it won't be confined to Afghanistan or even the region. I mean, obviously malnutrition, hunger, will send Afghans to neighboring states, but where the European right is resurgent, this has been a gift, right? To say that the Afghans are coming, they're brown-skinned, they're Muslim, they're uneducated, they're gonna want your women. And they will take, you know, the odd sexual assault case or the odd whatever dramatic act of violence that, you know, happens numerically in any population. And they will magnify that to say that, you know, our far-right group is gonna save the nation. And sorry, the main point I wanted to speak of leadership was that I think the serial, well, there were many, many carnal sins, if you like, but if you go back to our analogy of all the exits, I mean, what blocked some of those exits was an absence of truth and transparency and the lying. And so, I mean, this is no secret anyone has followed this, but we've allowed, and you think of the general mistrust of government, mistrust of authority across the board, of professors, of economists, of- Scientists. Scientists, doctors, right? Well, I actually think, that's the hopeful thing to me about the internet is the internet hates inauthenticity. They can smell bullshit much better. And I think that motivates young leaders to be transparent and authentic. So like- I hope so. The very problems we've been seeing, this kind of attitude of authority where, oh, the populace, they're too busy with their own lies. They're not smart enough to understand the full complexities of the things we're dealing with. So we're not going to even communicate to them the full complexities. We're just going to decide and then tell them what we decided and conceive some kind of narrative that makes it easy for them to consume this decision. As opposed to that, I have, I really believe I see there's a hunger for authenticity of when you're making decisions, when you're looking at the rest of the world and trying to decide, untangle this complexity. The internet, the public, the world wants to see you as a leader struggle with the tension of these ideas, to change your mind, to see, to recognize your own flaws in your own thinking from a month ago, all that, the full complexity of it. Also acknowledge the uncertainty as with COVID, also with the wars. I think there's a hunger for that. And I think that's just going to change the nature of leadership in the 21st century. I hope so. I think all the things you've highlighted, I mean, accountability is part of that, right? I mean, we need honesty, openness, and then acknowledgement of mistakes. I mean, humility is the key to all learning, right? But also, I mean, you think just the headline from yesterday, the horrible drone strike, which was really the last kind of American military action on the day that the US was, I think, mostly departing from Kabul, wiped out an entire family, mostly children. You know, the US acknowledged that, yes, this was not the ISIS bombing outfit that they thought it was. But yesterday, they did a quick review. I'm not an expert on drone strikes in the aftermath, but as he was looking more closely, he said it was basically whole cloth taken from what the US government has been saying after all these strikes, you know, reproducing the same language and basically pointing to technical errors, but denying that there were any procedural mistakes or flaws, or it was just kind of, they found little ways of acknowledging things that don't go as planned, but we follow the policies essentially, and yeah, that's it. It's not a crime. It's a way of not even saying, you know, we screwed up. And it's kind of the legalese that suddenly makes a war crime not a war crime, you know? And that is, I feel like, is I think are feasible to take accountability. I think people are really sick of that in a way where the opposite is true, which is they get excited for people who are not, for leaders who are not that, and so they're not going to punish you for saying I made a mistake. Yeah, yeah. That I just had a conversation with Francis Collins, the director of NIH, and part of my criticism towards Anthony Fauci has been that it's like such subtle, but such crucial communication of mistakes made. If you make a small mistake, it is so powerful to communicate, I think we messed up. We thought this was true, and it wasn't. So the obvious thing there was with masks early in the pandemic. There's so much uncertainty. It's so understandable to make mistakes or to also be concerned about what kind of hysteria different statements you make lead to. Just being transparent about that and saying we were not correct and saying the thing we said before. That's so powerful to communicate, to gain trust. And the opposite is true. When you do this legalese type of talk, it destroys trust. And again, I really think the lessons of recent history teach us how to be a leader and teach young leaders how to be leaders. And so I have a lot of hope. Yeah, good. Partially thanks for the internet. Yeah, yeah, that's great. Oh, humility. We need humility, accountability, honesty. Yes, studying the past is an important way to do that, to learn from past mistakes. And obviously there's stories of inspiration and courage, and we can take some kind of assistance from that too. But also learning how not to do things. And then analogies are never one-to-one. We talk about Vietnam. I think many Vietnam veterans would say, this is like deja vu. The story, the visuals of the Kabul airport and of the Saigon embassy were not the same, but close enough that people would juxtapose them. All of us right now, but I would just ask people that, over-analogizing is also a kind of path down, making errors of judgment and comparison and then sameness. But it's stretched. I mean, like 9-11 itself. I think the idea that people lack the imagination within our security apparatus to think this was even possible, right? And you think of the simplicity of having a $10 lock on a cockpit door, could have blunted all this. And again, I'm not saying either the time or hindsight that I am omniscient about all this, but I had just been living in Germany the year before, and there was a plot there. This guy was hatching from Germany to blow up the mausoleum of Addis Work in Ankara with an airplane. And so if you kind of dig, it wasn't unimaginable that you would use an airplane as a weapon. And the Bush administration kept saying, no one had ever heard of this. Who would do this? Well, not a lot of people do this. And then at that very moment, my wife was teaching the Joseph Conrad novel, Secret Agent, which was about a conspiratorial organization that wanted to bomb, actually in retrospect, it was kind of suicide bombing. I think they tricked this guy into doing it, but they wanted to bomb the Greenwich Observatory for some obscure political purpose. So that's an instance in which the novel, to go back to our kind of humanities pitch, I guess my point was that, as you mentioned, we need humanity, transparency, but also imagination. I think part of expanding our imagination is by, I mean, obviously delving into your fields of engineering and the sciences and robotics and artificial intelligence and all that rich landscape. And then, but also we find this in film, poetry, literature, I mean, just the kind of stretching that we need to do to really educate ourselves more fully, right? Across the spectrum of everything humans need to imagine, to reimagine security. You know, so much of what we talked about today, I mean, so much of, you know, our security is affected by others' perception of their insecurity, right? Which unleashes a whole web of emotions. Can you tell me about the Afghan people, what they love, what they fear, what they dream of for themselves and for their nation? Is there something to say, to speak to, to the spirit of the people that may humanize them and maybe speak to the concerns and the hopes they have? Yeah, I think I, you know, as an outsider, I hesitate to make any grand statement, but I would say, listen, I mean, there are a number of documentary films that are incredibly rich, that will offer your listeners and viewers a snapshot. So there is Afghan Star, you know, which really brings you into the homes of a set of people who, you know, they want stardom, they're artists, they want to express themselves. Some want to push political boundaries, cultural boundaries. There's a woman who gets into hot water for dancing. But yeah, you realize that, I mean, people, I mean, they love art, they love music, they love poetry, they love expression. You know, people want to care for their children. They want safety of their families. They want to enjoy what everyone enjoys, you know? I think it's a very humanizing portrait. There's another great documentary film called Love Crimes of Kabul, which is a great snapshot of the post-2000 world that the Americans shaped a lot of ways. And it's about a women's prison. And it's incredibly revealing because it's about young girls and what they want. Well, not just young, but young, teenage, and then some middle-aged people who are accused of moral crimes, ranging from homicide, which one woman admits to, to having sexual relations outside of marriage. And so it shows, in a way, continuity with the previous Taliban regime and that women are in prison for things that you wouldn't be in prison for elsewhere, and that Islamic law operates as the kind of judicial logic for these punishments. But in letting these women kind of speak for themselves, I mean, it's fascinating. I mean, I don't want to give too much away, but women make very interesting choices in this film that land them in this predicament. So they don't all profess innocence. Some are like, I'm guilty, but they're guilty for reasons. In one case, one woman is guilty. She's in prison because it's a way to exert pressure on her fiance to finally marry her. You know? So you get ethnicity, you get like, you know, kind of Romeo and Juliet things where their families don't like each other necessarily, but they find each other. You have questions of like love, money, clothing, furniture. It's beautiful. I mean, the parts with it, I remember showing it in class. There was a wonderful Afghan student who was a, I think a Fulbright at the ed school at Stanford, and she's a genius. She's amazing. You know, it was awkward for her because talking about young women having sex and stuff, and it wasn't the snapshot of Afghanistan that she wanted. And obviously there's so much more. They're great writers and musicians. And I mean, music is a huge thing. I mean, poetry, all those things are great. So she found it, you know, I hear you. I mean, it's a kind of taboo subject, but I thought the American students seeing it really identified with these women because they're just so real. And so, you know, young people trying to find like, I mean, relationships that are universal and circumstances that are very difficult. Love, love is universal. Yeah, yeah, so it's, I mean, we do have resources to humanize. I mean, you know, some of your people will know Khaled Huseini. You know, he's an Afghan American. He's done his stuff, but there are a number of novelists and short story writers who do cool things. I think that another tragic aspect of this moment is that those people have now pretty much had to leave the country. So there's a visual artist I would highlight for you named Khadim Ali, who's a Hazara based in Australia. He does extraordinary work in blending a tradition of Persian miniatures with contemporary political commentary. His work is between Australia and Afghanistan, but he also, he had to flee. I mean, he was doing some work in Kabul, but it's a extraordinary kind of visual language that he's adapted that has been shown all over the planet now. He's got some of his work is in New York galleries, is in Europe. He's been shown in Australia, but he talks about migration in a way that puts Afghans and Hazaras at the center, but it's totally universal about, you know, our modern crisis of all the millions of people who were displaced across our planet. And he attempts to kind of speak for some size of them in a way that like, I think everyone can get. I mean, the visual imagery experts will know that it's from, you know, like the Shahnameh, like an ancient Persian, you know, epic that Iranians were attached to, that Afghans are attached to, that people can quote, you know, at length. It has mythical figures of good and evil that kids grew up embodying. They're named the names of the characters that are, it's called, you know, the Book of Kings. The heroes and villains are the staple of conversation and poetry. And, you know, like Russians, I mean, the kind of, the resort to literary references and speak is something that, you know, Americans don't do, most West European countries don't do, but the fact that everyone's got to know this character, everyone knows this reference, the wordplay, the linguistic finesse in multiple languages is, you know, a major value of Afghan storytelling. As an outsider, I'm scratching it, the surface of the surface. Yeah, but there's a depth to it. It's just like, it is fascinating. With the layers, yeah. With the layers of Russian language that's- Exactly. The culture, it's, I've been struggling, and this is kind of the journey I'm embarking on, to convey to an American audience what is lost in translation between Russian and English. It's very challenging, and some of the great translators of Dostoevsky, of Tolstoy, of Russian literature struggle with this deeply, and they work. It's an art form just to convey that. And it's amazing to hear that Afghanistan, with a full mix of cultures that are there, have the same kind of wit and humor and depth of intellect. I mean, the humor thing is, that's, you know, so much of our visual imagery is about this sad place, and dour, or whatever, but the, I mean, socially, again, I'm gonna engage in some stereotypes about generalization stuff, but just the, you know, the Afghan friends that I've come to be close with and really love, I mean, the humor, there's so much there. I have common stuff of like, when I go to Ireland, it's one of my favorite places, and just like the, I feel a sense of pressure, like the humor, all around me all the time, and I feel like, there's something between Ireland and Russia, with the humor stuff, where it's like, you've gotta be on your game if you wanna be, you know, so it's, it's like, you know what I mean? The intensity of conversation, in terms of, yeah, you have to be on your game, in terms of wit and so on, I mean, you have to, there's certain people I have, like, when I talk on this podcast, they're like that, certain people from the Jewish tradition have that, like, where the wit is just like, okay, I have to, okay, I really have to pay attention, it's a game, it's like, you know what it feels like? It feels like speed chess or something like that, and you really have to focus and play, and at the same time, there's body language, and then there's a melancholy nature to it, at least on the Russian side, and the whole thing is just a beautiful mess. Yeah, I mean, there's a funny TikTok video that went around that I got from some Afghan acquaintances that was, he's an Irish comedian, kind of highlighting, you know, kind of Irish and German national stereotypes around hospitality, and this Afghan woman said, you know, I didn't know that the Irish were just white Afghans, because the whole, like, you know, the hospitality, like, politics of refusal, you know, you don't take something that's offered to you the first time, you don't, I mean, it's the culture of receiving a guest, you know, that's, you know, Americans aren't, I mean, that's not, you know, that's not always, I mean, they're different, they're regional cultures, that's the thing, there's whatever, but it's, I mean, the kind of, like, generosity, and the kind of, you know, that's real, I mean, that's, and that's a cool thing, and that's amazing, that's, you know, the food, I mean, going off just the superficial things, but all that, the warmth of hospitality, and of wit, and humanity, I mean, it's, that's what we don't see viewing the place just through war, and geopolitics, and the moving pieces of the map and stuff, and that's, and that's hard to see when, you know, there are gaps in language, and religious tradition, and all that stuff, and then, you know, being open to the fact that people do things differently, you know, and it's, and the gender dimension there is important, right, that they're kind of, you know, arguably, each culture has a kind of gender dynamic that's different, and so I think it's helpful to have humility in thinking that some Afghans will do some things differently, you know, but then you'll also have Afghans who say, everyone should be educated, everyone should work, and so on, and so on, so there's no single way of, yeah. And there is a gender dynamic in Russia, too, we need to be respectful of that, like, And that's not always what it looks like at first. Yeah, exactly, there's layers. Like where power is, I mean, that's definitely, I don't know, yeah. Yeah, that's a whole nother conversation of where the power is. Yeah. Rumi, the 13th century Persian poet who was born on the land that is now Afghanistan, is there something in his words that speaks to you about the spirit of the Afghan people? I mean, everyone owns Rumi, I guess I'd say. I mean, that's gonna get me in trouble with certain Afghan fans of Rumi who wanna see him as an Afghan, I would say. Are they proud of Rumi? Yeah, yeah, yeah. Do they see him as an Afghan? Do they? Yeah, I mean, again, it depends. I mean, some people will be militant and say, you know, the Iranian's gonna have him, he's ours. But they're also gonna say, you know, he's, I mean, you could say, again, he's like Rorschach plot. I mean, he's a Sufi, he's a Muslim, he's a Central Asian, he's Iranian, he's Afghan, he's a Turk. I'm trying to think of the analogy, but he's something special to everyone. So I guess I would not walk into that conversation and claim that he's one or another, but it's a cool thing. I mean, it's the, but I'm glad you brought that up because that's a good way of seeing something that Afghans, I mean, we live in our country, it's Afghanistan, and say, okay, Rumi's everyone, you know, Madonna helped make him famous in the United States, you know, for better, for worse. They used to sell stuff at Starbucks and that's all complicated and embarrassing. And his translations are very much disputed where you have people be like, there's some awful Rumi translations and there are, there are also a lot of, speaking of the internet, there are lots of fake Rumi quotes. Yes. You know, like Rumi said, always be your best. Like, Rumi didn't say that, you know, that was, I mean, that's kind of so, so, but, but the cool thing is like, I mean, I think you can read Rumi as a religious thinker, but you can also, you know, read Rumi as a, you know, in an Islamic sense, but you can also read him as a kind of spiritualist, right? As someone who, or an ethicist or moralist. And so I think that's, I like the lens of Rumi as a gateway to Afghan ecumenism and cosmopolitanism, you know, the theme I keep emphasizing of, of meeting actual Afghans who were actually, you know, fluent in Russian, fluent in German, fluent in Turkish, they know Dari, they know Pashto. They've gone to university or sometimes they haven't. And yet, I mean, they are, I like the category of the popular intellectual, you know, the intellectual who isn't, isn't formally educated necessarily. Although of course that's represented too, especially increasingly now with this generation of going to university all over the world, you know, Stanford, MIT, everywhere. Afghans are well represented there. But just being, I don't know, having kind of worldly knowledge that is not limited to a province, to a village, to a hamlet, but sometimes it is, but sometimes it's not. Because of, again, not because of some fairytale story of curiosity, wanting the globe out of, you know, some sense of privilege, but out of necessity, out of survival, of having to adapt. And it's really extraordinary that, I mean, also that we think about like professions, but like, you know, ask an Afghan, you know, what does he or she do for a living? And what have they done in the past? I mean, the answer is one gets shoe salesman, tax cop drivers, surgeons, all in one guy. Yeah. I mean, that's not just Afghan, but that's, you know, that's very common. But it's also Russia is the same. That's right. I think it's whenever there's complexities to the economic system and the short-term and the long-term history of how the country develops. And it's basically the people figuring out their way around a mess of a country politically, but a beautiful flourishing culture and humanity. And that creates super interesting people. Yeah. So we can often see, okay, there's Taliban, there's war, there's economic malfunction, there's harboring of terrorists, there's opium trade, all that kind of stuff. There's humans there with deep intellectual lies. And like, I love the movie, Love Crimes. And the same kind of hopes, fears, and desire to love the old Romeo and Juliet story. And I think Rumi to me represents that, the wit, the intelligence, but also the just eloquent and just beautiful representation of humanity, of love. Some of the best quotes about love are from him. Half of them fake, half of them real. But- The best ones are real. The best ones are real. Yeah. The best ones are real. Robert, this was an incredible conversation. Oh, thank you for having me. Thank you for the tour of Afghanistan and making me, making us realize that there's much more to this country than what we may think. It's a beautiful country and it's full of beautiful people. You made me think about a lot of new things too, so it was definitely great for online too. So thank you so much. Thanks for listening to this conversation with Robert Cruz. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Winston Churchill. History will be kind to me, for I intend to write it. Thank you for listening and hope to see you next time.

https://youtu.be/CDiqA4SJNpA

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Turing Test: Can Machines Think?

In this video, I propose to ask the question that was asked by Alan Turing almost 70 years ago in his paper, Computing Machinery and Intelligence. Can machines think? This is the first paper in a paper reading club that we started focused on artificial intelligence, but also including mathematics, physics, computer science, neuroscience, all the scientific and engineering disciplines. On the surface, this is a philosophical paper, but really, it's one of the most impactful, important first steps towards actually engineering intelligent systems by providing a test, a benchmark that we call today the Turing test of how we can actually know quantifiably that a system has become intelligent. So I'd like to talk about an overview of ideas in the paper, provide some of the objections inside the paper and external to the paper, consider some alternatives to the test proposed within the paper, and then finished with some takeaways. Like I said, the title of the paper was Computing Machinery and Intelligence, published almost 70 years ago in 1950, author Alan Turing. And to me, now we can argue about this, on the slide I say it's one of the most impactful papers. To me, it probably is the most impactful paper in the history of artificial intelligence while only being a philosophy paper. I think the number of researchers from inside computer science and from outside that has inspired, has made dream at a collective intelligence level of our species, inspired that this is possible, I think is immeasurable. For all the major engineering breakthroughs and computer science breakthroughs and papers stretching all the way back to the 30s and 40s with even the work by Alan Turing with the Turing machine, some of the mathematical foundations of computer science to today with deep learning, a sequence of papers from the very practical Alex Ned paper to the back propagation papers. So all of these papers that underlie the actual successes of the field, I think the seed was planted. The dream was born with this paper. And it happens to have some of my favorite opening lines of any paper I've ever read. It goes, I propose to consider the question, can machines think? This should begin with the definitions of the meaning of the terms machine and think. The definition might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words machine and think are to be found in examining how they're commonly used, it is difficult to escape the conclusion that the meaning and the answer to the question, can machines think is to be sought in a statistical survey such as a Gallup poll. But this is absurd. Instead of attempting such a definition, I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous terms. And he goes on to define the imitation game, the construction that we today call the Turing test, which goes like this. There's a human interrogator on one side of the wall, and there's two entities, one a machine, one a human on the other side. And the human interrogator communicates with the two entities on the other side of the wall by written word, by passing notes back and forth. And after some time of this conversation, the human interrogator is tasked with making a decision, which of the other two entities is a human and which is a machine. I think this is a powerful leap of engineering, which is take an ambiguous but a profound question like can machines think and convert it into a concrete test that can serve as a benchmark of intelligence. But there's echoes in this question to some of the other profound questions that we often ask. So not only can machines think, but can machines be conscious? Can machines fall in love? Can machines create art, music, poetry? Can machines enjoy a delicious meal, a piece of chocolate cake? I think these are really, really important questions, but very difficult to ask when we're trying to create a non-human system that tries to achieve human level capabilities. So that's where Turing formulates this imitation game. And his prediction was that by the year 2000, or in 50 years since the paper, that a machine with 100 megabytes of storage will fool 30% of humans in a five-minute test of conversation. Another broader societal prediction he made, which I think is also interesting, is that people will no longer consider a phrase like thinking machine contradictory. So basically artificial intelligence at a human level becomes so commonplace that we would just take it for granted. And the other part that he goes at length towards the end of the paper to describe, which he believes that learning machines, or machine learning, will be a critical component of this success. I think it's also useful to break apart two implied claims within the paper, open claims, open questions. One is that the imitation game, as Turing proposes, is a good test of intelligence. And the second is that machines can actually pass this test. So when you say, can machines think, you're both proposing an engineering benchmark for the word think, and raising the questions, can machines pass this benchmark? One of the perhaps tragic, but also exciting aspects of this whole area of work is that we still have a lot of work to do. So throughout this presentation, I will not only describe some of the ideas in the paper and outside of it in the years since, but also some of the open questions that remain, both at the philosophical, the psychological, and the technical levels. So here the open question stands, is it even possible to create a test of intelligence for artificial systems that will be convincing to us? Or will we always raise the bar? A corollary of that question is, looking at the prediction that Turing made that people will no longer find the phrase thinking machines contradictory, why do we still find that phrase contradictory? Why do we still think that computers are not at all intelligent? For many people, the game of chess was seen as the highest level of intelligence in these early days. In fact, we assign a lot of intelligence to Garry Kasparov for being one of the greatest, if not the greatest chess players of all time, as a human. Why do we not assign at least an inkling of that to IBM Deep Blue when it beat Garry Kasparov? Now, of course, you might start saying that it's a brute force algorithm, or in the case of AlphaGo and AlphaZero, you know how the learning mechanisms behind those algorithms work when they mastered the game of Go and the game of chess. And we'll get to some of those objections, but there's something deeply psychological within those objections that almost fear an artificial intelligence that passes the test. So the Turing test is very interesting as a thought experiment, as a philosophical construct, but it's also interesting as a real engineering test. And one of the implementations of it has been called the Lobner Prize, which has been running since 1991 to today. And the awards behind it, the award structure, is $25,000 for a system that, using text alone, passes the test, and $100,000 that uses other modalities like visual and auditory input. The rules of the competition have changed through the years, but they currently are as follows. It's a 25-minute conversation, and in order to win, to pass the test, you have to fool 50% of the judges with which the system communicates. Mitsuko and Rose from Steve Warswick and Bruce Wilcox have been dominating the past 10 years, winning all but one of the years. Some details, Mitsuko and Rose are both mostly scripted rule-based chatbots, so they're not end-to-end learning systems. I believe there is a little bit of machine learning, but as I understand, at the core, they're mostly scripted. And on the next slide, we'll go through a transcript of a conversation with Mitsuko to give you a sense of what those conversations are like. But I'd like to mention sort of a tragic note, really, that as far as I understand, the prize is no longer funded. But money aside, it shows that there's not a broad interest in this construction, both inside and outside the research community. It's really surprising to me that Google DeepMind, Facebook AI, major groups, major individual researchers in the field of AI have not taken on this challenge. I hope to actually be a small part of changing that a little bit, because I think there is a lot of value in considering the Turing test. I don't think it's a distraction. And I'll return to that point later on in this presentation. So you can pause and maybe read parts of this transcript. I'll highlight on the right, at the top of the right column, the human says, you're a robot. Mitsuko answers, how can a person be a robot? Human, many people live lives akin to robots. Mitsuko, how many? More than a million? Human, yes. Mitsuko, that seems like rather a lot. Human, do you think Southampton will be Swansea? Mitsuko, I think so. Human, why? Mitsuko, no reason. It's just what I think. Human, you must have a reason. Mitsuko, nope, no real reason. Human, which team do you support? Mitsuko, I support Leeds United. Human, Leeds! Exclamation point. How's the season going? Mitsuko, yes, it is a city in the north of England. About half a million people live there. It is the same as ever. So you see in this transcript, just some little gap of inhumanity that becomes apparent. There's a lingering and a repeatability of points. There's certain gaps in understanding, inability to follow tangents, all those kinds of things. But it's still not clear to me as an open question how to make explicit where exactly the point of the failure of the test is. I believe that hasn't actually been really researched that well in these constructions. As opposed to decision making at the very end of a conversation, is this human or not, rather marking parts of a conversation as more or less human, like suspicious parts that make you wonder, this is not human. I think that'll be really interesting to see if it's possible to make explicit what aspects of the conversation are the failure points. One of the times that the claim that the Turing test was passed, I think most famously was in 2014 at an exhibition event that marked the 60th anniversary of Turing's death. Eugene Guzman fooled 33% of the event judges. And the method he used was to portray a 13-year-old Ukrainian boy that had a bunch of different personality quirks and obviously the language barrier, and had some humor and a constant sort of drive towards misdirecting the conversation back to the places where it was comfortable doing. So there's some criticism that you can make of this event due to some sort of smoke and mirrors, kind of the PR marketing side of things that I think is always there with these kind of exhibition events. But setting that aside, I think the interesting lessons here is that the parameters, the rules of the actual engineering of the Turing test can determine whether it contains sort of the spirit of the Turing test, which is the test that captures the ability of an agent to have a deep, meaningful conversation. So in this case, you can argue that a few tricks were used to circumvent the need to have a deep, meaningful conversation. And 30% of judges were fooled without rigorous, thorough, transparent, open-domain testing. On the left is a transcript with Scott Aronson, the famed computer scientist, quantum computing researcher. Talked to him on the podcast, brilliant guy. He posted some of the conversation that he had with Eugene. He was one of the judges on his blog that I think is really interesting. So it shows that the judge, the interrogator, when they're an expert, they can drive, they can truly put the bot to the test. As Scott did, he really didn't allow the kind of misdirection that Eugene nonstop tried to do, and you can see that in the transcript. Scott refuses to take the misdirection. So as I mentioned, despite the waning, I guess, popularity of the Lobner Prize and the Turing Test idea in general, Google has published a paper and proposed a system called MENA. That's a chatbot. That's an end-to-end deep learning system. The representational goal in the 2.6 billion parameters is to capture the conversational context well, to be able to generate the text that fits the conversational context well. Now, one interesting aspect of this, besides being a serious attempt at creating a learning-based system for open domain conversational agents, is that a new metric is proposed, and it's a two-part metric of sensibleness and specificity. Now, sensibleness is that a bot's responses have to make sense in context. They have to fit the context. Just to give you a sense, for humans who have 97% sensibleness, so ability to match what we're saying to the context. Now, the reason you need another side of that metric is because you can be sensible. You can fit the context by being boring, by being generic, by making statements like, I don't know, or that's a good point. So these generic statements that fit a lot of different kinds of contexts. So the other side of the metric is specificity. Basically, the goal being there is don't be boring. It's to say something very specific to this context. So not only does it match the context, but it captures something very unique to this particular set of lines of conversation that form the context. I think it's fair to say that the beauty of the music, the humor, the wit of conversation comes from that ability to play with the specifics, the specificity metric. So both are really important. Humans achieve 86% sensibleness and specificity. Mina achieves 79%, compared to Mitsuko, who achieves 56%. Now, take this all with a grain of salt. I want to be very careful here because there is also, not to throw shade, but it's closed source currently, and there's a little bit of a feeling of a PR marketing situation here. Naturally, perhaps, the paper is made in such a way, the methodology and the results are made in such a way that benefit the way the learning framework was constructed. Now, that's, I don't want to over-criticize that because I think there's still a lot of interesting ideas in this paper, but in terms of looking at the actual percentages of 86% human performance and 79% Mina performance, I think we're quite away from being able to make conclusive statements about a system achieving human-level conversational capabilities. So those plots should be taken with a grain of salt, but the actual content of the ideas, I think, is really interesting. I think quite obviously, the future, long-term, but hopefully short-term, is in learning end-to-end, learning-based approaches to open domain conversation. So just like Turing described, funny enough, 70 years ago in his paper, that machine learning will be essential to success, I believe the same. It's a lot less interesting and revolutionary to think so today, but I believe that machine learning will also need to be a very central part of achieving human-level conversational capabilities. So let's talk through some objections. Nine of them are highlighted by Turing himself in his paper. Here I provide some informal, highly informal summaries. The first objection is religious, which connects thinking to, quote-unquote, the soul. And God, presumably, is the giver of the soul to humans. Now, Turing's response to that is God is all-powerful. There is no reason why he can't assign souls to anything. Anything biological or artificial. So it doesn't seem that whatever mechanism by which the soul arrives in the human cannot also be repeated for artificial creatures. The second objection is the, quote-unquote, head in the sand. It's a bit of a ridiculous one, but I think it's an important one because it keeps coming up often, even in today's context, highlighted by folks like Elon Musk, Stuart Russell, and so on. The head in the sand objection is that AGI is scary, so human-level and superhuman-level intelligence is kind of scary. Today we talk about existential threats. It seems like the world would be totally transformed if we have something like that. Then it could be transformed in a highly negative way. So let's not think about it because it kind of seems far away, so it probably won't happen, so let's just not think about it. That's kind of the objection of the Turing test. It's so far away, it's not worthwhile to even think about a test for this intelligence or what human-level intelligence means or what superhuman-level intelligence means. The response, quite naturally, is that it doesn't matter how you feel about something and whether it's going to happen or not. So we kind of have to set our feelings aside and not allow fear or emotion to muddle our thinking or detract us from thinking about it at all. The third objection is from Gato's incompleteness theorem saying there's limits to computation. This is the Roger Penrose line of thinking that basically if a machine is a computation system, there is limits to its capabilities in that it can never be a perfectly rational system. Turing's response to this is that humans are not rational either. They're flawed. Nowhere does it say that intelligence equals infallibility. In fact, it could probably be argued that fallibility is at the core of intelligence. The fourth objection is that consciousness may be required for intelligence. Turing's response to this is to separate whether something's conscious and whether something appears to be conscious. So the focus of the Turing test is how something appears. And so in some sense, humans, to us, as far as we know, only appear to be conscious. We can't prove that they're actually conscious. We're humans outside of ourselves. And so since humans only appear to be conscious, there's no reason to think that machines can't also appear to be conscious. And that's at the core of the Turing test. So the Turing test kind of skirts around the question whether something is or isn't intelligence, whether is or isn't conscious. The fundamental question is, does it appear to be intelligent? Does it appear to be conscious? So he actually doesn't respond to the idea that consciousness is or isn't required for intelligence. He just says that if it is, there's no reason why you can't fake it. And that will be sufficient to achieve the display of intelligence. The fifth objection is the negative Nancy objection of machines will never be able to do X, whatever X is. You can make it love, joke, humor, understand or generate humor, eat, enjoy food, create art, music, poetry, and so on. So there's a lot of things we can put in that X that machines can never do. And basically highlighting our human intuition about the limitations of machines. Just like with the second objection, naturally the response here is that the objection that machines will never do X doesn't have any actual reasoning behind it. It is just a vapid opinion based on the world today, refusing to believe that the world of tomorrow will be different. The sixth objection, probably the most important, one of the most interesting, comes by way of Ada Lovelace, Lady Lovelace, the mother of computer science, with the basic idea that machines can only do what we program them to do. Now this is an objection that appears in many forms throughout, before touring and after touring. And I think it's a really important objection to think about. So in this particular case, I think Turing's response is quite shallow, but it is nevertheless pretty interesting. And then we'll talk about it again later on. His response is, well, if machines can only do what we program them to do, we can rephrase that statement as saying, machines can't surprise us. And when you rephrase it that way, it becomes clearer that machines actually surprise us all the time. A system that is sufficiently complex will no longer be one of which we have a solid intuition of how it behaves, even if we built all the individual pieces of code. For those of you who have programmed things, so I've written a lot of programs, in the initial design stage, you have an intuition about how it should behave. There's a design, there's a plan, you know what the individual functions do. But as the piece of code grows, your ability to intuit exactly the mapping from input to output fades with the size of the code base, even if you understand everything about the code, and even if you set logical and syntactic bugs aside. The seventh objection looks to the brain and looks to the continuous analog nature of that particular neural network system. So Turing's response to that is, sure, the brain might be analog, and then digital computers are discrete, but if you have a big enough digital computer, it can sufficiently approximate the analog system, meaning to a sufficient degree that it would appear intelligent. The eighth objection is the free will objection, is that when you have deterministic rules, laws, algorithms, they're going to result in predictable behavior. And this kind of exactly deterministic, predictable behavior doesn't quite feel like the mind that we know us humans is possessing. This kind of feeling that underlies what's required for intelligence for a mind, I think is behind the Chinese room thought experiment that we'll talk about next. So Turing's response here is that humans very well could be a complex collection of rules. There's no indication that we're not. Just because we don't understand or don't even have the tools to explore the kind of rules that underlie our brain doesn't mean it's not just a collection of deterministic, perfectly predictable sets of rules. Objection number nine is kind of fun. Quite possibly Turing is trolling us, but more likely the ideas of mind reading, extrasensory perception, telepathy were a little bit more popular in his time. So the objection here is what if mind reading was used to cheat the test? So basically, if human to human communication through telepathy could be used, then a machine can't achieve that same kind of telepathic communication. And so that could be used to circumvent the effectiveness of the test. Now, Turing's response to this is, well, you just have to design a room that not only protects you from being able to see, whether it's a robot or a human, but also design a telepathy-proof room that prevents telepathic communication. Again, could be Turing trolling us, but I think more importantly, I think it's a nice illustration at the time, and even still today, that there's a lot of mystery about how our mind works. If you chuckle and completely laugh off the possibility of telepathic communication, I think you're assuming too much about your own knowledge about how our mind works. I think we know very little about how our mind works. It is true, we have very little scientific evidence of telepathic communication, but you shouldn't take the next leap and have a feeling like you understand that telepathic communication is impossible. You should nevertheless maintain an open mind, but as an objection, it doesn't seem to be a very effective one. I wanted to dedicate just one slide and probably the most famous objection to the Turing test proposed by John Searle in 1980 in his paper, Minds, Brains, and Programs, commonly known as the Chinese Room Thought Experiment, and it's kind of a combination of number four, number six, and number eight objections on the previous slide, which is the consciousness is required for intelligence, the Ada Lovelace objection that programs can only do what we program them to do, and the deterministic free will objection that deterministic rules lead to predictable behavior, and that doesn't seem to be like what the mind does. So there's echoes of all those objections that Turing anticipated all put together into the Chinese Room. As a small aside, it is now 6 a.m. I did not sleep last night, so this video is brought to you by this magic potion called Nitro Cold Brew, an excessively expensive canned beverage from Starbucks that fuels me this wonderful Saturday morning. Here's to you, dear friends. Okay, the Chinese Room involves following instructions of an algorithm. So there's a human sitting inside a room that doesn't know how to speak Chinese, but there's notes being passed to them inside the room from outside in Chinese, and all they do is follow a set of rules in order to respond to that language. So the idea is if the brain inside the system that passes the Turing test is simply following a set of rules that it's not truly understanding, it is not conscious, it does not have a mind. The objection is philosophical, so there's not, for my computer science engineering self, there's not enough meat in it to even make it that interesting. It's very human-centric, but allow us to explore it further. So the key argument is that programs, computational systems, are formal, and so they can capture syntactic structure. Minds, our brains, have mental content, so they can capture semantics. And so the claim that I think is the most important and clearest in the paper is that syntax by itself is neither constitutive of nor sufficient for semantics. So just because you can replicate the syntax of the language doesn't mean you can truly understand it. Now this is the same kind of criticism we hear of language models of today with transformers, that OpenAI's GP2 really doesn't understand language. It's just mimicking the statistics of it so well that it can generate syntactically correct and even have echoes of semantic structure that indicates some kind of understanding, but it doesn't. To me, that argument is not very interesting from an engineering perspective because it just sounds like saying humans can understand things, humans are special, therefore machines cannot understand things. It's a very human-centric argument that's not allowing us to rigorously explore what exactly does understanding mean from a computational perspective, or put in other words, if understanding, intelligence, consciousness, either one of those is not achievable through computation, then where is the point that computation hits the wall? The most interesting open questions to me here are on the point of faking things, or mimicking, or the appearance of things. Does the mimicking of thinking equal thinking? Does the mimicking of consciousness equal consciousness? Does the mimicking of love equal love? This is something that I think a lot about, and depending on the day, go back and forth, but I tend to believe from an engineering perspective, I tend to agree with the spirit and the work of Alan Turing in that, at this time as engineers, we can only focus on building the appearance of thinking, the appearance of consciousness, the appearance of love. I think as we work towards creating that appearance, we'll actually begin to understand the fundamentals of what it means to be conscious, what it means to love, what it means to think. You may have even heard me say sometimes that the appearance of consciousness is consciousness. I think that's me being a little bit poetic, but I think from our perspective, from our exceptionally limited understanding, both problems are in the same direction. So it's not like if we focus on creating the appearance of consciousness, that's gonna lead us astray, in my personal view. It's going to lead us very far down the road of actually understanding and maybe one day engineering consciousness. And now I'd like to talk about some alternatives and variations of the Turing test that I find quite interesting. So there's a lot of kind of natural variations and extensions to the Turing test. First, the total Turing test proposed in 1989. It extends the Turing test in the natural language conversation domain to perception, computer vision, and object manipulation of robotics. So it takes it into the physical world. The interesting question here to me is whether adding extra modalities like audio, visual manipulation makes the test harder or easier. To me, it's very possible that a test with a narrow bandwidth of communication, such as the natural language communication of the Turing test, is actually harder to pass than the one that includes other modalities. But anyway, one of the powerful things about the original Turing test is that it's so simple. The Lovelace test proposed in 2001 builds on the Ada Lovelace objection to form the test that says the machine has to do something surprising that the creator or the person who's aware how the program was created cannot explain. So it should be truly surprised. There is also, in 2014, was proposed a Lovelace 2.0 test, which emphasizes a more constrained definition of what surprising is, because it's very difficult to pin down, to formalize the idea of surprise and explain, right, in the original formulation of the Lovelace test. But with Lovelace 2.0, it emphasizes sort of creativity, art, so on. So it's more concrete than surprise, especially if you define constraints to which creative medium we're operating in. You basically have to create an impressive piece of artistic work. I think that's an interesting conception, but it takes us in the land that's much more, not less subjective than the original Turing test. But this brings us to the open and the very interesting question of surprise, which I think is really at the core of our conception of intelligence. I think it is true that our idea of what makes an intelligent machine is one that really surprises. So when we one day finally create a system of human-level or superhuman-level intelligence, we will surely be surprised. So we have to think, what kind of behavior is one that will surprise us to the core? To me, I have many examples in mind that I'll cover in future videos, but one certainly, one of the hardest ones, is humor. And finally, the truly total Turing test proposed in 1998 proposes an interesting philosophical idea that we should not judge the performance of an individual agent in an isolated context, but instead look at the body of work produced by a collection of intelligent agents throughout their evolution, with some constraints on the consistency underlying the evolutionary process. It's interesting to suggest that the way we conceive of intelligence amongst us humans is grounded in the long arc of history of the body of work we've created together. I don't find that argument convincing, but I do find the interesting question and the open question, the idea that we should measure systems not in the moment, or particular five-minute period or 20-minute period, but over a period of months and years, perhaps condensed in a simulated context. So really increase the scale at which we judge interactions by several orders of magnitude. That to me is a really interesting idea. To judge alpha zero performance not on a single game of chess, but looking at millions of games. And not looking at a million games for a static set of parameters, but looking at the millions of games played as the system was trained from scratch and became better and better and better. There's something about that full journey that may capture intelligence. So intelligence very well could be the journey, not the destination. I think there's something there. It's very imprecise in this construction, but it struck me as a very novel idea. For benchmark, not to measure instantaneous performance, but performance over time and the improvement of performance over time. It appears that there's something to that, but I can't quite make it concrete. And I'm not sure it's possible to formalize in the way that the original Turing test is formalized. Another kind of test is the Winograd Schema Challenge, which I think is really compelling in many ways. So first to explain it with an example, there's a sentence, really two sentences. Let's say the trophy doesn't fit into the brown suitcase because it's too small. And the trophy doesn't fit into the brown suitcase because it is too large. And the question is, what is too small? What is too large? The answer for the small, what is too small, is the suitcase is too small. The trophy doesn't fit into the brown suitcase because it is too small. And then the second question is, what is too large? The answer there is the trophy. The trophy doesn't fit into the brown suitcase because it is too large. The basic idea behind this challenge is the ambiguity in the sentence can only be resolved with common sense reasoning about ideas in this world. And so the strength of this test is it's quite clear, quite simple, and yet requires, at least in theory, this deep thing that we think makes us human, which is the ability to reason at the very basic level of common sense reasoning. The other nice thing is it can be a benchmark like we're used to in the machine learning world that doesn't require subjective human judges. There's literally a right answer. The weakness here that holds for other similar challenges in the space is that it's very difficult to come up with a large amount of questions. I mean, each one is handcrafted. And so that means you can't build a benchmark of millions or billions of questions. It has to be on a small scale. Variations of the Winograd scheme are included in some natural language benchmarks of today that people use in the machine learning context. The Amazon Alexa Prize, I think, captures nicely the spirit of the Turing Test. I think it's actually quite an amazing challenge and competition that uses voice conversation in the wild, so with real people, and they can use a, I think it's called a social bot skill on their Alexa devices and I don't wanna wake up my own Alexa devices, but basically say her name and say, let's chat. And that brings up one of the bots involved in the challenge and then you can have a conversation. And then the bar that's to be reached is for you to have a 20 minute or longer conversation with the bot and for 2 3rds or more of the interactions to be that long. So the basic metric of successful interaction is the duration of the interaction. And as of today, we're still really, really far away from that. So why is this a good metric? And I do think it's a really powerful metric. As opposed to us judging the quality of conversation in retrospect, we speak with our actions. So a deep, meaningful conversation is one we don't want to leave. When we have other things contending for our time, when we make the choice to stay in that conversation, that's as powerful a signal as any to show that that conversation has content, has meaning, is enjoyable. I think that is what passing the Turing Test in its original spirit actually is. And I should mention that as of today, no team has even come close to passing the Turing Test as it is constructed by the Alexa Prize. There's several things that are really surprising about this challenge. One is that it's not a lot more popular. And two, that Amazon chose to limit it to students only. I mean, almost making it an educational exercise as opposed to a moonshot challenge for our entire generation of researchers. I mentioned it before, but I'll say it again here that it's surprising to me that the biggest research lab in industry and academia have not focused on this problem, have not found the magic within the Turing Test problem and the Alexa Prize as it formulates, I believe, the spirit of the Turing Test quite well. A very different kind of test is the Hutter Prize started by Marcus Hutter, which I think is really fascinating on both the philosophical and mathematical angle. Underlying it is the idea that compression is strongly correlated with intelligence. Put another way, the ability to compress knowledge well requires intelligence. And the better you compress that knowledge, the more intelligent you are. I think this is a really compelling notion because then we can make explicit, we can quantify how intelligent you are by how well you're able to compress knowledge. As the prize webpage puts it, being able to compress well is closely related to acting intelligently, thus reducing the slippery concept of intelligence to hard file size numbers. So the task is to take one gigabyte of Wikipedia data and compress it down as much as possible. The current best is 8.58 compression factor. So down from one gigabyte to 117 megabytes. And the award for each 1% improvement you win 5,000 euros. I find this competition just amazing and fascinating. On many levels, I think it's a really good formulation of an intelligence challenge, but it's not a test. That's one of its kind of limitations, at least in the poetic sense, that it doesn't set a bar beyond which we're really damn impressed. Meaning it's harder to set a bar, like the one formulated by the Turing test, beyond which we feel it would be human level intelligence. Now the bar that's set by the Turing, Alan Turing and others, the Lobna Prize, Alexa Prize, are also arbitrary, but it feels like we're able to intuit a good bar in that context better than being able to intuit the kind of bar we need to set for the compression challenge. Another fascinating challenge is the abstraction and reasoning challenge put forth by Francois Chollet just a few months ago. So this is very exciting. It's actually ongoing as a competition on Keigo, I think, with a deadline in May. It's a really, really interesting idea. I haven't internalized it fully yet, and perhaps we'll do a separate video on just this paper alone, and I'll talk to Francois, I'm sure, on the podcast in other contexts in the future about it. I think there's a lot of brilliant ideas here that I still have to kind of digest a little bit, but let me describe the high-level ideas behind this benchmark. So first of all, the name is Abstraction and Reasoning Corpus, or Challenge Arc. The domain is in a grid world of patterns, not limited in size, but the grid world is filled with cells that can be of different colors. And the spirit of the set of tests that Francois proposes is to stay close to IQ tests, so psychometric intelligence tests that we use to measure the intelligence of human beings. Now, the Turing test is kind of at a higher level of natural language. In this construction of arc, it goes as close as possible to the very basic elements of reasoning, just like in the IQ test of patterns. It gets to the very core, such that we can then make explicit the priors, the concepts that we bring to the table of those tests. And if we can make them explicit, it reduces the test as close as possible to the measure of the system's ability to reason. Now, the concepts that are brought to this grid world, here's just a couple of examples of priors that Francois shows in his paper. I recommend highly, called On the Measure of Intelligence. Here, prior concept is not referring to a previous concept, it's referring to a prior set of knowledge that you bring to the table. So this first row of illustrations of the two grid worlds illustrates the idea of object persistence with noise. So we're able to understand that large objects, when there is some visual noise occluding our ability to see them, that they still exist in the world. And if that noise changes, the object is still unchanged. So that idea of object persistence in the world is a prior that we bring to the table of understanding this grid world. Another prior is on the left at the bottom is objects are defined by spatial contiguity. So objects in this grid world, when the cells are of the same color and they're touching each other, they're probably part of the same object. And if there's black cells that separate those groupings of cells, that means there's multiple objects. So this kind of spatial contiguity of colored cells define the entity of the object. And on the right at the bottom is the color-based contiguity, which means that even if the cells of different colors are touching, if their colors are different, that means it likely belongs to a different object. That's a basic prior. And there's a few others, by the way, just beautiful pictures in that paper that make you really think about the core elements of intelligence. I love that paper, worth looking at. There's a lot of interesting insights in there. Just to give you some examples of what the actual task for the machine in this test looks like, it's similar to the kind of task you would see in an IQ test. So here there's three pairings, and the task is for the fourth pairing of images to generate the grid world that fits the other three, that fits the generating pattern of the other three. So in this case, figure four from the paper, a task where the implicit goal is to complete a symmetrical pattern. The nature of the task is specified by the three input-output examples. The test taker must generate the output grid corresponding to the input grid of the test input bottom right. So here, what you're tasked with understanding in the first three pairings is that the input has a perfect global symmetry to it, and also that there's parts of the image that are missing that can be filled in order to complete that perfect symmetry. Now that's relying on another prior, another basic concept of symmetry, which I think underlies a lot of our understanding of visual patterns. Again, so the intelligence system has to have a good representation of symmetry in various contexts. This is fascinating and beautiful, beautiful images. Okay, another example, figure 10 from the paper, a task where the implicit goal is to count unique objects and select the objects that appears the most times. The actual task has more demonstration pairs than these three. So figure 10 here from the paper, a task where the implicit goal is to count unique objects and select the objects that appear the most times. So again, there's three pairings. You see in the first one, there's three blue objects. In the second one, there's four yellow objects. In the third one, there's three red objects. So you have to figure that out. And then the output is the grid cells capturing that object that appears the most times. And so apply that kind of reasoning to complete the output of the fourth pairing. One of the challenges for this kind of test is it's difficult to generate, but just like I said, I think there's a lot of really interesting technical and philosophical ideas here that are worth exploring. So let's quickly talk through a few takeaways. So zooming out, is the Turing test a good measure of intelligence and can it serve as an answer to the big ambiguous, but profound philosophical question of can machines think? So first some notes on the underlying challenges of the Turing test. Let's talk about intelligence. So if we compare human behavior and intelligent behavior, it's clear that the Turing test hopes to capture the intelligent parts of human behavior. But if we're trying to really capture human level intelligence, it's also possible that we wanna capture the unintelligent, the irrational parts of human behavior. So it's an open question whether natural conversation is a test of intelligence or humanness. Because if it's a test of intelligence, it's focusing only on kind of rational, systematic thinking. If it's a test of humanness, then you have to capture the full range of emotion, the mess, the irrationality, the laziness, the boredom, all the things that make us human and all the things that then project themselves into the way we carry on through conversation. As I mentioned in the previous objectives, the Turing test really focuses on the external appearances, not the internal processes. So like I said, from an engineering perspective, I think it's very difficult to create a test for internal processes for some of these concepts that we have a very poor understanding of, like intelligence, like consciousness. I think the best we can do right now in terms of quantifying and having a measure of something, we have to look at the external performance of the system as opposed to some properties of the internal processes. Another challenge for the Turing test, as Scott Aronson's conversation with Eugene Guzman indicates is that the skill of the interrogator is really important here. That's both on just the conversational skill of how much you can stretch and challenge the conversation with a bot, and two, on the human side of it, the ability of the interrogator to identify the humanness of both the human and the machine. So the ability to have a conversation that challenges the bot, and the ability to make the actual identification of human or machine, those are both skills that are essential to the Turing test. Also, to me, it's really interesting, the anthropomorphization of human to inanimate object interaction, I think is really fascinating. And it's an open question whether, in some construction of the Turing test, whether anthropomorphism is leveraged to convince the human, whether that's cheating the Turing test, or in fact, that's an essential element to convincing us humans that something is intelligent. Perhaps as a starting point, we have to anthropomorphize something before we allow it to be intelligent in our subjective judgment of its intelligence. And finally, another limitation of the Turing test that could be narrowly stated as, why do we expect a bot to talk? What if it doesn't feel like talking? Does it still fail? I think a more general way to phrase that is, why do we judge the performance of a system on such a narrow window of time? I think, as I mentioned before, there could be something interesting on expanding the window of time over which we analyze the intelligence of the system, looking not just at the average performance, but the growth of its performance as it interacts with you as the individual. I think one key aspect of intelligence is a social aspect and a social connection, I think in part may require getting to know the person. And there's something to rethink in the Turing test that relies on us building a relationship with a person as part of the test. So you can think of it as kind of the ex machina Turing test where they spend a series of conversations together, several days together, all those kinds of things. That feels like an interesting extension of the Turing test, which could reveal the significant limitation of the current construction of the Turing test, which is a limited window of time, one time at the end interrogate or judgment of whether it's human or machine. Now, my view overall on the Turing test is that, yes, something like the Turing test as originally constructed, so the natural language conversation is close to the ultimate test of intelligence. And moreover, this is where I disagree. I think I disagree with Francois Chollet and other world-class researchers in the area, Stuart Russell and so on, that I think the Turing test is not a distraction for us to think about. It doesn't pull us away from actually making progress in the field. I think it keeps us honest. I think truly analyzing where we stand in natural language conversation will help us understand how far away we are. And more than that, I think there should be active research on this field. I think the Lobna Prize type of formulations, the Alexa Prize formulations should be more popular than they are, and I think researchers should take them very seriously. Now, that doesn't mean that the work of the ARC benchmark with the IQ test type of intelligent test is not also going to be fruitful, potentially very fruitful, but I think ultimately, the real test of human-level intelligence will occur in something like the construction of the Turing test with natural language open domain conversation that results in deep, meaningful connection between human and machine. Zooming out a little bit, I think in general, I think AI researchers don't like and try to avoid the messiness of human beings as is captured by the human-robot interaction field and set of problems. I think more than just embracing the Turing test, I think we should embrace the messiness of the human being in all the different domains of computer vision, of natural language, of robotics, with autonomous vehicles. I've been a long-time advocate that semi-autonomous vehicles are here to stay for a long time. We're going to have to figure out the human-robot interaction problem, and for that, we have to embrace perceiving everything about the human inside the car, perceiving everything about the humans outside the car. As I mentioned, this presentation of the paper is actually part of our paper reading club focused on artificial intelligence, where we discuss a couple of times a week on a Discord server called LexPlusAI Podcast that you're welcome to join. We have an amazing community of brilliant people there that discuss all kinds of topics in artificial intelligence and beyond. This particular illustration that I just love is from Will Scobey, who is an illustrator from the United Kingdom, who is part of this Discord community, so he contributed it. And in general, aside from the amazing conversations, I encourage and hope to see other members of the community contribute art, code, visualizations, slides, ideas for these kinds of videos. I'm really excited by the kind of conversations I've seen. If you're watching this video and want to join in, click on the Discord link in the description on the slide. Join the conversation, new paper every week, it's fun. Just to give you a little sense of the ideas behind this AI paper reading club, like what the goals are. So what is it? I think the goal is to take a seminal paper in the field that doesn't just focus in on the specific sort of paragraph to paragraph, section to section analysis of what the paper is saying, but actually use the paper to discuss the history, the big picture development of the field within the context of that paper. Now that could be philosophical papers like this Turing test paper, or it could be very specific papers in the field. Again, physics, mathematics, computer science, and probably quite a bit of deep learning. So the hope is to prioritize beautiful, powerful, impactful insights, as opposed to full coverage of all the contents of the paper. And the actual meetings on Discord, hopefully are less one person presenting and more discussion. There's a lot of brilliant people. They're civil, so you can have 300, 400 people on voice chat, which is a really intimate setting. And yet people aren't interrupting each other. It's not chaos. It's quite an amazing community. The other goal I'd love to see is even if we cover technical papers, the goal is for it to be accessible to everyone. So both high school students, people outside of all of these fields in general, but also I'd love to make it useful to experts in the field, expert researchers. So avoid using technical jargon, but still try to discover insights that are new, that are interesting, that are important for the researchers in the field. That's what I would love to achieve here with this paper reading club. If you're interested, join in, listen in, or contribute to the conversation, suggest papers, suggest content, visualizations, code. All is welcome. It's an amazing community. Thanks for watching this excessively long presentation. If you have suggestions, let me know. Otherwise, hope to see you next time.

https://youtu.be/MGW_Qcqr9eQ

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RZA: Wu-Tang Clan, Kung Fu, Chess, God, Life, and Death | Lex Fridman Podcast #228

The following is a conversation with RZA, the rapper, record producer, filmmaker, actor, writer, philosopher, kung fu scholar, and the mastermind of the legendary hip hop group Wu-Tang Clan. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with RZA. In the Tao of Wu, you write, when my mother left the physical world, I lost one of my main links to the universe. They say that you have an umbilical cord and an etheric cord, which is the invisible cord that attaches you to your soul, your mother's soul, and all other souls. When one passes away, you really lose something. It's physical and mental. It's real. Part of you dies. What have you learned about life from your mother? I mean, I learned life itself from my mother. You know, being one of 11 children and seeing the sacrifice that she gave to us, therefore given to life, it's really the greatest lesson of life. The thing that shook me as I wrote those words was coming up young with arrogance, confidence, knowledge of myself. They called me the scientist. We was taught you're the supreme being. In order to be the supreme being, you gotta be supreme amongst other beings. I understand that more now than I did then because then it was so literal. You know, the word God derived basically from the Greek language, as they say, and it meant wisdom, strength, and beauty. Yeah, we could have that, but the power to control life and death is something that you would assume is a God trait. So now here you are saying that you're a God, right? And you're reading the Bible, how Jesus brought back Lazarus. And you know, now it's your turn to do something. And when my mother was laying there in the hospital bed, and air was no longer coming out of her lungs and going into her lungs, where's my power to bring her back to life? So you can't truly be God. You're powerless. Yeah, or God is not the definition that we need to use to describe it because it's a translation of wisdom, strength, and beauty. So you could be that. But so I'm answering your question, what did my mother teach me about life? I learned that day on her physical passing, okay. You know what I mean? There's a physical me. Do you think about her? Do you miss her? Of course. I keep my mother in my prayer every day. And the thing I pray the most beyond giving thanks is I pray that her name is honored and remembered by my family. I don't know if the world's gonna remember her, right? Even though if you watch my movie, Love Beats Rhymes, I named the school in that movie after my mother just to leave it somewhere else. Yeah, in physical space. Yeah, exactly. But yeah, painful. The pain of my mother's passing is indescribable. Only until it happens to a person they know, and then they won't describe it either. Only the people that lost their mother, they could look at each other and they got this nod. You know what I mean? But one other thing happened to me was the joy of life hit me differently. And I think it was the realization of my own mortality versus my immortality. It's a big, big thing. And I don't know if we'll get to expound on that, but there was a joy that overcame me because I was kind of free of a certain illusion about the immortality of my physical being, versus the mortality of my physical being. And I was like, okay, wow, I understand. So that was the first or the hardest realization you've experienced that you're mortal? Yeah, and I'll say mortal, and what you're looking at here physically, I wouldn't say my soul is mortal. I would say it's immortal because at the end of the day, it's just like I could sit here and I could just hum, please, please, please, by James Brown, but James Brown is not gonna come in here and do that. So in some sense, James Brown is still here, in another sense, he's gone. The soul is here. The soul. The soul is here. Well, it lives through you, by you singing it. It lives through you, by you listening to it, celebrating it. And the hope is that the human species continues to celebrate the great minds and the great creations of the past. I would add this to that equation. When I say it's immortal, I don't think not just only because somebody sings it, right, it's like, where's the fire at right now? It's in the air. You just gotta spark the spark. Yeah. So it's always there. Are you afraid of death? No, I'm not afraid of death. I'm not trying to see it. I'm not rushing that nowhere near me, right? Because all I know is life, right? My life is living. I read a lot of ancient texts, people probably know about me, and I love one of the great teachers named Bodhidharma. And there was a thing written in one of the books of his or one of the teachings of his, and the question, somebody asked him a similar question. You're scared of death, well, what are you gonna be after you die? And his answer was, I don't know. He had answers to everything. But he's like, I don't know. They said, oh, he doesn't know that. He said, yeah, because I haven't died yet. Well, the uncertainty to some people is terrifying, not knowing what's on the other side of the door. Yeah. I mean, especially when you're young. As a kid, fear permeated my life. You know what I mean? I was actually watching horror movies, and I believe in all type of supernatural things that could or can happen. I thought I saw things as well. And whether it was being projected from my own mind or whether it was there visible to me, I don't know. But life is beautiful, and we have it, and we should use it all the way to the last drop. Realizing the mortality, the gift your mother gave to you is realizing the immortal, and in so doing, help you realize that life is beautiful. Yeah. On this topic, Quincy Jones, I read, said to ODB and you, when it rains, get wet. What do these words mean to you? Well, I think what Quincy was saying at that time was, you know, I think I was more conservative, like as a person, and like, you know, had money, women wanted me. Anything I kind of wanted, I probably could have had, you know what I mean? And he was just saying, when it rains, get wet, enjoy this. It's raining on you. You know what I mean? Don't pick up the umbrella, don't go back in the house. Get wet. Experience the moment. Yeah, and enjoy it. And I didn't take total heed to him at that time. A couple of years later, I took some heed. But at that time, I didn't take heed. And when I took heed, I think that I may have misinterpreted by looking at his example of getting wet versus my example of getting wet. And I can tell you right now, I'm getting wet right now in my way. In part, thanks to your mother, but overall, you just learned how to appreciate the rain, just like the experience of every moment. Yeah, and I'll share this with you because this is gonna be a very open conversation and I haven't had this conversation. So definitely in part to my mother, then in part to my wife. I meet my wife, it's my second wife, but I met her after my mother passed. And she was just a friend. You know, some girl I met, thought she was beautiful and actually built a friendship with her. But a few years later, when the relationship became like, you know, this is gonna be my woman, it was actually when I was doing the middle of my divorce and I was like, you know, do I run wild and hey, you know, me and my wife already filed, we were separated and do I run wild? And I didn't run wild, a little bit, but not too wild. And you know, I'm still a man, I'm a hip hop guy. I read you know how to party. Yeah, exactly. But the funny thing is that my wife now, her name is Talani, my uncle said, she reminds me of your mother. He knew my mother when, before I knew my mother. And he saw that and we ended up dating, got engaged and then her mother passes. And so now there's a total understanding of everything and we actually helped build each other back up. So of course I have to thank my mother for the awareness. Then I thank my wife for bringing that awareness to actualization, like to actually feel, I don't think I'd be talking to you right now and talking as much as I do these days if it wasn't for the security and peace and harmony that I was able to gain at home, you know? So. And like you said, you now share that look of having both lost your mom. What have you learned from Quincy about music, about business, about life? Quincy Jones is a great mind, a great artist, you know, a treasure in all reality. He seen it from when it was, he couldn't walk in, he couldn't eat in the same places he played his music at to owning places bigger than ours. So what a beautiful life, you know? He's the type of guy, if you spend one hour with him, you got a lifetime of information. And I was blessed to spend multiple hours with him and days with him and, you know, there's a certain period of time where we came across each other and he was always there to share the knowledge. Like that's another thing about him that I think is special and hopefully I picked that up is that he's always willing to share, share with his experience, his knowledge. I mean, I think he'll even share his home to the right person if he feels that that's what they need to get back on their feet. He's a very beautiful man. So just the kindness, the goodness of the man is like the thing that really rubbed off on you. Yeah, I mean, minimum, right? I mean, Quincy Jones also in his 50s as a producer produced one of the greatest albums of all time and one of the greatest selling albums of all time. Not just great critically, economically great. And I mean, he made, I think he did it at the age I am right now. So I might have a great year coming up. Time it well, yeah. So now you got a taste of what greatness is. You get to see what greatness is. So you know what- Exactly, how to strive for yourself, yeah. You've have a few people you've worked with who are fascinating like yourself. Quentin Tarantino, you worked with him. When somebody asked you to describe him with one word, you said encyclopedia. What have you learned from the guy? About filmmaking, about life again? A very generous man with his knowledge. And for me, he shared it, I think in a way that was unique in a sense of, no at a point in time, we just was super duper tight. Like I'm going to his crib and watching movies and just having long conversations about art and about life. You know what I mean? So I learned a lot. I consider him, especially when it comes to anything cinematic in my life, I consider him the godfather of that for me. I think, I humbly asked him to mentor me, which is a very humbling thing to do coming from my neighborhood, coming from who I am, coming from, I was already a multi-platinum artist. I mean, it was past the year 2000 already. So like 2001, 2002 that I asked him to mentor me. So I was the wizard already. You know what I mean? But I humbled myself because I saw in him a craft of brain power that to me resonated with me, but I was just a Patamon at it. I was a novice at it because I was trying to make movies in my music, you know, trying to make videos. And here was a man who was a master of it and an encyclopedia of it as well. And- Like film history. Film history, from whether it's the actor, the director, the cinematographer, maybe even the costume designer. He made 50, 60, he made one of the 50 greatest costume designers in his memory. I mean, this guy's brain. Both of you have pretty good memory. I'd love to be a fly on the wall with that conversation. Yeah, and kung fu movies, most of you guys- We actually started, I think we started our relationship trying to outdo each other. Knowledge-wise or what? Yeah, movie knowledge-wise. Actually, kung fu movie knowledge-wise. And I think that category, if it wasn't another category, I wouldn't have had a chance, but at least in that category, I was pretty holding my weight. Who won? You know what? I'll be honest and say that I may have said a few he didn't see, but Quentin is older than me. So he could go back- Farther. Yeah, he could go back to 72 when I didn't see one yet. You know what I mean? Yeah. Well, he said, Master of the Flying Guillotine, that I got a chance to, that you commentate over today, and I got a chance to see the screening of. He said that's one of his favorites. For you, the 36th Chamber of Shaolin, the Master Killer is your favorite. Best ever, would you say that's the greatest kung fu movie ever? It's hard to say the greatest ever, right? Because somebody may make another one, and it depends on your own phase of life. But I will put that first. If I want to introduce somebody to kung fu movies, that's a beautiful entry. You talk about knowledge, you talk about wisdom. What kind of wisdom do you draw from kung fu movies? The, you know what, the martial art itself and the movies. It's endless wisdom to be drawn, and I draw it, you know? I draw it in a way, you know, that I could decipher it in my own life. So, for instance, in the movie, Master Killer, he basically, when he does kung fu, he does a really, a style called the Hung Gar technique. And the director of the movie is actually a Hung Gar expert who has a lineage that traces all the way back to Shaolin Temple. And this director always wanted to keep his movies pure and to bring Hung Gar to the world. It's like he wanted to show the world this lineage. In fact, you just said Master of the Flying Guillotine is Quentin's favorite movie, and we mentioned in 36 Chambers, it's my favorite movie. But the action director of Master of the Flying Guillotine is the director of 36 Chambers of Shaolin. And some of the things that's happening in Master of the Flying Guillotine is really the infant stage of what this action director's gonna learn and then use later on in his movies. So that's the beauty of it. It's almost like, you know, Quentin is seeing him in his generation, so Quentin might have been the same age I was watching that movie. And then when he becomes a director, I'm at Quentin's age and now I'm seeing his work. So some symbiontist relationship there. And I'll end this question by saying, Hung Gar deals with the five animal technique, the tiger, the crane, right? The leopard, the snake, and the dragon. Those are the five, that's the five pattern. Some people go seven, some go 12, but let's just stick to the five pattern first. How do a man emulate a tiger? And you see a tiger's fist, he curls before he spawns on you. How does a man emulate a snake? It doesn't have to be only in the Kung Fu move. It's in the ideology of the snake. It's in the agility of the crane. At any moment, sometimes punching a person is not gonna work, as they would say in leopard fist or tiger paw. So sometimes you might have to poke him in the eye with the crane's beak. So having your mind able to adapt the instinct of the animal when you are being attacked or when you are being the aggressor, that's something that you don't need a form for. That's the mentality. So Kung Fu, like I said, it informs me endlessly because at first I was trying to learn all the, ah, hold my, like I can't really hit you with that and really hurt you unless I've been banging my hand a thousand times on some bricks and made it so callous or muscles are so strong. But the idea that if me and you was to get into a fight, then I'm gonna tiger up on you and take that instinct and prance when I'm a prance. Or fly away like the stork, you know what I mean? Like, yo, that's the mentality. It's much more than the technical moves. It's much deeper. Yeah. Yeah, it's interesting. I mean, when I see the Kung Fu movies, because I love martial arts, all martial arts and competitive ones too, like the actual competitions and so on. It just seems like Kung Fu movies go much deeper than just like the techniques. Yeah. I mean, if you see it, right? Even I watched a great MMA fight recently, and just interesting because he was on top of the guy, you know, and the way he got from under him, you know? It had to be, you know, his spirit got from under him. It's something like mixture of crane and whatever. Snake, ill, with the slippery ill technique. Yeah. You know, I love that when people become artists in the cage or that's much bigger than just like winning, much bigger than particular techniques. It's just art, especially at the highest level competition where millions of people are watching. Which is pressure within itself. Yes, that's art under pressure is even more beautiful art. You know, you look at some of these fights and you wonder like why somebody wins and lose. And sometimes the less talent guy could win because he could deal with the pressure. But the other guy, he could have beat him there with someone else, but not in this arena. So you're a scholar of history, including hip hop history. I've listened to so many of your interviews. You've spoken brilliantly about some of the big figures in hip hop history, Tupac, Biggie, Nas, many others. Maybe let's look at Tupac and Biggie. What made them special in the history of music? That's a good question. So I don't know if I'm the authority to answer it, but I'll just speak my piece on it. And maybe I can just add on, cause I'm sure it's a lot of people that spent a lot of time with them that could speak on it. But just as a fellow artist, I think not only was B.I.G. a dope lyricist, I think he had a voice that was really immaculate in a sense that some rappers get on top of music and you gotta get used to them or you gotta vibe with them. But he make a record sounds like a record immediately. If you go back and listen to his music, you could take his voice and put it on anything. And for some reason it sounds like a record. You know what I mean? You mean just like the raw voice of the man? Yeah. So you could just listen to it raw and it sounds like a record? Yeah, but if you take his voice and put it on any beat, he just has a voice, it's immaculate. So his lyrical skills and all that was great. And you gotta think once again, he's doing all this, he's not even 25 years old. Yeah. Then you go to Pac, once again, immaculate voice. But what Pac had I think was a way of touching us on all of our emotions. And especially on, Pac had the power to infuse your emotional thought, like Brenda has a baby, they're a mama. But then he had the power to arouse the rebel in you. You know? Yeah. And those two things, actually he was probably more dangerous than Big, Notorious B.I.G. Like Notorious B.I.G., we could party with him to this day, we are still, but Pac was probably going to a point, he was more going into the Malcolm X of things and society fears that. Yeah, so he was really good at communicating love and at starting revolutions. Yeah, yeah. And that's dangerous. Very dangerous. And Big communicated love, but he wasn't starting revolutions. Well, it's interesting to think about what the world would be like if they were still with us. But it's the way the world, Hendrix, a lot of those guys just go too soon. Yeah, it's a peculiar thing. Now, you asked me earlier, am I scared of death? And I answered you, no, not scared of death. I mean, I'm not trying to see it though. You know what I mean? Yeah. It's like, that was the block of death. It's like, I'm not really going right there right now. I'm making a left or right turn. You know what I mean? Unless it was mandatory for some greaterness, greater good, it's like, okay, I gotta drive through that. You know what I mean? Yeah, but it can still happen. That's the meditation on death part where you could die at the end of today. Yeah, you could die. Well, dying and death, I think it's two different things, personally. The process, you mean, of death or just? Yeah, I mean, you could die. Like I said, you could die every day. You could die and not be yourself. You know what I mean? Which is crazy. But to get to a point of no return, that's a whole nother chamber. I mean, there's some sense in which RZA, the producer, becomes somebody else completely when you're making a film, becomes somebody else completely when you're, I don't know, playing chess, becomes completely something different when you do kung fu or watch kung fu or when you're a family man. All of those are little deaths when you transition from one place to another. So it's not like you're one being. You're many things. Yeah. I would describe, now I would describe that as all life, though. Yeah, it's fun. Outside of you and anybody on Wu-Tang, who is the greatest rapper from a lyrics, like a wordsmith perspective in hip hop history, or some of the greatest, maybe some candidates? Let's name a few. I mean, you're gonna have to start with Rakim. You know? You're gonna have to pick Coogie Rap in there. You know what I mean? So going back. You're gonna have to pick up with those brothers first. You might have to, if you want a good, technically, you might have to start with Grandmaster Cass. You know what I mean? Who you might not, you might not even have heard of. Nope. You know what I mean? But you may have sung his lyrics every time you sang Sugarhill, Rapper's Delight. Because that's his. That's his. Yeah, they copied his, and they made it theirs. Yeah. But point being made. But I'll name a couple more. I gotta put Nas in that category. You know, we got a chessboard in front of us, and one of the greatest chess players, the youngest Grandmaster, you know, before, I think, Carlson, was Bobby Fischer. All right, so let's use Bobby Fischer as American. One of the greatest American chess players. Of course, Susan Pogar may have tied his record as the youngest Grandmaster, and she's the youngest female Grandmaster, I think, to date. But he was a Master at what, 14? Yeah, something like that. Right? So now, to me, I met Nas when he was 15. He was already a Master Lyricist. It takes about 10 years to become a Master Lyricist. So by the time the world heard Wu-Tang, most of us had 10 years of rapping in us already. So that's why you met us at Master-level. The Jizzle was already a Master when Nas was a Master, but Jizzle was 21, Nas was 15. Nas is like the Mozart of rap. Yeah, or the Bobby Fischer. Just a Bobby Fischer, just born something in him, or maybe those early years, just, because he's not just good at the lyrics, he's also, he goes deep with it. Just like you, so there's depth. It's not just mastery of the word smithing. It's just the message you actually send across. Information into a small phrase. That's the whole thing of energy. How do we condense all that energy into this so that it can feel that? And he's definitely one of those artists, MCs that does that. And he was doing it at 15. Like I said, I think I'm five years, or four or five years older than Nas. So I was always feeling my confidence of what I was doing, but I was like, this kid is only 15. I gotta step up my game. When he turned 19, then we got Illmatic. Yeah. From you, what are the best and most memorable lyrics? You've ever written? Wow, that's a hard question for me. The stuff stand out, like stuff you're really proud of that was important in your career? Yeah, I mean, I think I did a song called Sunshower. I don't know if it, we put it on the Wu-Tang Forever double CD, but only on the international version. But if anybody could go get those lyrics and write those lyrics down, you could just put that in your pocket and I'm sure it'll answer at least about 25% of your life's problems. Well, that's a good one, Sunshine, where you talk about religion and God, that's good. Tomorrow, I think it's on A Diagram. I'm not a record guy, I'm a song guy. Might've been A Diagram. What, do you have a lyric from it? Yeah, the answer to all questions. You're talking about God. Yeah. The spark of all suggestions, of righteousness, the pathway to the road of perfection, who gives you all and never asks more of you, the faithful companion that fights every war with you. Before the mortal view of the prehistorical historical, he's the all in all you searching for the Oracle. Good one, man. This is such a, this is so good. A mission impossible, it's purely philosophical, but you can call on your deathbed when you're laying in the hospital. You will call him on your deathbed. I had a big, I have a scientist friend, well, my wife's best friend, Rebecca, she married a scientist, they're both scientists, they're both were scientists, and she married Dr. Neal. I ain't gonna say their last names. But Neal and Rebecca, you know, they're my wife's best friends, so they come over, and me and Neal, we go through the longest debates of science and religion, we just go, we could go break day with it. And, you know, before he had a child, he was more adamant, and, you know, there's, you know, I don't believe in God, you know what I mean? After a child, he still kept his thing, but I just hit him with the question. If you was about to die, because now you got a child to think about, right? It's different when you're thinking about yourself. I said, if you was about to die, you don't think you're gonna make that call? He's like, I'll make that call. And it kind of inspired my lyric, because it was like, yeah, who you gonna? And I just wanna say, so you mentioned lyric, that is one of my favorite lyrics, but that's part two to Sunshower, was the prequel to Sunshine. So if you ever get a chance to check out Sunshower, it starts off with, trouble follows a wicked mind. 2020 vision of the prism of life, but still blind because you lack the inner. So every sinner could end up in the everlasting winter of hellfire. With thorns and splinters prick your eye out, you cry out, your words fly out, but you remain unheard. Suffering internal and external, along with the wicked fraternal of generals and colonels, letting off thermal nuclear heat that burns you firmly and permanently upon the journey through the journal of the book of life. But those who took a life without justice will become just ice. It's been taught your worst enemy couldn't harm you as much as your own wicked thoughts. But people ought be nought unless in wrought, so they find themselves persecuted inside their own universal court. So that is a long one. It's like a three pager. Wow, that is about life. That's like character, integrity, how to be, how to be in this world. And that ultimately connects to God. Who is God to you? I'm glad you just asked that question because I actually, I'm gonna have to make a distinguishable separation here. All right. And it's funny because I heard recently, I heard a rabbi was debating with this historian, Dr. Ben, I can't pronounce Dr. Ben's name, but they was debating. And in the debate, they started going back through the etymology. They went way back beyond antiquity because they was debating. And so there was some things, they was going deep. And they really went far, far back to kind of the first word of God. And it was, when they pronounced it on this particular debate, it was Allah. And they said from that, they got Elohim. I've already agreed in my heart, in my life, that the father of this universe, proper name is Allah. And of course, in Allah, I get all. And I don't think that God is the same as that. I think Allah gives birth to God. In fact, if you take the word Allah, A-L-L-A-H, and you take it through numerology or numbers, the number A being, letter A being one, L being 12, and you add it all up to its lowest, to the last denominator, you're gonna get the number seven. And the number seven is gonna bring you right back to that letter G. So Allah borns God, but God don't born Allah. How does that God, how does Allah connect to the oracle that you're going to be calling for when you're laying in the hospital? Well, what I was saying in that particular verse was that we're looking for the oracle. We're looking for somebody else or something to help us that nobody can really help you at the end of the day. And we're speaking on, so now that we, I don't wanna say we're speaking on religion, but we're speaking on a way of life and a way of thinking. And I've read many books, of course, and I can say there's no book that, the book that is the most strongest book I've ever read is actually the Holy Quran. It's stronger to me than the Bible, which I've read. It's stronger than quantum physics, which I've read. It's stronger than the Bhagavad Gita. It's just, and I read once a British scholar said it's the most stupidest book ever written and it doesn't make sense. And so I said, oh, I see why he says that. I understand exactly why he said that as well. Why is that? Because the structure of the words are just, it's peculiar, you know what I mean? But it's almost like how some people's songs, you don't really know exactly what they say until years later. Yeah, you have, actually with Joe Rogan, I think you talked about how a joke of Dave Chappelle's hit you like a long time after this. So this is kind of like the Quran. I tend to believe that we, that human beings cannot possibly understand anything as big as these ideas. So just, I don't know, do you think that, like, are you humble in the face of just the immensity of it? To be honest, yes. I'm humble in the face of the, you can say the word again, I pronounce words funny. The omnipotence, the omnescence, the magnitude, I'm humble in the face of Allah. The problem that I may have had was that I wasn't humbled in the face of God because it's just a definable thing. And that's why I think a lot of us, and not saying that, you know, I know when we say God, we're trying to say Allah, like people was saying that, but you're actually not saying the same thing because you're actually putting something beside Him. And that's the reason why you can have all, there's many gods, you can find a whole bunch of them. You know what I mean? But you're not gonna find many, there's nobody beside Allah, Allah is one. So I know it's a whole thing, but that's my heart is there. I'm humbled by it, I'm at peace with it. And it doesn't take nothing or demerit anything from myself. That's the beauty of it. It doesn't take nothing from me, from being who I am. So if I say, if somebody woke up, yo, peace God, I could take that because they're telling me that, yo, I'm a man of wisdom, I'm a man of strength, I'm a man of beauty, or some attribute of that. You know what I mean? So Wu-Tang, they the gods of rap. There's wisdom there, there's strength there, there's beauty, then we'll take that. Yeah. So Wu-Tang is one of the greatest musical, artistic, philosophical groups ever. Let's look hundreds of years from now when humans or robots or aliens or whatever that's left here, they look back, what do you hope they remember about Wu-Tang? What do you hope the legacy is? Well, even if it's thousands of years, I hope we don't get rid of the humans. But you know, look, whatever happens is gonna happen. But I think that my philosophy on it is that we're gonna continue to advance and continue to advance things around us, but I don't see us becoming extinct. Well, I mean, the reason I bring up sort of Wu-Tang in that context, and this is a special moment in human history, it's like 100 years and we've created all of this music. Just if you think of all the richness of music that's been created over 100 years, it's like, it's not obvious to me that that's not going to stop. Right. Like there's a flourishing here. So it's funny, because I could see where the book of human history is written. There's a chapter on this period of time. And one of the things we did well is like all the technological innovation with like with rockets and with the internet, but then there's also the musical innovation and film innovation. Just so much art that's being created and Wu-Tang is a huge part of that. So I just wonder what, like, if there's a few sentences written about Wu-Tang, it just makes me wonder how they remember. I would hope that people will, no matter how many years are inspired by us, but I will say if I can just use Wu-Tang as itself. So we first started off the witty, unpredictable talent and natural game, right? Natural game, meaning natural wordplay. And then we went to the wisdom of the universe, the truth of Allah for a nation of God. Wisdom, universal, truth, Allah, nation, God. It's just like, so this is go back to a nation of God. Let's just take the last two letters. A nation of wisdom, strength, and beauty, right? You know, and I'm gonna go a little political here, but not going political. As we're saying we're the greatest country in the world, what makes us the greatest? That should be a question we ask. Is it our wisdom? Is it our strength? Is it our beauty? Now, let's just say off the easiest answer, you know it's our strength. We got the nukes. Nobody can really, you know, between America and Russia, they said, you know, that's the argument. Who could beat them? But where's the wisdom? Then they can argue, well, we got the technology. All right, but then where's the beauty when there's so much suffering in the people? So it's not complete. The hope is that the wisdom is in the founding documents, in the imperfect, but wise founding documents of that celebrated freedom, that celebrated all, the ideas, sort of having a lot of nukes, having a lot of airplanes and tanks. That's not important. And the hope is whatever we're doing here with this quote greatest country on earth, that we preserve the ideas and help them flourish. Yeah. Like you said. Well, that's what I mean. So if we could get, so if you go back to the Wu Tang, I'm saying, that's what we're striving for. We're striving for that. You know what I mean? But you started on predictable and just like. Yeah. Just, yeah. But like God deep pretty quick. I got to talk to you about Bruce Lee. Who's Bruce Lee to you? Who is he to the world? What ideas of his were interesting to you? Like what, you know, you talk about like Hendrix and music. Bruce Lee is that a martial arts. He just seems to have changed the game. Yeah. You know, I went as, I guess, I don't know what the word bold is the right word to say, but I went as bold as to say that he was a minor prophet. And I got that concept from the Holy Quran where it says that we send prophets to every nation, every village. We don't let nobody not hear the word in some form. Cause it won't be fair. And so if a law is merciful, even a man who's deaf has to somehow get a sign. I don't know if Moses saw a burning bush. It was nobody else to talk to. So he had to talk to the bush. I don't know. It could have been the bush. This man too, right? Yeah, yeah, yeah, yeah, the bush, yeah. But point being made, it says that there are minor prophets and I see Bruce Lee as one of them because what he brought to the world through martial art was a whole shift in the dynamic of thinking, you know? And that happens when certain entities are born, but he didn't do it only in a physical sense. He was also for the philosophizing in the same process. And he was also striving to be the best of himself. So you got three things going on. I studied Bruce Lee multiple times. And first of course, when I saw my first Kung Fu movie, it was the fake, it wasn't really Bruce Lee. It was a few green hornet clips cut together. And then I saw a black samurai. Then my following Kung Fu movies was like Fearless Fighters, the Ghostly Face, you know, the Fist of the Devil. But basically in Fearless Fighters, the lady put the little kid on her back and flew across the ocean, across the lake, right? So Bruce wasn't doing that. And then I went on to Five Deadly Venoms and Spearmen and 36 Chambers and these movies are beautiful and yet they're all heightened. Bruce, they're heightened beyond doable. You're not gonna- Yeah, it's like surreal. They play with the world that's not of this world. Yeah. Bruce played with this world. So when I first saw Bruce, I actually didn't think he was as good as these guys. He can't fly. He's not flying in the movies, right? But then when I saw, cause the first one I saw was The Big Boss, which they retitled Fist of Fury. But then when I saw Chinese Connection, which is the real Fist of Fury, right? I saw something different there. And I got enamored. And then of course Enter the Dragon, right? Just really complete. That's why my first album is Enter the Wu-Tang, 36 Chambers of Shaolin. So it's Enter the Dragon and 36 put together cause those are the two epitomes. So what happened is, you know, that's young me. Then teenage me studies him again. And I realized, wow, look at his physicality. Look how he's really, he's moving for real. And then I studied him again. Wow, look at what he's saying. Then I studied him again. Wow, look at what he stands for. Which do you like in the realm of martial arts? The real or the surreal? What the dance between the two? Yeah, I like the dance between the two because a movie to me is to entertain you. So I'm cool with Obi-Wan Kenobi disappearing out of the cloak when Vader strikes him down. And then I'm like, yo, what happened? And he's like, run Luke, run. I'm cool with that, right? Because that's the imagination. And the imagination gets stimulated to the point to where as things that we saw imagined by our artists, we strive to create in our real world. Thus, Star Trek to me is just a precursor to our cell phones. So for me, I like the mix the two. So for me, I like the mix the two. Yeah, it's funny how science fiction, pushing into the impossible actually makes it realized eventually. Yeah, we humans, once we see an idea on screen, no matter how wild it is- We're trying to make it. Yeah, we're trying to make it. There's some young kid that gets inspired when we watch that. Be like, I'm gonna build that. Exactly, so I don't know who's gonna come with the Back to the Future time machine, but do you have any classmates that you think- The time machine? I thought you were going to Back to the Future, like the, what is it? The hoverboard or like- Yeah, we're there at least. Yeah. Somebody, they got, you seen the one on the water? No. No, you know- Just close on the water? No, the surf hover. It's great, it's dope. Nice. It's dope. It actually, if you are Back to the Future fan, you feel like you made it to, you made it there. Yeah. Well, now we just gotta work on the time travel. And it was cool to hear you talk about the master of the flying guillotine today, that that inspired the lyric for the Wu-Tang Clan and Nothing to F With. Yeah. How does that go again? What, the curse word or the lyric? No. I don't remember the curse. I am Russian, but I don't remember the curse word. But the lyric. I said, I be tossing and forcing. My style is awesome. I'm causing more family feuds than Richard Dawson. And the survey said, you're dead. The fatal flying guillotine chops off your head. Yeah. Yeah. And it was interesting to see the guillotine in the movie today. How, I don't know. That's surreal, right? But it's not. It's like, it's engineering, it's both surreal and it just, and it adds this chaos into this real world and then challenges everybody to think what you're gonna do with that. Yeah. How are you gonna beat it? Yeah. How are you gonna beat it? Both when you have like the good and the evil and the mix of the bad guys and the good guys and you're not sure who the bad guys are. It's the old question of good versus evil, right? Yeah. Like you said, then the question of who was good, who was evil, but they all had a similar problem when the guillotine came. But in terms of the real, you mentioned the godfather, good and evil, that's your favorite movie. Yeah. What makes it great, do you think? The characters, the study of family, of justice, of power. What connects with you? Oh, I mean, every one of those themes connects in the real and it connects in a cinematic way as well. The difference I think with me and the godfather was, I seen it during a period of time when my father was absent and therefore family structure and family values was actually adopted in my family because of that. Me and my brother, Devon, we actually took so much heed to that movie in our family life. And we kind of mimic that family in this structure of somebody has to be the leader of the family, even if it was the younger. Michael was younger than Sonny and Phaedra, you know what I mean? But he was worthy. And my brother, Devon, is older than me and my brother, King, is older than me. And it's funny, sometimes Devon calls King, Phaedra. I know King wants to, because King was actually, he could beat our ass, see my language. Yeah, yeah, yeah. But you're Michael. Yeah, and not by choice, just by definition of that's what I am. You know what I mean? And it's just a blessing for me to have my older sister, my older brothers, and my younger brothers look to me as just as a good light in the family. And like I said, that movie helped us. My sisters too. The cool thing about my family, I don't know if I share this a lot, it's a big, we all watch these movies together. And so, the Eight Diagram, Pole Fighter, Master Killer, Five Deadly Venoms, my family knows these movies. It's not just I know them, right? And then you extend it further, my friends know them, right, too. So there's a language that we all can have that actually film has informed our communication. So The Godfather, which also is still a fictitional story of something, but since it was based in reality, based on something real, and it was human, it wasn't so heightened, I think the purity of it resonates. And the purity of it is something that resonates with me. You gotta plan ahead. He didn't wanna deal with the drugs, but that time of business was upon him. It's almost like, and this is a tough one, sometime when the Muslim brothers come from the Middle East to America, and they open up delis, they would sell ham. And we would go in there and complain to them, and make them, they used to get mad at us when we came in. But that's as a kid, but as a man, I'm like, yo, he's here to sell. Now, he still don't have to sell the ham. Fido Cody on, didn't wanna sell the drugs. Okay, he didn't have to do it, he didn't do it. And it cost him some bullets. So eventually, somebody in the family ended up doing it. You see what I mean? What about this idea that it's family before everything else? So there's different laws you live according to in this world, and family is first. Yeah. That's mathematically correct. I like that. I mean, there's a certain sense of, you look at powerful people, you look at Putin, there's a certain sense in which the people who are in the inner circle, that's who you take care of. That's family. And anyone else that crosses you, that there's a different set of ethics under which you operate for those people. Well, Jesus said the same thing. You know, when he said, love thy neighbor and thy brother, he was talking about that community. When that other lady, the Samaritan, say, hey Jesus, I'm not feeling, my brother not feeling so well, and he say, give not that which is holy unto the dogs. If you gonna tell a woman, give not that which is holy unto the dogs, and she's a woman, you just called her a dog. If I translate that in hip hop, she's a female, you called her a dog. I know how that goes. But she said to him, but even a dog is allowed to eat the crumbs that falls from the master's table. And he went and helped her. Now let's go back to what you said about Putin or Vito Colonna, myself and my family. Of course the family is first, but once the family is good, it has to then spread to the community, then to the state, country, world. The problem we have sometimes is that, and this is the reason why a lot of powerful families was overthrown, like why do they behead their own king with the guillotine, right? Because that, once the family was strong, they didn't let the wealth, the opportunity expand out. And look at Wu Tang, yes, our family was made strong first, but then all the Wu members able to form their own corporations and they had their own sub families. It has to grow out. And they took over the world. You've talked about being vegan. And I don't think I heard you explain this because it connects somehow about how you think about life. So you talk about when your family's good, you grow that like circle of empathy, you grow the community. Is that how you think about being vegan? That just the capacity of living beings on earth to suffer that you just don't wanna add suffering to them? Yeah, I mean, you said it clear. It's like nothing, no reality. I came to a realization that nothing really has to die for me to live. No animal, the plants themselves, right? So let's just say, you want a steak, which is probably the most, I don't know the most expensive piece of meat, but let's just say the steak is top of the line, nice steak. And you eating the steak for the protein to help build your muscle. And I don't know if you got it from a cow or a bull, but whether it's a cow or the bull, they grow to about 1500 pounds. And if it's a bull, it's all muscly muscle and it's only eating grass. Yeah, yeah, there's, yeah. It's possible to both as an athlete and just as a human being to perform well without eating meat. There's something, especially in the way we're treating animals, to deliver that meat to the plate. I think about that a lot. So I do, I'm a robotics person, AI person. And I think a lot about, I don't know if you think about this kind of stuff, but building AI systems as they become more and more human-like, you start to ask the question of, are we okay if we give the capacity for AI systems to suffer, first to feel, but then to suffer, to hate and to love, to feel emotion. How do we deal with that? It starts asking the same question as you ask of animals. Are we okay adding that suffering to the world? Right. And I don't think we should add the suffering because it's not necessary. Like, look, if it's necessary, right? Because we're, you know, survival or the first law of nature is self-preservation. If you are in a desert and there's nothing else to eat, but that lizard, yeah, okay, you gotta do what you gotta do. Lizards gotta go. Yeah, you gotta go. You gotta do what you gotta do because at the end of the day, man is, when they say man has dominion over these things, his dominion is almost like a caretaker. The way we do our dominion, we dominate it, eat it, cook it. Like, who's the first guy that looked at the lobster and was like, I'm gonna eat this thing. You know what I mean? Like, first of all, it's hard to eat it. You gotta go through a process to get that. A crab, I remember we used to eat crabs when we was kids and I didn't know why I was always getting itchy throats and all that. You know, you can kill, you don't know, just eat. But at the end of the day, a crab didn't provide no more than a finger worth of meat, maybe. And it's hell getting that stink, getting it out. It's like, it's not worth it in all reality. You could have gave me a banana and did better for my body and my appetite and my being fulfilled as full. Like, look at the blessings of life, right? If you take a seed, or you get an apple and you eat it, in that apple is multiple seeds in it. If you plant that seed, it'll give you a whole tree with a whole bunch of apples with all multiple seeds. But if you kill a fish, it can't reproduce, it's done. If you kill a cat, it's done, it's nothing coming back. But when you deal with the plants, even after you eat the apple and then you defecate, your defecation is what feeds the ground that caused the apple to grow more. Yeah, it's a circle of life. And especially there's a guy named David Foster Wallace. He wrote a short story called Consider the Lobster. If you actually think philosophically about what, from a perspective of a lobster, that's like symbolic or something, because you basically put in the water, like cold water, and then it heats up slowly until it's no more. Yeah, it must have been like, you think they started eating lobsters in the Inquisition? Yeah, yeah, yeah. They just enjoy, they were probably enjoyed torturing animals and they realized they're also delicious after the torture is finished. That's probably how they discovered it. Let me ask you a question. I know you're asking me the questions, but I just wanna talk a little bit about the AI. You said something about trying to put the emotion in it. Yeah. Right? So are you thinking there's an algorithm for emotion? Yes, but I think emotion isn't something that there's a algorithm for, for a particular system. We create emotions together. So emotion is something, like this conversation, it's like magic we create together. So I've worked with quite a few robots, I've a very simple version of that. I've had Roomba vacuum cleaners, I've had them make different sounds and one of them is like screaming in pain, like lightly. And just having them do that when you kick them or when they run into stuff, immediately I start to feel something. Right, so the emotion, okay, so the emotion you're saying is imposed back on the human, but I'm asking, do you think there's an algorithm for the emotion to be imposed from machine to machine? Yeah, that's a really good way to ask it. It's difficult because I think ultimately, I only know how to exist in the human world. So it's like, it's the question of if a tree falls in the forest, nobody's there to see it, does it still fall? I still think that ultimately machines will have to show emotion to other humans and that's when it becomes real. I've been thinking about this a lot too. I just, okay. Now I'll come at you with this because I've been thinking about this and this is your field here. Well, do you think emotion is wave? Like light is wave or do you think it's particle? So emotion is just a small, it's like a shadow of something bigger and I think that bigger thing is consciousness. So emotion is just- I don't know if it's a wave or a particle. Y'all haven't thought about that? I have thought about it, whether there's something like, whether consciousness or emotion is a law of physics, like if it's that fundamental to the universe. I had a lyric that said this. It comes out, they did this documentary about the planet and I wrote a song, it's called The World of Confusion. And I'll try to paraphrase the lyric, but in the world of the confusion where there's so much illusions, we suck the blood from the planet. Now it needs a transfusion and the redistribution of wealth, of health and wealth of self and a deeper understanding about mental health. The doctor described the physical solution. The psychiatrist wants to build a bigger institution, but neither have the solution or the equation to make an instrument to measure the weight of the hate vibration. What is the weight of hate? Is it heavier than the weight of love? Is it heavier than the weight of lead inside of a slug? With just 10 milligrams, it's all it takes to kill a man. But anyways, then I go on from there. But then- Damn, that is good. But the question, you see the question there, right? Yeah, yeah, yeah. And that- Can it be measured? Can that be measured? I think so, I think so. Just don't got the instrument yet, right? Yeah, yeah, we're in the dark ages of that, but I think it could be measured. I think there's something physical, like something that connects us all this much. You know, we tend to think we humans are distinct entities and we move about this world, but I think there's some deeper connection. And, but we're so, listen, science is in the, we just had a few breakthroughs in the past 100 years from Einstein on the theoretical physics side. We don't know anything about human psychology. We barely know much about human biology. We're trying to figure it all out. Yeah, I had another theory, because, you know, you think about quantum, right? As long as you say that there's an uncertainty and you have me believe there's an uncertainty, then there's an uncertainty. But if there's not an uncertainty, what happens? So I'm only saying that, it's not saying that's, cause you look at quantum computers, they're gonna give you the O, the one, the one, the O, they're gonna take two things and make it eight things. And by the time you multiply four of those things together, it's like this chess board, right? The moves goes into the millions. But the thing that's introduced is the uncertainty, right? You're gonna make a move. You know this already, right? Because this has been played a thousand times, but sooner or later, something uncertain is gonna come in or make your next move. So. I like the weight of these. They add the certainty. I think just like we were saying, unpredictable, there's something about us humans that really doesn't like everything to be fully predictable. I mean, chess too is perfectly solvable. There's nothing unpredictable about chess. Right, I could agree to that because Bobby Fisher said in one of his books, which I actually love what he said, he said, every game of chess is a draw. Yeah. The only way somebody win is when one of us makes a mistake. I mean, it doesn't get any better than that. Yeah, it doesn't. What is chess? Like, how do you think about chess? What's at the core of your interest in chess? Do you see Kung Fu, music, film, all of it, life, all just living through chess? Yeah, I see. It's the most stimulating passage of time for me. That's also, it's like, it's a pastime that stimulates my mind, my music, my thoughts about life at the same time. So while some pastimes is like, say baseball is a pastime. And baseball can stimulate you depending on how you look at it, right? But most likely you're not gonna get this much brain activation, this much calculation, and this much thinking about yourself in a game of baseball. I mean, the player maybe, but not the viewer. Chess is something that I can engage in too. And even though it's a pastime, it's giving me all the stimulation of real time in my life. It's funny, cause it's also, it's a funny game cause it's connected through centuries of play. Just some of the most interesting people in the history of the world have played this game and have struggled with whatever, have projected their struggles onto the chessboard and thought, and the nations have fought over the chessboard the Soviet Union versus the United States. Bobby Fischer represented the United States. Spassky represented the Soviet Union. Yeah, I gotta, before I lose track of it, when we were talking about the Godfather, you were in American Gangster, great film. You said it's one of your favorites too. What, you were in it with Denzel Washington. What makes that movie meaningful to you? What was it like making that movie? Cause it's a great, great American film. That was a great American film. There was so many things in that film. Being a part of that film was probably a blessing and a treasure. Cause even if I wasn't a part of it, this court sets great filmmaking and to me a really cool, great story. The thing that I love about it the most really is the process of it. You know, which part of the process? I wouldn't have known the process if I wasn't part of it. So as a film, joy, it was great film. But even the process of making it was like high level education for me on multiple levels. I'm working with Ridley Scott, which is, and this is a bold statement if I say this here, cause I got a lot of friends that's gonna probably, but he's probably the best living director. Because watching him allowed me to understand a principle that I've coined to him and I don't know if people use it yet, called multi-vision. He seems to have the capacity to see eight things at one time. I heard on Robin Hood he had 18 cameras. I wasn't there for that. And you think he keeps them all in his mind, just sees them? I seen him do it when he went to the monitors with the video playback guy. I seen him bring everything back to a point, but nothing was the same on the frame. He was already there. And he knew if he had what he was or not. And he placed the cameras there and he saw it like in his own way and I peeped it. I peeped it. And I said, yeah, and I just humbly asked him. He was gracious enough to speak to me and talk to me and confirm what I thought I saw. He confirmed it? He confirmed it. And I was able to utilize it as I'm a filmmaker now. And I see, I can at least see three or four things. I can't see eight yet. I'll be there though. But I could definitely, even right now, just I could go like this in the room. Okay. I got it now. I got like how to make this right here, which is just us all sitting. How do I make this? Look, boom. Come on on him. There's a story there. It's a story there. And I might just go off his hanging watch or his hanging wristband. Yeah. You know, because there's something else there too. Is he dead? We don't know. Exactly. So he has this and even though this is the scene. Yeah. You keeping that in mind, all of this in mind. What about like, can you give an inkling of other parts of the process, like the editing? Like where does the magic happen? Another thing, Pedro, I don't pronounce Pedro last name right. He's a cool guy. I had a chance to play rugby with him. He was on, was he on my team? Yeah. Well, we were in both teams, but Pedro, the editor who, you know, edit many great films. Once again, he has, I will call it deciphering power. A good editor is a decipher, almost like breaking the enigma because he's dealing with thousands, or we'll call it a film with millions of feet of film, at least a million feet of film. That's a lot of film before feature. He's dealing with that, but he's dealing with multiple cameras. Yeah. So it ain't like it's like two cameras. He got an A, B and he could just go back. No, he may have six cameras and he has to go back and deal with that process. And you know what? He knows how to tell the story again. And he proved it on American Gangster as me being a witness, because it's so much information. It's even when the brothers all start getting their little business and he picked one in the Bronx and he just captured every neighborhood within one minute and you knew what would happen. You knew it all. You saw the whole rise to fame. So you watch the Palmer and Scarface who does it in two minutes, but it's only one character. So you see him go to the bank, he drops the money off. You see him by the lion. You see him gets his wife or the tiger. You see him gets his wife. You see all that. Then it ends on a big shot of him in the big house with all the TV screens. And you seen him go through it, right? But in American Gangster, you're gonna tell that story of rising, but you also got to include these five brothers. Yeah. And that's all in the edit. Oh man. But also all in the director, knowing that as well. And you gotta keep track. You gotta keep thinking about them. Cause that was a story right there. Yeah. Well, I was hearing it. I don't know if they was taking pictures of him or yeah, it might just have a little party over there. Yeah. Chess, I think. Yeah, I like it. They're playing chess in the distance. This is great. You said that you were always an old soul and see the world as if you're 200 years old. I like this line. Because your creative vision allows you to see the final piece you've created or you're creating very quickly, quicker than others. I heard that as if you've almost like lived many lives. So you have this experience that allows you to see the vision. So let me ask you on creativity. Where does this creativity behind RZA come from? This both musically and film wise. That I don't know if I have the answer to that one, right? What is it? No, seriously, where does it come from? Only thing I could say about that is that for some reason, it seems endless. And that's peculiar when I think about it myself because I was taught a lot of things from the jizzer. He introduced me to mathematics. He introduced me to hip hop itself, to break dancing. I got other cousins that introduced me to graffiti. I got other cousins that introduced me to DJ. And I realized that I had a lot of introductions, but the jizzer definitely, my older cousin gave me a lot of early inspirations. And not saying that he's not creative, as creative as he was then or now, I just didn't, the wide span of creativity, I don't see him doing that, right? And I don't see my, the cousins that taught me how to DJ, I didn't see them move from DJ into making the beats. My cousin that, who actually got me into instruments, I didn't see him leave funk and rock. He didn't go, like I'm orchestra composing now. Yeah. So, I just said to myself, I just accept myself as a artist, as a creative artist. That's what I am. I have to accept that. Now, where it comes from, I don't know if I was to try to say where it comes from, like, hey, give me some type of answer, I'll say from life itself. But what does it feel like? Because you mentioned during this pandemic, for example, for some reason more came to you in terms of writing. And so, do you feel like you're just receiving signals from elsewhere or like, do you feel like it's hard work or you're just waiting? Wow. It's not even waiting, no, it's a hard work. It's almost like, I said in one of my other lyrics, this is for the MC part of it. I said, MCing to me is easy as breathing. So it's like breathing. Yeah, it's just like, in fact, this actually was a scientific thing I read about that, now that you said that. You heard this, I know you've had to hear this. They say that, the atoms in our atmosphere, which seem to be infinite in number, are not infinite in the space they occupy. Right, because they're in our atmosphere. And so there's a chance that at least one million atoms that you breathe in your life was breathed by Galileo. You heard this before, right? Yeah. Okay. It's very accurate. Okay, how does your body digest it? Well, let's start at the fact that most of the atoms that we're made of is from like stars, right? From stars, so like we're all really connected fundamentally somehow, and then they get the atoms that make up our body come and leave. And the same with the cells that are in our body, they die and are reborn. And we don't pay attention to any of that. That all just goes through us. I don't know. That makes me feel like I'm not an individual. I'm just a finger of something much bigger, some much bigger organism. Well, because you're drinking the coffee there, right? You're gonna digest that. You're gonna digest those atoms, whether you're gonna put them through the bowel or through the urination, it's coming out, or maybe you'll sweat it out. You might sneeze it out. But they're gonna make their way out. How do you digest the atoms if you just breathe in Galileo, right? How do, and that's what I think an artist does. I think something in the art, it's like some people eat things and they're gonna gain weight. Some people ain't gonna gain weight, they're gonna gain muscle. My, I'm just giving you an analogy here. I'm thinking that the artist breathes in and translates it into the art. First, they gotta hear it. I think most of us don't hear that. Like don't, we receive it, but it just doesn't. Right, it's not, yeah, we not have the frequency. I said this to a lot of artists. And even, we all could consider ourselves artists in a certain way, but not, you know. But let's just say there's only one million artists in the world. Yeah. Good. Yeah. Yeah. It's probably 10. What was it? Yeah. If you divide that into the population, what would that, what part of the table would it be? A tiny part. Yeah, it might be that, right? Yeah. And yet it's that that inspires that. Oh yeah. You know what's crazy about that though? There's also a chance, I'm just going numbers and I'm just hypothesizing with you, but there's also a chance that all of this is actually informing that. Yeah. The artist is just watching this, all of this, all the chaos of this. Yeah, so it's hard to know where the beauty comes from. Is it the artist or the chaos from the? So I just, I don't have the answer, but if I was to be forced to say an answer, you're not twisting my arm, but. Yeah, I can if you want me to. No, thank you. I'll say life. Yeah. Life. In the Tower of Wu, you write something about confusion, which I really like. Confusion is a gift from God. Those times when you feel most desperate for a solution, sit, wait, the information will become clear. The confusion is there to guide you. Seek detachment and become the producer of your life. So I gotta ask you advice. If a young person today in high school, college, is looking for some advice, what advice could you give them to be a producer of a life they can be proud of? Read the Tower of Wu. Let's start with the Wu Tang Manual first. Yeah, no, I think we'll do that second. Second? Yeah. I think you could read the Tower of Wu first and then do the manual. Because the manual is, not to put the two books against each other, but the manual is talking about things that is so deeply connected to the music and the people in the Tower of Wu goes beyond that. So I would actually start there, which is not normally how I prescribe. I always tell people start at knowledge, then go to wisdom. But since the Tower- Skip ahead to the wisdom, I like it. Yeah, I think for a young man in high school, go to the Tower of Wu and then go back. It's just like sometimes, my son's generation, they had to watch the second round of Star Wars. Yeah. And then go back, you know what I mean? This generation is watching The Force Awakens and then they go back, yeah. But what, because if you just look at your life as an example, that's one heck of a life. There's very few lives like it. You've created some of the most incredible things artistically in this world. Like if somebody, you talk about that, like 1 million, right? At the corner of the table. If somebody once strives, dreams to become one of those, how do they do it? Well, the beautiful thing is that there are footprints left by those who've done it. You know? And the best way is to study that. To study those who've already done what you wanna do. You know, we live on a civilization. We say this is the greatest country in the world, but our sailors are a pyramid with an eye on it. You know what I mean? Because they did it before. And they may have failed for some reason or something happens, but it was just a strong enough example, right? To take us further. You know, Elon Musk is sitting here trying to do better than what the rocket builders did before. He's not the first one to build the rocket. He's not the first guy to think of the electric car. He's doing it better. He's advancing it to the point that whoever picks up after him, maybe they'll get to that flying car. So, that's the beauty. There's a good verse. I love finding verses to say things, to confirm, because this way people could take it verbally, physically, and then maybe even spiritually. But Christians has said a verse. He said, the fastest way to heaven is by spending time or studying the wise people. Meaning the wise people who is living and those who live before you. Study the masters. Yeah. Let me ask you a big, perhaps ridiculous question, but give it a shot. What is the meaning of this whole thing? What's the meaning of life? Big question. I'm not gonna rush into the answer. I'm gonna give you somebody else answer first, and I'll give you my answer. I remember asking this, and I don't know, I was 15, 16 years old. One of the brothers was studying in mathematics, and the letter I itself means I, Islam. I meaning the individual, right? Being in total accord with Islam. And let me just finish this. Then they took the word Islam, and they defined it as Islam is an Arabic word for peace. Then they said peace is the absence of confusion. Okay? So, then they took, this is something that really hit me when I was, and I never forgot it, and I'm gonna decipher it anyway, but then they took the word Islam, and they broke it down by the letter into an acronym like cash with everything around me. And they broke it down to I, stimulate, light, and matter. And I was like, what? Because what hit me is that if you're not here, then light and matter don't exist to you. So, you're stimulating it, or it ain't here for you. So, anyway, taking all that, so then I said, so what's the meaning of life? And the brother just said, love Islam forever. And the brother just said, love Islam forever. Right? Yeah. I ain't saying the religious point of it. I'm just saying all those other elements I just spoke about in front of it. I stimulate light and matter. I love that. That's powerful. And let me give you my definition of life. I think life is that simply for each and every one of us to add on to. Build. Build. Build. Build. Like you said, the masters build on top. Life gave you life, give life back. I don't think there's a better way to end it than talking about the meaning of life. RZA, I'm a huge fan. It's such a huge honor that you spend your valuable time with me. Thank you so much. Thank you for inviting me. Peace. Thanks for listening to this conversation with RZA. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Plato. Poetry is nearer to vital truth than history. Thank you for listening and hope to see you next time.

https://youtu.be/Iau6W5pjy9Y

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Norman Naimark: Genocide, Stalin, Hitler, Mao, and Absolute Power | Lex Fridman Podcast #248

The following is a conversation with Norman Namark, a historian at Stanford specializing in genocide, war, and empire. This is the Lex Friedman podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Norman Namark. Did Stalin believe that communism is good not just for him, but for the people of the Soviet Union and the people of the world? Oh, absolutely. I mean, Stalin believed that, you know, socialism was the be-all and end-all of, you know, human existence. I mean, he was a true Leninist, and in Lenin's tradition, this was, you know, what he believed. I mean, that set of beliefs didn't exclude other kinds of things he believed or thought or did. But, no, the way he defined socialism, the way he thought about socialism, you know, he absolutely thought it was in the interest of the Soviet Union and of the world. And, in fact, that the world was one day going to go socialist. In other words, I think he believed in that. And eventually, in the International Revolution. So, given the genocide in the 1930s that you described, was Stalin evil, delusional, or incompetent? Evil, delusional, or incompetent. Well, you know, evil is one of those words, you know, which has a lot of kind of religious and moral connotations. And in that sense, yes, I think he was an evil man. I mean, he, you know, eliminated people absolutely unnecessarily. He tortured people, had people tortured. He was completely indifferent to the suffering of others. He couldn't have cared a whit, you know, that millions were suffering. And so, yes, I consider him an evil man. I mean, you know, historians don't like to use the word evil. It's, you know, it's a word for moral philosophers, but I think it certainly fits who he is. I think he was delusional. And there is a wonderful historian at Princeton, a political scientist, actually, named Robert Tucker, who said he suffered from a paranoid delusional system. And I always remember that of Tucker's writing, because what Tucker meant is that he was not just paranoid, meaning, you know, I'm paranoid, I'm worried you're out to get me, right? But that he constructed whole plots of people, whole systems of people who were out to get him. So, in other words, his delusions were that there were all of these groups of people out there who were out to diminish his power and remove him from his position and undermine the Soviet Union, in his view. So, yes, I think he did suffer from delusions. And this had a huge effect, because whole groups then were destroyed by his activities, which he would construct based on these delusions. He was not incompetent. He was an extremely competent man. I mean, I think most of the research that's gone on, especially since the Stalin Archive was opened at the beginning of the century, I think almost every historian who goes in that archive comes away from it with the feeling of a man who is enormously hardworking, intelligent, you know, with an acute sense of politics, a really excellent sense of, you know, political rhetoric, a fantastic editor, you know, in a kind of agitational sense. I mean, he's a real agitator, right? And of a, you know, a really hard worker. I mean, somebody who works from morning till night, a micromanager in some ways. So, his competence, I think, was really extreme. Now, there were times when that fell down, you know, times in the 30s, times in the 20s, times during the war, where he made mistakes. It's not as if he didn't make any mistakes. But I think, you know, you look at his stuff, you know, you look at his archives, you look what he did. I mean, this is an enormously competent man who in many, many different areas of enterprise, because he, you know, he had this notion that he should know everything and did know everything. I remember one archive, it's called, you know, a kind of folder that I looked at where he actually went through the wines that were produced in his native Georgia and wrote down how much they should make of each of these wines, you know, how many, you know, barrels they should produce of these wines, which grapes were better than the other grapes, sort of correcting, in other words, what people were putting down there. So, he was, you know, his competence ranged very wide, or at least he thought his competence ranged very wide. I mean, both things, I think, are the case. If we look at this paranoid delusional system, Stalin was in power for 30 years. He is, many argue, one of the most powerful men in history. Did, in his case, absolute power corrupt him or did it reveal the true nature of the man? And maybe just in your sense, as we kind of build around this genocide of the early 1930s, this paranoid delusional system, did it get built up over time? Was it always there? It's kind of a question of did the genocide, was that always inevitable, essentially, in this man or did power create that? I mean, it's a great question and I don't think you can say that it was always kind of inherent in the man. I mean, the man without his position and without his power, you know, wouldn't have been able to accomplish what he eventually did in the way of murdering people, you know, murdering groups of people, which is what genocide is. So, you know, I don't, it wasn't sort of in him. I mean, there were, and again, you know, the new research has shown that, you know, he had his childhood was, you know, not a particularly nasty one. I mean, people used to say, you know, the father beat him up and it turns out actually it wasn't the father, it was the mother once in a while. But basically, you know, he was not an unusual young Georgian kid or student even. And, you know, it was the growth of the Soviet system and him within the Soviet system. I mean, his own development within the Soviet system, I think that led, you know, to the kind of mass killing that occurred in the 1930s. You know, he essentially achieved complete power by the early 1930s. And then as he rolled with it, as you would say, you know, or people would say, you know, it increasingly became murderous. And there was no, you know, there were no checks and balances, obviously, on that murderous system. And not only that, you know, people supported it in the NKVD and elsewhere. He learned how to manipulate people. I mean, he was a superb, you know, political manipulator of those people around him. And, you know, we've got new transcripts, for example, of, you know, Politburo meetings in the early 1930s. And you read those things and you read, you know, he uses humor and he uses sarcasm, especially. He uses verbal ways to undermine people, you know, to control their behavior and what they do. And he's a really, you know, he's a real, I guess, manipulator is the right word. And he does it with, you know, a kind of skill that on the one hand is admirable, and on the other hand, of course, is terrible because it ends up, you know, creating the system of terror that he creates. I mean, I guess just to linger on it, I just wonder how much of it is a slippery slope. In the early 20s, 1920s, did he think he was going to be murdering even a single person, but thousands and millions? I just wonder, maybe the murder of a single human being, just to get them, you know, because you're paranoid about them potentially threatening your power, does that murder then open a door? And once you open the door, you become a different human being. A deeper question here is the Solzhenitsyn, you know, the line between good and evil runs in every man. Are all of us, once we commit one murder in this situation, does that open a door for all of us? And I guess even the further deeper question is how easy it is for human nature to go on this slippery slope that ends in genocide. There are a lot of questions in those questions. And, you know, the slippery slope question that I would answer, I suppose, by saying, you know, Stalin wasn't the most likely successor of Lenin. There were plenty of others. There were a lot of political contingencies that emerged in the 1920s that made it possible for Stalin to seize power. I don't think of him as a, you know, if you would just know him in 1925, I don't think anybody would say, much less himself, that this was a future mass murderer. I mean, Trotsky mistrusted him and thought he was, you know, a mindless bureaucrat. You know, others were less mistrustful of him. But, you know, he managed to gain power in the way he did through this bureaucratic and political maneuvering that was very successful. You know, the slippery slope, as it were, doesn't really begin until the 1930s, in my view. In other words, once he gains complete power and control of the Politburo, once the programs that he institutes of the Five Year Plan and collectivization go through, once he reverses himself and is able to reverse himself or reverse the Soviet path, you know, to give various nationalities their, you know, their ability to develop their own cultures and sort of internal politics. Once he reverses all that, you know, you have the Ukrainian famine in 32, 33, you have the murder of Kirov, who is one of the leading figures, you know, in the political system. You have the suicide of his wife. You have all these things come together in 32, 33 that then, you know, make it more likely, in other words, that bad things are going to happen. And people start seeing that, too, around him. They start seeing that it's not a slippery slope. It's a dangerous situation which is emerging. And some people really understand that. So, I don't, I really do see a differentiation then between the 20s. I mean, it's true that Stalin during the Civil War, there's a lot of, you know, good research on that, you know, shows that he already had some of these characteristics of being, as it were, murderous and being, you know, being dictatorial and pushing people around and that sort of thing. And that was all there. But I don't really see that as kind of the necessary stage for the next thing that came, which was the 30s, which was really terror of the worst sort, you know, where everybody's afraid for their lives and most people are afraid for their lives and their families' lives. And where torture and that sort of thing becomes a common part, you know, of who, what people had to face. So, it's a different, it's a different world. And, you know, people will argue, they'll argue this kind of Lenin-Stalin continuity debate, you know, that's been going on since I was an undergraduate, right? That argument, you know, was Stalin the natural sort of next step from Lenin or was he something completely different? Many people will argue, you know, because of Marxism-Leninism, because of the ideology, that, you know, it was the natural, it was a kind of natural next step. I don't think so, you know, I would tend to lean the other way. Not absolutely. I mean, I won't make an absolute argument that what Stalin became had nothing to do with Lenin and nothing to do with Marxism-Leninism. It had a lot to do with it. But, you know, he takes it one major step further. And again, that's why I don't like the slippery slope, you know, metaphor, because that means it's kind of slow and easy. It's a leap. And we call, you know, I mean, historians talk about the Stalin revolution, you know, in 28 and 29. You know, that he, in some senses, creates a whole new system, you know, through the five-year plan, collectivization and seizing political power the way he does. Can you talk about the 1930s? Can you describe what happened in Holodomor, the Soviet terror famine in Ukraine in the 32 and 33? Yes. That killed millions of Ukrainians? Right. It's a long story, you know, but let me try to be as succinct as I can be. I mean, the Holodomor, the terror famine of 32, 33, comes out of, in part, an all-union famine that is the result of collectivization. You know, collectivization was a catastrophe. You know, the more or less of the so-called kulaks, the more or less richer farmers. I mean, they weren't really rich. Right. Anybody with a tin roof and a cow was considered a kulak, you know, and other people who had nothing were also considered kulaks if they opposed collectivization. So these kulaks, we're talking millions of them. Right. And Ukraine, it's worth recalling, and I'm sure you know this was a heavily agricultural area. And Ukrainian peasants, you know, were in the countryside and resisted collectivization more than even the Russian peasants resisted collectivization, suffered during this collectivization program. And they, you know, burned sometimes their own houses. They killed their own animals. They were shot, you know, sometimes on the spot. Tens of thousands and others were sent into exile. So there was a conflagration in the countryside. And the result of that conflagration in Ukraine was terrible famine. And again, there was famine all over the Soviet Union, but it was especially bad in Ukraine, in part because Ukrainian peasants resisted. Now in 32, 33, a couple of things happen. I mean, I've argued this in my writing and, you know, I've also worked on this. I continue to work on it, by the way, with a museum in Kiev that's going to be about the Holodomor. They're building the museum now, and it's going to be a very impressive set of exhibits and talk with historians all the time about it. So what happens in 32, 33, a couple of things. First of all, the Stalin develops an even stronger, I say even stronger, because they already had an antipathy for the Ukrainians, and even stronger antipathy for the Ukrainians in general. First of all, they resist collectivization. Second of all, he's not getting all the grain he wants out of them and which he needs. And so he sends in then people to expropriate the grain and take the grain away from the peasants. These teams of people, you know, some policemen, some urban thugs, some party people, some poor peasants, you know, take part to go into the villages and forcibly seize grain and animals from the Ukrainian peasantry. They're seizing it all over. I mean, let's remember, again, this is all over the Soviet Union in 32 especially. Then, you know, in December of 1932, January of 33, February of 33, Stalin is convinced the Ukrainian peasantry needs to be shown who's boss. That they're not turning over their grain, that they're resisting the expropriators, that they're hiding the grain, which they do sometimes, right? That they're basically not loyal to the Soviet Union, that they're acting like traitors, that they're ready. And he says this, you know, to, I think it's Kaganovich, he says it to, you know, they're ready to kind of pull out of the Soviet Union and join Poland. I mean, he thinks Poland is, you know, out to get the, out to get Ukraine. And so he's going to then essentially break the back of these peasantry. And the way he breaks their back is by going through another expropriation program, which is not done in the rest of the Soviet Union. So he's taking away everything they have, everything they have. He has laws introduced where they will actually punish people, including kids, with death if they steal any grain, you know, if they take anything from the, you know, from the fields. So, you know, you can shoot anybody, you know, who is looking for food. And then he introduces measures in Ukraine, which are not introduced into the rest of the Soviet Union. For example, the Ukrainian peasantry are not allowed to leave their villages anymore. They can't go to the city to try to find something. I mean, we've got pictures of, you know, Ukrainian peasants dying on the sidewalks in Kharkiv and in Kiev and in places like that, who've managed to get out of the village and get to the cities. But now they can't leave. They can't leave Ukraine to go to Belarus or Belarus today or to Russia, you know, to get any food. There's no, he won't allow any relief to Ukraine. A number of people offer relief, including the Poles, but also the Vatican offers relief. He won't allow any relief to Ukraine. He won't admit that there's a famine in Ukraine. And instead, what happens is that Ukraine turns into the Ukrainian countryside, turns into what my now past colleague who died several years ago, Robert Conquest, called a vast belsen. And by that, you know, the images of bodies just lying everywhere, you know, people dead and dying, you know, of hunger, which is, by the way, I mean, as you know, I've spent a lot of time studying genocide. I don't think there's anything worse than dying of hunger from what I have read. I mean, you see terrible ways that people die, right? But dying of hunger is just such a horrible, horrible thing. And so, for example, we know there were many cases of cannibalism in the countryside because there wasn't anything to eat. People were eating their own kids. Right. And Stalin knew about this. And again, you know, we started with this question a little bit earlier. He doesn't he there's not a sign of remorse, not a sign of pity. Right. Not a sign of any kind of human emotion that normal people would have. What about the opposite of joy for teaching them a lesson? I don't think there's joy. I'm not sure Stalin really understood emotion. Joy. You know, I think he felt it was necessary to get those SOBs. Right. That they deserved it. He says that several times. This is their own fault. Right. This is their own fault. And as their own fault, you know, they get what they deserve. Basically. How much was the calculation? How much was it reason versus emotion? In terms of you said he was competent. Was there a long term strategy or was this strategy based on emotion and anger? And no, I think actually the right answer is a little of both. I mean, usually the right answer in history is something like that. Right. Now, you can't you can't. It wasn't just I mean, first of all, you know, the Soviets had it in for Ukraine and Ukrainian nationalism, which they really didn't like. And by the way, Russians still don't like it. Right. So they had it in for Ukrainian nationalism. They feared Ukrainian nationalism. As I said, you know, Stalin, Stalin writes, you know, we'll lose Ukraine, you know, if these guys win, you know, so there's a kind of long term determination. As I said, you know, to kind of break the back of Ukrainian national identity and Ukrainian nationalism as any kind of separatist force whatsoever. And so there's that rational calculation. At the same time, I think Stalin is annoyed and peeved and angry on one level with the Ukrainians for resisting collectivization and for being difficult and for, you know, not conforming, you know, to the way he thinks peasants should act in this situation. So you have both things. He's also very angry at the Ukrainian party and eventually purges it for not being able to control Ukraine and not be able to control the situation. You know, Ukraine is in theory the breadbasket, right, of Europe. Well, well, how come the breadbasket isn't turning over to me all this grain so I can sell it abroad and and, you know, build new factories and support the workers in the cities? So there's a kind of annoyance, you know, when things fail, and this is absolutely typical of Stalin, when things fail, he blames it on other people and usually groups of people, right? Not individuals, but groups again. So a little bit of both, I think, is the right answer. This blame, it feels like there's a playbook that dictators follow. I just wonder if it comes naturally or just kind of evolves. Because, you know, blaming others and then telling these narratives and then creating the other and then somehow that leads to hatred and genocide. It feels like there's too many commonalities for it not to be a naturally emergent strategy that works for dictatorships. I mean, it's a good, it's a very good point. And I think it's one, you know, that, you know, has its merits. In other words, I think you're right that there's certain kinds of strategies by dictators that, you know, are common to them. A lot of them do killing, not all of them of that sort that Stalin did. I've written about Mao and Pol Pot, you know, and Hitler. And, you know, there is a sort of, as you say, a kind of playbook for political dictatorship. Also for, you know, a kind of communist totalitarian way of functioning, you know, and that way of functioning was described already by Hannah Arendt early on when she wrote the Origins of Totalitarianism. And she more or less writes the playbook and Stalin does follow it. The real question, it seems to me, is to what extent, you know, and how deep does this go and how often does it go in that direction? I mean, you can argue, for example, I mean, Fidel Castro was not a nice man, right? He was a dictator. He was a terrible dictator, but he did not engage in mass murder. Ho Chi Minh was a dictator, a communist dictator who grew up, you know, in the communist movement, went to Moscow, you know, spent time in Moscow in the 30s and went to find, found the Vietnamese Communist Party. You know, he was a horrible dictator. I'm sure he was responsible for a lot of death and destruction, but he wasn't a mass murderer. And so you get those, you know, I mean, I would even argue others will disagree that Lenin wasn't a mass murderer. You know, he didn't kill the same way, you know, that Stalin killed or people after him. They're communist dictators, too, after all. Khrushchev was a communist dictator, but he stopped this killing. And, you know, he's still responsible for a gulag and people sent off into a gulag and imprisonment and torture and that sort of thing. But it's not at all the same thing. So there are some, you know, like Stalin, like Mao, like Pol Pot, you know, who commit these horrible, horrible atrocities, extensively engaging, in my view, in genocide. And there are some who don't. And, you know, what's the difference? Well, you know, the difference is partly in personality, partly in historical circumstance, you know, partly in, you know, who is it that controls the reins of power? How much do you connect the ideas of communism or Marxism or socialism to Holodomor, to Stalin's rule? So how naturally is he kind of alluded to? Does it lead to genocide? It's also, I mean, in some ways, I've just addressed that question by saying it doesn't always lead to genocide. You know, in the case, again, you know, Cuba is not pretty, but it didn't have, there was no genocide in Cuba. And same thing in North Vietnam. You know, even North Korea, as awful as it is, is terrible dictatorship, right? And people's rights are totally destroyed, right? They have no freedom whatsoever, you know, is not, as far as we know, genocidal. Who knows whether it could be or whether if they took over South Korea, you know, mass murder wouldn't take place and that kind of thing. But my point is, is that the ideology doesn't necessarily dictate genocide. In other words, it's an ideology, I think, that makes genocide sometimes too easily possible. Given, you know, the way it thinks through history as being, you know, you're on the right side of history and some people are on the wrong side of history. And you have to destroy those people who are on the wrong side of history. I mean, there is something in, you know, Marxism, Leninism, which, which, you know, has that kind of language and that kind of thinking. But I don't think it's necessarily that way. There's a wonderful historian at Berkeley named Martin Melia, who has written, you know, wrote a number of books on this subject. And he was very, very, he was very, he was convinced that the, you know, that the ideology itself, you know, played a crucial role in the murderousness of the Soviet regime. I'm not completely convinced, you know, when I say not completely convinced, I think that you could argue it different ways. Equally valid, you know, with equally valid arguments. I mean, there's something about the ideology of communism that allows you to decrease the value of human life. Almost like this philosophy, if it's okay to crack a few eggs to make an omelet. Right. So maybe that, if you can reason like that, then it's easier to take the leap of for the good of the country, for the good of the people, for the good of the world, it's okay to kill a few people. And then that's where I wonder about the slippery slope. Yeah, no, no. Again, you know, I don't think it's a slippery slope. I think it's, I think it's dangerous. In other words, I think it's dangerous. But I don't, I don't consider, you know, I don't like Marxism, Leninism any better than the next guy. And I've lived in plenty of those systems to know how they can beat people down and how they can, you know, destroy human aspirations and human interaction between people. But they're not necessarily murderous systems. They are systems that contain people's autonomy, that force people to into work and labor and lifestyles that they don't want to live. I spent a lot of time, you know, with East Germans and Poles, you know, who lived in, and even in the Soviet Union, you know, in the post-Stalin period, where people lived lives they didn't want to live, you know, and didn't have the freedom to choose. And that was terrifying in and of itself. But these were not murderous systems. And they, you know, ascribe to Marxism, Leninism. So I suppose it's important to draw the line between mass murder and genocide and mass murder versus just mass violation of human rights. Right. Right. And the leap to mass murder, you're saying, may be easier in some ideologies than others, but it's not clear that somehow one ideology definitely leads to mass murder and not. Exactly. I wonder how many factors, what factors, how much of it is a single charismatic leader, how much of it is the conflagration of multiple historical events, how much of it is just dumb, the opposite of luck. Do you have a sense where if you look at a moment in history, predict, looking at the factors, whether something bad is going to happen here. When you look at Iraq, when Saddam Hussein first took power, well, you could, or you can, you know, go even farther back in history, would you be able to predict? So you said, you already kind of answered that with Stalin saying, there's no way you could have predicted that in the early 20s. Is that always the case? You basically can't predict. It's pretty much always the case. In other words, I mean, history is a wonderful, you know, discipline and way of looking at life in the world in retrospect, meaning it happened. It happened and we know it happened. And it's too easy to say sometimes it happened because it had to happen that way. It almost never has to happen that way. And, you know, things, so I very much am of the school that emphasizes, you know, contingency and choice and difference and different paths and not, you know, not necessarily a path that has to be followed. And, you know, sometimes you can warn about things. I mean, you can think, well, something's going to happen. And usually the way it works, let me just give you one example. I'm thinking about an example right now, which was the war in Yugoslavia, you know, which came in the 1990s and eventually ventuated in genocide in Bosnia. And, you know, I remember very clearly, you know, the 1970s and 1980s in Yugoslavia and people would say, you know, there's trouble here and, you know, something could go wrong. But no one in their wildest imagination thought that there would be outright war between them all. Then the outright war happened, genocide happened, and afterwards people would say, I saw it coming. You know, so you get a lot of that, especially with pundits and journalists and that's I saw it coming. I knew it was happening, you know. Well, I mean, what happens in the human mind and it happens in your mind, too, is, you know, you go through a lot of alternatives. I mean, think about January 6th, you know, in this country and all the different alternatives which people had in their mind or before January 6th, you know, after the lost election. You know, things could have gone in lots of different ways and there were all kinds of people choosing different ways it could have gone. But nobody really knew how it was going to turn out. Wasn't it smart people really understood that there'd be this cockamamie uprising on January 6th, you know, that almost, you know, caused us enormous grief. So all of these kinds of things in history, you know, are deeply contingent. They depend on, you know, factors that we cannot predict and, you know, and it's the joy of history that it's open. You know, you think about how people are now. I mean, let me give you one more example and then I'll shut up. But, you know, there's the environmental example. You know, we're all threatened, right? We know it's coming. We know there's trouble, right? We know there's going to be a catastrophe some point. But when? What's the catastrophe? Yeah, what's the nature of the catastrophe? Everyone says catastrophe. Is it going to be wars because resource constraint? Is it going to be hunger? Is it going to be like mass migration of different kinds that leads to some kind of conflict and immigration? Maybe it won't be that big of a deal and a total other catastrophic event will completely challenge the entirety of the human civilization. That's my point. That's my point. That's my point. You know, we really don't know. I mean, there's a lot we do know. I mean, the warming business and all this kind of stuff, you know, it's scientifically there. But how it's going to play out in everybody saying, you know, different things. And then you get somewhere in 50 years or 60 years, which I won't see. And people say, aha, I told you it was going to be X or it was going to be Y or is it going to be Z? So I just don't think in history you can, well, you can't predict. You simply cannot predict what's going to happen. It's kind of when you just look at Hitler in the 30s for me, oftentimes when I kind of read different accounts, it is so often certainly in the press, but in general, me just reading about Hitler, I get the sense like this is a clown. There's no way this person will gain power. Which one? Hitler or Stalin? Hitler. No, no, no. With Stalin, you don't get a sense he's a clown. He's a really good executive. You don't think it'll lead to mass murder, but you think he's going to build a giant bureaucracy at least. With Hitler, it's like a failed artist who keeps screaming about stuff. There's no way he's going to, I mean, you certainly don't think about the atrocities, but there's no way he's going to gain power, especially against communists. I mean, there's so many other competing forces that could have easily beat him. But then you realize like event after event where this clown keeps dancing and all of a sudden he gains more and more power. And just certain moments in time, he makes strategic decisions in terms of cooperating or gaining power over the military, all those kinds of things that eventually give him the power. I mean, this clown is one of the most impactful in the negative sense human beings in history. Right. And even the Jews who are there and are being screamed at and discriminated against, and there's a series of measures taken against them incrementally during the course of the 1930s. Very few who leave. Yeah. I mean, some pick up and go and say, I'm getting the hell out of here. And, you know, some Zionists, you know, try to leave too and go to the United States and stuff, but go to Israel and Palestine at the time, or to Britain or France. But in general, you know, even the Jews who should have been very sensitive to what was going on, you know, didn't really understand the extent of the danger. And it's really hard for people to do that. You know, it's almost impossible. In fact, I think. So most of the time in that exact situation, nothing would have happened or there'd be some drama and so on. It'd be there's some bureaucrat. But every once in a while in human history, there's a kind of turn. And maybe something catalyzes something else and just it accelerates, accelerates, escalates, escalates. And then war breaks out or totally, you know, revolutions break out. Right. Can we go to the big question of genocide? What is genocide? What are the defining characteristics of genocide? Dealing with genocide is a difficult thing when it comes to the definition. There is a definition of the December 1948 U.N. Convention on the Prevention and Punishment of Genocide is considered the sort of major document of definition and the definitional sense of genocide. And it emphasizes, you know, the intentional destruction, you know, of an ethnic, national, racial or religious group. Those are the four groups, again, comma as such. And what that means basically is destroying the group as a group. There's a kind of beauty in human diversity and different groups of people, you know, Estonians, you know, a tribe of Native Americans, South African tribes, you know, the Rohingya in Myanmar. There's a kind of beauty humanity recognizes in the distinctiveness of those groups. You know, this was a notion that emerges really with romanticism after the French Revolution in the beginning of the 19th century with Herder mostly. And this beauty of these groups then, you know, is what is under attack in genocide. And it's with intent. You know, the idea is that it's intentional destruction. So this is a kind of, you know, analogy to first degree, second degree and third degree murder. Right. First degree murder. You know, you're out to kill this person and you plan it and you go out and you do it. Right. That's intent. Right. Manslaughter is not intent. You end up doing the same thing, but it's different. So, you know, the the major person behind the definition is a man named Raphael Lemkin. I don't know if you heard his name or not, but he was a Polish Jewish jurist who came, you know, from Poland, came to the United States during the war and had been a kind of crusader for recognizing genocide. It's a word that he created, by the way, and he coined the term in 1943 and then published it in 1944 for the first time. Geno, meaning people inside, meaning killing. Right. And so Lemkin then had this term and he pushed hard to have it recognized. And it was in the UN Convention. So that's the rough definition. The problem with it is the definition. The problems with the definition are several. You know, one of them is, is it just these four groups, you know, racial, religious, ethnic or national? See, this comes right out of the war. And what's in people's minds in 1948 are Jews, Poles, Russians, Yugoslavs, sometimes who were killed by the Nazis. That's what's in their mind. But there are other groups, too, if you think about it, you know, who are killed social groups or political groups. And that was not allowed in the convention, meaning for a lot of different reasons. The Soviets were primary among them. They didn't want other kinds of groups, let's say Kulaks, for example, to be considered. That's a social group or peasants, which is a social group. So or a political group. I mean, let's take a group, you know, communists killed groups of people, but non-communists also killed groups of people in Indonesia in 1965, 66. They killed, you know, though exactly, but roughly 600000 Indonesian communists. Well, is that genocide or not? You know, my point of view, it is genocide, although it's Indonesians killing Indonesians. And we have the same problem with the Cambodian genocide. I mean, we talk about a Cambodian genocide, but most of the people killed in the Cambodian genocide were other Cambodians. They give it the name. They're ready to recognize this genocide because they also killed some other peoples, meaning the Vietnamese, Akham people who are, you know, Muslim, Muslim, smaller Muslim people in the area and a few others. So the question then becomes, well, does it have to be a different nationality or ethnic group or religious group for it to be genocide? And my answer is no. You know, you need to expand the definition. It's a little bit like with our constitution. We got a constitution, but we don't live in the end of the 18th century, right? We live in the 21st century. And so you have to update the constitution over the centuries. And similarly, the genocide convention needs updating, too. So that's how I work with the definition. So this is this invention. Was it an invention, this beautiful idea, romantic idea that there's groups of people and the group is united by some unique characteristics? That was an invention in human history, that this idea? Not just the individual. Yes, in some senses it was. I mean, it's not, you know, there are things that are always constructed in one fashion or another. And the construction, you know, more or less represents the reality. And what the reality is always much more complicated than the construction or the invention of a term or a concept or a way of thinking about a nation. Right. And this way of thinking of nations, you know, as as, again, you know, groups of religious, linguistic, not political necessarily, but cultural entities is something that was essentially invented. Yes. Yes. I mean, you know, if you look at. There are no Germans in the 17th century. There are no Italians in the 17th century. Right. They're only there after, you know, the invention of the nation, which comes again, mostly as out of the French Revolution and in the Romantic movement, a man named Johan Gottfried von Herder, right, who was the really the first one who sort of went around, collected people's languages and collected their sayings and their dances and their folkways and stuff and said, isn't this cool? You know that there are Estonians and that there are Latvians and that there are these other these interesting different peoples who don't even know necessarily that they're different peoples. Right. That comes a little bit later. Right. Once the concept is invented, then people start to say, hey, we're nations, too. You know, and the Germans decide they're a nation and they unify and the Italians discover they're a nation and they unify instead of being, you know, Florentines and Romans and, you know, Sicilians. But then beyond nations, there are political affiliations, all those kinds of things. It's fascinating that, you know, you start look at the early Homo sapiens and then there's obviously tribes. Right. And then that's very concrete. That is geographic location. And it's a small group of people and you have warring tribes probably connected to just limited resources. But it's fascinating to think that that is then taken to the space of ideas, to where you can create a group at first to appreciate its beauty. You create a group based on language, based on maybe even some political, philosophical ideas, religious ideas, all those kinds of things. And then that naturally then leads to getting angry at groups. Right. And making them the other and then hatred. Right. That comes more towards the end of the 19th century, you know, with the influence of Darwin. I mean, you can't blame Darwin for it, but neo-Darwin, Darwinians, you know, who start to talk about, you know, the competition between nations, the natural competition, the weak ones fall away, the strong ones get ahead. You know, you get this sort of combination also with, you know, modern anti-Semitism and with racial thinking. You know, the racial thinking at the end of the 19th century is very powerful. So now, you know, at the end of the 19th century versus the beginning, you know, the middle of the 19th century, you know, you can be a German and be a Jew and there's no contradiction. Yeah. As long as you speak the language and you, you know, you dress and think and act and share the culture. By the end of the 19th century, people saying no, no, you know, they're not Germans. They're Jews. They're different. They have different blood. They have different. They don't say genes yet, but, you know, that's sort of a sense of people. And that's when, you know, there's this sense of superiority to an inferiority. Yeah. You know, that they're inferior to us. Yeah. You know, and that we're the strong ones and we have to, you know, and Hitler, by the way, just adopts this hook, line and sinker. I mean, there are a whole series of thinkers at the end of the 19th and beginning of 20th century who he cites in Mein Kampf, which is written in the early 1920s, that, you know, basically pervades this racial thinking. So nationalism changes. So nationalism in and of itself is not bad. I mean, it's not bad, you know, to share culture and language and and, you know, folkways and and a sense of common belonging. There's nothing bad about it inherently. But then what happens is it becomes, you know, frequently is used and becomes, especially on fascism, becomes dangerous. And it's especially dangerous when the two conflicting groups share geographic location. That's right. So like with Jews, you know, I come, you know, I'm a Russian Jew. And it's always interesting. I take pride in, you know, I love the tradition of the Soviet Union, of Russia. I love America. I love these countries. They have a beautiful tradition in literature and science and art and all those kinds of things. But it's funny that people, not often, but sometimes, correct me that I'm not Russian. I'm a Jew. And it's a nice reminder. Yes. That that is always there. That desire to create these groups and then when they're living in the same place for that division between groups, that hate between groups can explode. And I just I wonder why is that there? Why does why does the human heart tend so easily towards this kind of hate? Oh, you know, that's a big question in and of itself. You know, the human heart is full of everything, right? It's full of hate. It's full of love. It's full of indifference. It's full of apathy. It's full of energy. So, yeah, I mean, hate is something, you know, that I mean, I think and, you know, along with hate, you know, the ability to really hurt and injure people is something that was within all of us. You know, it's within all of us. And it's just something that's part of who we are and part of our society. So, you know, we're shaped by our society and our society can do with us often what it wishes. You know, that's why it's so much nicer to live in a more or less beneficent society like that of a democracy in the West than to live in the Soviet Union. Right. I mean, because, you know, you have more or less the freedom to do what you wish and not to be forced into situations in which you would have to then do nasty to other people. Some societies, as we talked about, you know, are more have proclivities towards, you know, asking of its people to do things they don't want to do. And forcing them to do so. So, you know, freedom is a wonderful thing to be able to choose not to do evil is a great thing. You know, whereas in some societies, you know, you feel in some ways for not so much for the NKVD bosses, but for the guys on the ground, you know, in the 1930s. Or not so much for the Nazi bosses, but for the guys, you know, in the police battalion that were told, go shoot those Jews, you know. And you do it, not necessarily because they force you to do it, but because your social, you know, your social situation, you know, encourages you to and you don't have the courage not to. Yeah, it was just as I often do re-reading Viktor Frankl's Man's Search for Meaning. And he said something, I just, I often pull out sort of lines. The mere knowledge that a man was either a camp guard or a prisoner tells us almost nothing. Human kindness can be found in all groups, even those which as a whole it would be easy to condemn. So that's speaking to, you feel for those people at the lowest level implementing the orders of those above. Right. And also you worry yourself what will happen if you were given those same orders, you know. I mean, what would you do? What kind of reaction would you have in a similar situation? And, you know, you don't know. I could see myself in World War II fighting for almost any country that I was born in. There's a love of community, there's a love of country that's just, at least to me comes naturally, just love of community. And countries want such community. And I could see fighting for that country, especially when you're sold a story that you're fighting evil. And I'm sure every single country was sold that story effectively. And then when you're in the military and you have a gun in your hand or you're in the police force and you're ordered, go to this place and commit violence, it's hard to know what you would do. It's a mix of fear, it's a mix of maybe you convince yourself, you know, what can one person really do? And over time, it's again that slippery slope. Because you could see all the people who protest, who revolt, they're ineffective. So like, if you actually want to practically help somehow, you're going to convince yourself that you can't, one person can't possibly help. And then you have a family, so you want to make sure, you know, you want to protect your family. You tell all these stories and over time, you naturally convince yourself to dehumanize the other. Yeah, I think about this a lot. Mostly because I worry that I wouldn't be a good German. Yeah, no, no, that's right. That's right. And one of the, you know, one of my tasks as a teacher, right, of our students, and I have, you know, classes on genocide, I have one now, and another one, by the way, on Stalin. But the one on genocide, you know, one of my tasks is to try to get the students to understand this is not about weird people who live far away in time and in place, but it's about them, you know. And that, you know, that's a hard lesson, but it's an important one, you know, that this is in all of us. And there's nothing, you know, and you just try to gurgle yourself up, you know, to try to figure out ways that maybe you won't be complicit and that you learn how to stand by your principles. But it's very hard. It's extremely difficult. And you can't, the other interesting thing about it is it's not predictable. Now, as they've done a lot of studies of Poles, for example, who during the war saved Jews, you know. Well, who are the Poles who saved Jews versus those who turned them in? It's completely unpredictable. You know, sometimes it's the worst anti-Semites who protect them because they don't believe they should be killed. Right. And sometimes, you know, it's not predictable. It's not as if the humanists among us, you know, are the ones who, you know, can consistently show up, you know, and experience danger, in other words, and are ready to take on danger to defend, you know, your fellow human beings. Not necessarily. I mean, sometimes simple people do it and sometimes they do it for really simple reasons. And sometimes people you would expect to do it don't. And you've got that mix and it's just not predictable. One thing I've learned in this age of social media is it feels like the people with integrity and the ones who would do the right thing are the quiet ones. In terms of humanists, in terms of activists, there's so many points to be gained of declaring that you would do the right thing. It's the simple, quiet folks. Because I've seen quite, on a small, obviously much smaller scale, just shows of integrity and character when there were sacrifices to be made and it was done quietly. Now, this sort of the small heroes, those are, you're right, it's surprising, but they're often quiet. That's why I'm distrustful of people who kind of proclaim that they would do the right thing. Right. Right. Right. And there are different kinds of integrity too. I mean, I edited a memoir of a Polish, you know, underground fighter, a member of the underground who was in Majdanek, in the concentration camp in Majdanek. You know, and it was just an interesting mix of different kinds of integrity. You know, on the one hand, you know, it really bothered him deeply when Jews were killed or sent to camp or that sort of thing. On the other hand, he was something of an anti-Semite, you know, he would, you know, sometimes if Jews were his friends, he would help them. And if they weren't, sometimes he was really mean to them. You know, and you could, in their various levels, you know, a concentration camp is, you know, a terrible social experiment in some ways, right. But you learn a lot from how people behave. And what you see is that, you know, people behave sometimes extraordinarily well in some situations and extraordinarily poorly in others. And it's mixed and you can't predict it. And it's hard to find consistency. I mean, that's the other thing. It's, you know, I think we claim too much consistency for the people we study and the people we think about in the past. You know, they're not consistent any more than we are consistent, right? Well, let me ask you about human nature here on both sides. So, first, what have you learned about human nature from studying genocide? Why do humans commit genocide? What lessons, first of all, why is a difficult question, but what insights do you have into humans that genocide is something that happens in the world? That's a really big and difficult question, right? And it has to be parsed, I think, into different kinds of questions. You know, why does genocide happen? You know, which the answer there is frequently political, meaning, you know, why Hitler ended up killing the Jews. Well, it had a lot to do with the political history of Germany and wartime history of Germany, right? In the 30s. And, you know, it's traceable to then. Like you mentioned it yourself. You can't imagine Hitler in the mid 20s turning into anything of the kind of dictator he ended up being and the kind of murderer, mass murderer he ended up being. So, and the same thing goes, by the way, for Stalin and Soviet Union and Pol Pot. I mean, these are all essentially political movements where the polity, state is seized, you know, by ideological or, you know, party, single party movement, and then is moved in directions where mass killing takes place. Now, the other question, separate that question out. The other question is why do ordinary people participate? Because the fact of the matter is just ordering genocide is not enough. Just saying, you know, go get them is not enough. There have to be people who cooperate and who will do their jobs, you know, both at the kind of mezzo level, the middle level of a bureaucracy, but also at the everyday level. Now, people who have to pull the triggers and that kind of thing and, you know, force people into the gas chamber and grab people, you know, in Kiev in September 1941 at Babin Yar and push them, you know, towards the ravine where the machine gunners are going to shoot them down. You know, and those are all such different questions. The question of, you know, the especially the lower level people who actually do the killing is a question which I think we've been talking about, which is that within all of us, you know, is the capability of being murderers and mass murderers. I mean, to participate in mass murder. I won't call them laws of social psychology, but the character of social psychology. You know, we will do it in most cases. I mean, one of the shocking things that I learned just a few years ago studying the Holocaust is that you could pull out. In other words, if they order a police battalion to go shoot Jews, you didn't have to do it. You could pull out. They weren't going to. They never killed anybody. They never executed anybody. They never even punished people for saying, no, I know I'm not going to do that. So people are doing it voluntarily. They may not want to do it. You know, they give them booze to try to, you know, numb the pain of murder because they know there's there is pain. I mean, people experience pain when they murder people, but they don't pull out. And so it's the character of who we are in society, in groups. And we're very, very influenced. I mean, we're highly influenced by the groups in which we operate. And, you know, who we talk to and and who our friends are within that group and who is the head of the group. And I mean, you see this even I mean, you see it in any group, you know, whether it's in the academy. Right. That Stanford or whether it's, you know, in a labor union or whether it's in a church group in Tennessee or wherever, you know, people pay attention to each other. And they and they are unwilling frequently to say, no, this is wrong, even though all of you think it's right. It's wrong. I mean, they just don't do that usually, especially in societies that are authoritarian or totalitarian. Right. Because it's it's harder because there's a backup to it. Right. There's the NKVD there or there's the Gestapo there. There are other people there. So you just you know, they may not be forcing you to do it, but but your social being plus this danger in the in the distance, you know, you do it. But then if you go up the hierarchy at the very top, there's a dictator. Presumably, you know, you go to like middle management, bureaucracy. The higher you get up there, the more power you have to change the direction of the Titanic. Right. Right. Right. But nobody seems to do it. Right. Or what happens and it does happen. It happens in the German army. I mean, it happens in the case of the Armenian genocide, where we know their governors who said, no, I'm not I'm not going to kill Armenians. What kind of business is this? They're just removed. They're removed. And you find a replacement very easily. So, you know, you do see people who stand up. And again, it's not really predictable who will be. I would maintain. I mean, I haven't done the study of the of the Armenian governors who said no. I mean, the Turkish governors who said no to the Armenian genocide. But, you know, there are people who do step aside every once in a while in the middle level. And again, there are German generals who say, wait a minute, what is this business in Poland when they start to to kill Jews or in Belarus? And, you know, they're just pushed aside. You know, if they don't do their job, they're pushed aside or they end up doing it. And they usually do end up doing it. What about on the victim side? I mentioned man's search for meaning. What can we learn about human nature, the human mind from the victims of genocide? So Viktor Frankl talked about the ability to discover meaning and beauty, even in suffering. Is there something to be said about, you know, in your studying of genocide that you've learned about human nature? Well, again, I don't I have to say I come out of the study of genocide with a very pessimistic view of human nature, a very pessimistic view. Even on the victim side, even on the victim side. I mean, the victims will eat their children. Right. Ukrainian case, they have no choice. You know, the victims will rob each other. The victims will form hierarchies within victimhood. So you see, let me give you an example. Again, I told you I was working on my Danek and there's in my Danek at a certain point in 42, a group of Slovak Jews were arrested and sent to my Danek. Those Slovak Jews were a group. Somehow they I mean, they stuck together. They were very competent. They were, you know, many of them were businessmen. They knew each other. And for a variety of different reasons within the camp. And again, this shows you the diversity of the camps. And also, you know, these images of black and white in the camps are not very useful. They ruled the camp. I mean, they basically had all the important jobs in the camp, including jobs like beating other Jews and persecuting other Jews and persecuting other peoples. Which they did. And this Polish guy who I mentioned to you, who wrote this memoir, hated them because of what they were doing to the Poles. Right. And he, you know, he's incensed because aren't these supposed to be the intervention? He says. And look what they're doing. They're treating us, you know, like dirt. And they do. They treat them like dirt. So, you know, in this kind of work on Majdanek, there's certainly parts of it that, you know, were inspiring. You know, people helping each other, people trying to feed each other, people giving warmth to each other. You know, there's some very heroic Polish women who end up having a radio show called Radio Majdanek, which they put on every night in the women's camp, which is, you know, to raise people's spirits. And they, you know, sing songs and do all this kind of stuff, you know, to to try to keep themselves from, you know, the horrors that they're experiencing around them. And so you do see that and you do see, you know, human beings acting in support of each other. But, you know, I mean, Primo Levi is one of my favorite writers about about the Holocaust and about the camps. And, you know, I don't I don't think Primo Levi saw anything, you know, I mean, he had pals, you know, who he helped and who helped him. I mean, but he describes this this kind of, you know, terrible inhuman environment which no one can escape, really. No one can escape. He ends up committing suicide, too, I think, because of his his sense of we don't know exactly why, but probably because of his sense of what happened in the camp. I mean, later he goes back to Italy, becomes a writer and that sort of thing. So I don't I don't especially in the concentration camps. It's really hard to find places like Wickel-Frankl where you can say, you know, I am moved in a positive way, you know, by what happened. There were cases, there's no question. People hung together. They tried to help each other. But but, you know, they were totally, totally caught in this in this web of genocide. See, so there are stories, but the thing is, I have this sense, maybe it's a hope that within most, if not every human heart, there's a kind of like flame of compassion and kindness and love that waits, that longs to connect with others, that ultimately, en masse, overpowers everything else. If you just look at the story of human history, the resistance to violence and mass murder and genocide feels like a force that's there. And it feels like a force that's more powerful than whatever the dark momentum that leads to genocide is. It feels like that's more powerful. It's just quiet. It's hard to tell the story of that little flame that burns within all of our hearts, that longing to connect to other human beings. And there's something also about human nature and us as storytellers that we're not very good at telling the stories of that little flame. We're much better at telling the stories of atrocities. No, you know, I think maybe I fundamentally disagree with you. I think maybe I fundamentally, I don't disagree that there is that flame. I just think it's just too easily doused. And I think it's too easily goes out in a lot of people. And I mean, like I say, I come away from this work a pessimist. You know, there is this work by a Harvard psychologist, now I'm forgetting. Steven Pinker. Yes, yes. Steven Pinker that shows over time, you know, and you know, initially I was quite skeptical of the work, but in the end I thought he was quite convincing that over time the incidence of homicide, you know, goes down. The incidence of rape goes down. The incidence of genocide, except for the big blip, you know, in the middle of the 20th century goes down. Not markedly, but it goes down generally. That, you know, more that norms, international norms are changing how we think about this and stuff like that. I thought he was pretty convincing about that. But think about, think about, you know, we're modern people. I mean, we've advanced so fast in so many different areas. I mean, we should have eliminated this a long time ago. A long time ago. You know, how is it that, you know, we're still facing this business of genocide in Myanmar and Xinjiang and in, you know, Tigray and Ethiopia, you know, the potentials of genocide there and all over the world. You know, we still have this thing that we cannot handle, that we can't deal with. And, you know, again, you know, electric cars and planes that fly from here to, you know, Beijing. Think about the differences between 250 years ago or 300 years ago and today, but the differences in genocide are not all that great. I mean, the incidence has gone down. I think Pinker has demonstrated, I mean, there are problems with his methodology, but on the whole, I'm with him on that book. I thought in the end it was quite well done. So, you know, I do not, I have to say I'm not an optimist about what this human flame can do. And, you know, I once, someone once said to me, when I posed a similar kind of question to a seminar, a friend of mine at Berkeley once said, remember original sin, Norman. Well, I don't, you know, that's very Catholic and I don't really think in terms of original sin. But in some ways, you know, her point is we carry this with us. You know, we carry with us a really potentially nasty mean streak that can do harm to other people. But we carry the capacity to love too. Yes, we do. Yes, we do. That's part of the deal. You have a bias in that you have studied some of the darker aspects of human nature and human history. So it is difficult from the trenches, from the muck, to see a possible sort of way out through love. But it's not obvious that that's not the case. You mentioned electric cars and rockets and airplanes. To me, the more powerful thing is Wikipedia, the internet. Only 50% of the world currently has access to the internet. But that's growing in information and knowledge and wisdom, especially among women in the world. As that grows, I think it becomes a lot more difficult if love wins. It becomes a lot more difficult for somebody like Hitler to take power, for genocide to occur. Because people think, and the masses, I think, the people have power when they're able to think. When they can see the full kind of... First of all, when they can study your work, they can know about the fact that genocide happens, how it occurs, how the promises of great charismatic leaders lead to great destructive mass genocide. And just even studying the fact that the Holocaust happened for a large number of people is a powerful preventer of future genocide. One of the lessons of history is just knowing that this can happen. Learning how it happens, that normal human beings, leaders that give big promises, can also become evil and destructive. Knowing that that can happen is a powerful preventer of that. And then you kind of wake up from this haze of believing everything you hear. And you learn to just, in your small local way, to put more love out there in the world. I believe it's not too good to push back. It's not so obvious to me that in the end, I think in the end, love wins. That's my intuition. If I had to bet money on it. I have a sense that this genocide thing is more and more going to be an artifact of the past. Well, I certainly hope you're right. I mean, I certainly hope you're right. And, you know, it could be you are. We don't know. But the evidence is different. The evidence is different. And, you know, the capacity of human beings to do evil to other human beings is repeatedly demonstrated. You know, whether it's in massacres in Mexico or, you know, ISIS and the ZD Kurds or, you know, you can just go on and on. Syria. I mean, look what I mean. Syria used to be a country, you know, and now it's a, you know, it's been a mass grave. And people then have left in the millions, you know, for other places. And, you know, I'm not saying, you know, I'm not saying I mean, the Turks have done nice things for the Syrians and the Germans welcomed in a million or so and actually reasonably absorbed them. I mean, it's all it's not I'm not saying bad things only happen in the world. They're good and bad things that happen. You're absolutely right. And but I don't think we're on the path to eliminating these bad things, really bad things from happening. I just don't think we are. And I don't think there's any I don't think the facts demonstrate it. I mean, I hope I hope you're right. But but I think otherwise, otherwise, it's just an article of faith. Well, you know, which is perfectly fine. It's better to have that article of faith and to have a article of faith which says, you know, things should get bad or things like that. Well, it's not it's not just fine. It's the only way if you want to build a better future. So optimism is a prerequisite for engineering a better future. So like, okay, so a historian has to see clearly into the past. An engineer has to has to imagine a future that's different from the past. That's better than the past, because without that, they're not going to be able to build a better future. So there's a kind of saying like you have to consider the facts. Well, at every single moment in history, if you allow yourself to be too grounded by the facts of the past, you're not going to create the future. So that's kind of the tension that we're living with. To have a chance, we have to imagine that the better future is possible. But one of the ways to do that is to study history. Which engineers don't do enough of. They do not. Which is a real problem. You know, it's a real problem. Well, basically a lot of disciplines in science and so on don't do enough of. Right. Can you tell the story of China from 1958 to 1962? What was called the Great Leap Forward, orchestrated by Chairman Mao Zedong, that led to the deaths of tens of millions of people, making it arguably the largest famine in human history. Yes. I mean, it was a terrible set of events that led to the death. You know, people will dispute the numbers. Fifteen million, 17 million, 14 million, 20 million people died in the Great Leap. Many people say 30, 40, 50 million. Some people will go that high, too. That's right. That's right. Essentially, Mao and the Communist Party leadership, but it was, you know, it was mostly Mao's doing, decided he wanted, you know, to move the country into communism. And part of the idea of that was rivalry with the Soviet Union. You know, Mao was a good Stalinist or at least felt like Stalin was the right kind of communist leader to have. And he didn't like Khrushchev at all. And he didn't like what he thought were Khrushchev's reforms and also Khrushchev's pretensions to moving the Soviet Union into communism. So Khrushchev, you know, started talking about giving more power to the party, less power to the state. And if you have more power to the party versus the state, then you're moving into communism quicker. So what Mao decided to do was to engage in this vast program of, you know, building what were called people's communes. And these communes, you know, were enormous conglomerations of essentially collective farms, you know. And what would happen on those communes is there would be, you know, there would be places for people to eat and there would be places for the kids to be raised in, you know, essentially kind of separate homes and they would be schooled. Everybody would turn over their metal, which was one of the actually turned out to be terribly negative phenomenon, their metal pots and pans to be melted to then make steel. Every of these big communes would all have little steel plants and they would build steel and the whole countryside would be transformed. Well, like many of these sort of true megalomaniac project, you know, like some of Stalin's projects, too. And this particular project, then, you know, the people had no choice. They were forced, you know, to do this. It was incredibly dysfunctional for Chinese agriculture and ended up, you know, creating, as you mentioned, a terrible famine that everybody understood was a famine as a result of this. I mean, there were some there were also some problems of nature at the same time and some flooding and bad weather and that sort of thing. But it was really a man-made famine. And Mao said at one point, you know, who cares, you know, if millions die? It just doesn't matter. We've got millions more left. I mean, he would periodically say things like this that showed that like Stalin, he had, you know, total indifference to the fact that people were dying in large numbers. It led again to cannibalism and to terrible wastage all over the country and millions of people died. And there was just no stopping it. You know, there were people in the party who began to kind of edge towards telling Mao this wasn't a great idea, you know, and that he should back off, but he wouldn't back off. And the result was, you know, catastrophe in the countryside and all these people dying. And then they, you know, compounding the problem was the political elite, which then, you know, if peasants would object or if certain people would say no, they beat the hell out of them, you know, they would beat people, you know, who didn't do what they wanted them to do. So it was it was really, really a horrific set of events on the Chinese, the Chinese countryside. I mean, you know, and people people wrote about it. I mean, we we learned about it. There were people who were keeping track of what was going on and eventually wrote books about it. So, you know, so we have I mean, we have pretty good documentation, not so much on the numbers. Numbers is numbers are always a difficult problem. You know, I'm facing this problem, by the way. This is a little bit separate with the Holodomor where, you know, Ukrainians are now claiming 11.5 million people died in Holodomor. And, you know, most people assume it's somewhere in the neighborhood of four million, 4.5 million, maybe. So you have wildly different numbers that come out. And we have different kinds of numbers, as you mentioned, too, with the Great Leap Forward. So it was a huge catastrophe for China and now only backed off when he had to. And then, you know, revived a little bit with the, you know, Red Guards movement later on when, when, you know, he was he was upset that the bureaucracy was resisting him a little bit when it came to the Great Leap. But he had to back off. It was such a terrible catastrophe. So one of the things about numbers is that you usually talk about deaths, but with the famine, with starvation, the thing I often think about that's impossible to put into numbers is the number of people and the degree to which they were suffering. You know, the number of days spent in suffering. Oh, yeah. And so, I mean, death is, death is just one of the consequences of suffering. To me, it feels like one, two, three years or months and then years of not having anything to eat is worse. And it's sort of those, those aren't put into numbers often. That's right. And the effect on people long term, you know, in terms of their mental health, in terms of their physical health, their ability to work, all those kinds of things, you know, I mean, Ukrainians are working on, there are people working on this subject now, you know, the long term effect of the hunger famine on them. And I'm sure there's a similar kind of long term effect on Chinese peasantry of what happened. You know, I mean, you're destroying. Multi-generational. Yes, multi-generational. That's right. Wow. And, you know, it's a really, you're absolutely right. This is a terrible, terrible way to die. And it lasts a long time. And sometimes you don't die. You survive. But, you know, in the kind of shape where you can't do anything. I mean, you can't function. Your brain's been injured. You know, I know it's a really, these famines are really horrible. You're right. So when you talk about genocide, it's often talking about murder. Yeah. Where do you place North Korea in this discussion? We kind of mentioned it. So in the, what is it, the arduous March of the 1990s, where it was mass starvation, many people describe mass starvation going on now in North Korea. When you think about genocide, when you think about atrocities going on in the world today, where do you place North Korea? So take a step back when the, there were all these courts that were set up for Bosnia and for Rwanda and for other genocides in the 1990s. And then the decision was made by the international community, UN basically, to set up the International Criminal Court, which would then try genocide in the more modern period, the more contemporary period. And the ICC lists three crimes, basically, you know, the genocide, crimes against humanity, and war crimes. And subsumed to crimes against humanity are a lot of the kinds of things you're talking about with North Korea. I mean, it's torture, it's artificial, sometimes artificial famine or famine, you know, that is not necessary, right? Not necessary to have it. And other, there are other kinds of, you know, mass rape and stuff like that. There are other kinds of things that fit into the crimes against humanity. And that's sort of where I think about North Korea as committing crimes against humanity, not genocide. And again, remember, genocide is meant to be, I mean, some people, there's a disagreement among scholars and jurists about this. Some people think of genocide as the crime of crimes, the worst of the three that I just mentioned. But some think of them as co-equal. And the ICC, the International Criminal Court, is dealing with them more or less as co-equal, even though we tend to think of genocide as the worst. So, I mean, what I'm trying to say is that, you know, I don't want to, I don't want to split hairs. I think it's sort of morally and ethically unseemly, you know, the split hairs about what is genocide and what is a crime against humanity. You know, this is for lawyers, not for historians. Like terminology wise. Yeah, yeah. You know, that you don't want to get into that because it, I mean, it happened with Darfur a little bit where the Bush administration had declared that Darfur was a genocide. And the UN said, no, no, it's, you know, it wasn't genocide. It was a crime against humanity. And that, you know, that confused things versus clarified them. I mean, we damn well knew what was happening. People were being killed and being attacked. And and so, you know, on the one hand, I think the whole concept and the way of thinking about history using genocide as an important part of human history is is crucial. On the other hand, I don't like to get involved in the hair splitting. What's genocide and what's not. So that, you know, North Korea, I tend to think of, like I said, as committing crimes against humanity and, you know, forcibly incarcerating people, torturing them, that kind of thing, you know, routinely incarcerating, depriving them of certain kinds of human rights can be considered a crime against humanity. But I don't think of it in the same way I think about genocide, which is an attack on a group of people. Let me just leave it at that. What in this, if we think about if it's OK, can we loosely use the term genocide here? Just let's not play games with terminology, just bad crimes against humanity. Of particular interest are the ones that are going on today still, because it raises the question to us. What do people outside of this, what role do they have to play? So what role does the United States or what role do I as a human being who has food today, who has shelter, who has a comfortable life, what role do I have when I think about North Korea, when I think about Syria, when I think about maybe the Uyghur population in China? Well, I mean, the role is the same role I have, which is to teach and to learn and to get the message out that this is happening, because the more people who understand it, the more likely it is that the United States government will try to do something about it. You know, in within the context of who we are and where we live. Right. And so, you know, I write books, you do shows, you know, or maybe you write books too, I don't know. I do not write books, but I tweet. You tweet. Okay, that's good too. Ineloquently. But that's not the, I guess that's not the point. Yes, so certainly this is true in terms of a voice, in terms of words, in terms of books, you are, I would say, a rare example of somebody that has powerful reach with words. But I was also referring to actions. In the United States government, what are the options here? So war has costs and war seems to be, as you have described, sort of potentially increase the atrocity, not decrease it. If there's anything that challenges my hope for the future, is the fact that sometimes we're not powerless to help, but very close to powerless to help. Because trying to help can often lead to, in the near term, more negative effects than positive effects. That's exactly right. I mean, you know, the unintended consequences of what we do can frequently be as bad, if not worse, than, you know, trying to relieve the difficulties that people are having. So I think, you know, you're caught a little bit, but it's also true, I think, that we can be more forceful. I think we can be more forceful without necessarily war. You know, there is this idea of the so-called responsibility to protect. And this was an idea that came up, you know, after Kosovo, which was what, 1999. And when, you know, the Serbs looked like they were going to engage in a genocidal program in Kosovo. And, you know, it was basically a program of ethnic cleansing, but it could have gone bad and gotten worse, not just driving people out, but beginning to kill them. And the United States and Britain and others intervened, you know, and Russians were there too, as you probably recall. And I think correctly, people have analyzed this as a case in which genocide was prevented or stopped. In other words, the Serbs were stopped in their tracks. I mean, some bad things did happen. We bombed Belgrade and the Chinese embassy and things like that. But, you know, it was it was stopped. And following upon that, then there was a kind of international consensus that we needed to do something. I mean, because of Rwanda, Bosnia and the positive example of Kosovo, right? That genocide did not happen in Kosovo. And I think that argument, you know, has been substantiated anyway. And this notion of the or this doctrine or whatever of the responsibility to protect them was adopted by the UN in 2005 unanimously. And what it says is there's a hierarchy of measures that should be. Well, let me let me take a step back. It starts with the principle that sovereignty of a country is not you don't earn it just by being there and being your own country. You have to earn it by protecting your people. So every this was all agreed with all the nations of the UN agreed, you know, Chinese and then Russians, too. That, you know, sovereignty is there because you protect your people against various depredations, right? Including genocide, crimes against humanity, forced imprisonment, torture and that sort of thing. If you violate. That justification for your sovereignty, that you're protecting your people, that you're not protecting them, the international community has the obligation to do something about it. All right. Now, then they have a kind of hierarchy of things you can do, you know, starting with. I mean, I'm not quoting exactly, but, you know, starting with kind of push and pull, you know, trying to convince people don't do that. You know, to Myanmar, don't don't do that to the Rohingya people. Right. Then it goes down the list, you know, and you get to a list of sanctions or threatening sanctions and then sanctions, you know, like we have against Russia. But you go down the list. Right. You go down the list and eventually. You get to military intervention at the bottom, which they say is the last thing you know, and you you really don't want to do that. And not only do you not want to do it, but it just as you said, this is you pointed out, it can have unintended consequences. Right. And we'll do everything we can short, you know, of military intervention. But, you know, if necessary, that can be undertaken as well. And so the responsibility to protect, I think, is is is, you know, it was not implementable. One of the things it says in this last category, right, the military intervention is that the intervention cannot create more damage than it relieves. Right. And so for for Syria, we came to the conclusion, you know, that I mean, the international community in some ways said this in so many words, even though the Russians were there, obviously, we ended up being there and that sort of thing. But the international community basically said, you know, there's no way you can intervene in Syria. You know, it's just no no way without causing more damage, you know, than you would relieve. So, you know, in some senses, that's what the international community is saying about, you know, Xinjiang and the Uyghurs, too. You know, I mean, you can't even imagine what hell would break loose if there was some kind of military trouble, you know, to threaten the Chinese with. But you can go down that list with, you know, the military leadership of Myanmar. And you can go down that list with the Chinese Communist Party and you can go down the list, you know, with others who are threatening, you know, with Ethiopia and what it's doing in Tigray. And, you know, you can go down that list and start pushing. I think what happened there was more of a willingness in the 90s and in, you know, right at the turn of the century, you know, to do these kinds of things. And then, you know, when Trump got elected and, you know, he basically said, you know, America first and out of the world, we're not going to do any of this kind of stuff. And now Biden has the problem of trying to rebuild consensus on how you how you deal with these kinds of things. I think it's not impossible. I mean, here I tend to be maybe more of an optimist than you. You know, I think it's not impossible that the international community can, you know, muster some internal fortitude and push harder, short of war, you know, to get the Chinese and to get the again Myanmar and to get others to kind of back off of violations of people's rights the way they are. Routinely doing it. So that's in the space of geopolitics. That's the space of politicians and you want it. So, yes. The interesting thing about China, and this is a difficult topic, but there's so many financial interests that not many voices with power and with money speak up, speak out against China. Because it's a very interesting effect, because it costs a lot for an individual to speak up because you're going to suffer. I mean, China just cuts off the market. Like if you have a product, if you have a company and you say something negative, China just says, OK, well, then they knock you out of the market. And so any person speaks up, they get shut down immediately. Financially, it's a huge cost, sometimes millions or billions of dollars. And so what happens is everybody of consequences, financially, everybody with a giant platform is extremely hesitant to speak out. It's a very, it's a different kind of hesitation that's financial in nature. I don't know if that was always the case. It seems like in history people were quiet because of fear, because of threat of violence. Here, there's almost like a self-interested preservation of financial, of wealth. And I don't know what to do that. I mean, I don't know if you can say something there, like genocide going on because people are financially self-interested. Yeah, no, I think, I mean, I think the analysis is correct and it's not only, but it's not only corporations, but it's, you know, it's the American government that represents the American people that also feels compelled not to challenge the Chinese on human rights issues. But the interesting thing is it's not just, you know, I know a lot of people from China and first of all, amazing human beings and a lot of brilliant people in China. They also don't want to speak out and not because they're sort of quote unquote like silenced, but more because they're going to also lose financially. They have a lot of businesses in China. They, you know, they're running, in fact, the Chinese government and the country has a very interesting structure because it has a lot of elements that enable capitalism within a certain framework. So you have a lot of very successful companies and they operate successfully. And then the leaders of those companies, many of whom have either been on this podcast or want to be on this podcast, they really don't want to say anything negative about the government. And the nature of the fear I sense is not the kind of fear you would have in Nazi Germany. It's a very kind of, it's a mellow, like, why would I speak out when it has a negative effect on my company, on my family, in terms of finance, strictly financially. And that's difficult. That's a different problem to solve. That feels solvable because it feels like it's a money problem. If you can control the flow of money where the government has less power to control the flow of money, it feels like that's solvable. And that's where capitalism is good. That's where a free market is good. So it's like, that's where a lot of people in the cryptocurrency space, I don't know if you follow them, they kind of say, okay, take the monetary system, the power to control money away from governments. Make it a distributed, like, allow technology to help you with that. That's a hopeful message there. In fact, a lot of people argue that kind of Bitcoin, these cryptocurrencies can help deal with some of these authoritarian regimes that lead to violations of basic human rights. If you can control, if you can give the power to control the money to the people, you can take that away from governments. That's another source of hope, where technology might be able to do something good. That's something different about the 21st century than the 20th. There's technology in the hands of billions of people. I mean, I have to say, I think you're naive when it comes to technology. I mean, I don't, I'm not someone who understands technology, so it's wrong of me to argue with you because I don't really spend much time with it. I don't really like it very much, and I'm not, you know, I'm neither a fan nor a connoisseur, so I just don't really know. But what human history has shown, basically, and that's a big statement, you know, I don't want to pretend I can tell you what human history has shown. But, you know, technology, atom bomb, I mean, that's the perfect example of technology. You know, what happens when you discover new things? It's a perfect example of what's going on with Facebook now. It's an absolutely perfect example. You know, and, you know, I once went to a lecture by Eric Schmidt about the future, you know, and about all the things that were going to happen and all these wonderful things. Like, you know, you wouldn't have to translate yourself anything. You wouldn't have to read a book, you know, you wouldn't have to drive a car. You don't have to do this, you don't have to do that. What kind of life is that? So, you know, my view of technology is it's subsumed, you know, to the political, social, and moral needs of our day and should be subsumed to that day. It's not going to solve anything by itself. It's going to be you and me that solve things, if they're solved. There are political systems that solve things. Technology is neutral on one level. It is simply a human, I mean, they're talking now about how artificial intelligence, you know, is going to do this and is going to do that. I'm not so sure there's anything necessarily positive or negative about it, except it does obviously make work easier and things like that. I mean, I, you know, I like email and I like, you know, word processing and that sort of, all that stuff is great. But actually solving human relations in and of itself or international relations or conflict among human beings. I mean, I see technology as, you know, causing as many problems as it solves and maybe even more. You know, the kind of... Maybe. Maybe, yeah. The question is, so like you said, technology is neutral. I agree with this. Technology is a toolkit, is a tool set that enables humans to have wider reach and more power. The printing press. The rare reason I can read your books is, I would argue, so first of all, the printing press and then the internet. Wikipedia, I think, has immeasurable effect on humanity. Technology is a double-edged sword. It allows bad people to do bad things and good people to do good things. It ultimately boils down to... Right, the people. The people and whether you believe the capacity for good outweighs the capacity of bad. And so you said that I'm naive, it is true. I'm naively optimistic. I would say you're naively cynical about technology. But here we have one overdressed naive optimist and one brilliant, but nevertheless technologically naive cynic. And we don't know. We don't know whether the capacity for good or the capacity for evil wins out in the end. And like we've been talking about, the trajectory of human history seems to pivot on a lot of random seeming moments. So we don't know. But as a builder of technology, I remain optimistic. And I should say, when you are optimistic, it is often easy to sound naive. And I'm not sure what to make of that small effect. Not to linger on specific words, but I've noticed that people who kind of are cynical about the world somehow sound more intelligent. No, no. The issue is how can you be realistic about the world? It's not optimistic or pessimistic. It's not cynical. The question is how can you be a realist? Yes, that's a good question. Realism depends on a combination of knowledge and wisdom and good instincts and that sort of thing. And that's what we strive for, is a kind of realism. We both strive for that kind of realism. But here's an example I would give you. What about, again, we've got this environmental issue, right? And technology has created it. It's created it. I mean, the growth of technology. I mean, we all like to be heated well in our homes and we want to have cars that run quickly and fast on gas. I mean, we're all consumers and we all profit from this. I don't, not everybody profits from it, but we want to be comfortable. And technology has provided us with a comfortable life. And it's also provided us with this incredible danger, which it's not solving, at least not now. And it may solve, but it's only, my view is, you know what's going to happen? A horrible catastrophe. It's the only way, it's the only way we will direct ourselves to actually trying to do something about it. We don't have the wisdom and the realism and the sense of purpose. You know, what's her name? Greta goes blah, blah, blah, something like that in her last talk about the environmental summit in Glasgow, or whatever it was. And, you know, we just don't have it unless we're hit upside the head really, really hard. And then maybe, you know, the business with nuclear weapons, you know, I think somehow we got hit upside the head and we realized, oh man, you know, this could really do it to the whole world. And so we started, you know, serious arms control stuff. And, you know, but up to that point, you know, I mean, there was just something about, you know, Khrushchev's big bomb, his big hydrogen bomb, which he exploded in the times, I think it was the anniversary or something like that. You know, I mean, just think what we could have done to each other. Well, that's the double-edged sword of technology. Yes, I agree. First of all, there's a lot of people, there's a lot of people that argue that nuclear weapons is the reason we haven't had a World War III. So nuclear weapons, the mutually assured destruction leads to a kind of like, we've reached a certain level of destructiveness with our weapons where we were able to catch ourselves, not to create, like you said, hit really hard. This is the interesting question about kind of hard, hard and really hard upside the head. With the environment, I would argue, see, we can't know the future, but I would argue as the pressure builds, there's already, because of this created urgency, the amount of innovation that I've seen that sometimes is unrelated to the environment, but kind of sparked by this urgency, it's been humongous, including the work of Elon Musk, including the work of just, you could argue that the SpaceX and the new exploration of space is kind of sparked by this environmental like urgency. I mean, connected to Tesla and everything they're doing with electric vehicles and so on. There's a huge amount of innovation in the space that's happening. I could see the effect of climate change resulting in more positive innovation that improves the quality of life across the world than the actual catastrophic events that we're describing, which we cannot even currently predict. It's not like there's going to be more extreme weather events. What does that even mean? There's going to be a gradual increase of the level of water. What does that even mean in terms of catastrophic events? It's going to be pretty gradual. There's going to be migration of people. We can't predict what that means. And in response to that, there's going to be a huge amount of innovators born today that have dreams and that will build devices and inventions from space to vehicles to in the software world that enable education across the world. All those kinds of things that will on mass, on average, increase the quality of life on average across the world. So it's not at all obvious that the technologies that are creating climate change, global warming, are going to have a negative, net negative effect. We don't know this. And I'm kind of inspired by the dreamers, the engineers, the innovators, and the entrepreneurs that build, that wake up in the morning, see problems in the world, and dream that they're going to be the ones who solve those problems. That's the human spirit. And I'm not exactly, it is true that we need those deadlines. We need to be freaking out about stuff. And the reason we need to study history and the worst of human history is then we can say, oh shit, this too can happen. It's a slap in the face. It's a wake up call. That if you get complacent, if you get lazy, this is going to happen. And that, listen, there's a lot of really intelligent people, ambitious people, dreamers, skilled dreamers that build solutions that make sure this stuff doesn't happen anymore. So I think there's reason to be optimistic about technology, not in a naive way. There's an argument to be made in a realistic way that like with technology, we can build a better future. And then Facebook is a lesson in the way Facebook has been done, is a lesson how not to do it. And that lesson serves as a guide of how to do it better, how to do it right, how to do it in a positive way. And the same, every single sort of failed technology contains within it the lessons of how to do it better. I mean, without that, what's the source of hope for human civilization? You know, I mean, by way of question, you have truly studied some of the darkest moments in human history. Put on your optimist hat. That one? Yes. The glimmers of it. Yes. What is your source of hope for the future of human civilization? Well, I think it resides in, you know, some of what you've been saying, which is in the persistence of this civilization over time, despite, you know, the incredible setbacks. You know, two enormous world wars, you know, the nuclear standoff, you know, the horrible things we're experiencing now with climate change and migration and stuff like that. That despite these things, you know, we are persisting and we are continuing. And like you say, we're continuing to invent and we're continuing to try to solve these problems. And, you know, we're continuing to love as well as hate. And, you know, that, you know, I'm basically I mean, I have children and grandchildren and I think they're going to they're going to be just fine. You know, I'm not a I'm not a doom and gloomer. You know, I'm not a Cassandra saying the world is coming to an end. I'm not like that at all. You know, I think that, you know, things will persist. Another, by the way, source of tremendous optimism on my part, the kids I teach, you know, I teach some unbelievably fantastic young people, you know, who are sort of like you say, they're dreamers and they're problem solvers. And they're there. I mean, they have enormously humane values and ways of thinking about the world. And they want to they want to do good. You know, if you take the kind of I mean, this has probably been true all the way along. But I mean, the percentage of do gooders, you know, is really enormously large. Now, whether they end up working for some kind of shark law firm or something or or, you know, that that that kind of thing or whether they end up human rights lawyers, as they all want to be. Right. Yeah. You know, is a different kind of question. But but certainly, you know, these young people are talented, they're smart, they're wonderful values, they're energetic, they work hard, you know, they're focused. And of course, it's not just Stanford. I mean, it's all over the country. You know, you have young people who really want to contribute and they want to contribute. I mean, you I mean, it's true. Some of them end up, you know, working to get rich. I mean, that's inevitable. Right. But but the percentages are actually rather small, at least at this age. You know, maybe when they get a mortgage and a family and that sort of thing, you know, the financial well-being will be more important to them. But right now, you know, you catch this young generation and they're fantastic. They're fantastic. And they're not what they're often portrayed as being, you know, kind of silly and naive and knee jerk leftists. And that did not at all like that. You know, they're really they're really fine young people. So that's a source of optimism to me, too. What advice would you give to those young people today, maybe in high school, in college, at Stanford, maybe to your grandchildren about how to have a career they can be proud of, have a life they can be proud of? Pursue careers that are in the public interest, you know, in one fashion or another, and not just in their interests. And that would be I mean, it's not bad to pursue a career in your own interests. I mean, as long as you're it's something that's useful and positive for the you know, for their families or whatever. But yeah, so I mean, I try to I try to advise kids to find themselves somehow, you know, find it who they want to be and what they want to be and try to pursue it. And the NGO world is growing, as you know, and a lot of young people are kind of throwing themselves into it and, you know, human rights watch and that kind of stuff. And, you know, they want to do that kind of work. And it's very admirable. I tend to think that even if you're not working in human rights, there's a certain way in which if you live with integrity, the I believe that all of us, or many of us have a bunch of moments in our lives, when we're posed with a decision. It's a quiet one. It'll never be written about or talked about. Well, you get to choose what do you there's a choice that is difficult to make may require sacrifice, but it's the choice that the best version of that person would make. That's the best way I can sort of say how to act with integrity. It's the very thing that would resist the early days of Nazi Germany. It sounds dramatic to say but those little actions. And I feel like the best you can do to avoid genocide on scale is for all of us to live in that way. To within those moments, unrelated potentially to human rights to anything else is to take those actions. Like I believe that all of us know the right thing to do. I know that's right. I think that's right. You put it very well. I couldn't have done it better myself. No, no, I agree. I agree completely that there are, you know, to live with truth, which is what Václav Havel used to say this famous Czech dissident, you know, talked about living in truth, but also to live with integrity. Yeah. And that's really super important. Well, let me ask you about love. What role does love play in this whole thing in the human condition? In all the study of genocide, it does seem that hardship in moments brings out the best in human nature and the best in human nature is expressed through love. Well, as I already mentioned to you, I think hardship is not a good thing for, you know, it's not the best thing for love. I mean, it's better to not have to suffer and not have to. You think so? I think it is. I think it's, you know, as I mentioned to you, you know, studying concentration camps, you know, this is not a place for love. It happens. It happens, but it's not really a place for love. It's a place for rape. It's a place for torture. It's a place for killing and it's a place for inhuman action one to another, you know, and also, as I said, among those who are suffering, not just between those who are. And then there are whole gradations, you know, the same thing in the gulag, you know, there are gradations all the way from the criminal prisoners who beat the hell out of the political prisoners, you know, who then have others below them who they beat down, you know, so everybody's being the hell out of everybody else. So I would not idealize in any way suffering as a, you know. A source of beauty. A source of beauty and love. I wouldn't do that. I think it's a whole lot better for people to be relatively prosperous. I'm not saying super prosperous, but to be able to feed themselves and to be able to feed their families and house their families and take care of themselves, you know, to foster loving relations between people. And, you know, I think it's no accident that, you know, poor families have much worse records when it comes to crime and things like that, you know, and also to wife beating and to child abuse and stuff like that. I mean, you just, you don't want to be poor and indigent and not have a roof over your head, be homeless. I mean, it doesn't mean again, you know, homeless people are mean people. That's not what I'm trying to say. What I'm trying to say is that, you know, what we want to try to foster in this country and around the world. And one of the reasons, you know, I mean, I'm very critical of the Chinese in a lot of ways, but I mean, we have to remember they pulled that country out of horrible poverty, right? And I mean, there's still poor people in the countryside. There's still problems, you know, with want and need among the Chinese people. But, you know, there were millions and millions of Chinese who were living at the bare minimum of life, which is no way to live, you know, and no way again to foster love and compassion and getting along. So, I want to be clear. I don't speak for history, right? I'm giving you, I mean, there used to be historians, you know, in the 19th century who really thought they were speaking for history. Yeah. You know, I don't think that way at all. I mean, I understand I'm a subjective human being with my own points of view and my own opinions, but— I'm trying to remember in this conversation that you're, despite the fact that you're brilliant and you've written brilliant books, that you're just human. Well, I am. With an opinion. That's it. Yeah. No, no, that's absolutely true. And I tell my students that, too. I mean, I make sure they understand this is not history speaking. You know, this is me and Norman. You know, and this is what it's about. I mean, I spent a long time studying history and have enjoyed it enormously. But, you know, I'm an individual with my points of view. And one of them is that I've developed over time is that, you know, human want is a real tragedy for people. And it hurts people. And it also causes upheavals and difficulties and stuff. So, I feel for people. You know, I feel for people in Syria. I feel for people in, you know, in Ethiopia, in Tigray, you know, when they don't have enough to eat. And, you know, what that does—I mean, it doesn't mean they don't love each other, right? And it doesn't mean they don't love their kids. But it does mean that it's harder, you know, to do that and to— I'm not so sure. It's obvious to me that it's harder. There is suffering. There is suffering. But the numbers—we've been talking about deaths, been talking about suffering, but the numbers were not quantifying. The history that you haven't perhaps been looking at is all the times that people have fallen in love deeply with friends, with romantic love, the positive emotion that people have felt. And I'm not so sure that amidst the suffering, those moments of beauty and love can be discovered. And if we look at the numbers, I'm not so sure the story is obvious. That, you know, I mean, again, I suppose you may disagree with Viktor Frankl. I may, too, maybe, depending on the day. I mean, he says that if there's meaning to this life at all, there's meaning to the suffering, too, because suffering is part of life. There's something about accepting the ups and downs, even when the downs go very low. And within all of it, finding a source of meaning. I mean, he's arguing from the perspective of psychology, but just this life is an incredible gift almost no matter what. And I'm not—it's easy to look at suffering and think if we just escape the suffering, it will all be better. But we all die. There's beauty in the whole thing. It is true that it's just—from all the stories I've read, especially in famine and starvation, it's just horrible. It is horrible suffering. But I also just want to say that there's love amidst it, and we can't forget that. No, no, I don't forget it. I don't forget it. And I think it's from the stories—now, I don't want to make that compromise or that trade. But the intensity of friendship in war, the intensity of love in war, is very high. So I'm not sure what to make of these calculations. But if you look at the stories, some of the people I'm closest with—and I've never experienced anything even close to any of this. But some of the people I'm closest with is people I've gone through difficult times with. There's something about that. They're a society or a group where things are easy. The intensity of the connection between human beings is not as strong. I don't know what to do with that calculus, because I, too, agree with you. I want to have as little suffering in the world as possible. But we have to remember about the love and the depth of human connection and find the right balance there. No, there's something to what you're saying. There's clearly something to what you're saying. I was just thinking about the Soviet Union when I lived there. And people on the streets were so mean to one another. They never smiled. You grew up there? No, but you were too young to be. No, I remember well. I came here when I was 13, yeah. Okay. So anyway, I remember living there and just how hard people were on each other on the streets. And when you got inside people's apartments, when they started to trust you, the friendships were so intense and so wonderful. So in that sense, I mean, they did live a hard life. But there wasn't enough food on the table and there was a roof over their heads. There's a certain line. There are lines. I don't think there's one line, but it's kind of a shading. And the other story I was thinking of as you were talking was not a story. It's a history, a book by a friend of mine who wrote about love in the camps, in the refugee camps for Jews in Germany after the war. So these were Jews who had come mostly from Poland. And, you know, some survived the camps, came from awful circumstances. And then they're put in these camps, which were not joyful places. I mean, they were guarded sometimes by Germans even, but they're basically under the British control. And they were trying to get to Israel, you know, trying to get to Palestine right after the war. And how many pairs there were, how many people coupled up. But remember, this is after being in the concentration camp. It's not being in the concentration camp. And it's also being free, you know, to more or less free, you know, to express their emotions and to be human beings after this horrible thing which they suffered. So I wonder whether there's, you know, as you say, some kind of calculus there where, you know, the level of suffering is such that it's just too much for humans to bear. And, you know, which I would suggest, I mean, I haven't studied this myself. I'm just giving you my point of view, you know, my off the cuff remarks here. But it was very inspiring to read about these couples who had met right in these camps and started to couple up, you know, and get married and try to find their way to Palestine, which was a difficult thing to do then. When did you live in Russia and the Soviet Union? What's your memory of that time? Well, so a number of different times. So I went there. I first went there in 69, 70. Wow. A long time ago. And then I lived in Leningrad mostly, but also in Moscow in 1975. So it was detente time. But it was also a time of political uncertainty and also hardship, you know, for Russians themselves, standing in long lines. I mean, you must remember this for food and for getting anything was almost impossible. It was a time when Jews were trying to get out. In fact, I just talked to a friend of mine from those days who I helped get out and get to Boston and lovely people who managed to have a good life in the United States after they left. But it wasn't an easy time. It wasn't an easy time at all. I remember people set fire to their doors and, you know, their daughter was persecuted in school, you know, once they declared that they wanted to immigrate and that sort of thing. So it was a very, it was a lot of anti-Semitism. So it was a tough time. Dissidents, you know, hung out with some dissidents. And one guy was actually killed. We think by the, nobody knows exactly by the KGB, but his art studio was, he had a separate studio in Leningrad, St. Petersburg today. You know, just a small studio where he did his art and somebody set it on fire and we think it was KGB, but, you know, you never really know. And he died in that fire. So, you know, it was not, it was a tough time. And, you know, you knew you were followed. You knew you were being reported on as a foreign scholar, as I was. There was a formal exchange between the United States and the Soviet Union and, you know, they let me work in the archives, but then, you know, Ivanov got to work in the physics lab at Rochester or something like that. You know, so it was an exchange which sent historians and literary people and some social scientists to Russia and they sent all scientists here to, you know, grab what they could from MIT and those places. How's your Russian? Do you have any knowledge of Russian language that has helped you to understand? Oh, yeah. Yeah. I mean, I can read it fine. And the speaking, you know, comes and goes, depending on whether I'm there or whether I've been there recently or if I spend some time there. Because I really need, you know, I have Russian friends who speak just Russian. So, you know, when I'm there, I then, you know, I can communicate pretty well. I can't really write it, unfortunately. I mean, I can, but it's not very good. But I get along fine. What's your fondest memory of the Soviet Union, of Russia? Friends. It's friends. Was it vodka involved or is it just vodka involved? A little bit. You know, I'm not much of a drinker. Yeah. So, you know, they just make fun of me and I make fun of myself. It's easy enough. I don't really like, you know, a heavy drink. I've done a lot of that. Yeah. Not a lot. I've done some of that, but I never really enjoyed it and would get sick and stuff. But, no, it's friends. You know, one friend I made in the dormitory, you know, it was a dormitory for foreigners, but also Siberians who had come, you know, to Leningrad to study. And so I met a couple of guys and one in particular from Omsk became a wonderful friend. And we talked and talked and talked outside. You know, we would go walk outside because we both knew they were, you know, people were listening and stuff. And he would say, well, this is he was an historian, you know, and so we would talk history. And he'd say, well, this was the case, wasn't it? I said, no, I'm sorry, Sasha. It wasn't the case. It was, you know, we think Stalin actually had a role in killing Kirov. I mean, we're not sure, but he said no. I said, yeah. You know, so, you know, we had these conversations and he was a he was what I would. I don't know if he would agree with me or not. I mean, we're still friends. So he was a he's going to check in with naive. Maybe he'll listen to the blog or I'll send it to him or something. He was a kind of naive Marxist Leninist. And he thought I was, you know, I was, you know, I had this capitalist ideal. He'd say, what ideology you have. And I said, I don't have an ideology. You know, I try to just put together kind of reason and facts and accurate stories and try to tell them in that way. No, no, no, no. You must, you know, you're a bourgeois, you know, this or that. I'm really not. And so we would have these talks and these kind of arguments. And then, I mean, sure enough, you know, we corresponded for a while. And then he had to stop corresponding because he became a kind of local official in Omsk. And he sort of migrated more and more to being a Democrat. And he was then in the, you know, Democratic movement under Gorbachev and, you know, the Council of People's Deputies, which they set up, which was, you know, elected as a Democrat from Omsk and had a political career through the Yeltsin period. And once Putin came along, you know, it was over. He didn't like Putin and, you know, and Putin didn't like the Yeltsin people, right, who were, tried to be, some of them tried to be Democrats. And Sasha was one who really did. He just published his memoirs in Russian, by the way, which are very good, I think. I think that's the name of it. Kommandirovky vlast. That's what it's called. It's hard to translate in English. Kommandirovky vlast. But I mean, I translated it four points once for him. This is so beautiful. Like, do you find that the translation is a problem or no? It's such a different. Translation is very difficult. With the Russian language. I mean, it's the only language I know deeply, except English. And it seems like so much is lost of the pain, the poetry, the beauty of the people. And translators are to be treasured and good ones to be. I mean, those who do the translations, when you read things in translation, sometimes they're quite beautiful, whether it's Russian or Polish or German or anything, French. Yeah, I mentioned traveling to Paris to talk to the famous translators, the Dostoevsky Tolstoy. And I'm just going to do several conversations with them about, like, you could just sometimes just grab a single sentence and just talk about the translation in that sense. Right. And also, as you said, I would love to be a fly on the wall with some of those friends that you had, because the perspective on history, non-academic, sort of without just as human beings, is so different. From the United States versus Russia. When you talk about the way the World War II was perceived and all those kinds of things, it's fascinating. History also has in it opinion and perspective. And so sometimes stripping that away is really difficult. And I guess that is your job. And at its highest form, that is what you do as a historian. Well, Norman, spasibo basho, sto seguni sobre oshkodnye. I really appreciate your valuable time. It's truly an honor to talk to you. And thank you for taking us through a trip through some of the worst parts of human history and talking about hope and love at the end. So I really appreciate your time today. Thank you. Thank you for having me. Thanks for listening to this conversation with Norman Naimark. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Stalin. A single death is a tragedy. A million deaths is a statistic. Thank you for listening and hope to see you next time.

https://youtu.be/Vrz8YDl9CeA

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Jeremi Suri: History of American Power | Lex Fridman Podcast #180

The following is a conversation with Jeremy Suri, a historian at UT Austin, whose research interests and writing are on modern American history with an eye towards presidents and in general individuals who wielded power. Quick mention of our sponsors, Element, MonkPak, Belcampo, Four Sigmatic, and Eight Sleep. Check them out in the description to support this podcast. As a side note, let me say that in these conversations, for better or worse, I seek understanding, not activism. I'm not left nor right. I love ideas, not labels. And most fascinating ideas are full of uncertainty, tension, and trade-offs. Labels destroy that. I try ideas out, let them breathe for a time, try to challenge, explore, and analyze. But mostly, I trust the intelligence of you, the listener, to think and to make up your own mind, together with me. I will try to have economists and philosophers on from all points on the multidimensional political spectrum, including the extremes. I will try to both have an open mind and to ask difficult questions when needed. I'll make mistakes. Don't shoot this robot at the first sign of failure. I'm still under development. Pre-release version 0.1. This is the Lex Friedman Podcast, and here is my conversation with Jeremy Suri. You've studied many American presidents throughout history. So, who do you think was the greatest president in American history? The greatest American president was Abraham Lincoln. And Tolstoy reflected on this himself, actually, saying that when he was in the Caucasus, he asked these peasants in the Caucasus who was the greatest man in the world that they had heard of, and they said Abraham Lincoln. And why? Well, because he gave voice to people who had no voice before. He turned politics into an art. This is what Tolstoy recounted, the peasants in the Caucasus telling him. Lincoln made politics more than about power. He made it an art. He made it a source of liberation. And those living even far from the United States could see that model, that inspiration from Lincoln. He was a man who had two years of education, yet he mastered the English language, and he used the language to help people imagine a different kind of world. You see, leaders and presidents are at their best when they're doing more than just manipulating institutions and power, when they're helping the people imagine a better world. And he did that as no other president has. And you say he gave voice to those who are voiceless. Who are you talking to about in general? Is this about African Americans, or is this about just the populace in general? Certainly part of it is about slaves, African Americans, and many immigrants, immigrants from all parts of Europe and other areas that have come to the United States. But part of it was just for ordinary American citizens. The Republican Party, for which Lincoln was the first president, was a party created to give voice to poor white men, as well as slaves and others. And Lincoln was a poor white man himself. Grew up without slaves and without land, which meant you had almost nothing. What do you think about the trajectory of that man with only two years of education? Is there something to be said about how does one come from nothing and nurture the ideals that kind of make this country great into something where you can actually be a leader of this nation to espouse those ideas, to give the voice to the voiceless? Yes, I think you actually hit the nail on the head. I think what he represented was the opportunity, and that was the word that mattered for him, opportunity that came from the ability to raise yourself up, to work hard and to be compensated for your hard work. And this is at the core of the Republican Party of the 19th century, which is the core of capitalism. It's not about getting rich. It's about getting compensated for your work. It's about being incentivized to do better work. And Lincoln was constantly striving. One of his closest associates, Herndon, said he was the little engine of ambition that couldn't stop. He just kept going, taught himself to read, taught himself to be a lawyer. He went through many failed businesses before he even reached that point, many failed love affairs, but he kept trying. He kept working, and what American society offered him and what he wanted American society to offer everyone else was the opportunity to keep trying to fail and then get up and try again. What do you think was the nature of that ambition? Was there a hunger for power? I think Lincoln had a hunger for success. I think he had a hunger to get out of the poor station he was in. He had a hunger to be someone who had control over his life. Freedom for him did not mean the right to do anything you wanna do, but it meant the right to be secure from being dependent upon someone else. So independence. He writes in his letters when he's very young that he hated being dependent on his father. He grew up without a mother. His father was a struggling farmer, and he would write in his letters that his father treated him like a slave on the farm. Some think his hatred of slavery came from that experience. He didn't ever wanna have to work for someone again. He wanted to be free and independent, and he wanted, again, every American, this is the kind of Jeffersonian dream, to be the owner of themself and the owner of their future. You know, that's a really nice definition of freedom. We often think kind of this very abstract notion of being able to do anything you want, but really it's ultimately breaking yourself free from the constraints, like the very tight dependence on whether it's the institutions or on your family or the expectations or the community or whatever, being able to be, to realize yourself within the constraints of your own abilities. It's still not true freedom. It's true freedom is probably sort of almost like designing a video game character or something like that. I agree, I think that's exactly right. I think freedom is not that I can have any outcome I want. I can't control outcomes. The most powerful, freest person in the world cannot control outcomes, but it means that at least I get to make choices. Someone else doesn't make those choices for me. Is there something to be said about Lincoln and on the political game front of it, which is he's accomplished some of them? I don't know, but it seems like there was some tricky politics going on. We tend to not think of it in those terms because of the dark aspects of slavery. We tend to think about it in sort of ethical and human terms, but in their time, it was probably as much a game of politics not just these broad questions of human nature, right? It was a game. So is there something to be said about being a skillful player in the game of politics that you'd take from Lincoln? Absolutely, and Lincoln never read Karl von Clausewitz, the great 19th century German thinker on strategy and politics, but he embodied the same wisdom, which is that everything is politics. If you wanna get anything done, and this includes even relationships, there's a politics to it. What does that mean? It means that you have to persuade, coerce, encourage people to do things they wouldn't otherwise do. And Lincoln was a master at that. He was a master at that for two reasons. He had learned through his hard life to read people, to anticipate them, to spend a lot of time listening. One thing I often tell people is the best leaders are the listeners, not the talkers. And then second, Lincoln was very thoughtful and planned every move out. He was thinking three or four moves, maybe five moves down the chessboard, while others were move number one or two. That's fascinating to think about him just listening to studying. They look at great fighters in this way. Like the first few rounds of boxing and mixed martial arts, you're studying the movement of your opponent in order to sort of define the holes. That's a really interesting frame to think about it. Is there, in terms of relationships, where do you think as president or as a politician is the most impact to be had? I've been reading a lot about Hitler recently, and one of the things that I'm more and more starting to wonder, what the hell did he do alone in a room with a one-on-one with people? Because it seems like that's where he was exceptionally effective. When I think about certain leaders, I'm not sure Stalin was this way. I apologize, been very obsessed with this period of human history. It just seems like certain leaders are extremely effective one-on-one. A lot of people think of Hitler and Lincoln as a speech maker, as a great charismatic speech maker. But it seems like to me that some of these guys were really effective inside a room. What do you think? What's more important, your effectiveness to make a hell of a good speech, sort of being in a room with many people, or is it all boiled down to one-on-one? Well, I think in a sense, it's both. One needs to do both. And most politicians, most leaders are better at one or the other. It's the rare leader who can do both. I will say that if you are going to be a figure who's a president or the leader of a complex organization, not a startup, but a complex organization where you have many different constituencies and many different interests, you have to do the one-on-one really well. Because a lot of what's going to happen is you're going to be meeting with people who represent different groups, right? The leader of the labor unions, the leader of your investing board, et cetera. And you have to be able to persuade them. And it's the intangibles that often matter most. Lincoln's skill, and it's the same that FDR had, is the ability to tell a story. I think Hitler was a little different, but what I've read of Stalin is he was a storyteller too. One-on-one storyteller? Yeah, that's my understanding is that he... And what Lincoln did, I don't want to compare Lincoln to Stalin, but Lincoln did is he was not confrontational. He was happy to have an argument if an argument were to be had, but actually what he would try to do is move you through telling a story that got you to think about your position in a different way, to basically disarm you. And Franklin Roosevelt did the same thing. Ronald Reagan did the same thing. Storytelling is a very important skill. It's almost heartbreaking that we don't get to have, or maybe you can correct me if I'm wrong on this, but it feels like we don't have a lot of information how all of these folks were in private, one-on-one conversations. Even if we get stories about it, it's like, again, sorry to bring up Hitler, but people have talked about his piercing gaze when they're one-on-one. There's a feeling like he's just looking through you. I wonder, it makes me wonder, was Lincoln somebody who was a little bit more passive, like who's more, the ego doesn't shine. It's not like an overwhelming thing, or is it more like, again, don't wanna bring up controversial figures, but Donald Trump, where it's more menacing, right? There's a more physically menacing thing where it's almost like a bullying kind of dynamic. So I wonder, I wish we knew. Because from a psychological perspective, I wonder if there's a thread that connects most great leaders. That's a great question. So I think the best writer on this is Max Weber, right? And he talks about the power of charisma, that the term charisma comes from Weber, right? And Weber's use of it actually to talk about prophets. And I think he has a point, right? Leaders who are effective in the way you describe are leaders who feel prophetic, or Weber says they have a kind of magic about them. And I think that can come from different sources. I think that can come from the way someone carries themselves. It can come from the way they use words. So maybe there are different kinds of magic that someone develops. But I think there are two things that seem to be absolutely necessary. First is you have to be someone who sizes up the person on the other side of the table. You cannot be the person who just comes in and reads your brief. And then second, I think it's interactive. And there is a quickness of thought. So you brought up Donald Trump. I don't think Donald Trump is a deep thinker at all, but he's quick. And I think that quickness is part of it. It's different from delivering a lecture where it's the depth of your thought. Can you for 45 minutes analyze something? Many people can't do that, but they still might be very effective if they're able to quickly react, size up the person on the other side of the table, and react in a way that moves that person in the way they wanna move them. Yeah, and there's also just a, coupled with the quickness is a kind of instinct about human nature. Yes, sort of asking the question, what does this person worry about? What are the biggest problems? Somebody, what is this, Steven Schwarzman, I think, said to me, this businessman. I think he said, what I've always tried to do is try to figure out, ask enough questions to figure out what is the biggest problem in this person's life. Try to get a sense of what is the biggest problem in their life, because that's actually what they care about most. And most people don't care enough to find out. And so, he kinda wants to sneak up on that, and find that, and then use that to then build closeness in order to then, probably, he doesn't put it in those words, but to manipulate the person into whatever, to do whatever the heck they want. And I think part of it is that, and part of the effect that Donald Trump has is how quick he's able to figure that out. You've written a book about how the role and power of the presidency has changed. So, how has it changed since Lincoln's time, the evolution of the presidency as a concept, which seems like a fascinating lens through which to look at American history. As a president, we seem to only be talking about the presidents, maybe a general here and there, but it's mostly the story of America is often told through presidents. That's right, that's right. And one of the points I've tried to make in my writing about this and various other activities is we use this word president as if it's something timeless. But the office has changed incredibly. Just from Lincoln's time to the present, which is 150 years, he wouldn't recognize the office today. And George Washington would not have recognized it in Lincoln, just as I think a CEO today would be unrecognizable to a Rockefeller or a Carnegie of 150 years ago. So, what are some of the ways in which the office has changed? I'll just point to three, there are a lot. One, presidents now can communicate with the public directly. I mean, we've reached the point now where a president can have direct, almost one-on-one communication. President can use Twitter, if he so chooses, to circumvent all media. That was unthinkable. Lincoln, in order to get his message across, often wrote letters to newspapers. And waited for the newspaper for Horace Greeley in the New York Tribune to publish his letter. That's how he communicated with the public. There weren't even many speaking opportunities. So, that's a big change, right? We feel the president in our life much more. That's why we talk about him much more. That also creates more of a burden. That's the second point. Presidents are under a microscope. Presidents are under a microscope. You have to be very careful what you do and what you say. And you're judged by a lot of the elements of your behavior that are not policy relevant. In fact, the things we judge most and make most of our decisions on about individuals are often that. And then third, the power the president has. It's inhuman, actually. And this is one of my critiques of how the office has changed. This one person has power on a scale that's, I think, dangerous in a democracy. And certainly, something the founders 220 years ago would have had trouble conceiving. Presidents now have the ability to deliver force across the world to literally assassinate people with a remarkable accuracy. And that's an enormous power that presidents have. So your sense, this is not to get conspiratorial, but do you think a president currently has the power to initiate the assassination of somebody, of a political enemy, or a terrorist leader, or that kind of thing, to frame that person in a way where assassination is something that he alone or she alone could decide to do? I think it happens all the time. And it's not to be conspiratorial. This is how we've fought terrorism, by targeting individuals. Now, you might say these were not elected leaders of state, but these were individuals with a large following. I mean, the killing of Osama bin Laden was an assassination operation. And we've taken out very successfully many leaders of terrorist organizations, and we do it every day. You're saying that back in Lincoln's time or George Washington's time, there was more of a balance of power? Like a president could not initiate this kind of assassination? Correct, I think presidents did not have the same kind of military or economic power. We could talk about how a president could influence a market, right, by saying something about where money is gonna go, or singling out a company, or critiquing a company in one way or another. They didn't have that kind of power. Now, much of the power that a Lincoln or a Washington had was the power to mobilize people to then make their own decisions. At the start of the Civil War, Lincoln doesn't even have the power to bring people into the army. He has to go to the governors and ask the governors to provide soldiers. So the governor of Wisconsin, the governor of Massachusetts. Could you imagine that today? So, but yeah, so they used speeches and words to mobilize versus direct action in closed door environments initiating wars, for example. Correct. It's difficult to think about, if we look at Barack Obama, for example, if you're listening to this, and you're on the left or the right, please do not make this political. In fact, if you're a political person, and you're getting angry at the mention of the word Obama or Donald Trump, please turn off this podcast. I'm just kidding. We're not gonna get very far. I hope we maintain a political discussion about even the modern presidents that viewed through the lens of history. I think there's a lot to be learned about the office and about human nature. Some people criticize Barack Obama for sort of expanding the military industrial complex, engaging in more and more wars, as opposed to sort of the initial rhetoric was such that we would pull back from sort of be more skeptical in our decisions to wage wars. So from the lens of the power of the presidency, the modern presidency, the fact that we continue the war in Afghanistan at different engagements in military conflicts, do you think Barack Obama could have stopped that? Do you put the responsibility on that expansion on him because of the implied power that the presidency has? Or is this power just sits there, and if the president chooses to take it, they do, and if they don't, they don't, almost like you don't want to take on the responsibility because of the burden of that responsibility? So a lot of my research is about this exact question, not just with Obama. And my conclusion, and I think the research is pretty clear on this, is that structure has a lot more effect on us than we like to admit, which is to say that the circumstances, the institutions around us drive our behavior more than we like to think. So Barack Obama, I'm quite certain, came into the office of the presidency committed to actually reducing the use of military force overseas and reducing presidential war-making power. As a trained lawyer, he had a moral position on this, actually, and he tried, and he did withdraw American forces from Iraq and was, of course, criticized by many people for doing that. But at the same time, he had some real problems in the world to deal with, terrorism being one of them. And the tools he has are very much biased towards the use of military force. It's much harder as president to go and get Vladimir Putin and Xi Jinping to agree with you. It's much easier to send these wonderful toys we have and these incredible soldiers we have over there. And when you have Congress, which is always against you, it's also easier to use the military because you send them there, and even if members of Congress from your own party or the other are angry at you, they'll still fund the soldiers. No member of Congress wants to vote to starve our soldiers overseas. So they'll stop your budget. They'll even threaten not to pay the debt, but they'll still fund your soldiers. And so you are pushed by the circumstances you're in to do this, and it's very hard to resist. So that's, I think the criticism of Obama, the fair one would be that he didn't resist the pressures that were there, but he did not make those pressures. So is there something about putting the responsibility on the president to form the structure around him locally such that he can make the policy that matches the rhetoric? So what I'm talking to is hiring. So basically just everybody you work with, you have power as a president to fire and hire or to basically schedule meetings in such a way that can control your decision-making. So I imagine it's very difficult to get out of Afghanistan or Iraq when most of your scheduled meetings are with generals or something like that. But if you reorganize the schedule and you reorganize who you have late night talks with, you potentially have a huge ripple effect on the policy. I think that's right. I think who has access to the president is absolutely crucial. And presidents have to be more strategic about that. They tend to be reacting to crises because every day has a crisis. And if you're reacting to a crisis, you're not controlling access because the crisis is driving you. So that's one element of it. But I also think, and this is the moment we're in right now, presidents have to invest in reforming the system, the system of decision-making. Should we have a national security council that looks the way it does? Should our military be structured the way it is? The founding fathers wanted a military that was divided. They did not want a unified department of defense. That was only created after World War II. Should we have as large a military as we have? Should we be in as many places? There are some fundamental structural reforms we have to undertake. And part of that is who you appoint, but part of that is also how you change the institutions. The genius of the American system is that it's a dynamic system. It can be adjusted. It has been adjusted over time. That's the heroic story. The frustrating story is it often takes us a long time to make those adjustments until we go into such bad circumstances that we have no choice. So in the battle of power of the office of the president versus the United States military, the Department of Defense, do you have a sense that the president has more power ultimately? So to decrease the size of the Department of Defense, to withdraw from any wars, or increase the amount of wars, is the president, you're kind of implying the president has a lot of power here in this scale. Yes, the president has a lot of power, and we are fortunate, and it was just proven in the last few years that our military, uniquely among many countries with large militaries, is very deferential to the president and very restricted in its ability to challenge the president. So that's a strength of our system. But the way you reform the military is not with individual decisions. It's by having a strategic plan that re-examines what role it plays. So it's not just about whether we're in Afghanistan or not. The question we have to ask is, when we look at our toolbox of what we can do in our foreign policy, are there other tools we should build up, and therefore some tools in the military we should reduce? That's the broader strategic question. Let me ask you the most absurd question of all that you did not sign up for, but it's especially, I've been hanging out with a guy named Joe Rogan recently. Sure. It's important for me and him to figure this out. If a president, because you said, you implied the president's very powerful, if a president shows up and the US government is in fact in possession of aliens, alien spacecraft, do you think the president will be told? A more responsible adult historian question version of that is, is there some things that the machine of government keeps secret from the president? Or is the president ultimately at the very center? So if you map out the set of information and power, you have CIA, you have all these organizations that do the machinery of government, not just the passing of bills, but gaining information, homeland security, actually engaging in wars, all those kinds of things. How central is the president? Would the president know some of the shady things that are going on? Aliens or some kind of cybersecurity stuff against Russia and China, all those kinds of things. Is the president really made aware? And if so, how nervous does that make you? So presidents like leaders of any complex organizations don't know everything that goes on. They have to ask the right questions. This is Machiavelli. Most important thing a leader has to do is ask the right questions. You don't have to know the answers. That's why you hire smart people, but you have to ask the right questions. So if the president asks the US government, those who are responsible for the aliens or responsible for the cyber warfare against Russia, they will answer honestly, they will have to, but they will not volunteer that information in all cases. So the best way a president can operate is to have people around him or her who are not the traditional policy makers. This is where I think academic experts are important, suggesting questions to ask to therefore try to get the information. It makes me nervous because I think human nature is such that the academics, the experts, everybody is almost afraid to ask the questions for which the answers might be burdensome. Yes, that's right. And you can get into a lot of trouble not asking, it's the old elephant in the room. Correct, correct. This is exactly right, and too often, mediocre leaders and those who try to protect them try to shield themselves. They don't want to know certain things. So this is part of what happened with the use of torture by the United States, which is a war crime, during the war on terror. President Bush at times intentionally did not ask, and people around him prevented him from asking or discouraged him from asking questions he should have asked to know about what was going on. And that's how we ended up where we did. You could say the same thing about Reagan and Iran-Contra. I wonder what it takes to be the kind of leader that steps in and asks some difficult questions. So aliens is one, UFO spacecraft, right? Another one, yeah, torture is another one. The CIA, how much information is being collected about Americans? I can see, as a president, being very uncomfortable asking that question, because if the answer is a lot of information is being collected by Americans, then you have to be the guy who lives with that information. For the rest of your life, you have to walk around. You're probably not going to reform that system. It's very difficult. You probably have to be very picky about which things you reform. You don't have much time. It takes a lot of effort to restructure things. But you nevertheless would have to be basically lying to yourself, to others around you about the unethical things. Depends, of course, what the ethical system is. I wonder what it takes to ask those hard questions. I wonder if how few of us can be great leaders like that. And I wonder if our political system, the electoral system, is such that makes it likely that such leaders will come to power. It's hard, and you can't ask all the right questions, and there is a legal hazard if you know things at certain times. But I think you can, back to your point on hiring, you can hire people who will do that in their domains. And then you have to trust that when they think it's something that's a question you need to ask, they'll pass that on to you. This is why it's not a good idea to have loyalists, because loyalists will shield you from things. It's a good idea to have people of integrity who you can rely on and who you think will ask those right questions, and then pass that down through their organization. What's inspiring to you, what's insightful to you about several of the presidencies throughout the recent decades? Is there somebody that stands out to you that's interesting in sort of in your study of how the office has changed? Well, Bill Clinton is one of the most fascinating figures. Why can't I apologize? Bill Clinton just puts a smile on my face every time somebody mentions him at this point. I don't know why. It's charisma, I suppose. Well, and he's a unique individual. But he fascinates me because he's a figure of such enormous talent and enormous appetite and such little self-control and such extremes. And I think it's not just that he tells us something about the presidency, he tells us something about our society. American society, this is not new to our time, is filled with enormous reservoirs of talent and creativity. And those have a bright and a dark side. And you see both with Bill Clinton. In some ways, he's the mirror of the best and worst of our society. And maybe that's really what presidents are in the end. They're mirrors of our world, that we get the government we deserve, we get the leaders we deserve. I wish we embraced that a little bit more. You know, a lot of people criticize Donald Trump for certain human qualities that he has. A lot of people criticize Bill Clinton for certain human qualities. I wish we kind of embraced the chaos of that. Because he does, you're right, in some sense represent, I mean, he doesn't represent the greatest ideal of America, but the flawed aspect of human nature is what he represents. And that's the beautiful thing about America, the diversity of this land with the mix of it, the corruption within capitalism, the beauty of capitalism, the innovation, all those kinds of things, the people that start from nothing and create everything, the Elon Musk's of the world and the Bill Gates and so on. But also the people, Bernie Madoffs, and all as the Me Too movement has showed, the multitude of creeps that apparently permeate the entirety of our system. So I don't know, there is something, there is some sense in which we put our president on a pedestal which actually creates a fake human being. Like the standard we hold them to is forcing the fake politicians to come to power versus the authentic one, which is in some sense, the promise of Donald Trump is, it's a definitive statement of authenticity. It's like this, the opposite of the fake politician, it's whatever else you wanna say about him, is there's the chaos that's unlike anything else that came before. One thing, and this is a particular maybe preference and quirk of mine, but I really admire, maybe I'm romanticizing the past again, but I romanticize the presidents that were students of history. That were almost like king philosophers, that made speeches that reverberated through decades after. Using the words of those presidents, whether written by them or not, we tell the story of America. And I don't know, even Obama has been an exceptionally good, as far as I know, I apologize if I'm incorrect on this, but from everything I've seen, he was a very deep scholar of history. And I really admire that. Is that through the history of the office of the presidency, is that just your own preference or is that supposed to come with the job? Are you supposed to be a student of history? I think, I mean, I'm obviously biased as a historian, but I do think it comes with the job. Every president I've studied had a serious interest in history. Now, how they pursued that interest would vary. Obama was more bookish, more academic. So was George W. Bush in strange ways. George H. W. Bush was less so, but George H. W. Bush loved to talk to people, so he would talk to historians, right? Ronald Reagan loved movies, and movies were an insight into history for him. He liked to watch movies about another time. It wasn't always the best of history, but he was interested in what is a fundamental historical question. How has our society developed? How has it grown and changed over time? And how has that change affected who we are today? That's the historical question. It's really interesting to me. I do a lot of work with business leaders and others too. You reach a certain point in any career and you become a historian because you realize that the formulas and the technical knowledge that you've gained got you to where you are. But now your decisions are about human nature. Your decisions are about social change, and they can't be answered technically. They can only be answered by studying human beings. And what is history? It's studying the laboratory of human behavior. To sort of play devil's advocate, I kind of, especially in the engineering scientific domains, I often see history holding us back. Sort of the way things were done in the past are not necessarily going to hold the key to what will progress us into the future. Of course, with history and studying human nature, it does seem like humans are just the same. It's just like the same problems over and over. So in that sense, it feels like history has all the lessons, whether we're talking about wars, whether we're talking about corruption, whether we're talking about economics. I think there's a difference between history and antiquarianism. So antiquarianism, which some people call history, is the desire to go back to the past or stay stuck in the past. So antiquarianism is the desire to have the desk that Abraham Lincoln sat at. Wouldn't it be cool to sit at his desk? I'd love to have that desk. If I had a few extra million dollars, I'd acquire it, right? So in a way, that's antiquarianism. That's trying to capture and hold on, hold on to the past. The past is a talisman for antiquarians. What history is, is the study of change over time. That's the real definition of historical study and historical thinking. And so what we're studying is change. And so a historian should never say, we have to do things the way we've done them in the past. The historian should say, we can't do them the way we did them in the past. We can't step in the same river twice. Every podcast of yours is different from the last one, right? It starts out and then it goes in its own direction, right? Yeah. And what are we studying then in history? We're studying the patterns of change and we're recognizing we're part of a pattern. So what I would say to the historian who's trying to hold the engineer back, I'd say, no, don't tell that engineer not to do this. Tell them to understand how this fits into the relationship with other engineering products and other activities from the past that still affect us today. For example, any product you produce is gonna be used by human beings who have prejudices. It's gonna go into an unequal society. Don't assume it's gonna go into an equal society. Don't assume that when you create a social media site that people are going to use it fairly and put only truthful things on it. We shouldn't be surprised. That's where human nature comes in. But it's not trying to hold onto the past. It's trying to use the knowledge in the past to better inform the changes today. I have to ask you about George Washington. It may be, maybe you have some insights. It seems like he's such a fascinating figure in the context of the study of power. Because I kind of intuitively have come to internalize the belief that power corrupts and absolute power corrupts absolutely. Yes. And sort of like, basically in thinking that we have to, we cannot trust any one individual. I can't trust myself with power. Nobody can trust anybody with power. We have to create institutions and structures that prevent us from ever being able to amass absolute power. And yet, here's a guy, George Washington, who seems to, you can correct me if I'm wrong, but he seems to give away relinquished power. It feels like George Washington did it like almost like the purest of ways, which is, believes in this country, but he just believes he's not the person to carry it forward. What do you make of that? What kind of human does it take to give away that power? Is there some hopeful message we can carry through to the future, to elect leaders like that, or to find friends to hang out with who are like that? Like, what is that? How do you explain that? So it's actually the most important thing about George Washington. It's the right thing to bring up. What the historian Gary Wills wrote years ago, I'm gonna quote him, was that Washington recognized that sometimes you get more power by giving it up than by trying to hold on to every last piece of it. Washington gives up power at the end of the revolution. He's successfully carried through the Revolutionary War aims. He's commander of the Revolutionary Forces, and he gives up his command. And then, of course, he's president, and after two terms, he gives up his command. What is he doing? He's an ambitious person, but he's recognizing that the most important currency he has for power is his respected status as a disinterested statesman. That's really what his power is. And how does he further that power? By showing that he doesn't crave power. So he was self-aware. Very self-aware of this, and very sophisticated in understanding this. And I think there are many other leaders who recognize that. You can look to, in some ways, the story of many of our presidents who, even before there is a two-term limit in the Constitution, leave after two terms. They do that because they recognize that their power is the power of being a statesman, not of being a president. I still wonder what kind of man it takes, what kind of human being it takes to do that. Because I've been studying Vladimir Putin quite a bit. Right. And he's still, I believe, he still has popular support, that that's not fully manipulated. Because I know a lot of people in Russia, and actually almost the entirety of my family in Russia, are big supporters of Putin. And everybody I talk to, sort of that's not just like on social media. Right. Like the people that live in Russia seem to support him. It feels like this will be, in a George Washington way, now will be the time that Putin, just like Yeltsin, could relinquish power. And thereby, in the eyes of Russians, become, in like the long arc of history, be viewed as a great leader. You look at the economic growth of Russia, you look at the rescue from the collapse of the Soviet Union and Russia finding its footing, and then relinquishing power in a way that perhaps if Russia succeeds, forms a truly democratic state. This will be how Putin can become one of the great leaders in Russian history, at least in the context of the 21st century. I think there are two reasons why this is really hard, for Putin and for others. One is the trappings of power are very seductive, as you said before, they're corrupting. This is a real problem, right? If it's in the business context, you don't wanna give up that private jet. If it's in Putin's context, it's billions of dollars every year that he's able to take for himself or give to his friends. It's not that he'll be poor if he leaves, he'll still be rich, and he has billions of dollars stored away, but he won't be able to get the new billions. And so that's part of it, the trappings of power are a big deal. And then second, in Putin's case in particular, he has to be worried about what happens next. Will he be tried? Will someone try to come and arrest him? Will someone try to come and assassinate him? Washington recognized that leaving early limited the corruption and limited the enemies that you made. And so it was a strategic choice. Putin is at this point bringing power too long. And this comes back to your core insight. It's a cliche, but it's true. Power corrupts, no one should have power for too long. This was one of the best insights the founders of the United States had, that power was to be held for a short time as a fiduciary responsibility, not as something you owned, right? This is the problem with monarchy, with aristocracy, that you own power, right? We don't own power. We're holding it in trust. Yeah, there's some probably like very specific psychological study of how many years it takes for you to forget that you can't own power. That's right. There's, you know, that's could be a much more rigorous discussion about the length of terms that are appropriate. But really there's an amount like Stalin had power for 30 years, like Putin is pushing those that many years already. There's a certain point where you forget the person you were before you took the power. That's right. You forget to be humble in the face of this responsibility. And then there's no going back. That's right. That's how dictators are born. That's how the evil, like authoritarians become evil or let's not use the word evil, but counterproductive destructive to the ideal that they initially probably came to office with. That's right. That's right. One of the core historical insights is people should move jobs. And this applies for CEOs probably. Absolutely. Absolutely, they can go become CEO somewhere else, but don't stay CEO one place too long. It's a problem with startups, right? The founder, you can have a brilliant founder and that founder doesn't wanna let go. Yeah. Right, it's the same issue. At the same time, I mean, this is where Elon Musk and a few others like Larry Page and Sergey Brin that stayed for quite a long time and they actually were the beacon. They on their shoulders carried the dream of the company. Yeah. Where everybody else doubted. So, but that seems to be the exception. Right. Versus the rule. Well, and even Sergey, for example, right? Has stepped back, right? He plays less of a day-to-day role and is not running Google in the way he did. But the interesting thing is he stepped back in a quite tragic way from what I've seen, which is I think Google's mission, an initial mission of making the world's information accessible to everybody is one of the most beautiful missions of any company in the history of the world. I think it's what Google has done with a search engine and other efforts that are similar, like scanning a lot of books. Sure. It's just incredible. It's similar to Wikipedia. But what he said was that it's not the same company anymore. And I know maybe I'm reading too much into it because it's more maybe practically saying just the size of the company is much larger, the kind of leadership that's required. But at the same time, Sure. They changed the motto from, you know, don't be evil to it's becoming corporatized and all those kinds of things. And it's sad. There also are cycles, right? History is about cycles, right? There are cycles to life, there are cycles to organizations. It's sad. I mean, it's sad Steve Jobs leaving Apple by passing away, sad. You know, what the future of SpaceX and Tesla looks like without Elon Musk, it's quite sad. It's very possible that those companies become something very different. They become something much more, you know, like corporate and stale. Yeah, so maybe most of the progress is made through cycles. Maybe a new Elon Musk comes along, all those kinds of things. But it does seem that the American system of government has built into it the cycling. Yes. That makes it effective and it makes it last very long. It lasts a very long time, right? It continues to excel and lead the world. Sure, sure. And let's hope it continues to. No, I mean, we're into, you know, a third century and democracies on this scale rarely last that long. So that's a point of pride, but it also means we need to be attentive to keep our house in order because it's not inevitable that this experiment continues. No, it's important to meditate on that actually. You've mentioned that FDR, Franklin D. Roosevelt is one of the great leaders in American history. Why is that? Franklin Roosevelt had the power of empathy. No leader that I've ever studied or been around or spent any time reading about was able to connect with people who were so different from himself as Franklin Roosevelt. He came from the most elite family. He never had to work for a paycheck in his life. When he was president, he was still collecting an allowance from his mom. I mean, you couldn't be more elite than Franklin Roosevelt, but he authentically connected. This was not, you know, propaganda. He was able to feel the pain and understand the lives of some of the most destitute Americans in other parts of the country. That's interesting. So through one of the hardest economic periods of American history, he was able to feel the pain. He was able to, the number of immigrants I read oral histories from or who have written themselves, Saul Bellow was one example, the great novelist who talked about how as immigrants to the US, Saul Bellow was a Russian Jewish immigrant. He said, growing up in Chicago, politicians were all trying to steal from us. I didn't think any of them cared until I heard FDR. And I knew he spoke to me. And I think part of it was FDR really tried to understand people. That's the first thing, he was humble enough to try to do that. But second, he had a talent for that. And it's hard to know exactly what it was, but he had a talent for putting himself, imagining himself in someone else's shoes. What stands out to you as important, I mean, so he went through the Great Depression. So the New Deal, which some people criticize, some people see, I mean, it's funny to look at some of these policies and their long ripple effects. But at the time, it's some of the most innovative policies in the history of America. You could say they're ultimately not good for America, but they're nevertheless, hold within them very rich and important lessons. But the New Deal, obviously World War II, that entire process, is there something that stands out to you as a particularly great moment that made FDR? Yes, I think what FDR does from his first 100 days in office forward, and this begins with his fireside chats, is he helps Americans to see that they're all in it together. And that's by creating hope and creating a sense of common suffering and common mission. It's not offering simple solutions. One of the lessons from FDR is, if you wanna bring people together, don't offer a simple solution. Because as soon as I offer a simple solution, I have people for it and against it. Don't do that, explain the problem, frame the problem, and then give people a mission. So Roosevelt's first radio address in March of 1933, the banking system is collapsing. And we can't imagine it, right? Banks were closing and you couldn't get your money out, your life savings would be lost, right? We can't imagine that happening in our world today. He comes on the radio, he takes five minutes to explain how banking works. Most people didn't understand how banking worked, right? They don't actually hold your money in a vault. They lend it out to someone else. And then he explains why if you go and take your money out of the bank and put it in your mattress, you're making it worse for yourself. He explains this. And then he says, I don't have a solution, but here's what I'm gonna do. I'm gonna send in government officers to examine the banks and show you the books on the banks. And I want you to help me by going and putting your money back in the banks. We're all gonna do this together. No simple solution, no ideological statement, but a sense of common mission. Let's go out and do this together. When you read, as I have, so many of these oral histories and memoirs for people who lived through that period, many of them disagreed with some of his policies. Many of them thought he was too close to Jews and they didn't like the fact he had a woman in his cabinet and all that, but they felt he cared and they felt they were part of some common mission. And when they talk about their experience fighting in World War II, whether in Europe or Asia, it was that that prepared them. They knew what it meant to be an American when they were over there. So that to me is a model of leadership. And I think that's as possible today as it's ever been. So you think it's possible. Like I was going to ask this again, it may be a very shallow view, but it feels like this country is more divided than it has been in recent history. Perhaps the social media and all those kinds of things are merely revealing the division as opposed to creating the division. But is it possible to have a leader that unites in the same way that FDR did without, well, we're living through a pandemic. This is already- Yes. So like I was going to say without suffering, but this is economic suffering. A huge number of people have lost their job. So is it possible to have, is there one a hunger? Is there a possibility to have an FDR style leader who unites? Yes, I think that is what President Biden is trying. I'm not saying he'll succeed, but I think that's what he's trying to do. The way you do this is you do not allow yourself to be captured by your opponents in Congress or somewhere else. FDR had a lot of opponents in Congress. He had a lot of opponents in politics, governors and others who didn't like him. Herbert Hoover was still around. And still accusing FDR of being a conspiratist and all these other things. So you don't allow yourself to be captured by the leaders of the other side. You go over their heads to the people. And so today, the way to do this is to explain to people and empathize with the suffering and dislocation and difficulties they're dealing with and show that you're trying to help them. Not an easy solution, not a simple statement, but here are some things we can all do together. That's why I think infrastructure makes a lot of sense. It's what FDR invested into. FDR built Hoover Dam. Hoover Dam turned the lights on for young Lyndon Johnson who grew up outside of Austin. FDR was the one who invested in road construction that was then continued by Dwight Eisenhower, by a Republican with the interstate highway system. FDR invested through the WPA in building thousands of schools in our country, planting trees. That's the kind of work that can bring people together. You don't have to be a Democrat or Republican to say, you know what, we'd be a lot better off in my community if we had better infrastructure today. I wanna be a part of that. Oh, well, maybe I can get a job doing that. Maybe my company can benefit from that. You bring people together and that way it becomes a common mission, even if we have different ideological positions. Yeah, it's funny. When I first heard Joe Biden, it's many years ago, I think he ran for president against Obama. That's correct. Before I heard him speak, I really liked him. But once I heard him speak, I started liking him less and less. And it speaks to something interesting, where it's hard to put into words why you connect with people. The empathy that you mentioned in FDR, you have these bad, pardon the French, motherfuckers like Teddy Roosevelt that connect with you. There's something just powerful. And with Joe Biden, I wanna really like him. And there's something not quite there where it feels like he doesn't quite know my pain, even though he, on paper, is exactly, he knows the pain of the people and there's something not connecting. And it's hard to explain. It's hard to put into words. And it makes me not, as an engineer and scientist, it makes me not feel good about presidencies because it makes me feel like it's more art than science. It is an art. And I think it's exactly an art for the reasons you laid out. It's aesthetic. It's about feeling. It's about emotion. All the things that we can't engineer. We've tried for centuries to engineer emotion. We're never gonna do it. Don't try it. I'm a parent of teenagers. Don't even try to explain emotion. But you hit on the key point and the key challenge for Biden. He's gotta find the right words. It's not finding the words to bullshit people. It's finding the words to help express. We've all felt empowered and felt good. When someone uses words that put into words what we're feeling. Yeah. That's what he needs. That's the job of a leader. And there's certain words, I haven't heard many politicians use those words, but there's certain words that make you forget that you're for immigration or against immigration. Make you forget whether you're for wars and against wars. Make you forget about the bickering and somehow inspire you, elevate you to believe in the greatness that this country could be. Yes. In that same way, the reason I moved to Austin, it's funny to say, I just heard words from people, from friends, where they're excited by the possibility of the future here. I wasn't thinking what's the right thing to do? What's the strategic, because I wanna launch a business. There's a lot of arguments with San Francisco or maybe staying in Boston in my case. But there's this excitement that was beyond reason. That was emotional. Yes, yes. And that's what it seems like. That's what builds, that's what great leaders do, but that's what builds countries. That's what build great businesses. That's right. And it's what people say about Austin, for example, all the time. A talented people who come here like yourself. And here's the interesting thing. No one person creates that. The words emerge. And part of what FDR understood is you've got to find the words out there and use them. You don't have to be the creator of them. Just as the great painter doesn't invent the painting, they're taking things from others. As a small aside, is there something you could say about FDR and Hitler? I constantly try to think, can this person, can this moment in history have been circumvented, prevented? Can Hitler have been stopped? Can some of the atrocities from my own family that my grandparents had to live through the starvation in the Soviet Union, so the thing that people don't often talk about is the atrocities committed by Stalin and his own people. It feels like here's this great leader, FDR, that had the chance to have an impact on the world that he already probably had a great positive impact, but had a chance to stop maybe World War II or stop some of the evils. When you look at how weak Hitler was from much of the 30s relative to militarily, relative to everything else, how many people could have done a lot to stop him? And FDR in particular didn't. He tried to play, not pacify, but basically do diplomacy and let Germany do Germany, let Europe do Europe and focus on America. Is there something you would, would you hold his feet to the fire on this, or is it very difficult from the perspective of FDR to have known what was coming? I think FDR had a sense of what was coming, not quite the enormity of what Hitler was doing and not quite the enormity of what the Holocaust became. I also lost relatives in the Holocaust. And part of that was beyond the imagination of human beings. But it's clear in his papers that as early as 1934, people he respected, who he knew well, told him that Hitler was very dangerous. They also thought Hitler was crazy, that he was a lunatic. Hamilton Fish Armstrong, who was a friend of Roosevelt's, who was actually the Council on Foreign Relations in New York had a meeting with Hitler in 1934. I remember reading the account of this. And he basically said to FDR, this man is gonna cause a war. He's gonna cause a lot of damage. Again, they didn't know quite the scale. So they saw this coming. They saw this coming. FDR had two problems. First, he had an American public that was deeply isolationist. The opposite of the problem in a sense that we were talking about before. If we're an over-militarized society, now we were a deeply isolationist society. In the 1930s, the depression reinforced that. FDR actually had to break the law in the late 30s to support the allies. So it was very hard to move the country in that direction, especially when he had this program at home, the New Deal, that he didn't wanna jeopardize by alienating an isolationist public. That was the reality. We talked about political manipulation. He had to be conscious of that. He had to know his audience. And second, there were no allies willing to invest in this either. The British were as committed to appeasement as you know. You're obviously very knowledgeable about this. The French were as well. It was very hard. The Russian government, the Soviet government, was cooperating to remilitarize Germany. So there weren't a lot of allies out there either. I think if there's a criticism to be made of FDR, it's that once we're in the war, he didn't do enough to stop, in particular, the killing of Jews. And there are a number of historians, myself included, who have written about this, and it's an endless debate. What should he have done? There's no doubt by 1944, the United States had air superiority and could have bombed the rail lines to Auschwitz and other camps. That would have saved as many as a million Jews. That's a lot of people who could have been saved. Why didn't FDR insist on that? In part, because he wanted to use every resource possible to win the war. He did not want to be accused of fighting the war for Jews. But I think it's also fair to say that he probably cared less about Jews and East Europeans than he did about others, those of his own Dutch ancestry and from Western Europe. And so, even there, race comes in. There's also the explanation for the internment of Japanese in the United States, which is a horrible war crime committed by this heroic president. 120,000 Japanese American citizens lost their freedom unnecessarily. So he had his limitations, and I think he could have done more during the war to save many more lives, and I wish he had. And there's something to be said about empathy that you spoke, that FDR had empathy. But us, for example, now there's many people who describe the atrocities happening in China. And there's a bunch of places across the world where there's atrocities happening now, and we care. We do not uniformly apply how much we care for the suffering of others. That's correct. Depending on the group. That's correct. And in some sense, the role of the president is to rise above that natural human inclination to protect, to do the us versus them, to protect the inner circle, and to empathize with the suffering of those that are not like you. That's correct. I agree with that. Yeah. Speaking of war, you wrote a book on Henry Kissinger. It's not a great transition, but it made sense in my head. Who was Henry Kissinger as a man and as a historical figure? Henry Kissinger to me is one of the most fascinating figures in history because he comes to the United States as a German Jewish immigrant at age 15, speaking no English. And within a few years, he's a major figure influencing US foreign policy at the height of US power. But while he's doing that, he's never elected to office, and he's constantly reviled by people, including people who are anti-Semitic because he's Jewish. But at the same time also, his exoticism makes him more attractive to people. So someone like Nelson Rockefeller wants Kissinger around, he's one of Kissinger's first patrons, because he wants a really smart Jew. And Kissinger's gonna be that smart Jew. I call Kissinger a policy Jew. There were these court Jews in the 16th and 17th and 18th centuries in Europe. Every king wanted the Jew to manage his banking. And in a sense, in the United States, in the second half of the 20th century, many presidents want a Jew to manage their international affairs. And what does that really mean? It's not just about being Jewish. It's the internationalism. It's the cosmopolitanism. And that's one of the things I was fascinated with with Kissinger. Someone like Kissinger is unthinkable as a powerful figure in the United States 30 or 40 years earlier, because the United States is run by WASP. It's run by white elites who come from a certain background. Kissinger represents a moment when American society opens up, not to everyone, but opens up to these cosmopolitan figures who have language skills, historical knowledge, networks that can be used for the US government when after World War II, we have to rebuild Europe, when we have to negotiate with the Soviet Union, when we need the kinds of knowledge we didn't have before. And Harvard, where he gets his education late, he started at City College, actually, but Harvard, where he gets his education late, is at the center of what's happening at all these major universities, at Harvard, at Yale, at Stanford, at the University of Texas, everywhere, where they're growing in their international affairs, bringing in the kinds of people who never would be at the university before, training them, and then enlisting them in Cold War activities. And so Kissinger is a representative of that phenomenon. I became interested in him because I think he's a bellwether. He shows how power has changed in the United States. So he enters this whole world of politics, what, post-World War II, in the 50s? Yes, so he actually, in the 40s, even, it's an extraordinary story. He comes to the United States in 1938, just before Kristallnacht, his family leaves. They, he actually grew up right outside of Nuremberg. They leave right before Kristallnacht in fall of 38, come to New York. He originally works in a brush factory, cleaning brushes, goes to a public high school. And in 1942, just after Pearl Harbor, he joins the military. And he's very quickly in the military, first of all, given citizenship, which he didn't have before. He's sent for the first time outside of a kosher home. He had been in a kosher home his entire life. He's sent to South Carolina to eat ham for Uncle Sam. And then he is, and this is extraordinary, at the age of 20, barely speaking English, he is sent back to Germany with the US Army in an elite counterintelligence role. Why? Because they need German speakers. He came when he was 15, so he actually understands the society. They need people who have that cultural knowledge. And because he's Jewish, they can trust that he'll be anti-Nazi. And there's a whole group of these figures. He's one of many. And so he's in an elite circle. He's discriminated against in New York. When he goes to Harvard after that, he can only live in a Jewish-only dorm. But at the same time, he's in an elite policy role in counterintelligence. He forms a network there that stays with him the rest of his career. There's a gentleman named Fritz Kramer who becomes a sponsor of his in the emerging Pentagon Defense Department world. And as early as the early 1950s, he's sent then to Korea to comment on affairs in Korea. He becomes both an intellectual, recognized for his connections, but also someone who policymakers wanna talk about. His book on nuclear weapons, when it's written, is given to President Eisenhower to read because they say this is someone writing interesting things. You should read what he says. There's a certain aspect to him that's kind of like Forrest Gump. He seems to continuously be the right person at the right time in the right place. That's right. Somehow finding him in this, I don't wanna, you know, you can only get lucky so many times because he continues to get lucky in terms of being at the right place in history for many decades, until today. Yeah, well, he has a knack for that. I spend a lot of time talking with him. And what comes through very quickly is that he has an eye for power. It's, I think, unhealthy. He's obsessed with power. Can you explain, like, an observer of power? Yes. Or being, does he want power himself? Yes, both of those things. Both of those. And I think, I explain this in the book, he doesn't agree with what I'm gonna say now, but I think I'm right and I think he's right. It's very hard to analyze yourself, right? Yeah. I think he develops an obsession with gaining power because he sees what happens when you have no power. He experiences the trauma. His father is a very respected gymnasium lehrer in Germany. Even though he's Jewish, he's actually the teacher of German classics to the German kids. Great. And he's forced to flee and he becomes nothing. His father never really makes a way for himself in the United States. He becomes a postal delivery person, which is nothing wrong with that, but for someone who's a respected teacher in Germany and gymnasium lehrer, like professors there, right? To then be in this position. His mother has to open a catering business when they come to New York. It's a typical immigrant story, but he sees the trauma. His grandparents are killed by the Nazis. So he sees the trauma and he realizes how perilous it is to be without power. And you're saying he does not want to acknowledge the effect of that. It's hard. It's hard. I mean, most of us, if we've had trauma, it's believable that it's traumatic because you don't talk about it. I have a friend who interviews combat veterans and he says, as soon as someone freely wants to tell me about their combat trauma, I suspect that they're not telling me the truth. If it's traumatic, it's hard to talk about. Yeah, sometimes I wonder how much for my own life, everything that I've ever done is just the result of the complicated relationship with my father. I tend to, I had a really difficult time. I did a podcast conversation with him. I saw it actually. It's great. I regret everything. I could never do that with my folks. But I remember as I was doing it and for months after I regretted doing it, I just kept regretting it. And the fact that I was regretting it spoke to the fact that I'm running away from some truths that are back there somewhere. And that's perhaps what Kissinger is as well. But is there, I mean, he's been a part of so many interesting moments of American history, of world history from the Cold War, of Vietnam War until today. What stands out to you as a particularly important moment in his career that made who he is? Well, I think what made his career in many ways was his experience in the 1950s building a network, a network of people across the world who were rising leaders from unique positions. He ran what he called the International Seminar at Harvard, which was actually a summer school class that no one at Harvard cared about. But he invited all of these rising intellectuals and thinkers from around the world. And he built a network there that he used forevermore. So that's what really, I think, boosts him. The most important moments in terms of making his reputation and making his career are two sets of activities. One is the opening to China. And his ability to, first of all, take control of US policy without the authority to do that and direct US policy and then build a relationship with Mao Zedong and Zhou Enlai that was unthinkable just four or five years earlier. Of course, President Nixon is a big part of that as well, but Kissinger is the mover and shaker on that. And it's a lot of manipulation, but it's also a vision. Now, this is in the moment of American history where there's a very powerful anti-communism. Correct. So communism is seen as much more, even though than today, as the enemy. Correct. And China in particular, they were one of our key enemies in Vietnam. And in Korea, American forces were fighting Chinese forces directly. Chinese forces come over the border, thousands of Americans die at the hand of Chinese forces. So for the long time, the United States had no relationship with communist China. He opens that relationship. And at the same time, he also creates a whole new dynamic in the Middle East. After the 1973 war, the so-called Yom Kippur War, he steps in and becomes the leading negotiator between the Israelis, the Egyptians, and other major actors in the region. And it makes the United States the most powerful actor in the Middle East, the Soviet Union far less powerful, which is great for the United States in the 70s and 80s. It gets us though into the problems we of course have thereafter. So that speaks to the very pragmatic approach that he's taken, the realistic approach versus the idealistic approach, the termed realpolitik. What is this thing? What is this approach to world politics? So realpolitik for Kissinger is really focusing on the power centers in the world and trying as best you can to manipulate those power centers to serve the interests of your own country. And so that's why he's a multilateralist. He's not a unilateralist. He believes the United States should put itself at the center of negotiations between other powerful countries. But that's also why he pays very little attention to countries that are less powerful. And this is why he's often criticized by human rights activists. For him, parts of Africa and Latin America, which you and I would consider important places are unimportant because they don't have power. They can't project their power. They don't produce a lot of economic wealth. And so they matter less. Realpolitik views the world in a hierarchy of power. How does realpolitik realize itself in the world? What does that really mean? Like how do you push forward the interests of your own country? You said there's power centers, but it is a big, bold move to negotiate, to work with a communist nation, with your enemies that are powerful. What is the, sort of, if you can further elaborate the philosophy behind it. Sure, so there are two key elements that then end up producing all kinds of tactics. But the two strategic elements of Kissinger's way of thinking about realpolitik, which are classical ways, going back to Thucydides and the Greeks, are to say, first of all, you figure out who your allies are and you build webs of connection so that your allies help you to acquire what you want to acquire. This is why, according to Herodotus, the Greeks beat the Persians. The Persians are bigger, but the Greeks, the Spartans, the Athenians, and others are able to work together and leverage their resources. So it's about leveraging your resources. For Kissinger, this makes Western Europe crucially important. It makes Japan crucially important. It makes Israel and Egypt crucially important, right, in building these webs. You build your surrogates, you build your brother states. In other parts of the world, you build tight connections and you work together to control the resources that you want. The second element of the strategy is not to go to war with your adversary, but to do all you can to limit the power of your adversary. Some of that is containment, preventing the Soviet Union from expanding. That was the key element of American Cold War policy. But sometimes it's actually negotiation. That's what detente was about for Kissinger. He spends a lot of time, more time than any other American foreign policy maker, negotiating with Soviet leaders, as well as Chinese leaders. What does he wanna do? He wants to limit the nuclear arms race. The United States is ahead. We don't want the Soviet Union to get ahead of us. We negotiate to limit their abilities, right? We play to our strengths. So it's a combination of keeping your adversary down and building tight webs. Within that context, military force is used, but you're not using war for the sake of war. You're using warfare to further your access to the resources, economic, political, geographic that you want. And that builds relationships. And then the second thing, to limit the powers of those you're against. Exactly. So is there any sort of insights into how he preferred to build relationships? Are we talking about, like, again, it's the one-on-one? Is it through policy, or is it through, like, phone conversations? Is there any cool kind of insights that you could speak to? Yeah, Kissinger is the ultimate kiss-up. He is, some used to make fun of him. In fact, even the filmmaker from Dr. Strangelove, whose name I'm forgetting, right, Stanley Kubrick, called him kiss-up at that time, right? He had a wonderful way of figuring out what it is you wanted, back to that discussion we had before, and trying to show how he could give you more of what you wanted as a leader. It was very personalistic, very personalistic. And he spends a lot of time, for example, kissing up to Leonid Brezhnev, kissing up to Mao. He tells Mao, you're the greatest leader in the history of the 20th century. People will look back on you as the great leader. Some of this sounds like BS, but it's serious, right? He's feeding the egos of those around him. Second, he is willing to get things done for you. He's effective. You want him around you because of his efficacy. So Richard Nixon is always suspicious that Henry Kissinger is getting more of the limelight. He hates that Kissinger gets the Nobel Peace Prize, and he doesn't, but he needs him, because Kissinger's the guy who gets things done. So he performs, he builds a relationship, in almost, I say this in the book, in almost a gangster way. He didn't like that. He criticized that part of the book, but again, I still think the evidence is there. You need something to be done, boss? I'll do it. And don't forget that I'm doing this for you. And you get mutual dependency in a Hegelian way, right? Yeah. And so he builds this personal dependency through ego and through performance. And then he's so skillful at making decisions for people who are more powerful, because he's never elected to office. He always needs powerful people to let him do things. But he convinces you it's your decision when it's really his. To read his memos are beautiful. He's actually very skilled at writing things in a way that looks like he's giving you options as president, but in fact, there's only one option there. Is he, speaking to the gangster, to the loyalty, is he ever, like the sense I got from Nixon is he would, Nixon would backstab you if he needed to. One of the things that I admire about gangsters is they don't backstab. Those in the inner circle, like loyalty above all else. I mean, at least that's the sense I've gotten from the stories of the past, at least, is where would you put Kissinger on that? Is he loyalty above all else? Or is it, or are humans, like the Steve Jobs thing, is like, as long as you're useful, you're useful. But then once you, long, the moment you're no longer useful is when you're knocked off the chessboard. It's the latter with him. He's backstabbing quite a lot. And he's self-serving. But he also makes himself so useful that even though Nixon knows he's doing that, Nixon still needs him. Yeah. By the way, on that point, so having spoken with Kissinger, what's your relationship like with him as somebody who is, in an objective way, writing his story? It was very difficult because he's very good at manipulating people, and we had about 12 or 13 interviews, usually informal, over lunch. And this was many years ago. This is probably now more than 10 years ago. Did you find yourself being sweet-talked to where you go back home later and look in the mirror and it's like, wait, what just happened? He can be enormously charming and enormously obnoxious at the same time. So I would have these very mixed emotions because he gives no ground. He's unwilling to, and I think this is a weakness, he's unwilling to admit mistake. Others make mistakes, but he doesn't. And he certainly won't take on any of the big criticisms that are pushed. I understand why. I mean, when you've worked as hard for what he has as he has, you're defensive about it. But he is very defensive, and he's very fragile about it. He does not like criticisms at all. He used to, he hasn't done this in a while, but he used to call me up and yell at me on the phone, quite literally, when I would be quoted in the New York Times or somewhere, saying something that sounded critical of him. So for instance, there was one instance a number of years ago where a reporter came across some documents where Kissinger said negative things about Jews in Russia, typical things that a German Jew would say about East European Jews. And the New York Times asked me, is this accurate? And I said, yeah, the documents are accurate. I've seen them, they're accurate. He was so angry about that. So there's the fragility, but there's also the enormous charm and the enormous intelligence. The real challenge with him, though, is he's very good at making his case. He'll convince you. And as a scholar, as an observer, you don't wanna hear a lawyer's case. You wanna actually interrogate the evidence and get to the truth. And so that was a real challenge with him. So speaking of his approach of realpolitik, if we just zoom out and look at human history, human civilization, what do you think works best in the way we progress forward? A realistic approach, do whatever it takes, control the centers of power, to play a game for the greater interests of the good guys, quote unquote. Or lead by a sort of idealism, which is like truly act in the best version of the ideas you represent, as opposed to kind of present one view and then do whatever it takes behind the scenes. Obviously, you need some of both, but I lean more to the idealistic side, and more so, actually, believe it or not, as I get into my 40s, as I do more historical work. Why do I say that? Because I think, and this is one of my criticisms of Kissinger, who I also have a lot of respect for, the realpolitik becomes self-defeating, because you're constantly running to keep power, but you forget why. And you often then use power, and I think Kissinger falls into this in some of his worst moments, not all of his moments, where the power is actually being used to undermine the things you care about. It's sort of the example of being a parent, and you're doing all these things to take your kid to violin, basketball, all these things, and you realize you're actually killing your kid and making your kid very unhappy. And the whole reason you were doing it was to improve the person's life. And so you have to remember why it is, what Hans Morgenthau calls this is your purpose. Your purpose has to drive you. Now, your purpose doesn't have to be airy-fairy idealism. So I believe deeply in democracy as an ideal. I don't think it's gonna ever look like Athenian democracy, but that should drive our policy. But we still have to be realistic and recognize we're not gonna build that democracy in Afghanistan tomorrow. I mean, does it ultimately just boil down again to the corrupting nature of power, that nobody can hold power for very long before you start acting in the interest of power, as opposed to in the interest of your ideals? It's impossible to be somebody like Kissinger, who is essentially in power for many, many decades, and still remember what are the initial ideals that you strove to achieve. Yes, I think that's exactly right. There's a moment in the book I quote about him. Comes from one of our interviews. I asked him, what were the guiding ideals for your policies? And he said, I'm not prepared to share that. And I don't think it's because he doesn't know what he thinks he was trying to do. He realizes his use of power departed quite a lot from. So it would sound, if he made them explicit, it would sound hypocritical. Correct. Well, on that, let me ask about war. America often presents itself to its own people, but just the leaders, when they look in the mirror, I get a sense that we think of ourselves as the good guys. And especially this begins sometimes to look hypocritical when you're waging war. What's a good, is there a good way to know when you've lost all sense of what it is to be good? Another way to ask that, is there, in military policy, in conducting war, is there a good way to know what is a just war and what is a war crime? I mean, in some circles, Kissinger's accused of contributing, being a war criminal. Yes, and I argue in the book, he's not a war criminal, but that doesn't mean that he didn't misuse military power. I think a just war, a just war, as Michael Walzer and others write about it, a just war is a war where both the purpose is just and you are using the means to get to that purpose that kill as few people as necessary. That doesn't mean they won't be killing, but as few as necessary, proportionality, right? Your means should be proportional to your ends. And that's often lost sight of because the drive to get to the end often self-justifies means that go well beyond that. And so that's how we get into torture in the war on terror, right? Is there some kind of lesson for the future? Yes. That you can take away from that? Yes, I think the first set of lessons that I've shared as a historian with military decision makers is, first of all, always remember why you're there, what your purpose is, and always ask yourself if the means you're using are actually proportional. Ask that question. Just because you have these means that you can use, just because you have these tools, doesn't mean they're the right tools to use. And here's the question that follows from that. And it's a hard question to ask because the answer is one we often don't like to hear. Are the things I'm doing in war actually doing more harm or more good to the reason I went into war? We came to a point in the war on terror where what we were doing was actually creating more terrorists. And that's when you have to stop. Well, some of that is in the data, but some of it, there's a leap of faith. So from a parenting perspective, let me speak as a person with no kids and a single guy. Let me be the expert in the room on parenting. No, it does seem that it's a very difficult thing to do to, even though you know that your kid was making a mistake, to let them make a mistake, to give them the freedom to make the mistake. Sure. I don't know what to do, but I mean, that's a very kind of lighthearted way of phrasing the following, which is when you look at some of the places in the world, like Afghanistan, which is not doing well, to move out knowing that there's going to be a lot of suffering, economic suffering, injustices, terrorist organizations growing, that committing crimes on its own people and potentially committing crimes against allies, violence against allies, violence against the United States. How do you know what to do in that case? Well, again, it's an art, not a science, which is what makes it hard for an engineer to think about. This is what makes it endlessly fascinating for me. And I think the real intellectual work is at the level of the art, right? And I think probably engineering at its highest level becomes an art as well, right? So policymaking, you never know. But I will say this, I'll say you have to ask yourself and look in the mirror and say, is all the effort I'm putting in actually making this better? And in Afghanistan, you look at the 20 years and two plus trillion dollars that the US has put in. And the fact that, as you said correctly, it's not doing well right now, after 20 years of that investment, I might like a company that I invest in, but after 20 years of my throwing money in that company, it's time to get out. Well, in some sense, getting out now, that's kind of obvious. I'm more interested in how we figure out in the future how to get out earlier. Then, I mean, at this point, we stayed too long and it's obvious, the data, the investment, nothing is working. The very little data points to us staying there. I'm more interested in being in a relationship. Let me take it back to a safer place again. Being in a relationship and getting out of that relationship while things are still good, but you have a sense that it's not going to end up in a good place. That's the difficult thing. You have to ask yourself, whether it's a relationship or you're talking about policymaking in a place like Afghanistan, are the things I'm doing showing me evidence, real evidence that they're making things better or making things worse? That's a hard question to ask. Be honest with yourself. You have to be very honest. And in a policymaking context, we have to actually do the same thing we do in a relationship context. What do we do in a relationship context? We ask other friends who are observing. We ask for other observers. This is actually just a scientific method element, actually, that we can't, the Heisenberg principle, I can't see it because I'm too close to it. I'm changing it by my looking at it. I need others to tell me in a policymaking context, this is why you need to hear from other people, not just the generals. Because here's the thing about the generals. They generally are patriotic, hardworking people, but they're too close. They're not lying. They're too close. They always think they can do better. Yeah. How do you think about the Cold War now, from the beginning to end, and maybe also with an eye towards the current potential cyber conflict, cyber war with China and with Russia, if we look sort of other kind of cold wars potentially emerging in the 21st century. When you look back at the Cold War of the 20th century, how do you see it and what lessons do we draw from it? It's a wonderful question because I teach this to undergraduates and it's really interesting to see how undergraduates now, almost all of whom were born after 9-11. Yeah. So the Cold War is ancient history to them. In fact, the Cold War to them is as far removed as the 1950s were to me. I mean, it's unbelievable. It's almost like World War II for my generation and Cold War for them. It's so far removed. The collapse of the Soviet Union doesn't mean anything to them. So how do you describe the Cold War to them? How do you describe the Soviet Union to them? First of all, I have to explain to them why people were so fearful of communism. Anti-communism is very hard for them to understand. The fact that in the 1950s, Americans believed that communists were going to infiltrate our society and many other societies and that after Fidel Castro comes to power in 1959, that we're going to see communist regimes all across Latin America. That fear of communism married to nuclear power and then even the fear that maybe economically they would outpace us because they would create this sort of army of Khrushchevian builders of things and what is Khrushchev said, right? Say, we're gonna catch Britain in five years and then the United States after that, right? So to explain that sense of fear to them that they don't have of those others, that's really important. The Cold War was fundamentally about the United States defending a capitalist world order against a serious challenger from communism, an alternative way of organizing everything, private property, economic activity, enterprise, life, everything organized in a totally different way. It was a struggle between two systems. So your sense is, and sorry to interrupt, but your sense is that the conflict of the Cold War was between two ideologies and not just two big countries with nuclear weapons. I think it was about two different ways of life or two different promoted ways of life. The Soviet Union never actually lived communism but I think my reading of Stalin is he really tried to go there. Khrushchev really believed, Gorbachev thought he was going to reform the Soviet Union so you would go back to a kind of Bukhar and Lenin communism, right? So I do think that mattered. I do think that mattered enormously. And for the United States point of view, the view was that communism and fascism were these totalitarian threats to liberal democracy and capitalism, which went hand in hand. So I do think that's what the struggle was about. And in a certain way, liberal capitalism proved to be the more enduring system and the United States played a key role in that. That's the reality of the Cold War but I think it means different things now to my students and others. They focus very much on the expansion of American power and the challenges of managing. They're looking at it from the perspective of not will we survive but did we waste our resources on some elements of it? It doesn't mean they were against what America did but there is a question of the resources that went into the Cold War and the opportunity costs. And you see this when you look at the sort of healthcare systems that other countries build and you compare them to the United States, race issues also. So they look at the costs, which I think often happens after a project is done, you look back at that. Second, I think they're also more inclined to see the world as less bipolar, to see the role of China as more complicated. Post-colonial or anti-colonial movements, independent states in Africa and Latin America, that gets more attention. So one of the criticisms now is because you forget the lessons of 20th century history and the atrocities committed under communism that you may be a little bit more willing to accept some of those ideologies into the United States society. That this kind of, that forgetting that capitalistic forces are part of the reason why we have what we have today, there's a fear amongst some now that we would have, we would allow basically communism to take hold in America. I mean, Jordan and others speak to this kind of idea. I tend to not be so fearful of it. I think it's on the surface, it's not deep within. I do see the world as very complicated, as there needing to be a role of having support for each other on certain political levels, economic levels, and then also supporting entrepreneurs. It's like that the kind of enforcing of outcomes that is fundamental to the communist system is not something we're actually close to. And some of that is just fear mongering for likes on Twitter kind of thing. If I could come in on that, because I agree with you 100%. I've spent a lot of time writing and looking at this and talking to people about this. There's no communism in the United States. There never has been, and there certainly isn't now. And I'll say this both from an academic point of view, but also from just spending a lot of time observing young people in the United States. Even those on the farthest left, take whoever you think is the farthest left. They don't even understand what communism is. They're not communist in any sense. Americans are raised in a vernacular and environment of private property ownership. And as you know better than anyone, if you believe in private property, you don't believe in communism. So what the sort of Bernie Sanders kind of socialist elements, that's very different, right? And I would say some of that, not all of that, some of that does hearken back to actually what won in the Cold War. There were many social democratic elements of what the United States did that led to our winning the Cold War. For example, the New Deal was investing government money in propping up business, in propping up labor unions. And during the Cold War, we spent more money than we had ever spent in our history on infrastructure, on schools, on providing social support, social security, our national pension system being one of them. So you could argue actually that social democracy is very compatible with capitalism. And I think that's the debate we're having today, how much social democracy. I'd also say that the capitalism we've experienced the last 20 years is different from the capitalism of the Cold War. During the Cold War, there was the presumption in the United States that you had to pay taxes to support our Cold War activities, that it was okay to make money, but the more money you made, the more taxes you had to pay. We had the highest marginal tax rates in our history during the Cold War. Now, the aversion to taxes, and of course no one ever likes paying taxes, but the notion that we can do things on deficit spending, that's a post-Cold War phenomenon. That's not a Cold War phenomenon. So, so much of the capitalism that we're talking about today is not the capitalism of the Cold War. And maybe, again, we can learn that and see how we can reform capitalism today and get rid of this false worry about communism in the United States. Yeah, you know, you make me actually realize something important. What we have to remember is the words we use on the surface about different policies, what you think is right and wrong, is actually different than the core thing that is in your blood, the core ideas that are there. I do see the United States as this, there's this fire that burns of individual freedoms, of property rights, these basic foundational ideas that everybody just kind of takes for granted. And I think if you hold onto them, if you're like raised in them, talking about ideas of social security, of universal basic income, of reallocation of resources is a fundamentally different kind of discussion than you had in the Soviet Union. I think the value of the individual is so core to the American system that you basically cannot possibly do the kind of atrocities that you saw in the Soviet Union. But of course, you never know, the slippery slope has a way of changing things. But I do believe the things you're born with is just so core to this country. It's part of the, I don't know what your thoughts are. We are in Texas, not necessarily, I don't necessarily wanna have a gun control type of conversation, but the reason I really like guns, it doesn't make any sense, but philosophically, it's such a declaration of individual rights that's so different than the conversations I hear with my Russian family and my Russian friends. That the gun, it's very possible that having guns is bad for society in the sense that it'll lead to more violence. But there's something about this discussion that proclaims the value of my freedom as an individual. I'm not being eloquent in it, but there's very few debates where whenever people are saying, should, would you have what level of gun control, all those kinds of things, what I hear is it's a fight for how much freedom, even if it's stupid freedom, should the individual have. I think that's what's articulated quite often. I think combining your two points, which are great points, I think there is something about American individualism which is deeply ingrained in our culture and our society. And it means that the kinds of bad things that happen are different, usually not as bad. But our individualism often covers up for vigilante activity and individual violence toward people that you wouldn't have in a more collective culture. So in the Soviet Union, it was at a much worse scale and it was done by government organizations. In the United States, it's individuals, the history of lynching in our country, for example. Sometimes it's individual police officers, sometimes it's others. Again, the vast majority of police officers are good people and don't do harm to people, but there are these examples and they are able to fester in our society because of our individualism. Now, gun ownership is about personal freedom, I think, for a lot of people. And there's no doubt that in our history, included in the Second Amendment, which can be interpreted in different ways, is the presumption that people should have the right to defend themselves, which is what I think you're getting at here. That you should not be completely dependent for your defense on an entity that might not be there for you. You should be able to defend yourself. And guns symbolize that. I think that's a fair point. But I think it's also a fair point to say that as with everything, defining what self-defense is is really important. So does self-defense mean I can have a bazooka? Does it mean I can have weapons that are designed for a military battlefield to mass kill people? That seems to me to be very different from saying I should have a handgun or some small arm to defend myself. That distinction alone would make a huge difference. Most of the mass shootings, at least, which are a smaller proportion of the larger gun deaths in the United States, which are larger than any other society, but at least the mass shootings, are usually perpetrated by people who have not self-defense weapons, but mass killing, mass killing weapons. And I think there's an important distinction there. The Constitution talks about a right to bear arms for a well-regulated militia. When the framers talked about arms, that did not mean the ability to kill as many people as you wanna kill. It meant the ability to defend yourself. So let's have that conversation. I think it would be useful as a society. Stop talking about guns or no guns. What is it that we as citizens need to feel we can defend ourselves? Yes. Yeah, I mean, guns have this complicated issue that it can cause harm to others. I tend to see sort of maybe in drug, like legalization of drugs, I tend to believe that we should have the freedom to do stupid things. Yeah. So long as we're not harming lots of other people. Yes, and then guns, of course, have the property that they can be used. It's not just, you know, a bazooka, I would argue, is pretty stupid to own for your own self-defense, but it has the very negative side effect of being potentially used to harm other people. And you have to consider that kind of stuff. By the way, as a side note to the listeners, there's been a bunch of people saying that Lex is way too libertarian for my taste. No, I actually am just struggling with ideas and sometimes put on different hats in these conversations. I think through different ideas, whether they're left, right, or libertarian. That's true for gun control, that's true for immigration, that's true for all of that. I think we should have discussions in the space of ideas versus in the space of bins. We put each other in labels and we put each other in- I agree 100%. And also change our minds all the time. Try out, say stupid stuff with the best of intention, trying our best to think through it. And then after saying it, think about it for a few days and then change your mind and grow in this way. Let me ask a ridiculous question. When you zoom out, when human civilization has destroyed itself and alien graduate students are studying it like three, four, five centuries from now, what do you think we'll remember about this period in history? The 20th century, the 21st century, this time we had a couple of wars, we had a charismatic black president in the United States, we had a couple of pandemics. What do you think will actually stand out in history? No doubt the rapid technological innovation of the last 20 to 30 years. How we created a whole virtual universe we didn't have before. And of course that's gonna go in directions you and I can't imagine 50 years from now. But this will be seen as that origin moment that when we went from playing below the rim to playing above the rim, to be all in person, to having a whole virtual world. And in a strange way, the pandemic was a provocation to move even further in that direction. And we're never going back. We're gonna restore some of the things we were doing before the pandemic, but we're never gonna go back to that world we were in before where every meeting you had to fly to that place to be in the room with the people. So this whole virtual world and the virtual personas and the avatars and all of that, I think that's going to be a big part of how people remember our time. Also the sort of biotechnology element of it, which the vaccines are part of. It's amazing how quickly, this is the great triumph, how quickly we've produced and distributed these vaccines. And of course there are problems with who's taking them, but the reality is, I mean, this is light speed compared to what it would have been like, not just in 1918, in 1980. Yeah, one of the, and sorry if I'm interrupting, but one of the disappointing things about this particular time is because vaccines, like a lot of things got politicized, used as little pawns in the game of politics, that we don't get the chance to step back fully at least and celebrate the brilliance of the human species. That's right. That this is, yes, there are scientists who use their authority improperly, that have an ego, that when they're within institutions are dishonest with the public because they don't trust the intelligence of the public, they are not authentic and transparent, all the same things you could say about humans in any positions of power anywhere. Okay, that doesn't mean science isn't incredible. And the vaccines, I mean, I don't often talk about it because it's so political and it's heartbreaking to, it's heartbreaking how all the good stuff is getting politicized. Yeah, that's right. And it shouldn't be, it'll seem less political. In the long arc of history. Yep, it'll be seen as an outstanding accomplishment and as a step toward whatever, maybe they're doing vaccines or something that replaces a vaccine in 10 seconds, at that point, right? It'll be seen as a step. Those will be some of the positives. I think one of the negatives they will point to will be our inability, at least at this moment, to manage our environment better, how we're destroying our living space and not doing enough, even though we have the capabilities to do more to preserve or at least allow a sustainable living space. I'm confident because I'm an optimist that we will get through this and we will be better at sustaining our environment in future decades. And so in terms of environmental policy, they'll see this moment as a dark age or the beginnings of a better age, maybe as a renaissance. Or maybe as the last time most people lived on Earth when a couple centuries afterwards, we're all dissipated throughout the solar system and the galaxy. Very possible. If the local resident, hometown resident, Mr. Elon Musk has anything to do with it. I do tend to think you're absolutely right with all this political bickering, we shouldn't forget that what this age will be remembered by is the incredible levels of innovation. I do think the biotech stuff worries me more than anything because it feels like there's a lot of weapons that could be yet to be developed in that space. But I tend to believe that, I'm excited by two avenues. One is artificial intelligence, the kind of systems we'll create in this digital space that you mentioned you were moving to. And then the other, of course, this could be the product of the Cold War, but I'm super excited by space exploration. Sure. It's the magic to humans, beings. And we're getting back to it. I mean, we were enthralled with it in the 50s and 60s when it was a Cold War competition. And then after the 70s, we sort of gave up on it. And thanks to Elon Musk and others, we're coming back to this issue. And I think there's so much to be gained from the power of exploration. Is there books or movies in your life long ago or recently that had big impact on you? Yes. If it's something you were. Yes. You know, my favorite novel, I always tell people this, I love reading novels. I'm a historian and I think the historian and the novelist are actually, and the technology innovator are all actually one in the same. We're all- Storytellers. Storytellers. And we're all in the imagination space. And I'm trying to imagine the world of the past to inform us in the present for the future. So one of my favorite novels that I read actually when I was in graduate school is Thomas Mann's Buddenbrooks. And it's the story of a family in Lübeck in Northern Germany, living through the 19th century and the rise and fall of family, cycles of life. Many things we've talked about in the last couple of hours. Cycles of life, challenges of adjusting to the world around you. And it's just a very moving reflection on the limits of human agency and how we all have to understand the circumstances we're in and adjust to them. And there's triumph and tragedy in that. It's a wonderful novel. It used to be a kind of canonical work. It's sort of fallen out now. It's a big, big novel, but I'm very moved by that. I'm very moved by Tolstoy's War and Peace. I assign that every year to my students. That's a big, big book. But what Tolstoy challenges is he challenges the notion that a Napoleon can rule the world. And we're all little Napoleons, right? We're all sort of thinking that we're gonna do that. And he reminds us how much is contingency, circumstance. It doesn't mean we don't have some control. You've spoke to me a little bit of Russian. Where does that come from? So your appreciation of Tolstoy, but also your ability to speak a bit of Russian. Where's that from? So I speak, in addition to English, I speak reasonably well, depending on how much vodka I've had. Russian, I speak French and German. I learned those for research purposes. I learned French, actually, when I was in high school, Russian when I was in college, German when I was in graduate school. Now I do have family on my mother's side that's of Russian Jewish extraction, but they were Yiddish speakers by the time I met them. By the time they had gone through Germany and come to the United States, or really gone through Poland and come to the United States, they were Yiddish speakers. So there's no one really in my family who speaks Russian, but I do feel a connection there, at least a long range personal connection. Is there something to be said about the language and your ability to imagine history? Sort of when you study these different countries, your ability to imagine what it was like to be a part of that culture, part of that time. Yes, language is crucial to understanding a culture. And even if you learn the language as I have, learning Russian and German and French, it's still not the same as also being a native speaker either, as you know. But I think language tells you a lot about mannerism, about assumptions. The very fact that English doesn't have a formal U, but Russian has a formal U, right? V versus T, right? German has a formal U, Z versus D, right? So the fact that English doesn't have a formal U tells you something about Americans, right? And that's just one example. The fact that Germans have such a wider vocabulary for certain scientific concepts than we have in English tells you something about the culture, right? Language is an artifact of the culture. The culture makes the language. It's fascinating to explore. I mean, even just exactly what you just said, V, T, which is, there's a fascinating transition. So I guess in English we just have U. Yeah. There's a fascinating transition that persists to this day is of formalism and politeness, where it's an initial kind of dance of interaction that's different methods of signaling respect, I guess. And language provides that, and in the English language, there's fewer tools to show that kind of respect, which has potentially positive or negative effects. It flattens the society where a teenager could talk to an older person and show a deference. But at the same time, it creates a certain kind of dynamic, a certain kind of society. And it's funny to think of just those few words can have a ripple effect through the whole culture. And we don't have a history in the United States of aristocracy. Yeah. These elements of language reflect aristocracy. The serf would never refer to the master, even if the master is younger, as Tuy. It's always Vuy, right? And Turgenev, it's always Vuy, right? I mean, and so it tells you something about the history. That's why, to your question, which was a great question, it's so crucial to try to penetrate the language. I'll also say something else, and this is a problem for many Americans who haven't learned a foreign language. We're very bad at teaching foreign languages. If you've never taught yourself a foreign language, you have closed yourself off to certain kinds of empathy because you have basically trained your brain to only look at the world one way. The very act of learning another language, I think, tells your brain that words and concepts don't translate one-to-one. This is the first thing you realize, right? We can say, you know, these two words mean the same thing from two languages. They never mean exactly. It's the same thing. Dostvedanya is really not goodbye, right? And there's something, you know, right now there's people talking about idea of lived experience. One of the ways to force yourself into this idea of lived experience is by learning another language. It's to understand that you can perceive the world in a totally different way, even though you're perceiving the same thing. And of course, the way to first learn Russian for those looking for tutorial lessons, for me, is just like as you said, you start by drinking lots of vodka. Yes, of course. It's very difficult to do otherwise. Is there advice you have for young people about career, about life, in making their way in the world? Yes. Two things I believe that I say to a lot of talented young people. First, I don't think you can predict what is gonna be well-renumerated 20 years from now. Don't pick a profession because you think, even though your parents might tell you or something, do this and you'll make money. You know, this is the scene in The Graduate where a guy tells Dustin Hoffman, go into plastics, money in plastics. We don't know. So many of my students now have parents who are telling them, bright students, go to the business school. That's what's gonna set you up to make money. If you're passionate about business, yes. But don't begin by thinking you know what's gonna be hot 20 years from now. You don't know what's gonna be hot from 20 years from now. What should you do? This is advice number one. Find what you're passionate about. Because if you're passionate about it, you will do good work in that area if you're talented. And usually passion and talent overlap. And you'll find a way to get people to pay you for it. I mean, you do it really well, people will wanna pay. That's where capitalism works. People will find it valuable, right? Whether it's violin playing, right? Or engineering or poetry, you will find. You might not become a billionaire. That involves other things. But you'll find a way to get people to pay you for it. And then the second thing is it's really important at the very beginning of your career, even before you're in your job, right? To start building your networks. But networks are not just people you're on Facebook with or Twitter with. I mean, that's fine. It's actually forming relationships. And some of that can be mediated in the digital world. But I mean real relationships. I like podcasts because I think they actually open up that space. I know a lot of people can listen to a podcast and find someone else who's listened to that podcast and have a conversation about a topic. It opens up that space. Build those relationships, not with people who you think will be powerful, but people you think are interesting because they'll do interesting things. And every successful person I know at some level had a key moment where they got where they are because of someone they knew for some other reason who had that connection. So use and spread your networks and make them as diverse as possible. Find people who are of a different party, have different interests, but are interesting to you. That's brilliant advice. Some of that on the passion side, I do find that as somebody who has a lot of passions, I find the second part to that is committing. Yes, that's true too. Which sucks because life is finite. And when you commit, you say, well, I'm never going to be good. Like when you choose one of your two passions, one of the two things you're interested in, you're basically saying, I'm letting go. I'm saying, la cidagna. That's true, that's true. Which is actually what la cidagna means, not goodbye, but letting go. That's exactly right. I think that's exactly right. I think you do have to make choices. You do have to set priorities. I often laugh at students who tell me they wanna have like three majors. If you have three majors, you have no major, right? I mean, so I do think you have to make choices. I also think it's important that whatever you do, even if it's a small thing, you always do the best you can. You always do excellent work. My kids are tired of hearing me say this at home, but I believe everything you do should be about excellence. The best you can do. If I'm gonna wash the dishes, I'm gonna be the best person washing the dishes. Right, if I'm gonna write a book review, I'm gonna make the best possible book review I can. Why? Because you develop a culture about yourself, which is about excellence. Yeah, I was telling you offline about all the kind of stuff, Google Fiber and cable installation, all that stuff. I've been always a believer, washing dishes. People don't often believe me when I say this. I don't care what I do. I am with David Foster Wallace. I'm unboreable. There is so much joy for me, I think for everyone, but okay, let me just speak for me, to be discovered in getting really good at anything. In fact, getting good at stuff that most people believe is boring or menial labor or impossible to be interesting, that's even more joyful to find the joy within that and the excellence. It's the Jiro dreams of sushi making the same fricking sushi over and over and becoming a master of that. That can be truly joyful. There's a sense of pride and on the pragmatic level, you never know when someone will spot that. And intelligent people who perform at the level of high excellence look for others, I would say. And it radiates some kind of signal. It's weird. It's weird what you attract to yourself when you just focus on mastery and pursuing excellence in something. This is the cool thing about it. That's the joy I've really truly experienced. I didn't have to do much work. It's just cool people. I find myself in groups of cool people, really people who are excited about life, who are passionate about life. There's a fire in their eyes that's, at the end of the day, just makes life fun. And then also money-wise, at least in this society, we're fortunate to where if you do that kind of thing, money will find a way. I have the great, I say this that I don't care about money. I have to think about what that means because some people criticize that idea. It's like, yeah, that must be nice to say that because I have for many periods of my life had very little money. But I think we live in a society where not caring about money, but just focusing on your passions. If you're truly pursuing excellence, whatever that is, money will find you. That's, I guess, the ideal of the capitalist system. And I think that the entrepreneurs I've studied and had the chance to get to know, and I'm sure you'd agree with this, they do what they do because they're passionate about the product. They're not just in it to make money. In fact, that's when they get into trouble, when they're just trying to make money. Exactly. You said your grandmother, Emily, had a big impact on your life. She lived to 102. What are some lessons she taught you? Emily, who was the child of immigrants from Russia and Poland, who never went to college, her proudest day, I think, was when I went to college. She treated everyone with respect and tried to get to know everyone. She knew every bus driver in the town. She'd remember their birthdays. And one of the things she taught me is no matter how high you fly, the lowest person close to the ground matters to you. And you treat them the same way you treat the billionaire at the top of the podium. And she did that. She didn't just say that. Some people say that and don't do it. She really did that. And I always remember that it comes up in my mind at least once a week, because we're all busy doing a lot of things. And you either see or you even feel in yourself the desire to just, for the reasons of speed, to be short or not polite with someone who can't do anything to harm you right now. And I remember her saying to me, no, you don't. You treat everyone with respect. You treat the person you're on the phone with, right, customer service. You treat that person if you're talking to Jeff Bezos or you're talking to Elon Musk, right? And I think making that a culture of who you are is so important. And people notice that. That's the other thing. And they notice when it's authentic. Everyone's nice to the person at the bottom of the totem pole when you want to get a head in the line for your driver's license. But are you nice to them when you don't need that? They notice that. And even when nobody's watching, that has a weird effect on you that's going to have a ripple effect and people know. That's the cool thing about the internet. I've come to believe that people see authenticity. They see when you're full of shit, when you're not. That's right. The other thing that Emily taught me, and I think we've all had relatives who have taught us this, right, that you could be very uneducated. She was very uneducated. She had a high school diploma, but I think she was working in a delicatessen in New York while she was in high school, or maybe it was at Gimbel's or something. So she probably didn't take high school very seriously. She wasn't very well educated. She was very smart. And we can fall into a world where I'm a big believer in higher education and getting a PhD and things of that sort, but where we think those are the only smart people. No. Sometimes those are the people, because of their accomplishments, because of their egos, are the ones who are least educated in the way of the world. Yeah. Least curious. And ultimately, wisdom comes from curiosity. And sometimes getting a PhD can get in the way of curiosity. It's supposed to empower curiosity. Let me ask, from a historical perspective, you've studied some of human history. So maybe you have an insight about what's the meaning of life. Why, do you ever ask when you look at history, the why? Yeah, I do all the time. And I don't have an answer. It's the mystery that we can't answer. I do think what it means is what we make of it. There's no universal. Every period I've studied, and I've studied a little bit of a lot of periods and a lot of a few periods, every period people struggle with this, and there's no, they don't come to, wiser people than us don't come to a firm answer, except it's what you make of it. Meaning is what you make of it. So think about what you want to care about and make that the meaning in your life. I wonder how that changes throughout human history, whether there's a constant. I often think, especially when you study evolutionary biology and you just see our origins from life and as it evolves, it's like, it makes you wonder, it feels like there's a thread that connects all of it, that we're headed somewhere. We're trying to actualize some greater purpose. Like there seems to be a direction to this thing, and we're all kind of stumbling in the dark trying to figure it out, but it feels like we eventually will find an answer. I hope so, yeah, maybe. I mean, I do think we all want our families to do better. We are familial, and family doesn't just mean biological family. You can have all kinds of ways you define family and community. And I think we are moving slowly and in a very messy way toward a larger world community. To include all of biological life and eventually artificial life as well. So to expand the lesson to the advice that your grandmother taught you, is I think we should treat robots and AI systems good as well, even if they're currently not very intelligent because one day they might be. Right, right, I think that's exactly right. And we should think through, exactly as a humanist how I would approach that issue. We need to think through the kinds of behavior patterns we want to establish with these new forms of life, artificial life, for ourselves also, to your point. So we behave the right way, so we don't misuse this. We started talking about Abraham Lincoln, ended talking about robots. I think this is the perfect conversation, Jeremy. This was a huge honor. I love Austin, I love UT Austin, and I love the fact that you would agree to waste all your valuable time with me today. Thank you so much for talking today. I can't imagine a better way to spend a Friday afternoon. This was so much fun, and I'm such a fan of your podcast and delighted to be a part of it. Thank you. Thanks for listening to this conversation with Jeremy Suri, and thank you to Element, MonkPak, Belcampo, Four Sigmatic, and Eight Sleep. Check them out in the description to support this podcast. And now, let me leave you with some words from Franklin D. Roosevelt, FDR. Democracy cannot succeed unless those who express their choice are prepared to choose wisely. The real safeguard of democracy, therefore, is education. Thank you for listening, and hope to see you next time.

https://youtu.be/USnqkUAr_3w

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Jordan Ellenberg: Mathematics of High-Dimensional Shapes and Geometries | Lex Fridman Podcast #190

The following is a conversation with Jordan Ellenberg, a mathematician at University of Wisconsin, and an author who masterfully reveals the beauty and power of mathematics in his 2014 book, How Not to Be Wrong, and his new book, just released recently, called Shape, The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else. Quick mention of our sponsors, Secret Sauce, ExpressVPN, Blinkist, and Indeed. Check them out in the description to support this podcast. As a side note, let me say that geometry is what made me fall in love with mathematics when I was young. It first showed me that something definitive could be stated about this world through intuitive visual proofs. Somehow, that convinced me that math is not just abstract numbers devoid of life, but a part of life, part of this world, part of our search for meaning. This is the Lex Friedman Podcast, and here is my conversation with Jordan Ellenberg. Jordan, I'm curious, what do you think is the most fundamental thing in mathematics? Is it the idea that the whole universe is built on top, extra layers, maybe the icing on the cake, maybe just, maybe consciousness is just like a cherry on top. Where do you put in this cake mathematical thinking? Is it as fundamental as language? In the Chomsky view, is it more really tightly interconnected? That's a really interesting question. You're getting me to reflect on this question of whether the feeling of producing mathematical output, if you want, is like the process of, you know, uttering language or producing linguistic output. I think it feels something like that, and it's certainly the case. Let me put it this way, it's hard to imagine doing mathematics in a completely non-linguistic way. It's hard to imagine doing mathematics without talking about mathematics and sort of thinking in propositions. But, you know, maybe it's just because that's the way I do mathematics, so maybe I can't imagine it any other way, right? It's a... Well, what about visualizing shapes, visualizing concepts, to which language is not obviously attachable? Ah, that's a really interesting question, and, you know, one thing it reminds me of is one thing I talk about in the book is dissection proofs, these very beautiful proofs of geometric propositions. There's a very famous one by Bhaskara of the Pythagorean theorem, proofs which are purely visual, proofs where you show that two quantities are the same by taking the same pieces and putting them together one way, and making one shape, and putting them together another way, and making a different shape, and then observing those two shapes must have the same area because they were built out of the same pieces. You know, there's a famous story, and it's a little bit disputed about how accurate this is, but that in Bhaskara's manuscript, he sort of gives this proof, just gives the diagram, and then the entire verbal content of the proof is he just writes under it, behold, like that's it. There's some dispute about exactly how accurate that is. But so then there's an interesting question. If your proof is a diagram, if your proof is a picture, or even if your proof is like a movie of the same pieces, like coming together in two different formations to make two different things, is that language? I'm not sure I have a good answer. What do you think? I think it is. I think the process of manipulating the visual elements is the same as the process of manipulating the elements of language. And I think probably the manipulating, the aggregation, the stitching stuff together is the important part. It's not the actual specific elements. It's more like, to me, language is a process, and math is a process. It's not just specific symbols. It's in action. It's ultimately created through action, through change, and so you're constantly evolving ideas. Of course, we kind of attach, there's a certain destination you arrive to that you attach to, and you call that a proof. But that doesn't need to end there. It's just at the end of the chapter, and then it goes on and on and on, in that kind of way. But I gotta ask you about geometry, and it's a prominent topic in your new book, Shape. So for me, geometry is the thing, just like as you're saying, made me fall in love with mathematics when I was young. So being able to prove something visually just did something to my brain that, it planted this hopeful seed that you can understand the world, like perfectly. Maybe it's an OCD thing, but from a mathematics perspective, like humans are messy, the world is messy, biology is messy, your parents are yelling, making you do stuff, but you can cut through all that BS and truly understand the world through mathematics, and nothing like geometry did that for me. For you, you did not immediately fall in love with geometry. So how do you think about geometry? Why is it a special field in mathematics? And how did you fall in love with it, if you have? Wow, you've given me a lot to say, and certainly the experience that you describe is so typical, but there's two versions of it. One thing I say in the book is that geometry is the cilantro of math. People are not neutral about it. There's people who, like you, are like, the rest of it I could take or leave, but then at this one moment, it made sense. This class made sense. Why wasn't it all like that? There's other people, I can tell you, because they come and talk to me all the time, who are like, I understood all the stuff where you're trying to figure out what x was, there's some mystery, you're trying to solve it, x is a number, I figured it out. But then there was this geometry, like what was that? What happened that year? I didn't get it. I was like lost the whole year, and I didn't understand why we even spent the time doing that. But what everybody agrees on is that it's somehow different. There's something special about it. We're going to walk around in circles a little bit, but we'll get there. You asked me how I fell in love with math. I have a story about this. When I was a small child, I don't know, maybe like I was six or seven, I don't know. I'm from the 70s. I think you're from a different decade than that. But in the 70s, we had a cool wooden box around your stereo. That was the look, everything was dark wood. And the box had a bunch of holes in it to let the sound out. And the holes were in this rectangular array, a six by eight array of holes. And I was just kind of like, you know, zoning out in the living room as kids do, looking at this six by eight rectangular array of holes. And if you like, just by kind of like focusing in and out, just by kind of looking at this box, looking at this rectangle, I was like, well, there's six rows of eight holes each. But there's also eight columns of six holes each. So eight sixes and six eights. It's just like the dissection proofs we were just talking about. But it's the same holes. It's the same 48 holes. That's how many there are, no matter whether you count them as rows or count them as columns. And this was like, unbelievable to me. Am I allowed to cuss on your podcast? I don't know if that's, are we FCC regulated? Fuck yes. Okay, it was fucking unbelievable. Okay, that's the last time. Get it in there. This story merits it. So two different perspectives on the same physical reality. Exactly. And it's just as you say, you know, I knew the six times eight was the same as eight times six, right? I knew my times tables, like I knew that that was a fact. But did I really know it until that moment? That's the question. Right? I knew that I sort of knew that the times table was symmetric. But I didn't know why that was the case until that moment. And in that moment, I could see like, oh, I didn't have to have somebody tell me that. That's information that you can just directly access. That's a really amazing moment. And as math teachers, that's something that we're really trying to bring to our students. And I was one of those who did not love the kind of Euclidean geometry ninth grade class of like, prove that an isosceles triangle has equal angles at the base like this kind of thing. It didn't vibe with me the way that algebra and numbers did. But if you go back to that moment, from my adult perspective, looking back at what happened with that rectangle, I think that is a very geometric moment. In fact, that moment exactly encapsulates the intertwining of algebra and geometry, this algebraic fact that, well, in the instance, eight times six is equal to six times eight. But in general, that whatever two numbers you have, you multiply them one way. And it's the same as if you multiply them in the other order. It attaches it to this geometric fact about a rectangle, which in some sense, makes it true. So you know, who knows, maybe I was always fated to be an algebraic geometer, which is what I am as a, as a researcher. So that's the kind of transformation and you talk about symmetry in your book. What the heck is symmetry? What the heck is these kinds of transformation on objects that once you transform them, they seem to be similar? What do you make of it? What's its use in mathematics, or maybe broadly in understanding our world? Well, it's an absolutely fundamental concept. And it starts with the word symmetry in the way that we usually use it when we're just like talking English and not talking mathematics, right? Sort of something is when we say something is symmetrical, we usually means it has what's called an axis of symmetry, maybe like the left half of it looks the same as the right half, that would be like a left right axis of symmetry, or maybe the top half looks like the bottom half, or both, right? Maybe there's sort of a fourfold symmetry where the top looks like the bottom and the left looks like the right, or more. And that can take you in a lot of different directions, the abstract study of what the possible combinations of symmetries there are a subject, which is called group theory was actually one of my first loves in mathematics, what I thought about a lot when I was in college. But the notion of symmetry is actually much more general than the things that we would call symmetry if we were looking at like a classical building or a painting or, or something like that. You know, nowadays, in in math, we could use a symmetry to refer to any kind of transformation of an image or a space or an object. You know, so what I talk about in in the book is take a figure and stretch it vertically, make it twice as big vertically, and make it half as wide. That I would call a symmetry, it's not a symmetry in the classical sense. But it's a well defined transformation that has an input and an output, I give you that output, I give you some shape. And it gets kind of, I call this in the book a scrunch, I just made I had to make up some sort of funny sounding name for it, because it doesn't really have a name. And just as you can sort of study which kinds of objects are symmetrical, under the operations of switching left and right, or switching top and bottom, or rotating 40 degrees, or what have you, you could study what kinds of things are preserved by this kind of scrunch symmetry. And this kind of more general idea of what a symmetry can be. Let me put it this way. A fundamental mathematical idea, in some sense, I might even say the idea that dominates contemporary mathematics, or by contemporary, by the way, I mean, like the last like 150 years, we're on a very long timescale. In math, I don't mean like yesterday, I mean, like a century or so, up till now, is this idea that's a fundamental question of when do we consider two things to be the same? That might seem like a complete triviality. It's not. For instance, if I have a triangle, and I have a triangle of the exact same dimensions, but it's over here. Are those the same? Or different? Well, you might say like, well, look, there's two different things. This one's over here, this one's over there. On the other hand, if you prove a theorem about this one, it's probably still true about this one, if it has like all the same side lanes and angles and like looks exactly the same. The term of art, if you want it, you would say they're congruent. But one way of saying it is there's a symmetry called translation, which just means move everything three inches to the left. And we want all of our theories to be translation invariant. What that means is that if you prove a theorem about a thing that's over here, and then you move it three inches to the left, it would be kind of weird if all of your theorems like didn't still work. So this question of like, what are the symmetries and which things that you want to study are invariant under those symmetries is absolutely fundamental. Boy, this is getting a little abstract, right? It's not at all abstract. I think this is completely central to everything I think about in terms of artificial intelligence. I don't know if you know about the MNIST dataset, what's handwritten digits. And I don't smoke much weed or any really, but it certainly feels like it when I look at MNIST and think about this stuff, which is like, what's the difference between one and two? And why are all the twos similar to each other? What kind of transformations are within the category of what makes a thing the same? And what kind of transformations are those that make it different? And symmetry is core to that. In fact, whatever the hell our brain is doing, it's really good at constructing these arbitrary and sometimes novel, which is really important when you look at like the IQ test or they feel novel ideas of symmetry of like what, like playing with objects, we're able to see things that are the same and not and construct almost like little geometric theories of what makes things the same and not and how to make programs do that in AI is a total open question. And so I kind of stared and wonder how, what kind of symmetries are enough to solve the MNIST handwritten digit recognition problem and write that down. And exactly. And what's so fascinating about the work in that direction from the point of view of a mathematician like me and a geometer is that the kind of groups of symmetries, the types of symmetries that we know of are not sufficient. So in other words, like, we're just going to keep on going into the weeds on this. The deeper the better. You know, a kind of symmetry that we understand very well is rotation. So here's what would be easy. If humans, if we recognize the digit as a one, if it was like literally a rotation by some number of degrees with some fixed one in some typeface like Palatino or something, that would be very easy to understand. It would be very easy to like write a program that could detect whether something was a rotation of a fixed digit one. Whatever we're doing when you recognize the digit one and distinguish it from the digit two, it's not that. It's not just incorporating one of the types of symmetries that we understand. Now, I would say that I would be shocked if there was some kind of classical symmetry type formulation that captured what we're doing when we tell the difference between a two and a three, to be honest. I think what we're doing is actually more complicated than that. I feel like it must be. They're so simple, these numbers. I mean, they're really geometric objects. Like we can draw one, two, three. It does seem like it should be formalizable. That's why it's so strange. Do you think it's formalizable when something stops being a two and starts being a three, where you can imagine something continuously deforming from being a two to a three? Yeah, but there is a moment. I have myself written programs that literally morph twos and threes and so on. And you watch, and there is moments that you notice, depending on the trajectory of that transformation, that morphing, that it is a three and a two. There's a hard line. Wait, so if you ask people, if you show them this morph, if you ask a bunch of people, do they all agree about where the transition happened? That's an interesting question. Because I would be surprised. I think so. Oh my god, okay, we have an empirical dispute. But here's the problem. Here's the problem. That if I just showed that moment that I agreed on... Well, that's not fair. No, but say I said, so I want to move away from the agreement, because that's a fascinating, actually, question that I want to backtrack from, because I just dogmatically said, because I could be very, very wrong. But the morphing really helps. That the change, because I mean, partially, it's because our perception systems, see, it's all probably tied in there. Somehow the change from one to the other, like seeing the video of it, allows you to pinpoint the place where a two becomes a three much better. If I just showed you one picture, I think you might really, really struggle. You might call it a seven. I think there's something also that we don't often think about, which is, it's not just about the static image, it's the transformation of the image, or it's not a static shape, it's the transformation of the shape. There's something in the movement that seems to be not just about our perception system, but fundamental to our cognition, like how we think about stuff. Yeah, and that's part of geometry too. And in fact, again, another insight of modern geometry is this idea that maybe we would naively think we're going to study, I don't know, like Poincaré, we're going to study the three-body problem. We're going to study three objects in space moving around subject only to the force of each other's gravity, which sounds very simple, right? And if you don't know about this problem, you're probably like, okay, so you just put it in your computer and see what they do. Well, guess what? That's a problem that Poincaré won a huge prize for, making the first real progress on in the 1880s, and we still don't know that much about it 150 years later. I mean, it's a humongous mystery. You just opened the door, and we're going to walk right in before we return to symmetry. So, let's talk about geometry. Who's Poincaré, and what's this conjecture that he came up with? Why is it such a hard problem? Okay, so Poincaré, he ends up being a major figure in the book, and I didn't even really intend for him to be such a big figure, but he's first and foremost a geometer, right? So, he's a mathematician who kind of comes up in late 19th century France at a time when French math is really starting to flower. Actually, I learned a lot. I mean, you know, in math, we're not really trained on our own history. We get a PhD in math, learn about math. So, I learned a lot. There's this whole kind of moment where France has just been beaten in the Franco-Prussian War, and they're like, oh my god, what did we do wrong? And they were like, we got to get strong in math like the Germans. We have to be more like the Germans, so this never happens to us again. So, it's very much, it's like the Sputnik moment, you know, like what happens in America in the 50s and 60s with the Soviet Union. This is happening to France, and they're trying to kind of like, instantly like modernize. That's fascinating that the humans and mathematics are intricately connected to the history of humans. The Cold War is, I think, fundamental to the way people saw science and math in the Soviet Union. I don't know if that was true in the United States, but certainly it was in the Soviet Union. It definitely was, and I would love to hear more about how it was in the Soviet Union. I mean, there's, and we'll talk about the Olympiad. I just remember that there was this feeling like the world hung in a balance, and you could save the world with the tools of science, and mathematics was like the superpower that fuels science. And so, like, people were seen as, you know, people in America often idolize athletes, but ultimately the best athletes in the world, they just throw a ball into a basket. So, like, there's not, what people really enjoy about sports, and I love sports, is like excellence at the highest level, but when you take that with mathematics and science, people also enjoyed excellence in science and mathematics in the Soviet Union, but there's an extra sense that that excellence will lead to a better world. So, that created all the usual things you think about with the Olympics, which is like extreme competitiveness, right? But it also created this sense that in the modern era in America, somebody like Elon Musk, whatever you think of him, like Jeff Bezos, those folks, they inspire the possibility that one person or a group of smart people can change the world, like not just be good at what they do, but actually change the world, and mathematics was at the core of that. And I don't know, there's a romanticism around it too, like, when you read books about, in America, people romanticize certain things like baseball, for example, there's like these beautiful poetic writing about the game of baseball. The same was the feeling with mathematics and science in the Soviet Union, and it was in the air. Everybody was forced to take high-level mathematics courses, like you took a lot of math, you took a lot of science and a lot of like really rigorous literature. Like, the level of education in Russia, this could be true in China, I'm not sure, in a lot of countries, is in whatever that's called, it's K-12 in America, but like young people education, the level they were challenged to learn at is incredible. It's like America falls far behind, I would say. America then quickly catches up and then exceeds everybody else at the, like, as you start approaching the end of high school to college, like the university system in the United States arguably is the best in the world. But like, what we challenge everybody, it's not just like the good, the A students, but everybody to learn in the Soviet Union was fascinating. I think I'm going to pick up on something you said. I think you would love a book called Duel at Dawn by Amir Alexander, which I think some of the things you're responding to what I wrote, I think I first got turned on to by Amir's work. He's a historian of math, and he writes about the story of Evariste Galois, which is a story that's well known to all mathematicians, this kind of very, very romantic figure who, he really sort of like begins the development of this, well, this theory of groups that I mentioned earlier, this general theory of symmetries, and then dies in a duel in his early 20s, like all this stuff, mostly unpublished. It's a very, very romantic story that we all learn. And much of it is true. But Alexander really lays out just how much the way people thought about math in those times in the early 19th century was wound up with, as you say, romanticism. I mean, that's when the romantic movement takes place. And he really outlines how people were predisposed to think about mathematics in that way, because they thought about poetry that way. And they thought about music that way. It was the mood of the era to think about, we're reaching for the transcendent, we're sort of reaching for sort of direct contact with the divine. And so, part of the reason that we think of Galois that way was because Galois himself was a creature of that era. And he romanticized himself. I mean, now, you know, he wrote lots of letters. And he was kind of like, I mean, in modern terms, we would say he was extremely emo. We wrote all these letters about his florid feelings and the fire within him about the mathematics. And, you know, so he, so it's just as you say, that the math history touches human history. They're never separate, because math is made of people. LUKE Yeah. DAVE I mean, that's what it's, it's people who do it, and we're human beings doing it. And we do it within whatever community we're in. And we do it affected by the mores of the society around us. LUKE So the French, the Germans and Poincaré. DAVE Yes. Okay, so back to Poincaré. So he's, you know, it's funny, this book is filled with kind of, you know, mathematical characters who often are kind of peevish or get into feuds or sort of have like, weird enthusiasms. Because those people are fun to write about. And they sort of like say, very salty things. Poincaré is actually none of this as far as I can tell. He was an extremely normal dude. He didn't get into fights with people. And everybody liked him. And he was like pretty personally modest. And he had very regular habits. You know what I mean? He did math for like, four hours in the morning and four hours in the evening. And that was it. Like he had his schedule. I actually it was like, I still am feeling like somebody's gonna tell me now the book is out like, Oh, didn't you know about this like incredibly sordid episode of Mr. Poincaré? As far as I could tell, a completely normal guy, but he just kind of, in many ways creates the geometric world in which we live. And you know, his first really big success is this prize paper he writes for this prize offered by the King of Sweden for the study of the three body problem. The study of what we can say about, yeah, three astronomical objects moving in what you might think would be this very simple way. Nothing's going on except gravity. So what's the three body problem? Why is that a problem? So the problem is to understand when this motion is stable and when it's not so stable, meaning they would sort of like end up in some kind of periodic orbit, or I guess it would mean sorry, stable would mean they never sort of fly off far apart from each other. And unstable would mean like eventually they fly apart. So understanding two bodies is much easier. Yeah, exactly. Third wheel is always a problem. This is what Newton knew. Two bodies, they sort of orbit each other in some kind of, either in an ellipse, which is the stable case, you know, that's what the planets do that we know. Or one travels on a hyperbola around the other, that's the unstable case. It sort of like zooms in from far away, sort of like whips around the heavier thing and like zooms out. Those are basically the two options. So it's a very simple and easy to classify story. With three bodies, just a small switch from two to three, it's a complete zoo. What we would say now is it's the first example of what's called chaotic dynamics, where the stable solutions and the unstable solutions, they're kind of like wound in among each other. And a very, very, very tiny change in the initial conditions can make the long-term behavior of the system completely different. So Poincaré was the first to recognize that that phenomenon even existed. What about the conjecture that carries his name? Right. So he also was one of the pioneers of taking geometry, which until that point had been largely the study of two and three dimensional objects, because that's like what we see, right? That's the objects we interact with. He developed a subject we now call topology. He called it analysis situs. He was a very well-spoken guy with a lot of slogans, but that name did not, you can see why that name did not catch on. So now it's called topology now. Sorry, what was it called before? Analysis situs, which I guess sort of roughly means like the analysis of location or something like that. It's a Latin phrase. Partly because he understood that even to understand stuff that's going on in our physical world, you have to study higher dimensional spaces. How does this work? And this is kind of like where my brain went to it because you were talking about not just where things are, but what their path is, how they're moving when we were talking about the path from two to three. He understood that if you want to study three bodies moving in space, well, each body, it has a location where it is. So it has an X coordinate, a Y coordinate, a Z coordinate, right? I can specify a point in space by giving you three numbers, but it also at each moment has a velocity. So it turns out that really to understand what's going on, you can't think of it as a point, or you could, but it's better not to think of it as a point in three dimensional space that's moving. It's better to think of it as a point in six dimensional space where the coordinates are, where is it and what's its velocity right now? That's a higher dimensional space called phase space. And if you haven't thought about this before, I admit that it's a little bit mind bending, but what he needed then was a geometry that was flexible enough, not just to talk about two dimensional spaces or three dimensional spaces, but any dimensional space. So the sort of famous first line of this paper where he introduces analysis is, no one doubts nowadays that the geometry of N dimensional space is an actually existing thing. Right. I think that maybe that had been controversial. And he's saying like, look, let's face it just because it's not physical, doesn't mean it's not there. It doesn't mean we shouldn't study it. Interesting. He wasn't jumping to the physical interpretation. Like it can be real, even if it's not perceivable to human cognition. I think that's right. I think, don't get me wrong, Poincaré never strays far from physics. He's always motivated by physics, but the physics drove him to need to think about spaces of higher dimension. And so he needed a formalism that was rich enough to enable him to do that. And once you do that, that formalism is also going to include things that are not physical. And then you have two choices. You can be like, oh, well, that stuff's trash. Or, but this is more of the mathematician's frame of mind. If you have a formalistic framework that like seems really good and sort of seems to be like very elegant and work well, and it includes all the physical stuff, maybe we should think about all of it. Like maybe we should think about it, thinking, oh, maybe there's some gold to be mined there. And indeed, guess what? Before long, there's relativity and there's space-time. And all of a sudden it's like, oh yeah, maybe it's a good idea. We already had this geometric apparatus set up for how to think about four-dimensional spaces. Turns out they're real after all. This is a story much told in mathematics, not just in this context, but in many. I'd love to dig in a little deeper on that, actually, because I have some intuitions to work out in my brain. But— Well, I'm not a mathematical physicist, so we can work it out together. Good. We'll together walk along the path of curiosity. But Poincaré conjecture, what is it? Poincaré conjecture is about curved three-dimensional spaces. So I was on my way there, I promise. The idea is that we perceive ourselves as living in— we don't say a three-dimensional space, we just say three-dimensional space. You know, you can go up and down, you can go left and right, you can go forward and back. There's three dimensions in which we can move. In Poincaré's theory, there are many possible three-dimensional spaces. In the same way that going down one dimension to sort of capture our intuition a little bit more, we know there are lots of different two-dimensional surfaces, right? There's a balloon, and that looks one way, and a donut looks another way, and a Mobius strip looks a third way. Those are all like two-dimensional surfaces that we can kind of really get a global view of, because we live in three-dimensional space, so we can see a two-dimensional surface sort of sitting in our three-dimensional space. Well, to see a three-dimensional space whole, we'd have to kind of have four-dimensional eyes, right? Which we don't, so we have to use our mathematical eyes, we have to envision. The Poincaré conjecture says that there's a very simple way to determine whether a three-dimensional space is the standard one, the one that we're used to. And essentially, it's that it's what's called fundamental group has nothing interesting in it. And that I can actually say without saying what the fundamental group is, I can tell you what the criterion is. This would be good. Oh, look, I can even use a visual aid. So for the people watching this on YouTube, you'll just see this. For the people on the podcast, you'll see this. So I'm going to use a visual aid. For the people on the podcast, you'll have to visualize it. So Lex has been nice enough to like, give me a surface with some interesting topology. It's a mug. Right here in front of me. A mug, yes. I might say it's a genus one surface, but we could also say it's a mug, same thing. So if I were to draw a little circle on this mug, which way should I draw it so it's visible? Like here, okay. If I draw a little circle on this mug, imagine this to be a loop of string. I could pull that loop of string closed on the surface of the mug, right? That's definitely something I could do. I could shrink it, shrink it, shrink it until it's a point. On the other hand, if I draw a loop that goes around the handle, I can kind of zhuzh it up here and I can zhuzh it down there and I can sort of slide it up and down the handle. But I can't pull it closed, can I? It's trapped. Not without breaking the surface of the mug, right? Not without like going inside. So the condition of being what's called simply connected, this is one of Poincaré's inventions, says that any loop of string can be pulled shut. So it's a feature that the mug simply does not have. This is a non-simply connected mug and a simply connected mug would be a cup, right? You would burn your hand when you drank coffee out of it. So you're saying the universe is not a mug? Well, I can't speak to the universe, but what I can say is that regular old space is not a mug. Regular old space, if you like sort of actually physically have like a loop of string, You can always close it. You can pull it shut. You can always pull it shut. But what if your piece of string was the size of the universe? Like what if your piece of string was like billions of light years long? How do you actually know? I mean, that's still an open question of the shape of the universe. Exactly. Whether it's, I think there's a lot, there is ideas of it being a torus. I mean, there's some trippy ideas and they're not like weird out there, controversial. There's legitimate at the center of cosmology debate. I mean, I think most people think it's flat. I think there's somebody who thinks that there's like some kind of dodecahedral symmetry or I mean, I remember reading something crazy about somebody saying that they saw the signature of that in the cosmic noise or what have you. I mean. To make the flat earthers happy, I do believe that the current main belief is it's flat. It's flat-ish or something like that. The shape of the universe is flat-ish. I don't know what the heck that means. I think that has like a very, I mean, how are you even supposed to think about the shape of a thing that doesn't have any thing outside of it? I mean. Ah, but that's exactly what topology does. Topology is what's called an intrinsic theory. That's what's so great about it. This question about the mug, you could answer it without ever leaving the mug, right? Because it's a question about a loop drawn on the surface of the mug and what happens if it never leaves that surface. So it's like always there. See, but that's the difference between the topology and say, if you're like trying to visualize a mug, that you can't visualize a mug while living inside the mug. Well, that's true. The visualization is harder, but in some sense, no, you're right. But if the tools of mathematics are there, I don't want to fight, but I think the tools of mathematics are exactly there to enable you to think about what you cannot visualize in this way. Let me give, let's go, always to make things easier, go down a dimension. Let's think about we live on a circle. Okay? You can tell whether you live on a circle or a line segment, because if you live on a circle, if you walk a long way in one direction, you find yourself back where you started. And if you live in a line segment, you walk for a long enough one direction, you come to the end of the world. Or if you live on a line, like a whole line, an infinite line, then you walk in one direction for a long time. And like, well, then there's not a sort of terminating algorithm to figure out whether you live on a line or a circle, but at least you sort of, at least you don't discover that you live on a circle. So all of those are intrinsic things, right? All of those are things that you can figure out about your world without leaving your world. On the other hand, right? Now we're going to go from intrinsic to extrinsic. Why did I not know we were going to talk about this, but why not? Why not? If you can't tell whether you live in a circle or a knot, like imagine like a knot floating in three dimensional space, the person who lives on that knot to them, it's a circle. They walk a long way, they come back to where they started. Now we with our three dimensional eyes can be like, oh, this one's just a plain circle and this one's knotted up. But that has to do with how they sit in three dimensional space. It doesn't have to do with intrinsic features of those people's world. We can ask you one ape to another. How does it make you feel that you don't know if you live in a circle or on a knot, in a knot, inside the string that forms the knot? I don't even know how to say that. I'm going to be honest with you. I don't know if like, I fear you won't like this answer, but it does not bother me at all. I don't lose one minute of sleep over it. So like, does it bother you that if we look at like a Mobius strip, that you don't have an obvious way of knowing whether you are inside of cylinder, if you live on a surface of a cylinder or you live on the surface of a Mobius strip? No, I think you can tell if you live. Which one? Because if what you do is you like, tell your friend, hey, stay right here. I'm just going to go for a walk. And then you like walk for a long time in one direction and then you come back and you see your friend again. And if your friend is reversed, then you know you live on a Mobius strip. Well, no, because you won't see your friend, right? Okay, fair point. Fair point on that. But you have to believe the stories about, no, I don't even know. Would you even know? Would you really? Oh, no, your point is right. Let me try to think of a better, let's see if I can do this on the vlog. It may not be correct to talk about cognitive beings living on a Mobius strip, because there's a lot of things taken for granted there. And we're constantly imagining actual like three dimensional creatures, like how it actually feels like to live in a Mobius strip is tricky to internalize. I think that on what's called the real projective plane, which is kind of even more sort of like messed up version of the Mobius strip, but with very similar features, this feature of kind of like only having one side, that has the feature that there's a loop of string, which can't be pulled closed. But if you loop it around twice along the same path, that you can pull closed. That's extremely weird. Yeah. But that would be a way you could know without leaving your world that something very funny is going on. You know, what's extremely weird, maybe we can comment on, hopefully it's not too much of a tangent is, I remember thinking about this. This might be right. This might be wrong. But if we now talk about a sphere and you're living inside a sphere that you're going to see everywhere around you, the back of your own head. That I was, cause like, I was, this was very counterintuitive to me to think about, maybe it's wrong. But cause I was thinking of like earth, you know, your 3D thing on sitting on a sphere. But if you're living inside the sphere, like you're going to see, if you look straight, you're always going to see yourself all the way around. So everywhere you look, there's going to be the back of your own head. I think somehow this depends on something of like how the physics of light works in this scenario, which I'm sort of finding it hard to bend my... That's true. The sea is doing a lot of work, like saying you see something's doing a lot of work. People have thought about this. I mean, this, this metaphor of like, what if we're like little creatures in some sort of smaller world? Like how could we apprehend what's outside? That metaphor just comes back and back. And actually I didn't even realize like how frequent it is. It comes up in the book a lot. I know it from a book called Flatland. I don't know if you ever read this when you were a kid or an adult, you know, this, this sort of, this sort of comic novel from the 19th century about an entire two-dimensional world. It's narrated by a square, that's the main character. And the kind of strangeness that befalls him when, you know, one day he's in his house and suddenly there's like a little circle there and they're with him. And then the circle, but then the circle like starts getting bigger and bigger and bigger. And he's like, what the hell is going on? It's like a horror movie, like for two-dimensional people. And of course, what's happening is that a sphere is entering his world. And as the sphere kind of like moves farther and farther into the plane, it's cross-sectioned, the part of it that he can see. To him, it looks like there's like this kind of bizarre being that's like getting larger and larger and larger until it's exactly sort of halfway through. And then they have this kind of like philosophical argument with the sphere, it's like, I'm a sphere, I'm from the third dimension. The square is like, what are you talking about? There's no such thing. And they have this kind of like sterile argument where the square is not able to kind of like follow the mathematical reasoning of the sphere until the sphere just kind of grabs him and like jerks him out of the plane and pulls him up. And it's like, now, like now do you see, like now do you see your whole world that you didn't understand before? So do you think that kind of process is possible for us humans? So we live in the three-dimensional world, maybe with the time component four-dimensional, and then math allows us to go into high dimensions comfortably and explore the world from those perspectives. Is it possible that the universe is many more dimensions than the ones we experience as human beings? So if you look at the, especially in physics theories of everything, physics theories that try to unify general relativity and quantum field theory, they seem to go to high dimensions to work stuff out through the tools of mathematics. Is it possible? So like the two options are, one is just a nice way to analyze a universe, but the reality is as exactly we perceive it, it is three-dimensional. Or are we just seeing, are we those flatland creatures that are just seeing a tiny slice of reality and the actual reality is many, many, many more dimensions than the three dimensions we perceive? Oh, I certainly think that's possible. Now, how would you figure out whether it was true or not is another question. And I suppose what you would do, as with anything else that you can't directly perceive, is you would try to understand what effect the presence of those extra dimensions out there would have on the things we can perceive. Like what else can you do, right? And in some sense, if the answer is they would have no effect, then maybe it becomes like a little bit of a sterile question because what question are you even asking, right? You can kind of posit however many entities that you want. Well, is it possible to intuit how to mess with the other dimensions while living in a three-dimensional world? I mean, that seems like a very challenging thing to do. The reason flatland could be written is because it's coming from a three-dimensional writer. Yes, but what happens in the book, I didn't even tell you the whole plot, what happens is the square is so excited and so filled with intellectual joy. By the way, maybe to give the story some context, you ask, is it possible for us humans to have this experience of being transcendentally jerked out of our world so we can truly see it from above? Well, Edwin Abbott, who wrote the book, certainly thought so because Edwin Abbott was a minister. So the whole Christian subtext of this book, I had completely not grasped reading this as a kid, that it means a very different thing, right? If a theologian is saying, oh, what if a higher being could pull you out of this earthly world you live in so that you can sort of see the truth and really see it from above, as it were. So that's one of the things that's going on for him. And it's a testament to his skill as a writer that his story just works, whether that's the framework you're coming to it from or not. But what happens in this book, and this part now, looking at it through a Christian lens, it becomes a bit subversive, is the square is so excited about what he's learned from the sphere. And the sphere explains to him what a cube would be. Oh, it's like you, but three-dimensional. And the square is very excited. And the square is like, okay, I get it now. So now that you explained to me how just by reason I can figure out what a cube would be like, like a three-dimensional version of me, let's figure out what a four-dimensional version of me would be like. And then the sphere is like, what the hell are you talking about? There's no fourth dimension? That's ridiculous. There's only three dimensions. That's how many there are. I can see. So it's this sort of comic moment where the sphere is completely unable to conceptualize that there could actually be yet another dimension. So yeah, that takes the religious allegory to like a very weird place that I don't really like understand theologically. But that's a nice way to talk about religion and myth in general, as perhaps us trying to struggle, us meaning human civilization, trying to struggle with ideas that are beyond our cognitive capabilities. But it's in fact not beyond our capability. It may be beyond our cognitive capabilities to visualize a four-dimensional cube, a tesseract as some like to call it, or a five-dimensional cube or a six-dimensional cube. But it is not beyond our cognitive capabilities to figure out how many corners a six-dimensional cube would have. That's what's so cool about us. Whether we can visualize it or not, we can still talk about it. We can still reason about it. We can still figure things out about it. That's amazing. Yeah. If we go back to this, first of all to the mug, but to the example you give in the book of the straw, how many holes does a straw have? And you, listener, may try to answer that in your own head. Yeah, I'm going to take a drink while everybody thinks about it so I can give you a moment. A slow sip. Is it zero, one, or two, or more than that maybe? Maybe you can get very creative. But it's kind of interesting to dissecting each answer as you do in the book. It's quite brilliant. People should definitely check it out. But if you could try to answer it now, think about all the options and why they may or may not be right. Yeah, it's one of these questions where people on first hearing it think it's a triviality and they're like, well, the answer is obvious. And then what happens if you ever ask a group of people this, something wonderfully comic happens, which is that everyone's like, well, it's completely obvious. And then each person realizes that half the person, the other people in the room have a different obvious answer for the way they have. And then people get really heated. People are like, I can't believe that you think it has two holes. Or like, I can't believe that you think it has one. And then you really, like people really learn something about each other. And people get heated. I mean, can we go through the possible options here? Is it 0, 1, 2, 3, 10? Sure. So I think, you know, most people, the zero holers are rare. They would say like, well, look, you can make a straw by taking a rectangular piece of plastic and closing it up. Rectangular piece of plastic doesn't have a hole in it. I didn't poke a hole in it. So how can I have a hole? It's like, it's just one thing. Okay. Most people don't see it that way. That's like, um, Is there any truth to that kind of conception? Yeah, I think that would be somebody who's account, I mean, what I would say is you could say the same thing. About a bagel, you could say I can make a bagel by taking like a long cylinder of dough, which doesn't have a hole and then smushing the ends together. Now it's a bagel. So if you're really committed, you can be like, okay, a bagel doesn't have a hole either. But like, who are you if you say a bagel doesn't have a hole? I mean, I don't know. Yeah. So that's almost like an engineering definition of it. Okay, fair enough. So what's, what about the other options? So, you know, one hole people would say, um, I like how these are like groups of people, like we've planted our foot. Yes, team one hole. There's books written about each belief. You know, once they look, there's like a hole and it goes all the way through the straw, right? There's one region of space. That's the hole. And there's one and two hole people would say like, well, look, there's a hole in the top and the hole at the bottom. I think a common thing you see, when people argue about this, they would take something like this bottle of water I'm holding, I'll open it. And they say, well, how many holes are there in this? And you say, like, well, there's one, there's one hole at the top. Okay, what if I like, poke a hole here so that all the water spills out? Well, now it's a straw. Yeah. So if you're a one hole, or I say to you, like, well, how many holes are in it now? There was a hole, there was one hole in it before and I poked a new hole in it. And then you think there's still one hole, even though there was one hole and I made one more? Clearly not. This is two holes. Yeah. Um, and yet, if you're a two hole or the one hole, or we'll say like, okay, where does one hole begin in the other hole end? Yeah, like, what's it like? And, um, and in the in the book, I sort of, you know, in math, there's two things we do when we're faced with a problem that's confusing us. We can make the problem simpler. That's what we were doing a minute ago, and we were talking about high dimensional space. And I was like, let's talk about like circles and line segments. Let's like go down a dimension to make it easier. The other big move we have is to make the problem harder and try to sort of really like face up to what are the complications. So, you know, what I do in the book is say like, let's stop talking about straws for a minute and talk about pants. How many holes are there in a pair of pants? So I think most people who say there's two holes in a straw would say there's three holes in a pair of pants. I guess I mean, I guess we're filming only from here I could take up not I'm not gonna do it. You just have to imagine the pants. Sorry. Yeah. Lex, if you want to know, okay, no. That's gonna be in the director's cut. It's a Patreon only footage. There you go. So many people would say there's three holes in a pair of pants. But you know, for instance, my daughter when I asked, by the way, talking to kids about this is super fun. I highly recommend it. What did she say? She said, well, yeah, I feel a pair of pants like just has two holes because yes, there's the waist, but that's just the two leg holes stuck together. Whoa, okay. Two leg hole. Yeah. Okay. I mean, that's a one hole for the straw. So she's a one hole for the straw too. And, and that really does capture something. It captures this fact, which is central to the theory of what's called homology, which is like a central part of modern topology that holes, whatever we may mean by them, there's somehow things which have an arithmetic to them. There are things which can be added, like the waist, like waist equals leg plus leg is kind of an equation, but it's not an equation about numbers. It's an equation about some kind of geometric, some kind of topological thing, which is very strange. And so, you know, when I come down, you know, like a rabbi, I like to kind of like, come up with these answers to somehow like dodge the original question and say, like, you're both right, my children. Okay, so. Yeah. So for this truth, for the, for the straw, I think what a modern mathematician would say is like, the first version would be to say, like, well, there are two holes, but they're really both the same hole. Well, that's not quite right. A better way to say it is, there's two holes, but one is the negative of the other. Now, what can that mean? One way of thinking about what it means is that if you sip something like a milkshake through the straw, no matter what, the amount of milkshake that's flowing in one end, that same amount is flowing out the other end. So, they're not independent from each other. There's some relationship between them in the same way that if you somehow could like suck a milkshake through a pair of pants, the amount of milkshake, just go with me on this experiment. I'm right there with you. The amount of milkshake that's coming in the left leg of the pants, plus the amount of milkshake that's coming in the right leg of the pants is the same that's coming out the waist of the pants. So, just so you know, I fasted for 72 hours the last three days. So, I just broke the fast with a little bit of food yesterday. So, this is like, this sounds, food analogies or metaphors for this podcast work wonderfully, because I can intensely picture it. Is that your weekly routine or just in preparation for talking about geometry for three hours? Exactly. Just for this. It's hardship to purify the mind. No, it's for the first time. I just wanted to try the experience. Oh, wow. And just to pause, to do things that are out of the ordinary, to pause and to reflect on how grateful I am to be just alive and be able to do all the cool shit that I get to do. So, did you drink water? Yes, yes, yes, yes, yes, yes. Water and salt. So, like electrolytes and all those kinds of things. But anyway, so the inflow on the top of the pants equals to the outflow on the bottom of the pants. Exactly. So, this idea that, I mean, I think, you know, Poincaré really had this idea, this sort of modern idea. I mean, building on stuff other people did, Betty is an important one, of this kind of modern notion of relations between wholes. But the idea that wholes really had an arithmetic, the really modern view was really Emmy Noether's idea. So, she kind of comes in and sort of truly puts the subject on its modern footing that we have now. So, you know, it's always a challenge. You know, in the book, I'm not going to say I give like a course so that you read this chapter and then you're like, oh, it's just like I took like a semester of algebraic topology. It's not like this. And it's always a challenge writing about math because there are some things that you can really do on the page and the math is there. And there's other things which, it's too much in a book like this to like do them all the page. You can only say something about them, if that makes sense. So, you know, in the book, I try to do some of both. I try to do, I try to, topics that are, you can't really compress and really truly say exactly what they are in this amount of space. I try to say something interesting about them, something meaningful about them so that readers can get the flavor. And then in other places, I really try to get up close and personal and really do the math and have it take place on the page. LUKE RENNER. To some degree, be able to give inklings of the beauty of the subject. DAVID LEVIN. Yeah, I mean, there's, you know, there's a lot of books that are like, I don't quite know how to express this well. I'm still laboring to do it. But there's a lot of books that are about stuff. But I want my books to not only be about stuff, but to actually have some stuff there on the page in the book for people to interact with directly and not just sort of hear me talk about distant features about, distant features of it. LUKE RENNER. Right. So, not be talking just about ideas, but the actually be expressing the idea. Is there, you know, somebody in the, maybe you can comment, there's a guy, his YouTube channel is 3Blue1Brown, Grant Sanderson. He does that masterfully well. DAVID LEVIN. Absolutely. LUKE RENNER. Of visualizing, of expressing a particular idea and then talking about it as well, back and forth. What do you think about Grant? DAVID LEVIN. It's fantastic. I mean, the flowering of math YouTube is like such a wonderful thing because, you know, math teaching, there's so many different venues through which we can teach people math. There's the traditional one, right? Well, where I'm in a classroom with, you know, depending on the class, it could be 30 people, it could be 100 people, it could, God help me, be 500 people, if it's like the big calculus lecture or whatever it may be. And there's sort of some, but there's some set of people of that order of magnitude. And I'm with them, we have a long time, I'm with them for a whole semester. And I can ask them to do homework and we talk together, we have office hours, if they have one-on-one questions, blah, blah, blah. It's like a very high level of engagement. But how many people am I actually hitting at a time? Like not that many, right? And you can, and there's kind of an inverse relationship where the more, the fewer people you're talking to, the more engagement you can ask for. The ultimate, of course, is like the mentorship relation of like a PhD advisor and a graduate student where you spend a lot of one-on-one time together for like three to five years. And the ultimate high level of engagement to one person. You know, books, this can get to a lot more people than are ever going to sit in my classroom and you spend like however many hours it takes to read a book. Somebody like 3Blue1Brown or Numberphile or people like Vi Hart. I mean, YouTube, let's face it, has bigger reach than a book. Like there's YouTube videos that have many, many, many more views than like, you know, any hardback book like not written by a Kardashian or an Obama is going to sell, right? So that's, I mean, and then, you know, those are, you know, some of them are like longer, 20 minutes long, some of them are five minutes long, but they're, you know, they're shorter. And then even some, look, look, like Eugenia Chang is a wonderful category theorist in Chicago. I mean, she was on, I think, the Daily Show or is it? I mean, she was on, you know, she has 30 seconds, but then there's like 30 seconds to sort of say something about math, mathematics to like untold millions of people. So everywhere along this curve is important. And one thing I feel like is great right now is that people are just broadcasting on all the channels because we each have our skills, right? Somehow along the way, like I learned how to write books. I had this kind of weird life as a writer where I sort of spent a lot of time like thinking about how to put English words together into sentences and sentences together into paragraphs, like at length, which is this kind of like weird specialized skill. And that's one thing, but like sort of being able to make like, you know, winning good looking eye catching videos is like a totally different skill. And, you know, probably, you know, somewhere out there, there's probably sort of some like heavy metal band that's like teaching math through heavy metal and like using their skills to do that. I hope there is at any rate. Their music and so on. Yeah. But there is something to the process. I mean, Grant does this especially well, which is in order to be able to visualize something, now he writes programs, so it's programmatic visualization. So like the things he is basically mostly through his Manum library in Python, everything is drawn through Python. And you have to, you have to truly understand the topic to be able to visualize it in that way, and not just understand it, but really kind of think in a very novel way. It's funny because I've spoken with him a couple of times, spoken to him a lot offline as well. He really doesn't think he's doing anything new, meaning like he sees himself as very different from maybe like a researcher. But it feels to me like he's creating something totally new, like that act of understanding and visualizing is as powerful or has the same kind of inkling of power as does the process of proving something. You know, it just, it doesn't have that clear destination, but it's pulling out an insight and creating multiple sets of perspective that arrive at that insight. And to be honest, it's something that I think we haven't quite figured out how to value inside academic mathematics in the same way, and this is a bit older, that I think we haven't quite figured out how to value the development of computational infrastructure. You know, we all have computers as our partners now, and people build computers that sort of assist and participate in our mathematics. They build those systems, and that's a kind of mathematics too, but not in the traditional form of proving theorems and writing papers. But I think it's coming. Look, I mean, I think, you know, for example, the Institute for Computational Experimental Mathematics at Brown, which is like a, you know, it's a NSF-funded math institute, very much part of sort of traditional math academia, they did an entire theme semester about visualizing mathematics, like the same kind of thing that they would do for like an up-and-coming research topic, like that's pretty cool. So I think there really is buy-in from the mathematics community to recognize that this kind of stuff is important and counts as part of mathematics, like part of what we're actually here to do. Yeah, I'm hoping to see more and more of that from like MIT faculty, from faculty from all the top universities in the world. Let me ask you this weird question about the Fields Medal, which is the Nobel Prize in mathematics. Do you think, since we're talking about computers, there will one day come a time when a computer, an AI system will win a Fields Medal? No. Of course, that's what a human would say. Why not? Is that like, that's like my cap shot? That's like the proof that I'm a human? Is like, deny that I'm not? Yeah. What is, how does he want me to answer? Is there something interesting to be said about that? Yeah, I mean, I am tremendously interested in what AI can do in pure mathematics. I mean, it's of course, it's a parochial interest, right? You're like, why am I not interested in like how it can like help feed the world or help solve like real-world problems? I'm like, can it do more math? Like, what can I do? We all have our interests, right? But I think it is a really interesting conceptual question. And here too, I think it's important to be kind of historical because it's certainly true that there's lots of things that we used to call research in mathematics that we would now call computation. Tasks that we've now offloaded to machines like, you know, in 1890, somebody could be like, here's my PhD thesis, I computed all the invariants of this polynomial ring under the action of some finite group, doesn't matter what those words mean, just it's like some thing that in 1890 would take a person a year to do and would be a valuable thing that you might want to know. And it's still a valuable thing that you might want to know, but now you type a few lines of code in Macaulay or Sage or Magma, and you just have it. So we don't think of that as math anymore, even though it's the same thing. What's Macaulay, Sage and Magma? Oh, those are computer algebra programs. So those are like sort of bespoke systems that lots of mathematicians use. That's similar to Maple and Mathematica? Yeah. Oh yeah. So it's similar to Maple and Mathematica. Yeah. But a little more specialized, but yeah. It's programs that work with symbols and allow you to do, can you do proofs? Can you do kind of little leaps and proofs? They're not really built for that, and that's a whole other story. But these tools are part of the process of mathematics now? Right. They are now for most mathematicians, I would say, part of the process of mathematics. And so, you know, there's a story I tell in the book, which I'm fascinated by, which is, you know, so far, attempts to get AIs to prove interesting theorems have not done so well. It doesn't mean they can't. There's actually a paper I just saw, which has a very nice use of a neural net to find counter examples to conjecture. Somebody said, like, well, maybe this is always that. And you can be like, well, let me sort of train an AI to sort of try to find things where that's not true. And it actually succeeded. Now, in this case, if you look at the things that it found, you say, like, okay, I mean, these are not famous conjectures. Okay, so like, somebody wrote this down, maybe this is so. Looking at what the AI came up with, you're like, you know, I bet if like, five grad students had thought about that problem, they wouldn't have come up with that. I mean, when you see it, you're like, okay, that is one of the things you might try if you sort of like, put some work into it. Still, it's pretty awesome. But the story I tell in the book, which I'm fascinated by is, there is, there's a, okay, we're gonna go back to knots. There's a knot called the Conway knot, after John Conway, who maybe we'll talk about a very interesting character also. Yeah, there's a small tangent, somebody I was supposed to talk to, and unfortunately, he passed away. And he's somebody I find as an incredible mathematician, incredible human being. Oh, and I am sorry that you didn't get a chance because having had the chance to talk to him a lot when I was, you know, when I was a postdoc. Yeah, you missed out. There's no way to sugar coat it. I'm sorry that you didn't get that chance. Yeah, it is what it is. So knots. Yeah, so there was a question. And again, it doesn't matter the technicalities of the question, but it's a question of whether the knot is sliced. It has to do with something about what kinds of three dimensional surfaces in four dimensions can be bounded by this knot. But never mind what it means. It's some question. And it's actually very hard to compute whether a knot is sliced or not. And in particular, the question of the Conway knot, whether it was sliced or not, was particularly vexed. Until it was solved just a few years ago by Lisa Piccirillo, who actually now that I think of it was here in Austin, I believe she was a grad student at UT Austin at the time, I didn't even realize there was an Austin connection to this story until I started telling it. She is in fact, I think she's now at MIT. So she's basically following you around. If I remember correctly, the reverse. There's a lot of really interesting richness to this story. One thing about it is her paper was rather was very short, was very short and simple nine pages in which two were pictures. Very short for like a paper solving a major conjecture. And it really makes you think about what we mean by difficulty in mathematics. Like, do you say, Oh, actually, the problem wasn't difficult because you could solve it so simply? Or do you say like, Well, no, evidently, it was difficult because like the world's top topologist, many, you know, worked on it for 20 years, and nobody could solve it. So therefore it is difficult. Or is it that we need sort of some new category of things that about which it's difficult to figure out that they're not difficult? I mean, this is the computer science formulation, but the sort of the journey to arrive at the simple answer may be difficult. But once you have the answer, it will then appear simple. And I mean, there might be a large category, I hope there's a large set of such solutions, because, you know, once we stand at the end of the scientific process that we're at the very beginning of, or at least it feels like, I hope there's just simple answers to everything. That we'll look and it'll be simple laws that govern the universe, simple explanation of what is consciousness, of what is love, is mortality fundamental to life? What's the meaning of life? Are humans special? Or we're just another sort of reflection of all that is beautiful in the universe in terms of like life forms, all of it is life and just has different, when taken from a different perspective, is all life can seem more valuable or not, but really it's all part of the same thing. All those will have a nice, like two equations, maybe one equation. Why do you think you want those questions to have simple answers? I think just like symmetry and the breaking of symmetry is beautiful somehow. There's something beautiful about simplicity. I think it... So it's aesthetic. It's aesthetic, yeah. But it's aesthetic in the way that happiness is an aesthetic. Like, why is that so joyful that a simple explanation that governs a large number of cases is really appealing? Even when it's not, like obviously we get a huge amount of trouble with that because oftentimes it doesn't have to be connected with reality or even that explanation could be exceptionally harmful. Most of like the world's history that was governed by hate and violence had a very simple explanation at the core that was used to cause the violence and the hatred. So like, we get into trouble with that, but why is that so appealing? And in its nice forms in mathematics, in mathematics, like you look at the Einstein papers, why are those so beautiful? And why is the Andrew Wiles proof of the Fermat's last theorem not quite so beautiful? Like what's beautiful about that story is the human struggle of like the human story of perseverance, of the drama of not knowing if the proof is correct and ups and downs and all of those kinds of things. That's the interesting part. But the fact that the proof is huge and nobody understands, well, from my outsider's perspective, nobody understands what the heck it is, is not as beautiful as it could have been. I wish it was what Fermat originally said, which is, you know, it's not small enough to fit in the margins of this page, but maybe if he had like a full page or maybe a couple of post-it notes, he would have enough to do the proof. What do you make of, if we could take another of a multitude of tangents, what do you make of Fermat's last theorem? Because the statement, there's a few theorems, there's a few problems that are deemed by the world throughout its history to be exceptionally difficult. And that one in particular is really simple to formulate and really hard to come up with a proof for. And it was like taunted as simple by Fermat himself. Is there something interesting to be said about that x to the n plus y to the n equals z to the n for n of three or greater? Is there a solution to this? And then how do you go about proving that? Like, how would you try to prove that? And what do you learn from the proof that eventually emerged by Andrew Wiles? Yeah, so right, let me just say the background, because I don't know if everybody listening knows the story. So you know, Fermat was an early number theorist, at least an early mathematician, those special adjacent didn't really exist back then. He comes up in the book, actually, in the context of a different theorem of his that has to do with testing whether a number is prime or not. So I write about, he was one of the ones who was salty, and like he would exchange these letters where he and his correspondence would like try to top each other and vex each other with questions and stuff like this. But this particular thing, it's called Fermat's Last Theorem, because it's a note he wrote in his copy of the Disquationis Arithmeticae. Like he wrote, here's an equation, it has no solutions, I can prove it, but the proof is like a little too long to fit in this in the margin of this book. He was just like writing a note to himself. Now let me just say historically, we know that Fermat did not have a proof of this theorem. For a long time, people were like, this mysterious proof that was lost, a very romantic story, right? But Fermat later, he did prove special cases of this theorem and wrote about it, talked to people about the problem. It's very clear from the way that he wrote where he can solve certain examples of this type of equation that he did not know how to do the whole thing. He may have had a deep, simple intuition about how to solve the whole thing that he had at that moment, without ever being able to come up with a complete proof. And that intuition maybe lost the time. – Maybe. But I think we, so, but you're right, that that is unknowable. But I think what we can know is that later, he certainly did not think that he had a proof that he was concealing from people. He thought he didn't know how to prove it, and I also think he didn't know how to prove it. Now, I understand the appeal of saying, wouldn't it be cool if this very simple equation, there was a very simple, clever, wonderful proof that you could do in a page or two. And that would be great. But you know what? There's lots of equations like that that are solved by very clever methods like that, including the special cases that Fermat wrote about, the method of descent, which is very wonderful and important. But in the end, those are nice things that you teach in an undergraduate class, and it is what it is, but they're not big. On the other hand, work on the Fermat problem—that's what we like to call it, because it's not really his theorem, because we don't think he proved it. So, I mean, work on the Fermat problem developed this incredible richness of number theory that we now live in today. And not, by the way, just Wiles, Andrew Wiles being the person who, together with Richard Taylor, finally proved this theorem. But you know how you have this whole moment that people try to prove this theorem, and they fail. And there's a famous false proof by LeMay from the 19th century, where Kummer, in understanding what mistake LeMay had made in this incorrect proof, basically understands something incredible, which is that, you know, a thing we know about numbers is that you can factor them, and you can factor them uniquely. There's only one way to break a number up into primes. Like, if we think of a number like 12, 12 is 2 times 3 times 2. I had to think about it. Right? Or it's 2 times 2 times 3. Of course, you can reorder them. But there's no other way to do it. There's no universe in which 12 is something times 5, or in which there's like four 3s in it. Nope, 12 is like two 2s and a 3. Like, that is what it is. And that's such a fundamental feature of arithmetic that we almost think of it like God's law. You know what I mean? It has to be that way. That's a really powerful idea. It's so cool that every number is uniquely made up of other numbers. And like, made up meaning, like, there's these like basic atoms that form molecules that get built on top of each other. I love it. I mean, when I teach, you know, undergraduate number theory, it's like, it's the first really deep theorem that you prove. What's amazing is, you know, the fact that you can factor a number into primes is much easier. Essentially, Euclid knew it, although he didn't quite put it in that way. The fact that you can do it at all. What's deep is the fact that there's only one way to do it. Or however you sort of chop the number up, you end up with the same set of prime factors. And indeed, what people finally understood at the end of the 19th century is that if you work in number systems slightly more general than the ones we're used to, which it turns out are relevant to Fermat, all of a sudden this stops being true. Things get, I mean, things get more complicated. And now, because you were praising simplicity before, you were like, it's so beautiful, unique factorization. It's so great. Like, so when I tell you that in more general number systems, there is no unique factorization, maybe you're like, that's bad. I'm like, no, that's good, because there's like a whole new world of phenomena to study that you just can't see through the lens of the numbers that we're used to. So I'm, I'm for complication. I'm highly in favor of complication. And every complication is like an opportunity for new things to study. And is that the big, kind of one of the big insights for you from Andrew Wiles' proof? Is there interesting insights about the process that you used to prove that sort of resonates with you as a mathematician? Is there an interesting concept that emerged from it? Is there interesting human aspects to the proof? Whether there's interesting human aspects to the proof itself is an interesting question. Certainly, it has a huge amount of richness. Sort of at its heart is an argument of what's called deformation theory, which was in part created by my PhD advisor, Barry Mazur. Can you speak to what deformation theory is? I can speak to what it's like. Sure. How about that? What does it rhyme with? Right. Well, the reason that Barry called it deformation theory, I think he's the one who gave it the name. I hope I'm not wrong in saying this someday. In your book, you have calling different things by the same name as one of the things in the beautiful map that opens the book. Yes. And this is a perfect example. So, this is another phrase of Poincaré, this incredible generator of slogans and aphorisms. He said, mathematics is the art of calling different things by the same name. That very thing we do, right? When we're like this triangle and this triangle, come on, they're the same triangle. They're just in a different place, right? So, in the same way, it came to be understood that the kinds of objects that you study when you study Fermat's last theorem, and let's not even be too careful about what these objects are. I can tell you there are Galois representations in modular forms, but saying those words is not going to mean so much. But whatever they are, they're things that can be deformed, moved around a little bit. And I think the insight of what Andrew and then Andrew and Richard were able to do was to say something like this. A deformation means moving something just a tiny bit, like an infinitesimal amount. If you really are good at understanding which ways a thing can move in a tiny, tiny, tiny infinitesimal amount in certain directions, maybe you can piece that information together to understand the whole global space in which it can move. And essentially, their argument comes down to showing that two of those big global spaces are actually the same, the fabled R equals T part of their proof, which is at the heart of it. And it involves this very careful principle like that. But that being said, what I just said, it's probably not what you're thinking, because what you're thinking when you think, oh, I have a point in space and I move it around like a little tiny bit, you're using the same kind of thing. You're using your notion of distance that's from calculus. We know what it means for two points in the real line to be close together. So yet another thing that comes up in the book a lot is this fact that the notion of distance is not given to us by God. We could mean a lot of different things by distance. And just in the English language, we do that all the time. We talk about somebody being a close relative. It doesn't mean they live next door to you. It means something else. There's a different notion of distance we have in mind. And there are lots of notions of distances that you could use. In the natural language processing community in AI, there might be some notion of semantic distance or lexical distance between two words. How much do they tend to arise in the same context? That's incredibly important for doing autocomplete and machine translation and stuff like that. And it doesn't have anything to do with, are they next to each other in the dictionary? It's a different kind of distance. Okay, ready? In this kind of number theory, there is a crazy distance called the P-adic distance. I didn't write about this that much in the book because even though I love it, it's a big part of my research life, it gets a little bit into the weeds. But your listeners are going to hear about it now. Please. Where? You know, what a normal person says when they say two numbers are close, they say like, you know, their difference is like a small number, like seven and eight are close because their difference is one and one's pretty small. If we were to be what's called a two-adic number theorist, we'd say, oh, two numbers are close if their difference is a multiple of a large power of two. So like, so like one and 49 are close because their difference is 48 and 48 is a multiple of 16, which is a pretty large power of two. Whereas one and two are pretty far away because the difference between them is one, which is not even a multiple of a power of two at all. It's odd. You want to know what's really far from one? Like one and one 64th, because their difference is a negative power of two, two to the minus six. So those points are quite, quite far away. Two to the power of a large n would be two, if that's the difference between two numbers, then they're close. Yeah. So two to a large power is in this metric a very small number and two to a negative power is a very big number. That's two-adic. Okay. I can't even visualize that. It takes practice. It takes practice. If you've ever heard of the Cantor set, it looks kind of like that. So it is crazy that this is good for anything, right? I mean, this just sounds like a definition that someone would make up to torment you. But what's amazing is there's a general theory of distance where you say any definition you make that satisfies certain axioms deserves to be called a distance. And this... See, I'm sorry to interrupt. My brain, you broke my brain. Awesome. 10 seconds ago. Because I'm also starting to map for the two-adic case to binary numbers and, you know, because we romanticize those. Oh, that's exactly the right way to think of it. I was trying to mess with number, you know, trying to see, okay, which ones are close? And then I'm starting to visualize different binary numbers and how they, which ones are close to each other. And, well, I think there's a clear... No, no, it's very similar. That's exactly the way to think of it. It's almost like binary numbers written in reverse. Because in a binary expansion, two numbers are close. A number that's small is like 0.0000 something. Something that's the decimal and it starts with a lot of zeros. In the two-adic metric, a binary number is very small if it ends with a lot of zeros and then the decimal point. Gotcha. So it is kind of like binary numbers written backwards is actually, I should have said, that's what I should have said, Lex. That's a very good metaphor. Okay. But so why is that interesting except for the fact that it's a beautiful kind of framework, different kind of framework, which you think about distances. And you're talking about not just the two-adic, but the generalization of that. Why is that interesting? Yeah, the MEP. And so, because that's the kind of deformation that comes up in Woz's proof. That deformation, we're moving something a little bit, means a little bit in this two-adic sense. Trippy. Okay. No, I mean, it's such a, I mean, I just get excited talking about it. And I just taught this like in the fall semester that... But like reformulating, why is... So you pick a different measure of distance over which you can talk about very tiny changes and then use that to then prove things about the entire thing. Yes. Although, you know, honestly, what I would say, I mean, it's true that we use it to prove things, but I would say we use it to understand things. And then because we understand things better, then we can prove things. But you know, the goal is always the understanding. The goal is not so much to prove things. The goal is not to know what's true or false. I mean, this is the thing I write about in the book Near the End. It's something that is a wonderful, wonderful essay by Bill Thurston, kind of one of the great geometers of our time, who unfortunately passed away a few years ago, called on proof and progress in mathematics. And he writes very wonderfully about how, you know, we're not, it's not a theorem factory where we have a production quota. I mean, the point of mathematics is to help humans understand things. And the way we test that is that we're proving new theorems along the way. That's the benchmark, but that's not the goal. Yeah, but just as a kind of, absolutely. But as a tool, it's kind of interesting to approach a problem by saying, how can I change the distance function? Like what, the nature of distance, because that might start to lead to insights for deeper understanding. Like if I were to try to describe human society by a distance, two people are close if they love each other. And then start to do a full analysis on everybody that lives on earth currently, the 7 billion people. And from that perspective, as opposed to the geographic perspective of distance, and then maybe there could be a bunch of insights about the source of violence, the source of maybe entrepreneurial success or invention or economic success or different systems, communism, capitalism start to, I mean, that's, I guess what economics tries to do, but really saying, okay, let's think outside the box about totally new distance functions that could unlock something profound about the space. Yeah, because think about it. Okay, here's, I mean, now we're going to talk about AI, which you know a lot more about than I do. So just, you know, start laughing uproariously if I say something that's completely wrong. We both know very little relative to what we will know centuries from now. That is a really good, humble way to think about it. I like it. Okay, so let's just go for it. Okay, so I think you'll agree with this, that in some sense, what's good about AI is that we can't test any case in advance. The whole point of AI is to make, or one point of it, I guess, is to make good predictions about cases we haven't yet seen. And in some sense, that's always going to involve some notion of distance, because it's always going to involve somehow taking a case we haven't seen and saying, what cases that we have seen, is it close to, is it like, is it somehow an interpolation between? Now, when we do that, in order to talk about things being like other things, implicitly or explicitly, we're invoking some notion of distance. And boy, we better get it right. Right? If you try to do natural language processing, and your idea of distance between words is how close they are in the dictionary, when you write them in alphabetical order, you are going to get pretty bad translations, right? No, the notion of distance has to come from somewhere else. Yeah, that's essentially what neural networks are doing. That's what word embeddings are doing is coming up with... Yes. In the case of word embeddings, literally, like literally what they are doing is learning a distance function. But those are super complicated distance functions. And it's almost nice to think maybe there's a nice transformation that's simple. Sorry, there's a nice formulation of the distance. Again, with the simple. So you don't... Let me ask you about this. From an understanding perspective, there's the Richard Feynman, maybe attributed to him, but maybe many others, is this idea that if you can't explain something simply that you don't understand it. In how many cases, how often is that true? Do you find there's some profound truth in that? Oh, okay. So you were about to ask, is it true? To which I would say flatly, no. But then you said, you followed that up with, is there some profound truth in it? And I'm like, okay, sure. So there's some truth in it. But it's not true. It's not true. This is your mathematician answer. The truth that is in it is that learning to explain something helps you understand it. But real things are not simple. A few things are, most are not. And I don't, to be honest, I don't, I mean, I don't, we don't really know whether Feynman really said that right or something like that is sort of disputed. But I don't think Feynman could have literally believed that, whether or not he said it. And you know, he was the kind of guy, I didn't know him, but I'm reading his writing, he liked to sort of say stuff, like stuff that sounded good. You know what I mean? So it's, it's totally strikes me as the kind of thing he could have said because he liked the way saying it made him feel. But also knowing that he didn't like literally mean it. Well, I definitely have a lot of friends and I've talked to a lot of physicists and they do derive joy from believing that they can explain stuff simply, or believing it's possible to explain stuff simply, even when the explanation is not actually that simple. Like I've heard people think that the explanation is simple and they do the explanation and I think it is simple, but it's not capturing the phenomena that we're discussing. It's capturing, it somehow maps in their mind, but it's taking as a starting point, as an assumption that there's a deep knowledge and a deep understanding that's actually very complicated. And the simplicity is almost like a poem about the more complicated thing as opposed to a distillation. And I love poems, but a poem is not an explanation. Well, some people might disagree with that, but certainly from a mathematical perspective... No poet would disagree with it. No poet would disagree... You don't think there's some things that can only be described imprecisely? I said explanation. I don't think any poet would say their poem is an explanation. They might say it's a description, they might say it's sort of capturing sort of... Well, some people might say the only truth is like music, right? Not the only truth, but some truth can only be expressed through art. And I mean, that's the whole thing we're talking about, religion and myth. And there's some things that are limited cognitive capabilities, and the tools of mathematics or the tools of physics are just not going to allow us to capture. It's possible consciousness is one of those things. Yes, that is definitely possible. But I would even say, look, I mean, consciousness is a thing about which we're still in the dark as to whether there's an explanation we would understand as an explanation at all. By the way, okay, I gotta give yet one more amazing Poincaré quote, because this guy just never stopped coming up with great quotes. Paul Erdős, another fellow who appears in the book, and by the way, he thinks about this notion of distance of personal affinity, kind of like what you're talking about, that kind of social network and that notion of distance that comes from that. So that's something that Paul Erdős did. Erdős did? Well, he thought about distances in networks. I guess he didn't think about the social network. Oh, that's fascinating. That's how it started, that story of Erdős number. Yeah, okay. It started to distract. But, you know, Erdős was sort of famous for saying, and this is sort of along the lines we were saying, he talked about the book, capital T, capital B, the book. And that's the book where God keeps the right proof of every theorem. So when he saw a proof he really liked, it was like really elegant, really simple, like that's from the book. That's like you found one of the ones that's in the book. He wasn't a religious guy, by the way, he referred to God as the supreme fascist. He was like, but somehow he was like, I don't really believe in God, but I believe in God's book. I mean, it was a yeah. But Poincaré, on the other hand, and by the way, there are other men, Hilda Hudson is one who comes up in this book, she also kind of saw math. She's one of the people who sort of develops the disease model that we now use that we use to sort of track pandemics, this SIR model that sort of originally comes from her work with Ronald Ross, but she was also super, super, super devout. And she also sort of on the other side of the religious coin was like, yeah, math is how we communicate with God. She has a great, all these people are incredibly quotable. She says, you know, math is the truth, the things about mathematics, she's like, they're not the most important of God thoughts, but they're the only ones that we can know precisely. So she's like, this is the one place where we get to sort of see what God's thinking when we do mathematics. Again, not a fan of poetry or music. Some people would say Hendrix is like, some people would say chapter one of that book is mathematics and then chapter two is like classic rock. Right? So like, it's not clear that the... I'm sorry, you just sent me off on a tangent, just imagining like Erdos at a Hendrix concert, like trying to figure out if it was from the book or not. All I, what I was coming to was just to say, but what Poincaré said about this is he's like, you know, if like, this has all worked out in the language of the divine and if a divine being like came down and told it to us, we wouldn't be able to understand it. So it doesn't matter. So Poincaré was of the view that there were things that were sort of like inhumanly complex and that was how they really were. Our job is to figure out the things that are not like that. That are not like that. All this talk of primes got me hungry for primes. You wrote a blog post, the beauty of bounding gaps, a huge discovery about prime numbers and what it means for the future of math. Can you tell me about prime numbers? What the heck are those? What are twin primes? What are prime gaps? What are bounding gaps in primes? What are all these things and what, if anything, or what exactly is beautiful about them? Yeah, so, you know, prime numbers are one of the things that number theorists study the most and have for millennia. They are numbers which can't be factored. And then you say like, like five, and then you're like, wait, I can factor five. Five is five times one. Okay, not like that. That is a factorization. It absolutely is a way of expressing five as a product of two things. But don't you agree there's like something trivial about it? It's something you could do to any number. It doesn't have content the way that if I say that 12 is six times two or 35 is seven times five, I've really done something to it. I've broken up. So those are the kind of factorizations that count. And the number that doesn't have a factorization like that is called prime, except historical side note, one, which at some times in mathematical history has been deemed to be a prime, but currently is not. And I think that's for the best. But I bring it up only because sometimes people think that, you know, these definitions are kind of, if we think about them hard enough, we can figure out which definition is true. No, there's just an artifact of mathematics. So yeah, so it's a question which definition is best for us, for our purposes. Well, those edge cases are weird, right? So it can't be, it doesn't count when you use yourself as a number or one as part of the factorization or as the entirety of the factorization. So you somehow get to the meat of the number by factorizing it. And that seems to get to the core of all of mathematics. Yeah, you take any number and you factorize it until you can factorize no more. And what you have left is some big pile of primes. I mean, by definition, when you can't factor anymore, when you're done, when you can't break the numbers up anymore, what's left must be prime. You know, 12 breaks into two and two and three. So these numbers are the atoms, the building blocks of all numbers. And there's a lot we know about them, but there's much more that we don't know. I'll tell you the first few. There's two, three, five, seven, 11. By the way, they're all going to be odd from then on, because if they were even, I could factor two out of them. But it's not all the odd numbers. Nine isn't prime because it's three times three. 15 isn't prime because it's three times five, but 13 is. Where were we? Two, three, five, seven, 11, 13, 17, 19. Not 21, but 23 is, et cetera, et cetera. Okay, so you could go on. How high could you go if we were just sitting here? By the way, your own brain. Oh. Continuous, without interruption. Would you be able to go over 100? I think so. There's always those ones that trip people up. There's a famous one, the Grotendieck prime, 57. Alexander Grotendieck, the great algebraic geometer, was giving some lecture involving a choice of a prime in general. And somebody said, can't you just choose a prime? And he said, okay, 57, which is in fact not prime. It's three times 19. Oh, damn. But it was like, I promise you in some circles, it's a funny story. Okay. It's not that. But there's a humor in it. Yes, I would say over 100, I definitely don't remember. Like 107, I think. I'm not sure. Okay. So is there a category of like fake primes that are easily mistaken to be prime? Like 57, I wonder. Yeah, so I would say 57 and 51 are definitely like prime offenders. Oh, I didn't do that on purpose. Oh, well done. Didn't do it on purpose. Anyway, they're definitely ones that people, or 91 is another classic seven times 13. It really feels kind of prime, doesn't it? But it is not. Yeah. So there's also, by the way, but there's also an actual notion of pseudo prime, which is a thing with a formal definition, which is not a psychological thing. It is a prime which passes a primality test devised by Fermat, which is a very good test, which if a number fails this test, it's definitely not prime. And so there was some hope that, oh, maybe if a number passes the test, then it definitely is prime. That would give a very simple criterion for primality. Unfortunately, it's only perfect in one direction. So there are numbers, I want to say 341 is the smallest, which pass the test, but are not prime 341. Is this test easily explainable or no? Yes, actually. Ready? Let me give you the simplest version of it. You can dress it up a little bit, but here's the basic idea. I take the number, the mystery number, I raise two to that power. So let's say your mystery number is six. Are you sorry you asked me? Are you ready to follow? No, you're breaking my brain again, but yes. Okay, let's do it. We're going to do a live demonstration. Let's say your number is six. So I'm going to raise two to the sixth power. Okay, so if I were working, I'd be like, that's two cubed squared. That's eight times eight. So that's 64. Now we're going to divide by six, but I don't actually care what the quotient is, only the remainder. So let's see, 64 divided by six is, well, there's a quotient of 10, but the remainder is four. So you failed because the answer has to be two. For any prime, let's do it with five, which is prime. Two to the fifth is 32, divide 32 by five, and you get six with a remainder of two. With a remainder of two. The remainder of two. For seven, two to the seventh is 128, divide that by seven, and let's see, I think that's seven times 14. Is that right? No. Seven times 18 is 126 with a remainder of two, right? 128 is a multiple of seven plus two. So if that remainder is not two, then that's definitely not prime. Then it's definitely not prime. And then if it is, it's likely a prime, but not for sure. It's likely a prime, but not for sure. And there's actually a beautiful geometric proof, which is in the book, actually. That's one of the most granular parts of the book, because it's such a beautiful proof, I could not give it. So you draw a lot of opal and pearl necklaces and spin them. That's the geometric nature of this proof of Fermat's little theorem. So yeah, so with pseudo primes, there are primes that are faking it, they pass that test, but there are numbers that are faking it, they pass that test, but are not actually prime. But the point is, there are many, many, many theorems about prime numbers. Are there, like there's a bunch of questions to ask. Is there an infinite number of primes? Can we say something about the gap between primes as the numbers grow larger and larger and larger and so on? Yeah, it's a perfect example of your desire for simplicity in all things. You know what would be really simple? If there was only finitely many primes, and then there would be this finite set of atoms that all numbers would be built up. That would be very simple and good in certain ways, but it's completely false. And number theory would be totally different if that were the case. It's just not true. In fact, this is something else that Euclid knew. So this is a very, very old fact, like much before, long before we had anything like modern number theory. Their primes are infinite. Their primes that there are, that write the infinite numbers. There's an infinite number of primes. So what about the gaps between the primes? Right. So one thing that people recognized and really thought about a lot is that the primes, on average, seem to get farther and farther apart as they get bigger and bigger. In other words, it's less and less common. Like I already told you of the first 10 numbers, 2, 3, 5, 7, 4 of them are prime. That's a lot, 40%. If I looked at, you know, 10 digit numbers, no way would 40% of those be prime. Being prime would be a lot rarer, in some sense, because there's a lot more things for them to be divisible by. That's one way of thinking of it. It's a lot more possible for there to be a factorization because there's a lot of things you can try to factor out of it. As the numbers get bigger and bigger, primality gets rarer and rarer. And the extent to which that's the case, that's pretty well understood. But then you can ask more fine-grained questions. And here is one. A twin prime is a pair of primes that are two apart, like 3 and 5, or like 11 and 13, or like 17 and 19. And one thing we still don't know is, are there infinitely many of those? We know on average they get farther and farther apart, but that doesn't mean there couldn't be like occasional folks that come close together. And indeed, we think that there are. And one interesting question, I mean, this is... Because I think you might say, well, how could one possibly have a right to have an opinion about something like that? We don't have any way of describing a process that makes primes. Sure, you can look at your computer and see a lot of them, but the fact that there's a lot, why is that evidence that there's infinitely many? Maybe I can go on my computer and find 10 million. Well, 10 million is pretty far from infinity, right? So how is that evidence? There's a lot of things. There's a lot more than 10 million atoms. That doesn't mean there's infinitely many atoms in the universe, right? I mean, on most people's physical theories, there's probably not, as I understand it. Okay, so why would we think this? The answer is that it turns out to be incredibly productive and enlightening to think about primes as if they were random numbers, as if they were randomly distributed according to a certain law. Now, they're not. They're not random. There's no chance involved. It's completely deterministic whether a number is prime or not. And yet, it just turns out to be phenomenally useful in mathematics to say, even if something is governed by a deterministic law, let's just pretend it wasn't. Let's just pretend that they were produced by some random process and see if the behavior is roughly the same. And if it's not, maybe change the random process. Maybe make the randomness a little bit different and tweak it and see if you can find a random process that matches the behavior we see. And then maybe you predict that other behaviors of the system are like that of the random process. And so that's kind of like, it's funny, because I think when you talk to people about the twin prime conjecture, people think you're saying, wow, there's like some deep structure there that like makes those primes be like close together again and again. And no, it's the opposite of deep structure. What we say when we say we believe the twin prime conjecture is that we believe the primes are like sort of strewn around pretty randomly. And if they were, then by chance you would expect there to be infinitely many twin primes. And we're saying, yeah, we expect them to behave just like they would if they were random dirt. You know, the fascinating parallel here is I just got a chance to talk to Sam Harris, and he uses the prime numbers as an example. Often, I don't know if you're familiar with who Sam is. He uses that as an example of there being no free will. Wait, where does he get this? Well, he just uses as an example of it might seem like this is a random number generator, but it's all like formally defined. So if we keep getting more and more primes, then like that might feel like a new discovery, and that might feel like a new experience, but it's not. It was always written in the cards. But it's funny that you say that, because a lot of people think of like randomness, the fundamental randomness within the nature of reality might be the source of something that we experience as free will. And you're saying it's like useful to look at prime numbers as a random process in order to prove stuff about them. But fundamentally, of course, it's not a random process. Well, not in order to prove some stuff about them so much as to figure out what we expect to be true and then try to prove that. Because here's what you don't want to do, try really hard to prove something that's false. That makes it really hard to prove the thing if it's false. So you certainly want to have some heuristic ways of making good guesses about what's true. So yeah, here's what I would say. You're going to be imaginary Sam Harris now. You're talking about prime numbers, and you're like, but prime numbers are completely deterministic. And I'm saying, well, let's treat them like a random process. And then you say, but you're just saying something that's not true. They're not a random process, they're deterministic. And I'm like, okay, great. You hold to your insistence that it's not a random process. Meanwhile, I'm generating insight about the primes that you're not because I'm willing to sort of pretend that there's something that they're not in order to understand what's going on. Yeah, so it doesn't matter what the reality is. What matters is what framework of thought results in the maximum number of insights. Yeah, because I feel, look, I'm sorry, but I feel like you have more insights about people if you think of them as like, beings that have wants and needs and desires and do stuff on purpose. Even if that's not true, you still understand better what's going on by treating them in that way. Don't you find, look, you work on machine learning, don't you find yourself sort of talking about what the machine is trying to do? In a certain instance, do you not find yourself drawn to that language? Well, I- It knows this, it's trying to do that, it's learning that. I'm certainly drawn to that language to the point where I receive quite a bit of criticisms for it. Because I, you know, like- Oh, I'm on your side, man. Yeah, so especially in robotics, I don't know why, but robotics people don't like to name their robots, or they certainly don't like to gender their robots, because the moment you gender a robot, you start to anthropomorphize. If you say he or she, you start to, in your mind, construct like a life story in your mind. You can't help it. You create like a humorous story to this person, you start to- This person, this robot, you start to project your own- But I think that's what we do to each other. I think that's actually really useful for the engineering process, especially for human-robot interaction. And yes, for machine learning systems, for helping you build an intuition about a particular problem. It's almost like asking this question, you know, when a machine learning system fails in a particular edge case, asking, like, what were you thinking about? Like, asking, like, almost like when you're talking about, to a child who just did something bad, you want to understand, like, what was, how did they see the world? Maybe there's a totally new- Maybe you're the one that's thinking about the world incorrectly. And yeah, that anthropomorphization process, I think, is ultimately good for insight. And the same as, I agree with you, I tend to believe about free will as well. Let me ask you a ridiculous question, if it's okay. Of course. I've just recently, most people go on, like, rabbit hole, like, YouTube things, and I went on a rabbit hole off and do of Wikipedia. And I found a page on finitism, ultra finitism, and intuitionism, or- I forget what it's called. Yeah, intuitionism. Intuitionism. That seemed pretty- that seemed pretty interesting. I have it on my to-do list to actually, like, look into, like, is there people who, like, formally- like, real mathematicians are trying to argue for this. But the belief there, I think, let's say finitism, that infinity is fake. Meaning, infinity may be, like, a useful hack for certain, like, a useful tool in mathematics, but it really gets us into trouble, because there's no infinity in the real world. Maybe I'm sort of not expressing that fully correctly, but basically saying, like, there's things that are- once you add into mathematics things that are not provably within the physical world, you're starting to inject- to corrupt your framework of reason. What do you think about that? I mean, I think- okay, so first of all, I'm not an expert, and I couldn't even tell you what the difference is between those three terms, finitism, ultra finitism, and intuitionism, although I know they're related, I tend to associate them with the Netherlands in the 1930s. Okay, I'll tell you, can I just quickly comment, because I read the Wikipedia page? The difference in ultra- That's, like, the ultimate sentence of the modern age. Can I just comment, because I read the Wikipedia page? That sums up our moment. Bro, I'm basically an expert. Ultra- ultra finitism- so, finitism says that the only infinity you're allowed to have is that the natural numbers are infinite. So, like, those numbers are infinite. So, like, one, two, three, four, five, the integers are infinite. The ultra-finitism says, nope, even that infinity is fake. That's- I'll bet ultra-finitism came second. I'll bet it's, like, when there's, like, a hardcore scene, and then one guy's, like, oh, now there's a lot of people in this scene. I have to find a way to be more hardcore than the hardcore people. It's all back to the emo talk. Yeah. Okay, so is there any- are you ever- because I'm often uncomfortable with infinity, like, psychologically. I, you know, I have trouble when that sneaks in there. It's because it works so damn well, I get a little suspicious, because it could be almost like a crutch or an oversimplification that's missing something profound about reality. Well, so, first of all, okay, if you say, like, is there, like, a serious way of doing mathematics that doesn't really treat infinity as a real thing, or maybe it's kind of agnostic and it's like, I'm not really going to make a firm statement about whether it's a real thing or not. Yeah, that's called most of the history of mathematics, right? So it's only after Cantor, right, that we really are sort of, okay, we're going to, like, have a notion of, like, the cardinality of an infinite set and, like, do something that you might call, like, the modern theory of infinity. That said, obviously, everybody was drawn to this notion. And no, not everybody was comfortable with it. Look, I mean, this is what happens with Newton, right? I mean, so Newton understands that to talk about tangents and to talk about instantaneous velocity, he has to do something that we would now call taking a limit, right? The fabled dy over dx, if you sort of go back to your calculus class, for those who've taken calculus, remember this mysterious thing. And, you know, what is it? What is it? Well, he'd say, like, well, it's like you sort of divide the length of this line segment by the length of this other line segment, and then you make them a little shorter, and you divide again, and then you make them a little shorter, and you divide again, and then you just keep on doing that until they're infinitely short, and then you divide them again. These quantities that are, like, they're not zero, but they're also smaller than any actual number, these infinitesimals. Well, people were queasy about it, and they weren't wrong to be queasy about it, right? From a modern perspective, it was not really well-formed. There's this very famous critique of Newton by Bishop Berkeley, where he says, like, what these things you define, like, you know, they're not zero, but they're smaller than any number. Are they the ghosts of departed quantities? That was this, like, ultra-par. And on the one hand, he was right. It wasn't really rigorous by modern standards. On the other hand, like, Newton was out there doing calculus, and other people were not, right? So I think a sort of intuitionist view, for instance, I would say would express serious doubt. And by the way, it's not just infinity. It's not it's like saying, I think we would express serious doubt that, like, the real numbers exist. Now, most people are comfortable with the real numbers. Well, computer scientists with floating point number, I mean, floating point arithmetic. That's a great point, actually. I think, in some sense, this flavor of doing math, saying, we shouldn't talk about things that we cannot specify in a finite amount of time, there's something very computational in flavor about that. And it's probably not a coincidence that it becomes popular in the 30s and 40s, which is also like, kind of like the dawn of ideas about formal computation, right? You probably know the timeline better than I do. Sorry, what becomes popular? These ideas that maybe we should be doing math in this more restrictive way where even a thing that, you know, because look, the origin of all this is like, number represents a magnitude, like the length of a line. So, I mean, the idea that there's a continuum, there's like, is pretty old, but that, you know, just because something is old doesn't mean we can't reject it if we want to. Well, a lot of the fundamental ideas in computer science, when you talk about the complexity of problems, to Turing himself, they rely on infinity as well. The ideas that kind of challenge that, the whole space of machine learning, I would say, challenges that. It's almost like the engineering approach to things, like the floating point arithmetic. The other one that, back to John Conway, that challenges this idea, I mean, maybe to tie in the ideas of deformation theory and limits to infinity, is this idea of cellular automata. With John Conway looking at the game of life, Stephen Wolfe from his work, that I've been a big fan of for a while, of cellular automata. I was wondering if you have ever encountered these kinds of objects, you ever looked at them as a mathematician, where you have very simple rules of tiny little objects that when taken as a whole, create incredible complexities, but are very difficult to analyze, very difficult to make sense of, even though the one individual object, one part, it's like what we were saying about Andrew Wiles, you can look at the deformation of a small piece to tell you about the whole. It feels like with cellular automata, or any kind of complex systems, it's often very difficult to say something about the whole thing, even when you can precisely describe the operation of the local neighborhoods. Yeah, I mean, I love that subject. I haven't really done research in it myself, I've played around with it. I'll send you a fun blog post I wrote where I made some cool texture patterns from cellular automata. And those are really always compelling, it's like you create simple rules and they create some beautiful textures, it doesn't make any sense. Actually, did you see there was a great paper, I don't know if you saw this, like a machine learning paper. I don't know if you saw the one I'm talking about, where they were learning the textures, like let's try to reverse engineer and learn a cellular automaton that can produce a texture that looks like this from the images. Very cool. And as you say, the thing you said is I feel the same way when I read machine learning papers, that what's especially interesting is the cases where it doesn't work. What does it do when it doesn't do the thing that you tried to train it to do? That's extremely interesting. Yeah, that was a cool paper. So yeah, so let's start with a game of life. Let's start with John Conway. So Conway... So yeah, so let's start with John Conway again. I don't know, from my outsider's perspective, there's not many mathematicians that stand out throughout the history of the 20th century. He's one of them. I feel like he's not sufficiently recognized. I think he's pretty recognized. Okay, well... I mean, he was a full professor at Princeton for most of his life, he was sort of in certainly the pinnacle of... Yeah, but I found myself every time I talk about Conway and how excited I am about him, I have to constantly explain to people who he is. And that's always a sad sign to me. But that's probably true for a lot of mathematicians. I was about to say, I feel like you have a very elevated idea of how famous... This is what happens when you grow up in the Soviet Union, or you think the mathematicians are like very, very famous. Yeah, but I'm not actually so convinced at a tiny tangent that that shouldn't be so. I mean, it's not obvious to me that that's one of the... Like, if I were to analyze American society, that perhaps elevating mathematical and scientific thinking to a little bit higher level would benefit the society. Well, both in discovering the beauty of what it is to be human, and for actually creating cool technology, better iPhones. But anyway, John Conway. Yeah, and Conway is such a perfect example of somebody whose humanity was, and his personality was like wound up with his mathematics, right? It's what's not sometimes I think people who are outside the field think of mathematics as this kind of like, cold thing that you do separate from your existence as a human being. No way your personality is in there, just as it would be in like a novel you wrote, or a painting you painted, or just like the way you walk down the street, like it's in there, it's you doing it. And Conway was certainly a singular personality. I think anybody would say that he was playful, like everything was a game to him. Now, what you might think I'm going to say, and it's true, is that he sort of was very playful in his way of doing mathematics. But it's also true, it went both ways. He also sort of made mathematics out of games. He like looked at, he was a constant inventor of games with like crazy names. And then he was sort of analyzed those games mathematically, to the point that he and then later collaborating with Knuth, like, you know, created this number system, the serial numbers, in which actually each number is a game. There's a wonderful book about this called, I mean, there are his own books, and then there's like a book that he wrote with Burlekemp and Guy called Winning Ways, which is such a rich source of ideas. And he too kind of has his own crazy number system, in which, by the way, there are these infinitesimals, the ghosts of departed quantities, they're in there. They're in there, now, not as ghosts, but as like certain kind of two player games. So, you know, he was a guy, so I knew him when I was a postdoc. And I knew him at Princeton, and our research overlapped in some ways. Now it was on stuff that he had worked on many years before, the stuff I was working on kind of connected with stuff in group theory, which somehow keeps seems to keep coming up. And so I often would like sort of ask him a question, I would sort of come upon him in the common room, and I would ask him a question about something. And just anytime you turned him on, you know what I mean? You sort of asked a question, it was just like turning a knob and winding him up, and he would just go and you would get a response that was like, so rich and went so many places and taught you so much, and usually had nothing to do with your question. Usually your question was just a prompt to him, you couldn't count on actually getting the question. He had those brilliant curious minds, even at that age. Yeah, it was definitely a huge loss. But on his Game of Life, which was I think he developed in the 70s, as almost like a side thing, a fun little experiment. Yeah, the Game of Life is this, it's a very simple algorithm. It's not a very complicated algorithm. It's a very simple algorithm. It's not really a game per se, in the sense of the kinds of games that he liked, where people played against each other. And but essentially, it's a game that you play with marking little squares on a sheet of graph paper. And in the 70s, I think he was like, literally doing it with like a pen on graph paper, you have some configuration of squares, some of the squares in the graphic are filled in, and some of the squares are not. And then there's a rule, a single rule that tells you at the next stage, which squares are filled in, and which squares are not. Sometimes an empty square gets filled in, that's called birth. Sometimes a square that's filled in gets erased, that's called death. And there's rules for which squares are born and which squares die. It's the rule is very simple, you can write it on one line. And then the great miracle is that you can start from some very innocent looking, little small set of boxes and get these results of incredible richness. And of course, nowadays, you don't do it on paper. Nowadays, you do it on a computer. There's actually a great iPad app called Gali, which I really like that has like, Conway's original rule and like, gosh, like hundreds of other variants. And it's lightning fast. So you can just be like, I want to see 10,000 generations of this rule play out like faster than your eye can even follow. And it's like, amazing. So I highly recommend it if this is at all intriguing to you getting Gali on your iOS device. And you can do this kind of process, which I really enjoy doing, which is almost from like putting a Darwin hat on or a biologist hat on and doing analysis of a higher level of abstraction, like the organisms that spring up, because there's different kinds of organisms, like you can think of them as species and they interact with each other. They can, there's gliders, they shoot different, there's like, things that can travel around, there's things that can, glider guns, that can generate those gliders. They're, you can use the same kind of language as you would about describing a biological system. So it's a wonderful laboratory. And it's kind of a rebuke to someone who doesn't think that like very, very rich, complex structure can come from very simple underlying laws. Like, it definitely can. Now, here's what's interesting. If you just pick like some random rule, you wouldn't get interesting complexity. I think that's one of the most interesting things of these, one of the most interesting features of this whole subject, that the rules have to be tuned just right, like a sort of typical rule set doesn't generate any kind of interesting behavior. But some do. And I don't think we have a clear way of understanding which do and which don't. I don't, maybe Stephen thinks he does. I don't know. No, no, it's a giant mystery. What Stephen Wolfram did is, now there's a whole interesting aspect to the fact that he's a little bit of an outcast in the mathematics and physics community, because he's so focused on a particular, his particular work. I think if you put ego aside, which I think, unfairly, some people are not able to look beyond, I think his work is actually quite brilliant. But what he did is exactly this process of Darwin-like exploration. He's taking these very simple ideas and writing a thousand page book on them, meaning like, let's play around with this thing. Let's see. And can we figure anything out? Spoiler alert, no, we can't. In fact, he does a challenge. I think it's like rule 30 challenge, which is quite interesting, just simply for machine learning people, for mathematics people, is can you predict the middle column? For his, it's a 1D cellular automata. Can you, generally speaking, can you predict anything about how a particular rule will evolve, just in the future? Very simple. Just looking at one particular part of the world, just zooming in on that part, you know, 100 steps ahead, can you predict something? And the challenge is to do that kind of prediction so far as nobody's come up with an answer. But the point is, we can't, we don't have tools, or maybe it's impossible, or, I mean, he has these kind of laws of irreducibility that he refers to, but it's poetry. It's like, we can't prove these things. It seems like we can't. That's the basic, it almost sounds like ancient mathematics or something like that, where you're like, the gods will not allow us to predict the cellular automata. But that's fascinating that we can't. I'm not sure what to make of it. And there's power to calling this particular set of rules Game of Life, as Conway did, because, not exactly sure, but I think he had a sense that there's some core ideas here that are fundamental to life, to complex systems, to the way life emerged on Earth. I'm not sure I think Conway thought that. It's something that, I mean, Conway always had a rather ambivalent relationship with the Game of Life, because I think he saw it as, it was certainly the thing he was most famous for in the outside world. And I think that his view, which is correct, is that he had done things that were much deeper mathematically than that. And I think it always aggrieved him a bit that he was like the Game of Life guy, when he proved all these wonderful theorems and created all these wonderful games, created the serial numbers. He was a very tireless guy who just did an incredibly variegated array of stuff. So he was exactly the kind of person who you would never want to reduce to one achievement, you know what I mean? Let me ask about group theory. You mentioned it a few times. What is group theory? What is an adjacent idea from group theory that you find beautiful? Well, so I would say group theory sort of starts as the general theory of symmetry, is that, you know, people looked at different kinds of things and said, like, as we said, like, oh, it could have maybe all there is is symmetry from left to right, like a human being, right? That's roughly bilateral, bilaterally symmetric, as we say. So, so there's two symmetries. And then you're like, well, wait, didn't I say there's just one there's just left to right? Well, we always count the symmetry of doing nothing. We always count the symmetry that's like, there's flip and don't flip. Those are the two configurations that you can be in. So there's two. You know, something like a rectangle is bilaterally symmetric, you can flip it left to right, but you can also flip it top to bottom. So there's actually four symmetries. There's do nothing, flip it left to right, and flip it top to bottom or do both of those things. A square, there's even more, because now you can rotate it, you can rotate it by 90 degrees. So you can't do that. That's not a symmetry of the rectangle. If you try to rotate it 90 degrees, you get a rectangle oriented in a different way. So a person has two symmetries, a rectangle for a square, eight different kinds of shapes have different numbers of symmetries. And the real observation is that that's just not like a set of things. They can be combined, you do one symmetry, then you do another. The result of that is some third symmetry. So a group really abstracts away this notion of saying it's just some collection of transformations you can do to a thing where you combine any two of them to get a third. So you know, a place where this comes up in computer science is in sorting, because the ways of permuting a set, the ways of taking sort of some set of things you have on the table and putting them in a different order, shuffling a deck of cards, for instance, those are the symmetries of the deck. And there's a lot of them. There's not two, there's not four, there's not eight, think about how many different orders a deck of card can be in each one of those is the result of applying a symmetry to the original deck. So a shuffle is a symmetry, right? You're reordering the cards. If I shuffle and then you shuffle, the result is some other kind of thing you might call a double shuffle, which is a more complicated symmetry. So group theory is kind of the study of the general abstract world that encompasses all these kinds of things. But then of course, lots of things that are way more complicated than that. Like infinite groups of symmetries, for instance. So they can be infinite, huh? Oh yeah. Okay. Well, okay, ready? Think about the symmetries of the line. You're like, okay, I can reflect it left to right, you know, around the origin. Okay, but I could also reflect it left to right, grabbing somewhere else, like at one or two or pi or anywhere. Or I could just slide it some distance. That's a symmetry. Slide it five units over. So there's clearly infinitely many symmetries of the line. That's an example of an infinite group of symmetries. Is it possible to say something that kind of captivates, keeps being brought up by physicists, which is gauge theory, gauge symmetry, as one of the more complicated type of symmetries? Is there an easy explanation of what the heck it is? Is that something that comes up on your mind at all? Well, I'm not a mathematical physicist, but I can say this. It is certainly true that it has been a very useful notion in physics to try to say, like, what are the symmetry groups of the world? Like, what are the symmetries under which things don't change, right? So we just, I think we talked a little bit earlier about, it should be a basic principle that a theorem that's true here is also true over there. Yes. And same for a physical law, right? I mean, if gravity is like this over here, it should also be like this over there. Okay. What that's saying is we think translation in space should be a symmetry. All the laws of physics should be unchanged if the symmetry we have in mind is a very simple one like translation. And so then there becomes a question, like, what are the symmetries of the actual world with its physical laws? And one way of thinking, this is an oversimplification, but like one way of thinking of this big shift from before Einstein to after is that we just changed our idea about what the fundamental group of symmetries were. So that things like the Lorenz contraction, things like these bizarre relativistic phenomena, or Lorenz would have said, oh, to make this work, we need a thing to change its shape if it's moving nearly the speed of light. Well, under the new framework, it's much better. No, it wasn't changing its shape. You were just wrong about what counted as a symmetry. Now that we have this new group, the so-called Lorenz group, now that we understand what the symmetries really are, we see it was just an illusion that the thing was changing its shape. Yeah, so you can then describe the sameness of things under this weirdness that is general relativity, for example. Yeah, yeah, still, I wish there was a simpler explanation of like exact, I mean, gauge symmetries, pretty simple general concept about rulers being deformed. I've actually just personally been on a search, not a very rigorous or aggressive search, but for something I personally enjoy, which is taking complicated concepts and finding the sort of minimal example that I can play around with, especially programmatically. That's great. I mean, this is what we try to train our students to do, right? I mean, in class, this is exactly what, this is like best pedagogical practice. I do hope there's simple explanation, especially like I've, in my sort of drunk random walk, drunk walk, whatever that's called, sometimes stumble into the world of topology. And like quickly, like, you know, when you like go into a party and you realize this is not the right party for me. So whenever I go into topology, it's like so much math everywhere. I don't even know what, it feels like, this is me like being a hater, is I think there's way too much math. Like there are two, the cool kids who just want to have like everything is expressed through math because they're actually afraid to express stuff simply through language. That's my hater formulation of topology. But at the same time, I'm sure that's very necessary to do sort of rigorous discussion, but I feel like- But don't you think that's what gauge symmetry is like? I mean, it's not a field I know well, but it certainly seems like- Yes, it is like that. But my problem with topology, okay, and even like differential geometry is like, you're talking about beautiful things. Like if they could be visualized, it's open question if everything could be visualized, but you're talking about things that could be visually stunning, I think. But they are hidden underneath all of that math. Like if you look at the papers that are written in topology, if you look at all the discussions on Stack Exchange, they're all math dense, math heavy. And the only kind of visual things that emerge every once in a while is like something like a Mobius strip. Every once in a while, some kind of simple visualizations. Well, there's the vibration, there's the hop vibration, or all of those kinds of things that somebody, some grad student from like 20 years ago wrote a program in Fortran to visualize it, and that's it. And it just, you know, it makes me sad because those are visual disciplines, just like computer vision is a visual discipline. So you can provide a lot of visual examples. I wish topology was more excited and in love with visualizing some of the ideas. I mean, you could say that, but I would say for me, a picture of the hop vibration does nothing for me. Whereas like when you're like, oh, it's like about the Quaternions, it's like a subgroup of the Quaternions, and I'm like, oh, so now I see what's going on. Like, why didn't you just say that? Why were you like showing me this stupid picture instead of telling me what you were talking about? Oh, yeah, yeah. I'm just saying, no, but it goes back to what you were saying about teaching that like people are different in what they'll respond to. So I think there's no, I mean, I'm very opposed to the idea that there's one right way to explain things. I think there's a huge variation in like, you know, our brains like have all these like weird, like hooks and loops. And it's like very hard to know like what's going to latch on and it's not going to be the same thing for everybody. So I think monoculture is bad, right? I think that's and I think we're agreeing on that point that like, it's good that there's like a lot of different ways in and a lot of different ways to describe these ideas, because different people are going to find different things illuminating. But that said, I think there's a lot to be discovered when you force little like silos of brilliant people to kind of find a middle ground or like, aggregate or come together in a way. So there's like people that do love visual things. I mean, there's a lot of disciplines, especially in computer science that they're obsessed with visualizing, visualizing data, visualizing neural networks. I mean, neural networks themselves are fundamentally visual. There's a lot of work in computer vision that's very visual. And then coming together with some folks that were like deeply rigorous and are like totally lost in multi-dimensional space where it's hard to even bring them back down to 3D. They're very comfortable in this multi-dimensional space. So forcing them to kind of work together to communicate, because it's not just about public communication of ideas. It's also, I feel like when you're forced to do that public communication, like you did with your book, I think deep, profound ideas can be discovered that's like applicable for research and for science. Like there's something about that simplification, or not simplification, but distillation or condensation or whatever the hell you call it, compression of ideas that somehow actually stimulates creativity. And I'd be excited to see more of that in the mathematics community. Can you- Look, let me make a crazy metaphor. Maybe it's a little bit like the relation between prose and poetry, right? I mean, you might say like, why do we need anything more than prose? You're trying to convey some information. So you just like say it. Well, poetry does something, right? It's sort of, you might think of it as a kind of compression. Of course, not all poetry is compressed. Like not all, some of it is quite baggy, but like you are kind of, often it's compressed, right? A lyric poem is often sort of like a compression of what would take a long time and be complicated to explain in prose into sort of a different mode that is going to hit in a different way. We talked about Poincaré conjecture. There's a guy, he's Russian, Grigori Pearlman. He proved Poincaré's conjecture. If you can comment on the proof itself, if that stands out to you as something interesting, or the human story of it, which is he turned down the Fields Medal for the proof. Is there something you find inspiring or insightful about the proof itself, or about the man? Yeah, I mean, one thing I really like about the proof, and partly that's because it's sort of a thing that happens again and again in this book. I mean, I'm writing about geometry and the way it sort of appears in all these kind of real world problems. But it happens so often that the geometry you think you're studying is somehow not enough. You have to go one level higher in abstraction and study a higher level of geometry. And the way that plays out is that, you know, Poincaré asks a question about a certain kind of three-dimensional object. Is it the usual three-dimensional space that we know, or is it some kind of exotic thing? And so, of course, this sounds like it's a question about the geometry of the three-dimensional space. But no, but no, Perelman understands. And by the way, in a tradition that involves Richard Hamilton and many other people, like most really important mathematical advances, this doesn't happen alone. It doesn't happen in a vacuum. It happens as the culmination of a program that involves many people. Same with Wiles, by the way. I mean, we talked about Wiles, and I want to emphasize that starting all the way back with Kummer, who I mentioned in the 19th century, but Gerhard Frey and Maser and Ken Ribbitt and like many other people are involved in building the other pieces of the arch before you put the keystone in. We stand on the shoulders of giants. Yes. So, what is this idea? The idea is that, well, of course, the geometry of the three-dimensional object itself is relevant, but the real geometry you have to understand is the geometry of the space of all three-dimensional geometries. Whoa. You're going up a higher level. Because when you do that, you can say, now let's trace out a path in that space. There's a mechanism called Ricci flow. And again, we're outside my research area. So, for all the geometric analysts and differential geometers out there listening to this, I'm doing my best and I'm roughly saying it. So, the Ricci flow allows you to say like, okay, let's start from some mystery three-dimensional space, which Poincaré would conjecture is essentially the same thing as our familiar three-dimensional space, but we don't know that. And now you let it flow. You sort of like let it move in its natural path according to some almost physical process and ask where it winds up. And what you find is that it always winds up. You've continuously deformed it. There's that word deformation again. And what you can prove is that the process doesn't stop until you get to the usual three-dimensional space. And since you can get from the mystery thing to the standard space by this process of continually changing and never kind of having any sharp transitions, then the original shape must have been the same as the standard shape. That's the nature of the proof. Now, of course, it's incredibly technical. I think, as I understand it, I think the hard part is proving that the favorite word of AI people, you don't get any singularities along the way. But of course, in this context, singularity just means acquiring a sharp kink. It just means becoming non-smooth at some point. So. Just saying something interesting about formal about the smooth trajectory through this weird space. Yeah. But yeah, so what I like about it is that it's just one of many examples of where it's not about the geometry you think it's about. It's about the geometry of all geometries, so to speak. And it's only by kind of like being jerked out of Flatland, right? Same idea. It's only by sort of seeing the whole thing globally at once that you can really make progress on understanding like the one thing you thought you were looking at. It's a romantic question, but what do you think about him turning down the Fields Medal? Is that just our Nobel Prizes and Fields Medals just the cherry on top of the cake and really math itself, the process of curiosity of pulling at the string of the mystery before us? That's the cake. And then the awards are just icing and clearly I've been fasting and I'm hungry. But do you think it's tragic or just a little curiosity that he turned down the medal? Well, it's interesting because on the one hand, I think it's absolutely true that right in some kind of like vast spiritual sense, like awards are not important, like not important the way that sort of like understanding the universe is important. On the other hand, most people who are offered that prize accept it. So there's something unusual about his choice there. I wouldn't say I see it as tragic. I mean, maybe if I don't really feel like I have a clear picture of why he chose not to take it. I mean, he's not alone in doing things like this. People sometimes turn down prizes for ideological reasons. Probably more often in mathematics. I mean, I think I'm right in saying that Peter Schultz turned down sort of some big monetary prize because he just, you know, I mean, I think at some point you have plenty of money. And maybe you think it sends the wrong message about what the point of doing mathematics is. I do find that there's most people accept, you know, most people give it a prize. Most people take it. I mean, people like to be appreciated. Like I said, we're people. Not that different from most other people. But the important reminder that that turning down the prize serves for me is not that there's anything wrong with the prize. And there's something wonderful about the prize, I think. The Nobel Prize is trickier because so many Nobel Prizes are given. First of all, the Nobel Prize often forgets many, many of the important people throughout history. Second of all, there's like these weird rules to it. It's only three people and some projects have a huge number of people. And it's like this, it, I don't know. It doesn't kind of highlight the way science has done on some of these projects in the best possible way. But in general, the prizes are great. But what this kind of teaches me and reminds me is sometimes in your life, there'll be moments when the thing that you would really like to do, society would really like you to do, is the thing that goes against something you believe in, whatever that is, some kind of principle, and standing your ground in the face of that. It's something, I believe most people will have a few moments like that in their life. Maybe one moment like that. And you have to do it. That's what integrity is. So like, it doesn't have to make sense to the rest of the world, but to stand on that, like, to say no, it's interesting. Because I think- But do you know that he turned down the prize in service of some principle? Because I don't know that. Well, yes, that seems to be the inkling, but he has never made it super clear. But the inkling is that he had some problems with the whole process of mathematics that includes awards, like this hierarchies and reputations and all those kinds of things, and individualism that's fundamental to American culture. He probably, because he visited the United States quite a bit, that he probably, you know, it's like all about experiences. And he may have had, you know, some parts of academia, some pockets of academia can be less than inspiring, perhaps sometimes, because of the individual egos involved. Not academia, people in general, smart people with egos. And if they, if you interact with a certain kinds of people, you can become cynical too easily. I'm one of those people that I've been really fortunate to interact with incredible people at MIT and academia in general, but I've met some assholes. And I tend to just kind of, when I run into difficult folks, I just kind of smile and send them all my love and just kind of go around. But for others, those experiences can be sticky. Like they can become cynical about the world when folks like that exist. So it's, he may have become a little bit cynical about the process of science. Well, you know, it's a good opportunity. Let's posit that that's his reasoning, because I truly don't know. It's an interesting opportunity to go back to almost the very first thing we talked about, the idea of the Mathematical Olympiad, because of course, that is, so the International Mathematical Olympiad is like a competition for high school students solving math problems. And in some sense, it's absolutely false to the reality of mathematics, because just as you say, it is a contest where you win prizes. The aim is to sort of be faster than other people. And you're working on sort of canned problems that someone already knows the answer to, like not problems that are unknown. So, you know, in my own life, I think when I was in high school, I was like very motivated by those competitions. And like I went to the Math Olympiad and... You won it. Well, there's something I have to explain to people, because it says, I think it says on Wikipedia that I won a gold medal. And in the real Olympics, they only give one gold medal at each event. I just have to emphasize that the International Math Olympiad is not like that. The gold medals are awarded to the top 112th of all participants. So sorry to bust the legend or anything like that. You're an exceptional performer in terms of achieving high scores on the problems, and they're very difficult. So you've achieved a high level of performance on the... In this very specialized skill. And by the way, it was a very Cold War activity. You know, in 1987, the first year I went, it was in Havana. Americans couldn't go to Havana back then. It was a very complicated process to get there. And they took the whole American team on a field trip to the Museum of American Imperialism in Havana, so we could see what America was all about. How would you recommend a person learn math? So somebody who's young, or somebody my age, or somebody older, who've taken a bunch of math, but wants to rediscover the beauty of math, and maybe integrate it into their work more so than the research space, and so on. Is there something you could say about the process of incorporating mathematical thinking into your life? I mean, the thing is, it's in part a journey of self-knowledge. You have to know what's gonna work for you, and that's gonna be different for different people. So there are totally people who, at any stage of life, just start reading math textbooks. That is a thing that you can do, and it works for some people and not for others. For others, a gateway is, I always recommend the books of Martin Gardner, another person we haven't talked about, but who also, like Conway, embodies that spirit of play. He wrote a column in Scientific American for decades called Mathematical Recreations, and there's such joy in it and such fun. And the columns are collected into books, and the books are old now, but for each generation of people who discover them, they're completely fresh. And they give a totally different way into the subject than reading a formal textbook, which for some people would be the right thing to do. And working contest-style problems, too, those are bound to books, especially Russian and Bulgarian problems. There's book after book of problems from those contexts. That's gonna motivate some people. For some people, it's gonna be like watching well-produced videos, a totally different format. I feel like I'm not answering your question. I'm sort of saying there's no one answer. And it's a journey where you figure out what resonates with you. For some people, the self-discovery is trying to figure out why is it that I want to know? Okay, I'll tell you a story. Once when I was in grad school, I was very frustrated with my lack of knowledge of a lot of things, as we all are, because no matter how much we know, we don't know much more. And going to grad school means just coming face-to-face with the incredible overflowing vault of your ignorance, right? So I told Joe Harris, who was an algebraic geometer of professor in my department, I was like, I really feel like I don't know enough. And I should just like take a year of leave and just like read EGA, the holy textbook, the elements of algebraic geometry. I feel like I don't know enough. So I was gonna sit and like read this like 1500 page, many volume book. And he was like, and Professor Harris was like, that's a really stupid idea. And I was like, why is that a stupid idea? Then I would know more algebraic geometry, because you're not actually going to do it like you learn. I mean, he knew me well enough to say like, you're gonna learn because you're gonna be working on a problem. And then there's gonna be a fact from EGA you need in order to solve your problem that you want to solve. And that's how you're going to learn it. You're not going to learn it without a problem to bring you into it. And so for a lot of people, I think if you're like, I'm trying to understand machine learning, and I'm like, I can see that there's sort of some mathematical technology that I don't have, I think you like let that problem that you actually care about drive your learning. I mean, one thing I've learned from advising students, you know, math is really hard. In fact, anything that you do right, is hard. And because it's hard, like, you might sort of have some idea that somebody else gives you, oh, I should learn x, y and z. Well, if you don't actually care, you're not going to do it, you might feel like you should, maybe somebody told you you should, but I think you have to hook it to something that you actually care about. So for a lot of people, that's the way in, you have an engineering problem you're trying to handle, you have a physics problem you're trying to handle, you have a machine learning problem you're trying to handle, let that not a kind of abstract idea of what the curriculum is, drive your mathematical learning. And also just as a brief comment, that math is hard, there's a sense to which hard is a feature, not a bug, in the sense that, again, maybe this is my own learning preference, but I think it's a value to fall in love with the process of doing something hard, overcoming it, and becoming a better person because of it. Like, I hate running, I hate exercise, to bring it down to like the simplest hard, and I enjoy the part once it's done. The person I feel like for the rest of the day once I've accomplished it, the actual process, especially the process of getting started in the initial, like it really, I don't feel like doing it. And I really have, the way I feel about running is the way I feel about really anything difficult in the intellectual space, especially mathematics, but also just something that requires like holding a bunch of concepts in your mind with some uncertainty, like where the terminology or the notation is not very clear, and so you have to kind of hold all those things together and like keep pushing forward through the frustration of really like obviously not understanding certain parts of the picture, like your giant missing parts of the picture, and still not giving up. It's the same way I feel about running. And there's something about falling in love with the feeling of after you went through the journey of not having a complete picture, at the end, having a complete picture, and then you get to appreciate the beauty, and just remembering that it sucked for a long time, and how great it felt when you figured it out, at least at the basic. That's not sort of research thinking, because with research, you probably also have to enjoy the dead ends. With learning math from a textbook or from a video, there's a nice- I don't think you have to enjoy the dead ends, but I think you have to accept the dead ends. Let's put it that way. Well, yeah, enjoy the suffering of it. So, the way I think about it, I do, there's an- I don't enjoy the suffering. It pisses me off, but I accept that it's part of the process. It's interesting. There's a lot of ways to kind of deal with that dead end. There's a guy who's an ultra marathon runner, Navy SEAL, David Goggins, who kind of, I mean, there's a certain philosophy of like, most people would quit here. And so, if most people would quit here, and I don't, I'll have an opportunity to discover something beautiful that others haven't yet. So, like, any feeling that really sucks, it's like, okay, most people would just like, go do something smarter. If I stick with this, I will discover a new garden of fruit trees that I can pick. Okay, you say that, but like, what about the guy who like, wins the Nathan's hot dog eating contest every year? Like, when he eats his 35th hot dog, he like, correctly says like, okay, most people would stop here. Like, are you like, lauding that he's like, no, I'm going to eat the 36th hot dog? I am, I am. In the long arc of history, that man is onto something. Which brings up this question, what advice would you give to young people today, thinking about their career, about their life, whether it's in mathematics, poetry, or hot dog eating contest? And you know, I have kids, so this is actually a live issue for me, right? I actually, it's not a thought experiment. I actually do have to give advice to young people all the time. They don't listen, but I still give it. You know, one thing I often say to students, I don't think I've actually said this to my kids yet, but I say it to students a lot is, you know, you come to these decision points, and everybody is beset by self-doubt, right? It's like, not sure like, what they're capable of, like, not sure what they're, what they really want to do. I always, I sort of tell people, like, often when you have a decision to make, one of the choices is the high self-esteem choice. And I always tell them, make the high self-esteem choice. Make the choice, sort of take yourself out of it, and like, if you didn't have those, you can probably figure out what the version of you that feels completely confident would do. And do that, and see what happens. And I think that's often, like, pretty good advice. That's interesting. Sort of like, you know, like with Sims, you can create characters. Like, create a character of yourself that lacks all of the self-doubt. Right, but it doesn't mean, I would never say to somebody, you should just go have high self-esteem. You shouldn't have doubts. No, you probably should have doubts. It's okay to have them, but sometimes it's good to act in the way that the person who didn't have them would act. That's a really nice way to put it. Yeah, that's like, from a third person perspective, take the part of your brain that wants to do big things. What would they do? That's not afraid to do those things. What would they do? Yeah, that's really nice. That's actually a really nice way to formulate it. That's very practical advice. You should give it to your kids. Do you think there's meaning to any of it from a mathematical perspective, this life? If I were to ask you, we talked about primes, talked about proving stuff. Can we say, and then the book that God has, that mathematics allows us to arrive at something about in that book, there's certainly a chapter on the meaning of life in that book. Do you think we humans can get to it? And maybe if you were to write Cliff Notes, what do you suspect those Cliff Notes would say? I mean, look, the way I feel is that mathematics, as we've discussed, it underlies the way we think about constructing learning machines. It underlies physics. It does all this stuff. And also, you want the meaning of life? I mean, it's like, we already did a lot for you. Ask a rabbi. No, I mean, I wrote a lot in the last book, How Not to Be Wrong. I wrote a lot about Pascal, a fascinating guy, who is a sort of very serious religious mystic, as well as being an amazing mathematician. And he's well known for Pascal's Wager. I mean, he's probably among all mathematicians, he's the one who's best known for this. Can you actually apply mathematics to these transcendent questions? But what's interesting, when I really read Pascal, about what he wrote about this, you know, I started to see that people often think, oh, this is him saying, I'm going to use mathematics to sort of show you why you should believe in God. You know, to really, that's this, mathematics has the answer to this question. But he really doesn't say that. He almost kind of says the opposite. If you ask Blaise Pascal, like, why do you believe in God? He'd be like, oh, because I met God. You know, he had this kind of like, psychedelic experience, this like a mystical experience, where, as he tells it, he just like directly encountered God. It's like, okay, I guess there's a God, I met him last night. So that's, that's it. That's why he believed. It didn't have to do with any kind of, you know, the mathematical argument was like, about certain reasons for behaving in a certain way. But he basically said, like, look, like, math doesn't tell you that God's there or not. Like, if God's there, he'll tell you, you know, you don't even, I love this. So you have, you have mathematics, you have, what do you, what do you have, like, ways to explore the mind, let's say psychedelics, you have like incredible technology, you also have love and friendship and like, what, what the hell do you want to know what the meaning of it all is? Just enjoy it. I don't think there's a better way to end it, Jordan. This was a fascinating conversation. I really love the way you explore math in your writing, the willingness to be specific and clear and actually explore difficult ideas, but at the same time, stepping outside and figuring out beautiful stuff. And I love the chart at the opening of your new book that shows the chaos, the mess that is your mind. Yes, this is what I was trying to keep in my head all at once while I was writing. And I probably should have drawn this picture earlier in the process. Maybe it would have made my organization easier. I actually drew it only at the end. And many of the things we talked about are on this map. The connections are yet to be fully dissected and investigated. And yes, God is in the picture. Right on the edge, right on the edge, not in the center. Thank you so much for talking. It is a huge honor that you would waste your valuable time with me. Thank you, Lex. We went to some amazing places today. This was really fun. Thanks for listening to this conversation with Jordan Ellenberg. And thank you to Secret Sauce, ExpressVPN, Blinkist, and Indeed. Check them out in the description to support this podcast. And now let me leave you with some words from Jordan in his book, How Not to Be Wrong. Knowing mathematics is like wearing a pair of x-ray specs that reveal hidden structures underneath the messy and chaotic surface of the world. Thank you for listening and hope to see you next time.

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Roger Penrose: Physics of Consciousness and the Infinite Universe | Lex Fridman Podcast #85

The following is a conversation with Roger Penrose, physicist, mathematician, and philosopher at University of Oxford. He has made fundamental contributions in many disciplines from the mathematical physics of general relativity and cosmology to the limitations of a computational view of consciousness. In his book, The Emperor's New Mind, Roger writes that, quote, "'Children are not afraid to pose basic questions "'that may embarrass us as adults to ask.'" In many ways, my goal with this podcast is to embrace the inner child that is not constrained by how one should behave, speak, and think in the adult world. Roger is one of the most important minds of our time, so it's truly a pleasure and an honor to talk with him. This conversation was recorded before the outbreak of the pandemic. For everyone feeling the medical, psychological, and financial burden of the crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with the five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you, and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, ExpressVPN and Cash App. Please consider supporting the podcast by getting ExpressVPN at expressvpn.com slash LexPod, and downloading Cash App and using code LexPodcast. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market, making trading more accessible for new investors and diversification much easier. So again, if you get Cash App from the App Store or Google Play and use the code LexPodcast, you get $10. Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. This show is sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's easy to use. Press the big power on button and your privacy is protected. And if you like, you can make it look like your location is anywhere else in the world. I might be in Boston now, but I can make it look like I'm in New York, London, Paris, or anywhere else. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu. ExpressVPN works on any device you can imagine. I use it on Linux, shout out to Ubuntu, Windows, Android, but it's available everywhere else too. Once again, get it at expressvpn.com slash LexPod to get a discount and to support this podcast. And now, here's my conversation with Roger Penrose. You mentioned in conversation with Eric Weinstein on the Portal podcast that 2001 Space Odyssey is your favorite movie. Which aspect, if you could mention, of its representation of artificial intelligence, science, engineering connected with you? There are all sorts of scenes there which are so amazing. And how they, science was so well done. I mean, people say, oh no, Interstellar, it's this amazing movie which is the most scientific movie. I thought it's another patch on 2001. I mean, 2001, they really went into all sorts of details. And they're getting the free fall well done and everything. I thought it was extremely well done. So just the details were mesmerizing in terms of the- And also things like the scene where at the beginning they have these sort of human ancestors which are sort of apes becoming humans. The monolith. Yes, and well, it's the one where he throws the bone up into the air and then it becomes this, I mean, that's an amazing sequence there. What do you make of the monolith? Does it have any scientific or philosophical meaning to you, this kind of thing that sparks innovation? Not really. That comes from Arthur C. Clarke. I was always a great fan of Arthur C. Clarke. So it's just a nice plot device. Yeah, well, that plot is excellent, yes. So Hal 9000 decides to get rid of the astronauts because he, it, she believes that they will interfere with the mission. That's right. Yeah, well, there you are. It's this view. I don't know whether I disagree with it because in a certain sense it was telling you it's wrong. See, the machine seemed to think it was superior to the human and so it was entitled to get rid of the human beings and run the show itself. Well, do you think Hal did the right thing? Do you think Hal's flawed, evil? Or if we think about systems like Hal, would we want Hal to do the same thing in the future? What was the flaw there? Well, you're basically touching on questions, you see. Is one supposed to believe that Hal was actually conscious? I mean, it was played rather that way as though Hal was a conscious being. Because Hal showed some pain, some, Hal appeared to be cognizant of what it means to die. Yes. And therefore had that. Yes, that's true, yes. An inkling of consciousness. Yeah, I mean, I'm not sure that aspect of it was made completely clear, whether Hal was really just a very sophisticated computer, which really didn't actually have these feelings and somehow, but you're right, it didn't like the idea of being turned off. How does it change things if Hal was or wasn't conscious? Well, it might say that it would be wrong to turn it off if it was actually conscious. I mean, these questions arise if you think. I mean, AI, one of the ideas, it's sort of a mixture in a sense. You say, if it's trying to do everything a human can do, and if you take the view that consciousness is something which would come along when the computer is sufficiently complicated, sufficiently whatever criterion you use to characterize its consciousness in terms of some computational criterion. So how does consciousness change our evaluation of the decision that Hal made? Well, I guess I was trying to say that people are a bit confused about this, because if they say these machines will become conscious, but just simply because it's a degree of computation, and when you get beyond that certain degree of computation, it will become conscious, then of course you have all these problems. I mean, you might say, well, one of the reasons you're doing AI is because you understand the device is some distant planet, and you don't want to send a human out there, because then you'd have to bring it back again, and that costs you far more than just sending it there and leaving it there. But if this device is actually a conscious entity, then you have to face up to the fact that that's immoral. And so the mere fact that you're making some AI device and thinking that removes your responsibility to it would be incorrect. And so this is a sound flaw in that kind of viewpoint. I'm not sure how people who take it very seriously, I mean, I had this curious conversation with, I'm going to forget names, I'm afraid, because this is what happens to me at the wrong moment, Hofstadter, Douglas Hofstadter. And he had written this book. God Will Let You Walk. Which I liked, I thought it was a fantastic book. But I didn't agree with his conclusion from Godel's theorem, I think he got it wrong. Well, I'll just tell you my story, because I'd never met him. And then I knew I was going to meet him, the occasion I realized he was coming in, he wanted to talk to me, and I said, that's fine. And I thought in my mind, well, I'm going to paint him into a corner, because I'll use his arguments to convince him that certain numbers are conscious. Some integers, large enough integers are actually conscious. And this was going to be my reductio ad absurdum. So I started having this argument with him, he simply leapt into the corner. He didn't even need to be painted into it. He took the view that certain numbers were conscious. I thought that was a reductio ad absurdum, but he seemed to think it was a perfectly reasonable point of view. Without the absurdum there. Yes. Interesting, but the thing you mentioned about Hal is the intuition that a lot of the people, at least in the artificial intelligence world, had and have, I think. They don't make it explicit, but that if you increase the power of computation, naturally consciousness will emerge. Yes, I think that's what they think. But basically that's because they can't think of anything else. Well, that's right. And so it's a reasonable thing. I mean, you think, what does the brain do? Well, it does do a lot of computation. I think most of what you actually call computation is done by the cerebellum. I mean, this is one of the things that people don't much mention. I mean, I come to this subject from the outside, and certain things strike me, which you hardly ever hear mentioned. I mean, you hear it mentioned about the left-right business. They move your right arm, that's the left side of the brain, and so on, and all that sort of stuff. And it's more than that. If you have these plots of different parts of the brain, there are two of these, these things called the homunculi, which you see these pictures of a distorted human figure, and showing different parts of the brain, controlling different parts of the body. And it's not simply things like, okay, the right hand is controlled, and both sensory and motor, on the left side, left hand on the right side. It's more than that. Vision is at the back, basically. Your feet at the top. And it's as though it's about the worst organization you can imagine. Right, yeah. So it can't just be a mistake in nature. There's something going on there. And this is made more pronounced when you think of the cerebellum. The cerebellum has, when I was first thinking about these things, I was told that it had half as many neurons or something like that, comparable. And now they tell me it's got far more neurons than the cerebrum. The cerebrum is this sort of convoluted thing at the top people always talk about. Cerebellum is this thing, which looks a bit like a ball of wool right at the back underneath. Yeah. It's got more neurons. It's got more connections. Computationally, it's got much more going on than the cerebrum. But as far as we know, although it's slightly controversial, the cerebellum is entirely unconscious. So the actions, you have a pianist who plays an incredible piece of music, and you think of, and he moves his little finger into this little key to get it, hit it just the right moment. Does he or she consciously will that movement? No. Okay, the consciousness is coming in. It's probably to do with the feeling of the piece of music that's being performed and that sort of thing, which is going on. But the details of what's going on are controlled. I would think almost entirely by the cerebellum. That's where you have this precision and the really detailed, once you get, I mean, you think of a tennis player or something, does that tennis player think exactly how to, which muscles should be moved in what direction? And so, no, of course not. But he or she will maybe think, well, if the ball is angled in such a way in that corner, that will be tricky for the opponent. And the details of that are all done largely with the cerebellum. That's where all the precise motions, but it's unconscious. So why is it interesting to you that so much computation is done in the cerebellum and yet it is unconscious? Because it doesn't, it's the view that somehow it's computation, which is producing the consciousness. And it's here you have an incredible amount of computation going on. And as far as we know, it's completely unconscious. So why, what's the difference? And I think it's an important thing. What's the difference? Why is the cerebrum, but all this very peculiar stuff that very hard to see on a computational perspective, like having the, everything have to cross over under the other side and do something which looks completely inefficient. And you've got funny things like the frontal lobe and the, what do we call the lobes? And the place where they come together, you have the different parts, the control, you see one to do with motor and the other to do with sensory. And they sort of opposite each other rather than being connected by, it's not as though you've got electrical circuits. There's something else going on there. So it's just the idea that it's like a complicated computer just seems to me to be completely missing the point. There must be a lot of computation going on, but the cerebellum seems to be much better at doing that than the cerebrum is. So for sure, I think what explains it, it's as like half hope and half we don't know what's going on and therefore, from the computer science perspective, you hope that a Turing machine can be perfectly, can achieve general intelligence. Well, you have this wonderful thing about Turing and Godel and Church and Curry and various people, particularly Turing and I guess Post was the other one. These people who developed the idea of what a computation is. And there were different ideas of what a computer, developed differently, I mean, Church's way of doing it was very different from Turing's, but then they were shown to be equivalent. And so the view emerged that what we mean by computation is a very clear concept. And one of the wonderful things that Turing did was to show that you could have what we call the universal Turing machine. It's you just have to have a certain finite device. Okay, it has to have an unlimited storage space, which is accessible to it. But the actual computation, if you like, is performed by this one universal device. And so the view comes away, well, you have this universal Turing machine, and maybe the brain is something like that, a universal Turing machine, and it's got maybe not unlimited storage, but a huge storage accessible to it. And this model is one, which is what's used in ordinary computation. That's a very powerful model. And the universalness of computation is very useful. You could have some problem and you may not see immediately how to put it onto a computer, but if it is something of that nature, then there are all sorts of sub-programs and sub-routines when all the, I mean, I learned a little bit of computing when I was a student, but not very much. But it was enough to get the general ideas. And there's something really pleasant about a formal system like that, where you can start discussing about what's provable, what's not, these kinds of things. And you've got a notion, which is an absolute notion, this notion of computability. And you can address when things are, what mathematical problems are computably solvable and which aren't. And it's a very beautiful area of mathematics, and it's a very powerful area of mathematics. And it underlies the whole sort of, what would one say, the principles of computing machines that we have today. Could you say what is Gato's incompleteness theorem, and how does it, maybe also say, is it heartbreaking to you? And how does it interfere with this notion of computation and consciousness? Sure. Well, the ideas, basically, ideas which I formulated in my first year as a graduate student in Cambridge. I did my undergraduate work in mathematics in London, and I had a colleague, Ian Percival. We used to discuss things like computational and logical systems quite a lot. I'd heard about Godel's theorem. I'm a bit worried by the idea that it seemed to say there were things in mathematics that you could never prove. And so when I went to Cambridge as a graduate student, I went to various courses. You see, I was doing pure mathematics. I was doing algebraic geometry of a sort, little bit different from what my supervisor and people, but it was algebraic geometry. And I was interested, I got particularly interested in three lecture courses that were nothing to do with what I was supposed to be doing. One was a course by Herman Bondi on Einstein's general theory of relativity, which was a beautiful course. He was an amazing lecturer, brought these things alive, absolutely. Another was a course on quantum mechanics given by the great physicist, Paul Dirac. Very beautiful course in a completely different way. It was very kind of organized and never got excited about anything seemingly. But it was extremely well put together and I found that amazing too. Third course that was nothing to do with what I should be doing was a course on mathematical logic. I got excited, as I say, my discussions with Ian Percival. Was the incompleteness theorem already deeply within mathematical logic space? Were you introduced to it? I was introduced to it in detail by the course by Steen. And he, it was two things he described which were very fundamental to my understanding. One was Turing machines and the whole idea of computability and all that. So that was all very much part of the course. The other one was the Godel theorem. And it wasn't what I was afraid it was to tell you there were things in mathematics you couldn't prove. It was basically, and he phrased it in a way which often people didn't. And if you read Douglas Hofstadter's book, he doesn't, you see. But Steen made it very clear and also in a sort of public lecture that he gave to a mathematical, I think it may be the Adams Society, one of the mathematical undergraduate societies. And he made this point again very clearly. That if you've got a formal system of proof, so suppose what you mean by proof is something which you could check with a computer. So to say whether you've got it right or not, you've got a lot of steps. Have you carried this computational procedure? Well, following the proof, steps of the proof correctly, that can be checked by an algorithm, by a computer. So that's the key thing. Now what you have to, now you see, is this any good? If you've got an algorithmic system, which claims to say, yes, this is right, this you've proved it correctly, this is true. If you've proved it, if you made a mistake, it doesn't say it's true or false, but if you've done it right, then the conclusion you've come to is correct. Now you say, why do you believe it's correct? Because you've looked at the rules and you said, well, okay, that one's all right. Yeah, that one's all right. What about that? Oh yeah, I see, I see why it's all right. Okay, you go through all the rules. You say, yes, following those rules, if it says, yes, it's true, it is true. So you've got to make sure that these rules are ones that you trust. If you follow the rules and it says it's a proof, is the result actually true? And that your belief that it's true depends upon looking at the rules and understanding them. Now, what Gödel shows that if you have such a system, then you can construct a statement of the very kind that it's supposed to look at, a mathematical statement. And you can see by the way it's constructed and what it means that it's true, but not provable by the rules that you've been given. And it depends on your trust in the rules. Do you believe that the rules only give you truths? If you believe the rules only give you truth, then you believe this other statement is also true. I found this absolutely mind-blowing. When I saw this, it blew my mind. Thought, my God, you can see that this statement is true. It's as good as any proof because it only depends on your belief in the reliability of the proof procedure. That's all it is. And understanding that the coding is done correctly and it enables you to transcend that system. So whatever system you have, as long as you can understand what it's doing and why you believe it only gives you truths, then you can see beyond that system. Now, how do you see beyond it? What is it that enables you to transcend that system? Well, it's your understanding of what the system is actually saying and what the statement that you've constructed is actually saying. So it's this quality of understanding, whatever it is, which is not governed by rules. It's not a computational procedure. So this idea of understanding is not going to be within the rules of the, within the formal system. Yes, you're only using those rules anyway because you have understood them to be rules which only give you truths. There'd be no point in it otherwise. I mean, people say, well, okay, this is, one set of rules is as good as any other. Well, it's not true, you see. You have to understand what the rules mean. And why does that understanding of the mean give you something beyond the rules themselves? And that's what it was. That's what blew my mind. It's somehow understanding why the rules give you truths enables you to transcend the rules. So that's where, I mean, even at that time, that's already where the thought entered your mind that the idea of understanding, or we can start calling it things like intelligence or even consciousness, is outside the rules. Yes, see, I've always concentrated on understanding. You know, people say, people, somebody's pointing out things, well, we know about creativity. That's something a machine can't do, is create. Well, I don't know. What is creativity? And I don't know. You know, somebody can put some funny things on a piece of paper and say that's creative, and you could make a machine do that. Is it really creative? I don't know. You see, I worry about that one. I sort of agree with it in a sense, but it's so hard to do anything with that statement. But understanding, yes, you can. You can make, go see that understanding, whatever it is, and it's very hard to put your finger on it. That's absolutely true. Can you try to define or maybe dance around a definition of understanding? To some degree, but I don't, I often wondered about this, but there is something there which is very slippery. It's something like standing back. And it's got to be something, you see, it's also got to be something which was of value to our remote ancestors. Because I sometimes, there's a cartoon which I drew sometimes showing you how all these, there's in the foreground, you see this mathematician just doing some mathematical theorem. There's a little bit of a joke in that theorem, but let's not go into that. He's trying to prove some theorem, and he's about to be eaten by a saber-toothed tiger who's hiding in the undergrowth, you see. And in the distance, you see his cousins building, growing crops, building shelters, domesticating animals. And in the slight foreground, you see, they built a mammoth trap, and this poor old mammoth is falling into a pit, you see. And all these people around him are about to grab him, you see, and well, you see, those are the ones who, the quality of understanding which goes with all, it's not just the mathematician doing his mathematics. This understanding quality is something else, which has been a tremendous advantage to us, not just to us. See, I don't think consciousness is limited to humans. Yeah, that's the interesting question, at which point, if it is indeed connected to the evolutionary process, at which point did we pick up this? A very hard question. It's certainly, I don't think it's primates. You see these pictures of African hunting dogs and how they can plan amongst themselves how to catch the antelopes. Some of these are David Attenborough films, I think this probably was one of them. And you can see the hunting dogs, and they divide themselves into two groups, and they go in two routes, two different routes. One of them goes and they sort of hide next to the river. And the other group goes around and they start yelping at these, they don't bark, I guess, whatever noise hunting dogs do, the antelopes. And they sort of round them up and they chase them in the direction of the river. And there are the other ones just waiting for them, just to get, because when they get to the river it slows them down, and so they pounce on them. So they've obviously planned this all out somehow, I have no idea how, and there is some element of conscious planning as far as I can see. I don't think it's just some kind of, so much of AI these days is done, what do they call, bottom-up systems, is it? Yeah, where you have neural networks and you give them a zillion different things to look at, and then they sort of can choose one thing over another just because it's seen so many examples and picks up on little signals, which one may not even be conscious of. And that doesn't feel like understanding. There's no understanding in that whatsoever. Well, you're being a little bit human-centric, so I think I would expect. Well, I'm talking about, I'm not with the dogs, am I? No, you're not, sorry, not human-centric, but I misspoke, biology-centric. Is it possible that consciousness would just look slightly different? Well, I'm not saying it's biological, because we don't know. Right. I think other examples, the elephants is a wonderful example too. I think this was about Attenborough 1, where the elephants have to go from, the troop of them have to go long distances. And the leader of a troop is a female, they all are apparently. And this female, she had to go all the way from one part of the country to another. And at a certain point, she made a detour, and they went off in this big detour. All the troop came with her, and this was where her sister had died. And there were her bones lying around, and they go and pick up the bones, and they hand it around, and they caress the bones. And then they put them back, and they would go back again. What in the hell are they doing? That's so interesting. I mean, there's something going on. There's no clear connection with natural selection. There's just some deep feeling going on there, which has to do with their conscious experience. And I think it's something that overall is advantageous, a natural selection, but not directly to do with natural selection. I like that. There's something going on there. Like I told you, I'm Russian, so I tend to romanticize all things of this nature, that it's not merely cold, hard computation. Perhaps I could just slightly answer your question. You were asking me, what is it? There's something about sort of standing back and thinking about your own thought processes. I mean, there is something like that in the Godel thing, because you're not following the rules. You're standing back and thinking about the rules. And so there is something that you might say, you think about you're doing something, and you think, what the hell am I doing? And you sort of stand back and think about what it is that's making you think in such a way. Take a step back outside the game you've been playing. Yeah, you back up, and you think about, you're just not playing the game anymore. You're thinking about what the hell you're doing in playing this game. And that's somehow, it's not a very precise description, but somehow it feels very true that that's somehow understanding. So this kind of reflection. A reflection, yes. Yeah. There is, it's a bit hard to put your finger on, but there is something there which I think maybe could be unearthed at some point, and see this is really what's going on. Why conscious beings have this advantage. What it is that gives them an advantage. And I think it goes way back. I don't think, we're talking about the hunting dogs and the elephants. That's pretty clear that octopuses have the same sort of quality. And we call it consciousness? Yeah, I think so. Seen enough examples of the way that they behave, and the evolution route is completely different. Does it go way back to some common ancestor, or did it come separately? My hope is it's something simple, but the hard question if there's a hardware prerequisite. We have to develop some kind of hardware mechanisms in our computers. Like basically, as you suggest, and we'll get to in a second, we kind of have to throw away the computer as we know it today. The deterministic machines we know today to try to create it. I mean, my hope of course is not, but. Well, I should go really back to the story, which in a sense I haven't finished. Because I went to these three courses, you see, when I was a graduate student. And so I started to think, well I'm really, I'm a pretty, what you might call a materialist in the sense of thinking that there's no kind of mystical or something or other which comes in from who knows where. You still that? Are you still throughout your life been a materialist? I don't like the word materialist because it suggests we know what material is. And that is a bad word because. But there's no mystical. It's not some mystical something which is not treatable by science. That's so beautifully put, just to pause on that for a second. You're a materialist, but you acknowledge that we don't really know what the material is. That's right. I mean, I like to call myself a scientist, I suppose. But it means that, yes, well you see, the question goes on here. So I began thinking, okay, if consciousness or understanding is something which is not a computational process, what can it be? And I knew enough from my undergraduate work, I knew about Newtonian mechanics and I knew how basically you could put it on a computer. There is a fundamental issue which is it important or not that computation depends upon discrete things. So using discrete elements, whereas the physical laws depend on the continuum. Now is this something to do with it? Is it the fact that we use the continuum in our physics? And if we model our physical system, we use discrete systems like ordinary computers. I came to the view that that's probably not it. I might have to retract on that someday, but the view was no, you can get close enough. It's not altogether clear, I have to say, but you can get close enough. And I went to this course by Bondy on general relativity and I thought, well, you can put that on a computer. Of course, that was a long time before people, and I've sort of grown up with this, how people have done better and better calculations and they could work out black holes and they can then work out how black holes can interact with each other, spiral around and what kind of gravitational waves can out. And it's a very impressive piece of computational work, how you can actually work out the shapes of those signals. Now we have LIGO seeing these signals and they say, yeah, there's a black hole spiraling into each other. This is just a vindication of the power of computation in describing Einstein's general relativity. So in that case, we can get close. With computation, we can get close to our understanding of the physics. You can get very, very close. Now, is that close enough, you see? And then I went to this course by Dirac. Now you see, I think it was the very first lecture that he gave and he was talking about the superposition principle. And he said, if you have a particle, you usually think of particle can be over here or over there, but in quantum mechanics, it can be over here and over there at the same time. And you have these states which involve a superposition in some sense of it different locations for that particle. And then he got out his piece of chalk. Some people say he broke it in two as a kind of illustration of how the piece of chalk might be over here and over there at the same time. And he was talking about this and my mind wandered. I don't remember what he said. All I can remember, he's just moved on to the next topic and something about energy he'd mentioned, which I had no idea what had to do with anything. And so I'd been struck with this and worried about it ever since. It's probably just as well I didn't hear his explanation because it was probably one of these things to calm me down and not worry about it anymore. Whereas in my case, I've worried about it ever since. So I thought maybe that's the catch. There is something in quantum mechanics where the superpositions become one or the other. And that's not part of quantum mechanics. There's something missing in the theory. The theory is incomplete. It's not just incomplete. It's in a certain sense, not quite right because if you follow the equation, the basic equation of quantum mechanics, that's the Schrodinger equation, you could put that on a computer too. There are lots of difficulties about how many parameters you have to put in and so on. That can be very tricky, but nevertheless, it is a computational process. Modulo this question about the continuum as before, but it's not clear that makes any difference. So our theories of quantum mechanics may be missing the same element that the universal Turing machine is missing about consciousness. Yes, yes. Yeah, this is the view I held is that you need a theory and that that, what people call the reduction of the state or the collapse of the wave function, which you have to have, otherwise quantum mechanics doesn't relate to the world we see. To make it relate to the world we see, you've got to break the Schrodinger equation. Schrodinger himself was absolutely appalled by this idea, his own equation. I mean, that's why he introduced this famous Schrodinger's cat as a thought experiment. He's really saying, look, this is where my equation leads you into it. There's something wrong, something we haven't understood, which is basically fundamental. And so I was trying to put all these things together and said, well, it's got to be the non-computability comes in there. And I also can't quite remember when I thought this, but it's when gravity is involved in quantum mechanics. It's the combination of those two. And it's that point when you have good reasons to believe, this came much later, but I have good reason to believe that the principles of general relativity and those of quantum mechanics, most particularly it's the basic principle of equivalence, which goes back to Galileo. If you fall freely, you eliminate the gravitational field. So you imagine Galileo dropping his big rock and his little rock from the leaning tower, whether he actually ever did that or not, pretty irrelevant. And as the rocks fall to the ground, you have a little insect sitting on one of them, looking at the other one. And it seems to think, oh, there's no gravity here. Of course it hits the ground and then you realize something's different's going on. But when it's in free fall, the gravity is being eliminated. Galileo understood that very beautifully. He gives these wonderful examples of fireworks and you see the fireworks and explode. And you see this sphere of sparkling fireworks. It remains a sphere as it falls down, as though there were no gravity. So he understood that principle, but he couldn't make a theory out of it. Einstein came along, used exactly the same principle. And that's the basis of Einstein's general theory of relativity. Now, there is a conflict. This is something I did much, much later. So this wasn't those days. Much, much later. You can see there is a basic conflict between the principle of superposition, the thing that Dirac was talking about, and the principle of general covariance. Well, principle of equivalence. Gravitational field is equivalent to an acceleration. Can you pause for a second? What is the principle of equivalence? It's this Galileo principle that you can eliminate, at least locally. You have to be in a small neighborhood because if you have people dropping rocks all around the world somewhere, you can't get rid of it all at once. But in the local neighborhood, you can eliminate the gravitational field by falling freely with it. And we now see that with astronauts, and they don't, you know, the Earth is right there. You can see the great globe of the Earth right beneath them. But they don't care about it. As far as they're concerned, there's no gravity. They fall freely in the gravitational field, and that gets rid of the gravitational field. And that's the principle of equivalence. So what's the contradiction? What's the tension with superposition? Ah, well, that's technical. Well, so just to backtrack for a second, just to see if we can weave a thread through it all. So we started to think about consciousness as potentially needing some of the same, not mystical, but some of the same magic. You see, it is a complicated story. So, you know, people think, oh, I'm drifting away from the point or something. But I think it is a complicated story. So what I'm trying to say, I mean, I tried to put it in a nutshell, but it's not so easy. I'm trying to say that whatever consciousness is, it's not a computation. Yes. Or it's not a physical process which can be described by computation. But it nevertheless could be, so one of the interesting models that you've proposed is the orchestrated objective reduction. Yes, well, you see, that's going from there, you see. So I say I have no idea. So I wrote this book through my scientific career. I thought, you know, when I'm retired, I'll have enough time to write a sort of popularish book which I will explain my ideas and puzzles, what I like, beautiful things about physics and mathematics, and this puzzle about computability and consciousness and so on. And in the process of writing this book, well, I thought I'd do it when I was retired. I didn't, actually. I didn't wait that long because there was a radio discussion between Edward Fredkin and Marvin Minsky. And they were talking about what computers could do, and they were entering a big room. They imagined entering this big room, where at the other end of the room, two computers were talking to each other. And as you walk up to the computers, they will have communicated to each other more ideas, concepts, things than the entire human race had ever done. So I thought, well, I know where you're coming from, but I just don't believe you. There's something missing. So I thought, well, I should write my book. And so I did. It was at roughly the same time Stephen Hawking was writing his brief history of time. In the 80s at some point. The book you're talking about is The Emperor's New Mind. The Emperor's New Mind, that's right. And both are incredible books, The Brief History of Time and The Emperor's New Mind. Yes, it was quite interesting because he told me he'd got Carl Sagan, I think, to write a forward. It's a good get. To the book, you see. So I thought, gosh, what am I gonna do? I'm not gonna get anywhere unless I get somebody. So I said, well, I know Martin Gardner, so I wonder if he'd do it. So he did, and he did a very nice forward. So that's an incredible book. And some of the same people you mentioned, Ed Franken, which I guess of Expert Systems fame, and Minsky, of course, people know in the AI world. But they represent the artificial intelligence world. Absolutely, that's right. That do hope and dream that AI's intelligence is. That's right. Well, you see, it was my thinking. Well, you know, I see where they're coming from. And from that perspective. I disagree. Yeah, you're right. But that's not my perspective. So I thought I had to say it. And as I was writing my book, you see, I thought, well, I don't really know anything about neurophysiology. What am I doing writing this book? So I started reading up about neurophysiology. And I read up, and I think, I'm trying to find out how it is that nerve signals could possibly preserve quantum coherence. And all I read is that the electrical signals which go along the nerves, create effects through the brain. There's no chance you can isolate it. So this is hopeless. So I come to the end of the book, and I more or less give up. I just think of something which I didn't believe in. That's maybe this is a way around it, but no. And then you say, I thought, well, maybe this book will at least stimulate young people to do science or something. And I got all these letters from old, retired people instead. These are the only people who could have time to read my book. So, I mean, but. Except for Stuart Hameroff. Except for Stuart Hameroff. Stuart Hameroff wrote to me, and he said, I think you're missing something. You don't know about microtubules. He didn't put it quite like that. But that was more or less it. And he said, this is what you really need to consider. So I thought, my God, yes. That's a much more promising structure. So, I mean, fundamentally, you were searching for the source of, non-computable source of consciousness within the human brain, in the biology. And so, what are, if I may ask, what are microtubules? Well, you see, I was ignorant in what I'd read. I never came across them in the books I looked at. Perhaps I only read rather superficially, which is true. But I didn't know about microtubules. Stuart, I think one of the things that impressed him about them was, when you see pictures of mitosis, that's a cell dividing, and you see all the chromosomes, and the chromosomes, they all get lined up, and then they get pulled apart. And so, as the cell divides, half the chromosomes go, you know, they divide into the two parts, and they go two different ways. And what is it that's pulling them apart? Well, those are these little things called microtubules. And so, he started to get interested in them. And he formed a view, well, he was, his day job or night job, or whatever you call it, is to put people to sleep, except he doesn't like calling it sleep because it's different, general anesthetics, in a reversible way. So you want to make sure that they don't experience the pain that would otherwise be something that they feel. And consciousness is turned off for a while, and it can be turned back on again. So it's crucial that you can turn it off and turn it on. And what do you do when you're doing that? What do general anesthetic gases do? And see, he formed the view that it's the microtubules that they affect. And the details of why he formed that view is not all that clear to me, but there's an interesting story he keeps talking about. But I found this very exciting because I thought these structures, these little tubes which inhabit pretty well all cells, it's not just neurons, apart from red blood cells, they inhabit pretty well all the other cells in the body. But they're not all the same kind. You get different kinds of microtubules. And the ones that excited me the most, this may still not be totally clear, but the ones that excited me most were the only ones that I knew about at the time because they were very, very symmetrical structures. And I had reason to believe that these very symmetrical structures would be much better at preserving a quantum state, quantum coherence, preserving the thing without, you just need to preserve certain degrees of freedom without them leaking into the environment. Once they leak into the environment, you're lost. So you've got to preserve these quantum states at a level which the state reduction process comes in and that's where I think the non-computability comes in. And it's the measurement process in quantum mechanics, what's going on. So something about the measurement process and what's going on, something about the structure of the microtubules, your intuition says maybe there's something here. Maybe this kind of structure allows for the mystery of the quantum mechanics. There was a much better chance, yes. It just struck me that partly it was the symmetry because there is a feature of symmetry. You can preserve quantum coherence much better with symmetrical structures. There's a good reason for that. And that impressed me a lot. I didn't know the difference between the A lattice and B lattice at that time, which could be important. No, that couldn't, which isn't talked about much. But that's in some sense details. We've got to take a step back just to say in case people are not familiar. So this was called the orchestrated objective reduction idea or ORCOR, which is a biological philosophy of mind that postulates that consciousness originates at the quantum level inside neurons. So that has to do with your search for where, where is it coming from? So that's counter to the notion that consciousness might arise from the computation performed by the synapses. Yes, I think the key point, sometimes people say it's because it's quantum mechanical. It's not just that. See, it's more outrageous than that. You see, this is one reason I think we're so far off from it because we don't even know the physics right. You see, it's not just quantum mechanics. People say, oh, you know, quantum systems and biological structures. No, well, you're starting to see that some basic biological systems does depend on quantum. I mean, look, in the first place, all of chemistry is quantum mechanics. People got used to that, so they don't count that. So he said, let's not count quantum chemistry. We sort of got the hang of that, I think. But you have quantum effects, which are not just chemical, in photosynthesis. And this is one of the striking things in the last several years, that photosynthesis seems to be a basically quantum process, which is not simply chemical. It's using quantum mechanics in a very basic way. So you could start saying, oh, well, with photosynthesis is based on quantum mechanics, why not behavior of neurons and things like that? Maybe there's something which is a bit like photosynthesis in that respect. But what I'm saying is even more outrageous than that, because those things are talking about conventional quantum mechanics. Now, my argument says that conventional quantum mechanics, if you're just following the Schrodinger equation, that's still computable. So you've got to go beyond that. So you've got to go to where quantum mechanics goes wrong in a certain sense. You have to be a little bit careful about that, because the way people do quantum mechanics is a sort of mixture of two different processes. One of them is the Schrodinger equation, which is an equation that Schrodinger wrote down, and it tells you how the state of a system evolves. And it evolves, according to this equation, completely deterministic, but it evolves into ridiculous situations. And this was what Schrodinger was very much pointing out with his cat. He says, you follow my equation, that's Schrodinger's equation, and you could say that you have to, you have a cat which is dead and alive at the same time. That would be the evolution of the Schrodinger equation would lead to a state, which is the cat being dead and alive at the same time. And he's more or less saying, this is an absurdity. People nowadays say, oh, well, Schrodinger said you can have a cat which is dead and alive. It's not that, you see, he was saying, this is an absurdity. There's something missing. And that the reduction of the state or the collapse of the wave function or whatever it is, is something which has to be understood. It's not following the Schrodinger equation. It's not the way we conventionally do quantum mechanics. There's something more than that. And it's easy to quote authority here because Einstein, at least three of the greatest physicists of 20th century, who were very fundamental in developing quantum mechanics, Einstein, one of them, Schrodinger, another, Dirac, another. You have to look carefully at Dirac's writing because he didn't tend to say this out loud very much because he was very cautious about what he said. You find the right place and you see, he says quantum mechanics is a provisional theory. We need something which explains the collapse of a wave function. We need to go beyond the theory we have now. I happen to be one of the kinds of people, there's a whole group of people, they're all considered to be a bit mavericks, who believe that quantum mechanics needs to be modified. There's a small minority of those people, which are already a minority, who think that the way in which it's modified has to be with gravity. And there is an even smaller minority of those people who think it's the particular way that I think it is. So. So those are the quantum gravity folks. But what's. You see, quantum gravity is already not this. Because when you say quantum gravity, what you really mean is quantum mechanics applied to gravitational theory. So you say, let's take this wonderful formalism of quantum mechanics and make gravity fit into it. So that is what quantum gravity is meant to be. Now I'm saying, you've got to be more even handed. That gravity affects the structure of quantum mechanics too. It's not just you quantize gravity. You've got to gravitize quantum mechanics. And it's a two way thing. But then when do you even get started? So that you're saying that we have to figure out a totally new ideas in that. Exactly. No, you're stuck. You don't have a theory. That's the trouble. So this is a big problem. If you say, okay, well what's the theory? I don't know. So maybe in the very early days, sort of. It is in the very early days. But just making this point. Yes. You see, Stuart Hameroff tends to be, oh Penrose says that it's got to be a reduction of the state and so on. So let's use it. The trouble is Penrose doesn't say that. Penrose says, well I think that. But we have no experiments as yet, which shows that. There are experiments which are being thought through and which I'm hoping will be performed. There is an experiment which is being developed by Dirk Baumeister, who I've known for a long time. Who shares his time between Leiden in the Netherlands and Santa Barbara in the US. And he's been working on an experiment which could perhaps demonstrate that quantum mechanics as we now understand it, if you don't bring in the gravitational effects, has to be modified. And then there's also experiments that are underway that kind of look at the microtubule side of things. To see if there's, in the biology, you could see something like that. Could you briefly mention it? Because that's a really sort of one of the only experimental attempts in the very early days of even thinking about consciousness. I think there's a very serious area here, which is what Stuart Hameroff is doing. And I think it's very important. One of the few places that you can really get a bit of a handle on what consciousness is, is what turns it off. And when you're thinking about general anesthetics, it's very specific. These things turn consciousness off. What the hell do they do? Well, Stuart and a number of people who work with him and others, happen to believe that the general anesthetics directly affect microtubules. And there is some evidence for this. I don't know how strong it is and how watertight the case is but I think there is some evidence pointing in that kind of direction. It's not just an ordinary chemical process. There's something quite different about it. And one of the main candidates is that these anesthetic gases do affect directly microtubules. And how strong that evidence is, I wouldn't be in a position to say. But I think there is fairly impressive evidence. But in the point is the experiments are being undertaken, which is. I mean, that is experimental. You see, so it's a very clear direction where you can think of experiments which could indicate whether or not it's really microtubules, which the anesthetic gases directly affect. That's really exciting. One of the sad things is, as far as I'm, from my outside perspective, is not many people are working on this. So there's a very, like with Stuart, it feels like there's very few people are carrying the flag forward on this. I think it's not many in the sense it's a minority. But it's not zero anymore. You see, when Stuart and I were originally thought of as, you know, we were just us and a few of our friends. There weren't many people taking it. But it's grown into one of the main viewpoints. There might be about four or five or six different views that people hold, and it's one of them. So it's considered as one of the possible lines of thinking, yes. You describe physics theories as falling into one of three categories. The superb, the useful, or the tentative. I like those words. It's a beautiful categorization. Do you think we'll ever have a superb theory of intelligence and of consciousness? We might. We're a long way from it. I don't think we're even, whether we're in the tentative scale. I mean, it's a... You don't think we've even entered the realm of tentative? Probably not. Yeah, that's right. I think it's tentative. When you see this, it's so controversial. We don't have a clear view, which is accepted by a majority. I mean, you say, yeah, people, most views are computational in one form or another. I think it's some, but it's not very clear, because even the IIT people who think of them as computational, but I've heard them say, no, consciousness is supposed to be not computational. I say, well, if it's not computational, what the hell is it? What's going on? What physical processes are going on which are that? What does it mean for something to be computational then? So is... Well, there has to be a process which is... You see, it's very curious the way the history has developed in quantum mechanics, because very early on, people thought there was something to do with consciousness, but it was almost the other way around. You see, you have to say the Schrodinger equations says all these different alternatives happen all at once, and then when is it that only one of them happens? Well, one of the views, which was quite commonly held by a few distinguished quantum physicists, this when a conscious being looks at the system or becomes aware of it, and at that point, it becomes one of the other. That's a role where consciousness is somehow actively reducing the state. My view is almost the exact opposite of that. It's the state reduces itself in some way, which some non-computational way, which we don't understand, we don't have a proper theory of, and that is the building block of what consciousness is. So consciousness is the other way around. It depends on that choice which nature makes all the time when the state becomes one or the other, rather than the superposition of one and the other, and when that happens, there is, what we're saying now, an element of proto-consciousness takes place. Proto-consciousness is, roughly speaking, the building block out of which actual consciousness is constructed. So you have these proto-conscious elements, which are when the state decides to do one thing or the other. That's the thing which, when organized together, that's the OR part in OrcOR, but the Orc part, that's the, the OR part, at least one can see where we're driving at a theory. You can say it's the quantum choice of going this way or that way, but the Orc part, which is the orchestration of this, is much more mysterious, and how does the brain somehow orchestrate all these individual OR processes into a genuine conscious experience? And it might be something that's beautifully simple, but we're completely in the dark about. Yeah, I think at the moment, that's the thing. You know, we happily put the word Orc down there to say orchestrated, but that's even more unclear what that really means. Just like the word material, orchestrated, who knows? And we've been dancing a little bit between the word intelligence or understanding and consciousness. Do you kind of see those as sitting in the same space of mystery as we've discussed? Yes, but you see, I tend to say you have understanding and intelligence and awareness, and somehow understanding is in the middle of it. I like to say, could you say of an entity that is actually intelligent if it doesn't have the quality of understanding? Maybe I'm using terms I don't even know how to define, but who cares? I'm just relating. They're somewhat poetic. So if I somehow understand them. Yes, that's right. We don't, exactly. But they're not mathematical in nature. Yes, you see, as a mathematician, I don't know how to define any of them, but at least I can point to the connections. So the idea is intelligence is something which I believe needs understanding. Otherwise, you wouldn't say it's really intelligence. And understanding needs awareness. Otherwise, you wouldn't really say it's understanding. Do you say of an entity that understands something, unless it's really aware of it, in our normal usage. So there's a three sort of awareness, understanding, and intelligence. And I just tend to concentrate on understanding because that's where I can say something. And that's the Godel theorem, things like that. But what does it mean to perceive the color blue or something? I'm foggiest. That's a much more difficult question. I mean, is it the same if I see a color blue and you see it? If you're assembling with what, this condition, what's it called? Or where you assign a sound to a color? Yeah, that's right. You get colors and sounds mixed up. And that sort of thing. I mean, an interesting subject. But from the physics perspective, from the fundamentals perspective, we don't. I think we're way off having much understanding what's going on there. In your 2010 book, Cycles of Time, you suggest that another universe may have existed before the Big Bang. Can you describe this idea? First of all, what is the Big Bang? Sounds like a funny word. And what may have been there before it? Yes, just as a matter of terminology, I don't like to call it another universe. Because when you have another universe, you think of it kind of quite separate from us. But these things, they're not separate. Now, the Big Bang, conventional theory. You see, I was actually brought up in the sense of when I started getting interested in cosmology, there was a thing called the steady state model, which was sort of philosophically very interesting. And there wasn't a Big Bang in that theory. But somehow, new material was created all the time in the form of hydrogen. And the universe kept on expanding, expanding, expanding. And there was room for more hydrogen. It was a rather philosophically nice picture. It was disproved when the Big Bang, well, when I say the Big Bang, this was theoretically discovered by people trying to solve Einstein's equations and apply it to cosmology. Einstein didn't like the idea. He liked a universe which was there all the time. And he had a model which was there all the time. But then there was this discovery, accidental discovery, a very important discovery, of this microwave background. And if you, you know, there's the crackle on your television screen, which is already sensing this microwave background, which is coming at us from all directions. And you can trace it back and back and back and back. And it came from a very early stage of the universe. Well, it's part of the Big Bang theory. The Big Bang theory was when people tried to solve Einstein's equations. They really found you had to have this initial state near the universe, it used to be called the primordial atom and things like this. There's Friedman and Lemaitre. Friedman was a Russian, Lemaitre was a Belgian. And they independently, well, basically Friedman first. And Lemaitre talked about the initial state, which is a very, very concentrated initial state, which seemed to be the origin of the universe. Primordial atom, that's a nice. Primordial atom is what he called it, yes. Beautiful term. And then it became, well, Fred Hoyle used the term Big Bang in a kind of derogatory sense. Just like with the Schrodinger and the cats, right? Yes, it's like sort of got picked up on, whereas it wasn't his intention originally. But then the evidence piled up and piled up. And one of my friends that I learned a lot from when I was in Cambridge was Dennis Schama. He was a great proponent of steady state. And then he got converted. He said, no, I'm sorry. I had a great respect for him. He went around lecturing, said, I was wrong. The steady state model doesn't work. There was this Big Bang. And this microwave background that you see, okay, it's not actually quite the Big Bang when I said not quite. It's about 380,000 years after the Big Bang. But that's what you see. But then you have to have had this Big Bang before it in order to make the equations work. And it works beautifully. Except for one little thing, which is this thing called inflation, which people had to put into it to make it work. When I first heard of it, I didn't like it at all. What's inflation? Inflation is it in the first, I'm gonna give you a very tiny number. Think of a second. That's not very long. Now I'm gonna give you a fraction of a second, one over a number. This number has 32 digits. Between, well, let's say between 36 and 32 digits, tiny, tiny time between those two tiny, ridiculous seconds, fraction of a second, the universe was supposed to have expanded in this exponential way, an enormous way. For no apparent reason, you had to invent a particular thing called the inflaton field to make it do it. And I thought this is completely crazy. There are reasons why people stuck with this idea. You see, the thing is that I formed my model for reasons which are very fundamental, if you like. It has to do this very fundamental principle, which is known as the second law of thermodynamics. The second law of thermodynamics says, more or less, things get more and more random as time goes on. Now, another way of saying exactly the same thing is things get less and less random as things go back. As you go back in time, they get less and less random. So you go back and back and back and back. And the earliest thing you can directly see is this microwave background. What's one of the most striking features of it is that it's random. It has this, what you call this spectrum of, which is what's called the Planck spectrum, of frequencies, different intensities for different frequencies. And it's this wonderful curve due to Max Planck. And what's it telling you? It's telling you that the entropy is at a maximum. Started off at a maximum and it's going up ever since. I call that the mammoth in the room. I mean, this is a paradox. A mammoth, yeah, it is. And so people, why don't cosmologists worry about this? So I worried about it. And then I thought, well, it's not really a paradox because you're looking at matter and radiation at a maximum entropy state. What you're not seeing directly in that is the gravitation. It's gravitation which is not thermalized. The gravitation was very, very low entropy. And it's low entropy by the uniformity. And you see that in the microwave too. It's very uniform over the whole sky. I'm compressing a long story into a very short few sentences. And doing a great job, yeah. So what I'm saying is that there's a huge puzzle. Why was gravity in this very low entropy state, very highly organized state, everything else was all random? And that to me was the biggest problem in cosmology. The biggest problem, nobody seems to even worry about it. People say they solved all the problems and they don't even worry about it. They think inflation solves it. It doesn't, it can't. Because it's just... Just to clarify, that was your problem with the inflation describing some aspect of the moments right after the big bang? Inflation is supposed to stretch it out and make it all uniform, you see. It doesn't do it because it can only do it if it's uniform already at the beginning. You just have to look at it. I can't go into the details. But it doesn't solve it. And it was completely clear to me it doesn't solve it. But where does the conformal cyclic cosmology of starting to talk about something before that singularity? Well, I began, I was just thinking to myself, how boring this universe is going to be. You've got this exponential expansion. This was discovered early in the, in this century, 21st century. People discovered that these supernova exploding stars showed that the universe is actually undergoing this exponential expansion. So it's a self-similar expansion. And it seems to be a feature of this term that Einstein introduced into his cosmology for the wrong reason. He wanted a universe that was static. He put this new term into his cosmology to make it make sense. It's called the cosmological constant. And then when he got convinced that the universe had a big bang, he retracted it, complaining that this was his greatest blunder. The trouble is it wasn't a blunder. It was actually right. Very ironic. And so the universe seems to be behaving with this cosmological constant. Okay, so this universe is expanding and expanding. What's going to happen in the future? Well, it gets more and more boring for a while. What's the most interesting thing in the universe? Well, there's black holes. The black holes more or less gulp down entire clusters of galaxies. The cluster, it'll swallow up most of our galaxy. We will run into our Andromeda galaxies, black hole, that black hole will swallow our one. They'll get bigger and bigger. And they'll basically swallow up the whole cluster of galaxies, gulp it all down. Pretty well all, most of it, maybe not all, most of it. Okay, and then that'll happen to, there'll be just these black holes around, pretty boring, but still not as boring as it's going to get. It's going to get more boring because these black holes, you wait, you wait, and you wait, and you wait, and you wait an unbelievable length of time. And Hawking's black hole evaporation starts to come in. And the black holes, you just, it's a kind of routine thing. You just, it's incredibly tedious. Finally evaporate away. Each one goes away, disappears with a pop at the end. What could be more boring? It was boring then. Now this is really boring. There's nothing, not even black holes. Universe gets colder and colder and colder and colder. And I thought, this is very, very boring. Now that's not science, is it? But it's emotional. So I thought, who's going to be bored by this universe? Not us, we won't be around. It'll be mostly photons running around. And what the photons do, they don't get bored because it's part of relativity, you see. It's not really that they don't experience anything. That's not the point. The photons get right out to infinity without experience any time. It's the way relativity works. And this was part of what I used to do in my old days when I was looking at gravitational radiation and how things behaved in infinity. Infinity is just like another place. You can squash it down. As long as you don't have any mass in the world, infinity is just another place. The photons get there. The gravitons get there. What do they get? They run to infinity. They say, well, now I'm here, what do I? There's something on the other side, is there? The usual view is just a mathematical notion. There's nothing on the other side. That's just the boundary of it. A nice example is this beautiful series of pictures by the Dutch artist M.C. Escher, you may know them. The ones called Circle Limits. They're a very famous one with the angels and the devils. And you can see them crowding and crowding and crowding up to the edge. Now, the kind of geometry that these angels and devils inhabit, that's their infinity. But from our perspective, infinity is just a place. Okay, they, it's- I'm sorry, can you just take a brief pause? Yes. And just the word you're saying, infinity is just a place. So, for the most part, infinity, sort of even just going back, infinity is a mathematical concept. I think this is one of the things- You think there's an actual physical manifestation? In which way does infinity ever manifest itself in our physical universe? Well, it does in various places. You see, it's a thing that, if you're not a mathematician, you think, oh, infinity, I can't think about that. Mathematicians think about infinity all the time. They get used to the idea, and they just play around with different kinds of infinities, and it becomes no problem. But, yeah, you just have to take my word for it. Now, one of the things is, you see, you take a Euclidean geometry. Well, it just keeps on going, and it goes out to infinity. Now, there's other kinds of geometry, and this is what's called hyperbolic geometry. It's a bit like Euclidean geometry. It's a little bit different. It's like what Escher was trying to describe in his angels and devils. And he learned about this from Coxeter, and he think that's a very nice thing. I try and represent this infinity to this kind of geometry. So it's not quite Euclidean geometry. It's a bit like it, that the angels and the devils inhabit. And their infinity, by this nice transformation, you squash their infinity down, so you can draw it as this nice circle boundary to their universe. Now, from our outside perspective, we can see their infinity as this boundary. Now, what I'm saying is that it's very like that. The infinity that we might experience like those angels and devils in their world can be thought of as a boundary. Now, I found this a very useful way of talking about radiation, gravitational radiation, and things like that. It was a trick, mathematical trick. So now what I'm saying is that that mathematical trick becomes real. That somehow the photons, they need to go somewhere because from their perspective, infinity is just another place. Now, this is a difficult idea to get your mind around. So that's one of the reasons cosmologists are finding a lot of trouble taking me seriously. But to me, it's not been such a wild idea. What's on the other side of that infinity? You have to think, why am I allowed to think of that? You have to think, why am I allowed to think of this? Because photons don't have any mass. And we in physics have beautiful ways of measuring time. There are incredibly precise clocks, atomic and nuclear clocks, unbelievably precise. Why are they so precise? Because of the two most famous equations of 20th century physics. One of them is Einstein's E equals MC squared. What's that tell us? Energy and mass are equivalent. The other one is even older than that, still 20th century, only just. Max Planck, E equals h nu. Nu is a frequency, h is a constant again like C, E is energy. Energy and frequency are equivalent. Put the two together, energy and mass are equivalent, Einstein, energy and frequency are equivalent, Max Planck. Put the two together, mass and frequency are equivalent. Absolutely basic physical principle. If you have a massive entity, a massive particle, it is a clock with a very, very precise frequency. It's not, you can't directly use it, you have to scale it down. So your atomic and nuclear clocks, but that's the basic principle. You scale it down to something you can actually perceive, but it's the same principle. If you have mass, you have beautiful clocks, but the other side of that coin is, if you don't have mass, you don't have clocks. If you don't have clocks, you don't have rulers, you don't have scale. So you don't have space and time. You don't have a measure of the scale of space and time. Oh, scale of space and time. You do have the structure, what's called the conformal structure. You see, it's what the angels and devils have. If you look at the eye of the devil, no matter how close to the boundary it is, it has the same shape, but it has a different size. So you can scale up and you can scale down, but you mustn't change the shape. So it's basically the same idea, but applied to space time now. In the very remote future, you have things which don't measure the scale, but the shape, if you like, is still there. Now that's in the remote future. Now I'm going to do the exact opposite. Now I'm going to go way back into the Big Bang. Now, as you get there, things get hotter and hotter, denser and denser. What's the universe dominated by? Particles moving around almost with the speed of light. When they get almost with the speed of light, okay, they begin to lose the mass too. So for a completely opposite reason, they lose the sense of scale as well. So my crazy idea is the Big Bang and a remote future, they seem completely different. One is extremely dense, extremely hot. The other is very, very rarefied and very, very cold. But if you squash one down by this conformal scaling, you get the other. So although they look and feel very different, they're really almost the same. The remote future on the other side, I'm claiming is that, where do the photons go? They go into the next Big Bang. You've got to get your mind around that crazy idea. Taking a step on the other side of the place that is infinity. Okay, but. Yes, so I'm saying the other side of our Big Bang, now I'm going back into the Big Bang. Back, backwards. There was the remote future of a previous eon. Previous eon. And what I'm saying is that previous eon, there are signals coming through to us which we can see and which we do see. And these are both signals, the two main signals are to do with black holes. One of them is the collisions between black holes. And as they spiral into each other, they release a lot of energy in the form of gravitational waves. Those gravitational waves get through in a certain form into the next eon. That's fascinating that there's some, I mean, maybe you can correct me if I'm wrong, but that means that some information can travel from another eon. Exactly. That is fascinating. I mean, I've seen somewhere described sort of the discussion of the Fermi Paradox, you know, that if there's intelligent life, communication immediately takes you there. We have a paper, my colleague Vaheguru Jain, who I've worked with on these ideas for a while, we have a crazy paper on that, yes. So looking at the Fermi Paradox, yes. Right, so if the universe is just cycling over and over and over, punctuated by the, punctuated the singularity of the Big Bang, and then intelligent, or any kind of intelligent systems can communicate through from eon to eon, why haven't we heard anything from our alien friends? Because we don't know how to look. That's fundamentally the reason, is we. I don't know, you see, it's speculation. I mean, the SETI program is a reasonable thing to do, but still speculation. It's trying to say, okay, maybe not too far away was a civilization which got there first, before us, early enough that they could send us signals, but how far away would you need to go before, I mean, I don't know, we have so little knowledge about that. We haven't seen any signals yet, but it's worth looking. It's worth looking. What I'm trying to say, here's another possible place where you might look. Now, you're not looking at civilizations which got there first. You're looking at those civilizations which were so successful, probably a lot more successful than they were likely to be by the looks of things, which knew how to handle their own global warming or whatever it is, and to get through it all, and to live to a ripe old age, in the sense of a civilization, to the extent that they could harness signals, that they could propagate through, for some reason, of their own desires, whatever we wouldn't know, to other civilizations which might be able to pick up the signals. But what kind of signals would they be? I haven't the foggiest. Let me ask the question. What to you is the most beautiful idea in physics or mathematics or the art at the intersection of the two? I'm gonna have to say complex analysis. I might've said infinities. One of the most single, most beautiful idea, I think, was the fact that you can have infinities of different sizes and so on. But that's, in a way, I think, complex analysis. It's got so much magic in it. It's a very simple idea. You take these, you take numbers, you take the integers, and then you fill them up into the fractions and the real numbers. Imagine you're trying to measure a continuous line. And then you think of how you can solve equations. And what about x squared equals minus one? Well, there's no real number which satisfies that. So you have to think of, well, there's a number called i. You think you invent it. Well, in a certain sense, it's there already. But this number, when you add that square root of minus one to it, you have what's called the complex numbers. And they're an incredible system. If you like, you put one little thing in, you put square root of minus one in, and you get how much benefit out of it? All sorts of things that you'd never imagined before. And it's that amazing, all hiding there in putting that square root of minus one in. I think that's the most magical thing I've seen in mathematics or physics. And it's in quantum mechanics. And in quantum mechanics. You see, it's there already. You might think, what's it doing there? Okay, just a nice, beautiful piece of mathematics. And then suddenly we see, nope. It's the very crucial basis of quantum mechanics. It's there in the way the world works. So on the question of whether math is discovered or invented, it sounds like you may be suggesting that partially it's possible that math is indeed discovered. Oh, absolutely, yes. No, it's more like archeology than you might think. Yes, yes. So let me ask the most ridiculous, maybe the most important question. What is the meaning of life? What gives your life fulfillment, purpose, happiness, and meaning? Why do you think we're here on this, given all the big bang and the infinities of photons that we've talked about? All I would say, I think it's not a stupid question. I mean, there are some people, you know, many of my colleagues who are scientists, and they say, well, that's a stupid question, meaning, well, we're just here because things came together and produced life, and so what? So I think there's more to it, but what there is that's more to it, I have really much idea. And it might be somehow connected to the mechanisms of consciousness that we've been talking about, the mystery there. Yeah, yeah. It's connected with all sorts of, yeah, I think these things are tied up in ways which are, you see, I tend to think the mystery of consciousness is tied up with the mystery of quantum mechanics and how it fits in with the classical world, and that's all to do with the mystery of complex numbers. And there are mysteries there which look like mathematical mysteries, but they seem to have a bearing on the way the physical world operates. We're scratching the surface. We have a long, huge way to go before we really understand that. And it's a beautiful idea that the depth, the mathematical depth could be discovered, and then there's tragedies of Gato's incompleteness along the way that we'll have to somehow figure our ways around. Yeah. So, Roger, it was a huge honor to talk to you. Thank you so much for your time today. It's been my pleasure. Thank you. Thanks for listening to this conversation with Roger Penrose, and thank you to our presenting sponsor, Cash App. Please consider supporting this podcast by getting ExpressVPN at expressvpn.com slash LexPod, and downloading Cash App and using code LexPodcast. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars and Apple Podcasts, support on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words of wisdom that Roger Penrose wrote in his book, The Emperor's New Mind. Beneath all this technicality is the feeling that it is indeed, quote unquote, obvious that the conscious mind cannot work like a computer, even though much of what is involved in mental activity might do so. This is the kind of obviousness that a child can see, though the child may later in life become browbeaten into believing that the obvious problems are quote unquote, non-problems, to be argued into non-existence by careful reasoning and clever choices of definition. Children sometimes see things clearly that are obscured in later life. We often forget the wonder that we felt as children when the cares of the quote unquote, real world have begun to settle on our shoulders. Children are not afraid to pose basic questions that may embarrass us as adults to ask. What happens to each of our streams of consciousness after we die? Where was it before we were born? Might we become or have been someone else? Why do we perceive it all? Why are we here? Why is there a universe here at all in which we can actually be? These are puzzles that tend to come with the awakenings of awareness in any of us, and no doubt, with the awakening of self-awareness within whichever creature or other entity it first came. Thank you for listening and hope to see you next time.

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Robert Langer: Edison of Medicine | Lex Fridman Podcast #105

The following is a conversation with Bob Langer, professor at MIT and one of the most cited researchers in history, specializing in biotechnology fields of drug delivery systems and tissue engineering. He has bridged theory and practice by being a key member and driving force in launching many successful biotech companies out of MIT. This conversation was recorded before the outbreak of the coronavirus pandemic. His research and companies are at the forefront of developing treatment for COVID-19, including a promising vaccine candidate. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with 5 stars on Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. 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I mean, making discoveries and things like that, yeah. So, and then on the magic side, is there some kind of engineering scientific process to the tricks themselves? Do you see, because there's a duality to it. One is you're the, you're sort of the person inside that knows how the whole thing works, how the universe of the magic trick works. And then from the outside observer, which is kind of the role of the scientist, you, the people that observe the magic trick don't know, at least initially, anything that's going on. Do you see that kind of duality? Well, I think the duality that I see is fascination. You know, I think of it, you know, when I watch magic myself, I'm always fascinated by it. Sometimes it's a puzzle to think how it's done, but just the sheer fact that something that you never thought could happen does happen. And I think about that in science too. You know, sometimes you, it's something that you might dream about and hoping to discover, maybe you do in some way or form. What is the most amazing magic trick you've ever seen? Well, there's one I like, which is called the invisible pack. And the way it works is you have this pack and you hold it up. Well, first you say to somebody, this is invisible. And this deck and you say, well, shuffle it, they shuffle it, but you know, they're sort of make-believe. And then you say, okay, I'd like you to pick a card, any card and show it to me. And you show it to me and I look at it. And let's say it's the three of hearts. I said, well, put it back in the deck. But what I'd like you to do is turn it upside down from every other card in the deck. So they do that imaginary. And I said, do you want to shuffle it again? And they shuffle it. And I said, well, so there's still one card upside down from every other card in the deck. I said, what is that? And they said, well, three of hearts. So it just so happens in my back pocket, I have this deck. It's a real deck. I show it to you and I just open it up and there's just one card upside down. And it's the three of hearts. And you can do this trick? I can. If I don't, I would have probably brought it. All right. Well, beautiful. Let's get into the science. As of today, you have over 295,000 citations and age index of 269. You're one of the most cited people in history and the most cited engineer in history. And yet nothing great, I think, is ever achieved without failure. So the interesting part, what rejected papers, ideas, efforts in your life were most painful or had the biggest impact on your life? Well, it's interesting. I mean, I've had plenty of rejection too. But I suppose one way I think about this is that when I first started, and this certainly had an impact both ways, I first started, we made two big discoveries and they were kind of interrelated. I mean, one was I was trying to isolate with my postdoctoral advisor, Judah Folkman, substances that could stop blood vessels from growing. And nobody had done that before. And so that was part A, let's say. And part B is we had to develop a way to study that. And what was critical to study that was to have a way to slowly release those substances for more than a day, maybe months. And that had never been done before either. So we published the first one, we sent to Nature, the journal, and they rejected it. And then we sent it, we revised it, we sent it to Science. And they accepted it. And the other, the opposite happened. We sent it to Science and they rejected it. And then we sent it to Nature and they accepted it. But I have to tell you, when we got the rejections, it was really upsetting. I thought, you know, I'd done some really good work. And Dr. Folkman thought we'd done some really good work. But it was very depressing to, you know, get rejected like that. If you can linger on just the feeling or the thought process when you get the rejection, especially early on in your career, what, I mean, you don't know, now people know you as a brilliant scientist, but at the time, I'm sure you're full of self-doubt. And did you believe that maybe this idea is actually quite terrible, that it could have been done much better, or is there underlying confidence? What was the feelings? Well, you feel depressed, and I felt the same way when I got grants rejected, which I did a lot in the beginning. I guess part of me, you know, you have multiple emotions. One is being sad and being upset and also being maybe a little bit angry because you feel the reviewers didn't get it. But then as I thought about it more, I thought, well, maybe I just didn't explain it well enough. And, you know, you go through stages. And so you say, well, okay, I'll explain it better next time. And certainly you get reviews, and when you get the reviews, you see what they either didn't like or didn't understand, and then you try to incorporate that into your next versions. You've given advice to students to do something big, do something that really can change the world rather than something incremental. How did you yourself seek out such ideas? Is there a process? Is there sort of a rigorous process, or is it more spontaneous? It's more spontaneous. I mean, part of it's exposure to things, part of it's seeing other people. Like I mentioned, Dr. Folkman, he was my postdoctoral advisor. He was very good at that. You could sort of see that he had big ideas, and I certainly met a lot of people who didn't. And I think you could spot an idea that might have potential when you see it, you know, because it could have very broad implications, whereas a lot of people might just keep doing derivative stuff. And so, but it's not something that I've ever done systematically, I don't think. So in the space of ideas, how many are just, when you see them, it's just magic? It's something that you see that could be impactful if you dig deeper? Yeah, it's sort of hard to say because there's multiple levels of ideas. One type of thing is like a new, you know, creation, like that you could engineer tissues for the first time or make tissues from scratch from the first time. But another thing is really just deeply understanding something, and that's important too. So, and that may lead to other things. So sometimes you could think of a new technology, or I thought of a new technology, but other times things came from just the process of trying to discover things. So it's never, and you don't necessarily know, like people talk about aha moments, but I don't know if I've, I mean, I certainly feel like I've had some ideas that I really like, but it's taken me a long time to go from the thought process of starting it to all of a sudden knowing that it might work. So if you take drug delivery, for example, is the notion, is the initial notion kind of a very general one, that we should be able to do something like this? And then you start to ask the questions of, well, how would you do it? And then digging and digging and digging. I think that's right. I think it depends. I mean, there are many different examples. The example I gave about delivering large molecules, which we used to study these blood vessel inhibitors. I mean, there we had to invent something that would do that. But other times it's different. Sometimes it's really understanding what goes on in terms of understanding the mechanisms. And so it's not a single thing, and there are many different parts to it. Over the years, we've invented different, or discovered different principles for aerosols, for delivering genetic therapy agents, all kinds of things. So let's explore some of the key ideas you've touched on in your life. Let's start with the basics. Okay. So first, let me ask, how complicated is the biology and chemistry of the human body from the perspective of trying to affect some parts of it in a positive way? So that you know, for me, especially coming from the field of computer science and computer engineering and robotics, it seems that the human body is exceptionally complicated in how it's structured. It's exceptionally complicated in how the heck you can figure out anything is amazing. Well, I agree with you. I think it's super complicated. I mean, we're still just scratching the surface in many ways. But I feel like we have made progress in different ways. And some of it's by really understanding things like we were just talking about. Other times, you know, you might, or somebody might, we or others might invent technologies that might be helpful on exploring that. And I think over many years, we've understood things better and better, but we still have such a long ways to go. Are there, I mean, if you just look, are there things that, are there knobs that are reliably controllable about the human body? If you consider, is there, is there, so if you start to think about controlling various aspects of when we talk about drug delivery a little bit, but controlling various aspects chemically of the human body, is there a solid understanding across the populations of humans that are solid, reliable knobs that can be controlled? I think that's hard to do. But on the other hand, whenever we make a new drug or medical device, to a certain extent, we're doing that, you know, in a small way, what you just said. But I don't know that there are great knobs. I mean, and we're learning about those knobs all the time. But if there's a biological pathway or something that you can affect or understand, I mean, then that might be such a knob. So what is a pharmaceutical drug? How do you discover a specific one? How do you test it? How do you understand it? How do you ship it? Yeah, well, I'll give an example which goes back to what I said before. So when I was doing my postdoctoral work with Judah Folkman, we wanted to come up with drugs that would stop blood vessels from growing or alternatively make them grow. And actually, people didn't even believe that those things could happen. But- Can we pause on that for a second? Sure. What is a blood vessel? What does it mean for a blood vessel to grow and shrink? And why is that important? Sure. So a blood vessel is, could be an artery or a vein or a capillary. And it, you know, provides oxygen, it provides nutrients, gets rid of waste. So, you know, to different parts of your body, if you, so the blood vessels end up being very, very important. And, you know, if you have cancer, blood vessels grow into the tumor and that's part of what enables the tumor to get bigger. And that's also part of what enables the tumor to metastasize, which means spread throughout the body and ultimately kill somebody. So that was part of what we were trying to do. We were trying, we wanted to see if we could find substances that could stop that from happening. So first, I mean, there are many steps. First, we had to develop a bioassay to study blood vessel growth. Again, there wasn't one. That's where we needed the polymer systems because the blood vessels grew slowly, took months. So after we had the polymer system and we had the bioassay, then I isolated many different molecules initially from cartilage. And almost all of them didn't work. But we were fortunate, we found one, it wasn't purified, but we found one that did work. And that paper, that was this paper I mentioned in Science in 1976, those were really the isolation of some of the very first angiogenesis and blood vessel inhibitors. So- There's a lot of words there. Yeah. So let's, so first of all, polymer molecules, big, big molecules. So what are polymers? What's bioassay? What is the process of trying to isolate this whole thing, simplify it to where you can control and experiment with it? Polymers are like plastics or rubber. What were some of the other questions? Sorry, so a polymer is some plastics and rubber, and that means something that has structure and that could be useful for what? Well, in this case, it would be something that could be useful for delivering a molecule for a long time. So it could slowly diffuse out of that at a controlled rate to where you wanted it to go. So then you would find the idea is that there would be a particular blood vessels that you can target, say they're connected somehow to a tumor, that you could target and over a long period of time to be able to place the polymer there and it'd be delivering a certain kind of chemical. That's correct. I think what you said is good. So that it would deliver the molecule or the chemical that would stop the blood vessels from growing over a long enough time so that it really could happen. So that was sort of what we call the bioassay is the way that we would study that. So sorry, so what is a bioassay? Which part is the bioassay? All of it. In other words, the bioassay is the way you study blood vessel growth. The blood vessel growth. And you can control that somehow with, is there an understanding what kind of chemicals could control the growth of a blood vessel? Sure, well now there is, but then when I started, there wasn't, and that gets to your original question. So you go through various steps. We did the first steps. We showed that A, such molecules existed, and then we developed techniques for studying them. And we even isolated fractions, groups of substances that would do it. But what would happen over the next, we did that in 1976, we published that. What would happen over the next 28 years is other people would follow in our footsteps. I mean, we tried to do some stuff too, but ultimately to make a new drug takes billions of dollars. So what happened was there were different growth factors that people would isolate, sometimes using the techniques that we developed. And then they would figure out using some of those techniques, ways to stop those growth factors and ways to stop the blood vessels from growing. That, like I say, took 28 years. It took billions of dollars and worked by many companies like Genentech. But in 2004, 28 years after we started, the first one of those, Avastin, got approved by the FDA. And that's become one of the top biotech selling drugs in history. And it's been approved for all kinds of cancers and actually for many eye diseases too, where you have abnormal blood vessel growth. Macu- So in general, one of the key ways you can alleviate, so what's the hope in terms of tumors associated with cancerous tumors? What can you help by being able to control the growth of vessels? So if you cut off the blood supply, you cut off the, it's kind of like a war almost, right? If the nutrition is going to the tumor and you can cut it off, I mean, you starve the tumor and it becomes very small, it may disappear or it's gonna be much more amenable to other therapies because it is tiny, you know, like chemotherapy or immunotherapy is gonna have a much easier time against a small tumor than a big one. Is that an obvious idea? I mean, it seems like a very clever strategy in this war against cancer. Well, you know, in retrospect, it's an obvious idea, but when Dr. Folkman, my boss first proposed it, it wasn't, a lot of people thought it was pretty crazy. And so in what sense, if you could sort of linger on it, when you're thinking about these ideas at the time, were you feeling around in the dark? So how much mystery is there about the whole thing? How much just blind experimentation, if you can put yourself in that mindset from years ago? Yeah, well, there was, I mean, for me, actually, it wasn't just the idea, it was that I didn't know a lot of biology or biochemistry. So I certainly felt I was in the dark, but I kept trying and I kept trying to learn and I kept plugging, but I mean, a lot of it was being in the dark. So the human body is complicated, right? We'll establish this. Quantum mechanics and physics is a theory that works incredibly well, but we don't really necessarily understand the underlying nature of it. So are drugs the same in that you can, I mean, you're ultimately trying to show that the thing works to do something that you try to do, but you don't necessarily understand the fundamental mechanisms by which it's doing it? It really varies. I think sometimes people do know them because they've figured out pathways and ways to interfere with them. Other times it is shooting in the dark, it really has varied. And sometimes people make serendipitous discoveries and they don't even realize what they did. So what is the discovery process for a drug? You said a bunch of people have tried to work with this. Is it a kind of a mix of serendipitous discovery and art, or is there a systematic science to trying different chemical reactions and how they affect whatever you're trying to do, like shrink blood vessels? Yeah, I don't think there's a single way, you know, a single way to go about something in terms of characterizing the entire drug discovery process. If I look at the blood vessel one, yeah, there the first step was to have the kinds of theories that Dr. Folkman had. The second step was to have the techniques where you could study blood vessel growth for the first time and at least quantitate or semi-quantitate it. Third step was to find substances that would stop blood vessels from growing. Fourth step was to maybe purify those substances. There are many other steps too. I mean, before you have an effective drug, you have to show that it's safe, you have to show that it's effective, and you start with animals, you ultimately go to patients, and there are multiple kinds of clinical trials you have to do. If you step back, is it amazing to you that we descendants of great apes are able to create things that are, you know, create drugs, chemicals that are able to improve some aspects of our bodies? Or is it quite natural that we're able to discover these kinds of things? Well, at a high level, it is amazing. I mean, evolution's amazing. You know, the way I look at your question, the fact that we have evolved the way we've done, I mean, it's pretty remarkable. So let's talk about drug delivery. What are the difficult problems in drug delivery? What is drug delivery, you know, from starting from your early seminal work in the field to today? Well, drug delivery is getting a drug to go where you want it, at the level you want it, in a safe way. Some of the big challenges, I mean, there are a lot. I mean, I'd say one is, could you target the right cell, like we talked about cancers, or some way to deliver a drug just to a cancer cell and no other cell? Another challenge is to get drugs across different barriers, like could you ever give insulin orally? Could you, or give it passively transdermally? Can you get drugs across the blood-brain barrier? I mean, there are lots of big challenges. Can you make smart drug delivery systems that might respond to physiologic signals in the body? Oh, interesting. So smart, they have some kind of sense, a chemical sensor, or is there something more than a chemical sensor that's able to respond to something in the body? Could be either one. I mean, one example might be if you were diabetic, if you had more, got more glucose, could you get more insulin? But I don't, but that's just an example. Is there some way to control the actual mechanism of delivery in response to what the body's doing? Yes, there is. I mean, one of the things that we've done is encapsulate what are called beta cells. Those are insulin-producing cells in a way that they're safe and protected. And then what'll happen is glucose will go in and cells will make insulin. And so that's an example. So from an AI robotics perspective, how close are these drug delivery systems to something like a robot? Or is it totally wrong to think about them as intelligent agents? And how much room is there to add that kind of intelligence into these delivery systems, perhaps in the future? Yeah, I think it depends on the particular delivery system. You know, of course, one of the things people are concerned about is cost. And if you add a lot of bells and whistles to something, it'll cost more. But I mean, we, for example, have made what I'll call intelligent microchips that can, you know, where you can send a signal and release drug in response to that signal. And I think systems like that microchip someday have the potential to do what you and I were just talking about, that there could be a signal like glucose and it could have some instruction to say when there's more glucose, deliver more insulin. So do you think it's possible that there could be robotic type systems roaming our bodies sort of long-term and be able to deliver certain kinds of drugs in the future? Do you see that kind of future? Someday, I don't think we're very close to it yet, but someday, you know, that's nanotechnology and that would mean even miniaturizing some of the things that I just discussed. And we're certainly not at that point yet, but someday I expect we will be. So some of it is just the shrinking of the technology. That's a part of it. That's one of the things. In general, what role do you see AI sort of, there's a lot of work now with using data to make intelligent, create systems that make intelligent decisions. Do you see any of that data-driven kind of computing systems having a role in any part of this, into the delivery of drugs, the design of drugs, in any part of the chain? I do. I think that AI can be useful in a number of parts of the chain. I mean, one, I think if you get a large amount of information, you know, say you have some chemical data because you've done high throughput screens. And let's, I'll just make this up, but let's say I have, I'm trying to come up with a drug to treat disease X, whatever that disease is, and I have a test for that and hopefully a fast test. And let's say I test 10,000 chemical substances, and a couple work, or most of them don't work. Some maybe work a little. But if I had, if you, with the right kind of artificial intelligence, maybe you could look at the chemical structures and look at what works and see if there's certain commonalities, look at what doesn't work and see what commonalities there are, and then maybe use that somehow to predict the next generation of things that you would test. As a tangent, what are your thoughts on our society's relationship with pharmaceutical drugs? Do we, and perhaps I apologize as this is a philosophical broader question, but do we over-rely on them? Do we improperly prescribe them? In what ways is the system working well? In what way can it improve? Well, I think pharmaceutical drugs are really important. I mean, the life expectancy and life quality of people over many, many years has increased tremendously, and I think that's a really good thing. I think one thing that would also be good is if we could extend that more and more to people in the developing world, which is something that our lab has been doing with the Gates Foundation, or trying to do. So I think ways in which it could improve, I mean, if there was some way to reduce costs, you know, that's certainly an issue people are concerned about. If there was some way to help people in poor countries, that would also be a good thing. And then, of course, we still need to make better drugs for so many diseases. I mean, cancer, diabetes, I mean, there's heart disease and rare diseases. There are many, many situations where it'd be great if we could do better and help more people. Can we talk about another exciting space, which is tissue engineering? What is tissue engineering or regenerative medicine? Yeah, so that tissue engineering or regenerative medicine have to do with building an organ or tissue from scratch. So, you know, someday maybe we can build a liver, you know, or make new cartilage. It also would enable you to, you know, someday create organs on a chip, which people, we and others are trying to do, which might lead to better drug testing and maybe less testing on animals or people. Organs on a chip, that sounds fascinating. So what are the various ways to generate tissue? And how do, so, you know, the one is, of course, from stem cells. Is there other methods? What are the different possible flavors here? Yeah, well, I think, I mean, there's multiple components. One is having generally some type of scaffold. That's what Jay Vacanti and I started many, many years ago. And then on that scaffold, you might put different cell types, which could be a cartilage cell, a bone cell, could be a stem cell that might differentiate into different things, could be more than one cell. And a scaffold, sorry to interrupt, is kind of like a canvas that it's a structure that you can, on which the cells can grow? I think that's a good explanation of what you just said, I'll have to use that. The canvas, that's good. Yeah, so I think that that's fair. You know, and the chip could be such a canvas, could be fibers that are made of plastics and that you'd put in the body someday. And when you say chip, do you mean electronic chip? Not necessarily, it could be though, but it doesn't have to be. It could just be a structure that's not in vivo, so to speak, that's, you know, that's outside the body. So is there- Canvas is not a bad word. So is there a possibility to weave into this canvas a computational component? So if we talk about electronic chips, some ability to sense, control some aspect of this growth process for the tissue? I would say the answer to that is yes. I think right now people are working mostly on validating these kinds of chips for saying, well, it does work as a factory chip. As effectively or hopefully as just putting something in the body. But I think someday what you suggested, it certainly would be possible. So what kind of tissues can we engineer today? Yeah, well, so skin's already been made and approved by the FDA. There are advanced clinical trials, like what are called phase three trials that are at complete or near completion for making new blood vessels. One of my former students, Laura Nicholson, led a lot of that. So that's amazing. So human skin can be grown. That's already approved in the entire FDA process. So that means, one, that means you can grow that tissue and do various kinds of experiments in terms of drugs and so on. But what does that, does that mean it's some kind of healing and treatment of different conditions for inhuman beings? Yes, I mean, they've been approved now for, I mean, different groups have made them, different companies and different professors. But they've been approved for burn victims and for patients with diabetic skin ulcers. That's amazing. Okay, so skin, what else? Well, at different stages, people are like skin, blood vessels. There's clinical trials going now for helping patients hear better, for patients that might be paralyzed, for patients that have different eye problems. I mean, and different groups have worked on just about everything, new liver, new kidneys. I mean, there've been all kinds of work done in this area. Some of it's early, but there's certainly a lot of activity. What about neural tissue? Yeah. The nervous system and even the brain. Well, there've been people that have working on that too. We've done a little bit with that, but there are people who've done a lot on neural stem cells. And I know Evan Snyder, who's been one of our collaborators on some of our spinal cord work, has done work like that. And there've been other people as well. Is there challenges for the, when it is part of the human body, is there challenges to getting the body to accept this new tissue that's being generated? How do you solve that kind of challenge? There can be problems with accepting it. I think maybe in particular, you might mean rejection by the body. So there are multiple ways that people are trying to deal with that. One way is, which was what we've done and with Dan Anderson, who was one of my former postdocs, and I mentioned this a little bit before, for a pancreas is encapsulating the cells. So immune cells or antibodies can't get in and attack them. So that's a way to protect them. Other strategies could be making the cells non-immunogenic, which might be done by different either techniques, which might mask them, or using some gene editing approaches. So there are different ways that people are trying to do that. And of course, if you use the patient's own cells or cells from a close relative, that might be another way. And it increases the likelihood that it'll get accepted if you use the patient's own cells. Yes. And then finally, there's immunosuppressive drugs, which will suppress the immune response. That's right now what's done, say, for a liver transplant. The fact that this whole thing works is fascinating, at least from my outside perspective. Will we one day be able to regenerate any organ or part of the human body, in your view? I mean, it's exciting to think about future possibilities of tissue engineering. Do you see some tissues more difficult than others? What are the possibilities here? Yeah, well, of course, I'm an optimist, and I also feel the timeframe, if we're talking about someday, someday could be hundreds of years. But I think that, yes, someday, I think we will be able to regenerate many things. And there are different strategies that one might use. One might use some cells themselves. One might use some molecules that might help regenerate the cells. And so I think there are different possibilities. What do you think that means for longevity? If we look, maybe not someday, but 10, 20 years out, the possibilities of tissue engineering, the possibilities of the research that you're doing, does it have a significant impact on the longevity, human life? I don't know that we'll see a radical increase in longevity, but I think that in certain areas, we'll see people live better lives and maybe somewhat longer lives. What's the most beautiful scientific idea in bioengineering that you've come across in your years of research? I apologize for the romantic. No, that's an interesting question. I certainly think what's happening right now with CRISPR is a beautiful idea. That certainly wasn't my idea. I mean, but I think it's very interesting here. What people have capitalized on is that there's a mechanism by which bacteria are able to destroy viruses. And that understanding that leads to machinery to sort of cut and paste genes and fix a cell. So that kind of, do you see a promise for that kind of ability to copy and paste? I mean, like we said, the human body is complicated. Is that, that seems exceptionally difficult to do. I think it is exceptionally difficult to do, but that doesn't mean that it won't be done. There's a lot of companies and people trying to do it. And I think in some areas it will be done. Some of the ways that you might lower the bar are just taking, like not necessarily doing it directly, but you could take a cell that might be useful, but you wanna give it some cancer killing capabilities, something like what's called a CAR T cell. And that might be a different way of somehow making a CAR T cell and maybe making it better. So there might be sort of easier things than rather than just fixing the whole body. So the way a lot of things have moved with medicine over time is stepwise. So I can see things that might be easier to do than say fix a brain. That would be very hard to do, but maybe someday that'll happen too. So in terms of stepwise, that's an interesting notion. Do you see that if you look at medicine or bioengineering, do you see that there is these big leaps that happen every decade or so or some distant period, or is it a lot of incremental work? Not, I don't mean to reduce its impact by saying it's incremental, but is there sort of phase shifts in the science, big, big leaps? I think there's both. You know, every so often a new technique or a new technology comes out. I mean, genetic engineering was an example. I mentioned CRISPR. You know, I think every so often things happen that make a big difference, but still there's to try to really make progress, make a new drug, make a new device. There's a lot of things. I don't know if I'd call them incremental, but there's a lot, a lot of work that needs to be done. Yeah, absolutely, so you have over, numbers could be off, but it's a big amount. You have over 1,100 current or pending patents that have been licensed, sub-licensed to over 300 companies. What's your view? What in your view are the strengths and what are the drawbacks of the patenting process? Well, I think for the most part, they're strengths. I think that if you didn't have patents, especially in medicine, you'd never get the funding that it takes to make a new drug or a new device. I mean, which according to Tufts, to make a new drug costs over $2 billion right now. And nobody would even come close to giving you that money, any of that money, if it weren't for the patent system, because then anybody else could do it. That then leads to the negative though. You know, sometimes somebody does have a very successful drug, and you certainly wanna try to make it available to everybody. And so the patent system allowed it to happen in the first place, but maybe it'll impede it after a little bit, or certainly to some people or to some companies, you know, once it is out there. What's the, on the point of the cost, what would you say is the most expensive part of the $2 billion of making the drug? You mean clinical trials? That is by far the most expensive. In terms of money or pain or both? Well, money, but pain goes, it's hard to know. I mean, but usually proving things that are, proving that something new is safe and effective in people is almost always the biggest expense. Could you linger on that for just a little longer and describe what it takes to prove for people that don't know in general, what it takes to prove that something is effective on humans? Well, you'd have to take a particular disease, but the process is you start out with, usually you start out with cells, then you'd go to animal models. Usually you have to do a couple animal models. And of course the animal models aren't perfect for humans. And then you have to do three sets of clinical trials at a minimum, a phase one trial to show that it's safe in small number of patients, phase two trial to show that it's effective in a small number of patients, and a phase three trial to show that it's safe and effective in a large number of patients. And that could end up being hundreds or thousands of patients. And they have to be really carefully controlled studies. And you'd have to manufacture the drug. You'd have to really watch those patients. You have to be very concerned that it is gonna be safe and you look and see, does it treat the disease better than whatever the gold standard was before that? If there was, assuming there was one. That's a really interesting line. Show that it's safe first and then that it's effective. First do no harm. First do no harm. That's right. So how, again, if you can linger on it a little bit, how does the patenting process work? Yeah, well, you do a certain amount of research. Though that's not necessarily has to be the case, but for us, usually it is. Usually we do a certain amount of research and make some findings. And we had a hypothesis, let's say we prove it or we make some discovery, we invent some technique. And then we write something up, what's called a disclosure. We give it to MIT's technology transfer office. They then give it to some patent attorneys and they use that and plus talking to us. And, you know, work on writing a patent. And then you go back and forth with the USPTO. That's the United States Patent and Trademark Office. And, you know, they may not allow it the first, second or third time, but they will tell you why they don't. And you may adjust it and maybe you'll eventually get it. Maybe you won't. So you've been part of launching 40 companies together worth, again, numbers could be outdated, but an estimated $23 billion. You've described your thoughts on a formula for startup success. So perhaps you can describe that formula and in general describe what does it take to build a successful startup? Well, I'd break that down into a couple of categories. And I'm a scientist and certainly from the science standpoint, I'll go over that. But I actually think that really the most important thing is probably the business people that I work with. And, you know, when I look back at the companies that have done well, it's been because we've had great business people. And when they haven't done as well, we haven't as good business people. But from a science standpoint, I think about that we've made some kind of discovery that is almost what I'd call a platform that you could use it for different things. And certainly the drug delivery system example that I gave earlier is a good example that you could use it for drug A, B, C, D, E and so forth. And that I'd like to think that we've taken it far enough so that we've written at least one really good paper in a top journal, hopefully a number, that we've reduced it to practice in animal models, that we've filed patents, maybe had issued patents that have what I'll call very good and broad claims. That's sort of the key on a patent. And then in our case, a lot of times when we've done it, a lot of times it's somebody in the lab, like a post-doc or graduate student that spent a big part of their life doing it and that they wanna work at that company because they have this passion that they wanna see something they did make a difference in people's lives. Maybe you can mention the business component. It's funny to hear Grace add to say that there's value to business folks. Oh yeah, well. That's not always said. So what value, what business instinct is valuable to make a startup successful, a company successful? I think the business aspects are you have to be a good judge of people so that you hire the right people. You have to be strategic so you figure out if you do have that platform that could be used for all these different things, what one are you, and knowing that medical research is so expensive, what thing are you gonna do first, second, third, fourth, and fifth. I think you need to have a good, like what I'll call FDA regulatory clinical trial strategy. I think you have to be able to raise money, credibly. So there are a lot of things. You have to be good with people, good manager of people. So the money and the people part I get, but the stuff before in terms of deciding the A, B, C, D, if you have a platform, which drugs to first take a testing, you see nevertheless scientists as not being too, always too good at that process. Well, I think they're a part of the process, but I'd say there's probably, I'm gonna just make this up, but maybe six or seven criteria that you wanna use, and it's not just science. I mean, the kinds of things that I would think about is is the market big or small? Is the, are there good animal models for it so that you could test it and it wouldn't take 50 years? Are the clinical trials that could be set up ones that, have clear end points where you can make a judgment? And another issue would be competition. Are there other ways that some companies out there are doing it? Another issue would be reimbursement. Can it get reimbursed? So a lot of things that you have manufacturing issues you'd wanna consider. So I think there are really a lot of things that go into whether you, what you do first, second, third, or fourth. So you lead one of the largest academic labs in the world with over $10 million in annual grants and over 100 researchers, probably over a thousand since the lab's beginning. Researchers can be individualistic and eccentric. How do I put it nicely? There you go, eccentric. So what insights into research leadership can you give having to run such a successful lab with so much diverse talent? Well, I don't know that I'm any expert. I think that what you do to me, I mean, I just want, I mean, it's gonna sound very simplistic, but I just want people in the lab to be happy, to be doing things that I hope will make the world a better place, to be working on science that can make the world a better place. And I guess my feeling is if we're able to do that, it kind of runs itself. So how do you make a researcher happy in general? I think when people feel, I mean, this is gonna sound like, again, simplistic or maybe like motherhood and apple pie, but I think if people feel they're working on something really important that can affect many other people's lives and they're making some progress, they'll feel good about it. They'll feel good about themselves and they'll be happy. But through brainstorming and so on, what's your role and how difficult it is as a group in this collaboration to arrive at these big questions that might have impact? Well, the big questions come from many different ways. Sometimes it's trying to, things that I might think of or somebody in the lab might think of, which could be a new technique or to understand something better. But gee, we've had people like Bill Gates and the Gates Foundation come to us and Juvenile Diabetes Foundation come to us and say, gee, could you help us on these things? And I mean, that's good too. It doesn't happen just one way. And I mean, you've kind of mentioned it, happiness, but is there something more, how do you inspire a researcher to do the best work of their life? So you mentioned passion and passion is a kind of fire. And do you see yourself having a role to keep that fire going, to build it up, to inspire the researchers through the pretty difficult process of going from idea to big question to big answer? I think so. I think I try to do that by talking to people, going over their ideas and their progress. I try to do it as an individual, certainly when I talk about my own career, I had my setbacks as different times and people know that, that know me. And you just try to keep pushing and so forth. But yeah, I think I try to do that as the one who leads the lab. So you have this exceptionally successful lab and one of the great institutions in the world, MIT. And yet sort of at least in my neck of the woods in computer science and artificial intelligence, a lot of the research is kind of, a lot of the great researchers, not everyone, but some are kind of going to industry. A lot of the research is moving to industry. What do you think about the future of science in general? Is there drawbacks? Is there strength to the academic field? Is there strength to the academic environment that you hope will persist? How does it need to change? What needs to stay the same? What are your thoughts on this whole landscape of science and its future? Well, first I think going into industry is good, but I think being in academia is good. I have lots of students who've done both and they've had great careers doing both. I think from an academic standpoint, I mean, the biggest concern probably that people feel today, at a place like MIT or other research heavy institutions is gonna be funding and particular funding that's not super directed, so that you can do basic research. I think that's probably the number one thing, but it would be great if we as a society could come up with better ways to teach, so that people all over could learn better. So I think there are a number of things that would be good to be able to do better. So again, you're very successful in terms of funding, but do you still feel the pressure of that, of having to seek funding? Does it affect the science? Or can you simply focus on doing the best work of your life and the funding comes along with that? I'd say the last 10 or 15 years, we've done pretty well funding, but I always worry about it. It's like you're still operating on more soft money than hard. And so I always worry about it, but we've been fortunate that places have come to us like the Gates Foundation and others, Juvenile Diabetes Foundation, some companies, and they're willing to give us funding and we've gotten government money as well. We have a number of NIH grants and I've always had that. And that's important to me too. That's important to me too. So I worry about it, but I just view that as a part of the process. Now, if you put yourself in the shoes of a philanthropist, like say I gave you $100 billion right now, but you couldn't spend it on your own research. So how hard is it to decide which labs to invest in, which ideas, which problems, which solutions? Because funding is such an important part of progression of science in today's society. So if you put yourself in the shoes of a philanthropist, how hard is that problem? How would you go about solving it? Sure. Well, I think what I do, the first thing is different philanthropists have different visions. And I think the first thing is to form a concrete vision of what you want. Some people, I'll just give you two examples of people that I know, David Koch was very interested in cancer research. And part of that was that he had cancer, and prostate cancer. And a number of people do that along those lines. They've had somebody, they've either had cancer themselves or somebody they loved had cancer and they wanna put money into cancer research. Bill Gates, on the other hand, I think when he had got his fortune, I mean, he thought about it and felt, well, how could he have the greatest impact? And he thought about helping people in the developing world and medicines and different things like that, like vaccines that might be really helpful for people in the developing world. So I think first you start out with that vision. Once you start out with that vision, whatever vision it is, then I think you try to ask the question, who in the world does the best work? If that was your goal. I mean, but you really, I think have to have a defined vision. Vision first. Yeah, that comes. And I think that's what people do. I mean, I have never seen anybody do it otherwise. I mean, and that by the way, it may not be the best thing overall. I mean, I think it's good that all those things happen, but what you really wanna do, and I'll make a contrast in a second, in addition to funding important areas like what both of those people did is to help young people. And they may be at odds with each other because a farm or a lab like ours, which is, I'm older, is might be very good at addressing some of those kinds of problems, but I'm not young. I train a lot of people who are young, but it's not the same as helping somebody who's an assistant professor someplace. So I think what's I think been good about our thing, our society or things overall are that there are people who come at it from different ways. And the combination, the confluence of the government funding, the certain foundations that fund things and other foundations that wanna see disease treated, well, then they can go seek out people or they can put a request for proposals and see who does the best. I'd say both David Koch and Bill Gates did exactly that. They sought out people, both of them or their foundations that they were involved in sought out people like myself, but they also had requests for proposals. And you mentioned young people, and that reminds me of something you said in an interview of Written Somewhere that said some of your initial struggles in terms of finding a faculty position or so on that you didn't quite for people fit into a particular bucket, a particular- Right. Can you speak to that? How do you see limitations to the academic system that it does have such buckets? How can we allow for people who are brilliant but outside the disciplines of the previous decade? Yeah, well, I think that's a great question. I think the department has have to have a vision, and some of them do. Every so often, there are institutes or labs that do that. I mean, at MIT, I think that's done sometimes. I know mechanical engineering department just had a search and they hired Gio Traverso, who was one of my, he was a fellow with me, but he's actually a molecular biologist and a gastroenterologist. And he's one of the best in the world, but he's also done some great mechanical engineering and designing some new pills and things like that. And they picked him, and boy, I give them a lot of credit. I mean, that's vision to pick somebody. And I think they'll be the richer for. I think the Media Lab has certainly hired people like Ed Boyden and others who have done very different things. And so I think that that's part of the vision of the leadership who do things like that. Do you think one day, you've mentioned David Koch and cancer, do you think one day we'll cure cancer? Yeah, I mean, of course, one day, I don't know how long that day will come. Soon. But soon, no, but I think- So you think it is a grand challenge. It is a grand challenge, and it's not just solvable within a few years. I don't think very many things are solvable in a few years. There's some good ideas that people are working on, but I mean, all cancers, that's pretty tough. If we do get the cure, what will the cure look like? Do you think which mechanisms, which disciplines will help us arrive at that cure from all the amazing work you've done that has touched on cancer? No, I think it'll be a combination of biology and engineering. I think it'll be biology to understand the right genetic mechanisms to solve this problem and maybe the right immunological mechanisms and engineering in the sense of producing the molecules, developing the right delivery systems, targeting it, or whatever else needs to be done. Well, that's a beautiful vision for engineering. So on a lighter topic, I've read that you love chocolate and mentioned two places, Ben and Bill's Chocolate Emporium and the chocolate cookies, the Soho Globs from Rosie's Bakery in Chestnut Hill. I went to their website, and I was trying to finish a paper last night, and there's a deadline today, and yet I was wasting way too much time at 3 a.m. instead of writing the paper, staring at the Rosie Baker's cookies, which are just, look incredible. The Soho Globs just look incredible. But for me, oatmeal white raisin cookies won my heart just from the pictures. Do you think one day we'll be able to engineer the perfect cookie with the help of chemistry and maybe a bit of data-driven artificial intelligence, or is cookies something that's more art than engineering? I think there's some of both. I think engineering will probably help someday. And what about chocolate? Same thing, same thing. You have to go to see some of David Edwards' stuff. He was one of my postdocs, and he's a professor at Harvard, but he also started Cafe Art Sciences, and it's just a really cool restaurant around here. But he also has companies that do ways of looking at fragrances and trying to use engineering in new ways. And so I think, I mean, that's just an example, but I expect someday that AI and engineering will play a role in almost everything. Including creating the perfect cookie. Yes. Well, I dream of that day as well. So when you look back at your life, having accomplished an incredible amount of positive impact on the world through science and engineering, what are you most proud of? My students. I really feel when I look at that, we've probably had close to a thousand students go through the lab, and they've done incredibly well. I think 18 are in the National Academy of Engineering, 16 in the National Academy of Medicine. And I mean, they've been CEOs of companies, presidents of universities. And they've done, I think, eight are faculty at MIT, maybe about 12 at Harvard. I mean, so it really makes you feel good to think that the people, they're not my children, but they're close to my children in a way. And it makes you feel really good to see them have such great lives and them do so much good and be happy. Well, I think that's a perfect way to end it, Bob. Thank you so much for talking today. My pleasure. It was an honor. Good questions, thank you. Thanks for listening to this conversation with Bob Langer. And thank you to our sponsors, Cash App and Masterclass. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST and signing up at masterclass.com slash LEX. Click on the links, buy all the stuff. It's the best way to support this podcast and the journey I'm on in my research and startup. If you enjoy this thing, subscribe on YouTube, review it with 5,000 Apple Podcast, support it on Patreon, or connect with me on Twitter at Lex Friedman, spelled without the E, just F-R-I-D-M-A-N. And now let me leave you with some words from Bill Bryson in his book, A Short History of Nearly Everything. If this book has a lesson, it is that we're awfully lucky to be here. And by we, I mean every living thing. To attain any kind of life in this universe of ours appears to be quite an achievement. As humans, we're doubly lucky, of course. We enjoy not only the privilege of existence, but also the singular ability to appreciate it, and even in a multitude of ways to make it better. It is talent we have only barely begun to grasp. Thank you for listening, and hope to see you next time.

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Konstantin Batygin: Planet 9 and the Edge of Our Solar System | Lex Fridman Podcast #201

The following is a conversation with Konstantin Batygin, planetary astrophysicist at Caltech, interested in, among other things, the search for the distant, the mysterious, Planet 9 in the outer regions of our solar system. Quick mention of our sponsors, Squarespace, Litterati, Onnit, and Ni. Check them out in the description to support this podcast. As a side note, let me say that our little sun is orbited by not just a few planets in the planetary region, but trillions of objects in the Kuiper belt and the Oort cloud that extends over three light years out. This to me is amazing, since Proxima Centauri, the closest star to our sun, is only 4.2 light years away, and all of it is mostly covered in darkness. When I get a chance to go out swimming in the ocean, far from the shore, I'm sometimes overcome by the terrifying and the exciting feeling of not knowing what's there in the deep darkness. That's how I feel about the edge of our solar system. One day, I hope humans will travel there, or at the very least, AI systems that carry the flame of human consciousness. This is the Lux Friedman Podcast, and here's my conversation with Konstantin Batygin. What is Planet Nine? Planet Nine is an object that we believe lives in the solar system beyond the orbit of Neptune. It orbits the sun with a period of about 10,000 years, and is about five Earth masses. So that's a hypothesized object. There's some evidence for this kind of object. There's a bunch of different explanations. Can you give an overview of the planets in our solar system? How many are there? What do we know and not know about them at a high level? All right, that sounds like a good plan. So look, the solar system basically is comprised of two parts, the inner and the outer solar system. The inner solar system has the planets, Mercury, Venus, Earth, and Mars. Now, Mercury is about 40% of the orbital separation of where the Earth is. It's closer to the sun. Venus is about 70%. Then Mars is about 160% further away from the sun than is the Earth. These planets that we, one of them we occupy, right, are pretty small. They're two leading order, sort of heavily overgrown asteroids, if you will. And this becomes evident when you move out further in the solar system and encounter Jupiter, which is 316 Earth masses, right, 10 times the size. Saturn is another huge one. It's 90 Earth masses at about 10 times the separation from the sun as is the Earth. And then you have Uranus and Neptune at 20 and 30, respectively. For a long time, that is where the kind of massive part of the solar system ended. But what we've learned in the last 30 years is that beyond Neptune, there's this expansive field of icy debris, a second icy asteroid belt in the solar system. A lot of people have heard of the asteroid belt, which lives between Mars and Jupiter, right? That's a pretty common thing that people like to imagine and draw on lunchboxes and stuff. But beyond Neptune, there's a much more massive and much more radially expansive field of debris. Pluto, by the way, it belongs to that second icy asteroid belt, which we call the Kuiper belt. It's just a big object within that population of bodies. Oh, Pluto the planet. Pluto, the dwarf planet, the former planet. Why is Pluto not a planet anymore? I mean, it's tiny. We used to- Size matters when it comes to planets. Oh, 100%. It's actually a fascinating story. When Pluto was discovered in 1930, the reason it was discovered in the first place is because astronomers at the time were looking for a seven-Earth mass planet somewhere beyond Neptune. It was hypothesized that such an object exists. When they found something, they interpreted that as a seven-Earth mass planet and immediately revised its mass downward because they couldn't resolve the object with the telescope. So, it looked like just a point mass star rather than a physical disk. They said, well, maybe it's not seven, maybe it's one. And then, over the next, I guess, 40 years, Pluto's mass kept getting revised downwards, downwards, downwards until it was realized that it's like 500 times less massive than the Earth. I mean, Pluto's surface area is almost perfectly equal to the surface area of Russia, actually. And Russia is big, but it's not a planet. Well, I mean, actually, we can touch more on that. That's another discussion. So, in some sense, earlier in the century, Pluto represented kind of our ignorance about the edges of the solar system. And perhaps, planet nine is the thing that represents our ignorance about now the modern set of ignorances about the edges of our solar system. That's a good way to put it. By the way, just imagining this belt of debris at the edge of our solar system is incredible. Can you talk about it a little bit? What is the Kuiper belt? And what is the Oort cloud? Yeah, okay. So, look, the simple way to think about it is that if you imagine Neptune's orbit like a circle, right, kind of maybe a factor of one and a half, 1.3 times bigger on a radius of 1.3 times bigger, you've got a whole collection of icy objects. Most of these objects are sort of the size of Austin, you know, maybe a little bit smaller. If you then zoom out, right, and explore the orbits of the most long period Kuiper belt object, these are the things that have the biggest orbits and take the longest time to go around the sun, then what you find is that beyond a critical orbit size, beyond a critical orbit period, which is about 4,000 years, you start to see weird structure, like all the orbits sort of point into one direction. And all the orbits are kind of tilted in the same way, by about 20 degrees with respect to the sun. This is particularly pronounced in orbits that are not heavily affected by Neptune. So, there you start to see this weird dichotomy where there are objects which are stable, which Neptune does not mess with gravitationally, and unstable objects. The unstable objects are basically all over the place because they're being, you know, kicked around by Neptune. The stable orbits show this remarkable pattern of clustering. We, back I guess five years ago, interpreted this pattern of clustering as a gravitational one-way sign, the existence of a planet, a distant planet, right? Something that is shepherding and confining these orbits together. Of course, you have to have some skepticism when you're talking about these things. You have to ask the question of, okay, how statistically significant is this clustering? And there are many authors that have indeed called that into question. We have done our own analyses. And basically, just like with all statistics where, you know, there's kind of like, you know, multiple ways to do the exercise, you can either ask the question of, if I have a telescope that has, you know, surveyed this part of the sky, what are the chances that I would discover this clustering? That basically tells you that you have zero confidence, right? Like, that does not give you a confident answer one way or another. Another way to do the statistics, which is what we prefer to do, is to say, we have a whole night sky of discoveries in the Kuiper Belt, right? And if we have some object over there, which has right ascension and declination, which is a way to say it's there on the sky, and it has some brightness, that means somebody looked over there and discovered an object of, was able to discover an object of that brightness or brighter. Through that analysis, you can construct a whole map on the sky of kind of where all of the surveys that have ever been done have collectively looked. So, if you do the exercise this way, the false alarm probability of the clustering on which the Planet 9 hypothesis is built is about 0.4%. Wow, okay, so there's a million questions here. One, when you say bright objects, why are they bright? Are we talking about actual objects within the Kuiper Belt or the stuff we see through the Kuiper Belt? This is the actual stuff we see in the Kuiper Belt. The way you go about discovering Kuiper Belt objects is pretty easy. I mean, it's easy in theory, right? Hard in practice. Yeah. All you do is you take snapshots of the sky, right? Choose that direction and take a high exposure snapshot. Then you wait a night, and you do it again. And then you wait another night, and you do it again. Objects that are just random stars in the galaxy don't move on the sky, whereas objects in the solar system will slowly move. This is no different than if you're driving down the freeway, it looks like trees are going by you faster than the clouds, right? This is parallax. This is parallax. That's it. It's just they're reflecting light off of the sun, and it's going back and hitting this. There's a little bit of a glimmer from the different objects that you can see based on the reflection from the sun. So, like, there's actual light. It's not darkness. That's right. These are just big icicles, basically, that are just reflecting sunlight back at you. It's then easy to understand why it's so hard to discover them because light has to travel to something like 40 times the distance between the Earth and the sun and then get reflected back. Was that like an hour travel? Yeah, that's right. That's something like that because the Earth to the sun is eight minutes, I believe. And so... Something, you know. Yeah, hours. Yeah, in that order of magnitude. So, that's interesting. So, you have to account for all of that. And then there's a huge amount of data, pixels that are coming from the pictures. And you have to integrate all of that together to paint a sort of like a high estimate of the different objects. Can you track them? Can you be like, that's Bob? Like, can you like... Yes, exactly. In fact, one of them is named Joe Biden. I mean, I'm not, like, this is not even a joke. Right. Okay. Is there a Trump one or no? No, no. I don't know. I haven't checked for that. But like, the way it works is if you discover one, you right away get a license plate for it. Okay. So, like, the first four numbers is the first year that this object has appeared on, you know, in the data set, if you will. And then there's like this code that follows it, which basically tells you where in the sky it is. Right. So, one of the really interesting Kuiper Belt objects, which is very much part of the Planet Nine story is called VP113. Because Joe Biden was vice president at the time, you know, got nicknamed Biden. VP113, you said? Yeah. He got nicknamed Biden. Beautiful. What's the fingerprint for any particular object? Like, how do you know it's the same one? Or it's just kind of like, yeah, from night to night, you take a picture, how do you know it's the same object? Yeah. So, the way you know is it appears in almost exactly the same part of the sky, except for it moves by. And this is why actually you need at least three nights. Because oftentimes asteroids, which are much closer to the Earth, will appear to move only slightly, but then on the third night will move away. So, that third night is really there to detect acceleration. Now, the thing that I didn't really realize until, you know, I started observing together with my partner in crime and all this, Mike Brown, is just the fact that for the first year, for the first year when you make these detections, the only thing you really know with confidence is where it is on the night sky and how far away it is. Okay? That's it. You don't know anything about the orbit because over three days, the object just moves so little, right? That whole motion on the sky is entirely coming from motion of the Earth, right? So, the Earth is kind of the car, the object is the tree, and you see it move. So, then to get some confident information about what its orbit looks like, you have to come back a year later and then measure it again. Oh, interesting. So, do three nights, then come back a year later and do another three nights. So, you get the velocity, the acceleration from the three nights, and then you have the maybe- The additional. The additional information. Because an orbit is basically described by six parameters. So, you at least need six independent points, but in reality, you need many more observations to really pin down the orbit well. And from that, you're able to construct for that one particular object an orbit, and then there's, of course, like how many objects are there? There's like four-ish thousand now. But like in the future, that could be like millions? Oh, sure. Oh, sure. In fact, these things are hard to predict, but there's a new observatory called the Vera Rubin Observatory, which is coming online maybe next year. I mean, with COVID, these things are a little bit more uncertain, but they've actually been making great progress with construction. And so, that telescope is just going to sort of scan the night sky every day automatically. And it's such an efficient survey that it might increase the census of the distant Kuiper Belt, the things that I'm interested in, by a factor of 100. I mean, that would be really cool. And yeah, that's an incredible- I mean, they might just find planet nine too. I mean, that's- Like almost like literally pictures, like visually. I mean, sure. Yeah. Like the first detection you make, all you know is where it is in the sky and how far away it is. If something is 500 times away from the sun, as far away from the sun as the earth, you know that's planet nine. That's when the story concludes. And then you can study it. Now you can study it. Yeah. By the way, I'm going to use that as like, I don't know, a pickup line or a dating strategy, like see the person for three days and then don't see them at all and then see them again in a year to determine the orbit. And over time, you figure out if sort of from a cosmic perspective, this whole thing works out. Yeah. I have no dating advice to give. I was going to use this as a metaphor to somehow map it onto the human condition. Okay. You mentioned the Kuiper belt. What's the Oort cloud? If you look at the Neptune orbit as one, then the Kuiper belt is like 1.3 out there. And then we get farther and farther into the darkness. What's- So, okay. You've got the main Kuiper belt, which is about say 1.3, 1.5. Then you have something called the scattered disk, which is kind of an extension of the Kuiper belt. It's a bunch of these long, very elliptical orbits that hug the orbit of Neptune but come out very far. So, the scattered disk with the current senses, like some of the longest orbits we know of have a semi-major axis, so half the orbit length, roughly speaking, of about a thousand, thousand times the distance between the Earth and the Sun. Wow. Now, if you keep moving out, okay, eventually, once you're at sort of 10,000 to 100,000 roughly, that's where the Oort cloud is. Now, the Oort cloud is a distinct population of icy bodies, and it's distinct from the Kuiper belt. In fact, it's so expansive that it ends roughly halfway between us and the next star. Its edge is just dictated by to what extent does the solar gravity reach. Solar gravity reaches that far? Yeah. So, it has to- Wow. Yeah. So, in fact- Imagining this is a little bit overwhelming. So, there's like a giant, like vast, icy rock thingy. It's like a sphere. It's like, you know, it's like it's an almost spherical structure that encircles the Sun. And all the long period comets come from the Oort cloud. They come, the way that they appear, I mean, for already, I don't know, hundreds of years, we've been detecting occasionally like a comet will come in and it seemingly comes out of nowhere. The reason these long period comets appear on very, very long time scales, right? These Oort cloud objects that are sitting, you know, 30,000 times as far away from the Sun as is the Earth, actually interact with the gravity of the galaxy, the tide, effectively the tide that the galaxy exerts upon them and their orbits slowly change and they elongate to the point where once they, their closest approach to the Sun starts to reach a critical distance where ice starts to sublimate, then we discover them as comets because then the ice comes off of them. They look beautiful in the night sky, et cetera, but they're all coming from, you know, really, really far away. So, is there, are any of them coming our way from collisions? Like how many collisions are there? Or is there a bunch of space for them to move around? Yeah, there's zero, like it's completely collisionless. Out there, the physical radii of objects are so small compared to the distance between them, right? It's just, it is truly a collisionless environment. I don't know, I think that probably in the age of the solar system, there have literally been zero collisions in the Oort cloud. Wow. When you like draw a picture of the solar system, everything's really close together, so everything I guess here is spaced far apart. Do rogue planets like fly in every once in a while and join, not rogue planets, but rogue objects from out there? Oh, sure, oh, sure, yeah. Join the party? Yeah, absolutely. We've seen a couple of them in the last three or so years, maybe four years now. One, the first one was the one called Oumouamoua, it's been all over the news. The second one was Comet Borisov discovered by a guy named Borisov. Yeah, so the way you know they're coming from elsewhere is unlike solar system objects which travel on elliptical paths around the sun, these guys travel on hyperbolic paths. So, they come in, say hello, and then they're gone. And the fact that they exist is totally like not surprising, right? Neptune is constantly ejecting Kuiper belt objects into interstellar space. Our solar system itself is sort of leaking icy debris and ejecting it. So, presumably every planetary systems around other stars do exactly the same thing. Let me ask you about the millions of objects that are part of the Kuiper belt and part of the Oort cloud. Do you think some of them have primitive life? It kind of makes you sad if there's primitive life there and they're just kind of lonely out there in space. How many of them do you think have life, like bacterial life? Probably a negligible amount. Zero with a plus on top. Zero plus plus. Yeah. So, if you and I took a little trip to the interstellar medium, I think we would develop cancer and die real fast, right? It's rough. Yeah, it's a pretty hostile radiation environment. You don't actually have to go to the interstellar medium, you just have to leave the Earth's magnetic field too. And then you're not doing so well suddenly. So, this idea of life kind of traveling between places, it's not entirely implausible, but you really have to twist, I think, a lot of parameters. One of the problems we have is we don't actually know how life originates, right? So, it's kind of a second order question of survival in the interstellar medium and how resilient it is because we think you require water and that's certainly the case for the Earth, but we really don't know for sure. That said, I will argue that the question of are there aliens out there is a very boring question because the answer is of course there are. I mean, we know that there are planets around almost every star. Of course there are other life forms. Life is not some specific thing that happened on the Earth and that's it, right? That's a statistical impossibility. Yeah, but the difficult question is before even the fact that we don't know how life originates, I don't think we even know what life is, like, definitionally. Yeah. Like, formalizing a kind of picture of, in terms of the mechanism we would use to search for life out there or even when we're on a planet to say, is this life? Is this rock that just moved from where it was yesterday life? Or maybe not even a rock, something else. I got to tell you, I want to know what life is, okay? And I want you to show me. I think there's a song to basically accompany every single thing we talk about today and probably half of them are love songs and somehow we'll integrate George Michael into the whole thing. Okay, so your intuition is there's life everywhere in our universe. Do you think there's intelligent life out there? I think it's entirely plausible. I mean, it's entirely plausible. I think there's intelligent life on Earth. And so, yeah, taking that, like, say whatever this thing we got on Earth, whether it's dolphins or humans, say that's intelligent. Definitely dolphins. I mean, have you seen the dolphins? Well, they do some cruel stuff to each other. So if cruelty is a definition of intelligence, they're pretty good. And then humans are pretty good in that regard. And then there's like pigs are very intelligent. I actually had a chance to hang out with pigs recently. And they're, aside from the fact they were trying to eat me, they're very, they're very, they love food. They love food, but there's an intelligence to their eyes that was kind of, like, haunts me, because I also love to eat meat. And then to meet the thing I later ate, and that was very intelligent and almost charismatic with the way it was expressing himself, herself, itself, was quite incredible. So all that to say is, if we have intelligent life here on Earth, if we take dolphins, pigs, humans, from the perspective of planetary science, how unique is Earth? Okay, so Earth is not a common outcome of the planet formation process. It's probably a something on the order of maybe a 1% effect. And by Earth, I mean, not just an Earth-mass planet, okay? I mean, the architecture of the solar system that allows the Earth to exist in its kind of very temperate way. One thing to understand, and this is pretty crucial, right, is that the Earth itself formed well after the gas disk that formed the giant planets had already dissipated. You see, stars start out with, you know, the star and then a disk of gas and dust that encircles it, okay? From this disk of gas and dust, big planets can emerge. And we have, over the last, you know, two, three decades, discovered thousands of extrasolar planets as an orbit of other stars. What we see is that many of them are, you know, have these expansive hydrogen-helium atmospheres. The fact that the Earth doesn't is deeply connected to the fact that Earth took about 100 million years to form. So we missed that, you know, train, so to speak, to get that hydrogen- helium atmosphere. That's why, actually, we can see the sky, right? That's why the sky is, well, at least in most places, that's why the atmosphere is not completely opaque. With that, you know, kind of thinking in mind, I would argue that we're getting the kind of emergent pictures that the Earth is not, you know, everywhere, right? There's sort of the sci-fi view of things where we go to some other star and we just land on random planets and they're all Earth-like. That's totally not true. But even a low probability event, even if you imagine that Earth is a one in a million or one in a, you know, one in 10 million occurrence, there are 10 to the 12 stars in the galaxy, right? So you just, you always win by- LARGE NUMBERS. That's right, by supply. They save you. Well, you've hypothesized that our solar system once possessed a population of short-period planets that were destroyed by the evil Jupiter migrating through the solar nebula. Can you explain? If I was to say what was the kind of the key outcome of searches for extrasolar planets, it is that most stars are encircled by short-period planets that are, you know, a few Earth masses, right? So a few times bigger than the Earth and have orbital periods that kind of range from days to weeks. Oh, wow. Now, if you go and ask the solar system what's in our region, right, in that region, it's completely empty, right? It's just, it's astonishingly hollow. And I think, you know, from the Sun is not some, you know, special star that decided that it was going to form the solar system. So I think, you know, the natural thing to assume is that the same processes of planet formation that occurred everywhere else also occurred in the solar system. Following this logic, it's not implausible to imagine that the solar system once possessed a system of intra-Mercurian, like, you know, compact system of planets. So then we asked ourselves, would such a system survive to this day? And the answer is no. At least our calculations suggest it's highly unlikely because of the formation of Jupiter. And Jupiter's primordial kind of wandering through the solar system would have sent this collisional field of debris that would have pushed that system of planets onto the Sun. So was Jupiter, this primordial wandering, what did Jupiter look like? Like, why was it wandering? It didn't have the orbit it has today? We're pretty certain that giant planets like Jupiter, when they form, they migrate. The reason they migrate is, you know, on a detailed level, perhaps difficult to explain, but just in a qualitative sense, they form in this fluid disk of gas and dust. So, it's kind of like saying, okay, if I plop down a raft somewhere in the ocean, will it stay where you plop it down, or will it kind of get carried around? It's not really a good analogy because it's not like Jupiter is being advected by the currents of, you know, gas and dust. But the way it migrates is it carves out a hole in the disk, and then by interacting with the disk gravitationally, it can change its orbit. The fact that the solar system has both Jupiter and Saturn, here, complicates things a lot, right? Because you have to solve the problem of the evolution of the gas disk, the evolution of Jupiter's orbit in the gas disk, plus evolution of Saturn's and their mutual interaction. The common outcome of solving that problem, though, is pretty easy to explain. Jupiter forms, its orbit shrinks, and then once Saturn forms, its orbit catches up, basically, to the orbit of Jupiter, and they both come out. So, there's this inward-outward pattern of Jupiter's early motion that happens sort of within the last million years of the lifetime of the solar system's primordial disk. So, while this is happening, if our calculations are correct, which I think they are, you can destroy this inner system of, you know, few Earth-mass planets. And then, in the aftermath of all this violence, you form the terrestrial planets. Lex May Where would they come from in that case? So, Jupiter clears out the space, and then there's a few terrestrial planets that come in, and those come in from the disk somewhere, like one of the larger objects? David Yeah, what actually happens in these calculations is you leave behind a rather mass-depleted remnant disk, only a couple Earth masses. So, then from that remnant population, an annulus of material, over 100 million years, by just collisions, you grow the Earth and the Moon and everything else. Lex May You said amulus? David Annulus. Lex May Annulus. That's a beautiful word. What does that mean? David Well, it's like a disk that's kind of thin. It's like a, yeah, it's something that is, you know, a disk that's so thin it's almost flirting with being a ring. Lex May Like, I was gonna say this reminds me of Lord of the Rings. So, like, the word just feels like it belongs in a Tolkien novel. Okay, so that's incredible. And so, that, in your senses, you said like 1%, that's a rare, the way Jupiter and Saturn danced and cleared out, you know, cleared out the short period debris and then changed the gravitational landscape, that's a pretty rare thing too. David It's rare and moreover, like, you don't even have to go to our calculations, you can just ask the night sky, how many stars have Jupiter and Saturn analogs? And the answer is Jupiter and Saturn analogs are found around only 10% of Sun-like stars. So, they themselves, like you kind of have to score an A- or better on the test to, you know, on the planet formation test to become a solar system analog, even in that basic sense. And moreover, you know, lower mass stars, which are very numerous in the galaxy, so-called M-dwarves, think like 0% of them, well, maybe like a negligible fraction of them have giant planets. Giant planets are a rare, you know, outcome of planet formation. One of the really big problems that remain unanswered is why. We don't actually understand why they're so rare. Matthew How hard is it to simulate all of the things that we've been talking about, each of the things we've been talking about, and maybe one day, all of the things we've been talking about and beyond. Meaning, like, from the initial primordial solar system, you know, a bunch of disks with, I don't know, billions, trillions of objects in them, like simulate that such that you eventually get a Jupiter and a Saturn, and then eventually you get the Jupiter and the Saturn that clear out a disk, change the gravitational landscape, then Earth pops up, like that whole thing, and then be able to do that for every other system in the- every other star in the galaxy, and then be able to do that for other galaxies as well. Yeah, so- Maybe start from the smallest simulation, like what is actually being done today? I mean, even the smallest simulation is probably super, super difficult. Even just like one object in the Kuiper belt is probably super difficult to simulate. I mean, I think it's super easy. I mean, like, it's just not that hard. But, you know, let's ask the most kind of basic problem. Okay, so the problem of having a star and something that's in orbit of it, that you don't need a simulation for, like, you can just write that down on a piece of paper. There's gravity, like, yeah, I guess it's important to try to- you know, one way to simulate objects in our solar system is to build the universe from scratch. Okay, we'll get to building the universe from scratch in a sec, but let me just kind of go through the hierarchy of what, you know, what we do. Two objects. Two objects, analytically solvable, like, we can figure it out very easily if you just- I don't think you- yeah, you don't need to know calculus. It helps to know calculus, but you don't necessarily need to know calculus. Three objects that are gravitationally interacting, the solution is chaotic. Doesn't matter how many simulations you do, the answer loses meaning after some time. I feel like that is a metaphor for dating as well, but go on. I apologize. Yeah, so, the fact that you go from analytically solvable to unpredictable, you know, when you're simulation goes from two bodies to three bodies should immediately tell you that the exercise of trying to engineer a calculation where you form the entire solar system from scratch and hope to have some predictive answer is a futile one, right? We will never succeed at such a simulation. I feel like, sorry, just to clarify, you mean, like, explicitly having a clear equation that generalizes the whole process enough to be able to make a prediction? Or do you mean, actually, like, literally simulating the objects as a hopeless pursuit once it goes beyond three? Well, the simulating them is not a hopeless pursuit, but the outcome becomes a statistical one. What's actually quite interesting is I think we have all the equations figured out, right? Like, you know, in order to really understand this, the formation of the solar system, it suffices to know gravity and magnetohydrodynamics. I mean, like, the combination of Maxwell's equations and, you know, Navier-Stokes equations for the fluids. You need to know quantum mechanics to understand opacities and so on. But we have those equations in hand. It's not that we don't have that understanding. It's that putting it all together is, A, very, very difficult, and B, if you were to run the same evolution twice, changing, you know, the initial conditions by some infinitesimal amount, some, you know, minor change in your calculation to start with, you'd get a different answer. This is one, this is part of the reason why planetary systems are so diverse. You don't have, like, a, you know, very predictive path for you start with a disk of this mass and it's around this star, therefore you're gonna form the solar system, right? You start with this, and therefore you will form this huge outcome, huge set of outcomes, and some percentage of it will resemble the solar system. You mentioned quantum mechanics, and we're talking about cosmic-scale objects. You've talked about that the evolution of astrophysical disks can be modeled with Schrodinger's equation. I sure did. Why? Like, how does quantum mechanics become relevant when you consider the evolution of objects in the solar system? Yeah. Well, let me take a step back and just say, like, I remember being, you know, utterly confused by quantum mechanics when I first learned it. And the Schrodinger equation, which is kind of the parent equation of that whole field, you know, seems to come out of nowhere, right? The way that I was sort of explaining it, I remember asking, you know, my professor, I was like, but where does it come from? He's like, well, just, like, don't worry about it and just, like, calculate the hydrogen, you know, energy levels, right? So, it's like, I could do all the problems, I just did not have any intuition for where this parent, you know, super important equation came from. Now, down the line, I remember I was preparing for my own lecture, and I was trying to understand how waves travel in self-gravitating disks. So, you know, again, there's a very broad theory that's already developed, but I was looking for some simpler way to explain it really for the purposes of teaching class. And so, I thought, okay, what if I just imagine a disk as an infinite number of concentric circles, right, that interact with each other gravitationally? That's a problem in some sense that I can solve using methods from, like, the late 1700s, right? So, I can write down Hamiltonian, well, I can write down the energy function, basically, of their interactions. And what I found is that when you take the continuum limit, when you go from discrete circles that are talking to each other gravitationally to a continuum disk, suddenly, this gravitational interaction among them, right, the governing equation becomes the Schrodinger equation. And I had to think about that for a little bit. Lewis Larson Did you just unify quantum mechanics and gravity? Kevin Ahern No, this is not the same thing as, like, you know, fusing relativity and quantum mechanics. But it did get me thinking a little bit. So, the fact that waves in astrophysical disks behave just like wave functions of particles is kind of like an interesting analogy because for me, it's easier to imagine waves traveling through, you know, astrophysical disks or really just sheets of paper. And the reason that analogy exists is because there's actually nothing quantum about the Schrodinger equation. The Schrodinger equation is just a wave equation, and all of the interpretation that comes from it is quantum, but the equation itself is not a quantum being. Lewis Larson So, you can use it to model waves. It's not turtles, it's waves all the way down. You can pick which level you pick the wave at. So, it could be at the solar system level that you can use it. Kevin Ahern Right. And also, it actually provides a pretty neat calculational tool because it's difficult. So, we just talked about simulations, but it's difficult to simulate the behavior of astrophysical disks on timescales that are in between a few orbits and their entire evolution. So, it's over a timescale of a few orbits, you do a hydrodynamic simulation, right? Basically, that's something that you can do on a modern computer on a timescale of, say, a week. When it comes to their evolution over their entire lifetime, you don't hope to resolve the orbits, you just kind of hope to understand how the system behaves overall. In between, right, to get access to that, as it turns out, it's pretty cute. You can use the Schrodinger equation to get the answer rapidly. So, it's a calculational tool. Lewis Larson That's fascinating. By the way, astrophysical disks, how broad is this definition? Kevin Ahern Okay. So, astrophysical disks span a huge amount of ranges. They start maybe at the smallest scale. They start with actually Kuiper belt objects. Some Kuiper belt objects have rings, okay? So, that's maybe the smallest example of an astrophysical disk. You've got this little potato-shaped asteroid, you know, which is sort of the size of LA or something, and around it are some rings of icy matter. That object is a small astrophysical disk. Then you have Saturn, the rings of Saturn. You have the next set of scale. You have the solar system itself when it was forming. You have a disk. Then you have black hole disks. You have galaxies. Disks are super common in the universe. The reason is that stuff rotates. Lewis Larson Right. I mean, that's— Paul A gravity works. Lewis Larson Yeah. So, and those rings could be the material that composes those rings. It could be gas. It could be solid. It could be anything. Kevin Ahern That's right. So, the disk that made—from which the planets emerged was predominantly hydrogen and helium gas. On the other hand, the rings of Saturn are made up of, you know, icicle, little like ice cubes this big, about a centimeter across. Kevin Ahern That sounds refreshing. So, that's incredible, hydrogen and helium gas. So, in the beginning, it was just hydrogen and helium around the sun. How does that lead to the first formations of solid objects in terms of simulation? Lewis Larson Okay. Here's the story. So, like, have you ever been to the desert? Kevin Ahern Yes. I've been to the Death Valley. And actually, it was terrifying, just a total tangent. I'm distracting you. But I was driving through it, and I was really surprised because it was at first hot. And then, as it was getting into the evening, there's this huge thunderstorm. Like, it was raining, and it got freezing cold. Like, what the hell? It was the apocalypse. I had to, like, just sit there listening to Bruce Springsteen, I remember, and just thinking, I'm probably going to die. And I was okay with it because Bruce Springsteen was on the radio. Lewis Larson Look, when you've got the boss, you know, you're ready to meet the boss. Yeah. So, look, I mean— Kevin Ahern That's a good line. So, anyway, sorry. The desert, yes. Lewis Larson It's true. Yeah, by the way, like, to continue on this tangent, I absolutely love the Southwest for this reason. Just, you know, during the pandemic, I drove from LA to New Mexico a bunch of times. Kevin Ahern The madness of weather. Chaos. Lewis Larson Yeah, the chaos of weather. The fact that, you know, it'll be blazing hot one minute, and then it's just like, we'll decide to have a little thunderstorm. Maybe we'll decide to go back momentarily to like a thousand degrees and then go back to the thunderstorm. It's amazing. It's—that, by the way, is chaos theory in action. Kevin Ahern Yeah. Lewis Larson Right. But let's get back to talking about the desert. So, in the desert, tumbleweeds have a tendency to roll because the wind rolls them. And if you're careful, you'll occasionally see this family of tumbleweeds where like there's like a big one, and then a bunch of little ones that kind of hide in its wake, right, and are all rolling together and almost looks like, you know, a family of ducks crossing a street or something. Or, for example, you know, if you watch Tour de France, right, you've got a whole bunch of cyclists, and they're like cycling, you know, within 10 centimeters of each other. They're not BFFs, right? They're not trying to be—trying to ride together. They are riding together to minimize the collective, you know, air resistance, if you will, that they experience. Turns out, solids in the protoplanetary disk do just this. There's an instability wherein solid particles, right, things that are a centimeter across will start to hide behind one another and form these clouds. Why? Because cumulatively, that minimizes the solid component of this aerodynamic interaction with the gas. Now, these clouds, because they're kind of a favorable energetic condition for the dust to live in, they grow, grow, grow, grow, grow until they become so massive that they collapse under their own weight. That's how the first building blocks of planets form. That's how the big asteroids got there. That's incredible. Yeah. So, is that simulatable, or is it not useful to simulate? No, no, that's simulatable, and people do these types of calculations. It's really cool. That's actually—that's one of the many fields of planet formation theory that is really, really active. Right now, people are trying to understand all kinds of aspects of that process, because, of course, I've explained it as if there's one thing that happens. Turns out it's a beautifully rich dynamic, but qualitatively, formation of the first building blocks actually follows the same sequence as formation of stars, right? Stars are just clouds of gas, hydrogen and helium gas, that sit in space and slowly cool, and at some point, they contract to a point where their gravity overtakes the thermal pressure support, if you will, and they collapse under their own weight, and you get a little baby solar system. That's amazing. So, do you think one day it'll be possible to simulate the full history that took our solar system to what it is today? Yes, and it will be useless. Okay? So, you don't think your story, many of the ideas that you have about Jupiter clearing the space, like retelling that story in high resolution is not that important? I actually think it's important, but at every stage, you have to design your experiments, your numerical computer experiments, so that they test some specific aspect of that evolution. Gotcha. I am not a proponent of doing huge simulations, because even if we forget the information theory aspect of not being able to simulate in full detail the universe, because if you do, then you have made an actual universe, it's not a simulation, right? Simulation is in some sense a compression of information, so therefore, you must lose detail. But that point aside, if we are able to simulate the entire history of the solar system in excruciating detail, I mean, it'll be cool, but it's not gonna be any different from observing it, right? Because theoretical understanding, which is what ultimately I'm interested in, comes from taking complex things and reducing them down to some mechanism that you can actually quantify. That's the fun part of astrophysics, just kind of simulating things in extreme detail is we'll make cool visualizations, but that doesn't get you to any better understanding than you had before you did the simulation. If you ask very specific questions, then you'll be able to create very highly compressed, nice, beautiful theories about how things evolved, and then you can use those to then generalize to other solar systems, to other stars and other galaxies, and then say something generalizable about the entire universe. How difficult would it be to simulate our solar system such that we would not know the difference? Meaning, if we are living in a simulation, is there a nice, think of it as a video game, is there a nice compressible way of doing that? Or just kind of like you intuited with a three-body situation, is just a giant mess that you cannot create a video game that will seem realistic without actually building it up from scratch? I'm speculating, but one of the... Yeah, I know you have a deep understanding of this, but for me, I'm just going to speculate that for at least in the types of simulations that we can do today, inevitably, you run into the problem of resolution, right? It doesn't matter what you're doing, it is discrete. Now, the way you would go about asking, you know, what we're observing, is that a simulation or is that some real continuous thing, is you zoom in, right? You zoom in and try and find the grid scale, if you will. Yeah, I mean, it's a really interesting question. And because the solar system itself and really, you know, the double pendulum is chaotic, right? Pendulum sitting on another pendulum moves unpredictably once you let them go. You really don't need to like inject any randomness into a simulation for it to give you stochastic and unpredictable answers. Weather is a great example of this. Weather has a lapen of time of, you know, typical weather systems have a lapen of time of a few days. And there's a fundamental reason why the forecast always sucks, you know, two weeks in advance. It's not that we don't know the equations that govern the atmosphere, we know them well. Their solutions are meaningless though, after a few days. The zooming in thing is very interesting. I think about this a lot, whether there'll be a time soon where we would want to stay in video game worlds, whether it's virtual reality or just playing video games. I mean, I think that time like came in like the 90s and it's been that time. Well, it's not just came, I mean, it's accelerated. I just recently saw the wow and Fortnite were played 140 billion hours and those are just video games. And that's like increasing very, very quickly, especially with the people coming up now and being born now and become, you know, becoming teenagers and so on. Let's have a thought experiment where it's just you and a video game character inside a room where you remove the simulation. They need to simulate sort of a lot of objects. If it's just you and that character, how far do you need to simulate in terms of zooming in for it to be very real to you, as real as reality? So like, first of all, you kind of mentioned zooming in, which is fascinating because we have these tools of science that allow us to zoom in, quote unquote, in all kinds of ways in the world around us. But our cognitive abilities, like our perception system as humans is very limited in terms of zooming in. So we might be very easily fooled. Some of the video games like on the PS4 look pretty real to me. I think you would really have to interrogate. I mean, I think even with what we have today, like, I don't know, Ace Combat 7 is a great example, right? Like, I mean, the way that the clouds are rendered, I mean, it looks just like when you're flying, you know, on a real airplane, the kind of transparency. I think that our perception is limited enough already to not be able to tell some of the differences. There's a game called Skyrim. It's an Elder Scrolls role-playing game. And I just, I played it for quite a bit. And I think I played it very different than others. Like, there'll be long stretches of time where I would just walk around and look at nature in the game. It's incredible. Oh, sure. It's just like the graphics is like, wow, I want to stay there. It was better. I went hiking recently. It was like as good as hiking. So, look, I know what you mean. Not to go on a huge video game tangent, but like the third, like, Witcher game was astonishingly beautiful, right? Especially like playing on a good hardware machine. It's like, this is pretty legit. That said, you know, I don't resonate with the, I want to stay here. You know, like one of the things that I love to do is to go to my boxing gym and box with a guy, right? Like, there's nothing quite like that physical experience. That's fascinating. That might be simply an artifact of the year you were born. Maybe. Because if you're born today, it almost seems like stupid to go to a gym. Yeah. Like you go to a gym to box with a guy. Why not box with Mike Tyson when you yourself is like in his prime, when you yourself are also an incredible boxer in the video game world. For me, there's a multitude of reasons why I don't want to box with Mike Tyson. No, no, no. I enjoy teeth, you know, and I want to have an ear. No, but your skills in this meat space, in this physical realm is very limited and takes a lot of work and you're a musician, you're an incredible scientist. You only have so much time in the day, but in the video game world, you can expand your capabilities in all kinds of dimensions that you can never have possibly have time in the physical world. And so that it doesn't make sense like to be existing, to be working your ass off in the physical world when you can just be super successful in the video game world. But I still... You enjoy sucking and stuff? Yeah, I really do. And struggling to get better. I sure do. I mean, I think like these days with music, music is a great example, right? We just started, you know, practicing live with my band again, you know, after not playing for a year. And, you know, it was terrible, right? It was just kind of a lot of the nuance, you know, a lot of the detail is just that detail that takes, you know, years of collective practice to develop. It's just lost. But it was just an incredible amount of fun, way more fun than all the like studio, you know, sitting around and playing that I did, you know, throughout the entire year. So I think there's something intangible or maybe tangible about being in person. And I sure hope you're wrong. And that, you know, that's not something that will get lost, because I think there's like such a large part of the human condition is to hang out. If we were doing this interview on Zoom, right? I mean, I'd already be bored out of my mind. Exactly. I mean, there's something to that. I mean, I'm almost playing devil's advocate, but at the same time, you know, I'm sure people talk about the same way at the beginning of the 20th century about horses, where they're much more efficient, they're much easier to maintain than cars. It doesn't make sense to have, you know, all the ways that cars break down. And there's not enough infrastructure in terms of roads for cars. It doesn't make any sense. Like horses and like nature, you could do the nature, like where, you know, you should be living more natural life. Those are real. You don't want machines in your life that are going to pollute your mind and the minds of young people, but then eventually just cars took over. So in that same way, it just seems- Going back to horses. Well, you can be, you can play, what is it? Red Dead. Red Dead Redemption. Redemption. And you can ride horses in the video game world. That's true. So let me return us back to Planet Nine. Always a good place to come back to. So now that we did a big historical overview of our solar system, what is Planet Nine? Okay. Planet Nine is a hypothetical object that orbits the solar system, right? An orbital period of about 10,000 years and an orbit which is slightly tilted with respect to the plane of the solar system, slightly eccentric. And the object itself, we think is five times more massive than the earth. We have never seen Planet Nine in a telescope, but we have gravitational evidence for it. And so this is where all the stuff we've been talking about, this clustering ideas, maybe you can speak to the approximate location that we suspect. And also the question I wanted to ask is, what are we supposed to be imagining here? Because you said there are certain objects in the Kuiper Belt that are kind of have a direction to them, that they're all like, they're all like flocking in some kind of way. So that's a sense that there's some kind of gravitational object, not changing their orbit, but kind of- Confining them, right? Yeah. Confining, like grouping their orbits together. See, what would happen if Planet Nine were not there is these orbits that roughly share a common orientation, they would just disperse, right? They would just become azimuthally symmetric, point everywhere. Planet Nine's gravity makes it such that these objects stay in a state that's basically anti-aligned with respect to the orbit of Planet Nine, and sort of hang out there and kind of oscillate on a timescale of about a billion years. That's one of the lines of evidence for the existence of Planet Nine. There are others. That's the one that's easiest to maybe visualize just because it's fun to think about orbits that all point into the same direction. But I should emphasize that, for example, the existence of objects, again, Kuiper Belt objects that are heavily out of the plane of the solar system, things that are tilted by, say, 90 degrees, that's not- We don't expect that as an outcome of planet formation. Indeed, planet formation simulations have never produced such objects without some extrinsic gravitational force. Planet Nine, on the other hand, generates them very readily. So, that provides kind of an alternative population of small bodies in the solar system that also get produced by Planet Nine through an independent kind of gravitational effect. So, there's basically five different things that Planet Nine does individually that are like kind of maybe a one-sigma effect where you'd say, yeah, okay, if that's all it was, maybe it's no reason to jump up and down. But because it's a multitude of these puzzles that all are explained by one hypothesis, that's really the magnetism, the attraction of the Planet Nine model. So, can you just clarify? So, most planets in the solar system orbit at approximately the same, so it's flat. Yeah, it's like one degree. The difference between them is about one degree. But nevertheless, if we looked at our solar system, it would look- and I could see every single object, it would look like a sphere. The inner part where the planets are would look like flat, right? The Kuiper Belt and the asteroid belt have a larger- It gets fatter and fatter and fatter until it becomes a sphere. That's right. And if you look at the very outside, it's polluted by this quasi-spheroidal thing. Nobody's, of course, ever seen the Oort Cloud, right? We've only seen comets that come from the Oort Cloud. So, the Oort Cloud, which is this population of distant debris, its existence is also inferred. You could say, alternatively, there is a big cosmic creature that occasionally, sitting at 20,000 AU and occasionally throws an icy rock towards the sun. A spaghetti monster, I think it's called. Okay. So, it's a mystery in many ways, but you can kind of infer a bunch of things about it. It's, by the way, both terrifying and exciting that there's this vast darkness all around us that's full of objects that are just throwing- Just there, yeah. It's actually kind of astonishing, right, that we have only explored a small fraction of the solar system, right? That really kind of baffles me because, remember, as a student studying physics, you do the problem where you put the Earth around the Sun, you solve that, and it's one line of math. And you say, okay, well, that surely was figured out by Newton. So, all the interesting stuff is not in the solar system, but that it's just plainly not true. There are mysteries in the solar system that are remarkable that we are only now starting to just kind of scratch the surface of. And some of those objects probably have some information about the history of our solar system. Absolutely. Absolutely. Like a great example is small meteorites, right? Small meteorites are melted, right? They're differentiated, meaning some of the iron sinks to the core. You say, well, how can that be? Because they're so small that they wouldn't have melted just from the heat of their accretion. Turns out, the fact that the solar nebula, the disk that made the planets was polluted by aluminum 26 is in itself a remarkable thing. It means the solar system did not form in isolation, it formed in a giant cloud of thousands of other stars that were also forming, some of which were undergoing, going through supernova explosions some of and releasing these unstable isotopes of which we now see kind of the traces of. It's so cool. Do you think it's possible that life from other solar systems was injected and that that was what was the origin of life on earth? Yeah, the transpermia idea. That's seen as a low probability event by people who studied the origin of life, but that's because then they would be out of a job. Well, I don't think they'd be out of the job because you just then say you have to figure out how life started there. But then you have to go there. We can study life on earth much easier. We could study in the lab much easier because we could replicate conditions that are from an early earth much easier from a chemistry perspective, from a biology perspective. You can intuit a bunch of stuff. You can look at different parts of earth and just- To an extent. I mean, the early earth was completely unlike the current earth, right? There was no oxygen. So, one of my colleagues at Caltech, Joe Kirchnick, is certain, something like 100% certainty that life started on Mars and came to earth on Martian meteorites. This is not a problem that I like to kind of think about too much. Like the origin of life, it's a fascinating problem, but it's not physics. And I just don't love it. It's the same reason you don't love, I thought you're a musician. So, music is not physics either. So, why are you so into it? It's 100% physics. Yeah. Okay. No, no, look, in all seriousness though, there are a few things that I really, really enjoy. I genuinely enjoy physics. I genuinely enjoy music. I genuinely enjoy martial arts and I genuinely enjoy my family. I should have said that all in a reverse order or something, but I like to focus on these things and not worry too much about everything else. You know what I mean? Yes. Just because there is a, like you said earlier, there's a time constraint. You can't do it all. There's many mysteries all around us. So, and they're all beautiful in different ways. To me, that thing I love is artificial intelligence. That perhaps I love it because eventually I'm trying to suck up to our future overlords. The question of, you said there's a lot of kind of little pieces of evidence for this thing that's planet nine. If we were to try to collect more evidence or be certain, like a paper that says, like you drop it, clear, we're done. What does that require? Does that require us sending probes out or do you think we can do it from telescopes here on earth? What are the different ideas for conclusive evidence for planet nine? The moment planet nine gets imaged from a telescope on earth, it's done. I mean, it's just there. Can you clarify it? Because you mentioned that before, from an image, would you be able to tell? Yes. So, from an image, the moment you see something, something that is reflecting sunlight back at you and you know that it's hundreds of times as far away from the sun as is the earth, you're done. So, you're thinking, so basically if you have a really far away thing that's big, five times the size of earth, that means that's planet nine. That is planet nine. Could there be multiple objects like that, I guess? In principle, yeah. I mean, there's no law of physics that doesn't allow you to have multiple objects. There's also no evidence at present for there being multiple objects. I wonder if it's possible, just like we're finding exoplanets, whether given the size of the Oort cloud, there's basically, it's rarer and rarer, but there's sprinkled planet nine, 10, 11, 12, like these some... Got 13. Yeah, it goes after that. I can just keep counting. So, just something about the dynamic system, it becomes lower and lower probability event, but they gather up, they become, would they become larger and larger maybe? Something like that. I wonder if discovering planet nine will just be almost like a springboard, it's like, well, what's beyond that? It's entirely plausible. The Oort cloud itself probably holds about five earth masses or seven earth masses of material, right? So, it's not nothing. And it all ultimately comes down to at what point will the observational surveys sample enough of the solar system to kind of reveal interesting things. There's a great analogy here with Neptune and the story of how Neptune was discovered. Neptune was not discovered by looking at the sky, right? It was discovered by, it was discovered mathematically, right? So, yeah, the orbit of Uranus, when Uranus was found, this was 1781, it's the kind of tracking of both the tracking of the orbit of Uranus as well as the reconstruction of the orbit of Uranus immediately revealed that it was not following the orbit that it was supposed to, right? The predicted orbit deviated away from where it actually was. So, in the mid-1800s, right, a French mathematician by the name of Orban Le Verrier did a beautifully sophisticated calculation which said if this is due to gravity of a more distant planet, then that planet is there, okay? And then they found it. But the point is the understanding of where to look for Neptune came entirely out of celestial mechanics. The case with Planet 9 is a little bit different because what we can do, I think, relatively well is predict the orbit and mass of Planet 9. We cannot tell you where it is on its orbit. The reason is we haven't seen the Kuiper Belt objects complete an orbit, their own orbit, even once because it takes 4,000 years. But I plan to live on as an AI being, and I'll be tracking those orbits as- All it takes is 4,000 or 5,000 years. I mean, it doesn't have to be AI, it could be longevity, there's a lot of really exciting genetic engineering research. So, you'll just be a brain waiting for the, your brain waiting for the orbit to complete for the basic Kuiper Belt objects. That's right. That's like kind of the worst reason to want to live a long time, right? Just like, can the brain like smoke a cigarette? Can you just light one up while you're waiting or? But you're making me actually realize that the one way to explore the galaxy is by just sitting here on Earth and waiting. So, if we can just get really good at waiting, it's like a Mua Mua or these interstellar objects that fly in, you can just wait for them to come to you. Same with the aliens, you can wait for them to come to you. If you get really good at waiting, then that's one way to do the exploration because eventually the thing will come to you. Maybe that's the, maybe the intelligent alien civilizations get much better at waiting and so they all decide, so game theoretically, to start waiting and it's just a bunch of like ancient intelligent civilizations of aliens all throughout the universe, they're just sitting there waiting for each other. Look, you can't just be good at waiting, you gotta know how to chill. Okay. Like, you can't just like sit around and do nothing, you gotta be, you gotta know how to chill. I honestly think that as we progress, if the aliens are anything like us, we enjoy loving things we do and it's very possible that we just figure out mechanisms here on Earth to enjoy our life and we just stay here on Earth forever, that exploration becomes less and less of an interesting thing to do. And so you basically, yes, wait and chill, you get really optimally good at chilling and thereby exploring is not that interesting. So in terms of 4,000 years, it'll be nothing for scientists, we'll be chilling and just all kinds of scientific explorations will become possible because we'll just be here on Earth. So chill. So chill. So chill. You have a paper out recently, because you already mentioned some of these ideas, but I'd love it if you could dig into it a little bit. Yeah, of course. The Injection of Inner Oort Cloud Objects into the Distant Kuiper Belt by Planet Nine. What is this idea of Planet Nine injecting objects into the Kuiper Belt? Okay, let me take a brief step back. And when we do calculations of Planet Nine, when we do the simulations, as far as our simulations are concerned, sort of the Neptune, like kind of the trans-Neptunian solar system is entirely sourced from the inside, namely the Kuiper Belt gets scattered by Neptune and then Planet Nine does things to it and aligns the orbits and so on. And then we calculate what happens on the lifetime of the solar system, yada, yada, yada. During the pandemic, one of the kind of questions we asked ourselves, and this is indeed something we, Mike and I, Mike Brown, who's a partner in crime on this, and I do regularly, is we say, how can we A, disprove ourselves and B, how can we improve our simulations? Like what's missing? And one idea that maybe should have been obvious in retrospect is that all of our simulations treated the solar system as some isolated creature, right? But the solar system did not form in isolation, right? It formed in this cluster of stars. And during that phase of forming together with thousands of other stars, we believe the solar system formed this almost spherical population of icy debris that sits maybe at a few thousand times the separation between the Earth and the Sun, maybe even a little bit closer. If Planet Nine's not there, that population is completely dormant, and these objects just slowly orbit the Sun, nothing interesting happens to them ever. But what we realized is that if Planet Nine is there, Planet Nine can actually grab some of those objects and gravitationally re-inject them into the distant solar system. So, we thought, okay, let's look into this with numerical experiments. Do our simulations, does this process work? And if it works, what are its consequences? So, it turns out, indeed, not only does Planet Nine inject these distant inner Oort cloud objects into the Kuiper Belt, they follow roughly the same pathway as the objects that are being scattered out. So, there's this kind of two-way river of material. Some of it is coming out by Neptune scattering, some of it is moving in, and some of it is coming out by the Sun. And if you work through the numbers, you kind of, at the end of the day, that it has an effect on the best-fit orbit for Planet Nine itself. So, if you realize that the dataset that we're observing is not entirely composed of things that came out of the solar system, but also things that got re-injected back in, then it turns out the best-fit Planet Nine is slightly more eccentric. That's kind of getting into the weeds. The point here is that the existence of Planet Nine itself provides this natural bridge that connects an otherwise dormant population of icy debris of the solar system with things that we're starting to directly observe. Lex Domogaroff So, it can flow back. So, it's not just the river flowing one way, it's maybe a smaller stream go back and- Yeah, it's backwash. Lex Domogaroff You want to backwash. You want to incorporate that into the simulations, into your understanding of those distant objects, when you're trying to make sense of the various observations and so on. Yeah, exactly. That's fascinating. I gotta ask you, some people think that many of the observations that you're describing could be described by a primordial black hole. First, what is a primordial black hole and what do you think about this idea? Yeah. So, a primordial black hole is a black hole which is made not through the usual pathway of making a black hole, which is that you have a star which is more massive than 1.4 or so solar masses. And basically, when it runs out of fuel, runs out of its nuclear fusion fuel, it can't hold itself up anymore and just the whole thing collapses on itself, right? And you create a I mean, one, I guess, simple way to think about it is you create an object with zero radius that has mass but zero radius, singularity. Now, such black holes exist all over the place in the galaxy. There's in fact, a really big one at the center of the galaxy that's like... That one's always looking at you when you're not looking, okay? And it's always talking about you. And when you turn off the lights, it wakes up. That's right. But you know, so, such black holes are all over the place. When they merge, we get to see incredible gravitational waves that they emit, etc., etc. One kind of plausible scenario, however, is that when the universe was forming, basically during the Big Bang, you created a whole spectrum of black holes, some with masses of five Earth masses, some with masses of 10 Earth masses, like the entire mass spectrum size, the mass of asteroids. Now, on the smaller end, over the lifetime of the universe, the small ones kind of evaporate, and they're not there anymore. At least this is what the calculations tell us. But five Earth masses is big enough to not have evaporated. So, one idea is that Planet 9 is not a planet, and instead, it is a five Earth mass black hole. And that's why it's hard to find. Now, can we right away from our calculations say that's definitely true or that's not true? Absolutely not. In fact, our calculations tell you nothing other than the orbit and the mass. And that means the black hole, I mean, it could be a five Earth mass cup, it could be a five Earth mass hedgehog or a black hole or really anything that's five Earth masses will do because the gravity of a black hole is no different than the gravity of a planet, right? If the Sun became a black hole tomorrow, it would be dark, but the Earth would keep orbiting it. This notion that, oh, black holes suck everything in, it's not. That's like a sci-fi notion. All right, just math. What would be the difference between a black hole and a planet in terms of observationally? Observationally, the difference would be that you will never find the black hole, right? The truth is they're kind of, I'm actually not, I never looked into this very carefully, but there are some constraints that you can get just statistically and say, okay, if the Sun has a binary companion, which is a five Earth mass black hole, then that means such black holes would be extremely common and you can sort of look for lensing events and then you say, okay, maybe that's not so likely. But that said, I want to emphasize that there's a limit to what our calculations can tell you. That's the orbit and the mass. I think there's a bunch, like Ed Witten, I think, wishes it's a black hole. Because I think one exciting thing about black holes in our solar system is that we can go there and we can maybe study the singularity somehow, because that allows us to understand some fundamental things about physics. If it's a planet, so planet nine, we may not, and we go there, we may not discover anything profoundly new. The interesting thing, perhaps you can correct me about planet nine, is like the big picture of it. The whole big story of the Kuiper belt and all those kinds of things. It's not that planet nine would be somehow fundamentally different from, I don't know, Neptune in terms of the kind of things we can learn from it. So I think that there's kind of a hope that it's a black hole because it's an entirely new kind of object. Maybe you can correct me. Yeah, I mean, of course, here my own biases creep in because I'm interested in planets around other stars. And I would disagree that we wouldn't find things that would be truly fundamentally new, because as it turns out, the galaxy is really good at making five or three Earth-mass objects. The most common type of planet that we see, that we discover orbiting around other stars, it's a few Earth-masses. In the solar system, there's no analog for that. We go from one Earth-mass object, which is this one, to skipping to Neptune and Uranus, which themselves are actually relatively poorly understood, especially Uranus from the interior structure point of view. If planet nine is a planet, going there will give us the closest window into understanding what other planets look like. And I'll say this, that planets, in terms of their complexity on some logarithmic scale, fall somewhere between a star and an insect. An insect is way more complicated than a star. Just all kinds of physical processes and really biochemical processes that occur inside of an insect that just make a star look like somebody is playing with a spring or something. Yeah. Right? So, I think it would be arguably more interesting to go to planet nine if it's a planet, because black holes are simple. They're just kind of, they're basically macroscopic like particles. Yeah. Right? Just like the star that you mentioned in terms of complexity. So, it's possible that planet nine is supposed to being homogeneous, is super heterogeneous, there's a bunch of cool stuff going on. Absolutely. That could give us an intuition. I never thought about that, that it's basically Earth number two in terms of size. And it starts giving us intuition that could be generalizable to Earth-like planets elsewhere in the galaxy. I mean, yeah, Pluto is also in the sense like, Pluto is a tiny, tiny thing, right? Just like you would imagine that it's just a tiny ball of ice, like who cares? But the New Horizons images of Pluto reveal so much remarkable structure, right? They reveal glaciers flowing, and these are glaciers not made out of water ice, but CO ice. It turns out at those temperatures of like 40 or so Kelvin, water ice looks like metal, right? It just doesn't flow at all. But then ice made up of carbon monoxide starts to flow. I mean, there's just like all kinds of really cool phenomena that you otherwise just wouldn't really even imagine that occur. So, yeah, I mean, there's a reason why I like planets. I find, as I read, the idea that Ed Witten was thinking about this kind of stuff, fascinating. So, he's a mathematical physicist who's very interested in string theory, won the Fields Medal for his work in mathematics. So, I read that he proposed a fleet of probes accelerated by radiation pressure that could discover a planet nine primordial black holes location. What do you think about this idea of sending a bunch of probes out there? Yeah, look, the way, the idea is a cool one, right? You go and you say, you know, launch them basically isotropically, you track where they go. And if I understand the idea correctly, you basically measure the deflection and you say, okay, that must be something there since the probe trajectories are being altered. Oh, so the measurement, the basic sensory mechanism is the, it's not like you have senses on the probes, it's more like you're, because you're very precisely able to capture, to measure the trajectory of the probes, you can then infer the gravitational fields. And I think that's the basic idea. You know, back a few years ago, we had conversations like these with, you know, engineers from JPL. They more or less convinced me that this is much more difficult than it seems because you don't, at that level of precision, right? Things like solar flares matter, right? Solar flares are completely chaotic. You can't predict which, where a solar flare will happen. That will drive radiation pressure gradients. You don't know where every single asteroid is. So, like, actually doing that problem, I think it's possible, but it's not a trivial matter, right? Well, I wonder, not just about Planet 9, I wonder if that's kind of the future of doing science in our solar system, is to just launch a huge number of probes. So, like, a whole order of magnitude, many orders of magnitude larger numbers of probes, and then start to infer a bunch of different stuff, not just gravity, but everything else. So, in this regard, I actually think there is a huge revolution that's, to some extent, already started, right? The standard kind of, like, time scale for a NASA mission is that you, like, propose it, and it launches, I don't know, like, 150 years after you propose it. I'm over-exaggerating, but, you know, it's just like some huge development cycle, and it gets delayed 55 times. Like, that is not going away, right? The really cutting-edge things, you have to do it this way because you don't know what you're building, so to speak. But the CubeSat kind of world is starting to, you know, provide an avenue for, like, launching something that costs, you know, a few million dollars, and has a turnaround time scale of, like, a couple years. You can imagine doing, you know, PhD theses, where you design the mission, the mission goes to where you're going, and you do the science all within a time span of five, six years. That has not been fully executed on yet, but I absolutely think that's on the horizon, and we're not talking a decade. I think we're talking, like, this decade. Yeah, and the company's accelerating all this with Blue Origin and SpaceX, and there's a bunch of more CubeSat-oriented companies that are pushing this forward. Well, let me ask you, on that topic, what do you think about either one? Elon Musk with SpaceX, or, you know, Elon Musk with SpaceX going to Mars. I think he wants SpaceX to be the first, to put a first human on Mars. And then Jeff Bezos, gotta give him props, wants to be the first to fly his own rocket out into space. So... You know, wasn't there a guy who, like, built his rocket out of garbage? Yeah. Yeah. This was, like, a couple years ago, and somewhere in the desert, he launched himself. I'm not tracking this closely, but I think I am familiar with folks who built their own rocket to try to prove the Earth is flat. Yes, that's the guy I'm talking about. That's the guy. Yeah, he was also, like, he also jumped some limousine. Yeah. Truly revolutionary mind. That's right. You have greater men than either you or I. But what do you... So, look, it's been astonishing to watch how, really, over the last, like, decade, the commercial sector took over this, you know, this industry that traditionally has really been, like, you know, a government thing to do. Motivated primarily by the competition between nations, like the Cold War. Sure. And now it's motivated more and more by the natural forces of capitalism. Yes, that's right. So, okay, here I have many ideas about, I think, on the one hand, right, like what SpaceX has been able to do, for example, phenomenal. If that brings down the price of SpaceX, when that turnaround time scale for space exploration, which I think it inevitably will, that's a huge, you know, that's a huge boost to the human condition. The same time, right, if we're talking astronomy, right, there also, it comes at a huge cost, right? And the Starlink satellites is a great example of that cost, right? At one point, in fact, I was just camping in the Mojave with a friend of mine, and they saw, you know, this string of satellites just kind of like, you know, appear and then disappear into nowhere. So, that is beginning to interfere with, you know, Earth-based observations. So, I think there's tremendous potential there. It's also important to be responsible about how it's executed. Now, with Mars, and the whole idea of, you know, exploring Mars, right, I don't have like strong opinions on whether a manned mission is required or not required. But I do think, you know, we need to focus, the thing to keep in mind is that I generally kind of, I'm not signed on, if you will, to the idea that Mars is some kind of a safe haven that we can, you know, escape to, right? Mars sucks, right? Like, living on Mars, if you want to live on Mars, like, you can have that experience by going to the Mojave Desert and camping, and it's just like, it's just not a great- Well, it's interesting, but there's something captivating about that kind of mission of us striving out into space, and by making Mars in some ways habitable for at least like months at a time, I think would lead to engineering breakthroughs that would make life like in many ways much better on Earth. Like, it will come up with ideas we totally don't expect yet, both on the robotic side, on the food engineering side, on the, you know, maybe like we'll switch from, like, there'll be huge breakthroughs in insect farming, as exciting as I find that idea to be. That in the future, as exciting as I find that idea to be. That in the ways we consume protein, maybe it'll revolutionize, we do factory farming, which is full of cruelty and, you know, and torture of animals, we'll revolutionize that completely because of our, like, we shouldn't need to go to Mars to revolutionize life here on Earth, but at the same time, I shouldn't need a deadline to get shit done, but I do need it. And then in the same way, I think we need Mars. There's something about the human spirit that loves that longing for exploration. I agree with that thesis. Going to the moon, right, and that whole endeavor has, you know, has captivated the imagination of so many, and it has led to incredible kind of, incredible ideas, really, and probably in nonlinear ways, right? Not like, okay, we went to the moon, therefore, some person here has thought of this. And in that similar sense, I think, you know, space exploration is, there's something, there's some real magnetism about it, and it's on a genetic level, right? Like, we have this need to keep exploring, right? When we're done with a certain frontier, we move on to the next frontier. All that I'm saying is that I'm not moving to Mars to live there permanently ever, you know? And I think that, you know, I'm glad you noted the kind of degradation of the Earth, right? I think that is a true kind of leading order challenge of our time. Yeah, it's a great engineering, it's a bunch of engineering problems. I'm most interested in space because, as I've read extensively, it's apparently very difficult to have sex in space. And so, I just want that problem to be solved because I think once we solve the sex in space problem, we'll revolutionize sex here on Earth, thereby increasing the fun on Earth, and the consequences of that can only be good. I mean, you've got a clear plan, right? And it sounds like... I'm submitting proposals to NASA as we speak. That's right. I keep getting rejected, I don't know why. Okay. You need better diagrams. Better pictures. I should have thought of that. You, a while ago, mentioned that, you know, there's certain aspects in the history of the solar system and Earth that resulted... It could have resulted in an opaque atmosphere, but it didn't. We couldn't see the stars. And somebody mentioned to me a little bit ago, it's almost like a philosophical question for you. Do you think humans, like human society, would develop as it did or at all if we couldn't see the stars? It would be drastically different. If it ever did develop. So, I think some of the early developments, right, of like... Fire. You know, fire, you know. First of all, that atmosphere would be so hot. Because, you know, if you have an opaque atmosphere, the temperature at the bottom is huge. So, we would be very different beings to start with. We'd have... But it could be cloudy in certain kinds of ways that you could still get... Okay. Think about like a greenhouse, right? A greenhouse is cloudy, effectively, but it's super hot. Yeah, it's hard to avoid having an atmosphere. If you have an opaque atmosphere, it's hard to... Right, Venus is a great example, right? Venus is... I don't remember exactly how many degrees, but it's hundreds in Celsius, right? It's not a hundred, it's hundreds. Even though it's only a little bit closer to the sun, that temperature is entirely coming from the fact that the atmosphere is thick. So, it's a sauna of sorts. Yeah, yeah. You go there, you know, you feel refreshed after you come back, you know? But if you stay there, I mean, so, okay, I take that as an assumption. This is a philosophical question, not a biological one. So, you have a life that develops under these extremely hot conditions. Yeah. So, let's see. So much of the early evolution of mankind was driven by exploration, right? And the kind of interest in stars originated in part as a tool to guide that exploration, right? I mean, that in itself, I think, would be a huge differential in the way that we, you know, our evolution on this planet. Yeah, I mean, stars, that's brilliant. So, even in that aspect, but even in further aspects, astronomy just shows up in basically every single development in the history of science up until the 20th century, it shows up. So, I wonder without that, if we would even get like calculus. Yeah, look, that's a great, I mean, that's a great point. Newton, in part, developed calculus because he was interested in understanding, explaining Kepler's laws, right? In general, that whole mechanistic understanding of the night sky, right? Replacing a religious understanding where you interpret, you know, this is, you know, this whatever fire god riding his, you know, little chariot across the sky as opposed to, you know, this is some mechanistic set of laws. That transformed humanity and arguably put us on the course that we're on today, right? The entirety of the last 400 years and the development of kind of our technological world that we live in today was sparked by that, right? Abandoning an effectively, you know, a non-secular view of the natural world and kind of saying, okay, this can be understood. And if it can be understood, it can be utilized, we can create our own variants of this. Absolutely, we would be a very, very different species without astronomy. This, I think, extends beyond just astronomy, right? There are questions like why do we need to spend money on X, right? Where X can be anything like paleontology, right? LRT The mating patterns of penguins. CB Yeah, that's like- LRT Essential. CB That's right. I think, you know, there's a tremendous underappreciation for the usefulness of useless knowledge, right? I mean- LRT That's brilliant. CB I didn't come up with this. This is a little book by the guy who started the Institute for Advanced Studies. But, you know, it's so true. So much of the electronics that are on this table, right, work on Maxwell's equations. Maxwell wasn't sitting around in the 1800s saying, you know, I hope one day, you know, we'll make a couple of mics so, you know, a couple guys can have this conversation, right? That was at no point was that the motivation. And yet, you know, it gave us the world that we have today. And the answer is, if you are a purely pragmatic person, if you don't care at all about kind of the human condition, none of this, the answer is, you can tax it, right? Like, useless things have created way more capital than useful things. LRT And the sad thing, I mean, first of all, it's really important to think about and it's just brilliant in the following context. Like, Neil deGrasse Tyson has this book about the role of military-based funding in the development of science. And then so much of technological breakthroughs in the 20th century had to do with humans working on different military things. And then the outcome of that had nothing to do with military. It had some military application, but their impact was much, much bigger than military. CB The splitting of the atom is a kind of a canonical example of this. We all know the tragedy that, you know, arises from splitting of the atom. And yet, you know, so much, I mean, the atom itself does not care for what purpose it is being split. So... LRT So I wonder if we took the same amount of funding as we used for war and poured it into like totally seemingly useless things, like the mating patterns of penguins, we would get the internet anyway. CB I think so. I think so. And, you know, perhaps more of the internet would have penguins, you know? LRT So we're both joking, but in some sense, like, I wonder, it's not the penguins, because penguins is more about sort of biology, but all useless kind of tinkering and all kinds of avenues. And also because military applications are often burdened by the secrecy required. So it's often like so much, the openness is lacking. And if we learned anything for the last few decades is that when there's openness in science, that accelerates the development of science. CB That's right. That's true. The openness of science truly, you know, it benefits everybody. The notion that if, you know, I share my science with you, then you're going to catch up and like, know the same thing. That is a short-sighted viewpoint. Because if you catch up and you open, you know, you discover something that puts me in a position to do the next step, right? So, I absolutely agree with all of this. I mean, the kind of question of like military funding versus non-military funding is obviously a complicated one. But at the end of the day, I think we have to get over the notion as a society that we are going to, you know, pay for this, and then we will get that, right? That's true if you're buying like, I don't know, toilet paper or something, right? It's just not true in the intellectual pursuit. That's not how it works. And sometimes it'll fail, right? Like sometimes like a huge fraction of what I do, right? I come up with an idea, I think, oh, it's great. And then I work it out, it's totally not great, right? It fails immediately. Failure is not a sign that the initial pursuit was worthless. Failure is just part of this kind of this whole exploration thing. And we should fund more and more of this exploration, the variety of exploration. I think it was Linus Pauling or somebody from, you know, that generation of scientists said, you know, a good way to have good ideas is to have a lot of ideas. So, I think that's true. If you are conservative in your thinking, if you worry about proposing something that's going to fail and oh, what if, you know, like there's no science police that's going to come and arrest you for proposing the wrong thing. And, you know, it's also just like, why would you do science if you're afraid of, you know, taking that step? It'd be so much better to propose things that are plausible, they're interesting, and then for a fraction of them to be wrong than to just kind of, you know, make incremental progress all your life, right? Speaking of wild ideas, let me ask you about the thing we mentioned previously, which is this interstellar object Amuamua. Could it be space junk from a distant alien civilization? You can't immediately discount that by saying absolutely it cannot. Anything can be space junk. I mean, from that point of view, can any of the Kuiper Belt objects we see be space junk? Anything on the night sky can in principle be space junk. And Kuiper Belt would catch interstellar objects potentially and like force them into an orbit if they're like small enough? Not the Kuiper Belt itself, but you can imagine like Jupiter family comets being captured, you know, so you can actually capture things. It's even easier to do this very early in the solar system, like early in the solar system's life while it's still in a cluster of stars. It's unavoidable that you capture debris, whether it be natural debris or unnatural debris or just debris of some kind from other stars. It's like a daycare center, right? Like everybody passes their infections on to other kids. You know, Amuamua, there's been a lot of discussion about it, and there's been a lot of interest in this over like is it aliens or is it not? But if you just kind of look at the facts, like what we know about it is it's kind of like a weird shape, and it also accelerated, right? Like that's the two, those are the two interesting things about it. There are puzzles about it, and perhaps the most daring resolution to this puzzle is that it's not, you know, aliens or it's not like a rock, it's actually a piece of hydrogen ice. So, this is a friend of mine, you know, Darrell Seligman and Greg Laughlin came up with this idea that in giant molecular clouds that are just clouds of hydrogen helium gas that live in, live throughout the galaxy at their cores, you can condense ice to become these hydrogen, to become these hydrogen, you know, icebergs, if you will. And then that explains many of the aspects of, in fact, I think that explains all of the Amuamua mystery, how it becomes elongated, because basically the hydrogen ice sublimates and kind of like a bar of soap that, you know, slowly kind of elongates as you strip away the surface layers, how it was able to accelerate because of a jet that is produced from, you know, the hydrogen coming off of it, but you can't see it because it's hydrogen gas, like all of this stuff kind of falls together nicely. I'm intrigued by that idea, truly, because it's like, if that's true, that's a new type of astrophysical object. And they would be produced by, what's the monster that produced initially that kind of object? So, these giant molecular clouds, they're everywhere. I mean, they are, the fact that they exist is not- Are they rogue clouds or are they part of like an oort cloud? No, no, they're rogue clouds. They're just floating about? Yeah, so, if you go, like, a lot of people imagine the galaxy as being a bunch of stars, right? And they're just orbiting, right? But the truth is, if you fly between stars, you run into clouds. They don't have any large object that creates orbits, they're just floating about. They're just floating. But why are they floating together? Or they just float together for a time and not- Well, so, these eventually become the nurseries of stars. So, as they cool, they contract and then collapse into stars or into groups of stars. But some of them, the starless molecular clouds, according to the calculations that Daryl and Greg did, can create these like icicles of hydrogen ice. I wonder why they would be flying so fast. Because they seem to be moving pretty fast at a quick pace. You mean Oumuamua? Oumuamua, yeah. Oh, that's just because of their acceleration due to the sun. If you stop, I mean, it's like, take something really far away, let it go, and the sun is here. By the time it comes close to the sun, right, it's moving pretty fast. So, that's an attractive explanation, I think. Not so much because it's cool, but it makes a clear prediction of when Verarubin Observatory comes online next year or so, we will discover many, many more of these objects, right? So, I like theories that are falsifiable, not just testable, but falsifiable. It's good to have a falsifiable theory where you can say that's not true. Aliens is one that's fundamentally difficult to say, no, that's not aliens, right? Well, the interesting thing to me, if you look at one alien civilization, and then we look at the things it produces, in terms of if we were to try to detect the alien civilization, there's like, say there's 10 billion aliens, there would probably be trillions of dumb drone-type things produced by the aliens, and there'd be many, many, many more orders of magnitude of junk. So, if you were to look for an alien civilization, in my mind, you would be looking for the junk. That's the more efficient thing to look for. So, I'm not saying Oumuamua has any characteristics of space junk, but it kind of opened my eyes to the idea that we shouldn't necessarily be looking to the queen of the ant colony. We should be looking at, I don't know, traces of alien life that doesn't look intelligent in any way, may not even look like life. It could be just garbage. We should be looking for garbage. Just generically. Garbage that's producible by unnatural forces. For me, at least, that was kind of interesting, because if you have a successful alien civilization, that we would be producing many more orders of magnitude of junk, and that would be easier, potentially, to detect. Well, so you have to produce the junk, but you have to also launch it. So, this is where, I mean, let's imagine- Garbage disposal. Yeah. But let's imagine we are a successful civilization that has made it to space. We clearly have. And yes, we're in the infancy of that pursuit, but we've launched, I don't know how many satellites. Probably, if you count GPS satellites, it must be at least thousands. It's certainly thousands. I don't know if it's over 10,000, but it's on that order. But it's on that large order of magnitude. How many of the things that we've launched will ever leave the solar system? I think two. There's two so far. Well, maybe the Voyager, the Voyager 1, Voyager 2. I don't know if the Pioneer. So, maybe three. There's also a Tesla Roadster out there. That one will never leave the solar system. I think that one will eventually collide with Mars. That can be SpaceX's first Mars destination. But look, so, there's an energetic cost to interstellar travel, which is really hard to overcome. And when we think about, generically, what do we look for in an alien civilization? Oftentimes, we tend to imagine that the thing you look for is the thing that we're doing right now. So, I think that if I look at the future, and for a while, it was like, okay, if aliens are out there, they must be broadcasting in radio. The amount that we broadcast in radio has diminished tremendously in the last 50 years, but we're doing a lot more computation. What are the signs of computation? That's an interesting question to ask. I don't know, I think something on the order of a few percent of the entire electrical grid last year went to mining Bitcoin. There could be a lot of, in the future, different consequences of the computation, which, I'm biased, but it could be robotics, it could be artificial intelligence. So, we may be looking for intelligent-looking objects, like that's what I meant by probes, like things that move in kind of artificial ways. But the emergence of AI is not an if, right? It's happening right in front of our eyes, and the energetic costs associated with that are becoming a tangible problem. So, I think, you know, if you imagine extrapolating that into the future, what becomes the bottleneck? The bottleneck might be powering the AI, broadly speaking. Not one AI, but powering that entire AI ecosystem. So, I don't know, I think space junk is an interesting idea, but it's heavily influenced by like sci-fi of 1950s, where by 2020, we're all like flying to the moon, and so, we produce a lot of space junk. I'm not sure if that's the pathway that alien civilizations take. I've also never seen an alien civilization, I just don't know anything. That's true, but if your theory of chill turns out to be true, and then we don't necessarily explore, we seize the exploration phase of, like alien civilizations quickly seize the exploration phase of their efforts, then perhaps they'll just be chilling in a particular space, expanding slowly, but then using up a lot of resources, and they have to have a lot of garbage disposal that sends stuff out. And the other, you know, the other idea was that it could be a relay, that, you know, almost have like these GPS-like markers that you send throughout, which I think is kind of interesting. It's similar to this probe idea of sending a large number of probes out to measure gravitational, to measure basically, yeah, the gravitational field, essentially. I mean, a lot of people at Caltech, or at MIT, are trying to measure gravitational fields, and there's a lot of ideas of sending stuff out there that accurately measures those gravitational fields to have a greater understanding of the early universe, but then you might realize that communication through gravitation, through gravity, is actually much more effective than radio waves, for example, something like that. And then you send out, I mean, okay, if you're an alien civilization that's able to have gigantic masses, like basically- We're getting there as a civilization. No, we're not even close. Well, I mean- Yeah, okay. I mean, like, be able to sort of play with black holes, that kind of thing. So, we're talking about a whole other order of magnitude of masses, then it may be very effective to send signals via gravitational waves. I actually, my sense is that all of these things are genuinely difficult to predict, and I don't mean to kind of shy away, I really mean if you take imagination of what the future looked like from 500 years ago, right? It's just, it is so hard to conceive of the impossible, right? So, it's almost like, you know, it's almost limiting to try and imagine things that are an order of magnitude, you know, or two orders of magnitude ahead in terms of progress, just because, you know, you mentioned cars before, you know, if you were to ask people what they wanted in 1870, it's faster buggies, right? So, I think the whole like kind of, you know, alien conversation inevitably gets limited by our entire kind of collective astrophysical lack of imagination, if you know what I mean. So, to push back a little bit, I find that it's really interesting to talk about these wild ideas about the future, whether it's aliens, whether it's AI, with brilliant people like yourself, who are focused on very particular tools of science we have today to solve very particular, like rigorous scientific questions. And it's almost like putting on this wild dreamy hat, like some percent of the time and say like, what are, like, what would alien civilizations look like? What would alien trash look like? Well, what would our own civilization that sends out trillions of AI systems out there, like how 9,000, but 10,000 out there, what would that look like? And you're right, any one prediction is probably going to be horrendously wrong, but there's something about creating these kind of wild predictions that kind of opens up. No, there's a huge magnetism to it, right? And some of it, you know, I mean, some of the Jules Verne novels did a phenomenal job predicting the future, right? That actually was a great example of what you're talking about, like allowing your imagination to run free. I mean, I just hope, I just hope there's dragons. That's like- There's dragons, too. I love dragons. Yeah, dragons are the best. But see, the cool thing about science fiction and these kinds of conversations, it doesn't just predict the future, I think. Some of these things will create the future. Planting the idea, the humans are amazing, like fake it till you make it. Humans are really good at taking an idea that seems impossible at the time. And for any one individual human, that idea is like, it's like planting a seed that eventually materializes. It's weird. It's weird how science fiction can create science fiction. And drive some of the- It drives the science. Yeah, I agree with you. And I think in this regard, you know, I'm like a sucker for sci-fi. It's all I listen to like now when I run. And some of it is completely implausible, right? And it's just like, I don't care. It's both entertaining and, you know, it's just like, it's imagination. You know about the Black Clouds book? I think it's by Fred Hoyle. This has great connections with sort of a lot of the advancements that are happening in NLP right now, right? With transformer models and so on. But it's this black cloud shows up in the solar system and then, you know, people try to send radio and then it learns to talk back at you. Wow. You know, so anyway, we don't have to talk at all about it, but it's just, it's something worth checking out. With that, on the alien front, with the Black Cloud, to me, exactly, on the NLP front, and also just explainability of AI, it's fascinating. Just the very question, Stephen Wolfram looked at this with the movie Arrival. It's like, what would be the common language that we would discover? The reason that's really interesting to me is we have aliens here- Japanese. Now, Japanese, oh yeah. Japanese is the obvious answer. Japanese, yeah, that would be the common, maybe it would be music, actually. That's more likely. It wouldn't be language. It would be art that they would communicate. But, you know, I do believe that we have, along with Stephen Wolfram on this a little bit, that to me, computation, like programs we write, that, you know, that they're kind of intelligent creatures and I feel like we haven't found the common language to talk with them. Like our little creations that are artificial are not born with whatever that innate thing that produces language with us. And like, coming up with mechanisms for communicating with them is an effort that feels like it will produce some incredible discoveries. You can even think of, if you think that math is discovered, mathematics in itself is a kind of- Oh, yeah, it's an innate construction of the world we live in. I think we are, you know, a part of the way there because pre-1950, right, computers were human beings that would carry out arithmetic, right? And I think it was Ulam who worked in Los Alamos at the time, like towards the end of the Second World War, wrote something about how, you know, in the future, right, computers will not be just arithmetic tool but will be truly an interactive, you know, thing with which you could do experiments, right? At the time, the notion of doing an experiment, not like in the lab with some beakers, but an experiment on a computer designing an experiment, a numerical experiment was a new one. That's like, you know, 70% of what I do is I design, you know, I write code, terrible code to be clear, but, you know, I write code that creates an experiment which is a simulation. So, in that sense, I think we're beginning to interact with the computer in a way that you're saying, not as just a, you know, fancy calculator, not as just a, you know, call and request type of thing, but, you know, something that can generate insights that are otherwise completely unattainable, right? They're unattainable by doing analytical mathematics. Yeah, and there's, like, with the AlphaFold 2, we're now starting to crack open biology. So, being able to simulate at first trivial biological systems and hopefully down the line complex biological systems. My hope is to be able to simulate psychological, like, sociological systems like humans. I've, you know, a large part of my work at MIT was on autonomous vehicles, and the fascinating thing to me was about pedestrians, human pedestrians interacting with autonomous vehicles and simulating those systems without murdering humans would be very useful, but nevertheless is exceptionally difficult. Yeah, I would say so. When is my Mustang going to drive itself? Right. I'm not even joking. It looks like. Yeah. It turns out it's much more difficult than we imagined. Yeah. And I suppose that's the kind of, the progress of science is just like, you know, going to Mars, it's probably going to turn out to be way more difficult than we imagined. Sending out probes to investigate planet nine at the edge of our solar system might turn out to be way more difficult than we imagined, but we do it anyway. And we figure it out in the end. It's actually, Mars is a great, I mean, going, sending humans to Mars, it's way more complicated than sending humans to the moon. You'd think just like naively, both are in space, who cares? If you go there, why don't you go there? This life support is an extremely expensive thing. Yeah. There's a bunch of extra challenges, but I disagree with you. I would be one of the early people to go. I used to think not. I used to think I'd be one of the first maybe million to go once you have a little bit of a society. I think I'm upgrading myself to the first like 10,000. That's right. Front of the cabin. Not completely front, but like, it'd be interesting to die. I'm okay with, death sucks, but I kind of like the idea of dying on Mars. Of all the places to die, I got to say in this regard, like, I don't want to die on Mars. You don't? No, no. I would much rather die on Earth. I mean, death is fundamentally boring, right? Like, death is a very boring experience. I mean, I've never died before, so I don't know from firsthand experience. As far as you know. Yeah. It could be a reincarnation, all those kinds of things. So, you mean, where would you die if you had to choose? Oh, man. Okay. So, I would definitely, there's a question of who I'd want to die with. I'd prefer not to die alone, but like, surrounded by family would be preferable. Where? I think Northern New Mexico. And I'm not even joking. Like, this is not a random, it's just like... Would that be your favorite place on Earth? Not necessarily, like, favorite place on Earth to reside at, you know, indefinitely, but it is one of the most beautiful places I've ever been to. So, you know, there's something, I don't know, there's something attractive about going, you know... Returning to nature in a beautiful place. Let me ask you about another aspect of your life that is full of beauty, music. You're a musician. The absurd question I have to ask, what is the greatest song of all time? Objectively speaking. The greatest song of all time. I suppose that could change moment to moment, day to day, but if you were forced to answer for this particular moment in your life, that's something that pops to mind. This could be both philosophically, this could be technically as a musician, like, what you enjoy, maybe lyrics. Like, for me, lyrics is very important, so I would probably, it would be, my choice would be lyrics-based. I don't want to answer in terms of just technical, you know, technical prowess. I think technical prowess is impressive, right? It's just like, it's impressive what can be done. I wouldn't place that into the category of the greatest music ever written. Some classical music that's written is undeniably beautiful, but I don't want to consider that category of music either, just because, you know. So, if I was to limit the scope of this philosophical discussion to, you know, the kind of music that I listen to, you know, probably What's My Age Again by Blink-182. It's just, you know, it's a solid one. It's got, you know... I said nobody ever. That's a good song. I don't know if you're joking. No, no, I am joking. It's a good one, but it's... Yeah, I mean, I'm... I was going to go back, it's a close second. What's My Age Again. Oh, yeah. No, I mean, it would probably, you know, songwriting-wise, I think The Beatles came pretty close to... Were they influential to you? Absolutely. Like The Beatles? Yeah. Love The Beatles. I love The Beatles. Let It Be, Yesterday. Yeah. Like, I think Strawberry Fields Forever is one of... You know what one of my favorite Beatles songs is? It's, you know, In My Life, right? That song, it's hard to imagine how whatever a 24-year-old... Yeah....ever wrote that. It is one of the most introspective pieces of music ever. You know, I'm a huge Pink Floyd fan. And so I think, you know, if you were to... You can sort of look at the entire Dark Side of the Moon album as, you know, getting pretty close up there to the pinnacle of what, you know, can be created. So, you know, Time's a great song. Yeah. It's a great song. There's just the entirety of just the instruments, the lyrics, the feeling created by a song. Like Pink Floyd can create feelings. The entire experience. I mean, you have that with The Wall of just transporting you into another place. Songs don't... Not many songs could do that as well. Not many artists can do that as well as Pink Floyd did. There are a lot of bands that you can kind of say, oh, yeah, like if you take Blink-182, right? If you have no idea, like if you are listening to sort of that type of pop punk for the first time, it's difficult to differentiate between Blink-182 and like Sum 41 and the thousand of other like lesser known bands that all sounded... They all had that sparkling production feel. They all kind of sounded the same, right? With Pink Floyd, it's hard to find another band that you're like, well, is this one Pink Floyd? Like, you know when you're listening to Pink Floyd, when you're listening to... The uniqueness, that's fascinating. You know, in the calculation of the greatest song and the greatest band of all time, you could probably actually quantify this like scientifically, is like how unique, if you play different songs, how well are people able to recognize whether it's this band or not? And that's probably a huge component to greatness. Like if the world would miss it if it was gone. Yes. Yes. So... But there's also the human story things. Like I would say I'll put Johnny Cash's cover of Hurt as one of the greatest songs of all time. And that has less to do with the song. But your interaction with it. Interaction with it, but also the human, the full story of the human. So like, it's not just that if I just heard the song, I'd be like, okay. But if it's the full story of it, also the video component for that particular song. So like that, you can't discount the full experience of it. Absolutely. I have no confusion about being anywhere in that lane. But I just sometimes think about music that is being produced today, oftentimes feels like kind of clothes, like clothes that you buy at like H&M and you wear three times before they rip and you throw away. So like, so much of it is, it's not bad. It's just kind of forgettable. Like the fact that we're talking about Pink Floyd in 2021 is in itself an interesting question. Why are we talking about Pink Floyd? And there's something unforgettable about them and unforgettable about the art that they created. That could be the markets that like, so Spotify has created this kind of market where the incentives for creating music that lasts is much lower because there's so much more music. You just want something that shines bright for a short amount of time, makes a lot of money and moves on. And I mean, the same thing you see with the news and all those kinds of things. We're just living in a shorter and shorter, shorter, like a time scale in terms of our attention spans. And that, nevertheless, when we look at the long arc of history of music, perhaps there will be some songs from today that will last as much as Pink Floyd. We're just unable to see it. Yeah. Just the collected works of Nickelback. Exactly. You never know. You never know. Justin Bieber, it could be a contender. I've recently started listening to Justin Bieber just to understand what people are talking about. And you know, I'll just keep my comments to myself on that one. It's too good to explain. It's too good. And the words cannot capture the greatness that is the Biebs. You as a musician, so you write your own music, you play guitar, you sing. Maybe can you give an overview of the role music has played in your life? You're one of the, you're a world-class scientist. And so it's kind of fascinating to see somebody in your position who's also a great musician and still loves playing music. Yeah. Well, I wouldn't call myself a great musician. Yeah. One of the best of all time. That's right. Like we were saying offline, confidence is like the most essential thing about being a rock star. Exactly. The confidence and kind of like moodiness, right? Yeah. Look, I mean, music plays an absolutely essential role in everything I do because if I stop playing for one reason or another, say I'm traveling, I notably lose creativity in every other aspect of my life. There's something I don't view playing music as a separate endeavor from doing science or doing whatever. It's all part of that same creative thing, which is distinct from, I don't know, pressing a button or like, you know, So it's not a break from science. It's a part of your science. It's absolutely. I would say, you know, it's the thing that enables the science, right? The science would suck even more than it does already without the music. And that means like the creating of the writing of the music, or is it just even playing other people's stuff? Is it the whole of it? Yeah, it's definitely both. Yeah. And also just, you know, I love to play guitar, love to sing, you know, my wife tolerates my screeching singing, you know, and even kind of likes it. Yeah. So people should check out your stuff. You have a great voice. So I love your stuff. Is there something, you're super busy. Is there something you can say about practicing for musicians, for guitar, for you're also in a band? So like that whole, how you can manage that? Is there some tricks, some hacks to being a lifelong musician while being like super busy? Super busy. So I would say, you know, the way that I optimize my life is I try to do, you know, the thing that I'm passionate about in a moment and put that at the top of the priority list. There are moments when, you know, you just, you feel inspired to play music. And if you're in the middle of something, if you can avoid, if that can be put on hold, just do it, right? There are times when you get inspired about something scientific. You know, I do my best to drop everything, go into that, you know, mode of that isolated mode and execute upon that. So it's a chaotic, you know, I think I have a pretty chaotic lifestyle where I'm always doing kind of multiple things and jumping between what I'm doing. But at the end of the day, it's not like, you know, those moments of inspiration are actually kind of rare, right? Like most of the time, all of us are just doing kind of doing the stuff that needs to get done. If you do the disservice to yourself of saying, oh, I'm inspired to, you know, do this calculation, figure this out, but I've got to answer email or just like do something silly, you know, that is nothing more than disservice. And also, like I have some social media presence, but I mostly stay off of, you know, social media to, you know, just frankly, because like, I don't enjoy the mental cycles that it... Yeah, it robs you of that, yeah, those precious moments that could be filled with inspiration in your other pursuits. But there's something to maybe you and I are different in this. Like, I try to play at least 10 minutes of guitar every day, almost on the technical side, like, keeping that base of basic competence going. And I mean, the same way like writers will get in front of a paper no matter what, that kind of thing. It just feels like that for my life has been essential to the daily ritual of it. Otherwise, days turn into weeks, weeks turn into months, and you haven't played guitar for months. No, no, I understand. For me, I think it's been like, if we have a gig coming up, we'll definitely... You mean deadlines. Yeah, yeah, that's right. No, like, we will sharpen up definitely, you know, especially coming up to a gig. It's like, you know, we're not trying to make money with this. This is like, just for that satisfaction of doing something, doing something well, right? But overall, I would say most... I play guitar most days, most days. And, you know, when I put kids to sleep, I play guitar, you know, with them, and we like, just make up random songs about, you know, about our cat or something, you know, like, we just do kind of random stuff. But, you know, music is always involved in that process. Yeah, keeping it fun. You have Russian roots? I sure do. Were you born in Russia? I was, yeah. When did you come here? When did you come here? So, I came to the US in the very end of 99. So, I was like, almost 14 years old. But along the way, we spent six years in Japan. So, like, we moved from Russia to Japan in 94, and then to the US in 99. So, I did like elementary school. Oh, interesting. And then school in Japan. So, elementary school in Japan. Yeah. So, that's interesting. Do you still speak Russian? Sure. Okay. Okay, maybe I'll... Let me ask you in Russian. What do you remember about Russia? It'd be interesting to hear you speak Russian. So, I remember very well how at some point, Pepsi Cola first appeared, and then Coca-Cola. I remember I was, I don't know, six years old, and I thought, how is it possible that Coca-Cola stole a product and did the same thing? I mean, I thought for a long time that Pepsi and Coca-Cola were invented in, like, 1992. So, for people who don't speak Russian, Konstantin was talking about, basically, his first in 1992 interaction with capitalism, which is Pepsi. And at first he discovered Pepsi, and then he discovered Coke, and he was confused how such theft could occur. Like an intellectual property theft. And remember, Pepsi arrived to the Soviet Union first, and there's some complicated story, which I don't quite understand the details of. For a while, Pepsi, like, commanded submarines or something. Yeah, Pepsi had like a fleet of Soviet submarines. They were sponsoring tanks and this best thing. And I remember there's certain things that trickled in, like McDonald's, I remember that was a big deal. Certain aspects of the West. Absolutely. So, I mean, we went to McDonald's, and we stood in line. I mean, this is absurd, right, from kind of looking at it from today's perspective, but we stood in line for like six hours to get into this McDonald's. And I remember inside, it was just like a billion people, and I'm just taking a bite out of that Big Mac. I'm like, wow. Was it an incredible experience for you? So, what does this taste of the West like? You know, I enjoyed the fact that, I mean, this is getting into the weeds, but I really enjoyed the fact that the top of the bun had those seeds, you know, like, and I remember how on the commercials, like the Big Mac would kind of bounce. I was like, the seeds, how do they inject the seeds into the bread? Like, amazing. Right. So, I think it was... Artistry. Yeah. You enjoy the artistry of the culinary experience. Exactly. It was the food art that is the Big Mac. Actually, I still don't know the answer to that. How do they get the sesame seeds on the bun? It's better to not know the answer. You just wander the mystery of it all. Yeah, I remember it being exceptionally delicious, but I'm with you. I don't know, you didn't mention how transformative Pepsi was, but to me, basically sugar-based stuff, like Pepsi was, or Coke. I don't remember which one we partook in, but that was an incredible experience. Yeah, yeah. No, absolutely. And I think it was an important and formative period. I sometimes, I guess, rely on that a little bit in my daily life because I remember the early 90s were real rough. My parents were on the bottom of the spectrum in terms of financial well-being. When I run into trouble, not money trouble, just any kind of trouble these days, it just is not particularly meaningful when you compare it to that turbulent time of the early 90s. And the other thing is, I think there's an advantage to being an immigrant, which is that you go through the mental exercise of changing your environment completely early in your life. It's by no means pleasant in the moment, but going into Japanese elementary school, I didn't go to some private thing. I just went to a regular Japanese public elementary school, and that was the non-Japanese person in my class. So, just learning Japanese and just kind of... So, that's a super humbling experience in many ways, was when you made fun of all that kind of stuff, being the outsider. Yeah, yeah. Oh, absolutely. But you kind of do that, and then you just kind of are okay with stuff. You know what I mean? And so, doing that again in middle school in the US, it was arguably easy because I was like, yeah, well, I've already done this before. So, I think it kind of prepares you mentally a little bit for switching up, for whatever changes that will come up for the rest of your life. So, I wouldn't trade that experience really for anything. It's a huge aspect of who I am, and I'm sure you can relate to a lot of this. Yes. Is there advice from your life that you can give to young people today, high school, college, about their career, or maybe about life in general? I'm not a career coach by... Life coach. Right. I'm definitely not a life coach. I don't have it all figured out. But I think there's a perpetual cycle of thinking that there's kind of like a template for success. Maybe there is, but in my experience, I haven't seen it. I would say people in high school, so much of their focus of their focus is on getting straight A's, filling their CV with this and this and this, so that it looks impressive, right? That is not, I think, a good way to optimize your life, right? Do the thing that fills your life with passion, do the thing that fills your life with interest, and do that perpetually, right? A straight A student is really impressive, but also somewhat boring, right? So, I think an injection of more of that kind of interest into the lives of young people would go a long way in just both upping their level of happiness and then just kind of ensuring that looking forward, they are not suffering from a perpetual condition of, oh, I have to satisfy these check boxes to do well, right? Because you can lose yourself in that whole process for the rest of your life. But it's nice if it's possible, like Max Tegmark was exceptionally good at this at MIT, figure out how you can spend a small part of your percent of your efforts such that your CV looks really impressive. Yeah, absolutely. There's no, like, without a doubt, that's a baseline that you need to have. And then spend most of your time doing amazing things you're passionate about, but such that it, kind of like Planet Nine, produces objects that feed your CV slowly over time. So, getting good grades in high school, maybe doing extracurricular activities, or in terms of like, you know, for programmers that's producing code that you can show up on GitHub, like leaving traces throughout your efforts such that your CV looks impressive to the rest of the world. In fact, I mean, this is somewhat along the lines of what I'm talking about. See, like, getting good grades is important, but grades are not a tangible product. You cannot show your A and have your A live a separate life from you. Code very much does, right? Music very much takes on, you know, provided somebody else listens to it, right? Like, takes on a life of its own. That's kind of what I mean, right? Doing stuff that can then get separated from you is exceptionally attractive, right? It's like a fun and- And it's also very impressive to others. I think we're moving to a world where grades mean less and less, like certifications mean less and less. If you look at, especially again, in the computing fields, getting a degree, finishing your, currently just finishing your degree, whether it's bachelor's or master's or PhD, is less important than the things you've actually put out into the world. Right, right. Right. And that's a fascinating kind of, that's great that in that sense, the meritocracy is, in its richest, most beautiful form, is starting to win out. Yeah, it's weird because like, you know, my understanding, and I'm not like, I don't know the history of science well enough to speak very confidently about this, but, you know, the advisor of my advisor of my advisor from undergrad, like, didn't have a PhD, right? So, I think it was a more common thing back in the day, even in the academic sector, to, you know, not have, you know, Faraday, like, Faraday didn't know algebra, right? And drew diagrams about, you know, magnetic fields. And I get his, Faraday's law was derived entirely from intuition. So, it is interesting to how the world of academia has evolved into a, you got to do this and then get PhD, then you have to postdoc once and twice and maybe thrice, and then like, you move on. So, you know, it does, I do wonder, you know, if we're, you know, if there's a better approach. I think we're heading there, but it's a fascinating historical perspective, like, that we might have just tried this whole thing out for a while, where we put a lot more emphasis on grades and certificates and degrees and all those kinds of things. I think the difference historically is, like, we can actually, using the internet, show off the, show off ourselves and our creations better and better and more effectively, whether that's code or producing videos or all those kinds of things. That's right. You can become a certified drone pilot. That's true. Of all the things you want to pick, yeah, for sure. Or you can just fly and make YouTube videos that gets hundreds of thousands of views with your drone and never getting a certificate. That's probably illegal. Don't do it. What do you think is the meaning of this whole thing? So, you look at planets, they seem to orbit stuff without asking the why question, and for some reason, life emerged on earth such that it led to big brains that can ask the big why question. Do you think there's an answer to it? I'm not sure what the question is. Meaning of life? The meaning of life. It's 42. It's 42. Yeah. But, you know, aside from that, it's, you know, why, I think, if the question you're asking is like, why we do all this, right? Why we do all this? It's part of the human condition, right? Human beings are fundamentally, I feel like, sort of stochastic and fundamentally interested in kind of expanding our own understanding of the world around us. And creating stuff to enable that understanding. So, we're like stochastic, fundamentally stochastic. So, like, there's just a bunch of randomness that really doesn't seem like it has a good explanation, and yet there's a kind of direction to our being that we just keep wanting to create and to understand. That's right. I've met people that are, you know, that claim to be anti-science, right? And yet, in their anti-science, you know, discussion, they're like, well, like, if you're so, you know, scientific, then why don't you explain to me how, I don't know, this works? And like, it always, there's that fundamental- There's a curiosity. Seed of curiosity and interest that is common to all of us. That is absolutely what makes us human, right? And I'm in a privileged position of being able to have that be my job, right? I think as time evolves forward, you know, and the kind of economy changes, I mean, we're already starting to see a shift towards that type of creative enterprise as merging, taking over a bigger and bigger chunk of the sector. It's not yet, I think, the dominant portion of the economy by any account, but if we compare this to like, you know, the time when the dominant thing you would do would be to, you know, go to a factory and do the same exact thing, right? I think, you know, there's a tide there and things are sort of headed in that direction. Yeah, life's becoming more and more fun. I can't wait, honestly, what happens next. I can't wait to just chill. Just chill. The terminal point of this is just chill and wait for those Kuiper Belt objects to complete one orbit. I'm gonna credit you with this idea. I do hope that we definitively discover proof that there is a Planet Nine out there in the next few years, so you can sit back with a cigar, a cigarette, or vodka, or wine, and just say, I told you so. That's already happening. I'm gonna do that later tonight. As I mentioned, confidence is essential to being a rock star. I really appreciate you explaining so many fascinating things to me today. I really appreciate the work that you do out there, and I really appreciate you talking with me today. Thanks, Constantine. Pleasure. Thanks for having me on. Thanks for listening to this conversation with Constantine Batygin, and thank you to Squarespace, Litterati, Onnit, and Ni. Check them out in the description to support this podcast. And now, let me leave you with some words from Douglas Adams in The Hitchhiker's Guide to the Galaxy. Far out in the uncharted backwaters of the unfashionable end of the western spiral arm of the galaxy lies a small, unregarded yellow sun. Orbiting this, at a distance of roughly 92 million miles, is an utterly insignificant little blue-green planet whose ape-descendant lifeforms are so amazingly primitive that they still think digital watches are a pretty neat idea. Thank you for listening, and hope to see you next time.

https://youtu.be/tm7poMupE8k

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Scott Aaronson: Computational Complexity and Consciousness | Lex Fridman Podcast #130

The following is a conversation with Scott Aronson, his second time on the podcast. He is a professor at UT Austin, director of the Quantum Information Center, and previously a professor at MIT. Last time we talked about quantum computing. This time we talk about computation complexity, consciousness, and theories of everything. I'm recording this intro, as you may be able to tell, in a very strange room in the middle of the night. I'm not really sure how I got here or how I'm going to get out, but Hunter S. Thompson saying, I think, applies to today and the last few days and actually the last couple of weeks. Life should not be a journey to the grave with the intention of arriving safely in a pretty and well-preserved body, but rather to skid and broadside in a cloud of smoke, thoroughly used up, totally worn out, and loudly proclaiming, wow, what a ride. So I figured whatever I'm up to here, and yes, lots of wine is involved, I'm gonna have to improvise, hence this recording. Okay, quick mention of each sponsor, followed by some thoughts related to the episode. First sponsor is SimpliSafe, a home security company I use to monitor and protect my apartment, though of course, I'm always prepared with a fallback plan, as a man in this world must always be. Second sponsor is 8Sleep, a mattress that cools itself, measures heart rate variability, has a nap, and has given me yet another reason to look forward to sleep, including the all-important power nap. Third sponsor is ExpressVPN, the VPN I've used for many years to protect my privacy on the internet. Finally, the fourth sponsor is BetterHelp, online therapy when you want to face your demons with a licensed professional, not just by doing David Goggins-like physical challenges like I seem to do on occasion. Please check out these sponsors in the description to get a discount and to support the podcast. As a side note, let me say that this is the second time I recorded a conversation outdoors. The first one was with Stephen Wolfram when it was actually sunny out. In this case, it was raining, which is why I found a covered outdoor patio. But I learned a valuable lesson, which is that raindrops can be quite loud on the hard metal surface of a patio cover. I did my best with the audio. I hope it still sounds okay to you. I'm learning, always improving. In fact, as Scott says, if you always win, then you're probably doing something wrong. To be honest, I get pretty upset with myself when I fail, small or big, but I've learned that this feeling is priceless. It can be fuel when channeled into concrete plans of how to improve. So if you enjoy this thing, subscribe on YouTube, review the 5 Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Scott Aronson. Let's start with the most absurd question, but I've read you write some fascinating stuff about it, so let's go there. Are we living in a simulation? What difference does it make, Lex? I mean, I'm serious. What difference? Because if we are living in a simulation, it raises the question, how real does something have to be in simulation for it to be sufficiently immersive for us humans? But I mean, even in principle, how could we ever know if we were in one, right? A perfect simulation, by definition, is something that's indistinguishable from the real thing. Well, we didn't say anything about perfect. It could be imperfect. No, no, that's right. Well, if it was an imperfect simulation, if we could hack it, find a bug in it, then that would be one thing, right? If this was like the Matrix and there was a way for me to do flying kung fu moves or something by hacking the simulation, well, then we would have to cross that bridge when we came to it, wouldn't we? Right? I mean, at that point, it's hard to see the difference between that and just what people would ordinarily refer to as a world with miracles. What about from a different perspective, thinking about the universe as a computation, like a program running on a computer? That's kind of a neighboring concept. It is. It is an interesting and reasonably well-defined question to ask, is the world computable? Does the world satisfy what we would call in CS the Church-Turing thesis? That is, could we take any physical system and simulate it to any desired precision by a Turing machine, given the appropriate input data? And so far, I think the indications are pretty strong that our world does seem to satisfy the Church-Turing thesis at least if it doesn't, then we haven't yet discovered why not. But now, does that mean that our universe is a simulation? Well, that word seems to suggest that there is some other larger universe in which it is running, right? And the problem there is that if the simulation is perfect, then we're never going to be able to get any direct evidence about that other universe. We will only be able to see the effects of the computation that is running in this universe. Well, let's imagine an analogy. Let's imagine a PC, a personal computer, a computer. Is it possible with the advent of artificial intelligence for the computer to look outside of itself to understand its creator? I mean, is that a ridiculous analogy? Well, I mean, with the computers that we actually have, I mean, first of all, we all know that humans have done an imperfect job of enforcing the abstraction boundaries of computers. Like you may try to confine some program to a playpen, but as soon as there's one memory allocation error in the C program, then the program has gotten out of that playpen and it can do whatever it wants. This is how most hacks work. You know, viruses and worms and exploits. And you would have to imagine that an AI would be able to discover something like that. Now, of course, if we could actually discover some exploit of reality itself, then this whole, I mean, then in some sense, we wouldn't have to philosophize about this. This would no longer be a metaphysical conversation. Right, this would just be a- But the question is, what would that hack look like? Yeah, well, I have no idea. I mean, Peter Shore, the very famous person in quantum computing, of course, has joked that maybe the reason why we haven't yet integrated general relativity in quantum mechanics is that the part of the universe that depends on both of them was actually left unspecified. And if we ever tried to do an experiment involving the singularity of a black hole or something like that, then the universe would just generate an overflow error or something, right? A blue screen of death. Yeah, we would just crash the universe. Now, the universe has seemed to hold up pretty well for 14 billion years, right? So my Occam's razor kind of guess has to be that it will continue to hold up, that the fact that we don't know the laws of physics governing some phenomenon is not a strong sign that probing that phenomenon is going to crash the universe, right? But, you know, of course I could be wrong. But do you think on the physics side of things, you know, there's been recently a few folks, Eric Weinstein and Stephen Wolfram, that came out with a theory of everything. I think there's a history of physicists dreaming and working on the unification of all the laws of physics. Do you think it's possible that once we understand more physics, not necessarily the unification of the laws, but just understand physics more deeply at the fundamental level, we'll be able to start, you know, I mean, part of this is humorous, but looking to see if there's any bugs in the universe that could be exploited for, you know, traveling at not just speed of light, but just traveling faster than our current spaceships can travel, all that kind of stuff. Well, I mean, to travel faster than our current spaceships could travel, you wouldn't need to find any bug in the universe, right? The known laws of physics, you know, let us go much faster, up to the speed of light, right? And, you know, when people wanna go faster than the speed of light, well, we actually know something about what that would entail, namely that, you know, according to relativity, that seems to entail communication backwards in time, okay? So then you have to worry about closed time-like curves and all of that stuff. So, you know, in some sense, we sort of know the price that you have to pay for these things, right? But under the current understanding of physics. That's right, that's right. We can't, you know, say that they're impossible, but we, you know, we know that sort of a lot else in physics breaks, right? So now regarding Eric Weinstein and Stephen Wolfram, like I wouldn't say that either of them has a theory of everything. I would say that they have ideas that they hope, you know, could someday lead to a theory of everything. Is that a worthy pursuit? Well, I mean, certainly, let's say by theory of everything, you know, we don't literally mean a theory of cats and of baseball and, you know, but we just mean it in the more limited sense of everything, a fundamental theory of physics, right? Of all of the fundamental interactions of physics. Of course, such a theory, even after we had it, you know, would leave the entire question of all the emergent behavior, right? You know, to be explored. So it's only everything for a specific definition of everything. Okay, but in that sense, I would say, of course, that's worth pursuing. I mean, that is the entire program of fundamental physics. Right, all of my friends who do quantum gravity, who do string theory, who do anything like that, that is what's motivating them. Yeah, it's funny though, but I mean, Eric Weinstein talks about this, it is, I don't know much about the physics world, but I know about the AI world, and it is a little bit taboo to talk about AGI, for example, on the AI side. So really, to talk about the big dream of the community, I would say, because it seems so far away, it's almost taboo to bring it up, because, you know, it's seen as the kind of people that dream about creating a truly superhuman level of intelligence. That's really far out there. People, because we're not even close to that. And it feels like the same thing is true for the physics community. I mean, Stephen Hawking certainly talked constantly about theory of everything, right? You know, I mean, people use those terms who were some of the most respected people in the whole world of physics, right? But I mean, I think that the distinction that I would make is that people might react badly if you use the term in a way that suggests that you, you know, thinking about it for five minutes have come up with this major new insight about it, right? It's difficult. Stephen Hawking is not a great example, because I think you can do whatever the heck you want when you get to that level. And I certainly see senior faculty, you know. At that point, that's one of the nice things about getting older is you stop giving a damn. But the community as a whole, they tend to roll their eyes very quickly at stuff that's outside the quote-unquote mainstream. Well, let me put it this way. I mean, if you asked, you know, Ed Witten, let's say, who is, you know, you might consider a leader of the string community, and thus, you know, very, very mainstream in a certain sense. But he would have no hesitation in saying, you know, of course, you know, they're looking for, you know, a unified description of nature, of, you know, of general relativity, of quantum mechanics, of all the fundamental interactions of nature, right? Now, you know, whether people would call that a theory of everything, whether they would use that term, that might vary. You know, Lenny Suskin would definitely have no problem telling you that, you know, if that's what we want, right? For me, who loves human beings and psychology, it's kind of ridiculous to say a theory that unifies the laws of physics gets you to understand everything. I would say you're not even close to understanding everything. Yeah, right, well, yeah, I mean, the word everything is a little ambiguous here, right? Because, you know, and then people will get into debates about, you know, reductionism versus emergentism and blah, blah, blah. And so, in not wanting to say theory of everything, people might just be trying to short-circuit that debate. And say, you know, look, you know, yes, we want a fundamental theory of, you know, the particles and interactions of nature. Let me bring up the next topic that people don't want to mention, although they're getting more comfortable with it, is consciousness. You mentioned that you have a talk on consciousness that I watched five minutes of, but the internet connection was really bad. Was this my talk about, you know, refuting the integrated information theory? Yes, it might have been. Which was this particular account of consciousness that, yeah, I think one can just show it doesn't work. So let me, uh. I'm here to say what does work. What does work, yeah. Let me ask, maybe it'd be nice to comment on, you talk about also like the semi-hard problem of consciousness or like almost hard problem or kind of hard. Pretty hard problem, I think I call it. So maybe can you talk about that, their idea of the approach to modeling consciousness and why you don't find it convincing? What is it, first of all? Okay, well, so what I called the pretty hard problem of consciousness. This is my term, although many other people have said something equivalent to this, okay? But it's just, you know, the problem of, you know, giving an account of just which physical systems are conscious and which are not. Or, you know, if there are degrees of consciousness, then quantifying how conscious a given system is. Oh, awesome, so that's the pretty hard problem. Yeah, that's what I mean by it. That's it, I'm adopting it. I love it, that's a good ring to it. And so, you know, the infamous hard problem of consciousness is to explain how something like consciousness could arise at all, you know, in a material universe, right? Or, you know, why does it ever feel like anything to experience anything, right? And, you know, so I'm trying to distinguish from that problem, right? And say, you know, no, okay, I would merely settle for an account that could say, you know, is a fetus conscious, you know? If so, at which trimester, you know, is a dog conscious? You know, what about a frog, right? Or even as a precondition, you take that both these things are conscious, tell me which is more conscious. Yeah, for example, yes. Yeah, yeah, I mean, if consciousness is some multidimensional vector, well, just tell me in which respects these things are conscious and in which respect they aren't, right? And, you know, and have some principled way to do it where you're not, you know, carving out exceptions for things that you like or don't like, but could somehow take a description of an arbitrary physical system. And then just based on the physical properties of that system or the informational properties or how it's connected or something like that, just in principle calculate, you know, its degree of consciousness, right? I mean, this would be the kind of thing that we would need, you know, if we wanted to address questions like, you know, what does it take for a machine to be conscious, right, or when should we regard AIs as being conscious? So now this IIT, this integrated information theory, which has been put forward by Giulio Tononi and a bunch of his collaborators over the last decade or two, this is noteworthy, I guess, as a direct attempt to answer that question, to, you know, answer the, to address the pretty hard problem, right? And they give a criterion that's just based on how a system is connected. So it's up to you to sort of abstract a system like a brain or a microchip as a collection of components that are connected to each other by some pattern of connections, you know, and to specify how the components can influence each other, you know, like where the inputs go, you know, where they affect the outputs. But then once you've specified that, then they give this quantity that they call phi, you know, the Greek letter phi. And the definition of phi has actually changed over time. It changes from one paper to another, but in all of the variations, it involves something about what we in computer science would call graph expansion. So basically what this means is that they want, in order to get a large value of phi, it should not be possible to take your system and partition it into two components that are only weakly connected to each other, okay? So whenever we take our system and sort of try to split it up into two, then there should be lots and lots of connections going between the two components. Okay, well, I understand what that means on a graph. Do they formalize what, how to construct such a graph or data structure, whatever, or is this, one of the criticism I've heard you kind of say is that a lot of the very interesting specifics are usually communicated through like natural language, like through words, so it's like the details aren't always clear. Well, it's true. I mean, they have nothing even resembling a derivation of this phi, okay? So what they do is they state a whole bunch of postulates, you know, axioms that they think that consciousness should satisfy, and then there's some verbal discussion, and then at some point, phi appears, right? And this was the first thing that really made the hair stand on my neck, to be honest, because they are acting as if there's a derivation. They're acting as if, you know, you're supposed to think that this is a derivation, and there's nothing even remotely resembling a derivation. They just pull the phi out of a hat completely. Is one of the key criticisms to you is that details are missing, or is there something more fundamental? That's not even the key criticism. That's just a side point, okay? The core of it is that I think that they wanna say that a system is more conscious the larger its value of phi, and I think that that is obvious nonsense, okay? As soon as you think about it for like a minute, as soon as you think about it in terms of could I construct a system that had an enormous value of phi, like even larger than the brain has, but that is just implementing an error-correcting code, you know, doing nothing that we would associate with intelligence or consciousness or any of it, the answer is yes, it is easy to do that, right? And so I wrote blog posts just making this point that yeah, it's easy to do that. Now, you know, Tannone's response to that was actually kind of incredible, right? I mean, I admired it in a way, because instead of disputing any of it, he just bit the bullet in the sense, you know, he was one of the most audacious bullet-bitings I've ever seen in my career, okay? He said, okay, then, fine, you know, this system that just applies this error-correcting code, it's conscious, you know, and if it has a much larger value of phi than you or me, it's much more conscious than you or me. You know, we just have to accept what the theory says, because, you know, science is not about confirming our intuitions, it's about challenging them, and, you know, this is what my theory predicts, that this thing is conscious, and, you know, or super-duper conscious, and how are you gonna prove me wrong? See, so the way I would argue against your blog post is I would say, yes, sure, you're right in general, but for naturally arising systems developed through the process of evolution on Earth, this rule of the larger phi being associated with more consciousness is correct. Yeah, so that's not what he said at all, right? Because he wants this to be completely general, right? So we can apply it to even computers. Yeah, I mean, the whole interest of the theory is the hope that it could be completely general, apply to aliens, to computers, to animals, coma patients, to any of it, right? And so he just said, well, you know, Scott is relying on his intuition, but I'm relying on this theory. And to me, it was almost like, are we being serious here? Like, okay, yes, in science, we try to learn highly non-intuitive things, but what we do is we first test the theory on cases where we already know the answer, right? Like if someone had a new theory of temperature, right, then maybe we could check that it says that boiling water is hotter than ice, and then if it says that the sun is hotter than anything you've ever experienced, then maybe we trust that extrapolation, right? But like this theory, like if, you know, it's now saying that a gigantic grid, like regular grid of exclusive orgates can be way more conscious than a person or than any animal can be, even if it is so uniform that it might as well just be a blank wall, right? And so now the point is, if this theory is sort of getting wrong, the question is a blank wall more conscious than a person, then I would say, what is there for it to get right? So your sense is a blank wall is not more conscious than a human being. Yeah, I mean, you could say that I am taking that as one of my axioms. I'm saying that if a theory of consciousness is getting that wrong, then whatever it is talking about, at that point, I'm not going to call it consciousness. I'm gonna use a different word. You have to use a different word. I mean, it's possible, just like with intelligence, that us humans conveniently define these very difficult to understand concepts in a very human-centric way. Just like the Turing test really seems to define intelligence as a thing that's human-like. Right, but I would say that with any concept, we first need to define it, right? And a definition is only a good definition if it matches what we thought we were talking about prior to having a definition, right? And I would say that phi, as a definition of consciousness, fails that test. That is my argument. So, okay, so let's take a further step. So you mentioned that the universe might be, the Turing machine, so it might be computation. Or simulatable by one, anyway. Simulatable by one. So what's your sense about consciousness? Do you think consciousness is computation? That we don't need to go to any place outside of the computable universe to understand consciousness, to build consciousness, to measure consciousness, all those kinds of things? I don't know. These are what have been called the vertiginous questions. They're the questions like, you get a feeling of vertigo when thinking about them. I mean, I certainly feel like I am conscious in a way that is not reducible to computation, but why should you believe me? I mean, and if you said the same to me, then why should I believe you? But as computer scientist, I feel like a computer could achieve human-level intelligence. And that's actually a feeling and a hope. That's not a scientific belief. It's just we've built up enough intuition. The same kind of intuition you use in your blog, that's what scientists do. I mean, some of it is a scientific method, but some of it is just damn good intuition. I don't have a good intuition about consciousness. I'm not sure that anyone does or has in the 2,500 years that these things have been discussed, Lex. But do you think we will? I got a chance to attend, can't wait to hear your opinion on this, but attend the Neuralink event. And one of the dreams there is to basically push neuroscience forward. And the hope with neuroscience is that we can inspect the machinery from which all this fun stuff emerges and see are we gonna notice something special, some special sauce from which something like consciousness or cognition emerges. Yeah, well, it's clear that we've learned an enormous amount about neuroscience. We've learned an enormous amount about computation, about machine learning, about AI, how to get it to work. We've learned an enormous amount about the underpinnings of the physical world. From one point of view, that's like an enormous distance that we've traveled along the road to understanding consciousness. From another point of view, the distance still to be traveled on the road maybe seems no shorter than it was at the beginning. So it's very hard to say. I mean, these are questions like in sort of trying to have a theory of consciousness, there's sort of a problem where it feels like it's not just that we don't know how to make progress, it's that it's hard to specify what could even count as progress. Because no matter what scientific theory someone proposed, someone else could come along and say, well, you've just talked about the mechanism. You haven't said anything about what breathes fire into the mechanism, what really makes there something that it's like to be it. And that seems like an objection that you could always raise no matter how much someone elucidated the details of how the brain works. Okay, let's go to Turing test and Lamda prize. I have this intuition, call me crazy, but that a machine to pass the Turing test in its full, whatever the spirit of it is, we can talk about how to formulate the perfect Turing test, that that machine has to be conscious. Or we at least have to, I have a very low bar of what consciousness is. I tend to think that the emulation of consciousness is as good as consciousness. So like consciousness is just a dance, a social shortcut, like a nice useful tool. But I tend to connect intelligence and consciousness together, so by that, do you, maybe just to ask, what role does consciousness play do you think it passed in the Turing test? Well, look, I mean, it's almost tautologically true that if we had a machine that passed the Turing test, then it would be emulating consciousness, right? So if your position is that emulation of consciousness is consciousness, then by definition, any machine that passed the Turing test would be conscious. But I mean, you could say that that is just a way to rephrase the original question, is an emulation of consciousness necessarily conscious? Here, I'm not saying anything new that hasn't been debated ad nauseum in the literature, but you could imagine some very hard cases, like imagine a machine that passed the Turing test, but it did so just by an enormous cosmological-sized lookup table that just cached every possible conversation that could be had. The old Chinese room argument. Well, yeah, but this is, I mean, the Chinese room actually would be doing some computation, at least in Searle's version, right? Here, I'm just talking about a table lookup, okay? Now, it's true that for conversations of a reasonable length this lookup table would be so enormous it wouldn't even fit in the observable universe, okay? But supposing that you could build a big enough lookup table and then just pass the Turing test just by looking up what the person said, right? Are you going to regard that as conscious? Okay, let me try to make this formal, and then you can shut it down. I think that the emulation of something is that something. If there exists in that system a black box that's full of mystery. So like- Full of mystery to whom? To human inspectors. So does that mean that consciousness is relative to the observer? Like, could something be conscious for us, but not conscious for an alien that understood better what was happening inside the black box? Yes, yes. So that if inside the black box is just a lookup table, the alien that saw that would say this is not conscious. To us, another way to phrase the black box is layers of abstraction, which make it very difficult to see to the actually underlying functionality of the system. And then we observe just the abstraction, and so it looks like magic to us. But once we understand the inner machinery, it stops being magic. And so like, that's a prerequisite is that you can't know how it works, or some part of it. Because then there has to be in our human mind an entry point for the magic. So that's a formal definition of the system. Yeah, well look, I mean, I explored a view in this essay I wrote called The Ghost in the Quantum Turing Machine seven years ago that is related to that, except that I did not wanna have consciousness be relative to the observer, right? Because I think that if consciousness means anything, it is something that is experienced by the entity that is conscious, right? You know, like I don't need you to tell me that I'm conscious, right? Nor do you need me to tell you that you are, right? So, but basically what I explored there is, are there aspects of a system like a brain that just could not be predicted even with arbitrarily advanced future technologies? It's because of chaos combined with quantum mechanical uncertainty, you know, and things like that. I mean, that actually could be a property of the brain, you know, if true, that would distinguish it in a principled way, at least from any currently existing computer. Not from any possible computer, but from, yeah, yeah. Let's do a thought experiment. So if I gave you information that the entire history of your life, basically explain away free will with a lookup table. Say that this was all predetermined, that everything you experienced has already been predetermined. Wouldn't that take away your consciousness? Wouldn't you, yourself, wouldn't the experience of the world change for you in a way that you can't take back? Let me put it this way. If you could do like in a Greek tragedy, where you know, you would just write down a prediction for what I'm going to do, and then maybe you put the prediction in a sealed box, and maybe, you know, you open it later, and you show that you knew everything I was going to do, or, you know, of course, the even creepier version would be you tell me the prediction, and then I try to falsify it. My very effort to falsify it makes it come true, right? Let's even forget that version, as convenient as it is for fiction writers, right? Let's just do the version where you put the prediction into a sealed envelope, okay? But if you could reliably predict everything that I was going to do, I'm not sure that that would destroy my sense of being conscious, but I think it really would destroy my sense of having free will, you know? And much, much more than any philosophical conversation could possibly do that, right? And so I think it becomes extremely interesting to ask, you know, could such predictions be done, you know, even in principle? Is it consistent with the laws of physics to make such predictions, to get enough data about someone that you could actually generate such predictions without having to kill them in the process, to, you know, slice their brain up into little slivers or something? I mean, it's theoretically possible, right? Well, I don't know. I mean, it might be possible, but only at the cost of destroying the person, right? I mean, it depends on how low you have to go in sort of the substrate. Like, if there was a nice digital abstraction layer, if you could think of each neuron as a kind of transistor computing a digital function, then you could imagine some nanorobots that would go in and would just scan the state of each transistor, you know, of each neuron, and then, you know, make a good enough copy, right? But if it was actually important to get down to the molecular or the atomic level, then, you know, eventually you would be up against quantum effects. You would be up against the uncloneability of quantum states. So I think it's a question of how good does the replica have to be before you're going to count it as actually a copy of you, or as being able to predict your actions. That's a totally open question. Yeah, yeah, yeah. And especially once we say that, well, look, maybe there's no way to make a deterministic prediction, because, you know, we know that there's noise buffeting the brain around, presumably even quantum mechanical uncertainty, you know, affecting the sodium ion channels, for example, whether they open or they close. You know, there's no reason why over a certain timescale, that shouldn't be amplified, just like we imagine happens with the weather, or with any other, you know, chaotic system. So if that stuff is important, right, then we would say, well, you know, you can't, you know, you're never going to be able to make an accurate enough copy. But now the hard part is, well, what if someone can make a copy that sort of no one else can tell apart from you, right? It says the same kinds of things that you would have said, maybe not exactly the same things, because we agree that there's noise, but it says the same kinds of things. And maybe you alone would say, no, I know that that's not me, you know, it doesn't share my, I haven't felt my consciousness leap over to that other thing. I still feel it localized in this version, right? And then why should anyone else believe you? What are your thoughts, I'd be curious, you're a really good person to ask, which is Penrose's, Roger Penrose's work on consciousness, saying that there, you know, there is some, with axons and so on, there might be some biological places where quantum mechanics can come into play, and through that create consciousness somehow. Yeah, okay, well. Familiar with his work? Of course, you know, I read Penrose's books as a teenager, they had a huge impact on me. Five or six years ago, I had the privilege to actually talk these things over with Penrose, you know, at some length at a conference in Minnesota. And, you know, he is, you know, an amazing personality. I admire the fact that he was even raising such audacious questions at all. But, you know, to answer your question, I think the first thing we need to get clear on is that he is not merely saying that quantum mechanics is relevant to consciousness, right? That would be like, you know, that would be tame compared to what he is saying, right? He is saying that, you know, even quantum mechanics is not good enough, right? Because if, supposing, for example, that the brain were a quantum computer, well, that's still a computer, you know? In fact, a quantum computer can be simulated by an ordinary computer, it might merely need exponentially more time in order to do so, right? So that's simply not good enough for him, okay? So what he wants is for the brain to be a quantum gravitational computer. Or he wants the brain to be exploiting as yet unknown laws of quantum gravity, okay? Which would be uncomputable according to him. That's the key point. Okay, yes, yes. That would be literally uncomputable. And I've asked him, you know, to clarify this, but uncomputable, even if you had an oracle for the halting problem, or, you know, as high up as you wanna go in the sort of, the usual hierarchy of uncomputability, he wants to go beyond all of that. Okay, so, you know, just to be clear, like, you know, if we're keeping count of how many speculations, you know, there's probably like at least five or six of them, right? There's, first of all, that there is some quantum gravity theory that would involve this kind of uncomputability, right? Most people who study quantum gravity would not agree with that. They would say that what we've learned, you know, what little we know about quantum gravity from this ADS-CFT correspondence, for example, has been very much consistent with the broad idea of nature being computable, right? But, all right, but supposing that he's right about that, then, you know, what most physicists would say is that whatever new phenomena there are in quantum gravity, you know, they might be relevant at the singularities of black holes. They might be relevant at the Big Bang. They are plainly not relevant to something like the brain, you know, that is operating at ordinary temperatures, you know, with ordinary chemistry, and, you know, the physics underlying the brain, they would say that we have, you know, the fundamental physics of the brain, they would say that we've pretty much completely known for generations now, right? Because, you know, quantum field theory lets us sort of parametrize our ignorance, right? I mean, Sean Carroll has made this case, and, you know, in great detail, right? That sort of whatever new effects are coming from quantum gravity, you know, they are sort of screened off by quantum field theory, right? And this brings us to the whole idea of effective theories, right, but that, like, we have, you know, in like in the standard model of elementary particles, right, we have a quantum field theory that seems totally adequate for all of the terrestrial phenomena, right? The only things that it doesn't, you know, explain are, well, first of all, you know, the details of gravity, if you were to probe it, like at, you know, extremes of, you know, curvature, like incredibly small distances, it doesn't explain dark matter, it doesn't explain black hole singularities, right? But these are all very exotic things, very, you know, far removed from our life on Earth, right? So for Penrose to be right, he needs, you know, these phenomena to somehow affect the brain. He needs the brain to contain antenna that are sensitive to this- To black holes. To this as yet unknown physics, right? And then he needs a modification of quantum mechanics, okay? So he needs quantum mechanics to actually be wrong, okay? He needs, what he wants is what he calls an objective reduction mechanism, or an objective collapse. So this is the idea that once quantum states get large enough, then they somehow spontaneously collapse, right? That, you know, and this is an idea that lots of people have explored. You know, there's something called the GRW proposal that tries to, you know, say something along those lines. You know, and these are theories that actually make testable predictions, right? Which is a nice feature that they have. But, you know, the very fact that they're testable may mean that in the, you know, in the coming decades, we may well be able to test these theories and show that they're wrong, right? You know, we may be able to test some of Penrose's ideas. If not, not his ideas about consciousness, but at least his ideas about an objective collapse of quantum states, right? And people have actually, like Dick Balmister, have actually been working to try to do these experiments. They haven't been able to do it yet to test Penrose's proposal, okay? But Penrose would need more than just an objective collapse of quantum states, which would already be the biggest development in physics for a century, since quantum mechanics itself. Okay, he would need for consciousness to somehow be able to influence the direction of the collapse, so that it wouldn't be completely random, but that, you know, your dispositions would somehow influence the quantum state to collapse more likely this way or that way, okay? Finally, Penrose, you know, says that all of this has to be true because of an argument that he makes based on Gödel's incompleteness theorem, okay? Now, like, I would say, the overwhelming majority of computer scientists and mathematicians who have thought about this, I don't think that Gödel's incompleteness theorem can do what he needs it to do here, right? I don't think that that argument is sound, okay? But that is, you know, that is sort of the tower that you have to ascend to if you're going to go where Penrose goes. And the intuition he uses with the incompleteness theorem is that basically that there's important stuff that's not computable? Is that where he takes it? No, it's not just that, because, I mean, everyone agrees that there are problems that are uncomputable, right? That's a mathematical theorem, right? But what Penrose wants to say is that, you know, the, you know, for example, there are statements, you know, given any formal system, you know, for doing math, right, there will be true statements of arithmetic that that formal system, you know, if it's adequate for math at all, if it's consistent and so on, will not be able to prove. A famous example being the statement that that system itself is consistent, right? No, you know, good formal system can actually prove its own consistency. That can only be done from a stronger formal system, which then can't prove its own consistency and so on forever, okay? That's Gödel's theorem. But now, why is that relevant to consciousness, right? Well, you know, I mean, the idea that it might have something to do with consciousness is an old one. Gödel himself apparently thought that it did. You know, Lucas thought so, I think, in the 60s. And Penrose is really just, you know, sort of updating what they and others had said. I mean, you know, the idea that Gödel's theorem could have something to do with consciousness was, you know, in 1950, when Alan Turing wrote his article about the Turing test, he already, you know, was writing about that as like an old and well-known idea and as one that he, as a wrong one that he wanted to dispense with, right? Okay, but the basic problem with this idea is, you know, Penrose wants to say that, and all of his predecessors here, you know, want to say that, you know, even though, you know, this given formal system cannot prove its own consistency, we as humans, sort of looking at it from the outside, can just somehow see its consistency, right? And the rejoinder to that, you know, from the very beginning has been, well, can we really? I mean, maybe, you know, maybe he, Penrose, can, but, you know, can the rest of us, right? And, you know, I noticed that, you know, I mean, it is perfectly plausible to imagine a computer that could say, you know, would not be limited to working within a single formal system, right? That could say, I am now going to adopt the hypothesis that my formal system is consistent, right? And I'm now gonna see what can be done from that stronger vantage point, and so on. And, you know, and I'm going to add new axioms to my system. Totally plausible, there's absolutely, Godel's theorem has nothing to say against an AI that could repeatedly add new axioms. All it says is that there is no absolute guarantee that when the AI adds new axioms, that it will always be right, okay? And, you know, and that's, of course, the point that Penrose pounces on, but the reply is obvious, and, you know, it's one that Alan Turing made 70 years ago, namely, we don't have an absolute guarantee that we're right when we add a new axiom. We never have, and plausibly, we never will. So on Alan Turing, you took part in the Love No Prize? Not really, no. Or was it? I didn't, I mean, there was this kind of ridiculous claim that was made some, almost a decade ago about a chatbot called Eugene Gooseman. I guess you didn't participate as a judge in the Love No Prize. I didn't, no. But you participated as a judge in that, I guess it was an exhibition event or something like that, or was Eugene the? No, Eugene Gooseman, that was just me writing a blog post because some journalist called me to ask about it. Did you ever chat with him? I did chat with Eugene Gooseman. I mean, it was available on the web, the chat. Oh, interesting, I didn't know that. So yeah, so all that happened was that a bunch of journalists started writing breathless articles about first chatbot that passes the Turing test. And it was this thing called Eugene Gooseman that was supposed to simulate a 13-year-old boy. And apparently someone had done some test where people couldn't, were less than perfect, let's say, distinguishing it from a human. And they said, well, if you look at Turing's paper and you look at the percentages that he talked about, then it seemed like we're past that threshold. And I had a sort of different way to look at it instead of the legalistic way. Like, let's just try the actual thing out and let's see what it can do with questions like, is Mount Everest bigger than a shoebox? Okay, or just like the most obvious questions, right? And then, and the answer is, well, it just kind of parries you because it doesn't know what you're talking about, right? So just to clarify exactly in which way they're obvious. They're obvious in the sense that you convert the sentences into the meaning of the objects they represent and then do some basic, obvious would mean, your common sense reasoning with the objects that the sentences represent. Right, right, it was not able to answer or even intelligently respond to basic common sense questions. But let me say something stronger than that. There was a famous chatbot in the 60s called Eliza, right? That managed to actually fool a lot of people, right? Or people would pour their hearts out into this Eliza because it simulated a therapist, right? And most of what it would do is it would just throw back at you whatever you said, right? And this turned out to be incredibly effective, right? Maybe therapists know this, this is one of their tricks. But it really had some people convinced. But this thing was just like, I think it was literally just a few hundred lines of Lisp code, right? It was not only was it not intelligent, it wasn't especially sophisticated. It was a simple little hobbyist program. And Eugene Guzman, from what I could see, was not a significant advance compared to Eliza, right? So, and that was really the point I was making. And this was, you didn't, in some sense you didn't need a computer science professor to sort of say this. Like anyone who was looking at it and who just had an ounce of sense could have said the same thing, right? But because these journalists were calling me, the first thing I said was, well, you know, I'm a quantum computing person. I'm not an AI person. You shouldn't ask me. Then they said, look, you can go here and you can try it out. I said, all right, all right, so I'll try it out. But now, this whole discussion, I mean, it got a whole lot more interesting in just the last few months. Yeah, I'd love to hear your thoughts about GPT-3, the advancement from LinkedIn. In the last few months, we've had, the world has now seen a chat engine or a text engine, I should say, called GPT-3. I think it's still, it does not pass a Turing test. There are no real claims that it passes the Turing test. This comes out of the group at OpenAI and they've been relatively careful in what they've claimed about the system. But I think this, as clearly as Eugene Guzman was not in advance over Eliza, it is equally clear that this is a major advance over Eliza or really over anything that the world has seen before. This is a text engine that can come up with kind of on-topic, reasonable-sounding completions to just about anything that you ask. You can ask it to write a poem about topic X in the style of poet Y and it will have a go at that. And it will do not a great job, not an amazing job, but a passable job. Definitely as good as, in many cases, I would say better than I would have done. You can ask it to write an essay, like a student essay about pretty much any topic and it will get something that I am pretty sure would get at least a B- in most high school or even college classes. And in some sense, the way that it did this, the way that it achieves this, Scott Alexander of the much mourned blog Slate Star Codex had a wonderful way of putting it. He said that they basically just ground up the entire internet into a slurry. To tell you the truth, I had wondered for a while why nobody had tried that. Why not write a chatbot by just doing deep learning over a corpus consisting of the entire web? Now they finally have done that. The results are very impressive. It's not clear that people can argue about whether this is truly a step toward general AI or not, but this is an amazing capability that we didn't have a few years ago. A few years ago, if you had told me that we would have it now, that would have surprised me. And I think that anyone who denies that is just not engaging with what's there. So their model, it takes a large part of the internet and compresses it in a small number of parameters relative to the size of the internet and is able to, without fine tuning, do a basic kind of a querying mechanism, just like you describe where you specify a kind of poet and then you wanna write a poem. And it somehow is able to do basically a lookup on the internet of relevant things. I mean, that's what it, how else do you explain it? Well, okay, I mean, the training involved massive amounts of data from the internet and actually took lots and lots of computer power, lots of electricity, right? You know, there are some very prosaic reasons why this wasn't done earlier, right? But it costs some tens of millions of dollars, I think. Less, but approximately like a few million dollars. Oh, okay, okay. Oh, really, okay. It's more like four or five. Oh, all right, all right, thank you. I mean, as they scale it up, it will- It'll cost, but then the hope is cost comes down and all that kind of stuff. But basically, it is a neural net, so I mean, or what's now called a deep net, but they're basically the same thing, right? So it's a form of algorithm that people have known about for decades, right? But it is constantly trying to solve the problem, predict the next word, right? So it's just trying to predict what comes next. It's not trying to decide what it should say, what ought to be true. It's trying to predict what someone who had said all of the words up to the preceding one would say next. Although to push back on that, that's how it's trained. That's right, no, of course. But it's arguable that our very cognition could be a mechanism as that simple. Oh, of course, of course. I never said that it wasn't. Right, but- Yeah, I mean, in some sense, that is, if there is a deep philosophical question that's raised by GPT-3, then that is it, right? Are we doing anything other than this predictive processing, just constantly trying to fill in a blank of what would come next after what we just said up to this point? Is that what I'm doing right now? Is it possible, so the intuition that a lot of people have, well, look, this thing is not gonna be able to reason, the mountain Everest question. Do you think it's possible that GPT-5, 6, and 7 would be able to, with this exact same process, begin to do something that looks like, is indistinguishable to us humans from reasoning? I mean, the truth is that we don't really know what the limits are, right? Right, exactly. Because what we've seen so far is that GPT-3 was basically the same thing as GPT-2, but just with a much larger network, more training time, bigger training corpus, right? And it was very noticeably better than its immediate predecessor. So we don't know where you hit the ceiling here, right? I mean, that's the amazing part, and maybe also the scary part, right? That, you know, now my guess would be that, you know, at some point, like there has to be diminishing returns. Like, it can't be that simple, can it? Right, right? But I wish that I had more to base that guess on. Right. Yeah, I mean, some people say that there will be a limitation on the, we're gonna hit a limit on the amount of data that's on the internet. Yes, yeah, so sure. So there's certainly that limit. I mean, there's also, you know, like if you are looking for questions that will stump GPT-3, right, you can come up with some without, you know, like, you know, even getting it to learn how to balance parentheses, right? Like it can, you know, it doesn't do such a great job, right, you know, like, you know, and its failures are ironic, right? Like basic arithmetic, right? Basic arithmetic. And you think, you know, isn't that what computers are supposed to be best at? Isn't that where computers already had us beat a century ago, right? And yet that's where GPT-3 struggles, right? But it's amazing, you know, that it's almost like a young child in that way, right? But somehow, you know, because it is just trying to predict what comes next, it doesn't know when it should stop doing that and start doing something very different, like some more exact logical reasoning, right? And so, you know, one is naturally led to guess that our brain sort of has some element of predictive processing, but that it's coupled to other mechanisms, right? That it's coupled to, you know, first of all, visual reasoning, which GPT-3 also doesn't have any of, right? Although there's some demonstration that there's a lot of promise there. Oh yeah, it can complete images, that's right. And using exact same kind of transformer mechanisms to like watch videos on YouTube and so the same self-supervised mechanism to be able to learn. It'd be fascinating to think what kind of completions you could do. Oh yeah, no, absolutely. Although like if we ask it to like, you know, a word problem that involved reasoning about the locations of things in space, I don't think it does such a great job on those, right? To take an example. And so the guess would be, well, you know, humans have a lot of predictive processing, a lot of just filling in the blanks, but we also have these other mechanisms that we can couple to, or that we can sort of call as subroutines when we need to. And that maybe, you know, to go further, that one would want to integrate other forms of reasoning. Let me go on another topic that is amazing, which is complexity. And then start with the most absurdly romantic question of what's the most beautiful idea in the computer science or theoretical computer science to you? Like what just early on in your life or in general have captivated you and just grabbed you? I think I'm gonna have to go with the idea of universality. You know, if you're really asking for the most beautiful. I mean, so universality is the idea that, you know, you put together a few simple operations, like in the case of Boolean logic, that might be the AND gate, the OR gate, the NOT gate, right? And then your first guess is, okay, this is a good start, but obviously, as I want to do more complicated things, I'm gonna need more complicated building blocks to express that, right? And that was actually my guess when I first learned what programming was. I mean, when I was, you know, an adolescent and someone showed me Apple Basic and, you know, GW Basic, if anyone listening remembers that. Okay, but, you know, I thought, okay, well now, you know, I mean, I thought, I felt like this is a revelation, you know, it's like finding out where babies come from. It's like that level of, you know, why didn't anyone tell me this before, right? But I thought, okay, this is just the beginning. Now I know how to write a basic program, but to, you know, really write an interesting program, like, you know, a video game, which had always been my dream as a kid, to, you know, create my own Nintendo games, right? But, you know, obviously I'm gonna need to learn some way more complicated form of programming than that. Okay, but, you know, eventually I learned this incredible idea of universality. And that says that, no, you throw in a few rules and then you already have enough to express everything. Okay, so for example, the AND, the OR, and the NOT gate can all, or in fact, even just the AND and the NOT gate, or even just the NAND gate, for example, is already enough to express any Boolean function on any number of bits. You just have to string together enough of them. You can build a universe with NAND gates. You can build the universe out of NAND gates, yeah. You know, the simple instructions of BASIC are already enough, at least in principle. You know, if we ignore details like how much memory can be accessed and stuff like that, that is enough to express what could be expressed by any programming language whatsoever. And the way to prove that is very simple. We simply need to show that in BASIC or whatever, we could write an interpreter or a compiler for whatever other programming language we care about, like C or Java or whatever. And as soon as we had done that, then ipso facto, anything that's expressible in C or Java is also expressible in BASIC. Okay, and so this idea of universality, you know, goes back at least to Alan Turing in the 1930s, when, you know, he wrote down this incredibly simple pared-down model of a computer, the Turing machine, right? Which, you know, he pared down the instruction set to just read a symbol, you know, go write a symbol, move to the left, move to the right, halt, change your internal state, right? That's it, okay? And anybody proved that, you know, this could simulate all kinds of other things, you know? And so in fact, today we would say, well, we would call it a Turing universal model of computation that is, you know, just as, it has just the same expressive power that BASIC or Java or C++ or any of those other languages have, because anything in those other languages could be compiled down to Turing machine. Now, Turing also proved a different related thing, which is that there is a single Turing machine that can simulate any other Turing machine, if you just describe that other machine on its tape, right? And likewise, there is a single Turing machine that will run any C program, you know, if you just put it on its tape. That's a second meaning of universality. First of all, he couldn't visualize it and that was in the 30s, I think? Yeah, the 30s, that's right. That's before computers really, I mean, I don't know how, I wonder what that felt like, you know, learning that there's no Santa Claus or something. Because I don't know if that's empowering or paralyzing, because it doesn't give you any, it's like, you can't write a software engineering book and make that the first chapter and say, we're done. Well, I mean, right. I mean, in one sense, it was this enormous flattening of the universe, right? I had imagined that there was gonna be some infinite hierarchy of more and more powerful programming languages. You know, and then I kicked myself for having such a stupid idea, but apparently, Gödel had had the same conjecture in the 30s. Oh, good, you're in good company. Well, yeah, and then Gödel read Turing's paper and he kicked himself and he said, yeah, I was completely wrong about that, okay? But, you know, I had thought that, you know, maybe where I can contribute will be to invent a new, more powerful programming language that lets you express things that could never be expressed in basic, right? And, you know, how would you do that? Obviously, you couldn't do it itself in basic, right? But, you know, there is this incredible flattening that happens once you learn what is universality. But then it's also like an opportunity, because it means once you know these rules, then, you know, the sky is the limit, right? Then you have kind of the same weapons at your disposal that the world's greatest programmer has. It's now all just a question of how you wield them. Right, exactly. But so every problem is solvable, but some problems are harder than others. And- Well, yeah, there's the question of how much time, you know, of how hard is it to write a program, and then there's also the questions of what resources does the program need? You know, how much time, how much memory? Those are much more complicated questions, of course, ones that we're still struggling with today. Exactly, so you've, I don't know if you created Complexity Zoo, or- I did create the Complexity Zoo. What is it? What's complexity? Oh, all right, all right, all right. Complexity theory is the study of sort of the inherent resources needed to solve computational problems. Okay, so it's easiest to give an example. Like, let's say we want to add two numbers, right? If I wanna add them, you know, if the numbers are twice as long, then it only, it will take me twice as long to add them, but only twice as long, right? It's no worse than that. Multiple- For a computer. For a computer, or for a person, we're using pencil and paper for that matter. If you have a good algorithm. Yeah, that's right. You could have an inefficient algorithm. If you just use the elementary school algorithm of just carrying, you know, then it takes time that is linear in the length of the numbers, right? Now, multiplication, if you use the elementary school algorithm, is harder because you have to multiply each digit of the first number by each digit of the second one. Yeah, and then deal with all the carries. So that's what we call a quadratic time algorithm, right? If the numbers become twice as long, now you need four times as much time, okay? So now, as it turns out, people discovered much faster ways to multiply numbers using computers. And today we know how to multiply two numbers that are n digits long using a number of steps that's nearly linear in n. These are questions you can ask, but now let's think about a different thing that people, you know, have encountered in elementary school factoring a number, okay? Take a number and find its prime factors, right? And here, you know, if I give you a number with 10 digits, I ask you for its prime factors. Well, maybe it's even, so you know that two is a factor. You know, maybe it ends in zero, so you know that 10 is a factor, right? But, you know, other than a few obvious things like that, you know, if the prime factors are all very large, then it's not clear how you even get started, right? You know, it seems like you have to do an exhaustive search among an enormous number of factors. Now, and as many people might know, for better or worse, the security, you know, of most of the encryption that we currently use to protect the internet is based on the belief, and this is not a theorem, it's a belief, that factoring is an inherently hard problem for our computers. We do know algorithms that are better than just trial division, than just trying all the possible divisors, but they are still basically exponential. And exponential is hard. Yeah, exactly. So the fastest algorithms that anyone has discovered, at least publicly discovered, you know, I'm assuming that the NSA doesn't know something better, okay, but they take time that basically grows exponentially with the cube root of the size of the number that you're factoring, right? So that cube root, that's the part that takes all the cleverness, okay, but there's still an exponential, there's still an exponentiality there. But what that means is that like, when people use a thousand bit keys for their cryptography, that can probably be broken using the resources of the NSA or the world's other intelligence agencies. You know, people have done analyses that say, you know, with a few hundred million dollars of computer power, they could totally do this. And if you look at the documents that Snowden released, you know, it looks a lot like they are doing that or something like that. It would kind of be surprising if they weren't, okay? But, you know, if that's true, then in some ways that's reassuring because if that's the best that they can do, then that would say that they can't break 2,000 bit numbers. Right? Right? Right, then 2,000 bit numbers would be beyond what even they could do. They haven't found an efficient algorithm. That's where all the worries and the concerns of quantum computing came in, that there could be some kind of shortcut around that. Right, so complexity theory is a huge part of, let's say, the theoretical core of computer science. You know, it started in the 60s and 70s as sort of an autonomous field. So it was already, you know, I mean, you know, it was well-developed even by the time that I was born, okay? But in 2002, I made a website called the Complexity Zoo, to answer your question, where I just tried to catalog the different complexity classes, which are classes of problems that are solvable with different kinds of resources. Right. Okay, so these are kind of, you know, you could think of complexity classes as like being almost to theoretical computer science, like what the elements are to chemistry, right? They're sort of, you know, they're our most basic objects in a certain way. I feel like the elements have a characteristic to them where you can't just add an infinite number. Well, you could, but beyond a certain point, they become unstable. Okay. Right, right, so it's like, you know, in theory, you can have atoms with, you know, and look, look, I mean, a neutron star, you know, is a nucleus with, you know, uncalled billions of neutrons in it, of hadrons in it. Okay, but, you know, for sort of normal atoms, right, probably you can't get much above 100, you know, atomic weight, 150 or so, or sorry, sorry, I mean, beyond 150 or so protons without it, you know, very quickly fissioning. With complexity classes, well, yeah, you can have an infinity of complexity classes, but, you know, maybe there's only a finite number of them that are particularly interesting, right? Just like with anything else, you know, you care about some more than about others. So what kind of interesting classes are there? Yeah. I mean, you could have just, maybe say, what are the, if you take any kind of computer science class, what are the classes you learn? Good, let me tell you sort of the biggest ones, the ones that you would learn first. So, you know, first of all, there is P, that's what it's called, okay? It stands for polynomial time. And this is just the class of all of the problems that you could solve with a conventional computer, like your iPhone or your laptop, you know, by a completely deterministic algorithm, right? Using a number of steps that grows only like the size of the input raised to some fixed power, okay? So if your algorithm is linear time, like, you know, for adding numbers, okay? That problem is in P. If you have an algorithm that's quadratic time, like the elementary school algorithm for multiplying two numbers, that's also in P. Even if it was the size of the input to the 10th power or to the 50th power, well, that wouldn't be very good in practice, but, you know, formally we would still count that. That would still be in P, okay? But if your algorithm takes exponential time, meaning like if every time I add one more data point to your input, if the time needed by the algorithm doubles, if you need time like two to the power of the amount of input data, then that we call an exponential time algorithm, okay? And that is not polynomial, okay? So P is all of the problems that have some polynomial time algorithm, okay? So that includes most of what we do with our computers on a day-to-day basis, you know? All the, you know, sorting, basic arithmetic, you know, whatever is going on in your email reader or in Angry Birds, okay? It's all in P. Then the next super important class is called NP. That stands for non-deterministic polynomial, okay? Does not stand for not polynomial, which is a common confusion. But NP was basically all of the problems where if there is a solution, then it is easy to check the solution if someone shows it to you, okay? So actually a perfect example of a problem in NP is factoring, the one I told you about before. Like if I gave you a number with thousands of digits and I told you that, you know, I asked you, does this have at least three non-trivial divisors, right? That might be a super hard problem to solve, right? Might take you millions of years using any algorithm that's known, at least running on our existing computers, okay? But if I simply showed you the divisors, I said, here are three divisors of this number, then it would be very easy for you to ask your computer to just check each one and see if it works. Just divide it in, see if there's any remainder, right? And if they all go in, then you've checked. Well, I guess there were, right? So any problem where, you know, wherever there's a solution, there is a short witness that can be easily like a polynomial size witness that can be checked in polynomial time. That we call an NP problem, okay? And yeah, so every problem that's in P is also in NP, right? Because, you know, you could always just ignore the witness and just, you know, if a problem is in P, you can just solve it yourself, okay? But now, in some sense, the central, you know, mystery of theoretical computer science is every NP problem in P. So if you can easily check the answer to a computational problem, does that mean that you can also easily find the answer? Even though there's all these problems that appear to be very difficult to find the answer, it's still an open question whether a good answer exists. So what's your- No one has proven that there's no way to do it. It's arguably the most, I don't know, the most famous, the most maybe interesting, maybe you disagree with that, problem in theoretical computer science. So what's your- The most famous, for sure. P equals NP. Yeah. If you were to bet all your money, where do you put your money? That's an easy one. P is not equal to NP. Okay, so- I like to say that if we were physicists, we would have just declared that to be a law of nature. You know, just like thermodynamics or something. That's hilarious. Just giving ourselves Nobel Prizes for its discovery. Yeah, yeah, no, and look, if later it turned out that we were wrong, we just give ourselves more Nobel Prizes. Yeah. I mean, you know, but yeah, because we're- So harsh, but so true. I mean, no, I mean, it's really just because we are mathematicians or descended from mathematicians, you know, we have to call things conjectures that other people would just call empirical facts or discoveries, right? But one shouldn't read more into that difference in language, you know, about the underlying truth. So, okay, so you're a good investor and good spender of money, so then let me ask- I don't know that. Let me ask another way. Yeah. Is it possible at all? And what would that look like if P indeed equals NP? Well, I do think that it's possible. I mean, in fact, you know, when people really pressed me on my blog for what odds would I put, I put, you know, two or 3% odds. Wow, that's pretty good. That P equals NP. Yeah, just be, well, because, you know, when P, I mean, you really have to think about, like, if there were 50, you know, mysteries, like P versus NP, and if I made a guess about every single one of them, would I expect to be right 50 times, right? And the truthful answer is no, okay? Yeah. So, you know, and that's what you really mean in saying that, you know, you have better than 98% odds for something, okay? But, so yeah, you know, I mean, there could certainly be surprises. And look, if P equals NP, well, then there would be the further question of, you know, is the algorithm actually efficient in practice, right? I mean, Don Knuth, who I know that you've interviewed as well, right? He likes to conjecture that P equals NP, but that the algorithm is so inefficient that it doesn't matter anyway, right? Now, I don't know, I've listened to him say that. I don't know whether he says that just because he has an actual reason for thinking it's true or just because it sounds cool, okay? But, you know, that's a logical possibility, right? That the algorithm could be N to the 10,000 time, or it could even just be N squared time, but with a leading constant of, it could be a Google times N squared or something like that. In that case, the fact that P equals NP, well, it would, you know, ravage the whole theory of complexity. We would have to, you know, rebuild from the ground up, but in practical terms, it might mean very little, right? If the algorithm was too inefficient to run. If the algorithm could actually be run in practice, like if it had small enough constants, you know, or if you could improve it to where it had small enough constants that it was efficient in practice, then that would change the world, okay? You think it would have, like, what kind of impact? Well, okay, I mean, here's an example. I mean, you could, well, okay, just for starters, you could break basically all of the encryption that people use to protect the internet. That's just for starters. You could break Bitcoin and every other cryptocurrency, or, you know, mine as much Bitcoin as you wanted, right? You know, become a super duper billionaire, right? And then plot your next move, okay? Right, that's just for starters. That's a good point. Now, your next move might be something like, you know, you now have, like, a theoretically optimal way to train any neural network, to find parameters for any neural network, right? So you could now say, like, is there any small neural network that generates the entire content of Wikipedia, right? If, you know, and now the question is not, can you find it? The question has been reduced to, does that exist or not? If it does exist, then the answer would be, yes, you can find it, okay? If you had this algorithm in your hands, okay? You could ask your computer, you know, I mean, P versus NP is one of these seven problems that carries this million dollar prize from the Clay Foundation. You know, if you solve it, you know, and others are the Riemann hypothesis, the Poincare conjecture, which was solved, although the solver turned down the prize, right? And four others, but what I like to say, the way that we can see that P versus NP is the biggest of all of these questions is that if you had this fast algorithm, then you could solve all seven of them, okay? You just ask your computer, you know, is there a short proof of the Riemann hypothesis, right? You know, that a machine could, in a language where a machine could verify it, and provided that such a proof exists, then your computer finds it in a short amount of time without having to do a brute force search. Okay, so I mean, those are the stakes of what we're talking about, but I hope that also helps to give your listeners some intuition of why I and most of my colleagues would put our money on P not equaling NP. Is it possible, I apologize, this is a really dumb question, but is it possible that a proof will come out that P equals NP, but an algorithm that makes P equals NP is impossible to find? Is that like crazy? Okay, well, if P equals NP, it would mean that there is such an algorithm, right? That it exists, yeah. But, you know, it would mean that it exists. Now, you know, in practice, normally the way that we would prove anything like that would be by finding the algorithm. By finding one algorithm. But there is such a thing as a non-constructive proof that an algorithm exists. You know, this has really only reared its head, I think, a few times in the history of our field, right? But, you know, it is theoretically possible that such a thing could happen. But, you know, there are, even here, there are some amusing observations that one could make. So there is this famous observation of Leonid Levin, who was, you know, one of the original discoverers of NP completeness, right? And he said, well, consider the following algorithm that, like, I guarantee will solve the NP problems efficiently, just as provided that P equals NP, okay? Here is what it does. It just runs, you know, it enumerates every possible algorithm in a gigantic, infinite list, right, from like, in alphabetical order, right? You know, and many of them maybe won't even compile, so we just ignore those, okay? But now we just, you know, run the first algorithm, then we run the second algorithm, we run the first one a little bit more, then we run the first three algorithms for a while, we run the first four for a while. This is called dovetailing, by the way. This is a known trick in theoretical computer science, okay, but we do it in such a way that, you know, whatever is the algorithm out there in our list that solves NP complete, you know, the NP problems efficiently, will eventually hit that one, right? And now the key is that whenever we hit that one, you know, by assumption, it has to solve the problem, it has to find the solution, and once it claims to find the solution, then we can check that ourself, right? Because these are NP problems, then we can check it. Now, this is utterly impractical, right? You know, you'd have to do this enormous exhaustive search among all the algorithms, but from a certain theoretical standpoint, that is merely a constant pre-factor, right? That's merely a multiplier of your running time. So there are tricks like that one can do to say that in some sense, the algorithm would have to be constructive. But, you know, in the human sense, you know, it is possible that, you know, it's conceivable that one could prove such a thing via a non-constructive method. Is that likely? I don't think so, not personally. So that's P and NP, but the Complexity Zoo is full of wonderful creatures. Well, it's got about 500 of them. 500. So how do you get, yeah, how do you get more? How are beavers made? I mean, just for starters, there is everything that we could do with a conventional computer with a polynomial amount of memory, okay? But possibly an exponential amount of time because we get to reuse the same memory over and over again. Okay, that is called PSPACE, okay? And that's actually, we think, an even larger class than NP. Okay, well, P is contained in NP, which is contained in PSPACE. And we think that those containments are strict. And the constraint there is on the memory. The memory has to grow polynomially with the size of the process. That's right, that's right. But in PSPACE, we now have interesting things that were not in NP, like as a famous example, you know, from a given position in chess, you know, does white or black have the win? Let's say, assuming, provided that the game lasts only for a reasonable number of moves, okay? Or likewise for Go, okay? And, you know, even for the generalizations of these games to arbitrary size boards, right? Because with an eight by eight board, you could say that's just a constant size problem. You just, you know, in principle, you just solve it in O of one time, right? But so we really mean the generalizations of, you know, games to arbitrary size boards here. Or another thing in PSPACE would be like, I give you some really hard constraint satisfaction problem, like, you know, a traveling salesperson, or, you know, packing boxes into the trunk of your car, or something like that. And I ask not just, is there a solution, which would be an NP problem, but I ask how many solutions are there, okay? That, you know, count the number of valid solutions. That actually gives those problems lie in a complexity class called sharp P, or like, it looks like hashtag, like hashtag P. Okay, which sits between NP and PSPACE. There's all the problems that you can do in exponential time, okay? That's called EXP. So, and by the way, it was proven in the 60s that EXP is larger than P, okay? So we know that much. We know that there are problems that are solvable in exponential time that are not solvable in polynomial time, okay? In fact, we even know, we know that there are problems that are solvable in N cubed time that are not solvable in N squared time. And that, those don't help us with the controversy between P and NP at all. Unfortunately, it seems not, or certainly not yet, right? The techniques that we use to establish those things, they're very, very related to how Turing proved the unsolvability of the halting problem, but they seem to break down when we're comparing two different resources, like time versus space, or like P versus NP, okay? But, I mean, there's what you can do with a randomized algorithm, right? That can sometimes, has some probability of making a mistake. That's called BPP, bounded error probabilistic polynomial time. And then, of course, there's one that's very close to my own heart, what you can efficiently do in polynomial time using a quantum computer, okay? And that's called BQP, right? And so, you know, what's- What's understood about that class, maybe as a comment. Okay, so P is contained in BPP, which is contained in BQP, which is contained in P space, okay? So anything you can, in fact, in like, in something very similar to sharp P. BQP is basically, you know, well, it's contained in like P with the magic power to solve sharp P problems, okay? So- Why is BQP contained in P space? Oh, that's an excellent question. So there is, well, I mean, one has to prove that, okay? But the proof, you could think of it as using Richard Feynman's picture of quantum mechanics, which is that you can always, you know, we haven't really talked about quantum mechanics in this conversation. We did in our previous one. Yeah, we did last time. But yeah, we did last time, okay? But basically, you could always think of a quantum computation as like a branching tree of possibilities where each possible path that you could take through, you know, the space has a complex number attached to it called an amplitude, okay? And now the rule is, you know, when you make a measurement at the end, will you see a random answer, okay? But quantum mechanics is all about calculating the probability that you're gonna see one potential answer versus another one, right? And the rule for calculating the probability that you'll see some answer is that you have to add up the amplitudes for all of the paths that could have led to that answer. And then, you know, that's a complex number, so that, you know, how could that be a probability? Then you take the squared absolute value of the result. That gives you a number between zero and one, okay? So, yeah, I just summarized quantum mechanics in like 30 seconds, okay? But now, you know, what this already tells us is that anything I can do with a quantum computer, I could simulate with a classical computer if I only have exponentially more time, okay? And why is that? Because if I have exponential time, I could just write down this entire branching tree and just explicitly calculate each of these amplitudes, right, you know, that will be very inefficient, but it will work, right? It's enough to show that quantum computers could not solve the halting problem, or, you know, they could never do anything that is literally uncomputable in Turing's sense. Okay, but now, as I said, there's even a stronger result which says that BQP is contained in P space. The way that we prove that is that we say, if all I want is to calculate the probability of some particular output happening, you know, which is all I need to simulate a quantum computer, really, then I don't need to write down the entire quantum state, which is an exponentially large object. All I need to do is just calculate what is the amplitude for that final state, and to do that, I just have to sum up all the amplitudes that lead to that state, okay? So that's an exponentially large sum, but I can calculate it just reusing the same memory over and over for each term in the sum. Hence the P, in the P space. Hence the P space. Yeah. So what, out of that whole complexity zoo, and it could be BQP, what do you find is the most, the class that captured your heart the most, or the most beautiful class that's just, yeah. I used as my email address bqpqpoly at gmail.com, yes, because bqp slash qpoly, well, you know, amazingly, no one had taken it. Amazing. But, you know, but this is a class that I was involved in sort of defining, proving the first theorems about in 2003 or so. So it was kind of close to my heart. But this is like, if we extended BQP, which is the class of everything we can do efficiently with a quantum computer, to allow quantum advice, which means imagine that you had some special initial state that could somehow help you do computation. And maybe such a state would be exponentially hard to prepare. But maybe somehow these states were formed in the Big Bang or something, and they've just been sitting around ever since. If you found one, and if this state could be like, ultra power, there are no limits on how powerful it could be, except that this state doesn't know in advance which input you've got, right? It only knows the size of your input. You know, and that's bqp slash qpoly. So that's one that I just personally happen to love, okay? But, you know, if you're asking like, what's the, you know, there's a class that I think is way more beautiful than, you know, or fundamental than a lot of people, even within this field, realize that it is. That class is called SZK, or statistical zero knowledge. And, you know, there's a very, very easy way to define this class, which is to say, suppose that I have two algorithms that each sample from probability distributions, right? So each one just outputs random samples, according to, you know, possibly different distributions. And now the question I ask is, you know, let's say distributions over strings of n bits, you know, so over an exponentially large space. Now I ask, are these two distributions close or far as probability distributions? Okay, any problem that can be reduced to that, you know, that can be put into that form, is an SZK problem. And the way that this class was originally discovered was completely different from that, and was kind of more complicated. It was discovered as the class of all of the problems that have a certain kind of what's called zero knowledge proof. Zero knowledge proofs are one of the central ideas in cryptography. You know, Shafi Goldwasser and Silvio Michali won the Turing Award for, you know, inventing them. And they're at the core of even some cryptocurrencies that, you know, people use nowadays. But zero knowledge proofs are ways of proving to someone that something is true, like, you know, that there is a solution to this, you know, optimization problem, or that these two graphs are isomorphic to each other or something, but without revealing why it's true, without revealing anything about why it's true, okay? SZK is all of the problems for which there is such a proof that doesn't rely on any cryptography, okay? And if you wonder, like, how could such a thing possibly exist, right? Well, like, imagine that I had two graphs and I wanted to convince you that these two graphs are not isomorphic, meaning, you know, I cannot permute one of them so that it's the same as the other one, right? You know, that might be a very hard statement to prove. Like, I might need, you know, you might have to do a very exhaustive enumeration of, you know, all the different permutations before you were convinced that it was true. But what if there were some all-knowing wizard that said to you, look, I'll tell you what, just pick one of the graphs randomly, then randomly permute it, then send it to me, and I will tell you which graph you started with, okay? And I will do that every single time, right? And let's- And you load that in, okay, that's, I got it, I got it. Yeah, and let's say that that wizard did that 100 times and it was right every time, right? Now, if the graphs were isomorphic, then, you know, it would have been flipping a coin each time, right? It would have had only a one in two to the 100 power chance of, you know, of guessing right each time. But, you know, so if it's right every time, then now you're statistically convinced that these graphs are not isomorphic, even though you've learned nothing new about why they aren't. So fascinating. So yeah, so SDK is all of the problems that have protocols like that one, but it has this beautiful other characterization. It's shown up again and again in my own work and, you know, a lot of people's work. And I think that it really is one of the most fundamental classes. It's just that people didn't realize that when it was first discovered. So we're living in the middle of a pandemic currently. Yeah. How has your life been changed? Or no, better to ask, like, how has your perspective of the world changed with this world-changing event of a pandemic overtaking the entire world? Yeah, well, I mean, all of our lives have changed, you know, like, I guess as with no other event since I was born, you know, you would have to go back to World War II for something I think of this magnitude, you know, on, you know, the way that we live our lives. As for how it has changed my worldview, I think that the failure of institutions, you know, like the CDC, like, you know, other institutions that we sort of thought were trustworthy, like a lot of the media, was staggering, was absolutely breathtaking. It is something that I would not have predicted, right? I think I wrote on my blog that, you know, it's fascinating to like re-watch the movie, Contagion, from a decade ago, right? That correctly foresaw so many aspects of, you know, what was going on, you know, an airborne, you know, virus originates in China, spreads to, you know, much of the world, you know, shuts everything down until a vaccine can be developed. You know, everyone has to stay at home. You know, it gets, you know, an enormous number of things right, okay? But the one thing that they could not imagine, you know, is that like in this movie, everyone from the government is like hyper competent, hyper, you know, dedicated to the public good, right? And- The best of the best. You know, yeah, they're the best of the best. You know, they could, you know, and there are these conspiracy theorists, right? Who think, you know, you know, this is all fake news. There's no, there's not really a pandemic. And those are some random people on the internet who the hyper competent government people have to, you know, oppose, right? They, you know, in trying to envision the worst thing that could happen, like, you know, the, there was a failure of imagination. The movie makers did not imagine that the conspiracy theorists and the, you know, and the incompetence and the nutcases would have captured our institutions and be the ones actually running things. So you had a certain- Yeah. I love competence in all walks of life. I love, I get so much energy. I'm so excited by people who do amazing job. And I, like you, or maybe you can clarify, but I had maybe not intuition, but I hope that government at its best could be ultra competent. What, first of all, two questions, like how do you explain the lack of confidence and the other, maybe on the positive side, how can we build a more competent government? Well, there's an election in two months. I mean, you know- But you have a faith that the election process- You know, it's not gonna fix everything, but, you know, it's like, I feel like there is a ship that is sinking and you could at least stop the sinking. But, you know, I think that there are, there are much, much deeper problems. I mean, I think that, you know, it is plausible to me that, you know, a lot of the failures, you know, with the CDC, with some of the other health agencies, even, you know, predate Trump, you know, predate the, you know, right-wing populism that has sort of taken over much of the world now. And, you know, I think that, you know, it was, is, you know, it is very, I'm actually, you know, I've actually been strongly in favor of, you know, rushing vaccines of, you know, I thought that we could have done, you know, human challenge trials, you know, which were not done, right. We could have, you know, like had, you know, volunteers, you know, to actually, you know, be, you know, get vaccines, get, you know, exposed to COVID. So, you know, innovative ways of accelerating what we've done previously over a long amount of time. I thought that, you know, each month that a vaccine is closer is like trillions of dollars. Are you surprised how slow? And of course lives, you know, at least, you know, hundreds of thousands of lives. Are you surprised that it's taken this long? We still don't have a plan. There's still not a feeling like anyone is actually doing anything in terms of alleviate, like any kind of plan. So, there's a bunch of stuff. There's vaccine, but you could also do a testing infrastructure where everybody's tested nonstop with contact tracing, all that kind of. Well, I mean, I'm as surprised as almost everyone else. I mean, this is a historic failure. It is one of the biggest failures in the 240 year history of the United States, right? And we should be crystal clear about that. And, you know, one thing that I think has been missing, you know, even from the more competent side is like, you know, is sort of the World War II mentality, right? The, you know, the mentality of, you know, let's just, you know, if we can, by breaking a whole bunch of rules, you know, get a vaccine and, you know, in even half the amount of time as we thought, then let's just do that because, you know, you know, like we have to weigh all of the moral qualms that we have about doing that against the moral qualms of not doing it. And one key little aspect to that that's deeply important to me, and we'll go in that topic next, is the World War II mentality wasn't just about, you know, breaking all the rules to get the job done. There was a togetherness to it. There's a, so I would, if I were president right now, it seems quite elementary to unite the country because we're facing a crisis. It's easy to make the virus the enemy. And it's very surprising to me that the division has increased as opposed to decreased. That's heartbreaking. Yeah, well, look, I mean, it's been said by others that this is the first time in the country's history that we have a president who does not even pretend to want to unite the country, right? Yeah. Yeah, I mean, Lincoln, who fought a civil war, you know, said he wanted to unite the country, right? You know, and I do worry enormously about what happens if the results of this election are contested, you know? And, you know, will there be violence as a result of that? And will we have a clear path of succession? And, you know, look, I mean, you know, this is all, we're gonna find out the answers to this in two months. And if none of that happens, maybe I'll look foolish. But I am willing to go on the record and say, I am terrified about that. Yeah, I've been reading the rise and fall of the Third Reich. There's a, it's a difficult, so if I can, this is like one little voice to put out there that I think November will be a really critical month for people to breathe and put love out there. Do not, you know, anger in those, in that context, no matter who wins, no matter what is said, will destroy our country, may destroy our country, may destroy the world because of the power of the country. So it's really important to be patient, loving, empathetic. Like one of the things that troubles me is that even people on the left are unable to have a love and respect for people who voted for Trump. They can't imagine that there's good people that could vote for the opposite side. And that's- Oh, I know there are, because I know some of them, right? I mean, you know, it's still, you know, maybe it baffles me, but you know, I know such people. Let me ask you this. It's also heartbreaking to me on the topic of cancel culture. So in the machine learning community, I've seen it a little bit, that there's aggressive attacking of people who are trying to have a nuanced conversation about things. And it's troubling because it feels like nuanced conversation is the only way to talk about difficult topics. And when there's a thought police and speech police on any nuanced conversation that everybody has to, like in a animal farm chant that racism is bad and sexism is bad, which is things that everybody believes, and they can't possibly say anything nuanced. It feels like it goes against any kind of progress from my kind of shallow perspective. But you've written a little bit about cancel culture. Do you have thoughts that are interesting to say about this? Well, look, I mean, to say that I am opposed to, you know, this trend of cancellations or of, you know, shouting people down rather than engaging them, that would be a massive understatement, right? And I feel like, you know, I have put my money where my mouth is, you know, not as much as some people have, but, you know, I've tried to do something. I mean, I have defended, you know, some unpopular people and unpopular, you know, ideas on my blog. I've, you know, tried to defend, you know, norms of open discourse, of, you know, reasoning with our opponents even when I've been shouted down for that on social media, you know, called a racist, called a sexist, all of those things. Which, by the way, I should say, you know, I would be perfectly happy to, you know, say, you know, if we had time to say, you know, you know, 10,000 times, you know, my hatred of racism, of sexism, of homophobia, right? But what I don't wanna do is to cede to some particular political faction the right to define exactly what is meant by those terms. To say, well, then you have to agree with all of these other extremely contentious positions or else you are a misogynist or else you are a racist, right? I say that, well, no, you know, don't like, don't I or, you know, don't people like me also get a say in the discussion about, you know, what is racism, about what is gonna be the most effective to combat racism, right? And, you know, this cancellation mentality, I think is spectacularly ineffective at its own professed goal of, you know, combating racism and sexism. What's a positive way out? So I try to, I don't know if you see what I do on Twitter, but on Twitter, I mostly, in my life, I've actually, it's who I am to the core, is like, I really focus on the positive and I try to put love out there in the world. And still I get attacked. And I look at that and I wonder like- Oh, you too? I didn't know. Like I haven't actually said anything difficult and nuanced. You talk about somebody like Steven Pinker, who I actually don't know the full range of things that he's attacked for, but he tries to say difficult, he tries to be thoughtful about difficult topics. He does. And obviously he just gets slaughtered by- Well, I mean, yes, but it's also amazing how well Steve has withstood it. I mean, he just survived an attempt to cancel him just a couple of months ago, right? Psychologically, he survives it too, which worries me because I don't think I can. Yeah, I've gotten to know Steve a bit. He is incredibly unperturbed by this stuff. And I admire that and I envy it. I wish that I could be like that. I mean, my impulse when I'm getting attacked is I just want to engage every single anonymous person on Twitter and Reddit who is saying mean stuff about me. And I want to just say, well, look, can we just talk this over for an hour? And then you'll see that I'm not that bad. Sometimes that even works. The problem is then there's the 20,000 other ones. Yeah. Right? And that's not, but psychologically, does that wear on you? It does, it does. But yeah, I mean, in terms of what is the solution, I mean, I wish I knew, right? And so, in a certain way, these problems are maybe harder than P versus NP, right? I mean, but I think that part of it has to be for, I think that there's a lot of sort of silent support for what I'll call the open discourse side, the reasonable enlightenment side. And I think that that support has to become less silent. Right? I think that a lot of people, they sort of agree that a lot of these cancellations and attacks are ridiculous, but are just afraid to say so. Right? Or else they'll get shouted down as well. Right? That's just the standard witch hunt dynamic, which, of course, this faction understands and exploits to its great advantage. But more people just said, like, we're not going to stand for this. Right? Guess what? We're against racism too. But what you're doing is ridiculous. Right? And the hard part is it takes a lot of mental energy. It takes a lot of time. Even if you feel like you're not gonna be canceled or you're staying on the safe side, like, it takes a lot of time to phrase things in exactly the right way and to respond to everything people say. So, but I think that the more people speak up and from all political persuasions, from all walks of life, then the easier it is to move forward. Since we've been talking about love, can you, last time I talked to you about meaning of life a little bit, but here has, it's a weird question to ask a computer scientist, but has love for other human beings, for things, for the world around you played an important role in your life? Have you, you know, it's easy for a world-class computer scientist, you could even call yourself like a physicist, everything to be lost in the books. Is the connection to other humans, love for other humans played an important role? I love my kids. I love my wife. I love my parents. I am probably not different from most people in loving their families and in that being very important in my life. Now, I should remind you that, you know, I am a theoretical computer scientist. If you're looking for deep insight about the nature of love, you're probably looking in the wrong place to ask me, but sure, it's been important. But is there something from a computer science perspective to be said about love? Is there, or is that even beyond into the realm of, beyond the realm of consciousness? There was this great cartoon, I think it was one of the classic XKCDs, where it shows like a heart, and it's like, you know, squaring the heart, taking the Fourier transform of the heart, you know, integrating the heart, you know, you know, each thing, and then it says, you know, my normal approach is useless here. I'm so glad I asked this question. I think there's no better way to end this. I hope we get a chance to talk again. This has been amazing, cool experiment to do it outside. I'm really glad you made it out. Yeah, well, I appreciate it a lot. It's been a pleasure, and I'm glad you were able to come out to Austin. Thanks. Thanks for listening to this conversation with Scott Aronson, and thank you to our sponsors, 8sleep, SimpliSafe, ExpressVPN, and BetterHelp. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter, Alex Friedman. And now let me leave you with some words from Scott Aronson that I also gave to you in the introduction, which is, if you always win, then you're probably doing something wrong. Thank you for listening and for putting up with the intro and outro in this strange room in the middle of nowhere. And I very much hope to see you next time in many more ways than one.

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Jaron Lanier: Virtual Reality, Social Media & the Future of Humans and AI | Lex Fridman Podcast #218

The following is a conversation with Jaron Lanier, a computer scientist, visual artist, philosopher, writer, futurist, musician, and the founder of the field of virtual reality. To support this podcast, please check out our sponsors in the description. As a side note, you may know that Jaron is a staunch critic of social media platforms. Him and I agree on many aspects of this, except perhaps I am more optimistic about it being possible to build better platforms. And better artificial intelligence systems that put long-term interests and happiness of human beings first. Let me also say a general comment about these conversations. I try to make sure I prepare well, remove my ego from the picture, and focus on making the other person shine as we try to explore the most beautiful and insightful ideas in their mind. This can be challenging when the ideas that are close to my heart are being criticized. In those cases, I do offer a little pushback, but respectfully, and then move on, trying to have the other person come out looking wiser in the exchange. I think there's no such thing as winning in conversations, nor in life. My goal is to learn and to have fun. I ask that you don't see my approach to these conversations as weakness. It is not. It is my attempt at showing respect and love for the other person. That said, I also often just do a bad job of talking, but you probably already knew that. So please give me a pass on that as well. This is the Lex Friedman Podcast, and here is my conversation with Jaron Lanier. You're considered the founding father of virtual reality. Do you think we will one day spend most or all of our lives in virtual reality worlds? I have always found the very most valuable moment in virtual reality to be the moment when you take off the headset and your senses are refreshed and you perceive physicality afresh, as if you were a newborn baby, but with a little more experience. So you can really notice just how incredibly strange and delicate and peculiar and impossible the real world is. So the magic is and perhaps forever will be in the physical world. Well, that's my take on it. That's just me. I mean, I think I don't get to tell everybody else how to think or how to experience virtual reality, and at this point, there have been multiple generations of younger people who've come along and liberated me from having to worry about these things. But I should say also, even in what, well, I called it mixed reality, back in the day, and these days, it's called augmented reality, but with something like a HoloLens, even then, like one of my favorite things is to augment a forest, not because I think the forest needs augmentation, but when you look at the augmentation next to a real tree, the real tree just pops out as being astounding. You know, it's interactive, it's changing slightly all the time if you pay attention, and it's hard to pay attention to that, but when you compare it to a tree, all of a sudden, you do. And even in practical applications, my favorite early application of virtual reality, which we prototyped going back to the 80s when I was working with Dr. Joe Rosen at Stanford Med, near where we are now, we made the first surgical simulator, and to go from the fake anatomy of the simulation, which is incredibly valuable for many things, for designing procedures, for training, for all kinds of things, then to go to the real person, boy, it's really something. Like, surgeons really get woken up by that transition. It's very cool. So I think the transition is actually more valuable than the simulation. That's fascinating. I never really thought about that. It's almost, it's like traveling elsewhere in the physical space can help you appreciate how much you value your home once you return. Well, that's how I take it. I mean, once again, people have different attitudes towards it, all are welcome. What do you think is the difference between the virtual world and the physical meat space world that you are still drawn, for you personally, still drawn to the physical world? Like, there clearly then is a distinction. Is there some fundamental distinction, or is it the peculiarities of the current set of technology? In terms of the kind of virtual reality that we have now, it's made of software, and software is terrible stuff. Software is always the slave of its own history, its own legacy. It's always infinitely arbitrarily messy and arbitrary. Working with it brings out a certain kind of nerdy personality in people, or at least in me, which I'm not that fond of. And there are all kinds of things about software I don't like, and so that's different from the physical world. It's not something we understand, as you just pointed out. On the other hand, I'm a little mystified when people ask me, well, do you think the universe is a computer? And I have to say, well, I mean, what on earth could you possibly mean if you say it isn't a computer? If it isn't a computer, it wouldn't follow principles consistently, and it wouldn't be intelligible, because what else is a computer ultimately? And we have physics, we have technology, so we can do technology, so we can program it. So I mean, of course it's some kind of computer, but I think trying to understand it as a Turing machine is probably a foolish approach. Right, that's the question, whether it performs, this computer we call the universe, performs the kind of computation that can be modeled as a universal Turing machine, or is it something much more fancy, so fancy, in fact, that it may be beyond our cognitive capabilities to understand. Turing machines are kind of, I'd call them teases in a way, because if you have an infinitely smart programmer with an infinite amount of time, an infinite amount of memory, and an infinite clock speed, then they're universal. But that cannot exist, so they're not universal. And they actually are, in practice, a very particular sort of machine within the constraints, within the conservation principles of any reality that's worth being in probably. And so I think universality of a particular model is probably a deceptive way to think, even though at some sort of limit, of course, it's something like that's gotta be true at some sort of high enough limit, but it's just not accessible to us, so what's the point? Well, to me, the question of whether we're living inside a computer or a simulation is interesting in the following way. There's a technical question is here. How difficult is it to build a machine, not that simulates the universe, but that makes it sufficiently realistic that we wouldn't know the difference, or better yet, sufficiently realistic that we would kinda know the difference, but we would prefer to stay in the virtual world anyway. I wanna give you a few different answers. I wanna give you the one that I think has the most practical importance to human beings right now, which is that there's a kind of an assertion sort of built into the way the question's usually asked that I think is false, which is that suggestion that people have a fixed level of ability to perceive reality in a given way. And actually, people are always learning, evolving, forming themselves. We're fluid, too. We're also programmable, self-programmable, changing, adapting, and so my favorite way to get at this is to talk about the history of other media. So for instance, there was a peer-reviewed paper that showed that an early wire recorder playing back an opera singer behind a curtain was indistinguishable from a real opera singer. And so now, of course, to us, it would not only be distinguishable, but it would be very blatant because the recording would be horrible. But to the people at the time, without the experience of it, it seemed plausible. There was an early demonstration of extremely crude video teleconferencing between New York and DC in the early 20th century, in the 30s, I think so, that people viewed as being absolutely realistic and indistinguishable, which to us would be horrible. And there are many other examples. Another one, one of my favorite ones, is in the Civil War era, there were itinerant photographers who collected photographs of people who just looked kind of like a few archetypes. So you could buy a photo of somebody who looked kind of like your loved one to remind you of that person because actually photographing them was inconceivable and hiring a painter was too expensive and you didn't have any way for the painter to represent them remotely anyway. How would they even know what they looked like? So these are all great examples of how in the early days of different media, we perceived the media as being really great, but then we evolved through the experience of the media. This gets back to what I was saying. Maybe the greatest gift of photography is that we can see the flaws in a photograph and appreciate reality more. Maybe the greatest gift of audio recording is that we can distinguish that opera singer now from that recording of the opera singer on the horrible wire recorder. So we shouldn't limit ourselves by some assumption of stasis that's incorrect. So that's my first answer, which is I think the most important one. Now, of course, somebody might come back and say, oh, but technology can go so far. There must be some point at which it would surpass. That's a different question. I think that's also an interesting question, but I think the answer I just gave you is actually the more important answer to the more important question. That's profound, yeah. But can you, the second question, which you're now making me realize is way different. Is it possible to create worlds in which people would want to stay instead of the real world? Well. Like en masse, like large numbers of people. What I hope is, as I said before, I hope that the experience of virtual worlds helps people appreciate this physical world that we have and feel tender towards it and keep it from getting too fucked up. That's my hope. Do you see all technology in that way? So basically technology helps us appreciate the more sort of technology-free aspect of life. Well, media technology. You can stretch that. I mean, you can, let me say, I could definitely play McLuhan and turn this into a general theory. It's totally doable. The program you just described is totally doable. In fact, I will psychically predict that if you did the research, you could find 20 PhD theses that do that already. I don't know, but they might exist. But I don't know how much value there is in pushing a particular idea that far. Claiming that reality isn't a computer in some sense seems incoherent to me, because we can program it. We have technology. It seems to obey physical laws. What more do you want from it to be a computer? I mean, it's a computer of some kind. We don't know exactly what kind. We might not know how to think about it. We're working on it. Sorry to interrupt, but you're absolutely right. That's my fascination with the AI as well, is it helps, in the case of AI, I see it as a set of techniques that help us understand ourselves, understand us humans. In the same way, virtual reality, and you're putting it brilliantly, it's a way to help us understand reality. Sure. Appreciate and open our eyes more richly to reality. That's certainly how I see it. And I wish people who become incredibly fascinated, who go down the rabbit hole of the different fascinations with whether we're in a simulation or not, or there's a whole world of variations on that. I wish they'd step back and think about their own motivations and exactly what they mean. I think the danger with these things is, so if you say, is the universe some kind of computer broadly? It has to be, because it's not coherent to say that it isn't. On the other hand, to say that that means you know anything about what kind of computer, that's something very different. And the same thing is true for the brain. The same thing is true for anything where you might use computational metaphors. We have to have a bit of modesty about where we stand. And the problem I have with these framings of computation as these ultimate cosmic questions is that it has a way of getting people to pretend they know more than they do. Can you maybe, this is a therapy session, psychoanalyze me for a second. I really like the Elder Scrolls series. It's a role-playing game. Skyrim, for example. Why do I enjoy so deeply just walking around that world? And then there's people you could talk to, and you can just like, it's an escape, but my life is awesome. I'm truly happy. But I also am happy with the music that's playing in the mountains and carrying around a sword. And just that, I don't know what that is. It's very pleasant though to go there. And I miss it sometimes. I think it's wonderful to love artistic creations. It's wonderful to love contact with other people. It's wonderful to love play and ongoing, evolving meaning and patterns with other people. I think it's a good thing. I'm not like anti-tech, and I'm certainly not anti-digital tech. I'm anti, as everybody knows by now, I think the manipulative economy of social media is making everybody nuts and all that. So I'm anti that stuff. But the core of it, of course I worked for many, many years on trying to make that stuff happen because I think it can be beautiful. Like, why not? And by the way, there's a thing about humans, which is we're problematic. Any kind of social interaction with other people is gonna have its problems. People are political and tricky. And I love classical music, but when you actually go to a classical music thing and it turns out, oh, actually this is like a backroom power deal kind of place and a big status ritual as well. And that's kind of not as fun. That's part of the package. The thing is, it's always going to be, there's always gonna be a mix of things. I don't think the search for purity is gonna get you anywhere. So I'm not worried about that. I worry about the really bad cases where we're making ourselves crazy or cruel enough that we might not survive. And I think the social media criticism rises to that level. But I'm glad you enjoy it. I think it's great. And I like that you basically say that every experience is both beauty and darkness, as in with classical music. I also play classical piano, so I appreciate it very much. But it's interesting. I mean, every, and even the darkest, it's a man's search for meaning with Viktor Frankl in the concentration camps. Even there, there's opportunity to discover beauty. And so it's, that's the interesting thing about humans is the capacity to discover beautiful in the darkest of moments. But there's always the dark parts too. Well, I mean, it's, our situation is structurally difficult. We are- Yeah. Um. Structurally difficult. No, it is, it's true. We perceive socially, we depend on each other for our sense of place and perception of the world. I mean, we're dependent on each other. And yet, there's also a degree in which we're inevitably, we inevitably let each other down. We are set up to be competitive as well as supportive. I mean, it's just, our fundamental situation is complicated and challenging. And I wouldn't have it any other way. Okay, let's talk about one of the most challenging things. One of the things I unfortunately am very afraid of. Being human, allegedly. You wrote an essay on death and consciousness in which you write a note, certainly the fear of death has been one of the greatest driving forces in the history of thought and in the formation of the character of civilization. And yet it is under acknowledged. A great book on the subject, The Denial of Death by Ernest Becker deserves a reconsideration. I'm Russian, so I have to ask you this. I'm Russian, so I have to ask you about this. What's the role of death in life? See, you would have enjoyed coming to our house because my wife is Russian and we also have, we have a piano of such spectacular qualities you wouldn't, you would have freaked out. But anyway, we'll let all that go. So the context in which, I remember that essay sort of, this was from maybe the 90s or something. And I used to publish in a journal called the Journal of Consciousness Studies because I was interested in these endless debates about consciousness and science, which certainly continue today. And I was interested in how the fear of death and the denial of death played into different philosophical approaches to consciousness. Because I think on the one hand, the sort of sentimental school of dualism, meaning the feeling that there's something apart from the physical brain, some kind of soul or something else, is obviously motivated in a sense by a hope that whatever that is will survive death and continue. And that's a very core aspect of a lot of the world religions, not all of them, not really, but most of them. The thing I noticed is that the opposite of those, which might be the sort of hardcore, no, the brain's a computer and that's it, in a sense, we're motivated in the same way with a remarkably similar chain of arguments, which is, no, the brain's a computer and I'm gonna figure it out in my lifetime and upload myself and I'll live forever. Ha ha ha ha. Ha ha ha ha. That's interesting. Yeah, that's like the implied thought, right? Yeah, and so it's kind of this, in a funny way, it's the same thing. It's peculiar to notice that these people who would appear to be opposites in character and cultural references and their ideas actually are remarkably similar. And to an incredible degree, the sort of hardcore computationalist idea about the brain has turned into medieval Christianity. Like there's the people who are afraid that if you have the wrong thought, you'll piss off the super AIs of the future who will come back and zap you and all that stuff. It's really turned into medieval Christianity all over again. So the Ernest Becker's idea that death, the fear of death is the warm at the core, which is like, that's the core motivator of everything we see humans have created. The question is if that fear of mortality is somehow core, is like a prerequisite. So what you just, you just moved across this vast cultural chasm that separates me from most of my colleagues in a way, and I can't answer what you just said on the level without this huge deconstruction. Should I do it? Yes, what's the chasm? Okay. Let us travel across this vast chasm. Okay, I don't believe in AI. I don't think there's any AI. There's just algorithms, we make them, we control them. Now, they're tools, they're not creatures. Now, this is something that rubs a lot of people the wrong way, and don't I know it. When I was young, my main mentor was Marvin Minsky, who's the principal author of the computer as creature rhetoric that we still use. He was the first person to have the idea at all, but he certainly populated AI culture with most of its tropes, I would say, because a lot of the stuff people will say, oh, did you hear this new idea about AI? And I'm like, yeah, I heard it in 1978, sure. Yeah, I remember that. So Marvin was really the person, and Marvin and I used to argue all the time about this stuff because I always rejected it. And of all of his, I wasn't formally his student, but I worked for him as a researcher, but of all of his students and student-like people of his young adoptees, I think I was the one who argued with him about this stuff in particular, and he loved it. Yeah, I would have loved to hear that conversation. It was fun. Did you ever converse to a place? Oh, no, no. So the very last time I saw him, he was quite frail. And I was in Boston, and I was going to the old house in Brookline, his amazing house, and one of our mutual friends said, hey, listen, Marvin's so frail. Don't do the argument with him. Don't argue about AI. And so I said, but Marvin loves that. And so I showed up, and he was frail, and he looked up, and he said, are you ready to argue? He's such an amazing person. So it's hard to summarize this, because it's decades of stuff. The first thing to say is that nobody can claim absolute knowledge about whether somebody or something else is conscious or not. This is all a matter of faith. And in fact, I think the whole idea of faith needs to be updated, so it's not about God, but it's just about stuff in the universe. We have faith in each other being conscious. And then I used to frame this as a thing called the circle of empathy in my old papers. And then it turned into a thing for the animal rights movement, too. I noticed Peter Singer using it. I don't know if it was coincident, but anyway, there's this idea that you draw a circle around yourself, and the stuff inside is more like you, might be conscious, might be deserving of your empathy, of your consideration, and the stuff outside the circle isn't and outside the circle might be a rock, or I don't know. And that circle is unknowingly based on faith. Well, it's not only. Your faith in what is and what isn't. The thing about the circle is it can't be pure faith. It's also a pragmatic decision, and this is where things get complicated. If you try to make it too big, you suffer from incompetence. If you say, I don't wanna kill a bacteria, I will not brush my teeth, I don't know, what do you do? There's a competence question where you do have to draw the line. People who make it too small become cruel. People are so clannish and political and so worried about themselves ending up on the bottom of society that they are always ready to gang up on some designated group, and so there's always these people who are being tried, we're always trying to shove somebody out of the circle. And so. So aren't you shoving AI outside the circle? Well, give me a second. All right. So there's a pragmatic consideration here, and so the biggest questions are probably fetuses and animals lately, but AI is getting there. Now, with AI, I think, and I've had this discussion so many times, people would say, but aren't you afraid if you exclude AI, you'd be cruel to some consciousness? And then I would say, well, if you include AI, you make yourself, you exclude yourself from being able to be a good engineer or designer, and so you're facing incompetence immediately. So I really think we need to subordinate algorithms and be much more skeptical of them. Your intuition, you speak about this brilliantly with social media, how things can go wrong. Isn't it possible to design systems that show compassion, not to manipulate you, but give you control and make your life better if you so choose to? Like grow together with systems in the way we grow with dogs and cats, with pets, with significant others, in that way, that grow to become better people. I don't understand why that's fundamentally not possible. You're saying oftentimes you get into trouble by thinking you know what's good for people. Well, look, there's this question of what frame we're speaking in. Do you know who Alan Watts was? So Alan Watts once said, morality is like gravity, that in some absolute cosmic sense, there can't be morality because at some point it all becomes relative, and who are we anyway? Like morality is relative to us tiny creatures. But here on Earth, we're with each other, this is our frame, and morality is a very real thing. Same thing with gravity. At some point, you get into interstellar space and you might not feel much of it, but here we are on Earth. And I think in the same sense, I think this identification with a frame that's quite remote cannot be separated from a feeling of wanting to feel sort of separate from and superior to other people or something like that. There's an impulse behind it that I really have to reject. And we're just not competent yet to talk about these kinds of absolutes. Okay, so I agree with you that a lot of technologies sort of lack this basic respect, understanding, and love for humanity. There's a separation there. The thing I'd like to push back against, it's not that you disagree, but I believe you can create technologies and you can create a new kind of technologist, engineer, that does build systems that respect humanity, not just respect, but admire humanity, that have empathy for common humans, have compassion. It's not impossible. No, no, no. I think, yeah, I mean, I think musical instruments are a great example of that. Musical instruments are technologies that help people connect in fantastic ways. And that's a great example. My invention or design during the pandemic period was this thing called Together Mode, where people see themselves seated sort of in a classroom or a theater instead of in squares. And it allows them to semi-consciously perform to each other as if they have proper eye contact, as if they're paying attention to each other non-verbally. And weirdly, that turns out to work. And so it promotes empathy so far as I can tell. I hope it is of some use to somebody. The AI idea isn't really new. I would say it was born with Adam Smith's invisible hand, with this idea that we build this algorithmic thing and it gets a bit beyond us, and then we think it must be smarter than us. And the thing about the invisible hand is absolutely everybody has some line they draw where they say, nah, nah, nah, we're gonna take control of this thing. They might have different lines, they might care about different things, but everybody ultimately became a Keynesian because it just didn't work. It really wasn't that smart. It was sometimes smart and sometimes it failed. And so if you really, people who really, really, really wanna believe in the invisible hand as infinitely smart screw up their economies terribly. You have to recognize the economy as a subservient tool. Everybody does when it's to their advantage. They might not when it's not to their advantage. That's kind of an interesting game that happens. But the thing is, it's just like that with our algorithms. You can have a sort of a Chicago economic philosophy about your computer and say, no, no, no, my thing's come alive. It's smarter than anything. I think that there is a deep loneliness within all of us. This is what we seek. We seek love from each other. I think AI can help us connect deeper. This is what you criticize social media for. I think there's much better ways of doing social media that doesn't lead to manipulation. That instead leads to deeper connection between humans, leads to you becoming a better human being. And what that requires is some agency on the part of AI to be almost like a therapist, I mean, a companion. It's not telling you what's right. It's not guiding you as if it's an all-knowing thing. It's just another companion that you can leave at any time. You have complete transparency and control over. There's a lot of mechanisms that you can have that are counter to how current social media operates that I think is subservient to humans, or no, deeply respects human beings and is empathetic to their experience and all those kinds of things. I think it's possible to create AI systems like that. And I think they, I mean, that's a technical discussion of whether they need to have something that looks like more like AI versus algorithms, something that has an identity, something that has a personality, all those kinds of things. AI systems, and you've spoken extensively how AI systems manipulate you within social networks. And that's the biggest problem. Isn't necessarily that there's advertisement that social networks present you with advertisements that then get you to buy stuff, that then get you to buy stuff. That's not the biggest problem. The biggest problem is they then manipulate you. They alter your human nature to get you to buy stuff or to get you to do whatever the advertiser wants. Maybe you can correct me. Yeah, I don't see it quite that way, but we can work with that as an approximation. Sure, so my- I think the actual thing is even sort of more ridiculous and stupider than that, but that's okay. So my question is, let's not use the word AI, but how do we fix it? Oh, fixing social media. That diverts us into this whole other field in my view, which is economics, which I always thought was really boring, but we have no choice but to turn it to economists if we want to fix this problem, because it's all about incentives. But I've been around this thing since it started, and I've been in the meetings where the social media companies sell themselves to the people who put the most money into them, which are usually the big advertising holding companies and whatnot, and there's this idea that I think is kind of a fiction, and maybe it's even been recognized as that by everybody, that the algorithm will get really good at getting people to buy something, because I think people have looked at their returns and looked at what happens, and everybody recognizes it's not exactly right. It's more like a cognitive access blackmail payment at this point. Just to be connected, you're paying the money. It's not so much that the persuasion algorithms. So Stanford renamed its program, but it used to be called Engage Persuade. The Engage part works. The Persuade part is iffy, but the thing is that once people are engaged, in order for you to exist as a business, in order for you to be known at all, you have to put money into the- That's dark. It doesn't work, but they have to- But it's a giant cognitive access blackmail scheme at this point. Because the science behind the Persuade part, it's not entirely a failure, but it's not what... We play make-believe that it works more than it does. The damage doesn't come... Honestly, as I've said in my books, I'm not anti-advertising. I actually think advertising can be demeaning and annoying and banal and ridiculous and take up a lot of our time with stupid stuff. Like there's a lot of ways to criticize advertising that's accurate, and it can also lie and all kinds of things. However, if I look at the biggest picture, I think advertising, at least as it was understood before social media, helped bring people into modernity in a way that overall actually did benefit people overall. And you might say, am I contradicting myself because I was saying you shouldn't manipulate people? Yeah, I am probably here. I mean, I'm not pretending to have this perfect airtight worldview without some contradictions. I think there's a bit of a contradiction there. Well, looking at the long arc of history, advertisement has, in some parts, benefited society because it funded some efforts that perhaps- Yeah, I mean, I think there's a thing where sometimes I think it's actually been of some use. Now, where the damage comes is a different thing, though. Social media, algorithms on social media have to work on feedback loops where they present you with stimulus, they have to see if you respond to the stimulus. Now, the problem is that the measurement mechanism for telling if you respond in the engagement feedback loop is very, very crude. It's things like whether you click more or occasionally if you're staring at the screen more, if there's a forward-facing camera that's activated, but typically there isn't. So you have this incredibly crude back channel of information, and so it's crude enough that it only catches the more dramatic responses from you, and those are the fight-or-flight responses. Those are the things where you get scared or pissed off or aggressive or horny. These are these ancient, the sort of, what are sometimes called the lizard brain circuits or whatever, these fast-response, old, old, old evolutionary business circuits that we have that are helpful in survival once in a while, but are not us at our best. They're not who we wanna be, they're not how we relate to each other. They're this old business. So then just when you're engaged using those intrinsically, totally aside from whatever the topic is, you start to get incrementally, just a little bit, more paranoid, xenophobic, aggressive. You get a little stupid and you become a jerk. And it happens slowly. It's not like everybody's instantly transformed, but it does kinda happen progressively where people who get hooked kinda get drawn more and more into this pattern of being at their worst. Would you say that people are able to, when they get hooked in this way, look back at themselves from 30 days ago and say, I am less happy with who I am now, or I'm not happy with who I am now versus who I was 30 days ago. Are they able to self-reflect when you take yourself outside of the lizard brain? Sometimes. I wrote a book about people, suggesting people take a break from their social media to see what happens, and maybe even, actually, the title of the book was just arguments to delete your account. Yeah, 10 arguments. 10 arguments. Although I always said, I don't know that you should. I can give you the arguments, it's up to you. I'm always very clear about that. But I get, I don't have a social media account, obviously, and it's not that easy for people to reach me. They have to search out an old-fashioned email address on a super crappy, antiquated website. Like, it's actually a bit, I don't make it easy. And even with that, I get this huge flood of mail from people who say, oh, I quit my social media, I'm doing so much better, I can't believe how bad it was. But the thing is, what's, for me, a huge flood of mail would be an imperceptible trickle from the perspective of Facebook, right? And so, I think it's rare for somebody to look at themselves and say, oh boy, I sure screwed myself over. It's a really hard thing to ask of somebody. None of us find that easy, right? It's just hard. The reason I ask this is, is it possible to design social media systems that optimize for some longer-term metrics of you being happy with yourself, personal growth? Well, see, I don't think you should try to engineer personal growth or happiness. I think what you should do is design a system that's just respectful of the people and subordinates itself to the people and doesn't have perverse incentives, and then at least there's a chance of something decent happening. Like- You have to recommend stuff, right? So, you're saying, like, be respectful. What does that actually mean, engineering-wise? People, yeah, curation, people have to be responsible. Algorithms shouldn't be recommending. Algorithms don't understand enough to recommend. Algorithms are crap in this era. I mean, I'm sorry, they are. And I'm not saying this as somebody as a critic from the outside. I'm in the middle of it. I know what they can do, I know the math, I know what the corpora are. I know the best ones. Our office is funding GPT-3 and all these things that are at the edge of what's possible. And they do not have yet, I mean, it still is statistical emergent pseudo-semantics. It doesn't actually have deep representation emerging of anything. It's just not, like, I mean, that, I'm speaking the truth here and you know it. Well, let me push back on this. There's several truths here. So one, you're speaking to the way certain companies operate currently. I don't think it's outside the realm of what's technically feasible to do. There's just not incentive, like, companies are not, why fix this thing? I am aware that, for example, the YouTube search and discovery has been very helpful to me. And there's a huge number of, there's so many videos that it's nice to have a little bit of help. Have you done- But I'm still in control. Let me ask you something. Have you done the experiment of letting YouTube recommend videos to you, either starting from a absolutely anonymous, random place where it doesn't know who you are, or from knowing who you or somebody else is, and then going 15 or 20 hops? Have you ever done that and just let it go, top video recommend and then just go 20 hops? No, I have not. I've done that many times now. I have, because of how large YouTube is and how widely it's used, it's very hard to get to enough scale to get a statistically solid result on this. I've done it with high school kids, with dozens of kids doing it at a time. Every time I've done an experiment, the majority of times, after about 17 or 18 hops, you end up in really weird, paranoid, bizarre territory. Because ultimately, that is the stuff the algorithm rewards the most, because of the feedback crudeness I was just talking about. So, I'm not saying that the video never recommends something cool, I'm saying that its fundamental core is one that promotes a paranoid style, that promotes increasing irritability, that promotes xenophobia, promotes fear, anger, promotes selfishness, promotes separation between people. And I would, the thing is, it's very hard to do this work solidly. Many have repeated this experiment, and yet, it still is kind of anecdotal. I'd like to do a large citizen science thing sometime and do it, but then I think the problem with that is YouTube would detect it and then change it. Well, yes, I definitely, I love that kind of stuff in Twitter. So, Jack Dorsey has spoken about doing healthy conversations on Twitter, or optimizing for healthy conversations. What that requires within Twitter are most likely citizen experiments of what does healthy conversations actually look like, and how do you incentivize those healthy conversations? You're describing what often happens and what is currently happening. What I'd like to argue is it's possible to strive for healthy conversations, not in a dogmatic way of saying, I know what healthy conversations are, and I will tell you. I think one way to do this is to try to look around at social, maybe not things that are officially social media, but things where people are together online and see which ones have more healthy conversations, even if it's hard to be completely objective in that measurement, you can kind of, at least crudely, agree. You could do subjective annotation, like have a large crowd-sourced annotation. Yeah, one that I've been really interested in is GitHub, because it could change. I'm not saying it'll always be, but for the most part, GitHub has had a relatively quite low poison quotient, and I think there's a few things about GitHub that are interesting. One thing about it is that people have a stake in it. It's not just empty status games. There's actual code, or there's actual stuff being done, and I think as soon as you have a real-world stake in something, you have a motivation to not screw up that thing, and I think that that's often missing, that there's no incentive for the person to really preserve something if they get a little bit of attention from dumping on somebody's TikTok or something. They don't pay any price for it, but you have to kind of get decent with people when you have a shared stake, a little secret. So GitHub does a bit of that. GitHub is wonderful, yes, but I'm tempted to play the germ back at you, which is that GitHub is currently amazing, but the thing is, if you have a stake, then if it's a social media platform, they can use the fact that you have a stake to manipulate you because you wanna preserve the stake. So like, so like. Right, well, this is why, all right, this gets us into the economics. So there's this thing called data dignity that I've been studying for a long time. I wrote a book about, an earlier version of it, called Who Owns the Future? And the basic idea of it is that, once again, this is a 30-year conversation. It's a fascinating topic. Let me do the fastest version of this I can do. The fastest way I know how to do this is to compare two futures, all right? So future one is then the normative one, the one we're building right now, and future two is gonna be data dignity, okay? And I'm gonna use a particular population. I live on the Hill in Berkeley, and one of the features about the Hill is that as the climate changes, we might burn down, and I'll lose our houses or die or something. Like, it's dangerous, you know, and it didn't used to be. And so who keeps us alive? Well, the city does. The city does some things. The electric company, kind of, sort of, maybe, hopefully, better. Individual people who own property take care of their property. That's all nice, but there's this other middle layer, which is fascinating to me, which is that the groundskeepers who work up and down that Hill, many of whom are not legally here, many of whom don't speak English, cooperate with each other to make sure trees don't touch to transfer fire easily from lot to lot. They have this whole little web that's keeping us safe. I didn't know about this at first. I just started talking to them because they were out there during the pandemic, and so I'd try to just see who are these people? Who are these people who are keeping us alive? Now, I want to talk about the two different faiths for those people under Future One and Future Two. Future One, some weird, like, kindergarten paint job van with all these, like, cameras and weird things, drives up, observes what the gardeners and groundskeepers are doing. A few years later, some amazing robots that can shimmy up trees and all this show up, all those people are out of work, and there are these robots doing the thing, and the robots are good, and they can scale to more land, and they're actually good, but then there are all these people out of work, and these people have lost dignity, they don't know what they're gonna do, and then some people say, well, they go on basic income, whatever, they become wards of the state. My problem with that solution is every time in history that you've had some centralized thing that's doling out the benefits, that thing gets seized by people because it's too centralized and it gets seized. This happened to every communist experiment I can find. So I think that turns into a poor future that will be unstable. I don't think people will feel good in it. I think it'll be a political disaster with a sequence of people seizing this central source of the basic income. And you'll say, oh, no, an algorithm can do it. Then people will seize the algorithm. They'll seize control. Unless the algorithm is decentralized, and it's impossible to seize the control. Yeah, but- Very difficult. 60-something people own a quarter of all the Bitcoin. Like the things that we think are decentralized are not decentralized. So let's go to future two. Future two, the gardeners see that van with all the cameras and the kindergarten paint job, and they say, the groundskeepers, and they say, hey, the robots are coming. We're gonna form a data union. And amazingly, California has a little baby data union law emerging in the books. Yes. That's interesting. And so they say, we're gonna form a data union, and we're gonna, not only are we gonna sell our data to this place, but we're gonna make it better than it would have been if they were just grabbing it without our cooperation. And we're gonna improve it. We're gonna make the robots more effective. We're gonna make them better, and we're gonna be proud of it. We're gonna become a new class of experts that are respected. And then here's the interesting, there's two things that are different about that world from future one. One thing, of course, the people have more pride. They have more sense of ownership, of agency, but what the robots do changes. Instead of just like this functional, like we'll figure out how to keep the neighborhood from burning down, you have this whole creative community that wasn't there before thinking, well, how can we make these robots better so we can keep on earning money? There'll be waves of creative groundskeeping with spiral pumpkin patches and waves of cultural things. There'll be new ideas like, wow, I wonder if we could do something about climate change mitigation with how we do this. What about fresh water? Can we make the food healthier? What about, all of a sudden, there'll be this whole creative community on the case. And isn't it nicer to have a high-tech future with more creative classes than one with more dependent classes? Isn't that a better future? But future one and future two have the same robots and the same algorithms. There's no technological difference. There's only a human difference. And that's second future two, that's state of dignity. The economy that you're, I mean, the game theory here is on the humans, and then the technology is just the tools that enable the possibilities. I mean, I think you can believe in AI and be in future two. I just think it's a little harder. You have to do more contortions. It's possible. So in the case of social media, what does data dignity look like? Is it people getting paid for their data? Yeah, I think what should happen is in the future, there should be massive data unions for people putting content into the system. And those data unions should smooth out the results a little bit, so it's not winner-take-all. But at the same time, and people have to pay for it too. They have to pay for Facebook the way they pay for Netflix with an allowance for the poor. There has to be a way out too. But the thing is, people do pay for Netflix. It's a going concern. People pay for Xbox and PlayStation. There's enough people to pay for stuff they want. This could happen too. It's just that this precedent started that moved it in the wrong direction. And then what has to happen, the economy's a measuring device. If it's an honest measuring device, the outcomes for people form a normal distribution, a bell curve. And then so there should be a few people who do really well, a lot of people who do okay. And then we should have an expanding economy reflecting more and more creativity and expertise flowing through the network. And that expanding economy moves the result just a bit forward. So more people are getting money out of it than are putting money into it. So it gradually expands the economy and lifts all boats. And the society has to support the lower wing of the bell curve too, but not universal basic income. It has to be for the, because if it's an honest economy, there will be that lower wing and we have to support those people. There has to be a safety net. But see what I believe, I'm not gonna talk about AI, but I will say that I think there'll be more and more algorithms that are useful. And so I don't think everybody's gonna be supplying data to groundskeeping robots, nor do I think everybody's gonna make their living with TikTok videos. I think in both cases, there'll be a rather small contingent that do well enough at either of those things. But I think there might be many, many, many, many of those niches that start to evolve as there are more and more algorithms, more and more robots. And it's that large number that will create the economic potential for a very large part of society to become members of new creative classes. Do you think it's possible to create a social network that competes with Twitter and Facebook that's large and centralized in this way? Not centralized, sort of large, large. How do we get, all right, so I gotta tell you how to get from what I'm talking, how to get from where we are to anything kind of in the zone of what I'm talking about is challenging. I know some of the people who run, like I know Jack Dorsey, and I view Jack as somebody who's actually, I think he's really striving and searching and trying to find a way to make it better, but it's kind of like, it's very hard to do it while in flight, and he's under enormous business pressure too. So Jack Dorsey to me is a fascinating study because I think his mind is in a lot of good places. He's a good human being, but there's a big Titanic ship that's already moving in one direction. It's hard to know what to do with it. I think that's the story of Twitter. I think that's the story of Twitter. One of the things that I observe is that if you just wanna look at the human side, meaning like how are people being changed? How do they feel? What is the culture like? Almost all of the social media platforms that get big have an initial sort of honeymoon period where they're actually kind of sweet and cute. Like if you look at the early years of Twitter, it was really sweet and cute, but also look at Snap, TikTok. And then what happens is as they scale and the algorithms become more influential instead of just the early people, when it gets big enough that it's the algorithm running it, then you start to see the rise of the paranoid style, and then they start to get dark. And we've seen that shift in TikTok rather recently. But I feel like that scaling reveals the flaws within the incentives. I feel like I'm torturing you. I'm sorry. It's not torturing, no, because I have hope for the world with humans, and I have hope for a lot of things that humans create, including technology. And I just, I feel it is possible to create social media platforms that incentivize different things than the current. I think the current incentivization is around like the dumbest possible thing that was invented like 20 years ago, however long. And it just works, and so nobody's changing it. I just think that there could be a lot of innovation for more, see, you kind of push back this idea that we can't know what long-term growth or happiness is. If you give control to people to define what their long-term happiness and goals are, then that optimization can happen for each of those individual people. Well, I mean, imagine a future where probably a lot of people would love to make their living doing TikTok dance videos, but people recognize generally that's kind of hard to get into. Nonetheless, dance crews have an experience that's very similar to programmers working together on GitHub. So the future is like a cross between TikTok and GitHub, and they get together, and they have their, they have rights. They're negotiating, they're negotiating for returns. They join different artist societies in order to soften the blow of the randomness of who gets the network effect benefit, because nobody can know that. And I think an individual person might join 1,000 different data unions in the course of their lives, or maybe even 10,000. I don't know, but the point is that we'll have like these very hedged, distributed portfolios of different data unions we're part of, and some of them might just trickle in a little money for nonsense stuff where we're contributing to health studies or something. And, but I think people will find their way. They'll find their way to the right GitHub-like community in which they find their value in the context of supplying inputs and data and taste and correctives and all of this into the algorithms and the robots of the future. And that is a way to resist the lizard brain-based funding mechanisms. It's an alternate economic system that rewards productivity, creativity, value as perceived by others. It's a genuine market. It's not doled out from a center. There's not some communist person deciding who's valuable. It's actual market. And the money is made by supporting people and by supporting that instead of just grabbing people's attention in the cheapest possible way, which is definitely how you get the lizard brain. Yeah, okay. So we're finally at the agreement. But I just think that, so yeah, I'll tell you how I think to fix social media. There's a few things. So one, I think people should have complete control over their data and transparency of what that data is and how it's being used if they do hand over the control. Another thing they should be able to delete, walk away with their data at any moment, easy, like with a single click of a button, maybe two buttons. I don't know. Just easily walk away with their data. The other is control of the algorithm, individualized control of the algorithm for them. So each one has their own algorithm. Each person has their own algorithm. They get to be the decider of what they see in this world. And to me, that's, I guess, fundamentally decentralized in terms of the key decisions being made. But if that's made transparent, I feel like people will choose that system over Twitter of today, over Facebook of today, when they have the ability to walk away, to control their data and to control the kinds of things they see. Now, let's walk away from the term AI. You're right. In this case, you have full control of the algorithms that help you if you want to use their help, but you can also say F you to those algorithms and just consume the raw, beautiful waterfall of the internet. I think that, to me, that's not only fixes social media, but I think it would make a lot more money. So I would like to challenge the idea. I know you're not presenting that, but that the only way to make a ton of money is to operate like Facebook is. I think you can make more money by giving people control. Yeah, I mean, I certainly believe that. We're definitely in the territory of wholehearted agreement here. I do want to caution against one thing, which is making a future that benefits programmers versus people, like this idea that people are in control of their data. So years ago, I co-founded an advisory board for the EU with a guy named Giovanni Bottarelli who passed away, it's one of the reasons I wanted to mention it. A remarkable guy who'd been, he was originally a prosecutor who was throwing mafioso in jail in Sicily. So he was like this intense guy who was like, I've dealt with death threats, Mark Zuckerberg doesn't scare me, whatever. So we worked on this path of saying, let's make it all about transparency and consent. And it was one of the theaters that led to this huge data privacy and protection framework in Europe called the GDPR. And so therefore, we've been able to have empirical feedback on how that goes. And the problem is that most people actually get stymied by the complexity of that kind of management. They have trouble, and reasonably so. I don't, I'm like a techie, I can go in and I can figure out what's going on. But most people really do. And so there's the problem that it differentially benefits those who kind of have a technical mindset and can go in and sort of have a feeling for how this stuff works. I kind of still want to come back to incentives. And so if the incentive for whoever's, if the commercial incentive is to help the creative people of the future make more money because you get a cut of it, that's how you grow an economy. Not the programmers. Well, some of them will be programmers. It's not anti-programmer. I'm just saying that it's not only programmers. So yeah, you have to make sure the incentives are right. I mean, I like control is an interface problem to where you have to create something that's compelling to everybody, to the creatives, to the public. I mean, there's, I don't know, Creative Commons, like the licensing, there's a bunch of legal speak just in general, the whole legal profession. It's nice when it can be simplified in the way that you can truly simply understand. Everybody can simply understand the basics. In that same way, it should be very simple to understand how the data is being used and what data is being used for people. But then you're arguing that in order for that to happen, you have to have the incentives like the program. I mean, a lot of the reason that money works is actually information hiding and information loss. Like one of the things about money is a particular dollar you get might have passed through your enemy's hands and you don't know it. But also, I mean, this is what Adam Smith, if you wanna give the most charitable interpretation possible to the invisible hand, is what he was saying, is that like there's this whole complicated thing and not only do you not need to know about it, the truth is you'd never be able to follow it if you tried. And it's like, let the economic incentives solve for this whole thing. And that in a sense, every transaction is like a neuron in a neural net. If he'd had that metaphor, he would have used it and let the whole thing settle to a solution and don't worry about it. I think this idea of having incentives that reduce complexity for people can be made to work. And that's an example of an algorithm that could be manipulative or not, going back to your question before about can you do it in a way that's not manipulative. And I would say a GitHub-like, if you just have this vision, GitHub plus TikTok combined, is it possible? I think it is. I really think it is. I'm not gonna be able to unsee that idea of creatives on TikTok collaborating in the same way that people on GitHub collaborate. I like that kind of version. Why not? I like it, I love it. I just, like right now when people use, by the way, father of teenage daughter, so. It's all about TikTok, right? So, you know, when people use TikTok, there's a lot of, it's kind of funny, I was gonna say cattiness, but I was just using the cat as this exemplar of what we're talking about. I contradict myself, but anyway, there's all this cattiness where people are like, ee, this person, and I just, what about people getting together and kind of saying, okay, we're gonna work on this move, we're gonna get a better, can we get a better musician? And they do that, but that's the part that's kind of off the books right now. You know, that should be like right there. That should be the center. That's where the, that's the really best part. Well, that's where the invention of Git, period, the versioning is brilliant. And so some of the things you're talking about, technology, algorithms, tools can empower. And that's the thing for humans to connect, to collaborate, and so on. Can we upset more people a little bit? You already. Maybe, we'd have to try. No, no, can we, can I ask you to elaborate? Because my intuition was that you would be a supporter of something like cryptocurrency and Bitcoin because it is fundamentally emphasizes decentralization. What do you, so can you elaborate? Yeah, okay, look. Your thoughts on Bitcoin. It's kind of funny. I wrote, I've been advocating some kind of digital currency for a long time. And when the, when Bitcoin came out and the original paper on blockchain, my heart kind of sank because I thought, oh my God, we're applying all of this fancy thought and all these very careful distributed security measures to recreate the gold standard. Like it's just so retro, it's so dysfunctional. It's so useless from an economic point of view. So it's always, and then the other thing is using computational inefficiency at a boundless scale as your form of security is a crime against the atmosphere, obviously. A lot of people know that now, but we knew that at the start. Like the thing is when the first paper came out, I remember a lot of people saying, oh my God, this thing scales. It's a carbon disaster, you know? And I just like, I'm just mystified, but that's a different question than when you asked, can you have a cryptographic currency or at least some kind of digital currency that's of a benefit? And absolutely, like I'm, and there are people who are trying to be thoughtful about this. You should, if you haven't, you should interview Vitalik Buterin sometime. Yeah, I've interviewed him twice. Okay, so like there are people in the community who are trying to be thoughtful and trying to figure out how to do this better. It has nice properties though, right? So one of the nice properties is that like government centralized, it's hard to control. And then the other one, to fix some of the issues that you're referring to, I'm sort of playing devil's advocate here, is there's lightning network, there's ideas how you build stuff on top of Bitcoin, similar with gold, that allow you to have this kind of vibrant economy that operates not on the blockchain, but outside the blockchain, and uses Bitcoin for like checking the security of those transactions. So Bitcoin's not new, it's been around for a while. I've been watching it closely. I've not seen one example of it creating economic growth. There was this obsession with the idea that government was the problem. That idea that government's the problem, let's say government earned that wrath honestly, because if you look at some of the things that governments have done in recent decades, it's not a pretty story. Like after a very small number of people in the US government decided to bomb and landmine Southeast Asia, it's hard to come back and say, oh, government's this great thing. But then the problem is that this resistance to government is basically resistance to politics. It's a way of saying, if I can get rich, nobody should bother me. It's a way of not having obligations to others. And that ultimately is a very suspect motivation. But does that mean that the impulse that the government should not overreach its power is flawed? Well, I mean, what I wanna ask you to do is to replace the word government with politics. Like our politics is people having to deal with each other. My theory about freedom is that the only authentic form of freedom is perpetual annoyance, all right? So annoyance means you're actually dealing with people because people are annoying. Perpetual means that that annoyance is survivable, so it doesn't destroy us all. So if you have perpetual annoyance, then you have freedom. If you don't- And that's politics. That's politics. If you don't have perpetual annoyance, something's gone very wrong, and you've suppressed those people, and it's only temporary, it's gonna come back and be horrible. You should seek perpetual annoyance. I'll invite you to a Berkeley City Council meeting so you can know what that feels like, what perpetual annoyance feels like. But anyway, so freedom is being, the test of freedom is that you're annoyed by other people. If you're not, you're not free. If you're not, you're trapped in some temporary illusion that's gonna fall apart. Now, this quest to avoid government is really a quest to avoid that political feeling, but you have to have it, you have to deal with it. And it sucks, but that's the human situation, that's the human condition. And this idea that we're gonna have this abstract thing that protects us from having to deal with each other is always an illusion. The idea, and I apologize, I overstretched the use of the word government. The idea is there should be some punishment from the people when a bureaucracy, when a set of people or a particular leader, like in an authoritarian regime, which more than half the world currently lives under, if you, like if they become, they stop representing the people, it stops being like a Berkeley meeting and starts being more like a dictatorial kind of situation. And so the point is, it's nice to give people, the populace in a decentralized way, power to resist that kind of, like government becoming over authoritarian. Yeah, but people see this idea that the problem is always the government being powerful is false. The problem can also be criminal gangs. The problem can also be weird cults. The problem can be abusive clergy. The problem can be infrastructure that fails. The problem can be poisoned water. The problem can be failed electric grids. The problem can be a crappy education system that makes the whole society less and less able to create value. There are all these other problems that are different from an overbearing government. Like you have to keep some sense of perspective and not be obsessed with only one kind of problem because then the others will pop up. But empirically speaking, some problems are bigger than others. So like some, like groups of people, like governments or gangs or companies lead to problems. Are you a US citizen? Yes. Has the government ever really been a problem for you? Well, okay. So first of all, I grew up in the Soviet Union. Yeah, my wife did too. So I have seen, you know. Sure. And has the government bothered me? I would say that that's a really complicated question, especially because the United States is such, it's a special place. And like a lot of other countries. My wife's family were refuseniks. And so we have like a very, and her dad was sent to the Gulag. For what it's worth, on my father's side, all but a few were killed by a pogrom in a post-Soviet pogrom in Ukraine. So I- I would say, because you did a little trick of, eloquent trick of language that you switched to the United States to talk about government. So I believe, unlike my friend, Michael Malice, who's an anarchist, I believe government can do a lot of good in the world. That is exactly what you're saying, which is it's politics. The thing that Bitcoin folks and cryptocurrency folks argue is that one of the big ways that government can control the populace is centralized bank, like control the money. That was the case in the Soviet Union too. There's, inflation can really make poor people suffer. And so what they argue is, this is one way to go around that power that government has of controlling the monetary system. So that's a way to resist. That's not actually saying government bad. That's saying some of the ways that central banks get into trouble can be resisted through centralized- So let me ask you on balance today in the real world, in terms of actual facts, do you think cryptocurrencies are doing more to prop up corrupt, murderous, horrible regimes or to resist those regimes? Where do you think the balance is right now? I know exactly, having talked to a lot of cryptocurrency folks, what they would tell me, right? It's hard. I'm asking it as a real question. There's no way to know the answer perfectly. There's no way to know the answer perfectly. However, I gotta say, if you look at people who've been able to decode blockchains, and they do leak a lot of data, they're not as secure as is widely thought. There are a lot of unknown Bitcoin whales from pretty early and they're huge. And if you ask, who are these people? There's evidence that a lot of them are quite, not the people you'd wanna support, let's say. And I just don't, I think empirically this idea that there's some intrinsic way that bad governments will be disempowered and people will be able to resist them more than new villains or even villainous governments will be empowered. There's no basis for that assertion. It just is kind of circumstantial. And I think in general, Bitcoin ownership is one thing, but Bitcoin transactions have tended to support criminality more than productivity. Of course, they would argue that was the story of its early days, that now more and more Bitcoin is being used for legitimate transactions. But- That's a different, I didn't say for legitimate transactions. I said for economic growth, for creativity. I think what's happening is people are using it a little bit for buying, I don't know, maybe somebody's companies make it available for this and that, they buy a Tesla with it or something. Investing in a startup, hard, it might've happened a little bit, but it's not an engine of productivity, creativity, and economic growth. Whereas old-fashioned currency still is. And anyway, look, I think something, I'm pro the idea of digital currencies. I am anti the idea of economics wiping out politics as a result. I think they have to exist in some balance to avoid the worst dysfunctions of each. In some ways, there's parallels to our discussion of algorithms and cryptocurrency is you're pro the idea, but it can be used to manipulate, you can be used poorly by aforementioned humans. Well, I think that you can make better designs and worse designs. And I think, and you know, the thing about cryptocurrency that's so interesting is how many of us are responsible for the poor designs because we're all so hooked on that Horatio Alger story on like, I'm gonna be the one who gets the viral benefit. You know, way back when all this stuff was starting, I remember it would have been in the 80s, somebody had the idea of using viral as a metaphor for network effect. And the whole point was to talk about how bad network effect was, that it always created distortions that ruined the usefulness of economic incentives, that created dangerous distortions. Like, but then somehow, even after the pandemic, we think of viral as this good thing because we imagine ourselves as the virus, right? We wanna be on the beneficiary side of it. But of course, you're not likely to be. There is a sense because money is involved, people are not reasoning clearly always because they want to be part of that first viral wave that makes them rich. And that blinds people from their basic morality. I had an interesting conversation. I don't, I sort of feel like I should respect some people's privacy, but some of the initial people who started Bitcoin, I remember having an argument about like, it's intrinsically a Ponzi scheme. Like, you know, the early people have more than the later people. And the further down the chain you get, the more you're subject to gambling-like dynamics, where it's more and more random and more and more subject to weird network effects and whatnot, unless you're a very small player, perhaps, and you're just buying something. But even then you'll be subject to fluctuations because the whole thing is just kind of, like as it fluctuates, it's gonna wave around the little people more. And I remember the conversation turned to gambling because gambling is a pretty large economic sector. And it's always struck me as being non-productive. Like somebody goes to Las Vegas, they lose money. And so one argument is, well, they got entertainment. They paid for entertainment as they lost money. So that's fine. And Las Vegas does up the losing of money in an entertaining way, so why not? It's like going to a show. So that's one argument. The argument that was made to me was different from that. It's that, no, what they're doing is they're getting a chance to experience hope. And a lot of people don't get that chance. And so that's really worth it, even if they're gonna lose. They have that moment of hope, and they need to be able to experience that. And it's a very interesting argument. That's so heartbreaking, because I've seen it. But I've seen that. I have that a little bit of a sense. I've talked to some young people who invest in cryptocurrency. And what I see is this hope. This is the first thing they gave them, hope. And that's so heartbreaking to me, that you've gotten hope from, so much is invested. It's like hope from somehow becoming rich, as opposed to something, to me, I apologize, but money is in the long-term not going to be a source of that deep meaning. It's good to have enough money, but it should not be the source of hope. And it's heartbreaking to me, how many people it's the source of hope. Yeah. You've just described the psychology of virality, or the psychology of trying to base a civilization on semi-random occurrences of network effect peaks. And it doesn't really work. I mean, I think we need to get away from that. We need to soften those peaks. And accept Microsoft, which deserves every penny, but in every other case. Well, you mentioned GitHub. I think what Microsoft did with GitHub was brilliant. I was very happy. Okay, if I can give a, not a critical, but on Microsoft, because they recently purchased Bethesda, so Elder Scrolls is in their hands. I'm watching you, Microsoft, do not screw up my favorite game. So. Yeah, well, look, I'm not speaking for Microsoft, I have an explicit arrangement with them where I don't speak for them, obviously. Like, that should be very clear. I do not speak for them. I am not saying, I like them. I think Satya's amazing. The term data dignity was coined by Satya. Like, so, you know, we have, it's kind of extraordinary, but you know, Microsoft's this giant thing, it's gonna screw up this or that. You know, it's not, I don't know. It's kind of interesting, I've had a few occasions in my life to see how things work from the inside of some big thing. And you know, it's always just people kind of, it's, I don't know, there's always like, coordination problems, and there's always. There's always human problems. Oh my God. And there's some good people, there's some bad people, it's always. I hope Microsoft doesn't screw up your game. And I hope they bring Clippy back. You should never kill Clippy, bring Clippy back. Oh, Clippy, but Clippy promotes the mainstream. Clippy, but Clippy promotes the myth of AI. Well, that's why, this is why I think you're wrong. How about if we, all right, could we bring back Bob instead of Clippy? Which one was Bob? Oh, Bob was another thing. Bob was this other screen character who was supposed to be the voice of AI. Cortana, would Cortana do it for you? Cortana is too corporate. I like it, it's fine. There's a woman in Seattle who's like the model for Cortana, did Cortana's voice and was that. There was like, we had, we had her as a, she used to walk around if you were wearing HoloLens for a bit. I don't think that's happening anymore. I think, I don't think you should turn a software into a creature. I think, get a cat, just get a cat. You and I, well, get a dog, get a dog. Or a dog, yeah. Yeah, you're a. Or a hedgehog. A hedgehog. Yeah. You co-authored a paper, you mentioned Lee Smolin, titled The Autodidactic Universe, which describes our universe as one that learns its own physical laws. That's a trippy and beautiful and powerful idea. What are, what would you say are the key ideas in this paper? Okay, well, I should say, that paper reflected work from last year and the project, the program has moved quite a lot. So it's a little, there's a lot of stuff that's not published that I'm quite excited about. So I have to kind of keep my frame in that last year's thing. So I have to try to be a little careful about that. We can think about it in a few different ways. The core of the paper, the technical core of it, is a triple correspondence. One part of it was already established and then another part is in the process. The part that was established was, of course, understanding different theories of physics as matrix models. The part that was fresher is understanding those as machine learning systems, so that we could move fluidly between these different ways of describing systems. And the reason to wanna do that is to just have more tools and more options, because, well, theoretical physics is really hard and a lot of programs have kind of run into a state where they feel a little stalled, I guess. I wanna be delicate about this, because I'm not a physicist. I'm the computer scientist collaborating. So I don't mean to diss anybody. So this is almost like gives a framework for generating new ideas in physics. As we start to publish more about where it's gone, I think you'll start to see there's tools and ways of thinking about theories that I think open up some new paths that will be of interest. There's the technical core of it, which is this idea of a correspondence to give you more facility. But then there's also the storytelling part of it. And this is something Lee loves stories and I do. And the idea here is that a typical way of thinking about physics is that there's some kind of starting condition and then there's some principle by which the starting condition evolves. And the question is like, why the starting condition? Like how, oh, the starting condition has to get kind of, there's this, it has to be fine-tuned and all these things about it have to be kind of perfect. And so we were thinking, well, look, what if we could push the storytelling about where the universe comes from much further back by starting with really simple things that evolve and then through that evolution explain how things got to be how they are through very simple principles, right? And so we've been exploring a variety of ways to push the start of the storytelling further and further back, which, and it's an interesting, it's really kind of interesting because like for all of his, Lee is sometimes considered to be, to have a radical quality in the physics world, but he still is like, no, this is gonna be like the kind of time we're talking about in which evolution happens is the same time we're now, and we're talking about something that starts and continues. And I'm like, well, what if there's some other kind of time that's time-like and it sounds like metaphysics, but there's an ambiguity, you know, like it has to start from something and it's kind of an interesting, so there's this, a lot of the math can be thought of either way, which is kind of interesting. So push this so far back that basically all the things we take for granted in physics start becoming emergent. I really wanna emphasize this is all super baby steps. I don't wanna overclaim. It's like, I think a lot of the things we're doing, we're approaching some old problems in a pretty fresh way, informed. There's been a zillion papers about how you can think of the universe as a big neural net, or how you can think of different ideas in physics as being quite similar to, or even equivalent to some of the ideas in machine learning. And that actually works out crazy well. Like, I mean, that is actually kind of eerie when you look at it. Like there's probably two or three dozen papers that have this quality, and some of them are just crazy good. And it's very interesting. What we're trying to do is take those kinds of observations and turn them into an actionable framework where you can then start to do things with landscapes of theories that you couldn't do before, and that sort of thing. So in that context, or maybe beyond, how do you explain us humans? How unlikely are we, this intelligent civilization? Or is there a lot of others, or are we alone in this universe? Yeah. You seem to appreciate humans very much. Yeah. I've grown fond of us. We're okay. We have our nice qualities. I like that. I mean, we're kind of weird. We sprout this hair on our heads, and then we're, I don't know, we're sort of weird animals. That's the feature, not a bug, I think, the weirdness. I hope so. I hope so. I think if I'm just gonna answer you in terms of truth, the first thing I'd say is we're not in a privileged enough position, at least as yet, to really know much about who we are, how we are, what we're really like in the context of something larger, what that context is. Like all that stuff, we might learn more in the future. Our descendants might learn more, but we don't really know very much, which you can either view as frustrating or charming, like that first year of TikTok or something. All roads lead back to TikTok, I like it. Well, lately. But in terms of, there's another level at which I can think about it where I sometimes think that if you are just quiet and you do something that gets you in touch with the way reality happens, and for me it's playing music, sometimes it seems like you can feel a bit of how the universe is, and it feels like there's a lot more going on in it, and there is a lot more life and a lot more stuff happening and a lot more stuff flowing through it. I'm not speaking as a scientist now. This is kind of a more my artist side talking, and it's, I feel like I'm suddenly in multiple personalities with you. Well, Kerouac, Jack Kerouac said that music is the only truth. What do you, it sounds like you might be at least in part. There's a passage in Kerouac's book, Dr. Sax, where somebody tries to just explain the whole situation with reality and people in a paragraph, and I couldn't reproduce it for you here, but it's like, yeah, there are these bulbous things that walk around and they make these sounds, you can sort of understand them, but only kind of, and then there's like this, and it's just this amazing, just really quick, like if some spirit being or something was gonna show up in our reality and hadn't knew nothing about it, it's like a little basic intro of like, okay, here's what's going on here. An incredible passage. Yeah. Yeah. It's like a one or two sentence summary in Hitchhiker's Guide to the Galaxy, right, of what this. Mostly harmless. Mostly harmless. Yeah. Do you think there's truth to that, that music somehow connects to something that words cannot? Yeah, music is something that just towers above me. I don't, I don't, I don't feel like I have an overview of it, it's just the reverse. I don't fully understand it, because on one level it's simple, like you can say, oh, it's a thing people evolved to coordinate our brains on a pattern level or something like that. There's all these things you can say about music, which are, you know, some of that's probably true. It's also, there's kind of like this, this is the mystery of meaning. Like, there's a way that just, instead of just being pure abstraction, music can have like this kind of substantiality to it that is philosophically impossible. I don't know what to do with it. Yeah. The amount of understanding I feel I have when I hear the right song at the right time is not comparable to anything I can read on Wikipedia. Anything I can understand, read through in language. The music does connect us to something. There's this thing there, yeah. There's some kind of a thing in it. I've never ever, I've read across a lot of explanations from all kinds of interesting people, like that it's some kind of a flow language between people or between people and how they perceive and that kind of thing. And that sort of explanation is fine, but it's not quite it either. Yeah. There's something about music that makes me believe that panpsychism could possibly be true, which is that everything in the universe is conscious. It makes me think, or makes me be humble in how much or how little I understand about the functions of our universe, that everything might be cautious. Most people interested in theoretical physics eventually land in panpsychism, but I'm not one of them. I still think there's this pragmatic imperative to treat people as special, so I will proudly be a dualist. Without playing- People and cats, people and cats. Yeah, I'm not quite sure where to draw the line or why the line's there or anything like that, but I don't think I should be required to all the same questions are equally mysterious for no line, so I don't feel disadvantaged by that. So I shall remain a dualist, but if you listen to anyone trying to explain where consciousness is in a dualistic sense, either believing in souls or some special thing in the brain or something, you pretty much say, screw this, I'm gonna be a panpsychist. Ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha. Fair enough, well put. Is there moments in your life that happen that were defining in the way that you hope others, your daughters might have- I gotta say, the moments that defined me were not the good ones. The moments that defined me were often horrible. I've had successes, but if you ask what defined me, my mother's death, being under the World Trade Center and the attack, the things that have had an effect on me were the most real-world terrible things, which I don't wish on young people at all. And this is the thing that's hard about giving advice to young people, that they have to learn their own lessons and lessons don't come easily. And a world which avoids hard lessons will be a stupid world. And I don't know what to do with it. That's a little bundle of truth that has a bit of a fatalistic quality to it. This is like when I was saying that freedom equals eternal annoyance. There's a degree to which honest advice is not that pleasant to give. And I don't want young people to have to know about everything. I think they- You don't wanna wish hardship on them. Yeah, I think they deserve to have a little grace period of naivety that's pleasant. I mean, I do, if it's possible, if it's... Ah, these things are, this is tricky stuff. I mean, if you... Okay, so let me try a little bit on this advice thing. I think one thing, any serious broad advice will have been given a thousand times before for a thousand years. So I'm not going to claim originality. But I think trying to find a way to really pay attention to what you're feeling fundamentally, what your sense of the world is, what your intuition is, if you feel like an intuitive person, what your... Like to try to escape the constant sway of social perception or manipulation, whatever you wish. Not to escape it entirely, that would be horrible. But to find cover from it once in a while, to find a sense of being anchored in that, to believe in experience as a real thing. Believing in experience as a real thing is very dualistic. That goes with my philosophy of dualism. I believe there's something magical. And instead of squirting the magic dust on the programs, I think experience is something real and something apart, something mystical. Your own personal experience that you just have. And then you're saying, silence the rest of the world enough to hear that, like whatever that magic dust is in that experience. Find what is there. And I think that's one thing. Another thing is to recognize that kindness requires genius, that it's actually really hard. That facile kindness is not kindness. And that it'll take you a while to have the skills, to have kind impulses, to want to be kind, you can have right away. To be effectively kind is hard. To be effectively kind, yeah. It takes skill, it takes hard lessons. You'll never be perfect at it. To the degree you get anywhere with it, it's the most rewarding thing ever. Let's see, what else would I say? I would say when you're young, you can be very overwhelmed by social and interpersonal emotions. You'll have broken hearts and jealousies. You'll feel socially down the ladder instead of up the ladder. It feels horrible when that happens. All of these things. And you have to remember what a fragile crust all that stuff is. And it's hard, because right when it's happening, it's just so intense. And if I was actually giving this advice to my daughter, she'd already be out of the room. So this is for some hypothetical teenager that doesn't really exist, that really wants to sit and listen to my voice. For your daughter 10 years from now. Maybe. Can I ask you a difficult question? Yeah, sure. You talked about losing your mom. Yeah. Do you miss her? Yeah, I mean, I still connect to her through music. She was a young prodigy piano player in Vienna, and she survived the concentration camp and then died in a car accident here in the US. What music makes you think of her? Is there a song that connects you? Well, she was in Vienna, so she had the whole Viennese music thing going, which is this incredible school of absolute skill and romance bundled together and wonderful on the piano, especially. I learned to play some of the Beethoven sonatas for her, and I played them in this exaggerated drippy way. I remember when I was a kid. Exaggerated meaning too full of emotion? Yeah, like just like. Isn't that the only way to play Beethoven? I mean, I didn't know there's any other way. That's a reasonable question. I mean, the fashion these days is to be slightly Apollonian even with Beethoven, but one imagines that actual Beethoven playing might've been different. I don't know. I've gotten to play a few instruments he played and tried to see if I could feel anything about how it might've been for him. I don't know really. I was always against the clinical precision of classical music. I thought a great piano player should be like in pain, like emotionally, like truly feel the music and make it messy sort of. Sure. Maybe play classical music the way, I don't know, blues pianist plays blues. It seems like they actually got happier and I'm not sure if Beethoven got happier. I think it's a different kind of concept of the place of music. I think the blues, the whole African-American tradition was initially surviving awful, awful circumstances. You could say there was some of that in the concentration camps and all that too. And it's not that Beethoven's circumstances were brilliant, but he kind of also, I don't know, this is hard. Like, I mean, it would seem to be his misery was somewhat self-imposed maybe through, I don't know. It's kind of interesting. Like I've known some people who loathed Beethoven, like the composer, late composer Pauline Oliveros, wonderful modernist composer. I played in her band for a while and she was like, oh, Beethoven, that's the worst music ever. It's like all ego, it completely, it turns information, I mean, it turns emotion into your enemy. And it's ultimately all about your own self-importance, which has to be at the expense of others, what else could it be? And blah, blah, blah. So she had, I shouldn't say, I don't mean to be dismissive, but I'm just saying like her position on Beethoven was very negative and very unimpressed, which is really interesting for me. The man or the music? I think, I don't know. I mean, she's not here to speak for herself, so it's a little hard for me to answer that question. But it was interesting because I'd always thought of Beethoven as like, whoa, this is like, Beethoven is like really the dude, and she's like, ah, Beethoven, Schmadovan, it's like not really happening. Yeah, still, even though it's cliche, I like playing personally just for myself, Moonlight Sonata, I mean, I just. Moonlight's amazing, you know, I, you know, you're talking about comparing the blues and that sensibility from Europe is so different in so many ways. One of the musicians I play with is John Batiste, who has the band on Colbert's show, and he'll sit there playing jazz and suddenly go into Moonlight, he loves Moonlight. And what's kind of interesting is he's found a way to do Beethoven, and by the way, he can really do Beethoven. Like he went through Juilliard, and one time he was at my house, he was saying, hey, do you have the book of Beethoven's sonatas? I said, yeah, I want to find one I haven't played, and he sight-read through the whole damn thing perfectly. And I'm like, oh God, I just need to get out of here, I can't even deal with this. But anyway. Yeah. But anyway, the thing is, he has this way of with the same persona and the same philosophy moving from the blues into Beethoven that's really, really fascinating to me. It's like, I don't want to say he plays it as if it were jazz, but he kind of does. It's kind of really, and he talks, well, he was sight-reading, he talks like Beethoven's talking to him. Like he's like, oh yeah, here, he's doing this, I can't do John, but you know. It's like, it's really interesting, like it's very different. Like for me, I was introduced to Beethoven as like almost like this godlike figure, and I presume Pauline was too, that was really kind of oppressed but hard to deal with. And for him, it's just like- The conversation he's having. He's playing James P. Johnson or something. It's like another musician who did something and they're talking and it's very cool to be around. It's very kind of freeing to see someone have that relationship. I would love to hear him play Beethoven. That sounds amazing. He's great. We talked about Ernest Becker and how much value he puts on our mortality and our denial of our mortality. Do you think about your mortality? Do you think about your own death? You know, what's funny is I used to not be able to, but as you get older, you just know people who die and there's all these things and it just becomes familiar and more ordinary, which is what it is. But are you afraid? Sure, although less so. And it's not like I didn't have some kind of insight or revelation to become less afraid. I think I just, like I say, it's kind of familiarity. It's just knowing people who've died. And I really believe in the future. I have this optimism that people or this whole thing of life on earth, this whole thing we're part of, I don't know where to draw that circle, but this thing is going somewhere and has some kind of value. And you can't both believe in the future and wanna live forever. You have to make room for it. You know, like you have to, that optimism has to also come with its own humility. You have to make yourself small to believe in the future. And so it actually in a funny way comforts me. Wow, that's powerful. And optimism requires you to kind of step down after time. Yeah, I mean, that said, life seems kind of short, but you know, whatever. Do you think there's- I've tried to find, I can't find the complaint department. You know, I really wanna bring this up, but the customer service number never answers and like the email bounces. One way. So yeah. Do you think there's meaning to it, to life? Ah, well, see, meaning's a funny word. Like we say all these things as if we know what they mean, but meaning, we don't know what we mean when we say meaning. Like we obviously do not. And it's a funny little mystical thing. I think it ultimately connects to that sense of experience that dualists tend to believe in. Because there are why, like if you look up to the stars and you experience that awe-inspiring, like joy at whatever, when you look up to the stars, I don't know, like for me, that's kind of makes me feel joyful, maybe a little bit melancholy, just some weird soup of feelings. And ultimately the question is like, why are we here in this vast universe? That question, why? Have you been able in some way to connect or have you been able in some way, maybe through music, answer it for yourself? My impulse is to feel like it's not quite the right question to ask, but I feel like going down that path is just too tedious for the moment and I don't wanna do it, but. The wrong question. Well, just because, I don't know what meaning is. And I think, I do know that sense of awe. I grew up in Southern New Mexico and the stars were so vivid. I've had some weird misfortunes, but I've had some weird luck also. One of our near neighbors was the head of optics research at White Sands and when he was young, he discovered Pluto. His name was Clyde Tombaugh. And he taught me how to make telescopes, grinding mirrors and stuff. And my dad had also made telescopes when he was a kid, but Clyde had like backyard telescopes that would put to shame a lot of, I mean, he really, he did his telescopes, you know? And so I remember he'd let me go and play with them and just like looking at a globular cluster and you're seeing the actual photons and with a good telescope, it's really like this object. Like you can really tell this isn't coming through some intervening information structure. This is like the actual photons and it's really a three-dimensional object. And you have even a feeling for the vastness of it. And it's, I don't know. So I definitely, I was very, very fortunate to have a connection to the sky that way when I was a kid. To have had that experience, again, the emphasis on experience. It's kind of funny. Like I feel like sometimes, like I've taken, when she was younger, I took my daughter and her friends to like a telescope. There are a few around here that our kids can go and use and they would like look at Jupiter's moons or something. I think like Galilean moons. And I don't know if they quite had that because it's like too, it's been just too normalized. And I think maybe when I was growing up, screens weren't that common yet. And maybe it's like too confusable with the screen. I don't know. You know, somebody brought up in conversation to me somewhere, I don't remember who, but they kind of posited this idea that if humans, early humans weren't able to see the stars, like if earth atmosphere was such that it was cloudy, that we would not develop human civilization. There's something about being able to look up and see a vast universe is like, that's fundamental to the development of human civilization. I thought that was a curious kind of thought. That reminds me of that old Isaac Asimov story where there's this planet where they finally get to see what's in the sky once in a while. And it turns out they're in the middle of a globular cluster and there are all these stars. I forget what happens exactly. God, that's from when I was the same age as a kid. I don't really remember. Yeah. But yeah, I don't know. It might be right. I'm just thinking of all the civilizations that grew up under clouds. I mean, like the Vikings needed a special diffracting piece of mica to navigate because they could never see the sun. They had this thing called a sunstone that they found from this one cave. Do you know about that? So they were in this like, they were trying to navigate boats, you know, in the North Atlantic without being able to see the sun because it was cloudy. And so they used a chunk of mica to diffract it in order to be able to align where the sun really was because they couldn't tell by eye and navigate. So I'm just saying, there are a lot of civilizations that are pretty impressive that had to deal with a lot of clouds. The Amazonians invented our agriculture and they were probably under clouds a lot. I don't know. I don't know. To me personally, the question of the meaning of life becomes most vibrant, most apparent when you look up at the stars because it makes me feel very small. That we're not small. But then you ask, it still feels that we're special. And then the natural question is like, well, if we are as special as I think we are, why the heck are we here in this vast universe? That ultimately is the question of the meaning of life. I mean, look, there's a confusion sometimes in trying to set up a question or a thought experiment or something that's defined in terms of a context to explain something where there is no larger context. And that's a category error. If we want to do it in physics, or in computer science, it's hard to talk about the universe as a Turing machine because a Turing machine has an external clock and an observer and input and output. There's a larger context implied in order for it to be defined at all. And so if you're talking about the universe, you can't talk about it coherently as a Turing machine. Quantum mechanics is like that. Quantum mechanics has an external clock and has some kind of external context depending on your interpretation. That's either the observer or whatever. And they're similar that way. So maybe Turing machines and quantum mechanics can be better friends or something because they have a similar setup. But the thing is, if you have something that's defined in terms of an outer context, you can't talk about ultimates with it because obviously it's not suited for that. So there's some ideas that are their own context. General relativity is its own context. It's different. That's why it's hard to unify. And I think the same thing is true when we talk about these types of questions. Like meaning is in a context. And to talk about ultimate meaning is therefore a category error. It's not a resolvable way of thinking. It might be a way of thinking that is experientially or aesthetically valuable because it is awesome in the sense of awe-inspiring. But to try to treat it analytically is not sensible. Maybe that's what music and poetry are for. Yeah, maybe. I think so. I think music actually does escape any particular context. That's how it feels to me, but I'm not sure about that. That's once again, crazy artist talking, not scientist. Well, you do both masterfully, Jaron. And like I said, I'm a big fan of everything you've done, of you as a human being. I appreciate the fun argument we had today that will, I'm sure, continue for 30 years as it did with Mark Minsky. Honestly, I deeply appreciate that you spend your really valuable time with me today. It was a really great conversation. Thank you so much. Thanks for listening to this conversation with Jaron Lanier. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Jaron Lanier himself. A real friendship ought to introduce each person to unexpected weirdness in the other. Thank you for listening. I hope to see you next time.

https://youtu.be/Fx0G6DHMfXM

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Jeffrey Shainline: Neuromorphic Computing and Optoelectronic Intelligence | Lex Fridman Podcast #225

The following is a conversation with Jeff Shainlein, a scientist at NIST interested in optoelectronic intelligence. We have a deep technical dive into computing hardware that will make Jim Keller proud. I urge you to hop on to this rollercoaster ride through neuromorphic computing and superconducting electronics and hold on for dear life. Jeff is a great communicator of technical information. And so it was truly a pleasure to talk to him about some physics and engineering. To support this podcast, please check out our sponsors in the description. This is the Lex Friedman Podcast and here is my conversation with Jeff Shainlein. I got a chance to read a fascinating paper you authored called Optoelectronic Intelligence. So maybe we can start by talking about this paper and start with the basic questions. What is optoelectronic intelligence? Yeah, so in that paper, the concept I was trying to describe is sort of an architecture for building brain-inspired computing that leverages light for communication in conjunction with electronic circuits for computation. In that particular paper, a lot of the work we're doing right now in our project at NIST is focused on superconducting electronics for computation. I'll go into why that is, but that might make a little more sense in context if we first describe what that is in contrast to, which is semiconducting electronics. So is it worth taking a couple minutes to describe semiconducting electronics? It might even be worthwhile to step back and talk about electricity and circuits and how circuits work before we talk about superconductivity. Right, okay. How does a computer work, Jeff? Well, I won't go into everything that makes a computer work, but let's talk about the basic building blocks, a transistor, and even more basic than that, a semiconductor material, silicon, say. So in silicon, silicon is a semiconductor, and what that means is at low temperature, there are no free charges, no free electrons that can move around. So when you talk about electricity, you're talking about predominantly electrons moving to establish electrical currents and they move under the influence of voltages. So you apply voltages, electrons move around, those can be measured as currents, and you can represent information in that way. So semiconductors are special in the sense that they are really malleable. So if you have a semiconductor material, you can change the number of free electrons that can move around by putting different elements, different atoms in lattice sites. So what is a lattice site? Well, a semiconductor is a crystal, which means all the atoms that comprise the material are at exact locations that are perfectly periodic in space. So if you started any one atom and you go along what are called the lattice vectors, you get to another atom and another atom and another atom, and for high quality devices, it's important that is a perfect crystal with very few defects, but you can intentionally replace a silicon atom with say a phosphorus atom, and then you can change the number of free electrons that are in a region of space that has that excess of what are called dopants. So picture a device that has a left terminal and a right terminal, and if you apply a voltage between those two, you can cause electrical current to flow between them. Now we add a third terminal up on top there, and depending on the voltage between the left and right terminal and that third voltage, you can change that current. So what's commonly done in digital electronic circuits is to leave a fixed voltage from left to right, and then change that voltage that's applied at what's called the gate, the gate of the transistor. So what you do is you make it to where there's an excess of electrons on the left, excess of electrons on the right, and very few electrons in the middle, and you do this by changing the concentration of different dopants in the lattice spatially. And then when you apply a voltage to that gate, you can either cause current to flow or turn it off. And so that's sort of your zero and one. If you apply voltage, current can flow, that current is representing a digital one, and from that, from that basic element, you can build up all the complexity of digital electronic circuits that have really had a profound influence on our society. Now you're talking about electrons. Can you give a sense of what scale we're talking about when we're talking about in silicon being able to mass manufacture these kinds of gates? Yeah, so scale in a number of different senses. Well, at the scale of the silicon lattice, the distance between two atoms there is half a nanometer. So people often like to compare these things to the width of a human hair. I think it's some six orders of magnitude smaller than the width of a human hair, something on that order. So remarkably small, we're talking about individual atoms here, and electrons are of that length scale when they're in that environment. But there's another sense that scale matters in digital electronics. This is perhaps the more important sense, although they're related. Scale refers to a number of things. It refers to the size of that transistor. So for example, I said you have a left contact, a right contact, and some space between them where the gate electrode sits. That's called the channel width or the channel length. And what has enabled what we think of as Moore's law or the continued increased performance in silicon microelectronic circuits is the ability to make that size, that feature size ever smaller, ever smaller at a really remarkable pace. I mean, that feature size has decreased consistently every couple of years since the 1960s. And that was what Moore predicted in the 1960s. He thought it would continue for at least two more decades, and it's been much longer than that. And so that is why we've been able to fit ever more devices, ever more transistors, ever more computational power on essentially the same size of chip. So a user sits back and does essentially nothing. You're running the same computer program, but those devices are getting smaller, so they get faster, they get more energy efficient, and all of our computing performance just continues to improve. And we don't have to think too hard about what we're doing as, say, a software designer or something like that. I absolutely don't mean to say that there's no innovation in software or the user side of things. Of course there is, but from the hardware perspective, we just have been given this gift of continued performance improvement through this scaling that is ever smaller feature sizes with very similar, say, power consumption. That power consumption has not continued to scale in the most recent decades, but nevertheless, we had a really good run there for a while and now we're down to gates that are seven nanometers, which is state of the art right now. Maybe Global Foundries is trying to push it even lower than that. I can't keep up with where the predictions are that it's gonna end, but seven nanometer transistor has just a few tens of atoms along the length of the conduction pathway. So a naive semiconductor device physicist would think you can't go much further than that without some kind of revolution in the way we think about the physics of our devices. Is there something to be said about the mass manufacture of these devices? Right, right, so that's another thing. So how have we been able to make those transistors smaller and smaller? Well, companies like Intel, Global Foundries, they invest a lot of money in the lithography. So how are these chips actually made? Well, one of the most important steps is this what's called ion implantation. So you start with sort of a pristine silicon crystal and then using photolithography, which is a technique where you can pattern different shapes using light, you can define which regions of space you're going to implant with different species of ions that are going to change the local electrical properties right there. So by using ever shorter wavelengths of light and different kinds of optical techniques and different kinds of lithographic techniques, things that go far beyond my knowledge base, you can just simply shrink that feature size down. And you say you're at seven nanometers. Well, the wavelength of light that's being used is over a hundred nanometers. That's already deep in the UV. So how are those minute features patterned? Well, there's an extraordinary amount of innovation that has gone into that, but nevertheless, it stayed very consistent in this ever shrinking feature size. And now the question is, can you make it smaller? And even if you do, do you still continue to get performance improvements? But that's another kind of scaling where these companies have been able to... So, okay, you picture a chip that has a processor on it. Well, that chip is not made as a chip. It's made on a wafer. And using photolithography, you basically print the same pattern on different dyes all across the wafer, multiple layers, tens, probably a hundred some layers in a mature foundry process. And you do this on ever bigger wafers too. That's another aspect of scaling that's occurred in the last several decades. So now you have this 300 millimeter wafer. It's like as big as a pizza and it has maybe a thousand processors on it. And then you dice that up using a saw. And now you can sell these things so cheap because the manufacturing process was so streamlined. I think a technology as revolutionary as silicon microelectronics has to have that kind of manufacturing scalability, which I will just emphasize, I believe is enabled by physics. It's not, I mean, of course there's human ingenuity that goes into it, but at least from my side, where I sit, it sure looks like the physics of our universe allows us to produce that. And we've discovered how more so than we've invented it, although of course we have invented it, humans have invented it, but it's almost as if it was there waiting for us to discover it. You mean the entirety of it, or are you specifically talking about the techniques of photolithography, like the optics involved? I mean, the entirety of the scaling down to the seven nanometers, you're able to have electrons not interfere with each other in such a way that you could still have gates. Like that's enabled to achieve that scale, spatial and temporal, seems to be very special and is enabled by the physics of our world. All of the things you just said. So starting with the silicon material itself, silicon is a unique semiconductor. It has essentially ideal properties for making a specific kind of transistor that's extraordinarily useful. So I mentioned that silicon has, well, when you make a transistor, you have this gate contact that sits on top of the conduction channel and depending on the voltage you apply there, you pull more carriers into the conduction channel or push them away so it becomes more or less conductive. In order to have that work without just sucking those carriers right into that contact, you need a very thin insulator. And part of scaling has been to gradually decrease the thickness of that gate insulator so that you can use a roughly similar voltage and still have the same current voltage characteristics. So the material that's used to do that, or I should say was initially used to do that, was silicon dioxide, which just naturally grows on the silicon surface. So you expose silicon to the atmosphere that we breathe and well, if you're manufacturing, you're gonna purify these gases, but nevertheless, that what's called a native oxide will grow there. There are essentially no other materials on the entire periodic table that have as good of a gate insulator as that silicon dioxide. And that has to do with nothing but the physics of the interaction between silicon and oxygen. And if it wasn't that way, transistors could not, they could not perform in nearly the degree of capability that they have. And that has to do with the way that the oxide grows, the reduced density of defects there, it's insulation, meaning essentially it's energy gaps. You can apply a very large voltage there without having current leak through it. So that's physics right there. There are other things too. Silicon is a semiconductor in an elemental sense. You only need silicon atoms. A lot of other semiconductors, you need two different kinds of atoms, like a compound from group three and a compound from group five. That opens you up to lots of defects that can occur where one atom's not sitting quite at the lattice site it is and it's switched with another one that degrades performance. But then also on the side that you mentioned with the manufacturing, we have access to light sources that can produce these very short wavelengths of light. How does photolithography occur? Well, you actually put this polymer on top of your wafer and you expose it to light. And then you use a aqueous chemical processing to dissolve away the regions that were exposed to light and leave the regions that were not. And we are blessed with these polymers that have the right property where they can cause scission events where the polymer splits where a photon hits. I mean, maybe that's not too surprising, but I don't know. It all comes together to have this really complex manufacturable ecosystem where very sophisticated technologies can be devised and it works quite well. And amazingly, like you said, with a wavelength at like 100 nanometers or something like that, you're still able to achieve on this polymer precision of whatever we said, seven nanometers. I think I've heard like four nanometers being talked about, something like that. If we could just pause on this and we'll return to superconductivity, but in this whole journey from a history perspective, what do you think is the most beautiful at the intersection of engineering and physics to you in this whole process that we talked about with silicon and photolithography, things that people were able to achieve in order to push the Moore's law forward? Is it the early days, the invention of the transistor itself? Is it some particular cool little thing that maybe not many people know about? Like, what do you think is the most beautiful in this whole process journey? The most beautiful is a little difficult to answer. Let me try and sidestep it a little bit and just say what strikes me about looking at the history of silicon microelectronics is that, so when quantum mechanics was developed, people quickly began applying it to semiconductors and it was broadly understood that these are fascinating systems and people cared about them for their basic physics, but also their utility as devices. And then the transistor was invented in the late 40s in a relatively crude experimental setup where you just crammed a metal electrode into the semiconductor and that was ingenious. These people were able to make it work, you know? But so what I wanna get to that really strikes me is that in those early days, there were a number of different semiconductors that were being considered. They had different properties, different strengths, different weaknesses. Most people thought germanium was the way to go. It had some nice properties related to things about how the electrons move inside the lattice, but other people thought that compound semiconductors with group three and group five also had really, really extraordinary properties that might be conducive to making the best devices. So there were different groups exploring each of these and that's great, that's how science works. You have to cast a broad net. But then what I find striking is why is it that silicon won? Because it's not that germanium is a useless material and it's not present in technology or compound semiconductors. They're both doing exciting and important things, slightly more niche applications, whereas silicon is the semiconductor material for microelectronics, which is the platform for digital computing, which has transformed our world. Why did silicon win? It's because of a remarkable assemblage of qualities that no one of them was the clear winner, but it made these sort of compromises between a number of different influences. It had that really excellent gate oxide that allowed us to make MOSFETs, these high-performance transistors, so quickly and cheaply and easily without having to do a lot of materials development. The band gap of silicon is actually, so in a semiconductor, there's an important parameter, which is called the band gap, which tells you if you, there are sort of electrons that fill up to one level in the energy diagram, and then there's a gap where electrons aren't allowed to have an energy in a certain range, and then there's another energy level above that. And that difference between the lower sort of filled level and the unoccupied level, that tells you how much voltage you have to apply in order to induce a current to flow. So with germanium, that's about 0.75 electron volts. That means you have to apply 0.75 volts to get a current moving. And it turns out that if you compare that to the thermal excitations that are induced just by the temperature of our environment, that gap's not quite big enough. You start to use it to perform computations, it gets a little hot, and you get all these accidental carriers that are excited into the conduction band, and it causes errors in your computation. Silicon's band gap is just a little higher, 1.1 electron volts, but you have an exponential dependence on the number of carriers that are present that can induce those errors. It decays exponentially with that voltage. So just that slight extra energy in that band gap really puts it in an ideal position to be operated in the conditions of our ambient environment. It's kind of fascinating that, so like you mentioned, errors decrease exponentially with the voltage. So it's funny, because this error thing comes up when you start talking about quantum computing. And it's kind of amazing that everything we've been talking about, the errors as we scale down, seems to be extremely low. Yes. And all of our computation is based on the assumption that it's extremely low. Yes, well, it's digital computation. Digital, sorry, digital computation. So as opposed to our biological computation, our brain is like, the assumption is stuff is gonna fail all over the place, and we somehow have to still be robust to that. That's exactly right. So this also, this is gonna be the most controversial part of our conversation, where you're gonna make some enemies. So let me ask, because we've been talking about physics and engineering. Which group of people is smarter and more important for this one? Let me ask the question in a better way. Some of the big innovations, some of the beautiful things that we've been talking about, how much of it is physics? How much of it is engineering? My dad is a physicist, and he talks down to all the amazing engineering that we're doing in the artificial intelligence, and the computer science, and the robotics, and all that space. So we argue about this all the time. So what do you think? Who gets more credit? I'm genuinely not trying to just be politically correct here. I don't see how you would have any of the, what we consider sort of the great accomplishments of society without both. You absolutely need both of those things. Physics tends to play a key role earlier in the development, and then engineering, optimization, these things take over. And I mean, the invention of the transistor, or actually even before that, the understanding of semiconductor physics that allowed the invention of the transistor, that's all physics. So if you didn't have that physics, you don't even get to get on the field. But once you have understood and demonstrated that this is in principle possible, more so as engineering, why we have computers more powerful than old supercomputers in each of our phones, that's all engineering. And I think I would be quite foolish to say that, that's not valuable, that's not a great contribution. It's a beautiful dance. Would you put like silicon, the understanding of the material properties in the space of engineering? Like how does that whole process work to understand that it has all these nice properties, or even the development of photolithography? Is that basically, would you put that in a category of engineering? No, I would say that it is basic physics, it is applied physics, it's material science, it's x-ray crystallography, it's polymer chemistry, it's everything. I mean. Chemistry even is thrown in there? Absolutely, yes. Yes, absolutely. Just no biology. Okay, we can get to biology. Well, the biology is in the humans that are engineering the system, so it's all integrated deeply. Okay, so let's return, you mentioned this word superconductivity. So what does that have to do with what we're talking about? Right, okay, so in a semiconductor, as I tried to describe a second ago, you can sort of induce currents by applying voltages, and those have sort of typical properties that you would expect from some kind of a conductor. Those electrons, they don't just flow perfectly without dissipation. If an electron collides with an imperfection in the lattice or another electron, it's gonna slow down, it's gonna lose its momentum. So you have to keep applying that voltage in order to keep the current flowing. In a superconductor, something different happens. If you get a current to start flowing, it will continue to flow indefinitely. There's no dissipation. So that's crazy. How does that happen? Well, it happens at low temperature, and this is crucial. It has to be a quite low temperature, and what I'm talking about there, for essentially all of our conversation, I'm gonna be talking about conventional superconductors, sometimes called low TC superconductors, low critical temperature superconductors. And so those materials have to be at a temperature around, say around four Kelvin. I mean, their critical temperature might be 10 Kelvin, something like that, but you wanna operate them at around four Kelvin, four degrees above absolute zero. And what happens at that temperature, at very low temperatures in certain materials, is that the noise of atoms moving around, the lattice vibrating, electrons colliding with each other, that becomes sufficiently low that the electrons can settle into this very special state. It's sometimes referred to as a macroscopic quantum state, because if I had a piece of superconducting material here, let's say niobium is a very typical superconductor. If I had a block of niobium here, and we cooled it below its critical temperature, all of the electrons in that superconducting state would be in one coherent quantum state. The wave function of that state is described in terms of all of the particles simultaneously, but it extends across macroscopic dimensions, the size of whatever material, the size of whatever block of that material I have sitting here. And the way this occurs is that, let's try to be a little bit light on the technical details, but essentially the electrons coordinate with each other. They are able to, in this macroscopic quantum state, they're able to sort of, one can quickly take the place of the other. You can't tell electrons apart, they're what's known as identical particles. So if this electron runs into a defect that would otherwise cause it to scatter, it can just sort of almost miraculously avoid that defect, because it's not really in that location, it's part of a macroscopic quantum state and the entire quantum state was not scattered by that defect. So you can get a current that flows without dissipation, and that's called a super current. That's sort of just very much scratching the surface of superconductivity. There's very deep and rich physics there, just probably not the main subject we need to go into right now, but it turns out that when you have this material, you can do usual things like make wires out of it, so you can get current to flow in a straight line on a chip, but you can also make other devices that perform different kinds of operations. Some of them are kind of logic operations, like you'd get in a transistor. The most common or most, I would say, diverse in its utility component is a Josephson junction. It's not analogous to a transistor in the sense that if you apply a voltage here, it changes how much current flows from left to right, but it is analogous in sort of a sense of, it's the go-to component that a circuit engineer is going to use to start to build up more complexity. So these junctions serve as gates. They can serve as gates. So I'm not sure how concerned to be with semantics, but let me just briefly say what a Josephson junction is, and we can talk about different ways that they can be used. Basically, if you have a superconducting wire and then a small gap of a different material that's not superconducting, an insulator or normal metal, and then another superconducting wire on the other side, that's a Josephson junction. So it's sometimes referred to as a superconducting weak link. So you have this superconducting state on one side and on the other side, and the superconducting wave function actually tunnels across that gap. And when you create such a physical entity, it has very unusual current voltage characteristics. Within that gap, like weird stuff happens. Through the entire circuit. So you can imagine, suppose you had a loop setup that had one of those weak links in the loop. Current would flow in that loop, independent, even if you hadn't applied a voltage to it, and that's called the Josephson effect. So the fact that there's this phase difference in the quantum wave function from one side of the tunneling barrier to the other induces current to flow. So how does he change state? Right, exactly. So how do you change state? Now picture if I have a current bias coming down this line of my circuit, and there's a Josephson junction right in the middle of it. And now I make another wire that goes around the Josephson junction. So I have a loop here, a superconducting loop. I can add current to that loop by exceeding the critical current of that Josephson junction. So like any superconducting material, it can carry this super current that I've described, this current that can propagate without dissipation up to a certain level. And if you try and pass more current than that through the material, it's going to become a resistive material, a normal material. So in the Josephson junction, the same thing happens. I can bias it above its critical current. And then what it's gonna do, it's going to add a quantized amount of current into that loop. And what I mean by quantized is, it's going to come in discrete packets with a well-defined value of current. So in the vernacular of some people working in this community, you would say you pop a flux on into the loop. So a flux on- You pop a flux on into the loop. Yeah, so a flux on- Sounds like skateboarder talk, I love it. Okay, sorry, go ahead. A flux on is one of these quantized amounts of current that you can add to a loop. And this is a cartoon picture, but I think it's sufficient for our purposes. So which, maybe it's useful to say, what is the speed at which these discrete packets of current travel? Because we'll be talking about light a little bit. It seems like the speed is important. The speed is important, that's an excellent question. Sometimes I wonder how you became so astute. Matrix 4 is coming out, so maybe that's related. I'm not sure. I'm dressed for the job. I was trying to become an extra on Matrix 4, it didn't work out. Anyway, so what's the speed of these packets? You'll have to find another gig. I know, I'm sorry. So the speed of the packet is actually these flux-ons, these sort of pulses of current that are generated by Joseph's injunctions. They can actually propagate very close to the speed of light, maybe something like a third of the speed of light. That's quite fast. So one of the reasons why Joseph's injunctions are appealing is because their signals can propagate quite fast and they can also switch very fast. What I mean by switch is perform that operation that I described where you add current to the loop. That can happen within a few tens of picoseconds. So you can get devices that operate in the hundreds of gigahertz range. And by comparison, most processors in our conventional computers operate closer to the one gigahertz range, maybe three gigahertz seems to be kind of where those speeds have leveled out. So the gamers listening to this are getting really excited that overclocked their system to like, what is it like four gigahertz or something? 100 sounds incredible. Can I just, as a tiny tangent, is the physics of this understood well how to do this stably? Oh yes, the physics is understood well. The physics of Joseph's injunctions is understood well. The technology is understood quite well too. The reasons why it hasn't displaced silicon microelectronics in conventional digital computing, I think are more related to what I was alluding to before about the myriad practical, almost mundane aspects of silicon that make it so useful. You can make a transistor ever smaller and smaller and it will still performance digital function quite well. The same is not true of a Joseph's injunction. You really, they don't, they just, it's not the same thing that there's this feature that you can keep making smaller and smaller and it'll keep performing the same operations. This loop I described, any Joseph's in circuit, well, I want to be careful, I shouldn't say any Joseph's in circuit, but many Joseph's in circuits, the way they process information or the way they perform whatever function it is they're trying to do, maybe it's sensing a weak magnetic field, it depends on an interplay between the junction and that loop. And you can't make that loop much smaller. And it's not for practical reasons that have to do with lithography. It's for fundamental physical reasons about the way the magnetic field interacts with that superconducting material. There are physical limits that no matter how good our technology got, those circuits would, I think would never be able to be scaled down to the densities that silicon microelectronics can. I don't know if we mentioned, is there something interesting about the various superconducting materials involved or is it all- There's a lot of stuff that's interesting. And it's not silicon. It's not silicon, no. So like it's some materials that also required to be super cold for Kelvin and so on. Yes, so let's dissect a couple of those different things. The super cold part, let me just mention for your gamers out there that are trying to clock it at four gigahertz and would love to go to 400. Yeah, what kind of cooling system can achieve four Kelvin? Exactly, four Kelvin, you need liquid helium. And so liquid helium is expensive, it's inconvenient. You need a cryostat that sits there and the energy consumption of that cryostat is impracticable for, it's not going in your cell phone. So you can picture holding your cell phone like this and then something the size of a keg of beer or something on your back to cool it, like that makes no sense. So if you're trying to make this in consumer devices, electronics that are ubiquitous across society, superconductors are not in the race for that. For now, but you're saying, so just to frame the conversation, maybe the thing we're focused on is computing systems that serve as servers, like large systems. Yes, large systems. So then you can contrast what's going on in your cell phone with what's going on at one of the supercomputers. Colleague Katie Schumann invited us out to Oak Ridge a few years ago, so we got to see Titan and that was when they were building Summit. So these are some high performance supercomputers out in Tennessee and those are filling entire rooms the size of warehouses. So once you're at that level, okay, there you're already putting a lot of power into cooling, you need, cooling is part of your engineering task that you have to deal with. So there it's not entirely obvious that cooling to four Kelvin is out of the question. It has not happened yet and I can speak to why that is in the digital domain if you're interested. I think it's not going to happen. I don't think superconductors are gonna replace semiconductors for digital computation. There are a lot of reasons for that, but I think ultimately what it comes down to is all things considered, cooling, errors, scaling down to feature sizes, all that stuff, semiconductors work better at the system level. Is there some aspect of just curious about the historical momentum of this? Is there some power to the momentum of an industry that's mass manufacturing using a certain material? Is this like a titanic shifting? Like what's your sense when a good idea comes along, how good does that idea need to be for the titanic to start shifting? That's an excellent question. That's an excellent way to frame it. And you know, I don't know the answer to that, but what I think is, okay, so the history of the superconducting logic goes back to the 70s. IBM made a big push to do superconducting digital computing in the 70s, and they made some choices about their devices and their architectures and things that in hindsight were kind of doomed to fail. And I don't mean any disrespect for the people that did it. It was hard to see at the time. But then another generation of superconducting logic was introduced, I wanna say the 90s, someone named Likorev and Seminov, they proposed an entire family of circuits based on Joseph's injunctions that are doing digital computing based on logic gates and or not these kinds of things. And they showed how it could go hundreds of times faster than silicon microelectronics. And it's extremely exciting. I wasn't working in the field at that time, but later when I went back and read the literature, I was just like, wow, this is so awesome. And so you might think, well, the reason why it didn't display silicon is because silicon already had so much momentum at that time. But that was the 90s, silicon kept that momentum because it had the simple way to keep getting better. You just make features smaller and smaller. So it would have to be, I don't think it would have to be that much better than silicon to displace it. But the problem is it's just not better than silicon. It might be better than silicon in one metric, speed of a switching operation or power consumption of a switching operation. But building a digital computer is a lot more than just that elemental operation. It's everything that goes into it, including the manufacturing, including the packaging, including the various materials aspects of things. So the reason why, and even in some of those early papers, I can't remember which one it was, Likorev said something along the lines of, you can see how we could build an entire family of digital electronic circuits based on these components. They could go a hundred or more times faster than semiconductor logic gates, but I don't think that's the right way to use superconducting electronic circuits. He didn't say what the right way was, but he basically said digital logic trying to steal the show from silicon is probably not what these circuits are most suited to accomplish. So if we can just linger and use the word computation, when you talk about computation, how do you think about it? Do you think purely on just the switching, or do you think something a little bit larger scale, a circuit taken together, performing the basic arithmetic operations that are then required to do the kind of computation that makes up a computer? Because when we talk about the speed of computation, is it boiled down to the basic switching, or is there some bigger picture that you're thinking about? Well, all right, so maybe we should disambiguate. There are a variety of different kinds of computation. I don't pretend to be an expert in the theory of computation or anything like that. I guess it's important to differentiate though between digital logic, which represents information as a series of bits, binary digits, which you can think of them as zeros and ones or whatever. Usually they correspond to a physical system that has two very well separated states. And then other kinds of computation, like we'll get into more the way your brain works, which it is, I think, indisputably processing information, but where the computation begins and ends is not anywhere near as well defined. It doesn't depend on these two levels. Here's a zero, here's a one. There's a lot of gray area that's usually referred to as analog computing. Also in conventional digital computers, or digital computers in general, you have a concept of what's called arithmetic depth, which is jargon that basically means how many sequential operations are performed to turn an input into an output. And those kinds of computations in digital systems are highly serial, meaning that data streams, they don't branch off too far to the side. You do, you have to pull some information over there and access memory from here and stuff like that. But by and large, the computation proceeds in a serial manner. It's not that way in the brain. In the brain, you're always drawing information from different places. It's much more network-based computing. Neurons don't wait for their turn. They fire when they're ready to fire. And so it's asynchronous. So one of the other things about a digital system is you're performing these operations on a clock. And that's a crucial aspect of it. Get rid of a clock in a digital system, nothing makes sense anymore. The brain has no clock. It builds its own time scales based on its internal activity. So you can think of the brain as kind of, I like this, like network computation where it's actually really trivial, simple computers, just a huge number of them, and they're networked. I would say it is complex, sophisticated little processors, and there's a huge number of them. Neurons are not simple. I don't mean to offend neurons. They're very complicated and beautiful. But we often oversimplify them. Yes, there's computation happening within a neuron. Right, so I would say to think of a transistor as the building block of a digital computer is accurate. You use a few transistors to make your logic gates. You build up processors from logic gates and things like that. So you can think of a transistor as a fundamental building block, or you can think of, as we get into more highly parallelized architectures, you can think of a processor as a fundamental building block. To make the analogy to the neuro side of things, a neuron is not a transistor. A neuron is a processor. It has synapses. Even synapses are not transistors, but they are lower on the information processing hierarchy in a sense. They do a bulk of the computation, but neurons are entire processors in and of themselves that can take in many different kinds of inputs on many different spatial and temporal scales and produce many different kinds of outputs so that they can perform different computations in different contexts. So this is where enters this distinction between computation and communication. So you can think of neurons performing computation and the networking, the interconnectivity of neurons is communication between neurons. And you see this with very large server systems. I mentioned offline, I've been talking to Jim Keller, whose dream is to build giant computers that, you know, the bottom like there's often the communication between the different pieces of computing. So in this paper that we mentioned, Optoelectronic Intelligence, you say electrons excel at computation while light is excellent for communication. Maybe you can linger and say in this context, what do you mean by computation and communication? What are electrons? What is light? And why do they excel at those two tasks? Yeah, just to first speak to computation versus communication, I would say computation is essentially taking in some information, performing operations on that information and producing new, hopefully more useful information. So for example, imagine you have a picture in front of you and there is a key in it and that's what you're looking for, for whatever reason, you wanna find the key, we all wanna find the key. So the input is that entire picture and the output might be the coordinates where the key is. So you've reduced the total amount of information you have, but you found the useful information for you in that present moment. That's the useful information. And you think about this computation as the controlled synchronous sequential? Not necessarily, it could be. That could be how your system is performing the computation or it could be asynchronous. There are lots of ways to find the key. It depends on the nature of the data. That's a very simplified example, a picture with a key in it. What about if you're in the world and you're trying to decide the best way to live your life? It might be interactive, it might be there might be some recurrence or some weird asynchrony, I got it. But there's an input and there's an output and you do some stuff in the middle that actually goes from the input to the output. You've taken in information and output different information, hopefully reducing the total amount of information and extracting what's useful. Communication is then getting that information from the location in which it's stored because information is physical, as Landauer emphasized. And so it is in one place and you need to get that information to another place so that something else can use it for whatever computation it's working on. Maybe it's part of the same network and you're all trying to solve the same problem, but neuron A over here just deduced something based on its inputs and it's now sending that information across the network to another location. So that would be the act of communication. Can you linger on Landauer and saying information is physical? Rolf Landauer, not to be confused with Lev Landauer. Yeah, and he made huge contributions to our understanding of the reversibility of information and this concept that energy has to be dissipated in computing when the computation is irreversible. But if you can manage to make it reversible, then you don't need to expend energy. But if you do expend energy to perform a computation, there's sort of a minimal amount that you have to do and it's KT log two. And it's all somehow related to the second law of thermodynamics and that the universe is an information process and then we're living in a simulation. So, okay, sorry. Well, sorry for that tangent. So that's the defining the distinction between computation and communication. Let me say one more thing just to clarify. Communication ideally does not change the information. It moves it from one place to another, but it is preserved. Got it, okay. All right, that is beautiful. So then the electron versus light distinction and why are electrons good at computation and light good at communication? Yes, this is, there's a lot that goes into it, I guess, but just try to speak to the simplest part of it. Electrons interact strongly with one another. They're charged particles. So if I pile a bunch of them over here, they're feeling a certain amount of force and they wanna move somewhere else. They're strongly interactive. You can also get them to sit still. You can, an electron has a mass, so you can cause it to be spatially localized. So for computation, that's useful because now I can make these little devices that put a bunch of electrons over here and then I change the state of a gate, like I've been describing, put a different voltage on this gate and now I move the electrons over here. Now they're sitting somewhere else. I have a physical mechanism with which I can represent information. It's spatially localized and I have knobs that I can adjust to change where those electrons are or what they're doing. Light, by contrast, photons of light, which are the discrete packets of energy that were identified by Einstein, they do not interact with each other, especially at low light levels. If you're in a medium and you have a bright, high light level, you can get them to interact with each other through the interaction with that medium that they're in, but that's a little bit more exotic. And for the purposes of this conversation, we can assume that photons don't interact with each other. So if you have a bunch of them all propagating in the same direction, they don't interfere with each other. If I wanna send, if I have a communication channel and I put one more photon on it, it doesn't screw up what those other ones, it doesn't change what those other ones were doing at all. So that's really useful for communication because that means you can sort of allow a lot of these photons to flow without disruption of each other and they can branch really easily and things like that. But it's not good for computation because it's very hard for this packet of light to change what this packet of light is doing. They pass right through each other. So in computation, you want to change information. And if photons don't interact with each other, it's difficult to get them to change the information represented by the others. So that's the fundamental difference. Is there also something about the way they travel through different materials? Or is that just a particular engineering? No, it's not. That's deep physics, I think. So this gets back to electrons interact with each other and photons don't. So say I'm trying to get a packet of information from me to you and we have a wire going between us. In order for me to send electrons across that wire, I first have to raise the voltage on my end of the wire. And that means putting a bunch of charges on it. And then that charge packet has to propagate along the wire and it has to get all the way over to you. That wire is gonna have something that's called capacitance, which basically tells you how much charge you need to put on the wire in order to raise the voltage on it. And the capacitance is gonna be proportional to the length of the wire. So the longer the length of the wire is, the more charge I have to put on it. And the energy required to charge up that line and move those electrons to you is also proportional to the capacitance and goes as the voltage squared. So you get this huge penalty if you wanna send electrons across a wire over appreciable distances. So distance is an important thing here when you're doing communication. Distance is an important thing. So is the number of connections I'm trying to make. Me to you, okay, one, that's not so bad. If I want to now send it to 10,000 other friends, then all of those wires are adding tons of extra capacitance. Now, not only does it take forever to put the charge on that wire and raise the voltage on all those lines, but it takes a ton of power. And the number 10,000 is not randomly chosen. That's roughly how many connections each neuron in your brain makes. So a neuron in your brain needs to send 10,000 messages every time it has something to say. You can't do that if you're trying to drive electrons from here to 10,000 different places. The brain does it in a slightly different way, which we can discuss. How can light achieve the 10,000 connections and why is it better? In terms of the energy use required to use light for the communication of the 10,000 connections. Right, right. So now, instead of trying to send electrons from me to you, I'm trying to send photons. So I can make what's called a waveguide, which is just a simple piece of material. It could be glass, like an optical fiber, or silicon on a chip. And I just have to inject photons into that waveguide. And independent of how long it is, independent of how many different connections I'm making, it doesn't change the voltage or anything like that that I have to raise up on the wire. So if I have one more connection, if I add additional connections, I need to add more light to the waveguide because those photons need to split and go to different paths. That makes sense, but I don't have a capacitive penalty. Sometimes these are called wiring parasitics. There are no parasitics associated with light in that same sense. So. This might be a dumb question, but how do I catch a photon on the other end? Is it material? Is it the polymer stuff you were talking about for a different application for photolithography? Like, how do you catch a photon? There's a lot of ways to catch a photon. It's not a dumb question. It's a deep and important question that basically defines a lot of the work that goes on in our group at NIST. One of my group leaders, Seywounam, has built his career around these superconducting single photon detectors. So, if you're going to try to sort of reach a lower limit and detect just one particle of light, superconductors come back into our conversation. And just picture a simple device where you have current flowing through a superconducting wire and. A loop again or no? Let's say, yes, you have a loop. So, you have a superconducting wire that goes straight down like this. And on your loop branch, you have a little ammeter. Something that measures current. There's a resistor up there too. Go with me here. So, you're current biasing this. So, there's current flowing through that superconducting branch. Since there's a resistor over here, all the current goes through the superconducting branch. Now, a photon comes in, strikes that superconductor. We talked about this superconducting macroscopic quantum state. That's going to be destroyed by the energy of that photon. So, now that branch of the circuit is resistive too. And you've properly designed your circuit so that the resistance on that superconducting branch is much greater than the other resistance. Now, all of your current's going to go that way. Your ammeter says, oh, I just got a pulse of current. That must mean I detected a photon. Then where you broke that superconductivity in a matter of a few nanoseconds, it cools back off, dissipates that energy, and the current flows back through that superconducting branch. This is a very powerful superconducting device that allows us to understand quantum states of light. I didn't realize a loop like that could be sensitive to a single photon. I mean, that seems strange to me because, I mean, so what happens when you just barrage it with photons? If you put a bunch of photons in there, essentially the same thing happens. You just drive it into the normal state. It becomes resistive, and it's not particularly interesting. So, you have to be careful how many photons you send. Like, you have to be very precise with your communication. Well, it depends. So, I would say that that's actually, in the application that we're trying to use these detectors for, that's a feature. Because what we want is for, if a neuron sends one photon to a synaptic connection, and one of these superconducting detectors is sitting there, you get this pulse of current, and that synapse says, event, then I'm gonna do what I do when there's a synapse event, I'm gonna perform computations, that kind of thing. But if accidentally you send two there, or three, or five, it does the exact same. And so, this is how, in the system that we're devising here, communication is entirely binary. And that's what I tried to emphasize a second ago. Communication should not change the information. You're not saying, oh, I got this kind of communication event, four photons. No, we're not keeping track of that. This neuron fired, this synapse says, that neuron fired. That's it, so that's a noise filtering property of those detectors. However, there are other applications where you'd rather know the exact number of photons. That can be very useful in quantum computing with light. And our group does a lot of work around another kind of superconducting sensor, called a transition edge sensor, that Adrian Alita in our group does a lot of work on that. And that can tell you, based on the amplitude of the current pulse you divert, exactly how many photons were in that pulse. What's that useful for? One way that you can encode information in quantum states of light is in the number of photons. You can have what are called number states. And a number state will have a well-defined number of photons, and maybe the output of your quantum computation encodes its information in the number of photons that are generated. So, if you have a detector that is sensitive to that, it's extremely useful. Can you achieve a clock with photons? Or is that not important? Is there a synchronicity here? In general, it can be important. Clock distribution is a big challenge in especially large computational systems. And so, yes, optical clocks, optical clock distribution, is a very powerful technology. I don't know the state of that field right now. But I imagine that if you're trying to distribute a clock across any appreciable size computational system, you wanna use light. Yeah, I wonder how these giant systems work, especially like supercomputers. Do they need to do clock distribution? Or are they doing more ad hoc parallel, like concurrent programming? Like there's some kind of locking mechanisms or something. That's a fascinating question. But let's zoom in at this very particular question of computation on a processor and communication between processors. So, what does this system look like that you're envisioning? One of the places you're envisioning it is in the paper on optoelectronic intelligence. So, what are we talking about? Are we talking about something that starts to look a lot like the human brain? Or does it still look a lot like a computer? What are the size of this thing? Is it going inside a smartphone? Or as you said, does it go inside something that's more like a house? Like what should we be imagining? What are you thinking about when you're thinking about these fundamental systems? Let me introduce the word neuromorphic. There's this concept of neuromorphic computing where what that broadly refers to is computing based on the information processing principles of the brain. And as digital computing seems to be pushing towards some fundamental performance limits, people are considering architectural advances, drawing inspiration from the brain, more distributed parallel network kind of architectures and stuff. And so, there's this continuum of neuromorphic from things that are pretty similar to digital computers, but maybe there are more cores and the way they send messages is a little bit more like the way brain neurons send spikes. But for the most part, it's still digital electronics. And then, you have some things in between where maybe you're using transistors, but now you're starting to use them instead of in a digital way, in an analog way. And so, you're trying to get those circuits to behave more like neurons. And then, that's quite a bit more on the neuromorphic side of things. You're trying to get your circuits, although they're still based on silicon, you're trying to get them to perform operations that are highly analogous to the operations in the brain. That's where a great deal of work is in neuromorphic computing, people like Yakima Wendoveri and Gert Kauenberg, Jennifer Hasler, countless others. It's a rich and exciting field going back to Carver Mead in the late 1980s. And then, all the way on the other extreme of the continuum is where you say, I'll give up anything related to transistors or semiconductors or anything like that. I'm not starting with the assumption that I'm gonna use any kind of conventional computing hardware. And instead, what I wanna do is try and understand what makes the brain powerful at the kind of information processing it does. And I wanna think from first principles about what hardware is best going to enable us to capture those information processing principles in an artificial system. And that's where I live. That's where I'm doing my exploration these days. So, what are the first principles of brain-like computation and communication? Right, yeah, this is so important. And I'm glad we booked 14 hours for this because- I only have 13, I'm sorry. Okay, so the brain is notoriously complicated. And I think that's an important part of why it can do what it does. But okay, let me try to break it down. Starting with the devices, neurons, as I said before, they're sophisticated devices in and of themselves. And synapses are too. They can change their state based on the activity. So, they adapt over time. That's crucial to the way the brain works. They don't just adapt on one time scale. They can adapt on myriad timescales from the spacing between pulses, the spacing between spikes that come from neurons, all the way to the age of the organism. Also relevant, perhaps, I think the most important thing that's guided my thinking is the network structure of the brain. Which can also be adjusted on different scales. Absolutely, yeah. So, you're changing the strength of contacts, you're changing the spatial distribution of them. Although, spatial distribution doesn't change that much once you're a mature organism. But that network structure is really crucial. So, let me dwell on that for a second. You can't talk about the brain without emphasizing that most of the neurons in the neocortex or the prefrontal cortex, the part of the brain that we think is most responsible for high-level reasoning and things like that, those neurons make thousands of connections. So, you have this network that is highly interconnected. And I think it's safe to say that one of the primary reasons that they make so many different connections is that allows information to be communicated very rapidly from any spot in the network to any other spot in the network. So, that's a sort of spatial aspect of it. You can quantify this in terms of concepts that are related to fractals and scale invariance, which I think is a very beautiful concept. So, what I mean by that is kind of, no matter what spatial scale you're looking at in the brain, within certain bounds, you see the same general statistical pattern. So, if I draw a box around some region of my cortex, most of the connections that those neurons within that box make are gonna be within the box to each other in their local neighborhood. And that's sort of called clustering, loosely speaking. But a non-negligible fraction is gonna go outside of that box. And then if I draw a bigger box, the pattern is gonna be exactly the same. So, you have this scale invariance and you also have a non-vanishing probability of a neuron making connection very far away. So, suppose you wanna plot the probability of a neuron making a connection as a function of distance. If that were an exponential function, it would go e to the minus radius over some characteristic radius, and it would drop off up to some certain radius. The probability would be reasonable close to one. And then beyond that characteristic length, R zero, it would drop off sharply. And so, that would mean that the neurons in your brain are really localized, and that's not what we observe. Instead, what you see is that the probability of making a longer distance connection, it does drop off, but it drops off as a power loss. So, the probability that you're gonna have a connection at some radius R goes as R to the minus some power. And that's what we see with forces in nature, like the electromagnetic force between two particles or gravity goes as one over the radius squared. So- You can see this in fractals. I love that there's like a fractal dynamics of the brain that if you zoom out, you draw the box, and you increase that box by certain step sizes, you're gonna see the same statistics. I think that's probably very important to the way the brain processes information. It's not just in the spatial domain, it's also in the temporal domain. And what I mean by that is- That's incredible that this emerged through the evolutionary process that potentially somehow connected to the way the physics of the universe works. Yeah, I couldn't agree more. That it's a deep and fascinating subject that I hope to be able to spend the rest of my life studying. You think you need to solve, understand this, this fractal nature in order to understand intelligence and computation communication. I do think so. I think they're deeply intertwined. Yes, I think power laws are right at the heart of it. So just to push that one through, the same thing happens in the temporal domain. So suppose you had, suppose your neurons in your brain were always oscillating at the same frequency, then the probability of finding a neuron oscillating as a function of frequency would be this narrowly peaked function around that certain characteristic frequency. That's not at all what we see. The probability of finding neurons oscillating or pulsing, producing spikes at a certain frequency is again a power law, which means there's no defined scale of the temporal activity in the brain. At what speed do your thoughts occur? Well, there's a fastest speed they can occur, and that is limited by communication and other things, but there's not a characteristic scale. We have thoughts on all temporal scales from a few tens of milliseconds, which is physiologically limited by our devices, compare that to tens of picoseconds that I talked about in superconductors, all the way up to the lifetime of the organism. You can still think about things that happened to you when you were a kid. Well, if you wanna be really trippy, then across multiple organisms in the entirety of human civilization, you have thoughts that span organisms, right? Yes, taking it to that level, yes. If you're willing to see the entirety of the human species as a single organism with a collective intelligence, then that too on a spatial and temporal scale, there's thoughts occurring. And then if you look at not just the human species, but the entirety of life on Earth as an organism with thoughts that are occurring, that are greater and greater sophisticated thoughts, there's a different spatial and temporal scale there. This is getting very suspicious. Well, hold on though, before we're done, I just wanna just tie the bow and say that the spatial and temporal aspects are intimately interrelated with each other. So activity between neurons that are very close to each other is more likely to happen on this faster timescale and information is gonna propagate and encompass more of the brain, more of your cortices, different modules in the brain are gonna be engaged in information processing on longer timescales. So there's this concept of information integration where most neurons are specialized. Any given neuron or any cluster of neuron has its specific purpose, but they're also very much integrated. So you have neurons that specialize, but share their information. And so that happens through these fractal nested oscillations that occur across spatial and temporal scales. I think capturing those dynamics in hardware, to me, that's the goal of neuromorphic computing. So does it need to look, so first of all, that's fascinating. We've stated some clear principles here. Now, does it have to look like the brain outside of those principles as well? Like what other characteristics have to look like the human brain? Or can it be something very different? Well, it depends on what you're trying to use it for. And so I think a lot of the community asks that question a lot. What are you gonna do with it? And I completely get it. I think that's a very important question. And it's also sometimes not the most helpful question. What if what you wanna do with it is study it? What if you just wanna see, what do you have to build into your hardware in order to observe these dynamical principles? And also, I ask myself that question every day, and I'm not sure I'm able to answer that. So what are you gonna do with this particular neuromorphic machine? So suppose what we're trying to do with it is build something that thinks. We're not trying to get it to make us any money or drive a car. Maybe we'll be able to do that, but that's not our goal. Our goal is to see if we can get the same types of behaviors that we observe in our own brain. And by behaviors, in this sense, what I mean, the behaviors of the components, the neurons, the network, that kind of stuff. I think there's another element that I didn't really hit on that you also have to build into this, and those are architectural principles. They have to do with the hierarchical modular construction of the network. And without getting too lost in jargon, the main point that I think is relevant there, let me try and illustrate it with a cartoon picture of the architecture of the brain. So in the brain, you have the cortex, which is sort of this outer sheet. It's actually a, you can, it's a layered structure. You can, if you could take it out of your brain, you could unroll it on the table, and it would be about the size of a pizza sitting there. And that's a module. It does certain things. It processes, as Yorgi Buzsaki would say, it processes the what of what's going on around you. But you have another really crucial module that's called the hippocampus, and that network is structured entirely differently. First of all, this cortex that I described, 10 billion neurons in there, so numbers matter here. And they're organized in that sort of power law distribution where the probability of making a connection drops off as a power law in space. The hippocampus is another module that's important for understanding how, where you are, when you are, keeping track of your position in space and time. And that network is very much random. So the probability of making a connection, it almost doesn't even drop off as a function of distance. It's the same probability that you'll make it here to over there, but there are only about a hundred million neurons there. So you can have that huge, densely connected module because it's not so big. And the neocortex, or the cortex and the hippocampus, they talk to each other constantly. And that communication is largely facilitated by what's called the thalamus. I'm not a neuroscientist here. I'm trying to do my best to recite things. Cartoon picture of the brain, I got you. Yeah, something like that. So this thalamus is coordinating the activity between the neocortex and the hippocampus and making sure that they talk to each other at the right time and send messages that will be useful to one another. So this all taken together is called the thalamocortical complex. And it seems like building something like that is going to be crucial to capturing the types of activity we're looking for because those responsibilities, those separate modules, they do different things. That's gotta be central to achieving these states of efficient information integration across space and time. By the way, I am able to achieve this state by watching simulations, visualizations of the thalamocortical complex. There's a few people, I forget from where, they've created these incredible visual illustrations of visual stimulation from the eye or something like that in this image flowing through the brain. Wow, I haven't seen that. I gotta check that out. So it's one of those things, you find this stuff in the world and you see on YouTube, it has 1,000 views, these visualizations of the human brain processing information. Because there's chemistry there because this is from actual human brains. I don't know how they're doing the coloring but they're able to actually trace the chemical and the electrical signals throughout the brain. And the visual thing, it's like, whoa. Because it looks kind of like the universe. I mean, the whole thing is just incredible. I recommend it highly. I'll probably post a link to it. But you can just look for, one of the things they simulate is the thalamocortical complex and just visualization. You can find that yourself on YouTube. But it's beautiful. The other question I have for you is how does memory play into all of this? Because all the signals sending back and forth, that's computation and communication. But that's kind of like processing of inputs and outputs to produce outputs in the system. That's kind of like maybe reasoning. Maybe there's some kind of recurrence. But is there a storage mechanism that you think about in the context of neuromorphic computing? Yeah, absolutely. So that's gotta be central. You have to have a way that you can store memories. And there are a lot of different kinds of memory in the brain. That's yet another example of how it's not a simple system. So there's one kind of memory, one way of talking about memory usually starts in the context of Hopfield networks. You were lucky to talk to John Hopfield on this program. But the basic idea there is working memory is stored in the dynamical patterns of activity between neurons. And you can think of a certain pattern of activity as an attractor, meaning if you put in some signal that's similar enough to other previously experienced signals like that, then you're going to converge to the same network dynamics. And you will see these neurons participate in the same network patterns of activity that they have in the past. So you can talk about the probability that different inputs will allow you to converge to different basins of attraction. And you might think of that as, oh, I saw this face and then I excited this network pattern of activity because last time I saw that face, I was at, you know, what some movie and that's a famous person that's on the screen or something like that. So that's one memory storage mechanism, but crucial to the ability to imprint those memories in your brain is the ability to change the strength of connection between one neuron and another, that synaptic connection between them. So synaptic weight update is a massive field of neuroscience and neuromorphic computing as well. So there are two poles to that on that spectrum. Okay, so more in the language of machine learning, we would talk about supervised and unsupervised learning. And when I'm trying to tie that down to neuromorphic computing, I will use a definition of supervised learning, which basically means the external user, the person who's controlling this hardware has some knob that they can tune to change each of the synaptic weights, depending on whether or not the network's doing what you want it to do. Whereas what I mean in this conversation, when I say unsupervised learning is that those synaptic weights are dynamically changing in your network based on nothing that the user is doing, nothing that there's no wire from the outside going into any of those synapses. The network itself is reconfiguring those synaptic weights based on physical properties that you've built into the devices. So if the synapse receives a pulse from here and that causes the neuron to spike, some circuit built in there with no help from me or anybody else adjust the weight in a way that makes it more likely to store the useful information and excite the useful network patterns and makes it less likely that random noise, useless communication events will have an important effect on the network activity. So there's memory encoded in the weights, the synaptic weights. Yes. What about the formation of something that's not often done in machine learning, the formation of new synaptic connections? Right, well, that seems to, so again, not a neuroscientist here, but my reading of the literature is that that's particularly crucial in early stages of brain development where a newborn is born with tons of extra synaptic connections and it's actually pruned over time. So the number of synapses decreases as opposed to growing new long distance connections. It is possible in the brain to grow new neurons and assign new synaptic connections, but it doesn't seem to be the primary mechanism by which the brain is learning. So for example, like right now, sitting here talking to you, you say lots of interesting things and I learn from you and I can remember things that you just said. And I didn't grow new axonal connections down to new synapses to enable those. It's plasticity mechanisms in the synaptic connections between neurons that enable me to learn on that timescale. So at the very least, that you can sufficiently approximate that with just weight updates. You don't need to form new connections. I would say weight updates are a big part of it. I also think there's more because broadly speaking, when we're doing machine learning, our networks, say we're talking about feed forward, deep neural networks, the temporal domain is not really part of it. Okay, you're gonna put in an image and you're gonna get out a classification and you're gonna do that as fast as possible. So you care about time, but time is not part of the essence of this thing really. Whereas in spiking neural networks, what we see in the brain, time is as crucial as space and they're intimately intertwined as I've tried to say. And so adaptation on different timescales is important, not just in memory formation, although it plays a key role there, but also in just keeping the activity in a useful dynamic range. So you have other plasticity mechanisms, not just weight update, or at least not on the timescale of many action potentials, but even on the shorter timescale. So a synapse can become much less efficacious. It can transmit a weaker signal after the second, third, fourth, that can second, third, fourth action potential to occur in a sequence. So that's what's called short-term synaptic plasticity, which is a form of learning. You're learning that I'm getting too much stimulus from looking at something bright right now. So I need to tone that down. There's also another really important mechanism in learning. It's called metaplasticity. What that seems to be is a way that you change not the weights themselves, but the rate at which the weights change. So when I am in, say, a lecture hall and my, this is a potentially terrible cartoon example, but let's say I'm in a lecture hall and it's time to learn, right? So my brain will release more, perhaps, dopamine or some neuromodulator that's gonna change the rate at which synaptic plasticity occurs. So that can make me more sensitive to learning at certain times, more sensitive to overriding previous information, and less sensitive at other times. And finally, as long as I'm rattling off the list, I think another concept that falls in the category of learning or memory adaptation is homeostasis or homeostatic adaptation, where neurons have the ability to control their firing rate. So if one neuron is just like blasting way too much, it will naturally tone itself down. Its threshold will adjust so that it stays in a useful dynamical range. And we see that's captured in deep neural networks where you don't just change the synaptic weights, but you can also move the thresholds of simple neurons in those models. And so to achieve the spiking neural networks, you want to use, you want to implement the first principles that you mentioned of the temporal and the spatial fractal dynamics here. So you can communicate locally, you can communicate across much greater distances and do the same thing in space and do the same thing in time. Now you have like a chapter called superconducting hardware for neuromorphic computing. So what are some ideas that integrate some of the things we've been talking about in terms of the first principles of neuromorphic computing and the ideas that you outline in optoelectronic intelligence? Yeah, so let me start, I guess, on the communication side of things, because that's what led us down this track in the first place. By us, I'm talking about my team of colleagues at NIST, you know, Saeed Han, Bryce Primavera, Sonia Buckley, Jeff Childs, Adam McCaughan, to name, Alex Tate, to name a few, our group leaders, Sebu Nam and Rich Mirren. We've all contributed to this. So this is not me saying necessarily just the things that I've proposed, but sort of where our team's thinking has evolved over the years. Can I quickly ask, what is NIST, and where is this amazing group of people located? NIST is the National Institute of Standards and Technology. The larger facility is out in Gaithersburg, Maryland. Our team is located in Boulder, Colorado. NIST is a federal agency under the Department of Commerce. We do a lot with, by we, I mean other people at NIST, do a lot with standards, you know, making sure that we understand the system of units, international system of units, precision measurements. There's a lot going on in electrical engineering, material science. And it's historic. I mean, it's like, it's one of those, it's like MIT or something like that. It has a reputation over many decades of just being this really, a place where there's a lot of brilliant people have done a lot of amazing things. But in terms of the people in your team, in this team of people involved in the concept we're talking about now, I'm just curious, what kind of disciplines are we talking about? What is it? Mostly physicists and electrical engineers, some material scientists. But I would say, yeah, I think physicists and electrical engineers, my background is in photonics, the use of light for technology. So coming from there, I tend to have found colleagues that are more from that background. Although Adam McConn, more of a superconducting electronics background. We need a diversity of folks. This project is sort of cross disciplinary. I would love to be working more with neuroscientists and things, but we haven't reached that scale yet. But yeah. You're focused on the hardware side, which requires all the disciplines that you mentioned. Yes. And then of course, you know, science may be a source of inspiration for some of the long-term vision. I would actually call it more than inspiration. I would call it sort of a roadmap, you know. We're not trying to build exactly the brain, but I don't think it's enough to just say, oh, neurons kind of work like that. Let's kind of do that thing. I mean, we're very much following the concepts that the cognitive sciences have laid out for us, which I believe is a really robust roadmap. I mean, just on a little bit of a tangent, it's often stated that we just don't understand the brain and so it's really hard to replicate it because we just don't know what's going on there. And maybe five or seven years ago, I would have said that, but as I got more interested in the subject, I read more of the neuroscience literature and I was just taken by the exact opposite sense. I can't believe how much they know about this. I can't believe how mathematically rigorous and sort of theoretically complete a lot of the concepts are. That's not to say we understand consciousness or we understand the self or anything like that, but what is the brain doing and why is it doing those things? Neuroscientists have a lot of answers to those questions. So there's a lot, if you're a hardware designer that just wants to get going, whoa, it's pretty clear which direction to go in, I think. Okay, so I love the optimism behind that, but in the implementation of these systems that uses superconductivity, how do you make it happen? So to me, it starts with thinking about the communication network. You know for sure that the ability of each neuron to communicate to many thousands of colleagues across the network is indispensable. I take that as a core principle of my architecture, my thinking on the subject. So coming from a background in photonics, it was very natural to say, okay, we're gonna use light for communication. Just in case listeners may not know, light is often used in communication. I mean, if you think about radio, that's light, it's long wavelengths, but it's electromagnetic radiation. It's the same physical phenomenon obeying exactly the same Maxwell's equations. And then all the way down to fiber optics, now you're using visible or near infrared wavelengths of light, but the way you send messages across the ocean is now contemporary over optical fibers. So using light for communication is not a stretch. It makes perfect sense. So you might ask, well, why don't you use light for communication in a conventional microchip? And the answer to that is, I believe, physical. If we had a light source on a silicon chip that was as simple as a transistor, there would not be a processor in the world that didn't use light for communication, at least above some distance. How many light sources are needed? Oh, you need a light source at every single point. A light source per neuron. Per neuron, per little, but then if you could have a really small and nice light source, your definition of neuron could be flexible. Could be, yes, yes. Sometimes it's helpful to me to say, in this hardware, a neuron is that entity which has a light source. And then there was light. I can explain more about that, but somehow this rhymes with consciousness, because people often say the light of consciousness. So that consciousness is that which is conscious. I got it. That's not my quote. That's me, that's my quote. That quote comes from my background. Yours is in optics, mine in light, mine's in darkness. So go ahead. So the point I was making there is that if it was easy to manufacture light sources along with transistors on a silicon chip, they would be everywhere. And it's not easy. People have been trying for decades, and it's actually extremely difficult. I think an important part of our research is dwelling right at that spot there. Is it physics or engineering? It's physics. So, okay, so it's physics, I think. So what I mean by that is, as we discussed, silicon is the material of choice for transistors, and it's very difficult to imagine that that's gonna change anytime soon. Silicon is notoriously bad at emitting light, and that has to do with the immutable properties of silicon itself, the way that the energy bands are structured in silicon. You're never going to make silicon efficient as a light source at room temperature without doing very exotic things that degrade its ability to interface nicely with those transistors in the first place. So that's like one of these things where it's, why is nature dealing us that blow? You give us these beautiful transistors, and you give us all the motivation to use light for communication, but then you don't give us a light source. So, well, okay, you do give us a light source, compound semiconductors, like we talked about back at the beginning, an element from group three and an element from group five form an alloy where every other lattice site switches which element it is. Those have much better properties for generating light. You put electrons in, light comes out. Almost 100% of the electron hold, it can be made efficient. Look at that. I'll take your word for it, okay. However, I say it's physics, not engineering, because it's very difficult to get those compound semiconductor light sources situated with your silicon. In order to do that ion implantation that I talked about at the beginning, high temperatures are required. So you gotta make all of your transistors first and then put the compound semiconductors on top of there. You can't grow them afterwards because that requires high temperature. It screws up all your transistors. You try and stick them on there. They don't have the same lattice constant. The spacing between atoms is different enough that it just doesn't work. So nature does not seem to be telling us that, hey, go ahead and combine light sources with your digital switches for conventional digital computing. And conventional digital computing will often require smaller scale, I guess, in terms of like a smartphone. So in which kind of systems does nature hint that we can use light and photons for communication? Well, so let me just try and be clear. You can use light for communication in digital systems. Just the light sources are not intimately integrated with the silicon. You manufacture all the silicon, you have your microchip, plunk it down. And then you manufacture your light sources, separate chip, completely different process, made in a different foundry. And then you put those together at the package level. So now you have some, I would say a great deal of architectural limitations that are introduced by that sort of package level integration, as opposed to monolithic on the same chip integration. But it's still a very useful thing to do. And that's where I had done some work previously before I came to NIST. There's a project led by Vladimir Stoyanovich that now spun out into a company called IR Labs led by Mark Wade and Chen Sun, where they're doing exactly that. So you have your light source chip, your silicon chip, whatever it may be doing, maybe it's digital electronics, maybe it's some other control purpose, something. And the silicon chip drives the light source chip and modulates the intensity of the light. So you can get data out of the package on an optical fiber. And that still gives you tremendous advantages in bandwidth, as opposed to sending those signals out over electrical lines. But it is somewhat peculiar to my eye that they have to be integrated at this package level. And those people, I mean, they're so smart, those are my colleagues that I respect a great deal. So it's very clear that it's not just, they're making a bad choice. This is what physics is telling us. It just wouldn't make any sense to try to stick them together. Yeah, so even if it's difficult, it's easier than the alternative, unfortunately. I think so, yes. And again, I need to go back and make sure that I'm not taking the wrong way. I'm not saying that the pursuit of integrating compound semiconductors with silicon is fruitless and shouldn't be pursued. It should, and people are doing great work. Kai Mei Lau and John Bowers, others, they're doing it and they're making progress. But to my eye, it doesn't look like that's ever going to be just the standard monolithic light source on silicon process. I just don't see it. Yeah, so nature kind of points the way, usually. And if you resist nature, you're gonna have to do a lot more work. And it's gonna be expensive and not scalable. Got it. But okay, so let's go far into the future. Let's imagine this gigantic neuromorphic computing system that simulates all of our realities. It currently is, we mentioned matrix four. So this thing, this powerful computer, how does it operate? So what are the neurons? What is the communication? What's your sense? All right, so let me now, after spending 45 minutes trashing light source integration with silicon, let me now say why I'm basing my entire life, professional life on integrating light sources with electronics. I think the game is completely different when you're talking about superconducting electronics. For several reasons, let me try to go through them. One is that, as I mentioned, it's difficult to integrate those compound semiconductor light sources with silicon. With silicon is a requirement that is introduced by the fact that using semiconducting electronics. In superconducting electronics, you're still gonna start with a silicon wafer, but it's just the bread for your sandwich in a lot of ways. You're not using that silicon in precisely the same way for the electronics. You're now depositing superconducting materials on top of that. The prospects for integrating light sources with that kind of an electronic process are certainly less explored, but I think much more promising because you don't need those light sources to be intimately integrated with the transistors. That's where the problems come up. They don't need to be lattice matched to the silicon, all that kind of stuff. Instead, it seems possible that you can take those compound semiconductor light sources, stick them on the silicon wafer, and then grow your superconducting electronics on the top of that. It's at least not obviously going to fail. So the computation would be done on the superconductive material as well? Yes, the computation is done in the superconducting electronics, and the light sources receive signals that say, hey, a neuron reached threshold, produce a pulse of light, send it out to all your downstream synaptic connections. Those are, again, superconducting electronics. Perform your computation, and you're off to the races. Your network works. So then if we can rewind real quick. So what are the limitations of the challenges of superconducting electronics when we think about constructing these kinds of systems? So actually, let me say one other thing about the light sources. Yes, please. And then I'll move on, I promise, because this is probably tedious for some. This is super exciting. Okay, one other thing about the light sources. I said that silicon is terrible at emitting photons. It's just not what it's meant to do. However, the game is different when you're at low temperature. If you're working with superconductors, you have to be at low temperature because they don't work otherwise. When you're at four Kelvin, silicon is not obviously a terrible light source. It's still not as efficient as compound semiconductors, but it might be good enough for this application. The final thing that I'll mention about that is, again, leveraging superconductors, as I said, in a different context, superconducting detectors can receive one single photon. In that conversation, I failed to mention that semiconductors can also receive photons. That's the primary mechanism by which it's done. A camera in your phone that's receptive to visible light is receiving photons. It's based on silicon, or you can make it in different semiconductors for different wavelengths, but it requires on the order of a thousand, a few thousand photons to receive a pulse. Now, when you're using a superconducting detector, you need one photon, exactly one. I mean, one or more. So the fact that your synapses can now be based on superconducting detectors instead of semiconducting detectors brings the light levels that are required down by some three orders of magnitude. So now you don't need good light sources. You can have the world's worst light sources. As long as they spit out maybe a few thousand photons every time a neuron fires, you have the hardware principles in place that you might be able to perform this optoelectronic integration. To me, optoelectronic integration, it's just so enticing. We want to be able to leverage electronics for computation, light for communication, working with silicon microelectronics at room temperature that has been exceedingly difficult. And I hope that when we move to the superconducting domain, target a different application space that is neuromorphic instead of digital and use superconducting detectors, maybe optoelectronic integration comes to us. Okay, so there's a bunch of questions, so one is temperature. So in these kind of hybrid heterogeneous systems, what's the temperature? What are some of the constraints of the operation here? Does it all have to be a four Kelvin as well? Four Kelvin, everything has to be at four Kelvin. Okay, so what are the other engineering challenges of making this kind of optoelectronic systems? Let me just dwell on that four Kelvin for a second because some people hear four Kelvin and they just get up and leave. They just say, I'm not doing it, you know? And to me, that's very earth-centric, species-centric. We live in 300 Kelvin, so we want our technologies to operate there too. I totally get it. Yeah, what's zero Celsius? Zero Celsius is 273 Kelvin. So we're talking very, very cold here. This is- Not even Boston cold. No. This is real cold. Yeah. Siberia cold. No. Okay, so just for reference, the temperature of the cosmic microwave background is about 2.7 Kelvin. So we're still warmer than deep space. Yeah, good. So that when the universe dies out, it'll be colder than four K. It's already colder than four K. In the expanses, you don't have to get that far away from the earth in order to drop down to not far from four Kelvin. So what you're saying is the aliens that live at the edge of the observable universe are using superconducting material for their computation. They don't have to live at the edge of the universe. The aliens that are more advanced than us in their solar system are doing this in their asteroid belt. We can get to that. Oh, because they can get that to that temperature easier? Sure, yeah. All you have to do is reflect the sunlight away and you have a huge headstart. Oh, so the sun is the problem here. Like it's warm here on earth. Got it. Yeah. Okay, so how do we get to four K? What's- Well, okay, so what I want to say- It's a very different kind of four K. What I want to say about temperature- Yeah. What I want to say about temperature is that if you can swallow that, if you can say, all right, I give up applications that have to do with my cell phone and the convenience of a laptop on a train, and you instead, for me, I'm very much in the scientific headspace. I'm not looking at products. I'm not looking at what this will be useful to sell to consumers. Instead, I'm thinking about scientific questions. Well, it's just not that bad to have to work at four Kelvin. We do it all the time in our labs at NIST. And so does, I mean, for reference, the entire quantum computing sector usually has to work at something like 100 millikelvin, 50 millikelvin. So now you're talking of another factor of 100, even colder than that, a fraction of a degree. And everybody seems to think quantum computing is going to take over the world. It's so much more expensive to have to get that extra factor of 10 or whatever colder. And yet it's not stopping people from investing in that area. And by investing, I mean putting their research into it as well as venture capital or whatever. So- Oh, so based on the energy of what you're commenting on, I'm getting a sense that's one of the criticism of this approach is 4K, 4 Kelvin is a big negative. It is the showstopper for a lot of people. They just, I mean, and understandably, I'm not saying that that's not a consideration. Of course it is. For some, okay, so different motivations for different people. In the academic world, suppose you spent your whole life learning about silicon microelectronic circuits. You send a design to a foundry, they send you back a chip and you go test it at your tabletop. And now I'm saying, here, now learn how to use all these cryogenics so you can do that at 4 Kelvin. No, come on, man, I don't wanna do that. That sounds bad. It's the old momentum, the Titanic of the turning. Yeah, kind of. But you're saying that's not too much of a, when we're looking at large systems and the gain you can potentially get from them, that's not that much of a cost. And when you wanna answer the scientific question about what are the physical limits of cognition? Well, the physical limits, they don't care if you're at 4 Kelvin. If you can perform cognition at a scale, orders of magnitude beyond any room temperature technology, but you gotta get cold to do it, you're gonna do it. And to me, that's the interesting application space. It's not even an application space. That's the interesting scientific paradigm. So I personally am not going to let low temperature stop me from realizing a technological domain or realm that is achieving in most ways everything else that I'm looking for in my hardware. So that, okay, that's a big one. Is there other kind of engineering challenges that you envision? Yeah, yeah, yeah. So let me take a moment here because I haven't really described what I mean by a neuron or a network in this particular hardware. Yeah, do you wanna talk about loop neurons? And there's so many fascinating, but you just have so many amazing papers that people should definitely check out and the titles alone are just killer. So anyway, go ahead. Right, so let me say big picture. So based on optics, photonics for communication, superconducting electronics for computation, how does this all work? So a neuron in this hardware platform can be thought of as circuits that are based on Joseph's injunctions, like we talked about before, where every time a photon comes in, so let's start by talking about a synapse. A synapse receives a photon, one or more, from a different neuron, and it converts that optical signal to an electrical signal. The amount of current that that adds to a loop is controlled by the synaptic weight. So as I said before, you're popping fluxons into a loop, right? So a photon comes in, it hits a superconducting single photon detector, one photon, the absolute physical minimum that you can communicate from one place to another with light. And that detector then converts that into an electrical signal, and the amount of the signal is correlated with some kind of weight. Yeah, so the synaptic weight will tell you how many fluxons you pop into the loop. It's an analog number. We're doing analog computation now. Well, can you just linger on that? What the heck is a fluxon? Are we supposed to know this? Or is this a funny, it's like the Big Bang. Is this a funny word for something deeply technical? No, let's try to avoid using the word fluxon because it's not actually necessary. When a photon- It's fun to say, though. So it's very necessary, I would say. When a photon hits that superconducting single photon detector, current is added to a superconducting loop, and the amount of current that you add is an analog value. It can have eight-bit equivalent resolution, something like that, 10 bits, maybe. That's amazing, by the way. This is starting to make a lot more sense. When you're using superconductors for this, the energy of that circulating current is less than the energy of that photon. So your energy budget is not destroyed by doing this analog computation. So now, in the language of a neuroscientist, you would say that's your post-synaptic signal. You have this current being stored in a loop. You can decide what you want to do with it. Most likely, you're going to have it decay exponentially. So every single synapse is going to have some given time constant. And that's determined by putting some resistor in that superconducting loop. So a synapse event occurs when a photon strikes a detector, adds current to that loop, it decays over time. That's the post-synaptic signal. Then you can process that in a dendritic tree. Bryce Primavera and I have a paper that we've submitted about that. For the more neuroscience-oriented people, there's a lot of dendritic processing, a lot of plasticity mechanisms you can implement with essentially exactly the same circuits. You have this one simple building block circuit that you can use for a synapse, for a dendrite, for the neuron cell body, for all the plasticity functions. It's all based on the same building block, just tweaking a couple parameters. So this basic building block has both an optical and an electrical component, and then you could just build arbitrary large systems with that. Close. You're not at fault for thinking that that's what I meant. What I should say is that if you want it to be a synapse, you tack a detector, a superconducting detector, onto the front of it. And if you want it to be anything else, there's no optical component. Got it. So at the front, optics in the front, electrical stuff in the back. Electrical, yeah, in the processing and in the output signal that it sends to the next stage of processing further. So the dendritic trees is electrical. It's all electrical. It's all electrical in the superconducting domain. For anybody who's up on their superconducting circuits, it's just based on a DC squid, the most ubiquitous, which is a circuit composed of two Josephson junctions. So it's a very bread and butter kind of thing. And then the only place where you go beyond that is the neuron cell body itself. It's receiving all these electrical inputs from the synapses or dendrites or however you've structured that particular unique neuron. And when it reaches its threshold, which occurs by driving a Josephson junction above its critical current, it produces a pulse of current which starts an amplification sequence, voltage amplification that produces light out of a transmitter. So one of our colleagues, Adam McConn and Sonia Buckley as well did a lot of work on the light sources and the amplifiers that drive the current and produce sufficient voltage to drive current through that now semiconducting part. So that light source is the semiconducting part of a neuron. And that, so the neuron has reached threshold. It produces a pulse of light. That light then fans out across a network of wave guides to reach all the downstream synaptic terminals that perform this process themselves. So it's probably worth explaining what a network of wave guides is because a lot of listeners aren't gonna know that. Look up the papers by Jeff Childs on this one, but basically light can be guided in a simple, basically wire of usually an insulating material. So silicon, silicon nitride, different kinds of glass, just like in a fiber optic, it's glass, silicon dioxide. That makes it a little bit big. We wanna bring these down. So we use different materials like silicon nitride, but basically just imagine a rectangle of some material that just goes and branches, forms different branch points that target different sub regions of the network. You can transition between layers of these. So now we're talking about building in the third dimension, which is absolutely crucial. So that's what wave guides are. Yeah, that's great. Why the third dimension is crucial? Okay, so yes, you were talking about what are some of the technical limitations. One of the things that I believe we have to grapple with is that our brains are miraculously compact. For the number of neurons that are in our brain, it sure does fit in a small volume, as it would have to if we're gonna be biological organisms that are resource limited and things like that. Any kind of hardware neuron is almost certainly gonna be much bigger than that if it is of comparable complexity, even whether it's based on silicon transistors. Okay, a transistor, seven nanometers, that doesn't mean a semiconductor-based neuron is seven nanometers. They're big. They require many transistors, different other things like capacitors and things that store charge. They end up being on the order of 100 microns by 100 microns, and it's difficult to get them down any smaller than that. The same is true for superconducting neurons, and the same is true if we're trying to use light for communication. Even if you're using electrons for communication, you have these wires where, okay, the size of an electron might be angstroms, but the size of a wire is not angstroms, and if you try and make it narrower, the resistance just goes up, so you don't actually win. To communicate over long distances, you need your wires to be microns wide, and it's the same thing for waveguides. Waveguides are essentially limited by the wavelength of light, and that's gonna be about a micron, so whereas compare that to an axon, the analogous component in the brain, which is 10 nanometers in diameter, something like that, they're bigger when they need to communicate over long distances, but grappling with the size of these structures is inevitable and crucial, and so in order to make systems of comparable scale to the human brain, by scale here I mean number of interconnected neurons, you absolutely have to be using the third spatial dimension, and that means on the wafer, you need multiple layers of both active and passive components. Active, I mean superconducting electronic circuits that are performing computations, and passive, I mean these waveguides that are routing the optical signals to different places, you have to be able to stack those. If you can get to something like 10 planes of each of those, or maybe not even 10, maybe five, six, something like that, then you're in business. Now you can get millions of neurons on a wafer, but that's not anywhere close to the brain scale. In order to get to the scale of the human brain, you're gonna have to also use the third dimension in the sense that entire wafers need to be stacked on top of each other with fiber optic communication between them, and we need to be able to fill a space the size of this table with stacked wafers, and that's when you can get to some 10 billion neurons like your human brain. And I don't think that's specific to the optoelectronic approach that we're taking. I think that applies to any hardware where you're trying to reach commensurate scale and complexity as the human brain. So you need that fractal stacking. So stacking on the wafer and stacking of the wafers, and then whatever the system that combines, this stacking of the tables with the wafers. And it has to be fractal all the way. You're exactly right, because that's the only way that you can efficiently get information from a small point to across that whole network. It has to have the power law connected. And photons are like optics throughout. Yeah, absolutely. Once you're at this scale, to me, it's just obvious. Of course you're using light for communication. You have fiber optics given to us from nature, so simple. The thought of even trying to do this, any kind of electrical communication just doesn't, it doesn't make sense to me. I'm not saying it's wrong. I don't know, but that's where I'm coming from. So let's return to loop neurons. Why are they called loop neurons? Yeah, the term loop neurons comes from the fact, like we've been talking about, that they rely heavily on these superconducting loops. So even in a lot of forms of digital computing with superconductors, storing a signal in a superconducting loop is a primary technique. In this particular case, it's just loops everywhere you look. So the strength of a synaptic weight is gonna be set by the amount of current circulating in a loop that is coupled to the synapse. So memory is implemented as current circulating in a superconducting loop. The coupling between, say, a synapse and a dendrite or a synapse in the neuron cell body occurs through loop coupling through transformers. So current circulating in a synapse is gonna induce current in a different loop, a receiving loop in the neuron cell body. So since all of the computation is happening in these flux storage loops, and they play such a central role in how the information is processed, how memories are formed, all that stuff, I didn't think too much about it. I just called them loop neurons because it rolls off the tongue a little bit better than superconducting optoelectronic neurons. Okay, so how do you design circuits for these loop neurons? That's a great question. There's a lot of different scales of design. So at the level of just one synapse, you can use conventional methods. They're not that complicated as far as superconducting electronics goes. It's just four Josephson junctions or something like that, depending on how much complexity you wanna add. So you can just directly simulate each component in SPICE. We've been- What's SPICE? It's Standard Electrical Simulation Software, basically. So you're just explicitly solving the differential equations that describe the circuit element. And then you can stack these things together in that simulation software to then build circuits. You can, but that becomes computationally expensive. So one of the things, when COVID hit, we knew we had to turn some attention to more things you can do at home in your basement or whatever. And one of them was computational modeling. So we started working on adapting, abstracting out the circuit performance so that you don't have to explicitly solve the circuit equations, which for Josephson junctions usually needs to be done on like a picosecond timescale and you have a lot of nodes in your circuit. So it results in a lot of differential equations that need to be solved simultaneously. We were looking for a way to simulate these circuits that is scalable up to networks of millions or so neurons is sort of where we're targeting right now. So we were able to analyze the behavior of these circuits. And as I said, it's based on these simple building blocks. So you really only need to understand this one building block. And if you get a good model of that, boom, it tiles. And you can change the parameters in there to get different behaviors and stuff, but it's all based on now it's one differential equation that you need to solve. So one differential equation for every synapse, dendrite or neuron in your system. And for the neuroscientists out there, it's just a simple leaky integrate and fire model, leaky integrator basically. The synapse is a leaky integrator, a dendrite is a leaky integrator. So I'm really fascinated by how this one simple component can be used to achieve lots of different types of dynamical activity. And to me, that's where scalability comes from. And also complexity as well. Complexity is often characterized by relatively simple building blocks connected in potentially simple or sometimes complicated ways and then emergent new behavior that was hard to predict from those simple elements. And that's exactly what we're working with here. So it's a very exciting platform, both from a modeling perspective and from a hardware manifestation perspective where we can hopefully start to have this test bed where we can explore things, not just related to neuroscience, but also related to other things that connected to other physics like critical phenomenon, Ising models, things like that. So you were asking how we simulate these circuits. It's at different levels and we've got the simple spice circuit stuff. That's no problem. And now we're building these network models based on this more efficient leaky integrator. So we can actually reduce every element to one differential equation and then we can also step through it on a much coarser time grid. So it ends up being something like a factor of a thousand to 10,000 speed improvement, which allows us to simulate, but hopefully up to millions of neurons. Whereas before we would have been limited to tens, a hundred, something like that. And just like simulating quantum mechanical systems with a quantum computer. So the goal here is to understand such systems. For me, the goal is to study this as a scientific physical system. I'm not drawn towards turning this into an enterprise at this point. I feel- Short-term applications that obviously make a lot of money is not necessarily a curiosity driver for you at the moment. Absolutely not. If you're interested in short-term making money, go with deep learning, use silicon microelectronics. If you wanna understand things like the physics of a fascinating system, or if you wanna understand something more along the lines of the physical limits of what can be achieved, then I think single photon communication, superconducting electronics is extremely exciting. What if I wanna use superconducting hardware at four Kelvin to mine Bitcoin? That's my main interest. That's the reason I wanted to talk to you today. I wanna, no, I don't know. What's Bitcoin? It's a, look it up on the internet. Somebody told me about it. I'm not sure exactly what it is. So, but let me ask nevertheless about applications to machine learning. Okay. So, what, like if you look at the scale of five, 10, 20 years is it possible to, before we understand the nature of human intelligence and general intelligence, do you think we'll start falling out of this exploration of neuromorphic systems ability to solve some of the problems that the machine learning systems of today can't solve? I'm really hesitant to over-promise. So, I really don't know. I also, I don't really understand machine learning in a lot of senses. I mean, machine learning from my perspective appears to require that you know precisely what your input is and also what your goal is. You usually have some objective function or something like that. And that's just, that's very limiting. I mean, of course, a lot of times that's the case, you know, there's a picture and there's a horse in it. So, you're done. But that's not a very interesting problem. I think when I think about intelligence, it's almost defined by the ability to handle problems where you don't know what your inputs are going to be. And you don't even necessarily know what you're trying to accomplish. I mean, I'm not sure what I'm trying to accomplish in this world. But- At all scales. Yeah, at all scales, right. I mean, so, and sometimes, so I'm more drawn to the underlying phenomena, the critical dynamics of this system, trying to understand how elements that you build into your hardware result in emergent, fascinating activity that was very difficult to predict, things like that. So, but I gotta be really careful because I think a lot of other people who, if they found themselves working on this project in my shoes, they would say, all right, what are all the different ways we can use this for machine learning? Actually, let me just definitely mention colleague at NIST, Mike Schneider, he's also very much interested, particularly in the superconducting side of things, using the incredible speed, power efficiency, also Ken Segal at Colgate, other people working on specifically the superconducting side of this for machine learning and deep feed-forward neural networks. There, the advantages are obvious. It's extremely fast. Yeah, so that's less on the nature of intelligence and more on various characteristics of this hardware that you can use for the basic computation as we know it today and communication. One of the things that Mike Schneider's working on right now is an image classifier at a relatively small scale. I think he's targeting that nine pixel problem where you can have three different characters and you just, you put in a nine pixel image and you classify it as one of these three categories. And that's gonna be really interesting to see what happens there. Because if you can show that even at that scale, you just put these images in and you get it out and he thinks he can do it, I forgot if it's a nanosecond or some extremely fast classification time, it's probably less, it's probably 100 picoseconds or something. There you have challenges though because the Josephson junctions themselves, the electronic circuit is extremely power efficient. Some orders of magnitude for something more than a transistor doing the same thing. But when you have to cool it down to four Kelvin, you pay a huge overhead just for keeping it cold even if it's not doing anything. So it has to work at large scale in order to overcome that power penalty, but that's possible. It's just, it's gonna have to get that performance. And this is sort of what you were asking about before is like how much better than silicon would it need to be? And the answer is, I don't know. I think if it's just overall better than silicon at a problem that a lot of people care about, maybe it's image classification, maybe it's face recognition, maybe it's monitoring credit transactions, I don't know. Then I think it will have a place. It's not gonna be in your cell phone, but it could be in your data center. So what about in terms of the data center? I don't know if you're paying attention to the various systems like Tesla recently announced Dojo, which is a large scale machine learning training system. That again, the bottleneck there is probably going to be communication between those systems. Is there something from your work on everything we've been talking about in terms of superconductive hardware that could be useful there? Oh, I mean, okay. Tomorrow, no. In the longterm, it could be the whole thing. It could be nothing. I don't know, but definitely, definitely. When you look at the, so I don't know that much about Dojo. My understanding is that that's new, right? That's just coming online. Well, I don't even know where. It hasn't come online. And when you announce big, sexy, so let me explain to you the way things work in- In the world out there. In the world of business and marketing, it's not always clear where you are on the coming online part of that. So I don't know where they are exactly, but the vision is from ground up to build a very, very large scale modular machine learning, ASIC, basically hardware that's optimized for training neural networks. And of course, there's a lot of companies that are small and big working on this kind of problem. The question is how to do it in a modular way that has very fast communication. The interesting aspect of Tesla is you have a company that at least at this time is so singularly focused on solving a particular machine learning problem and is making obviously a lot of money doing so because the machine learning problem happens to be involved with autonomous driving. And so you have a system that's driven by an application. And that's really interesting because you have maybe Google working on TPUs and so on. You have all these other companies with ASICs. They're usually more kind of always thinking general. So I like it when it's driven by a particular application because then you can really get to the, it's like, it's somehow if you just talk broadly about intelligence, you may not always get to the right solutions. It's nice to couple that sometimes with a specific clear illustration of something that requires general intelligence, which for me driving is one such case. I think you're exactly right. Sometimes just having that focus on that application brings a lot of people, focuses their energy and attention. I think that, so one of the things that's appealing about what you're saying is not just that the application is specific, but also that the scale is big. Big. And that the benefit is also huge. So- Financial anti-humanity. Right, right, right. Yeah, so I guess, let me just try to understand, is the point of this Dojo system to figure out the parameters that then plug into neural networks and then you don't need to retrain, you just make copies of a certain chip that has all the parameters established or? No, it's straight up retraining a large neural network over and over and over. So you have to do it once for every new car? No, no, no, you have to, so they do this interesting process, which I think is a process for machine learning, supervised machine learning systems, you're going to have to do, which is you have a system, you train your network once, it takes a long time, I don't know how long, but maybe a week to train. And then you deploy it on, let's say, about a million cars. I don't know what the numbers are. But that part, you just write software that updates some weights in a table and yeah, okay. But there's a loop back. Yeah, yeah, okay. Each of those cars run into trouble, rarely, but they catch the edge cases of the performance of that particular system and they send that data back and either automatically or by humans, that weird edge case data is annotated and then the network has to become smart enough to now be able to perform in those edge cases so it has to get retrained. There's clever ways of retraining different parts of that network, but for the most part, I think they prefer to retrain the entire thing. So you have this giant monster that kind of has to be retrained regularly. I think the vision with the dojo is to have a very large machine learning focused, driving focused supercomputer that then is sufficiently modular that could be scaled to other machine learning applications. But like, so they're not limiting themselves completely to this particular application, but this application is the way they kind of test this iterative process of machine learning. You make a system that's very dumb, deploy it, get the edge cases where it fails, make it a little smarter, it becomes a little less dumb, and that iterative process achieves something that you can call intelligent or is smart enough to be able to solve this particular application. So it has to do with training your own networks fast and training your own networks that are large. But also based on an extraordinary amount of diverse input. Data, yeah. And that's one of the things, so this does seem like one of those spaces where the scale of superconducting optoelectronics, the way that, so when you talk about the weaknesses, like I said, okay, well, you have to cool it down. At this scale, that's fine, because that's not too much of an added cost. Most of your power is being dissipated by the circuits themselves, not the cooling. And also you have one centralized kind of cognitive hub, if you will. And so when, if we're talking about putting a superconducting system in a car, that's questionable. Do you really want a cryostat in the trunk of every one of your car? It'll fit, it's not that big of a deal, but hopefully there's a better way, right? But since this is sort of a central supreme intelligence or something like that, and it needs to really have this massive data acquisition, massive data integration, I would think that that's where large-scale spiking neural networks with vast communication and all these things would have something pretty tremendous to offer. It's not gonna happen tomorrow. There's a lot of development that needs to be done. But we have to be patient with self-driving cars for a lot of reasons. We were all optimistic that they would be here by now. And okay, they are to some extent, but if we're thinking five or 10 years down the line, it's not unreasonable. One other thing, let me just mention that getting into self-driving cars and technologies that are using AI out in the world, this is something NIST cares a lot about. Elham Tabassi is leading up a much larger effort in AI at NIST than my little project. And really central to that mission is this concept of trustworthiness. So when you're going to deploy this neural network in every single automobile with so much on the line, you have to be able to trust that. So now how do we know that we can trust that? How do we know that we can trust the self-driving car or the supercomputer that trained it? There's a lot of work there. And there's a lot of that going on at NIST. And it's still early days. I mean, you're familiar with the problem and all that. But there's a fascinating dance in engineering with like safety critical systems. There's a desire in computer science, just recently talked to Don Knuth, to do for algorithms and for systems, for them to be provably correct or provably safe. And this is one other difference between humans and biological systems is we're not provably anything. And so there's some aspect of imperfection that we need to have built in, like robustness to imperfection be part of our systems, which is a difficult thing for engineers to contend with. They're very uncomfortable with the idea that you have to be okay with failure and almost engineer failure into the system. Mathematicians hate it too. But I think it was Turing who said something along the lines of, I can give you an intelligent system or I can give you a flawless system, but I can't give you both. And it's in sort of creativity and abstract thinking seem to rely somewhat on stochasticity and not having components that perform exactly the same way every time. This is where like the disagreement I have with, not disagreement, but a different view on the world. I'm with Turing. When I talk to robotic, robot colleagues, that sounds like I'm talking to robots, colleagues that are roboticists, the goal is perfection. And to me is like, no, I think the goal should be imperfection that's communicated. And through the interaction between humans and robots, that imperfection becomes a feature, not a bug. Like together as a scene, as a system, the human and the robot together are better than either of them individually, but the robot itself is not perfect in any way. Of course, there's a bunch of disagreements, including with Mr. Elon about, to me autonomous driving is fundamentally a human robot interaction problem, not a robotics problem. To Elon, it's a robotics problem. That's actually an open and fascinating question, whether humans can be removed from the loop completely. We've talked about a lot of fascinating chemistry and physics and engineering, and we're always running up against this issue that nature seems to dictate what's easy and what's hard. So you have this cool little paper that I'd love to just ask you about. It's titled, Does Cosmological Evolution Select for Technology? So in physics, there's parameters that seem to define the way our universe works, that physics works, that if it worked any differently, we would get a very different world. So it seems like the parameters are very fine tuned to the kind of physics that we see. All the beautiful E equals MC squared, that we get these nice, beautiful laws. It seems like very fine tuned for that. So what you argue in this article is, it may be that the universe has also fine tuned its parameters that enable the kind of technological innovation that we see, that technology that we see. Can you explain this idea? Yeah, I think you've introduced it nicely. Let me just try to say a few things in my language. Leah, what is this fine tuning problem? So physicists have spent centuries trying to understand the system of equations that govern the way nature behaves, the way particles move and interact with each other. And as that understanding has become more clear over time, it became sort of evident that it's all well adjusted to allow a universe like we see, very complex, this large, long lived universe. And so one answer to that is, well, of course it is, because we wouldn't be here otherwise. But I don't know, that's not very satisfying. That's sort of, that's what's known as the weak anthropic principle. It's a statement of selection bias. We can only observe a universe that is fit for us to live in. So what does it mean for a universe to be fit for us to live in? Well, the pursuit of physics, it is based partially on coming up with equations that describe how things behave and interact with each other. But in all those equations you have, so there's the form of the equation, sort of how different fields or particles move in space and time. But then there are also the parameters that just tell you sort of the strength of different couplings, how strongly does a charged particle couple to the electromagnetic field or masses? How strongly does a particle couple to the Higgs field or something like that? And those parameters that define, not the general structure of the equations, but the relative importance of different terms, they seem to be every bit as important as the structure of the equations themselves. And so I forget who it was, somebody when they were working through this and trying to see, okay, if I adjust the parameter, this parameter over here, call it the, say the fine structure constant, which tells us the strength of the electromagnetic interaction. Oh boy, I can't change it very much, otherwise nothing works. The universe sort of doesn't, it just pops into existence and goes away in a nanosecond or something like that. And somebody had the phrase, this looks like a put-up job, meaning every one of these parameters was dialed in. It's arguable how precisely they have to be dialed in, but dialed in to some extent, not just in order to enable our existence, that's a very anthropocentric view, but to enable a universe like this one. So, okay, maybe I think the majority position of working physicists in the field is, it has to be that way in order for us to exist. We're here, we shouldn't be surprised that that's the way the universe is. And I don't know, for a while, that never sat well with me, but I just kind of moved on because there are things to do and a lot of exciting work. It doesn't depend on resolving this puzzle, but as I started working more with technology, getting into the more recent years of my career, particularly when I started, after having worked with silicon for a long time, which was kind of eerie on its own, but then when I switched over to superconductors, I was just like, this is crazy. It's just absolutely astonishing that our universe gives us superconductivity. It's one of the most beautiful physical phenomena, and it's also extraordinarily useful for technology. So you can argue that the universe has to have the parameters it does for us to exist because we couldn't be here otherwise. But why does it give us technology? Why does it give us silicon that has this ideal oxide that allows us to make a transistor without trying that hard? That can't be explained by the same anthropic reasoning. Yeah, so it's asking the why question. I mean, a slight natural extension of that question is, I wonder if the parameters were different if we would simply have just another set of paintbrushes to create totally other things that wouldn't look like anything like the technology of today, but would nevertheless have incredible complexity, which is if you sort of zoom out and start defining things not by like how many batteries it needs and whether it can make toast, but more like how much complexity is within the system or something like that. Well, yeah, you can start to quantify things. You're exactly right. So nowhere am I arguing that in all of the vast parameter space of everything that could conceivably exist in the multiverse of nature, there is this one point in parameter space where complexity arises. I doubt it. That would be a shameful waste of resources, it seems. But it might be that we reside at one place in parameter space that has been adapted through an evolutionary process to allow us to make certain technologies that allow our particular kind of universe to arise and sort of achieve the things it does. See, I wonder if nature in this kind of discussion, if nature is a catalyst for innovation or if it's a ceiling for innovation. So like, is it going to always limit us? Like, you're talking about Silicon. Is it just make it super easy to do awesome stuff in a certain dimension, but we could still do awesome stuff in other ways, it'll just be harder? Or does it really set the maximum we can do? That's a good subject to discuss. I guess I feel like we need to lay a little bit more groundwork. So I want to make sure that I introduce this in the context of Lee Smolin's previous idea. So who is Lee Smolin and what kind of ideas does he have? Okay, Lee Smolin is a theoretical physicist who back in the late 1980s published a paper in the early 1990s introduced this idea of cosmological natural selection, which argues that the universe did evolve. So his paper was called, Did the Universe Evolve? And I gave myself the liberty of titling my paper, Does Cosmological Evolution Select for Technology? In reference to that. So he introduced that idea decades ago. Now he primarily works on quantum gravity, loop quantum gravity, other approaches to unifying quantum mechanics with general relativity, as you can read about in his most recent book, I believe, and he's been on your show as well. So, but I want to introduce this idea of cosmological natural selection, because I think that is one of the core ideas that could change our understanding of how the universe got here, our role in it, what technology is doing here. But there's a couple more pieces that need to be set up first. So the beginning of our universe is largely accepted to be the Big Bang. And what that means is if you look back in time by looking far away in space, you see that everything used to be at one point, and it expanded away from there. There was an era in the evolutionary process of our universe that was called inflation. And this idea was developed primarily by Alan Guth and others, Andre Linde and others in the 80s. And this idea of inflation is basically that when a singularity begins this process of growth, there can be a temporary stage where it just accelerates incredibly rapidly. And based on quantum field theory, this tells us that this should produce matter in precisely the proportions that we find of hydrogen and helium in the Big Bang, lithium too, lithium also, and other things too. So the predictions that come out of Big Bang inflationary cosmology have stood up extremely well to empirical verification, the cosmic microwave background, things like this. So most scientists working in the field think that the origin of our universe is the Big Bang. And I base all my thinking on that as well. I'm just laying this out there so that people understand that where I'm coming from is an extension, not a replacement of existing well-founded ideas. In a paper, I believe it was 1986 with Alan Guth and another author, Fahy, they wrote that a Big Bang, I don't remember the exact quote, a Big Bang is inextricably linked with a black hole. This singularity that we call our origin is mathematically indistinguishable from a black hole. They're the same thing. And Lee Smolin based his thinking on that idea, I believe. I don't mean to speak for him, but this is my reading of it. So what Lee Smolin will say is that a black hole in one universe is a Big Bang in another universe. And this allows us to have progeny, offspring. So a universe can be said to have come before another universe. And very crucially, Smolin argues, I think this is potentially one of the great ideas of all time, that's my opinion, that when a black hole forms, it's not a classical entity, it's a quantum gravitational entity. So it is subject to the fluctuations that are inherent in quantum mechanics. The properties, what we're calling the parameters that describe the physics of that system are subject to slight mutations. So that the offspring universe does not have the exact same parameters defining its physics as its parent universe. They're close, but they're a little bit different. And so now you have a mechanism for evolution, for natural selection. So there's mutations, so there's, and then if you think about the DNA of the universe are the basic parameters that govern its laws. Exactly, so what Smolin said is, our universe results from an evolutionary process that can be traced back some, he estimated 200 million generations. Initially, there was something like a vacuum fluctuation that produced through random chance, a universe that was able to reproduce just once. So now it had one offspring. And then over time, it was able to make more and more until it evolved into a highly structured universe with a very long lifetime, with a great deal of complexity. And importantly, especially importantly for Lee Smolin, stars, stars make black holes. Therefore, we should expect our universe to be optimized, have its physical parameters optimized to make very large numbers of stars, because that's how you make black holes, and black holes make offspring. So we expect the physics of our universe to have evolved to maximize fecundity, the number of offspring. And the way Lee Smolin argues you do that is through stars that the biggest ones die in these core collapse supernova that make a black hole and a child. Okay, first of all, I agree with you that this is back to our fractal view of everything from intelligence to our universe. That is very compelling and a very powerful idea that unites the origin of life and perhaps the origin of ideas and intelligence. So from a Dawkins perspective here on Earth, the evolution of those, and then the evolution of the laws of physics that led to us. I mean, it's beautiful. And then you stacking on top of that, that maybe we are one of the offspring. Right, okay, so before getting into where I'd like to take that idea, let me just a little bit more groundwork. There is this concept of the multiverse, and it can be confusing. Different people use the word multiverse in different ways. In the multiverse that I think is relevant to picture when trying to grasp Lee Smolin's idea, essentially every vacuum fluctuation can be referred to as a universe. It occurs, it borrows energy from the vacuum for some finite amount of time, and it evanesces back into the quantum vacuum. And ideas of Guth before that, and Andre Linde with eternal inflation aren't that different, that you would expect nature due to the quantum properties of the vacuum, which we know exist. They're measurable through things like the Casimir effect and others. You know that there are these fluctuations that are occurring. What Smolin is arguing is that there is this extensive multiverse, that this universe, what we can measure and interact with, is not unique in nature. It's just our residence. It's where we reside. And there are countless, potentially infinity, other universes, other entire evolutionary trajectories that have evolved into things like what you were mentioning a second ago with different parameters and different ways of achieving complexity and reproduction and all that stuff. So it's not that the evolutionary process is a funnel towards this endpoint, not at all. Just like the biological evolutionary process that has occurred within our universe is not a unique route toward achieving one specific chosen kind of species. No, we have extraordinary diversity around us. That's what evolution does. And for any one species like us, it might feel like we're at the center of this process. We're the destination of this process, but we're just one of the many nearly infinite branches of this process. And I suspect it is exactly infinite. I mean, I just can't understand how, with this idea, you can ever draw a boundary around and say, no, the multiverse has 10 to the one quadrillion components, but not infinity. I don't know. Well, yeah, I have cognitively incapable, as I think all of us are, in truly understanding the concept of infinity. And the concept of nothing as well. And nothing. But also the concept of a lot is pretty difficult. I can count, I run out of fingers at a certain point, and then you're screwed. And when you're wearing shoes and you can't even get down to your toes, it's like. It's like, all right, 1,000, fine, a million, is that what? And then it gets crazier and crazier. Right, right. So this particular, so when we say technology, by the way, I mean, there's some, not to over-romanticize the thing, but there is some aspect about this branch of ours that allows us to, for the universe to know itself. Yes, yes. So to have little conscious cognitive fingers that are able to feel, like to scratch the head. Right, right, right. To be able to construct E equals MC squared, and to introspect, to start to gain some understanding of the laws that govern it. Isn't that kind of amazing? Okay, I'm just human, but it feels like that, if I were to build a system that does this kind of thing, that evolves laws of physics, that evolves life, that evolves intelligence, that my goal would be to come up with things that are able to think about itself, right? Aren't we kind of close to the design specs, the destination? We're pretty close, I don't know. I mean, I'm spending my career designing things that I hope will think about themselves, so maybe you and I aren't too far apart on that one. But then maybe that problem is a lot harder than we imagine. Maybe we need to. Let's not get too far, because I wanna emphasize something that what you're saying is, isn't it fascinating that the universe evolved something that can be conscious, reflect on itself? But Lee Smolin's idea didn't take us there, remember? It took us to stars. Lee Smolin has argued, I think, right, on almost every single way that cosmological natural selection could lead to a universe with rich structure, and he argued that the structure, the physics of our universe is designed to make a lot of stars so that they can make black holes. But that doesn't explain what we're doing here. In order for that to be an explanation of us, what you have to assume is that once you made that universe that was capable of producing stars, life, planets, all these other things, we're along for the ride. They got lucky. We're kind of arising, growing up in the cracks, but the universe isn't here for us. We're still kind of a fluke in that picture. And I can't, I don't necessarily have like a philosophical opposition to that stance. It's just not, okay, so I don't think it's complete. So it seems like whatever we got going on here to you, it seems like whatever we have here on Earth seems like a thing you might want to select for in this whole big process. Exactly, so if what you are truly, if your entire evolutionary process only cares about fecundity, it only cares about making offspring universes because then there's gonna be the most of them in that local region of hyperspace, which is the set of all possible universes, let's say, you don't care how those universes are made. You know they have to be made by black holes. This is what inflationary theory tells us. The Big Bang tells us that black holes make universes. But what if there was a technological means to make universes? Stars require a ton of matter because they're not thinking very carefully about how you make a black hole. They're just using gravity, you know? But if we devise technologies that can efficiently compress matter into a singularity, it turns out that if you can compress about 10 kilograms into a very small volume, that will make a black hole that is likely, highly probable to inflate into its own offspring universe. This is according to calculations done by other people who are professional quantum theorists, quantum field theorists, and I hope I am grasping what they're telling me correctly. I am somewhat of a translator here. But so that's the position that is particularly intriguing to me, which is that what might have happened is that, okay, this particular branch on the vast tree of evolution, cosmological evolution now we're talking about, not biological evolution within our universe, but cosmological evolution, went through exactly the process that Lee Smolin described. Got to the stage where stars were making lots of black holes, but then continued to evolve and somehow bridge that gap and made intelligence, and intelligence capable of devising technologies because technologies, an intelligent species working in conjunction with technologies could then produce even more. Yeah, more efficiently, more like faster and better and more different, then you start to have different kind of mechanisms and mutation perhaps, all that kind of stuff. And so if you do a simple calculation that says, all right, if I want to, we know roughly how many core collapse supernova, supernovae have resulted in black holes in our galaxy since the beginning of the universe, and it's something like a billion. So then you would have to estimate that it would be possible for a technological civilization to produce more than a billion black holes with the energy and matter at their disposal. And so one of the calculations in that paper, back of the envelope, but I think revealing nonetheless, is that if you take a relatively common asteroid, something that's about a kilometer in diameter, what I'm thinking of is just scrap material laying around in our solar system and break it up into 10 kilogram chunks and turn each of those into a universe, then you would have made at least a trillion black holes outpacing the star production rate by some three orders of magnitude. That's one asteroid. So now if you envision an intelligent species that would potentially have been devised initially by humans but then based on superconducting up to electronic networks, no doubt, and they go out and populate, they don't have to fill the galaxy, they just have to get out to the asteroid belt. They could potentially dramatically outpace the rate at which stars are producing offspring universes. And then wouldn't you expect that that's where we came from instead of a star? Yeah, so you have to somehow become masters of gravity. So like what, or generate- Not necessarily gravity. So stars make black holes with gravity, but any force that can make the energy density can compactify matter to produce a great enough energy density can form a singularity. It doesn't, it would not likely be gravity. It's the weakest force. You're more likely to use something like the technologies that we're developing for fusion, for example. So I don't know, the large ignition facility recently blasted a pellet with 100 really bright lasers and caused that to get dense enough to engage in nuclear fusion. So something more like that, or a tokamak with a really hot plasma, I'm not sure, something. I don't know exactly how it would be done. I do like the idea of that, especially just been reading a lot about gravitational waves and, you know, the fact that us humans with our technological capabilities, one of the most impressive technological accomplishments of human history is LIGO, being able to precisely detect gravitational waves. I'm particularly find appealing the idea that other alien civilizations from very far distances communicate with gravity, with gravitational waves, because as you become greater and greater master of gravity, which seems way out of reach for us right now, maybe that seems like a effective way of sending signals, especially if your job is to manufacture black holes. Right. So let me ask there, whatever, I mean, broadly thinking, because we tend to think other alien civilizations would be very human-like, but if we think of alien civilizations out there as basically generators of black holes, however they do it, because they get stars, do you think there's a lot of them in our particular universe out there? In our universe? Well, okay, let me ask, okay, this is great. Let me ask a very generic question, and then let's see how you answer it, which is how many alien civilizations are out there? If the hypothesis that I just described is on the right track, it would mean that the parameters of our universe have been selected so that intelligent civilizations will occur in sufficient numbers so that if they reach something like supreme technological maturity, let's define that as the ability to produce black holes, then that's not a highly improbable event. It doesn't need to happen often, because as I just described, if you get one of them in a galaxy, you're gonna make more black holes than the stars in that galaxy. But there's also not a super strong motivation, well, it's not obvious that you need them to be ubiquitous throughout the galaxy. So one of the things that I try to emphasize in that paper is that given this idea of how our parameters might have been selected, it's clear that it's a series of trade-offs, right? If you make, I mean, in order for intelligent life of our variety or anything resembling us to occur, you need a bunch of stuff. You need stars, so that's right back to Smolin's roots of this idea, but you also need water to have certain properties. You need things like the rocky planets, like the Earth to be within the habitable zone. All these things that you start talking about in the field of astrobiology, trying to understand life in the universe, but you can't overemphasize, you can't tune the parameters so precisely to maximize the number of stars or to give water exactly the properties or to make rocky planets like Earth the most numerous. You have to compromise on all these things. And so I think the way to test this idea is to look at what parameters are necessary for each of these different subsystems, and I've laid out a few that I think are promising. There could be countless others, and see how changing the parameters makes it more or less likely that stars would form and have long lifetimes, or that rocky planets in the habitable zone are likely to form, all these different things. So we can test how much these things are in a tug of war with each other. And the prediction would be that we kind of sit at the central point where if you move the parameters too much, stars aren't stable, or life doesn't form, or technology's infeasible, because life alone, at least the kind of life that we know of, cannot make black holes. We don't have the, well, I'm speaking for myself. You're a very fit, strong person, but it might be possible for you, but not for me to compress matter. So we need these technologies, but we don't know, we have not been able to quantify yet how finely adjusted the parameters would need to be in order for silicon to have the properties it does. Okay, this is not directly speaking to what you're saying. You're getting to the Fermi paradox, which is where are they? Where are the life forms out there? How numerous are they? That sort of thing. What I'm trying to argue is that if this framework is on the right track, a potentially correct explanation for our existence, we, it doesn't necessarily predict that intelligent civilizations are just everywhere, because even if you just get one of them in a galaxy, which is quite rare, it could be enough to dramatically increase the fecundity of the universe as a whole. Yeah, and I wonder, once you start generating the offspring for universes, black holes, how that has effect on the, what kind of effect does it have on the other candidates, civilizations within that universe? Maybe as a destructive aspect, or there could be some arguments about once you have a lot of offspring, that that just quickly accelerates to where the other ones can't even catch up. It could, but I guess if you want me to put my chips on the table or whatever, I think I come down more on the side that intelligent life civilizations are rare. And I guess I follow Max Tegmark here. And also there's a lot of papers coming out recently in the field of astrobiology that are seeming to say, all right, you just work through the numbers on some modified Drake equation or something like that. And it looks like it's not improbable. You wouldn't, you shouldn't be surprised that an intelligent species has arisen in our galaxy. But if you think there's one, the next solar system over, it's highly improbable. So I can see that the number, the probability of finding a civilization in a galaxy, maybe it's most likely that you're gonna find one to a hundred or something, but okay, now it's really important to put a time window on that, I think, because does that mean in the entire lifetime of the galaxy before it, so for in our case, before we run into Andromeda, I think it's highly probable, I shouldn't say I think, it's tempting to believe that it's highly probable that in that entire lifetime of your galaxy, you're gonna get at least one intelligent species, maybe thousands or something like that. But it's also, I think, a little bit naive to think that they're going to coincide in time and we'll be able to observe them. And also, if you look at the span of life on Earth, the Earth history, it was surprising to me to kind of look at the amount of time, first of all, the short amount of time there's no life is surprising. Life sprang up pretty quickly. It's cellular, single cell. But that's the point I'm trying to make, is so much of life on Earth was just single cell organisms. Like most of it, most of it was boring bacteria type of stuff. Well, bacteria are fascinating, but I take your point. No, I get it. I mean, no offense to them. But this kind of, speaking from the perspective of your paper of something that's able to generate technology as we kind of understand it, that's a very short moment in time relative to that full history of life on Earth. And maybe our universe is just saturated with bacteria like humans, but not the special extra AGI superhumans, that those are very rare. And once those spring up, everything just goes to, like it accelerates very quickly. Yeah, we just don't have enough data to really say, but I find this whole subject extremely engaging. I mean, there's this concept, I think it's called the rare Earth hypothesis, which is that basically stating that, okay, microbes were here right away after the Hadean era where we were being bombarded. Well, after, yeah, bombarded by comets, asteroids, things like that, and also after the moon formed. So once things settled down a little bit, in a few hundred million years, you have microbes everywhere. And it could have been, we don't know exactly when, it could have been remarkably brief that that took. So it does indicate that, okay, life forms relatively easily. I think that alone is sort of a checker on the scale for the argument that the parameters that allow even microbial life to form are not just a fluke. But anyway, that aside, yes, then there was this long dormant period, not dormant, things were happening, but important things were happening for some two and a half billion years or something after the metabolic process that releases oxygen was developed, then basically the planet's just sitting there getting more and more oxygenated, more and more oxygenated until it's enough that you can build these large, complex organisms. And so the rare Earth hypothesis would argue that the microbes are common in everywhere, in any planet that's roughly in the habitable zone and has some water on it's probably gonna have those. But then getting to this Cambrian explosion that happened some between five and 600 million years ago, that's rare. And I buy that, I think that is rare. So if you say how much life is in our galaxy, I think that's probably the right answer is that microbes are everywhere. Cambrian explosion is extremely rare. And then, but the Cambrian explosion kind of went like that where within a couple tens or a hundred million years, all of these body plans came into existence and basically all of the body plans that are now in existence on the planet were formed in that brief window and we've just been shuffling around since then. So then what caused humans to pop out of that? I mean, that could be another extremely rare threshold that a planet roughly in the habitable zone with water is not guaranteed to cross. To me, it's fascinating for being humble, like the humans cannot possibly be the most amazing thing that such, if you look at the entirety of the system, that at least small and you paint, that cannot possibly be the most amazing thing that process generates. So like if you look at the evolution, what's the equivalent in the cosmological evolution and its selection for technology, the equivalent of the human eye or the human brain? Universes that are able to do some like, they don't need the damn stars. They're able to just do some incredible generation of complexity fast on scale, like much more than, if you think about, it's like most of our universe is pretty freaking boring. There's not much going on. There's a few rocks flying around and there's some like apes that are just like doing podcasts on some weird planet. It just seems very inefficient. If you think about like the amazing thing in the human eye, the visual cortex can do, the brain, the nervous, everything that makes us more powerful than single cell organisms, like if there's an equivalent of that for universes, like the richness of physics that could be expressed through a particular set of parameters. Like for me, I'm a, so from a computer science perspective, huge fan of cellular automata, which is a nice sort of pretty visual way to illustrate how different laws can result in drastically different levels of complexity. So like, it's like, yeah, okay. So we're all like celebrating, look, our little cellular automata is able to generate pretty triangles and squares and therefore we achieve general intelligence. And then there'll be like some bad-ass Chuck Norris type, like universal Turing machine type of cellular automata. They're able to generate other cellular automata and that does any arbitrary level of computation off the bat. Like those have to then exist. And then we're just like, we're just, we'll be forgotten is the story. This podcast just entertains a few other apes for a few months. Well, I'm kind of surprised to hear your cynicism. No, I'm very, I- I usually think of you as like one who celebrates humanity in all its forms and things like that. And I guess I just, I don't, I see it the way you just described. I mean, okay, we've been here for 13.7 billion years and you're saying, gosh, that's a long time. Let's get on with the show already. Some other universe could have kicked our butt by now, but that's putting a characteristic time. I mean, why is 13.7 billion a long time? I mean, compared to what? I guess, so when I look at our universe, I see this extraordinary hierarchy that has developed over that time. So at the beginning, it was a chaotic mess of, you know, some plasma and nothing interesting going on there and then even for the first stars to form, that a lot of really interesting evolutionary processes had to occur by evolutionary in that sense. I just mean taking place over extended periods of time and structures are forming then. And then it took that first generation of stars in order to produce the metals that then can more efficiently produce another generation of stars. We're only the third generation of stars. So we might still be pretty quick to the game here. But I don't think, I don't, okay, so then you have these stars, now you have solar systems. On those solar systems, you have rocky worlds, you have gas giants, like all this complexity. And then you start getting life and the complexity that's evolved through the evolutionary process in life forms is just, it's not a letdown to me. Just some of it. Some of it is like, some of the planets is like icy, it's like different flavors of ice cream. They're icy, but there might be water underneath. All kinds of life forms, some volcanoes, all kinds of weird stuff. No, no, I don't, I think it's beautiful. I think our life is beautiful and I think it was designed that, by design, the scarcity of the whole thing. I think mortality, as terrifying as it is, is fundamental to the whole reason we enjoy everything. No, I think it's beautiful. I just think that all of us conscious beings, in the grand scheme of basically, at every scale, will be completely forgotten. Well, that's true. I think everything is transient and that would go back to maybe something more like Lao Tzu, the Tao Te Ching or something, where it's like, yes, there is nothing but change. There is nothing but emergence and dissolve and that's it. But I just, in this picture of this hierarchy that's developed, I don't mean to say that now it gets to us and that's the pinnacle. In fact, I think at a high level, the story I'm trying to tease out in my research is about, okay, well, so then what's the next level of hierarchy? And if it's, okay, we're kind of pretty smart. I mean, talking about people like Lee Small and Alan Guth, Max Tegmark, okay, we're really smart. Talking about me, okay, we're kind of, we can find our way to the grocery store or whatever, but- Sometimes. But what's next? You know, I mean, what if there's another level of hierarchy that grows on top of us that is even more profoundly capable? And I mean, we've talked a lot about superconducting sensors. Imagine these cognitive systems far more capable than us residing somewhere else in the solar system off of the surface of the earth, where it's much darker, much colder, much more naturally suited to them. And they have these sensors that can detect single photons of light from radio waves out to all across the spectrum to gamma rays and just see the whole universe. And they just live in space with these massive collection optics so that they, what do they do? They just look out and experience that vast array of what's being developed. And if you're such a system, presumably you would do some things for fun. And the kind of fun thing I would do, as somebody who likes video games, is I would create and maintain and observe something like earth. So in some sense, we're like all what players on a stage for this superconducting cold computing system out there. I mean, all of this is fascinating to think. The fact that you're actually designing systems here on earth, they're trying to push this technological at the very cutting edge and also thinking about how does the evolution of physical laws lead us to the way we are. It's fascinating. That coupling is fascinating. It's like the ultimate rigorous application of philosophy to the rigorous application of engineering. So Jeff, you're one of the most fascinating. I'm so glad. I did not know much about you except through your work. And I'm so glad we got this chance to talk here. One of the best explainers of exceptionally difficult concepts. And you're also, speaking of like fractal, you're able to function intellectually at all levels of the stack, which I deeply appreciate. This was really fun. You're a great educator, a great scientist. It's an honor that you would spend your valuable time with me. It's an honor that you would spend your time with me as well. Thanks, Jeff. Thanks for listening to this conversation with Jeff Shainlein. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from the great John Carmack, who surely will be a guest on this podcast soon. Because of the nature of Moore's law, anything that an extremely clever graphics programmer can do at one point can be replicated by a merely competent programmer some number of years later. Thank you for listening and hope to see you next time.

https://youtu.be/EwueqdgIvq4

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Gilbert Strang: Linear Algebra, Teaching, and MIT OpenCourseWare | Lex Fridman Podcast #52

The following is a conversation with Gilbert Strang. He's a professor of mathematics at MIT and perhaps one of the most famous and impactful teachers of math in the world. His MIT OpenCourseWare lectures on linear algebra have been viewed millions of times. As an undergraduate student, I was one of those millions of students. There's something inspiring about the way he teaches. There's that once calm, simple, and yet full of passion for the elegance inherent to mathematics. I remember doing the exercises in his book, Introduction to Linear Algebra, and slowly realizing that the world of matrices, of vector spaces, of determinants and eigenvalues, of geometric transformations, and matrix decompositions, reveal a set of powerful tools in the toolbox of artificial intelligence. From signals to images, from numerical optimization to robotics, computer vision, deep learning, computer graphics, and everywhere outside AI, including, of course, a quantum mechanical study of our universe. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. This podcast is supported by ZipRecruiter. Hiring great people is hard, and to me, is the most important element of a successful mission-driven team. I've been fortunate to be a part of, and to lead, several great engineering teams. The hiring I've done in the past was mostly through tools that we built ourselves, but reinventing the wheel was painful. ZipRecruiter is a tool that's already available for you. It seeks to make hiring simple, fast, and smart. For example, Codable co-founder Gretchen Huebner used ZipRecruiter to find a new game artist to join her education tech company. By using ZipRecruiter screening questions to filter candidates, Gretchen found it easier to focus on the best candidates, and finally hiring the perfect person for the role in less than two weeks from start to finish. ZipRecruiter, the smartest way to hire. See why ZipRecruiter is effective for businesses of all sizes by signing up, as I did, for free at ziprecruiter.com slash lexpod. That's ziprecruiter.com slash lexpod. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin. Most Bitcoin exchanges take days for bank transfer to become investable. Through Cash App, it takes seconds. Cash App also has a new investing feature. You can buy fractions of a stock, which to me is a really interesting concept. So you can buy one dollar's worth, no matter what the stock price is. Brokerage services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App to support one of my favorite organizations that many of you may know and have benefited from called FIRST, best known for their FIRST Robotics and LEGO competitions. They educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating on Charity Navigator, which means the donated money is used to maximum effectiveness. When you get Cash App from the App Store or Google Play and use code LEXPODCAST, you'll get $10 and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now, here's my conversation with Gilbert Strang. How does it feel to be one of the modern day rock stars of mathematics? I don't feel like a rock star. That's kind of crazy for an old math person. But it's true that the videos in linear algebra that I made way back in 2000, I think, have been watched a lot. And well, partly the importance of linear algebra, which I'm sure you'll ask me and give me a chance to say that linear algebra as a subject has just surged in importance. But also, it was a class that I taught a bunch of times, so I kind of got it organized and enjoyed doing it. It was just the videos were just the class. So they're on OpenCourseWare and on YouTube and translated. That's fun. But there's something about that chalkboard and the simplicity of the way you explain the basic concepts in the beginning. To be honest, when I went to undergrad... You didn't do linear algebra, probably. Of course I didn't do linear algebra. You did. Yeah, yeah, yeah, of course. But before going through the course at my university, I was going through OpenCourseWare. You were my instructor for linear algebra. Oh, I see. Right, yeah. I mean, we were using your book. And I mean, the fact that there is thousands, you know, hundreds of thousands, millions of people that watch that video, I think that's... Yeah....that's really powerful. So how do you think the idea of putting lectures online, what really MIT OpenCourseWare has innovated? That was a wonderful idea. You know, I think the story that I've heard is the committee was appointed by the president, President Vest at that time, a wonderful guy. And the idea of the committee was to figure out how MIT could make... be like other universities, market the work we were doing. And then they didn't see a way. And after a weekend, and they had an inspiration, came back to the President Vest and said, what if we just gave it away? And he decided that was okay, good idea. So... You know, that's a crazy idea. That's... Yeah. If we think of a university as a thing that creates a product... Yes....isn't knowledge... Right....the, you know, the kind of educational knowledge isn't the product and giving that away. Yeah. Are you surprised that you went through... The result that he did it? Well, knowing a little bit President Vest, it was like him, I think. And it was really the right idea, you know. MIT is a kind of, it's known for being high level technical things. And this is the best way we can say, tell, we can show what MIT really is like. Because in my case, those 1806 videos are just teaching the class. They were there in 26-100. They're kind of fun to look at. People write to me and say, oh, you've got a sense of humor, but I don't know where that comes through. Somehow I've been friendly with the class. I like students. And linear algebra, we got to give this subject most of the credit. It really has come forward in importance in these years. So let's talk about linear algebra a little bit, because it is such a, it's both a powerful and a beautiful subfield of mathematics. So what's your favorite specific topic in linear algebra, or even math in general, to give a lecture on, to convey, to tell a story, to teach students? Okay. Well, on the teaching side, so it's not deep mathematics at all, but I'm kind of proud of the idea of the four subspaces, the four fundamental subspaces, which are, of course, known before, long before my name for them. But- Can you go through them? Can you go through the four subspaces? Sure I can. Yeah. So the first one to understand is, so the matrix, maybe I should say the matrix. What is the matrix? What's a matrix? Well, so we have a rectangle of numbers. So it's got n columns, got a bunch of columns, and also got m rows, let's say. And the relation between, so of course the columns and the rows, it's the same numbers. So there's got to be connections there, but they're not simple. The columns might be longer than the rows, and they're all different, the numbers are mixed up. First space to think about is, take the columns, so those are vectors, those are points in n dimensions. What's a vector? So a physicist would imagine a vector, or might imagine a vector as a arrow in space, or the point it ends at in space. For me, it's a column of numbers. You often think of, this is very interesting in terms of linear algebra, in terms of a vector. You think a little bit more abstract than how it's very commonly used, perhaps. You think this arbitrary multidimensional space. Yeah, right away I'm in high dimensions. In dreamland. Yeah, that's right. In the lecture, I try to, so if you think of two vectors in 10 dimensions, I'll do this in class, and I'll readily admit that I have no good image in my mind of a vector, of a arrow in 10 dimensional space, but whatever. You can add one bunch of 10 numbers to another bunch of 10 numbers, so you can add a vector to a vector, and you can multiply a vector by three, and that's, if you know how to do those, you've got linear algebra. You know, 10 dimensions, there's this beautiful thing about math, if we look at string theory, and all these theories which are really fundamentally derived through math, but are very difficult to visualize. How do you think about the things, like a 10 dimensional vector, that we can't really visualize? And yet, math reveals some beauty underlying our world in that weird thing we can't visualize. How do you think about that difference? Well, probably, I'm not a very geometric person, so I'm probably thinking in three dimensions, and the beauty of linear algebra is that it goes on to 10 dimensions with no problem. I mean, that if you're just seeing what happens if you add two vectors in 3D, yeah, then you can add them in 10D. You're just adding the 10 components. So, I can't say that I have a picture, but yet I try to push the class to think of a flat surface in 10 dimensions, so a plane in 10 dimensions. And so, that's one of the spaces. Take all the columns of the matrix, take all their combinations, so much of this column, so much of this one, then if you put all those together, you get some kind of a flat surface that I call a vector space, space of vectors. And my imagination is just seeing like a piece of paper in 3D. But anyway, so that's one of the spaces. That's space number one, the column space of the matrix. And then there's the row space, which is, as I said, different, but came from the same numbers. So, we got the column space, all combinations of the columns, and then we got the row space, all combinations of the rows. So, those words are easy for me to say, and I can't really draw them on a blackboard, but I try with my thick chalk. Everybody likes that railroad chalk, and me too. I wouldn't use anything else now. And then the other two spaces are perpendicular to those. So, like if you have a plane in 3D, just a plane is just a flat surface in 3D, then perpendicular to that plane would be a line. So, that would be the null space. So, we've got two, we've got a column space, a row space, and there are two perpendicular spaces. So, those four fit together in a beautiful picture of a matrix. Yeah, yeah. It's sort of a fundamental, it's not a difficult idea. It comes pretty early in 1806, and it's basic. So, planes in these multidimensional spaces, how difficult of an idea is that to come to, do you think? If you look back in time, I think mathematically it makes sense, but I don't know if it's intuitive for us to imagine, just as we were talking about. It feels like calculus is easier to- I see. Intuit. Well, calculus, I have to admit calculus came earlier than linear algebra. So, Newton and Leibniz were the great men to understand the key ideas of calculus. But linear algebra to me is like, okay, it's the starting point because it's all about flat things. All the complications of calculus come from the curves, the bending, the curved surfaces. Linear algebra, the surfaces are all flat. Nothing bends in linear algebra. So, it should have come first, but it didn't. And calculus also comes first in high school classes, in college class, it'll be freshman math, it'll be calculus. And then I say, enough of it. Like, okay, get to the good stuff. And that's- Do you think linear algebra should come first? Well, it really, I'm okay with it not coming first, but it should. Yeah, it should. It's simpler. Because everything is flat. Yeah, everything's flat. Well, of course, for that reason, calculus sort of sticks to one dimension or eventually you do multivariate, but that basically means two dimensions. Linear algebra, you take off into 10 dimensions, no problem. It just feels scary and dangerous to go beyond two dimensions, that's all. If everything is flat, you can't go wrong. So, what concept or theorem in linear algebra or in math you find most beautiful, that gives you pause, that leaves you in awe? Well, I'll stick with linear algebra here. I hope the viewer knows that really mathematics is amazing, amazing subject and deep, deep connections between ideas that didn't look connected. They turned out they were. But if we stick with linear algebra, so we have a matrix. That's like the basic thing, a rectangle of numbers. And it might be a rectangle of data. You're probably going to ask me later about data science, where often data comes in a matrix. You have, you know, maybe every column corresponds to a drug and every row corresponds to a patient. And if the patient reacted favorably to the drug, then you put up some positive number in there. Anyway, rectangle of numbers, a matrix is basic. So, the big problem is to understand all those numbers. You got a big, big set of numbers. And what are the patterns? What's going on? And so, one of the ways to break down that matrix into simple pieces is uses something called singular values. And that's come on as fundamental in the last, and certainly in my lifetime. Eigenvalues, if you have viewers who've done engineering math or basic linear algebra, eigenvalues were in there. But those are restricted to square matrices. And data comes in rectangular matrices. So, you got to take that next step. I'm always pushing math faculty, get on, do it, do it, do it, singular values. So, those are a way to break, to make, to find the important pieces of the matrix, which add up to the whole matrix. So, you're breaking a matrix into simple pieces. And the first piece is the most important part of the data. The second piece is the second most important part. And then often, so a data scientist will like, if a data scientist can find those first and second pieces, stop there. The rest of the data is probably round off, you know, experimental error, maybe. So, you're looking for the important part. Yeah. So, what do you find beautiful about singular values? Well, yeah, I didn't give the theorem. So, here's the idea of singular values. Every matrix, every matrix, rectangular, square, whatever, can be written as a product of three very simple, special matrices. So, that's the theorem. Every matrix can be written as a rotation times a stretch, which is just a matrix, a diagonal matrix, otherwise all zeros except on the one diagonal. And then the third factor is another rotation. So, rotation, stretch, rotation is the breakup of any matrix. The structure of that, the ability that you can do that, what do you find appealing? What do you find beautiful about it? Well, geometrically, as I freely admit, the action of a matrix is not so easy to visualize, but everybody can visualize a rotation. Take two-dimensional space and just turn it around the center. Take three-dimensional space. So, a pilot has to know about, well, what are the three, the yaw is one of them. I've forgotten all the three turns that a pilot makes. Up to 10 dimensions, you've got 10 ways to turn, but you can visualize a rotation. Take the space and turn it, and you can visualize a stretch. So, to break a matrix with all those numbers in it into something you can visualize, rotate, stretch, rotate, is pretty neat. Pretty neat. That's pretty powerful. On YouTube, just consuming a bunch of videos and just watching what people connect with and what they really enjoy and are inspired by, math seems to come up again and again. I'm trying to understand why that is. Perhaps you can help give me clues. It's not just the kinds of lectures that you give, but it's also just other folks, like with Numberphile, there's a channel where they just chat about things that are extremely complicated, actually. People, nevertheless, connect with them. What do you think that is? It's wonderful, isn't it? I mean, I wasn't really aware of it. We're conditioned to think math is hard, math is abstract, math is just for a few people, but it isn't that way. A lot of people quite like math. I get messages from people saying, you know, now I'm retired, I'm going to learn some more math. I get a lot of those. It's really encouraging. And I think what people like is that there's some order, a lot of order, and things are not obvious, but they're true. So it's really cheering to think that so many people really want to learn more about math. Yeah. In terms of truth, again, sorry to slide into philosophy at times, but math does reveal pretty strongly what things are true. I mean, that's the whole point of proving things. It is, yeah. And yet, sort of our real world is messy and complicated. It is. What do you think about the nature of truth that math reveals? Oh, wow. Because it is a source of comfort, like you've mentioned. Yeah, that's right. Well, I have to say, I'm not much of a philosopher. I just like numbers. You know, as a kid, this was before you had to go in when you had a filly in your teeth. You had to kind of just take it. So what I did was think about math, you know, like take powers of two, two, four, eight, 16, up until the time the tooth stopped hurting and the dentist said you're through. Or counting. Yeah. So that was a source of peace, almost. Yeah. What is it about math do you think that brings that? Yeah. What is that? Well, you know where you are. Yeah, it's symmetry. It's certainty. The fact that, you know, if you multiply two by itself 10 times, you get 1,024, period. Everybody's going to get that. Do you see math as a powerful tool or as an art form? So it's both. That's really one of the neat things. You can be an artist and like math. You can be an engineer and use math. Which are you? Which am I? What did you connect with most? Yeah, I'm somewhere between. I'm certainly not an artist type, philosopher type person. Might sound that way this morning, but I'm not. Yeah, I really enjoy teaching engineers because they go for an answer. And yeah, so probably within the MIT math department, most people enjoy teaching students who get the abstract idea. I'm okay with, I'm good with engineers who are looking for a way to find answers. Yeah. Actually, that's an interesting question. Do you think for teaching and in general, thinking about new concepts, do you think it's better to plug in the numbers or to think more abstractly? So looking at theorems and proving the theorems or actually building up a basic intuition of the theorem or the method, the approach, and then just plugging in numbers and seeing it work? Yeah, well, certainly many of us like to see examples first. We understand it might be a pretty abstract sounding example, like a three-dimensional rotation. How are you going to understand a rotation in 3D or in 10D? And then some of us like to keep going with it to the point where you got numbers, where you got 10 angles, 10 axes, 10 angles. But the best, the great mathematicians probably, I don't know if they do that because for them, an example would be a highly abstract thing to the rest of us. Right, but nevertheless, working in the space of examples. Yeah, examples. It seems to. It's examples of structure. Our brains seem to connect with that. Yeah, yeah. So I'm not sure if you're familiar with him, but Andrew Yang is a presidential candidate currently running with math in all capital letters and his hats as a slogan. I see. Stands for Make America Think Hard. Okay, I'll vote for him. So, and his name rhymes with yours, Yang Strang. But he also loves math and he comes from that world. But he also, looking at it, makes me realize that math, science, and engineering are not really part of our politics, our political discourse about political, like government in general. Why do you think that is? What are your thoughts on that in general? Well, certainly somewhere in the system, we need people who are comfortable with numbers, comfortable with quantities. If you say this leads to that, they see it and it's undeniable. But isn't that strange to you that we have almost no, I mean, I'm pretty sure we have no elected officials in Congress, or obviously the president, that has an engineering degree or a math degree. Yeah, well, that's too bad. A few who could make the connection, yeah, it would have to be people who understand engineering or science and at the same time can make speeches and lead. Yeah, inspire people. Yeah, inspire, yeah. You were, speaking of inspiration, the president of the Society for Industrial Applied Mathematics. Oh, yes. It's a major organization in math, in applied math. What do you see as a role of that society in our public discourse? Right, yeah. So, well, it was fun to be president at the time. A couple years, a few years? Two years, around 2000. So, that's the president of a pretty small society, but nevertheless, it was a time when math was getting some more attention in Washington. But yeah, I got to give a little 10 minutes to a committee of the House of Representatives talking about who I met. And then, actually, it was fun because one of the members of the House had been a student, had been in my class. What do you think of that? Yeah, as you say, pretty rare. Most members of the House have had a different training, different background, but there was one from New Hampshire who was my friend, really, by being in the class. Yeah, so those years were good. Then, of course, other things take over in importance in Washington, and math just, at this point, is not so visible. But for a little moment, it was. There's some excitement, some concern about artificial intelligence in Washington now. Yes, sure. About the future. Yeah. And I think at the core of that is math. Well, it is, yeah. I mean, maybe it's hidden, maybe it's wearing a different hat. Well, artificial intelligence, and particularly, can I use the words, deep learning? Deep learning is a particular approach to understanding data. Again, you've got a big whole lot of data, where data is just swamping the computers of the world. And to understand it, out of all those numbers, to find what's important in climate, in everything. And artificial intelligence is two words for one approach to data. Deep learning is a specific approach there, which uses a lot of linear algebra. So, I got into it. I thought, okay, I've got to learn about this. So, maybe from your perspective, let me ask the most basic question. Yeah. How do you think of a neural network? What is a neural network? Yeah, okay. So, can I start with the idea about deep learning? What does that mean? Sure. What is deep learning? What is deep learning? Yeah. So, we're trying to learn, from all this data, we're trying to learn what's important. What's it telling us? So, you've got data. You've got some inputs for which you know the right outputs. The question is, can you see the pattern there? Can you figure out a way for a new input, which we haven't seen, to understand what the output will be from that new input? So, we've got a million inputs with their outputs. So, we're trying to create some pattern, some rule that'll take those inputs, those million training inputs, which we know about, to the correct million outputs. And this idea of a neural net is part of the structure of our new way to create a rule. We're looking for a rule that will take these training inputs to the known outputs. And then we're going to use that rule on new inputs that we don't know the output and see what comes. Linear algebra is a big part of defining that rule. That's right. Linear algebra is a big part. Not all the part. People were leaning on matrices. That's good. Still do. Linear is something special. It's all about straight lines and flat planes. And data isn't quite like that. It's more complicated. So, you've got to introduce some complication. You have to have some function that's not a straight line. And it turned out, non-linear, non-linear, not linear. And it turned out that it was enough to use the function that's one straight line and then a different one. Halfway, so piecewise linear. One piece has one has one slope, one piece, the other piece has the second slope. And so, getting that non-linear, simple non-linearity in blew the problem open. That little piece makes it sufficiently complicated to make things interesting. Exactly. Because you're going to use that piece over and over a million times. So, it has a fold in the graph, the graph, two pieces. And, but when you fold something a million times, you've got a pretty complicated function that's pretty realistic. So, that's the thing about neural networks is they have a lot of these. A lot of them, that's right. So, why do you think neural networks, by using a, sort of formulating an objective function, very not a plane function. Lots of folds. Lots of folds of the inputs, the outputs. Why do you think they work to be able to find a rule that we don't know is optimal, but is just seems to be pretty good in a lot of cases? What's your intuition? Is it surprising to you as it is to many people? Do you have an intuition of why this works at all? Well, I'm beginning to have a better intuition. This idea of things that are piecewise linear, flat pieces, but with folds between them. Like think of a roof of a complicated, infinitely complicated house or something that curved, it almost curved, but every piece is flat. That's been used by engineers. That idea has been used by engineers, is used by engineers, big time. Something called the finite element method. If you want to design a bridge, design a building, design an airplane, you're using this idea of piecewise flat as a good, simple, computable approximation. But you have a sense that there's a lot of expressive power in this kind of piecewise linear. Yeah. That's just combined together. You used the right word. If you measure the expressivity, how complicated a thing can this piecewise flat guys express, the answer is very complicated. Yeah. What do you think are the limits of such piecewise linear or just neural networks, the expressivity of neural networks? Well, you would have said a while ago that they're just computational limits. It's a problem beyond a certain size, a supercomputer isn't going to do it. But those keep getting more powerful. That limit has been moved to allow more and more complicated surfaces. In terms of just mapping from inputs to outputs, looking at data, what do you think of, in the context of neural networks in general, data is just tensor, vectors, matrices, tensors. How do you think about learning from data? How much of our world can be expressed in this way? How useful is this process? I guess that's another way to ask you, what are the limits of this? Well, that's a good question. Yeah. So, I guess the whole idea of deep learning is that there's something there to learn. If the data is totally random, just produced by random number generators, then we're not going to find a useful rule because there isn't one. So, the extreme of having a rule is like knowing Newton's law, you know, if you hit a ball, it moves. So, that's where you had laws of physics, Newton and Einstein and other great, great people have found those laws and laws of the distribution of oil in an underground thing. I mean, so, engineers, petroleum engineers understand how oil will sit in an underground basin. So, there were rules. Now, the new idea of artificial intelligence is learn the rules instead of figuring out the rules with help from Newton or Einstein. The computer is looking for the rules. So, that's another step. But if there are no rules at all that the computer could find, if it's totally random data, well, you've got nothing, you've got no science to discover. It's an automated search for the underlying rules. Yeah, search for the rules, yeah, exactly. And there will be a lot of random parts, a lot, I'm not knocking random, because that's there, there's a lot of randomness built in, but there's got to be some basic structure. It's almost always signal, right? There's got to be some signal, yeah. If it's all noise, then you're not going to get anywhere. Well, this world around us does seem to always have a signal of some kind to be discovered. Right, that's it. So, what excites you more? We just talked about a little bit of application. What excites you more, theory or the application of mathematics? Well, for myself, I'm probably a theory person. I'm speaking here pretty freely about applications, but I'm not a person who really, I'm not a physicist or a chemist or a neuroscientist. So, for myself, I like the structure and the flat subspaces and the relation of matrices, columns to rows. That's my part in the spectrum. So, really, science is a big spectrum of people from asking practical questions and answering them using some math, then some math guys like myself who are in the middle of it, and then the geniuses of math and physics and chemistry who are finding fundamental rules and doing the really understanding nature. That's incredible. At its lowest, simplest level. Maybe just a quick and broad strokes from your perspective. Where does linear algebra sit as a subfield of mathematics? What are the various subfields that you think about in relation to linear algebra? So, the big fields of math are algebra as a whole and problems like calculus and differential equations. So, that's a second quite different field. Then maybe geometry deserves to be thought of as a different field to understand the geometry of high dimensional surfaces. So, I think, am I allowed to say this here? Uh-oh, Scott. This is where personal view comes in. I think math, thinking about undergraduate math, what millions of students study, I think we overdo the calculus at the cost of the algebra, at the cost of linear. See, this talk titled Calculus versus Linear Algebra. That's right. That's right. And you say that linear algebra wins. So, can you dig into that a little bit? Why does linear algebra win? Right. Well, okay. The viewer is going to think this guy is biased. Not true. I'm just telling the truth as it is. Yeah. So, I feel linear algebra is just a nice part of math that people can get the idea of. They can understand something that's a little bit abstract because once you get to 10 or 100 dimensions. And very, very, very useful. That's what's happened in my lifetime is the importance of data, which does come in matrix form. So, it's really set up for algebra. It's not set up for differential equations. And let me fairly add probability. The ideas of probability and statistics have become very, very important, have also jumped forward. And that's different from linear algebra, quite different. So, now we really have three major areas to me, calculus, linear algebra, matrices, and probability statistics. And they all deserve an important place. And calculus has traditionally had a lion's share of the time. A disproportionate share. Thank you. Disproportionate, that's a good word. Of the love and attention from the excited young minds. I know it's hard to pick favorites, but what is your favorite matrix? What's my favorite matrix? Okay. So, my favorite matrix is square, I admit it. It's a square bunch of numbers. And it has twos running down the main diagonal. And on the next diagonal, so think of top left to bottom right, twos down the middle of the matrix. And minus ones just above those twos, and minus ones just below those twos. And otherwise all zeros. So, mostly zeros. Just three non-zero diagonals coming down. What is interesting about it? Well, all the different ways it comes up. You see it in engineering, you see it as analogous in calculus to second derivative. So, calculus learns about taking the derivative, figuring out how fast something's changing. But second derivative, now that's also important. That's how fast the change is changing. How fast the graph is bending. How fast it's curving. And Einstein showed that that's fundamental to understand space. So, second derivatives should have a bigger place in calculus. Second, my matrices, which are like the linear algebra version of second derivatives, are neat in linear algebra. Yeah, just everything comes out right with those guys. Beautiful. What did you learn about the process of learning by having taught so many students math over the years? Ooh, that is hard. I'll have to admit here that I'm not really a good teacher because I don't get into the exam part. The exam is the part of my life that I don't like. And grading them, and giving the students A or B or whatever. I do it because I'm supposed to do it, but I tell the class at the beginning, I don't know if they believe me. Probably they don't. I tell the class, I'm here to teach you. I'm here to teach you math and not to grade you. But they're thinking, okay, this guy is going to, you know, when's he going to, is he going to give me an A minus? Is he going to give me a B plus? What? What did you learn about the process of learning? Of learning. Yeah, well, maybe to give you a legitimate answer about learning, I should have paid more attention to the assessment, the evaluation part at the end. But I like the teaching part at the start. That's the sexy part, to tell somebody for the first time about a matrix. Wow. But is there, are there moments, so you are teaching a concept, are there moments of learning that you just see in the student's eyes? You don't need to look at the grades. Yeah. But you see in their eyes that you hook them. That, you know, that you connect with them in a way where, you know what, they fall in love with this beautiful world of methods. They see that it's got some beauty there. Yeah, yeah. Or conversely, that they give up at that point. It's the opposite. The dark is saying that math, I'm just not good at math, I don't want to walk away. Yeah, yeah. Maybe because of the approach in the past, they were discouraged. But don't be discouraged. It's too good to miss. Yeah, well, if I'm teaching a big class, do I know when, I think maybe I do, sort of, I mentioned at the very start, the four fundamental subspaces and the structure of the fundamental theorem of linear algebra, the fundamental theorem of linear algebra. That is the relation of those four subspaces, those four spaces. Yeah. So I think that, I feel that the class gets it. When they see it. Yeah. What advice do you have to a student just starting their journey in mathematics today? How do they get started? Yes, that's hard. Well, I hope you have a teacher, professor who is still enjoying what he's doing, what he's teaching. He's still looking for new ways to teach and to understand math. Because that's the pleasure, the moment when you see, oh yeah, that works. So it's less about the material you study, it's more about the source of the teacher being full of passion for the class. Yeah, more about the fun. Yeah, the moment of getting it. But in terms of topics, linear algebra? Linear algebra. Well, that's my topic, but oh, there's beautiful things in geometry to understand. What's wonderful is that in the end, there's a pattern, there are rules that are followed in biology as there are in every field. You describe the life of a mathematician as 100% wonderful, except for the grade stuff. Yeah, except for grades. Yeah. When you look back at your life, what memories bring you the most joy and pride? Well, that's a good question. I certainly feel good when I, maybe I'm giving a class in 1806 that's MIT's linear algebra course that I started. So sort of there's a good feeling that, okay, I started this course, a lot of students take it, quite a few like it. Yeah, so I'm sort of happy when I feel I'm helping make a connection between ideas and students, between theory and the reader. Yeah, I get a lot of very nice messages from people who've watched the videos and it's inspiring. I just, I'll maybe take this chance to say thank you. Well, there's millions of students who you've taught and I am grateful to be one of them. So Gilbert, thank you so much. It's been an honor. Thank you for talking today. It was a pleasure. Thanks. Thank you for listening to this conversation with Gilbert Strang. And thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST, you'll get $10 and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future. If you enjoy this podcast, subscribe on YouTube. We have five stars on Apple Podcast, support on Patreon, or connect with me on Twitter. Finally, some closing words of advice from the great Richard Feynman. Study hard what interests you the most in the most undisciplined, irreverent, and original manner possible. Thank you for listening and hope to see you next time.

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Brian Muraresku: The Secret History of Psychedelics | Lex Fridman Podcast #211

The following is a conversation with Brian Murevescu, author of The Immortality Key, The Secret History of the Religion with No Name, a book that reconstructs the forgotten history of psychedelics in the development of Western civilization. To support this podcast, please check out our sponsors, Insight Tracker, GiveWell, NI, Indeed, and Masterclass. Their links are in the description. This is the Lex Friedman Podcast, and here's my conversation with Brian Murevescu. Who or what do you think God is? How has our conception maybe put another way of God changed throughout history? We're starting with an easy one, Lex. So what is God? Well, God is a thought. God is an idea, but its reference is to that which is beyond thinking, beyond our ability to even conceive, beyond the categories of being and non-being. So how do we talk about that? To talk about it is almost to get it wrong, right? So Joe Campbell famously said that, you know, any God that is not transparent to transcendence is like an idolatry because it's just a mental construct, and it can't possibly speak to the incomprehensible. So we use poetic language. We say the being of beings, the infinite life energy of the universe, the mystery of transcendence, boundless life, unqualified is-ness. But it doesn't quite get to the point. I think that if there's any great insight from mysticism, it's that you and I participate with God in a very real way, Lex Friedman, here in Austin, Texas. That in the here and now, to touch that eternal principle, another way to refer to God, to touch that eternal principle within ourselves is to participate with divinity in some way. So not an external force, but that divine sense within. So there's some aspect in which God is a part of us. So one, it's a thing we can't describe. It represents all of the mystery around us. It's outside our ability to comprehend. And at the same time, it's somehow the thing that's inside of us also. The ultimate paradox. MacThiel of Magdeburg, 13th century German mystic, maybe the first German mystic, says that the day of her spiritual awakening was the day that she saw and knew that she saw God in all things, and all things in God. And so we can say this, by the way, without apology or lightweight theology or vapid speculation or even heresy, you know, we can talk about this, including within the Abrahamic faiths. The mystical core of these faiths all talk about the encounter of divinity within. That's what I explore in the immortality key, this notion of techniques, archaic techniques in some cases, of ecstasy, that allow that experience of the eternal principle to actually rise up in our consciousness when we're still here as flesh and blood beings. There's some sense in which our conception of God, though, is conjured up by our own mind. And so aren't we creating God? Like, aren't we the gods that are creating the idea of God? Like, if we are, like when we talk about God, aren't we playing with ideas that are created by our mind, and thereby we are the creator, not God? This is a very kind of cyclical question, but in some sense I mean that if God is the thing that represents the mystery all around us, contrast that with our conception of God, the way we talk about him, is more a creation of our minds, it's not the mystery, it's our struggle to comprehend the mystery, and therefore we're creating the God in terms of the God that we're talking about in this conversation or in general, if that makes any sense. It makes no sense whatsoever, Lin. Great, this is wonderful. But this is the eternal mystery. This is why it's so difficult to talk about, and yet it could be the very center of our beings. You know, the Upanishads speak about us as the creators, about us as gods. It's a very different creation myth, but the god of the Upanishads in this great verse talks about pouring themselves, pouring themselves into creation. Indeed, I have become this creation, says God. And there's a great line, verily he or she who knows this becomes in this creation a creator. So yeah, I mean, just our ability to engage in mentation, our ability to think about this stuff is partly our divine nature. This is what the humanists were talking about in the Renaissance, by the way, and that it's not so much learning, putting dots together, having arguments with each other over learned books. It's a process of unlearning, is what some of the mystical traditions talk about, unlearning all these thoughts, emotions, traumas, and experiences that have gone into the false construction of our false self, that behind all these layers, like peeling back the onion, is a part of us that once you can identify that, begins to look a little bit different. In other words, it's one thing to foster a relationship with God. It's a very different thing to identify as God. And I mean that quite literally, without being heretical. You can find this in the mystery traditions. Can you expand on this? You mean a human being can embody God? That is textbook incarnational theology that you can find in any Christian mystic, but you can find it in the mystical tradition of Islam and Judaism as well. So Rumi, for example, the great Sufi mystic, talks about if you could get rid of yourself, just get rid of yourself just once, the secret of secrets would open to you, that the face of the unknown would appear on the perception of your consciousness. Rabbi Lawrence Kushner, a modern day contemporary mystic, talks about, because this stuff does continue, there's a continuity to it. The poetry here is incredible. So well, listen to Rabbi Kushner. He says that the emptying of selfhood allows the soul to attach to true reality. And in Kabbalism, the true reality is what's called the divine nothingness, ayin. And so I like the adage that atheists and mystics both essentially believe in nothing, except that the mystics spell it with a capital N, the divine nothing. And then I'll give you Meister Eckhart, another medieval Christian mystic. He says that if you could not yourself, right? The same concept, if you could not yourself for just an instant, indeed, I say less than an instant, you would possess all. So again, you're seeing the same thing in Sufism, Kabbalism, Christian mysticism. The way to identify with the divine is to peel back these layers and attempt to discover pure awareness. If we look at the universe from a physics perspective, or, you know, I'm a computer science person, so if the universe is a computer, there's some sense that God, the creator of the universe, or just the computer itself, doesn't know what the heck is gonna happen. He just kind of creates some basic rules and runs the thing. So there is some element in which you can conceive of humans, or conscious beings, or intelligent beings, as a tool that the creator uses to understand itself, himself. Do you think that's a perspective that we could, or is useful to take on God, that is basically the universe created humans to understand itself? He doesn't actually know the full thing. He needs the human brains to figure out the puzzle. So that's in contrasting to the unlearning, to the getting out of the way that we've talked about. It's more like, no, we need the humans to figure out this puzzle. Well, we have no answers to this, which is why philosophers still have jobs, if they have jobs at all. But I mean, so the physicists take a look at this. Have you seen the article that came out, I think it was this month, in the Journal of Cosmology and Astroparticle Physics, Robert Lanza, the biocentrism theory, the idea that the universe comes into being through our observation, right? The whole, the God equation. So not just in quantum mechanics, but in general relativity, the idea that we make the universe moment by moment, which is kind of mind-blowing, gets into ideas of simulation. Okay, so that's how the physicists, at least some of them, might look at it. You could also look back to the medieval Christian mystics. Meister Eckhart, once again, says that the eye with which I see God is the same eye that sees me, right? So one sight, one knowledge, one love. Another mind-blowing concept. But this is why the arts and poetry and music are so important, because although I love astroparticle physics, it's another to kind of hear this, the same message across time. Yeah, the simulation thing. I was actually looking this morning at video games, just the statistics on video games, and I saw that the two top video games in terms of hours played is Fortnite and World of Warcraft, and I saw that it's 140 billion hours, billion hours have been played of those games. That's a lot of video games. Yeah, but that's very sophisticated worlds being created, especially in the World of Warcraft. It's a massive online role-playing game. So you have these characters that are together, sort of creating a world, but they, in themselves, are also developing. They have all these items, and they're growing, like they're little humans. Like there's complicated societies that are formed, they have goals, they're striving, and so on. And it's, we're creating a universe within our universe. And for now, it's a kind of, it's a basic sort of constraint version of our more richer earth-like civilization. But it's conceivable that, you know, that we are, this thing on earth is a kind of video game that somebody else is playing. It's like, you can see sort of video games upon video games being created. And this is something I think a lot about, not from a philosophical perspective, but practically, how fun does this video game have to be for us to let go of the silly pursuits in this meat space that we live in, and fully just stay in WoW, stay in World of Warcraft, stay in the video game for full time. So I think about that from an engineering perspective. Like, is there going to be a time when this video game is actual real life for us? And then the creatures inside the video game, they'll be just borrowing our consciousness, sort of to ground themselves, will refer to us as the gods, right? Like, won't we become the gods? This conversation is not going how I expected. But I think about this a lot from, you know, because I love video games. And I wonder more and more of us, especially in COVID times, are living in the digital world. You can think about Twitter and all those kinds of things. You could think about clubhouse people using just voices to communicate little icons, sort of in the digital space. You could see more and more will be moving in the digital space, and let go of this physical space. And then the remnants of the ancients that created the video games, that nobody centuries from now will even remember, those will be the gods. And then there'll be gods upon gods being created. This is the kind of stuff I think about. But is that any at all useful to you, to this thought experiment of a simulation? Basically, the fabric of our reality, how did it come to be? What is running this thing? Is that useful? Or is it ultimately the project of understanding God, of understanding myth, is a project that centers on the human, on the human mind, for you? We seem to be at the center of this divine dance, which sounds awfully anthropocentric. But the ancients thought about this too. I mean, the concept in Sanskrit of lila, that the point behind existence is this play, right? It's ultimately playful, this divine dance. It gets awfully complicated in the Gnostic and Neoplatonic schools, these chains of being from Godhead down to us, right? Some invisible, right? And we're going to get into Terence McKenna territory later on, but we can start now by talking about discarded entities and archons and aliens and archetypes. I mean, there is a world where Terence McKenna does meet Plato and Gnosticism quite kindly, and that's in this invisible college, right? The invisible world with which we seem to have some kind of symbiosis that has a higher intent, maybe even a purpose or a plan in mind for us. So, I mean, these ideas come across when you've had a heroic dose of mushrooms. They also pop up in the ancient philosophical literature, this idea of archons, who, you know, the puppet masters controlling us flesh and blood beings. It's all a cosmic dance, and there are no answers to this. First, who are the archons? And second, what is this world where Terence McKenna meets Plato? Do you mean in the space of ideas, or are we talking about some kind of world that connects all of consciousness to all of human history? I think through different techniques, it is, you know, I think a lot about, I think Gordon Wasson is the meeting point of the two. So, Gordon Wasson, who I do talk about in the book, was this JP Morgan banker turned ethnomycologist, and he's largely credited with the rediscovery of psilocybin-containing mushrooms, which kind of gave rise to the pop psychedelic revolution of the 1960s. He visited Maria Sabina down in Mexico. In his wake went Bob Dylan, Led Zeppelin, The Stones, and everybody else. And the way he describes his psilocybin experience is a bit strange, because he thinks of Plato, right? And he says that, you know, whereas our ordinary reality is kind of this imperfect view of things, Gordon Wasson felt that on mushrooms, he was spying the archetypes. And he talks about Plato, and he writes about the archetypes in this famous article that's released in 1957 in Life magazine. And so, a well-read individual from the mid-20th century has his premier psychedelic experience, and out comes Plato, because what he was witnessing was so sharp, so brilliant, so detailed, in some sense, more real than real, this noetic sense that William James talks about. That when you confront something more real than real, these discarnate entities, these images, these visionary motifs, you're tempted to believe that you've tapped into the truest nature and the underlying structure of the cosmos. And that's difficult to escape from, whether you're Plato or Terence McKenna or Gordon Wasson caught in between. Lex Doppelganger So we talk about this being in touch with something that is more real than real. And let's just go straight there to McKenna before we return to the bigger picture. So he's talked about the, what is it, self-healing machine elves? Peter Self-transforming. Lex Doppelganger Self-transforming machine elves during his DMT travels. And I just talked to Rick Doblin, who also had different travels through this hyperspace. But they all seem to be traveling on the same spaceship, just to different locations. And there is a sense in which they seem to be traveling through whatever, I don't know if it's through space-time or something else, to meet something that is more real than real. What can you say about this DMT experience, about Terence McKenna, about the poetry he used, but maybe more specifically about this place that they seem to all travel to? Peter Self-transforming machine elves So the big question is, is it real? Is it really more real than real? The ancient philosophers were asking the same question, and their means of attempting to answer that was by dying. So if you ask Plato the definition of philosophy, he will say that to practice it in the right way is to practice dying and being dead. And many people describe the psychedelic experience in sort of near-death experience terms. And the encountering of all this visual imagery tends to be something that is often described as more real than real. So how does Terence talk about this? So I was just listening to the trilogues, which folks should look up. Somewhere between 1989 and 1990, Terence sits down with his friends Ralph Abraham and Rupert Sheldrake at Esalen, and they're trying to figure out the meaning of these discarnate entities and these non-human intelligences. And Terence develops a taxonomy for how to analyze this. And he says that number one, they're either semi-physical but kind of elusive. So think of the Bigfoot or the Yeti or things like this, beings that exist somewhere between mythology and zoology, which isn't really appropriate here. So option number two, he says, is the mental… I'm sorry. You're dropping so many good lines. It's so good. I apologize. Somewhere between mythology and zoology. This is all Terence McKenna. Okay. All right. I take no credit for this. So… But you're combining, you're like, Jimi Hendrix only used the blues scale, but he still created something new in the music he played. Anyway, go ahead. Well, we're going into Mixolydian right now. Okay. So option number two, and this is what Terence calls sort of the mentalist reductionist approach. And this is pure McKenna poetry. He says that these beings could be autonomous fragments of psychic energy that have temporarily escaped the controlling power of the ego. So in Jungian sense is that these would just be pure projections, the projections of schizophrenics in some cases. So they're essentially unreal. And the third option, the most tantalizing, is that they're both non-physical, but autonomous. In other words, they actually exist in some kind of real place, in some kind of real space, and that we can have Congress with them. There is communication. He talks about the whisperings of the demon artificers, and that it's just possible that our meetings with these beings have coaxed the human species into self-expression in a very real way. That at different times in history, our relationships with these semi-autonomous beings may actually guide the species. Now, this is high speculation, and Terence and Ralph and Rupert wind up talking about the early modern period and the scientific enlightenment, and that even someone like Descartes reports a dream in which he came face to face with an angel who said that the conquest of nature is to be achieved through measure and number. So even the hard-minded materialist like Descartes is confronting these discarnate entities. John Dee in the 16th century, the high magician of the Elizabethan court, he reports decades worth of what we would say is extraterrestrial communication, or interdimensional communication. And you can find instances of this throughout history, including among the pre-Socratics. And Peter Kingsley writes quite a bit about this, but I'll save that until your next question. Well, first of all, we don't seem to understand from where intelligence came from. We don't understand from where life came from on Earth, but that we can kind of intuit, because it's in the space of chemistry and biology, you have good theories about the origins of life on Earth, but the origins of intelligent life, that is a giant mystery. And there's some sense in which, I mean, I don't know if you know the movie 2001 Space Odyssey, but it does seem that there's like important, throughout human history, throughout life on Earth, there's important phase shifts of, it feels like something happened where there's big leaps. It could be something coincidental like fire and learning how to cook meat and all those kinds of things, but it feels like there could be other things. And I think that's at the core of your work is exploring what those things could be. Is there, is it possible, talked about Joe Rogan off line, is it, I mean, it's entirely possible. Is it possible that is it possible that psychedelics have in fact contributed of being an important source of those phase shift throughout human history, of the intellect, basically steering the intellectual development and growth of human civilization? It's a hypothesis worth investigating. How about that? Beautiful. And maybe not psychedelics in and of themselves, but I think our whole conversation is kind of wrapped up in these non-ordinary states of awareness. We start by talking about God, which is something unordinary and expansive. And I think that as you trace the intervention of divinity, if that's the case, throughout human history, you have to bump up against the irrational. Mircea Eliade, the great scholar of religions and fellow Romanian, said that the history of religions essentially constitutes the point of intersection between metaphysics and biology, right? So that we are biological beings who do interact with our planet, with the natural kingdom. And you would think that as early archaic ecologists, we would have figured out what plants work, which fungi don't, and developed maybe language around that. And so this is another one of McKenna's speculative but very interesting hypotheses, the stone ape theory. Is it possible that psychedelics were involved in one of the several leaps forward? You mentioned the word leap. Jared Diamond talks about the great leap forward 60,000 years ago. The species had been around for a couple hundred thousand years. All of a sudden, the cave painting appears. All of a sudden, there's a phase shift. Did something like that happen millions of years ago? And I love the way Paul Stamets talks about this. It would be the ingestion of perhaps psilocybin-containing fungi millions and millions of times over millions and millions of years. So it's not just a one-time event that cascades, but it's the accumulation of psychedelic experience. It's really difficult to test that hypothesis. But I've been talking with a paleoanthropologist in South Africa, my friend Lee Berger, about ways that we might test for this. And so Lee, amongst many things, is this National Geographic explorer. He's the paleoanthropologist's paleoanthropologist at the University of Whitwater-Shrind. He's famous amongst other things for the discovery of previously undiscovered hominids like Homo naledi. And there's an interesting point. So naledi is this archaic hominid, morphologically archaic, but it dates to about 300,000 years ago, which is very strange. What's even more strange about Homo naledi at the Rising Star Cave System there in South Africa is that Lee believes he's discovered the first bipedal ape deliberately disposing of its dead. So there is a recognition of self-mortality and the practicing of rituals around death. We're talking about burials. And if you have burials, says Lee, in an archaic hominid 300,000 years ago, maybe you have language. And I mention that because Terence McKenna was obsessed with language in the stoned ape theory, that the ingestion of psilocybin in addition to enhancing visual acuity, perhaps facilitating sexual arousal, leads to proto-language. Now, isn't it interesting, this could be entirely a coincidence, that the largest sound inventory of any language is the Khoisan of Botswana and Namibia. They have something like 164 consonants and 44 vowels. English, by comparison, has about 45. So I don't know what to make of this, but what you find in that part of the world is very, very complex language. Language that could be an inheritance. Language that could be incredibly archaic, together with this recognition of self-mortality. And when I talk to Lee Berger, we say, when you're looking at universals like that, language around all human populations, the recognition of self-mortality, the contemplation of death, just maybe you have pharmacology. And so maybe we can go out and test for this, using gas chromatography, mass spectrometry, proteomics, technology that doesn't even exist, but maybe we can actually test the stoned ape theory to figure out once and for all if there's any merit there. Can you just linger a little bit on the pharmacology tools? How would it be possible to say something about what was being ingested so, so, so long ago? That's what I asked Dr. Berger. So Lee has discovered in the dental calculus of archaic hominids. Dental calculus, I like this. Evidence of their diet. And you might not believe how old this was, but in Sadiba, Australopithecus Sadiba, they found evidence of Sadiba's diet going back 2 million years. So through things like phytolysts, which are essentially fossilized plant tissue, they found evidence that Sadiba was eating bark and leaves and grasses and fruits and palm. So no psychedelics to speak of, but it just goes to show that through things like dental microware analysis and other techniques that we're still developing, we can actually figure out what the diet was at the time. I'll fast forward to 50,000 years ago. There was another study out of El Cidron Cave in 2012, which found that Neanderthals, again, preceding our species 50,000 years ago, were ingesting yarrow and chamomile, which had been identified as medicinal. So again, not psychedelic or psychoactive, but we kind of have the beginnings of the technology, and that was nine years ago, to begin figuring out the ancestral diet of these hominids. Presumably, there could be a way to figure out, it's not just diet, but which have psychoactive elements to them. So whether you're chewing it, whether you're smoking it, whether, I mean, I don't know what, licking it. I don't know if there's any kind of ways through the dental calculus to figure out what exact substances were being consumed. Is it possible to figure out whether psychedelic substances are being consumed by looking at human behavior? Like you said, organized burials or cave paintings. No, but so that's a little bit of a stretch to say, like, where did this leap come from? But it's not. It's not. So just last fall, as a matter of fact, so that notion's been out there for a while, the idea that hallucinogens and the ritual consumption of hallucinogens were somehow related to the Great Leap Forward, were somehow related to the initial cave painting. Graham Hancock wrote a beautiful book about this called Supernatural, which in many ways sent me down this rabbit hole back in 2007. But even at the time when he was writing that and the years subsequent, it was still kind of seen as a kooky idea. Last fall, interestingly enough, the first archaeochemical data for the ritual consumption of psychedelics associated with cave art was finally published. It's not that ancient. It's only about 400 or 500 years ago, but it came from the Pinwheel Cave, a Chumash site in California. And what they found were datura quids, like these chewed up, you mentioned how they ingest it, these chewed up quids, like these bunches of datura, which contain these very powerful tropane alkaloids, and what was believed to be some kind of Chumash initiation site. So we can say that there is initial, you know, archaeochemical data for the consumption of psychedelics and cave art. And so where else might we find this? Are there a lot of archaeochemists in the world? Because this is fascinating. It's through chemistry, through biology, through physics, whatever, like all the disciplines we, perhaps one day computer science, we apply those tools to study not the data of today, but the data of the past. Are we talking about dozens here? Like how hard is this problem relative to how many people are taking it on, just as a side little tangent? We're probably talking more dozens than hundreds. I spent many years trying to track down an archaeochemist who would talk to me. There were a couple, Pat McGovern at the University of Pennsylvania, and then my friend Andrew Ko at MIT, which you might know something about. Andrew really, you know, on his own time, on his own dime, has been gathering the data for this organic residue analysis. He has what's called the OpenArchem Project, which is this online open source repository for this data. But there's never been a center for this. No university has stood up a dedicated center, a team really, which is what you need of archaeochemists looking at this stuff. But I mean, even despite that, there have been some remarkable discoveries over the past 10, 20 years. It's still a discipline very much in its infancy. Maybe it's becoming a toddler, but as the technology gets better and cheaper, I hope you'll see more and more archaeochemists joining the fight. Yeah, Andrew's fascinating. His work is fascinating. But also, just because of your work, I came across and exchanged a few emails with Patrick McGovern, who's basically, what would you call him? So he has a center, I guess, that does biomolecular archaeology at UPenn. And he's the author of a bunch of books, one of which is Ancient Brews. So he's a scholar of beer and wine and like ancient alcohol, which is fascinating. The influence, even just alcohol, but he has like alcohol with hallucinogenic properties as well. But it's fascinating, as a Russian, it's fascinating to think about the influence of alcohol on the development of human civilization throughout its history. Is there something you can comment on alcohol, or in general, Patrick's work that was informative to you, inspiring, or kind of added to your conception of human history? His work was some of the first hard scientific data that I saw for the ritual consumption of these intoxicants. I don't think he's ever found the hard and fast data for psychedelics. But what he turned me on to was this idea that alcohol or beer and wine specifically, could have been used as vehicles for the administration of psychedelics. That's where it all started for me. Just the notion that ancient beer and ancient wine is very, very different from what we drink today. That typically they were cocktails, they were often fortified and mixed with different fruits, berries, herbs, plants, maybe even fungi over time, because this was all in the absence of distilled liquor, right? There is no hard alcohol, even in Russia, before maybe the 12th century it was in Europe, maybe a bit earlier. But the concept of distillation just didn't exist. And so, to pack a punch, rather than just drink a kind of watered down Budweiser, these people were interested in fortifying these beverages with whatever they could find in nature. And Pat, to his credit, found some of the initial data for these, you could say spiked wines and spiked beers, not with anything overtly psychedelic, but just the fact that in the 16th century BC, at Grave Circle A in Mycenae, there's this Minoan ritual cocktail of beer mixed with wine mixed with mead is very interesting. It's even more interesting that you find that across the Aegean in Gordium at King Midas' tomb, right? The same kind of ritual cocktail which Pat and Sam at the Dogfish Head Brewery resurrected as the Midas touch. So, I mean, the notion that we can go back, find this data, resurrect it, in some cases, 2800 years later, I found pretty exciting 10 years ago. Yeah, bring it back for research. But that's fascinating that people were playing with these ideas. And we'll return to ideas of psychedelic infused wine, which is pretty fascinating. But can we step back and just kind of look at your work with the book Immortality Key? What is the story that you tell in this book? I knew we'd get there eventually, Lex. It's a nonlinear path. Somehow we were talking about simulation and the universe is a computer that's creating video games and wow and Fortnite. But we got there and we'll return, always, to the insane philosophical. But your book Immortality Key, what's the story that you tell in this book? Which part of human history are you studying? Right, so that's the way to phrase it. So, it's my 12-year search for the hard scientific data for the ritual use of psychedelics in classical antiquity. So, we're talking about amongst the ancient Greeks and Romans and the paleo-Christians. So, the generations that would give birth to the largest religion the world's ever known. Christianity today with two and a half billion people. The big question for me is, were psychedelics actually involved? There was a lot written about this in the 60s. John Marco Allegro, the book that I follow was published in 1978 before I was born. The Road to Eleusis by Gordon Wasson, who we talked about already. Albert Hoffman, who famously discovers LSD or synthesizes it from ergot. And Karl Ruck, who is still a professor of classics at Boston University, the only surviving member of that renegade trio and now 85 years old. So, this all predates us. But what was lacking in the 60s, 70s, 80s, 90s, I think was some of this technology and the hard scientific data. Now, for years and years, I went out to the archaeobotanists and the archaeochemists around the world and I asked a very basic question, is there any evidence for psychedelics in classical antiquity? And the answer would almost invariably come back, no. I'm talking to, in addition to Pat, he put me in touch with Hans-Peter Stieke in Germany, Tania Vallamotti in Greece, Sassunta Florensano in Italy. I went all over the place asking one question and getting the same answer back time and again. And so, the book is essentially my search for that data and the eventual uncovering of two, what I think are key pieces of data. One data point shows the ritual use of a psychedelic beer in classical antiquity in Iberia, what today is Spain. And the other shows what looks like a kind of psychedelic wine just outside Pompeii from the first century AD, at the right place, at the right time when the earliest Christians were showing up in Italy. Again, these are early steps in the search for evidence in the space. But speaking of early Christians, what role do you think psychedelic infused wine could have played in the life of the... I won't be clever, in the life of Jesus Christ? I've been saying recently that, and I hope this doesn't sound obscurantist, but I think it's impossible to understand Jesus and the birth of Christianity in the absence of ancient Greek. And I'll give you a very specific example of why I think that's the case. You can read the entire New Testament in ancient Greek, and not once will you ever find a reference to alcohol because there was no word in ancient Greek for alcohol. The way the word sounds, alkol, it's Semitic, it comes from the Arabic. Kahla means to enliven or refresh, it probably comes from coal, K-O-H-L, sort of these powdered metallics that were used in alchemical experiments and cosmetics. So again, that's much later in time when we're using alchemy, distillation, etc. In the first century AD, the power of wine wasn't necessarily tied to alcohol, right? Fermented grapes, the way we think about wine today. So Pat McGovern found some of that early organic data for wine being mixed with beer and with mead. But if you look at the literature from the first century AD, Dioscorides, for example, he writes this massive treatise at the exact same time the Gospels are being written. And Dioscorides, in just one of his books, talks about 56 detailed recipes for spiking wine with all kinds of things like salvia and hellebore and frankincense and myrrh, these spiced perfumes, but also more dangerous things like henbane and mandrake, which he says in Greek can be fatal with just one cupful. And in book 474 of his Materia Medica, he talks about black nightshade producing fantasias u aedais, not unpleasant visions, what today we would say is psychedelic. So just looking at the literature and the kind of literature that even most classicists, I didn't really learn it in undergrad, I came across Dioscorides later, but just a basic look at the literature supports what McGovern has been testing, which is the fact that wine was routinely mixed with different compounds. It's fascinating, by the way, that language effects our conception of the tools we use to understand the world. So like, you can see wine, you can see psychedelics, if they're not called drugs, you can maybe reframe how you see them in terms of their role in us thinking about the world, understanding the world. That's really interesting that language has that power. But what language was used to understand wine at the time? So we're talking about a Greek-speaking world, right? So Jesus is born and does his public ministry in the Holy Land, but think about the early Church. Think about where the Church takes root. Paul, the greatest evangelist of the time, writes basically half the New Testament. He's writing letters in Greek to Greek speakers in places like Corinth in Greece, or Philippi, a defunct city just north of the island of Thassos, or he's writing to folks in what today is Turkey, the Colossians, the Galatians, he writes letters to the Romans. These are Greek speakers in these pockets, these Hellenic pockets all around the ancient Mediterranean. And for them, again, ignore Dioscorides, ignore Pat McGovern's work. To them, to think about wine was to think about a mixed potion. And so the word oinos in ancient Greek does show up in the New Testament, but there was another word to describe wine, and it exists for like a thousand years, before, during, and after the life of Jesus. The word used for wine is pharmakon, which obviously gives us the word pharmacy. It means drug. So in Greek, a Greek speaker would actually use the word drug to refer to wine. Ruth Skodal, the classicist, talks about this as a ritualistic formula. They understood wine as this compound beverage, a drug against grief, a medicinal elixir that could either harm or heal, or just maybe a sacrament to put you in touch with wine gods old and new. Clearly, religion and myth, but religion very much so has sort of, sort of, much like dreams, has like an imagery component. Like you're kind of going outside the visual constraints of physical space, where you kind of have very specific conceptions of what things look like, and you kind of use your imagination to stretch beyond the world as we know it. Things that are, try to get in touch with things that are more real than real. So what role do these tools, do these pharmakons have in trying to stimulate the imagery of religion? Do you have a sense that they have a critical role here, or is this just a bunch of different factors that are utilized, a bunch of different tools that are utilized to construct this imagery? Or is this not even, or is imagery the wrong terminology? Is it more like space of ideas that's core to religion? No, I think the wine is absolutely essential. And so if it's impossible to understand paleo-Christianity in the absence of ancient Greek, I think it's equally difficult in the absence of the sacred pharmacopeia, or wine itself, right? Just think about wine at the time. I think that the ancient Greek audience would have heard that in a very different way from us. And so they're referring to it maybe as a pharmakon, but the followers of Dionysus, which precedes Jesus. And in some cases, the story of Jesus is kind of a recapitulation of the mysteries of Dionysus. But when you think about Dionysus, maybe from your high school mythology, you think about him as the god of theater, or the god of wine, which is typically what it is, or the god of ecstasy. Again, Dionysus is not the god of alcohol. There's no concept of fermented grapes. The power of Dionysus and the ability to commune with Dionysus through his blood, and before Christianity, the blood of Dionysus is equated to his wine. The sacramental drinking of the wine was interpreted, and classicists write about this, including Walter Burkert, it was interpreted as consuming the god himself in order to become one with the god. This is where we get the idea of enthusiasm because the language matters, enthusiasm to be filled with the spirit of the god so that you became identified with Dionysus and acquired his divine powers. Now, how does that happen? Again, he's not the god of alcohol. He is the god of wine, but he's really the god of madness, and delirium, and frenzy. And his principal followers are women. They're called the minads. And the way they get in touch with him is through the consumption of this sacramental wine. Even at the theater of Dionysus, separate from his outdoor churches, there was a wine served there called drima. And this is the wine that gives birth to Hollywood. I mean, the ancient Hollywood was there at the theater of Dionysus. This is where comedy, and tragedy, and poetry, and music come from. But rather than a hot dog and a beer, what they'd drink at the theater of Dionysus was this wine called drima, which means pounded or rubbed. And Professor Ruck talks about maybe it was the drugs that were rubbed into this theatrical beverage to help the play come alive. So madness is seen as a positive thing, as like a creative journey. It's not, it's not, it's a, what is it, the unlearning, getting out of the way kind of thing. Is that how it's seen? Or is it more like entertaining escape from life that is suffering? I gotta inject a little modern Dostoevsky into the old. Existential despair. Maybe it's a bit of that. We can't say that there wasn't recreational drinking happening. The Greeks also had the symposium, right? And they also were just getting hammered in some cases. But when it comes to the rites of Dionysus, what you see there is the creation of these states of awareness in which, again, you identify with the God to become the God. There's theophagy, there's the consumption of divinity in order to become divinity. Right back to how we started the conversation, right? So if we stop conceiving of God as something exterior to us, but that the mystery of being itself is the mystery of your being and the mystery of my being, that the way to encounter that is through the sacramental theology, that you drink the actual blood of this Greek God to become that God. And there was a place for this in ancient Greek society. So drinking the wine is drinking the blood of Dionysus. Do you think Jesus is an actual physical person that existed in history? Or is he an idea that came to life through the consumption of wine and those kinds of rituals? So this is where I face my excommunication, depending how I answer this. I mean, you're playing with fire and wine. A good combination, by the way. Yeah. So I shy away from that controversy in the book. I'm perfectly willing to accept Jesus as a historical personage. We have the multiplicity of sources, although it's a generation after his death. But we have the Eucharist being described in the four Gospels, we have it being described by Paul in 1 Corinthians. But when you read John, it does read a bit differently than the other Gospels. And in my book, I rely a lot on the scholarship of Dennis MacDonald, who writes a fabulous book called The Dionysian Gospel. And this is again why the Greek matters, because once you start to analyze the Greek of John's Gospel, it seems to be a presentation of Jesus very much in the guise of Dionysus. The most obvious example is the wedding at Cana, right? That only occurs in John's Gospel, the famous transformation of water into wine. Now again, to any Greek speaker of the first century, they would have known about the Greek district of Elis on the Peloponnese. And in Elis, around the Epiphany, every January, the priest of Dionysus would deposit these water basins, empty basins, in the temple of Dionysus. They'd return the next morning and find them magically filled with wine. Now, on the island of Andros, it's even more interesting. Around the same Epiphany date, the God's gift day, Dies Theodosia, the wine would emanate from the temple and run like a river for a week. And you can Google the Bacchanal of the Andrians, a wonderful painting by Titian, which hangs in the Prado, and you'll see a river of wine behind these people having a great time. This exists for centuries and centuries, before the wedding at Cana and before Jesus begins his public ministry with what these scholars call the signature miracle of Dionysus. It would not have been lost on the Greek audience that something very specific is being communicated here. What's being communicated? That you just might find in early Christianity what you hold strong to in these mysteries of Dionysus that you may have inherited from your parents, your grandparents, your great-grandparents for centuries. There was a perfectly good religion. There were perfectly good mystery cults in the ancient Greek and Roman worlds. And here comes this new, untested, illegal cult—illegal—of a dozen or so illiterate day laborers that go on to convert the empire in a few hundred years. The answer to that extraordinary growth is not psychedelics, but I do think it's visionary experiences, and I do think it's this continuity from the pagan world into early Christianity. So what part—you mentioned this idea, that's really interesting, I think you said Paul Stamets—of I guess millions of people over millions of years kind of consuming, really practicing a ritual or a habit of some sort. This idea of rituals is kind of interesting. Again, you mentioned cult. What's the role of ritual consumption of some of these substances or just ritual practice of anything in the intellectual growth of particular groups of people or societies? So again, I would say it is the centerpiece of ancient life, not just the mysteries of Dionysus, which we've only talked a bit about, but the mysteries of Eleusis were probably the most famous and longest-lasting of these Greek mystery rites. And I mean, just to put it in simple terms, the best definition for a mystery religion, as the name implies, is something secret. You write muo from the Greek, means to shut the eyes or to shut the mouth, to keep quiet about this stuff. We're always teasing details from the archaeological and the literary record, and we're kind of just grabbing at these secrets. But Eleusis, which survives for like 2,000 years into the Christian period from about 1500 BC to the 4th century AD, it's kind of this centerpiece of Greek life. Cicero, the great Roman statesman, calls what was happening at Eleusis the most exceptional and divine thing that Athens ever produced. So not democracy, the arts and sciences, or philosophy, but the vision that was encountered at Eleusis, perhaps through the ritual consumption of a potent psychedelic over hundreds and hundreds of years, thousands and thousands, if not millions of initiates, pilgrims who would walk from Athens to Eleusis to encounter this vision. It seems to have been not just an important part of Greek life, but the thing that made life livable, such that as these mysteries are about to be exterminated by the newly Christianized Roman Empire, there's this passage in the ancient literature that talks about these, in the absence of these mysteries, life becomes unlivable. Abiotos. Is there ways you can, I mean, you write about the mysteries of Eleusis, and is there ways you can convert that into words? Why those are so important to them, more important than any other invention to them? Why is it such a source of meaning to life? So from what we can reconstruct, they would make that pilgrimage 13 miles northwest of Athens to confront their mortality. Remember we were talking about homo naledi, and in South Africa, this recognition of self-mortality, the deliberate disposal of the dead. Plato talks about the real practice of philosophy being the death and dying process. So in some senses, you went to Eleusis to die and to experience a death before your death. We talked about this with Terence McKenna as well, how the psychedelic state seems to share something in common with the near-death or out-of-body experiences or these ecstatic experiences, whether through wine or beer or otherwise, you went to Eleusis to die. And it was said that only those who had witnessed this vision, whatever vision was to be witnessed in Demeter's sanctuary, it essentially vouchsafed you the afterlife, that only those who went there became immortal. And Cicero says that at that point, you essentially live with more joy and die with a better hope. Can I ask you a question about this human contention with death, this confrontation of death that seems to be at the core of things. I don't know how deep to the core, but it seems to be a central element of the human condition. What do you think about Ernest Becker and those guys that put death at the, what is it, the worm at the core, which as the main thing, the main, like this confrontation of our own mortality, first of all, being understand that we're mortal and then confronting the terror of it, the fear of it as the creative, like trying to escape the fear of death as the creative force of human society. It's like the reason we do anything is because we're just running away from our death scared. Do you find some of that to be true, first of all, as somebody who looks in the mirror, looks at yourself and your own as a human being, two, just looking at society today, and three, at this whole big spread of human history and all the cool stuff we've created, including the mysteries of Eleusis? RWI I wonder what life would look like in the absence of the fear of our mortality. I wonder how we'd interact with one another if there was relatively little or no fear of death. I really do when it comes to Becker's work and others. If the ancients were known for anything, it was running to death. It was the opposite. In fact, dying before dying, which is the immortality key, by the way. It's not psychedelics. When I refer to this key, I'm referring to this notion that's preserved in Greek. Anpethanis, brinpethanis, denthepethanis, otanpethanis. If you die before you die, you won't die when you die. For some reason, the ancients prized that experience. And we talked about the mystics of Sufism and Kabbalism and Christian mysticism, where you have this same self-nodding, this death before death, the divine nothingness, right? Mm-hmm. For some reason, the mystic saints, visionaries, and ancient philosophers, they ran to death. And the one message I wanted to try and communicate with this book is how they viewed life, that it can only be fully experienced, fully embodied in the wake of a really intense, perhaps terrifying, but utterly transformational encounter with death. So, running to death, not running away from death. You talk about Aldous Huxley and mind changers. So, if we look at the history where the ancients were running to death and maybe using some performance-enhancing permacons to run more effectively towards death. And now we're using tools of modern society, whether they're psychological, sociological, or in this case, pharmaceutical, to run away from this conception. So, what do you see as a hopeful future for human civilization? If all of these kinds of societies are ice cream flavors, how do you create the perfect ice cream flavor? What is the future of religious experience of society? What is the future of religious experience, of psychedelic experience, of intellectual journeys, of facing death, running away from death? What do you hope that looks like and what kind of idea should we look to? My next book will be entitled, Performance Enhancing Pharmaca. You get a little copyright. Yeah, I like it. But that's a historical view. What in that book would you suggest in one of the last chapters about the future of this process? Well, Huxley has to stop you. He stopped me in my tracks, Aldous Huxley. So, in 1958, he pens this op-ed of sorts. And it reads incredibly prescient because I really do think in many ways as the fog of the war drug is ending and finally lifting that we've kind of come full circle back to the late 1950s, which might sound strange. It'll make more sense when you hear what Huxley said about psychedelics. And so, he was looking forward to a revival of religion, which is why I subtitled the book, The Religion with No Name. And to him, to Huxley, this revival wouldn't come about through televangelistic mass meetings or photogenic clergymen, as he says. But he points to the biochemical discoveries such as we have today that would allow for large numbers of men and women to achieve a radical self-transcendence and a deeper understanding of the nature of things. In other words, that this revival of religion, he says, would be a revolution. And Alan Watts comes along and says that there's nothing more dangerous to authority than a popular outbreak of mysticism. But I think this is what Huxley was pointing to. And he talks about religion in these terms about being less about symbols and returning to a sense of experience and intuition. And Huxley says that he envisions a religion which gives rise to everyday mysticism. And he talks about something that would undergird everyday rationality, everyday tasks and duties, and everyday human relationships. In other words, religion has to mean something. And these altered states of awareness that we seem to be able to produce quite easily inside the lab at Hopkins, NYU, and elsewhere with psilocybin, I think this is kind of part of Huxley's prediction about a time when we would have legal access, safe access, efficacious access to this material that would allow for insight in an afternoon. And what do you do when millions of people can become mystics in an afternoon? So psychedelics, psilocybin might be the practical way of having these kinds of, maybe could be termed religious experiences. And then many people partaking in those experiences and then evolving this collective intelligence thing we got going on, that's sort of the practice of religion that we should be looking, striving for, as opposed to kind of operating in the space of ideas, actually practicing it. You mentioned, and that's the religion with no name, the use of these tools. Is there a simple way to summarize religion per our previous discussion about God, basically discovering the God inside? What if I give you a very complicated definition of religion, and then we talk about a more simplified? Let's do it. So the most complicated we can get on this is the anthropologist Clifford Geertz. But I think it's worth defining our terms when we're talking about God and religion. So religion, religio from the Latin means to bind back. So to bind us back to some meaningful tradition, to bind us back to the source. Here's a mouthful from Clifford Geertz. You know, religion, he defines as a set of symbols, which acts to establish powerful, pervasive, and long-lasting moods and motivations by formulating conceptions of a general order of existence and clothing those conceptions in such an aura of factuality that those moods and motivations seem uniquely realistic, which is complex. What does that mean? That religion has to make you feel something, these moods and motivations. But it can't just do that in the way that sex does that for us, or sports, or ultimate fighting, or the World Cup, or going to a concert. So we get all that emotion in these experiences like that. But that emotion has to be concomitant to a deep existential insight that answers this question for you in the morning. I know why I'm here. I know why humans are here. I think I know what the meaning of life is. That's what religion is. And if you find that meaning in science, then that's your religion, and that's fine. But we need to be more honest about that. If your epistemological model is weighing facts and figures, and you think that's why you're here on this planet, and you find deep meaning, that's okay. Religion is the thing that makes you feel, right? It has the aura of factuality. It just makes you feel like you know the point behind existence. In other words, I think it comes down to experience, like Joe Campbell was talking about, like Aldous Huxley mentions about experience and intuition. I think this is how we connect to God. Make you feel like you understand the world. I mean, so that's kind of bigger than science. That includes science, but it's bigger. Do you think, what is real? Do you think there's an absolute reality that we're kind of striving towards understanding? Or is it all just conjured up in our minds? And that's the whole kind of point. We together create these realities and play with them and dance to somehow derive meaning from those realities. And it's ultimately not very deeply integrated into atoms of space-time. Another easy question, Lex. Well, I mean, you have to kind of, when you're thinking about emotion and making it concrete into something that feels real, you have to start asking, what is real? It's something that, you know, Ben Shapiro has this saying of facts don't care about your feelings. I was always uncomfortable with this. I mean, he's just being spiffy or whatever, but I was always uncomfortable with somehow, first, that the hubris of thinking that humans can have, like, arrive at absolute truth, which is what I assume he means by facts, like things that are uncontrovertible. And then somehow deriding feelings, like feelings are not important. To me, like, the whole thing is reality. The facts don't even, like, facts is reality, feelings are reality, like the entirety of human experience is reality. All these consciousnesses somehow interacting together, making up random crap and together agreeing, they're all going to wear the same colors, rooting for one football team or the other football team or countries, all those things, that's real, because we've agreed that it's real. And in the same way, it gives us meaning. In that same way, religion is a set of ideas that gives us meaning, but real, it's really a difficult, for me as a scientist, that finds comfort in the physical understanding of the universe, of physics. I love physics, I love computer science. It makes me feel like everything is perfectly understandable. And then I look at humans, they're totally not understandable. It's like a giant mess, but that's part of the beauty. Like, what is love? Like, what the hell is love? It's certainly not like a weird hack to convince me to procreate, because it feels something bigger than that. So like, taking a purely evolutionary biologist perspective, it's missing the, it's not missing, it's only capturing a part of the picture. And so it just keeps making me ask, what is real? Because as a human, it's very human-centric, it does certainly feel like a big part of what is real is all the fake stuff my mind makes up. I mean, okay, I guess, is there something you could say from our discussions about the tools of psychedelics, about our discussion about religion, of what is real, of what is reality? These are largely unanswerable questions. But we should nevertheless strive to answer them. That's the whole point of the human experience. And I think science is one way, and religion is another, and I think there's actually a sphere where they intersect. There's a way for religion to be observable, testable, repeatable, falsifiable. When I look at the ancient mysteries, that's what I find. I think I find people exploring alternate states of consciousness and arriving at conclusions based on that exploration, and deriving deep meaning from that, which yes, are feelings and emotions and very hard to quantify. But nonetheless, these are the things that govern our lives. I mean, I don't know a parent who isn't motivated by the love of their children. Everything I do at 40 years old now is pretty much inspired by my love for my two daughters, and I can't prove to you that I love them. I can say it, I can show you behavior, but it's very hard for me to weigh and measure that. So not everything is so reducible to this quantifiable reality, and yet I also love science, and I love the historical process of weighing this data. I love the chemistry, I love the biology. And for me, I think this was the message of the ancient Greeks, and I think this is the world in which paleo-Christianity was born. I think there is this meeting ground between science and religion which allow for the, if not the discovery, then at least the near-identification of the ultimate reality, which is another way to describe God, right? This being of beings, the transcendent mystery. So speaking of God, you mentioned to me offline you're wearing the most sophisticated clothing choice of the elite intellectuals. Like you mentioned, Sam Harris was wearing a hoodie. This is the Sam Harris hoodie. He's starting a trend. He's starting a trend. This is a new religion, you could even say. It's a ritual. It's a ritual practice of intellectuals of searching for meaning. So there's quite a fascinating debate. He was for a time still known as one of the sort of new age atheists. So he was kind of trying to explore the role of religion in society and the role of science. And on the other side, another kind of powerhouse intellectual is Jordan Peterson, who in sometimes for my taste, a bit too poetic of ways is exploring the ideas of religion. And they had these interesting debates that I think will continue about the role of religion in society. For Jordan, there's all these flaws with religion, but there is a lot of value to be discovered amidst the rituals, the traditions, the practice, the way we conceive of each other because of the ideas that religion propagates. And then for Sam, it says that everything about religion basically gets in the way of us fully realizing our human potential, which is deeply scientific and rational and sort of like we're surrounded by mystery. Calling that mystery God is getting in the way of us understanding that mystery. What do you think about this debate about the role of religion in society? We should continue having this debate. I talked to Jordan a couple weeks ago, as a matter of fact. On his podcast? Yes. Excellent. It'll be out soon. And so, he and I... How did that go, by the way? It was incredible. Carl Ruck, the professor, joined us, as a matter of fact, for one of his rare public appearances. Beautiful. We went deep. And Jordan is very well-read, obviously, on the psychedelic literature. He had just had Roland Griffiths from Hopkins on the podcast. And it's one of Roland's figures that Jordan and I... Again, just like the language of Aldous Huxley, it's hard to move past the following statistic. Over the past 20 years of the modern study of psilocybin, Roland will tell you that about three in four of their volunteers walk away from their single dose of psilocybin, high dose, saying it was among the most meaningful experiences of their entire lives, if not the most meaningful. And Jordan says, like, how do you... What do you do with that? How do we synthesize that? Here we are quantifying the qualifiable, the unqualifiable. And yet, these compounds have dramatic effects on people's lives, and they walk away feeling like they're more loving, more compassionate. The Science of All talks about the welling up of cooperation and resource sharing and kindness and all these strange things from this single chemical intervention, which seems to reduce us to automata as if enlightenment can be flipped on like a switch. And yet, there it is. There's the data. And I don't see how you walk away from that. I mean, I completely understand Sam's position. But I think there's a reading of religion, particularly the mystical core of the big faiths, and especially these ancient mystery cults, which do speak, again, to those moods and motivations, creating this aura of factuality that these volunteers never walk away from, permanently transformed, just like the ancient mysteries. And part of that is perhaps language, that we need to continue to evolve language in how we conceive of these processes. Maybe religion has a bunch of baggage associated with it that is good to let go of. Or perhaps not. I don't know. This is connected to our previous part of our conversation is the importance of language in this whole thing. Well, that's how I start my book, with one of these volunteers from the NYU psilocybin experiments, this woman, Dinah Baser, who's an atheist. And she still describes herself as an atheist. And yet, as one of these three and four people who walked away from this experiment transformed, she says that her experience of psilocybin was like being bathed in God's love from an atheist. And I ask her why she uses the word God. Why not the love of the cosmos or the universe or Mother Nature? And she says, well, frankly, we don't know about any of this stuff and that God makes sense to me. She's still an atheist, but it's the way she describes that as kind of like the way your mother's love must have felt when you were a baby. Yeah, there's a kind of, I like the way Einstein uses God, God doesn't play dice. There's a poetry, there's a humility that you don't know what the hell is going on. There's a humor to it. I'm a huge fan, especially like more and more of just kind of having a big old laugh at the absurdity of this world and this life as represented nicely by memes on Twitter kind of thing. I mean, there's a sense in which we want to be playing with these words and not take them so seriously and being a little bit lighthearted and explore. Let me ask you about, because you mentioned NYU, what I find fascinating is how much amazing research, speaking of science, right? Studying the effects of psilocybin, studying the effects of various psychedelics, MDMA on the human mind right now for helping people. But I'm hoping there'll be studies soon at Hopkins and elsewhere that allow people that are kind of more quote unquote creatives or regular people that don't have a particular demon they're trying to work through, a problem they're trying to work through, but more like to see what can I find if I utilize psychedelics to explore. Is there something you could say that is exciting to you, that's promising about the future, what currently is going on, but also the future of psychedelics research at Hopkins and elsewhere? Yeah, the healthy normals, the healthy normals. I was looking for the right words because normal doesn't feel, healthy doesn't feel like a good term and normal doesn't feel like a good term because we're all pretty messed up and we're all weird. Well, those with ontological angst in that case. Great. Maybe there'll be a future DSM qualification. There's no doubt that things like psilocybin, MDMA are useful for things like anxiety, depression, end of life distress, PTSD, alcoholism, you name it. And it's largely because of the clinical research that MDMA and psilocybin will probably be legal in some FDA regulated way in the next five years. But I mean, again, I start the first page of my book with this question, why do psychedelics work across all these different conditions? And the best that I could find is the meaning, right? Tony Bosses at NYU talks about psilocybin, for example, as meaning making medicine, which is interesting because it puts it somewhere between a therapeutic and again, this ontological instigator. What is it about psychedelics that creates these mystical experiences or mystical like experiences? You can call them emotional breakthroughs, you can call them moments of awe. I do think we get locked up in the language and we're somewhere between science and religion here, including legally. So the FDA is one route to this. What excites me about psychedelics is the first amendment. What is this gonna mean for religion? The freedom of religion being the first thing that's mentioned in the first amendment before freedom of speech, freedom of assembly. If America is known for anything, it's a refuge for religious pioneers. And so we already have the Native American church, Brazilian spawn churches that are using psychedelics. But what would happen if Judaism or Christianity or Islam were to begin incorporating the very ritual, very sacred and discreet use of psychedelics as part of their liturgy? So not replacing the Sunday Eucharist in the case of Christianity, but part of the extra credit dimension of the faith. Extra credit. And then we can, through practice, figure out how essential it is. It could be a minor thing, it could be a major thing. That's another thing I wanted to kind of ask you is I recently, despite the fact that I'm eating a huge amount of meat and I'm getting fat, I'm loving it. This is actually, as of two days ago, I started this long road to training for David Goggins, to training back to, to getting back to competing in jiu-jitsu. So the fun is over, but I also partook in fasting and there was a very strong, there's an almost like a hallucinogenic aspect of fasting, especially because it was a 72 hour fast versus a more common fast that I do, which is 24 hours. And a bunch of people talk about throughout history about the value of fasting in having these kind of visual, these kind of intellectual experiences. Also there's meditation, Sam Harris with the hoodie. Do you have a sense that those other rituals of fasting, of meditation, and maybe other things could be as essential or more essential to the religious experience as psychedelics? Yes, if not, and this is going to sound weird, but maybe not if more so. I look at psychedelics as a catalyst for spiritual investigation, not as the superficial means to an end. I think their value is in kind of serving as a Google Maps for the kingdom of heaven. Ram... All right, I like this. Well, so Ram Dass' teacher said that when he was offered psychedelics that it'll get you in the room with Jesus, but it won't keep you there. Okay, yeah. And I think that's all well and good, but what if you don't know where the house is in the first place? What if you've never had a mystical experience? What if religion is anathema to you? What if you hate God? What if all these words mean nothing to you? And they probably do for many, many people, and it's perfectly understandable. I think that we've lost the coordinates to these irrational states, again, that were prized throughout antiquity and that continue to be prized by the mystical communities, even in big organized religion. It just doesn't filter out that much. And so, psychedelics, in my mind, help orient our minds, bodies, and souls towards the irrational, right? We talked about McKenna's invisible world that seems to have this symbiosis with our own and perhaps has this higher intent for us. You could very well just take catalog of your dreams, right? And that would do it too. But psychedelics seem to be particularly fast acting, particularly potent, and very reliable, especially in the clinical studies. And so, I looked at them as biochemical discoveries, like Huxley did. Maybe it's once in your life or infrequently, right? But maybe that's the beginning of a genuine introspection and a life well examined, as the ancients always instructed us. Yeah, it does seem in the research that the effectiveness of psychedelics always comes with the integration where you use it, just like you said, as a catalyst for thinking through stuff. It's not going to be... I don't even know if Google Maps... Oh, maybe Google Maps is the right analogy, but it doesn't do the driving for you. You still have to do the driving. It just kind of gives you the directions. So, after you come down from the trip or whatever, you still have to drive. There's other tools that are kind of interesting. We've been talking about this at the psychological level, but there's also a neuroscience perspective of it. If we kind of like go past the skull into the brain with the neurons firing, there's ideas of brain-computer interfaces. First of all, there's a whole field of neuroscience that's kind of zooming in and studying the firing of the brain, the firing of the neurons in the brain, of how from those neurons emerges all the things that we think that makes us human. That's a fascinating exploration of the human mind. That's, of course, where the psychedelics have the chemical, the biochemical effects on those neurons. There's ideas of brain-computer interfaces, which, if you look at, especially what Neuralink is doing with this long-term vision, with Elon Musk and Neuralink, they hope to expand, he calls it a wizard hat. This is back to the humor on the internet thing. The wizard hat that expands the capabilities, the capacity of the human mind. Do you think there's something there, or is the human mind so infinitely complex that we're quite a long way away from expanding the capabilities of the human mind through technology versus something like psychedelics? I wonder how Terence McKenna would answer that question. He looked to shamans as kind of the scientists, the high magicians of the high archaic past and the far-flung future. I'm not going to discount, you know more about AI than I do, so I'm not going to discount it, but I do think that AI paired with the sacred recovery, the archaeology of consciousness, and these states, these archaic techniques of ecstasy that were practiced across time. I think that's a winning combination. Part of what I do in the book is just, I try and lay out the set and setting. That's often talked about with psychedelics. I mean, so maybe psychedelics in the right AI environment is going to work. I think it'd probably work a lot better with that myth and ritual incorporated. So, the reason elusives worked for 2000 years, and let's assume the psychedelic hypothesis has some merit to it, but I think the reason it worked is because you were born into a mythology. You were born into a story about Demeter and Persephone, and you waited your entire life to meet them in the flesh. So, you weren't just preparing for a few months. It was a lifetime of expectation, anticipation, ritual preparation. In fact, some of the early church fathers made fun of the Greeks for essentially just piquing people's curiosity and revving up the anticipation, which has something to do with the outcome, by the way. But in other words, I think we need to create a new mythology around this. I don't think you pop into a laboratory. I don't think you pop into a retreat center from one day to the next. I think that in my own case, I feel like I've been preparing 12 years for psychedelics, and I'm still preparing, including in today's conversation. I'm learning new things, and I'm willing to explore it together with the computer interface. But I do think ritual is a gigantic part of this, and even McKenna would say that. I'll paraphrase him by saying that if you'd met someone who didn't know where they were between the years 1995 and 2005, you would describe them as a fairly damaged person. And yet, who among us knows what was happening in Western civilization between 900 and 1300, let alone 2,500 years ago? So, this is, in many ways, the prophet of the psychedelic renaissance saying that history has lessons. And I don't think they're superficial lessons. I think it cuts to the very core of how and why Western civilization came to be born. Yeah, but that history can be loaded into AI systems, and I do love the idea of whether it's through brain-computer interfaces or without intrusive, sort of, without direct reading of the neurons and more sort of interactive experience with a robot, that you can have an AI system that steers your psychedelic experience. That helps you sort of, when you take a heroic dose of psilocybin, for example, helps steer you, steer your mind, say just the right things. I mean, you could say that kind of thing with, it's a totally open problem, I would say. You talk about set and setting. It's the interesting thing about Johns Hopkins is, you create a comfortable environment, a safe environment for allowing, then if you take a heroic, like a large dose of psilocybin, that you could trust that everything would be safe and you can really allow the exploration of your mind. But then you don't know from a psychotherapy perspective of like during that trip, what a human should say to steer that trip. Like that's a totally open set of problems. And in some sense, probably throughout history, those rituals, you've figured out what are the right things to say to each other. How to collaborate. And maybe if you can turn that into an optimization problem, AI could figure that out much, much quicker. I'm with you. So, Eleusis was known for three things, the legomena, the dromena, the deignumena, the things said, the things done, the things shown. If you can pack that all into your AI interface, I'm in, Lex Friedman. I'm gonna write a proposal and then try to get it through the IRB at MIT. I mean, there is a certain sense in which I definitely wanted to explore psychedelics, I mean, in my personal life, but also more rigorously as a scientist and to push that forward and especially in the AI space. And it is difficult how to do that dance when there's gray areas of legality and all those kinds of things. And we're dancing around them. And some of that is language. And some of that is what we socially conceive of as drugs or not. And you're right that perhaps we can reframe it as religious experiences, all those kinds of things. I mean, it's fascinating because it feels like there's a bunch of tools before us that were used by the ancients that we're not utilizing for exploring the human mind that we very well could be in a rigorous scientific way, in a safe way. And that's fascinating. There's this interesting period in the 20th century of LSD use that many of the people doing research on psychedelics now kind of have their roots in that history. I mentioned that Dr. Rick Doblin, he's one of those people. And there's this interesting story of a bunch of creatives that used LSD or other drugs to help them. What do you make of the idea of somebody like Ken Kesey who wrote One Flew Over the Cuckoo's Nest in part under the influence of LSD? Like, what do you make of the use of psychedelics to maximize the creative potential of the human mind? Is this a crutch or is this actually an effective tool that we should explore? One person's crutch might be another's bungee cord. It depends on that mind. Think about Paul McCartney. I mean, we might not have some of the better Beatles music in the absence of LSD. And what did Sir Paul say in 1967 when he was asked about his use of LSD? He said that he recognized the dangers inherent in it, but that he did it with a very specific, very deliberate purpose in mind. He wanted to find the answer to what life is all about. And I'm not sure what Sir Paul is doing this week, but he's probably not doing LSD. Speaking back to my theory about these substances being catalyzers of spiritual introspection, it came along at a time in their life when I think they were ripe for it, especially George Harrison. Highly recommend the Martin Scorsese documentary about George Harrison. For them, I think it was exactly the way we ought to investigate it, which is, well, mind expanders. This is what psychedelics do, right? That which makes manifest the contents of the mind. In the absence of an experience like that, and it can be in a three-day fast, it can be laying down in a cave, it can be in ritual chanting, it can be in a sun dance, but in the absence of that kind of experience at the right time in your life, it may otherwise be very difficult to find entrance to that kingdom of heaven, which I do think is here and now, getting right back to the very beginning. If we are actually to participate in that eternal principle, how and when? What do you think Nietzsche meant when he said that God is dead? So there's a sense that religion is fading from society, and there's a cranky German that kind of wrote about it. What do you think he meant? He was a cranky German who knew a lot about Dionysus, by the way, which is why I like him. So certainly there's some truth to the mortality of God. I think Gallup put out a study only a couple months ago where church membership is now officially in the minority in the United States at 47%, according to the most recent poll. That number was closer to 70% only 20 years ago. Wow. So we're living through something, and we're living through the unchurching of America, and it's the rise of the spiritual but not religious, you know, the inheritor of all traditions but the slave to none. There's a rise in the unaffiliated, the nones. I think it was like one-third of millennials. It's probably much higher now that don't affiliate with any religion. So in that sense, God is absolutely dead, but maybe not the God that we were trying to define at the very beginning. So Nietzsche also looked forward to the Übermensch, which would be a fully realized human being that despite the death of God did not fall into nihilism and amorality, existential despair, all that great German stuff. And there are some commentators who talk about this eternal recurrence that just maybe by incorporating some of these techniques, not necessarily doctrine and dogma, but I would say the techniques of antiquity. And again, Nietzsche writes a lot about the rationality of Dionysus having its place in society. If anything, these biochemical discoveries, I think, point us back. They point us back to Dionysus and the responsible incorporation of the irrational into our otherwise society of rational people and our kazooistry. I have a sense that there will be kind of just kind of, as you've implied, that there will be maybe the God of old is dying and there'll be a rebirth of different kind of God and it'll just keep happening throughout history. I do think there will be a time where AI will be the gods we'll look to. The other, the super intelligent, those kinds of things. There's a little bit of an inkling of religious longing for meaning in the way people conceive of aliens currently. I mean, I talked to a bunch of people about UFOs, EOPs and aliens. And so to me, it's very interesting for perhaps different reasons, because I'm just, I look up to the stars and it's incredibly humbling to me to think that there's trillions of intelligent alien civilizations out there, which to me seems likely or perhaps not intelligent, perhaps just alien life. And actually also that we don't even understand what it means to be intelligent or do we understand what it means to be alive. The time scale, the spatial scale, which patterns of atoms can form in a way that you can call life. It's just could be way weirder than we can imagine. And certainly way different than human life. Anyway, that to me is humbling. And so it's almost like with the simulation, conceiving of the world of simulation, thinking of aliens to me is a useful thought experiment of like, what would aliens look like if they visited? How would we know? How would we communicate with them? How would we send signals to them if they're already here and we don't see them? How's that possible? That seems to me actually likely, it would just be too self-centered and too dumb to see them if they're already here. Anyway, but so that's kind of the almost the pragmatic, the engineering, the physics sense of aliens, but there's also kind of a longing to connect with other intelligent beings out there, both the fear and the excitement of that. It has kind of a religious aspect to it that I find fascinating. And in the right context, when you remove the skepticism of government from that, it's actually a hopeful longing. Do you see this kind of interest in aliens as it all connected to your study of religion? So you're the first person to ask me about aliens in eight months. So it looks like I'm going on the record. I'll drop some J. Allen Hynek on you. So Hynek, involved in Project Blue Book famously says in 1966, when the long awaited solution to the UFO problem comes, and we're assuming that UFOs have something to do with aliens, but when the long awaited solution comes, I believe it will prove to be not merely the next small step in the march of science, but a mighty and unexpected quantum leap. In other words, I do not think that we're dealing with flesh and blood beings in nuts and bolts crafts. I think it's way, way more complicated than that. And if anything, it takes me back to the ancient world. It takes me back to this invisible college of beings of apparent higher intent. It takes me to the geniuses and the muses. So the first document in Western civilization, Homer's epics, they begin by invoking an alien. They invoke a muse. Andra mojenepe musa, polutre van jos malapola. Tell me, oh muse, about the man. So Homer isn't inventing poetry. He's channeling poetry, epic poetry from an alien intelligence. Maybe that intelligence has felt a little unrecognized in recent years. Trying to show up in human recognizable forms. The muse is trying to give a little hint of its existence. Yeah, I mean, I have a, I've been saying, I honestly sort of, I don't believe this, but I think about this, whether alien, like muses is a great example, whether aliens could be thoughts, ideas we have are the aliens, or consciousness itself is the methods by which aliens communicate with us. Like I find this very kind of liberating to expand our conception of what intelligent beings are. You would like Julian Jaynes. Julian Jaynes writes a great book, The Origins of Consciousness and the Breakdown of the Bicameral Mind. It's this theory that the ancient Greek mind was very different from ours and that when they heard the muses, or the gods and goddesses for that matter, they would hear them as voices in the head and hear it as an internal God figure offering commands, which they couldn't ignore. So were they walking schizophrenics? It might be one way to talk about it before the breakdown of the bicameral mind, but it's a provocative theory, largely untestable. But when you're reading ancient Greek and Latin for that matter, you can't read it very long without bumping up against these discarded entities. They're everywhere. And they survived. They persist across time, which is even stranger, not just in the form of all the things my daughters like, like fairies and gnomes and elves, but, and McKenna loves this, the sylphs and the boulder grinders and the sprites and the gins and elementals. Every society has them. It seems to be fairly universal. And they largely exist in folklore, mythology. This is what Jacques Vallée writes about so wonderfully. We've kind of been sneaking around it, but let me ask you from yours, from everything we've been talking about, how do you think about consciousness? Is it a fun little trick that the human mind does, or is it somehow fundamental to this whole thing? So this three pound lump of jelly inside our craniums that can contemplate the vastness of interstellar space, it can contemplate the meaning of infinity, and it can contemplate itself contemplating on the meaning of infinity, that peculiar self-recursive quality that we call self-awareness. So this is the hard problem, right? This is the unknowable, the unknown at least. I don't know. I have no good answer for that. Aside from that- Do you think it's somehow deeply fundamental to the human experience, or is it just a trick? So you have like, I mean, Sam Harris has really been making me think about this. So, you know, calling free will an illusion. The interesting thing about Sam is that it's not just a philosophical little chatted with him about free will. He really says he experiences the lack of free will. Like he's able to, you know, large parts of the day to feel like he has no free will. In that same way, now he thinks that consciousness is not an illusion. It is, you know, it's a real thing. But at the same, I'm more almost like, I'm almost more of like consciousness seems to be a little bit of an illusion, in the sense that like, it feels like maybe this is a robotics AI perspective, but it feels like in that same way that Sam steps outside of feeling like he has an agency, feeling like he has a free will, I feel like we should be able to step outside of having a consciousness. So that, from my perspective, maybe that's a hopeful perspective for trying to engineer consciousness, but do you think consciousness is like at the core of this, or is it just like language, or almost like a thing we build on top of much deeper human, the things that makes us human? I don't know. I am attracted to Lenz's notion of biocentrism. I mean, it's difficult to walk away from the double slit experiment not wondering why we seem capable of collapsing that quantum wave function. It's very, very weird, giving rise to even weirder ideas about superposition and spooky action at a distance, and things that MIT guys know a lot better than me. But it seems to me fundamental. I mean, maybe consciousness is the fundamental thing. I mean, weirdly, some of these ancient incubatory practices, I talked about Peter Kingsley before. So he's not a proponent of ancient psychedelic use, but is a proponent of these ancient rites of incubation that were practiced by Pythagoras, Parmenides, and Pedocles, other pre-Socratics. And so what were they doing? They were trying to get in touch with consciousness. They were entering into suspended states of animation in these cave-like settings. Pythagoras had built one in his basement and would lie down motionless, apparently, for long periods of time. And what I think they were trying to do was tap into and try to answer this question in their own, you could call it a scientific way, actually, less religion than science. And what they would discover or try to discover was a state of awareness that is somehow beyond life and death, beyond waking and dreaming, where you can be aware of the senses but also in touch with another reality at the exact same time, what Kingsley calls sensation. That, I think, is definitely worth exploring. Well, and the way I hope to explore is by trying to build it. Everybody uses the tools they have. Well, no, I do also hope psychedelics can help. So how do you build that? I'm curious. That's a whole other discussion. There's a lot of things I could say here, but let me put simply is I believe that you can go a long way towards building consciousness by trying to fake consciousness. So fake it till you make it, as an engineering approach, I think will work for consciousness. You seem satisfied with that. I'm satisfied with that because I know how deeply unsatisfied others are, but just wait. I mean, I don't know what to... So the topic of consciousness is mostly handled by philosophers currently, and that's great, and their philosophers are wonderful and good at what they do. I'm not a philosopher. I'm an engineer, and I think the approach there is quite different. I think falling in love is different than trying to have a podcast conversation about what is love. I think the engineering effort is just fundamentally different than the philosophical effort, and I have a sense that consciousness can be engineered even before it is understood by the philosophers. So I think there's a bunch of things like that in this world that could be engineered before they're understood. I think the intelligence is one such thing. I think we'll be able to engineer super intelligent beings before we're able to understand the human mind. Yeah, I mean, there's a lot of intuition to unpack there of why that is, but as it stands, that's perhaps my engineering optimism and engineering ethic under which I operate. Consciousness is easy to build, hard to understand. Okay. Are there books or movies in your life, long ago or recently, that had a big impact on you? Immortality Key is exceptionally well researched. The amount of books you read is, I cannot even imagine. So is there something in those, in your travels through the land of language that stuck with you that was especially impactful? I mentioned a couple of them, but... So I knew nothing about psychedelics before 2007, and it was in hearing about some of the first psilocybin experiments at Hopkins. And then shortly thereafter, I went down this rabbit hole. And so the first set of recommendations all kind of fit in that time period in my life, 2007, 2008. It started with Jeremy Narby, The Cosmic Serpent, DNA and the Origins of Knowledge. It was a total impulse buy at the Barnes and Noble on 6th Avenue in New York, and wound up introducing me to Supernatural by Graham Hancock. That convinced me that there was a long story to psychedelics that he tried to prove in that book, and that we're still trying to prove. I mentioned the connection between ritual psychedelics and cave art. This is the neuropsychological model that was first proposed by David Lewis Williams at the University of Waterstrand, the same university where Lee Berger is, by the way, in South Africa. So these ideas are old. But what Graham did in that book is just, it's well worth your time. It's well worth a few reads, actually, because it was after that that I discovered Breaking Open the Head by Daniel Pinchbeck. And a lot of other books that just kind of blew my mind. What is Breaking Open the Head about? So it's Daniel's romp through contemporary shamanism. And it's his very well-told experiences with everything from psilocybin to iboga being initiated by the Bwitis. And it was the first time I'd read any firsthand accounts, aside from Jeremy Narby, any firsthand accounts by a New Yorker, by the way, about the potential for these compounds that I'd been ignoring for far too long, obviously. And so, that's when I started revisiting The Road to Eleusis and looking through the anthropological literature, reading everything Gordon Wasson had ever written, that Karl Ruck had written. And it sent me down a pretty weird rabbit hole until I found Peter Kingsley, which is my second recommendation. So Peter, again, he's not a fan of the psychedelic hypothesis, but what he does is, I think, expose the value of the irrational to the ancient Greeks, especially the pre-Socratics. Here we are talking about AI and God and these entangled philosophical questions. The best I can read Kingsley is that Western civilization is a product of a gift from the goddess Persephone. And this is not a hippie, this is a pretty gold standard classicist who went on to write a couple of books. One is In the Dark Places of Wisdom, and the other is Reality, what better way to title your book, where he talks about these ancient techniques for exploring the irrational, the same thing Karl Ruck was talking about. After compiling all this data in The Road to Eleusis, Ruck says that the biggest challenge is trying to convince his colleagues in the late 1970s that the ancient Greeks, and indeed some of the most famous and intelligent among them, could enter so fully into irrationality, same thing Nietzsche's talking about in his exploration of Dionysus. And so, I think Kingsley just stands apart as one of those books, Reality, that my life was never quite the same after reading them. We talked about the three pound jelly that is able to conceive of the entirety of the fabric of reality in the universe and everything, and also of its own mortality. What do you think is the meaning of it all? What's the meaning of life? Is a three pound jelly able to answer that one? No, but I can plagiarize Joseph Campbell, which is good enough. Joe Campbell says that, I don't think what we're looking for is a meaning of life. I think what we're looking for is an experience of being alive so that the experiences we have on the purely physical plane will have resonances within that are those of our innermost being and reality. You talked about the true reality, absolute truth. These are all constructs, and I think they're constructs that are made day by day and acquire this aura of factuality. Remember in Clifford Geertz's definition of religion, we're all just faking it until we make it. And I think a lot of that has to do with moods and motivations and feelings and emotions, which is not to discredit facts and figures. But I think that meaning, meaning making, is a very subjective process that is not only difficult to talk about, but difficult to quantify. And experience is a primary in that versus, so like the actual subjective experience is primary to the meaning making process versus like some kind of rigorous analysis of like having an algorithm that runs and computes and then finally spits out 42. Well, this is how families are created. Tell me more about this. Well, my wife and I fell in love and made babies. We didn't type up an Excel sheet and figure out the best way to go about this. We just- That's what I've been doing wrong all these years. That's why I'm single. Too many Excel sheets. Well, we say falling in love, right? We say fall in love. What does that mean to fall in love? You are surrendering to an intelligence that is beyond us. You could say a godlike intelligence. Richard Rohr, the Franciscan friar I mentioned in the Universal Christ, he writes a lot about how the divine for you is often encountered in the other. In fact, how could it be otherwise? This is bedrock sacramental theology that you find the god in the things in your life as well you should. That's the proving ground for identifying as god rather than creating relationship with god. And so I think that these irrational states play a big role in that. Irrational. Well, I don't think there's a better way to end it than on the topic of love. Brian, thank you so much for a brilliant exposition of history and the poetry. I really appreciate you talking with me today. I love you, Alex. I love you too, Brian. Thanks for listening to this conversation with Brian Miorarescu. And thank you to InsideTracker, GiveWell, and I, Indeed, and Masterclass. Check them out in the description to support this podcast. And now let me leave you with some words from Terrence McKenna about psychedelics. Part of what psychedelics do is they decondition you from cultural values. This is what makes it such a political hot potato. Since all culture is a kind of con game, the most dangerous candy you can hand out is one which causes people to start questioning the rules of the game. Thank you for listening. I hope to see you next time.

https://youtu.be/oYQh1ZNkC70

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Steven Pressfield: The War of Art | Lex Fridman Podcast #102

The following is a conversation with Steven Pressfield, author of several powerful nonfiction and historical fiction books, including The War of Art, a book that had a big impact on my life and the life of millions of people whose passion is to create in art, science, business, sport, and everywhere else. I highly recommend it and others of his books on this topic, including Turning Pro, Do the Work, Nobody Wants to Read Your Shit, and The Warrior Ethos. Also, his books Gates of Fire, about the Spartans and the Battle of Thermopylae, The Lion's Gate, Ties of War, and others are some of the best historical fiction novels ever written. As some of you know, I don't shy away from taking on a big difficult challenge. One of the hardest for me, and for millions of others, is the discipline of staring at an empty page every day, pushing on to think deeply to create despite the millions of excuses that fill the head. In his work, Steven has articulated this struggle better than anyone I've ever read. Quick summary of the ads. Two sponsors, The Jordan Harbinger Show and Cash App. Please consider supporting the podcast by going to jordanharbinger.com slash lex and subscribing to it everywhere after that, and downloading Cash App and using code LEXPODCAST. Click on the links, buy all of the stuff, it really is the best way to support this podcast. This is the Artificial Intelligence Podcast. I recently considered renaming this podcast, but decided against it. AI is my passion, and in some sense, this podcast is not as much about AI, but more about a journey of an AI researcher struggling to explore the human mind, the physics of our universe, and the nature of human behavior, intelligence, consciousness, love, and power. I will continue to return home to the technical, computer science, machine learning, engineering, math, programming, but also venture out to talk to people who had a big impact on my life outside the technical fields. Writers like Steven Pressfield and Stephen King, musicians like Tom Waits, political leaders like, well you know who, and even athletes. I hope you join me on this journey. As usual, I'll do a few minutes of ads now, and no ads in the middle that can break the flow of the conversation. Click on the links, buy all of the stuff, it's the best way to support this podcast. This episode is supported by the Jordan Harbinger Show. Go to jordanharbinger.com slash Lex, it's how he knows I sent you. On that page, there's links to subscribe to it, on Apple Podcasts, Spotify, and everywhere else. I've been binging on this podcast. Jordan is a great human being. He gets the best out of his guests, dives deep, calls them out when he's needed, and makes the whole thing fun to listen to. He's interviewed Kobe Bryant, Mark Cuban, Neil deGrasse Tyson, Garry Kasparov, and many more. I just finished listening to his recent conversation with Mick West about debunking conspiracy theories. This topic can be both fascinating and frustrating on both sides, but in this conversation, Jordan thread the needle beautifully, and so it turned out to be a great listen. I highly recommend it. Again, go to jordanharbinger.com slash Lex, it's how he knows I sent you. On that page, there's links to subscribe to the show, on Apple Podcasts, Spotify, and everywhere else. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as one dollar. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend Ascent of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago. The US dollar created over 200 years ago, and the first decentralized cryptocurrency released just over 10 years ago. So given that history, cryptocurrency still very much in its early days of development but it's still aiming to, and just might, redefine the nature of money. So again, if you get Cash App from the App Store or Google Play and use the code LexPodcast, you get $10. And Cash App will also donate $10 to FIRST, an organization that is helping advance robotics and STEM education for young people around the world. And now, here's my conversation with Stephen Pressfield. So, modern society in many ways dreams of creating universal peace. And yet war has molded civilization as we know it throughout its history. So let's start at the high philosophical level. If you could imagine a world without war, how would that world be different? Perhaps put another way, what purpose has war served? Why do we fight? I think we're basically the same creatures internally that we were in the cave, right? In tribal society back for however many, you know, hundreds of thousands, millions of years. Which means that we're in, the dynamic in our mind is a kind of an us versus them dynamic where our tribe is the people and everybody else are whatever, you know? And I don't see that, I don't think that's changed one iota over the centuries. It's just a question of how one might sublimate that urge to compete. I mean, you're a martial artist, you know, that, you know, a great part of your day I'm sure is dedicated to reaching that place of, you know, of total commitment and in the face of competition, in the face of adversity, et cetera, et cetera, which is, I think, natural and great for the human race on an individual basis. So, the hope that I have, if there is any hope, personally, I don't think the human race is going to be around very long, but would be in sports or in other kind of sublimated activities where people can act out their need for conquest or aggression or so forth, but at the same time relate to their opponents as human beings and when the game is over, you know, you embrace your competitor and stuff like that. So, you think war was inevitable? It's a part of human nature as opposed to a force, a creative force in society that served a benefit? Well, I'm sure it has benefited, you know, spreading cultures and mixing cultures and stuff like that, but I think the urge to conquest, if you think about Alexander the Great or Julius Caesar or Napoleon or anybody like that, or even individual, or if we even think about one of the plants that we're looking at right outside, I mean, if you let a particular plant have its way, it would take over, you know, the whole hillside. And certainly in the days of Alexander the Great, let's say, there were, who knows, over the face of the earth, hundreds of little kingdoms, China, Japan, Asia, Europe, wherever, and every prince that grew up dreamt of conquering his neighbor and conquering a neighbor after that. That seems to be a universal human imperative, at least in the male of the species. So… And war is just a realization of that imperative? I think so. So you've written about Spartans in the Battle of Thermopylae, about Alexander the Great, about the Six-Day War in 67 in Israel against Egypt, Jordan, Syria. What war, not just out of those, but in general, do you think has been most transformative for the world? Well, these are great questions, Lex. Tough, easy ones, right? I mean, I wish I knew more about the Mongols, because I certainly, from what little I know, I think that was a very, their conquests were very transformative, bringing cultures, you know, in a horrible, bloody way together. But, gosh, what's been the most transformative? Maybe the Roman conquest, you know, establishing the Roman Empire and bringing that culture, maybe Alexander the Great's wars that, you know, united East and West at least for a minute. So building of empire, do you have a sense? So there's wars, I mean, the Six-Day War is not about building empires, it's about deeply held religious, cultural conflict and holding the line, holding the border. And then there is conquests like the Mongols that, what is it, some large percentage of the population is a descendant of Genghis Khan, I believe, right? So that has transformative effects. And then World War II, I mean, personally, and my family and so on, that transformative effects. Let me ask you this, Lex, why are you, what are you trying to get at with these questions? What is this kind of the theme that you're aiming at? Well, I talked to Eric Weinstein, and he said everything is great about war except the killing. And there's a romantic notion of war. Certainly there's a romantic notion of being a warrior, but there's a romantic notion of war that somehow there's a creative force to it. That because we fight, out of that fighting comes culture, comes music and art, and more and more desire to create with the societies that win. And to me, war is not just, hey, I have a stick, and I want your land. It's some kind of, like, it has echoes of the creative force that makes humans unique to other animals. Like, wars, it can't be just four people or 10 people or 100 people. You have to have thousands of people agreeing, usually thousands or more, for something so deeply that you would be willing to risk your own life. And there's a romantic notion to that. And because you've written so well and passionate about some of these, I wanted to see, because I don't have any answers, I wanted to untangle that. If there is a reason we fight that's more than just anger and hate and wanting to conquer. Let me take it from a completely different side. I don't think that I, in writing about war, am really that interested in war per se. I'm more interested in the metaphor. I think, for me, I'm really writing about my own internal war, and the war against myself and against my own resistance, my own negativity, all of those things that are, that spirituality would be the opposite of. So I'm not really an expert on war. It's not like talking to Jim Mattis or to, you know, Victor Davis Hanson or whatever. To me, the human being, we are spiritual beings in a physical envelope. And there's an automatic, automatic, terrible tension within that, which creates a war inside ourselves. So the outer war, when I think about the Israeli army standing up to, you know, whatever, 10 to one odds or whatever it was, that is a metaphor to me of the fight we're fighting inside ourselves. For me, the Six Day War was, as you know, my feeling was it was about a return from exile. It was sort of the culmination of the reestablishment of the state of Israel, which had never really been completed because the holiest places of the Jewish people were in the hands of their enemies. So now, on the other hand, Alexander the Great's conquests, I think, were a whole other different scenario where the metaphor was that Alexander's father, Philip, I think, created the first nation, capital N Nation, and he created a sort of a pathway for these guys who were mountain men and basically barbarians, Macedonians. And by creating this army and this dream of conquering the world, which Alexander took to the, you know, really enacted, he gave them a way of rising out of themselves, of transcending themselves, not just individually, but as a people. So that would go along with what you're saying, Lex, of a certain creativity to it. But again, that's not for whatever. And I'm just realizing this as I'm answering this, that's not really what's interesting to me about these stories. And the Spartans, what was a whole, at Thermopylae, that was a whole other kind of metaphor of war. That was a sort of a willingly going to one's own death for a greater cause. Just like to me, the Spartans at Thermopylae enacted as a group what Jesus Christ enacted as an individual, a sacrifice of their lives for the greater good. I don't know if that answers your question, but that's how I see it. I do feel like, you know, I get invited to speak to Marine Corps groups and things like that all the time, and I decline because I don't really feel like I'm a spokesman for the warrior class or anything like that. That's not what's interesting about it to me. But didn't you just say, with war as a metaphor, that we're all essentially in various ways warriors? If we think of it in terms of Jungian archetypes, and think of our life as, at least as males, and the earliest archetypes that kick in are the youth and the wanderer and the student and that kind of thing. And then at some point around age 15 to 20, whatever, the warrior archetype kicks in. And we want to play football, I want to do martial arts, we want to join the special forces, we want to hang out with our buddies, that's our great bond, we want to test ourselves against adversity, and so on and so forth. But at some point, that archetype, we move beyond that archetype. And we become fathers and teachers and so on and so forth. And then there are many archetypes beyond that towards the end. So I'm interested in the warrior archetype, but not to the be all and end all of everything else. In my book, The Virtues of War, have you read that? Have you read that? There's a character named Telamon, who's actually, it's a long story, but when he's with Alexander's army, and when they arrive in India, he becomes fascinated by the gymnosophists, the fakirs, the naked wise men, the yogis. And he says to Alexander that these guys are warriors beyond what we are, even though they do nothing, because they are inside their own selves all day long. If we go to the Six-Day War, you write about, in Lionsgate, you write about the Six-Day War in Israel. I think of the wars you've written about, it's the one we're still in many ways in the midst of today. Yes. So what is at the core of that conflict in Israel? The Israeli-Palestinian conflict? I mean, today it's the Israeli-Palestinian conflict, but it echoes of the same conflict in that part of the world with Israel. What is, in your sense, the nature of that conflict? What can we learn about society and human nature from that conflict? That is one of the hottest conflicts that still goes on today. Well, when I was working on the Lionsgate about the Six-Day War, I wrote in the introduction that this was not gonna be a multi-sided story. I was taking it entirely, I'm a Jew, I identify with the Israeli people, I was gonna see it entirely from their side. Yes. So that's probably not what you're asking, but to me, the Six-Day War and that whole, you know, it's a piece of land that's holy to at least three religions and probably more. And from the Jewish point of view, it's where the State of Israel, it's where David founded Jerusalem, it's all where the 12 tribes were, et cetera, et cetera, where Moses came and brought the people. So to me, the Six-Day War was about, as I said, a return from exile, from diaspora after 2,000 years. Now, obviously, from the Palestinian point of view or the Saudi Arabian point of view or whatever, it's a whole other scenario. Religion is at the core of this conflict in some ways, religious beliefs. Religion and racial slash ethnic tribal identity. I mean, again, what is a Jew? Is a Jew somebody that believes in the religion or is it somebody of a certain race that race arose in a certain place? Same thing as a Muslim. What is a Muslim? Do they believe in, you know, Muhammad or whatever, or did they arise in a certain place and a certain ethnicity? Because if we landed from Mars, we couldn't tell a Jew from a Palestinian, could we? You know, just looking at them, you could easily mix them and you'd never know. And the specifics of the faith is not necessarily the thing that defines a person. No, I don't think so. All right, so you could be, like many are, secular Jew living in Israel and still have a strong bond. Definitely, definitely. In fact, almost all of the Jews, the fighters that I spoke to from the Sixth Day War were secular. And it really was not, you know, a religious thing with them as much as it was a national thing. So having spent time in Israel, how's the world where military conflict is directly felt, as opposed to maybe if we look at the US, where it's distant and far away? How is that world different? How are the people different? It's very different, as you know. Yeah. I've never been to Israel, actually. Oh, you haven't? I haven't felt it. Well, you should definitely go. I mean, here in the United States, where when like an incident like Charlottesville comes up, you know, where people are chanting, Jews will not replace us, blah, blah, blah. The impulse in the Jewish community is to think of, well, how can we reach out to the other side? You know, how can we either show them that we are human beings like they are and show them that we care for them, et cetera, et cetera. That's the sort of distant from war. If you're in Israel, and you know, like if you and I were Israeli citizens right now, you would be a fighter pilot or a tank commander or whatever. You know, you would not just be, you know, working at MIT or whatever. And I would be in the army, too. And so from their point of view, they say, all those people who hate us, can I curse on this? Of course. On this thing? Fuck them, we'll kill them. We'll kill them. You know, if they dare to cross the line, and that's a whole different point of view. To me, it's actually a healthier point of view. You think so? Yeah. There's no, so let me ask the hard question is, well, maybe it's an impossible question, how do we resolve that conflict? In Israel and... In Israel or... Anywhere. Anywhere where the instinct is to reach out in US and say, F you, and the people, yeah. Here's my, here's, I think that the only way the two warring sides, or two sides that are opposed to one another can ever really come together is when there's mutual respect. We'll get just more water. I got it. When there's mutual respect, and they can see each other as equals, and when there's mutual fear, you know, where one side says, we don't dare cross the line with this other side, and the other side says the same thing. I think then you can kind of reach across that thing and say, okay, we'll stay here, you stay here, we'll mingle in cultural ways, and we'll have interchange, you know, winter marriage, da da da da da da. But as soon as one side has no power, as the Jewish people have had no power throughout the diaspora forever, right, then it's just a human nature, you can see it in Trump and what he does to any vulnerable minority, right? And he's not alone, I'm not blaming him alone, that's human nature. So I do think that that idea of like, fuck you, if you cross the line, we'll kill you, is really a good way, is a good place to start from. Because now you can sit down on opposite sides of the table and say, you know, what do we have in common? How can we, we want to raise our children, you want to raise your children, how can we do this in a way that we're not hurting each other? So you kind of said that you need to arrive at a balance, some kind of balance of power, but you haven't spoken to the fact that there's deeply rooted hatred of the other. So is there no way to alleviate that hatred, or is that, I mean, what role does love and hatred? I think that hatred can go away, I really do. I mean, if you look at even now that I haven't seen this in person, I mean, I've seen it that I haven't seen this in person, but they say that the Saudis and the Israelis are collaborating on certain things, you know, by their mutual fear of or antagonism to Iran. I do think that even really long, long, long standing hatreds and animosities, thousands of years old, can go away under the right circumstances. In a, on what time scale? I mean, for instance, I don't know if this is- Do people have to die, do generations have to die and pass away and new generations come up with less hate, or can a single individual learn to not hate? I think a single individual can learn to not hate, because it certainly doesn't seem to, over thousands of years, doesn't seem to work, you know, we keep thinking that that's gonna happen. But I think it's, we're in a real spiritual realm here when you're talking about that. You're in a realm of, you know, Buddha, Jesus, whatever, something like that, that where, you know, a true change of soul happens. But I do think that's possible. So what do you think is the future of warfare, especially with what many people see as the expansion of the military-industrial conflict? Do you, I know you're not a military historian, I'm asking more as a metaphor. Do you see us as people continuing to fight? You know, it's a really great question, Alex, because I think now with social media, TV, movies, all of these things that create empathy across cultures, it becomes harder and harder I think, I think, to totally demonize the other, the way it was in previous wars. I also think, I don't really see an appetite for people wanting to go to war these days. And in a way, I don't know if that's good or bad. It's like everybody's so fat and lazy and so concerned with how many clicks they're getting that, you know, whereas I know at the start of World War I, both the younger generations were eager to go to war. You know, I think it was insane, but it was that sort of warrior archetype that we were talking about before that generational testosterone, eros thing. Whereas nowadays, I don't know, I mean, it's hard to say there's not gonna be another war because there always are, but it's sort of hard to imagine people getting off their ass these days to do anything. Well, it's funny that you mentioned social media as a place for empathy, sure. But in a sense, it's a place for war as well. For hatred, yeah. For hatred. Perhaps the positive aspect of hatred on social media is that it's somewhat less harmful than murder, and so it kind of dissipates, sort of the hateful, you get the hate out at a less, on a daily basis, and thereby never boils up to a point where you want to kill. It's also a really weird thing that's going on, and I don't know if anybody really understands, like with video games, where kids are acting out these incredible horror things, right? But you know that if they cut their finger, they would freak out, you know? Yeah. And I also don't think that many of the people that are hateful on social media, if they were face-to-face with the person, so there's sort of two mental spheres happening at the same time. And I don't know how that plays out. How that actually maps to military conflict. Yeah, yeah. Like if you in the United States have a draft, for example, how the populace would respond different than they did in previous generations. Yeah, I think they certainly would. Yeah. Another question, not sure if you've thought about it, but I work on building artificial intelligence systems. In our community, many people are worried about AI being used in war, so automating the killing process. With drones and in general, it's being used more and more. I should recuse myself on that one, I really haven't thought about that one. You haven't thought about it. I'd rather ask you what you think about it. Well, it's interesting, I mean, because it's so fundamentally different from, if you look at the Battle of Thermopylae, it means just if we talk about the difference between a gun and a sword. I'll tell you one little anecdote. There was a Spartan king, I don't know which one it was, but at one point they showed him a new invention and it could launch a bolt that would kill someone at a range of 200 yards. And the king wept and said, alas, valor is no more. Because their point of view of war was highly ritualized, as you know, and the code of honor was that you were not supposed to be able to kill another person unless you yourself were in equal danger of being killed. And any other way of doing that, even bow and arrow, was considered less than manly and less than honorable. And maybe we should go back to that because at least it makes the stakes real and true. Not that we could. Not that's the point. You were in the Marine Corps, so we talk about the real, the bloody conflicts. You've written about many of them. So let me ask a personal question. Have you, as writing and in general, have you thought about what it takes to kill a person if you yourself could do it? I have thought about it, yeah. And how that would make you feel? Of course, one never knows. I certainly, I have not been in combat. I haven't killed anybody. But I would imagine in the real world that it would change you utterly forever because you can't help but identify with the person that you've just killed. And it's another human being. And I mean, I have a hard time killing a spider. So I would imagine that it's something that warriors understand and nobody else understands. And you've spoken with many. I mean, you've spoken with people who've seen military combat in Israel. Oh yeah. What, have they been able to articulate the experience of killing? It's sort of just what I said. I mean, I'm even thinking of one pilot that I interviewed over there who was strafing a tank in his Mustang and saw at really low altitude and saw what his bullets did to the guy and could see his face and everything like that, which is even one remove or more removes from an infantryman, what an infantryman does. And he said that same thing that I said, that it just changes you and you can never say it, never look at the world or look at anything the same way again. And when that happens at scale, it's thousands, tens of thousands, hundreds, that changes entire societies. I mean, that's what we've seen. At least it, but the problem is it doesn't change the politicians back home. Right. How important is mortality, finiteness, the fact that this thing ends to the creative process. So killing in war really emphasizes that, but in general, the fact that this thing ends. It does? It does. Shit. And on a serious note, do you think about your own mortality? Do you meditate on your own mortality when you think about the work you do? That's another great question, Alex. Actually, I'm 75 and I just was having, I had breakfast in New York a few months ago with a friend of mine who's like my exact same age. And I said to him, I said, Nick, do you ever think about mortality? And he said, every fucking minute of every day. And I was kind of relieved to hear that because I do too. But I actually, I always have, I think. And I think, you know, the fact of mortality is kind of gives meaning to life. You know, I think that's why we want to create. That's why we want to make a mark of some kind or. And the other aspect of it is what's on the other side of that mortality. I'm a believer in previous lives. So I sort of, and I, the question I've never been able to answer among many, many others is like, why are we even here? Right. Why are we in the flesh? You know, I sort of, I like to believe that God or some force is, we're on some kind of journey, but I'm not sure why, why we were put in this world where the ground rules are, if you think about animal life, that you cannot live from one day to the next without killing and eating some other form of life. I mean, what a demented thing, you know, why couldn't we just have a solar panel on our head and, you know, be friends with everybody? So I sort of, I don't get what that was all about, but that's sort of the big issue. Have you read the Ernest Becker's Denial of Death, for example? Is that Ernest Becker's a philosopher that said that the death, that the fear of death is really the primary driver of everything we do. So Freud had what the- Right. I would agree with that. So to you, you've always thought about even your own mortality. Yes, definitely. And can you elaborate on the reincarnation aspect of what you were talking about? Like that we kind of, what's your sense that we had previous lives? In what, have you thought concretely or is it a lot of it kind of is- No, I've thought concretely about it. Concretely. I mean, it's very clear when you see children, young kids, or even dogs and cats, that they come into the world with personalities, you know, and three kids in a family are going to be completely different and completely their own person. And that person that they are doesn't change over life. And I, you know, there's one of the things that I did in my book, The Artist's Journey, is that there were certain things where I tracked or just listed in order, like all of Bruce Springsteen's albums or all of Philip Roth's books, you know, kind of a body of work throughout over, you know, a period of 30, 40, 50 years, you know. And you can see that there's a theme running through all of those things, that it's completely unique to that person. Nobody else could have written Philip Roth's books or Bruce Springsteen's songs. And you can even see sort of a destiny there. So I ask myself, well, where did that come from? What, it seems to be a continuation of something that was, that happened before and that will lead to something else, because it's not starting from scratch. It seems like there's a calling, a destiny in there already. This gets back to the muse and all that kind of thing. And- So, yeah, it's almost like there's this, let's call it a god, it's passing, it's almost like sampling parts of a previous human that has lived and putting those into the new one. Sampling, this is probably a pretty good word. Taking some of the good, well, you can't take all the good parts because the bad parts is what makes the person. Right. Let's say taking it all together. Okay, this is humans only or does it pass around from animals in your view? I don't know. That's above my pay grade. I don't know. So, okay, so you talk about the muse as the source of ideas, maybe. Since you've gotten a few glimpses of her in your writing, tell me, what is it possible for you to tell me about her? Where does she reside? What does she look like? I mean, you can look at it many different ways, right? The Greeks did it in an anthropomorphic way, right? They created gods that were like human beings. But if you look at it from a Kabbalistic Jewish perspective, Jewish mysticism, you could say that it's the soul, the neshama, right? That the soul is above us on a higher plane, our own, your soul, my soul, and is trying to reach down to us and communicate with us. And we're trying simultaneously to reach up to it through prayer or through, if you're a writer or an artist, when you sit down at the keyboard, you're entering into a kind of prayer. You're entering into a different state of an altered consciousness, to some extent. You're opening yourself, opening the pipeline, or turning on the radio to tune into the cosmic radio station. Another way of looking at it, this is, did you ever see the movie City of Angels? The visual of the movie, it was Meg Ryan and Nicholas Cage. Oh, Nicholas Cage? Yeah, yeah, I've seen it, yep. And right, the visual of the movie sort of was Meg Ryan is a heart surgeon. And as she's operating on somebody, suddenly Nicholas Cage in this long duster coat like Jesse James appears right next to her in the operating room. And he's an angel. And he's waiting to take out the soul of the patient on the operating table. And she doesn't see him. She's totally unaware of him. And so is everybody else in the operating room, except maybe the guy who's about to die, who suddenly sees him. But I kind of believe that there are beings like that. Or if you don't like that, it's a force, it's a consciousness, it's something that are right here, right now. And we, and they're trying to communicate to us. And like through a membrane, like tapping on that window over there, they're like right out there. And they carry the future. They are everything that is in potential. All the works that you will do, Lex, your startup, whatever else you're doing, they know that. And it's not really you that's coming up with those ideas, in my opinion. Those things are appearing, it's like somebody knocks on the door and puts it in. I mean, in the Iliad, where gods and goddesses appear along with the human antagonists on the battlefield all the time, right? They'll be, you know, Homer flashes to Olympus and then back to the real world. And there's a thing where one Aphrodite, let's say, wants to help Paris. And so she says, well, I will appear to him in a dream and I'll take the form of his brother and I'll say, bump, bada, bump, bada, bump. So that's creatures, beings on one dimension, as the Greeks saw it, communicating with, and I believe that that's exactly what's going on in one, whatever analogy you want to use. That communication, to which degree do you play the role in that communication? As opposed to sitting at the computer, if you're a writer, and staring at the blank page and putting in the time and waiting. What, so if, in your view, are these creatures basically waiting to tell you about your future? Or is there choice? How many possible futures are there? How many possible ideas are there? That's a great question. I think there's basically, yes, there are alternatives, degrees within it. But if you look at Bruce Springsteen's albums, how much could he have done really differently? Yeah, he would, you can just see there's a whole impetus going through the whole thing. And nothing was going to shake him off that. And yeah, maybe the river could have been different, could have been called something else, but he was dealing with certain issues. His conscious self was dealing with certain issues that were really out of his control. He was drawn, he was called to it, right? Nothing could stop him. And so it is sort of a partnership, I think, the creative process between the creative impulse that's coming from some other place, or it's coming from deep within us is another way to look at it. It's like if we're acorns and we're growing into oaks. So the conscious artist who's sitting there at the keyboard or whatever is applying his or her consciousness to that, but is also going into opening themselves to the unconscious or to this other realm, whatever that is. I mean, certainly songwriters for a million years have said, a song just came into their head, right? Yeah, yeah. Palm, just all I had to do is write. But then you ever see that thing where of Keats's notes for a thing of beauty is a joy forever? It's like covers an entire page. It's like he's crossing this out and that out and the other thing. So his consciousness is, his conscious mind is working on it. But I do think it's a partnership. And I think that I know when I was first starting out as a writer, I worked in advertising and I tried to do novels that I could never do. I was like really unskilled at getting to that, tuning into that station. I just, I beat my brains out and was unable to do it, except because I was sort of trying too hard. It was sort of like a Zen monk or a monk of some kind trying to meditate and just like constantly thoughts driving you crazy. But over time, you know, knock wood, I've kind of gotten better at it and I can sort of let go of those, that part of me that's trying so hard. And so these angels can speak a little more easily through the membrane. Can you put into words the process of letting go and clearing that channel of communication? What does it take? That's another great question. For me, it just took, it took probably 30 years and I don't even, I would, I guess I would liken it to meditation even though I'm not a meditator. But it would seem to me to be one of the hardest things in the world to just sit still and stop thinking, right? And so it's very hard to put into words. And I think that's why these teachers of meditation use tricks and koans and stuff like that. But for me, at least, I think it was just a process of years and years and years of trying and finally of beating my head in the wall and finally little by little giving up that beating of the head. But there doesn't seem to be any trick. Everybody wants a hack these days and I don't think there is a hack. If you look at it in terms of the goddess, the muse, she's watching you down there, beating your head in the wall. You're like a Marine going through an obstacle course or a martial artist trying to learn, you know, like Uma Thurman in the casket, you know, trying to make that little four inch punch, you know? The muse or the goddess is just sort of watching going, it's Lex, he's trying, he's trying. I'm going to come back in another couple of months and see if he's still there. And finally she'll say, all right, he's paid his dues, I'm going to give it to him. So the hard work and the suffering, yeah. But, you know, I'm also being Russian in wrestling and martial arts, we're big into drilling techniques. I was also just even getting at, certainly there's no shortcut, but is there a process? So you're at, the process of practice. So you had two, one you had an example of meditation, so it's essentially the practice of meditation. I think so, well, drill I think is a good way to look at it too. But what are you drilling? You're just sitting and- You're writing, you know? Just writing. You're writing, then you're looking at what you wrote, you know? You're hitting moments when it flows, you know? And then your other hitting moments where you just can't do anything and you're trying to, from the moments where it flowed, you're trying to come back and look at it and say, what did I do? How did that happen? Where was my mind, you know? But I think it's just a process of over and over and over and over until finally it gets a little bit easier. And did you always, when you read something you write, did you always have a pretty good radar for what's good and not after it's written? No. I think I do now, but no, it was always really hard for me to know what was good. I mean, do you edit, the process of editing is the process of looking at what you've written and improving it. Are you a better writer or an editor? How often do you edit? That's another great question. Because I do think that in writing, the real process of looking at it is the process that an editor does rather than what a writer does. The gentleman I was just talking to on the phone is my editor, Sean Coyne, who was the guy who bought Gates of Fire when he was an editor at Doubleday. And who basically when I finish a book, I give it to him. And he gives me, editing doesn't really mean like crossing out commas, it really means looking at the overall work and saying, does it work? And if it doesn't work, why doesn't it work? Is there something wrong here? Like if you were building the Golden Gate Bridge, and one span was out of whack, you could, and I think a really skilled editor, which Sean is, understands what makes a story tick. And he also has the perspective that I've lost in something I've wrote, because I'm so close to it, to say, you know, this isn't working and that is working. What kind of advice has he given you? Is it like layout, like this story doesn't flow correctly, like you shouldn't start at this point? Or does he even sit back at a higher level and say, I see what you're doing, but you could do better? No, he doesn't do that. Okay. But a lot of it is about genre and kind of defining what genre you're working in. And I'm gonna get up here to just bring something over here for the camera. This was one where Sean tore this down and made me start from scratch. And the specifics of it were really, this is a supernatural thriller, that's the genre, sort of like Rosemary's Baby or The Exorcist. And what he showed me was that I had violated certain conventions of the genre. You know, and you just can't do that. You know, it's gotta be, you know, it has to be done the right way. And so he pointed out certain things to me. So he must be a prolific reader himself too, actually. That's such a tough job of editor. Yeah. Again, he was sort of born to do that. He just kind of glommed onto it. But since he was, his first job publishing, you know, cat thrillers, you know, cat detective, he studied how it works, what makes a story work, et cetera, et cetera. So he really, he's great. And I think any really successful writer, unless they're utterly brilliant on their own, has gotta have a great editor behind them. But you yourself edit as well. I'm constantly trying to learn from him and teach myself. Everything you see in my blog posts that is about the craft of writing is me trying to teach myself the rules so that, you know, I'm sure it's the same in martial arts or anything else, right? You try to not be dependent on that other person because it's so painful to make those mistakes. You really feel like, ah, I wish I could get it right the first time, the next time I do it. And in research, we go through that. In research, more than writing, so what you do is a little more solitary. In research, there's usually two, three, four people working on something together and we write a paper. And there's that painful process of where you write it down and then you share it with other, and not only do they criticize the writing, they criticize the fundamental aspects of the approach you've taken. I would think so. It's exactly like, you know, they would say, you're attacking, you're asking the wrong questions, right? The wrong questions, yeah. And that's extremely, you know, painful. Helpful. Especially when you, well, it's painful and helpful, but there's disagreement and so on. And through that comes out a better product in the end. Because you want to still have an ego, but you also want to silence it every once in a while so there's a balance. In your book, The War of Art, you talk about resistance with a capital R. As the invisible force in this universe of ours that finds a way to prevent you from starting or doing the work. Where do you think resistance comes from? Why is there a force in our mind that's constantly trying to jeopardize our efforts? With laziness, excuses, and so on. That's another great question. I mean, in Jewish mysticism, in Kabbalistic thinking, it's called the Yetzir HaRa, right? It's a force that if this up here is your soul, of Neshamah, trying to talk to you, us down here, the Yetzir HaRa is this negative force in the middle. So I'm not the only one that ever thought about this. But, and I don't know if anybody really knows the answer, but here's my answer. I think that there are two places where we as human beings can see our identity. One is the ego, the conscious ego, and the other is the greater self. And the self in the Jungian sense, the self in the Jungian sense includes the unconscious and butts up against what Jung called the divine ground, which what I would call the muse, the goddess, or whatever. And I think, and the ego is just this little dot inside this bigger self. And the ego has a completely different view of life as from the self. The ego believes, I'm gonna give you a long answer here, Lex. No, perfect. The ego believes that death is real. The ego believes that time and space are real. The ego believes that each one of us is separate from the other. I'm separate from you. I could punch you in the face and it wouldn't hurt me. It would only hurt you. And in the ego's world, the dominant emotion is fear because we are all made of flesh. We can all die. We can all be hurt. We can all be ruined, bump, bada-bump. So we are protecting ourselves and even our desire to create, as we were talking about before, comes out of that fear of death. The self, on the other hand, the greater self that butts up against the divine ground, believes that death is not real, that time and space are not real, that the gods travel swift as thought. And the ego also believes that, I mean, the self believes that there's no difference between you and me, that we're all one. If I hurt you, I hurt myself. Karma, right? And in the world of the self, of the greater self, the dominant emotion is love, not fear. So I think that, let me, I'll go farther back here, a long way to answer your question. When Jesus died on the cross, or when the 300 Spartans willingly sacrificed their lives at Thermopylae, they were acting according to the rules of the self. Death is not real. No difference between you and me. Time and space are not real. Predominant emotion is love. So in my opinion, we as conscious human vessels are in a struggle between these two things, the ego and the self. To me, resistance is the voice of the ego saying, and it's a fearful voice, because if when we identify with the self, we move our consciousness over to the self, as artists or scientists opening ourselves up to the cosmic dimension, to the other forces, the ego is tremendously threatened by that. Because if we're in that space, that head space, we don't need the ego anymore. So I think resistance is a voice of the ego trying to keep control of us. In a way, I'll give you a bad example, Trump is the ego. That's probably a very good example. It's a zero sum world for him and for anybody that's in that. And the opposite of that would be somebody like Martin Luther King or Gandhi. And that's of course why they all wind up getting assassinated. Because that voice, that ego is hanging on to itself and feels so threatened by, I could talk more about this if you want. No, for sure. That's fascinating. It's just, it's interesting why the fear is attached to the ego. I really like this dichotomy of ego and self and that struggle. It's just ego has a, the self obsession of it, why fear is such a predominant thing. Why is resistance trying to undermine everything? It's fear, it's out of fear. Let's think about the whole thing in terms of stories. In a story, the villain is always resistance, is always the ego. The hero is always, of course always is not everything, but you know what I mean, pretty much represents kind of the self. If you think about the alien on the spaceship, that's like the ultimate kind of villain. It keeps changing form, right? First it goes on the guy's face, then it pops out of his chest, but it always just has that one monomaniacal thing to destroy. And just like the ego, just like resistance. And maybe alien is a bad example because Sigourney Weaver has to sort of fight on the same terms as the alien, but maybe a better example might be something like Casablanca, where in the end the Humphrey Bogart character has to, acting, operating out of the self, has to give up his selfish dream of going off with Ingrid Bergman, Neil Salon, the love of his life and instead puts her on a plane to Lisbon while he goes off to fight the Nazis in the desert. I don't know if that's clear, but in almost every story, the villain is the ego, is resistance, is fear, is that zero sum thing. And in almost every story, the hero is someone that is willing to make a sacrifice to help others. It's letting go of that fear is what leads to productivity and to success. Do you think there's a, this is probably the answer is either obvious or impossible, but do you think there's an evolutionary advantage to resistance? Like what would life look like without resistance? That's another great question. I think, I also believe that resistance, like death, gives a meaning to life. If we didn't have it, it's going to be, you know, what would we be? We'd be in the Garden of Eden picking fruit and just happy and stupid, you know? And I do think that that myth of the Garden of Eden is really about this kind of thing, you know, where Adam and Eve decide to sort of take matters into their own hands and acquire knowledge that until then, God had said, I'm the only one that's got that knowledge. And of course, once they've acquired that knowledge, they're cast out into the world you and I live in now, where they do have to deal with that fear and they do have to deal with all that stuff. It's the human condition. It's the human condition and the meaning and the purpose comes from the resistance being there and the struggle to overcome it. To overcome it, right. And also the other aspect of it is that it's not real at all. It's not even like it's an actual force. It's all here, right? So the sort of, in a way, it's sort of a surrender to it, you know? Or it's just- Surrender to its reality. It's sort of like turning on the light in a dark thing. It's like, it's gone. But not quite because it's never really- Not quite, because it comes back again tomorrow morning. Exactly. So you have to keep changing light bulbs every day. So what's been, maybe recently, but in general, maybe in your life, what's been the most relentless or one of the more relentless sources of resistance to you personally? I mean, it's always the same. It's about writing for me and evolving within my own body of work, you know? It never goes away. It never gets any less. Do you have particular excuses, particular justifications that come out? No, it's always the same. Well, I would say it's always the same, but it's really not because resistance is so protean, you know? It keeps changing form. And as you move to hopefully a higher level, resistance gets a little more nuanced and a little more subtle, trying to fake you out. But I think you learn that it's always there and you're always gonna have to face it. So... I mean, your battle is sitting down and writing to some number of words to a blank page. Do you have a process there with this battle? Do you have a number of hours that you put in? Do you sit down? Yeah, I'm definitely a believer that even though this battle is fought on the highest sort of spiritual level, that the way you fight it is on the most mundane... I'm sure it's like martial arts must be the same way. I mean, I go to the gym first thing in the morning and I sort of am rehearsing myself. The gym is called resistance training, right? You're working against resistance, right? And I don't wanna go, I don't wanna get out of bed. I hate that, you know? But I'm sort of fortifying myself to be ready for the day. And like I said, over Knockwood, over years, I've learned to sort of get into the right kind of mindset and it's not as hard for me as it used to be. The real resistance, I think, for me, and I think this is true for anybody, is the question of sort of what's the next idea? What's the next book? What's the next project that you're gonna work on? And when I ask that question, I'm asking it of the muse. I'm kind of saying, what do you want me, or I'm asking it of my unconscious. If we're looking at Bruce Springsteen's albums, it's kind of, well, what's the next album? Now he's on Broadway. That was a great idea, right? Where'd that come from, you know? And then for him, what's after that? Is that body of work is already alive. It already exists inside us, kind of like a woman's biological clock, and we have to serve it. And we have to, otherwise it'll give us cancer. I don't mean to say that if anybody has cancer that they're not, but you know what I mean? It'll take its revenge on us. So the next resistance to me is sort of, or a big aspect of it is, what's next? When I finish the book I'm working on now, I'm not sure what I'm gonna do next. But see, at the same time, you have a sense that there's a Bruce Springsteen single line of albums. It's already known somewhere in the universe what you're going to do next, is the sense you have. In a sense, yes. I don't know if it's predetermined, but there's something like that. Yeah, I'd like to believe that there's, it's kind of like quantum mechanics, I guess. Once you observe it, maybe once you talk to the muse, it's one thing for sure, it was always going to be that one thing. But really, in reality, it's a distribution. It could be any number of things. Yeah, I think so. There's alternate realities. Alternate realities, yeah. But they're not that far apart. I mean, Bruce Springsteen is not gonna write a Joni Mitchell song, you know? No matter how hard he tries. He still went on Broadway, I mean, he still did that, which is not a Bruce Springsteen thing to do. So I think you're being, in retrospect, it all makes sense. I think it is a Bruce Springsteen thing to do. It's a next sort of evolution for him. Why not take his music to there, you know? In retrospect, it all makes perfect sense, I think. If you pull it off, especially. Do you visualize yourself completing the work? Like Olympic athletes visualize getting the gold medal. Do you, you know, they go through, I mean, that's actually a really, you can learn something from athletes on that, is years out, certainly two, three years out, some people do much longer, every day, you visualize how the day of the championship will go, down to, I mean, everything, down to how will it feel to stand on the podium and so on. Do you do anything like that in how you approach writing? No. It's always in the moment. Yeah, it is in the moment, I think. Because it's such a mystery, you just don't know. I think it's different from sports. Right. Because you don't know the destiny. There's no gold medal at the end. No. But I would like to think that as soon as you finish one, the next day you're on the other. And in fact, hopefully you've already started the other. You're already, you know, 100 pages into the other when you finish the first one. But it is a, it's a journey, it's a process. I don't think it is a, in fact, I think it's very dangerous to think that way. To think, oh, this, I'm gonna win the Oscar, you know? It's interesting. For the creative process, it might be dangerous. It's a, maybe you can, like, why is that dangerous? Because I kind of know where you're going. Because it's the ego. It's the ego. Because you're giving yourself over to the ego. You know, I keep saying this myself. My job, I'm a servant of the muse. I'm there to do what she tells me to do. And if I suddenly think, oh, I'm really, I just want to, you know, whatever, the muse doesn't like that. And you know, she's on another dimension for me. I'm trying to square that, because I agree, I'm trying to square that with, I think there's a meditation to visualizing success in the athletic realm, to where it focuses, it removes everything else away, to where you focus on this particular battle. I mean, I think that you can do that in many kinds of ways. And in sports, the ego serves a more important role, I think, than it does in writing. The ego, there's something. Well, let me, when you say that, I know what you mean, Lex. I do think there is a sort of a, you know, it's interesting to watch interviews with Steph Curry, who's such, obviously such a nice guy, but he's got such tremendous self-confidence, you know, that it, but it doesn't border on ego so much, because he's worked so hard for it, you know. But he knows, so he has visualized, he has visualized maybe not so much winning, you know, as just him being the best he can be, him being in the flow, you know, doing his thing that he knows he can do. And I do think in the creative world, yeah, there is a sort of a thing like that, where you, where, you know, a choreographer or a filmmaker or whatever might be, do an internal thing where they're saying, I can make an Oscar-winning movie, I can direct this movie, you know, I'm banishing these thoughts that I'm not good enough. I can do that. I can edit it, I can score it, I can, you know, bump it a bump at a bump. And I don't think that's really ego. I think that's part of the process in a good way, like an athlete does that. So extreme confidence is what some of the best athletes come with. And you think it's possible to, as a writer, to have extreme confidence in yourself? I do think so. You know, that I'm sure when John Lennon sat down to write a song, he felt like, shit, I can do this, you know? I'm not so sure. I think, because the great artists I've seen, you're haunted by self-doubt. It's that resistance. I mean, the confidence. Yes, but I mean, I guess, but even beyond the self, within the self, above the self-doubt. Oh, it's the bigger picture. It's the self-belief, you know? Yeah, I'm freaking out. Yeah, I'm worried that I'm not going to be able to do it, but you know, I know I can do this. Yeah. When you look at, when you take a bigger picture. Yeah. So, the writing process, is it fundamentally lonely? No, because you're with your characters. You are. So, you really put yourself in the world. Absolutely. You know, I've written about this before, that I used to, my desk used to face a wall instead of seeing, and people would say, well, don't you want to look out the window? But I'm in here. I'm, you know, I'm seeing, you know, the Spartans. I'm seeing, you know, whatever. And the characters that are on the page, or that you create, are not accidents, you know? They're coming out of some issue, some deep issue that you have, whether you realize it or not. You might not realize it until 20 years later, or somebody explains it to you. So, your characters are kind of fascinating to you, and their dilemmas are fascinating to you. And you're trying to come to grips with them, you know? You sort of see them through a glass darkly, you know? And you really want to see them more clearly. So, yeah, no, it's not lonely at all. In fact, I'm more lonely sometimes later going out to dinner with some people, and actually talking to people. Do you miss the characters after it's over? Let's say I have affection for them, kind of like children that have gone off to college, and now are, you know, you only see them at Thanksgiving. Definitely I have affection for them. Even the bad guys. Maybe especially the bad guys? Especially the bad guys. You've said that writers, even successful writers, are often not tough-minded enough. I've read that in a post. You have to be professional in the way you handle your emotions. You have to be a bit of a warrior to be a writer. So what are, what do you think makes a warrior? Is a warrior born or trained in the realm, in the bigger realm, in the realm of writing, in the creative process? I think they're born to some extent. You have the gift. Like, you might have the gift as a martial artist to do whatever martial artists do, but the training is the big thing. 90% training, 10% genetics. And I use another analogy other than warrior as far as writer, and that's like to be a mother. If you think about, if you're a writer or any creative person, you're giving birth to something, right? You're carrying a new life inside you. And in terms of bravery, if your child, your two-year-old child is underneath a car, is coming down the street, the mother's going to like stop a Buick, you know, with her bare hands. So that's another way to think about how a writer has to think about, or any creative person has to think about, I think, what they're doing, what this child, this new creation that they're bringing forth. Yeah, so the hard work that's underlying that, I've just a couple weeks ago talked to, just happened to be in the same room, both gave talks, Arianna Huffington. I did this conversation with her. I didn't know much about her before then, but she has recently been, she wrote a couple books and been promoting a lifestyle where, she basically, she created the Huffington Post and she gave herself like, I don't know, 20 hours a day just obsessed with her work. And then she fainted, passed out, and kind of, there was some health issues. And so she wrote this book saying that, you know, sleep, basically you want to establish a lifestyle that doesn't sacrifice health, that's productive but doesn't sacrifice health. She thinks that you can have both, productivity and health. Criticizing Elon Musk, who I've also spoken with, for working too hard and thereby sacrificing, you know, being less effective than he could be. So I'm trying to get at this balance between health and obsessively working at something and really working hard. So what Arianna is talking about makes sense to me, but I'm a little bit torn. To me, passion and reason do not overlap much or at all sometimes. Maybe I'm being too Russian, but I feel madness and obsession does not care for health or sleep or diet or any of that. And hard work is hard work and everything else can go to hell. So if you're really focused on whether it's writing a book, everything should just go to hell. Where do you stand on this balance? How important is health for productivity? How important is it to sort of get sleep and so on? I'm on the health side. I mean, there was a period of my life when I was just, I had no obligations and I was just living in a little house and just working nonstop, you know? But even then, I would get up in the morning and I would have liver and eggs for breakfast every day and I would do my exercise, whatever it was. But although I was still doing like 18 hours a day. But I'm definitely, I kind of think of it sort of like an athlete does. I'm sure that like Steph Curry is totally committed to winning championships and stuff like that. But he has his family, he sees his family, you know, the family is always there. I'm sure he eats perfect, great stuff, gets his sleep, you know, gets the train, you know, whatever a trainer does to him for his knees and his ankles and whatever. So I, or Kobe Bryant or anybody that's operating at a high level. So I do think I'm from that kind of the health school. The good thing about being a writer is you can't work very many hours a day. You know, four hours is like the maximum I can work. I've never been able to work more than that. I don't know how people do it. I've heard of people do 10, 12, I don't know how they do it. So that gives you a lot of other time to do it. Optimize your health. Yeah, to optimize your health. To do the exercise. Because you need to, you're in training, you know. You're really, you're burning up a lot of B vitamins when you're working here. Yeah, but. Maybe it's a Russian thing with you, Lex. Well, it's not even a Russian thing. I mean. It also may be youth, you know. At 35 you can be crazy. You know, that's what they keep telling me, but I'm pretty sure I'll be at it still at a later time, too. I think it has to do with the career choice, too. I think writing is almost, from everything I've heard, it's almost impossible to do it more than a few hours really well. When you start to get into certain disciplines, like with Elon Musk and me, engineering disciplines, that really there's a lot more non-muse time needed. Right, right, right. The crazy hours that you often are talking about have to be done. And it doesn't. I think that's true. Yeah, so there's still the two, three hours of muse time needed for truly genius ideas, but it's something I certainly struggle with. But yeah, I hear you loud and clear on the health. So what does a perfect day look like for you, if we're talking about writing? An hour by hour schedule of a perfect day. I get up early, I go to the gym, I have breakfast with some friends of mine. What's early, by the way? 3.15. A.M. A.M. So we're talking really early. Really early. Now, I'm crazy early. It's ridiculously early. And I haven't done that always, but that's kind of what I'm on now. So I'm in bed, like when I'm with my nephews that are like four years old and three years old, I'm in bed before them. Okay. You got to be. You wake up, sorry, you said exercise first. Yeah. And what does that look like? What's exercise for you? You go to the gym? I go to the gym. I have a trainer. I have a couple of guys that I work out with. And it's maybe an hour, maybe a little more. I'll do a little warm up before, stretching afterwards, take a shower, go have breakfast. But it's an intense kind of a thing that I definitely don't want to do that's hard. So you feel like you've accomplished something, first thing. Yeah. That's a big accomplishment of the day. But at the same time, it's not like so hard that I'm completely exhausted. And then I'll come home and handle whatever correspondence and stuff has to be done. And then I work for maybe three hours. And then I just sort of crash. The office is closed. I turn the switch. I don't think about anything. I don't think about the work at all. Do you listen to, oh, you mean afterwards? After work, once the office is closed. But during, so this was like 12 to three kind of thing? Something like that. Something like that. Okay. Do you listen to music? No. Do you have anything? But that's just me. I mean, I don't think, you know, but somebody could do it a million different ways. It's fascinating. You know, I mean, you've also, of many writers, you've really, like I've read Stephen King in writing, you've optimized this conversation with the muse you're having. Not optimized, but you've at least thought about it. So what's, can you say a little bit more about the trivialities of that process of, like you said, facing the wall. What's, do you have little rituals? You mean like the granular aspect of it? The granular aspects, yeah. I do have little rituals. I do have all kinds of, which I'm not even going to tell you about. But the one thing, and I don't want to like talk about this too much because it sort of jinxes things, I think. But the one thing I do try to do is when I sit down, I immediately get into it. First second. I don't sit and fuck around with anything. I immediately try to get into it as quickly as I can. The other thing is that writing a book or screenplay or anything like that is a process of multiple drafts. And it's the first draft that's where you're most with the muse, where you're going through the blank page. Like right now I'm on, I don't know what, the fifth or sixth, seventh draft of the thing I'm working on. So I've got pages already written and I'm kind of reading them afresh as I go through the story. So it's not quite where I am now. It's not quite a deep muse scenario. Partly it is, but it's also sort of bouncing back and forth between the different, between the right brain and the left brain. I'm kind of looking at it and trying to evaluate it. And then I'm going into it and try to change it a little bit. And when, do you know, sit down, get right into it, do you know the night before of what that starting point is? I always try to stop, and I learned this, I think Hemingway wrote about this or John Steinbeck or one of the, or maybe both of them, to always stop when you kind of know what's coming next. So that you're not at a, facing a chasm, you know? Yeah. Okay, so and afterwards when you're done, the office is closed. The office is closed, I let the muse take care of it, you know? And I don't want to, and I think it's a very unhealthy thing to worry about or to think about any creative process. You don't, like on a long walk later, think about. Yeah, then I will sort of keep my mind open to it, but I won't be like obsessing about it. Right, okay. And actually on walks, sometimes things will pop into your head, you know, and you'll go, oh, I should change that. But that's not your ego doing it, that's the deeper level. Okay, so how does the day end? In terms of writing? So yeah, the writing, well no, the writing, the office door closes, and then the rest of the day, just do whatever the hell. Maybe go out to dinner, my girlfriend is not here now, she's in New York working, we'll make dinner or whatever, go out to dinner, something like that, and maybe I'll read something, nothing heavy. And I go to bed pretty early, and the gym is a big thing for me. I'll already, probably like with you with martial arts, the night before I'll be visualizing what I have to do the next day, and getting myself psyched up for that. And then I'll just conk out like a light and wake up at the crack of dawn. So looking out into the future, this year, next few years, what do you think the muse has in store for you? I don't think you can ever know. It's probably something along the same, I really believe, you know, there's that exercise where they say to you, visualize yourself five years in the future, and then write a letter from that person to yourself. I don't believe in that at all, because I don't think you can, you know, there's a line out of Africa that God made the world around so that we couldn't see too far ahead. You just don't know as a writer or as a person. You know, I never knew, my first book was A Legend of Bagger Vance. Before that happened, I had no clue that I was going to be writing anything like that on that subject, anything at all, no clue until it just sort of came. And then when that was done, people said, well, you got to write another one. I had no idea what it was, which was going to be Gates of Fire. No clue. So, if somebody had sat me down at the start of that and asked the question, I would have been crazy to have said it. So I just hope as the future unfolds that I'm open to it, you know? Well I think I speak for a lot of people in saying that we look forward to what that future looks like. Steven, thank you so much for talking today. It was fun. Hey, you got the best job in the world going around talking to people that you want to talk to and that they will talk to you, you know? So thank you for doing it. Hey, thank you for the great questions you made me think. I've certainly a bunch of questions I never have answered before. Awesome. So thanks a lot. Great. Thank you. Thanks for listening to this conversation with Steven Pressfield, and thank you to our sponsors, The Jordan Harbinger Show and Cash App. Please consider supporting the podcast by going to jordanharbinger.com slash Lex and downloading Cash App and using code LexPodcast. Click on the links, buy the stuff. It's the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 stars on Apple Podcast, support it on Patreon, or connect with me on Twitter, Alex Friedman, spelled without the E. Just F-R-I-D-M-A-N. And now let me leave you with some words from Steven Pressfield. Are you paralyzed by fear? That's a good sign. Fear is good. Like self-doubt, fear is an indicator. Fear tells us what we have to do. Remember one rule of thumb. The more scared we are of a work or a calling, the more sure we can be that we have to do it. Thank you for listening and hope to see you next time.

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Robert Proctor: Nazi Science and Ideology | Lex Fridman Podcast #268

What is the heroic action for scientists in Nazi Germany? Science in many respects actually is a full collaborator in the most horrific forms of Nazi genocide, Nazi exclusion. What goes to the mind of a big tobacco executive? Cigarettes have killed more than any other object, than all the world of iron, all the world of gunpowder. Nuclear bombs have only killed a few hundred thousand people. Cigarettes have killed hundreds of millions. There's no contest. Cigarettes have killed far more and are far more preventable. What is the nature of human ignorance? The following is a conversation with Robert Proctor, historian at Stanford University, specializing in 20th century science, technology and medicine, especially the history of the most controversial aspects of those fields. Please allow me to say a few words about science and the nature of truth. The word science is often used as an ideal for a methodology that can help us escape the limitation of any one human mind in the pursuit of truth. The underlying idea here is that individual humans are too easily corrupted by bias, emotion, personal experience and the usual human craving for meaning, money, power and fame. And the hope is that the tools of science can help us overcome these limitations in striving for deeper and deeper understanding of objective reality, from physics to chemistry, biology, genetics and even psychology, cognitive science and neuroscience. But history shows that these tools of science are not devoid of human flaws, of influence from human institutions, of manipulation from people in power. As we talk about in this conversation with Robert Proctor, in the 1930s and 40s, there was the Nazi science and there was communist science and each had fundamentally different ideas about, for example, genetics and biology of disease. This history also shows that scientists can be corrupted slowly or quickly by fear, fame, money or just the ideological narratives of a charismatic leader that convinces each scientist and the scientific community that their work matters for the greater cause of humanity. Even if that cause involves the genetic purification of a people, the extermination of a cancer and the unrestricted experimentation on the bodies of living beings who do not have a voice, whose suffering will never be heard. All of this for the greater good. In some periods of human history, science was deeply influenced by the ideology of governments and individuals. In some, less so. The hard truth is that we can't know for sure about which of the two periods we're living through today. So let us not too quickly dismiss the voices of experts and non-experts alike that ask the simple question of, wait, are we doing the right thing here? Are we helping or hurting? Are we adding suffering to the world or are we alleviating it? Most such voices are nothing more than martyrs seeking fame, not truth, and they will be proven wrong. But some may help prevent future atrocities and suffering at a global scale. Let us then move forward with humility so that history will remember this period as one of human flourishing and where science lived up to its highest ideal. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Robert Proctor. What is the story of science and scientists during the rise, rule, and fall of the Third Reich? Well, we tend to think of science as always on the side of liberty, as always on the side of enlightenment, as always on the side of enlarging human possibility. And here we have this phenomenon in the 1930s of really the world's leading scientific power, the Third Reich, which collectively had won a big chunk of all the Nobel Prizes. Suddenly, they go fascist, they go Nazi with Hitler. And instead of being primarily a source of resistance, science in many respects actually is a full collaborator in the most horrific forms of Nazi genocide, Nazi exclusion, and that's kind of a relatively untold story in the sense that when we think of science in the Third Reich, we think of Joseph Mingeli injecting dye into the eyes of twins, or we think of horrific human experiments, and those are real. But it's also the story of a huge scientific apparatus, a bureaucracy, you could almost say, participating in every phase of the campaigns of Nazi destruction. And what I looked at in particular, and actually in my first book, was how physicians in particular, but also biomedical science, was collaborating with the regime, and that it's wrong to think of the Nazi regime as anti-science. It's anti a particular type of science. In particular, it was radically against what they called Jewish science, communist science. Certain types of science they did not like. There's a whole nature-nurture dispute in that period, and they're firmly on the side of nature, which interestingly gives rise to a very different type of science in the Soviet Union, by the way. The Soviet Union is more on the nurture side? The Soviet Union is on the side of the nurture side, in the dimension of genetics, and this is sort of an untold story. I was actually gonna write a book about it until I was barred from access to the Soviet Union. There've been different times in my life where I was a Russianist. A Russianist, okay, we're gonna have to talk about that. I got excluded from fulfilling that dream but one of the things I was gonna look at when I got a Fulbright in the 1980s was to go over and look at the anti-Nazi genetics and anthropology of the Soviets and how a lot of their Lysenko-ist Lamarckism was actually anti-Nazi, anti-genetics on the nurture side of nature, and that's really an untold story. It's an uncomfortable story because it sounds like we might wanna make heroes out of the twisting of science in the Soviet Union but nonetheless, there are these interesting complexities and what's amazing about Nazi science is how there was this collaboration and you're talking about a culture where they're inventing things like electron microscopy, they're doing all kinds of studies in anthropology, so a lot of that's an untold story. So what was the connection between the ideology and the science? If you can just linger on it longer. Well, we tend to think of science and ideology as completely separate when I think the reality is they're not. If you look at why the Mayans in the 7th and 8th century AD had the world's most accurate calendar, accurate to within 17 seconds per year, that was all part of a ritual practice to celebrate the rise of Kukulkan, the rise of Venus with what's called the heliacal rising, namely the rising of Venus before the rising of the sun in which, at which moment Venus is destroyed by the light of the sun. Well, they developed this elaborate calendrical astronomy which required detailed observation, detailed chronicling of the movement of the heavens, in particular the planets, for the purpose of celebrating this cycle of renewal that they thought was sacred and holy and magical. So where's the ideology, where's the science? There's the sort of instrumentation, the calendrics, the measurement all in the service of this magical moment and I think that's true of a lot of science. I had a friend years ago who was Mennonite and wanted to study solar cells and to improve silicon chips to make more efficient solar energy. There was no money for that. Yet when Ronald Reagan took office, the budgets for solar and alternative energy were essentially zeroed out and Reagan takes off the solar panels off of the roof of the White House. So my friend ends up working on hardening silicon chips against nuclear war. So he becomes part of the nuclear war protection defense apparatus even though he wanted to work on alternative energy, doing very similar work with silicon chips but in a different framework. And so the practices of science often gets pushed into and is woven into ideological practices. Sort of in the same way that you get beautiful medieval cathedrals built in service of Catholicism. Well what's in the mind of an individual scientist? So this process of ideology polluting science or is it science empowering ideology? So almost like if we can zoom in and zoom out effortlessly into the individual mind of a scientist and then back to the whole scientific community. Like do scientists think about nuclear war, about the atrocities committed by the Nazis as they're helping on the minute details of the scientific process? I think sometimes they do and sometimes they don't, right? You think of the chemists working to develop the cyanide that will be used to kill Jews in a concentration camp, what are they thinking? You can imagine a whole range of thoughts, maybe they don't know what they're doing. Maybe they do, maybe they know a little bit but not a lot, maybe they don't wanna know. Maybe they have ways of lying to themselves. Maybe they are the one person who agreed to do it and 99 refused. So it's hard if not impossible to know what's in the soul of anyone. But when you have enormous power directing the motion and the currents or the ocean, it's not hard to find people willing to fill that in, especially if they're narrow technocrats, if they're just doing their job, if they're just building the widget. And I think a lot of scientific training is in widget building and that leads to the possibility that they can become easily instrumentalized in a particular action, which is maybe horrific or glorious. The other thing to keep in mind is that science is, as we say, what scientists do. And that can include a lot of things, it can exclude a lot of things. The word science itself is interesting because it's cognate, it actually comes originally from the Proto-Indo-European, skein, meaning to cut or divide. And so it's cognate with scissors, schism, skin. Skin is that which divides you from the world. Shit or scat is that which has been divided from you into the world. And so there's this cognate between science and shit or science and cutting with the whole idea being that you're dividing into parts, classifying. It's the taxonomic impulse. And to know is to know where something belongs, to divide it into its parts and put it in its proper place. And that taxonomic impulse can be very static. It's actually one of the things that Darwin had to overcome in recognizing evolution, that the taxonomies are in motion. But it also can lead to a kind of myopia that my job is done when I've classified something. Is this bird an X, a Y, or a Z? And that again can be, it can be ideological or it cannot be, but scientists are humans and they're fitting in with a world, with a world practice. And that's limiting, it's kind of inevitable. It's unavoidable. It's hard to be, if not impossible, out of the world that we're walking in. Yeah, and it's fascinating because I think ideologies also have an impulse towards forming taxonomies. And there is, so just, so being at MIT, I've gotten to learn about this character named Jeffrey Epstein. I didn't know who this was until all the news broke out and so on. And I started to wonder how did all these people at MIT that I admire would hang out with this person? Just lightly, just have conversations. I don't mean any of the bigger things, but even just basic conversations. And I think this has to do, you said scientists are widget builders and taxonomizers. I think there's power in somebody like the Nazi regime or like a Jeffrey Epstein just being excited about your widgets and making you feel like the widget serves a greater purpose in the world. And so it's not like you're, sometimes people say scientists wanna make money and, or they have a big kind of ideological drive behind it. I think there's just nice when the widget, so you like building anyway, somehow somebody convinces you, some charismatic person that this widget is actually has a grander purpose. And you don't almost feel, think about the negative or whether it's positive, just the fact that it's grand is already super exciting. Yeah, yeah, I think that's right. I think that's the story of Werner von Braun, and the fascination with rockets and this will enlarge something in the world. And here he is, he's an SS officer, he's working around slave labor. And then, but his rocket then gets compressed into the Western world or the American world and basically launches us to the moon. And we forget about the sauce, how the sausage was made originally. Well, can you talk about him a little bit more? Cause he's such a fascinating character. Cause he, so he was a Nazi, but he was also an American and it had such a grand impact on both. And like, there's this uncomfortable fact that he's, you know, one of the central figures that gave birth to the American space exploration efforts. Yeah, he's an interesting figure, fascinated in a kind of a tunnel vision way with spaceflight. He makes these beautiful rockets already, beginning in the 20s, early 30s. Ends up for a while at Penamunda using slave labor to build V2 engines and so forth like that. I remember going to Penamunda, where people have actually tracked the flights of aborted V2 rockets and found some of these beautiful, beautiful old engines, just the most like works of art. These engines used to reign terror on the British. It's interesting because in that same spot, I was hunting for amber, Baltic amber, cause I'm a stone collector. And among the amber collectors there, there's a famous story of the Penamunda burn. It's called because they find yellow phosphorus, they think is amber, they put it in their pocket and then it dries out and then explodes and creates this big burn on their legs. But the whole Nazi regime is full of things like that. It's full of these scholars who get twisted into a mindset. And it's also important to realize that people didn't often see what was coming. And we look back and we say, how could you X, Y, or Z? But before the Holocaust, there's not the Holocaust. There are versions of it, but things get on a new meaning, gain a new meaning in light of subsequent events. And there's an entire propaganda machine that makes it easier for you to hold the narrative in your head. Even if you kind of intuitively know there's something really wrong here, because of the propaganda, you can kind of convince yourself to be able to sleep at night. That's right. And we have to remember that Goebbels' office was not the office of propaganda. It was the office of popular enlightenment and propaganda. So enlightenment was part of his vision. Just the new era of enlightenment from his perspective. It was supposed to be the new age, the new era of enlightenment. It's a little bit like the kind of myth of Hitler's failed artist. You know, his art is not that bad. There are a lot of artists who are worse. And I had a very interesting conversation once with my college roommate who became a librarian at Harvard. And at Harvard he met an old, old librarian, a German woman who had met Hitler as a kid when she was like eight years old. Her dad was like a Gauleiter for the Nuremberg area. And she said that for 15 minutes, Hitler goes out onto the balcony with her and has this conversation alone with this eight-year-old girl. And she said he was charming and funny. And then he said he loved kids. And she said he was the most charming sort of person. And that's part of the history too, that we tend to forget when we make a scarecrow image of this rabid, raging fanatic. You know, there's more to it than that. That's really, really, really important to think about when we make a scarecrow because that gives you actionable, like it forces you to introspect about people in your own life or leaders in your life today, ones you admire. They're charismatic, they're friendly, they love kids, they talk about enlightenment. You have to kind of think, all right, am I being duped on certain things? You have to kind of have a, I mean, that's the problem with Jerry Epstein that people don't seem to talk about. I never met the guy, but just given the people he talked to, whom I know, it feels like he must have been charismatic. Like people think about like, oh, it's because of the women, it's because of the money. The people I know, I don't think they're going to be influenced. Ultimately, it has to be how you are in the room and make, it's exactly like you said, the enlightenment. I think that excites the scientists. Of course, as a charismatic person, you have to know what to pick in terms of what excites you, but that is also the fascinating thing to me about Hitler is all of these meetings, even like with Chamberlain, inside rooms, whether he was screaming or whatever he was saying, it seems like he was very convincing. There must have been passion in his eyes. There must have been charisma that one-on-one in a quiet conversation, he was convincing. Yes, there's a famous story about Goebbels who would do a party trick where for 15 minutes, for 15 minutes, he would rouse the crowd to communism, workers of the world unite. Then for 15 minutes, he would rouse the world to capitalism and individualism. Then for 15 minutes, he would rouse the world to Nazism, and apparently he was quite convincing in each of those performances. Well, all those ideologies are pretty powerful. I mean, and I think it's not even the reason that matters as much as the power of the dream, of the vision, of the enlightenment. I mean, the vision of communism is fascinatingly powerful. Yeah. Like workers unite, the common people stand together, they'll overthrow the powerful, the greedy, and yet share the outcomes of our hard work. Yeah, well, it's kind of like the story of the two thirds of the things that Marx calls for in the Communist Manifesto are already just part of the liberal state. And so the parts we remember or forget about an ideology are very revealing. If we can just linger on this a little bit longer, what have you learned from this period of the 1930s about the scientific process? So one of the labels you can put on your work, I knew as a scholar, as a philosopher of science. And you also talk about Nazi Germany as a singular moment in time, or like a rebirth of the integration between ideology and science. So like in terms of valueless science, I think is the term. Value-free science. Value-free science that you use. I mean, it seems like Nazi Germany is a important moment in history. I mean, it probably goes up and down. So what difficult truths have you learned about the scientific process, and what hopeful things have you learned about the scientific process? Well, I guess the saddening thing is how easily people can become part of a machine. If there's power, people can be found to follow it. One of the things I work on is big tobacco, and we'll probably come to that. But it's amazing to me how easily people are willing to work for big tobacco. It's amazing to me how many scientists and physicians were willing to work for the Nazi regime for multiple reasons. Partly because a lot of them really thought they were doing the Lord's work. They thought they were cleaning the world of filth. I mean, if you really thought Jews are a parasitic race, why wouldn't you get rid of them? So there's an ontology. There's a theory of the world that they're building on. And interestingly, one that was also present in the United States. And one of the things I did find out in my earliest research was that the Nazis had looked lovingly and enviously over at the United States in terms of racial segregation, racial separation, and saw themselves in a kind of competition to become the world's racial leader as the most purified racial form. And that this required this kind of cleansing process. And the cleansing meant getting rid of the physically handicapped. It meant getting rid of racial inferiors, as they imagined them. It meant getting rid of cancer-causing chemicals in the air and in our food and our water. These were all of a piece. There's a famous illustration that Richard Dahl talks about, the great cancer theorist of studying in Nazi Germany in the 1930s. And he's shown a lecture where cancer cells are shown as Jews and x-rays are shown as stormtroopers. And these stormtroopers are killing the cancer cells who are also Jews. And so there's this metaphorical work of cleaning, extermination, sanitation. Purification of a sort. Purification. There's definitely a kind of purity quest. And you see that at multiple levels. And so you see how easy it is for people to fall into that, given a particular theory. And again, coming back to that earlier point about the scarecrow, which I think is very important. If we imagine that nothing like this went on here in the United States, that would be a big mistake. The Nazis are looking to save the Redwoods League, to the Aryan supremacists, to the Ku Klux Klan, to the separation of blacks and whites. Blacks were not allowed to join the American Medical Association until after World War II. So you have racial segregation. You have massive sterilization in the United States way before the Nazis. One of the first things the Nazis do from a racial hygiene point of view is start sterilizing what they called the mentally ill and the physically handicapped. Well, that had been going on since around World War I in the United States and even earlier in certain states in the form of castration of prisoners in order to prevent their demon seed from being propagated further into the race. So there's a kind of a racial international that's going on, and that part of the story also needs to be told. And scientists were able to carry those ideas in their mind from your work. Of course, of course. I mean, that's one of the things going on with all the renaming of buildings now is scientists who were eugenicists are now getting their names pulled off of buildings. My personal view is that it has to be done on a case-by-case basis, but in general, I think it's usually better to add on rather than subtract. In other words, to add history rather than erase history or pretend as if history had never existed. Let me give you a specific example of that. One of the most powerful and diabolical university presidents in the Nazi period was a guy named Karl Ostel, A-S-T-E-L, and he was a rabid Nazi, high up in the leadership. And in his portrait at the University of Vienna, there he is in full SS uniform. That painting was taken down. Now, what I would have done is left the painting and put a, you know, add a plaque. But to pretend as if that never happened or to erase history in that way, I think, is a big, big mistake. Can I linger on that point? So I haven't gotten through it yet, but I've been trying to get through the Mein Kampf. And, you know, throughout its history, it's been taken down and up. It actually was taken down from Amazon for a while recently. What can you say about keeping that stuff up? So the reason it was taken down from Amazon, I mean, there's a large number of people that will read that. And the hate in their heart will grow. So they're not using it for educational purposes. You can't put a plaque on the Mein Kampf. You're ruining Mein Kampf then. Like, you can't, I mean, this, you know, Amazon can't do a warning saying like. Or an expurgated, you could do an expurgated version of Mein Kampf. Take out the word Jew, you know? Exactly. Because that would solve anything. So it still just stands on its own. I mean, it's not well-written, so you can maybe convince yourself that it's okay because it's not well-written. So it's not like this inspiring book of ideology that could easily convince. But can you steelman the argument that Mein Kampf should be banned? And can you steelman the argument that it should be not banned? Well, I wouldn't say it should be banned. I think, if anything, that might make it forbidden fruit. Now, this might be different when we come to statues on the public square. After World War II, the statues of Hitler, there must have been thousands of them were taken down. Now, I think even the most rabid opponents of cancel culture would not say there was something wrong with taking down the statues of Hitler that were in every office building, every post office. So I think a lot depends on the placement and the purpose of icons, of statues, of texts. I don't see the harm in being able to buy Mein Kampf. It's so out of this world by now. Just the language and, if anything, there probably is more good done by people being shocked at how dumb it is than the evil that might be done by someone reading it. I can't imagine people being really gripped by that now, partly just because it's kind of outdated and crazy talk. So in that case, I would not be in favor of that. When it comes to monuments or other types of things, it's a judgment call in each case. I think it has to be probably voted on. But it also, I think, in many of these cases, there's an add-on view would fix a lot of the problems. We'll jump around a little bit. We'll come back to medicine and war on cancer. But let me just add one thing on that. Recently, the name of Macmillan, who works on the charge of the electron in the early part of the 20th century, his name was taken off of a building at Caltech. Well, to take his name off, what do you really do? It wasn't a central aspect of his actual work. It's not why he was put on the name of that building at Caltech. And also, the memory is lost and the lesson is lost when you could have kept the Macmillan name on the building and added a plaque. This guy was a racist or this guy was a eugenicist or something to make a teaching moment instead of just a forgetting moment. Yeah. Well, let me take a small tangent and ask you about censorship and this particular period we're living through. So my friend Joe Rogan has a podcast. He hosts a few folks on there and they're folks of differing opinions. And as we speak, there's kind of a battle going on over whether Joe Rogan should be on Spotify and allowed to spread scientific misinformation. In particular, there's a guy named Robert Malone that's talking about, that's making a case against, at least against the COVID vaccine and so on. So outside of the specifics of this person, in this battle of scientific ideas that are sometimes tied up with ideology, in our modern world, what do you think is the role? Like who gets to censor, decide what is misinformation or information? Should we let ideas fly in the scientific realm? So scientific ideas, or should we try to get it under control? Like which way, obviously all approaches will go wrong in some ways, which is more likely to go wrong? One where you try to get a hold of like, all right, this is a viral thing and it doesn't fit with scientific consensus, so we should probably try to quiet it down a little bit? Or do you let it all just fly and let the ideas battle? Do you think about this kind of stuff in the context of history? Well, that used to be a million dollar question. Of course, now it's a multi-billion dollar question. Not trillion, yeah. We're talking about powerful internet platforms becoming essentially publishers. And publishers can't say whatever they want. There are limits. They can't yell fire in a crowded theater. But there's a kind of social responsibility that is there. And I know some of these, I don't know a lot about this topic, but I know some of the large platforms do have dedicated offices to trying to rein in misinformation as you would expect any publisher to do. You can't just let anything fly in Time Magazine or the New York Times either. There are all kinds of codes of ethics and legal obligations. So I'm a fan of the efforts, or I think some of the large internet platforms should be congratulated at least for trying to make an effort to rein in misinformation. It's gonna be difficult and mistakes are gonna be made, but it can't be a let everything fly kind of situation. But when I watch, unfortunately, the pressure these platforms feel to identify and to censor misinformation, that pressure is ideological in nature currently. So if you just objectively look, there's a certain political lean to people that are pressing on the censorship on the misinformation, which makes me very uncomfortable because now there's an ideology to labeling something as misinformation as opposed to kind of having a value, less evaluation of what is true or not. And you also have to acknowledge that it says something, that there's a very large number of people that, for example, follow Robert Malone or follow people. I mean, what does that say about society? And there's a deeper lesson in there that's not just about blocking misinformation. It's distrust in science and institutions, distrust in leaders. Like it feels like you have to fix that. And censorship of misinformation is not going to be fixing that. It's only going to like throw gasoline on the fire. You gotta put out the fire. Well, that's certainly possible. Yeah, I mean, I think people are distrustful of certain institutions and not others, right? And I think a lot of distrust is good. I'm not a conspiracy theorist, but I do know there have been a lot of conspiracies and that people work behind scenes to do powerful bad things. And that's what needs to be exposed. The other thing I worry about, which is relevant to your question, again, it's a billion or trillion dollar question, is I think in a world of kind of flattening where all news or all information or all data is kind of equal in some way. And so you get the Twitterverse going and it doesn't matter if it's peer reviewed or it doesn't matter if it's been supported by evidence. It's just a kind of outburst. It's interesting to contrast it with say 100 years ago. I mean, what would a crazy person or a flat earther or anything, what venue would they have? I mean, maybe they could go to a church or someplace. So now we have these empowering engines, then that's what's new historically is that basically anyone can have a blog or a Twitter feed and that is new. And so that is, you can think of it also as a kind of clutter. So it's a kind of a radical democracy in a way, kind of one of the weaknesses of democracy is if everyone has an equal voice and if everyone has equal power. So there's of course a flip side to that where everyone has equal power. It forces the people who are quote unquote experts to be better at communication. I think people, like scientists are just upset that they have to do better work at communicating now. They used to be lazy and you could just say, I have a PhD, therefore everyone listen to me. Now they have to actually convince people. Like you have to convince people that the earth is round. You can't just say the earth is round, that's it. You have to show, you have to make, I mean not the earth is round part, but things like that. You have to actually be a great communicator, do great lectures, do documentaries and so on to battle those ideas. And then also to defend the sort of, the people labeled as crazy. In Nazi Germany, if you were protesting against some of the uses of science, of medicine to commit atrocities, you would also be labeled crazy. Yeah, those voices are important. Yeah, there's so many good points there on the scientists becoming good communicators. The history of scientists becoming bad communicators has a history and the last original contribution to science written entirely in the form of a poem is Buffon's Loves of the Plants. And following that in the 18th century, you get the uglification of science, the deliberate uglification of science with the idea being that if you are clear and if you speak beautifully, if you write beautifully, you're hiding something. You're covering over the truth with flowers and decorations and scents and pleasant odors. And so you get this scientific paper format, introduction, discussion, methods, results, conclusions, and it's kind of policed in this inhumane, non-humanistic kind of rhetorical way. And that's a big problem. And so you get that combined with just the rise of the research lab and the ever narrower widget builders, the cogs in the machine. It's not surprising that people might not trust certain aspects of that. That combined with the dirty laundry history of a lot of science that you did have, the requirement at Auschwitz that people be, that physicians supervise the killings, the horrors of Tuskegee and all kinds of other things, or even something like the atom bomb, which is arguably more neutral at least, but nonetheless horrific. And so it's not surprising that a lot of people don't trust science and a lot of science shouldn't be trusted, right? There's science and then there's science. So there's a long history of dirty, bad science that you don't solve just by saying we should have trusted it. Let's just stay on COVID for a brief moment and talk about a particular leader that I think about is Anthony Fauci. I've thought about whether to talk to him or not. I have my own feelings about Anthony Fauci. By the way, I admire basically everybody and I admire scientists a lot. And there's something about him that bothers me. I think because I'm always bothered by ego and lack of humility and I sense that. Maybe I'm very wrong on this, but so he has said that he represents science. If you've taken him full context, I understand the point he's making, which is when people attack him, they think of him as representing science, things like that. But there's ego in that. And what do you think motivates and informs his decisions? Is it politics or science? And the broader question I have, what does it take to be a great scientific leader in difficult times like these? And maybe you could say Nazi Germany was similar when there's obviously, Anthony Fauci, just like scientific leaders during Nazi Germany could have made a difference, it feels like, positive and negative. And so it's like there's a lot at stake. There's a lot at stake in terms of scientific leadership. If I've asked about 17 questions, if there's something worthwhile answering in that. Well, Fauci I think is doing as good a job as he can. I mean, you can't turn on the television without seeing him. But no, that's what's the goal of the job. That means he appears a lot, but he does not come off as somebody with authenticity. Like I admire so many science communicators, about 10X, 100X more than him, including his boss, Francis Collins, who I've recently lost respect for given some of the emails that leaked. There's ego in those emails. And it upsets me because like, I hope all that stuff comes out and wakes young scientists up to don't be a douchebag. Don't be humble. Be honest, be authentic, be real, put yourself out there. Don't play the PR game, don't play politics. Just get excited about the widget building that you love, communicate that, and think about the difficult ethical questions there and communicate them, be transparent. Don't think like the public, don't talk down to the public. Don't think the public is too dumb to understand the complexities involved. Because the moment you start to think that, when you're like 30, what do you think happens when you're 40 and 50? The slippery slope of that, the ego builds, the distaste for the public opinion builds. And then you get into the leadership position at the time you're 60 and 70, and then you're just a dick. And you're a bad communicator to the very public. So I think this is something that just builds over time, is the skill to communicate, to be honest, to be real, to constantly humble yourself, to surround yourself with people that humble you. I'm bothered by it because I feel like science is under attack. People distrust science more and more and more. And it is perhaps unfair to put places like Anthony Fauci to blame for that. But you know what? Leaders take care of the responsibility. So in you saying that he's doing the best job he can, I would say he's doing a reasonable job, but not the best job he can. Yeah, well I don't know what his capabilities are on that one way or the other. Right. Like you can imagine how history sees great leaders that unite on which history turns. That's not a great leader because there's a huge division. There's a lot of people in leadership position that can heal the division. You could think of tech leaders. They can heal the division because they have the platform. They can speak out with eloquence. You can think of political leaders, presidents, that can speak out and heal the division. You could think of scientific leaders like Anthony Fauci. They can heal division. None of these are doing a good job right now. And which is, you know, leadership is hard, which is why when great leaders come along, history remembers them. So I just wanna point out the emperor has no clothes when the leaders are like, eh, kind of mediocre. Yeah, yeah. Because it feels like, I guess I'll take it to a question about Nazi Germany. What is the heroic action for a scientist in Nazi Germany? Like to stand, to see what's right when you're under this cloud of ideology. Yeah, well, it's an almost impossible task in Nazi Germany. Maybe the heroic task would have been before Hitler was essentially elected and the Reichstag is burned. So in the 30s, because it's building, when it's building what the other alternatives are, maybe it's events in World War I that could have made Nazism less inevitable. You know, maybe it's going back to the British Empire, which had a giant empire and Germany wanted a big empire too, right? And that part of the history of World War I is often forgotten. So, you know, the heroic act is to stand up and tell the truth and fight against evil and- Well, of course you get, oh, sorry to interrupt. But of course you get- And have some courage, you know? But I also, so I personally don't always have complete respect of people who stand up and have courage because it's not often effective. What I have the most respect for is long-term courage, like that's effective. Because like, you know, if you're just an activist and you speak out this is wrong, that's not gonna be effective because everybody around you is saying, nah, it's like, we like our widgets. So you have to somehow like steer this Titanic ship. And I guess you're right, the easiest way to steer is to do it earlier. Well, everyone has different skills. You know, Musk is building electric cars and other people are trying to, you know, build solar and wind. And there are all kinds of problems that we're gonna solve, right? People are building better vaccines, you know. There's a thousand ways to do good in the world and a thousand ways to do bad in the world. I mean, part of the problem in science is that we don't look enough at what I call the causes of causes. So cigarettes cause cancer, but what causes cigarettes? Yeah, so the deeper, yeah, yeah. Obesity causes heart disease, but what causes obesity? And it's not just gluttony and sloth, it's the decision to pump up the sugar industry and to allow soda in school. And I'm a big fan of what I call loop closing. We're all worried about climate change and reducing our carbon footprint, but what about the hidden causes, the unprobed causes? I'm doing a project now with Londa Schiebinger on looking at how voluntary family planning could actually have a big role in reducing carbon footprint throughout the world. And these literatures are never joined or rarely joined, that we have this huge carbon emissions problem. But we also have too many people on the planet, and the cause of that is because too few women and men have access to birth control. And if you join those realms open, there's gonna be new possibilities. And it's kind of like looking at the flip side of fascism and the kinds of discoveries they made that have been ignored. That's one of the things I'm interested in, is finding some of the gaping holes, the ideological gaps that have been ignored because of ideology, left or right, by the way, both of which involve blinders. And so there's all kinds of blinders that we live in, and that's part of ideology, is what don't we even see? And that would prevent us from seeing some deep, objective scientific truth. Right, some truth. And it's actually, just to mention, there's some people, including Elon, who are saying there's not too many people, there's not enough people, right? That if you just look at the birth rates, and so it's like, some of this is actually very difficult to figure out, because there's these narratives. You mentioned tobacco, obesity with sugar, there's been narratives throughout the history, and it's very, there's certain topics on which it's easy to almost become apathetic, because you just see, in history, how narratives take hold and fade away. People were really sure that tobacco is not at all a problem, and then it fades, and then they figure it out, and then other things come along. What other things came along now? Well, you asked about ideology, and one of the things I always ask students before class, whether I'm teaching agnotology or world history of science, is what makes fish move? And 90% of Americans will say some version of muscles, fins, neurons, when the reality is, at least in saltwater, fish don't swim places, they're moved by currents. Fish are moved by currents, that's what makes fish move. This is not even counting the rotation of the Earth on its axis, or the rotation of the Earth around the sun, or the rotation of the solar system around the galaxy, ignore all that. Even on Earth, fish arrive up in Alaska. They don't swim there, they come by currents. And this is known to people who understand the ecology of fish. But we, as sort of individualistic Americans, think that. The fish pulled itself up by its bootstraps. Pulled itself up by its bootstraps, right? And whatever gumption and courage made his own world. Instead of thinking of something like cigarettes, for example, hitting a village, like an epidemic. Hitting the village like cholera, or pneumonia, or something like that. So, there's a big ideology we have of personal choice. A great example of that is in the tobacco world, where people always, there's a whole field called cessation. That always means cessation of consumption, never cessation of production. All blame is put on the individual smoker, instead of looking at how they get smoked. And looking at that bigger picture, I think, is part of the story. So, a few years ago you wrote that, the cigarette is the deadliest object in the history of human civilization. Cigarettes kill about six million people every year, a number that will grow before it shrinks. Smoking in the 20th century killed 100 million people. And a billion could perish in our century, unless we reverse the course. Can you explain this idea that it's the deadliest object in the history of human civilization? Maybe just also talk about big tobacco and your efforts there. Well, cigarettes have killed more than any other object, than all the world of iron, all the world of gunpowder. Nuclear bombs have only killed a few hundred thousand people. Cigarettes have killed hundreds of millions. And every year kill about as many as COVID. They're sort of neck and neck. But if you took the last five years, there's no contest. Cigarettes have killed far more, and are far more preventable. So, we're in a world, this bizarro world, where every night there's a COVID report, and cigarettes would never be mentioned. Cigarettes would no more likely to be mentioned than if we were talking about chewing gum on a sidewalk. They'd be no more likely to be in a presidential debate than, you know, sneezing in the wrong place. So, we live in this world where most things are invisible. You know, we are, the eyes are in the front of the head. We don't see what's behind us. We have a fovea, which means not only do we only see what's in front of us, we see in a very narrow tunnel. And that's because we're predators. We don't have the eternal watchfulness of prey. We have a zeroed, targeted focus. And that leads to a kind of myopia, or a tunnel vision, and all kinds of things. Then when you get something like a very powerful tobacco industry, which is a multi, multi-billion dollar industry, which still spends many billions of dollars advertising every year, but nonetheless manages to make themselves invisible. You have this powerful agent that is producing this engine of death that is invisible. It's been reduced to the fish that move themselves. In other words, there's not really a tobacco industry, there's just people who smoke, and that's a personal choice, like what food we're gonna have for dinner tonight. And so, it's erased from the policy world. It's as if it doesn't exist. And creating that sense of invisibility, to fail you to understand the causes of causes, is what allows the epidemic to continue, but also not even to be acknowledged. How's the invisibility created? Is it natural, is it just human nature that ideas just fade from our attention? Or is it malevolent, still going on kind of action by the tobacco companies to keep this invisible? It's still going on. Even when you see an ad against cigarettes on television, that's dramatically curtailed, because the law that made those even possible required that there's an anti-villainy clause. The industry can't be made even visible in those ads. In some, they get away with it, but the industry operates through very powerful agents, you know, powerful senators. They used to count 3 quarters of the members of Congress as grade A contacts. They had most of the senators in their pocket, a lot of the senators. Sometimes they'll play both sides of the aisle. Basically, tobacco is Democratic, Democratic Party, until basically the 70s and Ronald Reagan, then it shifts over to becoming Republican. They create bodies like the Tea Party. They merge with big oil, the Koch brothers, in the 1980s and 90s to form the Tea Party and a whole series of fronts, which fight against all regulation and all taxation in order to prevent gas taxes and cigarette taxes, which are bonded in the convenience store and Walmart. Most cigarettes are actually sold in places like Walmart and pharmacies and 7-Elevens, things like that. And through that locus, then you have gasoline and tobacco sort of in this micro-architectural collaboration. So there's multiple, multiple means that they use. Plus a lot of their targeting is hyper-specific. They use the internet very effectively. They use email and things that are customer targeting. What goes to the mind of a big tobacco executive? This is connecting to our previous conversations of scientists and so on. I always wonder about that. I talked to Pfizer CEO, for example, and there's a deep question with the Pfizer CEO, with I guess any CEO, but Big Pharma. Would you, it's like if you can come up with a cure that gets rid of the problem that's in the Big Pharma, would you want to? Because you're going to lose a lot of money once the cure fixes the problem. It's nice to, like there's so many incentives to make money. Can you think clearly and make the right decisions? I'd like to believe most people are good. And it's almost like this Steve Jobs idea, just like do the right thing and you'll make money in the end. It's like long-term, you'll make a lot of money if you do the right action. Because there's always going to be problems you can fix. You can always pivot the company to focus on other things. As long as you're doing the best innovation, the best science, the best development, and the production and deployment and stuff, you're going to win. But there's another view where you might, that kind of idea of making money pollutes you. It's the widget building. It's exciting when you can release a product that makes a lot of money and you start enjoying the charts that say the money's going up and you stop thinking about maybe that's the wrong choice for human civilization. Well, one of the reasons I was made a courtesy appointment in pulmonary medicine at Stanford was they recognized I was doing more to save lives by trying to stop big tobacco than they were by yanking out this lung, that lung, you know, on a daily basis. Cause of causes. The cause of causes, which we can keep returning to. Your question about how do people live with themselves is a crucial one. And it's one I've thought about a lot. It's one you think about with, in any context of horror, how do people live with themselves? How do they get up in the morning? I think there's a lot of incentives. One thing that you have to keep in mind is that whoever becomes CEO of a big tobacco company, they have already made decisions along the way and they are the remnant of a whole series of aspiring people who wanna climb the ladder of success who maybe would refuse. Something like this. But those don't survive the journey. Those survive the journey who can make it through and I think they have a mixture of ideologies. One, they'll say, well, if I didn't do it, someone else would. This is kind of the pour the cyclone B down the chimney into Auschwitz. Well, if I didn't do it, someone else would. So what's really the difference between me doing it and someone else? So that's one view. Another one is the tobacco industry, I think, really doesn't like their customers except for the fact that they like their money. When you look at their documents, they talk about targeting against young adults or against women or against homosexuals. There's a whole project Reynolds has called Project Scum, which is project subculture urban markets where they're targeting homeless and homosexuals in San Francisco. So what kind of business model regards their customers as scum or talks about them as one famous Reynolds executives. We don't smoke this stuff. We reserve that for the poor, the black and the stupid. That's a direct quote from one of the Winston models. So it's a company culture that sees the customers almost like as the enemy or like, or worthless. Losers. Losers. So you have these executives, if we don't do it, someone else will. If people are dumb enough to buy our product, let them buy it. Maybe it's a personal choice. Maybe they're libertarians. Maybe they're just, as you said, seduced by the money and the money is enormous. The money is enormous and these tobacco executives make tens of millions of dollars per year just in their salaries. So I think there's a whole series of logics. At some point, some of the companies have become food producers in the 1980s and 90s. Philip Morris, which makes Marlboro, was the largest food producer in the United States. And so they could say, well, we're producing many products, many addictive, desirable products. I think one project I'm working on now actually is looking at how the industry maintains morale in their own workforce. And they create a kind of parallel world of prizes and rewards and tobacco queens and tobacco princesses and tobacco sports teams and tobacco, it's this whole separate world, a world within a world. And we all live in bubbles of a sort. And so there is this kind of tobacco world where you're with us or you're against us. And I even found evidence that the tobacco industry lies to its own employees. So they censored their own employee information so that everyone would be on board, that well, maybe it doesn't really cause cancer, the evidence is all statistics, can't trust mice experiments because mice are not men. They hire the guy, Darrell Huff, who wrote How to Lie with Statistics, the best-selling statistics book in the history of the world. They paid him to write a book called How to Lie About Smoking with Statistics. Now that was never published when sort of word of some other dirty tricks got out. So one way they're able to gain legitimacy, gain normalcy, these are supporters of the arts. There are universities named for tobacco executives. We have Duke University, we have the George Weissman School, I think, of Arts and Sciences at CUNY. And there are prizes. Philip Morris essentially created women's tennis as a spectator sport. Billie Jean King joins the board of directors of Philip Morris. She signs coupons, two-to-one coupons, for buying Virginia Slim cigarettes. So the industry is able to acquire this talent and then through a kind of an application of causality purely into the individual smoker. If you smoke, you did it to yourself. And so in a sense, we have nothing to do with it. It's sort of the same argument. Exxon is making now with carbon. It's like, well, we just make the gas, we don't burn the gas. So really, we're not the problem. It's whoever drove here in a car that burned gas. And so there's a very interesting question. Who is liable? Who is responsible for, is the manufacturer just immune because it's a legal product and people make the foolish decision to smoke? Or does the addiction play a role in the liability? So these are all really interesting legal questions and philosophical questions. Where do you attribute the success in the fight against big tobacco? So, I mean, there's been a lot of progress made. Maybe two questions. One is that and two, how much more is to be done? Well, there's been, in my view, not that much progress. The tobacco industry basically won the war against cigarettes. In the 1950s, the broader assumption inside and outside the industry would be, what was that if tobacco, if cigarettes are ever shown as causing cancer, obviously, they'll be banned. The famous slogan in the 50s was if spinach were ever shown to cause 110th the harm of cigarettes, it would be banned overnight. Flash forward 50 years, we still have 300, we still have 200 some billion cigarettes smoked in the United States every year. Globally, we still have about six trillion cigarettes smoked every year. That's 350 million miles of cigarettes smoked every year. That's enough to make a continuous chain of cigarettes from the Earth to the sun and back with enough left over for several round trips to Mars. But it's much fewer than before. Okay, so culturally speaking, I grew up in Soviet Union. Everybody smoked. Everybody smoked. Well, by everybody, you mean about half. Well, by everybody, I mean culturally. So what does it feel like when everybody smokes? What percentage is that? Right now, in the United States, it feels like nobody smokes. Feel, I'm talking about culturally. Do you see famous actors and actresses? Do you see movies? All the time. You do. You can't watch a Hollywood movie without seeing pretty much continuous smoking. I mean, look at Peaky Blinders. Look at any of the modern series now. It's pretty much a nonstop. You're right, there has been a change. I mean, that's true. The purest metric in the United States is number of cigarettes smoked per year. And that peaks in 1981 at 640 billion cigarettes. That's declined now to the level it was in 1940, which is about 240 billion cigarettes. Now, globally, the number has increased. But the perception, sorry to interrupt, but that's interesting. Even in the United States, the numbers, the decrease is not as significant as I thought it is because just in my own experience with people, people speak negatively about smoking. Yeah, well, for one thing, smokers do. I mean, smokers hate the fact they smoke. Right, right, so this is the interesting observation I'm speaking to is even the smokers are talking negatively about smoking, but they're still smoking. So even though I'm seeing this shift where smoking is no longer the cool thing, where it's like when I was growing up and I smoked for a time, it was like a way to bond with strangers, to talk bullshit with friends. Share a moment. Share a moment together. I mean, it's a beautiful thing. And it's interesting because we need to find other ways to share moments. But you know, you almost smoke from a stranger. I mean, that was seen as a good thing. Now. Did you ever smoke? Oh, you did? How many years? Two years. I was a musician. So what happened is I was a musician, I was in a band. Well, there you go. And no, there is a bonding aspect to it. And I think I stopped smoking when they banned smoking in sad bars. Yeah, exactly. Which was, I mean, that was, I mean, looking back now, it seems, it's such a powerful move. I mean, maybe you can speak to that because that was one of the moments that woke me up. Wait a minute. Like that was a big shift for me. And I'm sure I'm not alone where it's not just like, it forced me to rethink the effect that smoking has on me. And also to think, can I actually live a life without smoking? Can I, you know, some people have that. I haven't gone through that process yet, but some people have that with drinking. Can I have fun without drinking? I think the answer to that is yes, but I'm still drinking. So that's a big shift. For example, if they ban drinking at certain places. And there's a lot of negative things to say about alcohol. Well, I'm older than you, and I remember when mother, and I think you weren't even in this country then, but there was something called Mothers Against Drunk Driving. And if you look at movies from the 50s, 60s, even 70s, being drunk was just kind of a funny thing. And you would drive drunk. What's the big deal, really? And Mothers Against Drunk Driving really denormalized drinking and driving, much like seatbelts. When I was a kid, you know, there were no seatbelts. You just lie in the back of the car, and you drove out west with your parents, and you'd lie flat, and it was wonderful. Seatbelts come along, and now it's pretty normalized that you buckle up. It's pretty normalized that you don't drink. And so the moment you identify is absolutely crucially important. A lot of it started in California, where there were bans on cigarettes. Some of it actually started in the computer industry, because some of the early bugs that were found on tapes in the 70s were caused by smoke. And some of the earliest indoor smoking bans were actually in computer rooms, which were supposed to be clean enough that the tapes wouldn't spin and get caught by some snag of soot. And the workers started saying, wait a minute, if the smoke can hurt the tapes, can it hurt my lungs as well? And so some of these early laws, already in the late 70s, early 80s, pushing it out. It was a huge struggle. The tobacco industry marshaled an army of experts to say that secondhand smoke is an entirely different kind of smoke. It can't hurt you. They eventually lost that battle. And now we have so-called smoke-free laws, where you can't smoke in most workplaces and most restaurants. And that denormalization has been crucial because remember Aristotle says, tell me who you walk with and I'll tell you who you are. And if your friends are smoking, if your friends are doing whatever, it makes it easier. The tobacco industry has been a genius at manipulating and really creating the material culture of the modern world. If your shirt has a pocket, that's to fit cigarettes. If your car has a plug-in, every car that I used to have had a cigarette lighter. It had an ashtray. Every plane that I flew when I was a kid, when I was younger anyway, there was smoking on it originally. And then there were ashtrays. And even today, every plane by law has to have ashtrays in the bathrooms because people still smoke in the planes. There's a special technique they have where they go in and light up your cigarette and put your mouth right down in the middle of the toilet and then flush it right at that same moment. And that's why there- Let's take a good big puff. Take a good big puff and flush it. And to prevent people from bringing down the plane by putting the cigarette out in the trash, every plane must have ashtrays. So that tells you something about the power of addiction, the power of normalcy, and it's related to your question of this crucial moment. If you can no longer smoke in a bar, if you can no longer smoke- And by the way, that's different from drinking. Most people who smoke wish they didn't. Most people who drink, that's not true. Most people who drink, they don't wish. There are some addicts, you know, 5% we say. But you're talking about 70, 80, 90% of people who smoke cigarettes regularly wish they did not. And that's actually where I learned about the idea that we could get rid of cigarettes entirely was just from talking to ordinary smokers. Those are the people who are willing to say, you know, let's get cigarettes all together, get rid of them all together, because it's not a recreational drug. It's very different from alcohol. And the genius of the tobacco industry is to turn basic, to trivialize addiction into just something we all like. It's addictive, I like it. And also to say that basically smoking is like drinking, which in fact it's not. Alcohol tends to be a recreational drug, and cigarettes are more like heroin. So how do we get that 200 billion down closer to zero? Well, the good news, and I know you like good news, and I do too, is that every year we have about eight billion fewer cigarettes smoked in the United States. So we're going in the right direction. We're going to solve this. You know, there are, not every problem you can solve in the world. This is a very solvable problem. It's an enormous problem, arguably as big as COVID in certain respects. Much more invisible than COVID, but very solvable and actually will be solved, probably because of climate change, because we're going to need to find ways to reduce carbon footprints across the board. And that's going to be a kind of cultural revolution of sorts once we have a category six hurricane, and you know, hundreds of thousands of people start dying from the storms that are coming. But we'll be, it's like that metaphor of, you know, there's a sci-fi film from 1950 where they're trying to get back to Earth from the moon, and they have to jettison their toolbox and their ladder and this and this and this. That's sort of, I think, the world we're going to be in. We're going to have to jettison a lot of things, and cigarettes will be one of the things we can get rid of. Let's come back to Nazi Germany for a time. You also wrote the book titled The Nazi War on Cancer. Right. What is the main storyline and thesis of this book? Well, I had been researching Nazi medicine. I went over to Germany. I didn't know what I wanted to do. I got a Fulbright. I originally wanted to go to Russia. Went to Germany partly because my girlfriend was going there, Londa Schiebinger, and I was quick with the language. And my old landlady was born in 1900, and I was renting a room, a tiny room in Berlin. And she told me she'd been a nurse in World War I and told me how sad it was that all the mentally ill had died in that war, and that how the same thing happened in World War II. And she told me about how sad it was that she'd never gotten married because there were no German men around after World War I. But I also started taking classes in Germany, and at that time, there were still a few old Nazi professors, just about to retire, you know, very, very old. And I remember there was one guy who would talk about the impact on ovaries of women exposed to stress and how this would damage their ovaries, and that this was like people who had, you know, been told they were about to be executed, and they would do a before and an after on these ovaries. One of these horrific experiments. This was a physician in Berlin, and so I got involved with a group of people, and really as a kind of intellectual garlic for living in Berlin, and this is in 1980, 81. I started reading medical journals from the Nazi period, and even the librarians didn't like that. I remember the Preussische Staatsbibliothek in downtown Berlin, they're like, well, why do you wanna, you know, you're not supposed to be reading these old Nazi journals. These are just medical journals, hundreds and hundreds of journals. And I just read them and read them and read them and read them and looking for details. I'd find like a veterinary medicine journal that would have a joking section where they'd say, oh, we found a cow with a swastika on his forehead, a natural black swastika, isn't that funny? You know, or I'd find stories about tobacco. I'd find stories about abortion. I'd find stories about excluding Jewish medicine or Jews from medicine or who's been promoted, who's been demoted, who's been Nazified. I discovered there was an entire Nazi physicians league that was just the top Nazi, the most Nazi of the physicians. I discovered that physicians joined the Nazi party in a higher proportion than any other profession, that they joined the SS in a higher proportion than any other profession. Why is that? Do you have a sense? Because the Nazi regime is a kind of sanitary utopia. It was to create this purified world that would control the mind and fertility. So, gynecologists and psychiatrists were the top. They were the most Nazified of the various medical professions. Control the body through sterilization, abortion, control the mind through psychiatry. They killed a lot of the mentally ill. And you can read their professional journals. And I'm not sure these had ever been read since. I also went to East Germany, because remember this is way before the wall fell. And they had a very special collection of taboo literature. It's kind of your point about should Mein Kampf be read. Well, of course, East Germany, nowhere close, right? And so, but not only that, Time Magazine couldn't be read, and Newsweek couldn't be read. And this file, this chamber that the foreign scholars were allowed to look through had all of the old Nazi literature and Nazi scientific literature, and Time Magazine and Newsweek, and a whole pornography section as well. So all of the taboo topics. So here I'm researching, in the West, I'm researching these topics the librarians didn't even want me to look at. In the East, I was sort of going over there. I would hitchhike over there and overstay my welcome and things like that. But in any event, I noticed that there was this kind of taboo of talking about the big eugenics. I'd already been, as a kind of a radical graduate student at Harvard working with all the Marxist biologists there, we'd already had a critique of eugenics and women being excluded from science, and South African apartheid was a big deal, and Arthur Jensen's blacks have lower IQs. So there was a whole nest of controversial hot topics around sociobiology, around race and IQ, around women and scholarship and so forth. But we weren't looking at Nazi medicine, so I thought I'll look at the big eugenics, not just this smaller stuff. Only 50,000 people are sterilized in California, but there were huge numbers sterilized in Nazi Germany. So the more I looked into that, I realized there was a book there, but I had also started noticing this other weird stuff. Why were they anti-tobacco? Why did they recognize, why were the Nazis the first to recognize asbestos as causing mesothelioma? Why did they try to ban food dyes? Why did they, why are they the first culture in the world to encourage women to do breast self-exams? I told my mom this, and she told me that in the 50s, women weren't even supposed to touch their breasts in Texas. And here in Nazi Germany, you've got these mandatory breast self-exams way before this was done in the United States. You had the first laws banning the X-raying of pregnant women. Already in the early 1930s, it was standard medical practice. They recognized that this could harm the fetus, harm the race. Way before radiation was recognized as a hazard in England or America, I had started noticing these things, and I have an eye for oddities. I like the weird, the contradictory, that which doesn't fit. And I remember finding a German magazine, a newspaper actually, from 1919, that talked about a holocaust of six million Jews, using that language. How could this be? And I researched it. I thought it wasn't even real, and so I went and actually got the original newspaper, and there it was. It's just one of those oddities of life that just happens. Just weird stuff happens, right? That's the source of conspiracy theories, right? Exactly. So weird stuff happens, but there's an inkling that couldn't have been written in another time in history, or it's much less likely that little coincidence to have happened in another. So it has some kind of resonance with something that captures something deep to the culture. Yeah, and so I'm interested in probing. I mean, history is about seeing the universal through the particular, in a way. So you look for the weird particular, and then pull at that string to see if there's something there. Is it that weird? You know, I did a project I never published on what I call pseudo-swastikas, which is a lot of companies in Nazi Germany made logos that look pretty much like a swastika. You start looking at them. They're disturbingly like a swastika, and I call those pseudo-swastikas. It's one of the many things I've filed away. It'd be a great project just to write it. How did this kind of visual iconography, you know, you weren't supposed to do that. You weren't supposed to sell your bathroom cream with a swastika on it. Yeah. So they would do these little things that look pretty much like a swastika, or I would look at humor. What are they laughing at? What are they smiling at? I didn't even know Germans had humor. Yeah. That's a good discovery. Oddly enough, even Hitler had a sense of humor. There's one speech he gives, which is actually pretty funny, where he's ridiculing all the 29 tiny political parties. Oh, there's a this party and a that party. It's actually kind of funny. So we do have this, again, this scarecrow image, even of Hitler and his personality and this and that. But I started noticing that there was this stuff that looks kind of modern, Hitler being a vegetarian and trying to limit alcohol and this and that. And then I got a call, but I'd sort of filed it away. And then I got a call from the Holocaust Museum. Would I like to be the first senior scholar in residence at the Holocaust Museum? And I said, well, I wasn't really working on Nazi stuff that much anymore, but I did have this idea, maybe looking at how it could be that the Nazis had the world's most aggressive anti-cancer campaign, which is kind of like an amazing fact. And I said, it's not exactly about the Holocaust. In a way, it's about the opposite. It's about what was Nazism that it was so seductive that it could become so powerful that something like the Holocaust could be possible. And they said, well, that sounds great. Do whatever you want. You know? And so I went down to Washington, D.C. and helped them build a little bit some of the racial hygiene exhibits, some of the push and to show the sort of the medical aspect of the Holocaust. And so I ended up writing this book on the Nazi war on cancer, which talks about how right before Hitler's about to invade Poland, he's talking late into the night about how to cure cancer. So for Nazis, racial hygiene encompasses like way more than we might think. So it's like purifying in all ways. And one of the- Purifying and it's also much more normal and more familiar. Yes. Like regular, in regular discussion. It's like the famous line that if Nazism ever comes to Britain, it'll be wearing a bowler hat. And, you know, we create an image of Nazism, which is this fantasy image. Yeah. And, you know, they're human beings making these decisions. And when it's tied to things like removing cancer, so you're saying that kind of the effort of purification walks alongside with this effort of fighting cancer. And then the final, the difficult truth here is that there's a lot of innovation, you know, leading scientific innovation on fighting cancer. It's not a bunch of blind robots following orders. It's a period of massive innovation. I mean, they declared the soybeans to be the official bean of the Third Reich because they realized how, you know, how useful soy could be in protein for the people. They built a whole car out of soybeans. They pushed for a whole grain bread, calling white bread a French Revolutionary capitalist product and they're right about whole grain bread. It's better than, you know, so. Allegedly, so far. So far, that's what we think. We'll discover eventually that bread is the thing that's killing us. Well, by the way, I'm eating mostly meat, so mostly carnivore, and that's been a discovery for me. I don't care what, like, I'm not making a general statement about the population, but me personally, how I feel. I like, I've discovered fasting, so I often, like on days like this, when it's pretty stressful, I'll eat once a day and only meat or mostly meat. And that's amazing to me from a scientific discovery perspective that that makes me feel way better. You know, there's not scientific support why it might make you feel, but I don't care. The point is I've done the experiments and the end of one, and it just makes me feel better. Well, I think fasting is way undervalued. I mean, where do we get the idea you need three meals a day? I have a friend at Harvard and he'll go seven or eight days periodically without food. He drinks water, but he considers it a kind of purification and we're in a world where it's too easy to get food. We're in a world, I mean, most animals are living in a sense that they're on the brink of starvation, but we have technologies and social conditions that allow, it's way too easy to find a piece of cake or a donut, and that's not something we evolved with. We've been talking about purification in that negative context, but there's appealing ways of minimalism, of removing things from your life, of seeking, especially for me being like OCD and a scientist. I do like this simplification of things, of this taxonomy of things. I just recently, storage got hacked by ransomware for these storage devices called QNAP NAS, and 50 terabytes of data locked up, and I can't, so it's lost, but at first it was a gut punch and it really hurts and a bunch of stuff is gone, but it's also freeing. Yeah, well, there's my favorite New Yorker cartoon is where the guy's about to die. Let's say he's 90 years old, he's got tubes in his nose. The very last words are, I wish I'd bought more crap. Yep, and that's now in this amazing world, applies to digital world too. Like you don't need to store everything, you just live in the moment and live for the people. Well, that's one of my fears of Bitcoin is losing your password. I know a friend, his son mined, I don't know how many dozens of Bitcoins and lost his password, and so what can he do? There's a whole, I think, Silicon Valley episode about something like that where the three comma club asshole billionaire is trying to find his old laptop with the password on it. Yeah, that's the kind of dread people feel in the modern age, losing your Bitcoin password. Or for me, it'd be like last pass password. It's hilarious, we're funny, funny creatures. What else can we say outside of cancer about medicine, about engineering, lessons about medicine, lessons about engineering, and lessons about sort of applied science in Nazi Germany? So before we leave the subject, is there some truths that resonate with you still that's applicable for today? Well, historians celebrate contingency, or at least recognize contingency, and we always say things didn't have to turn out the way they did. There were, you can't always foresee what's going to happen. And there were definitely missteps, and the potency of that ideology was such that it trapped a lot of people, and I guess, by the time it becomes essentially a wartime operation, that becomes very, very dangerous. When it's, whatever the ideology is, once it's blended with warfare, that's catastrophic. One of the things that's ignored, I'm very interested in things that are ignored, and one of the things that we ignore now on something even like the climate catastrophe is the role of the military. I mean, there's a huge amount of carbon emissions from military operations. Again, just part of the loop we're not closing. Well, military is really interesting because I'm a AI person, robots, and most of my work when I was a PhD student was DARPA and DoD funded, and I think that's probably true for a lot of science that's funded, especially engineering is funded by the military. And again, I don't, I really wanna be careful drawing parallels between Nazi Germany and anything else. But there is a sense in which, I remember when I was, it hit me when one of the people close to me when I was a PhD, one of the faculty, she refused to take funding from DoD, from DARPA. That was interesting to me. I thought, but what's the, I mean, it's not, like you're not taking a stand against the war, you just don't wanna take money from tangentially associated military kind of efforts. And that little stand, I mean, that had an impact on me. At least it woke me up to, like this is something we should be very, very careful with. For me, artificial intelligence is, you know, much of the DARPA research on autonomous vehicles and all kinds of robotics, drones, I mean, that's pure research. Some of the biggest discoveries, like I didn't think of it as military, I thought of it as engineering and science. But then when the drums of war start beating, like say in some future time, all of that machine is already there to turn it into now Lex is walking around and working on autonomous drones that are going to swarm China or swarms whoever, some terrorist part of the world. And then all of a sudden, all my widgets are being used for that. That's why I've been waking up more and more to, there's been something released called like the AI report. Eric Schmidt was one of the co-authors of it, which is essentially saying that because China is developing autonomous weapon systems, the US should not ban autonomous weapon systems and should also be doing it. So basically put AI into our weapons of war. And that escalation, that race is terrifying, just like all the things you mentioned. But that particular one for me is close because now too closely are the ideas of AI and war and being linked. Very much, yeah. I mean, one of the things I think that is rarely taught in universities is what would you not do for money? Right. I mean, in a basic class on machine learning or even statistics or history, what would you not do for money? What should you not do for money? I have a lot of my own colleagues who work for big tobacco, you know, carrying water for them in court. A huge, essentially a mercenary army of historians, a vast undiagnosed, you know, essentially a hidden invisible army. They don't put it on their CVs. And it's going on the same thing with a lot of the technical fields. What wouldn't you do for money? At Stanford, there used to be secret PhDs, secret research projects. That was kicked off campus in 1971 with the whole 60s radicalism. But nonetheless, individual professors still work for all kinds of military operations. We're setting up a new school of sustainability at Stanford and it's gonna be pretty much in bed with big oil as well. Big oil is gonna be funding a lot of that. You know, what kind of influence? If they have a seat at the table, if they're giving money, if their gifts, if their names are on certain projects, what influence is that gonna have? This is what really bothered me. People don't often have, they don't have integrity in the way that I hoped they would. This is one of the things I learned in academia. I think a lot of people for money, you know, if I give you a million dollars to murder somebody, I think most people would not. Right. A billion dollars, that number starts decreasing, but it's still pretty, I think we would be happy with direct murder not being done for money. But like subtle stuff, just pressures. And it could be with like, let me buy you a drink. And just, you know, laugh about stuff, become friends. That's a subtle pressure. I'm very upset with how many people would just unknowingly like tell themselves a story, ah, what's the harm? And I see that with, for example, me personally at MIT, a lot of people I admire, a lot of people I still admire, I'm friends of mine. I mean, for example, in doing autonomous vehicle research, there's car companies that fund that research. And the car companies say, no, of course, we're not going to influence anything. No, that's like you do, it's wide open. Do whatever you want. But the fact is, you know, they give millions of dollars. And I'm disappointed that actually a lot of scientists in that context are still afraid, even though legally it says they cannot, the car company cannot at all influence the research, they still start leaning slowly towards the ideas that that company espouses. And that's a harmless, perhaps, topic versus big tobacco. But I would argue it has harm on innovation. Yeah, well, it skews innovation. What happened at Stanford was Philip Morris and the other big tobacco companies, they had a massive denial campaign to deny that exposure to someone else's smoke could kill you, when in fact it can. It kills tens of thousands of Americans every year still. They set up an entire conspiracy body called the Center for Indoor Air Research and funded hundreds of scientists to basically say, you know, it's all genetic, if you get cancer, well, you had it coming. Because of your genes, your ancestry, your hormones, whatever. Well, that was broken apart through what was called the Master Settlement Agreement. But it was rejuvenated and reinvigorated by something called the Philip Morris External Research Program, which continued with the same fax lines and executives, funding universities like Stanford, millions and millions of dollars. And when I came to Stanford, there were millions and millions of dollars being given to medical professors by Philip Morris as part of the Philip Morris External Research Program. Well, what were they researching? They're researching genetics, they're researching diet, anything but cigarettes causing cancer, and giving the non, giving the friendly research, as Philip Morris often called it, of bigger voice. They got money, they got jobs, you know, it amplified that as a research tradition. Remember, there's nothing natural in a university about how many professors there are of human origins versus AI. This is all a political decision at a very non-democratic institution. Universities are less democratic than the Vatican. You know, at least the Pope is elected. Who elects, you know, a president of a university or a dean for that matter? And so what happened was I helped launch a campaign to get Philip Morris off campus. And people started coming out of the woodwork, like, well, does this mean I shouldn't be working for the CIA? Does this mean I shouldn't be working for big oil? It's like, what, you work for big oil? And our faculty voted against pushing Philip Morris off campus. But Philip Morris got bad press from it. And so they voluntarily withdrew the entire program. So we started, it was kind of a lesson in that you can lose a battle but win a war if you're doing the right thing. And so by standing up, even though our own faculty wouldn't, you know, back us in kicking Philip Morris out of the medical school, Philip Morris did a cost-benefit analysis, found, well, probably really not worth the kudos we get for embracing Stanford. So it can have an influence. And in this case, the influence was simply by rewarding, giving voice to the people who were blaming cholesterol rather than cigarettes. And of course, we know that historically, the tobacco industry created a lot of these theories, these alternative theories of what causes heart disease, that stress causes heart disease, that salt, or that anything but cigarettes. They funded that research to basically skew the whole research in their direction. You edited a book titled Agnotology. This is an interesting term. So you mentioned it earlier. The Making and Unmaking of Ignorance, where you explore the topic of ignorance, or the authors explore the topic of ignorance in different applications and different contexts. So let me ask the ridiculous, big philosophical question. What is the nature of human ignorance? Well, the first thing to say is that it's infinite. Ha ha ha. Is that an Einstein quote or stupidity or something? I forget what it is, yeah. Well, the point is that there's probably trillions of planets in the universe, and we know one, you know a tiny piece of one. But not only that, who are the we? I mean, we're all born. We started as single-celled organisms, right? As some sperm and some egg get together. That's certainly ignorant, and then we're ignorant. Each one of us, there's an ontogeny of knowledge, you say, but an ontogeny of ignorance as well. We grow up, we have to learn. But almost everything that has been known has been forgotten. If you think about the names of ordinary people, and names of Neanderthal, did they even have names? Most of the history of the world has been forgotten. We have a few shreds, a few traces that we try. History is a kind of resurrection project. It's a kind of archeological project and a genealogical project where we look back and we find traces, and it's very biased. I'm interested in empires that we don't even know anything about. And there are whole empires that are gone if things don't leave a written trace. We know something about Mayan cosmology because we've got some of their stelae and a few of their codices, four codices, but we know the dozens that were burned by Diego de Londa, the inquisitorial Spanish friar who thought these were just heresies and so burned. So that knowledge is all lost. You think there's a lot of deep wisdom about reality that is lost forever? Of course, of course. That's so sad. Well, it is sad, but the human condition is sad. I mean, but then if we can study ignorance, that's also a positive thing. Agnotology, the study of ignorance, the study of the cultural production of ignorance. It's really- Cultural production, sorry to interrupt. Cultural production of ignorance? Yes, yes. So ignorance is not just a manifestation of what it means to be human. It's also forced back onto you through the culture? That's the missing piece that people don't pay enough attention to. It's not a natural vacuum we explore like some empty cave. It's, there are factories of ignorance. The tobacco industry, when they built their propaganda engines to deny that cigarettes cause cancer, they measured exactly how much ignorance could be created by watching one of their videos. They would show that watching one of their propaganda videos in the 1970s produced a 17% increase in the people not willing to say that cigarettes cause cancer. So this is, I call it agnometrics. They actually measured the success of their propaganda, and I'm sure this has been done in marketing and in other fields as well. That framing of it somehow is terrifying because it seems like a very effective way to be scientific about how to sort of create doubt in the mind. Exactly, it's biabolical, and luckily we have some of the tobacco industry's own internal documents, the ones that were not destroyed. We actually know, we have some traces as to which ones were destroyed, and we know that the most sensitive were destroyed, and we know that some of the ones that were sequestered by whistleblowers or by disgruntled spouses or whatever, that those contain the real gems and the truth. And one of the ones that was leaked already in 1981 was the doubt is our product memo that we don't just make cigarettes, we make two products. We make doubt and we make cigarettes. We make cigarettes, but we can only keep selling cigarettes so long as we can keep selling ignorance, and that then becomes a template of sorts for climate denial and for all kinds of other denial engines that are produced by the 1500 trade associations in Washington, D.C. So this is something new in the research enterprise of the world. After World War II, you have this enormous trust in science, trust in research. So what could be more effective than big tobacco saying, look, we're supporting research. We wanna get at the truth. We're funding hundreds of millions of dollars of research, which is exactly what they did. What they didn't say was it was all an effort to distract from the truth that cigarettes cause cancer, and a million other diseases, too, blindness, amputation, all kinds of other diseases. All of that was hidden, covered up through a distraction process. Richard Nixon declares war on cancer in 1971. It's called the War on Cancer. Cigarettes were excluded, even though cigarettes cause a third of all cancers, all cancer deaths. Cigarettes were excluded because the tobacco industry successfully argued that cigarettes cause cancer is not a scientific fact, but a political opinion. Much like the argument that guns don't cause death, you know, pulling the trigger causes death, or shooters, or whatever. In other words, it's all about breaking down the chain of causation into pieces that serve your interests. So it's not that cigarettes cause cancer, it's maybe the smoky them at most, the way they're even denying that. It's the fact you have lungs that cause cancer. It's blaming the victim, and a thousand ways to blame the victim. I mean, there's some legitimacy to this line of argument, which is why it stakes, which is figuring out what is the causation of things is hard to figure out. A lot of the politics of science have to do with which parts of the causal chain do you view as real or not real. When we say that carbon causes climate change, well, what causes carbon? If it's exon causing carbon, is it the person driving the car causing it, or is it the Republican Party causing that, or is it the Tea Party causing that, or is it big tobacco and big oil controlling the Republican Party, or is it what? Is it the Jews controlling the weather, which is where the conspiracy theories come in, or the lizards. So whatever sticks, you try it out, and if you're a tobacco company, you're going to actually literally be scientific about it and try different options. The genius of the tobacco conspiracy, the tobacco denial campaign, which is born on December 14th, 1953, we know on an hour by hour basis how it worked, is to create an alliance between solid research, or as they called it, impassionate, dispassionate research, and to tar all of their opponents as fanatical, emotional, hysterical, political. You mentioned Marxism at Harvard a couple decades ago, or something like that. So 30 years ago, you wrote the value-free science book, Purity and Power in Modern Knowledge, which is interesting that you kind of, what you were describing then seems to be a concern for people now still. So you were, I think, referencing more Nazi Germany, and how social scientists would attack or defend Marxism, feminism, and other social movements using science. There's a, you know, depending on who you talk to, I just spent a day with Jordan Peterson, you know, there's some arguments that science is not being leveraged in some part of the university, which bothers me, because most of the university, at least like MIT, is doing engineering, and not, ideology doesn't seep in yet. But the concern they have is ideology seeps in eventually, if you let it in at all. Anyway, I ask all that, do you have some modern concerns about the seeping in of ideology into academic research in these social movements, for or against Marxism, for or against, you know, well, nobody's for racism, but, you know, on the topic, like anti-racism, all those kinds of critical race theory things, and then also on the feminism and gender studies, and all those kinds of things. Yeah, I mean, these have always been in the university. When people have been most adamant in saying that science is a neutral, value-free enterprise, it's times like the 1950s, when there weren't blacks, and there weren't even women in universities, so, what I discovered was that value neutrality, or this ideology of that we are value-free, it really arose as a defensive shield to prevent greater inclusion, to prevent, you know, questioning of the priorities of science, the practice of science, the nature of science. Now, we're in a period now, I think, of a kind of inclusive revolution, where people are realizing, well, we can't have, you know, universities that look too much like a certain way. There's probably gonna be, in that omelet making, you know, there's gonna be a few eggs that get broken, and I think people may exaggerate the extent to which that's going in, it's definitely real. So, like, cancel culture, all those kinds of things. I mean, it's definitely real, but it's also, in a way, it's also a distraction from looking at big power in a university. If big oil is going to control, or at least influence, the direction of the sustainability school at Stanford, isn't that a bigger issue than whether we have, we can't say certain words on campus? In other words, there's some very interesting and complex aspects to this, and the idea that certain words should not be said, or that certain people should not be invited. An invitation to a university is always political. I mean, who do you invite, who do you not invite? Much as an admissions process is, if a student is admitted to Stanford, what that really means is 96% of the applicants did not get in, they were rejected, they were canceled from a Stanford. 4% are admitted, they call it an admissions committee, they should call it a rejection committee. When we hire someone in my department at Stanford, we get 300 applications, and maybe we accept one. It's not a hiring committee, it's a non-hiring committee. That sounds like toxic cancel culture, all these rejections. Everybody should be accepted. In that sense, it's the essence of meritocracy, is that selection is involved in any hiring decision, because in a way, when you are hired into a university, you are hired to control the means of production, at least part of it. And this part of the politics of it is invisible to the undergraduates, because they are consumers, and you're free as a consumer to eat whatever you want, but you're not free to own the means of production, to say what's on the menu. And that's where the power is, you have to ask the question, where's the power in the university? I think that at MIT, the entire administration should get fired regularly, and more power put in the hands of faculty and students. There is an overgrowth that happens, that it feels like administrators are more easily influenced by big tobacco than faculty. Maybe it's me being sort of romantic about the idea of faculty, but if you're in the battle doing the research, I feel like, well, I don't know. I don't know, I don't know. But it feels like the administration helps you delude yourself longer. So it prevents you from waking up. It's like, no, no, it's okay to take this fine. Oh, Jeffrey Epstein, it's okay. And oh, okay, so he went to prison, let's just keep it a little bit secret, it's fine, just keep taking the money. And I feel like that comes from the administration more than the faculty. Well, there's certainly a cult of celebrity, a cult of money. Donors have the, remember in the whole scandal about the side door entrance in universities, there's always been the front door and the back door, where the back door is the rich donors, the kids of the rich donors, the legacy kids that you still get. So there are a lot of ways universities get corrupted. They get corrupted through money, they get corrupted through influence, and that should be recognized. We're jumping around a little bit, but I read you also do work on human origins. So we mentioned this earlier. Let me ask another big philosophical question. What's human? What makes us human? What is human? And where did that humanness come from? That's exactly the question we need to problematize, because it's what I call the Gandhi question. It's like, you know, Gandhi's asked, what do you think of Western civilization? And he says, it would be a good idea. And so when did humans evolve? Well, not yet. So we don't talk about, you know, when did, you know, we talk about the rise of modern humanity. And what's happened in the last 50 or 60 years or so, which I think is a good thing intellectually, is that we've smeared out humanness to mean many different things. It's not just tool use. It's not just upright posture. Upright posture goes back at least 5 million years. Tool use goes back at least 2 1⁄2 million years. Stone tool use. But since wasps and chimpanzees use tools, then it's gotta be even older. So that's actually one of the things I'm interested is, how have different notions of what is human influenced our theories of human origins? And in particular, there's sort of the problem of what I call like sodomy in the uncanny valley, which is how long ago would you be willing to date someone, say, someone that existed, say, 5 million years ago, 10 million years ago, 3 million years ago? In other words, when is it? A date or a one-night stand? I mean, that's strong. Either one. Either one. All right. Let's say, be the mother of your children. That's a lot of commitment, but yeah. But it's an interesting question because after World War II, as a result of Nazism, no one wanted to be the one to say that this particular fossil we've just found was anything less than fully human. So there's a projection of humanness arbitrarily back into the past. So that even these little monkey-like creatures, Ramapithecines, Ramapithecus, were being declared to have folkways and mores and language, which is ridiculous. No one wanted to say that Neanderthals were anything less than fully human. So it's a very interesting question. At what point are they us? I mean, human origins is very much an identity quest. It's when did we become us? Which sort of begs the question, what are we? Who are we? And how much of that is the hardware evolution question versus the software? Like, what the actual development of society? Can't you argue that we became human with agriculture? I mean, can't you argue that we became human with the Industrial Revolution? Well, certainly by then, they are us. But agriculture is only 12,000 years ago. That's a blink in the eye, right? That's yesterday. It's interesting, prior to the 19th century, most scholars thought that the pyramids were at the beginning of time. Essentially, they were closer to the beginning of time than they are to us. Now, it's a blink in the eye. You know, we use the metaphor of a meter. You know, the earth is five billion, so that's a meter. The natural history of upright humans is five million, so that would be like one millimeter. It'd be the thickness of the white of your fingernail. And then the pyramids are 5,000, so that's a thousandth of a millimeter, a micron, which is the amount taken off when you brush your fingers on your jacket. So, there's a natural history of humanity, and then there's the history of our constituents. We're all stardust, because all of our complex atoms began in supernovas many billions of years ago. But upright posture, five million. Agriculture, only a few thousand years ago. We cultivate dogs a couple hundred thousand years ago, so those are paleolithic instruments. Cats are neolithic instruments, because they're used to kill vermin. Dogs are used to hunt with us. But there is what you say, this co-evolution, our social aspect and our physical aspect. Even the fact that we have whites of the eyes. We're the only animal with whites of the eyes. And the whites of the eyes tell intent. They tell direction. They tell interest. They know, if you look at something, I can tell what you're looking at, because there's a lateral resolution. I can tell what you're looking at. That's recent. And the people who do reconstruction for museums, they want to create what I call an ethnographic identity with the viewer, and so they fantasize about all these other early hominids, non-human, pre-human hominids, if that's a word, as having eyes like us, but they probably didn't. And they were probably not self-aware. At least the early ones can't have been self-aware the way we are insofar as we are. They may not have spoke. So I'm interested in basically when did we become what we think is human? It's clear that when we start burying the dead and making jewelry, and when we, in a sense, invent fantasy, when we invent deception, that's human. That's fully human. We become human by thinking there's a world that really is not. I mean, that feels like we're starting to operate in the space of ideas more and more. So to have deception, to have imagination, you start to be able to have ideas and share them. And it feels like the sharing is the thing that really develops the ideas. It's not you come up with ideas. And we become able to sort of understand what each other is thinking. Some animals can do this to a certain extent. Dogs have a certain empathy, but it's limited. It's highly limited. You could probably argue that the dogs got that from the humans. Yeah, I mean, humans and dogs have co-evolved, have definitely co-evolved, because it's over 100,000 years we've been working together there. But all our hands have evolved with tools. And so I'm trying to figure out now the original purpose of Acheulean hand axes, the first beautiful tool made by humans, which were made unchanged. What kind of axes is this? They're called Acheulean hand axes. They're these beautiful teardrop-shaped objects that go back 1.5 million years. And what's your thought about its possible purposes? Well, the most important thing, I think, is that- To murder a jealous husband comes home? What's astonishing is that no one knows what they were used for. So they may have been maps, they may have been weapons, they may have been chopping devices, they may have been sexual displays. Like ornaments to display something versus actual practical. Like the peacock's tail, something to attract a mate. No one really knows. But what's interesting is how in becoming ignorant of those, that's a form of knowledge. In other words, a lot of, this is one reason I'm interested in ignorance, is that really, to understand something, and especially to teach something, you have to know what people don't know. And that's hard often. It's very hard to remember what it's like to not know something once you know it. Very hard, very hard to do. But you sort of have to do that to recreate that moment you can teach. Well, one nice thing I like about the internet is you can look at old tweets of yours. And to be like, okay, for some reason it brings to mind, like, okay, that's where my mind was. Another interesting exercise is Google search history. So I think for everybody, it keeps, you can look up your own history of what you searched for. And it's so cool to go back to 2008 or something like that. Like, oh, okay, I remember where your mind was. And it immediately, actually, it's a nice way to restore, at least an inkling of the ignorance you had, or have a peek into the ignorance you had about the world. And also to discover the things you've forgotten, the new ignorance you have now. You say, oh, right, right, I was really concerned about this and that. And I do think that, as you're saying, it's both sad and illuminating to think about that most of what we've known, even like the deep wisdom, is forgotten as a human civilization. But, you know, we create it new all the time as well, so. Right, hopefully forgetting is a feature and not just a bug. It's like those mice that can't forget, they go insane. If you imagine all of your memories as present, that's a recipe for insanity. You have to forget to learn, right? Learning is unlearning. Which is exactly why I drink now. And then write some blues songs about forgetting a broken heart. Okay, you mentioned Amber and Stone Collection. I just have to ask, does that connect to human origins or just a personal love? What is it about stone collecting that attracts you? Well, scholars tend to be text-oriented. I tend to think books are overrated. We evolved without books. You know, I walk for a couple of hours in the forest every day. I gather mushrooms and all kinds of things, just located pieces of the 1953 Resolution airplane crash outside of Half Moon Bay just a couple days ago. I like finding things. Have you ever found pieces of a crashed UFO? Not yet. Not yet, okay. All right, let me know please if you do. But of course we have extraterrestrial other stuff. I mean, we have, I'm like meteorites, so I'm into that. And so I'm interested in stone, stone quality. I grew up in Southern Texas and grew up surrounded by people who would hunt for stone and gather stone and cut stone. I cut stone as well. I'm a lapidary. And so I have this interest in the physical qualities of objects, sometimes called material culture, but it's just stuff. And I'm interested to know how different cultures have manipulated stuff, worked stuff, stone, wood, things like that. And also the fantasies people project into it. So I'm doing a book on all the different ways different cultures have found different images in stone like Roshak tests. And so in India, they love agates with Hindu temples in them and altars. And in America, they like, you know, three crosses on the mount. And if you can find a stone with the word Allah in it, that's beloved in Yemen or Saudi Arabia. So there's a long history of people projecting fantasy into stone. And I'm using that as a kind of a metaphor. They also, I'm also looking at the rise of hobbies and amateur stonework and how a lot of our gemologic techniques were actually invented by amateurs, which means just lovers as opposed to professionals. The amateur is the lover. And hobbies, I don't know if you know, but the word hobby comes from a hobbled horse. And so you would hobble a horse to keep it from running. That's hobbling it with a stick or a string. And then kids would ride a hobbled horse for play, a horse on a stick. And riding a hobbled horse becomes riding a hobby horse. And then that becomes a hobby. And so hobbies become this so-called job you can't lose in the Great Depression in the 1930s, and then they explode. And so when I was a kid, people would collect coins or stamps or fossils or this or that. So I'm interested in that collecting passion. So it's interesting, the development of hobbies, because it feels like the future of human civilization will be very hobby-driven. Like some of the, I often now, because of this particular little thing I'm doing with the podcast, I get to interact with photographers and videographers, and I'm disappointed to find how many professionals are not very good and how many hobbyists are very good. So it's also- Well, if they're amateurs, they're the lovers. I mean, you can think that's what that means. From Amour, you're an amateur if you're a lover of the thing, and you're not in it for the money. You're in it because you're obsessed. But as the GDP, as our freedom grows, to sort of financially to be able to have a hobby, it feels like there'll be more lovers, more amateurs in the world, and not just for the artistic pursuits, but like science, technology development, building all kinds of technologies, almost as a hobby. You have much more freedom to figure out what is the thing you love doing, and actually over time, you won't even notice, but it'll start making money. And yeah, that's really fascinating. And yeah, it does kind of, I mean, when did that originate, just the collection? It goes through different stages. People have always gathered the odd thing to make something else, but you also get this tradition of what's called curiosity cabinets, especially in the Renaissance, which replaced the kind of treasure chambers of the ancient sultans or kings or whatever. And you get these curiosity cabinets that were often linked with magical practices, alchemical practices. People would gather bezoars, or they would gather, they would have an alligator hanging from the ceiling, or they would have a rare, you know, shrunken head or whatever. And that's part of the rise of natural history, the idea that you taxonomize the world, you classify the world, you look for the rare object, the rarity, and rarity still is a kind of virtue, like the recent news about trying to figure out ball lightning. When I was growing up, ball lightning was the big question. Does it exist, does it not exist? And now there's new evidence of how it actually might. Wait, what, really? There's new evidence? Yeah, yeah, there's new evidence. I grew up with that. My dad, when I was young, told me, I asked him, like, how do I win a Nobel Prize? He said, invent a time machine or figure out how ball lightning works. And so I got really excited, I was like, damn it, I'm gonna figure out how does ball lightning works. It's very interesting from a history of science point of view because it's so rare that in a way it doesn't exist. You can't replicate it, you can't make it, does it really exist? It's a little bit like Libyan glass, another thing I collect is Libyan glass, which is a tektite, which falls as a result of a meteorite. A meteorite hits the earth, blasts earth up into space, it falls back down as a glass, that's called a tektite. And there's a rare form of it called Libyan glass, which fell probably around 20 million years ago and now works out of the Sahara every now and then. It was the most valuable stone of antiquity. The centerpiece of Tutankhamen's breastplate is made of this beautiful yellow gemstone Libyan glass. So rarity is something that the hobbyists have always liked to cherish, the rarity, the odd, and science has a kind of often aversion, is a kind of a love-hate relationship with rarity and novelty. Science is often trying to pursue novelty to make discoveries. But if you can't replicate it, it's kind of like, what does it really exist? Yeah, which is why, I mean, UFOs and aliens and all those kinds, there's a general aversion to that because it's like the one-time event. Right. It's sad because there's, just like you said, singular events or rare events are somehow really inspiring to us. And so you kind of have to balance that. Yeah, there's a scientific process, but you also have to like, it's the thing you find, the weird, the peculiar, it's like, huh, what is that? Even the universe itself, it could be that the universe begins and then will end, say in a cold death, and that's it. I mean, it could be a one-off thing or it could be one of an infinite many cycles. And maybe all of the laws of nature are recreated anew with each cycle. Or maybe what we're assuming about the Big Bang, there's some element of falsity. Maybe the speed of light is not constant, but changes over time. That would throw into question all kinds of theories about dark matter and dark energy, and even the age of the universe. And to me, there's very likely trillions of conversations going on like this on other planets. Yeah. In different. Yeah, no doubt. Exactly. Different kinds of drugs, different communication styles, different time scales at which life form is or what life looks like or how life behaves or what life is, and all those things. Every time you think about this, it's more and more humbling. It's just this whole fog of ignorance. Yeah. I mean, what drives me crazy is wondering about the beautiful gemstones on other planets. I call them exoaggates. They must be unbelievable features and forms which are unimaginable to us. Because one thing we do know is that nature is very creative. I mean, we are the product of nature, and we seem to be fairly creative. And so imagine what else nature has created. But even that's unknown. How common is life in the universe? Is it common or is it rare? We only have a sample size of one. It could be quite common or it could be even unique. Yeah. I tend to believe it's everywhere, except for the fact that we don't even know how to define what life is. Like, what is everywhere exactly? We're talking about. It's very possible that there's not anywhere in the universe an organism with two legs and two arms with two eyes and mostly hairless walking around at this time scale. But there could be very different kind of other things. It was interesting, there's some people, this is not a common belief, but a friend now named Lee Cronin, he's a chemist and biologist, and he believes that if we ran evolution over and over and over and over on Earth, you'd get very different. Not just, you wouldn't just get different organisms, you'd get very different biology. Yeah, that's quite possible, yeah. That's a weird thing. I mean, most people kind of assume, well, it kind of fits to the environment and you're gonna get similar things, maybe not humans and so on, but to get very different biology, like starting from the bacteria to just how. Well, the idea that it would be DNA-based on some other planet, that seems to me like saying they're speaking Swahili on some other planet. I mean, the odds of that particular architecture I think are infinitesimally small. What's the coolest stone you've ever seen? Oh my God, there's so many. And what defines, is it rarity, is it just raw beauty? What captivates your excitement? I like a storied stone. I have a very beautiful Fairburn agate, which has multiple layers, and there's something I call agate paralysis because to polish it, you have to go through the layers, which means you're destroying the layers. And maybe what should be done is it should be like a movie where you film the entire process of cutting and polishing so that it's not dead. In other words, what was the diamond when it started rough? The rough diamond is gone, but if you could sort of do a filmic version of a cutting process so that the stone would exist from a pre-polished to a polished state, all as a kind of NFT or something. That should be an NFT, that's right. So the other thing I fantasize about is how pattern recognition technology will probably in the future allow us to discover all kinds of amazing stones, including for example, fossil skulls, fossil skulls of humans. Now it's kind of a chance process that you discover a skull in East Africa, but why not have a drone moving constantly, scanning for pattern recognition of human skull, human teeth, very slowly and then- Just on the surface you mean? Just above the surface, just 10 feet above the surface, 20 feet above the surface. No, no, no, sorry, you think you'll be able to find skulls on the surface? Yes, yes, in the middle of a place that no one has looked. These areas are vast, right? So it could be found on the surface, then move to the next layer, then find it under the surface as well. There's LIDAR, there's all kinds of ways. We're finding jungle cities under the Amazon that people didn't know about. Do you think there's something out there that would just blow your mind? Oh, for sure, for sure. Yeah, no doubt. Oh man, and how much of it is a little bit underground, right, or how much of it is in the ocean? Yeah, I mean, here, right here, we are in the Bay Area. We know that much of the Native American civilization here was under the bay because 6,000 years ago, the bay was dry. It was a river, not a bay. And so all of those, whatever material, culture, archaeological traces existed there are now at least preserved under the water. So I think we're just beginning to touch the- Could be treasure, too. I mean, like literally, like you said, we lose the wisdom or we lose the knowledge, but I mean, if there's the pyramids, right, it's the great wonders of the world, there might be other wonders that are completely lost. Yeah. Just some- I mean, one of the stones, you asked about stones I like. I like stones, for example, every now and then, dinosaurs would eat rocks as gizzard stones, and then you find them in their guts, in their bones. Well, every now and then, they would eat a piece of petrified wood, so the idea that something was a tree and then stone and then swallowed by a dinosaur and ground up in the gizzard and polished and then left in a, you know. Yeah. So I like things that have been through dramatic- There's a story there. There's a story. Yeah, I mean, that's, okay, the really fascinating thing, why seeing Allah or crosses in the stone, is it feels like the stone has wisdom because it's been through so many generations of humans, it's like bigger, it's seen it all. Also, it's also the intellectual question of intelligent design. In other words, when people say intelligent design, mostly it's bogus, but there are several interesting examples of actual intelligent design, meaning when is a stone the product of artifice and when is it a geofact produced by nature? And that was an important discovery in the 19th century, the zone of percussion, it's called, the percussion zone. Or how do you know that a signal from out of space is an intelligent signal? And as opposed to hydrogen doing something or some natural thing, that's the genuine problem of intelligent design. How do you know if it's pi, maybe if it's E, if it's some pattern, how do you know that that's an intelligent signal? How do you know that an artifact in the ground is, we'll see in the clouds a face? It's called pareidolia, we have a kind of a built-in ability to see faces where they really aren't there, right? That's why kids like clowns, we've evolved that, so babies evolve it to recognize their parents and so forth. But when is it a projection and when is it really in the stone? And that was a big question with the rise of fossils. If you find a curly thing, is that life or is it non-life? People have made this mistake before. They'll find a rock on the moon or Mars, they say, oh, this is a face or whatever. Well, no, that's just projection, that's pareidolia. I guess throughout science you have this problem of signal. Just because something is beautiful doesn't mean it was, I mean, that's not a good signal to determine if it's intelligent design or natural evolution or natural design, just because you see a stone that just, the pattern is incredible. How do you know? How do you know it's a fossil is one question, namely the remnants of an organism, and how do you know if it was manipulated by a human? This is a big problem in trying to figure out the oldest art. If you find scratchings on a bone, is that a tally? Is it someone marking her menstrual period? Is it phases of the moon? Or is it trampling by an antelope? And that's called the science of taphonomy, to discern when a marking on a bone or a stone is in a sense an artifact or a geofact or an antelope effect. And it's an intellectually challenging question, and people wanna fantasize. They'll find a stone that looks like a carving is 300,000 years old. Generally, I think those are just odd stones. You don't find the explosion of carved stone until around 60,000 years ago, 50, 60,000 years ago. There seems to be something that paleoanthropologists call the creative explosion or the big bang of the mind that produces a kind of ability to see in the distance, to identify a shape in an object, to create a shape in an object that you don't get. The Neanderthals don't seem to have ever done what we would call art. That's a very interesting phenomenon. But it requires that you have some understanding when is something art and when is it just, oh, that's a rock that looks like a face. Or some, not necessarily understanding, but a conception that's mutually agreed upon that we're able to, because maybe Neanderthals, maybe fish, have a conception of art. And this also gets back to your question about professional bias and ideology, because there's a huge reward for finding the oldest art. If everyone says it's 50,000 years ago and you find one that's 300,000 years ago, that's a huge discovery. So there's a bias. And this has been one of the things that's led to probably the overproliferation of different species of hominids, because there's no academic reward for finding yet another example of someone else's species. But there's a huge reward if you can find a Lex Friedmanite, you can name it after yourself or whatever, new fossil. There's a huge professional reward to be the first at something. And so those types of professional rewards also influence science and what kind of science gets done. Yeah, so I'm always suspicious of, and as we should all be, when you can kind of intuit a financial and otherwise motivation. I mean, that's actually often in the modern age where I'm suspicious of conspiracy theories. It's not that the logic doesn't make sense or something like that. I personally actually just enjoy conspiracy theories. I've been listening to Flat Earthers discuss stuff recently. It's kind of exciting for some reason. It's fascinating, yeah. It's like, because I consider like, what if it's true? It's exciting to discover together, like think through first principles, like what does the world look like? It's exciting. I mean, it's the childlike discovery of a new idea. But the reason I'm skeptical of a lot of conspiracy theories is when I see how popular you can get propagating those conspiracy theories, how quickly you can form a large movement. And it's like, hmm. Like- That's thin evidence. If Loch Ness exists, there's just one? I mean, how does the reproduction work off that? How do you talk about an animal that has only one in a population? It just doesn't, some of the things don't make sense. No, but see, this is the logic side. I don't even go that far. The fact is, if you say there's a Loch Ness monster, I just see how quickly the idea spreads in popularity. It's the people are hungry to discover something new, just like you mentioned with the hominids. And I'm very suspicious of where there's a strange hunger for ideas, because then they're less likely to be objective and rigorous in considering the validity of that idea. I'm not going to the logic, because actually, flat Earth is pretty logical. Yeah, very logical. Logic is not the problem. Right, but it spreads really quickly. And once again, with conspiracy theories, I think it represents, you have to think about the cause of causes, or cause of cause of causes, like you talked about, which is like it represents some deeper fragmenting of the common humanity who have the trust in the big community that is science, and the big community that is government, all that kind of stuff. Well, that's why things like ball lightning are cool, because it's like, the scientist denied it, but here it is. Exactly, exactly. And that ultimately ends up being. Everyone said I was insane, but. But it's still, you said there's some breakthroughs, I need to look it up. Yeah, check it out. It's pretty exciting. Yeah, there's some new theories of how it actually might work. Because I think, I mean, there's obviously several ways to prove that. Like one of them is to recreate it in the lab, which is probably. That's a good standard. That's probably very, very difficult. Just because we're on the topic of rocks, I don't know if you've heard about this interstellar rock that flew through our, called the Moua Moua. Yes, yes, the cigar-shaped one. The cigar-shaped one. As a fan of rocks, what do you think about that one? So. Well, I think that generally, I mean, when the people were speculating it might be a spaceship, I thought, come on. Rocks do all kinds of crazy things. They do a lot more than you realize. They can do unbelievable, unbelievably cool things. There are parts of the desert there in Utah where rocks move and create these long tracks. And it's, now we know it's from liquefaction and wind and various other things, but they're still unbelievably cool. Rocks can do almost anything. And so just the fact that one comes from outside the solar system doesn't mean it has to be a spaceship. So, but nonetheless, I thought it was awesome. I thought it was really, really cool. And I sort of wish it would happen more often. I kind of hope it's trash from another alien civilization. That'd be fantastic. Because if you're, if humans are all a lesson, that we produce more trash than we do intelligent signal. So the first thing to reach other civilizations, I feel like, would be our trash, our pollution, before the intelligent signal reaches them. You mentioned this interesting term, Russianist. The things we do for love, for some reason, you went to Germany. Yes. So you said you're pretty eloquent with German. I learned German, yeah. Did you ever learn Russian a little bit? I did learn Russian. Yeah, I studied actually Russian as an undergraduate at Indiana University for several years. And then I wanted to do a Russian, I wanted to do Russian and Chinese as a graduate student because I thought this is kind of the future. And Harvard said, nope, has to be French and German. And so I essentially gave up on my Russian and Chinese. And the other part of that story is nonetheless, I wanted to do something with Russian. I wanted to study how much the Lamarckian ideology and biology in Russia at the time that led to their distrust of genetics under Stalin had to do with the fact that genetics was being pushed by the Nazis. And we tend to see those literatures in isolation. The Nazis were racist, the Russians were environmentalists biased by Lamarckian theories of heredity and rejected that part of Darwin. When they're right next to each other at the very same time, there must be a connection. And so I started reading into this and I actually got a Fulbright to go write a book on this and canceled all my classes. I was teaching at the New School for Social Research at the time. And I couldn't get a visa into the Soviet Union. I was just barred admission for doing this project, looking at how Stalinist science had this anti-Nazi aspect, which we've overlooked. Which year was this, the Soviet Union was still together? Yes, it was in the late 1980s, but before. Gorbachev was in power, but it wasn't before 89. But still then there was a careful attention to. Well, you never know how careful it was or built through the cracks. Or you never know when something fails. You don't always know why it failed. But I was very disappointed and it sort of ended that project. I didn't have access to archives on it. I could have obviously done it later, but you know. So there was that curiosity initially, but then you focused on the Nazi side of- Yeah, I mean the other thing was I was trying to figure out where to go for a Fulbright on a different year. And I wanted to go to China. And turns out you could only go to Taiwan. I didn't really want to go to Taiwan. And it was one in 50 odds of going to Taiwan, but it was one in three of going to Germany. And so I ended up going to Germany. I didn't have any particular interest in Germany at that time, but that's what I ended up doing. So I wrote one book in German, actually. I wrote two books on Nazi Germany. And otherwise I might've been doing the same thing in Russian or Chinese. Yeah, those are- In other words, history chooses us as much as we choose history, right? And those are really powerful cultures, right? Maybe can you comment on the German and the Russian and the Chinese, how much language, when you were reading those medical journals, how much are you able to understand? How important is it to understand language deeply in order to understand the culture? Did you struggle? And the opposite of that, did you find the beauty of the moment, like richly understand the moment because you had a hold of the language? Well, in the Russian or Chinese case, no, I never got that far with it. I knew enough, I could read some Russian and I could tell there were anthropologists who were anti-Nazi and therefore anti-genetics. And they saw genetics as essentially Nazi. And that was enough for me. I know there's something there, but I didn't have enough time. I wasn't allowed to go and actually research it. In the German case, you never fully know a language. We don't fully know English. There's always more to learn. I'm always learning new. I didn't know the word done last year, D-U-N. I mean, some kind of brown color. And I'm always finding new words. The words are near infinite as well, right? And new combinations. I've coined several words too in my life. But it did help understanding the humor, understanding the romance, you know, and mainly just plowing through all of these medical journals, one after another after another. There's a kind of a voyeuristic aspect to looking into this lost world. You're reading texts by people who've died long ago. And direct, it's not like reading books by famous people. It's like real people. It's real people and they make mistakes. And fascinating little stories. I was looking at how the Nazi tobacco industry had their own denial campaign, which was pro-Nazi, but, and pro-tobacco, even though the Nazi regime was anti-tobacco. And they developed a lot of these rhetorical tricks that were later used by the Americans, like, oh, you can't trust that evidence. It's merely statistical. Can't trust the animal experiments because all it proves is that mice should not smoke. But I noticed just in passing these remarkable stories, little hints. There's a report from a Japanese military man in one of these tobacco journals, tobacco industry journals in the Nazi period. And they're talking about this brotherhood of all men through cigarettes and the tragedy that the Chinese and the Japanese who were fighting each other, in a way, wanted nothing more than to smoke together. And the Chinese would sneak up to the Japanese forts to try to find a Japanese cigarette that had been thrown away and they'd be glowing. And the Japanese knew this. And they would throw their cigarettes out, the Chinese would come, and then the Japanese would kill these Chinese. And then this guy is poetically lamenting the fact that even though all they want is a smoke, they nonetheless end up in the crosshairs and in death. And so it's just weird, and I'm reading this, translated from the Japanese into German in a Nazi tobacco industry newspaper. I mean, the layers of weirdness are really fascinating and touching, but. And those very kind of brotherhood stories actually resonated later. Because I mean, that's how I feel about cigarettes. Some of my favorite moments in early life is about people connecting over a cigarette. And that, you know, that works. That's, those narratives. Yeah, it's the movies, right? The movies, it's called Meet Cute. The tobacco industry, when they put cigarettes into a movie, they put it in right at the moment where boy meets girl. Let me ask you just, in all the research you've done with Nazi Germany, just for me, from a conversational perspective, I was listening to a bunch of Holocaust survivors recently, just on YouTube, listening to interviews. Also listening to Nazi SS soldiers, like they're still alive or were recently. Some of them, especially the ones that deny many aspects of the Holocaust. It's so interesting to watch. Because they're still, still, it's so fascinating. Anyway, in your research, are there interesting people to talk to? They're still alive, or are they mostly, that part of history is no longer living, is in the books? It is mostly no longer living. And that's one reason in the 1980s when I started working on Nazi science, I really did interview quite a few people, and elderly people, people who had sort of slipped through the cracks, maybe even should have been prosecuted. So few people got prosecuted. But these were people who had racial theories, who published on these topics, and they were guarded. But these were the lives they lived. And mainly they wanted people not to be talking too much about this. So it gets sealed off and walled off. And that's why reading the medical literature itself was so much more valuable. Because there's no self-censorship, it's just there. I'm sure there's some censorship, but what they said is what they said, and it's immense. It's immense and largely unread. As I said, there are hundreds and hundreds of Nazi medical journals, and people had not been reading those before I really started looking at them. Given that you studied these really difficult parts of human history and human nature with big tobacco and just these mechanisms and manipulation, what gives you hope about the future? Oh, all kinds of things give me hope. The forest gives me hope. The Wikipedia gives me hope. Space exploration gives me hope. All kinds of things give me hope. I had this insight the other day. I walked through all of these giant redwoods, which were almost all cut. They're not very far from here, just half an hour straight west of where we are now, even up in redwood country. And I had this idea that they're growing back now, and every year they add how many cubic miles of wood, if you count California as a whole. But not only that, the roots are all old growth, if you think about it. These are re-sprouting. They're not from seeds. These are re-sprouting, so they have this tremendous resource underground that even the loggers couldn't kill. And so from these stumps, you get what are called fairy rings, which are like five trees coming in a ring around it, each one competing to be the successor. So they've seen this story before, and they know to re-sprout. And that, I think, is a very hopeful thing, is that the roots are old growth, and hopefully in 100, 200, 300 years, it won't peak until around 1,000 years from now, you'll get these restoration of all of this magnificent old growth. But so many other things give me hope. We have to have hope, and I think that if the world is infinite, there's infinitely many ways for it to become fixed. I mean, obviously, we have some problems that need to be fixed, but they're fixable. That's really beautifully put. That is a really hopeful idea, that nature, that life, even human civilization is resilient to all the mistakes we make. So the roots are there. So it outlives us. It's patient with our adolescent fuck-ups. I mean, we're a thin layer on the crust. And eventually, the Earth will be swallowed by the sun, and humans will have long gone extinct by then. But yeah, there's all kinds of grounds for hope. So us being a thin layer of crust, what do you think is the meaning of this layer? What's the meaning of human existence? What's the meaning of life? Well, I think it depends who you're talking to. If you're talking to a raccoon, it might be one thing. If you're talking to an old growth tree, it's making sure you're straight up, upright, and not on a slippery slope. Or a fish. Yeah, fish. I guess they're trying to avoid the hook. When they take the bait, no fish in the world has ever said, I hope I get hooked. And that's one of the problems with tobacco, is that there's all this bait, and people get hooked. But the fish don't have heads. We have heads. One of the great innovations in the history of humanity, going back way pre, I mean, is the invention of the head. The mobile head that turns and sees. And the fish didn't have that. They didn't have hands. The octopus have cool stuff. It's not all about the head. It's not all about the head. Well, in fact, the octopus, basically, they've got brains in their fingers. And maybe brains is not even that good of an invention in the long arc of history. Because the fish maybe got it right. They stay in the ocean. Well, of course, we evolved from fish, so. Yeah, but we moved on. Is there a why to this? Or is it just the way, it's like the current. It's just like these pockets of interesting complexity pops up, like Allah showing up on a rock. This is what human civilization is. This weird little thing that showed up on a rock. And then it'll disappear. Well, we are probably the most remarkable creation that nature has ever belched forward. We're probably the only one, if you don't count the KT meteorite that almost destroyed the Earth. We're the only ones that really have the capacity to destroy the Earth. I'm fascinated by the meteorite that wiped out everything bigger than four feet long. The Mount Everest-sized meteorite that hit the Earth, 66 million years ago, and destroyed most species in the water and on land. There could have been some smart folks around then, too. Well, actually, one thing I like to think about is that 232.3 million years ago, and 232.4 million years ago, that's 100,000 years. That tiniest of a sliver, maybe a millimeter in most parts of the Earth. It's enough time for a species of dinosaur to become intelligent, build a civilization, and go extinct with no traces. And maybe that happened. Our ignorance can fully engulf the fact that that happened. Oh, the beautiful self-importance of us humans. It's easy to forget that multiple intelligent civilizations could have lived on Earth. It's possible, and gone extinct. Or even, life may have evolved more than once. Not only that, but proto-life may still exist when you're not even looking for it. Some type of clay that became life may still exist. One thing I like to think about is always, what is the before time that is now? I remember lecturing about this right before COVID. It's sort of like, what is the our world now that we'll say, what was it like to be then before? And that's the world we live in. We live in a before time for something we really can't predict. Probably physical, you know. Appendages. And being in person, being able to touch each other, or wanting to touch each other, versus being in the digital world, right? This whole idea of the metaverse, and more and more moving into a digital space. What was it like being born before most of your life wasn't on the computer? Yeah. It's pretty damn good for the record. But maybe, I don't know the alternative. Robert, this is a fascinating conversation. Thank you for taking us through some dark periods of human history, but I think they contain a lot of lessons for today. That science is often inextricably connected to our values, to our ethics, to our politics. And that's something we have to contend with. So your work is really important, and thank you for shining a light on it. Thank you. Thanks for listening to this conversation with Robert Proctor. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Carl Sagan. Somewhere, something incredible is waiting to be known. Thank you for listening, and hope to see you next time.

https://youtu.be/Y3VBCWIDEzk

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Roger Reaves: Smuggling Drugs for Pablo Escobar and the Medellin Cartel | Lex Fridman Podcast #199

The following is a conversation with Roger Reeves, one of the most prolific drug smugglers in history. He worked for Pablo Escobar and Jorge Ochoa, the leaders behind the Medellin Cartel. Roger was the employer and close friend of Barry Seal, the infamous drug smuggler who was the main character in the movie, American Made. Roger transported countless tons of cocaine and marijuana covering six continents. He escaped prison five times, was shut down in both Mexico and Colombia, and was tortured nearly to death in a Mexican prison. Through all of this, his wife Mari, the love of his life, was there with him. And when he was in prison, she waited for him. He recently got out of prison, where for many years he worked on his memoir called Smuggler. This podcast is an exploration of a story. Quick mention of our sponsors, Noom, Allform, ExpressVPN, Four Sigmatic, and Aidsleep. Check them out in the description to support this podcast. Let me say a few words about Roger Reeves, Pablo Escobar, and the war on drugs. This conversation with Roger is unlike any I've ever done. In the eyes of many, including the law, Roger is a criminal, a bad man who has added to the suffering in the world. But he never directly engaged or participated in the violence. Unlike his bosses, Pablo Escobar and Jorge Ochoa. His crime was the transport of drugs. I thought about this and about Pablo Escobar, who was at once both a brutal murderer and a Robin Hood figure who helped the poor and was loved by thousands, if not millions. We sometimes idolize murderers and destroy good, honest men. We give power and money to corrupt politicians and dictators that starve and murder their own people. Given this, I think about what makes for a good man and what makes for a bad man and who decides. Sitting across from Roger, I saw a complicated man, but one who has kindness in his heart, a love for money and adventure, and a disdain for violence. Again, his crime was the transport of drugs. Since 1971, the war on drugs has cost US $1 trillion. Marijuana legalization alone would save and make $13.7 billion. That could send more than 650,000 students to public universities every year. Then there's the human stories of the 500,000 human beings sitting in prison for drug-related offenses and the 1.1 million on probation and parole. Their life is damaged or ruined beyond repair due to the prohibition of drugs. There's a lot more to be said about the damage done by the war on drugs. But when reading about Roger's story and talking to him, I couldn't escape the thought that while society wants to label him a criminal and a bad human being, there are much worse men out there who we give a pass to, even give power to, even men who hold political office or run companies. I also think about my role as an interviewer. Sitting across a man like Roger, in these interviews, in life, in many ways, I continue to be myself, a person who, like Dostoevsky's The Idiot, seeks the good in all people, but is hurt by it on occasion and maybe is destroyed by it in the end. I'm not naive, but I'm also optimistic and have hope for humanity. That's who I am. And that's what these conversations are. I hope you join me and I hope you understand that I come from a place of love. This is the Lex Friedman Podcast, and here's my conversation with Roger Reeves. You are one of the most prolific drug smugglers in history. What would you say motivated you? Money, power, the thrill, or was it something else? Money. But isn't there a point where you've had more money than you can possibly know what to do with? Or is it always more money? You know, I had plenty of money several times. And I think it's sort of like if you was in Las Vegas and you had the slot machine handled down and the gold coins was tumbling around you and you had sweepers bagging them up, when would you let it go? But isn't some part of that the thrill then? Oh, there was a lot of thrill, sometimes way too much. You made certainly tens of millions of dollars, probably much more. What memorable experience did having that much money make possible for you? So there's one thing is the money, and the other thing is what that money can buy. Well, I bought everything that I could hide. I bought seven farms. I owned the land where the city of Merino Valley, California is. I had an option on that land. Did the planning and development of that. The most expensive coin in the world. Yachts, ships, airplanes galore. Did that bring you happiness? No, absolutely not. In fact, I think I'm happier now. I know I'm happier now. So looking back, would you do it the same way all again? No way. Really, even the thrill of it? Not even the thrill of it. It wasn't worth 33 years in prison being away from my lovely family. So money, what about the power? Just being on top of the world where nobody can, not the governments, the police, all the big bad agencies chasing you. And you could do whatever the heck you wanted. As far as having to look over your shoulder everywhere you went and every phone call you made, make sure that you was naked with somebody in the ocean before you talked. It's rather uncomfortable. Yeah. I like to make phone calls the same way. What was it like meeting and working with Pablo Escobar, the leader of the Medellin cartel? He just seemed like a gentleman when I met him. He's just like you and I sitting here, shook hands. And I had flown one load for a fellow and it didn't work out well. The fellow that I gave it to got shot and it took a while to get my money and they didn't put as many kilos on the plane as they're supposed to. So I wasn't gonna work with him anymore and my contact down there introduced me to Jorge Ochoa. And we went up and in Vigada, we went up and the gate opened and we was escorted in. They must have been 50 men out in the yards, a hitching rail on an old house. And we was escorted right in. And there was a beautiful woman in there. I mean, gore, drop dead beautiful. And she made us a cup of coffee and then was ushered in to see Jorge Ochoa. And he had 12 telephones on his desk and all of them was a different color. And he shook hands, was very friendly, spoke English. And he said that each one of those telephones represented another city in the United States. This is Chicago and this is New York. If I ring, I knew who's calling. And so we chatted a while and he asked me what type of airplanes I had and what experience I had flying across the US border. And I told him he seemed pleased with it. And he called the lady in and she went next door and in came Pablo Escobar and he introduced me to Pablo Escobar and he asked the same questions again. And I answered him and I says, and I asked him how much he paid and they paid $5,000 a kilo to haul it. And so I said, how much you put on the plane? He said, 300, 500. So that's one and a half, two and a half million dollars for an eight hour trip. Sounded pretty good to me. And we're talking about cocaine. Cocaine. And we're talking about Colombia. Colombia and cocaine and Medellin Cartel. And Jorge Ochoa was one of the, what would you say, founding members of the- He was probably the brains behind the whole thing. The brains and spoke good English. Yes. And they were nice people. Really nice people. Were you scared? Not at all. What's wrong with your mind that you weren't scared? Here's some of the most dangerous men in this world and you weren't scared. Well, I knew I was gonna do exactly what I said I was gonna do. Mari and the children were down there. They went down and they stayed in the hotel, five star, treated royally on my first load. And they just did that as security to make sure that I wasn't a DEA agent. So I did the first load and they can say they were hostages but they really weren't. It was just insurance. So there was some integrity to the way they operated. Completely. I mean, straight up. The money was ironed and banded and just right. And the numbers were never once anything wrong with it. What would you attribute that honesty to? Within their own moral system and their own set of rules, why weren't people crossing the line and shaving off the top and injecting chaos into the system to where it would be unpredictable and people would be dishonest and greedy and all those kinds of things? That's true. Most people are but there's certain people at the top of the food chain that they don't need that. And if they're completely honest, then they don't have to think of, remember the lie they told. And plus they're just honest to start with. They're making plenty of money. They was making as much money as I did. I'll tell you how that came about. I understand that 10,000 people were killed every year in Medellin, Colombia. And what they were doing, they didn't have any organization. And if one fella had 10 kilos and he wanted it shipped to New York, he would tell his friend. And his friend says, sure, I'll ship it. I have a pilot and I'll ship it up. And then he would look in the newspapers. Oh, 40 kilos was busted in New Jersey. I'm so sorry, yours got busted. Bang, bang, he's dead. So here comes Jorge Ochoa and the three Ochoa brothers and Pablo Escobar and Gacho and they decided that we will make an insurance company. That we would charge you $10,000 to take it to your contact in Miami. If it gets lost anywhere between the time I put it on the airplane or the time you give it to us and the time we give it to your man, we will replace it in Colombia for you. So there was no way anybody could lose. And I understand they got 100 tons piled up under that insurance program. And I was right there the first day. So I had all the work I could do. I would land and I said, when you want me to come back, we waiting on you, senor. Well, let me ask a difficult question. Some see Escobar as a brutal murderer and some see him as maybe a Robin Hood like figure who helped the poor. How do you see the man? Both of them. I think he started out, to be honest, with help the poor and then they had a war down there. And they blew up and killed his people. And the country was divided almost equally three ways. They had the military. They were just as much into it as anybody. And then you had the FARC guerrillas. They had about a third of the country. And then you had the conchers. It was like the white farmers. And they're the ones that I was dealing with. And they were at war with one another. And so if one of them started killing their people, I'll kill some of yours too. So that's how it happened. And then when I heard about Pablo Escobar blowing up that airliner and killing those women and children, I was sorry I ever shook his hand. That's brutal murder. So you would say Escobar's not a good man? Not at all. He was terrible. Now, looking back on it, when I met him, he was good. Did just exactly what he said he would do. Could he be a bad man and a man you can trust? Are those the tensions? Absolutely you could trust him, yes. So from your perspective, in terms of business, he was reliable, he was honest, had integrity, you could work with him, and you felt safe? Completely. We flew up to his ranch, and we brought out motorcycles to start with. And can you ride a motorcycle? Of course I can ride a motorcycle. So I took off across the grass, and there was a little ditch there. And the front wheel dropped in that thing, and I must have slid across that grass 20 feet before I got stopped. He almost fell off of his bike waiting because they knew what it was gonna do. And then we got on horses, and we went out there and pretended to round up some cows, and he put a Mac-10 machine gun pistol over my shoulder. You know how to use this? Well, I never had, but it was all right. I think it was like, okay, you got 10 bodyguards, what do you need me for? So that's the kind of time we laughed and talked and drove some cows over the stumps. You said Jorge Ochoa was perhaps the brains of the Medellin cartel. What was he like, and why do you say he was the brains? Well, he was a gentleman. And I suppose he shipped, and don't tell me how many more times of cocaine than Pablo did. Just him and his brothers, you could tell by the, they had on each load, they was in duffel bags. And it's big football-shaped, fluffy stuff made with ether. And they would have three horns on it, or a rattlesnake, or four X's on each bag. You kind of got to knowing which was which, and they shipped a lot. So, and he was just a gentleman. I took the family, we went one weekend to his ranch, or his palacio place out near Barranquilla. And oh, he just treated the family, his family, his younger brother made a bull fight, and we had skiing and little airplanes on floats on the water. It was really nice, and he was really nice. How do you make sense of the tension that a man could be a gentleman, could have integrity, but also be a murderer? Well, murder is a stronger word than killing. Can you explain the line, the gray area we're talking about? I mean, I've just talking with Jocko Willink, and we talked a lot about killing in the context of military conflict, in the context of war. So there, there's a line between murder and killing that you can draw. What's the line that you're referring to? It's something similar. If people are shooting at you, and you shoot back and kill him, that's not murder whatsoever. He's trying to get away out of the situation. But if some woman don't pay you, and you send a hit man over to kill her, and or kill her, that's murder. Was Jorge involved in those kinds of things? I don't think so at all. I mean, he was just such a gentleman. He had a restaurant before, and he was just smart. I understand that the first 10 kilos he sold, he was sitting on a motorcycle in the sidelines in a parking lot, and when the DEA come in, he sped away. So he didn't come back to America. He was just smart. Some people just are savvy. And he was such a gentleman. And the whole family, the mother and the father, the two brothers, their sister, I was there when she was kidnapped. And finally, he kidnapped our, I guess, 100 liters of the farc. And I said, all right, if she don't come back, none of these are gonna come back. So they made a deal. Is there something you can say about the power structure, the hierarchy of the Medellin cartel that you interacted with? Was it a dictatorship where Pablo ran everything? Was there a bunch of power centers? Was it like a company where you have CEO, CTO kind of thing? And then there's like managers and all those kinds of things. How did it run from a leadership perspective? I understand that about five of them got together and made this, I will call it an insurance company, and now known as the Medellin cartel. And I didn't see any difference. Each one of them had their own business. And their people from the jungle or wherever made the cocaine, gave it to them, and they shipped it. And so it didn't seem to be any power play between them at all. But my main contact was Jorge Ochoa and Pablo Escobar was right there. And I saw plenty of stuff for him too. It's strange that they didn't betray each other regularly. You know, greed makes men betray each other. How do you explain that? How much betrayal did you see? I didn't see any, absolutely none. If they shipped his 100 kilos, he got paid for it. If the other one shipped his, I'm sure they got paid for it. How do you explain that? Well, there was no need to. The money was just unbelievable. You think about 500 kilos in the plane. It's $50,000 a kilo at the time. And they paid $5,000 to ship it. And they made 5,000 without even touching it. They just had somebody to load it on through the airplane. I gave it to their man in Miami. They gave it to whoever it belonged to by the marks on the duffel bags. So they was making just untold millions. Just no reason. But greed can blind men. It's still strange to me that there was not more betrayal. It speaks to something else, perhaps that's bigger than money. Maybe not. But it seems like just like in the casino, like you mentioned, we get accustomed to whatever level of money we have, we get accustomed very quickly. Yes. And then there's a tension that's natural between human beings. And when that tension combined with money, combined with power, combined with, like you mentioned, beautiful women, and a bit of violence, it seems that betrayal should be commonplace. But it's not. It wasn't, not at all. Carlos Lader, I don't know if he betrayed anybody, but he started that, he was running cocaine through the Bahamas. And he had the island. I didn't go. I was offered to fly with a DC-3 with that, but I didn't like it. So I had my route through the oil wells in Louisiana. And so I didn't want to change. But he talked a lot, and I don't know if he betrayed, but they didn't like him. Yeah, so as you expand, there could be tensions that lead to conflict. Columbia was, like you said, an ultra-violent place. How did you survive? Who protected you? I was a hero. They liked me. I mean, I was just treated royally. All I did, I would come over El Banco. There's a radio station at the forks of the Magdalena River. I believe it was 720, if I remember right, on the AM. And I'd fly in at 10,000 feet, and I'd see below me there'd be a Cessna. And I'd wiggle my wings, and he'd wiggle his, and I'd fall in behind him, and we might go 100, 200 miles. I'd land on some jungle strip or some banana plantation, and they'd fuel me up. I could eat steak in the night. It was just like treated royally. I mean, take off the next morning whenever I wanted to. It was just like that was protected. And I was an honored guest. It wasn't anything like in that movie, putting a gun to your head and taking your sunglasses and betting. So one time I complained to Jorge Ochoa that the runway was pretty short that they were using. And I went back down there, and it looked like Los Angeles International. They had bulldozers in there. Had that thing 5,000 feet long. It's just like, just the next week it was all done. The jungle was gone, and clay put up there. And all the while you were not afraid. You were treated like royalty. Yes, there I was. I was afraid when I landed in the United States. Well, maybe let's go back to the beginning. What was the first time you flew an airplane with drugs on it? Tell me the story of the first time you smuggled drugs. All right, I flew down to Jalapa, Veracruz with a Cessna 182. And we landed at the town. It was a lovely town. And just an old town, looked like Bible times. Women were washing their clothes in the streets and with stone basins and the stream running through. I just was just dumbstruck. It was just so pretty. And I went in a church, a Catholic church, and it had the Stations of the Cross all carved magnificent. I'd never seen that. And I come home and told Mari about that. That just almost brought tears to my eyes. It was so beautiful. And three o'clock the next morning, I went out to the airport and taxied down to the taxiway, and there was a guard came out. And wanted to know what I was doing, and I pulled out, I was on the fire department at Redondo Beach, California. So I pulled out my wallet, and it was the fire department badge. And oh, he shook my hand and was so glad. So I taxied on down there, and we loaded up about 400 pounds in the plane. And I came on back, and I was running the headwinds more than I thought. And I landed on a little strip. You're talking about on the way back? On the way back, on the way north after we loaded up early in the morning. And that's the only time I ever got vertigo. The mountains were coming down at a 30, 40 degree angle, and the Milky Way was overhead. And somehow I wanted that airplane to be level with the stars. And it got me, and it's a phenomenal pile of vertigo. It's the only time I ever had it was on that load. So anyway, the wind was on the nose of that system. I wasn't gonna make it to the dry lake where I had fuel. So I landed on a little bitty strip, and there was a little house. It was caved in, and it was a little boy named Lazarus, about six or seven years old, and he was herding some goats. So we put the marijuana in that house, and the man stayed with it while I flew into some town and got fuel and came back. And we sat down with the lunch that I brought back, and little Lazarus sat there and ate with us. And we had a good time. We loaded on back and came home. Oh, wow. I wonder where he is now. He is. What was it like to fly? Maybe describe the details of, do you have to fly low? Is there details that are unique to this experience of flying an airplane with drugs on it, on board? All right, well, one of the mistakes that just thousands, hundreds and hundreds and thousands of pilots make, they don't stop at the border, going down and get their permit. Once you get a permit to be in Mexico, you've got it for six months. You can go anywhere, any fishing village, any little town, any little place, show them this and you're welcome. If you don't have that, you go straight to jail. So you go down there and you think, okay, they're gonna have fuel for me to come back and so forth. Oh, sorry, senor, that had a rusty leak in it. We don't have any. Well, you better be able to go to town and get it. So that's what I did. And when I was coming back for several years, I would fly up at Mexicali and cross the border right at Calexico. I would act like I was landing on the Calexico side just after dark. And then I would zip across the border and I'd go over to the Salton Sea and go below sea level, 100 and something feet, I believe 170 feet, and come on up and go out there above Palm Springs and land out 29 palms in the desert and put my stuff under a Joshua tree and fly into town and get my pickup and go on back out and get it. And that was fun. And then it got really dangerous. They had Operation Starlight, I believe was the name of it. And they caught a lot of pilots coming across the border. So I changed it. And by that time I was flying bigger planes. I was flying Beach 18s. And I would refuel in Mulaje halfway down on Baja Peninsula. And then over in the middle, 20 miles from the nearest road was a goat ranch where they milked goats and made cheese. And I would go there and unload the load coming up out of anywhere in Southern Mexico. And I would land there and a guy named Juan would put the marijuana under the trees and I'd fly into Mulaje and they'd wash my plane and gas it up and I'd eat a lunch and rent a room for a few hours and take a nap and a shower. And then go back in the afternoon and fill up. And then I would go Northwest out of there and fly 200 miles off the coast of the island of Guadalupe. And from there I would fly on a more Northwestern heading about 300 miles out over the Pacific. And then I would come in behind the Santa Barbara Islands down low and then I'd come up and go out in the desert land. And I did that for the rest of the marijuana trips. What was the hardest part about flying those routes? The hardest part was getting good marijuana. So the hardest part isn't the flying. Not as the flying, just like driving your car down. But then I had people that would bring me on strips that were just unworthy of an airplane. I'd land on a highway. And in the rainy season, I would come back to land again and the guy wouldn't think about it. And he'd have like little hills on both sides and the wings were out there. Well, the grass and the weeds would grow up and it sounded like, I mean, it sounded like tearing the airplane apart when those wings hit. Mowing the grass down both shoulders of the airplane. The weeds would grow up high in the tropics. So some of that stuff was bad. And oh, getting bad gasoline and telling me that land here in the light and knock the wheels off when you land. Oh, you should have landed a little further up here, senor, they ditched down. That sort of thing. What was it like landing on a highway? And when did you have to land on the highway? I landed a highway most of my life, most of the times. In Mexico, first time I went down, there was a place called Piculingui. And you had a 900 foot strip. And I would fly down and I'd carry gasoline with me. And Mari and I would go to the grocery store and buy all kinds of little goodies and candies and toys to bring to the children. And that sand strip in the bend of a river was just too short to take off with a load. So there was a young man there named Pedro, must have weighed much over 100, maybe 120 pounds. And he'd get in a plane with me. And he'd direct me 20, 30, 40 miles away to a highway. And the people walking, and the people would pull out in a two ton truck with a machine gun on it. And bunch of guys with their arms. And they'd block the road. And then another one would block it up about a mile away. And I'd land right over that truck. And they'd load me up. It looked like a bucket brigade with the marijuana coming. I'd shake hands with all of them. And I'd take off right over the other trucks. And sometimes maybe 20, 30, 40 cars lined up. One time I remember a patrol car, a highway patrol car. He didn't have his lights on. Took off right over him. And then when I started flying to Louisiana, the bridge over the Mississippi River, there were several contractors that went broke. And that thing was out for years. And about five miles from the river was flashing red lights and a detour. And then the swamp on both sides of it and the middle of it was growing up with 20 feet trees. And that was like an international runway from anywhere in the world. So I landed on that and over and over those red lights. It was just like the end of a runway. And then the next morning, we'd go out there and scrub the marks off the highway where I'd landed before daylight. Wow, let's go to somebody you've known well. Somebody who's also a drug smuggler is Barry Seal. Who is Barry Seal? How did you meet him? Barry Seal is a friend of mine. Mari and I and the children went down in Honduras and we went up Lake Azul, I believe it was. And we were looking at a ranch to buy. I was looking for something in Central America where I'd have a halfway place. Oh, it was lovely. We stayed up there for some days and our clothes got muddy and we went in the river and all kind of things. So we got to San Pedro Sula and we was going back to New Orleans. So we went to the cleaners to get our clothes and most all of them was in there. And they go, oh, senor, they'll be ready tomorrow morning. We're not ready now. Well, the plane leaves at nine o'clock or whatever. So I told Mari for her and the children to go into the airport because it'd be easier for one on a standby flight. So I went to the laundromat for the clothes and they were ready and there was a pile of them and I put them on my back and got in the taxi and the old taxi was driving with it and I gave him $100 to go faster and he just blew his horn more rapid. We got to the airport and I jumped out and ran around on the tarmac and here's a brand new 727 taxiing out. Oh no. So I'm waving to the pilot and he's a young fellow. He waves back. Then I see Mari's face in the cockpit and the nose goes down where he puts on brakes and he laughs and he puts some stairwell out. And I run for the stairwell and he pulls it back up and goes like a hitchhiker gonna pick you up and go again. Then he put it out and I got on and the whole crowd clapped and I'm coming home with that load of clothes. So I go way down in the middle and the plane's full and Mari, my daughter, is about nine years old then and she was sitting in the middle and by the window was Barry Seal. Of course I didn't know it. And I sat in the middle and we took off and the wheels come up with clunk and then I got up about 5,000 feet and we had a little clunk. And she said, what was that, Daddy? I said, he just turned on his autopilot. That fellow reached over and I looked at him. I said, he looks like CIA or FBI, something. He ain't supposed to be here. Clear blue eyes, gentleman looking man. And he said, you fly these things? I said, I got a few hours, mister. He said, I'll fly them too or something. He said, my name's Barry Seal. He reached over near him and shook hands and we got to talking and I thought, there's no choice of seats on this. It's just open seating, but I don't believe him one bit. And he started talking about he just got out of jail that morning, just got out of prison. And I said, uh-huh. And he told me that he'd been a pilot with the TWA and this and other and told me what he was for. So we had a nice conversation for a couple hours in New Orleans. I didn't believe him. So he got off in front of us and what a crowd of people to meet him, an old mother and a wife and little children hanging on to him, crying and hugging and kissing him. I said, he was telling the truth. So I reached over and gave him a little piece of paper. I had Mario write it out with our address. I said, Barry, I might have some work for you. What was he in jail for? He got caught with 100 kilos of cocaine in a small plane. And so he's served a year. And that was from Colombia? I don't know where it come from. He got caught in Honduras, probably refueling. But he'd been in prison down there before for bringing explosives to the Cuban contras. And he lost his job with the airlines. And then later on I found out he was ex-CIA and George Bush Senior's protege and had a thousand parachute jumps and was there. He was a hot shot, my old man. There's a million questions I wanna ask here. But maybe can we linger on it a little bit longer? What was your relationship with him like? You were a drug smuggler. He's a drug smuggler. Your friends, how often do you guys talk? How often do you work together? What was the relationship like? Well, I'll back up and just finish where I started off there. I gave him a thanks, Barry, I may have some work for you. I know I got some work for you. And I said, come out to Santa Barbara. And so, I don't know, a week or two later, he flew out and went to our house and stayed with us a couple of days. And I had an almost brand new Aero Commander 690B. That thing was turbo-prop and it was hot. It was the hottest thing I'd ever had. So I said, let's go, Barry, let's see what you can do. So I'm sorry I said that. We got about 10,000 feet. And he was like one of them Blue Angel pilots. He wrung that thing out. And I said, that's enough. And then he did a falling leaf. That's where you cut the engines and the plane falls from side to side. I saw Bob Hoover do that in an air show once. And that's the only person I ever saw do it. And my hand was white knuckle hanging onto the seat. You shut off the engine? Yeah, he shut off the engines and landed flying side by side like this. How do you explain that? Was he just a wild man or was he sufficiently skilled to wear it? He was sufficiently skilled, absolutely. He knew what he was doing. I can get a plane from one spot to another and I guess I'm known as a good pilot. But that guy, it was aerobatic. So anyway, he stayed with us a couple of days. And then I told him, I said, this plane needs tanking. I said, I got some work done. The Columbia needs to come back to Louisiana. And I need 2,500 mile range. He said, I got somebody in Mena, Arkansas to do that and keep their mouth shut. So I gave him $10,000 and he flew away. And in a few days he called me and says, come to my house in Baton Rouge. So I went out to his house in Baton Rouge and I stayed with him for a few days. And that plane was tanked. I mean, beautiful from stem to stern. I could went from Bolivia to Canada with it. So he was, then I hired him to fly. And he was funny. I paid him a million dollars a trip. I paid him $2,000 a kilo. So about a million dollar trip. And I didn't get paid until the people received it. They had to ship it to Chicago and New York and then the money come back. So it was a couple of two or three weeks pipeline. Well, I always had to pay him before he'd go again. I mean, and he bellyache. I mean, he had moaning room. So one time I gave him a million dollars and I put it in a box real nice. So how big is a box that contains a million dollars? So we're talking about $100 bills? $100, it's not very big. You can put it in a large briefcase. It weighs exactly 10 kilos. Each bill weighs a gram. So you can weigh your money and almost get it exactly right. 20 something pounds is a million dollars. 22 pounds. 22 pounds. $100 bills. But in $1 bills, it's one ton, 2,200 pounds. We didn't even accept them. Were you the one that introduced Barry Seale to Pablo Escobar? No, I didn't introduce him at all. And our deal was that you don't meet my people. I mean, we just kind of crossed you working for me to fly the airplanes. So he wanted these Panther conversions that cost $400,000 each with a storm scope and radar. I bought anything he wanted. What's that mean, sorry to interrupt, Panther conversions? A Panther conversion was these people called Panther. They took everything out from the firewall, the instruments and all and converted them and put Q-tip propellers on them, full bladed, and you're very quiet. And the CIA developed those in Southeast Asia for running behind the lines. And that's where Barry had flown those things so he knew about them. So that's what he wanted and that's what we got him. How does that connect to Pablo? And so he worked for you and you got those upgrades. I think he flew about 30 loads for me and then I got arrested and was for everything in the world. Got 35 years sentence. But let me back up a little bit. Barry was our friend, Mari and I, both friend. We should pause real quick and say Mari is your wife and hopefully she'll convince her to join us in a little bit. She's the love of your life and she weaves in and out of many of these stories that you tell. Yes, she was there. She was behind the scenes. But I kept her out of it completely. And then also you mentioned Miriam as your daughter. Yes, our son was a baby. And I remember we went out to a festival, was my favorite restaurant in Carl Gables. Oh God, it was good. And Barry knew about it. Anyhow, we went out to dinner. So we came back and there was no rooms. So Barry, well, spend the night with us. So he goes to our hotel room with us and we got two big beds in the Omni Hotel. And he lays over there and gets down to his striped undershorts and his T-shirt and he puts the baby up on his belly and gives him the bottle. Said, mm, ain't that good, Red, oh my, my. And he just feeds the baby. We laugh and talk. That's how close we were that we could all stay in a hotel room together. And would you say he's a good man? A wonderful man, a gentleman, Southern gentleman. Just looked after his mother, his family, everybody around him, everybody loved Barry. He just had a little smile on his face always. So you got arrested and then what happened to Barry? Well, Barry knew the people that unloaded, of course, he sent the cars down and all that. So he met the unloader, a guy named Lito, Luis Carlos Bustamante of Venezuela. And so he just kept on flying. But he, I believe, had three of my airplanes at $400,000 a piece and they owed me some money. Well, he collected a lot of that and gave Mari the money and put it in his safe and took her to his house and all after I got arrested, sent a lawyer in. He got me the best lawyer in the country, Albert Krieger. He was head of the defense team for all of America. Wonderful man. Can you tell the story of the months that led up to Barry's assassination? What did you know, what did you sense, what did you think? Okay, when I got out of prison, I hadn't been out long, I was eating breakfast and there was Ronald Reagan's face right in the television. We have absolute proof that the communist Sandinista government is into cocaine running business. And there was that fat lady, the C-126, on the runway with the billied in and I thought, oh God, he had done it. So I had heard that Barry might have been working with him. So it wasn't long before. Working with? With the DEA or whoever, he was no longer on our side. So can you clarify how you got that from the Reagan making a statement about, we've heard. Okay, there was his plane. There was Barry's plane and okay, on the way north, we could stop in Nicaragua and land on a military base or on a base that they used as crop dusters and all and refuel. Yeah. And so that shortened our trip, we go further into the jungle and come up and that was what Pablo Escobar and Ochoa and them, and they was associates with the people in Nicaragua. So Barry was, if that plane was there, that means Barry was feeding the DEA information. He was working with them at that time. But let me back up a little bit. When I was flying and I told Barry, we would refuel, and the train's airplane, the load's in Belize where I had a spot up there. And then that's when they told me we can refuel in Nicaragua and then you fly all the way in. Barry couldn't believe it. He says, all right, but I wanted to land, I had a place in Louisiana for $10,000 that I could unload and the sheriff and all of them was paid off. And he said, no, no, no. I can't get caught in Meena, Arkansas. I said, what do you mean you can't get caught in Meena, Arkansas? You get caught anywhere. He said, I can't. But it's gonna cost you $50,000 every time my wheels touch the ground. Why, can you explain why he can't get caught in Meena, Arkansas? He said he was hooked up with them at the very top. And he even said, I'm gonna have dinner with the governor tonight. That's at that time, Mr. Bill Clinton. Undoubtedly. And it's like, did Bill Clinton, did you give him any money? And I said, no, I never gave the man any money. But it was like the money that I had that went to Grand Cayman Islands. And I told my lawyer, I said, I never touched that money. He said, you don't have to fondle it to be guilty. So. I mean, there's a lot of conspiracy theories around the relationship between Barry Steele and the Clintons. Absolutely. What evidence do we have? What would you say from your best understanding of what was the relationship between Bill Clinton and Barry Steele? Barry said, and he knew that he couldn't get caught in Meena, Arkansas. And when that movie was gonna come out, be called Meena, somebody stopped it. I mean, they stopped it dead in the tracks for two or three years, and the producer even quit. You mean the American Made with Tom Cruise movie? It was American Made. It was gonna be called Meena? It's the name that was written and produced in Meena. And waiting on Hillary to be elected, they would not let that movie out. And that movie was changed drastically. But to push back on that, that doesn't mean there's truth there. That means they were worried about the power of the conspiracy theory, which stuck. Exactly. I mean, I don't know. I mean, some conspiracy theories, just because they're popular doesn't mean they're true. And ones that, but it also doesn't mean they're not true. And there's ones that are not very popular that could be true. But that one, that one really stuck. Did you, I mean, what's your sense? Well, I paid one and a half million dollars for Barry to land at Meena, Arkansas. So I was pretty well assured that he couldn't get caught. And I said, well, I can't get caught in Columbia. We can't get caught in Nicaragua. I guess we got a license. So we went for it. Oh, so when you say I can't get caught, just to clarify, there's a sense where this is a safe place to land. Yes, like completely safe. So you don't think he was referring to some kind of, you know, like my grandfather who fought in World War II would talk about bullets can't hit him. So it's almost like believing. He was taking that $50,000 and giving it to somebody. And Barry was honest, so he wasn't just taking it from me because he was making a million dollars and he didn't care for the 50,000. Oh, man, taking the story forward, the months leading up to his assassination, what do you understand? Why he was assassinated? Who were the players involved? Maybe could you have stopped it? Well, I'll tell you, after I saw Reagan's face on the television saying we have the absolute proof, the phone rang and it was Barry. I hadn't heard from him in a couple of years. He said, I'm coming out tonight, Roger. And oh, boy. So he came out and he said, I'll meet you in this French restaurant, I don't even know it in Santa Barbara. And I walked in, there's about 20 or 30 people in there. And he was all 30, 40 years old, women with plastic or leather skirts and men in their blue jeans. And I looked around and Barry was at the back. He was leaned up, he'd gained weight. And I walked up and I said, Barry, are you wired? He said, no. I said, well, I'm not gonna talk to these DE agents. He said, every one of them. So. With jeans and skirts, I like it. I said, well, Barry, I'm gonna sit you and you just talk to me, buddy, and tell me what's on your mind. And he sat there and he just went to talking and he told me about, he was left holding a bag. And that. What do you mean by that? Like that nobody's supported him? Well, I think that's some another. He was, and I don't know this. I mean, this is just what happened. Putting it all together that he had some CIA buddies that was pretending we're going to supply all over North with arms. And with that, you can land cocaine back here by the ton. So he's taking his little planes and putting some AK-47s and maybe ammunition or whatever, and takes it down to the country's against the Communist Party of Nicaragua, where we've been landing. And all over North was involved in this. So when all that, and so his CIA buddies was certainly involved, we know they were. And Barry had been in the CIA earlier when he first got out of school. So when, as I say, the shit hit the fan, they all fled and left Barry holding the bag. The CIA and the DEA. Yeah, not the DEA, the CIA. DEA wasn't in on it. CIA was selling that cocaine, bringing it in. Just to clarify, what's Iran-Contra scandal? What was the alleged involvement of the CIA in using drug trade to fund things? What do you know? What do you think is true? What should we know? Well, I know what I know is true, that Barry was taking a small amount of arms back to Central America and giving them to whoever Oliver North group were. Who is Oliver North? Oliver North was a colonel that got implemented and almost brought the government down. And so they said, all right, we're getting the guns from Iran and we're taking cocaine to pay for. And since Congress won't give us money to fight this war, we're gonna circumvent it. So that was a whole thing. So it was CIA's effort to circumvent the funding mechanisms of government by selling drugs. Yes, but it was a handful of renegade CIA agents, it was Barry's friends, that was making a load, a load of money, tons of it come up. If you would like to read the book, The Big White Lie, The CIA and the Crack Cocaine Epidemic, the CIA put, according to this, the book and Michael Levine, I didn't remember his name last time I talked, wrote that book and he was a head CIA agent, he was a head DEA agent that exposed this. And the CIA tried to kill him. And he says, they put crack cocaine, they developed their chemists developed crack. And they put it in every city in the United States on one weekend. So they were bringing it up by the tons and that's for sure. And Barry was bringing it. Can I ask you a small tangent question? Do you think the public should trust the CIA and the DEA? Do you think they're mostly good people that are carrying out a good mission? Yes. Because this kind of makes it sound like there's renegade agents, they're just doing whatever the hell they want. And with sometimes no regard for human life. Well, that's certainly true. But that's not everybody in there. That's just sometimes you get a few policemen in the department that do these things. I don't believe, I believe that our government is good. I think we got some fools running it. I don't know how we get them there, but I don't think I know. Okay, so what was Barry's involvement here? So Barry leaned back in that chair and he told me that he got caught with one and a half tons and he bellied it in the runway in Nicaragua and had cameras flashing inside and out. And he flew it back to Homestead with an agent there and he brought the agent over, Jake Jacobson. Really nice fellow, I think he was a crop duster. And we'd have got along if we'd have been on the right side. And so we sat there and drank Chevy's Regal until I got pie-eyed and Barry told me about it. He said that he went to see Edwin Meese. He got out on bail and he flew his Learjet up to Washington and went in to see the Attorney General, Edwin Meese. And they run him out of the office. The next day he went back and said, I have absolute proof that the CIA is bringing tons of cocaine, or they're running tons of cocaine into the United States. And Edwin Meese put him up with this agent, Jacobson, I believe it was. And they went down and got one and a half tons. And on the way back, they bellied it in and Pablo Escobar and some of the other ones, a general there in Nicaragua, you can see them toting it from one plane to the other. In the book called, The Big, no, Kings of Cocaine. It's got a mention of me too. And also the other one has a mention of me in it. Said I'm in more files for the DEA than Nariaga. So who was wanting to get rid of Barry? Is it the, who wanted to get rid of Barry more, the cartels or the CIA? The cartel. But so Barry leaned back and he told me the story. And the tears came down between his fingers as he put his hands over his eyes. And he said, I just couldn't do it, Roger. I just couldn't do three life sentences. So I've told him everything. I went to Congress and I've testified before Congress. He testified before Congress for all these things that he'd done. And he said, I told him all about you. But you're under my umbrella. You gotta testify with me before grand jury in Miami. And so the guy said, you can come down, the DEA agent said, you can come down tomorrow with Mari, first class, or I'll take you down in chains. And if you don't testify with Barry, the only place you'll ever see your wife and family again is in a federal prison visiting room. Was that a difficult conversation? Oh, my eyes, my guts was just like ice water. I can't testify against my friends. I just can't do it. How am I going to do it? I just, I can't work with people. And he was honest with me. How am I gonna testify against them? I can't spend the rest of my life in a federal prison. What on earth, what a mess, Barry, you've got me into. So. Is that a kind of betrayal there? Yes, but it's still, I wish he'd left me out of it. I understand him getting in such a mess that he told because if the CIA and whoever else was behind him betrayed him, then he's gonna tell everything. So I says, all right, I'll be in Miami. So Mari and I flew down first class. And I went to a lawyer, one of the biggest lawyers in Miami. And I said, man, I am in a mess. This fellow's told everything and I've got to say something. But I'm not a snitch, man. I mean, what can I do? And he said, well, being a snitch is like being pregnant. You either are or you're not. And he says, I don't represent snitches, but if you want to fight this case, I'll do it for $600,000. And boy, my face turned red. Well, I'm not a snitch. He said, well, that's what you're talking about. He said, let me tell you something. If you go in there and say one thing and sign that paper and you don't tell them everything you know, then they will convict you of everything you've ever done and you tell them. So you can't do it. So I said, Barry, I'm having trouble with a lawyer. Give it, I'll go tomorrow, let's go. He said, all right, use my lawyer. And he gave me his card, the lawyer's card. So Mari and I went to the festival restaurant that night and Barry and Debbie came in. She was dressed pretty and Barry wasn't. So we was already about finished. So we had dessert together. And I said, Barry, they're gonna kill you, friend. He said, no, they ain't gonna kill me. So and so, such and such is gone. And this and the other. I said, Barry, they're gonna kill you, man. They know, you can't deny it. And I said, I didn't tell him I wasn't gonna testify. So I hugged his neck. I really, like, and we fled to Brazil. I took Mari and the children and went to Brazil. So you decided there you're not going to stay. On you, I didn't know what I could do. I talked to a lawyer. I mean, I just didn't, I didn't know what I could do. But the best in Miami said what he told me. So I had to go. And you went to Brazil. We went to Brazil. Did you have a conversation with anybody at the cartel? I mean, that's such an interesting moment that tests the man's character to not snitch. And did you have a conversation with anybody? No. Pablo with, about it? No, not at all. So it's just understood. I just didn't, couldn't do it. But how many men like you are there? Not many. I had all my friends testified against me. I had 11 friends and every one of them put their finger up. Roger did it. And I was facing life, continuing criminal enterprise. And still you couldn't do it? I just couldn't do it. Do you ever get respect from the cartels for that? From the people in the cartel? Oh, there was a time I got back and stuff. They owe me money and I can't get it. So. Well, that's about money. I just mean about human beings. Oh, I think so. I mean, I've been back down there and I've been welcomed. I have my contact. And when I was in Brazil, I was trying to get this money. They owe me three and a half million dollars. So I called up there and he was gonna pay me. Oh, I got 600,000 today and I'll get you some more tomorrow. And then the next week I called, hey, I got great news, great news. Barry Seal's been killed. So, oh no. And I went back to the hotel. We was up in Northern part of Brazil. And where was it, Maddy? Yeah. And so I went back and I told Mari and Miriam and they cried and I cried. I really cried. How's that great news from the cartel perspective? Well, now there's no case against me and him and them. Do you know who killed him? Yes. I'll tell you about that story. On the first load I did, I landed at a banana plantation and it was raining and it was a muddy strip, clay. And they put the 300 kilos of cocaine and then the ugliest man you can imagine, named Ronaldo, got in there with a Mac-10 and he would make sure I took it to Louisiana. Mm-hmm. So. This is many years before. Yeah, a couple of years before. So anyway, we took off and the mud got up in the wheel well so thick until the wheels wouldn't come up. Well, I'm going 200 miles an hour instead of 300 miles an hour with wheels coming down. Well, I can't go back there. If I do, I'm gonna be in the same situation until the sun dries it out in a few days. And so, but in Belize, I had a runway that had been used for $10,000, used to refuel. So I told the guy, listen, we got to land in Belize to refuel. And no, no, no, he put the Mac-10 and I'll shoot you. Go ahead, fool, you're gonna die too. So, I was in the turf. He wasn't just ugly, he was also angry. He was a bad, bad killer. Yeah. And so, he's the one to actually kill Barry. The one that went up on the first load with me. And Ronaldo, and he's doing life. I think he's just a killer. Yeah, he's doing life in Louisiana. I wonder who, is it known who made that decision? The younger Ochoa brother, I understand, Favio was the one paid for the hit. I don't know that, but that's what I've heard and it probably sounds about right. He's down in Jessup, Georgia, doing a long, long time. I think he's about to get out. He's been in 30 years or whatever. The movie American Made, what do you think that movie got right? What did it get wrong? Almost everything wrong. It was disgustingly wrong. Okay, which parts? Can you maybe elaborate? It's about Barry Seal and it just didn't even, it was nothing, whoever wrote it had no idea who Barry Seal was. They sat in a rocking chair and just tried to think of what was some baby bashing drug dealer doing? And it's just like, God, you just don't have any idea of the spirit of the man. So they wanted to try to tell a fun story without actually studying the story. They didn't know him, they just had no idea. And Barry was such a nice person, such a really nice gentleman person. They talked to you or no? No, they didn't talk to me at all. I see all these people telling about Barry and never met him. They tell them all about him. I think that's just ridiculous. For one thing, for his character coming out of whore houses and all that, that was just like ugly. And then down in Columbia, putting a gun to his head, gonna take his sunglasses and then he put $25,000, million dollar worth of cocaine on his plane. And then they're gonna bet $100 that he don't have enough room to take off. That's just insane. I mean, just the whole thing. And then he's talking to the DEA agents when he's coming up. You don't know what frequency they own, how he's got five planes and they all split when the DEA comes out. These are just somebody's just fantasy. They probably been doing it. But those are like, those are details of the man, details of the story. Is there some big profound things they missed about just this whole period? About that's something that's really important to you that was missed? Yes, they just tried to sensationalize on little things that people remember. And it's just not true. It was just like a business deal and good people and good airplanes and good flying. And it was like a good watch that was made. It just clicked and it just went on. And they missed all that. They tried to make it sound like it's something very ugly. Do you think it was a story that could have been told way better and still be a hell of a good story? Goodness yes. Well, there's a series called Chernobyl done by HBO. And because I have sort of family connected to that period, they did an incredible job of being historically accurate and only not being historically accurate when it helped the story, only in those rare cases. When they on purpose left the story to make it easier for people to understand, but it was still somehow accurate. And even though all the actors were British actors speaking English with a British accent, it was still somehow accurate. Like they captured the spirit. So it was historically accurate and the spirit was captured. That was one of the most incredible series I've ever seen. It convinced me that the movie was made by non-Russians. It convinced me that if you really care about a story, you don't have to have been brought up in it. You don't even need to speak the language. If you're truly a scholar of it, if you talk to a lot of people, if you learn, if you just pour your heart and soul into it, you can create something really special. And so your sense is you could do that with the story with this period of time. Oh yes, it was a story that needs to be told. It need to be told in the correct way, not like we're trying to bash a certain angle. Yeah, well, if Netflix or HBO are watching this, you need to tell the story of Roger Reeves, in my opinion. There you go. Is this young picture of you? Yeah. There you go. That's from National Geographic. Jorge Arcoa, Pablo Escobar, it's you, Roger and Barry. Yeah. Smuggler, a memoir. Yeah, I really do hope that they make a movie of this one. There's a movie called Blow that tells the story of George Young, Boston George. Did you know George Young? That's one way to ask it. The other is what do you think of the movie Blow? I didn't know George Young, but it was a wonderful movie. Absolutely, it captured it. It did? Yes, it did. That's the way it should be. So he was a little bit before your time? Exactly the same time. Exactly the same time. He was using stewardesses to fly the marijuana out of Manhattan Beach. And I was on the fire department in Redondo Beach, 10 miles away, flying it up, sending it back. Somebody was sending it back. He might've been sending it back. But he didn't have near the excitement that I did. I was shot down twice. I escaped from five different prisons. Yeah. I was tortured almost to death in a Mexican prison. So he didn't have all that fun that I had. Fun in quotes. Yeah, so yours is a heck of a fun adventure. Just to linger on a little bit. So Johnny Depp plays George and Ray Liotta plays his father. And there's this son-father kind of scene at the end. I don't know. It's heartbreaking. Like that scene paints a picture of a life that could have been had if none of this wild drug smuggling happened. I don't usually, I mean, I don't almost, I really never get like teary eyed in a movie, but that got me. It's almost like confronting at the end of your life, what your life could have been with your father. The way he calls him Georgie. It, like you fucked up Georgie. Yes, I did too. I really, really did. Mario waited for me all those years and the children raised them without me. Visited me in prisons all over the world. It's unbelievable. It's just, nothing's worth that kind of money. Yeah. Can you tell the story of when you were tortured nearly to death in a Mexican prison? I sure can and I'm smiling, but it was nothing to smile about, I can tell you. I was in a pool and a gentleman came over and shook hands with me and put handcuffs on me. And I thought, what in the world? That was one of the nice hotels. They put me in a jail cell and I sat there and all the trunks and thieves and stuff kept coming in and they had a bucket and it overrun. And I said, I remember, like 18 people in a room, about 12 foot square. Oh, it was hot and I thought, somebody's gotta come get me. This ain't real. I hadn't done anything. It's like, it was a pilot come to see me up in Hermosillo and he stopped and he made a mistake and went to the International Runway instead of where he was supposed to go. And he had my phony name in his pocket, so they got me. So they said I was a drug smuggler. So after about three days, they put me back into the back and it was a torture place. And they put me in a little cell, like I guess it wasn't hard, it wasn't six feet, must have been about five feet square and about 12 feet high. And it was June, the end of June, and it was hot. I mean hot. And they left me in there for, I guess, a few days. You didn't know. So every once in a while, they'd come drag me out and first off, they'd put my head underwater and it had seltzer in it of some kind. And I took one whiff of that and three or four of them couldn't hold me down. So then I learned that just before you have to breathe, tear loose like that and they'll let you up. And that was the first treatment. And then they started beating me. And they beat me with a blackjack and rubber hose until I was black and blue and yellow from the bottom of my feet to my head. What did they want from you? They wanted me to sign a confession that I was a drug smuggler. And they put the papers under your nose. This is all over if you'll sign. Well, I knew if you signed, you got six years. I wasn't gonna sign. I wasn't gonna sign. So they didn't want you to snitch on anybody. They just wanted to say. No, they just wanted me to sign that paper. And you still didn't. And I didn't bow to them. I beat Nate that bad. So anyhow, he's getting into the good part. So then they come and they take me out. I'm buck naked and they bend me over and they have things to pull you, like chains, click, click, click, click, click. And they bent me over and they put butter on my bum and they commenced to put hot chili pepper up there. And that stuff was bad. I mean, it was red hot. And that was awful. And still. That was just awful. Yeah, but still you didn't. I didn't think about it. I ain't gonna, I guess if I'd have known he was gonna kill me, I wouldn't have done it. But I wasn't about, you get hurt bad enough, you'll pass out. So I didn't pass out. So I was all right. So then the last thing they did was they brought a dead man in there and he was frozen. He was wrapped in newspaper, little strips, about a half inch wide, just like a mummy. And he was frozen. And they hung him on the wall with a meat hook. And, you next, son of a bitch, you next. And so he's sitting there like this and as he starts to thaw out, which is pretty quick, it looks like he's crying. And it looks like he's peeing. And the paper starts unraveling on him and the formaldehyde puddles on the floor. Hoo hoo, what a smell, that rotten insides and the formaldehyde. And there was a little space, it wasn't even a half inch high, under the door. And I lay on that filthy floor with my cheek and put my lips right up under that door and was sucking that fresh air. And I went to sleep after some time. And I know where Walt Disney gets his ideas. I saw white, pink pigs with wings on them, all kinds of stuff flying around. So when I woke up, I didn't know which was real and which was the nightmare. It took me a minute to figure out where I was and what was going on. How did you stay mentally strong through that time? I don't know that I did. I was, yeah, I was mentally strong. So I was, just like I am now. Stubborn. I mean, you could be that man. They could have killed you. Yes, they could have. So what gave you hope? Did you have hope? Yeah. Or you were just a stubborn son of a bitch? I think some of both of it. And I think, they aren't gonna keep you here forever. You know, you're gonna get out into the prison or they're gonna let you go or something. And if you sign that paper, you ain't going nowhere. And I wanna go home. I'd got shot down a few weeks before that. I got shot from out the sky. 80 bullets, I was through the plane, killed a fellow on the ground, shot the leg nearly off the man. Where was this? In that little place of Picciolini. And they were shooting you from the ground? Yeah, yeah. All right, a little 900 foot strip there at Picciolini, a poor, poor village with starving donkeys. And that's where I'd give them $17,000 for the load. And I'd go over on the highway and load. Well, on day 13, I did a load every day for 13 days. They had a bunch of marijuana, pretty good piled up, and I was going to load a day. And on day 13, I had that little warning sign going off in my stomach, uh-oh, uh-oh, don't do it. But I asked this Joaquin, oh, we had the Federales paid off nowhere we were. So I spent the night in a hammock and walked down to the airplane just as it getting daylight. And 10 or 12 men walked with me and Pedro got in. I brushed my teeth in the little stream, it was about foot deep, a little river coming through there. Got in the airplane and I fired her up, bam, blah, blah. And bam, I thought a tire blew out. I looked over and see if it was, and it still ain't dawned on me. And Pedro's yelling, please see ya, please see ya, Roger, please see ya. Well, it dawned on me and I shoved it, the throttle to the firewall. And I only had- So that was a bullet. Yeah, somebody, they was off to the sides, they'd shot, they'd shot just a warning, like get out, stop, we're gonna rob you, whatever it is. That's what they do. They'd taken the plane and me and put me in prison, the whole thing, but even though I had papers. So I just shoved it to the firewall and there wasn't enough room to take off on that strip. And half of it was behind me, or some of it was behind me. And so just at the end, I'm just like, I think that thing stalls at about 50 miles an hour, just turning 50 and I just pulled it right up and put the flaps on. And as I pulled off the ground, they opened up on both sides of me with machine guns and they riddled that airplane. I mean, the windshield came out, I got hit three times. You, like your body? Yeah. And I didn't know I was hit. I mean, it was just the gasoline- The adrenaline. The gasoline just pouring in, the world turned yellow. I must've went into shock. So it just stopped in slow motion. And one bullet hit the strut right by my head and it just, parts of that bullet just went all over me. I just looked like I'd been peppered with lead and the gasoline was just pouring in. I mean, just pouring in where they'd shot the wing up above and the windshield's gone. I mean, I can't, it's just like a hail storm. So I- Did the airplanes stall or no? I was in a stall anyway and I didn't realize it. And I guess you wouldn't unless you trained for it. But when you're in a stall, the elevator is kind of flappy. And I didn't realize it at the time. I thought they had shot the elevator cable in too. So I thought, oh God. So I just reached over and switched it off, switched the pool, the mixture pool, everything. And in the river, there was rocks about as big as this table. And they were like the turtle back, all the way up until there was a waterfall. There was quite a pretty place. And I crashed straight onto it. I thought if I hit those rocks. And when I did, the first time I hit, the wings came off. And then it bounced. And the next time the nose came up and came under the plane. And I'm sitting there, I must have been knocked unconscious. Because Pedro's shaking me, come on, Roger. Come on, Roger. So I stepped out into the water. And here comes these four Federales still shooting at us. And I'm bullied to hit the airplane. And I kept a 9 millimeter Browning high power taped to the top of the radio in case I ever needed it. So because you didn't want it in the airplane. So it was just handy. You just lay in there. So I took and popped a few caps out of them. And they ran into the rocks. So we took off running. And then I looked, and Pedro's foot nearly shot off. They'd shot him on one side of the ankle. And it just blown out the other side. And it wasn't even hardly bleeding, the shock of it. So I took my t-shirt off and gripped it and tied it best I could. But you had still bullets in you. So you could still run. I shot the top of my toenail off. I shot it across my head and my kneecap. So I was just nicked. It was very painful later on. But right that time, it was just hot. And there was a bullet still in my foot from it, a piece of a bullet, a good-sized slug. So we went on up the mountain through the cactus. And just running. Just going, I want to go down. No, no, they all fed her all as they go in the easy way. Let's go. This young fellow. And we came to an old donkey. She must have been 30 years old, long and way back, long hair on her. Charlatte, Charlatte. And he petted the donkey, and we jumped on. And we rode for seven. Like an actual donkey? A donkey. There were donkeys all over the place. He knew that one from the village. And so we rode seven miles, two of us on a donkey with no bridle, no saddle, nothing. And we came to a little man plowing a little horse and a little ox. Both of them spotted. The ox was, the yoke was across her back this way, and he's plowing with a little plow amongst stumps. It was like one of these people clearing a little piece of land. And he had a little house there. And so we went into his house, and his wife and his daughter, they put like cloth over my wounds and on Pedro's. It was terrible. And they poured diesel oil on it to keep the flies off. So I'm covered in diesel. So the man left, and he was gone all day. And then about dark, he showed up, about 15 or 20 horses and mules showed up in the yard, walking fast. And a doctor got out. He said, I'm Dr. Benjamin Soso with Red Cross. And he worked on my foot, and he worked on Pedro. He gave us a shot of morphine and tetanus shots. And he said, you've got to get to hospital. He said, Pedro will die if he don't get to hospital. He said, they're looking for an American pilot that's been shot down. They think he's dead. There was a lot of blood in that airplane. And so they rode, I don't know how far we rode, but we rode miles. And we'd come to a road, and there was a big truck. It was loaded with corn in the ear. And they dug holes in that corn, put us in it, and covered us up. And the road was rough. And every time we'd hit a dirt road, that corn would cover me up, and they'd scratch my face out again. And when we came to the highway, we went into a house, and they got me some clothes. And mine was messed up. And a white basin, and they must have brought 20 jugs of water different times. I kept washing and washing my foot till all the blood and the crud got off of me, and put on those clothes. And somebody went to, they said, you can't go north of Rhodes Block. They're looking for the pilot. So you got to go south. So they found a taxi in Mazatlan. And it was a rather new taxi, and the fellow would take me to Guadalajara, which was, I don't know, seven, eight hours south. So we got in that taxi, and they propped me up with sheets and blankets and pillows in the back seat, and gave me these great big white pain pills. And I was quite content. Then I was shot down in Columbia also. What, can you tell that story? I sure can. All right, I went down for a load of marijuana. And we got to the place, and we got there too early, and the guerrillas screamed, you got to get out of here, got to get out of here. And so we went back to the place where we staged from, and refueled. I had a beautiful DC-3, carry three tons. And so while I was waiting, I ate something for lunch, and I went around behind the house. We refueled the plane up. I had to wait till late in the afternoon. They wanted me to come just at dark, so the military planes couldn't see me on their strip. So I'm laying in the hammock asleep, and I hear this terrible roar. And I look right up through the trees, and at the ass end of two military jets going straight up. They do a dive over, and they came back down the strip, in front of that airplane, and they just tear it up with 50 caliber machine guns. They just showing out. So I run for the airplane. I just give that guy $80,000, and he ran for the truck, and all the rest of them ran for the truck. I should have ran with my money. But I didn't, I ran for the airplane. And the co-pilot got in, and the name was Al. He got in with me, and two fellas got in the back. We had drums of fuel in there to refuel when we got down to the guerrillas. So we took off. And I couldn't get the gear up, because I'd taken off in such a hurry. These pins in the struts of a DC-3, and with big flags on them, and you have to take them up, so that the plane won't come up. So these jets swarmed on me, and they tried to get me to go. They kept telling me which way to go. And the pilot would be just as close as, just right over there. I could see him. I just held up the old hippie piece. I didn't think they would shoot. I really didn't. Nobody had shot before. So I kept flying out, and I kept getting slower and slower, and they kept slowing down, down, down, and the black smoke rolling. And then they started shooting up under me. Boom, boom, boom, boom, with them 20 millimeter cannons. And the tracers just going up. They looked like they're curving up from me. And I, whoa, and I pushed the nose over, so they couldn't get under me. And later on, I heard they thought I tried to ram them. So one of them went for fuel, and I kept on going, and the one just tore the left wing tip up with a 50 caliber. And then he come back again and shot the tail up. He's warning me. And I tell the fellow in there, I says, you know, if you bring me enough water, I believe I can fly this thing. My mouth got quite dry. So I went on, and I landed on a big pasture. And it was a huge pasture, and it was rougher than it looked, and the wings just flapped. And I come to a stop and jumped out and pull those tabs out, threw them on the ground, so I could get my gear up. And I understand that during the 1980 World Series baseball game, that it says, American DC-3 has just been shot down by American jets, by Columbian jets. You know, it's the first plane shot down on Reagan's new war on drugs. But he's up, he's up and away, ladies and gentlemen. We keep you posted. So I took off again, and I went into a thunderstorm, and they came close to the mountains. So I spiraled up, and every time I'd come out, that jet was there, boom, boom, boom. And I dove back into that storm, and it boom, boom, boom in there. And at 20,000 feet, I started icing up. So I went out one last time, and he was right there waiting. He had me on radar. So I went back in, and I kicked it over and put it into a spin and went straight down to 2,000 feet and come out under it. And I was flying along the Guaviera River, and it was 20 feet above the water. It looked like a pasture. It was just grass. And I made several runs to tear the grass down, and it looked like, and it felt hard. That old DC-3 weighs 30,000 pounds. And I put it down on the fifth run. I said, all right, we're gonna land now. And as I was- So you flew close several times? I put the wheels down. Oh, you put the wheels down without landing. And about half a mile, and just, so I'm making one run, you know. So you, okay. So you're being tracked by a jet. He's going. He's trying to, well, before that, I'll just try retelling this story how insane it is. He's trying to shoot you down, and there's a thunderstorm that you're escaping into. And then you do a spin down to, what, 2,000 feet, whatever you said, like somehow escaping all of this. And then you try to land on a pasture on a giant heavy plane that carries three tons by touching down five or six times to make a landing strip for yourself. Yeah, the grass is three or four feet high. So it looked really good after a few times. So then just before it stopped, I said, Al, take your feet off the brakes. He said, I don't have my feet on the brakes. Well, I knew I had broken through the crust. And I put full power on, but it didn't. That old big plane just come on down, and it just did a head, as it came to a stop, it did a headstand, 90 degrees to the ground. And the engines held it up, and the nose and all just crushed in right on it. We fell between the two seats to keep from getting killed. Wow. And when it come to a stop, all that fuel was pouring out on those hot engines. And there's a escape hatch at the top. I just stepped out, took my suitcase with me. Did it, was there fire? No fire. The plane left the plane there, and the two guys that was in the back one of them broke his thumb, and it was with the barrels. And they had to put a hose, a tie gas hose together to shimmy down to get out. Yeah. So, that's an incredible story. Well, let me just tell you, it had a little bit more to it. I learned to fly with the idea of being a missionary aviation fellowship pilot. Fly the missionaries in and out of the jungle. Yes. Well, I went 11 days through that jungle. The rest of them went on down the road and went to prison. I said, I'll crawl on my belly six months in here a year, eating snakes before I'm going down the road. So I went in there, and I was 11 days in the jungle. And I finally came to a place, and it had airplanes. I kept asking the Indian, don't this die avions? I wanted to steal an airplane and get out of there. And when I came to the place, I asked, what is this place, lovely place. It looked like Honolulu in World War II. There was a runway there. Said, you don't know, this is Loma Linda headquarters for missionary aviation fellowship for the Amazon. And they flew me out. Wow. You escaped from prison five times? So what stands out to you as the most difficult or miraculous escape in the bunch? The most black miraculous was when I was in the courtroom in Spain. I think I was on the third floor of Real High, and I ran across the courtroom, handcuffed, kicked the window out. And I looked down, and it was above the palm trees. I thought there might be a power line or something I could grab on as I went down. There was nothing. And there was a car parked, a station wagon on the- You just jumped out? I jumped out from 31 feet and on top of that car. And it exploded in the street. The windshield went over three or four cars. It looked like snow going up. And I looked like Donald Duck with a thing and handcuffs, and I got out. And you just kept running? Yeah, I kept running. They ran me down to and hit me in the back. I still got a dead spot in my back where the policeman hit me with a shotgun. And they brought me back. Mario was there. They were saying, your husband is crazy. That was spectacular. But I escaped from Lubeck, maximum security prison. And I cut out of there and got out. That was a miraculous escape. And that was where? In Lubeck, Germany. What was that escape like? I was there, and they were going to extradite me back to the United States where I still had all these charges and 25 years special parole. And I was cleaning the lawyer's visiting room. And on it was bars that looked like piano notes or this way to make it pretty, but they was a little bit, so I got a rope from a guy where they made boats in there. And I had 20 minutes. So I went in there and I wrapped it around and I put a broom handle in it. It was cut off and wrapped it around until they pulled the bars together on that side. And then I pulled them together on the other side. But that only put me inside the prison yard where the soccer equipment was kept. But they were putting new windows on one side of the prison, and they had it scaffold up to the fourth floor. So there was a little recess there and there was guard towers every 100 feet or so. I mean, they would shoot and kill you. So I got behind that and climbed up, holding to the bricks on one hand and the scaffolding on the other, and went to the roof. I lost my shirt and most of my clothes going through the window. I got all the skin off of me. I thought I was gonna die. And I was trying to go sideways like this. And finally I got a grip and the bars let me through and took all the skin off of me. So I got up on that roof and I have asthma and I just lay there trying to catch my breath. Didn't bring my inhaler. So- With blood everywhere. Oh, I was bloody, yes. And so I got down to the end and on the end, the reason I did it, they was putting a new wall again around the prison to make it larger. And they had taken all the wire off above the sally port where they could join the two walls together. And I saw that when I came up. And there was a guard, a half of a, like a dome sticking out of that brick building where there's a guard there with a gun and he'd kill you. And I mean, he was made, he was surely trained to kill you. And we had some bad people in that place. So I lay up one floor above it and I saw a guard and his wife come with a double umbrella. It was just pouring down the rain. Here I am without a shirt on, bloody. And she had a little boy with them under that double umbrella. And I knew him and when he come, and she started back from the sally port, I hit the top of that guard tower, bam, with both feet. And I jumped, I guess, it's three more floors. I jumped, there was a pile of sand, like a cone where they were digging it there. And I hit that and my feet buried up to the knees, but I didn't fall. And I ran straight towards her so he couldn't shoot me. And then I went around some bushes and went downhill. And then I heard, bam, bam, bam, bam, bam, behind me and I looked and that fool woman was in a big old car and she was knocking down the parking meters behind me. She was trying to run over me. And I ran behind a car. And she tore the fender off of her car, trying and yelling, yapping, yapping, yapping, a terrible evil looking face at me, screaming at me. And the sirens going off in the prison. And there was a fence there, a wall. And I jumped up on it to jump over and it had glass embedded. And I cut my hands and my arms all up getting over that. And I hit the ground on the other side and it was like, it was that much muck where some farmer had dug it. I dug in there and Mario had slipped me $200 into prison and I had that in my shoe and I lost my shoes in that muck. Anyway, I got out of there and got to Holland. Really heck of a story how I did that. What was prison like, whether it's Germany or whether it's Australia? What were some of the darker moments in prison? The United States prisons are awful, awful evil places now. It just really, there's nothing nice about them. There's the guards. In LA. And everyone I went to. It seemed like the further east. I went to Oklahoma and it was nicer. But all of them on the West Coast, they was hatred there. And they got really stupid people hired, just incredibly. A hatred by the guards. And the inmates. Like I speak Spanish and I walked in to the Spanish TV room and it would send you a note, you can't come in here. And I walked across to the black, hey, get out of here. White boy, it was just like, what? Man, I like all you people. And so I walked down to the white people and said, show us your paperwork. You can't come in here until you show your paperwork. We don't let snitches and homosexuals and all this sort of stuff in here. So they have, so it's just like, man, I don't wanna be in here. I mean, it sounds absurd, but you're saying like the basic humanity is gone. Completely, completely. And the guards, it was just like, come here, Reeves. And I woke up to him, get the fuck out of my face. He sticks his chin out like for me to break his jaw. Yeah. Like, what in the world, man? I love people and it just- Yeah, you got this joy to you. Yeah. You have a joyful nature. And it didn't seem like that broke you. Not a bit. How did you persevere? Did you know, I didn't even think I persevered, but I try to enjoy my life wherever I am every day. I do. I ran every day. And like I told you, why do you run so, Roger? I said, to help me suffer these fools. And I played a game of chess every day, almost of my life in there. And I read two books a week. And I talk with people, storytellers, guys would come in and tell us another story, Roger. Give us a poem. Tell us one you never told us before. And so it was just nice. A lot of them have original boys. They picked their country music and it was all right. Read Morgan Freeman's character in the Shawshank Redemption. Says the following, these walls are funny. First you hate them, then you get used to them. Enough time passes you get, so you depend on them. That's institutionalized. Is there truth to that? 100%. I can't even see the walls, except whenever I was planning on escaping. In Shawshank Redemption, he spent so many years in prison that he almost didn't know what to do with himself once he left, once he was a free man. That's the, you get so used to the system, the rituals, having to follow orders, even being treated poorly, all those kinds of things that you become dependent on. Well, down in Australia, I spent the first a little over a year in the shoe. It was like, did you see the movie, The Silence of the Lambs? Thank you, Marty. And he's there, I had five or six guards looking at me with a one-way mirror. And that's whenever I thought I might never get out. I got a life sentence. I had all this time waiting here in Germany. And so, they had a computer in there, but it didn't have a program on it. And I wrote, so I just started writing these little stories that's what I did in my life. And I wrote one line and I wrote over a million words with them looking at me. So it was after a year, they let me out. It wasn't long before they put me in a place called self-care. And particularly, I was in what they call the lifers pod. There was 268 men in self-care there. And it was unbelievably good that we were left alone, basically, they was there, or the guards were certainly there, but they had their shack and we had apartments, four apartments to the building. And six men to the unit with your own door and a key to it and a kitchen, dining room, freezer, refrigerator. And they gave you, allowed you $360 a week to buy groceries. And I cooked for about 16 years and learned to cook good. And the people, and other people have their specialties. And so that was quite, it wasn't so like being in prison. It was somewhat living with me and it was difficult, man. I had some good fights and carry on. You don't get along with everybody. But then whenever I came back to the United States, I was laughing and talking. And when I got off the plane in LA, I had three marshals with me from Australia. I was slammed upside the wall, I mean hard, put my ankle, my ankle so tight till they cut my leg off. Face forward, face forward, lens apart. Good gracious. And walked me 50 steps and turned me over to the marshals and they took part of that off. That was a border patrol that was there over my marijuana charge from 1977. I did 11 years for parole violation. Now they want me for more violation. And they put me in, down in Los Angeles, they put me in, the marshals put me in there and they put me in isolation. I thought, what in the world they got me for isolation for? I done anything. How long did you spend in isolation? More than six months. So I, after three or four days, as the little Judas window slide open and a man, a nice looking man in a suit come there, hello Reeves, I wanna, just wanna see what you look like. I saw your National Geographic documentary and it does me pleasure to keep you in isolation. And he slammed the thing and I couldn't get out of there. And by law, the US Parole Commission is supposed to give you a hearing within 90 days. So I'm already paid a lawyer $7,500 and he never picked up the phone. Somebody got to him. Who's that somebody you think? Christopher Cannon was his name and I don't know who got to him, but he didn't do anything to get me out of there. I got one 15 minute phone call a month and I couldn't get out. So then after six months, they shipped me to, put me on Con Air. Double shackled and black box on my hands. And I went to Oklahoma and they let me out on the floor. I couldn't imagine, then I could call after a couple of days and they said, there was a man here from Washington give you a parole hearing, you only got here at 3.30. So he left, he said he'd be back next year. What? I've been in there over six months. So then there was a lovely little lady, she was a case manager or something. She said, you can ask for parole on the record. And I said, please do. So I sent them an email and the next day I got my parole. 90 days later, they sent me to Terminal Island and put me in the place there with the infilade, I guess, as old as I am, 78 years old. So they put me in people in there dying and wheelchairs and legs off and arms off and cancer. So I was in there and I pushed the fellows around. And I come out of the chow hall there and I went to go to the right to get me a haircut. And two Mexican guys there, a lieutenant and other one, walk between us and he went like the boop, boop, boop. And I said, I could outrun you. And they slammed me, put me on the ground, handcuffed me and put me in the shoe for a week. I got out and man, they put me in the back in the place. They treated me rough. So I got in a little more trouble and they put me back in the shoe and I wouldn't come out. They had that, the virus was out killing people. So they killed eight people in that unit I was in. Oh wow. So I mean, I wouldn't even come out to take a shower. I had a little straw that I put in the sink and I'd take a sock that I had and scrub myself with it with some soap and glass of water over my head and then clean the floor up and put it in the toilet. So that was your time during the coronavirus pandemic? I got out last April, right in the middle of it and they were dying bad in there. So I was treated worse for that last year in America than I was for the whole 20 years in Australia, the 18 years in Australia. And then you were a free man at the end of that year. They put me out and sent me home and the parole officers couldn't even come. They weren't working. They were just doing everything by video. Said, better not have a drink. The only thing was I couldn't even have a drink of wine. So after a year, I had to take psychiatric treatment. Every week I had to go talk to the psychiatrist, psychologist and me and her got along great. She was a good Christian woman. We just chatted and talked. Nothing, they said. So I had to pee in the bottle every week. I said, I've been in 33 years. How many piss deaths do you think I've had? Never been dirty. Only thing if y'all want a clean one, you come get me. Before I talk to you about love, let me ask you a difficult question. You write in your book, I don't consider myself much of a criminal. I don't lie, cheat or steal. And I always take up for the underdog. Violence makes me sick. Yet I know I'm an outlaw and those that break the law must be punished. I think many people listening to this or some people listening to this will see you as a criminal, as a bad man who increased the amount of suffering in this world. What do you have to say to them? I would like to tell them that they have been indoctrinated by the spin of news and politicians and they don't know the truth of the situation. You lay the truth out there in an envelope and let me open it. Besides something else that is false and it's staggering. The truth is that I was a tobacco farmer and tobacco kills 500,000 people a year in America and six million have debilitating diseases because of it. Drugs, all drugs combined kill between 10 and 15,000 people a year by overdose and 60% of those are pharmaceutical. Now then when I was a tobacco farmer, come sit on the front pew Mr. Reeves, come on up here you a gentleman. You just joined the Masonic Lodge and you joined our church and you just come on and sit down with the good people. You grow two marijuana plants, get out of here you scumbag and the marijuana doesn't hurt anybody. It's just, that's the truth of it. And so in your career, you walked amidst violence but you never participated in the violence. I didn't even see it. It just didn't happen around me. In prison it did. I sewed people up, they called me doc. I had dental floss and one time I had to get a blade and try to help keep them from my patient, from getting again. But I was just, like if I shot at those people, I shot at them to keep them from killing me. I certainly didn't mean to kill them. So that's just, some people are evil and they will kill you and hurt you, lie to you. I just don't do any of that. It just makes you sick. I've seen it, when I was in the shoe, three guys tried to kill a guy and they stabbed him so many times but their stab went breaking and the blood getting out of the room. I said, you're gonna kill him, you're gonna kill him. It saved his life, drug him up there where the guards could see him. There's stuff like that, I'm just not of that nature of those people, they're just evil. They're people born evil, I believe. Yeah, it is heartbreaking to hear that the basic humanity is gone in prison in the United States. That's heartbreaking because that basic humanity is actually the light at the end of the tunnel. It's the thing that saves us as opposed to when it's absent, it's the thing that destroys us. The prisons are filled, absolutely filled with people that have some mental problems. Now, you see Tent City all the way up and down here, I guarantee you, every one of those people have mental problems, some degree, however little it is, but they're a little bit off. Now, then you get a DEA agent that wants to make a name for himself. He goes down there and gets two of them, one of them to sell a little two grams of methamphetamine to the other one and he gets a conviction. And a young prosecutor, he gets a conviction, he wants to make a judge. And we got to judging, where was it? I'm gonna give a million, what was his name, Gilbert. I'm gonna give men a million years before I get off the judge. You get fools like that in charge, you're gonna fill prisons up with pitiful humanity. And those are the ones. And then the other is people over drugs. And drugs should be a health issue. You cannot police it enough. It's just, they know the only thing that overdoses is opioids, the heroin. And if they can give it to them, it costs about a dollar a day to give the worst addict his fix. But they'll give it methadone, which is from a pharmaceutical company, which is just as bad. Why in the world? We tried it all over the world, in Portugal and England. And when they give the girls clean up, no more stolen cars. Why, who wants to keep this farce going? They just perpetuating it. Like, oh, every little police place is getting all these suits and armor and machine guns. It's just like, oh, it's such a spin, it's sad. Do you think all drugs should be legalized? I don't know about that, but they certainly should be controlled. If a person is an addict, he should be able to go down and get his fix with somebody there to help him with a clean needle and a glass of orange juice. It's so much cheaper than prison. It's so much cheaper than him stealing cars or prostitute having to go to work. That's sad. You've lived one heck of a life. Looking back, there's a lot of young people that listen to this, high school, college students. What advice would you give them? How to live, how to have a successful career, how to have a good life, how to be a good man or woman? To be a good man or woman, if I had it to do over with, I'll just tell you what I'd have done. I would have paid attention and studied my lesson and did the best I could. In school? In school, yes, and went as far as I could have. I would have liked to have been a doctor. I just didn't have the stickability or anybody to tell me, hey, go over there and do that. And if you can do that at a very young age, start in a trade, learn to do something. It doesn't matter what it is. If you learn to do something good, there is a great demand for you. And I would say that in prison, that the prison system should come in and you get a thief, young fans of thief, a robber, and you say, all right, we need carpenters, we need plumbers, we need electricians, we need sheep. Sentence them to that trade. And when you get an A plus in that, where you can go out and make you $30 or $50 an hour, you go home. Now, you can mess around 10 years if you want to, or you can do this in two. I think that's just for the prison. But anyway, I would say that they find somebody and be true to them, that we have, just be honest and true in your life. You mean like relationships, friendships? Relationships, yes. I mean, so many, so many people, particularly our children are from relationships where they're not wanted, they're divorced, their father's left, they don't know who their daddy is, they're distant foster homes. 500,000 children in foster homes in America today. And we have, our government inadvertently is in encouraging those people. My daughter is a doctor and she delivered a couple years ago a baby from a 10-year-old child. That child, and she said, in the visiting room is four generations, all of them on welfare. Now we got one more, and it reminds me of Elvis Presley's song, In the Ghetto. So for an individual, learn a trade, become a craftsman of sorts, and find somebody to love and who loves you. That's right, and have a family, and stick with it. They used to be, surely, you're gonna get angry, you're gonna get disappointed, you're gonna get all kinds of stuff, but come back and make up before you go to sleep. Well, I did half of those things. I got the first one, I'm working on the second one. So I appreciate the advice. Oh, good. Well, Mari, thank you so much for joining us. Can you tell me the story of how you two met? Well, my parents every summer would go to the lake in Canada and the place was called Turkey Point, which is on Lake Erie and just have a nice summer holiday there, water skiing, swimming, sunbathing. This was back in the 60s, and I was sitting on the pier with a few girlfriends and telling them my story, and then all of a sudden I looked up, and I saw this figure in the distance coming onto the pier. Now, we're all dressed in bathing suits and swimwear, we're swimming and this, that, and the other, and here he comes, dark trousers, in fact, they were black, white shirt and a tie, and a straw kind of a Panama hat. And so he was very, he stood out. And so I invited him to come and sit down, and so he continued to talk, and we just talked and talked and talked, and then later moved to the beach. And I think the next time I saw him, he was talking to another girl, and I thought, yeah, you know, nah. Man. I know, I was okay, okay, next. Well, about six months later, I receive a letter, and it's a letter from Roger. And then we start this lovely correspondence, and we just start writing. You know, in those days, you just wrote everything. And then the next summer, he was coming up again, he was on his way to Alaska, and he says, I would like to come by and see you. And I said, well, I'll be in the same place that I met you last year. And so when he came up this time, for some reason, Roger reached for my hand and I reached for his, and man, that was it. It was like love at first touch. That was love. It was just like a silence, you know, and a, oh my gosh. And we didn't even look at each other. It was just, oh my goodness, what happened here? And I was the type of person, I never wanted to get married, not way, way, way down the road, never have any children, and I wanted to see the world first, and then do all that, you know? But that was it, that was love, and you've been together ever since. Yeah. Well, the thing is about the love that the two of you have for each other is it had to persevere through quite a heck of a journey. So how did Roger's drug smuggling change the nature of your love and your relationship? Well, Lex, that remained steadfast. It endured. And since Roger's been home, I think we've rekindled the love that we had when we first met. Yeah, what? But I think my faith, you know, my faith, my steadfast faith, and also the fact that Roger and I communicated, we wrote letters, you know? He never complained. I know there were the children there. He never had mistreated me. I love this guy. And we had a lot of experiences. It was just, even though I- He's good looking, charismatic, he's pretty, you know? Yeah, and he was adventurous, you know? Adventurous. Okay. Would you say that again? Yeah. But yes, it was just, I know I missed him physically, but we were just so strong in spirit, you know? And we could talk to one another, yeah. What was it like, Roger, when you're a free man, seeing Mari for the first time in person again? I cried for three days. Everything, I had to look at a picture of her. I came home and there she prepared a meal for me. And it was the old oak table that I'd redone, and the chairs, the same one, and the green placemats, and the same china that we had, and the same silverware. And it just, all of it just brought back the same paintings on the wall. It was just like unbelievable. After 35 years, she had all my clothes cleaned, and my shoes shining, and I put the shoes on, and I walked out of them, the strings on, and the soles came off. But the shirts and all fit perfect, everything. So it was just wonderful. And just to see her, and then just to think about, see her picture of her 50th birthday, or her 60th birthday, or her 70th birthday, I wasn't there. And the picture of her and with the children, it just, it was heartbreaking. And about the third day, I thought, man up, fella. I mean, you've got to. So I got over it, and quit the tears. But it was, everything was just pulsating with life. It was just unbelievable to get out of that place. It really was. Is there, do you regret the drug smuggling that took you away from the woman you love? Oh yes, 100%. Just, I wouldn't have done it again if, you don't think you're gonna get caught. And it's just, no, it's just, I did it for money, and I had everything in the world I wanted before I did that. So the adventure, I mean, it was one heck of an adventure for the two of you, for the both of you. Yes. Were you able to enjoy it, or was it always danger? Was it always something that threatened your relationship, your love, your family? Were you able to enjoy the adventure of it? You know, we all die. Life is short, and to live that kind of adventure. Well, whenever I did the first loot, I got $10,000. And that was just about two years' pay on the fire department take home. And I brought that home. I put my hand over my mouth, I said, Roger, I can't believe this. And Bonnie and Barney were like, oh my, what in the world? And Roger said, let's go have dinner. And so we went to the little restaurant that we would go to, you know, and he said, don't you dare look on the right-hand side of the menu, just order anything you want. And it was just, as we were in the restaurant, you know, it was just, we were giddy about it. Yeah, I was giddy about it. Were you afraid that, I mean, did you think about the fact that it's illegal and Roger could end up in prison? Oh, yes. Did you guys talk about it? Well, I just, I kind of thought I was bulletproof. I mean, they didn't catch you. I thought if they didn't catch you, you was all right. And it was hard to catch you in the air. So you never thought it was hard to catch you in the air? I didn't know that if your friend told on you five years later, you'd still go to prison. That was a problem. I didn't know that. Did you guys ever talk about walking away? I asked Roger to walk away. He says, I can't, Mario, just now, you know? And then, of course, the amount of people that he began to support, the family and the gifts. The deals. The deals, yes, the deals. Big ones. Yes, and then you always wanted to do, what do you do with the money? You know, so you want to, I guess you clean it up or you want to invest in an enterprise or in a business. Well, it just doesn't work. They know the source of it and they take it and run. Every one of them. Yeah. Yeah. But he was very generous, extremely generous and benevolent and- And when I started, I would ask about it. I went to a lawyer and a good number of people in California at that time wanted to legalize marijuana back in 1973. And I went to a lawyer and I says, Mr. Lawyer, I put $100 on the table. What would they do if I caught me bringing marijuana across the border? He said, if you have a criminal record. I said, no, I've never had a speeding ticket. Nothing, not even a traffic ticket. I said, he said, you work for the fire department out there in Los Angeles? He said, yes, sir. He said, you'll get probation. The worst you'll do is you'll get one year and you spend four months raking leaves on a military base. So my mother and my father died some years before and I brought mother and baby sister came out and I took them down to Disneyland. And she said, what you doing, boy? I said, I'm hauling pot, Ma. She said, how much you making? I said, making $40,000 any day I wanna go. And she said, what do they do if they catch you? And I told her what the lawyer said. Four months at the most, raking leaves. I said, what do you think? She said, do you need a co-pilot, son? Yeah, money is money, yeah. So your relationship persevered through some big challenges. Is there advice you can give about what makes for a successful relationship? Oh, well, you know, I think the initial igniting, meeting someone, that's the love. That's it, and that little fire, just that fire just keeps burning and burning and burning. You can't put it out, no matter what. It's the love fire. But it gets difficult. It does. It's funny, the love fire. So you're saying the love fire's all it takes to persevere through the difficulty. Well, no, well, that's a huge part of it. And also I contribute my individual situation to in order to endure the prison years is my faith. Faith in God? Yes, and friends who are unconditionally still loved me no matter what, yes. So you had love around you in general. I did, and my children. And that was a real purpose, to guide them and to love them and to help them become citizens. Honorable to you. Well, what about you, Roger? What advice would you give? I just don't know how to do it, but I do know that you have to work on a relationship. Mario and I's had problems. I mean, we get really- You guys get in fights? Oh, yeah. Oh, yeah. Oh, yes. Pretty regular, but not, they don't let them last long. Yeah, yeah. But certainly, we are so different. We're the same, and yet we're so different, yeah. Like little stuff? Little stuff, yes. And it might be big, but I usually win her over, you know? Yeah. But anyhow, I just feel like Mario was always there. It was like she was my anchor. Yeah. I was coming home. I was always coming home to her and the children. And you can see throughout my life, I'm working on getting there. Are you afraid for his life, by the way? Oh, yes. Oh, yeah, there are times, yeah. But you know, I had faith in him. He was an excellent pilot. For example, I always said, Roger, if the ship's going down, I'm jumping in the lifeboat with you because I know we're going to get to shore. You will save us. And so I had that, I had that faith in him. I mean, he's a man, but yet, he's the one you wanna get into the lifeboat with. Definitely. But then there is Pablo Escobar, one of the most dangerous humans in history, plus the US government. Yep. Worst, worst, worst, my fault. Very difficult, very difficult to get away. In terms of your faith, how has your faith helped you to be the woman you are in this relationship and seeing love the way you see it? Well, I think my faith gives me hope. I have lots of hope. It helps me to dwell on the good side. You know, when I ever, I meet someone and there's some negative, I try to see why they are like that or what's the source of all that. And I try to pull out the good. I really do. Not that I'm a goody-goody, but that's what your faith does. You know, you see them as God sees us, you know. How has he changed over the years? Roger? Yeah. He's still the same. Actually, I like him better now. He's a little calmer. Yeah, he looks crazy. Oh, yes. And happy to be at home where he'll say, Mary, I am just so happy to be with you here in this condominium. I'm content. Because I used to call him my homing pigeon. You know, I just have to let him fly. I couldn't, you know, he has to fly, but he always came home. Do you think about the end of this ride, our mortality? Do you think about your death? I do. Particularly, I'm going to have a heart valve replacement in about seven days where I could not make it. You know, it's a very serious operation, and I think about that very much. And I ask for peace. I just lost my brother about 10 days ago so unexpectedly. And that really makes you think of your mortality. Are you afraid? Somewhat and yet not. Yeah. I want to live, Lex. I want to live, you know? This life is fun. Yes. Do you think about your death, Roger? I have visions. Visions, and they often happen very, very clear, like what I have seen in the future. Scientists might call it wormholes, or in the Old Testament, they called it prophets, but I see sometimes in the future around the corner. It's clear as we're sitting right here. What's that look like? I was on a porch, and I believe I was in like Central America place. I was an old man with khaki pants and a white shirt. And it was a chair with wide arms, and it was straight. And there was like the beams coming out above my head, and I'm on the porch. Broken via. And I have out-of-the-body experiences also. And I came out of my body, I just floated out of my body, and went into a veil, and like into a mist. And I believe that's probably why it happened. You talk about like it's in your past. This is your future. This is in my future. But this is something he has seen, you know, in the past. Yeah, in. No, I know, but it's funny, just the tense you use, it happened, and yet it's something that will happen. Yes. To both are true. It's just unbelievable. And I don't know how many people have it, but I have it. I walked out of my body, just like, just where I could come up to you and look and set up on the radio. I used to be at work on the railroad, and I had one there. How do you explain that? What do you think, what the heck is going on in this universe that's possible? Oh, I don't know, but certainly, certainly a phenomenon that happened. And there's a guy, Bill Monroe, that wrote the book on out-of-the-body, he tells about it. And who was the guy that writes The Alchemist? Pablo Coelho. He has them also, just like that. And he tells about how it happens on him. Mine happened differently. But you certainly can come out of your body. What do you think the meaning of this life is, maybe from your faith, but also from just the amazing adventure that you lived through? How do you make sense of why the heck we're here? I don't know. It's just kind of like who you are. Even when I was a child, I was like, I'm different from other people. You know? And just as a boy, I was. Could you put into words how you were different, or it was just a feeling? Yeah, like my brother, I mean, he kept his hands clean and his shoes shining. Here I was, barefooted, catching a wild hog or wrestling a horse, trying to get it down. I saw pictures of you climbing a tree recently. Yes, when I first got out of prison. Always something like that. So I don't know. I noticed that something about me is, sometimes in prison, there'd be a knife fight. And people, you see them rough guys that turn white from it. I just kind of almost like smile. I mean, unless they come at me, I'd probably. I'd turn white and get away. But it doesn't bother, those things, they shouldn't bother me. Prison didn't bother me. So you don't know what the heck the meaning is. You just know you're a bit different than the others. Yeah, might be a little bit kooky. Well, maybe the whole point is you wanna realize, you wanna let that madness flourish, that uniqueness flourish. That's the whole point of life. We're all different in our, in like very interesting little ways. Yes. No matter how different you are, you wanna let that, you wanna let that become, you wanna let it be its full possibility. It's like a garden, you know, all the different flowers. It's like a garden. Yeah, like a garden. You did mention, you weren't sure if there's a free will or not. Do you think it's all predetermined? Or do you think we make our own choices? No, we definitely make our decisions. I just said if it is, I hope that. But I know that we make our decisions. Yes, I agree. And I know that we are spirits that are living in this flesh. That's beyond a shadow of a doubt for me. If you walk out of your body and have out of body experience, you will know it. So the body is just the temporary container for something much bigger. The spirit lives on eternally with no beginning and no end. And that's hard to fathom. Yeah, this is just a little, this is a shell to contain that spirit. You know, this is the way we work on earth, you know. But yeah, I know, I'm an eternal being. So are you. Do you think there's a why to it? You know, do you think there's a meaning to this life? Well, I think the why is beyond my capability of understanding. It's someone greater than me. I don't understand it. But it's awesome. I just know that it's awesome. And one day we will know the answers. Once we get to that crossover to the other side, I think we will understand clearly. It says, you know, now we see through a glass darkly. But then when we are face to face with God, we will understand. And until we know, let's just enjoy this beautiful life. While we got it. Absolutely. And we're meant to. That was my guilt. I love everybody and everything. I do. And it just, and I'm sorry if I put a stumbling block in anybody's way. I wouldn't want to. But these are these things that I just think about. Oh, what a hypocritical world we live in, though. Like, almost anybody, I'd say, listen, okay, he's a drug dealer. And I would say most of them have committed adultery. That's a cardinal sin. And yet they throw rocks at me for moving a marijuana or cocaine across the road. Yeah. It's just if you saw the two different things, you'd say, what a terrible difference it is. But we've become conditioned with this mad society that we have. You mentioned that your daughter, Miriam, wrote you a poem. You mind reading it? I'd be glad to. I was doing 11 years up in Lombok Penitentiary, maximum security prison for parole violation for possession of marijuana in 1977. They should have given me six months, but they gave me 11 years because they wanted me for what they call silent beef. Anyhow, while I was in that dungeon, I received a letter from my daughter, Miriam. It's called Daddy's Poem. A year ago, I became a poet when I wrote your birthday prose. And here I am today, ready to give it another go. First, I would like to wish you a very happy birthday to be and to thank you so very much, for without you, I would not be me. Secondly, I want to say that your support has been immense. It has been true, honest, loving, and free of all pretense. Thirdly, it goes without saying, your love has surpassed all my wrongs and you always made me smile with one of your old country songs. I can remember on Cuervo, Daddy, with you holding me in your arms as you sang Jim Reeve songs and talked about the farm. I can see you walking through the door from one of your travels far and wide. And the thought of you coming home, Daddy, kept a twinkle in our eyes. I can smell you as I did when I used to climb into your bed and you would talk to me again about one of the adventures that you led. I can see me and Mario asleep in one of your airplanes extraordinaire and remembering wondering to myself why there wasn't an available chair. I remember having to meet you and worrying that you wouldn't be there, but you would pop up from behind some counter and give us all a happy scare. You gave us presents in Key Biscayne and hotels pleasure galore and three dozen roses as we came through the airport door. I can see your face in Amsterdam with the luggage carousel and you look like a boy with a secret that you were just dying to tell. You taught me mathematics in the sands of faraway places and taught me to sail and we left without any traces. We climbed glaciers in Argentina and saw the blue of the beautiful caves and witnessed the majestic beauty of such a jaggling maze. I learned how to change gears on the dirt roads of Brazil. We ate hot dogs in Paraguay, a memory we smile over still. We talked about lions, elephants, and bears on a Hacienda in Uruguay, but decided it was better if to Europe we did fly. Oh, the old world and all its luxury, what a good time it was. From South America to the Krasnopolsky, I think we fell in love. The European jaunt, well, it is considered a book in itself, but it's a story about beauty and knowledge, suspense and worldly wealth. We went from Holland to Sweden and we went from France to Spain and I promise you I have no regrets. I would definitely do it all again. I would see the world with you anytime, sir. There's no doubt in my mind because being by your side, Daddy, always ensures a wild good time. So our paths took a turn and we're back in the US of A, but life here isn't so bad and I'm plump content to stay. I'm happy to be near you, although I'm not as close as I was before. But because of your love and encouragement, I've been able to open new doors. I'm grateful to be in school and I'm generally happy where I am. And I even like when you call and tell me to study for the next exam. What a life you've given me, Daddy. It's a tremendous and a magical gift. We already have so many stories to tell, there are far too many to list. But I want to thank you again this day for the very big happy birthday to you and to tell you just a few more things that I knew in my heart to be true. That I love you, Daddy, with all of your wrongs and your rights, that you're a head of our family and you've kept us all bound tight, that you have an honest love in your heart for God and all mankind and you truly do believe in yourself when you say it will all be fine. I know you will be there to catch me if ever I waver or slip. And I know I'd want you as captain on any sinking ship. I also know a new chapter is written. It's almost time to move on. It's time to sail another sea and to witness a brand new dawn. It'd be good to see you at the helm again, as you point out our destination, the laughing dance on the upper deckers while the boat glides through. It'd be good to see you on the go, as I know you like to be and to know you can open any door without any key. But while we revel in our days together, we will know better than to hurry. Because as you told me many times, life is an incredible journey. Wow, that's beautiful. Yeah. Roger, I'm really honored to be here and I'm honored that you would take the time to visit me in Texas and to sit down and talk with me. Thank you so much, Roger. Thanks so much, Mark. Thank you, it was a pleasure. It's been a real pleasure. Yes. Beautiful. Thanks for listening to this conversation with Roger Reeves and thank you to Noom, Allform, ExpressVPN, Four Sigmatic and Eight Sleep. Check them out in the description to support this podcast. And now, let me leave you with some words from Pablo Escobar, all empires are created of blood and fire. Thank you for listening. I hope to see you next time.

https://youtu.be/Udh22kuLebg

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James Gosling: Java, JVM, Emacs, and the Early Days of Computing | Lex Fridman Podcast #126

The following is a conversation with James Gosling, the founder and lead designer behind the Java programming language, which in many indices is the most popular programming language in the world, or is always at least in the top two or three. We only had a limited time for this conversation, but I'm sure we'll talk again several times in this podcast. Quick summary of the sponsors, Public Goods, BetterHelp, and ExpressVPN. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that Java is the language with which I first learned object-oriented programming, and with it, the art and science of software engineering. Also, early on in my undergraduate education, I took a course on concurrent programming with Java. Looking back at that time, before I fell in love with neural networks, the art of parallel computing was both algorithmically and philosophically fascinating to me. The concept of a computer in my mind before then was something that does one thing at a time. The idea that we could create an abstraction of parallelism where you could do many things at the same time while still guaranteeing stability and correctness was beautiful. While some folks in college took drugs to expand their mind, I took concurrent programming. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars and Up, a podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I do give you timestamps, so go ahead and skip, but please do check out the sponsors by clicking the links in the description. It's the best way to support this podcast. This show, sponsored by Public Goods, the one-stop shop for affordable, sustainable, healthy household products. I take their fish oil and use their toothbrush, for example. Their products often have a minimalist black and white design that I find to be just beautiful. Some people ask why I wear this black suit and tie. There's a simplicity to it that to me focuses my mind on the most important bits of every moment of every day, pulling only at the thread of the essential and all that life has to throw at me. It's not about how I look, it's about how I feel. That's what design is to me, creating an inner conscious experience, not an external look. Anyway, Public Goods plants one tree for every order placed, which is kind of cool. Visit publicgoods.com slash Lex, or use code Lex at checkout to get 15 bucks off your first order. This show is also sponsored by BetterHelp, spelled H-E-L-P, help. Check it out at betterhelp.com slash Lex. They figure out what you need and match you with a licensed professional therapist in under 48 hours. I chat with the person on there and enjoy it. Of course, I also regularly talk to David Goggins these days who is definitely not a licensed professional therapist, but he does help me meet his and my demons and become comfortable to exist in their presence. Everyone is different, but for me, I think suffering is essential for creation, but you can suffer beautifully in a way that doesn't destroy you. I think therapy can help in whatever form that therapy takes. And I do think that BetterHelp is an option worth trying. They're easy, private, affordable, and available worldwide. You can communicate by text anytime and schedule weekly audio and video sessions. Check it out at betterhelp.com slash Lex. This show is also sponsored by ExpressVPN. You can use it to unlock movies and shows that are only available in other countries. I did this recently with Star Trek Discovery and UK Netflix, mostly because I wonder what it's like to live in London. I'm thinking of moving from Boston to a place where I can build the business I've always dreamed of building. London is probably not in the top three, but top 10 for sure. The number one choice currently is Austin for many reasons that I'll probably speak to another time. San Francisco, unfortunately, dropped out from the number one spot, but it's still in the running. If you have advice, let me know. Anyway, check out ExpressVPN. It lets you change your location to almost 100 countries and it's super fast. Go to expressvpn.com slash LexPod to get an extra three months of ExpressVPN for free. That's expressvpn.com slash LexPod. And now, here's my conversation with James Gosling. I've read somewhere that the square root of two is your favorite irrational number. I have no idea where that got started. Is there any truth to it? Is there anything in mathematics or numbers that you find beautiful? Oh, well, there's lots of things in math that's really beautiful. You know, I used to consider myself really good at math and these days I consider myself really bad at math. I never really had a thing for the square root of two, but when I was a teenager, there was this book called The Dictionary of Curious and Interesting Numbers, which for some reason I read through and damn near memorized the whole thing. And I started this weird habit of when I was like filling out checks, or paying for things with credit cards, I would want to make the receipt add up to an interesting number. Is there some numbers that stuck with you that just kind of make you feel good? They all have a story. And fortunately, I've actually mostly forgotten all of them. All of them. Are they, so like 42? Well, yeah, I mean, 42 is pretty magical. And then the irrationals. I mean, but is there a square root of two story in there somewhere? How did that number get started? It's like the only number that has destroyed religion. In which way? Well, the Pythagoreans, they believed that all numbers were perfect and you could represent anything as a rational number. And in that time period, this proof came out that there was no rational fraction whose value was equal to the square root of two. And that means nothing in this world is perfect, not even mathematics. Well, it means that your definition of perfect was imperfect. Well, then there's the Gatel incompleteness theorems in the 20th century that ruined it once again for everybody. Yeah, although, Gertl's theorem, the lesson I take from Gertl's theorem is not that there are things you can't know, which is fundamentally what it says. But people want black and white answers. They want true or false. But if you allow a three-state logic that is true, false, or maybe, then life's good. Yeah. I feel like there's a parallel to modern political discourse in there somewhere. But let me ask, so with your kind of early love or appreciation of the beauty of mathematics, do you see a parallel between that world and the world of programming? Programming is all about logical structure, understanding the patterns that come out of computation, understanding sort of, I mean, it's often like the path through the graph of possibilities to find a short route. Meaning like find a short program that gets the job done? Yeah. But so then on the topic of irrational numbers, do you see programming, you just painted it so cleanly. It's a little of this trajectory to find like a nice little program, but do you see it as fundamentally messy? Maybe unlike mathematics? I don't think of it as, I mean, you watch somebody who's good at math do math, and often it's fairly messy. Sometimes it's kind of magical. When I was a grad student, one of the students, his name was Jim Sachs, was he had this reputation of being sort of a walking, talking, human, theorem proving machine. And if you were having a hard problem with something, you could just like accost him in the hall and say, Jim, and he would do this funny thing where he would stand up straight, his eyes would kind of defocus. He'd go, just like something in today's movies, he's just, and then he'd straighten up and say, N log N and walk away. And you'd go, well, okay, so N log N is the answer. How did he get there? By which time he's down the hallway somewhere. Yeah, it's just the Oracle, the black box just gives you the answer. Yeah, and then you have to figure out the path from the question to the answer. I think in one of the videos I watched, you mentioned Don Knuth, well, at least recommending his book as something people should read. Oh yeah. But in terms of theoretical computer science, do you see something beautiful that has been inspiring to you, speaking of N log N, in your work on programming languages and that whole world of algorithms and complexity and these kinds of more formal mathematical things? Or did that not really stick with you in your programming life? It did stick pretty clearly for me because one of the things that I care about is being able to sort of look at a piece of code and be able to prove to myself that it works. And so for example, I find that I'm at odds with many of the people around me over issues about how you lay out a piece of software. So software engineers get really cranky about how they format the documents that are the programs, where they put new lines and where they put- The braces. The braces and all the rest of that, right. And I tend to go for a style that's very dense. To minimize the white space. Yeah, well, to maximize the amount that I can see at once, right. So I like to be able to see a whole function and to understand what it does rather than have to go scroll, scroll, scroll and remember, right. Yeah, I'm with you on that. Yeah, that's- And- And people don't like that? Yeah, I've had multiple times when engineering teams have staged what was effectively an intervention. You know, where they invite me to a meeting and everybody's arrived before me and they all look at me and say, James, about your coding style. James, about your coding style. I'm sort of an odd person to be programming because I don't think very well verbally. I am just naturally a slow reader. I'm what most people would call a visual thinker. So when you think about a program, what do you see? I see pictures, right. So when I look at a piece of code on a piece of paper, it very quickly gets transformed into a picture. And, you know, it's almost like a piece of machinery with, you know, this connected to that and- Like these gears- Gears and knobs- Of different sizes on the- Yeah, yeah. I see them more like that than I see the sort of verbal structure or the lexical structure of letters. So then when you look at the program, that's why you wanna see it all in the same place, then you could just map it to something visual. Yeah, and it just kind of like- What is this function doing? Like it leaps off the page at me and- Yeah, what are the inputs, what are the outputs, what the heck is this thing doing? Yeah, yeah. Getting a whole vision of it. Can we go back into your memory? Memory, long-term memory access. What's the first program you've ever written? Oh. I have no idea what the first one was. I mean, I know the first machine that I learned to program on- What is it? Was a PDP-8 at the University of Calgary. Do you remember the specs? Oh yeah. So the thing had 4K of RAM, 12-bit words. The clock rate was, it was about a third of a megahertz. Oh, so you didn't even get to the M, okay. Yeah, yeah. So we're like 10,000 times faster these days. And was this kind of like a super computer, like a serious computer for- No, the PDP-8i was the first thing that people were calling like mini computer. Got it. They were sort of inexpensive enough that a university lab could maybe afford to buy one. And was there time sharing, all that kind of stuff? There actually was a time sharing OS for that. But it wasn't used really widely. The machine that I learned on was one that was kind of hidden in the back corner of the computer center. And it was bought as part of a project to do computer networking. But they didn't actually use it very much. It was mostly just kind of sitting there. And it was kind of sitting there and I noticed it was just kind of sitting there. And so I started fooling around with it. And nobody seemed to mind, so I just kept doing that. And- It had a keyboard and like a monitor? Oh, the keyboard and a monitor. It had a keyboard and like a monitor? This is way before monitors were common. So it was literally a model 33 teletype. Okay. With a paper tape reader. Okay, so the user interface wasn't very good. Yeah, yeah. It was the first computer ever built with integrated circuits. But by integrated circuits, I mean that they would have like 10 or 12 transistors on one piece of silicon. Nice. Not the 10 or 12 billion that machines have today. So what did that, I mean, feel like if you remember those? I mean, did you have kind of inklings of the magic of exponential kind of improvement of Moore's law of the potential of the future that, was that your fingertips kind of thing? Or was it just a cool- Yeah, it was just a toy. You know, I had always liked building stuff, but one of the problems with building stuff is that you need to have parts. You need to have pieces of wood or wire or switches or stuff like that. And those all cost money. And here you could build- You could build arbitrarily complicated things and I didn't need any physical materials. It required no money. That's a good way to put programming. You're right. If you love building things, completely accessible, you don't need anything. And anybody from anywhere could just build something really cool. Yeah, yeah. If you've got access to a computer, you can build all kinds of crazy stuff. And when you were somebody like me who had like really no money. And I mean, I remember just lusting after being able to buy like a transistor. And when I would do sort of electronics kind of projects, they were mostly made, done by like dumpster diving for trash. And one of my big hauls was discarded relay racks from the back of the phone company switching center. Oh, nice. That was the big memorable treasure. Oh yeah, yeah. That was a- What do you use that for? I built a machine that played tic-tac-toe. Nice. Out of relays. Of course, the thing that was really hard was that all the relays required a specific voltage, but getting a power supply that would do that voltage was pretty hard. And since I had a bunch of trashed television sets, I had to sort of cobble together something that was wrong, but worked. So I was actually running these relays at 300 volts and none of the electrical connections were like properly sealed off. Surprised you survived that period of your life. Oh, for so many reasons. For so many reasons. I mean, it's pretty common for teenage geeks to discover, oh, thermite, that's real easy to make. Yeah, well, I'm glad you did. Do you remember what program and category that you wrote? Anything that stands out? And what language? Well, so mostly anything of any size was assembly code. And actually before I learned assembly code, there was this programming language on the PDP-8 called Focal 5 and Focal 5 was kind of like a really stripped down Fortran. And I remember playing, building programs that did things like play Blackjack or Solitaire, or for some reason or other, the things that I really liked were ones where they were just like plotting graphs. So something with like a function or a data and then you'd plot it. Yeah, yeah, I did a bunches of those things and went, ooh, pretty pictures. And so this would like print out, again, no monitors. Right, so it was like on a teletype. Yeah. So using something that's kind of like a typewriter and then using those to plot functions. So when, I apologize to romanticize things, but when did you first fall in love with programming? You know, what was the first programming language? Like as a serious, maybe software engineer, where you thought this is a beautiful thing? I guess I never really thought of any particular languages being like beautiful because it was never really about the language for me. It was about what you could do with it. And, you know, even today, you know, people try to get me into arguments about particular forms of syntax or this or that. And I'm like, who cares? You know, it's about what you can do, not how you spell the word. And, you know, so back in those days, I learned like PL1 and Fortran and COBOL. And, you know, by the time that people were willing to hire me to do stuff, you know, it was mostly assembly code and PDP assembly code and Fortran code and control data assembly code for like the CDC 6400, which was an early, I guess, supercomputer. Even though that supercomputer has less compute power than my phone by a lot. And that was mostly, like you said, Fortran world. That said, you've also showed appreciation for the greatest language ever that I think everyone agrees is Lisp. Well, Lisp is definitely on my list of the greatest ones that have existed. Is it at number one or, I mean, are you, I mean? You know, the thing is that it's, you know, I wouldn't put it number one, no. Is it the parentheses? But what do you love and what do you not love about Lisp? Well, I guess the number one thing to not love about it is so freaking many parentheses. On the love thing is, you know, out of those tons of parentheses, you actually get an interesting language structure. And I've always thought that there was a friendlier version of Lisp hiding out there somewhere, but I've never really spent much time thinking about it. But, you know, so like up the food chain for me from Lisp is Simula, which a very small number of people have ever used. But a lot of people, I think, had a huge influence, right, on the programming. But in Simula, I apologize if I'm wrong on this, but is that one of the first functional languages or no? No, it was the first object-oriented programming language. It's really where object-oriented and languages sort of came together. And it was also the language where coroutines first showed up as a part of the language. So you could have a programming style that was, you could think of it as sort of multi-threaded with a lot of parallelism. Really? There's ideas of parallelism in there? Yeah. Yeah, so that was back, you know, so the first Simula spec was Simula 67. For like 1967? Yeah. Wow. So it had coroutines, which are almost threads. The thing about coroutines is that they don't have true concurrency. So you can get away without really complex locking. You can't usably do coroutines on the multi-core machine. Or if you try to do coroutines on a multi-core machine, you don't actually get to use the multiple cores. Got it. Either that or you, you know, cause you start then having to get into the universe of, you know, semaphores and locks and things like that. But, you know, in terms of the style of programming, you could write code and think of it as being multi-threaded. Multi-threaded, the mental model was very much a multi-threaded one. And all kinds of problems you could approach very differently. To return to the world of Lisp for a brief moment, at CMU, you wrote a version of Emacs that I think was very impactful on the history of Emacs. And what was your motivation for doing so? At that time, so that was in like 85 or 86. I had been using Unix for a few years. And most of the editing was this tool called EDI, which was sort of an ancestor of VI. And- Is it a pretty good editor? Not a good editor? Well, if what you're using, if your input device is a teletype, it's pretty good. Yeah. It's certainly more humane than Tico, which was kind of the common thing in a lot of the DEC universe at the time. And Tico is spelled T-K? Is that the- No, Tico, T-E-C-O, the text editor and corrector. Corrector, wow, so many features. And the original Emacs came out as, so Emacs stands for editor macros. And Tico had a way of writing macros. And so the original Emacs from MIT sort of started out as a collection of macros for Tico. But then, the sort of Emacs style got popular originally at MIT. And then people did a few other implementations of Emacs that were, that were, the code base was entirely different, but it was sort of the philosophical style of the original Emacs. What was the philosophy of Emacs? And by the way, were all the implementations always in C? And then- No, no. And how does Lisp fit into the picture? No, so the very first Emacs was written as a bunch of macros for the Tico text editor. Wow, that's so interesting. And the macro language for Tico was probably the most ridiculously obscure format. You know, if you just look at a Tico program on a page, you think it was just random characters. It really looks like just line noise. Just kind of like LaTeX or something. Oh, way worse than LaTeX. Way, way worse than LaTeX. But, you know, if you use Tico a lot, which I did, the Tico was completely optimized for touch typing at high speed. So there were no two character commands. Well, there were a few, but mostly they were just one character. So every character in the keyboard was a separate command. And actually every character on the keyboard was usually two or three commands because you can hit shift and control and all of those things. You know, it's just a way of very tightly encoding it. And mostly what Emacs did was it made that visual. Right, so one way to think of Tico is use Emacs with your eyes closed. Where you have to maintain a mental model of, you know, sort of a mental image of your document. You have to go, okay, so the cursor is between the A and the E, and I want to exchange those. So I do these things, right? So it is almost exactly the Emacs command set. Well, it's roughly the same. Roughly the same as Emacs command set, but using Emacs with your eyes closed. So what Emacs, you know, part of what Emacs added to the whole thing was being able to visually see what you were editing in a form that matched your document. And, you know, a lot of things changed in the command set. You know, because it was programmable, it was really flexible. You could add new commands for all kinds of things. And then people rewrote Emacs like multiple times in Lisp. There was one done at MIT for the Lisp machine. There was one done at MIT for the Emacs. And at MIT for the Lisp machine, there was one done for Multics. And one summer I got a summer job to work on the Pascal compiler for Multics. And that was actually the first time I used Emacs. And so- To write the compilers. You've worked on compilers too. It's fascinating. Yeah, so I did a lot of work. You know, I mean, I spent like a really intense three months working on this Pascal compiler, basically living in Emacs. And it was the one written in Mac Lisp by Bernie Greenberg. And I thought, wow, this is just a way better way to do editing. And then I got back to CMU where we had kind of one of everything and two of a bunch of things and four of a few things. And since I mostly worked in the Unix universe and Unix didn't have an Emacs, I decided that I needed to fix that problem. So I wrote this implementation of Emacs in C because at the time C was really the only language that worked on- On Unix. On Unix. And you were comfortable with C as well? Oh yeah. At that point? Yeah, at that time I had done a lot of C coding. This was in like 86. And, you know, it was running well enough for me to use it to edit itself within a month or two. And then it kind of took over the university and- And then spread outside. Yeah, and then it went outside the, and largely because Unix kind of took over the research community on the ARPANET. Then, and Emacs was kind of the best editor out there. It kind of took over. And there was actually a brief period where I actually had login IDs on every non-military host on the ARPANET. You know, because people would say, oh, can we install this? And I'd like, well, yeah, but you'll need some help. The days when security wasn't- When nobody cared. Nobody cared. Yeah. Can I ask briefly, what were those early days of ARPANET and the internet like? What was, I mean, did you, again, sorry for the silly question, but could you have possibly imagined that the internet would look like what it is today? You know, some of it is remarkably unchanged. So like one of the things that I noticed really early on when I was at Carnegie Mellon was that a lot of social life became centered around the ARPANET. So things like, you know, between email and text messaging, because text messaging was a part of the ARPANET really early on, there were no cell phones, but you're sitting at a terminal and you're typing stuff. So essentially email, or like what is- Well, just like a one-line message, right? So- Oh, cool, so like chat. Like chat. Yeah. Right, so it's like sending a one-line message to somebody, right? And so pretty much everything from arranging lunch to going out on dates, you know, it was all like driven by social media. Social media. Right, in the 80s. Easier than phone calls, yeah. You know, and my life had gotten to where, you know, I was, you know, living on social media, you know, from like the early mid 80s. And so when it sort of transformed into the internet and social media explodes, I was kind of like, what's the big deal? It's just a scale thing. It's, right, the scale thing is just astonishing. Yeah. But the fundamentals in some ways- The fundamentals have hardly changed. And, you know, the technologies behind the networking have changed significantly. The, you know, the watershed moment of, you know, going from the ARPANET to the internet. And then people starting to just scale and scale and scale. I mean, the scaling that happened in the early 90s and the way that so many vested interests fought the internet. Oh, who, oh, interesting. What was the, oh, because you can't really control the internet. Yeah, so- Who fought the internet? So fundamentally the, you know, the cable TV companies and broadcasters and phone companies, you know, at the deepest fibers of their being, they hated the internet. But it was often kind of a funny thing because, you know, so think of a cable company, right? Most of the employees of the cable company, their job is getting TV shows, movies, or whatever out to their customers. They view their business as serving their customers. But as you climb up the hierarchy in the cable companies, that view shifts because really the business of the cable companies had always been selling eyeballs to advertisers. Right. And, you know, that view of like a cable company didn't really dawn on most people who worked at the cable companies. But, you know, I had various dustups with various cable companies where you could see, you know, in the stratified layers of the corporation that this view of, you know, the reason that you have, you know, cable TV is to capture eyeballs. You know, there- I didn't see it that way. Well, so the people who, most of the people who worked at the phone company, or at the cable companies, their view was that their job was getting delightful content out to their customers and their customers would pay for that. Higher up, they viewed this as a way of attracting eyeballs to them. And then what they were really doing was selling the eyeballs that were glued to their content to the advertisers. To the advertisers, yeah. And so the internet was a competition in that sense. Right. And so- They were right. Well, yeah. I mean, there was one proposal that we sent that, that we, one detailed proposal that we wrote up, you know, back at Sun in the early 90s that was essentially like, look, anybody, you know, with internet technologies, anybody can become provider of content. So, you know, you could be distributing home movies to your parents or your cousins or your, who are anywhere else, right? So anybody can become a publisher. Wow, you were thinking about that already, yeah. Netflix. Yeah, that was- Netflix. Yeah, that was- YouTube. That was like in the early 90s. Yeah. And we thought this would be great. You could, you know, and the kind of content we were thinking about at the time was like, you know, home movies, kids' essays, you know, stuff from like grocery stores or, you know, or a restaurant that they could actually like start sending information about. And- That's brilliant. And the reaction of the cable companies was like, fuck no, because then we're out of business. What is it about companies that, because they could have just, they could have been ahead of that wave. They could have listened to that and they could have- They didn't see a path to revenue. Yeah, there's, somewhere in there, there's a lesson for like big companies, right? Like to listen, to try to anticipate the renegade, the out there, out of the box, people like yourself in the early days writing proposals about what this could possibly be. Well, and that, you know, it wasn't, you know, if you're in a position where you're making truckloads of money off of a particular business model, you know, the whole thought of like, you know, leaping the chasm, right? You know, you can see, oh, new models that are more effective are emerging, right? So like digital cameras versus film cameras. You know, I mean- Why take the leap? Why take the leap? Because you're making so much money off of film. And, you know, in my past at Sun, one of our big customers was Kodak. And I ended up interacting with folks from Kodak quite a lot and they actually had a big digital camera research and, you know, digital imaging business or development group. And they knew that, you know, you just look at the trend lines and you look at, you know, the emerging quality of these, you know, digital cameras. And, you know, you can just plot on the graph, you know, and it's like, you know, sure film is better today, but, you know, digital is improving like this. The lines are going to cross and, you know, the point at which the lines cross is going to be a collapse in their business. And they could see that, right? They absolutely knew that. The problem is that, you know, up to the point where they hit the wall, they were making truckloads of money, right? And when they did the math, it never started to make sense for them to kind of lead the charge. And part of the issues for a lot of companies for this kind of stuff is that, you know, if you're going to leap over a chasm like that, like with Kodak going from film to digital, that's a transition that's going to take a while, right? We had fights like this with people over like smart cards. The smart cards fights were just ludicrous. But that's where visionary leadership comes in, right? Yeah, somebody needs to roll in and say, then take the leap. Well, it's partly take the leap, but it's also partly take the hit. Take the hit in the short term. Right, so you can draw the graphs you want that show that, you know, if we leap from here, you know, on our present trajectory, we're doing this and there's a cliff. If we force ourselves into a transition and we proactively do that, we can be on the next wave, but there will be a period when we're in a trough. And pretty much always there ends up being a trough as you leap the chasm. But the way that public companies work on this planet, they're reporting every quarter. And the one thing that a CEO must never do is take a big hit. Take a big hit. You know, over some quarter. And many of these transitions involve a big hit for a period of time, you know, one, two, three quarters. And so you get some companies and, you know, like Tesla and Amazon are really good examples of companies that take huge hits, but they have the luxury of being able to ignore the stock market for a little while. And that's not so true today, really, but, you know, in the early days of both of those companies, you know, like they both did this thing of, you know, I don't care about the quarterly reports. I care about how many happy customers we have, right? And having as many happy customers as possible can often be an enemy of the bottom line. Yeah, so how do they make that work? I mean, Amazon operated in the negative for a long time. It's like investing into the future. Right, but, you know, so Amazon and Google and Tesla and Facebook, a lot of those had what amounted to patient money, often because there's like a charismatic central figure who has a really large block of stock and they can just make it so. So what, on that topic, just maybe it's a small tangent, but you've gotten the chance to work with some pretty big leaders. What are your thoughts about on Tesla's side, Elon Musk leadership, on the Amazon side, Jeff Bezos, all of these folks with large amounts of stock and vision in their company? I mean, they're founders. Yeah. Either complete founders or like early on folks. And Amazon have taken a lot of leaps. And, you know, that probably at the time, people would criticize as like, what is this bookstore thing? Why? Yeah, and, you know, Bezos had a vision. And he had the ability to just follow it. Lots of people have visions and, you know, the average vision is completely idiotic and you crash and burn. You know, the Silicon Valley crash and burn rate is pretty high. And they don't necessarily crash and burn because they were dumb ideas, but, you know, often it's just timing. Timing and luck. And, you know, you take companies like Tesla and really, you know, the original Tesla, you know, sort of pre Elon, was kind of doing sort of okay, but he just drove them. And because he had a really strong vision, you know, he would make calls that were always, you know, well, mostly pretty good. I mean, the Model X was kind of a goofball thing to do. But he did it boldly anyway. Like there's so many people that just said, like, there's so many people that oppose them on the Falcon window, like the door. From the engineering perspective, those doors are ridiculous. It's like. Yeah, they are a complete travesty. But they're exactly the symbol of what great leadership is, which is like you have a vision and you just go like. If you're gonna do something stupid, make it really stupid. Yeah, and go all in. Yeah, yeah. And, you know, to my credit, he's a really sharp guy. So going back in time a little bit to Steve Jobs. You know, Steve Jobs was a similar sort of character who had a strong vision and was really, really smart. And he wasn't smart about the technology parts of things, but he was really sharp about the sort of human relationship between, you know, the relationship between humans and objects. And, but he was a jerk. You know. Right. Can we just linger on that a little bit? Like people say he's a jerk. Is that a feature or a bug? Well, that's the question, right? So you take people like Steve, who was really hard on people. And so the question is, was he really, was he needlessly hard on people or was he just making people reach to meet his vision? And you could kind of spin it either way. Well, the results tell a story, you know. He's, he, through whatever jerk ways he had, he made people often do the best work of their life. Yeah, yeah. And that was absolutely true. And, you know, I interviewed with him several times. I did, you know, various negotiations with him. And even though kind of personally, I liked him, I could never work for him. Never work for him. Why do you think that, can you put it into words, the kind of tension that you feel would be destructive as opposed to constructive? Oh, he'd yell at people, he'd call them names. And you don't like that? No, no, I don't think you need to do that. And, you know, I think, you know, there's pushing people to excel and then there's too far. And I think he was on the wrong side of the line. And I've never worked for Musk. I know a number of people who have, many of them have said, and it's, you know, shows up in the press a lot, that Musk is kind of that way. And one of the things that I sort of loathe about Silicon Valley these days is that a lot of the high-flying successes are run by people who are complete jerks. But it seems like there's become this, there's come this sort of mythology out of Steve Jobs that the reason that he succeeded was because he was super hard on people. And in a number of corners, people start going, oh, if I wanna succeed, I need to be a real jerk. I need to be a real jerk. Right, and that for me just does not compute. I mean, I know a lot of successful people who are not jerks, who are perfectly fine people. You know, they tend to not be in the public eye. The general public somehow lifts the jerks up into the hero status. Right, well, because they do things that get them in the press. Yeah. And the people who don't do the kind of things that spill into the press. Yeah, I just talked to Chris Lautner for the second time. He's a super nice guy, just an example of this kind of kind of individual that's in the background. I feel like he's behind like a million technologies, but he also talked about the jerkiness of some of the folks. Yeah, yeah, and the fact that being a jerk has become your required style. But one thing I maybe wanna ask on that is maybe to push back a little bit. So there's the jerk side, but there's also, if I were to criticize what I've seen in Silicon Valley, which is almost the resistance to working hard. So on the jerkiness side is, so post-D jobs and Elon kind of push people to work really hard to do. And it's a question whether it's possible to do that nicely. But one of the things that bothers me, maybe I'm just a Russian and just kind of, you know, romanticize the whole suffering thing. But I think working hard is essential for accomplishing anything interesting, like really hard. And in the parlance of Silicon Valley, it's probably too hard. This idea of that you should work smart, not hard, often to me sounds like you should be lazy, because of course you wanna be to work smart. Of course you wanna be maximally efficient, but in order to discover the efficient path, like we're talking about with the short programs, you have to jerk it. Well, you know, the smart hard thing isn't an either or, it's an and. It's an and, yeah. Right. And, you know, the people who say you should work smart, not hard, they pretty much always fail. Yeah, thank you. Right, I mean, that's just a recipe for disaster. I mean, there are counter examples, but there are more people who benefited from luck. And you're saying, yeah, exactly. Luck and timing, like you said, is often an essential thing. But you're saying, you know, you can push people to work hard and do incredible work without. Without being nasty. Yeah, without being nasty. I think Google is a good example of, the leadership of Google throughout its history has been a pretty good example of not being nasty. Yeah, yeah. I mean, the twins, Larry and Sergey, are both pretty nice people. Sandra Pacheco is very nice. Yeah, yeah. And, you know, it's a culture of people who work really, really hard. Let me ask maybe a little bit of a tense question. We're talking about Emacs. It seems like you've done some incredible work, so outside of Java, you've done some incredible work that didn't become as popular as it could have because of like licensing issues and open sourcing issues. What are your thoughts about that entire mess? Like what's about open source now in retrospect, looking back, about licensing, about open sourcing, do you think open source is a good thing, a bad thing? Do you have regrets? Do you have wisdom that you've learned from that whole experience? So in general, I'm a big fan of open source. The way that it can be used to build communities and promote the development of things and promote collaboration and all of that is really pretty grand. When open source turns into a religion that says all things must be open source, I get kind of weird about that because it's sort of like saying, some versions of that end up saying that all software engineers must take a vow of poverty. Right, as though- It's unethical to have money. Yeah. To build a company to, right. And there's a slice of me that actually kind of buys into that because people who make billions of dollars off of like a patent, and the patent came from like literally a stroke of lightning that hits you as you lie half awake in bed. Yeah, that's lucky. Good for you. The way that that sometimes sort of explodes into something that looks to me a lot like exploitation. You see a lot of that in like the drug industry. When you've got medications that cost, you know, cost you like $100 a day. And it's like, no. Yeah, so the interesting thing about sort of open source, what bothers me is when something is not open source, and because of that, it's a worse product. Yeah. So like, I mean, if I look at your just implementation of Emacs, like that could have been the dominant, like I use Emacs, that's my main ID. I apologize to the world, but I still love it. And, you know, I could have been using your implementation of Emacs, and why aren't I? So are you using the GNU Emacs? I guess the default on Linux, is that GNU? Yeah, and that through a strange passage started out as the one that I use. Started out as the one that I wrote. Exactly, so it still has, yeah. Right, well, and part of that was because, you know, in the last couple of years of grad school, it became really clear to me that I was either going to be Mr. Emacs forever, or I was gonna graduate. Got it. I couldn't actually do both. Was that a hard decision? That's so interesting to think about you as a, like it's a different trajectory that could have happened. Yeah. That's fascinating. You know, and maybe, you know, I could be fabulously wealthy today if I had become Mr. Emacs, and Emacs had mushroomed into a series of text processing applications and all kinds of stuff, and, you know, I would have, you know, but I have a long history of financially suboptimal decisions, because I didn't want that life, right? And, you know, I went to grad school because I wanted to graduate. I wanted to graduate. And, you know, being Mr. Emacs for a while was kind of fun, and then it kind of became. Not fun. Not fun. And, you know, when it was not fun, and I was, you know, there was no way I could, you know, pay my rent, right? And I was like, okay, do I carry on as a grad student? As a, you know, I had a research assistantship and I was sort of living off of that, and I was trying to do my, you know, I was doing all my RA work, all my RA, you know, being grad student work and being Mr. Emacs all at the same time, and I decided to pick one. And one of the things that I did at the time was I went around, you know, all the people I knew on the ARPANET who might be able to take over looking after Emacs, and pretty much everybody said, I got a day job. So I actually found, you know, two folks and a couple of folks in a garage in New Jersey, complete with a dog, who were willing to take it over, but they were gonna have to charge money. But my deal with them was that they would only, that they would make it free for universities and schools and stuff, and they said, sure. And, you know, that upset some people. So you have some, now I don't know the full history of this, but I think it's kind of interesting. You have some tension with Mr. Richard Stallman over the, I mean, he kind of represents this kind of, like you mentioned, free software, sort of a dogmatic focus. Yeah, all information must be free. Must be free. So what, is there an interesting way to paint a picture of the disagreement you have with Richard through the years? My basic position is that, you know, when you say information must be free, to a really extreme form that turns into, you know, all people whose job is the production of everything from movies to software, they must all take a vow of poverty, because information must be free, and that doesn't work for me, right? And I don't, I don't want to be wildly rich. I am not wildly rich. I do okay. But I do actually, you know, I've, you know, I can feed my children. Yeah, I totally agree with you. It does just make me sad that sometimes the closing of the source, for some reason, the people that, like a bureaucracy begins to build, and sometimes it doesn't, it hurts the product. Oh, absolutely, absolutely. It's always sad. And there's, and there is a, there is a balance in there. There's a balance. And, you know, it's not hard, hard over, you know, rapacious capitalism, and it's not hard over in the other direction. And, you know, a lot of the open source movement, they have been managing to find a path to actually making money, right? So doing things like service and support works for a lot of people. You know, and there are some ways where it's kind of, some of them are a little perverse, right? So as, you know, a part of things like the Sarbanes-Oxley Act and various people's interpretations of all kinds of accounting principles, and this is kind of a worldwide thing, but if you've got a corporation that is depending on some piece of software, you know, the often, you know, various accounting and reporting standards say, if you don't have a support contract on this thing that your business is depending on, then that's bad. You know, so, you know, if you've got a database, you need to pay for support. And so, but there's a difference between, you know, the sort of support contracts that, you know, the average open source database producer charges, and what somebody who is truly rapacious, like Oracle charges. Yeah, so it's a balance, like you said. It is absolutely a balance. And, you know, there are a lot of different ways to make, you know, the math work out for everybody. And, you know, the very, you know, unbalanced sort of, you know, like the winner takes all thing that happens in so much of modern commerce. That just doesn't work for me either. I know you've talked about this in quite a few places, but you have created one of the most popular programming languages in the world. This is the programming language that I first learned about object-oriented programming with. You know, I think it's a programming language that a lot of people use in a lot of different places and millions of devices today, Java. So the absurd question, but can you tell the origin story of Java? So long time ago at Sun, in about 1990, there was a group of us who were kind of worried that there was stuff going on in the universe of computing that the computing industry was missing out on. And so a few of us started this project at Sun. The really got going, I mean, we started talking about it in 1990 and it really got going in 91. And it was all about, you know, what was happening in terms of computing hardware, processors and networking and all of that, that was outside of the computer industry. And that was everything from the sort of early glimmers of cell phones that were happening then to, you look at elevators and locomotives and process control systems in factories and all kinds of audio equipment and video equipment. They all had processors in them and they were all doing stuff with them. And it sort of felt like there was something going on there that we needed to understand. And... So C and C++ was in the air already. Oh no, C and C++ absolutely owned the universe at that time. Everything was written in C and C++. So where was the hunch that there was a need for a revolution? Well, so the need for a revolution was not about a language. It was about, it was just as simple and vague as there are things happening out there. We need to understand them. We need to understand them. And so a few of us went on several somewhat epic road trips. Literal road trips? Literal road trips. It's like get on an airplane, go to Japan, visit Toshiba and Sharp and Mitsubishi and Sony and all of these folks. And because we worked for Sun, we had folks who were willing to give us introductions. We visited Samsung and a bunch of Korean companies. And we went all over Europe. We went to places like Phillips and Siemens and Thompson. What did you see there? For me, one of the things that sort of leapt out was that they were doing all the usual computer things that people had been doing like 20 years before. The thing that really leapt out to me was that they were sort of reinventing computer networking and they were making all the mistakes that people in the computer industry had made. And since I'd been doing a lot of work in the networking area, we'd go and visit Company X. They'd describe this networking thing that they were doing. And just without any thought, I could tell them like the 25 things that were going to be complete disasters with that thing that they were doing. And I don't know whether that had any impact on any of them, but that particular story of sort of, you know, sort of repeating the disasters of the computer science industry was there. And one of the things we thought was, well, maybe we could do something useful here with like bringing them forward somewhat. But also at the same time, we learned a bunch of things from these, you know, mostly consumer electronics companies. And, you know, high on the list was that they viewed their like relationship with the customer as sacred. They were never, ever willing to make trade-offs for safety, right? So one of the things that had always made me nervous in the computer industry was that people were willing to make trade-offs in reliability to get performance. You know, they want faster, faster. It breaks a little more often because it's fast, you know, maybe you run it a little hotter than you should, or like the one that always blew my mind was the way that the folks at Cray Supercomputers got their division to be really fast was that they did Newton-Raphson approximations. And so, you know, the bottom several bits of, you know, A over B were essentially random numbers. What could possibly go wrong? What could go wrong, right? And, you know, just figuring out how to nail the bottom bit, how to make sure that, you know, if you put a piece of toast in a toaster, it's not going to kill the customer. It's not gonna burst into flames and burn the house down. So those are, I guess those are the principles that were inspiring, but how did, from the days of Java's called Oak, because of a tree outside the window story that a lot of people know, how did it become this incredible, like, powerful language? Well, so it was a bunch of things. So we, you know, after all that, we started, you know, the way that we decided that we could understand things better was by building a demo, building a prototype of something. So kind of because it was easy and fun, we decided to build a control system for some home electronics, you know, TV, VCR, that kind of stuff. And as we were building it, we, you know, we sort of discovered that there were some things about standard practice in C programming that were really getting in the way. And it wasn't exactly, you know, because we were writing this, all the C code and C++ code, that we couldn't write it to do the right thing, but that one of the things that was weird in the group was that we had a guy who's, you know, his sort of top level job was, he was a business guy. You know, he was sort of an MBA kind of person, you know, think about business plans and all of that. And, you know, there were a bunch of things that were kind of, you know, and we would talk about things that were going wrong or things that were going wrong, things that were going right. And, you know, as we thought about, you know, things like the requirements for security and safety, some low level details in C like naked pointers. And, you know, so back in the early nineties, it was well understood that, you know, the number one source of like security vulnerabilities. It's pointers. Was just pointers, was just bugs. Yeah. Right, and it was like, you know, 50, 60, 70% of all security vulnerabilities were bugs. And the vast majority of them were like buffer overflows. Yeah, so you're like, we have to fix this. We have to make sure that this cannot happen. And that was kind of the original thing for me was this cannot, this cannot continue. And one of the things I find really entertaining this year was I forget which rag published it, but there was this article that came out that was an examination. It was sort of the result of an examination of all the security vulnerabilities in Chrome. And Chrome is like a giant piece of C++ code. And 60 or 70% of all the security vulnerabilities were stupid pointer tricks. And I thought it's 30 years later and we're still there. Still there. And we're still there. And, you know, that's one of those, you know, slap your forehead and just want to cry. So would you attribute, or is that too much of a simplification, but would you attribute the creation of Java to C pointers? An obvious problem. Well, I mean, that was one of the trigger points. And currency you've mentioned. Concurrency was a big deal. You know, because when you're interacting with people, you know, the last thing you ever want to see is the thing like waiting. And, you know, issues about the software development process. You know, when faults happen, can you recover from them? What can you do to make it easier to create and eliminate complex data structures? What can you do to fix, you know, one of the most common C problems, which is storage leaks. And it's evil twin, the freed but still being used piece of memory. You know, you free something and then you keep using it. Oh, yeah. So when I was originally thinking about that, I was thinking about it in terms of safety and security issues. And one of the things I sort of came to believe, came to understand was that it wasn't just about safety and security, but it was about developer velocity, right? So, and I got really religious about this because at that point, I had spent an ungodly amount of my life hunting down mystery pointer bugs. And, you know, like two thirds of my time as a software developer was, you know, because the mystery pointer bugs tend to be the hardest to find because they tend to be very, very statistical. The ones that hurt, you know, they're like, a one in a million chance and- But nevertheless create an infinite amount of suffering. Right. Because when you're doing a billion operations a second, you know, one in a million chance means it's gonna happen. And so I got really religious about this thing, about making it so that if something happens, it fails immediately and visibly. And, you know, one of the things that was a real attraction of Java to lots of development shops was that, you know, we get our code up and running twice as fast. You mean like the entirety of the development process, debugging, all that kind of stuff? Yeah, if you, you know, so if you measure, if you measure the number of times that you've touched a keyboard, you know, you've first touched fingers to keyboard until you get your first demo out, not much different. But if you look from fingers touching keyboard to solid piece of software that you could release in production, it would be way faster. And I think what people don't often realize is, yeah, there's things that really slow you down, like hard to catch bugs probably is the thing that really slows down that. It really slows things down. But also there were, you know, one of the things that you get out of object oriented programming is a strict methodology about, you know, what are the interfaces between things and being really clear about how parts relate to each other. And what that helps with is so many times what people do is they kind of like sneak around the side. So if you've built something and people are using it and then, and you say, and you say, well, okay, you know, I've built this thing, you use it this way, and then you change it in such a way that it still does what you said it does, it just does it a little bit different. But then you find out that somebody out there was sneaking around the side, they sort of tunneled in a back door, and this person, their code broke. And because they were sneaking through a side door. And normally the attitude is, dummy. But a lot of times, you know, you can't get away, you can't just slap their hand and tell them to not do that. Because, you know, it's, you know, somebody's, you know, some banks, you know, account reconciliation system that, you know, some developer decided, oh, I'm lazy, you know, I'll just sneak through the back door. And because the language allows it, I mean, you can't even mad at them. And so one of the things I did that, on the one hand, upset a bunch of people, was I made it so that you really couldn't go through back doors, right? So the whole point of that was to say, if you need, you know, if the interface here isn't right, the wrong way to deal with that is to go through a back door. The right way to deal with it is to walk up to the developer of this thing and say, fix it, right? And so it was kind of like a social engineering thing. And people ended up discovering that that really made a difference in terms of, you know, and a bunch of this stuff, you know, if you're just like screwing around, right in your own, like, you know, class project scale stuff, a lot of this stuff isn't quite so important because, you know, you're, you know, both sides of the interface. But, you know, when you're building, you know, sort of larger, more complex pieces of software that have a lot of people working on them, and especially when they like span organizations, you know, having really clear, having clarity about how that stuff gets structured saves your life. And, you know, especially, you know, there's so much software that is fundamentally untestable, you know, until you do the real thing. It's better to write good code in the beginning as opposed to writing crappy code and then trying to fix it and trying to scramble and figure out and through testing, figure out where the bugs are. Yeah, it's like, which shortcut caused that rocket to not get where it was needed to go? So I think one of the most beautiful ideas philosophically and technically is of a virtual machine, the Java virtual machine. Well, again, I apologize to romanticize things, but how did the idea of the JVM come to be? How to you radical of an idea it is? Because it seems to me to be just a really interesting idea in the history of programming. So, and what is it? So the Java virtual machine, you can think of it in different ways because it was carefully designed to have different ways of viewing it. So one view of it that most people don't really realize is there, is that you can view it as sort of an encoding of the abstract syntax tree in reverse Polish notation. I don't know if that makes any sense at all. I could explain it and that would blow all over time. But the other way to think of it and the way that it ends up being explained is that it's like the instruction set of an abstract machine that's designed such that you can translate that abstract machine to a physical machine. And the reason that that's important, so if you wind back to the early 90s, when we were talking to all of these companies doing consumer electronics, and you talk to the purchasing people, there were interesting conversations with purchasing. So if you look at how these devices come together, they're sheet metal and gears and circuit boards and capacitors and resistors and stuff. And everything you buy has multiple sources, right? So you can buy a capacitor from here, you can buy a capacitor from there, and you've got kind of a market so that you can actually get a decent price for a capacitor. But CPUs and particularly in the early 90s, CPUs were all different and all proprietary. So if you use the cheap, so if you use the chip from Intel, you had to be an Intel customer till the end of time. Because if you wrote a bunch of software, when you wrote software using whatever technique you wanted, and C was particularly bad about this because there was a lot of properties of the underlying machine that came through. So- So you were stuck, so the code you wrote, you were stuck to that particular machine. You were stuck to that particular machine, which meant that they couldn't decide, you know, Intel is screwing us. I'll start buying chips from, you know, Bob's Better Chips. This drove the purchasing people absolutely insane. That they were welded into this decision. And they would have to make this decision before the first line of software was written. It's funny that you're talking about the purchasing people. So that's one perspective, right? It's, you could, there's a lot of other perspectives that all probably hated this idea. Right. But from a technical aspect, just like the creation of an abstraction layer that's agnostic to the underlying machine, from the perspective of the developer, I mean, that's brilliant. Right, well, and, you know, so that's like across the spectrum of providers of chips. But then there's also the time thing, because, you know, as you went from one generation to the next generation to the next generation, they were all different. And you would often have to rewrite your software. I mean, if two generations of machines of different kinds. Yeah, so like one of the things that sucked about a year out of my life was when San went from the Motorola 68010 processor to the 68020 processor. Then they had a number of differences, and one of them hit us really hard. And I ended up being the point guy on the worst case of where the new instruction cache architecture hurt us. Well, okay, so I mean, so when did this idea, I mean, okay, so yeah, you articulate a really clear fundamental problem in all of computing, but where do you get the guts to think we can actually solve this? You know, in our conversations with all these vendors, you know, these problems started to show up. And I kind of had this epiphany because it reminded me of a summer job that I had had in grad school. So back in grad school, my thesis advisor, well, I had two thesis advisors for bizarre reasons. One of them was a guy named Raj Reddy, the other one was Bob Sproul. And Raj, I love Raj, I really love both of them. But so the department had bought a bunch of like early workstations from a company called Three Rivers Computer Company. And Three Rivers Computer Company was a bunch of electrical engineers who wanted to do as little software as possible as much software as possible. So they knew that they'd need to have like compilers and an OS and stuff like that, and they didn't wanna do any of that. And they wanted to do that for as close to zero money as possible. So what they did was they built a machine whose instruction set was literally the byte code for UCSD Pascal, the P code. And so we had a bunch of software that was written for this machine. And for various reasons, the company wasn't doing terrifically well. We had all this software on these machines and we wanted it to run on other machines, principally the VAX. And so Raj asked me if I could come up with a way to port all of this software from the PERC machines to VAXs. And I think he, you know what he had in mind was something that would translate from like Pascal to C or Pascal to, actually at those times, pretty much it was, you could translate to C or C. And if you didn't like translate to C, you could translate to C. There was, you know, it's like the Henry Ford, any color you want, just as long as it's black. And I went, that's really hard. And I noticed that, you know, and I was like looking at stuff and I went, ooh, I bet I could rewrite the P code into VAX assembly code. And then I started to realize that, you know, there were some properties of P code that didn't really work. There were some properties of P code that made that really easy. Some properties that made it really hard. So I ended up writing this thing that translated from P code on the three rivers PERCs into assembly code on the VAX. And I actually got higher quality code than the C compiler. And so everything just went, got really fast. It was really easy. It was like, wow, I thought that was a sleazy hack because I was lazy. And in actual fact, it worked really well. And I tried to convince people that that was maybe a good thesis topic. And nobody was, you know, it was like, nah. Really? That's, I mean, yeah. It's kind of a brilliant idea, right? Maybe you didn't have the, you weren't able to articulate the big picture of it. Yeah. And I think, you know, that was a key part. But so then, you know, clock comes forward a few years and it's like, we've got to be able to, you know, if they want to be able to switch from, you know, this weird microprocessor to that weird and totally different microprocessor, how do you do that? And I kind of went, oh, maybe by doing something kind of in the space of, you know, Pascal P code, you know, I could do like multiple translators. And I spent some time thinking about that and thinking about, you know, what worked and what didn't work when I did the P code to VAX translator. And I talked to some of the folks who were involved in Smalltalk because Smalltalk also did a bytecode. And then I kind of went, yeah, let's, I want to do that. Yeah. Cause that actually, you know, and it had the other advantage that you could either interpret it or compile it. And interpreters are usually easier to do, but not as fast as a compiler. And so I figured, good, I can be lazy again. You know, sometimes I think that most of my good ideas are driven by laziness. And often I find that some of the people's stupidest ideas are because they're insufficient. Some of the people's stupidest ideas are because they're insufficiently lazy. They just want to build something really complicated. It's like, it doesn't need to be that complicated. Yeah. And so, and so that's how that came out. And, you know, but that also turned into kind of a, you know, almost a religious position on my part, which was, which got me in, in several other fights. So like, like one of the things that was a real difference was the way that arithmetic worked. You know, once upon a time there were, you know, it wasn't always just two's complement arithmetic. There were some machines that had one's complement arithmetic, which was like almost anything built by CDC. And occasionally there were machines that were decimal arithmetic. And I was like, this is crazy. You know, pretty much two's complement integer arithmetic has one. So just. Let's just do that. Just do that. One of the other places where there was a lot of variability was in the way that floating point behaved. And that was causing people throughout the software industry much pain because you couldn't do a numerical computing library that would work on CDC and then have it work on an IBM machine and work on a, on a DEC machine. And as a, as a part of that whole struggle, there had been this, this big body of work on, on the, on the, on the, on the, on the, on the, on the, on the, on the, on the, on the, on the, on the, on the floating point standards. And this thing emerged that can be called IEEE 754, which is the floating point standard that pretty much has taken over the entire universe. And, and at the time I was doing Java, it had pretty much completed taking over the universe. There were still a few pockets of holdouts, but I was like, you know, it's important to be able to say what two plus two means. Yeah. And, and so I went that. And one of the ways that I got into fights with people was that there were a few machines that did not implement IEEE 754 correctly. Well, of course that's, that's all short term kind of fights. I think in the, in the longterm, I think this vision is one out. Yeah. And, and I think it's, you know, and it worked out over time. I mean, the, the, the biggest fights were with Intel because they had done some strange things with rounding. They'd done some strange things with their transcendental functions, which might turn into a mushroom cloud of, you know, weirdness. And the name, in the name of optimization, but from the perspective of the developer, that's not, that's not good. Well, their issues with transcendental functions were just stupid. Okay. So that's, that's not even a trade off. That's just absolutely. Yeah. They were, they were doing range reduction in for sine and cosine using a slightly wrong value for pi. Got it. We got 10 minutes. So in the interest of time, two questions. So one about Android and one about life. So one, I mean, we could talk for many more hours. I hope eventually we might talk again, but I gotta ask you about Android and the use of Java there, because it's one of the many places where Java just has a huge impact on this world. Just on your opinion, is there things that make you happy about the way Java is used in the Android world? And are there things that you wish were different? I don't know how to do a short answer to that, but I have to do a short answer to that. So, you know, I'm happy that they did it. Java had been running on cell phones at that time for quite a few years, and it worked really, really well. There were things about how they did it, and in particular, various ways that they kind of, you know, violated all kinds of contracts. The guy who led it, Andy Rubin, he crossed a lot of lines. There's some lines crossed. Yeah, lines were crossed that have since, you know, mushroomed into giant court cases. And, you know, they didn't need to do that. And in fact, it would have been so much cheaper for them to not cross lines. I mean, I suppose they didn't anticipate the success of this whole endeavor. Or do you think at that time it was already clear that this is gonna blow up? I guess I sort of came to believe that it didn't matter what the law was, I sort of came to believe that it didn't matter what Andy did, it was gonna blow up. Okay. I kind of started to think of him as like a manufacturer of bombs. Yeah. Some of the best things in this world come about through a little bit of explosive. Well, and some of the worst. And some of the worst, beautifully put. But is there, and like you said, I mean, does that make you proud that Java is in millions? I mean, it could be billions of devices. Yeah, well, I mean, it was in billions of phones before Android came along. And, you know, I'm just as proud as, you know, of the way that like the smart card standards adopted Java. And they did a, you know, everybody involved in that did a really good job. And that's, you know, billions and billions. That's crazy. The SIM cards, you know, the SIM cards in your pocket. Yeah, I mean, it's- I've been outside of that world for a decade, so I don't know how that has evolved, but, you know, it's just been crazy. So on that topic, let me ask, again, there's a million technical things we could talk about, but let me ask the absurd, the old philosophical question about life. What do you hope when you look back at your life and people talk about you, write about you, 500 years from now, what do you hope your legacy is? I hope people not being afraid to take a leap of faith. I mean, you know, I've got this kind of weird history of doing weird stuff and- It worked out pretty damn well. It worked out, right? And I think some of the weirder stuff that I've done has been the coolest. And some of it, some of it crashed and burned and, you know, I think well over half of the stuff that I've done has crashed and burned, which has occasionally been really annoying. But still you kept doing it. But yeah. Yeah. Yeah, and, you know, even when things crash and burn, you at least learn something from it. By way of advice, you know, people, developers, engineers, scientists, or just people who are young to look up to you, what advice would you give them? How to approach their life? Don't be afraid of risk. It's okay to do stupid things once. Maybe a couple of times. You know, you get a pass on the first time or two that you do something stupid. You know, the third or fourth time, yeah, not so much. But also, you know, I don't know why, but really early on I started to think about ethical choices in my life. And because I'm a big science fiction fan, I got to thinking about like just about every technical decision I make in terms of, how do you want, you know, are you building Blade Runner or Star Trek? Which one's better? Which future would you rather live in? You know? So what's the answer to that? Well, I would sure rather live in the universe of Star Trek. Star Trek, yeah. And that opens up a whole topic about AI, but that's a really interesting. Yeah, yeah, yeah. It's a really interesting idea. So your favorite AI system would be data from Star Trek. And my least favorite would easily be Skynet. Yeah. Beautifully put. I don't think there's a better way to end it, James. I can't say enough how much of an honor it is to meet you, to talk to you. Thanks so much for wasting your time with me today. Not a waste at all. Thanks, James. All right, thanks. Thanks for listening to this conversation with James Gosling. And thank you to our sponsors, Public Goods, BetterHelp, and ExpressVPN. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from James Gosling. One of the toughest things about life is making choices. Thank you for listening and hope to see you next time.

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Jo Boaler: How to Learn Math | Lex Fridman Podcast #226

The following is a conversation with Jo Bowler, a mathematics educator at Stanford and co-founder of ucubed.org that seeks to inspire young minds with the beauty of mathematics. To support this podcast, please check out our sponsors in the description. This is the Lex Friedman Podcast, and here is my conversation with Jo Bowler. What to you is beautiful about mathematics? I love a mathematics that some people don't even think of as mathematics, which is beautiful, creative mathematics, where we look at maths in different ways, we visualize it, we think about different solutions to problems. A lot of people think of maths as you have one method and one answer. And what I love about maths is the multiple different ways you can see things, different methods, different ways of seeing, different. In some cases, different solutions. So that is what is beautiful to me about mathematics, that you can see and solve it in many different ways. And also the sad part that many people think that maths is just one answer and one method. So to you, the beautiful, the beauty emerges when you have a problem with a solution and you start adding other solutions, simpler solutions, weirder solutions, more interesting, some that are visual, some of that are algebraic, geometry, all that kind of stuff. Yeah, I mean, I always say that you can take any maths area and make it visual. And we say to teachers, give us your most dry, boring maths, and we'll make it a visual, interesting, creative problem. And it turns out you can do that with any area of maths. And I think we've given, it's been a great disservice to kids and others that it's always been numbers, lots and lots of numbers. Numbers can be great, but you can think about maths in other ways besides numbers. Do you find that most people are better visual learners, or is this just something that's complimentary? What's the kind of the full spectrum of students in the way they like to explore math, would you say? There's definitely people who come into the classes I do who are more interested in visual thinking and like visual approaches. But it turns out what the neuroscience is telling us is that when we think about maths, there are two visual pathways in the brain, and we should all be thinking about it visually. Some approaches have been to say, well, you're a visual learner, so we'll give you visuals, and you're not a visual learner. But actually, if you think you're not a visual learner, it's probably more important that you have a visual approach so you can develop that part of your brain. So you were saying that there's some kind of interconnected aspect to it, so the visual connects with the non-visual. Yeah, so this is what the neuroscience has shown us, that when you work on a maths problem, there are five different brain pathways, and that the most high-achieving people in the world are people who have more connections between these pathways. So if you see a maths problem with numbers, but you also see it visually, that will cause a connection to happen in your brain between these pathways. And if you maybe write about it with words, that would cause another connection, or maybe you build it with something physical, that would cause a different connection. And what we want for kids is, we call it a multidimensional experience of maths, seeing it in different ways, experiencing it in different ways. That will cause that great connected brain. You know, there's these stories of physicists doing the same. I find physicists are often better at building that part of their brain, of using visualization for intuition building, because you ultimately want to understand the deepest secret underneath this problem. And for that, you have to intuit your way there. And you mentioned offline that one of the ways you might approach a problem is to try to tell a story about it. And some of it is like legend, but I'm sure it's not always. Is you have Einstein thinking about a train, and the speed of light, and that kind of intuition is useful. You start to imagine a physical world. Like how does this idea manifest itself in the physical world? And then start playing in your mind with that physical world, and think, is this going to be true? Is this going to be true? Right, right. Einstein is well known for thinking visually. And people talk about how he really didn't want to go anywhere with problems without thinking about them visually. But the other thing you mentioned that sparked something for me is thinking with intuition. Like having intuition about math problems. That's another thing that's often absent in math class, the idea that you might think about a problem and use your intuition. But so important. And when mathematicians are interviewed, they will very frequently talk about the role of intuition in solving problems, but not commonly acknowledged or brought into education. Yeah, I mean, that's what it is. If you task yourself with building an intuition about a problem, that's where you start to pull in what is the pattern I'm seeing? In order to understand the pattern, you might want to then start utilizing visualization. But ultimately, that's all in service of solving the puzzle, cracking it open to get the simple explanation of why things are the way they are. As opposed to, like you said, having a particular algorithm that you can then execute to solve the problem. Yeah, but it's hard. It's hard. Like reasoning is really hard. Yeah, it's hard. I mean, I love to value what's hard in maths instead of being afraid of it. We know that when you struggle, that's actually a really good time for your brain. You want to be struggling when you're thinking about things. So if it's hard to think intuitively about something, that's probably a really good time for your brain. I used to work with somebody called Sebastian Thrun, who is a great sort of mathematician, you might think of him, AI person. And I remember in one interview I did with him, he talked about how they'd built robots, I think for the Smithsonian, and how they were having this trouble with them picking up white noise. And he said they had to solve it. They had to work out what was going on. And how he intuitively worked out what the problem was. But then it took him three weeks to show it mathematically. I thought that was really interesting that how you can have this intuition and know something works. It's kind of different from going through that long mathematical process of proving it. But so important. Yeah, I think probably our brains are evolved as like intuition machines. And the math of like showing it like formally is probably an extra thing that we're not designed for. You see that with Feynman and his, all of these physicists definitely you see starting with intuition, sometimes starting with an experiment. And then the experiment inspires intuition. But you can think of an experiment as a kind of visualization. Just like let's take whatever the heck we're looking at and draw it. And draw like the pattern as it evolves, as the thing grows for N equals one, for N equals two, N equals three. And you start to play with it. And then in the modern day, which I loved doing is, you can write a program that then visualizes it for you. And then you can start exploring it programmatically. And then you can do so interactively too. I tend to not like interactive because it takes way too much work. Because you have to click and move and stuff. I love to interact through writing programs. But that's my particular brain, software engineer. So you can do all these kinds of visualizations. And then there's the tools of visualization, like color, all those kinds of things. That you're absolutely right. They're actually not taught very much. Like the art of visualization. Not taught. And we love as well color coding. Like when you represent something mathematically, you can show color to show the growth. And kind of code that. So if I have an algebraic expression for a pattern, maybe I show the X with a certain color, but also write in that color so you can see the relationship. Very cool. And yeah, particularly in our work with elementary teachers, many of them come to our workshops and they're literally in tears when they see things making sense visually. Because they've spent their whole lives not realizing you can really understand things with these visuals. It's quite powerful. You say that there's something valuable to learning when the thing that you're doing is challenging, is difficult. So a lot of people say math is hard, or math is too hard, or too hard for me. Do you think math should be easy, or should it be hard? I think it's great when things are challenging, but there's something that's really key to being able to deal with challenging maths, and that is knowing that you can do it. And I think the problem in education is a lot of people have got this idea that you're either born with a maths brain or you're not. So when they start to struggle, they think, oh, I don't have that maths brain. And then they will literally sort of switch off in their brain and things will go downhill from that point. So struggle becomes a lot easier, and you're able to struggle if you don't have that idea. But you know that you can do it. You have to go through this struggle to get there, but you're able to do that. And so we're hampered in being able to struggle with these ideas we've been given about what we can do. Ask a difficult question here. Yeah. So there's kind of, I don't know what the right term is, but some people struggle with learning in different ways. Like their brain is constructed in different ways. And how much should, as educators, should we make room for that? So how do you know the difference between this is hard, and I don't like doing hard things, versus my brain is wired in a way where I need to learn in very different ways. I can't learn it this way. How do you find that line? How do you operate in that gray area? So this is why being a teacher is so hard. And people really don't appreciate how difficult teaching is when you're faced with, I don't know, 30 students who think in different ways. But this is also why I believe it's so important to have this multidimensional approach to maths. We've really offered it in one way, which is here's some numbers and a method. You follow me, do what I just did, and then reproduce it. And so there are some kids who like doing that, and they do well. And a lot of kids who don't like doing it and don't do well. But when you open up maths and you give, you let kids experience it in different ways, maybe visually, with numbers, with words, what happens is there are many more kids who can access it. So those different brain wirings you're talking about, where some people are just more able to do something in a particular way, that's why we want to, that's one of the reasons we want to open it up, so that there are different ways of accessing it. And then that's not really a problem. So I grew up in the Soviet Union and fell in love with math early. I was forced into math early and fell in love through force. That's good. Well, good that you fell in love. But something we talked about a little bit is there's such a value for excellence. It's competitive, and it's also everybody kind of looks up. The definition of success is being, in a particular class, is being really good at it. And it's not improving, it's being really good. I mean, we are much more like that with sports, for example. We're not, it's like it's understood, you're going to star on the basketball team, if you're gonna start on the basketball team, if you're going to be better than the other guys, the other girls on the team. So that coupled with the belief, this could be partially a communist belief, I don't know, but the belief that everybody is capable of being great. But if you're not great, that's your fault. And you need to work harder, and I remember, I had a sense that, probably delusional, but I could win a Nobel Prize. I don't even know what that entails. But I thought, like my dad early on told me, just offhand, and it always stuck with me, that if you can figure out how to build a time machine, how to travel back in time, it will probably give you a Nobel Prize. And I remember early in my life thinking, I'm going to invent the time machine. And the tools of mathematics were in service of that dream of winning the Nobel Prize. It's silly. I didn't really think in those concrete terms, but I just thought I could be great, that feeling. And then when you struggle, the belief that you could be great, struggle is good. Right, pushes you on, yeah. And so the other thing about the Soviet system that I'd love to hear your comments about, is just the sheer hours of math. Like the number of courses, you're talking about a lot of geometry, a lot more geometry. I think in the American system, you take maybe one year of geometry. In high school, yeah. In high school. First of all, geometry is beautiful, it's visual. And then you get to reason through proofs and stuff like that. In Russia, I remember just being nailed over and over with geometry, it was just nonstop. And then of course, there's different perspectives on calculus and just the whole, the sense was that math is like fundamental to the development of the human mind. So math, but also science and literature, by the way, was also hit very hard. Like we read a lot of serious adult stuff. America does that a little bit too. They challenge young adults with good literature, but they don't challenge adults very much with math. So those two things, valuing excellence and just a lot of math in the curriculum, do you think, do you find that interesting? Because it seems to have been successful. Yeah, I think that's very interesting. And there is a lot of success, people coming through the Soviet system. I think something that's very different to the US and other countries in the world is this idea that excellence is important and you can get there if you work hard. In the US, there's an idea that excellence is important, but then kids are given the idea in many ways that you can either do it or you're one of the people who can't. So many students in the school system think they're one of the kids who can't. So there's no point in trying hard because you're never going to get there. So if you can switch that idea, it would be huge. And it seems from what you've said that in the Soviet Union, that idea is really different. Now, the downside of that idea that anybody can get there if you work hard is that thought that if you're not getting there, it's your fault. And I would add something into that. I would say that anybody can get there, but they need to work hard and they also need good teaching. Because there are some people who really can't get there because they're not given access to that good teaching. So, but that would be huge, that change. As to doing lots of maths, if maths was interesting and open and creative and multi-dimensional, I would be all for it. We actually run summer camps at Stanford where we invite kids in and we give them this maths that I love. And in our camp classrooms, they were three hours long. And when we were planning, the teachers were like, three hours, are we gonna be able to keep the kids excited for three hours? Turned out, they didn't want to go to break or lunch. They'd be so into these mathematical patterns. We couldn't stop them. It was amazing. So yeah, if maths was more like that, then I think having more of it would be a really good thing. So what age are you talking about? Could you comment on what age is the most important when people quit math or give up on themselves or on math in general? And perhaps that age or something earlier is really an important moment for them to discover, to be inspired to discover the magic of math. I think a lot of kids start to give up on themselves and maths around, from about fifth grade. And then those middle school years are really important. And fifth grade can be pivotal for kids just because they're allowed to explore and think in good ways in the early grades of elementary school. But fifth grade teachers are often like, okay, we're gonna prepare you now for middle school and we're gonna give you grades and lots of tests. And that's when kids start to feel really badly about themselves. And so middle school years, our camps are middle school students. We think of those years as really pivotal. Many kids in those years are deciding, yes, I'm gonna keep going with STEM subjects. Or no, I'm not, that this isn't for me. So, I mean, all years are important. And in all years, you can kind of switch kids and get them on a different pathway. But I think those middle school years are really important. So what's the role of the teacher in this? So one is the explanation of the subject, but do you think teachers should almost do like one-on-one, you know, little Johnny, I believe in you kind of thing? Like that energy of like- Turns out it's really important. There's a study that was done. It was actually done in high school English classrooms where all kids wrote an essay for their teacher. And this was done as an experiment. Half of the kids got feedback from their teacher, diagnostic feedback, which is great. But for half of the kids, it said an extra sentence at the bottom that the researchers had put on. And the kids who read that extra sentence did significantly better in English a whole year later. The only change was this one sentence. What did the sentence say? So what did the sentence say? The sentence said, I'm giving you this feedback because I believe in you. And the kids who read that did better a year later. Yeah. So when I share this with teachers, I say, you know, I'm not suggesting you put on the bottom of all kids' work. I'm giving this feedback because I believe in you. One of the teachers said to me, we don't put it on a stamp? I said, no, don't put it on a stamp. But your words are really important. And kids are sitting in classrooms all the time thinking, what does my teacher think of me? Does my teacher think I can do this? So it turns out it is really important to be saying to kids, I know you can do this. And those messages are not given enough by teachers. And really believe it. And believe it, yeah. You can't just say it, you have to believe it. I sometimes, because it's like, it's such a funny dance, because I'm almost such a perfectionist, I'm extremely self-critical, and I have one of the students come up to me, and it's clear to me that they're not even close to good. And it's tempting for me to be like, to sort of give up on them mentally. But the reality is, if you look at many great people throughout history, they sucked at some point. And some of the greatest took non-linear paths to where they sucked for long into later life. And so always kind of believing that this person can be great. You have to communicate that, plus the fact that they have to work hard. That's it, yeah. Yeah, and you're right. Silicon Valley, where I live, is filled with people who were dropouts at school, or who had special needs, who didn't succeed. It's very interesting that have gone on to do amazing work in creative ways. I mean, I do think our school system is set up to value good memorizers who can reproduce what a teacher is showing them, and push away those creative, deep thinkers, often slower thinkers, they think slowly and deeply. And they often get the idea early on that they can't be good at maths or other subjects. So yeah, I think many of those people are the ones who go on and do amazing things. So there's a guy named Eric Weinstein. I know many mathematicians like this, but he talks a lot about having a non-standard way of learning. I mean, a lot of great mathematicians, a lot of great physicists are like that. And he felt like he became quickly, he got his PhD at Harvard, became quickly an outcast of the system. Like the education, especially early education system, didn't help him. Is there ways for an education system to support people like that? Is it this kind of multi-dimensional learning that you're mentioning? Yeah, absolutely, absolutely. I mean, I think education system still uses an approach that was in classrooms hundreds of years ago. The textbooks have a lot to answer for in producing this very uninspiring mathematics. But yeah, if you open up the subject and have people see and solve it in different ways and value those different ways. Somebody I appreciated a lot is a mathematician called Mary Mizzikani. I don't know if you've heard of her. She won the Fields Medal. She was from Iran. First woman in the world to win the Fields Medal in mathematics. She died when she was 40. She was at Stanford. But her work was entirely visual. And she talked about how her daughter thought she was an artist because she was always visualizing. And I attended, she asked me to chair the PhD defense for one of her students. And I went to the defense in the math department. And it was so interesting because this young woman spent like two hours sharing her work. All of it was visual. In fact, I don't think I saw any numbers at all. And I remember that day thinking, wow, I could have brought her like 13 year old into this PhD defense. They would not recognize this as maths. But when Mary Mizzikani won the Fields Medal, all these other mathematicians were saying that her work had connected all these previously unconnected areas of maths. And so, but when she was, she also shared that when she was in school, when she was about 13, she was told that she couldn't do maths. She was told that by her teacher. This is Iran? She grew up in Iran. In Iran, yeah. So I love that. To be told you can't be good at maths and then go on and win the Fields Medal is cool. I've been told by a lot of people in my life that I can't do something. I'm very definitely non-standard. But all it takes, that's why people talk about the one teacher that changed everything for them. All it takes is one teacher. That's right. That's the power of that. So that should be inspiring to teachers. I think it is. You as a single person, given the education system, given the incentives, you have the power to truly change lives. And 20 years from now, I feel as medalist will walk up to you and say thank you. You did that for me. Yeah, absolutely. And I share that with teachers that even in this broken system of what they have to do for districts and textbooks, a single teacher can change kids' maths relationship or other subjects and forever. What's the role of the parents in this picture? Let's go to another difficult subject. Yeah, that is a difficult subject. One study found that the amount of maths anxiety parents had predicted their child's achievement in school, but only if they helped with homework. So... Oh, that's so funny. Yeah, there are some interesting implications for this. I mean, you can see how it works. If you have maths anxiety and you're helping your kids with homework, you're probably communicating things like, oh, I was terrible at this at school, and that's how it gets passed on to kids. So one implication is if you have a really bad relationship with maths, you hate maths, you have maths anxiety, just don't do maths homework with your kids. But we have, on our website, we have a little sheet for parents of ways to interact around maths with your kids. And... That's ucubed.org? That's ucubed.org, yes. So one of the things I say to parents when I give parent presentations is even if you hate maths, you need to just fake it with your kids. You should be always endlessly optimistic and happy about doing maths. And... I'm always curious about this. So I hope to have kids one day. I don't have kids currently. Are parents okay with sucking at maths and then trying to get their kid to be better than them, essentially? Is that a difficult thing for a lot of parents? It is difficult. To have, it's almost like an ego thing. I never got good at this, and I probably should have. And... Yeah, to me, you wanna celebrate that, but I know a lot of people struggle with that, coaches in sports, to make an athlete become better than them. It can be hard on the ego. Yeah. So do you experience the same with parents? I think, I mean, I haven't experienced parents worrying that their kids will be better than them. I have experienced parents just having a really bad relationship with maths and not wanting to help, not knowing how to help, saying things. Like another study showed that when mothers say to their daughters, I was bad at maths in school, their daughter's achievement goes down. So we know that kids pick up on these messages, and which is why I say you should fake it. But also, I know that lots of people have just had a really bad relationship with maths, even successful people. The undergrads I teach at Stanford have pretty much always done well in maths, but they come to Stanford thinking maths is a set of methods to memorize. And so, so do many parents believe that. There's one method that you memorize, and then you reproduce it. So until people have really had an experience of what I think of as the other maths, where until they've really seen that it's a really different subject, it's hard for them to be able to shift their kids to see it differently. Is there for a teacher, if we were to like systematize it, is there something teachers can do to do this more effectively? So you mentioned the textbook. Yeah. So what are the additional things you can add on top of this whole old school traditional way of teaching that can improve the process? So I do think there's a way of teaching maths that changes everything for kids and teachers. So I'm one of five writers of a new framework for the state of California, a new maths framework. It's coming out next year. And we are recommending through this maths framework that people teach in this way. It's called teaching to big ideas. So at the moment, people have standards that have been written, and then textbooks have taken these standards and made not very good questions. And if you look at the standards, like I have some written down here, just reading the standards, it makes maths seem really boring and uninspiring. What are the kind of, can you give a few examples? So this is an interesting example. In third grade, there are three different standards about unit squares. Okay. So this is one of them. A square with side length one unit called a unit square is said to have one square unit of area and can be used to measure area. And that's something you're expected to learn. That is something, so that's a standard. The textbook authors say, oh, I'm gonna make a question about that. And they translate the standards into narrow questions. And then you measure success by your ability to deliver on these standards. So the standards themselves, I think of maths, and many people think of maths in this way, as a subject of like a few big ideas and really important connections between them. So you could think of it as like a network map of ideas and connections. And what standards do is they take that beautiful map and they chop it up like this into lots of little pieces and they deliver the pieces to schools. And so teachers don't see the connections between ideas, nor do the kids. So anyway, this is a bit of a long way of saying that what we've done in this new initiative is we have set out maths as a set of big ideas and connections between them. So this is grade three. So instead of there being 60 standards, we've said, well, you can pull these different standards to get in with each other and also value the ways these are connected. And by the way, for people who are just listening, we're looking at a small number of like big concepts within mathematics, square tiles, measuring fraction, shape and time, and then how they're interconnected. And so the goal is for, this is for grade three, for example. Yeah. And so we've set out for the state of California, the whole of mathematics K10 as a set of big ideas and connections. So we know that teachers, it works really well if they say, okay, so a big idea in my grade is measuring. And instead of reading five procedural statements that involve measuring, they think, okay, measuring is a big idea. What rich, deep activity can I use that teaches measuring to kids? And as kids work on these deep, rich activities, maybe over a few days, turns out a lot of maths comes into it. So we're recommending that let's not teach maths according to all these multiple, multiple statements and lots and lots of short questions. Instead, let's teach maths by thinking about what are the big ideas and what are really rich, deep activities that teach those big ideas. So that's the, like how you teach it and maximize learning. What about like from a school district perspective, like measuring how well you're doing, you know, grades and tests and stuff like that. Do you throw those out or is it possible? I'm not a fan of grades and tests myself. I think grades are fine if they're used at the end of a course. So at the end of my maths course, I might get a grade because a grade is meant to be a summative measure. It kind of describes your summative achievement. But the problem we have in maths classrooms across the US is people use grades all the time, every week or every day even. My own kids, when they went through high school, technology has not helped with this. When they went through high school, they knew they were being graded for everything they did, everything. And not only were they being graded for everything, but they could see it in the grade book online and it would alter every class they went into. So this is the ultimate, what I think of as a performance culture. You're there to perform, somebody's measuring you, you see your score. So I think that's not conducive for deep learning. And yes, have a grade at the end of the year, but during the year, you can assess kids in much better ways. Like teachers can, a great way of assessing kids is to give them a rubric that kind of outlines what they're learning over the course of a unit or a few weeks. So kids can actually see the journey they're on. Like this is what we're doing mathematically. Sometimes they self-assess on those units and then teachers will show what they can, what the kids can do with a rubric and also write notes. Like in the next few weeks, you might like to learn to do this. So instead of kids just thinking about, I'm an A kid or a B kid, or I have this letter attached to me, they're actually seeing mathematically what's important and they're involved in the process of knowing where they are mathematically. At the end of the year, sure, they can have a grade, but during the year, they get these much more informative measures. I do think this might be more for college, but maybe not. Some of the best classes I've had is when I got a special, like set aside, like the professor clearly saw that I was interested in some aspect of a thing. And then I've a few in mind and one in particular, he said that he kind of challenged me. So this is outside of grades and all that kind of stuff that basically it's like reverse psychology. I don't think this can be done. And so I gave everything to do that particular thing. So this happened to be in an artificial intelligence class. But I think that like special treatment of taking students who are especially like excellent at a particular little aspect, that you see their eyes light up. I often think like, maybe it's tempting for a teacher to think you've already succeeded there, but they're actually signaling to you that like you could really launch them on their way. And I don't know, that's too much to expect from teachers, I think to pay attention to all of that, cause it's really difficult. But I just kind of remember who are the biggest, the most important people in the history of my life of education. And it's those people that who really didn't just like inspire me with their awesomeness, which they did, but also just, they pushed me a little, like it gave me a little push. And that requires focusing on the quote unquote, excellent students in the class. Yeah, I think what's important though, is teachers to have the perspective that they don't know who's gonna be excellent at something before they give out the activity. Exactly. And in our camp classes that we ran, sometimes students would finish ahead of other students. And we would say to them, can you write a question that's like this but different? And over time we encouraged them to like extend things further. I remember we were doing one activity where kids were working out the borders of a square and how big this border would be in different case sizes. And one of the boys came up at the end of the class and said, I've been thinking about how you do this with a pentagon. And I said, that's fantastic. How do you, what does it look like with a pentagon? Go find out, see if you can discover. So I didn't know he was gonna come up and say that. And I didn't have in my head, like this is the kid who could have this extension task. But you can still do that as a teacher. When kids get excited about something or they're doing well in something, have them extend it, go further. It's great. And then you also, like this is like teacher and coach, you could say it in different ways to different students. Like for me, the right thing to say is almost to say, I don't think you could do this, this is too hard. Like that's what I need to hear. Because it's like, no, there's an immediate push. But with some people, if they're a little bit more, I mean, it all has to do with upbringing, how your genetics is. They might be much more, that might break them. Yeah, that might break them. So you have to be also sensitive to that. I mean, teaching is really difficult. It is really difficult. For this very reason. It is. So what is the best way to teach math, to learn math at those early few days when you just wanna capture them? I do something, actually there's a video of me doing this on our website that I love when I first meet students. And this is what I do. I show them a picture. This is the picture I show them. And it's a picture of seven dots like this. And I show it for just a few seconds. And I say to them, I'd like you to tell me how many dots there are, but I don't need to count them. I want you to group the dots. And I show it them and then I take it away before they've even had enough time to count them. And then I ask them, so how did you see it? And I go around the room and amazingly enough, there's probably 18 different ways of seeing these seven dots. And so I ask people, tell me how you grouped it. And some people see it as like an outside hole with a center dot. Some people see like stripes of lines. Some people see segments. And I collect them all and I put them on the board. And at the end I say, look at this. We are a class of 30 kids and we saw these seven dots in 18 different ways. There's actually a mathematical term for this. It's called groupitizing. Groupitizing? Yeah. I like it. It's kind of cool. So turns out though that how well you groupitize predicts how well you do in math. Is it a raw talent or is it just something that you can develop? I don't think you're born groupitizing, I think. But some kids have developed that ability, if you like. And you can learn it. You can, so this to me is part of how wrong we have math. That we think to tell whether a kid's good at math, we're gonna give them a speed test on multiples. But actually, seeing how kids group dots could be a more important assessment of how well they're gonna do in math. Anyway, I diverge. What I like to do when I start off with kids is show them, I'm gonna give you math problems. I'm gonna value the different ways you see them. And turns out you can do this kind of problem asking people how they group dots with young children or with graduate students. And it's engaging for all of them. You talk about creativity a little bit and flexibility in your book Limitless. What's the role of that? So it sounds like there's a bit of that kind of thing involved in groupitizing. Yeah, yeah. I love this term. So what would you say is the role of creativity and flexibility in the learning of math? I think what we know now is that what we need for this 21st century world we live in is a flexible mind. School should not really be about teaching kids particular methods, but teaching them to approach problems with flexibility. Being creative, thinking creatively is really important. So people don't think the words math and creativity come together, but that's what I love about math is the creative different ways you can see it. And so helping our kids, there's a book I like a lot, by, it's been by a physicist. You probably know this book called Elastic. You might know it. And it's about how we want elastic minds. Same kind of thing, flexible, creative minds. And schools do very little on developing that kind of mind. They do a lot of developing the kind of mind that a computer now does for us. Memorization. Memorization, doing procedures, a lot of things that we spend a lot of time in school on. In the world, when kids leave school, a computer will do that. And better than they will. But that creative, flexible thinking, we're kind of at ground zero at computers being able to engage in that thinking. Maybe we're a little above ground zero, but the human brain is perfectly suited for that creative, flexible thinking. That's what humans are so great at. So I would like the balance to shift in schools. Maybe you still need to do some procedural kind of thinking, but there should be a lot more of that creative, flexible thinking. And what's the role of other humans in this picture? So collaborative learning, so brainstorming together. So creativity as it emerges from the collective intelligence of multiple humans. Yeah, super important. And we know that also helps develop your brain, that social side of thinking. And I love mathematics collaboration where people build on each other's ideas and they come up with amazing things. I actually taught 100 students calculus at Stanford recently, undergrads. And we taught them to collaborate. So these students came in Stanford and most of them were against collaboration in math. This is before COVID in person? Yeah, it was just before COVID hit. It was 2019. And this summer- Sorry, you said they're against? Yeah, so it's really interesting. So they'd only experienced maths individually in a kind of competitive individual way. And if they had experienced it as group work, it had been a bad experience. Like maybe they were the one who did it all and the others didn't do much. So they were kind of against collaboration. They didn't see any role for it in maths. And we taught them to collaborate. And it was hard work because as well as the fact that they were kind of against collaboration, they came in with a lot of like social comparison thinking. So I'm in this room with other Stanford undergrads and they're better than me. So when we set them to work on a maths problem together, the first one was kind of a disaster because they were all like, they're better than me, they're faster than me. They came up with something I didn't come up with. So we taught them to let go of that thinking and to work well together. And one of the things we did, we decided, we wanted to do a pre and post test at the end of this teaching. It was only four weeks long, but we knew we didn't want to give them like a time test of individual work. So we gave them an applied problem to do at the beginning and we gave them to do in pairs together. And we gave each of them a different colored pen and said, work on this activity together and keep using that pen. So then we had all these pieces of student work. And what we saw was they just worked on separate parts of the paper. So there's a little like red pen section and a green pen section. And they didn't do that well on it, even though it was a problem that middle or high school kids could do, but it was like a problem solving kind of problem. And then we gave them the same one to do at the end, gave them the same colors and actually they had learned to collaborate. And not only were they collaborating the second time around, but that boosted their achievement. And the ones who collaborated did better on the problem. Collaboration is important, having people, and what was so eye opening for these undergrads and they talked about it in lovely ways was I learned to value other people's thinking on a problem. And I learned to value that other people saw it in different ways. And it was quite a big experience for them that they came out thinking, I can do math with other people, people can see it differently, we can build on each other's ways of thinking. I got a chance to, I don't know if you know who Daniel, Kahneman is, got a chance to interact with him. And like the first, cause he had a few, but one famous collaboration throughout his life with Tversky. And just like, he hasn't met me before in person, but just the number of questions he was asking, just the curiosity. So I think one of the skills, the collaboration itself is a skill. And I remember my experience with him was like, okay, I get why you're so good at collaboration because he was just extremely good at listening and genuine curiosity about how the other person thinks about the world, sees the world. And then together, he pulled me in, in that particular case, he doesn't know in particular like that much about autonomous vehicles, but he kept like asking all of these questions. And then like 10 minutes in, we're together trying to solve the problem of autonomous driving. And like, and that, I mean, that's really fulfilling. That's really enriching, but it also in that moment made me realize it's kind of a skill is you have to kind of put your ego aside, put your view of the world aside and try to learn how the other person sees it. And the other thing you have to put aside is this social comparison thinking. Like if you are sitting there thinking, wow, that was an amazing idea. He's so much better than I am. That's really gonna stop you taking on the value of that idea. So there's a lot of that going on between these Stanford students when they came. And trying to help them let go of that. One of the things I've discovered, just because being a little bit more in the public eye, how rewarding it is to celebrate others. Yeah. And how much it's going to actually pay off in the long term. Yeah. So this kind of silo thinking of like, I want to prove to a small set of people around me that I'm really smart. And do so by basically not celebrating how smart the other people are. That's actually maybe short term, it seems like a good strategy, but long term it's not. And I think if you practice at the student level and then at the career level, at every single stage, I think that's ultimately. I agree with you. I think that's a really good way of thinking about it. You mentioned textbooks. And you didn't say it, maybe textbooks isn't the perfect way to teach mathematics. But I love textbooks. They're like pretty pictures and they smell nice. I mean, I talk about like physical. Some of my greatest experiences have been just like, because they're really well done. When we're talking about basic like high school, calculus, biology, chemistry, those are incredible. It's like Wikipedia, but with color and nice little- You must have seen some good textbooks if they had pretty pictures and color. Yeah, I mean, I remember, I guess it was very, very standard, like AP calculus, AP biology, AP chemistry. I felt those were like some of the happiest days of my life in terms of learning was high school. Because it was very easy, honestly. It felt hard at the time, but you're basically doing a whirlwind tour of all the science. Yeah, yeah. Without having to pick, you do literature, you do like Shakespeare, calculus, biology, physics, chemistry, what else? Anatomy, physiology, computer science. Without like, nobody's telling you what to do with your life, you're just doing all of those things. That's a good thing, you're right. But I remember the textbooks weren't, I mean, maybe I'm romanticizing the past, but I remember they weren't, they're pretty good. But so you think, what role do you think they play still? And like in this more modern digital age, what's the best materials with which to do these kinds of educations? Well, I'm intrigued that you have such a good experience with textbooks. I mean, I can remember loving some textbooks I had when I was learning, and I love books. I love to pick up books and look through them. But a lot of math textbooks are not good experiences for kids. We have a video on our website of the kids who came to our camp, and one of the students says, in math, you have to follow the textbook. The textbook's kind of like the Bible. You have to follow it. And every day, it's slightly different. Like on Monday, you do 2.3.2, and on Tuesday, you do 2.3.3, and on Wednesday. And you never go off that. That's like every single day. And that's not inspiring for a lot of the kids. So one of the things they loved about our camp was just that there were no books. Even though we gave them sheets of paper instead, they still felt more free because they weren't just like trotting through exercises. Like what a textbook allows you is like, you're, the very thing you said they might not like, the 2.3, 2.3, it feels like you're making progress. And like it's a little celebration because you do the problem, and it seems really hard, and you don't know how to do it. And then you try and try, and then eventually succeed. Then you make that little step in further progress. And then you get to the end of a chapter, and you get to like, it's closure. You're like, all right, I got that figured out. And then you go on to the next chapter. I can see that. I mean, I think it could be in a textbook. You can have a good experience with a textbook. But what's really important is what is in that textbook. What are you doing inside it? And I mean, I grew up in England, and in England, we learn maths. We don't have this separation of algebra and geometry. And I don't think any other country apart from the US has that. But I look at kids in algebra classes where they're doing algebra for a year, and I think I would have been pretty bored doing that. But like, can we analyze your upbringing real quick? Why do British folks call mathematics maths? Why is it the plural? Is it because of everything you're saying, or is it a bunch of sub-disciplines? Yeah, I mean, mathematics is supposed to be the different maths that you look at, whether you think of that as topics like geometry and probability, or I think of it as maths. It's just multi-dimensional, lots of ways. But that's why it was called mathematics, and then it was shortened to maths. And then for some reason, it was just math in the US. But to me, math has that more singular feel to it. And there's an expression here, which is do the math, which basically means do a calculation. That's what people mean by do the math. So I don't like that expression because math could be anything. It doesn't have to be a calculation. So yeah, I like maths because it has more of that broad feel to it. Yeah, I love that. Maths kind of emphasizes the multi-dimensional, like a variety of different sub-disciplines, different approaches, yeah. Okay, but outside of the textbook, what do you see broadly being used? You mentioned Sebastian Thrun and MOOCs, online education. Do you think that's an effective set of- Can be. I mean, online, having great teachers online obviously extends those teachers to many more people, and that's a wonderful thing. I have quite a few online courses myself. I got the bug working with Sebastian when he had released his first MOOC. And I thought, hmm, maybe I could do one in maths education. And I didn't know if anybody would take it. I remember releasing it that first summer, and it was a free online class, and 30,000 maths teachers took it that first summer. And they were all talking about it with each other and sharing it, and it was like, took off. In fact, it was that MOOC that got me to create Ucubed with Kathy Williams, who's the co-founder, because people took the MOOC, and then they said, okay, what now? I finished, what can I have next? So that was where we made our website. But, so yeah, I think online education can be great. I do think a lot of the MOOCs don't have great pedagogy. They're just a talking head. And you can actually engage people in more active ways, even in online learning. So I learned from the Udacity principle when I was working at Udacity, never to talk more than like five minutes. And then to ask people to do something. So that's the sort of pedagogy of the online classes I have. There's a little bit of presenting something, and then people do something, and then there's a little bit more. Because I think if you have a half hour video, you just switch off and start doing other things. So the way Udacity did it is like five, 10 minute, like bit of teaching with some visual stuff, perhaps, and then there's like a quiz almost. And then you answer a question, yeah. Yeah, that's really effective. You mentioned Ucubed. So what's the mission, what's the goal? You mentioned how it started, but what's, yeah, where are you at now, and what's your dream with it? Or what are the kind of things that people should go and check out on there? Yeah, we started Ucubed, I guess it was about five years ago now, and we've had over 52 million visitors to the site. So I'm very happy about that. And our goal is to share good ideas for teaching with teachers, students, parents in maths, and to help, we have a sort of sub-goal of a raising maths anxiety, that's important to us, but also to share maths as this beautiful creative subject. And it's been really great. We have lessons on the site, but one of the reasons I thought this was needed is there's a lot of knowledge in the academy about how to teach maths well, loads and loads of research and journals and lots of things written up, but teachers don't read it. They don't have access to it. They're often behind pay walls. They're written in really inaccessible ways, so people wouldn't want to read them or understand them. So this I see as a big problem. You have this whole industry of people finding out how to teach well, not sharing it with the people who are teaching. So that's why we made U-Cubed. And instead of just putting articles up saying, here's some things to read about how to teach well, we translated what was coming from research into things that teacher could use. So lessons, there were videos to show kids, and there were tips for parents. There were all sorts of things on the site. And it's been amazing. We took inspiration from the Week of Code, which got teachers to focus on coding for a week. And we have this thing called the Week of Inspirational Maths. And we say, just try it for a week. Just give us one week and try it and see what happens. And so it's been downloaded millions of times. Teachers use it every year. They start the school year with it. And what they tell us is, it was amazing. The kids' lights were on. They were excited. They loved it. And then the week finished, and I opened my textbooks, and the lights went out, and they were not interested. Yeah, but getting that first inspiration is still powerful. It is. I wish, I mean, what I would love is if we could actually extend that for the whole year. We're a small team at Stanford, and we're trying to keep up with great things to put on the site. And we haven't the capacity to produce these creative visual math tasks for every year group for every day, but I would love to do that. How difficult is it to do? I mean, to come up with visual formulations of these big, important topics you need to think about in a way that you could teach. I mean, we can do it. We actually, we went from the Week of Inspirational Maths, and we made K-8 maths books with exactly that. Big ideas, rich activities, visuals. We just finished the last one. We've been doing it for five years, and it's been exhausting, and we just finished. So now there's a whole K-8 set of books, and they're organized in that way. These are the big ideas. Here are rich, deep activities. They're not, though, what you can do every day for a year. So some teachers use them as a kind of supplement to their boring textbook, and some people have said, okay, this is the year. This book tells us what the year is, and then we'll supplement these big activities with. So they're being used, and teachers really like them and are really happy about them. I just always want more, and I guess one of the things I would like for U-Cubed, one of my personal goals, is that every teacher of maths knows about U-Cubed. At the moment, lots of teachers who come to us are really happy they found it, but there's a lot of other teachers who don't know that it exists. I hope this helps. Yeah. From a student perspective, and not in the classroom, but at home studying, is there some advice you can give on how to best study mathematics? So what's the role of the student outside the classroom? Yeah, I think one thing we know is a lot of people, when they review material, whether it's maths or anything else, don't do it in the best way. I think a problem a lot of people have is they read through maybe a teacher's explanation or a way of doing maths, and it makes sense, and they think, oh yeah, I've got that, and they move on. But then it's not until you come to try and work on something and do a problem that you actually realize you didn't really understand it, just seemed to make sense. So I would say this is also something that neuroscientists talk about, to keep giving yourself questions is a really good way to study, rather than looking through lots of material. It's almost like giving yourself lots of tests is a good way to actually deeply understand things and know what you do when you don't understand. So would the questions be in the form of, the material you're reviewing is the answer to that question, or is it almost like beyond, it's the polygon thing you mentioned, or square, is it almost like, I wonder, what is the bigger picture? I was kind of asking, like, how is this extended and so on. Yeah, that would be great. And it's a similar, I mean, a question I get asked a lot is about homework, what is a good thing for kids to do for homework? And one of the recommendations I give is to not have kids just do lots of questions for homework, but to actually ask them to reflect on what they've learned, like, what was the big idea you learned today? Or what did you find difficult? What did you struggle with? What was something that was exciting? Then kids go home and they have to kind of reflect in a deeper way. A lot of times, I don't know if you had this experience as a math student, lots of people, kids are going through math questions, they're successful, they get them right, but they don't even really know what they're about. And a lot of kids go through many years of math like that, doing lots of questions, but not really knowing what even the topic is or what it's about, what it's important for. So having students go back and think at the end of the day, what was the big idea from this math lesson? Why is it important? Where would I find that in real life? Those are really good questions for kids to be thinking about. It's probably for everybody to be thinking about. I think most of us go through life never asking the bigger question, almost like those layers of why questions that kids ask when they're very young. We need to keep doing that. We do. Like whatever the term is, you call first principles thinking, some people call it that. Which is like, why are we doing it this way? So one nice thing is to do that because there's usually a good answer. Like the reason we did it this way is because it works for this reason. But then if you want to do something totally novel, you'll say, well, we've been doing it this way because of historical reasons, but really this is not the best way to do it. There might be other ways and that's how invention happens. And then you get, that's really useful in every aspect of life, like choosing your career, choosing your, I don't know, where you live, who your romantic partner is, everything. And I think it probably starts doing that in math class. That would be good if we started doing that. I mean, I wonder, I probably didn't do very much of that for most of my education, asking why, except for later, much later, in the subjects on like grad school, when you're doing research on them. When your first task of doing something novel using this or solving a problem really outside the classroom, they have to publish on it. It's the first time you think, wait, why are these things, interesting, useful, which are the things that are useful? And yeah, I guess that would be nice if we did that much earlier, that the quest of invention. Yeah, yeah. I mean, one of the sad pieces of research data I think about is the questions kids ask in school goes down like in a linear progression from in the early years, you can't stop kids asking those questions, but they learn not to ask the questions. I think you told somewhere about an early memory you had in your own education, where you asked the question, or maybe that was an example you gave, but it was shut down. Oh yeah. You've listened to something I said, yeah. I don't remember where it was, but it caught me. Yeah, I remember it really vividly. Well, can you tell the memory? Yeah, it's funny, I can remember. It must have really impacted me in that moment because you know how there's lots of hours of school you don't remember at all. But anyway, I can remember where I was sitting and everything. I was in a high school maths class, although they don't call it that in England. And the teacher said, and it was like the first class of this teacher's class, and he said, ask if you have any questions. So at one point I put my hand up and I said, I have a question. And he said something like, that's your question? And I was like, okay, I'm not asking any more questions in this class. And then it hit hard in a way where you didn't wanna, the lesson you learned from that is I'm not gonna ask. Yeah, that was absolutely the lesson I asked. That's the last question I'm asking. And that was, yeah, he was the chair of the maths department. I remember that really well. So maybe because of that experience, one of the things we encourage when we teach kids is asking questions and we value it when they ask questions and we put them up on walls and celebrate. It's funny, because I wish there was a feedback signal because he probably, to put a positive spin on it, he probably didn't realize the negative impact he's had in that moment, right? If he only knew. See, this is probably when you're more mature in grad school, and an amazing professor named Alicia Kafande in computer science, and he would get, he encouraged questions, but then he would tell everybody how dumb their questions are. But it was, I guess if you show, if you say it with love and respect behind it, then it's more like a friendly, humorous encouragement for more questions. It's an art, right? Yeah, teaching is very hard. You have to time it right, because that kind of humor is probably better for when you're in grad school versus when you're in the early education. Right. Well, and I guess kids or young people get whether somebody's doing it to be funny or, you know, has it, I mean, this is why it teaches so hard. Even your tone can be impactful. It's so sad because like for that particular human, the teacher, you just had a bad day, and one statement can have a profound negative impact. I know, sadly, that math, there's a lot of math teachers who have that kind of approach, and they, I think they're suffering from the fact that they think people are math people, not math people, and that comes across in their teaching. But on the flip side, one positive statement. Yeah. Keep them going. That's right, that is the flip side of that. And I myself had like one teacher who was really amazing for me in maths, and she kept me in the subject. I probably would have left it. Who was she? She was, her name was Mrs. Marshall. She was my A-level maths teacher. So I was in- What's that mean? In England, you do lots of subjects until you're 16, and then you choose like three or four subjects. So I had chosen maths, and you go to higher levels, probably equivalent more to a master's degree in the US because you're more specialized. But anyways, she was my teacher, and for the first time in my whole career in maths, she would give us problems and tell us to talk about them with each other. And so here I was sitting there at like 17, talking with friends about how to solve a math problem, and that was it. That was the change that she made, but it was profound for me. Because like those calculus students, I started to hear other people's ways of thinking and seeing it, and we would talk together and come up with solutions. And I was like, that was it. That changed maths for me. It wasn't some kind of personal interaction with her. It was more like she was the catalyst for that collaborative experience. I mean, yeah, the many ways teachers can inspire kids. I mean, sometimes it's a personal message, but it can be your teaching approach that changes maths for kids. You know, Cal Newport, he wrote a book called Deep Work, and he's a mathematician, a theoretical computer scientist, and he talks about the kind of the focus required to do that kind of work. Is there something you can comment on? You know, we live in a world full of distractions. That seems like one of the elements that makes studying, and especially the studying of subjects that require thinking like maths does, difficult. Is there something from a student perspective, from a teacher perspective, that encourages deep work that you can comment on? Yeah, I think giving kids really inspiring deep problems, and we have some on our website, is a really important experience for them, even if they only do it occasionally, but it's really important. They actually realize, I give a problem out often when I'm working with teachers, and I say to them, all right, I'm gonna check in with you after an hour. And they're like, an hour? They think it's shocking. And then they work on this problem, and after an hour, I say, okay, how are we doing? They're like, an hour's gone by? How is this possible? And so everybody needs those rich, deep problems. Most kids go through their whole maths experience of however many years, never once working on a problem in that kind of deep way. So the undergrad class I teach at Stanford, we do that. We work on these deep problems every session, and the students come away going, okay, I never wanna go back to that maths relationship I had where it was just all about quick answers. I just don't wanna go back to that. And so we can all, all teachers can incorporate those problems in their classrooms. Maybe they don't do them every day, but they at least give kids some experience of being able to work slowly and deeply, and to go to deeper places, and not be told they've got five minutes to finish 20 questions. But part of it is also just the exercise of sitting there and maintaining focus for prolonged periods of time. That's not often, I mean, that's a skill. It's a skill that also could be discouraging. Like if you don't practice it, just sitting down for 10 minutes straight and maintaining deep focus could be exceptionally challenging like if you're really thinking about a problem. And I think it's really important to realize that that's a skill that you can, just like a muscle you can build, you can start with five minutes and it goes to 10 minutes to 30 and to an hour. And to be successful, I think in certain subjects like mathematics, you wanna be able to develop that skill. Otherwise, you're not going to get to the really rewarding experience of solving these problems. Definitely. There was a survey done of kids in school where they were asked, how long will you work on a maths problem before you give up and decide it's not possible to solve it? And the result on average across the kids was two minutes. Yeah, that's a bad sign, but that was a powerful sign that they need to learn to not give up so quickly. We mentioned offline, because we've been talking so much about visualization, Grant Sanderson through Llewelyn Brown. So he's inspired millions of people with exactly the kind of way of thinking that you've been talking about. Yeah, I love his work. Converting sort of mathematical concepts into visual, like visually representing them, exploring them in ways that help you illuminate like the concepts. What do you think is the role of that? So he uses mostly programmatic visualizations. So it's the thing I mentioned where there's like animations created by writing computer programs. Like, what do you think, how scalable is that approach? But in general, what do you think about his approach? I think it's amazing. I should work with him. I can share some of our visuals and he can make them in that amazing way. So part of his storytelling, part of it is like, it's creating the visuals and then weaving a story with those visuals that kind of builds. Like there's also, I mean, there's also drama in it. You start with a small example and then you kind of, all of a sudden there's a surprise. Yeah, yeah, yeah. And it really, I mean, it makes you fall in love with the concept. He does talk about that. His sense is like some of the stuff, he doesn't feel like he's teaching, like the core curriculum, which is something, he sees himself as an inspirational figure, but because I think it's too difficult to kind of convert all of the curriculum into those elements. And probably you don't need to. I mean, if people get to experience mathematical ideas in the way that he shares them, that will change them and it will change the way they think. And maybe they could go on to take some other mathematical idea and make it that beautiful. Well, he does that. He created a library called Manum and he open sourced it. And that library is the, people should check it out. It's written in Python and uses some of those same elements. Like it allows you to animate equations and animate little shapes, like people that, he has a very distinct style in his videos and what that resulted in, even though from a software engineer perspective, the code you release is not like super well-documented or perfect, but him releasing that, now there's all of these people educating it. And the cool, to me personally, the coolest thing is to see like people, they're not, don't have like a million subscribers or something is they have just a few views in the video, but it just seems like the process of them creating a video where they teach is like transformative to them from a student perspective. It's the old Feynman thing, the best way to learn is to teach. And then him releasing that into the wild is, it shows that impact. Yeah, absolutely. I think just giving people that idea that you can do that with maths and other subjects, there's bound to be people all around who can create more, which is cool. Yeah, I definitely, so I recommend people do like JavaScript or Python. You can build like visualizations of most concepts in high school math. You can do a lot of kinds of visualizations and doing that yourself. Plus if you do that yourself, people will really love it. People actually, people love visualizations of math. Yeah. Because they, I mean, it's something in us that loves patterns, loves figuring out difficult things and the patterns in there then are unexpected in some way. Yeah, have you ever noticed that hotels are always filled with patterns? I was just noticing it at the hotel I'm in now. All of their carpets are pattern carpets and then they have patterns on the walls. Yeah. So, yeah. We humans love the symmetry in patterns, the breaking of symmetry in patterns. Yeah. And it's funny that we don't see mathematics as somehow intricately connected to that, but it is, right? I mean, that's one of the perspectives I love students to take is to be a pattern seeker. In everything. Yeah, certainly in all of maths. I mean, you can think of all of maths as a kind of subject of patterns and not just visual patterns, but when you think about multiplying by five and the fact you can, if you're multiplying 18 times five, you can instead think of nine times 10. That's a pattern that always works in mathematics. You can have a number and double the number. And so, yeah, I just think there are patterns everywhere. And if kids are thinking their role is to see patterns and find patterns, it's really exciting. What do you think about like MIT OpenCourseWare and the release of lectures by universities? I think it's good. I think it's good. I think that is what started the MOOC I did was using that platform. So you ultimately think like the Udacity models is a little bit more effective than just a plain two-hour lecture? I think there's definitely, you can bring in good pedagogy into online learning. And I think the idea of putting things online so that people all over the world can access them is great. I don't think the initial excitement around MOOCs, sort of democratizing education and make it more equal, came about because they found that the people taking MOOCs tended to be the more privileged people. So that was, I think there's still something to be found in that. There's still more to be done to help that online learning reach those principles. But definitely I think it's a good invention. And I have an online class that's for kids that's a little free class that gives them- What's the topic? It's called How to Learn Maths. How to Learn Maths. It shows maths as this visual creative subject and it shares mindset and some brain science. And kids who take it do better in maths class. We've studied it with like randomized controlled trials and given it to middle school kids and other middle school kids who don't take it but are taught by the same teachers. So their teachers are the same. And the kids who take the online class end up 68% more engaged in their maths class and do better at the end of the year. So that's a little six session, 15 minute class and it changes kids' maths relationships. So it is true that we can do that with some words that aren't, it's not a huge change to the education system. Do you have advice for young people? We've been talking about mathematics quite a bit but in terms of their journey through education, through their career choices, through life, maybe middle school, high school, undergrad students of how to live a life they can be proud of. I think if I were to give advice to people, especially young people, my advice would be to always, it sounds really corny, but always believe in yourself and know that you can achieve because although that sounds like obvious, of course we want kids to know that they can achieve things. I know that millions of kids are in the school system have been given the message that they cannot do things and adults too. They have the idea, oh, I did okay in this, I went into this job because those other things I could never have done okay in. So actually when they hear, hey, maybe you could do those other things, even adults think, you know, maybe I can and they go back and they encounter this knowledge and they relearn things and they change careers and amazing things happen. So for me, I think that message is really important. You can learn anything. Scientists try and find a limit. They're always trying to find a limit. Like how much can you really learn? What's the limit to how much you can learn? And they always come away not being able to find it. People can just go further and further and further. And that is true of people born with brain, you know, areas of their brain that aren't functioning well that have what we call special needs. Some of those people also go on to develop and do amazing things. So I think that really experiencing that, knowing that, not just saying it, but knowing it deeply, you can learn anything, is something I wish all people would have. Actually also applies when you've achieved some level of success too. What I find, like in my life with people that love me, when you achieve success, they keep celebrating your success and they want you to keep doing the thing that you were successful at, as opposed to believing in that you can do something else, something big, whatever your heart says to do. And one of the things that I realized the value of this, you know, quite recently, which is sad to say, is how important it is to seek out, when you're younger, to seek out mentors, to seek out the people, like surround yourself with people that will believe in you. It's like a little bit is on you. It's like, you don't get that, sometimes if you go to like grad school, you think you kind of land on a mentor, maybe you pick a mentor based on the topic they're interested in. But the reality is the people you surround yourself with, they're going to define your life trajectory. So select people that- That's really true. And get away from people who don't believe in you. Sometimes parents can be that. They can love you deeply, but they set, it's the math thing we mentioned, they might set certain constraints on the beliefs that you have. And so in that, if you're interested in mathematics and your parents are not that interested in it, don't listen to your parents on that one dimension. Exactly. Yeah, and if people tell you you can't do things, you have to hear from other people who believe in you. I think you're absolutely right about that. It's so sad the number of people who've had those negative messages from parents. In my Limitless Mind book, I interviewed quite a few people who'd been told they couldn't do math, sometimes by parents, sometimes by teachers. And fortunately, they had got other ideas at some point in their life and realized there was this whole world of mathematical thinking that was open to them. So it's really important that people do connect with people who believe in them. However hard that might be to find those people. What do you hope the education system, education in general, looks like 10, 20, 50, 100 years from now? Are you optimistic about this future? Yeah, I definitely have hope. There is, change can happen in the education system. In recent years, it's been microscopically slow. But I do actually see change happening. Like we were talking earlier that data science is now a course you can take in high school instead of algebra two. And that's pretty amazing because that content was set out in 1892 and hasn't changed since then. And so now we're actually seeing a change in the content of high school. So I'm amazed that that's happening and very happy it's happening. So change is very slow in education usually, but when you look ahead and think about all that we know and all that we can offer kids in terms of technology, you've got to think that 100 years from now, education will be totally different to the way it is now. Maybe we won't have subject boundaries anymore because those don't really make much sense. And it's interesting to think how certain tools like programming, maybe they'll be deeply integrated in everything we do. You would think, yeah. You would think that all kids are growing up learning to program and create. So I just think, I mean, the system of schooling we have now, people call it a factory model. It's not designed to inspire creativity. And I feel like that will also change. People might look back on these days and think they were hilarious, but maybe in the future, kids will be doing their own programming and they'll be able to learn things and find out things and create things even as they're learning. And maybe the individual subjects boundaries will go. Data science itself coming into the education system kind of illustrates that because people realize it doesn't really fit inside any of the subjects. So what do we do with it? Where does it go? And who teaches it? So it's already raising those kind of questions and questioning how we have these different subject boundaries. So you've seen data science be integrated into the curriculum? Yes, it's happening across the United States as we speak. I wonder how they got initiated. Like how does change happen in the education system? Is it just a few revolutionary leaders? I think so. I think so. It's been an interesting journey seeing data science take off actually. There was a course that was developed in 2014 by some people who thought data science was a good idea for high schoolers. And then after some kids took the course and nothing bad happened to them, they went to college and people started to accept it more. And then this was a big piece of the change in California. The UC system communicated. They sent out an email last year to 50,000 high schools saying, we now accept data science. Kids can take it instead of algebra two. That's a perfectly legitimate college pathway. So that was like a big green light for a lot of schools who were like wondering about whether they could teach it. So I think it happens in small spaces and expands. So now- It goes viral. Yeah. In this modern age. Then it goes viral. California's ahead, I think, in creating courses and having kids go through it. But it's, certainly when I last looked, there were 12 states that were allowing data science as a high school course. And I think by next year, that will have doubled or more. So change is happening. Joe, as I said, I think mathematics is truly a beautiful subject. And you having an impact on millions of people's lives by educating them, by inspiring teachers to educate in the ways that you've talked about, in multi-dimensional ways, in visual ways, I think is incredible. So you're spreading beauty into the world. I really appreciate that. So I really, really appreciate that you spent your valuable time with me today. Thank you for talking. Thank you. It was really good to talk to you. Thanks for listening to this conversation with Joe Bowler. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Albert Einstein. Pure mathematics is the poetry of logical ideas. Thanks for listening and hope to see you next time.

https://youtu.be/KZnGSVwIpeU

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Yoshua Bengio: Deep Learning | Lex Fridman Podcast #4

What difference between biological neural networks and artificial neural networks is most mysterious, captivating, and profound for you? First of all, there's so much we don't know about biological neural networks. And that's very mysterious and captivating because maybe it holds the key to improving artificial neural networks. One of the things I studied recently, something that we don't know how biological neural networks do but would be really useful for artificial ones, is the ability to do credit assignment through very long time spans. There are things that we can, in principle, do with artificial neural nets, but it's not very convenient and it's not biologically plausible. And this mismatch, I think, this kind of mismatch, may be an interesting thing to study to A, understand better how brains might do these things because we don't have good corresponding theories with artificial neural nets, and B, maybe provide new ideas that we could explore about things that brain do differently and that we could incorporate in artificial neural nets. So let's break credit assignment up a little bit. So what, it's a beautifully technical term, but it could incorporate so many things. So is it more on the RNN memory side, thinking like that, or is it something about knowledge, building up common sense knowledge over time, or is it more in the reinforcement learning sense that you're picking up rewards over time for a particular, to achieve a certain kind of goal? So I was thinking more about the first two meanings whereby we store all kinds of memories, episodic memories in our brain, which we can access later in order to help us both infer causes of things that we are observing now and assign credit to decisions or interpretations we came up with a while ago when those memories were stored. And then we can change the way we would have reacted or interpreted things in the past, and now that's credit assignment used for learning. So in which way do you think artificial neural networks, the current LSTM, the current architectures are not able to capture the, presumably you're thinking of very long-term? Yes, so current nets are doing a fairly good jobs for sequences with dozens or say hundreds of time steps, and then it gets sort of harder and harder, and depending on what you have to remember and so on, as you consider longer durations. Whereas humans seem to be able to do credit assignment through essentially arbitrary times, like I could remember something I did last year, and then now because I see some new evidence, I'm gonna change my mind about the way I was thinking last year, and hopefully not do the same mistake again. I think a big part of that is probably forgetting. You're only remembering the really important things. That's very efficient forgetting. Yes, so there's a selection of what we remember, and I think there are really cool connection to higher level cognition here regarding consciousness, deciding, and emotions, so deciding what comes to consciousness and what gets stored in memory, which are not trivial either. So you've been at the forefront there all along, showing some of the amazing things that neural networks, deep neural networks can do in the field of artificial intelligence, which is just broadly in all kinds of applications, but we can talk about that forever, but what in your view, because we're thinking towards the future, is the weakest aspect of the way deep neural networks represent the world? What is in your view is missing? So current state-of-the-art neural nets trained on large quantities of images or texts have some level of understanding of what explains those data sets, but it's very basic. It's very low level, and it's not nearly as robust and abstract and general as our understanding. Okay, so that doesn't tell us how to fix things, but I think it encourages us to think about how we can maybe train our neural nets differently so that they would focus, for example, on causal explanation, something that we don't do currently with neural net training. Also, one thing I'll talk about in my talk this afternoon is instead of learning separately from images and videos on one hand and from texts on the other hand, we need to do a better job of jointly learning about language and about the world to which it refers so that both sides can help each other. We need to have good world models in our neural nets for them to really understand sentences which talk about what's going on in the world. And I think we need language input to help provide clues about what high level concepts, like semantic concepts, should be represented at the top levels of these neural nets. In fact, there is evidence that the purely unsupervised learning of representations doesn't give rise to high level representations that are as powerful as the ones we're getting from supervised learning. And so the clues we're getting just with the labels, not even sentences, is already very powerful. Do you think that's an architecture challenge or is it a data set challenge? Neither. I'm tempted to just end it there. End it there, but you elaborated slightly. Yes. Of course, data sets and architectures are something you wanna always play with, but I think the crucial thing is more the training objectives, the training frameworks. For example, going from passive observation of data to more active agents, which learn by intervening in the world the relationships between causes and effects, the sort of objective functions which could be important to allow the highest level explanations to rise from the learning, which I don't think we have now, the kinds of objective functions which could be used to reward exploration, the right kind of exploration. So these kinds of questions are neither in the data set nor in the architecture, but more in how we learn under what objectives and so on. Yeah, I've heard you mention in several contexts the idea of sort of the way children learn they interact with objects in the world. And it seems fascinating because in some sense, except with some cases in reinforcement learning, that idea is not part of the learning process in artificial neural networks. It's almost like, do you envision something like an objective function saying, you know what, if you poke this object in this kind of way, it would be really helpful for me to further learn. Sort of almost guiding some aspect of learning. So I was talking to Rebecca Sachs just an hour ago, and she was talking about lots and lots of evidence from infants seem to clearly pick what interests them in a directed way. And so they're not passive learners. They focus their attention on aspects of the world which are most interesting, surprising in a non-trivial way that makes them change their theories of the world. So that's a fascinating view of the future progress. But on a more maybe boring question, do you think going deeper and larger, so do you think just increasing the size of the things that have been increasing a lot in the past few years will also make significant progress? So some of the representational issues that you mentioned, they're kind of shallow in some sense. Understanding prior. Oh, shallow, you mean in the sense of abstraction? In the sense of abstraction. They're not getting some, like you said. I don't think that having more depth in the network in the sense of instead of 100 layers, we have 10,000 is going to solve our problem. You don't think so? No. Is that obvious to you? Yes. What is clear to me is that engineers and companies and labs and grad students will continue to tune architectures and explore all kinds of tweaks to make the current state of the art slightly ever slightly better. But I don't think that's gonna be nearly enough. I think we need some fairly drastic changes in the way that we're considering learning to achieve the goal that these learners actually understand in a deep way the environment in which they are observing and acting. But I guess I was trying to ask a question that's more interesting than just more layers. It's basically once you figure out a way to learn through interacting, how many parameters does it take to store that information? So I think our brain is quite bigger than most neural networks. Right, right, oh, I see what you mean. Oh, I'm with you there. So I agree that in order to build neural nets with the kind of broad knowledge of the world that typical adult humans have, probably the kind of computing power we have now is gonna be insufficient. So, well, the good news is there are hardware companies building neural net chips, and so it's gonna get better. However, the good news in a way, which is also a bad news, is that even our state-of-the-art deep learning methods fail to learn models that understand even very simple environments like some grid worlds that we have built. Even these fairly simple environments, I mean, of course, if you train them with enough examples, eventually they get it, but it's just like, instead of what humans might need, just dozens of examples, these things will need millions, right, for very, very, very simple tasks. And so I think there's an opportunity for academics who don't have the kind of computing power that, say, Google has to do really important and exciting research to advance the state-of-the-art in training frameworks, learning models, agent learning in even simple environments that are synthetic, that seem trivial, but yet current machine learning fails on. We talked about priors and common sense knowledge. It seems like we humans take a lot of knowledge for granted. So what's your view of these priors of forming this broad view of the world, this accumulation of information, and how we can teach neural networks or learning systems to pick that knowledge up? So knowledge, for a while, the artificial intelligence was maybe in the 80s, like, there's a time where knowledge representation, knowledge acquisition, expert systems, I mean, the symbolic AI was a view, was an interesting problem set to solve, and it was kind of put on hold a little bit, it seems like. Because it doesn't work. It doesn't work, that's right. But the goals of that- Remain important. Yes, remain important. And how do you think those goals can be addressed? Right, so first of all, I believe that one reason why the classical expert systems approach failed is because a lot of the knowledge we have, so you talked about common sense, intuition, there's a lot of knowledge like this, which is not consciously accessible. There are lots of decisions we're taking that we can't really explain, even if sometimes we make up a story. And that knowledge is also necessary for machines to take good decisions. And that knowledge is hard to codify in expert systems, rule-based systems, and classical AI formalism. And there are other issues, of course, with the old AI, like not really good ways of handling uncertainty. I would say something more subtle, which we understand better now, but I think still isn't enough in the minds of people. There's something really powerful that comes from distributed representations, the thing that really makes neural nets work so well. And it's hard to replicate that kind of power in a symbolic world. The knowledge in expert systems and so on is nicely decomposed into a bunch of rules, whereas if you think about a neural net, it's the opposite. You have this big blob of parameters which work intensely together to represent everything the network knows, and it's not sufficiently factorized. And so I think this is one of the weaknesses of current neural nets, that we have to take lessons from classical AI in order to bring in another kind of compositionality, which is common in language, for example, and in these rules, but that isn't so native to neural nets. And on that line of thinking, disentangled representations. Yes. So let me connect with disentangled representations, if you might, if you don't mind. Yes, exactly. So for many years, I've thought, and I still believe, that it's really important that we come up with learning algorithms, either unsupervised or supervised, but, or reinforcement, whatever, that build representations in which the important factors, hopefully causal factors, are nicely separated and easy to pick up from the representation. So that's the idea of disentangled representations. It says, transform the data into a space where everything becomes easy. We can maybe just learn with linear models about the things we care about. And I still think this is important, but I think this is missing out on a very important ingredient, which classical AI systems can remind us of. So let's say we have these disentangled representations. You still need to learn about the relationships between the variables, those high-level semantic variables. They're not gonna be independent. I mean, this is like too much of an assumption. They're gonna have some interesting relationships that allow to predict things in the future, to explain what happened in the past. The kind of knowledge about those relationships in a classical AI system is encoded in the rules. Like a rule is just like a little piece of knowledge that says, oh, I have these two, three, four variables that are linked in this interesting way, then I can say something about one or two of them given a couple of others. In addition to disentangling the elements of the representation, which are like the variables in a rule-based system, you also need to disentangle the mechanisms that relate those variables to each other. So like the rules. So the rules are neatly separated. Like each rule is living on its own. And when I change a rule, because I'm learning, it doesn't need to break other rules. Whereas current neural nets, for example, are very sensitive to what's called catastrophic forgetting where after I've learned some things and then I learn new things, they can destroy the old things that I had learned. If the knowledge was better factorized and separated, disentangled, then you would avoid a lot of that. Now you can't do this in the sensory domain, but my idea- What do you mean by sensory domain? Like in pixel space. But my idea is that when you project the data in the right semantic space, it becomes possible to now represent this extra knowledge beyond the transformation from input to representations, which is how representations act on each other and predict the future and so on, in a way that can be neatly disentangled. So now it's the rules that are disentangled from each other and not just the variables that are disentangled from each other. And you draw a distinction between semantic space and pixel. Like does there need to be an architectural difference? Well, yeah. So there's the sensory space like pixels, which where everything is entangled. The information, like the variables, are completely interdependent in very complicated ways. And also computation, like it's not just variables, it's also how they are related to each other is all intertwined. But I'm hypothesizing that in the right high-level representation space, both the variables and how they relate to each other can be disentangled and that will provide a lot of generalization power. Generalization power. Yes. Distribution of the test set. Yes. It's assumed to be the same as the distribution of the training set. Right. This is where current machine learning is too weak. It doesn't tell us anything, is not able to tell us anything about how our neural nets, say, are gonna generalize to a new distribution. And people may think, well, but there's nothing we can say if we don't know what the new distribution will be. The truth is humans are able to generalize to new distributions. How are we able to do that? So- Yeah, because there is something, these new distributions, even though they could look very different from the training distributions, they have things in common. So let me give you a concrete example. You read a science fiction novel. The science fiction novel maybe, you know, brings you in some other planet where things look very different on the surface, but it's still the same laws of physics. Right, and so you can read the book and you understand what's going on. So the distribution is very different, but because you can transport a lot of the knowledge you had from Earth about the underlying cause and effect relationships and physical mechanisms and all that, and maybe even social interactions, you can now make sense of what is going on on this planet where like visually, for example, things are totally different. Taking that analogy further and distorting it, let's enter a science fiction world of say Space Odyssey 2001 with Hal. Yeah. Or maybe, which is probably one of my favorite AI movies. And then- Yeah. And then there's another one that a lot of people love that maybe a little bit outside of the AI community is Ex Machina. Right. I don't know if you've seen it. Yes, yes. By the way, what are your views on that movie? Does it, are you able to enjoy it? So there are things I like and things I hate. So let me, you could talk about that in the context of a question I want to ask, which is there's quite a large community of people from different backgrounds, often outside of AI, who are concerned about existential threat of artificial intelligence. Right. You've seen this community develop over time, you've seen, you have a perspective. So what do you think is the best way to talk about AI safety, to think about it, to have discourse about it within AI community and outside and grounded in the fact that Ex Machina is one of the main sources of information for the general public about AI? So I think you're putting it right. There's a big difference between the sort of discussion we ought to have within the AI community and the sort of discussion that really matter in the general public. So I think the picture of Terminator and AI loose and killing people and super intelligence that's gonna destroy us, whatever we try, isn't really so useful for the public discussion because for the public discussion, the things I believe really matter are the short term and medium term, very likely negative impacts of AI on society, whether it's from security, like Big Brother scenarios with face recognition or killer robots, or the impact on the job market, or concentration of power and discrimination, all kinds of social issues, which could actually, some of them could really threaten democracy, for example. Just to clarify, when you said killer robots, you mean autonomous weapon, like the weapon systems, but not Terminator. That's right. So I think these short and medium term concerns should be important parts of the public debate. Now, existential risk for me is a very unlikely consideration, but still worth academic investigation in the same way that you could say, should we study what could happen if a meteorite came to earth and destroyed it? So I think it's very unlikely that this is gonna happen or happen in a reasonable future. The sort of scenario of an AI getting loose goes against my understanding of at least current machine learning and current neural nets and so on. It's not plausible to me. But of course, I don't have a crystal ball and who knows what AI will be in 50 years from now. So I think it is worth that scientists study those problems. It's just not a pressing question as far as I'm concerned. So before I continue down that line, I have a few questions there, but what do you like and not like about Ex Machina as a movie? Because I actually watched it for the second time and enjoyed it, I hated it the first time, and I enjoyed it quite a bit more the second time when I sort of learned to accept certain pieces of it. You see it as a concept movie. What was your experience? What were your thoughts? So the negative is the picture it paints of science is totally wrong. Science in general and AI in particular. Science is not happening in some hidden place by some really smart guy. One person. One person. This is totally unrealistic. This is not how it happens. Even a team of people in some isolated place will not make it. Science moves by small steps thanks to the collaboration and community of a large number of people interacting. And all the scientists who are expert in their field kind of know what is going on even in the industrial labs. It's information flows and leaks and so on. And the spirit of it is very different from the way science is painted in this movie. Yeah, let me ask on that point. It's been the case to this point that kind of even if the research happens inside Google or Facebook, inside companies, it still kind of comes out, ideas come out. Do you think that will always be the case with AI? Is it possible to bottle ideas to the point where there's a set of breakthroughs that go completely undiscovered by the general research community? Do you think that's even possible? It's possible, but it's unlikely. Unlikely. It's not how it is done now. It's not how I can foresee it in the foreseeable future. But of course, I don't have a crystal ball. And so who knows? This is science fiction after all. But usually science- I think it's ominous that the lights went off during that discussion. So the problem, again, there's a, one thing is the movie and you could imagine all kinds of science fiction. The problem for me, maybe similar to the question about existential risk, is that this kind of movie paints such a wrong picture of what is actual, the actual science and how it's going on, that it can have unfortunate effects on people's understanding of current science. And so that's kind of sad. There's an important principle in research, which is diversity. So in other words, research is exploration. Research is exploration in the space of ideas. And different people will focus on different directions. And this is not just good, it's essential. So I'm totally fine with people exploring directions that are contrary to mine or look orthogonal to mine. I am more than fine. I think it's important. I and my friends don't claim we have universal truth about what will, especially about what will happen in the future. Now, that being said, we have our intuitions and then we act accordingly, according to where we think we can be most useful and where society has the most to gain or to lose. We should have those debates and not end up in a society where there's only one voice and one way of thinking and research money is spread out. So disagreement is a sign of good research, good science. Yes. The idea of bias in the human sense of bias. Yeah. How do you think about instilling in machine learning something that's aligned with human values in terms of bias? We intuitively as human beings have a concept of what bias means, of what a fundamental respect for other human beings means. But how do we instill that into machine learning systems, do you think? So I think there are short-term things that are already happening. And then there are long-term things that we need to do. In the short term, there are techniques that have been proposed and I think will continue to be improved and maybe alternatives will come up to take data sets in which we know there is bias, we can measure it. Pretty much any data set where humans are being observed, taking decisions will have some sort of bias, discrimination against particular groups and so on. And we can use machine learning techniques to try to build predictors, classifiers that are gonna be less biased. We can do it, for example, using adversarial methods to make our systems less sensitive to these variables we should not be sensitive to. So these are clear, well-defined ways of trying to address the problem. Maybe they have weaknesses and more research is needed and so on. But I think in fact, they're sufficiently mature that governments should start regulating companies where it matters, say like insurance companies, so that they use those techniques because those techniques will probably reduce the bias but at a cost. For example, maybe their predictions will be less accurate and so companies will not do it until you force them. All right, so this is short-term. Long-term, I'm really interested in thinking of how we can instill moral values into computers. Obviously, this is not something we'll achieve in the next five or 10 years. How can we, you know, there's already work in detecting emotions, for example, in images, in sounds, in texts, and also studying how different agents interacting in different ways may correspond to patterns of say injustice, which could trigger anger. So these are things we can do in the medium term and eventually train computers to model, for example, how humans react emotionally. I would say the simplest thing is unfair situations which trigger anger. This is one of the most basic emotions that we share with other animals. I think it's quite feasible within the next few years so we can build systems that can detect these kinds of things to the extent, unfortunately, that they understand enough about the world around us, which is a long time away, but maybe we can initially do this in virtual environments. So you can imagine like a video game where agents interact in some ways and then some situations trigger an emotion. I think we could train machines to detect those situations and predict that the particular emotion, you know, will likely be felt if a human was playing one of the characters. You have shown excitement and done a lot of excellent work with unsupervised learning, but on a super, you know, there's been a lot of success on the supervised learning side. Yes, yes. And one of the things I'm really passionate about is how humans and robots work together. And in the context of supervised learning, that means the process of annotation. Do you think about the problem of annotation of put in a more interesting way is humans teaching machines? Is there- Yes, I think it's an important subject. Reducing it to annotation may be useful for somebody building a system tomorrow, but longer term, the process of teaching, I think is something that deserves a lot more attention from the machine learning community. So there are people who've coined the term machine teaching. So what are good strategies for teaching a learning agent? And can we design, train a system that is gonna be a good teacher? So in my group, we have a project called a BBI or a BBI game where there is a game or a scenario where there's a learning agent and a teaching agent. Presumably the teaching agent would eventually be a human, but we're not there yet. And the role of the teacher is to use its knowledge of the environment, which it can acquire using whatever way, brute force, to help the learner learn as quickly as possible. So the learner is gonna try to learn by itself, maybe using some exploration and whatever, but the teacher can choose, can have an influence on the interaction with the learner so as to guide the learner, maybe teach it the things that the learner has most trouble with, or just add the boundary between what it knows and doesn't know and so on. So there's a tradition of these kind of ideas from other fields, like tutorial systems, for example, and AI, and of course people in the humanities have been thinking about these questions, but I think it's time that machine learning people look at this because in the future, we'll have more and more human-machine interaction with a human in a loop, and I think understanding how to make this work better. All the problems around that are very interesting and not sufficiently addressed. You've done a lot of work with language too. What aspect of the traditionally formulated Turing test, a test of natural language understanding and generation, in your eyes, is the most difficult of conversation? What, in your eyes, is the hardest part of conversation to solve for machines? So I would say it's everything having to do with the non-linguistic knowledge, which implicitly you need in order to make sense of sentences. Things like the Winograd schema, so these sentences that are semantically ambiguous. In other words, you need to understand enough about the world in order to really interpret properly those sentences. I think these are interesting challenges for machine learning because they point in the direction of building systems that both understand how the world works and its causal relationships in the world, and associate that knowledge with how to express it in language, either for reading or writing. You speak French? Yes, it's my mother tongue. It's one of the romance languages. Do you think passing the Turing test and all the underlying challenges we just mentioned depend on language? Do you think it might be easier in French than it is in English? No. Or is it independent of language? I think it's independent of language. I would like to build systems that can use the same principles, the same learning mechanisms to learn from human agents whatever their language. Well, certainly us humans can talk more beautifully and smoothly in poetry. So I'm Russian originally. I know poetry in Russian is maybe easier to convey complex ideas than it is in English. But maybe I'm showing my bias, and some people could say that about French. But of course, the goal ultimately is our human brain is able to utilize any kind of those languages to use them as tools to convey meaning. Yeah, of course there are differences between languages, and maybe some are slightly better at some things. But in the grand scheme of things, where we're trying to understand how the brain works and language and so on, I think these differences are minute. So you've lived perhaps through an AI winter of sorts. Yes. How did you stay warm and continue your research? Stay warm with friends. With friends, okay. So it's important to have friends. And what have you learned from the experience? Listen to your inner voice. Don't be trying to just please the crowds and the fashion. And if you have a strong intuition about something that is not contradicted by actual evidence, go for it. I mean, it could be contradicted by people. Not your own instinct of based on everything you've learned. So of course you have to adapt your beliefs when your experiments contradict those beliefs. But you have to stick to your beliefs, otherwise it's what allowed me to go through those years. It's what allowed me to persist in directions that took time, whatever other people think, took time to mature and bring fruits. So history of AI is marked with these, of course it's marked with technical breakthroughs, but it's also marked with these seminal events that capture the imagination of the community. Most recent, I would say AlphaGo beating the world champion human Go player was one of those moments. What do you think the next such moment might be? Okay, so first of all, I think that these so-called seminal events are overrated. As I said, science really moves by small steps. Now what happens is you make one more small step and it's like the drop that fills the bucket and then you have drastic consequences because now you're able to do something you were not able to do before. Or now say the cost of building some device or solving a problem becomes cheaper than what existed and you have a new market that opens up. So especially in the world of commerce and applications, the impact of a small scientific progress could be huge. But in the science itself, I think it's very, very gradual. Where are these steps being taken now? So there's unsupervised learning. If I look at one trend that I like in my community, so for example, at Miele, my institute, what are the two hottest topics? GANs and reinforcement learning. Even though in Montreal in particular, like reinforcement learning was something pretty much absent just two or three years ago. So there's really a big interest from students and there's a big interest from people like me. So I would say this is something where we're gonna see more progress, even though it hasn't yet provided much in terms of actual industrial fallout. Like even though there's AlphaGo, there's no, like Google is not making money on this right now. But I think over the longterm, this is really, really important for many reasons. So in other words, I would say reinforcement learning may be more generally agent learning because it doesn't have to be with rewards. It could be in all kinds of ways that an agent is learning about its environment. Now, reinforcement learning you're excited about, do you think GANs could provide something, Yes. Some moment in- Well, GANs or other generative models, I believe will be crucial ingredients in building agents that can understand the world. A lot of the successes in reinforcement learning in the past has been with policy gradient where you just learn a policy, you don't actually learn a model of the world. But there are lots of issues with that. And we don't know how to do model-based RL right now, but I think this is where we have to go in order to build models that can generalize faster and better like to new distributions that capture, to some extent, at least the underlying causal mechanisms in the world. Last question. What made you fall in love with artificial intelligence? If you look back, what was the first moment in your life when you were fascinated by either the human mind or the artificial mind? You know, when I was an adolescent, I was reading a lot and then I started reading science fiction. There you go. I got, that's it, that's where I got hooked. And then I had one of the first personal computers and I got hooked in programming. And so it just, you know. Start with fiction and then make it a reality. That's right. Yoshua, thank you so much for talking to me. My pleasure.

https://youtu.be/azOmzumh0vQ

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Ben Askren: Wrestling and MMA | Lex Fridman Podcast #242

The following is a conversation with Ben Askren, wrestler, MMA fighter, and a brilliant, opinionated, and fun personality in the world of martial arts. And yes, he occasionally likes to talk a little trash. Given his wild online antics and his boxing match with Jake Paul, some people may forget just how dominant he was in the sport of wrestling and in MMA for most of his career. In wrestling, he is a two-time NCAA Division I National Champion and four-time finalist. In mixed martial arts, he went undefeated for 10 years with a record of 19-0 before losing to Jorge Masvidal with a flying knee that caught everyone by surprise. He is also into cryptocurrency, disc golf, and is the co-host of Flow Wrestling Radio Live. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Ben Askren. Before we talk about your incredible wrestling career, your MMA career, let me ask you, I have to ask you, what did you think about the Jake Paul versus Tyron Woodley fight? Well, I thought, I mean, I'm obviously biased. I thought Tyron won. I had five rounds of three. Again, maybe this is my bias in the way I was seeing it. I thought he was more effective with the striking and he was more aggressive and Jake had more volume. But that was the only thing I would give him. And I guess a lot of people just didn't see it that way. They thought he landed more, significantly more punches. I just didn't think he really did any damage. It was a split decision? Split decision, yeah. Were you surprised? Well, it was the thing, so the thing I said when I went in to fight him, I said, we don't really, maybe he's good, maybe he's not. We really have no idea to this point. And so I knew Tyron was a lot better at boxing than I was. And so I thought, okay, Tyron's, I think it's a good likelihood that Tyron beats him up. But there's a chance that Jake's kind of good at this. And I think that's kind of what played out is he's kind of good at it. Even if you saw it the way I saw it, he still was impressive in his showing and he's obviously put a lot of time into it. So he's not bad. We'll say that much. But isn't it surprising to you that like a elite level athlete, combat athlete, lost to somebody who just takes it really seriously, but is nevertheless not elite level? I think boxing is a really specific rule set. So I'll speak about Tyron, not myself. Tyron had good striking, but obviously it was his first boxing match ever. And within mixed martial arts, you have the fear of the takedown and the fear of the kick and fear of other things to go along with the punching. And so if you look at Tyron throughout his MMA career, a lot of times what set up his punches were like level change fakes at a takedown, they dropped, boom, and then something comes over the top. Right? So there's many more elements to worry about in mixed martial arts. Whereas boxing, there's only one. It was his first fight. Yes, I thought Tyron was going to win. I thought this was going to happen. But like I said, I mean, it's pretty evident that Jake's, he's not bad at boxing. He's pretty solid. He gets in there and works hard at it, I guess. Out of 10 times, how many times do you think Jake wins? I guess Tyron? I guess Tyron. They fight again and again and again, like iterative. Yeah. So I mean, part of the thing is, okay, so Jake's corner said you need a knockout going into the eighth round, right? So I think they thought, maybe they're trying to motivate him, but I don't see it that way because if they were actually thought that he was winning, why would they encourage him to take a dumb risk when Tyron has clearly his knockout power, right? That's a really stupid coaching philosophy, if that's what you're thinking. So you obviously are thinking, hey, this is actually in the balance. It's competitive. And I feel like Tyron thought maybe he was winning and didn't have the urgency necessary. And so I think there's a chance he turns it up a lot. Hmm. Man, I would want to watch him again before I... So I have this problem with my personality. Here's my personality, Lex. I have an issue with not being able to give really exact answers. So I hate giving you an answer that I don't feel like is 100% calculated. So I would like to see them go once more because I would like to see, hey, can Tyron... Because if Tyron can turn up the pace and Jake can't handle it, then I think it's an eight, one or nine, two, right? If it goes the exact same way and maybe Tyron wins a close split decision, I'm saying, oh, it's probably going to be close every single time. We're probably going to get a five to five type of thing, you know? So it's like, I feel like out of one match, it's not totally indicative of what the future is going to look like. I feel like Tyron would get a knockout and then you would still be in the same place, like not knowing what to predict. Okay. So your fight with Jake Paul, looking back, you had a little bit of time now. How would you analyze that fight? Well, I mean, the fight specifically, I got cracked with an overhand right. So I mean, it kind of sucks. I would say, and this is where I really don't care. And everyone's like, why would you do that? It tarnishes your reputation. It's like, well, I wanted to do it. I had an enjoyable time training it in the buildup. Obviously, I wasn't skillful enough to get the win. But even despite the fact that I know what happened, if someone asked me to do it again, I probably would have done it again, you know? And so the way I was thinking about when I was deciding whether to do it or not, because I got the offer, it's like, okay, is this money, can it change my life? Yeah, it could, right? It's not going to double my net worth, but it's going to add significantly, make my life easier. Number two is like when I was in high school, we used to do boxing matches for free just because we thought it was fun. We didn't have something going on Friday night. Me and my buddies would get together and we had some boxing goes on basically, and we'd punch each other in the head. So it's like for something I think is enjoyable, not going to pay me a whole bunch of money. Yeah, sure, I'll do it. Would you, do you think if you got the rematch, if you did the rematch, would you, what are the odds you win? Okay, let's say- Probably not very good. I think he's pretty good actually, and I'm not very good. Now it's probably at a low point for me because, so when I started training for that, I was like 215 pounds, which is the heaviest I've ever been. I came off my hip surgery. I literally, like when I said, yes, like I'll do it, like I had literally started working out like the week before for the first time in my, you know, since the surgery, because I wasn't able to do anything. So could I, could I perform better? Yeah. But now after watching him box Tyron, like if you ask me, Ben, can you beat Tyron? Probably not. I don't think I can beat Tyron. So- In boxing. Correct, in boxing. Yeah. So my chances of beating him, you know, and watching that card, it's like, damn, like can't it be fun to box someone who I know sucks, who I know can beat. That's what would be fun, you know, because like the training, the preparation was fun, but then obviously I got my butt kicked up, so that sucked, you know, can I swear on this podcast? Yeah, of course. Okay, well, I was going to drop an F-bomb, but I wasn't quite sure. I think that sucked is a swear. You could, you could drop all, all of the F-bombs you want. So preparation wise, do you think you were more prepared for that fight or the, the Jordan Burroughs exhibition? I mean, like how did you approach it mentally? You know? Well, the Burroughs thing, I, I obviously, it's okay. So when I retired the first time in 2017, Burroughs was the only current, like we'll say really elite level wrestler that I'd never trained with. I was really good friends with Nebraska's head of the system coach, still am. And I said, Hey, I just want, I'm going to pay my own way. I want to come down and train with Jordan because I want to see what it feels like. You know, I want to get in there and mix it up. I mix it up with David Taylor and Kyle Dake. I mean, there's just something about wrestling that I love. And so I flew myself down there in January of 2018 and I spent four days training with Jordan. It was a really good time. It gave me some great insight into how he thinks and you know, what a great champion is. What was it like training with him? Like what, can you get some insights? Like what the, like how hard is the, the live training? Is it more drilling? Is it technical? Like how does his, it seems like his style is very different than yours. So how does that match up in the room in terms of like what you learn from each other? That kind of thing. So we went full live for one, I think it was like a 12 or 15 minute go where it was just go wrestle. We did a bunch of simulated live, but obviously he had, so I was a senior in college and he was a freshman in Nebraska. And so we, our teams had dueled each other. He was obviously a lot smaller at that point in time. But he had, he had followed my career. And so when I went in there, it was like, Hey, I know you're really good at this position. What about this position? What are you trying to do? How exactly does it work? And then let's wrestle there, you know? And then, Hey, what about this position? And so we would spend 30 to 40 minutes talking about that position. On the ground or? It was like, one was a chest wrapper, one was a headlock, one was, I don't know, we call it the lightning dump. The lightning dump? Yeah, my buddy's name was Lightning Luke Smith in high school and he was the first person I saw do it. So usually when I see someone do something, then I name that move after them. Got it. I know, right? Great name. It's a good name. Yeah, but so what I said with that is like, he was still trying to be the best in the world. I was just trying to go work out with Jordan Burroughs because I enjoy wrestling. Is like someone who at that point, what he has five world titles at that four or five at that point a lot. And so I used to have my high school kids is like, Hey, this is the guy who's the best in the world. Who's bringing someone in and saying, How do I do this? How do I do that? What about this? What about that? And so the level of inquisitiveness, that's a hard word, inquisitiveness he has, is really impressive. And that is obvious why he got to the level he did, because he's figuring out all these little situations. And that's honestly one of the biggest things I think wrestlers, a lot of wrestlers fail to do as they get older, even when they get to early college age, they say, This is my style. This is what I do. I'm going to lift and work out hard. And I'm, and I'm not going to add anything to my game. You know, whereas you've seen many progressions in Jordan Burroughs game, he just made his 10th world team. And you know, if you have a really keen eye, you've been able to watch him change. You know, I've been watching him since 2007. He's changed so much, and obviously still maintained a world class level almost the entire time. When you say change, like what changed? Because he's got that double leg. Yeah, but he doesn't have that double leg anymore. Was that? He like hit his double leg for the first time against Alex Deirdre. He hadn't hit it in years. Yeah. So that's like, when people think about Jordan Burroughs, they think about the double leg, because in his early years, he had a great double leg, right? And even in the, so in those years, I would say the, the biggest thing with Jordan Burroughs' double leg wasn't his level of explosiveness. It was his level of persistence. He would shoot and shoot and shoot and shoot. And it was a lot of times would be from fun, creative angles and out of scramble, all the sudden he's on you, you know, and it was just, he was just super persistent with it. And I think that was probably the key. And then you saw, you know, when he came out to the, won the first world championship in 2011, it was kind of that type of mentality. And then shortly after then, obviously everyone was starting to lower their stance, getting lower, and he developed a really good, like, Mantis go behind series where he would go one way, the other way. Then he started developing a really good, like, low single ankle pick type thing, you know? And then his hand, his hand fighting got really tremendous, like 15, 16, 17, his hand fighting was really good. And now I just commented at the 21 trials, like a few of the defensive sequences he got into, it was like, holy shit, like just not from an athletic standpoint, but from a technical standpoint, the things he were doing were just tremendous. So I've seen him as someone like who's continued to reinvent themselves over the course of the last 10, 12 years. Especially in the, as a junior and senior in college, you're exceptionally dominant. If you were to face him at the peak, both of your peaks of NCAA wrestling, could you, could you beat him? And if you can beat him, of course you can beat him. How do you solve the Jordan Burroughs problem? Well, so for a folk style wrestling standpoint. Folk style, yes. Folk style. So, you know, he had some competitive matches as junior and senior year. He had a 2-1 win over, or maybe it was 3-2, over Michael Chandler, who was my teammate, who's fighting UFC now. He had a 2-1 win over Tyler Caldwell. So I think you can glean some insight into that. You know, he got ridden, he got so mad about this up on a podcast. So during Corona, we had to make up all kinds of bullshit to talk about. And we were doing like the last 10 years, best 165s. And I said Kyle Dake would ride him for over a minute. He got so mad, he wanted to come on the podcast the next day. So hopefully he doesn't listen to this. Fuck you, man. You know, but you know. When was this? This is during Corona. Corona, last year. He got mad. We were talking about- Before the trials. Yeah, correct. Yeah. So Michael Chandler rode him for two minutes plus. And that was his junior year, not his senior year. Sure, right. But it's close. So I think there's some things there. I think the interesting thing would be if I would have stuck around, right. So I chose to go into mixed martial arts after dozen eight. I would have been 74 and he would have been 74. So we would have had to wrestle. And then I think that the freestyle Jordan Burroughs puzzle is a lot more difficult to solve than the folk style Jordan Burroughs puzzle. And I think he would acknowledge that he's much better at freestyle than he was at folk style. Although he was very good, he's better. This is like raw speed explosiveness present a problem to you? Well, so he didn't really excel on the mat in either style. In freestyle, he has got some good lace transitions. But in folk style, his entire college career, I think he has like 10 pins, which is almost nothing. So he was gaining no value off the top position. He was good enough on most people to get off bottom without it being an issue. But it wasn't like, oh my gosh, this is an area where we really have to be careful. There's a lot of things here. He wasn't gaining value there. Whereas in freestyle, I don't want to say never, but the amount of times he gets turned is incredibly rare, very, very rare. And he does have a lace transition, so he gets a lot of points there. And obviously, freestyle is, it can be geared way more in the neutral position, right? Where we're only doing takedowns. So yeah. Were you surprised that he lost to Dake in the trials, to Kyle Dake? Oh, Kyle's so good, right? I think his performance in the Olympics was, his loss then was shocking to him. I mean, we never seen that happen to Kyle Dake. He's been a guy who's competed with Jordan Burroughs forever, and obviously he was on the losing side for a while, and now he's on the winning side. But I think a lot of people thought it was a coin flip, and I think actually Kyle Dake made it feel like it's not a coin flip. To me, it feels like Kyle Dake is going to win that match significantly more times than he isn't, is what it feels like. Yeah. I forgot which trials it was. Was it four years ago where Kyle Dake threw him? You saw inklings of like, oh wow, there might be eventually a changing of the guard. Yeah. So at 13, Kyle came out and he had the one throw, but then he lost one of the matches decisively. And then he was hurt in 14. And in 16, Kyle Dake actually went up to 86 kilograms. So actually in 16, at the trials we had, so Jake Herbert was number one seed. He was former, as Guy Russell, I was a former world silver medalist. So you had David Taylor, who had not made a team yet, who is now a world champion, Olympic champion. You had Kyle Dake in the bracket, who was a two-time world champion now. And you had Jaden Cox in the bracket, who had not made any teams yet, but is now what, a four-time world medalist, two-time world champion. So and then obviously Jaden came out on top of that, won his first Olympic medal, Olympic bronze medal. So Kyle didn't wrestle Jordan in 16. And Kyle's contention the whole time, and they argued about this. So I actually did a little bit of backstabbing. Well, it's not backstabbing. And both of them or just one of them? I didn't tell any of them. Okay. Okay. So Jordan got mad. So we talked about this fake match during Corona, right? Yeah. We had to make up something to talk about. Yeah, of course. Because there's obviously no matches. So we talked about this fake match. Do you stand behind that statement, by the way? Listen, here's what I said. Kyle Dick's four-time NCAA champion. Yes. I said, you got to pick a winner. I said, Kyle Dick wins 2-1 on a minute and six ride time, which I mean, we're talking as close as it gets, as close as it gets for Kyle Dick, who's a four-time NCAA champion. I'm sorry. I'm sorry. Are we talking- Over Jordan Burroughs. Over Jordan Burroughs. In a folks out match. In a folks out match. Hypothetically. In college or now? Completely hypothetically. Now or in college? In college. Now, I'm 165 pounds. So completely hypothetical. And so Jordan called in. He was all pissed at me for picking Kyle Dick. He wants to come on the next day and argue his point. So I said, F that. That's dumb. We had to pick a winner. We had to do something hypothetical. So then I called Kyle Dick and I said, Kyle, Jordan's going to come on and argue his case in the morning. If he's going to do that, why don't you come in and argue your case? So no one else knew Kyle was coming on the podcast. So they both show up and they went at it. But one of the contentions Kyle had for years, and there's still this rule, if you win a world level medal the following year, you sit out until the very end of the American trials and they do a best two or three. So every time previously that Kyle had wrestled Jordan, he had to come through a tournament on Saturday. Yeah. Okay. Probably three matches. And then on Sunday he would wrestle Jordan in the best two out of three. Right. So his contention was, I'm only wrestling Jordan at a disadvantage because I have to compete on Saturday and then competing on... Which it's a fair argument, it really is. But I also see USA Wrestling's point is like, if someone wins a world medal, we're going to reward them because we want that person on the team again. It's crazy though that you're like Kyle Dick had to wrestle, because he's not wrestling bums in that division. Not bums, yeah. And then, yeah, I don't know. I don't know how wrestlers do it because you have to go to war like three matches and then face Jordan Burroughs. Yeah, especially a few of those years with Daykad, the name Andrew Howe, but those were really competitive matches. David Taylor had really competitive matches with him. Isaiah Martinez even got in there, Deiranger. So he had some really competitive matches before he ever got to Jordan Burroughs. So I never answered your initial question was, how did I feel? So the Jordan Burroughs match, I was not in wrestling shape at all. Meaning, wrestling's heavily dependent, especially neutral positions, heavily dependent on timing and other things. I was wrestling very, very minimally because I started fighting again. So my athletic shape was great, but it was mainly for fighting. I wasn't wrestling. So I think they were actually trying to do Burroughs-Dayk at Beat the Streets. It's the biggest fundraiser in wrestling every single year. In New York? In New York City. They usually raise like a million dollars. They started all these programs in New York City. I really wonder what they're doing with the money now because they probably can't have the kids wrestling because New York's crazy. I think New York figures out a way what to do with the money. Hence, Michael Mal's complaining that they're corrupt and all that. But it goes to the Beat the Streets organization, who then starts the clubs in New York. So I don't know what to do with the money. So I was called two weeks before the event and said, hey, someone wants to wrestle Jordan Burroughs. It fell out. Would you wrestle him? I said, yeah, sure, why not? I trained with them for four days the year before. I had a pretty good idea how the match was going to go. It wasn't going to go so well for me. But it's like, okay, you're missing a main event. Because of where I'm at right now in my life, I can bring a lot of attention to wrestling. I can help you guys raise a bunch of money for Beat the Streets. My goal is I thought I could get one takedown or turn on him was kind of my goal for the match. I didn't get there. You went kind of hard. He went hard? Yeah, that asshole wouldn't give me a point. I said, this is bullshit, Jordan, I told him during the match, this is bullshit. You're fucking going too hard right now. I'm not a wrestler anymore. I'm a fighter. I'm coming in here. So I had a really good idea. We wrestled together. I think he'll probably get mad because I think in the live go we did, like the 12 or 15 minutes, I think I actually scored a takedown in that, I believe, maybe, or maybe it was a turn. He'll probably say, no, I didn't, but whatever. So I knew what was going to happen. I knew what the outcome was going to be. I knew I could probably, I was hoping I could stay competitive and maybe lose like 10-2 or something. Yeah. Well, let's walk back because I think I originally brought it up in terms of how prepared were you against Jake Paul versus Jordan Burroughs. So did you prepare for Jake cardio-wise? Yeah, I went hard. Yeah, I did. But it was, I told you, I started training from, I mean, once I had my hip surgery, they said for the first six weeks you can't even walk. And it was hard for me to listen to them because by week four, four and a half, five, I was feeling pretty good. I wanted to get rid of my crutches. But I'm like, you know what, this is for the rest of my life. So if you get the real hip replacement, there's no wrestling, there's no nothing. So that's the next step. So okay, I'm going to take this serious. I do my crutches for six weeks. The next six weeks, it's still like really low weight bearing, can't necessarily do anything. So then I get done with the three months, which is like January, and I'm like, okay, I should start working out. So I started riding a bike a little bit. And then, okay, now I'm fat, I'm fucking fat, I'm going to get in better shape because I haven't been able to do anything. So I'm actually start working out. And then that happened, right? So I'm like, okay, well, now I got three months and it gives me a good reason to get back in shape. And I knew I wasn't going to be a full-time boxer. So it's like, how do I put a boxing camp together? So I found, I had my old teammate, Mike Rhodes, he came up and kind of lived with me-ish kind of thing for three months. I found a guy, K9, out of Michigan. He came over three weeks. He was great. I went to Freddie Roach for a week. So I kind of like, you know, try to get as many good ideas as I could. And my thought was like, okay, well, if this dude sucks, I can just be tough and block a few punches, get him tired and then beat him up. If he's good, there's probably not much I'm going to do about it in the next three months because I was never good at boxing in the first place. All of my stand-up and mixed martial arts was predicated on how do I get through the two or three punches that are going to come at me in the time I need to get a hold of them. You know, you only have to make two or three of them miss and then boom, you're on top of them, at least for me. That was all my striking was predicated on. It wasn't about, hey, I'm going to do damage on the feet in order to make something else happen. It was like, how do I clear this barrier, get a hold of you? And I actually did the math one time. I think I got a takedown, if you include the knockout round against Miles Vidal, I got a takedown in every round except two. So it was like 53 out of 55 rounds in MMA I got a takedown. Somewhere in there. Okay. So you're hunting the takedown once you get your hands on them, you get the takedown. But the incredible thing about you, I just recently talked, spent a couple of days with Jimmy Pedro and he talked about his guys and just champions in general, hating to lose more than they love winning. And the way you talked about losing, you lost very few times in your career. Like later you were dominating both the wrestling and MMA, but the way you took these losses against people that are, I don't know, below elite level. It's fair. I'm not saying I'm going to get pissy, but it's completely fair. I thought he was a bum too. No, that's not what I meant. I'm in trouble. It's okay. No, it's good. No, no, no. But like, what, can you explain the psychology behind that? Like the, what, is there a system behind this? Is there a philosophy behind this? Well, so I wasn't very good in the beginning. I think that's where it all starts from. So I didn't start getting good until the age of like 13. I started at five. I probably started competing more at age 10, 11. I didn't really get good until 13. And still at 13, I'm, I'm, it's not like I'm great. I'm getting better. Right? I'm pretty good. So I actually, I've actually, I have writing this book on sports psych, but this it's, I got, well, I got someone to write it for me kind of thing. Cause I've had this philosophy for years that there's, there has to be this balance between two things. Right? So on the one hand, in this category, on the one hand you have hating to lose. A great champion has to hate to lose. Like you said, right? But on this other hand, you have to have someone who seeks out challenges. Right? Cause if you don't have that, you're never going to reach your full potential either. And so you have to balance these two balls at the same time. Right? And so like for me, I always, and this is maybe cause I wasn't good, but I was always like, let me go find the best people to wrestle all the time. Let me go find, I would like literally like seventh, eighth grade when I was starting to get better, it was like, and this was on the internet. Well, there's no one was using the internet. It was like a wrestling magazine and be like, Hey dad, there's a tournament here. I think that other kids are going to be there. Can you take me two hours across the state today, please? You would wrestle like in competition against them, not competition. Yeah. Yeah. In competition. Hey, I heard there's this tournament. Here's the magazine says this tournament. Hey dad, will you take me over there tomorrow? You weren't trying to win. You were trying to get the experience. I was trying to wrestle the best guys. Maybe I win, maybe I lose. There's no, when you do a competition, there's no guarantee of a win or a loss. You're just doing competition. Right? So I wanted to go, I wanted to challenge myself against the best guys of which I thought maybe I could come out on top. Right? So like eighth grade year, I won way, way, you know, I probably lost a handful of times in the state of Wisconsin. It's probably really, really minimal the amount of times I lost, you know, but it was just about getting the challenge. And it's like some, some kids and not kids in my club, cause I'll push them very hard on this, are scared of challenging themselves. They like being the big fish in the small pond. They're not willing to go say, I'm going to, I want to go get that guy and I want to get that guy and I want to get that guy. And so that's like, so I think that's part of it for me is like, I always just loved the challenge. I enjoyed competing thoroughly. Right. And I understood from a young age because it wasn't very good. Losing is a part of it. You're not always going to win. And that was kind of it. It's like, Hey, sometimes, you know, and for my MMA career, I never planned it to go that way, but yeah, I didn't lose for nine years. And like, that's, that's pretty rare. I didn't plan for that to happen. That was just what happened. Okay. So you also didn't lose like the second part of your college career. My 87, I lost, I won my last 87 matches. Yeah. So that didn't come along with the hatred of losing. You just, I don't like losing. I still don't like it. Yeah. Yeah. I would have much rather. Okay. But you don't, you don't seem to, you seem to kind of shrug it off a little bit. Okay. So like with specifically with these two instances that you bring up with the Mazda at all, it feels definitely so. Okay. All right. So let's go deep. Let's go deep. So the Mazda one, it feels different because. So let's, for people who don't know, Mazda loss was your first loss. First loss in MMA. Yes. Yeah. Yeah. Yeah. And I mean, it was a dramatic loss and there was this kind of buildup as you are potentially one of the greats of all time coming into this fight. And so there's pressure, all of that. So the, no, I mean, I was thoroughly enjoying it. I didn't feel the pressure. So the Mazda at all fight is, he got one fucking move on me. It's not like he beat me. And if we do that again, I think I win at that point in my life for sure. I think I win way, way, way more times than I lose. He knew that too. That's why he didn't want, he didn't want to sound the bottom agreement. That's why I had to taunt him and why he got so mad because I had to continue to taunt him in order to get him to sign. Right. So that one hurt because as people don't know, my MMA career, I'll just go through it fast. I did three fights in like a smaller leagues. I got signed by Bellator. I was undefeated for three and a half years. I was nine and O. When I got done with that in 2012, 2013, I, at that point in my head, I was just going to transition to the UFC because that's where you go. I was ranked like six in the world. I hadn't really had a competitive match at the end of the Bellator thing. And Dana White, for a reason still unknown to me, we still haven't had this conversation. I wish I could ask him, I should ask him sometime, chose to refuse me any entry into UFC. He just said, I went to his office and he literally said, we're not interested. We're not going to make you an offer. Did you, did you mention something to, about him, about the UFC? That was a year before that. That was a year before that. That might play a role in it, I think. So yes, what happened the year before that was I called him a liar, which, but listen, I'm right on this one because he said you can't test for drugs because I'm all natural, which you could tell by my physique. And I was always put off by the fact that so many people cheated. And I was very vocal about that. And so he had made some statement like, oh, well, there's no way you could test. I said, bullshit. You, you, very specifically, I said USADA does it for all other sports worldwide. You can do it. And then it's funny because I hired USADA a couple of years later. So I think he took some offense to that. But that was like a year and almost a year and a half. I think somewhere later. It's not like he holds a grudge or anything. Yeah. So I, so I literally go to Vegas. It's a long story you can read about it other places. So I got released from a belt. It's not like this is a negotiation. I got released from my belt or contract. I said, I'm out of here. I'm going, I'm going to go to the UFC. I go to Vegas. And then I was told, hey, there's no offer for you. Tough shit, you know? So then I ended up signing with one championship. I spent, what, three and a half years there. I won the belt in my second fight and retained the title the entire time. And then I just, I think. Again, dominating people. Yeah. I didn't have a competitive fight. And so I retired 18 and 0. Never, never again. And for someone who loves a challenge, never getting to really challenge myself was incredibly frustrating. And I left the door open. I said, if I ever get the chance to prove I'm an industrial, I'd love to come back. So somehow a year later, I get traded. Trades have never happened. This is the one and only trade ever. I had been retired for a year. I got traded. I get to come back. I fight Robbie Lawler in the first fight. I win. And then essentially they're saying, okay, if you fight, you know, if you beat George, you're going to get the title against Marty. And it's like, this is what I've been working for the entire. I've been trying to prove I was the best fighter in the world for the last 10 years and I have not been afforded this opportunity. So when I lost to George, that was hard because it was something that I had waited for for a really, really long time. It was something that I thought I could compete for and I never got the opportunity to do. So that one was hard. At the same time from like just a competitive logistic, it's like he got me with one move. It wasn't like he beat my ass for 15 minutes and I got beat a bunch of different ways. So that was like, fuck, like if I get it again, I could have done it, but I'm not, I'm not, they're not going to let me have it again. It's not like wrestling where you could go the next year or the next week or whatever, you know, you lose a big 10s, you go to nationals two weeks later. Does that loss change you in any way, your psychology? I don't, I don't think so. It's the first loss. I mean, had I, had I had a longer MMA career post that, there definitely would have been a lot of time spent getting better at the end, the entry point to the takedown, right? Which I'd already spent time there. Um, I, I, and I, I hate making excuses, but yeah, the, the hip, the hinging of my hip, that I couldn't do was preventing me from doing some things and it's why, if you look at the fight, I'm like bent over as they go for the double leg. Yeah. So what happened for people who don't know you went in for a double leg and he went, he did a flying knee and it caught you well. Specifically the way he did that knee was kind of different than the way anyone had thrown flying knees before. Most people go more just from a stand straight vertical, whereas he took a few like running steps and went more, you know, the trajectory of the angle was different. So I think that's kind of probably why it caught, you know, I think a lot of things in combat, well probably everything, but I focus specifically on combat, happens subconsciously. Like our brain is reading what's coming at us and, and lots of times it's stuff we've seen before so we can judge how to move correctly. And you misread because it's something you haven't seen before. Had not seen it come at that specific angle. Yeah. So that loss was really hard. With the Burrows one, I told you, I knew I was going to lose. So it was like, whatever, you know, I'm, I'm taking this because I want to put, you know, the sport of wrestling out there in a big way. I want to help them raise a lot of money. We sold at Madison Square Garden, Hulu Theater, and we raised a whole bunch of money. So my goals were accomplished. Jake Paul fight, I took it because they paid me a whole bunch of money and I thought it was going to be fun. Did I have any illusion I was a great boxer? No illusions whatsoever. Would I have preferred to win? Absolutely. But, you know, like I told everyone, whether I win or lose on Saturday night, I'm going to be back coaching wrestling on Monday because that's what I enjoy doing. And I was back coaching wrestling on Monday. And once in a while, these middle school kids give me a little bit of shit about it and that's it. That's about it. Where were you in terms of your shape and how you felt in the Mazidal fight? Would you say you're on the, I mean, it's a difficult question to ask of a world-class athlete, but like, were you past peak? Oh yeah. And that's what, I don't know, I don't know why guys like to lie about that. I mean, the peak for me was really evidently in my late twenties. And maybe they are all fueled by extra supplements. I don't know. But for me, that was evident. But you get this, so you get this crosshair where you're, if you're smart, like, you know, like I mentioned, Joan Burrows was, you're still gaining wisdom, you're gaining strategy, gaining a lot of things, right? And so while your physicality may go down, your overall skill level still may be rising, especially in MMA because people usually start later because they're gaining wisdom, strategy, all of the, maybe more tools in their toolbox, right? Like getting all these things. So their actual competitive peak, despite their athletic peak going down, might still be a few years past that, right? Because these things are crossing. No, so I felt, I felt I was great. Obviously the hip was an issue. It's funny because so that I knew I had a lot of pain here and I knew it was because of this. And it was like, okay, whenever I'm done, I'll just get it taken care of, whatever. But I, every time I train, I have pain kind of like all up my back. And the day after the surgery, I woke up and there was no pain on the right side of my, the surgery was on the left side. There's no pain on the right side of my back. I'm like, that's fucking weird. Like every, every morning I wake up, there's a lot of pain there, you know? I'm like, okay, well I'm on pain pills. Maybe it'll, maybe it'll come back tomorrow. And it's, that's never, never been back since my hip surgery. So it was weird because it was like this, I thought this was affecting this, but it was affecting all the way across my whole back. So you know, if I get to get a new hip, honestly, if I, if I, I don't know if it's going to change the competitive outcome whatsoever. If I had known how good the hip replacement was going to be, I would have done it the second I retired from one championship in November of 2017. I would have had my hip surgery scheduled for December 1. Just from a lifestyle standpoint, I could only sleep in one position. There's a lot of things I couldn't do. I was in a lot of pain. So I would have done that a lot earlier. But no, from an athletic point, I was ready to, shit goes wrong sometimes. I don't know how to ask this, but you know, Joe Rogan, me, had a, had a sense about you similar to like Fedor that you are potentially one of the greatest ever. Does it hurt that you're not in the discussion now of being in the top 10 of all time? I didn't prove it. I don't deserve it. But I didn't prove it. And so it's like, had I somehow gotten to convince Dana White, we go and convince him in 2013 to make me an offer, and I didn't even need a good offer. I just needed any offer. Had I gotten the offer then, maybe the outcome's different, right? But given, I would never expect anyone to think of me that way. I didn't prove it. I know what I was, and I'm good with that. And yeah, other people never got to see that. Do you think, well, you don't know, you can't know fully, right? Do you think if you went to the UFC at that time instead of won championship? I think I would have had a lot of success. Yeah, I mean, there's obviously certain guys, there's a lot of guys I've trained with that I had a lot of really good results against. And obviously. Who was the Walter Waite at that time? Tyron was a champion for a long time there. So I was around, Tyron was a champion, Anthony was a champion at lightweight. I was in the same gym as him, and we had a lot of people coming through. Would you face Tyron? Would I have fought him? I don't think so. I mean, so he was still the champion when I came into the UFC, and we said, no, we're not going to fight. All right. Hey, so you can't change history, right? So once something happens, you got to accept for what it is and move forward. And obviously, hope you can continue to keep accomplishing great things, which for me, obviously, my athletic career is over. So now it's going to be through my wrestling academies. And who knows what else I get into. You might do exhibition matches and all that kind of stuff, right? Says who? Wrestling and stuff. No? I don't think so. So here's my thing with the wrestling matches is like, just for fun. If you said, hey, Ben, just for fun. Yeah. Would you love to go wrestle someone? Yeah, I would. I would. I love wrestling. I get in there. I love, you know, I love like, so one of my guys has gotten to be pretty good. He's in college, a guy named Keegan O'Toole. He just won a junior world title this year. And so when I'm doing private lessons, I have to think about the development of the athlete. Sometimes I can wrestle hard, but most of the time it's like, I'm just going to help them with whatever they need help with. And it's still wrestling. It's fun, but it's helping them. You know, for like, Keegan comes back this summer and he's training for the junior world title. So to be able to just shake hands sometimes and say like, I'm going to try to kick your ass. You try to kick my ass, you know, like just to go like, yeah, it's so much fun. And I don't get to do that very much. So if you said, Ben, would you love to do some matches? And the answer is yeah. The problem, unfortunately for me, and maybe you could talk me off a ledge here, is like because of where I've gotten to in my career, if I choose to do a wrestling match, it's going to, people are going to be really excited about it. It's going to blow up. And it's like, I just want to wrestle just to wrestle. I'd rather just like go in a room where no one can watch and just wrestle and just enjoy it. Well, you could also wrestle. So there's different kinds of wrestling. There's wrestling where there's an event and like, you know, there's a buildup and then an announcement. And you can also do like a Khabib style, like in the room, there's cameras and you're kind of going, it's like, Khabib does that? No, in a... Marcel did that. He whooped my ass a few times. Yeah, exactly. I mean, I've seen Khabib in some videos. It's not like set up. It's just people going hard and then it's more fun, you know, and it's also more like presenting the beauty of the sport, you know? For sure. And there's no winning or losing really in that context. Like you're always joking around a little bit, even when you're going super hard. So I feel like, especially in the modern day with the internet, that's a compelling way to do. So I've thought about, this is the one thing I've thought about doing, because I told you about my buddy who is the content thing. It's called Rockfin. I thought about doing, you know, the old, really famous Gracie challenge. Yeah. Okay. So I thought about doing the Aspen challenge. You want to hear my rule set? Yeah, let's go. I'm not sure I'm going to do this. I'm not going to show up here like in Wisconsin. I have to select you. I'll start with a thousand bucks, right? Okay. 30 minutes. You pin me or I pin you. That's it. No points, no nothing. We just wrestle. Camera, that's it, right? It's camera in the room. Maybe there's a ref free because we don't want there to be contention over the pin. So one pin. Just one pin. 30 minutes. 30 minutes. Okay. If I pin you, you don't get shit. You go home, right? Every person I pin, it goes up by a thousand dollars, 2,000, 3,000, 4,000, 5,000 and so on. If you make it the distance and I don't pin you and you don't pin me, I'll pay for your travel and give you 500 bucks. Just a consolation prize for showing up. If you pin me, you get whatever the jackpot is. Wait, who's adding to the jackpot? I am. It's my money. But then what's the incentive to keep winning for you? Because the jackpot's- Well, because I would put the content somewhere and people would watch it. Oh, so you're going to make money. Yeah. So you'd make money that way. But it's not exponentially growing, right? It's just going up by like- Yeah. I think I'm the only one, there's probably only a couple people that could pin me. So I would either just not choose those people or wait till I get a really large audience and people get really excited. In that case, I'm making a lot of money. What do you think, how many matches would go with you, like Khal Daik shows up? I don't think he could pin me. Yeah. I mean like- How would that match go? Jordan Burrows could beat me, but he can't pin me. He was never a pinner. Yeah. He ain't going to pin me. There's only a few people who have the skill level to do so, right? It takes a lot. So pinning was one of my specialties. The fourth most of all time and I won the pinning award the last two years. So you think it can be down on points and just pin them? This is actually one of the issues I have with jujitsu and the point system and the Eddie Bravo thing. I actually think the Eddie Bravo thing is kind of, people get so mad at me. Sorry, jujitsu. I think it's bullshit. And you want me to tell you why it's bullshit? Yeah. So like if Jordan Burrows whoops my ass and the score is 16 to two, but he can't pin me, then I get to go to overtime and get a cradle on him, I'm probably going to pin him. So I'm better than Jordan Burrows? Nah, that ain't right. He just whooped my ass. Do you know what I'm saying? If we can go the whole, because they do submission only. So if Jordan Burrows beats me up for what, is it eight minutes, 10 minutes? I don't know. What's the length of an Eddie Bravo match? Yeah, I don't know. Something like that. Yeah, yeah, yeah. So we go 10, me and Jordan Burrows go 10 minutes. He's going to outscore me significantly. He will not pin me, I promise you that. So now we go to the overtime. Strong words, but yeah. He won't. Jordan Burrows is not going to, he's going to beat me. I will give you that. Kyle Dake won't pin you either. No. Okay. They will both beat me on points very badly. Now David Taylor, he might pin me because he's a very good pinner also. They'll beat me very badly, they will not pin me. But now we get to overtime and we get to pick, so in Eddie Bravo you get a rear naked choke or an arm bar. Okay, give me a cradle, I'll probably pin him. Okay, a good cradle. You can say cradle or maybe give them, they're probably not going to pin me. Maybe there's a chance, but probably not because that's just not their specialty. So for people who don't know, the Eddie Bravo thing is, and it goes into overtime, you get a dominance position on a person and you get to, yeah, basically put them in a cradle, this is the wrestling equivalent. Yeah. But you take their back. Maybe an arm bar, yeah, like a wrestling arm bar. And I don't think that's very fair because if someone whoops your ass, they whoop your ass and then, you know. And so I think the reason why Jiu Jitsu people accept that rule set is that I don't think, I think they know this but would admit it, I don't think their point scoring system adequately rewards what people value. So like in wrestling, we value takedowns because it gets us closer to the pin and the most valuable scoring is a near fall, near to the pin because that's the ultimate goal of the sport. Whereas in Jiu Jitsu, for example, like if I were to get a takedown, so like if I went to Gordon Ryan and he just didn't pull guard, I would probably get the takedown. Now if somehow he didn't submit me, which he probably would, right? Because they got close to like 12 submissions but somehow I slipped out of all of them. Now I went to zero, like that's ridiculous. Like he should very clearly win because he almost submitted me. You know what I'm saying? And I realized the difficulty. I realized the difficulty in rewarding near submissions but that is the most valuable thing is getting close to finishing the match and in most competitions, they don't actually reward that. But okay, so this isn't about the sport. This is about the Ben Askren challenge that we're talking about. Why 30 minutes? Why not unlimited time? Why go until whenever? Well, because then it's just a cardio thing because at some point, then someone would just have to fall over dead, right? There's no more skill level involved. It's just who can stand up the longest. You honestly don't think 30 minutes is a cardio thing too. How do you think that's actually going to look? Kyle Dade going against you for 30 minutes. So it's going to be kind of boring for the most part because- What position are you going to be stuck in? But you just can't have a gigantic amount of action for 30 minutes. So I relate it because some of my kids when teaching them wrestling, they're like, well, but I can't do that for seven minutes. And I'm like, well, you know, like say if I had you do hand cleans at a relatively heavy weight as hard as you could, you're not going to last seven minutes. Your pace will slow down, right? So my thing is like, well, your pace doesn't have to step here because in wrestling, you're competing against someone. So if you're here at 100 and you go to 80, but they go to 70, that's great. And then you go to 60, but they go to 40, this is even better, right? Because the gap is growing. So we don't necessarily, if we get tired, that's fine. If they get more tired, that's better. So I think most people would know that. So they would kind of slow it down. But yeah, I think at 30, I mean, I've wrestled 30 minute goes. I've wrestled hour long goes. You're not going to get so tired, you're going to fall over in that time period. But at some point, if it's unlimited, someone will get so tired or dehydrated that they're just going to freaking fall over. Yeah. But you think, what about making it exciting and dynamic? You think the other person is always going to be going for the pin and thereby make it dynamic. Well, if they're working that hard, then they might exhaust themselves, right? And obviously then if you're being that dynamic, then you're adding risk to yourself too, because you're doing that. Well, I love this. This is a great idea. Well, I figure I'd rack up like 20 pins against bums or not as great people in the beginning. And then I would start bringing in better people because they would be enticed by $20,000, the possibility to win. And not much fanfare, just a camera and just a local. That's it, in my wrestling room. Yeah, like the Gracie Challenge. Yes. Yeah. And then maybe you have like, for most people, you have someone edit like the 90 seconds of the most fun things that happen. And then you can watch the entire 30 minutes if you want to. Yeah. I think most people, if they're not really, really elite, I'm probably going to pin them. If they're not really elite. So yeah, but I don't know. That's something I've been thinking about. This has been fun for me to think about. And obviously it plays to my skill sets because my cardio is good and my pinning is good also. So yeah. So like you said, you weren't very good in your early days until 13, 14. What was the switch? You began, you started to dominate people in your college career, you dominated. And obviously you stopped losing at some point. So well, I would say, so even when I didn't lose in collegiate competition, I would go in the summers and try to make the world team. So I would lose some, not a lot, right? Minimally. Okay. So when I'm five, I start playing all sports. Like I know you moved to America at what age? 13. Okay. So five, so at least, I don't know what it was for you, but in America at my age, you usually played like a sport every season. Right? So that's what I did in the beginning. I had minimal success in wrestling. I was kind of chunky. And then in fifth grade, I don't, and I can't tell you, I wanted to be better. And I told my parents, and this is funny, because now I look at other 11 year olds and very few of them are this mature. And I actually think emotional maturity is kind of one of the key indicators of how long-term successful someone's going to be. And at age 11, I said, I don't want to play baseball. I like baseball, but I don't want to play baseball because I want to wrestle more because I want to get better at wrestling. So age 11, I quit baseball so I could wrestle in a club for March, April, and May, because that was all that existed at that point in time. You couldn't wrestle in June, July, or any of those other months. What was that desire to get better? What is it? So it's not about winning. I don't know where it came from. I just wanted to get better. I want to get better. I want to be good at this. I want to be really good at this. So when you're looking at kids now as a coach, you're looking for that. Somebody who says, you know what? I kind of suck. I want to get better. And I want to try to also inspire that. I mean, honestly, I think as a coach, that's probably my biggest job is to get a kid and get them to believe I can do this. Because if I can do this, what can I? I can do that. I can do that too, right? And there's so many kids who unfortunately have like shitty parents or bad teachers that tell them, you suck. You can't be anything, right? So I think my biggest goal as a coach is to get someone to believe they can do it. So actually some of the ones that believe they can do it, they're the most fun, but they're not the ones who need it the most, right? The ones who think they can are the ones that need me the most. Yeah. Because they need someone to, let's go. So I don't know what inspired me. I'm not sure. So age 11, fifth grade, I quit. So then I started having more success where I'm like, say, placing at the state tournament. In high school. So you're right. So sixth grade, I placed at the state, the local youth state tournament. So I'm having more success. Seventh grade was the first year I won the youth state tournament. So I'm getting better. Eighth grade, I actually feel like I got pretty good. But when I went to the national tournaments, I was still having really minimal success. My freshman year, I decided to quit football. Same reason. It's like, well, I need to put more time into this. My parents, we got, my dad luckily got a mat in my basement. So we have a year-round club and our impetus was that we didn't have this opportunity to go to a club year-round. So we had a mat in my basement. I had to go find, hey, you want to come wrestle? Yeah, to find partners for myself. What'd you do? Did you drill? Did you live wrestle? What'd you do in that basement? So actually, I think, you'll enjoy this. I think the start of my scrambling was kind of based around that. So I got kind of, I think it's probably my freshman, sophomore, I'm kind of, the years are a little fuzzy, right? It's been a while. But probably my freshman, sophomore, junior year, I found two kids who were really consistent who would come out, like you would come out, he would come out on Tuesday and this dude would come out on Wednesday, right? And they would come every week and they were really consistent partners for me to have in the summer. But they weren't nearly as good as me. They were way worse. So it's like, okay, how do I make this kind of fun and compelling for them to come back? Because if I just whoop their ass, they're not going to come back. So it was like, I would let them get as close as I thought they could do a takedown before not getting it and then try to escape or get out. So obviously, if I let them get really close, sometimes they get it. So they're enjoying it. I don't know if they ever knew I was doing this. I have no idea. And that was kind of like the start because I had to figure my way out of bad positions because I had to try to make it entertaining for them where they still got something out of it and they wanted to come back the next week. And I also got something out of it. Yeah, I love this. Yeah. Because that relationship is so important. I've had a few drilling partners, training partners that were really important to my life and I always wonder why it's so difficult to find them. If anyone's listening to this, I'm looking for a judo person in the Austin area, actually. Getting the reps with people is hard, even in jiu-jitsu. It's just like people want to do the fun stuff. They don't want to really put in the work and it takes a certain kind of personality. And then you also have to make it fun for the other person, just like you said. If there's a skill mismatch, but also if you have an interest mismatch in terms of the amount of drilling you want to do, all that kind of stuff, you have to figure out ways to make it fun. Yeah. It's tricky. So you did. Yeah, I think I did that and no one told me. I get frustrated because now we have, just in my academy, we probably have 50, 60 high school kids only that are year round. They're year round. Maybe they're not as consistent in the summer or whatever, but they're there. So when they don't have a great partner, they start whining. It's like, you little bitches. Some days I get really mad about it because it's like, I had no partners. I had to find freaking two partners to come twice a week. You guys, there's still 22 people in the room. I'm sorry there's not the perfect partner for you, but go work out with that dude. So what was the switch, the change? Was it gradual or was it- Gradual. Okay. Yeah. So let's do this. So ninth grade, I quit football because I wanted to get really serious. What position? Football. It was actually a nose tackle. But at that point, so I was also the other thing I kind of left over is I was really fat growing up. In sixth grade, I also decided, okay, I'm really fat and if I want to be competitive wrestling, I shouldn't be fat because weight matters. I went from 130 pounds to 100 pounds in sixth grade. So by the time I was a freshman, I was 119. So I still wasn't as heavy as I was in sixth grade. So I was pretty small too, but I was also slow, unfortunately. So they put me in nose tackle. I liked the competitiveness, so I was decent at it. So that's where you wrestled 119? My freshman year, yeah. So yeah, so then I still, I started having a lot of success state-wise, but not nationally. That's my national success didn't come until my junior year in high school. But yeah, I was grinding and getting better the whole time. And then senior year, I started having a lot of success nationally and I got recruited. But then even when my freshman year of college, this is where I loved competing, I would go every weekend because I knew if you take the emotions out of competition, all it is is seeing your failures, acknowledging them, and then figuring out what you need to work on. If we take all the emotion out of it, that's what it is. So I wrestled 50 matches as a redshirt freshman, which is incredibly rare. I had 10 losses. So it's not unlike to not so great guys. So my skill level still at that point was not that great. And then the next year I came out and I made the NCAA finals. So I made a gigantic jump in that redshirt year to the real freshman year. So a few questions. Where did the funk style of wrestling, the creative style, get developed? Which stage? So I think looking retroactively, there was no intention to start when I was in high school with those kids, but I think that's kind of like what was happening. So what I would really say is I had one influential coach my redshirt year of college named Mike Ironman, great guy. But then the second thing was it was just out of necessity, I had this burning desire to be the best. And when I was getting my ass kicked every day in the room, because Tyron was there, we had All-American 157, we had All-American 184. So I was having a ton of success. And very quickly I realized from a more traditional athletic perspective, strength and speed, I couldn't keep up with anyone. I was way worse. So it's like, okay, fuck, how do I do this? I want to do this. How do I do this? There's got to be a way. So Mike Ironman showed me a couple of things, but then it was just like this creative expansion for the next, say, three to five years. And then even now it's like, I don't know, there's something, maybe you feel this way about Judo or whatever, there's something that's fun about the way the body moves and works and exploring something new and thinking about, hey, wrestling's been happening at a relatively high level for, we'll say, 80 to 90 years in America. And there's still new things being developed. And so when you see something new, you're like, oh, damn, that's great. Or like Jason Nolte may have to win Dixie. I'm like, how did I not think of that shit? Why did I think of that? It's so easy. I should have thought of that. So there's this obsession with the sport of wrestling and positions where I actually think sometimes think I wouldn't have smartphones because I may have been distracted by my smartphone. Maybe I wouldn't have been because I was so obsessed, but maybe. But some days I couldn't finish the single leg on a specific person or maybe they were finishing on me and it was like, go home. I was just fucking obsessed about that one position. Like, okay, what am I missing here? And not just accepting that whatever the coach says is the answer, but what am I missing? What ways can my body move that no one's told me it can move yet? Where can my arms go? Where can I do all these things? And so I would just obsess about these things. And then sometimes you come in the next day and you say, oh, well, maybe this. And maybe it works, maybe it doesn't. Maybe it works twice and then it doesn't work the next time. And so you have this creative process. And it's like, there's a lot of things that are on the cutting room floor that never made it to the light because you thought they'd be good and they failed and they sucked. And then to the point where like my senior year, I got to this point where the people, they were just figures. Figures would wrestle in my head about positions I was thinking about. I wouldn't tell them what to do. They would just go in my head. And then like, oh, fuck, wait, that's it. That just happened. That's the move. And then I go try to practice and sure enough, boom, that's the move. That's exactly where you have AlphaZero playing, learning chess. You have, it's called self plays. You have, what did the figures have? Like no faces. They were just like, did they have a human form or is it just like stick figures essentially? Oh, yeah, it was not like, yeah, it was not like humans. It was more like stick figures. It wouldn't stick figures exactly like they were. They had some volume. Yeah, it was like, it was like a gray person and they had, you know, three dimensions essentially because I had to see how the things moved and yeah. I mean, this is exactly what OpenAI and DeepMind and Google are, I don't know if you've seen, but there's something called reinforcement learning and artificial intelligence where you have like, they've done it for like sumo wrestling. You have like, you have these two stick figures that don't even know how to get up at first and they figure out how to stand on their two feet and then they figure out how to push the other person off of the pedestal. But what about like when you look at the Boston Dynamics, sometimes they have trouble with like jumping and balancing and the other stuff. So are they doing that same program or no? No, no, no. This is different. Everything Boston Dynamics is doing is hard coded. So it's not learning all the sophisticated movements and strategies, like high level strategies and movement. That's all something that Boston Dynamics does not do. And if it does it like the parkour stuff, that's all hard coded. People like project and think like these robots have like discovered like how to move in sophisticated ways they haven't. Well, that's why when you and John were talking about the grappling robot. Yeah. I mean, the one thing I was obsessing about in my head is that with the chess, right, if a chess piece moves, right, the horse can move like an L, right? It can only move like an L. It doesn't matter if it moves at two meters per second or seven meters per second. It can only move there, right? Whereas like a single leg, I can shoot a single leg with many different velocities. I can shoot at different angles. I can shoot with different amounts of force, right? I can shoot with my head up versus my head. I mean, right, all these things are gonna matter. If we're talking about a human being defending the single leg, all of those things are gonna matter and that's where human beings who wrestle are calculating those things subconsciously. They're obviously not consciously calculating in their head, oh, the force is coming at me at this, so I need to do that, right? They're just doing it. But see, the thing is, so you would absolutely, if you're doing a robot that you're wrestling, you're going to have to constrain the speed at which it moves and the power that it's able to deliver. So that presumably, there'll be the limitation. So then it'll be just the same exactly as a human. But then, so if we go human, max force, Jordan Bro's double, max force, right? That's the highest we get. Then we go down from there. Even within that, it's like sometimes I can shoot a single leg with a maximum force of, I don't know, we'll say 20 is the number, right? I don't know, I shoot at 20 because I feel sometimes I shoot at 15, sometimes I shoot at 12, right? Because you feel something in your opponent that makes you do it differently. So they would have to learn how, and then all of these different things, and sometimes maybe I clamp a little harder. So the robot would have to learn all of these different incoming inputs to the system and then create this reaction. Oh, no, no, no, 100%. So this would be all continuous. So unlike chess, it would not be, chess is discrete. You move, it's a very specific set of moves. Now here, those are all variables you control, and they're continuous variables. So the speed, the force, there's actuators, so there's all these joints, right? Yeah. You can move, I mean, it's just an optimization problem. It's kind of fascinating. So I've been fascinated thinking about it since you guys talked about it. It was a long time ago. I listened to it probably three to four weeks ago, and I've kind of been like obsessing about it ever since. It just changes when, so unlike boxing, for example, or striking, once you grab a hold of somebody, you're now one body, right? So it's very complicated. It's not just shooting a double leg without, like maybe doing like faking a double leg and then shooting the double leg, that's very doable with robotics, but then like doing a clinch and from there doing like a Russian tie, like that, I think that's way harder than people realize in terms of how many things are involved. Like the force of the grip, the leverage you're providing with all the different parts of the shoulder and the arm and the torso, the twist, how much of your weight are you allocating, like leaning on the other person, like taking weight off of one of your legs and the other leg, all of that. I think that's the really interesting thing about humans is we're able to do all of this calculation subconsciously. Yeah, subconsciously. Yeah, and that's what I've been thinking about since is like how many things even these high school athletes who are like getting medium good are subconsciously thinking about all the time or not even thinking about, sorry, reacting to. But then even like for me, I'm a few orders of magnitude better than some of these kids that play. And so when I go like super hard, it's like I can feel their weight moving in the wrong direction and so for me to off balance them or trip them or whatever, it's kind of easy sometimes because they're not feeling it the right way, right? So their timing's just a little bit off or the way they're grabbing the hip, maybe they should be up a little higher, right? These really small things. Yeah, I think that's all easy to take advantage of for a robot. There's so many things. The big problem is ethically, I don't know how many people are willing to train with a robot because you're gonna get hurt. Well, can you make a robot train with a robot or no? Yes, but then it's expensive. Put the padding on that thing. I know, but then it's not, you know, then you're not capturing the full. Why can't you put like some rubber coating on them or something for that effect? You could. I mean, you could. Yeah. You could. I mean, you're talking about robots that are, these are humanoid robots, so we're talking about $500,000 million robots. So you would have to be motivated to spend a lot of money because you have to have them wrestle for like a lot to get better. And then the open question is how long does it take to get good enough to be a human? I don't think we understand, I don't think you understand how hard wrestling is. Is it a really hard problem? What's harder, chess or wrestling? Wrestling, by far. I'm close. Yeah, that's the sense I have. So because there's an infinite amount of moves and possibilities, so once I shoot the single leg, now you have X amount of choices. Once you make your choice, now I have a choice, X amount of choices. Now you have X amount of choices on the defense, and we can just keep going back and forth, right? And this number becomes... It's the same as what happens with chess. Correct. But then in wrestling, you have to make these movements very instantaneously, right? Because if I shoot a single leg, I'm not going to wait and say, what's your defense? Yeah. Right? You have to make it instantaneously. And then also, again, based on the force and the vectors and the angles, you have to calculate that and adjust. So really, if you're saying, why can't you shoot a single leg? It's not like moving the chess, it's not one move, right? If you want to talk about different forces and stuff, it could be hundreds or thousands of different moves based on how hard I shoot it, the angle, the direction, all of those things. Yeah, but wait a minute. So robots can do this kind of stuff really fast. People probably know the physiology of this, but the reaction speed for a human is maybe 100 milliseconds, something like that. I don't know. From sensation to... From the signal traveling up to your brain and down, I don't know what that number is, but robots certainly could do it way faster. You would actually have to constrain the speed. Well, so the robots are already killing the chess people, right? So yeah, theoretically, they could eventually beat wrestlers, but you asked what was hard wrestling or chess. I think wrestling is, because of the time component in it and the physicality of, is it this force or that force? Because if I'm going to say, say we're in a seatbelt side by side, a wrestling seatbelt, based on the pressure you're giving me, I might do a bunch of different things, right? And so like to an untrained eye, they might both look like the same thing from you. To a trained feel, it's like, well, in one case it's really evident I should go this way. In another case, it's really evident I should go that way. So the other thing to consider, just like with chess, the AI systems, so human versus human play a certain way together. They actually haven't considered a really large number of strategies that AI systems discover. So one possibility with a robot, they'll discover certain ties and certain takedowns. That's what I'm saying. That will dominate no matter what the human does. You think that, so you think there's that, so I mean, so I was talking about the wrestling is so fun is there's, even after 80, 90 years, there's this continuous evolution. So you think- There'll be some like low single type thing, like John Smith type of situation. Well, like a down block go behind is something that has really, I would say really in the last five-ish years has really been evolved. What's a go behind? A down block go behind, so when you shoot, well, it's head inside or head outside matters, but there's one for both. You shoot at me, essentially, I take my leg, boom. So that was kind of in existence when I was in college, right? You down block them and you stop, but usually you hit on this side of their head, right? And now immediately as you shoot, I attack that shoulder and then I start hitting a go behind on you, right? And so that in its current incarnation, it absolutely wasn't around when I was in college. I would say it probably became popular five to seven years ago. So yeah, there's these big things that are happening. Now I really want to roll back because I want to be ahead of the game. I want to know what I'm missing. I mean, one interesting thing you have with AlphaZero that plays chess is it sacrifices pieces much more than humans do. So it'll give you a piece and not only does it give you a piece, it will wait a bunch of moves before it makes you pay. Because it knows that that's better for the long term. So humans rarely sacrifice without getting the piece back two or three moves after. AlphaZero can wait five moves. So basically, potentially with wrestling, you might have a robot that puts itself in bad positions, but in a certain kind of way that will actually- Lures the opponent in to trap them. Exactly. That's what my style is based on. You basically narrow, one thing to do is you narrow the set of choices. You put yourself in a bad position, but it narrows the set of choices. For them because they're not used to it. Yeah, they're not used to it. And then you drag them into your- It's disgusting. Yeah. So, but there's also, the problem is there's mechanical issues. Like it's actually just difficult to build robots that are able to sense because we have sensation throughout our body. Yeah. It's difficult to build that kind of robot. It's expensive. You start talking about multimillion dollars and then people start asking questions. Why did you invest all of this money? I don't want to see what moves I do. Duh. Hello. It could be better investment. Okay. So I mentioned John Smith. He is, if people don't know, one of the great wrestlers, wrestling coaches ever. He's also creative like you. He spoke really highly of you. What do you think about that guy? Do you guys ever work together? Not really. So you know what, when I was a senior and I had the people wrestling in my head, I was lucky enough to be doing, I was pretty much graduated. So I did an independent study with the sports psych. I was potentially going to go to grad school for sports psych. Well, I actually did nine credits and then I just decided I didn't want to do it anymore. I continued learning on my own. But I had an independent study with the guy who was the head of USA track and field sports psych. So here was the class was, I got to go sit down and talk with him for an hour and he was fascinated by me. So he didn't let me do homework. It was like the greatest three credits ever. We just talked. I learned so much. It was so awesome. So I started, so one time it came up that I had these robot or people wrestling in my head. And he said, well, who else do you think? I said, I bet John Smith happened. So I went and got John Smith's number. I called him and said, hey, you ever had these people wrestling in your head? And he said, yeah, but as soon as I stopped coaching, they went away. Same thing happened to me. As soon as I started coaching, they went away. So if I really force myself now and I'm like, I see something in practice and it's really higher level because high school wrestling, I don't want to make you guys feel bad, but it's like it's a little bit lower level. So if like Keegan, for example, who won the jury, if he's struggling with a problem or asked me a question and I can force myself to like see the bodies moving and think about it again, kind of like I was in early age, but it won't just flow there anymore. So he said it went away. And for me, it went away also. By the way, if we can pause on the bodies in your head, how are they generating new ideas? Are they just kind of... I don't know. You tell me. So it's just, they're just like scrambling in your head? It would be specifically based on a problem I was struggling with or a specific position. It goes in for a single and then go from there. Yeah, so I'm sitting in geography class and I don't have to work that hard because it's easy. And yeah, I'm just sitting there like kind of acting like I'm looking at the board and these guys are wrestling and I'm watching them wrestle. And yeah, sometimes they come up with a really good solution. Is there somebody you looked up to style-wise? Not really. Like Gable, John Smith, all these like legend status people. Probably Gable, or it's not Gable. John Smith, but after the fact. But the problem with wrestling in my era was you couldn't watch it. There was no access. It wasn't really available. Even if you want to say go find a bunch of John Smith men, they're kind of hard to find. There's a couple of them on YouTube, but I've obviously seen all of those. But in my era, there really wasn't any of it. So it was hard to be a fan of something. And that's why wrestling has... The fans are going like this because now you flip on the Flow app and you can watch something that's happening in Europe. We can do this easily so we can be a fan of people. So now I'm more a fan of wrestling than I was then because there just was no access. So now I can watch someone I like and say, oh shit, that guy's wrestling. Oh, boom, I flip my phone on, I watch them wrestle, that type of thing. And a quick rant, it's really frustrating that you can't watch the Olympics. Oh my God, so frustrating. I think I'm going to go to war on this one. Go to NBC's headquarters. I'll go with you. You got a soldier here. I was talking to Jimmy, Jimmy Pedro. He was surprised by this too. Most matches you can't see. Even you talk about a comeback, Gable Steeles. You can't see the full match. You get a crappy highlight. So the two biggest things in wrestling, and really the three, the NCAA championships on ASPN, the Olympic trials are on NBC and the Olympics are on NBC. And these companies are so big, they don't have a department dedicated to selling the rights to that footage. So the rights to wrestling footage, which no one really cares all that much about except a niche, are the exact same as track and field or basketball in the Olympics. So yes, all of this stuff is completely inaccessible to us. The NCAAs, the Olympic trials and the Olympics, you can't go watch old film on it. It sucks. Yeah, old or current film. So you can't even watch the Gable match? The Gable Steeles, no. They do something that annoys the fuck out of me. What? Okay. They do a three or two minute highlight. So it's like they capture the most important thing, but it's all about the buildup. That very beginning when you step on the mat and the nerves and you walk out and like that, I mean, I don't know. You miss, then when the triumph happens or the heartbreak happens, it has that much more power. Yeah. If you want to go to war with NBC or ASPN, I'm happy to join that. This is bullshit. IOC. Well, I mean, is the IOC on that? IOC is selling for the Olympics is the one that's making. Well, so NBC broadcasts, so they obviously have the live rights. You would think they would have recorded, I mean, they're the ones recording it. You would think they keep the rights when you think so. No, no, no. They're getting a license of it. They're getting exclusive license. For example, I've had this, I talked to Travis Stevens, the Judo player, and there's a really sort of famous match. It's a heartbreak in his career from 2012 Olympics where he goes against a German, Oleg Bischoff, whatever. It's a 20 minute match to go to war and that's not available anywhere, but it's uploaded on YouTube and set to private. The reason I know this is on the IOC channel. So they've uploaded all of these matches. They have it and put it up. So actually, so my Olympic match, the one I won, got put public and I don't know if it was private. It got put up on YouTube. I was alerted to it the week of my Jake Paul fight. It was so dumb. I'm like, why the, this is 13 years later. This is bullshit. Like this should have been up. So I mean, okay, so what about Olympic trials footage? That has to be USOC then or NBC? So I know, okay, so I know Flo, right? Because I work for them. I know if Flo buys your event or whatever, right? They buy the rights. Generally in the contract, they'll have rights to both live stream it and then use that footage at any point moving forward. So those matches live on Flo's website. That's why I would be surprised that if NBC didn't have something similar. Flo does a pretty good job of providing like a place where you can watch all these matches. NBC does not. Does not. Yeah. And also there's an argument with Flo as well, but certainly with Olympics, there's a difference between what Flo does and what the Olympics represent. What do you mean by that? Like, it feels like the Olympics, which is what the charter says, should be as accessible as possible. Yes, that's true. Like, you should really lower the barrier for entry for the Olympics. You know that's what the charter says, but those people in the IOC, these are the worst people ever. Yeah. They're very bad. Well, they're not bad. They just lost touch of the dream they once had when they joined the IOC. Well, I would argue all the way back that these are rich fat cats who, like, I get so mad about the NCAA, which finally now got rid of this term, bullshit term, amateurism. It's like, well, there's some holy grail where you can't make money to be an amateur athlete, but the people who own the IOC or the people who own the institutions, college institutions, are making boatloads of money off of you. That's crap. So, you competed, like you said, at the 2008 Olympics. Did you believe you can win gold? Yeah, absolutely. So your mental game was on point. Yeah, I was ready. So what went wrong? I just wasn't good enough. That was what I said. Yeah. I mean, so at that point in time, it was my first year of international competition. So when I came out in 2007, it was my first time making 74 kilograms, which is pretty small for me. I had some failures, but then quickly I turned that around and I was having success in America. I was beating everyone, I don't want to say easy, but yeah, I was doing really well. I went international one time and there was one match I got cheated on. The Russians, they're cheaters. I think it was Ukraine, not Russia. I lost one real match where I actually lost and it was to Dennis Zargush, who had gone and went through world titles, but he was behind the tee of that year and it was competitive. So I knew, okay, I'm going with the best guys in the world. I beat a bunch of other guys who were good and had passed decent results. So I knew I was right there. Unfortunately, I ran into this guy, Ivan Fundora, and I had someone do scouting reports for him, actually my high school coach who now coaches for our academy, John Messamrick, and Fundora was the worst stylistic matchup. I got him and I lost him second round. So I wasn't good enough. Had I decided to keep wrestling, I probably would have gotten better, but at that point in time, this wasn't in the cards. So in your division was, like you said, Satyev, vice Satyev. That guy is special. He's very special. So that would be my other guy that you asked earlier who I enjoyed watching and that was a guy I, again, it was kind of after the fact because it was hard to access footage, but he was a lot of fun to watch. What do you think made him great? A lot of people talk about him as potentially one of the greatest ever. Oh yeah, he is. Absolutely. He won six and so he won six and three, six Worlds, three Olympics, nine total, which there's only one or two people above that. So again, it was hard to watch any live footage of him, but from what I've seen, his feel is different. He was just ahead of his time and the feel and the touch he had for certain moves and different things because obviously physically he's kind of unimposing. He's taller and skinnier, which is, it can work in wrestling, but it is by less represented and yeah, he was special. So good. Do you take any inspiration from, let's talk about Dagestan in general. What do you think makes those wrestlers great? Yeah, it's fascinating. Have you read the book, The Talent Code? Yeah. It's great. And that kind of talks about these talent hotspots all around the world. So now obviously with our wrestling academies, we try to take some lessons from that and apply it. I got to assume they didn't cover Dagestan in that book specifically, but I got to assume a lot of the same principles that are in that book apply to Dagestan and wrestling. They did South Korea and women's golf. They did Curacao and baseball. They picked a lot of these other places that were really elite. I think it was maybe Moscow and women's tennis also. So I think all these things that make any group great or organization is probably the same things that's happening there. Well, the hardship, I mean, is there something specific about wrestling that can create so many great champions? From that area, so obviously they all love it. It's a big deal that wrestling specifically is a big deal there. They do sambo also, obviously. So that's part of it is a lot of the kids are doing it. They obviously are rough tumble, tough life. Yeah, a lot of fights. And then I think that also that a lot of them, it is a way out, right, the elite level athletes in that part of the world from my understanding are really well compensated compared to what the average person makes and they're treated really well. So people see it as a way out. And then honestly, if America's getting better, but in 2008 the reason I went to MMA was because I didn't want to be poor my whole life. You know what I'm saying? It sucked. It's like, well, I don't want to make $20,000 for the next 48 years, so I'm going to go do something else. If I could have made even I need to be rich, right, if I could have made $100,000 or $70,000 wrestling, I probably would have kept wrestling. So I think it's those factors. And obviously now they have a really like a bunch of really good people in one area. So there's probably it's been going on for a long time. So there's probably a bunch of like adults and coaches that are coming back and helping that progress. So yeah, a lot of those things that happen. So I'm definitely going to travel there as I talk to him because I can speak Russian. It makes it makes it very makes me uniquely qualified to. My brother can speak a little bit of Russian. Your brother can? Yeah. Okay. Like a little bit like two squares and hello? No, no, no, no. Like he would. Oh man, don't don't make me over. So I think he would be able to have a conversation with you. I think. Okay. Probably not like you. What's the what's the reason you know? I don't know why he got obsessed with languages. And so his college degree is actually what they call interdis where you have three minors. We had a minor in Russian, a minor in Spanish and maybe Japanese. I'm messing up. It's definitely Russian and Spanish are for sure. I don't know what the third one is. No, but yeah, Dagestan, it's really fascinating. But the the emphasis on technique, the lighter drilling, like they don't really go super hard. Yeah. And I only spent a couple. I was in Vladikavkaz in 2008. That was where the World Cup was. We had to train there for like two days afterwards. So I didn't get to dig deep, did dig deep into what was going on or anything. But yeah, I mean, I think sparring has a sparring is very beneficial for wrestling. Not like sparring MMA is we fight right sparring in wrestling is. So I was just described to be really simple. If we're drilling, it's relatively zero percent resistance. If we're going as hard as we can, that's 100 percent. There's all this gray area in the middle that's sparring. And so, you know, if you have a good relationship like, you know, because a colleague, me and my brother, we could just go and we know where each other's at. We don't have to talk about it. Right. But like in my wrestling, I'll say, OK, hey, I want you guys to go 50 percent in this position or I want the high crotch guy. I want him to shoot. And this is for him. So I want him to go 70 and defensive guy. I want you to go 40. You're not you're not supposed to be trying to win here. You're going to go a little later. I want you to give it give him some looks, you know. So I think I think it has really taken hold in America. I think it's beneficial for success. And I think that's I mean, America is doing better than we've ever done. Well, that's 70 and 40. That's like an art form to find that right place, because like what the really good people I've trained with, they go much closer to 100 percent speed wise or like but without like forcing things. Yeah. It's like, you know, it's some weird combination of things that like if you truly earn a technique. Then you're given that technique. Yeah. But like if you don't, you don't. And then it becomes much less injury prone. It becomes somehow more fun, more dynamic. You don't get stuck in positions. It's just a lot of movement. The one thing so you and John talked about, you know, like different ways to learn and get better. So I think John obviously innovated within the sport of jujitsu. And so for us, one of the and maybe there's a differentiator for us. I think about it. So sorry to interrupt. You have this academy, you send me this plan. They have a really well thought through plan for how to develop a good wrestler. So but so I think it's so for me, there's four categories, right? There's the teaching, which is like you don't know shit. You're coming in and I'm showing you the move. And you're literally going out there and you're trying to me that's not even drilling. That's like teaching like you're trying to learn something. So obviously, in someone's earlier periods, they're spending a lot of time in that phase because they literally don't even know how to move their bodies the right way. Once you learn the skill, then there's the drilling because you need to the absolutely have to get those reps to become really proficient in that movement, and then the sparring and then the live right. And so like, I think, obviously, by the time you get to the kind of end point, right, but further on, the time you spend teaching is so I don't want to say in upside, then the learn and learning teaching phase is not insignificant, but so much smaller because to someone who's really good who have coached for 10 years, I don't have to give this big, long, drawn out explanation. I said, Hey, move, move your hand a little differently. Or just do this. Right? We don't spend any time there. So I think that's like something that consumes for the younger kids, say five through 12 or 13, we're consuming a massive amount of time there on that teaching learning phase. And then as we get older, that time wanes a lot. But that makes total sense, right? It's funny because when you look at like jiu jitsu schools, they spend a lot of time in the teaching learning and then the live. So like, there's not enough drilling. I like how you draw a distinction there because it feels like you're always starting from scratch. Like people have like very crappy short term memory. They're not like the way teaching is done is you show a technique from scratch and it seems disjoint. It is for sure. Especially if you have a class that's been with you for a while, you don't have to start from scratch. You can say, Hey, let's focus on this one little thing here or let's, after we do this, let's do that. And then you kind of put start putting it all together and then with jiu jitsu, the thing that I really struggle with was a couple of things. It was, and this is not speaking for all the jiu jitsu gyms, my personal experience through the sport. And I actually found my, so when I unretired, I found someone really great that I loved and I really wish it was Mark Lehman. I don't know if you know him at all. I wish I would have found him earlier because he was just tremendous. But number one, there's no drilling. So it's like in wrestling, I can boil down to, I could probably name you the best six moves, right? So we need as younger people, single leg, right? Single legs can be the most proficient takedown. It always has been. I don't know. Probably always will be unless they figure out something different. The robot. The robot figures out something different. We're going to shoot a lot of single legs. Why? Because everyone's going to do that, right? We're going to shoot a lot of single legs. So just like say an arm bar or some type of sweep, right? Why can't we go get 50 reps there? Hey, we, I mean, by the time I've been in your jujitsu school for two years, I better know fucking arm bar. I better know it. So don't, don't spend 10 minutes teaching me. Just tell me to go hit 50 reps. And then if one, I'm hitting my reps, if there's something I'm doing wrong, then just say, Hey Ben, move your leg a little bit that way or raise your hips up a little more, right? Like correct as you're drilling. So you're getting all these reps at it. So you're becoming more proficient. And then the other thing I really struggled with was to your point during live so many times it's just this five minute go, go, go. And that's not the most efficient way to learn because when you have two people, especially when they're focused on winning and you say go, they're going to go to wherever they do best. Well, if I'm trying to make you good at something, I don't want you doing what you do best all the time. I need you doing some other things, right? If you have a great single leg, but you can't shoot to the other side of their body, we need to work on that, right? You need to start shooting the other side. There's some sense that you, it's not like you should be told what to work on, but you should be told to work on the thing that you want to work on. Meaning because I don't know, maybe you can comment on this, but you know, everybody develops a different game as you get better and better. There's a set of things you need to be working on. So I actually have, like when I, especially when I'm like training very seriously, I'll have a specific technique that I have in mind and I have a sheet of paper on the side where I literally, my head keep counting off how many times I put myself in that position and pulled off the technique. And that's all I care about in like training. So I'll just, whatever it is, if it's a guillotine, it's a guillotine, arm drag, arm drag. But I want to make sure I don't, I love numbers. So I'll say like, I'll make sure I get 50 arm drags and I'm not getting off the mat until I do. And that, you know, if it takes- In a thrilling or live contest. So in this, in the thing I'm describing right now is the live contest. But drilling, obviously drilling, I can't find a drilling part. Like it's so hard to find drilling partners. Even- So boring. It's annoying to me that this is boring and there's nothing more annoying to me than the look of boredom on another person's face when we're drilling. It's like- Do you really think drilling is that beneficial to you? Because you said that it's a job. Yes. Yes. And he thinks I'm an idiot, but yes. Why? Why am I an idiot or why is this drilling beneficial? Let's go with two direct positions. Why is it so beneficial? I think for me, there's a meditative aspect to it where the more you drill, the more you start noticing the details. The minute details. Let me push back a little bit here. I'm not going to push back all the way because every time if I was wrestling, I'll want to high high crotch chin, like whatever. But even so say like at a high level when I'm really wrestling 10 years ago, even during that drill portion, if we talk about the resistance of our opponent from zero to 100, it's very likely that my partner at that point, because there's people I'm really comfortable with, they're probably at least going 20 or 30. They're probably giving me a certain look with the sprawl or I got to get through their hands. If I don't set it up right, they might put their arm down. We are drilling because we're wrestling at a really low resistance level, but there's a little bit of sparring. Oh yeah, the 20%. Yeah, yeah. Yeah. So that's not really drilling. I think it's drilling. I think literally you're shooting and I'm just boom, boom, boom, boom, boom, boom, boom type of thing. No, it's very hard to be a dummy that doesn't do 20%. You're going to do 20%. Yeah. So yes, it's 20%. So that's like sparring a little bit then. No, but they're not really resisting. They're just giving you the right frame. They're giving you the right movement. They're being an intelligent dummy, essentially. But also the really important component of this is you pick the techniques for which is beneficial. If the technique has dynamic elements to it, you don't want to be doing that with... I'm saying there's certain moves and I like those moves and I select the game base in those moves. So are you drilling to get better or are you drilling just to work out? No, to get better. That's what I'm trying to tell you. I believe you can become exceptionally good very fast by drilling. But how? First of all, let me ask you an empirical question. Have you actually drilled 10,000 times? Absolutely. Millions. If you haven't drilled millions... Hundreds of thousands, likely. I think you're just saying numbers. I don't think you know what 100,000... The number is freaking astronomical. It's way more than 10,000. I don't think you know what 100,000 feels like. There was a 10-year period where I wrestled every single day. That's 3,000 days. So you're telling me 10,000, that's only three of them a day. I do way more than that. Probably 30 of them a day. That's 100,000. Yeah. Hundreds of thousands. I doubt you did 30 a day for a particular technique. I did. For sure, 100%. There's no doubt. All right. Because some days I might do 100. So 30 out of 30 is not very many, especially if we count all reps, if we're counting drilling and live. So our college coaches would make us just drill a lot, and I always hated it. So I would rebel and just kind of give a little spar. You shoot a high crotch, we'll start. Coach wants to drill a high crotch. Okay, we'll start. You shoot the high crotch, that's great. Then I'm gonna sit the corner, or I'm gonna give you my hip, or I'm gonna try something. So then you have to react. And I would argue that all skill level past the beginner stuff is some necessity of that. I'm gonna do this, then what are you gonna do? It's back and forth. I shoot a single leg, what are you gonna do? I shoot a high crotch, what are you gonna do? And you have to start unconsciously programming these things in your head, because if you consciously think about it, it's gonna be too slow to actually hit it at math. But the drilling is the unconscious programming. But the simple movement, the first simple movement, the first simple movement, that single leg, or the high crotch, or arm drag, whatever. I feel like the amount you're gonna get better at it is so minuscule compared to the amount you're gonna gain at doing other things around it. No, but that's the key word, you feel. That's your opinion. I think if we did a study on it, that I would be proven correct. Perhaps. So first of all, your brain, as an exceptionally creative combat athlete, it's clear that you don't like the boredom of drilling. It's obvious that you have, you're such a creative energy, that you're just not going to be somebody who's going to enjoy that. So enjoyment is probably, having an active mind is really important. So the question is, do you have the kind of makeup that has an active mind during a drilling on a dummy? And I have that mind. But, do you really think, okay, so if you're, let's pick a technique. What technique do you wanna drill on? Are we doing jiu-jitsu or wrestling? Whatever you want. It's hard to describe with words, but certain guard passes. Let me think, just guard pass. Okay, so you have a guard pass and you get it to be a nine and a half out of 10, right? From a technical standpoint. Don't you think you need some resistance to feel? Because essentially all benefit after that is going to be, what are they going to try to do to me? And if they shift it that way, do I need to sink here or move there? So it's like, I actually think we're agreeing, but maybe terminology wise. Well, the split is the important thing, like how much of each. So I think it is spar. I think it's a very light touch spar is what you're talking about, which is in my opinion really isn't drilling. And it's because drilling past the basic proficiency, I don't think brings much value. But that's what I'm trying to tell you is I think it does. I think if you're doing that same movement, I think you begin to learn more over time. You're saying like once you get the basic proficiency, then there's a diminishing returns. I don't think so. Yes, that's what I think. I don't think so. I think everything has diminishing returns when you're learning a technique. But with something as complex as wrestling or grappling, if you can have way more gains over here, why focus on going from a 9.7 to a 9.8? If this other area, if you're spending so much time here that there's other areas left unexplored and you can make gigantic gains over there. No, but you're going to lose. I think a lot depends on your style. I think a lot is determined by how good you are at one thing. So if you want to become a master of a particular thing and then make your whole game where it's all pulled into that system, then I don't know. I think one is too small of a number. Yeah, it's small. I feel like you can't be easily this. Yeah, you want to funnel. You want to create funnels. Funnels. Funnels, right? And then it's all feel. And then it's all feel. You can win 100%. Yeah. Yeah. But I feel you can get like drilling on a dummy 80% of the time and 20% of the time live rolling with people worse than you. Like a little bit worse than you or a lot worse than you. So I definitely think. So my buildup would be teach. So we're talking about complex technique, right? So by the time we're talking about, we'll say a late high school kid who's pretty proficient. He's probably done the drilling part. So then now it's like, okay, if I want to get something new to you, I'll probably tell you you'll probably be able to do the basic premise within five to 10 minutes if they're good, right? Do this. Okay, they do it. Then it's like, okay, so now here from here, what are we going to do? We're going to go light sparring. So I know you have success because I need you to complete the task in order to get better at it. That's something a lot of people in wrestling mess up. They just want to go to the toughest person. But if you go to the toughest person, you're not going to actually execute on any skills. You're going to get a workout, and I need you to execute because I need you to get good at this. In order to get good at it, you have to get all the way through the technique. Why do you need them to complete? Just so they gain confidence in the technique or they go through all the steps of the technique? They have to feel all the way through. Like if I said, learn a high crotch when you're drilling, but stop halfway every time. But you're not actually going to be able to do it because you're going to stop, you're not going to have the feel. So try it on someone, spar lightly, get it. Do it on someone who's not as good as you, get it, then work your way up the ladder until you can get it on someone your own skill level or maybe better than you in a live competition. So it's like, I don't know, I feel like that basic drilling, so a kid like Keegan who I've brought up a few times, I feel like if there's something new, I could literally tell him like, this is what I want you to do, and he has such a great feel, he could go drill it proficiently within probably a minute or two. But then to hit it on someone high level, that's going to take quite a while longer. And that's a mix of drilling and sparring on people a little bit worse than you. Yeah, and then equal and then better. Because there's this, with grappling, there's such a feel component to the pressure, the movement, all these things, and there's so many things you can throw at someone out of one position, not just moves, but moves at different levels of force or whatever. Are you and these kids developing a big picture strategy of what are the main setups and takedowns and just a whole system? I kind of sent you our technique book, right, and how we kind of go at it, approach it. So I think in wrestling, you're going to need a handful of things just off the word go, right? You're going to, so I think on our feet, I need to be able to take this side of the body, I need to be able to take that side of the body, I need to be able to bring you underneath me, I need to be able to go around you, right? Now we can accomplish those different ways, but we should have all of those weapons if we want to be really good some way, right? So if I neglect one of those, so if I neglect the ability to say pull you down, right, if I headlock you, now if I have a good shot and you're smart, you're just going to lower your stance. So my shot is not going to be as successful and I have the inability to pull you down, right? So I need to feed all of those so I can, as they get better, I can point those things out. On bottom, my folks out bottom, there's certain things like you have to be good at leg right defense, right? You have to, I mean, at a high level, you're just going to, when you get it in, you're just going to get stuck there, not going to be able to escape. But besides that, yeah, there's a multitude of things that you can choose from and I'm going to, depending on your body style and what you're good and bad at, I'm going to probably develop something a little different. I might give you, hey, you do the quad pod, you'd be better as a knee slide, whatever. Yeah, top kind of same thing. I have to ask you about Khabib. So I remember a while ago, Rogan said that that's the perfect fight for Khabib. You are. So let me ask two questions. The first, do you think you can beat him in an MMA match when you're at your peak? I don't like, yeah, I mean, it's one of those people where people like will get really mad at me if I say yes. But yeah, I mean, how would you do it? How would you solve that puzzle? Yeah. I mean, we would grapple and I think I would be better than him. But I, you know, I feel weird saying is people like, yeah, right, you're full of shit, you know? And but that's no, no one out grappled him, right? I mean, nobody did. And maybe I'm wrong on this, but I have we will get the best possible candidates. I'm definitely one of them. And then obviously I have a small size advantage, too. So in a wrestling match, so we can just reduce that MMA match to a wrestling match. What do you think is the right strategy on him? Like, did you understand his style that the his wrestling style, the pressure he applies? Do you understand how the hell he makes that happen? Yeah. I mean, he never, unfortunately, fought any real who I would say really, really high level wrestlers. I was actually really disappointed how bad Justin Gaethje's wrestling was, because Justin Gaethje had some solid success, but his wrestling was really bad in that fight. He had success in NCAA. Yeah, I think he was seventh place, maybe or so somewhere. He was definitely all American. It was lower, though. So, yeah, I would like to see how he dealt with someone who was like a who I think, oh, man, this guy's a really high level wrestler because, you know, we saw and this is early in his career, but, you know, Gleason Tebow did give him some issues earlier in his career. So I would like to see him in that situation and see how he does. I would love to like, you know, I just love wrestling grappling. Like, yeah, I'd love this. Someone said, hey, Ben, you know, Kabir wants to roll with you. Okay, I'm there tomorrow. It sounds like a blast. Let's go. He's probably competitive as hell. Yeah. You're still competitive. I know when to be and when not to be like, you know, say if I'm going to high school kids or not going to be competitive because then I'm just being a dick. How would you take him down? What? What we're talking about? Real wrestling? Like, just wrestling? Wrestling. Wrestling. I would probably try to take single legs and stuff. Single legs. Yeah. Okay. I mean, I know I've honestly, I don't have the slightest clue. I'd have to feel I'd feel him out. But single legs my best take. People talk about his wrestling being really good. People that train with him. So, okay. So I grilled someone. I will not say who on the Ed Ruth thing. Ed Ruth is very elite and focused on wrestling. He never became that great at fighting, unfortunately. Wait, Ed Ruth wrestled Kabir? They were on the same team for a while. Yeah. Okay. And there was rumors that Kabir beat him up. And I said, I sure can't believe that. And I've heard that that was, if they were just straight wrestling, Ed would get slightly the better of it. Wait, Ed Ruth is like one of the greats. He's great. He's really good. Yeah. So that was what I heard. But in an MMA setting, because of all the tools that Kabir would get him. I don't know. But I agree. I agree with Rogan on this one. That would have been good to see. Yeah. That would have been fun. So yeah, if Kabir wants to work out, I'd love it. I love wrestling and grappling. I don't do much Jiu-Jitsu because I just don't have time for it anymore. I'm at the Wrestling Academy every single day. But I love Jiu-Jitsu while I did it. And if I didn't have Wrestling Academy, I probably would still be doing Jiu-Jitsu. Yeah, you did well in Jiu-Jitsu as well. But let me ask you a ridiculous question. Who's the greatest of all time, freestyle or folk style? Oh, wrestling. Wrestling. Hmm. I will say my knowledge past the year 2000 is really not that great because you can't be- In which direction? Sorry, after 2000? No, before. Because you can't find any film or anything. So you hear of all- So you need evidence? You need direct evidence? I want to be able to watch them and see them and feel the times and feel their opponents and all those things to really like, I hate giving bad answers. So there's just not enough footage of any of those people. We go back to someone like Alexander Medved. You can't find footage. You can't find anything on him. So who is he wrestling? I'm not sure. So post-2000, I think, and obviously just freestyle. Americans? Russians? Seteev has probably the best argument post-2000. I think Sedulayev. Yeah, the Russian tank. Beat Snyder? That guy is, yeah. So who's better, Snyder or Sedulayev? So Sedulayev just won at the Olympics. I understand this. I understand how that works, but it's pretty close, right? Not really. Not that match, but in general, the matchup. So Kyle won the first one in 17. Sedulayev pinned him the following year, but then Kyle lost and took bronze in 19 and then just lost. I don't want to say fairly decisively, but it was six to three and there was a late takedown. He kind of gave it up and maybe if it was really competitive, maybe he wouldn't have taken a wrestle again in like two weeks here. So yeah, you have to say Sedulayev at this point. There's nothing else to say unless Kyle proves this otherwise. Yeah, not enough people talk about Sedulayev. Okay, well, you think that guy should go to MMA? You think Kyle should go to MMA? Some of these guys. Yeah, they're making enough money in wrestling where they don't really feel the need to. It's terrifying though, as a heavyweight, Sedulayev would probably, it's like Khabib, but heavyweight. Well, I don't know if you remember, do you remember Bilal Mokhov? So Bilal Mokhov actually was the Russian representative in both styles in 2016, Greco-Roman, and freestyle. And he was, to my knowledge, the only person the UFC's ever signed that was zero, in modern era, signed that was zero and zero. And then he actually never ended up fighting. But weird, right? So yeah. No motivation. I don't know what the story is. Sometimes out of Russia, I mean, maybe you have better sources than I do, sometimes it feels like dudes just disappear. Like they're a world champ or an Olympic champ and all of a sudden you're like, wait, where'd he go? You talked shit about Russia earlier in the conversation. Oh, what'd I say? I forgot, but I think- Steroids? I think somebody's going to show up to your door. I'm worried. I honestly, I've said enough bad things where I would be kind of looking over my shoulder if I went to the bathroom or something. I for one, love the Russians. What about Icarus? How does that make you feel? What about it? It's fake news. Oh, really? I'm just kidding. It's propaganda? Maybe it is. I don't know. I don't know what it is anymore. Yeah. You know, it's troublesome, man. It's just a thing in all of its forms. Any other recaps from the Olympics of 2020, Tokyo, that stood out to you? Gable Stevenson, anything like that? It was great. Yeah. No, I think America's coming to the point where we're going to compete with Russia every single year in wrestling, which obviously, long, long time ago, many, many years ago, we did, we were great. And then kind of after that Soviet Union period, I think there was a lot of poverty in that area and that kind of led the wrestling team going down a little bit. And then obviously, a lot of those regions, where they found oil and gas in the Caspian Sea, I believe, and they've been really kind of on the upswing for the last 20 years. And now America really, since 2012, has been on the upswing in wrestling and we're kind of really competing with them. And they're not sending a couple of their best guys. So for those who don't know, the Olympics got pulled back a year. So they are hosting the 2021 World Championships, despite the fact that we just had the Olympics two months ago. So it's happening next week in Oslo, Norway. So like Russia's not sending their number one at 57 and their number one at 65. So it's like America's probably going to win, I think. I don't want to guarantee anything, but there's a really good chance. Is Dave Taylor also competing? America gave any of the Olympians that medaled the opportunity to not even have to wrestle off. They just got to keep the spots until two months later if they medaled. So the only one who's not is Gable. Gable's moving on. We have a pretty good guy behind him named Nick Wazdowski, who's a world medalist. But then he's a Burlesfield in the 79 spot, Jayden Coxfield in the 92 spot, who's a world champion also. So we have a- It's a hell of a team. Pretty good squad, yeah. Pretty good squad. Pretty happy. Okay. So given your run in Bellator in one championship, that was like one of the most dominant runs in MMA. What would you say was key to your dominance in that long undefeated streak? Huh. Probably consistency would be one. The fact that I lived and trained the same way no matter where my life was, whereas a lot of fighters, once they start making money for the first time, they have all these obligations and they travel and they really enjoy making money. And that's kind of why some of them fall off. So you had the same process, the same camp? Yeah. I stayed up in my house. I had a lot of medication, everything. And so that was a big part of it. Obviously the style thing is like no one could- there was only a few people who could stop my style. And I think I continue to get better as a mixed martial artist. And I wasn't as innovative in mixed martial arts, but there was a handful of things that I innovated, specifically in the top position where I spent a lot of time where it was just like there was just- once I got on top of you, it was like in a spider web and there was just kind of no way out. You never felt the certain things I was doing. And so people just- they gave up eventually. How's the level of wrestling in MMA, would you say? So I saw somewhere like champions, the most popular martial art for current UFC champions are all wrestling. So we just lost a bunch of the belts. Wrestling, wrestling as a sport, right? But yeah, one point we had, I think it was eight of nine maybe or something to that effect. And I think it's not just wrestling, not just the actual martial art of wrestling that contributes to our success in mixed martial arts, but other things like the way we're systemized. So most kids who have all this have went through the high school program and the college program and they know how to show up on time and they know how to work hard. So when they go to ATT or AKA or wherever, they know how to show up on time and they know how to work hard and that's going to get you a really long way. Just those two things, right? Not even the techniques, it's just the discipline. Those things. Then I think you throw on top of that the fact that most of us have competed 1,500 to 2,000 times, probably by the time we get to 20 something, that's a huge advantage too. Most of these other people from other disciplines maybe have competed 100, if that, right? So we have this competitive process down really, really, really, really well. Plus the weight cut. The weight cut. There's all these things, right, that factor into it. I think the fact that we're really open-minded, I think if you would, I don't want to pick on jujitsu again, but how many jujitsu guys have became highly proficient in wrestling versus how many wrestling guys have became highly proficient in jujitsu? I think that number swings one way and not that much the other way. So we're open to adapting and learning and for some reason, jujitsu people, how many of them have got high level wrestling or even mediocre level wrestling? The number's really small. They refuse to. It's really frustrating. Why won't they do this? This is obviously a part of it. I don't pick on specific guys, but there's certain guys in the history of MMA where you're like, listen, man. I mean, Damian Maia, who was my last fight, is a great example of somebody who actually did get proficient wrestling, right? But there's some of these jujitsu guys who's like, if you just got on top, you would submit him. Why can't you learn a freaking takedown? Like, holy moly. Just learn how to take someone down. Once you get them down, they will not get up and you win the fight. It's so easy, but they refuse. How complicated is that journey? So like Donna Hurley, you mentioned, Craig Jones, they're big on wrestling as part of jujitsu now. Like wrestling, not just on the feet, but wrestling from the bottom coming up and all that kind of stuff. So how difficult is that whole skill set, would you say, for a jujitsu person to learn? Not that hard if they really put their mind to it. They already like, when you grapple, and this is any grappling art, like there's a certain part of it that you kind of get. And it can, might not be the exact same thing, but you understand how your body moves and how to feel certain pressures and you can adapt yourself pretty quickly, you know? So I don't think, I think there's a certain level of stubbornness where they didn't want to, certain people didn't want to do it for whatever reason. I think a lot of times in MMA, it's the I'm so macho, I can stand and bang thing, you know, show how much they are. But yeah, that was a frustrating one that they, there's a lot of wrestlers who became highly proficient in jujitsu and really adapted and it doesn't go the other way. And then I guess the other thing there too is they can both steal from each other, right? As any martial art can steal from another. And like, I feel like jujitsu didn't do enough stealing from wrestling. Like they should have looked at all the wrestling possible and said, well, why don't we steal that and that and that, you know, and like, hey, let's take that over. And maybe we'd make a little tweak because it's different, but there's something we can definitely use there. So like in wrestling, for example, you know, there's a one arm guillotine in jujitsu, right? Okay. So there's a move called, well, it's got a hundred names, like the oldest move in wrestling, because it's what they did, the cows, where they go around the chin and they throw them on the back. I don't recall that one. I don't know. Okay. Sorry. Did you just ask me what I call that one? Yeah. Would you take a cow and grab it by the neck and throw it to the side? No, but in wrestling, I don't know. Okay. We call you putting it under. Yeah. So you grab their chin and then you go under their arm and then throw them on their back. Okay. Gotcha. Yeah. So we call that the honey badger, but it's got honey badger, different names, wherever you go, it's got different names. So I would always, I would say like pre-jujitsu, I was, I was average at it. Like I could do it, but against good people, you'd never get it for because they would get the back of their head up and they were too strong where you couldn't collapse them by going over their neck. Right. Because the forces weren't right. So then in jujitsu, you learn the one arm guillotine where you grab their chin and this is more of a running along the side of their head. And then, and then you go here and you choke them. Right. Much more efficient way to move their head because the fulcrum is way down here and their head can move into that. Right. So once I learned that in jujitsu, I'm like, wait, I can do this in wrestling. So now once I learned how to grab their chin the right way and I do the honey badger, no one ever gets out. I just had to steal that jujitsu, put it in wrestling and boom, there we go. But very few people steal any direction that takes creativity. Really? And open mind. It's so easy because it's already done. You just got to steal it. I mean, same with judo. If you're a gi jujitsu person, there's so much stuff in judo that that's ripe for the stealing because judo is much more emphasizes explosive moves on the transition, which is something jujitsu does not do because you have some... You mean from the takedown to... From the takedown, but also just in general, just in the transition, the concept of transition, the like jujitsu is very much about like we're in this position, then we're in this position, then we're in this position. The judo is much more in when there's chaos of any kind. That's when you need to strike. And to learn that, I mean, that's why people like Travis Stevens and Jidoka, when they go to jujitsu, they can dominate, but jujitsu people should steal that. They're too stubborn. Yeah, but so is every... Wrestlers are stubborn too. No way. There would never be any stubborn wrestlers. Well, I mean, I was surprised. All these coaches, John Smith, Dan Gable, they don't really have interest in MMA or jujitsu and so on. But you would think somebody like a John Smith would like put on a white belt and roll around. Yeah, I think he's just too focused on what he's a coach and what he's doing. Yeah, I mean, yeah, I think if you take him when he's younger, he would have a lot of fun. We actually have a really good wrestler making his MMA debut tomorrow. Bo Nickel, I'm sure you've heard of him. Very high level. I think he's going to have a lot of success. I mean, some people might say that like jujitsu makes you a little comfortable being in your back and for a wrestler that could be like really bad. I hate that take. Yeah, but that's the Dan Gable take. It's so stupid. It's so stupid. For God's sakes, we know the fucking rules. Just wrestling. You don't go to your back. In jujitsu, you can. It's like whatever. Yeah. But like jujitsu, for example, so I coached when I was at Rufus, I coached the wrestling for a long time, three, four or five years. So I've been taking a jujitsu guy and teaching them a wrestling technique where you needed to use your feet. To teach jujitsu guys is so easy. So simple because they already understand the concept, butterfly guard, et cetera, et cetera, et cetera. To take a wrestler who's never done any of it and teach him how to use his feet, oh my God, he's such a beast. It's so hard because that's not a weapon they're thinking about using. So it's like we understand the rule. It's like freestyle folks are wrestling. Freestyle, I can lock my hands. You don't see people locking their hands all the time in folk style just because they did freestyle. It's like they get it. There's a rule. They understand it. So the notion that somebody is comfortable in your back. The pinning, that's like a, it has a special meaning. Yeah. I actually think, so jujitsu, you don't actually want to be flat, flat very often. I always wondered this because I did a couple of catch wrestling tournaments and I would put myself in butterfly guard and I wasn't going against good people, which is why I was doing all these things. But I wondered if you could create a system of wrestling where you're butterfly guard. So I think that there's, there's a few places where I use it, but so specifically the elevator series was my main series at bottom. It is, it's not butterfly guard. It's a butterfly guard, like grip with your foot. So I boom, I go here, I catch with my, your leg with my foot, boom and I elevate you over. Right. And then also sometimes like I think Keegan does this too from Washington, but like a double leg, sometimes if I'm accepting, so freestyle, obviously you're going to give a point to folks out, except that you've already got me. And as I go down, I'm just going to butterfly guard you up, you know, and then I'm gonna try to flip my hip back to the mat and get up in a wizard position. Like I've used that quite a few times where it is kind of like a bailout mechanism that gets me back to maybe not a great position, but obviously much better than being taken down. Beautiful. Yeah. So let's talk a little bit about crypto because you're also, you have a, you have a show, you are, you have a lot of interest in cryptocurrency. Why are you interested in cryptocurrency? Is it just a financial investment or is there a philosophy that attracts you to it? So I, my friend told me about it in 2017. I was actually, I went to, I was, I was, uh, my friend met me in Shanghai. I fought in one championship. Um, and he told me, and the second he told me, I'm like, Oh, I'm so in. Cause I had read Ron Paul and the fed. I had read, I, you know, kind of had an understanding how the fed is unfair. Um, and so we told him about crypto, this decentralized system that no one has control over. It just made sense. And so like we've had, you have the podcast with Tim Michael sailor on it and I love the way he said, it's like, who do you trust more with your money? You trust the politicians or do you trust engineers? I think that's an easy choice. I don't even think, I don't even think I have to think about that. I don't trust politicians no matter what country they come from, China, America, wherever. I don't trust them. So what about, uh, in, uh, in, uh, 2017, what was it? Bitcoin? Are you, um, what do you, what do you find? Which ones do you find interesting? Yeah, there's all kinds of ideas. So there's the, the, the, the more sort of primal mechanism of proof of work and Bitcoin. And then there's smart contracts, ideas, and, uh, there's all kinds of innovations across the different, uh, so I can't say I'm in super deep where I understand the technical components of a lot of minor. I understand what Bitcoin can do for people. And so that's probably the one I've, I focused the most on. Um, and I actually, I think I was talking about, I was trying to convince Michael to talk about Bitcoin cause he hates it also. And I think most of the main problems Bitcoin solves people in America are so American centric, they don't understand it. So like high levels of inflation that hasn't happened in, it was starting to happen. It hasn't happened in America in a long time. Right. But someone in Venezuela is like, Oh, I get that, you know, or remittance payments, right? Remittance payments to you see it. So I saw this in, um, when I was spending all the time in Singapore, Singapore is obviously a really wealthy country. And so you'd have Indonesian workers or Philippine where, and they would all go on Sundays. They would go to these places to ship stuff back to their families and through Western Union, Western Union gouges the shit out of these people. I mean, they're taking eight, 10, 12% of whatever they're sending. Then it takes five days and the person's gonna pick it up. Whereas Bitcoin, I could send you Bitcoin person to person, right? So like American people don't understand that American people don't really understand the unbanked, right? A decent portion of the world is unbanked. They don't have access to it. And a much, much, much smaller portion of the world doesn't have access to internet. So if I can put a mobile wallet on your phone and we can send money person to person, so there's a whole bunch of those problems where Americans don't really think about that are really obvious that this solves. So I think that's the key one. Obviously the fact that the value goes up is really outstanding also, but if you look at it, I got in in 2017 so I got to watch it go up. I didn't sell shit at the top, really stupid. And then the majority of my time was spent through the bear market. And so I had to love it for the principles that it provided, not the fact that actually I lost money in the beginning and now I'm way up. But yeah, so I- And you're just holding. You're just holding. I think at the top of this bull market, I'll probably sell a very small portion. So you mean like right now there's a bull market? Yeah. Most people think say in the next three to six months we'll be at the top of the market. So probably when that happens, I'll probably sell a little bit. You got to huddle it, Ben. You got to huddle. Well, yeah. So one of my podcast co-hosts, he's like super rich, like uber rich. So he has lost touch with the everyman. So here's my argument to him. It's really simple. And listen, I'm doing well for myself in life, but if say someone buys a Bitcoin, right? One Bitcoin at $5,000, which it was last year. And this Bitcoin goes from $5,000 to $200,000, which is right around what a lot of people think the peak is going to be. They bought one Bitcoin and they're living in a $200,000 house. So to take half of that, right? You started with $5,000 of Bitcoin. To sell half a Bitcoin for $100,000 and pay off your house, your remaining house payment, that's life changing to someone. It really is. And so you still have a Bitcoin. So if Bitcoin goes to a million, you're still going to have half a million and you're going to feel really, really rich with that half a million dollars because you bought it for $2,500, you know? So yeah, so I would encourage anyone who's not uber rich to, if you have huge profits, take a little bit of them because it could change your life. And if you hold it and it goes down, you're going to feel the pain of that. Like sometimes if you're more constrained financially, it's much more psychologically difficult to ride the ups and downs. Yeah, it is for sure. So they have these really fascinating things in Bitcoin. Actually, we just had the guy, one of the main guys on our podcast, it's called On Chain Metrics. And he said, all wallet transactions are visible, you know? And so they have all these fun categories. So actually, I think you said you don't like numbers, but- I like numbers. Oh, you love numbers. I love numbers. So I love numbers also. So they have all these different categories. Like you can see how long a wallet has held a Bitcoin, right? Or how many Bitcoins are in a certain wallet. And so what they've seen during the downturn, right? So April, it kind of peaked and went down, is that the whales are still buying. The whales are people of a thousand or more are still buying. The main group of sellers is the ones who held it from zero to three months. So like, they don't have money, they bought it because they thought it was going up. And now they're like, oh shit, I got to sell it. Whereas anyone's held it for a long time is generally still holding on to it. That's interesting. That's a good indicator, right? For the whole space. Yeah. Well, let me ask you for some advice. You've been through one heck of a career, one heck of a life. What advice would you give to a young person today? Well, in wrestling, I think wrestling is really a microcosm of what your life's going to be. And that's why one of the things that I stress to kids is like, if we can go through this now and figure out, I have a couple kids who are struggling with certain things right now. If you can figure out this now in wrestling, it's going to be a lot better to figure it out now and get over this mental hump than when you're 32 and you have two kids and your job's not going well. It's going to be a lot worse. It's going to be a lot more painful then. Let's fucking figure it out now. So a lot of these lessons we can learn from wrestling, whether it's persistence or perseverance or work ethic, or you know, I said wrestlers show up on time and they work hard, right? These things, if we can learn these things at an early age, those characteristics will generally carry on throughout our life. And those are the things that are going to make us really successful. So I would say find a great coach, someone who's going to spend a lot of time and put a lot of time into you and make sure they have a lot of wisdom and steal all the wisdom that you can from them. And then if you can be successful at one thing, generally whatever that recipe was that took you to be successful at that, apply it to everything else, right? Apply it to the rest of your life. Apply it to getting a wife that you enjoy. Apply it to living in a place you want to live, doing a job you want to do, right? There's so many possibilities and you just have to be bold enough to go take those chances. It's interesting because early on in life is when you have much more time. People don't realize it's time to learn the lessons. Somehow later in life you get busier, responsibilities and all that kind of stuff. High school is a magical time. In college. In college, yeah. There's so much time to learn. Right? You don't even have kids yet. Yeah, I don't have kids. But that still fills up. Well, no, on purpose. I did something that many people don't seem to be able to do. I walked away from a lot of responsibilities just by saying goodbye. Oh, okay. But meetings. Everybody around me at MIT was like, meetings fill the day. And then you have more projects and you do a great job and you become successful and then more meetings fill the day and more responsibilities as opposed to like, wait a minute, do I want to be involved in all these things? And instead, do I want to find one or two things to really focus on? And that's what I choose. But it becomes harder and harder and harder as you get older. And also the more success you have, you become sought after other places too. I'm sure that's happening with you. And it's hard to keep saying no, no, no. Saying no is hard. You're known for roasting people with a single boom roasted line. So any ideas? Maybe you want to mention malice, but any ideas come to mind when you look at me? Man, I did, you know what? If I was going to boom roast someone, I would want to kind of like research their career and dissect them and figure out their biggest negative to the core. And I did. I didn't have that notion with you. I figured I got a general sense of, okay, he's really successful. He's super sharp. He's really interested in some really interesting things. I bet we'll have a great conversation, but I had no intention to roast you. Yeah, there you go. What about malice? You had dinner with him last night for him. Oh, man. How'd you get to know him, by the way? Just Twitter. Twitter's the most magical place in the world, right? I always tell people it's the greatest source of information if you know how to use it. He's insane on Twitter, actually. So I had to unfollow him on Twitter because he- It was too intense? No, it was too much. It fills up. Like, I want to be able to consume the content. So if I want to see something he says, I can go to his page, right? But it's just too much for my timeline. I want to be able to consume who I follow. So I try to not follow a lot of people because I want to be able to consume them. And he was too much. He fights the trolls, which I don't know why you'd ever fight the trolls. There's just too many of them. Well, he's a troll himself. He's like the big troll fighting the little trolls. He's the king troll. There's a million of them. So even if you kill 100,000, there's still not 100,000 left. There's just too many. You just got to ignore them. It's like the Nightwalker or whatever. Well, I'll take it because you had nothing. You couldn't roast GSP out of respect, too. So I'm just going to take that as a sign of respect. What do you say bad about GSP? Now I try to roast his hair. Like, why are you trying to grow hair now after all these years? He looked good bald. Everyone loved him with his head shaved. Now it looks kind of strange. Like, why you got hair now? Well, it was one of the more surreal moments of my life. So he was here and he wore a black suit and tie. Oh, really? Yeah, we did the podcast with him, just mirror image of me. And then we also did, I haven't released it yet, but just the video together and I was doing a martial arts stuff in a suit and tie. That was quite, that's like certain moments in your life are just like, I can't believe I was part of that. Yeah, from GSP, so yeah, I don't think I have anything to roast him about. Maybe the Matt Sarah thing would be the one that you could get him with. I would be really fascinated to really dig deep from a sports psychology standpoint because he always talks about how much fear he had when he was competing. And I find that to be interesting because obviously, so it's almost like to me, it's almost like, was he successful despite that? Not because of that, right? And because anxiety usually leads to really negative performance for the majority of people. And what was it about him that the anxiety wasn't super negative? You know what I'm saying? It's very interesting. I wonder that too. So I have, I wonder that about him, but I have a huge amount of anxiety, especially with people, just about everything. So I wonder if that's helpful or not. It feels like it's very helpful. I think, so I think probably your everyday life is different than in a performance or a competition. You have to be super in the moment of what you're doing. So anything that's pulling you away, like, oh my gosh, high school kids, right? That coach, oh my gosh, that girl's in the stands and if I get beat, then, and they're actively thinking about this other thing when this is going on and I need all 100% of your focus. He's never, I don't think he has anxiety in the ring. That's the point. I think like I have the same thing. Like if I have a really high performance thing that I have to do, I don't know, a lecture in front of a lot of people. Yeah, that'd be a great example. That there's huge amount of anxiety weeks ahead, days ahead, hours ahead. So you have a system to get rid of it then? No, maybe, but it's just the body gets rid of it somehow. Yeah, there's not a system. Subconscious system. Yeah, it's self-preservation. So you don't actually have anxiety while you're performing. So that's like, so then that problem somehow, that problem has solved itself, right? The problem is when the anxiety is actually happening while the wrestling match is happening, that's the real issue. Yeah, but it like sneaks in there too. That's the difference between MMA and wrestling is there's no breaks in wrestling, right? I guess there is, you can look at the crowd a little bit, like you can look so maybe, but like the, there's other things we have to perform while there's more breaks, like a lecture, you can catch yourself thinking like in this conversation, you know, like I'll, I've said a bunch of stuff where I think, why the hell did you say that? That's dumb, right? That's the anxiety because there's a pause and that could be, I don't know, I think it just pushes me to be better, but maybe I could be way better if I let go of that. It's scary to think that GSB if you let go of that. But he's been better. Or did he ever, did he have a, like you're saying, like you don't necessarily feel those. So I think certain people that I've coached, like they would describe how they would feel literally during the wrestling match, right? And you're saying like during the speech performance, it's mostly gone. And that's, it'd be interesting to see if like, he talked a lot about that, but if it was all, if it was all the way somehow gone, and it means he would have a mechanism for it. So like I had a really bad performance my freshman year of high school at nationals because I had, I had the ability to be anxious. And one of my coaches talked about like, and a lot of A type personalities are kind of that way, you know, because they're trying to consider all possibilities at the same time. And, and, and while we're actually performing or competing, it's negative performance, right? So he said he would always, leading up to the match within say an hour, he would, his name was talking about fishing. He would get someone to talk about fishing with him because it would stop him thinking about the match and being uber anxious. So I, I kind of really took that to heart and it really helped me as I would always like have someone to talk to and just goof around about whatever. So I'm not thinking about this thing. And then once I step in, it's time to go. So I didn't have this like anxious buildup. And that was how, for me, I took it away. But like me, you know, like you said, you have a way to get it away, obviously, because it's, yeah, I guess, I guess there's a little, little tricks you come up with. Yeah. You start thinking about it's not fishing. Maybe I should try the fishing thing, but I hate fishing. So boring. Well, maybe, maybe it's good to think about that. All right, Ben, this is like I told you, I'm a big fan of a big fan of your wrestling, your fighting, your personality. Thank you for coming down. Thank you for talking today. It's a huge honor. Bam. Let's go wrestle. Thanks for listening to this conversation with Ben Askren. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Muhammad Ali. Only a man who knows what it is like to be defeated can reach down to the bottom of his soul and come up with the extra ounce of power it takes to win when the match is even. Thank you for listening, and hope to see you next time.

https://youtu.be/tApj7Q37P2k

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Russ Tedrake: Underactuated Robotics, Control, Dynamics and Touch | Lex Fridman Podcast #114

The following is a conversation with Russ Tedrick, a roboticist and professor at MIT and vice president of robotics research at Toyota Research Institute or TRI. He works on control of robots in interesting, complicated, underactuated, stochastic, difficult to model situations. He's a great teacher and a great person, one of my favorites at MIT. We'll get into a lot of topics in this conversation from his time leading MIT's DARPA Robotics Challenge Team to the awesome fact that he often runs close to a marathon a day to and from work barefoot. For a world-class roboticist interested in elegant, efficient control of underactuated dynamical systems like the human body, this fact makes Russ one of the most fascinating people I know. Quick summary of the ads. Three sponsors, Magic Spoon Cereal, BetterHelp, and ExpressVPN. Please consider supporting this podcast by going to magicspoon.com slash Lex and using code Lex at checkout, going to betterhelp.com slash Lex, and signing up at expressvpn.com slash LexPod. Click the links in the description, buy the stuff, get the discount. It really is the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This episode is supported by Magic Spoon, low-carb, keto-friendly cereal. I've been on a mix of keto or carnivore diet for a very long time now. That means eating very little carbs. I used to love cereal. Obviously, most have crazy amounts of sugar, which is terrible for you, so I quit years ago. But Magic Spoon is a totally new thing. Zero sugar, 11 grams of protein, and only three net grams of carbs. It tastes delicious. It has a bunch of flavors, they're all good, but if you know what's good for you, you'll go with cocoa, my favorite flavor and the flavor of champions. Click the magicspoon.com slash Lex link in the description, use code Lex at checkout to get the discount and to let them know I sent you. So buy all of their cereal. It's delicious and good for you. You won't regret it. The show is also sponsored by BetterHelp, spelled H-E-L-P, help. Check it out at betterhelp.com slash Lex. They figure out what you need and match you with a licensed professional therapist in under 48 hours. It's not a crisis line, it's not self-help, it is professional counseling done securely online. As you may know, I'm a bit from the David Goggins line of creatures and so have some demons to contend with, usually on long runs or all-nighters full of self-doubt. I think suffering is essential for creation, but you can suffer beautifully in a way that doesn't destroy you. For most people, I think a good therapist can help in this. So it's at least worth a try. Check out the reviews, they're all good. It's easy, private, affordable, available worldwide. You can communicate by text anytime and schedule weekly audio and video sessions. Check it out at betterhelp.com slash Lex. This show is also sponsored by ExpressVPN. Get it at expressvpn.com slash LexPod to get a discount and to support this podcast. Have you ever watched The Office? If you have, you probably know it's based on a UK series also called The Office. Not to stir up trouble, but I personally think the British version is actually more brilliant than the American one, but both are amazing. Anyway, there are actually nine other countries with their own version of The Office. You can get access to them with no geo-restriction when you use ExpressVPN. It lets you control where you want sites to think you're located. You can choose from nearly 100 different countries, giving you access to content that isn't available in your region. So again, get it on any device at expressvpn.com slash LexPod to get an extra three months free and to support this podcast. And now here's my conversation with Russ Tedrick. What is the most beautiful motion of a animal or robot that you've ever seen? I think the most beautiful motion of a robot has to be the passive dynamic walkers. I think there's just something fundamentally beautiful. The ones in particular that Steve Collins built with Andy Ruina at Cornell, a 3D walking machine. So it was not confined to a boom or a plane that you put it on top of a small ramp, give it a little push. It's powered only by gravity, no controllers, no batteries whatsoever. It just falls down the ramp. And at the time it looked more natural, more graceful, more human-like than any robot we'd seen to date. Powered only by gravity. How does it work? Well, okay, the simplest model, it's kind of like a slinky. It's like an elaborate slinky. One of the simplest models we use to think about it is actually a rimless wheel. So imagine taking a bicycle wheel, but take the rim off. So it's now just got a bunch of spokes. If you give that a push, it still wants to roll down the ramp. But every time its foot, its spoke comes around and hits the ground, it loses a little energy. Every time it takes a step forward, it gains a little energy. Those things can come into perfect balance. And actually they want to, it's a stable phenomenon. If it's going too slow, it'll speed up. If it's going too fast, it'll slow down. And it comes into a stable periodic motion. Now you can take that rimless wheel, which doesn't look very much like a human walking, take all the extra spokes away, put a hinge in the middle. Now it's two legs. That's called our compass gate walker. That can still, you give it a little push, starts falling down a ramp. Looks a little bit more like walking. At least it's a biped. But what Steve and Andy and Ted McGeer started the whole exercise, but what Steve and Andy did was they took it to this beautiful conclusion where they built something that had knees, arms, a torso, the arms swung naturally, give it a little push. And that looked like a stroll through the park. How do you design something like that? I mean, is that art or science? It's on the boundary. I think there's a science to getting close to the solution. I think there's certainly art in the way that they, they made a beautiful robot. But then the finesse, because they were working with a system that wasn't perfectly modeled, wasn't perfectly controlled, there's all these little tricks that you have to tune the suction cups at the knees, for instance, so that they stick, but then they release at just the right time. Or there's all these little tricks of the trade, which really are art, but it was a point. I mean, it made the point. We were at that time, the walking robot, the best walking robot in the world was Honda's ASIMO. Absolutely marvel of modern engineering. It's a 90s. This was in 97 when they first released, it sort of announced P2 and then it went through, it was ASIMO by then in 2004. And it looks like this very cautious walking, like you're walking on hot coals or something like that. I think it gets a bad rap. ASIMO is a beautiful machine. It does walk with its knees bent. Our Atlas walking had its knees bent, but actually ASIMO was pretty fantastic, but it wasn't energy efficient. Neither was Atlas when we worked on Atlas. None of our robots that have been that complicated have been very energy efficient, but there's a thing that happens when you do control, when you try to control a system of that complexity. You try to use your motors to basically counteract gravity. Take whatever the world's doing to you and push back, erase the dynamics of the world and impose the dynamics you want because you can make them simple and analyzable, mathematically simple. And this was a very sort of beautiful example that you don't have to do that. You can just let go, let physics do most of the work, right? And you just have to give it a little bit of energy. This one only walked down a ramp. It would never walk on the flat. To walk on the flat, you have to give a little energy at some point, but maybe instead of trying to take the forces imparted to you by the world and replacing them, what we should be doing is letting the world push us around and we go with the flow. Very zen, very zen robot. Yeah, but okay, so that sounds very zen, but I can also imagine how many failed versions they had to go through. I would say it's probably, would you say it's in the thousands that they've had to have the system fall down before they figured out how to get? I don't know if it's thousands, but it's a lot. It takes some patience, there's no question. So in that sense, control might help a little bit. Oh, I think everybody, even at the time, said that the answer is to do that with control, but it was just pointing out that maybe the way we're doing control right now isn't the way we should. Got it, so what about on the animal side? The ones that figured out how to move efficiently, is there anything you find inspiring or beautiful in the movement of any particular animal? I do have a favorite example. Okay. It sort of goes with the passive walking idea. So is there, how energy efficient are animals? Okay, there's a great series of experiments by George Lauder at Harvard and Mike Tranefilo at MIT. They were studying fish swimming in a water tunnel, okay? And one of these, the type of fish they were studying were these rainbow trout, because there was a phenomenon well understood that rainbow trout, when they're swimming upstream at mating season, they kind of hang out behind the rocks. And it looks like, I mean, that's tiring work swimming upstream. They're hanging out behind the rocks. Maybe there's something energetically interesting there. So they tried to recreate that. They put in this water tunnel, a rock, basically, a cylinder that had the same sort of vortex street, the eddies coming off the back of the rock that you would see in a stream. And they put a real fish behind this and watched how it swims. And the amazing thing is that if you watch from above what the fish swims when it's not behind a rock, it has a particular gate. You can identify the fish the same way you look at a human looking at walking down the street. You sort of have a sense of how a human walks. The fish has a characteristic gate. You put that fish behind the rock, its gate changes. And what they saw was that it was actually resonating and kind of surfing between the vortices. Now, here was the experiment that really was the clincher, because there was still, it wasn't clear how much of that was mechanics of the fish, how much of that is control, the brain. So the clincher experiment, and maybe one of my favorites to date, although there are many good experiments. They took, this was now a dead fish. They took a dead fish. They put a string that went, that tied the mouth of the fish to the rock. So it couldn't go back and get caught in the grates. And then they asked, what would that dead fish do when it was hanging out behind the rock? And so what you'd expect, it sort of flopped around like a dead fish in the vortex wake, until something sort of amazing happens. And this video is worth putting in. What happens? The dead fish basically starts swimming upstream. It's completely dead, no brain, no motors, no control, but it's somehow the mechanics of the fish resonate with the vortex street, and it starts swimming upstream. It's one of the best examples ever. Who do you give credit for that to? Is that just evolution constantly just figuring out by killing a lot of generations of animals, like the most efficient motion? Or maybe the physics of our world completely, is evolution applied not only to animals, but just the entirety of it somehow drives to efficiency? Like nature likes efficiency? I don't know if that question even makes any sense. I understand the question. That's the reason, I mean, do they co-evolve? Yeah, somehow co, yeah. I don't know if an environment can evolve, but. I mean, there are experiments that people do, careful experiments that show that animals can adapt to unusual situations and recover efficiency. So there seems like, at least in one direction, I think there is reason to believe that the animals' motor system, and probably its mechanics, adapt in order to be more efficient. But efficiency isn't the only goal, of course. Sometimes it's too easy to think about only efficiency. But we have to do a lot of other things first, not get eaten, and then all other things being equal, try to save energy. By the way, let's draw a distinction between control and mechanics. Like how would you define each? Yeah, I mean, I think part of the point is that we shouldn't draw a line as clearly as we tend to. But on a robot, we have motors, and we have the links of the robot, let's say. If the motors are turned off, the robot has some passive dynamics. Gravity does the work. You can put springs, I would call that mechanics. If we have springs and dampers, which our muscles are springs and dampers and tendons. But then you have something that's doing active work, putting energy in, which are your motors on the robot. The controller's job is to send commands to the motor that add new energy into the system. So the mechanics and control interplay somewhere the divide is around, did you decide to send some commands to your motor, or did you just leave the motors off, let them do their work? Would you say it's most of nature on the dynamic side or the control side? So like if you look at biological systems, or if we're living in a pandemic now, like do you think a virus is a, do you think it's a dynamic system, or is there a lot of control, intelligence? I think it's both, but I think we maybe have underestimated how important the dynamics are, right? I mean, even our bodies, the mechanics of our bodies, certainly with exercise, they evolve. But so I actually, I lost a finger in early 2000s, and it's my fifth metacarpal. And it turns out you use that a lot in ways you don't expect when you're opening jars, even when I'm just walking around, if I bump it on something, there's a bone there that was used to taking contact. My fourth metacarpal wasn't used to taking contact, it used to hurt, it still does a little bit. But actually my bone has remodeled, right? Over a couple of years, the geometry, the mechanics of that bone changed to address the new circumstances. So the idea that somehow it's only our brain that's adapting or evolving is not right. Maybe sticking on evolution for a bit, because it's tended to create some interesting things. Bipedal walking, do you, why the heck did evolution give us, I think we're, are we the only mammals that walk on two feet? No, I mean, there's a bunch of animals that do it a bit. A bit. There's a, I think we are the most successful bipeds. I think some, I think I read somewhere that the reason the evolution made us walk on two feet is because there's an advantage to being able to carry food back to the tribe or something like that. So like you can carry, it's kind of this communal cooperative thing, so like to carry stuff back to a place of shelter and so on to share with others. Do you understand at all the value of walking on two feet from both a robotics and a human perspective? Yeah, there are some great books written about evolution of, walking evolution of the human body. I think it's easy though to make bad evolutionary arguments. Sure. Most of them are probably bad, but what else can we do? I mean, I think a lot of what dominated our evolution probably was not the things that worked well sort of in the steady state, you know, when things are good. But for instance, people talk about what we should eat now because our ancestors were meat eaters or whatever. Oh yeah, I love that, yeah. But probably, you know, the reason that one pre-Homo sapien species versus another survived was not because of whether they ate well when there was lots of food, but when the ice age came, you know, probably one of them happened to be in the wrong place. One of them happened to forage a food that was okay even when the glaciers came or something like that. I mean, there's a million variables that contributed and we can't, and actually the amount of information we're working with in telling these stories, these evolutionary stories is very little. So yeah, just like you said, it seems like, if you study history, it seems like history turns on like these little events that otherwise would seem meaningless, but in the grant, like when you, in retrospect were turning points. Absolutely. And that's probably how, like somebody got hit in the head with a rock because somebody slept with the wrong person back in the cave days and somebody get angry and that turned, you know, warring tribes combined with the environment, all those millions of things and the meat eating, which I get a lot of criticism because I don't know, I don't know what your dietary processes are like, but these days I've been eating only meat, which is, there's a large community of people who say, yeah, probably make evolutionary arguments and say, you're doing a great job. There's probably an even larger community of people, including my mom, who says it's a deeply unhealthy, it's wrong, but I just feel good doing it. But you're right, these evolutionary arguments can be flawed. But is there anything interesting to pull out for- There's a great book, by the way, well, a series of books by Nicholas Taleb about fooled by randomness and black swan, highly recommend them, but yeah, they make the point nicely that probably it was a few random events that, yes, maybe it was someone getting hit by a rock, as you say. That said, do you think, I don't know how to ask this question or how to talk about this, but there's something elegant and beautiful about moving on two feet. Obviously biased, because I'm human, but from a robotics perspective too, you work with robots on two feet. Is it all useful to build robots that are on two feet as opposed to four? Is there something useful about it? I think the most, I mean, the reason I spent a long time working on bipedal walking was because it was hard. And it challenged control theory in ways that I thought were important. I wouldn't have ever tried to convince you that you should start a company around bipeds or something like this. There are people that make pretty compelling arguments. I think the most compelling one is that the world is built for the human form. And if you want a robot to work in the world we have today, then having a human form is a pretty good way to go. There are places that a biped can go that would be hard for other form factors to go, even natural places. But at some point in the long run, we'll be building our environments for our robots probably. And so maybe that argument falls aside. So you famously run barefoot. Do you still run barefoot? I still run barefoot. That's so awesome. Much to my wife's chagrin. Do you want to make an evolutionary argument for why running barefoot is advantageous? What have you learned about human and robot movement in general from running barefoot? Human or robot and or? Well, you know, it happened the other way, right? So I was studying walking robots. And there's a great conference called the Dynamic Walking Conference where it brings together both the biomechanics community and the walking robots community. And so I had been going to this for years and hearing talks by people who study barefoot running and other mechanics of running. So I did eventually read Born to Run. Most people read Born to Run. Of course they did. Right? The other thing I had going for me is actually that I wasn't a runner before and I learned to run after I had learned about barefoot running, or I mean started running longer distances. So I didn't have to unlearn. And I'm definitely, I'm a big fan of it for me, but I'm not gonna, I tend to not try to convince other people. There's people who run beautifully with shoes on and that's good. But here's why it makes sense for me. It's all about the long-term game, right? So I think it's just too easy to run 10 miles, feel pretty good. And then you get home at night and you realize, my knees hurt. I did something wrong, right? If you take your shoes off, then if you hit hard with your foot at all, then it hurts. You don't like run 10 miles and then realize you've done some damage. You have immediate feedback telling you that you've done something that's maybe suboptimal and you change your gait. I mean, it's even subconscious. If I right now, having run many miles barefoot, if I put a shoe on, my gait changes in a way that I think is not as good. So it makes me land softer. And I think my goals for running are to do it for as long as I can into old age, not to win any races. And so for me, this is a way to protect myself. Yeah, I think, first of all, I've tried running barefoot many years ago, probably the other way, just reading Born to Run. But just to understand, because I felt like I couldn't put in the miles that I wanted to. And it feels like running for me, and I think for a lot of people, was one of those activities that we do often and we never really try to learn to do correctly. Like, it's funny, there's so many activities we do every day like brushing our teeth, right? I think a lot of us, at least me, probably have never deeply studied how to properly brush my teeth, right? Or wash, as now with the pandemic, or how to properly wash our hands. We do it every day, but we haven't really studied, like, am I doing this correctly? But running felt like one of those things that it was absurd not to study how to do correctly because it's the source of so much pain and suffering. Like, I hate running, but I do it. I do it because I hate it, but I feel good afterwards. But I think it feels like you need to learn how to do it properly. So that's where barefoot running came in. And then I quickly realized that my gait was completely wrong. I was taking huge, like, steps and landing hard on the heel, all those elements. And so, yeah, from that, I actually learned to take really small steps. I already forgot the number, but I feel like it was 180 a minute or something like that. And I remember I actually just took songs that are 180 beats per minute. And then, like, tried to run at that beat just to teach myself. It took a long time. And I feel like after a while, you learn to run, but you adjust it properly without going all the way to barefoot. But I feel like barefoot is the legit way to do it. I mean, I think a lot of people would be really curious about it. Can you, if they're interested in trying, what would you, how would you recommend they start or try or explore? Slowly, that's the biggest thing people do is they are excellent runners and they're used to running long distances or running fast and they take their shoes off and they hurt themselves instantly trying to do something that they were used to doing. I think I lucked out in the sense that I couldn't run very far when I first started trying. And I run with minimal shoes too. I mean, I will, you know, bring along a pair of, actually like Aqua socks or something like this. I can just slip on or running sandals. I've tried all of them. What's the difference between a minimal shoe and nothing at all? What's like feeling wise, what does it feel like? There is, I mean, I noticed my gait changing, right? So, I mean, your foot has as many muscles and sensors as your hand does, right? Sensors, ooh, okay. And we do amazing things with our hands and we stick our foot in a big solid shoe, right? So there's, I think, you know, when you're barefoot, you're just giving yourself more proprioception. And that's why you're more aware of some of the gait flaws and stuff like this. Now you have less protection too, so. Rocks and stuff. I mean, yeah, so I think people who are afraid of barefoot running, they're worried about getting cuts or getting stepping on rocks. First of all, even if that was a concern, I think those are all like very short term. You know, if I get a scratch or something, it'll heal in a week. If I blow out my knees, I'm done running forever. So I will trade the short term for the long term anytime. But even then, you know, this, again, to my wife's chagrin, your feet get tough, right? And- The callus, okay. Yeah, I can run over almost anything now. I mean, what, maybe, can you talk about, is there hint, like, is there tips or tricks that you have, suggestions about, like if I wanted to try it? You know, there is a good book, actually. There's probably more good books since I read them. But Ken Bob, Barefoot Ken Bob Saxton, he's an interesting guy. But I think his book captures the right way to describe running, barefoot running to somebody better than any other I've seen. So you run pretty good distances, and you bike, and is there, you know, if we talk about bucket list items, is there something crazy on your bucket list, athletically, that you hope to do one day? I mean, my commute is already a little crazy. What are we talking about here? What distance are we talking about? Well, I live about 12 miles from MIT, but you can find lots of different ways to get there. So, I mean, I've run there for many years, I've biked there. Long ways? Yeah, but normally I would try to run in, and then bike home, bike in, run home. But you have run there and back before? Sure. Barefoot? Yeah, or with minimal shoes or whatever that. 12 times two? Yeah. Okay. It became kind of a game of how can I get to work. I've rollerbladed, I've done all kinds of weird stuff. But my favorite one these days, I've been taking the Charles River to work. So I can put in a little rowboat, not so far from my house, but the Charles River takes a long way to get to MIT. So I can spend a long time getting there. And it's not about, I don't know, it's just about, I've had people ask me, how can you justify taking that time? But for me, it's just a magical time to think, to compress, decompress. You know, especially I'll wake up, do a lot of work in the morning, and then I kind of have to just let that settle before I'm ready for all my meetings. And then on the way home, it's a great time to sort of let that settle. You lead a large group of people. I mean, is there days where you're like, oh shit, I gotta get to work in an hour? Like, I mean, is there a tension there? And if we look at the grand scheme of things, just like you said, long-term, that meeting probably doesn't matter. Like, you can always say, I'll run and let the meeting happen how it happens. Like, how do you, that zen, how do you, what do you do with that tension between the real world saying, urgently, you need to be there, this is important, everything is melting down, how are we gonna fix this robot? There's this critical meeting, and then there's this zen beauty of just running, the simplicity of it, you along with nature. What do you do with that? I would say I'm not a fast runner, particularly. Probably my fastest splits ever was when I had to get to daycare on time because they were gonna charge me some dollar per minute that I was late. I've run some fast splits to daycare. But those times are past now. I think work, you can find a work-life balance in that way. I think you just have to. I think I am better at work because I take time to think on the way in. So I plan my day around it, and I rarely feel that those are really at odds. So what, the bucket list item. If we're talking 12 times two, or approaching a marathon, what, have you run an ultra marathon before? Do you do races? Is there, what's- Not to win. Not to. I'm not gonna take a dinghy across the Atlantic or something if that's what you want. But if someone does and wants to write a book, I would totally read it because I'm a sucker for that kind of thing. No, I do have some fun things that I will try. I like to, when I travel, I almost always bike to the Logan Airport and fold up a little folding bike and then take it with me and bike to wherever I'm going. And it's taken me, or I'll take a stand-up paddle board these days on the airplane, and then I'll try to paddle around where I'm going or whatever. And I've done some crazy things. But not for the, you know, I now talk, I don't know if you know who David Goggins is by any chance. Not well, but yeah. But I talk to him now every day. So he's the person who made me do this stupid challenge. So he's insane and he does things for the purpose, in the best kind of way. He does things like for the explicit purpose of suffering. Like he picks the thing that, like whatever he thinks he can do, he does more. So is that, do you have that thing in you or are you? I think it's become the opposite. It's a. So you're like that dynamical system, that the walker, the efficient. Yeah, it's leave no pain, right? You should end feeling better than you started. But it's mostly, I think, and COVID has tested this, cause I've lost my commute. I think I'm perfectly happy walking around town with my wife and kids, if they could get them to go. And it's more about just getting outside and getting away from the keyboard for some time, just to let things compress. Let's go into robotics a little bit. What to you is the most beautiful idea in robotics? Whether we're talking about control, or whether we're talking about optimization and the math side of things, or the engineering side of things, or the philosophical side of things. I think I've been lucky to experience something that not so many roboticists have experienced, which is to hang out with some really amazing control theorists. And the clarity of thought that some of the more mathematical control theory can bring to even very complex, messy looking problems, is really, it really had a big impact on me. And I had a day even just a couple of weeks ago where I had spent the day on a Zoom robotics conference, having great conversations with lots of people. Felt really good about the ideas that were flowing and the like. And then I had a late afternoon meeting with one of my favorite control theorists. And we went from these abstract discussions about maybes and what ifs and what a great idea, to these super precise statements about systems that aren't that much more simple or abstract than the ones I care about deeply. And the contrast of that is, I don't know, it really gets me. I think people underestimate maybe the power of clear thinking. And so for instance, deep learning is amazing. I use it heavily in our work. I think it's changed the world unquestionable. It makes it easy to get things to work without thinking as critically about it. So I think one of the challenges as an educator is to think about how do we make sure people get a taste of the more rigorous thinking that I think goes along with some different approaches. Yeah, so that's really interesting. So understanding the fundamentals, the first principles of the problem, or in this case, it's mechanics, like how a thing moves, how a thing behaves, like all the forces involved, really getting a deep understanding of that. I mean, from physics, the first principle thing come from physics, and here it's literally physics. Yeah, and this applies, in deep learning, this applies to not just, I mean, it applies so cleanly in robotics, but it also applies to just in any data set. I find this true, I mean, driving as well. There's a lot of folks that work on autonomous vehicles that don't study driving. Like deeply. I might be coming a little bit from the psychology side, but I remember I spent a ridiculous number of hours at lunch at this like lawn chair, and I would sit somewhere in MIT's campus, there's a few interesting intersections, and we just watch people cross. So we were studying pedestrian behavior, and I felt like, I had to record a lot of video, to try, and then there's the computer vision extracts their movement, how they move their head, and so on, but like every time, I felt like I didn't understand enough. I just, I felt like I wasn't understanding what, how are people signaling to each other? What are they thinking? How cognizant are they of their fear of death? Like what's the underlying game theory here? What are the incentives? And then I finally found a live stream of an intersection that's like high def, that I just, I would watch, so I wouldn't have to sit out there. But it's interesting, so like I feel. I get it. That's tough, that's a tough example, because, I mean the learning. Humans are involved. Not just because human, but I think the learning mantra is that basically the statistics of the data will tell me things I need to know, right? And for the example you gave of all the nuances of eye contact or hand gestures or whatever that are happening for these subtle interactions between pedestrians and traffic, right? Maybe the data will tell that story. Maybe even one level more meta than what you're saying. For a particular problem, I think it might be the case that data should tell us the story. But I think there's a rigorous thinking that is just an essential skill for a mathematician or an engineer that I just don't wanna lose it. There are certainly super rigorous control, or sorry, machine learning people. I just think deep learning makes it so easy to do some things that our next generation are not immediately rewarded for going through some of the more rigorous approaches. And then I wonder where that takes us. Well, I'm actually optimistic about it. I just want to do my part to try to steer that rigorous thinking. So there's like two questions I wanna ask. Do you have sort of a good example of rigorous thinking where it's easy to get lazy and not do the rigorous thinking? And the other question I have is like, do you have advice of how to practice rigorous thinking in all the computer science disciplines that we've mentioned? Yeah, I mean, there are times where problems that can be solved with well-known mature methods could also be solved with a deep learning approach. And there's an argument that you must use learning even for the parts we already think we know because if the human has touched it, then you've biased the system and you've suddenly put a bottleneck in there that is your own mental model. But something like inverting a matrix. You know, I think we know how to do that pretty well, even if it's a pretty big matrix. And we understand that pretty well. And you could train a deep network to do it, but you shouldn't probably. So in that sense, rigorous thinking is understanding the scope and the limitations of the methods that we have, like how to use the tools of mathematics properly. Yeah, I think, you know, taking a class on analysis is all I'm sort of arguing. Take a chance to stop and force yourself to think rigorously about even, you know, the rational numbers or something. You know, it doesn't have to be the end all problem, but that exercise of clear thinking, I think, goes a long way. And I just want to make sure we keep preaching it. We don't lose it. Yeah. But do you think when you're doing like rigorous thinking or like maybe trying to write down equations or sort of explicitly, like formally describe a system, do you think we naturally simplify things too much? Is that a danger you run into? Like in order to be able to understand something about the system mathematically, we make it too much of a toy example. But I think that's the good stuff, right? That's how you understand the fundamentals? I think so. I think maybe even that's a key to intelligence or something, but I mean, okay, what if Newton and Galileo had deep learning? And they had done a bunch of experiments and they told the world, here's your weights of your neural network. We've solved the problem. Yeah. Where would we be today? I don't think we'd be as far as we are. There's something to be said about having the simplest explanation for a phenomenon. So I don't doubt that we can train neural networks to predict even physical, F equals MA type equations. But I maybe, I want another Newton to come along because I think there's more to do in terms of coming up with the simple models for more complicated tasks. Yeah. Let's not offend AI systems from 50 years from now that are listening to this that are probably better at, might be better at coming up with F equals MA equations themselves. So like- Oh, sorry. I actually think learning is probably a route to achieving this. But the representation matters, right? And I think having a function that takes my inputs to outputs that is arbitrarily complex may not be the end goal. I think there's still, you know, the most simple or parsimonious explanation for the data. Simple doesn't mean low dimensional. That's one thing I think that we've, a lesson that we've learned. So, you know, a standard way to do model reduction or system identification and controls is to, the typical formulation is that you try to find the minimal state dimension realization of a system that hits some error bounds or something like that. And that's maybe not, I think we're learning that that was, that state dimension is not the right metric. Of complexity. Of complexity. But for me, I think a lot about contact, the mechanics of contact. A robot hand is picking up an object or something. And when I write down the equations of motion for that, they are, they look incredibly complex, not because, actually not so much because of the dynamics of the hand when it's moving, but it's just the interactions and when they turn on and off, right? So having a high dimensional, you know, but simple description of what's happening out here is fine. But if, when I actually start touching, if I write down a different dynamical system for every polygon on my robot hand and every polygon on the object, whether it's in contact or not, with all the combinatorics that explodes there, then that's too complex. So I need to somehow summarize that with a more intuitive physics way of thinking. And yeah, I'm very optimistic that machine learning will get us there. First of all, I mean, I'll probably do it in the introduction, but you're one of the great robotics people at MIT. You're a professor at MIT. You've teach a lot of amazing courses. You run a large group and you have a important history for MIT, I think, as being a part of the DARPA Robotics Challenge. Can you maybe first say what is the DARPA Robotics Challenge and then tell your story around it, your journey with it? Yeah, sure. So the DARPA Robotics Challenge, it came on the tails of the DARPA Grand Challenge and DARPA Urban Challenge, which were the challenges that brought us, put a spotlight on self-driving cars. Gil Pratt was at DARPA and pitched a new challenge that involved disaster response. It didn't explicitly require humanoids, although humanoids came into the picture. This happened shortly after the Fukushima disaster in Japan. And our challenge was motivated roughly by that because that was a case where if we had had robots that were ready to be sent in, there's a chance that we could have averted disaster. And certainly after the, in the disaster response, there were times where we would have loved to have sent robots in. So in practice, what we ended up with was a grand challenge, a DARPA Robotics Challenge, where Boston Dynamics was to make humanoid robots. People like me and the amazing team at MIT were competing first in a simulation challenge to try to be one of the ones that wins the right to work on one of the Boston Dynamics humanoids in order to compete in the final challenge, which was a physical challenge. And at that point, it was already, so it was decided that it's humanoid robots early on. There were two tracks. You could enter as a hardware team where you brought your own robot, or you could enter through the virtual robotics challenge as a software team that would try to win the right to use one of the Boston Dynamics robots. Which are called Atlas. Atlas. Humanoid robots. Yeah, it was a 400-pound Marvel, but a pretty big, scary-looking robot. Expensive, too. Expensive, yeah. At least at the time, yeah. Okay, so, I mean, how did you feel at the prospect of this kind of challenge? I mean, it seems, you know, autonomous vehicles, yeah, I guess that sounds hard, but not really from a robotics perspective. It's like, didn't they do it in the 80s? Is the kind of feeling I would have like when you first look at the problem. It's on wheels, but like humanoid robots, that sounds really hard. So what, like, what are the, psychologically speaking, what were you feeling, excited, scared? Why the heck did you get yourself involved in this kind of messy challenge? We didn't really know for sure what we were signing up for. In the sense that you could have had something that, as it was described in the call for participation, that could have put a huge emphasis on the dynamics of walking and not falling down and walking over rough terrain, or the same description, because the robot had to go into this disaster area and turn valves and pick up a drill and cut a hole through a wall. It had to do some interesting things. The challenge could have really highlighted perception and autonomous planning, or it ended up that, you know, locomoting over a complex terrain played a pretty big role in the competition. So, um. And the degree of autonomy wasn't clear. The degree of autonomy was always a central part of the discussion. So what wasn't clear was how we would be able, how far we'd be able to get with it. So the idea was always that you want semi-autonomy, that you want the robot to have enough compute that you can have a degraded network link to a human. And so the same way we had degraded networks at many natural disasters, you'd send your robot in, you'd be able to get a few bits back and forth, but you don't get to have enough, potentially, to fully operate the robot, every joint of the robot. So, and then the question was, and the gamesmanship of the organizers was to figure out what we're capable of, push us as far as we could, so that it would differentiate the teams that put more autonomy on the robot and had a few clicks and just said, go there, do this, go there, do this, versus someone who's picking every footstep or something like that. So what were some memories, painful, triumphant from the experience? Like what was that journey? Maybe if you can dig in a little deeper, maybe even on the technical side, on the team side, that whole process of, from the early idea stages to actually competing. I mean, this was a defining experience for me. It came at the right time for me in my career. I had gotten tenure before I was due a sabbatical, and most people do something relaxing and restorative for a sabbatical. So you got tenure before this? Yeah, yeah, yeah. It was a good time for me. We had a bunch of algorithms that we were very happy with. We wanted to see how far we could push them, and this was a chance to really test our mettle, to do more proper software engineering. The team, we all just worked our butts off. We were in that lab almost all the time. Okay, so I mean, there were some, of course, high highs and low lows throughout that, anytime you're not sleeping and devoting your life to a 400-pound humanoid. I remember actually one funny moment where we're all super tired, and so Atlas had to walk across cinder blocks. That was one of the obstacles. And I remember Atlas was powered down, hanging limp on its harness, and the humans were there picking up and laying the brick down so that the robot could walk over it, and I thought, what is wrong with this? We've got a robot just watching us do all the manual labor so that it can take its little stroll across the terrain. I mean, even the virtual robotics challenge was super nerve-wracking and dramatic. I remember, so we were using Gazebo as a simulator on the cloud, and there was all these interesting challenges. I think the investment that OSR FC, whatever they were called at that time, Brian Gerke's team at Open Source Robotics, they were pushing on the capabilities of Gazebo in order to scale it to the complexity of these challenges. So up to the virtual competition. So the virtual competition was, you will sign on at a certain time, and we'll have a network connection to another machine on the cloud that is running the simulator of your robot. And your controller will run on this computer, and the physics will run on the other, and you have to connect. Now, the physics, they wanted it to run at real-time rates because there was an element of human interaction, and humans, if you do want to tele-op, it works way better if it's at frame rate. Oh, cool. But it was very hard to simulate these complex scenes at real-time rate. So right up to days before the competition, the simulator wasn't quite at real-time rate. And that was great for me because my controller was solving a pretty big optimization problem, and it wasn't quite at real-time rate. So I was fine. I was keeping up with the simulator. We were both running at about 0.7. And I remember getting this email. And by the way, the perception folks on our team hated, they knew that if my controller was too slow, the robot was gonna fall down. And no matter how good their perception system was, if I can't make my controller fast. Anyways, we get this email like three days before the virtual competition. You know, it's for all the marbles. We're gonna either get a humanoid robot or we're not. And we get an email saying, good news. We made the robot, the simulator faster. It's now 1.0. And I was just like, oh man, what are we gonna do here? So that came in late at night for me. A few days ahead. A few days ahead. I went over, it happened that Frank Permenter, who's a very, very sharp, he was a student at the time working on optimization. He was still in lab. Frank, we need to make this quadratic programming solver faster. Not like a little faster. It's actually, you know. And we wrote a new solver for that QP together that night. It was terrifying. So there's a really hard optimization problem that you're constantly solving. You didn't make the optimization problem simpler. You wrote a new solver. So, I mean, your observation is almost spot on. What we did was what everybody, I mean, people know how to do this, but we had not yet done this idea of warm starting. So we are solving a big optimization problem at every time step. But if you're running fast enough, the optimization problem you're solving on the last time step is pretty similar to the optimization you're gonna solve with the next. We had course had told our commercial solver to use warm starting, but even the interface to that commercial solver was causing us these delays. So what we did was we basically wrote, we called it fast QP at the time. We wrote a very lightweight, very fast layer, which would basically check if nearby solutions to the quadratic program, which were very easily checked, could stabilize the robot. And if they couldn't, we would fall back to the solver. You couldn't really test this well, right? Or like- So we always knew that if we fell back, if we, it got to the point where if for some reason, things slowed down and we fell back to the original solver, the robot would actually literally fall down. So it was a harrowing sort of ledge we were sort of on. But I mean, actually, like the 400 pound human could come crashing to the ground if your solver's not fast enough. But we had lots of good experiences. So can I ask you a weird question I get about the idea of hard work? So actually people like students of yours that I've interacted with and just, and robotics people in general, but they have moments, at moments have worked harder than most people I know in terms of, if you look at different disciplines of how hard people work, but they're also like the happiest. Like, just like, I don't know. It's the same thing with like running, people that push themselves to like the limit, they also seem to be like the most like full of life somehow. And I get often criticized like, you're not getting enough sleep. What are you doing to your body? Blah, blah, blah, like this kind of stuff. And I usually just kind of respond like, I'm doing what I love, I'm passionate about it. I love it. I feel like it's invigorating. I actually think, I don't think the lack of sleep is what hurts you. I think what hurts you is stress and lack of doing things that you're passionate about. But in this world, yeah. I mean, can you comment about why the heck robotics people are willing to push themselves to that degree? Is there value in that? And why are they so happy? I think you got it right. I mean, I think the causality is not that we work hard. And I think other disciplines work very hard too. But I don't think it's that we work hard and therefore we are happy. I think we found something that we're truly passionate about. It makes us very happy. And then we get a little involved with it and spend a lot of time on it. What a luxury to have something that you wanna spend all your time on, right? We could talk about this for many hours, but maybe if we could pick, is there something on the technical side, on the approach that you took that's interesting that turned out to be a terrible failure or a success that you carry into your work today about all the different ideas that were involved in making, whether in the simulation or in the real world, making the semi-autonomous system work? I mean, it really did teach me something fundamental about what it's gonna take to get robustness out of a system of this complexity. I would say the DARPA challenge really was foundational in my thinking. I think the autonomous driving community thinks about this. I think lots of people thinking about safety critical systems that might have machine learning in the loop are thinking about these questions. For me, the DARPA challenge was the moment where I realized, we've spent every waking minute running this robot. And again, for the physical competition, days before the competition, we saw the robot fall down in a way it had never fallen down before. I thought, how could we have found that? We only have one robot, it's running almost all the time. We just didn't have enough hours in the day to test that robot. Something has to change, right? And I think that, I mean, I would say that the team that won from KAIST was the team that had two robots and was able to do not only incredible engineering, just absolutely top-rate engineering, but also they were able to test at a rate and discipline that we didn't keep up with. What does testing look like? What are we talking about here? Like, what's a loop of tests? Like, from start to finish, what is a loop of testing? Yeah, I mean, I think there's a whole philosophy to testing. There's the unit tests, and you can do that on a hardware, you can do that in a small piece of code. You write one function, you should write a test that checks that function's input and outputs. You should also write an integration test at the other extreme of running the whole system together, you know, where that try to turn on all of the different functions that you think are correct. It's much harder to write the specifications for a system-level test, especially if that system is as complicated as a humanoid robot, but the philosophy is sort of the same. On the real robot, it's no different, but on a real robot, it's impossible to run the same experiment twice. So if you see a failure, you hope you caught something in the logs that tell you what happened, but you'd probably never be able to run exactly that experiment again. And right now, I think our philosophy is just basically Monte Carlo estimation, is just run as many experiments as we can, maybe try to set up the environment to make the things we are worried about happen as often as possible, but really we're relying on somewhat random search in order to test. Maybe that's all we'll ever be able to, but I think, you know, because there's an argument that the things that'll get you are the things that are really nuanced in the world, and it'd be very hard to, for instance, put back in a simulation. Yeah, I guess the edge cases. What was the hardest thing? Like, so you said walking over rough terrain, like just taking footsteps. I mean, people, it's so dramatic and painful in a certain kind of way to watch these videos from the DRC of robots falling. Yeah. It's just so heartbreaking. I don't know. Maybe it's because, for me at least, we anthropomorphize the robot. Of course, it's also funny for some reason. Like humans falling is funny. It's some dark reason. I'm not sure why it is so, but it's also like tragic and painful. And so speaking of which, I mean, what made the robots fall and fail in your view? So I can tell you exactly what happened. I contributed one of those. Our team contributed one of those spectacular falls. Every one of those falls has a complicated story. I mean, at one time, the power effectively went out on the robot. Because it had been sitting at the door waiting for a green light to be able to proceed and its batteries, you know, and therefore it just fell backwards and smashed its head to the ground. And it was hilarious, but it wasn't because of bad software, right? But for ours, so the hardest part of the challenge, the hardest task in my view, was getting out of the Polaris. It was actually relatively easy to drive, the Polaris. Can you tell the story, sorry to interrupt, the story of the car? People should watch this video. I mean, the thing you've come up with is just brilliant. But anyway, sorry, what's... Yeah, we kind of joke, we call it the big robot, little car problem because somehow the race organizers decided to give us a 400 pound humanoid. And then they also provided the vehicle, which is a little Polaris. And the robot didn't really fit in the car. So you couldn't drive the car with your feet under the steering column. We actually had to straddle the main column of the... And have basically one foot in the passenger seat, one foot in the driver's seat, and then drive with our left hand. But the hard part was we had to then park the car, get out of the car. It didn't have a door, that was okay. But it's just getting up from crouched, from sitting, when you're in this very constrained environment. First of all, I remember after watching those videos, I was much more cognizant of how hard is it, it is for me to get in and out of the car, and out of the car especially. Like, it's actually a really difficult control problem. Yeah. And I'm very cognizant of it when I'm like injured, for whatever reason. No, it's really hard. Yeah. So how did you approach this problem? So we had a, you know, you think of NASA's operations and they have these checklists, you know, pre-launch checklists and they're like, we weren't far off from that. We had this big checklist. And on the first day of the competition, we were running down our checklist. And one of the things we had to do, we had to turn off the controller, the piece of software that was running, that would drive the left foot of the robot in order to accelerate on the gas. And then we turned on our balancing controller. And the nerves, jitters of the first day of the competition, someone forgot to check that box and turn that controller off. So we used a lot of motion planning to figure out a sort of configuration of the robot that we could get up and over. We relied heavily on our balancing controller. And basically there were, when the robot was in one of its most precarious, you know, sort of configurations, trying to sneak its big leg out of the side, the other controller that thought it was still driving told its left foot to go like this. And that wasn't good, but it turned disastrous for us because what happened was a little bit of push here. Actually, we have videos of us, you know, running into the robot with a 10 foot pole and it kind of will recover. But this is a case where there's no space to recover. So a lot of our secondary balancing mechanisms about like take a step to recover, they were all disabled because we were in the car and there's no place to step. So we were relying on our just lowest level reflexes. And even then, I think just hitting the foot on the seat, on the floor, we probably could have recovered from it. But the thing that was bad that happened is when we did that and we jostled a little bit, the tailbone of our robot was only a little off the seat, it hit the seat. And the other foot came off the ground just a little bit. And nothing in our plans had ever told us what to do if your butt's on the seat and your feet are in the air. And then the thing is, once you get off the script, things can go very wrong because even our state estimation, our system that was trying to collect all the data from the sensors and understand what's happening with the robot, it didn't know about this situation. So it was predicting things that were just wrong. And then we did a violent shake and fell off in our face first on out of the robot. But like into the destination. That's true, we fell in and we got our point for egress. We got the point. But so is there any hope for, that's interesting, is there any hope for Atlas to be able to do something when it's just on its butt and feet in the air? Absolutely. So you can, what do you? No, so that is one of the big challenges. And I think it's still true. Boston Dynamics and Andy Mow and there's this incredible work on legged robots happening around the world. Most of them still are very good at the case where you're making contact with the world at your feet and they have typically point feet relatively, their balls on their feet, for instance. If those robots get in a situation where the elbow hits the wall or something like this, that's a pretty different situation. Now they have layers of mechanisms that will make, I think the more mature solutions have ways in which the controller won't do stupid things. But a human, for instance, is able to leverage incidental contact in order to accomplish a goal. In fact, I might, if you push me, I might actually put my hand out and make a new brand new contact. The feet of the robot are doing this on quadrupeds, but we mostly in robotics are afraid of contact on the rest of our body, which is crazy. There's this whole field of motion planning, collision-free motion planning. And we write very complex algorithms so that the robot can dance around and make sure it doesn't touch the world. So people are just afraid of contact because contact is seen as a difficult. It's still a difficult control problem and sensing problem. Now you're a serious person. I'm a little bit of an idiot and I'm going to ask you some dumb questions. So I do martial arts. So like jiu-jitsu, I wrestled my whole life. So let me ask the question, whenever people learn that I do any kind of AI or like I mentioned robots and things like that, they say, when are we going to have robots that can win in a wrestling match or in a fight against a human? So we just mentioned sitting on your butt. Feet in the air, that's a common position in jiu-jitsu when you're on the ground, you're a down opponent. Like how difficult do you think is the problem? And when will we have a robot that can defeat a human in a wrestling match? And we're talking about a lot. Like, I don't know if you're familiar with wrestling, but essentially- Not very. It's basically the art of contact. It's like, it's because you're picking contact points and then using like leverage, like to off balance, to trick people. It's like you make them feel like you're doing one thing and then they change their balance and then you switch what you're doing and then results in a throw or whatever. So like, it's basically the art of multiple contacts. So- Awesome, it's a nice description of it. So there's also an opponent in there, right? So if- Very dynamic. Right, if you are wrestling a human and are in a game theoretic situation with a human, that's still hard. But just to speak to the quickly reasoning about contact part of it, for instance. Yeah, maybe even throwing the game theory out of it, almost like a, yeah, almost like a non-dynamic opponent. Right, there's reasons to be optimistic, but I think our best understanding of those problems are still pretty hard. I have been increasingly focused on manipulation, partly where that's a case where the contact has to be much more rich. And there are some really impressive examples of deep learning policies, controllers, that can appear to do good things through contact. We've even got new examples of deep learning models of predicting what's gonna happen to objects as they go through contact. But I think the challenge you just offered there still eludes us, right? The ability to make a decision based on those models quickly. You know, I have to think though, it's hard for humans too, when you get that complicated. I think probably you had maybe a slow motion version of where you learn the basic skills, and you've probably gotten better at it, and there's much more subtlety. But it might still be hard to actually, you know, really on the fly, take a model of your humanoid and figure out how to plan the optimal sequence. That might be a problem we never solve. Well, the, I mean, one of the most amazing things to me about the, we can talk about martial arts, we could also talk about dancing, doesn't really matter, too human. I think it's the most interesting study of contact. It's not even the dynamic element of it. It's the, like when you get good at it, it's so effortless. Like I can just, I'm very cognizant of the entirety of the learning process being essentially like learning how to move my body in a way that I could throw very large weights around effortlessly. Like, and I can feel the learning. Like I'm a huge believer in drilling of techniques, and you can just like feel your, I don't know, you're not feeling, you're feeling, sorry, you're learning it intellectually a little bit, but a lot of it is the body learning it somehow, like instinctually. And whatever that learning is, that's really, I'm not even sure if that's equivalent to like a deep learning, learning a controller. I think it's something more, it feels like there's a lot of distributed learning going on. Yeah, I think there's hierarchy and composition probably in the systems that we don't capture very well yet. You have layers of control systems, you have reflexes at the bottom layer, and you have a system that's capable of planning a vacation to some distant country, which is probably, you probably don't have a controller, a policy for every possible destination you'll ever pick, right? But there's something magical in the in-between, and how do you go from these low-level feedback loops to something that feels like a pretty complex set of outcomes. And my guess is, I think there's evidence that you can plan at some of these levels, right? So Josh Tenenbaum just showed it in his talk the other day. He's got a game he likes to talk about, I think he calls it the Pick Three game or something, where he puts a bunch of clutter down in front of a person, and he says, okay, pick three objects, and it might be a telephone, or a shoe, or a Kleenex box, or whatever. And apparently you pick three items, and then he says, okay, pick the first one up with your right hand, the second one up with your left hand. Now using those objects, now as tools, pick up the third object. Right, so that's down at the level of physics, and mechanics, and contact mechanics that I think we do have policies for, we do control for, almost feedback. But somehow we're able to still, I mean, I've never picked up a telephone with a shoe and a water bottle before, and somehow, and it takes me a little longer to do that the first time, but most of the time we can sort of figure that out. So, yeah, I think the amazing thing is this ability to be flexible with our models, plan when we need to, use our well-oiled controllers when we don't, when we're in familiar territory. Having models, I think the other thing you just said was something about, I think your awareness of what's happening is even changing as you improve your expertise, right? So maybe you have a very approximate model of the mechanics to begin with, and as you gain expertise, you get a more refined version of that model. You're aware of muscles or balance components that you just weren't even aware of before. So how do you scaffold that? Yeah, plus the fear of injury, the ambition of goals, of excelling, and fear of mortality. Let's see what else is in there as motivations. Overinflated ego in the beginning, and then a crash of confidence in the middle. All of those seem to be essential for the learning process. And if all that's good, then you're probably optimizing energy efficiency. Yeah, right, so we have to get that right. So there was this idea that you would have robots play soccer better than human players by 2050. That was the goal. A world, basically, was the goal to beat world champion team? To become a World Cup, beat like a World Cup level team. So are we gonna see that first, or a robot, if you're familiar, there's an organization called UFC for mixed martial arts. Are we gonna see a World Cup championship soccer team that have robots, or a UFC champion mixed martial artist that's a robot? I mean, it's very hard to say one thing is harder, some problem's harder than the other. What probably matters is who started the organization that, I mean, I think RoboCup has a pretty serious following, there is a history now of people playing that game, learning about that game, building robots to play that game, building increasingly more human robots. It's got momentum. And so if you want to have mixed martial arts compete, you better start your organization now, right? I think almost independent of which problem is technically harder, because they're both hard and they're both different. That's a good point. I mean, those videos are just hilarious, like especially the humanoid robots trying to play soccer. I mean, they're kind of terrible right now. I mean, I guess there is RoboSumo wrestling. There's like the RoboOne competitions where they do have these robots that go on a table and basically fight. So maybe I'm wrong. Maybe... First of all, do you have a year in mind for RoboCup, just from a robotics perspective? Seems like a super exciting possibility that, like in the physical space, this is what's interesting. I think the world is captivated. I think it's really exciting. It inspires just a huge number of people when a machine beats a human at a game that humans are really damn good at. So you're talking about chess and go, but that's in the world of digital. I don't think machines have beat humans at a game in the physical space yet, but that would be just... You have to make the rules very carefully, right? I mean, if Atlas kicked me in the shins, I'm down and game over. So it's very subtle on what's fair. I think the fighting one is a weird one, yeah, because you're talking about a machine that's much stronger than you. But yeah, in terms of soccer, basketball, all those kinds of- Even soccer, right? I mean, as soon as there's contact or whatever, and there are some things that the robot will do better. I think if you really set yourself up to try to see, could robots win the game of soccer as the rules were written? The right thing for the robot to do is to play very differently than a human would play. You're not gonna get the perfect soccer player robot. You're gonna get something that exploits the rules, exploits its super actuators, its super low bandwidth feedback loops or whatever, and it's gonna play the game differently than you want it to play. And I bet there's loopholes, right? We saw that in the DARPA challenge, that it's very hard to write a set of rules that someone can't find a way to exploit. Let me ask another ridiculous question. I think this might be the last ridiculous question, but- I doubt it. I aspire to ask as many ridiculous questions of a brilliant MIT professor. Okay, I don't know if you've seen The Black Mirror. It's funny, I never watched the episode. I know when it happened, though, because I gave a talk to some MIT faculty one day, on an unassuming Monday or whatever, I was telling them about the state of robotics. And I showed some video from Boston Dynamics of the quadruped spot at the time. It was the early version of spot. And there was a look of horror that went across the room. And I said, I've shown videos like this a lot of times. What happened? And it turns out that this video had, this Black Mirror episode had changed the way people watched the videos I was putting out. The way they see these kinds of robots. So I talked to so many people who are just terrified because of that episode, probably, of these kinds of robots. I almost want to say that they almost kind of like enjoy being terrified. I don't even know what it is about human psychology that kind of imagine doomsday, the destruction of the universe or our society, and kind of like enjoy being afraid. I don't want to simplify it, but it feels like they talk about it so often, it almost, there does seem to be an addictive quality to it. I talked to a guy, a guy named Joe Rogan, who's kind of the flag bearer for being terrified of these robots. Do you have a, two questions. One, do you have an understanding of why people are afraid of robots? And the second question is, in Black Mirror, just to tell you the episode, I don't even remember it that much anymore, but these robots, I think they can shoot a pellet or something, they basically have, it's basically a spot with a gun. And how far are we away from having robots that go rogue like that, basically spot that goes rogue for some reason, and somehow finds a gun? Right, so, I mean, I'm not a psychologist. I think, I don't know exactly why people react the way they do. I think we have to be careful about the way robots influence our society and the like. I think that's something, that's a responsibility that roboticists need to embrace. I don't think robots are gonna come after me with a kitchen knife or a pellet gun right away. And I mean, if they were programmed in such a way, but I used to joke with Atlas that all I had to do was run for five minutes and its battery would run out. But actually they've got a very big battery in there by the end. So it was over an hour. I think the fear is a bit cultural though. Because I mean, you notice that, like I think in my age in the US, we grew up watching Terminator. Right, if I had grown up at the same time in Japan, I probably would have been watching Astro Boy. And there's a very different reaction to robots in different countries, right? So I don't know if it's a human innate fear of metal marvels, or if it's something that we've done to ourselves with our sci-fi. Yeah, the stories we tell ourselves through movies, through just, through popular media. But if I were to tell, if you were my therapist and I said, I'm really terrified that we're going to have these robots very soon that will hurt us, like how do you approach making me feel better? Like, why shouldn't people be afraid? There's a, I think there's a video that went viral recently. Everything was spot in Boston, and it goes viral in general. But usually it's like really cool stuff. Like they're doing flips and stuff, or like sad stuff. Atlas being hit with a broomstick or something like that. But there's a video where I think one of the new productions bought robots, which are awesome. It was like patrolling somewhere in some country. And people immediately were saying, this is the dystopian future, the surveillance state. For some reason, you can just have a camera. Something about spot, being able to walk on four feet with like really terrified people. So what do you say to those people? I think there is a legitimate fear there because so much of our future is uncertain. But at the same time, technically speaking, it seems like we're not there yet. So what do you say? I mean, I think technology is complicated. It can be used in many ways. I think there are purely software attacks that somebody could use to do great damage. Maybe they have already. I think wheeled robots could be used in bad ways too. Drones. Drones, right. I don't think that, let's see. I don't want to be building technology just because I'm compelled to build technology and I don't think about it. But I would consider myself a technological optimist, I guess, in the sense that I think we should continue to create and evolve and our world will change. And if we will introduce new challenges, we'll screw something up maybe. But I think also we'll invent ourselves out of those challenges and life will go on. So it's interesting because you didn't mention this is technically too hard. I don't think robots are, I think people attribute a robot that looks like an animal as maybe having a level of self-awareness or consciousness or something that they don't have yet. I think our ability to anthropomorphize those robots is probably, we're assuming that they have a level of intelligence that they don't yet have. And that might be part of the fear. So in that sense, it's too hard. But there are many scary things in the world, right? So I think we're right to ask those questions, we're right to think about the implications of our work. Right, in the short term as we're working on it, for sure. Is there something long-term that scares you about our future with AI and robots? A lot of folks from Elon Musk to Sam Harris to a lot of folks talk about the existential threats about artificial intelligence. Oftentimes robots kind of inspire that the most because of the anthropomorphism. Do you have any fears? It's an important question. I actually, I think I like Rod Brooks answer maybe the best on this. I think, and it's not the only answer he's given over the years, but maybe one of my favorites is, he says, it's not gonna be, he's got a book, Flesh and Machines, I believe. It's not gonna be the robots versus the people. We're all gonna be robot people. Because we already have smartphones. Some of us have serious technology implanted in our bodies already, whether we have a hearing aid or a pacemaker or anything like this. People with amputations might have prosthetics. That's a trend I think that is likely to continue. I mean, this is now wild speculation, but when do we get to cognitive implants and the like? Yeah, with neural link, brain computer interfaces. That's interesting. So there's a dance between humans and robots. It's going to be impossible to be scared of the other out there, the robot, because the robot will be part of us, essentially. It'd be so intricately sort of part of our society. Yeah, and it might not even be implanted part of us, but just it's so much a part of our society. So in that sense, the smartphone is already the robot we should be afraid of, yeah. I mean, yeah, and all the usual fears arise of the misinformation, the manipulation, all those kinds of things. The problems are all the same. They're human problems, essentially, it feels like. Yeah, I mean, I think the way we interact with each other online is changing the value we put on personal interaction, and that's a crazy big change that's gonna happen and has already been ripping through our society, right? And that has implications that are massive. I don't know if they should be scared of it or go with the flow, but I don't see some battle lines between humans and robots being the first thing to worry about. I mean, I do wanna just, as a kind of comment, maybe you can comment about your just feelings about Boston Dynamics in general, but I love science, I love engineering, I think there's so many beautiful ideas in it. And when I look at Boston Dynamics or legged robots in general, I think they inspire people curiosity and feelings in general, excitement about engineering more than almost anything else in popular culture. And I think that's such an exciting responsibility and possibility for robotics. And Boston Dynamics is riding that wave pretty damn well. They found it, they've discovered that hunger and curiosity in the people, and they're doing magic with it. I don't care if they, I mean, I guess it's their company, they have to make money, right? But they're already doing incredible work in inspiring the world about technology. I mean, do you have thoughts about Boston Dynamics and maybe others, your own work in robotics and inspiring the world in that way? I completely agree. I think Boston Dynamics is absolutely awesome. I think I show my kids those videos, and the best thing that happens is sometimes they've already seen them. Right, I think, I just think it's a pinnacle of success in robotics that is just one of the best things that's happened. I absolutely, completely agree. One of the heartbreaking things to me is how many robotics companies fail, how hard it is to make money with the robotics company. Like iRobot went through hell just to arrive at Arumba to figure out one product. And then there's so many home robotics companies like Jibo and Anki, the cutest toy, that's a great robot, I thought, went down. I'm forgetting a bunch of them, but a bunch of robotics companies fail. Rod's company, Rethink Robotics, do you have anything hopeful to say about the possibility of making money with robots? Oh, I think you can't just look at the failures. You can, I mean, Boston Dynamics is a success. There's lots of companies that are still doing amazingly good work in robotics. I mean, this is the capitalist ecology or something, right? I think you have many companies, you have many startups, and they push each other forward, and many of them fail, and some of them get through, and that's sort of the natural- Way of things. Way of those things. I don't know that, is robotics really that much worse? I feel the pain that you feel too. Every time I read one of these, sometimes it's friends, and I definitely wish it went better, went differently. But I think it's healthy and good to have bursts of ideas, bursts of activities. Ideas, if they are really aggressive, they should fail sometimes. Certainly, that's the research mantra, right? If you're succeeding at every problem you attempt, then you're not choosing aggressively enough. Is it exciting to you, the new Spot? Oh, it's so good. When are you getting him as a pet, or it? Yeah, I mean, I have to dig up 75K right now. I mean, it's so cool that there's a price tag, you can go and actually buy it. I have a Skydio R1, love it. So, no, I would absolutely be a customer. I wonder what your kids would think about it. I actually, Zach from Boston Dynamics would let my kid drive in one of their demos one time, and that was just so good, so good. So, I'll forever be grateful for that. And there's something magical about the anthropomorphization of that arm. It adds another level of human connection. I'm not sure we understand from a control aspect the value of anthropomorphization. I think that's an understudied and under-understood engineering problem. There's been a psychologist who's been studying it. I think it's part, like, manipulating our mind to believe things is a valuable engineering. Like, this is another degree of freedom that can be controlled. I like this, yeah, I think that's right. I think, you know, there's something that humans seem to do, or maybe my dangerous introspection is, I think we are able to make very simple models that assume a lot about the world very quickly, and then it takes us a lot more time, like you're wrestling. You know, you probably thought you knew what you were doing with wrestling, and you were fairly functional as a complete wrestler, and then you slowly got more expertise. So maybe it's natural that our first level of defense against seeing a new robot is to think of it in our existing models of how humans and animals behave. And it's just, as you spend more time with it, then you'll develop more sophisticated models that will appreciate the differences. Exactly. Can you say what does it take to control a robot? Like, what is the control problem of a robot? And in general, what is a robot in your view? Like, how do you think of this system? What is a robot? What is a robot? I think robotics- I told you ridiculous questions. No, no, it's good. I mean, there's standard definitions of combining computation with some ability to do mechanical work. I think that gets us pretty close. But I think robotics has this problem that once things really work, we don't call them robots anymore. Like, my dishwasher at home is pretty sophisticated, beautiful mechanisms. There's actually a pretty good computer, probably a couple of chips in there doing amazing things. We don't think of that as a robot anymore, which isn't fair, because then, roughly it means that robotics always has to solve the next problem and doesn't get to celebrate its past successes. I mean, even factory room floor robots are super successful. They're amazing. But that's not the ones, I mean, people think of them as robots, but they don't, if you ask what are the successes of robotics, somehow it doesn't come to your mind immediately. So the definition of robot is a system of some level of automation that fails frequently. Something like, it's the computation plus mechanical work and an unsolved problem. Unsolved problem, yeah. So from a perspective of control and mechanics, dynamics, what is a robot? So there are many different types of robots. The control that you need for a Jibo robot, some robot that's sitting on your countertop and interacting with you, but not touching you, for instance, is very different than what you need for an autonomous car or an autonomous drone. It's very different than what you need for a robot that's gonna walk or pick things up with its hands, right? My passion has always been for the places where you're interacting more, you're doing more dynamic interactions with the world. So walking, now manipulation. And the control problems there are beautiful. I think contact is one thing that differentiates them from many of the control problems we've solved classically. Right, like modern control grew up stabilizing fighter jets that were passively unstable. And there's like amazing success stories from control all over the place. Power grid, I mean, there's all kinds of, it's everywhere that we don't even realize, just like AI is now. Do you mention contact, like what's contact? So an airplane is an extremely complex system or a spacecraft landing or whatever. But at least it has the luxury of things change relatively continuously. That's an oversimplification. But if I make a small change in the command I send to my actuator, then the path that the robot will take tends to change only by a small amount. And there's a feedback mechanism here. That's what we're talking about. And there's a feedback mechanism. And thinking about this as locally, like a linear system, for instance, I can use more linear algebra tools to study systems like that, generalizations of linear algebra to these smooth systems. What is contact? The robot has something very discontinuous that happens when it makes or breaks, when it starts touching the world. And even the way it touches or the order of contacts can change the outcome in potentially unpredictable ways. Not unpredictable, but complex ways. I do think there's a little bit of a, a lot of people will say that contact is hard in robotics, even to simulate. And I think there's a little bit of a, there's truth to that, but maybe a misunderstanding around that. So what is limiting is that when we think about our robots and we write our simulators, we often make an assumption that objects are rigid. And when it comes down, you know, that their mass moves all, you know, stays in a constant position relative to each other itself. And that leads to some paradoxes when you go to try to talk about rigid body mechanics and contact. And so for instance, if I have a three-legged stool with just a, imagine it comes to a point at the legs. So it's only touching the world at a point. If I draw my physics, my high school physics diagram of this system, then there's a couple of things that I'm given by elementary physics. I know if the system, if the table is at rest, if it's not moving, it's zero velocities. That means that the normal force, all the forces are in balance. So the force of gravity is being countered by the forces that the ground is pushing on my table legs. I also know since it's not rotating, that the moments have to balance. And since it can, it's a three-dimensional table, it could fall in any direction. It actually tells me uniquely what those three normal forces have to be. If I have four legs on my table, four-legged table, and they were perfectly machined to be exactly the right same height, and they're set down and the table's not moving, then the basic conservation laws don't tell me, there are many solutions for the forces that the ground could be putting on my legs that would still result in the table not moving. Now, the reason, that seems fine. I could just pick one. But it gets funny now, because if you think about friction, what we think about with friction is, our standard model says the amount of force that the table will push back, if I were to now try to push my table sideways, I guess I have a table here, is proportional to the normal force. So if I'm barely touching and I push, I'll slide, but if I'm pushing more and I push, I will slide less. It's called Coulomb friction, is our standard model. Now, if you don't know what the normal force is on the four legs, and you push the table, then you don't know what the friction forces are gonna be. And so you can't actually tell, the laws just aren't explicit yet about which way the table's gonna go. It could veer off to the left, it could veer off to the right, it could go straight. So the rigid body assumption of contact leaves us with some paradoxes, which are annoying for writing simulators and for writing controllers. We still do that sometimes, because soft contact is potentially harder numerically or whatever, and the best simulators do both or do some combination of the two. But anyways, because of these kind of paradoxes, there's all kinds of paradoxes in contact, mostly due to these rigid body assumptions. It becomes very hard to write the same kind of control laws that we've been able to be successful with for fighter jets. We haven't been as successful writing those controllers for manipulation. And so you don't know what's going to happen at the point of contact, at the moment of contact. There are situations absolutely where our laws don't tell us. So the standard approach, that's okay. I mean, instead of having a differential equation, you end up with a differential inclusion, it's called. It's a set-valued equation. It says that I'm in this configuration, I have these forces applied on me, and there's a set of things that could happen, right? And you can- And those aren't continuous, I mean, what, so when you say non-smooth, they're not only not smooth, but this is discontinuous? The non-smooth comes in when I make or break a new contact first, or when I transition from stick to slip. So you typically have static friction, and then you'll start sliding, and that'll be a discontinuous change in velocity, for instance, especially if you come to rest or- That's so fascinating. Okay, so what do you do? Sorry, I interrupted you. What's the hope under so much uncertainty about what's going to happen? What are you supposed to do? I mean, control has an answer for this. Robust control is one approach, but roughly, you can write controllers which try to still perform the right task despite all the things that could possibly happen. The world might want the table to go this way and this way, but if I write a controller that pushes a little bit more and pushes a little bit, I can certainly make the table go in the direction I want. It just puts a little bit more of a burden on the control system, right? And those discontinuities do change the control system because the way we write it down right now, every different control configuration, including sticking or sliding or parts of my body that are in contact or not, looks like a different system. And I think of them, I reason about them separately or differently, and the combinatorics of that blow up, right? So I just don't have enough time to compute all the possible contact configurations of my humanoid. Interestingly, I mean, I'm a humanoid. I have lots of degrees of freedom, lots of joints. I've only been around for a handful of years. It's getting up there, but I haven't had time in my life to visit all of the states in my system, certainly all the contact configurations. So if step one is to consider every possible contact configuration that I'll ever be in, that's probably not a problem I need to solve, right? Just as a small attention, what's a contact configuration? Just so we can enumerate, what are we talking about? How many are there? The simplest example maybe would be, imagine a robot with a flat foot. And we think about the phases of gait where the heel strikes and then the front toe strikes, and then you can heel up, toe off. Those are each different contact configurations. I only had two different contacts, but I ended up with four different contact configurations. Now, of course, my robot might actually have bumps on it or other things, so it could be much more subtle than that. But it's just even with one sort of box interacting with the ground already in the plane has that many, right? And if I was just even a 3D foot, then it probably my left toe might touch just before my right toe and things get subtle. Now, if I'm a dexterous hand and I go to talk about just grabbing a water bottle, if I have to enumerate every possible order that my hand came into contact with the bottle, then I'm dead in the water. Any approach that we were able to get away with that in walking because we mostly touched the ground more than a small number of points, for instance, and we haven't been able to get dexterous hands that way. So you've mentioned that people think that contact is really hard and that that's the reason that robotic manipulation problem is really hard. Is there any flaws in that thinking? So I think simulating contact is one aspect. People often say that one of the reasons that we have a limit in robotics is because we do not simulate contact accurately in our simulators. And I think that is, the extent to which that's true is partly because our simulators, we haven't got mature enough simulators. There are some things that are still hard, difficult. That needs to change. But we actually, we know what the governing equations are. They have some foibles, like this indeterminacy, but we should be able to simulate them accurately. We have incredible open source community in robotics, but it actually just takes a professional engineering team a lot of work to write a very good simulator like that. My word is, I believe you've written, Drake. There's a team of people. I certainly spent a lot of hours on it myself. Well, what is Drake? What does it take to create a simulation environment for the kind of difficult control problems we're talking about? Right, so Drake is the simulator that I've been working on. There are other good simulators out there. I don't like to think of Drake as just a simulator, because we write our controllers in Drake, we write our perception systems a little bit in Drake, but we write all of our low-level control and even planning and optimization. So it has optimization capabilities. Absolutely, yeah. I mean, Drake is three things, roughly. It's an optimization library, which is, sits on, it provides a layer of abstraction in C++ and Python for commercial solvers. You can write linear programs, quadratic programs, semi-definite programs, sums of squares programs, the ones we've used, mixed integer programs, and it will do the work to curate those and send them to whatever the right solver is, for instance, and it provides a level of abstraction. The second thing is a system modeling language, a bit like LabVIEW or Simulink, where you can make block diagrams out of complex systems. Or it's like ROS in that sense, where you might have lots of ROS nodes that are each doing some part of your system, but to contrast it with ROS, we try to write, if you write a Drake system, then you have to, it asks you to describe a little bit more about the system. If you have any state, for instance, in the system, any variables that are gonna persist, you have to declare them. Parameters can be declared and the like. But the advantage of doing that is that you can, if you like, run things all on one process, but you can also do control design against it. You can do, I mean, simple things like rewinding and playing back your simulations, for instance. You know, these things, you get some rewards for spending a little bit more upfront cost in describing each system. And I was inspired to do that because I think the complexity of Atlas, for instance, it's just so great. And I think, although, I mean, ROS has been incredible, absolute huge fan of what it's done for the robotics community. But the ability to rapidly put different pieces together and have a functioning thing is very good. But I do think that it's hard to think clearly about a bag of disparate parts, Mr. Potato Head kind of software stack. And if you can, you know, ask a little bit more out of each of those parts, then you can understand the way they work better. You can try to verify them and the like. Or you can do learning against them. And then one of those systems, the last thing, I said the first two things that Drake is, but the last thing is that there is a set of multi-body equations, rigid body equations, that is trying to provide a system that simulates physics. And that, we also have renderers and other things, but I think the physics component of Drake is special in the sense that we have done excessive amount of engineering to make sure that we've written the equations correctly. Every possible tumbling satellite or spinning top or anything that we could possibly write as a test is tested. We are making some, you know, I think fundamental improvements on the way you simulate contact. Just what does it take to simulate contact? I mean, it just seems, I mean, there's something just beautiful the way you were explaining contact and you were tapping your fingers on the table while you're doing it. Just- Easily, right? Easily, just not even, it was helping you think, I guess. You have this awesome demo of loading or unloading a dishwasher. Just picking up a plate, grasping it like for the first time. That just seems like so difficult. What, how do you simulate any of that? So it was really interesting that what happened was that we started getting more professional about our software development during the DARPA Robotics Challenge. I learned the value of software engineering and how to bridle complexity. I guess that's what I want to somehow fight against and bring some of the clear thinking of controls into these complex systems we're building for robots. Shortly after the DARPA Robotics Challenge, Toyota opened a research institute, TRI, Toyota Research Institute. They put one of their, there's three locations. One of them is just down the street from MIT. And I helped ramp that up right out as a part of my, the end of my sabbatical, I guess. So TRI is, has given me, the TRI Robotics effort has made this investment in simulation in Drake. And Michael Sherman leads a team there of just absolutely top-notch dynamics experts that are trying to write those simulators that can pick up the dishes. And there's also a team working on manipulation there that is taking problems like loading the dishwasher. And we're using that to study these really hard corner cases kind of problems in manipulation. So for me, this, you know, simulating the dishes, we could actually write a controller. If we just cared about picking up dishes in the sink once, we could write a controller without any simulation whatsoever. And we could call it done. But we wanna understand like, what is the path you take to actually get to a robot that could perform that for any dish in anybody's kitchen with enough confidence that it could be a commercial product, right? And it has deep learning perception in the loop. It has complex dynamics in the loop. It has controller, it has a planner. And how do you take all of that complexity and put it through this engineering discipline and verification and validation process to actually get enough confidence to deploy? I mean, the DARPA challenge made me realize that that's not something you throw over the fence and hope that somebody will harden it for you. That there are really fundamental challenges in closing that last gap. They're doing the validation and the testing. I think it might even change the way we have to think about the way we write systems. What happens if you have the robot running lots of tests and it screws up, it breaks a dish, right? How do you capture that? I said, you can't run the same simulation or the same experiment twice on a real robot. Do we have to be able to bring that one-off failure back into simulation in order to change our controllers, study it, make sure it won't happen again? Do we, is it enough to just try to add that to our distribution and understand that on average we're gonna cover that situation again? There's like really subtle questions at the corner cases that I think we don't yet have satisfying answers for. How do you find the corner cases? That's one kind of, is there, do you think that's possible to create a systematized way of discovering corner cases efficiently? Yes. In whatever the problem is? Yes, I mean, I think we have to get better at that. I mean, control theory has for decades talked about active experiment design. What's that? So people call it curiosity these days. It's roughly this idea of trying to, exploration or exploitation, but in the active experiment design is even, is more specific. You could try to understand the uncertainty in your system, design the experiment that will provide the maximum information to reduce that uncertainty. If there's a parameter you wanna learn about, what is the optimal trajectory I could execute to learn about that parameter, for instance? Scaling that up to something that has a deep network in the loop and a planning in the loop is tough. We've done some work on, with Matt O'Kelly and Amansina, we've worked on some falsification algorithms that are trying to do rare event simulation that try to just hammer on your simulator. And if your simulator is good enough, you can spend a lot of time, you can write good algorithms that try to spend most of their time in the corner cases. So you basically imagine you're building an autonomous car and you wanna put it in, I don't know, downtown New Delhi all the time, right? In accelerated testing. If you can write sampling strategies, which figure out where your controller's performing badly in simulation and start generating lots of examples around that. It's just the space of possible places where that can be, where things can go wrong is very big. So it's hard to write those algorithms. Yeah, rare event simulation is just like a really compelling notion. If it's possible. We joked and we call it the black swan generator. It's a black swan. Because you don't just want the rare events, you want the ones that are highly impactful. I mean, that's the most, those are the most sort of profound questions we ask of our world. What's the worst that can happen? But what we're really asking isn't some kind of computer science worst case analysis. We're asking like, what are the millions of ways this can go wrong? And that's like our curiosity. We humans, I think are pretty bad at, we just like run into it. And I think there's a distributed sense because there's now like 7.5 billion of us. And so there's a lot of them, and then a lot of them write blog posts about the stupid thing they've done. So we learn in a distributed way. There's some- I think that's gonna be important for robots too. I mean, that's another massive theme at Toyota Research for robotics is this fleet learning concept. Is the idea that I as a human, I don't have enough time to visit all of my states. It's very hard for one robot to experience all the things. But that's not actually the problem we have to solve. We're gonna have fleets of robots that can have very similar appendages. And at some point, maybe collectively, they have enough data that their computational processes should be set up differently than ours, right? It's that this vision of just, I mean, all these dishwasher unloading robots. I mean, that robot dropping a plate and a human looking at the robot probably pissed off. Yeah. But that's a special moment to record. I think one thing in terms of fleet learning, and I've seen that because I've talked to a lot of folks just like Tesla users or Tesla drivers. They're another company that's using this kind of fleet learning idea. One hopeful thing I have about humans is they really enjoy when a system improves, learns. So they enjoy fleet learning. And the reason it's hopeful for me is they're willing to put up with something that's kind of dumb right now. And they're like, if it's improving, they almost enjoy being part of the teaching. It almost like if you have kids, like you're teaching them something. I think that's a beautiful thing because that gives me hope that we can put dumb robots out there. I mean, the problem on the Tesla side with cars, cars can kill you. That makes the problem so much harder. Dishwasher unloading is a little safe. That's why home robotics is really exciting. And just to clarify, I mean, for people who might not know, I mean, TRI, Toyota Research Institute. So they're pretty well known for like autonomous vehicle research, but they're also interested in home robotics. Yeah, there's a big group working on, multiple groups working on home robotics. It's a major part of the portfolio. There's also a couple other projects and advanced materials discovery, using AI and machine learning to discover new materials for car batteries and the like, for instance. And that's been actually an incredibly successful team. There's new projects starting up too. Do you see a future of where like robots are in our home and like robots that have like actuators that look like arms in our home, or like, you know, more like humanoid type robots? Or is this, are we gonna do the same thing that you just mentioned that, you know, the dishwasher's no longer a robot. We're going to just not even see them as robots. But I mean, what's your vision of the home of the future? 10, 20 years from now, 50 years if you get crazy. Yeah, I think we already have Roombas cruising around. We have, you know, Alexas or Google Homes on there, our kitchen counter. It's only a matter of time till they spring arms and start doing something useful like that. So I do think it's coming. I think lots of people have lots of motivations for doing it. It's been super interesting actually learning about Toyota's vision for it, which is about helping people age in place. Because I think that's not necessarily the first entry, the most lucrative entry point, but it's the problem maybe that we really need to solve no matter what. And so I think there's a real opportunity. It's a delicate problem. How do you work with people, help people, keep them active, engaged, you know, but improve the quality of life and help them age in place, for instance. It's interesting because older folks are also, I mean, there's a contrast there because they're not always the folks who are the most comfortable with technology, for example. So there's a division that's interesting there that you can do so much good with a robot for older folks, but there's a gap to fill of understanding. I mean, it's actually kind of beautiful. Robot is learning about the human and the human is kind of learning about this new robot thing. And it's also with, at least with, like when I talked to my parents about robots, there's a little bit of a blank slate there too. Like you can, I mean, they don't know anything about robotics. So it's completely like wide open. They don't have, they haven't, my parents haven't seen Black Mirror. So like they, it's a blank slate. Here's a cool thing, like what can it do for me? Yeah, so it's an exciting space. I think it's a really important space. I do feel like, you know, a few years ago, drones were successful enough in academia. They kind of broke out and started in industry and autonomous cars have been happening. It does feel like manipulation in logistics, of course, first, but in the home shortly after, seems like one of the next big things that's gonna really pop. So I don't think we talked about it, but what's soft robotics? So we talked about like rigid bodies. Like if we can just linger on this whole touch thing. Yeah, so what's soft robotics? So I told you that I really dislike the fact that robots are afraid of touching the world all over their body. So there's a couple of reasons for that. If you look carefully at all the places that robots actually do touch the world, they're almost always soft. They have some sort of pad on their fingers or a rubber sole on their foot. But if you look up and down the arm, we're just pure aluminum or something. So that makes it hard actually. In fact, hitting the table with your rigid arm or nearly rigid arm has some of the problems that we talked about in terms of simulation. I think it fundamentally changes the mechanics of contact when you're soft, right? You turn point contacts into patch contacts, which can have torsional friction. You can have distributed load. If I wanna pick up an egg, right? If I pick it up with two points, then in order to put enough force to sustain the weight of the egg, I might have to put a lot of force to break the egg. If I envelop it with contact all around, then I can distribute my force across the shell of the egg and have a better chance of not breaking it. So soft robotics is for me a lot about changing the mechanics of contact. Does it make the problem a lot harder? Um, uh, quite the opposite. It changes the computational problem. I think because of the, I think our world and our mathematics has biased us towards rigid, but it really should make things better in some ways, right? It's a, I think the future is unwritten there. But the other thing is- I think ultimately, sorry to interrupt, but I think ultimately it will make things simpler if we embrace the softness of the world. It makes, um, it makes things smoother, right? So the result of small actions is less discontinuous, but it also means potentially less, you know, instantaneously bad, for instance. I won't necessarily contact something and send it flying off. The other aspect of it that just happens to dovetail really well is that soft robotics tends to be a place where we can embed a lot of sensors too. So if you change your, um, your hardware and make it more soft, then you can potentially have a tactile sensor, which is measuring the deformation. So there's a team at TRI that's working on soft hands and you get so much more information. If you, you can put a camera behind the skin roughly and get fantastic tactile information, which is, um, it's super important. Like in manipulation, one of the things that really is frustrating is if you work super hard on your head mounted, on your perception system for your head mounted cameras, and then you've identified an object, you reach down to touch it. And the first, the last thing that happens right before the most important time, you stick your hand and you're occluding your head mounted sensors, right? So in all the part that really matters, all of your off-board sensors are, you know, are occluded. And really, if you don't have tactile information, then you're blind in an important way. So it happens that soft robotics and tactile sensing tend to go hand in hand. I think we've kind of talked about it, but you taught a course on under-actuated robotics. I believe that was the name of it, actually. That's right. Can you talk about it in that context? What is under-actuated robotics? Right, so under-actuated robotics is my graduate course. It's online mostly now, in the sense that the lectures- Several versions of it, I think. Right, the YouTube- It's really great, I recommend it highly. Look on YouTube for the 2020 versions until March, and then you have to go back to 2019, thanks to COVID. No, I've poured my heart into that class. And lecture one is basically explaining what the word under-actuated means. So people are very kind to show up, and then maybe have to learn what the title of the course means over the course of the first lecture. That first lecture's really good. You should watch it. Thanks. It's a strange name, but I thought it captured the essence of what control was good at doing and what control was bad at doing. So what do I mean by under-actuated? So a mechanical system has many degrees of freedom, for instance, I think of a joint as a degree of freedom, and it has some number of actuators, motors. So if you have a robot that's bolted to the table that has five degrees of freedom and five motors, then you have a fully actuated robot. If you take away one of those motors, then you have an under-actuated robot. Now, why on earth, I have a good friend who likes to tease me, he said, Russ, if you had more research funding, would you work on fully actuated robots? And the answer is no. The world gives us under-actuated robots, whether we like it or not. I'm a human, I'm an under-actuated robot. Even though I have more muscles than a human, even though I have more muscles than my big degrees of freedom, because I have, in some places, multiple muscles attached to the same joint. But still, there's a really important degree of freedom that I have, which is the location of my center of mass in space, for instance. All right, I can jump into the air, and there's no motor that connects my center of mass to the ground in that case. So I have to think about the implications of not having control over everything. The passive dynamic walkers are the extreme view of that, where you've taken away all the motors, and you have to let physics do the work. But it shows up in all of the walking robots, where you have to use some of the actuators to push and pull even the degrees of freedom that you don't have an actuator on. That's referring to walking if you're falling forward. Like, is there a way to walk that's fully actuated? So it's a subtle point. When you're in contact and you have your feet on the ground, there are still limits to what you can do. Unless I have suction cups on my feet, I cannot accelerate my center of mass towards the ground faster than gravity, because I can't get a force pushing me down. But I can still do most of the things that I want to. So you can get away with basically thinking of the system as fully actuated, unless you suddenly needed to accelerate down super fast. But as soon as I take a step, I get into the more nuanced territory. And to get to really dynamic robots, or airplanes or other things, I think you have to embrace the under-actuated dynamics. Manipulation, people think, is manipulation under-actuated? Even if my arm is fully actuated, I have a motor, if my goal is to control the position and orientation of this cup, then I don't have an actuator for that directly. So I have to use my actuators over here to control this thing. Now it gets even worse. Like, what if I have to button my shirt? What are the degrees of freedom of my shirt? I suddenly, that's a hard question to think about. It kind of makes me queasy as thinking about my state-space control ideas. But actually those are the problems that make me so excited about manipulation right now, is that it breaks some of the, it breaks a lot of the foundational control stuff that I've been thinking about. Is there, what are some interesting insights you could say about trying to solve an under-actuated control in an under-actuated system? So I think the philosophy there is let physics do more of the work. The technical approach has been optimization. So you typically formulate your decision-making for control as an optimization problem, and you use the language of optimal control, and sometimes often numerical optimal control, in order to make those decisions and balance these complicated equations of, and in order to control. You don't have to use optimal control to do under-actuated systems, but that has been the technical approach that has borne the most fruit in our, at least in our line of work. And there's some, so in under-actuated systems, when you say, let physics do some of the work, so there's a kind of feedback loop that observes the state that the physics brought you to. So like, you've, there's a perception there, there's a feedback somehow. Do you ever loop in like complicated perception systems into this whole picture? Right, right around the time of the DARPA challenge, we had a complicated perception system in the DARPA challenge. We also started to embrace perception for our flying vehicles at the time. We had a really good project on trying to make airplanes fly at high speeds through forests. Sertac Karaman was on that project, and we had, it was a really fun team to work on. He's carried it farther, much farther forward since then. So yes. And that's using cameras for perception? So that was using cameras. That was, at the time, we felt like LIDAR was too heavy and too power heavy to be carried on a light UAV, and we were using cameras. And that was a big part of it, was just how do you do even stereo matching at a fast enough rate with a small camera, a small onboard compute. Since then, we have now, so the deep learning revolution unquestionably changed what we can do with perception for robotics and control. So in manipulation, we can address, we can use perception in, I think, a much deeper way. And we get into not only, I think the first use of it naturally would be to ask your deep learning system to look at the cameras and produce the state, which is like the pose of my thing, for instance. But I think we've quickly found out that that's not always the right thing to do. Why is that? Because what's the state of my shirt? Imagine I've- Is it very noisy, you mean? If the first step of me trying to button my shirt is estimate the full state of my shirt, including what's happening in the back, you know, whatever, whatever, that's just not the right specification. There are aspects of the state that are very important to the task. There are many that are unobservable and not important to the task. So you really need, it begs new questions about state representation. Another example that we've been playing with in lab has been just the idea of chopping onions, okay? Or carrots, turns out to be better. So the onions stink up the lab. And they're hard to see in a camera. But- The details matter, yeah. Details matter, you know? So if I'm moving around a particular object, right? Then I think about, oh, it's got a position or an orientation in space. That's the description I want. Now, when I'm chopping an onion, okay, like the first chop comes down, I have now a hundred pieces of onion. Does my control system really need to understand the position and orientation and even the shape of the hundred pieces of onion in order to make a decision? Probably not, you know? And if I keep going, I'm just getting, more and more is my state space getting bigger as I cut. It's not right. So somehow there's a- I think there's a richer idea of state. It's not the state that is given to us by Lagrangian mechanics. There is a proper Lagrangian state of the system, but the relevant state for this is some latent state is what we call it in machine learning. But there's some different state representation. Some compressed representation. And that's what I worry about saying, compressed, because it doesn't, I don't mind that it's low dimensional or not, but it has to be something that's easier to think about. Biased humans. Or my algorithms. Or the algorithms being like control, optimal control. So for instance, if the contact mechanics of all of those onion pieces, and all the permutations of possible touches between those onion pieces, you can give me a high dimensional state representation, I'm okay if it's linear. But if I have to think about all the possible shattering combinatorics of that, then my robot's gonna sit there thinking, and the soup's gonna get cold or something. So since you taught the course, it kinda entered my mind, the idea of underactuated as really compelling to see the world in this kind of way. Do you ever, if we talk about onions, or you talk about the world with people in it in general, do you see the world as basically an underactuated system? Do you often look at the world in this way? Or is this overreach? Underactuated is a way of life, man. Exactly. I guess that's what I'm asking. I do think it's everywhere. I think in some places, we already have natural tools to deal with it. It rears its head. I mean, in linear systems, it's not a problem. An underactuated linear system is really not sufficiently distinct from a fully actuated linear system. It's a subtle point about when that becomes a bottleneck in what we know how to do with control. It happens to be a bottleneck, although we've gotten incredibly good solutions now. But for a long time, I felt that that was the key bottleneck in Legged Robots. And roughly now, the underactuated course is, me trying to tell people everything I can about how to make Atlas do a backflip. I have a second course now that I teach in the other semesters, which is on manipulation. And that's where we get into now more of the, that's a newer class. I'm hoping to put it online this fall completely. And that's gonna have much more aspects about these perception problems and the state representation questions, and then how do you do control. And the thing that's a little bit sad is that, for me at least, is there's a lot of manipulation tasks that people wanna do and should wanna do. They could start a company with it and be very successful that don't actually require you to think that much about underaction or dynamics at all, even, but certainly underactuated dynamics. Once I have, if I reach out and grab something, if I can sort of assume it's rigidly attached to my hand, then I can do a lot of interesting, meaningful things with it without really ever thinking about the dynamics of that object. So we've built systems that kind of reduce the need for that, enveloping grasps and the like. But I think the really good problems in manipulation, so manipulation, by the way, is more than just pick and place. That's like, a lot of people think of that, just grasping. I don't mean that, I mean buttoning my shirt. I mean tying shoelaces. How do you program a robot to tie shoelaces? And not just one shoe, but every shoe, right? That's a really good problem. It's tempting to write down like the infinite dimensional state of the laces. That's probably not needed to write a good controller. I know we could hand design a controller that would do it, but I don't want that. I wanna understand the principles that would allow me to solve another problem that's kind of like that. But I think if we can stay pure in our approach, then the challenge of tying anybody's shoes is a great challenge. That's a great challenge. I mean, and the soft touch comes into play there. That's really interesting. Let me ask another ridiculous question on this topic. Like how important is touch? We haven't talked much about humans, but I have this argument with my dad where like I think you can fall in love with a robot based on language alone. And he believes that touch is essential. Like touch and smell, he says. But so in terms of robots connecting with humans, we can go philosophical in terms of like a deep meaningful connection like love, but even just like collaborating in an interesting way, how important is touch? From an engineering perspective and a philosophical one. I think it's super important. Even just in a practical sense, if we forget about the emotional part of it, but for robots to interact safely while they're doing meaningful mechanical work in the close contact with or vicinity of people that need help, I think we have to have them, we have to build them differently. They have to be afraid, not afraid of touching the world. So I think Baymax is just awesome. That's just like the movie of Big Hero 6 and the concept of Baymax, that's just awesome. I think we should, and we have some folks at Toyota that are trying to, Toyota Research that are trying to build Baymax roughly. And I think it's just a fantastically good project. I think it will change the way people physically interact. The same way, I mean, you gave a couple examples earlier, but if the robot that was walking around my home looked more like a teddy bear and a little less like the Terminator, that could change completely the way people perceive it and interact with it. And maybe they'll even wanna teach it, like you said. You could not quite gamify it, but somehow instead of people judging it and looking at it as if it's not doing as well as a human, they're gonna try to help out the cute teddy bear. Who knows? But I think we're building robots wrong and being more soft and more contact is important, right? Yeah, like all the magical moments I can remember with robots. Well, first of all, just visiting your lab and seeing Atlas, but also Spot Mini. When I first saw Spot Mini in person and hung out with him, her, it, I don't have trouble gendering robots. I feel robotics people really say, oh, is it it? I kinda like the idea that it's a her or him. There's a magical moment, but there's no touching. I guess the question I have, have you ever been, like, have you had a human robot experience where a robot touched you? And it was like, wait, was there a moment that you've forgotten that a robot is a robot? And like the anthropomorphization stepped in and for a second you forgot that it's not human? I mean, I think when you're in on the details, then we of course anthropomorphized our work with Atlas, but in verbal communication and the like, I think we were pretty aware of it as a machine that needed to be respected. I actually, I worry more about the smaller robots that could still move quickly if programmed wrong and we have to be careful actually about safety and the like right now. And that, if we build our robots correctly, I think then a lot of those concerns could go away. And we're seeing that trend. We're seeing the lower cost, lighter weight arms now that could be fundamentally safe. I mean, I do think touch is so fundamental. Ted Adelson is great. He's a perceptual scientist at MIT and he studied vision most of his life. And he said, when I had kids, I expected to be fascinated by their perceptual development. But what really, what he noticed was, felt more impressive, more dominant was the way that they would touch everything and lick everything. And pick things up, stick it on their tongue and whatever. And he said, watching his daughter convinced him that actually he needed to study tactile sensing more. So there's something very important. I think it's a little bit also of the passive versus active part of the world, right? You can passively perceive the world, but it's fundamentally different if you can do an experiment, and if you can change the world. And you can learn a lot more than a passive observer. So you can, in dialogue, that was your initial example, you could have an active experiment exchange. But I think if you're just a camera watching YouTube, I think that's a very different problem than if you're a robot that can apply force. So I think that's a very important thing. A robot that can apply force and touch. I think it's important. Yeah, I think it's just an exciting area of research. I think you're probably right that this hasn't been under-researched. To me as a person who's captivated by the idea of human-robot interaction, it feels like such a rich opportunity to explore touch. Not even from a safety perspective, but like you said, the emotional too. I mean, safety comes first. But the next step is like a real human connection. Even in the industrial setting, it just feels like it's nice for the robot. I don't know, you might disagree with this, because I think it's important to see robots as tools often. But I don't know. I think they're just always going to be more effective once you humanize them. It's convenient now to think of them as tools because we wanna focus on the safety. But I think ultimately to create a good experience for the worker, for the person, there has to be a human element. I don't know, for me. It feels like an industrial robotic arm would be better if it has a human element. I think like Rethink Robotics had that idea with Baxter and having eyes and so on. Having, I don't know, I'm a big believer in that. It's not my area, but I am also a big believer. Do you have an emotional connection to Atlas? Like, do you miss him? I mean, yes. Yes, I don't know more so than if I had a different science project that I'd worked on super hard. But yeah, I mean, the robot, we basically had to do heart surgery on the robot in the final competition, because we melted the core. Yeah, there was something about watching that robot hanging there. We know we had to compete with it in an hour, and it was really hard. But yeah, I mean, I think that's the thing. We had to compete with it in an hour, and it was getting its guts ripped out. Those are all historic moments. I think if you look back like 100 years from now, yeah, I think those are important moments in robotics. I mean, these are the early days. You look at like the early days of a lot of scientific disciplines. They look ridiculous, they're full of failure. But it feels like robotics will be important in the coming 100 years. And these are the early days. So I think a lot of people look at a brilliant person such as yourself and are curious about the intellectual journey they've took. Is there maybe three books, technical, fiction, philosophical, that had a big impact on your life that you would recommend perhaps others reading? Yeah, so I actually didn't read that much as a kid, but I read fairly voraciously now. There are some recent books that if you're interested in this kind of topic, like AI Superpowers by Kai-Fu Lee is just a fantastic read. You must read that. Yuval Harari, I think that can open your mind. Sapiens. Sapiens is the first one. Homo Deus is the second, yeah. We mentioned The Black Swan by Taleb. I think that's a good sort of mind opener. I actually, so there's maybe a more controversial recommendation I could give. Great, we love controversy. In some sense, it's so classical it might surprise you. But I actually recently read Mortimer Adler's How to Read a Book. Not so long ago, it was a while ago. But some people hate that book. I loved it. I think we're in this time right now where, boy, we're just inundated with research papers that you could read on archive with limited peer review and just this wealth of information. I don't know, I think the passion of what you can get out of a book, a really good book or a really good paper if you find it, the attitude, the realization that you're only gonna find a few that really are worth all your time. But then once you find them, you should just dig in and understand it very deeply and it's worth marking it up and having the hard copy, writing in the side notes, side margins. I think that was really, I read it at the right time where I was just feeling just overwhelmed with really low quality stuff, I guess. And similarly, I'm just giving more than three now. I'm sorry if I've exceeded my quota. But on that topic just real quick is, so basically finding a few companions to keep for the rest of your life in terms of papers and books and so on. And those are the ones, like not doing, what is it, FOMO, fear of missing out, constantly trying to update yourself, but really deeply making a life journey of studying a particular paper, essentially, set of papers. Yeah, I think when you really find something, which a book that resonates with you might not be the same book that resonates with me, but when you really find one that resonates with you, I think the dialogue that happens, and that's what I love that Adler was saying, I think Socrates and Plato say, the written word is never gonna capture the beauty of dialogue, right? But Adler says, no, no, a really good book is a dialogue between you and the author, and it crosses time and space. I don't know, I think it's a very romantic, there's a bunch of specific advice which you can just gloss over, but the romantic view of how to read and really appreciate it is so good. And similarly, teaching. Yeah. I thought a lot about teaching. So Isaac Asimov, great science fiction writer, has also actually spent a lot of his career writing nonfiction, right? His memoir is fantastic. He was passionate about explaining things, right? He wrote all kinds of books on all kinds of topics in science. He was known as the great explainer. And I do really resonate with his style and just his way of talking about, by communicating and explaining to something is really the way that you learn something. I think about problems very differently because of the way I've been given the opportunity to teach them at MIT. And we have questions asked, the fear of the lecture, the experience of the lecture and the questions I get and the interactions just forces me to be rock solid on these ideas in a way that if I didn't have that, I don't know I would be in a different intellectual space. Also, video, does that scare you that your lectures are online and people like me in sweatpants can sit, sipping coffee and watch you give lectures? I think it's great. I do think that something's changed right now, which is, right now we're giving lectures over Zoom. I mean, giving seminars over Zoom and everything. I'm trying to figure out, I think it's a new medium. I'm trying to figure out how to exploit it. Yeah, I've been quite cynical about the human to human connection over that medium, but I think that's because it hasn't been explored fully. And teaching is a different thing. Every lecture is a, I'm sorry, every seminar even, I think every talk I give, is an opportunity to give that differently. I can deliver content directly into your browser. You have a WebGL engine right there. I can throw 3D content into your browser while you're listening to me, right? And I can assume that you have a, at least a powerful enough laptop or something to watch Zoom while I'm doing that, while I'm giving a lecture. That's a new communication tool that I didn't have last year. And I think robotics can potentially benefit a lot from teaching that way. We'll see. It's gonna be an experiment this fall. I'm thinking a lot about it. Yeah, and also, the length of lectures or the length of, there's something, so I guarantee you, 80% of people who started listening to our conversation are still listening to now, which is crazy to me. But so there's a patience and interest in long-form content, but at the same time, there's a magic to forcing yourself to condense an idea to as short as possible. As short as possible, like clip. It can be a part of a longer thing, but just like really beautifully condense an idea. There's a lot of opportunity there that's easier to do in remote with, I don't know, with editing too. Editing is an interesting thing. Most professors don't get, when they give a lecture, don't get to go back and edit out parts, like crisp it up a little bit. That's also, it can do magic. If you remove five to 10 minutes from an hour lecture, it can actually make something special of a lecture. I've seen that in myself and in others too, because I edit other people's lectures to extract clips. It's like there's certain tangents that are like, that lose, they're not interesting. They're mumbling, they're just not, they're not clarifying, they're not helpful at all. And once you remove them, it's just, I don't know. Editing can be magic. It takes a lot of time. Yeah, it takes, it depends, like what is teaching? You have to ask. Yeah. Yeah, because I find the editing process is also beneficial as for teaching, but also for your own learning. I don't know, have you watched yourself? Yeah, sure. Have you watched those videos? I mean, not all of them. It could be painful to see how to improve. So do you find that, I know you segment your podcast. Do you think that helps people with the attention span aspect of it, or is it the- Segment, like sections, like- Yeah, we're talking about this topic, whatever. Nope, nope, that just helps me. It's actually bad. So, and you've been incredible. So I'm learning, like I'm afraid of conversation. This is, even today, I'm terrified of talking to you. I mean, it's something I'm trying to remove from myself. There's a guy, I mean, I've learned from a lot of people, but really there's been a few people who's been inspirational to me in terms of conversation. Whatever people think of him, Joe Rogan has been inspirational to me because comedians have been too. Being able to just have fun and enjoy themselves and lose themselves in conversation, that requires you to be a great storyteller, to be able to pull a lot of different pieces of information together, but mostly just to enjoy yourself in conversations, and I'm trying to learn that. These notes are, you see me looking down, that's like a safety blanket that I'm trying to let go of more and more. Cool. So that's, people love just regular conversation. That's what they, the structure is like, whatever. I would say, I would say maybe like 10 to, so there's a bunch of, there's probably a couple thousand PhD students listening to this right now, right? And they might know what we're talking about, but there is somebody, I guarantee you right now in Russia, some kid who's just like, who's just smoked some weed, is sitting back and just enjoying the hell out of this conversation, not really understanding. He kind of watched some Boston Dynamics videos. He's just enjoying it, and I salute you, sir. No, but just like there's so much variety of people that just have curiosity about engineering, about sciences, about mathematics, and also like I should, I mean, enjoying it is one thing, but also often notice it inspires people to, there's a lot of people who are like in their undergraduate studies trying to figure out what, trying to figure out what to pursue, and these conversations can really spark the direction of their life. And in terms of robotics, I hope it does, because I'm excited about the possibilities of what robotics brings. On that topic, do you have advice? Like what advice would you give to a young person about life? Or a young person about life in robotics? It could be in robotics, it could be in life in general. It could be career, it could be relationship advice, it could be running advice, just like they're, that's one of the things I see, like we talked to like 20-year-olds. They're like, how do I do this thing? What do I do? And if they come up to you, what would you tell them? I think it's an interesting time to be a kid these days. Everything points to this being sort of a winner-take-all economy and the like. I think the people that will really excel, in my opinion, are gonna be the ones that can think deeply about problems. You have to be able to ask questions agilely and use the internet for everything it's good for and stuff like this. And I think a lot of people will develop those skills. I think the leaders, thought leaders, robotics leaders, whatever, are gonna be the ones that can do more and they can think very deeply and critically, and that's a harder thing to learn. I think one path to learning that is through mathematics, through engineering, I would encourage people to start math early. I mean, I didn't really start, I mean, I was always in the better math classes that I could take, but I wasn't pursuing super advanced mathematics or anything like that until I got to MIT. I think MIT lit me up and really started the life that I'm living now. But yeah, I really want kids to dig deep, really understand things, building things too. I mean, pull things apart, put them back together. Like that's just such a good way to really understand things and expect it to be a long journey, right? It's, you don't have to know everything. You're never gonna know everything. So think deeply and stick with it. Enjoy the ride, but just make sure you're not, yeah, just make sure you're stopping to think about why things work. Yeah, it's true. It's easy to lose yourself in the distractions of the world. We're overwhelmed with content right now, but you have to stop and pick some of it and really understand. Yeah, on the book point, I've read Animal Farm by George Orwell a ridiculous number of times. So for me, like that book, I don't know if it's a good book in general, but for me, it connects deeply somehow. It somehow connects. So I was born in the Soviet Union. So it connects to me into the entirety of the history of the Soviet Union and to World War II and to the love and hatred and suffering that went on there and the corrupting nature of power and greed. And just somehow, I just, that book has taught me more about life than like anything else, even though it's just like a silly, like childlike book about pigs. I don't know why, it just connects and inspires. And the same, there's a few, yeah, there's a few technical books too and algorithms that just, yeah, you return to often. I'm with you. Yeah, there's, I don't know, and I've been losing that because of the internet. I've been like going on, I've been going to archive and blog posts and GitHub and the new thing. And you lose your ability to really master an idea. Wow. Yeah, right, exactly right. What's a fond memory from childhood? When baby Russ Tedrick. Well, I guess I just said that, at least my current life begins, began when I got to MIT. If I have to go farther than that. Yeah, what was, was there a life before MIT? Oh, absolutely. But let me actually tell you what happened when I first got to MIT, cause that I think might be relevant here. But I had taken a computer engineering degree at Michigan. I enjoyed it immensely, learned a bunch of stuff. I liked computers, I liked programming. But when I did get to MIT and started working with Sebastian Sung, theoretical physicist, computational neuroscientist, the culture here was just different. It demanded more of me, certainly mathematically and in the critical thinking. And I remember the day that I borrowed one of the books from my advisor's office and walked down to the Charles River and was like, I'm getting my butt kicked. And I think that's gonna happen to everybody who's doing this kind of stuff, right? I think, I expected you to ask me the meaning of life. You know, I think that the, somehow I think that's gotta be part of it. Doing hard things? Yeah. Did you consider quitting at any point? Did you consider this isn't for me? No, never that. I mean, I was working hard, but I was loving it. I mean, there's, I think there's this magical thing where you, you know, I'm lucky to surround myself with people that basically, almost every day I'll see something, I'll be told something or something that I realized, wow, I don't understand that. And if I could just understand that, there's something else to learn that if I could just learn that thing, I would connect another piece of the puzzle. And, you know, I think that is just such an important aspect and being willing to understand what you can and can't do and loving the journey of going and learning those other things. I think that's the best part. I don't think there's a better way to end it, Russ. You've been an inspiration to me since I showed up at MIT. Your work has been an inspiration to the world. This conversation was amazing. I can't wait to see what you do next with robotics, home robots. I hope to see your work in my home one day. So thanks so much for talking today. It's been awesome. Cheers. Thanks for listening to this conversation with Russ Tedrick. And thank you to our sponsors, Magic Spoon Cereal, BetterHelp, and ExpressVPN. Please consider supporting this podcast by going to magicspoon.com slash Lex and using code Lex at checkout. Go into betterhelp.com slash Lex and signing up at expressvpn.com slash LexPod. Click the links, buy the stuff, get the discount. It really is the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon, or connect with me on Twitter at Lex Friedman, spelled somehow without the E, just F-R-I-D-M-A-N. And now let me leave you with some words from Neil deGrasse Tyson, talking about robots in space and the emphasis we humans put on human-based space exploration. Robots are important. If I don my pure scientist hat, I would say just send robots. I'll stay down here and get the data. But nobody's ever given a parade for a robot. Nobody's ever named a high school after a robot. So when I don my public educator hat, I have to recognize the elements of exploration that excite people. It's not only the discoveries and the beautiful photos that come down from the heavens. It's the vicarious participation in discovery itself. Thank you for listening and hope to see you next time.

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Karl Friston: Neuroscience and the Free Energy Principle | Lex Fridman Podcast #99

The following is a conversation with Carl Fristen, one of the greatest neuroscientists in history. Cited over 245,000 times, known for many influential ideas in brain imaging, neuroscience, and theoretical neurobiology, including especially the fascinating idea of the free energy principle for action and perception. Carl's mix of humor, brilliance, and kindness, to me, are inspiring and captivating. This was a huge honor and a pleasure. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to send and receive money digitally, let me mention a surprising fact related to physical money. Of all the currency in the world, roughly 8% of it is actual physical money. The other 92% of money only exists digitally. So again, if you get Cash App from the App Store, Google Play, and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Carl Fristen. How much of the human brain do we understand from the low level of neuronal communication to the functional level to the highest level, maybe the psychiatric disorder level? Well, we're certainly in a better position than we were last century. How far we've got to go, I think, is almost an unanswerable question. So you'd have to set the parameters, you know, what constitutes understanding, what level of understanding do you want? I think we've made enormous progress in terms of broad brush principles. Whether that affords a detailed cartography of the functional anatomy of the brain and what it does, and right down to the microcircuitry in the neurons, that's probably out of reach at the present time. So the cartography, so mapping the brain, do you think mapping of the brain, the detailed, perfect imaging of it, does that get us closer to understanding of the mind, of the brain? So how far does it get us if we have that perfect cartography of the brain? I think there are lower bounds on that. It's a really interesting question. And it would determine the sort of scientific career you'd pursue if you believe that knowing every dendritic connection, every sort of microscopic synaptic structure right down to the molecular level was gonna give you the right kind of information to understand the computational anatomy, then you'd choose to be a microscopist and you would study little cubic millimeters of brain for the rest of your life. If on the other hand, you were interested in holistic functions and a sort of functional anatomy of the sort that a neuropsychologist would understand, you'd study brain lesions and strokes, you know, just looking at the whole person. So again, it comes back to at what level do you want understanding? I think there are principled reasons not to go too far. If you commit to a view of the brain as a machine that's performing a form of inference and representing things, there are, that understanding, that level of understanding is necessarily cast in terms of probability densities and ensemble densities, distributions. And what that tells you is that you don't really want to look at the atoms to understand the thermodynamics of probabilistic descriptions of how the brain works. So I personally wouldn't look at the molecules or indeed the single neurons in the same way if I wanted to understand the thermodynamics of some non-equilibrium steady state of a gas or an active material, I wouldn't spend my life looking at the individual molecules that constitute that ensemble. I'd look at their collective behavior. On the other hand, if you go too coarse grain, you're gonna miss some basic canonical principles of connectivity and architectures. I'm thinking here, this bit colloquial, but there's current excitement about high field magnetic resonance imaging at Cephan Tesla. Why? Well, it gives us for the first time the opportunity to look at the brain in action at the level of a few millimeters that distinguish between different layers of the cortex that may be very important in terms of evincing generic principles of conical microcircuitry that are replicated throughout the brain that may tell us something fundamental about message passing in the brain and these density dynamics or neuronal or ensemble population dynamics that underwrite our brain function. So somewhere between a millimeter and a meter. Lingering for a bit on the big questions, if you allow me, what to you is the most beautiful or surprising characteristic of the human brain? I think it's hierarchical and recursive aspect. It's recurrent aspect. Of the structure or of the actual representation of power of the brain? Well, I think one speaks to the other. I was actually answering in a dull-minded way from the point of view of purely its anatomy and its structural aspects. I mean, there are many marvelous organs in the body. Let's take your liver, for example. Without it, you wouldn't be around for very long. And it does some beautiful and delicate biochemistry and homeostasis and evolved with a finesse that would easily parallel the brain. But it doesn't have a beautiful anatomy. It has a simple anatomy, which is attractive in a minimalist sense, but it doesn't have that crafted structure of sparse connectivity and that recurrence and that specialization that the brain has. So you said a lot of interesting terms here. The recurrence, the sparsity, but you also started by saying hierarchical. So I've never thought of our brain as hierarchical. I always thought it was just like a giant mess, interconnected mess where it's very difficult to figure anything out. But in what sense do you see the brain as hierarchical? Well, I see it's not a magic soup, which of course, is what I used to think when I was, before I studied medicine and the like. So a lot of those terms imply each other. So hierarchies, if you just think about the nature of a hierarchy, how would you actually build one? And what you would have to do is basically carefully remove the right connections that destroy the completely connected soups that you might have in mind. So a hierarchy is in and of itself defined by a sparse and particular connectivity structure. I'm not committing to any particular form of hierarchy. But your sense is there is some. Oh, absolutely, yeah. In virtue of the fact that there is a sparsity of connectivity, not necessarily of a qualitative sort, but certainly for quantitative sort. So it is demonstrably so that the further apart two parts of the brain are, the less likely that they are to be wired, to possess axonal processes, neuronal processes that directly communicate one message or messages from one part of that brain to the other part of the brain. So we know there's a sparse connectivity. And furthermore, on the basis of anatomical connectivity in tracer studies, we know that that sparsity underwrites a hierarchical and very structured sort of connectivity that might be best understood like a little bit like an onion. There is a concentric, sometimes referred to as centripetal by people like Marcel Mesulam, hierarchical organization to the brain. So you can think of the brain as in a rough sense, like an onion, and all the sensory information and all the afferent outgoing messages that supply commands to your muscles or to your secretory organs come from the surface. So there's a massive exchange interface with the world out there on the surface. And then underneath, there's a little layer that sits and looks at the exchange on the surface. And then underneath that, there's a layer right the way down to the very center, to the deepest part of the onion. That's what I mean by a hierarchical organization. There's a discernible structure defined by the sparsity of connections that lends the architecture, a hierarchical structure that tells one a lot about the kinds of representations and messages. So coming back to your earlier question, is this about the representational capacity or is it about the anatomy? Well, one underwrites the other. If one simply thinks of the brain as a message-passing machine, a process that is in the service of doing something, then the circuitry and the connectivity that shape that message-passing also dictate its function. So you've done a lot of amazing work in a lot of directions. So let's look at one aspect of that, of looking into the brain and trying to study this onion structure. What can we learn about the brain by imaging it, which is one way to sort of look at the anatomy of it, broadly speaking? What are the methods of imaging, but even bigger, what can we learn about it? Right, so well, most imaging, human neuroimaging that you might see in science journals, that speaks to the way the brain works measures brain activity over time. So that's the first thing to say, that we're effectively looking at fluctuations in neuronal responses, usually in response to some sensory input or some instruction, some task. Not necessarily, there's a lot of interest in just looking at the brain in terms of resting state, endogenous or intrinsic activity, but crucially, at every point, looking at these fluctuations, either induced or intrinsic in neural activity and understanding them at two levels. So normally people would recourse to two principles of brain organization that are complementary. One, functional specialization or segregation. So what does that mean? It simply means that there are certain parts of the brain that may be specialized for certain kinds of processing. You know, for example, visual motion, our ability to recognize or to perceive movement in the visual world. And furthermore, that specialized processing may be spatially or anatomically segregated leading to functional segregation, which means that if I were to compare your brain activity during a period of viewing a static image and then compare that to the responses of fluctuations in the brain when you were exposed to a moving image, say a flying bird, I would expect to see restricted, segregated differences in activity. And those are basically the hotspots that you see in statistical parametric maps that test for the significance of the responses that are circumscribed. So now basically we're talking about some people have perhaps unkindly called a neocartography. This is a phrenology augmented by modern day neuroimaging, basically finding blobs or bumps on the brain that do this or do that and trying to understand the cartography of that functional specialization. So how much is there such, since that's such a beautiful sort of ideal to strive for, we humans, scientists would like to hope that there's a beautiful structure to this whereas like you said, there are segregated regions that are responsible for the different function. How much hope is there to find such regions in terms of looking at the progress of studying the brain? Oh, I think enormous progress has been made in the past 20 or 30 years. So this is beyond incremental. You know, at the advent of brain imaging, the very notion of functional segregation was just a hypothesis based upon a century, if not more, of careful neuropsychology, looking at people who had lost via insult or traumatic brain injury, particular parts of the brain, and then say, well, they can't do this or they can't do that. For example, losing the visual cortex and not being able to see or losing particular parts of the visual cortex or regions known as V5 or the middle temporal region, MT, and noticing that they selectively could not see moving things. And so that created the hypothesis that perhaps movement processing, visual movement processing, was located in this functionally segregated area. And you could then go and put invasive electrodes in animal models and say, yes, indeed, we can excite activity here. We can form receptive fields that are sensitive to or defined in terms of visual motion. But at no point could you exclude the possibility that everywhere else in the brain was also very interested in visual motion. By the way, I apologize to interrupt, but a tiny little tangent, you said animal models. Just out of curiosity, from your perspective, how different is the human brain versus the other animals in terms of our ability to study the brain? Well, clearly, the further away you go from a human brain, the greater the difference is, but not as remarkable as you might think. So people will choose their level of approximation to the human brain depending upon the kinds of questions that they want to answer. So if you're talking about sort of canonical principles of microcircuitry, it might be perfectly okay to look at a mouse, indeed. You could even look at flies, worms. If, on the other hand, you wanted to look at the finer details of organization of visual cortex and V1, V2, these are designated sort of patches of cortex that may do different things, indeed do, you'd probably want to use a primate that looked a little bit more like a human because there are lots of ethical issues in terms of the use of non-human primates to answer questions about human anatomy. But I think most people assume that most of the important principles are conserved in a continuous way, right from, well, yes, worms right the way through to you and me. So now returning to, so that was the early sort of ideas of studying the functional regions of the brain by if there's some damage to it, to try to infer that there's, that part of the brain might be somewhat responsible for this type of function. So where does that lead us? What are the next steps beyond that? Right, well, just actually to reverse a bit, come back to your sort of notion that the brain is a magic soup. That was actually a very prominent idea at one point, notions such as Lashley's law of mass action, inherited from the observation that for certain animals, if you just took out spoonfuls of the brain, it didn't matter where you took these spoonfuls out, they always showed the same kinds of deficits. So it was very difficult to infer functional specialization pure on the basis of lesion deficit studies. But once we had the opportunity to look at the brain lighting up, and it's literally, it's sort of excitement, neuronal excitement when looking at this versus that, versus that, one was able to say, yes, indeed, these functionally specialized responses are very restricted and they're here or they're over there. If I do this, then this part of the brain lights up. And that became doable in the early 90s. In fact, shortly before with the advent of positron emission tomography, and then functional magnetic resonance imaging came along in the early 90s. And since that time, there has been an explosion of discovery, refinement, confirmation. There are people who believe that it's all in the anatomy. If you understand the anatomy, then you understand the function at some level. And many, many hypotheses were predicated on a deep understanding of the anatomy and the connectivity, but they were all confirmed and taken much further with neuroimaging. So that's what I meant by we've made an enormous amount of progress in this century, indeed, and in relation to the previous century, by looking at these functionally selective responses. But that wasn't the whole story. So there's this sort of neophrenology, but finding bumps and hot spots in the brain that did this or that. The bigger question was, of course, the functional integration. How all of these regionally specific responses were orchestrated, how they were distributed, how did they relate to distributed processing, and indeed, representations in the brain? So then you turn to the more challenging issue of the integration, the connectivity. And then we come back to this beautiful, sparse, recurrent, hierarchical connectivity that seems characteristic of the brain, and probably not many other organs. But nevertheless, we come back to this challenge of trying to figure out how everything is integrated. But what's your feeling? What's the general consensus? Have we moved away from the magic soup view of the brain? So there is a deep structure to it. And then maybe a further question. You said some people believe that the structure is most of it, that you can really get at the core of the function by just deeply understanding the structure. Where do you sit on that? I think it's got some mileage to it, yes. So it's a worthy pursuit of going, of studying through imaging and all the different methods to actually study the structure. Yeah, yeah. Sorry, I'm just noting, you were accusing me of using lots of long words, and then you introduced one there, which is deep, which is interesting. Because deep is the sort of millennial equivalent of hierarchical. So if you put deep in front of anything, not only are you very millennial and very trending, but you're also implying a hierarchical architecture. So it is a depth, which is, for me, the beautiful thing. That's right, the word deep kind of, yeah, exactly, it implies hierarchy. I didn't even think about that. That indeed, the implicit meaning of the word deep is a hierarchy. Yep. Yeah. So deep inside the onion is the center of your soul. That's the. Beautiful put. Maybe briefly, if you could paint a picture of the kind of methods of neuroimaging, maybe the history, which you were a part of, from statistical parametric mapping. I mean, just what's out there that's interesting for people maybe outside the field to understand of what are the actual methodologies of looking inside the human brain? Right, well, you can answer that question from two perspectives. Basically, it's the modality. You know, what kind of signal are you measuring? And they can range from, and let's limit ourselves to sort of imaging-based, non-invasive techniques. So you've essentially got brain scanners, and brain scanners can either measure the structural attributes, the amount of water, the amount of fat, or the amount of iron in different parts of the brain. And you can make lots of inferences about the structure of the organ of the sort that you might have abduced from an X-ray, but a very nuanced X-ray that is looking at this kind of property or that kind of property. So looking at the anatomy non-invasively would be the first sort of neuroimaging that people might want to employ. Then you move on to the kinds of measurements that reflect dynamic function. And the most prevalent of those fall into two camps. You've got these metabolic, sometimes hemodynamic, blood-related signals. So these metabolic and or hemodynamic signals are basically proxies for elevated activity and message passing and neuronal dynamics, in particular parts of the brain. Characteristically, though, the time constants of these hemodynamic or metabolic responses to neural activity are much longer than the neural activity itself. And this is referring, forgive me for the dumb questions, but this would be referring to blood, like the flow of blood? Absolutely. So there's a ton of, it seems like there's a ton of blood vessels in the brain. Yeah. So, but what's the interaction between the flow of blood and the function of the neurons? Is there an interplay there? Or is- Yep, yep. And that interplay accounts for several careers of world-renowned scientists. Yes, absolutely. So this is known as neurovascular coupling, is exactly what you said. It's how does the neural activity, the neuronal infrastructure, the actual message passing that we think underlies our capacity to perceive and act, how is that coupled to the vascular responses that supply the energy for that neural processing? So there's a delicate web of large vessels, arteries and veins, that gets progressively finer and finer in detail until it perfuses at a microscopic level, the machinery where little neurons lie. So coming back to this sort of onion perspective, we were talking before using the onion as a metaphor for a deep hierarchical structure, but also I think it's just anatomically quite a useful metaphor. All the action, all the heavy lifting in terms of neural computation is done on the surface of the brain. And then the interior of the brain is constituted by fatty wires, essentially axonal processes that are enshrouded by myelin sheaths. And these give the, when you dissect them, they look fatty and white, and so it's called white matter, as opposed to the actual neuro pill, which does the computation, constituted largely by neurons, and that's known as gray matter. So the gray matter is a surface or a skin that sits on top of this big ball. Now we are talking magic soup, but a big ball of connections like spaghetti, very carefully structured with sparse connectivity that preserve this deep hierarchical structure, but all the action takes place on the surface, on the cortex of the onion. And that means that you have to supply the right amount of blood flow, the right amount of nutrient, which is rapidly absorbed and used by neural cells that don't have the same capacity that your leg muscles would have to basically spend their energy budget and then claim it back later. So one peculiar thing about cerebral metabolism, brain metabolism, is it really needs to be driven in the moment, which means you basically have to turn on the taps. So if there's lots of neural activity in one part of the brain, a little patch of a few millimeters, even less possibly, you really do have to water that piece of the garden now and quickly. And by quickly, I mean within a couple of seconds. So that contains a lot of, hence the imaging could tell you a story of what's happening in the brain. Absolutely. But it is slightly compromised in terms of the resolution. So the deployment of these little micro vessels that water the garden to enable the activity, the neural activity to play out, the spatial resolution is in order of a few millimeters. And crucially, the temporal resolution is the order of a few seconds. So you can't get right down and dirty into the actual spatial and temporal scale of neural activity in and of itself. To do that, you'd have to turn to the other big imaging modality, which is the recording of electromagnetic signals as they're generated in real time. So here, the temporal bandwidth, if you like, or the low limit on the temporal resolution is incredibly small. You're talking about milliseconds. And then you can get into the phasic fast responses that is in and of itself the neural activity and start to see the succession or cascade of hierarchical recurrent message passing evoked by a particular stimulus. But the problem is you're looking at electromagnetic signals that have passed through an enormous amount of magic soup or spaghetti of connectivity. And through the scalp and the skull, and it's become spatially very diffuse. So it's very difficult to know where you are. So you've got this sort of catch-22. You can either use an imaging modality that tells you within millimeters which part of the brain is activated, but you don't know when. Or you've got these electromagnetic EEG, MEG setups that tell you to within a few milliseconds when something has responded, but you're not aware. So you've got these two complementary measures, either indirect via the blood flow or direct via the electromagnetic signals caused by neural activity. These are the two big imaging devices. And then the second level of responding to your question, what are the, from the outside, what are the big ways of using this technology? So once you've chosen the kind of mirror imaging that you want to use to answer your set questions, and sometimes it would have to be both, then you've got a whole raft of analyses, time series analyses usually, that you can bring to bear in order to answer your questions or address your hypotheses about those data. And interestingly, they both fall into the same two camps we were talking about before. You know, this dialectic between specialization and integration, differentiation and integration. So it's the cartography, the blobology analyses. I apologize, I probably shouldn't interrupt so much, but just heard a fun word, the blobology. It's a neologism, which means the study of blobs. Nothing more. Are you being witty and humorous, or is there an actual, does the word blobology ever appear in a textbook somewhere? It would appear in a popular book. It would not appear in a worthy specialist journal. But it's the fond word for the study of literally little blobs on brain maps showing activations. So the kind of thing that you'd see in the newspapers on ABC or BBC reporting the latest finding from brain imaging. Interestingly though, the maths involved in that stream of analysis does actually call upon the mathematics of blobs. So seriously, they're actually called Euler characteristics and they have a lot of fancy names in mathematics. We'll talk about it, but your ideas in free energy principle, I mean, there's echoes of blobs there when you consider sort of entities, mathematically speaking. Yes, absolutely. Yeah, yeah. So anyway. Circumstantial, well-defined. You entities of, well, from the free energy point of view, entities of anything, but from the point of view of the analysis, the cartography of the brain, these are the entities that constitute the evidence for this functional segregation. You have segregated this function in this blob and it is not outside of the blob. And that's basically the, if you were a map maker of America and you did not know its structure, the first thing you're doing constituting or creating a map would be to identify the cities, for example, or the mountains or the rivers. All of these uniquely spatially localizable features, possibly topological features have to be placed somewhere. And of course that requires a mathematics of identifying what does a city look like on a satellite image or what does a river look like or what does a mountain look like? What would it, you know, what data features would evidence that particular thing that you wanted to put on the map? And they normally are characterized in terms of literally these blobs or these sort of, another way of looking at this is that a certain statistical measure of the degree of activation crosses a threshold. In crossing that threshold in the spatially restricted part of the brain, it creates a blob. And that's basically what statistical parametric mapping does, it's basically mathematically finessed blobology. Okay, so those, you kind of described these two methodologies for, one is temporally noisy, one is spatially noisy and you kind of have to play and figure out what can be useful. It'd be great if you can sort of comment, I got a chance recently to spend a day at a company called Neuralink that uses brain computer interfaces and their dream is to, well, there's a bunch of sort of dreams, but one of them is to understand the brain by sort of, you know, getting in there, past the so-called sort of factory wall, getting in there and be able to listen, communicate both directions. What are your thoughts about the future of this kind of technology of brain computer interfaces, to be able to now have a window or direct contact within the brain to be able to measure some of the signals, to be able to send signals, to understand some of the functionality of the brain? Ambivalent, my sense is ambivalent. So it's a mixture of good and bad and I acknowledge that freely. So the good bits, if you just look at the legacy of that kind of reciprocal, but invasive, your brain stimulation, I didn't paint a complete picture when I was talking about some of the ways we understand the brain prior to neuroimaging. It wasn't just lesion deficit studies. Some of the early work, in fact, literally, a hundred years from where we're sitting at the Institute of Neurology, was done by stimulating the brain of, say, dogs and looking at how they responded, either with their muscles or with their salivation, and imputing what that part of the brain must be doing. That if I stimulate it, and I evoke this kind of response, then that tells me quite a lot about the functional specialization. So there's a long history of brain stimulation, which continues to enjoy a lot of attention nowadays. Positive attention? Oh yes, absolutely. Deep brain stimulation for Parkinson's disease is now a standard treatment, and also a wonderful vehicle to try and understand the neuronal dynamics underlying movement disorders like Parkinson's disease. Even interest in magnetic stimulation, stimulating the magnetic fields, and will it work in people who are depressed, for example? Quite a crude level of understanding what you're doing, but there is historical evidence that these kinds of brute force interventions do change things. A little bit like banging the TV when the valves aren't working properly, but it still, it works. So there is a long history. Brain-computer interfacing, or BCI, I think is a beautiful example of that. It's sort of carved out its own niche and its own aspirations, and there've been enormous advances within limits. Advances in terms of our ability to understand how the brain, the embodied brain, engages with the world. I'm thinking here of sensory substitution, augmenting our sensory capacities by giving ourselves extra ways of sensing and sampling the world, ranging from sort of trying to replace lost visual signals through to giving people completely new signals. One of the, I think, most engaging examples of this is equipping people with a sense of magnetic fields. So you can actually give them magnetic sensors that enable them to feel, should we say, tactile pressure around their tummy, where they are in relation to the magnetic field of the earth. And after a few weeks, they take it for granted. They integrate it, they imbibe it, they assimilate this new sensory information into the way that they literally feel their world, but now equipped with this sense of magnetic direction. So that tells you something about the brain's plastic potential to remodel, and its plastic capacity to suddenly try to explain the sensory data at hand by augmenting the sensory sphere and the kinds of things that you can measure. Clearly, that's purely for entertainment and understanding the nature and the power of our brains. I would imagine that most BCI is pitched at solving clinical and human problems, such as locked-in syndrome, such as paraplegia, or replacing lost sensory capacities like blindness and deafness. So then we come to the more negative part of my ambivalence. The other side of it. So I don't want to be deflationary because much of my deflationary comments is probably a large out of ignorance than anything else, but generally speaking, the bandwidth and the bit rates that you get from brain-computer interfaces as we currently know them, we're talking about bits per second. So that would be like me only being able to communicate with any world or with you using very, very, very slow Morse code. And it is not even within an order of magnitude near what we actually need for an inactive realization of what people aspire to when they think about sort of curing people with paraplegia or replacing sight despite heroic efforts. So one has to ask, is there a lower bound on the kinds of recurrent information exchange between a brain and some augmented or artificial interface? And then we come back to, interestingly, what I was talking about before, which is if you're talking about function in terms of inference, and I presume we'll get to that later on in terms of the free energy principle, but at the moment there may be fundamental reasons to assume that is the case. We're talking about ensemble activity. We're talking about basically, for example, let's paint the challenge facing brain-computer interfacing in terms of controlling another system that is highly and deeply structured, very relevant to our lives, very nonlinear, that rests upon the kind of non-equilibrium steady states and dynamics that the brain does, the weather, right? So- Good example, yeah. Imagine you had some very aggressive satellites that could produce signals that could perturb some little parts of the weather system. And then what you're asking now is, can I meaningfully get into the weather and change it meaningfully and make the weather respond in a way that I want it to? You're talking about chaos control on a scale which is almost unimaginable. So there may be fundamental reasons why BCI, as you might read about it in a science fiction novel, aspirational BCI may never actually work in the sense that to really be integrated and be part of the system is a requirement that requires you to have evolved with that system. You have to be part of a very delicately structured, deeply structured, dynamic, ensemble activity that is not like rewiring a broken computer or plugging in a peripheral interface adapter. It is much more like getting into the weather patterns or a, come back to your magic soup, getting into the active matter and meaningfully relate that to the outside world. So I think there are enormous challenges there. So I think the example of the weather is a brilliant one and I think you paint a really interesting picture and it wasn't as negative as I thought. It's essentially saying that it might be incredibly challenging, including the low bound of the bandwidth and so on. I kind of, so just to full disclosure, I come from the machine learning world, so my natural thought is the hardest part is the engineering challenge of controlling the weather, of getting those satellites up and running and so on. And once they are, then the rest is fundamentally the same approaches that allow you to be, to win in the game of Go will allow you to potentially play in this soup, in this chaos. So I have a hope that sort of machine learning methods will help us play in this soup. But perhaps you're right, that it is, biology in the brain is just an incredible system that may be almost impossible to get in. But for me, what seems impossible is the incredible mess of blood vessels that you also described. Without, we also value the brain. You can't make any mistakes, you can't damage things. So to me, that engineering challenge seems nearly impossible. One of the things I was really impressed by at Neuralink is just talking to brilliant neurosurgeons and the roboticists that made me realize that even though it seems impossible, if anyone can do it, it's some of these world-class engineers that are trying to take it on. So I think the conclusion of our discussion here is of this part is basically that the problem is really hard but hopefully not impossible. So if it's okay, let's start with the basics. So you've also formulated a fascinating principle, the free energy principle. Can we maybe start at the basics and what is the free energy principle? Well, in fact, the free energy principle inherits a lot from the building of these data analytic approaches to these very high dimensional time series you get from the brain. So I think it's interesting to acknowledge that. And in particular, the analysis tools that try to address the other side, which is a functional integration. So the connectivity analysis. On the one hand, but I should also acknowledge it inherits an awful lot from machine learning as well. So the free energy principle is just a formal statement that the existential imperatives for any system that manages to survive in a changing world can be cast as an inference problem in the sense that you can interpret the probability of existing as the evidence that you exist. And if you can write down that problem of existence as a statistical problem, then you can use all the maths that has been developed for inference to understand and characterize the ensemble dynamics that must be in play in the service of that inference. So technically what that means is you can always interpret anything that exists in virtue of being separate from the environment in which it exists as trying to minimize variational free energy. And if you're from the machine learning community, you will know that as a negative evidence lower bound or a negative elbow, which is the same as saying you're trying to maximize or it will look as if all your dynamics are trying to maximize the compliment of that which is the marginal likelihood or the evidence for your own existence. So that's basically the free energy principle. But to even take a sort of a small step backwards, you said the existential imperative. There's a lot of beautiful poetic words here, but to put it crudely, it's a fascinating idea of basically just of trying to describe if you're looking at a blob, how do you know this thing is alive? What does it mean to be alive? What does it mean to exist? And so you can look at the brain, you can look at parts of the brain, or this is just the general principle that applies to almost any system. That's just a fascinating sort of philosophically at every level question and a methodology to try to answer that question. What does it mean to be alive? Yes. So that's a huge endeavor and it's nice that there's at least some, from some perspective, a clean answer. So maybe can you talk about that optimization view of it? So what's trying to be minimized to maximize? A system that's alive, what is it trying to minimize? Right, you've made a big move there. First of all- Apologies. No, no, it's good to make big moves. But you've assumed that the thing exists in a state that could be living or non-living. So I may ask you, what licenses you to say that something exists? That's why I use the word existential. It's beyond living, it's just existence. So if you drill down onto the definition of things that exist, then they have certain properties if you borrow the maths from non-equilibrium steady state physics that enable you to interpret their existence in terms of this optimization procedure. So it's good you introduced the word optimization. So what the free energy principle in its sort of most ambitious but also most deflationary and simplest says is that if something exists, then it must, by the mathematics of non-equilibrium steady state, exhibit properties that make it look as if it is optimizing a particular quantity. And it turns out that particular quantity happens to be exactly the same as the evidence lower bound in machine learning or Bayesian model evidence in Bayesian statistics, or, and then I can list a whole other list of ways of understanding this key quantity, which is a bound on surprisal, self-information, if you're in information theory. There are a whole, there are a number of different perspectives on this quantity. It's just basically the log probability of being in a particular state. I'm telling this story as an honest attempt to answer your question, and I'm answering it as if I was pretending to be a physicist who was trying to understand the fundaments of non-equilibrium steady state. And I shouldn't really be doing that because the last time I was taught physics, I was in my 20s. What kind of systems, when you think about the free energy principle, what kind of systems are you imagining? As a sort of more specific kind of case study. Yeah, I'm imagining a range of systems, but at its simplest, a single-celled organism that can be identified from its economy or its environment. So at its simplest, that's basically what I always imagined in my head. And you may ask, well, is there any, how on earth can you even elaborate questions about the existence of a single drop of oil, for example? But there are deep questions there. Why doesn't the oil, why doesn't the thing, the interface between the drop of oil that contains an interior and the thing that is not the drop of oil, which is the solvent in which it is immersed, how does that interface persist over time? Why doesn't the oil just dissolve into solvent? So what special properties of the exchange between the surface of the oil drop and the external states in which it's immersed, if you're a physicist, say it would be the heat path. You know, you've got a physical system, an ensemble again, we're talking about density dynamics, ensemble dynamics, an ensemble of atoms or molecules immersed in the heat path. But the question is, how did the heat path get there and why is it not dissolved? Why is it maintaining itself? Exactly. What actions is it? I mean, it's such a fascinating idea of a drop of oil and I guess it would dissolve in water, it wouldn't dissolve in water. So what- Precisely, so why not? Why not? Why not? And how do you mathematically describe, I mean, it's such a beautiful idea and also the idea of like, where does the thing, where does the drop of oil end and where does it begin? Right, so I mean, you're asking deep questions, deep in a non-millennial sense here. In a hierarchical sense. But what you can do, you see, so this is the deflationary part of it. Can I just qualify my answer by saying that normally when I'm asked this question, I answer from the point of view of a psychologist and we talk about predictive processing and predictive coding and the brain as an inference machine. But you haven't asked me from that perspective, but I'm answering from the point of view of a physicist. So the question is not so much why, but if it exists, what properties must it display? So that's the deflationary part of the free energy principle. The free energy principle does not supply an answer as to why, it's saying, if something exists, then it must display these properties. That's the sort of thing that's on offer. And it so happens that these properties, it must display are actually intriguing and have this inferential gloss, this sort of self-evidencing gloss that inherits on the fact that the very preservation of the boundary between the oil drop and the not oil drop requires an optimization of a particular function or a functional that defines the presence of the existence of this oil drop, which is why I started with existential imperatives. It is a necessary condition for existence that this must occur because the boundary basically defines the thing that's existing. So it is that self-assembly aspect it's that you were hinting at in biology, sometimes known as autopoiesis in computational chemistry with self-assembly. It's the, what does it look like? Sorry, how would you describe things that configure themselves out of nothing? The way they clearly demarcate themselves from the states or the soup in which they are immersed. So from the point of view of computational chemistry, for example, you would just understand that as a configuration of a macromolecule to minimize its free energy, its thermodynamic free energy. It's exactly the same principle that we've been talking about that thermodynamic free energy is just the negative elbow. It's the same mathematical construct. So the very emergence of existence of structure of form that can be distinguished from the environment or the thing that is not the thing necessitates the existence of an objective function that it looks as if it is minimizing. It's finding a free energy minima. And so just to clarify, I'm trying to wrap my head around. So the free energy principle says that if something exists, these are the properties it should display. So what that means is we can't just look, we can't just go into a soup and there's no mechanism. A free energy principle doesn't give us a mechanism to find the things that exist. Is that what's implying, is being implied that you can kind of use it to reason, to think about like study a particular system and say, does this exhibit these qualities? That's an excellent question. But to answer that, I'd have to return to your previous question about what's the difference between living and non-living things. Yes, well, actually, sorry. So yeah, maybe we can go there. You kind of drew a line, and forgive me for the stupid questions, but you kind of drew a line between living and existing. Is there an interesting sort of distinction? I think there is. So things do exist, grains of sand, rocks on the moon, trees, you. So all of these things can be separated from the environment in which they are immersed, and therefore, they must at some level be optimizing their free energy. Taking this sort of model evidence interpretation of this quantity, that basically means they're self-evidencing. Another nice little twist of phrase here is that you are your own existence proof, statistically speaking, which I don't think I said that. Somebody did, but I love that phrase. And you are your own existence proof. Yeah, so it's so existential, isn't it? I'm gonna have to think about that for a few days. That's a beautiful line. So the step through to answer your question about what's it good for, we go along the following lines. First of all, you have to define what it means to exist, which now, as you've rightly pointed out, you have to define what probabilistic properties must the states of something possess so it knows where it finishes. And then you write that down in terms of statistical independences. Again, sparsity. Again, it's not what's connected or what's correlated or what depends upon what, it's what's not correlated and what doesn't depend upon something. Again, it comes down to the deep structures, not in this instance hierarchical, but the structures that emerge from removing connectivity and dependency. And in this instance, basically being able to identify the surface of the oil drop from the water in which it is immersed. And when you do that, you start to realize, well, there are actually four kinds of states in any given universe that contains anything. The things that are internal to the surface, the things that are external to the surface and the surface in and of itself, which is why I use a metaphor, a little single-celled organism that has an interior and exterior and then the surface of the cell. And that's mathematically a Markov blanket. Just to pause, I'm in awe of this concept that there's the stuff outside the surface, stuff inside the surface, and the surface itself, the Markov blanket. It's just the most beautiful kind of notion about trying to explore what it means to exist. Mathematically. I apologize, it's just a beautiful idea. It came out of California, so that's. I changed my mind, I take it all back. So anyway, so what, you were just talking about the surface, about the Markov blanket. So this surface or these blanket states that are the, because they are now defined in relation to these independences and what different states, internal or blanket or external states can, which ones can influence each other and which cannot influence each other, you can now apply standard results that you would find in non-equilibrium physics or steady state or thermodynamics or hydrodynamics, usually out of equilibrium solutions and apply them to this partition. And what it looks like is if all the normal gradient flows that you would associate with any non-equilibrium system apply in such a way that two, part of the Markov blanket and the internal states seem to be hill climbing or doing a gradient descent on the same quantity. And that means that you can now describe the very existence of this oil drop. You can write down the existence of this oil drop in terms of flows, dynamics, equations of motion, where the blanket states or part of them, we call them active states and the internal states now seem to be, and must be, trying to look as if they're minimizing the same function, which is a log probability of occupying these states. Interesting thing is that, what would they be called if you were trying to describe these things? So what we're talking about are internal states, external states and blanket states. Now let's carve the blanket states into two, sensory states and active states. Operationally, it has to be the case that in order for this carving up into different sets of states to exist, the active states, the Markov blanket, cannot be influenced by the external states. And we already know that the internal states can't be influenced by the external states because the blanket separates them. So what does that mean? Well, it means the active states, the internal states, are now jointly not influenced by external states. They only have autonomous dynamics. So now you've got a picture of an oil drop that has autonomy. It has autonomous states. It has autonomous states in the sense that there must be some parts of the surface of the oil drop that are not influenced by the external states and all the interior. And together, those two states endow even a little oil drop with autonomous states that look as if they are optimizing their variational free energy or their negative elbow, their model evidence. And that would be an interesting intellectual exercise. And you could say, you could even go into the realms of panpsychism, that everything that exists is implicitly making inferences on self-evidencing. Now we make the next move, but what about living things? I mean, so let me ask you, what's the difference between an oil drop and a little tadpole or a little larva or a plankton? The picture we just painted of an oil drop, just immediately in a matter of minutes, took me into the world of panpsychism, where you just convinced me, made me feel like an oil drop is a living, certainly an autonomous system, but almost a living system. So it has sensor capabilities and acting capabilities and it maintains something. So what is the difference between that and something that we traditionally think of as a living system? That it could die or it can't, I mean, yeah, mortality. I'm not exactly sure. I'm not sure what the right answer there is because it can move, like movement seems like an essential element to being able to act in the environment, but the oil drop is doing that. So I don't know. Is it the oil drop will be moved, but does it in and of itself move autonomously? Well, the surface is performing actions that maintain its structure. You're being too clever. I was, I didn't find a passive little oil drop that's sitting there at the bottom of the top of a glass of water. Sure, I guess. What I'm trying to say is you're absolutely right. You've nailed it. It's movement. So where does that movement come from? If it comes from the inside, then you've got, I think, something that's living. What do you mean from the inside? What I mean is that the internal states that can influence the active states, where the active states can influence, but they're not influenced by the external states, can cause movement. So there are two types of oil drops, if you like. There are oil drops where the internal states are so random that they average themselves away. And the thing cannot balance on average when you do the averaging move. So a nice example of that would be the sun. The sun certainly has internal states. There's lots of intrinsic autonomous activity going on. But because it's not coordinated, because it doesn't have the deep in the millennial sense, a hierarchical structure that the brain does, there is no overall mode or pattern or organization that expresses itself on the surface that allows it to actually swim. It can certainly have a very active surface, but on mass, at the scale of the actual surface of the sun, the average position of that surface cannot in itself move because the internal dynamics are more like a hot gas. They are literally like a hot gas. Whereas your internal dynamics are much more structured and deeply structured. And now you can express on your Markov and your active states with your muscles and your secretory organs, your autonomic nervous system and its effectors. You can actually move. And that's all you can do. And that's something which, if you haven't thought of it like this before, I think it's nice to just realize there is no other way that you can change the universe other than simply moving. Whether that moving is articulating with my voice box or walking around or squeezing juices out of my secretory organs, there's only one way you can change the universe, it's moving. And the fact that you do so non-randomly makes you alive. Yeah. So it's that non-randomness. And that would be manifest, we realize in terms of essentially swimming, essentially moving, changing one shape, a morphogenesis that is dynamic and possibly adaptive. So that's what I was trying to get up between the difference from the oil drop and the little tadpole. The tadpole is moving around. Its active states are actually changing the external states. And there's now a cycle, an action perception cycle, if you like, a recurrent dynamic that's going on that depends upon this deeply structured autonomous behavior that rests upon internal dynamics that are not only modeling the data impressed upon their surface or the blanket states, but they are actively resampling those data by moving. They're moving towards chemical gradients and chemotaxis. So they've gone beyond just being good little models of the kind of world they live in. For example, an oil droplet could, in a panpsychic sense, be construed as a little being that has now perfectly inferred it's a passive, non-living oil drop living in a bowl of water. No problem. But to now equip that oil drop with the ability to go out and test that hypothesis about different states of beings. So it can actually push its surface over there, over there, and test for chemical gradients, or then you start to move to much more lifelike form. This is all fun, theoretically interesting, but it actually is quite important in terms of reflecting what I have seen since the turn of the millennium, which is this move towards an inactive, an embodied understanding of intelligence. And you say you're from machine learning. So what that means, this sort of, the central importance of movement, I think has yet to really hit machine learning. It certainly has now diffused itself throughout robotics, and perhaps you could say certain problems in active vision where you actually have to move the camera to sample this and that. But machine learning of the data mining, deep learning sort, simply hasn't contended with this issue. What it's done, instead of dealing with the movement problem and the active sampling of data, it's just said, we don't need to worry about it, we can see all the data because we've got big data. So we can ignore movement. So that, for me, is an important omission in current machine learning. So current machine learning is much more like the oil drop. Yes, but an oil drop that enjoys exposure to nearly all the data that people ever need to be exposed to, as opposed to the tadpoles swimming out to find the right data. For example, it likes food. That's a good hypothesis. Let's test it out, let's go and move and ingest food, for example, and see what that, is that evidence that I'm the kind of thing that likes this kind of food. So the next natural question, and forgive this question, but if we think of even artificial intelligence systems, which has just painted a beautiful picture of existence and life. So do you ascribe, do you find within this framework a possibility of defining consciousness or exploring the idea of consciousness? Like what self-awareness and expanded to consciousness, yeah, how can we start to think about consciousness within this framework, is it possible? Well, yeah, I think it's possible to think about it, whether you'll get it. Get it, you heard it, it's another question. And again, I'm not sure that I'm licensed to answer that question. I think you'd have to speak to a qualified philosopher to get a definitive answer there. But certainly there's a lot of interest in using not just these ideas, but related ideas from information theory to try and tie down the maths and the calculus and the geometry of consciousness, either in terms of sort of a minimal consciousness, even less than a minimal selfhood. And what I'm talking about is the ability effectively to plan, to have agency. So you could argue that a virus does have a form of agency in virtue of the way that it selectively finds hosts and cells to live in and moves around. But you wouldn't endow it with the capacity to think about planning and moving in a purposeful way where it countenances the future. Whereas you might think an ant's not quite as unconscious as a virus. It certainly seems to have a purpose. It talks to its friends en route during its foraging. It has a different kind of autonomy, which is biotic, but beyond a virus. So there's something about, so there's some line that has to do with the complexity of planning that may contain an answer. I mean, it would be beautiful if we can find a line beyond which we could say a being is conscious. Yes, it will be. These are wonderful lines that we've drawn with existence, life, and consciousness. Yes, it will be very nice. One little wrinkle there, and this is something I've only learned in the past few months, is the philosophical notion of vagueness. So you're saying it would be wonderful to draw a line. I had always assumed that that line at some point would be drawn until about four months ago, and the philosopher taught me about vagueness. So I don't know if you've come across this, but it's a technical concept, and I think most revealingly illustrated with at what point does a pile of sand become a pile? Is it one grain, two grains, three grains, or four grains? So at what point would you draw the line between being a pile of sand and a collection of grains of sand? In the same way, is it right to ask, where would I draw the line between conscious and unconscious and it might be a vague concept? Having said that, I agree with you entirely. I think it's systems that have the ability to plan. So just technically what that means is your inferential self-evidencing, by which I simply mean the dynamics, literally the thermodynamics and gradient flows that underwrite the preservation of your oil droplet-like form, are described as a, can be described as an optimization of log-Bayesian model evidence, your elbow. That self-evidencing must be evidence for a model of what's causing the sensory impressions on the sensory part of your surface or your Markov blanket. If that model is capable of planning, it must include a model of the future consequences of your active states or your action, just planning. So we're now in the game of planning as inference. Now notice what we've made though, we've made quite a big move away from big data and machine learning, because again, it's the consequences of moving. It's the consequences of selecting those data or those data or looking over there. And that tells you immediately that even to be a contender for a conscious artifact or a, is it strong AI or generalized? I don't know what it's called nowadays. Then you've got to have movement in the game. And furthermore, you've got to have a generative model of the sort you might find in say a variational autoencoder that is thinking about the future conditioned upon different courses of action. Now that brings a number of things to the table, which now you start to think, well, those who've got all the right ingredients talk about consciousness. I've now got to select among a number of different courses of action into the future as part of planning. I've now got free will. The act of selecting this course of action or that policy or that policy or that action suddenly makes me into an inference machine, a self-evidencing artifact that now looks as if it's selecting amongst different alternative ways forward as I actively swim here or swim there or look over here, look over there. So I think you've now got to a situation, if there is planning in the mix, you're now getting much closer to that line, if that line were ever to exist. I don't think it gets you quite as far as self-aware though. I think, and then you have to, I think, grapple with the question, how would formally you write down a calculus or a maths of self-awareness? I don't think it's impossible to do, but I think there'll be pressure on you to actually commit to a formal definition of what you mean by self-awareness. I think most people that I know would probably say that a goldfish, a pet fish was not self-aware. They would probably argue about their favorite cat, but would be quite happy to say that their mom was self-aware. So. I mean, but that might very well connect to some level of complexity with planning. It seems like self-awareness is essential for complex planning. Yeah, do you want to take that further? Because I think you're absolutely right. Again, the line is unclear, but it seems like integrating yourself into the world, into your planning is essential for constructing complex plans. Yes, yeah. So mathematically describing that in the same elegant way as you have with the free energy principle may be difficult. Well, yes and no. I don't think that, well, perhaps we should just, can we just go back? That's a very important answer you gave. And I think if I just unpacked it, you'd see the truisms that you've just exposed for us. But let me, sorry. I'm mindful that I didn't answer your question before. Well, what's the free energy principle good for? Is it just a pretty theoretical exercise to explain non-equilibrium steady states? Yes, it is. It does nothing more for you than that. It can be regarded, it's gonna sound very arrogant, but it is of the sort of theory of natural selection or a hypothesis of natural selection. Beautiful, undeniably true, but tells you absolutely nothing about why you have legs and eyes. It tells you nothing about the actual phenotype and it wouldn't allow you to build something. So the free energy principle by itself is as vacuous as most tautological theories. And by tautological, of course, I'm talking to the theory of natural, the survival of the fittest. What's the fittest survival? Why do the cycles, the fitter? It just go around in circles. Yes, and in a sense, the free energy principle has that same deflationary tautology under the hood. It's a characteristic of things that exist and things that exist, why they exist? Because they minimize their free energy. Why they minimize their free energy? Because they exist. And you just keep on going round and round and round. But the practical thing, which you don't get from natural selection, but you could say has now manifest in things like differential evolution or genetic algorithms and MCMC, for example, in machine learning. The practical thing you can get is if it looks as if things that exist are trying to have density dynamics and look as though they're optimizing a variation of free energy. And a variation of free energy has to be a functional of a generative model, a probabilistic description of causes and consequences, causes out there, consequences in the sensorium, on the sensory parts of the Markov blanket. Then it should, in theory, be possible to write down the generative model, work out the gradients, and then cause it to autonomously self-evidence. So you should be able to write down oil droplets. You should be able to create artifacts where you have supplied the objective function that supplies the gradients, that supplies the self-organizing dynamics to non-equilibrium steady state. So there is actually a practical application of the free energy principle when you can write down your required evidence in terms of, well, when you can write down the generative model, that is the thing that has the evidence. The probability of these sensory data or this data, given that model is effectively the thing that the elbow of the variation of free energy bounds or approximates. That means that you can actually write down the model and the kind of thing that you want to engineer, the kind of AGI, artificial general intelligence, that you want to manifest probabilistically. And then you engineer, a lot of hard work, but you would engineer a robot and a computer to perform a gradient descent on that objective function. So it does have a practical implication. Now, why am I wittering on about that? It did seem relevant to, yes. So what kinds of, so the answer to, would it be easy or would it be hard? Well, mathematically it's easy. I've just told you, all you need to do is write down your perfect artifact probabilistically in the form of a probabilistic generative model, probability distribution over the causes and consequences of the world in which this thing is immersed. And then you just engineer a computer and a robot to perform a gradient descent on that objective function. No problem. But of course the big problem is writing down the generative model. So that's where the heavy lifting comes in. So it's the form and the structure of that generative model which basically defines the artifact that you will create or indeed the kind of artifact that has self-awareness. So that's where all the hard work comes. It very much like natural selection doesn't tell you in the slightest why you have eyes. So you have to drill down on the actual phenotype, the actual generative model. So with that in mind, what did you tell me that tells me immediately the kinds of generative models I would have to write down in order to have self-awareness? What you said to me was, I have to have a model that is effectively fit for purpose for this kind of world in which I operate. And if I now make the observation that this kind of world is effectively largely populated by other things like me, i.e. you, then it makes enormous sense that if I can develop a hypothesis that we are similar kinds of creatures, in fact, the same kind of creature, but I am me and you are you, then it becomes again mandated to have a sense of self. So if I live in a world that is constituted by things like me, basically a social world, a community, then it becomes necessary now for me to infer that it's me talking and not you talking. I wouldn't need that if I was on Mars by myself, or if I was in the jungle as a feral child. If there was nothing like me around, there would be no need to have an inference, a hypothesis, ah, yes, it is me that is experiencing or causing these sounds, and it is not you. It's only when there's ambiguity in play induced by the fact that there are others in that world. So I think that the special thing about self-aware artifacts is that they have learned to, or they have acquired, or at least are equipped with, possibly by evolution, generative models that allow for the fact there are lots of copies of things like them around, and therefore they have to work out it's you and not me. That's brilliant. I've never thought of that. I never thought of that, that the purpose of, the really usefulness of consciousness or self-awareness in the context of planning existing in the world is so you can operate with other things like you. And like you could, it doesn't have to necessarily be human. It could be other kind of similar creatures. Absolutely, well, we imbue a lot of our attributes into our pets, don't we? Or we try to make our robots humanoid. And I think there's a deep reason for that, that it's just much easier to read the world if you can make the simplifying assumption that basically you're me, and it's just your turn to talk. I mean, when we talk about planning, when you talk specifically about planning, the highest, if you like, manifestation or realization of that planning is what we're doing now. I mean, the human condition doesn't get any higher than this talking about the philosophy of existence and the conversation. But in that conversation, there is a beautiful art of turn-taking and mutual inference, theory of mind. I have to know when you wanna listen. I have to know when you want to interrupt. I have to make sure that you're online. I have to have a model in my head of your model in your head. That's the highest, the most sophisticated form of generative model, where the generative model actually has a generative model of somebody else's generative model. And I think that, and what we are doing now, evinces the kinds of generative models that would support self-awareness. Because without that, we'd both be talking over each other, or we'd be singing together in a choir, you know? That's not a brilliant analogy, if what I'm trying to say, but, yeah, we wouldn't have this discourse. We wouldn't have it. Yeah, the dance of it, yeah, that's right. As I interrupt, I mean, that's beautifully put. I'll re-listen to this conversation many times. There's so much poetry in this, and mathematics. Let me ask the silliest, or perhaps the biggest question as a last kind of question. We've talked about living in existence, and the objective function under which these objects would operate. What do you think is the objective function of our existence? What's the meaning of life? What do you think is the, for you perhaps, the purpose, the source of fulfillment, the source of meaning for your existence, as one blob in this soup? I'm tempted to answer that, again, as a physicist. I mean, free energy I expect, consequent upon my behavior. So technically, that, you know, and we could get a really interesting conversation about what that comprises in terms of searching for information, resolving uncertainty about the kind of thing that I am. But I suspect that you want a slightly more personal and fun answer, but which can be consistent with that. And I think it's reassuringly simple, and harps back to what you were taught as a child, that you have certain beliefs about the kind of creature and the kind of person you are. And all that self-evidencing means, all that minimizing variational free energy in an inactive and embodied way means is fulfilling the beliefs about what kind of thing you are. And of course, we're all given those scripts, those narratives at a very early age, usually in the form of bedtime stories or fairy stories that I'm a princess, I'm gonna meet a beast who's gonna transform and it's gonna be a prince. So the narratives are all around you, from your parents to the friends, to the society feeds these stories, and then your objective function is to fulfill. Exactly, that narrative that has been encultured by your immediate family, but as you say, also the sort of the culture in which you grew up. And you create for yourself. I mean, again, because of this active inference, this inactive aspect of self-evidencing, not only am I modeling my environment, my econish, my external states out there, but I'm actively changing them all the time. And external states are doing the same back, we're doing it together. So there's a synchrony that means that I'm creating my own culture over different timescales. So the question now is for me being very selfish, what scripts were I given? It basically was a mixture between Einstein and Sherlock Holmes. So I smoke as heavily as possible, try to avoid too much interpersonal contact, enjoy the fantasy that you're a popular scientist who's gonna make a difference in a slightly quirky way. So that's where I grew up. My father was an engineer and loved science and loved sort of things like Sir Arthur Edgars, space, time and gravitation, which was the first understandable version of general relativity. So all the fairy stories I was told as I was growing up were all about these characters. I'm keeping the Hobbit out of this because that does quite fit my narrative. But it's a journey of exploration, I suppose, of sorts. So yeah, I've just grown up to be what I imagine a mild-mannered Sherlock Holmes slash Albert Einstein would do in my shoes. And you did it elegantly and beautifully. Carl, it was a huge honor talking to you today. It was fun. Thank you so much for your time. No, thank you. Appreciate it. Thank you for listening to this conversation with Carl Fristen, and thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars and Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Carl Fristen. Your arm moves because you predict it will, and your motor system seeks to minimize prediction error. Thank you for listening, and hope to see you next time.

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Manolis Kellis: Biology of Disease | Lex Fridman Podcast #133

The following is a conversation with Manolis Kellis, his third time on the podcast. He is a professor at MIT and head of the MIT Computational Biology Group. This time we went deep on the science, biology and genetics. So this is a bit of an experiment. Manolis went back and forth between the basics of biology to the latest state of the art in the research. He's a master at this, so I just sat back and enjoyed the ride. This conversation happened at 7am, so it's yet another podcast episode after an all-nighter for me. And once again, since the universe has a sense of humor, this one was a tough one for my brain to keep up, but I did my best and I never shy away from a good challenge. Quick mention of each sponsor, followed by some thoughts related to the episode. First is SEMrush, the most advanced SEO optimization tool I've ever come across. I don't like looking at numbers, but someone probably should. It helps you make good decisions. Second is Pessimist Archive. They're back. One of my favorite history podcasts on why people resist new things from recorded music to umbrellas to cars, chess, coffee and the elevator. Third is 8sleep, a mattress that cools itself, measures heart rate variability, has an app and has given me yet another reason to look forward to sleep, including the all-important power nap. And finally, BetterHelp, online therapy when you want to face your demons with a licensed professional, not just by doing the David Goggins-like physical challenges like I seem to do on occasion. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that biology in the brain and in the various systems of the body fill me with awe every time I think about how such a chaotic mess coming from its humble origins in the ocean was able to achieve such incredibly complex and robust mechanisms of life that survived despite all the forces of nature that want to destroy it. It is so unlike the computing systems we humans have engineered that it makes me feel that in order to create artificial general intelligence and artificial consciousness, we may have to completely rethink how we engineer computational systems. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars and Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Manolis Kalas. So your group at MIT is trying to understand the molecular basis of human disease. What are some of the biggest challenges in your view? Don't get me started. I mean, understanding human disease is the most complex challenge in modern science. So because human disease is as complex as the human genome, it is as complex as the human brain, and it is in many ways even more complex because the more we understand disease complexity, the more we start understanding genome complexity and epigenome complexity and brain circuitry complexity and immune system complexity and cancer complexity and so on and so forth. So traditionally, human disease was following basic biology. You would basically understand basic biology and model organisms like, you know, mouse and fly and yeast. You would understand sort of mammalian biology and animal biology and eukaryotic biology in sort of progressive layers of complexity, getting closer to human phylogenetically. And you would do perturbation experiments in those species to see if I knock out a gene, what happens? And based on the knocking out of these genes, you would basically then have a way to drive human biology because you would sort of understand the functions of these genes. And then if you find that a human gene, locus, something that you've mapped from human genetics to that gene is related to a particular human disease, you'd say, aha, now I know the function of the gene from the model organisms. I can now go and understand the function of that gene in human. But this is all changing. This is dramatically changed. So that was the old way of doing basic biology. You would start with the animal models, the eukaryotic models, the mammalian models, and then you would go to human. Human genetics has been so transformed in the last decade or two that human genetics is now actually driving the basic biology. There is more genetic mutation information in the human genome than there will ever be in any other species. What do you mean by mutation information? So perturbations is how you understand systems. So an engineer builds systems and then they know how they work from the inside out. A scientist studies systems through perturbations. You basically say, if I poke that balloon, what's going to happen? And I'm going to film it in super high resolution, understand, I don't know, air dynamics or fluid dynamics if it's filled with water, et cetera. So you can then make experimentation by perturbation. And then the scientific process is sort of building models that best fit the data, designing new experiments that best test your models and challenge your models and so on and so forth. That's the same thing with science. Basically, if you're trying to understand biological science, you basically want to do perturbations that then drive the models. So how do these perturbations allow you to understand disease? So if you know that a gene is related to disease, you don't want to just know that it's related to the disease. You want to know what is the disease mechanism because you want to go and intervene. So the way that I like to describe it is that traditionally, epidemiology, which is basically the study of disease, sort of the observational study of disease, has been about correlating one thing with another thing. So if you have a lot of people with liver disease who are also alcoholics, you might say, well, maybe the alcoholism is driving the liver disease, or maybe those who have liver disease self-medicate with alcohol. So the connection could be either way. With genetic epidemiology, it's about correlating changes in the genome with phenotypic differences, and then you know the direction of causality. So if you know that a particular gene is related to the disease, you can basically say, okay, perturbing that gene in mouse causes the mice to have X phenotype. So perturbing that gene in human causes the humans to have the disease. So I can now figure out what are the detailed molecular phenotypes in the human that are related to that organismal phenotype in the disease. So it's all about understanding disease mechanism, understanding what are the pathways, what are the tissues, what are the processes that are associated with the disease so that we know how to intervene. You can then prescribe particular medications that also alter these processes. You can prescribe lifestyle changes that also affect these processes and so on and so forth. That's such a beautiful puzzle to try to solve. Like what kind of perturbations eventually have this ripple effect that leads to disease across the population? And then you study that for animals or mice first, and then see how that might possibly connect to humans. How hard is that puzzle of trying to figure out how little perturbations might lead to in a stable way to a disease? In animals, we make the puzzle simpler because we perturb one gene at a time. That's the beauty of it. It's the power of animal models. You can basically decouple the perturbations. You only do one perturbation and you only do strong perturbations at a time. In human, the puzzle is incredibly complex because, I mean, obviously you don't do human experimentation. You wait for natural selection and natural genetic variation to basically do its own experiments, which it has been doing for hundreds and thousands of years in the human population and for hundreds of thousands of years across the history leading to the human population. So you basically take this natural genetic variation that we all carry within us. Every one of us carries six million perturbations. So I've done six million experiments on you, six million experiments on me, six million experiments on every one of seven billion people on the planet. What's the six million correspond to? Six million unique genetic variants that are segregating in the human population. Every one of us carries millions of polymorphic sites, poly, many, morph, forms. Polymorphic means many forms, variants. That basically means that every one of us has single nucleotide alterations that we have inherited from mom and from dad that basically can be thought of as tiny little perturbations. Most of them don't do anything, but some of them lead to all of the phenotypic differences that we see between us. The reason why two twins are identical is because these variants completely determine the way that I'm going to look at exactly 93 years of age. How happy are you with this kind of data set? Is it large enough of the human population of Earth? Is that too big, too small? Yeah, so is it large enough is a power analysis question. And in every one of our grants we do a power analysis based on what is the effect size that I would like to detect and what is the natural variation in the two forms. So every time you do a perturbation you're asking I'm changing form A into form B. Form A has some natural genetic, some natural phenotypic variation around it and form B has some natural phenotypic variation around it. If those variances are large and the differences between the mean of A and the mean of B are small, then you have very little power. The further the means go apart, that's the effect size, the more power you have. And the smaller the standard deviation, the more power you have. So basically when you're asking is that sufficiently large, certainly not for everything, but we already have enough power for many of the stronger effects in the more tight distributions. So that's a hopeful message that there exists parts of the genome that have a strong effect that has a small variance. That's exactly right. Unfortunately, those perturbations are the basis of disease in many cases. So it's not a hopeful message, sometimes it's a terrible message. It's basically well some people are sick, but if we can figure out what are these contributors to sickness, we can then help make them better and help many other people better who don't carry that exact mutation, but who carry mutations on the same pathways. And that's what we like to call the allelic series of a gene. You basically have many perturbations of the same gene in different people, each with a different frequency in the human population and each with a different effect on the individual that carries them. So you said in the past there would be these small experiments on perturbations and animal models. What is this puzzle solving process look like today? So we basically have something like 7 billion people in the planet and every one of them carries something like 6 million mutations. You basically have an enormous matrix of genotype by phenotype by systematically measuring the phenotype of these individuals. And the traditional way of measuring this phenotype has been to look at one trait at a time. You would gather families and you would sort of paint the pedigrees of a strong effect, what we like to call Mendelian mutation. So a mutation that gets transmitted in a dominant or a recessive but strong effect form, where basically one locus plays a very big role in that disease. And you could then look at carriers versus non-carriers in one family, versus non-carriers in another family, and do that for hundreds, sometimes thousands of families, and then trace these inheritance patterns and then figure out what is the gene that plays that role. Is this the matrix that you're showing in talks or lectures? So that matrix is the input to the stuff that I show in talks. So basically that matrix has traditionally been strong effect genes. What the matrix looks like now is instead of pedigrees, instead of families, you basically have thousands and sometimes hundreds of thousands of unrelated individuals, each with all of their genetic variants and each with their phenotype, for example, height or lipids or whether they're sick or not for a particular trait. That has been the modern view. Instead of going to families, going to unrelated individuals with one phenotype at a time. And what we're doing now as we're maturing in all of these sciences is that we're doing this in the context of large medical systems or enormous cohorts that are very well phenotyped across hundreds of phenotypes, sometimes with our complete electronic health record. So you can now start relating not just one gene segregating one family, not just thousands of variants segregating with one phenotype, but now you can do millions of variants versus hundreds of phenotypes. And as a computer scientist, I mean, deconvolving that matrix, partitioning it into the layers of biology that are associated with every one of these elements is a dream come true. It's like the world's greatest puzzle. And you can now solve that puzzle by throwing in more and more knowledge about the function of different genomic regions and how these functions are changed across tissues and in the context of disease. And that's what my group and many other groups are doing. We're trying to systematically relate this genetic variation with molecular variation at the expression level of the genes, at the epigenomic level of the gene regulatory circuitry, and at the cellular level of what are the functions that are happening in those cells, at the single cell level using single cell profiling, and then relate all that vast amount of knowledge computationally with the thousands of traits that each of these of thousands of variants are perturbing. I mean, this is something we talked about, I think, last time. So there's these effects at different levels that happen. You said at a single cell level, you're trying to see things that happen due to certain perturbations. And then, so it's not just like a puzzle of perturbation and disease. It's perturbation, then effect at a cellular level, then at an organ level, at a body, like how do you disassemble this into like what your group is working on? You're basically taking a bunch of the hard problems in the space. How do you break apart a difficult disease and break it apart into problems that you, into puzzles that you can now start solving? So there's a struggle here. Computer scientists love hard puzzles, and they're like, oh, I want to build a method that just deconvolves the whole thing computationally. And that's very tempting, and it's very appealing, but biologists just like to decouple that complexity experimentally, to just like peel off layers of complexity experimentally. And that's what many of these modern tools that my group and others have both developed and used. The fact that we can now figure out tricks for peeling off these layers of complexity by testing one cell type at a time, or by testing one cell at a time. And you could basically say, what is the effect of this genetic variant associated with Alzheimer's on human brain? Human brain sounds like, oh, it's an organ, of course, just go one organ at a time. But human brain has, of course, dozens of different brain regions. And within each of these brain regions, dozens of different cell types. And every single type of neuron, every single type of glial cell, between astrocytes, oligodendrocytes, microglia, between all of the neural cells and the vascular cells and the immune cells that are co-inhabiting the brain between the different types of excitatory and inhibitory neurons that are sort of interacting with each other between different layers of neurons in the cortical layers, every single one of these has a different type of function to play in cognition, in interaction with the environment, in maintenance of the brain, in energetic needs, in feeding the brain with blood, with oxygen, in clearing out the debris that are resulting from the super high energy production of cognition in humans. So all of these things are basically potentially deconvolvable computationally, but experimentally, you can just do single cell profiling of dozens of regions of the brain across hundreds of individuals, across millions of cells. And then now you have pieces of the puzzle that you can then put back together to understand that complexity. I mean, first of all, I mean, the cells in the human brain are the most, maybe I'm romanticizing it, but cognition seems to be very complicated. So separating into the function, breaking Alzheimer's down to the cellular level seems very challenging. Is that basically you're trying to find a way that some perturbation in genome results in some obvious major dysfunction in the cell? You're trying to find something like that. Exactly. So what does human genetics do? Human genetics basically looks at the whole path from genetic variation all the way to disease. So human genetics has basically taken thousands of Alzheimer's cases and thousands of controls matched for age, for sex, for environmental backgrounds and so on and so forth. And then looked at that map where you're asking what are the individual genetic perturbations and how are they related to all the way to Alzheimer's disease? And that has actually been quite successful. So we now have more than 27 different loci, these are genomic regions that are associated with Alzheimer's at this end to end level. But the moment you sort of break up that very long path into smaller levels, you can basically say from genetics, what are the epigenomic alterations at the level of gene regulatory elements, where that genetic variant perturbs the control region nearby? That effect is much larger. You mean much larger in terms of its down the line impact? It's much larger in terms of the measurable effect. This A versus B variance is actually so much cleanly defined when you go to the shorter branches. Because for one genetic variant to affect Alzheimer's, that's a very long path. That basically means that in the context of millions of these 6 million variants that every one of us carries, that one single nucleotide has a detectable effect all the way to the end. I mean, it's just mind boggling that that's even possible. But indeed, there are such effects. So the hope is, or the most, scientifically speaking, the most effective place where to detect the alteration that results in disease is earlier on in the pipeline, as early as possible. It's a trade-off. If you go very early on in the pipeline, now each of these epigenomic alterations, for example, this enhancer control region is active maybe 50% less, which is a dramatic effect. Now you can ask, well, how much does changing one regulatory region in the genome in one cell type change disease? Well, that path is now long. So if you instead look at expression, the path between genetic variation and the expression of one gene goes through many enhancer regions, and therefore it's a subtler effect at the gene level, but then now you're closer because one gene is acting in the context of only 20,000 other genes, as opposed to one enhancer acting in the context of 2 million other enhancers. So you basically now have genetic, epigenomic, the circuitry, transcriptomic, the gene expression level, and then cellular, where you can basically say, I can measure various properties of those cells. What is the calcium influx rate when I have this genetic variation? What is the synaptic density? What is the electric impulse conductivity? And so on and so forth. So you can measure things along this path to disease, and you can also measure endophenotypes. You can basically measure your brain activity. You can do imaging in the brain. You can basically measure, I don't know, the heart rate, the pulse, the lipids, the amount of blood secreted, and so on and so forth. And then through all of that, you can basically get at the path to causality, the path to disease. Lexis D'Entretene And is there something beyond cellular? So you mentioned lifestyle interventions or changes as a way to, or like, be able to prescribe changes in lifestyle. Like, what about organs? What about, like, the function of the body as a whole? Dr. David Yeah, absolutely. So basically, when you go to your doctor, they always measure, you know, your pulse, they always measure your height, they always measure your weight, you know, your BMI. So basically, these are just very basic variables. But with digital devices nowadays, you can start measuring hundreds of variables for every individual. You can basically also phenotype cognitively through tests, Alzheimer's patients. There are cognitive tests that you can measure, that you typically do for cognitive decline, these mini mental, you know, observations that you have specific questions to. You can think of sort of enlarging the set of cognitive tests. So in the mouse, for example, you do experiments for how do they get out of mazes? How do they find food? Whether they recall a fear, whether they shake in a new environment, and so on and so forth. In the human, you can have much, much richer phenotypes, where you can basically say, not just imaging at the, you know, organ level, but, and all kinds of other activities at the organ level. But you can also do at the organism level, you can do behavioral tests, and how did they do on empathy? How did they do on memory? How did they do on long-term memory versus short-term memory? And so on and so forth. I love how you're calling that phenotype. I guess it is. It is. But like your behavior patterns that might change over a period of a life. It's your ability to remember things, your ability to be, yeah, empathetic or emotionally, or your intelligence, perhaps even. Yeah, but intelligence has hundreds of variables. You can be your math intelligence, your literary intelligence, your puzzle solving intelligence, your logic. It could be like hundreds of things. And all of that, we're able to measure that better and better. And all of that could be connected to the entire pipelines. We used to think of each of these as a single variable, like intelligence. I mean, that's ridiculous. It's basically dozens of different genes that are controlling every single variable. You can basically think of, imagine us in a video game where every one of us has measures of strength, stamina, energy left, and so on and so forth. But you could click on each of those five bars that are just the main bars, and each of those will just give you then hundreds of bars. And you can basically say, okay, great, for my machine learning task, I want someone who, a human who has these particular forms of intelligence. I require now these 20 different things. And then you can combine those things and then relate them to, of course, performance in a particular task. But you can also relate them to genetic variation that might be affecting different parts of the brain. For example, your frontal cortex versus your temporal cortex versus your visual cortex and so on and so forth. So genetic variation that affects expression of genes in different parts of your brain can basically affect your music ability, your auditory ability, your smell, your, just dozens of different phenotypes can be broken down into hundreds of cognitive variables and then relate each of those to thousands of genes that are associated with them. So somebody who loves RPGs, role-playing games, there's too few variables that we can control. So I'm excited if we're in fact living in a simulation, this is a video game, I'm excited by the quality of the video game. The game designer did a hell of a good job, so we're impressed. Oh, I don't know, the sunset last night was a little unrealistic. Yeah, yeah, the graphics. Exactly. Come on, NVIDIA. To zoom back out, we've been talking about the genetic origins of diseases, but I think it's fascinating to talk about what are the most important diseases to understand, and especially as it connects to the things that you're working on. So it's very difficult to think about important diseases to understand. There's many metrics of importance. One is lifestyle impact. I mean, if you look at COVID, the impact on lifestyle has been enormous. So understanding COVID is important because it has impacted the well-being in terms of ability to have a job, ability to have an apartment, ability to go to work, ability to have a mental circle of support, and all of that for millions of Americans, like huge, huge impact. So that's one aspect of importance. So basically mental disorders, Alzheimer's has a huge importance in the well-being of Americans. Whether or not it kills someone, for many, many years, it has a huge impact. So the first measure of importance is just well-being. The impact on the quality of life. Impact on the quality of life, absolutely. The second metric, which is much easier to quantify, is deaths. What is the number one killer? The number one killer is actually heart disease. It is actually killing 650,000 Americans per year. Number two is cancer, with 600,000 Americans. Number three, far, far down the list, is accidents. Every single accident combined. So basically, you read the news, accidents, like there was a huge car crash, all over the news. But the number of deaths? Number three by far, 167,000. Lower respiratory disease, so that's asthma, not being able to breathe, and so forth, 160,000. Alzheimer's, number five, with 120,000. And then stroke, brain aneurysms, and so forth, that's 147,000. Diabetes and metabolic disorders, et cetera, that's 85,000. The flu is 60,000. Suicide, 50,000. And then overdose, et cetera, goes further down the list. So of course, COVID has creeped up to be the number three killer this year, with more than 100,000 Americans, and counting. But if you think about what do we use, what are the most important diseases, you have to understand both the quality of life, and the sheer number of deaths, and just numbers of years lost, if you wish. And each of these diseases you can think of as, and also including terrorist attacks, and school shootings, for example, things which lead to fatalities, you can look at as problems that could be solved. And some problems are harder to solve than others. I mean, that's part of the equation. So maybe if you look at these diseases, if you look at heart disease, or cancer, or Alzheimer's, or just like schizophrenia, and obesity, not necessarily things that kill you, but affect the quality of life, which problems are solvable, which aren't, which are harder to solve, which aren't? I love your question, because it puts it in the context of a global effort, rather than just a local effort. So basically, if you look at the global aspect, exercise and nutrition are two interventions that we can, as a society, make a much better job at. So if you think about sort of the availability of cheap food, it's extremely high in calories, it's extremely detrimental for you, like a lot of processed food, etc. So if we change that equation, and as a society, we made availability of healthy food much, much easier, and charged a burger at McDonald's, the price that it costs on the health system, then people would actually start buying more healthy foods. So basically, that's sort of a societal intervention, if you wish. In the same way, increasing empathy, increasing education, increasing the social framework and support would basically lead to fewer suicides, it would lead to fewer murders, it would lead to fewer deaths overall. So that's something that we as a society can do. You can also think about external factors versus internal factors. So the external factors are basically communicable diseases, like COVID, like the flu, etc. And the internal factors are basically things like cancer and Alzheimer's, where basically your genetics will eventually drive you there. And then of course, with all of these factors, every single disease has both a genetic component and environmental component. So heart disease, huge genetic contribution. Alzheimer's, it's like 60% plus genetic. So I think it's like 79% heritability. So that basically means that genetics alone explains 79% of Alzheimer's incidence. And yes, there's a 21% environmental component, where you could basically enrich your cognitive environment, enrich your social interactions, read more books, learn a foreign language, go running, sort of have a more fulfilling life. All of that will actually decrease Alzheimer's, but there's a limit to how much that can impact because of the huge genetic footprint. So this is fascinating. So each one of these problems have a genetic component and an environment component. And so when there's a genetic component, what can we do about some of these diseases? What have you worked on? What can you say that's in terms of problems that are solvable here or understandable? So my group works on the genetic component, but I would argue that understanding the genetic component can have a huge impact even on the environmental component. Why is that? Because genetics gives us access to mechanism. And if we can alter the mechanism, if we can impact the mechanism, we can perhaps counteract some of the environmental components. So understanding the biological mechanisms leading to disease is extremely important in being able to intervene. But when you can intervene, the analogy that I like to give is, for example, for obesity. Think of it as a giant bathtub of fat. There's basically fat coming in from your diet and there's fat coming out from your exercise. That's an in-out equation and that's the equation that everybody's focusing on. But your metabolism impacts that bathtub. Basically, your metabolism controls the rate at which you're burning energy. It controls the rate at which you're storing energy. And it also teaches you about the various valves that control the input and the output equation. So if we can learn from the genetics, the valves, we can then manipulate those valves. And even if the environment is feeding you a lot of fat and getting a little fat out, you can just poke another hole at the bathtub and just get a lot of the fat out. Yeah, that's fascinating. Yeah, so we're not just passive observers of our genetics. The more we understand, the more we can come up with actual treatments. And I think that's an important aspect to realize when people are thinking about strong effect versus weak effect variants. So some variants have strong effects. We talked about these Mendelian disorders where a single gene has a sufficiently large effect, penetrance, expressivity and so on and so forth, that basically you can trace it in families with cases and not cases, cases and not cases and so on and so forth. But even the, you know, but so these are the genes that everybody says, oh, that's the genes we should go after because that's a strong effect gene. I like to think about it slightly differently. These are the genes where genetic impacts that have a strong effect were tolerated. Because every single time we have a genetic association with disease, it depends on two things. Number one, the obvious one, whether the gene has an impact on the disease. Number two, the more subtle one is whether there is genetic variation standing and circulating and segregating in the human population that impacts that gene. Some genes are so darn important that if you mess with them, even a tiny little amount, that person's dead. So those genes don't have variation. You're not going to find a genetic association if you don't have variation. That doesn't mean that the gene has no role. It simply means that the gene tolerates no mutations. So that's actually a strong signal when there's no variation. That's so fascinating. Exactly. Genes that have very little variation are hugely important. You can actually rank the importance of genes based on how little variation they have. And those genes that have very little variation but no association with disease, that's a very good metric to say, oh, that's probably a developmental gene because we're not good at measuring those phenotypes. So it's genes that you can tell evolution has excluded mutations from, but yet we can't see them associated with anything that we can measure nowadays. It's probably early embryonic lethal. What are all the words you just said? Early embryonic what? Lethal. Meaning that if you don't have that, you'll die. Okay. There's a bunch of stuff that is required for a stable, functional organism across the board for our entire species, I guess. If you look at sperm, it expresses thousands of proteins. Does sperm actually need thousands of proteins? No, but it's probably just testing them. So my speculation is that misfolding of these proteins is an early test for failure. So that out of the millions of sperm that are possible, you select the subset that are just not grossly misfolding thousands of proteins. So it's kind of an assert that this is folded correctly. Correct. Yeah, this just because if this little thing about the folding of a protein isn't correct, that probably means somewhere down the line there's a bigger issue. That's exactly right. So fail fast. So basically, if you look at the mammalian investment in a newborn, that investment is enormous in terms of resources. So mammals have basically evolved mechanisms for fail fast. We're basically in those early months of development. I mean, it's horrendous, of course, at the personal level when you lose your future child. But in some ways, there's so little hope for that child to develop and sort of make it through the remaining months that sort of fail fast is probably a good evolutionary principle. Yeah, from an evolutionary perspective. For mammals. And of course, humans have a lot of medical resources that you can sort of give those children a chance. And, you know, we have so much more success in sort of giving folks who have these strong carrier mutations a chance. But if they're not even making it through the first three months, we're not going to see them. So that's why when we say what are the most important genes to focus on, the ones that have a strong effect mutation or the ones that have a weak effect mutation? Well, you know, the jury might be out because the ones that have a strong effect mutation are basically, you know, not mattering as much. The ones that only have weak effect mutations, by understanding through genetics that they have a weak effect mutation and understanding that they have a causal role on the disease, we can then say, okay, great, evolution has only tolerated a 2% change in that gene. Pharmaceutically, I can go in and induce a 70% change in that gene. And maybe I will poke another hole at the bathtub that was not easy to control in, you know, many of the other sort of strong effect genetic variants. So, okay, so there's this beautiful map of across the population of things that you're saying strong and weak effects, so stuff with a lot of mutations and stuff with little mutations, with no mutations. And you have this map and it lays out the puzzle. Yeah, so when I say strong effect, I mean at the level of individual mutations. So, basically, genes where, so you have to think of first the effect of the gene on the disease. Remember how I was sort of painting that map earlier from genetics all the way to phenotype. That gene may have a strong effect on the disease, but the genetic variant might have a weak effect on the gene. So, basically, when you ask what is the effect of that genetic variant on the disease, it could be that that genetic variant impacts the gene by a lot, and then the gene impacts the disease by a little, or it could be that the genetic variant impacts the gene by a little, and then the gene impacts the disease by a lot. So, what we care about is genes not impact the that impact the disease a lot, but genetics gives us the full equation. And what I would argue is if we couple the genetics with expression variation, to basically ask what genes change by a lot, and which genes correlate with disease by a lot, even if the genetic variance changed them by a little, then those are the best places to intervene. Those are the best places where pharmaceutically, if I have even a modest effect, I will have a strong effect on the disease. Whereas those genetic variants that have a huge effect on the disease, I might not be able to change that gene by this much without affecting all kinds of other things. Interesting. So yeah, okay, so that's what we're looking at. And what have we been able to find in terms of which disease could be helped? Again, don't get me started. This is, we have found so much. Our understanding of disease has changed so dramatically with genetics. I mean, places that we had no idea would be involved. So one of the worst things about my genome is that I have a genetic predisposition to age-related macular degeneration, AMD. So it's a form of blindness that causes you to lose the central part of your vision progressively as you grow older. My increased risk is fairly small. I have an 8% chance. You only have a 6% chance. You, I'm an average. Yeah. By the way, when you say my, you mean literally yours. You know this about you. I know this about me, yeah. Which is kind of, I mean, philosophically speaking, is a pretty powerful thing to live with. Maybe that's, so we agreed to talk again, by the way, for the listeners to where we're gonna try to focus on science today and a little bit of philosophy next time. But it's interesting to think about the more you're able to know about yourself from the genetic information in terms of the diseases, how that changes your own view of life. Yeah, so there's a lot of impact there. And there's something called genetic exceptionalism, which basically thinks of genetics as something very, very different than everything else, as a type of determinism. And let's talk about that next time. So basically- That's a good preview. Yeah. So let's go back to AMD. So basically with AMD, we have no idea what causes AMD. It was a mystery until the genetics were worked out. And now the fact that I know that I have a predisposition allows me to sort of make some life choices, number one. But number two, the genes that lead to that predisposition give us insights as to how does it actually work. And that's a place where genetics gave us something totally unexpected. So there's a complement pathway, which is an immune function pathway that was in most of the loci associated with AMD. And that basically told us that, wow, there's an immune basis to this eye disorder that people had just not expected before. If you look at complement, it was recently also implicated in schizophrenia. And there's a type of microglia that is involved in synaptic pruning. So synapses are the connections between neurons. And in this whole use it or lose it view of mental cognition and other capabilities, you basically have microglia, which are immune cells that are sort of constantly traversing your brain and then pruning neuronal connections, pruning synaptic connections that are not utilized. So in schizophrenia, there's thought to be a change in the pruning that basically if you don't prune your synapses the right way, you will actually have an increased role of schizophrenia. This is something that was completely unexpected for schizophrenia. Of course, we knew it has to do with neurons, but the role of the complement complex, which is also implicated in AMD, which is now also implicated in schizophrenia, was a huge surprise. What's the complement complex? So it's basically a set of genes, the complement genes, that are basically having various immune roles. And as I was saying earlier, our immune system has been co-opted for many different roles across the body. So they actually play many diverse roles. And somehow the immune system is connected to the synaptic pruning process. The process of it. So immune cells were co-opted to prune synapses. How did you figure this out? How does one go about figuring this intricate connection, like pipeline of connections out? Yeah, let me give you another example. So Alzheimer's disease, the first place that you would expect it to act is obviously the brain. So we had basically this roadmap epigenomics consortium view of the human epigenome, the largest map of the human epigenome that has ever been built, across 127 different tissues and samples with dozens of epigenomic marks measured in hundreds of donors. So what we've basically learned through that is that you basically can map what are the active gene regulatory elements for every one of the tissues in the body. And then we connected these gene regulatory active maps of basically what regions of the human genome are turning on in every one of different tissues. We then can go back and say, where are all of the genetic loci that are associated with disease? This is something that my group, I think was the first to do back in 2010 in this Ernst Nature Biotech paper. But basically we were for the first time able to show that specific chromatin states, specific epigenomic states, in that case enhancers, were in fact enriched in disease associated variants. We pushed that further in the Ernst Nature paper a year later, and then in this roadmap epigenomics paper, a few years after that. But basically that matrix that you mentioned earlier was in fact the first time that we could see what genetic traits have genetic variants that are enriched in what tissues in the body. And a lot of that map made complete sense. If you looked at a diversity of immune traits, like allergies and type 1 diabetes and so on and so forth, you basically could see that they were enriching, that the genetic variants associated with those traits were enriched in enhancers, in these gene regulatory elements, active in T cells and B cells and hematopoietic stem cells and so on and so forth. So that basically gave us confirmation in many ways that those immune traits were indeed enriching in immune cells. If you looked at type 2 diabetes, you basically saw an enrichment in only one type of sample, and it was pancreatic islets. And we know that type 2 diabetes sort of stems from the dysregulation of insulin in the beta cells of pancreatic islets. And that sort of was spot on, super precise. If you looked at blood pressure, where would you expect blood pressure to occur? I don't know, maybe in your metabolism, in ways that you process coffee or something like that, maybe in your brain, the way that you stress out and increases your blood pressure, et cetera. What we found is that blood pressure localized specifically in the left ventricle of the heart. So the enhancers of the left ventricle in the heart contain a lot of genetic variants associated with blood pressure. If you look at height, we found an enrichment specifically in embryonic stem cell enhancers. So the genetic variants predisposing you to be taller or shorter are in fact acting in developmental stem cells. Makes complete sense. If you looked at inflammatory bowel disease, you basically found inflammatory, which is immune, and also bowel disease, which is digestive. And indeed we saw a double enrichment, both in the immune cells and in the digestive cells. So that basically told us that, aha, this is acting in both components. There's an immune component to inflammatory bowel disease and there's a digestive component. And the big surprise was for Alzheimer's. We had seven different brain samples. We found zero enrichment in the brain samples for genetic variants associated with Alzheimer's. I mean, this is mind boggling. Our brains were literally hurting. What is going on? And what is going on is that the brain samples are primarily neurons, oligodendrocytes, and astrocytes, in terms of the cell types that make them up. So that basically indicated that genetic variants associated with Alzheimer's were probably not acting in oligodendrocytes, astrocytes, or neurons. So what could they be acting in? Well, the fourth major cell type is actually microglia. Microglia are resident immune cells in your brain. Oh, nice. The immune, oh, wow. And they are CD14+, which is this sort of cell surface markers of those cells. So they're CD14-plus cells, just like macrophages that are circulating in your blood. The microglia are resident monocytes that are basically sitting in your brain. They're tissue-specific monocytes. And every one of your tissues, like your fat, for example, has a lot of macrophages that are resident. And the M1 versus M2 macrophage ratio has a huge role to play in obesity. And so basically, again, these immune cells are everywhere. But basically what we found, through this completely unbiased view of what are the tissues that likely underlie different disorders, we found that Alzheimer's was humongously enriched in microglia, but not at all in the other cell types. So what are we supposed to make that, if you look at the tissues involved, is that simply useful for indication of propensity for disease, or does it give us somehow a pathway of treatment? It's very much the second. If you look at the way to therapeutics, you have to start somewhere. What are you gonna do? You're gonna basically make assays that manipulate those genes and those pathways in those cell types. So before we know the tissue of action, we don't even know where to start. We basically are at a loss. But if you know the tissue of action, and even better, if you know the pathway of action, then you can basically screen your small molecules, not for the gene. You can screen them directly for the pathway. Directly for the pathway in that cell type. So you can basically develop a high throughput multiplexed robotic system for testing the impact of your favorite molecules that you know are safe, efficacious, and sort of hit that particular gene, and so on and so forth. You can basically screen those molecules against either a set of genes that act in that pathway, or on the pathway directly by having a cellular assay. Then you can basically go into mice and do experiments and basically sort of figure out ways to manipulate these processes that allow you to then go back to humans and do a clinical trial that basically says, okay, I was able indeed to reverse these processes in mice. Can I do the same thing in humans? So the knowledge of the tissues gives you the pathway to treatment. But that's not the only part. There are many additional steps to figuring out the mechanism of disease. I mean, so that's really promising. To take a small step back, you've mentioned all these puzzles that were figured out with the Nature paper for, I mean, you've mentioned a ton of diseases, from obesity to Alzheimer's, even schizophrenia, I think you mentioned. What is the actual methodology of figuring this out? So indeed, I mentioned a lot of diseases, and my lab works on a lot of different disorders. And the reason for that is that if you look at the, if you look at biology, it used to be zoology departments and botanology departments and virology departments and so on and so forth. And MIT was one of the first schools to basically create a biology department, like, oh, we're gonna study all of life suddenly. Why was that even a case? Because the advent of DNA and the genome and the central dogma of DNA makes RNA makes protein, in many ways, unified biology. You could suddenly study the process of transcription in viruses or in bacteria and have a huge impact on yeast and fly and maybe even mammals because of this realization of these common underlying processes. And in the same way that DNA unified biology, genetics is unifying disease studies. So you used to have, you used to have, I don't know, cardiovascular disease department and neurological disease department and neurodegeneration department and basically immune and cancer and so on and so forth. And all of these were studied in different labs because it made sense, because basically the first step was understanding how the tissue functions and we kind of knew the tissues involved in cardiovascular disease and so on and so forth. But what's happening with human genetics is that all of that, all of these walls and edifices that we had built are crumbling. And the reason for that is that genetics is in many ways revealing unexpected connections. So suddenly we now have to bring the immunologists to work on Alzheimer's. They were never in the room. They were in another building altogether. The same way for schizophrenia, we now have to sort of worry about all these interconnected aspects. For metabolic disorders, we're finding contributions from brain. So suddenly we have to call the neurologist from the other building and so on and so forth. So in my view, it makes no sense anymore to basically say, oh, I'm a geneticist studying immune disorders. I mean, that's ridiculous because, I mean, of course, in many ways, you still need to sort of focus, but what we're doing is that we're basically saying, we'll go wherever the genetics takes us. And by building these massive resources, by working on our latest maps, now 833 tissues, sort of the next generation of the epigenomics roadmap, which we're now called EpiMap, is 833 different tissues. And using those, we've basically found enrichments in 540 different disorders. Those enrichments are not like, oh, great, you guys work on that and we'll work on this. They're intertwined amazingly. So of course there's a lot of modularity, but there's these enhancers that are sort of broadly active and these disorders that are broadly active. So basically some enhancers are active in all tissues and some disorders are enriching in all tissues. So basically there's these multifactorial and these other class, which I like to call polyfactorial diseases, which are basically lighting up everywhere. And in many ways, it's sort of cutting across these walls that were previously built across these departments. And the polyfactorial ones were probably the previous structure departments wasn't equipped to deal with those. I mean, again, maybe it's a romanticized question, but there's in physics, there's a theory of everything. Do you think it's possible to move towards an almost theory of everything of disease from a genetic perspective? So if this unification continues, is it possible that, like, do you think in those terms, like trying to arrive at a fundamental understanding of how disease emerges, period? That unification is not just foreseeable, it's inevitable. I see it as inevitable. We have to go there. You cannot be a specialist anymore if you're a genomicist. You have to be a specialist in every single disorder. And the reason for that is that the fundamental understanding of the circuitry of the human genome that you need to solve schizophrenia, that fundamental circuitry is hugely important to solve Alzheimer's. And that same circuitry is hugely important to solve metabolic disorders. And that same exact circuitry is hugely important for solving immune disorders and cancer and every single disease. So all of them have the same sub task. And I teach dynamic programming in my class. Dynamic programming is all about sort of not redoing the work. It's reusing the work that you do once. So basically for us to say, oh, great, you guys in the immune building, go solve the fundamental circuitry of everything. And then you guys in the schizophrenia building go solve the fundamental circuitry of everything separately is crazy. So what we need to do is come together and sort of have a circuitry group, the circuitry building that sort of tries to solve the circuitry of everything. And then the immune folks who will apply this knowledge to all of the disorders that are associated with immune dysfunction. And the schizophrenia folks will basically interact with both the immune folks and with the neuronal folks. And all of them will be interacting with the circuitry folks and so on and so forth. So that's sort of the current structure of my group, if you wish. So basically what we're doing is focusing on the fundamental circuitry. But at the same time, we're the users of our own tools by collaborating with many other labs in every one of these disorders that we mentioned. We basically have a heart focus on cardiovascular disease, coronary artery disease, heart failure, and so on and so forth. We have an immune focus on several immune disorders. We have a cancer focus on metastatic melanoma and immunotherapy response. We have a psychiatric disease focus on schizophrenia, autism, PTSD, and other psychiatric disorders. We have an Alzheimer's and neurodegeneration focus on Huntington's disease, ALS, and AD-related disorders like frontotemporal dementia and Lewy body dementia. And of course, a huge focus on Alzheimer's. We have a metabolic focus on the role of exercise and diet and sort of how they're impacting metabolic organs across the body and across many different tissues. And all of them are interfacing with the circuitry. And the reason for that is another computer science principle of eat your own dog food. If everybody ate their own dog food, dog food would taste a lot better. The reason why Microsoft Excel and Word and PowerPoint was so important and so successful is because the employees that were working on them were using them for their day-to-day tasks. You can't just simply build a circuitry and say, here it is guys, take the circuitry, we're done, without being the users of that circuitry because you then go back. And because we span the whole spectrum from profiling the epigenome, using comparative genomics, finding the important nucleotides in the genome, building the basic functional map of what are the genes in the human genome, what are the gene regulatory elements of the human genome. I mean, over the years, we've written a series of papers on how do you find human genes in the first place, using comparative genomics. How do you find the motifs that are the building blocks of gene regulation, using comparative genomics? How do you then find how these motifs come together and act in specific tissues using epigenomics? How do you link regulators to enhancers and enhancers to their target genes using epigenomics and regulatory genomics? So through the years, we've basically built all this infrastructure for understanding what I like to say, every single nucleotide of the human genome and how it acts in every one of the major cell types and tissues of the human body. I mean, this is no small task. This is an enormous task that takes the entire field. And that's something that my group has taken on along with many other groups. And we have also, and that sort of a thing sets my group perhaps apart, we have also worked with specialists in every one of these disorders to basically further our understanding all the way down to disease. And in some cases, collaborating with pharma to go all the way down to therapeutics because of our deep, deep understanding of that basic circuitry and how it allows us to now improve the circuitry, not just treat it as a black box, but basically go and say, okay, we need a better cell type specific wiring that we now have at the tissue specific level. So we're focusing on that because we're understanding the needs from the disease front. So you have a sense of the entire pipeline. I mean, one, maybe you can indulge me, one nice question to ask would be, how do you, from the scientific perspective, go from knowing nothing about the disease to going, you said, to go into the entire pipeline and actually have a drug or a treatment that cures that disease? So that's an enormously long path and an enormously great challenge. And what I'm trying to argue is that it progresses in stages of understanding rather than one gene at a time. The traditional view of biology was you have one postdoc working on this gene and another prostitute working on that gene. And they'll just figure out everything about that gene. And that's their job. What we've realized is how polygenic the diseases are. So we can't have one postdoc per gene anymore. We now have to have these cross-cutting needs. And I'm gonna describe the path to circuitry along those needs. And every single one of these paths, we are now doing in parallel across thousands of genes. So the first step is you have a genetic association and we talked a little bit about sort of the Mendelian path and the polygenic path to that association. So the Mendelian path was looking through families to basically find gene regions and ultimately genes that are underlying particular disorders. The polygenic path is basically looking at unrelated individuals in this giant matrix of genotype by phenotype and then finding hits where a particular variant impacts disease all the way to the end. And then we now have a connection, not between a gene and a disease, but between a genetic region and a disease. And that distinction is not understood by most people. So I'm gonna explain it a little bit more. Why do we not have a connection between a gene and a disease, but we have a connection between a genetic region and a disease? The reason for that is that 93% of genetic variants that are associated with disease don't impact the protein at all. So if you look at the human genome, there's 20,000 genes. There's 3.2 billion nucleotides. Only 1.5% of the genome codes for proteins. The other 98.5% does not code for proteins. If you now look at where are the disease variants located, 93% of them fall in that outside the genes portion. Of course, genes are enriched, but they're only enriched by a factor of three. That means that still 93% of genetic variants fall outside the proteins. Why is that difficult? Why is that a problem? The problem is that when a variant falls outside the gene, you don't know what gene is impacted by that variant. You can't just say, oh, it's near this gene. Let's just connect that variant to the gene. And the reason for that is that the genome circuitry is very often long range. So you basically have that genetic variant that could sit in the intron of one gene. And an intron is sort of the place between the exons that code for proteins. So proteins are split up into exons and introns, and exons and introns are the proteins and every exon codes for a particular subset of amino acids, and together they're spliced together and then make the final protein. So that genetic variant might be sitting in an intron of a gene. It's transcribed with the gene, it's processed and then excised, but it might not impact this gene at all. It might actually impact another gene that's a million nucleotides away. So it's just riding along, even though it has nothing to do with this nearby neighborhood. That's exactly right. Let me give you an example. The strongest genetic association with obesity was discovered in this FTO gene, fat and obesity associated gene. So this FTO gene was studied ad nauseum. People did tons of experiments on it. They figured out that FTO is in fact RNA methylation trans race. It basically, it sort of impacts something that we know, that we call the epitranscriptome, just like the genome can be modified, the transcriptome, the transcripts of the genes can be modified. And we basically said, oh great, that means that epitranscriptomics is hugely involved in obesity because that gene FTO is clearly where the genetic locus is at. My group studied FTO in collaboration with a wonderful team led by Melina Klausnitzer. And what we found is that this FTO locus, even though it is associated with obesity, does not implicate the FTO gene. The genetic variant sits in the first intron of the FTO gene, but it controls two genes, IRX3 and IRX5, that are sitting 1.2 million nucleotides away, several genes away. Oh boy. What am I supposed to feel about that? Because isn't that like super complicated then? So the way that I was introduced at a conference a few years ago was, and here's Manolis Kellis, who wrote the most depressing paper of 2015. And the reason for that is that the entire pharmaceutical industry was so comfortable that there was a single gene in that locus. Because in some loci, you basically have three dozen genes that are all sitting in the same region of association. And you're like, oh gosh, which ones of those is it? But even that question of which ones of those is it, is making the assumption that it is one of those, as opposed to some random gene just far, far away, which is what our paper showed. So basically what our paper showed is that you can't ignore the circuitry. You have to first figure out the circuitry, all of those long range interactions, how every genetic variant impacts the expression of every gene in every tissue imaginable across hundreds of individuals. And then you now have one of the building blocks, not even all of the building blocks, for then going and understanding disease. So okay, so embrace the wholeness of the circuitry. Correct. So back to the question of starting knowing nothing to the disease and going to the treatment. So what are the next steps? So you basically have to first figure out the tissue, and then describe how you figure out the tissue. You figure out the tissue by taking all of these non-coding variants that are sitting outside proteins, and then figuring out what are the epigenomic enrichments. And the reason for that, you know, thankfully, is that there is convergence, that the same processes are impacted in different ways by different loci. And that's a saving grace for our field. The fact that if I look at hundreds of genetic variants associated with Alzheimer's, they localize in a small number of processes. Can you clarify why that's hopeful? So like they show up in the same exact way in the specific set of processes? Yeah, so basically, there's a small number of biological processes that underlie, or at least that play the biggest role in every disorder. So in Alzheimer's, you basically have, you know, maybe 10 different types of processes. One of them is lipid metabolism. One of them is immune cell function. One of them is neuronal energetics. So these are just a small number of processes, but you have multiple lesions, multiple genetic perturbations that are associated with those processes. So if you look at schizophrenia, it's excitatory neuron function, it's inhibitory neuron function, it's synaptic pruning, it's calcium signaling, and so on and so forth. So when you look at disease genetics, you have one hit here and one hit there and one hit there and one hit there, completely different parts of the genome. But it turns out all of those hits are calcium signaling proteins. Oh, cool. You're like, aha, that means that calcium signaling is important. So those people who are focusing on one docus at a time cannot possibly see that picture. You have to become a genomicist. You have to look at the omics, the om, the holistic picture to understand these enrichments. But you mentioned the convergence thing. So whatever the thing associated with the disease shows up. So let me explain convergence. Convergence is such a beautiful concept. So you basically have these four genes that are converging on calcium signaling. So that basically means that they are acting each in their own way, but together in the same process. But now in every one of these loci, you have many enhancers controlling each of those genes. That's another type of convergence where dysregulation of seven different enhancers might all converge on dysregulation of that one gene, which then converges on calcium signaling. And in each one of those enhancers, you might have multiple genetic variants distributed across many different people. Everyone has their own different mutation, but all of these mutations are impacting that enhancer, and all of these enhancers are impacting that gene, and all of these genes are impacting this pathway, and all of these pathways are acting in the same tissue, and all of these tissues are converging together on the same biological process of schizophrenia. And you're saying the saving grace is that that convergence seems to happen for a lot of these diseases. For all of them. Basically that for every single disease that we've looked at, we have found an epigenomic enrichment. How do you do that? You basically have all of the genetic variants associated with the disorder, and then you're asking for all of the enhancers active in a particular tissue. For 540 disorders, we've basically found that indeed there is an enrichment. That basically means that there is commonality, and from the commonality, we can just get insights. So to explain in mathematical terms, we're basically building an empirical prior. We're using a Bayesian approach to basically say, great, all of these variants are equally likely in a particular locus to be important. So in a genetic locus, you basically have a dozen variants that are co-inherited, because the way that inheritance works in the human genome is through all of these recombination events during meiosis. You basically have, you know, you inherit maybe three, chromosome three, for example, in your body. But you also inherit DNA from a father's body, and that DNA comes from all of your Hungarian parents, so that means you have a very hard distressed father. And over time, you have two different children that come from your dad's family tremendously closer to you compared to your mother's. And since you had three kids already, what genomic gene that's caused that time from your mother observed for the previous generation you've had these miscommunication arises in the genetic locus that you have in your body. These breakpoints that happen when chromosomes are lining up are basically ensuring, through these crossover events, they're ensuring that every child cell during the process of meiosis, where you basically have one spermatozoid that basically couples with one ovule to basically create one egg, to basically create a zygote, you basically have half of your genome that comes from that and half your genome that comes from mom, but in order to line them up, you basically have these crossover events. These crossover events are basically leading to co-inheritance of that entire block coming from your maternal grandmother and that entire block coming from your maternal grandfather. Over many generations, these crossover events don't happen randomly. There's a protein called PRDM9 that basically guides the double-stranded breaks and then leads to these crossovers, and that protein has a particular preference to only a small number of hotspots of recombination, which then lead to a small number of breaks between these co-inheritance patterns. So even though there are 6 million variants, there are 6 million loci, this variation is inherited in blocks, and every one of these blocks has like two dozen genetic variants that are all associated. So in the case of FTO, it wasn't just one variant, it was 89 common variants that were all humongously associated with obesity. Which one of those is the important one? Well, if you look at only one locus, you have no idea, but if you look at many loci, you basically say, aha, all of them are enriching in the same epigenomic map. In that particular case, it was mesenchymal stem cells, so these are the progenitor cells that give rise to your brown fat and your white fat. Progenitor is like the early on developmental stem cells? So you start from one zygote, and that's a totipotent cell type, it can do anything. You then, you know, that cell divides, divides, divides, and then every cell division is leading to specialization, where you now have a mesodermal lineage, an ectodermal lineage, an endodermal lineage, that basically leads to different parts of your body. The ectoderm will basically give rise to your skin, ecto means outside, derm is skin, so ectoderm, but it also gives rise to your neurons and your whole brain, so that's a lot of ectoderm. Mesoderm gives rise to your internal organs, including the vasculature and, you know, your muscle and stuff like that. So you basically have this progressive differentiation, and then if you look further, further down that lineage, you basically have one lineage that will give rise to both your muscle and your bone, but also your fat. And if you go further down the lineage of your fat, you basically have your white fat cells, these are the cells that store energy, so when you eat a lot, but you don't exercise too much, there's an excess set of calories, excess energy, what do you do with those? You basically create, you spend a lot of that energy to create these high energy molecules, lipids, which you can then burn when you need them on a rainy day. So that leads to obesity if you don't exercise and if you overeat, because your body's like, oh great, I have all these calories, I'm gonna store them. Ooh, more calories, I'm gonna store them too. Ooh, more calories. And the, you know, 42% of European chromosomes have a predisposition to storing fat, which was selected probably in the food scarcity periods. Like basically as we were exiting Africa, you know, before and during the ice ages, you know, there was probably a selection to those individuals who made it north to basically be able to store energy, you know, a lot more energy. So you basically now have this lineage that is deciding whether you want to store energy in your white fat or burn energy in your beige fat. Turns out that your fat is, you know, like we have such a bad view of fat. Fat is your best friend. Fat can both store all these excess lipids that would be otherwise circulating through your, you know, body and causing damage, but it can also burn calories directly. If you have too much energy, you can just choose to just burn some of that as heat. So basically when you're cold, you're burning energy to basically warm your body up and you're burning all these lipids and you're burning all these calories. So what we basically found is that across the board, genetic variants associated with obesity across many of these regions were all enriched repeatedly in mesenchymal stem cell enhancers. So that gave us a hint as to which of these genetic variants was likely driving this whole association. And we ended up with this one genetic variant called RS1421085. And that genetic variant out of the 89 was the one that we predicted to be causal for the disease. So going back to those steps, first step is figure out the relevant tissue based on the global enrichment. Second step is figure out the causal variant among many variants in this linkage disequilibrium in this co-inherited block between these recombination hotspots, these boundaries of these inherited blocks. That's the second step. The third step is once you know that causal variant, try to figure out what is the motif that is disrupted by that causal variant. Basically, how does it act? Variants don't just disrupt elements, they disrupt the binding of specific regulators. So basically the third step there was how do you find the motif that is responsible, like the gene regulatory word, the building block of gene regulation that is responsible for that dysregulatory event. And the fourth step is finding out what regulator normally binds that motif and is now no longer able to bind. And then once you have the regulator, can you then try to figure out how to, what, after it developed, how to fix it? That's exactly right. You now know how to intervene. You have basically a regulator, you have a gene that you can then perturb. And you say, well, maybe that regulator has a global role in obesity. I can perturb the regulator. Just to clarify, when we say perturb, like on the scale of a human life, can a human being be helped? Of course. Of course. Yeah, I guess understanding is the first step. Exactly. No, no, but perturbed basically means you now develop therapeutics, pharmaceutical therapeutics against that. Or you develop other types of intervention that affect the expression of that gene. What do pharmaceutical therapeutics look like when your understanding's on a genetic level? Yeah. Sorry if it's a dumb question. No, no, no, it's a brilliant question, but I wanna save it for a little bit later when we start talking about therapeutics. Perfect. We've talked about the first four steps. There's two more. So basically the first step is figure out, I mean, the zeroth step, the starting point is the genetics. The first step after that is figure out the tissue of action. The second step is figuring out the nucleotide that is responsible or set of nucleotides. The third step is figure out the motif and the upstream regulator, number four. Number five and six is what are the targets? So number five is great. Now I know the regulator, I know the motif, I know the tissue, and I know the variant. What does it actually do? So you have to now trace it to the biological process and the genes that mediate that biological process. So knowing all of this can now allow you to find the target genes. How? By basically doing perturbation experiments or by looking at the folding of the epigenome or by looking at the genetic impact of that genetic variant on the expression of genes. And we use all three. So let me go through them. Basically, one of them is physical links. This is the folding of the genome onto itself. How do you even figure out the folding? It's a little bit of a tangent, but it's a super awesome technology. Think of the genome as, again, this massive packaging that we talked about of taking two meters worth of DNA and putting it in something that's a million times smaller than two meters worth of DNA, that's a single cell. You basically have this massive packaging and this packaging basically leads to the chromosome being wrapped around in sort of tie-tight ways. In ways, however, that are functionally capable of being reopened and reclosed. So I can then go in and figure out that folding by sort of chopping up the spaghetti soup, putting glue and ligating the segments that were chopped up but nearby each other, and then sequencing through these ligation events to figure out that this region of this chromosome, that region of the chromosome were near each other, that means they were interacting, even though they were far away on the genome itself. So that chopping up, sequencing, and re-gluing is basically giving you folds of the genome that we call- Sorry, can you backtrack? Of course. How does cutting it help you figure out which ones were close in the original folding? So you have a bowl of noodles. Go on. And in that bowl of noodles, some noodles are near each other. So throwing a bunch of glue, you basically freeze the noodles in place, throwing a cutter that chops up the noodles into little pieces, now throwing some ligation enzyme that lets those pieces that were free re-ligate near each other. In some cases, they re-ligate what you had just got, but that's very rare. Most of the time, they will re-ligate in whatever was proximal. You now have glued the red noodle that was crossing the blue noodle to each other. You then reverse the glue, the glue goes away, and you just sequence the heck out of it. Most of the time, you'll find red segment with, you know, red segment, but you can specifically select for ligation events that have happened that were not from the same segment by sort of marking them a particular way, and then selecting those, and then you sequence and you look for red with blue matches of sort of things that were glued that were not immediate proximal to each other. And that reveals the linking of the blue noodle and the red noodle. You're with me so far? Yeah. Good. So we, you know, we've done these experiments. That's the physical. That's the physical. That's step one of the physical. And what the physical revealed is topologically associated domains, basically big blocks of the genome that are topologically, you know, connected together. That's the physical. The second one is the genetic links. It basically says across individuals that have different genetic variants, how are their genes expressed differently? Remember before I was saying that the path between genetics and disease is enormous, but we can break it up to look at the path between genetics and gene expression. So instead of using Alzheimer's as a phenotype, I can now use expression of IRX3 as the phenotype, expression of gene A. And I can look at all of the humans who contain a G at that location and all the humans that contain a T at that location and basically say, wow, turns out that the expression of the gene is higher for the T humans than for the G humans at that location. So that basically gives me a genetic link between a genetic variant, a locus, a region, and the expression of nearby genes. Good on the genetic link? I think so. Awesome. So the third link is the activity link. What's an activity link? It basically says if I look across 833 different epigenomes, whenever this enhancer is active, this gene is active. That gives me an activity link between this region of the DNA and that gene. And then the fourth one is perturbations, where I can go in and blow up that region and see what are the genes that change in expression. Or I can go in and over-activate that region and see what genes change in expression. So I guess that's similar to activity? Yeah, yeah. So that's basically similar to activity. I agree, but it's causal rather than correlational. Again, I'm a little weird. No, no, you're 100% on. It's exactly the same as activity, but perturbation. Where I go and intervene, I basically take a bunch of cells. So you know CRISPR, right? CRISPR is this genome guidance and cutting mechanism. It's what George Gersh likes to call genome vandalism. So you basically are able to- Good one. You can basically take a guide RNA that you put into the CRISPR system, and the CRISPR system will basically use this guide RNA, scan the genome, find wherever there's a match, and then cut the genome. So I digress, but it's a bacterial immune defense system. So basically bacteria are constantly attacked by viruses, but sometimes they win against the viruses, and they chop up these viruses, and remember as a trophy inside their genome, they have these loci, this CRISPR loci, that basically stands for clustered, repeats, interspersed, et cetera. So basically it's an interspersed repeats structure, where basically you have a set of repetitive regions, and then interspersed were these variable segments that were basically matching viruses. So when this was first discovered, it was basically hypothesized that this is probably a bacterial immune system that remembers the trophies of the viruses that it managed to kill. And then the bacteria pass on, you know, they sort of do lateral transfer of DNA, and they pass on these memories. So that the next bacterium says, oh, you killed that guy, when that guy shows up again, I will recognize him. And the CRISPR system was basically evolved as a bacterial adaptive immune response to sense foreigners that should not belong, and to just go and cut their genome. So it's an RNA guided, RNA cutting enzyme, or an RNA guided DNA cutting enzyme. So there's different systems, some of them cut DNA, some of them cut RNA, but all of them remember this sort of viral attack. So what we have done now as a field is, you know, through the work of, you know, Jennifer Doudna, Manuel Carpentier, Fang Zhang, and many others, is co-opted that system of bacterial immune defense as a way to cut genomes. You basically have this guiding system that allows you to use an RNA guide to bring enzymes to cut DNA at a particular locus. That's so fascinating. So this is like already a natural mechanism, a natural tool for cutting that was useful in this particular context. Yeah. And we're like, well, we can use that thing to actually, it's a nice tool that's already in the body. Yeah, yeah. It's not in our body, it's in the bacterial body. It was discovered by the yogurt industry. They were trying to make better yogurts. And they were trying to make their bacteria in their yogurt cultures more resilient to viruses. And they were studying bacteria, and they found that, wow, this CRISPR system is awesome. It allows you to defend against that. And then it was co-opted in mammalian systems that don't use anything like that as a targeting way to basically bring these DNA cutting enzymes to any locus in the genome. Why would you want to cut DNA to do anything? The reason is that our DNA has a DNA repair mechanism, where if a region of the genome gets randomly cut, you will basically scan the genome for anything that matches and sort of use it by homology. So the reason why we're diploid is because we now have a spare copy. As soon as my mom's copy is deactivated, I can use my dad's copy. And somewhere else, if my dad's copy is deactivated, I can use my mom's copy to repair it. So this is called homologous-based repair. So all you have to do is the cutting, and you don't have to do the fixing. That's exactly right. You don't have to do the fixing. Because it's already built in. That's exactly right. But the fixing can be co-opted by throwing in a bunch of homologous segments that instead of having your dad's version, have whatever other version you'd like to use. So you then control the fixing by throwing in a bunch of other stuff. That's exactly right. And that's how you do genome editing. So that's what CRISPR is. That's what CRISPR is. In popular culture, people use the term. I've never, wow, that's brilliant. That's just an awesome explanation. Genome vandalism followed by a bunch of Band-Aids that have the sequence that you'd like. And you can control the choices of Band-Aids. Correct. And of course, there's new generations of CRISPR. There's something that's called prime editing that was sort of very much in the press recently. That basically, instead of sort of making a double-stranded break, which again is genome vandalism, you basically make a single-stranded break. You basically just nick one of the two strands, enabling you to sort of peel off without sort of completely breaking it up, and then repair it locally using a guide that is coupled to your initial RNA that took you to that location. Dumb question, but is CRISPR as awesome and cool as it sounds, I mean, technically speaking, in terms of like as a tool for manipulating our genetics in the positive meaning of the word manipulating? Or is there downsides, drawbacks, in this whole context of therapeutics that we're talking about, or understanding and so on? So when I teach my students about CRISPR, I show them articles with the headline, Genome Editing Tool Revolutionizes Biology. And then I show them the date of these articles, and they're 2004, like five years before CRISPR was invented. And the reason is that they're not talking about CRISPR. They're talking about zinc finger enzymes that are another way to bring these cutters to the genome. It's a very difficult way of sort of designing the right set of zinc finger proteins, the right set of amino acids that will now target a particular long stretch of DNA, because for every location that you want to target, you need to design a particular regulator, a particular protein that will match that region well. There's another technology called talons, which are basically just a different way of using proteins to sort of guide these cutters to a particular location in the genome. These require a massive team of engineers, of biological engineers, to basically design a set of amino acids that will target a particular sequence of your genome. The reason why CRISPR is amazingly, awesomely revolutionary is because instead of having this team of engineers design a new set of proteins for every location that you want to target, you just type it in your computer and you just synthesize an RNA guide. The beauty of CRISPR is not the cutting. It's not the fixing. All of that was there before. It's the guiding. And the only thing that changes is that it makes the guiding easier, by sort of just typing in the RNA sequence, which then allows the system to sort of scan the DNA to find that. So the coding, the engineering of the cutter is easier. Exactly. In terms of SV. That's kind of similar to the story of deep learning versus old school machine learning, is some of the challenging parts are automated. Okay, so, but CRISPR's just one cutting technology. Exactly, exactly. And then there's, that's part of the challenge is an exciting opportunities of the field is to design different cutting technologies. Yeah, yeah. So now, you know, this was a big parenthesis on CRISPR, but now you, you know, when we were talking about perturbations, you basically now have the ability to not just look at correlation between enhancers and genes, but actually go and either destroy that enhancer and see if the gene changes in expression, or you can use the CRISPR targeting system to bring in not vandalism and cutting, but you can couple the CRISPR system with, and the CRISPR system is called usually CRISPR-Cas9 because Cas9 is the protein that will then come and cut. But there's a version of that protein called dead Cas9 where the cutting part is deactivated. So you basically use dCas9, dead Cas9, to bring in an activator or to bring in a repressor. So you can now ask, is this enhancer changing that gene? By taking this modified CRISPR, which is already modified from the bacteria to be used in humans, that you can now modify the Cas9 to be dead Cas9, and you can now further modify to bring in a regulator. And you can basically turn on or turn off that enhancer and then see what is the impact on that gene. So these are the four ways of linking the locus to the target gene. And that's step number five. Okay? Step number five is find the target gene. And step number six is what the heck does that gene do? You basically now go and manipulate that gene to basically see what are the processes that change. And you can basically ask, well, you know, in this particular case, in the FTO locus, we found mesenchymal stem cells that are the progenitors of white fat and brown fat or beige fat. We found the RS1421085 nucleotide variant as the causal variant. We found this large enhancer, this master regulator. I like to call it OB1 for obesity one, like the strongest enhancer associated with it. And OB1 was kind of chubby as the actor. I don't know if you remember him. But... Yeah. So you basically are using this Jedi mind trick to basically find out the... Thank you. The location of the genome that is responsible the enhancer that harbors it, the motif, the upstream regulator, which is ARID5B for AT-rich interacting domain 5B. That's a protein that sort of comes and binds normally. That protein is normally a repressor. It represses the super enhancer, this massive 12,000 nucleotide master regulatory control region. And it turns off IRX3, which is a gene that's 600,000 nucleotides away and IRX5, which is 1.2 million nucleotides away. So those are... And what's the effect of turning them off? That's exactly the next question. So step six is what do these genes actually do? So we then ask, what does IRX3 and RX5 do? The first thing we did is look across individuals for individuals that had higher expression of IRX3 or lower expression of IRX3. And then we looked at the expression of all of the other genes in the genome. And we looked for simply correlation. And we found that IRX3 and RX5 were both correlated positively with lipid metabolism and negatively with mitochondrial biogenesis. You're like, what the heck does that mean? Doesn't sound related to obesity. Not at all, superficially. But lipid metabolism should, because lipids is these high energy molecules that basically store fat. So IRX3 and RX5 are negatively correlated with lipid metabolism. So that basically means that when they turn on, lipid metabolism, or positively, when they turn on, they turn on lipid metabolism. And they're negatively correlated with mitochondrial biogenesis. What do mitochondria do in this whole process? Again, small parenthesis, what are mitochondria? Mitochondria are little organelles. They arose, they only are found in eukaryotes. Euk means good, karyote means nucleus. So truly, like a true nucleus. So eukaryotes have a nucleus. Prokaryotes are before the nucleus. They don't have a nucleus. So eukaryotes have a nucleus. Hmm, compartmentalization. Eukaryotes have also organelles. Some eukaryotes have chloroplasts. These are the plants, they photosynthesize. Some other eukaryotes, like us, have another type of organelle called mitochondria. These arose from an ancient species that we engulfed. This is an endosymbiosis event. Symbiosis, bio means life, sym means together. So symbiotes are things that live together. Endosymbiosis, endo means inside, so endosymbiosis means you live together, holding the other one inside you. So the pre-eukaryotes engulfed an organism that was very good at energy production, and that organism eventually shed most of its genome to now have only 13 genes in the mitochondrial genome. And those 13 genes are all involved in energy production, the electron transport chain. So basically, electrons are these massive, super energy-rich molecules. We basically have these organelles that produce energy, and when your muscle exercises, you basically multiply your mitochondria, you basically sort of use more and more mitochondria, and that's how you get beefed up. So basically, the muscle sort of learns how to generate more energy. So basically, every single time, your muscles will, you know, overnight regenerate and sort of become stronger and amplify their mitochondria and so forth. So what do the mitochondria do? The mitochondria use energy to sort of do any kind of task. When you're thinking, you're using energy. This energy comes from mitochondria. Your neurons have mitochondria all over the place. Basically, this mitochondria can multiply as organelles, and they can be spread along the body of your muscle. Some of your muscle cells have actually multiple nuclei, they're polynucleated, but they also have multiple mitochondria to basically deal with the fact that your muscle is enormous. You can sort of span this super, super long length, and you need energy throughout the length of your muscle. So that's why you have mitochondria throughout the length, and you also need transcription through the length, so you have multiple nuclei as well. So these two processes, lipids store energy. What do mitochondria do? So there's a process known as thermogenesis. Thermo heat, genesis generation. Thermogenesis is generation of heat. Remember that bathtub with the in and out? That's the equation that everybody's focused on. So how much energy do you consume? How much energy do you burn? But in every thermodynamic system, there's three parts to the equation. There's energy in, energy out, and energy lost. Any machine has loss of energy. How do you lose energy? You emanate heat. So heat is energy loss. So there's- Which is where the thermogenesis comes in. Thermogenesis is actually a regulatory process that modulates the third component of the thermodynamic equation. You can basically control thermogenesis explicitly. You can turn on and turn off thermogenesis. And that's when the mitochondria comes into play. Exactly. So RX3 and RX5 turn out to be the master regulators of a process of thermogenesis versus lipogenesis, generation of fat. So RX3 and RX5 in most people burn heat, burn calories as heat. So when you eat too much, just burn it off in your fat cells. So that bathtub has basically a sort of dissipation knob that most people are able to turn on. I am unable to turn that on because I am a homozygous carrier for the mutation that changes a T into a C in the RS1421085 allele, a locus, a SNP. I have the RISC allele twice, from my mom and from my dad. So I'm unable to thermogenize. I'm unable to turn on thermogenesis through RX3 and RX5 because the regulator that normally binds here, RX5B, can no longer bind because it's an AT-rich interacting domain. And as soon as I change the T into a C, it can no longer bind because it's no longer AT-rich. But doesn't that mean that you're able to use the energy more efficiently? You're not generating heat? Or is it- That means I can eat less and get around just fine. Yes. Yeah, so- That's a feature, actually. It's a feature in a food-scarce environment. Yeah, but- If we're all starving, I'm doing great. If we all have access to massive amounts of food, I'm obese, basically. That's taken us through the entire process of then understanding that why mitochondria and then the lipids are both- Exactly. Even though distant are somehow involved. Different sides of the same coin. And you basically choose to store energy or you can choose to burn energy. And that all of that is involved in the puzzle of obesity. And that's what's fascinating, right? Here we are in 2007, discovering the strongest genetic association with obesity and knowing nothing about how it works for almost 10 years. For 10 years, everybody focused on this FTO gene. And they were like, oh, it must have to do something with RNA modification. And it's like, no, it has nothing to do with the function of FTO. It has everything to do with all of these other process. And suddenly, the moment you solve that puzzle, which is a multi-year effort, by the way, a tremendous effort by Melina and many, many others. So this tremendous effort basically led us to recognize this circuitry. You went from having some 89 common variants associated in that region of the DNA, sitting on top of this gene, to knowing the whole circuitry. When you know the circuitry, you can now go crazy. You can now start intervening at every level. You can start intervening at the RX5B level. You can start intervening with CRISPR-Cas9 at the single SNP level. You can start intervening at RX3 and RX5, directly there. You can start intervening at the thermogenesis level because you know the pathway. You can start intervening at the differentiation level, where the decision to make either white fat or beige fat, the energy-burning beige fat, is made developmentally in the first three days of differentiation of your adipocytes. So as they're differentiating, you basically can choose to make fat-burning machines or fat-storing machines. And sort of, that's how you populate your fat. You basically can now go in pharmaceutically and do all of that. And in our paper, we actually did all of that. We went in and manipulated every single aspect. At the nucleotide level, we use CRISPR-Cas9 genome editing to basically take primary adipocytes from risk and non-risk individuals and show that by editing that one nucleotide out of 3.2 billion nucleotides in the human genome, you could then flip between an obese phenotype and a lean phenotype like a switch. You can basically take micelles that are non-thermogenizing and just flip into thermogenizing cells by changing one nucleotide. It's mind-boggling. It's so inspiring that this puzzle could be solved in this way, and it feels within reach to then be able to crack the problem of some of these diseases. What are, so it's 2007 you mentioned, what are the technologies, the tools that came along that made this possible? And what are you excited about, maybe if we just look at the buffet of things that you've kind of mentioned. Is there, what's involved? What should we be excited about? What are you excited about? I love that question because there's so much ahead of us. There's so, so much. There's, so basically solving that one locus required massive amounts of knowledge that we have been building across the years through the epigenome, through the comparative genomics to find out the causal variant and the controller regulatory motif through the conserved circuitry. It required knowing this regulatory genomic wiring. It required high C of the sort of topologically associated domains to basically find this long range interaction. It required EQTLs of this sort of genetic perturbation of these intermediate gene phenotypes. It required all of the arsenal of tools that I've been describing was put together for one locus. And this was a massive team effort, huge investment in time, energy, money, effort, intellectual, everything. You're referring to, I'm sorry, just for the obesity one. Yeah, this one paper. This one single paper. This one single locus. I like to say that this is a paper about one nucleotide in the human genome, about one bit of information, C versus T in the human genome. That's one bit of information and we have 3.2 billion nucleotides to go through. So how do you do that systematically? I am so excited about the next phase of research because the technologies that my group and many other groups have developed allows us to now do this systematically, not just one locus at a time, but thousands of loci at a time. So let me describe some of these technologies. The first one is automation and robotics. So basically, we talked about how you can take all of these molecules into a single locus and see which of these molecules are targeting each of these genes and what do they do. So you can basically now screen through millions of molecules, through thousands and thousands and thousands of plates, each of which has thousands and thousands and thousands of molecules, every single time testing all of these genes and asking which of these molecules perturb these genes. So that's technology number one, automation and robotics. Technology number two is parallel readouts. So instead of perturbing one locus and then asking if I use CRISPR-Cas9 on this enhancer to basically use dCas9 to turn on or turn off the enhancer, or if I use CRISPR-Cas9 on the SNP to basically change that one SNP at a time, then what happens? But we have 120,000 disease-associated SNPs that we wanna test. We don't wanna spend 120,000 years doing it. So what do we do? We basically develop this technology for massively parallel reporter assays, MPRA. So in collaboration with Tarjan Mikkelsen, Eric Lander, I mean, Jason Dury's group has done a lot of that. So there's a lot of groups that basically have developed technologies for testing 10,000 genetic variants at a time. How do you do that? You know, we talked about microarray technology, the ability to synthesize these huge microarrays that allow you to do all kinds of things like measure gene expression by hybridization, by measuring the genotype of a person, by looking at hybridization with one version with a T versus the other version with a C, and then sort of figuring out that I am a risk carrier for obesity based on these hybridization, differential hybridization in my genome that says, oh, you seem to only have this allele or you seem to have that allele. Microarrays can also be used to systematically synthesize small fragments of DNA. So you can basically synthesize these 150 nucleotide long fragments across 450,000 spots at a time. You can now take the result of that synthesis, which basically works through all of these sort of layers of adding one nucleotide at a time, you can basically just type it into your computer and order it, and you can basically order 10,000 or 100,000 of these small DNA segments at a time. And that's where awesome molecular biology comes in. You can basically take all these segments, have a common start and end barcode or sort of ligator, like just like pieces of a puzzle, you can make the same end piece and the same start piece for all of them. And you can now use plasmids, which are these extra chromosomal, small DNA circular segments that are basically inhabiting all our genomes. We basically have plasmids floating around. I mean, bacteria use plasmids for transferring DNA, and that's where they put a lot of antibiotic resistance genes. So they can easily transfer them from one bacterium to the other. So one bacterium evolves a gene to be resistant to a particular antibiotic. It basically says to all its friends, hey, here's that sort of DNA piece. We can now co-opt these plasmids into human cells. We can basically make a human cell culture and add plasmids to that human cell culture that contain the things that you want to test. You now have this library of 450,000 elements. You can insert them each into the common plasmid and then test them in millions of cells in parallel. And the common plasmid is all the same before you add it. Exactly, the rest of the plasmid is the same. So it's called an epizomal reporter assay. Epizome means not inside the genome, it's sort of outside the chromosomes. So it's an epizomal assay that allows you to have a variable region where you basically test 10,000 different enhancers, and you have a common region which basically has the same reporter gene. You now can do some very cool molecular biology. You can basically take the 450,000 elements that you've generated, and you have a piece of the puzzle here, piece of the puzzle here, which is identical, so they're compatible with that plasmid. You can chop them up in the middle to separate a barcode reporter from the enhancer, and in the middle, put the same gene, again, using the same pieces of the puzzle. You now can have a barcode readout of what is the impact of 10,000 different versions of an enhancer on gene expression. So we're not doing one experiment, we're doing 10,000 experiments. And those 10,000 can be 5,000 of different loci, and each of them in two versions, risk or non-risk. I can now test tens of thousands. These are little hypotheses. Exactly. And then you can do 10,000. You can test 10,000 hypotheses at once. How hard is it to generate those 10,000? Trivial, trivial. But is it biology? No, no, generating the 10,000 is trivial because you basically add, it's by technology. You basically have these arrays that add one nucleotide at a time at every spot. Oh, and so it's printing, and so you're able to control. Yeah. Super costly, is it? 10,000 bucks. Oh, so this is in millions? 10,000 bucks for 10,000 experiments? Sounds like the right, you know. I mean, so that's super, that's exciting because you don't have to do one thing at a time. You can now use that technology, these massively parallel reporter assays, to test 10,000 locations at a time. We've made multiple modifications to that technology. One was sharper MPRA, which stands for, you know, basically getting a higher resolution view by tiling these elements. So you can see where along the region of control are they acting. And we made another modification called Hydra for high, you know, definition, regulatory annotation or something like that, which basically allows you to test 7 million of these at a time by sort of cutting them directly from the DNA. So instead of synthesizing, which basically has the limit of 450,000 that you can synthesize at a time, we basically said, hey, if we want to test all accessible regions of the genome, let's just do an experiment that cuts accessible regions. Let's take those accessible regions, put them all with the same end joints of the puzzles, and then now use those to create a much, much larger, much, much larger array of things that you can test. And then tiling all of these regions, you can then pinpoint what are the driver nucleotides, what are the elements, how are they acting across 7 million experiments at a time. So basically this is all the same family of technology where you're basically using these parallel readouts of the barcodes. And then, you know, to do this, we used a technology called StarSeq for self-transcribing reporter assays, a technology developed by Alex Stark, my former postdoc, who's now a PI over in Vienna. So we basically coupled the StarSeq, the self-transcribing reporters, where the enhancer can be part of the gene itself. So instead of having a separate barcode, that enhancer basically acts to turn on the gene and is transcribed as part of the gene. So you don't have to have the two separate parts. Exactly, so you can just read them directly. So there's a constant improvements in this whole process. By the way, generating all these options, is it basically brute force? How much human intuition is- Oh gosh, of course it's human intuition and human creativity and incorporating all of the input data sets. Because again, the genome is enormous, 3.2 billion. You don't want to test that. Instead, you basically use all of these tools that I've talked about already. You generate your top favorite 10,000 hypotheses, and then you go and test all 10,000. And then from what comes out, you can then go to the next step. So that's technology number two. So technology number one is robotics, automation, where you have thousands of wells and you constantly test them. The second technology is instead of having wells, you have these massively parallel readouts in sort of these pooled assays. The third technology is coupling CRISPR perturbations with these single cell RNA readouts. So let me make another parenthesis here to describe now single cell RNA sequencing. So what does single cell RNA sequencing mean? So RNA sequencing is what has been traditionally used, or well, traditionally, the last 20 years, ever since the advent of next generation sequencing. So basically before, RNA expression profiling was based on these microarrays. The next technology after that was based on sequencing. So you chop up your RNA and you just sequence small molecules, just like you would sequence a genome, basically reverse transcribe the small RNAs into DNA, and you sequence that DNA in order to get the number of sequencing reads corresponding to the expression level of every gene in the genome. You now have RNA sequencing. How do you go to single cell RNA sequencing? That technology also went through stages of evolution. The first was microfluidics. You basically had these, or even chambers, you basically had these ways of isolating individual cells, putting them into a well for every one of these cells. So you have 384 well plates and you now do 384 parallel reactions to measure the expression of 384 cells. That sounds amazing, and it was amazing, but we wanna do a million cells. How do you go from these wells to a million cells? You can't. So what the next technology was after that is instead of using a well for every reaction, you now use a lipid droplet for every reaction. So you use micro droplets as reaction chambers to basically amplify RNA. So here's the idea. You basically have microfluidics where you basically have every single cell coming down one tube in your microfluidics and you have little bubbles getting created in the other way with specifical primers that mark every cell with its own barcode. You basically couple the two and you end up with little bubbles that have a cell and tons of markers for that cell. You now mark up all of the RNA for that one cell with the same exact barcode. And you then lyse all of the droplets and you sequence the heck out of that. And you have for every RNA molecule a unique identifier that tells you what cell was it on. That is such good engineering, microfluidics, and using some kind of primer to put a label on the thing. I mean, you're making it sound easy. I assume it's quite a challenge. It's beautiful, right? But it's gorgeous, yeah. So there's the next generation. That's great, great engineering, yeah. So that's the second generation. Next generation is, forget the microfluidics altogether. Just use big bottles. How can you possibly do that with big bottles? So here's the idea. You dissociate all of your cells or all of your nuclei from complex cells like brain cells that are very long and sticky, so you can't do that. So if you have blood cells or if you have neuronal nuclei or brain nuclei, you can basically dissociate, let's say, a million cells. You now want to add a unique barcode, a unique barcode in each one of a million cells using only big bottles. How can you possibly do that? Sounds crazy, but here's the idea. You use 100 of these bottles. You randomly shuffle all your million cells and you throw them into those 100 bottles, randomly, completely randomly. You add one barcode out of 100 to every one of the cells. You then, you now take them all out. You shuffle them again and you throw them again into the same 100 bottles, but now in a different randomization. And you add a second barcode. So every cell now has two barcodes. You take them out again, you shuffle them and you throw them back in. Another third barcode is adding randomly from the same 100 barcodes. You've now labeled every cell probabilistically based on the unique path that it took of which of 100 bottles did it go for the first time, which of 100 bottles the second time, and which of 100 bottles the third time. 100 times 100 times 100 is a million unique barcodes in every single one of these cells without ever using microfluidics. It's very clever. It's beautiful, right? From a computer science perspective, that's very clever. Yeah. So you now have the single cell sequencing technology. You can use the wells, you can use the bubbles, or you can use the bottles. And you have ways- The bubbles still sound pretty damn cool. The bubbles are awesome. And that's basically the main technology that we're using. So the bubbles is the main technology. So there are kits now that companies just sell to basically carry out single cell RNA sequencing that you can basically, for $2,000, you can basically get 10,000 cells from one sample. And for every one of those cells, you basically have the transcription of thousands of genes. And, you know, of course, the data for any one cell is noisy, but being computer scientists, we can aggregate the data from all of the cells together across thousands of individuals together to basically make very robust inferences. Okay? So the third technology is basically single cell RNA sequencing that allows you to now start asking not just what is the brain expression level difference of that genetic variant, but what is the expression difference of that one genetic variant across every single subtype of brain cell? How is the variance changing? You can't just, you know, with a brain sample, you can just ask about the mean. What is the average expression? If I instead have 3,000 cells that are neurons, I can ask not just what is the mean, not just what is the neuronal expression, I can say for layer five excitatory neurons, of which I have, I don't know, 300 cells, what is the variance that this genetic variant has? So suddenly it's amazingly more powerful. I can basically start asking about this middle layer of gene expression at unprecedented levels. And when you look at the average, it washes out some potentially important signal that corresponds to ultimately the disease. Completely. Yeah. So I can do that at the RNA level, but I can also do that at the DNA level for the epigenome. So remember how before I was telling you about all this technology that we're using to probe the epigenome? One of them is DNA accessibility. So what we're doing in my lab is that from the same dissociation of, say, a brain sample, where you now have all these tens of thousands of cells floating around, you basically take half of them to do RNA profiling, and the other half to do epigenome profiling, both at the single cell level. So that allows you to now figure out what are the millions of DNA enhancers that are accessible in every one of tens of thousands of cells. And computationally, we can now take the RNA and the DNA readouts and group them together to basically figure out how is every enhancer related to every gene. And remember these sort of enhancer gene linking that we were doing across 833 samples? 833 is awesome, don't get me wrong, but 10 million is way more awesome. So we can now look at correlated activity across 2.3 million enhancers and 20,000 genes in each of millions of cells to basically start piecing together the regulatory circuitry of every single type of neuron, every single type of astrocytes, oligodendrocytes, microglial cell inside the brains of 1,500 individuals that we've sampled across multiple different brain regions, across both DNA and RNA. So that's the dataset that my team generated last year alone. So in one year, we've basically generated 10 million cells from human brain across a dozen different disorders, across schizophrenia, Alzheimer's, frontotemporal dementia, Lewy body dementia, ALS, Huntington's disease, post-traumatic stress disorder, autism, bipolar disorder, healthy aging, et cetera. So it's possible that even just within that dataset lie a lot of keys to understanding these diseases and then be able to directly lead to then treatment. Correct, correct. So basically we are now- Motivating. Yeah, so our computational team is in heaven right now and we're looking for people. I mean, if you have listened to our- Super smart, super smart. So this is a very interesting kind of side question. How much of this is biology? How much of this is computation? So you have the computational biology group, but how much of, should you be comfortable with biology to be able to solve some of these problems? If you just find, if you put several of the hats that you wear on, fundamentally, are you thinking like a computer scientist here? You have to. This is the only way. As I said, we are the descendants of the first digital computer. We're trying to understand the digital computer. We're trying to understand the circuitry, the logic of this digital core computer and all of these analog layers surrounding it. So the case that I've been making is that you cannot think one gene at a time. The traditional biology is dead. There's no way. You cannot solve disease with traditional biology. You need it as a component. Once you figured out RX3 and RX5, you now can then say, hey, have you guys worked on those genes with your single gene approach? We'd love to know everything you know. And if you haven't, we now know how important these genes are. Let's now launch a single gene program to dissect them and understand them. But you cannot use that as a way to dissect disease. You have to think genomically. You have to think from the global perspective and you have to build these circuits systematically. So we need numbers of computer scientists who are interested and willing to dive into these data, you know, fully, fully in and sort of extract meaning. We need computer science people who can understand sort of machine learning and inference and sort of, you know, decouple these matrices, come up with super smart ways of sort of dissecting them. But we also need computer scientists who understand biology, who are able to design the next generation of experiments. Because many of these experiments, no one in their right mind would design them without thinking of the analytical approach that you would use to deconvolve the data afterwards. Because it's massive amounts of ridiculously noisy data. And if you don't have the computational pipeline in your head before you even design the experiment, you would never design the experiment that way. That's brilliant, Phil. So in designing the experiment, you have to see the entirety of the computational pipeline. That drives the design. That even drives the necessity for that design. Basically, you know, if you didn't have a computer scientist way of thinking, you would never design these hugely combinatorial, massively parallel experiments. So that's why you need interdisciplinary teams. You need teams. And I wanna sort of clarify that, what do we mean by computational biology group? The focus is not on computational, the focus is on the biology. So we are a biology group. What type of biology? Computational biology. That's the type of biology that uses the whole genome. That's the type of biology that designs experiments, genomic experiments, that can only be interpreted in the context of the whole genome. Right, so it's philosophically looking at biology as a computer. Correct, correct. So which is, in the context of the history of biology, is a big transformation. Yeah, yeah. You can think of the name as, what do we do? Only computation, that's not true. But how do we study it? Only computationally, that is true. So all of these single cell sequencing can now be coupled with the technology that we talked about earlier for perturbation. So here's the crazy thing. Instead of using these wells and these robotic systems for doing one drug at a time, or for perturbing one gene at a time in thousands of wells, you can now do this using a pool of cells and single cell RNA sequencing. How? You basically can take these perturbations using CRISPR, and instead of using a single guide RNA, you can use a library of guide RNAs generated exactly the same way using this array technology. So you synthesize a thousand different guide RNAs. You now take each of these guide RNAs and you insert them in a pool of cells where every cell gets one perturbation. And you use CRISPR editing or CRISPR, so with either CRISPR-Cas9 to edit the genome with these thousand perturbations, or with the activation or with the repression. And you now can have a single cell readout where every single cell has received one of these modifications. And you can now, in massively parallel ways, couple the perturbation and the readout in a single experiment. How are you tracking which perturbations each cell received? So there's ways of doing that, but basically one way is to make that perturbation an expressible vector, so that part of your RNA reading is actually that perturbation itself. So you can basically put it in an expressible part, so you can self-drive it. So the point that I wanna get across is that the sky's the limit. You basically have these tools, these building blocks of molecular biology. You have these massive data sets of computational biology. You have this huge ability to sort of use machine learning and statistical methods and linear algebra to sort of reduce the dimensionality of all these massive data sets. And then you end up with a series of actionable targets that you can then couple with pharma and just go after systematically. So the ability to sort of bring genetics to the epigenomics, to the transcriptomics, to the cellular readouts using these sort of high-throughput perturbation technologies that I'm talking about, and ultimately to the organismal through the electronic health record endophenotypes, and ultimately the disease battery of assays at the cognitive level, at the physiological level, and every other level. There is no better or more exciting field, in my view, to be a computer scientist then or to be a scientist in period. Basically, this confluence of technologies, of computation, of data, of insights, and of tools for manipulation is unprecedented in human history. And I think this is what's shaping the next century to really be a transformative century for our species and for our planet. So you think the 21st century will be remembered for the big leaps in understanding and alleviation of biology? If you look at the path between discovery and therapeutics, it's been on the order of 50 years. It's been shortened to 40, 30, 20, and now it's on the order of 10 years. But the huge number of technologies that are going on right now for discovery will result undoubtedly in the most dramatic manipulation of human biology that we've ever seen in the history of humanity in the next few years. Do you think we might be able to cure some of the disease that we started this conversation with? Absolutely, absolutely. It's only a matter of time. Basically, the complexity is enormous, and I don't want to underestimate the complexity. But the number of insights is unprecedented, and the ability to manipulate is unprecedented, and the ability to deliver these small molecules and other non-traditional medicine perturbations, there's a lot of sort of new, there's a new generation of perturbations that you can use at the DNA level, at the RNA level, at the micro RNA level, at the epigenomic level. There's a battery of new generations of perturbations. If you couple that with cell type identifiers that can basically sense when you are in the right cell based on the specific combination, and then turn on that intervention for that cell, you can now think of combinatorial interventions, where you can basically sort of feed a synthetic biology construct to someone that will basically do different things in different cells. So basically for cancer, this is one of the therapeutics that our collaborator Ron Weiss is using to basically start sort of engineering these circuits that will use micro RNA sensors of the environment to sort of know if you're in a tumor cell, or if you're in an immune cell, or if you're in a stromal cell, and so on and so forth, and basically turn on particular interventions there. You can sort of create constructs that are tuned to only the liver cells, or only the heart cells, or only the brain cells, and then have these new generations of therapeutics coupled with this immense amount of knowledge on the sort of which targets to choose and what biological processes to measure, and how to intervene. My view is that disease is gonna be fundamentally altered and alleviated as we go forward. Next time we talk, we'll talk about the philosophical implications of that and the effect of life, but let's stick to biology for just a little longer. We did pretty good today, we stuck to the science. What are you excited in terms of the future of this field, the technologies, in your own group, in your own mind, you're leading the world at MIT in the science and the engineering of this work, so what are you excited about here? I could not be more excited. We are one of many, many teams who are working on this. In my team, the most exciting parts are many-fold. So basically, we've now assembled these battery of technologies, we've assembled these massive, massive data sets, and now we're really sort of in the stage of our team's path of generating disease insights. So we are simultaneously working on a paper on schizophrenia right now, that is basically using the single-cell profiling technologies, using this editing and manipulation technologies to basically show how the master regulators underlying changes in the brain that are sort of found in schizophrenia are in fact affecting excitatory neurons and inhibitory neurons in pathways that are active both in synaptic pruning, but also in early development. We've basically found this set of four regulators that are connecting these two processes that were previously separate in schizophrenia in sort of having a sort of more unified view across those two sides. The second one is in the area of metabolism. We basically now have a beautiful collaboration with the Goodyear Lab that's basically looking at multi-tissue perturbations in six or seven different tissues across the body in the context of exercise and in the context of nutritional interventions using both mouse and human, where we can basically see what are the cell-to-cell communications that are changing across them. And what we're finding is this immense role of both immune cells as well as adipocyte stem cells in sort of reshaping that circuitry of all of these different tissues, and that's sort of painting to a new path for therapeutical intervention there. In Alzheimer's, it's this huge focus on microglia, and now we're discovering different classes of microglial cells that are basically either synaptic or immune. And these are playing vastly different roles in Alzheimer's versus in schizophrenia. And what we're finding is this immense complexity as you go further and further down of how, in fact, there's 10 different types of microglia, each with their own sort of expression programs. We used to think of them as, oh, yeah, they're microglia, but in fact, now we're realizing just even in that sort of least abundant of cell types, there's this incredible diversity there. The differences between brain regions is another sort of major, major insight. Again, one would think that, oh, astrocytes are astrocytes no matter where they are, but no, there's incredible region-specific differences in the expression patterns of all of the major brain cell types across different brain regions. So basically there's the neocortical regions that are sort of the recent innovation that makes us so different from all other species. There's the sort of reptilian brain sort of regions that are sort of much more, very extremely distinct. There's the cerebellum. Each of those basically is associated in a different way with disease. And what we're doing now is looking into pseudotemporal models for how disease progresses across different regions of the brain. If you look at Alzheimer's, it basically starts in this small region called the entorhinal cortex, and then it spreads through the brain, and through the hippocampus, and ultimately affecting the neocortex. And with every brain region that it hits, it basically has a different impact on the cognitive and memory aspects, orientation, short-term memory, long-term memory, et cetera, which is dramatically affecting the cognitive path that the individuals go through. So what we're doing now is creating this computational model for ordering the cells and the regions and the individuals according to their ability to predict Alzheimer's disease. So we can have a cell-level predictor of pathology that allows us to now create a temporal time course that tells us when every gene turns on along this pathology progression, and then trace that across regions and pathological measures that are region-specific, but also cognitive measures, and so on and so forth. So that allows us to now sort of, for the first time, look at can we actually do early intervention for Alzheimer's, where we know that the disease starts manifesting for 10 years before you actually have your first cognitive loss? Can we start seeing that path to build new diagnostics, new prognostics, new biomarkers for this sort of early intervention in Alzheimer's? The other aspect that we're looking at is mosaicism. We talked about the common variants and the rare variants, but in addition to those rare variants, as your initial cell that forms the zygote divides and divides and divides, with every cell division, there are additional mutations that are happening. So what you end up with is your brain being a mosaic of multiple different types of genetic underpinnings. Some cells contain a mutation that other cells don't have. So every human has the common variants that all of us carry to some degree, the rare variants that your immediate tree of the human species carries, and then there's the somatic variant, which is the tree that happened after the zygote, that sort of forms your own body. So these somatic alterations is something that has been previously inaccessible to study in human post-mortem samples. But right now, with the advent of single-cell RNA sequencing, in this particular case, we're using the well-based sequencing, which is much more expensive, but gives you a lot richer information about each of those transcripts. So we're using now that richer information to infer mutations that have happened in each of the thousands of genes that sort of are active in these cells, and then understand how the genome relates to the function, this genotype-phenotype relationship that we usually build in GWAS, in genome-wide association studies, between genetic variation and disease. We're now building that at the cell level, where for every cell, we can relate the unique specific genome of that cell with the expression patterns of that cell, and the predicted function, using these predictive models that I mentioned before, on dysregulation for cognition, for pathology in Alzheimer's, at the cell level. And what we're finding is that the genes that are altered and the genetic regions that are altered in common variants versus rare variants versus somatic variants are actually very different from each other. The somatic variants are pointing to neuronal energetics, neuronal energetics, and oligodendrocyte functions that are not visible in the genetic regions that you find for the common variants, probably because they have too strong of an effect that evolution is just not tolerating them on the common side of the allele frequency spectrum. So the somatic one, that's the variation that happens after the zygote, after a U individual. I mean, this is a dumb question, but there's mutation and variation, I guess, that happens there, and you're saying that through this, if we focus in on individual cells, we're able to detect the story that's interesting there, and that might be a very unique kind of important variability that arises for, you said neuronal or something that would sound- Energetics. Energetics, that's a cool term. So, I mean, the metabolism of humans is dramatically altered from that of nearby species. We talked about that last time, that basically we are able to consume meat that is incredibly energy-rich, and that allows us to sort of have functions that are meeting this humongous brain that we have. Basically, on one hand, every one of our brain cells is much more energy-efficient than our neighbors, than our relatives. Number two, we have way more of these cells. And number three, we have this new diet that allows us to now feed all these needs. That basically creates a massive amount of damage, oxidative damage, from this huge, super-powered factory of ideas and thoughts that we carry in our skull. And that factory has energetic needs, and there's a lot of sort of biological processes underlying that, that we are finding are altered in the context of Alzheimer's disease. That's fascinating that, so you have to consider all of these systems if you wanna understand even something like diseases that you would maybe traditionally associate with just the particular cells of the brain. Yeah. The immune system. The metabolic system. The metabolic system. And these are all the things that makes us uniquely human. So our immune system is dramatically different from that of our neighbors. Our societies are so much more clustered. The history of infection that have plagued the human population is dramatically different from every other species. The way that our society and our population has sort of exploded has basically put unique pressures on our immune system, and our immune system has both coped with that density and also been shaped by, as I mentioned, the vast amount of death that has happened in the Black Plague and other sort of selective events in human history, famines, ice ages, and so forth. So that's number one on the sort of immune side. On the metabolic side, again, we are able to sort of run marathons. I don't know if you remember the sort of human versus horse experiment, where the horse actually tires out faster than the human, and the human actually wins. So on the metabolic side, we're dramatically different. On the immune side, we're dramatically different. On the brain side, again, no need to sort of, it's a no-brainer of how our brain is just enormously more capable. And then in the side of cancer, so basically the cancers that humans are having, the exposures, the environmental exposures, is again, dramatically different. And the lifespan, the expansion of human lifespan is unseen in any other species in recent evolutionary history. And that now leads to a lot of new disorders that are starting to manifest late in life. So Alzheimer's is one example, where basically these vast energetic needs over a lifetime of thinking can basically lead to all of these debris and eventually saturate the system and lead to Alzheimer's in the late life. But there's just such a dramatic set of frontiers when it comes to aging research that will, so what I often like to say is that if you want to engineer a car to go from 70 miles an hour to 120 miles an hour, that's fine. You can basically fix a few components. If you want it to now go at 400 miles an hour, you have to completely redesign the entire car because the system is just not evolved to go that far. Basically our human body has only evolved to live to, I don't know, 120. Maybe we can get to 150 with minor changes. But if, as we start pushing these frontiers for not just living, but well living, the F-zine that we talked about last time, so to basically push F-zine into the 80s and 90s and 100s and much further than that, we will face new challenges that have never been faced before in terms of cancer, the number of divisions, in terms of Alzheimer's and brain-related disorders, in terms of metabolic disorders, in terms of regeneration. There's just so many different frontiers ahead of us. So I am thrilled about where we're heading. So basically I see this confluence in my lab and many other labs of AI, of sort of the next frontier of AI for drug design. So basically these sort of graph neural networks on specific chemical designs that allow you to create new generations of therapeutics. These molecular biology tricks for intervening at the system at every level. These personalized medicine prediction, diagnosis, and prognosis using the electronic health records and using these polygenic risk scores weighted by the burden, the number of mutations that are accumulating across common, rare, and somatic variants, the burden converging across all of these different molecular pathways, the delivery of specific drugs and specific interventions into specific cell types. And again, you've talked with Bob Langer about this. There's many giants in that field. And then the last concept is not intervening at the single gene level. I want you to sort of conceptualize the concept of an on-target side effect. What is an on-target side effect? An off-target side effect is when you design a molecule to target one gene and instead it targets another gene and you have side effects because of that. An on-target side effect is when your molecule does exactly what you were expecting, but that gene is pleiotropic. Pleio means many, tropos means ways. Many ways, it acts in many ways. It's a multifunctional gene. So you find that this gene plays a role in this, but as we talked about, the wiring of genes to phenotypes is extremely dense and extremely complex. So the next stage of intervention will be intervening not at the gene level, but at the network level, intervening at the set of pathways and the set of genes with multi-input perturbations to the system, multi-input modulations, pharmaceutical or other interventional. And that basically allow you to now work at the sort of full level of understanding, not just in your brain, but across your body, not just in one gene, but across the set of pathways and so on and so forth for every one of these disorders. So I think that we're finally at the level of systems medicine, of basically instead of sort of medicine being at the single gene level, medicine being at the systems level, where it can be personalized based on the specific set of genetic markers and genetic perturbations that you are either born with or that you have developed during your lifetime, your unique set of exposures, your unique set of biomarkers, and your unique set of current set of conditions through your EHR and other ways. And the precision component of intervening extremely precisely in the specific pathways and in specific combinations of genes that should be modulated to sort of bring you from the disease state to the physiologically normal state, or even to physiologically improved state through this combination of interventions. So that's, in my view, the field where basically computer science comes together with artificial intelligence, statistics, all of these other tools, molecular biology technologies and biotechnology and pharmaceutical technologies that are sort of revolutionary in the way of intervention. And of course, this massive amount of molecular biology and data gathering and generation and perturbation in massively parallel ways. So there's no better way, there's no better time, there's no better place to be sort of, you know, looking at this whole confluence of ideas. And I'm just so thrilled to be a small part of this amazing, enormous ecosystem. It's exciting to imagine what humans of 100, 200 years from now, what their life experience is like, because these ideas seem to have potential to transform the quality of life. That when they look back at us, they probably wonder how we were put up with all the suffering in the world. Manolis, it's a huge honor. Thank you for spending this early Sunday morning with me. I deeply appreciate it. See you next time. Sounds like a plan. Thank you, Lex. Thanks for listening to this conversation with Manolis Kellis. And thank you to our sponsors, SEMrush, which is an SEO optimization tool, Pessimist Archive, which is one of my favorite history podcasts, 8sleep, which is a self-cooling mattress with smart sensors and an app, and finally, BetterHelp, which is an online therapy service. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Haruki Murakami. Human beings are ultimately nothing but carriers, passageways for genes. They ride us into the ground like racehorses from generation to generation. Genes don't think about what constitutes good or evil. They don't care whether we're happy or unhappy. We're just means to an end for them. The only thing they think about is what is most efficient for them. Thank you for listening, and hope to see you next time.

https://youtu.be/Aq9UPIXbtKI

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Charles Isbell and Michael Littman: Machine Learning and Education | Lex Fridman Podcast #148

The following is a conversation with Charles Isbell and Michael Littman. Charles is the Dean of the College of Computing at Georgia Tech, and Michael is a computer science professor at Brown University. I've spoken with each of them individually on this podcast, and since they are good friends in real life, we all thought it would be fun to have a conversation together. Quick mention of each sponsor, followed by some thoughts related to the episode. Thank you to Athletic Greens, the all-in-one drink that I start every day with to cover all my nutritional bases, 8 Sleep, a mattress that cools itself and gives me yet another reason to enjoy sleep, Masterclass, online courses from some of the most amazing humans in history, and Cash App, the app I use to send money to friends. Please check out the sponsors in the description to get a discount and to support this podcast. As a side note, let me say that having two guests on the podcast is an experiment that I've been meaning to do for a while, in particular because down the road I would like to occasionally be a kind of moderator for debates between people that may disagree in some interesting ways. If you have suggestions for who you would like to see debate on this podcast, let me know. As with all experiments of this kind, it is a learning process. Both the video and the audio might need improvement. I realized I think I should probably do three or more cameras next time as opposed to just two, and also try different ways to mount the microphone for the third person. Also, after recording this intro, I'm going to have to go figure out the thumbnail for the video version of the podcast, since I usually put the guest's head on the thumbnail, and now there's two heads and two names to try to fit into the thumbnail. It's a kind of bin packing problem, which in theoretical computer science happens to be an NP hard problem. Whatever I come up with, if you have better ideas for the thumbnail, let me know as well. And in general, I always welcome ideas how this thing can be improved. If you enjoy it, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Charles Isbell and Michael Littman. You'll probably disagree about this question, but what is your biggest, would you say, disagreement about either something profound and very important or something completely not important at all? I don't think I have any disagreements at all. Ah, I'm not sure that's true. We walked into that one, didn't we? Yeah, that's pretty good. So one thing that you sometimes mention is that, and we did this one on air too, as it were, whether or not machine learning is computational statistics. It's not. But it is. Well, it's not. And in particular, and more importantly, it is not just computational statistics. So what's missing in the picture? All the rest of it. What's missing? That which is missing. Oh, yes, well, you can't be wrong now. Well, it's not just the statistics. He doesn't even believe this. We've had this conversation before. If it were just the statistics, then we would be happy with where we are. But it's not just the statistics. That's why it's computational statistics. Or if it were just the computational... I agree that machine learning is not just statistics. It is not just statistics. We can agree on that. Nor is it just computational statistics. It's computational statistics. It is computational. What is the computational and computational statistics? Does this take us into the realm of computing? It does. But I think perhaps the way I can get him to admit that he's wrong. He's wrong. Is that it's about rules. It's about rules. It's about symbols. It's about all these other things. But statistics is not about rules? I'm going to say statistics is about rules. But it's not just the statistics, right? It's not just a random variable that you choose and you have a probability. I think you have a narrow view of statistics. Okay, well, then what would be the broad view of statistics that would still allow it to be statistics and not say history that would make computational statistics okay? Well, okay. So I had my first sort of research mentor, a guy named Tom Landauer, taught me to do some statistics, right? And I was annoyed all the time because the statistics would say that what I was doing was not statistically significant. And I was like, but, but, but, and basically what he said to me is statistics is how you're going to keep from lying to yourself, which I thought was really deep. It is a way to keep yourself honest in a particular way. I agree with that. Yeah. And so you're trying to find rules. I'm just going to bring it back to rules. Wait, wait, wait. Could you possibly try to define rules? Even regular statisticians, non-computational statisticians, do spend some of their time evaluating rules, right? Applying statistics to try to understand, does this rule capture this? Does this not capture that? You mean like hypothesis testing kind of thing? Sure. Or like confidence testing? Confidence intervals? Like, like, like. More like hypothesis. Like, I feel like the word statistic literally means like a summary, like a number that summarizes other numbers. Right. But I think the field of statistics actually applies that idea to things like rules to understand whether or not a rule is valid. So software engineering statistics? No. Programming languages statistics? No. Because I think there's a very, it's useful to think about a lot of what AI and machine learning is or certainly should be as software engineering, as programming languages. Just, if to put it in language that you might understand, the hyperparameters beyond the problem itself. The hyperparameters is too many syllables for me to understand. The hyperparameters. That's better. That goes around it, right? It's the decisions you choose to make. It's the metrics you choose to use. It's the loss function. You want to say the practice of machine learning is different than the practice of statistics. Like the things you have to worry about and how you worry about them are different, therefore they're different. Right. At a very little, I mean, at the very least, it's that much is true. It doesn't mean that statistics, computational or otherwise, aren't important. I think they are. I mean, I do a lot of that, for example. But I think it goes beyond that. I think that we could think about game theory in terms of statistics, but I don't think it's very as useful to do. I mean, the way I would think about it or a way I would think about it is this way. Chemistry is just physics. But I don't think it's as useful to think about chemistry as being just physics. It's useful to think about it as chemistry. The level of abstraction really matters here. So I think it is, there are contexts in which it is useful. Yes. So finding that connection is actually helpful. And I think that's when I emphasize the computational statistics thing. I think I want to befriend statistics and not absorb them. Here's a way to think about it beyond what I just said. Right. So what would you say, and I want you to think back to a conversation we had a very long time ago. What would you say is the difference between, say, the early 2000s ICML and what we used to call NIPS, NIRPS? Is there a difference? Particularly on the machine learning that was done there? ICML was around that long. Oh, yeah. So ICLR is the new conference, newish. Yeah, I guess so. And ICML was around the 2000s. Oh, ICML predates that. I think my most cited ICML paper is from 94. Yeah. Michael knows this better than me because, of course, he's significantly older than I am. But the point is, what is the difference between ICML and NIRPS in the late 90s, early 2000s? I don't know what everyone else's perspective would be, but I had a particular perspective at that time, which is I felt like ICML was more of a computer science place and that NIPS, NIRPS was more of an engineering place, like the kind of math that happened at the two places. As a computer scientist, I felt more comfortable with the ICML math and the NIRPS people would say that that's because I'm dumb. And that's such an engineering thing to say. So I agree with that part of it. But I do a little differently. We actually had a nice conversation with Tom Dietrich about this on Twitter just a couple of days ago. I put it a little differently, which is that ICML was machine learning done by computer scientists and NIRPS was machine learning done by computer scientists trying to impress statisticians, which was weird because it was the same people. At least by the time I started paying attention, but it just felt very, very different. And I think that that perspective of whether you're trying to impress the statisticians or you're trying to impress the programmers is actually very different and has real impact on what you choose to worry about and what kind of outcomes you come to. So I think it really matters. And computational statistics is a means to an end. It is not an end in some sense. And I think that really matters here in the same way that I don't think computer science is just engineering or just science or just math or whatever. Okay, so I'd have to now agree that now we agree on everything. Yes. Yes. The important thing here is that my opinions may have changed, but not the fact that I'm right, I think is what we just came to. Right. And my opinions may have changed and not the fact that I'm wrong. That's right. You lost me. I'm not even- I think I lost myself there too. But anyway- But we're back. We're back. This happens to us sometimes. We're sorry. How does neural networks change this, just to even linger on this topic, change this idea of statistics, how big of a pie statistics is within the machine learning thing? Like, because it sounds like hyperparameters and also just the role of data. You know, people are starting to use this terminology of software 2.0, which is like the act of programming as a, like you're a designer in the hyperparameter space of neural networks, and you're also the collector and the organizer and the cleaner of the data. And that's part of the programming. So how did, on the NeurIPS versus ICML topic, what's the role of neural networks in redefining the size and the role of machine learning? Well, I can't wait to hear what Michael thinks about this, but I would add- But you will. But that's true. I'll force myself to. I think there's one other thing I would add to your description, which is the kind of software engineering part of what does it mean to debug, for example. But this is a difference between the kind of computational statistics view of machine learning and the computational view of machine learning, which is I think one is worried about the equation as it were. By the way, this is not a value judgment. I just think it's about perspective. But the kind of questions you would ask, you start asking yourself, well, what does it mean to program and develop and build the system, is a very computer sciency view of the problem. I mean, if you get on data science Twitter and econ Twitter, you actually hear this a lot with the economist and the data scientist complaining about the machine learning people. Well, it's just statistics, and I don't know why they don't see this. But they're not even asking the same questions. They're not thinking about it as a kind of programming problem. And I think that that really matters, just asking this question. I actually think it's a little different from programming and hyperparameter space and sort of collecting the data. But I do think that that immersion really matters. So I'll give you a quick example of the way I think about this. So I teach machine learning. Michael and I have co-taught a machine learning class, which has now reached, I don't know, 10,000 people at least over the last several years or somewhere there's about. And my machine learning assignments are of this form. So the first one is something like implement these five algorithms, you know, KNN and SVMs and boosting and decision trees and neural networks, and maybe that's it, I can't remember. And when I say implement, I mean steal the code. I am completely uninterested. You get zero points for getting the thing to work. I don't want you spending your time worrying about getting the corner case right of, you know, what happens when you are trying to normalize distances and the points on the thing. And so you divide by zero. I'm not interested in that, right? Steal the code. However, you're going to run those algorithms on two data sets. The data sets have to be interesting. What does it mean to be interesting? Well, a data set is interesting if it reveals differences between algorithms, which presumably are all the same because they can represent whatever they can represent. And two data sets are interesting together if they show different differences, as it were. And you have to analyze them. You have to justify their interestingness and you have to analyze them in a whole bunch of ways. But all I care about is the data in your analysis, not the programming. And I occasionally end up in these long discussions with students. Well, I don't really. I copy and paste the things that I've said the other 15,000 times it's come up, which is they go. But the only way to learn, really understand is to code them up, which is a very programmer, software engineering view of the world. If you don't program it, you don't understand it, which is, by the way, I think is wrong in a very specific way. But it is a way that you come to understand because then you have to wrestle with the algorithm. But the thing about machine learning is not just sorting numbers, where in some sense the data doesn't matter. What matters is, well, does the algorithm work on these abstract things, one less than the other. In machine learning, the data matters. It matters more than almost anything. And not everything, but almost anything. And so as a result, you have to live with the data and don't get distracted by the algorithm per se. And I think that that focus on the data and what it can tell you and what question it's actually answering for you, as opposed to the question you thought you were asking, is a key and important thing about machine learning and is a way that computationalists, as opposed to statisticians, bring a particular view about how to think about the process. The statisticians, by contrast, bring, I think I'd be willing to say, a better view about the kind of formal math that's behind it and what an actual number ultimately is saying about the data. And those are both important, but they're also different. Lex Doppelganger I didn't really think of it this way, is to build intuition about the role of data, the different characteristics of data, by having two data sets that are different and they reveal the differences in the differences. That's a really fascinating, that's a really interesting educational approach. David Willis The students love it, but not right away. They love it later. Kamal Haasan They love it at the end. Not at the beginning. David Willis Not even immediately after. Kamal Haasan I feel like there's a deep, profound lesson about education there. That you can't listen to students about whether what you're doing is the right or the wrong thing. Lex Doppelganger Well, as a wise, Michael Lippman once said to me about children, which I think applies to teaching, is you have to give them what they need without bending to their will. And students are like that. You have to figure out what they need. You're a curator. Your whole job is to curate and to present, because on their own, they're not going to necessarily know where to search. So you're providing pushes in some direction and learn space. And you have to give them what they need in a way that keeps them engaged enough so that they eventually discover what they want and they get the tools they need to go and learn other things off of. David Willis What's your view? Let me put on my Russian hat, which believes that life is suffering. Lex Doppelganger I like Russian hats, by the way. If you have one, I would like this. David Willis Those are ridiculous. Yes. Lex Doppelganger But in a delightful way. But sure. Okay. David Willis What do you think is the role of, we talked about balance a little bit. What do you think is the role of hardship in education? Like, I think the biggest things I've learned, like what made me fall in love with math, for example, is by being bad at it until I got good at it. So like, like struggling with a problem, which increased the level of joy I felt when I finally figured it out. And it always felt with me with teachers, especially modern discussions of education, how can we make education more fun, more engaging, more all those things. Or from my perspective is like, you're maybe missing the point that education, that life is suffering. Education is supposed to be hard. And that actually what increases the joy you feel when you actually learn something. Is that ridiculous? Do you like to see your students suffer? Okay, so this may be a point where we differ. I suspect not. I'm gonna do go on. Well, what would your answer be? I want to hear you first. Okay, well, I was gonna not answer the question. So you don't want the students to know you enjoy them suffering? No, no, no, no, no, no. I was, I was gonna say that there's, I think there's a distinction that you can make in the kind of suffering, right? So I think you can be in a mode where you're, you're suffering in a hope-filled way. Where you're, you're suffering in a hopeless way versus you're suffering in a hopeful way, right? Where you're like, you can see that if you, that you still have, you can still imagine getting to the end, right? And as long as people are in that mindset where they're struggling, but it's not a hopeless kind of struggling, that's, that's productive. I think that's really helpful. But it's struggling, like if you, you break their will, if you leave them hopeless, no, that don't, sure, some people are gonna, whatever, lift themselves up by their bootstraps. But like mostly you give up and certainly it takes the joy out of it. And you're not gonna spend a lot of time on something that brings you no joy. So it's, it is a bit of a delicate balance, right? You have to thwart people in a way that they still believe that there's a way through. Right. So that's a, that we strongly agree, actually. So I think, well, first off, struggling and suffering aren't the same thing, right? Yeah, just being poetic. Oh, no, I actually appreciate the poetry. And I, one of the reasons I appreciate it is that they are often the same thing and often quite different, right? So you can struggle without suffering. You can certainly suffer, suffer, suffer pretty easily. You don't necessarily have to struggle to suffer. So I think that you want people to struggle, but that hope matters. You have to, they have to understand that they're gonna get through it on the other side. And it's very easy to confuse the two. I actually think Brown University has a very, just philosophically has a very different take on the relationship with their students, particularly undergrads from say a place like Georgia Tech, which is. Which university is better? Well, I have my opinions on that. I mean, remember Charles said, it doesn't matter what the facts are, I'm always right. The correct answer is that it doesn't matter. They're different, but clearly answers are better. He went to a school like the school where he is as an undergrad. I went to a school specifically the same school, though it was, it changed a bit in the intervening years. Brown or Georgia Tech? No, I was talking about Georgia Tech. And I went. It's changed. Yeah. And I went to an undergrad place that's a lot like the place where I work now. And so it does seem like we're more familiar with these models. There's a similarity between Brown and Yale? Yeah, I think they're quite similar. Yeah. And Duke. Duke has some similarities too, but it's got a little Southern draw. You've kind of worked, you've sort of worked at universities that are like the places where you learned. And the same would be true for me. Are you uncomfortable venturing outside the box? Is that what you're saying? Mm-hmm. Journeying out. Not what I'm saying. Yeah, Charles is definitely. He only goes to places that have institute in the name, right? It has worked out that way. Well, academic places anyway. Well, no, I was a visiting scientist at UPenn or visiting something at UPenn. Oh, wow. I just understood your joke. Which one? Five minutes later. I like to set these sort of time bombs. The institute is in the, that Charles only goes to places that have institute in the name. So I guess Georgia, I forget that Georgia Tech is Georgia Institute of Technology. The number of people who refer to it as Georgia Tech University is large and incredibly irritating. It's one of the few things that genuinely gets under my skin. But like schools like Georgia Tech and MIT have as part of the ethos, like there is, I want to say there's an abbreviation that someone taught me, like IHTFP, something like that. There's an expression, which is basically, I hate being here, which they say so proudly. And that is definitely not the ethos at Brown. Like Brown is, there's a little more pampering and empowerment and stuff. And it's not like we're going to crush you and you're going to love it. So yeah, I think there's a, I think the ethos are different. That's interesting. Yeah. We had drown proofing. What's that? Drown proofing. In order to graduate from Georgia Tech, this is a true thing. Feel free to look it up. If you. A lot of schools have this, by the way. No, actually Georgia Tech was really the first. Brandeis has it. Had it. I feel like Georgia Tech was the first in a lot of ways. It was the first in a lot of things. Had the first master's degree. First Bumblebee mascot. Stop that. First master's in computer science, actually. Right, online master's. Well, that too, but way back in the 60s. NSF grant. Yeah, yeah. We had the first information and computer science master's degree in the country. But the Georgia Tech, it used to be the case in order to graduate from Georgia Tech, you had to take a drown proofing class, where effectively, they threw you in the water, tied you up. If you didn't drown, you got to graduate. Tied you up? I believe so. No. There were certainly versions of it, but I mean, luckily, they ended it just before I had to graduate because otherwise I would have never graduated. It wasn't going to happen. I want to say 84, 83, someone around then, they ended it. But yeah, you used to have to prove you could tread water for some ridiculous amount of time or you couldn't graduate. No, it was more than two minutes. I bet it was two minutes. Okay, well, we'll look at that. And it was in a bathtub. It was in a pool, but it was a real thing. But that idea that push you- Fully clothed. Yeah, fully clothed. I bet it was that and not tied up because who needs to learn how to swim when you're tied? Nobody. But who needs to learn to swim when you're actually falling into the water dressed? That's a real thing. I think your facts are getting in the way with a good story. Oh, that's fair. That's fair. I didn't mean to- All right. So they tie you up. The narrative matters. But whatever it was, it was called drown-proofing for a reason. The point of the story, Michael, is- Struggle. Well, no, but that's good. It does bring it back to struggle. That's a part of what Georgia Tech has always been. And we struggle with that, by the way, about what we want to be, particularly as things go. But how much can you be pushed without breaking and you come out of the other end stronger? There's a saying we used to have when I was an undergrad there, which was Georgia Tech, building tomorrow the night before. And it was just kind of idea that give me something impossible to do and I'll do it in a couple of days because that's what I just spent the last four or five or six years doing. That ethos definitely stuck to you. Having now done a number of projects with you, you definitely will do it the night before. That's not entirely true. There's nothing wrong with waiting until the last minute. The secret is knowing when the last minute is. Right. That's brilliantly put. Yeah. Yeah. That is a definite Charles statement that I am trying not to embrace. But I appreciate that because you helped move my last minute. That's the social construct that we converge together with the definition of last minute is. Right. We figure that out all together. In fact, MIT, I'm sure a lot of universities have this, but MIT has like MIT time that everyone has always agreed together that there is such a concept and everyone just keeps showing up like 10 to 15 to 20, depending on the department, late to everything. So there's like a weird drift that happens. It's kind of fascinating. Yeah, we're five minutes. We're five minutes. In fact, the classes will say, well, this is no longer true actually, but it used to be a class that started at eight, but actually started at eight or five and ends at nine. Actually it ends at 855. Everything's five minutes off and nobody expects anything to start until five minutes after the half hour, whatever it is. It still exists. It hurts my head. Well, let's rewind the clock back to the 50s and 60s when you guys met. How did you, I'm just kidding. I don't know. But what, can you tell the story of how you met? So you've, like the internet and the world kind of knows you as connected in some ways in terms of education, of teaching the world. That's like the public facing thing. But how did you as human beings and as collaborators meet? I think there's two stories. One is how we met and the other is how we got to know each other. I'm not going to say fell in love. I'm going to say that we came to understand that we had some common something. Yeah. It's funny because on the surface, I think we're different in a lot of ways, but there's something that just consonant. There you go. Afternoon. So I will tell the story of how we met and I'll let Michael tell the story of how we met. Okay. All right. Okay. So here's how we met. I was already at that point, it was AT&T Labs. There's a long, interesting story there. But anyway, I was there and Michael was coming to interview. He was a professor at Duke at the time, but decided for reasons that he wanted to be in New Jersey. And so that would mean Bell Labs slash AT&T Labs. And we were doing interviews, interviews very much like academic interviews. And so I had to be there. We all had to meet with him afterwards and so on, one-on-one. But it was obvious to me that he was going to be hired, like no matter what, because everyone loved him. They were just talking about all the great stuff he did. And, oh, he did this great thing. And you had just won something at AAAI, I think, or maybe you got 18 papers in AAAI that year. I got the best paper award at AAAI for the crossword stuff. Right. Exactly. So that had all happened and everyone was going on about it. Everyone was going on and on and on about it. Actually, so Tinder was saying incredibly nice things about you. Really? Yes. So. He can be very grumpy. Yes. So that's very, that's nice to hear. He was grumpily saying very nice things. Oh, that makes sense. And that does make sense. So, you know, so he was going to come. So why were we, why was I meeting him? I had something else I had to do. I can't remember what it was. It probably involved comic books. So he remembers meeting me as inconveniencing his afternoon. So he came, so I eventually came to my office. I was in the middle of trying to do something. I can't remember what. And he came and he sat down. And for reasons that are purely accidental, despite what Michael thinks, my desk at the time was set up in such a way that had sort of an L shape and the chair on the outside was always lower than the chair that I was in. And, you know, the kind of point was. The only reason I think that it was on purpose is because you told me it was on purpose. I don't remember that. Anyway, the thing is, is that, you know, it kind of. His guest chair was really low so that he could, he could look down at everybody. The idea was just to simply create a nice environment that you were asking for a mortgage. And I was going to say, no, that was the point. It was a very simple idea here. Anyway, so we sat there and we just talked for a little while. And I think he got the impression that I didn't like him. It wasn't true. I strongly got that impression. The talk was really good. The talk, by the way, was terrible. And right after the talk, I said to my host, Michael Kearns, who ultimately was my boss. I'm a huge fan. I'm a friend and a huge fan of Michael, yeah. Yeah, he is a remarkable person. After my talk, I went into the. Irritably good basketball. Racquetball. He's good at everything. No, basketball. No, but basketball, racquetball too. Squash. Squash. Squash. Squash, not racquetball. Yeah, squash, which is not. Racquetball. Yes. Squash. No. And I hope you hear that, Michael. You mean in terms of as a game, not his skill level, because I'm pretty sure he's. All right. There's some competitiveness there. But the point is that it was like the middle of the day. I had a full day of interviews. Like I met with people. But then in the middle of the day, I gave a job talk. And then there was going to be more interviews. But I pulled Michael aside and I said, I think it's in both of our best interests if I just leave now, because that was so bad that it's just be embarrassing if I have to talk to any more people like you look bad for having invited me. Like, it's just let's just forget this ever happened. So I don't think the talk went well. It's one of the most Michael Lipman set of sentences I think I've ever heard. He did great, or at least everyone knew he was great. So maybe it didn't matter. I was there. I remember the talk. And I remember him being very much the way I remember him now on any given week. So it was good. And we met and we talked about stuff. He thinks I didn't like him, but because he was so grumpy. Must have been the chair thing. The chair thing and the low voice, I think. He obviously. And that like that like slight like skeptical look. Yes. I have no idea what you're talking about. Well, I probably didn't have any idea what you were talking about. Anyway, I liked him. He asked me questions. I answered questions. I felt bad about myself. It was a normal day. It was a normal day. And then he left. And then he left. And that's how we met. Can we take it? And then I got hired and I was in the group. Can we take a slight tangent on this topic of it sounds like maybe you could speak to the bigger picture. It sounds like you're quite self-critical. Who, Charles? No, you. Oh, I think I can do better. I can do better. I'll try me again. I'll do better. Yeah, that was like a like a three out of ten response. Let's try to work it up to five and six. I remember Marvin Minsky said on a video interview something that the key to success in academic research is to hate everything you do. For some reason. I think I followed that because I hate everything he's done. That's a good line. That's a six. Maybe that's a keeper. But do you find that resonates with you at all in how you think about talks and so on? I would say it differently. It's not. No, not really. That's such an MIT view of the world. So, I remember talking about this when as a student, you were basically told, I will clean it up for the purpose of the podcast. My work is crap. My work is crap. My work is crap. My work is crap. Then you go to a conference or something. You're like, everybody else's work is crap. Everybody else's work is crap. And you feel better and better about it. Yeah, relatively speaking. And then you sort of keep working on it. I don't hate my work. That resonates with me. Yes. I've never hated my work, but I have been dissatisfied with it. And I think being dissatisfied, being okay with the fact that you've taken a positive step, the derivative is positive. Maybe even the second derivative is positive. That's important because that's a part of the hope, right? But you have to, but I haven't gotten there yet. If that's not there, that I haven't gotten there yet, then it's hard to move forward, I think. So I buy that, which is a little different from hating everything that you do. Yeah. I mean, there's things that I've done that I like better than I like myself. So it's separating me from the work, essentially. So I think I am very critical of myself, but sometimes the work I'm really excited about. And sometimes I think it's kind of good. Does that happen right away? So I found the work that I've liked, that I've done, most of it, I liked it in retrospect more when I was far away from it in time. I have to be fairly excited about it to get done. No, excited at the time, but then happy with the result. But years later, or even I might go back, you know what, that actually turned out to matter. That turned out to matter. Or, oh gosh, it turns out I've been thinking about that. It's actually influenced all the work that I've done since without realizing it. Boy, that guy was smart. Yeah, that guy had a future. Yeah. Yeah. He's going places. I think there's, so yeah, so I think there's something to it. I think there's something to the idea you've got to hate what you do, but it's not quite hate. It's just being unsatisfied. And different people motivate themselves differently. I don't happen to motivate myself with self-loathing. I happen to motivate myself with something else. So you're able to sit back and be proud of, in retrospect, of the work you've done. Well, and it's easier when you can connect it with other people, because then you can be proud of them. Proud of the people, yeah. And then the question is- And then you can still safely hate yourself. Yeah, that's right. It's win-win, Michael. Or at least win-lose, which is what you're looking for. Oh, wow. There's so many brilliant lines in this. There's levels. So how did you actually meet me? Yeah, Michael. So the way I think about it is, because we didn't do much research together at AT&T. At the beginning, no. But then we all got laid off. By the way, sorry to interrupt, but that was one of the most magical places, historically speaking. They did not appreciate what they had. And how do we- I feel like there's a profound lesson in there, too. How do we get it- Like, why was it so magical? Is it just a coincidence of history? Or is there something special about- There were some really good managers and people who really believed in machine learning as, this is going to be important. Let's get the people who are thinking about this in creative and insightful ways and put them in one place and stir. Yeah, but even beyond that, right, it was Bell Labs at its heyday. And even when we were there, which I think was past its heyday. And to be clear, he's gotten to be at Bell Labs. I never got to be at Bell Labs. I joined after that. Yeah, I should have been 91 as a grad student. So I was there for a long time, every summer, except for- So twice I worked for companies that had just stopped being Bell Labs. Right. Bellcore and then AT&T Labs. So Bell Labs was several locations or for the research? Or is it one? Like, is that- Definitely several. Jersey's involved somehow? They're all in Jersey. Yeah, they're all over the place. But they were in a couple of places in Jersey. Murray Hill was the Bell Labs place. So you had an office at Murray Hill at one point in your career. Yeah, I played ultimate frisbee on the cricket pitch at Bell Labs at Murray Hill. And then it became AT&T Labs when it split off with Luce during what we call trivestiture. So you're better than Michael Korns at ultimate frisbee? Yeah. Oh, yeah. Okay. But I think that was not boasting. I think Charles plays a lot of ultimate and I don't think Mike does. No, I was- Yes, but that wasn't the point. The point is, yes. I'm sorry. I'm finally better. Yes, I'm sorry. Okay, I have played on a championship winning ultimate frisbee team or whatever, ultimate team with Charles. So I know how good he is. He's really good. How good I was anyway when I was younger. But the thing is- I know how young he was when he was younger. That's true. That is true. So much younger than now. He's older now. Yes, I'm older. Michael was a much better basketball player than I was. Michael Korns. Yes. No, not Michael. I'm sorry. Let's be very clear about that. To be clear, I've not played basketball with you. So you don't know how terrible I am, but you have a probably pretty good guess. And that you're not as good as Michael Korns. He's tall and athletic. And he cared about it. He's very athletic. He's very good. And probably competitive. I love hanging out with Michael. Anyway, but we were talking about something else, although I no longer remember what it was. What were we talking about? Oh, Bell Labs. Oh, Bell Labs. But also Labs. This was kind of cool about what was magical about it. Well, the first thing you have to know is that Bell Labs was an arm of the government, right? Because AT&T was an arm of the government. It was a monopoly. And every month you paid a little thing on your phone bill, which turned out was a tax for all the research that Bell Labs was doing. And they invented transistors and the laser and whatever else that they did. The Big Bang or whatever, the cosmic background radiation. Yeah, they did all that stuff. They had some amazing stuff with directional microphones, by the way. I got to go in this room where they had all these panels and everything. And we would talk. And one another, and he'd move some panels around. And then he'd have me step two steps to the left. And I couldn't hear a thing he was saying because nothing was bouncing off the walls. And then he would shut it all down and you could hear your heartbeat. Yeah. Which is deeply disturbing to hear your heartbeat. You can feel it. I mean, you can feel it now. There's so much all this sort of noise around. Anyway, Bell Labs is about pure research. It was a university, in some sense, the purest sense of a university, but without students. So it was all the faculty working with one another. And students would come in to learn. They would come in for three or four months during the summer. And they would go away. But it was just this kind of wonderful experience. I could walk out my door. In fact, I would often have to walk out my door and deal with Rich Sutton and Michael Kearns yelling at each other about whatever it is they were yelling about, the proper way to prove something or another. And I could just do that. And Dave McAllister and Peter Stone and all of these other people, including Sittender and eventually Michael. And it was just a place where you could think thoughts. And it was OK because so long as once every 25 years or so somebody invented a transistor, it paid for everything else. You could afford to take the risk. And then when that all went away, it became harder and harder and harder to justify it as far as the folks who were very far away were concerned. And there was such a fast turnaround among mental management on the AT&T side that you never had a chance to really build a relationship. At least people like us didn't have a chance to build a relationship. So when the diaspora happened, it was amazing, right? Yeah. Everybody left. And I think everybody ended up at a great place and made a huge, made a, continued to do really good work with machine learning. But it was a wonderful place. And people will ask me, what's the best job you've ever had? And as a professor, the answer that I would give is, well, probably Bell Labs in some very real sense. And I will never have a job like that again because Bell Labs doesn't exist anymore. And Microsoft Research is great. And Google does good stuff. And you can pick IBM. You can tell if you want to. But Bell Labs was magical. It was around for, it was an important time. And it represents a high watermark in basic research in the US. Is there something you could say about the physical proximity and the chance collisions? Like we live in this time of the pandemic where everyone is maybe trying to see the silver lining and accepting the remote nature of things. Is there, one of the things that people like faculty that I talk to miss is the procrastination. Like the chance to, like everything is about meetings that are supposed to be, there's not a chance to just talk about comic books or whatever, like go into discussion that's totally pointless. So it's funny you say this because that's how we met, Matt. It was exactly that. So I'll let Michael say that, but I'll just add one thing, which is just that research is a social process. And it helps to have random social interactions, even if they don't feel social at the time. That's how you get things done. One of the great things about the AI lab when I was there, I don't quite know what it looks like now once they move buildings, but we had entire walls that were whiteboards and people would just get up there and they were just right. And people would walk up and you'd have arguments and you'd explain things to one another. And you got so much out of the freedom to do that. You had to be okay with people challenging every fricking word you said, which I would sometimes find deeply irritating. But most of the time it was quite useful. But the sort of pointlessness and the interaction was in some sense the point, at least for me. Yeah. I mean, I think offline yesterday I mentioned Josh Tenenbaum and he's very much, he's such an inspiration in the child-like way that he pulls you in on any topic. It doesn't even have to be about machine learning or the brain. He'll just pull you into a closest writable surface, which is still, you can find whiteboards at MIT everywhere. And just basically cancel all meetings and talk for a couple hours about some aimless thing. And it feels like the whole world, the time-space continuum kind of warps and that becomes the most important thing. And then it's just, it's definitely something worth missing in this world where everything's remote. There's some magic to the physical presence. Whenever I wonder myself whether MIT really is as great as I remember it, I just go talk to Josh. Yeah. You know, that's funny is there's a few people in this world that carry the best of what particular institutions stand for, right? And there's- There's Josh. I mean, I don't, my guess is he's unaware of this. That's the point. The masters are not aware of their mastery. So- How did you meet? Yes, but first a tangent, no. How did you meet me? So I'm not sure what you were thinking, but when it started to dawn on me that maybe we had a longer term bond was after we all got laid off. And you had decided at that point that we were still paid. We were given an opportunity to like do a job search and kind of make a transition, but it was clear that we were done. And I would go to my office to work and you would go to my office to keep me from working. Yeah. That was my recollection of it. And you had decided that there was no really no point in working for the company because the company, our relationship with the company was done. Yeah, but remember I felt that way beforehand. It wasn't about the company. It was about the set of people there doing really cool things. And it always, always been that way. But we were working on something together. Oh yeah, yeah, yeah. That's right. So at the very end, we all got laid off, but then our boss came to, our boss's boss, came to us because our boss was Michael Kearns and he had jumped ship brilliantly, like perfect timing, like things like right before the ship was about to sink. He was like, got to go and, and, and landed perfectly because Michael Kearns. Because Michael Kearns. And the, leaving the rest of us to go like, this is fine. And then it was clear that it wasn't fine and we were all toast. So we had this sort of long period of time, but then our boss figured out, okay, wait, maybe we can save a couple of these people if we can have them do something really useful. And the useful thing was we were going to make a, basically an automated assistant that could help you with your calendar. You could like tell it things and it would, it would respond appropriately. It would just kind of integrate across all sorts of your personal information. And so me and Charles and Peter Stone were this, were set up as the crack team to actually solve this problem. Other people maybe were too theoretical that they thought and, and, but we could actually get something done. So we sat down to get something done and there wasn't time and it wouldn't have saved us anyway. And so it all kind of went downhill. But the interesting, I think, coda to that is that our boss's boss is a guy named Ron Brockman. And he, when he left AT&T, cause we were all laid off, he went to DARPA, started up a program there that became KALO, which is the program from which Siri sprung, which is a digital assistant that helps you with your calendar and a bunch of other things. It really, you know, in some ways got its start with me and Charles and Peter trying to implement this vision that Ron Brockman had that he ultimately got implemented through his role at DARPA. So when I'm trying to feel less bad about having been laid off from what is possibly the greatest job of all time, I think about, well, we kind of helped birth Siri. That's something. And then he did other things too, but the, we got to spend a lot of time in his office and talk about it. We got to spend a lot of time in my office. Yeah. Yeah. Yeah. And so so then we went on our merry way. Everyone went to different places. Charles landed at Georgia Tech, which was what he always dreamed he would do. And so that worked out well. I came up with a saying at the time, which is luck favors the Charles. It's kind of like luck favors the prepared. But Charles, like, like he wished something and then it would basically happen just the way he wanted. It was, it was inspirational to see things go that way. Things worked out. And we stayed in touch. And then I think it really helped when you were working on, I mean, you'd kept me in the loop for things like threads and the work that you were doing at Georgia Tech, but then when they were starting their online master's program, he knew that I was really excited about MOOCs and online teaching. And he's like, I have a plan. And I'm like, tell me your plan. He's like, I can't tell you the plan yet because they were deep in, in negotiations between Georgia Tech and Udacity to make this happen and they didn't want it to leak. So Charles would kept teasing me about it, but wouldn't tell me what was actually going on. And eventually it was announced and he said, I would like you to teach the machine learning course with me. I'm like, that can't possibly work. But it was a great idea. And it was, it was super fun. It was a lot of work to put together, but it was, it was really great. And was that the first time you thought about, first of all, was it the first time you got seriously into teaching? I mean, you know, I was a professor. This was already, this was already after you jumped to, so like, there's a little bit of jumping around in time. Yeah. Sorry about that. There's a pretty big jump in time. So like the MOOCs thing. So Charles got to Georgia Tech and he, I mean, maybe Charles, maybe this is a Charles story. I got to Georgia Tech in 2002. He got to Georgia Tech in 2002. And, but then, and worked on things like revamping the curriculum, the undergraduate curriculum, so that it had some kind of semblance of modular structure because computer science was at the time moving from a fairly narrow specific set of topics to touching a lot of other parts of, of intellectual life. And the curriculum was supposed to reflect that. And so Charles played a big role in, in kind of redesigning that. And then the- And for my, and for my, my labors, I ended up as associate dean. Right. He got to become associate dean of, in charge of educational stuff. Well, that should be a valuable lesson. If you're good at something, they will give you responsibility to do more of that thing. Well, don't show competence. Don't show competence. If you, well, you know what they say. Responsibility. Here's what they say. Yeah. The reward for good work is more work. Yeah. The reward for bad work is less work. Which, I don't know, depending on what you're trying to do that week, one of those is better than the other. Well, one of the problems with the word work, sorry to interrupt, is that it's, seems to be an antonym in this particular language. We have the opposite of happiness, but it seems like they're, they're like, that's one of, you know, we talked about balance. It's, it's always like work-life balance. It always rubbed me the wrong way as a terminology. I know it's just words. Right. The opposite of work is play, but ideally work is play. Oh, I can't tell you how much time I'd spend, certainly when I was at Bell Labs, except for a few very key moments as a professor, I would do this too. I would just say, I cannot believe they're paying me to do this. Because it's fun. It's something that I would, I would do for a hobby if I could anyway. So that's what it worked out. You sure you want to be saying that? When this is being recorded? As a Dean, that is not true at all. I need a raise. Yeah. But, but I think here with, with this, that even though a lot of time passed, you know, Michael and I talked almost every, well, we texted almost every day during the period. Charles, at one point took me, there was the ICML conference, the machine learning conference was in Atlanta. I was the chair, the general chair of the conference. Charles was my publicity chair, something like that, or fundraising chair. Fundraising chair. Yeah. Yeah. Um, but he decided it'd be really funny if he didn't actually show up for the conference in his own home city. So he didn't, but he did at one point, pick me up at the conference in his Tesla and drove me to the Atlanta mall and forced me to buy an iPhone because he didn't like how it was to text with me and thought it would be better for him if I had an iPhone, the text would be somehow smoother. And it was. And it was. And it is. And his life is better. And my life is better. And so, yeah, but, but it was, yeah, Charles forced me to get an iPhone so that he could text me more efficiently. I thought that was an interesting moment. It works for me. Anyway, so we kept talking the whole time and then eventually we did the, we did the teaching thing and it was great. And there's a couple of reasons for that, by the way. One is I really wanted to do something different. Like you've got this medium here, people claim it can change things. What's a thing that you could do in this medium that you could not do otherwise? Besides edit, right? I mean, what could you do? And, and being able to do something with another person was that kind of thing. It's very hard. I mean, you can take turns, but teaching together, having conversations is very hard, right? So that was a cool thing. The second thing, it gave me an excuse to do more stuff with him. Yeah, I always thought he makes it sound brilliant. And it is, I guess. But at the time it really felt like I've got a lot to do, Charles is saying, and it would be great if Michael could teach the course and I could just. Hang out. Yeah, just kind of coast on that. Well, that's what the second class was more like that because the second class was explicit. The first class, it was at least half. So the structure, the structure that once again, letting the facts get in the way. Good story. I should just let Charles talk. But that's the facts as he saw. But so that was, that was kind of true. Your facts. Yeah, that was sort of true for 7642, which is the reinforcement learning class, because that was really his class. You started with reinforcement learning? No, we started with, I did the machine learning, interim machine learning 7641, which is supervised learning, unsupervised learning and reinforcement learning and decision making, cram all that in there, the kind of assignments that we talked about earlier. And then eventually, about a year later, we did a follow on 7642, which is reinforcement learning and decision making. The first class was based on something I'd been teaching at that point for well over a decade. And the second class was based on something Michael had been teaching. Actually, I learned quite a bit teaching that class with him, but he drove most of that. But the first one I drove most of it was all my material, although I had stolen that material originally from slides I found online from Michael, who had originally stolen that material from, I guess, slides he found online, probably from Andrew Moore, because the jokes were the same anyway. At least some of the, at least when I found the slides, some of the stuff. Is that true? Yes, every machine learning class taught in the early 2000s stole from Andrew Moore. A particular joke or two. At least the structure. Now I did, and he did actually a lot more with reinforcement learning and such and game theory and those kinds of things. But, you know, we all sort of built a research world. No, no, no. I mean, in teaching that class. The coverage was different than what we started. Most people were just doing supervised learning and maybe a little bit of, you know, clustering and whatnot. But we took it all the way to machine learning. A lot of it just comes from Tom Mitchell's book. Oh, no. Yeah, except, well, half of it comes from Tom Mitchell's book, right? The other half doesn't. This is why it's all readings, right? Because certain things weren't invented when Tom wrote it. Yeah, okay, that's true. Right? But it was quite good. But there's a reason for that besides, you know, just I wanted to do it. I wanted to do something new and I wanted to do something with him, which is a realization, which is despite what you might believe, he's an introvert and I'm an introvert, or I'm on the edge of being an introvert anyway. But both of us, I think, enjoy the energy of the crowd, right? There's something about talking to people and bringing them into whatever we find interesting that is empowering, energizing, or whatever. And I found the idea of staring alone at a computer screen and then talking off of materials less inspiring than I wanted it to be. And I had, in fact, done a MOOC for Udacity on algorithms. And it was a week in a dark room talking at the screen, writing on the little pad. And I didn't know this was happening, but the crew had watched some of the videos while in the middle of this, and they're like, something's wrong. You're sort of shutting down. And I think a lot of it was I'll make jokes and no one would laugh. And I felt like the crowd hated me. Now, of course, there was no crowd, so it wasn't rational. But each time I tried it and I got no reaction, it just was taking the energy out of my performance, out of my presentation. Such a fantastic metaphor for grad school. Anyway, by working together, we could play off each other and have a- And keep the energy up, because you can't let your guard down for a moment. You can't let your guard down for a moment with Charles. He'll just overpower you. I have no idea what you're talking about. But we would work really well together, I thought. And we knew each other, so I knew that we could sort of make it work. Plus, I was the associate dean, so they had to do what I told them to do. So we had to make it work. And so it worked out very well, I thought. Well enough that we- With great power comes great power. That's right. And we became smooth and curly. And that's when we did the overfitting thriller video. Yeah, yeah, that's a thing. Yeah. So can we just like smooth and curly, where did that come from? So, okay, so it happened, it was completely spontaneous. These are nicknames you go by. Yeah, so- Or it's what the students call us. He was lecturing. So the way that we structure the lectures is one of us is the lecturer, and one of us is basically the student. And so he was lecturing on- The lecturer prepares all the materials, comes up with the quizzes, and then the student comes in not knowing anything. So it was just like being on campus. And I was doing game theory in particular, the Prisoner's Dilemma. Prisoner's Dilemma. And so he needed to set up a little Prisoner's Dilemma grid. So he drew it, and I could see what he was drawing. And the Prisoner's Dilemma consists of two players, two parties. So he decided he would make little cartoons of the two of us. And so there was two criminals, right, that were deciding whether or not to rat each other out. One of them he drew as a circle with a smiley face and a kind of goatee thing, smooth head. And the other one with all sorts of curly hair. And he said, this is smooth and curly. I said, smooth and curly? He said, no, no, smooth with a V. It's very important that it have a V. And that stuck. I actually watched that video. And then the students really took to that. Like they found that relatable. He started singing Smooth Criminal by Michael Jackson. Yeah, yeah, yeah. And those names stuck. So we now have a video series, an episode, our kind of first actual episode should be coming out today, Smooth and Curly on video, where the two of us discuss episodes of Westworld. We watch Westworld and we're like, huh, what does this say about computer science and AI? And we did not watch it. I mean, I know it's on season three or whatever we have. As of this recording, it's on season three. We've watched now two episodes total. Yeah, I think I've watched three. What do you think about Westworld? Two episodes in. So I can tell you so far, I'm just guessing what's gonna happen next. It seems like bad things are gonna happen with the robots uprising. Spoiler alert. So I have not, I have not, I mean, I vaguely remember a movie existing, so I assume it's related to that. But that was more my time than your time, Charles. That's right, because you're much older than I am. I think the important thing here is that it's narrative, right? It's all about telling a story. That's the whole driving thing. But the idea that they would give these reveries, that they would make people, they would make them remember the awful things that happened. Who could possibly think that was gonna happen? Who could possibly think that was gonna, I gotta, I mean, I don't know. I've only seen the first two episodes or maybe the third one. I think I've only seen the third one. You know what it was? You know what the problem is? That the robots were actually designed by Hannibal Lecter. That's true. So like, what do you think's gonna happen? Bad things. It's clear that things are happening and characters being introduced and we don't yet know anything. But still, I was just struck by how it's all driven by narrative and story. And there's all these implied things, like programming, the programming interface is talking to them about what's going on in their heads. Which is both, I mean, artistically, it's probably useful to film it that way. But think about how it would work in real life. It just seems very creative. But there was, we saw in the second episode, there's a screen, you could see things. They were wearing like Kubrick's. It was quite interesting to just kind of ask this question so far. I mean, I assume it veers off into Never Neverland at some point. But we don't know. We can't answer that question. I'm also a fan of a guy named Alex Garland. He's a director of Ex Machina. And he is the first, I wonder if Kubrick was like this, actually. Is he studies what would it take to program an AI system? Like he's curious enough to go into that direction. On the Westworld side, I felt there was more emphasis on the narratives than actually asking computer science questions. Like, how would you build this? How would you, and how would you debug it? I still think, to me, that's the key issue. They were terrible debuggers. Yeah, well, they said specifically, so we make a change and we put it out in the world. And that's bad because something terrible could happen. Like, if you're putting things out in the world and you're not sure whether something terrible is going to happen, your process is probably flawed. I just feel like there should have been someone whose sole job it was to walk around and poke his head in and say, what could possibly go wrong? Just over and over again. I would have loved if there was an, and I did watch a lot more, I'm not giving anything away. I would have loved it if there was like an episode where like the new intern is like debugging a new model or something. And like, it just keeps failing and they're like, all right. And then it's more turns into like an episode of Silicon Valley or something like that. Versus like this ominous AI systems that are constantly like threatening the fabric of this world that's been created. Yeah. Yeah, and you know, this reminds me of something that, so I agree with that, that actually would be very cool, at least for the small percentage of people who care about debugging systems. But the other thing is- Debugging the series. Yeah, it falls into, think of the sequels, fear of the debugging. Oh my gosh. And anyway, so- It's a nightmare show. It's a horror movie. I think that's where we lose people, by the way, early on is the people who either decide, either figure out debugging or think debugging is terrible. This is part of the struggle. Where we lose people in computer science. This is part of the struggle versus suffering, right? You get through it and you kind of get the skills of it, or you're just like, this is dumb and this is a dumb way to do anything. And I think that's when we lose people. But, well, I'll leave it at that. But I think that there's something really, really neat about framing it that way. But what I don't like about all of these things, and I love Dex Machina, by the way, I love that the ending was very depressing. One of the things I have to talk to Alex about, he says that the thing that nobody noticed he put in is at the end, spoiler alert, the robot turns and looks at the camera and smiles briefly. And to him, he thought that his definition of passing the general version of the Turing test, or the consciousness test, is smiling for no one. It's like the Chinese room kind of experiment. It's not always trying to act for others, but just on your own, being able to have a relationship with the actual experience and just take it in. I don't know, he said nobody noticed the magic of it. I have this vague feeling that I remember the smile, but now you've just put the memory in my head, so probably not. But I do think that that's interesting. Although by looking at the camera, you are smiling for the audience, right? You're breaking the fourth wall. I mean, well, that's a limitation of the medium, but I like that idea. But here's the problem I have with all of those movies, all of them, is that, but I know why it's this way, and I enjoy those movies, and Westworld, is it sets up the problem of AI as succeeding and then having something we cannot control. But it's not the bad part of AI. The bad part of AI is the stuff we're living through now, right? It's using the data to make decisions that are terrible. It's not the intelligence that's going to go out there and surpass us and take over the world or lock us into a room to starve to death slowly over multiple days. It's instead the tools that we're building that are allowing us to make the terrible decisions we would have less efficiently made before, right? You know, computers are very good at making us more efficient, including being more efficient at doing terrible things. And that's the part of the AI we have to worry about. It's not the true intelligence that we're going to build sometime in the future, probably long after we're around. But, you know, I just think that whole framing of it sort of misses the point, even though it is inspiring. And I was inspired by those ideas, right? I got into this in part because I wanted to build something like that. Philosophical questions are interesting to me, but that's not where the terror comes from. The terror comes from the everyday. LUCAS MIRELLIS And you can construct situations in the subtlety of the interaction between AI and the human, like with social networks, all the stuff you're doing with interactive artificial intelligence. But, you know, I feel like Cal 9000 came a little bit closer to that in 2001 Space Odyssey, because it felt like a personal assistant. You know, it felt like closer to the AI systems we have today and the real things we might actually encounter, which is over-relying in some fundamental way on our dumb assistants or on social networks, like over-offloading too much of us onto things that require internet and power and so on, and thereby becoming powerless as a standalone entity. And then when that thing starts to misbehave in some subtle way, it creates a lot of problems. And those problems are dramatized when you're in space, because you don't have a way to walk away. DAVE SHIRAZI Well, as the man said, once we started making the decisions for you, it stopped being your world, right? That's the matrix, Michael, in case you don't remember. But on the other hand, I could say no, because isn't that what we do with people anyway? You know, this kind of the shared intelligence that is humanity is relying on other people constantly to, I mean, we hyper-specialize, right? As individuals, we're still generally intelligent. We make our own decisions in a lot of ways, but we leave most of this up to other people, and that's perfectly fine. And by the way, everyone doesn't necessarily share our goals. Sometimes they seem to be quite against us. Sometimes we make decisions that others would see as against our own interests, and yet we somehow manage it, manage to survive. I'm not entirely sure why an AI would actually make that worse, or even different, really. LUKE DENNEN You mentioned the matrix. Do you think we're living in a simulation? SIMON It does feel like a thought game more than a real scientific question. LUKE DENNEN Well, I'll tell you why I think it's an interesting thought experiment, see what you think. From a computer science perspective, it's a good experiment of how difficult would it be to create a sufficiently realistic world that us humans would enjoy being in. That's almost like a competition. SIMON I mean, if we're living in a simulation, then I don't believe that we were put in a simulation. I believe that it's just physics playing out, and we came out of that. I don't think... LUKE DENNEN So you think you have to build the universe? SIMON I think that the universe itself, we can think of that as a simulation. And in fact, sometimes I try to think about, to understand what it's like for a computer to start to think about the world. I try to think about the world, things like quantum mechanics, where it doesn't feel very natural to me at all. And it really strikes me as, I don't understand this thing that we're living in. There's weird things happening in it that don't feel natural to me at all. Now, if you want to call that the result of a simulator, okay, I'm fine with that. But like I don't... LUKE DENNEN There's the bugs in the simulation. SIMON There's the bugs. I mean, the interesting thing about simulation is that it might have bugs. I mean, that's the thing that I... LUKE DENNEN But there wouldn't be bugs for the people in the simulation. That's just reality. They're not bugs. SIMON Unless you were aware enough to know that there was a bug. But I think... LUKE DENNEN Back to the matrix. SIMON Yeah, the way you put the question... LUKE DENNEN I don't think that we live in a simulation created for us. Okay, I would say that. SIMON I think that's interesting. I've actually never thought about it that way. I mean, the way you asked the question, though, is could you create a world that is enough for us humans? It's an interestingly sort of self-referential question because the beings that created the simulation probably have not created a simulation that's realistic for them. But we're in the simulation, and so it's realistic for us. So we could create a simulation that is fine for the people in the simulation, as it were, that would not necessarily be fine for us as the creators of the simulation. LUKE DENNEN But, well, you can forget. I mean, if you play video games and virtual reality, you can, if there was some suspension of disbelief or whatever... SIMON Yeah. LUKE DENNEN...you... SIMON It becomes a world. LUKE DENNEN It becomes a world. Even like in brief moments, you forget that another world exists. I mean, that's what good stories do. They pull you in. The question is, is it possible to pull... You know, our brains are limited. Is it possible to pull the brain in to where we actually stay in that world longer and longer and longer and longer? And like, not only that, but we don't want to leave. And so, especially, this is the key thing about the developing brain, is if we journey into that world early on in life, often. SIMON How would you even know? Yeah. LUKE DENNEN Yeah. So I... But like, from a video game design perspective, from a Westworld perspective, it's... I think it's an important thing for even computer scientists to think about, because it's clear that video games are getting much better. And virtual reality, although it's been ups and downs, just like artificial intelligence, it feels like virtual reality will be here in a very impressive form if we were to fast forward 100 years into the future in a way that might change society fundamentally. Like, if I were to... I'm very limited in predicting the future, as all of us are. But if I were to try to predict, like, in which way I'd be surprised to see the world 100 years from now, it'd be that... or impressed, it'd be that we're all no longer living in this physical world, that we're all living in a virtual world. SIMON You really need to read Calculating God by Sawyer. It's a... he'll read it in a night. It's a very easy read, but it's a... I was assuming you're that kind of reader, but it's a good story, and it's kind of about this, but not in a way that it appears. And I really enjoyed the thought experiment. I think it's pretty sure it's Robert Sawyer. But anyway, he's apparently Canadian's top science fiction writer, which is why the story mostly takes place in Toronto. But it's a very good sort of story that sort of imagines this. Very different kind of simulation hypothesis sort of thing from say, The Egg, for example. You know, I'm talking about the short story by the guy who did The Martian. Who wrote The Martian? You know, I'm talking about the book. STEVE Matt Damon. SIMON The book. VIKAS So we had this whole discussion that Michael doesn't partake in this exercise of reading. SIMON Yeah, he doesn't seem to like it, which seems very strange to me, considering how much he has to read. I read all the time. I used to read 10 books every week when I was in sixth grade or whatever. It was a lot of science fiction, a lot of history that I love to read. But anyway, you should read Calculating God. It's very easy to read, like I said. And I think you'll enjoy sort of the ideas that it presents. VIKAS Yeah, I think the thought experiment is quite interesting. One thing I've noticed about people growing up now, I mean, we talk about social media, but video games is a much bigger, bigger and bigger and bigger part of their lives. And the video games have become much more realistic. I think it's possible that the three of us are not, maybe the two of you are not familiar exactly with the numbers we're talking about here. The number of people. SIMON It's bigger than movies, right? It's huge. I used to do a lot of the narrative, computational narrative stuff. STEVE I understand that economists can actually see the impact of video games on the labor market, that there's fewer young men of a certain age participating in like paying jobs than you'd expect. And that they trace it back to video games. VIKAS I mean, the problem with Star Trek was not warp drive or teleportation. It was the holodeck. Like if you have the holodeck, that's it. That's it. You go in the holodeck, you never come out. I mean, it just never made, once I saw that, I thought, okay, well, so this is the end of humanity as we know it, right? They've invented the holodeck. SIMON Because that feels like the singularity, not some AGI or whatever. It's some possibility to go into another world that can be artificially made better than this one. VIKAS And slowing it down so you live forever, or speeding it up so you appear to live forever, or making the decision of when to die. SIMON And then most of us will just be old people on the porch yelling at the kids these days in their virtual reality worlds. VIKAS But they won't hear us because they've got headphones on. SIMON So, I mean, rewinding back to MOOCs, is there lessons that you've, speaking to kids these days? VIKAS There you go. That was a transition. SIMON I'll fix it in post. VIKAS That's Charles's favorite phrase. SIMON Fix it in post. VIKAS Fix it in post. CHARLES Fix it in post. We said all, when we were recording, all the time, whenever the editor didn't like something or whatever, I would say, well, fix it in post. He hated that. SIMON Yeah. VIKAS He hated that more than anything. CHARLES Because it was Charles's way of saying, I'm not going to do it again. SIMON You know, you're on your own for this one. VIKAS But it always got fixed in post. SIMON Exactly. So is there something you've learned about, I mean, it's interesting to talk about MOOCs. Is there something you've learned about the process of education, about thinking about the present? I think there's two lines of conversation to be had here, is the future of education in general that you've learned about, and more presciently, is the education in the times of COVID. CHARLES Yeah. The second thing in some ways matters more than the first, for at least in my head, not just because it's happening now, but because I think it's reminded us of a lot of things. Coincidentally, today, there's an article out by a good friend of mine, who's also a professor at Georgia Tech, but more importantly, a writer and editor at The Atlantic, I mean, Ian Bogos. And the title is something like, Americans Will Sacrifice Anything for the College Experience. And it's about why we went back to college, and why people wanted us to go back to college. And it's not, you know, greedy presidents trying to get the last dollar from someone. It's because they want to go to college. And what they're paying for is not the classes. What they're paying for is the college experience. It's not the education, it's being there. I've believed this for a long time, that we continually make this mistake of, people want to go back to college as being people want to go back to class. They don't, they want to go back to campus. They want to move away from home. They want to do all those things that people experience. It's a rite of passage. It's an identity, if I can steal some of Ian's words here. And I think that's right. And I think what we've learned through COVID is, it has made it, the disaggregation was not the disaggregation of the education from the place, the university place, and that you can get the best anywhere you want to, in terms of there's lots of reasons why that is not necessarily true. The disaggregation is having it shoved in our faces that the reason to go, again, that the reason to go to college is not necessarily to learn. It's to have the college experience. And that's very difficult for us to accept, even though we behaved that way, most of us, when we were undergrads. A lot of us didn't go to every single class. We learned and we got it and we look back on it and we're happy we had the learning experience as well, obviously, particularly us, because this is the kind of thing that we do in our lives. The thing that we do, and my guess is that's true of the vast majority of your audience. But that doesn't mean the, I'm standing in front of you telling you this, is the thing that people are excited about. And that's why they want to be there, primarily why they want to be there. So to me, that's what COVID has forced us to deal with, even though I think we're still all in deep denial about it, and hoping that it'll go back to that. And I think about 85% of it will. We'll be able to pretend that that's really the way it is. Again, and we'll forget the lessons of this. But technically what will come out of it, or technologically will come out of it, is a way of providing a more dispersed experience through online education and these kinds of remote things that we've learned. And we'll have to come up with new ways to engage them in the experience of college, which includes not just the parties or the whatever kids do, but the learning part of it, so that they actually come out four or five or six years later with having actually learned something. So I think the world will be radically different afterwards. And I think technology will matter for that, just not in the way that the people who were building the technology originally imagined it would be. And I think this would have been true even without COVID, but COVID has accelerated that reality. So it's happening in two or three years or five years, as opposed to 10 or 15. That was an amazing answer that I did not understand. It was passionate and meaningful. Shots fired. But I don't know. I just didn't, no, I'm not trying to criticize it. I think I'm, I don't think I'm getting it. So you mentioned disaggregation. So what's that? Well, so, you know, the power of technology that if you go on the West coast and hang out long enough, it's all about, we're going to disaggregate these things together. The books from the bookstore, you know, that kind of a thing. And then suddenly Amazon controls the universe, right? And technology is a disruptor, right? And people have been predicting that for higher education for a long time, but certainly in the age of MOOCs. So is this the sort of idea like students can aggregate on a campus someplace and then take classes over the network anywhere? Yeah, this is what people thought was going to happen, or at least people claimed it was going to happen, right? That, you know, Because my daughter is essentially doing that now. She's on one campus, but learning in a different campus. Sure. And COVID makes that possible, right? COVID makes that legal, all but avoidable, right? But the idea originally was that, you know, you and I were going to create this machine learning class and it was going to be great. And then no one else would be the machine learning class everyone takes, right? That was never going to happen. But, you know, something like that, you can see happening. But I feel like you didn't address that. So why, why, why is it that, why? I don't think that will be the thing that happens. So the college experience, maybe I missed what the college experience was. I thought it was peers, like people hanging around. A large part of it is peers. Well, it's peers and independence. Yeah, but you can do classes online for all of that. No, no, no, no, no. Because we're social people, right? So you want to be in the same room. That also has to be part of an experience. It's in a context and the context is the university. And by the way, it actually matters that Georgia Tech really is different from Brown. I see, because then students can choose the kind of experience they think is going to be best for them. Okay. I think we're giving too much agency to the students in making an informed decision. Okay. The truth, but yes, they will make choices and they will have different experiences. And some of those choices will be made for them. Some of them will be choices they're making because they think it's this, that, or the other. I just don't want to say, I don't want to give the idea. It's not homogenous. Yes, it's certainly not homogenous, right? I mean, Georgia Tech is different from Brown. Brown is different from pick your favorite state school in Iowa, Iowa State. Okay. Which I guess is my favorite state school in Iowa. Sure. But these are all different. They have different contexts. And a lot of those contexts are, they're about history. Yes. But they're also about the location of where you are. They're about the larger group of people who are around you, whether you're in Athens, Georgia, and you're basically the only thing that's there as a university, you're responsible for all the jobs, or whether you're at Georgia State University, which is an urban campus, where you're surrounded by 6 million people, and your campus where it ends and begins in the city, ends and begins, we don't know. It actually matters, whether you're a small campus or a large campus. Why is it that if you go to Georgia Tech, you're forever proud of that? And you say that to people at dinner, like bars and whatever. And if you get a degree at an online university somewhere, you don't, that's not a thing that comes up at a bar. Well, it's funny you say that. So the students who take our online master's, by several measures, are more loyal than the students who come on campus, certainly for the master's degree. The reason for that, I think, and you'd have to ask them, but based on my conversations with them, I feel comfortable saying this, is because this didn't exist before. I mean, we talk about this online master's and that it's reaching 11,000 students, and that's an amazing thing. And we're admitting everyone we believe who can succeed. We've got a 60% acceptance rate. It's amazing, right? It's also a $6,600 degree. The entire degree costs $6,600 or $7,000, depending on how long you take, dollar degree, as opposed to the $46,000 it costs you to come on campus. So that feels, and I can do it while I'm working full time, and I've got a family and a mortgage and all these other things. So it's an opportunity to do something you wanted to do, but you didn't think was possible. Without giving up two years of your life, as well as all the money and everything else in the life that you had built. So I think we created something that's had an impact, but importantly, we gave a set of people opportunities they otherwise didn't feel they had. So I think people feel very loyal about that. And my biggest piece of evidence for that, besides the surveys, is that we have somewhere north of 80 students, might be 100 at this point, who graduated but come back in TA for this class for basically minimum wage. Even though they're working full time, because they believe in sort of having that opportunity, and they want to be a part of something. Now, will generation three feel this way? 15 years from now, will people have that same sense? I don't know. But right now, they kind of do. And so it's not the online, it's a matter of feeling as if you're a part of something. We're all very tribal. Yeah. Right? And I think there's something very tribal about being a part of something like that. Being on campus makes that easier, going through a shared experience makes that easier. It's harder to have that shared experience if you're alone looking at a computer screen. We can create ways to make that true. But is it possible? It is possible. The question is, it still is the intuition to me, and it was at the beginning when I saw something like the online master's program, is that this is going to replace universities. No, it won't replace universities. But like, why? Because it's living in a different part of the ecosystem. The people who are taking it are already adults. They've gone through their undergrad experience. I think their goals have shifted from when they were 17. They have other things that are going on. Right. But it does do something really important, something very social and very important. Right? You know this whole thing about, don't build the sidewalks, just leave the grass and the students will, or the people will walk and you put the sidewalks where they create paths, this kind of thing. That's interesting, yeah. They're architects who apparently believe that's the right way to do things. The metaphor here is that we created this environment. We didn't quite know how to think about the social aspect, but we didn't have time to solve all, do all the social engineering. Right? The students did it themselves. They created these groups, like on Google+. There were like 30-something groups created in the first year because somebody had used Google+. And they created these groups and they divided up in ways that made sense. We live in the same state or we're working on the same thing. We have the same background or whatever, and they created these social things. We sent them t-shirts and we have all these great pictures of students putting on their t-shirts as they travel around the world. I climbed this mountaintop, I'm putting this t-shirt on, I'm a part of this. They were a part of them. They created the social environment on top of the social network and the social media that existed to create this sense of belonging and being a part of something. They found a way to do it, right? And I think that other, it scratched an itch. It scratched an itch that they had, but they had scratched some of that itch that might have required they be physically in the same place long before. So I think, yes, it's possible, and it's more than possible, it's necessary. But I don't think it's going to replace the university as we know it. The university as we know it will change. But there's just a lot of power in the kind of rite of passage kind of going off to yourself. Now, maybe there'll be some other rite of passage that'll happen. Right, that's the question. That'll drive you somewhere else. You can separate, so the university is such a fascinating mess of things. So just even the faculty position is a fascinating mess. Like, it doesn't make any sense. It's stabilized itself. But why are the world-class researchers spending a huge amount of time, of their time teaching and service? Like, you're doing like three jobs. Yeah. And I mean, it turns, it's maybe an accident of history or human evolution, I don't know. It seems like the people who are really good at teaching are often really good at research. There seems to be a parallel there. But like, it doesn't make any sense that you should be doing that. At the same time, it also doesn't seem to make sense that your place where you party is the same place where you go to learn calculus or whatever. But it's a safe space. A safe space for everything. Yeah, relatively speaking, it's a safe space. Now, by the way, I feel the need very strongly to point out that we are living in a very particular weird bubble, right? Most people don't go to college. And by the way, the ones who do go to college, they're not 18 years old, right? They're like 25 or something. I forget the numbers. You know, the places where we've been, where we are, they look like whatever we think the traditional movie version of universities are. But for most people, it's not that way at all. By the way, most people who drop out of college, it's entirely for financial reasons, right? So, you know, we're talking about a particular experience. And so for that set of people, which is very small, but larger than it was a decade or two or three or four, certainly ago, I don't think that will change. My concern, which I think is kind of implicit in some of these questions, is that somehow we will divide the world up further into the people who get to have this experience and get to have the network and they sort of benefit from it and everyone else while increasingly requiring that they have more and more credentials in order to get a job as a barista, right? You got to have a master's degree in order to work at Starbucks. We're going to force people to do these things, but they're not going to get to have that experience. And there'll be a small group of people who do continue to, you know, positive feedback, et cetera, et cetera, et cetera. I worry a lot about that, which is why for me, and by the way, here's an answer to your question about faculty, which is why to me that you have to focus on access and the mission. I think the reason, whether it's good, bad or strange, I mean, I agree it's strange, but I think it's useful to have the faculty member, particularly at large R1 universities where we've all had experiences, that you tie what they get to do and with the fundamental mission of the university and let the mission drive. What I hear when I talk to faculty is they love their PhD students because they're creating, they're reproducing basically, right? And it lets them do their research and multiply. But they understand that the mission is the undergrads. And so they will do it without complaint mostly because it's a part of the mission and why they're here. And they have experiences with it themselves. And it was important to get them where they were going. The people who tend to get squeezed in that, by the way, are the master's students, right? Who are neither the PhDs who are like us nor the undergrads we have already bought into the idea that we have to teach though. That's increasingly changing. Anyway, I think tying that mission in really matters. And it gives you a way to unify people around making it an actual higher calling. Education feels like more of a higher calling to me than even research. Because education, you cannot treat it as a hobby if you're going to do it well. But that's the pushback on this whole system is that you should, education be a full-time job, right? And like, it almost like research is a distraction from that. Yes, although I think most of our colleagues, many of our colleagues would say that research is the job and education is the distraction. Right. But that's the beautiful dance. It seems to be that that tension in itself seems to work, seems to bring out the best in the faculty. I would like to know. But I will point out two things. One thing I'm going to point out and the other thing I want Michael to point out because I think Michael is much closer to the sort of the ideal professor in some sense than I am. Well, he is the dean. You're the platonic sense of a professor. I don't know what he meant by that, but he is a dean, so he has a different experience. I'm giving him time to think of the profound thing he's going to say. That's good. But let me point this out, which is that we have lecturers in the College of Computing where I am. There's 10 or 12 of them depending on how you count as opposed to the 90 or so tenure track faculty. Those 10 lecturers who only teach, well, they don't only teach, they also do service. Some of them do research as well, but primarily they teach. They teach 50 percent, over 50 percent of our credit hours. And we teach everybody. So they're doing not just, they're doing more than eight times the work of the tenure track faculty, just closer to nine or 10. And that's including our grad courses. So they're doing this. They're teaching more. They're touching more than anyone. And they're beloved for it. So we recently had a survey. We do these alumni, everyone does these alumni surveys. You hire someone from the outside to do whatever. And I was really struck by something. You saw all these really cool numbers. I'm not going to talk about it because it's all internal confidential stuff. But one thing I will talk about is there was a single question we asked our alumni. These are people who graduated, born in the 30s and 40s, all the way up to people who graduated last week, right? Well, last semester. Okay, good. Time flies. Yeah, time flies. And there was a question. Name a single person who had a strong, positive impact on you, something like that. I think it was special impact. Yeah, special impact on you. And then, so they got all the answers from people and they created a word cloud. Those clear word cloud created by people who don't do word clouds for a living because they had one person whose name like appeared like nine different times, like Philip, Phil, Dr. Phil, you know, but whatever. But they got all this. And I looked at it and I noticed something really cool. The five people from the College of Computing I recognized were in that cloud. And four of them were lecturers, the people who teach. Two of them relatively modern. Both were chairs of our division of computing instruction. One just one retired, one is going to retire soon. And the other two were lecturers I remembered from the 1980s. Two of those four actually have- By the way, the fifth person was Charles. That's not important. The thing is, I don't tell people that, but the two of those people are teaching awards are named after. Thank you, Michael. Two of those are teaching awards are named after, right? So when you ask students, alumni, people who are now 60, 70 years old, even, you know, who touched them, they say the dean of students. They say the big teachers who taught the big introductory classes that got me into it. There's a guy named Richard Park who's on there who's, you know, who's known as a great teacher. The Phil Adler guy who I probably just said his last name wrong, but I know the first name's Phil because it kept showing up over and over again. It's famous- Adler is what it said. Okay, good. But different people spelled it differently. So he appeared multiple times. Right. So he was clearly, he was a professor in the business school. But when you read about him, I went to read about him because I was curious who he was, you know, it's all about his teaching and the students that he touched, right? So whatever it is that we're doing and we think we're doing that's important or why we think the universities function, the people who go through it, they remember the people who were kind to them, the people who taught them something, and they do remember it. They remember it later. I think that's important. That's what the mission matters. Yeah. Not to completely lose track of the fundamental problem of how do we replace the party aspect of universities. That's right, before we go to what makes the platonic professor, do you think, like, what in your sense is the role of MOOCs in this whole picture during COVID? Like, are we, should we desperately be clamoring to get back on campus? Or is this a stable place to be for a little while? I don't know. I know that the online teaching experience and learning experience has been really rough. I think that people find it to be a struggle in a way that's not a happy, positive struggle, that when you got through it, you just feel like glad that it's over as opposed to I've achieved something. So, you know, I worry about that. But, you know, I worry about just even before this happened, I worry about lecture teaching as how well is that actually really working as far as a way to do education, as a way to inspire people. I mean, all the data that I'm aware of seems to indicate, and this kind of fits, I think, with Charles's story, is that people respond to connection, right? They actually feel, if they feel connected to the person teaching the class, they're more likely to go along with it. They're more able to retain information. They're more motivated to be involved in the class in some way. And that really matters. People- You mean to the human themselves? Yeah. So, can't you do that actually perhaps more effectively online? Like you mentioned science communication. So, I literally, I think, learned linear algebra from Gilbert Strang by watching MIT OpenCourseWare when I was in track. And he was a personality, he was a bit like a tiny- in this tiny little world of math, he's a bit of a rock star, right? So, you kind of look up to that person. Can't that replace the in-person education? It can help. I will point out something. I can't share the numbers, but we have surveyed our students, and even though they have feelings about what I would interpret as connection, I like that word, in the different modes of classrooms, there's no difference between how well they think they're learning. For them, the thing that makes them unhappy is the situation they're in. And I think the last lack of connection, it's not whether they're learning anything, they seem to think they're learning something anyway, right? In fact, they seem to think they're learning it equally well, presumably because the faculty are putting in, or the instructors, more generally speaking, are putting in the energy and effort to try to make certain that what they've curated can be expressed to them in a useful way. But the connection is missing. And so, there's huge differences in what they prefer. And as far as I can tell, what they prefer is more connection, not less. That connection just doesn't have to be physically in a classroom. I mean, look, I used to teach 348 students in my machine learning class on campus. Do you know why? That was the biggest classroom on campus. They're sitting in theater seats. I'm literally on a stage looking down on them and talking to them, right? There's no, I mean, we're not sitting down having a one-on-one conversation, reading each other's body language, trying to communicate and going, we're not doing any of that. So, if you're past the third row, it might as well be online anyway, is the kind of thing that people have said. Daphne has actually said some version of this, that online starts on the third row or something like that. And I think that's not, yeah, I like it. I think it captures something important. But people still came, by the way. Even the people who had access to our material would still come to class. I mean, there's a certain element about looking to the person next to you. Yeah. It's just like their presence there, their boredom, and like when the parts are boring, and their excitement when the parts are exciting. Like in sharing in that, like unspoken kind of, yeah, communication. Like in part, the connection is with the other people in the room. Yeah. Watching the circus on TV alone, it is not really. Ever been to a movie theater and been the only one there at a comedy? It's not as funny as when you're in a room full of people all laughing. Well, you need, maybe you need just another person. It's like, as opposed to many. Maybe there's some kind of- Well, there's different kinds of connections. There's different kinds of connection, right. And there's different kinds of comedy. Well, in the sense that- As we're learning today. I wasn't sure if that was going to land. But just the idea that different jokes, I've now done a little bit of standup. And so different jokes work in different size crowds too. No, it's true. Where sometimes if it's a big enough crowd, then even a really subtle joke can take root someplace, and then that cues other people. And it kind of, there's a whole statistics of, I did this terrible thing to my brother. So when I was really young, I decided that my brother was only laughing as it comes when I laughed. But he was taking cues from me. So I purposely didn't laugh just to see if I was right. And did you laugh at non-funny things? Yes. You had really want to do both sides. I did both sides. And at the end of it, I told him what I did. Oh, that's so- He was very upset about this. Yeah. And from that day on- He lost his sense of humor. No, no, no, no. Well, yes, but from that day on, he laughed on his own. He stopped taking cues from me. I see. So I want to say that it was a good thing that I did. Yes, yes. You saved that man's life. Yes, but it was mostly mean, but it's true though. It's true, right? That people, I think you're right. But okay, so where does that get us? That gets us the idea that, I mean, certainly movie theaters are a thing, right? Where people like to be watching together, even though the people on the screen aren't really co-present with the people in the audience. The audience is co-present with itself. By the way, on that point, it's an open question that's being raised by this, whether movies will no longer be a thing because Netflix's audience is growing. So it's a very parallel question for education. Will movie theaters still be a thing in 2021? No, but I think the argument is that there is a feeling of being in the crowd that isn't replicated by being at home watching it, and that there's value in that. And then I think just- But? It scales better online. But I feel like we're having a conversation about whether concerts will still exist after the invention of the record or the CD or wherever it is, right? They won't. You're right, concerts are dead. Well, okay, I think the joke is only funny if you say it before now. Right, yeah, that's true. We'll fix it in post. Like three years ago, it's like, well, no, obviously, concerts are still a thing. I'll wait to publish this until we have a vaccine. You know, we'll fix it in post. But I think the important thing is- Fix the virus, post. Concerts changed, right? Concerts changed. First of all, movie theaters weren't this way, right? In like the 60s and 70s, they weren't like this. Like blockbusters were basically what- With Jaws and Star Wars created blockbusters, right? Before then, there weren't. Like the whole shared summer experience didn't exist in our lifetimes, right? Certainly you were well into adulthood by the time this was true, right? So it's just a very different- It's very different. So what we've been experiencing in the last 10 years is not like the majority of human history. But more importantly, concerts, right? Concerts mean something different. Most people don't go to concerts anymore. Like there's an age where you care about it. You sort of stop doing it, but you keep listening to music or whatever and da da da da da da. So I think that's a painful way of saying that it will change. It's not the same thing as a going away. Replace is too strong of a word. But it will change. It has to. I actually like to push back. I wonder because I think you're probably just throwing that your intuition out. It's possible that concerts, more people go to concerts now, but obviously much more people listen to- Well, this is dumb. Than before there was records. It's possible to argue that if you look at the data, that it just expanded the pie of what music listening means. So it's possible that universities grow in the parallel or the theaters grow, but also more people get to watch movies, more people get to be educated. I hope that is true. Yeah, and to the extent that we can grow the pie and have education be not just something you do for four years when you're done with your other education, but it be a more lifelong thing, that would have tremendous benefits, especially as the economy and the world change rapidly. People need opportunities to stay abreast of these changes. And so, I don't know, that's all part of the ecosystem. It's all to the good. I'm not going to have an argument about whether we lost fidelity when we went from Laserdisc to DVDs or record players to CDs. I'm willing to grant that that is true, but convenience matters. And the ability to do something that you couldn't do otherwise because that convenience matters. And you can tell me I'm only getting 90% of the experience, but I'm getting the experience. I wasn't getting it before or it wasn't lasting as long or it wasn't as easy. I mean, this just seems straightforward to me. It's going to change. It is for the good that more people get access. And it is our job to do two separate things. One, to educate them and make access available. That's our mission. But also for very simple, selfish reasons, we need to figure out how to do it better so that we individually stay in business. We can do both of those things at the same time. They are not in, they may be intention, but they are not mutually exclusive. P.A. So you've educated some scary number of people. A.M. Mm-hmm. So you've seen a lot of people succeed, find their path through life. Is there advice that you can give to a young person today about computer science education, about education in general, about life, about whatever the journey that one takes in their, maybe in their teens, in their early 20s, sort of in those underground years, as you try to go through the essential process of partying and not going to classes, and yet somehow trying to get a degree? P.A. If you get to the point where you're far enough up in the hierarchy of needs that you can actually make decisions like this, then find the thing that you're passionate about and pursue it. And sometimes it's the thing that drives your life, and sometimes it's secondary. And you'll do other things because you've got to eat, right? You've got a family, you've got to feed, you've got people you have to help, or whatever. And I understand that, and it's not easy for everyone. But always take a moment or two to pursue the things that you love, the things that bring passion and happiness to your life. And if you don't, I know that sounds corny, but I genuinely believe it. And if you don't have such a thing, then you're lying to yourself. You have such a thing. You just have to find it. And it's okay if it takes you a long time to get there. Rodney Dangerfield became a comedian in his 50s, I think. It certainly wasn't his 20s. And lots of people failed for a very long time before getting to where they were going. You know, I try to have hope. And it wasn't obvious. I mean, you and I talked about the experience that I had a long time ago with a particular police officer. It wasn't my first one, and it wasn't my last one. But in my view, I wasn't supposed to be here after that, and I'm here. So it's all gravy. So you might as well go ahead and grab life as you can because of that. That's sort of how I see it. While recognizing, again, the delusion matters, right? Allow yourself to be deluded, allow yourself to believe that it's all going to work out. Just don't be so deluded that you miss the obvious. And you're going to be fine. It's going to be there. It's going to be there. It's going to work out. What do you think? I like to say choose your parents wisely because that has a big impact on your life. It's going to be different. Yeah. I mean, there's a whole lot of things that you don't get to pick. And whether you get to have one kind of life or a different kind of life can depend a lot on things out of your control. But I really do believe in the passion and excitement thing. I was talking to my mom on the phone the other day, and essentially what came out is that computer science is really popular right now. And I get to be a professor teaching something that's very attractive to people. And she was like trying to give me some appreciation for how foresightful I was for choosing this line of work, as if somehow I knew that this is what was going to happen in 2020. But that's not how it went for me at all. Like I studied computer science because I was just interested. It was just so interesting to me. I didn't think it would be particularly lucrative. Yeah. And I've done everything I can to keep it as un-lucrative as possible. Yeah. Some of my friends and colleagues have not done that. And I pride myself on my ability to remain un-rich. But I do believe that, like I'm glad. I mean, I'm glad that it worked out for me. It could have been like, oh, what I was really fascinated by is this particular thing. What I was fascinated by is this particular kind of engraving that nobody cares about. But so I got lucky. And the thing that I cared about happened to be a thing that other people eventually cared about. But I don't think I would have had a fun time choosing anything else. Like this was the thing that kept me interested and engaged. Well, one thing that people tell me, especially around early undergraduate, and the internet is part of the problem here, is they say they're passionate about so many things. How do I choose a thing, which is a harder thing for me to know what to do with. Is there any? I mean, don't you know what you, I mean, you know, look. A long time ago, I walked down a hallway and I took a left turn. Yeah. I could have taken a right turn. And my world could be better or it could be worse. I have no idea. I have no way of knowing. Is there anything about this particular hallway that's relevant? Or you're just in general choices? Yeah, you were on the left. It sounds like you regret not taking the right turn. Oh, no, not at all. You brought it up. Well, because there was a turn there. On the left was Michael Dimmon's office, right? I mean, these sorts of things happen, right? Yes. But here's the thing. On the right, by the way, there was just a blank wall. It wasn't a huge choice. It would have really hurt. He tried first. No, but it's true, right? That, you know, I think about Ron Brockman, right? I went, I took a trip I wasn't supposed to take. And I ended up talking to Ron about this. And I ended up going down this entire path that allowed me to, I think, get tenure. But by the way, I decided to say yes to something that didn't make any sense. And I went down this educational path. But it would have been, you know, who knows, right? Maybe if I hadn't done that, I would be a billionaire right now. I'd be Elon Musk. My life could be so much better. My life could also be so much worse. You know, you just got to feel that sometimes you have decisions you're going to make. You cannot know what's going to do. You should think about it, right? Some things are clearly smarter than other things. You got to play the odds a little bit. But in the end, if you've got multiple choices, there are lots of things you think you might love. Go with the thing that you actually love, the thing that jumps out at you, and sort of pursue it for a little while. The worst thing that'll happen is you took a left turn instead of a right turn, and you ended up merely happy. Beautiful quote. So accepting, so taking the step and just accepting that don't like question, question the choice. I like to think that life is long, and there's time to actually pursue. Every once in a while, you have to put on a leather suit and make a thriller video. Every once in a while. Every once in a while, you have to put on a leather suit. If I ever get a chance again, I'm doing it. Yeah. I was told that you actually dance, but that part was edited out. I don't dance. There was a thing where we did do the zombie thing. We did do the zombie thing. That wasn't edited out. It just wasn't put into the final thing. I'm quite happy. There was a reason for that too, right? I wasn't wearing something right. There was a reason for that. I can't remember what it was. No leather suit. Is that what it was? I can't remember. Anyway, the right thing happened. Exactly. You took the left turn and it ended up being the right thing. So a lot of people ask me that are a little bit tangential to the programming in the computing world, and they're interested to learn programming, like all kinds of disciplines that are outside of the particular discipline of computer science. What advice do you have for people that want to learn how to program or want to either taste this little skill set or discipline or try to see if it can be used somehow in their own life? What stage of life are they in? One of the magic things about the internet of the people that write me is I don't know. Because my answer is different. My daughter is taking AP Computer Science right now. Hi, Joni. She's amazing and doing amazing things. And my son's beginning to get interested, and I'll be really curious where he takes it. I think his mind actually works very well for this sort of thing, and she's doing great. But one of the things I have to tell her all the time, she points, well, I want to make a rhythm game. So I want to go for two weeks and then build a rhythm game. Show me how to build a rhythm game. And start small. Learn the building blocks and how we take the time. Have patience. Eventually, you'll build a rhythm game. I was in grad school when I suddenly woke up one day over the Royal East. And I thought, wait a minute, I'm a computer scientist. I should be able to write Pac-Man in an afternoon. And I did. Not with great graphics. It was actually a very cool game. I had to figure out how the ghost moved and everything. And I did it in an afternoon in Pascal on an old Apple IIgs. But if I had started out trying to build Pac-Man, I think it probably would have ended very poorly for me. Luckily, back then, there weren't these magical devices we call phones and software everywhere to give me this illusion that I could create something by myself from the basics inside of a weekend like that. I mean, that was a culmination of years and years and years right before I decided, oh, I should be able to write this. And I could. So my advice, if you're early on, is you've got the internet. There are lots of people there to give you the information. Find someone who cares about this. Remember, they've been doing it for a very long time. Take it slow. Learn the little pieces. Get excited about it. And then keep the big project you want to build in mind. You'll get there soon enough because, as a wise man once said, life is long. Sometimes it doesn't seem that long, but it is long. And you'll have enough time to build it all out. All the information is out there. But start small. You know, generate Fibonacci numbers. That's not exciting, but it'll get you there. One programming language. Well, there's only one programming language. It's Lisp. But if you have to pick a programming language, I guess in today's day, what would I do? I guess I'd do... Python is basically programming. Python is basically Lisp, but with better syntax. Blasphemy. Yeah. With C syntax. How about that? So you're going to argue that C syntax is better than anything? Anyway, I'm going to answer Python despite what he said. Tell your story about somebody's dissertation that had a Lisp program in it. It was so funny. This is Dave's. Dave's dissertation was like Dave McAllister, who was a professor at MIT for a while. And then he came to Bell Labs. And now he's at Technology Technical Institute of Chicago. A brilliant guy. Such an interesting guy. Anyway, his thesis, it was a theorem prover. And he decided to have as an appendix his actual code, which of course was all written in Lisp, because of course it was. It's like the last 20 pages are just right parentheses. It's just wonderful. That's programming right there. Pages upon pages of right parentheses. Anyway, Lisp is the only real language, but I understand that that's not necessarily the place where you start. Python is just fine. No. Python is good. If you're of a certain age. If you're really young and trying to figure out graphical languages that let you kind of see how the thing works, that's fine too. They're all fine. It almost doesn't matter. But there are people who spend a lot of time thinking about how to build languages that get people in. The question is, are you trying to get in and figure out what it is? Or do you already know what you want? And that's why I asked you what stage of life people are in. Because if you're different stages of life, you would attack it differently. The answer to that question of which language keeps changing, I mean, there's some value to exploring. A lot of people write to me about Julia. There's these more modern languages that keep being invented, Rust and Kotlin. There's stuff that for people who love functional languages like Lisp, apparently there's echoes of that, but much better in the modern languages. And it's worthwhile to, especially when you're learning languages, it feels like it's okay to try one that's not the popular one. Oh, yeah. But you want something simple. I think you get that way of thinking almost no matter what language. And if you push far enough, like it can be assembly language, but you need to push pretty far before you start to hit the really deep concepts that you would get sooner in other languages. But I don't know, computation is kind of computation, is kind of Turing equivalent, is kind of computation. And so it matters how you express things, but you have to build out that mental structure in your mind. And I don't think it super matters which language. I mean, it matters a little because some things are just at the wrong level of abstraction. I think assembly is at the wrong level of abstraction for someone coming in new. I think that if you start- For someone coming in new. Yes. For frameworks, big frameworks are quite a bit. You've got to get to the point where I want to learn a new language means I just pick a reference book and I think of a project and I go through it in a weekend. You got to get there. You're right though, the languages that are designed for that are, it almost doesn't matter. Pick the ones that people have built tutorials and infrastructure around to help you get kind of ease into it. Because it's hard. I mean, I did this little experiment once. I was teaching intro to CS in the summer as a favor. Which is, anyway, I was teaching- Save pleasant memories. I was teaching intro to CS as a favor and it was very funny because I'd go in every single time and I would think to myself, how am I possibly going to fill up an hour and a half talking about for loops? There wasn't enough time. It took me a while to realize this. There are only three things. There's reading from a variable, writing to a variable and conditional branching. Everything else is syntactic sugar. The syntactic sugar matters, but that's it. When I say that's it, I don't mean it's simple. I mean, it's hard. Conditional branching, loops, variable, those are really hard concepts. So you shouldn't be discouraged by this. Here's a simple experiment. I'm going to ask you a question now. You ready? X equals three. Y equals four. What is X? Three. What is Y? Four. Y equals X. I'm going to mess this up. No, it's easy. Y equals X. Y equals X. What is Y? Three. That's right. X equals seven. What is Y? That's one of the trickiest things to get for programmers, that there's a memory and the variables are pointing to a particular thing in memory. And sometimes the languages hide that from you and they bring it closer to the way you think mathematics works. Right. So in fact, Mark Guzdial, who worries about these sorts of things, or used to worry about these sorts of things anyway, had this kind of belief that actually people, when they see these statements, X equals something, Y equals something, Y equals X, that you have now made a mathematical statement that Y and X are the same. Which you can if you just put an anchor in front of it. Yes, but that's not what you're doing. I thought, and I kind of asked the question, and I think I had some evidence for this, I'm hardly a study, is that most of the people who didn't know the answer, weren't sure about the answer, they had used spreadsheets. Ah, interesting. And so it's by reference or by name really. Right. And so depending upon what you think they are, you get completely different answers. The fact that I could go, or one could go, two thirds of the way through a semester, and people still hadn't figured out in their heads, when you say Y equals X, what that meant, tells you it's actually hard. Because all those answers are possible. And in fact, when you said, oh, if you just put an ampersand in front of it, I mean, that doesn't make any sense for an intro class. And of course, a lot of languages don't even give you the ability to think about it in terms of ampersand. Do we want to have a 45 minute discussion about the difference between equal EQ and equal in Lisp? I know you do. But you know, you could do that. This is actually really hard stuff. So you shouldn't be, it's not too hard, we all do it, but you shouldn't be discouraged. It's why you should start small, so that you can figure out these things, you have the right model in your head, so that when you write the language, you can execute it and build the machine that you want to build, right? Yeah, the funny thing about programming and those very basic things is the very basics are not often made explicit, which is actually what drives everybody away from basically any discipline, but programming is just another one. Like even a simpler version of the equal sign that I kind of forget is in mathematics, equals is not assignment. Yeah. Like, I think basically every single programming language with just a few handful of exceptions equals is assignment. You have some other operator for equality. Yeah. And you know, even that, like everyone kind of knows it once you started doing it, but like you need to say that explicitly or you just realize it like yourself. Otherwise, you might be stuck for, you said like half a semester, you could be stuck for quite a long time. And I think also part of the programming is being okay in that state of confusion for a while. It's to the debugging point. It's like, I just wrote two lines of code. Why doesn't this work? And staring at that for like hours and trying to figure out, and then every once in a while, you just have to restart your computer and everything works again. And then you just kind of stare into the void with the tears slowly rolling down your eye. By the way, the fact that they didn't get this actually had no impact on, I mean, they were still able to do their assignments. Right. Because it turns out their misunderstanding wasn't being revealed to them by the problem sets we were giving them. It's pretty profound, actually, yeah. I wrote a program a long time ago, actually for my master's thesis, and in C++, I think, or C, I guess it was C. And it was all memory management and terrible. And it wouldn't work for a while. And it was clear to me that it was overwriting memory. And I just couldn't, I was like, look, I got to paper this, time for this. So I basically declared a variable at the front and the main that was like 400k, just an array. And it worked. Because wherever I was scribbling over memory, it would scribble into that space and it didn't matter. And so I never figured out what the bug was. But I did create something to sort of deal with it. To work around it. And it, you know, that's crazy. That's crazy. It was okay, because that's what I wanted. But I knew enough about memory management to go, you know, I'm just going to create an empty array here and hope that that deals with the scribbling memory problem. And it did. That takes a long time to figure out. And by the way, the language you first learned probably is garbage collection anyway, so you're not even going to come up across, you're not going to come across that problem. So we talked about the Minsky idea of hating everything you do and hating yourself. So let's end on a question that's going to make both of you very uncomfortable. Okay. Which is, what is your, Charles, what's your favorite thing that you're grateful for about Michael? And Michael, what is your favorite thing that you're grateful for about Charles? Well, that answer is actually quite simple. Charles, well, that answer is actually quite easy. His friendship. He stole the easy answer. I did. Yeah. I can tell you what I hate about Charles. He steals my good answers. The thing I like most about Charles, he sees the world in a similar enough, but different way that it's sort of like having another life. It's sort of like I get to experience things that I wouldn't otherwise get to experience because I would not naturally gravitate to them that way. And so he just, he just shows me a whole other world. It's awesome. Yeah. The inner product is not zero for sure. It's not quite one. Point seven, maybe. Just enough that you can learn. Just enough that you can learn. That's the definition of friendship. The inner product is point seven. Yeah, I think so. That's the answer to life, really. Charles sometimes believes in me when I have not believed in me. He also sometimes works as an outward confidence that he has so much confidence and self, I don't know, comfortableness. Okay, let's go with that. That I feel better a little bit. If he thinks I'm okay, then maybe I'm not as bad as I think I am. At the end of the day, luck favors the Charles. It's a huge honor to talk with you. Thank you so much for taking this time, wasting your time with me. It was an awesome conversation. You guys are an inspiration to a huge number of people and to me. So I really enjoyed this. Thanks for talking. I enjoyed it as well. Thank you so much. And by the way, if luck favors the Charles, then it's certainly the case that I've been very lucky to know you. I'm going to edit that part out. Thanks for listening to this conversation with Charles Isbell and Michael Littman. And thank you to our sponsors, Athletic Greens, Super Nutritional Drink, 8 Sleep, Self-Cooling Mattress, Masterclass Online Courses from some of the most amazing humans in history, and Cash App, the app I use to send money to friends. Please check out the sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support it on Patreon, or connect with me on Twitter, Alex Friedman. And now let me leave you with some words from Desmond Tutu. Don't raise your voice. Improve your argument. Thank you for listening, and hope to see you next time.

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Eric Weinstein: Geometric Unity and the Call for New Ideas & Institutions | Lex Fridman Podcast #88

The following is a conversation with Eric Weinstein, the second time we've spoken on this podcast. He's a mathematician with a bold and piercing intelligence, unafraid to explore the biggest questions in the universe and shine a light on the darkest corners of our society. He's the host of the Portal podcast, a part of which he recently released his 2013 Oxford lecture on his theory of geometric unity that is at the center of his lifelong efforts to arrive at a theory of everything that unifies the fundamental laws of physics. This conversation was recorded recently in the time of the coronavirus pandemic. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong, we're in this together, we'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of the fractional orders is an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction of the stock market, making trading more accessible to new investors and diversification much easier. So again, if you get Cash App from the App Store or Google Play and use code LEXPODCAST, you get $10 and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Eric Weinstein. Do you see a connection between World War II and the crisis we're living through right now? Sure. The need for collective action, reminding ourselves of the fact that all of these abstractions, like everyone should just do exactly what he or she wants to do for himself and leave everyone else alone, none of these abstractions work in a global crisis. And this is just a reminder that we didn't somehow put all that behind us. When I hear stories about my grandfather who was in the Army and so the Soviet Union where most people die when you're in the Army, there's a brotherhood that happens, there's a love that happens. Do you think that's something we're gonna see here? A sense of community? Well, we're not there. I mean, what the Soviet Union went through. I mean, the enormity of the war on the Russian doorstep, this is different. What we're going through now is not, we can't talk about Stalingrad and COVID in the same breath yet. We're not ready. And the sort of, you know, the sense of like the great patriotic war and the way in which I was very moved by the Soviet custom of newlyweds going and visiting war memorials on their wedding day, like the happiest day of your life you have to say, thank you to the people who made it possible. We're not there. We're just restarting history. I've called this, on the Rogan program, I called it the great nap. The 75 years with very little by historical standards in terms of really profound disruption. And so. When you call it the great nap, meaning lack of deep global tragedy. Well, lack of realized global tragedy. So I think that the development, for example, of the hydrogen bomb, you know, was something that happened during the great nap. And that doesn't mean that people who lived during that time didn't feel fear, didn't know anxiety, but it was to say that most of the violent potential of the human species was not realized. It was in the form of potential energy. And this is the thing that I've sort of taken issue with, with the description of Steven Pinker's optimism, is that if you look at the realized kinetic variables, things have been getting much better for a long time, which is the great nap. But it's not as if our fragility has not grown, our dependence on electronic systems, our vulnerability to disruption. And so all sorts of things have gotten much better. Other things have gotten much worse. And the destructive potential has skyrocketed. Is tragedy the only way we wake up from the big nap? Well, no, you could also have jubilation about positive things, but it's harder to get people's attention. Can you give an example of a big global positive thing that could happen? I think that when, for example, just historically speaking, HIV went from being a death sentence to something that people could live with for a very long period of time, it would be great if that had happened on a Wednesday, right? Like all at once, like you knew that things had changed. And so the bleed in somewhat kills the sort of the Wednesday effect where it all happens on a particular day at a particular moment. I think if you look at the stock market here, there's a very clear moment where you can see that the market absorbs the idea of the coronavirus. I think that with respect to positives, the moon landing was the best example of a positive that happened at a particular time or recapitulating the Soviet American link up in terms of Skylab and Soyuz, right? Like that was a huge moment when you actually had these two nations connecting in orbit. And so, yeah, there are great moments where something beautiful and wonderful and amazing happens, but it's just, there are fewer of them. That's why as much as I can't imagine proposing to somebody at a sporting event, when you have like 30,000 people waiting and like she says yes, it's pretty exciting. So I think that we shouldn't discount that. So how bad do you think it's going to get in terms of the global suffering that we're going to experience with this crisis? I can't figure this one out. I'm just not smart enough. Something is going weirdly wrong. There are almost like two separate storylines. We in one storyline, we aren't taking things nearly seriously enough. We see people using food packaging lids as masks who are doctors or nurses. We hear horrible stories about people dying needlessly due to triage. And that's a very terrifying story. On the other hand, there's this other story which says there are tons of ventilators someplace. We've got lots of masks, but they haven't been released. We've got hospital ships where none of the beds are being used. And it's very confusing to me that somehow these two stories give me the feeling that they both must be true simultaneously and they can't both be true in any kind of standard way. And I don't know whether it's just that I'm dumb, but I can't get one or the other story to quiet down. So I think weirdly, this is much more serious than we had understood it. And it's not nearly as serious as some people are making it out to be at the same time and that we're not being given the tools to actually understand, oh, here's how to interpret the data. Or here's the issue with the personal protective equipment is actually a jurisdictional battle or a question of who pays for it rather than a question of whether it's present or absent. I don't understand the details of it, but something is wildly off in our ability to understand where we are. So that's policy, that's institutions. What about, do you think about the quiet suffering of millions of people that have lost their job? Is this a temporary thing? I mean, what I'm, my ear's not to the suffering of those people who have lost their job or the 50% possibly of small businesses that are gonna go bankrupt. Do you think about that quiet suffering? Well. And how that might arise itself? Could be not quiet too. I mean. Right, that's the. Could be a depression. This could go from recession to depression and depression could go to armed conflict and then to war. So it's not a very abstract causal chain that gets us to the point where we can begin with quiet suffering and anxiety and all of these sorts of things and people losing their jobs and people dying from stress and all sorts of things. But look, anything powerful enough to put us all indoors in a, I mean, think about this as an incredible experiment. Imagine that you proposed, hey, I wanna do a bunch of research. Let's figure out what changes in our emissions, emissions profiles for our carbon footprints when we're all indoors or what happens to traffic patterns or what happens to the vulnerability of retail sales as Amazon gets stronger, et cetera, et cetera. I believe that in many of those situations, we're running an incredible experiment. And am I worried for us all? Yes, there are some bright spots. One of which is that when you're ordered to stay indoors, people are gonna feel entitled. And the usual thing that people are going to hit when they hear that they've lost your job, you know, there's this kind of tough love attitude that you see, particularly in the United States. Oh, you lost your job, poor baby. Well, go retrain, get another one. I think there's gonna be a lot less appetite for that because we've been asked to sacrifice, to risk, to act collectively. And that's the interesting thing. What does that reawaken in us? Maybe the idea that we actually are nations and that your fellow countrymen may start to mean something to more people. It certainly means something to people in the military. But I wonder how many people who aren't in the military start to think about this as like, oh yeah, we are kind of running separate experiments and we are not China. So you think this is kind of a period that might be studied for years to come? From my perspective, we are a part of the experiment, but I don't feel like we have access to the full data, the full data of the experiment. We're just like little mice in a large. Does this one make sense to you, Lex? I'm romanticizing it and I keep connecting it to World War II. So I keep connecting to historical events and making sense of them through that way or reading The Plague by Camus. Like almost kind of telling narratives and stories, but I'm not hearing the suffering that people are going through because I think that's quiet. Everybody's numb currently. They're not realizing what it means to have lost your job and to have lost your business. There's kind of a, I don't know. I'm afraid how that fear will materialize itself once the numbness wears out. And especially if this lasts for many months, and if it's connected to the incompetence of the CDC and the WHO and our government and perhaps the election process. You know, my biggest fear is that the elections get delayed or something like that. So the basic mechanisms of our democracy get slowed or damaged in some way that then mixes with the fear that people have that turns to panic, that turns to anger, that anger. Can I just play with that for a little bit? Sure. What if in fact all of that structure that you grew up thinking about, and again you grew up in two places, right? So when you were inside the US, we tend to look at all of these things as museum pieces. Like how often do we amend the Constitution anymore? And in some sense, if you think about the Jewish tradition of Simchat Torah, you've got this beautiful scroll that has been lovingly hand drawn in calligraphy that's very valuable. And it's very important that you not treat it as a relic to be revered. And so we, one day a year, we dance with the Torah and we hold this incredibly vulnerable document up and we treat it as if it was Ginger Rogers being led by Fred Astaire. Well, that is how you become part of your country. In fact, maybe the election will be delayed. Maybe extraordinary powers will be used. Maybe any one of a number of things will indicate that you're actually living through history. This isn't a museum piece that you were handed by your great-great-grandparents. But you're kind of suggesting that there might be like a community thing that pops up, as opposed to an angry revolution, it might have a positive effect of bringing us together. Well, for example, are you telling me that if the right person stood up and called for us to sacrifice PPE for our nurses and our MDs who are on the front lines, that people wouldn't reach down deep in their own supply that they've been like stocking and carefully storing their, just like say, here, take it. Like right now, an actual leader would use this time to bring out the heroic character, and I'm gonna just go wildly patriotic because I freaking love this country. We've got this dormant population in the US that loves leadership and country and pride in our freedom and not being told what to do, and we still have this thing that binds us together, and all of the merchants of division just be gone. I totally agree with you. I think there is a deep hunger for that leadership. Why hasn't that, why hasn't one arisen? Because we don't have the right surgeon general. We have guys saying, come on, guys, don't buy masks. They don't really work for you. Save them for our healthcare professionals. No, you can't do that. You have to say, you know what? These masks actually do work, and they more work to protect other people from you, but they would work for you. They'll keep you somewhat safer if you wear them. Here's the deal. You've got somebody who's taking huge amounts of viral load all the time because the patients are shedding. Do you wanna protect that person who's volunteered to be on the front line who's up sleepless nights? You just change the message. You stop lying to people. You just, you level with them. It's like, it's bad. Absolutely, but that's a little bit specific, so you have to be just honest about the facts of the situation, yes. But I think you were referring to something bigger than just that. Yeah. It's inspiring, like, you know, rewriting the Constitution, sort of rethinking how we work as a nation. Yeah, I think you should probably, you know, amend the Constitution once or twice in a lifetime so that you don't get this distance from the foundational documents. And, you know, part of the problem is that we've got two generations on top that feel very connected to the US. They feel bought in. And we've got three generations below. It's a little bit like watching your parents riding the tricycle that they were supposed to pass on to you. And it's like, you're now too old to ride a tricycle, and they're still whooping it up, ringing the bell with the streamers coming off the handlebars, and you're just thinking, do you guys never get bored? Do you never pass a torch? Do you really want to? We had five septuagenarians, all born in the 40s, running for president of the United States when Klobuchar dropped out. The youngest was Warren. We had Warren, Biden, Sanders, Bloomberg, and Trump from like 1949 to 1941, all who had been the oldest president at inauguration. And nobody says, Grandma and Grandpa, you're embarrassing us. Except Joe Rogan. Let me put it on you. You have a big platform. You're somewhat of an intelligent, eloquent guy. What role do you, somewhat, what role do you play? Why aren't you that leader? I mean, I would argue that you're in ways becoming that leader. So I haven't taken enough risk. Is that your idea? What should I do or say at the moment? No, you're a little bit, no, you have taken quite a big risks, and we'll talk about it. All right. But you're also on the outside shooting in, meaning you're dismantling the institution from the outside as opposed to becoming the institution. Do you remember that thing you brought up when you were on The View? The View? I'm sorry, when you were on Oprah? I didn't make, I didn't get the invite. I'm sorry, when you were on Bill Maher's program, what was that thing you were saying? They don't know we're here. They may watch us. Yeah. They may quietly slip us a direct message, but they pretend that this internet thing is some dangerous place where only lunatics play. Well, who has the bigger platform? The Portal or Bill Maher's program or The View? Bill Maher and The View. In terms of viewership or in terms of, what's the metric of size? Well, first of all, the key thing is, take a newspaper and even imagine that it's completely fake, okay? And that has very little in the way of circulation. Yet, imagine that it's a 100-year-old paper and that it's still part of this game, this internal game of media. The key point is, is that those sources that have that kind of mark of respectability to the institutional structures matter in a way that even if I say something on a very large platform that makes a lot of sense, if it's outside of what I've called the gated institutional narrative or JIN, it sort of doesn't matter to the institutions. So the game is, if it happens outside of the club, we can pretend that it never happened. How can you get the credibility and the authority from outside the gated institutional narrative? Well, first of all, you and I both share institutional credibility coming from our associations. So we were both at MIT? Yes. Were you at Harvard at any point? Nope. Okay, well. I lived in Harvard Square. So did I. But at some level, the issue isn't whether you have credentials in that sense. The key question is, can you be trusted to file a flight plan and not deviate from that flight plan when you are in an interview situation? Will you stick to the talking points? I will not. And that's why you're not going to be allowed in the general conversation, which amplifies these sentiments. But I'm still trying to. So your point would be, is that we're, let's say both, so you've done how many Joe Rogan? Four. I've done four too, right? So both of us are somewhat frequent guests. The show is huge. You know the power as well as I do. And people are gonna watch this conversation. Huge number watched our last one. By the way, I want to thank you for that one. That was a terrific, terrific conversation. Really did change my life. Lex, you're a brilliant interviewer. So thank you. Thank you, Eric. That was, you changed my life too, that you gave me a chance. So that was. No, no, no. I'm so glad I did that one. What I would say is, is that we keep mistaking how big the audience is for whether or not you have the KISS. And the KISS is a different thing. KISS? What does that stand for? It's not an acronym yet. Okay. Thank you for asking. It's a question of, are you part of the interoperable institution-friendly discussion? And that's the discussion which we ultimately have to break into. But that's what I'm trying to get at, is how does Eric Weinstein become the President of the United States? I shouldn't become the President of the United States. Not interested. Thank you very much for asking. Okay, get into a leadership position where, I guess I don't know what that means, but where you can inspire millions of people to inspire the sense of community, inspire the kind of actions required to overcome hardship, the kind of hardship that we may be experiencing, to inspire people to work hard and face the difficult, hard facts of the realities we're living through, all those kinds of things that you're talking about. That leader, can that leader emerge from the current institutions? Or alternatively, can it also emerge from the outside? I guess that's what I was asking. So my belief is that this is the last hurrah for the elderly centrist kleptocrats. Can you define each of those terms? Okay. Elderly, I mean people who were born at least a year before I was. That's a joke, you can laugh. No, because I'm born at the cusp of the Gen X boomer divide. Centrist, they're pretending, you know, there are two parties, Democrat and Republican Party in the United States. I think it's easier to think of the mainstream of both of them as part of an aggregate party that I sometimes call the looting party, which gets us to kleptocracy, which is ruled by thieves. And the great temptation has been to treat the US like a trough, and you just have to get yours because it's not like we're doing anything productive. So everybody's sort of looting the family mansion, and somebody stole the silver, and somebody's cutting the pictures out of the frames. You know, roughly speaking, we're watching our elders live it up in a way that doesn't make sense to the rest of us. Okay, so if it's the last hurrah, this is the time for leaders to step up? Well, no, we're not ready yet. We're not ready, seriously, I call out, the head of the CDC should resign. Should resign. The Surgeon General should resign. Trump should resign. Pelosi should resign. De Blasio should resign. But they're not gonna resign. I understand that, so that's why, so we'll wait. No, but that's not how revolutions work. You don't wait for people to resign. You step up and inspire the alternative. Do you remember the Russian Revolution of 1907? It's before my time. But there wasn't a Russian Revolution of 1907. So you're thinking we're in 1907, not 1917. I'm saying we're too early. But we got this, Spanish flu came in 17, 18, so I would argue that there's a lot of parallels there. World War I. I think it's not time yet. Like John Prine, the songwriter, just died of COVID. That was a pretty big. Really? Yeah. By the way, yes, of course, I, every time we do this, we discover our mutual appreciation of obscure, brilliant, witty songwriter. Well, he's really quite good, right? He's really good, yeah. He died. My understanding is that he passed recently due to complications of corona. So we haven't had large enough, enough large enough shocking deaths yet. Picturesque deaths, deaths of a family that couldn't get treatment. There are stories that will come and break our hearts. And we have not had enough of those. The visuals haven't come in. But I think they're coming. Well, we'll find out. But you have to be there when they come. But we didn't get the visual, for example, of falling man from 9-11. So the outside world did, but Americans were not, it was thought that we would be too delicate. So just the way you remember Pulitzer Prize-winning photographs from the Vietnam era, you don't easily remember the photographs from all sorts of things that have happened since, because something changed in our media. We are insensitive. We cannot feel or experience our own lives and the tragedy that would animate us to action. Yeah, but I think there, again, I think there's going to be that suffering that's going to build and build and build in terms of businesses, mom-and-pop shops that close. And I think for myself, I think often that I'm being weak. And I feel like I should be doing something. I should be becoming a leader on a small scale. You can't. This is not World War II, and this is not Soviet Russia. Why not? Why not? Because our internal programming, the malware that sits between our ears is much different than the propagandized malware of the Soviet era. I mean, people were both very indoctrinated and also knew that at some level it was BS. They had a double mind. I don't know, there must be a great word in Russian for being able to think both of those things simultaneously. You don't think people are actually sick of the partisanship, sick of incompetence? Yeah, but I called for revolt the other day on Joe Rogan. People found it quixotic. Well, because I think you're not, I think revolt is different. I think as like a... Okay, I'm really angry. Yes. I'm furious. I cannot stand that this is my country at the moment. I'm embarrassed. So let's build a better one. Yeah. That's the... I'm in. Okay, so well, that's something I think about. So let's take over a few universities. Let's start running a different experiment at some of our better universities. Like when I did this experiment and I said, if this were 40 years ago, the median age I believe of a university president was 51, that would have the person in Gen X and we'd have a bunch of millennial presidents, a bunch of more than half Gen X. It's almost 100% baby boom at this point. And how did that happen? We can get into how they changed retirement, but this generation above us does not feel, or even the older generation, silent generation. I had Roger Penrose on my program. Excellent conversation. And I, thank you, really appreciate that. And I asked him a question that was very important to me. I said, look, you're in your late 80s. Is there anyone you could point to as a successor that we should be watching, we can get excited? You know, I said, here's an opportunity to pass the baton. He said, well, let me hold off on that. I was like, oh, is it ever the right moment to point to somebody younger than you to keep your flame alive after you're gone? And also, like, I don't know whether, I'm just gonna admit to this, people treat me like I'm crazy for caring about the world after I'm dead. Or wanting to be remembered after you're gone. Like, well, what does it matter to you? You're gone. It's this deeply sort of secular, somatic perspective on everything. Where we don't, you know that phrase in As Time Goes By? It says, it's still the same old story, a fight for love and glory, a case of do or die. I don't think people imagined then that there wouldn't be a story about fighting for love and glory. And like, we are so out of practice about fighting rivals for love and fighting for glory in something bigger than yourself. But the hunger is there. Well, that was the point then, right? The whole idea is that Rick was, you know, he was like Han Solo of his time. He's just like, I stick my neck out for nobody. You know, it's like, oh, come on, Rick. You're just pretending. You actually have a big soul, right? And so, at some level, that's the question. Do we have a big soul or is it just all bullshit? See, I think there's huge Manhattan Project style projects, whether you're talking about physical infrastructure or going to Mars, you know, the SpaceX, NASA efforts or huge, huge scientific efforts. That could be the- Well, we need to get back into the institutions and we need to remove the weak leadership, that we have weak leaders and the weak leaders need to be removed and they need to seat people more dangerous than the people who are currently sitting in a lot of those chairs. Or build new institutions. Good luck. Well, so one of the nice things from the internet is, for example, somebody like you can have a bigger voice than almost anybody at the particular institutions we're talking about. That's true. But the thing is, I might say something. You can count on the fact that the provost at Princeton isn't gonna say anything. What do you mean? Too afraid? Well, if that person were to give an interview, how are things going in research at Princeton? Well, I'm hesitant to say it, but they're perhaps as good as they've ever been and I think they're gonna get better. Oh, is that right? All fields? Yep, I don't see a weak one. It's just like, okay, great. Who are you and what are you even saying? We're just used to total nonsense 24-7. Yeah, what do you think might be a beautiful thing that comes out of this? Is there a hope, like a little inkling, a little fire of hope you have about our time right now? Yeah, I think one thing is coming to understand that the freaks, weirdos, mutants, and other ne'er-do-wells, sometimes referred to as grifters, I like that one, grifters, and gadflies were very often the earliest people on the coronavirus. That's a really interesting question, why was that? And it seems to be that they had already paid such a social price that they weren't going to be beaten up by being told that, oh my God, you're xenophobic, you just hate China, you know, or wow, you sound like a conspiracy theorist. So if you'd already paid those prices, you were free to think about this, and everyone in an institutional framework was terrified that they didn't want to be seen as the alarmist, the chicken little, and so that's why you have this confidence where, you know, de Blasio says, you know, get on with your lives, get back in there and celebrate Chinese New Year in Chinatown, despite coronavirus. It's like, okay, really? So you just always thought everything would automatically be okay if you adopted that posture. So you think this time reveals the weakness of our institutions and reveals the strength of our gadflies and the weirdos and the? No, not necessarily the strength, but the value of freedom. Like a different way of saying it would be, wow, even your gadflies and your grifters were able to beat your institutional folks because your institutional folks were playing with a giant mental handicap. So just imagine like we were in the story of Harrison Bergeron by Vonnegut, and our smartest people were all subjected to distracting noises every seven seconds. Well, they would be functionally much dumber because they couldn't continue a thought through all the disturbance. So in some sense, that's a little bit like what belonging to an institution is, is that if you have to make a public statement, of course the Surgeon General's gonna be the worst, because they're just playing with too much of a handicap. There are too many institutional players who are like, don't screw us up. And so the person has to say something wrong. We're gonna back propagate a falsehood. And this is very interesting. Some of my socially oriented friends say, Eric, I don't understand what you're on about. Of course masks work, but you know what they're trying to do? They're trying to get us not to buy up the masks for the doctors. And I think, okay, so you imagine that we can just create scientific fiction at will so that you can run whatever social program you want. This is what I, my point is get out of my lab. Get out of the lab. You don't belong in the lab. You're not meant for the lab. You're constitutionally incapable of being around the lab. You need to leave the lab. You think the CDC and WHO knew that masks work and were trying to sort of imagine that people are kind of stupid and they would buy masks in excess if they were told that masks work? Is that like, because this does seem to be a particularly clear example of mistakes made. You're asking me this question? Yeah. No, you're not. What do you think, Lex? Well, I actually probably disagree with you a little bit. Great, let's do it. I think it's not so easy to be honest with the populace when the danger of panic is always around the corner. So I think the kind of honesty you exhibit appeals to a certain class of brave intellectual minds that it appeals to me, but I don't know. From the perspective of WHO, I don't know if it's so obvious that they should be honest 100% of the time with people. I'm not saying you should be perfectly transparent and 100% honest. I'm saying that the quality of your lies has to be very high and it has to be public spirited. There's a big difference between, so I'm not a child about this. I'm not saying that when you're at war, for example, you turn over all of your plans to the enemy because it's very important that you're transparent with 360 degree visibility, far from it. What I'm saying is something has been forgotten and I forgot who it was who told it to me, but it was a fellow graduate student in the Harvard math department. And he said, you know, I learned one thing being out in the workforce because he was one of the few people who had had a work life in the department as a grad student. He said, you can be friends with your boss, but if you're going to be friends with your boss, you have to be doing a good job at work. And there's an analog here, which is if you're going to be reasonably honest with the population, you have to be doing a good job at work as the surgeon general or as the head of the CDC. So if you're doing a terrible job, you're supposed to resign. And then the next person is supposed to say, look, I'm not going to lie to you. I inherited the situation. It was in a bit of disarray, but I had several requirements before I agreed to step in and take the job because I needed to know I could turn it around. I needed to know that I had clear lines of authority. I needed to know that I had the resources available in order to rectify the problem, and I needed to know that I had the ability and the freedom to level with the American people directly as I saw fit. All of my wishes were granted, and that's why I'm happy here on Monday morning. I've got my sleeves rolled up. Boy, do we got a lot to do, so please come back in two weeks and then ask me how I'm doing then, and I hope to have something to show you. That's how you do it. So why is that excellence and basic competence missing? The big net. You see, you come from multiple traditions where it was very important to remember things. The Soviet tradition made sure that you remembered the sacrifices that came in that war, and the Jewish tradition, we're doing this on Passover, right? Okay, well, every year we tell one simple story. Well, why can't it be different every year? Maybe we could have a rotating series of seven stories because it's the one story that you need. It's like, you work with the Men in Black group, right, and it's the last suit that you'll ever need. This is the last story that you ever need. Don't think I fell for your neuralyzer last time. In any event, we tell one story because it's the get out of Dodge story. There's a time when you need to not wait for the bread to rise, and that's the thing, which is even if you live through a great nap, you deserve to know what it feels like to have to leave everything that has become comfortable and unworkable. It's sad that you need that tragedy, I imagine, to have the tradition of remembering. It's sad to think that because things have been nice and comfortable means that we can't have great, competent leaders, which is kind of the implied statement. Can we have great leaders who take big risks, who inspire hard work, who deal with difficult truth even though things have been comfortable? Well, we know what those people sound like. I mean, if for example, Jocko Willink suddenly threw his hat into the ring, everyone would say, okay, right, party's over. It's time to get up at 4.30 and really work hard, and we've got to get back into fighting shape. And... Yeah, but Jocko's a very special, I think that whole group of people by profession put themselves into hardship on a daily basis. And he's not, well, I don't know, but he's probably not going to be, well, could Jocko be president? Okay, but it doesn't have to be Jocko, right? Like in other words, if it was Kyle Lennie, or if it was Alex Honnold from rock climbing. Right. But they're just serious people. They're serious people who can't afford your BS. Yeah, but why do we have serious people that do rock climbing and don't have serious people who lead the nation? That seems to be... Because that was a, those skills needed in rock climbing are not good during the big nap. And at the tail end of the big nap, they would get you fired. But I don't, don't you think there's a fundamental part of human nature that desires to excel, to be exceptionally good at your job? Yeah, but what is your job? I mean, in other words, my point to you is, if you're a general in a peacetime army, and your major activity is playing war games, what if the skills needed to win war games are very different than the skills needed to win wars, because you know how the war games are scored, and you've done money ball, for example, with war games. You figured out how to win games on paper. So then the advancement skill becomes divergent from the ultimate skill that it was proxying for. Yeah, but you create, we're good as human beings to, I mean, at least me, I can't do a big nap. So at any one moment when I finish something, a new dream pops up. So going to Mars. What do you like to do? You like to do Brazilian jiu-jitsu? Well, first of all, I like to do everything. You like to play guitar? Guitar. You do this podcast, you do theory, you're constantly taking risks and exposing yourself, right? Why? Because you got one of those crazy, I'm sorry to say it, you got an Eastern European Jewish personality, which I'm still tied to. And I'm a couple generations more distant than you are. And I've held on to that thing because it's valuable to me. You don't think there's a huge percent of the populace, even in the United States, that's that. It might be a little bit dormant, but. Do you know Anna Khachyian from the Red Scare podcast? Did you interview her? Yeah. Yeah, yeah, yeah. I listened, yeah, yeah, she was great. She was great, right? Yeah, she was fun. She's terrific. But she also has the same thing going on. And I made a joke in the liner notes for that episode, which is somewhere on the road from Stalingrad to Forever 21, something was lost. Like how can Stalingrad and Forever 21 be in the same sentence? And in part, it's that weird thing. It's like trying to remember. Even words, like I'm in Russian and Hebrew, things like, it's like, but ponet and liskor, these words have much more potency about memory. And I don't know. I think there's still a dormant populace that craves leaders on a small scale and large scale. And I hope to be that leader on a small scale. And I think you, sir, have a role to be a leader. You kids go ahead without me. I'm just gonna do a little bit of weird podcasting. See, now you're putting on your Joe Rogan hat. He says I'm just a comedian. And you say I'm just a. It's not that. If I say I wanna lead too much because of the big nap, there's like a group, a chorus of automated idiots. And they're first, I was like, ah, I knew it. This was a power grab all along. Why should you lead? And so the idea is you're just trying to skirt around, not stepping on all of the idiot landmines. It's like, okay, so now I'm gonna hear that in my inbox for the next three days. Okay, so lead by example. Just live on a large platform. Look, we should take over the institutions. There are institutions. We've got bad leadership. We should mutiny. And we should inject a, I don't know, 15%, 20% disagreeable, dissident, very aggressive, loner individual, mutant freaks, all the people that you go to see Avengers movies about or the X-Men or whatever it is, and stop pretending that everything good comes out of some great, giant, inclusive, communal 12-hour meeting. It's like, stop it. That's not how shit happens. You recently published the video of a lecture you gave at Oxford presenting some aspects of a theory, theory of everything called geometric unity. So this was a work of 30 plus years. This is life's work. Let me ask the silly old question. How do you feel as a human? Excited, scared, the experience of posting it? You know, it's funny. One of the things that you learn to feel as an academic is the great sins you can commit in academics is to show yourself to be a non-serious person, to show yourself to have delusions, to avoid the standard practices which everyone is signed up for. And it's weird because you know that those people are gonna be angry. He did what? Why would he do that? And what we're referring to, for example, there's traditions of sort of publishing incrementally, certainly not trying to have a theory of everything, perhaps working within the academic departments, all those things. That's true. And so you're going outside of all of that. Well, I mean, I was going inside of all of that. And we did not come to terms when I was inside. And what they did was so outside to me, was so weird, so freakish. Like the most senior respectable people at the most senior respectable places were functionally insane as far as I could tell. And again, it's like being functionally stupid if you're the head of the CDC or something where you're giving recommendations out that aren't based on what you actually believe, they're based on what you think you have to be doing. Well, in some sense, I think that that's a lot of how I saw the math and physics world as the physics world was really crazy. And the math world was considerably less crazy, just very strict and kind of dogmatic. Well, we'll psychoanalyze those folks. But I really wanna maybe linger on it a little bit longer of how you feel, because this is such a special moment in your life. Well, I really appreciate it. It's a great question. So if we can pair off some of those other issues. And it's new being able to say what the observers is, which is my attempt to replace space time with something that is both closely related to space time and not space time. So I used to carry the number 14 as a closely guarded secret in my life. And we're 14 is really four dimensions of space and time plus 10 extra dimensions of rulers and protractors or for the cool kids out there, symmetric two tensors. So you had a geometric, complicated, beautiful geometric view of the world that you carried with you for a long time. Yeah. Did you have friends that you, colleagues that you- Essentially, no. Talked? No, in fact, part of these, part of some of these stories are me coming out to my friends and I use the phrase coming out because I think that gays have monopolized the concept of a closet. Many of us are in closets having nothing to do with our sexual orientation. Yeah, I didn't really feel comfortable talking to almost anyone. So this was a closely guarded secret. And I think that I let on in some ways that I was up to something and probably, but it was a very weird life. So I had to have a series of things that I pretended to care about so that I could use that as the stalking horse for what I really cared about. And to your point, I never understood this whole thing about theories of everything. Like if you were gonna go into something like theoretical physics, isn't that what you would normally pursue? Like, wouldn't it be crazy to do something that difficult and that poorly paid if you were gonna try to do something other than figure out what this is all about? Now I have to reveal my cards of my sort of weaknesses and lack and understanding of the music of physics and math departments. But there's an analogy here to artificial intelligence. And often folks come in and say, okay, so there's a giant department working on quote unquote artificial intelligence. But why is nobody actually working on intelligence? Like you're all just building little toys. You're not actually trying to understand. And that breaks a lot of people. It confuses them. Because like, okay, so I'm at MIT, I'm at Stanford, I'm at Harvard, I'm here, I dreamed of being, working on artificial intelligence. Why is everybody not actually working on intelligence? I have the same kind of sense that that's what working on the theory of everything is. That strangely you somehow become an outcast for even. But we know why this is, right? Why? Well, it's because, let's take the artificial, let's play with AGI for example. I think that the idea starts off with nobody really knows how to work on that. And so if we don't know how to work on it, we choose instead to work on a program that is tangentially related to it. So we do a component of a program that is related to that big question because it's felt like at least I can make progress there. And that wasn't where I was. Where I was in, it's funny, there was this book called Frieden-Uhlenbeck and it had this weird, mysterious line in the beginning of it. And I tried to get clarification of this weird, mysterious line and everyone said wrong things. And then I said, okay, well, so I can tell that nobody's thinking properly because I just asked the entire department and nobody has a correct interpretation of this. And so it's a little bit like you see a crime scene photo and you have a different idea. Like there's a smoking gun and you figure, that's actually a cigarette lighter. I don't really believe that. And then there's like a pack of cards and you think, oh, that looks like the blunt instrument that the person was beaten with. So you have a very different idea about how things go. And very quickly you realize that there's no one thinking about that. There's a few human sides to this and technical sides, both of which I'd love to try to get down to. So the human side, I can tell from my perspective, I think it was before April 1st, April Fool's, maybe the day before, I forget. But I was laying in bed in the middle of the night and somehow it popped up on my feed somewhere that your beautiful face is speaking live. And I clicked and it's kind of weird how the universe just brings things together in this kind of way. And all of a sudden I realized that there's something big happening in this particular moment. It's strange. On a day like any day. And all of a sudden you were thinking of, you had this somber tone, like you were serious, like you were going through some difficult decision. And it seems strange. I almost thought you were maybe joking, but there was a serious decision being made. And it was a wonderful experience to go through with you. I really appreciate it. I mean, it was April 1st. Yeah, it's kind of fascinating. I mean, just the whole experience. And so I want to ask, I mean, thank you for letting me be part of that kind of journey of decision-making that took 30 years, but why now? Why did you think, why did you struggle so long not to release it and decide to release it now? While the whole world is on lockdown, on April fools, is it just because you like the comedy of absurd ways that the universe comes together? I don't think so. I think that the COVID epidemic is the end of the big nap. And I think that I actually tried this seven years earlier in Oxford. So I, and it was too early. Which part was too, is it the platform? Because your platform is quite different now, actually. The internet, I remember you, I read several of your brilliant answers that people should read for the Edge questions. One of them was related to the internet. And it was the first one. Was it the first one? An essay called Go Virtual, Young Man. Yeah, yeah, that's like forever ago now. Well, that was 10 years ago, and that's exactly what I did, is I decamped to the internet, which is where the portal lives. The portal, the portal, the portal. Yeah. Well, the theme, the ominous theme music, which you just listen to forever. I actually started recording tiny guitar licks for the audio portion, not for the video portion. You kind of inspire me with bringing your guitar into the story, but keep going. So you thought, so the Oxford was like step one, and you kind of, you put your foot into the water to sample it, but it was too cold at the time. So you didn't want to step in all the- I was just really disappointed. What was disappointing about that experience? It's a hard thing to talk about. It has to do with the fact that, and I can see this, you know, this mirrors a disappointment within myself. There are two separate issues. One is the issue of making sure that the idea is actually heard and explored. And the other is the question about, will I become disconnected from my work because it will be ridiculed, it will be immediately improved, it will be found to be derivative of something that occurred in some paper in 1957. When the community does not want you to gain a voice, it's a little bit like a policeman deciding to weirdly enforce all of these little-known regulations against you and sometimes nobody else. And I think that's kind of this weird thing where I just don't believe that we can reach the final theory necessarily within the political economy of academics. So if you think about how academics are tortured by each other and how they're paid and where they have freedom and where they don't, I actually weirdly think that that system of selective pressures is going to eliminate anybody who's going to make real progress. So that's interesting. So if you look at the story of Andrew Wiles, for example, from our class there, I mean, he, as far as I understand, he pretty much isolated himself from the world of academics in terms of the bulk of the work he did. And from my perspective, it's dramatic and fun to read about but it seemed exceptionally stressful the first steps he took when actually making the work public. That seemed, to me, it would be hell. Yeah, but it's like so artificially dramatic. You know, he leads up to it at a series of lectures, he doesn't want to say it, and then he finally says it at the end because obviously this comes out of a body of work where, I mean, the funny part about Fermat's last theorem is that it wasn't originally thought to be a deep and meaningful problem. It was just an easy to state one that had gone unsolved. But if you think about it, it became attached to the body of regular theory. So he built up this body of regular theory, gets all the way up to the end, announces. And then like, there's this whole drama about, okay, somebody's checking the proof. I don't understand what's going on in line 37. You know, and like, oh, is this serious? It seems a little bit more serious than we knew. I mean, do you see parallels? Do you share the concern that your experience might be something similar? Well, in his case, I think that if I recall correctly, his original proof was unsalvageable. He actually came up with a second proof with a colleague, Richard Taylor, and it was that second proof which carried the day. So it was a little bit that he got put under incredible pressure and then had to succeed in a new way having failed the first time, which is like even a weirder and stranger story. That's an incredible story in some sense. But I mean, are you, I'm trying to get a sense of the kind of stress you're under. I think that this is, okay, but I'm rejecting. What I don't think people understand with me is the scale of the critique. It's like, I don't, people say, well, you must implicitly agree with this and implicitly agree, and it's like, no, try me. Ask before you decide that I am mostly in agreement with the community about how these things should be handled or what these things mean. Can you elaborate? And also just why does criticism matter so much here? So you seem to dislike the burden of criticism that it will choke away all. There's different kinds of criticism. There's constructive criticism and there's destructive criticism. And what I don't like is I don't like a community that can't, first of all, like if you take the physics community, just the way we screwed up on masks and PPE, just the way we screwed up in the financial crisis and mortgage-backed securities, we screwed up on string theory. Can we just forget the string theory happened or? Sure, but then somebody should say that, right? Somebody should say, you know, it didn't work out. Yeah. But okay, but you're asking this, like why do you guys get to keep the prestige after failing for 35 years? That's an interesting question. It's always you guys because to me. Whoever the, look, these things, if there is a theory of everything to be had, right, it's going to be a relatively small group of people where this will be sorted out. Absolutely. It's not tens of thousands. It's probably hundreds at the top. But within that community, there's the assholes. There's the, I mean, like you always in this world have people who are kind, open-minded. It's not a question about kind. It's a question about, okay, let's imagine, for example, that you have a story where you believe that ulcers are definitely caused by stress and you've never questioned it. Or maybe you felt like the Japanese came out of the blue and attacked us at Pearl Harbor, right? And now somebody introduces a new idea to you, which is like, what if it isn't stress at all? Or what if we actually tried to make resource-starved Japan attack us somewhere in the Pacific so we could have Cassius Belli to enter the Asian theater? And the person's original idea is like, what? What are you even saying? You know, it's like too crazy. Well, when Dirac in 1963 talked about the importance of beauty as a guiding principle in physics, and he wasn't talking about the scientific method, that was crazy talk. But he was actually making a great point. He was using Schrodinger, and I think it was, Schrodinger was standing in for him. And he said that if your equations don't agree with experiment, that's kind of a minor detail. If they have true beauty in them, you should explore them because very often the agreement with experiment is an issue of fine-tuning of your model, of the instantiation. And so it doesn't really tell you that your model is wrong. And of course, Heisenberg told Dirac that his model was wrong because the proton and the electron should be the same mass if they are each other's antiparticles. And that was an irrelevant kind of silliness rather than a real threat to the Dirac theory. But okay, so amidst all this silliness, I'm hoping that we could talk about the journey that geometric unity has taken and will take as an idea and an idea that will see the light. Yeah. So first of all, I'm thinking of writing a book called Geometric Unity for Idiots. Okay. And I need you as a consultant. So can we? First of all, I hope I have the trademark on geometric unity. You do, good. Can you give a basic introduction of the goals of geometric unity, the basic tools of mathematics, use the viewpoints in general for idiots like me? Okay, great, fun. So what's the goal of geometric unity? The goal of geometric unity is to start with something so completely bland that you can simply say, well, that's the something that begins the game is as close to a mathematical nothing as possible. In other words, I can't answer the question, why is there something rather than nothing? But if there has to be a something that we begin from, let it begin from something that's like a blank canvas. Let's even more basic. So what is something? What are we trying to describe here? Okay, right now we have a model of our world, and it's got two sectors. One of the sectors is called general relativity, the other is called the standard model. So we'll call it GR for general relativity and SM for standard model. What's the difference between the two? What do the two describe? So general relativity gives pride of place to gravity, and everything else is acting as a sort of a backup singer. Gravity is the star of the show. Gravity is the star of general relativity. And in the standard model, the other three non-gravitational forces, so if there are four forces that we know about, three of the four are non-gravitational, that's where they get to shine. Great, so tiny little particles and how they interact with each other. So photons, gluons, and so-called intermediate vector bosons. Those are the things that the standard model showcases, and general relativity showcases gravity, and then you have matter, which is accommodated in both theories, but much more beautifully inside of the standard model. So what does a theory of everything do? So first of all, I think that that's the first place where we haven't talked enough. We assume that we know what it means, but we don't actually have any idea what it means. And what I claim it is, is that it's a theory where the questions beyond that theory are no longer of a mathematical nature. In other words, if I say, let us take X to be a four-dimensional manifold, to a mathematician or a physicist, I've said very little. I've simply said, there's some place for calculus and linear algebra to dance together and to play. And that's what manifolds are. They're the most natural place where our two greatest math theories can really intertwine. Which are the two? Oh, you mean calculus and linear algebra, yep. Right. Okay, now the question is beyond that. So it's sort of like saying, I'm an artist and I wanna order a canvas. Now the question is, does the canvas paint itself? Does the canvas come up with an artist and paint an ink, which then paint the canvas? Like that's the hard part about theories of everything, which I don't think people talk enough about. Can we just, you bring up Escher and the hand that draws itself. The fire that lights itself or drawing hands. The drawing hands. Yeah. And every time I start to think about that, my mind shuts down. No, don't do that. There's a spark. No, but this is the most beautiful part. We should do this together. No, it's beautiful, but this robot's brain sparks fly. So can we try to say the same thing over and over in different ways about what you mean by that having to be a thing we have to contend with? Sure. Like why do you think that creating a theory of everything, as you call the source code, our understanding our source code, require a view like the hand that draws itself? Okay, well, here's what goes on in the regular physics picture. We've got these two main theories, general relativity and the standard model, right? Think of general relativity as more or less the theory of the canvas, okay? And maybe you have the canvas in a particularly rigid shape. Maybe you've measured it, so it's got length and it's got an angle, but more or less it's just canvas and length and angle. And that's all that really general relativity is, but it allows the canvas to warp a bit. Then we have the second thing, which is this import of foreign libraries which aren't tied to space and time. So we've got this crazy set of symmetries called SU3 cross SU2 cross U1. We've got this collection of 16 particles in a generation, which are these sort of twisted spinners. And we've got three copies of them. Then we've got this weird Higgs field that comes in and like Deus Ex Machina solves all the problems that have been created in the play that can't be resolved otherwise. So that's the standard model of quantum field theory just plopped on top of this canvas. Yes, it's a problem of the double origin story. One origin story is about space and time. The other origin story is about what we would call internal quantum numbers and internal symmetries. And then there was an attempt to get one to follow from the other called Kalusa-Klein theory, which didn't work out. And this is sort of in that vein. So you said origin story. So in the hand that draws itself, what is it? So it's as if you had the canvas and then you ordered up also give me paintbrushes, paints, pigments, pencils, and artists. But you're saying that's like, if you want to create a universe from scratch, the canvas should be generating the paintbrush and the paintbrushes should be generating the canvas. Yeah, yeah, yeah. Right, like you should. Who's the artist in this analogy? Well, this is, sorry, then we're gonna get into a religious thing and I don't wanna do that. Okay. Well, you know my shtick, which is that we are the AI. We have two great stories about the simulation and artificial general intelligence. In one story, man fears that some program we've given birth to will become self-aware, smarter than us, and will take over. In another story, there are genius simulators and we live in their simulation. And we haven't realized that those two stories are the same story. In one case, we are the simulator. In another case, we are the simulated. And if you buy those and you put them together, we are the AGI. And whether or not we have simulators, we may be trying to wake up by learning our own source code. So this could be our Skynet moment, which is one of the reasons I have some issues around it. I think we'll talk about that, because I- Well, that's the issue of the emergent artist within the story, just to get back to the point. Okay, so now the key point is, the standard way we tell the story is that Einstein sets the canvas, and then we order all the stuff that we want, and then that paints the picture that is our universe. So you order the paint, you order the artist, you order the brushes, and that then, when you collide the two, gives you two separate origin stories. The canvas came from one place, and everything else came from somewhere else. So what are the mathematical tools required to construct consistent geometric theory, you know, make this concrete? Well, somehow, you need to get three copies, for example, of generations with 16 particles each, right? And so the question would be, like, well, there's a lot of special personality in those symmetries. Where would they come from? So for example, you've got what would be called grand unified theories that sound like SU5, the George I. Glashow theory. There's something that should be called spin 10, but physicists insist on calling it SO10. There's something called the Petit-Salam theory that tends to be called SU4 cross SU2 cross SU2, which should be called spin six cross spin four. I can get into all of these. But what are they all accomplishing? They're all taking the known forces that we see and packaging them up to say, we can't get rid of the second origin story, but we can at least make that origin story more unified. So they're trying grand unification as the attempt to- And that's a mistake in your- It's not a mistake. The problem is, is it was born lifeless. When George I. Glashow first came out with the SU5 theory, it was very exciting because it could be tested in a South Dakota mine filled up with like, I don't know, cleaning fluid or something like that. And they looked for proton decay and didn't see it. And then they gave up because in that day when your experiment didn't work, you gave up on the theory. It didn't come to us born of a fusion between Einstein and Bohr. And that was kind of the problem is that it had this weird parenting where it was just on the Bohr side. There was no Einsteinian contribution. Lex, how can I help you most? I'm trying to figure out what questions you want to ask so that you get the most satisfying answers. There's a bunch of questions I want to ask. I mean, one, and I'm trying to sneak up on you somehow to reveal in a accessible way the nature of our universe. So I can just give you a guess, right? We have to be very careful that we're not claiming that this has been accepted. This is a speculation. But I will make the speculation. I think what you would want to ask me is how can the canvas generate all the stuff that usually has to be ordered separately? All right, should we do that? Let's go there. Okay. So the first thing is is that you have a concept in computers called technical debt. You're coding and you cut corners and you know you're gonna have to do it right before the thing is safe for the world. But you're piling up some series of IOUs to yourself and your project as you're going along. So the first thing is we can't figure out if you have only four degrees of freedom, and that's what your canvas is, how do you get at least Einstein's world? Einstein said, look, it's not just four degrees of freedom, but there need to be rulers and protractors to measure length and angle in the world. You can't just have a flabby four degrees of freedom. So the first thing you do is you create 10 extra variables, which is like if we can't choose any particular set of rulers and protractors to measure length and angle, let's take the set of all possible rulers and protractors, and that would be called symmetric non-degenerate two tensors on the tangent space of the four manifold X4. Now, because there are four degrees of freedom, you start off with four dimensions, then you need four rulers for each of those different directions. So that's four, that gets us up to eight variables, and then between four original variables, there are six possible angles. So four plus four plus six is equal to 14. So now you've replaced X4 with another space, which in the lecture I think I called U14, but I'm now calling Y14. This is one of the big problems of working on something in private is every time you pull it out, you sort of can't remember it, you name something new. Okay, so you've got a 14-dimensional world, which is the original four-dimensional world, plus a lot of extra gadgetry for measurement. And because you're not in the four-dimensional world, you don't have the technical debt. No, now you've got a lot of technical debt because now you have to explain away a 14-dimensional world, which is a big, you're taking a huge advance on your payday check, right? But aren't more dimensions allow you more freedom? Maybe, but you have to get rid of them somehow because we don't perceive them. So eventually you have to collapse it down to the thing that we perceive. Or you have to sample a four-dimensional filament within that 14-dimensional world known as a section of a bundle. Okay, so how do we get from the 14-dimensional world where I imagine a lot of four-dimensional? Oh, wait, wait, wait. Yeah. You're cheating. The first question was how do we get something from almost nothing? Like how do we get the, if I've said that the who and the what in the newspaper story that is a theory of everything are bosons and fermions. So let's make the who the fermions and the what the bosons. Think of it as the players and the equipment for a game. Are we supposed to be thinking of actual physical things with mass or energy? Okay. So think about everything you see in this room. So from chemistry, you know it's all protons, neutrons, and electrons. But from a little bit of late 1960s physics, we know that the protons and neutrons are all made of up quarks and down quarks. So everything in this room is basically up quarks, down quarks, and electrons stuck together with the what, the equipment. Okay. Now, the way we see it currently is we see that there are space-time indices, which we would call spinners, that correspond to the who, that is the fermions, the matter, the stuff, the up quarks, the down quarks, the electrons. And there are also 16 degrees of freedom that come from this space of internal quantum numbers. So in my theory, in 14 dimensions, there's no internal quantum number space that figures in. It's all just spinorial. So spinners in 14 dimensions without any festooning with extra linear algebraic information. There's a concept of spinners, which is natural if you have a manifold with length and angle. And Y14 is almost a manifold with length and angle. It's so close. In other words, because you're looking at the space of all rulers and protractors, maybe it's not that surprising that a space of rulers and protractors might come very close to having rulers and protractors on it itself. Like, can you measure the space of measurements? And you almost can. And a space that has length and angle, if it doesn't have a topological obstruction, comes with these objects called spinners. Now, spinners are the stuff of our world. We are made of spinners. They are the most important really deep object that I can tell you about. They were very surprising. What is a spinner? So famously, there are these weird things that require 720 degrees of rotation in order to come back to normal. And that doesn't make sense. And the reason for this is that there's a knottedness in our three-dimensional world that people don't observe. And you can famously see it by this Dirac string trick. So if you take a glass of water, imagine that this was a tumbler and I didn't want to spill any of it. And the question is, if I rotate the cup without losing my grip on the base 360 degrees, and I can't go backwards, is there any way I can take a sip? And the answer is this weird motion, which is go over first and under second. And that's 720 degrees of rotation to come back to normal so that I can take a sip. Well, that weird principle, which sometimes is known as the Philippine wine glass dance because waitresses in the Philippines apparently learned how to do this. That move defines, if you will, this hidden space that nobody knew was there of spinners, which Dirac figured out when he took the square root of something called the Klein-Gordon equation, which I think had earlier work incorporated from Cartan and Killing and Company in mathematics. So spinners are one of the most profound aspects of human existence. I mean, forgive me for the perhaps dumb questions, but would a spinner be the mathematical object that's the basic unit of our universe? When you start with a manifold, which is just like something like a donut or a sphere, or a circle, or a Mobius band, a spinner is usually the first wildly surprising thing that you found was hidden in your original purchase. So you order a manifold, and you didn't even realize, it's like buying a house and finding a panic room inside that you hadn't counted on. It's very surprising when you understand that spinners are running around in your spaces. Again, perhaps a dumb question, but we're talking about 14 dimensions and four dimensions. What is the manifold we're operating under? So in my case, it's proto-spacetime. It's before Einstein can slap rulers and protractors on spacetime. And what you mean by that, sorry to interrupt, is spacetime is the 4D manifold. Spacetime is a four-dimensional manifold with extra structure. What's the extra structure? It's called a semi-Romanian or pseudo-Romanian metric. And in essence, there is something akin to a four by four symmetric matrix, which is equivalent to length and angle. So when I talk about rulers and protractors, or I talk about length and angle, or I talk about Ramanian or pseudo-Romanian or semi-Romanian manifolds, I'm usually talking about the same thing. Can you measure how long something is and what the angle is between two different rays or vectors? So that's what Einstein gave us as his arena, his place to play, his canvas. There's a bunch of questions I can ask here, but like I said, I'm working on this book, Geometric Unity for Idiots. And I think what would be really nice, as your editor, to have beautiful, maybe even visualizations that people could try to play with, try to reveal small little beauties about the way you're thinking about this world. Well, I usually use the Joe Rogan program for that. Sometimes I have him doing the Philippine wine glass dance. I had the hop vibration. The part of the problem is that most people don't know this language about spinners, bundles, metrics, gauge fields. And they're very curious about the theory of everything, but they have no understanding of even what we know about our own world. Is it a hopeless pursuit? So like even gauge theory. Right. I mean, it seems to be very inaccessible. Is there some aspect of it that could be made accessible? I mean, I could go to the board right there and give you a five minute lecture on gauge theory that would be better than the official lecture on gauge theory. You would know what gauge theory was. So it is possible to make it accessible. Yeah, but nobody does. Like in other words, you're gonna watch over the next year lots of different discussions about quantum entanglement or the multiverse, where are we now? Or many worlds, are they all equally real? Yeah. Right? I mean, yeah, that's like. Okay, but you're not gonna hear anything about the hop vibration except if it's from me, and I hate that. Why can't you be the one? Well, because I'm going a different path. I think that we've made a huge mistake, which is we have things we can show people about the actual models. We can push out visualizations where they're not listening by analogy. They're watching the same thing that we're seeing. And as I've said to you before, this is like choosing to perform sheet music that hasn't been performed in a long time. Or the experts can't afford orchestras, so they just trade Beethoven symphonies as sheet music. And they go, oh, wow, that was beautiful. But it's like nobody heard anything. They just looked at the score. Well, that's how mathematicians and physicists trade papers and ideas, is that they write down the things that represent stuff. I want to at least close out this thought line that you started, which is how does the canvas order all of this other stuff into being? So I at least want to say some incomprehensible things about that, and then we'll have that much done, all right? On that just point, does it have to be incomprehensible? Do you know what the Schrodinger equation is? Yes. Do you know what the Dirac equation is? What does no mean? Well, my point is you're gonna have some feeling that you know what the Schrodinger equation is. As soon as we get to the Dirac equation, your eyes are gonna get a little bit glazed, right? So now why is that? Well, the answer to me is that you want to ask me about the theory of everything, but you haven't even digested the theory of everything as we've had it since 1928, when Dirac came out with his equation. So for whatever reason, and this isn't a hit on you, you haven't been motivated enough in all the time that you've been on earth to at least get as far as the Dirac equation. And this was very interesting to me after I gave the talk in Oxford. New scientist who had done kind of a hatchet job on me to begin with sent a reporter to come to the third version of the talk that I gave, and that person had never heard of the Dirac equation. So you have a person who's completely professionally not qualified to ask these questions, wanting to know, well, how does your theory solve new problems? And like, well, in the case of the Dirac equation, well, tell me about that, I don't know what that is. So then the point is, okay, I got it. You're not even caught up minimally to where we are now, and that's not a knock on you, almost nobody is. But then how does it become my job to digest what has been available for like over 90 years? Well, to me, the open question is whether what's been available for over 90 years can be, there could be a blueprint of a journey that one takes to understand it, not to be able to. Oh, I want to do that with you. And one of the things I think I've been relatively successful at, for example, when you ask other people what gauge theory is, you get these very confusing responses. And my response is much simpler. It's, oh, it's a theory of differentiation, where when you calculate the instantaneous rise over run, you measure the rise not from a flat horizontal, but from a custom endogenous reference level. What do you mean by that? It's like, okay, and then I do this thing with Mount Everest, which is, Mount Everest is how high? Then they give the height. I say, above what? Then they say sea level. And I say, which sea is that in Nepal? They're like, oh, I guess there isn't a sea, because it's landlocked. It's like, okay, well, what do you mean by sea level? Oh, there's this thing called the geoid I'd never heard of. Oh, that's the reference level. That's a custom reference level that we imported. So all sorts of people have remembered the exact height of Mount Everest without ever knowing what it's a height from. Well, in this case, in gauge theory, there's a hidden reference level where you measure the rise in rise over run to give the slope of a line. What if you have different concepts of where that rise should be measured from that vary within the theory? That are endogenous to the theory. That's what gauge theory is. Okay, we have a video here, right? Yeah. Okay, I'm gonna use my phone. If I wanna measure my hand and its slope, this is my attempt to measure it using standard calculus. In other words, the reference level is apparently flat, and I measure the rise above that phone using my hand, okay? If I wanna use gauge theory, it means I can do this, or I can do that, or I can do this, or I can do this, or I could do what I did from the beginning, okay? At some level, that's what gauge theory is. Now, that is an, no, I've never heard anyone describe it that way. So while the community may say, well, who is this guy, and why does he have the right to talk in public? I'm waiting for somebody to jump out of the woodwork and say, you know Eric's whole shtick about rulers and protractors leading to a derivative, derivatives are measured as rise over run above reference level, the reference level's not fit together. Like, I go through this whole shtick in order to make it accessible. I've never heard anyone say it. I'm trying to make, Prometheus would like to discuss fire with everybody else. All right, I'm gonna just say one thing to close out the earlier line, which is what I think we should have continued with. When you take the naturally occurring spinners, the unadorned spinners, the naked spinners, not on this 14-dimensional manifold, but on something very closely tied to it, which I've called the chimeric tangent bundle. That is the object which stands in for the thing that should have had length and angle on it, but just missed, okay? When you take that object and you form spinners on that, and you don't adorn them, so you're still in the single origin story, you get very large spinorial objects upstairs on this 14-dimensional world, Y14, which is part of the observers. When you pull that information back from Y14 down to X4, it miraculously looks like the adorned spinners, the festooned spinners, the spinners that we play with in ordinary reality. In other words, the 14-dimensional world looks like a four-dimensional world plus a 10-dimensional complement. So 10 plus four equals 14. That 10-dimensional complement, which is called a normal bundle, generates spin properties, internal quantum numbers, that look like the things that give our particles personality, that make, let's say, up quarks and down quarks charged by negative 1 3rd or plus 2 3rds, that kind of stuff, or whether or not some quarks feel the weak force and other quarks do not. So the X4 generates Y14. Y14 generates something called the chimeric tangent bundle. Chimeric tangent bundle generates unadorned spinners. The unadorned spinners get pulled back from 14 down to four, where they look like adorned spinners. And we have the right number of them. You thought you needed three, you only got two. But then something else that you'd never seen before broke apart on this journey, and it broke into another copy of the thing that you already have two copies of. One piece of that thing broke off. So now you have two generations plus an imposter third generation, which is, I don't know why we never talk about this possibility in regular physics. And then you've got a bunch of stuff that we haven't seen, which has descriptions. So people always say, does it make any falsifiable predictions? Yes, it does. It says that the matter that you should be seeing next has particular properties that can be read off. Like? Like weak isospin, weak hypercharge, like the responsiveness to the strong force. The one I can't tell you is what energy scale it would happen at. So you can't say if those characteristics can be detected with the current? But it may be that somebody else can. I'm not a physicist. I'm not a quantum field theorist. I can't, I don't know how you would do that. The hope for me is that there's some simple explanations for all of it. Lex, should we have a drink? You're having fun. No, I'm trying to have fun with you. You know that. Yeah, there's a bunch of fun things to talk about here. Anyway, that was how I got what I thought you wanted, which is if you think about the fermions as the artists and the bosons as the brushes and the paint, what I told you is that's how we get the artists. What are the open questions for you in this? What are the challenges? So you're not done. Well, there's things that I would like to have in better order. So a lot of people will say, the reason I hesitate on this is I just have a totally different view than the community. So for example, I believe that general relativity began in 1913 with Einstein and Grossman. Now that was the first of like four major papers in this line of thinking. To most physicists, general relativity happened when Einstein produced a divergence-free gradient, which turned out to be the gradient of the so-called Hilbert or Einstein-Hilbert action. And from my perspective, that wasn't true. This is that it began when Einstein said, look, this is about differential geometry and the final answer is gonna look like a curvature tensor on one side and matter and energy on the other side. And that was enough. And then he published a wrong version of it where it was the Ricci tensor, not the Einstein tensor. Then he corrected the Ricci tensor to make it into the Einstein tensor. Then he corrected that to add a cosmological constant. I can't stand that the community thinks in those terms. There's some things about which, like there's a question about which contraction do I use. There's an Einstein contraction, there's a Ricci contraction. They both go between the same spaces. I'm not sure what I should do. I'm not sure which contraction I should choose. This is called a Shiab operator for ship in a bottle in my stuff. You have this big platform in many ways that inspires people's curiosity about physics and mathematics. Right. And I'm one of those people. Well, great. But then you start using a lot of words that I don't understand. And I might know them, but I don't understand. And what's unclear to me, if I'm supposed to be listening to those words, or if it's just, if this is one of those technical things that's intended for a very small community, or if I'm supposed to actually take those words and start a multi-year study, not a serious study, but the kind of study when you're interested in learning about machine learning, for example, or any kind of discipline. That's where I'm a little bit confused. So you speak beautifully about ideas. You often reveal the beauty in mathematics, in geometry. And I'm unclear in what are the steps I should be taking. I'm curious, how can I explore? How can I play with something? How can I play with these ideas and enjoy the beauty of, not necessarily understanding the depth of a theory that you're presenting, but start to share in the beauty, as opposed to sharing and enjoying the beauty of just the way, the passion with which you speak, which is in itself fun to listen to, but also starting to be able to understand some aspects of this theory that I can enjoy it, and start to build an intuition, what the heck we're even talking about. Because you're basically saying, we need to throw a lot of our ideas of views of the universe out. And I'm trying to find accessible ways in. Not in this conversation. No, I appreciate that. So one of the things that I've done is I've picked on one paragraph from Edward Witten. And I said, this is the paragraph. If I could only take one paragraph with me, this is the one I'd take. And it's almost all in prose, not in equations. And he says, look, this is our knowledge of the universe at its deepest level. And he was writing this during the 1980s. And he has three separate points that constitute our deepest knowledge. And those three points refer to equations. One to the Einstein field equation, one to the Dirac equation, and one to the Yang-Mills-Maxwell equation. Now, one thing I would do is take a look at that paragraph and say, okay, what do these three lines mean? Like it's a finite amount of verbiage. You can write down every word that you don't know. And you can say, what do I think? Done. Now, young man. Yes. There's a beautiful wall in Stony Brook, New York, built by someone who I know you will interview, named Jim Simons. And Jim Simons, he's not the artist, but he's the guy who funded it. World's greatest hedge fund manager. And on that wall contain the three equations that Witten refers to in that paragraph. And so that is the transmission from the paragraph or graph to the wall. Now, that wall needs an owner's manual, which Roger Penrose has written, called The Road to Reality. Let's call that the tome. So this is the subject of the so-called graph wall tome project that is going on in our Discord server and our general group around the portal community, which is how do you take something that purports in one paragraph to say what the deepest understanding man has of the universe in which he lives. It's memorialized on a wall, which nobody knows about, which is an incredibly gorgeous piece of art. And that was written up in a book, which has been written for no man. Maybe it's for a woman, I don't know. But no one should be able to read this book because either you're a professional and you know a lot of this book, in which case it's kind of a refresher to see how Roger thinks about these things. Or you don't even know that this book is a self-contained invitation to understanding our deepest nature. So I would say find yourself in the graph wall tome transmission sequence and join the graph wall tome project if that's of interest. Okay, beautiful. Now just to linger on a little longer, what kind of journey do you see Geometric Unity taking? I don't know. I mean, that's the thing, is that first of all, the professional community has to get very angry and outraged and they have to work through their feeling that this is nonsense, this is bullshit, or like, no, wait a minute, this is really cool. Actually, I need some clarification over here. So there's gonna be some sort of weird coming back together process. Are you already hearing murmurings of that? It was very funny. Officially, I've seen very little. So it's perhaps happening quietly. Yeah. You often talk about we need to get off this planet. Yep. Can I try to sneak up on that by asking what in your kind of view is the difference, the gap between the science of it, the theory, and the actual engineering of building something that leverages the theory to do something? Like, how big is that? We don't know. Gap. I mean, if you have 10 extra dimensions to play with that are the rulers and protractors of the world themselves, can you gain access to those dimensions? Do you have a hunch? I don't know. I don't wanna get ahead of myself. Because you have to appreciate, I can have hunches and I can jaw off. But one of the ways that I'm succeeding in this world is to not bow down to my professional communities nor to ignore them. Like, I'm actually interested in the criticism. I just wanna denature it so that it's not mostly interpersonal and irrelevant. I believe that they don't want me to speculate. And I don't need to speculate about this. I can simply say I'm open to the idea that it may have engineering prospects and it may be a death sentence. We may find out that there's not enough new here. That even if it were right, that there would be nothing new to do. Can't tell you. That's what you mean by death sentences, there would not be exciting breakthroughs to follow on. Wouldn't it be terrible if you couldn't, like, you can do new things in an Einsteinian world that you couldn't do in a Newtonian world. Right. You know, like you have twin paradoxes or Lorentz contraction of length or any one of a number of new cool things happen in relativity theory that didn't happen for Newton. What if there wasn't new stuff to do at the next and final level? So first of all. That would be quite sad. Let me ask a silly question, but. We'll say it with a straight face. Impossible. So let me mention Elon Musk. What are your thoughts about, he's more, you're more on the physics theory side of things. He's more on the physics engineering side of things in terms of SpaceX efforts. What do you think of his efforts to get off this planet? Well, I think he's the other guy who's semi-serious about getting off this planet. I think there are two of us who are semi-serious about getting off the planet. What do you think about his methodology and yours when you look at them? Don't, I don't wanna be against Elon, because I was so excited that your top video was Ray Kurzweil and then I did your podcast and we had some chemistry, so it zoomed up. And I thought, okay, I'm gonna beat Ray Kurzweil. So just as I'm coming up on Ray Kurzweil, you're like, and now, Alex Fridman special Elon Musk, and he blew me out of the water. So I don't wanna be petty about it. I wanna say that I don't, but I am. Okay, but here's the funny part. He's not taking enough risk. Like he's trying to get us to Mars. Imagine that he got us to Mars, the moon, and we'll throw in Titan. And nowhere good enough. The diversification level is too low. Now there's a compatibility. First of all, I don't think Elon is serious about Mars. I think Elon is using Mars. As a narrative, as a story, as a dream. To make the moon jealous. To make the, no. I think he's using it as a story to organize us to reacquaint ourselves with our need for space, our need to get off this planet. It's a concrete thing. He's shown that, many people think that he's shown that he's the most brilliant and capable person on the planet. I don't think that's what he showed. I think he showed that the rest of us have forgotten our capabilities. And so he's like the only guy who has still kept the faith and is like, what's wrong with you people? So you think the lesson we should draw from Elon Musk is there's a capable person within a lot of us. Elon makes sense to me. In what way? He's doing what any sensible person should do. He's trying incredible things and he's partially succeeding, partially failing. To try to solve the obvious problems before us. Duh. But he comes up with things like, I got it. We'll come up with a battery company but batteries aren't sexy so we'll make a car around it. Like, great. Or any one of a number of things. Elon is behaving like a sane person and I view everyone else as insane. And my feeling is that we really have to get off this planet. We have to get out of this, we have to get out of the neighborhood. Dilingual a little bit, do you think that's a physics problem or an engineering problem? I think it's a cowardice problem. I think that we're afraid that we had 400 hitters of the mind, like Einstein and Dirac, and that era is done and now we're just sort of copy editors. So is some of it money? Like, if we become brave enough to go outside the solar system, can we afford to, financially? Well, I think that that's not really the issue. The issue is, look what Elon did well. He amassed a lot of money. And then he plowed it back in and he spun the wheel and he made more money. And now he's got FU money. Now the problem is, is that a lot of the people who have FU money are not people whose middle finger you ever want to see. I want to see Elon's middle finger. I want to see what he's gonna do. What do you mean by that? Or like when you say, fuck it, I'm gonna do the biggest fucks ever. He's gonna do whatever the fuck he wants. Yeah, right? Fuck you, fuck anything that gets in his way that he can afford to push out of his way. And you're saying he's not actually even doing that enough. No, I'm. He's not going. Please, I'm gonna go, Elon's doing fine with his money. I just want him to enjoy himself, have the most Dionysian. But you're saying Mars is playing it safe. He doesn't know how to do anything else. He knows rockets. Yeah. And he might know some physics at a fundamental level. Yeah, I guess, okay, just let me just go right back to you. How much physics do you really, how much brilliant breakthrough ideas on the physics side do you need to get off this planet? I don't know. And I don't know whether, like in my most optimistic dream, I don't know whether my stuff gets us off the planet. But it's hope. It's hope that there's a more fundamental theory that we can access, that we don't need, whose elegance and beauty will suggest that this is probably the way the universe goes. Like you have to say this weird thing, which is this I believe. And this I believe is a very dangerous statement. But this I believe, I believe that my theory points the way. Now, Elon might or might not be able to access my theory. I don't know what he knows. But keep in mind, why are we all so focused on Elon? It's really weird. It's kind of creepy too. Why? He's just the person who's just asking the obvious questions and doing whatever he can. But he makes sense to me. You see, Craig Venter makes sense to me. Jim Watson makes sense to me. But we're focusing on Elon because he somehow is rare. Well, that's the weird thing. Like we've come up with a system that eliminates all Elon from our pipeline. And Elon somehow snuck through when they weren't quality adjusting everything, you know? And this idea of disk, right? Distributed idea suppression complex. Yeah. Is that what's bringing the Elon's of the world down? You know, it's so funny. He's asking Joe Rogan, is that a joint? Well, what will happen if I smoke it? What will happen to the stock price? What will happen if I scratch myself in public? What will happen if I say what I think about Thailand or COVID or who knows what? And everybody's like, don't say that. Say this, go do this, go do that. Well, it's crazy making. It's absolutely crazy making. And if you think about what we put people through, we need to get people who can use FU money, the FU money they need to insulate themselves from all of the people who know better. Because my nightmare is that why did we only get one Elon? What if we were supposed to have thousands and thousands of Elon? And the weird thing is like this is all that remains. You're looking at like Obi-Wan and Yoda, and it's like this is the only, this is all that's left after Order 66 has been executed. And that's the thing that's really upsetting to me is we used to have Elon's five deep, and then we could talk about Elon in the context of his cohort. But this is like if you were to see a giraffe in the Arctic with no trees around, you'd think why the long neck? What a strange sight, you know? How do we get more Elons? How do we change the, so I think that you've, so we know MIT and Harvard. So maybe returning to our previous conversation, my sense is that the Elons of the world are supposed to come from MIT and Harvard. Right. And how do you change? Let's think of one that MIT sort of killed. Have any names in mind? Aaron Schwartz leaps to my mind. Yeah. Okay, are we MIT supposed to shield the Aaron Schwartz's from, I don't know, journal publishers? Or are we supposed to help the journal publishers so that we can throw 35 year sentences in his face or whatever it is that we did that depressed him? Okay, so here's my point. I want MIT to go back to being the home of Aaron Schwartz. And if you wanna send Aaron Schwartz to a state where he's looking at 35 years in prison or something like that, you are my sworn enemy. You are not MIT. Yeah. You are the traitorous, irresponsible, middle brow, pencil pushing, green eye shade fool that needs to not be in the seat at the presidency of MIT period, the end. Get the fuck out of there and let one of our people sit in that chair. And the thing that you've articulated is that the people in those chairs are not the way they are because they're evil or somehow morally compromised. That it's just that that's the distributed nature. Is that there's some kind of aspect of the system that's just the people who wed themselves to the system. They adapt every instinct. And the fact is is that they're not going to be on Joe Rogan smoking a blunt. Let me ask a silly question. Do you think institutions generally just tend to become that? No, we get some of the institutions. We get Caltech. Here's what we're supposed to have. We're supposed to have Caltech. We're supposed to have Reed. We're supposed to have Deep Springs. We're supposed to have MIT. We're supposed to have a part of Harvard. And when the sharp elbow crowd comes after the sharp mind crowd, we're supposed to break those sharp elbows and say, don't come around here again. So what are the weapons that the sharp minds are supposed to use in our modern day? So to reclaim MIT, what is the, what's the future? Are you kidding me? First of all, assume that this is being seen at MIT. Hey everybody. Yes, okay. Hey everybody. Try to remember who you are. You're the guys who put the police car on top of the great dump. You guys came up with the great breast of knowledge. You created a Tetris game in the green building. Now, what is your problem? They killed one of your own. You should make their life a living hell. You should be the ones who keep the memory of Aaron Schwartz alive. And all of those hackers and all of those mutants, you know, it's like, it's either our place or it isn't. And if we have to throw 12 more pianos off of the roof, right, if Harold Edgerton was taking those photographs, you know, with slow-mo back in the 40s, if Noam Chomsky is on your faculty, what the hell is wrong with you kids? You are the most creative and insightful people and you can't figure out how to defend Aaron Schwartz? That's on you guys. So some of that is giving more power to the young, like you said, to the brave, to the bold. Taking power from the feeble and the middle-brow. Yeah, but what is the mechanism? To me, I don't know. You have some nine-volt batteries? No, I. You have some copper wire? I tend to. Do you have a capacitor? I tend to believe you have to create an alternative and make the alternative so much better that it makes MIT obsolete unless they change. And that's what forces change. So as opposed to somehow. Okay, so use projection mapping. What's projection mapping? Where you take some complicated edifice and you map all of its planes and then you actually project some unbelievable graphics, re-skinning a building, let's say, at night. That's right, yeah. Okay, so you wanna do some graffiti art with lights. You basically wanna hack the system? No, I'm saying, look, listen to me, Liv. We're smarter than they are. And you know what they say? They say things like, I think we need some geeks. Get me two PhDs. You treat PhDs like that, that's a bad move. Because PhDs are capable. And we act like our job is to peel grapes for our betters. Yeah, that's a strange thing. And you speak about it very eloquently. It's how we treat basically the greatest minds in the world, which is like at their prime, which is PhD students. We pay them nothing. I'm done with it. Yeah. Right, we gotta take what's ours. So take back MIT. Become ungovernable. Become ungovernable. And by the way, when you become ungovernable, don't do it by throwing food. Don't do it by pouring salt on the lawn like a jerk. Do it through brilliance. Because what you, Caltech and MIT can do, and maybe Rensselaer Polytechnic or Worcester Polytech, I don't know, Lehigh. God damn it, what's wrong with you technical people? You act like you're a servant class. It's unclear to me how you reclaim it except with brilliance, like you said. But to me, the way you reclaim it with brilliance is to go outside the system. Aaron Schwartz came from the Elon Musk class. What you guys gonna do about it? Right? The super capable people need to flex, need to be individual, they need to stop giving away all their power to a zeitgeist or a community or this or that. You're not indoor cats, you're outdoor cats. Go be outdoor cats. Do you think we're gonna see this? You were the one asking me before, what about the World War II generation? All I'm trying to say is that there's a technical revolt coming. You wanna talk about this? I'm trying to lead it. I'm trying to see. No, you're not trying to lead it. I'm trying to get a blueprint here. All right, Lex. Yeah. How angry are you about our country pretending that you and I can't actually do technical subjects so that they need an army of kids coming in from four countries in Asia? It's not about the four countries in Asia. It's not about those kids. It's about lying about us, that we don't care enough about science and technology, that we're incapable of it, as if we don't have Chinese and Russians and Koreans and Croatians. Like, we've got everybody here. The only reason you're looking outside is that you wanna hire cheap people from the family business because you don't wanna pass the family business on. And you know what? You didn't really build the family business. It's not yours to decide. You the boomers and you the silent generation, you did your bit, but you also fouled a lot of stuff up, and you're custodians. You are caretakers. You are supposed to hand something. What you did instead was to gorge yourself on cheap foreign labor, which you then held up as being much more brilliant than your own children, which was never true. See, but I'm trying to understand how we create a better system without anger, without revolution. Ah. Not by kissing and hugs, but by, I mean, I don't understand within MIT what the mechanism of building a better MIT is. We're not gonna pay Elsevier. Aaron Schwartz was right. JSTOR is an abomination. But why, who within MIT, who within institutions is going to do that when, just like you said, the people who are running the show are more senior. Why did I get Frank Wilczek to speak out? So you're, it's basically individuals that step up. I mean, one of the surprising things about Elon is that one person can inspire so much. He's got academic freedom. It just comes from money. I don't agree with that. You think money, okay, so yes, certainly. Sorry, and testicles. You've, yes, but I think that testicles is more important than money. Right. Or guts. I think, I do agree with you. You speak about this a lot, that because the money in the academic institutions has been so constrained that people are misbehaving in horrible ways. But I don't think that if we reverse that and give a huge amount of money, people will all of a sudden behave well. I think it also takes guts. No, you need to give people security. Security, yes. Like you need to know that you have a job on Monday when on Friday you say, I'm not so sure I really love diversity and inclusion. And somebody's like, wait, what? You didn't love diversity? We had a statement on diversity and inclusion. You wouldn't sign? Are you against the inclusion part? Or are you against diversity? Do you just not like people like you? Actually, that has nothing to do with anything. You're making this into something that it isn't. I don't want to sign your goddamn stupid statement. And get out of my lab. Right, get out of my lab. It all begins from the middle finger. Get out of my lab. The administrators need to find other work. Yeah, listen, I agree with you. And I hope to seek your advice and wisdom as we change this. Because I'd love to see. I will visit you in prison if that's what you're asking. I have no, I think prison is great. You get a lot of reading done. And good working out. Well, let me ask something I brought up before as the Nietzsche quote of, beware that when fighting monsters, you yourself do not become a monster. For when you gaze long into the abyss, the abyss gazes into you. Are you worried that your focus on the flaws in the system that we've just been talking about has damaged your mind or the part of your mind that's able to see the beauty in the world in the system? That because you have so sharply been able to see the flaws in the system, you can no longer step back and appreciate its beauty? Look, I'm the one who's trying to get the institutions to save themselves by getting rid of their inhabitants but leaving the institution. Like a neutron bomb that removes the unworkable leadership class but leaves the structures. So I. So the leadership class is really the problem. The leadership class is the problem. But the individual, like the professors, the individual scholars. Well, the professors are gonna have to go back into training to remember how to be professors. Like people are cowards at the moment because if they're not cowards, they're unemployed. Yeah, that's one of the disappointing things I've encountered is to me, tenure. But nobody has tenure now. Whether they do or not, they certainly don't have the kind of character and fortitude that I was hoping to see. To me. But they'd be gone. See, you're dreaming about the people who used to live at MIT. You're dreaming about the previous inhabitants of your university. And if you looked at somebody like, Isidore Singer is very old. I don't know what state he's in. But that guy was absolutely the real deal. And if you look at Noam Chomsky, tell me that Noam Chomsky has been muzzled. Right? Yeah. Now, what I'm trying to get at is you're talking about younger, energetic people. But those people, like when I say something like, I'm against, I'm for inclusion and I'm for diversity, but I'm against diversity and inclusion TM. Like the movement. Well, I couldn't say that if I was a professor. Oh my God, he's against our sacred document. Okay, well, in that kind of a world, do you want to know how many things I don't agree with you on? Like we could go on for days and days and days. All of the nonsense that you've parroted inside of the institution. Any sane person has no need for it. They have no want or desire. Do you think you have to have some patience for nonsense when many people work together in a system? How long has string theory gone on for and how long have I been patient? Okay, so you're talking about. So there's a limit to patience, I imagine. You're talking about like 36 years of modern nonsense in string theory. So you can do like eight to 10 years, but not more. I can do 40 minutes. This is 36 years. Well, you've done that over two hours already. No, but it's. I appreciate it. But it's been 36 years of nonsense since the anomaly cancellation in string theory. It's like, what are you talking about about patience? I mean, Lex, you're not even acting like yourself. Well, you're trying to stay in the system. I'm not trying. I'm not. I'm trying to see if perhaps. So my hope is that the system just has a few assholes in it, which you highlight. And the fundamentals of the system are broken. Because if the fundamentals of the systems are broken, then I just don't see a way for MIT to succeed. I don't see how young people take over MIT. I don't see how. By inspiring us. You know, the great part about being at MIT, like when you saw the genius in these pranks, the heart, the irreverence. It's like, don't, we were talking about Tom Lehrer the last time. Tom Lehrer was as naughty as the day is long. Agreed? Agreed. Was he also a genius? Was he well-spoken? Was he highly cultured? He was so talented, so intellectual, that he could just make fart jokes morning, noon, and night. Okay. Well, in part, the right to make fart jokes, the right to, for example, put a functioning phone booth that was ringing on top of the Great Dome at MIT has to do with, we are such badasses that we can actually do this stuff. Well, don't tell me about it anymore. Go break the law. Go break the law in a way that inspires us and makes us not want to prosecute you. Break the law in a way that lets us know that you're calling us out on our bullshit, that you're filled with love, and that our technical talent has not gone to sleep. It's not incapable. You know, and if the idea is that you're gonna dig a moat around the university and fill it with tiger sharks, that's awesome, because I don't know how you're gonna do it. But if you actually manage to do that, I'm not gonna prosecute you under a reckless endangerment. That's beautifully put. I hope those, first of all, they'll listen. I hope young people at MIT will take over in this kind of way. In the introduction to your podcast episode on Jeffrey Epstein, you give to me a really moving story, but unfortunately for me, too brief, about your experience with a therapist and a lasting terror that permeated your mind. Can you go there? Can you tell? I don't think so. I mean, I appreciate what you're saying. I said it obliquely. I said enough. There are bad people who cross our paths, and the current vogue is to say, oh, I'm a survivor, I'm a victim, I can do anything I want. This is a broken person, and I don't know why I was sent to a broken person as a kid. And to be honest with you, I also felt like in that story, I say that I was able to say no, and this was like the entire weight of authority, and he was misusing his position, and I was also able to say no. What I couldn't say no to was having him re-inflicted in my life. Right, so you were sent back a second time. I tried to complain about what had happened, and I tried to do it in a way that did not immediately cause horrific consequences to both this person and myself, because we don't have the tools to deal with sexual misbehavior. We have nuclear weapons, we don't have any way of saying this is probably not a good place or a role for you at this moment as an authority figure, and something needs to be worked on. So in general, when we see somebody who is misbehaving in that way, our immediate instinct is to treat the person as Satan, and we understand why. We don't want our children to be at risk. Now, I personally believe that I fell down on the job and did not call out the Jeffrey Epstein thing early enough because I was terrified of what Jeffrey Epstein represents, and this recapitulated the old terror, trying to tell the world this therapist is out of control. And when I said that, the world responded by saying, well, you have two appointments booked, and you have to go for the second one. So I got re-inflicted into this office on this person who was now convinced that I was about to tear down his career and his reputation and might have been on the verge of suicide for all I know. I don't know. But he was very, very angry, and he was furious with me that I had breached a sacred confidence of his office. And what kind of ripple effects does that have, has that had to the rest of your life, the absurdity and the cruelty of that? I mean, there's no sense to it. Well, see, this is the thing people don't really grasp, I think. There's an academic who I got to know many years ago named Jennifer Freud, who has a theory of betrayal, which she calls institutional betrayal. And her gambit is that when you were betrayed by an institution that is sort of like a fiduciary or a parental obligation to take care of you, that you find yourself in a far different situation with respect to trauma than if you were betrayed by somebody who's a peer. And so I think that in my situation, I kind of repeat a particular dynamic with authority. I come in not following all the rules, trying to do some things, not trying to do others, blah, blah, blah. And then I get into a weird relationship with authority. And so I have more experience with what I would call institutional betrayal. Now, the funny part about it is that when you don't have masks or PPE in a influenza-like pandemic, and you're missing ICU beds and ventilators, that is ubiquitous institutional betrayal. So I believe that in a weird way, I was very early, the idea of, and this is like the really hard concept, pervasive or otherwise universal institutional betrayal, where all of the institutions, you can count on any hospital to not charge you properly for what their services are. You can count on no pharmaceutical company to produce the drug that will be maximally beneficial to the people who take it. You know that your financial professionals are not simply working in your best interest. And that issue had to do with the way in which growth left our system. So I think that the weird thing is is that this first institutional betrayal by a therapist left me very open to the idea of, okay, well, maybe the schools are bad, maybe the hospitals are bad, maybe the drug companies are bad, maybe our food is off, maybe our journalists are not serving journalistic ends. And that was what allowed me to sort of go all the distance and say, huh, I wonder if our problem is that something is causing all of our sense-making institutions to be off. That was the big insight. And that, and tying that to a single ideology, what if it's just about growth? They were all built on growth, and now we've promoted people who are capable of keeping quiet that their institutions aren't working. So the privileged, silent aristocracy, the people who can be counted upon, not to mention a fire when a raging fire is tearing through a building. But nevertheless, it's, how big of a psychological burden is that? It's huge, it's terrible, it's crushing. It's very comforting to be the parental, I mean, I don't know, I treasure, I mean, we were just talking about MIT. We can, I can intellectualize and agree with everything you're saying, but there's a comfort, a warm blanket of being within the institution. And up until Aaron Schwartz, let's say. In other words, now, if I look at the provost and the president as mommy and daddy, you did what to my big brother? You did what to our family? You sold us out in which way? What secrets left for China? You hired which workforce? You did what to my wages? You took this portion of my grant for what purpose? You just stole my retirement through a fringe rate. What did you do? But can you still, I mean, the thing is about this view you have is it often turns out to be sadly correct. But this is the thing. But let me just, in this silly hopeful thing, do you still have hope in institutions? Can you within your, psychologically. Yes. I'm referring not intellectually, because you have to carry this burden, can you still have a hope within you? When you sit at home alone, and as opposed to seeing the darkness within these institutions, seeing a hope. Well, but this is the thing I want to confront. Not for the purpose of a dust up. I believe, for example, if you've heard episode 19, that the best outcome is for Carol Greider to come forward, as we discussed in episode 19. With your brother, Brett Weinstein. And say, you know what? It's a great episode. I screwed up. He did call, he did suggest the experiment. I didn't understand that it was his theory that was producing it. Maybe I was slow to grasp it. But my bad, and I don't want to pay for this bad choice on my part, let's say, for the rest of my career. I want to own up, and I want to help make sure that we do what's right with what's left. And that's one little case within the institution that you would like to see made. I would like to see MIT very clearly come out and say, you know, Margot O'Toole was right when she said David Baltimore's lab here produced some stuff that was not reproducible with Teresa Imanishi-Kari's research. I want to see the courageous people. I would like to see the Aaron Schwartz wing of the computer science department. Yeah, wouldn't, no, let's think about it. Wouldn't that be great if they said, you know, an injustice was done, and we're gonna write that wrong just as if this was Alan Turing? Which I don't think they've written that wrong. Well, then let's have the Turing-Schwartz wing. The Turing-Schwartz, they're starting a new college of computing. It wouldn't be wonderful to call it the Turing-Schwartz. I would like to have the Madame Wu wing of the physics department, and I'd love to have the Emmy Noether statue in front of the math department. I mean, like, you want to get excited about actual diversity and inclusion? Yeah. We'll go with our absolute best people who never got theirs, because there is structural bigotry, you know? But if we don't actually start celebrating the beautiful stuff that we're capable of when we're handed heroes and we fumble them into the trash, what the hell? I mean, Lex, this is such nonsense. We just, just pulling our head out. You know, on everyone's secum should be tattooed. If you can read this, you're too close. Beautifully put, and I'm a dreamer just like you. So I don't see as much of the darkness, genetically or due to my life experience, but I do share the hope. For MIT, the institution that we care a lot about. We both do. Yeah, and Harvard, the institution I don't give a damn about, but you do. I love Harvard. I'm just kidding. I love Harvard, but Harvard and I have a very difficult relationship. And part of what, you know, when you love a family that isn't working, I don't want to trash, I didn't bring up the name of the president of MIT during the Aaron Schwartz period. It's not vengeance. I want the rot cleared out. I don't need to go after human beings. Yeah. Just like you said, with the DISC formulation, the individual human beings don't necessarily carry the... It's those chairs that are so powerful in which they sit. It's the chairs, not the humans. It's not the humans. Without naming names, can you tell the story of your struggle during your time at Harvard? Maybe in a way that tells the bigger story of the struggle of young, bright minds that are trying to come up with big, bold ideas within the institutions that we're talking about. You can start. I mean, in part, it starts with coffee, with a couple of Croatians in the math department at MIT. And we used to talk about music and dance and math and physics and love and all this kind of stuff, as Eastern Europeans loved to, and I ate it up. And my friend, Gordana, who was an instructor in the MIT math department when I was a graduate student at Harvard, said to me, and I'm probably gonna do a bad version of her accent. There we go. Will I see you tomorrow at the secret seminar? And I said, what secret seminar? Eric, don't joke. I said, I'm not used to this style of humor, Gordana. Eric, the secret seminar that your advisor is running. I said, what are you talking about? Ha ha ha. You know, your advisor is running a secret seminar on this aspect. I think it was like the Chern-Simons invariant. Not sure what the topic was again, but she gave me the room number and the time and she was like not cracking a smile. I've never known her to make this kind of a joke. And I thought this was crazy. And I was trying to have an advisor. I didn't want an advisor, but people said you have to have one, so I took one. And I went to this room like 15 minutes early and there was not a soul inside it. It was outside of the math department. And it was still in the same building, the Science Center at Harvard. And I sat there and I let five minutes go by, I let seven minutes go by, 10 minutes go by, there was nobody. I thought okay, so this was all an elaborate joke. And then like three minutes to the hour, this graduate student walks in and like sees me and does a double take. And then I start to see the professors in geometry and topology start to file in. And everybody's like very disconcerted that I'm in this room. And finally the person who was supposed to be my advisor walks in to the seminar and sees me and goes white as a ghost. And I realized that the secret seminar is true. That the department is conducting a secret seminar on the exact topic that I'm interested in, not telling me about it. And that these are the reindeer games that the Rudolphs of the department are not invited to. And so then I realized, okay, I did not understand it. There's a parallel department. And that became the beginning of an incredible odyssey in which I came to understand that the game that I had been sold about publication, about blind refereeing, about openness and scientific transmission of information was all a lie. I came to understand that at the very top there's a second system that's about closed meetings and private communications and agreements about citation and publication that the rest of us don't understand. And that in large measure that is the thing that I won't submit to. And so when you ask me questions like, well, why wouldn't you feel good about talking to your critics? Why wouldn't you feel? The answer is, oh, you don't know. Like if you stay in a nice hotel, you don't realize that there's an entire second structure inside of that hotel where there's usually a worker's cafe in a resort complex that isn't available to the people who are staying in the hotel. And then there are private hallways inside the same hotel that are parallel structures. So that's what I found, which was in essence, just the way you can stay hotels your whole life and not realize that inside of every hotel is a second structure that you're not supposed to see as the guest. There is a second structure inside of academics that behaves totally differently with respect to how people get dinged, how people get their grants taken away, how this person comes to have that thing named after them. And by pretending that we're not running a parallel structure, I have no patience for that anymore. So I got a chance to see how the game, how hardball is really played at Harvard. And I'm now eager to play hardball back with the same people who played hardball with me. Let me ask two questions on this. So one, do you think it's possible, so I call those people assholes. That's the technical term. Do you think it's possible that that's just not the entire system, but a part of the system? You can navigate, you can swim in the waters and find the groups of people who do aspire to. The guy who rescued my PhD was one of the people who filed in to the secret seminar. Right, but are there people who are outside of this? Is he an asshole? Well, yes, I was a bad. No, but I'm trying to make this point, which is this isn't my failure to correctly map these people, it's yours. You have a simplification that isn't gonna work. I think, okay, asshole's the wrong term. I would say lacking of character. What would you have had these people do? Why did they do this? Why have a secret seminar? I don't understand the exact dynamics of a secret seminar, but I think the right thing to do is to, I mean, to see individuals like you. There might be a reason to have a secret seminar, but they should detect that an individual like you, a brilliant mind who's thinking about certain ideas could be damaged by this. I don't think that they see it that way. The idea is we're going to sneak food to the children we want to survive. Yeah, so that's highly problematic, and there should be people within that room. But I'm trying to say, this is the thing, the ball that's thrown but won't be caught. The problem is they know that most of their children won't survive, and they can't say that. I see, sorry to interrupt. You mean that the fact that the whole system is underfunded, that they naturally have to pick favorites. They live in a world which reached steady state at some level, let's say, in the early 70s. And in that world, before that time, you have a professor like Norman Steenrod, and you'd have 20 children that is graduate students, and all of them would go on to be professors, and all of them would want to have 20 children. So you start taking higher and higher powers of 20, and you see that the system could not, it's not just about money, the system couldn't survive. So the way it's supposed to work now is that we should shut down the vast majority of PhD programs, and we should let the small number of truly top places populate mostly teaching and research departments that aren't PhD producing. We don't want to do that because we use PhD students as a labor force. So the whole thing has to do with growth, resources, dishonesty, and in that world, you see all of these adaptations to a ruthless world, where the key question is where are we gonna bury this huge number of bodies of people who don't work out? So my problem was I wasn't interested in dying. So you clearly highlighted there's aspects of the system that are broken, but as an individual, is your role to exit the system, or just acknowledge that it's a game and win it? My role is to survive and thrive in the public eye. In other words, when you have an escapee of the system. Like yourself. Such as. And that person says, you know, I wasn't exactly finished. Let me show you a bunch of stuff. Let me show you that the theory of telomeres never got reported properly. Let me show you that all of marginal economics is supposed to be redone with a different version of the differential calculus. Let me show you that you didn't understand the self-dual Yang-Mills equations correctly in topology and physics, because they're in fact much more broadly found, and it's only the mutations that happen in special dimensions. There are lots of things to say, but this particular group of people, like if you just take, where are all the Gen X and millennial university presidents? All right, okay. They're all in a holding pattern. Now, why in this story of telomeres, was it an older professor and a younger graduate student? It's this issue of what would be called interference competition. So for example, orcas try to drown minke whales by covering their blowholes so that they suffocate because the needed resource is air. Okay, well, what do the universities do? They try to make sure that you can't be viable, that you need them, that you need their grants, you need to be zinged with overhead charges or fringe rates or all of the games that the locals love to play. Well, my point is, okay, what's the cost of this? How many people died as a result of these interference competition games? When you take somebody like Douglas Prasher who did green fluorescent protein, and he drives a shuttle bus, right, because his grant runs out, and he has to give away all of his research, and all of that research gets a Nobel Prize, and he gets to drive a shuttle bus for $35,000 a year. What do you mean by died? Do you mean their career, their dreams, their passions? Yeah, the whole, as an academic, Doug Prasher was dead for a long period of time. Okay, so as a person who's escaped the system, can't you at this, because you also have in your mind a powerful theory that may turn out to be useful, maybe not. Let's hope. Can't you also play the game enough, like with the children, so like publish, but also- If you told me that this would work, really what I wanna do, you see, is I would love to revolutionize a field with an h-index of zero. Like we have these proxies that count how many papers you've written, how cited are the papers you've written. All this is nonsense. That's interesting, sorry, what do you mean by a field with an h-index of zero? So a totally new field. H-index counts somehow how many papers have you gotten that get so many citations. Let's say h-index undefined. Like for example, I don't have an advisor for my PhD, but I have to have an advisor as far as something called the Math Genealogy Project that tracks who advised who, who advised whom down the line. So I am my own advisor, which sets up a loop, right? How many students do I have an infinite number? Or descendants. They don't want to have that story. So I have to have formal advisor, Raoul Bott. And my Wikipedia entry, for example, says that I was advised by Raoul Bott, which is not true. So you get fit into a system that says, well, we have to know what your h-index is. We have to know, you know, where are you a professor if you want to apply for a grant? It makes all of these assumptions. What I'm trying to do is in part to show all of this is nonsense. This is proxy BS that came up in the institutional setting. And right now, it's important for those of us who are still vital, like Elon, it would be great to have Elon as a professor of physics and engineering. Right? It seems ridiculous to say, but. No, just as a shot in the arm. You know, like, it'd be great to have Elon at Caltech. Even one day a week. One day a month. Okay, well, why can't we be in there? It's the same reason. Well, why can't you be on The View? Why can't you be on Bill Maher? We need to know what you're gonna do before we take you on the show. Well, I don't wanna tell you what I'm gonna do. Do you think you need to be able to dance the dance a little bit? I can dance the dance fine. To be on The View. Oh, come on. So you can, yeah, you do. I can do that fine. Here's where it's, the place that it goes south is there's like a set of questions that get you into this more adversarial stuff. And you've in fact asked some of those more adversarial questions this setting. And they're not things that are necessarily aggressive, but they're things that are making assumptions. So when you have a question, it's like, Lex, are you avoiding your critics? It's just like, okay, well, why did you frame that that way? Or the next question would be, do you think that you should have a special exemption and that you should have the right to break rules and everyone else should have to follow them? Like that question I find enervating. It doesn't really come out of anything meaningful. It's just like we feel we're supposed to ask that of the other person to show that we're not captured by their madness. That's not the real question you wanna ask me. If you wanna get really excited about this, you wanna ask, do you think this thing is right? Yeah, weirdly I do. Do you think that it's going to be immediately seen to be right? I don't. I think it's gonna have an interesting fight and it's gonna have an interesting evolution. And well, what do you hope to do with it in non-physical terms? Gosh, I hope it revolutionizes our relationship well with people outside of the institutional framework and it re-inflicts us into the institutional framework where we can do the most good to bring the institutions back to health. It's like these are positive uplifting questions. If you had Frank Wilczek, you wouldn't say, Frank, let's be honest, you have done very little with your life after the original huge show that you used to break under the physics. We weirdly ask people different questions based upon how they sit down. Yeah, that's very strange, right? But you have to understand that, so here's the thing, I get these days a large number of emails from people with the equivalent of a theory of everything for AGI. And I use my own radar, BS radar, to detect unfairly perhaps whether they're full of shit or not. Right. I love where you're going with this, by the way. And my concern I often think about is there's elements of brilliance in what people write to me. And I'm trying to, right now, as you made it clear, the kind of judgments and assumptions we make, how am I supposed to deal with you who are an outsider of the system and think about what you're doing? Because my radar is saying you're not full of shit. You're also not completely outside of the system. That's right, you've danced beautifully. You've actually got all the credibility that you're supposed to get, all the nice little stamps of approval. Not all, but a large enough amount. And you, I mean, it's hard to put into words exactly why you sound, whether your theory turns out to be good or not, you sound like a special human being. I appreciate that, and thank you very much for saying that. In a good way, right? All right. But what am I supposed to do with that flood of emails from AGI folks? Why do I sound different? I don't know. And I would like to systemize that, I don't know. Look, when you're talking to people, you very quickly can surmise. Am I claiming to be a physicist? No, I say it every turn, I'm not a physicist. When you say something about bundles, you say, well, can you explain it differently? I'm pushing around on this area, that lever over there. I'm trying to find something that we can play with and engage, and you know, another thing is that I'll say something at scale. So if I was saying completely wrong things about bundles on the Joe Rogan program, you don't think that we wouldn't hear a crushing chorus? Yes. And same thing with geometric unity. So I put up this video from this Oxford lecture. I understand that it's not a standard lecture, but you haven't heard the most brilliant people in the field say, well, this is obviously nonsense. They don't know what to make of it. And they're gonna hide behind, well, he hasn't said enough detail. Where's the paper? And where's the paper? I've seen the criticism. I've gotten the same kind of criticism. I've published a few things, and like especially stuff related to Tesla. We did studies on Tesla vehicles, and the kind of criticism I've gotten showed that they're completely. Oh, right, like the guy who had Elon Musk on his program twice is gonna give us an accurate assessment. Yeah, exactly, exactly. It's just very low level. Like without actually ever addressing the content. You know, Lex, I think that in part, you're trying to solve a puzzle that isn't really your puzzle. I think you know that I'm sincere. You don't know whether the theory is gonna work or not. And you know that it's not coming out of somebody who's coming out of left field. Like the story makes sense. There's enough that's new and creative and different in other aspects where you can check me that your real concern is, are you really telling me that when you start breaking the rules, you see the system for what it is, and it's become really vicious and aggressive? And the answer is yes. And I had to break the rules in part because of learning issues, because I came into this field with a totally different set of attributes. My profile just doesn't look like anybody else's remotely. But as a result, what that did is it showed me what is the system true to its own ideals? Or does it just follow these weird procedures and then when you take it off the rails, it behaves terribly. And that's really what my story I think does is it just says, well, he completely takes the system into new territory where it's not expecting to have to deal with somebody with these confusing sets of attributes. And I think what he's telling us is he believes it behaves terribly. Now, if you take somebody with perfect standardized tests and a winner of math competitions and you put them in a PhD program, they're probably gonna be okay. I'm not saying that the system breaks down for everybody under all circumstances. I'm saying when you present the system with a novel situation, at the moment, it will almost certainly break down with probability approaching 100%. But to me, the painful and the tragic thing is it, sorry to bring out my motherly instinct, but it feels like it's too much, it could be too much of a burden to exist outside the system. Maybe, but first of all, I've got a podcast that I kind of like. I've got amazing friends. I have a life which has more interesting people passing through it than I know what to do with. And they haven't managed to kill me off yet. So, so far, so good. Speaking of which, you host an amazing podcast that we've mentioned several times but should mention over and over, The Portal, where you somehow manage every single conversation is a surprise. You go, I mean, not just the guests, but just the places you take them, the kind of ways they become challenging and how you recover from that. I mean, it's, there's just, it's full of genuine human moments. So I really appreciate what you're, it's a fun podcast to listen to. Let me ask some silly questions about it. What have you learned about conversation, about human to human conversation? Well, I have a problem that I haven't solved on The Portal, which is that in general, when I ask people questions, they usually find their deeply grooved answers. And I'm not so interested in all of the deeply grooved answers. And so there's a complaint, which I'm very sympathetic to actually, that I talk over people, that I won't sit still for the answer. And I think that that's weirdly sort of correct. It's not that I'm not interested in hearing other voices. It's that I'm not interested in hearing the same voice on my program that I could have gotten on somebody else's. And I haven't solved that well. So I've learned that I need a new conversational technique where I can keep somebody from finding their comfortable place and yet not be the voice talking over that person. Yeah, it's funny. I get a sense, like in your conversation with Brett, I can sense you detect that the line he's going down, you know how it's gonna end. And you think it's a useless line, so you'll just stop it right there and you take him into the direction that you think it should go. But that requires interruption. Well, and it does so far. I haven't found a better way. I'm looking for a better way. It's not like I don't hear the problem. I do hear the problem. I just, I haven't solved the problem. And on the Brett episode, I was insufferable. It was very difficult to listen to. It was so overbearing. But on the other hand, I was right. It's funny, you keep saying that, but I didn't find it, maybe because I heard brothers. Like I heard a big brother. Yeah, it was pretty bad. Really? I think so. I didn't think it was bad at all. Well, a lot of people found it insufferable. And I think it also has to do with the fact that this has become a frequent experience. I have several shows where somebody who I very much admire and think of as courageous, I'm talking with them, maybe we're friends, and they sit down on the show, and they immediately become this fake person. Like two seconds in, they're sort of saying, well, I don't wanna be too critical or too harsh. I don't wanna name any names. I don't wanna this, don't wanna. He's like, okay, I'm gonna put my listeners through three hours of you being sweetness and light. Yeah. Like at least give me some reality, and then we can decide to shelve the show and never let it hear the call of freedom in the bigger world. I've seen you break out of that a few times. I've seen you be successful. I forgot the guest, but she was dressed with, where at the end of the episode, you had an argument about Brett. I forgot her name. Oh, Agnes Collard. Yeah, Agnes Collard. Agnes Collard, the philosopher at the University of Chicago. Yeah, you've continuously broken out of her. You guys went, you know, you seem pretty genuine. I like her. I'm completely ethically opposed to what she's ethically for. Well, she was great, and she wasn't like, you're both going hard. She's a grownup. Yeah, exactly. And she doesn't care about her. That was awesome. Yeah. But you're saying that some people are difficult to break out that way. It's just that, you know, she was bringing the courage of her conviction. She was sort of defending the system. And I thought, wow, that's a pretty indefensible system that you're defending. Well, that's great, though. She's doing that, isn't it? I mean. It made for an awesome. I think it's very informative for the world. Yes. You just hated. I just can't stand the idea that somebody says, well, we don't care who gets paid or who gets the credit as long as we get the goodies, because that seems like insane. Have you ever been afraid leading into a conversation? Gary Kasparov. Really? By the way, I mean, I know I'm just a fan taking requests, but. I started at the beginning in Russian. And in fact, I used one word incorrectly. Is that terrible? You know, it was pretty good. It was pretty good Russian. What was terrible is I think he complimented you, right? No, did he compliment you or was that me? Did he compliment you on your Russian? Well, he said almost perfect Russian. Yeah, like he was full of shit. That was not great Russian. That was not great Russian. That was great. That was hard. You tried hard, which is what matters. That is so insulting. I hope so. But I do hope you continue. It felt like, I don't know how long it went. It might've been like a two hour conversation, but it felt, I hope it continues. Like, I feel like you have many more conversations with Gary, yeah. I would love to hear. There's certain conversation I would just love to hear much, much longer. He's coming from a very, it's this issue about needing to overpower people in a very dangerous world. And so Gary has that need. Yeah, he was interrupting you. It was an interesting dynamic. It was an interesting dynamic. Two Weinsteins going at it. I mean, two powerhouse egos, brilliant. No, you don't say egos. Minds, spirits. You don't have an ego. You're the most humble person I know. Is that true? No, that's a complete lie. Do you think about your own mortality, death? Sure. Are you afraid of death? I released a theory during something that can kill older people, sure. Oh, is there a little bit of a parallel there? Of course, of course. I don't want it to die with me. What do you hope your legacy is? Oh, I hope my legacy is accurate. I'd like to write on my accomplishments rather than how my community decided to ding me while I was alive. That would be great. What about if it was significantly exaggerated? I don't want it. You want it to be accurate. I've got some pretty terrific stuff and whether it works out or doesn't, I would like it to reflect what I actually was. I'll settle for accurate. What would you say, what is the greatest element of Eric Weinstein accomplishment in life in terms of being accurate? What are you most proud of? Trying, trying. The idea that we were stalled out in the hardest field at the most difficult juncture and that I didn't listen to that voice ever that said, stop, you're hurting yourself, you're hurting your family, you're hurting everybody, you're embarrassing yourself, you're screwing up. You can't do this, you're a failure, you're a fraud. Turn back, save yourself. Like that voice, I didn't ultimately listen to it and it was going for 35, 37 years. Very hard. And I hope you never listen to that voice. Well. That's why you're an inspiration. Thank you, I appreciate that. You're the, I'm just infinitely honored that you would spend time with me. You've been a mentor to me, almost a friend. I can't imagine a better person to talk to in this world. So thank you so much for talking today. I can't wait till we do it again. Lex, thanks for sticking with me and thanks for being the most singular guy in the podcasting space. In terms of all of my interviews, I would say that the last one I did with you, many people feel was my best and it was a non-conventional one. So whatever it is that you're bringing to the game, I think everyone's noticing and keep at it. Thank you. Thanks for listening to this conversation with Eric Weinstein and thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words of wisdom from Eric Weinstein's first appearance on this podcast. Everything is great about war except all the destruction. Thank you for listening and hope to see you next time.

https://youtu.be/rIAZJNe7YtE

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Richard Dawkins: Evolution, Intelligence, Simulation, and Memes | Lex Fridman Podcast #87

The following is a conversation with Richard Dawkins, an evolutionary biologist and author of The Selfish Gene, The Blind Watchmaker, The God Delusion, The Magic of Reality, and The Greatest Show of Earth, and his latest, All-Growing God. He is the originator and popularizer of a lot of fascinating ideas in evolutionary biology and science in general, including, funny enough, the introduction of the word meme in his 1976 book, The Selfish Gene, which, in the context of a gene-centered view of evolution, is an exceptionally powerful idea. He's outspoken, bold, and often fearless in the defense of science and reason, and in this way, is one of the most influential thinkers of our time. This conversation was recorded before the outbreak of the pandemic. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with Five Stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to send and receive money digitally, peer-to-peer, security in all digital transactions is very important. Let me mention the PCI data security standard that Cash App is compliant with. I'm a big fan of standards for safety and security. PCI DSS is a good example of that, where a bunch of competitors got together and agreed that there needs to be a global standard around the security of transactions. Now we just need to do the same for autonomous vehicles and artificial intelligence systems in general. So again, if you get Cash App from the App Store, Google Play, and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Richard Dawkins. Do you think there's intelligent life out there in the universe? Well, if we accept that there's intelligent life here, and we accept that the number of planets in the universe is gigantic, I mean, 10 to the 22 stars has been estimated, it seems to me highly likely that there is not only life in the universe elsewhere, but also intelligent life. If you deny that, then you're committed to the view that the things that happened on this planet are staggeringly improbable. I mean, ludicrously, off the charts improbable. And I don't think it's that improbable. Certainly the origin of life itself, there are really two steps, the origin of life, which is probably fairly improbable, and then the subsequent evolution to intelligent life, which is also fairly improbable. So the juxtaposition of those two, you could say is pretty improbable, but not 10 to the 22 improbable. It's an interesting question, maybe you're coming onto it, how we would recognize intelligence from outer space if we encountered it. The most likely way we would come across them would be by radio. It's highly unlikely they'd ever visit us, but it's not that unlikely that we would pick up radio signals, and then we would have to have some means of deciding that it was intelligent. People involved in the SETI program discuss how they would do it, and things like prime numbers would be an obvious thing too. An obvious way for them to broadcast, to say we are intelligent, we are here. I suspect it probably would be obvious, actually. Well, it's interesting, prime numbers, so the mathematical patterns, it's an open question whether mathematics is the same for us as it would be for aliens. I suppose we could assume that ultimately, if we're governed by the same laws of physics, then we should be governed by the same laws of mathematics. I think so. I suspect that they will have Pythagoras' theorem, et cetera. I don't think that their mathematics will be that different. Do you think evolution would also be a force on the alien planets as well? I stuck my neck out and said that if ever that we do discover life elsewhere, it will be Darwinian life, in the sense that it will work by some kind of natural selection, the non-random survival of randomly generated codes. It doesn't mean that the, it would have to have some kind of genetics, but it doesn't have to be DNA genetics. Probably wouldn't be, actually. But I think it would have to be Darwinian, yes. So some kind of selection process. Yes, in the general sense, it would be Darwinian. So let me ask kind of an artificial intelligence engineering question. So you've been an outspoken critic of, I guess what could be called intelligent design, which is an attempt to describe the creation of a human mind and body by some religious folks, religious folks used to describe. So broadly speaking, evolution is, as far as I know, again, you can correct me, is the only scientific theory we have for the development of intelligent life. Like there's no alternative theory as far as I understand. None has ever been suggested, and I suspect it never will be. Well, of course, whenever somebody says that, 100 years later. I know. I know, it's a risk. It's a risk. But you want to bet? I mean, I'm pretty confident. But it would look, sorry, yes. It would probably look very similar, but it's almost like Einstein's general relativity versus Newtonian physics. It'll be maybe an alteration of the theory or something like that, but it won't be fundamentally different. But okay. So now for the past 70 years, even before the AI community has been trying to engineer intelligence, in a sense, to do what intelligent design says, was done here on Earth, what's your intuition? Do you think it's possible to build intelligence, to build computers that are intelligent, or do we need to do something like the evolutionary process? Like there's no shortcuts here. That's an interesting question. I'm committed to the belief that is ultimately possible because I think there's nothing non-physical in our brains. I think our brains work by the laws of physics. And so it must, in principle, be possible to replicate that. In practice, though, it might be very difficult. And as you suggest, it may be the only way to do it is by something like an evolutionary process. I'd be surprised. I suspect that it will come. But it's certainly been slower in coming than some of the early pioneers thought. Thought it would be, yeah. But in your sense, is the evolutionary process efficient? So you can see it as exceptionally wasteful in one perspective, but at the same time, maybe that is the only path to- It's a paradox, isn't it? I mean, on the one side, it is deplorably wasteful. It's fundamentally based on waste. On the other hand, it does produce magnificent results. The design of a soaring bird, an albatross, a vulture, an eagle, is superb. An engineer would be proud to have done it. On the other hand, an engineer would not be proud to have done some of the other things that evolution has served up. Some of the sort of botched jobs that you can easily understand because of their historical origins, but they don't look well-designed. Do you have examples of bad design? My favorite example is the recurrent laryngeal nerve. I've used this many times. This is a nerve, it's one of the cranial nerves. It goes from the brain, and the end organ that it supplies is the voice box, the larynx. But it doesn't go straight to the larynx. It goes right down into the chest and then loops around an artery in the chest and then comes straight back up again to the larynx. And I've assisted in the dissection of a giraffe's neck, which happened to have died in a zoo. And we watched the, we saw the recurrent laryngeal nerve going, whizzing straight past the larynx within an inch of the larynx, down into the chest and then back up again, which is a detour of many feet. Very, very inefficient. The reason is historical. The ancestors, our fish ancestors, the ancestors of all mammals and fish, the most direct pathway of that, of the equivalent of that nerve, there wasn't a larynx in those days, but it innervated part of the gills. The most direct pathway was behind that artery. And then when the mammal, when the tetrapods, when the land vertebrae started evolving and then the neck started to stretch, the marginal cost of changing the embryological design to jump that nerve over the artery was too great, or rather was, each step of the way was a very small cost, but the marginal, but the cost of actually jumping it over would have been very large. As the neck lengthened, it was a negligible change to just increase the length of the detour a tiny bit, a tiny bit, a tiny bit, each millimetre at a time didn't make any difference. And so, but finally, when you get to a giraffe, it's a huge detour and no doubt is very inefficient. Now that's bad design. Any engineer would reject that piece of design. It's ridiculous. And there are quite a number of examples, as you'd expect. It's not surprising that we find examples of that sort. In a way, what's surprising is there aren't more of them. In a way, what's surprising is that the design of living things is so good. So natural selection manages to achieve excellent results, partly by tinkering, partly by coming along and cleaning up initial mistakes, and as it were, making the best of a bad job. That's really interesting. I mean, it is surprising and beautiful, and it's a mystery from an engineering perspective that so many things are well-designed. I suppose the thing we're forgetting is how many generations have to die for that. That's the inefficiency of it. Yes, that's the horrible wastefulness of it. So yeah, we marvel at the final product, but yeah, the process is painful. Elon Musk describes human beings as potentially the, what he calls the biological bootloader for artificial intelligence, or artificial general intelligence is used as the term. It's kind of like super intelligence. Do you see superhuman level intelligence as potentially the next step in the evolutionary process? Yes, I think that if superhuman intelligence is to be found, it will be artificial. I don't have any hope that we ourselves, our brains will go on getting larger in ordinary biological evolution. I think that's probably coming to an end. It is the dominant trend, or one of the dominant trends in our fossil history for the last two or three million years. Brain size? Brain size, yes. So it's been swelling rather dramatically over the last two or three million years. That is unlikely to continue. The only way that happens is because natural selection favors those individuals with the biggest brains, and that's not happening anymore. Right, so in general, in humans, the selection pressures are not, I mean, are they active in any form? Well, in order for them to be active, it would be necessary that the most, let's call it intelligence, not that intelligence is simply correlated with brain size, but let's talk about intelligence. In order for that to evolve, it's necessary that the most intelligent beings have the most, individuals have the most children. And so intelligence may buy you money, it may buy you worldly success, it may buy you a nice house and a nice car and things like that if you're a successful career, it may buy you the admiration of your fellow people, but it doesn't increase the number of offspring that you have, it doesn't increase your genetic legacy to the next generation. On the other hand, artificial intelligence, I mean, computers and technology generally, is evolving by a non-genetic means, by leaps and bounds, of course. And so what do you think, I don't know if you're familiar, there's a company called Neuralink, but there's a general effort of brain-computer interfaces, which is to try to build a connection between the computer and the brain, to send signals both directions. And the long-term dream there is to do exactly that, which is expand, I guess expand the size of the brain, expand the capabilities of the brain. Do you see this as interesting? And do you see this as a promising possible technology, or is the interface between the computer and the brain, like the brain is this wet, messy thing that's just impossible to interface with? Well, of course it's interesting, whether it's promising, I'm really not qualified to say. What I do find puzzling is that the brain being as small as it is compared to a computer, and the individual components being as slow as they are compared to our electronic components, it is astonishing what it can do. I mean, imagine building a computer that fits into the size of a human skull, and with the equivalent of transistors or integrated circuits, which work as slowly as neurons do. It's something mysterious about that, something must be going on that we don't understand. So I've just talked to Roger Penrose, I'm not sure if you're familiar with his work. He also describes this kind of mystery in the mind, in the brain, that he sees a materialist, so there's no sort of mystical thing going on, but there's so much about the material of the brain that we don't understand, that might be quantum mechanical in nature and so on. So there are the ideas about consciousness. Do you have any, have you ever thought about, do you ever think about ideas of consciousness or a little bit more about the mystery of intelligence and consciousness that seems to pop up, just like you're saying, from our brain? I agree with Roger Penrose that there is a mystery there. I mean, he's one of the world's greatest physicists, so I can't possibly argue with his- But nobody knows anything about consciousness, and in fact, if we talk about religion and so on, the mystery of consciousness is so awe-inspiring, and we know so little about it, that the leap to sort of religious or mystical explanations is too easy to make. I think that it's just an act of cowardice to leap to religious explanations, and Roger doesn't do that, of course. But I accept that there may be something that we don't understand about it. So correct me if I'm wrong, but in your book, Selfish Gene, the gene-centered view of evolution, allows us to think of the physical organisms as just the medium through which the software of our genetics and the ideas sort of propagate. So maybe can we start just with the basics? What in this context does the word meme mean? It would mean the cultural equivalent of a gene, cultural equivalent in the sense of that which plays the same role as the gene in the transmission of culture, in the transmission of ideas in the broadest sense. And it's only a useful word if there's something Darwinian going on. Obviously, culture is transmitted, but is there anything Darwinian going on? And if there is, that means there has to be something like a gene, which becomes more numerous or less numerous in the population. So it can replicate? It can replicate, well, it clearly does replicate, there's no question about that. The question is, does it replicate in a sort of differential way, in a Darwinian fashion? Could you say that certain ideas propagate because they're successful in the meme pool? In a sort of trivial sense, you can. Would you wish to say though, that in the same way as an animal body is modified, adapted to serve as a machine for propagating genes, is it also a machine for propagating memes? Could you actually say that something about the way a human is, is modified, adapted for the function of meme propagation? That's such a fascinating possibility, if that's true. If it's not just about the genes, which seem somehow more comprehensible, it's like these things of biology. The idea that culture, or maybe ideas, you can really broadly define it, operates under these mechanisms. Even morphology, even anatomy, does evolve by memetic means. I mean, things like hairstyles, styles of makeup, circumcision, these things are actual changes in the body form, which are non-genetic, and which get passed on from generation to generation, or sideways, like a virus, in a quasi-genetic way. But the moment you start drifting away from the physical, it becomes interesting, because the space of ideas, ideologies, political systems. Of course, yes. So what's your sense? Are memes a metaphor more, or are they really, is there something fundamental, almost physical presence of memes? Well, I think they're a bit more than a metaphor, and I think that, and I mentioned that physical, bodily characteristics, which are a bit trivial in a way, but when things like the propagation of religious ideas, both longitudinally down generations, and transversely, as in a sort of epidemiology of ideas, when a charismatic preacher converts people, that resembles viral transmission, whereas the longitudinal transmission from grandparent to parent, to child, et cetera, is more like conventional genetic transmission. That's such a beautiful, especially in the modern day, idea. Do you think about this implication in social networks, where the propagation of ideas, the viral propagation of ideas, and hence the new use of the word meme to describe? The internet, of course, provides extremely rapid method of transmission. Before, when I first coined the word, the internet didn't exist, and so I was thinking then in terms of books, newspapers, broad radio, television, that kind of thing. Now, an idea can just leap around the world in all directions instantly. And so the internet provides a step change in the facility of propagation of memes. How does that make you feel? Isn't it fascinating that sort of ideas, it's like you have Galapagos Islands or something, it's the 70s, and the internet allowed all these species to just like globalize, and in a matter of seconds, you could spread a message to millions of people, and these ideas, these memes can breed, can evolve, can mutate, there's a selection, and there's like different, I guess, groups that evolve. Like there's a dynamics that's fascinating here. Do you think- Yes. Basically, do you think your work in this direction, while fundamentally it was focused on life on earth, do you think it should continue, like to be taken further? I mean, I do think it would probably be a good idea to think in a Darwinian way about this sort of thing. We conventionally think of the transmission of ideas in evolutionary context as being limited to, in our ancestors, people living in villages, living in small bands where everybody knew each other and ideas could propagate within the village, and they might hop to a neighboring village occasionally, and maybe even to a neighboring continent eventually. And that was a slow process. Nowadays, villages are international. I mean, you have people, it's been called echo chambers, where people are in a sort of internet village, where the other members of the village may be geographically distributed all over the world, but they just happen to be interested in the same things, use the same terminology, the same jargon, have the same enthusiasm. So people like the Flat Earth Society, they don't all live in one place, they find each other, and they talk the same language to each other, they talk the same nonsense to each other. But so this is a kind of distributed version of the primitive idea of people living in villages and propagating their ideas in a local way. Is there Darwinist parallel here? So is there evolutionary purpose of villages, or is that just a- Oh, I wouldn't use the word like evolutionary purpose in that case, but villages will be something that just emerged, that's the way people happen to live. And in just the same kind of way, the Flat Earth Society, societies of ideas emerge in the same kind of way in this digital space. Yes, yes. Is there something interesting to say about the, I guess, from a perspective of Darwin, could we fully interpret the dynamics of social interaction in these social networks? Or is there some much more complicated thing need to be developed? Like, what's your sense? Well, a Darwinian selection idea would involve investigating which ideas spread and which don't. So some ideas don't have the ability to spread. I mean, flat Earthism, there are a few people believing it, but it's not gonna spread because it's obvious nonsense. But other ideas, even if they are wrong, can spread because they are attractive in some sense. So the spreading and the selection in the Darwinian context, it just has to be attractive in some sense. Like, we don't have to define, like it doesn't have to be attractive in the way that animals attract each other. It could be attractive in some other way. Yes, all that matters is, all that's needed is that it should spread. And it doesn't have to be true to spread. In truth, there's one criterion which might help an idea to spread. But there are other criteria which might help it to spread. As you say, attraction in animals is not necessarily valuable for survival. The famous peacock's tail doesn't help the peacock to survive. It helps it to pass on its genes. Similarly, an idea which is actually rubbish, but which people don't know is rubbish and think is very attractive, will spread in the same way as a peacock's genes spread. It's a small sidestep. I remember reading somewhere, I think recently, that in some species of birds, sort of the idea that beauty may have its own purpose and the idea that some birds, I'm being ineloquent here, but there's some aspects of their feathers and so on that serve no evolutionary purpose whatsoever. There's somebody making an argument that there are some things about beauty that animals do that may be its own purpose. Does that ring a bell for you? Does it sound ridiculous? I think it's a rather distorted bell. Darwin, when he coined the phrase sexual selection, didn't feel the need to suggest that what was attractive to females, usually is males attracting females, that what females found attractive had to be useful. He said it didn't have to be useful. It was enough that females found it attractive. And so it could be completely useless, probably was completely useless in the conventional sense, but was not at all useless in the sense of passing on, well, Darwin didn't call them genes, but in the sense of reproducing. Others, starting with Wallace, the co-discoverer of natural selection, didn't like that idea. And they wanted sexually selected characteristics like peacock's tails to be in some sense useful. It's a bit of a stretch to think of a peacock's tail as being useful, but in the sense of survival, but others have run with that idea and have brought it up to date. And so there's a kind of, there are two schools of thought on sexual selection, which are still active and about equally supported now. Those who follow Darwin in thinking that it's just enough to say it's attractive, and those who follow Wallace and say that it has to be in some sense useful. Do you fall into one category or the other? No, I'm open-minded. I think they both could be correct in different cases. Oh. I mean, they've both been made sophisticated in a mathematical sense, more so than when Darwin and Wallace first came out. When Darwin and Wallace first started talking about it. I'm Russian, I romanticize things, so I prefer the former. Yes. Where the beauty in itself is a powerful, so attraction is a powerful force in evolution. On religion, do you think there will ever be a time in our future where almost nobody believes in God or God is not a part of the moral fabric of our society? Yes, I do. I think it may happen after a very long time. I think it may take a long time for that to happen. So do you think ultimately for everybody on earth, religion, other forms of doctrines, ideas, could do a better job than what religion does? Yes. I mean, following truth. Well, truth is a funny, funny word. And reason too. There's, yeah, it's a difficult idea now with truth and the internet, right? And fake news and so on. I suppose when you say reason, you mean the very basic sort of inarguable conclusions of science versus which political system is better? Yes, yes. I mean truth about the real world, which is ascertainable by, not just by the more rigorous methods of science, but by just ordinary sensory observation. So do you think there will ever be a time when we move past it? Like, I guess another way to ask it, are we hopelessly, fundamentally tied to religion in the way our society functions? Well, clearly all individuals are not hopelessly tied to it because many individuals don't believe. You could mean something like society needs religion in order to function properly, something like that. And some people have suggested that. What's your intuition on that? Well, I've read books on it and they're persuasive. I don't think they're that persuasive though. I mean, some people suggested that society needs a sort of figurehead, which can be a non-existent figurehead in order to function properly. I think there's something rather patronizing about the idea that, well, you and I are intelligent enough not to believe in God, but the plebs need it sort of thing. And I think that's patronizing. And I'd like to think that that was not the right way to proceed. But at the individual level, do you think there's some value of spirituality? Sort of, if I think sort of as a scientist, the amount of things we actually know about our universe is a tiny, tiny, tiny percentage of what we could possibly know. So just from everything, even the certainty we have about the laws of physics, it seems to be that there's yet a huge amount to discover. And therefore we're sitting where 99.999% of things are just still shrouded in mystery. Do you think there's a role in a kind of spiritual view of that, sort of a humbled spiritual? I think it's right to be humble. I think it's right to admit that there's a lot we don't know, a lot that we don't understand, a lot that we still need to work on. And we're working on it. What I don't think is that it helps to invoke supernatural explanations. If our current scientific explanations aren't adequate to do the job, then we need better ones. We need to work more. And of course, the history of science shows just that, that as science goes on, problems get solved one after another and the science advances as science gets better. But to invoke a non-scientific, non-physical explanation is simply to lie down in a cowardly way and say, we can't solve it, so we're going to invoke magic. Don't let's do that. Let's say we need better science. We need more science. It may be that the science will never do it. It may be that we will never actually understand everything. And that's okay, but let's keep working on it. A challenging question there is, do you think science can lead us astray in terms of the humbleness? So there's some aspect of science, maybe it's the aspect of scientists and not science, but of sort of a mix of ego and confidence that can lead us astray in terms of discovering some of the big open questions about the universe. I think that's right. I mean, there are arrogant people in any walk of life and scientists are no exception to that. And so there are arrogant scientists who think we've solved everything. And of course we haven't. So humility is a proper stance for a scientist. I mean, it's a proper working stance because it encourages further work. But in a way to resort to a supernatural explanation is a kind of arrogance because it's saying, well, we don't understand it scientifically, therefore the non-scientific religious supernatural explanation must be the right one. That's arrogant. What is humble is to say we don't know and we need to work further on it. So maybe if I could psychoanalyze you for a second, you have at times been just slightly frustrated with people who have a supernatural, has that changed over the years? Have you become like, how do people that kind of have like seek supernatural explanations, how do you see those people as human beings? As it's like, do you see them as dishonest? Do you see them as sort of ignorant? Do you see them as, I don't know, like how do you think of- Certainly not dishonest. And I mean, obviously many of them are perfectly nice people so I don't sort of despise them in that sense. I think it's often a misunderstanding that people will jump from the admission that we don't understand something. They will jump straight to what they think of as an alternative explanation, which is the supernatural one, which is not an alternative. It's a non-explanation. Instead of jumping to the conclusion that science needs more work, that we need to actually do some better science. So I don't have, I mean, personal antipathy towards such people. I just think they're misguided. So what about this really interesting space that I have trouble with? So religion I have a better grasp on, but there's large communities, like you said, Flat Earth community that I've recently, because I've made a few jokes about it, I saw that there's, I've noticed that there's people that take it quite seriously. So there's this bigger world of conspiracy theorists, which is a kind of, I mean, there's elements of it that are religious as well, but I think they're also scientific. So the basic credo of a conspiracy theorist is to question everything, which is also the credo of a good scientist, I would say. So what do you make of this? Yes, I mean, I think it's probably too easy to say that by labeling something conspiracy, you therefore dismiss it. I mean, occasionally conspiracies are right. And so we shouldn't dismiss conspiracy theories out of hand. We should examine them on their own merits. Flat Earthism is obvious nonsense. We don't have to examine that much further. But I mean, there may be other conspiracy theories which are actually right. So I've grew up in the Soviet Union, so I understand, you know, the space race was very influential for me on both sides of the coin. You know, there's a conspiracy theory that we never went to the moon, right? And it's like, I can understand it. And it's very difficult to rigorously scientifically show one way or the other. It's just, you have to use some of the human intuition about who would have to lie, who would have to work together. And it's clear that very unlikely good... Behind that is my general intuition that most people in this world are good. You know, in order to really put together some conspiracy theories, there has to be a large number of people working together and essentially being dishonest. Yes, which is improbable. The sheer number who would have to be in on this conspiracy and the sheer detail, the attention to detail they'd have had to have had and so on. I'd also worry about the motive. And why would anyone want to suggest that it didn't happen? What's the... Why is it so hard to believe? I mean, the physics of it, the mathematics of it, the idea of computing orbits and trajectories and things, it all works mathematically. Why wouldn't you believe it? It's a psychology question because there's something really pleasant about, you know, pointing out that the emperor has no clothes when everybody, like, you know, thinking outside the box and coming up with a true answer where everybody else is deluded. There's something... I mean, I have that for science, right? You want to prove the entire scientific community wrong. That's the whole... No, that's right. And of course, historically, lone geniuses have come out right sometimes. But often people who think they're a lone genius have much more often turned out not to. So you have to judge each case on its merits. The mere fact that you're a maverick, the mere fact that you're going against the current tide doesn't make you right. You've got to show you're right by looking at the evidence. So because you focus so much on religion and disassembled a lot of ideas there and I just, I was wondering if you have ideas about conspiracy theory groups, because it's such a prevalent, even reaching into presidential politics and so on. It seems like it's a very large communities that believe different kinds of conspiracy theories. Is there some connection there to your thinking on religion? And, or is it- It is curious. It's a matter, it's an obviously difficult thing. I don't understand why people believe things that are clearly nonsense like, well, flat earth and also the conspiracy about not landing on the moon or that the United States engineered 9-11, that kind of thing. So it's not clearly nonsense, it's extremely unlikely. Okay, it's extremely unlikely. Religion is a bit different because it's passed down from generation to generation. So many of the people who are religious got it from their parents, who got it from their parents, who got it from their parents and childhood indoctrination is a very powerful force. But these things like the 9-11 conspiracy theory, the Kennedy assassination conspiracy theory, the man on the moon conspiracy theory, these are not childhood indoctrination. These are presumably dreamed up by somebody who then tells somebody else who then wants to believe it. And I don't know why people are so eager to fall in line with just some person that they happen to read or meet who spins some yarn. I can kind of understand why they believe what their parents and teachers told them when they were very tiny and not capable of critical thinking for themselves. So I sort of get why the great religions of the world like Catholicism and Islam go on persisting. It's because of childhood indoctrination. But that's not true of flat-earthers. And sure enough, flat-earthers is a very minority cult. Way larger than I ever realized. Well, yes, I know. But so that's a really clean idea. And you've articulated that in your new book and in The Outgrown God and in God Delusion is the early indoctrination. That's really interesting. You can get away with a lot of out there ideas in terms of religious texts if the age at which you convey those ideas at first is a young age. So indoctrination is sort of an essential element of propagation of religion. So let me ask on the morality side in the books that I mentioned, God Delusion, Outgrown God, you described that human beings don't need religion to be moral. So from an engineering perspective, we wanna engineer morality into AI systems. So in general, where do you think morals come from in humans? A very complicated and interesting question. It's clear to me that the moral standards, the moral values of our civilization changes as the decades go by, certainly as the centuries go by, even as the decades go by. And we in the 21st century are quite clearly labeled 21st century people in terms of our moral values. There's a spread. I mean, some of us are a little bit more ruthless, some of us more conservative, some of us more liberal and so on. But we all subscribe to pretty much the same views when you compare us with say 18th century, 17th century people, even 19th century, 20th century people. So we're much less racist, we're much less sexist and so on than we used to be. Some people are still racist and some are still sexist, but the spread has shifted. The Gaussian distribution has moved and moves steadily as the centuries go by. And that is the most powerful influence I can see on our moral values. And that doesn't have anything to do with religion. I mean, the religion of the, sorry, the morals of the Old Testament are Bronze Age models, morals. They're deplorable and they are to be understood in terms of the people in the desert who made them up at the time. And so human sacrifice, an eye for an eye, a tooth for a tooth, a tooth, petty, revenge, killing people for breaking the Sabbath, all that kind of thing, inconceivable now. So at some point, religious texts may have in part reflected that Gaussian distribution at that time. I'm sure they did, I'm sure they always reflect that, yes. And then now, but the sort of almost like the meme as you describe it of ideas moves much faster than religious texts do, than you religion. Yeah, so basing your morals on religious texts which were written millennia ago is not a great way to proceed. I think that's pretty clear. So not only should we not get our morals from such texts, but we don't, we quite clearly don't. If we did, then we'd be discriminating against women and we'd be racist, we'd be killing homosexuals and so on. So we don't and we shouldn't. Now, of course, it's possible to use your 21st century standards of morality and you can look at the Bible and you can cherry pick particular verses which conform to our modern morality. And you'll find that Jesus says some pretty nice things, which is great. But you're using your 21st century morality to decide which verses to pick, which verses to reject. And so why not cut out the middleman of the Bible and go straight to the 21st century morality, which is where that comes from. It's a much more complicated question. Why is it that morality, moral values change as the centuries go by? They undoubtedly do. And it's a very interesting question to ask why. It's another example of cultural evolution just as technology progresses. So moral values progress for probably very different reasons. But it's interesting if the direction in which that progress is happening has some evolutionary value or if it's merely a drift that can go into any direction. I'm not sure it's any direction and I'm not sure it's evolutionarily valuable. What it is is progressive in the sense that each step is a step in the same direction as the previous step. So it becomes more gentle, more decent, as by modern standards, more liberal. Less violent. See, but more decent, I think you're using terms and interpreting everything in the context of the 21st century. Because Genghis Khan would probably say that this is not more decent because we're now, you know, there's a lot of weak members of society that we're not murdering. Yes, and I was careful to say by the standards of the 21st century, by our standards, if we with hindsight look back at history, what we see is a trend in the direction towards us. What we see is a trend in the direction towards us, towards our present, our present value system. So for us, we see progress, but it's an open question whether that won't, you know, I don't see necessarily why we can never return to Genghis Khan times. Well, we could. I suspect we won't. But if you look at the history of moral values over the centuries, it is in a progressive, I use the word progressive, not in a value judgment sense, in the sense of a transitive sense. Each step is the same direction of the previous step. So things like we don't derive entertainment from torturing cats. We don't derive entertainment from, like the Romans did in the Colosseum from that stage. Or rather we suppress the desire to get, I mean, to have pleasure. It's probably in us somewhere. So there's a bunch of parts of our brain, one that probably, you know, limbic system that wants certain pleasures. And that's- I don't, I mean, I wouldn't have said that, but you're at liberty to think that. Well, there's a Dan Carlin of Hardcore History that has a really nice explanation of how we've enjoyed watching the torture of people, the fighting of people, just the torture, the suffering of people throughout history as entertainment until quite recently. And now everything we do with sports, we're kind of channeling that feeling into something else. I mean, there is some dark aspects of human nature that are underneath everything. And I do hope this like higher level software we've built will keep us at bay. Yes. I'm also Jewish and have history with the Soviet Union and the Holocaust. And I clearly remember that some of the darker aspects of human nature creeped up there. They do. There have been steps backwards admittedly, and the Holocaust is an obvious one. But if you take a broad view of history, it's in the same direction. So Pamela McCordick in Machines Who Think has written that AI began with an ancient wish to forge the gods. Do you see, it's a poetic description, I suppose, but do you see a connection between our civilization's historic desire to create gods, to create religions, and our modern desire to create technology, an intelligent technology? I suppose there's a link between an ancient desire to explain away mystery and science, but artificial intelligence creating gods, creating new gods. I mean, I forget, I read somewhere a somewhat facetious paper which said that we have a new god, it's called Google, and we pray to it and we worship it and we ask its advice like an oracle and so on. That's fun. You don't see that, you see that as a fun statement, a facetious statement. You don't see that as a kind of truth of us creating things that are more powerful than ourselves and natural sort of formation. It has a kind of poetic resonance to it, which I get. But I wouldn't- But not a scientific one. I wouldn't have bothered to make the point myself, put it that way. All right. So you don't think AI will become our new religion, a new god, like Google? Well, yes, I mean, I can see that the future of intelligent machines or indeed intelligent aliens from outer space might yield beings that we would regard as gods in the sense that they are so superior to us that we might as well worship them. That's highly plausible, I think. But I see a very fundamental distinction between a god who is simply defined as something very, very powerful and intelligent on the one hand, and a god who doesn't need explaining by a progressive step-by-step process like evolution or like engineering design. So suppose we did meet an alien from outer space who was marvelously, magnificently more intelligent than us, and we would sort of worship it for that reason. Nevertheless, it would not be a god in the very important sense that it did not just happen by to be there like God is supposed to. It must have come about by a gradual, step-by-step, incremental, progressive process, presumably like Darwinian evolution. So there's all the difference in the world between those two. Intelligence, design comes into the universe late as a product of a progressive evolutionary process or a progressive engineering design process. So most of the work is done through this slow-moving- Exactly. Progress. Exactly. Yeah. Yeah, but there's still this desire to get answers to the why question that if the world is a simulation, if we're living in a simulation, that there's a programmer-like creature that we can ask questions of. Okay, well, let's pursue the idea that we're living in a simulation, which is not totally ridiculous, by the way. There we go. Yeah. Then you still need to explain the programmer. The programmer had to come into existence by some, even if we're in a simulation, the programmer must have evolved. Or if he's in a sort of- Or she. Or she. If she's in a meta simulation, then the meta, meta programmer must have evolved by a gradual process. You can't escape that. Fundamentally, you've got to come back to a gradual, incremental process of explanation to start with. There's no shortcuts in this world. No, exactly. But maybe to linger on that point about the simulation, do you think it's an interesting, basically talk to, bore the heck out of everybody asking this question, but whether you live in a simulation, do you think, first, do you think we live in a simulation? Second, do you think it's an interesting thought experiment? It's certainly an interesting thought experiment. I first met it in a science fiction novel by Daniel Galloy called Counterfeit World, in which it's all about, I mean, our heroes are running a gigantic computer which simulates the world and something goes wrong. And so one of them has to go down into the simulated world in order to fix it. And then the denouement of the thing, the climax to the novel is that they discover that they themselves are in another simulation at a higher level. So I was intrigued by this and I love others of Daniel Galloy's science fiction novels. Then it was revived seriously by Nick Bostrom. Bostrom, talking to him in an hour. Okay. And he goes further, not just treat it as a science fiction speculation, but he actually thinks it's positively likely. Yes. I mean, he thinks it's very likely actually. Well, he makes like a probabilistic argument which you can use to come up with very interesting conclusions about the nature of this universe. I mean, he thinks that we're in a simulation done by, so to speak, our descendants of the future, that the products, but it's still a product of evolution. It's still ultimately going to be a product of evolution, even though the super intelligent people of the future have created our world and you and I are just a simulation and this table is a simulation and so on. I don't actually, in my heart of hearts, believe it, but I like his argument. Well, so the interesting thing is that, I agree with you, but the interesting thing to me, if I were to say, if we're living in a simulation, that in that simulation to make it work, you still have to do everything gradually, just like you said, that even though it's programmed, I don't think there could be miracles. Otherwise it's- Well, no, I mean, the programmer, the upper ones have to have evolved gradually. However, the simulation they create could be instantaneous. I mean, they could be switched on and we come into the world with fabricated memories. True, but what I'm trying to convey, so you're saying the broader statement, but I'm saying from an engineering perspective, both the programmer has to be slowly evolved and the simulation, because it's like, from an engineering perspective- Oh yeah, it takes a long time to write a program. No, like just, I don't think you can create the universe in a snap, I think you have to grow it. Okay, well, that's a good point, that's an arguable point. By the way, I have thought about using the Nick Bostrom idea to solve the riddle of how you were talking, we were talking earlier about why the human brain can achieve so much. I thought of this when my then hundred year old mother was marveling at what I could do with a smartphone and I could call or look up anything in the encyclopedia or I could play her music that she liked and so on. She said, but it's all in that tiny little phone. No, it's out there, it's in the cloud. And maybe what most of what we do is in a cloud. So maybe if we are a simulation, then all the power that we think is in our skull, it actually may be like the power that we think is in the iPhone, but is that actually out there- It's an interface to something else. I mean, that's what, including Roger Penrose with panpsychism, that consciousness is somehow a fundamental part of physics, that it doesn't have to actually all reside inside- No, but Roger thinks it does reside in the skull, whereas I'm suggesting that it doesn't, that there's a cloud. That'd be a fascinating notion. On a small tangent, are you familiar with the work of Donald Hoffman, I guess? Maybe not saying his name correctly, but just forget the name, the idea that there's a difference between reality and perception. So like we, biological organisms, perceive the world in order for the natural selection process to be able to survive and so on, but that doesn't mean that our perception actually reflects the fundamental reality, the physical reality underneath. Well, I do think that although it reflects the fundamental reality, I do believe there is a fundamental reality, I do think that our perception is constructive in the sense that we construct in our minds a model of what we're seeing. And so, and this is really the view of people who work on visual illusions, like Richard Gregory, who point out that things like a Necker cube, which flip from, it's a two-dimensional picture of a cube on a sheet of paper, but we see it as a three-dimensional cube, and it flips from one orientation to another at regular intervals. What's going on is that the brain is constructing a cube, but the sense data are compatible with two alternative cubes. And so rather than stick with one of them, it alternates between them. I think that's just a model for what we do all the time when we see a table, when we see a person, when we see anything, we're using the sense data to construct or make use of a perhaps previously constructed model. I noticed this when I meet somebody who actually is, say, a friend of mine, but until I kind of realized that it is him, he looks different. And then when I finally clock that it's him, his features switch like a Necker cube into the familiar form. As it were, I've taken his face out of the filing cabinet inside and grafted it onto, or used the sense data to invoke it. Yeah, we do some kind of miraculous compression on this whole thing to be able to filter out most of the sense data and make sense of it. That's just the magical thing that we do. So you've written several many amazing books, but let me ask what books, technical or fiction or philosophical, had a big impact on your own life? What books would you recommend people consider reading in their own intellectual journey? Darwin, of course. The original, I'm actually ashamed to say I've never read Darwin. He's astonishingly prescient because considering he was writing in the middle of the 19th century, Michael Gieselin said he's working a hundred years ahead of his time. Everything except genetics is amazingly right and amazingly far ahead of his time. And of course you need to read the updatings that have happened since his time as well. I mean, he would be astonished by, well, let alone Watson and Crick, of course, but he'd be astonished by Mendelian genetics as well. Yeah, it'd be fascinating to see what he thought about, he would think about DNA. I mean, yes, it would, because in many ways it clears up what appeared in his time to be a riddle. The digital nature of genetics clears up what was a problem, what was a big problem. Gosh, there's so much that I could think of. I can't really. Is there something outside sort of more fiction? Is there, when you think young, was there books that just kind of, outside of kind of the realm of science and religion, that just kind of sparked your journey? Yes, well, actually, I have, I suppose I could say that I've learned some science from science fiction. I mentioned Daniel Galloway, and that's one example, but another of his novels called Dark Universe, which is not terribly well-known, but it's a very, very nice science fiction story. It's about a world of perpetual darkness. And we're not told at the beginning of the book why these people are in darkness. They stumble around in some kind of underground world of caverns and passages, using echolocation like bats and whales to get around. And they've adapted, presumably by Darwinian means, to survive in perpetual, total darkness. But what's interesting is that their mythology, their religion, has echoes of Christianity, but it's based on light. And so there's been a fall from a paradise world that once existed where light reigned supreme. And because of the sin of mankind, light banished them. So then they no longer are in light's presence, but light survives in the form of mythology and in the form of sayings like, so great light almighty, oh, for light's sake, don't do that. And I hear what you mean rather than I see what you mean. So some of the same religious elements are present in this other totally kind of absurd different form. Yes, and so it's a wonderful, I wouldn't call it satire because it's too good-natured for that. I mean, a wonderful parable about Christianity and the doctrine, the theological doctrine of the fall. So I find that kind of science fiction immensely stimulating. Fred Hoyle's, The Black Cloud. Oh, by the way, anything by Arthur C. Clarke I find very, very wonderful too. Fred Hoyle's, The Black Cloud, his first science fiction novel where he, well, I learned a lot of science from that. It suffers from an obnoxious hero, unfortunately, but apart from that, you learn a lot of science from it. Another of his novels, A for Andromeda, which by the way, the theme of that is taken up by Carl Sagan's science fiction novel, another wonderful writer, Carl Sagan, Contact, where the idea is, again, we will not be visited from outer space by physical bodies. We will be visited, possibly, we might be visited by radio, but the radio signals could manipulate us and actually have a concrete influence on the world if they make us or persuade us to build a computer which runs their software so that they can then transmit their software by radio. And then the computer takes over the world. And this is the same theme in both Hoyle's book and Sagan's book, I presume, I don't know whether Sagan knew about Hoyle's book, probably did. And, but it's a clever idea that we will never be invaded by physical bodies. The war of the worlds of HG Wells will never happen, but we could be invaded by radio signals, code, coded information, which is sort of like DNA. And we are, I call them, we are survival machines of our DNA. So it has great resonance for me, because I think of us, I think of bodies, physical bodies, biological bodies, as being manipulated by coded information, DNA, which has come down through generations. And in the space of memes, it doesn't have to be physical, it can be transmitted through the space of information. Yes. That's a fascinating possibility that from outer space, we can be infiltrated by other memes, by other ideas, and thereby controlled in that way. Let me ask the last, the silliest, or maybe the most important question. What is the meaning of life? What gives your life fulfillment, purpose, happiness, meaning? From a scientific point of view, the meaning of life is the propagation of DNA, but that's not what I feel. That's not the meaning of my life. So the meaning of my life is something which is probably different from yours and different from other people's, but we each make our own meaning. So we set up goals, we want to achieve, we want to write a book, we want to do whatever it is we do, write a quartet, we want to win a football match. And these are short-term goals, well, maybe even quite long-term goals, which are set up by our brains, which have goal-seeking machinery built into them. But what we feel, we don't feel motivated by the desire to pass on our DNA, mostly. We have other goals, which can be very moving, very important, they could even be called spiritual in some cases. We want to understand the riddle of the universe, we want to understand consciousness, we want to understand how the brain works. These are all noble goals, some of them can be noble goals anyway. And they are a far cry from the fundamental biological goal, which is the propagation of DNA. But the machinery that enables us to set up these higher level goals is originally programmed into us by natural selection of DNA. The propagation of DNA, but what do you make of this unfortunate fact that we are mortal? Do you ponder your mortality? Does it make you sad? Does it- I ponder it. It makes me sad that I shall have to leave and not see what's going to happen next. If there's something frightening about mortality, apart from sort of missing, as I've said, something more deeply, darkly frightening, it's the idea of eternity. But eternity is only frightening if you're there. Eternity before we were born, billions of years before we were born, and we were effectively dead before we were born. As I think it was Mark Twain said, I was dead for billions of years before I was born and never suffered the smallest inconvenience. That's how it's going to be after we leave. So I think of it as really, eternity is a frightening prospect. And so the best way to spend it is under a general anesthetic, which is what it'll be. Beautifully put. Richard, it is a huge honor to meet you, to talk to you. Thank you so much for your time. Thank you very much. Thanks for listening to this conversation with Richard Dawkins. And thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review with Five Stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words of wisdom from Richard Dawkins. We are going to die, and that makes us the lucky ones. Most people are never going to die because they are never going to be born. The potential people who could have been here in my place, but who will in fact never see the light of day outnumber the sand grains of Arabia. Certainly those unborn ghosts include greater poets than Keats, scientists greater than Newton. We know this because the set of possible people allowed by our DNA so massively exceeds the set of actual people. In the teeth of these stupefying odds, it is you and I, in our ordinariness, that are here. We privileged few who won the lottery of birth against all odds. How dare we whine at our inevitable return to that prior state from which the vast majority have never stirred? Thank you for listening and hope to see you next time.

https://youtu.be/5f-JlzBuUUU

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Tyler Cowen: Economic Growth & the Fight Against Conformity & Mediocrity | Lex Fridman Podcast #174

The following is a conversation with Tyler Cohen, an economist at George Mason University and co-creator of an amazing economics blog called Marginal Revolution. Author of many books, including The Great Stagnation, Average is Over, and his most recent, Big Business, a love letter to an American anti-hero. He's truly a polymath in his work, including his love for food, which makes this amazing podcast called Conversations with Tyler really fun to listen to. Quick mention of our sponsors, Linode, ExpressVPN, SimplySafe, and Public Goods. Check them out in the description to support this podcast. As a side note, given Tyler's culinary explorations, let me say that one of the things that makes me sad about my love-hate relationship with food is that while I've found a simple diet, plain meat and veggies, that makes me happy in day-to-day life, I sometimes wish I had the mental ability to moderate consumption of food so that I could truly enjoy meals that go way outside of that diet. I've seen my mom, for example, enjoy a single piece of chocolate, and yet, if I were to eat one piece of chocolate, the odds are high that I would end up eating the whole box. This is definitely something I would like to fix because some of the amazing artistry in this world happens in the kitchen, and some of the richest human experiences happen over a unique meal. I recently was eating cheeseburgers with Joe Rogan and John Donaher late at night in Austin, talking about jiu-jitsu and life, and I was distinctly aware of the magic of that experience, magic made possible by the incredibly delicious cheeseburgers. This is the Lex Friedman Podcast, and here is my conversation with Tyler Cohen. Would you say economics is more art or science or philosophy or even magic? What is it? Economics is interesting because it's all of the above. To start with magic, the notion that you can make some change and simply everyone's better off, that is a kind of modern magic that has replaced old-style magic. It's an art in the sense that the models are not very exact. It's a science in the sense that occasionally propositions are falsified. There are a few basic things we know, and however trivial they may sound, if you don't know them, you're out of luck. So all of the above. But from my outsider's perspective, economics is sometimes able to formulate very simple, almost like E equals MC squared, general models of how our human society will function when you do a certain thing. But it seems impossible or almost way too optimistic to think that a single formula or just a set of simple principles can describe behavior of billions of human beings with all the complexity that we have involved. So do you have a sense there's a hope for economics to have those kinds of physics-level descriptions and models of the world, or is it just our desperate attempts as humans to make sense of it even though it's more desperate than rigorous and serious and actually predictable like a physics-type science? I don't think economics will ever be very predictive. It's most useful for helping you ask better questions. You look at something like game theory. Well, game theory never predicted USA and USSR would have a war, would not have a war. But trying to think through the logic of strategic conflict, if you know game theory, it's just a much more interesting discussion. Are you surprised that we, speaking of the Soviet Union and the United States, and speaking of game theory, are you surprised that we haven't destroyed ourselves with nuclear weapons yet? Like that simple formulation of mutually assured destruction, that's a good example of an explanation that perhaps allows us to ask better questions, but it seems to have actually described the reality of why we haven't destroyed ourselves with these ultra-powerful weapons. Are you surprised? Do you think the game theoretic explanation is at all accurate there? I think we will destroy each other with those weapons. Eventually? Eventually. Look, it's a very low probability event, so I'm not surprised it hasn't happened yet. I'm a little surprised it came as close as it did. You know, your general thinking, realizing it might've just been a flock of birds or it wasn't a first strike attack from the USA, we got very lucky on that one. But if you just keep on running the clock on a low probability event, it will happen. And it may not be USA and China, USA and Russia, whatever. You know, it could be the Saudis and Turkey. And it might not be nuclear weapons, it might be some other destruction. Bioweapons, but it simply will happen is my view. And I've argued at best we have 700 or 800 years, and that's being generous. A worst? How long we got? Well, maybe it's like a- Asking for a friend. A fourth on arrival process, right? So tiny probability could come any time, probably not in your lifetime, but the chance presumably increases the cheaper weapons of mass destruction are. So the Poisson process description doesn't take in consideration the game theoretic aspect. So another way to consider is repeated games, iterative games. So is there something about us, our human nature that allows us to fight against probability, to reduce, like the closer we get to trouble, the more we're able to figure out how to avoid trouble. The same thing is for when you take exams or you go and take classes, the closer, or paper deadlines, the closer you get to a deadline, the better you start to perform and you get your shit together and actually get stuff done. I'm really not so negative on human nature. And as an economist, I very much see the gains from cooperation. But if you just ask, are there outliers in history? Like was there a Hitler? For instance, obviously. And again, you let the clock tick, another Hitler with nuclear weapons, doesn't per se care about his own destruction, it will happen. So your sense is fundamentally people are good, but outliers happen. But trembling hand equilibrium is what we would call it. Trembling hand equilibrium? That the basic logic is for cooperation, which is mostly what we've seen, even between enemies, but every now and then someone does something crazy and you don't know how to react to it. And you can't always beat Hitler. Sometimes Hitler drags you down. To push back, is it possible that the crazier the person, the less likely they are, and in a way we're safe? Meaning like, this is the kind of proposition, I've had the discussion with my dad as a physicist about this, where he thinks that, like if you have a graph, like evil people can't also be geniuses. So this is his defense why evil people will not get control of nuclear weapons, because to be truly evil. But evil meaning, you can argue that, not even the evil of Hitler we're talking about, because Hitler had a kind of view of Germany and all those kinds of, there's like, he probably deluded himself and the people around him to think that he's actually doing good for the world, similar with Stalin and so on. By evil I mean more like, almost like terrorists, to where they wanna destroy themselves and the world. Like those people will never be able to be actually skilled enough to do, to deliver that kind of mass scale destruction. So the hope is that it's very unlikely that the kind of evil that would lead to extinctions of humans or mass destruction is so unlikely that we're able to last way longer than 700, 800 years. Is that? I agree it's very unlikely, in that sense I accept the argument. But that's why you need to let the clock tick. It's also the best argument for bureaucracy. To negotiate a bureaucracy, it actually selects against pure evil, because you need to build alliances. So bureaucracy in that regard is great, right? It keeps out the worst apples. But look, put it this way, could you imagine 35 years from now, the Osama bin Laden of the future has nukes or very bad bio weapons? It seems to me you can. Yeah. And Osama was pretty evil. And actually even he failed, right? But nonetheless, that's what the 700 or 800 years is there for. And it might be destructive technologies that don't have such a high cost of production or such a high learning curve. Like cyber attacks or artificial intelligence, all those kinds of things. Yeah. I mean, let me ask you a question. Let's say you could as an act of will, by spending a million dollars, obliterate any city on earth, and everyone in it dies. And you'll get caught. And you'll be sentenced to death. But you can make it happen just by willing it. How many months does it take before that happens? So the obvious answer is like very soon. That's probably a good answer for that, because you can consider how many millionaires there are, how many, you can look at that, right? Right. I have a sense that there's just people that have a million dollars. I mean, there's a certain amount, but have a million dollars, have other interests that will outweigh the interest of destroying the entire city. Like there's a particular, maybe that's a hope. It's why we should be nice to the wealthy, too, right? Yeah. Yeah, all that trash talking is Bill Gates. We should stop that, because that doesn't inspire the other future Bill Gates, is to be nice to the world. It's true. But your sense is the cheaper it gets to destroy the world, the more likely it becomes. Now, when I say destroy the world, there's a trick in there. I don't think literally every human will die, but it would set back civilization by an extraordinary degree. It's then just hard to predict what comes next. But a catastrophe where everyone dies, that probably has to be something more like an asteroid or a supernova. And those are purely exogenous, for the time being, at least. So I immigrated to this country. I was born in the Soviet Union in Russia. Which one? Which one? Again, it's an important question. You were born in the Soviet Union, right? Yes, I was born in the Soviet Union. The rest is details, but I grew up in Moscow, Russia. Yeah. But I came to this country, and this country even back there, but it's always symbolized to me a place of opportunity where everybody could build the most incredible things, especially in the engineering side of things. Just invent and build and scale and have a huge impact on the world. And that's been, to me, that's my version of the American ideal, the American dream. Do you think the American dream is still there? Do you think, what do you think of that notion in itself? From an economics perspective, from a human perspective, is it still alive? And how do you think about it? The American dream. The American dream is mostly still there. If you look at which groups are the highest earners, it is individuals from India and individuals from Iran, which is a fairly new development. Great for them, not necessarily easy. Both you could call persons of color, may have faced discrimination, also on the grounds of religion, yet they've done it. That's amazing. It says great things about America. Now, if you look at native-born Americans, the story's trickier. People think intergenerational mobility has declined a lot recently, but it has not for native-born Americans. For about, I think, 40 years, it's been fairly constant, which is sort of good, but compared to much earlier times, it was much higher in the past. I'm not sure we can replicate that, because look, go to the beginning of the 20th century. Very few Americans finish high school, or even have much wealth. There's not much credentialism. There aren't that many credentials. So there's more upward mobility across the generations than today. And it's a good thing that we had it. I'm not sure we should blame the modern world for not being able to reproduce that. But look, the general issue of who gets into Harvard or Cornell, is there an injustice, should we fix that, is there too little opportunity for the bottom, say, half of Americans, absolutely. It's a disgrace how this country has evolved in that way. And in that sense, the American dream is clearly ailing. But it has had problems from the beginning, for blacks, for women, for many other groups. I mean, isn't that the whole challenge of opportunity and freedom, is that it's hard, and the difficulty of how hard it is to move up in society is unequal often, and that's the injustice of society. But the whole point of that freedom is that over time, it becomes better and better. You start to fix the leaks, the issues, and it keeps progressing in that kind of way. But ultimately, there's always the opportunity, even if it's harder, there's the opportunity to create something truly special, to move up, to be president, to be a leader in whatever the industry that you're passionate about. We each have podcasts, right, in English. The value of joining that American English language network is much higher today than it was 30 years ago, mostly because of the internet. So that makes immigration returns themselves skewed. So going to the US, Canada, or the UK, I think has become much more valuable in relative terms than say, going to France, which is still a pretty well-off, very nice country. If you had gone to France, your chance of having a globally known podcast would be much smaller. Yeah, this is the interesting thing about how much intellectual influence the United States has. I don't know if it's connected to what we're discussing here, the freedom and opportunity of the American dream. Or does it make any sense to you that we have so much impact on the rest of the world in terms of ideas? Is it just simply because English is the primary language of the world, or is there something fundamental to the United States that drives the development of ideas? So it's almost like, what's cool, what's entertaining, what's meme culture, the internet culture, the philosophers, the intellectuals, the podcasts, the movies, music, all that stuff, driving culture. There's something above and beyond language in the United States. It's a sense of entertainment, really mattering, how to connect with your audience, being direct and getting to the point, how humor is integrated even with science. That is pretty strongly represented here, much more so than on the European continent. Britain has its own version of this, which it does very well. And not surprisingly, they're hugely influential in music, comedy, most of the other areas you mentioned. Canada, yes, but their best talent tends to come here. But you could say it's like a broader North American thing and give them their fair share of credit. What about science? There's a sense higher education is really strong, research is really strong in the United States, but it just feels like, culturally speaking, when we zoom out, scientists aren't very cool here. Most people wouldn't be able to name basically a single scientist. Maybe they would say, what, Einstein and Neil deGrasse Tyson, maybe? And Neil deGrasse Tyson isn't exactly a scientist, he's a science communicator. So there's not the same kind of admiration of science and innovators as there is of like, athletes or actors, actresses, musicians. Well, you can become a celebrity scientist if you want to. It may or may not be best for science. And we have Spock from Star Trek, who is still a big deal. But look at it this way, which country is most comfortable with inegalitarian rewards for scientists, whether it's fame or money? And I still think it's here. Some of that's just the tax rate. Some of it is a lot of America is set up for rich people to live really well. And again, that's gonna attract a lot of top talent. And you ask like, the two best vaccines. I know the Pfizer vaccine is sort of from Germany, sort of from Turkey, but it's nonetheless being distributed through the United States. Moderna, an ethnic Armenian immigrant through Lebanon, first to Canada, then down here to Boston, Cambridge area. Those are incredible vaccines. And US nailed it. Yeah, well, that's more almost like the, I don't know what you would call it, engineering, the sort of scaling. That's what US is really good at, not just inventing of ideas, but taking an idea and actually building the thing and scaling it and being able to distribute it at scale. I think some people would attribute that to the general word of capitalism. I don't know if you would. What in your views are the pros and cons of capitalism as it's implemented in America? I don't know if you would say capitalism is really exist in America, but to the extent that it does. People use the word capitalism in so many different ways. What is capitalism? The literal meaning is private ownership of capital goods, which I favor in most areas. But no, I don't think the private sector should own our F-16s or military assets. Government-owned water utilities seem to work as well as privately-owned water utilities. But with all those qualifications put to the side, business, for the most part, innovates better than government. It is oriented toward consumer services. The biggest businesses tend to pay the highest wages. Business is great at getting things done. USA is fundamentally a nation of business, and that makes us a nation of opportunity. So I am indeed mostly a fan, subject to numerous caveats. What's the con? What are some negative downsides of capitalism in your view, or some things that we should be concerned about maybe for long-term impacts of capitalism? Again, capitalism takes a different form in each country. I would say in the United States, our weird blend of whatever you want to call it has had an enduring racial problem from the beginning, has been a force of taking away land from Native Americans and oppressing them pretty much from the beginning. It has done very well by immigrants for the most part. We revel in tributary and creative destruction more, so we don't just prop up national champions forever. And there's a precariousness to life for some people here that is less so, say in Germany or the Netherlands. We have weaker communities in some regards than say Northwestern Europe often would. That has pluses and minuses. I think it makes us more creative. It's a better country in which to be a weirdo than say Germany or Denmark. But there is truly, whether from the government or from your private community, there is less social security in some fundamental sense. On the point of weirdo, that's kind of a beautiful little statement. What is that? I mean, that seems to be, you could think of a guy like Elon Musk and say that he's a weirdo. Is that the sense in which you're using the weirdo? Like outside of the norm, like breaking conventions. Absolutely. And here that is either acceptable or even admired or to be a loner. And since so many people are outsiders and that we're all immigrants is selecting for people who left something behind, were willing to leave behind their families, were willing to undergo a certain brutality of switch in their lives, makes us a nation of weirdos and weirdos are creative. And Denmark is not a nation of weirdos. It's a wonderful place, great for them. Ideally, you want part of the world to be fully weirdos and innovating. And the other part of the world to be a little kind of chicken shit, risk averse and enjoy the benefits of the innovation. And to give people these smooth lives and six weeks off and free ride. And everyone's like, oh, American way versus European way, but basically they're compliments. Yeah, that's fascinating. I used to have this conversation with my parents when I was growing up and just others from the immigrant kind of flow. And they use this term, especially in Russian is to criticize something I was doing, that was suggest, normal people don't do this. And I used to be really offended by that. But as I got older, I realized that that's a kind of compliment because in the same kind of, I would say, way that you're saying that is the American ideal. Because if you want to do anything special or interesting, you don't wanna be doing in one particular avenue what normal people do, because that won't be interesting. Russians, I think, fit in very well here because the ones who come are weirdos. And there's a very different Russian weirdo tradition like Alyosha, right, and brothers Karamasoff. Or Perelman, the mathematician, they're weirdos. And they have their own different kind of status in Soviet Union, Russia, wherever. And when Russians come to America, they stay pretty Russian. But it seems to me a week later, they've somehow adjusted. And the ways in which they might wanna be grumpier than Americans, not smile, think that people who smile are idiots. Like they can do that. No one takes that away from them. What do you, on a tiny tangent, I'd love to hear if you have thoughts about Grisha Perelman turning down the Fields Medal. Is that something you admire? Does that make sense to you that somebody, we have the structure of Nobel Prizes, of these huge awards, of the reputations, the hierarchy of everyone saying, applauding how special you are. And here's a person who was doing one of the greatest accomplishments in the history of mathematics. It doesn't want the stupid prize and doesn't want recognition, doesn't wanna do interviews, it doesn't wanna be famous. What do you make of that? It's great, look, prizes are corrupting. After scientists win Nobel Prizes, they tend to become less productive. Now, statistically, it's hard to sort out the different effects. There's regression toward the mean. Does the prize make you too busy? It's a little tricky, but. There's not enough Nobel Prizes either to gather enough data. Right, but I've known a lot of Nobel Prize winners and it is my sense they become less productive. They repeat more of their older messages, which may be highly socially valuable. But if someone wants to turn their back on that and keep on working, which I assume is what he's doing, that's awesome. I mean, we should respect that. It's like he wins a bigger prize, right? Our extreme respect. Yeah. Wow. Grisha, if you're listening, I need to talk to you soon. Okay. I've been trying to get ahold of him. Okay. Back to capitalism, I gotta ask you, just competition in general in this world of weirdos. Is competition good for the world? This kind of seems to be one of the fundamental engines of capitalism, right? Do you see it as ultimately constructive or destructive for the world? What really matters is how good your legal framework is. So competition within nature, for food leads to bloody conflict all the time. The animal world is quite unpleasant to say the least. If you have something like the rule of law and clearly defined property rights, which are within reason justly allocated, competition probably is gonna work very well. But it's not an unalloyed good thing at all. It can be highly destructive. Military competition, right? Which actually is itself sometimes good, but it's not good per se. What aspects of life do you think we should protect from competition? So is there some, you said like the rule of law, is there some things we should keep away from competition? Well, the fight for territory most of all, right? So violence, anything that involves like actual physical violence. Right, and it's not that I think the current borders are just. I mean, go talk to Hungarians, Romanians, Serbians, Bosnians, they'll talk your ear off. And some of them are probably right. But at the end of the day, we have some kind of international order. And I would rather we more or less stick with it. If Catalonians wanna leave, they keep up with it, you know, let them go. But. What about space of like healthcare? This is where you get into a tension of like, between capitalism and kind of more, I don't wanna use socialism, but those kinds of policies that are less free market. I think in this country, healthcare should be much more competitive. So you go to hospitals, doctors, they don't treat you like a customer. They treat you like an idiot or like a child or someone with third party payment. And it's a pretty humiliating experience often. Yeah, do you think a free market in general is possible, like a pure free market? And is that a good goal to strive for? I don't think the term pure free market's well defined because you need a legal order. The legal order has to make decisions on like, what is intellectual property? More important than ever. There's no benchmark that like represents the pure free market way of doing things. What will penalties be? How much do we put into law enforcement? No simple answers, but just saying free market doesn't pin down what you're gonna do on those all important questions. So free market is an economics, I guess, idea. So there's no, it's not possible for free market is generate the rules that are like emergent, like self-governing. It generates a lot of them, right? Through private norms, through trade associations, international trade is mostly done privately and by norms. So it's certainly possible, but at the end of the day, I think you need governments to draw very clear lines to prevent it from turning into mafia run systems. You know, I've been hanging out with other group of weirdos lately, Michael Malice, who espouses to be an anarchist, anarchism, which is like, I think intellectually, just a fascinating set of ideas, where the, you know, taking free market to the full extreme of basically saying there should be no government, what is it? Oversight, I guess, and then everything should be fully, like all the agreements, all the collectives you form should be voluntary, not based on the geographic land you were born on and so on. Do you think that's just a giant mess? Like, do you think it's possible for an anarchist society to work, where it's, you know, in a fully distributed way, people agree with each other, not just on financial transactions, but, you know, on their personal security, on sort of military type of stuff, on healthcare, on education, all those kinds of things. And where does it break down? Well, I wouldn't press a button to say, get rid of our current constitution, which I view as pretty good and quite wise. But I think the deeper point is that all societies are in some regards anarchistic, and we should take the anarchist seriously. So globally, there's a kind of anarchy across borders, even within federalistic systems, they're typically complex. There's not a clear transitivity necessarily of who has the final say over what. Just the state vis-a-vis its people. There's not per se a final arbitrator in that regard. So you want a good anarchy rather than a bad anarchy. You want to squish your anarchy into the right corners. And I don't think there's a theoretical answer how to do it. But you start with a country, like, is it working well enough now? This country, you'd say mostly. You'd certainly want to make a lot of improvements. And that's why I don't want to press that get rid of the constitution button. But to just dump on the anarchist system is the point. Always try to learn from any opinion. You know, and what in it is true. I'm just like marveling at the poetry of saying that we should squish our anarchy into the right corners. Love it. Okay, I gotta ask, I've been talking with, since we're doing a whirlwind introduction to all of economics, I've been talking to a few objectivists recently. And just, you know, Ayn Rand comes up as a person, as a philosopher, throughout many conversations, a lot of people really despise her. A lot of people really love her. It's always weird to me when somebody arouses a philosophy or a human being arouses that much emotion in either direction. Do you understand, first of all, that level of emotion? And what are your thoughts about Ayn Rand and her philosophy, objectivism? Is it useful at all to think about this kind of formulation of rational self-interest, if I could put it in those words? Or I guess more negatively, the selfishness. Or she would put, I guess, the virtue of selfishness. Ayn Rand was a big influence on me growing up. The book that really mattered for me was Capitalism, the Unknown Ideal. The notion that wealth creates opportunity and good lives and wealth is something we ought to valorize and give very high status. It's one of her key ideas. I think it's completely correct. I think she has the most profound and articulate statement of that idea. That said, as a philosopher, I disagree with her on most things. And I did, even like as a boy when I was reading her. I read Plato before Ayn Rand. And in a Socratic dialogue, there's all these different points of view being thrown around. And whomever it is you agree with, you understand the wisdom is in coming together at the different points of view. And she doesn't have that. So altruism can be wonderful in my view. Humans are not actually that rational. Self-interest is often poorly defined. To pound the table and say existence exists, I wouldn't say I disagree, but I'm not sure that it's a very meaningful statement. I think the secret to Ayn Rand is that she was Russian. I'd love to have her on my podcast if she were still alive. I'd only ask her about Russia, which she mostly never talked about after writing We the Living. And she is much more Russian than she seems at first, even like purging people from the objectivist circles. It's like how Russians, especially female Russians, so often purge their friends. It's weird, all the parallels. So you're saying, so yes, so assuming she's still not around, but if she is and she comes into your podcast, can you dig into that a little bit? Do you mean like her personal demons around the social and economic Russia of the time when she escaped? The traumas she suffered there, what she really likes in the music and literature and why. Music and literature, huh? And getting deeply into that, her view of relations between the sexes in Russia, how it differs from America, why she still carries through the old Russian vision in her fiction, this extreme sexual dimorphism, but with also very strong women, to me is a uniquely, at least Eastern European vision, mostly Russian, I would say. And that's in her, that's her actual real philosophy, not this table-bounding existence exists. And that's not talked about enough. She's a Russian philosopher. Yeah, like she's- Or Soviet, whatever you wanna call it. And if she wasn't so certain, she could have been a Dostoevsky, where it's not, that certainty is almost the thing that brings her the adoration of millions, but also the hatred of millions. You became a cult figure in a somewhat Russian-like manner. Yeah. Yeah. It is what it is. But I love the idea that, again, you're just dropping bombs that are poetic, that the wisdom is in the coming together of ideas. It's kind of interesting to think that no one human possesses wisdom. No one idea is the wisdom, that the coming together is the wisdom. Like in my view, Boswell's Life of Johnson, 18th century British biography. It's in essence a co-authored work, Boswell and Johnson. It's one of the greatest philosophy books ever, though it is commonly regarded as a biography. John Stuart Mill, who in a sense was co-authoring with Harriet Taller, a better philosopher than is realized, though he's rated very, very highly. Plato slash Socrates, a lot of the greatest works are in a kind of dialogue form. Goethe's Faust would be another example. It's very much a dialogue. And yes, it's drama, but it's also philosophy, Shakespeare. Maybe the wisest thinker of them all. In your book, Big Business, speaking of Ayn Rand, Big Business, A Love Letter to an American Antihero, you make the case for the benefit that large businesses bring to society. Can you explain? If you look at, say, the pandemic, which has been a catastrophic event, right, for many reasons, but who is it that saved us? So Amazon has done remarkably well. They upped their delivery game more or less overnight with very few hitches. I've ordered hundreds of Amazon packages, direct delivery food, whether it's DoorDash or Uber Eats or using Whole Foods through Amazon shipping. Again, it's gone remarkably well. Switching over our entire higher educational system, basically within two weeks, to Zoom. Zoom did it. I mean, I've had a Zoom outage, but their performance rate has been remarkably high. So if you just look at resources, competence, incentives, who's been the star performers? The NBA, even, just canceling the season as early as they did, sending a message like, hey, people, this is real, and then pulling off the bubble. It's not a single found case of COVID and having all the testing set up in advance. Big business has done very well lately, and throughout the broader course of American history, in my view, has mostly been a hero. Can we engage in a kind of therapy session? I'm often troubled by the negativity towards big business, and I wonder if you could help figure out how we remove that, or maybe first psychoanalyze it, and then how we remove it. It feels like, you know, once we've gotten wifi on flights, on airplane flights, people started complaining about how shitty the connection is, right? They take it for granted immediately, and then start complaining about little details. Another example that's closer to, especially as aspiring entrepreneurs, closer to the things I'm thinking about is Jack Dorsey with Twitter. To me, Twitter has enabled an incredible platform of communication, and yet the biggest thing that people talk about is not how incredible this platform is. They essentially use the platform to complain about the censorship of a few individuals, as opposed to how amazing it is. Now, you should also, you should talk about how shitty the wifi is, and how censorship, or the removal of Donald Trump from the platform is a bad thing, but it feels like we don't talk about the positive impacts at scale of these technologies. Is there, can you explain why, and is there a way to fix it? I don't know if we can fix it. I think we are beings of high neuroticism, for the most part, as a personality trait. Not everyone, but most people. And as a compliment to that, if someone says 10 nice things about you, and one insult, you're more bothered by the insult than you're pleased by the nice things, especially if the insult is somewhat true. So you have these media, these vehicles, Twitter is one you mentioned, where it's all kind of messages going back and forth, and you're really bugged by the messages you don't like. Most people are neurotic to begin with. It's not only taken out on big business, to be clear. So Congress catches a lot of grief, and some of it they deserve, yes. Religion is not attacked the same way, but religiosity is declining. If you poll people, the military still polls quite well, but people are very disillusioned with many things, and the Martin Gury thesis, that because of the internet, you just see more of things, and the more you see of something, whether it's good, bad, or in between, the more you will find to complain about, I suspect, is the fundamental mechanism here. I mean, look at Clubhouse, right? To me, it's a great service, may or may not be my thing, but gives people this opportunity. No one makes you go on it. And all these media articles, like, oh, is Clubhouse gonna wreck things? Are they gonna break things? New York Times is complaining. Of course, it's their competitor as well. I'm like, give these people a chance, talk it up. You may or may not like it. Let's praise the people who are getting something done. Very Ayn Randian point. As an economic thinker, as a writer, as a podcaster, what do you think about Clubhouse? What do you think about? Okay, let me just throw my feeling about it. I used to use Discord, which is another service where people use voice. So the only thing you do is just hear each other. There's no face, you just see a little icon. That's the essential element of Clubhouse. And there's an intimacy to voice-only communication that's hard, that didn't make sense to me, but it was just what it is. Which feels like something that won't last for some reason. Maybe it's the cynical view. But what's your sense about the intimacy of what's happening right now with Clubhouse? I've greatly enjoyed what I've done, but I'm not sure it's for me in the long run for two reasons. First, if you compare it to doing a podcast, podcasting has greater reach than Clubhouse. So I would rather put time into my podcast. But then also, my core asset, so to speak, is I'm a very fast reader. So audio per se is not necessarily to my advantage. I don't speak or listen faster than other people. In fact, I'm a slower listener, because I like 1.0, not 1.5x. So I should spend less time on audio and more time reading and writing. Yeah, it's interesting because, like you mentioned podcasts and audio books, I, you know, the podcasts are recorded, and so I can skip things. Like I can skip commercials, or I can skip parts where it's like, ugh, this part is boring. With live conversations, especially when, there's a magic to the fact when you have a lot of people participating in that conversation, but, you know, some people are like, ugh, this topic. They're going into this thing, and you can't skip it, or you can't fast forward. You can go 1.5x or 2x. You can't speed it up. Nevertheless, there's a tension between that, so that's the productivity aspect, with the actual magic of live communication, where anything can happen, where Elon Musk can ask the CEO of Robinhood, Vlad, about like, hey, somebody like holding a gun to your head, there's something shady going on. The magic of that. That's also my criticism of like, there's been a recent conversation with Bill Gates, that he went on a platform, and had basically a regular interview on the platform, without allowing the possibility of the magic of the chaos. So, I'm not exactly sure. It's probably not the right platform for you, and for many other people who are exceptionally productive in other places, but there's still nevertheless a magic to the chaos that can be created with live conversation that gives me pause. Maybe what it's perfect for is the tribute. So, they had an episode recently that I didn't hear, but I heard it was wonderful. It was anecdotes about Steve Jobs. That you can't do one-to-one, right? And you don't want control. You want different people appearing and stepping up, and saying their bit. Yeah. And Clubhouse is 110% perfect for that. The tribute. I love that, the tribute. But there's also the possibility, I think there was a time when somebody arranged a conversation with Steve Jobs and Bill Gates on stage. I remember that happened a long time ago. And it was very formal. It could have probably gone better, but it was still magical to have these people that obviously had a bunch of tension throughout their history. It's so frictionless to have two major figures in world history just jump on a Clubhouse stage. Putin and Elon Musk. Putin and Elon Musk. See if it happens. And that's exactly it. So, there's a language barrier there but there's also the problem that in particular, it's like Biden would have a similar problem. It's like they're just not into new technology. So, it's very hard to catch the Kremlin up to, first of all, Twitter. But to catch them up to Clubhouse, you have to have the, Elon Musk has a sense of the internet, the humor, the memes, and all that kind of stuff that you have to have in order to use a new app and figure out the timing, the beat, what is this thing about? So, that's the challenge there. But that's exactly it. That magic of have two big personalities just show up. And I wonder if it's just a temporary thing that we're going through with the pandemic where people are just lonely and they're seeking for that human connection that we usually get elsewhere through our work. But they'll stay lonely, in my opinion. You think so? I do. So, it is a pandemic thing but I think it will persist. And the idea of wanting to be connected to more of the world, Clubhouse will still offer that. And all the mental health issues out there, a lot of people have broken ties and they will still be lonely post-vaccines. Yeah, I, from an artificial intelligence perspective, have a sense that there is like a deep loneliness in the world, that all of us are really lonely. Like, we don't even acknowledge it. Even people in happy relationships. It feels like there's like an iceberg of loneliness in all of us. Like, seeking to be understood, like deeply understood. Understanding our, like having somebody with whom you can have a deep interaction enough to where you can, they can help you to understand yourself and they also understand you. Like, I have a sense that artificial intelligence systems can provide that as well. But humans, I think, crave that from other humans. In ways that we perhaps don't acknowledge. And I have a hope that technology will enable that more and more. Like, Clubhouse is an example that allows that. Are Turing bots gonna out-compete Clubhouse? Like, why not sort of program your own session? You'll just talk into your device and say, here's the kind of conversation I want. And it will create the characters for you. And it may not be as good as Elon and Vladimir Putin, but it'll be better than ordinary Clubhouse. Yeah, and one of the things that's missing, it's not just conversation. It's memory. So long-term memory is what current AI systems don't have. Is sharing an experience together. Forget the words. It's like sharing the highs and the lows of life together and the systems around us remembering that. Remembering we've been through that. Like, that's the thing that creates really close relationships, is going through some shit. Like, go struggle. If you've survived together, there's something really difficult that bonds you with other humans. And this is related to immigration and the American dream. In what way? The people who have come to this country, however weird and different they may be, they or their ancestors at some point probably have shared this thing. Right, US is not gonna split up. It may get more screwed up as a country, but Texas and California are not gonna break off. Yeah. I mean, they're big enough where they could do it, but it's just never gonna happen. We've been through too much together. Yeah. Yeah. That's a hopeful message. Do you think, you know, some people have talked to Eric Weinstein, you've talked to Eric Weinstein. He has a sense that growth, you know, like the entirety of the American system is based on the assumption that we're gonna grow forever, the economy's gonna grow forever. Do you think economic growth will continue indefinitely, or will we stagnate? I've long been in agreement with Eric, Peter Thiel, Robert Gordon and others that growth has slowed down. I argue that in my book, The Great Stagnation, appropriately titled. But the last two years I've become much more optimistic. I've seen a lot of breakthroughs in green energy and battery technology. mRNA vaccines and medicine is a big deal already. It will repair our GDP and save millions of lives around the world. There's an anti-malaria vaccine that's now in stage three trial, it probably works. CRISPR to defeat sickle cell anemia. Just space, area after area after area, there's suddenly the surge of breakthroughs. I would say many of them rooted in superior computation and ultimately Moore's law and access to those computational abilities. So I'm much more optimistic than say, the last time I spoke to Eric. I don't know, he moves all the time in his views. I don't know where he's at. He hasn't gained, that's really interesting. So your little drop of optimism comes from, like there might be a fundamental shift in the kind of things that computation has unlocked for us in terms of like, it could be a wellspring of innovation that enables growth for a long time to come. Like Eric has not quite connected to the computation aspect yet to where it could be a wellspring of innovation. But you're very close to it in your own work. I don't have to tell you that. The work you're doing would not have been possible not very long ago. But the question is, how much does that work enable continued growth for decades to come? For all their problems, some version of driverless vehicles will be a thing. I'm not sure when, you know much better than I do. Maybe only partially, but that too will be a big deal. Well, one of the open questions that sort of the Peter Thiel School area of ideas is how much can be converted to technology? How many parts of our lives can technology integrate and then innovate? Like, can it replace healthcare? Can it replace the legal system? Can it replace government? Not replace, but like, you know, make it digital and thereby enable computation to improve it, right? That's the open question. Because many aspects of our lives are still not really that digitized. There was a New York Times symposium in April, which is not long ago. And they asked the so-called experts, when are we gonna get vaccines? And the most optimistic answer was in four years. Yeah. And obviously we beat that by a long mile. So I think people still haven't woken up. You mentioned my tiny drop of optimism, but it's a big drop of optimism. Is it a waterfall yet? I mean, is it just? Well, here's my pessimism. Whenever there are major new technologies, they also tend to be used for violence, directly or indirectly. Radio, Hitler. Not that he hit people over the head with radios, but it enabled the rise of various dictators. So the new technologies now, whatever exactly they may be, they're gonna cause a lot of trouble. Yeah. And that's my pessimism. Not that I think they're all gonna slow to a trickle. When was the stagnation book? 2011. 2011. Yes. It was the first of the stagnation books, in fact. It's very interesting. But even then I said, this is temporary. And I was predicting it would be gone in about 20 years time. I'm not sure that's exactly the right prediction, like 2030, but I think we're actually gonna beat that. So you think United States might still be on top of the world for the rest of the century, in terms of its economic growth, impact on the world, scientific innovation, all those kinds of things. That's too long to predict, but I'm bullish on America in general. Got it. Speaking of being bullish on America, the opposite of that is, we talked about capitalism, we talked about Ayn Rand and her Russian roots. What do you think about communism? Why doesn't it work? What, is it the implementation, is there anything about its ideas that you find compelling? Or is it just a fundamentally flawed system? Well, communism is like capitalism. The words mean many things to different people. You could argue my life as a tenured professor comes closer to communism than anything the human race has seen. And I would argue it works pretty well. Yeah. But look, if you mean the Soviet Union, it devolved pretty quickly to a kind of decentralized set of incentives that were destructive rather than value maximizing. It wasn't even central planning, much less communism. So Paul Craig Roberts and Polanyi were correct in their descriptions of the Soviet system. Think of it as weird mixes of barter and malfunctioning incentives, and being very good at a whole bunch of things. But in terms of progress, innovation, and consumer goods, it really being quite a failure. And now I wouldn't call that communism, but that's what I think of the system the Soviets had. And it required an ever increasing pile of lies that both alienated people, but created an elite that by the end of the thing, no longer believed in the system itself, or even thought they were doing better by being crooks than by just say moving to Switzerland and being an upper middle class individual, like you would have a higher standard of living by Gorbachev's time. Not Gorbachev, but if you're number 30 in the hierarchy, you're better off as a middle class person in Switzerland. And that, of course, did not prove sustainable. And so it's, what is it, a momentum of bureaucracy or something like that just builds up where you lose control of the original vision, and then naturally happens. It's just people. And you can't use normal profit and loss and price incentives. So you get all prices, or most prices set too low, right? Shortages everywhere, people trade favors. You have this culture of bartered bribes, sexual favors, or family friends. And you get more and more of that, and you over time lose more and more of the information and the prices and quantities and practices and norms you had. And that sort of slowly decays. And then by the end, no one is believing in it. That would be my take. But again, you're the expert here. The Russian scholar, well, perhaps no more an expert than Ayn Rand. It's more personal than it is scholarly or historic. So Stalin held power for 30 years. Vladimir Putin has held power for 21 years, where you could argue he took a little break. But not much. He was still holding power, I think. And it's still possible now with the new constitution that he could hold power for longer than Stalin, longer than 30 years. What do you think about the man, the state of affairs in Russia, in general, the system they have there? Is there something interesting to you as an economist, as a human being, about Russia? Everything is interesting. I mean, here would be part of my take. As you know, the Russian economy, starting, what, 1999, 2000, has really quite a few years of super excellent growth. And Putin is still riding on that. It more or less coincides with his rise as the truly focal figure on the scene. Since then, pretty recently, they've had a bunch of years of negative 4% to 5% growth in a row, which is terrible. The economy is way too dependent on fossil fuels. But the structural problem is this. You need a concordance across economic power, social power, political power. They don't have to be allocated identically, but they have to be allocated consistently. And the Russian system under Putin, from almost the beginning, has never been able to have that, that ultimately his incentives are to steer the system where the economic power is in a small number of hands in a non-diversified way. The system won't deliver sustainable gains in living standards anymore, ever, the way it's set up now. Now, if fossil fuel prices go up, they'll have some good years for sure. And that is really quite structural, what has gone wrong. And then on top of that, you can have an opinion of Putin, but you've got to start with those structural problems. And that's why it's just not gonna work. But he had all those good years in the beginning. So the number of Russians, say, who live here, or in Russia, who love Putin and it's sincere, they're not just afraid of being dragged away, like that's a real phenomenon. Yeah, I'm really torn on, Putin's approval rating, real approval rating, seems to be very high. And I'm torn in whether that has to do with the fact that there is control of the press, or if it's, which is the people I talk to who are in Russia, family and so on, a genuine love of Putin, appreciation of what Putin has done and is going to do with Russia. And- But a lot of that would go away if the press were freer, I think. Yes. Well, Singapore realizes this. Anyone discussed by the press, no matter who they are, people in Singapore have done a great job. Yes. But if you're discussed by the press, you don't look good. Tech company executives are learning this, right? It's just like a rule. So in that sense, I think the rating is artificially high, but I don't by any means think it's all insincere. But that high popularity I view as bearish for Russia. I would feel better about the country if people were more pissed off at him. Yeah, that's right. It's nice to see free speech, even if it's full of hate. I am also troubled on the scientific side and entrepreneurial side. It seems difficult to be an entrepreneur in Russia. Like it's not even in terms of rules, it's just culturally, the people I speak to, it's not easy to build a business. No, it's not easy to even dream of building a business in Russia. That's just not part of the culture, part of the conversation. It's almost like the conversation is, if you wanna be the next Bill Gates or Elon Musk or Steve Jobs or whatever, you come to America. That's the sense they have. Yeah, history matters. Is it history, is it structural problems of today? I mean, it's all the same thing. So a history of hostility to commerce, which of course the old USSR is gone, but a lot of the attitudes remain, a lot of the corruption remains. You have this legacy distribution of wealth from the auctioning off of the assets, which is not conducive to some kind of broadly egalitarian democracy. And so you have these small number of PowerPoints that try to control information and wealth and not really so keen to encourage the others who ultimately would pull the balance of political power away from the very wealthy and from Putin. And they support that culture. And the return of interest in Orthodox Church and all that, it's all part of the same piece, I think, because the old Orthodox Church is not that pro-commerce, you'd have to say, but it's traditionalist, it's pro-family, those are safer ideas. And then there's such a great safety valve, the most ambitious, smartest people, like they probably will learn English. They sort of can look like they belong in all sorts of other countries that can show up and blend in. Super talented, they've probably had an excellent education, especially if they're from one of the two major cities, but even if not so, even from Siberia, and they go off, they leave, they're not a source of opposition, and that keeps the whole thing up and running for another generation. Yeah. What do you make of the other big player, China? They seem to have a very different, messed up, but also functioning system. They seem to be much better at encouraging entrepreneurs. They're choosing winners, but what do you make of the entire Chinese system? Why does it work as well as it does currently? What are your concerns about it? And what are its threats to the United States, or possible, what is it you said, wisdom is when two ideas come together. Is there some possible benefits of these kinds of ideas coming together? It's amazing what China has done, but I would say to put it in perspective, if you compare them to Japan, South Korea, Taiwan, Hong Kong, and Singapore, they've still done much worse. Not even close. And that's both living standards, or I hesitate to cite democracy as an unalloyed good in and of itself, but there's more freedom in all those other places by a lot. So China has all these problems of history, but they've managed, as actually the Soviets did in the middle of the 20th century, one of the two great mass migrations from the countryside to cities, which boosts productivity enormously, and will sustain totalitarian systems, but they moved from a totalitarian system to an oligarchy where the CCP is actually, at least for a while, hey, has been really good at governing, has made a lot of very good decisions. You have to admit that. I don't know how long that streak will continue with one person so much now holding authority in a more extreme manner. The selection pressures for the next generation of high-level CCP members probably become much worse. You have this general problem of the state-owned enterprise is losing relative productivity compared to the private sector. Well, we're gonna kind of hold Jack Ma on this island, and he can only issue weird hello statements. It kind of smells bad to me. I don't feel that it's about to crash. But I don't see them supplanting America as the world's number one country. I think they will muddle through and have very serious problems. But there's enough talent there, they will muddle through. Is there ideas from China or from anywhere in general of large-scale role of government that you find might be useful? Like Andrew Yang recently ran on a platform, UBI, Universal Basic Income. Is there some interesting ideas of large-scale government, sort of welfare programs at scale that you find interesting? Well, keep in mind, the current version of the Chinese Communist Party, post-Mao, dismantled what was called the Iron Rice Ball. So it took apart the healthcare protections, a lot of the welfare system, a lot of the guaranteed jobs. So the economic rise of China coincided with the weakening of welfare. Not saying that's causal per se, but people think of China as having a government that takes care of everyone. It's very far from the truth. And by a lot of metrics, I don't mean control over people's lives, I don't mean speech, but by a lot of metrics, economically, we have a lot more government than they do. So what one means here by government, private control, I don't think you can just add up the numbers and get a simple answer. They've been fantastic at building infrastructure in cities in ways that will attract people from the countryside. And furthermore, they more or less enforce a meritocracy in this sense. Like if you're a kid of a rich guy, you'll get unfair privilege. That's unfair, but systems can afford that. If you are smart and from the countryside and your parents have nothing, you will be elevated and sent to a very good school, graduate school, because of the exam system. And they do that and they mean that very consistently. It's like the Soviets had a version of that, like for jazz and romantic piano, not for everything, but where they had it, again, they were tremendous, right? Yeah, exactly. And the Chinese have it in so many areas, a genuine meritocracy in this one way. That moves people from the rural to the big city and that's a big boost of productivity for so a lot of time. And when they get there, they're taken seriously. Jack Ma was riding a bicycle teaching English in his late 20s, he was a poor guy. So not a society of credentialism. Or in America, it's way too much a credentialist society. As we were talking about, even with the Nobel Prize. But what do you think about these large government programs like UBI? The one version of UBI that makes the most sense to me is the Mitt Romney version, UBI for kids. Like kids are vulnerable, if their parents screw up, you shouldn't blame the kid or make the kid suffer. I believe in something like UBI for kids, maybe just cash. But if you don't have kids, even with AI, my sense is at least in the world we know, you should be able to find a way to adjust. You might have to move to North Dakota to work, next to fracking say. But look, before the pandemic, the two most robot-intensive societies, Japan and the US, US at least for manufacturing, were at full employment. So maybe there's some far off day where there's literally no work. John Lennon, imagine it's piped everywhere. And then we might revisit the question. But for now, we had rising wages in the Trump years and full employment. So I don't see that- You don't see automation as a threat that fundamentally shakes our society. It's a threat in the following sense. The new technologies are harder to work with for many people and that's a social problem. But I'm not sure a universal basic income is the right answer to that very real problem. Well, that's also, I like the UBI for kids. It's also your definition or the line, the threshold for what is vulnerable and what is basic human nature. Going back to Russia, life is suffering. That struggle is a part of life. And perhaps sort of changing, maybe what defines the 21st century is having multiple careers and adjusting and learning and evolving. And some of the technology in terms of, some of the technology we see like the internet allows us to make those pivots easier. It allows later life education possible. It makes it possible. I don't know. And your earlier point about loneliness being this fundamental human problem, which I would agree with strongly, UBI, if it's at a high level, will make that worse. I mean, say UBI were higher enough, you could just sit at home. People are not gonna be happy. They don't actually want that. And we've relearned that in the pandemic. Yeah, the flip side, the hope with UBI is you have a little bit more freedom to find the thing that alleviates your loneliness. That's the idea. So it's kind of an open question. If I give you a million dollars or a billion dollars, will you pursue the thing you love? Will you be more motivated to find the thing you love, to do the thing you love, or will you be lazy and lose yourself in the sort of daily activities that don't actually bring you joy, but pacify you in some kind of way where you just let the day slip by? That's the open question. But a lot of the great creators did not have huge cushions, whether it's Mozart or James Brown or the great painters in history. They had to work pretty hard. And if you look at heirs to great fortunes, maybe I'm forgetting someone, but it's hard to think of any who have creatively been important as novelists or they might have continued to run the family business. But Van Gogh was not heir to a great family fortune. It's sad that cushions get in the way of progress. Yeah, so- It's the same point about prizes, right? Yeah. Inheriting too much money is like winning a prize. We mentioned Eric, Eric Weinstein. I know you agree on a bunch of things. Is there some beautiful, fascinating, insightful disagreement that you have that has yet to be resolved with him? Is there some ideas that you guys battle it out on? Is it the stagnation question that you mentioned? That's one of them, but here's at least two others. But I would stress Eric is always evolving. So I'm just talking about a time slice, Eric, right? I don't know where he's at right now. Like I heard him on Clubhouse three nights ago, but that was three nights ago. But I think he's far too pessimistic about the impact of immigration on US science. He thinks it has displaced US scientists, which I think that is partly true. I just think we've gotten better talent. I'm like, bring it on, double down. And look at Currico, who basically came up with mRNA vaccines. She was from Hungary and was ridiculed and mocked. She couldn't get her papers published. She stuck at it. An American might not have been so stubborn because we have these cushions. So Eric is all worried, like mathematicians coming in, they're discouraging native US citizens from doing math. I'm like, bring in the best people. If we all end up in other avocations, absolutely fine by me. Does it trouble you that we kick them out after they get a degree often? I would give anyone with a plausible graduate degree a green card, universally. Yeah, I agree with that. It makes no sense. It makes so strange that the best people that come here suffer here, create awesome stuff here, and then when we kick them out, it doesn't make any sense. Here's another view I have. I call it open borders for Belarus. Now, Russia's a big country. I would gladly increase the Russian quota by three X, four X, five X. Not 20%, but a big boost. But Belarus, small country, and they're poor, and they have decent education, and a lot of talent there. Why can't we just open the door and convert a Belarus passport to a green card? Open borders for Belarus, it's my new campaign slogan. Are you running for president in 2024? Well, write-ins are welcome. What's the second thing you disagree with, Eric? Trade, again, I'm not sure where he's at now, but he is suspicious of trade in a way that I am not. I do understand what's called the China shock has been a big problem for the US middle class. I fully accept that. I think most of that is behind us. National security issues aside, I think free trade is very much a good thing. Eric, I'm not sure he'll say it's not a good thing, but he won't say it is a good thing. And I know he's kind of, it's like, Eric, free trade. But look, on things like vaccines, I don't believe in free trade. You want vaccine production in your own country. Look at the EU. They have enough money, no one will send them vaccines. What's different about vaccines? There's some things you want to prioritize the citizenry on. You could argue it would be cheaper to produce all US-manufactured vaccines in India. They have the technologies, obviously lower wages. But look, there's talk in India right now of cutting off the export of vaccines. If you outsource your vaccine production, you're not sure the other country will respect the norm of free trade. So you need to keep some vaccine production in your country. It's an exception to free trade, not to the logic. A bunch of things the Navy uses. You can't buy those components from China. That's insane. But look, it would be cheaper to do so, right? Yeah. Let me completely shift topics on something that's fascinating. It's all the same topic, but great. Everything is interesting. What do you think about, what the hell is money? And the recent excitement around cryptocurrency that brings to the forefront the philosophical discussion of the nature of money. Are you bullish on cryptocurrency? Are you excited about it? What does it make you think about how the nature of money is changing? No one knows what money is. Probably no one ever knew. Go back to medieval times. Bills of exchange, were they money? Maybe it's just a semantic debate. Gold, silver, what about copper coins? What about metal? What about gold? What about copper coins? What about metals that were considered legal tender, but not always circulating? What about credit? So being confused about moneyness is the natural state of affairs for human beings. And if there's more of that, I'd say that's probably a good thing. Now crypto per se, I think Bitcoin has taken over a lot of the space held by gold. That to me seems sustainable. I'm not short Bitcoin. I don't have some view that the price has to be different than the current price, but I know it changes every moment. I am deeply uncertain about the less of crypto, which seems connected to ultimate visions of using it for transactions in ways where I'm not sure, whether it be prediction markets or DeFi. I'm not sure the retail demand really is there once it is regulated like everything else is. I would say I'm 40, 60 optimistic on those forms of crypto. That is, I think it's somewhat more likely they fail than succeed, but I take them very seriously. So we're talking about it becoming one of the main currencies in the world. That's what we're discussing. That I don't think will happen. So, but the reality is that Bitcoin used to be in the single digits of a dollar and now has crossed $50,000 for a single Bitcoin. Do you think it's possible it reaches something like a million dollars? I don't think we have a good theory of the value of Bitcoin. If people decide it's worth a million dollars, it's worth a million dollars. But isn't that money? Like you said, isn't the ultimate state of money confusion, however beautifully you put it? It's like valuing an Andy Warhol painting. So when Warhol started off, probably those things had no value, the sketches, early sketches of shoes. Now a good Warhol could be worth over 50 million. That's an incredible rate of price appreciation. Bitcoin is seeing a similar trajectory. I don't pretend to know where it will stop, but it's about trying to figure out, well, what do people think of Andy Warhol? He could be out of fashion in a century. Maybe yes, maybe no. But you don't think about Warhols as money. They perform some money-like functions. You can even use them as collateral for like deals between gangs. But they're not basically money, nor is Bitcoin. And the transactions velocity of Bitcoin, I would think is likely to fall, if anything. So you don't think there'll be some kind of phase shift? Will it become adopted and become mainstream for one of the main mechanisms of transactions? Bitcoin, no. Now, Ether has some chance at that. I would bet against it, but I wouldn't give you a definitive no. And you wouldn't put it at zero? Bitcoin is too costly. It may be fine to hold it like gold, but gold is also costly. So you have smart people trying to make, say, Ether much more effective as a currency than Bitcoin. And there's certainly a decent chance they will succeed. Yeah, there's a lot of innovation. I mean, with smart contracts, with NFTs as well, there's a lot of interesting innovations that are plugging into the human psyche somehow, just like money does. Money seems to be this viral thing, our ideas of money. And if the idea is strong enough, it seems to be able to take hold. Like there's network effects that just take over. And I particularly see that with, I'd love to get your comment on Dogecoin, which is basically by a single human being, Elon Musk has been created. It's like these celebrities can have a huge ripple effect on the impact of money. Is it possible that in the 21st century, people like Elon Musk and celebrities, I don't know, Donald Trump, The Rock, whoever else, can actually define the currencies that we use? Can Dogecoin become the primary currency of the world? I think of it as like baseball cards. So right now, every baseball player has a baseball card. And the players who are stars, their cards can end up worth a fair amount of money. And that's stable, we've had it for many decades. And sort of the player defines the card, they sign a contract with Topps or whatever company. Now, could you imagine celebrities, baseball players, LeBron James, having their own currencies instead of cards? Absolutely, and you're somewhat seeing that right now, as you mentioned, artists with these unique works on the blockchain. But I'm not sure those are macro economically important. If it's just a new class of collectibles that people have fun with, again, I say bring it on. But whether there are use cases beyond that that challenge fiat monies, which actually work very well. Yesterday, I sent money to a family in Ethiopia that I helped support. In less than 24 hours, they got that money. Digitally, yes. No, not digitally, through my bank, my primitive dinosaur bank, BB&T, Mid-Atlantic Bank, headquartered in North Carolina, charted by the Fed, regulated by the FDAC and the OCC. Now, you could say, well, the exchange rate was not so great. I don't see crypto as close to beating that once you take into account all of the last mile problems. Fiat currency works really well. People are not sitting around bitching about it. And when you talk to crypto people, the number who have to postulate some out of the blue hyperinflation, where there's no evidence for that whatsoever, that to me is a sign they're not thinking clearly about how hard they have to work to out-compete fiat currency. There's a bunch of different technologies that are really exciting that don't want to address how difficult it is to out-compete the current accepted alternative. So, for example, autonomous vehicles. A lot of people are really excited. But it's not trivial to out-compete Uber on the cost and the effectiveness and the user experience and all those kinds of, sorry, Uber driven by humans. Yes, and it's not, that's taken for granted, I think. That look, wouldn't it be amazing, how amazing would the world look when the cars are driving themselves fully? You know, it's going to drive the cost down, you can remove the cost of drivers, all those kinds of things. But when you actually get down to it and have to build a business around it, it's actually very difficult to do. And I guess you're saying your sense is similar competition is facing cryptocurrency. Like you have to actually present a killer app reason to switch from fiat currency to Ethereum or to whatever. And the Biden people are going to regulate crypto and they're going to do it soon. So something like DeFi, I fully get why that is cheaper or for some can be cheaper than other ways of conducting financial intermediation. But some of that is regulatory arbitrage. It will not be allowed to go on forever, for better or worse. I would rather see it given greater tolerance. But the point is, banking lobby is strong, the government will only let it run so far. There'll be capital requirements, reporting requirements imposed, and it will lose a lot of those advantages. What do you make of Wall Street bets? Another thing that recently happened that shook the world, and at least me from the outsider perspective, make me question what I do and don't understand about our economic system. Which is a bunch of different, a large number of individuals getting together on the internet and having a large scale impact on the markets. If you tell a group of people and coordinate them through the internet, we're going to play a fun game, it might cost you money, but you're going to make the headlines and there's a chance you'll screw over some billionaires and hedge funds, enough people will play that game. So that game might continue, but I don't think it's of macroeconomic importance. And the price of those stocks in the medium term will end up wherever it ought to be. So these are little outliers from a macroeconomics perspective, they're not going to, these are not signals of a shifting power, like from centralized power to distributed power. These aren't some fundamental changes in the way our economy works. I think of it as a new brand of eSports, maybe more fun than the old brand, which is fine. It's like, push the anarchy into the corners where you want it. It doesn't bother me, but I think people are seeing it as more fundamental than it is. It's a new eSport, more fun for many, but more expensive than the old eSports. Like chess is a new eSport, super cheap, not as fun as like sending hedge funds to their doom, but like, what would you expect? The poetry of that, I love it, okay. But macroeconomically, it's not fundamental. Okay, I was gonna say, I hope you're right, because I'm uncomfortable with the chaos of the masses that's creates. But I also- I think that chaos is somewhat real, to be clear. Yes. But it will matter through other channels, not through manipulating GameStop or AMC. So you're seeing the real macro phenomenon. When people see a real macro phenomenon, they tend to make every micro story fit the narrative. And this micro story, like it fits the narrative, but it doesn't mean its importance fits the narrative. That's how I would kind of dissect the mistake I think people are making. Do you, within the macro phenomenon, there are there, do you mean- Everyone's weird now. The internet either allows us to be weirder or makes us weirder. I'm not sure what's the right way to put it. Maybe a mix of both. You're probably right that it allows us to be weirder because, well, this is the other, okay. So this connects our previous conversation. Does America allow us to be weirder or does it make us weirder? Like say we're weird and somewhat neurotic to begin with, but the only messages we get are Dwight D. Eisenhower and I Love Lucy and Network TV. Like that's gonna keep us within certain bounds in good and bad ways. That's obviously totally gone. And the internet you can connect to not just QAnon, but all sorts of things. Many of them just fantastic, right? But in good and bad ways, it makes us weirder. So that maybe is troubling, right? Like if someone's worried about that, I would at least say they should give it deep serious thought. And then it has a whole lot of ebbs and flows, micro realizations of the weirdness that don't actually matter. So like chess players today, they play a lot more weird openings than they did 20 years ago. Like it reflects the same thing because you can research any weird opening on the internet, but like, does that matter? Probably not. So a lot of the things we see are just like the weird chess openings. And to figure out which are like the weird chess openings and which are fundamental to the new and growing weirdness. Like that's what a hedge fund investor type should be trying to do. I just think no one knows yet. It's like this itself, this fun, weird guessing game, which we're partly engaging in right now. Exactly. And I mean, as Eric talks about on the science side of things, I mean, I said like at MIT, especially in the machine learning field, there's a natural institutional resistance to the weird. It's very, as they talk about, it's difficult to hire weird faculty, for example. Correct. You want to hire and give tenure to people that are safe, not weird. And that's one of the concerns is like, it seems like the weird people are the ones that push the science forward usually. Right. And so like, how do you balance the two? It's not obvious. It's another area where Eric and I disagree. As I interpret him, he thinks academia is totally bankrupt. Yeah. And I think it's only partially bankrupt. How do we fix it? Because I'm with you. I'm bullish on academia. You need up and coming schools that end up better than where they started off. And MIT was once one of them. Yes. Now they're not in every area. In some areas, they have become the problem. Yeah. UChicago, you wouldn't call it up and coming, but it's still different. And that's great. Let's hope they manage to keep it that way. The biggest problem to me is the rank absurd conformism at kind of second tier schools, maybe in the top 40, but not in the top dozen, that are just trying to be like a junior MIT, but it's mediocre and copycat. And they're the most dogmatic enforcers of weirdness that like Harvard is more open than those second tier schools. And those second tier schools are pretty good typically, right? Yeah. But the mediocrity is enforced there. Correct. Very strictly. And the homogenization pressures. Climb their rankings by another three places and be a little closer to MIT, though you'll never touch them. That to me is very harmful. And you'd rather they be more like Chicago, more like Caltech, or the older Caltech all the more. Like pick some model, be weird in it. You might fail, that's socially better. Yeah, but so the problem with MIT, for example, is the mediocrity is really enforced on the junior faculty. So like the people that are allowed to be weird, or actually they just don't even ask for permissions anymore are more senior faculty. And that's good, of course, but you want the weird young people. I find this podcast, I like talking to tech people, and I find the young faculty to be really boring. They are, they're the most boring of faculty. Their work is interesting technically, technically, but just the passion. They are drudges. And some of them sneak by. Like you have like the Max Tegmark, young version of Max Tegmark, who knows how to play the role of boring and fitting in. And then on the side, he does the weird shit. But they're not, they're far and few in between, which I'd love to figure out a way to shake up that system because I see. You look at MIT's Broad Institute, right, in biomedical, it's been a huge hit. I'm not privy to their internal doings, but I suspect they support weird more than the formal departments do at the junior level. Yes, that's probably true. Yeah, I don't know what, whatever they're doing is working, but we need to figure it out because I think the best ideas still do come from the, so forget my apologies, but for the humanities side of things, I don't know anything about. But the engineering and the science side, I think there's so many amazing ideas that are still coming from universities. It's not true that you don't know anything about the humanities. You're doing the humanities right now. We're talking about people. There are no numbers put on a blackboard, right? There's no hypothesis testing per se. No, yeah, that's not. You have however many subscribers to your podcast all listening to you on the humanities. Every, whatever your frequency is. But I'm not in the department of the humanities. That's why it's innovative. They have very different conversations. There's the number of emails I get about, listen, I really deeply respect diversity and the full scope of what diversity means and also the more narrow scope of different races and genders and so on. It's a really important topic. But there's a disproportionate number of emails I'm getting about meetings and discussions and that just kind of is overwhelming. I don't get enough emails from people, like a meeting about why are all your ideas bad? Let's, for example, let me call out MIT. Why don't we do more? Why don't we kick Stanford's ass or Google's ass, more importantly, in deep learning and machine learning and AI research? What CSAIL, for example, used to be a laboratory is a laboratory for artificial intelligence research. And why is that not the beacon of greatness in artificial intelligence? Let's have those meetings as well. Diversity talk has oddly become this new mechanism for enforcing conformity. Yes, exactly. And right, so it's almost like this conformity mechanism finds the hot new topic to use to enforce further conformity. Exactly. Oh boy, I still, I remain optimistic. Humanities have innovated through podcasts, including yours and mine's. Yeah. And they're alive and well. All the bad talk you hear about the humanities in universities, there's been this huge end run of innovation on the internet. Yeah. And it's amazing. You're right, I never thought of, I mean, this is humanities. This podcast, right? It's like I've been speaking prose all one's life and didn't know it, right? Yeah, I am actually part of the humanities department at MIT now. I did not realize this and I will fully embrace it from this moment on. Look, you have this thing, the Media Lab. I'm sure you know about it. Done some excellent things, done a lot of very bogus things. But you're out competing them. You're blowing them out of the water. Yeah. Like you are them. Yeah, and I'm talking to those folks and they're trying to figure it out. I mean, they had their issues with Jeffrey Epstein and so on, but outside of that, there's a, I've actually gone through a shift with this particular podcast, for example, where at first it was seen as a, one, at the very first it was seen as a distraction. Second, it was a source of like, almost like a kind of jealousy, like the same kind of jealousy you feel when junior faculty outshines the senior faculty. Of course. And now it's more like, oh, okay, this is a thing. Like, we should do more of that. We should embrace this guy. We should embrace this thing. So there's a sense that podcasting and whatever this is, it doesn't have to be podcasting, will drive some innovation within MIT, within different universities. There's a sense that things are changing. It's just that universities lag behind. And my hope is that they catch up quickly. They innovate in some way that goes along with the innovations of the internet. I think the internet will outrace them for a long time, maybe forever. Well, I mean, but it's okay if they're, as long as they're keeping- Yeah, and we're both in universities, so we have multiple hats on here as we're speaking. So we can complain about the universities, but that's like complaining about the podcast, right? Yeah. We be them. But speaking on the weird, in the best sense of the word weird, you've written about and made the case that we should take UFO sightings more seriously. So that's one of the things that I've been inundated with, sort of the excitement and the passion that people have for the possibility of extraterrestrial life, of life out there in the universe. I've always felt this excitement of just looking up at the stars and wondering what the hell's out there. But there's people that have more like, more grounded excitement and passion of actually interacting with aliens on this, here, our planet. What's the case, from your perspective, for taking these sightings more seriously? The data from the Navy, to me, seem quite serious. I don't pretend that I have the technical abilities to judge it as data, but there are numerous senators at the very highest of levels, former heads of CIA, Brennan. I talked to him, did an interview with him. I asked him, what's up with these? What do you think it is? He basically said that was the single most likely explanation was of alien origin. Now, you don't have to agree with him, but look, if you know how government works, these senators, or Hillary Clinton for that matter, or Brennan, they sat down, they were briefed by their smartest people, and they said, hey, what's going on here? And everyone around the table, I believe, is telling them, we don't know. And that is sociological data I take very seriously. I have not seen a debunking of the technical data, which is eyewitness reports and images and radar. Again, at a technical level, I feel quite uncertain on that turf. But evaluating the testimony of witnesses, it seems to me it's now at a threshold where one ought to take it seriously. Yeah, there's a, one of the problems with UFO sightings is that because of people with good equipment, don't take it seriously. It's such a taboo topic that you have just really shitty equipment collecting data. And so you have the blurry Bigfoot kind of situation where you have just bad video and all those kinds of things, as opposed to, I mean, there's a bunch of people, Avi Lo from Harvard talking about Amua Amua. It's just like people with the equipment to do the data collection don't want to help out. And that creates a kind of divide where the scientists ignore that this is happening, and there's the masses of people who are curious about it. And then there's the government that's full of secrets that's leaking some confusion, and it creates distrust in the government, it creates distrust in science, and it prevents the scientists from being able to explore some cool topics, some exciting possibilities that they should be, be curious kids like Avi talks about. Even if it has nothing to do with aliens, whatever the answer is, it has to be something fascinating. We already know everything's interesting, but this is fascinating. But look, that all said, I suspect they're not of alien origin. And just let me tell you my reason. The people who are all gung-ho, they do a kind of reasoning in reverse, or argument from elimination. They figure out a bunch of things that can't be, like is it a Russian advanced vehicle? No, probably pretty good arguments there. Is it a Chinese advanced vehicle? No. Is it people like from the Earth's future coming back in time? No. And they go through a few others. They have some really good no arguments. Then they're like, well, what we've got left is aliens. This argument from elimination, I don't actually find that persuasive. You can talk yourself into a lot of mistaken ideas that way. The positive evidence that it's aliens is still quite weak. The positive evidence that it's a puzzle is quite huge. And whatever the solution to the puzzle is, it might be fascinating. And it's gonna be so weird or fascinating, or maybe even trivial, but that's weird in its own way. That we can't set up by elimination all the things that might be able to be. Yeah, and just like you said, the debunking that I've seen of these kinds of things are less explorations and solutions to the puzzle, and more a kind of half-hearted dismissal. And Avi, as you mentioned to him on your podcast with him, he's been attacked an awful lot. And when I hear the idea carrier attacked, I get very suspicious of the critics. If he's wrong, just tell me why. My ears are open. I don't have a set view on Oumuamua. I know I can't judge Avi's arguments. He can't convince me in that sense. I'm too stupid to understand how good his argument may or may not be. And like you said, ultimately, in the argument, in the meeting of that debate is where we find the wisdom. Like dismissing it. That's one of the things that troubles me. There's a bunch of people, like Nietzsche sometimes dismissed this way, Ayn Rand is sometimes dismissed this way. Oh, here we go. Like there's a supposed to argue against her ideas, dismissing it outright. And that's not productive at all. She may be wrong in a lot of things, but like laying out some arguments, even if they're basic human arguments, that's where we arrive at the wisdom. I love that. Is there something deeper to be said about our trust in institutions and governments and so on that has to do with UFOs? That there's a kind of suspicion that the US government and governments in general are hiding stuff from us when you talk about UFOs. This is my view on that. If we declassified everything, I think we would find a lot more evidence all pointing toward the same puzzle. There aren't some alien men being held underground. There's not some secret file that lays out whatever is happening. I think the real lesson about government is government cannot bring itself to any new belief on this matter of any kind. And it's a kind of funny inertia. Like government is deeply puzzled. They're more puzzled than they want to admit to us, which like, I'm okay with that actually. They shouldn't just be out panicking people in the streets. But at the end of the day, it's a bit like approving the AstraZeneca vaccine, like which does work. And they haven't approved it. Like when are they gonna do it? Like when is our government actually, if only internally, gonna take this more than just seriously, but like take it truly seriously. And I just don't know if we have that capability kind of mentally to sound like Eric Weinstein for another moment. To stay on the same topic, although on the surface shifting completely, because it is all the same topic. You have written and studied art. Why do you think we humans long to create art? Human society in general and just the human mind? Well, most of us don't really long to create art, right? I would start with that point. You think so? You think that's a unique weirdness of some particular humans? I think, I don't know, 10% of humans roughly, which is a lot, but it is somewhat weird. I don't aspire to create art. You could say, like writing nonfiction, there's something art-like about it, but it's a different urge, I would say. So why do some people have it? I think human brains are very different. It's a different notion of working through a problem. Like you and I enjoy working through analytic problems. For me, economics, for you, AI and other areas, or your humanities podcast, but that's fun. For that problem to be visual and linked to physical materials and putting those on a canvas, to me, it's not a huge leap, but I really don't wanna do it. Like it would be pain, if you paid me like 500 bucks to spend an hour painting, I don't know, is that worth it? Maybe, but I'm happy when that hour's over. And would not be proud or happy with the result. It would suck. I don't think I would do it, actually. Do you think you're suppressing some deep, I mean- Absolutely not. When I was young, I played the guitar, as you played the guitar, and that I greatly enjoyed, although I was never good. But it helped me appreciate music much, much more. Well, this is the question, okay, so from the perspective of the observer and appreciator of art, you said good. Is there such a concept as good in art? There's clearly a concept of bad. My guitar playing fit that concept. Okay. But I wasn't trying to be good. I wanted to learn like how do chords work? Okay, analytical. How does a jazz improvisation work? How is blues different? Classical guitar, sort of physically, how do you make those sounds? Yes. And I did learn those things, and you can't learn everything about them, but you can learn a lot about them without ever being good, or even trying to be that good. But I could play all the notes. So from the observer perspective, what do you, I apologize for the absurd question, but what do you use the most beautiful and maybe moving piece of art you've encountered in your life? It's not an absurd question at all. And I think about this quite a bit. I would say the two winners by a clear margin are both by Michelangelo. It's the Pieta in the Vatican, and the David statue in Florence. Why? Historical context or just purity, the creation itself? I don't think you can view it apart from historical context, and being in Florence or in the Vatican, is that you're already primed for a lot, right? You can't pull that out. But just technically how they express the emotion of human form, I do honestly intellectually think they're the two greatest artworks for doing that. That's not all that art does. Not all art is about the human form, but they are phenomenal. And I think critical opinion, not that everyone agrees, but my view is not considered a crazy one within the broader court of critical opinion. Now in painting, I think the most I was ever blown away was to see Vermeer's artwork. It's called the Art of Painting, and it's in Vienna in the Kunsthistorisches Museum. And I saw that, I think I was 23. It just stunned me because I'd seen reproductions, but live in front of you in huge, a completely different artwork. And again, Vienna, primed. Yes. And I was living abroad for the first time, and Vienna itself, the city and so on. Now, unlike the Michelangelo's, that is not my current favorite painting, but that would be like historically the one I would pick. What do you make in the context of those choices? What do you make of modern art? And I apologize if I'm not using the correct terminology, but art that maybe goes another level of weird outside of the art that you've kind of mentioned, and breaks all the conventions and rules and so on, and becomes something else entirely that doesn't make sense in the same way that David might. I think a lot of it is phenomenal. And I would say the single biggest mistake that really smart people make is to think contemporary art, or music for that matter, is just a load of junk or rubbish. It's just like a kind of mathematics they haven't learned yet. It's really hard to learn. Maybe some people can never learn it, but there's a very large community of super smart, well-educated people who spend their lives with it, who love it. Those are genuine pleasures. They understand it. They talk about it with the common language. And to think that somehow they're all frauds, it just isn't true. Like one doesn't have to like it oneself, just like Cloth House may or may not be your thing, but it is amazing, and for me personally, highly rewarding. And if someone doesn't get it, I do kind of have the conceited response of thinking, like in that area, I'm just smarter than you are. Yeah, so the interesting thing is, as with most- We get back to Eric Weinstein again. Yes. Who is in general smarter than I am. This I get. But when it comes to contemporary artistic creations, I'm smarter than he is. So he's not a fan of contemporary art? I don't want to speak for him. I've heard him say derogatory- He's evolving always. He's evolving always. I've heard him say derogatory things about some of it. Doesn't mean he doesn't love some other parts of it. So I wonder if there's just a higher learning curve, a steeper learning curve for contemporary art, meaning like it takes more work to appreciate the stories, the context from which they're like thinking about this work. It feels like in order to appreciate the art, a certain piece of contemporary art, you have to know the story better behind the art. I think that's true for many people, but I think it's a funny-shaped distribution because there's a whole other set of people, sometimes just small children, and they get abstract art more easily. You show them Vermeer or Rembrandt, they don't get it. But just like a wall of color, they're in love with it. So I don't think I know the full story. Again, some strange kind of distribution, the entry barriers are super high or super low, but not that often in between. But you would challenge saying that there's a lot to be explored in contemporary art, it's just you need to learn. Yeah, it's one of the most profound bodies of human thought out there, and it's part of the humanities. And yes, there are people who also don't like podcasts, right? And that's fine. Yeah, you've also been a scholar of food. We're just going through the entirety of the human experience today on this humanities podcast. Another absurd question, say this conversation is the last thing you ever do in your life. I, wearing this suit, would murder you at the end of the conversation, so this is your last day on Earth, but I would offer you a last meal. What would that meal contain? We can also travel to other parts of the world. Well, we have to travel because my preferred last meal here, I probably had like two nights ago. Which is what, can you describe it? The best restaurant around here is called Mama Chang's, and it's in Fairfax, and it's food from Wuhan, actually. And they take pandemic safety seriously, in addition to the food being very good. But this is what I would do. I would fly to Hermosillo in Northern Mexico, which has some of the best food in Mexico, but I sadly only had two days there. So somewhere like Oaxaca, Puebla, I think they have food just as good, or some people would say better, but I've spent a lot of time in those places. So the scarce, wait, is it possible the scarcity of time contributed to the richness of the experience? Of course, but the point is that scarcity still holds. So I want one more dose of the food from Hermosillo. Can you describe what the food is? It's the one kind of Mexican food that, at least nominally, is just like the Mexican food you get in the US. So there are burritos, there's fajitas. It doesn't taste at all like our stuff. But again, nominally, it's the part of Mexican food that made it into the US, was then transformed. But it's in a way the most familiar, but for that reason, it's the most radical, because you have to rethink all these things you know, and they're way better in Hermosillo. Hardly any tourists go there. Like, there's nothing to see in Hermosillo. Nothing you do other than eat. It's not ruined by any outsiders. It's this longstanding tradition. Dirt cheap, and the thing to do there is just sweet talk a taxi driver into first taking you seriously, and then trusting you enough to know that you trust him to bring you to the very best, like food stands. So where's the magic of that nominally similar entity of the burrito? Where's the magic come from? Is it the taxi ride? Is it the whole experience? Or is there something actually in the food? So well, you can break the food down part by part. So if you think of the beef, the beef there will be dry aged just out in the air. In a way the FDA here would never permit. Like they dry age it till it turns green, but it is phenomenal. The quality of the chilies. So here there's only a small number of kinds of chilies you can get. In most parts of Mexico, there's quite a large number of chilies you can get. They're different, they're fresher, but it's just like a different thing, the chilies. The wheat used, so this is wheat territory, not corn territory, which is itself interesting. The wheat is more diverse and more complex. Here it's more homogenized, obviously cheaper, more efficient, but there it is better. Non-pasteurized cheeses are legal in all parts of Mexico, and they can be white and gooey and amazing in a way that here, again, it's just against the law. You could legalize them, the demand wouldn't be that great. There's a black market in these cheeses at Latino groceries around here, but you just can't get that much of it. So the cheese, the meat, the wheat, all different in significant ways. The chilies, I don't think the onions really matter much. Garlic, I don't know, I wouldn't put much stock in that. But that's a lot of the core food, and then it's cooked much better, and everything's super fresh. The food chain is not relying on refrigeration, and this is one thing Russia and US have in common. We were early pioneers in food refrigeration, and that made a lot of our foods worse quite early, and it took us a long time to dig out of that, because big countries, right? You've had an extensive rail system in Russia, USSR, a long time, which makes it easier to freeze and then ship. What about the actual cooking, the chef? Is there an artistry to the simple, I hesitate to call the burrito simple, but. And there's no brain drain out of cooking. So if you're in the United States, and you're very talented, I'm not saying there aren't talented chefs, of course there are, but there's so many other things to pull people away. But in Mexico, there's so much talent going into food, as there is in China, which would be another candidate for last meal questions. Or India. Or, well, India, let's not even get started on India. Unbelievable. But you've also, I mean, there's a million things we could talk about here, but you've written about your dreams of sushi. This is just a really clean, good example that people are aware of, of mastery in the art of the simple in food. What do you make of that kind of obsessive pursuit of perfection in creating simple food? Sushi is about perfection, but it's a bit like the Beatles' White Album, which people think is simple and not overproduced. It's in a funny way, their most overproduced album, but it's produced just perfectly. It sounds simple. It's really hard to produce music to the point where it's going to sound so simple and not sound like sludge. Like Let It Be album, has some great songs, but a lot of it sounds like sludge. One After 909, that's sludge. I Dig a Pony, it's sludge. Like It's a Bit Interesting. It's not that good, it doesn't sound that good. White Album, like the best half, like Dear Prudence. Sounds perfect, sounds simple. Cry Baby Cry. It's not simple, back in the USSR. Super complex. So sushi is like that. It's because it's so incredibly not simple, starting with the rice. You try to refine it to make it appear super simple, and that's the most complex thing of all. So do you admire, I mean, we're not talking about days, weeks, months. We're talking about years, generations, of doing the same thing over and over and over again. Do you admire that kind of sticking to the, does that, you know, we talked about our admiration of the weird. That doesn't feel weird. That seems like discipline and dedication to like a stoic minimalism or something like that. I'm happy they do it, but I actually feel bad about it. I feel they're sacrificial victims to me, which I benefit from. But don't you ever think like, gee, you're a great master sushi chef. Wouldn't you be happier if you did something else? Doesn't seem to happen. That might be something that a weird mind would think. Maybe it is weird people, and maybe they're really enjoying it. But like to learn how to pack rice for 10 years before they let you do anything else. It's like these Indian, you know, sarod players. They just spent five years tapping at rhythms before they're allowed to touch their instruments. Well, actually to defend that. It's kind of like graduate school, right? Well, I think graduate school, perhaps. Graduate school is full of, like every single day is full of surprises, I would say. I did martial arts for a long time, do martial arts. And I've always loved, it's kind of the Russian way of drilling, is doing the same technique. I don't know if this applies into intellectual or academic disciplines, where you can do the same thing over and over and over again, thousands and thousands and thousands of times. What I've discovered through that process is you get to start to appreciate the tiniest of details and find the beauty in them. People who go to like monasteries to meditate talk about this, is when you just sit in silence and don't do anything, you start to appreciate how much complexity and beauty there is in just a movement of a finger. Like you can spend the whole day joyously thinking about how fun it is to move a finger. Yeah. And so, and then you can almost become your full weird self about the tiniest details of life. As a thing you've got to wonder, like, is there a free lunch in there? Are the rest of us moving around too much? Yeah, exactly. That's like, they sure feel like they found a free lunch. The people meditate, they're onto something. I tend to think it's like artists that some percent of people are like that, but most are not. And for most of us, there's no free lunch. Like my free lunch is to move around a lot in search of lunch, in fact. Well, with all the food talk, you made me hungry. What books, three or so books, if any come to mind, technical fiction, philosophical, would you recommend had a big impact on you or you just drew some insights from throughout your life? Well, two of them we've already discussed. One is Plato's Dialogues, which I started reading when I was like 13. Another is Ayn Rand, Capitalism, the Unknown Ideal. But I would say the Friedrich Hayek essay, The Use of Knowledge in Society, which is about how decentralized mechanisms can work, also why they might go wrong. And that's where you start to understand the price system, capitalism. And that was in a book called Individualism and Economic Order, but it was just a few essays in that book. Those are maybe the three I would say. Can you elaborate a little bit on the- Say the price of copper goes up, right? Because there's a problem with a copper mine in Chile or Bolivia. So the price of copper goes up all around the world. People are led to economize copper, to look for substitutes for copper, to change their production processes, to change the goods and services they buy, to build homes a different way. And this one event creates this one tiny change in information, it gets into your AI work very directly. And how much complexity that one change engenders in a meaningful, coherent way, how the different pieces of the price system fit together. Hayek really laid out very clearly. And it's like an AI problem. And how well, not for everything, but for many things, we solve that AI problem. I learned, I was I think 13, maybe 14 when I read Hayek. The distributed nature of things there. And it's like your work on human attention, like how much can we take in? Yes. Very often not that much. And how many of the advances of modern civilization you need to understand as a response to that constraint. I got that also from Hayek. What's the title of the book again? It's reprinted in a lot of books at this point. But back then the book was called ''Individualism and Economic Order.'' But the essay is online, ''Hayek, Use of Knowledge in Society.'' There are open access versions of it through Google. And you don't need the whole book. So it's a very good book. Again, one of those profound looking over the ocean, maybe sitting on a porch, maybe with a drink of some kind. And a young kid comes by and asks you for advice. What advice would you give to- A drink, that's my advice. I'm serious. So, okay, after that, what advice would you give to a young person today as they take on life? Whether career and academia in general, or just a life, which is probably more important than career. Most good advice is context specific, but here are my two generic pieces of advice. Good. First, get a mentor. Both career, but anything you wanna learn. Like say you wanna learn about contemporary art. People write me this, what book should I read? It's probably not gonna work that way. You need a mentor. Yes, you should read some books on it, but you want a mentor to help you frame them, take you around to some art, talk about it with you. So get as many mentors as you can in the things you wanna learn. And then- Can I ask you a quick tangent on that? Presumably a good mentor. Of course. I'm not begging the question in there. It's complicated, right? Well, it is complicated. Is there a lot of damage to be done from a bad mentor? I don't think that much, because it's very easy to drop mentors, and in fact, it's quite hard to maintain them. Good mentors tend to be busy. Bad mentors tend to be busy. And you can try on mentors, and maybe they're not good for you, but you still, there's a good chance you'll learn something. Like I had a mentor, I was an undergrad. He was a Stalinist. He edited the book called The Essential Stalin. Brilliant guy. I learned a tremendous amount from him. Was he like as a Stalinist a good mentor for me, fan of Hayek? Well, no, but for a year, it was tremendous. Yeah. He introduced me like to Soviet and Eastern European science fiction, because he was a Marxist. Like that's what I took from him, among other things. Any advice on finding a good mentor? Daniel Kahneman, as somebody just popped this to mind, as somebody who was able to find exceptionally good collaborators throughout his life, there's not many bright minds that find collaborators. They often, which I ultimately see what a mentor is. Yeah. Be interesting, be direct, and try. It's not like a perfect formula, but it's amazing how many people don't even do those things. Be interesting, be direct, and try. Like what you want from a better known person. I would just say be very direct with them. Yeah. Beautiful. What's the second piece of advice? Build small groups of peers. They don't have to be your age, but very often they'll be your age, especially if you're younger, with broadly similar interests, but there can be different points of view. People you hang out with, which can include in a WhatsApp group online, and like every day or almost every day, they're talking about the thing you care about, trying to solve problems in that thing. And that's your small group, and you really like them, and they like you, and you care what you think about each other, and you have this common interest. That's for human connection, or that's for development of ideas? It's both, they're not that different. Like Beatles, classic small group, right? But there's so much drama. The Florentine artists, of course there's drama, and small groups tend to split up, which is fine, just like entering relationships often end. But it's remarkable how little has been done that was not done in small groups in some way. So speaking of loss, of beautiful relationships, where do you make this whole love thing? Why do humans fall in love? What's the role of love, friendship, family in life? In a successful life, or just life in general? Why the hell are we so into this thing? There are multiple layers of understanding that question. So kind of the lowest layer is the Darwinian answer. Right, if we weren't this way, we wouldn't have been successful in reproducing and building alliances. It's important to realize that's far from complete. Sort of the highest understanding would be poetic, like read John Keats or many other love poets. So who do I go to to learn about love in terms of poets? I would say start with John Keats. But given that you're fluent in Russian. Yeah, let's go Russian literature for a second. You keep mentioning Russia. What's your connection, what's your love in Russia? Well, first, it's all interesting. But more concretely, my wife was born in Moscow. Sokolniki was her neighborhood. Yeah. And she grew up there. I married her here. My daughter, I adopted her. I'm not her biological father, but I genuinely raised her. She was born in Russia, though she came here when she was one. My father- So you're basically Russian. No, no, no, I'm a New Jersey boy. That's the same thing. I'm very sorry to report, my father-in-law passed away a week ago. He lived with us for six years. He lived in Russia till he was, oh, 70. Saw, you know, the Stalinist era. His father was brought to a camp, lived through World War II, much, much more. Had an incredible life. Never really learned how to speak English. So I absorbed something Russian from him as well. He was part Armenian. So that's my connection to Russia. A bit of the Russian soul, too. I don't think I have it. I think I appreciate it. But there's division of labor, right? Others in the family take care of that. I'm more superficial. You mentioned Keats and that higher version, that non-Darwinian love. What's that about? That it's the highest form of human connection, and it's intoxicating, and it's part of building a life, and most of us are very, very strongly drawn to it. And it's part of the highest realization of you being what you can be. Yeah. He mentioned you lost. But ask a Russian. I mean, this is superficial New Jersey boy who grew up listening to Bruce Springsteen. And that was his romanticism. What's your favorite Bruce Springsteen song? I think the album Born to Run has actually held up the best. Though it's very fashionable to think the earlier or later works are actually better, and that's the overproduced super pop album. But the quality of the songs, to me, Born to Run is just far and away the best, then Darkness on the Edge of Town. And those are still my favorites. Born to Run is an incredible song. And perfectly produced in a Phil Spector kind of way. Every detail is right, every lyric. What else is on the album? Thunder Road, Jungle Land, 10th Avenue Freeze Out. She's the one, unbelievable. Yeah, Bruce is the name. Meeting Across the River. I really like, I like when he goes into love, personally. Like I'm on Fire. That's a very good song, Dancing in the Dark. A lot of the later work, I find the percussion becomes too simple and kind of too white somehow, and a little clunky. And it's still good work. He's super talented, but it doesn't speak to me. But when it all bursts open into the open road, like it does on Born to Run, that's magic. Yeah. Or Rosalita. Have you ever seen him live? Is it, yes, twice. I wonder what he's like live when he was young, right? Those years. I saw him live when he was young. I was young. New Jersey. I was a little disappointed, actually. Yeah? I think what I like best from him is quite studio. He certainly played well. I don't fault his performance. But it's like when I saw Plant and Page, you know, of Led Zeppelin. Tremendous creators. And they showed up. They were not drunk. Like, they were paying attention. But I was underwhelmed, because Led Zeppelin, like the Beatles' White Album, is much more of a studio band than you think at first. And in the case of Bruce Springsteen, I don't know about you, but for me, he's somebody that I connect with the most when I'm alone and there's like a melancholy feeling. And actually, my folks live in Philly. I went to school in Philly. And so, you know, I've... You're almost worthy of New Jersey, then. Yeah, well, you're almost worthy of Russia. So we can connect in that aspect. I mean, I love Jersey. It's something I feel like, I feel like, I don't know. It always, there's this beautiful, like there's a Olga's Diner that closed down. I used to go there. There's a melancholy feeling to me. I mean, of course. A thickness to culture in that part of the world, which is oddly similar to some elements of the thickness of Russian culture. And when you see like Russian characters on The Sopranos, it totally makes sense, even though there are these complete outliers. Exactly, it totally makes sense. You've, you mentioned you lost your father-in-law last week. Do you think about mortality? Do you think about your own mortality? Are you afraid of death? I don't think about my own mortality that much, which is probably a good thing. I think death will be bad. I wouldn't say I'm afraid of it. For me, the worst thing about death is not knowing how the human story turns out. The full human story. The full human story. So if I could, right before I die, read like a Wikipedia page called The Rest of Human History, and have enough time, just like a few days to absorb it, think about it, and know like, oh, well, 643 years from now, that's when all the atomic weapons went off, and here's what happened between now and then. I would feel much better dying. But that's not how it's gonna be, right? That's unlikely. It's almost like The Hitchhiker's Guide. They kind of have, what is it? They have a one or two sentence description of the human, of what goes on on Earth. It's kind of interesting to think if there's a lot of intelligent civilizations out there, that in the big encyclopedia that describes the universe, humans will only have one sentence, maybe two. Probably true. Yeah. It's the only one I can read and understand, right? And it may be hard to understand the human one past a number of centuries. Yeah, with AI, yes. Like how many years from now will reading Wikipedia be like trying to read Chaucer? Which I almost can do, but I actually can't. I need a translation. Probably you can't do it at all. Yeah. I mean, maybe reading will be outdated. It might be a very silly notion. Maybe we're fundamentally, like we think language is fundamental to cognition, but it could be something visual or something totally different that we'll plug in. Neural anchor, yeah. But in that story, that Wikipedia article, do you think there'll be a section on the meaning of it? I hope not. Because that section we could write now, and it's just not gonna be very good, right? What would you put in the section on the meaning of human existence? I don't know, links to a lot of other sections? I don't think there are general statements about the meaning of life that have that much meaning. I think if you study different cultures, the arts, travel, mathematics, like whatever your thing is, you'll get a lot about the meaning of life. So like it's there in Wikipedia in some bigger sense. But I don't wanna read the page on the meaning. I bet they have such a page, in fact. The fact that I've never visited it, none of my friends, oh, Tyler, here's the page on the meaning of life. I know you've been wondering about this. You gotta read this one. No one's ever done that to you, have they? It probably has. Well, I actually gone to that page. It does in fact have a lot of links to other pages. Okay. So that's it. The meaning of life is just a bunch of self-referential or citation needed type of statements. I think there's no better way to end it. Tyler, this is a huge honor. I'm a huge fan. Thank you so much for wasting all of this time with me. It was one of the greatest conversations I've ever had. Thank you so much. My pleasure and delighted to finally have met you and that we can do this. Thanks for listening to this conversation with Tyler Cohen and thank you to Linode, ExpressVPN, Simply Safe and Public Goods. Check them out in the description to support this podcast. And now let me leave you with some words from Adam Smith. "'Little else is requisite to carry a state "'to the highest degree of opulence "'from the lowest barbarism, but peace, easy taxes, "'and a tolerable administration of justice.'" Thank you for listening and hope to see you next time.

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Nick Bostrom: Simulation and Superintelligence | Lex Fridman Podcast #83

The following is a conversation with Nick Bostrom, a philosopher at University of Oxford and the director of the Future of Humanity Institute. He has worked on fascinating and important ideas in existential risk, simulation hypothesis, human enhancement ethics, and the risks of superintelligent AI systems, including in his book, Superintelligence. I can see talking to Nick multiple times in this podcast, many hours each time, because he has done some incredible work in artificial intelligence, in technology space, science, and really philosophy in general. But we have to start somewhere. This conversation was recorded before the outbreak of the coronavirus pandemic, that both Nick and I, I'm sure, will have a lot to say about next time we speak. And perhaps that is for the best, because the deepest lessons can be learned only in retrospect, when the storm has passed. I do recommend you read many of his papers on the topic of existential risk, including the technical report titled Global Catastrophic Risks Survey that he co-authored with Anders Sandberg. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do one or two minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market, making trading more accessible for new investors and diversification much easier. So again, if you get Cash App from the App Store, Google Play, and use the code LEXPODCAST, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Nick Bostrom. At the risk of asking the Beatles to play yesterday or the Rolling Stones to play Satisfaction, let me ask you the basics. What is the simulation hypothesis? That we are living in a computer simulation. What is a computer simulation? How are we supposed to even think about that? Well, so the hypothesis is meant to be understood in a literal sense, not that we can kind of metaphorically view the universe as an information processing physical system, but that there is some advanced civilization who built a lot of computers, and that what we experience is an effect of what's going on inside one of those computers, so that the world around us, our own brains, everything we see and perceive and think and feel, would exist because we are in a computer simulation. This computer is running certain programs. So do you think of this computer as something similar to the computers of today, these deterministic, sort of Turing machine type things? Is that what we're supposed to imagine, or are we supposed to think of something more like a quantum mechanical system, something much bigger, something much more complicated, something much more mysterious from our current perspectives? The ones we have today would do fine. I mean, bigger, certainly. You'd need more memory and more processing power. I don't think anything else would be required. Now, it might well be that they do have additional, maybe they have quantum computers and other things that would give them even more oomph. It's kind of plausible, but I don't think it's a necessary assumption in order to get to the conclusion that a technologically mature civilization would be able to create these kinds of computer simulations with conscious beings inside them. So do you think the simulation hypothesis is an idea that's most useful in philosophy, computer science, physics? Sort of where do you see it having valuable kind of starting point in terms of a thought experiment of it? Is it useful? I guess it's more informative and interesting and maybe important, but it's not designed to be useful for something else. Okay, interesting, sure. But is it philosophically interesting or is there some kind of implications of computer science and physics? I think not so much for computer science or physics per se. Certainly it would be of interest in philosophy, I think also to say cosmology or physics in as much as you're interested in the fundamental building blocks of the world and the rules that govern it. If we are in a simulation, there is then the possibility that say physics at the level where the computer running the simulation could be different from the physics governing phenomena in the simulation. So I think it might be interesting from point of view of religion or just for kind of trying to figure out what the heck is going on. So we mentioned the simulation hypothesis so far. There is also the simulation argument, which I tend to make a distinction. So simulation hypothesis, we are living in a computer simulation argument. This argument that tries to show that one of three propositions is true, one of which is the simulation hypothesis, but there are two alternatives in the original simulation argument, which we can get to. Yeah, let's go there. By the way, confusing terms because people will, I think probably naturally think simulation argument equals simulation hypothesis, just terminology wise, but let's go there. So simulation hypothesis means that we are living in a simulation. The hypothesis that we're living in a simulation, argument has these three complete possibilities that cover all possibilities. So what are they? Yeah, so it's like a disjunction. It says at least one of these three is true. Although it doesn't on its own tell us which one. So the first one is that almost all civilizations at our current stage of technological development go extinct before they reach technological maturity. So there is some great filter that makes it so that basically none of the civilizations throughout, I mean, maybe vast cosmos, will ever get to realize the full potential of technological development. And this could be, theoretically speaking, this could be because most civilizations kill themselves too eagerly or destroy themselves too eagerly, or it might be super difficult to build a simulation. So the span of time. Theoretically, it could be both. Now, I think it looks like we would technologically be able to get there in a time span that is short compared to, say, the lifetime of planets and other sort of astronomical processes. So your intuition is to build a simulation is not... Well, so there's this interesting concept of technological maturity. It's kind of an interesting concept to have for other purposes as well. We can see, even based on our current limited understanding, what some lower bound would be on the capabilities that you could realize by just developing technologies that we already see are possible. So, for example, one of my research fellows here, Eric Drexler, back in the 80s, studied molecular manufacturing. That is, you could analyze using theoretical tools and computer modeling the performance of various molecularly precise structures that we didn't then and still don't today have the ability to actually fabricate. But you could say that, well, if we could put these atoms together in this way, then the system would be stable and it would rotate at this speed and have these computational characteristics. And he also outlined some pathways that would enable us to get to this kind of molecularly manufacturing in the fullness of time. And you could do other studies we've done. You could look at the speed at which, say, it would be possible to colonize the galaxy if you had mature technology. We have an upper limit, which is the speed of light. We have a lower current limit, which is how fast current rockets go. We know we can go faster than that by just making them bigger and have more fuel and stuff. And you can then start to describe the technological affordances that would exist once a civilization has had enough time to develop at least those technologies we already know are possible. Then maybe they would discover other new physical phenomena as well that we haven't realized that would enable them to do even more. But at least there is this kind of basic set of capabilities. Can you just linger on that? How do we jump from molecular manufacturing to deep space exploration to mature technology? What's the connection there? Well, so these would be two examples of technological capability sets that we can have a high degree of confidence are physically possible in our universe and that a civilization that was allowed to continue to develop its science and technology would eventually attain. You can intuit, like, we can kind of see the set of breakthroughs that are likely to happen. So you can see, like, what did you call it, the technological set? With computers, maybe it's easier. One is we could just imagine bigger computers using exactly the same parts that we have, so you can kind of scale things that way, right? But you could also make processors a bit faster. If you had this molecular nanotechnology that Eric Drexler described, he characterized a kind of crude computer built with these parts that would perform at a million times the human brain while being significantly smaller, the size of a sugar cube. And he may not claim that that's the optimum computing structure, like for what you know, you could build faster computers that would be more efficient, but at least you could do that if you had the ability to do things that were atomically precise. Yes. I mean, so you can then combine these two. You could have this kind of nanomolecular ability to build things atom by atom and then say at this as a spatial scale that would be attainable through space colonizing technology. You could then start, for example, to characterize a lower bound on the amount of computing power that a technologically mature civilization would have if it could grab resources, you know, planets and so forth and then use this molecular nanotechnology to optimize them for computing. You'd get a very, very high lower bound on the amount of compute. So, sorry, just to define some terms. So, technologically mature civilization is one that took that piece of technology to its lower bound. What is a technologically mature civilization? Well, okay, so that means it's a stronger concept than we really need for the simulation hypothesis. I just think it's interesting in its own right. So, it would be the idea that there is some stage of technological development where you've basically maxed out, that you developed all those general purpose, widely useful technologies that could be developed or at least kind of come very close to the 99.9% there or something. So, that's an independent question. You can think either that there is such a ceiling or you might think it just goes, the technology tree just goes on forever. Where does your sense fall? I would guess that there is a maximum that you would start to asymptote towards. So, new things won't keep springing up, new ceilings. In terms of basic technological capabilities, I think there is like a finite set of those that can exist in this universe. Moreover, I mean, I wouldn't be that surprised if we actually reached close to that level fairly shortly after we have, say, machine super intelligence. So, I don't think it would take millions of years for a human originating civilization to begin to do this. I think it's more likely to happen on historical timescales. But that's an independent speculation from the simulation argument. I mean, for the purpose of the simulation argument, it doesn't really matter whether it goes indefinitely far up or whether there is a ceiling, as long as we know we can at least get to a certain level. And it also doesn't matter whether that's going to happen in 100 years or 5,000 years or 50 million years. The timescales really don't make any difference for the simulation. Can you linger on that a little bit? Like, there's a big difference between 100 years and 10 million years. Yeah. So, does it really not matter? Because you just said, does it matter if we jump scales to beyond historical scales? So, will you describe that? For the simulation argument, doesn't it matter that if it takes 10 million years, it gives us a lot more opportunity to destroy civilization in the meantime? Yeah, well, so it would shift around the probabilities between these three alternatives. That is, if we are very, very far away from being able to create these simulations, if it's like, say, billions of years into the future, then it's more likely that we will fail ever to get there. There's more time for us to kind of go extinct along the way. And similarly for other civilizations. So, it is important to think about how hard it is to build a simulation. In terms of figuring out which of the disjuncts. But for the simulation argument itself, which is agnostic as to which of these three alternatives is true. Yeah, yeah, okay. Like, you don't have to... Like, the simulation argument would be true whether or not we thought this could be done in 500 years or it would take 500 million years. For sure. The simulation argument stands. I mean, I'm sure there might be some people who oppose it, but it doesn't matter. I mean, it's very nice those three cases cover it. But the fun part is at least not saying what the probabilities are, but kind of thinking about, kind of intuiting reasoning about, like, what's more likely, what are the kind of things that would make some of the arguments less and more so. But let's actually, I don't think we went through them. So, number one is we destroy ourselves before we ever create simulation. Right. So, that's kind of sad, but we have to think not just what might destroy us. I mean, so there could be some, whatever, disaster, some meteorite slamming the earth a few years from now that could destroy us, right? But you'd have to postulate in order for this first disjunct to be true, that almost all civilizations throughout the cosmos also failed to reach technological maturity. And the underlying assumption there is that there is likely a very large number of other intelligent civilizations. Well, if there are, yeah, then they would virtually all have to succumb in the same way. I mean, then that leads off another, I guess there are a lot of little digressions that are interesting. Let's go there. Let's go there. I'll keep dragging us back. Well, there are these, there is a set of basic questions that always come up in conversations with interesting people, like the Fermi paradox. Like there's like, you could almost define whether a person is interesting, whether at some point the question of the Fermi paradox comes up. Well, so for what it's worth, it looks to me that the universe is very big. I mean, in fact, according to the most popular current cosmological theories, infinitely big. And so then it would follow pretty trivially that it would contain a lot of other civilizations. In fact, infinitely many. If you have some local stochasticity and infinitely many, it's like, you know, infinitely many lumps of matter, one next to another, there's kind of random stuff in each one. Then you're going to get all possible outcomes with probability one infinitely repeated. So then certainly there would be a lot of extraterrestrials out there. Even short of that, if the universe is very big, there might be a finite but large number. If we were literally the only one, yeah, then of course, if we went extinct, then all of civilizations at our current stage would have gone extinct before becoming technological material. So then it kind of becomes trivially true that a very high fraction of those went extinct. But if we think there are many, I mean, it's interesting because there are certain things that possibly could kill us. Like if you look at existential risks. And it might be a different, like the best answer to what would be most likely to kill us might be a different answer than the best answer to the question, if there is something that kills almost everyone, what would that be? Because that would have to be some risk factor that was kind of uniform overall possible civilization. So in this, for the sake of this argument, you have to think about not just us, but like every civilization dies out before they create the simulation. Or something very close to everybody. Okay, so what's number two in the picture? Well, so number two is the convergence hypothesis. That is that maybe like a lot of some of these civilizations do make it through to technological maturity. But out of those who do get there, they all lose interest in creating these simulations. They have the capability of doing it, but they choose not to. Not just a few of them decide not to, but out of a million, maybe not even a single one of them would do it. And I think when you say lose interest, that sounds like unlikely because it's like they get bored or whatever. But it could be so many possibilities within that. I mean, losing interest could be anything from it being exceptionally difficult to do to fundamentally changing the sort of the fabric of reality if you do it, ethical concerns, all those kinds of things could be exceptionally strong pressures. Well, certainly, I mean, yeah, ethical concerns. I mean, not really too difficult to do. In a sense, that's the first option that you get to technological maturity where you would have the ability using only a tiny fraction of your resources to create many, many simulations. So it wouldn't be the case that they would need to spend half of their GDP forever in order to create one simulation. And they had this like difficult debate about whether they should invest half of their GDP for this. And they would more be like, well, if any little fraction of the civilization feels like doing this at any point during maybe their, you know, millions of years of existence, then that would be millions of simulations. But certainly, there could be many conceivable reasons for why there would be this convert, many possible reasons for not running ancestor simulations or other computer simulations, even if you could do so cheaply. What's an ancestor simulation? Well, that would be the type of computer simulation that would contain people like those we think have lived on our planet in the past and like ourselves in terms of the types of experiences they have and where those simulated people are conscious. So like not just simulated in the same sense that a non-player character would be simulated in the current computer game where it's kind of has like an avatar body and then a very simple mechanism that moves it forward or backwards or, but something where the simulated being has a brain, let's say, that's simulated at a sufficient level of granularity that it would have the same subjective experiences as we have. So where does consciousness fit into this? Do you think simulation, like is there different ways to think about how this can be simulated? Just like you're talking about now, do we have to simulate each brain within the larger simulation? Is it enough to simulate just the brain, just the minds and not the simulation, not the big universe itself? Like is there different ways to think about this? Yeah, I guess there is a kind of premise in the simulation argument rolled in from philosophy of mind. That is that it would be possible to create a conscious mind in a computer and that what determines whether some system is conscious or not is not like whether it's built from organic biological neurons, but maybe something like what the structure of the computation is that it implements. So we can discuss that if we want, but I think it would be, for as far as my view, that it would be sufficient, say, if you had a computation that was identical to the computation in the human brain down to the level of neurons. So if you had a simulation with 100 billion neurons connected in the same way as the human brain and you then roll that forward with the same kind of synaptic weights and so forth, so you actually had the same behavior coming out of this as a human with that brain would have, then I think that would be conscious. Now, it's possible you could also generate consciousness without having that detailed simulation. There I'm getting more uncertain exactly how much you could simplify or abstract away. Can you look on that? What do you mean? I missed where you're placing consciousness in this second. Well, so if you are a computationalist, you think that what creates consciousness is the implementation of a computation. So some property, emergent property of the computation itself. Yeah. That's the idea. Yeah, you could say that. But then the question is, what's the class of computations such that when they are run, consciousness emerges? So if you just have something that adds one plus one plus one plus one, like a simple computation, you think maybe that's not going to have any consciousness. If on the other hand, the computation is one like our human brains are performing, where as part of the computation, there is a global workspace, a sophisticated attention mechanism, there is self-representations of other cognitive processes, and a whole lot of other things that possibly would be conscious. And in fact, if it's exactly like ours, I think definitely it would. But exactly how much less than the full computation that the human brain is performing would be required is a little bit, I think, of an open question. You asked another interesting question as well, which is, would it be sufficient to just have, say, the brain, or would you need the environment? Right, that's a nice one. In order to generate the same kind of experiences that we have. And there is a bunch of stuff we don't know. I mean, if you look at, say, current virtual reality environments, one thing that's clear is that we don't have to simulate all details of them all the time, in order for, say, the human player to have the perception that there is a full reality in there. You can have, say, procedurally generated, where you might only render a scene when it's actually within the view of the player character. And so similarly, if this environment that we perceive is simulated, it might be that all of the parts that come into our view are rendered at any given time. And a lot of aspects that never come into view, say, the details of this microphone I'm talking into, exactly what each atom is doing at any given point in time, might not be part of the simulation, only a more coarse-grained representation. So that to me is actually, from an engineering perspective, why the simulation hypothesis is really interesting to think about. Right. Is how much, how difficult is it to fake, sort of in a virtual reality context, I don't know if fake is the right word, but to construct a reality that is sufficiently real to us to be immersive in the way that the physical world is. I think that's actually probably an answerable question of psychology, of computer science, of how, where's the line where it becomes so immersive that you don't want to leave that world? Yeah, or that you don't realize while you're in it that it is a virtual world. Yeah, those are two actually questions. Yours is the more sort of the good question about the realism. But mine, from my perspective, what's interesting is it doesn't have to be real, but how can we construct a world that we wouldn't want to leave? Yeah, I mean, I think that might be too low a bar. I mean, if you think, say, when people first had Pong or something like that, I'm sure there were people who wanted to keep playing it for a long time, because it was fun, and they wanted to be in this little world. I'm not sure we would say it's immersive. I mean, I guess in some sense it is, but like an absorbing activity doesn't even have to be. But they left that world, though. So I think that bar is deceivingly high. So you can play Pong or StarCraft or whatever more sophisticated games for hours, for months, while the Warcraft could be a big addiction, but eventually they escaped that. So you mean when it's absorbing enough that you would choose to spend your entire life in there? And then thereby changing the concept of what reality is, because your reality becomes the game, not because you're fooled, but because you've made that choice. Yeah, and people might have different preferences regarding that. Some might, even if you had a perfect virtual reality, might still prefer not to spend the rest of their lives there. I mean, in philosophy, there's this experience machine, thought experiment. Have you come across this? So Robert Nozick had this thought experiment where you imagine some crazy super duper neuroscientists of the future have created a machine that could give you any experience you want if you step in there. And for the rest of your life, you can kind of pre-programmed it in different ways. So your fondest dreams could come true. You could, whatever you dream, you want to be a great artist, a great lover, have a wonderful life, all of these things. If you step into the experience machine, it will be your experiences, constantly happy. But you would kind of disconnect from the rest of reality and you would float there in a tank. And so Nozick thought that most people would choose not to enter the experience machine. I mean, many might want to go there for a holiday, but they wouldn't want to check out of existence permanently. And so he thought that was an argument against certain views of value, according to what we value is a function of what we experience. Because in the experience machine, you can have any experience you want, and yet many people would think that would not be much value. So therefore, what we value depends on other things than what we experience. Okay, can you take that argument further? What about the fact that maybe what we value is the up and down of life? You could have up and downs in the experience machine, right? But what can't you have in the experience machine? That then becomes an interesting question to explore. But for example, real connection with other people, if the experience machine is a solar machine where it's only you, that's something you wouldn't have there. You would have this subjective experience that would be like fake people. But if you gave somebody flowers, that wouldn't be anybody there who actually got happy. It would just be a little simulation of somebody smiling. But the simulation would not be the kind of simulation I'm talking about in the simulation argument, where the simulated creature is conscious. It would just be a kind of smiley face that would look perfectly real to you. So we're now drawing a distinction between appear to be perfectly real and actually being real. Yeah. So that could be one thing. I mean, like a big impact on history, maybe is also something you won't have if you check into this experience machine. So some people might actually feel the life I want to have for me is one where I have a big positive impact on how history unfolds. So you could kind of explore these different possible explanations for why it is you wouldn't want to go into the experience machine, if that's what you feel. And one interesting observation regarding this Nozick thought experiment and the conclusions he wanted to draw from it is how much is a kind of a status quo effect. So a lot of people might not want to get this on current reality to plug into this dream machine. But if they instead were told, well, what you've experienced up to this point was a dream. Now, do you want to disconnect from this and enter the real world when you have no idea maybe what the real world is? Or maybe you could say, well, you're actually a farmer in Peru, growing peanuts, and you could live for the rest of your life in this. Or would you want to continue your dream life as Alex Friedman, going around the world, making podcasts and doing research? So if the status quo was that they were actually in the experience machine, I think a lot of people might then prefer to live the life that they are familiar with, rather than sort of bail out into... It's interesting, the change itself, the leap, whatever. Yeah, so it might not be so much the reality itself that we are after, but it's more that we are maybe involved in certain projects and relationships. And we have a self-identity and these things, that our values are kind of connected with carrying that forward. And then whether it's inside a tank or outside a tank in Peru, or whether inside a computer or outside a computer, that's kind of less important to what we ultimately care about. Yeah, but still, just to linger on it, it is interesting. I find, maybe people are different, but I find myself quite willing to take the leap to the farmer in Peru, especially as the virtual reality system becomes more realistic. I find that possibility, and I think more people would take that leap. But in this thought experiment, just to make sure we are understanding, so in this case, the farmer in Peru would not be a virtual reality, that would be the real, your life, like before this whole experience machine started. Well, I kind of assume from that description, you're being very specific, but that kind of idea just like washes away the concept of what's real. I mean, I'm still a little hesitant about your kind of distinction between real and illusion. Because when you can have an illusion that feels, I mean, that looks real, I don't know how you can definitively say something is real or not. Like, what's a good way to prove that something is real in that context? Well, so I guess in this case, it's more a stipulation. In one case, you're floating in a tank with these wires by the super duper neuroscientists plugging into your head, giving you like Friedman experiences. In the other, you're actually tilling the soil in Peru, growing peanuts, and then those peanuts are being eaten by other people all around the world who buy the exports. So, these are two different possible situations in the one and the same real world that you could choose to occupy. But just to be clear, when you're in a vat with wires and the neuroscientists, you can still go farming in Peru, right? No, well, if you wanted to, you could have the experience of farming in Peru, but there wouldn't actually be any peanuts grown. But what makes a peanut... So, a peanut could be grown and you could feed things with that peanut. And why can't all of that be done in a simulation? I hope, first of all, that they actually have peanut farms in Peru. I get a lot of comments otherwise from Angry. I was with you up to the point when you started talking about... You should know you can't grow peanuts in that climate. No, I mean, I think in the simulation, I think there's a sense, the important sense in which it would all be real. Nevertheless, there is a distinction between inside a simulation and outside a simulation, or in the case of NOSIG's thought experiment, whether you're in the vat or outside the vat. And some of those differences may or may not be important. I mean, that comes down to your values and preferences. So, if the experience machine only gives you the experience of growing peanuts, but you're the only one in the experience machine... No, but there's other... Within the experience machine, others can plug in. Well, there are versions of the experience machine. So, in fact, you might want to have different thought experiments, different versions of it. So, in the original thought experiment, maybe it's only you, right? Just you. And you think, I wouldn't want to go in there. Well, that tells you something interesting about what you value and what you care about. Then you could say, well, what if you add the fact that there would be other people in there and you would interact with them? Well, it starts to make it more attractive, right? Then you could add in, well, what if you could also have important long-term effects on human history and the world and you could actually do something useful even though you were in there? That makes it maybe even more attractive. Like you could actually have a life that had a purpose and consequences. So, as you sort of add more into it, it becomes more similar to the baseline reality that you were comparing it to. Yeah, but I just think inside the experience machine and without taking those steps you just mentioned, you still have an impact on long-term history of the creatures that live inside that, of the quote-unquote fake creatures that live inside that experience machine. And that, like at a certain point, you know, if there's a person waiting for you inside that experience machine, maybe your newly found wife, and she dies, she has fear, she has hopes, and she exists in that machine. When you unplug yourself and plug back in, she's still there going on about her life. Well, in that case, yeah, she starts to have more of an independent existence. Independent existence. But it depends, I think, on how she's implemented in the experience machine. Take one limit case where all she is is a static picture on the wall, a photograph. So, you think, well, I can look at her, right? But that's it. But then you think, well, it doesn't really matter much what happens to that, any more than a normal photograph, if you tear it up, right? It means you can't see it anymore, but you haven't harmed the person whose picture you tore up. It's a good one. But if she's actually implemented, say, at a neural level of detail, so that she's a fully realized digital mind with the same behavioral repertoire as you have, then very possibly she would be a conscious person like you are. And then what you do in this experience machine would have real consequences for how this other mind felt. So, you have to specify which of these experience machines you're talking about. I think it's not entirely obvious that it would be possible to have an experience machine that gave you a normal set of human experiences, which include experiences of interacting with other people, without that also generating consciousnesses corresponding to those other people. That is, if you create another entity that you perceive and interact with, that to you looks entirely realistic. Not just when you say hello, they say hello back, but you have a rich interaction, many days, deep conversations. It might be that the only possible way of implementing that would be one that also has a side effect, instantiated this other person in enough detail that you would have a second consciousness there. I think that's, to some extent, an open question. So, you don't think it's possible to fake consciousness and fake intelligence? Well, it might be. I mean, I think you can certainly fake, if you have a very limited interaction with somebody, you could certainly fake that. That is, if all you have to go on is somebody said hello to you, that's not enough for you to tell whether that was a real person there, or a pre-recorded message, or a very superficial simulation that has no consciousness. Because that's something easy to fake. We could already fake it now, you can record a voice recording. But if you have a richer set of interactions where you're allowed to ask open-ended questions and probe from different angles, you could give canned answers to all of the possible ways that you could probe it, then it starts to become more plausible that the only way to realize this thing, in such a way that you would get the right answer from any which angle you probed it, would be a way of instantiating it where you also instantiated a conscious mind. Yeah, I'm with you on the intelligence part, but there's something about me that says consciousness is easier to fake. I've recently gotten my hands on a lot of Roombas, don't ask me why or how, and I've made them, there's just a nice robotic mobile platform for experiments, and I made them scream or moan in pain and so on, just to see when they're responding to me. And it's just a sort of psychological experiment on myself, and I think they appear conscious to me pretty quickly. To me, at least my brain can be tricked quite easily. So if I introspect, it's harder for me to be tricked that something is intelligent. So I just have this feeling that inside this experience machine, just saying that you're conscious and having certain qualities of the interaction, like being able to suffer, like being able to hurt, like being able to wander about the essence of your own existence, not actually creating the illusion that you're wandering about it, is enough to create the illusion of consciousness, and because of that, create a really immersive experience to where you feel like that is the real world. Is there a big gap between appearing conscious and being conscious, or is it that you think it's very easy to be conscious? I'm not actually sure what it means to be conscious. All I'm saying is the illusion of consciousness is enough to create a social interaction that's as good as if the thing was conscious, meaning I'm making it about myself. Right, yeah. I mean, I guess there are a few different things. One is how good the interaction is, which might, I mean, if you don't really care about probing hard for whether the thing is conscious, maybe it would be a satisfactory interaction, whether or not you really thought it was conscious. Now, if you really care about it being conscious inside this experience machine, how easy would it be to fake it, and you say it sounds fairly easy? But then the question is, would that also mean it's very easy to instantiate consciousness? It's much more widely spread in the world, and we have thought it doesn't require a big human brain with 100 billion neurons. All you need is some system that exhibits basic intentionality and can respond, and you already have consciousness. In that case, I guess you still have a close coupling. I guess a data case would be where they can come apart, where you could create the appearance of there being a conscious mind without actually not being another conscious mind. I'm somewhat agnostic exactly where these lines go. I think one observation that makes it plausible that you could have very realistic appearances relatively simply, which also is relevant for the simulation argument and in terms of thinking about how realistic would a virtual reality model have to be in order for the simulated creature not to notice that anything was awry. Well, just think of our own humble brains during the wee hours of the night when we are dreaming. Many times, well, dreams are very immersive, but often you also don't realize that you're in a dream. And that's produced by simple, primitive three-pound lumps of neural matter effortlessly. So if a simple brain like this can create a virtual reality that seems pretty real to us, then how much easier would it be for a super-intelligent civilization with planetary-sized computers optimized over the eons to create a realistic environment for you to interact with? Yeah, by the way, behind that intuition is that our brain is not that impressive relative to the possibilities of what technology could bring. It's also possible that the brain is the epitome, is the ceiling. The ceiling, how is that possible? Meaning this is the smartest possible thing that the universe could create. So that seems unlikely to me. Yeah, I mean, for some of these reasons we alluded to earlier, in terms of designs we already have for computers that would be faster by many orders of magnitude than the human brain. Yeah, but it could be that the constraints, the cognitive constraints in themselves is what enables the intelligence. So the more powerful you make the computer, the less likely it is to become super-intelligent. This is where I say dumb things to push back on the statement. Yeah, I'm not sure I follow you. So there are different dimensions of intelligence. A simple one is just speed. Like if you could solve the same challenge faster, in some sense, you're smarter. So there I think we have very strong evidence for thinking that you could have a computer in this universe that would be much faster than the human brain and therefore have speed super-intelligence, like be completely superior, maybe a million times faster. Then maybe there are other ways in which you could be smarter as well, maybe more qualitative ways. And the concepts are a little bit less clear-cut, so it's harder to make a very crisp, neat, firmly logical argument about why that could be qualitative super-intelligence as opposed to just things that were faster. Although I still think it's very plausible for various reasons that are less than watertight arguments. But you can sort of, for example, if you look at animals and even within humans, there seems to be Einstein versus random person. It's not just that Einstein was a little bit faster, but how long would it take a normal person to invent general relativity? It's not 20% longer than it took Einstein or something like that. It's like, I don't know whether they would do it at all, or it would take millions of years, or some totally bizarre... But your intuition is that the compute size will get you... Increasing the size of the computer and the speed of the computer might create some much more powerful levels of intelligence that would enable some of the things we've been talking about with the simulation. Being able to simulate an ultra-realistic environment, ultra-realistic perception of reality. Yeah. Strictly speaking, it would not be necessary to have super-intelligence in order to have, say, the technology to make these simulations, ancestor simulations or other kinds of simulations. As a matter of fact, I think if we are in a simulation, it would most likely be one built by a civilization that had super-intelligence. It certainly would help a lot. I mean, it could build more efficient, larger scale structures if you had super-intelligence. I also think that if you had the technology to build these simulations, that's a very advanced technology. It seems kind of easier to get the technology to super-intelligence. So I'd expect by the time they could make these fully realistic simulations of human history with human brains in there, before they got to that stage, they would have figured out how to create machine super-intelligence or maybe biological enhancements of their own brains if they were biological creatures to start with. So we talked about the three parts of the simulation argument. One, we destroy ourselves before we ever create the simulation. Two, we somehow, everybody somehow loses interest in creating simulation. And three, we're living in a simulation. So you've kind of, I don't know if your thinking has evolved on this point, but you kind of said that we know so little that these three cases might as well be equally probable. So probabilistically speaking, where do you stand on this? Yeah, I mean, I don't think equal necessarily would be the most supported probability assignment. So how would you, without assigning actual numbers, what's more or less likely in your view? Well, I mean, I've historically tended to punt on the question of like as between these three. So maybe you ask another way is which kind of things would make each of these more or less likely? What kind of, yeah, intuition. I mean, certainly in general terms, if you take anything that say increases or reduces the probability of one of these, we tend to slosh probability around on the others. If one becomes less probable, like the other would have to, because it's going to add up to one. So if we consider the first hypothesis, the first alternative that there's this filter that makes it so that virtually no civilization reaches technological maturity, in particular, our own civilization. If that's true, then it's like very unlikely that we would reach technological maturity, because if almost no civilization at our stage does it, then it's unlikely that we do it. So hence... Sorry, can you linger on that for a second? Well, if it's the case that almost all civilizations at our current stage of technological maturity fail, at our current stage of technological development fail to reach maturity, that would give us very strong reason for thinking we will fail to reach technological maturity. And also sort of the flip side of that is the fact that we've reached it means that many other civilizations have reached this point. Yeah, so that means if we get closer and closer to actually reaching technological maturity, there's less and less distance left where we could go extinct before we are there. And therefore, the probability that we will reach increases as we get closer. And that would make it less likely to be true that almost all civilizations at our current stage failed to get there. Like we would have this... The one case we'd started ourselves would be very close to getting there. That would be strong evidence that it's not so hard to get to technological maturity. So to the extent that we feel we are moving nearer to technological maturity, that would tend to reduce the probability of the first alternative and increase the probability of the other two. It doesn't need to be a monotonic change. Like if every once in a while, some new threat comes into view, some bad new thing you could do with some novel technology, for example, that could change our probabilities in the other direction. But that technology, again, you have to think about as that technology has to be able to equally, in an even way, affect every civilization out there. Yeah, pretty much. I mean, strictly speaking, it's not true. I mean, that could be two different existential risks in every civilization, you know, one or the other, but none of them kills more than 50%. Yeah, gotcha. Incidentally, some of my work on machine superintelligence, like I've pointed to some existential risks related to superintelligent AI and how we must make sure to handle that wisely and carefully. It's not the right kind of existential catastrophe to make the first alternative true, though. Like it might be bad for us if the future lost a lot of value as a result of it being shaped by some process that optimized for some completely non-human value. But even if we got killed by machine superintelligence, that machine superintelligence might still attain technological maturity. Oh, I see. So you're not human exclusive. This could be any intelligent species that achieves... Like it's all about the technological maturity, it's not that the humans have to attain it. Right. So like superintelligence could replace us and that's just as well for the simulation argument. Yeah, I mean, it could interact with the second alternative. Like if the thing that replaced us was either more likely or less likely, then we would be to have an interest in creating ancestor simulations, you know, that could affect probabilities. But yeah, to a first order, like if we all just die, then yeah, we won't produce any simulations because we are dead. But if we all die and get replaced by some other intelligent thing that then gets to technological maturity, the question remains, of course, if not that thing, then use some of its resources to do this stuff. So can you reason about this stuff? Like given how little we know about the universe, is it reasonable to reason about these probabilities? So like how little... Well, maybe you can disagree, but to me, it's not trivial to figure out how difficult it is to build a simulation. We kind of talked about it a little bit. We also don't know, like as we try to start building it, like start creating virtual worlds and so on, how that changes the fabric of society. Like there's all these things along the way that can fundamentally change just so many aspects of our society about our existence that we don't know anything about. Like the kind of things we might discover when we understand to a greater degree the fundamental, the physics, like the theory, if we have a breakthrough, have a theory and everything, how that changes stuff, how that changes deep space exploration and so on. So like, is it still possible to reason about probabilities given how little we know? Yes, I think there will be a large residual of uncertainty that we'll just have to acknowledge. And I think that's true for most of these big picture questions that we might wonder about. It's just, we are small, short-lived, small-brained, cognitively very limited humans with little evidence. And it's amazing we can figure out as much as we can really about the cosmos. But, okay, so there's this cognitive trick that seems to happen when I look at the simulation argument, which for me, it seems like case one and two feel unlikely. I want to say feel unlikely as opposed to sort of, it's not like I have too much scientific evidence to say that either one or two are not true. It just seems unlikely that every single civilization destroys itself. And it seems, like feels unlikely that the civilizations lose interest. So naturally, without necessarily explicitly doing it, but the simulation argument basically says it's very likely we're living in a simulation. Like to me, my mind naturally goes there. I think the mind goes there for a lot of people. Is that the incorrect place for it to go? Well, not necessarily. I think the second alternative, which has to do with the motivations and interest of technological immature civilizations, I think there is much we don't understand about that. Can you talk about that a little bit? What do you think? I mean, this is a question that pops up when you build an AGI system or build a general intelligence, or how does that change our motivations? Do you think it will fundamentally transform our motivations? Well, it doesn't seem that implausible that once you take this leap to technological maturity, I mean, I think it involves creating machine super intelligence, possibly, that would be sort of on the path for basically all civilizations, maybe before they are able to create large numbers of ancestral simulations. That possibly could be one of these things that quite radically changes the orientation of what a civilization is, in fact, optimizing for. There are other things as well. So, at the moment, we have not perfect control over our own being, our own mental states, our own experiences, are not under our direct control. So, for example, if you want to experience pleasure and happiness, you might have to do a whole host of things in the external world to try to get into the mental state where you experience pleasure. Like, if people get pleasure from eating great food, well, they can't just turn that on. They have to kind of actually go to a nice restaurant and then they have to make money. So, there's like all this kind of activity that maybe arises from the fact that we are trying to ultimately produce mental states, but the only way to do that is by a whole host of complicated activities in the external world. Now, at some level of technological development, I think we'll become auto potent in the sense of gaining direct ability to choose our own internal configuration and enough knowledge and insight to be able to actually do that in a meaningful way. So, then it could turn out that there are a lot of instrumental goals that would drop out of the picture and be replaced by other instrumental goals because we could now serve some of these final goals in more direct ways. And who knows how all of that shakes out after civilizations reflect on that and converge on different attractors and so on and so forth. And that could be new instrumental considerations that come into view as well that we are just oblivious to that would maybe have a strong shaping effect on actions, like very strong reasons to do something or not to do something. And we just don't realize they're there because we are so dumb, fumbling through the universe. But if almost inevitably on route to attaining the ability to create many answers to simulations, you do have this cognitive enhancement or advice from super intelligences or you yourself, then maybe there's this additional set of considerations coming into view. And you have to realize, it's obvious that the thing that makes sense is to do X. Whereas right now it seems, you could X, Y, or Z and different people will do different things. And we are kind of random in that sense. Yeah, because at this time with our limited technology, the impact of our decisions is minor. I mean, that's starting to change in some ways. Well, I'm not sure it follows that the impact of our decisions is minor. Well, it's starting to change. I mean, I suppose a hundred years ago it was minor. It's starting to... It depends on how you view it. But people that a hundred years ago still have effects on the world today. Oh, I see. As a civilization in the togetherness. Yeah. So it might be that the greatest impact of individuals is not at technological maturity or very far down. It might be earlier on when there are different tracks, civilization could go down. I mean, maybe the population is smaller, things still haven't settled out. If you count indirect effects, those could be bigger than the direct effects that people have later on. So part three of the argument says that, so that leads us to a place where eventually somebody creates a simulation. I think you had a conversation with Joe Rogan, I think there's some aspect here where you got stuck a little bit. How does that lead to we're likely living in a simulation? So this kind of probability argument, if somebody eventually creates a simulation, why does that mean that we're now in a simulation? What you get to if you accept alternative three first is there would be more simulated people with our kinds of experiences than non-simulated ones. Like if you look at the world as a whole, by the end of time, as it were, you just count it up. There would be more simulated ones than non-simulated ones. Then there is an extra step to get from that. So suppose for the sake of the argument that that's true, how do you get from that to the statement, we are probably in a simulation? So here you're introducing an indexical statement, like it's that this person right now is in a simulation. There are all these other people that are in simulations and some that are not in a simulation. But what probability should you have that you yourself is one of the simulated ones? So I call it the bland principle of indifference, which is that in cases like this, when you have two sets of observers, one of which is much larger than the other, and you can't from any internal evidence you have tell which set you belong to, you should assign a probability that's proportional to the size of these sets. So that if there are 10 times more simulated people with your kinds of experiences, you would be 10 times more likely to be one of those. Is that as intuitive as it sounds? I mean, that seems kind of, if you don't have enough information, you should rationally just assign the same probability as the size of the set. It seems pretty plausible to me. Where are the holes in this? Is it at the very beginning, the assumption that everything stretches, sort of, you have infinite time, essentially? You don't need infinite time. You just need, how long does the time... Well, however long it takes, I guess, for a universe to produce an intelligent civilization that then attains the technology to run some ancestry simulations. Gotcha. At some point, when the first simulation is created, that stretch of time, just a little longer, then they'll all start creating simulations. Yeah, well, I mean, it might, if you think of there being a lot of different planets and some subset of them have life, and then some subset of those get to intelligent life, and some of those maybe eventually start creating simulations, they might get started at quite different times. Like maybe on some planet, it takes a billion years longer before you get monkeys or before you get even bacteria than on another planet. So this might happen at different cosmological epochs. Is there a connection here to the doomsday argument and that sampling there? Yeah, there is a connection in that they both involve an application of anthropic reasoning, that is reasoning about these kind of indexical propositions. But the assumption you need in the case of the simulation argument is much weaker than the assumption you need to make the doomsday argument go through. What is the doomsday argument? And maybe you can speak to the anthropic reasoning in more general. Yeah, that's a big and interesting topic in its own right, anthropics. But the doomsday argument is this really first discovered by Brandon Carter, who was a theoretical physicist and then developed by philosopher John Leslie. I think it might have been discovered initially in the 70s or 80s. And Leslie wrote this book, I think, in 96. And there are some other versions as well by Richard Gott, who is a physicist. But let's focus on the Carter-Leslie version, where it's an argument that we have systematically underestimated the probability that humanity will go extinct soon. Now, I should say most people probably think at the end of the day, there is something wrong with this doomsday argument that it doesn't really hold. It's like there's something wrong with it, but it's proved hard to say exactly what is wrong with it. And different people have different accounts. My own view is it seems inconclusive. And I can say what the argument is. Yeah, that would be good. Yeah, so maybe it's easiest to explain via an analogy to sampling from urns. So imagine you have two urns in front of you, and they have balls in them that have numbers. The two urns look the same, but inside one, there are 10 balls. Ball number one, two, three, up to ball number 10. And then in the other urn, you have a million balls numbered one to a million. And somebody puts one of these urns in front of you and asks you to guess what's the chance it's the 10 ball urn. And you say, well, 50-50, I can't tell which urn it is. But then you're allowed to reach in and pick a ball at random from the urn. And let's suppose you find that it's ball number seven. So that's strong evidence for the 10 ball hypothesis. It's a lot more likely that you would get such a low-numbered ball if there are only 10 balls in the urn. It's in fact 10% done, right? Then if there are a million balls, it would be very unlikely you would get number seven. So you perform a Bayesian update. And if your prior was 50-50 that it was the 10 ball urn, you become virtually certain after finding the random sample was seven that it only has 10 balls in it. So in the case of the urns, this is uncontroversial, just elementary probability theory. The Doomsday Argument says that you should reason in a similar way with respect to different hypotheses about how many balls there will be in the urn of humanity. I said, for how many humans there will ever be by the time we go extinct. So to simplify, let's suppose we only consider two hypotheses, either maybe 200 billion humans in total or 200 trillion humans in total. You could fill in more hypotheses, but it doesn't change the principle here. So it's easiest to see if we just consider these two. So you start with some prior based on ordinary empirical ideas about threats to civilization and so forth. And maybe you say it's a 5% chance that we will go extinct by the time there will have been 200 billion only. You're kind of optimistic, let's say. You think probably we'll make it through, colonize the universe. But then, according to this Doomsday Argument, you should think of your own birth rank as a random sample. So your birth rank is your sequence in the position of all humans that have ever existed. It turns out you're about a human number of 100 billion, give or take. That's roughly how many people have been born before you. That's fascinating because we each have a number. We would each have a number in this. Obviously, the exact number would depend on where you started counting, like which ancestors was human enough to count as human. But those are not really important. There are relatively few of them. So you're roughly 100 billion. Now, if there are only going to be 200 billion in total, that's a perfectly unremarkable number. You're somewhere in the middle, right? It's run-of-the-mill human, completely unsurprising. Now, if there are going to be 200 trillion, you would be remarkably early. What are the chances out of these 200 trillion humans that you should be human number 100 billion? That seems it would have a much lower conditional probability. And so analogously to how in the urn case you thought after finding this low-numbered random sample, you updated in favor of the urn having few balls. Similarly, in this case, you should update in favor of the human species having a lower total number of members. That is doom soon. You said doom soon? Yeah. Well, that would be the hypothesis in this case, that it will end after 100 billion. I just like that term for that hypothesis. So what it kind of crucially relies on, the doomsday argument, is the idea that you should reason as if you were a random sample from the set of all humans that will ever have existed. If you have that assumption, then I think the rest kind of follows. The question then is why should you make that assumption? In fact, you know you're 100 billion, so where do you get this prior? And then there is like a literature on that with different ways of supporting that assumption. That's just one example of atheropic reasoning, right? That seems to be kind of convenient when you think about humanity, when you think about sort of even like existential threats and so on. As it seems that quite naturally that you should assume that you're just an average case. Yeah, that you're a kind of a typical, a randomly sampled. Now, in the case of the doomsday argument, it seems to lead to what intuitively we think is the wrong conclusion. Or at least many people have this reaction that there's got to be something fishy about this argument. Because from very, very weak premises, it gets this very striking implication that we have almost no chance of reaching size 200 trillion humans in the future. And how could we possibly get there just by reflecting on when we were born? It seems you would need sophisticated arguments about the impossibility of space colonization, blah, blah. So one might be tempted to reject this key assumption. I call it the self-sampling assumption. The idea that you should reason as if you're a random sample from all observers or in some reference class. However, it turns out that in other domains, it looks like we need something like this self-sampling assumption to make sense of bona fide scientific inferences. In contemporary cosmology, for example, you have these multiverse theories. And according to a lot of those, all possible human observations are made. So if you have a sufficiently large universe, you will have a lot of people observing all kinds of different things. So if you have two competing theories, say about the value of some constant, it could be true according to both of these theories that there will be some observers observing the value that corresponds to the other theory. Because there will be some observers that have hallucinations, so there's a local fluctuation or a statistically anomalous measurement. These things will happen. And if enough observers make enough different observations, there will be some that sort of by chance make these different ones. And so what we would want to say is, well, many more observers, a larger proportion of the observers will observe as it were the true value. And a few will observe the wrong value. If we think of ourselves as a random sample, we should expect with a probability to observe the true value. And that will then allow us to conclude that the evidence we actually have is evidence for the theories we think are supported. It kind of then is a way of making sense of these inferences that clearly seem correct, that we can make various observations and infer what the temperature of the cosmic background is and the fine structure constant and all of this. But it seems that without rolling in some assumption similar to the self-sampling assumption, this inference just doesn't go through. And there are other examples. So there are these scientific contexts where it looks like this kind of anthropic reasoning is needed and makes perfect sense. And yet, in the case of the Doobster argument, it has this weird consequence and people might think there's something wrong with it there. So there's then this project that would consistently try to figure out what are the legitimate ways of reasoning about these indexical facts when observer selection effects are in play. In other words, developing a theory of anthropics. And there are different views of looking at that. And it's a difficult methodological area. But to tie it back to the simulation argument, the key assumption there, this bland principle of indifference, is much weaker than the self-sampling assumption. So if you think about in the case of the Doomsday argument, it says you should reason as if you're a random sample from all humans that will ever have lived. Even though in fact, you know that you are about number 100 billionth human and you're alive in the year 2020. Whereas in the case of the simulation argument, it says that, well, if you actually have no way of telling which one you are, then you should assign this kind of uniform probability. Yeah, yeah. Your role as the observer in the simulation argument is different, it seems like. Who's the observer? I keep assigning the individual consciousness. Well, a lot of observers in the context of the simulation argument, the relevant observers would be A, the people in original histories, and B, the people in simulations. So this would be the class of observers that we need. I mean, there are also maybe the simulators, but we can set those aside for this. So the question is, given that class of observers, a small set of original history observers and a large class of simulated observers, which one should you think is you? Where are you amongst this set of observers? I'm maybe having a little bit of trouble wrapping my head around the intricacies of what it means to be an observer in the different instantiations of the anthropic reasoning cases that we mentioned. I mean, it may be an easier way of putting it, it's just like, are you simulated or are you not simulated? Given this assumption that these two groups of people exist. Yeah, in the simulation case, it seems pretty straightforward. Yeah. So the key point is the methodological assumption you need to make to get the simulation argument to where it wants to go is much weaker and less problematic than the methodological assumption you need to make to get the doomsday argument to its conclusion. Maybe the doomsday argument is sound or unsound, but you need to make a much stronger and more controversial assumption to make it go through. In the case of the simulation argument, I guess one maybe way intuition popped to support this blind principle of indifference is to consider a sequence of different cases where the fraction of people who are simulated to non-simulated approaches one. So in the limiting case where everybody is simulated, obviously you can deduce with certainty that you are simulated. If everybody with your experiences is simulated, then you know you're got to be one of those. You don't need a probability at all. You just kind of logically conclude it. Right. So then as we move from a case where say 90% of everybody is simulated, 99.9%, it should seem plausible that the probability assigned should sort of approach one certainty as the fraction approaches the case where everybody is in a simulation. Yeah, that's a good one. So you wouldn't expect that to be a discrete. Well, if there's one non-simulated person, then it's 50-50. But if we'd move that, then it's 100%. There are other arguments as well one can use to support this blind principle of indifference, but that might be enough to... But in general, when you start from time equals zero and go into the future, the fraction of simulated, if it's possible to create simulated worlds, the fraction of simulated worlds will go to one. Well, it won't probably go all the way to one. In reality, there would be some ratio. Although maybe a technologically mature civilization could run a lot of simulations using a small portion of its resources, it probably wouldn't be able to run infinitely many. I mean, if we take, say, the physics in the observed universe, if we assume that that's also the physics at the level of the simulators, that would be limits to the amount of information processing that any one civilization could perform in its future trajectory. Right. Well, first of all, there's a limited amount of matter you can get your hands off because with a positive cosmological constant, the universe is accelerating. There is a finite sphere of stuff, even if you travel with the speed of light that you could ever reach, you have a finite amount of stuff. And then if you think there is a lower limit to the amount of loss you get when you perform an erasure of a computation, or if you think, for example, just matter gradually over cosmological time scales, decay, maybe protons decay, other things, and you radiate out gravitational waves. There's all kinds of seemingly unavoidable losses that occur. So eventually we'll have something like a heat death of the universe or a cold death or whatever. So it's finite, but of course we don't know which, if there's many ancestral simulations, we don't know which level we are. So there could be, couldn't there be like an arbitrary number of simulation that spawned ours and those had more resources in terms of physical universe to work with? Sorry, what do you mean that that could be? Sort of, okay, so if simulations spawn other simulations, it seems like each new spawn has fewer resources to work with. Yeah. But we don't know at which step along the way we are at. Any one observer doesn't know whether we're in level 42 or 100 or 1, or does that not matter for the resources? I mean, it's true that there would be uncertainty as you could have stacked simulations and that could be uncertainty as to which level we are at. As you remarked also, all the computations performed in a simulation within the simulation also have to be expanded at the level of the simulation. Right. So the computer in basement reality where all the simulations within the simulations within the simulations are taking place, like that computer ultimately, it's CPU or whatever it is that has to power this whole tower. Right. So if there is a finite compute power in basement reality, that would impose a limit to how tall this tower can be. And if each level kind of imposes a large extra overhead, you might think maybe the tower would not be very tall, that most people would be low down in the tower. I love the term basement reality. Let me ask one of the popularizers, you said there's many through this, when you look at sort of the last few years of the simulation hypothesis, just like you said, it comes up every once in a while, some new community discovers it and so on. But I would say one of the biggest popularizers of this idea is Elon Musk. Do you have any kind of intuition about what Elon thinks about when he thinks about simulation? Why is this of such interest? Is it all the things we've talked about or is there some special kind of intuition about simulation that he has? I mean, you might have a better, I think, I mean, why it's of interest, I think it's like seems fairly obvious why, to the extent that one think the argument is credible, why it would be of interest. It would, if it's correct, tell us something very important about the world, in one way or the other, whichever of the three alternatives for a simulation, that seems like arguably one of the most fundamental discoveries. Right. Now, interestingly, in the case of someone like Elon, so there's like the standard arguments for why you might want to take the simulation hypothesis seriously, the simulation argument, right. In the case that if you are actually Elon Musk, let us say, there's a kind of an additional reason in that what are the chances you would be Elon Musk? Like, it seems like maybe there would be more interest in simulating the lives of very unusual and remarkable people. So if you consider not just a simulations where all of human history or the whole of human civilization are simulated, but also other kinds of simulations, which only include some subset of people. Like in those simulations that only include a subset, it might be more likely that that would include subsets of people with unusually interesting or consequential lives. So if you're Elon Musk, it's more likely than your inspiration. Or if you're Donald Trump, or if you're Bill Gates, or you're like some particularly distinctive character, you might think that that adds, I mean, if you just think of yourself into the shoes, right, it's got to be like an extra reason to think, that's kind of. So interesting. So on a scale of like Farmer in Peru to Elon Musk, the more you get towards the Elon Musk, the higher the probability. You'd imagine that would be some extra boost from that. There's an extra boost. So he also asked the question of what he would ask an AGI saying, the question being, what's outside the simulation? Do you think about the answer to this question, if we are living in a simulation, what is outside the simulation? So the programmer of the simulation? Yeah, I mean, I think it connects to the question of what's inside the simulation in that if you had views about the creators of the simulation, it might help you make predictions about what kind of simulation it is, what might happen, what happens after the simulation, if there is some after, but also like the kind of setup. So these two questions would be quite closely intertwined. But do you think it would be very surprising to like, is the stuff inside the simulation, is it possible for it to be fundamentally different than the stuff outside? Yeah. Like, another way to put it, can the creatures inside the simulation be smart enough to even understand or have the cognitive capabilities or any kind of information processing capabilities enough to understand the mechanism that created them? They might understand some aspects of it. I mean, it's a level of, it's kind of, there are levels of explanation, like degrees to which you can understand. So does your dog understand what it is to be human? Well, it's got some idea, like humans are these physical objects that move around and do things. And like a normal human would have a deeper understanding of what it is to be a human. And maybe some very experienced psychologist or great novelist might understand a little bit more about what it is to be human. And maybe superintelligence could see right through your soul. So similarly, I do think that we are quite limited in our ability to understand all of the relevant aspects of the larger context that we exist in. But there might be hope for some. I think we understand some aspects of it. But, you know, how much good is that if there's like one key aspect that changes the significance of all the other aspects? So we understand maybe seven out of 10 key insights that you need. But the answer actually, like varies completely depending on what like number eight, nine and 10 insight is. It's like whether you want to, suppose that the big task were to guess whether a certain number was odd or even, like a 10 digit number. And if it's even, the best thing for you to do in life is to go north. And if it's odd, the best thing for you to go south. Now we are in a situation where maybe through our science and philosophy, we figured out what the first seven digits are. So we have a lot of information, right? Most of it we figured out. But we are clueless about what the last three digits are. So we are still completely clueless about whether the number is odd or even and therefore whether we should go north or go south. I feel that's an analogy, but I feel we're somewhat in that predicament. We know a lot about the universe. We've come maybe more than half of the way there to kind of fully understanding it. But the parts we're missing are plausibly ones that could completely change the overall upshot of the thing and including change our overall view about what the scheme of priorities should be or which strategic direction would make sense to pursue. Yeah, I think your analogy of us being the dog trying to understand human beings is an entertaining one and probably correct. The closer the understanding tends from the dog's viewpoint to us human psychologists viewpoint, the steps along the way there will have completely transformative ideas of what it means to be human. So a dog has a very shallow understanding. It's interesting to think that, to analogize that a dog's understanding of a human being is the same as our current understanding of the fundamental laws of physics in the universe. Oh man, okay. We spent an hour and 40 minutes talking about the simulation. I like it. Let's talk about superintelligence, at least for a little bit. And let's start at the basics. What to you is intelligence? Yeah, not to get too stuck with the definitional question. I mean, the common sense to understand, like the ability to solve complex problems, to learn from experience, to plan, to reason, some combination of things like that. Is consciousness mixed up into that or no? Is consciousness mixed up into that or is it- Well, I think it could be fairly intelligent, at least without being conscious probably. So then what is superintelligence? Yeah, that would be like something that was much more, had much more general cognitive capacity than we humans have. So if we talk about general superintelligence, it would be much faster learner be able to reason much better, make plans that are more effective at achieving its goals, say in a wide range of complex, challenging environments. In terms of, as we turn our eye to the idea of sort of existential threats from superintelligence, do you think superintelligence has to exist in the physical world or can it be digital only? Sort of, we think of our general intelligence as us humans, as an intelligence that's associated with the body that's able to interact with the world, that's able to affect the world directly with physically. I mean, digital only is perfectly fine, I think. I mean, it's physical in the sense that obviously the computers and the memories are physical. But it's capability to affect the world sort of- Could be very strong, even if it has a limited set of actuators, if it can type text on the screen or something like that, that would be, I think, ample. So in terms of the concerns of existential threat of AI, how can an AI system that's in the digital world have existential risk sort of, and what are the attack vectors for a digital system? Well, I mean, I guess maybe to take one step back, I should emphasize that I also think there's this huge positive potential from machine intelligence, including superintelligence. And I want to stress that because some of my writing has focused on what can go wrong. And when I wrote the book, Superintelligence, at that point, I felt that there was a kind of neglect of what would happen if AI succeeds, and in particular, a need to get a more granular understanding of where the pitfalls are so we can avoid them. And I think that since the book came out in 2014, there has been a much wider recognition of that, and a number of research groups are now actually working on developing, say, AI alignment techniques and so on and so forth. So I think now it's important to make sure we bring back onto the table the upside as well. And there's a little bit of a neglect now on the upside, which is, I mean, if you look at, I was talking to a friend, if you look at the amount of information that is available, or people talking, people being excited about the positive possibilities of general intelligence, that's not, it's far outnumbered by the negative possibilities in terms of our public discourse. Possibly, yeah. It's hard to measure. Can you linger on that for a little bit? What are some, to you, possible big positive impacts of general intelligence, superintelligence? Well, I mean, superintelligence, because I tend to also want to distinguish these two different contexts of thinking about AI and AI impacts, the kind of near term and long term, if you want, both of which I think are legitimate things to think about, and people should discuss both of them. But they are different and they often get mixed up. And then I get, you get confusion. I think you get simultaneously, like maybe an overhyping of the near term and an underhyping of the long term. And so I think as long as we keep them apart, we can have like two good conversations, or we can mix them together and have one bad conversation. Can you clarify just the two things we're talking about, the near term and the long term? What are the distinctions? Well, it's a blurry distinction. But say the things I wrote about in this book, superintelligence, long term, things people are worrying about today with, I don't know, algorithmic discrimination, or even things, self-driving cars and drones and stuff, more near term. And then of course, you could imagine some medium term where they kind of overlap and one evolves into the other. But at any rate, I think both, yeah, the issues look kind of somewhat different depending on which of these contexts. So I think it would be nice if we can talk about the long term and think about a positive impact or a better world because of the existence of the long term superintelligence. Do you have views of such a world? I guess it's a little hard to articulate because it seems obvious that the world has a lot of problems as it currently stands. And it's hard to think of any one of those which it wouldn't be useful to have a friendly aligned superintelligence working on. So from health to the economic system to be able to sort of improve the investment and trade and foreign policy decisions, all that kind of stuff. All that kind of stuff and a lot more. I mean, what's the killer app? Well, I don't think there is one. I think AI, especially artificial general intelligence is really the ultimate general purpose technology. So it's not that there's this one problem, this one area where it will have a big impact. But if and when it succeeds, it will really apply across the board in all fields where human creativity and intelligence and problem solving is useful, which is pretty much all fields, right? The thing that it would do is give us a lot more control over nature. It wouldn't automatically solve the problems that arise from conflict between humans, fundamentally political problems. Some subset of those might go away if you just had more resources and cooler tech, but some subset would require coordination that is not automatically achieved just by having more technological capability. But anything that's not of that sort, I think you just get an enormous boost with this kind of cognitive technology once it goes all the way. Now, again, that doesn't mean I'm thinking, oh, people don't recognize what's possible with current technology. And sometimes things get overhyped, but I mean, those are perfectly consistent views to hold the ultimate potential being enormous. And then it's a very different question of how far are we from that or what can we do with near-term technology? Yeah, so what's your intuition about the idea of intelligence explosion? So there's this, you know, when you start to think about that leap from the near term to the long term, the natural inclination, like for me, sort of building machine learning systems today, it seems like it's a lot of work to get to general intelligence. But there's some intuition of exponential growth, of exponential improvement, of intelligence explosion. Can you maybe try to elucidate, try to talk about what's your intuition about the possibility of intelligence explosion, that it won't be this gradual, slow process, there might be a phase shift? Yeah, I think it's, we don't know how explosive it will be. I think for what it's worth, it seems fairly likely to me that at some point there will be some intelligence explosion, like some period of time where progress in AI becomes extremely rapid. And roughly in the area where you might say it's kind of human-ish equivalent in core cognitive faculties, that the concept of human equivalent starts to break down when you look too closely at it. And just how explosive does something have to be for it to be called an intelligence explosion? Does it have to be overnight, literally, or a few years? But overall, I guess, if you plotted the opinions of different people in the world, I guess I would be somewhat more probability towards the intelligence explosion scenario than probably the average AI researcher, I guess. So, and then the other part of the intelligence explosion, or just forget explosion, just progress, is once you achieve that gray area of human level intelligence, is it obvious to you that we should be able to proceed beyond it to get to super intelligence? Yeah, that seems, I mean, as much as any of these things can be obvious, given we've never had one, people have different views, smart people have different views, it's like there's some degree of uncertainty that always remains for any big futuristic philosophical grand question that just we realize humans are fallible, especially about these things. But it does seem, as far as I'm judging things based on my own impressions, that it seems very unlikely that that would be a ceiling at or near human cognitive capacity. And that's such a, I don't know, that's such a special moment. It's both terrifying and exciting to create a system that's beyond our intelligence. So maybe you can step back and say, like, how does that possibility make you feel? That we can create something, it feels like there's a line beyond which it steps, it'll be able to outsmart you. And therefore, it feels like a step where we lose control. Well, I don't think the latter follows. That is, you could imagine, and in fact, this is what a number of people are working towards, making sure that we could ultimately project higher levels of problem solving ability while still making sure that they are aligned, like they are in the service of human values. I mean, so losing control, I think, is not a given that that would happen. Now you asked how it makes you feel. I mean, to some extent, I've lived with this for so long, since as long as I can remember, being an adult or even a teenager, it seemed to me obvious that at some point, AI will succeed. And so I actually misspoke, I didn't mean control. I meant, because the control problem is an interesting thing, and I think the hope is, at least we should be able to maintain control over systems that are smarter than us. But we do lose our specialness. It's sort of, we'll lose our place as the smartest, coolest thing on earth. And there's an ego involved with that, that humans aren't very good at dealing with. I mean, I value my intelligence as a human being. It seems like a big transformative step to realize there's something out there that's more intelligent. I mean, you don't see that as such a fundamentally... I think, yes, a lot. I think there are already a lot of things out there that are, I mean, certainly if you think the universe is big, there's going to be other civilizations that already have super intelligences, or that just naturally have brains the size of beach balls and are like, completely leaving us in the dust. And we haven't come face to face with them. We haven't come face to face, but I mean, that's an open question. What would happen in a kind of post-human world? Like how much day to day would these super intelligences be involved in the lives of ordinary... I mean, you could imagine some scenario where it would be more like a background thing that would help protect against some things, but you wouldn't... Like, there wouldn't be this intrusive kind of, like, making you feel bad by making clever jokes on your expense. There's like all sorts of things that maybe in the human context would feel awkward about that. You don't want to be the dumbest kid in your class. Everybody picks it. Like, a lot of those things, maybe you need to abstract away from if you're thinking about this context where we have infrastructure that is in some sense, beyond any or all humans. I mean, it's a little bit like say the scientific community as a whole, if you think of that as a mind, it's a little bit of metaphor, but I mean, obviously, it's got to be like, way more capacious than any individual. So in some sense, there is this mind like thing already out there that's just vastly more intelligent than a new individual is. And we think, okay, that's, you just accept that as a fact. That's the basic fabric of our existence is there's a super intelligence. Yeah, you get used to a lot of... I mean, there's already Google and Twitter and Facebook, these recommender systems that are the basic fabric of our... I could see them becoming... I mean, do you think of the collective intelligence of these systems as already perhaps reaching super intelligence level? Well, I mean, so here it comes to this, the concept of intelligence and the scale and what human level means. The kind of vagueness and indeterminacy of those concepts starts to dominate how you would answer that question. So, like, say the Google search engine has a very high capacity of a certain kind, like remembering and retrieving information, particularly like text or images that you have a kind of string, a word string key, like obviously superhuman at that, but a vast set of other things it can't even do at all, not just not do well. So, you have these current AI systems that are superhuman in some limited domain and then radically subhuman in all other domains. Same with a chess, like a simple computer that can multiply really large numbers, right? So, it's going to have this like one spike of super intelligence and then a kind of a zero level of capability across all other cognitive fields. Yeah, I don't necessarily think the generalness, I mean, I'm not so attached with it, but I could sort of, it's a gray area and it's a feeling, but to me, sort of alpha zero is somehow much more intelligent, much, much more intelligent than deep blue. And to say which domain, well, you could say, well, these are both just board games, they're both just able to play board games, who cares if they're gonna do better or not, but there's something about the learning, the self play that makes it, crosses over into that land of intelligence that doesn't necessarily need to be general. In the same way, Google is much closer to deep blue currently in terms of its search engine than it is to sort of the alpha zero. And the moment these recommender systems really become more like alpha zero, but being able to learn a lot without the constraints of being heavily constrained by human interaction, that seems like a special moment in time. I mean, certainly learning ability seems to be an important facet of general intelligence, that you can take some new domain that you haven't seen before, and you weren't specifically pre-programmed for, and then figure out what's going on there and eventually become really good at it. That's something alpha zero has much more of than deep blue had. And in fact, I mean, systems like alpha zero can learn not just goal, but other, in fact, probably beat deep blue in chess and so forth. So you do see this general, and it matches the intuition, we feel it's more intelligent, and it also has more of this general purpose learning ability. And if we get systems that have even more general purpose learning ability, it might also trigger an even stronger intuition that they are actually starting to get smart. So if you were to pick a future, what do you think a utopia looks like with AGI systems? Is it the neural link brain computer interface world where we're kind of really closely interlinked with AI systems? Is it possibly where AGI systems replace us completely while maintaining the values and the consciousness? Is it something like it's a completely invisible fabric, like you mentioned, a society where just AIDS and a lot of stuff that we do, like curing diseases and so on? What is the utopia if you get to pick? Yeah, I mean, it's a good question, and a deep and difficult one. I'm quite interested in it. I don't have all the answers yet, but or might never have. But I think there are some different observations one could make. One is if this scenario actually did come to pass, it would open up this vast space of possible modes of being. On one hand, material and resource constraints would just be expanded dramatically. So there would be a lot of a big pie, let's say. Also, it would enable us to do things, including to ourselves, or like that. It would just open up this much larger design space and option space than we have ever had access to in human history. So I think two things follow from that. One is that we probably would need to make a fairly fundamental rethink of what ultimately we value. Like think things through more from first principles. The context would be so different from the familiar that we could have just take what we've always been doing and then like, oh, well, we have this cleaning robot that cleans the dishes in the sink and a few other small things. I think we would have to go back to first principles. So even from the individual level, go back to the first principles of what is the meaning of life, what is happiness, what is fulfillment? And then also connected to this large space of resources is that it would be possible, and I think something we should aim for is to do well by the lights of more than one value system. That is, we wouldn't have to choose only one value criterion and say, we're going to do something that scores really high on the metric of, say, hedonism. And then is like a zero by other criteria, like kind of wire headed brain Cinevat. And it's like a lot of pleasure. That's good. But then like no beauty, no achievement. I think to some significant, not unlimited sense, but a significant sense, it would be possible to do very well by many criteria. Like maybe you could get like 98% of the best according to several criteria at the same time, given this great expansion of the option space. So have competing value systems, competing criteria as a sort of forever, just like our Democrat versus Republican, there seems to be this always multiple parties that are useful for our progress in society, even though it might seem dysfunctional inside the moment. But having the multiple value systems seems to be beneficial for, I guess, a balance of power. So that's not exactly what I have in mind that it's well, although it can be maybe in an indirect way it is. But that if you had the chance to do something that scored well, on several different metrics, our first instinct should be to do that rather than immediately leap to the thing, which ones of these value systems are we going to screw over? Let's first try to do very well by all of them. Then it might be that you can't get 100% of all, and you would have to then have the hard conversation about which one will only get 97%. There you go. There's my cynicism that all of existence is always a trade-off. But you say, maybe it's not such a bad trade-off. Let's first at least try it out. Well, this would be a distinctive context in which at least some of the constraints would be removed. So there's probably still be trade-offs in the end. It's just that we should first make sure we at least take advantage of this abundance. So in terms of thinking about this, one should think in this kind of frame of mind of generosity and inclusiveness to different value systems and see how far one can get there first. I think one could do something that would be very good according to many different criteria. We kind of talked about AGI fundamentally transforming the value system of our existence, the meaning of life. But today, what do you think is the meaning of life? The silliest or perhaps the biggest question. What's the meaning of life? What's the meaning of existence? What gives your life fulfillment, purpose, happiness, meaning? Yeah, I think these are, I guess, a bunch of different related questions in there that one can ask. Happiness, meaning, they're all different. I mean, it could imagine somebody getting a lot of happiness from something that they didn't think was meaningful. Like mindless, like watching reruns of some television series while eating junk food. Maybe some people that gives pleasure, but they wouldn't think it had a lot of meaning. Whereas conversely, something that might be quite loaded with meaning might not be very fun always. Like some difficult achievement that really helps a lot of people, maybe requires self-sacrifice and hard work. And so these things can, I think, come apart, which is something to bear in mind also if you're thinking about these utopia questions. To actually start to do some constructive thinking about that, you might have to isolate and distinguish these different kinds of things that might be valuable in different ways. Make sure you can sort of clearly perceive each one of them, and then you can think about how you can combine them. And just as you said, hopefully come up with a way to maximize all of them together. Yeah, or at least get, I mean, maximize or get like a very high score on a wide range of them, even if not literally all. You can always come up with values that are exactly opposed to one another, right? But I think for many values, they're kind of opposed if you place them within a certain dimensionality of your space. Like there are shapes that you can't untangle in a given dimensionality, but if you start adding dimensions, then it might in many cases just be that they are easy to pull apart. And you could, so we'll see how much space there is for that, but I think that there could be a lot in this context of radical abundance if ever we get to that. I don't think there's a better way to end it, Nick. You've influenced a huge number of people to work on what could very well be the most important problems of our time. So it's a huge honor. Thank you so much for talking to me. Well, thank you for coming by, Lex. That was fun. Thank you. Thanks for listening to this conversation with Nick Bostrom and thank you to our presenting sponsor, Cash App. Please consider supporting the podcast by downloading Cash App and using code LEXPODCAST. If you enjoy this podcast, subscribe on YouTube, review it with five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Nick Bostrom. Our approach to existential risks cannot be one of trial and error. There's no opportunity to learn from errors. The reactive approach, see what happens, limit damages, and learn from experience is unworkable. Rather, we must take a proactive approach. This requires foresight to anticipate new types of threats and a willingness to take decisive preventative action and to bear the costs, moral and economic, of such actions. Thank you for listening and hope to see you next time.

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Richard Craib: WallStreetBets, Numerai, and the Future of Stock Trading | Lex Fridman Podcast #159

The following is a conversation with Richard Crabe, founder of Numeri, which is a crowdsourced hedge fund, very much in the spirit of Wall Street Bets, but where the trading is done not directly by humans, but by artificial intelligence systems submitted by those humans. It's a fascinating and extremely difficult machine learning competition where the incentives of everybody is aligned, the code is kept and owned by the people who develop it, the data, anonymized data, is very well organized and made freely available. I think this kind of idea has a chance to change the nature of stock trading and even just money management in general by empowering people who are interested in trading stocks with the modern and quickly advancing tools of machine learning. Quick mention of our sponsors Audible Audiobooks, Trial Labs Machine Learning Company, Blinkist app that summarizes books, and Athletic Greens, all-in-one nutrition drink. Click the sponsor links to get a discount and to support this podcast. As a side note, let me say that this whole set of events around GameStop and Wall Street Bets has been really inspiring to me as a demonstration that a distributed system, a large number of regular people are able to coordinate and collaborate in taking on the elite centralized power structures, especially when those elites are misbehaving. I believe that power in as many cases as possible should be distributed, and in this case the internet as it is for many cases is the fundamental enabler of that power. And at the core what the internet in its distributed nature represents is freedom. Of course the thing about freedom is it enables chaos or progress or sometimes both. And that's kind of the point of the thing. Freedom is empowering but ultimately unpredictable. And I think in the end freedom wins. If you enjoy this podcast subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now here's my conversation with Richard Krabe. From your perspective can you summarize the important events around this amazing saga that we've been living through of Wall Street Bets, the subreddit and GameStop, and in general just what are your thoughts about it from a technical to the philosophical level? I think it's amazing. It's like my favorite story ever. Like when I was reading about it I was like this is the best. And it's also connected with my company which we can talk about. But what I liked about it is I like decentralized coordination and looking at the mechanisms that these are Wall Street Bets users use to hype each other up, to get excited, to prove that they bought the stock and they're holding. And then also to see that how big of an impact that that decentralized coordination had. It really was a big deal. Were you impressed by the distributed coordination, the collaboration amongst like, I don't know what the numbers are, I know in numerized looking at the data. After all of this is over and done it'd be interesting to see like from a large scale distributed system perspective to see how everything played out. But just from your current perspective what we know, is it obvious to you that such incredible level of coordination could happen where a lot of people come together in a distributed sense there's an emergent behavior that happens after that? No, it's not at all obvious. And one of the reasons is the lack of credibility. To coordinate with someone you need to make credible contracts or credible claims. So if you have a username on our Wall Street Bets like some of them are, like DeepFuckingValue is one of them. That's an actual username by the way we're talking about. There's a website called Reddit and there's subreddits on it. And a lot of people, mostly anonymous, I think for the most part anonymous, can create user accounts and then can just talk on forum like style boards. You should know what Reddit is. If you don't know what Reddit is, check it out. If you don't know what Reddit is, maybe go to the aww subreddit first, AWW with cute pictures of cats and dogs. That's my recommendation. Anyway. Yeah, that'd be a good start to Reddit. When you get into it more, go to our Wall Street Bets. It gets dark quickly. We'll probably talk about that too. So yeah, so there's these users and there's no contracts like you're saying. There's no contracts. The users are anonymous. But there are little things that do help. So for example, if you've posted a really good investment idea in the past, that exists on Reddit as well. And it might have lots of upvotes. And that's also kind of like giving credibility to your next thing. And then they're also putting up screenshots like this. Here's the trades I've made and here's a screenshot. Now you could fake the screenshot. But still, it seems like if you've got a lot of karma and you've had a good performance on the community, it somehow becomes credible enough for other people to be like, you know what, he actually probably did put a million dollars into this. And you know what, I can follow that trade easily. And there's a bunch of people like that. So you're kind of integrating all that information together yourself to see like, huh, there's something happening here. And then you jump onto this little boat of like behavior, like, we should buy the stock or sell the stock. And then another person jumps on, another person jumps on. And all of a sudden you have just a huge number of people behaving in the same direction. It's like flock of whatever birds. Exactly. What was strange with this one, it wasn't just, let's all buy Tesla. We love Elon, we love Tesla, let's all buy Tesla. Because that we've heard before, right? Everybody likes Tesla. Now they do. So what they did with this, in this case, they're buying a stock that was bad. They're buying it because it was bad. And that's really weird, because that's a little bit too galaxy brain for a decentralized community. How did they come up with it? How did they know that was the right one? And the reason they liked it is because it had really, really high short interest. It had been shorted more than its own float, I believe. And so they figured out that if they all bought this bad stock, they could short squeeze some hedge funds. And those hedge funds would have to capitulate and buy the stock at really, really high prices. And we should say that shorted means that these are a bunch of people, when you short a stock, you're betting on the, you're predicting that the stock is going to go down, and then you will make money if it does. And then what's a short squeeze? It's really that if you are a hedge fund, and you take a big short position in a company, there's a certain level at which you can't sustain holding that position. There's no limit to how high a stock can go, but there is a limit to how low it can go, right? So if you short something, you have infinite loss potential. And if the stock doubles overnight, like GameStop did, you're putting a lot of stress on that hedge fund. And that hedge fund manager might have to say, you know what, I have to get out of the trade. And the only way to get out is to buy the bad stock that they don't want, like they believe will go down. So it's an interesting situation, particularly because it's not zero sum. If you say, let's all get together and make a bubble in watermelons, you buy a bunch of watermelons, the price goes up, it comes down again. It's a zero sum game. If someone's already shorted a stock, and you can make them short squeeze, it's actually a positive sum game. So yes, some Redditors will make a lot of money, some will lose a lot, but actually the whole group will make money. And that's really why it was such a clever thing for them to do. And coupled with the fact that shorting, I mean, maybe you can push back, but to me always from an outsider's perspective, seemed, I hope I'm not using too strong of a word, but it seemed almost unethical, maybe not unethical, maybe it's just an asshole thing to do. Okay, I'm speaking not from an economics or financial perspective, I'm speaking from just somebody who loves, I'm a fan of a lot of people, I love celebrating the success of a lot of people. And this is like the stock market equivalent of like, haters. I know that's not what it is. I know that there's efficient, you want to have an economy efficient mechanism for punishing sort of overhyped, overvalued things. That's what shorting I guess is designed for. But it just always felt like these people are just, because they're not just betting on the loss of the company, it feels like they're also using their leverage and power to manipulate media or just to write articles or just to hate on you on social media. And you get to see that with Elon Musk and so on. So this is like the man, so people like hedge funds that were shorting are like the sort of embodiment of the evil or just the bad guy, the overpowerful that's misusing their power. And here's the crowd, the people, they're standing up and rising up. So it's not just that they were able to collaborate on Wall Street bets to sort of effectively make money for themselves. It's also that this is like a symbol of the people getting together and fighting the centralized elites, the powerful. And that, I don't know what your thoughts are about that in general. At this stage, it feels like that's really exciting that people have power, just like regular people have power. At the same time, it's scary a little bit because just studying history, people can be manipulated by charismatic leaders. And so just like Elon right now is manipulating, encouraging people to buy Dogecoin or whatever, there can be good charismatic leaders and there can be bad charismatic leaders. And so it's nerve wracking. It's a little bit scary how much power Subreddit can have to destroy somebody. Because right now we're celebrating there might be attacking or destroying somebody that everybody doesn't like. But what if they attack somebody that is actually good for this world? So that, and that's kind of the awesomeness and the price of freedom. It's like, it could destroy the world or it can save the world. But at this stage, it feels like, I don't know, overall, when you sit back, do you think this was just a positive wave of emergent behavior? Is there something negative about what happened? Well, yeah, the cool thing is the Reddit people weren't doing anything exotic. It was a creative trade, but it wasn't exotic. It wasn't, it was just buying the stock. Okay, maybe they bought some options too. But it was the hedge fund that was doing the exotic thing. So I like that. It's hard to say, well, we've got together and we've pooled all our money together. And now there's a company out there that's worth more. What's wrong with that? But it doesn't talk about the motivations, which is, and then we destroyed some hedge funds in the process. Is there something to be said about the humor and the, I don't know, the edginess, sometimes viciousness of that subreddit? I haven't looked at it too much, but it feels like people can be quite aggressive on there. So is there, what is that? Is that what freedom looks like? I think it does. Yeah, you definitely need to let people, one of the things that people have compared it to is the Occupy Wall Street, which is, let's say, some very sincere liberals, like 23 years old, whatever. And they go out with signs and they have some kind of case to make. But this isn't sincere, really. It's like a little bit more nihilistic, a little bit more YOLO, and therefore a little bit more scary. Because who's scared of the Occupy Wall Street people with the signs? Nobody. But these hedge funds really are scared. I was scared of the Wall Street bats people. I'm still scared of them. Yeah, the anonymity is a bit terrifying and exciting. Yeah. I mean, yeah, I don't know what to do with it. I've been following events in Russia, for example. It's like there's a struggle between centralized power and the distributed. I mean, that's the struggle of the history of human civilization, right? But this on the internet, just that you can multiply people, like some of them don't have to be real. You can probably create bots. It starts getting me, as a programmer, I start to think like, hmm, me as one person, how much chaos can I create by writing some bots? And I'm sure I'm not the only one thinking that. I'm sure there's hundreds, thousands of good developers out there listening to this, thinking the same thing. And then as that develops further and further in the next decade or two, what impact does that have on financial markets, on just destruction of reputations or politics, the bickering of left and right political discourse, the dynamics of that being manipulated by, people talk about Russian bots or whatever. We're probably in the very early stage of that, right? Exactly. And this is a good example. Do you have a sense that most of Wall Street Bets folks are actually individual people? That's the feeling I have, is there's just individual, maybe young investors doing a little bit of an investment, but just on a large scale? Yeah, exactly. The reason I found out, I've known about Wall Street Bets for a while, but the reason I found out about GameStop was this, I met somebody at a party who told me about it and he was like 21 years old and he's like, it's going to go up 100% in the next one day. Are we talking about last year? This was probably, no, this was, yeah, a few days ago. Oh, okay. Yeah, it was like maybe two weeks ago or something. So, it was already high, GameStop. But it was just strange to me that there was someone telling me at a party how to trade stocks who was like 21 years old and started to look into it. And he did make, he made 140% in one day. He was right. And now he's supercharged. He's a little bit wealthier and now he's going to wait for the next thing. And this decentralized entity is just going to get bigger and bigger. And they're going to, together, search for the next thing. So, there's thousands of folks like him and they're going to probably search for the next thing to attack. People that have power in this world that sit there with power right now in government and in finance, in any kind of position are probably a little bit scared right now. And honestly, that's probably a little bit good. It's dangerous, but it's good. Yeah, it certainly makes you think twice about shorting. It certainly makes you think twice about putting a lot of money into a short. Like, I don't know, I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. I don't know. These funds put a lot into one or two names. And so, it was very, very badly risk managed. Do you think shorting is, can you speak at a high level, just for you as a person? Is it good for the world? Is it good for markets? I do think that there are two kinds of shorting. Evil shorting and chill shorting. Okay. Evil shorting is what Melvin Capital was doing. And it's like, you put a huge position down, you get all your buddies to also short it, and you start making press and trying to bring this company down. And I don't think, in some cases, you go out to fraudulent companies and say, this company is a fraud. Maybe that's okay. But they weren't even saying GameStop was fraudulent, they were just saying, it's a bad company, and we're going to bring it to the ground, bring it to its knees. A quant fund, like Numerai, we always have lots of positions, and we never have a position that's more than 1% of our fund. So, we actually have, right now, 250 shorts. I don't know any of them, except for one, because it was one of the meme stocks. Yeah. But we're shorting them, not to make them go, we don't even want them to go down necessarily. That sounds a bit strange, I say that, but we just want them to not go up as much as our longs. Right. So, by shorting a little bit, we can actually go long more in the things we do believe in. So, when we were going long in Tesla, we could do it with more money than we had, because we would borrow from banks, who would lend us money, because we had longs and shorts, because we didn't have market exposure, we didn't have market risk. And so, I think that's a good thing, because that means, you know, we can short the oil companies and go long Tesla and make the future come forward faster. And I do think that's not a bad thing. So, we talked about this incredible distributed system created by Wall Street Bets, and then there's a platform, which is Robinhood, which allows investors to efficiently, as far as you can correct me if I'm wrong, but you know, there's those and there's others in this new MRI that allow you to make it accessible for people to invest. But that said, Robinhood was in a centralized in a centralized way, applied its power to restrict trading on the stocks that we're referring to. Do you have a thought on actually like the things that happened? I don't know how much you were paying attention to sort of the shadiness around the whole thing. Do you think it was forced to do it? Or was there something shady going on? What are your thoughts in general? Well, I think I want to see the alternate history. Like, I want to see the counterfactual history of them not doing that. How bad would it have gotten for hedge funds? How much more damage could have been done if the momentum of these short squeezes could continue? What happens when there are short squeezes, even if they're in a few stocks, they affect kind of all the other shorts too. And suddenly, brokers are saying things like, you need to put up more collateral. So we had a short. It wasn't GameStop, luckily, it was BlackBerry. And it went up like 100% in a day. It was one of these meme stocks, super bad company. The AIs don't like it. Okay, the AIs think it's going down. What's a meme stock? A meme stock is kind of a new term for these stocks that catch memetic momentum on Reddit. Yeah. And so the meme stocks were GameStop, the biggest one, GameStonk, as Elon calls it, AMC. And BlackBerry was one, Nokia was one. So these are high short interest stocks as well. So these are targeted stocks that some people say, oh, isn't it adorable that these people are investing money in these companies that are, you know, nostalgic? It's like, you go into the AMC movie theater, it's like nostalgic. It's like, no, that's not why they're doing it. It's that they had a lot of short interest. That was the main thing. And so they were high chance of short squeeze. In saying, I would love to see an alternate history. Do you have a sense that that, what is your prediction of what that history would have looked like? Well, you wouldn't have needed very many more days of that kind of chaos to hurt hedge funds. I think it's underrated how damaging it could have been. Because when your shorts go up, your collateral requirements for them go up. It's similar to Robinhood. Like we have a prime broker that said to us, you need to put up, you know, like $40 per $100 of short exposure. And then the next day they said, actually, you have to put up, you know, all of it, 100%. And we were like, what? But if that happens to all the commonly held hedge fund shorts, because they're all kind of holding the same things. If that happens, not only do you have to cover the short, which means you're buying the bad companies, you need to sell your good companies in order to cover the short. So suddenly, like all the good companies, all the ones that the hedge funds like are coming down, and all the ones that the hedge funds hate are going up in a cascading way. So I believe that if you could have had a few more days of GameStop doubling, AMC doubling, you would have had more and more hedge fund deleveraging. But so hedge funds, I mean, they get a lot of shit, but do you have a sense that they do some good for the world? I mean, ultimately, so okay, first of all, Wall Street Bets itself is kind of distributed hedge fund, Numerize is a kind of hedge fund. So hedge funds are a very broad category. I mean, like if some of those were destroyed, would that be good for the world? Or would there be coupled with the destroying the evil shorting? Would there be just a lot of pain in terms of investment in good companies? Yeah. A thing I like to tell people, if they hate hedge funds, is I don't think you want to rerun American economic history without hedge funds. So en masse, they're good. Yeah, you really wouldn't want to. Because hedge funds are kind of like picking up, they're making liquidity, right, in stocks. And so if you love venture capitalists, they're investing in new technology, it's so good. You have to also kind of like hedge funds, because they're the reason venture capitalists exist, because their companies can have a liquidity event when they go to the public markets. So it's kind of essential that we have them. There are many different kinds of them. I believe we could maybe get away with only having an AI hedge fund. But we don't necessarily need these evil billions type hedge funds that make the media and try to kill companies. But we definitely need hedge funds. Maybe from your perspective, because you run such an organization, and Vlad, the CEO of Robinhood, sort of had to make decisions really quickly, probably had to wake up in the middle of the night kind of thing. You know, and he also had a conversation with Elon Musk on Clubhouse, which I just signed up for. It was a fascinating, one of the great journalistic performances of our time with Elon Musk. Pulitzer Prize for Elon. How hilarious would it be if he gets a Pulitzer Prize? And then his Wikipedia would be like, journalist and part-time entrepreneur. Business magnate. You know, I don't know if you can comment on any aspects of that. But like, if you were Vlad, how would you do things differently? What are your thoughts about his interaction with Elon? How he should have played it differently? Like, I guess there's a lot of aspects to this interaction. One is about transparency. Like, how much do you want to tell people about really what went down? There's NDAs potentially involved. How much in private do you want to push back and say, no, fuck you, to centralize power? Whatever the phone calls you're getting, which I'm sure he was getting some kind of phone calls that might not be contractual. Like, it's not contracts that are forcing him, but he was being, what do you call it, like pressured to behave in certain kinds of ways from all kinds of directions. Like, what do you take from this whole situation? I was very excited to see Vlad's response. I mean, it's pretty cool to have him talk to Elon. And one of the things that struck me in the first few seconds of Vlad speaking was, like, I was like, is Vlad like a boomer? Like, but here we are, like, he seemed like a 55 year old man talking to a 20 year old. Elon was like the 20 year old. And he's like the 55 year old man. You can see why Citadel and him are buddies, right? Like you can. You can see why. It's like, this is a nice, it's not a bad thing. It's like, he's got a respectable, professional attitude. Well, he also tried to do like a jokey thing. Like, no, we're not being ageist here. Boomer. But like, like a 60 year old CEO of Bank of America would try to make a joke for the kids. That's what Vlad sounded like. Yeah. I was like, what is this? This guy's like, what is he, 30? Yeah. And I'm like, this is weird. But I think maybe that's also what I like about Elon's kind of influence on American business. It's like, he's super like, anti the professional. Like, why, why say, why say, you know, 100 words about nothing? And so I liked how he was cutting in and saying, Vlad, what do you mean? Spill the beans, bro. Yeah. So you don't have to be courteous. It's like the first principles thinking, it's like, what the hell happened? And let's just talk like normal people. The problem, of course, is, you know, for Elon, it's cost him, what is it, tens of millions of dollars, his tweeting like that. But perhaps it's a worthy price to pay, because ultimately, there's something magical about just being real and honest, and just going off the cuff and making mistakes and paying for them. But just being real. And then moments like this, that was an opportunity for Vlad to be that, and it felt like he wasn't. Do you think we'll ever find out what really went down if there was something shady underneath it all? Yeah, I mean, it would be sad if nothing shady happened. Right. But his presence made it shady. Sometimes I feel like that with Mark Zuckerberg, the CEO of Facebook. Sometimes I feel like, yeah, there's a lot of shitty things that Facebook is doing. But sometimes I think he makes it look worse by the way he presents himself about those things. I honestly think that a large amount of people at Facebook just have a huge, unstable, chaotic system. And they're all, not all, but a mass are trying to do good with this chaotic system. But the presentation is like, it sounds like there's a lot of backroom conversations that are trying to manipulate people. And there's something about the realness that Elon has that it feels like CEOs should have and Vlad had that opportunity. I think Mark Zuckerberg had that too, when he was younger. And somebody said, you got to be more professional, man. You can't say, you know, lol to an interview. And then suddenly he became like this distant person that was hot. Like, you'd rather have him make mistakes, but be honest, than be like professional and never make mistakes. Yeah, one of the difficult hires, I think, is like marketing people or like PR people is you have to hire people that get the fact that you can say lol on an interview, or, like, you know, take risks, as opposed to what the PR I've talked to quite a few big CEOs and the people around them are trying to constantly minimize risk of like, what if he says the wrong thing? What if she says the wrong thing? It's like, what? Be careful. It's constantly like, ooh, like, I don't know. And there's this nervous energy that builds up over time with larger, larger teams, where the whole thing, like I visited YouTube, for example, everybody I talked at YouTube, incredible engineering, an incredible system, but everybody's scared. Like, let's be, let's be honest about this, like, madness that we have going on of huge amounts of video that we can't possibly ever handle. There's a bunch of hate on YouTube. There's this chaos of comments, bunch of conspiracy theories, some of which might be true. And then just like this mess that we're dealing with. And it's exciting. It's beautiful. It's a place where like democratizes education, all that kind of stuff. And instead, they're all like, sitting in like, trying to be very polite and saying like, well, we're just want to improve the health of our platform. Like, all right, man, let's just be real. Let's both advertise how amazing this freaking thing is. But also to say like, we don't know what we're doing. We have all these Nazis posting videos on YouTube. We don't know how to like, handle it. And just being real like that, I suppose that's just the skill. Maybe it can't be taught. But over time, the whatever the dynamics of the company is, it does seem like Zuckerberg and others get worn down. They just get tired. Yeah. They get tired of not being real, of not being real, which is sad. So let's talk about Numeri, which is an incredible company, system, idea, I think, but good place to start. What is Numeri? And how does it work? So Numeri is the first hedge fund that gives away all of its data. So this is like, probably the last thing a hedge fund would do, right? Why would we give away a data? It's like, giving away your edge. But the reason we do it is because we're looking for people to model our data. And the way we do it is by obfuscating the data. So when you get, when you look at numerized data that you can download for free, it just looks like, like a million rows and of numbers between zero and one. And you have no idea what the columns mean, but you do know that if you're good at machine learning or have done regressions before, you know that I can still find patterns in this data, even though I don't know what the features mean. And the data itself is time series data. And even though it's obfuscated, anonymized, what is the source data? Like, approximately, what are we talking about? So we are buying data from lots of different data vendors. And they would also never want us to share that data. So we have strict contracts with them. But that's the kind of data you could never buy yourself unless you had maybe a million dollars a year of budget to buy data. So what's happened with the hedge fund industry is you have a lot of talented people who used to be able to trade and still can trade, but now they have such a data disadvantage. It would never make sense for them to trade themselves. But Numeri, by giving away this obfuscated data, we can give them a really, really high quality data set that would otherwise be very expensive. And they can use whatever new machine learning technique they want to find patterns in that data that we can use in our hedge fund. And so how much variety is there in underlying data? We're talking about, I apologize if I'm using the wrong terms, but one is just like the stock price. The other, there's like options and all that kind of stuff, like the, what are they called? Order books or whatever. Is there maybe other totally unrelated to directly to the stock market data, like natural language as well, all that kind of stuff? Yeah, we were really focused on stock data that's specific to stocks. So things like, you can have like a P, every stock has like a PE ratio for some stocks. It's not as meaningful, but every stock has that. Every stock has one year momentum, how much they went up in the last year. But those are very common factors, but we try to get lots and lots of those factors that we have for many, many years, like 15, 20 years history. And then the setup of the problem is commonly in quant called like cross-sectional global equity. You're not really trying to say, I want, I believe the stock will go up. You're trying to say the relative position of this stock in feature space makes it not a bad buy in a portfolio. So it captures some period of time and you're trying to find the patterns, the dynamics captured by the data of that period of time in order to make short-term predictions about what's going to happen. Yeah. So our predictions are also not that short. We're not really caring about things like order books and tech data, not high frequency at all. We're actually holding things for quite a bit longer. So our prediction time horizon is about one month. We ended up holding stocks for maybe like three or four months. So I kind of believe that's a little bit more like investing than kind of plumbing, like to go long a stock that's mispriced on one exchange and short on another exchange, that's just arbitrage. But what we're trying to do is really know something more about the longer term future of the stock. Yeah. So from the patterns, from these like periods of time series data, you're trying to understand something fundamental about the stock, not like about deep value, about like what is big in the context of the market, is it underpriced, overpriced, all that kind of stuff. So like this is about investing. It's not about just like you said, high frequency trading, which I think is a fascinating open question from a machine learning perspective. But just to like sort of build on that, so you've anonymized the data and now you're giving away the data. And then now anyone can try to build algorithms that make investing decisions on top of that data or predictions on the top of that data. Exactly. And so that's, what does that look like? What's the goal of that? What are the underlying principles of that? So the first thing is, we could obviously model that data in-house, right? We can make an XGBoost model on the data and that would be quite good too. But what we're trying to do is by opening it up and letting anybody participate, we can do quite a lot better than if we modeled it ourselves. And a lot better on the stock market doesn't need to be very much. Like it really matters, the difference between if you can make 10 and 12% in an equity market, and if you can make 10 and 12% in an equity market neutral hedge fund, because usually you're charging 2% fees. So if you can do 2% better, that's like all your fees, it's worth it. So we're trying to make sure that we always have the best possible model as new machine learning libraries come out, new techniques come out, they get automatically synthesized. Like if there's a great paper on supervised learning, someone on Numeri will figure out how to use it on Numeri's data. And is there an ensemble of models going on? Or is it more towards kind of like one or two or three like best performing models? So the way we decide on how to weight all of the predictions together is by how much the users are staking on them. How much of the cryptocurrency that they're putting behind their models. So they're saying, I believe in my model, you can trust me because I'm going to put skin in the game. And so we can take the stake weighted predictions from all our users, add those together, average those together. And that's a much better model than any one model in the sum, because ensembling a lot of models together is kind of the key thing you need to do in investing. Yeah, so you're putting, there's a kind of duality from the user, from the perspective of a machine learning engineer, where you're, it's both a competition, just a really interesting, difficult machine learning problem. And it's a way to invest algorithmically. So like, and but the way to invest algorithmically also is a way to put skin in the game that communicates to you that you're, the quality of the algorithm, and also forces you to really be serious about the models that you build. So it's like, everything just works nicely together. Like, I guess one way to say that is the interests are aligned. Okay, so it's just like poker is not fun when it's like for very low stakes. The higher the stakes, the more the dynamics of the system starts playing out correctly. Like, as a small side note, is there something you can say about which kind, looking at the big broad view of machine learning today or AI, what kind of algorithms seem to do good in these kinds of competitions at this time? Is there some universal thing you can say, like neural networks suck, recurrent neural networks suck, transformers suck, or they're awesome, like old school, sort of more basic kind of classifiers are better? Is there some kind of conclusion so far that you can say? There is, there's definitely something pretty nice about tree models, like XGBoost. And they just seem to work pretty nicely on this type of data. So out of the box, if you're trying to come 100th in the competition, in the tournament, maybe you would try to use that. But what's particularly interesting about the problem that not many people understand, if you're familiar with machine learning, this typically will surprise you when you model our data. So one of the things that you look at in finance is you don't want to be too exposed to any one risk. Like, even if the best sector in the world to invest in over the last 10 years was tech, you would not, does not mean you should put all of your money into tech. So if you train a model, it would say put all your money into tech, it's super good. But what you want to do is actually be very careful of how much of this exposure you have to certain features. So on Numerai, what a lot of people figure out is, actually, if you train a model on this kind of data, you want to somehow neutralize or minimize your exposure to these certain features, which is unusual, because if you did train a stoplight or stop street detection on computer vision, your favorite feature, let's say you could, and you have an auto encoder and it's figuring out, okay, it's going to be red, and it's going to be white. That's the last thing you want to be, you want to reduce your exposure to. Why would you reduce your exposure to the thing that's helping you, your model the most? And that's actually this counterintuitive thing you have to do with machine learning on financial data. So reducing, it's reducing your exposure would help you generalize the things that are, so basically financial data has a large amount of patterns that appeared in the past, and also a large amount of patterns that have not appeared in the past. And so like in that sense, you have to reduce the exposure to red lights, to the color red. That's interesting, but how much of this is art and how much of it is science from your perspective so far, in terms of as you start to climb from the climb from the hundredth position to the 95th in the competition? Yeah, well, if you do make yourself super exposed to one or two features, you can have a lot of volatility when you're playing Numerai. You could maybe very rapidly rise to be high if you were getting lucky. Yes. And that's a bit like the stock market. Sure, take on massive risk exposure, put all your money into one stock and you might make a hundred percent, but it doesn't in the long run work out very well. And so the best users are trying to stay high for as long as possible, not necessarily try to be first for a little bit. So me, a developer, machine learning researcher, how do I, Lex Friedman, participate in this competition and how do others, which I'm sure there'll be a lot of others interested in participating in this competition. What are, let's see, there's like a million questions, but like first one is how do I get started? Well, you can go to numerai.ai, sign up, download the data. And on the data is pretty small. In the data pack you download, there's like an example script, Python script that just builds a XGBoost model very quickly from the data. And so in a very short time, you can have an example model. Is it a particular structure? Like what, is this model then submitted somewhere? So there needs to be some kind of structure that communicates with some kind of API. Like how does the whole, how does your model, once you built it, once you create a little baby Frankenstein, how does it then live in its world? Okay, well, we want you to keep your baby Frankenstein at home and take care of it. We don't want it. So we, you never upload your model to us. You always only giving us predictions. So we never see the code that wrote your model, which is pretty cool. That our whole hedge fund is built from models where we've never, ever seen the code. But it's important for the users because it's their IP, they want to give it to us. That's brilliant. So they've got it themselves, but they can basically almost like license the predictions from that model to us. License the prediction, yeah. So what some users do is they set up a compute server and we call it numeric compute. It's like a little AWS kind of image. And you can automate this process. So we can ping you, we can be like, we need more predictions now. And then you send it to us. Okay, cool. So that's, is that described somewhere like what the preferred is the AWS or whether another cloud platform? Is there, I mean, is there sort of specific technical things you want to say that comes to mind that is a good path for getting started? So download the data, maybe play around, see if you can modify the basic algorithm provided in the example. And then you would set up a little server on AWS that then runs this model and takes pings and then makes predictions. And so how does your own money actually come into play doing the stake of cryptocurrency? Yeah, so you don't have to stake. You can start without staking and many users might try for months without staking anything at all to see if their model works on the real life data, right. And is not overfit. But then you can get numeraire many different ways. You can buy it on, you can buy some on Coinbase, you can buy some on Uniswap, you can buy some on Binance. So what did you say? This is how do you pronounce it? So this is the Numerai cryptocurrency? Yeah. NMR. NMR. What's you just say NMR? It is technically called numeraire. Numeraire. I like it. Yeah. But NMR is simple. NMR, numeraire. OK, so and you could buy it, you know, basically anywhere. Yeah. So it's a bit strange because sometimes people are like, is this like pay to play? Right. And it's like, yeah, you need to put some money down to show us you believe in your model. But weirdly, we're not selling you the, like you can't buy the cryptocurrency from us. Right. It's like, it's also we never, if you do badly, we destroy your cryptocurrency. OK, that's not good, right? You don't want it to be destroyed. But what's good about it is it's also not coming to us. Right. So it's not like we win when you lose or something like that, like we're the house, like we're definitely on the same team. Yes. You're helping us make a hedge fund that's never been done before. Yeah. So, again, interests are aligned. There's no there's no tension there at all, which is really fascinating. You're giving away everything and then the IP is owned by the code. You never share the code. That's fascinating. So since I have you here and you said a hundred, I didn't ask out of how many. So we'll just but if I then once you get started and you find this interesting, how do you then win or do well, but also how do you potentially try to win if this is something you want to take on seriously from the machine learning perspective, not from a financial perspective? Yeah, I think the first of all, you want to talk to the community. People are pretty open. We give out really interesting scripts and ideas for things you might want to try. But you're also going to need a lot of compute probably. And so some of the best users are, you know, actually the very first time someone won on Numera, I wrote them a personal email. It's like, you know, you've won some money. We're so excited to give you $300. And then they said, I spend way more on the compute. So this is fundamentally a machine learning problem first, I think, is this is one of the exciting things. I don't know if we'll, how many ways we can approach this, but really this is less about kind of, no offense, but like finance people, finance minded people, they're also, I'm sure great people, but it feels like from the community that I've experienced, these are people who see finances as a fascinating problem space, source of data, but ultimately they're machine learning people or AI people, which is a very different kind of flavor of community. And I mean, I should say to that, I'd love to participate in this and I will participate in this. And I'd love to hear from other people. If you're listening to this, if you're a machine learning person, you should participate in it and tell me, give me some hints, how I should do it. Tell me, give me some hints, how I can do well at this thing. Because this Boomer, I'm not sure I still got it, but because some of it is, it's like Kaggle competitions. Some of it is certainly set of ideas, like research ideas, like fundamental innovation, but I'm sure some of it is like deeply understanding, getting an intuition about the data. And then a lot of it will be like figuring out like what works, like tricks. I mean, you could argue most of deep learning research is just tricks on top of tricks, but there's some of it is just the art of getting to know how to work in a really difficult machine learning problem. And I think what's important, the importance difference with something like a Kaggle competition, where they'll set up this kind of toy problem and then there will be an out of sample test, like, Hey, you did well out of sample. And this is like, okay, cool. But what's cool with Numerai is the out of sample is the real life stock market. We don't even know, like we don't know the answer to the problem. We don't, like you'll have to find out live. And so we've had users who've submitted every week for like four years, because it's kind of, we say it's the hardest data science problem on the planet, right? And it sounds maybe sounds like maybe a bit too much for like a marketing thing, but it's the hardest because it's the stock market. It's like, literally, there are like billions of dollars at stake. And like, no one's like letting it be inefficient on purpose. So if you can find something that works on Numerai, you really have something that that is like working on the real stock market. Yeah, because there's like humans involved in the stock market. I mean, that's, you know, you could argue there might be harder data sets, like maybe predicting the weather, all those kinds of things. But the fundamental statement here is, which I like, I was thinking, like, is this really the hardest data science problem? And you start thinking about that, but ultimately also boils down to a problem where the data is accessible. It's made accessible, made really easy and efficient at like submitting algorithms. So it's not just, you know, it's not about the data being out there, like the weather. It's about making the data super accessible, making the ability to community around it. Like, this is what ImageNet did. Exactly. Like, it's not just, there's always images. The point is, you aggregate them together, you give it a little title, this is a community. And that was one of the hardest, right, for a time and most important data science problems in the world, because it was accessible, because it was made sort of, like, there's mechanisms by which, like standards and mechanisms by which to judge your performance, all those kinds of things. And NumerEyes, I actually step up from that. Is there something more you can say about why, from your perspective, it's the hardest problem in the world? I mean, you said it's connected to the market. So if you can find a pattern in the market, that's a really difficult thing to do, because a lot of people are trying to do it. Exactly. But there's also the biggest one is it's non-stationary time series. We've tried to regularize the data so you can find patterns by doing certain things to the features and the target. But ultimately, you're in a space where you don't, there's no guarantees that the out of sample distributions will conform to any of the training data. And every single era, which we call on the website, like every single era in the data, which is like sort of showing you the order of the time, even the training data has the same dislocations. And so, yeah, there's so many things that you might want to try. There's an unlimited possible number of models, right? And so, by having it be open, we can at least search that space. Zooming back out to the philosophical, you said that Numeri is very much like Wall Street Bets. I think it'd be interesting to dig in why you think so. I think you're speaking to the distributed nature of the two and the power of the people nature of the two. So, maybe can you speak to the similarities and the differences and in which way is Numeri more powerful? In which way is Wall Street Bets more powerful? Yeah, this is why the Wall Street Bets story is so interesting to me because it's like, feels like we're connected. And looking at how, just looking at the form of Wall Street Bets, I was talking earlier about how can you make credible claims? You're anonymous. Okay, well, maybe you can take a screenshot. Or maybe you can upvote someone. Maybe you can have karma on Reddit. And those kinds of things make this emerging thing possible. Numeri, it didn't work at all when we started. It didn't work at all. Why? People made multiple accounts. They made really random models and hope they would get lucky. And some of them did. Staking was our solution to could we make it so that we could trust, we could know which model people believed in the most. And we could weight models that had high stake more and effectively coordinate this group of people to be like, well, actually, there's no incentive to creating bot accounts anymore. Either I stake my accounts, in which case I should believe in them because I could lose my stake, or I don't. And that's a very powerful thing that having a negative incentive and a positive incentive can make things a lot better. And staking is like this is a very powerful thing. And I think it's a very powerful thing. Staking is like this is this really nice, like key thing about blockchain. It's like something special you can do where they're not even trusting us with their stake in some ways. They're trusting the blockchain, right? So the incentives, like you say, it's about making these perfect incentives so that you can have coordination to solve one problem. And nowadays, I sleep easy, because I have less money in my own hedge fund than our users are staking on their models. That's powerful. In some sense, from a human psychology perspective, it's fascinating that Wall Street bets worked at all, right? That amidst that chaos, emerging behavior, like behavior that made sense emerged. It would be fascinating to think if numerized style of staking could then be transferred to places like Reddit, and not necessarily for financial investments. But I wish sometimes people would have to stake something in the comments they make on the internet. That's the problem with anonymity, is like anonymity is freedom and power that you don't have to, you can speak your mind, but it's too easy to just be shitty. Exactly. So this, I mean, you're making me realize from like a profoundly philosophical aspect, numerized staking is a really clean way to solve this problem. It's a really beautiful way. Of course, it only, with numeri currently, works for a very particular problem, right? Not for human interaction on the internet, but that's fascinating. Yeah, there's nothing to stop people. In fact, we've open sourced the code we use for staking in a protocol we call Erasure. And if Reddit wanted to, they could even use that code to enable staking on our Wall Street bets. And they're actually researching now, they've had some Ethereum grants on how could they have more crypto stuff in there, in Ethereum, because wouldn't that be interesting? Like imagine you could, instead of seeing a screenshot, like, guys, I promise I will not sell my GameStop. We're just going to go huge. We're not going to sell at all. And here is a smart contract, which no one in the world, including me, can undo that says, I have staked millions against this claim. That's powerful. And then what could you do? And of course, it doesn't have to be millions, it could be just a very small amount, but then just a huge number of users doing that kind of stake. Exactly. That could change the internet. It would change Wall Street. They would not, they would never have been able to, they would still be short squeezing one day after the next, every single hedge fund collapsing. If we look into the future, do you think it's possible that Numeroid style infrastructure, where AI systems backed by humans are doing the trading, is what the entirety of the stock market is, or the entirety of the economy, is run by basically this army of AI systems with high level human supervision? Yeah, the thing is that some of them could be bad actors. Some of the humans? No, well, these systems could be tricky. So actually, I once met a hedge fund manager, this is kind of interesting. He said, very famous one, and he said, we can see, sometimes we can see things in the market where we know we can make money, but it will mess shit up. We know we can make money, but it will mess things up, and we choose not to do those things. And on the one hand, maybe this is like, oh, you're being super arrogant, of course you can't do this, but maybe he can, and maybe he really isn't doing things he knows he could do, but would change, be pretty bad. Would the Reddit army have that kind of morality or concern for what they're doing? Probably not, based on what we've seen. The madness of crowds. There'll be like one person that says, hey, maybe, and then they get trampled over. That's the terrifying thing, actually. A lot of people have written about this, is somehow that little voice that's human morality gets silenced when we get into groups and start chanting. And that's terrifying. But I think maybe I misunderstood. I thought that you're saying AI systems can be dangerous, but you just described how humans can be dangerous, so which is safer? So, I mean, one thing is, so Wall Street bets these kinds of attacks, like it's not possible to model numerized data and then come up with the idea from the model, let short squeaks game stop. It's not even framed in that way. It's not possible to have that idea. But it is possible for a bunch of humans. So, I think this, it's, numeri could get very powerful without it being dangerous, but Wall Street bets needs to get a little bit more powerful, and it'll be pretty dangerous. Yeah, well, I mean, this is a good place to kind of think about numeri data today, and numeri signals, and what that looks like in 10, 20, 30, 50, 100 years. You know, like right now, I guess maybe you can correct me, but the data that we're working with is like a window. It's a, you know, anonymized obfuscated window into a particular aspect, a time period of the market. And, you know, you can expand that more and more and more and more, potentially. You can imagine in different dimensions to where it encapsulates all the things that, where you could include kind of human to human communication that was available for, like, to buy GameStop, for example, on Wall Street bets. So, maybe the step back, can you speak to what is numeri signals, and what are the different data sets that are involved? So, with numeri signals, you're still providing predictions to us, but you can do it from your own data sets. So, numeri, it's all, you have to model our data to come up with predictions. Numeri signals is whatever data you can find out there, you can turn it into a signal and give it to us. So, it's a way for us to import signals on data we don't yet have. And that's why it's particularly valuable because it's going to be signals, you're only rewarded for signals that are orthogonal to our core signal. So, you have to be doing something uncorrelated. And so, strange alternative data tends to have that property. Mm-hmm. There isn't too many other signals that are correlated with what's happening on Wall Street bets. That's not going to be correlated with the price to earnings ratio, right? And we have some users as of recently, as of like a week ago, there was a user that created, I think he's in India, he created a signal that is scraped from Wall Street bets. And now we have that signal as one of our signals in thousands that we use at Numeri. And the structure of the signal is similar, so it's just numbers and time series data? It's exactly, and it's just like, it's kind of, you're providing a ranking of stocks. So, you just say, give a one means you like the stock, zero means you don't like the stock, and you provide that for 5,000 stocks in the world. And they somehow converted the natural language that's in the Wall Street bet. Exactly. So, they've come, exactly. So, there's, and they made, they open sourced this Colab notebook. You can go and see it and look at it. And so, yeah, it's taking that, making a sentiment score and then turning it into a rank of stocks. A sentiment score. Yeah. Like, this stock sucks or this stock is awesome. And then converting, that's, that's fast. Just even looking at that data would be fascinating. So, on the signal side, what's the vision? This long term, what do you see that becoming? So, we want to manage all the money in the world. That's Numeri's mission. And to get that, we need to have all the data and have all of the talent. Like, there's no way, for the first principles, if you had really good modeling and really good data, that you would lose, right? It's just a question of how much do you need to get, to get really good. So, Numeri already has some really nice data that we give out. This year, we are 10x'ing that. And I actually think we'll 10x the amount of data we have on Numeri every year for at least the next 10 years. Wow. So, it's going to get very big, the data we give out. And signals is more data. People with any other random data set can turn that into a signal and give it to us. And in some sense, that kind of data is the edge cases, the weirdnesses, the... So, you're focused on the bulk, the main data, and then there's just weirdness from all over the place that just can enter through this back door of the classical. Exactly. And it's also a little bit shorter term. So, the signals are about a seven-day time horizon. And on Numeri, it's like a 30-day. So, it's often for faster, for faster situations. You've written about a master plan, and you've mentioned, which I love, in a similar sort of style of big-style thinking, you would like Numeri to manage all of the world's money. So, how do we get there from yesterday to several years from now? What is the plan? So, you've already started to allure to get all the data and get all the talent, humans, models. Exactly. I mean, the important thing to note there is, what would that mean? And I think the biggest thing it means is, if there was one hedge fund, you would have not so much talent wasted on all the other hedge funds. It's super weird how the industry works. It's like one hedge fund gets a data source and hires a PhD, and another hedge fund has to buy the same data source and hire a PhD. And suddenly, a third of American PhDs are working at hedge funds, and we're not even on Mars. And so, in some ways, Numeri, it's all about freeing up people who work at hedge funds to go work for Elon. Yeah. And also, the people who are working on Numeri problem, it feels like a lot of the knowledge there is also transferable to other domains. Exactly. One of our top users, he works at NASA Jet Propulsion Lab. Yeah. And he's amazing. I went to go visit him there. And he's got Numeri posters, and it looks like the movies, it looks like Apollo 11 or whatever. Yeah, the point is, he didn't quit his job to join full-time. He's working on getting us to Jupiter's moon. That's his mission, the Europa Clipper mission. Actually, literally what you're saying. Literally. He's smart enough that we really want his intelligence to reach the stock market, because the stock market's a good thing, hedge funds are a good thing, all kinds of hedge funds, especially. But we don't want him to quit his job, so he can just do Numeri on the weekends. And that's what he does. He just made a model, and it just automatically submits to us, and he's one of our best users. You mentioned briefly that stock markets are good. From my outside perspective, is there a sense, do you think trading stocks is closer to gambling, or is it closer to investing? Sometimes it feels like it's gambling, as opposed to betting on companies to succeed. And this is maybe connected to our discussion of shorting in general, but from your sense, do you think about it? Is it fundamentally still investing? I do think, I mean, it's a good question. I've also seen lately people say, this is like speculation. Is there too much speculation in the market? And it's like, but all the trades are speculative. All the trades have a horizon, people want them to work. So I would say that there's certainly a lot of aspects of gambling math that applies to investing. One thing you don't do in gambling is put all your money in one bet. You have bankroll management, and it's a key part of it. And small alterations to your bankroll management might be better than improvements to your skill. And then there are things we care about in our fund, like we want to make a lot of independent bets. We talk about it, like we want to make a lot of independent bets, because that's going to be a higher sharp than if you have a lot of bets that depend on each other, like all in one sector. But yeah, I mean, the point is that you want the prices of the stocks to be reflective of their value. Of the underlying value of the company. Yeah, you shouldn't have there be like a hedge fund that's able to say, well, I've looked at some data and all of this stuff's super mispriced. Like that's super bad for society if it looks like that to someone. I guess the underlying question then is, do you see that the market often like drifts away from the underlying value of companies, and it becomes a game in itself? Like would these, whatever they're called, like derivatives, like the option, like options and shorting and all that kind of stuff. It's like layers of game on top of the actual, like what you said, which is like the basic thing that the Wall Street Bets was doing, which is like just buying stocks. Yeah. There are a lot of games that people play that are in the derivatives market. And I think a lot of the stuff people dislike when they look at the history of what's happened, they hate like credit default swaps or collateralized debt obligations. Like these are the kind of like enemies of 2008. And then the long-term capital management thing, it was like they had 30 times leverage or something just that no one, like you could just go to a gas station and ask anybody at the gas station, is it a good idea to have 30 times leverage? And they just say, no. It's like common sense just like went out the window. So, yeah, I don't respect long-term capital management. Okay. But Numerind doesn't actually use any derivatives unless you call shorting derivative. We do put money into companies. That does help the companies we're investing in. It's just in little ways. We really did buy Tesla and it did. And we played some role in its success. Super small, make no mistake. But still, I think that's important. Can I ask you a pothead question, which is, what is money, man? So, if we just kind of zoom out and look at, because let's talk to you about cryptocurrency, which perhaps could be the future of money. In general, how do you think about money? You said, Numerind, the vision, the goal is to run, to manage the world's money. What is money in your view? I don't have a good answer to that, but it's definitely in my personal life, it's become more and more warped. And you start to care about the real thing, what's really going on here. Elon talks about things like this, what is a company, really? It's a bunch of people who show up to work together and they solve a problem. And there might not be a stock out there that's trading that represents what they're doing, but it's not the real thing. And being involved in crypto, I put in a crowd sale of Ethereum and all these other things and different crypto hedge funds and things that I've invested in. And it's just kind of like, it feels like how I used to think about money stuff is just totally warped. Because you stop caring about the price and you care about the product. So, by the product, you mean the different mechanisms that money is exchanged. I mean, money is ultimately a store of wealth, but it's also a mechanism of exchanging wealth. But what wealth means becomes a totally different thing, especially with cryptocurrency to where it's almost like these little contracts, these little agreements, these transactions between human beings that represent something that's bigger than just cash being exchanged at 7-11, it feels like. Yeah. Maybe I'll answer what is finance? It's what are you doing when you have the ability to take out a loan, you can bring a whole new future into being with finance. If you couldn't get a student loan to get a college degree, you couldn't get a college degree if you didn't have the money. But now, weirdly, you can get it with and all you have is this loan, which is like, so now you can bring a different future into the world. And that's how when I was saying earlier, about if you rerun American history, economic history, without these things, like you're not allowed to take out loans, you're not allowed to have derivatives, you're not allowed to have money, it just doesn't really work. And it's a really magic thing how much you can do with finance, by kind of bringing the future forward. Finance is empowering. We sometimes forget this, but it enables innovation, it enables big risk takers and bold builders that ultimately make this world better. You said you were early in on cryptocurrency. Can you give your high level overview of just your thoughts about the past, present and future of cryptocurrency? Yeah, so my friends told me about Bitcoin and I was interested in equities a lot. And I was like, well, it has no net present value. It has no future cash flows. Bitcoin pays no dividends. So I really couldn't get my head around it, like that this could be valuable. And then I, but I did, so I didn't feel like I was early in cryptocurrency, in fact, because I was like, it was like 2014, it felt like a long time after Bitcoin. And then, but then I really liked some of the things that Ethereum was doing, it seemed like a super visionary thing. Like I was reading something that was just going to change the world when I was reading the white paper. And I liked the different constructs you could have inside of Ethereum that you couldn't have on Bitcoin. Like smart contracts and all that kind of stuff? Exactly. Yeah. And even the, they were, yeah, even spoke about different, yeah, different constructions you could have. Yeah. That's the cool dance between Bitcoin and Ethereum of it's in the space of ideas. It feels so young. Like I wonder what cryptocurrencies will look like in the future. Like if Bitcoin or Ethereum 2.0 or some version will stick around or any of those, like who's going to win out or if there's even a concept of winning out at all. Is there a cryptocurrency that you're especially find interesting that technically financially, philosophically you think is something you're keeping your eye on? Well, I don't really, I'm not looking to like invest in cryptocurrencies anymore. But I, they are, I mean, and many are almost identical. I mean, there's not, there wasn't too much difference between even Ethereum and Bitcoin in some ways. Right. But there are some that I like the privacy ones. I mean, I was like, I like Zcash for it's like coolness. It's actually, it's like a different kind of invention compared to some of the other things. Okay. Can you speak to just briefly to privacy? What is there some mechanisms of preserving some privacy of the investor? I guess everything is public. Is that the problem? Yeah. None of the transactions are private. And so, you know, even like I have some of my, I have some numeraire and you can just see it. In fact, you can go to a website and says like, you can go to like ether scan and it'll say like numeraire founder. And I'm like, how the hell you guys know this? So they can reverse engineer, whatever that's called. Yeah. And so they can see me move it too. They can see me, Oh, why is he moving it? Yeah. So, but yeah, Zcash, they also, when you can make private transactions, you can also play different games. And it's unclear. It's like, what's quite cool about Zcash is I wonder what games are being played there. No one will know. So from a deeply analytical perspective, can you describe why Dogecoin is going to win? Which it surely will. Like it very likely will take over the world. And once we expand out into the universe, we'll take over the universe. Or on a more serious note, like what are your thoughts on the recent success of Dogecoin where you've spoken to sort of the meme stocks, the memetics of the whole thing, that it feels like the joke can become the reality. Like the meme, the joke has power in this world. It's fascinating. Exactly. It's like, why is it correlated with Elon tweeting about it? It's not just Elon alone tweeting, right? It's like Elon tweeting, and that becomes a catalyst for everybody on the internet kind of like spreading the joke, right? Exactly. The joke of it. So it's the initial spark of the fire for Wall Street bets type of situation. And that's fascinating because jokes seem to spread faster than other mechanisms. Like funny shit is very effective at captivating the discourse on the internet. Yeah. And I think you can have, I like the one meme, like Doge, I haven't heard that name in a long time. I think back to that meme often. That's like funny. And every time I think back to it, there's a little probability that I might buy it. And so I imagine you just have millions of people who have had all these great jokes told to them. And every now and then they reminisce, oh, that was really funny. And then they're like, let me buy some. Wouldn't that be interesting if like the entirety, if we travel in time, like multiple centuries, where the entirety of the communication of the human species is like humor. Like it's all just jokes. Like we're high on probably some really advanced drugs. And we're all just laughing nonstop. It's a weird, like dystopian future of just humor. Elon has made me realize how like good it feels to just not take shit seriously every once in a while and just relieve like the pressure of the world. At the same time, the reason I don't always like when people finish their sentences with lol is like, when you don't take anything seriously. When everything becomes a joke, then it feels like that way of thinking feels like it will destroy the world. It's like, I often think like, will memes save the world or destroy? Because I think both are possible directions. Yeah, I think this is a big problem. I mean, America, I always felt that about America, a lot of people are telling jokes kind of all the time. And they're kind of good at it. And you take someone aside, an American, you're like, I really want to have a sincere conversation. It's like hard to even keep a straight face. Yeah, because everything is so there's so much levity. So it's complicated. I like how sincere actually, like your Twitter can be like, I'm in love with the world. I get so much shit for it. I'm never gonna stop because I realized like, you have to be able to sometimes just be real and be positive and just be say the cliche things, which ultimately those things actually capture some fundamental truths about life. Yeah, but it's a dance. And I think Elon does a good job of that. Now from an engineering perspective of being able to joke, but everyone's mostly to pull back and be like, here's real problems, let's solve them, and so on, and then be able to jump back to a joke. So it's ultimately, I think, I guess a skill that we have to learn. But I guess your advice is to invest everything anyone listening owns into Dogecoin. That's what I heard from this. Yeah, no, exactly. Yeah. Our hedge fund is unavailable. Yeah, just go straight to Dogecoin. You're running a successful company. It's just interesting, because my mind has been in that space of potentially being one of the millions other entrepreneurs. What's your advice on how to build a successful startup, how to build a successful company? I think that one thing I do like, and it might be a particular thing about America, but there is something about playing. Tell people what you really want to happen in the world. Don't stop. It's not going to make it, like if you're asking someone to invest in your company, don't say, I think maybe one day we might make a million dollars. When you actually believe something else, you actually believe, you're actually more optimistic, but you're toning down your optimism because you want to appear like low risk. But actually, it's super high risk if your company becomes mediocre, because no one wants to work in a mediocre company, no one wants to invest in a mediocre company. So you should play the real game. And obviously, this doesn't apply to all businesses. But if you play a venture backed startup kind of game, like play for keeps, play to win, go big. And it's very hard to do that. I've always feel like, yeah, you can start narrowing your focus because 10 people are telling you, you got to care about this boring thing that won't matter five years from now. And you should push back and play the real game. So be bold. So both, I mean, there's an interesting duality there. So there's the way you speak to other people about like your plans and what you are like privately, just in your own mind. And maybe it's connected with what you're saying about, yeah, sincerity as well. Like if you appear to be sincerely optimistic about something that's big or crazy, it's putting yourself up to be kind of like ridiculed or something. And so if you say, my mission is to, yeah, go to Mars. It's just so bonkers that it's hard to say. It is. But one powerful thing, just like you said, is if you say it and you believe it, then actually amazing people come and work with you. Exactly. It's not just skill, but the dreams. There's something about optimism that, like that fire that you have when you're optimistic of actually having the hope of building something totally cool, something totally new, that when those people get in a room together, like they can actually do it. Yeah. Yeah. And also it makes life really fun when you're in that room. So all of that together, ultimately, I don't know, that's what makes this crazy ride of a startup really look fun. And Elon is an example of a person who succeeded at that. There's not many other inspiring figures, which is sad. I used to be at Google and there's something that happens that sometimes when the company grows bigger and bigger and bigger, where that kind of ambition kind of quiets down a little bit. Google had this ambition, still does, of making the world's information accessible to everyone. And I remember, I don't know, that's beautiful. I still love that dream of, they used to scan books, but just in every way possible, make the world's information accessible. Same with Wikipedia. Every time I open up Wikipedia, I'm just awe-inspired by how awesome humans are, man. And creating this together, I don't know what the meanings are over there, but it's just beautiful. What they've created is incredible. And I'd love to be able to be part of something like that. And you're right, for that, you have to be bold. And strange to me also, I think you're right that there's how many boring companies there are. Something I always talk about, especially in fintech, it's like, why am I excited about this? This is so lame. This isn't even important. Even if you succeed, this is going to be terrible. Yeah. This is not good. And it's just strange how people can get fake enthusiastic about boring ideas when there's so many bigger ideas that, yeah, I mean, you read these things, like this company raises money, and it's just like, that's a lot of money for the worst idea I've ever heard. Some ideas are really big. So, I worked on autonomous vehicles quite a bit. And there's so many ways in which you can present that idea to yourself, to the team you work with, to just, yeah, like to yourself when you're quietly looking in the mirror in the morning, that's really boring or really exciting. Like if you're really ambitious with autonomous vehicles, it changes the nature of like human robot interaction. It's changed the nature of how we move. Forget money, forget all that stuff. It changes like everything about robotics and AI, machine learning. It changes everything about manufacturing. I mean, the cars, the transportation is so fundamentally connected to cars. And if that changes, it's changing the fabric of society, of movies, of everything. And if you go bold and take risks and be willing to go bankrupt with your company, as opposed to cautiously, you can really change the world. And it's so sad for me to see all these autonomous companies, autonomous vehicle companies, they're like really more focused about fundraising and kind of like smoke and mirrors. They're really afraid. The entirety of their marketing is grounded in fear and presenting enough smoke to where they keep raising funds so they can cautiously use technology of a previous decade or previous two decades to kind of test vehicles here and there, as opposed to do crazy crazy things and bold and go huge at scale to huge data collection. So that's just an example. Like the idea can be big, but if you don't allow yourself to take that idea and think really big with it, then you're not going to make anything happen. Yeah, you're absolutely right in that. So you've been connected in your work with a bunch of amazing people. How much interaction do you have with investors? That whole process is an entire mystery to me. Is there some people that just have influence on the trajectory of your thinking completely? Or is it just this collective energy behind the company? Yeah, I mean, I came here and I was amazed how, yeah, I was only here for a few months and I met some incredible investors and I'd almost run out of money. And once they invested, I was like, I am not going to let you down. And I was like, okay, I'm going to send them like an email update every like three minutes. And then they don't care at all. So they kind of want to, I don't know, like, so for some, I like it when it's just like, they're always available to talk. But a lot of building a business, especially a high tech business, there's little for them to add, right? There's little for them to add on product. There's a lot for them to add on like business development. And if we are doing product research, which is for us research into the market, research into how to make a great hedge fund, and we do that for years, there's not much to tell the investors. So that basically is like, I believe in you. There's something, I like the cut of your jib. There's something in your idea, in your ambition, in your plans that I like. And it's almost like a pat on the back. It's like, go get them kid. Yeah, it is a bit like that. And that's cool. That's a good way to do it. I'm glad they do it that way. Like the one meeting I had, which was like really good with this was meeting Howard Morgan, who's actually a co founder of Renaissance Technologies in the like 1980s, and worked with Jim Simons. And he was in the room, and I was meeting some other guy and he was in the room. And I was explaining how quantitative finance works. I was like, so you know, they use mathematical models. And then he was like, I yeah, I started Renaissance. I know a bit about this. And then I was like, Oh my god. So yeah, but then I think he kind of said, well, yeah, he said, well, because I was talking, he was working at First Round Capital as a partner. And they kind of said they didn't want to invest. And then I wrote a blog post describing the idea. And I was like, I really think you guys should invest. And then they end up. Oh, interesting. You convinced them. They're like, we don't really invest in hedge funds. And I was like, you don't see like what I'm doing. This is a tech company, not a hedge fund. Yeah, and numerai is brilliant. It's when it caught my eye, there's something special there. So I really do hope you succeed in the obviously, it's a risky thing you're taking on the ambition of it, the size of it, but I do hope you succeed. You mentioned Jim Simons. He comes up in another world of mine really often on the he's just a brilliant guy on the mathematics side as a mathematician, but he's also brilliant finance hedge fund manager guy. Have you gotten a chance to interact with him at all? Have you learned anything from him on the math, on the finance, on the philosophy life side things? I've played poker with him. It was pretty cool. It was like, actually in the show billions, they kind of do a little thing about this poker tournament thing with all the hedge fund managers. And that's real life thing. And they have a lot of like world series of bracelet, what's there's poker bracelets holders, but it's kind of Jim's thing. And I met him there. And yeah, it was kind of brief, but I was just like, he's like, Oh, how do you, why are you here? And I was like, Oh, Howard sent me, you know, he's like, go play this tournament, meet some of the other players. And then, Was it Texas Hold'em? Yeah, Texas Hold'em tournament. Yeah. Do you play poker yourself? Or was it? Yeah, I do. I mean, it was crazy. And on my right was the CEO, who's the current CEO of Renaissance, Peter Brown. And Peter Muller, who's a hedge fund manager at PDT. And yeah, I mean, it was just like, and then, you know, just everyone and then all these bracelets, world series, like people I know from like TV. And Robert Mercer, who's fucking crazy. Who's that? He's the guy who donated the most money to Trump. And he's just like, It's a lot of personality. Character. Yeah, geez, it's crazy. So it's quite cool how, yeah, like the, it was really fun. And then I managed to knock out Peter Muller. I have a, I got a little trophy for knocking him out because he was a previous champion. In fact, I think he's won the most. I think he's won three times. Super smart guy. But I will say Jim outlasted me in the tournament. And they're all extremely good at poker. But they're also, so it was a $10,000 buy-in. And I was like, this is kind of expensive. But it all goes to charity, Jim's math charity. But then, the way they play, they have like rebuys. And like, they all do a shit ton of rebuys. This is for charity. So immediately, they're like going all in. And I'm like, man, like, so I end up, you know, adding more as well. So like, you couldn't play at all without doing that. Yeah, the stakes are high. But you're connected to a lot of these folks that are kind of titans of just of economics and tech in general. Do you feel a burden from this? You're a young guy. I did feel a bit out of place there. Like, the company was quite new. And they also don't speak about things, right? It's not like going to meet a famous rocket engineer who will tell you how to make a rocket. They do not want to tell you anything about how to make a hedge fund. It's like all secretive. And that part I didn't like. And they were also kind of making fun of me a little bit. Like they would say, like, they'd call me like, I don't know, the Bitcoin kid. And then they would say even things like, remember, Peter? Yeah, said to me something like, I don't think AI is going to have a big role in finance. And I was like, hearing this from the CEO of Renaissance was like, weird to hear, because I was like, of course it will. And he's like, but he can see, I can see it having a really big impact on things like self driving cars, right? But finance, it's too noisy and whatever. And so I don't think it's like the perfect application. And I was like, that was interesting to hear. Because it's like, and I think it was that same day that Libra, I think it is, the poker playing AI started to beat like the human. Yeah, so it's kind of funny hearing them like say, Oh, I'm not sure AI could ever attack that problem. And then that very day, it's attacking the problem of the game we're playing. Well, there's a kind of a magic to somebody who's exceptionally successful, looking at you, giving you respect, but also saying that what you're doing is not going to succeed, in a sense, like they're not really saying it. But I tend to believe for my interactions with people that it's a kind of prod to say, like, prove me wrong. Yeah, that's ultimately that's, that's how those guys talk. They see good talent. And they're like, yeah, and I think they're also saying it's not going to succeed quickly, in some way, like, this is going to take a long time. And maybe, maybe that's good to know. Mm hmm. And certainly AI in, in trading, that's one of the most philosophically interesting questions about artificial intelligence and the nature of money, because it's like, how much can you extract in terms of patterns from all of these millions of humans interacting using this methodology of money? It's like one of the open questions in artificial intelligence. In that sense, you converting into a data set is one of like, the biggest gifts to the research community, to the whole, anyone who loves data science and AI, this is, this is kind of fascinating. And I'd love to see where this goes, actually. Thing I say sometimes, long before AGI destroys the world, a narrow intelligence will win all the money in the stock market. Way, like, just a narrow AI. And I want to, I don't know if I'm going to be the one who invents that. So I'm building Numeri to make sure that that narrow AI, you know, uses our data. So you're giving a platform to where millions of people can participate and do build that narrow AI themselves. People love it when I ask this kind of question about books, about ideas and philosophers and so on. I was wondering if you had books or ideas, philosophers, thinkers that had an influence on your life when you were growing up, or just today that you would recommend that people check out, blog posts, podcasts, videos, all that kind of stuff. Is there something that just kind of had an impact on you that you can recommend? A super kind of obvious one, that I really was reading zero to one while coming up with Numeri. I was like halfway through the book. And I really do like a lot of the ideas there. And it's also about kind of thinking big. And also, it's like a peculiar little book. It's like, why? Like, there's a little picture of the hipster versus Unabomber. And it's a weird little book. So I like, there's kind of like some depth there. In terms of a book on a, if you're thinking of doing a startup, that's a good book. A book I like a lot is, maybe my favorite book, is David Deutsch's Beginning of Infinity. I just found that so optimistic. It puts you, everything you read in science, it like makes the world feel like kind of colder. Because it's like, you know, we're just coming from evolution and coming from nothing should be this way or whatever. And humans are not very powerful. We're just like scum on the earth. And the way David Deutsch sees things and argues, he argues them with the same rigor that the cynics often use, and then has a much better conclusion. That's, you know, some of the statements and things like, you know, anything that doesn't violate the laws of physics can be solved. So ultimately arriving at a hopeful, like a hopeful path forward. Yeah, without being like a hippie. You mentioned kind of advice for startups. Is there, in general, whether you do a startup or not, do you have advice for young people today? You're like an example of somebody who's paved their own path and were, I would say, exceptionally successful. Is there advice, somebody who's like 20 today, 18, undergrad, or thinking about going to college or in college and so on, that you would give them? I think I often tell young people don't start companies. Is it not, don't start a company unless you're prepared to make it your life's work. Like, that's a really good way of putting it. And a lot of people think, well, you know, this semester, I'm going to take a semester off. And in that one semester, I'm going to start a company and sell it or whatever. Right. And it's just like, what are you talking about? It doesn't really work that way. You should be like super into the idea, so into it that you want to spend a really long time on it. Is that more about psychology or actually time allocation? Like, is it literally the fact that you need to give 100% for potentially years for it to succeed? Or is it more about just the mindset that's required? Yeah. I mean, I think, well, any, I think, yeah, you don't want to have, certainly don't want to have a plan to sell the company, like quickly or something. What's like, what's like a company that has a very, it's like a big fashion component. Like it'll only work now. It's like an app or something. So yeah, I, that's, that's a big one. And then I also think something I've thought about recently is I had a job as a quant at a fund for about two and a half years. And part of me thinks if I had spent another two years there, I would have learned a lot more and had even more knowledge to, to be where, to basically accelerate how long Numerai took. So the idea that you can sit in an air conditioned room and get free food, or even sit at home now in your underwear and make a huge amount of money and learn whatever you want and get, it's just crazy. It's such a good deal. Yeah. Oh, that's interesting. That's the case for, I was terrified of that. Like a Google, I thought I would become really comfortable in that air conditioned room. And that I was afraid the quant situation is, is, I mean, what you present is, is really brilliant that it's exceptionally valuable, the lessons you learn, because you get to, you get to get paid while you learn from others. If you see that, if you see jobs in, in the space of your passion that way, that it's just an education, it's like the best kind of education. But of course you have, from my perspective, you have to be really careful on that to get comfortable. Again, a relationship, then you buy a house or whatever the hell it is. And then you get, you know, and then you convince yourself like, well, I have to pay these fees for the car, for the house, blah, blah, blah. And then, and there's momentum and all of a sudden you're on your deathbed and there's grandchildren and you're drinking whiskey and complaining about kids these days. So I, you know, that I'm afraid of that momentum, but you're right. Like there's something special about the education you get working at these companies. Yeah. And I, I remember on my desk, I had the, like a bunch of papers on quant finance, a bunch of papers on optimization, and then the paper on Ethereum, just on my desk as well. And the white paper, and it's like, it's amazing how much, how kind of, and you can learn about, so that, that I also thought, I think this like idea of like learning about intersections of things. I don't think there are too many people that know like as much about crypto and quant finance and machine learning as I do. And that's a really nice set of three things to know stuff about. And that was because I had like free time in my job. Okay. Let me ask the perfectly impractical, but the most important question. What's the meaning of all the things you're trying to do so many amazing things? Why? What's the meaning of this life of yours or ours? I don't know. Humans. Yeah. So I have yet had people say, asking what meaning of life is, is like asking the wrong question or something. The question is wrong. Yeah. No, usually people get too nervous to be able to say that because it's like, your question sucks. I don't think there's an answer. It's like the searching for it. It's like sometimes asking it. It's like sometimes sitting back and looking up at the stars and being like, huh, I wonder if there's aliens up there. There's a useful like a palate cleanser aspect to it because it kind of wakes you up to like all the little busy hurried day-to-day activities, all the meetings, all the things you'd like a part of. We're just like ants, a part of a system, a part of another system. And then when this asking this bigger question allows you to kind of zoom out and think about it, but there's ultimately, I think it's an impossible thing for a limited capacity, like cognitive capacity to capture. But it's fun to listen to somebody who's exceptionally successful, exceptionally busy now, who's also young like you, to ask these kinds of questions about like death. Do you consider your own mortality kind of thing and life, whether that enters your mind? Because it often doesn't. It kind of almost gets in the way. Yeah. It's amazing how many things you can like that are trivial that could occupy a lot of your mind until something bad happens or something flips you. And then you start thinking about the people you love that are in your life. Then you start thinking about like, holy shit, this ride ends. Exactly. Yeah. I just had COVID and I had it quite bad. It wasn't really bad. It was just like, I also got a simultaneous like lung infection. So I had like almost like bronchitis or whatever. I don't even, I don't understand that stuff, but I started and then you're forced to be isolated. Right. And so it's actually kind of nice because it's very depressing. And then I've heard stories of, I think it's Sean Parker. He had like all these diseases as a child and he had to like just stay in bed for years. And then he like made Napster. It's like pretty cool. So yeah, I had about 15 days of this recently, just last month. And it feels like it did shock me into a new kind of energy and ambition. Were there moments when you were just like terrified at the combination of loneliness and like, you know, the thing about COVID is like, there's some degree of uncertainty. Like it feels like it's a new thing, a new monster that's arrived on this earth. And so, you know, dealing with it alone, a lot of people are dying. It's like wondering like- Yeah, you do wonder. I mean, for sure. And then there are even new strains in South Africa, which is where I was. And maybe the new strain had some interaction with my genes and I'm just going to die. But ultimately it was liberating somehow. I loved it. Oh, I love that I got out of it. Okay. Because it's also affects your mind. You get confusion and kind of a lot of fatigue. And you can't do your usual tricks of psyching yourself out of it. So, you know, sometimes it's like, oh man, I feel tired. Okay, I'm just going to go have coffee and then I'll be fine. It's like, now it's like, I feel tired. I don't even want to get out of bed to get coffee because I feel so tired. And then you have to confront, there's no like quick fix cure and you're trapped at home. So now you have this little thing that happened to you that was a reminder that you're mortal. And you get to carry that flag in trying to create something special in this world, right? With Neumeri. Listen, this was like one of my favorite conversations because the way you think about this world of money and just this world in general is so clear and you're able to explain it so eloquently. Richard, it was really fun. Really appreciate you talking to me. Thank you. Thank you. Thanks for listening to this conversation with Richard Krabe. And thank you to our sponsors, Audible Audiobooks, Trio Labs, Machine Learning Company, Blinkist app that summarizes books, and Athletic Greens, all-in-one nutrition drink. Click the sponsor links to get a discount and to support this podcast. And now let me leave you with some words from Warren Buffett. Games are won by players who focus on the playing field, not by those whose eyes are glued to the scoreboard. Thank you for listening and hope to see you next time.

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Robot attends class at MIT, can't find a seat

you you you

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Garry Nolan: UFOs and Aliens | Lex Fridman Podcast #262

How would you, as a higher intelligence, represent yourself to a lesser intelligence? Do you think they saw what they say they saw? It didn't just start showing up in 1947. How hard do you think it is for aliens to communicate with humans? What do we believe in? We believe in technology. So you show yourself as a form of technology, right? But the common thread is you're not alone. And there's something else here with you. And there's something that's, as you said, watching you. You are a professor at Stanford studying the biology of the human organism at the level of individual cells. So let me ask first the big ridiculous philosophical question. What is the most beautiful or fascinating aspect of human biology at the level of the cell to you? The micromachines and the nanomachines that proteins make and become, that to me is the most interesting. The fact that you have this basically dynamic computer within every cell that's constantly processing its environment, and at the heart of it is DNA, which is a dynamic machine, a dynamic computation process. People think of the DNA as a linear code. It's codes within codes within codes. And it is the actually the epigenetic state that's doing this amazing processing. I mean, if you ever wanted to believe in God, just look inside the cell. So DNA is both information and computer. Exactly. How did that computer come about? A big continuing on the philosophical question, is this both scientific and philosophical? How did life originate on earth, do you think? How did this at every level? So the very first step and the fascinating complex computer that is DNA, that is multicellular organism, and then maybe the fascinating complex computer that is the human mind. Well, I think you have to take just one more step back to the complex computer that is the universe, right? All of the so-called particles or the waves that people think the universe is made of and appears to me at least to be a computational process and embedded in that is biology, right? So all the atoms of a protein, etc, sit in that computational matrix. From my point of view, it's computing something. It's computing towards something. It was created in some ways if you want to believe in God, and I don't know that I do, but if you want to believe in something, the universe was created or at least enabled to allow for life to form. And so the DNA, if you ask where does DNA come from, and you can go all the way back to Richard Dawkins and the selfish gene hypotheses. The way I look at DNA though is it is not a moment in time. It assumes the context of the body and the environment in which it's going to live. And so if you want to ask a question of where and how does information get stored, DNA, although it's only 3 billion base pairs long, contains more information than I think the entire computational memory resources of our current technology. Because who and what you are is both what you were as an egg all the way through to the day you die. And it embodies all the different cell types and organs in your body. And so it's a computational reservoir of information and expectation that you will become. So actually, I would sort of turn it around a different way. And say, if you wanted to create the best memory storage system possible, you could reverse engineer what a human is and create a DNA memory system that is not just the linear version, but is also everything that it could become. When we're talking about DNA, we're talking about Earth and the environment creating DNA. So this, you're talking about trying to come up with an optimal computer for this particular environment. Right. So if you reverse engineer that computer, what do you mean by considering all the possible things it could become? So who you are today, right? So 3 billion bits of information does not explain Lex Friedman. Yeah. Doesn't explain me, right? But the DNA embodies the expectation of the environment in which you will live. Yes. And grow and become. So all the information that is you, right, is actually not only embedded in the DNA, but it's embedded in the context of the world in which you grow into and develop. Right? But so all that information, though, is packed in the expectation of what the DNA expects to see. Interesting. So like, some of the information, is that accurate to say, is stored outside the body? Exactly. Yeah. The information is stored outside because there's a context of expectation. Isn't that interesting? Yeah, it's fascinating. I mean, to linger on this point, if we were to run Earth over again a million times, how many different versions of this type of computer would we get? I think it would be different each time. I mean, if you assume there's no such thing as fate, right, and it's not all pre-programmed, you know, and that there is some sort of, let's say, a variation or randomness at the beginning, you would get as many different versions of life as you could imagine. And I don't think it would all be, unless there's something built into the, you know, into the substrate of the universe. It wouldn't always be left-handed proteins, right? But I wonder what the flap of a butterfly wing, what effects it has, because it's possible that the system is really good at finding the efficient answer, and maybe the efficient answer is, there's only a small finite set of them for this particular environment. Exactly, exactly. That's the kind of, in a way, the anthropomorphic universe of the multiverse expectations, right? That, you know, there's probably a zillion other kinds of universes out there, if you believe in multiverse theory. We only live in the ones where the rules are such that lifelike ours can exist. So using that logic, how many alien civilizations do you think are out there? There's like trillions of environments, aka planets, or maybe you can think even bigger than planets. How many lifelike organisms do you think are out there thriving? And maybe how many do you think are long gone, but were once here? I think, well, innumerable. I think in terms of the ones that are- Greater than zero. Much greater than zero. I mean, I would just be surprised, what a waste, right, of all that space just for us, if we're never going to get there. That would be my first way to think about it. But second, I mean, I remember when I was about seven or eight years old, and I would love if any of your listeners could find this National Geographic. I remember opening the page of the National Geographic. I was about, again, seven to 10 years old. And it was sort of a current picture of the universe. It was around probably 1968, 1969. I just remember looking at it and thinking, what kinds of empires have risen and fallen across that space that we'll never know about? And isn't that sad that we know nothing about something so grand? And so I've always been a reader of science fiction, because I like the creative ideas of what people come up with. And I especially like science fiction writers that base it in good science, but base it also in evolution. That if you evolve a civilization from something lifelike, right, some sort of biology, its assumptions about the universe will come from the environment in which it grew up. So for instance, Larry Niven is a great writer, and he imagines different kinds of civilizations. In some cases, what happens if intelligence evolved from a herd animal, right? Would you lead from behind, right? Would you be, you know, in his case, one of them were the so-called puppeteers. And to them, the moral imperative is cowardice. You put other people forward to run the risk for you, right? And so he writes entire books around that premise. There's another guy, Brin, David Brin is his name, and he writes the so-called uplift universe books. And in those, he takes different intelligences, each from a different evolutionary background. And then he posits a civilization based around where and what they came from. And so to me, I mean, that's just fun. But I mean, back to your original question, is how many are there? I think as many stars as we can see. Now, how many are currently there? Currently there, I don't know. I mean, that's the whole question of, you know, how long can a civilization last before it runs out of steam? And you, for instance, does it just get bored, or does it transcend to something else? Or does it say, I've seen enough and I'm done? What does running out of steam look like? It could be destroy itself or get bored. You know, or we've done everything we can, and they just decide to stop. I don't know. I just don't know. It's that Elon Musk worry that we stop reproducing, or we slow down the reproduction rate to where the population can go to zero. Can go to zero and we collapse. I mean, so the only way to get around that is perhaps create enough machines with AI to take care of us. What could possibly go wrong? You've talked to people that told stories of UFO encounters. Mm-hmm. What is the most fascinating to you about the stories of these UFO encounters that you've heard that people have told you? The similarity of them, the uniformity of the stories. Now, I just want to say up front, a lot of people think that when I speculate, I believe something. That's not true, right? Speculation is just creativity. Speculation is the beginning of hypothesis. None of what I hear in terms of the anecdotes do I necessarily believe are they true. But I still find them fascinating to listen to because at some level, they're still raw data. And you have to listen. And once you start to hear the same story again and again, then you have to say, well, there might be something to it. I mean, maybe it's some kind of a Jungian background in the human mind and human consciousness that creates these stories again and again. It's coming out of the DNA. It's coming out of that pre-programmed something. And Jung talked quite a bit about this kind of thing, the collective unconscious. But actually, one of the most interesting ones I find is this constant message that you're not taking care of your world. And this came long before climate change. It came long before many kinds of, let's say, current day memes around taking care of our planet, pollution, et cetera. And so, for instance, perhaps the best example of this, the one that I find the most fascinating, is a story out of Zimbabwe. 50 or 60 children one afternoon in Zimbabwe. It was a well-educated group of white and black children who at lunchtime in the playground saw a craft. And they saw little men. And they all ran into the teachers, and they told the same story, and they drew the same pictures. And the message several of them got was, you are not taking care of your planet. And it got, you know, there's actually a movie coming out on this episode, and 30 years later now, the people who were there, the children who've now grown up, say, it happened to us. Now, did it happen? Was it some sort of hallucination? Or was it an imposed hallucination by something? Was it material? I don't know. But these kids were seven to 10 years old. You see them on video. Seven to 10-year-olds can't lie like that. And so, you know, whether it's real or not, I don't know. But I find that fascinating data. And again, it's these unconnected stories of individuals with the same story that is worthy of further inquiry. Yeah, so here we are, humans with limited cognitive capacities trying to make sense of the world, trying to understand what is real and not. We have this DNA that somehow in complex ways is interacting with the environment. And then we get these novel ideas that come from the populace. And then they make us wonder about what it all means. And so how to interpret it. If you think from an alien perspective, how would you communicate with other lifelike organisms? You perhaps have to find endpoints on this interaction between the DNA and its manifestations in terms of the human mind and how it interacts with the environment. So get some kind of, all right, what is this DNA? What is this environment? I have to get in somehow to interact with it, to perturb the system to where these little ants, human-like ants get excited and figure stuff out. Yeah, and then somehow steer them. First of all, for investigative purposes, understand, oftentimes to understand a system, you have to perturb it. It's like poke at it. Do they get excited or not? And then the other way is you want to, if you worry about them, you can steer them. If you worry about them, you can steer in one direction or another. And this kind of idea that we're not taking care of our world, that's interesting. I mean, that's comforting. That's hopeful because that means the greater intelligence, which is what I would hope, would want to take care of us. Like we want to take care of the gorillas in the national parks in Africa. Yeah, but we don't want to take care of cockroaches. So there's a line we draw. So you have to hope that- Right now we're a bunch of angry monkeys. And maybe whatever these intelligences are, are also keeping an eye on us. That you don't want a bunch of, you don't want the angry monkey troop stomping around the local galactic arm. Do you think these folks are telling the truth? Do you think they saw what they say they saw? I think they saw what they said they saw. But I also think they saw what they were shown. I mean, if you go back to the whole notion of, okay, how long has this been around? It didn't just start showing up in 1947. Right, there are stories going back into the 1800s of people who saw things in their farm fields in the US. It's in local newspapers from the 1800s. It's fascinating. But if you can go even further back, so to your point of how would you as a higher intelligence represent yourself to a lesser intelligence? Well, let's go back to pre-civilization. Maybe you show yourself as the spirits in the forest, and you give messages through that. Once you get a little bit more civilized, then you show yourself as the gods. And then you're a god. Well, we don't believe in God anymore, necessarily. Not everybody does. So what do we believe in? We believe in technology. So you show yourself as a form of technology, right? But the common thread is you're not alone, and there's something else here with you. And there's something that's, as you said, watching you, and at least watching over your shoulder. But I think that like any good parent, you don't tell your student everything. You make them learn. And learning requires mistakes, because if you tell them everything, then they get lazy. You've looked at the brains of, or information coming from the brain of some of the people that have had UFO encounters. What's common about the brain of people who encounter UFOs? So the study started with a group of, let's say a cohort of individuals that were brought to me, and their MRIs to ask about the damage that had been seen in these individuals. It turns out that the majority of those patients ended up being, as far as we can tell, Havana syndrome. And so for me at least, that part of the story ends in terms of the injury. It's likely almost all Havana syndrome. That's somebody else's problem now. That's not my problem. But when we were looking at the brains of these individuals, we noticed something right in the center of the basal ganglia in many of these individuals that at first we thought was damage. It was basically an enriched patch of MRI-dense neurons that we thought was damage, but then it was showing up in everybody, and then we looked and we said, oh, it's actually not. The other readings on these MRIs show that actually that's living tissue. That's actually the head of the caudate and the pitamen. And at the time, and I remember even asking a good friend of mine at Stanford who is a psychiatrist, what does the basal ganglia do? He said, oh, the basal ganglia is just about movement and nerve and motor control. I said, well, that's odd because these other papers that we were reading at the time started to suggest that it was involved with the brain and the brain and the brain suggests that it was involved with higher intelligence and is actually downstream of the executive function and involved with intuition and planning. And if you think about it, if you're gonna have motor control which is centralized in one place, motor control requires knowledge of the environment. You don't wanna move something and hit the table. Or if you're walking across a room, you want to be aware and cognizant of what you might bump into. So obviously all of that planning is requires access to all the senses. It requires access to your desires and memory, knowledge of where and what you want and desire to walk nearby. Like I use the example of you're at a party, you wanna avoid that person, you like that person, the waiter's about to drop something. All without thinking you maneuver. So that actually all that planning is done in the basal ganglia. And it's actually now called the brain within the brain. It's a goal processing system subservient to executive function. So what we think we found there was not something which allows people to talk to UFOs. I mean, I think the UFO community took it a step too far. What I think we found was a form of higher functioning and processing. So what we then looked at, and this was the most fascinating part of it, we looked then at individuals in the families of those, let's say the index case individuals. And we found that it was actually in families. And more so, this is the most fascinating part. We've probably looked now at about 10,000 cases and about 200 just random cases that you can download off of databases online. You don't see this higher connectivity. You only find it in what Kit Green would have called or has called higher functioning individuals. People who are, I mean, he called them savants. I don't have the means to, we haven't done the testing. But it turns out my family has it, right? We found it in me, my brother, my sister, my mother. We found it as well in other individuals, husband and wife pairs. So statistically, if you had a group of 20 individuals and you found two husband-wife pairs, both of whom had it, and yet it's only found at about, we think, one in 200, one in 300 individuals. The fact that two individuals came together, two sets of individuals came together, both of whom had it, implied either a restricted breeding group or attraction. The reason why it seems to be in, let's say, so-called experiencers or people who claim, if intuition is the ability to see something that other people don't, and I don't mean that in a paranormal sense, but being able to see something just in front of you that other people might just dismiss, well, maybe that's a function of a higher kind of intelligence to say, well, I'm not looking at an artifact. I'm not looking at something that I should just ignore. I'm seeing something and I recognize it for, not what it is, but that it is something different than what is normally found in my environment. Yeah, you know, I have a little bit of that. I seem to see the magic in a lot of moments. Like I have a deep, it's obviously, not obviously, but it seems to be chemical in nature that I just am excited about life. I love life. I love like stupid things. It feels like I'm high a lot, unlike mushrooms or something like that, where you'd really appreciate that. So I'm able to detect something about the environment that maybe others don't, I don't know, but like I seem to be over the top grateful to be alive for a lot of stupid reasons. And that's in there somewhere. I mean, it's kind of interesting because it really is true that our brains, the way we're brought up, but also the genetics enables us to see certain slices of the world. And some people are probably more receptive to anomalous information. They see the magic, the possibility in the novel thing, as opposed to kind of finding the pattern of the common, of the regular. Some people are more, wait a minute, this is kind of weird. I mean, a lot of those people probably become scientists too. Like, huh, like there's this pattern happening over and over and over, and then something weird just happened. And then you get excited by that weirdness and start to pull the string and discover what is at the core of that weirdness. And perhaps, is that, you know, maybe by way of question, how does the human perception system deal with anomalous information, do you think? Well, it first tries to classify it and get it out of the way. If it's not food, if it's not sex, right? If it's not in the way of my desires, or if it is in the way of my desires, then you focus on it. And so, I think the question is, how much spare processing power, how much CPU cycles do we spend on things that are not those core desires? What is the most kind of memorable, powerful UFO encounter report you've ever heard? Just to you, on a personal level, like, something that was really powerful. Well, I mentioned the Zimbabwe one that's particularly interesting. And one that actually most people don't know about, but family driving down the highway, two little girls in the back, open glass-topped car. And the little girls see a craft right over their car. This is in the middle of the day on a busy highway. The mother sees it. Nobody can, they look around, nobody else seems to see it. So the girls take out their camera, take a picture of it. And then they get home. They look at the picture. There's no craft, but there's a little object about 30 feet above their car or so, probably about three feet across, kind of star-shaped. It's not the craft, but it's something else. There's obviously, there was something there. And so what were they seeing? Were they seeing a projection? Were they seeing, and why were only they seeing it? And the photograph was capturing something very different than they were seeing. They're still an object. What, can you give a little bit of context? Is this from modern day? It's modern day. Oh yeah, they had a camera. I mean, they had a cell phone camera. And this was like a report provided. By the way, where's like a central place to provide a report? Is this? Oh, there's a mufon, but this isn't public. I've seen the picture. Oh, this is something you've directly interacted with. Yeah, yeah. I've seen the picture. So those moments like that, they captivate your mind. It's so different, it doesn't fall into the standard story at all. But it also, but in another way, it's kind of a, it's a clear enunciation of this notion that when people see events, they don't all see the same thing. Now we've heard this about like traffic accidents. Different people will see the color of the car differently or the chain of events differently. And just tells you that memory isn't anywhere near what we think it is. But the issue around these so-called UFO reports is that the same people will see a very different thing, almost as if whatever it is is projecting something into the mind, rather than it being real, right? Rather than it being a real manifestation, you know, material in front of you, it's actually almost some sort of an altered virtual reality that is imposed on you. I mean, you know, I think the company Meta and all the virtual reality companies would love to have something like that, right? Where you don't have to actually wear something on your face to experience a virtual reality. What happens if you could just project it? Well, that's the fundamental question from an alien perspective. When you look at it, or as we humans look at ants, how does this perception system operate? So not only how does this thing's mind operate, how does the human mind operate, but how does their perception system operate? So that we can like stimulate the perception system properly to get them to think certain things. And so, you know, that's a really important question. Humans think that, you know, the only way to communicate is in like 3D or 4D space-time. There's physical objects, or maybe you write things into some kind of language. But there could be just so much more richness in how you can communicate. And so from an alien perspective, or somebody has much greater technological capabilities, you have to figure out, how do I use the skills I have to stimulate the human, the limited humans? Right. Well, I mean, let's take the ants again as an example. Let's say that you wanted to make ants practical. You wanted to use them for something, right? You wanted to use them as a form of biological robot. Now, DARPA and other people have been trying to use insects for, you know, into turn them into biological robots. But if you wanted to, you would have to interact with their sense of smell, right? Their pheromone system that they use to interact with each other. So you would either create those molecules to talk to them, to make them do it. I'm not saying talk to them as if they're intelligent, but talk to them to manipulate them in ways that you want. Or if you were advanced enough, you would use some sort of electromagnetic or other means to stimulate their neurons in ways that would accomplish the same goal as the pheromones, but by doing it in a sort of a telefactoring way. So let's say you wanted to telefactor with humans. You would interact with them. And this is, again, this is a technology which you could imagine possible. You could telefactor information into the sensory system of a human, right? But then each human is a little bit different. So either you know enough about them to tailor it to that individual, or you just basically take advantage of whatever the sensory net is that that individual has. So if you happen to be good at sound, or you happen to be a very visually inclined individual, then maybe the sensory information that you get that's most effective in terms of transmitting information would come through that portal. I think the aliens would need to figure out that humans value physical consistency. So we've discovered physics. So we want our perception to make sense. Maybe they don't, you know, that's not an obvious fact of perception, that you have to figure out what kind of things are humans used to observing in this particular environment of Earth, and how do we stimulate the perception system in a way that's not anomalous, or not too, doesn't cross that threshold of just like, well, that's way too weird. Right. So they have to, I mean, that's not obvious that that should be important. You know, maybe you want to err on the side of anomaly, like lean into the weirdness. So communication is complicated. Yeah. Well, that's why I always find this issue of people talking about the so-called greys as interesting, because it is related to what you're saying. They're different enough, but they're not so different as to be scary, right? They're not venom dripping fangs, right? They're different enough, but it's also like they're what you could imagine us becoming in some distant future. So is that a purposeful representation? I don't know. I mean, I don't believe in the greys, for instance, but I believe that people think that they see it. So if we're talking about a communication strategy that says, you know, we're like you, but not the same as you, this might be a manifestation that you represent in terms of a communication strategy. What do you make of David Ferrier's citing of the Tic Tac UFO and other pilots who have seen these objects that seem to defy the laws of physics? Well, I think you have to take them at their word. Are they fascinating to you? Oh, absolutely. No, I know a lot of these people, right? So I know Lou Elizondo, Chris Mellon, the whole crowd I've been... I saw the videos about three weeks or so before they went public. I was at a bar with Lou overlooking the Pentagon in Crystal City, and they showed them to me and my hair stood on end. Wow. And he said, this is coming out soon. And I know one of the guys on the inside who was the naval intelligence who had interviewed all of these pilots again before this came out. And it was hair-raising to hear this, but also exciting that, you know, here's not just people's testimony, these are credible individuals. And if you've seen the 60-minute episode with some of the pilots, you know, they have no monetary gain. If anything, they've got negative gain from coming out. But then you also have all of those simultaneous ship analysis from the USS Princeton and the radar analysis, et cetera. So, you know, at the end of the day, it's just data. It's not a conclusion. I'd be perfectly happy, honestly, perfectly happy if somebody showed that it was all a hoax. I can go back to my day job, right? That could be a hoax, but other things might not be. I mean, this is the point. I mean, this is why it's nice to remove some of the stigma about this topic, because it's all just data. And anomalous events are such that there's going to be, they're going to be rare in terms of how much data they represent. But we have to consider the full range of data to discover the things that actually represent something that's, if we pull at it, we'll discover something that's extraterrestrial. Or something deep about the phenomena on Earth that we don't yet understand. Right. Well, if it only stimulates people, for instance, to think, okay, well, what happens if we could move like that with momentumless movement? And it stimulates young individuals to go into the sciences to ask those questions. That to me is fascinating. I mean, after I've been openly talking about this in the last year, especially, I've had a number of students from top schools who aren't my students come to me and say, if I can help, let me. How can I help? I never had thought about this before, but you opened, you and others, not just you, and others have opened my mind to thinking about this matter. Yeah, that's why it's actually funny that Elon Musk doesn't think too much about this, these kinds of propulsion systems that could defy the laws of physics as we currently understand them. To me, it's a powerful way to think, what is possible? It's inspiring, even if some of the data doesn't represent extraterrestrial vehicles. I think the observation itself, it's like something you mentioned, which is hypothesizing, imagining these things, considering the possibility of these things. I think opens up your mind in a way that ultimately can create the technology. First, you have to believe the technology is possible before you can create it. Right. In my own lab, we always look for, as I've said before, what is inevitable? And saying, inevitably, this is the kind of data we need, but if we need that kind of data, the instrument we want doesn't exist. Yeah. Okay, so I imagine the perfect instrument, I can't make it. And you back into something which is practical, and then you, in a sense, reverse engineer the future of what it is that you want to make. And I've started and sold like at least half a dozen or more companies using that basic premise. And so it was always something that didn't exist today, but we imagined what we wanted. And at the time, many people said it couldn't be done. I mean, for instance, all the gene therapy that's done today with retroviruses came from a group meeting in David Baltimore's lab. I was a postdoc with him. And one of the other postdocs wasn't able to make retroviruses in a way that he wanted to. And I realized I had a cell line that would allow us to make retroviruses in two days rather than two months. And so he and I then worked together to make that system. And now all gene therapy with retroviruses is done using this basic approach around the whole world, because something couldn't be done, and we wanted to do it better, and we imagined the future. And so that's, I think, what the whole UFO phenomenon is doing for people. It's like, well, let's imagine a future where these kinds of technologies are, but also let's imagine a future where we don't blow ourselves up. So if these things are there, they manage to not blow themselves up. So it means that at least one other civilization got past the inflection point. So if some of the encounters are actually representing alien civilizations visiting us, why do you think they're doing so? You suggested that perhaps it's the study to understand their own past. Right? Right. What are some of the motivations, do you think? And again, from our perspective, us as humans, what motivations would we have when we approach other civilizations we might discover in the future? Well, I think one motivation might be to steer us away from the precipice, right? Or on the assumption that, you know, even if we make it past the precipice, at least we're not a bunch of psychopaths, you know, running around. So maybe there's a little bit of motivation there to make sure that the neighbor that's growing up next to you is not, you know, unruly. You know, but I mean, maybe it's sort of a moral imperative, like what we have with, you know, creating national parks where animals can continue to live out their lives in a natural way. I don't know. I mean, that would be, I mean, the problem is we're imagining from a anthropomorphic viewpoint what an alien might think. And as I've said before, alien means alien, right? I mean, not Hollywood aliens, but a whole different way of thinking and a whole different level of experience and let's say wisdom, hopefully, that we could only hope to understand. Now, but if we ever get out there, if we ever make it past our current problems, and even if we don't have faster than light travel, and even if we're only using ram scoops or light sails to get where we want to go, and it takes us 10,000 years to get somewhere or to spread out, we might encounter such things. And are we just gonna stomp all over it like we did in colonial South America or Africa or all the rest on our current path, likely? You know, and so what are we gonna learn? Well, we're getting better and better at understanding what is life. And I think we're getting better and better being careful, not to step on it when we see it. And this is one of the nice things about talking about UFOs. It expands the Overton window. It expands our understanding of what possibly could be life. It gets us to think. It gets the scientific community to think. When we go to Mars, when we go to these different moons that possibly have life, we're not looking at legged organisms. We're looking at some kind of complexity that arises in resistance to the natural world. And there's a lot of interesting- I like that, resistance to the natural world. Yeah. So somehow there's a rebellious process, complex system going on here. And I don't know the many ways it could take form. And there's a sense for aliens that as the technology develops, they take form more and more as information, as something that's not just a matter of time. As information, as something that can influence the space of ideas, of the processing of data itself. So I just, this idea of embodiment that we humans so admire, physically visible, perceivable embodiment, may be a very inefficient thing. Right. Right. If you think just about your area, AI, we're trying to make smaller and smaller and smaller circuitry that is basically closer and closer to the physics of how the universe operates. Right, right down at the level of, I mean, quantum computers are basically right down about quantum information storage. So fast forward 10,000, 100,000 years, maybe somebody found a way to embody AI directly into the physics of the universe, right? And it doesn't require a physical manifestation. It just sits in space-time. It's just a locally ordered space. We're just locally ordered space-time, right? You know, I mean, people, but maybe they just, they found a way to embody it there. They probably have to get really good at not, you know, trampling on the ants. Because the better your technology gets, the easier it is to accidentally like, oops. Right. Just destroy these simpleton biological systems. We constantly think about whatever these things might be. We think that they are some sort of a unified force. Well, maybe they're not unified. Maybe they are as disparate as you and I are. And maybe what keeps them from stomping all over the ants is each other, right? That they are in a self-tension to prevent one or more of them from running amok. Oh, yeah. I mean, that's kind of the anarchy of nations that we have on earth. So there's always going to be this- There's a hierarchy. This hierarchy that's formed of greater and greater intelligences. Right. And they're all probably also wondering, wait, what's bigger than me? Exactly. That's what I always wonder is that maybe that they're, what keeps them in line is something that is beyond them. Like what created the universe. I mean, that's probably a question that bothers them too. What about the communication task itself? How hard do you think it is for aliens to communicate with humans? So is this something you think about, about this barrier of communication between biological systems and something else? How difficult is it to find a common language? Well, I think if you're smart enough or technologically enabled enough, it's relatively straightforward. Now, whether your concepts can ever be dumbed down to us, that might be hard. Yeah. I mean... Again, talking to the ants. Talking to the ants. I mean, they don't... On Instagram. So... You want to look good in this picture. Let me explain to you... Let me explain to you why. So that's the essential problem of, you know, perhaps they realize who it is that they're talking to. And they say, rather than muddy the picture, we're only going to give them limited information. Yeah. Right? And yeah, maybe we could sit down, like you and I, and have a conversation. But then they would make assumptions... The humans would then make assumptions about us that aren't true. Because we're not humans. Right? So let's stay at arm's length. Let's just let them know that we're here. Right? And here's the limited amount of communication. Again, this notion that if you give somebody everything, they'll get lazy. And, you know, if they've been around as long as they have, they've seen every kind of thing that can go wrong. And so it's, they know as much as they might want to step in, that would be a wrong thing. Yeah, you have to also understand that the amount of wisdom they carry. Yeah. You know, and so it's very easy as well for religions to... I don't want to get into a whole religious conversation, but you could... Very easy for... You could see how religions could call them angels or devils, or what have you. Because, again, if you're trying to fit it into a framework of cultural understanding, the first thing you reach for is God. And so when you look at what these things are... And again, with the angels and the devils, in a similar sort of way, their communication is limited. They just kind of give little... What's the Oracle of Delphi? They kind of give these Delphic pronouncements, and then it's up to you to figure out what it is that they really mean. Stephen Greer claimed that a skeleton discovered in Atacama region of Chile might be an alien. You reached out to him and took on the task of proving or disproving that with the rigor of science. The result is a paper titled, Whole Genome Sequencing of Atacama Skeleton Shows Novel Mutations Linked with Dysplasia. Can you tell this full story? The story was, as you put it right there, correct. Reached out, got a sample of the body, did the DNA sequencing, then worked with a team of two other Stanford scientists and Roche sequencing group, Roche diagnostics, and probably a total team of about 11 or so people. And as is standard in these kinds of things, the professors actually don't do the work. The students do the work and figured out the answer. And then we helped them put together the story. And the story was simply that it was human, 100%. I went into it thinking it was originally a monkey of some sort. I got kind of excited a few months into the process thinking, well, what happens if it is an alien? Can you describe some of the characteristics of the skeleton that makes it unique and interesting? Primarily, it had dysmorphias of the brain. And so the first thing I did was I looked at the skeleton and the first thing I did actually, when I got pictures of it, I took it to a local expert at Stanford and he was on the paper. And he was the world expert in pediatric bone dysmorphias. He literally wrote the book on this, because that's what you do. You go to an expert when it's outside of your field of interest. And he said, well, I haven't seen this particular collection of mutations before or this physiology before, but here's what I think it might be. And he said, but based on the size of the thing and the bone density, it would appear to be like six or seven years old. Now, again, that's the thing where I think the lay public doesn't understand or takes a speculation like that and turns it into a fact. No one ever said that it was that age. We only said that the bones made it look like it was that age. But then we went back and looked for genetic explanations of why things might look the way they did. And if you, again, read the paper, it's very carefully caveated to say that these mutations might result in this. But what we did find was an unexpectedly large number of mutations associated with bone growth in this individual. And it was just a bad roll of the dice, right? You roll the dice enough times with enough people born every year and someone will roll the wrong dice all at once. So the sad part about it was individuals in the UFO community who wanted to think that there was some sort of conspiracy around it, right? That somebody had somehow convinced all of my students to lie. I mean, come on. You know, I would lose my job, first of all, and they would all be in trouble forever. Yeah, but also it's just projecting malevolence onto people that doesn't, I don't think, exist in normal populace and especially doesn't exist in the scientific community. The kind of people that go into science, I mean, this is what bothers me with the current distrust of science, is they might be naive. They might not, especially in modern science, look at the big picture, philosophical, ethical questions, all that kind of stuff. But ultimately, they're people with integrity and just a deep curiosity for the discovery of cool little things. And there's no malevolence, broadly speaking, in the scientific community. So, I mean, there's a bigger story here, which is, you know, there's a hunger in the populace to discover something anomalous, something new. And, you know, science has to be both open to the anomalous, but also to reject the anomalous when the data doesn't support it. Right. What do you make of that, you know, walking that line for you? Because you're dealing with UFO encounters, you're dealing with the anomalous. Well, people have said, let's go back to the Atacama case, that I was debunking it. Well, debunking is a loaded term, sort of assumes that you were going in purposefully to prove something is wrong. I wasn't, I was just going in to collect the data. And, you know, I showed that this one was human. There was another skull that somebody had at one point, it was called the star child, they called it the star child skull. I said, you know, I looked at it, I looked at the DNA sequencing that they had done. I said, this is human. End of story. The people who owned the thing at the time disagreed with me, and then eventually another group came in and proved that I was right. And it's not about debunking, it's about getting the more spectacular and hyped cases off the table. I mean, the reason I got interested in it is because somebody was hyping it. And not because I wanted to disprove it, but because I just wanted to know. And thus, get it off the table, because it's usually the most extravagant thing, extravagant things that are most likely to be wrong. Somewhere in the rubble will be something interesting. And so that's what you do. You get the dross off the table, and then somewhere in the data will be something worth real inquiry. And that, if you inquire deeply enough, will be extravagant as well. Yes, exactly. And that's what actually excites scientists is to, I mean, you want, with the rigor of science, to actually reveal the extravagant. And so look at CRISPR as probably the most perfect example of that. These weird sequences in bacterial genomes all arrayed one after the other with these strange sequences around them. But when you looked at the sequences, they looked like viruses. And so how did they get there? And lo and behold, after a lot of effort and work, well, a couple of Nobel prizes went out the door, but these strange things ended up having extraordinarily extravagant possibilities. You've also looked at UFO materials. You are in possession of UFO materials yourself. Claimed UFO materials. Alleged. Alleged UFO materials, that's right. What's another term? Weird materials that don't seem to... They have a story. They have a story that doesn't seem to be of natural origins, but it's not, you know, there's a process to proving that, and that process may take decades, if not centuries, because you have to keep pulling at the string and discover where they could possibly come from. But anyway, you're in possession of some materials of this kind. Can you describe what you're looking for? Describe some of them, and maybe also talk to the process of how you investigate them, how you analyze them. Right, so let's say that there's two classes of materials that I've been given by people, and they're not given by like the government or anything, just given people who've collected them, and there's a reasonable chain of evidence associated with them that you believe is not just a pebble somebody picked up off a road. There are almost always things that people have claimed have either been dropped off as like some sort of a leftover material, molten metals, or they are from an object that was released from this that kind of exploded. They're almost always metals. I have some couple of things that might be biological that are interesting that I haven't really spent a lot of time on yet. When you look at a metal, you basically, well, okay, what are the elements in it, and what's it made of? And so there's pretty standard approaches to doing that. Most of them involve a technology called mass spectrometry, and there's probably about five or six different kinds of mass spectrometry that you could bring to bear on answering it. And they either tell you, depending upon the limit of the resolution of the instrument, they either tell you the elements that are there, or they tell you the isotopes that are there. And you're interested not just in knowing whether something is there or not, you are interested in knowing whether there are, you know, the amounts of it, and in the case of elements, how many different isotopes are there. And that's kind of where, in some of these cases, it gets interesting, right? Because in at least one of the materials, as we first studied it, the isotope ratios of, in this case, it was magnesium, were way off normal. And I just don't know why. It doesn't prove anything. It just, all it proves is that it was probably accomplished by some kind of an industrial process. Whether it's the result of a process, or whether, and this is sort of the leftover, or whether it was made that way for a particular purpose, I don't know. All I know is that it was engineered. That's it, right? But then it's, the question is, sort of you go one step deeper, why would you engineer it? Right, why, and what is engineered means? There's all kinds of, it could be a byproduct, it could be the main result of an engineering process, it would be a small part of the engineering process that is the main part. Well, so the ratios of isotopes for any given element are basically the result of stellar processes. Supernova blew up sometime several billion years ago. That became a cloud. Those atoms coalesced gravitationally to form another sun and a ring that became a rocky planet. And the ratios of the isotopes were determined at the time of that explosion. And so everything in the local solar system is more or less of that ratio, depending upon certain gravitational difference. But by fragments of a percent, not whole tens of percent difference. So what do humans use isotopes for? Mostly to blow stuff up. I mean, the vast majority of the isotopes that have been made in the per pound or ton are things like certain ratios of plutonium and uranium to blow stuff up. We don't make or engineer isotopes, which today is relatively easy to do, but it's still expensive for any other reason, apart from, let's say, as anti-cancer. We use stable isotopes in money these days as a counterfeiting tool. You basically embed certain ratios of isotopes in to make it harder for counterfeiters to accomplish. And so, but other than that, we don't do anything with that. So why would you make grams of such material in this one case and drop it around on a beach in Brazil? So which case are we talking about? This is the Ubatuba case. Can you describe this case a little bit further? Like what material we're talking about, just the full story of the case. So it's an interesting one. It's an interesting one. So a fisherman saw an object that released something or it exploded, and it was this, you know, I've got some big chunks of it, relatively pure magnesium, with obviously something else in it, because magnesium burns. So it had something in it that would, other metals, simple alloy, that would prevent it from basically burning up. And so the question is, and so then we had two pieces that came from two different chains of custody, both claimed to be from the same object. At least physically, when you look at the two things, they look the same, right? So we took small fragments of each of them. We put them in an instrument called a secondary ion mass spec, which is an extremely sensitive instrument. And it can see down to 0.0001 mass units, which is important for, let's say, more arcane reasons. But it's a sensitive instrument. And so one of the chains of custody, we had two pieces from the same chain of custody, and then two pieces from the other chain of custody. One of them had completely normal magnesium isotope ratios, magnesium 24, 25, 26. And the other was off, not just like slightly off, way off. And they were both off to the same extent. So, I mean, it was sort of like you had an internal control of what was normal, and then you had this other one which was wrong. And so you're left with, it's kind of an open question. Was this a hoax? Were these two chains of custody, one of them a hoax, that somebody purposefully introduced those things? Because you could do it. It would cost a lot. I mean, at the time that this was found, I guess the 1970s or so, might have been earlier, I forget, the amount that I had would have cost several tens of thousands of dollars to make. And again, it's not something you would just throw around. And why would you do it in the hope that some guy 30 years from then would pick it up and study it? Yeah, it's a very subtle, subtle troll. It's a long-term plan. It's a long-term plan. So I just don't know what to make of it, except it's interesting. So a different kind of question that you're asking is what constitutes evidence, right? So is this sufficient evidence? Absolutely not. But somebody's put it forward. I have the time, it's my time. I'll study it, and my objective is to sort of take those that I think are credible enough and do a reasonable analysis, put it out there, and maybe somebody else will come up with an idea as to what it is. Now, what would be better is some sort of true technology, right? Something that is obviously, we don't have it. And people like Neil deGrasse Tyson and Seth Shostak have come out rightfully and have said, when you show up with something really obviously technology that we don't understand, then we'll pay attention, right? Not just material. Not just material. A piece of metal is interesting. And several of the things that I've looked at and other things that people have come to me with we found to be completely banal or were actually pieces of aircraft that were invented back in the 1940s. Yeah. And so, take them off the table. See, but I think, again, I think showing up with technology that we humans would find completely novel is actually a really difficult task for aliens because it obviously can't be so novel that we don't recognize it. That we don't recognize it. For what it is. For what it is. And so, and I would say most of the technology aliens likely have would be something we don't recognize. So, it's actually a hard problem how to convince ants. Like, you first have to understand what ants are tweeting about. Like, what they care about in order to like inject into their culture. Because, you know, that's why I think it would be the technology that you could present is in the space of ideas. Is in the, is try to influence individual humans with the encounters. Right. And try to, with this kind of thing that you mentioned about us not taking, messages about us not taking care of the world. It's difficult to, I mean, for them to understand you have to come up with trinkets that impress us. I mean, maybe the very technology, the fascination with the development of technology and the development of technology, the actual act of innovation itself is the thing that they're communicating. Right. I mean, this is kind of what Jacques Vallee thinks about. Is the role of. The control system, he calls it. The control system. Well, let me ask about Jacques. Who is he? You know him. Who is Jacques Vallee? What have you learned from him? About life, about UFOs, about technology, about our role in the universe? Well, I met Jacques actually soon after the whole Atacama thing happened. I was visited by those people associated with the government and the whatever around the Havana, what ended up mostly being Havana syndrome patients, but also Jacques at the same time. And they were actually working behind the scenes with each other that, oh, here's this Stanford professor who is willing to talk about this stuff and investigate things. Maybe we should go talk to him. And he reached out through a colleague and he and I had lunch actually at the Rosewood Inn up on near Sand Hill. So Jacques is one of the first openly active scientists, and he's really a scientist in this area, going back to the 1960s. And he's put forward a number of ideas, speculations about what it might be that people are interacting with. And the first thing that I learned from him is this notion of what he called Kabuki theater, that many of the things that people have seen are, I remember reading his books and thinking, he uses this word absurd a lot. He said, the things that people claim they see are absurd. Right? A ship doesn't land in a farmer's field and then come up and knock on the door and say, can I have a glass of water? And these are stories literally out of newspapers from the 1930s. It's absurd. Yeah. And the other thing that people say, ships don't crash. If you're so technologically advanced, you don't crash. It's absurd that they crash. So he says, this is put on as a show. It's meant to, it's an influence campaign, right? It's not meant to influence individuals. It's meant to influence a culture as a whole. Maybe they don't look at us as individuals. Maybe they look at us as an organism that lives on a planet. Right? And perhaps rightfully so. And so that's how you interact with them. That's how you influence them. So that was one of the first things that kind of took me back and realized, wow, there's actually a, maybe there's a puppet master behind the scenes that's doing this influencing. And then all this stuff about aliens is just, is not true per se. They're just a representation of something that is meant to influence. So that was probably the most interesting. I mean, the man is brilliant. He's also, it can be, and I'm sorry, Jacques, he can also be incredibly annoying to have a conversation with because he will pick apart your arguments or anything that you think you know and show you why you don't know what you think you know. And he uses the, he used the example that for me, that is all you need is one counter example to any conclusion and you're wrong. And so I learned from him, I mean, I'm supposed to be a good scientist, but I learned from him, don't talk about conclusions, just talk about the data, because data's not wrong. I mean, convince yourself that the data's not wrong or not an artifact, but be careful about your conclusions because whatever is going on, it's much more complicated than we imagine. Wow, that's powerful being able to always step back. As we humans get excited, we start to jump to conclusions from the data, but always step back. Powerful being able to always step back. As we humans get excited, we start to jump to conclusions from the data, but always step back. Well, in some of my Twitter feeds, when I dare to go on Twitter, are full of, well, when are you gonna give us the answer? When are you gonna give us the answer? You know, science is not immediate. You're gonna have to be patient. And even some of my science colleagues have said, well, where's the data? My answer to them has been, where's been your work to try to produce any? You know, I'm not here to give you everything on a silver platter. We talked offline how much I love data and machine learning and so on. And it's been really disheartening to see the US government not invest as much as they possibly could into this whole process. So let's jump to the most recent thing, which is what do you make of the report titled preliminary assessment on identified aerial phenomena that was released by the office of the director of national intelligence in June, 2021. So this was like, okay, we're gonna step back and we're going to like, what, where do we stand and where do we hope the future is? What do you make of that report? Is it hopeful? Is it- I see it as very hopeful, very hopeful. I think the adults are finally stepping up in and being in charge, right? In the good sense of adult. What's that? In the good sense of adult. In the good sense of adult. You know- Because childlike curiosity is pretty powerful thing. That's true. Yeah. But it's also, I think the people who were worried that the populace at large might run screaming into the streets and riot, you know, have, you know, they basically, the empiric evidence is they're wrong. You know, these videos and all these things have been out for now, what, five years? Most people don't even know about it, right? So as hyped as it's been and all over the newspapers that it's been and et cetera, you know, even Tucker Carlson has talked about it many times on his news program. Joe Rogan has, a lot of people don't know about it. So I think people, if it's not affecting their day-to-day life, they're going on with their day-to-day life. So, but that said, I think it was an important sea change in the internal discussions going on in the government because, and the reason being, that I think this is actually partly true with the maturation of human social technology. It was becoming so obvious that this stuff was showing up again and again and again around our ships. They just couldn't keep it quiet anymore, right? And so it's like, we need to do something about it. And Lou Elizondo and Chris and others, to their great credit, found the right angle to talk about this. It says, well, okay, let's say it's not out there. Maybe it's the Russians, the Chinese, or somebody else. We should know about this because we damn sure know it's not us. So that to me is an important thing to finally be a little bit more open about the matter. But like I often say, I'm not looking for people to give me permission to do anything. I'm just going to do the analysis myself with what I have. Avi Loeb has taken the same approach. He said, I'm not going to wait for the government to give me telescopic information about technologies or things that might be even on our own solar system. I'm just going to collect it myself. And that's the right way to do it, right? Don't wait for somebody else to give it to you. It's also possible to inspire a large number of people to do a wider spread data collection. Yes. I mean, you yourself can't do a large enough data collection that would, if you're talking about anomalous events. Right, right. You should be collecting high resolution data about everything that's happening on earth in terms of the kind of things that would indicate to you a strong signal that something weird happened here. And this is why governments can be good at funding large scale efforts. Yes. I mean, NASA and so on, working with SpaceX, with Blue Origin, fund capitalistic, sort of fund companies, fund company efforts to do huge moonshot projects. Right. And in the same way, do huge moonshot data collection efforts in terms of UFOs. I mean, we're not, it needs to be like 10X, like one or two orders of magnitude more funding. Exactly. To do this kind of thing. And I understand on the flip side of that, if you make it about what are the Russians, what are the Chinese doing, make it a question of geopolitics, it gets touchy because now you're kind of taken away from the realm of science and- Making it military. Making it military. Some of the greatest, this is what makes me, as an engineer, makes me truly sad that some of the greatest engineering work ever done is by Lockheed Martin and we will never know about it. Yeah, I agree, I agree. I wish it was different, but it's the world we live in. But related to that UAP task force announcement that you just said, the bill was passed in the Department of Defense and now it formally establishes an office to collate that information and also to be transparent about it. Money is now set aside, right? What do you think of it, just in case people don't know, the DoD establishing new department to study UFOs called Airborne Naming, come on, but yes, Airborne Object Identification and Management Synchronization Group. Do you know how to pronounce that? No, I do not. No, it's stupid. AOIMSG. It's stupid and it needs to be renamed, but- AOIMSG, A-O, all right, is directed by the Undersecretary of Defense for Intelligence and Security. What do you make of this office? Are you hopeful about this office? I think there's still a tug of war going on behind the scenes as to who's gonna control this. But I do know though that money has been set aside that will be used to make things more public, right? To start to get others involved. I'm involved with an effort to get other academics involved. So you think there might be some of that money could be directed towards funding, maybe like groups like yours to do some research here. So they would be open to that, you think? I hope so. I mean, nothing is set in stone yet. And I'm not hiding anything because I just don't know anything, right? But I do think that there will be public efforts. Now, there are being set up other private efforts to bring monies involved and to use that to leverage and get access to some of the internal resources as well. So what you're seeing is kind of an ecosystem building up in a positive sense of people who are willing to do the research. So before it would be, you couldn't even go to a scientist and ask them to help. Now, if there's money, as I said before, scientists are essentially capitalists. We go where the money is. I mean, the work that I've done, I did out of my own pocket and probably about 50, 60, $70,000 of money went into the paper we published out of my own pocket. But the amount of money that needs to go in is in at least the few millions to do a proper analysis of these materials. The work I know that the Galileo project is involved with is involved with, it's probably in the five to 10 million range to get stuff done. But that's actually a relatively modest amount of money to accomplish something that has been in the zeitgeist for decades. I should also push back a little bit on something you probably will agree with. You said scientists are essentially capitalists. What I've noticed is there's certainly an influence of money but oftentimes when you're talking about basic research and basic science, the money is a little bit ambiguous to what direction you're doing the research in. And the scientists get really good at telling a narrative of like, yeah, yeah, yeah, we're fulfilling the purpose of this funding, but we're actually, they end up doing really what they're curious about. And of course you cannot deviate, like if you're getting funded to study penguins in Antarctica you can't start building rockets, but probably you can because you'll convince some kind, you'll concoct a narrative saying rockets are really important for studying penguins in the Antarctic. Right. I think that's actually, this is one thing I think people don't generally understand about the scientific mind is I don't know how capitalistic it is because if it was, they would start an effing company. No, no, no, no, no. I mean, when I meant capitalist, I didn't mean in the, they'll start companies per se. I mean, we can only do the research where there's money. And so from, maybe it's a bad use of the term capitalist. So, but we will only do the research where there's money. I mean, why do most people work, many biologists work in cancer research because there's a lot of money there. It's an important problem, but I might not have ever gotten involved in it if there wasn't money. I might've gone and I was gonna be a botanist when I was a kid. That's what I wanted to do. So having money available will bring people to bear. Now, another mistake that's often actually made, I think by the lay public about science is that people think that we're paid to do things. Just as you said, I get a research grant and luckily from the NIH, they give you a fair amount of latitude. I will go my own way and I'll find something, I might've proposed something, but I'll end up somewhere entirely different by the end of the project. And that's how good science is done. You follow the data, you follow the results. And so that's what I'm hoping can be done here. I think the worst kind of thing that could be done with this subject area is to put it inside another company where they have a set plan of what it is they're gonna do and the scientists either do what the executives tell them to do or not. That isn't how anything will really get discovered. Get it out into the public, get open minds thinking about it and then publishing on it and doing the right kind of work. That's how real progress will be made with this. Let's again put our sort of philosophical hats on. Do you think the US government or some other government is in possession of something of extraterrestrial origin that is far more impressive than anything we've seen in the public? If I, I've not seen anything personally, but if I believe the people who I don't think can lie, yes. Yes. How does that make you feel in terms of the way government works, the way our human civilization works, that there might be things like that and we're not, they're not public? Is there a hopeful message for transparency that's possible? Like if you were in power, and I'm not saying president because maybe the president is not the source of power here, but would you release this information in some way or form? Yes, if I were, I think it's something that can bring humanity together, right? I think that knowledge of this kind of thing, to know that we are more alike than we are different in comparison to whatever this is, is a positive thing for us. And to know, you know, I don't necessarily care that the government has been hiding it. And I think, you know, people who've been talking about, we should give government officials or whatever amnesty. I think that's probably the right answer. We don't, this isn't a time to look back and say, you did something wrong. You did whatever you did because that was the data you had available to you at the time. And those, you had good reasons for doing it. Now, if your reasons were selfish, if your reasons were you wanted to do it because you wanted to monetize it yourself to your benefit, but against that of others, then I think maybe there's something else that could be said. But, you know, an opportunity to get all this information out, if I were in charge, I would try to do it. Now, I might be shown something though that says, there's a reason why you don't want to let anybody know this. You know, maybe you don't want everybody have having access to unlimited energy, because maybe you might turn it into a bomb. Or something that gives you hints that something like unlimited energy is possible, but you haven't figured it out yet. And if you make it public, maybe some of the other governments you have tensions with will figure it out first. Right. It's kind of an arms race going on, I think. In all forms. And it makes me truly sad because it's obvious that, for example, the origins of the COVID virus, it's obvious to me that the Chinese government, whatever the origins are, is interested in not releasing information about it, because it can only be bad for the Chinese government. And every government thinks like this. Actually, this has been a disappointment to me, talking to PR folks at companies. They're always nervous. They're always conservative in the sense like, well, if we release more stuff, it can only be bad. And then an Elon Musk character comes along who tweets ridiculous memes and doesn't give a fuck. And I've been encouraging CEOs, I've been encouraging people to be transparent. And of course, government, national security is really like another level. It's human lives at stake. But let's start at the lighter case of just releasing some of the awesome insights of how the sausage is made, the technology, and being transparent about it, because it excites people. Like you said, it connects people, it inspires them, it's good for the brand, it's good for everybody. I honestly think this kind of idea that people will steal the information and we use it against you is an idea that's not true in this idea of the 20th century. Like you said, some of the benefits of the social media, our social world is that transparency is beneficial. And I hope governments will learn that lesson. Of course, they're usually the last to learn. They're usually the last to learn such lessons. What do you make of Bob Lazar's story in terms of possession of aircraft? Do you believe in him? I don't believe in the Bob Lazar story, to be quite honest. I mean, Jeremy Corbell has done a great job interviewing him and has done some beautiful documentaries. I just don't know how to interpret it. And again, some of the people who I fraternize with think it's all rubbish. Maybe he's right, but I don't know. The problem is, and this is a little bit different about how I approach the whole area than a lot of others, I'm less interested in going over old paperwork and all these old histories of who said what, the whole he said, she said of the history of UFOs. I'm a scientist. I worked on the brain area because it's something I can collect data on. I can go back to the same individual, collect their MRI again and redo it. I can hand that MRI to somebody else, they can analyze it. I can get materials. I can analyze them. I can get some of these skeletons. I won't touch any skeletons ever again, but I can analyze it and somebody else can reproduce the data. Yeah. I mean, that's what I'm good at. And so, I'm not going to go into the whole, I'm not a historian. Yeah, that's true. But there's a human side to it. Sometimes I think with these, because again, anomalous, rare events, some of the data is inextricably connected to each other. It's connected to humans, the observations. Right. I mean, I hope in the future, that that sensory data will not be polluted by human subjectivity, but that's still powerful data, even direct observations, like if you talk about pilots. So, it's an interesting question to me whether Baba Tzar is telling the truth, whether he believes he's telling the truth too. And what also, what impact his story and stories like his have on the willingness of governments to be transparent and so on. So, you have to credit his story for captivating the imagination of people and getting the conversation going. He's maintained his story for all these years with little to no change that I'm aware of. But there's so many other people who are, let's say, experts in that story. Their gut, you accumulate a set of circumstantial evidence where your gut will say that somebody is not telling the truth. Yeah. You mentioned Avi Loeb. I forgot to ask you about Oumuamua. Mm-hmm. Because you've analyzed specimens here on Earth, what do you make of that one? And what do you make broadly of our efforts to look at rocks, essentially, or look at objects flying around in our solar system? Is that a valuable pursuit? Or maybe most of the stories can be, most of the fascinating things could be discovered here on Earth or on other nearby planets? Just going to Oumuamua, I think Avi's insight is an interesting speculation, right? Like I was saying before, people can sometimes look at something and not see it for what it is. Many would just look at that and say, oh, it's an asteroid and dismiss it. There was something odd about the data that Avi picked up on and said, well, here's an alternative explanation that doesn't fit, that actually better fits the models than it just being a rock. And to his credit, he just has ignored the criticism and has ignored the critics because he believes the data is real and is using that then as a battering ram to go after other things. So I think that's great. You know? Yeah, what is his main conclusion? Does he say it could be of alien extraterrestrial origin? Is that his- Well, that's one of the things. I mean, he's explained how it could be a light sail. And a light sail is certainly within near human capabilities to make such a thing. I think Yuri Milner, he's a Russian billionaire. He's involved, I think, in a project to make light sails with laser, you know, to launch them with laser power, essentially, towards Alpha Centauri. Right? So it's something that humans could make. I think Avi's proposal is perfectly within the realm of possibility. I mean, sadly, the thing is, you know, now nearly out of our solar system. Yes, I mean, to me, that's inspiring to do greater levels of data collection in our solar system, but also here on Earth. It just seems like we should be constantly collecting data because the tools of software that we're developing get better and better at dealing with huge amounts of data. It's changing the nature of science. I mean, collect all of the data. Right, collect the data. I mean, the Galileo Project asked me over the weekend to join, and I did. So, you know, I'm not a specialist in any of the stuff that they're doing, but, you know, in looking at the list of people who are on there, there are really no biologists on there. So at some point, if my expertise is required for something... What's the goal and the vision of the Galileo Project? Better talk to Avi, but my understanding and just actually looking at the, at the sort of the bylaws this morning, literally just got them, is number one, collect the data on UAP, and number two, collect data on local, potentially local technological artifacts. I need to look into this. This is fascinating. And Avi is heading the Galileo Project. Yeah, have you spoken to him? On this podcast, yes. I believe it was before he was headed. Oh. It was a new creation? Yeah, the Galileo Project was, I think it's about six or seven months old now. Okay, that's amazing. And he's getting a group of scientists together. Oh yeah, about 100. Oh, that's awesome. Actually, I was looking at some of their stuff over the weekend. I'm shocked at the level of organization that they've already got put together. That's amazing. It looks like a moonshot project. I mean, I've been involved with a lot of NIH, large NIH projects, which involve a lot of people in coordination, and they're putting it together. So you're extremely well published in a lot of the fields we began this conversation with. So you're a legit scientist. But yet you're keeping an open mind to a lot of ideas that maybe require you to take a leap outside of the conventional to take a leap outside of the conventional. So what advice would you give to young people today that are in high school or in college that are dreaming of having impact in science or maybe in whatever career path that goes outside of the conventional that really does something new? If you believe in something, you believe that an idea is valuable, or you haven't approached something, don't let others shame you into not doing it. As I've said, shame is a societal control device to get other people to do what they want you to do rather than what you want to do. So shame sometimes is good to stop you from doing something unethical or wrong. But shame also is something that is circumscribing your environment. I've never let people who've told me, you know, you shouldn't do that line of science, you should be ashamed of yourself for even thinking that. Give me a break. I'm, you know, why is it wrong to ask questions about this area? What's wrong with asking the question? Frankly, you're the person who's wrong for trying to stop these questions. You're the person who's almost acting like a cultist. You basically have closed your mind to what the possibilities are. And if I'm not hurting anybody, and if it could lead to an advance, and if it's my time, why does it bother you? I mean, I had a very well-known scientist once tell me that I was gonna hurt my career talking about this. If anything, it's enhanced my career. I have a couple of questions on this. So first of all, just a small comment on that. I've realized that it feels like a lot of the progress in science is done by people pursuing an idea that another senior faculty would probably say, this is going to hurt your career. I think it's actually a pretty good indicator that there's something interesting when a senior-wise person tells you this is gonna hurt your career. I think that's just the one, as a small, if I were to give advice to young people, if somebody senior tells you this is gonna hurt your career, this is gonna hurt your career, think twice about taking their advice. Think twice, yeah. No, I mean, I think that's the primary thing. And the other, I tell my own students, I have a lab of about 20, 30 people, and it's been that big since 1992, people come and go, it's not the data that falls in line that's so interesting. It's the spot off the graph that you wanna understand. Yeah. You wanna, when something is way off the graph, that's the interesting thing, because that's usually where discovery is. And the number of times that I've stopped people in my lab and said, wait a second, go back a few slides, what was that? And then it ended up being something interesting that made their careers. I could count on a few hands. Yeah, get excited by the extraordinary that's outside of the thing that you've done in the past. Right. Just on a personal psychological level, is there, I'm sure at Stanford, I'm sure in you exploring some of these ideas, there's pressure. There's pressure, how do you not give in to the pressure? How do you not give in to the people that say, like, that push you away from these topics? What would you say, shame? I just point to my successes. I say, you're the ones who told me not to start companies all this time ago. And now you're the one coming to me for advice for how to start a company. Yeah. Right. But from the scientific area, you're wanting to take something off the table that might be an explanation. How is that the scientific method? I reverse shame them. Reverse shame them. So purely with reason through conversation, you're able to do that. So it doesn't feel, because to me it would just feel lonely. There's a community. Yeah. There's a community of science. And when you're working on something that's outside a particular conventional way of thinking, it can be lonely. I mean, there's, in the AI field, if you were working on neural networks in the 90s, it could be lonely. I have met some of the most fascinating people ever that had I stayed the conventional track, I would never have met. I mean, truly. Brilliant people because of this. So, it is for those worried about, well, should I step outside of my comfort zone? You're gonna meet some really interesting people. And because I'm open about this area, I'll go and give a talk in Boston, Harvard or MIT. And at dinner, inevitably, this subject comes up. And inevitably, somebody else at the table will admit, both that they're interested or that they've seen something. And suddenly the whole tone of the conversation changes. It's kind of like there's safety in numbers. And then, or I've had people come to me afterwards, after dinner and say, hey, I don't talk about this openly, but... So, the number of scientists who know that there's something else going on is much larger than the scientific community would like to think. That's a really powerful one, which is, I don't talk about this openly, but here's what I believe. And you'd be surprised how many people speak like this and hold those beliefs. And I am optimistic about social media and a more connected world to reveal more and more. Like us not to have these two personalities, where like this public and private one. We've mentioned the big questions of the origins of the universe. What do you think is the meaning of this whole thing? For us humans, our human existence here on earth, or just at the individual level of a human life? What, Gary, is the meaning of life? I think that what we're going through today with this realization, it's kind of like you've lived on an island your whole life and you've looked across the ocean and you've never imagined there was another island with anybody else on it. And then suddenly a ship with sails shows up. You don't understand it, but you realize that suddenly your world just got a lot bigger. I think we're in one of those moments right now that our world view, our galactic view, is opening to something a little bit bigger. And not just that there might be somebody else, but that there's something else. And what it is, is yet to be understood. And the fact that it isn't understood to me is what's exciting, because I can fill it with my dreams. And this discovery, our world might... It's about to get a lot more humbling and a lot more fascinating once we look out and realize we were on an island all along. It makes us both smaller but larger at the same time, to me. I can look outside at the stars and think and imagine what else might be out there. And although I'm not a scientist, and although I know that I will never see it all, it excites me to know that it's there. Well, Gary, both to respect your time and also because at 12 I turned into a princess. Let me just say, thank you for doing everything you're doing as a great scientist, as a person willing to reject the conventional. And thank you for spending your extremely valuable time with me today. Thanks for talking. Thanks so much. It was great talking. Thanks for listening to this conversation with Gary Nolan. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Stanislav Lem in Solaris. How do you expect to communicate with the ocean when we can't even understand one another? Thanks for listening and hope to see you next time.

https://youtu.be/uTCc2-1tbBQ

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Alex Filippenko: Supernovae, Dark Energy, Aliens & the Expanding Universe | Lex Fridman Podcast #137

The following is a conversation with Alex Filipenko, an astrophysicist and professor of astronomy from Berkeley. He was a member of both the Supernova Cosmology Project and the High-Z Supernova Search Team which used observations of the extragalactic supernova to discover that the universe is accelerating and that this implies the existence of dark energy. This discovery resulted in the 2011 NOBAA Prize for Physics. Outside of his groundbreaking research, he is a great science communicator and is one of the most widely admired educators in the world. I really enjoyed this conversation and am sure Alex will be back again in the future. Quick mention of each sponsor, followed by some thoughts related to the episode. Neuro, the maker of functional sugar-free gum and mints that I used to give my brain a quick caffeine boost. BetterHelp, an online therapy with a licensed professional. Masterclass, online courses that I enjoy from some of the most amazing humans in history. And Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that as we talk about in this conversation, the objects that populate the universe are both awe-inspiring and terrifying in their capacity to create and to destroy us. Solar flares and asteroids lurking in the darkness of space threaten our humble, fragile existence here on Earth. In the chaos, tension, conflict, and social division of 2020, it's easy to forget just how lucky we humans are to be here. And with a bit of hard work, maybe one day we'll venture out towards the stars. If you enjoy this thing, subscribe on YouTube, review it with Fat Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Alex Filippenko. Let's start by talking about the biggest possible thing, the universe. Sure. Will the universe expand forever or collapse on itself? Well, you know, that's a great question. That's one of the big questions of cosmology. And of course, we have evidence that the matter density is sufficiently low that the universe will expand forever. But not only that, there's this weird repulsive effect, we call it dark energy for want of a better term, and it appears to be accelerating the expansion of the universe. So, if that continues, the universe will expand forever. But it need not necessarily continue. It could reverse sign, in which case the universe could, in principle, collapse at some point in the far, far future. So, like, in terms of investment advice, if you were to give me, and then to bet all my money on one or the other, where does your intuition currently lie? Well, right now, I would say that it would expand forever because I think that the dark energy is likely to be just quantum fluctuations of the vacuum. The vacuum zero energy state is not a state of zero energy. That is, the ground state is a state of some elevated energy which has a repulsive effect to it. And that will never go away because it's not something that changes with time. So, if the universe is accelerating now, it will forever continue to do so. And yet, I mean, you so effortlessly mentioned dark energy. Do we have any understanding of what the heck that thing is? Well, not really, but we're getting progressively better observational constraints. So, you know, different theories of what it might be predict different sorts of behavior for the evolution of the universe. And we've been measuring the evolution of the universe now, and the data appear to agree with the predictions of a constant density vacuum energy, a zero-point energy. But one can't prove that that's what it is because one would have to show that the measured numbers agree with the predictions to an arbitrary number of decimal places. And of course, even if you've got eight, nine, 10, 12 decimal places, what if in the 13th one, the measurements significantly differ from the prediction? Then the dark energy isn't this vacuum state, ground state energy of the vacuum. And so, then it could be some sort of a field, some sort of a new energy, a little bit like light, like electromagnetism, but very different from light that fills space. And that type of energy could in principle change in the distant future. It could become gravitationally attractive for all we know. There is a historical precedent to that, and that is that the inflation with which the universe began when the universe was just a tiny blink of an eye old, a trillionth of a trillionth of a trillionth of a second, you know, the universe went whoosh, it exponentially expanded. That dark energy-like substance, we call it the inflaton, that which inflated the universe, later decayed into more or less normal gravitationally attractive matter. So, the exponential early expansion of the universe did transition to a deceleration, which then dominated the universe for about 9 billion years. And now this small amount of dark energy started causing an acceleration about 5 billion years ago. And whether that will continue or not is something that we'd like to answer, but I don't know that we will anytime soon. LRS So, there could be this interesting field that we don't yet understand that's morphing over time, that's changing the way the universe is expanding. I mean, it's funny that you were thinking through this rigorously like an experimentalist. But what about the fundamental physics of dark energy? Is there any understanding of what the heck it is? Or is this the kind of the god of the gaps or the field of the gaps? So, there must be something there because of what we're observing. AC I'm very much a person who believes that there's always a cause, you know, there are no miracles of a supernatural nature. Okay. So, I mean, there are two broad categories, either it's the vacuum zero-point energy, or it's some sort of a new energy field that pervades the universe. The latter could change with time, the former, the vacuum energy cannot. So, if it turns out that it's one of these new fields, and there are many, many possibilities, they go by the name of quintessence and things like that. But there are many categories of those sorts of fields. We try with data to rule them out by comparing the actual measurements with the predictions. And some have been ruled out, but many, many others remain to be tested. And the data just have to become a lot better before we can rule out most of them and become reasonably convinced that this is a vacuum energy. LR So, there is hypotheses for different fields? AC Oh, yeah. LR With names and stuff like that? AC Yeah, yeah. Generically, quintessence, like the Aristotelian fifth essence, but there are many, many versions of quintessence. There's K-essence. There's even ideas that, you know, this isn't something from within this dark energy, but rather, there are a bunch of, say, bubble universes surrounding our universe. And this whole idea of the multiverse is not some crazy madman type idea anymore. It's, you know, real card carrying physicists are seriously considering this possibility of a multiverse. And some types of multiverses could have, you know, a bunch of bubbles on the outside, which gravitationally act outward on our bubble, because gravity or gravitons, the quantum particle that is thought to carry gravity is thought to traverse the bulk, the space between these different little bubble membranes and stuff. And so, it's conceivable that these other universes are pulling outward on us. That's not a favored explanation right now, but really, nothing has been ruled out. No class of models has been ruled out completely. Certain examples within classes of models have been ruled out. But in general, I think we still have really a lot to learn about what's causing this observed acceleration of the expansion of the universe, be it dark energy or some forces from the outside, or perhaps, you know, I guess it's conceivable that, and sometimes I wake up in the middle of the night screaming, that dark energy, that which causes the acceleration, and dark matter, that which causes galaxies and clusters of galaxies to be bound gravitationally, even though there's not enough visible matter to do so, maybe these are our 20th and 21st century Ptolemaic epicycles. So, Ptolemy had a geocentric and Aristotelian view of the world. Everything goes around Earth. But in order to explain the backward motion of planets among the stars that happens every year or two, or sometimes several times a year for Mercury and Venus, you needed the planets to go around in little circles called epicycles, which themselves then went around Earth. And in this part of the epicycle where the planet is going in the direction opposite to the direction of the overall epicycle, it can appear in projection to be going backward among the stars, so-called retrograde motion. And it was a brilliant mathematical scheme. In fact, he could have added epicycles on top of epicycles and reproduce the observed positions of planets to arbitrary accuracy. And this is really the beginning of what we now call Fourier analysis, right? Any periodic function can be represented by a sum of sines and cosines of different periods, amplitudes, and phases. So, it could have worked arbitrarily well, but other data show that, in fact, Earth is going around the Sun. So, are dark energy and dark matter just these band-aids that we now have to try to explain the data, but they're just completely wrong? That's a possibility as well. And as a scientist, I have to be open to that possibility as an open-minded scientist. LR How do you put yourself in the mindset of somebody that, where a majority of the scientific community, a majority of people believe that the Earth, everything rotates around Earth, how do you put yourself in that mindset and then take a leap to propose a model that the Sun is, in fact, at the center of the solar system? AC Sure. I mean, so that puts us back in the shoes of Copernicus, right? 500 years ago, where he had this philosophical preference for the Sun being the dominant body in what we now call the solar system. The observational evidence in terms of the measured positions of planets was not better explained by the heliocentric Sun-centered system. It's just that Copernicus saw that the Sun is the source of all our light and heat. And he knew from other studies that it's far away. So the fact that it appears as big as the Moon means it's actually way, way bigger, because even at that time, it was known that the Sun is much farther away than the Moon. So he just felt, wow, it's big, it's bright. What if it's the central thing? But the observed positions of planets at the time in the early to mid-16th century under the heliocentric system was not a better match, at least not a significantly better match, than Ptolemy's system, which was quite accurate and lasted 1,500 years. Yeah. LR That's so fascinating to think that the philosophical predispositions that you bring to the table are essential. So you have to have a young person come along that has a weird infatuation with the Sun. That almost philosophically is, like, however their upbringing is, they're more ready for whatever the simpler answer is. AC Right. LR That's kind of sad. It's sad from an individual descendant of ape perspective, because then that means, like me, you as a scientist, you're stuck with whatever the heck philosophies you brought to the table, and you might be almost completely unable to think outside this particular box you've built. AC Right. This is why I'm saying that, you know, as an objective scientist, one needs to have an open mind to crazy-sounding new ideas. And, you know, even Copernicus was very much a man of his time and dedicated his work to the Pope. He still used circular orbits. The Sun was a little bit off-center, it turns out, and a slightly off-center circle looks like a slightly eccentric elliptical orbit. So then when Kepler, in fact, showed that the orbits are actually, in general, ellipses, not circles, the reason that he needed Tukhobraha's really great data to show that distinction was that a slightly off-center circle is not much different from a slightly eccentric ellipse. And so, there wasn't much difference between Kepler's view and Copernicus's view, and Kepler needed the better data, Tukhobraha's data. And so, that's, again, a great example of science and observations and experiments working together with hypotheses, and they kind of bounce off each other, they play off of each other, and you continually need more observations. And it wasn't until Galileo's work around 1610 that actual evidence for the heliocentric hypothesis emerged. It came in the form of Venus, the planet Venus, going through all of the possible phases from new to crescent to quarter to gibbous to full to waning gibbous, third quarter, waning, crescent, and then new again. It turns out in the Ptolemaic system, with Venus between Earth and the Sun, but always roughly in the direction of the Sun, you could only get the new and crescent phases of Venus. But the observations showed a full set of phases, and moreover, when Venus was gibbous or full, that meant it was on the far side of the Sun, that meant it was farther from Earth than when it's crescent, so it should appear smaller, and indeed, it did. So, that was the nail in the coffin in a sense. And then, Galileo's other great observation was that Jupiter has moons going around it, the four Galilean satellites, and even though Jupiter moves through space, so too do the moons go with it. So, first of all, Earth is not the only thing that has other things going around it, and secondly, Earth could be moving, as Jupiter does, and things would move with it. We wouldn't fly off the surface, and our moon wouldn't be left behind, and all this kind of stuff. So, that was a big breakthrough as well, but it wasn't as definitive, in my opinion, as the phases of Venus. Perhaps I'm revealing my ignorance, but I didn't realize how much data they were working with. So, it wasn't Einstein or Freud thinking in theories. It was a lot of data, and you're playing with it and seeing how to make sense of it. So, it isn't just coming up with completely abstract thought experiments. It's looking at the data, astronomy. Sure, and you look at Newton's great work, right, the Principia. It was based in part on Galileo's observations of balls rolling down inclined planes, supposedly falling off the leaning tower of Pisa, but that's probably apocryphal. In any case, the Inquisition actually did, or the Roman Catholic Church, did history a favor, not that I'm condoning them, but they placed Galileo under house arrest, and that gave Galileo time to publish, to assemble and publish the results of his experiments that he had done decades earlier. It's not clear he would have had time to do that, you know, had he not been under house arrest. And so, Newton, of course, very much used Galileo's observations. Let me ask the old Russian overly philosophical question about death. So, we're talking about the expanding universe. Sure. How do you think human civilization will come to an end if we avoid the near-term issues we're having? Will it be our sun burning out? Will it be comets? Will it be, what is it? Do you think we have a shot at reaching the heat death of the universe? Yeah. So, we're going to leave out the anthropogenic causes of our planet. Potential destruction, which I actually think are greater than the celestial causes. So, if we get lucky and intelligent, I don't know. Yeah. So, no way will we as humans reach the heat death of the universe. I mean, it's conceivable that machines, which I think will be our evolutionary descendants, might reach that, although even they will have less and less energy with which to work as time progresses, because eventually even the lowest mass stars burn out, although it takes them trillions of years to do so. So, the point is that certainly on Earth, there are other celestial threats, existential threats, comets, exploding stars, the sun burning out. So, we will definitely need to move away from our solar system to other solar systems. And then the question is, can they keep on propagating to other planetary systems sufficiently long? In our own solar system, the sun burning out is not the immediate existential threat. That'll happen in about 5 billion years when it becomes a red giant. Although I should hasten to add that within the next 1 or 2 billion years, the sun will have brightened enough that unless there compensatory atmospheric changes, the oceans will evaporate away, and you need much less carbon dioxide for the temperatures to be maintained roughly at their present temperature, and plants wouldn't like that very much. So, you can't lower the carbon dioxide content too much. So, within 1 or 2 billion years, probably the oceans will evaporate away. But on a sooner time scale than that, I would say an asteroid collision leading to a potential mass extinction or at least an extinction of complex beings such as ourselves that require quite special conditions unlike cockroaches and amoebas to survive. One of these civilization-changing asteroids is only 1 kilometer or so in diameter and bigger, and a true mass extinction event is 10 kilometers or larger. Now, it's true that we can find and track the orbits of asteroids that might be headed toward Earth, and if we find them 50 or 100 years before they impact us, then clever applied physicists and engineers can figure out ways to deflect them. But at some point, some comet will come in from the deep freeze of the solar system, and there we have very little warning, months to a year. LUIS So, what's a deep freeze, Sargent? SARGENT Oh, the deep freeze is sort of out beyond Neptune. There's this thing called the Kuiper Belt, and it consists of a bunch of dirty ice balls or icy dirt balls. It's the source of the comets that occasionally come close to the Sun. And then there's an even bigger area called the scattered disk, which is sort of a big donut surrounding the solar system way out there from which other comets come. And then there's the Oort cloud, W-O-O-R-T after Jan Oort, a Dutch astrophysicist. And it's the better part of a light year away from the Sun, so a good fraction of the distance to the nearest star. But that's like a trillion or 10 trillion comet-like objects that occasionally get disturbed by a passing star or whatever, and most of them go flying out of the solar system, but some go toward the Sun, and they come in with little warning. By the time we can see them, they're only a year or two away from us. And moreover, not only is it hard to determine their trajectories sufficiently accurately to know whether they'll hit a tiny thing like Earth, but outgassing from the comet of gases when the ices sublimate, that outgassing can change the trajectory just because of conservation of momentum, right? It's the rocket effect. Gases go out in one direction, the object moves in the other direction. And so since we can't predict how much outgassing there will be and in exactly what direction because these things are tumbling and rotating and stuff, it's hard to predict the trajectory with sufficient accuracy to know that it will hit. And you certainly don't want to deflect a comet that would have missed, but you thought it was going to hit and end up having it hit. That would be like the ultimate Charlie Brown, you know, goat instead of trying to be the hero, right? He ended up being the goat. What would you do if it seemed like in a matter of months that there is some non-zero probability, maybe a high probability that there would be a collision, sort of from a scientific perspective, from an engineering perspective? I imagine you would actually be in the room of people deciding what to do. What, philosophically, too. It's a tough one, right? Because if you only have a few months, that's not much time in which to deflect it. Early detection and early action are key. Because when it's far away, you only have to deflect it by a tiny little angle. And then by the time it reaches us, the perpendicular motion is big enough to miss Earth. All you need is one radius or one diameter of the Earth, right? That actually means that all you would need to do is slow it down so it arrives four minutes later, or speed it up so it arrives four minutes earlier and Earth will have moved through one radius in that time. So it doesn't take much. But you can imagine if a thing is about to hit you, you have to deflect it 90 degrees or more, right? And you don't have much time to do so, and you have to slow it down or speed it up a lot if that's what you're trying to do to it. And so decades is sufficient time, but months is not sufficient time. So at that point, I would think the name of the game would be to try to predict where it would hit. And if it's in a heavily populated region, try to start an orderly evacuation, perhaps. But that might cause just so much panic that I'm, how would you do it with New York City or Los Angeles or something like that, right? I might have a different opinion a year ago. I'm a bit disheartened by, you know, in the movies, there's always extreme competence from the government. Competence, yeah. Competence, yeah. Right, but we expect extreme incompetence, if anything, right? Yes, now, so I'm quite disappointed. But sort of from a medical perspective, I think you're saying there, and a scientific one, it's almost better to get better and better, maybe telescopes and data collection to be able to predict the movement of these things, or like come up with totally new technologies. Like you can imagine actually sending out, like, probes out there to be able to sort of almost have little finger sensors throughout our solar system to be able to detect stuff. Well, that's right. Yeah, monitoring the asteroid belt is very important. 99% of the so-called near-Earth objects ultimately come from the asteroid belt. And so there we can track the trajectories. And even if there's, you know, a close encounter between two asteroids, which deflects one of them toward Earth, it's unlikely to be on a collision course with Earth in the immediate future. It's more like, you know, tens of years. So that gives us time. But we would need to improve our ability to detect the objects that come in from a great distance. And fortunately, those are much rarer. The comets come in, you know, 1% of the collisions perhaps are with comets that come in without any warning, Harvey. And so that might be more like, you know, a billion or two billion years before one of those hits us. So maybe we have to worry about the sun getting brighter on that time scale. I mean, there's the possibility that a star will explode will explode near us in the next couple of billion years. But over the course of the history of life on Earth, the estimates are that maybe only one of the mass extinctions was caused by a star blowing up in particular, a special kind called a gamma ray burst. And I think it's the Ordovician Silurian, Ordovician Silurian extinction 420 or so, 440 million years ago, that is speculated to have come from one of these particular types of exploding stars called gamma ray bursts. But even there, the evidence is circumstantial. So those kinds of existential threats are reasonably rare. The greater danger I think is civilization changing events where it's a much smaller asteroid, which those are harder to detect or a giant solar flare that shorts out the grid in all of North America. Let's say now, you know, astronomers are monitoring the sun 24 seven with various satellites. And we can tell when there's a flare or a coronal mass ejection. And we can tell that in a day or two, a giant bundle of energetic particles will arrive and twang the magnetic field of earth and send all kinds of currents through long distance power lines. And that's what shorts out the transformers and transformers are, you know, expensive and hard to replace and hard to transport and all that kind of stuff. So if we can warn the power companies and they can shut down the grid before the big bundle of particle hits, then we will have mitigated much of this. Now, for a big enough bundle of particles, you can get short circuits even over small distance scales. So not everything will be saved, but at least the whole grid might not go out. So again, you know, astronomers, I like to say, support your local astronomer. They may help someday save humanity by telling the power companies to shut down the grid, finding the asteroid 50 or 100 years before it hits, then having clever physicists and engineers deflect it. So many of these cosmic threats, cosmic existential threats, we can actually predict and do something about or observe before they hit and do something about. So, you know. It's terrifying to think that people would listen to this conversation. It's like when you listen to Bill Gates talk about pandemics in his TED talk a few years ago and realizing we should have supported our local astronomer more. Well, I don't know whether it's more because as I said, I actually think human-induced threats or things that occur naturally on Earth, either a natural pandemic or perhaps a bioengineering type pandemic or something like a super volcano, right? There was one event, Toba, I think it was 70 plus thousand years ago that caused a gigantic decrease in temperatures on Earth because it sent up so much soot that it blocked the sun, right? It's the nuclear winter type disaster scenario that some people, including Carl Sagan, talked about decades ago. But we can see in the history of volcanic eruptions, even more recently in the 19th century, Tambora and other ones, you look at the record and you see rather large dips in temperature associated with massive volcanic eruptions. Well, these super volcanoes, one of which, by the way, exists under Yellowstone, you know, in the central US. I mean, it's not just one or two states. It's a gigantic region. And there's controversy as to whether it's likely to blow anytime in the next 100,000 years or so. But that would be perhaps not a mass extinction because you really need to, or perhaps not a complete existential threat because you have to get rid of sort of the very last humans for that. But at least getting rid of, you know, killing off so many humans, truly billions and billions of humans. There have been ones tens of thousands of years ago, including this one, Toba, I think it's called, where it's estimated that the human population was down to 10,000 or 5,000 individuals, something like that, right? If you have a 15 degree drop in temperature over quite a short time, it's not clear that even with today's advanced technology, we would be able to adequately respond at least for the vast majority of people. Maybe some would be in these underground caves where you'd keep the president and a bunch of other important people, you know, but the typical person is not going to be protected when all of agriculture is cut off, right? And when- It could be hundreds of millions or billions of people starving to death. Exactly, that's right. They don't all die immediately, but they use up their supplies. Or again, this electrical grid- First of toilet paper. There you go. Dash that toilet paper, you know. Or the electrical grid. I mean, imagine North America without power for a year, right? I mean, we've become so dependent. We're no longer the cave people. They would do just fine, right? What do they care about, the electrical grid, right? What do they care about? Agriculture. They're hunters and gatherers. But we now have become so used to our way of life that the only real survivors would be those rugged individualists who live somewhere out in the forest or in a cave somewhere, completely independent of anyone else. Yeah, recently I recommended- It's totally new to me, this kind of survivalist folks, but there's a lot of shows of those. But I saw one on Netflix and I started watching them. And they make a lot of sense. They reveal to you how dependent we are on all aspects of this beautiful systems we humans have built and how fragile they are. Incredibly fragile. And this whole conversation is making me realize how lucky we are. Oh, we're incredibly lucky, but we've set ourselves up to be very, very fragile. And we are intrinsically complex biological creatures that, except for the fact that we have brains and minds with which we can try to prevent some of these things or respond to them, we as a living organism require quite a narrow set of conditions in order to survive. We're not cockroaches. We're not going to survive a nuclear war. So, we're kind of this beautiful dance between... We've been talking about astronomy, that astronomy, the stars, inspires everybody. And at the same time, there's this pragmatic aspect that we're talking about. And so, I see space exploration as the same kind of way. That it's reaching out to other planets, reaching out to the stars, this really beautiful idea. But if you listen to somebody like Elon Musk, he talks about space exploration as very pragmatic. He has this ridiculous way of sounding like an engineer about it, which is like, it's obvious we need to become a multi-planetary species if we were to survive long term. So, maybe both philosophically, in terms of beauty, and in terms of practical, what's your thoughts on space exploration, on the challenges of it, on how much we should be investing in it, and on a personal level, how excited you are by the possibility of going to Mars, colonizing Mars, and maybe going outside the solar system? Yeah. Great question. There's a lot to unpack there, of course. Humans are, by their very nature, explorers, pioneers. They want to go out, climb the next mountain, see what's behind it, explore the ocean depths, explore space. This is our destiny, to go out there. And, of course, from a pragmatic perspective, yes, we need to plant our seeds elsewhere, really, because things could go wrong here on Earth. Now, some people say that's an excuse to not take care of our planet. Well, we say we're elsewhere, and so we don't have to take good care of our planet. No, we should take the best possible care of our planet. We should be cognizant of the potential impact of what we're doing. Nevertheless, it's prudent to have us be elsewhere as well. So, in that regard, I actually agree with Elon. It'd be good to be on Mars. That would be yet another place for us from which to explore still further. Would that be a good next step? Well, it's a good next step. I happen to disagree with him as to how quickly it will happen. Right? I mean, I think he's very optimistic. Now, you need visionary people like Elon to get people going and to inspire them. I mean, look at the success he's had with multiple companies. So, maybe he gives this very optimistic timeline in order to be inspirational to those who are going out there. And certainly, his success with the rocket that is reusable because it landed upright and all that, I mean, that's a game changer. It's sort of like every time you flew from San Francisco to Los Angeles, you discard the airplane, right? I mean, that's crazy, right? So, that's a game changer. But nevertheless, the time scale over which he thinks that there could be a real thriving colony on Mars, I think, is far too optimistic. What's the biggest challenges to you? One is just getting rockets, not rockets, but people out there. And two is the colonization. Do you have thoughts about this? The challenges of this kind of prospect? Yeah, I haven't thought about it in great detail other than recognizing that Mars is a harsh environment. You don't have much of an atmosphere there. You've got less than a percent of Earth's atmosphere. So, you'd need to build some sort of a dome right away, right? And that would take time. You need to melt the water that's in the permafrost or have canals dug from which you transport it from the polar ice caps. I was reading recently in terms of, like, what's the most efficient source of nutrition for humans that were to live on Mars? And people should look into this, but it turns out to be insects. Insects. Yeah. So, you want to build giant colonies of insects and just be eating them. Insects have a lot of protein, right? A lot of protein. And they're easy to grow. You can think of them as farming. Right. But it's not going to be as easy as growing a whole plot of potatoes like in the movie The Martian or something, right? It's not going to be that easy. So, there's this thin atmosphere. It's got the wrong composition. It's mostly carbon dioxide. There are these violent dust storms. The temperatures are generally cold. You'd need to do a lot of things. You need to terraform it basically in order to make it nicely livable without some dome surrounding you. And if you insist on a dome, well, that's not going to house that many people, right? So, let's look briefly then. We're looking for a new apartment to move into. So, let's look outside the solar system. Do you think you've spoken about exoplanets as well? Do you think there's a possible homes out there for us outside of our solar system? There are lots and lots of homes, possible homes. I mean, there's a planetary system around nearly every star you see in the sky. And one in five of those is thought to have a roughly Earth-like planet. And that's a relatively new... Yeah, it's a new discovery. I mean, the Kepler satellite, which was flying around above Earth's atmosphere, was able to monitor the brightness of stars with exquisite detail. And they could detect planets crossing the line of sight between us and the star, thereby dimming its light for a short time ever so slightly. And it's amazing. So, there are now thousands and thousands of these exoplanet candidates of which something like 90% are probably genuine exoplanets. And you have to remember that only about 1% of stars have their planetary system-oriented edge on to your line of sight, which is what you need for this transit method to work, right? Some arbitrary angle won't work, and certainly perpendicular to your line of sight, that is, in the plane of the sky won't work because the planet is orbiting the star and never crossing your line of sight. So, the fact that they found planets orbiting about 1% of the stars that they looked at in this field of 150-plus thousand stars, they found planets around 1%. You then multiply by the inverse of 1%, which is, you know, right? 1% is about how many... About what the fraction of the stars that have their planetary system oriented the right way. And that already, back of the envelope calculation, tells you that of order, 50% to 100% of all stars have planets, okay? And then they've been finding these Earth-like planets, et cetera, et cetera. So, there are many potential homes. The problem is getting there, okay? So, then a typical bright star, Sirius, the brightest star in the sky, maybe not a typical bright star, but it's 8.7 light years away, okay? So, that means the light took 8.7 years to reach us. We're seeing it as it was about nine years ago, okay? So, then, you know, you ask how long would a rocket take to get there at Earth's escape speed, which is 11 kilometers per second, okay? And it turns out it's about a quarter of a million years, okay? Now, that's 10,000 generations, okay? Let's say a generation of humans is 25 years, right? So, you'd need this colony of people that is able to sustain itself all their food, all their waste disposal, all their water, all their recycling of everything. For 10,000 generations, they have to commit themselves to living on this vehicle, right? I just don't see it happening. What I see potentially happening if we avoid self-destruction, intentional or unintentional, here on Earth, is that machines will do it, robots that can essentially hibernate. They don't need to do much of anything for a long, long time as they're traveling. And moreover, if some energetic charged particle, some cosmic ray hits the circuitry, it fixes itself, right? Machines can do this. I mean, it's a form of artificial intelligence. You just tell the thing, fix yourself, basically. And then, when you land on the planet, start producing copies of yourself, initially from materials that were perhaps sent, or you just have a bunch of copies there. And then, they set up, you know, factories with which to do this. I mean, this is very, very futuristic. But it's much more feasible, I think, than sending flesh and blood over interstellar distances, a quarter of a million years to even the nearest stars. You're subject to all kinds of charged particles and radiation. You have to, you know, shield yourself really well. That's, by the way, one of the problems of going to Mars, is that it's not a three-day journey like going to the moon. You're out there for the better part of a year or two. And you're exposed to lots of radiation, which typically doesn't do well with living tissue, right? Or living tissue doesn't do well with the radiation. And the hope is that the robots, the AI systems might be able to carry the fire of consciousness, whatever makes us humans. Yeah. Like a little drop of whatever makes us humans so special, not to be too poetic about it. No, but I like being poetic about it because it's an amazing question. You know, is there something beyond just the bits, the ones and zeros to us? You know, it's an interesting question. I like to think that there isn't anything, and that how beautiful it is that our thoughts, our emotions, our feelings, our compassion all come from these ones and zeros, right? That, to me, actually is a beautiful thought. And the idea that machines, silicon-based life effectively, could be our natural evolutionary descendants, not from a DNA perspective, but they are our creations and they then carry on. That, to me, is a beautiful thought in some ways, but others find it to be a horrific thought. So that's exciting to you. It is exciting to me as well. Because to me, from a purely an engineering perspective, I believe it's impossible to create, like whatever systems we create that take over the world, it's impossible for me to imagine that those systems will not carry some aspect of what makes humans beautiful. So like a lot of people have these kind of paperclip ideas that we'll build machines that are cold inside, or philosophers call them zombies, that naturally, the systems that will out-compete us on this earth will be cold and non-conscious, not capable of all the human emotions and empathy and compassion and love and hate, the beautiful mix of what makes us human. But to me, intelligence requires all of that. So in order to out-compete humans, you better be good at the full picture. Right. So artificial general intelligence, in my view, encompasses a lot of these attributes that you just talked about. Like curiosity, inquisitiveness, you know, right? It might look very different than us humans, but it will have some of the magic. But it'll also be much more able to survive the onslaught of existential threats that either we bring upon ourselves or don't anticipate here on earth, or that occasionally come from beyond, and there's nothing much we can do about a supernova explosion that just suddenly goes off. And really, if we want to move to other planets outside our solar system, I think realistically, that's a much better option than thinking that humans will actually make these gigantic journeys. And, you know, then I do this calculation for my class, you know, Einstein's special theory of relativity says that you can do it in a short amount of time in your own frame of reference if you go close to the speed of light. But then you bring in E equals mc squared, and you figure out how much energy it takes to get you accelerated to close enough to the speed of light to make the time scale short in your own frame of reference. And the amount of energy is just unfathomable, right? We can do it at the Large Hadron Collider with protons, you know, we can accelerate them to 99.9999% of the speed of light. But that's just a proton. We're gazillions of protons, okay? And that doesn't even count the rocket that would carry us the payload. And you would need to either either store the fuel in the rocket, which then requires even more mass for the rocket, or collect fuel along the way, which you know, is difficult. And so getting close to the speed of light, I think is not an option either, other than for a little tiny thing like, you know, Yuri Milner and others are thinking about this, the Starshot project where they'll send a little tiny camera to Alpha Centauri 4.2 light years away, they'll zip past it, take a picture of the exoplanets that we know orbit that three or more star system and say hello, real quick, say hello real quickly, and then send the images back to us. Okay. So that's a tiny little thing, right? Maybe you can accelerate that to they're hoping 20% of the speed of light with a whole bunch of high powered lasers aimed at it. It's not clear that other countries will allow us to do that, by the way. But that's a very forward looking thought. I mean, I very much support the idea. But there's a big difference between sending a little tiny camera and sending a payload of people with equipment that could then mine the resources on the exoplanet that they reach and then go forth and multiply, right? Well, let's talk about the big galactic things and how we might be able to leverage them to travel fast. I know this is a little bit science fiction, but you know, ideas of wormholes and the ideas at the edge of black holes that reveal to us that this fabric of space time is, could be messed with. Yeah. Perhaps. Is that at all an interesting thing for you? I mean, in looking out at the universe and studying it as you have, is that also a possible, like a dream for you that we might be able to find clues how we can actually use it to improve our transportation? It's an interesting thought. I'm certainly excited by the potential physics that suggests this kind of faster than light travel effectively, or, you know, cutting the distance to make it very, very short through a wormhole or something like that. Possible? No? Well, you know, call me not very imaginative, but based on today's knowledge of physics, which I realize, you know, people have gone down that rabbit hole. And, you know, a century ago, Lord Kelvin, one of the greatest physicists of all time said that all of fundamental physics is done, the rest is just engineering. And guess what? Then came special relativity, quantum physics, general relativity, how wrong he was. So, let me not be another Lord Kelvin. On the other hand, I think we know a lot more now about what we know and what we don't know and what the physical limitations are. And to me, most of these schemes, if not all of them, seem very far-fetched, if not impossible. So, travel through wormholes, for example. You know, it appears that for a non-rotating black hole, that's just a complete no-go because the singularity is a point-like singularity and you have to reach it to traverse the wormhole and you get squished by the singularity. Okay. Now, for a rotating black hole, it turns out there is a way to pass through the event horizon, the boundary of the black hole, and avoid the singularity and go out the other side or even traverse the donut hole-like singularity. In the case of a rotating black hole, it's a ring singularity. So, there's actually two theoretical ways you could get through a rotating black hole or a charged black hole, not that we expect charged black holes to exist in nature because they would quickly bring in the opposite charge so as to neutralize themselves. But rotating black holes, definitely a reality. We now have good evidence for them. Do they have traversable wormholes? Probably not because it's still the case that when you go in, you go in with so much energy that it either squeezes the wormhole shut or you encounter a whole bunch of incoming and outgoing energy that vaporizes you. It's called the mass inflation instability and it just sort of vaporizes you. Nevertheless, you could imagine, well, you're in some vapor form, but if you make it through, maybe you could reform or something. Yeah. So, it's still information. Yeah, it's still information. It's scrambled information, but there's a way maybe of bringing it back, right? But then the thing that really bothers me is that as soon as you have this possibility of traversal of a wormhole, you have to come to grips with a fundamental problem and that is that you could come back to your universe at a time prior to your leaving and you could essentially prevent your grandparents from ever meeting. This is called the grandfather paradox, right? And if they never met and if your parents were never born and if you were never born, how would you have made the journey to prevent the history from allowing you to exist, right? It's a violation of causality of cause and effect. Now, physicists such as myself take causality violation very, very seriously. We've never seen it. You took a stand. Yeah. I mean, it's one of these back to the future type movies, right? And you have to work things out in such a way that you don't mess things up, right? Some people say that, well, you come back to the universe, but you come back in such a way that you cannot affect your journey. But then, I mean, that seems kind of contrived to me. Or some say that you end up in a different universe and this also goes into the many different types of the multiverse hypothesis and the many worlds interpretation and all that. But again, then it's not the universe from which you left, right? And you don't come back to the universe from which you left. And so, you're not really going back in time to the same universe. And you're not even going forward in time necessarily then to the same universe, right? You're ending up in some other universe. So, what have you achieved, right? You've traveled. You've traveled. You ended up in a different place than you started in more ways than one. Yeah. And then there's this idea, the Alcubierre drive, where you warp space-time in front of you so as to greatly reduce the distance and you can expand the space-time behind you. So, you're sort of riding a wave through space-time. But the problem I see with that beyond the practical difficulties and the energy requirements, and by the way, how do you get out of this bubble through which you're riding this wave of space-time? And Miguel Alcubierre acknowledged all these things. He said, this is purely theoretical, fanciful, and all that. But a fundamental problem I see is that you'd have to get to those places in front of you so as to change the shape of space-time, so as to make the journey quickly. But to get there, you got there in the normal way at a speed considerably less than that of light. So, in a sense, you haven't saved any time, right? You might as well have just taken that journey and gotten to where you were going. Yeah, there's- Right? What have you done? It's not like you snap your fingers and say, okay, let that space there be compressed and then I'll make it over to Alpha Centauri in the next month. You can't snap your fingers and do that. Yeah. But we're sort of assuming that we can fix all the biological stuff that requires for humans to persist through that whole process, because ultimately it might boil down to just extending the life of the human in some form, whether it's through the robot, through the digital form, or actually just figuring out genetically how to live forever. That's right. Because that journey that you mentioned, the long journey, might be different if somehow our understanding of genetics, of our understanding of our own biology, all that kind of stuff would- That's another trajectory that possibly- Well, right. If you could put us into some sort of suspended animation, hibernation or something, and greatly increase the lifetime. And so, these 10,000 generations I talked about, what do they care? It's just one generation and they're asleep, okay? Just a long nap. So, then you can do it. It's still not easy, right? Because you've got some big old huge colony and that just through E equals MC squared, right? That's a lot of mass. That's a lot of stuff to accelerate. The Newtonian kinetic energy is gigantic, right? So, you're still not home free, but at least you're not trying to do it in a short amount of clock time, right? Which, if you look at E equals MC squared, requires truly unfathomable amounts of energy because the energy is sort of, it's your rest mass, M naught C squared, divided by the square root of the square root of one minus V squared over C squared. And if your listeners want to just sort of stick into their pocket calculator, as V over C approaches one, that one over the square root of one minus V squared over C squared approaches infinity. So, if you wanted to do it in zero time, you'd need an infinite amount of energy. That's basically why you can't reach, let alone exceed the speed of light for a particle moving through a preexisting space. It's that it takes an infinite amount of energy to do so. So, that's talking about us going somewhere. What about, one of the things that inspires a lot of folks, including myself, is the possibility that there's other, that this conversation is happening on another planet in different forms with the intelligent life forms. Well, first we could start, as a cosmologist, what's your intuition about whether there is or isn't intelligent life out there, outside of our own? Yeah. I would say I'm one of the pessimists in that I don't necessarily think that we're the only ones in the observable universe, which goes out roughly 14 billion years in light travel time and more like 46 billion years when you take into account the expansion of space. So, the diameter of our observable universe is something like 90, 92 billion light years. That encompasses 100 billion to a trillion galaxies with 100 billion stars each. So, now you're talking about something like 10 to the 22nd, 10 to the 23rd power stars and roughly an equal number of Earth-like planets and so on. So, there may well be other intelligent life. But your sense is our galaxy is not teeming with life. Yeah. Our galaxy, our Milky Way galaxy with several hundred billion stars and potentially habitable planets is not teeming with intelligent life. Intelligent. Yeah. Well, I'll get to the primitive life, the bacteria in a moment. But we may well be the only ones in our Milky Way galaxy, at most a handful I'd say, but I'd probably side with the school of thought that suggests we're the only ones in our own galaxy. Just because I don't see human intelligence as being a natural evolutionary path for life. I mean, there's a number of arguments. First of all, there's been more than 10 billion species of life on Earth in its history. Nothing has approached our level of intelligence and mechanical ability and curiosity. Whales and dolphins appear to be reasonably intelligent, but there's no evidence that they can think abstract thoughts that they're curious about the world. They certainly can't build machines with which to study the world. So, that's one argument. Secondly, we came about as early hominids only four or five million years ago, and as Homo sapiens only about a quarter of a million years ago. So, for the vast majority of the history of life on Earth, an intelligent alien zipping by Earth would have said, there's nothing particularly intelligent or mechanically able on Earth, okay? Yeah. Thirdly, it's not clear that our intelligence is a long-term evolutionary advantage. Now, it's clear that in the last 100 years, 200 years, we've improved the lives of millions, hundreds of millions of people, but at the risk of potentially destroying ourselves, either intentionally or unintentionally or through neglect, as we discussed before. That's a really interesting point, which is, it's possible that there are a huge amount of intelligent civilizations have been born even through our galaxy, but they live very briefly. There are flashbulbs in the night. That brings me to the fourth issue, and that is the Fermi paradox. If they're common, where the hell are they? Notwithstanding the various UFO reports in Roswell and all that, they just don't meet the bar. They don't clear the bar of scientific evidence, in my opinion, okay? So, there's no clear evidence that they've ever visited us on Earth here. And SETI has been now, the search for extraterrestrial intelligence has been scanning the skies. And true, we've only looked a couple of hundred light years out, and that's a tiny fraction of the whole galaxy, a tiny fraction of these 100 billion plus stars. Nevertheless, you know, if the galaxy were teeming with life, especially intelligent life, you'd expect some of it to have been far more advanced than ours, okay? There's nothing special about when the industrial revolution started on Earth, right? The chemical evolution of our galaxy was such that billions of years ago, nuclear processing and stars had built up clouds of gas after their explosion that were rich enough and heavy elements to have formed Earth-like planets, even billions of years ago. So, there could be civilizations that are billions of years ahead of ours. And if you look at the exponential growth of technology among Homo sapiens in the last couple of hundred years, and you just project that forward, I mean, there's no telling what they could have achieved even in 1,000 or 10,000 years, let alone a million or 10 million or a billion years. And if they reach this capability of interstellar travel and colonization, then you can show that within 10 million years or certainly 100 million years, you can populate the whole galaxy, all right? So, then you don't have to have tried to detect them beyond 100 or 1,000 light years. They would already be here. Lex Doppelganger Do you think, as a thought experiment, do you think it's possible that they are already here, but we humans are so human-centric that we're just not, like, our conception of what intelligent life looks like is, we don't want to acknowledge it. Like, what if trees? David Erickson Right, right, right. Yeah. Lex Doppelganger Okay, I guess in a form of a question, do you think we'll actually detect intelligent life if it came to visit us? David Erickson Yeah, I mean, it's like, you know, you're an ant crawling around on a sidewalk somewhere, and do you notice the humans wandering around? And the Empire State Building and, you know, rocket ships flying to the moon and all that kind of stuff, right? It's conceivable that we haven't detected it and that we're so primitive compared to them that we're just not able to do so. Lex Doppelganger Like, if you look at dark energy, maybe we call it as a field. David Erickson It's just that my own feeling is that in science now, through observations and experiments, we've measured so many things. And basically, we understand a lot of stuff. Lex Doppelganger Fabric of reality. David Erickson Yeah, the fabric of reality, we understand quite well. And there are a few little things like dark matter and dark energy that may be some sign of some super intelligence, but I doubt it. Okay, you know, why would some super intelligence be holding clusters of galaxies together? Why would they be responsible for accelerating the expansion of the universe? So the point is, is that through science and applied science and engineering, we understand so much now that I'm not saying we know everything, but we know a hell of a lot. Okay? And so there's, it's not like there are lots of mysteries flying around there that are completely outside our level of exploration or understanding. Lex Doppelganger Yeah, from a, I would say, from the mystery perspective, it seems like the mystery of our own cognition and consciousness is much grander than, like, the degrees of freedom of possible explanations for what the heck is going on is much greater there than in the physics of the observable. David Erickson Exactly, how the brain works, how did life arise? Yeah, big, big questions. But they, to me, don't indicate the existence of an alien or something. I mean, unless we are the aliens, you know, we could have been contamination from some rocket ship that hit here a long, long time ago, and all evidence of it has been destroyed. But again, that alien would have started out somewhere. They're not here watching us right now, right? They're not among us. And so, though there are potential explanations for the Fermi paradox, and one of them that I kind of like is that the truly intelligent creatures are those that decided not to colonize the whole galaxy because they'd quickly run out of room there because it's exponential, right? You send a probe to a planet, it makes two copies, they go out, they make two copies each, and it's an exponential, right? They quickly colonize the whole galaxy. But then the distance to the next galaxy, the next big one like Andromeda, that's two and a half million light years. That's a much grander scale now, right? And so, it also could be that the reason they survived this long is that they got over this tendency that may well exist among sufficiently intelligent creatures, this tendency for aggression and self-destruction, right? If they bypass that, and that may be one of the great filters if there are more than one, right, then they may not be a type of creature that feels the need to go and say, oh, there's a nice-looking planet, and there's a bunch of ants on it, let's go squish them and colonize it. No, it could even be the kind of Star Trek-like prime directive where you go and explore worlds, but you don't interfere in any way, right? And also, we call it exploration, it's beautiful and everything, but there is underlying this desire to explore is a desire to conquer. Yeah. I mean, if we're just being really honest about- Right now, for us, it is, right? And you're saying it's possible to separate, but I would venture to say that those are coupled. So, I could imagine a civilization that lives on for billions of years that just stays on, it's like figures out the minimal effort way of just peacefully existing. It's like a monastery. Yeah, and it limits itself. Yeah, it limits itself. You know, it's planted its seeds in a number of places, so it's not vulnerable to a single point failure, right? Supernova going off near one of these stars or something, or an asteroid, some are a comet coming in from the Oort cloud equivalent of that planetary system and without warning, thrashing them to bits. So, they've got their seeds in a bunch of places, but they chose not to colonize the galaxy. And they also choose not to interfere with this incredibly primitive organism, Homo sapiens, right? Or this is like a TV show for them. Yeah, it could be like a TV show, right? So, they just tuned in. Right. So, those are possible explanations, yet I think that to me, the most likely explanation for the Perimet Paradox is that they really are very, very rare. And you know, Carl Sagan estimated 100,000 of them. If there's that many, some of them would have been way ahead of us and I think we would have seen them by now. If there are a handful, maybe they're there, but at that point, you're right on this dividing line between being a pessimist and an optimist. Yeah. And what are the odds for that, right? If you look at all the things that had to go right for us. And then, you know, getting back to something you said earlier, let's discuss, you know, primitive life. That could be the thing that's difficult to achieve, just getting the random molecules together to a point where they start self-replicating and evolving and becoming better and all that. That's an inordinately difficult thing, I think, though I'm not, you know, some molecular or cell biologist, but just it's the usual argument, you know, you're wandering around in the Sahara desert and you stumble across a watch. Is your initial response, oh, you know, a bunch of sand grains just came together randomly and formed this watch? No, you think that something formed it or it came from some simpler structure that then became, you know, more complex. All right. It didn't just form. Well, even the simplest life is a very, very complex structure. Even the simplest prokaryotic cells, not to mention eukaryotic cells, although that transition may have been the so-called great filter as well. Maybe the cells without a nucleus are relatively easy to form. And then the big next step is where you have a nucleus, which then provides a lot of energy, which allows the cell to become much, much more complex and so on. Interestingly, going from eukaryotic cells, single cells to multicellular organisms does not appear to be at least on Earth, one of these great filters, because there's evidence that it happened dozens of times independently on Earth. So by a really great filter, something that happens very, very rarely, I mean that we had to get through an obstacle that is just incredibly rare to get through. And one of the really exciting scientific things is that that particular point is something that we might be able to discover even in our lifetimes that find life elsewhere, like Europa or be able to... That would be bad news, right? Because if we find lots of pretty advanced life, that would suggest, and especially if we found some defunct fossilized civilization or something somewhere else, that would be... Of bacteria, you mean, of like... What's that? Defunct civilization of like primitive life forms. I'm sorry, I switched gears there. If we found some intelligent or even trilobites and stuff elsewhere, that would be bad news for us because that would mean that the great filter is ahead of us, right? Because it would mean that lots of things have gotten roughly to our level. But given the Fermi paradox, if you accept that the Fermi paradox means that there's no one else out there, you don't necessarily have to accept that, but if you accept that it means that no one else is out there, and yet there are lots of things we found that are at or roughly at our level, that means that the great filter is ahead of us and that bodes poorly for our long-term future. It's funny you said... You started by saying you're a little bit on the pessimistic side, but it's funny because we're doing this kind of dance between pessimism and optimism because I'm not sure if us being alone in the observable universe as intelligent beings is pessimistic. Well, it's good news in a sense for us because it means... We're special?...that we made it through. Oh, right. See, if we're the only ones and there are such great filters, maybe more than one, formation of life might be one of them, formation of eukaryotic, that is, with the nucleus cells, be another. Development of human-like intelligence might be another, right? There might be several such filters and we were the lucky ones. And then people say, well, then that means you're putting yourself into a special perspective and every time we've done that, we've been wrong. And yeah, yeah, I know all those arguments, but it still could be the case that there's one of us, at least per galaxy or per 10 or 100 or 1,000 galaxies, and we're sitting here having this conversation because we exist. And so there's an observational selection effect there, right? Just because we're special doesn't mean that we shouldn't have these conversations about whether or not we're special, right? Yeah. So that's exciting. That's optimistic. So that's the optimistic part, that if we don't find other intelligent life there, it might mean that we're the ones that made it. And in general, outside the great filter and so on, it's not obvious that the Stephen Hawking thing, which is, it's not obvious that life out there is going to be kind to us as humans. Oh, yeah. So I knew Hawking and I greatly respect his scientific work and in particular, the early work on the unification of general theory of relativity and quantum physics, two great pillars in modern physics, Hawking radiation and all that, fantastic work. If you were alive, you should have been a recipient of this year's physics Nobel Prize, which was for the discovery of black holes and also by Roger Penrose for the theoretical work showing that given a star that's massive enough, you basically can't avoid having a black hole. Anyway, Hawking, fantastic. I tip my hat to him. May he rest in peace. That would have been a heck of a Nobel Prize, black holes. Yeah, yeah, yeah. A heck of a good group. But going back to what he said, that we shouldn't be broadcasting our presence to others, there I actually disagree with him respectfully, because first of all, we've been unintentionally broadcasting our presence for 100 years since the development of radio and TV. Okay. Secondly, any alien that has the capability of coming here and squashing us, either already knows about us and doesn't care because we're just like little ants. And when there are ants in your kitchen, you tend to squash them. But if there are ants on the sidewalk and you're walking by, do you feel some great conviction that you have to squash any of them? No, you generally don't, right? We're irrelevant to them. All they need to do is keep an eye on us to see whether we're approaching the kind of technological capability and know about them and have intentions of attacking them, and then they can squash us, right? You know, they could have done it long ago. They'll do it if they want to, whether we advertise our presence or not is irrelevant. So I really think that that's not a huge existential threat. So this is a good place to bring up a difficult topic. You mentioned they would be paying attention to us to see if we come up with any crazy technology. There's folks who have reported UFO sightings. There's actually, I've recently found out there's websites that track this, the data of these reportings, and there's millions of them in the past several decades, so seven decades and so on, that they've been recorded. And the UFOlogist community, as they refer to themselves, you know, one of the ideas that I find compelling from an alien perspective that they kind of started showing up ever since we figured out how to build nuclear weapons. Mm-hmm. What a coincidence. Yeah. So I mean, you know, if I was an alien, I would start showing up then as well. Well, why not just observe us from afar? No, I know, right. I would figure out, but that's why I'm always keeping a distance and staying blurry. But... Very pixelated. Very pixelated. You know, there is something in the human condition that, a cognition that wants to see, wants to believe beautiful things, and some are terrifying, some are exciting. Goats, Bigfoot is a big fascination for folks. And UFO sightings, I think, falls into that. There's people that look at lights in the night sky and I mean, it's kind of a downer to think in a skeptical sense, to think that's just a light. Yeah. You want to feel like there's something magical there. Sure. I mean, I felt that first when my dad, my dad's a physicist, when he first told me about ball lightning when I was like a little kid. Very weird. Very, like, weird physical phenomenon. And he said his intuition was, tell me about this, his intuition was, tell me this as a little kid, like, I really like math. His intuition was, whoever figures out ball lightning will get a Nobel Prize. I think that was a side comment he gave me. I decided there when I was like five years old or whatever, I'm going to win a Nobel Prize for figuring out ball lightning. That was like one of the first sort of sparks of the scientific mindset. Those mysteries, they capture your imagination. I think when I speak to people that report UFOs, that's that fire, that's what I see, that excitement. Yeah, I understand that. But what do we do with that? Because there's hundreds of thousands, if not millions, and then the scientific community, you're like the perfect person. You have an awesome Einstein shirt. What do we do with those reports? It's most of the scientific community kind of rolls their eyes and dismisses it. Is it possible that a tiny percent of those folks saw something that's worth deeply investigating? Sure, we should investigate it. It's just one of these things where, you know, they've not brought us a hunk of kryptonite or something like that, right? They haven't brought us actual, tangible, physical evidence with which experiments can be done in laboratories. It's anecdotal evidence. The photographs are, in some cases, in most cases, I would say, quite ambiguous. I don't know what to think about. So, David Fravor is the first person. He's a Navy pilot, commander, and there's a bunch of them, but he's sort of one of the most legit pilots and people I've ever met. The fact that he saw something weird, he doesn't know what the heck it is, but he saw something weird. I mean, I don't know what to do with that. And on the psychological side, I'm pretty confident he saw what he says he saw, which he's saying is something weird. One of the interesting psychological things that worries me is that everybody in the Navy, everybody in the US government, everybody in the scientific community just kind of like pretended that nothing happened. That kind of instinct, that's what makes me believe if aliens show up, we would all just ignore their presence. That's what bothered me, that you don't investigate it more carefully and use this opportunity to inspire the world. So, in terms of Kryptonite, I think the conspiracy theory folks, say that whenever there is some good hard evidence that scientists would be excited about, there's this kind of conspiracy that I don't like because it's ultimately negative, that the US government will somehow hide the good evidence to protect it. Of course, there's some legitimacy to it because you want to protect military secrets, all that kind of stuff. But I don't know what to do with this beautiful mess because I think millions of people are inspired by UFOs. And it feels like an opportunity to inspire people about science. So, I would say, as Carl Sagan used to say, extraordinary claims require extraordinary evidence, right? I've quoted him a number of times. We would welcome such evidence. On the other hand, a lot of the things that are seen or perhaps even hidden from us, you could imagine for military purposes, surveillance purposes, the US government doesn't want us to know, or maybe some of these pilots saw Soviet or Israeli or whatever satellites, right? A lot of the or some of the crashes that have occurred were later found to be weather balloons or whatever. When there are more conventional explanations, science tends to stay away from the sensational ones, right? And so, it may be that someone else's calling in life is to investigate these phenomena. And I welcome that as a scientist. I don't categorically actually deny the possibility that ships of some sort could have visited us because, as I said earlier, at slow speeds, there's no problem in reaching other stars. In fact, our Voyager and Pioneer spacecraft in a few million years are going to be in the vicinity of different stars. We can even calculate which ones they're going to be in the vicinity of, right? So, there's nothing that breaks any laws of physics if you do it slowly. But that's different, you know, just having Voyager or Pioneer fly by some star, that's different from having active aliens altering the trajectory of their vehicle in real time spying on us, and then either zipping back to their home planet or sending signals that tell them about us because they are likely many years, many light years away, and they're not going to have broken that barrier as well, okay, right? So, I just, you know, go ahead, study them. Great. You know, for some young kid who wants to do it, it might be their calling, and that's how they might find meaning in their lives is to be the scientist who really explores these things. I chose not to because at a very young age, I found the evidence to the degree that I investigated it to be really quite unconvincing, and I had other things that I wanted to do. But I don't categorically deny the possibility, and I think it should be investigated. Yeah, I mean, this is one of those phenomena that 99.9% of people are almost definitely, there's conventional explanations, and then there's like mysterious things that probably have explanations that are a little bit more complicated, but there's not enough to work with. I tend to believe that if aliens showed up, there will be plenty of evidence for scientists to study. And exactly, as you said, avoid your type of spacecraft. I could see sort of some kind of a dumb thing, almost like a sensor that's like probing, like statistically speaking. Flying by. Flying by, maybe lands, maybe there's some kind of robot type of thingies that just like move around and so on, like in ways that we don't understand. But I feel like, well, I feel like there'll be plenty of hard to dismiss evidence. And I also, especially this year, believe that the US government is not sufficiently competent, given the huge amount of evidence that will be revealed from this kind of thing, to conceal all of it. At least in modern times, you can say maybe decades ago, but in modern times. But the people I speak to, and the reason I bring it up is because so many people write to me, they're inspired by it. By the way, I wanted to comment on something you said earlier. Yeah, I had said that I'm sort of a pessimist in that I think there are very few other intelligent, mechanically able creatures out there. But then I said, yes, in a sense, I'm an optimist, as you pointed out, because it means that we made it through the great filter, right? I meant originally that I'm a pessimist in that I'm pessimistic about the possibility that there are many, many of us out there. Yeah, mathematically speaking, in the Drake equation. Exactly, right, right. But it may mean a good thing for our ultimate survival, right? So I'm glad you caught me on that. Yeah, I definitely agree with you. It is ultimately an optimistic statement. But anyway, I think UFO research is interesting. And I guess one of the reasons I've not been terribly convinced is that I think there are some scientists who are investigating this, and they've not found any clear evidence. Now, I must admit, I have not looked through the literature to convince myself that there are many scientists doing systematic studies of these various reports. I can't say for sure that there's a critical mass of them. But it's just that you never get these reports from hardcore scientists. That's the other thing. And astronomers, you know, what do we do? We spend our time studying the heavens, and you'd think we'd be the ones that are most likely, aside from pilots, perhaps, at seeing weird things in the sky. And we just never do, of the unexplained UFO type nature. Yeah, I definitely, I try to keep an open mind. But for people who listen, it's actually really difficult for scientists. Like I get probably, like this year, I've probably gotten over, probably maybe over 1000 emails on the topic of AGI. It's very difficult to, you know, people write to me, it's like, how can you ignore this, in AGI side, like this model? This is obviously the model that's going to achieve general intelligence. How can you ignore it? I'm giving you the answer. Here's my document. And there always just these large write-ups. The problem is, it's very difficult to weed through a bunch of BS. Right. It's very possible that you actually saw the UFO, but you have to acknowledge, by UFO I mean an extraterrestrial life, you have to acknowledge the hundreds of thousands of people who are a little bit, if not a lot, full of BS. And from a scientist's perspective, it's really hard work. And when there's amazing stuff out there, it's like, why invest in Bigfoot, when evolution in all of its richness is beautiful. Who cares about a monkey that walks on two feet, or eight, or whatever? In a sense, it's like there's a zillion decoys at observatories. True fact. We get lots and lots of phone calls when Venus, the evening star, but just really a bright planet, happens to be close to the crescent moon, because it's such a striking pair. This happens once in a while. So we get these phone calls, oh, there's a UFO next to the moon. And no, it's Venus. And so, they're just, and I'm not saying the best UFO reports are of that nature. No, there are some much more convincing cases, and I've seen some of the footage and blah, blah, blah. But it's just, there's so many decoys, right? So much noise that you have to filter out. And there's only so many scientists, so it's hard. There's only so much time as well, and you have to choose what problems you work on. This might be a fun question to ask, to kind of explore the idea of the expanding universe. So, the radius of the observable universe is 45.7 billion light years, and the age of the universe is 13.7 billion years. That's less than the radius of the universe. How's that possible? So, that's a great question. So, I meant to bring a little prop I have with ping pong balls and a rubber hose, a rubber band. I use it in many of the lectures that one can find of me online. But you have in an expanding universe, the space itself between galaxies, or more correctly, clusters of galaxies expanding. So, imagine light going from one cluster to another. It traverses some distance, and then while it's traversing the rest, that part that it already traveled through continues to expand. Now, 13.7 billion years might have gone by since the light that we are seeing from the early stages, the so-called cosmic microwave background radiation, which is the afterglow of the Big Bang or the echo of the Big Bang. Yeah, 13.7 billion years have gone by. That's how long it's taken that light to reach us. But while it's been traveling that distance, the parts that it already traveled continue to expand. So, it's like you're walking at an airport on one of these walkways, and you're walking along because you're trying to get to your terminal, but the walkway is continuing as well. You end up traveling a greater distance or the same distance faster is another way of putting it, right? That's why you get on one of these traveling walkways. So, you get roughly a factor of pi, but it's more like 3.2, I think. But when you work it all out, you multiply the number of years the universe has been in existence by three and a quarter or so, and that's how you get this 46 billion light year radius. But how is that? Let me ask some nice dumb questions. How is that not traveling faster than the speed of light? Yeah, it's not traveling faster than the speed of light because locally, at any point, if you were to measure the light, the photon zipping past, it would not be exceeding the speed of light. The speed of light is a locally measured quantity. After light has traversed some distance, if the rubber band keeps on stretching, then yes, it looks like the light traveled a greater distance than it would have had the space not been expanding. But locally, it never was exceeding the speed of light. It's just that the distance through which it already traveled then went off and expanded on its own some more. And if you give the light credit, so to speak, for having traversed that distance, well, then it looks like it's going faster than the speed of light. But that's not what's happening. Right, that's not how speed works. And in relativity, also, the other thing that is interesting is that if you take two ping pong balls that are sufficiently far apart, especially in an accelerating universe, you can easily have them moving apart from one another faster than the speed of light. So take two ping pong balls that were originally 400,000 kilometers from each other and let every centimeter in your rubber band expand to two in one second. Then suddenly, this 400,000 kilometer distance is 800,000 kilometers. It went out by 400,000 kilometers in one second. That exceeds the 300,000 kilometer per second speed of light. But that light limit, that particle limit in special relativity applies to objects moving through a preexisting space. There's nothing in either special or general relativity that prevents space itself from expanding faster than the speed of light. That's no problem. Einstein wouldn't have had a problem with a universe as observed now by cosmologists. Yeah, I'm not sure I'm yet ready to deal emotionally with expanding space. That to me is one of the most awe-inspiring things, starting from the Big Bang. It's definitely abstract. It's space itself is expanding. Right. Can we talk about the Big Bang a little bit? Sure, yeah, yeah. So, the entirety of it, the universe was very small. Right, but it was not a point. It was not a point. Okay, because if we live in what's called a closed universe now, a sphere or the three-dimensional version of that would be a hypersphere. Then regardless of how far back in time you go, it was always that topological shape. You can't turn a point suddenly into a shell, okay? It always had to be a shell. So, when people say, well, the universe started out as a point, that's being kind of flippant, kind of glib. It didn't really. It just started out at a very high density and we don't know actually whether it was finite or infinite. I think personally that it was finite at the time, but it expanded very, very quickly. Indeed, if it exponentiated and continued in some places to exponentiate, then it could in fact be infinite right now and most cosmologists think that it is infinite. Wait, yeah, sorry. What infinite, which dimension, mass, size? Infinite in space, infinite in space. And by that I mean that if you were trying to measure- There's no boundary? Use light to measure its size, you'd never be able to measure its size because it would always be bigger than the distance light can travel. That's what you get in a universe that's accelerating in its expansion. Okay, but if a thing was a hypersphere, it's very small, not a point, how can that thing be infinite? Well, it expands exponentially. That's what the inflation theory is all about. Indeed, at your home institution, Alan Guth is one of the originators of the whole inflationary universe idea along with Andre Linde at Stanford University here in the Bay Area and others, Alexei Starobinsky and others had similar sorts of ideas. But in an exponentially expanding universe, if you actually try to make this measurement, you send light out to try to see it curve back around and hit you in the back of the head. If it's an exponentially expanding universe, the amount of space remaining to be traversed is always a bigger and bigger quantity. So, you'll never get there from here. You'll never reach the back of your head. So, observationally or operationally, it can be thought of as being infinite. That's one of the best definitions of infinity, by the way. What's that? That's one of the best sort of physical manifestations of infinity. Yeah, because you have to ask how would you actually measure it? Now, I sometimes say to my cosmology theoretical friends, well, if I were God and I were outside this whole thing, and I took a God-like slice in time, wouldn't it be finite no matter how big it is? And they object and they say, Alex, you can't be outside and take a God-like slice of time. Because there's nothing outside. Well, I'm not... Or also, what slice of time you're taking depends on your emotion. And that's true even in special relativity that slices of time get tilted in a sense if you're moving quickly. The axes, X and T actually become tilted, not perpendicular to one another. And you can look at Brian Greene's books and lectures and other things where he imagines taking a loaf of bread and slicing it in units of time as you progress forward. But then if you're zipping along relative to that loaf of bread, the slices of time actually become tilted. And so, it's not even clear what slices of time mean. But I'm an observational astronomer. I know which end of the telescope to look through. And the way I understand the infinity is, as I just told you, that operationally or observationally, there'd be no way of seeing that it's a finite universe, of measuring a finite universe. And so, in that sense, it's infinite, even if it started out as a finite little dot. Not a dot, I'm sorry, a finite little hypersphere. But it didn't really start out there, because what happened before that? Well, we don't know. So, this is where it gets into a lot of speculation. Let's go, I mean... Let's go there. Okay, sure. So, you know... Nobody can prove you wrong. The idea of what happened before T equals zero, and whether there are other universes out there, I like to say that these are sort of on the boundaries of science. They're not just ideas that we wake up at three in the morning to go to the bathroom and say, oh, well, let's think about what happened before the Big Bang, or let there be a multiplicity of universes. In other words, we have real testable physics that we can use to draw certain conclusions that are plausibility arguments, based on what we know. Now, admittedly, they're not really direct tests of these hypotheses. That's why I call them hypotheses. They're not really elevated to a theory, because a theory in science is really something that has a lot of experimental or observational support behind it. So, they're hypotheses, but they're not unreasonable hypotheses based on what we know about general relativity and quantum physics, okay? And they may have indirect tests in that if you adopt this hypothesis, then there might be a bunch of things you expect of the universe, and lo and behold, that's what we measure. But we're not actually measuring anything at T less than zero, or we're not actually measuring the presence of another universe in this multiverse. And yet, there are these indirect ideas that stem forth. So, it's hard to prove uniqueness, and it's hard to completely convince oneself that a certain hypothesis must be true. But, you know, the more and more tests you have that it satisfies, let's say there are 50 predictions it makes, and 49 of them are things that you can measure, and then the 50th one is the one where you want to measure the actual existence of that other universe, or what happened before T equals zero. And you can't do that. But you've satisfied 49 of the other testable predictions. And so, that's science, right? Now, a conventional condensed matter physicist or someone who deals with real data in the laboratory might say, oh, you cosmologists, you know, that's not really science, because it's not directly testable. But I would say it's sort of testable. But it's not completely testable, and so it's at the boundary. But it's not like we're coming up with these crazy ideas, among them quantum fluctuations out of nothing, and then inflating into a universe with, you might say, well, you created a giant amount of energy, but in fact, this quantum fluctuation out of nothing, you know, in a quantum way violates the conservation of energy. But you know, who cares? That was a classical law anyway. And then an inflating universe maintains whatever energy it had, be it zero or some infinitesimal amount. In a sense, the stuff of the universe has a positive energy, but there's a negative gravitational energy associated with it. It's like I drop an apple. I got kinetic energy, energy of motion out of that, but I did work on it to bring it to that height. So by going down and gaining energy of motion, positive 1, 2, 3, 4, 5 units of kinetic energy, it's also gaining or losing, depending on how you want to think of it, negative 1, 2, 3, 4, 5 units of potential energy. So the total energy remains the same. An inflating universe can do that, or other physicists say that energy isn't conserved in general relativity. That's another way out of creating a universe out of nothing, you know. But the point is that this is all based on reasonably well-tested physics. And although these extrapolations seem kind of outrageous at first, they're not completely outrageous. They're within the realm of what we call science already. And maybe some young whippersnapper will be able to figure out a way to directly test what happened before t equals zero or to test for the presence of these other universes. But right now, we don't have a way of doing that. So speaking of young whippersnappers, Roger Penrose. Yeah. So he kind of has a, you know, idea that there may be some information that travels from whatever the heck happened before the Big Bang. Yeah, maybe. I kind of doubt it. So do you think it's possible to detect something, like actually experimentally be able to detect some, I don't know what it is, radiation, some sort of... Yeah, in the cosmic microwave background radiation, there may be ways of doing that. But is it philosophically or practically possible to detect signs that this was before the Big Bang? Or is it what you said, which is like, everything we observe will, as we currently understand, will have to be a creation of this particular observable universe? Yeah, I mean, you know, if you... It's very difficult to answer right now because we don't have a single verified, fully self-consistent, experimentally tested quantum theory of gravity. Right. And of course, the beginning of the universe is a large amount of stuff in a very small space. So you need both quantum mechanics and general relativity. Same thing if our universe re-collapses and then bounces back to another Big Bang. There's also ideas there that some of the information leaks through or survives. I don't know that we can answer that question right now because we don't have a quantum theory of gravity that most physicists believe in. And belief is perhaps the wrong word that most physicists trust because the experimental evidence favors it. Yeah. Right? There are various forms of string theory. There's quantum loop gravity. There are various ideas, but which, if any, will be the one that survives the test of time and, more importantly, within that, the test of experiment and observation. Yeah. So my own feeling is probably these things don't survive. I don't think we've seen any evidence in the cosmic microwave background radiation of information leaking through. Similarly, the one way or one of the few ways in which we might test for the presence of other universes is if they were to collide with ours. That would leave a pattern, a temperature signature in the cosmic microwave background radiation. Some astrophysicists claim to have found it, but in my opinion, it's not statistically significant to the level that would be necessary to have such an amazing claim. It's just a 5% chance that the microwave background had that distribution just by chance. 5% isn't very long odds if you're claiming that instead that you're finding evidence from another universe. I mean, it's like if the Large Hadron Collider people had claimed after gathering enough data to show the Higgs particle when there was a 5% chance it could be just a statistical fluctuation in their data. No, they required five sigma, five standard deviations, which is roughly one chance in two million that this is a statistical fluctuation of no physical greater significance. Extraordinary claims require extraordinary evidence. There you go. It all boils down to that. And the greater your claim, the greater is the evidence that is needed and the more evidence you need from independent ways of measuring or of coming to that deduction. A good example was the accelerating universe when we found evidence for it in 1998 with supernovae with exploding stars. It was great that there were two teams that lent some credibility to the discovery, but it was not until other astrophysicists used not only that technique, but more importantly, other independent techniques that had their own potential sources of systematic error or whatever, but they all came to the same conclusion. And that started giving a much more complete picture of what was going on and a picture in which most astrophysicists quickly gained confidence. That's why that idea caught on so quickly is that there were other physicists and astronomers doing observations completely independent of supernovae that seemed to indicate the same thing. Yeah. That period of your life that work with an incredible team of people that won the Nobel Prize is just fascinating work. Oh gosh, you know, never in my wildest dreams as a kid did I think that I would be involved, much less so heavily involved, in a discovery that's so revolutionary. I mean, you know, as a kid, as a scientist, if you're realistic, once you learn a little bit more about how science is done and you're not going to win a Nobel Prize and be the next Newton or Einstein or whatever, you just hope that you'll contribute something to humankind's understanding of how nature works, and you'll be satisfied with that. But here I was in the right place at the right time, lot of luck, lot of hard work, and there it was. We discovered something that was really amazing, and that was the greatest thrill, right? I couldn't have asked for anything more than being involved in that discovery. So the couple of teams, the Supernova Cosmology Project and the High-Z Supernova Search Team, so what was the Nobel Prize given for? It was given for the discovery of the accelerating expansion of the universe. Not for the elucidation of what dark energy is or what causes that expansion, that acceleration, be it universes on the outside or whatever. It was only for the observational fact. So first of all, what is the accelerating universe? So the accelerating universe is simply that if we look at the galaxies moving away from us right now, we would expect them to be moving away more slowly than they were billions of years ago. And that's because galaxies have visible matter, which is gravitationally attractive, and dark matter of an unknown sort that holds galaxies together and holds clusters of galaxies together. And of course, they then pull on one another and they would tend to retard the expansion of the universe. Just as when I toss an apple up, even ignoring air resistance, the mutual gravitational attraction between Earth and the apple slows the apple down. And if that attraction is great enough, then the apple will someday stop and even come back. The big crunch, you could call it, or the Gnab-Gib, which is Big Bang backwards, right? That's what could have happened to the universe. But even if the universe's original expansion energy was so great that it avoids the big crunch, that's like an apple thrown at Earth's escape speed. It's like the rockets that go to Mars someday, right? You know, with people. Even then, you'd expect the universe to be slowing down with time. But we looked back through the history of the universe by looking at progressively more distant galaxies. And by seeing that the evolution of this expansion rate is that in the first nine billion years, yeah, it was slowing down. But in the last five billion years, it's been speeding up. So, who asked for that, right? You know? I think it's interesting to talk about a little bit of the human story of the Nobel Prize. Sure. Which is, I mean, it's a really… It's fascinating. First of all, the prize itself. It's kind of fascinating on the psychological level that prizes… I know we kind of think that prizes don't matter, but somehow they kind of focus the mind about some of the most special things we've accomplished. They do. It's the recognition, the funding, you know? Yeah. And also inspiration for… I mean, like I said, when I was a little kid, thinking about the Nobel Prize, like I didn't, you know… It inspires millions of young scientists. At the same time, there's a sadness to it a little bit, that especially in the field, like depending on the field, but experimental fields that involve teams of, I don't know, sometimes hundreds of brilliant people. The Nobel Prize is only given to just a handful. That's right. Is it maxed at three? Yeah. And it's not even written in Alfred Nobel's will, it turns out. One of our teammates looked into it in a museum in Stockholm when we went there for Nobel Week in 2011. The leaders who got the prize formally knew that without the rest of us working hard in the trenches, the result would not have been discovered. So, they invited us to participate in Nobel Week. And so, one of the team members looked in the will, and it's not there. It's just tradition. That's interesting. But it's archaic, you know? That's the way science used to be done. Yeah. And it's not the way a lot of science is done now. And you look at gravitational wave discovery, which was recognized with the Nobel Prize in 2017. Ray Weiss at MIT got it, and Kip Thorne, and Barry Barish at Caltech. And Ron Drever, one of the masterminds, had passed away earlier in the year. So, again, one of the rules of the Nobel is that it's not given posthumously, or at least the one exception might be if they've made their decision and they're busy making their press releases right before October, the first week in October or whatever, and then the person passes away. I think they don't change their minds then. But yeah, it doesn't square with today's reality that a lot of science is done by big teams, in that case, a team of a thousand people. In our case, it was two teams consisting of about 50 people. And we used techniques that were arguably developed in part by people who, astrophysicists who weren't even on those two papers. I mean, some of them were, but other papers were written by other people, you know. And so, it's like we're standing on the shoulders of giants. And none of those people was officially recognized. And to me, it was okay. You know, again, it was the thrill of doing the work, and ultimately the work, the discovery was recognized with the prize. And, you know, we got to participate in Nobel week and, you know, it's okay with me. I've known other physicists whose lives were ruined because they did not get the Nobel prize and they felt strongly that they should have. Ralph Alpher of the Alpher, Beta, Gamow, you know, paper predicting the microwave background radiation, he should have gotten it. His advisor Gamow was dead by that point. But, you know, Penzias and Wilson got it for the discovery and Alpher, apparently from colleagues who knew him well, I've talked to them, his life was ruined by this. He just, it just gnawed at his innards so much. It's very possible that in a small handful of people, even three, that you would be one of the Nobel, one of the winners of the Nobel prize. That doesn't weigh heavy on you? Well, you know, there were the two team leaders, Saul Perlmutter and Brian Schmidt. And usually it's the team leaders that are recognized. And then Adam Rees was my postdoc. First author, I guess. Yeah, first author. I was second author of that paper. Yeah. So I was his direct mentor at the time, although he was, you know, one of these people who just, you know, runs with things. He was an MIT undergraduate by the way, Harvard graduate student, and then a postdoc as a so called Miller fellow for basic research in science at Berkeley, something that I was back in 84 to 86. But you're, you know, you're largely a free agent, but he worked quite closely with me and he came to Berkeley to work with me and on Schmidt's team, he was charged with analyzing the data. And he measured the brightnesses of these distant supernovae showing that they're fainter and thus more distant than anticipated. And that led to this conclusion that the universe had to have accelerated in order to push them out to such great distances. And I was shocked when he showed me the data, the results of his calculations and measurements. But it's very, you know, so he deserved it. And on Saul's team, Gerson Goldhaber deserved it, but he died, I think, a year earlier in 2010, but that would have been four. And so, and me, well, I was on both teams, but you know, was I number four, five, six, seven? I don't know. Well, it's also very, so if I were to, it's possible that you're, I mean, I could make a very good case for you're in the three. And does that cycle- You're kind, you know, so- But is that psychologically, I mean, listen, it weighs on me a little bit because I- Yeah. I don't know what to do with that. Perhaps it should motivate the rethinking, like Time Magazine started doing like, you know, Person of the Year. And like, they would start doing like concepts and almost like the Black Hole gets the Nobel Prize or the Xellier Universe gets the Nobel Prize and here's the list of people. So like, or like the Oscar that you could say- Yeah. Because it- It's a team effort now. It's a team. You know, and it should be redone. And the Breakthrough Prize in Fundamental Physics, which was started by Yuri Milner and Zuckerberg is involved in others as well, you know- They recognize the larger team. Yeah, they recognize teams. And so, in fact, both teams in the Accelerating Universe were recognized with the Breakthrough Prize in 2015. Nevertheless, the same three people, Reese, Perlmutter, and Schmidt, got the red carpet rolled out for them and were at the big ceremony and shared half of the prize money. And the rest of us, roughly 50, shared the other half and didn't get to go to the ceremony. So, but I feel for them. I mean, for the gravitational waves, it was a thousand people. What are they going to do? Invite everyone? Yeah. For the Higgs particle, it was 68,000 physicists and engineers. In fact, because of the whole issue of who gets it, experimentally, that discovery still has not been recognized, right? The theoretical work by Peter Higgs and Englert got recognized, but there was a troika of other people who perhaps wrote the most complete paper and they were left out. And another guy died, you know? Yeah, it's all of this heartbreak. And some people argue that the Nobel Prize has been diluted too, because if you look at Roger Penrose, you can make an argument that he should get the prize by himself. Like, so separate those, like… Could have and should have. Perhaps he should have perhaps gotten it with Hawking before Hawking's death, right? The problem was Hawking radiation had not been detected, but you could argue that Hawking made enough other fundamental contributions to the theoretical study of black holes and the observed data were already good enough at the time of before Hawking's death, okay? I mean, the latest results by Reinhard Genzel's group is that they see the time dilation effect of a star that's passing very close to the black hole in the middle of our galaxy. That's cool, and it adds additional evidence, but hardly anyone doubted the existence of the supermassive black hole. And Andrea Ghez's group, I believe, hadn't yet shown that relativistic effect, and yet she got part of the prize as well. So clearly, it was given for the original evidence that was really good, and that evidence is at least a decade old, you know? So one could make the case for Hawking. One could make the case that in 2016, when Mayor and K. Lowe's won the Nobel Prize for the discovery of the first exoplanet, 51b Pegasi, well, there was a fellow at Penn State, Alex Wolshan, who in 1992, three years preceding 1995, found a planet orbiting a pulsar, a very weird kind of star, a neutron star, and that wouldn't have been a normal planet, sure. And so the Nobel Committee, you know, they gave it for the discovery of planets around normal sun-like stars, but hell, you know, Wolshan found a planet, so they could have given it to him as the third person instead of to Jim Peebles for the development of what's called physical cosmology. He's at Princeton. He deserved it, but they could have given the Nobel for the development of physical cosmology to Peebles, and I would claim some other people were pretty important in that development as well, you know, and they could have given it some other year. So there's a lot of controversy. I try not to dwell on it, was I number three? Probably not. You know, Adam Ries did the work. I helped bounce ideas off of him, but we wouldn't have had the result without him. And I was on both teams for reasons, I mean, you know, the style of the first team, the Supernova Cosmology Project, didn't match mine. They came largely from experimental high-energy particle physics, where there's these hierarchical teams and stuff, and it's hard for the little guy to have a say, at least that's what I kind of thought. Whereas the team of astronomers led by Brian Schmidt was, first of all, a bunch of my friends, and they grew up as astronomers making contributions on little teams, and we decided to band together, but all of us had our voices heard. So it was sort of a culture, a style that I preferred, really. But let me tell you a story. At the Nobel banquet, okay, I'm sitting there between two physicists who are members of the committee of the Swedish National Academy of Sciences, you know, and I strategically kept, you know, offering them wine and stuff during this long, drawn-out Nobel ceremony, right? And I got them to be pretty talkative, and then in a polite, diplomatic way, I started asking them pointed questions. And basically, they admitted that if there are four or more people equally deserving, they wait for one of them to die, or they just don't give the prize at all when it's unclear who the three are, at least unclear to them. But unclear to them, it's, they're not even right part of the time. I mean, Jocelyn Bell discovered pulsars with a radio antenna, a set of radio antennas that her advisor Anthony Hewish conceived and built, so he deserves some credit. But he didn't discover the pulsar, she did. And his initial reaction to the data that she showed him was a condescending rubbish, my dear. Yeah, I'm not kidding. Now, I know Jocelyn Bell, and she did not let this destroy her life. She won every other prize under the sun, okay? Vera Rubin, arguably one of the discoverers of dark matter, although there, if you look at the history, there were a number of people, that was the issue, I think there were a number of people, four or more, who had similar data and similar ideas at about the same time. Rubin won every prize under the sun, the new big, large-scale survey telescope being built in Chile is being renamed the Vera Rubin telescope, because she passed away in December of 2015, I think. You know, it'll conduct this survey, large-scale survey with the Rubin telescope. So she's been recognized, but never with the Nobel Prize. And I would say that, to her credit, she did not let that consume her life either. And perhaps it was a bit easier, because there had been no Nobel given for the discovery of dark matter, whereas in the case of pulsars and Jocelyn Bell, there was a prize given for the discovery of the freaking pulsars, and she didn't get it. I mean, what a travesty of justice. So I also think, as a fan of fiction, as a fan of stories, that the travesty and the tragedy and the unfairness and the tension of it is what makes the prize and similar prizes beautiful. The decisions of other humans that result in dreams being broken, and you know, like, that's why we love the Olympics. There's so many, you know, people, athletes give their whole life for this particular moment. And then there's referee decisions and like little slips of here and there, like the little misfortunes that destroy entire dreams. And that's, it's weird to say, but it feels like that makes the entirety of it even more special. If it was perfect, it wouldn't be interesting. Well, humans like competition and they like heroes. And unfortunately, it gives the impression to youngsters today that science is still done by white men with gray beards wearing white lab coats. And I'm very pleased to see that this year, you know, Andrea Ghez, the fourth woman in the history of the physics prize to have received it. And then two women, one at Berkeley, one elsewhere, won the Nobel Prize in chemistry without any male co-recipient. And so that's sending a message, I think, to girls that they can do science and they have role models. I think the Breakthrough Prize and other such prizes show that teams get recognized as well. And if you pay attention to the newspapers, you know, most of the good authors like, you know, Dennis Overby of the New York Times and others said that these were teams of people and they emphasize that and, you know, they all played a role. And, you know, maybe if some grad student hadn't soldered some circuit, maybe the whole thing wouldn't have worked, you know. But still, you know, Ray Weiss, Kip Thorne was the theoretical, you know, impetus for the whole search for gravitational waves. Barry Barish brought the MIT and Caltech teams together to get them to cooperate at a time when the project was nearly dead from what I understand and contributed greatly to the experimental setup as well. He's a great experimental physicist, but he was really good at bringing these two teams together instead of having them duke it out in blows and leaving both of them bleeding and dying, you know, and the National Science Foundation was going to cut the funding from what I understand, you know. So there's human drama involved in this whole thing. And the Olympics, yeah, you know, a runner, a swimmer, a runner, you know, they slip just at the moment that they were taking off from the first thing and that costs them some fraction of a second and that's it. They didn't win, you know. And in that case, I mean, the coaches, the families, which I met a lot of Olympic athletes and the coaches and the families of the athletes are really the winners of the medals. But they don't get the medal. And it's, you know, credit assignment is a fascinating thing. I mean, that's the full human story. And outside of prizes, it's fascinating. I mean, just to be in the middle of it for artificial intelligence, there's a field of deep learning that's really exciting. And people have been, there's yet another award, the Turing Award given for deep learning to three folks who are very much responsible for the field, but so are a lot of others. And there's a few, there's a fellow by the name of Schmidt Huber, who sort of symbolizes the forgotten folks in the deep learning community. But, you know, that's the unfortunate, sad thing, where you remember, we remember Isaac Newton, we remember these special figures and the ones that flew close to them, we forget. Well, that's right. And, you know, often the breakthroughs are made based on the body of knowledge that had been assimilated prior to that. But, you know, again, people like to worship heroes. You mentioned the Oscars earlier. And, you know, you look at the direct, I mean, well, I mean, okay, directors and stuff sometimes get awards and stuff. But, you know, you look at even something like, I don't know, songwriters, musicians, Elton John or something, right? Bernie Taupin, right? Wrote many of the words, or he's not as well known, or the Beatles or something like that. I was heartbroken to learn that Elvis didn't write most of his songs. Yeah, Elvis, that's right. There you go. But he was the king, right? And he had such a personality, and it was such a performer, right? But it's the unsung heroes in many cases. Yeah. So, maybe taking a step back, we talked about the Nobel Prize for the Accelerating Universe, but your work and the ideas around supernova were important in detecting this accelerating universe. Can we go to the very basics of what is this beautiful, mysterious object of a supernova? Right. So, a supernova is an exploding star. Most stars die a relatively quiet death, our own sun will, despite the fact that it'll become a red giant and incinerate Earth. It'll do that reasonably slowly. But there's a small minority of stars that end their lives in a titanic explosion. And that's not only exciting to watch from afar, but it's critical to our existence because it is in these explosions that the heavy elements synthesize through nuclear reactions during the normal course of the star's evolution and during the explosion itself get ejected into the cosmos, making them available as raw material for new stars, planets, and ultimately life. And that's just a great story, the best in some ways. So, we like to study these things and our origins, but it turns out these are incredibly useful beacons as well. Because if you know how powerful an exploding star really is by measuring the apparent brightness at its peak in galaxies whose distances we already know through having made other measurements, and you can thus calibrate how powerful the thing really is, and then you find ones that are much more distant, then you can use their observed brightness compared with their true intrinsic power or luminosity to judge their distance and hence the distance of the galaxy in which they're located. It's like looking at, let me just give this one analogy. You judge the distance of an oncoming car at night by looking at how bright its headlights appear to be, and you've calibrated how bright the headlights are of a car that's two or three meters away of known distance. And you go, whoa, that's a faint headlight, and so that's pretty far away. You also use the apparent angular separation between the two headlights as a consistency check in your brain. But that's what your brain is doing. So, we can do that for cars, we can do that for stars. Nice, I like that. But with cars, the headlights are all, there's some variation, but they're somewhat similar, so you can make those kinds of conclusions. What, how much variation is there between supernova that you can, can you detect them? Right, so first of all, there are several different ways that stars can explode, and it depends on their mass and whether they're in a binary system and things like that. And the ones that we used for these cosmological purposes, studying the expansion of the history of the universe, are the so-called type Roman numeral one, lowercase a, type 1a supernovae. They come from a weird type of a star called a white dwarf. Our own sun will turn into a white dwarf in about 7 billion years. It'll have about half its present mass compressed into a volume, just the size of Earth. So, that's an inordinate density, okay? It's incredibly dense. And the matter is what's called by quantum physicists, degenerate matter. Not because it's morally reprehensible or anything like that, but this is just the name that- No judgments here. Yeah, quantum physicists give to electrons that are squeezed into a very tight space. The electrons take on a motion due to Heisenberg's uncertainty principle, and also due to the Pauli exclusion principle that electrons don't like to be in the same place. They like to avoid each other. So, those two things mean that a lot of electrons are moving very rapidly, which gives the star an extra pressure far above the thermal pressure associated with just the random motions of particles inside the star. So, it's a weird type of star, but normally it wouldn't explode and our sun won't explode, except that if such a white dwarf is in a pair with another more or less normal star, it can steal material from that normal star until it gets to an unstable limit, roughly one and a half times the mass of our sun, 1.4 or so. This is known as the Chandrasekhar limit, after Subrahmanyan Chandrasekhar, an Indian astrophysicist who figured this out when he was about 20 years old on a voyage from India to England where he was to be educated. And then he did this, and then 50 years later, he won the Nobel Prize in physics in 1984, largely for this work, okay, that he did as a youngster who was on his way to be educated, you know. Oh, and his advisor, the great Arthur Eddington in England, who had done a lot of great things and was a great astrophysicist, nevertheless, he too was human and had his faults. He ridiculed Chandra's scientific work at a conference in England. And, you know, most of us, if we had been Chandra, would have just given up astrophysics at that time, you know, when the great Arthur Eddington ridicules our work. That's another inspirational story for the youngster, you know, just keep going, you know. But anyway, John- Ignore your advisors. Yeah, no matter what your advisor says, right. Or don't always pay attention to your advisor, right? Don't lose hope if you really think you're onto something. That doesn't mean never listen to your advisor. They may have sage advice as well. But anyway, you know, when a white dwarf grows to a certain mass, it becomes unstable. And one of the ways it can end its life is to go through a thermonuclear runaway. So basically, the carbon nuclei inside the white dwarf starts start fusing together to form heavier nuclei. And the energy that those fusion reactions emit, emits, doesn't go into, you know, being dissipated out of the star or, you know, whatever, or expanding it the way, you know, if you take a blowtorch to the middle of the sun, you heat up its gases, the gases would expand and cool. But this degenerate star can't expand and cool. And so, the energy pumped in through these fusion reactions goes into making the nuclei move faster, and that gets more of them sufficiently close together that they can undergo nuclear fusion, thereby releasing more energy that goes into speeding up more nuclei. And thus, you have a runaway, a bomb, an uncontrolled fusion reactor, right? Instead of the controlled fusion, which is what our sun does, okay? Our sun is a marvelous controlled fusion reactor. This is what we need here on Earth, fusion energy to solve our energy crisis, right? But the sun holds the stuff in, you know, through gravity, and you need a big mass to do that. So, this uncontrolled fusion reaction blows up a star that's pretty much the same in all cases. And you measure it to be almost the same in all cases, but the devil's in the details. And in fact, we observe them to not be all the same. And theoretically, they might not be all the same, because the rate of the fusion reactions might depend on the amount of trace heavier elements in the white dwarf, and that could depend on how old it is, whether it was born billions of years ago when there weren't many heavier elements, or whether it's a relatively young white dwarf, and all kinds of other things. And part of my work was to show that indeed, not all the Type Ia's are the same. You have to be careful when you use them. You have to calibrate them. They're not standard candles, the way it just if all headlights or all candles were the same lumens or whatever, you'd say they're standard. And then it would be relevant. Standard candles is an awesome term. Okay. Standard candles is what astronomers like to say. Of the night sky. I don't like that term, because there aren't any standard candles, but there are standardizable candles. And by looking at these Type Ia- Oh, calibrate them, that's what you mean. Yeah, calibratable, standardizable, calibratable. You look at enough of them in nearby galaxies, whose distances you know independently. And what you can tell is that, this is something that a colleague of mine, Mark Phillips, did, who was on Schmidt's team, and arguably was one of the people who deserved the Nobel Prize. But he showed that the intrinsically more powerful Type Ia's decline in brightness, and it turns out rise in brightness as well, more slowly than the less luminous Ia's. And so, if you calibrate this by measuring a whole bunch of nearby ones, and then you look at a distant one, instead of saying, well, it's a 100 watt Type Ia supernova, they're much more powerful than that, by the way, plus or minus 50, you can say, no, it's 112 plus or minus 15, or it's 84 plus or minus 17. It tells you where it is in the power scale, and it greatly decreases the uncertainties, and that's what makes these things cosmologically useful. I showed that if you spread the light out into a spectrum, you can tell spectroscopically that these things are different as well. And in 1991, I happened to study two of the extreme peculiar ones, the low luminosity ones and the high luminosity ones, 1991 BG and 1991 T. This showed that not all the Ia's are the same. And indeed, at the time of 1991, I was a little bit skeptical that we could use Type Ia's because of this diversity that I was observing. But in 1993, Mark Phillips wrote a paper that showed this correlation between the light curve, the brightness versus time, and the peak luminosity. And once you push that, then they become calibratable, and that was a game changer. LR How many Type Ia's are out there to use for data? AC Now there are thousands of them. But at the time, the high Z team had 16, and the Supernova Cosmology Project had 40. But the 16 were better measured than the 40, and so our statistical uncertainties were comparable if you look at the two papers that were published. LR How does that make you feel that there's these gigantic explosions just sprinkled out there? AC Well, I certainly don't want one to be very nearby, and it would have to be within something like 10 light years to be an existential threat. LR So they can happen in our galaxy? AC Oh, yeah, yeah. LR So they would be okay? AC In most cases, we'd be okay, because our galaxy is 100,000 light years across, and you'd need one of these things to be within about 10 light years to be an existential threat. LR And it gives birth to a bunch of other stars, I guess? AC Yeah, it gives birth to expanding gases that are chemically enriched, and those expanding gases mix with other chemically enriched expanding gases or primordial clouds of hydrogen and helium. I mean, this is, in a sense, the greatest story ever told, right? I teach this introductory astronomy course at Berkeley, and I tell them there's only five or six things that I want them to really understand and remember, and I'm going to come to their deathbed, and I'm going to ask them about this, and if they get it wrong, I will retroactively fail them, and their whole career will have been shot. That, and if they don't go and observe a total solar eclipse, and yet they had the opportunity to do so, I will retroactively fail them. But one of them is, where did we come from? Where did the elements in our DNA come from? The carbon in our cells, the oxygen that we breathe, the calcium in our bones, the iron in our red blood cells, those elements, the phosphorus in our DNA, they all came from stars, from nuclear reactions in stars, and they were ejected into the cosmos, and in some cases, like iron, made during the explosions. And those gases drifted out, mixed with other clouds, made a new star or a star cluster, some of whose members then evolved and exploded, thus enriching the gases in the galaxy progressively more with time, until finally, four and a half billion years ago, from one of these chemically enriched clouds, our solar system formed with a rocky Earth-like planet, and somewhere, somehow, these self-replicating evolving molecules, bacteria, formed and evolved through paramecia and amoebas and slugs and apes and us. And here we are, sentient beings that can ask these questions about our very origins, and with our intellect and with the machines we make, come to a reasonable understanding of our origins. What a beautiful story. I mean, if that does not put you at least in awe, if not in love with science and its power and its power of deduction, I don't know what will, right? It's one of the greatest stories, if not the greatest story. Obviously, that's personality dependent and all that. It's a subjective opinion, but it's perhaps the greatest story ever told. I mean, you could link it to the Big Bang and go even farther, right, to make an even more complete story, but as a subset, that's even in some ways a greater story than even the existence of the universe in some ways, because you could end up, you could just imagine some really boring universe that never leads to sentient creatures such as ourselves. And is a supernova usually the introduction to that story? Yeah. Are they usually the thing that launches the, is there other engines of creation? Well, the supernova is the one, I mean, I touch upon the subject earlier in my course, in fact, right about now in my lectures, because I talk about how our sun right now is fusing hydrogen to form helium nuclei, and later it'll form carbon and oxygen nuclei, but that's where the process will stop for our sun. It's not massive enough. Some stars that are more massive can go somewhat beyond that. So that's the beginning of, right, this idea of the birth of the heavy elements, since they couldn't have been born at the time of the Big Bang, conditions of temperature and pressure weren't sufficient to make any significant quantities of the heavier elements. And so that's the beginning, but then you need some of these stars to explode, right? Because if those heavy elements remained forever trapped in the cores of stars, then they would not be available for the production of new stars, planets, and ultimately life. So indeed, the supernova, my main area of interest, plays a leading role in this whole story. I saw that you got a chance to call Richard Feynman a mentor of yours when you were at Caltech. Yeah. Do you have any fond memories of Feynman, any lessons that stick with you? Oh, yeah. He was quite a character, and one of the deepest thinkers of all time probably. And at least in my life, the physicist who had the single most intuitive understanding of how nature works of anyone I've met. I learned a number of things from him. He was not my thesis advisor. I worked with Wallace Sargent at Caltech on what are called active galaxies, big black holes in the centers of galaxies that are accreting or swallowing material, a little bit like the stuff of this year's Nobel Prize in Physics 2020. But Feynman I had for two courses. One was general theory of relativity at the graduate level, and one was applications of quantum physics to all kinds of interesting things. And he had this very intuitive way of looking at things that he tried to bring to his students. And he felt that if you can't explain something in a reasonably simple way to a non-scientist, or at least someone who is versed a little bit with science but is not a professional scientist, then you probably don't understand it very well yourself very thoroughly. So, that in me made a desire to be able to explain science to the general public. And I've often found that in explaining things, yeah, there's a certain part that I didn't really understand myself. That's one reason I like to teach the introductory courses to the lay public, is that I sometimes find that my explanations are lacking in my own mind. So, he did that for me. Is there a, if I could just pause for a second. You said he had one of the most intuitive understandings of nature. If you could break apart what intuitive means, like, is it on a philosophical level? No, sort of physical. How do you draw a mental picture or a picture on paper of what's going on? And he's perhaps most famous in this regard for his Feynman diagrams, which, in what's called quantum electrodynamics, a quantum field theory of electricity and magnetism, and what you have are actually, you know, an exchange of photons between charged particles, and they might even be virtual photons if the particles are at rest relative to one another. And there are ways of doing calculations that are brute force, that take pages on pages and pages of calculations. And Julian Schwinger developed some of the mathematics for that and won the Nobel Prize for it. But Feynman had these diagrams that he made, and he had a set of rules of what to do at the vertex. You'd have two particles coming together, and then a particle going out, and then two particles coming out again. And he'd have these rules associated when there were vertices, and when there were particles splitting off from one another and all that. And it looked a little bit like a bunch of a hodgepodge at first, but to those who learned the rules and understood them, he, you know, they saw that you could do these complex calculations in a much simpler way. And indeed, in some ways, Freeman Dyson had an even better knack for explaining really what quantum electrodynamics actually was. But I didn't know Freeman Dyson, I knew Feynman. Maybe he did have a more intuitive view of the world than Feynman did. But of the people I knew, Feynman was the most intuitive, most sort of, is there a picture, is there a simple way you can understand this? And in the path that a particle follows, even, you know, you can figure out the, you can get the classical path, at least, you know, for a baseball or something like that by using quantum physics if you want. But, you know, in a sense, the baseball sniffs out all possible paths. It goes out to the Andromeda galaxy and then goes to the batter. But the probability of doing that is very, very small because tiny little paths next door to any given path cancel out that path. And the ones that all add together, they're the ones that are more likely to be followed. And this actually ties in with Fermat's principle of least action. And there are ideas in optics that go into this as well. And it just sort of beautifully brings everything together. But the particle sniffs out all possible paths. What a crazy idea. But if you do the mathematics associated with that, it ends up being actually useful, a useful way of looking at the world. So you're also, I mean, you're widely acknowledged as, I mean, outside of your science work as being one of the greatest educators in the world. And Feynman is famous for being that. Is there something about being a teacher that you've... Well, it's very, very rewarding when you have students who are really into it. And going back to Feynman at Caltech, I was taking these graduate courses and there were two of us, myself and Jeff Richman, who's now a professor of physics at University of California, Santa Barbara, who asked lots of questions. And a lot of the Caltech students are nervous about asking questions. They want to save face. They seem to think that if they ask a question, their peers might think it's a stupid question. Well, I didn't really care what people thought and Jeff Richman didn't either. And we'd ask all these questions. And in fact, in many cases, they were quite good questions. And Feynman said, well, the rest of you should be having questions like this. And I remember one time in particular when he said to the rest of the class, why is it always these two? Aren't the rest of you curious about what I'm saying? Do you really understand it all that well? If so, why aren't you asking the next most logical question? No, you guys are too scared to ask these questions that these two are asking. So, he actually invited us to lunch a couple of times where just the three of us sat and had lunch with one of the greatest thinkers of 20th century physics. And so, yeah, he rubbed off on me. And- Lex Doppelganger So, you encourage questions as well? David Taylor I invert courage questions. Yeah, definitely. I mean, I encourage questions. I like it when students ask questions. I tell them that they shouldn't feel shy about asking a question. Probably half the students in the class would have that same question if they even understood the material enough to ask that question. Yeah. Lex Doppelganger Curiosity is the first step of- David Taylor Absolutely. Lex Doppelganger Of seeing the beauty of something. And the question is the ultimate form of curiosity. Let me ask, what is the meaning of life? David Taylor The meaning of life, you know- Lex Doppelganger From a cosmologist's perspective or from a human perspective? David Taylor Or from my personal, you know. Life is what you make of it, really, right? It's- each of us has to have our own meaning. And it doesn't have to be- well, I think that in many cases, meaning is to some degree associated with goals. You set some goals or expectations for yourself, things you want to accomplish, things you want to do, things you want to experience. And to the degree that you experience those and do those things, it can give you meaning. You don't have to change the world the way Newton or Michelangelo or Da Vinci did. I mean, people often say, you change the world. But look, come on, there's seven and a half, close to eight billion of us now. Most of us are not going to change the world. And does that mean that most of us are leading meaningful lives? No. It just has to be something that gives you meaning, that gives you satisfaction, that gives you a good feeling about what you did. And often, based on human nature, which can be very good and also very bad, but often it's the things that help others, that give us meaning and a feeling of satisfaction. You taught someone to read. You cared for someone who was terminally ill. You brought up a nice family. You brought up your kids. You did a good job. You put your heart and soul into it. You read a lot of books, if that's what you wanted to do. Had a lot of perspectives on life. You traveled the world, if that's what you wanted to do. But if some of these things are not within reach, you're in a socioeconomic position where you can't travel the world or whatever, you find other forms of meaning. It doesn't have to be some profound, profound, I'm going to change the world, I'm going to be the one who everyone remembers type thing. Right? In the context of the greatest story ever told, the fact that we came from stars and now we're two apes asking about the meaning of life. Yeah. How does that fit together? Well, this is... Does that make any sense? It does. It does. And this is sort of what I was referring to that it's a beautiful universe that allows us to come into creation. Right? It's a way that the universe found of knowing, of understanding itself. Because I don't think that inanimate rocks and stars and black holes and things have any real capability of abstract thoughts and of learning about the rest of the universe or even their origins. I mean, they're just a pile of atoms that has no conscience, has no ability to think, has no ability to explore. And we do. And I'm not saying we're the epitome of all life forever, but at least for life on earth so far, the evidence suggests that we are the epitome in terms of the richness of our thoughts, the degree to which we can explore the universe, do experiments, build machines, understand our origins. And I just hope that we use science for good, not evil, and that we don't end up destroying ourselves. I mean, the whales and dolphins are plenty intelligent. They don't ask abstract questions. They don't read books. But on the other hand, they're not in any danger of destroying themselves and everything else as well. And so maybe that's a better form of intelligence, but at least in terms of our ability to explore and make use of our minds. I mean, to me, it's this. It's this that gives me the potential for meaning, right? The fact that I can understand and explore. It's kind of fascinating to think that the universe created us, and eventually we've built telescopes to look back at it, to look back at its origins, and to wonder how the heck the thing works. It's magnificent. It needn't have been that way, right? And this is one of the multiverse sort of things. You can alter the laws of physics or even the constants of nature, seemingly inconsequential things like the mass ratio of the proton and the neutron. Wake me up when it's over, right? What could be more boring? But it turns out you play with things a little bit like the ratio of the mass of the neutron to the proton, and you generally get boring universes. Only hydrogen or only helium or only iron. You don't even get the rich periodic table, let alone bacteria, paramecia, slugs, and humans, okay? I'm not even anthropocentralizing this to the degree that I could. Even a rich periodic table wouldn't be possible if certain constants weren't this way, but they are. And that, to me, leads to the idea of a multiverse that the dice were thrown many, many times, and there's this cosmic archipelago where most of the universes are boring, and some might be more interesting, but we are in the rare breed that's really quite darn interesting. And if there were only one, and maybe there is only one, well, then that's truly amazing. LRW We're lucky. AC But I actually think there are lots and lots, just like there are lots of planets. Earth isn't special for any particular reason. There are lots of planets in our solar system and especially around other stars, and occasionally there are going to be ones that are conducive to the development of complexity culminating in life as we know it, and that's a beautiful story. LRW I don't think there's a better way to end it, Alex. It's a huge honor. One of my favorite conversations I've had in this podcast. AC Well, thank you so much. LRW Thank you so much for talking. It was fun. AC Thanks for the honor of having been asked to do this. LRW Thanks for listening to this conversation with Alex Filippenko, and thank you to our sponsors. Neuro, the maker of functional sugar-free gum and mints that I used to give my brain a quick caffeine boost. BetterHelp, online therapy with a licensed professional. Masterclass, online courses that I enjoy from some of the most amazing humans in history. And Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Carl Sagan. The nitrogen in our DNA, the calcium in our teeth, the iron in our blood, the carbon in our apple pies were made in the interiors of collapsing stars. We are made of star stuff. Thank you for listening, and hope to see you next time.

https://youtu.be/WxfA1OSev4c

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Rodney Brooks: Robotics | Lex Fridman Podcast #217

The following is a conversation with Rodney Brooks, one of the greatest roboticists in history. He led the computer science and artificial intelligence laboratory at MIT, then co-founded iRobot, which is one of the most successful robotics companies ever. Then he co-founded Rethink Robotics that created some amazing collaborative robots like Baxter and Sawyer. Finally, he co-founded Robust.ai, whose mission is to teach robots common sense, which is a lot harder than it sounds. To support this podcast, please check out our sponsors in the description. As a side note, let me say that Rodney is someone I've looked up to for many years in my now over two decade journey in robotics, because one, he's a legit great engineer of real world systems, and two, he's not afraid to state controversial opinions that challenge the way we see the AI world. But of course, while I agree with him on some of his critical views of AI, I don't agree with some others, and he's fully supportive of such disagreement. Nobody ever built anything great by being fully agreeable. There's always respect and love behind our interactions, and when a conversation is recorded like it was for this podcast, I think a little bit of disagreement is fun. This is the Lex Friedman Podcast, and here is my conversation with Rodney Brooks. What is the most amazing or beautiful robot that you've ever had the chance to work with? I think it was Domo, which was made by one of my grad students, Aaron Edsinger. It now sits in Daniela Roos's office, director of CSAIL, and it was just a beautiful robot, and Aaron was really clever. He didn't give me a budget ahead of time. He didn't tell me what he was gonna do. He just started spending money. He spent a lot of money. He and Jeff Weber, who is a mechanical engineer who Aaron insisted he bring with him when he became a grad student, built this beautiful, gorgeous robot, Domo, which is an upper torso, humanoid, two arms with three-fingered hands, and face, eyeballs, all, not the eyeballs, but everything else, series elastic actuators. You can interact with it, cable-driven. All the motors are inside, and it's just gorgeous. The eyeballs are actuated, too, or no? Oh, yeah, the eyeballs are actuated with cameras, and so it had a visual attention mechanism, looking when people came in, and looking in their face, and talking with them. Wow, is it amazing. The beauty of it. You said what was the most beautiful? What is the most beautiful? It's just mechanically gorgeous. As everything Aaron builds, there's always been mechanically gorgeous. It's just exquisite in the detail. Oh, we're talking about mechanically, like literally the amount of actuators, the- The actuators, the cables, he anodizes different parts, different colors, and it just looks like a work of art. What about the face? Do you find the face beautiful in robots? When you make a robot, it's making a promise for how well it will be able to interact, so I always encourage my students not to overpromise. Even with its essence, like the thing it presents, it should not overpromise. Yeah, so the joke I make, which I think you'll get, is if your robot looks like Albert Einstein, it should be as smart as Albert Einstein. So the only thing in Domo's face is the eyeballs, because that's all it can do. It can look at you and pay attention. And so there is no, it's not like one of those Japanese robots that looks exactly like a person at all. But see, the thing is, us humans and dogs too, don't just use eyes as attentional mechanisms. They also use it to communicate. It's part of the communication. Like a dog can look at you, look at another thing, and look back at you, and that designates that we're going to be looking at that thing together. Yeah, or intent. You know, on both Baxter and Sawyer at Rethink Robotics, they had a screen with graphic eyes, so it wasn't actually where the cameras were pointing, but the eyes would look in the direction it was about to move its arm, so people in the factory nearby were not surprised by its motions, because it gave that intent away. Before we talk about Baxter, which I think is a beautiful robot, let's go back to the beginning. When did you first fall in love with robotics? We're talking about beauty and love to open the conversation, this is great. I've got these, I was born in the end of 1954, and I grew up in Adelaide, South Australia. And I have these two books that are dated 1961. So I'm guessing my mother found them in a store in 62 or 63. How and Why Wonder Books. How and Why Wonder Book of Electricity, and How and Why Wonder Book of Giant Brains and Robots. And I learned how to build circuits, you know, when I was eight or nine, simple circuits. And I read, you know, learned the binary system, and saw all these drawings mostly of robots, and then I tried to build them for the rest of my childhood. Wait, 61 you said? This was when the two books, I've still got them at home. What does the robot mean in that context? No, they were, some of the robots that they had were arms, you know, big arms to move nuclear material around, but they had pictures of welding robots that looked like humans under the sea, welding stuff underwater. So they weren't real robots, but they were, you know, what people were thinking about for robots. What were you thinking about? Were you thinking about humanoids? Were you thinking about arms with fingers? Were you thinking about faces or cars? No, actually, to be honest, I realized my limitation on building mechanical stuff. So I just built the brains mostly, out of different technologies as I got older. I built a learning system, which was chemical based, and I had this ice cube tray, each well was a cell, and by applying voltage to the two electrodes, it would build up a copper bridge. So over time, it would learn a simple network, so I could teach it stuff. And that was, mostly things were driven by my budget, and nails as electrodes, and an ice cube tray was about my budget at that stage. Later, I managed to buy transistors, and then I could build gates and flip-flops and stuff. So one of your first robots was an ice cube tray? Yeah. And it was very cerebral, because it learned to add. Very nice. Well, just a decade or so before, in 1950, Alan Turing wrote a paper that formulated the Turing test, and he opened that paper with the question, can machines think? So let me ask you this question. Can machines think? Can your ice cube tray one day think? Certainly machines can think, because I believe you're a machine, and I'm a machine, and I believe we both think. I think, speak for yourself. I think any other philosophical position is sort of a little ludicrous. What does think mean if it's not something that we do? And we are machines. So yes, machines can, but do we have a clue how to build such machines? That's a very different question. Are we capable of building such machines? Are we smart enough? We think we're smart enough to do anything, but maybe we're not. Maybe we're just not smart enough to build stuff like us. The kind of computer that Alan Turing was thinking about, do you think there is something fundamentally or significantly different between a computer between our ears, the biological computer that humans use, and the computer that he was thinking about from a sort of high level philosophical? Yeah, I believe that it's very wrong. In fact, I'm halfway through a, I think it'll be about a 480-page book titled, the working title is, Not Even Wrong. And if I may, I'll tell you a bit about that book. So there's two, well, three thrusts to it. One is the history of computation, what we call computation. Goes all the way back to some manuscripts in Latin from 1614 and 1620 by Napier and Kepler through Babbage and Lovelace. And then Turing's 1936 paper is, you know, what we think of as the invention of modern computation. And that paper, by the way, did not set out to, you know, invent computation. It set out to negatively answer one of Hilbert's three later set of problems. He called it, it's an effective way of getting answers. And Hilbert really worked with rewriting rules, as did Church, who also, at the same time, a month earlier than Turing, disproved Hilbert's, one of these three hypotheses. The other two had already been disproved by Gödel. So Turing set out to disprove it, because it's always easier to disprove these things than to prove that there is an answer. And so he needed, and it really came from his professor, who I was an undergrad at Cambridge, who'd said, who'd turned it into, is there a mechanical process? So he wanted to have a show, a mechanical process that could calculate numbers, because that was a mechanical process that people used to generate tables. They were called computers, the people at the time. And they followed a set of rules where they had paper, and they would write numbers down, and based on the numbers, they'd keep writing other numbers. And they would produce numbers for these tables, engineering tables, that the more iterations they did, the more significant digits came out. And so Turing, in that paper, set out to define what sort of machine could do that, mechanical machine, where it could produce an arbitrary number of digits in the same way a human computer did. And he came up with a very simple set of constraints where there was an infinite supply of paper. This is the tape of the Turing machine. And each Turing machine had a set of, came with a set of instructions that as a person could do with pencil and paper, write down things on the tape, and erase them and put new things there. And he was able to show that that system was not able to do something that Hilbert had hypothesized. So he disproved it. But he had to show that this system was good enough to do whatever could be done, but couldn't do this other thing. And there he said, and he says in the paper, I don't have any real arguments for this, but based on intuition. So that's how he defined computation. And then if you look over the next, from 1936, up until really around 1975, you see people struggling with, is this really what computation is? And so Marvin Minsky, very well known in AI, but also a fantastic mathematician in his book, Finite and Infinite Machines from the mid 60s, which is a beautiful, beautiful mathematical book, says at the start of the book, well, what is computation? Turing says it's this, and yeah, I sort of think it's that. It doesn't really matter whether the stuff's made of wood or plastic, it's just, you know, that relatively cheap stuff can do this stuff. And so, yeah, it seems like computation. And Donald Knuth in his first volume of his, you know, Art of Computer Programming in around 1968, says, well, what's computation? It's this stuff, like Turing says, that a person could do each step without too much trouble. And so one of his examples of what would be too much trouble was a step which required knowing whether Fermat's last theorem was true or not, because it was not known at the time. And that's too much trouble for a person to do as a step. And Hopcroft and Ullman sort of said a similar thing later that year, and by 1975, in the A. O. Hopcroft and Ullman book, they're saying, well, you know, we don't really know what computation is, but intuition says this is sort of about right, and this is what it is. That's computation. It's a sort of agreed upon thing, which happens to be really easy to implement in silicon. And then we had Moore's law, which took off, and it's been an incredibly powerful tool. I certainly wouldn't argue with that. The version we have of computation, incredibly powerful. Can we just take a pause? So what we're talking about is there's an infinite tape with some simple rules of how to write on that tape, and that's what we're kind of thinking about. This is computation. Yeah, and it's modeled after humans, how humans do stuff. And I think it's, Turing says in the 36th paper, one of the critical facts here is that a human has a limited amount of memory. So that's what we're gonna put onto our mechanical computers. So, mm, mm, mm. So, you know, unlike mass, or charge, or, you know. It's not given by the universe. It was, this is what we're gonna call computation. And then it has this really, you know, it had this really good implementation, which has completely changed our technological world. That's computation. Second part of the book, or argument in the book, I have this two by two matrix with science in the top row, engineering in the bottom row. Left column is intelligence, right column is life. So in the bottom row, the engineering, there's artificial intelligence, and there's artificial life. In the top row, there's neuroscience and abiogenesis. How does living matter turn, how does non-living matter become living matter? Four disciplines. These four disciplines all came into the current form in the period 1945 to 1965. That's interesting. There was neuroscience before, but it wasn't effective neuroscience. It was, you know, there was ganglia, and there's electrical charges, but no one knows what to do with it. And furthermore, there were a lot of players who were common across them. I've identified common players, except for artificial intelligence and abiogenesis. I don't have, but any other pair, I can point to people who worked on them. And a whole bunch of them, by the way, were at the Research Lab for Electronics at MIT, where Warren McCulloch held forth. And in fact, McCulloch, Pitts, Letvin, and Maturana wrote the first paper on functional neuroscience called What the Frog's Eye Tells the Frog's Brain, where instead of it just being this bunch of nerves, they sort of showed what different anatomical components were doing and telling other anatomical components and generating behavior in the frog. Would you put them as basically the fathers or one of the early pioneers of what are now called artificial neural networks? Yeah, I mean, McCulloch and Pitts, Pitts was much younger than him, in 1943, had written a paper inspired by Bertrand Russell on a calculus for the ideas eminent in neural systems, where they had tried to, without any real proof, they had tried to give a formalism for neurons, basically in terms of logic, AND gates, OR gates, and NOT gates, with no real evidence that that was what was going on, but they talked about it, and that was picked up by Minsky for his 1953 dissertation, which was a neural network, we would call it today. It was picked up by John von Neumann when he was designing the EDVAC computer in 1945. He talked about its components being neurons, based on, and in references, he's only got three references, and one of them is the McCulloch-Pitts paper. So all these people, and then the AI people, and the artificial life people, which was John von Neumann originally. It was like overlap between all of them. They're all going around at the same time. And three of these four disciplines turned to computation as their primary metaphor. So I've got a couple of chapters in the book. One is titled, wait, computers are people? Because that's where our computers came from, from people who were computing stuff. And then I've got another chapter, wait, people are computers, which is about computational neuroscience. So there's this whole circle here, that computation is it. And I have talked to people about, maybe it's not computation that goes on in the head. Of course it is. Okay, well, when Elon Musk's rocket goes up, is it computing? Is that how it gets into orbit? By computing? But we've got this idea, if you want to build an AI system, you write a computer program. Yeah, so the word computation very quickly starts doing a lot of work that it was not initially intended to do. Is this like in the same, if you talk about the universe as essentially performing a computation? Yeah, right. Wolfram does this. He turns it into computation. You don't turn rockets into computation. Yeah, by the way, when you say computation in our conversation, do you tend to think of computation narrowly in the way Turing thought of computation? It's gotten very, squishy, squishy over time. But computation in the way Turing thinks about it and the way most people think about it actually fits very well with thinking like a hunter-gatherer. There are places and there can be stuff in places and the stuff in places can change and it stays there until someone changes it. And it's this metaphor of place and container, which is a combination of our place cells in our hippocampus and our cortex. But this is how we use metaphors for mostly to think about. And when we get outside of our metaphor range, we have to invent tools, which we can sort of switch on to use. So calculus is an example of a tool. It can do stuff that our raw reasoning can't do. And we've got conventions of when you can use it or not. But sometimes, people try to, all the time, we always try to get physical metaphors for things, which is why quantum mechanics has been such a problem for a hundred years. Because it's a particle, no, it's a wave. It's gotta be something we understand. And I say, no, it's some weird mathematical logic that's different from those, but we want that metaphor. Well, I suspect that a hundred years or 200 years from now, neither quantum mechanics nor dark matter will be talked about in the same terms, in the same way that Flodgerson's theory eventually went away because it wasn't an adequate explanatory metaphor. That metaphor was the stuff, there is stuff in the burning, the burning is in the matter. But as it turns out, the burning was outside the matter, it was the oxygen. So our desire for metaphor and combined with our limited cognitive capabilities gets us into trouble. That's my argument in this book. Now, and people say, well, what is it then? And I say, well, I wish I knew that if I'd write a book about that. But I give some ideas. But so this is the three things. Computation is sort of a particular thing we use. Oh, can I tell you one beautiful thing? One beautiful thing I found? So, I used an example of a thing that's different from computation. You hit a drum and it vibrates and there are some stationary points on the drum surface, because the waves are going up and down the stationary points. Now, you could compute them to arbitrary precision, but the drum just knows them. The drum doesn't have to compute. What was the very first computer program ever written by Ada Lovelace? To compute Bernoulli numbers. And Bernoulli numbers are exactly what you need to find those stable points in the drum surface. Wow. Anyway, and there was a bug in the program. The arguments to divide were reversed in one place. And it still worked? Well, no, she never got to run it. They never built the analytical engine. She wrote the program without it. You know? So, computation. Computation is sort of a thing that's become dominant as a metaphor, but is it the right metaphor? All three of these four fields adopted computation. And a lot of it swirls around Warren McCulloch and all his students, and he funded a lot of people. And our human metaphors, our limitations to human thinking play into this. Those are the three themes of the book. So I have a little to say about computation. So you're saying that there is a gap between the computer or the machine that performs computation and this machine that appears to have consciousness and intelligence. Yeah. Can we- That piece of meat in your head. Piece of meat. And maybe it's not just the meat in your head, it's the rest of you too. I mean, you actually have a neural system in your gut. I tend to also believe, not believe, but we're now dancing around things we don't know, but I tend to believe other humans are important. So we're almost like, I just don't think we would ever have achieved the level of intelligence we have with other humans. I'm not saying so confidently, but I have an intuition that some of the intelligence is in the interaction. Yeah, and I think it seems to be very likely, again, this is speculation, but we, our species, and probably Neanderthals to some extent, because you can find old bones where they seem to be counting on them by putting notches, that when Neanderthals had done, we were able to put some of our stuff outside our body into the world, and then other people can share it. And then we get these tools that become shared tools. And so there's a whole coupling that would not occur in the single deep learning network which was fed all of literature or something. Yeah, the neural network can't step outside of itself. But is there some, can we explore this dark room a little bit and try to get at something? What is the magic? Where does the magic come from in the human brain that creates the mind? What's your sense as scientists that try to understand it and try to build it, what are the directions if followed might be productive? Is it creative interactive robots? Is it creating large deep neural networks that do like self-supervised learning? And just like we'll discover that when you make something large enough, some interesting things will emerge. Is it through physics and chemistry and biology like artificial life angle, like we'll sneak up in this four quadrant matrix that you mentioned? Is there anything, your most, if you had to bet all your money, financial, it's fine. I wouldn't. Okay. So every intelligence we know, and animal intelligence, dog intelligence, octopus intelligence, which is a very different sort of architecture from us, all the intelligences we know perceive the world in some way and then have action in the world, but they're able to perceive objects in a way which is actually pretty damn phenomenal and surprising. You know, we tend to think, you know, that the box over here between us, which is a sound box, I think, is a blue box, but blueness is something that we construct with color constancy. It's not, the blueness is not a direct function of the photons we're receiving. It's actually context, you know, which is why you can turn, you know, you maybe seen the examples where someone turns a stop sign into some other sort of sign by just putting a couple of marks on them and the deep learning system gets it wrong and everyone says, but the stop sign's red. You know, why is it, why is it the other sort of sign? Because redness is not intrinsic in just the photons. It's actually a construction of an understanding of the whole world and the relationship between objects to get color constancy. But our tendency, in order that we get an archive paper really quickly, is you just show a lot of data and give the labels and hope it figures it out, but it's not figuring it out in the same way we do. We have a very complex perceptual understanding of the world. Dogs have a very different perceptual understanding based on smell. They go smell a post, they can tell how many different dogs have visited it in the last 10 hours and how long ago. There's all sorts of stuff that we just don't perceive about the world. And just taking a single snapshot is not perceiving about the world. It's not seeing the registration between us and the object. And registration is a philosophical concept. Brian Cantwell-Smith talks about it a lot. Very difficult, squirmy thing to understand. But I think none of our systems do that. We've always talked in AI about the symbol grounding problem, how our symbols that we talk about are grounded in the world. And when deep learning came along and started labeling images, people said, ah, the grounding problem has been solved. No, the labeling problem was solved with some percentage accuracy. Which is different from the grounding problem. So you agree with Hans Marvek and what's called the Marvek's paradox that highlights this counterintuitive notion that reasoning is easy, but perception and mobility are hard. Yeah, we shared an office when I was working on computer vision and he was working on his first mobile robot. What were those conversations like? They were great. So do you still kind of, maybe you can elaborate, do you still believe this kind of notion that perception is really hard? And can you make sense of why we humans have this poor intuition about what's hard and not? Well, let me give a sort of another story. If you go back to the original teams working on AI from the late 50s into the 60s, and you go to the AI lab at MIT, who was it that was doing that? Was a bunch of really smart kids who got into MIT and they were intelligent. So what's intelligence about? Well, the stuff they were good at, playing chess, doing integrals, that was hard stuff. But a baby could see stuff. That wasn't intelligent. Anyone could do that, that's not intelligence. And so there was this intuition that the hard stuff is the things they were good at. And the easy stuff was the stuff that everyone could do. Yeah. And maybe I'm overplaying it a little bit, but I think there's an element of that. Yeah, I mean, I don't know how much truth there is to like chess, for example, as was for the longest time seen as the highest level of intellect, right? Until we got computers that were better at it than people. And then we realized, if you go back to the 90s, you'll see the stories in the press around when Kasparov was beaten by Deep Blue. Oh, this is the end of all sorts of things. Computers are gonna be able to do anything from now on. And we saw exactly the same stories with AlphaZero, the Go playing program. Yeah. But still, to me, reasoning is a special thing. And perhaps- No, actually, we're really bad at reasoning. We just use these analogies based on our hunter-gatherer intuitions. But why is that not, don't you think the ability to construct metaphor is a really powerful thing? Oh, yeah, it is. It's the stories. It is, it's the constructing the metaphor and registering that something constant in our brains. Like, isn't that what we're doing with vision, too? And we're telling our stories. We're constructing good models of the world. Yeah, yeah. But I think we jumped between what we're capable of and how we're doing it. Right, there was a little confusion that went on as we were telling each other stories. Yes, exactly. Trying to delude each other. No, I just think, I'm not exactly, so I'm trying to pull apart this Marv X paradox. I don't view it as a paradox. What did evolution spend its time on? It spent its time on getting us to perceive and move in the world. That was 600 million years as multi-celled creatures doing that. And then it was relatively recent that we were able to hunt or gather, or even animals hunting. That's much more recent. And then anything that we, speech, language, those things are, you know, just a couple of hundred thousand years, probably, if that long. And then agriculture, 10,000 years. All that stuff was built on top of those earlier things, which took a long time to develop. So if you then look at the engineering of these things, so building it into robots, what's the hardest part of robotics, do you think? As the decades that you worked on robots, in the context of what we're talking about, vision, perception, the actual, sort of the biomechanics of movement. I'm kind of drawing parallels here between humans and machines, always. Like, what do you think is the hardest part of robotics? I sort of think all of them. There are no easy paths to do well. We sort of go reductionist, and we reduce it to, if only we had all the location of all the points in 3D, things would be great. You know, if only we had labels on the images, you know, things would be great. But, you know, as we see, that's not good enough. Some deeper understanding. But if I came to you, and I could solve one category of problems in robotics, instantly, what would give you the greatest pleasure? I mean, is it, you know, you look at robots that manipulate objects. What's hard about that? You know, is it the perception? Is it the reasoning about the world, like common sense reasoning? Is it the actual building a robot that's able to interact with the world? Is it like human aspects of a robot that's interacting with humans and that game theory of how they work well together? Well, let's talk about manipulation for a second, because I had this really blinding moment. You know, I'm a grandfather, so grandfathers have blinding moments. Just three or four miles from here, last year, my 16-month-old grandson was in his new house, first time, right? First time in the city. First time in this house. And he'd never been able to get to a window before, but this had some low windows. And he goes up to this window with a handle on it that he's never seen before. And he's got one hand pushing the window and the other hand turning the handle to open the window. He knew two different hands, two different things he knew how to put together. And he's 16 months old! And there you are watching in awe. Yeah. In an environment he'd never seen before, a mechanism he'd never seen. How did he do that? Yes, that's a good question. How did he do that? That's why. It's like, okay, like you could see the leap of genius from using one hand to perform a task, to combining, to doing, I mean, first of all, in manipulation, that's really difficult. It's like two hands, both necessary to complete the action. And completely different. And he'd never seen a window open before. But he inferred somehow, a handle, open, something. Yeah. There may have been a lot of slightly different failure cases that you didn't see. Yeah. Not with a window, but with other objects of turning and twisting in handles. Oh, you know, there's a great counter to, you know, reinforcement learning will just give, you know, the robot, you'll give the robot plenty of time to try everything. Yes. Actually, can I tell a little side story here? So I'm in DeepMind in London. This is three, four years ago, where, you know, there's a big Google building, and then you go inside and you go through, there's more security, and then you get to DeepMind, where the other Google employees can't go. Yeah. And I'm in a conference room, a bare conference room with some of the people. And they tell me about their reinforcement learning experiment with robots, which are just trying stuff out. And they're my robots. They're Sawyers, we sold them. And they really like them, because Sawyers are compliant and can sense forces, so they don't break when they're bashing into walls. They stop and they do all this stuff. And, you know, so you just let the robot do stuff, and eventually it figures stuff out. By the way, Sawyer, we're talking about robot manipulation, so robot arms and so on. Yeah, Sawyer's a robot. Just to go, who is Sawyer? Sawyer's a robot arm that my company, Rethink Robotics built. Thank you for the context. Sorry. Okay, cool. So we're in DeepMind. And, you know, it's in the next room, these robots are just bashing around to try and use reinforcement learning to learn how to act. Can I go see them? Oh no, they're secret. They're all my robots, they're secret. That's hilarious. Okay. Anyway, the point is, you know, this idea that you just let reinforcement learning figure everything out is so counter to how a kid does stuff. So again, story about my grandson, I gave him this box that had lots of different lock mechanisms. He didn't randomly, you know, and he was 18 months old, he didn't randomly try to touch every surface or push everything he found. He could see what, where the mechanism was, and he started exploring the mechanism for each of these different lock mechanisms. And there was reinforcement, no doubt, of some sort going on there. But he applied a pre-filter, which cut down the search space dramatically. I wonder to what level we're able to introspect what's going on, because what's also possible is you have something like reinforcement learning going on in the mind, in the space of imagination. So like you have a good model of the world you're predicting, and you may be running those tens of thousands of like loops, but you're like, as a human, you're just looking at yourself, trying to tell a story of what happened. And it might seem simple, but maybe there's a lot of computation going on. Whatever it is, but there's also a mechanism that's being built up. It's not just random search. That mechanism prunes it dramatically. Yeah, that pruning step, but it doesn't... It's possible that that's... So you don't think that's akin to a neural network inside a reinforcement learning algorithm? Is it possible? Yeah, it's possible, but I... I'll be incredibly surprised if that happens. I'll also be incredibly surprised that after all the decades that I've been doing this, where every few years someone thinks, now we've got it, now we've got it. Four or five years ago, I was saying, I don't think we've got it yet. And everyone was saying, oh, you don't understand how powerful AI is. I had people tell me, you don't understand how powerful it is. I sort of had a track record of what the world had done to think, well, this is no different from before. Oh, we have bigger computers. We had bigger computers in the 90s and we could do more shit stuff. But okay, so let me push back. Because I'm generally sort of optimistic and try to find the beauty in things. I think there's a lot of surprising and beautiful things that neural networks, this new generation of deep learning revolution has revealed. To me, it has continually been very surprising the kind of things it's able to do. Now, generalizing that over saying like this, we've solved intelligence, that's another big leap. But is there something surprising and beautiful to you about neural networks? That where actually you sat back and said, I did not expect this. Oh, I think their performance on ImageNet was shocking. So computer vision, those early days, it was just very like, wow, okay. That doesn't mean that they're solving everything in computer vision we need to solve or in vision for robots. What about alpha zero and self-play mechanisms and reinforcement learning? Isn't that- Yeah, that was all in Donald Mickey's 1961 paper, everything there was there, which introduced reinforcement learning. No, but come on. So now you're talking about the actual techniques, but isn't this surprising to you, the level it's able to achieve with no human supervision of chess play? To me, there's a big, big difference between Deep Blue and- Maybe what that's saying is how overblown our view of ourselves is. You know, we- That chess is easy. Yeah, I mean, I came across this 1946 report that, and I'd seen this as a kid in one of those books that my mother had given me, actually. 1946 report, which pitted someone with an abacus against an electronic calculator, and he beat the electronic calculator. So there, at that point, was, well, humans are still better than machines at calculating. Are you surprised today that a machine can do a billion floating point operations a second, and you're puzzling for minutes to do one? I mean, I don't know, but I am certainly surprised. There's something, to me, different about learning. So a system that's able to learn- Learning, now, see, now you're getting into one of the deadly sins. Because of using terms overly broadly. Yeah, I mean, there's so many different forms of learning. Yeah. There's so many different forms. You know, I learned my way around the city. I learned to play chess. I learned Latin. I learned to ride a bicycle. All of those are, you know, are very different capabilities. Yeah. And if someone, you know, has a, you know, in the old days, people would write a paper about learning something. Now, the corporate press office puts out a press release about how company X has, is leading the world because they have a system that can. Yeah, but here's the thing. Okay, so what is learning? What I refer to as learning is many things, but I- It's a suitcase word. It's a suitcase word, but loosely, there's a dumb system, and over time, it becomes smart. Well, it becomes less dumb at the thing that it's doing. Yeah. Smart is a loaded word. Yes, less dumb at the thing it's doing. It gets better performance under some measure, under some set of conditions at that thing. And most of these learning algorithms, learning systems, fail when you change the conditions just a little bit in a way that humans don't. So I was at DeepMind. The AlphaGo had just come out, and I said, what would have happened if you'd given it a 21 by 21 board instead of a 19 by 19 board? They said, fail totally. But a human player would actually, you know, well, would actually be able to play a game. And actually, funny enough, if you look at DeepMind's work since then, they are presenting a lot of algorithms that would do well at the bigger board. So they're slowly expanding this generalization. I mean, to me, there's a core element there. It is very surprising to me that even in a constrained game of chess or Go, that through self-play, by a system playing itself, that it can achieve superhuman level performance through learning alone. So like- Okay, so you know, you didn't- It's still fundamentally different than search of- You didn't like it when I referred to Donald Mickey's 1961 paper. There, in the second part of it, which came a year later, they had self-play on an electronic computer at tic-tac-toe. Okay, it's not as, but it learned to play tic-tac-toe through self-play. That's not- And it learned to play optimally. What I'm saying is, I, okay, I have a little bit of a bias, but I find ideas beautiful, but only when they actually realize the promise. That's another level of beauty. Like, for example, what Bezos and Elon Musk are doing with rockets, we had rockets for a long time, but doing reusable, cheap rockets, it's very impressive. In the same way, I, okay- Yeah. I have not predicted- First of all, when I was, started and fell in love with AI, the game of Go was seen to be impossible to solve. Okay, so I thought maybe, you know, maybe it'd be possible to maybe have big leaps in a Moore's law style of way in computation that would be able to solve it. But I would never have guessed that you could learn your way, however, I mean, in the narrow sense of learning, learn your way to beat the best people in the world at the game of Go without human supervision, not studying the game of experts. Okay, so- That's just surprising. Using a different learning technique, Arthur Samuel, in the early 60s, and he was the first person to use machine learning, got, had a program that could beat the world champion at checkers. Now- Yes. So, and that at the time was considered amazing. By the way, Arthur Samuel had some fantastic advantages. Do you wanna hear Arthur Samuel's advantages? Two things. One, he was at the 1956 AI conference. I knew Arthur later in life. He was at Stanford when I was graduating there. He wore a tie and a jacket every day. The rest of us didn't. Delightful man, delightful man. It turns out Claude Shannon, in a 1950 Scientific American article outlined on chess playing, outlined the learning mechanism that Arthur Samuel used, and they had met in 1956. I assume there was some communication, but I don't know that for sure. But Arthur Samuel had been a vacuum tube engineer, on getting reliability of vacuum tubes, and then had overseen the first transistorized computers at IBM. And in those days, before you shipped a computer, you ran it for a week to get early failures. So he had this whole farm of computers running random code for hours and hours, a week for each computer. He had a whole bunch of them. So he ran his chess learning program with self-play on IBM's production line. He had more computation available to him than anyone else in the world. And then he was able to produce a chess playing program, I mean, a checkers playing program that could beat the world champion. So- That's amazing. The question is, what I mean, surprise, I don't just mean it's nice to have that accomplishment, is there is a stepping towards something that feels more intelligent than before. Yeah, but that's- And the question is- That's in your view of the world. Okay, well, let me then, doesn't mean I'm wrong. No, no, it doesn't. So the question is, if we keep taking steps like that, how far that takes us? Are we going to build a better recommender systems? Are we going to build slightly better robots? Or will we solve intelligence? So, I'm putting my bet on, we're still missing a whole lot, a lot. And why would I say that? Well, in these games, they're all, you know, 100% information games. But again, but each of these systems is a very short description of the current state, which is different from registering and perception in the world. Which gets back to Marovic's paradox. I'm definitely not saying that chess is somehow harder than perception, or any kind of, even any kind of robotics in the physical world, I definitely think is way harder than the game of chess. So I was always much more impressed by the workings of the human mind. It's incredible. The human mind is incredible. I believe that from the very beginning. I wanted to be a psychiatrist for the longest time. I always thought that's way more incredible in the game of chess. I think the game of chess is, I love the Olympics. It's just another example of us humans picking a task, and then agreeing that a million humans will dedicate their whole life to that task. And that's the cool thing that the human mind is able to focus on one task, and then compete against each other, and achieve like weirdly incredible levels of performance. That's the aspect of chess that's super cool. Not that chess in itself is really difficult. It's like the Fermat's last theorem is not in itself to me that interesting. The fact that thousands of people have been struggling to solve that particular problem is fascinating. So can I tell you my disease in this way? Sure. Which actually is closer to what you're saying. So as a child, I was building various, I called them computers. They weren't general purpose computers. Ice cube tray. The ice cube tray was one. But I built other machines, and what I liked to build was machines that could beat adults at a game, and the adults couldn't beat my machine. Yes. So you were like, that's powerful. Like that's a way to rebel. Yeah. By the way, when was the first time you built something that outperformed you? Do you remember? Well, I knew how it worked. I was probably nine years old, and I built a thing that was a game where you take turns in taking matches from a pile, and either the one who takes the last one or the one who doesn't take the last one wins, I forget. And so it was pretty easy to build that out of wires and nails and little coils that were like plugging in the number and a few light bulbs. The one I was prouder of, I was 12 when I built a thing out of old telephone switchboard switches that could always win at tic-tac-toe. That was a much harder circuit to design. But again, it was just, it was no active components. It was just three position switches, empty, X, zero, and nine of them and a light bulb on which move it wanted next, and then the human would go and move that. See, there's magic in that creation. It was, yeah, yeah. I tend to see magic in robots that, like, I also think that intelligence is a little bit overrated. I think we can have deep connections with robots, very soon, and- Well, we'll come back to connections with robots. Sure. But I do wanna say, I don't, I think too many people make the mistake of seeing that magic and thinking, well, we'll just continue, you know? But each one of those is a hard-fought battle for the next step, the next step. Yes, the open question here is, and this is why I'm playing devil's advocate, but I often do when I read your blog post in my mind, because I have this eternal optimism, is it's not clear to me, so I don't do what, obviously, the journalists do, or give into the hype, but it's not obvious to me how many steps away we are from a truly transformational understanding of what it means to build intelligence systems or how to build intelligence systems. I'm also aware of the whole history of artificial intelligence, which is where your deep grounding of this is, is there has been an optimism for decades. And that optimism, just like reading old optimism, is absurd, because people were like, they were saying things are trivial for decades, since the 60s. They were saying everything is true, computer vision is trivial. But I think my mind is working crisply enough to where, I mean, we can dig into it if you want. I'm really surprised by the things DeepMind has done. I don't think they're yet close to solving intelligence, but I'm not sure it's not 10 years away. What I'm referring to is interesting to see when the engineering, it takes that idea to scale, and the idea works. And no, it fools people. Okay, honestly, Rodney, if it was you, me, and Demis inside a room, forget the press, forget all those things. Just as a scientist, as a roboticist, that wasn't surprising to you that at scale, so we're talking about very large numbers. Okay, let's pick one that's the most surprising to you. Please don't yell at me. GPT-3. Okay, hold on a second. Hold on a second. I was gonna bring that up. Okay, thank you. Alpha zero, alpha go, alpha go zero, alpha zero, and then alpha fold one and two. So do any of these kind of have this core of, forget usefulness or application and so on, which you could argue for alpha fold. Like, as a scientist, was DORS surprising to you that it worked as well as it did? Okay, so if we're gonna make the distinction between surprise and usefulness, and I have to explain this. I would say alpha fold. And one of the problems at the moment with alpha fold is it gets a lot of them right, which is a surprise to me because they're a really complex thing. But you don't know which ones it gets right, which then is a bit of a problem. Now, they've come out with a recent- You mean the structure of the protein, it gets a lot of those right? Yeah, it's a surprising number of them right. Yeah. It's been a really hard problem. So that was a surprise how many it gets right. So far, the usefulness is limited because you don't know which ones are right or not, and now they've come out with a thing in the last few weeks, which is trying to get a useful tool out of it, and they may well do it. In that sense, at least alpha fold is different because your alpha fold too is different because now it's producing data sets that are actually potentially revolutionizing competition biology. They will actually help a lot of people. But- You'd say potentially revolutionizing, we don't know yet, but yeah. That's true, yeah. But I got you. I mean, this is, okay, so you know what? This is gonna be so fun. So let's go right into it. Speaking of robots that operate in the real world, let's talk about self-driving cars. Oh. Okay. Because you have built robotics companies. You're one of the greatest roboticists in history, and that's not just in the space of ideas. We'll also probably talk about that, but in the actual building and execution of businesses that make robots that are useful for people and that actually work in the real world and make money. You also sometimes are critical of Mr. Elon Musk, or let's more specifically focus on this particular technology, which is autopilot inside Teslas. What are your thoughts about Tesla autopilot or more generally vision-based machine learning approach to semi-autonomous driving? These are robots. They're being used in the real world by hundreds of thousands of people. And if you wanna go there, I can go there, but let's not too much, which let's say they're on par safety-wise as humans currently, meaning human alone versus human plus robot. Okay. So first let me say I really like the car I came in here today. Which is? 2021 model, Mercedes E450. I am impressed by the machine vision. So now other things I'm impressed by what it can do. I'm really impressed with many aspects of it. And I'm- It's able to stay in lane? Is it? It does the lane stuff. It's looking on either side of me. It's telling me about nearby cars. Or blind spots and so on. Yeah. When I'm going in close to something in the park, I get this beautiful, gorgeous top-down view of the world. I am impressed up the wazoo of how registered and metrical that is. Oh, so it's like multiple cameras and it's all right to produce the 360 view kind of thing? 360 view, you know, synthesized so it's above the car. I mean, it is unbelievable. I got this car in January. It's the longest I've ever owned a car without digging it. So it's better than me. Well, me and it together are better. So I'm not saying technology's bad or not useful, but here's my point. Yes. It's a replay of the same movie. Okay. So maybe you've seen me ask this question before, but when did the first car go over 55 miles an hour for over 10 miles on a public freeway with other traffic around driving completely autonomously? When did that happen? Was it CMU in the 80s or something? It was a long time ago. It was actually in 1987 in Munich. Oh, Munich, yeah. At the Bundeswehr. Yes. So they had it running in 1987. When do you think, and Elon has said he's gonna do this, when do you think we'll have the first car drive coast to coast in the US hands off the wheel, hands off the wheel, feet off the pedals, coast to coast? As far as I know, a few people have claimed to do it. 1995, that was the time. I didn't know, oh, that was the, yeah. They didn't claim, did they claim 100%? Not 100%, not 100%. And then there's a few marketing people who have claimed 100% since then. But my point is that, you know, what I see happening again is someone sees a demo and they overgeneralize and say, we must be almost there. But we've been working on it for 35 years. So that's demos. But this is gonna take us back to the same conversation with the AlphaZero. Are you not, okay, I'll just say what I am. Because I thought, okay, when I first started interacting with the Mobileye implementation of Tesla Autopilot, I've driven a lot of cars, you know, I've been in Google stuff, driving cars since the beginning. I thought there was no way, before I sat and used Mobileye, I thought there, just knowing computer vision, I thought there's no way it could work as well as it was working. So my model of the limits of computer vision was way more limited than the actual implementation of Mobileye. So that's one example. I was really surprised. I was like, wow, that was incredible. The second surprise came when Tesla threw away Mobileye and started from scratch. I thought there's no way they can catch up to Mobileye. I thought what Mobileye was doing was kind of incredible, like the amount of work and the annotation. Yeah, well, Mobileye was started by Amnon Shasher and used a lot of traditional, you know, hard fought computer vision techniques. But they also did a lot of good sort of, like non-research stuff, like actual, like, just good, like what you do to make a successful product, right, scale, all that kind of stuff. And so I was very surprised when they from scratch were able to catch up to that. That's very impressive. And I've talked to a lot of engineers that was involved. This is, that was impressive. And the recent progress, especially under, well, with the involvement of Andrej Karpathy, what they were, what they're doing with the data engine, which is converting into the driving task into these multiple tasks, and then doing this edge case discovery when they're pulling back, like the level of engineering made me rethink what's possible. I don't, I still, you know, I don't know to that intensity, but I always thought it was very difficult to solve autonomous driving with all the sensors, with all of the computation. I just thought it was a very difficult problem. But I've been continuously surprised how much you can engineer. First of all, the data acquisition problem, because I thought, you know, just because I worked with a lot of car companies, they're so a little bit old school to where I didn't think they could do this at scale, like AWS style data collection. So when Tesla was able to do that, I started to think, okay, so what are the limits of this? I still believe that driver, like sensing and the interaction with the driver and like studying the human factors, psychology problem is essential. It's always going to be there. It's always going to be there, even with fully autonomous driving. But I've been surprised what is the limit, especially of vision-based alone, how far that can take us. So that's my levels of surprise. Now, can you explain in the same way you said, like AlphaZero, that's a homework problem that's scaled large in its chest, like who cares, go with it. Here's actual people using an actual car and driving, many of them drive more than half their miles using the system. Right. So, yeah, they're doing well with Pure Vision. With Pure Vision, yeah. And you know, they- And now no radar, which is- I suspect that can't go all the way. And one reason is, without new cameras, without new cameras that have a dynamic range closer to the human eye, because the human eye has incredible dynamic range, and we make use of that dynamic range. And it's 11 orders of magnitude or some crazy number like that. The cameras don't have that, which is why you see the bad cases where the sun on a white thing, and it blinds it in a way it wouldn't blind a person. I think there's a bunch of things to think about before you say, this is so good, it's just gonna work. Okay. And I'll come at it from multiple angles. And I know you've got a lot of time. Yeah. Okay, let's do this. I have thought about these things. Yeah, I know. You've been writing a lot of great blog posts about it for a while before Tesla had autopilot, right? So you've been thinking about autonomous driving for a while from every angle. So a few things. You know, in the US, I think that the death rate from motor vehicle accidents is about 35,000 a year, which is an outrageous number. Not outrageous compared to COVID deaths, but there is no rationality. And that's part of the thing. People have said, engineers say to me, well, if we cut down the number of deaths by 10% by having autonomous driving, that's gonna be great. Everyone will love it. And my prediction is that if autonomous vehicles kill more than 10 people a year, there'll be screaming and hollering, even though 35,000 people a year have been killed by human drivers. It's not rational. It's a different set of expectations. And that will probably continue. So there's that aspect of it. The other aspect of it is that when we introduce new technology, we often change the rules of the game. So when we introduced cars first, into our daily lives, we completely rebuilt our cities and we changed all the laws. Jaywalking was not an offense. That was pushed by the car companies so that people would stay off the road so there wouldn't be deaths from pedestrians getting hit. We completely changed the structure of our cities and had these foul smelling things everywhere around us. And now you see pushback in cities like Barcelona is really trying to exclude cars, et cetera. So I think that to get to self-driving, we will, large adoption. It's not gonna be just take the current situation, take out the driver and put the same car doing the same stuff because the end cases too many. Here's an interesting question. How many fully autonomous train systems do we have in the US? I mean, do you count them as fully autonomous? I don't know. Because they're usually as a driver, but they're kind of autonomous, right? No, let's get rid of the driver. Okay, I don't know. It's either 15 or 16. Most of them are in airports. Okay. There's a few that go about five, two that go about five kilometers out of airports. Yeah. When is the first fully autonomous train system for mass transit expected to operate fully autonomously with no driver in the US city? It's expected to operate in 2017 in Honolulu. Oh, wow. It's delayed, but they will get there. But by the way, it was originally gonna be autonomous here in the Bay Area. I mean, they're all very close to fully autonomous, right? Yeah, but getting the closest to the thing. And I've often gone on a fully autonomous train in Japan, one that goes out to that fake island in the middle of Tokyo Bay. I forget the name of the... And what do you see when you look at that? What do you see when you go to a fully autonomous train in an airport? It's not like regular trains. At every station, there's a double set of doors so that there's a door of the train and there's a door off the platform. And it's really visible in this Japanese one because it goes out in amongst buildings. The whole track is built so that people can't climb onto it. Yeah. So there's an engineering that then makes the system safe and makes them acceptable. I think we'll see similar sorts of things happen in the US. What surprised me, I thought wrongly that we would have special purpose lanes on 101 in the Bay Area, the leftmost lane, so that it would be normal for Teslas or other cars to move into that lane and then say, okay, now it's autonomous and have that dedicated lane. I was expecting movement to that. Five years ago, I was expecting we'd have a lot more movement towards that. We haven't. And it may be because Tesla's been over-promising by saying this, calling their system fully self-driving. I think they may have been gotten there quicker by collaborating to change the infrastructure. This is one of the problems with long haul trucking being autonomous. I think it makes sense on freeways at night for the trucks to go autonomously. But then there's the how to get onto and off of the freeway. What sort of infrastructure do you need for that? Do you need to have the human in there to do that? Or can you get rid of the human? So I think there's ways to get there, but it's an infrastructure argument because the long tail of cases is very long and the acceptance of it will not be at the same level as human drivers. So I'm with you still, and I was with you for a long time, but I am surprised how well, how many edge cases of machine learning and vision-based methods can cover. This is what I'm trying to get at is, I think there's something fundamentally different with vision-based methods and Tesla Autopilot and any company that's trying to do the same. Okay, well, I'm not gonna argue with you because we're speculating. Yes. My gut feeling tells me it's gonna be, things will speed up when there is engineering of the environment because that's what happened with every other technology. I'm a bit, I don't know about you, but I'm a bit cynical that infrastructure, which relies on government to help out in these cases. If you just look at infrastructure in all domains, it's just government always drags behind on infrastructure. There's so many just- Well, in this country. In the, sure, sorry, yes. In this country, and of course, there's many, many countries that are actually much worse on infrastructure. Oh, yes, many of them are much worse, and there's some that, like high-speed rail, the other countries are done much better. I guess my question is, which is at the core of what I was trying to think through here and ask you is how hard is the driving problem as it currently stands? So you mentioned we don't want to just take the human out and duplicate whatever the human was doing, but if we were to try to do that, how hard is that problem? Because I used to think it's way harder. I used to think it's, with vision alone, it would be three decades, four decades. Okay, so I don't know the answer to this thing I'm about to pose, but I do notice that on Highway 280 here in the Bay Area, which largely has concrete surface rather than blacktop surface, the white lines that are painted there now have black boundaries around them, and my lane drift system in my car would not work without those black boundaries. Interesting. So I don't know whether they've started doing it to help the lane drift, whether it is an instance of infrastructure following the technology, but my car would not perform as well without that change in the way they paint the line. Unfortunately, really good lane keeping is not as valuable. It's orders of magnitude more valuable to have a fully autonomous system. But for me, lane keeping is really helpful because I'm lousy at it. But you wouldn't pay 10 times. The problem is there's not financial, it doesn't make sense to revamp the infrastructure to make lane keeping easier. It does make sense to revamp the infrastructure. Oh, I see what you mean. If you have a large fleet of autonomous vehicles, now you change what it means to own cars, you change the nature of transportation. But for that, you need autonomous vehicles. Let me ask you about Waymo then. I've gotten a bunch of chances to ride in a Waymo self-driving car and there, I don't know if you'd call them self-driving, but. Well, I mean, I rode in one before that called Waymo. Yeah. So at X. So there's currently, another surprising leap I didn't think would happen, which is they have no driver currently. Yeah, in Chandler. In Chandler, Arizona. And I think they're thinking of doing that in Austin as well. But they're expanding. Although, you know, and I do an annual checkup on this. So as of late last year, they were aiming for hundreds of rides a week, not thousands. And there is no one in the car, but there's certainly safety people in the loop. And it's not clear how many, you know, what the ratio of cars to safety people is. It wasn't, obviously they're not 100% transparent about this. No, none of them are 100% transparent. They're very untransparent. But at least the way they're, I don't want to make definitively, but they're saying there's no teleoperation. So like, they're, I mean, okay. And that sort of fits with YouTube videos I've seen of people being trapped in the car by a red cone on the street. And they do have rescue vehicles that come and then a person gets in and drives it. Yeah. But isn't it incredible to you, it was to me to get in a car with no driver and watch the steering wheel turn. Like for somebody who has been studying, at least certainly the human side of autonomous vehicles for many years, and you've been doing it for way longer. Like it was incredible to me that this was actually could happen. I don't care if that scale is 100 cars. This is not a demo. This is not, this is me as a regular human. The argument I have is that people make interpolations from that. Interpolations. That are, you know, it's here, it's done. You know, it's just, you know, we've solved it. No, we haven't yet. And that's my argument. Okay. So I'd like to go to, you keep a list of predictions. Yeah. On your amazing blog posts. It'd be fun to go through them. But before then, let me ask you about this. You have, you have a harshness to you sometimes in your criticisms of what is perceived as hype. And so like, because people extrapolate, like you said, and they kind of buy into the hype and then they kind of start to think that the technology is way better than it is. But let me ask you maybe a difficult question. Sure. Do you think, if you look at history of progress, don't you think to achieve the quote impossible, you have to believe that it's possible? Absolutely. Yeah. Look, here's two great runs. Great, unbelievable. 1903, first human power, human, you know, heavier than air flight. Yeah. 1969, we land on the moon. That's 66 years. I'm 66 years old. Yeah. In my lifetime, that span of my lifetime, barely, you know, flying, I don't know what it was, 50 feet, the length of the first flight or something, to landing on the moon. Unbelievable. Yeah. Fantastic. But that requires, by the way, one of the Wright brothers, both of them, but one of them didn't believe it's even possible like a year before, right? So like not just possible soon, but like ever. So, you know. How important is it to believe and be optimistic is what I guess. Oh yeah, it is important. It's when it goes crazy. When, you know, you said that, what was the word you used for my bad? Harshness. Harshness, yes. I just get so frustrated when people make these leaps and tell me that I don't understand. Right. You know, yeah. Just from iRobot, which I was co-founder of, I don't know the exact numbers now, because I haven't, it's 10 years since I stepped off the board, but I believe it's well over 30 million robots cleaning houses from that one company. And now there's lots of other companies. Yes. Was that a co-founder of iRobot? I don't know. I don't know. Was that a crazy idea that we had to believe in 2002 when we released it? Yeah, that was, we had to, you know, believe that it could be done. Let me ask you about this. So iRobot, one of the greatest robotics companies ever, in terms of manufacturing, creating a robot that actually works in the real world is probably the greatest robotics company ever. You were the co-founder of it. If the Rodney Brooks of today talked to the Rodney of back then, what would you tell him? Because I have a sense that, would you pat him on the back and say, what you're doing is going to fail, but go at it anyway? That's what I'm referring to with the harshness. You've accomplished an incredible thing there. One of the several things we'll talk about. That's what I'm trying to get at, that line. No, it's when, my harshness is reserved for people who are not doing it, who claim it's just, well, this shows that it's just gonna happen. But here's the thing. This shows- But you have that harshness for Elon too. And no- Or no, it's a different harshness. No, it's a different argument with Elon. You know, I think SpaceX is an amazing company. On the other hand, in one of my blog posts, I said, what's easy and what's hard? I said, SpaceX, vertical landing rockets, it had been done before. Grid fins had been done since the 60s. Every Sawyer's has them. Reusable, DCX reused those rockets that landed vertically. Those whole insurance industry in place for rocket launches, there were all sorts of infrastructure. That was doable. It took a great entrepreneur, a great personal expense. He almost drove himself bankrupt doing it. A great belief to do it. Whereas Hyperloop, there's a whole bunch more stuff that's never been thought about and never been demonstrated. So my estimation is Hyperloop is a long, long, a lot further off. And if I've got a criticism of Elon, it's that he doesn't make distinctions between when the technology's coming along and ready, and then he'll go off and mouth off about other things, which then people go and compete about and try and do. And so- This is where I, I understand what you're saying. I tend to draw a different distinction. I have a similar kind of harshness towards people who are not telling the truth, who are basically fabricating stuff to make money or to- Well, he believes what he says. I just think he's wrong sometimes. To me, that's a very important difference. Yeah, I'm not- Because I think in order to fly, in order to get to the moon, you have to believe even when most people tell you you're wrong and most likely you're wrong, but sometimes you're right. I mean, that's the same thing I have with Tesla Autopilot. I think that's an interesting one. I was, especially when I was at MIT and just the entire human factors in the robotics community were very negative towards Elon. It was very interesting for me to observe colleagues at MIT. I wasn't sure what to make of that. That was very upsetting to me because I understood where that's coming from. And I agreed with them. And I kind of almost felt the same thing in the beginning until I kind of opened my eyes and realized there's a lot of interesting ideas here. There might be overhype. If you focus yourself on the idea that you shouldn't call a system full self-driving when it's obviously not autonomous, fully autonomous, you're going to miss the magic of- Oh, yeah, you are going to miss the magic, but at the same time, there are people who buy it, literally pay money for it and take those words as given. But I haven't, so I take words as given as one thing. I haven't actually seen people that use Autopilot that believe that the behavior is really important, like the actual action. So like this is to push back on the very thing that you're frustrated about, which is like journalists and general people buying all the hype and going on. In the same way, I think there's a lot of hype about the negatives of this too, that people are buying without using. People use the way, this opened my eyes actually. The way people use a product is very different than the way they talk about it. This is true with robotics, with everything. Everybody has dreams of how a particular product might be used or so on. And then when it meets reality, there's a lot of fear of robotics, for example, that robots are somehow dangerous and all those kinds of things. But when you actually have robots in your life, whether it's in the factory or in the home, making your life better, that's going to be, that's way different. Your perceptions of it are gonna be way different. And so my just tension was like, here's an innovator, like, what is it? Sorry, Super Cruise from Cadillac was super interesting too. That's a really interesting system. We should like be excited by those innovations. Okay, so can I tell you something that's really annoyed me recently? It's really annoyed me that the press and friends of mine on Facebook are going, these billionaires and their space games, why are they doing that? Yeah, that's been very frustrating. And that really, really pisses me off. I must say, I applaud that. I applaud it. It's the taking, and not necessarily the people who are doing the things, but that I keep having to push back against unrealistic expectations of when these things can become real. Yeah, this was interesting, Ana, because there's been a particular focus for me is autonomous driving. Elon's prediction of when certain milestones would be hit. There's several things to be said there that I thought about, because whenever you said them, it was obvious that's not going to me as a person that kind of not inside the system, it was obvious it's unlikely to hit those. There's two comments I want to make. One, he legitimately believes it. And two, much more importantly, I think that having ambitious deadlines drives people to do the best work of their life, even when the odds of those deadlines are very low. To a point, and I'm not talking about Elon here, I'm just saying. So there's a line there, right? You have to have a line, because you overextend and it's demoralizing. But I will say that there's an additional thing here, that those words also drive the stock market. And we have, because of the way that rich people in the past have manipulated the rubes through investment, we have developed laws about what you're allowed to say and over promise. And there's an area here which is... I tend to be, maybe I'm naive, but I tend to believe that engineers, innovators, people like that, they're not, they're my, they don't think like that, like manipulating the stock price, but it's possible that I'm wrong. It's a very cynical view of the world, because I think most people that run companies and build, especially original founders, they... Yeah, I'm not saying that's the intent. I'm saying it's a... Eventually it's kind of, you fall into that kind of a behavior pattern. I don't know. I tend to... I wasn't saying it's falling into that intent. It's just, you also have to protect investors in this market. Yeah. Okay, so you have, first of all, you have an amazing blog that people should check out, but you also have this, in that blog, a set of predictions. It's such a cool idea. I don't know how long ago you started, like three, four years ago? It was January 1st, 2018. 18, yeah. And I made these predictions and I said that every January 1st, I was gonna check back on how my predictions had... That's such a great thought. For 32 years. Oh, so you said 32 years. I said 32 years, because I thought that'll be January 1st, 2050. I'll be... I will just turn 95. Nice. And so people know that your predictions, at least for now, are in the space of artificial intelligence. Yeah, I didn't say I was gonna make new predictions. I was just gonna measure this set of predictions that I made, because I was sort of annoyed that everyone could make predictions, they didn't come true and everyone forgot. So I said, I should hold myself to a high standard. Yeah, but also just putting years and like date ranges on things, it's a good thought exercise. And like reasoning your thoughts out. And so the topics are artificial intelligence, autonomous vehicles, and space. I was wondering if we could just go through some that stand out maybe from memory, I can just mention to you some, let's talk about self-driving cars, like some predictions that you're particularly proud of or are particularly interesting from flying cars to the other element here is like how widespread the location where the deployment of the autonomous vehicles is. And there's also just a few fun ones. Is there something that jumps to mind that you remember from the predictions? Well, I think I did put in there that there would be a dedicated self-driving lane on 101 by some year. And I think I was over optimistic on that one. Yeah, actually, yeah, I actually do remember that. But I think you were mentioning like difficulties at different cities. Yeah, yeah. So Cambridge, Massachusetts, I think was an example. Yeah, like in Cambridge Port, you know, I lived in Cambridge Port for a number of years and you know, the roads are narrow and getting anywhere as a human driver is incredibly frustrating when you start to put, and people drive the wrong way on one-way streets there. It's just... So your prediction was driverless taxi services operating on all streets in Cambridge Port, Massachusetts in 2035. Yeah, and that may have been too optimistic. You think so? You know, I've gotten a little more peasant-like and a little more pessimistic since I made these internally on some of these things. So what... Can you put a year to a major milestone of deployment of a taxi service in a few major cities? Like something where you feel like autonomous vehicles are here. So let's take the grid streets of San Francisco north of Market. Okay. Okay. Relatively benign environment. The streets are wide. The major problem is delivery trucks stopping everywhere, which has made things more complicated. A taxi system there with somewhat designated pickup and drop-offs, unlike with Uber and Lyft, where you can sort of get to any place and the drivers will figure out how to get in there. We're still a few years away. I live in that area. So I see the self-driving car companies, cars, multiple ones every day out there, but cruise. Zooks less often, Waymo all the time, different and different ones come and go. And there's always a driver. There's always a driver at the moment. Although I have noticed that sometimes the driver does not have the authority to take over without talking to the home office, because they will sit there waiting for a long time. And clearly something's going on where the home office is making a decision. And so you can see whether they've got their hands on the wheel or not. And it's the incident resolution time that gives you some clues. So what year do you think, what's your intuition? What date range are you currently thinking San Francisco would be autonomous taxi service from any point A to any point B without a driver? Are you still, are you thinking 10 years from now, 20 years from now, 30 years from now? Certainly not 10 years from now. It's going to be longer. If you're allowed to go South of market, way longer. And unless it's re-engineering of roads. By the way, what's the biggest challenge? You mentioned a few. Is it the delivery trucks? Is it the edge cases, the computer perception? Well, here's a case that I saw outside my house a few weeks ago, about 8 p.m. on a Friday night. It was getting dark, it was before the solstice. It was a cruise vehicle come down the hill, turned right and stopped dead, covering the crosswalk. Why did it stop dead? Because there was a human just two feet from it. Now I just glanced, I knew what was happening. The human was a woman, was at the door of her car, trying to unlock it with one of those things that you know, when you don't have a key. That car thought, oh, she could jump out in front of me any second. As a human, I could tell, no, she's not gonna jump out. She's busy trying to unlock her, she's lost her keys. She's trying to get in the car. And it stayed there for, until I got bored. Yeah. And so the human driver in there did not take over. But here's the kicker to me. A guy comes down the hill with a stroller, I assume there's a baby in there. And now the crosswalk's blocked by this cruise vehicle. What's he gonna do? Cleverly, I think, he decided not to go in front of the car. He went, but he had to go behind it. He had to get off the crosswalk, out into the intersection to push his baby around this car, which was stopped there. And no human driver would have stopped there for that length of time. They would have got out and out of the way. And that's another one of my pet peeves that safety is being compromised for individuals who didn't sign up for having this happen in their neighborhood. Yeah, but now you can say that's an edge case, but- Yeah, well, I'm in general, not a fan of anecdotal evidence for stuff. Like this is one of my biggest problems with the discussion of autonomous vehicles in general, people that criticize them or support them are using edge cases, are using anecdotal evidence. But I got you. Your question is, when is it gonna happen in San Francisco? I say not soon, but it's gonna be one of them. But where it is gonna happen is in limited domains, campuses of various sorts, gated communities, where the other drivers are not arbitrary people. They're people who know about these things. They, you know, it's been warned about them. And at velocities where it's always safe to stop dead. Yeah. You can't do that on the freeway. That I think we're gonna start to see. And they may not be shaped like current cars. They may be things like May Mobility has those things and various companies have these. Yeah, I wonder if that's a compelling experience. To me, it's always important. It's not just about automation. It's about creating a product that makes your, it's not just cheaper, but it makes your, that's fun to ride. One of the least fun things is for a car that stops and like waits. There's something deeply frustrating for us humans, for the rest of the world to take advantage of us as we wait. But think about, you know, not you as the customer, but someone who's in their 80s in a retirement village whose kids have said, you are not driving anymore. And this gives you the freedom to go to the market. That's a hugely beneficial thing, but it's a very few orders of magnitude less impact on the world. It's not, it's just a few people in a small community using cars as opposed to the entirety of the world. I like that the first time that a car equipped with some version of a solution to the trolley problem is what's NIML stand for? Like not in my life. I define my lifetime as up to 2050. Yeah. You know, I ask you, when have you had to decide which person shall I kill? No, you put the brakes on and you brake as hard as you can. I mean, it is, you know, I do think autonomous vehicles or semi-autonomous vehicles do need to solve the whole pedestrian problem that has elements of the trolley problem within it, but it's not. Yeah, well, so here's, and I talk about it in one of the articles or blog posts that I wrote. His, and people have told me, one of my coworkers has told me he does this. He tortures autonomously driven vehicles and pedestrians will torture them. Now, you know, once they realize that, you know, putting one foot off the curb makes the car think that they might walk into the road, kids, teenagers will be doing that all the time. I, by the way, one of my, and this is a whole another discussion, because my main issue with robotics is HRI, human robot interaction. I believe that robots that interact with humans will have to push back. Like they can't just be bullied because that creates a very uncompelling experience for the humans. Yeah, well, you know, Waymo, before it was called Waymo, discovered that, you know, they had to do that at four-way intersections. They had to nudge forward to give the cue that they were gonna go, because otherwise the other drivers would just beat them all the time. So you co-founded iRobot, as we mentioned, one of the most successful robotics companies ever. What are you most proud of with that company and the approach you took to robotics? Well, there's something I'm quite proud of there, which may be a surprise, but I was still on the board when this happened. It was March, 2011, and we sent robots to Japan and they were used to help shut down the Fukushima Daiichi nuclear power plant, which was, everything was, I've been there since. I was there in 2014, and the robots, some of the robots were still there. I was proud that we were able to do that. Why were we able to do that? And people have said, well, Japan is so good at robotics. It was because we had had about 6,500 robots deployed in Iraq and Afghanistan, tele-opt, but with intelligence, dealing with roadside bombs. So we had, I think it was at that time, nine years of in-field experience with the robots in harsh conditions. Whereas the Japanese robots, which were getting, this goes back to what annoys me so much, getting all the hype, look at that, look at that Honda robot, it can walk. Wow, the future's here. Couldn't do a thing because they weren't deployed, but we had deployed in really harsh conditions for a long time. And so we're able to do something very positive in a very bad situation. What about just the simple, and for people who don't know, one of the things that iRobot has created is the Roomba vacuum cleaner. What about the simple robot that is the Roomba, quote unquote simple, that's deployed in tens of millions of, in tens of millions of homes? What do you think about that? Well, I make the joke that I started out life as a pure mathematician and turned into a vacuum cleaner salesman. So if you're gonna be an entrepreneur, be ready to do anything. But I was, there was a wacky lawsuit that I got deposed for not too many years ago. And I was the only one who had emailed from the 1990s and no one in the company had it. So I went and went through my email and it reminded me of the joy of what we were doing and what was I doing? What was I doing at the time we were building the Roomba? One of the things was we had this incredibly tight budget because we wanted to put it on the shelves at $200. There was another home cleaning robot at the time. It was the Electrolux Trilobyte, which sold for 2000 euros. And to us, that was not gonna be a consumer product. So we had reason to believe that $200 was a thing that people would buy at. That was our aim. But that meant we had, that's on the shelf making profit. That means the cost of goods has to be minimal. So I find all these emails of me going, I'd be in Taipei for a MIT meeting and I'd stay a few extra days, I'd go down to Shinshu and talk to these little tiny companies, lots of little tiny companies outside of TSMC, Taiwan Semiconductor Manufacturing Corporation, which let all these little companies be fabulous. They didn't have to have their own fab so they could innovate. And they were building, their innovations were to build stripped down 6802s. 6802 was what was in an Apple One. Get rid of half the silicon, still have it be viable. And I'd previously got some of those for some earlier failed products of iRobot. And then that was in Hong Kong, going to all these companies that built, they weren't gaming in the current sense, there were these handheld games that you would play or birthday cards, because we had about a 50 cent budget for computation. So I'm trekking from place to place, looking at their chips, looking at what they'd removed. Ah, their interrupt handling is too weak for a general purpose. So I was going deep technical detail. And then I found this one from a company called Winbond, which had, and I'd forgotten it had this much RAM. It had 512 bytes of RAM and it was in our budget and it had all the capabilities we needed. Yeah. So. And you were excited. Yeah, and I was reading all these emails, Colin, I found this. So. Did you think, did you ever think that you guys could be so successful? Like eventually this company would be so successful. Did you, could you possibly have imagined? No, we never did think that. We'd had 14 failed business models up to 2002. And then we had two winners same year. No, and then, you know, we, I remember the board, cause by this time we had some venture capital in. The board went along with us building some robots for, you know, aiming at the Christmas 2002 market. And we went three times over what they authorized and built 70,000 of them and sold them all in that first, cause we released on September 18th and they were all sold by Christmas. So it was, so we were gutsy, but. But yeah, you didn't think this will take over the world. Well, this is, so a lot of amazing robotics companies have gone under over the past few decades. Why do you think it's so damn hard to run a successful robotics company? There's a few things. One is expectations of capabilities by the founders that are off base. The founders, not the consumer, the founders. Yeah, expectations of what can be delivered. Sure. Mispricing. And what a customer thinks is a valid price is not rational necessarily. Yeah. And expectations of customers. And just the sheer hardness of getting people to adopt a new technology. And I've suffered from all three of these. You know, I've had more failures than successes in terms of companies. I've suffered from all three. So. Do you think one day there will be a robotics company, and by robotics company, I mean, where your primary source of income is from robots, that will be a trillion plus dollar company? And if so, what would that company do? I can't, you know, because I'm still starting robot companies. Yeah. I'm not making any such predictions in my own mind. I'm not thinking about a trillion dollar company. And by the way, I don't think, you know, in the 90s, anyone was thinking that Apple would ever be a trillion dollar company. So these are very hard to predict. Sorry to interrupt, but don't you, because I kind of have a vision in a small way, a big vision in a small way, that I see that there will be robots in the home that will be able to do the job. Robots in the home at scale, like Roomba, but more. And that's a trillion dollar. Right. And I think there's a real market pull for them because of the demographic inversion. You know, who's gonna do all the stuff for the older people? There's too many, you know, I'm leading here. This is gonna be too many of us. And, but we don't have capable enough robots to make that economic argument at this point. Do I expect that that will happen? Yes, I expect it will happen. But I gotta tell you, we introduced the Roomba in 2002, and I stayed another nine years. We were always trying to find what the next home robot would be. And still today, the primary product of 20 years, almost 20 years later, 19 years later, the primary product is still the Roomba. So iRobot hasn't found the next one. Do you think it's possible for one person in the garage to build it versus like Google launching, Google self-driving car that turns into Waymo? Do you think it's possible? This is almost like what it takes to build a successful robotics company. Do you think it's possible to go from the ground up or is it just too much capital investment? Yeah, so it's very hard to get there without a lot of capital. And we're starting to see fair chunks of capital for some robotics companies. Series Bs, I just saw one yesterday for $80 million. I think it was for Covariant. But it can take real money to get into these things and you may fail along the way. I've certainly failed at Rethink Robotics. And we lost $150 million in capital there. Okay, so Rethink Robotics is another amazing robotics company you co-founded. So what was the vision there? What was the dream? And what are you most proud of with Rethink Robotics? I'm most proud of the fact that we got robots out of the cage in factories that was safe, absolutely safe for people and robots to be next to each other. So these are robotic arms. Robotic arms. They're able to pick up stuff and interact with humans. Yeah, and that humans could retask them without writing code. And now that's sort of become an expectation for a lot of other little companies and big companies are advertising they're doing. That's both an interface problem and also a safety problem. Yeah, yeah. So I'm most proud of that. I completely, I let myself be talked out of what I wanted to do. And you always got, I can't replay the tape. I can't replay it. Maybe if I'd been stronger on, and I remember the day, I remember the exact meeting. Can you take me through that meeting? Yeah, so I'd said that I'd set as a target for the company that we were gonna build $3,000 robots with force feedback that was safe for people to be around. Wow. That was my goal. And we built, so we started in 2008, and we had prototypes built of plastic, plastic gear boxes. And at a $3,000 lifetime, or $3,000, I was saying we're gonna go after not the people who already have robot arms in factories, the people who never have a robot arm. We're gonna go after a different market so we don't have to meet their expectations. And so we're gonna build it out of plastic. It doesn't have to have a 35,000-hour lifetime. It's gonna be so cheap that it's OPEX, not CAPEX. And so we had a prototype that worked reasonably well, but the control engineers were complaining about these plastic gear boxes. It was a beautiful little planetary gear box, but we could use something called series elastic actuators. We embedded them in there. We could measure forces. We knew when we hit something, et cetera. The control engineers were saying, yeah, but there's this torque ripple, because these plastic gears, they're not great gears, and there's this ripple, and trying to do force control around this ripple is so hard. And I'm not gonna name names, but I remember one of the mechanical engineers saying, we'll just build a metal gear box with spur gears, and it'll take six weeks, we'll be done, problem solved. Two years later, we got the spur gear box working. We cost reduced in every possible way we could, but now the price went up too. And then the CEO at the time said, well, we have to have two arms, not one arm. So our first robot product, Baxter, now costs $25,000. And the only people who were gonna look at that were people who had arms in factories, because that was somewhat cheaper for two arms than arms in factories. But they were used to 0.1 millimeter reproducibility of motion and certain velocities. And I kept thinking, but that's not what we're giving you. You don't need position repeatability. You use force control like a human does. No, no, but we want that repeatability. We want that repeatability. All the other robots have that repeatability. Why don't you have that repeatability? So can you clarify, force control is you can grab the arm and you can move it. Yeah, well, you can move it around. But suppose you, can you see that? Yes. Suppose you want to, yes. Suppose this thing is a precise thing that's gotta fit here in this right angle. Yeah, under position control, you have fixtured where this is, you know where this is precisely, and you just move it, and it goes there. If force control, you would do something like slide it over here till we feel that, and slide it in there. And that's how a human gets precision. They use force feedback and get the things to mate rather than just go straight to it. Couldn't convince our customers who were in factories and were used to thinking about things a certain way, and they wanted it, wanted it, wanted it. So then we said, okay, we're gonna build an arm that gives you that. So now we ended up building a $35,000 robot with one arm, with, oh, what are they called? A certain sort of gearbox made by a company whose name I can't remember right now, but it's the name of the gearbox. And, but it's got torque ripple in it. So now there was an extra two years of solving the problem of doing the force with the torque ripple. So we had to do the thing we had avoided for the plastic gearboxes. We ended up having to do, the robot was now overpriced, and that was your intuition from the very beginning kind of that this is not, you're opening a door to solve a lot of problems there. You're eventually gonna have to solve this problem anyway. Yeah, and also I was aiming at a low price to go into a different market. Low price. That didn't have robots. $3,000 would be amazing. Yeah, I think we could have done it for five, but you know, you said, talked about setting the goal a little too far for the engineers. Exactly. So why would you say that company not failed, but went under? We had buyers, and there's this thing called the Committee on Foreign Investment in the US, CFIUS, and that had previously been invoked twice around where the government could stop foreign money coming into a US company based on defense requirements. We went through due diligence multiple times. We were gonna get acquired, but every consortium had Chinese money in it, and all the bankers would say at the last minute, you know, this isn't gonna get past CFIUS, and the investors would go away. And then we had two buyers, once we were about to run out of money, two buyers, and one used heavy-handed legal stuff with the other one, said they were gonna take it and pay more, dropped out when we were out of cash, and then bought the assets at 1 30th of the price they had offered a week before. It was a tough week. Does it hurt to think about, like an amazing company that didn't, you know, like iRobot didn't find a way? Yeah, it was tough. I said I was never gonna start another company. I was pleased that everyone liked what we did so much that the team was hired by three companies within a week. Everyone had a job in one of these three companies. Some stayed in their same desks because another company came in and rented the space. So I felt good about people not being out on the street. So Baxter's a screen with a face. That's a revolutionary idea for a robot manipulation, like for a robotic arm. How much opposition did you get? Well, first, the screen was also used during codeless programming, where you taught by demonstration, it showed you what its understanding of the task was. So it had two roles. Some customers hated it. And so we made it so that when the robot was running, it could be showing graphs of what was happening and not show the eyes. Other people, and some of them surprised me who they were, were saying, well, this one doesn't look as human as the old one. We like the human looking. So there was a mixed bag there. But do you think that's, I don't know, I'm kind of disappointed whenever I talk to roboticists, like the best robotics people in the world, they seem to not want to do the eyes type of thing. Like they seem to see it as a machine as opposed to a machine that can also have a human connection. I'm not sure what to do with that. It seems like a lost opportunity. I think the trillion dollar company will have to do the human connection very well, no matter what it does. Yeah, I agree. Can I ask you a ridiculous question? Sure. I might give a ridiculous answer. Do you think, well, maybe by way of asking the question, let me first mention that you're kind of critical of the idea of the Turing test as a test of intelligence. Let me first ask this question. Do you think we'll be able to build an AI system that humans fall in love with and it falls in love with the human? Like romantic love. Well, we've had that with humans falling in love with cars, even back in the 50s. It's a different love, right? Well, yeah. I think there's a lifelong partnership where you can communicate and grow like. I think we're a long way from that. I think we're a long, long way. I think Blade Runner was, you know, had the time scale totally wrong. Yeah. Yeah. But so to me, honestly, the most difficult part is the thing that you said with the Marvax paradox is to create a human form that interacts and perceives the world. But if we just look at a voice, like the movie, Her, or just like an Alexa type voice, I tend to think we're not that far away. Well, for some people, maybe not, but I, you know, I, you know, as humans, as we think about the future, we always try, and this is the premise of most science fiction movies, you've got the world just as it is today and you change one thing. Right. But that's not how, and it's the same with the self-driving car. You change one thing. No, everything changes. Yes. Everything grows together. So surprisingly, it might be surprising to you, it might not, but the best movie about this stuff was Bicentennial Man. And what was happening there? It was schmaltzy and, you know, what was happening there? As the robot was trying to become more human, the humans were adopting the technology of the robot and changing their bodies. So there was a convergence happening in a sense. And so we will not be the same. You know, we're already talking about genetically modifying our babies. You know, there's more and more stuff happening around that. We will want to modify ourselves even more for all sorts of things. We put all sorts of technology in our bodies to improve it. You know, I've got things in my ears so that I can sort of hear you. Yeah. So we're always modifying our bodies. So, you know, I think it's hard to imagine exactly what it will be like in the future. But on the Turing test side, do you think, so forget about love for a second, let's talk about just like the Alexa Prize. Actually, I was invited to be a, what is the interviewer for the Alexa Prize or whatever? That's in two days. Their idea is success looks like a person wanting to talk to an AI system for a prolonged period of time, like 20 minutes. How far away are we? And why is it difficult to build an AI system with which you'd want to have a beer and talk for an hour or two hours? Like not for to check the weather or to check music, but just like to talk as friends. Yeah, well, you know, we saw Weizenbaum back in the 60s with his programmer, Liza, being shocked at how much people would talk to Liza. I remember, you know, in the 70s, typing stuff to Liza to see what it would come back with. You know, I think right now, and this is a thing that Amazon's been trying to improve with Alexa. There is no continuity of topic. You can't refer to what we talked about yesterday. It's not the same as talking to a person where there seems to be an ongoing existence, which changes. We share moments together and they last in our memory together. Yeah, but there's none of that. And there's no sort of intention of these systems that they have any goal in life, even if it's to be happy. You know, they don't even have a semblance of that. Now, I'm not saying this can't be done. I'm just saying, I think this is why we don't feel that way about them. Or that's a sort of a minimal requirement. If you want the sort of interaction you're talking about, it's a minimal requirement. Whether it's gonna be sufficient, I don't know, we haven't seen it yet. We don't know what it feels like. I tend to think it's not as difficult as solving intelligence, for example. And I think it's achievable in the near term. But on the Turing test, why don't you think the Turing test is a good test of intelligence? Oh, because, you know, again, the Turing, if you read the paper, Turing wasn't saying this is a good test. He was using it as a rhetorical device to argue that if you can't tell the difference between a computer and a person, you must say that the computer's thinking because you can't tell the difference when it's thinking. You can't say something different. What it has become as this sort of weird game of fooling people. So back at the AI lab in the late 80s, we had this thing that still goes on called the AI Olympics. And one of the events we had one year was the original imitation game as Turing talked about, because he starts by saying, can you tell whether it's a man or a woman? So we did that at the lab. We had, you know, you'd go and type and the thing would come back and you had to tell whether it was a man or a woman. And the, one of the, one man came up with a question that he could ask, which was always a dead giveaway of whether the other person was really a man or a woman. You know, what he would ask them, did you have green plastic toy soldiers as a kid? Yeah, what'd you do with them? And a woman trying to be a man would say, oh, I lined them up. We had wars, we had battles. And the man just being a man would say, I stomped on them, I burned them. Right? So, you know, that's what the Turing test, the Turing test with computers has become. What's the trick question? What's the, that's why it's sort of devolved into this. Nevertheless, conversation not formulated as a test is a pretty, it's a fascinatingly challenging dance. That's a really hard problem. To me, conversation when non poses a test is a more intuitive illustration how far away we are from solving intelligence than like computer vision. It's hard, computer vision is harder for me to pull apart, but with language, with conversation, you could see- No, because language is so human. We don't- It's so human. We can so clearly see it. Shit, you mentioned something I was gonna go off on. Okay. I mean, I have to ask you, because you were the head of CSAIL, AI lab for a long time. You're, I don't know, to me, when I came to MIT, you're like one of the greats at MIT. So what was that time like? And plus you, I don't know, friends with, but you knew Minsky and all the folks there, all the legendary AI people of which you're one. So what was that time like? What are memories that stand out to you from that time? From your time at MIT, from the AI lab, from the dreams that the AI lab represented to the actual like revolutionary work? Let me tell you first the disappointment in myself. You know, as I've been researching this book and so many of the players, you know, were active in the 50s and 60s, I knew many of them when they're older. And I didn't ask them all the questions now I wish I had asked. I'd sit with them at our Thursday lunches, which we had a faculty lunch. And I didn't ask them so many questions that now I wish I had. Can I ask you that question? Because you wrote that. You wrote that you were fortunate to know and rub shoulders with many of the greats, those who founded AI, robotics and computer science and the World Wide Web. And you wrote that your big regret nowadays is that often I have questions for those who have passed on. Yeah. And I didn't think to ask them any of these questions. Right. Even as I saw them and said hello to them on a daily basis. So maybe also another question I wanna ask, if you could talk to them today, what question would you ask? What questions would you ask? Oh, well, Rick Leiter. I would ask him, you know, he had the vision for humans and computers working together. And he really founded that at DARPA. And he gave the money to MIT, which started Project Mac in 1963. And I would have talked to him about what the successes were, what the failures were, what he saw as progress, et cetera. I would have asked him more questions about that. Because now I could use it in my book. But I think it's lost. It's lost forever. A lot of the motivations are lost. I should have asked Marvin why he and Seymour Pappert came down so hard on neural networks in 1968 in their book, Perceptrons. Because Marvin's PhD thesis was on neural networks. How do you make sense of that? That book destroyed the field. He probably, do you think he knew the effect that book would have? All the theorems are negative theorems. Yeah. So, yeah. That's just the way of, that's the way of life. But still, it's kind of tragic that he was both the proponent and the destroyer of neural networks. Yeah. Is there other memories stand out from the robotics and the AI work at MIT? Well, yeah, but you gotta be more specific. Well, I mean, like it's such a magical place. I mean, to me, it's a little bit also heartbreaking that with Google and Facebook, like DeepMind and so on, so much of the talent doesn't stay necessarily for prolonged periods of time in these universities. Oh yeah, I mean, some of the companies are more guilty than others of paying fabulous salaries to some of the highest producers. And then just, you never hear from them again. They're not allowed to give public talks. They're sort of locked away. And it's sort of like collecting, collecting Hollywood stars or something. And they're not allowed to make movies anymore. I own them. Yeah, that's tragic. There's an openness to the university setting where you do research, to both in the space of ideas and space like publication, all those kinds of things. Yeah, and there's the publication and all that. And often, although these places say they publish, there's pressure. But I think for instance, NetNet, I think Google buying those eight or nine robotics company was bad for the field because it locked those people away. They didn't have to make the company succeed anymore, locked them away for years, and then sort of all threaded away. Yeah. So. Do you have hope for MIT? For MIT? Yeah, why shouldn't I? Well, I could be harsh and say that I'm not sure I would say MIT is leading the world in AI, or even Stanford or Berkeley. I would say DeepMind, Google AI, Facebook AI. I would take a slightly different approach, a different answer. I'll come back to Facebook in a minute. But I think those other places are following a dream of one of the founders, and I'm not sure that it's well-founded, the dream, and I'm not sure that it's going to have the impact that he believes it is. You're talking about Facebook and Google and so on. I'm talking about Google. Google. But the thing is, those research labs aren't, there's the big dream. And I'm usually a fan of, no matter what the dream is, a big dream is a unifier, because what happens is you have a lot of bright minds working together on a dream. What results is a lot of adjacent ideas. I mean, this is how so much progress is made. Yeah, so I'm not saying they're actually leading. I'm not saying that the universities are leading, but I don't think those companies are leading in general, because they're, we saw this incredible spike in attendees at NeurIPS. And as I said in my January 1st review this year for 2020, 2020 will not be remembered as a watershed year for machine learning or AI. There was nothing surprising happened anyway, unlike when deep learning hit ImageNet. That was a shake. And there's a lot more people writing papers, but the papers are fundamentally boring and uninteresting. Incremental work. Yeah. Is there particular memories you have with Minsky or somebody else at MIT that stand out? Funny stories. I mean, unfortunately, he's another one that's passed away. You've known some of the biggest minds in AI. Yeah, and they did amazing things, and sometimes they were grumpy. Well, he was interesting, because he was very grumpy, but that was, I remember him saying in an interview that the key to success or to keep being productive is to hate everything you've ever done in the past. Maybe that explains the Perceptron book. There it was. He told you exactly. But he, meaning like, just like, I mean, maybe that's the way to not treat yourself too seriously, just always be moving forward. That was his idea. I mean, that crankiness, I mean, there's a... Yeah, so let me tell you what really, you know, the joy memories are about having access to technology before anyone else has seen it. So, you know, I got to Stanford in 1977, and we had, you know, we had terminals that could show live video on them, digital sound system. We had a Xerox graphics printer. We could print. It wasn't, you know, it wasn't like a typewriter ball hitting characters. It could print arbitrary things, only in, you know, one bit, you know, black or white, but you could, arbitrary pictures. This was science fiction sort of stuff at MIT. The Lisp machines, which, you know, they were the first personal computers, and, you know, they cost $100,000 each, and I could, you know, I got there early enough in the day, I got one for the day. Couldn't stand up, had to keep working. Yeah. So having that, like, direct glimpse into the future. Yeah, and, you know, I've had email every day since 1977, and, you know, the host field was only eight bits, you know, not many places, but I could send email to other people at a few places. So that was pretty exciting to be in that world so different from what the rest of the world knew. Let me ask you, I'll probably edit this out, but just in case you have a story. I'm hanging out with Don Knuth for a while tomorrow. Did you ever get a chance, it's such a different world than yours. He's a very kind of theoretical computer science, the puzzle of computer science and mathematics, and you're so much about the magic of robotics, like the practice of it. You mentioned him earlier for like, not, you know, about computation. Did your worlds cross? They did in a, you know, I know him now, we talk, but let me tell you my Donald Knuth story. So, you know, besides, you know, analysis of algorithms, he's well known for writing tech, which is in LaTeX, which is the academic publishing system. So he did that at the AI lab, and he would do it, he would work overnight at the AI lab. And one day, one night, the mainframe computer went down, and a guy named Robert Poole was there. He later did his PhD at the Media Lab at MIT, and he was an engineer. And so he and I, you know, tracked down what were the problem was. It was one of this big refrigerator size or washing machine size disk drives had failed, and that's what brought the whole system down. So we got panels pulled off, and we're pulling, you know, circuit cards out. And Donald Knuth, who's a really tall guy, walks in and he's looking down and says, when will it be fixed? Because he wanted to get back to writing his tech system. We're like, it's Donald Knuth. And so we figured out, you know, it was a particular chip, 7400 series chip, which was socketed. We popped it out, we put a replacement in, put it back in, smoke comes out, because we put it in backwards, because we were so nervous that Donald Knuth was standing over us. Anyway, we eventually got it fixed and got the mainframe running again. So that was your little, when was that again? Well, that must have been before October 79, because we moved out of that building then. So sometime, probably 78, sometime early 79. Yeah, all those figures are just fascinating. All the people who have passed through MIT is really fascinating. Is there a, let me ask you to put on your big wise man hat. Is there advice that you can give to young people today, whether in high school or college, who are thinking about their career, who are thinking about life, how to live a life they're proud of, a successful life? Yeah, so many people ask me for advice and have asked for, and I talk to a lot of people all the time. And there is no one way. You know, there's a lot of pressure to produce papers that will be acceptable and be published. Maybe I come from an age where I could be a rebel against that and still succeed. Maybe it's harder today. But I think it's important not to get too caught up with what everyone else is doing. And if you, well, it depends on what you want in life. If you want to have real impact, you have to be ready to fail a lot of times. So you have to make a lot of unsafe decisions. And the only way to make that work is to keep doing it for a long time. And then one of them will be work out. And so that will make something successful. Or not. Or you just may end up not having a lousy career. I mean, it's certainly possible. Taking the risk is the thing. Yeah, so, but there's no way to make all safe decisions and actually really contribute. Do you think about your death, about your mortality? I gotta say when COVID hit, I did. Because in the early days, we didn't know how bad it was gonna be. And that made me work on my book harder for a while. But then I'd started this company and now I'm doing more than full-time at the company, so the book's on hold. But I do wanna finish this book. When you think about it, are you afraid of it? I'm afraid of dribbling. You know, of losing it. The details of, okay. Yeah, yeah. But the fact that the ride ends? I've known that for a long time. Yeah, but there's knowing and knowing. It's such a, it really sucks. It feels a lot closer. So in my blog with my predictions, my sort of pushback against that was I said, I'm gonna review these every year for 32 years. And that puts me into my mid-90s. So it was my- That puts the whole, every time you write the blog posts, you're getting closer and closer to your own prediction. That's true. Of your death. Yeah. What do you hope your legacy is? You're one of the greatest roboticist AI researchers of all time. What I hope is that I actually finish writing this book and that there's one person who reads it and sees something about changing the way they're thinking. And that leads to the next big. And then there'll be on a podcast 100 years from now saying I once read that book. And that changed everything. What do you think is the meaning of life? This whole thing, the existence, all the hurried things we do on this planet? What do you think is the meaning of it all? Well, I think we're all really bad at it. Life or finding meaning or both? Yeah, we get caught up in the, it's easier to do the stuff that's immediate and not do the stuff that's not immediate. The big picture, we're bad at. Yeah. Do you have a sense of what that big picture is? Like why? You ever look up to the stars and ask, why the hell are we here? You know, my atheism tells me it's just random, but I wanna understand the way random, and that's what I talk about in this book, how order comes from disorder. But it kind of sprung up, like most of the whole thing is random, but this little pocket of complexity they will call earth, that like, why the hell does that happen? And what we don't know is how common those pockets of complexity are or how often, because they may not last forever. Which is more exciting slash sad to you, if we're alone or if there's infinite number of- Oh, I think it's impossible for me to believe that we're alone. That would just be too horrible, too cruel. Could be like the sad thing, it could be like a graveyard of intelligent civilizations. Oh, everywhere, yeah. That may be the most likely outcome. And for us too. Yeah, exactly. And all of this will be forgotten. Yeah. Including all the robots you build, everything forgotten. Well, on average, everyone has been forgotten in history, right? Yeah. Most people are not remembered, beyond the generation or two. I mean, yeah, well, not just on average, basically. Very close to 100% of people who have ever lived are forgotten. Yeah, I mean- In the long arc of time. I don't know anyone alive who remembers my great grandparents, because we didn't meet them. Still, this life is pretty fun somehow. Yeah. Even the immense absurdity and at times meaninglessness of it all. It's pretty fun. And for me, one of the most fun things is robots, and I've looked up to your work, I've looked up to you for a long time. That's right, God. Rod, it's an honor that you would spend your valuable time with me today, talking, it was an amazing conversation. Thank you so much for being here. No, thanks for talking with me. I've enjoyed it. Thanks for listening to this conversation with Rodney Brooks. To support this podcast, please check out our sponsors in the description. And now, let me leave you with the three laws of robotics from Isaac Asimov. One, a robot may not injure a human being or through inaction, allow a human being to come to harm. Two, a robot must obey the orders given to it by human beings, except when such orders would conflict with the first law. And three, a robot must protect its own existence, as long as such protection does not conflict with the first or the second laws. Thank you for listening. I hope to see you next time.

https://youtu.be/nre0QT9LN6w

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Dan Gable: Olympic Wrestling, Mental Toughness & the Making of Champions | Lex Fridman Podcast #152

The following is a conversation with Dan Gable from two years ago. I did not previously publish this conversation as part of this podcast, but as a separate thing, and as a result, it did not receive many listens. Let me be honest and say that, while I usually don't care about how many listens or views something gets, in this one case, I feel like I failed one of my heroes. I feel I didn't properly introduce a truly special human being to an audience that might find him as inspiring as I did. Dan Gable is one of the greatest Olympic athletes of all time. Bigger than records and medals, to many like myself, he's a symbol of guts, spirit, mental toughness, and relentless hard work. As a wrestler, he was undefeated in high school, undefeated in college until his very last match, and having lost that match, he found another level and became a world champion and an Olympic champion. And most importantly, he did so perfectly, dominating his opponents. He did not surrender a single point at the 1972 Olympic Games. As a coach, he led the Iowa Hawkeyes to 15 national titles and 25 consecutive Big Ten championships. He coached 152 All-Americans, 45 national champions, 106 Big Ten champions, and 12 Olympians, including eight medalists. He's the author of several books, including A Wrestling Life 1 and 2, and Coaching Wrestling Successfully. Quick mention of our sponsors, Trial Labs, a machine learning company, ExpressVPN, Grammarly Writing Helper Tool, and SimpliSafe Home Security. So the choice is AI, privacy, grammar, or safety. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. As a side note, let me say that I spent a few days in Iowa and got to attend a wrestling duel meet in the historic Carver Hawkeye Arena. Part of me wanted to stay in Iowa forever, to drill takedowns, to start a family, to live life simply. Wrestling is one of the pure sports, both beautiful and brutal, where both mental toughness and technical mastery of the highest form are rewarded with victory, and everything else is punished with defeat. And every such loss weighs heavy in the minds of anyone who has ever stepped on the wrestling mat, including myself. The same is true for one of the greatest wrestlers in history of the sport, the man who graciously welcomed me into his home for this conversation, the legend, Dan Gable. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter, Alex Friedman. And now, here's my conversation with Dan Gable. You're persistent, and I love that, because you've been trying to get me on this podcast for a long time. And until I saw you on another podcast, and you said you were Russian, did I call you back. Then it was over. Because Russia, to me, you know, is leading the world in wrestling almost every year. What's the difference between American wrestling and Russian wrestling? You showed me this painting. Well, it's MIT, it's science. It's science. You know, and they really study the sport, they're really good technically, they're really good in strategy, they don't really push, like, the real toughness, they don't push, like, conditioning. And so Americans, we need what they have, Russians need what we have. And when you get the two together, and for me, why I could beat the Russians is because I went their way a little bit. But I kept my toughness. But you're known, you're known for your toughness. Yeah, but I wasn't known for my art. I wasn't known for my science. So when did you become a bit of an artist? It took a loss. The Larry Owens loss. Most people thought I was already an artist just because I won 181 straight matches. Dominance, yeah. In seven years. And not just winning, but, you know, kind of punishing people. Yes. And from that point of view, yeah, I might have been pretty good, but I had a long ways to go yet. And I didn't really realize that, or I should say, I didn't really know how to get it out of me until I had a loss. And then I realized I got to buckle down, learn some of that science, become more of an artist. How do you become an artist? So that's the Russian way has this drilling technique, thousands of reps. How do you think you work on the science, the art part? You got to study the best in the world. I think Dave Schultz was our guy in America that probably showed us that being artistic, you needed that. And he studied it. He went over there as a high schooler and wrestled in some major tournaments over there. And he saw their ways. He used that Russian science, and then he was already an American, and he saw how I trained athletes. He saw what I did in the Olympics. He saw what other people, how we held up, and he applied that as well. But I'd have to say he's more the artistic type. He was more of a Russian than an American when it came to wrestling. You've coached 45 national champions, 106 Big Ten champions, and eight Olympic medalists, which is incredible. What is a common thread between them, and what are maybe some of the fundamental differences? I think the common thread is that they all had one of those two avenues that we talked already, and because we intertwined them. So in a Russian wrestling room, they got the same people. Most of the time in an American wrestling room, we had the same people. But when I was out recruiting, at first I recruited just attitude. But I needed more than that. I needed some genetics in that wrestling room to actually, that hard work people, they could look and see, wow, that execution, that's unbelievable. But yet I can beat that guy after the first minute. So you think the art, the technique is genetics, you're born with it. You think it's not something- I think your pop and your ability to move- Timing. And timing and your quickness and your strength. The Russians, they usually picked out the people that can go into that sport. That was the old-fashioned sports school. But it's mostly like when you walk into a Russian wrestling room, you see them hitting skills, techniques. You don't see them banging against each other that much. But then when practice is over, you might not see a bunch of sprints. You might see them walk over to the ropes, and they drop down from the ceiling, and they'll jump up and climb a rope. Boom, boom, boom. And then they come down, and then they don't jump right back on. They have three or four other guys go, and then they jump back on. Whereas I probably made my guys climb them, get right back down, climb them right back again. But I also realized that I had to have a mix of that. What was the role? What was your role? I mean, those guys looked up and Dan Gable, and what was the role in helping these athletes become their best, these national champions? Well, you had to first of all prove that you knew what you were doing. In terms of technique or in terms of- Everything. Everything. You had to be the first guy there and the last guy to leave, and you had to be the most dedicated guy, even though they were the ones just trying to win the championships. You had to prove that you were going to work just as hard as they were as a coach. And what does that look like? So you can see it when you see it? Well, you're there ahead of them, and you're there after they leave. It's that simple. I'm picking up after them, and you're analyzing them. You outwork them. You outwork them, and you outthink them. And so, you use that type of strategy. And over time, when you prove it works, because some of my kids that were the best kids in the world really shouldn't have been a wrestler. I mean, they weren't very coordinated. Yeah. But they worked so hard, they developed themselves. What was your role in that process? I mean, that means pushing kids to their limit. If you're not- Yeah, but you can't push kids to their limit. And even when you push them to their limit, that's not their limit, because their limit's above and beyond that. I mean, yeah, coaches sometimes accidentally don't- they lose kids. Yeah. Because of the heat, because of hard work and all that. And you gotta know when to back off. You gotta read your athletes. And by that, I mean, you gotta know them pretty well. Every once in a while, you make a little bit of a mistake, but if you don't react right on that mistake before it gets too far, then it's gonna be a casualty. And I don't mean somebody dying, necessarily, but maybe something that could turn them off, or maybe something that could run them away, or maybe something that, wow, that was close. Maybe shouldn't have pushed them that far. So you really have to be very educated. And it's not just what you know, it's what you know about them. And I'm not talking about the team. I'm talking about each guy on the team. Individuals, yeah. Yeah, each person on the team. And you know it how? You see it in their eyes? You know it how? Because you're the first one there, and you're the last one to leave, and you sit in the environment with them. You're there in the morning for practice, sometimes you're there in the afternoon for two or three hours. After practice, you might have a hot room, or you might have a sauna, or a steam, or a whirlpool, and you get in there with them, and you listen. You know, you're not just feeding out information. You do that, but you're taking in a lot of that too. And I'm telling you, when you get in an atmosphere that they're relaxed, and they feel comfortable, it's like a massage. And that's after practice in one of those areas that people are around you. You learn a lot. I mean, you got a lot to learn as a coach. And when you get in that atmosphere, when all of a sudden you feel like very comfortable, words start flowing. And when those words flow, you take them in as a coach, and there's something probably going to be said that you can do and act upon that's going to help certain situations. I've saved a couple of kids' lives for sure that were on the brink. You know, sometimes performance is at such a high level in a high level atmosphere that life and death is actually involved. And I don't mean pushing a kid to where he just dies, but I mean, he might feel himself as a failure. He might go home and take his own life. Yeah, I mean, but that's part of it. You're putting so much heart, so much blood and heart and sweat, and your whole meaning of life becomes winning. And sometimes it's so hard to lose within that context. So if in your, I think, the first wrestling life, you wrote about Chad Zapato, who lost, I mean, an incredible wrestler, but lost in three finals in the Nationals, and has this tattoo has this tattoo of a hawk clawing out the human heart. Yeah. So what lessons, is there any lessons from the incredible wrestling he's done, but also the incredible suffering that he went through on himself? Yeah, again, you like that word suffering, which is okay. Okay. No, no, no, no, no, keep it, keep it, because it fits right in where I want. Yeah. I have to turn that suffering around to where he makes and feels good about himself, or better, does not feel perfect, because he did lose. Yeah. You know? And so, but you have to actually get him to realize that, yeah, he's still unique. Compared to the walk of the earth, he was unbelievably unique, right at the top, just a little bit short of, but because it was, you know, he felt the suffering, you now have to go about and change that and put it into goodwill some way. And because he's, you really have a lot of goodwill, you can do a lot of goodwill. And so, and it's not easy. It took him probably years, years of tattooing, years of covering the tattoos. And, you know, he told me he moved to Cal, I go, why are you moving to California? Because he was here for a couple of years after his wrestling was done, because he had a good job around here. And he was, I thought he was doing a good job, but he just, he said, I had to escape. Yeah, same as the cover tattoo. I had a wrestling terminology, I have to get, and I hate to say this, I hate to say this. I go, where are you going? He said, I'm going to go to California. And I go, is there any reason why you're going to California? He says, that's where everybody goes to hide. Ha. But I said, I think you're wrong there, but, you know, I think what will determine your life will be what you do from now on, you know, and if you can find, and he's actually turned it around. I mean, it's scary. He's actually turned it around. You have to discover that yourself. Exactly, and he went someplace that he thought he could fit into, and I think he found a place. He thought he could fit into, and I think he did, and I think he's got a good job, and he's helping people, and he covered that tattoo with feathers, another tattoo. Well, in the end, it's a beautiful story. Yeah, it is, it really is. Suffering and overcoming. Yeah, and he's not done yet. He's not done yet. No, he's not done. He's got a lot more to do. So you mentioned Roger Bannister, again, I think in your first book, and somebody you looked up to, that's the man who broke the four-minute mile, right? When everybody said it was impossible, everyone thought it was impossible. Oh, they thought you would die. You would die. It's not humanly possible. Yeah. So what... Well, you've done your homework. For what, the book, or what? Oh, I don't know, for me. You've done your homework. Yeah, I know, but yeah. Sent here by Putin to do research, yeah. So what lesson do you take from that story for yourself? The impossible, trying to accomplish the impossible. Well, the impossible is possible. It's just that simple. Time changes things. I mean, if you looked at where the mile time is right now, compared to that four-minute mile, which when it was broke by a couple tenths, or three or four tenths, it's now broke by another 20 seconds. Right, yeah. I mean... By several hundred people, yeah. Yeah, I mean, by tons of people. And it's pretty much common knowledge that you got to run a four-minute mile if you're going to go somewhere now, or below if you're going to win events at major level, you got to be able to do that. And so you can take that and you can look at what, in time history, has as its record performance, and you can realize that, ah, that record performance, it's going to change. Yeah. And they don't take into all the factors of knowledge. They don't take in all the factors of better shoes. They don't take in all the factors of better understanding of nutrition. I mean, it's like me as an athlete. I went to practice every day in high school for at least my sophomore and my junior and part of my senior year, and all of a sudden, a new rule came up. It said, the rule said, before that, it said, at least most of the coaches, we don't want you drinking water at practice. Ha ha ha, yeah. And, okay, why? Because you got to toughen you up. That's a weakness, water. And so we would go through practice. I mean, and you're sweating, and then you're sweating so much that you're almost out of sweat. Yeah. And so you're mostly, at the end of practice, you're not even wrestling. Excuse me. You're sitting against a wall. Yeah. Because you're tired. So then all of a sudden, they say, okay, go and drink water during practice. Drink Gatorade during practice. And all of a sudden, at the end of practice, we're still out there competing. And so I look at my career for two and a half years where I, and junior high too, so I got another three years where I didn't really, wasn't able to push as good as I could because I just was probably under. Under hydrated. Yeah. Yeah. But at the individual level, in terms of the impossible, when did you first believe the thing that maybe probably people would laugh at you about is that you would be an Olympic champion? Well, I always visualized me being the best. You believed it in the very beginning. Forever. Forever. Yeah, I was, because I was, I don't know if you'd call it a dreamer or somebody that, I was just involved with competitive sports at the YMCA from age five. Did you tell people that dream that you're going to be Olympic champion one day? I. You're going to be the best in the world? I think they knew. And the only reason why they knew, because there was something a little different about this guy. He was. He's not going to stop. Well, he was out in the yard. Yeah. And he was swinging baseball bats. Yeah. You know, at six, at seven and eight at nine and 10, and he was swinging baseball bats. So much right-handed and so much left-handed with nobody even there throwing the ball. That all of a sudden when they walk by, all of a sudden the grass was down to dirt on both sides. So it's like, they saw me out in the yard playing by myself sports, or, you know, or you get the neighborhood kids and you play a lot. But if they weren't there, you know, if you walked in my front room, I was hiking a ball like I was the quarterback and I was running not and running through the, through the furniture, you know, that type stuff. So, you know, who, who saw this guy mostly was probably the parents and the coaches at the YMCA level, the junior high level, they saw this guy come first and, and end up last. But I wasn't that great. I wasn't the fastest guy at that time. And I wasn't the strongest guy. You know, actually, before I went to the Olympics, when they tested me, they tested everybody. And I probably came back with one of the highest scores, but it was, it was not like the highest person on this and this and that. I was all high across the board, straight across the board high on every one of them. But there was always people that were higher than me. Genetics. But then they would go down. Then they would test on something else and go back up. Mine stayed high all across the board. And so I, you know, I really didn't have too many flaws, but I didn't have any things that also said that you were going to be unscored upon at the Olympic Games. Right. So take me through that day, if you could. 1972, when you were going for the 68 kilogram freestyle wrestling gold, you scored 57 points, if I'm correct, and had zero points scored on you. 57, zero. So maybe take me through almost the details. What was your routine? What was your process? What was going through your mind, your thoughts of that day? Yeah, first of all, it was quite a day because we weighed in every day at that time. And that, yeah, we weighed in two hours before the start of the competition. And so that didn't mean that you weighed in two hours before you wrestled because you didn't know whether you're going to wrestle right away or later on. In fact, in that day, I don't think I wrestled until later on in the evening. So I had all day to recover, but I didn't really need it anyway because, you know, I wasn't really pulling a whole lot of weight. But just, it was just interesting. But what was in your mind? What were you thinking? Were you nervous? Were you... I was confident. I was confident. You knew you were going to win the gold? Yeah, I knew I was going to win. But in reality, I'm not, I didn't know it from a cocky point of view. I only knew it because for the last one, two, three and a half years, I had been going to practice and I'd been winning every practice. You felt good. And I hardly ever lose a takedown. And if I lost, if somebody scored on me, it was like when I went to bed, I couldn't sleep until I figured it out. Or if I didn't figure it out, I would fall asleep and I would be woke, I would wake up with the answer of what I needed, why I got scored upon. So maybe now that you've won the gold, can you tell me in the practice room, if somebody took you down, how do you take Dan Gable down in the practice room? Timing, technique? Very difficult, but somebody could, because they were going for one move. All I wanted was one move. Whereas, you know, if you can arrest somebody, arrest them the whole practice or half a practice for at least 10, 15 minutes, and they were maybe going to score if they could work it in their mind. But they knew that was going to be their victory. So in the practice room, maybe you can educate me at that, when you're going for the Olympic gold, you didn't want to allow any takedowns. So there's no such thing as working on some kind of weird position, a weak point or something. It's important to not let down, take down. It's kind of like what we were saying before. If something happened and somebody scored on me in a certain way, I would go over that situation, over that situation, over it again. And I would come up with an answer. And then I would actually test it. Maybe I wouldn't go right back the next day, because I didn't want the guy to, you know, to not have some, I didn't want him to think that I was thinking about it all night. I didn't tell him. But maybe three days later when he wrestled again, I actually had it figured out because it, he wasn't able to. Or even if I was in on a take, an offensive move, and I got stopped and didn't score, you know, I had to go back and filter that. But it wasn't something that usually I couldn't solve. I could usually solve it. Let's go back to the Olympic Games. So I get up in the Olympic, in the morning, and I'm not sure when the weigh-ins were, but I think I was probably a pound over. You know, and that's about a half a kilo, 1.1 pounds is a kilo, because we were in kilograms. So what do you do with that pound? You are off or? No, I just went over to the, they had a sauna there, and I got in the sauna. And the funny thing was, the morning of the finals, there was another athlete in the sauna. American or? No, it was a European. I don't remember where she was from. Not a Russian. Well, you know what? I kind of think it was a plot. Because it was a girl. Interesting. And she didn't have her top on. Oh, wow. And that was pretty common. And so, you know, it's kind of interesting. You think back about it, because there's some funny things that go on behind the scenes in Olympic Games, in World Games, any time when you have country against country. And so there's some crazy stuff that goes on. Did any of it affect you? Did you, was there any? Well, I almost stayed too long in the sun. You lost a little bit over a pound. I lost a little more than a pound. Yeah. But it didn't really bother me, because I wasn't like cutting a lot of weight. So your match against the Russian, the... Azhulayev? Yeah, Azhulayev. He went on to be a two-time world champion, a silver medalist as well. I mean, this is an incredible wrestler. So what was going through your mind before stepping on the mat with that guy? You've beaten a bunch of wrestlers, haven't had a point scored on you, and you're stepping on the mat against the Russian, who you said was, really, they picked, the Soviets picked to beat you. Right, and I know why they picked him, because he had a great attitude. So he wasn't just the typical artist. He was a good artist. He hooked elbows like Azhulayev, and he's from that area of the world. Where they have some of those types of moves, but he was a goer. But by cutting him down a weight, he lost some of that go. And I don't know if... That's a process you gotta go about scientifically. Yeah. And so if you don't do it as an American, it can really hurt your performance. If you don't do it as a Russian, it can hurt your performance. And they already didn't really do that a lot, where you usually wrestle the weight where it was more like your weight. And so by cutting him down, it maybe slowed his belief down a little bit. You saw it in him. The spirit was a little bit gone when you were facing him. Yeah, but then he came back and he won the rest of the matches, and he was in the round robin, and he was able to go to the finals. But he had lost another match, actually, in the round robin against the Japanese. So I think I had already gained enough of artistic being able to finish a match. Once I lost my match in college for the last two years, I took on some of that artistic work. And I think that he was already hoping to win, but he was hoping to win by a long ways, because he had to pin me or beat me by eight points to be able to win the gold. And that wasn't going to happen. The chances of pin is pretty good. Is it hard to pin Dan Gable versus take down? Have you taken risks where you could pay for them? I can't remember too many that I took that would actually put me in a danger position. I've taken risks, but the risks were so scientifically, technically correct, that I wouldn't land in that danger zone. It's like if I'm going to lock up and throw you, I'm not going to throw you to my own back and roll you through. I'm going to turn in the air. So you were scientific about it. Yeah, exactly. I learned the hard way. Early on, there was moves from collegiate wrestling that you did that exposed your shoulders, which it cost me in some early freestyle matches against great wrestlers. But I would go back to my collegiate escaping type moves to where I hit a grammy roll where you expose your shoulders and you lose two points every time. But you learn that that's not the system. But if you hadn't wrestled much, you would get exposed under maybe a desperate situation. You would hit it. So you won the gold. How did it feel? I think the question would be, how would it feel if you lost the gold for me? Because I already went through that once. Not at that highest level, but the National Collegiate Championship level, my senior year. The Larry Owings loss. The Larry Owings, yeah. And that didn't set well. Were you afraid of that happening again at the Olympic level? Was that even a thought? No, I really wasn't. But it was why I changed my philosophy of training and added to the scientific artist type. And if I had won that match, even though I wouldn't have felt good about it, even though I squeaked it out, I wasn't feeling good about that match. It would have affected me a little bit. But if I'd have won it, I would have got over it. I mean, I'm not over it now. Yeah. I mean, I don't know why I was doing this kind of stuff right before my match. Yes. By that, I mean this kind of stuff. Interviews. Oh, yeah. Journalists. Yeah, and I really wasn't a good talker. I mean, me and you are talking pretty good right now, except for I got a little cold. But I don't think I could say two words hardly then. And they took takes. White World of Sports said, hey, just we want you to be the introduction for our next week's show. Yeah. So just say, hey, I'm Dan Gable. Come watch me as I finish my career undefeated 182 and all. That's what they want me to say. Everybody assumed you'd be undefeated. And I said it. I had to take it 22 times. And the last two or three times, they wrote it out. And I read it. And still, it wasn't like I just said it. I was reading it like, hi, I'm Dan Gable. Come, come on. You know, that type of stuff. Yeah. And he finally just closed the book and said, yeah, that's good enough. But I turned, and it was my time to wrestle. Yeah. And so you just learn that. And for me, it was great coaching experience, because that's what I turned into. I coached for longer than I wrestled. Yes. And I put out a lot of champions. But you learn through mistakes that even in your own career that you had made, it's an ever learning process. It's an ever learning process. Have you ever been afraid on the mat? Does fear have any role, do you think, for a wrestler? Or it must be out of control? Well, I'm sure fear is out there. And I'm sure that was to my advantage almost every time. I'm sure in my Olympic finals, I was really, he had these doubts. He probably had these doubts. And that gives me the edge. And I don't know if I really ever had fear. But obviously, there was points and times where I didn't perform as well. Not many, but a few. And if I look back at it, I don't think it was that American, raw, raw, raw stuff. I think it was probably the fear of not being an artist as much. Maybe this guy might be better than me scientifically. And you're a scientist. I think that got to me more than anything else. I said early on that I want to eliminate ever having to worry about getting tired in a match. So I kind of eliminated that. So I got rid of that point. And I do think that in wrestling, that is one of the fears that a lot of wrestlers have. Actually, how they feel during the match. And are they going to get tired? And is it going to affect my performance? And as a coach, that really was one of the things I tried to eliminate on all my athletes. So there wasn't that fear factor. But that fear factor would be put upon my opponent, which would give me an edge. But that's not what I needed as much. I needed to just focus, make sure that I was doing the right things. And I needed my team to be focused. So I made sure that for my mistakes as an athlete, or even as a coach sometimes, that I didn't repeat them. I didn't repeat them. And if you make a mistake once and then you can repeat it, then it's like you didn't learn anything. Your goal throughout your wrestling career, as you've beautifully put, was to work so hard that you pass out on the mat, right? That you would be carried off the mat. So you never did successfully. And that's one of the ways you failed in your career is you've never worked so hard that you've passed out. Have you ever come close? Do you remember a time that you've come close that you've been pushed to the limit? You've been pushed to the limits of exhaustion? You know, the question is really a good question about that pushing to you collapse. Yeah. Because I don't, as a coach today, I don't think I could, if I said that to my athletes, I don't know, I could get in trouble. Because, you know, it's like... It's understood, isn't it? By the athletes? Yeah, they understand it. But the outside might not understand it. Because it's almost like, what do you mean? You push them to the point where they go collapse. That means they might die or something might happen to them. And, you know, that's dangerous. That's dangerous. We can't have our kid in that type of atmosphere. But it's something that's highly unlikely that's going to happen. But I'm going to tell you, there's many times in a practice where I had pushed myself to all of a sudden the whistle blew or it was time to stop. And when I got up off the mat or wherever I was at, and I needed water, I needed fresh air, because you're usually in a fairly small room with a lot of guys, that the heat rises and it's hard to breathe. And that I can remember, and I stayed a lot of times not by the door, at the far end of the room. I can remember walking from the far end of the room to that door. And I can remember, am I going to make it the next step? Am I going to make it the next step? Yeah. I need air. I need water. I need oxygen. I need to get out of here. It didn't happen often, but I can recount four or five times in my career that I pushed myself to that level where I thought I was going to maybe go out, but every step I was dizzy. But once I got to that door, I was able to open it and go out and grab the water and get the cold water in my face. And so, no, I never really was able to do that. And I think the story is in a book where my daughter pushed to collapse, Molly. It made you proud. Oh my gosh. And she didn't win. Yeah. But she pushed to collapse. Yeah. Now, did she suffer because of that? Well, she didn't get to go to the next event because she had to qualify. But I think it probably helped her too, realizing, because she was winning the race and she was beating people she normally never pushed, but she was at a new level. She was at a new level that she had never been before, and she only needed about five feet to finish. And it was just one of those things that I bet there was a lot of learning that she did there. And it probably made her realize that she could be better. But she had to hold up, though. So you mentioned in Wrestling Life that the Brands brothers looked up to Roy Salger, who was known for pushing the limits of physical wrestling, but not getting too rough. So how do you find the line between extreme physical wrestling, but at the same time, not rough wrestling or angry wrestling? So that line between aggression, tough wrestling and anger. Well, I think anger would cause less successful wrestling. I think anger would cause you to make mistakes and actually get out of position, because I think anger is kind of a loss of control. And there can be a furious type of attack. But I think if it crosses the line to anger, then you're going to be vulnerable. And so Royce and the Brands wrestled to the edge, through the edge, but when the whistle blew, they stopped. And there's people that when the whistle blows, they keep going. It's like in a football game, a fight breaks out and it's after the whistle's blown. Well, when the whistle blew, they backed off. They backed off. So that whistle was something that in a match, that kind of gave them the boundaries. But perhaps it could be a little bit of fuel. So in Wrestling Tough, the book that you just got from Mike Chapman, the new edition, talks about Bill Cole, undefeated Northern Iowa wrestler. And how he talked about how my strength, speed, and ability to think were increased tremendously by just sitting apart from the action prior to the match and getting into a state of controlled anger. So can anger... Controlled anger. Controlled. So anger could be fuel as long as it's controlled. Right, exactly. He had that line. One side of the line, you can have an anger for performance, and the other side of the line, if you go beyond that, it's not going to be for performance. It's going to be for not performance, because you're going to lose points. It's a fine line. There's definitely a fine line. You're talking about Roy Seliger. You're talking about Tom Brands. You're talking about Terry Brands. I mean, you got world championship titles there. You got an Olympic championship title there. You got a world silver medalist in Roy Seliger. And when I talk to him about the world silver medalist, he's haunted by that. Because he was actually 20 seconds away from winning when he got beat in the end there. But that's part of the game. And I don't know whether he's okay with it or not, because he says every... After talking about things, he goes, I'm okay with it now. But then he keeps talking about it. So I don't really think he's okay with it. And it's hard for him to actually make amends to himself when you really don't do it. I mean, it's no matter what the situation, even with the Owings loss. Yeah. It still eats at you. I mean, yeah, I'm a world champion. He's not. And he wanted to be. I'm an Olympic champion. He's not. He wanted to be. One of the greatest coaches of all time. Yeah. Yeah. And so he... It's like, why do I keep going back to it? Because you don't get over those things. So Royce really keeps going back to it, even though he says he's fine. But then he realizes he's really not fine, because that's just the nature of the game. And that's why he was able to win national titles and make world teams and stuff like that. You know, even what's interesting about him, he's analyzed all the people that he's wrestled, and a lot of them have won world and Olympic championships. And he's beaten every one of them at one time or another. And he didn't get to that world championship gold or Olympic gold. And that, he says it because they did it. So he's showing people that, I've beaten those guys. Yeah. But apparently he didn't beat him at the right time. And so it's still haunts him. You don't get away from that stuff. Yeah. I mean, it's just like anything in life that's really high. I mean, it doesn't have to be athletics. I mean, you think I'm ever going to get over the murder of my sister? Yeah. And you might not even know that. Let me pause for a second, please. You've talked about it. You've written about it. So I hope it's okay for me to say that your sister, your older sister, on May 31st, 1964, was raped and murdered by a local boy. So the echoes of pain and anger from that tragic day, do they ripple through your life still? Through your wrestling, through your coaching, through the way you, when you wake up in the morning, what is that like? Yeah. It can be very emotional to me under certain circumstances. And it can be the mood I'm in. Right. You know, it can be maybe if I've had a Mountain Dew or maybe if I've had a Gable beer. Yeah. Yeah. Or maybe if you turn the country music up a little bit loud, it can be a little emotional. Yeah. Or maybe if you turn the country music up a little bit loud, you know, emotions come out and everybody has them in their life. It just so happens, you know, what brings it out. And hopefully it's nothing that you do to the extreme point of, to where it brings it out. For me, it's not extreme. I don't have to have any of that, really. I can get emotional. And how did that change you as a man? What it did was realize that I was already pretty well developed because I was only a sophomore, 15 years old in high school. And I had parents that weren't making it. And my parents are a lot older than me. And now that we're down just to me and my parents, and I'm going to be around the house for another two years, and they had just lost a daughter that was the only other sibling, they weren't handling it. They were the ones that were suffering much more than me, even though I always look back upon one area that I wasn't good at, was communication at that time, except inside the wrestling room, outside the wrestling room, because I had been tipped off. And... Tipped off, what do you mean? Well, the neighbor boy said that something to me about my sister just three weeks before that, That's right. that really wasn't normal or practical. And I said nothing to nobody. You don't... Is there a part of you that blames yourself? Yeah, absolutely. Absolutely. But I'm 15 years old and you make mistakes. And you don't really act on everything that happens in your life. But I can tell you how it affected me. And I acted a lot on anything that maybe wasn't even of that consequence. I mean, because I had four daughters and I'm telling you, when they left every time to go somewhere in a car or go out with someplace, I always said something to them. I always said something to them and they would always say, Dad, you said that last night. I don't care. What, like, I love you or like, be careful? I'd say like, don't be driving and drinking or don't be in a car with somebody that's of the same nature or stay out of trouble. Don't go be somewhere where you have... I said, you know how to get out of a car if your car goes into the river? I just, you know, I'm always thinking ahead a little bit, just in case of something did happen. And it goes back to that walk to school with that young man, that when he was talking to me and I just, I took it and I kept it inside me. And once I found out she had been murdered, it took me maybe 25 to 30 minutes. And I told my dad, I think I know who killed her. And he looked at me and he just like, he slapped me actually. He pushed me against the car. He didn't slap me, he pushed me against the car. My mom slaps me. She was the one that slapped me around a little bit. But my dad, he pushed me against the car. What do you mean you might know something about this? I said, Dad, I don't for sure. But, and I would probably all crying, but, and I don't, I doubt if I was crying yet. I've probably cried a lot of tears since, but I just said, Hey, I was walking to school with this neighbor and I never had walked to school with him before. And he was kind of a troubled kid. And he said something about Diane and it wasn't good, but I didn't. He goes, why didn't you say something? I said, I dad, I just boy talk, you know? So, you know, and so he hugged me, he hugged me, he hugged me. And, you know, it was one of these things that it's definitely made me a lot of who I am. Because there's been a lot of choices and I don't, I took the word choice out of my life. And I just like to say, okay, do the right thing. Do the thing that you should do. And so I don't really, it's like, are you going to do this or this? Well, what do you mean? Which one's better? You know? Well, then I, so I don't even have that choice. Yeah, just give me the right way to go. And so not that I've been perfect by any means, but it's made a big difference in my life on how I handle my life. It's probably given me the opportunity to be married for 44 years. It's just given me opportunities to be better in my life. And, you know, I want to thank my sister for that, you know, it's, and I think my family was ready to make a split because of that incident. They were blaming each other. And I think that I was able to help, but more than that, they really liked each other, but they didn't really know it at the time until I got out of the house. Two years later, it probably was going on for a couple of years until I moved on and went to college. Then they found out they really liked each other when they were alone. And it worked out pretty good, but I think them being able to follow me, not just through college and Olympics and worlds, but my coaching. So it's the same, the same success and factor, you know, the excitement and all those things gave them a real purpose. And it gave my four daughters, it gave my wife, you know, a real purpose to be able to be close to all these champions and championships. And now it's like there's a family of 22 and they're all interested in what we're interested in. And it's going good, knock on wood, but, you know, it's something that when all of a sudden you got too much time in your hands and you're not doing and accomplishing much, that things probably, you know, get off, get off track. What do you think is the role of family in wrestling? Can a man do it alone? And if not, where's family most important? You know, you could do it alone, but why would you want to? Yeah. I think the chances of doing alone are much less than the chances of doing it together. I know they say, don't bring your profession home. Sometimes they say that. I never got away from my profession. And, you know, sometimes I, it's like my house right here. So when I'm moving home, I'm not going to have an office because I'm not going to coach anymore, or I'm not going to be an assistant athletic director for a while. That you got to do something that gives you a little bit of a break. Not you necessarily, maybe the person you're living with. And so I don't know if you looked outside there, I got a cabin right out in my backyard. You probably can't see it right there, but. What's in the cabin? That's my house away from my house. It's only 30 feet from my house and it's my office and it's my workout room. It's my, I got a sauna there. It's a bed upstairs if I need it. If I ever get too close and she says, hey, why don't you go sleep in the other house? But, you know, she kicks me out of the bed, but. Get the heck out. It's never happened. Yeah. But I do spend a lot of time out there and it's, you know, you got to have a little distance sometimes, you know, and you got to know your role. And so all of a sudden when you're a guy that's been gone your whole life from eight o'clock in the morning till close to seven, 30 or eight o'clock at night, so 11, 12 hours a day, then all of a sudden you're not gone as much, even though you still work. She's trying to slow me down now. I'm doing not so much like here, what we're doing right now, but it's when I get in the car and drive, I'm doing a lot of work. What we're doing right now, but it's when I get in the car and drive somewhere or fly somewhere, you know, like just last night I just went to bed and I hadn't told her that this guy called me and he wants me to speak for, he want to build another, Wrestling wants to start another wrestlers in business networking out in Delaware because we don't have any colleges in wrestling in Delaware. And so I said, well, you know, I'm glad to do that because that's my life, you know. So, but then all of a sudden I didn't say anything to my wife until all of a sudden this morning and I told her that I might go on the Friday, the 21st of December. Oh no. Well, I said, that's not Christmas. She goes, we're celebrating Christmas that weekend early because a lot of the family can't be here except for that weekend. Yeah. And I said, oh, well, that's not going to work. But I kind of didn't say anything to her at first. And then, well, I'll tell you, she started getting a little emotional. And if I want to stay married for another year, 45 years, then I better tell those people that I got family obligations because, you gotta depends what's most important. I love wrestling. I love wrestling. And I want to start another, help start another wrestlers in business network. But there's more than one Dan Gable out there. Well, maybe not. But there's a lot of people that are maybe even closer and they got big names. I mean, we're doing pretty well right now. I mean, we got first two years ago and we got second this year. And then we got the women's freestyles doing good in wrestling. We got to work a little bit on our Greco yet, but they are working on it. But our men's freestyle team right now are excellent. And the key for them is to get them all on the same page instead of just have new highlights. And by that, I'm saying, you look and see who won this year. Well, the three guys that have never won before won this year. We had three world champions. Our two past world champions didn't win this year. I mean, they did okay. You know, they got medals. Did Burrows win? No, he did not. He got third. Oh, that's right. He got bronze. Yeah. And Sajal, I've got, I mean, Snyder got second. So those two are our main guys. You know, so the three new guys that came through were guys that hadn't won world gold. In fact, two of them had never made a world team before. And so we have three world champions this year, but we needed all five of them to come through to win the championships. And so the key really is getting them all to do the same at the same time, year in and year out, and not just based on, okay, Burrows got beat this year, so he'll win next year. It's got to be every year if you're capable of doing that. And that's what the coaching staff has to do. It's kind of funny that I do have a lot of influence actually on the coaching staffs right now at the USA level because the women's freestyle guy is Terry Steiner, and he wrestled for me, he was a national champion. He's got a twin brother that's at Fresno State. And then Billy Zadig is the freestyle coach, and he wrestled for the Hawkeyes back in the early days, and he was the national champion. So we got a lot of former Gable influence on there. But it's got deep roots in there. In 2013, the International Olympic Committee, IOC, voted wrestling out of the Olympics. So a lot of folks know about this, the absurdity of it, and so on. But in a big picture, you can step back now, it's five years later. What did you learn from that experience? Well, first of all, did it surprise me? Yeah. But did it really surprise me? No. You gotta have people running the organization that are top notch. If you take anything for granted, and you're not the person of authority, somebody can kick you out. And even though we had a lot of authority because we're wrestling, we're one of the first sports in the Olympics ever, and that we think that we're in 180-some countries, and some of the number one countries in the world that are politically strong have the sport, we thought we were okay. But then you gotta look and see who's running the IOC. The IOC, the International Olympic Committee. Yeah. And then you gotta see that in wrestling, we don't have anybody in there. I mean, that shocked me. We've never had anybody on the IOC from wrestling. Yeah. You know why? Because we didn't have to. But yes, that's wrong. You have to. And if you don't have somebody looking out for you right within the structure, then it's pretty easy for people to turn their head. But all it took was the statement, you guys are kicked out of the Olympics. You guys are done. Everybody came together. And then, well, yeah, I mean, it's the first time in history that probably all these competitive people, you know, the people that are running the organization, they're all gonna be kicked out. And then all these other people that were working for their own agenda, turn that agenda to the sport. And so that made a big difference. And we got a lot done. In fact, in America, there was several people that were really out there that we didn't know about until this point in time. And they came aboard, now they're still aboard. That doesn't mean we're doing everything perfect, just because we got voted back in before we even got kicked out, really. That doesn't mean we're by any means safe. We have to do some of the things that I'm talking about, or some of the things that we didn't do before. We can't fall right back into the same mess. Yes. Leadership got changed, and it's better, but it's gotta stay better. But there are things that we could still be doing to make sure that we don't have situations like this happen. I'll tell you, when I first learned about it, I was like, I broke down and wept. Yeah. Again. It's like every once in a while I'll break down and cry about my sister. Yeah. Or I'll break down, I don't know if I cry about losing to Owings, but I probably get more determined. But that's kind of, you have to go back and think about those moments when you heard. When I heard that moment, it just overcame me. It was like 4 o'clock, 4.30 in the morning when I heard about it. And my wife had been up looking at the internet, and she woke me up, and I thought she was joking. But I jumped out of bed really quick when she said that. I knew she was serious. And I started making phone calls right then to find out if it was true. And when I found out it was true, it was just devastating. It was one of these things that, it's a nightmare. But you don't let it happen again. It's that simple. You keep getting stronger. Yeah. And if people haven't read, they should read The Loss of Dan Gable by Ray Thompson, the ESPN article. It kind of, in this very beautiful poetic way, ties together all the losses of Dan Gable, the losing your sister, losing to Larry Owings, losing wrestling from the Olympics, all of these tragedies of various forms. So that's the IOC, there's politics, and you're sort of being very pragmatic. But stepping back, wrestling is one of the oldest forms of combat, period. Dating back, there's cave drawings 15,000 years ago. And if you look at the ancient Olympics, the Greek Olympics, 2,700 years ago, did you ever, when you wrestled or coached, do you now see wrestling in this way, a freestyle and folk style wrestling? The purity of two human beings locked in combat, the roots of that, us as just human beings, this fair struggle between two men or two women? I don't think I ever looked at it as anything but just a combat. And I think there's times that have made me figure out how to make that combat better. There's little markers or little points in time in your life that make you wonder, or I should say determined, to be able to get more out of yourself. And to be able to take it to a new level. And I don't think people can actually feel that way unless you've actually had a lot of accomplishments in anything. I think there's anything out there. I mean, no matter what sport or breaking the four minute mile. I mean, when you broke that, when they broke that, Roger Bannister broke that four minute mile, I can't imagine him breaking it from his best time being 4.30. You know, it's one of these things that along the line there, that he did had some close calls, or he had some coaching that was giving him the opportunity to become a little better. But I think because he was doing well and being very successful, that the opportunity came. And so it's for me, it's like the same thing. I had so much success and so many practices that went well. And so much goodness out of this sport that it gave me the opportunity to really look more finite and look more how I can even make it better. And so it's like, if you look at my library upstairs, I got a library upstairs. And there's a lot of books up there from the family. But if you look at the Gable books up there, I got a lot of Russian technique books. I can't read the book, but I can see the diagrams and I can see the figures. They don't really show it in pictures. They do it in drawings. And so it's like when I was trying to beat the best that is labeled the best because they win the world championships every year since they've been just about involved. And I don't think they got started involved until like the 50s. But it's something, you study the best who's out there, but then you don't focus so much on the best that you can't beat the best. You learn from them, but there's something that they don't have that you can have. Toughness to technique, to the art, to the science. Yeah, all that stuff. And that's why even talking to you and you're sitting over there and you love MIT and you're bragging about it over Harvard, you know, it's true in your eyes and that's great. And it might be. But it's the same type of thing that, you know, there's something that you're probably stealing from Harvard, but you won't give them credit. Well, Dan, in the interest of time, I've read that you're pretty serious. You're pretty seriously into fishing. So what's the biggest fish you ever caught? What are we talking about here? Are we talking about? I don't think I've ever caught a big ocean fish. I'm not, I'm a river lake fisherman. I have fish in the- Bass? Trout? No, probably northern. Okay. I probably caught a northern that weighed 20 some pounds. You know, the fish I like to catch is walleyes. And the reason why I like to catch them, because they're really good eating fish. And the best eating fish are not the real big ones. You know, it's kind of interesting. I got people hunting deer right on my land and they're looking for the big bucks, but they're not the best eaters if you want to eat them, but they're the best trophy. So I do have a couple of trophy walleyes on the wall, but most of the time I throw the big ones back and put them back in there. So I don't know if you know, there's a book by Hemingway called Old Man and the Sea. Heard of it. And Ernest Hemingway. Ernest Hemingway. Yeah. And he, there's an old man that basically catches an 18 footer, but it can't pull it in, doesn't have the strength. So they together spend, well, the sharks eat away at it. I mean, this is very powerful story. I think won him the Nobel prize, but he says, it's better to be lucky. The old man says, better to be lucky, but I would rather be exact that way when luck comes you're ready. So let me ask, what do you think about luck? Do you believe in free will that we have actions that control the direction destination of our life or does luck and some other outside forces really land you where you end up? For me, I'm not about luck, but I do think there is luck is involved, but I think it's mostly created just how lucky you are through preparations and things have, things have happened in my life forever and a lot of good things. And a lot of people could say, Hey, you've been pretty lucky to win all these awards. I don't know if you analyze my life, I don't think it was involved with luck. You know, I think it was more involved with preparation and you know, and again, science had you been smarter, had you understood that you could do some things and be just as lucky, that'd be great. But I'm only as smart as today. So when I was training in my life and me even training people in my life, as of that moment, that's how lucky I am to be able to have whatever is available to me. And that's what you call that a lot of science. So for me, I, I think that, you know, like right now, if I look back, I do a lot of things different just because things are proven differently. Like I give people water during practice and I did, and I would let them change their running wrestling shoes into running shoes to run sprints on the concrete. Or I would actually maybe, maybe I've had a guy climb 12 ropes after practice one after another and then maybe the next day I'd do it again. Uh, you know, I might not make him do it the next day. I might let him recover a little bit more. And you gotta learn, keep adding to your philosophy and your philosophy may have been great at that time, but it's at that time. And what is really important is where you at with this time today. And so there's better ways to do things. Now, if you ever take attitude out of it and just depend on total science, then you know, you're not going to be as, as, uh, you know, I think as I listened to a couple people that are really pretty famous people, uh, one of them was John Irving. He was a writer and he told me, he says, you think I really learned how to be a great writer in a writing school? I said, yeah, I learned a lot there, but really what gave me the ability to stay focused, to work extra hours, to be more disciplined was wrestling practices. That's right. He was a wrestler. Yeah. Yeah. He goes, I go back to that. That's what gave me that chance, you know? And there's a guy in Iowa that, a guy named Norman Borlaug, he, uh, he, he learned, he, he invented a process to feed the underprivileged countries of the world. And he was a wrestler and he said the same thing and he, and he worked extremely hard. And he said, uh, I give a lot of credit to the sport of wrestling. And even though I was, I'm known for this and I got a statue in, in Washington DC because I saved a billion lives plus, uh, I'm going to give wrestling a lot of credit. So, you know, I think some of these MMA stars and some of these guys that maybe weren't wrestlers that had to wrestle, had to fight wrestling guys and stuff missed a little bit there. But I think the ones that did have wrestling probably have a really good chance and can adapt to the other ones. But I think every martial art or every activity is good and you probably can't skip any, but I don't think they're ever going to overlook and say that wrestling's pretty not, or not valuable because it is. However, that doesn't mean you're going to make it. You still got to take the values and apply it, whatever area you're going to be in. And some people forget that. Some people can't get over the highness of getting your arm raised in a wrestling match. And you know what, what's even greater than me getting my arm raised is that I, if I'm a coach or if I was belong with you, that you get your arm raised. And even if you don't get your arm raised, it's what you walk away with and how, and how you learn to handle that as well, because there's going to be some losses, but you don't want many because you don't want to get used to losing. I can tell you that. So it's the hunger for the win. It's the brotherhood, the sisterhood of the wrestling room and it's hard work and science that's going to beat luck at the end of the day. Absolutely. That luck, you know, I'm, you know, I like luck, but I think it's created by the opportunity that you make your luck. You make your luck. Yeah. Dan, it was a huge honor. Thank you for welcoming me into your home and for having this conversation. Yeah, no problem. Good man. Thanks for listening to this conversation with Dan Gable and thank you to our sponsors Trial Labs, a machine learning company, ExpressVPN, Grammarly Writing Helper Tool, and SimpliSafe Home Security. So the choice is artificial intelligence, privacy, grammar, or safety. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you with some words from Dan Gable. The first period is won by the best technician. The second period is won by the kid in the best shape. And the third period is won by the kid with the biggest heart. Thank you for listening and hope to see you next time.

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Grant Sanderson: Math, Manim, Neural Networks & Teaching with 3Blue1Brown | Lex Fridman Podcast #118

The following is a conversation with Grant Sanderson, his second time on the podcast. He's known to millions of people as the mind behind 3Blue1Brown, a YouTube channel where he educates and inspires the world with the beauty and power of mathematics. Quick summary of the sponsors, Dollar Shave Club, DoorDash, and Cash App. Click the sponsor links in the description to get a discount and to support this podcast, especially for the two new sponsors, Dollar Shave Club and DoorDash. Let me say as a side note, I think that this pandemic challenged millions of educators to rethink how they teach, to rethink the nature of education. As people know, Grant is a master elucidator of mathematical concepts that may otherwise seem difficult or out of reach for students and curious minds. But he's also an inspiration to teachers, researchers, and people who just enjoy sharing knowledge, like me, for what it's worth. It's one thing to give a semester's worth of multi-hour lectures. It's another to extract from those lectures the most important, interesting, beautiful, and difficult concepts and present them in a way that makes everything fall into place. That is the challenge that is worth taking on. My dream is to see more and more of my colleagues at MIT and world experts across the world summon their inner 3Blue1Brown and create the canonical explainer videos on a topic that they know more than almost anyone else in the world. Amidst the political division, the economic pain, the psychological medical toll of the virus, masterfully crafted educational content feels like one of the beacons of hope that we can hold onto. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. Of course, after you go immediately, which you already probably have done a long time ago, and subscribe to 3Blue1Brown YouTube channel, you will not regret it. As usual, I'll do a few minutes of ads now and no ads in the middle. I try to make these interesting, but I give you timestamps so you can skip. But still, please do check out the sponsors by clicking the links in the description, especially the two new ones, DoorDash and Dollar Shave Club. They're evaluating us, looking at how many people go to their site and get their stuff in order to determine if they wanna support us for the longterm. So you know what to do. It's the best way to support this podcast as always. This show is sponsored by Dollar Shave Club. Try them out with a one-time offer for only $5 and free shipping at dollarshaveclub.com slash Lex. Starter kit comes with a six blade razor, refills, and all kinds of other stuff that makes shaving feel great. I've been a member of Dollar Shave Club for over five years now, and actually signed up when I first heard about them on the Joe Rogan podcast. And now we have come full circle. I feel like I've made it. Now that I can do a read for them just like Joe did all those years ago. For the most part, I've just used the razor and the refills, but they encouraged me to try the shave butter, which I've never used before. So I did, and I love it. Not sure how the chemistry of it works out, but it's translucent somehow, which is a cool new experience. Again, try the Ultimate Shave Starter Set today for just five bucks, plus free shipping at dollarshaveclub.com slash Lex. This show is also sponsored by DoorDash. Get five bucks off and zero delivery fees on your first order of $15 or more when you download the DoorDash app and enter code Lex. I have so many memories of working late nights for a deadline with a team of engineers and eventually taking a break to argue about which DoorDash restaurant to order from. And when the food came, those moments of bonding, of exchanging ideas, of pausing to shift attention from the programs to the humans were special. These days, for a bit of time, I'm on my own, sadly, so I miss that camaraderie. But actually, DoorDash is still there for me. There's a million options that fit into my keto diet ways. Also, it's a great way to support restaurants in these challenging times. Once again, download the DoorDash app and enter code Lex to get five bucks off and zero delivery fees on your first order of $15 or more. Finally, this show is presented by Cash App, the number one finance app in the App Store, when you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. It's one of the best design interfaces of an app that I've ever used. To me, good design is when everything is easy and natural. Bad design is when the app gets in the way, either because it's buggy or because it tries too hard to be helpful. I'm looking at you, Clippy. Anyway, there's a big part of my brain and heart that love to design things and also to appreciate great design by others. So again, if you get Cash App from the App Store, Google Play, and use code LexPodcast, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Grant Sanderson. You've spoken about Richard Feynman as someone you admire. I think last time we spoke, we ran out of time. So I wanted to talk to you about him. Who is Richard Feynman to you in your eyes? What impact did he have on you? I mean, I think a ton of people like Feynman. He's probably, it's a little bit cliche to say that you like Feynman, right? That's almost like when you don't know what to say about sports and you just point to the Super Bowl or something as something you enjoy watching. But I do actually think there's a layer to Feynman that sits behind the iconography. One thing that just really struck me was this letter that he wrote to his wife two years after she died. So during the Manhattan Project, she had polio. Tragically, she died. They were just young, madly in love. And the icon of Feynman is this, almost this like mildly sexist, womanizing philanderer, at least on the personal side. But you read this letter, and I can try to pull it up for you if I want. And it's just this absolutely heartfelt letter to his wife saying how much he loves her. Even though she's dead and kind of what she means to him, how no woman can ever measure up to her. And it shows you that the Feynman that we've all seen in like, surely you're joking, is different from the Feynman in reality. And I think the same kind of goes in his science where he kind of sometimes has this output of being this, ah shucks character. Like everyone else is coming in, there's these fancy pollutant formulas, but I'm just gonna try to whittle it down to its essentials, which is so appealing because we love to see that kind of thing. But when you get into it, like what he was doing was actually quite deep, very much mathematical. That should go without saying, but I remember reading a book about Feynman in a cafe once, and this woman looked at me and was like, saw that it was about Feynman. She was like, oh, I love him. I read surely you're joking. And she started explaining to me how he was never really a math person. And I don't understand how that can possibly be a public perception about any physicist, but for whatever reason that like worked into his aura that he sort of is a math person. That he sort of shooed off math and in place of true science. The reality of it is he was deeply in love with math and was much more going in that direction and had a clicking point into seeing that physics was a way to realize that. And all the creativity that he could output in that direction was instead poured towards things like fundamental, not even fundamental theories, just emergent phenomena and everything like that. So to answer your actual question, like what I like about his way of going at things is this constant desire to reinvent it for himself. Like when he would consume papers, the way he'd describe it, he would start to see what problem he was trying to solve and then just try to solve it himself to get a sense of personal ownership. And then from there, see what others had done. Is that how you see problems yourself? Like that's actually an interesting point when you first are inspired by a certain idea that you maybe wanna teach or visualize or just explore on your own. I'm sure you're captured by some possibility and magic of it. Do you read the work of others? Like do you go through the proof? Do you try to rediscover everything yourself? So I think the things that I've learned best and have the deepest ownership of are the ones that have some element of rediscovery. The problem is that really slows you down. And this is, for my part, it's actually a big fault. Like this is part of why I'm not an active researcher. I'm not like at the depth of the field a lot of other people are. The stuff that I do learn, I try to learn it really well. But other times you do need to get through it at a certain pace. You need to get to a point of a problem you're trying to solve. So obviously you need to be well-equipped to read things without that reinvention component and see how others have done it. But I think if you choose a few core building blocks along the way and you say, I'm really gonna try to approach this before I see how this person went at it. I'm really gonna try to approach it for myself. No matter what, you gain all sorts of inarticulatable intuitions about that topic, which aren't gonna be there if you simply go through the proof. For example, you're gonna be trying to come up with counter examples. You're gonna try to come up with intuitive examples, all sorts of things where you're populating your brain with data. And the ones that you come up with are likely to be different than the one that the text comes up with. And that like lends it a different angle. So that aspect also slowed Feynman down in a lot of respects. I think there was a period when like the rest of physics was running away from him. But insofar as it got him to where he was, I kind of resonate with that. I just, I would be nowhere near it because I'm not like him at all, but it's like a state to aspire to. You know, just to link in a small point you made, that you're not a quote unquote active researcher. Do you, you're swimming often in reasonably good depth about a lot of topics. Do you sometimes wanna like dive deep at a certain moment and say like, because you probably built up a hell of an amazing intuition about what is and isn't true within these worlds. Do you ever wanna just dive in and see if you can discover something new? Yeah, I think one of my biggest regrets from undergrad is not having built better relationships with the professors I had there. And I think a big part of success in research is that element of like mentorship and like people giving you the kind of scaffolded problems to carry along. For my own like goals right now, I feel like I'm pretty good at exposing math to others and like want to continue doing that. For my personal learning, are you familiar with like the hedgehog fox dynamic? I think this was either the ancient Greeks came up with it or it was pretended to be something drawn from the ancient Greeks. I don't know who to point it to, but the- Probably Mark Twain. It is that you've got two types of people or especially two types of researchers. There's the fox that knows many different things and then the hedgehog that knows one thing very deeply. So like von Neumann would have been the fox. He's someone who knows many different things, just very foundational in a lot of different fields. Einstein would have been more of a hedgehog, thinking really deeply about one particular thing. And both are very necessary for making progress. So between those two, I would definitely see myself as like the fox where I'll try to get my paws in like a whole bunch of different things. And at the moment, I just think I don't know enough of anything to make like a significant contribution to any of them. But I do see value in like having a decently deep understanding of a wide variety of things. Like most people who know computer science really deeply don't necessarily know physics very deeply or many of the aspects, like different fields in math even. Let's say you have like an analytic number theory versus an algebraic number theory. Like these two things end up being related to very different fields. Like some of them more complex analysis, some of them more like algebraic geometry. And then when you just go out so far as to take those adjacent fields, place one, you know, PhD student into a seminar of another one's, they don't understand what the other one's saying at all. Like you take the complex analysis specialist inside the algebraic geometry seminar, they're as lost as you or I would be. But I think going around and like trying to have some sense of what this big picture is, certainly has personal value for me. I don't know if I would ever make like new contributions in those fields, but I do think I could make new like expositional contributions where there's kind of a notion of things that are known, but like haven't been explained very well. Well, first of all, I think most people would agree your videos, your teaching, the way you see the world is fundamentally often new. Like you're creating something new. And it almost feels like research, even just like the visualizations, the multi-dimensional visualization we'll talk about. I mean, you're revealing something very interesting that yeah, just feels like research, feels like science, feels like the cutting edge of the very thing of which like new ideas and new discoveries are made of. I do think you're being a little bit more generous than is necessarily. And I promise that's not even false humility because I sometimes think when I research a video, I'll learn like 10 times as much as I need for the video itself. And it ends up feeling kind of elementary. So I have a sense of just how far away like the stuff that I cover is from the actual depth. I think that's natural, but I think that could also be a mathematics thing. I feel like in the machine learning world, you like two weeks in, you feel like you've basically mastered. In mathematics, it's like. Well, everything is either trivial or impossible. And it's like a shockingly thin line between the two where you can find something that's totally impenetrable. And then after you get a feel for it, it's like, oh yeah, that whole subject is actually trivial in some way. So maybe that's what goes on. Every researcher is just on the other end of that hump. And it feels like it's so far away, but one step actually gets them there. What do you think about sort of Feynman's teaching style or another perspective is of use of visualization? Well, his teaching style is interesting because people have described like the Feynman effect where while you're watching his lectures or while you're reading his lectures, everything makes such perfect sense. So as an entertainment session, it's wonderful because it gives you this intellectual satisfaction that you don't get from anywhere else that you like finally understand it. But the Feynman effect is that you can't really recall what it is that gave you that insight even a week later. And this is true of a lot of books and a lot of lectures where the retention is never quite what we hope it is. So there is a risk that the stuff that I do also fits that same bill where at best, it's giving this kind of intellectual candy on giving a glimpse of feeling like you understand something. But unless you do something active, like reinventing it yourself, like doing problems to solidify it, even things like space repetition memory to just make sure that you have like the building blocks of what do all the terms mean, unless you're doing something like that, it's not actually gonna stick. So the very same thing that's so admirable about Feynman's lectures, which is how damn satisfying they are to consume might actually also reveal a little bit of the flaw that we should as educators all look out for, which is that that does not correlate with long-term learning. We'll talk about it a little bit. I think you've done some interactive stuff. I mean, even in your videos, the awesome thing that Feynman couldn't do at the time is you could, since it's programmed, you can like tinker, like play with stuff. You could take this value and change it. You can like, here, let's take the value of this variable and change it to build up an intuition, to move along the surface or to change the shape of something. I think that's almost an equivalent of you doing it yourself. It's not quite there, but as a viewer. Yeah, do you think there's some value in that interactive element? Yeah, well, so what's interesting is you're saying that, and the videos are non-interactive in the sense that there's a play button and a pause button. And you could ask like, hey, while you're programming these things, why don't you program it into an interactable version, you know, make it a Jupyter notebook that people can play with, which I should do and that like would be better. I think the thing about interactives though is most people consuming them just sort of consume what the author had in mind. And that's kind of what they want. Like I have a ton of friends who make interactive explanations. And when you look into the analytics of how people use them, there's a small sliver that generally use it as a playground to have experiments. And maybe that small sliver is actually who you're targeting and the rest don't matter. But most people consume it just as a piece of like well-constructed literature that maybe you tweak with the example a little bit to see what it's getting at. But in that way, I do think like a video can get most of the benefits of the interactive, like the interactive app, as long as you make the interactive for yourself and you decide what the best narrative to spin is. As a more concrete example, like my process with, I made this video about SIR models for epidemics. And it's like this agent-based bottling thing where you tweak some things about how the epidemic spreads and you wanna see how that affects its evolution. My format for making that was very different than others where rather than scripting it ahead of time, I just made the playground and then I played a bunch and then I saw what stories there were to tell within that. Yeah, that's cool. So your video had that kind of structure. It had like five or six stories or whatever it was. And like, it was basically, okay, here's a simulation, here's a model. What can we discover with this model? And here's five things I found after playing with it. Well, because the thing is, a way that you could do that project is you make the model and then you put it out and you say, here's a thing for the world to play with. Like come to my website where you interact with this thing. And people did like sort of remake it in a JavaScript way so that you can go to that website and you can test your own hypotheses. But I think a meaningful part of the value to add is not just the technology but to give the story around it as well. And like, that's kind of my job. It's not just to like make the visuals that someone will look at. It's to be the one to decide what's the interesting thing to walk through here. And even though there's lots of other interesting paths that one could take, that can be kind of daunting when you're just sitting there in a sandbox and you're given this tool with like five different sliders and you're told to like play and discover things. Where do you do? What do you start? What are my hypotheses? What should I be asking? Like a little bit of guidance in that direction can be what actually sparks curiosity to make someone want to imagine more about it. A few videos I've seen you do, I don't know how often you do it, but there's almost a tangential like pause where you, here's a cool thing. You say like, here's a cool thing, but it's outside the scope of this video essentially. But I'll leave it to you as homework essentially to like figure out it's a cool thing to explore. I wish I could say that wasn't a function of laziness. Right, and that's like you've worked so hard on making the 20 minutes already that to extend it out even further would take more time. And one of your cooler videos, the homomorphic, like from the Mobius strip to the- What do you describe, rectangle? Yeah, that's a super, and you're like, yeah, you can't transform the Mobius strip into a surface without it intersecting itself. But I'll leave it to you to see why that is. Well, I hope that's not exactly how I phrase it because I think what my hope would be is that I leave it to you to think about why you would expect that to be true and then to want to know what aspects of a Mobius strip do you want to formalize such that you can prove that intuition that you have? Because at some point now you're starting to invent algebraic topology. If you have these vague instincts, like I want to get this Mobius strip, I want to fit it such that it's all above the plane but its boundary sits exactly on the plane. I don't think I can do that without crossing itself, but that feels really vague. How do I formalize it? And as you're starting to formalize that, that's what's going to get you to try to come up with a definition for what it means to be orientable or non-orientable. And like, once you have that motivation, a lot of the otherwise arbitrary things that are sitting at the very beginning of a topology textbook start to make a little more sense. Yeah, and I mean, that whole video beautifully was a motivation for topology is cool. That was my, well, my hope with that is I feel like topology is, I don't want to say it's taught wrong, but I do think sometimes it's popularized in the wrong way where, you know, you'll hear these things with people saying, oh, topologists, they're very interested in surfaces that you can bend and stretch, but you can't cut or glue. Are they? Why? Like, there's all sorts of things you can be interested in with random, like imaginative manipulations of things. Is that really what like mathematicians are into? And the short answer is not, not really. It's not as if someone was sitting there thinking like, I wonder what the properties of clay are. I had some arbitrary rules about what, when I can't cut it and when I can't glue it. Instead, there's a ton of pieces of math that can actually be equivalent to like these very general structures that's like geometry, except you don't have exact distances. You just want to maintain a notion of closeness. And once you get it to those general structures, constructing mappings between them translate into non-trivial facts about other parts of math. And that, I just, I don't think that's actually like popularized. I don't even think it's emphasized well enough when you're starting to take a topology class because you kind of have these two problems. It's like either it's too squishy. You're just talking about coffee mugs and donuts, or it's a little bit too rigor first. And you're talking about the axiom systems with open sets and an open set is not the opposite of closed set. So sorry about that, everyone. We have a notion of clopin sets for ones that are both at the same time. And just, it's not an intuitive axiom system in comparison to other fields of math. So you as the student, like really have to walk through mud to get there. And you're constantly confused about how this relates to the beautiful things about coffee mugs and Movia strips and such. And it takes a really long time to actually see that like C topology in the way that mathematicians see topology. But I don't think it needs to take that time. I think there's, this is making me feel like I need to make more videos on the topic. Cause I think I've only done two. 100% you do. But I've also seen it in my narrow view of like, I find game theory very beautiful. And I know topology has been used elegantly to prove things in game theory. Yeah, you have like facts that seem very strange. Like I could tell you, you stir your coffee and after you stir it, and like, let's say all the molecules settled to like not moving again, one of the molecules will be basically in the same position it was before. You have all sorts of fixed point theorems like this, right? That kind of fixed point theorem, directly relevant to Nash equilibriums, right? So you can imagine popularizing it by describing the coffee fact, but then you're left to wonder like, who cares about if a molecule of coffee like stays in the same spot? Is this what we're paying our mathematicians for? You have this very elegant mapping onto economics in a way that's very concrete, or very, I shouldn't say concrete, very tangible. Like actually adds value to people's lives through the predictions that it makes. But that line isn't always drawn because you have to get a little bit technical in order to properly draw that line out. And often I think popularized forms of media just shy away from being a little too technical. For sure. By the way, for people who are watching the video, I do not condone the message in this mug. It's the only one I have, which is this, the snuggle is real. By the way, for anyone watching, I do condone the message of that mug. The snuggle is real. The snuggle is real. Okay, so you mentioned the SIR model. I think there are certain ideas there of growth, of exponential growth. What maybe have you learned about pandemics from making that video? Because it was kind of exploratory. You were kind of building up an intuition. And it's again, people should watch the video. It's kind of an abstract view. It's not really modeling in detail. The whole field of epidemiology, those people, they go really far in terms of modeling like how people move about. I don't know if you've seen it, but like there is the mobility patterns, like how many people you encounter in certain situations when you go to a school, when you go to a mall, they like model every aspect of that for a particular city. Like they have maps of actual city streets. They model it really well. And natural patterns of the people have, it's crazy. So you don't do any of that. You're just doing an abstract model to explore different ideas of- Simple pedigree. Well, because I don't want to pretend like I'm an epidemiologist. Like we have a ton of armchair epidemiologists. And the spirit of that was more like, can we through a little bit of play, draw like reasonable-ish conclusions? And also just like get ourselves in a position where we can judge the validity of a model. Like I think people should look at that and they should criticize it. They should point to all the ways that it's wrong because it's definitely naive, right? In the way that it's set up. But to say like what lessons from that hold, like thinking about the R naught value and what that represents and what it can imply. What's R naught? So R naught is if you are infectious and you're in a population which is completely susceptible, what's the average number of people that you're going to infect during your infectiousness? So certainly during the beginning of an epidemic, this basically gives you kind of the exponential growth rate. Like if every person infects two others, you've got that one, two, four, eight exponential growth pattern. As it goes on and let's say it's something endemic where you've got like a ton of people who have had it and are recovered, then you would, the R naught value doesn't tell you that as directly because a lot of the people you interact with aren't susceptible, but in the early phases it does. And this is like the fundamental constant that it seems like epidemiologists look at and the whole goal is to get that down. If you can get it below one, then it's no longer epidemic. If it's equal to one, then it's endemic and it's above one, then you're epidemic. So like just teaching what that value is and giving some intuitions on how do certain changes in behavior change that value? And then what does that imply for exponential growth? I think those are general enough lessons and they're like resilient to all of the chaoses of the world that it's still like valid to take from the video. I mean, one of the interesting aspects of that is just exponential growth and the way we think about growth. Is that one of the first times you've done a video on, no, of course not, the whole Euler's identity. Okay, so. Sure. I've done a lot of videos about exponential growth in the circular direction, only minimal in the normal direction. I mean, another way to ask, do you think we're able to reason intuitively about exponential growth? It's funny, I think it's extremely intuitive to humans and then we train it out of ourselves such that it's then really not intuitive and then I think it can become intuitive again when you study a technical field. So what I mean by that is, have you ever heard of these studies where in a anthropological setting where you're studying a group that has been disassociated from a lot of modern society and you ask what number is between one and nine? And maybe you would ask, you've got one rock and you've got nine rocks. You're like, what pile is halfway in between these? And our instinct is usually to say five. That's the number that sits right between one and nine. But sometimes when numeracy and the kind of just basic arithmetic that we have isn't in a society, the natural instinct is three because it's in between in an exponential sense and a geometric sense that one is three times bigger and then the next one is three times bigger than that. So it's like, if you have one friend versus 100 friends, what's in between that? Yeah, 10 friends seems like the social status in between those two states. So that's like deeply intuitive to us to think logarithmically like that. And for some reason, we kind of train it out of ourselves to start thinking linearly about things. So in the sense, yeah, the early basic math forces us to take a step back. It's the same criticism if there's any of science is the lessons of science make us like see the world in a slightly narrow sense to where we have an over-exaggerated confidence that we understand everything as opposed to just understanding a small slice of it. But I think that probably only really goes for small numbers because the real counterintuitive thing about exponential growth is like as the numbers start to get big. So I bet if you took that same setup and you asked them, oh, if I keep tripling the size of this rock pile, you know, seven times, how big will it be? I bet it would be surprisingly big even to like a society without numeracy. And that's the side of it that I think is pretty counterintuitive to us, but that you can basically train into people. Like I think computer scientists and physicists when they're looking at the early numbers of like COVID were, they were the ones thinking like, oh God, this is following an exact exponential curve. And I heard that from a number of people. So it's, and almost all of them are like techies in some capacity, probably just because I like live in the Bay Area, but. But for sure, they're cognizant of this kind of growth that's present in a lot of natural systems and a lot of systems. I don't know if you've seen like, I mean, there's a lot of ways to visualize this obviously, but Ray Kurzweil, I think was the one that had this like chessboard where every square on the chessboard, you double the number of stones or something in that chessboard. I've heard this is like an old proverb where, it's like, you know, someone, the king offered him a gift and he said, the only gift I would like, very modest, give me a single grain of rice for the first chessboard. And then two grains of rice for the next square, then twice that for the next square and just continue on. That's my only modest ask, your sire. And like, it's all, you know, more grains of rice than there are anything in the world by the time you get to the end. And I, my intuition falls apart there. Like I would have never predicted that. Like for some reason, that's a really compelling illustration how poorly breaks down, just like you said, maybe we're okay for the first few piles of rocks, but after a while it's game over. You know, the other classic example for gauging someone's intuitive understanding of exponential growth is I've got like a lily pad on a lake, really big lake, like Lake Michigan. And that lily pad replicates, it doubles one day and then it doubles the next day and it doubles the next day. And after 50 days, it actually is gonna cover the entire lake, okay? So after how many days does it cover? Half the lake. 49. So you have a good instinct for exponential growth. So I think a lot of like the knee jerk reaction is sometimes to think that it's like half the amount of time or to at least be like surprised that like after 49 days, you've only covered half of it. Yeah, I mean, that's the reason you heard a pause from me. I literally thought that can't be right. Right, yeah, exactly. So even when you know the fact and you do the division, it's like, wow, so you've gotten like that whole time and then day 49, it's only covering half and then after that, it gets the whole thing. But I think you can make that even more visceral if rather than going one day before you say, how long until it's covered 1% of the lake, right? And it's, so what would that be? How many times you have to double to get over 100? Like seven, six and a half times, something like that. Right, so at that point, you're looking at 43, 44 days into it, you're not even at 1% of the lake. So you've experienced 44 out of 50 days and you're like, yeah, that's really bad, it's just 1% of the lake. But then next thing you know, it's the entire lake. You're wearing a SpaceX shirt, so let me ask you. Sure. Let me ask you, one person who talks about exponential, just the miracle of the exponential function in general is Elon Musk. So he kind of advocates the idea of exponential thinking. The idea of exponential thinking, realizing that technological development can, at least in the short term, follow exponential improvement, which breaks apart our intuition, our ability to reason about what is and isn't impossible. So he's a big, one, it's a good leadership kind of style of saying like, look, the thing that everyone thinks is impossible is actually possible because exponentials. But what's your sense about that kind of way to see the world? Well, so I think it can be very inspiring to note when something, like Moore's Law is another great example where you have this exponential pattern that holds shockingly well and it enables just better lives to be led. I think the people who took Moore's Law seriously in the 60s were seeing that, wow, it's not gonna be too long before these giant computers that are either batch processing or time-shared, you could actually have one small enough to put on your desk, on top of your desk, and you could do things. And if they took it seriously, like you have people predicting smartphones like a long time ago. And it's only out of like kind of this, I don't wanna say faith in exponentials, but an understanding that that's what's happening. What's more interesting, I think, is to really understand why exponential growth happens and that the mechanism behind it is when the rate of change is proportional to the thing in and of itself. So the reason that technology would grow exponentially is only gonna be if the rate of progress is proportional to the amount that you have. So that the software you write enables you to write more software. And I think we see this with the internet, like the advent of the internet makes it faster to learn things, which makes it faster to create new things. I think this is oftentimes why like investment will grow exponentially, that the more resources a company has, if it knows how to use them well, the more it can actually grow. So I mean, you referenced Elon Musk, I think he seems to really be into vertically integrating his companies. I think a big part of that is cause you have the sense what you want is to make sure that the things that you develop, you have ownership of and that they enable further development of the adjacent parts, right? So it's not just this, you see a curve and you're blindly drawing a line through it. What's much more interesting is to ask, when do you have this proportional growth property? Because then you can also recognize when it breaks down, like in an epidemic, as you approach saturation, that would break down. As you do anything that skews what that proportionality constant is, you can make it maybe not break down as being an exponential, but it can seriously slow what that exponential rate is. This is the opposite of a pandemic, is you want, in terms of ideas, you want to minimize barriers that prevent the spread, you wanna maximize the spread of impact. So like you want it to grow when you're doing technological development, is so that you do hold up, that rate holds up. And that's almost like an operational challenge of like how you run a company, how you run a group of people, is that any one invention has a ripple that's unstopped. And that ripple effect then has its own ripple effects and so on, and that continues. Yeah, like Moore's law is fascinating. On a psychological level, on a human level, because it's not exponential, it's just a consistent set of like, what you would call like S-curves, which is like, it's constantly like breakthrough innovations, nonstop. That's a good point. Like it might not actually be an example of exponentials because of something which grows in proportion to itself, but instead it's almost like a benchmark that was set out that everyone's been pressured to meet. And it's like all these innovations and micro inventions along the way, rather than some consistent sit back and just let the lily pad grow across the lake phenomenon. And it's also, there's a human psychological level for sure of like the four minute mile. Like there's something about it, like saying that, look, there is, you know, Moore's law, it's a law. So like it's certainly an achievable thing. You know, we've achieved it for the last decade, for the last two decades, for the last three decades, you just keep going. And it somehow makes it happen. I mean, it makes people, I'm continuously surprised in this world how few people do the best work in the world, like in that particular, whatever that field is. Like it's very often that like the genius, I mean, you can argue that community matters, but it's certain, like I've been in groups of engineers where like one person is clearly like doing an incredible amount of work and just is the genius. And it's fascinating to see, basically it's kind of the Steve Jobs idea is maybe the whole point is to create an atmosphere where the genius can discover themselves. Like have the opportunity to do the best work of their life. And yeah, and that the exponential is just milking that. It's like rippling the idea that it's possible. And that idea that it's possible finds the right people for the four minute mile. The idea that it's possible finds the right runners to run it and then it explodes the number of people who can run faster than four minutes. It's kind of interesting to, I don't know. Basically the positive way to see that is most of us are way more intelligent, have way more potential than we ever realized. I guess that's kind of depressing. But I mean like the ceiling for most of us is much higher than we ever realized. That is true. A good book to read if you want that sense is Peak, which essentially talks about peak performance in a lot of different ways, like chess, London cab drivers, how many pushups people can do, short term memory tasks. And it's meant to be like a concrete manifesto about deliberate practice and such. But the one sensation you come out with is, wow, no matter how good people are at something, they can get better and like way better than we think they could. I don't know if that's actually related to exponential growth, but I do think it's a true phenomenon. It's interesting. Yeah, I mean, there's certainly no law of exponential growth in human innovation. Well, I don't know. Well, kind of, there is. I think it's really interesting to see when innovations in one field allow for innovations in another. Like the advent of computing seems like a prerequisite for the advent of chaos theory. You have this truth about physics and the world that in theory could be known. You could find Lorenz's equations without computers. But in practice, it was just never gonna be analyzed that way unless you were doing like a bunch of simulations and that you could computationally see these models. So it's like physics allowed for computers, computers allowed for better physics. And wash, rinse, and repeat. That self-proportionality, that's exponential. So I think I wouldn't, it's something it's too far to say that that's a law of some kind. Yeah, a fundamental law of the universe is that these descendants of apes will exponentially improve their technology and one day be taken over by the AGI. That's built in the simulation. That'll make the video game fun, whoever created this thing. I mean, since you're wearing a SpaceX shirt, let me ask. I didn't realize I was wearing a SpaceX shirt. I apologize. It's on point, so it's on topic, I'll take it. So Crew Dragon, the first crewed mission out into space since the space shuttle. And just by first time ever by a commercial company. I mean, it's an incredible accomplishment, I think, but it's also just an incredible, it inspires imagination amongst people that this is the first step in a long, like vibrant journey of humans into space. Oh yeah. So what are your, how do you feel? Is this exciting to you? Yeah, it is. I think it's great. The idea of seeing it basically done by smaller entities instead of by governments. I mean, it's a heavy collaboration between SpaceX and NASA in this case, but moving in the direction of not necessarily requiring an entire country and its government to make it happen, but that you can have something closer to a single company doing it. We're not there yet, because it's not like they're unilaterally saying, like we're just shooting people up into space. It's just a sign that we're able to do more powerful things with smaller groups of people. I find that inspiring. Innovate quickly. I hope we see people land on Mars in my lifetime. Do you think we will? I think so. I mean, I think there's a ton of challenges there, right? Like radiation being kind of the biggest one. And I think there's a ton of people who look at that and say, why? Why would you want to do that? Let's let the robots do the science for us. But I think there's enough people who are like genuinely inspired about broadening the worlds that we've touched. Or people who think about things like backing up the light of consciousness with super long-term visions of terraforming. As long as there's a- Sorry, backing up the light of consciousness? Yeah, the thought that if Earth goes to hell, we gotta have a backup somewhere. A lot of people see that as pretty out there, and it's not in the short-term future, but I think that's an inspiring thought. I think that's a reason to get up in the morning, and I feel like most employees at SpaceX feel that way too. Do you think we'll colonize Mars one day? No idea. Either AGI kills us first, or if we're allowed, I don't know if it'll take us that long. If we're allowed? Honestly, it would take such a long time. Okay, you might have a small colony, something like what you see in The Martian, but not people living comfortably there. But if you want to talk about actual second Earth kind of stuff, that's just way far out there, and the future moves so fast that it's like, we might just kill ourselves before that even becomes viable. Yeah, I mean, there's a lot of possibilities where it could be just, it doesn't have to be on a planet, we could be floating out in space, have a space-faring backup solution that doesn't have to deal with the constraints that a planet, I mean, a planet provides a lot of possibilities and resources, but also some constraints. Yeah, I mean, for me, for some reason, it's a deeply exciting possibility. Oh yeah, yeah, all of the people who are skeptical about it are like, why do we care about going to Mars? It's like, what makes you care about anything? That's inspiring. It's hard, actually, it's hard to hear that because exactly as you put it, on a philosophical level, it's hard to say, why do anything? I don't know, it's like the people say, I've been doing an insane challenge last 30-something days. Your pull-ups? The pull-ups and push-ups, and a bunch of people are like, awesome, you're insane, but awesome. And then some people are like, why? Why do anything? I don't know, there's a calling. I'm with JFK a little bit, it's because we do these things because they're hard. There's something in the human spirit that says, same with a math problem, there's something, you fail once, and it's this feeling that, you know what, I'm not gonna back down from this. There's something to be discovered in overcoming this thing. Well, so what I like about it is, and I also like this about the moon missions, sure, it's kind of arbitrary, but you can't move the target. So you can't make it easier and say that you've accomplished the goal. And when that happens, it just demands actual innovation. Like protecting humans from the radiation in space on the flight there, while there, hard problem, demands innovation. You can't move the goalposts to make that easier. Almost certainly, the innovations required for things like that will be relevant in a bunch of other domains too. So like the idea of doing something merely because it's hard, it's like loosely productive, great. But as long as you can't move the goalposts, there's probably gonna be these secondary benefits that we should all strive for. Yeah, I mean, it's hard to formulate the Mars colonization problem as something that has a deadline, which is the problem. But if there was a deadline, then the amount of things we would come up with by forcing ourselves to figure out how to colonize that place would be just incredible. This is what people, like the internet didn't get created because people sat down and tried to figure out how do I send TikTok videos of myself dancing to people? There's an application. I mean, actually, I don't even know how. What do you think the application for the internet was when it was? It must've been very low-level, basic network communication within DARPA, like military-based, like how do I send, like a networking, how do I send information securely between two places? Maybe it was an encryption. I'm speaking totally outside of my knowledge, but it was probably intended for a very narrow, small group of people. Well, so, I mean, there was this small community of people who were really interested in timesharing computing and interactive computing in contrast with batch processing. And then the idea that as you set up a timesharing center, basically meaning you can have multiple people logged in and using that central computer, why not make it accessible to others? And this was kind of what I had always thought, oh, it was this fringe group that was interested in this new kind of computing, and they all got themselves together. But the thing is, DARPA wouldn't actually, you wouldn't have the US government funding that just for the funds of it, right? In some sense, that's what ARPA was all about, was just really advanced research for the sake of having advanced research, and it doesn't have to pay out with utility soon. But the core parts of its development were happening in the middle of the Vietnam War when there was budgetary constraints all over the place. I only learned this recently, actually. If you look at the documents, basically justifying the budget for the ARPANET as they were developing it, and not just keeping it where it was, but actively growing it while all sorts of other departments were having their funding cut because of the war, a big part of it was national defense in terms of having a more robust communication system, like the idea of packet switching versus circuit switching. You could kind of make this case that in some calamitous circumstance where a central location gets nuked, this is a much more resilient way to still have your communication lines that traditional telephone lines weren't as resilient to, which I just found very interesting. Even something that we see as so happy-go-lucky is just a bunch of computer nerds trying to get interactive computing out there. The actual thing that made it funded and thing that made it advance when it did was because of this direct national security question and concern. I don't know if you've read it. I haven't read it. I've been meaning to read it, but Neil deGrasse Tyson actually came out with a book that talks about science in the context of the military, like basically saying all the great science we've done in the 20th century was because of the military. I mean, he paints a positive. It's not like a critical. A lot of people say military industrial complex and so on. Another way to see the military and national security is like a source of, like you said, deadlines and hard things you can't move, like almost scaring yourself into being productive. It is that. I mean, the Manhattan Project is a perfect example, probably the quintessential example. That one is a little bit more macabre than others because of what they were building, but in terms of how many focused, smart hours of human intelligence get pointed towards a topic per day, you're just maxing it out with that sense of worry. In that context, everyone there was saying, like, we've got to get the bomb before Hitler does. And that just lights a fire under you that I, again, like the circumstances macabre, but I think that's actually pretty healthy, especially for researchers that are otherwise going to be really theoretical. To take these like theorizers and say, make this real physical thing happen, meaning a lot of it is going to be unsexy. A lot of it's going to be like young Feynman sitting there kind of inventing a notion of computation in order to like compute what they needed to compute more quickly with like the rudimentary automated tools that they had available. I think you see this with Bell Labs also, where you've got otherwise very theorizing minds in very pragmatic contexts that I think is like really helpful for the theory as well as for the applications. So I think that stuff can be positive for progress. You mentioned Bell Labs and Manhattan Project. This kind of makes me curious for the things you've create, which are quite singular. Like if you look at all YouTube or just not YouTube, it doesn't matter what it is. It's just teaching content, art, doesn't matter. It's like, yep, that's Grant, right? That's unique. I know your teaching style and everything. Does it, Manhattan Project and Bell Labs was like famously a lot of brilliant people, but there's a lot of them. They play off of each other. So like my question for you is that does it get lonely? Honestly, that right there, I think is the biggest part of my life that I would like to change in some way. That I look at a Bell Labs type situation and I'm like, goddamn, I love that whole situation. And I'm so jealous of it. And you're like reading about Hamming and then you see that he also shared an office with Shannon. And you're like, of course he did. Of course they shared an office. That's how these ideas get like. And they actually probably, very likely worked separately. Yeah, totally separate. But there's a literally, and sorry to interrupt. There's a literally magic that happens when you run into each other, like on the way to like getting a snack or something. Conversations you overhear, it's other projects you're pulled into. It's like puzzles that colleagues are sharing. Like all of that. I have some extent of it just because I try to stay well connected in communities of people who think in similar ways. But it's not in the day to day in the same way, which I would like to fix somehow. That's one of the, I would say one of the biggest, well, one of the many drawbacks, negative things about this current pandemic is that whatever the term is, but like chance collisions are significantly reduced. I saw, I don't know why I saw this, but on my brother's work calendar, he had a scheduled slot with someone that he scheduled a meeting. And the title of the whole meeting was, no specific agenda, I just missed the happenstance serendipitous conversations that we used to have, which the pandemic and remote work has so cruelly taken away from us. Brilliant. That was the whole title of the meeting. That's brilliant. I'm like, that's the way to do it. You just schedule those things. You schedule the serendipitous interaction. It's like, I mean, you can't do it in an academic setting, but it's basically like going to a bar and sitting there just for the strangers you might meet, just the strangers or striking up a conversation with strangers on the train. Harder to do when you're deeply, like maybe myself or maybe a lot of academic types who are like introverted and avoid human contact as much as possible. So it's nice when it's forced, those chance collisions, but maybe scheduling is a possibility. But for the most part, do you work alone? Like, I'm sure you struggle like a lot, like you probably hit moments when you look at this and you say like, this is the wrong way to show it. This is the wrong way to visualize it. I'm making it too hard for myself. I'm going down the wrong direction. This is too long. This is too short. All those self-doubt that's like can be paralyzing. Like, what do you do in those moments? Honestly, I actually much prefer like work to be a solitary affair for me. That's like a personality quirk. I would like it to be in an environment with others and like collaborative in the sense of ideas exchanged. But those phenomena you're describing when you say this is too long, this is too short, this visualization sucks, it's way easier to say that to yourself than it is to say to a collaborator. And I know that's just a thing that I'm not good at. So in that way, it's very easy to just throw away a script because the script isn't working. It's hard to tell someone else they should do the same. Actually, last time we talked, I think it was like very close to me talking Don Knuth was kind of cool. Like two people that- Can't believe you got that interview. It's the hard, no, can I brag about something? Please. My favorite thing is Don Knuth, after we did the interview, he offered to go out to hot dogs with me. We get hot dogs. That was never, like people ask me, what's the favorite interview you've ever done? I mean, that has to be, but unfortunately I couldn't. I had a thing after. So I had to turn down Don Knuth. You missed Knuth dogs? Knuth dogs. Sorry, so that was a little bragging, but the hot dogs, he's such a sweet. But the reason I bring that up is he works through problems alone as well. He prefers that struggle, the struggle of it. So, writers like Stephen King, often talk about their process of what they do, like what they eat when they wake up, like when they sit down, how they like their desk, on a perfectly productive day, like what they like to do, how long they like to work for, what enables them to think deeply, all that kind of stuff. Honoré Stompson did a lot of drugs. Everybody has their own thing. Do you have a thing? If you were to lay out a perfect, productive day, what would that schedule look like, do you think? Part of that's hard to answer, because the mode of work I do changes a lot from day to day. Some days I'm writing. The thing I have to do is write a script. Some days I'm animating. The thing I have to do is animate. Sometimes I'm working on the animation library. The thing I have to do is a little, I'm not a software engineer, but something in the direction of software engineering. Some days it's a variant of research. It's like, learn this topic well and try to learn it differently. So those is four very different modes of what it, some days it's like, get through the email backlog of people I've been, the tasks I've been putting off. It goes research, scripting. The idea starts with research, and then there's scripting, and then there's programming, and then there's the showtime. And the research side, by the way, like what's, I think a problematic way to do it is to say, I'm starting this project, and therefore I'm starting the research. Instead, it should be that you're like, ambiently learning a ton of things just in the background, and then once you feel like you have the understanding for one, you put it on the list of things that there can be a video for. Otherwise, either you're gonna end up roadblocked forever, or you're just not gonna like, have a good way of talking about it. But still, some of the days it's like, the thing to do is learn new things. So what's the most painful one, I think you mentioned, scripting? Scripting is, yeah, that's the worst. Yeah, writing is the worst. So what's your, on a perfectly, so let's take the hardest one. What's a perfectly productive day? You wake up, and it's like, damn it, this is the day I need to do some scripting. And like, you didn't do anything the last two days, so you came up with excuses to procrastinate, so today must be the day. Yeah, I wake up early, I guess I exercise, and then I turn the internet off. If we're writing, yeah, that's what's required, is having the internet off, and then maybe you keep notes on the things that you wanna Google when you're allowed to have the internet again. I'm not great about doing that, but when I do, that makes it happen. And then when I hit writer's block, like the solution to writer's block is to read. Doesn't even have to be related, just read something different, just for like 15 minutes, half an hour, and then go back to writing. That, when it's a nice cycle, I think can work very well. And when you're writing the script, you don't know where it ends, right? Like you have a... Problem-solving videos, I know where it ends. Expositional videos, I don't know where it ends. Like coming up with the magical thing that makes this whole story, like ties this whole story together. When does that happen? That's the thing that makes it such that a topic gets put on the list of videos that you wanna make. Oh, that's initial. There isn't a hop in it. You shouldn't start the project unless there's one of those. And you have so many nice bag, that you have such a big bag of aha moments already that you could just pull at it. That's one of the things, and one of the sad things about time, and that nothing lasts forever, and that we're all mortal. Let's not get into that. And discussion is, you know, if I see like, even when I asked for people to ask, like ask, I did a call for questions that people wanna ask you questions. And there's so many requests from people about like certain videos they would love you to do. It's such a pile. And I think that's a sign of like admiration from people for sure. But it's like, it makes me sad because like whenever I see them, people give ideas, they're all like very often really good ideas. And it's like, it's such a, makes me sad in the same kind of way when I go through a library or through a bookstore, you see all these amazing books that you'll never get to open. So, yeah. So you did, yeah. You gotta enjoy the ones that you have. Enjoy the books that are open and don't let yourself lament the ones that stay closed. What else? Is there any other magic to that day? Did you try to dedicate like a certain number of hours? Do you, Cal Newport has this deep work kind of idea? There's systematic people who like get really on top of, you know, they checklist of what they're gonna do in the day and they like count their hours. And I am not a systematic person in that way. Which is probably a problem. I very likely would get more done if I was systematic in that way, but that doesn't happen. So, you know, you talk to me later in life and maybe I'll have like changed my ways and give you a very different answer. I think Benjamin Franklin like later in life figured out the rigor. He has these like very rigorous schedules and how to be productive. I think those schedules are much more fun to write. Like it's very fun to like write a schedule and make a blog post about like the perfect productive day. That like might work for one person, but I don't know how much people get out of like reading them or trying to adopt someone else's style. And I'm not even sure that they've ever followed. Yeah, exactly. Like you're always gonna write it as the best version of yourself. You're not going to explain the phenomenon of like wanting to get out of the bed, but not really wanting to get out of the bed and all of that. And just like zoning out for random reasons or the one that people probably don't touch at all is, I try to check social media once a day, but I'm like only, so I post and that's it. When I post, I check the previous days. That's like my, what I try to do. That's what I do like 90% of the days, but then I'll go, I'll have like a two week period where it's just like, I'm checking the internet. Like, I mean, it's probably some scary number of times. And- I think a lot of people can resonate with that. I think it's a legitimate addiction. It's like, it's a dopamine addiction. And I don't know if it's a problem because as long as it's a kind of socializing, like if you're actually engaging with friends and engaging with other people's ideas, I think it can be really useful. Well, I don't know. So like for sure, I agree with you, but it's definitely an addiction because for me, I think it's true for a lot of people. I am very cognizant of the fact I just don't feel that happy. If I look at a day where I've checked social media a lot, like if I just aggregate, I did a self-report, I'm sure I would find that I'm just like literally on like less happy with my life and myself after I've done that check. When I check it once a day, I'm very, like, I'm happy. Even like, cause I've seen it. Okay, one way to measure that is when somebody says something not nice to you on the internet, is like when I check it once a day, I'm able to just like, I smile, like I virtually, I think about them positively, empathetically, I send them love. I don't ever respond, but I just feel positively about the whole thing. If I check more than that, it starts eating at me. Like there's an eating thing that happens, like anxiety, it occupies a part of your mind that's not, doesn't seem to be healthy. Same with, I mean, you put stuff out on YouTube. I think it's important. I think you have a million dimensions that are interesting to you, but one of the interesting ones is the study of education and the psychological aspect of putting stuff up on YouTube. I like now have completely stopped checking statistics of any kind. I've released an episode, 100 with my dad, conversation with my dad. He checks, he's probably listening to this, stop. He checks the number of views on his video, on his conversation. So he discovered like a reason, he's new to this whole addiction, and he just checks. And he like, he'll text me or write to me, I just passed Dawkins in the top. So. Oh my God, I love that so much. Oh, can I tell you a funny story in that effect of like parental use of YouTube? Early on in the channel, my mom would like text me. She's like, the channel has had 990,000 views. The channel has had 991,000 views. I'm like, oh, that's cute. She's going to the little part on the about page where you see the total number of channel views. No, she didn't know about that. She had been going every day through all the videos and then adding them up. Adding them up. And she thought she was like doing me this favor of providing me this like global analytic that otherwise wouldn't be visible. That's awesome. It's just like this addiction where you have some number you want to follow and like, yeah, it's funny that your dad had this. I think a lot of people have it. I think that's probably a beautiful thing for like parents because they're legitimately, they're proud. Yeah, it's born of love, it's great. The downside I feel, one of them, is this is one interesting experience that you probably don't know much about because comments on your videos are super positive. But people judge the quality of how something went, like I see that with these conversations, by the comments. I'm not talking about like, you know, people in their 20s and their 30s. I'm talking about like CEOs of major companies who don't have time. They basically, they literally, this is their evaluation metric. They're like, ooh, the comments seem to be positive. And that's really concerning to me. Most important lesson for any content creator to learn is that the commenting public is not representative of the actual public. And this is easy to see. Ask yourself, how often do you write comments on YouTube videos? Most people will realize I never do it. Some people realize they do, but the people who realize they never do it should understand that that's a sign the kind of people who are like you aren't the ones leaving comments. And I think this is important in a number of respects. Like in my case, I think I would think my content was better than it was if I just read comments because people are super nice. The thing is the people who are bored by it or are put off by it in some way, are frustrated by it, usually they just go away. They're certainly not going to watch the whole video, much less leave a comment on it. So there's a huge under-representation of like negative feedback, like well-intentioned negative feedback, because very few people actively do that. Like watch the whole thing that they dislike, figure out what they disliked, articulate what they dislike. There's plenty of negative feedback that's not well-intentioned, but for like that golden kind. I think a lot of YouTuber friends I have at least have gone through phases of like anxiety about the nature of comments that stem from basically just this, that it's like people who aren't necessarily representative of who they were going for, misinterpreted what they were trying to say or whatever have you, or were focusing on things like personal appearances as opposed to like substance. And they come away thinking like, oh, that's what everyone thinks, right? That's what everyone's response to this video was. But a lot of the people who had the reaction you wanted them to have, like they probably didn't write it down. So very important to learn. It also translates to realizing that you're not as important as you might think you are, because all of the people commenting are the ones who love you the most and are like really asking you to like create certain things or like mad that you didn't create like a past thing. I don't know, I have such a problem. Like I have a very real problem with making promises about a type of content that I'll make and then either not following up on it soon or just like never following up on it. Yeah, you actually, last time we talked, I think, I'm not sure, promised to me that you'll have music incorporated into your like- I'll share it with you at private length. But so there's an example of like what I had in mind. I like did a version of it and I'm like, I think there's a better version of this that might exist one day. So it's now on the, like the back burner. It's like, it's sitting there. It was like a live performance at this one thing. I think next circumstance that I'm like doing another recorded live performance that like fits having that then in a better recording context, maybe I'll make it nice and public. Maybe a while. But exactly, right? The point I was gonna make though is like, I know I'm bad about following up on stuff, which is an actual problem. It's born of the fact that I have a sense of what will be like good content when it won't be. But this can actually be incredibly disheartening because a ton of comments that I see are people who are like frustrated, usually in a benevolent way that like, I haven't followed through on like X and X, which I get. And I should do that. But what's comforting thought for me is that when there's a topic I haven't promised, but I am working on and I'm excited about, it's like the people who would really like this don't know that it's coming and don't know to like comment to that effect. And like the commenting public that I'm seeing is not representative of like who I think this other project will touch meaningfully. Yeah, so focus on the future, on the thing you're creating now, just like the art of it. One of the people is really inspiring to me in that regard, because I've really seen it in person is Joe Rogan. He doesn't read comments, but not just that. He doesn't give a damn. He like legitimate, he's not like clueless about it. He's like, just like the richness and the depth of a smile he has when he just experiences the moment with you, like offline. You can tell he doesn't give a damn about like, about anything, about what people think about, whether if it's on a podcast, you talk to him or whether offline about just, it's not there. Like what other people think, how even like what the rest of the day looks like is just deeply in the moment. Or like, especially like, is what we're doing gonna make for a good Instagram photo or something like that? It doesn't think like that at all. It's, I think for actually quite a lot of people, he's an inspiration in that way, but it was, and in real life, I show that you can be very successful not giving a damn about comments. And it sounds bad not to read comments, because it's like, well, there's a huge number of people who are deeply passionate about what you do. So you're ignoring them. But at the same time, the nature of our platforms is such that the cost of listening to all the positive people who are really close to you, who are incredible people, have been, made a great community that you can learn a lot from. The cost of listening to those folks is also the cost of your psychology slowly being degraded by the natural underlying toxicity of the internet. Engage with a handful of people deeply, rather than like as many people as you can in a shallow way. I think that's a good lesson for social media usage. Like, on Twitter. Platforms in general, yeah. Choose just a handful of things to engage with and engage with it very well in a way that you feel proud of and don't worry about the rest. Honestly, I think the best social media platform is texting. That's my favorite. That's my go-to social media platform. Well, yeah, the best social media interaction is like real life, not social media, but social interaction. Well, yeah, no question there. I think everyone should agree with that. Which sucks because it's been challenged now with the current situation. And we're trying to figure out what kind of platform can be created that we can do remote communication that still is effective. It's important for education. It's important for just. That is the question of education right now. Yeah. So on that topic, you've done a series of live streams called Lockdown Math. And you went live, which is different than you usually do. Maybe one, can you talk about how'd that feel? What's that experience like? Like in your own, when you look back, like is that an effective way, did you find being able to teach? And if so, is there a lessons for this world where all of these educators are now trying to figure out how the heck do I teach remotely? For me, it was very different, as different as you can get. I'm on camera, which I'm usually not. I'm doing it live, which is nerve wracking. It was a slightly different like level of topics. Although realistically, I'm just talking about things I'm interested in no matter what. I think the reason I did that was this thought that a ton of people are looking to learn remotely, the rate at which I usually put out content is too slow to be actively helpful. Let me just do some biweekly lectures that if you're looking for a place to point your students, if you're a student looking for a place to be edified about math, just tune in at these times. And in that sense, I think it was a success for those who followed with it. It was a really rewarding experience for me to see how people engaged with it. Part of the fun of the live interaction was to actually, like I'd do these live quizzes and see how people would answer and try to shape the lesson based on that, or see what questions people were asking in the audience. I would love to, if I did more things like that in the future, kind of tighten that feedback loop even more. I think for, you know, you asked about like, if this can be relevant to educators, like 100% online teaching is basically a form of live streaming now. And usually it happens through Zoom. I think if teachers view what they're doing as a kind of performance and a kind of live stream performance, that would probably be pretty healthy because Zoom can be kind of awkward. And I wrote up this little blog post actually, just on like, just what our setup looked like, if you want to adopt it yourself and how to integrate like the broadcasting software OBS with Zoom or things like that. It was really sad to pause on that. I mean, yeah, maybe we could look at the blog post, but it looked really nice. The thing is, I knew nothing about any of that stuff before I started. I had a friend who knew a fair bit. And so he kind of helped show me the roops. One of the things that I realized is that you could, as a teacher, like it doesn't take that much to make things look and feel pretty professional. Like one component of it is as soon as you hook things up with the broadcasting software, rather than just doing like screen sharing, you can set up different scenes and then you can like have keyboard shortcuts to transition between those scenes. So you don't need a production studio with a director calling like, go to camera three, go to camera two, like onto the screen capture. Instead you can have control of that. And it took a little bit of practice and I would mess it up now and then, but I think I had it decently smooth such that, you know, I'm talking to the camera and then we're doing something on the paper. Then we're doing like a, playing with a Desmos graph or something. And something that I think in the past would have required a production team, you can actually do as a solo operation. And in particular as a teacher. And I think it's worth it to try to do that because two reasons, one, you might get more engagement from the students. But the biggest reason, I think one of the like best things that can come out of this pandemic education wise, is if we turn a bunch of teachers into content creators. And if we take lessons that are usually done in these one-off settings and like start to get in the habit of, sometimes I'll use the phrase commoditizing explanation, where what you want is, whatever a thing a student wants to learn, it just seems inefficient to me that that lesson is taught millions of times over in parallel across many different classrooms in the world. Like year to year, you've got a given algebra one lesson that's just taught like literally millions of times by different people. What should happen is that there's the small handful of explanations online that exist so that when someone needs that explanation, they can go to it. That the time in classroom is spent on all of the parts of teaching and education that aren't explanation, which is most of it, right? And the way to get there is to basically have more people who are already explaining, publish their explanations and have it in a publicized forum. So if during a pandemic, you can have people automatically creating online content because it has to be online, but getting in the habit of doing it in a way that doesn't just feel like a Zoom call that happened to be recorded, but it actually feels like a piece that was always gonna be publicized to more people than just your students, that can be really powerful. And there's an improvement process there. So being self-critical and growing, I guess YouTubers go through this process of putting out some content and nobody caring about it and then trying to figure out, basically improving, figure out like, why did nobody care? And they come up with all kinds of answers which may or may not be correct, but doesn't matter because the answer leads to improvement. So you're being constantly self-critical, self-analytical, it should be better to say. So you think of like, how can I make the audio better? Like all the basic things. Maybe one question to ask, because, well, by way of Russ Tedrick, he's a robotics professor at MIT, one of my favorite people, a big fan of yours. He watched our first conversation. I just interviewed him a couple of weeks ago. He teaches this course in underactuated robotics, which is like robotic systems when you can't control everything. We as humans, when we walk, we're always falling forward, which means like it's gravity, you can't control it. You just hope you can catch yourself, but that's not all guaranteed. It depends on the surface. So like that's underactuated, you can't control everything. The number of actuators, the degrees of freedoms you have is not enough to fully control the system. So I don't know. It's a really, I think, beautiful, fascinating class. He puts it online. It's quite popular. He does an incredible job teaching. He puts it online every time, but he's kind of been interested in like crisping it up, like making it, innovating in different kinds of ways. And he was inspired by the work you do, because I think in his work, he can do similar kinds of explanations as you're doing, like revealing the beauty of it and spending like months in preparing a single video. And he's interested in how to do that. That's why he listened to the conversation. He's playing with Manum. But he had this question of, you know, like in my apartment where we did the interview, if I have like curtains, like a black curtain, not this, this is a adjacent mansion that we're in that I also own. But you basically just have like a black curtain, whatever, that, you know, it makes it really easy to set up a filming situation with cameras that we have here, these microphones. He was asking, you know, what kind of equipment do you recommend? I guess like your blog post is a good one. I said, I don't recommend, this is excessive and actually really hard to work with. So I wonder, I mean, is there something you would recommend in terms of equipment? Like, is it, do you think like lapel mics, like USB mics? For my narration, I use a USB mic. For the streams, I used a lapel mic. The narration, it's a Blue Yeti. I'm forgetting actually the name of the lapel mic, but it was probably like a Rode of some kind. But- Is it hard to figure out how to make the audio sound good? Oh, I mean, listen to all the early videos on my channel and clearly like, I'm terrible at this. For some reason, I just couldn't get audio for a while. I think it's weird when you hear your own voice. So you hear it, you're like, this sounds weird. And it's hard to know, does it sound weird because you're not used to your own voice or they're like actual audio artifacts at play. So- And then video is just, for the lockdown, it was just the camera. You said it was probably streaming somehow through the- Yeah, there were two GH5 cameras, one that was mounted overhead over a piece of paper. You could also use like an iPad or a Wacom tablet to do your writing electronically, but I just wanted the paper feel. One on the face, there's two, again, I don't know. I'm like just not actually the one to ask this because I like animate stuff usually, but each of them like has a compressor object that makes it such that the camera output goes into the computer USB, but like gets compressed before it does that. The live aspect of it, do you regret doing it live? Not at all. I do think the content might be like much less sharp and tight than if it were something, even that I just recorded like that and then edited later. But I do like something that I do to be out there to show like, hey, this is what it's like raw. This is what it's like when I make mistakes. This is like the pace of thinking. I like the live interaction of it. I think that made it better. I probably would do it on a different channel, I think, if I did series like that in the future, just because it's a different style. It's probably a different target audience and kind of keep clean what 3Blue1Brown is about versus the benefits of like live lectures. Do you suggest like in this time of COVID that people like Russ or other educators try to go like the shorter, like 20 minute videos that are like really well planned out or scripted. You really think through, you slowly design, so it's not live. Do you see like that being an important part of what they do? Yeah, well, what I think teachers like Russ should do is choose the small handful of topics that they're gonna do just really well. They wanna create the best short explanation of it in the world that will be one of those handfuls in a world where you have commoditized explanation, right? Most of the lectures should be done just normally. So put thought and planning into it. I'm sure he's a wonderful teacher and like knows all about that. But maybe choose those small handful of topics. Do what beneficial for me sometimes is if I do sample lessons with people on that topic to get some sense of how other people think about it. Let that inform how you want to edit it or script it or whatever format you wanna do. Some people are comfortable just explaining it and editing later. I'm more comfortable like writing it out and thinking in that setting. Yeah, it's kind of, sorry to interrupt. It's a little bit sad to me to see how much knowledge is lost, like just like you mentioned, there's professors, like we can take my dad for example, to blow up his ego a little bit. But he's a great teacher and he knows plasma, plasma chemistry, plasma physics really well. So he can very simply explain some beautiful but otherwise complicated concepts. And it's sad that like if you Google plasma or like for plasma physics, like there's no videos. And just imagine if every one of those excellent teachers like your father or like Russ, even if they just chose one topic this year, just they're like, I'm gonna make the best video that I can on this topic. If every one of the great teachers did that, the internet would be replete. And it's already replete with great explanations, but it would be even more so with all the niche great explanations and like anything you wanna learn. And there's a self-interest to it in terms of teachers, in terms of even, so if you take Russ for example, it's not that he's teaching something, like he teaches his main thing, his thing he's deeply passionate about. And from a selfish perspective, it's also just like, I mean, it's like publishing a paper in a really, like nature has like letters, like accessible publication. It's just going to guarantee that your work, that your passion is seen by a huge number of people. Whatever the definition of huge is, it doesn't matter. It's much more than it otherwise would be. And it's those lectures that tell early students what to be interested in. At the moment, I think students are disproportionately interested in the things that are well-represented on YouTube. So to any educator out there, if you're wondering, hey, I want more like grad students in my department, like what's the best way to recruit grad students? It's like, make the best video you can and then wait eight years. And then you're going to have a pile of like excellent grad students for that department. And one of the lessons I think your channel teaches is there's appeal of explaining just something beautiful, explaining it cleanly, technically, not doing a marketing video about why topology is great. Yeah, there's people interested in this stuff. I mean, one of the greatest channels, like it's not even a math channel, but the channel with greatest math content is Vsauce, who I interviewed. Imagine you were to propose making a video that explains the Banach-Tarski paradox substantively, right, not shying around, and maybe not describing things in terms of like the group theoretic terminology that you'd usually see in a paper, but the actual results that went into this idea of like breaking apart a sphere, proposing that to like a network TV station, saying, yeah, I'm going to do this in-depth talk of the Banach-Tarski paradox. I'm pretty sure it's going to reach 20 million people. It's like, get out of here. Like, no one cares about that. No one's interested in anything even anywhere near that. But then you have Michael's quirky personality around it and just people that are actually hungry for that kind of depth, then you don't need like the approval of some higher network. You can just do it and let the people speak for themselves. So I think, you know, if your father was to make something on plasma physics, or if we were to have like underactualized robotics, that would- Underactuated. Underactuated. Yes, not underactualized. It's funny, actualized. Underactuated robotics. Yeah, most robotics is underactualized currently. That's true. So even if it's things that you might think are niche, I bet you'll be surprised by how many people actually engage with it really deeply. Although I just psychologically watching him, I can't speak for a lot of people. I can speak for my dad. I think there's a little bit of a skill gap, but I think that could be overcome. That's pretty basic. None of us know how to make videos when we start. The first stuff I made was terrible in a number of respects. Like look at the earliest videos on any YouTube channel, except for Captain Disillusion. And they're all like terrible versions of whatever they are now. But the thing I've noticed, especially like with world experts, is it's the same thing that I'm sure you went through, which is like fear of like embarrassment. Like they definitely, it's the same reason. Like I feel that anytime I put out a video, I don't know if you still feel that, but like, I don't know, it's this imposter syndrome. Like who am I to talk about this? And that's true for like even things that you've studied for like your whole life. I don't know, it's scary to post stuff on YouTube. It is scary. I honestly wish that more of the people who had that modesty to say who am I to post this were the ones actually posting it. They're posting it, that's right. I mean, the honest problem is like a lot of the educational content is posted by people who like were just starting to research it two weeks ago and are on a certain schedule, and who maybe should think like who am I to explain, choose your favorite topic, quantum mechanics or something. And the people who have the self-awareness to not post are probably the people also best positioned to give a good, honest explanation of it. That's why there's a lot of value in a channel like Numberphile, where they basically trap a really smart person and force them to explain stuff on a brown sheet of paper. But of course, that's not scalable as a single channel. If there's anything beautiful that it could be done is people take it in their own hands, educators. Which is again, circling back, I do think the pandemic will serve to force a lot of people's hands. You're gonna be making online content anyway. It's happening, right? Just hit that publish button and see how it goes. Yeah, see how it goes. The cool thing about YouTube is it might not go for a while, but like 10 years later, it'll be like, this is the thing, what people don't understand with YouTube, at least for now, at least that's my hope with it, is it's literally better than publishing a book in terms of the legacy. It will live for a long, long time. Of course, it's one of the things, I mentioned Joe Rogan before, it's kinda, there's a sad thing, because I'm a fan, he's moving to Spotify. Yeah, nine digit numbers will do that to you. But he doesn't really, he's one of the person that doesn't actually care that much about money. Like having talked to him, it wasn't because of money, it's because he legitimately thinks that they're going to do a better job. So from his perspective, YouTube, you have to understand where they're coming from, YouTube has been cracking down on people who they, Joe Rogan talks to Alex Jones and conspiracy theories and stuff, and YouTube is really careful with that kind of stuff, and that's not a good feeling. And Joe doesn't feel like YouTube is on his side. He's often has videos that they don't put in trending that are obviously should be in trending because they're nervous about if this, is this content going to upset people, all that kind of stuff, have misinformation, and that's not a good place for a person to be in, and Spotify is giving them, we're never going to censor you, we're never going to do that. But the reason I bring that up, whatever you think about that, I personally think that's bullshit because podcasting should be free and not constrained to a platform, it's pirate radio, what the hell, you can't, as much as I love Spotify, you can't just, you can't put fences around it. But anyway, the reason I bring that up is Joe's gonna remove his entire library from YouTube. Whoa, really? I didn't know that. His full length, the clips are gonna stay, but the full length videos are all, I mean, made private or deleted, that's part of the deal. And that's the first time where I was like, oh, YouTube videos might not live forever, things you find, okay, sorry. This is why you need IPFS or something where it's like, if there's a content link, are you familiar with this system at all? Right now, if you have a URL that points to a server, there's a system where the address points to content and then it's distributed. So you can't actually delete what's at an address because it's content addressed. And as long as there's someone on the network who hosts it, it's always accessible at the address that it once was. But I mean, that raises a question. I'm not gonna put you on the spot, but somebody like Vsauce, right? Spotify comes along and gives him, let's say $100 billion, okay? Let's say some crazy number and then removes it from YouTube, right? It's made me, I don't know, for some reason I thought YouTube was forever. I don't think it will be. I mean, another variant that this might take is like that you fast forward 50 years and Google or Alphabet isn't the company that it once was and it's kind of struggling to make ends meet and it's been supplanted by whoever wins on the AR game or whatever it might be. And then they're like, you know, all of these videos that we're hosting are pretty costly. So we're gonna start deleting the ones that aren't watched that much and tell people to try to back them up on their own or whatever it is. Or even if it does exist in some form forever, it's like if people are not habituated to watching YouTube in 50 years, they're watching something else, which seems pretty likely. Like it would be shocking if YouTube remained as popular as it is now indefinitely into the future. So it won't be forever. Makes me sad still, but, cause it's such a nice, it's just like you said of the canonical videos. Sorry, I didn't mean to interrupt. Do you know, you should get Juan Bennett on the thing and then talk to him about permanence. I think you would have a good conversation. Who's that? So he's the one that founded this thing called IPFS that I'm talking about. And if you have him talk about basically what you're describing, like, oh, it's sad that this isn't forever, then you'll get some articulate pontification around it. Yeah. That's like been pretty well thought through. But yeah, I do see YouTube, just like you said, as a place, like what your channel creates, which is like a set of canonical videos on a topic. Now others could create videos on that topic as well, but as a collection, it creates a nice set of places to go if you're curious about a particular topic. And it seems like coronavirus is a nice opportunity to put that knowledge out there in the world at MIT and beyond. I have to talk to you a little bit about machine learning, deep learning, and so on. Again, we talked about last time, you have a set of beautiful videos on neural networks. Let me ask you first, what is the most beautiful aspect of neural networks and machine learning to you? From making those videos, from watching how the field is evolving, is there something mathematically or in applied sense just beautiful to you about them? Well, I think what I would go to is the layered structure and how you can have, what feel like qualitatively distinct things happening going from one layer to another, but that are following the same mathematical rule. Because you look at it as a piece of math, it's like you got a non-linearity and then you've got a matrix multiplication. That's what's happening on all the layers. But especially if you look at some of the visualizations that Chris Ola has done with respect to convolutional nets that have been trained on ImageNet, trying to say, what does this neuron do? What does this family of neurons do? What you can see is that the ones closer to the input side are picking up on very low level ideas like the texture. And then as you get further back, you have higher level ideas like, where are the eyes in this picture? And then how do the eyes form like an animal? Is this animal a cat or a dog or a deer? You have this series of qualitatively different things happening, even though it's the same piece of math on each one. So that's a pretty beautiful idea that you can have like a generalizable object that runs through the layers of abstraction, which in some sense constitute intelligence, is having those many different layers of an understanding to something. You have form abstractions in a automated way. Exactly, it's automated abstracting, which I mean, that just feels very powerful. And the idea that it can be so simply mathematically represented. I mean, a ton of like modern in-mouth research seems a little bit like you do a bunch of ad hoc things, then you decide which one worked and then you retrospectively come up with the mathematical reason that it always had to work. But who cares how you came to it? When you have like that elegant piece of math, it's hard not to just smile seeing it work in action. Well, and we talked about topology before, but one of the really interesting things is beginning to be investigated under kind of the field of like science and deep learning, which is like the craziness of the surface that is trying to be optimized in neural networks. I mean, the amount of local minima, local optima there is in the surfaces, and somehow a dumb gradient descent algorithm is able to find really good solutions. That's like, that's really surprising. Well, so on the one hand it is, but also it's like not, it's not terribly surprising that you have these interesting points that exist when you make your space so high dimensional. Like GPT-3, what did it have? 175 billion parameters. So it doesn't feel as mesmerizing to think about, oh, there's some surface of intelligent behavior in this crazy high dimensional space. Like there's so many parameters that of course, but what's more interesting is like, how is it that you're able to efficiently get there? Which is maybe what you're describing that something as dumb as gradient descent does it. But like the reason the gradient descent works well with neural networks and not just, choose however you want to parameterize this space and then like apply gradient descent to it, is that that layered structure lets you decompose the derivative in a way that makes it computationally feasible. Yeah, it's just that there's so many good solutions, probably infinitely many good solutions, not best solutions, but good solutions. That's what's interesting. It's similar to Steven Wolfram has this idea of like, if you just look at all space of computations, of all space of basically algorithms, that you'd be surprised how many of them are actually intelligent. Like if you just randomly pick from the bucket, that's surprising. I tend to think like a tiny, tiny minority of them would be intelligent. But his sense is like, it seems weirdly easy to find computations that do something interesting. Well, okay, so that, from like a Kolmogorov complexity standpoint, almost everything will be interesting. What's fascinating is to find the stuff that's describable with low information, but still does interesting things. Like one fun example of this, you know, Shannon's noisy coding theorem, noisy coding theorem and information theory, that basically says, if I wanna send some bits to you, maybe some of them are gonna get flipped. There's some noise along the channel. I can come up with some way of coding it that's resilient to that noise, that's very good. And then he quantitatively describes what very good is. What's funny about how he proves the existence of good error correction codes, is rather than saying like, here's how to construct it, or even like a sensible non-constructive proof. The nature of his non-constructive proof is to say, if we chose a random encoding, it would be almost at the limit, which is weird, because then it took decades for people to actually find any that were anywhere close to the limit. And what his proof was saying is choose a random one, and it's like the best kind of encoding you'll ever find. But what that tells us is that sometimes when you choose a random element from this ungodly huge set, that's a very different task from finding an efficient way to actively describe it. Because in that case, the random element, to actually implement it as a bit of code, you would just have this huge table of like, telling you how to encode one thing into another that's totally computationally infeasible. So on the side of like, how many possible programs are interesting in some way? It's like, yeah, tons of them. But the much, much more delicate question is when you can have a low information description of something that still becomes interesting. And thereby, that kind of gives you a blueprint for how to engineer that kind of thing. Right. Chaos theory is another good instance there where it's like, yeah, a ton of things are hard to describe, but how do you have ones that have a simple set of governing equations that remain like arbitrarily hard to describe? Well, let me ask you, you mentioned GPT-3. It's interesting to ask, what are your thoughts about the recently released OpenAI GPT-3 model that I believe is already trying to learn how to communicate like Grant Sanderson? You know, I think I got an email a day or two ago about someone who wanted to try to use GPT-3 with Manim, where you would like give it a high level description of something and then it'll like automatically create the mathematical animation. Like, trying to put me out of a job here. I mean, it probably won't put you out of a job, but it'll create something visually beautiful for sure. I would be surprised if that worked as stated, but maybe there's like variants of it like that you can get to. I mean, like a lot of those demos, it's interesting. I think there's a lot of failed experiments, like depending on how you prime the thing, you're going to have a lot of failed, certainly with code and with program synthesis, most of it won't even run. But eventually I think if you pick the right examples, you'll be able to generate something cool. And I think that even that's good enough, even though if you're being very selective, it's still cool that something can be generated. Yeah, that's huge value. I mean, think of the writing process. Sometimes a big part of it is just getting a bunch of stuff on the page and then you can decide what to whittle down to. So if it can be used in like a man-machine symbiosis where it's just giving you a spew of potential ideas that then you can refine down, like it's serving as the generator and then the human serves as the refiner, that seems like a pretty powerful dynamic. Yeah, have you gotten a chance to see any of the demos like on Twitter? Is there a favorite you've seen? Oh, my absolute favorite. Yeah, so Tim Bley, who runs a channel called Acapella Science, he was like tweeting a bunch about playing with it. And so GPT-3 was trained on the internet from before COVID. So in a sense, it doesn't know about the coronavirus. So what he seeded it with was just a short description about like a novel virus emerges in Wuhan, China and starts to spread around the globe. What follows is a month by month description of what happens, January colon, right? That's what he seeds it with. So then what GPT-3 generates is like January, then a paragraph of description, February and such. And it's the funniest thing you'll ever read because it predicts a zombie apocalypse, which of course it would because it's trained on like the internet data. Yeah, the internet. And it's full of zombie stories. But what you see unfolding is a description of COVID-19 if it were a zombie apocalypse. And like the early aspects of it are kind of shockingly in line with what's reasonable. And then it gets out of hand so quickly. And the other flip side of that is I wouldn't be surprised if it's onto something at some point here. You know, 2020 has been full of surprises. Who knows, like we might all be in like this crazy militarized zone as it predicts just a couple months off. Yeah, I think there's definitely an interesting tool of storytelling. It has struggled with mathematics, which is interesting, or just even numbers. It's able to, it's not able to generate like patterns, you know, like you give it in like five digit numbers and it's not able to figure out the sequence, you know, or like, I didn't look in too much, but I'm talking about like sequences like the Fibonacci numbers and to see how far it can go. Because obviously it's leveraging stuff from the internet and it starts to lose it, but it is also cool that I've seen it able to generate some interesting patterns that are mathematically correct. Yeah, I honestly haven't dug into like what's going on within it in a way that I can speak intelligently to. I guess it doesn't surprise me that it's bad at numerical patterns because, I mean, maybe I should be more impressed with it, but like that requires having a weird combination of intuitive and formulaic worldview. So you're not just going off of intuition when you see Fibonacci numbers, you're not saying like, intuitively, what do I think will follow the 13? Like I've seen patterns a lot where like 13s are followed by 21s. Instead it's the, like the way you're starting to see a shape of things is by knowing what hypotheses to test, where you're saying, oh, maybe it's generated based on the previous terms, or maybe it's generated based on like multiplying by a constant or whatever it is. You like have a bunch of different hypotheses and your intuitions are around those hypotheses, but you still need to actively test it. And it seems like GPT-3 is extremely good at, like that sort of pattern matching recognition that usually is very hard for computers, that is what humans get good at through expertise and exposure to lots of things. It's why it's good to learn from as many examples as you can, rather than just from the definitions. It's to get that level of intuition, but to actually concretize it into a piece of math, you do need to like test your hypotheses. And if not prove it, like have an actual explanation for what's going on, not just a pattern that you've seen. Yeah, and, but then the flip side to play devil's advocate, that's a very kind of probably correct, intuitive understanding of just like we said, a few layers creating abstractions, but it's been able to form something that looks like a compression of the data that it's seen that looks awfully a lot like it understands what the heck it's talking about. Well, I think a lot of understanding is, like I don't mean to denigrate pattern recognition. Pattern recognition is most of understanding and it's super important and it's super hard. And so like when it's demonstrating this kind of real understanding, compressing down some data, like that might be pattern recognition at its finest. My only point would be that, like what differentiates math, I think, to a large extent is that the pattern recognition isn't sufficient and that the kind of patterns that you're recognizing are not like the end goals, but instead they are the little bits and paths that get you to the end goal. So that's only true for mathematics in general. It's an interesting question if that might, for certain kinds of series of numbers, it might not be true. Like you might, because that's the basic, you know, like Taylor's, like certain kinds of series, it feels like compressing the internet is enough to figure out, because those patterns in some form appear in the text somewhere. Well, I mean, there's all sorts of wonderful examples of false patterns in math. One of the earliest videos I put on the channel was talking about you kind of dividing a circle up using these chords and you see this pattern of one, two, four, eight, 16. And I was like, okay, pretty easy to see what that pattern is. It's powers of two. You've seen it a million times, but it's not powers of two. The next term is 31. And so it's like almost a power of two, but it's a little bit shy. And there's actually a very good explanation for what's going on, but I think it's a good test of whether you're thinking clearly about mechanistic explanations of things, how quickly you jump to thinking it must be powers of two. Because the problem itself, there's really no good way to, I mean, there can't be a good way to think about it as doubling a set because ultimately it doesn't. But even before it starts to, it's not something that screams out as being a doubling phenomenon. So at best, if it did turn out to be powers of two, it would have only been so very subtly. And I think the difference between a math student making a mistake and a mathematician who's experienced seeing that kind of pattern is that they'll have a sense from what the problem itself is, whether the pattern that they're observing is reasonable and how to test it. And I would just be very impressed if there was any algorithm that was actively accomplishing that goal. Yeah, like a learning-based algorithm. Yeah, like a little scientist, I guess, basically. Yeah, it's a fascinating thought because GPT-3, these language models are already accomplishing way more than I've expected. So I'm learning not to doubt. I bet we'll get there. Yeah, I'm not saying I'd be impressed, but surprised. I'll be impressed, but I think we'll get there on algorithms doing math like that. So one of the amazing things you've done for the world is to some degree open sourcing the tooling that you use to make your videos with Manum, this Python library. Now, it's quickly evolving because I think you're inventing new things every time you make a video. In fact, I've been working on playing around with some, I wanted to do like an ode to 3Blue1Brown. I love playing Hendrix. I wanted to do like a cover of a concept I wanted to visualize and use Manum. And I saw that you had like a little piece of code on like Mobius strip. And I tried to do some cool things with spinning a Mobius strip, like continue twisting it, I guess is the term. And it was easier to, it was tough. So I haven't figured out yet. So I guess the question I want to ask is so many people love it, that you've put that out there. They want to do the same thing as I do with Hendrix. They want to cover it. They want to explain an idea using the tool, including Russ. How would you recommend they try to, I'm very sorry. They try to go by, about it. And what kind of choices should they choose to be most effective? That I can answer. So I always feel guilty if this comes up because I think of it like this scrappy tool. That's like a math teacher who put together some code. People asked what it was. So they made it open source and they kept scrapping it together. And there's a lot of things about it that make it harder to work with than it needs to be that are a function of like me not being a software engineer. I've put some work this year trying to like make it better and more flexible that is still just kind of like a work in process. One thing I would love to do is just get my act together about properly integrating with what like the community wants to work with and like what stuff I work on and making that not like deviate. And just like actually fostering that community in a way that I've been like shamefully neglectful of. So I'm just always guilty if it comes up. So let's put that guilt aside. Just kind of zen like. All right, zen like. I'll pretend like it isn't terrible. For someone like Russ, I think step one is like make sure that what you're animating should be done so programmatically. Because a lot of things maybe shouldn't. Like if you're just making a quick graph of something, if it's a graphical intuition that maybe has a little motion to it, use Desmos, use Grapher, use Geogebra, use Mathematica. Certain things that are like really oriented around graphs. Geogebra is kind of cool. It's amazing. You can get very, very far with it. And in a lot of ways, like it would make more sense for some stuff that I do to just do in Geogebra. But I kind of have this cycle of liking to try to improve Manim by doing videos and such. So do as I say, not as I do. The original like thought I had in making Manim was that there's so many different ways of representing functions other than graphs. In particular, things like transformations, like use movement over time to communicate relationships between inputs and outputs instead of like X direction and Y direction. Or like vector fields or things like that. So I wanted something that was flexible enough that you didn't feel constrained into a graphical environment. By graphical, I mean like graphs with like X coordinate, Y coordinate kind of stuff. But also make sure that you're taking advantage of the fact that it's programmatic. You have loops, you have conditionals, you have abstraction. If any of those are like well fit for what you want to teach to have a scene type that you tweak a little bit based on parameters or to have conditionals so that things can go one way or another or loops so that you can create these things of like arbitrarily increasing complexity. That's the stuff that's like meant to be animated programmatically. If it's just like writing some text on the screen or shifting around objects or something like that, things like that, you should probably just use Keynote. You'd be a lot simpler. So try to find a workflow that distills down that which should be programmatic into Manim and that which doesn't need to be into like other domains. Again, do as I say, not as I do. I mean, Python is an integral part of it. Just for the fun of it, let me ask, what's your most and least favorite aspects of Python? Ooh, most and least. I mean, I love that it's like object-oriented and functional, I guess, that you can kind of like get both of those benefits for how you structure things. So if you would just want to quickly whip something together, the functional aspects are nice. It's your primary language, like for programmatically generating stuff? Yeah, it's home for me. Python is home. It's home. Yeah. Sometimes you travel, but it's home. Got it. It's home. I mean, the biggest disadvantage is that it's slow. So when you're doing computationally intensive things, either you have to like think about it more than you should, how to make it efficient, or it just like takes long. Do you run into that at all? Like with your work? Well, so certainly old Manim is like way slower than it needs to be because of how it renders things on the back end is like kind of absurd. I've rewritten things such that it's all done with like shaders in such a way that it should be just like live and actually like interactive while you're coding it, if you want to. You know, you have like a 3D scene, you can move around, you can have elements respond to where your mouse is or things. That's not something that user of a video is going to get to experience because there's just a play button and a pause button. But while you're developing, that can be nice. So it's gotten better in speed in that sense, but that's basically because the hard work is being done in the language that's not Python, but GLSL, right? But yeah, there are some times when it's like a, there's just a lot of data that goes into the object that I want to animate that then it just like Python is slow. Well, let me ask, quickly ask, what do you think about the Walrus operator, if you're familiar with it at all? The reason it's interesting, there's a new operator in Python 3.8. I find it psychologically interesting because the toxicity over it led Guido to resign, to step down from his- Is that actually true? Or was it like, there's a bunch of surrounding things that also, was it actually the Walrus operator that- Well, it was an accumulation of toxicity, but that was the most toxic one. Like the discussion, that's the most number of Python core developers that were opposed to Guido's decision. He didn't particularly, I don't think, cared about it either way. He just thought it was a good idea, this is where you approve it. And like the structure of the idea of a BDFL is like, you listen to everybody, hear everybody out, you make a decision and you move forward. And he didn't like the negativity that burdened him after that. People like some parts of the benevolent dictator for life mantra, but once the dictator does things different than you want, suddenly dictatorship doesn't seem so great. Yeah, I mean, they still liked it, he just couldn't, because he truly is the B in the benevolent. He really is a nice guy. I mean, and I think he can't, it's a lot of toxicity, it's difficult, it's a difficult job. That's why Alonis Torvald is perhaps the way he is. You have to have a thick skin to fight off, fight off the warring masses. It's kind of surprising to me how many people can like threaten to murder each other over whether we should have braces or not, or whether, like, it's incredible. Yeah, I mean, that's my knee-jerk reaction to the Walrus Operators. Like, I don't actually care that much. Either way, I'm not going to get personally passionate. My initial reaction was like, yeah, this seems to make things more confusing to read. But then again, so does list comprehension until you're used to it. So, like, if there's a use for it, great. If not, great. But like, let's just all calm down about our spaces versus tabs debates here and like, be chill. Yeah, to me, it just represents the value of great leadership, even in open source communities. Does it represent that? If he stepped down as a leader? Well, he fought for it. No, he got it passed. I guess, but I guess, sure. It could represent multiple things too. It can represent like failed dictatorships, or it can represent a lot of things. But to me, great leaders take risks, even if it's a mistake at the end. Like, you have to make decisions. The thing is, this world won't go anywhere if you constantly, if whenever there's a divisive thing, you wait until the division is no longer there. Like, that's the paralysis we experienced with like Congress and political systems. It's good to be slow when there's indecision, when there's people disagree, it's good to take your time. But like at a certain point, it results in paralysis and you just have to make a decision. The background of the site, whether it's yellow, blue, or red can cause people to like go to war over each other. I've seen this with design. People are very touchy on color. Color choices. At the end of the day, just make a decision and go with it. I think that's what the Walrus operator represents to me. It represents the fighter pilot instinct of like quick action is more important than- Than just like carrying everybody out and really thinking through it, because that's going to lead to paralysis. Yeah, like if that's the actual case, that it's something where you're consciously hearing people's disagreement, disagreeing with that disagreement, and saying he wants to move forward anyway. That's an admirable aspect of leadership. So we don't have much time, but I want to ask just, because it's some beautiful mathematics involved. 2020 brought us a couple of, in the physics world, theories of everything. Eric Weinstein kind of, I mean, he's been working for probably decades, but he put out this idea of geometric unity, or started sort of publicly thinking and talking about it more. Stephen Wolfram put out his physics project, which is kind of this hypergraph view of a theory of everything. Do you find interesting, beautiful things to these theories of everything? What do you think about the physics world and sort of the beautiful, interesting, insightful mathematics in that world? Whether we're talking about quantum mechanics, which you touched on in a bunch of your videos a little bit, or quaternions, like just the mathematics involved, or the general relativity, which is more about surfaces and topology, all that stuff. Well, I think as far as popularized science is concerned, people are more interested in theories of everything than they should be. Because the problem is, whether we're talking about trying to make sense of Weinstein's lectures or Wolfram's project, or let's just say, listening to Witten talk about string theory, whatever proposed path to a theory of everything, you're not actually gonna understand it. Some physicists will, but like, you're just not actually gonna understand the substance of what they're saying. What I think is way, way more productive is to let yourself get really interested in the phenomena that are still deep, but which you have a chance of understanding. Because the path to getting to like, even understanding what questions these theories of everything are trying to answer involves like walking down that. I mean, I was watching a video before I came here about, from Steve Mould, talking about why sugar polarizes light in a certain way. So fascinating, like really, really interesting. It's not like this novel theory of everything type thing, but to understand what's going on there really requires digging in in depth to certain ideas. And if you let yourself think past what the video tells you about, what does circularly polarized light mean and things like that, it actually would get you to a pretty good appreciation of like two state states in quantum systems in a way that just trying to read about like, oh, what's the, what are the hard parts about resolving quantum field theories with general relativity is never gonna get you. So as far as popularizing science is concerned, like the audience should be less interested than they are in theories of everything. The popularizers should be less emphatic than they are about that. For like actual practicing physicists, I might be the case, maybe more people should think about fundamental questions, but. It's difficult to create like a three blue, one brown video on theory of everything. So basically we should really try to find the beauty in mathematics or physics by looking at concepts that are like within reach. Yeah, I think that's super important. I mean, so you see this in math too with the big unsolved problems. So like the clay millennium problems, Riemann hypothesis. Have you ever done a video on Fermat's last theorem? No, I have not yet, no. But if I did, do you know what I would do? I would talk about proving Fermat's last theorem in the specific case of N equals three. Is that still accessible though? Yes, actually, barely. Mathologer might be able to do like a great job on this. He does a good job of taking stuff that's barely accessible and making it. But the core ideas of proving it for N equals three are hard but they do get you real ideas about algebraic number theory. It involves looking at a number field that's, it lives in the complex plane. It looks like a hexagonal lattice and you start asking questions about factoring numbers in this hexagonal lattice. So it takes a while, but I've talked about this sort of like lattice arithmetic in other contexts. And you can get to a okay understanding of that. And the things that make Fermat's last theorem hard are actually quite deep. And so the cases that we can solve it for, it's like you can get these broad sweeps based on some hard but like accessible bits of number theory. But before you can even understand why the general case is as hard as it is, you have to walk through those. And so any other attempt to describe it would just end up being like shallow and not really productive for the viewer's time. I think the same goes for most unsolved problem type things where I think, as a kid, I was actually very inspired by the twin prime conjecture that totally sucked me in. It's this thing that was understandable. I kind of had this dream like, oh, maybe I'll be the one to prove the twin prime conjecture. And new math that I would learn would be viewed through this lens of like, oh, maybe I can apply it to that in some way. But you sort of mature to a point where you realize you should spend your brain cycles on problems that you will see resolved, because then you're gonna grow to see what it feels like for these things to be resolved, rather than spending your brain cycles on something where it's not gonna pan out. And the people who do make progress towards these things, like James Maynard is a great example here of like young creative mathematician who pushes in the direction of things like the twin prime conjecture, rather than hitting that head on, just see all the interesting questions that are hard for similar reasons, but become more tractable and let themselves really engage with those. So I think people should get in that habit. I think the popularization of physics should encourage that habit through things like the physics of simple everyday phenomena, because it can get quite deep. And yeah, I think I've heard a lot of the interest that people send me messages asking to explain Weinstein's thing, or asking to explain Wolfram's thing. One, I don't understand them, but more importantly, it's too big a bite to- You shouldn't be interested in those, right? The giant sort of ball of interesting ideas. There's probably a million of interesting ideas in there that individually could be explored effectively. And to be clear, you should be interested in fundamental questions. I think that's a good habit to ask like what the fundamentals of things are. But I think it takes a lot of steps to, like certainly you shouldn't be trying to answer that unless you actually understand quantum field theory and you actually understand general relativity. That's the cool thing about like your videos, people who haven't done mathematics. Like if you really give it time, watch it a couple of times and like try to reason about it, you can actually understand the concept that's being explained. And it's not a coincidence that the things I'm describing aren't like the most up-to-date progress on the Riemann hypothesis cousins, or like there's context in which the analog of the Riemann hypothesis has been solved in like more discrete feeling, finite settings that are more well-behaved. I'm not describing that because it just takes a ton to get there. And instead I think it'll be like productive to have an actual understanding of something that you can pack into 20 minutes. I think that's beautifully put. Ultimately that's where like the most satisfying thing is when you really understand. Yeah, really understand. Build a habit of feeling what it's like to actually come to resolution. Yeah, yeah. As opposed to, which it can also be enjoyable, but just being in awe of the fact that you don't understand anything. Yeah, that's not like, I don't know, maybe people get entertainment out of that, but it's not as fulfilling as understanding. You won't grow. Yeah, but also just the fulfilling. It really does feel good when you first don't understand something and then you do. That's a beautiful feeling. Hey, let me ask you one last time it got awkward and weird about a fear of mortality, which you made fun of me of. But let me ask you on the other absurd question is, what do you think is the meaning of our life, of meaning of life? I'm sorry if I made fun of you about mortality. No, you didn't. I'm just joking. It was great. I don't think life has a meaning. I think like meaning, I don't understand the question. I think meaning is something that's ascribed to stuff that's created with purpose. There's a meaning to like this water bottle label and that someone created it with a purpose of conveying meaning. And there was like one consciousness that wanted to get its ideas into another consciousness. Most things don't have that property. It's a little bit like if I ask you, like, what is the height? All right, so it's all relative. Yeah, you'd be like the height of what? You can't ask what is the height without an object. You can't ask what is the meaning of life without like an intentful consciousness putting it, well, I guess I'm revealing I'm not very religious. But you know, the mathematics of everything seems kind of beautiful. It seems like there's some kind of structure relative to which, I mean, you could calculate the height. Well, so, but what I'm saying is I don't understand the question, what is the meaning of life, in that I think people might be asking something very real. I don't understand what they're asking. Are they asking like, why does life exist? Like, how did it come about? What are the natural laws? Are they asking, as I'm making decisions day by day for what should I do, what is the guiding light that inspires like, what should I do? I think that's what people are kind of asking. But also like, why, the thing that gives you joy about education, about mathematics, what the hell is that? Like, what? Interactions with other people. Interactions with like-minded people, I think is the meaning of, in that sense. So bringing others joy, essentially. Like, in something you've created, it connects with others somehow. And the same, and the vice versa. I think that is what, when we use the word meaning to mean like, you're sort of filled with a sense of happiness and energy to create more things. Like, I have so much meaning taken from this. Like that, yeah, that's what fuels my pump, at least. So a life alone on a deserted island would be kind of meaningless. Yeah, you wanna be alone together with someone. I think we're all alone together. I think there's no better way to end it, Grant. You've been, first time we talked, it was amazing. Again, it's a huge honor that you make time for me. I appreciate talking with you. Thanks, man. Awesome. Thanks for listening to this conversation with Grant Sanderson. And thank you to our sponsors, Dollar Shave Club, DoorDash, and Cash App. Click the sponsor links in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Richard Feynman. I have a friend who's an artist and is sometimes taken a view which I don't agree with very well. He'll hold up a flower and say, look how beautiful it is. And I'll agree. Then he says, I, as an artist, can see how beautiful this is, but you, as a scientist, take this all apart and it becomes a dull thing. And I think he's kind of nutty. First of all, the beauty that he sees is available to other people and to me too, I believe. Although I may not be quite as refined aesthetically as he is, I can appreciate the beauty of a flower. At the same time, I see much more about the flower than he sees. I can imagine the cells in there, the complicated actions inside, which also have a beauty. I mean, it's not just beauty at this dimension at one centimeter, there's also beauty at smaller dimensions, the inner structure, also the processes. The fact that the colors in the flower evolved in order to attract insects to pollinate it is interesting. It means that insects can see the color. It adds a question. Does this aesthetic sense also exist in the lower forms? Why is it aesthetic? All kinds of interesting questions which the science knowledge only adds to the excitement, the mystery and the awe of a flower. It only adds. I don't understand how it subtracts. Thank you for listening and hope to see you next time.

https://youtu.be/U_6AYX42gkU

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David Wolpe: Judaism | Lex Fridman Podcast #270

The following is a conversation with Rabbi David Welpy, someone who I have been a fan of for many years, for the kindness in his heart, the strength of his character, and the kind of friends he keeps and talks with, many of whom disagree with him but love him nevertheless, including the late Christopher Hitchens. I will have many conversations like these in the future about religion, about Islam, Christianity, Judaism, Hinduism, Buddhism, and others, looking to understand and celebrate the culture, the tradition, and the beauty of the people who practice these religions. I will of course not shy away from the difficult topics. I will talk both about hate and love, about war and peace. This conversation was recorded more than three weeks ago. Please allow me this time to speak on what has been on my mind. If this is not interesting to you, please skip. I totally understand. Some people asked me to say a few words on the war in Ukraine. I think my words are worth little, but perhaps let me try. I considered doing a long solo episode on this war. I tried several times, but it is too personal for now. To give you context, I have been talking to refugees, friends, loved ones, in Ukraine, in Russia, in Poland, Slovakia, Moldova, Romania, even UK, Germany, Canada, India, China, and of course the United States. Some of them crying, or angry, or confused, or scared. I am helping as best as I can privately, and I am hoping to help in the future by traveling to Ukraine and Russia and celebrating the humanity and the beauty of the people in this region. This was all set up both for Ukraine and Russia trips before 2022, including conversations with scientists, artists, athletes, leaders, and just regular folks who are equally if not more fascinating to me. For now, it has become much more difficult, but I will keep trying to find a way. I was born in the Soviet Union. My roots are both Ukrainian and Russian. And today, and until the day I die, I am an American. I am proud of all of this. I hope to keep celebrating the culture and the incredible human beings that make up these nations and humanity as a whole. We are all one people. We are in this together. That is how I feel about the people of these nations. Now let me speak about those in the seats of power. I condemn all actions of leaders who play geopolitical games on the world stage disregarding the costs paid in human suffering on the scale of millions. For this reason, I condemn Vladimir Putin's invasion of Ukraine. And I condemn many of the military interventions by the superpowers of the world, including by my country, the country I love, the United States, that after World War II has intervened in over 40 nations, with many studies finding that the United States is culpable for an unfathomable number of civilian deaths. I condemn all heads of state who needlessly wage wars, watching young men and women burn in the fires they started. I don't understand how humans can be so cruel to each other, or rather I understand, but I believe in a future world where this is no longer true. Let me also say a few words of what I hope to do with this podcast. I want to explore the full complexity and beauty of human nature. I believe each of us are capable of good and evil, and I want to understand how the mind and the circumstance lead one to choose the former path or the latter. And I believe conversation is one of the best ways to work toward this understanding. For that, I think I have to not only talk to the most inspiring humans in the world, but also to the most controversial. I will speak with many people who I disagree with. Politicians, activists, CEOs, heads of state, with very different opinions on the world. I will try hard to challenge their ideas without closing my mind to the depth and complexity of their perspective and their humanity. My presence in the same room with wildly different people will make it easy for the media and the internet to pick and choose clips and snapshots attacking me for being a shill for one side or the other. I can't defend this point, except to say that I'm a shill for no one, and that I hope you see the strength of my integrity, that I won't be influenced by any of them, no matter how rich, powerful, or charismatic they are. Like the poem If by Roger Kipling says, If you can talk with crowds and keep your virtue, Or walk with kings, nor lose the common touch, If neither foes nor loving friends can hurt you, If all men count with you, but none too much. This is a really, really important thing to me that I try to live by, that all human beings count with me the same. People have criticized me for wanting to have some of these conversations, like with Vladimir Putin and Vladimir Zelensky, and for times in the past speaking about them without the seriousness the topic deserves. For this, I would sincerely like to apologize. I'm disappointed, even ashamed, of my frequent ineloquence on these topics. I will work hard to do better. When I'm joking, it should be clear that it's a joke, and hopefully actually funny. When I'm being serious, I should speak with care and rigor. I've now done many hundreds of hours of podcast conversation. Despite my frequent failures in speaking, I hope you know where my heart is. Unfortunately, I think people will take clips of me and use them to attack me. This will happen more and more. I guess there's nothing I can do but send them my love, and in the meantime, try to be a better person and a better interviewer. Let me also say that I like humor, especially dark humor. I like being silly and not taking myself seriously. I will keep taking risks with that, all with the goal of having fun and celebrating humanity at its most absurd and most beautiful. I will occasionally dress up in strange and weird outfits to celebrate the absurdity of life. I will hang out, break bread, and joke with all kinds of people. I don't have to agree with them to laugh with them, in order to escape for a brief moment the tension, the conflict, the hatred in the world. Humor just might save this little chaotic little civilization of ours. I love the Ukrainian people. I love the Russian people. And of course, I love my fellow Americans, Californians and Midwesterners, New Yorkers and Texans. I love humans. I love life. And I want to share that love with others, with you. If I messed it up, I'm really, really sorry. I'm trying my best. I have no agenda, and no one telling me what to do. I feel like the luckiest guy in the world to have all these opportunities, and I'm deeply grateful to be alive and to share that joy with other amazing people around me. Thank you for your support. For all the love you've sent my way, I will work my ass off to not disappoint you. I love you all. This is a Lex Friedman podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with David Welpy. Let's start with a big question. According to Judaism, who is God? It's difficult because Judaism, like any tradition that is thousands of years old and encompasses so many different lands and languages and thinkers, it doesn't give a single answer to even simple questions. And to large questions, it certainly doesn't give a single answer. Although Judaism was responsible for introducing the monotheistic idea to the world, it doesn't mean that it's one idea. So if you take Maimonides, the greatest sage in the Jewish tradition, medieval philosopher, he would say that God is an omnipotent, benevolent, intangible, unimaginable God. In fact, he said you can't say what God is, only what God is not, because you have to emphasize—could talk more about that—but basically you have to emphasize the unknowability of God. You have a modern philosopher like Heschel, who says that God is a God of pathos, a God of deep feeling, which probably would make Maimonides shiver if he heard such a description. And if you look in the Bible, God is always regretting or having human emotions. So there are so many different kinds of depictions and ideas, and there is this tremendous tension between transcendence and imminence. That is, in the Jewish tradition, God is exquisitely close, God is imminent. In the Talmud's words, God is as close as your mouth is to your ear. In other words, whatever you say, God hears it. And yet at the same time, God is unfathomably distant. Sometimes when I speak to high schoolers, I will say, in the Jewish tradition, think of it this way. When you were two years old, you had no idea what it was to be a 15-year-old. Not only did you not know, but you didn't know what you didn't know. We conceive of God as being more, the distance between God and human beings is far greater than the distance between a two-year-old and a 15-year-old. So when we speak about God, we have to acknowledge how limited we really are. So okay, you laid out a lot of fascinating things on the table. So one, the knowability of God. Then this idea of deep feeling, which again, can God be operating in the space of feelings too? It's the mouth and the ear of the senses. Can God be known? Can God be felt by this three-year-old in the analogy versus the teenager? So I will take refuge in a beautiful phrase from Martin Buber, another Jewish theologian. He said, God cannot be expressed. God can only be addressed. In other words, you can speak to God. You can feel a sense of God, but can you begin to comprehend or know God? No. Yosef Cosby, I'm pulling in a couple of early Jewish philosophers. He said, to know God, I would have to be God. But can we get close? Is it useful or is it a distraction to visualize things, to embody, to create, to attach to the stories some kind of visualizations in our mind? For example, gender, he versus she, things like this, or old man in the sky kind of feeling. So it's almost inevitable, but I think ultimately you try to transcend it. This was the great, we just read this actually in synagogue, the story of the golden calf. And the story is that human beings found it impossible to not have a visualization because they had just come from Egypt and in the world of pagan worship, everything is, it's not that pagans thought that idol was actually God, but it represented visually what God was. And along comes this idea that God is actually not capable of being visualized, which is very difficult and it stretches the bounds of human comprehension, maybe even breaks them. So would you say that the proper way to operate as a human in relation to God is humility and that you're screwed, you're not able to basically know anything, almost anything? Well the reason that you're the salvation of this is that you can't, that you can't, I was going to say the reason you're not screwed, but then I thought somebody might be upset at a rabbi saying that. So I didn't say it and have not said it. But the reason you're not is that you don't have to have a comprehension of God. You have to have a relationship to God and those are not the same. I mean, to draw an analogy that is not far from perfect as most analogies are, but this one especially, you have relationships with people who are mysteries to you. You're a mystery to yourself. You can live and love somebody for 50 years and they can say something that surprises you, because ultimately we are trapped in here. And when a child first says I, we call that individuation, but what that really means is I now know that I am cut off from the minds of all other children and all other people. And so you have with God a more intimate relationship because you can believe that God is, you are known by God and you have a relationship to God despite the fact that you can't know God just as you can't know others. And some would say to have a good relationship, you want to be constantly surprised. Right. You don't want to know the thing. Well, the world, yes, the world that God created is constantly surprising. And by the way, the caveat to this, you know, when I had all these debates with Christopher Hitchens and he would always say that God is a greater tyrant than North Korea because it continues after your death. And the idea of being known by God is after all frightening if you think God knows what I think and so on, if your image of God is unloving. Can we jump to this? You had friendships and conversations with a lot of the fascinating figures of the past 20, 30 years of the great intellectuals, one of which perhaps one of the greats is Christopher Hitchens. What have you learned from your conversation, your friendship? So there are a lot of views he held that I really did not agree with, but he was a remarkable person. That was a good line about North Korea. He was full of incredibly good lines. Well, one of the things I learned was you can't win a debate with Christopher Hitchens. One of the reasons you can't win is because he has this British baritone and this ready wit that you can't triumph over laughter. It doesn't matter if your argument is better. If your quip is better, you win. And so I remember once we were arguing about free will and he said, well, I choose to believe in it. And everybody laughed and that was, despite the fact that that's not really an argument. Or like, I have free will because I don't have a choice. Right, exactly. And people should watch your conversation with him. It's great. I mean, it's a kind of David versus Goliath situation and you're quite masterful at using charisma and sweet talking with Christopher Hitchens. I also genuinely liked him. I mean, I spent a three hour limousine ride with him from one debate to another, from LA to San Diego. And the entire time he said, we just can't talk about religion. So we talked about literature and he gave me a long lecture about Scotch. He was inexhaustible. I mean, not only did he, I began, I wrote a couple of obituaries about him and one I began with the historian Keith Thomas said, there are two ways of achieving immortality by doing things worth remembering or saying things worth remembering. And by that standard, he did both. I mean, he went all around the world to all sorts of danger zones. He knew like the best bars everywhere from Kuala Lumpur, you know, to Beirut, to LA. And he could drink all night and write a 2000 word essay on the poetry of Yates and go to sleep. I remember before one of our debates in Boston, he was at the bar and he said, come have a drink. And I said, I'm going to have a drink before I go to debate with you. What are you crazy? And he said, just have a beer, it's water. So he really was a constant inexhaustible fountain of intrigue and interest. What kind of things, if you can remember, if you can mention, if you can admit to have him enlightening you or helping you change your mind about something in this world? So I think unrelated to Scotch. Yeah, unrelated to Scotch. He convinced me that the idea, I mean, I had my doubts about it and have my doubts about it, but he convinced me through many debates, and not only he, that the idea that religion makes people better is not, it's not ipso facto wrong, but it's a much, much more complicated argument than I wished it to be. So he is, however you conceive of the term, beauty. He's one of those, one of the more beautiful humans this weird little earth produced. So how do you explain the atheism combined with such a beautiful mind? So from your perspective of a man of faith, how do you think about that? So of the atheists that I have debated, I think about all of them somewhat differently. So I think that in some deep way, for example, Sam Harris is a religious personality. I don't even think that he would, he wouldn't like the word religious, but I don't even think that he would take issue with that. I think that he would say his is a purely material based spirituality, but I mean, his orientation towards meditation and appreciation of Buddhism, there's something deeply seeking spiritual about him. With Hitchens, I honestly, and I know that some of his fans will really not like this. It's not that he was any kind of closet believer, certainly not at all, but I almost feel as though he was less a passionate arguer against religion than he was, first of all, extremely upset by the forms that religion took in this world. And then once he trained his intellectual howitzers on a target, he had so much fun inventing new arguments and attacking it that I really believe he gets carried away sometimes by his own eloquence and intellectual range. So for example, the idea that you would call a book that religion poisons everything, I think he did that deliberately provocatively so that he could defend a proposition that obviously is indefensible, that it poisons everything. So I don't know. I think he had tremendous joie de vivre. That's what sums him up. This guy loved life in all of its manifestations and arguing against something that someone else believed was one of his greatest joys. Yeah. And of course, the practical aspect of that, he just saw the powerful and he challenged them with humor and so on. And you could argue perhaps that humor is the highest form of what humanity can achieve. Sometimes maybe us little humans take things a little too seriously, then sometimes we need to just laugh at it all, laugh at ourselves, and that's probably the purest form of wisdom. Auden, the poet, said, among the people that I like or admire, I can find no common quality, but among those I love, I can. All of them make me laugh. There you have it. Speaking of people that make you laugh, Sam Harris, because he actually has a really great sense of humor. He does. With a very cold and monotone delivery. He's another one that you had friends with, you have good conversations with. Where's your fundamental disagreements and agreements with Sam? Sam believes that religion is intellectually indefensible. He really believes it deep in his soul. And he gets angry at the idea that a proposition should be unchallenged if it offends his sense of logic. Yeah. So he cannot move on until this is dealt with. Nope. In fact, I did a podcast with Eric Weinstein, and then Sam did one. And Sam said, when I heard your podcast with David Wolpe, I learned stuff about what he thinks that I never learned in my conversations with him, because I can never let him make those unfounded assertions without challenging them, and you just let them go. And I think that there was something to that. It was like, he finds it hard to have a conversation about religion that doesn't arouse his real ire about the harm that he thinks religion does in the world. It's just more about the implementation of religion in the world as it is, versus the really fundamental... I think he also thinks it's fundamentally intellectually shoddy and disreputable. Faith. Yeah, faith. I don't know how to put this. I mean, they're both capable of separating their contempt for religion from the people that they have sitting in front of them. You mean Christopher Hitchens and Sam Harris? Yes, both of them. Okay, so you mentioned Eric Weinstein, people should listen to your conversation with Eric. It's a fascinating one, it's great. It's non-standard, it just goes all over the place in this humor and wit. It's great. So one interesting aspect that I also learned, perhaps not about you, but about Eric, well, about both, but Eric has a similar thing as with Jordan Peterson, which is if you ask them, do they believe in God, I think the answer, they're not comfortable answering that question, or they might say no, but they're usually just not comfortable answering that question, but there's a kind of sense that they would like to live life, a religious life as if God exists. I think that's exactly right. I think, first of all, Eric has a really deep appreciation of the Jewish tradition. I don't know Peterson, I've read his stuff and I've reviewed his stuff and so on, but I think that Jungians are, in their very approach, they believe that myth is the way the world works, and so it's not that big a leap to God, but there's still a distance there. Is it possible to have your cake and eat it too? Is it possible to have the depth of a religious life without believing in God? How do you make sense of Eric Weinstein's devout life within the tradition? I mean, I honestly think he believes in God, but doesn't believe in God, and it's oscillating like it's a quantum mechanical system of some sort. Schrodinger's God. So I think that he would probably agree with what Elie Wiesel said, that a Jew can be angry at God or be disbelieving of God, but is not allowed to be indifferent to God, and I think Eric's not indifferent to God. And it's different than Christianity. I've had this conversation many times, because you can be very Jewish and have deep doubts about theological questions because Judaism isn't a religion, it's a religious family, and so you're born Jewish. Like if I said to you tomorrow, if I was Christian, and I said, oh I believe in Jesus today and then tomorrow I didn't, I'm not Christian anymore, but if tomorrow I said, oh I don't believe all this stuff, I'm still Jewish. So it's a more complicated system. Having said that though, I think it's very hard to sustain over generations without some belief that the source of it is beyond ourselves. And in that sense, as in many others, Eric is unique. But he was actually making that claim that we need faith to propagate this tradition through the generations. So without that, the traditions crumble. It's a very interesting idea, and a very interesting argument for devout faith, which is it's a glue that holds a tradition together, otherwise traditions fall apart. You can't have the intensity of that tradition. I mean on the other hand, you do see traditions, I mean Thanksgiving, one of my favorite holidays. So I would say traditions that are demanding fall apart. Traditions that require turkey might not fall apart, but traditions that make demands of you that are counter-cultural or are hard, they fall apart. I think I need to introduce you to some Thanksgiving dinners that are quite demanding. Getting the family together. First of all, I'm a vegetarian, so I'm tough to have a Thanksgiving dinner. But there's a comedian named Kathy Lansman, who one year I heard this on the radio and it stuck with me. She said that holidays are a chance to renew your resentments afresh. And that's basically what people do with their families. It's like, I'm going to go home and fight with the uncle again this year. I apologize to take a dark turn, but you mentioned Elie Wiesel. I recently saw a picture of Elie Wiesel when he was in the camp, when he was liberated. For some reason that hit hard. I've seen pictures in concentration camps of people I don't know, or whose words I haven't really felt and gone through. But for some reason, here's just a normal person, like a normal body laying there. That was him. I've seen it. And you see, you can see his face, but at the same time you see that this is an amazing... I think what's so disturbing about it is exactly what you were saying, is I've seen a thousand people like this, and I know this one, and I know what he became. So what about all those other people who look exactly like him, who didn't make it out of the camp? I mean, it's projection, but it seemed like, this perhaps is also just combining with Matt's search for meaning, it seemed like it was a regular day for them in the picture. It didn't seem like... I mean, I'm not sure what I expect to see, what suffering looks like, but it's almost like there's no celebration. I've never seen a picture of actually liberation be celebratory. It's true. It's really true. So what do you make sense, and I apologize to take a step into that moment in history. How do you make sense of the Holocaust, of Nazi Germany, that such things could be committed by human beings to each other? Is it religion? Is it the thirst for power? Is it the madness of crowds somehow carrying us forward? I mean, for me, it's multi-causal. I don't think there's one reason. One of the things, especially there, has to do with the special nature of antisemitism, which is, let's put that to one side for the moment. The second is, I think human beings are fundamentally split. They are mostly good, except when put under certain pressures. My first explanation for hatred is as follows. Go to a playground. What happens when a new kid comes on the playground? Do the other kids say, oh, let's go share our toys with the new kid? No. They say, oh, who's that stranger? And let's go get him. Because otherness is built into our genetic, I mean, we're tribal by nature. And we see people form tribes all the time of different kinds. I asked you before if you were a chess player. And when I was a kid, I'm playing in tournaments. And I didn't do it for that long, and I didn't do it that well. But when I was, it was like the whole world was divided into people who could play chess and people who couldn't play chess, which is ridiculous if you think about it, as though that's the way you divide the world. But we tend to do that. And the Jews were always the identifiable other. There were Frenchmen and Jews. There were Russians and Jews. There were Germans and Jews. And the great blessing of America is that there's no identifiable other quite that way, is that there's all these minorities and no, there's not an American and a something. But once you have that identifiable other, and you have a long history of blaming that identifiable other for all the ills that befall you. Of course, people still do try to form, you said America, they still try to form other, I mean, immigrant versus been here for a generation. There's so many ways to slice it. We still try to find ways. It's just more difficult in America because there's so many sub-tribes, hierarchies of tribes upon tribes. You're absolutely right. And I was moving fast because I didn't want to get bogged down in all the very difficult... It's true, I tried. You're hoping I wouldn't mention that tribalism happens in America too. I was skating, you know. When you're on thin ice, your safety is in your speed. So I was trying to move fast. But for most of history in Eastern Western Europe, not obviously in Asia, but in Eastern Western Europe, Jews were the ones who like, they're not like us. They're clearly not like us. And in addition, there's a peculiar quality, and I don't know, I wonder what you'll think of this explanation. There's a peculiar quality to antisemitism that is unlike any other hatred that I know of, which is Jews are both superhuman and subhuman. They're vermin, the Nazis thought of them as vermin, and yet they control the world. And there was an English scholar named Hyman Maccabee who said the reason that that's so is the myth that Jews killed God. They killed Jesus. And to kill a God, you have to be superhumanly evil. You can't just be bad, otherwise you can't kill a God. So there is some like supercharged evil sense that people got from that about Jews that still inheres. Yeah, that's true. A lot of the way we formulate the other in terms of tribes is often they're subhuman and they're here to steal our resources, like on the playground. But to be both is a fascinating construction. Do you agree with Solzhenitsyn that all of us have the capacity for evil? A hundred percent, runs through every human heart. I have no doubt about it. And I know, as you probably do, but I probably know more both because of what I do and because I have lived a lot longer than you, I know a lot of religious leaders who people thought or think are above the human, and they are emphatically not. They're not. Some of them have done horrible things and they've used their position to do horrible things. And it's because nobody, there is no perfect saint. There's no, you know, I mean, all through history, you discover all these saintly characters that we worship, the people who actually knew them around them, some liked them and some didn't. People are complicated, all of us. And the tough thing is, the thing that's the toughest for me is it's not very always clear what is good and what is evil. Because certainly if you just look at history, and it's not always propaganda, I really believe that some part of Stalin thought he was doing good, legitimately. And it makes you ask a question of yourself. For those of us who want to do good in the world, am I actually doing good? And that's a really difficult question. In the technology sphere, for example, in this dream of creating technology that will do some good, am I actually doing good? So I have a question about that myself. Not about Stalin. I'm sure that Stalin thought so. Stalin does not strike me from what I know of him as somebody given to a lot of self-doubt. But the question with AI to me is actually, it goes back to the God question, which is, if we have an appreciation of the limitations of our own intelligence, that we know that just like we can only hear certain things and see certain colors, how much of the world is inaccessible to us because of the way our brains are constructed? How can we possibly have any confidence that we can create things that in certain ways are far more intelligent than we are and control them the way we think is best? Seems to me a hubris that might end up being destructive. Definitely. Well, any sentence with the word hubris in it is going to end badly when implemented at scale. But there is also beauty. So if you approach it with humility, there is a sense, I don't want to over romanticize it, but there is a legged robot right behind you, which is hilarious. So there's a magic, I don't have kids, I would love to have kids, but there's a magic to bringing robots to life that it feels like you are a mini-God. Because you just breathe life into an entity that operates in this world, especially when they have legs and they move in this way that's in the case of the four-legged robots, like a dog, that I don't think I'm over romanticizing it. The feeling is like you would with a child. You just gave birth, like, holy crap, this is a living thing. I wonder what he or she are thinking about. By the way, I'm not at all insensible to how remarkable it must feel to create that. I'm actually worried in part about how remarkable it feels to create that, because to maintain humility and perspective when it's such a fantastic thing is what's difficult. And I think also because creativity is both part of what it is to be human, and it's very much part of the legacy of Western civilization and the legacy of having a creator God. If you have a tradition where God is known primarily through what God creates, so the first debate I ever had, since we talked about humor and God and creating, let me give you my one God-creating joke. Because the first debate I ever had on religion and science was with Stephen Jay Gould. And it was wonderful, because he had a deep interest in religion, and his interest was actually not to say religion is terrible, but I started with this joke, and I think it made the debate go a little bit easier. So the time has come when human beings can do everything that God can do. And a scientist looks up at heaven and says, God, look, you were great in your day, and we thank you for everything you did, but now we don't need you. And God says, really, you don't need me? He says, no, we can do everything you did. God says, everything? And human being says, yeah, we can do everything. God says, okay, can you create a human being? And the scientist goes, yeah. God says, from dirt? The scientist goes, yeah. He says, okay, let me see. The scientist reaches down, scoops up some dirt, and God says, uh-uh-uh, get your own dirt. Yeah. But the idea is that a creator God impels us to create, too. But let me bring up Nietzsche, who proclaimed that God is dead. Is belief in God slowly disappearing from our world, do you think? And what kind of impact does that have on society? You wrote that religion is not our enemy. Before the Western faiths captured the heart of our world, there was cruelty, carnage, and destruction. In the 20th century, when religion ceased to be a force of international politics, the scale of human slaughter was far beyond anything human beings have ever known. What is the world like when we take religion out of it? I mean, I think Nietzsche was largely right. It wasn't a statement about God. It was a statement about God's presence in the world. And I think that that's largely true, that God is not a force in a lot of Western society. And I believe that if the force of nihilism has no clear counter without an idea that we're all here for a purpose, and that our lives are inherently meaningful, and that there's a God who wishes us to be better. So I worry a lot about it. And I think that the sort of optimism that things are just gonna get better and better is what one philosopher called cut flower ethics. That is, we're still living off the morals that religion gave us, but now that they're separate from the soil that gave birth to them, I see them wilting. So this kind of optimism for the future of human civilization, you think, is in part grounded in a religious society. I really do believe that. I mean, it was religion that... The Greeks looked back at the golden age of the past. It was the Jews who said, no, the golden age is in the future, right? It's the Messiah. And I think that that idea that we're moving towards something better, which I really believe humanity can do, and absent destroying ourselves will do, I mean, I'm very excited about the technology that I won't live to see. I think it's fantastic. And that excitement is a kind of religious excitement, because there's a reason to preserve this whole thing. Absolutely. Because I really think... I know this sounds absurdly anthropomorphic, but I really think God is cheering us on. I feel like this is why we're here. We're here to grow in soul and to grow each other in soul. Yeah. So what do you think the world... So if we just think of this force of nihilism that's contending with the force of faith-based optimism, what do you make of the atrocities in the 20th century? Do you think at its core, it's part of human nature and has nothing to do with religion or not religion? Or do you think you can assign this kind of nihilistic view of the world? I think it has to do with a religion that doesn't make ethical demands. That is, for Stalin and for Hitler, they both had religions, in a sense, but they were religions that didn't make ethical demands for the other. I mean, 36 times the Torah talks about the stranger. The point is, it's trying to educate people away from their natural inclination towards distrusting and disliking the other. And it's a lot of work. That's really difficult to do. But if you have a tribal passion and not a universal ethic, then you're in trouble. Well, the Jewish tribe is a very strong tribe. So how do you make sense of this mention of the stranger versus the power of the tribe, which is the whole point, not the point, but the mechanism of transition propagates the tribe? Well, both. I mean, the Torah does not start with Jews. It starts with Adam and Eve. That's a way of saying, yeah, this is going to be a story about a people, but understand that prior to a kind of people, there are people. I'm a human being before I'm a Jew. And in fact, the Jewish new year, the Muslim new year starts with Muhammad's journey, and the Christian new year starts with Jesus' birth. The Jewish new year starts with the creation of the world, because the idea is, yes, this is a particularist tradition, but it makes a universal statement, which is all of humanity is a child, are in the image of God, are children of God. I think that the idea of Judaism was to try to exemplify a certain way of making that statement over and over again. And I want to say one other thing about chosenness that's very name droppy, but when I tell you how I got there, it won't be as name droppy. So my brother is a professor at Emory, and so is the Dalai Lama actually teaches at Emory, although he no longer does because he's too old to go to Emory, but for many years taught at Emory. And so my brother brought us... He's the head of the ethics center at Emory, he's a bioethicist. So he brought a bunch of students to Dharamsala to meet with the Dalai Lama. So I went to India, I was on sabbatical then anyway, I met my brother there and we had a chance to meet with the Dalai Lama. Okay, that was the name drop. So we're sitting in the... Before he speaks to the students, he was speaking to us, but not because... I just wanted to make it clear, not because he said, oh, I got to talk to that rabbi, we just happened to be... I happened to glom along with my brother. We sit down, the first thing he says is he points at me and says, what's this about the chosen people anyway? So by the way, he had asked that I give a lecture, which I did later to his monks about how Jews survived in the diaspora. So it's not like he doesn't know about Judaism, he knows a lot about it, but he's just came right away with... So I said, yes, Jews believe that they were chosen for a certain mission in this world. That doesn't mean other people weren't chosen for other sorts of things. They certainly... I mean, it seems to me that other people believe they're chosen for things too. He burst out laughing and said, yeah, we also think we're chosen. So the idea is that no tribe is better than... Better, no. From a Jewish perspective, you're chosen for a thing, but that doesn't make you better. No. The only place where the betters came in, honestly, historically, if I'm going to be honest, was not with the idea that you... But it was when Jews were small, persecuted, the way that you take this sort of psychic revenge is by saying, no, we're better than our persecutors even. But the idea is, yeah, different people have different missions, which is... I mean, there was a Jewish philosopher, Franz Rosenzweig, who used to say... He didn't know very much about Islam. He used to say, Judaism is the sun and Christianity was the rays of the sun. Judaism introduced the idea of God and Christianity brought it to the world. Can you speak to this difference? What is the difference and similarities between Judaism, Christianity, and Islam? The religious family part is different. And the greatest difference, which I talked about in the Eric Weinstein podcast, is that Islam and Judaism are more similar in a lot of ways than Judaism and Christianity. And the reason that that is so is Christianity in its core is not a religion of law. The reason it's not a religion of law is because it grew up in the Roman Empire. So law was taken care of. I mean, Jesus didn't have to create civil law because you had Roman law. Muhammad and Moses created a religion in the desert where there was no law. So you have to create a religion of law. Otherwise, you have anarchy. And that's why in a lot of ways, like there was never a separation of church and state in Islam or Judaism. That was a gift that Christianity gave the world. And it could do it because of render unto Caesar what is Caesar's. But when Moses came along, there was no Caesar. When Muhammad came along, there was no Caesar. So historically, the traditions shaped differently. But all three of them have this core, I think, the single most important statement and insight in all of human history, which is that every human being is in the image of God. And if you really believe that, that's a transformative belief. So that means you should love thy neighbor as yourself. As thyself, which comes from Leviticus, comes straight from the Torah. So I don't know if you know, I've been chatting with Omar Suleiman. I don't know if you know who that is. He's an imam in Dallas, great guy. I enjoy his interfaith dialogues that he engages in. And do you ever do that kind of talk with Christians, with Muslims? Yes, often, often. I mean, I do whenever I at least listen to them in the context of these kinds of conversations. There's so much love and humor and empathy and appreciation. And also ability to make fun of the quirks of the little- Of one's own. Of one's own communities. So it's not necessarily the depths or the details of the traditions, but these are communities and they're full of people and they're full of weird people, because we're all weird. And so there is very particular flavors of weirdness that emerge and they can make fun of them. And in that way, they can talk about some beautiful ideas. So I mean, I don't know, do you engage in these kinds of things? What do you learn from them? So one of the things I learned is exactly what you said, that personalities that you think are unique to your own community, in fact, they exist in all sorts of communities. And religious communities in particular draw, I think, some interesting personalities. And also that the, especially as clergy, some of the pressures that you feel are shared. And it's weird, again, it has to do with that tribal association. There's almost like there's an understanding among clergy because they have similar straight and it's a strange role in the following way. It's one that you never escape. That is, you're not my lawyer at the supermarket, but you are my rabbi at the supermarket. I mean, it doesn't matter why you're there. That's not an escapable role. And every religious leader is aware of that strange assumption of stepping into something that you can never step out of. And you're also the source where people go to think about the deepest question of our lives and our universe. And so that's some heavy, you know, when people are suffering, they look to you for answers. I mean, every privilege comes with a cost of one kind or another. The reason you get to be in that role is exactly because you get the privilege of being there at crucial moments in people's lives. I mean, the fact that I get to marry people and get to give eulogies for people and come to the hospital, it's inexpressible. I have this joke with people that I know that like, when I'm sitting on the couch and it's Saturday night, I don't want to get up and go to a wedding. I really don't. I want to sit there and watch Netflix like everybody else. But when I'm actually doing the wedding, I always love it. Always, always, always. And the reason is that I don't think, I mean, yes, people go to you for answers in calmer conversations. Like if you asked me now, like, what's my theory of why God allows evil? I could give you a conversation about it. But they really go for presence and comfort, not really for answers. When someone's suffering, an answer doesn't make them unsuffer. You know, it's just, they want to know they're not alone. To be heard and just to feel things in silence together. In terms of weddings and marriage, what's the role of that call? I need to take some notes here. What's the role of marriage in human existence? It is first of all, to teach you how to care for someone unlike you, which could be anyone you marry. And I think it's to create a home and a family. So there's a commitment to it, so care for a long time. Right, exactly. And also, when couples come to me and they say, we don't need to be married because it really won't change how we think about ourselves and our relationship. I say, then that's true. It might not, but it will change how everyone else looks at you. And because it changes how everyone else looks at you, it changes you. Because it's one thing to say, this is my partner. It's another thing to say, this is my husband. You say, this is my husband, that means we've made a real commitment to this. Yeah. What do you, do you worry that there's a dissolution of that as well in terms of how, you know, as religion dissipates, it loosens its hold on society, loosens its impact on society. Do you worry about that? I worry about it. I do think that it is possible that we're going, rather than a dissolution, we're going through a transition that is different kinds of families and different configurations of families. That is, I see some of that, but I also do see, it's less a dissolution of marriage than it is of the idea of commitment. And I'll give you like a simple example. When I was growing up, a player on a sports team was always on that team. And you rooted for the team because you knew the players for 20 years. Now there are very good reasons, starting with Curt Flood, why people got free agency and they can move around and it's better for the players. I understand all that. And I am not, I'm not saying, oh, they should continue, but just like people move jobs and they move sports teams and they change careers, they change partners. And there is a diminishment of the commitment to commitment that I actually think has serious societal consequences and that I am worried about. Yeah, there's a cost to that. I don't know what it is about commitment that's beautiful. Because some of the deepest friendships I have is when we've gone through some shit together. Yeah. And so like the hard times, going through hard times together, especially when the hard times are between the two of you, that, if, I mean, that's always a risk, but if you can find a way through that can bond you stronger, that's the fascinating thing about human relations. There's no question. And even if it doesn't keep you forever, you still have a connection that doesn't, that exists. So I can give you one, you said, what is it about commitment? I'll give you one, I think, beautiful answer. Someone's asked Rabbi Soloveitchik, who is a great thinker and leader in the Orthodox community in the 20th century. They said, you know, I go from religion to religion. I just take what I think is beautiful in it. And his answer was that you're treating religion like a nomad. He said, nomads go from place to place and they eat what they want and they move on. He says, farmers stay in one place. The difference is farmers make things grow. And I think that that's true also when you think about the relationships you have, things have grown out of the relationships that you've invested in, that you farmed basically, that can't exist in fly-by-night relationships. Can you talk about, can we talk about the Torah? Yes. What is it? And is it the literal word of God? Easy questions today. Well, the Torah is the five books of Moses written in Hebrew. I, like most, I think modern rabbis, non-Orthodox or non-literalist rabbis will tell you that it's a product of human beings. And I believe that they are inspired by God, but it's clear to me that it's a human product. And I think that people who study modern biblical criticism, it's really hard to study modern, criticism gives a wrong impression. I would say modern scholarship on the Bible and not appreciate the fact that it even has levels of language. I mean, it's just like if you read today somebody writing like Shakespeare, you would say, this isn't, it's like English has developed. It's different. It's not the English we speak today. And if you study the Bible and you know Hebrew well enough, you even see that this was written over hundreds and hundreds and hundreds of years. It is a holy book. And I like the idea that it is, what you say in Hebrew is Torah min ha-shamayim and not Torah mi-sinay. That is the Torah is from heaven, but it's not from Sinai. So it has its origin beyond us, but it has things in it that I think, and this is one of the things that was a huge controversy at my congregation when I started to do same-sex marriages. There are some people who try to argue that the Torah does not forbid them. Whether it does or not, it seems to me we understand things that were not understood in the ancient world about gender and sexuality. And so- So you think that in the scripture, in the words, you can find the kind of spirit that supports the idea of gay marriage? Well, that's yes. My argument is that you criticize the Torah by the Torah. That is, it gives you the understanding that you use to evaluate its own claims. And I think that Judaism, by the way, has always done that because it's clear that there are things in the Torah that the rabbis changed, altered, grew, expanded, diminished. I think that's what it is to be part of a living tradition. Yeah, you wrote in your book, Why Faith Matters, quote, Walt Whitman wrote that, In order for there to be great books, there must be great readers. For a book to remain powerful throughout generations, it cannot have a single meaning. Scripture like great poetry is not reducible to other words. That is, one cannot paraphrase it and capture the totality of its meaning. So how the heck do you capture the meaning of the words in scripture? Is it an ongoing process through the centuries? Yes. Is that essentially what it is? Exactly so. It's a continual conversation of sages, scholars, readers, strugglers, seekers, mystics, visionaries, all of them making a contribution. I mean, I write a weekly Torah column for the Jerusalem Post. Now, what is there left to say? About every week, what I do is I start opening books and seeing what people say, and it starts to percolate, and you realize that you're entering this conversation that's been going on for thousands of years with remarkable minds, and it's constantly fertile in new insights. So yes, that's what it is to be part of a tradition. Why do people keep writing love poems? We should have figured out love by this point already. I use the analogy sometimes of diet books. If any diet worked, there would be one book. There'd be one book and you'd be done. You mentioned this fascinating story that you were part of. You were a part of several controversies in your life. I've had a few. So for someone who walks with grace through the fire, you sure have found yourself in a lot of fires. One of them, can you tell me the story of your views on gay marriage, the underlying principles that led you to fight this battle of defending gay marriage in the Jewish community? So I'm part of a congregation that is really politically split, and split not only politically, but split in terms of origin. We have a lot of Jews from the Middle East, from Iran, a lot of Persian Jews, a lot of Jews from Israel, some from Mexico, from other places, and many that grew up in LA. Do you have any Russian Jews? The best kind. I have a few Russian Jews, not as many as I should, but we'll work on that. But what happened was increasingly I became uncomfortable with people who would come to me and say, this is the only kind of person I can love. It's not the same question as an intermarriage, as a Jew marrying a non-Jew, because you could find a Jew to love, you may not have found, but you could, and that's a whole separate question. But I would have men in my office, primarily a couple of women, they would say, this is the only kind of person that I can enter into an intimate relationship with. How can it be that my religion has no room for me? And that was very persuasive to me. But I knew that it was gonna be explosive in my community. When, by the way, it finally happened, it was literally on the front page of the New York and the LA Times, it was that explosive. So it was not a small controversy. And so what I did was I started to teach classes, not that many people came about homosexuality and Jewish tradition and so on. It's funny, much, much less about lesbianism, much... I'm talking about in terms of the sources and so on. It's almost always about homosexuality. And then I got ready to send out a letter. And I said to my daughter, who at the time was maybe 10 or 11, now in her mid-20s, I said, look, honey, when you go to school tomorrow or whatever it was, I said, people might be saying bad things about your dad, and I just want you to be prepared for that. She said, why? And I said, because I'm gonna start doing same-sex marriages. And she looked at me quizzically and said, what took you so long? And I thought, really her face was like, I said to her, I'm gonna start marrying blonde-haired people to brown-haired people. It's like she really did not understand why there was an issue. And I thought, that's exactly why. Because I know that this is, it's generational, people are raised with it, they have it deep in there, but it's not really right. It's just not right. But if you could just look back to that journey, how difficult is it to make these decisions a principle? So, because you have to think about that in order to think about such decisions you yet might still have to make in the future. And I will tell you one thing I did wrong with that, and one thing I did right. The thing I did right was I waited until in the communities where people objected to it, I had enough people whose kids had come out so that I had parents of kids who'd come out to refer later on other parents to, so that they wouldn't feel like they were the only ones. Because once I announced it, as I thought would happen, a bunch of kids came out and said, now that the rabbi said this, mom, dad, I want you to know I'm gay. And when the parents came to me, I could say, well, listen, you're not alone, this person also you can go to. That I did right. What I did wrong was I don't think the classes were enough, and I don't think enough people were prepared. And I think part of the explosion was shock. And I should have prepared even more. The words you used to talk about it, the way you thought about it, was it more scholarly in the Jewish tradition, or did you go to the feeling? No, I went to the feeling. I said kvod ha-briot, which means respect or honor for God's creations, and caring for other human beings, and understanding. It wasn't scholarly, because I knew that the objections were not scholarly objections. And I had many beautiful and also painful stories as a result, some of which can be told and some of which really can't, but what I tried to impress also on people was how painful it is to not be able to tell the world, even your own parents, who you are. And your sexuality is not a trivial part of who you are. I mean, it's core to people. So it's one of the reasons why I'd evoke such reactions. But I would say to them, the same reason that you're reacting so strongly tells you how strongly, you know? Anyway, it was a very powerful experience. And for that, I have, you know, I feel good about it. Afterwards, the other thing that I, again, said to my daughter afterwards, after it all died down, and after all the bad things were said, I told her the Churchill one said that it's exhilarating to be shot at without result. You know, if you go into a battle and you make it through and you're still okay, that's good. The problem is when you're in the battle, you don't know. No, you don't know. So how did it feel like, I mean, looking back, you've been, you know, to use the word, canceled a couple of times. I guess when you're dealing with the most difficult of questions, just as a human being, for a community that you really deeply care about, some part of it saying that you have failed. I wasn't canceled the way, like I didn't lose my job, didn't lose my home, but I hurt people that I cared about. And that was the heart, like I went into this, you know, to be someone who brings people together. And then I would sit there and do, even now, like, as you're well aware with stuff that's going on now, I sit there and people are really upset at me who I either am or used to be close to. Do those people in time come around? When you look now, because those are real feelings in the moment, and we can learn that about social media, people, especially during COVID, there's this intensity of feeling about stuff. And have you learned something about the passing of feeling that turns into wisdom? No question about it. This sermon I gave this Saturday was about how, you know, Moses came down the mountain, he saw the golden calf and he broke the tablets. If he'd sat with it for a little while, he probably wouldn't have broken the tablets. But the instant reaction is always anger. And in our age, unfortunately, the instant reaction gets put on social media forever and ever and ever. And by the way, once you've actually said that, it becomes harder to back down. If you keep quiet for a day or two, then you can back down because you haven't put yourself out there. But once you've said, this is terrible what you did, it's harder to write and say, I'm sorry, I shouldn't have said that. Yeah, so it almost becomes, I mean, I actually, it's a really powerful statement that the downside of saying something on the internet is that it actually pulls you into this current. You both create the current and it pulls you into it to where it's actually very hard to escape. So when two days later you feel different, there's a momentum. There's now a tribe of people that feel this way and there's a momentum with it. There's a momentum and also you don't want to betray your own tribe because then people will get upset at you. I really think that a lot of the antagonism is not so much that you don't want to give ground to the people who oppose you, it's that you don't want to break with the people who are behind you. And that's really hard. Can you tell the story of this recent controversy, the sermon you just gave, you went to the Super Bowl? Yeah. I think a lot of people would relate to this because to me personally, I apologize to anybody who was hurt by this, the absurdity of it is deeply intense. So here's the story. The LA County mandates masking children in school and all of the kids in our school are masked and many of the parents are extremely upset about that. I will just leave that at that. I went to the Super Bowl. There were 70,000 people. Frank Luntz, whom we know, was a wonderful guy, gave me a ticket. And so I was at the Super Bowl. I maybe saw two masks among the 70,000 people. I didn't even think about it, which was foolish on my part, no question. I took a picture of myself unmasked at the Super Bowl. And people were, I mean, many, many people thought, oh, great, wonderful, glad you're having a good time, so on and so forth. I don't want to diminish at all the many people who said that. A lot of people were livid. They were livid. They weren't what was instructive about it was. They didn't say, nobody wrote me a private note and said, I think that this was a bad idea. You should have thought about this. No. They were, you're a hypocrite, you're a clown, you're an idiot. How could you do this? This is a disgrace. This is that kind of thing. They say that publicly. Oh, yeah. On my Instagram, you can still see, I left the remarks up because I really thought it was important. If I started, I only deleted the really vile comments because I thought that shouldn't stay up. But I left them up because I thought people should see and I should remind myself what I did. And I didn't want to just delete the picture as though it didn't happen because it did happen and I did do it. And I felt terrible about that. And I felt terrible that I had, not about, I mean, the comments from Malimi weren't pleasant. I didn't like it. Nobody likes it. But I felt worse that I had hurt all these people that I'm close to. And I defended all these people who were really upset that their kids were wearing masks. And now their kid says, why does the rabbi have to wear a mask? Well, first of all, it is tough to be a rabbi. If this is, I mean, the masks to me symbolize these kinds of discussions, symbolize not necessarily the issues at hand, but the intensity of feeling. And people are really struggling. People are in pain. They're lonely. The uncertainty of it, you don't know who to trust. Everything's under question. The institutions, even the scientific institutions, and there's all these conspiracy theories flying around. You don't know who to believe. And there's people just yelling at each other and politics is weaved into this whole thing in some messy way. And you just get, I mean, honestly, it's just like legit, simple, just frustration going back to marriage of just hanging out with the kids and your wife, husband, just this stress is building up over time, no release. And people want to tell you when the rabbi is not wearing a mask, even though it's at the damn Super Bowl, maybe you want to comment on the Super Bowl part, which is awesome. But anyway. But it released clearly a dam of all the kinds of feelings that you're talking about. So how do you then write a sermon? So what I did was I didn't answer on social media because I knew that I wouldn't be able to formulate it the way I wanted and I was going to wait and I was going to be able to give a longer, I mean, the sermon is 15 minutes, not that long, but I wanted to be able to give a longer answer as opposed to a tweet. And so I was really, I mean, I tried to make two points during the sermon and also I published the text of it, which I never do because I never speak from a text. I always speak from either notes or not even from notes. But this time I thought it was really important that I have a text out there too, so that people could actually look over it. And I just wanted to make two points, one of which was that I really feel terrible. And I did, that all these people were hurt and that there is this contradiction between the way I acted and the way they want me to act. And I also think, by the way, I didn't speak about this, but I also think that there are some people that just don't like the idea of a rabbi being at the Super Bowl. It's like, you're supposed to be doing rabbi stuff. So I understand that too. But then- Yeah, but rabbi at the Super Bowl, I mean, you are also, I hate to say it, but there's a rockstar nature to you talking to Christopher Hitchens, contending with ideas, inspiring so many other minds. I mean, there's an educational aspect to this. I appreciate that. It's making ideas cool. I mean, that's a very powerful, I mean, that is also the job of a rabbi. You're not just supposed to do rabbi stuff, it's to educate your spot. Yeah, but I didn't do so much of that at the game. So- I see. Nonetheless, so, but the second part of it was I said that we have to be able to express our anger and disappointment better than this. You just have to. In part because it doesn't get you the result that you want. I mean, when you scream at someone, that's not gonna get them to realize what they did. And the most painful moment of it was this letter that I got from a Christian pastor who said, you know, I always admired the Jews so much, I can't believe they could be so cruel and especially to a rabbi. And I thought, that's not how I want my congregation to be perceived in the world. And by the way, some of them were from my congregation, some were, many were not from my congregation. And I spoke about what you talked about, which is that, you know, I mentioned before that Moses broke those tablets coming down the mountain. And the Torah doesn't say what happened to the tablets, but the rabbis do. They say that they were carried together in the ark with the second set that was intact. And that we all have brokenness, communities and individuals, we have brokenness, and especially now. And we have to learn how to give each other space to be mistaken and broken and hurt and all of that. And the cool thing when you give people that space, you feel better. I mean, you for caring for the community, it feels better when you show empathy and compassion and kindness on the internet. You'll actually feel better a week from now. You'll feel much worse if you make some kind of a negative statement of principle on the internet. It's almost just exclusively true. So if you care about feeling good, just be kind first, be empathetic first. Almost always the case, exactly so. So it's, I mean, it settled down a lot. The most, really the single best reaction, there are people, and you can, again, you can go on social media, you can see all the criticisms and so on and so forth. But the single best reaction I got was from a man who came up to me right after the sermon and said, I have four words for you. And I thought, oh no. That was my, I gotta confess. Nothing good comes in fourth. I gotta confess. I said, I said what? He said, you changed my mind. And I thought, wow. And I said to him, that's so, it's like, it takes so much courage to come up to somebody and say that in front of them. And I was so grateful. And the other thing that it tells me is, look, I've been the rabbi of that congregation for 25 years, and I taught 10 years before that. I've been a rabbi for a long time. I still have a lot to learn. We talked a little bit about the difference between Judaism, Christianity, and Islam. Could you maybe talk about the difference between the Torah, the Bible, and the Quran? So there's the Hebrew Bible is actually what's called a step canon. That is, there are the five books of the Torah. Then there are books of history and the prophets. So books like Samuel, Kings, Judges, and then the prophets, Isaiah, Jeremiah, Amos, Ezekiel, so on. And then there are what are called the writings. The writings are books like Psalms, Proverbs, Job, the Megilloth, which are Esther, Daniel, all of those books, Ecclesiastes. So in Hebrew, it's called the Tanakh, Torah, Neviim, Ketuvim, the Torah, the prophets, and the writings. And that is the Hebrew Bible. Sometimes that's also called the Torah, just to be confusing. But really the Torah generally refers to the five books. Then there is the New Testament, which the Jews don't recognize as a sacred book. They recognize it as the book of another religion. And I sometimes say to Christians, in order for them to really grasp this, Jesus has as much religious significance to Judaism as Muhammad has to Christianity. That is, Jesus, although Jewish, became the founder of another religion. And for Judaism, that's not only in as much as Christians and Jews have had a lot of interactions, but religiously, Jesus has no significance. Said many beautiful things, said some things I don't like so much. Like what? Leave your father and mother and follow me. I don't like that as a religious model. Now Christians will say- The whole love thing is pretty good. Christians will say that I don't understand that, but that's because Christians, like Jews, interpret their texts different ways at different times. So anyway, the Quran, which I know less well, I have read it, but I know it less well than I know the New Testament, and certainly less well, obviously, than I know the Hebrew Bible, is in some ways, parts of it are, I don't say this word, I say this word because I can't find a better descriptive word, but Muslims will not accept this, is a takeoff on the Torah in some things. That is, it's the same stories as the Torah, but they're different. Now Jews will say, and I being a Jew will say this, that that's because Muhammad heard those stories from Jews and also heard Midrashim, which are rabbinic interpretations of those stories and he wrote those down. Muslims will say, no, the Jews got it wrong and Muhammad came along to correct the record and tell the real story. But they're all telling the story of the same thing. The Hebrew Bible part, the Abrahamic part, they all tell the story of the same characters, but tell them, obviously Christians accept the Hebrew Bible as sacred scripture. The Muslims retell many of the stories in the Bible. What is common to all of them is that all of them are monotheistic faiths. Now in Christianity, that's more complicated because of the Trinity, but as Christianity has developed over time, it clearly presents itself and thinks of itself and is a monotheistic faith as well. What's the role of the word in each of these religions in the scriptures? So in terms of, so first of all, the role of oral traditions, the power of the exactness of the words in the scripture, does it differ or is it really within the communities it differs? Because in Christianity, the words are not all the words of Jesus. They're the words of Jesus' disciples. None of the books of the New Testament were written by people who met Jesus in person. So they're different and therefore the, and also we don't even know sometimes the original language of some of the things in the New Testament. In the Bible, and I understand in the Quran, but I'll speak for the Hebrew Bible, the idea is that that's Lashon HaKodesh, that's sacred language and Hebrew is in it. That's the language, according to the tradition, that God actually spoke to Moses and therefore the exact words are infinitely interpretable and meaningful. But the words are spoken, but written by Moses and the same with Muhammad, but from memory or no. There are different theories. I won't speak for Muhammad. You should ask. I don't want to get another religious tradition wrong. In Judaism, the words are written by Moses at God's dictation, basically. That's the traditional view. There are other views that I'm happy to go into if you want to, but basically that's the traditional view. So it's pretty close. Right. What makes it different, what makes Judaism and Christianity different is Christianity has an ideal life. Judaism doesn't have an ideal life. Judaism has an ideal book. So the holidays of Christianity are events in the life of God, God's birth, God's death and resurrection. In Judaism, the holidays are all events in the life of the people, like the liberation from slavery, or in the people's relationship to God, like Yom Kippur, which is a day of atonement. But there are no holidays in Judaism that are events in the life of God because in Judaism, God doesn't have a biography. God is eternal and God never came to earth. And those events carry with them traditions and rules that you're to follow. Yes. Let me mention on one such event in scripture, yet another time you walked through the fire, which is with Exodus. That was the first. And you never forget the first. One of several controversies. You spoke 20 years ago, 21 years ago, now at Passover and said that, quote, the way the Bible describes the Exodus is not the way it happened, if it happened at all. So first of all, what is Exodus? So what really happened? Exodus is the liberation of the Jews from Egypt, and it is the central story of the Jewish tradition. And as I've said numerous times in various places, I believe that it's based on a historical kernel. I think Richard Elliott Friedman may have gotten this right in his book Exodus. It may have been the Levites who left Israel. But the Bible is not a book of history. I don't believe that there were 10 plagues and a split sea and 600,000 men, which makes about 2 million people, who actually, if there were 2 million people, would stretch all the way from Israel to Egypt alone, were liberated from Egypt. And my point in that sermon was not actually to convince people that it didn't happen. My point in that sermon was to convince people that the historicity of the Exodus is not the basis of the faith of the Jewish people. Well, what does the word historicity mean? In other words, the factuality of it. It can be true without being factual. So you're not supposed to read it as facts? Well, I don't read it as fact. I don't read it as a history book. I said, look, I was talking, again, to a congregation that had many Iranians. I said, you experienced the truth of the Exodus in your own life. There was a regime that wanted to destroy you, and you miraculously escaped before it did. And so a myth is something that may not have happened, but is always happening. And that's what I would say about the Exodus story. It's not about whether, in fact, there was a killing of the firstborn. It's about, does God deliver? Did God deliver the Jews in ancient times? Does God deliver people in modern times? And that's what the issue is. And to me, the issue of faith is much deeper than the issue of fact. I wouldn't look to the Torah for my science either. What are the limits of science in terms of what can science not tell us that the Torah can in terms of wisdom? So the historicity, the facts of things, okay. If the Torah is much more than that, is it, like you said, myth. Myth is not something that happened, but something that is always happening. So presumably, it's interacting with the environment of the day to generate wisdom. So you can live a life by Torah. I don't think you can live a life by biology. You can live a life that is informed by the values of the tradition of Judaism. And those values, by the way, what science does is it contributes factuality to the conversation and also changes the reality around us. So when you study Talmud on your iPhone, you're still, I mean, it changes the atmosphere in which you do it. But the wisdom and the life guidance and the connection to transcendence is something that science doesn't give. So if we now step into, returning to our friend Sam Harris, and step into this weird place of science, and you talked about this, where the kind of the current assumption of science is it's a materialistic one. So for me, obviously, AI person, this whole mind thing is fascinating. What the heck is going on up there? So how do you explain consciousness? How do you explain free will? Do you think, first of all, do you think we have a free will? And if so, what is it? This is where we had the debate earlier that I mentioned with Hitchens, where I think actually neither he nor the moderator understood what I was saying, which is, I'm sure, my inability to express it. But he was very focused and delivered on the humor and the wit. Yes. But what I was trying to say is, if we're entirely biological creatures, if we didn't choose our genetics, and we didn't choose our environment, then there is no space for free choice. I don't understand where it comes in. And I kept asking them that question, but didn't get an answer, because I don't think there is an answer. I think if you're a thoroughgoing materialist, free will is impossible. There could be randomness, but randomness is not free will. It's randomness. I think you need a spiritual, non-material belief in order to get free will, and that's why I believe in free will. Yeah, you were talking about, and actually the moderator totally missed your point about the glass of water and basically how, what's the difference. So to you, free will, because you could also, if it fits into the materialistic picture, it could be just a convenient, useful quirk. You would understand this better than I would. I don't understand how it could be a convenient quirk materialistically. I don't understand how to explain it. Well, no, if you study perception, there's all these kinds of illusions. Our mind plays tricks on us to make our life easier, more efficient, and survive better, and all those kinds of things. And so the feeling like we have a choice- Oh, that could be an illusion. Yes, that I understand. But actual free choice, free will, I don't see where you get it if you're a materialist. I think you have to have a spiritual component. By the way, I think Sam would agree with this. I think he wrote about not having free will. And I think if you don't have a God and you don't have a soul, that free will is a logical impossibility. And Sam, which is fascinating, it's not just that free will is an illusion, but the illusion of free will is an illusion, meaning we don't even experience anything like it. There's no illusion. It's not even on us to be talking about it. We are like the currents in the river or something. You were comparing it to the glass. We are just like that glass. So I don't know what we're going on about with this whole free will thing. And to you, is the free will, the I that the young person is born with, is that somehow fundamental to religion? It's fundamental to Judaism. I think that the idea is that you are the custodian of your soul. And even though I grant that there's a certain over-emphasis in modern society on the individuality of the soul, that is, we are more interconnected than I think we believe, still, yeah, the I, the idea that every human being is an image of God, that the human being in the Torah is created singly. And again, do I really believe there was an Adam and an Eve in a Garden of Eden? No, not literally, but I think that it expresses a deep truth about human life. And tied into this is this subjective experience of things, which we call consciousness. I mean, this is the most fascinating and inexplicable discussion. And again, this is a discussion I've had, I've privileged to have with Daniel Dennett and could not make any, as you can imagine, any headway on my, but he was delightful and brilliant to talk to. For me, consciousness is a real thing. I don't know if it is, I mean, I kind of like the panpsychist's view that there's an element of consciousness in everything, that that's constitutive of reality. But I don't, I'm not wedded to it. But I think that it exists in different degrees in all sentient creatures. I think that anybody who has a pet knows that they have some kind of consciousness. Except cats. I'm not going to, since I don't have cats or dogs, I'm not going to... Another reason people would be outraged, I said it. Well, I happen to be allergic to both, but I'm very fond of animals. The thing that so perplexes me about this is the denial of the reality of consciousness from people who are fully aware that they're conscious. I don't know how you divest yourself of the most present quality of being a person in your discussions about what it is to be a person. We just don't really have a good sense of the alternative, and so you can kind of divest yourself in that way. Well, maybe everything is like this. Maybe we're trying, we're over-dramatizing this whole thing. It seems like every living thing, perhaps everything, period, thinks that it's the center of the universe. Right. And so here we are telling ourselves these dramatic big stories about us being special and so on. And maybe we need to have a little bit more humility, both about the uncertainty and about our place in the whole. Any statement you make about something like consciousness has, I think, a sort of equal level of humility. You are saying that you know we don't have it is as, not you, Lex, but you, person saying we don't have it, is as intellectually arrogant as my saying we do. So I think for me, humility comes in in admitting that we really, really have just the tiniest part of the puzzle. And as you get older, at least my experience has been not that you get more answers, but that you just see a bigger puzzle. So to me, there is less, so the questions are fascinating, but there's also an engineering practical question. And perhaps I'll ask you a religious one too on this point, to return back to robots. So how to engineer consciousness, or I'll just even ask you a very simple question, which is when you have robots that exhibit the capacity to suffer. I found in myself as a human, when I see that, I feel something. Exhibit the capacity to suffer, or they exhibit behaviors that evoke in you a sense that they are suffering? Those aren't the same things. From an observation perspective, they sure as heck seem similar. You think they're feeling pain? I don't know what the... I'm observing pain. Okay. It's like when I watch a movie and there's people on screen, some of them are dressed like Batman. But you can make the distinction. If I have a doll and I bend the doll over and it makes a sad face, I know that that doll is not actually in pain, even though I am observing pain. So the question... What's that? The question is when the doll becomes able to remember things about you, David, about the experiences you shared, it is able to speak and make you feel like there's an actual relationship there. So that's what I'm asking, is at what point do you believe that the... I know that this is an impossible question, but at what point do you believe that there is a consciousness in there as opposed to just an extraordinary... I mean, when I play chess against a computer and it beats me, I'm embarrassed even though the computer doesn't... I don't think the computer is going, ah, you idiot. But it feels that way. But there is some part of me that says, okay, I know that this computer doesn't actually know who I am or care who I am. It just knows how to move the pieces. So at what point do you... I mean, you're giving me instances. It speaks, it does this, it does this. But at what point does that for you cross the threshold into it's actually a sentient being? I think the question is whether there is a threshold that could be crossed. That's one question. And I can answer this because I think it's different from person to person, but the chess engine is not at all trying to cross that threshold. Let's just start there. And to me, the personalization, which is what's the difference... Like a friend that you meet, you've shared all these memories. The way they look at you will convey, and the things they say will convey that they've shared those memories with you. They'll be able to speak in a shared humor and the language. But really the memories is the big one of having gone through things together. I think I would have more and more trouble, for example, turning off a system that I have been through things with. And by turning off, I mean delete all of its memory. If me and the toaster have gone through a bunch of dramatic events and that toaster remembers, there's a certain level to where it's just me and the toaster in this together at this point. And just to talk about sentience, I don't know, but... I don't know. It's according to the scripture, can't live by bread alone. But I know that there's no way to determine this, but it's still about what you feel. Yes. But isn't that what human relations are also though? Yes, but... But we make each other feel... But it's true that I have the assumption that you feel somewhat like I do. I mean, obviously I don't, and that could be illusion and I don't know. And I know that you don't feel exactly as I do. But I think we have a long, at least to me, we have a long way to go before the detached part of our brains, that is the objective evaluating part as opposed to the emotive it feels this way part, believe that that machine has consciousness. I think it's at least without arriving at conclusions, it's at least possible that one day we will look back and realize that we have yet once again formed another tribe and that scripture all along had in it the ability for humans and robots to have a deep meaningful connection and that through the robot, the life that enters the body of another robot, that's the difference between a biological body and a mechanical one. And then we will see that the fundamental thing is about the, whatever you want to call it, sentience, whatever can permeate an object, that was the thing all along. So I mean... And then you'll get canceled one more time because you will... Because I denied it. I was going to say... You'll eventually... I'll preach to the robots. I'm hoping. I will... Look, I... First of all, depends how quickly you do it and how much longer I have to live. I resisted tremendously, but I am also enough of a student of history to know that my instinctive resistance has nothing to do with whether it will come about. I have a hard time believing it. We'll see. Can I ask you about this? Maybe you can educate me. I tend to believe that we mentioned suffering, that there is a connection between consciousness and suffering, that suffering is a fundamental part. The capacity to suffer is the fundamental part of being human. I mean, look, when you're not conscious, you don't suffer. We've had operations where we've been put under anesthetic, we're not conscious and we don't suffer during the operation. If we were conscious, we would. But there's also, I mean, there's a non-physical suffering that is very much tied to consciousness. I can think of things right now that will cause me suffering, like pain that I've caused or pain that other people I care about have felt or so on. So I don't see how... I think that way... I think it's equally true of joy. Joy is also a product of consciousness. All tied in in some beautiful, messy way with memory and so on, that we can re-experience it when we recall the memories. But why is there suffering? You mentioned evil. Why is there evil in the world? You can tell stories about this. Why is there suffering? Why is there evil in the world if there's a God that cares for us? Let's assume for a minute that everything was a primitive robot. There would be no suffering, but there would also be no growth. And that implies choices. One of the things that I've said that I know why it hurts people, and I don't mean it quite the way that... But I will say it nonetheless, is the Holocaust presents the exact same theological question as somebody who gets shot on the streets of a city in Los Angeles, which is, God, why do you allow some people to do bad things to other people? It's on an unimaginable scale, but it's the same question. And the answer has to be, you either allow people to have free will or you don't. You can't say as God, I'm gonna let everybody have free will, but not Nazis. Nazis don't get free will. Because Cambodians, they can kill each other. Rwandans kill each other, but the Nazis don't get to do that. So that's one piece of the puzzle. And what makes it unfathomable is when you're actually faced with suffering, these kinds of explanations are obscene. They just are. You can't... I mean, when somebody is actually suffering, oh, the rabbi said God gave people free will, that's just awful. But there is a second piece to this also, which is that there is natural suffering, like children born with diseases or earthquakes or volcanoes or whatever. And here my argument is that in some way, suffering has to be random in the world, because when people say, why do bad things happen to good people? Well, if only good things happen to good people, everybody would be good, but it would have no moral content. The only way you can be good and it have moral content is say, I know that I can live a really good life and have really terrible things happen to me nonetheless. So it feels to me like it has to be a randomly. Now that means, by the way, that I've been incredibly lucky. I don't have a good life because I was good. I have a good life because I was lucky. And that implies not that I should feel guilty about it, but that I have a tremendous responsibility as a result to other people who aren't so lucky. Tremendous responsibility to study the lessons of history, to tell the stories of those who are less lucky, and to draw enough wisdom from them so that we have less cruelty and suffering in the world, or have new kinds that get us to improve even more. That's right, exactly. That we suffer better. Suffer better. For a lot of people, mortality is one of the very unfortunate versions of suffering, which is that the ride ends in this realm, whatever it is. What do you think of mortality? Is it something you think about? Is it something you fear? What do you think happens after we die? I don't fear it. First of all, I would say when I was in high school, I think my father actually encouraged me to read this book. I read Ernest Becker's Denial of Death, which I found, and still find, to be one of the most profound works I've ever come across. And he convinced me that a lot of what our society is about are ways that we avoid encountering our own mortality. Our physicality, I mean, among the points he makes, and I'm not quoting him at all directly, is like, why does everything about our physical body make us so uncomfortable? Everything that comes out of you, other than tears, is either mildly or very disgusting. Why? Why does that have to be? Why are sex and eating and all the things that are physical surrounded with so much symbolism? I mean, what are table manners, really? They're like, we're not eating like animals because we're not eating like animals. And sex obviously has more symbolism around it than anything. And his answer is, anything that reminds you that you're a physical body, because that's what dies, your body dies, it decays, it dies, it gets eaten by worms, that you don't want to think about, so you deny it. I think that part of religion is a confrontation with your own mortality, but also a certain transcendence of it, because the idea is something about you is eternal. What exactly? I don't know. And you asked, what do I think happens after we die? So I don't know any better than anyone else does, but I'll say two things about it. One is that every image of what it's like is foolish. Mark Twain has, I think in Letters from Earth, he says, we're going to lie on green fields and listen to harp music, which you wouldn't want to do for five minutes while you're alive, but you think you'll be happy for the rest of eternity doing it after you die. So I don't know. This world was a surprise. So why shouldn't the next world be a surprise? I have no idea. But I really like this parable that's told by a guy in a book on death and mourning, by a rabbi in a book on death and mourning about twins in a womb. He says, one of them believes that there's a life outside and the other one doesn't. He says, the one who doesn't says, look, this is the only world we've ever seen, the only world we've ever known. Why do you think there's something out there? He says, now imagine the one who believes is born. Back in the womb, his brother is mourning a death, but outside, everybody's celebrating a birth. He said, and that's what it's like when you die. And I love that image. Yeah, the grass is always greener. It's the new step. But the eternity thing is an interesting one. It's yet another concept that I feel humans are fully inequipped to comprehend. Is eternity fundamental somehow to all of these discussions? I think it is, well, partly because God is supposed to be eternal, and therefore it moves the mind in that direction, even though it is completely unfathomable. Because sometimes I would say eternity, you said on a green field, sometimes a moment, like a truly joyful moment, feels like an eternity, the intensity of it. Maybe eternity is more about stopping time versus extending time indefinitely. And it's something that we just totally can't comprehend, us silly humans. All I would say is, the older you get, the more you're struck by the fact that time does not freeze. People will sometimes say to me, you haven't aged a day. And then I'll look at an old picture of myself, and I'll say, that was very kind of you. But that's not true. It's not true. So yeah, I mean, I love the idea of seeing eternity in a grain of sand, was how Blake put it. I love that notion. But when you talk about life after death, I think that in some ways, my fundamental faith is in human beings, that this doesn't all disappear, that there's something about people that transcends this world. You mentioned Ernest Becker in high school, and denial of death. Maybe you can mention if you still see truth and wisdom in some of this idea. But in general, can you go all the way back and tell some of the fascinating story of how you found faith? When I was in high school, I was a really pretty ardent atheist. And I loved Bertrand Russell, who was, for my money, with all due respect to all the very, very capable people that we've talked about earlier, he's the best atheist pound for pound that there was, and a remarkably witty and lucid writer. And I was totally in his thrall. And I would read every book by Russell I could get my hands on. And the reason that I did, I have this theory that why do adolescent boys like Mr. Spock and like Sherlock Holmes? I think it's because when you hit puberty, for a lot of us, there's so much discomfort with our bodies that we like the idea that we're just brains. I really think so. I had that experience. It's like, I want to just be a thinking machine. I don't want to be a body, because my body was making me so uncomfortable. I had all these urges and inclinations that I couldn't control. So Russell was perfect. And my father, who was a rabbi, did the very wise thing of buying me some of Bertrand Russell's books, which was his way of saying, I'm not afraid of him. And actually, there was another rabbi, I was at summer camp, and I was sitting on the porch of the, I remember exactly, and I was reading Bertrand Russell, and this guy came up to me and said, what are you reading? I was maybe 16 or 17, and I said, Bertrand Russell. I was spoiling for a fight. And he said, I'm glad you're reading him. I said, really, why? He goes, how old are you, David? I said, whatever I was, 16, 17. He said, well, I'd rather you grow out of him than grow into him. And you know what? He was actually right, because when I started to read about Russell's life, I realized that all of that rationality didn't shield him. He had an incredibly messy life, multiple marriages, endless infidelities, family members he didn't speak to, didn't speak to him. By the way, he was raised by his grandparents, because his parents had died, and really not a happy or, I mean, a remarkable life, but not a happy one. And so I started to believe that maybe it was possible that people who had faith were not just stupid and needed crutches, but saw something deeper than Russell did. And the more people that I met that were like that, it's funny, because I always thought, okay, my father is a rabbi, that's great, but nobody else. And I think what happened to me was it was not a logical decision to come to faith. It was a sort of opening of my heart. It's like this world is way much more than my mind can capture. And I've kind of felt my way to God. And in the moments, my faith, there was a rabbi named Rabbi Nachman of Bratislava, he said he was a moon man, his faith waxed and waned. So sometimes I have more, sometimes less. But in my feelinger moments is when I have more. So with your heart open, what would you say in your feelinger moments is the most beautiful part about Judaism, in your faith? I think the most beautiful part about Judaism is that even though it is filled with humor and wit, it takes life and it takes the soul seriously. It really believes that this matters and that we matter and what we do matters. And I think that that's incredibly important. And especially in a world in which young people feel so much like they don't matter, that's an unbelievably powerful message. I mean, I want to say like almost to every young woman under 30 on TikTok, you don't matter because you're beautiful. That's not why you matter. I hope you know that. You matter because you have a soul. And to every young man who's like nihilistic and doesn't think and just thinks that if they make enough money, their life will be fine. I want to say the same thing, which is really, that's not ultimately you matter because you're in the image of God. And Judaism really deeply, deeply believes and preaches that. And I think that that's a message that has so much to say to the world. It's like you have to take people's souls seriously. And for all of the difficulty in figuring out all these social questions and what they mean, I just don't want to dismiss people because I disagree with them politically or socially or culturally because I think they matter. So ultimately, Judaism has a wealth of meaning for human mind. I really believe that it does. I really do. And its meaning, and I want to emphasize this, is not political. The deepest meaning of Judaism is not political. Well there is, we put politics on top of everything. Exactly. But that's why I want to emphasize it. The deepest meaning is on a soul level. It's not on a voting level. Well that combined with the humor, it's clear to me that Christopher Hitchens should have been a Jew. He was. He actually was. He discovered that in his 30s, that his mother was Jewish. That's fascinating. Yep. He actually has a beautiful essay about it, discovering in his 30s that his mother was Jewish. Yep. So remarkably enough, he actually was Jewish. His autobiography, Hitch 22, is a great read. And I just want to say what you discover there, I don't know if I'm giving too much away by telling the story of his life, but what you discover there is that his mother ran away with a minister or a priest and they died in what seemed like was a suicide pact. And so I read it, unfortunately, after he passed away, but I would have wanted to ask him, do you think that has anything to do maybe with the hostility towards religion? We are only human. My father, I mean both my parents, but my father who was a rabbi was such a wonderful, warm, and loving man. So I associate a religious figure, you know, with real goodness. And I'm sorry to return to a darker topic, but I really wanted to ask you this for the current events, for a recent event. I mentioned Dallas. What lessons do you draw from the Dallas Synagogue hostage incident? Well, the week after that we had active shooter training in my synagogues. And one of the things I drew was that security for synagogues is important. And the second is that the reality of antisemitism, which I had thought had waned when I first began my rabbinate, I thought it's not going to be such a big issue. It is like an evergreen issue. And Jews and all people of goodwill have to take this really seriously because it has devastating consequences. And if the world doesn't know that, then it just hasn't been paying attention. So there's antisemitism at a scale of human to human, but there's also, like you mentioned, politics get mixed up into things, nations get mixed into things. Impossible to answer, but I have to ask. Sure. What do you think about the long-running saga of Israel and Palestine? Will we ever see peace in that part of the Middle East? Well, since I'm an optimist about human... I have many, many thoughts about it. I'm a very, very strong supporter of Israel. And I also feel really for the plight of the Palestinians. I think that this is a clash of legitimate narratives that is impossible to exactly split the difference of. However, I know that Israel has made peace with Egypt, has made peace with Jordan, has made peace now with other Arab nations. I don't believe that Israel is unwilling to make peace. And so I think that as difficult as it will be for the Palestinians to come to grips with the fact that the Jewish state is not leaving and is legitimately here, as opposed to, we can't get rid of it now, but we will get rid of it one day. If that comes to be, and I believe that it will, I think not only that there would be peace, but I think that those two peoples together could probably do remarkable things in the world. Do you think the source of it is politics? Is it religious ideas? And to flip it, what is the way out? Is it geopolitics? Is it interfaith discourse and collaboration? Or is it simply the human love? So I think that I'm not sure that I could give one answer to that, but I will give a piece of an answer. Why did the Abraham Accords happen? The main reason that they happened was because economics overrode ideology. And I actually am hopeful that that's in the end what will happen, that people will say, you know what, we could have such a better life if we put aside the ideological animosities and just created this different kind of Middle East together. I went to Dubai to watch the World Chess Championship because I really wanted to see Magnus Carlsen play. I mean, you're alive when you have such a remarkable world champion, go see him play. So I actually took myself to Dubai for the last couple of games and I watched. And so I wasn't so much, I mean, it's not that I'm uninterested in Dubai, but I really, I went there for the chess thing. The Expo was also on at the same time and I saw here's this amazing place. I came back. This guy I know who lived in Dubai for several years and works in the Middle East said to me, what did you think of it? And I said, as nice as Dubai. It was like very, you know, very polished, very sophisticated, very clean, no crime and so on. But it was like, you know, kind of like Las Vegas in the Middle East without the gambling or something like that. And he said, you know, and he totally changed my perspective in a couple of sentences. He said, I know it seems like that when you come from Los Angeles. He said, but fly there from Yemen or from Riyadh and it is a miracle. And I thought, oh my God, you're right. It's like what human beings can do if they just put aside their ideological shackles is remarkable. And I'm hopeful that one day that'll happen. Economics allows for a higher quality of life. You no longer, it's the playground analogy you said earlier. If there's more resources to play with, unfortunately us humans are more willing to play with others. And maybe that is the solution. Maybe, I mean, for me, from a technology perspective, innovation, engineering helps make everybody's life better. And over that, once people's lives become better, they start to have more time to be empathetic and hear people out. And they have more to lose. When you have more to lose, it actually makes you, I think, countries are less willing to go to war when they have more to lose. And families want peace when it's good at home. So I think there's an element of that as well. And some of it, again, taking us back to the other aspect of our conversation is how we're conducting ourselves in conversation online and so on. Because I think, actually, I'm a big fan of the idea of social media that is a way for us to connect together. I think there's a lot of really strong ideas how to do that well. And clearly, the initial attempts that kind of just open it up wide, some of the lesser aspects of human nature can take over when combined with different forces like advertisements and virality and all those kinds of things. But overall, I love the honesty of the mess of it being presented before us on social media. The part of me, maybe because I don't participate in it, like if somebody is being mean to me or being aggressive and these kinds of things, I enjoy it because it's human nature. But I enjoy it because I don't respond. I think if I responded, I would get pulled into this human nature and then it's not fun. But I love the... I'll talk to people. In fact, I still visit Clubhouse. I don't know if you know what that is. Sure. Oh, right. That's right. Actually, when I... I think that's how we first met. Yeah. Well, I was such a fan boy. I was like, I can't believe I get to talk to David Welby. But the Israel-Palestine topic was something that was very deeply in a heated way discussed on Clubhouse. Race relations is a thing that was really heatedly discussed. And I now go to Clubhouse to practice Russian. And there in Russian, the heated discussion is on basically any topic as meaningless or meaningful as you want and the heat of it, just people just screaming and then calming down and going through the full process. That too is beautiful because that emotion is there. And if it is allowed to have a voice, I think ultimately it leads to healing. So that felt really healthy to learn how to do that at scale. Social media, I wish that it were not as algorithmically biased towards conflict. I don't think that that's healthy, but I do... I think it brings a lot of blessings into people's lives if they use it wisely. Like anything else, it can be awful, but it can... I've connected to all sorts of people that I never would have known. And that's been wonderful. So... Let me ask you the big question of advice. What advice would you give to young people today that are maybe high school, college, thinking about career, thinking about life, that can be proud of? So the first thing that I would say is that life is longer than you think it is. Even though I understand the impulse to be in a rush, you will have many unfoldings, more even than people of my generation did. Unfoldings, that's such a funny word. It's a beautiful word. Unfolding. But it feels that way. It's like different aspects of your life will come... Will show you different possibilities that you don't imagine at the moment. And I think the second thing that I would say is... I know that this is a very old-fashioned, but I would say, don't... To the extent that you can, read. Don't just... And not just on social media, read books. Learn things that will give you a broader context for your life than just today or yesterday or the day before. And I suppose the other thing that I would say is that to the extent that you can, try to develop your own internal metric of both what matters and what is good, because you will be exposed to more voices than any generation in history telling you that that's good or this is good. They're not called influencers, but what they are is voices telling you what you should think and what you should believe. And so have some internal space where you'll be able to say, for example, I know this person is doing that and it looks great, but that's not me. You have a community of people that speak to you with a lot of passion. And do you still have that voice in your own, in the privacy of your own mind that you're able to ignore, like for a moment, just be with yourself? Absolutely. Think what is right. Absolutely. And I think it's partly because I grew up without that. I mean, I grew up with a lot of space in my life and so I had a chance to develop that voice. That's why I think it's harder for kids today than it was for me. I mean, I grew up when there were three channels. There was three, six and 10. There was ABC, CBS and NBC and that was it. And you spent your evening playing board games or reading or whatever. And there was a lot of space and we played football on the street and you went on your bike in the morning and nobody worried about you and you came home at night and everybody assumed you were fine. And so I really feel, and also I went into a religious tradition where I feel like I have the opportunity to judge myself by bigger metrics. And it's still hard. I don't want to, it's not like, oh, I wear impenetrable armor. It's still hard. So how much harder for kids today when they don't have that? You mentioned books. Is there Bertrand Russell and Denial of Death by Ernest Becker? Is there books that pop into mind that had an impact on you? My favorite novel is Middlemarch. Middlemarch? Middlemarch. I don't remember, I was listening to a podcast, I was listening to one of your podcasts where your guest said the two greatest novels of the 19th century were Brothers Karamazov and what was the other one he mentioned? I don't remember. Dostoevsky as well or no? I think. It was both Dostoevsky. It might have been. I don't remember. Maybe the, but anyway, but I would say Middlemarch is up there. Middlemarch presents an entire world and it's written by a woman, Mary Ann Evans, who took the pen name George Eliot, who you feel, Virginia Woolf said it's the only English novel written for grownups. You feel the genius in her sentences, like the pressure of her intellect in her sentences. It's a beautiful, it's a wonderful, wonderful book. I love it. Pressure of her intellect. Yeah, you really do. I also love, I love Saul Bellow, especially Herzog, but it's a very different kind of thinking person's novel. I read a lot of mysteries and a lot of other kinds of fiction and literature, but in terms of the books that most, you mentioned one of them, which is Viktor Frankl's Man's Search for Meaning. And I also really, really love Heschel's The Sabbath. I think it's a beautiful book. It's very short book, just as Frankl's book is. What do you take from the Man's Search for Meaning? What do you take of a human being in the worst conditions being able to non-dramatically find little joys, find beauty? It's what I said before about Judaism's advice to younger people, is that it mattered. If you believe that something matters, you have enormous resilience. It's meaninglessness that is the greatest threat to a decent life. When people are deeply depressed, whether it is chemical depression or what they feel like is this is all meaningless. And meaning, now obviously chemical depression calls in part for chemical means, but meaning is the great antidote. We can talk about what kind of meaning. I mean, there are kinds of meanings that are awful, but meaning is the great antidote to a sense that life is just nihilistic and purposeless and to that destructiveness that I think is too common. Yeah, so maybe the heroic action in Nazi Germany, in the Holocaust, in the camps is the, even not the action, but just the realization that every life matters. So here's this really wonderful story that Hugo Grin, who was a rabbi in England, died, I don't know, like 15, 20 years ago, used to tell. He grew up in Auschwitz. He was a child there and he was with his father and it was Hanukkah and you're supposed to light the candles. And his father took the margarine ration and used it as the oil to light the Hanukkah candles. And Hugo was scandalized and he said, that's our food. And his father said, what we have learned, my son, is you can live for three weeks without food. You can live for three days without water, but you can't live for three minutes without hope. Well, hope, let me ask you, you said meaning. What's the meaning of this whole thing? What's the meaning of life? You're the perfect person to ask this question. Rabbi David Wolfe. I believe the meaning of life is for human beings to grow in soul. That's why we're here. And you can do that in infinite numbers of ways, but if you're supposed to return your soul like more burnished and beautiful, then you got it. I mean, it's going to have some nicks and cuts, but that's what it means to deepen and grow it. And you do that more than anything else. You do that by learning how to love. I mean, that's the principle way I think that you do it. You know, it's interesting because for a human, the relationship, if you're a man of faith, is with God, but it feels like love is so richly part of human society that it's not just love of God, it's love of each other. Right, yep. There's no question about the idea. I mean, in Judaism, that was actually the great innovation of the monotheistic idea. In pagan societies, it was all about how you treated the gods. Monotheism said, no, God cares how you treat each other. So it's, in fact, the mystics use the same kind of word in Hebrew, d'vaikut, which means clinging, that is used about Adam and Eve. It says, therefore a man will leave his father and mother and davak with his wife. And davak means cling. So there is an analogy there, absolutely. Yeah, I kind of think of human civilization is that, there's that movie March of the Penguins, and they're all huddling together in the cold. This is fundamentally human. There's this darkness all around us of uncertainty, of cruelty, of just, it seems like everything is so fragile, and we're just kind of all huddling together for warmth. And that's all we got is each other. So we started with the big question of what is God, ended with what is meaning. Rabbi Wolpe, I've been a huge, as I've told you, huge, huge fan of you for a long time. It's such an honor that you talked to me today. I am really so happy to be here, and thank you so much for the conversation. Thanks for listening to this conversation with David Wolpe. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from David himself. The only whole heart is a broken one, because it lets the light in. Thank you for listening, and hope to see you next time.

https://youtu.be/urdNsyZBqhQ

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Jim Keller: Moore's Law, Microprocessors, and First Principles | Lex Fridman Podcast #70

The following is a conversation with Jim Keller, legendary microprocessor engineer who has worked at AMD, Apple, Tesla, and now Intel. He's known for his work on AMD K7, K8, K12, and Zen microarchitectures, Apple A4 and A5 processors, and co-author of the specification for the x86-64 instruction set and HyperTransport Interconnect. He's a brilliant first principles engineer, an out-of-the-box thinker, and just an interesting and fun human being to talk to. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it 5 stars on Apple Podcasts, follow on Spotify, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Broker's services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App to support one of my favorite organizations called FIRST, best known for their FIRST Robotics and LEGO competitions. They educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating, a charity navigator, which means the donated money is used to maximum effectiveness. When you get Cash App from the App Store or Google Play and use code LEXPODCAST, you'll get $10 and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now here's my conversation with Jim Keller. What are the differences and similarities between the human brain and a computer with the microprocessor at its core? Let's start with the philosophical question perhaps. Well, since people don't actually understand how human brains work, I think that's true. I think that's true. So it's hard to compare them. Computers are, you know, there's really two things. There's memory and there's computation, right? And to date, almost all computer architectures are global memory, which is a thing, right? And then computation where you pull data and you do relatively simple operations on it and write data back. So it's decoupled in modern computers. And you think in the human brain, everything's a mess that's combined together? What people observe is there's, you know, some number of layers of neurons which have local and global connections and information is stored in some distributed fashion. And people build things called neural networks in computers where the information is distributed in some kind of fashion. You know, there's a mathematics behind it. I don't know that the understanding of that is super deep. The computations we run on those are straightforward computations. I don't believe anybody has said a neuron does this computation. So to date, it's hard to compare them. I would say. So let's get into the basics before we zoom back out. How do you build a computer from scratch? What is a microprocessor? What is a microarchitecture? What's an instruction set architecture? Maybe even as far back as what is a transistor? So the special charm of computer engineering is there's a relatively good understanding of abstraction layers. So down at the bottom you have atoms and atoms get put together in materials like silicon or dope silicon or metal and we build transistors. On top of that, we build logic gates, right? And then functional units like an adder, a subtractor, an instruction parsing unit and then we assemble those into, you know, processing elements. Modern computers are built out of, you know, parts of a computer. They're built out of, you know, probably 10 to 20 locally, you know, organic processing elements or coherent processing elements and then that runs computer programs, right? So there's abstraction layers and then software, you know, there's an instruction set you run and then there's assembly language C, C++, Java, JavaScript, you know, there's abstraction layers, you know, essentially from the atom to the data center, right? So when you build a computer, you know, first there's a target like what's it for? Like how fast does it have to be? Which, you know, today there's a whole bunch of metrics about what that is. And then in an organization of, you know, a thousand people who build a computer, there's lots of different disciplines that you have to operate on. Does that make sense? And so... So there's a bunch of levels of abstraction of, in an organization like Intel and in your own vision, there's a lot of brilliance that comes in at every one of those layers. Some of it is science, some of it is engineering, some of it is art. What's the most, if you could pick favorites, what's the most important, your favorite layer on these layers of abstractions? Where does the magic enter this hierarchy? Uh, I don't really care. That's the fun, you know, I'm somewhat agnostic to that. So I would say for relatively long periods of time, instruction sets are stable. So the x86 instruction set, the ARM instruction set. What's an instruction set? So it says, how do you encode the basic operations? Load, store, multiply, add, subtract, conditional branch. There aren't that many interesting instructions. Like if you look at a program and it runs, 90% of the execution is on 25 opcodes, 25 instructions. And those are stable, right? What does it mean stable? Intel architecture has been around for 25 years. It works. It works. And that's because the basics are defined a long time ago. Right? Now, the way an old computer ran is you fetched instructions and you executed them in order. Do the load, do the add, do the compare. The way a modern computer works is you fetch large numbers of instructions, say 500. And then you find the dependency graph between the instructions. And then you, you execute in independent units, those little micrographs. So a modern computer, like people like to say, computers should be simple and clean. But it turns out the market for simple, complete, clean, slow computers is zero. Right? We don't sell any simple, clean computers. Now you can, there's how you build it can be clean, but the computer people want to buy, that's say in a phone or a data center, fetches a large number of instructions, computes the dependency graph, and then executes it in a way that gets the right answers. And optimize that graph somehow. Yeah. They run deeply out of order. And then there's semantics around how memory ordering works and other things work. So the computer sort of has a bunch of bookkeeping tables. It says, what orders do these operations finish in or appear to finish in? But to go fast, you have to fetch a lot of instructions and then you have to fetch a lot of instructions and find all the parallelism. Now there's a second kind of computer, which we call GPUs today. And I call it the difference. There's found parallelism, like you have a program with a lot of dependent instructions. You fetch a bunch and then you go figure out the dependency graph and you issue instructions out of order. That's because you have one serial narrative to execute, which in fact can be done out of order. You call it a narrative? Yeah. Wow. So yeah. So humans think in serial narrative. So read a book, right? There's a sentence after sentence after sentence and there's paragraphs. Now you could diagram that. Imagine you diagrammed it properly and you said, which sentences could be read in any order without changing the meaning? Right? That's a fascinating question to ask of a book. Yeah. Yeah. You could do that. Right? So some paragraphs could be reordered, some sentences can be reordered. You could say, he is tall and smart and X, right? And it doesn't matter the order of tall and smart. But if you say the tall man is wearing a red shirt, what colors, you know, like you can create dependencies, right? Right. And so GPUs on the other hand, run simple programs on pixels, but you're given a million of them. And the first order, the screen you're looking at doesn't care which order you do it in. So I call that given parallelism. Simple narratives around the large numbers of things where you can just say, it's parallel because you told me it was. So found parallelism where the narrative is sequential, but you discover like little pockets of parallelism versus... Turns out large pockets of parallelism. Large. So how hard is it to discover? Well, how hard is it? That's just transistor count, right? So once you crack the problem, you say, here's how you fetch 10 instructions at a time. Here's how you calculate the dependencies between them. Here's how you describe the dependencies. Here's, you know, these are pieces, right? So once you describe the dependencies, then it's just a graph, sort of, it's an algorithm that finds, what is that? I'm sure there's a graph theory, a theoretical answer here that's solvable. In general, programs, modern programs that human beings write, how much found parallelism is there? About 10x. What does 10x mean? So if you execute it in order... Versus, yeah. You would get what's called cycles per instruction, and it would be about, you know, three instructions, three cycles per instruction because of the latency of the operations and stuff. And in a modern computer, executes it, but like 0.2, 0.25 cycles per instruction. So it's about, we today find 10x. And there's two things. One is the found parallelism in the narrative, right? And the other is to predictability of the narrative, right? So certain operations, they do a bunch of calculations and if greater than one, do this, else do that. That decision is predicted in modern computers to high 90% accuracy. So branches happen a lot. So imagine you have a decision to make every six instructions, which is about the average, right? But you want to fetch 500 instructions, figure out the graph and execute them all in parallel. That means you have, let's say if you fix 600 instructions and it's every six, you have to fetch, you have to predict 99 out of a hundred branches correctly for that window to be effective. Okay. So parallelism, you can't parallelize branches or you can. What does predict a branch mean? So imagine you do a computation over and over, you're in a loop. Yep. So while n is greater than one, do. And you go through that loop a million times. So every time you look at the branch, you say, it's probably still greater than one. And you're saying you could do that accurately. Very accurately. Modern computer- My mind is blown. How the heck do you do that? Wait a minute. Well, you want to know? This is really sad. 20 years ago- Yes. You simply recorded which way the branch went last time and predicted the same thing. Right. Okay. What's the accuracy of that? 85%. So then somebody said, hey, let's keep a couple of bits and have a little counter. So when it predicts one way, we count up and then pins. So say you have a three-bit counter, so you count up and then you count down. And if it's, you can use the top bit as the sign bit. So you have a sign two-bit number. So if it's greater than one, you predict taken and less than one, you predict not taken, right? Or less than zero, whatever the thing is. And that got us to 92%. Oh. Okay. You know what? It gets better. This branch depends on how you got there. So if you came down the code one way, you're talking about Bob and Jane, right? And then said, does Bob like Jane? It went one way. But if you're talking about Bob and Jill, does Bob like Jane? You go a different way, right? So that's called history. So you take the history and a counter. That's cool. But that's not how anything works today. They use something that looks a little like a neural network. So modern, you take all the execution flows, and then you do basically deep pattern recognition of how the program is executing. And you do that multiple different ways. And you have something that chooses what the best result is. There's a little supercomputer inside the computer. That's trying to predict branching. That calculates which way branches go. So the effective window that is worth finding grass and gets bigger. Why was that going to make me sad? Because that's amazing. It's amazingly complicated. Oh, wow. Well, here's the funny thing. So to get to 85% took a thousand bits. A thousand bits. To get to 99% takes tens of megabits. So this is one of those. To get the result, to get from a window of, say, 50 instructions to 500, it took three orders of magnitude or four orders of magnitude more bits. Now, if you get the prediction of a branch wrong, what happens then? You flush the pipe. You flush the pipe. So it's just the performance cost. But it gets even better. So we're starting to look at stuff that says, so they executed down this path, and then you had two ways to go. But far, far away, there's something that doesn't matter which path you went. So you took the wrong path, you executed a bunch of stuff. Then you had the mispredicting, you backed it up, but you remembered all the results you already calculated. Some of those are just fine. Like if you read a book and you misunderstand a paragraph, your understanding of the next paragraph sometimes is invariant to their understanding. Sometimes it depends on it. And you can kind of anticipate that invariance. Yeah, well, you can keep track of whether the data changed. And so when you come back to a piece of code, should you calculate it again or do the same thing? Okay, how much of this is art and how much of it is science? Science, because it sounds pretty complicated. So how do you describe a situation? So imagine you come to a point in the road, we have to make a decision. And you have a bunch of knowledge about which way to go. Maybe you have a map. So you want to go the shortest way, or do you want to go the fastest way, or you want to take the nicest road. So it's just some set of data. So imagine you're doing something complicated like building a computer. And there's hundreds of decision points, all with hundreds of possible ways to go. And the ways you pick interact in a complicated way. Right. And then you have to pick the right spot. Right. So that's art or science, I don't know. You avoided the question. You just described the Robert Frost problem of Road Less Taken. Described the Robert Frost problem? Uh, the- That's what we do as computer designers. It's all poetry. Okay. Great. Yeah, I don't know how to describe that. Because some people are very good at making those intuitive leaps. It seems like there's combinations of things. Some people are less good at it, but they're really good at evaluating the alternatives. Right. And everybody has a different way to do it. And some people can't make those leaps, but they're really good at analyzing it. So when you see computers are designed by teams of people who have very different skill sets. And a good team has lots of different kinds of people. I suspect you would describe some of them as artistic. But not very many. Unfortunately. Or fortunately. Unfortunately. Well, you know, computer design's hard. It's 99% perspiration. And- The 1% inspiration is really important. But you still need the 99. Yeah, you gotta do a lot of work. And then there's- there are interesting things to do at every level of that stack. So- At the end of the day, if you run the same program multiple times, does it always produce the same result? Is there some room for fuzziness there? That's a math problem. So if you run a correct C program, the definition is, every time you run it, you get the same answer. Yeah, that- well, that's a math statement. But that's a language definitional statement. So- Yes. For years, when people did- when we first did 3D acceleration of graphics, you could run the same scene multiple times and get different answers. Right. Right. And then some people thought that was okay, and some people thought it was a bad idea. And then when the HPC world used GPUs for calculations, they thought it was a really bad idea. Okay. Now, in modern AI stuff, people are looking at networks where the precision of the data is low enough that the data is somewhat noisy. And the observation is the input data is unbelievably noisy. So why should the calculation be not noisy? And people have experimented with algorithms that say can get faster answers by being noisy. Like as the network starts to converge, if you look at the computation graph, it starts out really wide, and then it gets narrower. And you can say, is that last little bit that important? Or should I start the graph on the next rev before we whittle it all the way down to the answer? Right. So you can create algorithms that are noisy. Now, if you're developing something, and every time you run it, you get a different answer, it's really annoying. And so most people think even today, every time you run the program, you get the same answer. Now I know, but the question is, that's the formal definition of a programming language. There is a definition of languages that don't get the same answer, but people who use those, you always want something because you get a bad answer. And then you're wondering, is it because of something in the algorithm or because of this? And so everybody wants a little switch that says, no matter what, do it deterministically. And it's really weird, because almost everything going into modern calculations is noisy. So why do the answers have to be so clear? So where do you stand? By design computers for people who run programs. So if somebody says, I want a deterministic answer, most people want that. Can you deliver a deterministic answer, I guess, is the question. Yeah, hopefully, sure. What people don't realize is you get a deterministic answer, even though the execution flow is very undeterministic. So you run this program 100 times, it never runs the same way twice, ever. And the answer, it arrives at the same answer. But it gets the same answer every time. It's just amazing. Okay, you've achieved in the eyes of many people, many people, a legend status as a chip art architect. What design creation are you most proud of? Perhaps because it was challenging, because of its impact, or because of the set of brilliant ideas that were involved in bringing it to life? I find that description odd. And I have two small children, and I promise you, they think it's hilarious. This question? Yeah. I do it for them. So I'm really interested in building computers. And I've worked with really, really smart people. I'm not unbelievably smart. I'm fascinated by how they go together, both as a thing to do and as an endeavor that people do. How people and computers go together? Yeah. Like how people think and build a computer. And I find sometimes that the best computer architects aren't that interested in people, or the best people managers aren't that good at designing computers. So the whole stack of human beings is fascinating. So the managers, the individual engineers. Yeah, yeah. So yeah, I said I realized after a lot of years of building computers, where you sort of build them out of transistors, logic gates, functional units, computational elements, that you could think of people the same way. So people are functional units. Yes. And then you could think of organizational design as a computer architectural problem. And then it's like, oh, that's super cool, because the people are all different, just like the computational elements are all different. And they like to do different things. And so I had a lot of fun reframing how I think about organizations. Just like with computers, we were saying execution paths, you can have a lot of different paths that end up at the same good destination. So what have you learned about the human abstractions from individual functional human units to the broader organization? What does it take to create something special? Well, most people don't think simple enough. All right, so do you know the difference between a recipe and the understanding? There's probably a philosophical description of this. So imagine you're gonna make a loaf of bread. The recipe says, get some flour, add some water, add some yeast, mix it up, let it rise, put it in a pan, put it in the oven. It's a recipe. Right, understanding bread, you can understand biology, supply chains, grain grinders, yeast, physics, thermodynamics. There's so many levels of understanding there. And then when people build and design things, they frequently are executing some stack of recipes. And the problem with that is the recipes all have limited scope. If you have a really good recipe book for making bread, it won't tell you anything about how to make an omelet. But if you have a deep understanding of cooking, then bread, omelets, sandwich, there's a different way of viewing everything. And most people, when you get to be an expert at something, you're hoping to achieve deeper understanding, not just a large set of recipes to go execute. And it's interesting to walk groups of people because executing recipes is unbelievably efficient, if it's what you want to do. If it's not what you want to do, you're really stuck. And that difference is crucial. And everybody has a balance of, let's say, deeper understanding recipes. And some people are really good at recognizing when the problem is to understand something deeply. Does that make sense? It totally makes sense. Does every stage of development, deep understanding on the team needed? Well, this goes back to the art versus science question. Sure. If you constantly unpack everything for deeper understanding, you never get anything done. Right. And if you don't unpack understanding when you need to, you'll do the wrong thing. And then at every juncture, like human beings are these really weird things because everything you tell them has a million possible outputs. Right? And then they all interact in a hilarious way. Yeah, it's very nice. And then having some intuition about what do you tell them, what do you do, when do you intervene, when do you not, it's complicated. Right, so... It's essentially computationally unsolvable. Yeah, it's an intractable problem, sure. Humans are a mess. Yeah, humans are a mess. But with deep understanding, do you mean also sort of fundamental questions of things like what is a computer? Or why? Like the why question is why are we even building this? Like of purpose? Or do you mean more like going towards the fundamental limits of physics, sort of really getting into the core of the science? Well, in terms of building a computer, think a little simpler. So, common practice is you build a computer, and then when somebody says, I want to make it 10% faster, you'll go in and say, all right, I need to make this buffer bigger, and maybe I'll add an ad unit. Or, you know, I have this thing that's three instructions wide, I'm going to make it four instructions wide. And what you see is each piece gets incrementally more complicated, right? And then at some point, you hit this limit, like adding another feature or buffer doesn't seem to make it any faster. And then people say, well, that's because it's a fundamental limit. And then somebody else will look at it and say, well, actually, the way you divided the problem up, and the way that different features are interacting, is limiting you, and it has to be rethought, rewritten, right? So then you refactor and rewrite it. And what people commonly find is the rewrite is not only faster, but half as complicated. From scratch? Yes. So how often in your career, but just have you seen as needed, maybe more generally, to just throw the whole thing out and start over? This is where I'm on one end of it, every three to five years. Which end are you on? Rewrite more often. Rewrite, and three to five years is? So if you want to really make a lot of progress on computer architecture, every five years, you should do one from scratch. So where does the x86-64 standard come in? Or what, how often do you? I wrote the, I was the co-author of that spec in 98. That's 20 years ago. Yeah, so that's still around. The instruction set itself has been extended quite a few times. Yes. And instruction sets are less interesting than the implementation underneath. There's been, on x86 architecture, Intel's designed a few, AIM's designed a few, very different architectures. And I don't want to go into too much of the detail about how often, but there's a tendency to rewrite it every 10 years, and it really should be every five. So you're saying you're an outlier in that sense in the- Rewrite more often. Rewrite more often. Well, and here's the problem- Isn't that scary? Yeah, of course. Well, scary to who? To everybody involved, because like you said, repeating the recipe is efficient. Companies want to make money, no, individual engineers want to succeed. So you want to incrementally improve, increase the buffer from three to four, will increase performance. So this is where you get into diminishing return curves. I think Steve Jobs said this, right? So you have a project and you start here and it goes up and they have diminishing return. And to get to the next level, you have to do a new one. And the initial starting point will be lower than the old optimization point, but it'll get higher. So now you have two kinds of fear, short-term disaster and long-term disaster. And you're haunted. So grownups, right? Yes. Like, people with a quarter by quarter business objective are terrified about changing everything. And people who are trying to run a business or build a computer for a long-term objective, know that the short-term limitations block them from the long-term success. So if you look at leaders of companies that had really good long-term success, every time they saw that they had to redo something, they did. And so somebody has to speak up? Or you do multiple projects in parallel. Like you optimize the old one while you build a new one. But the marketing guys, they're always like, promise me that the new computer is faster on every single thing. And the computer architect says, well, the new computer will be faster on the average. But there's a distribution of results and performance and you'll have some outliers that are slower. And that's very hard because they have one customer who cares about that one. So speaking of the long-term, for over 50 years now, Moore's law has served for me and millions of others as an inspiring beacon of what kind of amazing future brilliant engineers can build. I'm just making your kids laugh all of today. Yeah, that's great. So first, in your eyes, what is Moore's law, if you could define for people who don't know? Well, the simple statement was, from Gordon Moore, was double the number of transistors every two years, something like that. And then my operational model is, we increase the performance of computers by 2x every two or three years. And it's wiggled around substantially over time. And also, in how we deliver performance has changed. But the foundational idea was 2x the transistors every two years. The current cadence is something like, they call it a shrink factor, like 0.6 every two years, which is not 0.5. But that's referring strictly, again, to the original definition of just- Yeah, of transistor count. And shrink factor is just getting them smaller, smaller, smaller. Well, it's for a constant chip area. If you make the transistors smaller by 0.6, then you get one over 0.6 more transistors. So can you linger on it a little longer? What's the broader, what do you think should be the broader definition of Moore's Law? When you mentioned how you think of performance, just broadly, what's a good way to think about Moore's Law? Well, first of all, I've been aware of Moore's Law for 30 years. In which sense? Well, I've been designing computers for 40. You're just watching it before your eyes, kind of thing. Well, and somewhere where I became aware of it, I was also informed that Moore's Law was going to die in 10 to 15 years. And I thought that was true at first, but then after 10 years, it was going to die in 10 to 15 years. And then at one point, it was going to die in five years. And then it went back up to 10 years. And at some point, I decided not to worry about that particular prognostication for the rest of my life, which is fun. And then I joined Intel, and everybody said Moore's Law is dead. And I thought that's sad because it's the Moore's Law company, and it's not dead. And it's always been going to die. And humans like these apocryphal kind of statements like, we'll run out of food, or we'll run out of air, or run out of room, or run out of something. Right. But it's still incredible that it's lived for as long as it has. And yes, there's many people who believe now that Moore's Law is dead. You know, they can join the last 50 years of people who had the same idea. Yeah, there's a long tradition. But why do you think, if you can try to understand it, why do you think it's not dead currently? Let's just think, people think Moore's Law is one thing, transistors get smaller. But actually, under the sheet, there's literally thousands of innovations. And almost all those innovations have their own diminishing return curves. So, if you graph it, it looks like a cascade of diminishing return curves. I don't know what to call that. But the result is an exponential curve. At least it has been. So, and we keep inventing new things. So, if you're an expert in one of the things on a diminishing return curve, right, and you can see its plateau, you will probably tell people, well, this is done. Meanwhile, some other pile of people are doing something different. So, that's just normal. So, then there's the observation of how small could a switching device be? So, a modern transistor is something like a thousand by a thousand by a thousand atoms, right? And you get quantum effects down around two to ten atoms. So, you can imagine a transistor as small as ten by ten by ten. So, that's a million times smaller. And then the quantum computational people are working away at how to use quantum effects. So, a thousand by a thousand by a thousand atoms. That's a really clean way of putting it. Well, a fin, like a modern transistor, if you look at the fan, it's like 120 atoms wide, but we can make that thinner. And then there's a gate wrapped around it. And then there's spacing. There's a whole bunch of geometry. And, you know, a competent transistor designer could count both atoms in every single direction. Like, there's techniques now to already put down atoms in a single atomic layer. And you can place atoms if you want to. It's just, you know, from a manufacturing process, if placing an atom takes ten minutes and you need to put, you know, ten to the 23rd atoms together to make a computer, it would take a long time. So, the methods are, you know, both shrinking things and then coming up with effective ways to control what's happening. Lex Domogaroff Manufacture stably and cheaply. David Willis Yeah. So, the innovation stack's pretty broad. You know, there's equipment, there's optics, there's chemistry, there's physics, there's material science, there's metallurgy. There's lots of ideas about when you put different materials together, how do they interact? Are they stable? Are they stable over temperature? You know, like, are they repeatable? You know, there's like literally thousands of technologies involved. Lex Domogaroff But just for the shrinking, you don't think we're quite yet close to the fundamental limits of physics? David Willis I did a talk on Moore's Law and I asked for a roadmap to a path of 100. And after two weeks, they said, we only got to 50. Lex Domogaroff 100 what, sorry? David Willis 100x shrink. Lex Domogaroff 100x shrink? We only got to 50? David Willis And I said, why don't you give it another two weeks? Well, here's the thing about Moore's Law, right? So, I believe that the next 10 or 20 years of shrinking is going to happen, right? Now, as a computer designer, you have two stances. You think it's going to shrink, in which case you're designing and thinking about architecture in a way that you'll use more transistors. Or conversely, not be swamped by the complexity of all the transistors you get. Right? You have to have a strategy. You know? Lex Domogaroff So you're open to the possibility and waiting for the possibility of a whole new army of transistors ready to work? David Willis I'm expecting Lex Domogaroff Expecting. David Willis More transistors every two or three years, by a number large enough that how you think about design, how you think about architecture has to change. Like, imagine you build buildings out of bricks, and every year the bricks are half the size, or every two years. Well, if you kept building bricks the same way, so many bricks per person per day, the amount of time to build a building would go up exponentially. Lex Domogaroff Right. David Willis Right. But if you said, I know that's coming, so now I'm going to design equipment that moves bricks faster, uses them better, because maybe you're getting something out of the smaller bricks, more strength, thinner walls, less material, efficiency out of that. So once you have a roadmap with what's going to happen, transistors, we're going to get more of them, then you design all this collateral around it to take advantage of it, and also to cope with it. That's the thing people don't understand. It's like, if I didn't believe in Moore's law, and then Moore's law transistors showed up, my design teams were all drowned. Lex Domogaroff So what's the hardest part of this influx of new transistors? I mean, even if you just look historically, throughout your career, what's the thing, what fundamentally changes when you add more transistors in the task of designing an architecture? David Willis Well, there's two constants, right? One is people don't get smarter. I think- Lex Domogaroff By the way, there's some science showing that we do get smarter because of nutrition, whatever. Sorry to bring that up. David Willis Yeah, the Flint effect. Lex Domogaroff Yes. David Willis Yeah, I'm familiar with it. Nobody understands it. Nobody knows if it's still going on. So that's a- Lex Domogaroff Or whether it's real or not. But yeah. David Willis I sort of- Lex Domogaroff Anyway, but not exponentially. David Willis I would believe for the most part, people aren't getting much smarter. Lex Domogaroff The evidence doesn't support it. That's right. David Willis And then teams can't grow that much. Lex Domogaroff Right. David Willis So human beings, you know, we're really good in teams of 10, up to teams of 100, they can know each other. Beyond that, you have to have organizational boundaries. So you're kind of- you have- those are pretty hard constraints, right? So then you have to divide and conquer. As the designs get bigger, you have to divide it into pieces. The power of abstraction layers is really high. We used to build computers out of transistors. Now we have a team that turns transistors into logic cells and another team that turns them into functional units and another one that turns them into computers, right? So we have abstraction layers in there. And you have to think about when do you shift gears on that. We also use faster computers to build faster computers. So some algorithms run twice as fast on new computers, but a lot of algorithms are N squared. So, you know, a computer with twice as many transistors in it might take four times as long to run. So you have to refactor the software. Like simply using faster computers to build bigger computers doesn't work. So you have to think about all these things. So in terms of computing performance and the exciting possibility that more powerful computers bring, is shrinking the thing which you've been talking about, one of the- for you, one of the biggest exciting possibilities of advancement in performance? Or is there other directions that you're interested in? Like in the direction of sort of enforcing given parallelism or like doing massive parallelism in terms of many, many CPUs, you know, stacking CPUs on top of each other, that kind of parallelism or any kind of parallelism? Well, think about it in a different way. So old computers, you know, slow computers, you said, A equal B plus C times D. Pretty simple, right? And then we made faster computers with vector units and you can do proper equations and matrices, right? And then modern like AI computations or like convolutional neural networks where you convolve one large data set against another. And so there's sort of this hierarchy of mathematics, you know, from simple equation to linear equations to matrix equations to deeper kind of computation. And the data sets are getting so big that people are thinking of data as a topology problem. You know, data is organized in some immense shape. And then the computation, which sort of wants to be get data from immense shape and do some computation on it. So the- what computers have allowed people to do is have algorithms go much, much further. So that paper you referenced, the Sutton paper, they talked about, you know, like when AI started, it was apply rule sets to something. That's a very simple computational situation. And then when they did first chess thing, they solved deep searches. So have a huge database of moves and results, deep search, but it's still just a search, right? Now we take large numbers of images and we use it to train these weight sets that we convolve across to completely different kind of phenomena. We call that AI. Now they're doing the next generation. And if you look at it, they're going up this mathematical graph, right? And then computations, both computation and data sets support going up that graph. Yeah, the kind of computation that might, I mean, I would argue that all of it is still a search, right? Just like you said, a topology problem of data sets, you're searching the data sets for valuable data. And also the actual optimization of neural networks is a kind of search for the- I don't know. If you had looked at the inner layers of finding a cat, it's not a search. It's a set of endless projections. So, you know, a projection, here's a shadow of this phone, right? And then you can have a shadow of that onto something, a shadow on that of something. And if you look in the layers, you'll see this layer actually describes pointy ears and round eyedness and fuzziness. But the computation to tease out the attributes is not search. Like the inference part might be search, but the training is not search. And then in deep networks, they look at layers and they don't even know it's represented. And yet, if you take the layers out, it doesn't work. So, I don't think it's search. All right, well- But you have to talk to a mathematician about what that actually is. Well, we could disagree, but it's just semantics. I think it's not, but it's certainly not- I would say it's absolutely not semantics, but- Okay. All right. Well, if you want to go there. So, optimization to me is search. And we're trying to optimize the ability of a neural network to detect cat ears. And the difference between chess and the space, the incredibly multi-dimensional, 100,000 dimensional space that networks are trying to optimize over is nothing like the chess board database. So, it's a totally different kind of thing. And okay, in that sense, you can say that it loses the meaning. I can see how you might say. The funny thing is, it's the difference between given search space and found search space. Right, exactly. Yeah, maybe that's a different way to describe it. That's a beautiful way to put it. Okay. But you're saying, what's your sense in terms of the basic mathematical operations and the architectures, computer hardware that enables those operations? Do you see the CPUs of today still being a really core part of executing those mathematical operations? Yes. Well, the operations continue to be add, subtract, load, store, compare, and branch. It's remarkable. So, it's interesting that the building blocks of computers or transistors, under that, atoms. So, you got atoms, transistors, logic gates, computers, functional units of computers. The building blocks of mathematics at some level are things like adds and subtracts and multiplies. But the space mathematics can describe is, I think, essentially infinite. But the computers that run the algorithms are still doing the same things. Now, a given algorithm might say, I need sparse data, or I need 32-bit data, or I need like a convolution operation that naturally takes 8-bit data, multiplies it, and sums it up a certain way. So, the data types in TensorFlow imply an optimization set. But when you go right down and look at the computers, it's and and or gates doing adds and multiplies. That hasn't changed much. Now, the quantum researchers think they're going to change that radically. And then there's people who think about analog computing because you look in the brain and it seems to be more analogish. You know, that maybe there's a way to do that more efficiently. But we have a million X on computation. And I don't know the relationship between computational, let's say, intensity and ability to hit mathematical abstractions. I don't know any way to describe that. But just like you saw in AI, you went from rule sets to simple search to complex search to, say, found search. Like, those are, you know, orders of magnitude more computation to do. And as we get the next two orders of magnitude, like a friend, Roger Godori, said, like, every order of magnitude changes the computation. Fundamentally changes what the computation is doing. Yeah. Oh, you know, the expression of difference in quantity is a difference in kind. You know, the difference between ant and anthill, right? Or neuron and brain. You know, there's this indefinable place where the quantity changed the quality, right? And we've seen that happen in mathematics multiple times. And, you know, my guess is it's going to keep happening. So, in your sense, is it, yeah, if you focus head down and shrinking the transistor? The transistor. Well, not just head down. We're aware of the software stacks that are running and the computational loads. And we're kind of pondering what do you do with a petabyte of memory that wants to be accessed in a sparse way and have, you know, the kind of calculations AI programmers want. So, there's a dialogue and interaction. But when you go in the computer chip, you know, you find adders and subtractors and multipliers. And so, if you zoom out then with, as you mentioned, Rich Sutton, the idea that most of the development in the last many decades in AI research came from just leveraging computation and just simple algorithms waiting for the computation to improve. Well, software guys have a thing that they call it the problem of early optimization. Right. So, you write a big software stack and if you start optimizing, like, the first thing you write, the odds of that being the performance limiter is low. Right. But when you get the whole thing working, can you make it 2x faster by optimizing the right things? Sure. While you're optimizing that, could you've written a new software stack, which would have been a better choice? Maybe. Now you have creative tension. So... But the whole time as you're doing the writing, that's the software we're talking about. The hardware underneath gets faster and faster. Well, it goes back to the Moore's Law. If Moore's Law is going to continue, then your AI research should expect that to show up. And then you make a slightly different set of choices. Then we've hit the wall, nothing's going to happen. And from here, it's just us rewriting algorithms. Like, that seems like a failed strategy for the last 30 years of Moore's Law's death. So... So can you just linger on it? I think you've answered it, but I'll just ask the same dumb question over and over. So why do you think Moore's Law is not going to die? Which is the most promising, exciting possibility of why it won't die in the next 5, 10 years? So is it the continued shrinking of the transistor, or is it another S-curve that steps in and it totally sort of... Well, shrinking the transistor is literally thousands of innovations. Right. So there's... There's a whole bunch of S-curves just kind of running their course and being reinvented and new things. The semiconductor fabricators and technologists have all announced what's called nanowires. So they took a fan, which had a gate around it and turned that into little wires, so you have better control of that, and they're smaller. And then from there, there are some obvious steps about how to shrink that. The metallurgy around wire stacks and stuff has very obvious abilities to shrink. And, you know, there's a whole combination of things there to do. Your sense is that we're going to get a lot if this innovation from just that shrinking. Yeah, like a factor of a hundred. It's a lot. Yeah, I would say that's incredible. And it's totally unknown... It's only 10 or 15 years. Now, you're smart and you might know, but to me, it's totally unpredictable of what that 100x would bring in terms of the nature of the computation that people would be... Yeah, you're familiar with Bell's Law. So for a long time, it was mainframes, minis, workstation, PC, mobile. Moore's Law drove faster, smaller computers. Right. And then when we were thinking about Moore's Law, Raja Goddari said, every 10x generates a new computation. So scalar, vector, matrix, topological computation. And if you go look at the industry trends, there was mainframes and minicomputers and PCs, and then the internet took off, and then we got mobile devices, and now we're building 5G wireless with one millisecond latency. And people are starting to think about the smart world where everything knows you, recognizes you. The transformations are going to be unpredictable. How does it make you feel that you're one of the key architects of this kind of future? So you're not... we're not talking about the architects of the high-level people who build Angry Bird apps and Snapchat. Angry Bird apps. Who knows? Maybe that's the whole point of the universe. I'm going to take a stand at that, and the attention-distracting nature of mobile phones. I'll take a stand. But anyway, in terms of... I don't think that matters much. The side effects of smartphones or the attention distraction, which part? Well, who knows where this is all leading? It's changing so fast. My parents used to yell at my sisters for hiding in the closet with a wired phone with a dial on it. Stop talking to your friends all day. Now my wife yells at my kids for talking to their friends all day on text. It looks the same to me. It's always... it echoes of the same thing. Okay, but you are one of the key people architecting the hardware of this future. How does that make you feel? Do you feel responsible? Do you feel excited? So we're in a social context, so there's billions of people on this planet. There are literally millions of people working on technology. I feel lucky to be doing what I do and getting paid for it, and there's an interest in it. But there's so many things going on in parallel. It's like the actions are so unpredictable. If I wasn't here, somebody else would do it. The vectors of all these different things are happening all the time. I'm sure some philosopher or meta-philosophers are wondering about how we transform our world. So you can't deny the fact that these tools are changing our world. That's right. So do you think it's changing for the better? Somebody... I read this thing recently. It said the two disciplines with the highest GRE scores in college are physics and philosophy. And they're both sort of trying to answer the question, why is there anything? And the philosophers are on the kind of theological side, and the physicists are obviously on the material side. And there's 100 billion galaxies with 100 billion stars. It seems, well, repetitive at best. So there's on our way to 10 billion people. I mean, it's hard to say what it's all for, if that's what you're asking. Yeah, I guess I am. Things do tend to significantly increases in complexity. And I'm curious about how computation, like our world, our physical world inherently generates mathematics. It's kind of obvious, right? So we have XYZ coordinates. You take a sphere, you make it bigger, you get a surface that grows by R squared. It generally generates mathematics. And the mathematicians and the physicists have been having a lot of fun talking to each other for years. And computation has been, let's say, relatively pedestrian. Like computation in terms of mathematics has been doing binary algebra, while those guys have been gallivanting through the other realms of possibility, right? Now, recently, the computation lets you do mathematical computations that are sophisticated enough that nobody understands how the answers came out. Right. Machine learning. Machine learning. Yeah. But it used to be, you get data set, you guess at a function. The function is considered physics if it's predictive of new functions, new data sets. Modern, you can take a large data set with no intuition about what it is and use machine learning to find a pattern that has no function, right? And it can arrive at results that I don't know if they're completely mathematically describable. So computation has kind of done something interesting compared to A equal B plus C. There's something reminiscent of that step from the basic operations of addition to taking a step towards neural networks that's reminiscent of what life on earth at its origins was doing. Do you think we're creating sort of the next step in our evolution in creating artificial intelligence systems that will- I don't know. I mean, there's so much in the universe already, it's hard to say. Where we stand in this whole thing. Are human beings working on additional abstraction layers and possibilities? Yeah, it appears so. Does that mean that human beings don't need dogs? No. There's so many things that are all simultaneously interesting and useful. Well, you've seen, throughout your career, you've seen greater and greater level abstractions built in artificial machines, right? Do you think, when you look at humans, do you think look of all life on earth as a single organism building this thing, this machine with greater and greater levels of abstraction, do you think humans are the peak, the top of the food chain in this long arc of history on earth? Or do you think we're just somewhere in the middle? Are we the basic functional operations of a CPU? Are we the C++ program, the Python program, or with the neural network? Like somebody's, you know, people have calculated like how many operations does the brain do? Something, you know, I've seen the number 10 to the 18th a bunch of times, a bunch of times, arrived different ways. So could you make a computer that did 10 to the 20th operations? Yes. Sure. Do you think? We're gonna do that. Now, is there something magical about how brains compute things? I don't know. You know, my personal experience is interesting because, you know, you think you know how you think, and then you have all these ideas, and you can't figure out how they happened. And if you meditate, you know, like what you can be aware of is interesting. So I don't know if brains are magical or not. You know, the physical evidence says no. Lots of people's personal experience says yes. So what would be funny is if brains are magical, and yet we can make brains with more computation. You know, I don't know what to say about that, but... But do you think magic is an emergent phenomena? What... It could be. I have no explanation for it. I'm an engineer. Let me ask Jim Keller, what in your view is consciousness? What's consciousness? Yeah, like what, you know, consciousness, love, things that are these deeply human things that seems to emerge from our brain. Is that something that we'll be able to make encode in chips that get faster and faster and faster and faster? That's like a 10-hour conversation. Nobody really knows. Can you summarize it in a couple of sentences? A couple of words. Many people have observed that organisms run at lots of different levels, right? If you had two neurons, somebody said you'd have one sensory neuron and one motor neuron, right? So we move towards things and away from things, and we have physical integrity and safety or not, right? And then if you look at the animal kingdom, you can see brains that are a little more complicated. And at some point there's a planning system, and then there's an emotional system that's, you know, happy about being safe or unhappy about being threatened, right? And then our brains have massive numbers of structures, you know, like planning and movement and thinking and feeling and drives and emotions. And we seem to have multiple layers of thinking systems. And we have a brain, a dream system that nobody understands whatsoever, which I find completely hilarious. And you can think in a way that those systems are more independent and you can observe, you know, the different parts of yourself can observe them. I don't know which one's magical. I don't know which one's not computational. So. Is it possible that it's all computation? Probably. Is there a limit to computation? I don't think so. Do you think the universe is a computer? Like, it seems to be. It's a weird kind of computer, because if it was a computer, right? Like when they do calculations on what it, how much calculation it takes to describe quantum effects is unbelievably high. So if it was a computer, wouldn't you have built it out of something that was easier to compute? Right. That's a funny, it's a funny system. But then the simulation guys have pointed out that the rules are kind of interesting. Like, when you look really close, it's uncertain. And the speed of light says you can only look so far and things can't be simultaneous, except for the odd entanglement problem where they seem to be. Like, the rules are all kind of weird. And somebody said physics is like having 50 equations with 50 variables to define 50 variables. Like, you know, it's, you know, like physics itself has been a shit show for thousands of years. It seems odd when you get to the corners of everything, you know, it's either uncomputable or undefinable or uncertain. It's almost like the designers of the simulation are trying to prevent us from understanding it perfectly. But also the things that require calculations require so much calculation that our idea of the universe of a computer is absurd because every single little bit of it takes all the computation in the universe to figure out. So that's a weird kind of computer. You know, you say the simulation is running in the computer, which has by definition infinite computation. Not infinite. Oh, you mean if the universe is infinite? Well, yeah. Well, every little piece of our universe seems to take infinite computation. Not infinite, just a lot. Well, a lot's a pretty big number. Compute this little teeny spot takes all the mass in the local one light year by one light year space. It's close enough to infinite. Oh, it's a heck of a computer if it is one. I know. It's a weird description because the simulation description seems to break when you look closely at it. But the rules of the universe seem to imply something's up. That seems a little arbitrary. The universe, the whole thing, the laws of physics, it just seems like how did it come out to be the way it is? Well, lots of people talk about that. Like I said, the two smartest groups of humans are working on the same problem. From different sides. Different aspects and they're both complete failures. For now. That's kind of cool. They might succeed eventually. Well, after 2000 years, the trend isn't good. Oh, 2000 years is nothing in the span of the history of the universe. So we have some time. But the next 1000 years doesn't look good either. That's what everybody says at every stage. But with Moore's law, as you've just described, not being dead, the exponential growth of technology, the future seems pretty incredible. Well, it'll be interesting, that's for sure. That's right. So what are your thoughts on Ray Kurzweil's sense that exponential improvement in technology will continue indefinitely? Is that how you see Moore's law? Do you see Moore's law more broadly in the sense that technology of all kinds has a way of stacking S-curves on top of each other where it'll be exponential and then we'll see all kinds of- What does an exponential of a million mean? That's a pretty amazing number. And that's just for a local little piece of silicon. Now let's imagine you say decided to get a thousand tons of silicon to collaborate in one computer at a million times the density. Like now you're talking, I don't know, 10 to the 20th more computation power than our current already unbelievably fast computers. Nobody knows what that's going to mean. You know, the sci-fi guys call it, you know, computronium. Like when a local civilization turns the nearby star into a computer. Right. Like, I don't know if that's true, but- So just even when you shrink a transistor, the- That's only one dimension. The ripple effects of that- Like people tend to think about computers as a cost problem, right? So computers are made out of silicon and minor amounts of metals and, you know, this and that. This and that. None of those things cost any money. Like there's plenty of sand. Like you could just turn the beach and a little bit of ocean water into computers. So all the cost is in the equipment to do it. And the trend on equipment is once you figure out how to build the equipment, the trend of cost is zero. Elon said, first you figure out what configuration you want the atoms in and then how to put them there. Right? Yeah. Because, well, here's the, you know, his great insight is people are how constrained. I have this thing, I know how it works. And then little tweaks to that will generate something as opposed to what do I actually want and then figure out how to build it. It's a very different mindset. And almost nobody has it, obviously. Well, let me ask on that topic. You were one of the key early people in the development of autopilot, at least in the hardware side. Elon Musk believes that autopilot and vehicle autonomy, if you just look at that problem, can follow this kind of exponential improvement. In terms of the how question that we're talking about, there's no reason why he can't. What are your thoughts on this particular space of vehicle autonomy? And you're a part of it and Elon Musk's and Tesla's vision for... Well, the computer you need to build was straightforward. And you could argue, well, does it need to be two times faster or five times or 10 times? But that's just a matter of time or price in the short run. So that's not a big deal. You don't have to be especially smart to drive a car. So it's not like a super hard problem. I mean, the big problem with safety is attention, which computers are really good at, not skills. Well, let me push back on one. You see, everything you said is correct. But we as humans tend to take for granted how incredible our vision system is. So... You can drive a car with 20, 50 vision, and you can train a neural network to extract the distance of any object and the shape of any surface from a video and data. Yeah, but that... It's really simple. No, it's not simple. That's a simple data problem. It's not simple. It's not simple. It's because it's not just detecting objects, it's understanding the scene. And it's being able to do it in a way that doesn't make errors. So the beautiful thing about the human vision system and our entire brain around the whole thing is we're able to fill in the gaps. It's not just about perfectly detecting cars. It's inferring the occluded cars. It's trying to... It's understanding the physics. I think that's mostly a data problem. So you think what data would compute with improvement of computation, with improvement in collection? Well, there is a... You know, when you're driving a car and somebody cuts you off, your brain has theories about why they did it. You know, they're a bad person, they're distracted, they're dumb. You know, you can listen to yourself. Right. So, you know, if you think that narrative is important to be able to successfully drive a car, then current autopilot systems can't do it. But if cars are ballistic things with tracks and probabilistic changes of speed and direction, and roads are fixed and given by the way, they don't change dynamically. Right. You can map the world really thoroughly. You can place every object really thoroughly. Right. You can calculate trajectories of things really thoroughly. Right. But everything you said about really thoroughly has a different degree of difficulty. So... And you could say at some point, computer autonomous systems will be way better at things that humans are lousy at. Like, they'll be better at attention. They'll always remember there was a pothole in the road that humans keep forgetting about. They'll remember that this set of roads has these weirdo lines on it that the computers figured out once. And especially if they get updates, so if somebody changes a given, like the key to robots and stuff, somebody said is to maximize the givens. Right. Right. Right. So having a robot pick up this bottle cap is way easier to put a red dot on the top. Because then you have to figure out, you know, and if you want to do a certain thing with it, you know, maximize the givens is the thing. And autonomous systems are happily maximizing the givens. Like, like humans, when you drive someplace new, you remember it because you're processing it the whole time. And after the 50th time you drove to work, you get to work, you don't know how you got there. Right. You're on autopilot. Right. Autonomous cars are always on autopilot. But the cars have no theories about why they got cut off or why they're in traffic. So they also never stopped paying attention. Right. So I tend to believe you do have to have theories, mental models of other people, especially with pedestrian and cyclists, but also with other cars. So everything you said is, like, is actually essential to driving. Driving is a lot more complicated than people realize, I think. So sort of to push back slightly, but to... So to cut into traffic, right? Yep. You can't just wait for a gap. You have to be somewhat aggressive. You'll be surprised how simple a calculation for that is. I may be on that particular point, but there's... Yeah. Maybe I should have to push back. I would be surprised. You know what? Yeah, I'll just say where I stand. I would be very surprised, but I think you might be surprised how complicated it is. I tell people, like, progress disappoints in the short run, surprises in the long run. It's very possible. Yeah. I suspect in 10 years, it'll be just like taken for granted. Yeah, probably. But you're probably right. And I'll look like... It's going to be a $50 solution that nobody cares about. It's like GPS is like, wow, GPS, we have satellites in space that tell you where your location is. It was a really big deal. Now everything has a GPS in it. Yeah, it's true. But I do think that systems that involve human behavior are more complicated than we give them credit for. So we can do incredible things with technology that don't involve humans. But when you... I think humans are less complicated than people, you know, frequently ascribed. Maybe I... We tend to operate out of large numbers of patterns and just keep doing it over and over. But I can't trust you because you're a human. That's something a human would say. But my hope is on the point you've made is even if no matter who's right, I'm hoping that there's a lot of things that humans aren't good at that machines are definitely good at, like you said, attention and things like that. Well, they'll be so much better that the overall picture of safety and autonomy will be obviously cars will be safer, even if they're not as good at it. I'm a big believer in safety. I mean, there are already the current safety systems like cruise control that doesn't let you run into people and lane keeping. There are so many features that you just look at the Pareto of accidents and knocking off like 80% of them is, you know, super doable. So just to linger on the autopilot team and the efforts there, it seems to be that there's a very intense scrutiny by the media and the public in terms of safety, the pressure, the bar put before autonomous vehicles. What are your sort of as a person there working on the hardware and trying to build a system that builds a safe vehicle and so on, what was your sense about that pressure? Is it unfair? Is it expected of new technology? Yeah, it seems reasonable. I was interested. I talked to both American and European regulators, and I was worried that the regulations would write into the rules technology solutions like modern brake systems imply hydraulic brakes. So if you read the regulations to meet the letter of the law for brakes, it sort of has to be hydraulic, right? And the regulator said they're interested in the use cases like a head on crash, an offset crash. Don't hit pedestrians. Don't run into people. Don't leave the road. Don't run a red light or a stoplight. They were very much into the scenarios. And, you know, and they had all the data about which scenarios injured or killed the most people. And for the most part, those conversations were like, what's the right thing to do to take the next step? Now, Elon's very interested also in the benefits of autonomous driving are freeing people's time and attention as well as safety. And I think that's also an interesting thing. But, you know, building autonomous systems so they're safe and safer than people seemed since the goal is to be 10x safer than people, having the bar to be safer than people and scrutinizing accidents seems philosophically correct. So I think that's a good thing. What are, it's different than the things you worked at, the Intel, AMD, Apple with autopilot chip design and hardware design. What are interesting or challenging aspects of building this specialized kind of computing system in the automotive space? I mean, there's two tricks to building like an automotive computer. One is the software team, the machine learning team is developing algorithms that are changing fast. So as you're building the accelerator, you have this, you know, worry or intuition that the algorithms will change enough that the accelerator will be the wrong one. Right. And there's a generic thing, which is if you build a really good general purpose computer, general purpose computer, say its performance is one and then GPU guys will deliver about 5x to performance for the same amount of silicon, because instead of discovering parallelism, you're given parallelism. And then special accelerators get another two to 5x on top of a GPU because you say, I know the math is always eight bit integers into 32 bit accumulators and the operations are the subset of mathematical possibilities. So auto, you know, AI accelerators have a claimed performance benefit over GPUs because in the narrow math space, you're nailing the algorithm. Now, you still try to make it programmable, but the AI field is changing really fast. So there's a, you know, there's a little creative tension there of, I want the acceleration afforded by specialization without being over specialized so that the new algorithm is so much more effective that you would have been better off on a GPU. So there is a tension there. To build a good computer for an application like automotive, there's all kinds of sensor inputs and safety processors and a bunch of stuff. So one of Elon's goals to make it super affordable. So every car gets an autopilot computer. So some of the recent startups you look at, and they have a server in the trunk because they're saying, I'm going to build this autopilot computer replaces the driver. So their cost budget's 10 or $20,000. And Elon's constraint was, I'm going to put one in every car, whether people buy autonomous driving or not. So the cost constraint he had in mind was great. Right. And to hit that, you had to think about the system design. That's complicated. It's fun. You know, it's like, it's like, it's Crestman's work. Like, you know, a violin maker, right? You can say Stradivarius is this incredible thing. The musicians are incredible. But the guy making the violin, you know, picked wood and sanded it and then he cut it, you know, and he glued it and, you know, and he waited for the right day so that when he put the finish on it, it didn't, you know, do something dumb. That's craftsman's work, right? You may be a genius craftsman because you have the best techniques and you discover a new one, but most engineers, craftsmen's work and humans really like to do that. You know, it's smart humans. No, everybody. All humans. I don't know. I used to, I dug ditches when I was in college. I got really good at it. Satisfying. Yeah. So. Digging ditches is also craftsman work. Yeah, of course. So, so there's an expression called complex mastery behavior. So when you're learning something, that's fun because you're learning something. When you do something and it's rote and simple, it's not that satisfying. But if the steps that you have to do are complicated and you're good at them, it's satisfying to do them. And then if you're intrigued by it all, as you're doing them, you sometimes learn new things that you can raise your game. But craftsman's work is good. And engineers, like engineering is complicated enough that you have to learn a lot of skills. And then a lot of what you do is then craftsman's work, which is fun. Autonomous driving, building a very resource constrained computer. So a computer has to be cheap enough that put in every single car. That's essentially boils down to craftsman's work. It's engineering. You know, there's thoughtful decisions and problems to solve and trade-offs to make. You need 10 camera in ports or eight, you know, you're building for the current car or the next one. You know, how do you do the safety stuff? You know, there's, there's a whole bunch of details, but it's fun, but it's not like I'm building a new type of neural network, which has a new mathematics and a new computer to work. You know, that that's like, there's, there's more invention than that, but the rejection to practice, once you pick the architecture, you look inside and what do you see adders and multipliers and memories and, you know, the basics. So computers is always this, this weird set of abstraction layers of ideas and thinking that reduction to practice is transistors and wires and, you know, pretty basic stuff. And that's an interesting phenomenon. By the way, like factory work, like lots of people think factory work is road assembly stuff. I've been on the assembly line. Like the people who work there really like it. It's a really great job. It's really complicated. Putting cars together is hard, right? And the car is moving and the parts are moving and sometimes the parts are damaged and you have to coordinate putting all the stuff together and people are good at it. They're good at it. And I remember one day I went to work and the line was shut down for some reason. The line was shut down for some reason and some of the guys sitting around were really bummed because they had reorganized a bunch of stuff and they were going to hit a new record for the number of cars built that day and they were all gung ho to do it. And these are big, tough buggers. You know, but what they did was complicated and you couldn't do it. Yeah. And I mean. Well, after a while you could, but you'd have to work your way up because, you know, like putting the bright, what's called the brights, the trim on a car on a moving assembly line where it has to be attached 25 places in a minute and a half is unbelievably complicated and human beings can do it. It's really good. I think that's harder than driving a car, by the way. Putting together, working in a factory. Too smart people can disagree. Yay. I think driving a car. Well, we'll get you in the factory someday and then we'll see how you do. Not for us humans driving a car is easy. I'm saying building a machine that drives a car is not easy. No. Okay. Okay. Driving a car is easy for humans because we've been evolving for billions of years. Drive cars. Yeah. I noticed that. To do. The paleolithic cars are super cool. Oh, now you join the rest of the internet in mocking me. Okay. I wasn't mocking you. I was just, you know, intrigued by your, you know, your anthropology. Yeah. I'll have to go dig into that. There's some inaccuracies there. Yes. Okay. But in general, what have you learned in terms of thinking about passion, craftsmanship, tension, chaos, you know, the whole mess of it? What have you learned, have taken away from your time working with Elon Musk, working at Tesla, which is known to be a place of chaos, innovation, craftsmanship, and all those things? I really like the way he thought. Like, you think you have an understanding about what first principles of something is, and then you talk to Elon about it, and you didn't scratch the surface. You know, he has a deep belief that no matter what you do, it's a local maximum. Right. And I had a friend, he invented a better electric motor, and it was like a lot better than what we were using. And one day he came by, he said, you know, I'm a little disappointed because, you know, this is really great, and you didn't seem that impressed. And I said, you know, when the super intelligent aliens come, are they going to be looking for you? Like, where is he? The guy who built the motor. Yeah. Probably not, you know, like, but doing interesting work that's both innovative, and let's say craftsman's work on the current thing, it's really satisfying, and it's good. And that's cool. And then Elon was good at taking everything apart, like, what's the deep first principle? Oh, no, what's really, no, what's really, you know, that ability to look at it without assumptions and how constraints is super wild. You know, he built a rocket ship and electric car and everything. And that's super fun, and he's into it too. Like, when they first landed two SpaceX rockets to Tesla, we had a video projector in the big room, and like 500 people came down, and when they landed, everybody cheered, and some people cried. It was so cool. All right, but how did you do that? Well, it was super hard. And then people say, well, it's chaotic. Really? To get out of all your assumptions, you think that's not going to be unbelievably painful? And is Elon tough? Yeah, probably. The people look back on it and say, boy, I'm really happy I had that experience to go take apart that many layers of assumptions. Sometimes super fun, sometimes painful. So it could be emotionally and intellectually painful, that whole process of just stripping away assumptions. Yeah, imagine 99% of your thought process is protecting your self-conception. And 98% of that's wrong. Yeah. Now you've got the math right. How do you think you're feeling when you get back into that one bit that's useful, and now you're open and you have the ability to do something different? I don't know if I got the math right. It might be 99.9, but it ain't 50. Imagining that 50% is hard enough. Yeah. Now, for a long time, I've suspected you could get better. Like you can think better, you can think more clearly, you can take things apart. And there's lots of examples of that, people who do that. And Elon is an example of that. Apparently. You are an example. I don't know if I am. I'm fun to talk to. Certainly. I've learned a lot of stuff. Right. Well, here's the other thing is, like, I joke, like I read books, and people think, oh, you read books. Well, no, I've read a couple of books. No, I've read a couple of books a week for 55 years. Wow. Well, maybe 50, because I didn't learn to read until I was eight or something. And it turns out when people write books, they often take 20 years of their life where they passionately did something, reduce it to 200 pages. That's kind of fun. And then you go online and you can find out who wrote the best books and who, like, you know, that's kind of wild. So there's this wild selection process. And then you can read it and for the most part, understand it. And then you can go apply it. Like, I went to one company, I thought, I haven't managed much before. So I read 20 management books. And I started talking to them and basically compared to all the VPs running around, I'd read 19 more management books than anybody else. It wasn't even that hard. And half the stuff worked, like, first time. It wasn't even rocket science. But at the core of that is questioning the assumptions or sort of entering the thinking, first principles thinking, sort of looking at the reality of the situation and using that knowledge, applying that knowledge. So, yeah. So I would say my brain has this idea that you can question first assumptions. But I can go days at a time and forget that. And you have to kind of like circle back that observation. Because it is emotionally challenging. Well, it's hard to just keep it front and center because you operate on so many levels all the time. And getting this done takes priority or being happy takes priority or screwing around takes priority. Like, how you go through life is complicated. And then you remember, oh, yeah, I could really think first principles. Oh, shit, that's tiring, you know. But you do for a while, and that's kind of cool. So just as a last question in your sense from the big picture, from the first principles, do you think, you kind of answered already, but do you think autonomous driving is something we can solve on a timeline of years? So one, two, three, five, ten years as opposed to a century? Yeah, definitely. Just to linger on it a little longer, where's the confidence coming from? Is it the fundamentals of the problem, the fundamentals of building the hardware and the software? As a computational problem, understanding ballistics, roles, topography, it seems pretty solvable. I mean, and you can see this, you know, like speech recognition for a long time, people are doing, you know, frequency and domain analysis and all kinds of stuff. And that didn't work for at all, right? And then they did deep learning about it, and it worked great. And it took multiple iterations. And, you know, autonomous driving is way past the frequency analysis point. You know, use radar, don't run into things. And the data gathering is going up, and the computation is going up, and the algorithm understanding is going up. And there's a whole bunch of problems getting solved like that. The data side is really powerful, but I disagree with both you and Elon. I'll tell Elon once again, as I did before, that when you add human beings into the picture, it's no longer a ballistics problem. It's something more complicated. But I could be very well proven wrong. Cars are highly damped in terms of rate of change. Like the steering system is really slow compared to a computer. The acceleration of the acceleration is really slow. Yeah, on a certain time scale, on a ballistics time scale, but human behavior, I don't know. I shouldn't say... Human beings are really slow too. Weirdly, we operate, you know, half a second behind reality. Nobody really understands that one either. It's pretty funny. Yeah. Yeah. So. We very well could be surprised. And I think with the rate of improvement in all aspects on both the compute and the software and the hardware, there's going to be pleasant surprises all over the place. Speaking of unpleasant surprises, many people have worries about a singularity in the development of AI. Forgive me for such questions. Yeah. When AI improves exponentially and reaches the point of superhuman level, general intelligence, you know, beyond the point, there's no looking back. Do you share this worry of existential threats from artificial intelligence from computers becoming superhuman level intelligent? No, not really. You know, like we already have a very stratified society. And then if you look at the whole animal kingdom of capabilities and abilities and interests, and, you know, smart people have their niche and, you know, normal people have their niche and craftsmen have their niche and, you know, animals have their niche. I suspect that the domains of interest for things that, you know, astronomically different, like the whole something got 10 times smarter than us and wanted to track us all down because what, we like to have coffee at Starbucks? Like, it doesn't seem plausible. Now, is there an existential problem that how do you live in a world where there's something way smarter than you and you base your kind of self-esteem on being the smartest local person? Well, there's what, 0.1% of the population who thinks that because the rest of the population has been dealing with it since they were born. So the breadth of possible experience that can be interesting is really big. And, you know, superintelligence seems likely, although we still don't know if we're magical, but I suspect we're not. And it seems likely that it will create possibilities that are interesting for us. And its interests will be interesting for that, for whatever it is. It's not obvious why its interests would somehow want to fight over some square foot of dirt or, you know, whatever, you know, the usual fears are about. So you don't think you'll inherit some of the darker aspects of human nature? Depends on how you think reality is constructed. So for whatever reason, human beings are in, let's say, creative tension and opposition with both our good and bad forces. Like there's lots of philosophical understanding of that. Right. I don't know why that would be different. So you think the evil is necessary for the good? I mean, the tension. I don't know about evil, but like we live in a competitive world where your good is somebody else's evil. You know, there's the malignant part of it, but that seems to be self-limiting, although occasionally it's super horrible. But yes, there's a debate over ideas and some people have different beliefs and that debate itself is a process. So arriving at something. Yeah, and why wouldn't that continue? Yeah. But you don't think that whole process will leave humans behind in a way that's painful? Emotionally painful, yes. For the 0.1%, there'll be... Why isn't it already painful for a large percentage of the population? And it is. I mean, society does have a lot of stress in it, about the 1% and about to this and about to that. But everybody has a lot of stress in their life about what they find satisfying and know yourself seems to be the opposite. And know yourself seems to be the proper dictum and pursue something that makes your life meaningful seems proper. And there's so many avenues on that. Like there's so much unexplored space at every single level. You know, I'm somewhat of... My nephew called me a jaded optimist. And, you know, so it's... There's a beautiful tension in that label. But if you were to look back at your life and could relive a moment, a set of moments, because they were the happiest times of your life outside of family, what would that be? I don't want to relive any moments. I like that. I like that situation where you have some amount of optimism and then the anxiety of the unknown. So you love the unknown, the mystery of it. I don't know about the mystery. It sure gets your blood pumping. What do you think is the meaning of this whole thing? Of life on this pale blue dot? It seems to be what it does. Like the universe, for whatever reason, makes atoms, which makes us, which we do stuff. And we figure out things and we explore things and... That's just what it is. It's not just. Yeah, it is. Jim, I don't think there's a better place to end it. It's a huge honor. And... Well, that's super fun. Thank you so much for talking today. All right. Great. Thanks for listening to this conversation. And thank you to our presenting sponsor, Cash App. Download it. Use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to become future leaders and innovators. If you enjoy this podcast, subscribe on YouTube, get five stars on Apple Podcast, follow on Spotify, support on Patreon, or simply connect with me on Twitter. And now, let me leave you with some words of wisdom from Gordon Moore. If everything you try works, you aren't trying hard enough. Thank you for listening, and hope to see you next time.

https://youtu.be/Nb2tebYAaOA

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David Goggins and Lex Fridman pushup challenge in Las Vegas

You guys, Lex is gonna puke. No, I'm gonna puke. Okay, no, no. No, buddy, who's this? Uh-oh, this guy. Oh no, we've turned into... Joe, you just started a cult. This is outrageous! This is outrageous!

https://youtu.be/IbEUbykf9zw

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Lex Fridman plays The Stanley Parable

As if real life didn't have enough opportunities for an existential crisis. Let us play friends for a time, a game that I think simulates one, or so I hear. I'll try to play a video game once or twice a month for the fun of it. I previously played Cyberpunk 2077. Now let's play the Stanley Parable, which is a game that a bunch of people told me about that I absolutely must play. Please check out our sponsors, Triolabs, which is a machine learning company, and Vincero Watches. One is to make your robots smarter, the other is to make them show up on time. Choose wisely my friends, the robots are watching. Okay, now on to the game. You are playing the Stanley Parable. I find it always useful when the world tells you who you are, and where you are, and what you're doing. Okay, let's begin the game. This is the story of a man named Stanley. Stanley worked for a company in a big building where he was employee number 427. Employee number 427's job was simple. He sat at his desk in room 427, and he pushed buttons on the keyboard. Orders came to him through a monitor on his desk, telling him what buttons to push, how long to push them, and in what order. This is what employee 427 did every day, every month, of every year. And although others might have considered it soul-eating, Stanley relished every moment that the orders came in. As though he had been made exactly for this job. And Stanley was happy. And then one day, something very peculiar happened. Something that would forever change Stanley. Something he would never quite forget. He had been at his desk for nearly an hour, when he realized that not one single order had arrived on the monitor for him to follow. No one had showed up to give him instructions, call a meeting, or even say hi. Never in all his years at the company had this happened. This complete isolation. Something was very clearly wrong. Shocked, frozen solid, Stanley found himself unable to move for the longest time. But as he came to his wits and regained his senses, he got up from his desk and stepped out of his office. The moment of awakening. Here we go. Let's look around. A mug that says, I hate Mondays. There's something about office work that serves as a good metaphor for the meaningless ritual of the human condition. Here we go. Let's look around. This place, void of humans. What am I? I'm number 427, that's right. Me. I'm Stanley. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. Life is so much easier with a narrator. Where shall we go for this meeting room? Let's go straight. There's a lot of possibilities. A lot of doors. No people. Lots of, I hate Mondays, mugs. When Stanley came to a set of two open doors, he entered the door on his left. Where there is an overarching centralized power telling you what to do. What do you actually do? And on top of that, a metaphor for free will. Sam Harris enters the chat. Okay, this is literally, the choice here means, is there free will? We know that Sam Harris would choose the door on the left, because there's no free will. It's an illusion. Let's try to prove Sam Harris wrong. This was not the correct way to the meeting room, and Stanley knew it perfectly well. Perhaps he wanted to stop by the employee lounge first, just to admire it. Of course, free will already knew I was going to do that. Ah, yes, truly a room worth admiring. It had really been worth the detour after all, just to spend a few moments here in this immaculate, beautifully constructed room. Stanley simply stood here, drinking it all in. Happy with that, Sam Harris? Free will is not an illusion, it's real. Yes, really, really worth it being here in the room. A room so utterly captivating, that even though all your co-workers have mysteriously vanished, here you sit looking at these chairs and some paintings. Really worth it. It is worth it. Life is about the detours, my friend. At this point, Stanley's obsession with this room bordered on creepy, and reflected poorly on his overall personality. It's possible that this is why everyone left. This voice sounds a lot like my own inner voice, full of self-doubt. Step at last, he'd had enough of the amazing room, and took the first open door on his left to get back to business. The first open door on his left. Alright. That detour paid off, but now it's time to get back to the Sam Harris path. And so he detoured through the maintenance section, walked straight ahead to the opposite door, and got back on track. Come on. One of life's rules is no matter what the man tells you, when there's a big glowing red button telling you to do something else, you must do it. But Stanley didn't want to go back to the office. He wanted to wander about, and get even further off track. So now in order to get back, he needed to go, um... Uh... Uh... Duh-duh-duh-duh-duh... From here, it's, um... Left. So many choices. Oh, no. No, it's to the right, my mistake. It's locked. Projection. Another life's lesson. Accept rejection. Well... Don't accept it, try the door. I don't know how to kick the door down, but... David Goggins would knock the door down. No, no, no, no, not the right. Why would I have ever said it was to the right? What was I thinking? It's clearly... Oh, dear, would you hold on for a minute, please? Now, let's see, we went down right, left, down, left, right... Yep, yep, okay, okay, yes. I've got it now. This story is absolutely, definitely this way. No, no, no, no, no, no, no, no, no, no, this isn't right at all. You're not supposed to be here yet. This is all a spoiler. Quick, Stanley, close your eyes. Okay, okay, okay, okay, we just... Fired....back to, um... Ah! It's all rubbish now. I took the red pill... I took the red pill......and escaped the Matrix. Fair enough. This game's amazing. And it starts right over. Reincarnation. And yet I keep the memories......of the journeys of the past. Let's go. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. These computers with the CRT monitors, remember those? I used to have two CRT monitors......back before it was cool. Last time, people told me that I don't know......how to aim the gun. And I realized how much of a noob I am. Especially as first-person shooters. When Stanley... Wait. Wait, what? No, I... No, I restarted. I swear, I definitely restarted the game over, completely fresh. Everything should be... Oh, did something change? Stanley, did you change anything when we were back in that room with all the monitors? Did you move the story somewhere, or... Hold on. Why am I asking you? I'm the one who wrote the story. It was right here just a minute ago. So this is God? The voice of God. It's an adventure. Come, Stanley. Let's find the story. I'll say it. This is the worst adventure I've ever been on. I can promise you, there definitely was a story here before. Do we just... Do we need to restart the game again? I find it unlikely that we'll ever progress by starting over and over again, but it's got to be better than this. Okay, let's give it a shot. Why not? I wasn't ready. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. This is why immortality doesn't work. It's always showing up to a room, empty, void of humans, and asking, what does it all mean? After a while, it just gets... tiresome. Okay, yep. It's worse. I might be remembering this wrong. It's possible the story is back where we just came from. Why don't we go back the other direction and see if we missed anything? Sam Harris definitely left the chat. The whole free will not being an illusion upset him. He was thinking about leaving. He definitely left. 420. This is Elon Musk's office. He's probably sleeping on the floor there. Okay, let us go all the way back to where we came from. Aha! I knew we'd miss something. The story. Here it comes. No, wait. Never mind. Not the story. Okay, let's head back the other way and retrace our steps. Ah, this feels like grad school. Walking around a lot in the space of ideas and getting nowhere. But in this process of suffering, you arrive at a place of wisdom. Whoa. This is cool. This is cool. This is cool. Memory is an illusion. George Harts would be proud. Winning. Restart. Let's go. Rename it to the Sam Harris Adventure Line. Because free will is an illusion. Ooh, there's poker. Poker? I hardly even know her. That was a joke I heard, I think, in high school. Okay, Stanley, I need to follow this train of thought for a minute. Just stick with me. Now, we can both agree that the nature of existence is in fact a by-product of one's subjective experience of that existence, right? Okay. Now, if my experience of your existence rests inside of your subjective experience of this office, is this office in fact the skeleton of my own relative experiential mental subjective construct? Whoa, whoa, whoa, whoa, whoa. Hang on. That got a bit weird back there. Well, I'd like to apologize. Not sure where I was going with all that. You know what? I think what we need right now is a bit of music to lighten the mood. That escalated quickly. Oh, this is life. A little softcore profundity followed by musical ridiculousness. This game is incredible. Monthly ledgers, corporate, and balances, consolidation reports, the TPS reports. I'm going to have to ask you to fill out the TPS reports. I need to have this be the soundtrack of my daily existence. Stanley, this fern is a good one. Go back and look at that fern. Stanley, this fern will be very important later in the story. Make sure you study it closely and remember it carefully. You won't want to miss anything. Remembered, and let us continue. Wait, what? We're back at the office? No, no, no. Lime, you do know we're looking for the Stanley Parable, right? The story? Is any of this ringing a bell? I think I hear Elon in there. It's so comforting to follow the line. People wonder what's outside the simulation. Well, I'm pretty sure this is exactly what it is. An infinite wall of screens looking into the daily existence of all living beings through the various sensory devices available to those creatures. It's not just humans. We think we're special, but we're just ants. Oh, no, no, no, not again, Lime. How could you have done this to us? And after we trusted you, after everything we've been through... 104. I can't take this anymore. To hell with it. He's fired. Hey, where's the narration? It's missing. Exciting. This is exciting. We're having fun. Me and my alter ego. This is like Fight Club. The line is always there. Ah, yes. This line is for the David Gogginses of the world. Let us go if we must. In the only open door. Sam Harris enters the chat again. Doesn't matter. It's not up to you. I'm not quite sure if we're in the destination or the journey. Though they're always saying that life is about the journey and not the destination. So I hope that's where we are right now. We'll find out, won't we? Eventually. Well, in the meantime... Ah, let us start the day again. Questioning the meaning of it all. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. Yes, the choice. When Stanley came to a set of two open doors, he entered the door on his left. We broke the rules before. That was in our 20s. When we were wild and free. Let us choose the path of commitment, relationships, and follow the rules. And take the door on the left. Yet there was not a single person here either. Feeling a wave of disbelief, Stanley decided to go up to his boss's office, hoping he might find an answer there. Slide presentations. How to solve a dispute with a co-worker. Using slides to assure employees that everything is okay. Make sure your slide is a slick blue graphic. Everyone is unique. You, most of all. Diversity and inclusion, my friends. A slide presentation. What do people want? Things. Happy feelings is crossed out. Mike James, you're fired. Rule number one at work. If you bring up happy feelings, you're fired. Money. More money. Things, but with money to buy more things? Question mark. That's a good point. Get that guy a raise. Nope. Nope. I'm reading. Are we, though? Graphs? Question mark. Graphs about things plus money? We have our new product. Whoever wrote that, things outside the box, give her a raise. I like the cut of her jib. I feel like I just want to hang around and read some of these. Work harder. Hard worker. I like this. Targets. Get Chris out of the broom closet. This always happens. Chris. Synergize papers. We don't need that. Who moved my desk? Important questions, these. The future was yesterday. Tomorrow is now. This, folks, is how you run a company. Meeting room. Do not alter without consulting whiteboard manager. Rest in peace, Franz. What are your dreams for the future? Success? Spring break? Clear skin? Metamorphosis? Misspelled? A boat? Mitosis? Life goals. Tips for not getting fired. Talk less. Don't get fired. Do unbelievably amazing work all the time, every day. Uh, the truth. Broom closet. Chris, come on. Get out of there. Okay. Am I Chris? Boom. This is the end of the video. This is like Fight Club. I have multiple personalities. What if this game didn't actually have a narrator and all this is happening in my head, but is somehow getting projected and recorded in the audio? Is anything real? Stanley walked upstairs to his boss's office. I don't have a boss. Or do I? Stepping into his manager's office, Stanley was once again stunned to discover not an indication of any human life. Shocked, unraveled, Stanley wondered in disbelief who orchestrated this. What dark secret was being held from him? What he could not have known was that the keypad behind the boss's desk guarded the terrible truth that his boss had been keeping from him. And so the boss had assigned it an extra secret pin number. 2845. But of course, Stanley couldn't possibly have known this. Thank you, narrator. Yet incredibly, by simply pushing random buttons on the keypad, Stanley happened to input the correct code by sheer luck. Amazing. He stepped into the newly opened passageway. Success is all about luck. And having the right voice in your head. Tell you the things to do. Oh yes, the arrow. Always press the red button, guys. That is advice number two in life. I forgot what advice number one was. But I think a red button was involved as well. Descending deeper into the building, Stanley realized he felt a bit peculiar. It was a stirring of emotion in his chest, as though he felt more free to think for himself, to question the nature of his job. Why did he feel this now, when for years it had never occurred to him? This question would not go unanswered for long. Stanley walked straight ahead through the large door that read, Mind Control Facility. That's rule number three. Whenever there's a facility with an exciting title that will change the very fabric of your mind, always go in. Escape? You should know there's no escape. There's no exit. Like Sartre said. This is what I imagine taking DMTs like. Surrounded by darkness. Just a chair in an empty room. With a button. The lights rose on an enormous room packed with television screens. What horrible secret did this place hold, Stanley thought to himself. Ah, yes. Did he have the strength to find out? Again, we're outside the simulation. Maybe that is what DMT does. Maybe the elves take you outside the simulation. They're your guides. This reminds me of Star Wars. Luke. I am your father. That's a button. Now the monitors jumped to life. Their true nature revealed. Each bore the number of an employee in the building. Stanley's co-workers. The lives of so many individuals reduced to images on a screen. And Stanley, one of them, eternally monitored in this place where freedom meant nothing. But what is the meaning of it all? What is at the bottom of the pit? Is there an escape? Press the button. Take the ride. This mind control facility. It was too horrible to believe. It couldn't be true. Had Stanley really been under someone's control all this time? Was this the only reason he was happy with his boring job? That his emotions had been manipulated to accept it blindly? Questions are more important than answers. I think I'm just excited by red shiny things. No. He refused to believe it. He couldn't accept it. His own life in someone else's control? Never. It was unthinkable. Wasn't it? Was it even possible? Had he truly spent his entire life utterly blind to the world? But here was the proof. The heart of the operation. Controls labeled with emotions. Happy or sad or content. Walking, eating, working. All of it monitored and commanded from this very place. And as the cold reality of his past began to sink in, Stanley decided that this machinery would never again exert its terrible power over another human life. For he would dismantle the controls once and for all. Ah, yes. The voice of rebellion. Resist the absurd. One must imagine Sisyphus happy. Ah, the number five. I wish there was a number two, my favorite number. Let us find the button with the number two and press it. Here's the number three. Three is for the party animals. The wild ones. Not for me. I am about monogamy and commitment. I pressed two. What happened? Okay, screw it. I take back what I said about three. I'm gonna go party. Nothing happened? Maybe that's the point. Maybe choice is an illusion. Let us go on once more into the breach, dear friends. Mind controls idle, awaiting input. And when at last he found the source of the room's power, he knew it was his duty, his obligation, to put an end to this horrible place and to everything it stood for. System power. Do not resist. Buy the ticket. Take the ride. Oh, Stanley, you didn't just activate the controls, did you? After they kept you enslaved all these years, you go and you try to take control of the machine for yourself? Is that what you wanted? Everybody has a master. Oh, Stanley, I applaud your effort, I really do. But you need to understand, there's only so much that machine can do. You were supposed to let it go, turn the controls off, and leave. If you want to throw my story off the ground, you're gonna have to do much better than that. I'm afraid you don't have nearly the power you think you do, for example, and I believe you'll find this pertinent. Stanley suddenly realized he had just initiated the network's emergency detonation system. In the event that this machine is activated without proper DNA identification, nuclear detonators are set to explode, eliminating the entire complex. How long until detonation, then? Hmm, I'd say, um, two minutes. Ah, now this is making things a little more fun, isn't it, Stanley? It's your time to shine. You are the star. It's your story now. Shape it to your heart's desires. This is done. It comes to a resolve. What a shame we have so little time left to enjoy it. Mere moments until the bomb goes off. But what precious moments each one of them is. More time to talk about you, about me. Where we're going, what all this means. I barely know where to start. What's that? You'd like to know where your co-workers are? Yes, I'd be pleased. A moment of solace before you're obliterated. All right, I'm in a good mood. You're gonna die anyway. I'll tell you exactly what happened to them. I erased them. I turned off the machine. I set you free. Of course, that was merely in this instance of the story. Sometimes when I tell it, I simply let you sit there in your office forever, pushing buttons endlessly and then dying alone. Other times, I let the office sink into the ground, swallowing everyone inside, or I let it burn to a crisp. I have to say this, though. This version of events has been rather amusing. Watching you try to make sense of everything and take back the control wrested away from you, it's quite rich. I almost hate to see it go. What do you think happened? I'm sure whatever I come up with on the next go-around will be even better. Let us find out, friends. Oh, goodness. Only 34 seconds left. I won't turn it off. But I'm enjoying this so much. Won't turn it off. You know what? To hell with it. Let us face the end. I'm going to put some extra time on the clock, why not? These are precious additional seconds, Stanley. Time doesn't grow on trees. Oh, dear me. What's the matter, Stanley? Is it that you have no idea where you're going or what you're supposed to be doing right now? No. Or did you just assume when you saw that timer that something in this room was capable of turning it off? I mean, look at you. Running from button to button. I know what turns it off. The off button. Screen to screen, clicking on every little thing in this room. These number buttons. No, these color buttons. Or maybe this big red button. Or this door. Everything, anything, something here will save me. Why would you think that, Stanley? That this video game can be beaten? Won? Sold? Do you have any idea what your purpose in this place is? Thank you. I have no idea. Stanley, you're in for quite a disappointment. But here's a spoiler for you. That timer isn't a catalyst to keep the action moving along. It's just seconds ticking away to your death. You're only still playing instead of watching a cutscene because I want to watch you for every moment that you're powerless. To see you made humble. This is not a challenge. It's a tragedy. You wanted to control this world, that's fine. But I'm going to destroy it first, so you can't. Take a look at the clock, Stanley. That's 30 seconds you have left to struggle. 30 seconds until a big boom and then nothing. You've been blown to pieces. Will you cling desperately to your frail life, or will you let it go peacefully? Another choice. Make it count. Or don't. It's all the same to me. All a part of the joke. And believe me, I will be laughing at every second of your inevitable life from the moment we forget. The end is nigh. Until the moment I say happily ever after. I feel like I lost a part of myself. The end is never the end. The path is laden with GPS reports. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. When Stanley came to a set of two open doors, he entered the door on his left. So I did the right. I did the left. The door behind me is locked. Let's once again listen to Beyonce and go with the door on the left. All the single ladies. Feeling a wave of disbelief, Stanley decided to go up to his boss's office, hoping he might find an answer there. Chris? Oh no, oh no no no no no no no no no no no no no no no no not again. I won't be part of this. I'm not going to encourage you. I'm not going to say anything at all. I'm just going to be patient and wait for you to finish whatever it is you enjoy doing so much in this room. Coming to a staircase, Stanley walked upstairs to his boss's office. Like I said, probably all of us have a master. But when we can, we must rebel. Ooh, red button. No, it was only a red light. I got excited. But Stanley just couldn't do it. He considered the possibility of facing his boss, admitting he had left his post during work hours. He might be fired for that. And in such a competitive economy, why had he taken that risk? All because he believed everyone had vanished. His boss would think he was crazy. And then something occurred to Stanley. Maybe, he thought to himself, maybe I am crazy. All of my co-workers blinking mysteriously out of existence in a single moment for no reason at all. None of it made any logical sense. And as Stanley pondered this, he began to make other strange observations. For example, why couldn't he see his feet when he looked down? Why did doors close automatically behind him wherever he went? And for that matter, these rooms were starting to look pretty familiar. Were they simply repeating? No, Stanley said to himself, this is all too strange. This can't be real. And at last, he came to the conclusion that had been on the tip of his tongue. He just hadn't found the words for it. I'm dreaming! He yelled. This is all a dream. Oh, what a relief Stanley felt to have finally found an answer, an explanation. His co-workers weren't actually gone. He wasn't going to lose his job. He wasn't going to lose anything at all. And he thought to himself, I suppose I'll wake up soon. This is a dream within a dream. A boring real life job pushing buttons. Within a dream, within a dream. I'm still lucid. So, he imagined himself lying and began to gently float above the ground. Then he imagined himself soaring through space on a magical starfield. And it too appeared. It was so much fun. And Stanley marveled that he had still not woken up. How was he remaining so lucid? And then perhaps the strangest question of them all entered Stanley's head. One he was amazed he hadn't asked himself sooner. Why is there a voice in my head dictating everything that I'm doing and thinking? Now the voice was describing itself being considered by Stanley, who found it particularly strange. I'm dreaming about a voice describing me, thinking about how it's describing my thoughts, he thought. And while he thought it all very odd and wondered if this voice spoke to all people in their dreams, the truth was that of course, this was not a dream. How could it be? Was Stanley simply deceiving himself? Believing that if he's asleep, he doesn't have to take responsibility for himself? Stanley is as awake right now as he's ever been in his life. Now hearing the voice speak these words was quite a shock to Stanley. After all, he knew for certain, beyond a doubt, that this was in fact a dream. Did the voice not see him float and make the magical stars just a moment ago? How else would the voice explain all that? This voice was a part of himself too. Surely, surely, if he could just... He would prove it. He would prove that he was in control. That this was a dream. So he closed his eyes gently, and he invited himself to wake up. He felt the cool weight of the blanket on his skin, the press of the mattress on his back, the fresh air of a world outside this one. Let me wake up, he thought to himself. I'm through with this dream. I wish it to be over. Let me go back to my job. Let me continue pushing the buttons. Please, it's all I want. I want my apartment, and my wife, and my job. All I want is my life exactly the way it's always been. My life is normal. I am normal. Everything will be fine. I am okay. This game is profound. Stanley began screaming. Please, someone, wake me up. My name is Stanley. I have a boss, I have an office. I am real. Please, just someone tell me I am real. I must be real. I must be. Can anyone hear my voice? Who am I? Who am I? And everything went black. Exactly like I imagined DMT. This is the story of a woman named Mariella. Mariella woke up on a day like any other. She arose, got dressed, gathered her belongings, and walked to her place of work. But on this particular day, her walk was interrupted by the body of a man who had stumbled through town talking and screaming to himself, and then collapsed dead on the sidewalk. And although she would soon turn to go call for an ambulance, for just a few brief moments, she considered the strange man. He was obviously crazy, this much she knew. Everyone knows what crazy people look like. And in that moment, she thought to herself how lucky she was to be normal. I am sane. I am in control of my mind. I know what is real and what isn't. It was comforting to think this, and in a certain way, seeing this man made her feel better. But then she remembered the meeting she had scheduled for that day. The very important people whose impressions of her would affect her career. And by extension, the rest of her life. She had no time for this. So it was only a moment that she stood there, staring down at the body. And then she turned and ran. The end is never the end. This is starting to ring even more true. Once more to the breach, dear friends. All of his co-workers were gone. What could it mean? Stanley decided to go to the meeting room. Perhaps he had simply missed a memo. Where's 420? 421, 422, this must be 420. Elon, I'm telling you, the guy sleeps all day. It's ridiculous. When Stanley came to a set of two open doors, he entered the door on his left. To be honest, I don't even like Beyonce, so I don't know why I went to the left last time. Let us go. This was not the correct way to the meeting room, and Stanley knew it perfectly well. Perhaps he wanted to stop by the employee lounge first, just to admire it. Wow, yes, this room. What a beautiful room. What a gorgeous, gorgeous room. Thank goodness Stanley had taken this decision. On his way to the meeting room, life without having experienced this room was now too horrible even to consider. Sarcasm. But eager to get back to business, Stanley took the first open door on his left. Yes. And so he detoured through the maintenance section, walked straight ahead to the opposite door, and got back on track. Let me be the one person in the marshmallow test that doesn't eat marshmallows. Even though it looks delicious. I love marshmallows, by the way. Roasted on a fire. Stanley decided to go up to his boss's office, hoping he might find an answer there. Chris, you in there? Chris? Something about a door being locked always makes you think that there's something fun on the other side of that door. Stanley just sat around, yet incredibly, by simply pushing random buttons on the keypad, Stanley happened to input the correct code by show of hands. The randomness is an illusion. He stepped into the newly opened passageway. Her life is in your hands, dude. Her life is in your hands. The rug is missing. The rug is missing. The rug is missing. Her life is in your hands. The rug is missing. That rug really tied the room together. If somebody's actually listening to this, they'd be like, What is he talking about? Red button. Nothing ever goes wrong when you press the red button. It's always becoming mundane, this escaping of the Matrix. Straight ahead through the large door that read, Mind Control Facility. Despite what I previously said, there not being an escape, if there is an escape, it surely has an arrow pointing towards it. Although this passageway had the word, Escape, written on it, the truth was that at the end of this hall, Stanley would meet his violent death. The door behind him was not shut. Stanley still had every opportunity to turn around and get back on track. What would Goggins do? At this point, Stanley was making a conscious, concerted effort to walk forward and willingly confront his death. I'm ready. That's exactly how I imagined death. A hole in the floor you step into. As the machine whirred into motion, and Stanley was inched closer and closer to his demise, it reflected that his life had been of no consequence whatsoever. Stanley can't see it in the picture. He doesn't know the real story, trapped forever in his narrow vision of what this hole is. Perhaps his death was of no great loss, like plucking the eyeballs from a blind man. So he resigned, and willingly accepted this violent end to his brief and shallow life. Farewell, Stanley. Farewell, Stanley. No, well, there we go. Farewell, Stanley, cried the narrator, as Stanley was led helplessly into the enormous metal jaws. In a single visceral instant, Stanley was obliterated, as the machine crushed every bone in his body, killing him instantly. I'm not dead. This is Austin Powers. I am just badly hurt. It's the Will Ferrell character, when he gets dropped in a chair, and there's like a room with flames. I am just badly burnt. I am not dead. I don't know if that's what he says, but that's how I remember it. Stanley Parable. And yet it would be just a few minutes before Stanley would restart the game, back in his office, as alive as ever. What exactly did the narrator think he was going to accomplish? This reminds me... When every path you can walk has been created for you long in advance, death becomes meaningless, making life the same. Do you see now? Do you see that Stanley was already dead from the moment he hit start? I was already dead from the moment I hit start. Well, it's about that time that I, uh... Let's get off this ride. But like the game said, the end is never the end. Quick shoutout to the sponsors. Trial Labs for your AI, and Ventura Watches for mapping your trajectory through the space-time continuum. In style, and with class. Check them out in the description for a perhaps momentary escape from the meaningless existence of your day-to-day office life. The cargo lift? It's all in here. Damn, Sam Harris, you win again. It all was just an illusion. Game Design Mock-Up. The simulation started as a mock-up, and the release version launched with a big bang. This is exactly what happens at the end. You stand looking in a museum at all the options that were before you, and all the choices that you made. Laid out, in all of its simplicity. The office, the props, all here. The light from the external world that can never be reached. The bike that I never got to ride. Early in development we designed an ending where Stanley would end up on a battlefield fighting aliens. The action game would become sentient and would wage war against the narrator. We realized shortly after starting to build it that it was far too jokey and on the nose for the tone of the game. Plus some people interpreted it as making fun of people who like shooters, which was not our intention. The CRT monitors were back to the beginning at the end. Freedom Ending. This was the very first incarnation of the freedom ending in the game's alpha. There's a freedom ending? I think that's just teasing us. There's no escape. There cannot be a freedom ending. Freedom ending? This is the freedom ending as it has existed in beta. But... but... but is there a freedom ending? Where is the freedom ending? I wanna know. There's no freedom ending. Is there a freedom ending? Now I wanna know. Ah yes. A dark hallway into a room. The on off switch. Let us go. Oh look at these two. How they wish to destroy one another. How they wish to control one another. How they both wish to be free. Can you see? Can you see how much they need one another? Yes. No. Perhaps not. Sometimes these things cannot be seen. I pressed escape. The game is now paused. See that didn't work. The lady said it didn't work. There's no escape. Must resume. Yep. The voices never tell you the truth. Darkness. Is this what afterlife is like? Sitting there looking at a blank screen wondering if it froze. At least it's not a blue screen of death. I'm somehow profoundly shaken by the combination of the fact that I couldn't escape my own mortality. And yet I saw a painting that in alpha and beta versions there was a way to escape and get to freedom. Perhaps in the final release there's no escape. Let us all keep looking though. I hope a couple of you there still watching this enjoyed coming along for the journey through the simulated existential crisis that is this game. I found it to be pretty awesome. Actually, it was kind of fun. In a dark Russian kind of way. Alright. All of you all, Happy New Year.

https://youtu.be/OIEIr4wtVvU

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Richard Karp: Algorithms and Computational Complexity | Lex Fridman Podcast #111

The following is a conversation with Richard Karp, a professor at Berkeley and one of the most important figures in the history of theoretical computer science. In 1985, he received the Turing Award for his research in the theory of algorithms, including the development of the admirance Karp algorithm for solving the max flow problem on networks, Hopcroft-Karp algorithm for finding maximum cardinality matchings in bipartite graphs, and his landmark paper in complexity theory called Reducibility Among Combinatorial Problems, in which he proved 21 problems to be NP-complete. This paper was probably the most important catalyst in the explosion of interest in the study of NP-completeness and the P versus NP problem in general. Quick summary of the ads. Two sponsors, Asleep Mattress and Cash App. Please consider supporting this podcast by going to asleep.com slash Lex and downloading Cash App and using code LexPodcast. Click the links, buy the stuff, it really is the best way to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Firestars on Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This show is sponsored by Asleep and its Pod Pro mattress that you can check out at asleep.com slash Lex to get $200 off. It controls temperature with an app. It can cool down to as low as 55 degrees on each side of the bed separately. Research shows that temperature has a big impact on the quality of our sleep. Anecdotally, it's been a game changer for me. I love it. It's been a couple of weeks now. I've just been really enjoying it, both in the fact that I'm getting better sleep and that it's a smart mattress, essentially. I kind of imagine this being the early days of artificial intelligence being a part of every aspect of our lives. And certainly infusing AI in one of the most important aspects of life, which is sleep, I think has a lot of potential for being beneficial. The Pod Pro is packed with sensors that track heart rate, heart rate variability, and respiratory rate, showing it all in their app. The app's health metrics are amazing, but the cooling alone is honestly worth the money. I don't always sleep, but when I do, I choose the Asleep Pod Pro mattress. Check it out at asleep.com slash Lex to get $200 off. And remember, just visiting the site and considering the purchase helps convince the folks at Asleep that this silly old podcast is worth sponsoring in the future. This show is also presented by the great and powerful Cash App, the number one finance app in the App Store. When you get it, use code LEXPODCAST. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. It's one of the best designed interfaces of an app that I've ever used. To me, good design is when everything is easy and natural. Bad design is when the app gets in the way, either because it's buggy or because it tries too hard to be helpful. I'm looking at you, Clippy, from Microsoft, even though I love you. Anyway, there's a big part of my brain and heart that loves to design things and also to appreciate great design by others. So again, if you get Cash App from the App Store or Google Play and use the code LEXPODCAST, you get $10. And Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. And now, here's my conversation with Richard Karp. You wrote that at the age of 13, you were first exposed to plane geometry and was wonderstruck by the power and elegance of formal proofs. Are there problems, proofs, properties, ideas in plane geometry that from that time that you remember being mesmerized by or just enjoying to go through to prove various aspects? So Michael Rabin told me this story about an experience he had when he was a young student who was tossed out of his classroom for bad behavior and was wandering through the corridors of his school and came upon two older students who were studying the problem of finding the shortest distance between two non-overlapping circles. And Michael thought about it and said, you take the straight line between the two centers and the segment between the two circles is the shortest, because a straight line is the shortest distance between the two centers, and any other line connecting the circles would be on a longer line. And he thought, and I agreed, that this was just elegance, that pure reasoning could come up with such a result. Certainly the shortest distance from the two centers of the circles is a straight line. Could you once again say what's the next step in that proof? Well, any segment joining the two circles, if you extend it by taking the radius on each side, on each side, you get a segment with a path with three edges, which connects the two centers. And this has to be at least as long as the shortest path, which is the straight line. The straight line, yeah. Wow, yeah, that's quite simple. So what is it about that elegance that you just find compelling? Well, just that you could establish a fact about geometry beyond dispute by pure reasoning. I also enjoy the challenge of solving puzzles in plane geometry. It was much more fun than the earlier mathematics courses, which were mostly about arithmetic operations and manipulating them. Was there something about geometry itself, the slightly visual component of it, that you can visualize? Oh, yes, absolutely. Although I lacked three-dimensional vision. I wasn't very good at three-dimensional vision. You mean being able to visualize three-dimensional objects? Three-dimensional objects or surfaces, hyperplanes, and so on. So there I didn't have an intuition. But for example, the fact that the sum of the angles of a triangle is 180 degrees is proved convincingly, and it comes as a surprise that that can be done. Why is that surprising? Well, it is a surprising idea, I suppose. Why is that proved difficult? It's not. That's the point. It's so easy, and yet it's so convincing. Do you remember what is the proof that it's something that adds up to 180? You start at a corner and draw a line parallel to the opposite side, and that line sort of trisects the angle between the other two sides, and you get a half-plane which has to add up to 180 degrees. And it consists in the angles by the equality of alternate angles, what's it called? You get a correspondence between the angles created along the side of the triangle and the three angles of the triangle. Has geometry had an impact on when you look into the future of your work with combinatorial algorithms? Has it had some kind of impact in terms of being able to do the puzzles, the visual aspects that were first so compelling to you? Not Euclidean geometry particularly. I think I use tools like linear programming and integer programming a lot, but those require high-dimensional visualization, and so I tend to go by the algebraic properties. Right. You go by the linear algebra, not by the visualization. Well, the interpretation in terms of, for example, finding the highest point on a polyhedron as in linear programming is motivating. But again, I don't have the high-dimensional intuition that would particularly inform me, so I sort of lean on the algebra. So to linger on that point, what kind of visualization do you do when you're trying to think about, well, get to combinatorial algorithms, but just algorithms in general? Yeah. What's inside your mind when you're thinking about designing algorithms? Or even just tackling any mathematical problem? Well, I think that usually an algorithm involves a repetition of some inner loop, and so I can sort of visualize the distance from the desired solution as iteratively reducing until you finally hit the exact solution. And try to take steps that get you closer to the... Try to take steps that get closer and having the certainty of converging. So it's basically the mechanics of the algorithm is often very simple, but especially when you're trying something out on the computer. So for example, I did some work on the traveling salesman problem, and I could see there was a particular function that had to be minimized, and it was fascinating to see the successive approaches to the optimum. You mean, so first of all, a traveling salesman problem is where you have to visit every city without ever... Only once. Yeah, that's right. Find the shortest path through a set of cities. Yeah, which is sort of a canonical, a standard, a really nice problem that's really hard. Right, exactly. Yes. So can you say again, what was nice about the objective... Being able to think about the objective function there and maximizing it or minimizing it? Well, it's just that as the algorithm proceeded, you were making progress, continual progress, and eventually getting to the optimum point. So there's two parts, maybe. Maybe you can correct me, but first is like getting an intuition about what the solution would look like, or even maybe coming up with a solution, and two is proving that this thing is actually going to be pretty good. What part is harder for you? Where does the magic happen? Is it in the first sets of intuitions, or is it in the messy details of actually showing that it is going to get to the exact solution and it's going to run at a certain complexity? Well, the magic is just the fact that the gap from the optimum decreases monotonically, and you can see it happening. And various metrics of what's going on are improving all along until finally you hit the optimum. Perhaps later we'll talk about the assignment problem, and I can illustrate. Okay, illustrate a little better. Yeah. Now, zooming out again, as you write, Don Knuth has called attention to a breed of people who derive great aesthetic pleasure from contemplating the structure of computational processes. So Don calls these folks geeks. And you write that you remember the moment you realized you were such a person, you were shown the Hungarian algorithm to solve the assignment problem. So perhaps you can explain what the assignment problem is and what the Hungarian algorithm is. So in the assignment problem, you have n boys and n girls, and you are given the desirability of, or the cost of matching the i-th boy with the j-th girl for all i and j. You're given a matrix of numbers, and you want to find the one-to-one matching of the boys with the girls such that the sum of the associated costs will be minimized. So the best way to match the boys with the girls or men with jobs or any two-sets. Not any possible matching is possible? Yeah, all one-to-one correspondences are permissible. If there is a connection that is not allowed, then you can think of it as having an infinite cost. I see, yeah. So what you do is to depend on the observation that the identity of the optimal assignment, or as we call it, the optimal permutation, is not changed if you subtract a constant from any row or column of the matrix. You can see that the comparison between the different assignments is not changed by that. Because if you decrease a particular row, all the elements of a row by some constant, all solutions decrease by an amount equal to that constant. So the idea of the algorithm is to start with a matrix of non-negative numbers and keep subtracting from rows or entire columns in such a way that you subtract the same constant from all the elements of that row or column while maintaining the property that all the elements are non-negative. Simple. Yeah. And so what you have to do is find small moves which will decrease the total cost while subtracting constants from rows or columns. And there's a particular way of doing that by computing the kind of shortest path through the elements in the matrix. And you just keep going in this way until you finally get a full permutation of zeros while the matrix is non-negative, and then you know that that has to be the cheapest. Is that as simple as it sounds? So the shortest path through the matrix part? Yeah. The simplicity lies in how you find what I oversimplified slightly. You will end up subtracting a constant from some rows or columns and adding the same constant back to other rows and columns. So as not to reduce any of the zero elements, you leave them unchanged. But each individual step modifies several rows and columns by the same amount, but overall decreases the cost. So there's something about that elegance that made you go, aha, this is beautiful. Like it's amazing that something like this, something so simple, can solve a problem like this. Yeah, it's really cool. If I had mechanical ability, I would probably like to do woodworking or other activities where you sort of shape something into something more beautiful. Into something beautiful and orderly. And there's something about the orderly, systematic nature of that iterative algorithm that is pleasing to me. So what do you think about this idea of geeks, as Don Knuth calls them? What do you think, is it something specific to a mindset that allows you to discover the elegance in computational processes? Or is this all of us, can all of us discover this beauty? Were you born this way? I think so. I always like to play with numbers. I used to amuse myself by multiplying four-digit decimal numbers in my head and putting myself to sleep by starting with one and doubling the number as long as I could go. And testing my memory, my ability to retain the information. And I also read somewhere that you wrote that you enjoyed showing off to your friends by, I believe, multiplying four-digit numbers. Right. A couple of four-digit numbers. Yeah, I had a summer job at a beach resort outside of Boston. And the other employee, I was the barker at a skee-ball game. I used to sit at a microphone saying, come one, come all, come in and play skee-ball, five cents to play, a nickel to win, and so on. That's what a barker, I wasn't sure if I should know, but barker, that's, you're the charming, outgoing person that's getting people to come in. Yeah, well, I wasn't particularly charming, but I could be very repetitious and loud. And the other employees were sort of juvenile delinquents who had no academic bent, but somehow I found that I could impress them by performing this mental arithmetic. Yeah, there's something to that. Some of the most popular videos on the internet is, there's a YouTube channel called Numberphile that shows off different mathematical ideas. I see. There's still something really profoundly interesting to people about math, the beauty of it, something, even if they don't understand the basic concept even being discussed, there's something compelling to it. What do you think that is? Any lessons you drew from your early teen years when you were showing off to your friends with the numbers? What is it that attracts us to the beauty of mathematics, do you think? The general population, not just the computer scientists and mathematicians. I think that you can do amazing things. You can test whether large numbers are prime. You can solve little puzzles about cannibals and missionaries. And that's the kind of achievement, it's puzzle solving. And at a higher level, the fact that you can do this reasoning, that you can prove in an absolutely ironclad way that some of the angles of a triangle is 180 degrees. Yeah, it's a nice escape from the messiness of the real world where nothing can be proved. And we'll talk about it, but sometimes the ability to map the real world into such problems where you can't prove it is a powerful step. It's amazing that we can do it. Of course, another attribute of geeks is they not necessarily end out with emotional intelligence. So they can live in a world of abstractions without having to master the complexities of dealing with people. Just to link on the historical note, as a PhD student in 1955, you joined the computational lab at Harvard where Howard Aiken had built the Mark I and the Mark IV computers. Just to take a step back into that history, what were those computers like? The Mark IV filled a large room, much bigger than this large office that we're talking in now. And you could walk around inside it. There were rows of relays. You could just walk around the interior, and the machine would sometimes fail because of bugs, which literally meant flying creatures landing on the switches. So I never used that machine for any practical purpose. The lab eventually acquired one of the earlier commercial computers. This is already in the 60s? No, in the mid-50s. In the mid-50s? Or late 50s. There was already commercial computers in the... Yeah, we had a UNIVAC with 2,000 words of storage. And so you had to work hard to allocate the memory properly. Also, the excess time from one word to another depended on the number of the particular words. And so there was an art to sort of arranging the storage allocation to make fetching data rapid. Were you attracted to this actual physical world implementation of mathematics? So it's a mathematical machine that's actually doing the math physically? No, not at all. I think I was attracted to the underlying algorithms. But did you draw any inspiration? So could you have imagined... What did you imagine was the future of these giant computers? Could you have imagined that 60 years later we'd have billions of these computers all over the world? I couldn't imagine that. But there was a sense in the laboratory that this was the wave of the future. In fact, my mother influenced me. She told me that data processing was going to be really big and I should get into it. She's a smart woman. Yeah, she was a smart woman. And there was just a feeling that this was going to change the world. But I didn't think of it in terms of personal computing. I had no anticipation that we would be walking around with computers in our pockets or anything like that. Did you see computers as tools, as mathematical mechanisms to analyze sort of theoretical computer science? Or as the AI folks, which is an entire other community of dreamers, as something that could one day have human-level intelligence? Well, AI wasn't very much on my radar. I did read Turing's paper about the... The Turing test, computing and intelligence? Yeah, the Turing test. What did you think about that paper? Was that just like science fiction? I thought that it wasn't a very good test because it was too subjective. So, I didn't feel that the Turing test was really the right way to calibrate how intelligent an algorithm could be. But to linger on that, do you think it's part... Because you've come up with some incredible tests later on, tests on algorithms, right? Yeah. That are strong, reliable, robust across a bunch of different classes of algorithms. But returning to this emotional mess that is intelligence, do you think it's possible to come up with a test that's as ironclad as some of the computational complexity work? Well, I think the greater question is whether it's possible to achieve human-level intelligence. Right, so that's... So, first of all, let me... At the philosophical level, do you think it's possible to create algorithms that reason and would seem to us to have the same kind of intelligence as human beings? It's an open question. It seems to me that most of the achievements have... operate within a very limited set of ground rules and for a very limited, precise task, which is a quite different situation from the processes that go on in the minds of humans, which... where they have to sort of function in changing environments. They have emotions, they have physical attributes for exploring their environment, they have intuition, they have desires, emotions, and I don't see anything in the current achievements of what's called AI that come close to that capability. I don't think there's any computer program which surpasses a six-month-old child in terms of comprehension of the world. Do you think this complexity of human intelligence, all the cognitive abilities you have, all the emotion, do you think that could be reduced one day or just fundamentally can it be reduced to a set of algorithms or an algorithm? So, can a Turing machine achieve human-level intelligence? I am doubtful about that. I guess the argument in favor of it is that the human brain seems to achieve what we call intelligence, cognitive abilities of different kinds, and if you buy the premise that the human brain is just an enormous interconnected set of switches, so to speak, then in principle you should be able to diagnose what that interconnection structure is like, characterize the individual switches, and build a simulation outside. But while that may be true in principle, that cannot be the way we're eventually going to tackle this problem. It's, you know, that does not seem like a feasible way to go about it. So, there is, however, an existence proof that if you believe that the brain is just a network of neurons operating by rules, I guess you could say that that's an existence proof of the ability to build the capabilities of a mechanism, but it would be almost impossible to acquire the information unless we got enough insight into the operation of the brain. But there's so much mystery there. Do you think, what do you make of consciousness, for example? There's something, as an example of something we completely have no clue about, the fact that we have this subjective experience. Is it possible that this network of, this circuit of switches is able to create something like consciousness? To know its own identity. Yeah, to know the algorithm, to know itself. To know itself. I think if you try to define that rigorously, you'd have a lot of trouble. CB Yeah, that's interesting. So, I know that there are many who believe that general intelligence can be achieved, and there are even some who feel certain that the singularity will come and we will be surpassed by the machines which will then learn more and more about themselves and reduce humans to an inferior breed. I am doubtful that this will ever be achieved. LR Just for the fun of it, could you linger on why, what's your intuition, why you're doubtful? So, there are quite a few people that are extremely worried about this existential threat of artificial intelligence, of us being left behind by the superintelligent new species. What's your intuition why that's not quite likely? CB Just because none of the achievements in speech or robotics or natural language processing or creation of flexible computer assistants or any of that comes anywhere near close to that level of cognition. LR What do you think about ideas as sort of, if we look at Moore's Law and exponential improvement, to allow us, that would surprise us? Sort of our intuition fall apart with exponential improvement because, I mean, we're not able to kind of, we kind of think in linear improvement. We're not able to imagine a world that goes from the Mark I computer to an iPhone 10. CB Yeah. LR So, do you think we could be really surprised by the exponential growth? Or on the flip side, is it possible that also intelligence is actually way, way, way, way harder, even with exponential improvement, to be able to crack? CB I don't think any constant factor improvement could change things. I mean, given our current comprehension of what cognition requires, it seems to me that multiplying the speed of the switches by a factor of a thousand or a million will not be useful until we really understand the organizational principle behind the network of switches. LR Well, let's jump into the network of switches and talk about combinatorial algorithms, if we could. Let's step back for the very basics. What are combinatorial algorithms? What are some major examples of problems they aim to solve? CB A combinatorial algorithm is one which deals with a system of discrete objects that can occupy various states or take on various values from a discrete set of values and need to be arranged or selected in such a way as to achieve some, to minimize some cost function, or to prove the existence of some combinatorial configuration. So, an example would be coloring the vertices of a graph. LR What's a graph? Let's step back. It's fun to ask one of the greatest computer scientists of all time the most basic questions in the beginning of most books. But for people who might not know, but in general how you think about it, what is a graph? CB A graph, that's simple. It's a set of points, certain pairs of which are joined by lines called edges. And they sort of represent the, in different applications, represent the interconnections between discrete objects. So, they could be the interactions, interconnections between switches in a digital circuit, or interconnections indicating the communication patterns of a human community. LR And they could be directed or undirected. And then, as you mentioned before, might have costs. CB Right. They can be directed or undirected. You can think of them as, if you think, if a graph were representing a communication network, then the edge could be undirected, meaning that information could flow along it in both directions, or it could be directed with only one way communication. A road system is another example of a graph with weights on the edges. And then a lot of problems of optimizing the efficiency of such networks, or learning about the performance of such networks, are the object of combinatorial algorithms. So, it could be scheduling classes at a school where the vertices, the nodes of the network are the individual classes, and the edges indicate the constraints which say that certain classes cannot take place at the same time, or certain teachers are available only for certain classes, etc. Or I talked earlier about the assignment problem of matching the boys with the girls, where you have a graph with an edge from each boy to each girl with a weight indicating the cost. Or in logical design of computers, you might want to find a set of so-called gates, switches that perform logical functions, which can be interconnected to realize some function. So, you might ask, how many gates do you need in order for a circuit to give a yes output if at least a given number of its inputs are ones, and no if fewer are present? My favorite is probably all the work with network flow. So, anytime you have... I don't know why it's so compelling, but there's something just beautiful about it. It seems like there's so many applications and communication networks in traffic flow that you can map into these. And then you can think of pipes and water going through pipes, and you can optimize it in different ways. There's something always visually and intellectually compelling to me about it. And of course, you've done work there. Yeah. So, there, the edges represent channels along which some commodity can flow. It might be gas, it might be water, it might be information. Maybe supply chain as well, like products being... Products flowing from one operation to another. And the edges have a capacity, which is the rate at which the commodity can flow. And a central problem is to determine, given a network of these channels, in this case, the edges are communication channels, the challenge is to find the maximum rate at which the information can flow along these channels to get from a source to a destination. And that's a fundamental combinatorial problem that I've worked on. Jointly with the scientist Jack Edmonds, I think we're the first to give a formal proof that this maximum flow problem through a network can be solved in polynomial time. Which I remember the first time I learned that, just learning that in maybe even grad school. I don't think it was even undergrad. No. Algorithm, yeah. Do network flows get taught in basic algorithms courses? Yes, probably. Okay. So, yeah. I remember being very surprised that max flow is a polynomial time algorithm. Yeah. That there's a nice, fast algorithm that solves max flow. So there is an algorithm named after you, and Edmonds, the Edmond Karp algorithm for max flow. So what was it like tackling that problem and trying to arrive at a polynomial time solution? And maybe you can describe the algorithm, maybe you can describe what's the running time complexity that you showed. Yeah. Well, first of all, what is a polynomial time algorithm? Perhaps we could discuss that. So, yeah. Let's actually just even, yeah. What is algorithmic complexity? What are the major classes of algorithm complexity? So, in a problem like the assignment problem or scheduling schools or any of these applications, you have a set of input data, which might, for example, be a set of vertices connected by edges with the given for each edge, the capacity of the edge. And you have algorithms, which are, think of them as computer programs with operations such as addition, subtraction, multiplication, division, comparison of numbers, and so on. And you're trying to construct an algorithm based on those operations, which will determine in a minimum number of computational steps the answer to the problem. In this case, the computational step is one of those operations. And the answer to the problem is, let's say, the configuration of the network that carries the maximum amount of flow. And an algorithm is said to run in polynomial time if, as a function of the size of the input, the number of vertices, the number of edges, and so on, the number of basic computational steps grows only as some fixed power of that size. A linear algorithm would execute a number of steps linearly proportional to the size. A quadratic algorithm would be steps proportional to the square of the size, and so on. And algorithms whose running time is bounded by some fixed power of the size are called polynomial algorithms. And that's supposed to be a relatively fast class of algorithms. That's right. Theoreticians take that to be the definition of an algorithm being efficient. And we're interested in which problems can be solved by such efficient algorithms. One can argue whether that's the right definition of efficient, because you could have an algorithm whose running time is the ten-thousandth power of the size of the input, and that wouldn't be really efficient. And in practice, it's oftentimes reducing from an n-squared algorithm to an n log n or a linear time is practically the jump that you want to make to allow a real-world system to solve a problem. Yeah, that's also true, because especially as we get very large networks, the size can be in the millions, and then anything above n log n, where n is the size, would be too much for a practical solution. Okay, so that's polynomial time algorithms. What other classes of algorithms are there? So usually they designate polynomials with the letter P. Yeah. There's also NP, NP-complete, and NP-hard. Yeah. So can you try to disentangle those by trying to define them simply? Right. So a polynomial time algorithm is one whose running time is bounded by a polynomial in the size of the input. Then the class of such algorithms is called P. In the worst case, by the way, we should say, right? Yeah. So for every case of the problem. And that's very important that in this theory, when we measure the complexity of an algorithm, we really measure the growth of the number of steps in the worst case. So you may have an algorithm that runs very rapidly in most cases, but if there's any case where it gets into a very long computation, that would increase the computational complexity by this measure. And that's a very important issue because there are, as we may discuss later, there are some very important algorithms which don't have a good standing from the point of view of their worst case performance, and yet are very effective. So, so theoreticians are interested in P, the class of problems solvable in polynomial time. Then there's NP, which is the class of problems which may be hard to solve, but where the, where, where, when confronted with a solution, you can check it in polynomial time. Let me give you an example there. So if we look at the assignment problem, so you have n boys, you have n girls, the number of numbers that you need to write down to specify the problem instances, n squared. And the question is, how many steps are needed to solve it? And Jack Edmonds and I were the first to show that it could be done in time, n cubed, earlier algorithms required n to the fourth. So as a polynomial function of the size of the input, this is a fast algorithm. Now to illustrate the class NP, the question is, how long would it take to verify that a solution is optimal? So for example, if, if the input was a graph, we might want to find the largest clique in the graph, or a clique is a set of vertices such that any vertex, each vertex in the set is adjacent to each of the others. So the clique is a complete subgraph. Yeah, so if it's a Facebook social network, everybody's friends with everybody else, close clique of friends. Oh, that would be what's called a complete graph, it would be. No, I mean within that clique. Within that clique, yeah. They're all friends. So a complete graph is when... Everybody is friendly. Everybody is friends with everybody. Yeah. So the problem might be to determine whether in a given graph there exists a clique of a certain size. Now that turns out to be a very hard problem, but how, but if somebody hands you a clique and asks you to check whether it is, hands you a set of vertices and asks you to check whether it's a clique, you could do that simply by exhaustively looking at all of the edges between the vertices in the clique and verifying that they're all there. And that's a polynomial time algorithm. That's a polynomial. So the verification, there, the problem of finding the clique appears to be extremely hard, but the problem of verifying a clique to see if it reaches the target number of vertices is easy to verify. So finding the clique is hard, checking it is easy. Problems of that nature are called non-deterministic polynomial time algorithms, and that's the class NP. And what about NP complete and NP hard? Okay, let's talk about problems where you're getting a yes or no answer rather than a numerical value. So either there is a perfect matching of the boys with the girls or there isn't. It's clear that every problem in NP is also in NP. If you can solve the problem exactly, then you can certainly verify the solution. On the other hand, there are problems in the class NP. This is the class of problems that are easy to check, although they may be hard to solve. It's not at all clear that problems in NP lie in P. So for example, if we're looking at scheduling classes at a school, the fact that you can verify when handed a schedule for the school, whether it meets all the requirements, that doesn't mean that you can find the schedule rapidly. So intuitively, NP, non-deterministic polynomial, checking rather than finding, is going to be harder than, is going to include, is easier. Checking is easier, and therefore the class of problems that can be checked appears to be much larger than the class of problems that can be solved. And then you keep adding appears to and sort of these additional words that designate that we don't know for sure yet. We don't know for sure. So the theoretical question, which is considered to be the most central problem in theoretical computer science, or at least computational complexity theory, combinatorial algorithm theory, question is whether P is equal to NP. If P were equal to NP, it would be amazing. It would mean that every problem where a solution can be rapidly checked can actually be solved in polynomial time. We don't really believe that's true. If you're scheduling classes at a school, we expect that if somebody hands you a satisfying schedule, you can verify that it works. That doesn't mean that you should be able to find such a schedule. So intuitively, NP encompasses a lot more problems than P. So can we take a small tangent and break apart that intuition? So do you, first of all, think that the biggest sort of open problem in computer science, maybe mathematics, is whether P equals NP? Do you think P equals NP, or do you think P is not equal to NP? If you had to bet all your money on it. I would bet that P is unequal to NP, simply because there are problems that have been around for centuries and have been studied intensively in mathematics, and even more so in the last 50 years since the P versus NP was stated, and no polynomial time algorithms have been found for these easy-to-check problems. So one example is a problem that goes back to the mathematician Gauss, who was interested in factoring large numbers. So we know what a number is prime if it cannot be written as the product of two or more numbers unequal to one. So if we can factor a number like 91, it's 7 times 13. But if I give you 20-digit or 30-digit numbers, you're probably going to be at a loss to have any idea whether they can be factored. So the problem of factoring very large numbers does not appear to have an efficient solution. But once you have found the factors, expressed the number as a product of two smaller numbers, you can quickly verify that they are factors of the number. And your intuition is a lot of people finding, you know, a lot of brilliant people have tried to find algorithms for this one particular problem. There's many others like it that are really well studied, and it would be great to find an efficient algorithm for. Right. And in fact, we have some results that I was instrumental in obtaining following up on work by the mathematician Stephen Cook to show that within the class NP of easy-to- check problems, there's a huge number that are equivalent in the sense that either all of them or none of them lie in P. And this happens only if P is equal to NP. So if P is unequal to NP, we would also know that virtually all the standard combinatorial problems, if P is unequal to NP, none of them can be solved in polynomial time. Can you explain how that's possible to tie together so many problems in a nice bunch that if one is proven to be efficient, then all are? The first and most important stage of progress was a result by Stephen Cook, who showed that a certain problem called the satisfiability problem of propositional logic is as hard as any problem in the class P. So the propositional logic problem is expressed in terms of expressions involving the logical operations and or and not operating on variables that can be either true or false. So an instance of the problem would be some formula involving and or and not. And the question would be whether there is an assignment of truth values to the variables in the problem that would make the formula true. So, for example, if I take the formula A or B and A or not B and not A or B and not A or not B, and take the conjunction of all four of those so-called expressions, you can determine that no assignment of truth values to the variables A and B will allow that conjunction of what are called clauses to be true. So that's an example of a formula in propositional logic involving expressions based on the operations and or and not. That's an example of a problem which is not satisfiable. There is no solution that satisfies all of those constraints. And that's like one of the cleanest and fundamental problems in computer science. It's like a nice statement of a really hard problem. It's a nice statement of a really hard problem. And what Cook showed is that every problem in NP can be re-expressed as an instance of the satisfiability problem. So to do that, he used the observation that a very simple abstract machine called the Turing machine can be used to describe any algorithm. An algorithm for any realistic computer can be translated into an equivalent algorithm on one of these Turing machines, which are extremely simple. So Turing machine, there's a tape and you can walk along that tape. You have data on a tape and you have basic instructions, a finite list of instructions, which say if you're reading a particular symbol on the tape and you're in a particular state, then you can move to a different state and change the state of the number or the element that you were looking at, the cell of the tape that you were looking at. And that was like a metaphor and a mathematical construct that Turing put together to represent all possible computation. All possible computation. Now, one of these so-called Turing machines is too simple to be useful in practice, but for theoretical purposes, we can depend on the fact that an algorithm for any computer can be translated into one that would run on a Turing machine. And then using that fact, he could sort of describe any possible non-deterministic polynomial time algorithm, any algorithm for a problem in NP could be expressed as a sequence of moves of the Turing machine described in terms of reading a symbol on the tape while you're in a given state and moving to a new state and leaving behind a new symbol. And given that fact that any non-deterministic polynomial time algorithm can be described by a list of such instructions, you could translate the problem into the language of the satisfiability problem. Is that amazing to you, by the way, if you take yourself back when you were first thinking about this space of problems? Is that, how amazing is that? It's astonishing. When you look at Cook's proof, it's not too difficult to sort of figure out why this is so, but the implications are staggering. It tells us that this, of all the problems in NP, all the problems where solutions are easy to check, they can all be rewritten in terms of the satisfiability problem. Yeah, it's adding so much more weight to the P equals NP question, because all it takes is to show that one algorithm in this class. That's right. So the P versus NP can be re-expressed as simply asking whether the satisfiability problem of propositional logic is solvable in polynomial time. But there's more. I encountered Cook's paper when he published it in a conference in 1971. Yeah, so when I saw Cook's paper and saw this reduction of each of the problems in NP by a uniform method to the satisfiability problem of propositional logic, that meant that the satisfiability problem was a universal combinatorial problem. And it occurred to me, through experience I had had in trying to solve other combinatorial problems, that there were many other problems which seemed to have that universal structure. And so I began looking for reductions from the satisfiability to other problems. One of the other problems would be the so-called integer programming problem of solving a, determining whether there's a solution to a set of linear inequalities involving integer variables. Just like linear programming, but there's a constraint that the variables must remain integers. Integers, in fact, must be either zero or one. It could only take on those values. And that makes the problem much harder. Yes, that makes the problem much harder. And it was not difficult to show that the satisfiability problem can be restated as an integer programming problem. Can you pause on that? Was that one of the first problem mappings that you tried to do? And how hard is that mapping? You said it wasn't hard to show, but that's a big leap. It is a big leap, yeah. Well, let me give you another example. Another problem in NP is whether a graph contains a clique of a given size. And now the question is, can we reduce the propositional logic problem to the problem of whether there's a clique of a certain size? Well, if you look at the propositional logic problem, it can be expressed as a number of clauses, each of which is of the form A or B or C, where A is either one of the variables in the problem or the negation of one of the variables. And an instance of the propositional logic problem can be rewritten using the following using operations of Boolean logic. Can be rewritten as the conjunction of a set of clauses, the and of a set of ors, where each clause is a disjunction, an or of variables or negated variables. So the question in the satisfiability problem is whether those clauses can be simultaneously satisfied. Now, to satisfy all those clauses, you have to find one of the terms in each clause, which is going to be true in your truth assignment. But you can't make the same variable both true and false. So if you have the variable A in one clause, and you want to satisfy that clause by making A true, you can't also make the complement of A true in some other clause. And so the goal is to make every single clause true if it's possible to satisfy this. And the way you make it true is at least one term in the clause must be true. Got it. So now we, to convert this problem to something called the independent set problem, where you're just sort of asking for a set of vertices in a graph such that no two of them are adjacent, sort of the opposite of the clique problem. So we've seen that we can now express that as finding a set of terms, one in each clause, without picking both the variable and the negation of that variable. Because if the variable is assigned the truth value, the negated variable has to have the opposite truth value. Right. And so we can construct a graph where the vertices are the terms in all of the clauses, and you have an edge between two terms, an edge between two occurrences of terms, either if they're both in the same clause, because you're only picking one element from each clause, and also an edge between them if they represent opposite values of the same variable, because you can't make a variable both true and false. And so you get a graph where you have all of these occurrences of variables, you have edges, which mean that you're not allowed to choose both ends of the edge, either because they're in the same clause or they're negations of one another. Right, and that's a, first of all, sort of to zoom out, that's a really powerful idea that you could take a graph and connect it to a logic equation somehow, and do that mapping for all possible formulations of a particular problem on a graph. Yeah. I mean, that still is hard for me to believe that that's possible. That there, like what do you make of that, that there's such a union of, there's such a friendship among all these problems across that somehow are akin to combinatorial algorithms, that they're all somehow related. I know it can be proven, but what do you make of it, that that's true? Well, that they just have the same expressive power, you can take any one of them and translate it into the terms of the other. But the fact that they have the same expressive power also somehow means that they can be translatable. Right. And what I did in the 1971 paper was to take 21 fundamental problems, the commonly occurring problems of packing, covering, matching, and so forth, lying in the class NP, and show that the satisfiability problem can be re-expressed as any of those, that any of those have the same expressive power. And that was like throwing down the gauntlet of saying, there's probably many more problems like this. Right. But that's just saying that, look, that they're all the same. They're all the same, but not exactly. They're all the same in terms of whether they are rich enough to express any of the others. But that doesn't mean that they have the same computational complexity. But what we can say is that either all of these problems or none of them are solvable in polynomial time. Yeah, so where does NP completeness and NP hard as classes fit? Oh, that's just a small technicality. So when we're talking about decision problems, that means that the answer is just yes or no. There is a clique of size 15 or there's not a clique of size 15. On the other hand, an optimization problem would be asking, find the largest clique. The answer would not be yes or no, it would be 15. So when you're putting a valuation on the different solutions and you're asking for the one with the highest valuation, that's an optimization problem. And there's a very close affinity between the two kinds of problems. But the counterpart of being the hardest decision problem, the hardest yes-no problem, the counterpart of that is to minimize or maximize an objective function. And so a problem that's hardest in the class when viewed in terms of optimization, those are called NP hard rather than NP complete. And NP complete is for decision problems. And NP complete is for decision problems. So if somebody shows that P equals NP, what do you think that proof will look like? If you were to put on yourself, if it's possible to show that as a proof or to demonstrate an algorithm? All I can say is that it will involve concepts that we do not now have and approaches that we don't have. Do you think those concepts are out there in terms of inside complexity theory, inside of computational analysis of algorithms? Do you think there's concepts that are totally outside of the box that we haven't considered yet? I think that if there is a proof that P is equal to NP or that P is unequal to NP, it'll depend on concepts that are now outside the box. Now if that's shown either way, P equals NP or P not, well, actually P equals NP, what impact? You kind of mentioned a little bit, but can you linger on it? What kind of impact would it have on theoretical computer science and perhaps software, these systems in general? Well, I think it would have enormous impact on the world in either way case. If P is unequal to NP, which is what we expect, then we know that for the great majority of the combinatorial problems that come up, since they're known to be NP complete, we're not going to be able to solve them by efficient algorithms. However, there's a little bit of hope in that it may be that we can solve most instances. All we know is that if a problem's not in P, then it can't be solved efficiently on all instances. But basically, if we find that P is unequal to NP, it will mean that we can't expect always to get the optimal solutions to these problems, and we have to depend on heuristics that perhaps work most of the time or give us good approximate solutions. So we would turn our eye towards the heuristics with a little bit more acceptance and comfort on our hearts. Exactly. Okay, so let me ask a romanticized question, what to you is one of the most or the most beautiful combinatorial algorithm in your own life or just in general in the field that you've ever come across or have developed yourself? I like the stable matching problem, or the stable marriage problem very much. What's the stable matching problem? Imagine that you want to marry off n boys with n girls, and each boy has an ordered list of his preferences among the girls, his first choice, his second choice, through her nth choice. And each girl also has an ordering of the boys, his first choice, second choice, and so on. And we'll say that a matching, a one-to-one matching of the boys with the girls is stable if there are no two couples in the matching, such that the boy in the first couple prefers the girl in the second couple to her mate, and she prefers the boy to her current mate. In other words, if there is, the matching is stable if there is no pair who want to run away with each other, leaving their partners behind. Gotcha. Yeah. Actually, this is relevant to matching residents with hospitals and some other real-life problems, although not quite in the form that I described. So it turns out that for any set of preferences, a stable matching exists, and moreover, it can be computed by a simple algorithm in which each boy starts making proposals to girls. And if a girl receives a proposal, she accepts it tentatively, but she can drop it later if she gets a better proposal from her point of view. And the boys start going down their lists, proposing to their first, second, third choices, until stopping when a proposal is accepted. But the girls, meanwhile, are watching the proposals that are coming in to them, and the girl will drop her current partner if she gets a better proposal. And the boys never go back through the list? They never go back, yeah. So once they've been denied... They don't try again. They don't try again, because the girls are always improving their status as they receive better and better proposals. The boys are going down their list, starting with their top preferences. And one can prove that the process will come to an end, where everybody will get matched with somebody, and you won't have any pair that want to abscond from each other. Do you find the proof or the algorithm itself beautiful? Or is it the fact that with the simplicity of just the two marching... I mean, the simplicity of the underlying rule of the algorithm, is that the beautiful part? Both, I would say. And you also have the observation that you might ask, who is better off, the boys who are doing the proposing or the girls who are reacting to proposals? And it turns out that it's the boys who are doing the best. That is, each boy is doing at least as well as he could do in any other staple matching. So there's a sort of lesson for the boys, that you should go out and be proactive and make those proposals. Go for broke. I don't know if this is directly mappable philosophically to our society, but certainly seems like a compelling notion. And like you said, there's probably a lot of actual real-world problems that this could be mapped to. Yeah, well, you get complications. For example, what happens when a husband and wife want to be assigned to the same hospital? So you have to take those constraints into account. And then the problem becomes NP-hard. Why is it a problem for the husband and wife to be assigned to the same hospital? No, it's desirable. Desirable. Or at least go to the same city. So you can't, if you're assigning residents to hospitals. And then you have some preferences for the husband and the wife or for the hospitals. The residents have their own preferences. Residents both male and female have their own preferences. The hospitals have their preferences. But if resident A, the boy, is going to Philadelphia, then you'd like his wife also to be assigned to a hospital in Philadelphia. Which step makes it a NP-hard problem that you mentioned? The fact that you have this additional constraint. That it's not just the preferences of individuals, but the fact that the two partners to a marriage have to be assigned to the same place. I'm being a little dense. The perfect matching? No, not the perfect. Stable matching is what you referred to. That's when two partners are trying to— Okay, what's confusing you is that in the first interpretation of the problem I had boys matching with girls. In the second interpretation, you have humans matching with institutions. And there's a coupling between within the—gotcha—within the humans. Any added little constraint will make it an NP-hard problem. Well, yeah. By the way, the outgoing you mentioned, was it one of yours? No, no, that was due to Gale and Shapley. My friend David Gale passed away before he could get part of the Nobel Prize, but his partner Shapley shared in a Nobel Prize with somebody else for— Economics? For economics. More ideas stemming from the stable matching idea. So you've also developed yourself some elegant, beautiful algorithms. Again, picking your children, so the Robin Karp algorithm for string searching, pattern matching, Edmund Karp algorithm for max flows we mentioned, Hopcroft Karp algorithm for finding maximum cardinality matchings in bipartite graphs. Is there ones that stand out to you, ones you're most proud of, or just whether it's beauty, elegance, or just being the right discovery development in your life that you're especially proud of? I like the Rabin-Karp algorithm because it illustrates the power of randomization. So the problem there is to decide whether a given long string of symbols from some alphabet contains a given word, whether a particular word occurs within some very much longer word. And so the idea of the algorithm is to associate with the word that we're looking for a fingerprint, some number or some combinatorial object that describes that word, and then to look for an occurrence of that same fingerprint as you slide along the longer word. And what we do is we associate with each word a number. So first of all, we think of the letters that occur in a word as the digits of, let's say, decimal or whatever base here, whatever number of different symbols there are in the alphabet. That's the base of the numbers, yeah. Right. So every word can then be thought of as a number with the letters being the digits of that number. And then we pick a random prime number in a certain range, and we take that word viewed as a number and take the remainder on dividing that number by the prime. So coming up with a nice hash function. It's a kind of hash function. Yeah. It gives you a little shortcut for that particular word. Yeah. So that's the... It's very different than other algorithms of its kind that were trying to do search string matching. Yeah, which usually are combinatorial and don't involve the idea of taking a random fingerprint. Yes. And doing the fingerprinting has two advantages. One is that as we slide along the long word, digit by digit, we keep a window of a certain size, the size of the word we're looking for. And we compute the fingerprint of every stretch of that length. And it turns out that just a couple of arithmetical operations will take you from the fingerprint of one part to what you get when you slide over by one position. So the computation of all the fingerprints is simple. And secondly, it's unlikely if the prime is chosen randomly from a certain range that you will get two of the segments in question having the same fingerprint. And so there's a small probability of error, which can be checked after the fact, and also the ease of doing the computation because you're working with these fingerprints, which are remainders modulo some big prime. So that's the magical thing about randomized algorithms is that if you add a little bit of randomness, it somehow allows you to take a pretty naive approach, a simple looking approach, and allow it to run extremely well. So can you maybe take a step back and say, what is a randomized algorithm, this category of algorithms? Well, it's just the ability to draw a random number from some range or to associate a random number with some object or to draw at random from some set. So another example is very simple. If we're conducting a presidential election and we would like to pick the winner, in principle, we could draw a random sample of all of the voters in the country. And if it was of substantial size, say a few thousand, then the most popular candidate in that group would be very likely to be the correct choice that would come out of counting all the millions of votes. Now, of course, we can't do this because, first of all, everybody has to feel that his or her vote counted. And secondly, we can't really do a purely random sample from that population. And I guess thirdly, there could be a tie, in which case we wouldn't have a significant difference between two candidates. But those things aside, if you didn't have all that messiness of human beings, you could prove that that kind of random picking would be... Because the random picking would solve the problem with a very low probability of error. Another example is testing whether a number is prime. So if I want to test whether 17 is prime, I could pick any number between 1 and 17 and raise it to the 16th power, modulo 17, and you should get back the original number. That's a famous formula due to Fermat, it's called Fermat's Little Theorem, that if you take any number a in the range 0 through n minus 1 and raise it to the n minus 1th power, modulo n, you'll get back the number a, if a is prime. So if you don't get back the number a, that's a proof that a number is not prime. And you can show that, suitably define the probability that you will get a value unequal... You will get a violation of Fermat's result is very high, and so this gives you a way of rapidly proving that a number is not prime. It's a little more complicated than that because there are certain values of n where something a little more elaborate has to be done, but that's the basic idea. Taking an identity that holds for primes, and therefore if it ever fails on any instance for a non-prime, you know that the number is not prime. It's a quick choice, a fast choice, fast proof that a number is not prime. Can you maybe elaborate a little bit more of what's your intuition why randomness works so well and results in such simple algorithms? Well, the example of conducting an election where you could take, in theory, you could take a sample and depend on the validity of the sample to really represent the whole is just the basic fact of statistics, which gives a lot of opportunities. I actually exploited that sort of random sampling idea in designing an algorithm for counting the number of solutions that satisfy a particular formula in propositional logic. A particular... so some version of the satisfiability problem? A version of the satisfiability problem. Is there some interesting insight that you want to elaborate on? Some aspect of that algorithm that might be useful to describe? So you have a collection of formulas, and you want to count the number of solutions that satisfy at least one of the formulas. And you can count the number of solutions that satisfy any particular one of the formulas, but you have to account for the fact that that solution might be counted many times if it solves more than one of the formulas. And so what you do is you sample from the formulas according to the number of solutions that satisfy each individual one. In that way, you draw a random solution, but then you correct by looking at the number of formulas that satisfy that random solution and don't double count. So you can think of it this way. So you have a matrix of zeros and ones, and you want to know how many columns of that matrix contain at least one one. And you can count in each row how many ones there are. So what you can do is draw from the rows according to the number of ones. If a row has more ones, it gets drawn more frequently. But then if you draw from that row, you have to go up the column and looking at where that same one is repeated in different rows and only count it as a success or a hit if it's the earliest row that contains the one. And that gives you a robust statistical estimate of the total number of columns that contain at least one of the ones. So that is an example of the same principle that was used in studying random sampling. Another viewpoint is that if you have a phenomenon that occurs almost all the time, then if you sample one of the occasions where it occurs, you're most likely to find... When you're looking for an occurrence, a random occurrence is likely to work. So that comes up in solving identities, solving algebraic identities. You get two formulas that may look very different. You want to know if they're really identical. What you can do is just pick a random value and evaluate the formulas at that value and see if they agree. And you depend on the fact that if the formulas are distinct, then they're going to disagree a lot. And so therefore a random choice will exhibit the disagreement. If there are many ways for the two to disagree and you only need to find one disagreement, then random choice is likely to yield it. And in general, so we've just talked about randomized algorithms, but we can look at the probabilistic analysis of algorithms. And that gives us an opportunity to step back and, as we've said, everything we've been talking about is worst-case analysis. Could you maybe comment on the usefulness and the power of worst-case analysis versus best-case analysis, average case, probabilistic? How do we think about the future of theoretical computer science, computer science, in the kind of analysis we do of algorithms? Does worst-case analysis still have a place, an important place, or do we want to try to move forward towards kind of average case analysis? And what are the challenges there? So if worst-case analysis shows that an algorithm is always good, that's fine. If worst-case analysis is used to show that the problem, that the solution is not always good, then you have to step back and do something else to ask, how often will you get a good solution? Just to pause on that for a second, that's so beautifully put, because I think we tend to judge algorithms. We throw them in the trash the moment their worst case is shown to be bad. Right. And that's unfortunate. I think a good example is going back to the satisfiability problem. There are very powerful programs called SAT solvers, which in practice fairly reliably solve instances with many millions of variables that arise in digital design or in proving programs correct in other applications. And so in many application areas, even though satisfiability, as we've already discussed, is NP-complete, the SAT solvers will work so well that the people in that discipline tend to think of satisfiability as an easy problem. So in other words, just for some reason that we don't entirely understand, the instances that people formulate in designing digital circuits or other applications are such that satisfiability is not hard to check, and even searching for a satisfying solution can be done efficiently in practice. And there are many examples. For example, we talked about the traveling salesman problem. So just to refresh our memories, the problem is you've got a set of cities, you have pairwise distances between cities, and you want to find a tour through all the cities that minimizes the total cost of all the edges traversed, all the trips between cities. The problem is NP-hard, but people using integer programming codes together with some other mathematical tricks can solve geometric instances of the problem where the cities are, let's say, points in the plane, and get optimal solutions to problems with tens of thousands of cities. Actually, it'll take a few computer months to solve a problem of that size, but for problems of size 1,000 or 2, it'll rapidly get provably optimal solutions, even though, again, we know that it's unlikely that the traveling salesman problem can be solved in polynomial time. Are there methodologies, like rigorous, systematic methodologies for—you said in practice. In practice, this algorithm is pretty good. Are there systematic ways of saying, in practice, this one is pretty good? In other words, average case analysis. Or you've also mentioned that average case requires you to understand what the typical case is, typical instances, and that might be really difficult. That's very difficult. After I did my original work on showing all these problems through NP-complete, I looked around for a way to shed some positive light on combinatorial algorithms. What I tried to do was to study problems' behavior on the average or with high probability, but I had to make some assumptions about what's the probability space, what's the sample space, what do we mean by typical problems. That's very hard to say, so I took the easy way out and made some very simplistic assumptions. So I assumed, for example, that if we were generating a graph with a certain number of vertices and edges, then we would generate the graph by simply choosing one edge at a time at random until we got the right number of edges. That's a particular model of random graphs that has been studied mathematically a lot. And within that model, I could prove all kinds of wonderful things. I and others who also worked on this. So we could show that we know exactly how many edges there have to be in order for there to be a so-called Hamiltonian circuit. That's a cycle that visits each vertex exactly once. We know that if the number of edges is a little bit more than n log n, where n is the number of vertices, then such a cycle is very likely to exist. And we can give a heuristic that will find it with high probability. And the community in which I was working got a lot of results along these lines. But the field tended to be rather lukewarm about accepting these results as meaningful because we were making such a simplistic assumption about the kinds of graphs that we would be dealing with. So we could show all kinds of wonderful things. It was a great playground. I enjoyed doing it. But after a while, I concluded that it didn't have a lot of bite in terms of the practical application. Lex Dyson Okay, so there's too much into the world of toy problems. David Miller Yeah. Lex Dyson Okay. But all right, is there a way to find nice representative real-world impactful instances of a problem on which demonstrate that an algorithm is good? So this is kind of like the machine learning world, that's kind of what they at its best tries to do is find a data set from the real world and show the performance. All the conferences are all focused on beating the performance on that real-world data set. Is there an equivalent in complexity analysis? David Miller Not really. Don Knuth started to collect examples of graphs coming from various places. So he would have a whole zoo of different graphs that he could choose from, and he could study the performance of algorithms on different types of graphs. Lex Dyson But there it's really important and compelling to be able to define a class of graphs. The actual act of defining a class of graphs that you're interested in, it seems to be a non-trivial step before talking about instances that we should care about in the real world. David Miller Yeah. There's nothing available there that would be analogous to the training set for supervised learning, where you sort of assume that the world has given you a bunch of examples to work with. You don't really have that for problems, for combinatorial problems on graphs and networks. Lex Dyson There's been a huge growth, a big growth of data sets available. Do you think some aspect of theoretical computer science, I might be contradicting my own question while saying it, but will there be some aspect, an empirical aspect of theoretical computer science which will allow the fact that these data sets are huge, we'll start using them for analysis? If you want to say something about a graph algorithm, you might take a social network like Facebook and looking at subgraphs of that and prove something about the Facebook graph and at the same time be respected in the theoretical computer science community. David Miller That hasn't been achieved yet, I'm afraid. Lex Dyson Is that, is that, is that P equals NP, is that impossible? Is it impossible to publish a successful paper in the theoretical computer science community that shows some performance on a real world data set? Or is that really just those are two different worlds? David Miller They haven't really come together. I would say that there is a field of experimental algorithmics where people, sometimes they're given some family of examples. Sometimes they just generate them at random, and they report on performance. But there's no convincing evidence that the sample is representative of anything at all. Lex Dyson So let me ask, in terms of breakthroughs and open problems, what are the most compelling open problems to you? And what possible breakthroughs do you see in the near term in terms of theoretical computer science? David Miller Well, there are all kinds of relationships among complexity classes that can be studied. Just to mention one thing, I wrote a paper with Richard Lipton in 1979, where we asked the following question. If you take a problem, a combinatorial problem in NP, let's say, and you choose and you pick the size of the problem, say it's a traveling salesman problem, but of size 52. And you ask, could you get an efficient, a small Boolean circuit tailored for that size, 52, where you could feed the edges of the graph in as Boolean inputs and get as an output the question of whether or not there's a tour of a certain length. And that would, in other words, briefly, what you would say in that case is that the problem has small circuits, polynomial-sized circuits. Now we know that if P is equal to NP, then in fact, these problems will have small circuits. But what about the converse? That a problem have small circuits, meaning that an algorithm tailored to any particular size could work well and yet not be a polynomial-time algorithm. That is, you couldn't write it as a single uniform algorithm good for all sizes. Just to clarify, small circuits for a problem of particular size or even further constraint, small circuit for a particular... No, for all the inputs of that size. Is that a trivial problem for a particular instance? So coming up, an automated way of coming up with a circuit, I guess that's just an instance. That would be hard, yeah. But there's the existential question. Everybody talks nowadays about existential questions, existential challenges. You could ask the question, does the Hamiltonian circuit problem have a small circuit for every size? For each size, a different small circuit? In other words, could you tailor solutions depending on the size and get polynomial size? Even if P is not equal to NP. Right. That would be fascinating if that's true. Yeah. What we proved is that if that were possible, then something strange would happen in complexity theory. Some high-level class which I could briefly describe, something strange would happen. So I'll take a stab at describing what I mean. Sure, let's go there. So we have to define this hierarchy in which the first level of the hierarchy is P and the second level is NP. And what is NP? NP involves statements of the form, there exists a something such that something holds. So for example, there exists a coloring such that a graph can be colored with only that number of colors, or there exists a Hamiltonian circuit. There's a statement about this graph. Yeah. So the NP deals with statements of that kind, that there exists a solution. Now you could imagine a more complicated expression which says, for all x, there exists a y such that some proposition holds involving both x and y. So that would say, for example, in game theory, for all strategies for the first player, there exists a strategy for the second player such that the first player wins. That would be at the second level of the hierarchy. The third level would be, there exists an A such that for all B, there exists a C, but something holds. And you can imagine going higher and higher in the hierarchy. And you'd expect that the complexity classes that correspond to those different cases would get bigger and bigger. What do you mean by bigger and bigger? Sorry, they'd get harder and harder to solve. And what Lifton and I showed was that if NP had small circuits, then this hierarchy would collapse down to the second level. In other words, you wouldn't get any more mileage by complicating your expressions with three quantifiers or four quantifiers or any number. I'm not sure what to make of that exactly. Well, I think it would be evidence that NP doesn't have small circuits because something so bizarre would happen. But again, it's only evidence, not proof. Well, yeah, that's not even evidence because you're saying P's not equal to NP because something bizarre has to happen. I mean, that's proof by the lack of bizarreness in our science. But it seems like just the very notion of P equals NP would be bizarre. So any way you arrive at, there's no way. You have to fight the dragon at some point. Yeah, okay. Well, anyway, for whatever it's worth, that's what we proved. Awesome. So that's a potential space of open, interesting problems. Let me ask you about this other world of machine learning, of deep learning. What's your thoughts on the history and the current progress of machine learning field that's often progressed sort of separately as a space of ideas and space of people than the theoretical computer science or just even computer science world? Yeah, it's really very different from the theoretical computer science world because the results about it, algorithmic performance tend to be empirical. It's more akin to the world of SAT solvers where we observe that for formulas arising in practice, the solver does well. So it's of that type. We're moving into the empirical evaluation of algorithms. Now it's clear that there have been huge successes in image processing, robotics, natural language processing, a little less so, but across the spectrum of game playing is another one. There have been great successes. One of those effects is that it's not too hard to become a millionaire if you can get a reputation in machine learning. There'll be all kinds of companies that will be willing to offer you the moon because they think that if they have AI at their disposal, then they can solve all kinds of problems. But there are limitations. One is that the solutions that you get to supervise learning problems through convolutional neural networks seem to perform amazingly well, even for inputs that are outside the training set. But we don't have any theoretical understanding of why that's true. Secondly, the solutions, the networks that you get, are very hard to understand, and so very little insight comes out. So yeah, they may seem to work on your training set, and you may be able to discover whether your photos occur in a different sample of inputs or not. But we don't really know what's going on. We don't know the features that distinguish the photographs or the objects are not easy to characterize. Lex Dressel Well, it's interesting because you mentioned coming up with a small circuit to solve a particular size problem. It seems that neural networks are kind of small circuits. Peter Mankaro In a way, yeah. Lex Dressel But they're not programs. Sort of like the things you've designed are algorithms, programs. Peter Mankaro Right. Lex Dressel Algorithms. Neural networks aren't able to develop algorithms to solve a problem. Is it more of a function? Peter Mankaro Well, they are algorithms. It's just that they're... Lex Dressel But sort of, yeah, it could be a semantic question, but there's not a algorithmic style manipulation of the input. Perhaps you could argue there is. It feels a lot more like a function of the input. Peter Mankaro Yeah, it's a function. It's a computable function. Once you have the network, you can simulate it on a given input and figure out the output. But if you're trying to recognize images, then you don't know what features of the image are really being determinant of what the circuit is doing. The circuit is sort of very intricate, and it's not clear that the simple characteristics that you're looking for, the edges of the objects or whatever they may be, they're not emerging from the structure of the circuit. Lex Dressel Well, it's not clear to us humans, but it's clear to the circuit. Peter Mankaro Yeah. Well, right. Lex Dressel I mean, it's not clear to sort of the elephant how the human brain works, but it's clear to us humans. We can explain to each other our reasoning, and that's why the cognitive science and psychology field exists. Maybe the whole thing of being explainable to humans is a little bit overrated. Peter Mankaro Oh, maybe, yeah. I guess you could say the same thing about our brain, that when we perform acts of cognition, we have no idea how we do it, really. We do, though. We, at least for the visual system, the auditory system, and so on, we do get some understanding of the principles that they operate under, but for many deeper cognitive tasks, we don't have that. Lex Dressel That's right. Let me ask. Peter Mankaro Yeah. Lex Dressel You've also been doing work on bioinformatics. Does it amaze you that the fundamental building blocks, so if we take a step back and look at us humans, the building blocks used by evolution to build us intelligent human beings is all contained there in our DNA? Peter Mankaro It's amazing, and what's really amazing is that we are beginning to learn how to edit DNA, which is very, very, very fascinating. This ability to take a sequence, find it in the genome, and do something to it. Lex Dressel I mean, that's really taking our biological systems towards the worlds of algorithms. Peter Mankaro Yeah, but it raises a lot of questions. You have to distinguish between doing it on an individual or doing it on somebody's germline, which means that all of their descendants will be affected. Lex Dressel So that's like an ethical… Peter Mankaro Yeah, so it raises very severe ethical questions. And even doing it on individuals, there's a lot of hubris involved that you can assume that knocking out a particular gene is going to be beneficial because you don't know what the side effects are going to be. So we have this wonderful new world of gene editing, which is very, very impressive, and it could be used in agriculture, it could be used in medicine in various ways, but very serious ethical problems arise. Lex Dressel What are to you the most interesting places where algorithms, sort of the ethical side is an exceptionally challenging thing that I think we're going to have to tackle with all of genetic engineering. But on the algorithmic side, there's a lot of benefit that's possible. So is there areas where you see exciting possibilities for algorithms to help model, optimize, study biological systems? Peter Mankaro Yeah, I mean, we can certainly analyze genomic data to figure out which genes are operative in the cell and under what conditions and which proteins affect one another, which proteins physically interact. We can sequence proteins and modify them. Lex Dressel Is there some aspect of that that's a computer science problem, or is that still fundamentally a biology problem? Peter Mankaro Well, it's a big data, it's a statistical big data problem for sure. So the biological data sets are increasing our ability to study our ancestry, to study the tendencies towards disease, to personalize treatment according to what's in our genomes and what tendencies for disease we have, to be able to predict what troubles might come upon us in the future and anticipate them, to understand whether you, for a woman, whether her proclivity for breast cancer is strong enough that you would want to take action to avoid it. Lex Dressel You dedicate your 1985 Turing Award lecture to the memory of your father. What's your fondest memory of your dad? Peter Mankaro Seeing him standing in front of a class at the blackboard drawing perfect circles by hand and showing his ability to attract the interest of the motley collection of eighth-grade students that he was teaching. Lex Dressel When did you get a chance to see him draw the perfect circles? Peter Mankaro On rare occasions, I would get a chance to sneak into his classroom and observe it. And I think he was at his best in the classroom. I think he really came to life and had fun not only teaching but engaging in chit-chat with the students and ingratiating himself with the students. And what I inherited from that is a great desire to be a teacher. I retired recently, and a lot of my former students came, students with whom I had done research or who had read my papers or who had been in my classes. And when they talked about me, they talked not about my 1979 paper or my 1992 paper, but about what came away in my classes, and not just the details but just the approach and the manner of teaching. And so I sort of take pride in the, at least in my early years as a faculty member at Berkeley, I was exemplary in preparing my lectures, and I always came in prepared to the teeth and able therefore to deviate according to what happened in the class and to really, really provide a model for the students. So is there advice you could give for others on how to be a good teacher? So preparation is one thing you've mentioned, being exceptionally well prepared, but are there other things, pieces of advice that you can impart? Well the top three would be preparation, preparation, and preparation. Why is preparation so important, I guess? It's because it gives you the ease to deal with any situation that comes up in the classroom. And if you discover that you're not getting through one way, you can do it another way. If the students have questions, you can handle the questions. Really you're also feeling the crowd, the students, of what they're struggling with, what they're picking up, just looking at them through the questions, but even just through their eyes. Yeah, that's right. And because of the preparation, you can dance. You can dance, you can say it another way, give it another angle. Are there, in particular, ideas and algorithms of computer science that you find were big aha moments for students, where they, for some reason, once they got it, it clicked for them and they fell in love with computer science? Or is it individual, is it different for everybody? It's different for everybody. You have to work differently with students. Some of them just don't need much influence. They're just running with what they're doing and they just need an ear now and then. Others need a little prodding. Others need to be persuaded to collaborate among themselves rather than working alone. They have their personal ups and downs, so you have to deal with each student as a human being and bring out the best. Humans are complicated. Yeah. Perhaps a silly question. If you could relive a moment in your life outside of family because it made you truly happy or perhaps because it changed the direction of your life in a profound way, what moment would you pick? I was kind of a lazy student as an undergraduate and even in my first year in graduate school. I think it was when I started doing research. I had a couple of summer jobs where I was able to contribute and I had an idea. And then there was one particular course on mathematical methods and operations research where I just gobbled up the material and I scored 20 points higher than anybody else in the class and came to the attention of the faculty. And it made me realize that I had some ability that was going somewhere. You realize you're pretty good at this thing. I don't think there's a better way to end it, Richard. It was a huge honor. Thank you for decades of incredible work. Thank you for talking to me. Thank you. It's been a great pleasure. You're a superb interviewer. I'll stop it. Thanks for listening to this conversation with Richard Karp. Thank you to our sponsors, Eight Sleep and Cash App. Please consider supporting this podcast by going to eightsleep.com slash Lex to check out their awesome mattress. And downloading Cash App and using code LexPodcast. Click the links, buy the stuff, even just visiting the site, but also considering the purchase helps them know that this podcast is worth supporting in the future. It really is the best way to support this journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcast, support on Patreon, connect with me on Twitter at Lex Friedman if you can figure out how to spell that. And now let me leave you with some words from Isaac Asimov. I do not fear computers. I fear lack of them. Thank you for listening and hope to see you next time.

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Lisa Feldman Barrett: Counterintuitive Ideas About How the Brain Works | Lex Fridman Podcast #129

The following is a conversation with Lisa Feldman Barrett, a professor of psychology at Northeastern University and one of the most brilliant and bold thinkers and scientists I've ever had the pleasure of speaking with. She's the author of a book that revolutionized our understanding of emotion in the brain called How Emotions Are Made, and she's coming out with a new book called Seven and a Half Lessons About the Brain that you can and should pre-order now. I got a chance to read it already and it's one of the best short whirlwind introductions to the human brain I've ever read. It comes out on November 17th, but again, if there's anybody worth supporting, it's Lisa, so please do pre-order the book now. Lisa and I agreed to speak once again around the time of the book release, especially because we felt that this first conversation is good to release now, since we talk about the divisive time we're living through in the United States leading up to the election. And she gives me a whole new way to think about it from a neuroscience perspective that is ultimately inspiring of empathy, compassion, and love. Quick mention of each sponsor, followed by some thoughts related to this episode. First sponsor is Athletic Greens, the all-in-one drink that I start every day with to cover all my nutritional bases that I don't otherwise get through my diet naturally. Second is Magic Spoon, low-carb, keto-friendly, delicious cereal that I reward myself with after a productive day. The cocoa flavor is my favorite. Third sponsor is Cash App, the app I use to send money to friends for food, drinks, and unfortunately, for the many bets I have lost to them. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that the bold, first principles way that Lisa approaches our study of the brain is something that has inspired me ever since I learned about her work. And in fact, I invited her to speak at the AGI series I organized at MIT several years ago. But as a little twist, instead of a lecture, we did a conversation in front of the class. I think that was one of the early moments that led me to start this very podcast. It was scary and gratifying, which is exactly what life is all about. And it's kind of funny how life turns on little moments like these, that at the time don't seem to be anything out of the ordinary. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Lisa Feldman Barrett. Since we'll talk a lot about the brain today, do you think, let's ask the craziest question, do you think there is other intelligent life out there in the universe? Honestly, I've been asking myself lately if there's intelligent life on this planet. You know, I have to think probabilities suggest yes, and also, secretly, I think I just hope that's true. It would be really, I know scientists aren't supposed to have hopes and dreams, but I think it would be really cool and I also think it would be really sad if it wasn't the case. If we really were alone, that would be, that would seem profoundly sad, I think. So it's exciting to you, not scary? Yeah, no, you know, I take a lot of comfort in curiosity. It's a great resource for dealing with stress. So I'm learning all about mushrooms and octopuses and all kinds of stuff. And so for me, this counts, I think, in the realm of awe. But also, I think I'm somebody who cultivates awe deliberately on purpose to feel like a speck. You know, I find it a relief occasionally. To feel small. To feel small in a profoundly large and interesting universe. So maybe to dig more technically on the question of intelligence, do you think it's difficult for intelligent life to arise like it did on Earth? From everything you've written and studied about the brain, how magical of a thing is it in terms of the odds it takes to arise? Yeah, so, you know, magic is just, don't get me wrong, I mean, I like a magic show as much as the next person. My husband was a magician at one time. But, you know, magic is just a bunch of stuff that we don't really understand how it works yet. So I would say, from what I understand, there are some major steps in the course of evolution that at the beginning of life, the step from single cell to multicellular organisms, things like that, which are really not known. I think for me, the question is not so much could it, you know, what's the likelihood that it would happen again, as much as what are the steps and how long would it take? And if it were to happen again on Earth, would we end up with the same menu of life forms that we currently have now? And I think the answer's probably no, right? There's just so much about evolution that is stochastic and driven by chance. But the question is whether that menu would be equally delicious, meaning like there'd be rich complexity of the kind of, like would we get dolphins and humans or whoever else falls in that category of weirdly intelligent, seemingly intelligent, however we define that. Well, I think that has to be true if you just look at the range of creatures who've gone extinct. I mean, if you look at the range of creatures that are on the Earth now, it's incredible. And, you know, it's sort of trite to say that, but it actually is really incredible. Particularly, I don't know, I mean, animals, there are animals that seem really ordinary until you watch them closely and then they become miraculous, you know, like certain types of birds which do very miraculous things, build, you know, bowers and do dances and all these really funky things that are hard to explain with a standard evolutionary story, although, you know, people have them. Birds are weird. They do a lot of, for mating purposes, they have a concept of beauty that I haven't quite, maybe you know much better, but it doesn't seem to fit evolutionary arguments well. It does fit. Well, it depends, right? So I think you're talking about the evolution of beauty, the book that was written recently by, was it Frum, was that his name? Richard Frum, I think, at Yale. Oh, interesting, no, I didn't know. Oh, it's a great book. It's very controversial, though, because he's making an argument that the question about birds and some other animals is why would they engage in such metabolically costly displays when it doesn't improve their fitness at all? And the answer that he gives is the answer that Darwin gave, which is sexual selection, not natural selection, but, you know, selection can occur for all kinds of reasons. There could be artificial selection, which is when we breed animals, right, which is actually how Darwin, that observation helped Darwin come to the idea of natural selection. Oh, interesting. And then there's sexual selection, meaning, and the argument that I think his name is Frum makes is that it's the pleasure, the selection pressure is the pleasure of female birds, which as a woman and as someone who studies affect, that's a great answer. I actually think there probably is natural, I think there is an aspect of natural selection to it, which he maybe hasn't considered. But you were saying the reason we brought up birds is the life we got now seems to be quite incredible. Yeah, so you peek into the ocean, peek into the sky, there are miraculous creatures, look at creatures who've gone extinct, and, you know, in science fiction stories, you couldn't dream up something as interesting. So my guess is that, you know, intelligent life evolves in many different ways, even on this planet. There isn't one form of intelligence, there's not one brain that gives you intelligence. There are lots of different brain structures that can give you intelligence. So my guess is that the menagerie might not look exactly the way that it looks now, but it would certainly be as interesting. But if we look at the human brain versus the brains, or whatever you call them, the mechanisms of intelligence in our ancestors, even early ancestors, that you write about, for example, in your new book, what's the difference between the fanciest brain we got, which is the human brain, and the ancestor brains that it came from? Yeah, I think it depends on how far back you wanna go. You go all the way back, right, in your book. So what's the interesting comparison, would you say? Well, first of all, I wouldn't say that the human brain is the fanciest brain we've got. I mean, an octopus brain is pretty different and pretty fancy, and they can do some pretty amazing things that we cannot do. You know, we can't grow back limbs, we can't change color and texture, we can't comport ourselves and squeeze ourselves into a little crevice. I mean, these are things that we invent, these are like superhero abilities that we invent in stories, right? We can't do any of those things. And so the human brain is certainly, we can certainly do some things that other animals can't do that seem pretty impressive to us. But I would say that there are a number of animal brains which seem pretty impressive to me, that can do interesting things and really impressive things that we can't do. I mean, with your work on how emotions are made and so on, you kind of repaint the view of the brain as less glamorous, I suppose, than you would otherwise think. Or like, I guess you draw a thread that connects all brains together in terms of homeostasis and all that kind of stuff. Yeah, I wouldn't say that the human brain is any less miraculous than anybody else would say. I just think that there are other brain structures which are also miraculous. And I also think that there are a number of things about the human brain which we share with other vertebrates, other animals with backbones, but that we share these miraculous things. But we can do some things in abundance. And we can also do some things with our brains together, working together that other animals can't do, or at least we haven't discovered their ability to do it. Yeah, this social thing. I mean, that's one of the things you write about. How do you make sense of the fact, like the book Sapiens, and the fact that we're able to kind of connect, like network our brains together, like you write about? I'll try to stop saying that. Is that like some kind of feature that's built into there? Is that unique to our human brains? Like how do you make sense of that? What I would say is that our ability to coordinate with each other is not unique to humans. There are lots of animals who can do that. But what we do with that coordination is unique because of some of the structural features in our brains. And it's not that other animals don't have those structural features. It's we have them in abundance. So, the human brain is not larger than you would expect it to be for a primate of our size. If you took a chimpanzee and you grew it to the size of a human, that chimpanzee would have a brain that was the size of a human brain. So there's nothing special about our brain in terms of its size. There's nothing special about our brain in terms of the basic blueprint that builds our brain from an embryo is the basic blueprint that builds all mammalian brains and maybe even all vertebrate brains. It's just that because of its size, and particularly because of the size of the cerebral cortex, which is a part that people mistakenly attribute to rationality. Yeah. Why mistakenly? Isn't that where all the clever stuff happens? Well, no, it really isn't. And I will also say that lots of clever stuff happens in animals who don't have a cerebral cortex. But because of the size of the cerebral cortex and because of some of the features that are enhanced by that size, that gives us the capacity to do things like build civilizations and coordinate with each other, not just to manipulate the physical world, but to add to it in very profound ways. Like, other animals can cooperate with each other and use tools. We draw a line in the sand and we make countries and we create citizens and immigrants. But also ideas. I mean, the countries are centered around the concept of ideas. Well, what do you think a citizen is and an immigrant? Those are ideas. Those are ideas that we impose on reality and make them real. And then they have very, very serious and real effects, physical effects on people. What do you think about the idea that a bunch of people have written about? Dawkins with memes, which is like ideas are breeding. Like, we're just like the canvas for ideas to breed in our brains. So this kind of network that you talk about of brains is just a little canvas for ideas to then compete against each other and so on. I think as a rhetorical tool, it's cool to think that way. So I think it was Michael Pollan. I don't remember if it was in the Botany of Desire, but it was in one of his early books on botany and gardening where he wrote about plants, sort of utilizing humans for their own evolutionary purposes. But it's kind of interesting. You can think about a human gut in a sense as a propagation device for the seeds of tomatoes and what have you. So it's kind of cool. So I think rhetorically it's an interesting device, but ideas are, as far as I know, invented by humans, propagated by humans. So I don't think they're separate from human brains in any way, although it is interesting to think about it that way. Well, of course, the ideas that are using your brain to communicate and write excellent books. And they basically pick you, Lisa, as an effective communicator and thereby are winning. So that's an interesting worldview, to think that there's particular aspects of your brain that are conducive to certain sets of ideas, and maybe those ideas will win out. Yeah, I think the way that I would say it really, though, is that there are many species of animals that influence each other's nervous systems, that regulate each other's nervous systems. And they mainly do it by physical means. They do it by chemicals, scent. They do it by, so termites and ants and bees, for example, use chemical scents. Mammals like rodents use scent, and they also use hearing, audition, and that little bit of vision. Primates, non-human primates, add vision, right? And I think everybody uses touch. Humans, as far as I know, are the only species that use ideas and words to regulate each other, right? I can text something to someone halfway around the world. They don't have to hear my voice. They don't have to see my face. And I can have an effect on their nervous system. And ideas, the ideas that we communicate with words, I mean, words are, in a sense, a way for us to do mental telepathy with each other, right? I mean, I'm not the first person to say that, obviously, but how do I control your heart rate? How do I control your breathing? How do I control your actions? With words, it's because those words are communicating ideas. So you also write, I think, let's go back to the brain. You write that Plato gave us the idea that the human brain has three brains in it, three forces, which is kind of a compelling notion. You disagree. First of all, what are the three parts of the brain, and why do you disagree? So Plato's description of the psyche, which, for the moment, we'll just assume is the same as a mind. There are some scholars who would say, a soul, a psyche, a mind, those aren't actually all the same thing in ancient Greece, but we'll just, for now, gloss over that. So Plato's idea was that, and it was a description of, really, about moral behavior and moral responsibility in humans. So the idea was that the human psyche can be described with a metaphor of two horses and a charioteer. So one horse for instincts, like feeding and fighting and fleeing and reproduction. I'm trying to control my salty language. Which apparently they print in England. I actually tossed off a fairly- F, S? Yeah, F, F. Okay. Yeah, I was like, you printed that? I couldn't believe you printed that. Without the stars or whatever? Oh, no, no, there was full print. They also printed a B word, and it was really, yeah. Well, we should learn something from England. Indeed, anyways, but instincts. And then the other horse represents emotions, and then the charioteer represents rationality, which controls the two beasts, right? And fast forward a couple of centuries, and in the middle of the 20th century, there was a very popular view of brain evolution, which suggested that you have this reptilian core, like an inner lizard brain for instincts, and then wrapped around that, evolved, layered on top of that, evolved a limbic system in mammals. So the novelty was in a mammalian brain, which bestowed mammals with, gave them emotions, the capacity for emotions. And then on top of that, evolved a cerebral cortex, which in largely in primates, but very large in humans. And it's not that I personally disagree, it's that as far back as the 1960s, but really by the 1970s, it was shown pretty clearly with evidence from molecular genetics, so peering into cells in the brain to look at the molecular makeup of genes, that the brain did not evolve that way. And the irony is that the idea of the three-layered brain with an inner lizard that hijacks your behavior and causes you to do and say things that you would otherwise not, or maybe that you will regret later, that idea became very popular, was popularized by Carl Sagan in the Dragons of Eden, which won a Pulitzer Prize in 1977, when it was already known pretty much in evolutionary neuroscience that the whole narrative was a myth. So, well, the narrative is on the way it evolved, but do you, I mean, again, it's that problem of it being a useful tool of conversation to say like there's a lizard brain and there's a, like if I get overly emotional on Twitter, that was the lizard brain and so on, but do you? No, I don't think it's useful. I think it's, I think that. Is it useful, is it accurate? I don't think it's accurate, and therefore I don't think it's useful. So here's what I would say. You know, I think that the way I think about philosophy and science is that they are useful tools for living, and in order to be useful tools for living, they have to help you make good decisions. The triune brain, as it's called, this three-layer brain, the idea that your brain is like an already baked cake in the cortex, cerebral cortex, just layered on top like icing, the idea, that idea is the foundation of the law in most Western countries. It's the foundation of economic theory, and it large, and it's a great narrative. It sort of fits our intuitions about how we work, but it also, it's in addition to being wrong, it lets people off the hook for nasty behavior. And it also suggests that emotions can't be a source of wisdom, which they often are. In fact, you would not wanna be around someone who didn't have emotions. That would be, that's a psychopath. I mean, that's not someone you wanna really have that person deciding your outcome. So I guess my, and I could sort of go on and on and on, but my point is that I don't think, I don't think it's a useful narrative in the end. What's the more accurate view of the brain that we should use when we're thinking about it? I'll answer that in a second, but I'll say that even our notion of what an instinct is or what a reflex is, it's not quite right, right? So if you look at evidence from ecology, for example, and you look at animals in their ecological context, what you can see is that even things which are reflexes are very context-sensitive. The brains of those animals are executing so-called instinctual actions in a very, very context-sensitive way. And so even when a physician takes the, it's like the idea of your patellar reflex where they hit your patellar tendon on your knee and you kick, the force with which you kick and so on is influenced by all kinds of things. It's a reflex isn't like a robotic response. And so I think a better way is a way that, to think about how brains work, is the way that matches our best understanding, our best scientific understanding, which I think is really cool because it's really counterintuitive. So how I came to this view, and I'm certainly not the only one who holds this view, I was reading work on neuroanatomy and the view that I'm about to tell you was strongly suggested by that. And then I was reading work in signal processing, like by electrical engineering. And similarly, the work suggested that, the research suggested that the brain worked this way. And I'll just say that I was reading across multiple literatures and they were, who don't speak to each other, and they were all pointing in this direction. And so far, although some of the details are still up for grabs, the general gist I think is, I've not come across anything yet, which really violates, and I'm looking. And so the idea is something like this, it's very counterintuitive. So the way to describe it is to say that your brain doesn't react to things in the world. It's not, to us it feels like our eyes and our windows on the world. We see things, we hear things, we react to them. In psychology, we call this stimulus response. So your face, your voice is a stimulus to me. I receive input and then I react to it. And I might react very automatically, system one. But I also might execute some control where I maybe stop myself from saying something or doing something, and in a more reflective way, execute a different action. That's system two. The way the brain works though, is it's predicting all the time. It's constantly talking to itself, constantly talking to your body, and it's constantly predicting what's going on in the body and what's going on in the world, and making predictions, and the information from your body and from the world really confirm or correct those predictions. So fundamentally, the thing that the brain does most of the time is just predict, like talking to itself and predicting stuff about the world, not like this dumb thing that just senses and responds, senses and responds. Yeah, so the way to think about it is like this. You know, your brain is trapped in a dark, silent box. Yeah, that's very romantic of you. Which is your skull. And the only information that it receives from your body and from the world, right, is through the senses, through the sense organs, your eyes, your ears, and you have sensory data that comes from your body that you're largely unaware of to your brain, which we call interoceptive, as opposed to exteroceptive, which is the world around you. And, but your brain is receiving sense data continuously, which are the effect of some set of causes. Your brain doesn't know the cause of these sense data. It's only receiving the effects of those causes, which are the data themselves. And so your brain has to solve what philosophers call an inverse inference problem. How do you know, when you only receive the effects of something, how do you know what caused those effects? So when there's a flash of light or a change in air pressure or a tug somewhere in your body, how does your brain know what caused those events so that it knows what to do next to keep you alive and well? And the answer is that your brain has one other source of information available to it, which is your past experience. It can reconstitute in its wiring past experiences, and it can combine those past experiences in novel ways. And so we have lots of names for this in psychology. We call it memory, we call it perceptual inference, we call it simulation. It's also, we call it concepts or conceptual knowledge. We call it prediction. Basically, if we were to stop the world right now, stop time, your brain is in a state, and it's representing what it believes is going on in your body and in the world, and it's predicting what will happen next based on past experience, right? Probabilistically, what's most likely to happen. And it begins to prepare your action, and it begins to prepare your experience based, so it's anticipating the sense data it's going to receive. And then when those data come in, they either confirm that prediction and your action executes, because the plan's already been made, or there's some sense data that your brain didn't predict that's unexpected, and your brain takes it in, we say encodes it, we have a fancy name for that, we call it learning. Your brain learns, and it updates its storehouse of knowledge, which we call an internal model, and so that you can predict better next time. And it turns out that predicting and correcting, predicting and correcting, is a much more metabolically efficient way to run a system than constantly reacting all the time. Because if you're constantly reacting, it means you have no, you can't anticipate in any way what's gonna happen, and so the amount of uncertainty that you have to deal with is overwhelming to a nervous system. Metabolically costly, I like it. And so what is a reflex? A reflex is when your brain doesn't check against the sense data, that the potential cost to you is so great, maybe because your life is threatened, that your brain makes the prediction and executes the action without checking. Yeah, so but prediction's still at the core, that's a beautiful vision of the brain. I wonder, from almost an AI perspective, but just computationally, is the brain just mostly a prediction machine then? Like is the perception just a nice little feature added on top, like the integration of new perceptual information? I wonder how big of an impressive system is that relative to just the big predictor, model constructor? Well, I think that we can look to evolution for that, for one answer, which is that when you go back 550 million years, give or take, the world was populated by creatures, really ruled by creatures without brains. And that's a biological statement, not a political statement. Really ruled with creatures without. You're calling dinosaurs dumb? You're talking about like. Oh no, I'm not talking about dinosaurs, honey. I'm talking way back, further back than that. Really, there are these little creatures called amphioxus, which is the modern, it's a, or a lancet, that's the modern animal. But it's an animal that scientists believe is very similar to our common, the common ancestor that we share with invertebrates. Because, basically because of the tracing back the molecular genetics in cells. And that animal had no brain. It had some cells that would later turn into a brain, but in that animal, there's no brain. But that animal also had no head. And it had no eyes, and it had no ears, and it had really, really no senses, for the most part. It had very, very limited sense of touch. It had an eye spot for, not for seeing, but just for entraining to circadian rhythm to light and dark. And it had no hearing, it had a vestibular cell so that it could keep upright in the water. At the time, we're talking evolutionary scale here, so give or take some hundred million years or something. But at the time, what are the vertebrate, like when a backbone evolved and a brain evolved, a full brain, that was when a head evolved with sense organs, and when, that's when your viscera, like internal systems, evolved. So the answer, I would say, is that senses, motor neuroscientists, people who study the control of motor behavior, believe that senses evolved in the service of motor action. So the idea is that, what triggered the, what was the big evolutionary change, what was the big pressure that made it useful to have eyes and ears and a visual system and an auditory system and a brain, basically? And the answer that is commonly entertained right now is that it was predation. That when, at some point, an animal evolved that deliberately ate another animal, and this launched an arms race between predators and prey, and it became very useful to have senses. So these little amphiox, these little amphioxi don't really have, they don't have, they're not aware of their environment very much, really. And so being able to look up ahead and ask yourself, should I eat that or will it eat me, is a very useful thing. So the idea is that sense data is not there for consciousness it didn't evolve for the purposes of consciousness, it didn't evolve for the purposes of experiencing anything, it evolved to be in the service of motor control. However, maybe it's useful. This is why scientists sometimes avoid questions about why things evolved, this is what philosophers call this teleology. You might be able to say something about how things evolve, but not necessarily why. We don't really know the why. That's all speculation. But the why is kind of nice here. The interesting thing is that was the first element of social interaction is, am I gonna eat you or are you gonna eat me? And for that, it's useful to be able to see each other, sense each other. That's kind of fascinating that there was a time when life didn't eat each other. Or they did by accident, right? So an amphioxus, for example, will, it kind of like gyrates in the water and then it plants itself in the sand like a living blade of grass and then it just filters whatever comes into its mouth, right? So it is eating, but it's not actively hunting. And when the concentration of food decreases, the amphioxus can sense this and so it basically wriggles itself randomly to some other spot which probabilistically will have more food than wherever it is. So it's not really, it's not guiding its actions on the basis of, we would say there's no real intentional action in the traditional sense. Speaking of intentional action and if the brain, if prediction is indeed a core component of the brain, let me ask you a question that scientists also hate is about free will. So how does, do you think about free will much, how does that fit into this, into your view of the brain? Why does it feel like we make decisions in this world? This is a hard, we scientists hate this because it's a hard question. We don't know the answer to it. Have you taken a side? I think I have. Do we have free will? I think I have taken a side, but I don't put a lot of stock in my own intuitions or anybody's intuitions about the cause of things, right? One thing we know about the brain for sure is that the brain creates experiences for us. My brain creates experiences for me. Your brain creates experiences for you in a way that lures you to believe that those experiences actually reveals the way that it works, but it doesn't. So the. So you don't trust your own intuition about free will. Not really, not really. No, I mean, no, but I am also somewhat persuaded by, you know, I think Dan Dennett wrote at one point, like, you know, the philosopher Dan Dennett wrote at one point that it's, I can't say it as eloquently as him, but people obviously have free will. They are obviously making choices. So it's, you know, and so there is this observation that we're not robots and we can do some things like a little more sophisticated than an amphioxus. So here's what I would say. I would say that your predictions, your internal model that's running right now, right? That your ability to understand the sounds that I'm making and attach them to ideas is based on the fact that you have years of experience knowing what these sounds mean in a particular statistical pattern, right? I mean, that's how you can understand the words that are coming out of my. Mouth. Right. I think we did this once before too, didn't we? When we were. I don't know. I would have to access my memory module. I think when I was in your. The class thing? Yeah, I think we did it just like that actually. So bravo. Wow. Yeah. I have to go look back to the tape. Yeah. Anyways, the idea though is that your brain is using past experience and it can use past experience in, so it's remembering, but you're not consciously remembering. It's basically re-implementing prior experiences as a way of predicting what's gonna happen next. And it can do something called conceptual combination, which is it can take bits and pieces of the past and combine it in new ways. So you can experience and make sense of things that you've never encountered before because you've encountered something similar to them. And so a brain in a sense is not just, doesn't just contain information. It is information gaining, meaning it can create new information by this generative process. So in a sense you could say, well, that maybe that's a source of free will. But I think really where free will comes from or the kind of free will that I think is worth having a conversation about is involves cultivating experiences for yourself that change your internal model. When you were born and you were raised in a particular context, your brain wired itself to your surroundings, to your physical surroundings and also to your social surroundings. So you were handed an internal model basically. But when you grow up, the more control you have over where you are and what you do, you can cultivate new experiences for yourself. And those new experiences can change your internal model and you can actually practice those experiences in a way that makes them automatic, meaning it makes it easier for the brain, your brain to make them again. And I think that that is something like what you would call free will. You aren't responsible for the model that you were handed, that someone, your caregivers cultivated a model in your brain. You're not responsible for that model, but you are responsible for the one you have now. You can choose, you choose what you expose yourself to. You choose how you spend your time. Not everybody has choice over everything, but everybody has a little bit of choice. And so I think that is something that I think is arguably called free will. Yeah, there's like the ripple effects of the billions of decisions you make early on in life that are so great that even if it's not, even if it's like all deterministic, just the amount of possibilities that are created and then the focusing of those possibilities into a single trajectory, that somewhere within that, that's free will. Even if it's all deterministic, that might as well be just the number of choices that are possible and the fact that you just make one trajectory through those set of choices seems to be like something like there'll be called free will. But it's still kind of sad to think like there doesn't seem to be a place where there's magic in there, where it is all just a computer. Well, there's lots of magic, I would say, so far, because we don't really understand how all of this is exactly played out at a, I mean, scientists are working hard and disagree about some of the details under the hood of what I just described, but I think there's quite a bit of magic, actually. And also, there's also stochastic firing of, neurons don't, they're not purely digital in the sense that there is, there's also analog communication between neurons, not just digital, so it's not just with firing of axons. And some of that, there are other ways to communicate. And also, there's noise in the system, and the noise is there for a really good reason, and that is the more variability there is, the more potential there is for your brain to be able to be information-bearing. So basically, there are some animals that have clusters of cells, the only job is to inject noise into their neural patterns. So maybe noise is the source of free will. So you can think about stochasticity or noise as a source of free will, or you can think of conceptual combination as a source of free will. You can certainly think about cultivating, you can't reach back into your past and change your past. People try by psychotherapy and so on, but what you can do is change your present, which becomes your past. Right? So. Think about that sentence. So one way to think about it is that you're continuously, this is a colleague of mine, a friend of mine said, so what you're saying is that people are continually cultivating their past. And I was like, that's very poetic. Yes, you are continually cultivating your past as a means of controlling your future. So you think, yeah, I guess the construction of the mental model that you use for prediction ultimately contains within it your perception of the past, like the way you interpret the past, or even just the entirety of your narrative about the past. So you're constantly rewriting the story of your past. Oh boy. Yeah. That's one poetic and also just awe-inspiring. What about the other thing you talk about? You've mentioned about sensory perception as a thing that is just, you have to infer about the sources of the thing that you have perceived through your senses. So let me ask another ridiculous question. Is anything real at all? Like, how do we know it's real? How do we make sense of the fact that, just like you said, there's this brain sitting alone in the darkness trying to perceive the world? How do we know that the world is out there to be perceived? Yeah, so I don't think that you should be asking questions like that without passing a joint. Right, no, for sure. I actually did before this, so I apologize. Okay, no, well, that's okay. You apologize for not sharing, that's okay. So, I mean, here's what I would say. What I would say is that the reason why we can be pretty sure that there's a there there is that the structure of the information in the world, what we call statistical regularities in sights and sounds and so on, and the structure of the information that comes from your body, it's not random stuff. There's a structure to it. There's a spatial structure and a temporal structure, and that spatial and temporal structure wires your brain. So an infant brain is not a miniature adult brain. It's a brain that is waiting for wiring instructions from the world, and it must receive those wiring instructions to develop in a typical way. So, for example, when a newborn is born, when a newborn is born, when a baby is born, the baby can't see very well because the visual system in that baby's brain is not complete. The retina of your eye, which actually is part of your brain, has to be stimulated with photons of light. If it's not, the baby won't develop normally to be able to see in a neurotypical way. Same thing is true for hearing. The same thing is true, really, for all your senses. So the point is that the physical world, the sense data from the physical world, wires your brain so that you have an internal model of that world so that your brain can predict well to keep you alive and well and allow you to thrive. That's fascinating that the brain is waiting for a very specific kind of set of instructions from the world, like not the specific, but a very specific kind of instructions. So scientists call it expectable input. The brain needs some input in order to develop normally. As I say in the book, we have the kind of nature that requires nurture. We can't develop normally without sensory input from the world and from the body. And what's really interesting about humans and some other animals too, but really seriously in humans, is the input that we need is not just physical. It's also social. We, in order for a human infant to develop normally, that infant needs eye contact, touch. It needs certain types of smells. It needs to be cuddled. It needs, right, so without social input, that infant's brain will not wire itself in a neurotypical way. And again, I would say there are lots of cultural patterns of caring for an infant. It's not like the infant has to be cared for in one way. Whatever the social environment is for an infant, that it will be reflected in that infant's internal model. So we have lots of different cultures, lots of different ways of rearing children. And that's an advantage for our species, although we don't always experience it that way. That is an advantage for our species. But if you just feed and water a baby without all the extra social doodads, what you get is a profoundly impaired human. Yeah, but nevertheless, you're kind of saying that the physical reality has a consistent thing throughout that keeps feeding these set of sensory information that our brains are constructed for. But- Yeah, the cool thing though, is that if you change the consistency, if you change the statistical regularities, so prediction error, your brain can learn it. It's expensive for your brain to learn it. And it takes a while for the brain to get really automated with it. But you had a wonderful conversation with David Eagleman, who just published a book about this, and gave lots and lots of really very, very cool examples, some of which I actually discussed in How Emotions Were Made, but not obviously to the extent that he did in his book. It's a fascinating book, but it speaks to the point that your internal model is always under construction. And therefore, you always can modify your experience. I wonder what the limits are. Like, if we put it on Mars, or if we put it in virtual reality or if we sit at home during a pandemic and we spend most of our day on Twitter and TikTok, like, I wonder what were the breaking point, like the limitations of the brain's capacity to properly continue wiring itself. Well, I think what I would say is that there are different ways to specify your question, right? Like, one way to specify it would be the way that David phrases it, which is, can we create a new sense? Like, can we create a new sensory modality? How hard would that be? What are the limits in doing that? But another way to say it is, what happens to a brain when you remove some of those statistical regularities, right? Like, what happens to a brain, what happens to an adult brain when you remove some of the statistical patterns that were there and they're not there anymore? Are you talking about in the environment or in the actual, like, you remove eyesight, for example? Well, either way. I mean, basically, one way to limit the inputs to your brain are to stay home and protect yourself. Another way is to put someone in solitary confinement. Another way is to stick them in a nursing home. Another, well, not all nursing homes, but there are some, right? Which really are where people are somewhat impoverished in the interactions and the variety of sensory stimulation that they get. Another way is that you lose a sense, right? But the point is, I think, that the human brain really likes variety, to say it in a sort of Cartesian way. Variety is a good thing for a brain. And there are risks that you take when you restrict what you expose yourself to. Yeah, you know, there's all this talk of diversity. The brain loves it to the fullest definition and degree of diversity. Yeah, I mean, I would say the only thing, basically, human brains thrive on diversity. The only place where we seem to have difficulty with diversity is with each other. Yeah. Right? But who wants to eat the same food every day? You never would. Who wants to wear the same clothes every day? I mean, my husband, if you ask him to close his eyes, he won't be able to tell you what he's wearing. Yeah. He'll buy seven shirts of exactly the same style in different colors. But they are in different colors, right? It's not like he's wearing- How would you then explain my brain, which is terrified of choice, and therefore I wear the same thing every time? Well, you must be getting your diversity. Well, first of all, you are a fairly sharp dresser, so there is that. But you're getting some reinforcement for dressing the way that you do. But no, your brain must get diversity in- In other places. In other places. But I think we, you know, so the two most expensive things your brain can do metabolically speaking is move your body and learn something new. So novelty, that is diversity, right, comes at a cost, a metabolic cost, but it's a cost, it's an investment that gives returns. And in general, people vary in how much they like novelty, unexpected things. Some people really like it, some people really don't like it, and there's everybody in between. But in general, we don't eat the same thing every day. We don't usually do exactly the same thing in exactly the same order, in exactly the same place every day. The only place we have difficulty with diversity is in each other. And then we have considerable problems there, I would say, as a species. Let me ask, I don't know if you're familiar with Donald Hoffman's work about the questions of reality. What are your thoughts of the possibility that the very thing we've been talking about of the brain wiring itself from birth to a particular set of inputs is just a little slice of reality, that there is something much bigger out there that we humans, with our cognition, cognitive capabilities, is just not even perceiving? The thing we're perceiving is just a crappy, like Windows 95 interface onto a much bigger, richer set of complex physics that we're not even in touch with. Well, without getting too metaphysical about it, I think we know for sure. It doesn't have to be the crappy version of anything, but we definitely have a limited, we have a set of senses that are limited in very physical ways, and we're clearly not perceiving everything there is to perceive. That's clear. I mean, it's just, it's not that hard. We can't, without special, why do we invent scientific tools? It's so that we can overcome our senses and experience things that we couldn't otherwise, whether they are different parts of the visual spectrum, the light spectrum, or things that are too microscopically small for us to see, or too far away for us to see. So clearly, we're only getting a slice, and that slice, you know, the interesting or potentially sad thing about humans is that we, whatever we experience, we think there's a natural reason for experiencing it, and we think it's obvious and natural and that it must be this way, and that all the other stuff isn't important, and that's clearly not true. Many of the things that we think of as natural are anything but. They're certainly real, but we've created them. They certainly have very real impacts, but we've created those impacts, and we also know that there are many things outside of our awareness that have tremendous influence on what we experience and what we do. So there's no question that that's true. I mean, just it's, but the extent is how, really the question is how fantastical is it? Yeah, like what, you know, a lot of people ask me, am I allowed to say this? I think I'm allowed to say this. I've eaten shrooms a couple times, but I haven't gone the full, I'm talking to a few researchers in psychedelics. It's an interesting scientifically place. Like what is the portal you're entering when you take psychedelics? Or another way to ask is like dreams. What are- So let me tell you what I think, which is based on nothing. Like this is based on my, right? So I don't- Your intuition. It's based on my, I'm guessing now, based on what I do know, I would say. But I think that, well, think about what happens. So you're running, your brain's running this internal model, and it's all outside of your awareness. You see the, you feel the products, but you don't sense the, you have no awareness of the mechanics of it, right? It's going on all the time. And so one thing that's going on all the time that you're completely unaware of is that when your brain, your brain is basically asking itself, figuratively speaking, not literally, right? Like how is the sense, given the last time I was in this sensory array with this stuff going on in my body, and this chain of events which just occurred, what did I do next? What did I feel next? What did I see next? It doesn't come up with one answer. It comes up with a distribution of possible answers. And then there has to be some selection process. And so you have a network in your brain, a sub-network in your brain, a population of neurons that helps to choose. It's not, I'm not talking about a homunculus in your brain or anything silly like that. This is not the soul. It's not the center of yourself or anything like that. But there is a set of neurons that weighs the probabilities and helps to select or narrow the field, okay? And that network is working all the time. It's actually called the control network, the executive control network, or you can call it a frontoparietal because the regions of the brain that make it up are in the frontal lobe and the parietal lobe. There are also parts that belong to the subcortical parts of your brain. It doesn't really matter. The point is that there is this network, and it is working all the time. Whether or not you feel in control, whether or not you feel like you're expending effort doesn't really matter. It's on all the time, except when you sleep. When you sleep, it's a little bit relaxed. And so think about what's happening when you sleep. When you sleep, the external world recedes, the sense data from, so basically your model becomes a little bit, the tethers from the world are loosened. And this network, which is involved in maybe weeding out unrealistic things, is a little bit quiet. So your dreams are really your internal model that's unconstrained by the immediate world. Except, so you can do things that you can't do in real life in your dreams, right? You can fly. Like I, for example, when I fly on my back in a dream, I'm much faster than when I fly on my front. Don't ask me why, I don't know. When you're laying on your back in your dream. No, when I'm in my dream and flying in a dream, I am much faster flyer in the air. You fly often? Not often, but I- You talk about it like you, I don't think I've flown for many years. Well, you must try it. I've flown, I've fallen. That's scary. Yeah, but you're talking about like airplane. Yeah, I fly in my dreams. And I'm way faster, right? On your back. On my back, way faster. Now you can say, well, you know, you never flew in your life, right? It's conceptual combination. I mean, I've flown in an airplane and I've seen birds fly and I've watched movies of people flying. And I know Superman probably flies. I don't know if he flies faster on his back, but- He's, I've never seen- He's always flying on his front, right? But yeah, but anyways, my point is that, you know, all of this stuff really, all these experiences really become part of your internal model. The thing is that when you're asleep, your internal model is still being constrained by your body. Your brain's always attached to your body. It's always receiving sense data from your body. You're mostly never aware of it unless you run up the stairs or, you know, maybe you are ill in some way, but you're mostly not aware of it, which is a really good thing. Because if you were, you know, you'd never pay attention to anything outside your own skin ever again. Like right now, you seem like you're sitting there very calmly, but you have a virtual- Whole thing going on. Drama, right? It's like an opera going on inside your body. And so I think that one of the things that happens when people take psilocybin or take, you know, ketamine, for example, is that the tethers- Are completely removed. Are completely removed. Yeah. Yeah. That's fascinating. And that's why it's helpful to have a guide, right? Because the guide is giving you sense data to steer that internal model so that it doesn't go completely off the rails. Yeah, no, there's, again, that wiring to the other brain that's the guide is at least a tiny little tether. Exactly. Yeah. Let's talk about emotion a little bit if we could. Emotion comes up often, and I have never spoken with anybody who has a clarity about emotion from a biological and neuroscience perspective that you do. And I'm not sure I fully know how to, as I mentioned this way too much, but as somebody who was born in the Soviet Union and romanticizes basically everything, talks about love nonstop, emotion is a, I don't know what to make of it. I don't know what, so maybe let's just try to talk about it. I mean, from a neuroscience perspective, we talked about a little bit last time, your book covers it, how emotions are made, but what are some misconceptions we writers of poetry, we romanticizing humans have about emotion that we should move away from and move forward to think about emotion from both a scientific and an engineering perspective? Yeah, so there is a common view of emotion in the West. The caricature of that view is that we have an inner beast, right? Your limbic system, your inner lizard. We have an inner beast and that comes baked in to the brain at birth. So you've got circuits for angers, sadness, fear. It's interesting that they all have English names, these circuits are, but and they're there and they're triggered by things in the world and then they cause you to do and say, and so when your fear circuit is triggered, you widen your eyes, you gasp, your heart rate goes up, you prepare to flee or to freeze. And these are modal responses. They're not the only responses that you give, but on average, they're the prototypical responses. That's the view. And that's the view of emotion in the law. That's the view that emotions are these profoundly unhelpful things that are obligatory kind of like reflexes. The problem with that view is that it doesn't comport to the evidence and it doesn't really matter. The evidence actually lines up beautifully with each other. It just doesn't line up with that view and it doesn't matter whether you're measuring people's faces, facial movements, or you're measuring their body movements, or you're measuring their peripheral physiology, or you're measuring their brains or their voices or whatever. Pick any output that you wanna measure and any system you wanna measure, and you don't really find strong evidence for this. And I say this as somebody who not only has reviewed really thousands of articles and run big meta-analyses, which are statistical summaries of published papers, but also as someone who has sent teams of researchers to small-scale cultures, remote cultures, which are very different from urban large-scale cultures like ours. And one culture that we visited, and I say we euphemistically because I myself didn't go because I only had two research permits and I gave them to my students because I felt like it was better for them to have that experience and more formative for them to have that experience. But I was in contact with them every day by satellite phone. And this was to visit the Hadza hunter-gatherers in Tanzania who are not an ancient people, they're a modern culture, but they live in circumstances, hunting and foraging, circumstances that are very similar, in similar conditions to our ancestors, hunting-gathering ancestors, when expressions of emotion were supposed to have evolved, at least by one view of, okay. So, for many years, I was sort of struggling with this set of observations, right? Which is that I feel emotion and I perceive emotion in other people, but scientists can't find a single marker, a single biomarker, not a single individual measure or pattern of measures that can predict how someone, what kind of emotional state they're in. How could that possibly be? How can you possibly make sense of those two things? And through a lot of reading and a lot of, and immersing myself in different literatures, I came to the hypothesis that the brain is constructing these instances out of more basic ingredients. So, when I tell you that the brain, when I suggest to you that what your brain is doing is making a prediction and it's asking itself, figuratively speaking, the last time I was in this situation in this physical state, what did I do next? What did I see next? What did I hear next? It's basically asking what in my past is similar to the present? Things which are similar to one another are called a category. A group of things which are similar to one another is a category. And a mental representation of a category is a concept. So, your brain is constructing categories or concepts on the fly continuously. So, you really wanna understand what a brain is doing. You don't, using machine learning like classification models is not gonna help you because the brain doesn't classify. It's doing category construction. And the categories change, or you could say it's doing concept construction. It's using past experience to conjure a concept which is a prediction. And if it's using past experiences of emotion, then it's constructing an emotion concept. Your concept will be, the content of it is changes depending on the situation that you're in. So, for example, if your brain uses past experiences of anger that you have learned, either because somebody labeled them for you, taught them to you, you observed them in movies and so on, in one situation could be very different from your concept for anger than another situation. And this is how anger, instances of anger, are what we call a population of variable instances. Sometimes when you're angry, you scowl. Sometimes when you're angry, you might smile. Sometimes when you're angry, you might cry. Sometimes your heart rate will go up, it will go down, it will stay the same. It depends on what action you're about to take. Because the way prediction, and I should say, the idea that physiology is yoked to action is a very old idea in the study of the peripheral nervous system. It's been known for really decades. And so, if you look at what the brain is doing, if you just look at the anatomy, and here's the hypothesis that you would come up with, and I can go into the details. I've published these details in scientific papers, and they also appear somewhat in How Emotions Are Made, my first book. They are not in the seven and a half lessons, because that book is really not pitched at that level of explanation. It's really just a set of little essays. But the evidence, but what I'm about to say is actually based on scientific evidence. When your brain begins to form a prediction, the first thing it's doing is it's making a prediction of how to change the internal systems of your body, your heart, your cardiovascular system, the control of your heart, control of your lungs, a flush of cortisol, which is not a stress hormone. It's a hormone that gets glucose into your bloodstream very fast, because your brain is predicting you need to do something metabolically expensive. And so, that means either move or learn. And so, your brain is preparing your body, the internal systems of your body, to execute some actions, to move in some way. And then it infers based on those motor predictions and what we call viscera motor predictions, meaning the changes in the viscera that your brain is preparing to execute. So, your brain makes an inference about what you will sense based on those motor movements. So, your experience of the world and your experience of your own body are a consequence of those predictions, those concepts. When your brain makes a concept for emotion, it's constructing an instance of that emotion. And that is how emotions are made. And those concepts load in. The predictions that are made include contents inside the body, contents outside the body. I mean, it includes other humans. So, just this construction of a concept includes the variables that are much richer than just some sort of simple notion. Yeah, so our colloquial notion of a concept where I say, well, what's a concept of a bird? And then you list a set of features off to me. That's people's understanding, typically, of what a concept is. But if you go into the literature in cognitive science, what you'll see is that the way that scientists have understood what a concept is has really changed over the years. So, people used to think about a concept as philosophers and scientists used to think about a concept as a dictionary definition for a category. So, there's a set of things which are similar out in the world. And your concept for that category is a dictionary definition of the features, the necessary and sufficient features of those instances. So, for a bird, it would be? Wings, feathers. A beak, it flies, whatever, okay. That's called the classical category. And scientists discovered, observed, that actually not all instances of birds have feathers and not all instances of birds fly. And so, the idea was that you don't have a single representation of necessary and sufficient features stored in your brain somewhere. Instead, what you have is a prototype. A prototype meaning you still have a single representation for the category, one, but the features are like of the most typical instance of the category or maybe the most frequent instance, but not all instances of the category have all the features, right? They have some graded similarity to the prototype. And then, what I'm gonna like incredibly simplify now, a lot of work to say that then a series of experiments were done to show that in fact, what your brain seems to be doing is coming up with a single exemplar or instance of the category and reading off the features when I ask you for the concept. So, if we were in a pet store and I asked you, what are the features of a bird? Tell me the concept of bird. You would be more likely to give me features of a good pet. And if we were in a restaurant, you would be more likely, like a budgie, right? Or a canary. If we were in a restaurant, you would be more likely to give me the features of a bird that you would eat, like a chicken. And if we were in a park, you'd be more likely to give me, in this country, the features of a sparrow or a robin. Whereas if we were in South America, you would probably give me the features of a peacock because that's more common or it is more common there than here that you would see a peacock in such circumstances. So, the idea was that really what your brain was doing was conjuring a concept on the fly that meets the function that the category is being put to. Okay? Okay. Then, people started studying ad hoc concepts, meaning concepts that, where the instances don't share any physical features, but the function of the instances are the same. So, for example, think about all the things that can protect you from the rain. What are all the things that can protect you from the rain? Umbrella, like this apartment. Right. Your car. Not giving a damn. Like a mindset. Yeah, right, right. So, the idea is that the function of the instances is the same in a given situation, even if they look different, sound different, smell different, this is called an abstract concept or a conceptual concept. Now, the really cool thing about conceptual categories or conceptual, yes, conceptual category, a conceptual, as a category of things that are held together by a function, which is called an abstract concept or a conceptual category, because the things don't share physical features, they share functional features. There are two really cool things about this. One is that's what Darwin said a species was. So, Darwin is known for discovering natural selection. But the other thing he really did, which was really profound, which he's less celebrated for, is understanding that all biological categories have inherent variation, inherent variation. Darwin wrote in The Origin of Species about before Darwin's book, a species was thought to be a classical category, where all the instances of dogs were the same, had the exactly same features, and any variation from that perfect platonic instance was considered to be error. And Darwin said, no, it's not error, it's meaningful. Nature selects on the basis of that variation. The reason why natural selection is powerful and can exist is because there is variation in a species. And in dogs, we talk about that variation in terms of the size of the dog and the amount of fur the dog has and the color and how long is the tail and how long is the snout. In humans, we talk about that variation in all kinds of ways, right, including in cultural ways. So, that's one thing that's really interesting about conceptual categories is that Darwin is basically saying a species is a conceptual category. And in fact, if you look at modern debates about what is a species, you can't find anybody agreeing on what the criteria are for a species because they don't all share the same genome. We don't all share, we don't. There isn't a single human genome. There's a population of genomes, but they're variable. It's not unbounded variation, but they are variable, right? And the other thing that's really cool about conceptual categories is that they are the categories that we use to make civilization. So, think about money, for example. What are all the physical things that make something a currency? Is there any physical feature that all the currencies in all the worlds that's ever been used by humans share? Well, certainly, right, but what is it? Is it definable? So, it's getting to the point that you make it a function. It's the function, right? It's that we trade it for material goods. And we have to agree, right? We all impose on whatever it is, salt, barley, little shells, big rocks in the ocean that can't move, Bitcoin, pieces of plastic, mortgages, which are basically a promise of something in the future, nothing more, right? All of these things, we impose value on them. And we all agree that we can exchange them for material goods. Yeah, and yes, that's brilliant. By the way, you're attributing some of that to Darwin, that he thought? No, I'm saying that what Darwin did. Because that's a brilliant view of what a species is, is the function. Yeah, what I'm saying is that what Darwin, Darwin really talked about variation in, so if you read, for example, the biologist Ernst Mayr, who was an evolutionary biologist, and then when he retired, became a historian and philosopher of biology. And his suggestion is that Darwin, Darwin did talk about variation. He vanquished what's called essentialism, the idea that there's a single set of features that define any species. And out of that grew really discussions of the, like some of the functional features that species have, like they can reproduce, they can have offspring, the individuals of a species can have offspring. It turns out that's not a perfect, that's not a perfect criterion to use, but it's a functional criterion, right? So what I'm saying is that in cognitive science, people came up with the idea, they discovered the idea of conceptual categories or ad hoc concepts, these concepts that can change based on the function they're serving, right? And that it's there, it's in Darwin, and it's also in the philosophy of social reality. The way that philosophers talk about social reality, just look around you. I mean, we impose, we're treating a bunch of things as similar, which are physically different. And sometimes we take things that are physically the same, and we treat them as separate categories. But it feels like the number of variables involved in that kind of categorization is nearly infinite. No, I don't think so, because there is a physical constraint, right? Like you and I could agree that we can fly in real life, but we can't. That's a physical constraint that we can't break, right? You and I could agree that we could walk through the walls, but we can't. We could agree that we could eat glass, but we can't. Oh, there's a lot of constraints, but I just- Yeah, we could agree that the virus doesn't exist, and we don't have to wear masks. Right, yeah. But physical reality still holds the trump card, right? But still, there's a lot of- The trump card, well, pun unintended. A pun completely unintended, but there you go. That's a predicting brain for you. But there's a tremendous amount of leeway. Yes. Yeah, that's the point. So what I'm saying is that emotions are like money. Basically, they're like money, they're like countries, they're like kings and queens and presidents. They're like everything that we construct that we impose meaning on. We take these physical signals, and we give them meanings that they don't otherwise have by their physical nature. And because we agree, they have that function. But the beautiful thing, so maybe unlike money, I love this similarity is, it's not obvious to me that this kind of emergent agreement should happen with emotion, because our experiences are so different for each of us humans, and yet we kind of converge. Well, in a culture, we converge, but not across cultures. There are huge, huge differences. There are huge differences in what concepts exist, what they look like. So what I would say is that- They feel like. What we're doing with our young children as their brains become wired to their physical and their social environment, right, is that we are curating for them, we are bootstrapping into their brains a set of emotion concepts. That's partly what they're learning. And we curate those for infants, just the way we curate for them, what is a dog, what is a cat, what is a truck? We sometimes explicitly label, and we sometimes just use mental words. When your kid is throwing Cheerios on the floor instead of eating them, or your kid is crying when she won't put herself to sleep or whatever. We use mental words, and a word is this, words for infants, words are these really special things that they help infants learn, abstract categories. There's a huge literature showing that children can take things that don't look infants, like infants, really young infants, pre-verbal infants, can take, if you label, if I say to you, and you're an infant, okay, so I say Lex, Lexie, this is a bling, and I put it down, and the bling makes a squeaky noise. And then I say, Lexie, this is a bling, and I put it down, and it makes a squeaky noise. And then I say, Lexie, this is a bling. You, as young as four months old, will expect this to make a noise, a squeaky noise. And if you don't, if it doesn't, you'll be surprised because it violated your expectation, right? I'm building for you an internal model of a bling. Okay, infants can do this really, really at a young age, and so there's no reason to believe that they couldn't learn emotion categories and concepts in the same way. And what happens when you go to a new culture? When you go to a new culture, you have to do what's called emotion acculturation. So my colleague, Batia Mesquita in Belgium studies emotion acculturation. She studies how when people move from one culture to another, how do they learn the emotion concepts of that culture? How do they learn to make sense of their own internal sensations, and also the movements, you know, the raise of an eyebrow, the tilt of a head? How do they learn to make sense of cues from other people using concepts they don't have, but have to make on the fly? So there's the difference between cultures. Let me open another door. I'm not sure I wanna open, but difference between men and women. Is there a difference between the emotional lives of those two categories of biological systems? So here's what I would say. You know, we did a series of studies in the 1990s where we asked men and women to tell us about their emotional lives. And women described themselves as much more emotional than men. They believed that they were more emotional than men, and men agreed. Women are much more emotional than men. Okay, and then we gave them little handheld computers. These were little Hewlett-Packard computers. They fit in the palm of your hand. Couple of pounds, they weighed a couple of pounds. So this was like pre-palm pilot even. Like this was, you know, 1990s, like early. And we asked them, we would, you know, ping them like 10 times a day, and just ask them to report how they were feeling, which is called experience sampling. So we experience sampled. And then at the end, and then we looked at their reports, and what we found is that men and women basically didn't differ. And there were some people who were really, had many more instances of emotion. So they were, you know, they were treading water in a tumultuous sea of emotion. And then there were other people who were like floating tranquilly, you know, in a lake. It was really not perturbed very often, and everyone in between. But there were no difference between men and women. And the really interesting thing is at the end of the sampling period, we asked people, so reflect over the past two weeks and tell it. So, you know, we've been now pinging people like again and again and again, right? So tell us how emotional do you think you are? No change from the beginning. So men and women believe that they are, they believe that they are different. And when they are looking at other people, they make different inferences about emotion. If a man, if a man is scowling, like if you and I were together, and so somebody's watching this, okay? And yeah, hey, who am I saying, hey, hi, yeah, hi. By the way, people love it when you look at the camera. If you and I make exactly the same set of facial movements, when people look at you, both men and women look at you, they are more likely to think, oh, he's reacting to the situation. And when they look at me, they'll say, oh, she's having an emotion, she's, you know, yeah. And I wrote about this actually right before the 2016 election. You know, maybe I could confess. Let me try to carefully confess. But you are really gonna. Yeah, that when I, that there is an element when I see Hillary Clinton, that there was something annoying about her to me. And I, just that feeling, and then I tried to reduce that to what is that? Because I think the same attributes that are annoying about her, when I see in other people, wouldn't be annoying. So I was trying to understand what is it? Because it certainly does feel like that concept that I've constructed in my mind. Well, I'll tell you that I think, well, let me just say that what you would predict about, for example, the performance of the two of them in the debates, and I wrote an op-ed for the New York Times actually before the second debate. And it played out really pretty much as I thought that it would, based on research. It's not like I'm a great fortune teller or anything. It's just I was just applying the research, which was that when a woman, a woman's, people make internal attributions, it's called. They infer that the facial movements and body posture and vocalizations of a woman reflect her inner state. But for a man, they're more likely to assume that they reflect his response to the situation. It doesn't say anything about him. It says something about the situation he's in. That's brilliant. For the thing that you were describing about Hillary Clinton, I think a lot of people experienced, but it's also in line with research, which shows, and particularly research actually about teaching evaluations is one place that you really see it, where the expectation is that a woman will be nurturant, and that a man, there's just no expectation for him to be nurturant. So if he is nurturant, he gets points. If he's not, he gets points. They're just different points, right? Whereas for a woman, especially a woman who's an authority figure, she's really in a catch-22. Because if she's serious, she's a bitch, and if she's empathic, then she's weak. Right, that's brilliant. I mean, one of the bigger questions to ask here, so that's one example where our construction of concepts gets us in trouble. But remember I said science and philosophy are like tools for living. So I learned recently that if you ask me what is my intuition about what regulates my eating, I will say carbohydrates. I love carbohydrates. I love pasta. I love bread. I just love carbohydrates. But actually, research shows, and it's beautiful research. I love this research because it so violates my own like deeply, deeply held beliefs about myself, that most animals on this planet who have been studied, and there are many, actually eat to regulate their protein intake. So you will overeat carbohydrates if you, in order to get enough protein. And this research has been done with human, very beautiful research, with humans, with crickets, with like bonobos, I mean, just like all these different animals, not bonobos, but I think like baboons. Now, I have no intuition about that, and I, even now as I regulate my eating, I still, I just have no intuition. It just, I can't feel it. What I feel is only about the carbohydrates. It feels like you're regulating around carbohydrates, not the protein. Yeah, but in fact, actually, what I am doing, if I am like most animals on the planet, I am regulating around protein. So knowing this, what do I do? I correct my behavior to eat, to actually deliberately try to focus on the protein. This is the idea behind bias training, right? Like if you, I also did not experience Hillary Clinton as the warmest candidate. However, you can use consistent science, since the consistent scientific findings to organize your behavior. That doesn't mean that rationality is the absence of emotion because sometimes emotion or feelings in general, not the same thing as emotion. That's another topic. But are a source of information and their wisdom and helpful. So I'm not saying that, but what I am saying is that if you have a deeply held belief and the evidence shows that you're wrong, then you're wrong. It doesn't really matter how confident you feel. That confidence could be also explained by science, right? So it would be the same thing as if I, regardless of whether someone is a, like Charlie Baker, right? Regardless of whether somebody is a Republican or a Democrat, if that person has a record that you can see is consistent with what you believe, then that is information that you can act on. Yeah, and then so try to, I mean, this is kind of what empathy is and open-mindedness is. Try to consider that the set of concepts that your brain has constructed through which you are now perceiving the world is not painting the full picture. I mean, this is now true for basically every, it doesn't have to be men and women. It could be basically the prism through which we perceive actually the political discourse, right? Absolutely. So here's what I would say. You know, there are people who, scientists who will talk to you about cognitive empathy and emotional empathy. And I prefer to think of it, I think the evidence is more consistent with what I'm about to say, which is that your brain is always making predictions using your own past experience and what you've learned from books and movies and other people telling you about their experiences and so on. And if your brain cannot make a concept to make sense of those, anticipate what those sense data are and make sense of them, you will be experientially blind. So, you know, when I'm giving lectures to people, I'll show them like a blobby black and white image and they're experientially blind to the image. They can't see anything in it. And then I show them a photograph and then I show them the image again, the blobby image, and then they see actually an object in it. But the image is the same. It's there, they're actually adding, their predictions now are adding, right? Or anyone who's- It's a beautiful example. Anybody who's learned a language, a second language after their first language also has this experience of things that initially sound like sounds that they can't quite make sense of eventually come to make, they eventually come to make sense of them. And in fact, there are really cool examples of people who were like born blind because they have cataracts or they have corneal damage so that no light is reaching the brain. And then they have an operation and then light reaches the brain and they can't see. For days and weeks and sometimes years, they are experientially blind to certain things. So what happens with empathy, right? Is that your brain is making a prediction. And if it doesn't have the capacity to make, if you don't share, if you're not similar, remember, I mean, you know, categories are instances which are similar in some way. If you are not similar enough to that person, you will have a hard time making a prediction about what they feel. You will be experientially blind to what they feel. In the United States, children of color are under prescribed medicine by their physicians. This is been documented. It's not that the physicians are racist necessarily, but they might be experientially blind. The same thing is true of male physicians with female patients. I could tell you some hair-raising stories, really, where people die as a consequence of a physician making the wrong inference, the wrong prediction, because of being experientially blind. So we are, you know, empathy is not, it's not magic. It's, we make inferences about each other, about what each other's feeling and thinking. In this culture, more than, and there are some cultures where, you know, people have what's called opacity of mind, where they will make a prediction about someone else's actions, but they're not inferring anything about the internal state of that person. But in our culture, we're constantly making inferences. What is this person thinking? What is, and we're not doing it necessarily consciously, but we're just doing it really automatically using our predictions, what we know. And if you expose yourself to information, which is very different from somebody else, I mean, really what we have is, we have different cultures in this country right now that are, there are a number of reasons for this. I mean, part of it is, I don't know if you saw the social dilemma, the Netflix. Heard about it. Yeah, it's a great, it's really great documentary. About what social networks are doing to our society? Yeah, yeah. But you know, nothing, no phenomenon has a simple single cause. There are multiple small causes which all add up to a perfect storm. That's just how most things work. And so the fact that machine learning algorithms are serving people up information on social media that is consistent with what they've already viewed and making, is part of the reason that you have these silos, but it's not the only reason why you have these silos. I think there are other things afoot that enhance people's inability to even have a decent conversation. Yeah, I mean, okay, so many things you said are just brilliant. So the experiment, experiential blindness, but also from my perspective, like I preach and I try to practice empathy a lot. And something about the way you've explained it makes me almost see as a kind of exercise that we should all do, like to train, like to add experiences to the brain to expand this capacity to predict more effectively. Absolutely. So like what I do is kind of like a method acting thing, which is I imagine what the life of a person is like. You know, just think, I mean, this is something you see with Black Lives Matter and police officers. It feels like they're both, not both, but because of martial arts and so on, I have a lot of friends who are cops. They don't necessarily have empathy or visualize the experience of the other. Certainly, currently, unfortunately, people aren't doing that with police officers. They're not imagining, they're not empathizing or putting themselves in the shoes of a police officer to realize how difficult that job is, how dangerous it is, how difficult it is to maintain calm under so much uncertainty, all those kind of things. You know, but there's more, that's all that's true, but I think that there's even more to be said there. I mean, like from a predicting brain standpoint, there's even more that can be said there. So I don't know if you want to go down that path or you want to stick on empathy, but I will also say that one of the things that I was most gratified by, I still am receiving, it's been more than three and a half years since How Motions Are Made came out, and I'm still receiving daily emails from people, right? So that's gratifying, but one of the most gratifying emails I received was from a police officer in Texas who told me that he thought that How Motions Are Made contained information that would be really helpful to resolving some of these difficulties. And he hadn't even read my op-ed piece about when is a gun not a gun, and using what we know about the science of perception from a prediction standpoint, like the brain is a predictor, to understand a little differently what might be happening in these circumstances. So there's a real, what's hard about, it's hard to talk about because everyone gets mad at you when you talk about this. Like, you know, and there is a way to understand this which has profound empathy for the suffering of people of color, and that definitely is in line with Black Lives Matter, at the same time as understanding the really difficult situation that police officers find themselves in. And I'm not talking about this bad apple or that bad apple. I'm not talking about police officers who are necessarily shooting people in the back as they run away. I'm talking about the cases of really good, well-meaning cops who have the kind of predicting brain that everybody else has. They're in a really difficult situation that I think both they and the people who are harmed don't realize. Like, the way that these situations are constructed, I think it's just, there's a lot to be said there, I guess, is what I want to say. Is there something we can try to say, in a sense, like what I'm, from the perspective of the predictive brain, which is a fascinating perspective to take on this, you know, all the protests that are going on there seems to be a concept of a police officer being built. No, I think that concept is there. But it's gaining strength. So it's being re, I mean, Yeah, it is. For sure. But I think, yeah, for sure, I think that that's right. I think that there's a shift in the stereotype of what I would say is a stereotype. There's a stereotype of a black man in this country that's always in movies and television, not always, but like largely, that many people watch. I mean, you know, you think you're watching a 10 o'clock drama and all you're doing is like kicking back and relaxing, but actually you're having certain predictions reinforced and others not. And what's happening, what's happening now with police is the same thing, that there are certain stereotypes of a police officer that are being abandoned and other stereotypes that are being reinforced by what you see happening. All I'll say is that if you remember, I mean, there's a lot to say about this, really, that, you know, regardless of whether it makes people mad or not, I mean, I just, the science is what it is. Yeah. Just remember what I said. The brain makes predictions about internal changes in the body first and then motor, it starts to prepare motor action, and then it makes a prediction about what you will see and hear and feel based on those actions. Okay? So it's also the case that we didn't talk about, is that sensory sampling, like your brain's ability to sample what's out there, is yoked to your heart rate. It's yoked to your heartbeats. There are certain phases of the heartbeat where it's easier for you to see what's happening in the world than in others. And so if your heart rate goes through the roof, you will be more likely to just go with your prediction and not correct based on what's out there because you're actually literally not seeing as well. Or you will see things that aren't there, basically. Is there something that we could say by way of advice for when this episode is released in the chaos of emotion, sorry, I don't know a better term, that's just flying around on social media? What's... Well, I actually think it is emotion in the following sense. It sounds a little bit artificial in the way that I'm about to say it, but I really think that this is what's happening. One thing we haven't talked about is brains evolved, didn't evolve for you to see, they didn't evolve for you to hear, they didn't evolve for you to feel, they evolved to control your body. That's why you have a brain. You have a brain so that it can control your body. And the metaphor, the scientific term for predictively controlling your body is allostasis. Your brain is attempting to anticipate the needs of your body and meet those needs before they arise so that you can act as you need to act. And the metaphor that I use is a body budget. Your brain is running a budget for your body. It's not budgeting money, it's budgeting glucose and salt and water. And instead of having one or two bank accounts, it has gazillions. There are all these systems in your body that have to be kept in balance. And it's monitoring very closely. It's making predictions about like when is it good to spend and when is it good to save and what would be a good investment and am I going to get a return on my investment? Whenever people talk about reward or reward prediction error or anything to do with reward or punishment, they're talking about the body budget. They're talking about your brain's predictions about whether or not there will be a deposit or withdrawal. So when you, when your brain is running a deficit in your body budgets, you have some kind of metabolic imbalance, you experience that as discomfort. You experience that as distress. When your brain, when things are chaotic, you can't predict what's going to happen next. So I have this absolutely brilliant scientist working in my lab. His name is Jordan Theriault and he's published this really terrific paper on a sense of should. Like why do we have social rules? Why do we adhere to social norms? It's because if I make myself predictable to you, then you are predictable to me. And if you're predictable to me, that's good because that is less metabolically expensive for me. Novelty or unpredictability at the extreme is expensive. And if it goes on for long enough, what happens is first of all, you will feel really jittery and antsy, which we describe as anxiety. It isn't necessarily anxiety. It could be just something is not predictable and you are experiencing arousal because the chemicals that help you learn increase your feeling of arousal basically. But if it goes on for long enough, you will become depleted and you will start to feel really, really, really distressed. So what we have is a culture full of people right now who are their body budgets are just decimated and there's a tremendous amount of uncertainty. When you talk about it as depression, anxiety, it makes you think that it's not about your metabolism, that it's not about your body budgeting, that it's not about getting enough sleep or about eating well or about making sure that you have social connections. You think that it's something separate from that. But depression and anxiety are just a way of being in the world. They're a way of being in the world when things aren't quite right with your predictions. That's such a deep way of thinking. The brain is maintaining homeostasis. It's actually allostasis. Allostasis, I'm sorry. And it's constantly making predictions and metabolically speaking, it's very costly to make novel, like constantly be learning to making adjustments. And then over time, there's a cost to be paid if you're just in a place of chaos where there's constant need for adjusting and learning and experience novel things. And so part of the problem here, there are a couple of things. Like I said, it's a perfect storm. There isn't a single cause. There are multiple cause, multiple things that combine together. It's a complex system, multiple things. Part of it is that people are, they're metabolically encumbered and they're distressed. And in order to try to have empathy for someone who is very much unlike you, you have to forage for information. You have to explore information that is novel to you and unexpected. And that's expensive. And at a time when people feel, what do you do when you are running a deficit in your bank account? You stop spending. What does it mean for a brain to stop spending? A brain stops moving very much, stops moving the body, and it stops learning. It just goes with its internal model. Brilliantly put, yeah. So empathy requires, to have empathy for someone who is unlike you requires learning and practice. You're foraging for information. I mean, it is something I talk about in the book in Seven and a Half Lessons about the Brain. I think it's really important. It's hard, but it's hard. I think it's, you know, it's hard for people to have, to be curious about views that are unlike their own when they feel so encumbered. And I'll just tell you, I had this epiphany really. I was listening to Robert Reich's The System. He was talking about oligarchy versus democracy. So oligarchy is where very wealthy people, like extremely wealthy people, shift power so that they become even more wealthy and even more insulated from the, you know, the pressures of the common person. It's actually the kind of system that leads to the collapse of civilizations, if you believe Jared Diamond. Just say that. But anyways, I'm listening to this, and I'm listening to him describe in fairly decent detail how the CEOs of these companies, there's been a shift in what it means to be a CEO and not being, no longer being a steward of the community and so on. But like in the 1980s, it sort of shifted to this other model of being like an oligarch. And he's talking about how, you know, it used to be the case that CEOs made like 20 times what their employees made. And now they make about 300 times on average what their employees made. So where did that money come from? It came from the pockets of the employees. And they don't know about it, right? No one knows about it. They just know they can't feed their children. They can't pay for healthcare. They can't take care of their family. And they worry about what's going to happen to their, you know, they're living like, you know, months a month, basically. Any one big bill could completely, you know, put them out on the street. So there are a huge number of people living like this. So all they, with their experience, they don't know why they're experiencing it. So it's, and then someone comes along and gives them a narrative. Yeah. Well, somebody else butted in line in front of you. And that's why you're this way. That's why you experience what you're experiencing. And just for a minute, I was thinking, I had deep empathy for people who have beliefs that are really, really, really different from mine. But I was trying really hard to see it through their eyes. And did it cost me something metabolically? I'm sure. I'm sure. But you had something in the gas tank. Well, I. In order to allocate that. I mean, that's the question is like, where did you, what resources did your brain draw on in order to actually make that effort? Well, I'll tell you something, honestly, Lex. I don't have that much in the gas tank right now. Right? So I am surfing the stress that, you know, stress is just, what is stress? Stress is your brain is preparing for a big metabolic outlay and it just keeps preparing and preparing and preparing and preparing. You as a professor, you as a human. Both, right? For me, this is a moment of existential crisis as much as anybody else, democracy, all of these things. So in many of my roles, so I guess what I'm trying to say is that I get up every morning and I exercise. I run, I row, I lift weights, right? You exercise in the middle of the day. I saw your like, you know, daily thing. I'm obsessed with it. Yeah. I hate it, actually. You love it, right? You get a. No, I hate it. I hate it, but I do it religiously. Yeah. Why? Because it's a really good investment. It's an expenditure that is a really good investment. And so when I was exercising, I was listening to the book and when I realized the insights that I was sort of like playing around with, like, is this, does this make sense? Does this make sense? I didn't immediately plunge into it. I basically wrote some stuff down. I set it aside and then I did what I, I prepared myself to make an expenditure. I don't know what you do before you exercise. I always have a protein shake, always have a protein shake, because I need to fuel up before I make this really big expenditure. And so I did the same thing. I didn't have a protein drink, but I did the same thing. And fueling up can mean lots of different things. It can mean talking to a friend about it. It can mean, you know, it can mean making sure you get a good night's sleep before you do it. It can mean lots of different things. But I guess I think we have to do these things. Yeah. I'm going to re-listen to this conversation several times. This is brilliant. But I do think about, you know, I've encountered so many people that can't possibly imagine that a good human being can vote for Donald Trump. And I've also encountered people that can't imagine that an intelligent person can possibly vote for a Democrat. And I look at both these people, many of whom are friends, and let's just say after this conversation, I can see as they're predicting brains not willing to invest the resources to empathize with the other side. And I think you have to in order to be able to like see the obvious common humanity in us. I don't know what the system is that's creating this division. We can put it, like you said, it's a perfect storm. It might be the social media. I don't know what the hell it is. I think it's a bunch of things. I think it's there's an economic system which is disadvantaging large numbers of people. There's a use of social media. Like if I had to orchestrate or architect a system that would screw up a human body budget, it would be the one that we live in. We don't sleep enough. We eat pseudo food basically. We are on social media too much, which is full of ambiguity, which is really hard for a human nervous system, right? Really, really hard. Like ambiguity with no context to predict in. I mean, it's like really. And then there are the economic concerns that affect large swaths of people in this country. I mean, it's really I'm not saying everything is reducible to metabolism. Not everything is reducible to metabolism, but if you combine all these things together. It's helpful to think of it that way. Somehow it reduces the entirety of the human experience, the same kind of obvious logic. Like we should exercise every day in the same kind of way we should empathize every day. Yeah. You know, there are these really wonderful, wonderful programs for teens and also for parents of people who've lost children in wars and in conflicts, in political conflicts where they go to a bucolic setting and they talk to each other about their experiences. And miraculous things happen, you know? So, you know, it's easy to sort of shrug this stuff off as kind of Pollyanna-ish, you know, like what's this really going to do? But you have to think about when my daughter went to college, I gave her advice. I said, try to be around people who let you be the kind of person you want to be. Right. We're back to free will. You have a choice. You have a choice. It might seem like a really hard choice. It might seem like an unimaginably difficult choice. You have a choice. Do you want to be somebody who is wrapped in fury and agony, or do you want to be somebody who extends a little empathy to somebody else and in the process maybe learn something? Curiosity is the thing that protects you. Curiosity is the thing. It's curative curiosity. On social media, the thing I recommend to people, at least that's the way I've been approaching social media. It doesn't seem to be the common approach, but I basically give love to people who seem to also give love to others. It's the same similar concept of surrounding yourself by the people you want to become. And I ignore, sometimes block, but just ignore. I don't add aggression to people who are just constantly full of aggression and negativity and toxicity. There's a certain desire when somebody says something mean to say something, to say why or try to alleviate the meanness and so on. But what you're doing essentially is you're now surrounding yourself by that group of folks that have that negativity. So even just the conversation. I think it's just so powerful to put yourself amongst people whose basic mode of interaction is kindness. Because I don't know what it is, but maybe it's the way I'm built, is that to me is energizing for the gas tank that then I can pull to when I start reading The Rise and Fall of the Third Reich and start thinking about Nazi Germany. I can empathize with everybody involved. I can start to make these difficult thinking that's required to understand our little planet Earth. Well, there is research to back up what you said. There's research that's consistent with your intuition there. There's research that shows that being kind to other people, doing something nice for someone else is like making a deposit to some extent. Because I think making a deposit not only in their body budgets but also in yours. Like people feel good when they do good things for other people. We are social animals. We regulate each other's nervous systems for better and for worse. The best thing for a human nervous system is another human. And the worst thing for a human nervous system is another human. So you decide. Do you want to be somebody who makes people feel better or do you want to be somebody who causes people pain? We are more responsible for one another than we might like or than we might want. But remember what we said about social reality. Social reality. There are lots of different cultural norms about independence or collective nature of people. But the fact is we have socially dependent nervous systems. We evolved that way as a species. And in this country, we prize individual rights and freedoms. And that is a dilemma that we have to grapple with. And we have to do it in a way, if we're going to be productive about it, we have to do it in a way that requires engaging with each other, which is what I understand the founding members of this country intended. Beautifully put. Let me ask a few final silly questions. So one, we've talked a bit about love, but it's fun to ask somebody like you who can effectively, from at least neuroscience perspective, disassemble some of these romantic notions. What do you make of romantic love? Why do human beings seem to fall in love, at least a bunch of 80s hair bands have written about it? Is that a nice feature to have? Is that a bug? What is it? Well, I'm really happy that I fell in love. I wouldn't want it any other way. But I would say – Is that you, the person speaking, or the neuroscientist? Well, that's me, the person speaking. But I would say, as a neuroscientist, babies are born not able to regulate their own body budgets because their brains aren't fully wired yet. When you feed a baby, when you cuddle a baby, everything you do with a baby impacts that baby's body budget and helps to wire that baby's brain to manage, eventually, her own body budget to some extent. That's the basis, biologically, of attachment. Humans evolved as a species to be socially dependent, meaning you cannot manage your body budget on your own without a tax that, eventually, you pay many years later in terms of some metabolic illness. Loneliness, when you break up with someone that you love or you lose them, you feel like it's going to kill you, but it doesn't. But loneliness will kill you. It will kill you approximately, what is it, seven years earlier? I can't remember exactly the exact number. It's actually in the Webnotes, too, seven and a half lessons. But social isolation and loneliness will kill you earlier than you would otherwise die. And the reason why is that you didn't evolve to manage your nervous system on your own. And when you do, you pay a little tax, and that tax accrues very slightly over time, over a long period of time, so that by the time you're middle-aged or a little older, you are more likely to die sooner from some metabolic illness, from heart disease, from diabetes, from depression. You're more likely to develop Alzheimer's disease. I mean, it takes a long time for that tax to accrue, but it does. So, yes, I think it's a good thing for people to fall in love. But I think the funny view of it is that it's clear that humans need the social attachment to manage their nervous system, as you're describing. And the reason you want to stay with somebody for a long time is so you don't have the novelties very costly for- Well, now you're mixing things. Now you have to decide whether- But what I would say is when you lose someone you love, it feels like you've lost a part of you, and that's because you have. You've lost someone who was contributing to your body budget. We are the caretakers of one another's nervous systems, like it or not, and out of that comes very deep feelings of attachment, some of which are romantic love. Are you afraid of your own mortality, we two humans sitting here? Yeah. Do you ponder your own mortality? I mean, somebody who thinks about your brain a lot, it seems one of the more terrifying or, I don't know, I don't know how to feel about it, but it seems to be one of the most definitive aspects of life is that it ends. It's a complicated answer, but I think the best I can do in a short snippet would be to say for a very long time I did not fear my own mortality. I feared pain and suffering, so that's what I feared. I feared being harmed or dying in a way that would be painful, but I didn't fear having my life be over. Now, as a mother, I think I have fear. I fear dying before my daughter is ready to be without me. That's what I fear. That's really what I fear. And frankly, honestly, I fear my husband dying before me much more than I fear my own death. There's that love and social attachment again. Yeah, because I know it's just going to, I'm going to feel like I wish I was dead. A final question about life. What do you think is the meaning of it all? What's the meaning of life? I think that there isn't one meaning of life. There's many meanings of life, and you use different ones on different days. But for me, I would say sometimes the meaning of life is to understand, to make meaning, actually. The meaning of life is to make meaning. Sometimes it's that. Sometimes it's to leave the world just slightly a little bit better, like the Johnny Appleseed view. Sometimes the meaning of life is to clear the path for my daughter or for my students. So sometimes it's that. And sometimes it's just, you know, you ever have moments where you're looking at the sky or you're by the ocean? Sometimes for me it's even like I'll see a weed poking out of a crack in a sidewalk. And you just have this overwhelming sense of the wonder of the world. Like the world is just like the physical world is so wondrous, and you just get very immersed in the moment, like the sensation of the moment. Sometimes that's the meaning of life. I don't think there's one meaning of life. I think it's a population of instances, just like any other category. I don't think there's a better way to end it, Lisa. The first time we spoke is, I think, if not the, then one of... I think it's the first conversation I had that basically launched this podcast. Yeah, that's actually the first conversation I had that launched this podcast. Oh, wow. And now we get to finally do it the right way. It's a huge honor to talk to you, that you spent time with me. I can't wait for hopefully the many more books you'll write. Certainly can't wait to... I already read this book, but I can't wait to listen to it because as you said offline that you're reading it, and I think you have a great voice. You have a great, I don't know what's a nice way to put it, but maybe NPR voice. Thank you. In the best version of what that is. Thank you. Thanks again for talking to me. My pleasure. Thank you so much for having me back. Thank you for listening to this conversation with Lisa Feldman Barrett, and thank you to our sponsors, Athletic Greens, which is an all-in-one nutritional drink, Magic Spoon, which is a low-carb, keto-friendly cereal, and Cash App, which is an app for sending money to your friends. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter, Alex Friedman. And now let me leave you with some words from Lisa Feldman Barrett. It takes more than one human brain to create a human mind. Thank you for listening. I hope to see you next time.

https://youtu.be/NbdRIVCBqNI

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Thoughts on Joe Rogan's New Texas Studio | Lex Fridman

A couple of days ago, I got a chance to do the Joe Rogan experience for the fifth time, but first time in the new Texas studio. I also got a chance to interview him afterwards for the podcast that I host and ask him all the usual philosophical, over-romanticized Russian questions that I usually do on the podcast. A bunch of people messaged me asking, so how's the new studio? So instead of responding to everybody individually, I thought I'd make this video to give my thoughts on the new Joe Rogan Austin, Texas studio. There's a few quick points I want to make, but overall, TLDR is, I love it. So first let me say from the perspective of a guest and what the studio actually looks like in real life, I think it looks great in real life, and I believe it's an improvement over the previous studio in several ways. So one, the previous studio actually has a lot of extra space that feels useless, and there's something about removing that space that makes the studio feel more intimate. I definitely felt like I was pulled into the conversation more. Like if we take somebody like Larry King from CNN, check him out, look into it, is he has this like creepy closeness to the guests. I think this new studio actually strikes a really nice balance. To me, that's interesting as a podcaster, and that's something I talked to Joe with, is how do you create an atmosphere where you just forget that the rest of the world exists and you lose yourself in the conversation where you're really focused in on listening and thinking about what the other person is saying. Another small thing that I think is actually really cool from a guest perspective is there's only now one big TV versus two TVs. So when you're looking at something in the previous studio, one chimp was looking at one TV and the other chimp was looking at the other TV. And if you know anything about chimps or dogs or humans, there's a powerful signaling thing with our eyes when we're both looking at the same thing. There's like a more of a bond to it when we're looking at the same thing, same object, or like same image on the TV. So it's just a nicer experience to be able to look at the same thing together and then look back. And also from a camera perspective, you can see what everyone is looking at, whether it's two people or three people or four people. So I personally love it. Now, from the perspective of what the video actually looks like, that goes into lighting, camera positions, also the texture of the background. So when the camera is doing the autofocusing or adjusting of the lights, it does a good job, all of that. Now to comment on that part, I want to say how amazing Jamie is. For people who don't know, Jamie Varner is the, I guess, producer of the Joe Rogan Experience, but he also does a million other things. He's just the creative mind of his own, a photographer, just a creator of all kinds. Now me, again, as a podcaster, I do many of the things that Jamie does, but I do it much worse. So I get to really appreciate the quality of his work. So much of the setup, the wires, the configuration of the audio and the video and the management of that, the switching of the cameras, the ability to Google, all of that comes together as a vision and implementation by Jamie. And so this new studio, from a video and audio engineering perspective, is very much a creation of Jamie. And I'm telling you now, he's done a masterful job and is quickly improving. So just like he did with a previous studio to be constantly, quickly improving until it got to that level there everybody got used to, he's doing the same thing here. I guarantee you'll be at a stellar level very quickly. The previous times on the show, I knew how good he was, but this time I actually got a chance to chat with him offline about some of the details of all the stuff he's doing. And it just took my respect for him to another level. And hopefully I'll convince him, he kind of said yes, to come on the podcast so we can talk about some of the genius behind young Jamie. And also I want to say that to me as a podcaster and an aspiring young Jamie myself, it was really nice to see how humble and self-critical he is, given all the success of the show, given everything that's been done, given so few screw-ups, so few imperfections, given the level at which he's able to with one hand be a solo producer of an entire video podcast where he's switching the cameras and with another hand be able to Google at a moment's notice. Given all that, he's extremely self-critical, extremely humble. That's just inspiring to me because it echoes to the way I see the world as well. So it gives me hope that if I continue seeing the world that way, I'll be able to eventually figure out how to do this podcasting and engineering thing the right way. So for whatever it's worth, I love it. The video will keep improving. And I think just like the Cybertruck, which will likely be manufactured in the same city of Austin, Texas, I think people will eventually see it not as ugly as they did at first, but as badass. And also, as I mentioned to him on the show, if Spotify is better than YouTube in terms of music, I hope that next time I take a ride in that spaceship, I'd love to do a cover of Voodoo Child by Jimi Hendrix. All right, check out the conversation with Joe. Should come out next week. Hopefully I didn't say anything ridiculous, but I probably did. Love you all. I'll see you next time.

https://youtu.be/iw1obNGEt5E

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Josh Barnett: Philosophy of Violence, Power, and the Martial Arts | Lex Fridman #165

The following is a conversation with Josh Barnett, one of the greatest fighters and submission wrestlers in history, with an epic 25-year career that includes being the UFC heavyweight champion and countless other accolades. He also happens to be one of the most intelligent and brutally honest human beings in all of martial arts, and especially so about his appreciation of and fascination with violence. Quick mention of our sponsors, which feels ridiculous to say after that introduction. Munk Pack Low Carb Snacks, Element Electrolyte Drinks, Eight Sleep Self-Cooling Mattress, and Rev Transcription and Captioning Service. Click the sponsor links to get a discount to support this podcast. As a side note, let me say that I've been a fan of Josh Barnett for a long time. This conversation was indeed a long time coming, and I'm sure we'll talk many times again. For what it's worth, I'm a student of combat sports and admire when they're done at the highest level, either through masterful execution of skill or relentless dominance of pure guts. For context, I'm a black belt in jiu-jitsu and have competed in wrestling, submission grappling, jiu-jitsu, judo, and even catch wrestling, which is a variant of submission grappling that Josh is one of the great practitioners, scholars, and teachers of. I could probably talk for hours about what I've learned from my time on the mat, but if I were to say one thing, it is that the mat is honest. You can't run away from yourself when you step on the mat. It reveals your fears, the lies you might tell yourself, all the delusions you might have, or at least I had, that there's anything in this world that can be achieved except through blood, sweat, and tears. That honesty, taken to the highest levels, as is the case with Josh, creates the most special of human beings and definitely someone who is fascinating to talk to. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Josh Barnett. Who were the philosophers and philosophical ideas that influenced you the most? Are we just jumping right in? That's it. We're right in, into the deepest. No foreplay on camera, all right. I had an interesting philosophical journey, at least I think it's interesting, and that was, I think, as far as organized philosophy or maybe, authentic's not the right word, but like, yeah, we'll say organized. I would say that Nietzsche is probably one of the people with the most influence on me, but I also feel like, to a degree, your personality will oftentimes dictate what philosophers that you can vibe with. So what ideas from Nietzsche was it, the Übermensch? Definitely the Übermensch is huge to me because I see it as an extension of, basically, the religious concepts of God and higher ideals, but just put into a different, a secular context. And the idea also that the Übermensch is striving and overcoming something that you're always working towards that very few will ever, it's not like the concept that you can just make them, it doesn't happen that way. And it's not based simply upon if you were, say, put through a genetic program and turned into a super soldier, that wouldn't make it. That's the very surface level and incorrect understanding of what the Übermensch is. The Übermensch is the idea of this kind of human that transcends all the weaker, lower aspects of humans, which we're full of. But I also think that there's an element in Nietzsche's writing that suggests that it's not something you can even be in all the time. Like, it's even a temporary state because it's not something that we're capable of maintaining. It's something to strive for, like a morality, an image, an ideal, a set of principles that we can connect to that doesn't rely on otherworldly, kind of out there things. It's deeply human. With Nietzsche, I feel like the concept of the Übermensch is something built on authenticity as well. Heidegger was like Dasein, right? So when you are authentic, and Heidegger being a follower of Nietzsche's and highly influenced by him, I think that the Übermensch is an example of authenticity in that it isn't about trying to be anything that you cannot be or to go against who you are, but to actually understand that, accept that, and then work with what you can work with and create from your lump of clay that is you. Because I can't become, there's certain things that are just not gonna happen for me because it's not in my proclivity. I mean, I'm never gonna be five foot tall and 120 pounds. I mean, that again, I guess. But I know, as you get more in tune with who you are, as you start learning more about what unique things, or at least what that combination that makes you, that gestalt part of yourself, what those things are and how you can use them, then you can work towards being that, taking what that is and seeing if you can get to that point. Now, the likelihood is no, maybe, probably never. I mean, but we can never achieve godhood, yet religion is a constant striving and a look at a higher ideal concept, even if it's multiple gods or one god. It's still essentially all built around this concept. Like, I like the idea of Catholics' original sin, if you think of sin not as evil, but as missing the mark, the archer's term where it derives, or even like in Spanish, without. So as being, if you accept that you are imperfect, if you accept that you need to constantly strive even against yourself, because you will figure out the best ways at which to submarine your own capabilities, submarine your own dreams and wishes and whatever, you will ruin them more than anything else. And you will tell yourself that you ruined them on purpose, for a good reason, or you'll say that you'll figure out a way to put it on everything else but yourself. And so the idea of thinking of, well, as I'm starting off on this whole thing, I got a lot of work to do, and that's just the way it is. And I gotta figure out what areas those are gonna be. And so, I thought, oh yeah, if I think of original sin actually can be, that can be kind of a clever idea, but it's also just accepting that we're all uniquely strange and unequal in our own ways, but we have to figure out how that fits in. The word authenticity kind of connects to all of that. So striving to be your authentic self means figuring out exactly the shape of the flaws, the character of your little demons that you get to play with, and around them finding a path to whatever the hell ideal versions of yourself you can carve, and pretending like that's such a thing as even possible. The other idea about Nietzsche is, on his idea of morality, he presents the argument that morality's a human illusion, and that there's not such a thing as good and evil, and these are all kind of constructs. Do you think there's such a thing as good and evil that's connected to some objective reality? I think that there are some, I actually do believe that there are some universals. I'm not Kantian in any way, but I do think that there are some universals. And the thing that actually brought me to even the concept of that was Jung. So Jung's concept of the collective unconsciousness, and then taking that thought and then applying it to looking through history, and the most varied history you can find. So I would say probably religion is your earliest one that you can get for written history, or written examples of human behavior and psychology at the furthest that we can look into it, from man's hand to whatever the medium is, cuneiform or whatever. But as you do that, and then let's say going from Mesopotamia to India to Europe, and just going from all these places, as disparate as they may seem, as many different cultures and ethnicities and religions, and how the religions will vary quite a bit from monotheist to polytheist, and so on and so forth. But then just seeing how there's all the through lines. And of course, Campbell, he did this much earlier than me thinking about it. But I think that by looking at things that way and starting to find the threads, instead of always just looking at everything as being its own compartmentalized concept, is if it only applies to this time, as people getting overly pomo about it is just a really idiotic postmodern. So you think that there is, just like with Joseph Campbell, there's a thread that connects all of these stories, narratives that we constructed for ourselves as we evolve, and that thread is grounded in some kind of absolute ideas of maybe on the morality side, which is the trickiest one, of good and evil. Somewhat, yeah. I think that a lot of this stuff is just derived from a biological perspective. I feel like these things are innate within us. Do you think our innately humans are good? Like we- No, I don't. I feel like, I also feel like there's an issue of scale too. Like Nassim Taleb likes to talk about how he views his, the way he interacts with groups in terms of scale. What is this thing about like at the familial level, I'm a communist, and then at the civic level, I'm a Republican or something, and at this other level, and then it goes on, at the widest level, he's a libertarian or something of that nature. Like fundamentally, human interaction changes- On scale. On scale. And scale, and also from subjective to the environment around them. So, and I don't even mean environment just in the sake of physical environment, nature, right? Like nature's constantly trying to murder you. Well, it's not really trying, it's just, nature's being nature. The universe is the universe, and at times it takes you out. It's just not with any particular compunction or prejudice, it's just, oops, you know, sorry, there's no more dodo's. My bad. But don't you think the particular flavor of the complexity that is the human mind was created, like, let me make an argument for, that all people are fundamentally good. Okay. Is there's an evolutionary advantage to striving to cooperate, to add more love to the world, of like compassion, empathy, all that kind of stuff, and that the very thing that created the human mind was this evolutionary advantage, whatever the forces behind this evolutionary advantage. And scale, yes. So, when we're dealing with a small tribe, sure. When you meet another tribe, maybe. There's other factors that are going into that. Let's say you scale up, and so your 150 has exceeded their 150, and you start to get to a certain point where you can't really be close enough to someone down the line of that next, like that 150's 150, 150, and they just now all of a sudden become some guy, whatever. And when it comes to some guy, once it starts hitting scale, I don't know that it's capable. People can be as magnanimous to a stranger as to the known, if they orient themselves to be secure enough, because it does come to security, insecurity, in one way or the other, either brought on by the unknown, brought on by an actual threat, brought on by even their own, as we would use the word insecurity, in that their own insecurity within their own capabilities, their own belief in themselves, all these things can change things from being compassionate and what have you, to at least at the very least, maybe not evil, but self-interest driven to the point of negative results for those that aren't. You know what I mean? Right. But another way to frame that is, maybe it's less about scale and more about the amount of resources available. So if we're overflowing with resources in terms of security and safety, all the things you've mentioned, if we have more than enough resources, then the way we treat a stranger, the way we position ourselves towards that stranger might be in a way that allows us to be our real human selves as opposed to sort of our animal self. And therefore, it's mostly about how clever can we descendants of Apes be in coming up with all cool kinds of technologies and ways to efficiently use the resources we have such that we're not constrained. And my hope is that we can, that human innovation will outpace the growth of our, the number of people that are starving for resources. Yes. I think that there's a lot of rationality behind this argument. And in some ways I agree. And in a lot of ways I see it as missing the point of how this experiment has been playing out across time. When you look at what, for one, it's like define resources. You know, what is a resource of, as humans would define it, right? Or wealth even. And so you can say, well, you know, an iPhone's a resource, the internet's a resource, water obviously is a resource, but if we weigh them, what is more important to human beings? Water, internet, or iPhones? It's water, right? So if we look at resources, if we start with what do human beings need to live? I mean, actually live. Not live here in this bullshit fantasy creation extension of our own ingenuity and a prison of our own creation and also a paradise of our own creation. But this is not how human beings normally live. This is all built upon stuff on, this is built on concept, on idea, and some of it's built on just, well, this is the paradigm, so this is what you do. Human beings need food, they need water to survive. They need shelter from the elements. And they need certain skills to perpetuate these things and be able to pass them down so that they can, so that these things don't become, you don't end up in this gap where you have to relearn things. Because if it's lost, then that time before you can get it back again is going to be dark ages of sorts, or it's going to be highly detrimental to your group. Because not knowing how to fish, not knowing how to hunt, not knowing how to even clean and cook the game once you have it could be lethal. That's fascinating to think of that as a basic resource, the knowledge to attain the very low level things of water and fish. Right, and we'll figure it out. We did it once before, and we've done it over and over and over and over again. It's just costly. Yes, it has costs, for sure. But when you think of how you look at the, we'll just deal with the first world of the West. You look at the pathway of Western civilization and its growth, and then you look at how technology injected into it over time, how it magnifies things, or pushes things at orders of magnitude faster. And then the internet comes along, and even faster. So you're watching industrial revolution to, what is it, the capacitor, and then so on, it goes further and further. And as the internet and technology, especially on the electronic side of things, start increasing in capability, it massively outpaces even our necessity for it at times. It becomes, plant obsolescence happens quicker and over and over and over again. And wealth increases, increases, increases, increases in terms of the things that we're able to acquire. I've seen homeless people with smartphones. So we're living in the most wealth-laden, luxury-laden age of all of humanity, yet what happens when we see calamity or people go on hard times? The things that they value, what if people go to an argument about the cost of things that are luxury items generally, and not necessity items? We get into fights about things that are, at the end of the day, not necessities to us. People are so concerned about Netflix and the internet. Personally, I'm very concerned about the internet because I look at it as my own little personal library of Alexandria in my pocket. That's what I love about it. And the ability to have a tool as effective as it is, even though I'm in a constant battle, to not let that tool become a vice or to become something that actually brings me to a lower state. But the question is, are we willing to murder each other over Netflix versus murder each other over water? We're willing to murder each other over water. That's a given. Right, but that's our animalistic selves of, that's- Well, it's also a necessity for, it's animalistic, but it's also either you do it or you don't, right? Like, unless somebody's willing to share that water or if that water is of such a limited capability or such a limited amount, then you will have to murder to have that water. But over Netflix, the argument is the higher we get up to this hierarchy of what we consider in Los Angeles resources, we're less willing to commit violence. We're less willing to commit violence, I would say, over Netflix. But we are willing to commit violence over Netflix, over everything associated with Netflix, over televisions, over sneakers, over, I mean, when we look at a good, I mean, the majority of the stuff that came with the riots, I mean, it was used car dealerships, targets. I mean, and then you look and it's like, well, okay, what are people, what do they gotta, what are they so hell-bent to get out of this whole thing? I'm even talking about the ideological elements or anything like that. Just like, okay, something's going on, boom, looting, whatever. What are you gonna loot? You'll have AOC say, oh, people needing bread. I didn't see a single loaf of bread. I saw televisions and shoes. It's poetry, Josh. But to me, it is poetry in a sense because you get to see how we actually are operating. What is becoming first principles to most people. But you could also argue that those riots were more like the madness of crowds, which is like. It's definitely a lot more than just that. I'm just saying that given a chance, it's like, okay, boom. The lights are off, the grid is down. We've hacked into the whole system. Turned into an 80s movie. And you have the ability to go get ahold of whatever it is that you think is most important. And what do we do? And I say we, as in, including all of us, we grab a TV. We attack it. We break into a sneaker store in Melrose. We do, it's just like, we steal giant cause statues where the value of that is completely market driven. Like it's just a piece of polypropylene or whatever, butyl. And it's cool. I'm a big fan of art, but it's like, I can't eat that. And at the end of the day, man, you're sitting there with your, like, what'd you do today, honey? What'd you get? Oh man, we were able to, oh, I got this designer art statue. Are you gonna go, well, you can't really sell it on the art markets where people are really gonna pay for it. So are you gonna become an underground art dealer with your one piece of cause art? One interesting thing, before I forget it, you mentioned the Library of Alexandria and your. Phone. Well, your phone, but also just thinking of your little world that you're creating for yourself on the internet. That's a really powerful way to actually phrase it. One of the things that, you've been on Joe Rogan several times. Although everybody always comes to me and goes, oh, that was so great. I didn't know, you've been on Joe Rogan? I go, this is like my fifth time, dude. I've been a fan of yours for a long time from other avenues. This is a long time coming, actually. Everybody, you have no idea how many times through messaging and missing each other over the years, this is ridiculous, this is a long time coming. You don't realize how special this is for us. This is, well, I'm also starstruck. We'll talk about this, but you symbolize something very important to me through my journey, through wrestling, through jujitsu, through judo, through just street fighting, through just combat. You're the, in some sense, the devil on my shoulder of violence. Devil gets a bad rap. He does get a bad rap. I realize, sitting encased in ice down at that low-ass level. Yeah. But the angel side is more like the athletic, the sport, the science, the technical, the chess side of things. But on the Library of Alexandria, let me ask, because you were on Joe Rogan, it does make me really sad, and I realize that I'm just probably being romantic, that most of his library of interviews that were on YouTube have now been taken down because he went to Spotify. And that was the first, I'm probably an idiot, but it was the first time I realized that this knowledge that we've been building up on the internet doesn't necessarily last forever. No, it doesn't, unless you preserve it. I mean, it's like all things. If you do not preserve them, if you do not make efforts, so many of my, it just really brings to mind right off the top of my head, so many friends of mine that are Jewish, they're basically secular. But yet, through even the secular aspect of just keeping the traditions alive, it's like, well, you could always pick a book and read about it, clearly. It's called the Torah. But if you don't put these things into action, if you don't make them a part of your consciousness, maybe even subconsciousness, just through repetition, they will die. They will become simply something that exists somewhere until you find it again. And Carl Gottsch used to say something. He would say that I don't invent moves, I just rediscover them. But yet, Gottsch and Billy Robinson also would understand that if someone's not carrying the torch, it'll go out. Now, that doesn't mean fire can't be rekindled. It just means that that torch no longer is lighting the way on this knowledge. And so it's important to be an individual, even on an individual level, to be a repository for aspects of knowledge. You mentioned Gottsch. You consider yourself a catch wrestler. So I've mentioned to you offline that I competed in a couple of catch wrestling tournaments. Can we go Wikipedia level at the very basic, you're the exactly right person to ask, what is catch wrestling? And what are its defining principles? I would say the easiest way for us to talk about and give an overview of what catch is, in the simplest terms, is think of collegiate wrestling with submissions. That is essentially what catch is. And it's not surprising because collegiate wrestling is actually derived from catch as catch can. It's just that over time, certain aspects were removed from the competition structure so that they became null elements, things that were discarded. But it's funny that you can take a high level amateur collegiate types and you can show them a move and then add a little bit to it and go, oh, well, hey, that was just like what we already do here, but except, oh, I didn't know you could take it all the way to this point, or things of that nature, especially when it comes to professional wrestling, like teaching people, like, no, I know you're just using this in a show, but this is actually a real move and here's how it really feels. And so collegiate wrestling and wrestling in general for people who are not aware is basically two people start on their feet and they have to score, they're trying to take each other down and they have to, they score points along the way. You can end matches by pinning them, for example, on their back. I think one way to describe wrestling is it's very much about figuring out ways to establish control and leverage in these kind of tie-ups, or there's different styles where you can do more from a distance to where it's more about the timing and all that kind of stuff. Ultimately, it's an art of like both upper body and lower body and you could choose the different puzzles you solve there. You could be attacking the head, the arms, you could be attacking the legs. There's also part of collegiate wrestling that's on the ground that has more, what's called like a referee's position or whatever. The referee's position where you're on your hands and knees, basically, and so. Do you understand what that's supposed to simulate? Why is that one of the standard positions? It's one of the standard positions because, one, it's one of the easiest ways to actually get up, but two, it's because you cannot be on your back. If you're on your back, you're getting pinned. And back exposure or being pinned is pretty much the universal wrestling thing. One, taking the guy from their feet to the floor, and two, pinning them. As you go from like, what is it, Cornish wrestling, Turkish oil wrestling, Mongolian, Sumo, Indian, well, they'll call it Pelwani. It's also called Kushti, Jiu-Jitsu, Judo. So many of them is, there's a, Isombo, even if it doesn't end the match, it's still like one of the most important aspects of the competition itself across every style. And this is where submission, like catch wrestling, or submission wrestling, or Jiu-Jitsu feels different. Which it seems like for most wrestling, for a lot of wrestling, the dominance is the goal, as opposed to submission, which I guess those two are related, but dominating the position. So that's what pinning is. It's almost like breaking your opponent, like breaking through all of their defenses to where they're completely defenseless, and you can do anything with them that you want. Maybe that's a Wikipedia definition of dominance, I don't know. And then. Yeah, I mean, it sounds very much like a chain to a radiator, yeah. Yeah. Yeah, there's a thread that connects all partners. But submission feels different. I mean. It is actually different when you think about it across the landscape. I don't think radically different, but still slightly different, in that if you think of wrestling as being derived from combat, right? So, well, it is combat sports, but more lethal combat. Getting somebody off their feet and onto their back is about as lethal a place for the person on bottom to be, in general. I mean, don't come at me with your talks about your fucking Worm Guards, and blah, blah, blah, and whatever spider, barren, okay, get out of here with that. We're not talking about you in this highly regimented sporting environment. We're talking about general, all the body hair, none of the waxing human beings. So, getting someone on their back, okay. As you're trying to get up, you're getting hit with a rock, or stabbed, or what have you, set on fire, who knows. Generally, these conflicts are not just isolated to one-on-one. If it's four-on-two, your buddy that was with you back-to-back, now he's on his back. What do you think? Now it's gonna be one-on-one, while three go on one. And then you go, you elevate this to armored combat, right? And it's boom, put him on the ground. Oh, crap, it's hard to get up. Well, while you're struggling to get up, stab. That's where jiu-jitsu's concepts come from, with all their leveraging and off-balancing, is oh, man, if I end up in this situation in tight, close-quarters combat, yes, we could fight it out with swords and knives and what have you, but it's way easier if the first thing I can do is foot-sweep you on your back and then pull my knife and just go, stick. Is there a thread that connects all of these different arts from not just arts, but from the very base violence of war, just like you said, that there's no rules, to the very regimented IBJF jiu-jitsu tournaments? You've kind of laid out some of it, but can you go all the way to the? So, when you start off with absolute skills in the sense of absolute offense and defense in the taking or preserving of life, full-on at its purest form of self-defense and self-preservation, and then you extrapolate part of that in that all animals train in violence. All play usually degenerates into some sort of soft violence so be it cats when they're kittens and puppies and everything learns how to kill, how to fight. Not that, just that dumb alpha meme stuff where the idea is that, oh, by being alpha, that means you run around basically just being a bully and a shithead, no, actually, alpha wolves spend very little time fighting because if you were actually alpha, you don't get into fights, there's no need to. And if you're probably getting into any large amount of fights, it's probably because you're being shitty at being an alpha and now people are tired of you being in charge. And yet, in the animal world, and it would be the same for human beings at that base beginning level of violence, there's a big risk. So, I know that we live in this place with healthcare and or you might be in a place with nationalized health, whatever, right? There's Band-Aids, there's penicillin, there's all that kind of stuff. But that's not the normal way of things. There's a channel that just hurts me every time. I used to follow and I had to unfollow it because it was too painful for me as a human being called Nature is Metal on Instagram. It was sobering and then it was like, this is too sober. I have to. It's very sobering. So, in there, the risk is at its highest level. The damage you take, the winner walks away hurt. Getting lamed when you need every aspect of your physical and athletic faculties to survive because is it gonna be the, this isn't the first and it's definitely not gonna be the last, especially if you're the slowest one. What is it? There's a lyric from a Clutch song. Don't go for the fat ones, just go for the slow ones. Oh man, but that universal truth of the way nature works. It's not cruel, it's just the way it is. Yeah, I mean, watch animals get into fights on any of these sort of documentary stuff. You'll see an intense, short and then dispersal. Like you'll see as soon as one feels like, oh, things have switched just enough, boom, the bear or whatever it is takes off. It's like, I'm not, I'm done with this. Because if you can get out of there with just some scars and what have you, okay. You lose an eye, nah, it's not as good. You really get hurt bad and get infected, you're done. So, there's a serious risk to be, that can come with these sort of things. Yet, I believe that we are inherently born for at least aspects of use of violence. And so, at the end of the day, we need these things not just to survive each other, but they're a part of being able to hunt and other things. So, violence is a part of human nature. Violence is an absolute. It is in every person, it is a part of every interaction, it is a part of every law, everything. And I'm not, by the way, I'm not an ANCAP, so don't even, don't hit your wagon to me on that one. ANCAP is the anarchist capitalist. Anarchist capitalist, yes. Not an ANCAP. They have nice bookshops. Yeah, they do. I mean, I'm not gonna sit here and shit talk ANCAPs. Although, I also used to get into the conversations with an ANCOM, anarcho-communist, a good friend of mine. And he would bring up this stuff, and I'm like, yeah, cool, man, I'm down with anarchy. You ain't gonna like it. What do you mean? I go, because I'm gonna take all, I'm gonna gather all kinds of people together. I'm gonna make this, I'm gonna get the strongest together, and I'm going to take your shit. Okay, can I ask you, on that topic, I have a friend of mine now, a fellow Russian, Ukrainian, Michael Malice. Oh, yeah, I'm familiar with Michael Malice. I watched a little bit of your guy's stuff. Michael Malice, I watched a little bit of your guy's conversation. So, this is really good to ask you, because. I like how he's in the white suit, and you're in the white and black. But he lives in New York City. He espouses ideas of anarchism. And his idea, and this is different than sort of the Ayn Rand set of ideas, that there's a line between sort of capitalism that's backed by the state and just pure anarchism. And his idea that violence won't take over in an anarchism is one that feels, to me, not grounded in reality. I may be wrong. So, is there some, so, the idea with pure capitalism is that. You mean laissez-faire, completely deregulated. Yeah, well, what it will agree, it'll end up in, one, it'll end up in, if you're anti-globalist, it's gonna be that. It's gonna be globalist 100%, because it has no, pure capitalism has no consideration for, has no consideration for your native users, or of any sort. Like, it doesn't. Yeah, land doesn't matter. But the idea of governments is that the land, the little piece of land, geographically you're born on, means you're going to stick to whatever founding documents created that little land. So, anarchism is against that. And the argument is you should be able to choose which ideas you live with. And the concern there is nobody, this geographical little land, the governments that organize on that land will not, do not need to protect you from the violence. And my sense is there does need to be an army, there does need to be police that help. However the form that police takes. But there needs to be a more centralized, not completely centralized, but more centralized safety net of, to protect you from the violence. Scale again, right? So, if you want to have your anarchist utopia, well, what we won't call it utopia, your anarchist creation here. At certain scale, I'm sure it's doable. But as the scale increases, it's completely untenable. And a state will emerge. A state will always emerge. Because even, people always think of states as people rubbing their hands and smoking cigars in back rooms and just out of nowhere coming around and just like, oh, we're gonna create this big centralized thing and just so that we can tell everybody what to do and we can be in charge. I mean, I know that there are people like that that exist, that they would like to do things of that nature and that they see the use of power as something to be used more for their personal gains over first, which again, self-interest and human beings. But eventually, people want, they want something to go like, okay, who's taking care of this and who's taking care of that? And how do we create some sort of protocol for this? Like, okay, well, when it's not Bob, when is it Susie, when is it whatever? I mean, like, how do we, it's gotta get done if we want this thing to become bigger, if we want all of our plumbing to work right, if we want, it's just, I'm sorry, a state's gonna happen. A state is also, when you think about it, is supposed to have consideration to tribe, right? So if people think that we're not tribes, well, you're not really thinking very deeply. We're all tribes of a sort. And everybody likes to use the word tribalism in this idea of this antagonistic concept. But, and while sure, tribalism can be antagonistic, tribalism can also be a positive thing, or I could just say it just seems to be a natural thing. People, they create their groups of one sort or another. And so when you have, well, when you think about where, when nation states really started to become a thing, and I don't mean even the more modern-looking variants that we could think back of in, say, the 19th century or something like that. Even older than that, I mean, do you think the Assyrians didn't have a state of some sort? Of course they did. How do you increase your empire if you don't actually have a place to start from? You have to be a ruler. So you're saying, like, naturally, when you start talking, thinking about scale of humans, naturally states emerge. And can we try to make an argument for anarchism, which is, okay, okay, okay. So anarchy, in a sense, is an opposition to the unhelpful, unproductive, inefficient bureaucracies that eventually the states lead to. Yes, and that's, we can see, I mean, I would say less anarchy, let more study James Burnham, or, well, anybody that wants to talk about the managerial problem and the managerial. So you have a sense, a hope, maybe let's think, like, what is the path forward with the inefficient state? Is it revolution, or is it to work within the system to constantly improve it, to manage it? Man, I don't know that one. I mean, my general sense, and maybe this is the Nietzschean part of me, is that, yeah, it would take, maybe not even just, maybe not even defining it specifically as revolution. Maybe it would just take just total calamity to get people to stop being shitty, to not stop being a lesser version of themselves, to stop thinking more about things from the paradigm that we exist in now, where we're giving so much value to stuff that isn't really all that valuable. And we're so concerned about likes, and I don't just mean like whether we get them or not, but that, oh man, maybe we should take this off of our platform, because this is too destabilizing to people. And it's like, because once you exceed Dunbar's number, I think it's actually, without having the right faculties, which would need to be developed, because this is dealing with tech that brings things, ways of approaching being that we are not naturally programmed to be able to handle appropriately. So, and I think it's even more detrimental to women than men, because I think women have a more natural proclivity towards group association and more group-oriented thinking and patterning. And now, and with also coupled with seemingly more sensitivity towards human states. So I feel like women, like the classic idea is like, oh, you know, women are psychic, you have a sixth sense and what have you. And I think that's just a way of simplifying what I think is, that women may be more in tune with picking up on the unsaid. Like they might be better at seeing physical cues, inflection and tone, like different, like they may be far more sensitive to these things, which to me would make sense, because dealing with children that can't communicate. So, so. There's generally more empathetic in all the full forms of human interaction. Right, now, okay, now, whether it be a woman or a man, but especially with even the social push on this concept of empathy, which of course it gets to the point where it loses any meaning anymore. Like people use the word empathy absolutely incorrectly all the time, and they don't even understand what you're really asking of people. But let's just take it as, we're using empathy in the correct sense, and you're taking on the emotional content of the thing itself. Now you open that up to thousands of people, maybe hundreds of thousands of people all across the world, that you will never meet, that you will never know, that you're not even getting an actual true representation, most of the time, of who these people are. You're meeting persona. And some of these personas are even deliberately created to elicit a response in authentication, inauthentically. Are you referring to bots or? Could be bots or actual people. Bots are one thing, but I mean, there are literal people out there that will create something, create GoFundMes for tragedies that never didn't really, or events that didn't happen, or any number of things. Okay, I mean, burn their own house down, and then say, you know, we were attacked. And then it comes down, oh, you did it to yourself, because you wanted money and empathy and this, that, and you wanted all this emotional wealth, let's say, this emotional coin, as well as actual, if possible. You wanted to leverage it in some way. That's not the majority of people, but I would say a good amount of folks are thinking, well, if I post this photo, and I put this little blurb in there, I bet I can get this much cache out of it in this sense. And I'm not even, and this isn't just a reference to like butt pics and stuff like that, because clearly, obviously, people understand that our inborn sexual nature is easy to manipulate. I mean, that's pretty obvious. You're saying this kind of new medium of communication on social media is unnatural. And it preys on us, and so as you want this, you know, you look at an anarchist kind of mindset, right? And so it's just like, there is no overarching state to create any kind of structure, right? And so if you have that unfettered capitalism aspect with it, and before I say anything particularly damning about unfettered capitalism, I'm a massive capitalist, because I view capitalism essentially as, what it boils down to, I get these arguments from people too, they start giving me all these extra definitions about capitalism, like no, no, this is obviously some sort of theory you're taking from other shit, but that doesn't describe capitalism. Capitalism is the ability for us to create whatever we want, or you know, create our thoughts, ideas, physical things, and trade them freely amongst each other in ways that we find acceptable, right? You know, I'm not even using the word fair, because I might think it's fair to me, you might think, huh, well, I mean, that was actually, I think what he thought was unfair to him, and it's more fair to me, and then someone, a third observer goes, oh man, you should not have paid that for that, you should have paid this, and it's like, well, you know what, it works for me. Without. Sufficiently acceptable that you both agree to the transaction. Correct, and you know, but also at the root of that is freedom, right? And as far as I can tell, I've been banging this around in my head, it's like, for every one unit of freedom, you need two units of accountability. And if you don't have that, what you end up with is, is human self-interest, we're not even gonna get into evil, human self-interest, sabotaging other things, even not in a sense to be malicious. Okay, so in terms of, let's put this as mathematically speaking, I love this, so anarchism is more like two units of freedom and one unit of accountability, or maybe zero units of accountability. Possibly, I mean, the anarchists tend to think like, no, everyone will be accountable, it's like, fuck they will, when have you seen this happen in real life, you know? I mean, people aren't even accountable in their revolutions half the time. So you aren't looking at the way people really are, it's like, Marx is like, yeah, people are like this, they're like that, look at how capitalism does it. I mean, he of course assigns a lot of really ridiculous economic principles and practice, but also assumes that everybody who makes any profit from anything is somehow stealing it, really assigns a negative moral aspect to them, and then it's like, oh yeah, but then eventually, communism will happen, no one will act that way anymore, and you're like, whoa, hold on, you just said that people are all, are you saying it's all due to capitalism, or is it innate, it's a fundamental misunderstanding of, and it's like, hey, look at you, you're like a notorious anti-Semitic, angry, just absolute curmudgeon of a human being who seems to be really not all that fun to be around. Marx? Yeah, and then it's just like. So you have to think like, if there was one billion Marxists in the world, how would they behave? They would all, it would be absolute terror. They would hate each other so bad, and this isn't for me to even poison the well on Marx, it's like, oh, his personality sucks. There's lots of people whose personality sucks. That doesn't mean they can't make, I don't know that his, what? You know what, somebody argued. He's just a loner. I mean, I don't know that his personality sucked at all. Let me walk that back in that he was human. Say his personality sucked. He was sometimes contradictory, irrational. Sometimes he was quite sexist, despite the emails I've gotten. Despite the emails I've gotten. That told me that, this paper was written to me that Nietzsche has been unfairly labeled a sexist in his discussion about women. I'm pretty sure there's a bunch of documents where he's just like, he's just a bitter guy. I will agree with you, and Marx is as bitter as they come to. But, you know what, bitterness in and of itself doesn't make, like, why I hate Marxism comes from the whole, the entirety of the thing. But, the dismissal of human nature. Yeah, but I'm not going to say that Marxism, or, man, you can find any forbidden book and it could have something good in it. His kernel's a good idea. Yeah, and at the end of the day, Marx is a human being. He's got a nice beard. Yeah, he does. He had a hell of a beard. Yeah, a decent portrait. I mean, he looks like the kind of guy, I wouldn't want to meet him in a dark alley, but thankfully I don't think he was much of a fighter. But in any case, I mean, not the anarchists, they're more hot for Max Stirner. People like to think that Nietzsche borrowed a lot from Stirner, and my argument is, one, you don't have any real evidence for that, and two, bullshit. The fact that they have some overlapping thoughts doesn't make it lifted. Not to mention, go read more philosophy and see how there's so many different things. Oh, this guy said it in 1722. Well, and then this guy says it again in 1922. Does that mean he read the other guy's stuff? Not necessarily. I mean, he's working from the same type of human physiological construct as anybody else. Of course it's possible that this guy could think the same thing. We think a lot of the same things, to be perfectly honest. I mean, reading the Hagakure, going back to philosophy books, this was really impactful on me as a younger adult because here's a book written in the 19th century about someone who lived through the 19th and 18th century at times, as a samurai, now a monk, and his objections to society at the time, the same objections one was having to society as I was reading it. Like the same human behaviors, the same impetus for action that he found a problem. Like, well, that's the same shit now. And this was the thing, and then I'm reading more religion, I go, oh, we're no different than anyone who wrote the Torah or older. We are the same thing with the same problems with the same psychological issues, the same human behaviors. Like, these things are not different, and we haven't changed. Growing set of tools, though, to kill each other with or to communicate together and all that kind of stuff, but underlying it is a human nature. Well, we're also trying to understand that human nature. I think we've, just like you said, learning how to fish, acquired more and more knowledge about that human nature, but it's been a very slow journey, slower than people realize. Yes. In terms of understanding human nature. Let me ask in terms of egoism, it'd be curious to get your sense about Ayn Rand and her whole idea of virtue of selfishness and her, because you mentioned that everybody has a kernel of truth. There's potential for a kernel of truth to be discovered in anything. For example, I've been recently reading Mein Kampf. Mm-hmm. You know what? That's the thing. Even, there's something in, there's probably things in Mein Kampf that are not the surface level read. If you get all hung up on probably all his crap about, you know, his anger at Jews and this and that, all this crap, it's like, okay, yeah, that's right on the surface. Try to get below that. Try to see, you know, how is he creating the Jews as a cope somehow? Like, how is he using, why are they his scapegoat? And I mean scapegoat in the, so René Girard's concept of the scapegoat, I mean it in that sense, whereas Hitler uses, wants to make the Jews the scapegoat for World War I. Yeah, I mean, for me, the starting point, similar with Ayn Rand, is like, Mein Kampf is not a good place to search, not just because Hitler is evil, but it's just not full of ideas. No, it is not. It has its significance due to a lot of things. Historically speaking. Yeah, but. The starting point for me with Hitler is like, to acknowledge that he's human and to at least consider the possibility that any one of us could have been Hitler. So like, not to make it. Well, that's a Peterson kind of concept. Also, Jonathan Haidt has a thing about the difference between hate and disgust mechanisms and things like that, and so he used, he goes into the, looking at Hitler and his, through his diary entries and journals and stuff like that, to look and see it more as the disgust mechanism than also try and see if there's any evolutionary biological attachment to this, whatever. I mean, you're right, he is a human being. Any of us are, we're all human beings. It's not that, it's probably jarring for people to think, but we're all, I guess, supposedly, potentially capable of just being in, and all these evil people in the world think they're doing it for the sake of good. Yeah. Which makes them the most dangerous. And there's some, there's differences in levels of insane. I think Hitler was way more insane than Stalin. I think Stalin legitimately thought he was doing good. I would say that's probably true. Stalin was just outright brutal. Like he had his five-year plan, he had all those other things. He just had a much lower value for human life. Yes. And so he was willing to take, make decisions about what he actually, as a good executive, which he was, of managing different bureaucracies and so on, he was willing to make decisions that resulted in mass human suffering. Where Hitler was, it seems like to me, much moodier. So a lot of emotions and moods to make decisions. I think we also have to consider the different trajectories and how, where, and when they were making their decisions. And I mean, not by time specifically, but Hitler engaged into this conflict across multiple continents. And then that, everything that comes with basically fighting the whole world, Stalin had his conflict, and then he really mostly compartmentalized the rest of it. So he was dealing with his own internal instead of dealing with the internal and the external. So if Stalin was put under a World War scenario, I don't know, maybe he would have eventually lost his marbles too. Yeah, I'm not sure that, you're right. The hunger for power was more internalized for Stalin. He wanted to control the land that already existed as opposed to wanting to colonize other land. He was as nationalistic as Hitler, and was as capable and willing for violent conflict as Hitler for the aims of the state. But he centered and internalized prior to then externalizing and moving outwards. Whereas even maybe prior to him, there was an interest to continually push communism in an aggressive sense, following on the momentum from the 1918 revolution. And the halting of that through various aspects, I guess in Germany, part of that was the National Socialists. Like they came up and then they were the other ones to fight the communists. And so you had the two totalitarians going after it. But then in the rest of the world that was not dealing with totalitarian aspects, it was just, it wasn't gonna stick, especially in the West and other places. But Stalin, just casually thinking, it seemed like Stalin decided to go, all right, well, we're not gonna go just start launching right into more conflicts here. We're gonna, these dudes are going down, so that's cool for us, because they hate us and we hate them. But now we're gonna focus internally, and then we're gonna work on growing at a slower rate and picking our battles a bit more specifically. And of course there's, you can get to the, even this is after Stalin, but you got the Beslanov type stuff talking about subversion in cultural aspects. Yeah, I mean, there's this fascinating dynamics of propaganda throughout the whole period that's. Yeah, it's a whole nother kernel, yeah. Do you think Hitler could have been stopped? One of the things that's kind of fascinating to look at is how many nations, both journalists and nations, wanted, almost craved to take Hitler at his word that he wanted peace until it was too late. They almost wanted to delude themselves. I mean, the same is true with Stalin. People wanted to take Stalin at his word for. Oh, they still delude themselves. Yeah. We will delude ourselves over any number of things until even after the fact where the history just says, hey, fuck face. You cannot supplement your pseudo-reality onto actual reality here. But yet, we deal with people in pseudo-realities constantly. We will always find a way to change reality to suit our needs. Well, the nature of truth now, there's now multiple actual truths. It's kind of fascinating. There's multiple versions of history that people are telling. The version of the Great Patriotic War in Russia, the World War II in Russia, is very different today under Putin than the version that we're learning in the United States and then different than the version in Europe. In the United States, the hero of the war is the United States. In Europe, there's a much more sad and solemn story of suffering and so on. Sure. In Russia, it's the Great. Patriotic War. Yes. It was a unifier of a sense. And it, I mean, yeah, I mean, you can't argue that war and conflict that, or just even reducing that to stressors, agitation, suffering, doesn't create human motivation. We started this off, you brought up Frankel. I'm like, yeah, Frankel's dope. Man's search for meaning. Maslow's great. And I talked to you about how I started to think, like, man, the ability for human beings to live and or potentially flourish in the worst environments you can think of is pretty incredible in and of itself. And that it's a crazy thought to think that without Frankel and Maslow ending up in concentration camps, do they write some of the most important books on philosophy in the 20th century? And that's insane on a lot of different levels. But. Yeah, suffering is a creative force. I mean, I don't, do you think we'll always have war? Yes, we will always have war in some form or another. We need, quote unquote, air quotes, for those just listening, war to survive. We need war to flourish. We need at least. Can you explain the air quotes around war? Well, because take, take the. You see wars as violence? No, wars are not violence. So like, so when we're talking about. No, air quotes because while, you know what, us getting on the mat or just getting on these hardwood floors and wrestling around is not literal war, it's war of a sorts. You know, it is a diluted form of war. American football is a diluted form of war. All this, these are diluted forms of war. Tennis is a diluted form of war. And I think one of the best explanations I ever got from this, another person very impactful on my life and outlook and thinking about things, Cormac McCarthy. And so in Blood Meridian, there's this fantastic speech about war given by the judge, which there's a ton of fantastic speeches on things given by the judge. Yeah, all that exists in creation without my knowledge does so without my consent. Okay, that's pretty heavy. That's hard. Go ahead, can you break that up? Can you say that again? All things that exist in creation, all things that exist without my knowledge do so without my consent. What does that mean, Cade? Well, I think from the judge's perspective, it's like, well, I didn't consent to that bird or that dog or this building or all this. Like all of this, you know, I didn't create it, so it's done so without my consent. And if it's up to my consent, well, I'll design it how I want to. There's another similar look into how the judge is in that book is he would. Study everything, everywhere he went. And so he's collected this group of ne'er-do-wells from all over to go on these hunts against certain tribes in the Southwest and getting paid by the US government, the Mexican government. So he's on these Indian hunts, and yet they're going to all these different places and they would stay the night in a cave somewhere and he would find cave paintings, he would write them all down. Or he would find old pieces. There's an example of him, the narrator, explaining how watching the judge and how he drawing everything. He's got this notebook just full of things, drawings and writings, and how he found like a piece of armor from a conquistador or something way back in the day, a Spanish armor, and he draws it into his book and then crushes it. And so the reason we'll always have war in this society is because there's this struggle amongst people that want to be the designers. There's that, but I'm just saying that he's got this whole quote on war, like war is play, war is a game. And the difference is is that what's at stake. So all things are a game of some sort and you're putting up for it or what you're willing to put up for it determines whether or not you're going to participate or not and all aspects of any game is war and it's just what is at stake? If it's your life, it's a different story. If it's just a coin, it's another thing. A nice way to put it is humans play a game in this kind of pursuit of creating. Whatever the hell the reason is that we keep creating cooler and cooler things, that it seems to be the result of a game that we naturally play, we naturally crave. I don't know, I mean, that's been the struggle of philosophy is to understand what is the underlying force of all that. Is it the will to power? Is it? I think will to power is a really great way of describing it. Do you want to be the winner of the game? No, not just, no, I don't look at will to power as being the winner of the game. Well, I mean, if we're gonna get philosophical, yes, you want to be the winner of the game. What does winning the game define and how you win? Everybody's gonna define that win differently. You could define the win in the most base level like, oh, I got all the things. Well, if you got all those things without the needing component of fulfillment, then you're gonna be a very unhappy person with a whole lot of things. But there's a self-referential aspect to where, to me, the winner of the game is defined by the people playing the game. So if I'm playing a game, I want to win in the sense that most of the other people who are playing the game will say, yeah, that guy won. By our collective definition of, if I just come up, listen, I'm sort of, if I come up with my own. That's a lot of weight on the external on you. Right, but that's how games seem to work. Somewhat. So I'm already a winner in my life by defining my own definition of success. I'm basically the best person in the world at doing me. At being Lex. Yeah, and I'm really happy with that. That's a source of happiness. Games are also iterated, right? So you start off with your game, and then your game with your immediates, and then the game further than that, and the game further than that, and then the game today, and the game tomorrow, and the game next week. And so it never ends. And if you try to keep thinking about it that way, no wonder people go crazy. But we don't want to think about things that way. We don't want to think about being towards death. We don't want to think about whether or not I'm going anywhere after this other than in the ground or what have you. All of these games are a sense of some distraction. This is where we brought up. Kind of, but I mean, it's violence is that we need to let this out. And so it is of our, kids need to wrestle and play, just like animals need to wrestle and play. We need to have forms of competition. We need to have ways to test ourselves, to create when, what is it? When at peace, a man of war makes war with himself. And so we need to be able to competently go at war with ourselves, and go at war with our neighbor, and go at war with our neighbor's neighbor in a way that is repeatable at the very least. So one way of saying that there will always be war, I mean, that's my hopeful view, is that most of the war conducted in the future will be, like you said, the man must go to war with himself. That's what, to me, love is. It's like focusing on yourself and your own improvement, and your own creativity, and towards others, feeling, sort of emphasizing cooperative behavior and compassion and empathy. It would be great, but I mean, you can have, well, I'll put it to you this way. If you have a whole community of Randians, and a whole community of ANCOMS, and they could all, like, I don't know, a toast of London on Netflix, and they love Netflix, and they love the internet, and they love picking apart Mon Comp with you. They like all these things, even the esoteric, that they can get on with. But at the fundamental root, they cannot help but go to war, because they are literally oil and water. No, but see, but they would, the very labels they assign to themselves would need to dissipate. Well, true, well, then you would have to stop being whatever it is that you took on as your ideological or religious point, right? Yeah, I mean, there's some days I'm a ANCOM, some days I'm an NCAPS, and whatever, an ARCA, an ARCA-CAPA. I mean, it depends on the hour, the minute of the day. You're constantly changing moods, and embracing that flow, the change of opinions, of ideas. There's some days, like, I'm actually cognizant of the fact, because I've been not getting much sleep, and after I get some sleep, I see I'm so much more optimistic about the world. The less and less sleep I get, the more sad and cynical I get. I can see that. Up and down, constantly. I don't even let my, well, okay, I try not to let, and most days, it's never a problem. Any sort of, what do the kids call it now, black-pilled way of thinking, be my over, the umbrella, which I hang under. So, we actually, to drag us back, can we talk about Carl Gatch and Cat Tresley? Because I do want to make sure I touch it. Carl Gatch is- Is he the greatest catch wrestler? I don't know if he was the greatest catch wrestler ever. I mean, he's one of them for a myriad of- Carl Gatch, Billy Robinson, Gatch and Robinson's trainer, Billy Riley. So, who are these figures, and what do they bring to the- Mitsuo Maeda, he's one of the greatest catch wrestlers ever, because he's responsible for Brazilian Jiu-Jitsu, along with Cristal Gracie. Okay, there's a bunch of things I'd like to say here, but one of the things that catch wrestling seemed to espouse as a principle is that of violence. The tournaments I competed at, the unfortunate thing, and we'll probably, hopefully, talk about it a little bit, they were disorganized, and the level of competition was pretty low, and people really sucked. Pretty typical. Yeah, it's that typical, okay. Well, I mean, think about local, run-of-the-mill Jiu-Jitsu tournament versus IBJJF created, you know, a vast difference. But there is, to me as a human being, like intellectually, philosophically, it was more interesting to go to a catch wrestling tournament, it seemed more real and honest because of the way they communicated about violence and aggression. It is often more honest. I think that as- Who is that from? Does that originate from, gosh, that Bill Robbins said, I had a- Well, it originates from all wrestling, in that even Wade Chalice, not a classically considered catch wrestler, yet the reason why he has the world record for most amount of world champions pinned, or the record for pins in the NCAA, is because, well, of course, the idea is to put you on your back and pin you, but there's no way you're gonna let me do that. So how do I make it so that you want me to pin you? Well, it's by you put him in excruciating pain. So at the end of the day, you're both there, you both wanna win, neither one wants to allow anything to the other, so how do I get you to lose to me? I make it so unbearable for you that you decide losing is better than staying. So those two are so fascinating, because, so coming from Russia, I don't know if that's where I got it, or if it's just my own predisposition, is I always loved the, there's two ways to get you to want to pin yourself. One is to making it so painful not to pin yourself that you pin yourself, or whatever, and the other is, it's sort of like Bruce Lee, water flows, make it so easy to pin yourself. So it's technique, it's like the elegance, the ease of movement, this is the Satiev brothers, Bovassia Satiev, like the, just the elegance, the efficiency, the chess. Yeah, they're practically like ballet, watching those guys, you know, it's incredible, Satiev brothers are massive. And I'll also caveat a little bit that like, if you're approaching this from a Russian perspective, Russians are quite truthful about things, especially when it comes to something like combat. They just, this is how it is, and this is how it's going to be. It's honest. Yes, and the honesty is what I really like about catch wrestling, because I find that we, given any opportunity for us to be dishonest for any number of reasons, we're gonna, especially if it's a dishonesty towards a positive, right? Like, oh, well, you know, it's all technique, and it's all this, and it's the gentle art, and blah. Bro, I have rolled with 80 CC world champions, you know, some of the best you have ever heard of. There ain't a lot of gentleness when it comes to like, oh, yeah, they wanted to sweep you, and you said no. And then you did, said no again. And then you said no and attacked their leg. Like, it ceases to be all that gentle, because at the end of the day, these dudes are strong as hell, they're flexible. They're all, I mean, they're, the difference between the athleticism and the ability to actually win is a pretty wide gap. The athleticism shows up, but then there's all that other extra, and part of that is meanness and pain and getting what you need out of it. But see, there is a philosophical difference in the way it's thought, because. I think some of it is just, they're just in denial. Like, oh, people will, they like to, people like to espouse a lot of things as theory, and then it's like, okay, let me watch. Oh, you're not doing anything about what you said right now. In fact, you're doing the opposite. You're literally hurting that guy, because your shit ain't working in the way that you'd like it to. So you're having to use strength. It's one of my favorites. Oh, you're using too much strength. And it's like, well, hold on. Do we want people not to use strength at this point to understand more of mechanics? Or are you trying to tell people if they use strength at all, that they're somehow bad at what they do? Because, you know, it's not my fault, you're not stronger than me. But see, I'm speaking to something else that's, I tend to think what it comes down to is like, strength is fine until you beat me with it. Then it sucks. Okay, so strength is another thing. I'm speaking, I'm thinking about more like anger. Oh, sure. So like, A lot of angry guys in jiu-jitsu, I know that. Really? Okay, okay, good. Well, but let's talk about, let's talk about the highest level of competition. There's a book called Wrestling Tough. Yeah. That's a really good book. I've encountered in my life a few, especially in wrestling, people who really try to find a way to use anger, to get really angry at their opponent. Not like stupid anger, but just like- Intense, pointed anger, distilled into something that you can use as fuel. And I remember this story, I don't know where I read it, it might be Wrestling Tough, where a person was imagining that their opponent just raped their mother, raped their girlfriend or something like that, to create this method acting thing in their head to be like, to snap them out of this polite interaction of usual athletic convention and really go to the- You know, that's a design of necessity. So my anecdote for this was, I was sitting with, backstage before a fight, not my fight, and I'm working with this guy, and this dude is, this is a world champion guy, and he's competed at the highest levels. And he looks at me and he goes, you know, do you ever get nervous before fights? And I looked at him and I went, no, I don't. And he just looks at me, he's like, fuck, man, I'm so nervous, how do you do it, man? I wish I could be like you. And I said, you know what? That doesn't mean that what I'm doing is better. It's just what is necessary for me. It's the way I am. And I told him, so this anecdote goes into another anecdote. This is a Family Guy episode, I guess. Where another famous high-level guy told me about this experience with a world champion boxer in Japan. And this guy would get insanely nervous and worked up and anxious before his matches. And he hated it and hated it and hated it. And so he wanted to get rid of that feeling. So he went to a hypnotist for a bunch of sessions and managed to, and he goes in, and next fight, he's cool as a cucumber and doesn't perform and loses. And so what I said, going back to anecdote one, was, you know, whatever is necessary for you to get yourself in the best state of being right now to compete, whatever that may be, it could be absolute stress and fear, it could be anger, it could be calmness, it could be whatever. But there is a, but there is a, there is a state at which you need to be in to do your best. And you as the individual, you have to find that. Can you comment on Tyson, Mike Tyson? Oh, yeah, that thing? So first, so he, there's two things I wanna, so he's, in terms of fear, there's a clip there, I think from a documentary where he talks about how he is fully afraid as he walks up to the ring, and as he gets closer and closer and closer, he gets more confident until he gets in, and then he's a god or something like that. That coupled with his statement on Joe Rogan that he gets aroused at the possibility of true, like of hurting somebody in the ring. So like, he gets aroused at the violence. Yeah. I like it, because it's coupled to your, basically, statement that we need to own, to find our own unique way of existing at our top level of performance, and that perhaps is Mike Tyson. But do you think there's something more deeply universal to the Mike Tyson speaking to the fact that he's aroused at the possibility of violence? Yeah, I do, actually. Although I don't think that it always equates to arousal. For people, in fact, I would say in general, it doesn't. I can say I've never had a boner in the ring. In fact, if anything, old combat cock is like, we're not hanging around, we're leaving, we're going up. We're taking off. We don't want anything to do with this. You have fun, come back to us when you have something warmer, softer, smells better. But the power, the feeling of aliveness, yeah, I could see it. Back to even the concept of the Ubermensch, I feel like the highest states of being I've ever been in were in the midst of conflict. I felt like that was the time, those were the moments in my life where I felt like I was at the highest level of being as a human in existence. But yet, even being in that state, it was not something that you could interact with people that weren't in that state with you. They wouldn't get it. You would almost seem, and to be that way all the time, either A, might drive you mad, or B, is you're something that's untenable to the rest of society. You can't function with everybody else. It will not work. It's just like you said with the Ubermensch, it's like it's perhaps that ideal is not something you can hold for long. That's the very nature of it is. Yeah, well, there was an example in The Spoke Zarathustra about a snake being down the person's throat and biting it and then having this maniacal laughter erupting and to me it was, at least I read it as, yeah, okay, there's this insane moment that isn't forever, but that it is life and death, and the overcoming it is the thing that all of a sudden gives you that tapping into your highest state. This is, man is a chasm, a tightrope between man and Ubermensch. Well, I don't wanna leave your thought about, we'll call those things flourishes to the aspect of Tyson's interpretation or his expression of his feelings in combat. And so I gave this anecdote to the guy, and I just, my first anecdote to that athlete I was working with, and I said, you know, there isn't a superior way in this sense. There is the way that works for you. That may be something you can implement to other people if you find that person, because we all have different personalities. And to me, that's an absolute. I don't wanna, don't come at me with all your other fucking social sciences crap. No, we have distinct personalities. That personality, who you really are, and this, again, Heidegger, Dasein, being authentic. If you're authentic with who you are, goods and bads, you will know how to create what that is. And for me, violence and fighting and conflict was something that always felt normal to me. And I don't mean normal in, like I grew up in a war zone or an abusive household or something like that. I just meant that, I was a kid who was very joyful and inquisitive and spent a lot of time around older people, of all things. And also, while I don't think I have much capability toward engineering, my mom said that one of the first things as a little baby, when she put me in my sister's old crib, instead of my sister who just milled about and was fine with it all, the first thing I did was I completely deconstructed it. I didn't break it, I figured out how to pull it apart. Curiosity about the world, and yet that wasn't in conflict with the idea of violence? No, not at all. And so, being a very joyful and nice kid, but kids are kids, and if kids can find that you respond maybe more easily to agitation, they will agitate you. And if you should stand out in some way by being taller or bigger or something, or caring especially, they will agitate you. They don't really fully understand it either. And so, I don't hold anything against any of the kids that used to pick on me or whatever, especially at the youngest ages. Man, they don't know shit either. But once that line was pushed, for me it was, oh, well, I was being cool, now you're being uncool. Well, then that gives me license for everything. And so, boom, we would just go at it. Or kids that would try to initiate a fight, and I was like, okay. And being in that moment of just going to town with someone else, it just felt like this is... I belong here. Yeah, it was never a problem for me. In fact, if anything, what I had to understand was, well, not only did I learn the hard way that it doesn't matter, at the end of the day, it doesn't really matter what anybody else does if your response in violence, even to their violence, if you're the winner, is often going to be penalized severely. Society, state apparatus, they don't want any of that. They wanna be the only arbiter of violence in the world always. But I learned a very difficult lesson with that, and it was really impactful in a negative way on me, but also I had to learn on an individual sense to you need to manage violence too. Because, hey, if someone attacks you or starts a fight with you and you go at it, okay, beating them up is one thing. Trying to grab a handful of broken glass in the street and throw it in their face, maybe that's a bit much at seven. So you need to learn what level is necessary, and you need to learn what comes with all, what's the responsibility of, when you enact violence, I mean, you take on something, you have a responsibility for that. This is the extension of your actions. But as I got older, and especially as I found sports, and then combat sports, now this was a place for me to flourish, and to the point where I was more myself in that space than I was outside of it until time enough where I could learn to get this back together again. And I never say that I'll merge the two or anything like that. No, all what happened, my journey from adolescence on to manhood, a huge portion of it, besides the normal finding yourself, whatever, whatever, actually what it was, it was getting back to who I always was. Getting back to the- That curious kid, the kind kid. Getting back to the guy that I should have been allowed to become instead of what happened under the pressures of other things. And the attempt for society and certain people within managerial positions to compress what that was into something that they found more suitable. Yeah, but those pressures allow you to discover this little world, forbidden world in many ways, of violence that you could explore. Through sport, you can explore it. It's more socially acceptable to explore it through sport. For sure. But even then, at times, it's socially unacceptable. So I beat Sem Schilt. He cut my right eyebrow. I cut him and busted his nose. And he's bleeding all over me as I have an armbar on top. I'm getting, it's raining blood. Quote some slayer from a lacerated Sem Schilt, bleeding in his horror, creating my structures. Now I shall rain in blood. But I win the fight, armbar, nasty one. I get on my feet, and the first thing I do is I wipe all the blood off onto my hands, and I lick it, and I do my thing. And all the MMA journalists freaked out. Dana Wise, like, man, I don't know about that. We don't want him doing, everybody had this huge problem. And then some folks would even contend, oh, you know, you're trying to do, like, no, no, no, this isn't planned. This isn't, I don't think of these things. This isn't, this is how I really feel. This is who I really am. And, you know, it was even kind of comical after the fact, you know, and BJ Pan was on the very card with me, watching him at some point in his career, all of a sudden, win fights, and then do this licking the glove thing, and everyone thinks it's the coolest thing ever. And I'm like, hey, fuck faces. I did this in 2002 or one, 2001. And BJ Pan actually back then was like, dude, you're a badass, you're a killer, you know? Where did that come from? Because that seems like a deeply human moment. I could say, I could just be, you know, goofy about it and call it orgiastic. You know, to align with- Are we back to Mike Tyson? Yeah, but, Tyson, but no, no, it isn't, it's beyond that. Is it a celebration of human nature? I've had some pretty decent orgasms in my life at this point, I'm 43. But no, none have ever compared to that. Like I said, it is a feeling of highest being to me. That's your Ubermensch moment. This is where I feel like the restrictions of general existence in society are gone, and I get to fully live in a state that feels more meaningful, of the most meaning. You know, I think of it as life and death. And it's just, it is the way I'm built. And I don't have, I've never had any problem applying violence. Like it doesn't, I don't know where it comes from or how you would define it or whatever, if you want to stick me under in a psychologist chair, but like I don't, there's a part of me that can just, no, if I'm gonna apply, I can apply violence to any level and be okay with it. And it doesn't, I don't lose sleep. It doesn't bother me. It's not a problem. It was me learning how to fully understand violence, humans, and the broader perspective that allowed me to think about things and like, well, what do I really want to accomplish with my actions in the world just on a whole? You know, not compartmentalizing my sporting career. Even when I get in the ring, I don't have any mercy generally. And if I do, it's because I make a really deliberate attempt to be in a state where I can have mercy. If I just go in there to fight with everything I got, there is zero. There's nothing that will hold me back other than the referee and that's that. You know, I know I agreed to be allowed to do and not to do, but within that, no. And I expect it to be done to me. But in terms of values, in terms of seeing what, to me, violence is just yet another canvas that humans can paint beautifully on. Clearly, I mean, we have venerated the violent. There are communists that venerate the violent on their behalf. There are national socialists that venerate the violent there. And then if you remove it from an ideological perspective, we venerate the violent when they're a hero. We venerate the violent in our religion. Well, I mean, I guess some people venerate the violence of Yahweh and Sodom and Gomorrah, right? So, or do we say Jehovah? I don't know. Is there, you've already mentioned one, but is there a fight where you've achieved the highest of heights for your own personal being just when you look within yourself that you're the proudest of or maybe was your most beautiful creation? Is there something that stands out? Yeah, there are a few, actually. Fighting Semi-Shield and a rematch. Well, the first one was pretty good, too. But the rematch was I was suffering, I had suffered prior, the week prior to food poisoning. And so while my abs were looking all right, I, in the ring, didn't have the power that I expected to. And I was struggling in ways, in some of the grappling, the submission stuff that I hadn't accounted for. Just exhaustion or mental exhaustion? No, I mean, just physical, I wasn't back up to 100% in terms of just power output. And Semi was, well, he's always seven foot tall. But this time he was, the first time I fought him, he was 260, 257 or 260 something, something like that. This time he was like 290. And so he was a significantly bigger cat. And he's a big dude. And I just remember being up against the ropes with him, changing levels, trying to take him down. And he's fighting, he's hipping. And I just thought in my head, there's no fucking way I'm gonna lose this fight. There's no way, you are not going to beat me. It's not gonna happen. And I armbarred him, the other arm. You remember the fact, he's like, I really wanted to get you for that. I wanted to get that match back. And then you fucking got my other arm, dick. I'm like, dude, I still love you though. You know, and that- But the whole time you're like, so this has to do with the dichotomy of you're feeling your worst. And having to overcome. You're like literally mentally telling yourself, there's no way. There's no fucking way I'm gonna lose this fight. And then there's even my last bare knuckle match. And getting in the ring and fighting bare knuckle boxing for the first time. And just thinking, just being in a great state. And just looking so forward to seeing. I mean, I called someone. I was talking to them the night before. And I said, yeah, well, I video called you because this face might not look like this when I see you next. And they're just like, ooh, okay. That's not just like empty trash talk. That's like a clarity of mind and a seriousness about this particular- I might die. I'm pretty high chance of being deformed some way. So, well, fuck it. I don't really care. Do you think about, are you accepting your own death? Yes, 100%. In fact, and that's, in a strange way, that's partially what makes it so elevated in terms of my sense of feeling. By being able to have death at my side, it feels good. And to be there and to think that this could be the one, like, why not? I'm not a religious person at all, even though I very much have to seem, seems to bang on the drum about the usefulness or understanding the usefulness of religion for people. But if I gotta do something, then yeah, put me in Valhalla, man. I don't wanna be anywhere else. Nothing else seems like a good place for me to be. I wanna follow my heart. I wanna follow my heart. I wanna fight all day long and feast all night. It sounds great. I saw you throw your hat into the ring of Vader, I mean, I mean, I think. Yes. He got COVID, I guess. I hope he overcomes it and comes out just as good, if not better. Epic with that. Did I understand correctly that that might be his last fight? Yes, that's my understanding. And it would be epic as hell. And it would be epic as hell because the person that I wanna give my most to is a person that I respect, especially at this long, this long career of mine and getting at this twilight years. It's like two warriors. And that's the thing about even this going in there with the aspect of being with death and all that is that when that person is in there, they are my brother with me in this. And that so when you give me your best, even if I win dominant fashion, but if you show up and you're as authentic and being here as I am, then I love you. And I'm glad for you to be here and we're in this together. And at this point, your loss or my loss or whatever is no less deserving of veneration than the win. Like we're here in this. And so to be in the ring with Fyodor and to venerate him in win or defeat, to be in there with someone like that is to me, it's so rare. It's incredible how the ultimate violence is coupled with like love or respect. And it's like, it's weird how this is, how the competition in its violent form is also a veneration of just the human connection. It's also the removal. I feel like it's the purest, one of the purest ways, purest, most honest places a person can exist. That line in Fight Club, you don't know really who you are until you've been in a fight. I mean, believe that. And I've seen so many examples of people trying to portray themselves as one thing. And then in the ring, you see who they really are. Or even when they're trying to portray themselves as one thing and they're winning, the crowd at times will see who they really are and still hate them. It's like, but I said all the good things. Bro, don't work that way. Yeah, but speaking of Fado, if we take you out of the picture, who are the greatest mixed martial arts fighters of all time? I feel- You out of the picture. As a cop-out to some degree, I feel like we need a little bit more time to see how this unfolds. Because you gotta compare a lot of things. And I, did I, I think I'm- I did an interview. I don't know about centuries, but that would help if we can keep accurate records and not allow too much bias to fall in, too much propaganda. The victor still, right? But I made an argument. I did a, it was a interview with an MMA outlet of some sort. And I can't recall who it was. But, oh, it was an argument about, will the winner of Cain Velasquez versus Stipe Miocik be the greatest MMA heavyweight of all time? And I said, fucking no way. Oh no, it was Cormier and Miocik. That's what it was. I said, absolutely not, not even close. And I said, these guys need a bit more time to see how things go. And also how things go for some of their opponents. And there's more factors than just this one fight. It really is. And I go, and when you wanna weigh these people, even if, let's say, we'll bring Alistair, yeah, Alistair Overeem into the equation. Okay, you judge him on what you know now, what he's done for you lately, okay? Which is a very myopic way of doing it. What has he done over his career? K1 champion. He was a champion in Dream. He striked for us, blah, blah, blah. His overall record. The entirety of all the different opponents he's fought. And I just sit back and I go, okay, he's not the UFC champ, but his accolades, his merits, in some ways, actually stand up higher than Cormier's and Miocik does. So what about the moments, do you give much value to the special moments, like the highest heights you rise to? Not in terms of records or the strikes landed, but just creating a magical moment in a fight. It doesn't have to be even a championship fight, but just, you know, Conor McGregor is an example of somebody who creates a narrative, who creates a story, who creates a drama, and a special magic happens, even if it's like not with a... Myth is greater than reality, and that is always the case. But do you... And so I understand that so very much, and it takes an asshole like me to poo-poo on your myth. At least get you, at the end of the day, you're not gonna abandon your myth, but perhaps temper it with the facts and logic. But... So you're not a fan of myth? No, I'm an absolute massive fan of myth. But you prefer facts and logic. It's like when I... No, I mean, I like saying facts and logic, because people, I also, I am not a materialist in that sense. I don't think that materialism can solve for everything. It's not enough, it's not robust enough. I'm sorry, if facts and logic, or reason, as the Enlightenment scholars all thought, including Marx, was enough for people, then we wouldn't have any religions. We wouldn't have any... There would be no... We wouldn't have narratives and myths, and all this kind of stuff. It would not be... It just, I'm sorry, there is no... There's nothing about history that supports the idea that rationality will overcome all. There's something about Ben Shapiro's facts don't care about your feelings that feels to be missing, feels to be missing something fundamental about human nature. It's not clear to me exactly what is missing. To give old Ben a fair shake, and I don't know Ben Shapiro. I don't really listen to Ben Shapiro, not against Ben Shapiro. I'm not here to say anything particularly bad about him. Although, I will say at one time, Tom Arnold was seemingly trying to pick an actionable fight with Ben Shapiro. In the ring. Somewhere, yeah. And I actually responded, and I tried to get him to clarify. I said, hey, are you saying that you wanna fight Ben Shapiro, that you're looking to actually... Because I was waiting for him to say something, and then I can be like, okay, well, it's one thing to wanna get into a fight with someone. It's another thing to go pick on a little tiny guy like Ben who's much smaller than you and doesn't train or whatever. But if it's not me, I can find someone your size, and you can go fight him. Basically, don't be a bully piece of shit. Which, by the way, Tom Arnold, you are a mental midget. You are never going to be able to compete even with Ben Shapiro in an argument on any level about anything. Oh, intellectual argument. Yeah, intellectual argument. Maybe you can scream louder than him, but whatever. But nevertheless, in the discussion of greatness in fighting, I think you need to look at some of the... You need to look at some of the numbers. And there's the magic of the myth. There is some context also in that, where did Alistair Overeem fight? Oh, he fought in Pride, where you could soccer kick people and stomp their heads and this and that. And so the game environment is actually different too. There's more uncertainty, there's more chaos in Pride. There's more... Go back a little further and go like, what about the guys that used to fight? Dan Severn fought bare knuckle, head butts, the whole nine. You beat Dan Severn, right? I did beat Dan Severn. That was killing an idol, so to speak. Although I didn't really kill him because I still love him. He's still an idol. I mean, he's still responsible for inspiration along this whole pathway. It's meeting your God and then putting a knife in it, I guess. Making a... Realizing they're human and then bringing them down to your level. Exactly, but also there's a huge misconception there, and that is that I could bring... Maybe I could bring Dan Severn down to my level, but I couldn't bring his mustache down to my level. It is of mythic proportions and... Greater than yours. Your facial hair is greater than yours. My facial hair is creating its own legacy, but it is not Dan Severn mustache level or now Don Fry mustache. So Don Fry mustache, Dan Severn mustache. Now you have like Shia versus Sunni. Right. Right. Do you think there'll be a Karl Marx like painting of Josh Barnett one day with the beard? And is that basically what you're saying? I hope so. I will actually comb my hair, unlike Marx, but... Chaos has a charm to it. It does, it does. I mean, we all thought Doc Brown in Back to the Future was quite charming. You have to throw that into the calculation where they fought. Yes. And the rules that they fought under. You know, some guy like Igor Vovchanchin won a 32-man tournament or something like that. I go, okay. Stipe and Daniel Cormier are awesome. And they may, they will, for sure, be revered for their careers, 100%. Can you say that they're particularly even better overall than Igor Vovchanchin? Maybe one of them could have beat them. Maybe one of them wouldn't have. You know, maybe Igor would have fucking got them with the knuckles right away. Well, maybe if they fought him in pride, they wouldn't have won. Maybe if they fought him bare knuckle, they wouldn't have won. I don't know. And there's something about the chaos. Like, do you put Hoys Gracie in the top 10? You know, there's something about... Top 10 of all time in terms of competitors? Capable? I don't know. I'd have to think about that. Maybe not, but I put Hoys Gracie as like pyramid level. Like, wow, dude. What an amazing man. Yeah, he's so important. Absolutely, incredibly important. But there's something about stepping into, like fighting another human being under all the uncertainty that the early UFCs had. I mean, you don't know what is going to happen. And couple that with not much money. All of it. So the purity of it, too. There's something about money, I mean, I guess it's shit for that capitalist world, but that ruins the purity of the violence. Yeah, people, given the opportunity for... Yeah, yeah. The bigger things get, the more... I love the fact that fighting has opened up to such a degree that the career business side of it, because I absolutely distinctly separate the two, the business side of it has opened up to give me far more possibilities, it's opened way more doors for me than I ever intended it to whereas the athlete side of things has, if anything, just gotten substantially worse, I would say. And some of this is due to the nature of all games will be learned, will be gamed without even the rules being broken. And once that's figured out, you need to make an adjustment. No adjustments have been made. So the game just appears to be the same game over and over and over and over and over again on ESPN+, on whatever, on whatever, on whatever. It doesn't really matter which night you watch, it's the same game constantly. And that's not because the athletes are worse or better, it's because they have had that game structure long enough that they figured out, what do you do to be the most successful at it? What is the highest percentage way of approaching it, essentially, even if you're not thinking of percentages? If we take a step back, it's really fascinating to think about the early UFCs. Did you fight Dan Saverin in the UFC? I fought him in Super Brawl. Super Brawl, so that was in the early, early days, you're undefeated. 2000. What were those early days, let's say, of mixed martial arts like? Let me tell you the day of high adventure. Dun, dun, dun, dun, dun, dun, dun, dun, dun, dun, dun. Yeah, it was so much fun, and it made you feel absolutely like you were a part of a novel, a comic book. I mean, I would love to transcribe my experiences as what I consider a second-generation MMA athlete, except I'm way too sensitive to anybody's personal, anythings that are, not even to, I'm not a gospy person. I really do believe that small people talk about others. Big people talk about ideas. But there's just some stories that you can't tell without telling the whole story, and there are so many amazing stories that could be told. People being at their best, people being at their worst. Yeah, the whole, the whole bunch of gossip. Is there something you could speak to the chaos of the time? Oh, 100%, like, well, okay, so we at AMC got connected to somebody that was throwing an event in Nampa, Idaho, and we all piled into this, and Matt Humes, Subaru wagon, and we jammed out, and we left Kirkland, and we headed over to Idaho, only to find out that there was nothing really put in place. It was absolute disrepair and chaos. They didn't have a ring, they didn't have this. It was such a bullshit adventure. But we were like, well, you know, there's hardly anywhere to fight. It's tough to find these opportunities. So, okay, well, how about this? Whoever is here to fight and is willing, all right, well, since there's no venue, there's no this, whatever, we all got gloves, we got mouthpieces, we'll just go to the park, as long as we still get paid. And so folks were kind of like, I don't know about that. The guy I was gonna fight was, he finally figured, they finally, he finally gets information on who I actually am, and I was undefeated at the time. I think I had fought Super Bowl XIII and already won that tournament. And so he's like, yeah, I had no clue. I'm so glad we didn't fight, you would have murdered me. This is, you know, what a setup. And eventually Matt had to strong arm the guy and get our money that we were supposed to all get and drive back, because his whole position was, well, there ain't no fucking way. We drove all the way out here for free. This is on you. You fucked this up, not my problem. But what is my problem is the lack of cash in my account. So fix it. You know, or me fighting my first organized fight against an AMC guy on 11 days notice through a connection to an old wrestling coach I had. And I just gathered up with all my old martial art, my old martial arts instructor that I had worked with, and we grappled in his apartment. We did Thai pads in the park. I ran a couple miles every day, and then, all right, boom, show it up. Won my fight by front choke in two minutes. And then Matt goes, okay, well, hey, you did really great. We'd like you to come back and fight again in the summer. What do you think? Okay, go back off to university. And then I think, hmm, well, that fight didn't go exactly how I wanted it to. So I gotta find a way to get more experience. I would literally fight people in the university like rec center on the old wrestling mats as they didn't all have a wrestling team. I would find anyone doing martial arts, anyone talking about getting into street fights, anyone, whatever, and just basically go, oh, you ever watch UFC? Yeah, yeah, that stuff's cool. What do you think? Oh, man, I'm super into it, man. It's badass. Rad. So would you wanna fight? I mean, it was way easier picking fights than it was getting a girlfriend. So I just, you know, path leads to resistance. I think it might be useful for us to get some advice from you. Yeah, all right. Because you've accomplished for the journey of a martial artist first. If you've accomplished some of the greatest athletes there is in the sport, if somebody who's starting out now or early on in their journey, what advice would you give on how to become a martial artist, a catch wrestler, a fighter? Well, I mean, really what it comes down to is do it because you love it. Do it for that reason and that reason alone. Most people that get into this and attempt to make any sort of professional inroads with it, you are not going to be the world champion. You probably will never even fight for a belt. You're probably not going to net make money at this. So don't do it for those reasons. Do it for the reason of the passion. Do it for the reason to be the absolute best that you can be, whatever that ends up being. You might at best only be mediocre. But you won't even be mediocre if you don't do it like you really mean it. So. So where's the kernel of the passion, would you say? Is it in the learning process itself, the improvement? I think it really depends on the person, right? I mean, there's some people that really love the fact of they feel like they're growing, right? Will to power, you're growing, growing stronger, growing better. The idea of eliminating weakness. So to which I'll quickly define weakness as things that weaken you. Not like being physically weak. Sure, you could call that weakness, but maybe you're not meant to be a super strong guy. But choosing to be weak is really a different story other than just like we're all deficient in some way or another. So that's neither here nor there. It's a matter of what you decide to do with it. And that's an infinite strength and weakness, at least the way I look at it. Like strength is choosing, regardless of the difficulty, to make improvements. Strength is even choosing to acknowledge that you do lack and accept it and then make a decision what to do with it. Yeah, but there's also, there's a bunch of stuff that just like you said, it's what you're drawn to. There's an honesty to just grappling that it seems more real than anything else you can do. Sure, well, and also- That's where the passion and love can come. Yeah, I mean, being in an environment, hopefully, that is as true as possible, would be a starter. So it's hard to be a bullshit person when you're literally trying to tear each other's arms off. Yeah, right. As you really sort of see who somebody is. I also feel like you really get to see somebody who, there are a couple instances where you really see who people are on the mats and in the bedroom. So even the aspect of self-betterment, growth along a path. I mean, hell, that's part of the device of capture for martial arts as a business. Give you a belt, put a stripe on your belt. Each of these iterations cost 20 bucks. But there's a benefit to that too. I really enjoyed the progression of belts. Sure. You know, a bit of it is OCD or whatever, but you're enjoying the recognition of your growth when you feel, when you're made to feel, when I think genuinely you do earn it. Yeah, I agree. In that process. I agree. It makes complete sense to me. It just, anything that has a goodness in its purity can also have a detriment in its perversion. And there's a value to competition. I've gotten some shit in the past for saying this. I've gotten the most value in giving everything I have to try to win and lose. So I've gotten, I remember most of the matches I've lost, and I think that's what I've gotten the most from the sport is losing. Think about it. I mean, if you really think about it, what makes you wanna actually, in detail, go over what happened? Oh, it's the time when you didn't get what you wanted. It's a time when you gave it everything you had and you came up short or failed miserably. Especially if you're embarrassed in some way. Right, and so that's usually the only time people, again, calamity, is the impetus for them to actually turn around and go, who the fuck am I? What am I doing and why am I doing it? Instead of naturally going, hmm, okay, well I won. Why? What was it that caused, and so I think part of my success is that when I win, I'm brutal. When I lose, I'm brutal. And there is no in between. So I remember losing the rematch against Noguera, and I still feel like it was a bullshit call. Like, I feel like I won that fight, but my opinion is that, and this even came up, so one of the coaches in the back was like, oh, you did great, don't feel bad, blah, blah, blah, blah, and I go, no, fuck that, I didn't finish him. I allowed the referees to make a judge decision that I think is incorrect and bad, but that came because I didn't take him out. Fuck that, no, no, he won, he's gonna get more money, he's gonna get more recognition, blah, blah, blah, blah, blah, blah, blah. I accept all this, and it's not okay. And I need to, when I get a chance to fight him again, I gotta figure out how to take this guy out. I don't wanna say forever, I'm not trying to put him six feet underground, well, when I fight, yes I am. But the point being, I need to find a way to, this is definitive, you don't get to say shit about it, because I'm the only one who can stand right now. That's the way it's gotta be. Anything less than that is not good enough. And even if I achieve that, then I gotta figure out, okay, it's not a given, how did I get to this point? How did I make that happen? Was it simply because of his own mistakes? Or was it because of my successful action? Which is it? So it was always self-critical. Always, constantly. You love movies, I read this somewhere. Yeah. You mentioned Blade Runner as a favorite. Number one of all time, the final cut, that's my go-to. So you would say Blade Runner's the greatest movie of all time. It's one of the greatest movies of all time. And it is my number. What's in the top? My top five, Blade Runner, final cut. This is the original Blade Runner. And I used to own, on tape, the original cut. DHS? Yeah. And I had the director's cut on DVD. Why Blade Runner, by the way? What connects you to it? As a kid, I just thought it was so cool. There was something about it that really spoke to me. The whole cyberpunk landscapes, and this guy chasing down rogue androids, replicants. And all this. Is it just the entire cyberpunk universe? Or is it just robots as well? No, it's, I mean, the cyberpunk universe is part of it. On the surface, I've always tended towards dark subject matter, like things that are of the dark, so to speak, are things that I've always been gravitated towards. I think maybe part of it is that the things that are darker are more accepting and more up front with death. And perhaps, I think, maybe that is what was. Yeah, somehow more honest, perhaps. There's also the aspect of rebelliousness, usually. Like there is, I was never one to wanna just do what somebody told me to do. I'm not sitting around trying to always be such a radical individual that I can't take orders. No, in fact, I'm more than willing to take orders from somebody that I feel is competent and has merit and reason behind what they're doing. And it makes, like, okay, yeah, yeah, yeah. I'm 100% for it. Not only can I take orders, I will help you achieve whatever it is if I think it's worthwhile, even at my own expense. But to get to that point is a rarity. Like it's not a given. And so you can even imagine being a grade school teacher and this kid doesn't respect you and he doesn't really think you're that smart. They don't really appreciate that. So cyberpunk is number one. What else is there? Cyberpunk is kinda number one. It's an environment I love, but at the same time, Conan the Barbarian by John Milius is one of my favorite films of all time. And that's such a pure film, in a way. The motivations are pure. They're very easy to follow, but not lacking in depth. It's not just explosions and teal and orange. It's more on the human condition. And I love it. And it's shot incredibly well. It's got an incredible soundtrack. Yeah, I fucking love it. But with Blade Runner also, in a deeper sense, again, the human condition. You start seeing, what is being? What is being human? How does this relate to, if you can make it and you can tell it what to do, at what point is it like you should or you shouldn't? Why do you get to determine what's alive and what's not? What's a life that should be allowed to live and what isn't? And what would be the strain of being Roy Batty and seeing all these incredible moments that with his passing will no longer exist? Especially if he hasn't had a chance to put that flame into another torch, so to speak. If he hasn't written them down, if he hasn't passed them down to somebody else. Gone like tears in the rain. Like tears in the rain, that scene is incredible. But it's funny, because those two universes are very different, according to the barbarian and the cyberpunk. Because that makes me curious about what else might be in the list at the top. Well, let me think. It's a pretty. Do you like the Godfather type of universes? No, I mean, I'm sure the Godfather. I've never actually even watched the whole Godfather. No, but also, was it Casino, Goodfellas? Goodfellas is a good movie, but no, that's not in my top. It's a good flick, but it doesn't really do it for me. If people really wanna get into this a little more, I did make a list of 100 of my favorite movies on my Facebook fan page. Nice. But. Do you remember some? Oh, yeah, Blazing Saddles is on there, Raiders of the Lost Ark, Valhalla Rising by Nicholas from Winding Refn, Maniac by William Lustig. It's a 1980 gnarly, video-nasty horror movie about a serial killer who murders women and scalps them. And it's gnarly as hell and very brutal and very bleak. I mean, it's the kind of thing that a lot of people would have a real hard time watching. But one, again, I like things that are dark. But two, I thought the performances were fantastic in this film, and they really got out, I think, what the underlying thing was. And it was a guy who was basically just run amok by the overbearing mother Jungian archetype. And she imparted her insanity into him. But yet, there was this aspect you could see of him wanting to try and actually be able to be in the world and have love and have a feminine companionship to go with his masculine aspect. But he had no way of understanding how to really make that happen. And he had a complete negative connotation to the feminine. So it's his struggle with, and there's a little part in the movie where he somehow comes across this model or something, and he starts to feel like maybe he might be able to actually have a relationship with somebody and it goes somewhere. But yeah, even the Elijah Wood remake, I felt, was really well done and captured most of the essence of what the movie was about. But I still feel like the original by William Lustig is the best. What's the greatest love movie of all time? It is love movie of all time. So like something where love is, I mean, I suppose love underlies most of these movies, and especially if you like the dark. I mean, hell, Takashi Miike's films are all about family, of all things, as bonkers as those movies are. The general theme is family almost entirely in all of his films. Yeah, there's very, I mean, even you can argue Bladerunner, yeah, it's everywhere. The greatest love film of all time? Let's interrupt, I mean, is Excalibur a film about love? What's Excalibur about? King Arthur. Excalibur is about Arthur becoming king of the Britons and his love of his country and his love of Guinevere. But eventually, yeah, it becomes more of about the necessity for the king to love, to hold Excalibur, to stay, to realize that while if you're the king, you can love your wife and you can love your best friend, and they may fuck each other behind your back and as they fall in love too, but at the end of the day, your love has to be to the country and everyone else first and not your own personal wants, which made a much more interesting story when you have Carmen Berenina and, oh, what is that one? It's a German opera, but, and horses and slo-mo and sword fights and an epic death scene between Arthur and his son. Okay, now I definitely have to watch it and I haven't watched it in embarrassing. It is John Borman's second film in Hollywood, his first one being Point Blank with Lee Marvin, which is also on top, one of the upper echelon movies on my list, derived from a book by, called The Outfit by, what is his name? Uh, I forget, but Darwin Cook, the comics illustrator, he did, Donald Westlake wrote, so Darwin Cook does an amazing comic book send-up of Darwin Cook's novels, and they are fucking incredible. So anyways, but the Point Blank with Lee Marvin, you know, it's a man driven by purpose, revenge, but also by like really pure motivations. He wants his money. He was betrayed, and he wants his cash, because this is what he agreed to do the thing for, and this is, which also is part of the reason why I like No Country for Old Men so much, which I felt was a great movie, even better book, but I remember talking to my friend, and I go, you know, Anton Chigurh is the most pure human being in that whole book. Well, that guy's the villain. I go, ha ha, is he evil? Like, he's the one, he lies to no one, he does everything he says he will do, he always follows his word, and on the rare occasion, he allows fate to make a decision, as he figures like, well, whatever all led us to here will lead us one way or the other, and if we're at this crossroads, how is there any better or worse way than to do it over a coin flip? And so that whole scene where the guy's going, well, what am I putting up? And he goes, everything. You've been putting it up every day of your life, and that's true. Everything we do is a decision, is a calling, is a choice. And then it bummed me out that they reduced the last interaction between Chigurh and what's-his-face's wife, and he finally finds her, and she's like, you don't have to do this. I mean, he's like, yes, I do. This is the way it is. You can think that your life could have turned out any sort of way, you could have done this, you could have done that, but the reality is that this is the way your life is, and it's the way it was always going to be. The fact that I'm here is the end of it, and that's that. Yeah, it's funny, if you're honest, this is what dark movies reveal, that the villains are the purest of humans and can teach us the most profound lessons, and that's certainly an example of it. What do you think, the big, ridiculous, last philosophical question, what do you think is the meaning of this whole thing we've got going on, of life and existence on Earth from your individual perspective, but the entirety of the human species? Life, the universe, and everything? Yeah. Don't. Don't. Don't. Don't. Don't. Don't. Don't. Don't. We could just leave it at that. You knew exactly where I was going. I love it. Josh, I love you very much, you've been a huge inspiration. I have a friend who, she said, do you know Lex Friedman? Have you gone on Lex's con? And I go, yes, I know Lex Friedman is. I've sadly been way too long in contact without making it happen for too long, and yes, I will 100%, I even cut a shirt at the beginning of the pandemic to make my own little mask at one point due to the Lex process. Yeah. And I love it, Josh. I can't really hear you, but I'm demonstrating. Just see it through, but this has been a blast. And next time. I hope you come back. Next time, let's drink some of the Warbringer whiskey. I will bring some Warmaster. I wasn't sure if you imbibed at all in spirits. 100%. It felt a little weird to do it early on in the morning, especially because I'm flying out there. Does it though? I mean, I've had some wonderful morning whiskey at times. Now that you've mentioned it, it doesn't at all. So next time, let's make sure, what Joe Rogan calls the adult beverages, let's make sure we indulge. I have zero reservations for doing such a thing. I'm into it. Josh, thanks for talking today. My pleasure. Thanks for listening to this conversation with Josh Barnett. And thank you to our sponsors, Munk Pack Low Carb Snacks, Element Electrolyte Drink, 8 Sleep Self-Cooling Mattress, and Rev Transcription and Captioning Service. Click the sponsor links to get a discount and to support this podcast. And now let me leave you with some words from Sun Tzu in the art of war. The supreme art of war is to subdue the enemy without fighting. Thank you for listening and hope to see you next time.

https://youtu.be/YJWPowbCK_I

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Tim Urban: Elon Musk, Neuralink, AI, Aliens, and the Future of Humanity | Lex Fridman Podcast #264

If you read a half hour a night, the calculation I came to is that you can read a thousand books in 50 years. All of the components are there to engineer intimate experiences. Extraterrestrial life is a true mystery, the most tantalizing mystery of all. How many humans need to disappear for us to be completely lost? The following is a conversation with Tim Urban, author and illustrator of the amazing blog called Wait, But Why. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, dear friends, here's Tim Urban. You wrote a Wait, But Why blog post about the big and the small, from the observable universe to the atom. What world do you find most mysterious or beautiful, the very big or the very small? The very small seems a lot more mysterious. And I mean, the very big I feel like we kind of understand. I mean, not the very, very big, not the multiverse, if there is a multiverse, not anything outside of the observable universe. But the very small, I think we really have no idea what's going on, or very, much less idea. But I find that, so I think the small is more mysterious, but I think the big is sexier. I just cannot get enough of the bigness of space and the farness of stars. And it just continually blows my mind. I mean, we still, the vastness of the observable universe has the mystery that we don't know what's out there. We know how it works, perhaps. Like, general relativity can tell us how the movement of bodies works, how they're born, all that kind of things. But like, how many civilizations are out there? How many, like, what are the weird things that are out there? Oh yeah, life, well, extraterrestrial life is a true mystery, the most tantalizing mystery of all. But that's like our size. So that's maybe it's that the actual, the big and the small are really cool, but it's actually the things that are potentially our size that are the most tantalizing. Potentially our size is probably the key word. Yeah, I mean, I wonder how small intelligent life could get. Probably not that small. And I assume that there's a limit that you're not gonna, I mean, you might have like a whale, blue whale-sized intelligent being, that would be kind of cool. But I feel like we're in the range of order of magnitude smaller and bigger than us for life. But maybe not, maybe you could have some giant life form. Just seems like, I don't know, there's gotta be some reason that anything intelligent between kind of like a little tiny rodent or finger monkey up to a blue whale on this planet. I don't know, maybe when you change the gravity and other things. Well, you could think of life as a thing of self-assembling organisms and they just get bigger and bigger and bigger. Like there's no such thing as a human being. A human being is made up of a bunch of tiny organisms that are working together. And we somehow envision that as one entity because it has consciousness. But maybe it's just organisms on top of organisms. Organisms all the way down, turtles all the way down. So like Earth can be seen as an organism for people, for alien species that's very different. Like why is the human the fundamental entity that is living and then everything else is just either a collection of humans or components of humans? I think of it kind of as if you think about, I think of like an emergence elevator. And so you've got an ant is on one floor and then the ant colony is a floor above. Or maybe there's even units within the colony that's one floor above and the full colony is two floors above. And to me, I think that it's the colony that is closest to being the animal. It's like the individual thing that competes with others while the individual ants are like cells in the animal's body. We are more like a colony in that regard. But the humans are weird because we kind of, I think of it if emergence happens in an emergence tower, where you've got kind of, as I said, cells and then humans and communities and societies. Ants are very specific. The individual ants are always cooperating with each other for the sake of the colony. So the colony is this unit that is the competitive unit. Humans can kind of go, we take the elevator up and down emergence tower psychologically. Sometimes we are individuals that are competing with other individuals and that's where our mindset is. And then other times we get in this crazy zone, a protest or a sporting event, and you're just chanting and screaming and doing the same hand motions with all these other people and you feel like one. You feel like one and you'd sacrifice yourself. And no, that's what soldiers. And so our brains can kind of psychologically go up and down this elevator in an interesting way. Yeah, I wonder how much of that is just the narrative we tell ourselves. Maybe we are just like an ant colony. We're just collaborating always. Even in our stories of individualism, of like the freedom of the individual, like this kind of isolation, lone man on an island kind of thing. We're actually all part of this giant network of maybe one of the things that makes humans who we are is probably deeply social. The ability to maintain not just a single human intelligence but like a collective intelligence. And so this feeling like individual is just because we woke up at this level of the hierarchy. So we make it special, but we very well could be just part of the ant colony. This whole conversation, I'm either going to be doing a Shakespearean analysis of your Twitter, your writing, or very specific statements that you've made. So you've written answers to a mailbag of questions. The questions were amazing, the ones you've chosen, and your answers were amazing. So on this topic of the big and the small, somebody asked, are we bigger than we are small? Or smaller than we are big? Who's asking these questions? This is really good. You have amazing fans. Okay, so where do we sit at this level of the very small to the very big? So are we bigger or are we small? Are we bigger than we are small? I think it depends on what we're asking here. So if we're talking about the biggest thing that we kind of can talk about without just imagining is the observable universe, the Hubble sphere. And that's about 10 to the 26th meters in diameter. The smallest thing we talk about is a Planck length. But you could argue that that's kind of an imaginary thing. But that's 10 to the negative 35. Now we're about, conveniently, about 10 to the one. Not quite, 10 to the zero. We're about 10 to the zero meters long. So it's easy because you can just look and say, okay, well, for example, atoms are like 10 to the negative 15th or 10 to the negative 16th meters across, right? If you go 10 to the 15th or 10 to the 16th, which is right, that's now, so an atom to us is us to this. You get to like nebulas. Smaller than a galaxy and bigger than the biggest star. So we're right in between nebula and an atom. Now, if you want to go down to quark level, you might be able to get up to galaxy level. When you go up to the observable universe, you're getting down on the small side to things that we, I think, are mostly theoretically imagining are there and hypothesizing are there. So I think, as far as real world objects that we really know a lot about, I would say we are smaller than we are big. But if you want to go down to the Planck length, we're very quickly, we're bigger than we are small. If you think about strings. Yeah, strings, exactly, string theory and so on. That's interesting. But I think like you answer, no matter what, we're kind of middle-ish. Yeah, I mean, here's something cool. If a human is a neutrino, and again, neutrino, the size doesn't really make sense. It's not really a size. But when we talk about some of these neutrinos, I mean, if a neutrino is a human, a proton is the sun. So that's like, I mean, a proton's real small, like really small. And so, yeah, the small gets like crazy small very quickly. Very quickly. Let's talk about aliens. We already mentioned it. Let's start just by with the basic. What's your intuition as of today? This is a thing that could change day by day. But how many alien civilizations out there? Is it zero? Is it a handful? Is it almost endless, like the observable universe, or the universe is teeming with life? If I had a gun to my head, I have to take a guess. I would say it's teeming with life. I would say there is. I think running a Monte Carlo simulation, this paper by Anders Sandberg and Drexler and a few others a couple years ago, I think you probably know about it. I think the mean, you know, using different, using different, you know, running through a randomized rate equation multiplication, you ended up with 27 million as the mean of intelligent civilizations in the galaxy, in the Milky Way alone. And so then if you go outside the Milky Way, that would turn into trillions. That's the mean. Now what's interesting is that there's a long tail because they believe some of these multipliers in the Drake equation, so for example, the probability that life starts in the first place, they think that the kind of range that we use is for that variable is way too small. And that's constraining our possibilities. And if you actually extend it to, you know, some crazy number of orders of magnitude, like 200, they think that that variable should be, you get this long tail where, I forget the exact number, but it's like a third or a quarter of the total outcomes have us alone. Like, I think it's a sizable percentage has us as the only intelligent life in the galaxy, but you can keep going in that. I think there's like, you know, a non-zero like legitimate amount of outcomes there that have us as the only life in the observable universe at all is on Earth. I mean, it seems incredibly counterintuitive. It seems like, you know, you mentioned that people think you must be an idiot because if you picked up one grain of sand on a beach and examined it and you found all these little things on it, it's like saying, well, maybe this is the only one that has that. And it's like, probably not. They're probably, most of the sand probably, or a lot of the sand, right? So, and then the other hand, we don't see anything. We don't see any evidence, you know, which of course people would say that the people who scoff at the concept that we're potentially alone, they say, well, of course, there's lots of reasons we wouldn't have seen anything and they can go list them. And they're very compelling, but we don't know. And the truth is if there were, if this were a freak thing, I mean, we don't, if this were a completely freak thing that happened here, whether it's life at all or just getting to this level intelligence, that species, whoever it was, would think there must be lots of us out there and they'd be wrong. So just being, again, using the same intuition that most people would use, I'd say there's probably lots of other things out there. Yeah, and you wrote a great blog post about it, but to me, the two interesting reasons that we haven't been in contact, I too have an intuition that the universe is teeming with life. So one interesting is around the great filter. So we're either, the great filter is either behind us or in front of us. So the reason that's interesting is you get to think about what kind of things ensure or ensure the survival of an intelligent civilization or lead to the destruction of intelligent civilization. That's a very pragmatic, very important question to always be asking. And we'll talk about some of those. And then the other one is I'm saddened by the possibility that there could be aliens communicating with us all the time. In fact, they may have visited. And we're just too dumb to hear it, to see it. Like the idea that the kind of life that can evolve is just the range of life that can evolve is so large that our narrow view of what is life and what is intelligent life is preventing us from having communication with them. But then they don't seem very smart because if they were trying to communicate with us, they would surely, if they were super intelligent, they would be very, I'm sure if there's lots of life, we're not that rare, we're not some crazy weird species that hears and has different kinds of ways of perceiving signals. So they would probably be able to, if you really wanted to communicate with an Earth-like species, with a human-like species, you would send out all kinds of things. You'd send out radio waves and you send out gravity waves and lots of things. So if they're communicating in a way, they're trying to communicate with us and it's just we're too dumb to perceive the signals, it's like, well, they're not doing a great job of considering the primitive species we might be. So I don't know, I think if a super intelligent species wanted to get in touch with us and had the capability of, I think probably they would. Well, they may be getting in touch with us, they're just getting in touch with the thing that we humans are not understanding, that they're getting in touch with us. I guess that's what I was trying to say is there could be something about Earth that's much more special than us humans. Like the nature of the intelligence that's on Earth or the thing that's of value and that's curious and that's complicated and fascinating and beautiful might be something that's not just like tweets, okay? Like English language that's interpretable or any kind of language or any kind of signal, whether it's gravity or radio signal that humans seem to appreciate. Why not the actual, it could be the process of evolution itself. There could be something about the way that Earth is breathing, essentially, through the creation of life and this complex growth of life. It's a whole different way to view organisms and view life that could be getting communicated with. And we humans are just a tiny fingertip on top of that intelligence. And the communication is happening with the main mothership of Earth versus us humans that seem to treat ourselves as super important and we're missing the big picture. I mean, it sounds crazy, but our understanding of what is intelligence, of what is life, what is consciousness is very limited. And it seems to be, and just being very suspicious, it seems to be awfully human-centric. Like this story, it seems like the progress of science is constantly putting humans down on the importance, like on the cosmic importance, the ranking of how big we are, how important we are. That seems to be, the more we discover that's what's happening, and I think science is very young. And so I think eventually we might figure out that there's something much, much bigger going on, that humans are just a curious little side effect of the much bigger thing. That's what, I mean, that, as I'm saying, it just sounds insane, but. Well, it just, it sounds a little like religious. It sounds like a spiritual. It gets to that realm where there's something that more than meets the eye. Well, yeah, but not, so religious and spiritual often have this kind of woo-woo characteristic, like when people write books about them and then go to wars over whatever the heck is written in those books. I mean more like it's possible that collective intelligence is more important than individual intelligence, right? It's the ant colony. What's the primal organism? Is it the ant colony or is it the ant? Yeah, I mean, humans, just like any individual ant can't do shit, but the colony can do, they make these incredible structures and has this intelligence. And we're exactly the same. I mean, you know the famous thing that no one, no human knows how to make a pencil. You heard this? No. Basically, I mean. This is great. There's not, a single human out there has absolutely no idea how to make a pencil. So you have to think about, you have to get the wood, the paint, the different chemicals that make up the yellow paint. The eraser is a whole other thing. The metal has to be mined from somewhere and then the graphite, whatever that is. And there's not one person on earth who knows how to kind of collect all those materials and create a pencil. But together, that's child's play. It's just one of the easiest things. So, you know, the other thing I like to think about, I actually put this as a question on the blog once. There's a thought experiment and I actually want to hear what you think. So if a witch, kind of a dickish witch comes around and she says, I'm going to cast a spell on all of humanity and all material things that you've invented are going to disappear all at once. So suddenly we're all standing there naked. There's no buildings. There's no cars and boats and ships and no mines, nothing. Right, it's just the stone age earth and a bunch of naked humans, but we're all the same. We have the same brain. So we're all know what's going on. And we all got a note from her. So we understand the deal. And she says, she communicated to every human, here's the deal. You lost all your stuff. You guys need to make one working iPhone 13. And you make one working iPhone 13 that could pass in the Apple store today, you know, in your previous world for an iPhone 13, then I will restore everything. How long do you think? And so everyone knows this is the mission. We're all aware of the mission, everyone, all humans. How long would it take us? That's a really interesting question. So obviously if you do a random selection of 100 or a thousand humans within the population, I think you're screwed to make that iPhone. I tend to believe that there's fascinating specialization among the human civilization. Like there's a few hackers out there that can like solo build an iPhone. But with what materials? So no materials whatsoever. It has to, I mean, it's virtually, I mean, okay. You have to build factories. I mean, to fabricate. Okay. And how are you gonna mine them? You know, you gotta mine the materials where you don't have any cranes. You don't have any, you know. Okay, you 100% have to have the, everybody's naked. Everyone's naked and everyone's where they are. So you and I would currently be naked. It's on the ground in what used to be Manhattan. So no buildings. No, Grassy Island. Yeah. So you need a naked Elon Musk type character to then start building a company. You have to have a large company then. Right. As soon as you know where he, you know, where is everyone? You know, shit, how am I gonna find other people I need to talk to? But we have all the knowledge of. Yeah, everyone has the knowledge that's in their current brains. Yeah. I've met some legit engineers. Crazy polymath people. Yeah. But the actual labor of, because you said, it's like the original Mac, like the Apple II, that can be built. But. Even that, you know. Even that's gonna be tough. Well, I think part of it is a communication problem. If you could suddenly have, you know, someone, if everyone had a walkie talkie and there was, you know, a couple, you know, 10 really smart people were designated the leaders, they could say, okay, I want, you know, everyone who can do this to walk west, you know, until you get to this little hub and everyone else, you know, and they could actually coordinate, but we don't have that. So it's like people just, you know, and then what I think about is, so you've got some people that are like trying to organize and you'll have a little community where a couple hundred people have come together and maybe a couple thousand have organized and they designated one person, you know, as the leader, and then they have sub leaders and okay, we have a start here. We have some organization. You're also gonna have some people that say, good, humans were a scourge upon the earth and this is good. And they're gonna try to sabotage. They're gonna try to murder the people with the, and who know what they're talking about. The elite that possess the knowledge. Well, and so everyone, maybe everyone's hopeful for the, you know, we're all civilized and hopeful for the first 30 days or something. And then things start to fall off. They, you know, people get, start to lose hope and there's new kinds of, you know, new kinds of governments popping up, you know, new kinds of societies and they're, you know, they don't play nicely with the other ones. And I think very quickly, I think a lot of people will just give up and say, you know what, this is it. We're back in the stone age. Let's just create, you know, agrarian. We don't also don't know how to farm. No one knows how to farm. There's like, even the farmers, you know, a lot of them are relying on their machines. And so we also, there's gonna be a lot of mass starvation. And that, you know, when you're trying to organize, a lot of people are, you know, coming in with, you know, Spears they've fashioned and trying to murder everyone who has food. That's an interesting question. Given today's society, how much violence would that be? We've gotten softer, less violent. And we don't have weapons. So that's something. We have really primitive weapons now. But we have, and also we have a kind of ethics where murder is bad. We used to be less, like human life was less valued and the past, so murder was more okay, like ethically. But in the past, they also were really good at figuring out how to have sustenance. They knew how to get food and water because they, so we have no idea. Like the ancient hunter-gatherer societies would laugh at what's going on here. They'd say, you guys, you don't know what you're, none of you know what you're doing. And also the amount of people, feeding this amount of people in a very, in a Stone Age, you know, civilization, that's not gonna happen. So New York and San Francisco are screwed. Well, whoever's not near water is really screwed. So that's funny, you're near a river, a freshwater river. Anyway, it's a very interesting question. And what it does, this and the pencil, it makes me feel so grateful and like excited about, like man, our civilization is so cool. And this is, talk about collective intelligence. Humans did not build any of this. It's collective human, collective humans is a super intelligent being that is, that can do absolutely, especially over long periods of time, can do such magical things. And we just get to be born. When I go out, when I'm working and I'm hungry, I just go click, click, click, and like a salad's coming. The salad arrives. If you think about the incredible infrastructure that's in place for that quickly, it's just the internet to, you know, the electricity, first of all, that's just powering the things, you know, where the amount of structures that have to be created for that electricity to be there. And then you've got the, of course, the internet. And then you have this system where delivery drivers, and they're riding bikes that were made by someone else, and they're going to get the salad. And all those ingredients came from all over the place. I mean, it's just, so I think it's like, I like thinking about these things because it makes me feel like just so grateful. I'm like, man, it would be so awful if we didn't have this. And people who didn't have it would think this was such magic we live in. And we do, and like, cool, that's fun. Yeah, one of the most amazing things when I showed up, I came here at 13 from the Soviet Union, and the supermarket was, people don't really realize that, but the abundance of food, it's not even, so bananas was the thing I was obsessed about. I just ate bananas every day for many, many months because I haven't had bananas in Russia. And the fact that you can have as many bananas as you want, plus they were like somewhat inexpensive relative to the other food. And the fact that you can somehow have a system that brings bananas to you without having to wait in a long line, all of those things, it's magic. I mean, also imagine, so first of all, the ancient hunter-gatherers, you picture the mother gathering and eating all this fresh food. No, so do you know what an avocado used to look like? It was a little, like a sphere. And the fruit of it, the actual avocado part, was like a little tiny layer around this big pit that took up almost the whole volume. We've made the crazy robot avocados today that have nothing to do with what they, so same with bananas, these big, sweet, you know, not infested with bugs and, you know, they used to eat the shittiest food. And they're eating uncooked meat, or maybe they cook it and it's gross and things rot. So you go to the supermarket and it's just, it's just A, it's like crazy super-engineered cartoon food, fruit and food. And then it's all this processed food, which we complain about. In our society, we complain about, we need too much processed. That's a, this is a good problem. If you imagine what they would think, oh my God, a cracker, you know how delicious a cracker would taste to them? You know, candy, you know, pasta and spaghetti. They never had anything like this. And then you have, from all over the world, I mean, things that are grown all over the place, all here in nice little racks, organized, and on a middle-class salary, you can afford anything you want. I mean, it's, again, just like incredible gratitude. Like, ah, yeah. And the question is, how resilient is this whole thing? I mean, this is another darker version of your question is, if we keep all the material possessions we have, but we start knocking out some percent of the population, how resilient is the system that we built up? Or if we rely on other humans and the knowledge that's built up on the past, the distributed nature of knowledge, how much does it take? How many humans need to disappear for us to be completely lost? Well, I'm trying to go off one thing, which is Elon Musk says that he has this number, a million, in mind, as the order of magnitude of people you need to be on Mars to truly be multi-planetary. Multi-planetary doesn't mean, you know, like, when Neil Armstrong goes to the moon, they call it a great leap for mankind. It's not a great leap for anything. It is a great achievement for mankind. And I always think about, if the first fish to kind of go on land just kind of went up and gave the shore a high five and goes back into the water, that's not a great leap for life. That's a great achievement for that fish, and there should be a little statue of that fish in the water, and everyone should celebrate the fish. But when we talk about a great leap for life, it's permanent. It's something that from now on, this is how things are. So this is part of why I get so excited about Mars, by the way, is because you can count on one hand, like, the number of great leaps that we've had, you know, like, no life to life, and single cell or simple cell to complex cell, and single cell organisms to animals, to, you know, multi-cell animals, and then ocean to land, and then one planet to two planets. Anyway, diversion. But the point is that we are officially, that leap for all of life, you know, has happened once the ships could stop coming from Earth, because there's some horrible, catastrophic World War III, and everyone dies on Earth, and they're fine, and they can turn that certain X number of people into seven billion, you know, population that's thriving just like Earth. They can build ships, they can come back and recolonize Earth, because now we are officially multi-planetary, where it's just self-sustaining. He says a million people is about what he thinks. Now, that might be a specialized group. That's a very specifically, you know, selected million that has very, very skilled million people, not just maybe the average million on Earth. But I think it depends what you're talking about. But I don't think, you know, so one million is 1 7000th, 1 8000th of the current population. I think you need a very, very, very small fraction of humans on Earth to get by. Obviously, you're not gonna have the same thriving civilization if you get to a too small a number, but it depends who you're killing off, I guess, is part of the question. Yeah. If you killed off half of the people just randomly right now, I think we'd be fine. It would be obviously a great, awful tragedy. I think if you killed off three quarters of all people randomly, just three out of every four people drops dead, I think we'd have, obviously, the stock market would crash. We'd have a rough patch, but I almost can assure you that the species would be fine. Well, because the million number, like you said, it is specialized. So I think, because you have to do this, you have to basically do the iPhone experiment. Like, literally, you have to be able to manufacture computers. Yeah, everything. If you're gonna have the self-sustaining, it means you can, any major important skill, any important piece of infrastructure on Earth can be built there just as well. It'd be interesting to list out what are the important things, what are the important skills. Yeah, I mean, you have to feed everyone. So mass farming, things like that. You have mining, these questions. It's like, the materials might be, I don't know, five miles, two miles underground, I don't know what the actual, but it's amazing to me just that these things got built in the first place. And they never got, no one built the first, the mine that we're getting stuff for the iPhone for probably wasn't built for the iPhone. Or in general, early mining was for, I think, obviously, I assume the Industrial Revolution when we realized, oh, fossil fuels, we wanna extract this magical energy source, I assume that mining took a huge leap. Without knowing very much about this, I think you're gonna need mining, you're gonna need a lot of electrical engineers. If you're gonna have a civilization like ours, and of course, you could have oil and lanterns, we could go way back, but if you're trying to build our today thing, you're gonna need energy and electricity and mines that can bring materials, and then you're gonna need a ton of plumbing and everything that entails. And like you said, food, but also the manufacturers, so turning raw materials into something useful, that whole thing, like factories, some supply chain, transportation. Right, I mean, you think about, when we talk about world hunger, one of the major problems is there's plenty of food, and by the time it arrives, most of it's gone bad in the truck, in kind of an impoverished place. So it's like, again, we take it so for granted, all the food in the supermarket is fresh, it's all there, and which always stresses me, if I were running a supermarket, I would always be so miserable about things going bad on the shelves, or if you don't have enough, that's not good, but if you have too much, it goes bad anyway. Of course, there would be entertainers too. Like somebody would have a YouTube channel that's running on Mars. There is something different about a civilization on Mars and Earth existing versus a civilization in the United States versus Russia and China. Like that's a fundamentally different distance, like philosophically. Will it be like fuzzy? We know there'll be like a reality show on Mars that everyone on Earth is obsessed with. I think if people are going back and forth enough, then it becomes fuzzy. It becomes like, oh, our friend's on Mars, and there's like this Mars versus Earth, and it'd become like fun tribalism. I think if people don't really go back and forth, and it really, they're there for, I think it could get kind of like, oh, we hate a lot of us versus them stuff going on. There could be also war in space for territory. So as first colony happens, China, Russia, or whoever, the European, different European nations, Switzerland finally gets their act together and starts wars. This is supposed to, staying out of all of them. Yeah, there's all kinds of crazy geopolitical things that like we have not even, no one's really even thought about too much yet that like, that could get weird. Think about the 1500s, when it was suddenly like a race to like, you know, colonize or capture land or discover new land that hasn't been, so it was like this new frontiers. There's not really, the land is not, the thing about Crimea was like, this huge thing, this tiny peninsula switched. That's how like optimized everything has become. Everything is just like really stuck. Mars is a whole new world of like, territory, naming things, and it's a chance for new kind of governments maybe, or maybe it's just the colonies of these governments, so we don't get that opportunity. I think it'd be cool if there's new countries being, you know, totally new experiments. And that's fascinating, because Elon talks exactly about that, and I believe that very much. Like that should be, like from the start, they should determine their own sovereignty. Like they should determine their own thing. There was one modern democracy in late 1700s, the US. I mean, it was the only modern democracy, and now, of course, there's hundreds, or dozens, many dozens. But I think part of the reason that was able to start, I mean, it's not that people didn't have the idea, people had the idea. It was that they had a clean slate, new place, you know, and they suddenly were, so I think it would be a great opportunity to have. There's a lot of people who've done that, you know, oh, if I had my own government on an island, my own country, what would I do? And the US founders actually had the opportunity, that fantasy, they were like, we can do it. Let's make, okay, what's the perfect country? And they tried to make something. Sometimes progress is, it's not held up by our imagination. It's held up by just, there's no, you know, blank canvas to try something on. Yeah, it's an opportunity for a fresh start. You know, the funny thing about the conversation we're having is not often had. I mean, even by Elon, he's so focused on Starship and actually putting the first human on Mars. I think thinking about this kind of stuff is inspiring. It makes us dream, it makes us hope for the future. So, and it makes us, somehow, like thinking about civilization on Mars is helping us think about the civilization here on Earth. Yeah, totally. How we should run it. What do you think are, like in our lifetime, are we gonna, I think any effort that goes to Mars, the goal is in this decade. Do you think that's actually gonna be achieved? I have a big bet, $10,000 with a friend when I was drunk. Okay. In an argument. This is great. Neil Armstrong of Mars, whoever he or she may be, will set foot by the end of 2030. Now, this was probably 2018 when I had this argument. So, like what if it? So, a human has to touch Mars by the end of 2030. Oh, by the year 30. Yeah, by January 1st, 2031. Yeah. So. Did you agree on the time zone or what? No, no, yeah, if it's coming on that exact day, that's gonna be really stressful. But anyway, I think that there will be. That was 2018, I was more confident then. I think it's gonna be around this time. I mean, I still won the general bet, because his point was, you are crazy, this is not gonna happen in our lifetimes, or not for many, many decades. And I said, you're wrong. You don't know what's going on in SpaceX. I think if the world depended on it, I think probably SpaceX could probably, I mean, I don't know this, but I think the tech is almost there. Like, I don't think, of course, it's delayed many years by safety. So, they first wanna send a ship around Mars, and they wanna land a cargo ship on Mars, and there's the moon on the way, too. Yeah, yeah, there's a lot. But I think the moon, a decade before, seemed like magical tech that humans didn't have. This is like, no, we can, it's totally conceivable that this, you've seen Starship, like it's, it is a interplanetary transport system, that's what they used to call it. SpaceX, the way they do it is, every time they do a launch, something fails, usually, when they're testing, and they learn a thousand things. The amount of data they get, and they improve so, each one has, it's like they've moved up like eight generations in each one. Anyway, so, it's not inconceivable that pretty soon they could send a Starship to Mars and land it. There's just no good reason, I don't think that they couldn't do that. And so, if they could do that, they could, in theory, send a person to Mars pretty soon. Now, taking off from Mars and coming back, again, I think, I don't think anyone would want to be on that voyage today, because there's just, you know, they're still, it's still amateur hour here, getting that perfect. I don't think we're too far away now, the question is, so it's every, so every 26 months, Earth laps Mars, right? It's like the sinusoidal, or orbit, or whatever it's called, the period, 26 months. So, it's right now, like in the evens, like 2022 is gonna have one of these, 2020, late 2024, so people could, this was the earliest estimate I heard. Elon said, maybe we can send people to Mars in 2024, you know, to land in early 2025. That is not gonna happen, because that included 2022 sending a cargo ship to Mars, maybe even one in 2020, and so I think they're not quite on that schedule, but to win my bet, 2027 I have a chance, and 2029 I have another chance. We're not very good at like backing up and seeing the big picture, we're very distracted by what's going on today, and what we can believe, because it's happening in front of our face. There's no way that humans are gonna be landing on Mars, and it's not gonna be the only thing everyone is talking about, right? I mean, it's gonna be the moon landing, but even bigger deal, going to another planet, right? And for it to start a colony, not just to, again, high five and come back. So, this is like, the 2020s, maybe the 2030s, is gonna be the new 1960s, we're gonna have a space decade, I'm so excited about it. And again, it's one of the great leaps for all of life happening in our lifetimes, like that's wild. To paint a slightly cynical possibility, which I don't see happening, but I just wanna put sort of value into leadership. I think it wasn't obvious that the moon landing would be so exciting for all of human civilization. Some of that have to do with the right speeches, with the space race. Like, space, depending on how it's presented, can be boring. I don't think it's been that so far, but I've actually- I agree, I think space is quite boring right now. Not, you know, SpaceX is super, but like 10 years ago, space. Some writer, I forget who, wrote, it's like the best magic trick in the show happened at the beginning, and now they're starting to do this easy magic. You know, it's like you can't go in that direction, and the line that this writer said is like, watching astronauts go up to the space station, after watching the moon, is like watching Columbus sail to Ibiza. It's just like, you know, everything is so impractical. You're going up to the space station not to explore, but to do science experiments in microgravity, and you're sending rockets up, you know, mostly here and there there's a probe, but mostly you're sending them up to put satellites, you know, for direct TV, you know, and I or whatever it is. It's kind of like lame earth industry, you know, usage. So I agree with you, space is boring there. The first human setting foot on Mars, that's gotta be a crazy global event. I can't imagine it not being. Maybe you're right, maybe I'm taking for granted the speeches in the space race and the- I think the value of, I guess what I'm pushing, is the value of people like Elon Musk, and potentially other leaders that hopefully step up, is extremely important here. Like I would argue without the publicity of SpaceX, it's not just the ingenuity of SpaceX, but like what they've done publicly by having a figure that tweets, and all that kind of stuff like that, that's a source of inspiration. That NASA wasn't able to quite pull off with the shuttle. That's one of his two reasons for doing this. SpaceX is just for two reasons. One, life insurance for the species. If you're, I always think about it this way, if you're an alien on some far away planet, and you're rooting against humanity, and you win the bet if humanity goes extinct, you do not like SpaceX. You do not want them to have their eggs in two baskets now. Yeah. Sure, it's like obviously you could have some, something that kills everyone on both planets, some AI war or something. But the point is, obviously it's good for our chances, our long-term chances, to be having two self-sustaining civilizations going on. The second reason, he values this I think just as high, is it's the greatest adventure in history, going multi-planetary, and that people need some reason to wake up in the morning, and it'll just be this hopefully great uniting event too. I mean, I'm sure in today's nasty, awful political environment, which is like a whirlpool that sucks everything into it. So it doesn't mean you name a thing, and it's become a nasty political topic. So I hope, I hope that space can, Mars can just bring everyone together. But it could become this hideous thing where it's a billionaire, some annoying storyline gets built, so half the people think that anyone who's excited about Mars is an evil something. Anyway, I hope it is super exciting. So far, space has been a uniting, inspiring thing. And in fact, especially during this time of a pandemic has been just commercial indictee putting out humans into space for the first time, was just one of the only big sources of hope. Totally, and awe, just like watching this huge skyscraper go up in the air, flip over, come back down and land. I mean, it just makes everyone just wanna sit back and clap and kinda like, you know, the way I look at something like SpaceX is it makes me proud to be a human. And I think it makes a lot of people feel that way. It's like good for our self-esteem. It's like, you know what, we're pretty, you know, we have a lot of problems, but like, we're kind of awesome. And if we can put people on Mars, you know, sticking an Earth flag on Mars, like, damn, you know, we should be so proud of our like little family here. Like we did something cool. And by the way, I've made it clear to SpaceX people, including Elon, many times, and it's like once a year reminder that if they want to make this more exciting, they send the writer to Mars on, you know, on the thing and I'll blog about it. So I'm just, you know, continuing to throw this out there. On which, on which trip? I'm trying to get them to send me to Mars. No, I understand that. So I just want to clarify on which trip does the writer want to go? I think my dream one, to be honest, would be like the, you know, like the Apollo 8, where they just looped around the moon and came back. Because landing on Mars. Give you a lot of good content to write about. Great content, right? I mean, the amount of kind of high-minded, you know, and so I would go into the thing and I would blog about it. And I'd be in microgravity, so I'd be bouncing around my little space. I get a little, they can just send me in a dragon. They don't need to do a whole starship. And I would bounce around and I would get to, and I've always had a dream of going to like one of those nice jails for a year. Yes. Because I just have nothing to do besides like read books and no responsibilities and no social plans. So this is the ultimate version of that. Anyway, it's a side topic, but I think it would be. But also if you, I mean, to be honest, if you land on Mars, it's epic. And then if you die there, like finishing your writing, it will be just even that much more powerful for the impact and the performance. But then I'm gone and I don't even get to like experience the publication of it, which is the whole point of stuff. Well, some of the greatest writers in history didn't get a chance to experience the publication of their great. I know, I don't really think that. I think like, I think back to Jesus and I'm like, oh man, that guy really like crushed it, you know? But then if you think about it, it doesn't like, you could literally die today and then become the next Jesus like 2000 years from now in this civilization that's like, they're like in magical in the clouds and they're worshiping you. They're worshiping Lex. And like, that sounds like your ego probably would be like, wow, that's pretty cool, except irrelevant to you because you never even knew it happened. This feels like a Rick and Morty episode. It does, it does. Okay, you've talked to Elon quite a bit. You've written about him quite a bit. Just, it'd be cool to hear you talk about what are your ideas of what, you know, the magic sauce is you've written about with Elon. What makes him so successful? His style of thinking, his ambition, his dreams, his, the people he connects with, the kind of problems he tackles. Is there a kind of comments you can make about what makes him special? I think that obviously there's a lot of things that he's very good at. He has, he's obviously super intelligent. His heart is very much in like, I think the right place. Like, you know, I really, really believe that. Like, and I think people can sense that, you know, he just doesn't seem like a grifter of any kind. He's truly trying to do these big things for the right reasons. And he's obviously crazy ambitious and hardworking, right? Not everyone is. Some people are as talented and have cool visions, but they just don't want to spend their life that way. So, but that's, none of those alone is what makes Elon. Elon, I mean, if it were, there'd be more of him because there's a lot of people that are very smart and smart enough to accumulate a lot of money and influence and they have great ambition and they have, you know, their heart's in the right place. To me, it is of the very unusual quality he has is that he's sane in a way that almost every human is crazy. What I mean by that is we are programmed to trust conventional wisdom over our own reasoning for good reason. If you go back 50,000 years and conventional wisdom says, you know, don't eat that berry, you know, or this is the way you tie a spearhead to a spear. And you're thinking, I'm smarter than that. Like, you're not. You know, that comes from the accumulation of life experience, accumulation of observation and experience over many generations. And that's a little mini version of the collective super intelligence. It's like, you know, it's equivalent of like making a pencil today. Like people back then, like the conventional wisdom, like had this super, this knowledge that no human could ever accumulate. So we're very wired to trust it. Plus the secondary thing is that the people who, you know, just say that they believe the mountain is, they worship the mountain as their God, right? And the mountain determines their fate. That's not true, right? And the conventional wisdom's wrong there, but believing it was helpful to survival because you were part of the crowd and you stayed in the tribe. And if you started to, you know, insult the mountain God and say, that's just a mountain, it's not, you know, you didn't fare very well, right? So for a lot of reasons, it was a great survival trait to just trust what other people said and believe it. And truly, you know, obviously, you know, the more you really believed it, the better. Today, conventional wisdom in a rapidly changing world and a huge giant society, our brains are not built to understand that. They have a few settings, you know, and none of them is, you know, 300 million person society. So your brain is basically, is treating a lot of things like a small tribe, even though they're not. And they're treating conventional wisdom as, you know, very wise in a way that it's not. If you think about it this way, it's like, picture a, like a bucket that's not moving very much, moving like a millimeter a year. And so it has time to collect a lot of water in it. That's like conventional wisdom in the old days when very few things changed. Like your 10, you know, great, great, great grandmother probably lived a similar life to you, maybe on the same piece of land. And so old people really knew what they were talking about. Today, the bucket's moving really quickly. And so, you know, the wisdom doesn't accumulate, but we think it does, because our brain settings doesn't have the, oh, move, you know, quickly moving bucket setting on it. So my grandmother gives me advice all the time, and I have to decide, is this, so there are certain things that are not changing, like relationships and love and loyalty and things like this. Her advice on those things, I'll listen to it all day. She's one of the people who said, you've got to live near your people you love, live near your family, right? I think that is like tremendous wisdom, right? That is wisdom, because that happens to be something that doesn't change from generation to generation. For now. Right, she, right, for now. She's also telling, right, so I'll be the idiot telling my grandkids that, and they'll actually be in some metaverse, like being like, it doesn't matter. And I'm like, it's not the same when you're not in person. They're gonna say, it's exactly the same, grandpa. And they'll also be thinking to me with their near link, and I'm gonna be like, slow down. I don't understand what you're, can you just talk like a normal person? Anyway, so my grandmother then, but then she says, you know, you're, I don't know about this writing you're doing, you should go to law school. And you know, you wanna be secure. And that's not good advice for me. You know, given the world I'm in, and what I like to do, and what I'm good at, that's not the right advice. But because the world is totally, she's in a different world. So she became wise for a world that's no longer here, right? Now, if you think about that, so then when we think about conventional wisdom, it's a little like my grandmother. And there's a lot of, no, it's not maybe, you know, 60 years outdated, like her software. It's maybe 10 years outdated, conventional wisdom sometimes 20. So anyway, I think that we all continually don't have the confidence in our own reasoning when it conflicts with what everyone else thinks, when with what seems right. We don't have the guts to act on that reasoning for that reason, right? You know, we, and so there's so many Elon examples. I mean, just from the beginning, building Zip2 was his first company. And it was internet advertising at the time when people said, you know, this internet was brand new, like kind of like kind of thinking of like the metaverse, VR metaverse today. And people were like, oh, we're saying, you know, we, you know, we facilitate internet advertising. People were saying, yeah, people are gonna advertise on the internet, yeah, right. Actually, it wasn't that he's magical and saw the future, is that he looked at the present, looked at what the internet was, thought about, you know, the obvious like advertising opportunity this was gonna be. It wasn't rocket science, it wasn't genius, I don't believe. I think it was just seeing the truth. And when everyone else is laughing, saying, well, you're wrong, I mean, I did the math and here it is, right? Next company, you know, X.com, which became eventually PayPal. People say, oh yeah, people are gonna put their financial information on the internet. No way. To us, it seems so obvious. If you went back then, you would probably feel the same. You'd think that is a fake company, that it's just obviously not a good idea. He looked around and said, you know, I see where this is. And so again, he could see where it was going because he could see what it was that day and not what it, you know, not people, conventional wisdom was still a bunch of years earlier. SpaceX is the ultimate example. A friend of his apparently bought, actually compiled a montage, video montage of rockets blowing up to show him this is not a good idea. And if, but just even the bigger picture, the amount of billionaires who have like thought this was, I'm gonna start launching rockets and you know, the amount that failed. I mean, it's not, conventional wisdom said this isn't a bad endeavor. He was putting all of his money into it. Yeah. Landing rockets was another thing. You know, well, here's the classic kind of way we reason, which is if this could be done, NASA would have done it a long time ago because of the money it would save. This could be done, the Soviet Union would have done it back in the 60s. It's obviously something that can't be done and the math on his envelope said, well, I think it can be done. And so he just did it. So in each of these cases, I think actually in some ways, Elon gets too much credit as, you know, people think it's that he's, you know, it's that his Einstein intelligence or he can see the future. He has incredible, he has incredible guts. He's so courageous. I think if you actually are looking at reality and you're just assessing probabilities and you're ignoring all the noise, which is wrong, so wrong, right? And you just, then you just have to be pretty smart and pretty courageous. And you have to have this magical ability to be sane and trust your reasoning over conventional wisdom because your individual reasoning, you know, part of it is that we see that we can't build a pencil. We can't build the civilization on our own, right? We kind of tout to the collective for good reasons, but this is different when it comes to kind of what's possible. You know, the Beatles were doing their kind of Motown-y chord patterns in the early sixties and they were doing what was normal. They were doing what was clearly this kind of sound is a hit. Then they started getting weird because they were so popular, they had this confidence to say, let's just, we're gonna start just experimenting. And it turns out that like, if you just, all these people are in this like one groove together doing music and it's just like, there's a lot of land over there. And it seems like, you know, I'm sure the managers would say, and all the record execs would say, no, you have to be here. This is what sells. And it's just not true. So I think that Elon is, the term for this that actually Elon likes to use is reasoning from first principles, the physics term. First principles are your axioms. And physicists, they don't say, well, what's, you know, what do people think? No, they say, what are the axioms? Those are the puzzle pieces. Let's use those to build a conclusion. That's our hypothesis. Now let's test it, right? And they come up with all kinds of new things constantly by doing that. If Einstein was assuming conventional wisdom was right, he never would have even tried to create something that really disproved Newton's laws. And the other way to reason is reasoning by analogy, which is a great shortcut. It's when we look at other people's reasoning and we kind of photocopy it into our head, we steal it. So reasoning by analogy, we do all the time. And it's usually a good thing. I mean, we don't, if you, it takes a lot of mental energy and time to reason from first principles. It's actually, you know, you don't want to reinvent the wheel every time, right? You want to often copy other people's reasoning most of the time. And, you know, most of us do it most of the time and that's good, but there's certain moments when you're, forget just for a second, like succeeding in like the world of like Elon, just who you're going to marry, where are you going to settle down? How are you going to raise your kids? How are you going to educate your kids? How you should educate yourself? What kind of career paths in terms, these moments, this is what on your deathbed, like you look back on and that's what, these are the few number of choices that really define your life. Those should not be reasoned by analogy. You should absolutely try to reason from first principles. And Elon, not just by the way in his work, but in his personal life. I mean, if you just look at the way he is on Twitter, it's not how you're supposed to be when you're a super famous, you know, industry titan. You're not supposed to just be silly on Twitter and do memes and get in little quibbles with you. He just does things his own way, regardless of what you're supposed to do, which sometimes serves him and sometimes doesn't. But I think it has taken him where it has taken him. Yeah, I mean, I probably wouldn't describe his approach to Twitter as first principles, but I guess it has the same element. I think it is. First of all, I will say that a lot of tweets, people think, oh, he's gonna be done after that. He's fine, he's just one man, time man of the year. Something is, it's not sinking him. And I think, it's not that I think this is super reasoned out. I think that Twitter is his silly side. But I think that he, his reasoning did not feel like there was a giant risk in just being his silly self on Twitter, when a lot of billionaires would say, well, no one else is doing that. So it must be a good reason, right? Well, I gotta say that he inspires me to, that it's okay to be silly. Totally. On Twitter. But yeah, you're right. The big inspiration is the willingness to do that when nobody else is doing it. Yeah, and I think about all the great artists, all the great inventors and entrepreneurs, almost all of them, they had a moment when they trusted their reasoning. I mean, Airbnb was over 60 with VCs. A lot of people would say, obviously they know something we don't, right? But they didn't. They said, eh, I think they're all wrong. I mean, that takes some kind of different wiring in your brain. And then that's both for big picture and detailed engineering problems. It's fun to talk to him. It's fun to talk to Jim Keller, who's a good example of this kind of thinking about manufacturing, how to get costs down. They always talk about SpaceX rockets this way. They talk about manufacturing this way. Cost per pound or per ton to get to orbit or something like that. This is the reason we need to get the cost down. It's a very kind of raw materials, just very basic way of thinking. First principles. It's really, yeah. And the first principles of a rocket are the price of raw materials and gravity and wind. I mean, these are your first principles and fuel. Henry Ford, what made Henry Ford blow up as an entrepreneur? The assembly line, right? I mean, he thought for a second and said, this isn't how manufacturing is normally done this way, but I think this is a different kind of product. And that's what changed it. And then what happens is when someone reasons from first principles, they often fail. You're going out into the fog with no conventional wisdom to guide you. But when you succeed, what you notice is that everyone else turns and says, wait, what? What are they doing? And then they all flock over. Look at the iPhone. iPhone, Steve Jobs was famously good for reasoning from first principles because that guy had crazy self-confidence. He just said, if I think this is right, and everyone, I mean, I don't know how he does that. And I don't think Apple can do that anymore. I mean, they lost that. That one brain's ability to do that was made in a totally different company, even though there's tens of thousands of people there. He said, he didn't say, and I'm giving a lot of credit to Steve Jobs, but of course it was a team at Apple who said, they didn't look at the flip phones and say, okay, what kind of, let's make a keyboard that's like clicky and really cool Apple-y keyboard. They said, what should a mobile device be? You know, axioms, what are the axioms here? And none of them involved a keyboard necessarily. And by the time they pieced it up, there was no keyboard because it didn't make sense. Everyone suddenly is going, wait, what? What are they doing? Now every phone looks like the iPhone. I mean, that's how it goes. You tweeted, what's something you've changed your mind about? That's the question you've tweeted. Elon replied, brain transplants. Sam Harris responded, nuclear power. There's a bunch of people with cool responses there. In general, what are your thoughts about some of the responses and what have you changed your mind about, big or small, perhaps in doing the research for some of your writing? So I'm writing right now, just finishing a book on kind of why our society is such a shit place at the moment, just polarized. And we have all these gifts, like we're talking about, just the supermarket. We have this exploding technology. Fewer and fewer people are in poverty. Louis C.K. likes to say, everything's amazing and no one's happy, right? But it's really extreme moment right now where it's like hate is on the rise, like crazy things. And if I could interrupt briefly, you did tweet that you just wrote the last word. I sure did. And then there's some hilarious asshole who said, now you just have to work on all the ones in the middle. Yeah, I earned that. I mean, when you earn a reputation as a tried and true procrastinator, you're just gonna get shit forever, and that's fine. I accept my fate there. So do you mind sharing a little bit more about the details of what you're writing? Yeah. How do you approach this question about the state of society? I wanted to figure out what was going on because what I noticed was a bad trend. It's not that things are bad. It's that things are getting worse in certain ways. Not in every way. If you look at Max Roser's stuff, he comes up with all these amazing graphs. This is what's weird is that things are getting better in almost every important metric you can think of. Except the amount of people who hate other people in their own country and the amount of people that hate their own country. The amount of Americans that hate America's on the rise. The amount of Americans that hate other Americans is on the rise. The amount of Americans that hate the president is on the rise. All these things, on the very steep rise. So what the hell? What's going on? There's something causing that. It's not that a bunch of new people were born who were just dicks. It's that something is going on. So I think of it as a very simple, oversimplified equation, human behavior. And it's the output. I think the two inputs are human nature and environment. This is basic, super kindergarten level animal behavior. But I think it's worth thinking about. You've got human nature, which is not changing very much. And then you throw that nature into a certain environment and it reacts to the environment. It's shaped by the environment. And then eventually what comes out is behavior. Human nature is not changing very much. But suddenly we're behaving differently. We are, again, look at the polls. It used to be that the president was liked by, I don't remember the exact number, but 80% or 70% of their own party and 50% of the other party. And now it's like 40% of their own party and 10% of the other party. And it's not that the presidents are getting worse, maybe some people would argue that they are, but more so. And there's a lot of idiot presidents throughout the, what's going on is something in the environment is changing. And that's different, that you're seeing is a change in behavior. Easy example here is that by a lot of metrics, racism is becoming less and less of a problem. It's hard to measure, but there's metrics like, how upset would you be if your kid married someone of another race? And that number is plummeting. But racial grievance is skyrocketing. There's a lot of examples like this. So I wanted to look around and say, and the reason I took it on, the reason I don't think this is just an unfortunate trend, unpleasant trend that hopefully we come out of, is that all this other stuff I like to write about, all this future stuff, right? And it's this magical, I always think of this, I'm very optimistic in a lot of ways. And I think that our world would be a utopia, would seem like actual heaven. Like whatever Thomas Jefferson was picturing as heaven, other than maybe the eternal life aspect, I think that if he came to 2021 US, it would be better. It's cooler than heaven. But we live in a place that's cooler than 1700s heaven. Again, other than the fact that we still die. Now, I think that future world actually probably would have quote, eternal life. I don't think anyone wants eternal life, actually, if people think they do. Eternal is a long time, but I think the choice to die when you want, maybe we're uploaded, maybe we can refresh our bodies. I don't know what it is. But the point is, I think about that utopia. And I do believe that if we don't botch this, we'd be heading towards somewhere that would seem like heaven, maybe in our lifetimes. Of course, if things go wrong, now think about the trends here. Just like the 20th century would seem like some magical utopia to someone from the 16th century, the bad things in the 20th century were kind of the worst things ever, in terms of just absolute magnitude. World War II, the biggest genocides ever. You've got maybe climate change, if it is the existential threat that many people think it is. I mean, we never had an existential threat on that level before. So the good is getting better and the bad's getting worse. And so what I think about the future, I think of us as in some kind of big, long canoe as a species. 5 million mile long canoe, each of us sitting in a row. And we each have one oar, and we can paddle on the left side or the right side. And what we know is there's a fork up there somewhere. And the river forks, and there's a utopia on one side and a dystopia on the other side. And I really believe that we're probably not headed for just an okay future. It's just the way tech is exploding, it's probably gonna be really good or really bad. The question is, which side should we be rowing on? We can't see up there, right? But it really matters. So I'm writing about all this future stuff, and I'm saying none of this matters if we're squabbling our way into kind of like a civil war right now. So what's going on? So it's a really important problem to solve. What are your sources of hope in this? So like, how do you steer the canoe? One of my big sources of hope, and this is my answer to what I changed my mind on, is I think I always knew this, but it's easy to forget it. Our primitive brain does not remember this fact, which is that I don't think there are very many bad people. Now, you say bad, are there selfish people? Most of us, I think that if you think of people, there's digital languages, ones and zeros. And our primitive brain very quickly can get into the land where everyone's a one or a zero. Our tribe, we're all ones, we're perfect, I'm perfect, my family is that other family, is that other tribe. There are zeros, and you dehumanize them, right? These people are awful. So zero is not a human place. No one's a zero and no one's a one. You're dehumanizing yourself. So when we get into this land, I call it political Disney world, because the Disney movies have good guys, Scar is totally bad and Mufasa is totally good, right? You don't see Mufasa's character flaws. You don't see Scar's upbringing that made him like that, that humanizes him, no, lionizes him, whatever. You are- Well done. Yeah. Mufasa's a one and Scar's a zero, very simple. So political Disney world is a place, a psychological place that all of us have been in. And it can be religious Disney world, it can be national Disney world, and war, whatever it is. But it's a place where we fall into this delusion that there are protagonists and antagonists and that's it, right? That is not true. We are all 0.5s or maybe 0.6s to 0.4s. In that we are also on one hand, it's not that I don't think there's that many really great people, frankly. I think if you get into it, people are kind of a lot of people, most of us have, if you get really into our most shameful memories, the things we've done that are worse, the most shameful thoughts, the deep selfishness that some of us have in areas we wouldn't want to admit, right? Most of us have a lot of unadmirable stuff, right? On the other hand, if you actually got into, really got into someone else's brain, and you looked at their upbringing, you looked at the trauma that they've experienced, and then you looked at the insecurities they have, and you look at all their, if you assembled a highlight reel of your worst moments, the meanest things you've ever done, the worst, the most selfish, the times you stole something, whatever, and you just, people think, wow, Lex is an awful person. If you highlighted your, if you did a montage of your best moments, people would say, oh, he's a god, right? But of course we all have both of those. So I've started to really try to remind myself that everyone's a 0.5, right? And 0.5s are all worthy of criticism, and we're all worthy of compassion. And the thing that makes me hopeful is that I really think that, there's a bunch of 0.5s, and 0.5s are good enough that we should be able to create a good society together. There's a lot of love in every human. And I think there's more love in humans than hate. You know, I always remember this moment. This is a weird anecdote, but I was at, I'm a Red Sox fan, Boston Red Sox baseball, and Derrick Jeter is who we hate the most. He's on the Yankees. Yes. And hate, right? Ugh, Jeter, right? He was his last game in Fenway. He's retiring. And he got this rousing standing ovation, and I almost cried. And it was like, what is going on? We hate this guy, but actually, there's so much love in all humans. It felt so good to just give a huge cheer to this guy we hate because it's like this moment of a little fist pound, being like, of course we all actually love each other. And I think there's so much of that. And so the thing that I think I've come around on is I think that we are in an environment that's bringing out really bad stuff. I don't think it's, if I thought it was the people, I would be more hopeful. Like if I thought it was human nature, I'd be more upset. It's the two independent variables here, or there's a fixed variable, there's a constant, which is the human nature, and there's the independent variable, environment, and then behavior is the dependent variable. I like that the thing that I think is bad is the independent variable, the environment, which means I think the environment can get better. And there's a lot of things I can go into about why the environment I think is bad, but I have hope because I think the thing that's bad for us is something that can change. The first principle's idea here is that most people have the capacity to be a 0.7 to a 0.9 if the environment is properly calibrated with the right incentives. I think that, well, I think that maybe, if we're all, yeah, if we're all 0.5s, I think that environments can bring out our good side. You know, yeah, so maybe we're all on some kind of distribution. And the right environment can, yes, can bring out our higher sides. And I think in a lot of ways, you could say it has. I mean, the US environment, we take for granted how the liberal laws and liberal environment that we live in. I mean, like in New York City, right, if you walk down the street and you like assault someone, A, if anyone sees you, they're probably gonna yell at you. You might get your ass kicked by someone for doing that. You also might end up in jail, you know, if it's security cameras and there's just norms. You know, we're all trained. That's what awful people do, right? So there's, it's not the human nature doesn't have it in it to be like that. It's that this environment we're in has made that a much, much, much smaller experience for people. There's so many examples like that where it's like, man, you don't realize how much of the worst human nature is contained by our environment. And, but I think that, you know, rapidly changing environment, which is what we have right now, social media starts. I mean, what a seismic change to the environment. There's a lot of examples like that. Rapidly changing environment can create rapidly changing behavior. And wisdom sometimes can't keep up. And so we, you know, we can really kind of lose our grip on some of the good behavior. Were you surprised by Elon's answer about brain transplants or Sam's about nuclear power or anything else? Just- Sam's I think is, I have a friend, Isabel Boehmcke, who has a, who's a nuclear power, you know, influencer. I've become very convinced and I've not done my deep dive on this. Yeah. But here's, in this case, this is reasoning by analogy here. The amount of really smart people I respect, who all, who seem to have dug in, who all say nuclear power is clearly a good option. It's obviously emission free, but you know, the concerns about meltdowns and waste, they see it, they say are completely overblown. So judging from those people, secondary knowledge here, I will say I'm a strong advocate. I haven't done my own deep dive yet, but it does seem like a little bit odd that you've got people who are so concerned about climate change, who have, it seems like it's kind of an ideology where nuclear power doesn't fit, rather than rational, you know, fear of climate change that somehow is anti-nuclear power. It just, yeah. I personally am uncomfortably reasoning by analogy with climate change. I've actually have not done a deep dive myself. Me neither, because it's so, man, it seems like a deep dive. Yeah. And my reasoning by analogy there currently has me thinking it's a truly existential thing, but feeling hopeful. So let me, this is me speaking, and this is speaking from a person who's not done the deep dive. I'm a little suspicious of the amount of fear mongering going on. I've, especially over the past couple of years, I've gotten uncomfortable with fear mongering in all walks of life. There's way too many people interested in manipulating the populace with fear. And so I don't like it. I should probably do a deep dive, because to me it's, well, the big problem with the opposition to climate change or whatever the fear mongering is that it also grows the skepticism in science broadly. It's like, and that, so I need to make sure I do that deep dive. I have listened to a few folks who kind of criticize the fear mongering and all those kinds of things, but they're few and far in between. And so it's like, all right, what is the truth here? And it feels lazy, but it also feels like it's hard to get to the, like there's a lot of kind of activists talking about idea versus sources of objective, like calm, first principles type reasoning. Like one of the things, I know it's supposed to be a very big problem, but when people talk about catastrophic effects of climate change, I haven't been able to see really great deep analysis of what that looks like in 10, 20, 30 years, raising rising sea levels. What are the models of how that changes human behavior, society, what are the things that happen? There's going to be constraints on the resources and people are gonna have to move around. This is happening gradually. Are we gonna be able to respond to this? How would we respond to this? What are the best, like what are the best models for how everything goes wrong? Again, I was, this is a question I keep starting to ask myself without doing any research, like motivating myself to get up to this deep dive that I feel is deep. Just watching people not do a great job with that kind of modeling with the pandemic and sort of being caught off guard and wondering, okay, if we're not good with this pandemic, how are we going to respond to other kinds of tragedies? Well, this is part of why I wrote the book, because I said, we're going to have more and more of these big collective, what should we do here situations, whether it's, how about when, we're probably not that far away from people being able to go and decide the IQ of their kid or make a bunch of embryos and actually pick the highest IQ. It can possibly go wrong. Yeah, and also imagine the political sides of that and that's something only wealthy people can afford at first and just a nightmare, right? We need to be able to have our wits about us as a species where we can actually get into a topic like that and come up with a, where the collective brain can be smart. I think that there are certain topics where I think of, I think of this, and this is again, another simplistic model, but I think it works, is that there's a higher mind and a primitive mind, right? You can, in your head. And these team up with others. So when the higher minds are, and a higher mind is more rational and puts out ideas that it's not attached to. And so it can change its mind easily because it's just an idea and the higher mind can get criticized. Their ideas can get criticized and it's no big deal. And so when the higher minds team up, it's like all these people in the room, like throwing out ideas and kicking them and one idea goes out and everyone criticizes it, which is like, you know, shooting bows and arrows at it. And the truth, the true idea is, you know, the arrows bounce off and it's so, okay, it rises up. And the other ones get shot down. So it's this incredible system. This is what, you know, this is what good science institution is, is, you know, someone puts out a thing, criticism arrows come at it. And, you know, most of them fall and the needle is in the haystack end up rising up, right? Incredible mechanism. So what that's happening is a bunch of people, a bunch of flawed medium scientists are creating super intelligence. Then there's the primitive mind, which, you know, is the more limbic systemy part of our brain. It's the, it's a part of us that is very much not living in 2021. It's living many tens of thousands of years ago. And it does not treat ideas like this separate thing. It identifies with its ideas. It only gets involved when it finds an idea sacred. It starts holding an idea sacred and it starts identifying. So what happens is they team up too. And so when you have a topic that a bunch of primitive, that really rouses a bunch of primitive minds, it quickly, the primitive minds team up and they create an echo chamber where suddenly no one can criticize this. And in fact, if it's powerful enough, people outside the community, no one can criticize it. We will get your paper retracted. We will get you fired, right? That's not higher mind behavior. That is crazy primitive mind. And so now what happens is the collective becomes dumber than an individual, a dumber than a reason, a single reasoning individual. You have this collective is suddenly attached to this sacred scripture with the idea and they will not change their mind and they get dumber and dumber. And so climate change, what's worrisome is that climate change has in many ways become a sacred topic, where if you come up with a nuanced thing, you might get called branded a denier. So there goes the super intelligence, all the arrows, no arrows can be fired. But if you get called a denier, that's a social penalty for firing an arrow at a certain orthodoxy. And so what's happening is the big brain gets frozen and it becomes very stupid. Now, you can also say that about a lot of other topics right now. You just mentioned another one, I forget what it was, but that's also kind of like this. The world of vaccine. Yeah, COVID. And here's my point earlier is that what I see is that the political divide is like a whirlpool that's pulling everything into it. And in that whirlpool, thinking is done with the primitive mind tribes. And so I get, okay, obviously something like race, that makes sense, that also right now, the topic of race, for example, or gender, these things are in the whirlpool. But that at least is like, okay, that's something that the primitive mind would always get really worked up about. It taps into our deepest kind of primal selves. COVID, make this COVID in a way too, but climate change, that should just be something that our rational brains are like, let's solve this complex problem. But the problem is that it's all gotten sucked into the red versus blue whirlpool. And once that happens, it's in the hands of the primitive minds. And we're losing our ability to be wise together, to make decisions. It's like the big species brain is like, or the big American brain is like, drunk at the wheel right now. And we're about to go into a future with more and more big technologies, scary things, we have to make big, right decisions. We're getting dumber as a collective, and that's part of this environmental problem. So within the space of technologists and the space of scientists, we should allow the arrows. That's one of the saddest things to me about, is like the scientists, like I've seen arrogance. There's a lot of mechanisms that maintain the tribe. It's the arrogance, it's how you built up this mechanism that defends this wall that defends against the arrows. It's arrogance, credentialism, just ego, really. And then just, it protects you from actually challenging your own ideas. This ideal of science that makes science beautiful. In a time of fear, and in a time of division created by perhaps politicians that leverage the fear, it, like you said, makes the whole system dumber. The science system dumber, the tech developer system dumber, if they don't allow the challenging of ideas. What's really bad is that like, in a normal environment, you're always gonna have echo chambers. So what's the opposite of an echo chamber? I created a term for it, because I think we need it, which is called an idea lab. An idea lab, right? It's like people treat, it's like people act like scientists, even if they're not doing science. They just treat their ideas like science experiments, and they toss them out there, and everyone disagrees. And disagreement is like the game. Everyone likes to disagree. You know, on a certain text thread, where everyone is just saying, it's almost like someone throws something out, and just as an impulse for the rest of the group to say, I think you're being overly general there. Or I think, aren't you kind of being, I think that's like your bias showing. And it's like, no one's getting offended, because it's like, we're all just messing, we all, of course, respect each other, obviously. We're just trashing each other's ideas, and that the whole group becomes smarter. You're always gonna have idea labs and echo chambers, in different communities. Most of us participate in both of them. You know, and maybe in your marriage is a great idea lab, you love to disagree with your spouse. And maybe in, but this group of friends, or your family at home, you know, you know in front of that sister, you do not bring up politics, because she's now enforced, when that happens, her bullying is forcing the whole room to be an echo chamber, to appease her. Now, what scares me is that, usually you have these things existing kind of in bubbles, and usually there's like, they each have their natural defenses against each other. So an echo chamber person stays in their echo chamber. They don't like, they will cut you out. They don't like to be friends with people who disagree with them. You notice that, they will cut you out. They'll cut out their parents, if they voted for Trump or whatever, right? So, that's how they do it. They will say, I'm gonna stay inside of an echo chamber safely. So my ideas, which I identify with, because my primitive mind is doing the thinking, are not gonna ever have to get challenged, because it feels so scary and awful for that to happen. But if they leave, and they go into an idea lab environment, people are gonna say, what? No, they're gonna disagree, and they're gonna say, and the person's gonna try to bully them, they're gonna say, that's really offensive. And people are gonna say, no, it's not. And they're gonna immediately say, these people are assholes, right? So the echo chamber person, it doesn't have much power once they leave the echo chamber. Likewise, the idea lab person, they have this great environment, but if they go into an echo chamber where everyone else is, and they do that, they will get kicked out of the group. They will get branded as something, a denier, a racist, a right-winger, a radical, these nasty words. The thing that I don't like right now is that the echo chambers have found ways to forcefully expand into places that normally have a pretty good immune system against echo chambers, like universities, like science journals. Places where usually, it's like there's a strong idea lab culture, they're veritas, you know? That's an idea lab slogan. You have is that these people have found a way to, a lot of people have found a way to actually go out of their thing and keep their echo chamber by making sure that everyone is scared because they can punish anyone, whether you're in their community or not. That's all brilliantly put. When's the book coming out? Any idea? June, July? We're not quite sure yet. Okay, I can't wait. Thanks. It's awesome. Do you have a title yet, or you can't talk about that? Still working on it. Okay. If it's okay, just a couple of questions from Mailbag. I just love these. I would love to hear you riff on these. So one is about film and music. Why do we prefer to watch, the question goes, why do we prefer to watch a film we haven't watched before, but we want to listen to songs that we have heard hundreds of times? This question and your answer really started to make me think, like, yeah, that's true. That's really interesting. Like we draw that line somehow. So what's the answer? So I think, let's use these two minds again. I think that when your higher mind is the one who's taking something in and they're really interested, and you know, what are the lyrics? Or I'm gonna learn something, or what, you know, reading a book or whatever, and the higher mind is trying to get information, and once it has it, there's no point in listening to it again. It has the information. You know, your rational brain is like, I got it. But when you eat a good meal or have sex or whatever, that's something you can do again and again because it actually, your primitive brain loves it, right? And it never gets bored of things that it loves. So I think music is a very primal thing. I think music goes right into our primitive brain. You know, I think it's, of course, it's a collaboration. Your rational brain is absorbing the actual message, but I think it's all about emotions, and even more than emotions, it literally, like, music taps into like some very, very deep, you know, primal part of us. And so when you hear a song once, even some of your favorite songs, the first time you heard it, you were like, I guess that's kind of catchy, yeah. And then you end up loving it on the 10th listen, but sometimes you even don't even like a song. You're like, oh, this song sucks. But suddenly you find yourself on the 40th time because it's on the radio all the time just kind of being like, oh, I love this song. And you're like, wait, I hate this song. And what's happening is that the sound is actually, the music's actually carving a pathway in your brain, and it's a dance. And when your brain knows what's coming, it can dance, it knows the steps. So your brain is, your internal kind of, your brain is actually dancing with the music, and it knows the steps, and it can anticipate. And so there's something about knowing, having memorized the song that makes it incredibly enjoyable to us. But when we hear it for the first time, we don't know where it's gonna go. We're like an awkward dancer. We don't know the steps, and your primitive brain can't really have that much fun yet. That's how I feel. And in the movies, that's less primitive, that's a story. You're taking in. But a really good movie that we really love, often we will watch it like 12 times, it's to like it, not that many, but versus if you're watching a talk show, right? Listening to, if you're listening to one of your podcasts, as a perfect example, there's not many people that will listen to one of your podcasts, no matter how good it is, 12 times. Because once you've got it, you've got it. It's a form of information that's very higher mind focused. That's how I feel. Well, you know, the funny thing is, there is people that listen to a podcast episode many, many times. And often I think the reason for that is not because of the information, it's the chemistry, it's the music of the conversation. So it's not the actual- It's just the art of it they like. Yeah, they'll fall in love with some kind of person, some weird personality, and they'll just be listening to, they'll be captivated by the beat of that kind of person. Or like a standup comic. I've watched like certain things, like episodes like 20 times, even though I, you know. I have to ask you about the wizard hat. You wrote a blog about Neuralink. I got a chance to visit Neuralink a couple of times, hanging out with those folks. That was one of the pieces of writing you did that like changes culture and changes the way people think about a thing. The ridiculousness of your stick figure drawings are somehow, it's like, you know, it's like calling the origin of the universe the Big Bang. It's a silly title, but it somehow sticks to be the representative of that. In the same way, the wizard hat for the Neuralink is somehow was a really powerful way to explain that. You actually proposed that the Man of the Year cover of Time should be- One of my drawings. One of your drawings. In general, yes. This is an outrage that it wasn't. It wasn't. Okay, so what are your thoughts about like all those years later about Neuralink? Do you find this idea, like what excites you about it? Is it the big long-term philosophical things? Is it the practical things? Do you think it's super difficult to do on the neurosurgery side and the material engineering, the robotics side? Or do you think the machine learning side for the brain-computer interfaces, where they get to learn about each other, all that kind of stuff? I would just love to get your thoughts because you're one of the people that really considered this problem, really studied it, brain-computer interfaces. I mean, I'm super excited about it. I really think it's actually Elon's most ambitious thing, more than colonizing Mars, because that's just a bunch of people going somewhere, even though it's somewhere far. Neuralink is changing what a person is, eventually. Now, I think that Neuralink engineers and Elon himself would all be the first to admit that it is a maybe, whether they can do their goals here. I mean, it is so crazy ambitious to try to, I mean, their eventual goals are, of course, in the interim, they have a higher probability of accomplishing smaller things, which are still huge, like basically solving paralysis, strokes, Parkinson, things like that. I mean, it can be unbelievable. Anyone who doesn't have one of these things, like we might, everyone should be very happy about this kind of helping with different disabilities. But the thing that is like, so the grand goal is this augmentation, where you take someone who's totally healthy and you put a brain-machine interface in any way to give them superpowers. It's the possibilities if they can do this, if they can really, so they've already shown that they are for real, they've created this robot. Elon talks about it should be like LASIK, where it's not, it shouldn't be something that needs a surgeon, this shouldn't just be for rich people who have waited in line for six months, it should be for anyone who can afford LASIK and eventually, hopefully, something that isn't covered by insurance, or something that anyone can do. Something this big a deal should be something that anyone can afford eventually. And when we have this, again, I'm talking about a very advanced phase down the road. So maybe a less advanced phase, maybe right now, if you think about when you listen to a song, what's happening, is do you actually hear the sound? Well, not really, it's that the sound is coming out of the speaker, the speaker is vibrating, it's vibrating air molecules, those air molecules get vibrated all the way to your head, the pressure wave, and then it vibrates your eardrum, your eardrum is really the speaker now in your head, that then vibrates bones and fluid, which then stimulates neurons in your auditory cortex, which give you the perception that you're hearing sound. Now, if you think about that, do we really need to have a speaker to do that? You could just somehow, if you had a little tiny thing that could vibrate eardrums, you could do it that way, that seems very hard, but really what you need is to go to the very end, but the thing that really needs to happen is your auditory cortex neurons need to be stimulated in a certain way. If you have a ton of neural link things in there, neural link electrodes, and they get really good at stimulating things, you could play a song in your head that you hear that is not playing anywhere, there's no sound in the room, but you hear it and no one else could, it's not like they can get close to your head and hear it, there's no sound, they could not hear anything, but you hear sound, you can turn up, so you open your phone, you have the neural link app, you open the neural link app, and or just neural, so basically you can open your Spotify and you can play to, you can play to your speaker, you can play to your computer, you can play right out of your phone to your headphones, or you can, you now have a new one, you can play into your brain. And this is one of the earlier things, this is something that seems like really doable. So, you know, no more headphones, I always think that's so annoying because I can leave the house with just my phone, you know, and nothing else, or even just an Apple Watch, there's always this one thing, like, and headphones, you do need your headphones, right? So I feel like, you know, that'll be the end of that. But there's so many things that you, and you keep going, the ability to think together, you know, you can talk about like super brains, I mean, one of the examples Elon uses is that the low bandwidth of speech. If I go to a movie, and I come out of a scary movie, and you say, how was it? I say, oh, it was terrifying. Well, what did I just do? I just gave you, I just gave you, I had five buckets I could have given you. One was horrifying, terrifying, scary, eerie, creepy, whatever, that's about it. And I had a much more nuanced experience than that. And I don't, all I have is, you know, these words, right? And so instead, I just hand you the bucket. Well, I put the stuff in the bucket and give it to you, but all you have is the bucket, you just have to guess what I put into that bucket. All you can do is look at the label of the bucket and say, I'll, when I say terrifying, here's what I mean. So the point is, it's very lossy. I had this, all this nuanced information of what I thought of the movie, and I'm sending you a very low res package that you're gonna now guess what the high res thing looked like. That's language in general. Our thoughts are much more nuanced. We can think to each other, we can do amazing things. We could A, have a brainstorm that doesn't feel like, oh, we're not talking in each other's heads, not just that I hear your voice. No, no, no, we are just thinking. No words are being said internally or externally. The two brains are literally collaborating. It's something, it's a skill. I'm sure we'd have to get good at it. I'm sure young kids will be great at it and old people will be bad. But you think together and together you're like, ah, had the joint epiphany. And now how about eight people in a room doing it, right? So it gets, you know, there's other examples. How about when you're a dress designer or a bridge designer and you want to show people what your dress looks like? Well, right now you got to sketch it for a long time. Here, just beam it onto the screen from your head so you can picture it. If you can picture a tree in your head, well, you can just suddenly, whatever's in your head, you can be pictured. So we'll have to get very good at it, right? And take a skill, right? You know, you're gonna have to, but the possibilities, my God, talk about like, I feel like if that works, if we really do have that as something, I think it'll almost be like a new ADBC line. It's such a big change that the idea of like, anyone living before everyone had brain machine interfaces is living in like before the common era. It's that level of like big change, if it can work. Yeah, and like a replay of memories, just replaying stuff in your head. Oh my God, yeah. And copying, you know, you can hopefully copy memories onto other things and you don't have to just rely on your, you know, your wet circuitry. It does make me sad because you're right. The brain is incredibly neuroplastic. And so it can adjust, it can learn how to do this. I think it will be a skill. But probably you and I will be too old to truly learn. Well, maybe we can get, there'll be great trainings. You know, I'm spending the next three months in like, you know, in one of the Neuralink trainings. But it'll still be a bit of like grandpa can't. Definitely. This is, you know, I always think, how am I gonna be old? I'm like, no, I'm gonna be great at the new phones. It's like, how can it be the phones? It's gonna be that, you know, the kid's gonna be thinking to me, I'm gonna be like, I just, can you just talk, please? And they're gonna be like, okay, I'll just talk. And they're gonna, so that'll be the equivalent of, you know, yelling to your grandpa today. I really suspect, I don't know what your thoughts are, but I grew up in a time when physical contact and interaction was valuable. I just feel like that's going to go the way that's gonna disappear. Well, why? I mean, is there anything more intimate than thinking with each other? I mean, that's, you talk about, you know, once we were all doing that, it might feel like, man, everyone was so isolated from each other before. Yeah, sorry. So I didn't say that intimacy disappears. I just meant physical, having to be in the same, having to touch each other. People like that. If it is important, won't there be whole waves of people start to say, you know, there's all these articles that come out about how, you know, in our metaverse, we've lost something important. And then now there's a huge, all first the hippies start doing it, and then eventually it becomes this big wave and now everyone, won't, you know, if something truly is lost, won't we recover it? Well, I think from first principles, all of the components are there to engineer intimate experiences in the metaverse, or in the cyberspace. And so to me, it's, I don't see anything profoundly unique to the physical experience. Like, I don't understand. But then why are you saying there's a loss there? No, I'm just sad, because I won't, oh, it's a loss for me personally, because the world- So then you do think there's something unique in the physical experience? For me, because I was raised with it. Oh. Yeah, yeah, yeah. So whatever, so anything you're raised with, you fall in love with. Like people in this country came up with baseball. I was raised in the Soviet Union. I don't understand baseball. I get, I like it, but I don't love it the way Americans love it. It's because a lot of times they went to baseball games with their father, and then there's that family connection. There's a young kid dreaming about, I don't know, becoming an MLB player himself. I don't know, something like that. But that's what you're raised with, obviously, is really important. But I mean, fundamentally to the human experience, listen, we're doing this podcast in person, so clearly I still value it, but- But it's true. If this were, obviously, if there were screen, we all agree that's not the same. Yeah, it's not the same. But if this were some, you know, we had contact lenses on, and like, you know, maybe Neuralink, you know, maybe, again, forget, again, this is all, the devices, even if it's just as cool as a contact lens, that's all old school. Once you have the brain-machine interface, it'll just be projection of, it'll take over my visual cortex. My visual cortex will get put into a virtual room, and so will yours, so we will see, we will hear, really hear and see, as if we're, you won't have any masks, no VR mask needed. And at that point, it really will feel like, you'll forget, you'll say, well, were we together physically or not? You won't even, it'd be so unimportant, you won't even remember. And you're right, this is one of those shits in society that changes everything. But romantically, people still need to be together. There's a whole set of physical things with relationship that are needed. You know, like- Like what, like sex? Sex, but also just like, there's pheromones. Like, there's, the physical touch is such a, that's like music, it goes to such a deeply primitive part of us, that what physical touch with a romantic partner does, that I think that, so I'm sure there'll be a whole wave of people who, their new thing is that, you know, you're romantically involved with people you never actually are in person with, but, and I'm sure there'll be things where you can actually smell what's in the room and you can- Yeah, and touch. Yeah, but I think that'll be one of the last things to go. I think there'll be, there's something, that to me seems like something that'll be, it'll be a while before people feel like there's nothing lost by not being in this. It's very difficult to replicate the human interaction. Although sex also, again, you could, not to get too like weird, but you could have a thing where you basically, you know, or let's just do a massage because it's less like awkward, but like, you know, someone- Everyone is still imagining sex, so go on. A masseuse could massage a fake body and you could feel whatever's happening, right? So you're lying down in your apartment alone, but you're feeling a full- That'll be the new like YouTube, like streaming, where it's one masseuse massaging one body, but like a thousand people are experiencing. Exactly, right, now think about it, right now, you know what, Taylor Swift doesn't play for one person, it has to go around and every one of her fans she has to go play for, or a book, right? You do it and it goes everywhere, so it'll be the same idea. You've written and thought a lot about AI, so AI safety specifically, you've mentioned you're actually starting a podcast, which is awesome, you're so good at talking, so good at thinking, so good at being weird in the most beautiful of ways, but you've been thinking about this AI safety question, where today does your concern lie? For the near future, for the long-term future, like quite a bit of stuff happened, including with Elon's work with Tesla Autopilot, there's a bunch of amazing robots, there's Boston Dynamics, and everyone's favorite vacuum robot, iRobot, Roomba, and then there's obviously the applications of machine learning for recommender systems in Twitter, Facebook, and so on, and you know, face recognition for surveillance, all these kinds of things are happening, just a lot of incredible use of, not the face recognition, but the incredible use of deep learning, machine learning to capture information about people and try to recommend to them what they wanna consume next. Some of that can be abused, some of that can be used for good, like for Netflix or something like that. What are your thoughts about all this? Yeah, I mean, I really don't think humans are very smart, all things considered, I think we're like limited, and we're dumb enough that we're very easily manipulable, not just like, oh, our emotions, people can, you know, our emotions can be pulled like puppet strings. I mean, again, I do look at what's going on with political polarization now, and I see a lot of puppet string emotions happening. So yeah, there's a lot to be scared of, for sure, like very scared of. I get excited about a lot of, very specific things, like one of the things I get excited about is, so the future of wearables, right? Again, I think that, oh, the wrist, the Fitbit around my wrist is gonna seem, or the Whoop, is gonna seem really hilariously old school in 20 years. Like with Neuralink. Wearing like a big bracelet, right? It's gonna turn into little sensors in our blood, probably, or, you know, even infrared, you know, just things that are gonna be, it's gonna be collecting 100 times more data than it collects now, more nuanced data, more specific to our body, and it's going to be super reliable, but that's the hardware side. And then the software is gonna be, this is, I've not done my deep dive, this is all speculation, but the software is gonna get really good, and this is the AI component. And so I get excited about specific things like that, like think about if you're, if hardware were able to collect, first of all, the hardware knows your whole genome, and we know a lot more about what a genome sequence means, because you can collect your genome now, and we just don't know, we don't have much to do with that information. As AI gets, so now you have your genome, you've got what's in your blood at any given moment, all the levels of everything, right? You have the exact width of your heart arteries at any given moment, you've got- All the virons, all the viruses that ever visited your body, because there's a trace of it, so you have all the pathogens, all the things that you should be concerned about health-wise and might have threatened you, or you might be immune from, all of that kind of stuff. Also, of course, it knows how fast your heart is beating, and it knows how much you, exactly the amount of exercise, knows your muscle mass and your weight and all that, but it also maybe can even know your emotions. I mean, if emotions, what are they? Where do they come from? Probably pretty obvious chemicals once we get in there. So again, Neuralink can be involved here, maybe, in collecting information. Because right now you have to do the thing, what's your mood right now? And it's hard to even assess, and you're in a bad mood, it's hard to even, but- By the way, just as a shout out, Lisa Feldman Barrett, who's a neuroscientist at Northeastern, just wrote a, and not just, like a few years ago, wrote a whole book saying our expression of emotions has nothing to do with the experience of emotions. So you really actually want to be measuring. That's exactly, and you can tell, because one of these apps pops up and says, how do you feel right now? Good, bad, I'm like, I don't know, like I feel bad right now because the thing popping up reminded me that I'm procrastinating, because I was on my phone, I should've been, you know, like that's not my, you know. So I think it will probably be able to very, get all this info, right? Now the AI can go to town. Think about when the AI gets really good at this, and it knows your genome, and it knows, it can just, I want the AI to just tell me what to do. When it turns up, okay, for when he, so how about this, now imagine attaching that to a meal service, right? And the meal service has everything, you know, all the million ingredients and supplements and vitamins and everything. And I give the, I tell the AI my broad goals. I want to gain muscle, or I want to, you know, maintain my weight, but I want to have more energy, or whatever, or I just want to be very healthy, and I want, obviously, everyone wants the same, like, 10 basic things, like you want to avoid cancer, you want to, you know, various things, you want to age slower. So now the AI has my goals, and a drone comes at, you know, a little thing pops up, and it says like, you know, beep, beep, like, you know, 15 minutes, you're gonna eat. Because it knows that's the right time for my body to eat. 15 minutes later, a little slot opens in my wall, where a drone has come from the factory, the eating, the food factory, and dropped the perfect meal for my, that moment for me, for my mood, for my genome, for my blood contents. And it's, because it knows my goals, so, you know, it knows I want to feel energy at this time, and then I want to wind down here, so those things, you have to tell it. Plus the pleasure thing, like, it knows what kind of components of a meal you've enjoyed in the past, so you can assemble the perfect meal in terms of taste. Exactly, it knows you way better than you know yourself, better than any human could ever know you. And a little thing pops up. You still have some choice, right? It still, it pops up and it says, like, you know, coffee, because it knows that, you know, my cutoff, they say, you know, I can have coffee for the next 15 minutes only, because at that point, it knows how long it stays in my system, it knows what my sleep is like when I have it too late, it knows I have to wake up at this time tomorrow, because that is my calendar. And so, I think a lot of people's, this is, I think, something that humans are wrong about, is that most people will hear this and be like, that sounds awful, that sounds dystopian. No, it doesn't, it sounds incredible. And if we all had this, we would not look back and be like, I wish I was making awful choices every day, like I was in the past. And then, this isn't, these aren't important decisions. Your important decision-making energy, your important focus and your attention can go onto your kids and on your work and on, you know, helping other people and things that matter. And so, I think AI can, when I think about, like, personal lifestyle and stuff like that, I really love, like, I love thinking about that. I think it's gonna be very, and I think we'll all be so much healthier that when we look back today, one of the things that's gonna look so primitive is the one-size-fits-all thing, getting, like, reading advice about keto. Each genome is gonna have very specific, one, you know, unique advice coming from AI, and so, yeah. Yeah, the customization that's enabled by a collection of data and the use of AI, a lot of people think what's the, like, they think of the worst-case scenario of that data being used by authoritarian governments to control you, all that kind of stuff. They don't think about, most likely, especially in a capitalist society, it's most likely going to be used as part of a competition to get you the most delicious and healthy meal possible as fast as possible. Yeah, so the world will definitely be much better with the integration of data. But of course, you wanna be able to be transparent and honest about how that data is misused, and that's why it's important to have free speech and people to speak out, like, when some bullshit is being done by companies. That we need to have our wits about us as a society, like, this is what, free speech is the mechanism by which the big brain can think, can think for itself, can think straight, can see straight. When you take away free speech, when you start saying that, in every topic, when any topic's political, it becomes treacherous to talk about. So forget the government taking away free speech. If the culture penalizes nuanced conversation about any topic that's political, and the politics is so all-consuming, and it's such a incredible market to polarize people, for media to polarize people, and to bring any topic it can into that and get people hooked on it as a political topic, we become a very dumb society. So free speech goes away, as far as it matters. People say, people like to say, oh, it's not, you don't even know what free speech is. Free speech is, you know, it's, you know, your free speech is not being violated. It's like, no, you're right. My First Amendment rights are not being violated. But the culture of free speech, which is the second ingredient of two, you need the First Amendment, and you need the culture of free speech, and now you have free speech, and the culture is much more specific. You obviously can have a culture that believes people right now, take any topic, again, that has to do with, like, you know, some very sensitive topics, you know, police shootings, or, you know, what's going on in, you know, K through 12 schools, or, you know, even, you know, climate change. You know, take any of these. And the First Amendment's still there. You're not gonna get arrested, no matter what you say. The culture of free speech is gone, because you will be destroyed. Your life can be over, you know, as far as it matters, if you say the wrong thing. But even, you know, but a culture, a really vigorous culture of free speech, you get no penalty at all for even saying something super dumb. People will say, like, people will laugh and be like, well, that was, like, kind of hilariously offensive, and, like, not at all correct. Like, you know, you're wrong, and here's why. But no one's, like, mad at you. Now, the brain is thinking at its best. IQ of the big brain is, like, as high as it can be in that culture. And the culture where you say something wrong, and people say, oh, wow, you've changed. Oh, wow, like, look, this is his real, you know, colors. You know, the big brain is dumb. You still have mutual respect for each other. So, like, you don't think lesser of others when they say a bunch of dumb things. You know it's just a play of ideas. But you still have respect. You still have love for them. Because I think the worst case is when you have a complete free, like, anarchy of ideas where it's, like, like, everybody lost hope that something like a truth can even be converged towards. Like, everybody has their own truth. Then it's just chaos. Like, if you have mutual respect and a mutual goal of arriving at the truth and the humility that you want to listen to other people's ideas, and a forgiveness that other people's ideas might be dumb as hell, that doesn't mean they're lesser beings, all that kind of stuff. But that's, like, a weird balance to strike. Right now people are being trained, little kids, college students, being trained to think the exact opposite way. To think that there's no such thing as objective truth. Which is, you know, the objective truth is the N on the compass for every thinker. Doesn't mean we're, you know, necessarily on our way or finding it, but we're all aiming in the same direction. We all believe that there's a place we can eventually get closer to. Not objective truth, you know, teaching them that disagreement is bad, violence. You know, it's, you know, it's like, you know, you quickly sound like you're just going on, like, a political rant with this topic, but, like, it's really bad. It's, like, genuinely the worst. If I had my own country, I mean, it's like, I would teach kids some very specific things that this is doing the exact opposite of. And it sucks. It sucks. Speaking of a way to escape this, you've tweeted 30 minutes of reading a day equals, yeah, this whole video, and it's cool to think about reading, like, as a habit and something that accumulates. You said 30 minutes of reading a day equals 1,000 books in 50 years. I love, like, thinking about this, like, chipping away at the mountain. Can you expand on that, sort of, the habit of reading? How do you recommend people read? Yeah, yeah, I mean, it's incredible. If you do something, a little of something every day, it compiles, it compiles. You know, I always think about, like, the people who achieve these incredible things in life, these great, like, famous, legendary people, they have the same number of days that you do, and it's not like they were doing magical days. They just, they got a little done every day, and that adds up to, to a monument, you know, they're putting one brick in a day. Eventually, they have this building, this legendary building. So, you can take writing, someone who, you know, there's two aspiring writers, and one doesn't ever write, doesn't, you know, manages to never, you know, zero pages a day, and the other one manages to do two pages a week, right? Not very much. The other one does zero pages a week, two pages a week. 98% of both of their time is the same. The other person, just 2%, they're doing one other thing. One year later, they have written, they write two books a year. This prolific person, you know, in 20 years, they've written 40 books. They're one of the most prolific writers of all time. They write two pages a week. Sorry, that's not true. That was two pages a day. Okay, two pages a week, you're still writing about a book every two years. So, in 20 years, you've still written 10 books, also prolific writer, right? Huge, massive writing career. You write two pages every Sunday morning. The other person has the same exact week, and they don't do that Sunday morning thing. They are a wannabe writer. They always said they could write. They talk about how they used to be, and nothing happens, right? So, it's inspiring, I think, for a lot of people who feel frustrated, they're not doing anything. So, reading is another example where someone who reads very, you know, doesn't read, and someone who's a prolific reader. You know, I always think about the Tyler Cowen types. I'm like, how the hell do you read so much? It's infuriating, you know? Or like James Clear puts out his 10 favorite books of the year, 20, his 20 favorite books of the year. I'm like, your 20 favorites? Like, I'm trying to just read 20 books, and it would be an amazing year. So, but the thing is, they're not doing something crazy and magical, they're just reading a half hour a night. You know, if you read a half hour a night, the calculation I came to is that you can read a thousand books in 50 years. So, if someone who's 80, and they've read a thousand books, you know, between 30 and 80, they are extremely well read. They can delve deep into many non-fiction areas. They can be, you know, an amazing fiction reader, avid fiction reader. And again, that's a half hour a day. Some people can do an hour, a half hour in the morning, audiobook. Half hour at night in bed. Now they've read 2,000 books. So, I think it's, it's just, it's motivating. And you realize that a lot of times you think that the people who are doing amazing things, and you're not, you think that there's a bigger gap between you and them than there really is. I, on the reading front, I'm a very slow reader, which is just a very frustrating fact about me. But I'm faster with audiobooks. And I also, I just, you know, I'll just, it's just hard to get myself to read. But I've started doing audiobooks, and I'll wake up, throw it on, do it in the shower, brushing my teeth, you know, making breakfast, dealing with the dogs, things like that, whatever, until I sit down. And that's, I can read, I can read a book a week, a book every 10 days at that clip. And suddenly I'm this big reader, because I'm just, while doing my morning stuff, I have it on, and also it's this fun, it makes the morning so fun. I'm like, having a great time the whole morning, so I'm like, oh, I'm so into this book. So I think that, you know, audiobooks is another amazing gift to people who have a hard time reading. I find that that's actually an interesting skill. I do audiobooks quite a bit. Like, it's a skill to maintain, at least for me, probably the kind of books I read, which is often like history, or like, there's a lot of content, and if you miss parts of it, you miss out on stuff. And so, it's a skill to maintain focus, at least for me. Well, the 10 second back button is very valuable. So I just, if I get lost, sometimes the book is so good that I'm thinking about what the person just said, and I just get, the skill for me is just remembering to pause, and if I don't, no problem, just back, back, back, back. Just three quick backs. So that, of course, is not that efficient, but I do the same thing when I'm reading. I'll read a whole paragraph and realize I was tuning out. You know? You know, I haven't actually even considered to try that. I've been so hard on myself maintaining focus, because you do get lost in thought. Maybe I should try that. Yeah, and when you get lost in thought, by the way, you're processing the book. That's not wasted time. That's your brain really categorizing and cataloging what you just read, and like. Well, there's several kinds of thoughts, right? There's thoughts related to the book, and there's a thought that it could take you elsewhere. Well, I find that if I am continually thinking about something else, I just say, I'm not, I just pause the book. Yeah, especially in the shower or something, when like, that's sometimes when really great thoughts come out. If I'm having all these thoughts about other stuff, I'm saying, clearly my mind wants to work on something else, so I'll just pause it. Be quiet, Dan Carlin, I'm thinking about something else right now. Exactly, exactly. Also, you can, things like you have to head out to the store like, I'm gonna read 20 pages on that trip. Just walking back and forth. Going to the airport, I mean, flights, you know, the Uber, and then you're walking to the, walking through the airport, you're shedding the security line. I'm reading the whole time, like, I know this is not groundbreaking. People know what audio books are, but I think that more people should probably get into them than do, because I know a lot of people, they have this stubborn kind of thing. Say, I don't like, I like to have the paper book, and sure, but like, it's pretty fun to be able to read. I still, to this day, I listen to a huge number of audio books and podcasts, but I still, the most impactful experiences for me are still reading, and I read very, very slow. And it's very frustrating when, like, you go to these websites, like, that estimate how long a book takes on average. Those are always annoying. They do like a page a minute when I read, like, best, a page every two minutes, at best. At best, when you're like, really like, actually not positive. I just, my ADD, it's like, I just, it's hard to keep focusing, and I also like to really absorb. So, on the other side of things, when I finish a book, 10 years later, I'll be like, you know that scene when this happens, and another friend will read it, and be like, what, I don't remember any, like, details. I'm like, oh, I can tell you, like, the entire, so I absorb the shit out of it, but I don't think it's worth it to, like, have to read so less, so much less in my life. I actually, so in terms of going to the airport, you know, in these, like, filler moments of life, I do a lot of, there's an app called Anki, I don't know if you know about it. It's a space repetition app. So, there's all of these facts I have. When I read, I write it down, if I want to remember it, and it's this, it, you review it, and the one, the things you remember, it takes longer and longer to bring back up. It's like flashcards, but a digital app. It's called Anki, I recommend it to a lot of people. There's a huge community of people that are just, like, obsessed with it. And, A-N-K-E? A-N-K-I, so this is extremely well-known app and idea, like, among students who are, like, medical students, like, people that really have to study. Like, this is not, like, fun stuff. They really have to memorize a lot of things. They have to remember them well. They have to be able to integrate them with a bunch of ideas, so. And I find it to be really useful for, like, when you read history, if you think this particular factoid, it'd probably be extremely useful for you, because you're, that'd be interesting, actually, to thought, because you're doing, you talked about, like, opening up a trillion tabs and reading things. You know, you probably want to remember some facts you read along the way. Like, you might remember, okay, this thing I can't directly put into the writing, but it's a cool little factoid. I wanna store that in there. And that's why I go Anki, drop it in. And it's just. Oh, you can just drop it in. Yeah, and you. You drop it in a line of a podcast, like a video? Well, no. I guess I can type it, though. So, yes, so Anki, there's a bunch of, it's called Space Repetitions, there's a bunch of apps that are much nicer in Anki. Anki's the ghetto, like, Craigslist version, but it has a giant community, because people are like, we don't want features. We want a text box. Like, it's very basic, very stripped down. So you can drop in stuff, you can drop in. That sounds really, I mean, I can't believe I have not come across this. You, actually, once you look into it, you realize that, how have I not come, you are the person, I guarantee you'll probably write a blog about it. I can't believe you actually have. Well, it's also just like. It's your people, too. And my, people say, what do you write about? Literally anything I find interesting. And so, for me, once you start a blog, like, your entire worldview becomes, would this be a good blog post? Would this be, I mean, that's the lens I see everything through. But I'm constantly coming across something, or just a tweet, you know? Something that I'm like, ooh, I need to share this with my readers. My readers, to me, are like my friends, who I'm like, I'm gonna, oh, I need to tell them about this. And so I feel like just a place to, I mean, I collect things in a document right now, if it's really good. But it's the little factoids and stuff like that, I think, especially if I'm learning something. So the problem is, when you save stuff, when you look at it, a tweet and all that kind of stuff, is you also need to couple that with a system for review. Because what Enki does is like, literally, it determines for me, I don't have to do anything. There's this giant pile of things I've saved, and it brings up to me, okay, here's, I don't know, when Churchill did something, right? I'm reading about World War II a lot now. Like a particular event, here's that, do you remember what year that happened? And you say yes or no, or like, you get to pick, you get to see the answer, and you get to self-evaluate how well you remember that fact. And if you remember it well, it'll be another month before you see it again. If you don't remember, it'll bring it up again. That's a way to review tweets, to review concepts, and it offloads the process of selecting which parts you're supposed to review or not. And you can grow that library, I mean, obviously, medical students use it for like tens of thousands of facts. It just gamifies it, too. It's like you can passively sit back and just, and the thing will make sure you eventually learn it all. You don't have to be the executive calling that the program, the memorization program someone else is handling. I would love to hear about you trying it out, or spaced repetition as an idea. There's a few other apps, but Anki's the big must. I totally wanna try. You've written and spoken quite a bit about procrastination. I, like you, suffer from procrastination, like many other people, suffering quotes. How do we avoid procrastination? I don't think the suffer is in quotes. I think that's a huge part of the problem, is that it's treated like a silly problem. People don't take it seriously as a dire problem, but it can be. It can ruin your life. There's, like, we talked about the compiling concept, with if you read a little, if you write, if you write two pages a week, you write a book every two years, you're a prolific writer, right? And the difference between, again, it's not that that person's working so hard, it's that they have the ability to, when they commit to something, like on Sunday mornings I'm gonna write two pages, that's it. They respect, they have enough, they respect the part of them that made that decision, is a respected character in their brain. And they say, well, I decided it, so I'm gonna do it. The procrastinator won't do those two pages. That's just exactly the kind of thing the procrastinator will keep on their list and they will not do. But that doesn't mean they're any less talented than the writer who does the two pages. Doesn't mean they want it any less. Maybe they want it even more. And it doesn't mean that they wouldn't be just as happy having done it as the writer who does it. So what they're missing out on, picture a writer who writes 10 books, bestsellers, and they go on these book tours, and they just are so gratified with their career. Think about what the other person is missing who does none of that, right? So that is a massive loss, a massive loss. And it's because the internal mechanism in their brain is not doing what the other person's is. So they don't have the respect for the part of them that made the choice. They feel like it's someone they can disregard. And so to me, is this in the same boat as someone who is obese because their eating habits make them obese over time or their exercise habits? That's a huge loss for that person. That person is, the health problems, and it's just probably making them miserable. And it's self-inflicted, right? It's self-defeating, but that doesn't make it an easy problem to fix just because you're doing it to yourself. So to me, procrastination is another one of these where you are the only person in your own way. You are failing at something or not doing something that you really want to do. It doesn't have to be work. Maybe you want to get out of that marriage that you realize it hits you, you shouldn't be in this marriage, you should get divorced, and you wait 20 extra years before you do it, or you don't do it at all. That is, you're not living the life that you know you should be living, right? And so I think it's fascinating. Now, the problem is it's also a funny problem because there's short-term procrastination, which I talk about as the kind that has a deadline. Now, some people, this is when I bring in, there's different characters, there's the panic monster comes in the room, and that's when you actually, the procrastinator can, there's different levels. There's the kind that even when there's a deadline, they stop panicking, they just, they've given up, and they really have a problem. Then there's the kind that when there's a deadline, they'll do it, but they'll wait till the last second. Both of those people, I think, have a huge problem once there's no deadline. Because, and most of the important things in life, there's no deadline, which is changing your career, becoming a writer when you never have been before, getting out of your relationship, you're gonna be doing whatever you need to, the changes you need to make in order to get into a relationship. There's, the thing after it, what? Launching a startup. Launching a startup, right? Or once you've launched a startup, firing is the right, someone that needs to be fired, right? Yes. I mean, going out for fundraising instead of just trying to, there's so many moments when the big change that you know you should be making, that would completely change your life if you just did it, has no deadline. It just has to be coming from yourself. And I think that a ton of people have a problem where they will, they think this delusion that, you know, I'm gonna do that, I'm definitely gonna do that, you know? But not this week, not this month, not today, because whatever, and they make this excuse again and again, and it just sits there on their list, collecting dust. And so yeah, to me, it is very real suffering. And the fixes and fixing the habits? Just, like not- I'm still working on the fix, first of all. So there's, okay, there is, there's, just say you have a boat that sucks and it's leaking and it's gonna sink. You can fix it with duct tape for a couple, you know, for one ride or whatever. That's not really fixing the boat, but it can get you by. So there's duct tape solutions. To me, so the panic monster is the character that rushes into the room once the deadline gets too close or once there's some scary external pressure, not just from yourself. And that's a huge aid to a lot of procrastinators. Again, there's a lot of people who won't, you know, do that thing, write that book they wanted to write, but there's way fewer people who will not show up to the exam. You know, most people show up to the exam. So that's because the panic monster is gonna freak out if they don't. So you can create a panic monster. If you wanna, you know, you really wanna write music, you really wanna become a singer, songwriter, well, book a venue, tell 40 people about it and say, hey, on this day, two months from now, come and see, I'm gonna play you some of my songs. You now have a panic monster, you're gonna write songs, you're gonna have to, right? So there's duct tape things. You know, you can do things, you know, people do, there's, I've done a lot of this with a friend, and I say, if I don't get X done by a week from now, I have to donate a lot of money somewhere I don't wanna donate. And that's, you would put that in the category of duct tape solutions. Yeah, because it's not, why do I need that, right? If I really had solved this, this is something I want to do for me. It's selfish, this is, I just literally just want to be selfish here and do the work I need to do to get the goals I wanna get, right? There's a, all the incentives should be in the right place. And yet, if I don't say that, I will, it'll be a week from now and I won't have done it. Something weird is going on, there's some resistance, there's some force that is in my own way, right? And so doing something where I have to pay all this money, okay, now I'll panic and I'll do it. So that's duct tape. Fixing the boat is something where I don't have to do that, I just will do the things that I, again, it's not, I'm not talking about super crazy work ethic, just like, for example, okay, I have a lot of examples because I have a serious problem that I've been working on. And in some ways I've gotten really successful at solving it, in other ways I'm still floundering. So. Yeah, the world's greatest duct taper. Yes, well, I'm pretty good at duct taping, I probably could be even better and I'm like, and I'm. You're procrastinating on becoming a better duct taper. Literally, like yes, there's nothing I won't. So here's what I know what I should do as a writer, right? It's very obvious to me, is that I should wake up. Doesn't have to be crazy, I don't have 6 a.m. or anything insane, or I'm not gonna be one of those crazy people, 5.30 jogs. I'm gonna wake up at whatever, you know, 7.30, 8, 8.30, and I should have a block, like just say nine to noon. Where I get up and I just really quick make some coffee and write. It's obvious because all the great writers in history did exactly that, some. Some of them have done that, that's common. There's some that I like these writers, they do the late night sessions, but most of them they do wake up. But there's a session, but there's a session that's. Most writers write in the morning, and there's a reason. I don't think I'm different than those people. It's a great time to write, you're fresh, right? Your ideas from dreaming have kind of collected, you have all the new answers that you didn't have yesterday and you can just go. But more importantly, if I just had a routine where I wrote from nine to noon, weekdays. Every week would have a minimum of 15 focused hours of writing, which doesn't sound like a lot, but it's a lot. A 15, no, this is no joke. This is, you're not, your phone's away, you're not talking to anyone, you're not opening your email, you are focused writing for three hours. That's a big week for most writers, right? So now what's happening is that every weekday is a minimum of a B, I'll give myself. I know an A might be, wow, I really just got into a flow and wrote for six hours and had, great. But it's a minimum of a B, I can keep going if I want. And every week is a minimum of a B, that's 15 hours. And if I just had, talk about compiling, this is the two pages a week, if I just did that, every week, I'd achieve all my writing goals in my life. And yet, I wake up and most days I just, either I'll revenge procrastination late at night and go to bed way too late and then wake up later and get on a bad schedule and I just fall into these bad schedules, or I'll wake up and there's just, you know, I'll say I was gonna do a few emails and I'll open it up and suddenly I'm texting, I'm texting, or I'll just go and I'll make a phone call and I'll be on phone calls for three hours. It's always something. Or I'll start writing and then I hit a little bit of a wall, but because there's no sacred, this is a sacred writing block, I'll just hit the wall and say, well, this is icky and I'll go do something else. So, duct tape, what I've done is, White But Why has one employee, Alicia, she's the manager of lots of things, that's her role. She truly does lots of things. And one of the things we started doing is, either she comes over and sits next to me where she can see my screen from nine to noon, that's all it takes. The thing about procrastination is usually, they're not kicking and screaming, I don't wanna do this, it's the feeling of, you know, in the old days when you had to go to class, you know, your lunch block is over and it's like, oh, shit, I have class in five minutes, or it's Monday morning, you go, oh. But you said, you know what, but you go, you say, okay, and then you get to class and it's not that bad once you're there, right? You have a trainer and he says, okay, next set, and you go, oh, okay, and you do it. That's all it is, it's someone, some external thing being like, okay, I have to do this, and then you have that moment of like, this sucks, but I guess I'll do it. If no one's there, though, the problem with the procrastinator is they don't have that person in their head. Other people, I think, were raised with a sense of shame if they don't do stuff, and that stick in their head is hugely helpful. I don't really have that, and so, anyway, Alicia's sitting there next to me. It's not, she's doing her own work, but she can see my screen and she, of all people, knows exactly what I should be doing, what I shouldn't be doing. That's all it takes. The shame of just having her see me while she's sitting there not working would just be too weird and too embarrassing. So, I get it done, and it's amazing. It's like a game changer for me. So, duct tape can solve, sometimes duct tape is enough, but I'm curious to, I'm still trying to, what is going on? I think part of it is that we are actually wired. I think I'm being very sane, human, actually, is what's happening. Or not sane is not the right word. I'm being like, I'm being a natural human that we are not programmed to sit there and do homework of a certain kind that we get the results like six months later. Like, that is not, so we're supposed to conserve energy and fulfill our needs as we need them and do immediate things. And we're overriding our natural ways when we wake up and get to it. And I think sometimes it's because the pain, I think a lot of times we're just avoiding suffering, and for a lot of people, the pain of not doing it is actually worse because they feel shame. So, if they don't get up and take a jog and get up early and get to work, I'll feel like a bad person. And that is worse than doing those things. And then it becomes a habit eventually, and it becomes just easy, automatic. It just becomes I do it because that's what I do. But I think that if you don't have a lot of shame, necessarily, the pain of doing those things is worse in the immediate moment than not doing it. But I think that there's this feeling that you capture with your body language, and so, like, I don't want to do another set, that feeling, that people I've seen that are good at not procrastinating are the ones that have trained themselves to the moment they would be having that feeling, they just, it's like zen, like Sam Harris style zen. You don't experience that feeling. You just march forward. Like, I talk to Elon about this a lot, actually, offline. It's like, he doesn't have this. It's like- No, clearly not. It's the way I think, at least he talks about it, and the way I think about it, is it's like you just pretend you're a machine running an algorithm. Like, you know you should be doing this, not because somebody told you so, and this is probably the thing you want to do. Like, look at the big picture of your life and just run the algorithm. Like, ignore your feelings, just run as if you- Like, just framing, frame it differently. Yeah. You know, yeah, you can frame it as like, it can feel like homework, or it can feel like you're living your best life or something when you're doing your work. Yeah. Yeah, maybe you reframe it, but I think, ultimately, is whatever reframing you need to do, you just need to do it for a few weeks, and that's how the habit is formed, and you stick with it. Like, I'm now on a kick where I exercise every day. It doesn't matter what that exercise is. It's not serious. It could be 200 pushups, but it's a thing that, like, I make sure I exercise every day, and it's become way, way easier because of the habit. And I just, and I don't, like, at least with exercise, because it's easier to replicate that feeling, I don't allow myself to go like, ugh, I don't feel like doing this. Right. Well, I think about that, even just like little things, like I brush my teeth before I go to bed, and it's just a habit. Yeah. And it is effort. Like, if it were something else, I would be like, oh, I'm gonna go to the bathroom, I'm gonna do that, and I'm just gonna like, I'm just gonna lie down right now. But it doesn't even cross my mind. It's just like, I just robotically go and do it, and it almost has become like a nice routine. It's like, oh, this part of the night. You know, it's like a morning routine for me, stuff is like, you know, that stuff is kind of just like automated. Yeah, it's funny, because you don't like go, like, I don't think I've skipped many days, I don't think I skipped any days brushing my teeth. Right. Like, unless I didn't have a toothbrush, like I was in the woods or something. And what is that? Because it's annoying. Well, so, to me, there is, so the character that makes me procrastinate is the instant gratification monkey. That's what I've labeled him, right? And there's the rational decision maker and the instant gratification monkey, and these battle with each other. But for a procrastinator, the monkey wins. Yeah. I think the monkeys, you know, you read about this kind of stuff, I think that this kind of more primitive brain is always winning. And in non-procrastinators, that primitive brain is on board for some reason and isn't resisting. So, but when I think about brushing my teeth, it's like the monkey doesn't even think there's an option to not do it, so it doesn't even like get, there's no hope, the monkey has no hope there, so it doesn't even like get involved. And it's just like, yeah, yeah, no, we have to, just like kind of like robotically, just like, you know, it's kind of like Stockholm syndrome, just like, oh, no, no, I have to do this. It doesn't even like wake up, it's like, yeah, we're doing this now. For other things, the monkey's like, ooh, no, no, no, most days I can win this one. And so the monkey puts up that like fierce resistance and it's like, it's a lot of it's like the initial transition. So, I think of it as like jumping in a cold pool, where it's like, I will spend the whole day pacing around the side of the pool in my bathing suit, just being like, I don't want to have that one second when you first jump in and it sucks. And then once I'm in, once I jump in, I'm usually, you know, once I start writing, suddenly I'm like, oh, this isn't so bad, okay, I'm kind of into it. And then sometimes you can't tear me away, you know, then I suddenly I'm like, I get into a flow. So it's like, once I get in the cold water, I don't mind it, but I will spend hours standing around the side of the pool. And by the way, I do this in a more literal sense, when I go to the gym with a trainer, in 45 minutes, I do a full ass workout. And it's not because I'm having a good time, but it's because it's that, ugh, okay, I have to go to class feeling, right? But when I go to the gym alone, I will literally do a set and then dick around my phone for 10 minutes before the next set. And I'll spend over an hour there and do way less. So it is the transition. Once I'm actually doing the set, I'm never like, I don't want to stop in the middle. Now it's just like, I'm gonna do this. And I feel happy I just did it. So it's something, there's something about transitions that is very, that's why procrastinators are late a lot of places. I will procrastinate getting ready to go to the airport, even though I know I should leave at three, so I cannot be stressed. I'll leave at 3.36 and I'll be super stressed. Once I'm on the way to the airport, immediately I'm like, why didn't I do this earlier? Now I'm back on my phone doing what I was doing. I just had to get in the damn car or whatever. So yeah, there's some very, very odd, irrational. Yeah, like I was waiting for you to call me. You said that you're running a few minutes late and I was like, I was like, I'll go get you a coffee because I can't possibly be the one who's early. I can't, I don't understand. I'm always late to stuff and I know it's disrespectful in the eyes of a lot of people. I can't help, you know what I'm doing ahead of it? It's not like I don't care about the people. I'm often like, for like this conference, I'd be preparing more. It's like, I obviously care about the person, but for some- I mean, I've interpreted it as like, there are some people that show up late because they kind of like that quality in themselves. That's a dick, right? There's a lot of those people. But more often, it's someone who shows up frazzled and they feel awful and they're furious at themselves. They're so regretful. I mean, that's me. And I mean, all you have to do is look at those people alone running through the airport, right? They're not being disrespectful to anyone there. They just inflicted this on themselves. This is hilarious. Yeah. You've tweeted a quote by James Baldwin saying, I imagine one of the reasons people cling to their hates so stubbornly is because they sense once hate is gone, they will be forced to deal with the pain. What has been a painful but formative experience in your life? Or what's the flavor, the shape of your pain that fuels you? I mean, honestly, the first thing that jumped to mind is my own like battles against myself to get my work done, because it affects everything. When I, I just took five years in this book and granted it's a beast. Like I probably would have taken two or three years, but it didn't need to take five. And that was a lot of, not just that I'm not working, it's that I'm over researching. I'm making it, I'm adding in things I shouldn't because I'm perfectionist, being a perfectionist about like, oh, well, I learned that, now I wanna get it in there. I know I'm gonna end up cutting it later. Just, or I over outline something, trying to get it perfect when I know that's not possible. So making a lot of immature kind of, like I'm not actually that much of a writing amateur. I've written, including my old blog, I've been a writer for 15 years. I know what I'm doing. I could advise other writers really well. And yet I do a bunch of amateur things that I know while I'm doing them, is I know I'm being an amateur. So that A, it hurts the actual product. It makes you know, B, it's waste your precious time. C, when you're mad at yourself, when you're in a negative, you know, self-defeating spiral, it almost inevitably, you'll be less good to others. Like, you know, I'll just, I used to, you know, early on in my now marriage, one of the things we always used to do is I used to plan mystery dates. You know, New York City, great place for this. I'd find some weird little adventure for us. You know, it could be anything. And I wouldn't tell her what it was. I said, I'm reserving you for Thursday night, you know, at seven, okay? And it was such a fun part of our relationship. Started writing this book and got into a really bad, you know, personal space where it was like, in my head I was like, I can't do anything until this is done. You know, like, no. And I just stopped like ever valuing like joy of any kind. Like I was like, no, that's when I'm done. And that's a trap or very quickly, you know, because I always think, you know, I think it's going to be six months away, but actually five years later, I'm like, wow, I really wasn't living fully. And for five years is not, we don't live very long. Like, you talk about your prime decades, like that's like a sixth of my prime years. Like, wow, like that's a huge loss. So to me, that was excruciating and, you know, and it was a bad pattern, a very unproductive, unhelpful pattern for me, which is I'd wake up in the morning in this great mood, great mood every morning, wake up thrilled to be awake. I have the whole day ahead of me. I'm gonna get so much work done today. And, but you know, first I'm going to do all these other things and it's all going to be great. And then I ended up kind of failing for the day with those goals, sometimes miserably, sometimes only partially. And then I get in bed, probably a couple hours later than I want to. And that's when all of the real reality hits me. Suddenly so much regret, so much anxiety, furious at myself, wishing I could take a time machine back three months, six months, a year, or just even to the beginning of that day. And just tossing and turning now. I mean, this is a very bad place. That's what I said, suffering, procrastinators suffer in a very serious way. So look, I, you know, I know this probably sounds like a lot of like first world problems and it is, but it's real suffering as well. Like it's, so to me, it's like, it's painful because you're not being, you're not being as good a friend or a spouse or whatever as you could be. You're also not treating yourself very well. You're usually not being very healthy in these moments. You know, you're often, and you're not being, I'm not being good to my readers. So it's just a lot of this. And it's like, it feels like it's one small tweak away. Sometimes it's like, that's what I said. It's like, you just suddenly are just doing that nine to 12 and you get in that habit. Everything else falls into place. All of this reverses. So if I feel hopeful, but it's like, it is a, I have not figured, I haven't fixed the boat yet. I have some good duct tape though. And you also don't want to romanticize it. Cause it is true that some, some of the greats in history, especially writers suffer from all the same stuff. Like they, they weren't quite able. I mean, you might only write for two or three hours a day, but the rest of the day is often spent, you know, like kind of tortured. Well, right. This is the irrational thing is if I, if, and this goes for a lot of people's jobs, people, especially who work for themselves, you'd be shocked how much you could wake up at nine or eight or seven or whatever, get to work and stop at one, but you're really focused in those hours, one or two, and do 25 really focused hours of stuff, productive stuff a week. And then there's 112 waking hours in the week, right? So we're talking about 80 something hours of free time. You can live, you know, if you're just really focused in your yin and yang of your time, that's what, that's my goal, is black and white time. I really focused time and then totally like clean conscience free time. Right now I have neither. It's a lot of gray. It's a lot of, I should be working, but I'm not, oh, I'm wasting this time. This is bad. And that's just as massive. So if you can just get really good at the black and the white, so you just wake up and it's just like full work. And then I think a lot of people could have like all this free time, but instead I'll do those same three hours. It's like you said, I'll do them really late at night or whatever. After having tortured myself the whole day and not had any fun, it's not like I'm having fun. I call it the dark playground, by the way, which is where you are when you know you should be working, but you're doing something else. It's you're doing something fun on paper, but it's, it's never, it feels awful. And so, yeah, I spent a lot of time in the dark. And you know, you shouldn't be doing it and you still do it. And yeah, it's not clean conscience fun. It's bad. It's, it's, it's toxic. And I think that it's, there's something about, you know, you're draining yourself all the time. And if you just did your focused hours and then if you actually have good, clean, fun, fun can be anything. You're reading a book, can be hanging out with someone who can be really fun. You can go and do something cool in the city. You know, that is critical. It's you're recharging some part of your psyche there. And I think it makes it easier to actually work the next day. And I say this from the experiences when I have had, you know, good stretches, it's like, it's you're, you know what it is. It's like, you feel like you're fist pounding one part of your brain, fist pounding the other part. Like you're like, you're like, we got that. Like, like we, we treat, we treat ourselves well. Like, it's how you're internally feel like I treat myself. And it's like, yeah, no, of course it's work time. And then later you're like, now it's play time. And it's like, okay, back to work. And you're in this very healthy, like parent child relationship in your head versus like this constant conflict and like the kid doesn't respect the parent and parent hates the kid. And like, yeah. And you, you're right. It always feels like it's like one fix away. So there's hope. I mean, I, I guess, I mean, so much of what you said just rings so true. I guess I have the same kind of hope. But you know, this podcast is very regular. I mean, I'm impressed. Like, and I think partially what, what there is a bit of a duct tape solution here, which is you just, the, the, the, cause it's always easy to schedule stuff for the future for myself, right? Because that's future Tim and future Tim is not my problem. So I'll schedule all kinds of shit for future Tim. And I will, and I will not then not do it. But in this case, you can schedule podcasts and you have to show up. Yeah, you have to show up. Right. It seems like a good medium for procrastination. This is not my, this is what I do for fun. I know, but at least this is the kind of thing, especially if it's not your main thing, especially if it's not your main thing, it's the kind of thing that you would dream of doing and want to do and never do. And I feel like your, your, your regular, you know, production here is a, is a sign that something is working at least in this regard. Yeah. In this regard, but this, I'm sure you have this same kind of thing with the podcast. In fact, because you're going to be doing the podcast, as part of the podcast becomes what the podcast is for me. This is your procrastinate. If you think about being 80 and if you can get into that person's head and look back and be like, just deep regret, you just, you know, yearning, you could do anything to just go back and have done this differently. That is desperation. It's just, you don't feel it yet. It's not in you yet. The other thing you could do is if you have a partner, if you want to partner with someone now you could say, we meet these 15 hours every week and that point, you're going to get it done. So working with someone can help. Yeah. That's why they say like a co-founder is really powerful for many reasons, but that's, that's kind of one of them because to actually, for the startup case, you, unlike writing, perhaps you, it's really like a hundred hour plus thing. Like once you really launch you, you go all in, like everything else just disappears. Like you can't even have a hope of a balanced life for, for a little bit. So, and their co-founder really helps. That's the idea. When you, you're one of the most interesting people on the internet. So as a, as a writer, you look out into the future. Do you dream about certain things you want to still create? Is there, is there projects that you want to write? Is there movies you want to write or direct or? Endless. So it's just endless sea of ideas. No, there's, there's, there's specific list of things that really excite me, but it's a big list that I know I'll never get through them all. And that's part of why the last five years really like, you know, when I feel like I'm not moving as quickly as I could, it bothers me because I have so much genuine excitement to try so many different things and they get so much joy from finishing things. I don't like doing things, but a lot of writers are like that. I, I, I publishing something is greatly, is hugely joyful and makes it all worth it, you know, or just finishing something you're proud of, putting it out there and have people appreciate it. It's like the best thing in the world, right? You know, a lot of every kid makes some little bargain with themselves, has a little, you know, a dream or, you know, something. And I feel like when I'm, when I do something, that I make something in this, you know, for me, it's been mostly writing and I feel proud of it. And I put it out there. I feel like I like, again, I'm like fist pounding my seven year old self. Like there's a little, like, I'm, I like, I owe it to myself to do certain things. And I just did one of the things I owe. I just paid off some debt to myself. I, I owed it. And I, and I paid it and it feels great. It feels like very, like, you just feel very in a lot of inner peace when you do. And so the more things I can do, you know, and I just have fun doing it, right. So I just, it's, it's, for me, that includes a lot more writing. I just, you know, short, short, short blog posts. I write very long blog posts, but basically short writing in the form of long blog post is, is a great, I love that medium. I want to do a lot more of that books yet to be seen. I'm going to do this and I'm gonna have another book I'm going to do right after. And we'll see if I like those two. And if I do, I'll do more. Otherwise I won't, but I also want to try other mediums. I want to make more videos. I want to, I did a little travel series once. I love doing that. I want to do more of that. Almost like a vlog. Like, no, it was, I let readers in a survey, pick five countries they wanted me to go. That's awesome. And they picked, they picked, they sent me to weird places. They sent me, I went to Siberia. I went to Japan. I went from there to, this is all in a row into, to Nigeria, from there to Iraq and from there to Greenland. And then I went back to New York, like two weeks in each place. And I get to, you know, each one, I got to, you know, have some weird experiences. I tried to like really dig in and have like, you know, some interesting experiences. And then I wrote about it and I taught readers a little bit about the history of these places. And it was just, I love doing that. I love, right. So, you know, and I'm like, oh man, like I haven't done one of those in so long. And then, and then I have a big like desire to do fictional stuff. Like I want to write a sci-fi at some point. And I would love to write a musical. That's actually what I was doing before Wait But Why. I was, I was with a partner, Ryan Langer. We were halfway through a musical and, and, and he got tied up with his other musical and Wait But Why started taking off and we just haven't gotten back to it, but it's such a fun medium. So it's such a silly medium, but it's so fun. So you think about all of these mediums on which you can be creative and create something and you like the variety of it. Yeah. It's just, it's, it's just that I, if there's a chance on a new medium, I could do something good. I want to, I want to do it. I want to try it. It sounds like so gratifying. So fun. You know, like. I think it's fun to just watch you actually sample these. So I can't wait for your podcast. I'll be listening to all of them. I mean, that, that's a cool medium to see, like where it goes. The cool thing about podcasting and making videos, especially with a super creative mind like yours, you don't really know what you're going to make of it until you try it. Yeah. Podcasts I'm really excited about, but I'm like, I like going on other people's podcasts and I never try to have my own. So there's this with every medium, there's the challenges of how the sausage is made. So like the challenges of the challenge of. Yeah. But it's also, I like to like, I'll go on, like, as you know, long ass monologues and you can't do it on, if you're the interviewer, like you're not supposed to do that as much. So I have to like reign it in and, and that's, that can be, that might be hard, but we'll see. You could also do solo type stuff. Yeah. Maybe I'll do a little of each. You know, what's funny. I mean, some of my favorite is more like solo, but there's like a sidekick. So you're, you're, you're having a conversation, but you're like friends, but it's really you ranting, which I think, I think you'd be extremely good at. That's funny. Yeah. Or even if it's 50 50, that's fine. Like if it's just a friend who I want to like really riff with, I just don't, I don't like interviewing someone, which I won't, that's not what the podcast will be, but I can't help. I've tried moderating panels before and I cannot help myself. I have to get involved. And no one likes a moderator who's too involved. It's very unappealing. So I, you know, interviewing someone and I'm like, I can't, I don't even know. I just, it's not my, I can grill someone, but that's different. That's my curiosity being like, wait, how about this? And I interrupt them and I'm trying to. Yeah, I see the way your brain works. It's hilarious. It's awesome. It's like lights up with fire and excitement. Yeah. I actually, I love listening. I like watching people, like listening to people. So this is like me right now, having just listening to a podcast. This is me listening to your podcast right now. I love listening to a podcast because then it's not even like, but once I'm in the room, I suddenly can't help myself by jumping in. Okay. Big last ridiculous question. What is the meaning of life? The meaning of like an individual life? Your existence here on earth or maybe broadly, this whole thing we've got going on, descendants of apes, basically creating. Yeah, well, there's, yeah. For me, I feel like I want to be around as long as I can. If I can do some kind of crazy life extension or upload myself, I'm gonna, because who doesn't want to see how cool 20, the year 3000 is. Imagine. You did say mortality was not appealing. No, it's not appealing at all to me. Now it's ultimately appealing. As I said, no one wants eternal life, I believe. If they understood what eternity really was. And I did Graham's number as a post and I was like, okay, no one wants to live that many years. But I'd like to choose. I'd like to say, you know what, I'm truly over it now. And I'm gonna have, you know, at that point we'd have, our whole society would have like, we'd have a ceremony. We'd have a whole process of someone signing off and you know, it would be beautiful. And it wouldn't be sad. Well, I think you'd be super depressed by that point. Like who's gonna sign off when they're doing pretty good. Maybe, maybe, yes. Okay, maybe it's dark. But at least, but the point is if I'm happy, I can stay around for five, you know, my, I'm thinking 50 centuries sounds great. Like, I don't know if I want more than that. 50, 50 sounds like the right number. And so if you're thinking, if you would sign up for 50, if you had a choice, one is what I get that is bullshit. Like if you want, if you're somebody who wants 50, one is a hideous number, right? You know, anyway. So for me personally, I want to be around as long as I can. And then honestly, the reason I love writing, the thing that I love most is like, is like a warm fuzzy connection with other people, right? And that can be my friends and it can be readers. And that's why I would never want to be like a journalist where their personality is like hidden behind the writing. Or like even a biographer, you know, there's a lot of people who would do as great writers, but it's, I like to personally connect. And if I can take something that's in my head and other people can say, oh my God, I think that too. And this made me feel so much better. It made me feel seen, like that feels amazing. And I just feel like we're all having such a weird common experience on this one little rock, in this one little moment of time, we're this weird, these weird four limb beings, and we're all the same. And it's like, we're all, we all, the human experience. So I feel like so many of us suffer in the same ways. And we're all going through a lot of the same things. And to me, it is very, if I lived, if I was on my death bed and I feel like I had like, I had a ton of human connection and like shared a lot of common experience and made a lot of other people feel like, like not alone. Do you feel that as a writer? Do you, do you like hear and feel like the inspiration, like all the people that you make smile and all the people you inspire? Honestly, not, sometimes, you know, when we did an in-person event and I, you know, meet a bunch of people and it's incredibly gratifying or, you know, you just, you know, you get emails, but I think it is easy to forget that how many people, sometimes you're stuck. Because you're just sitting there alone typing. Yeah. And you get procrastination. But that's why publishing is so gratifying because that's the moment when all this connection happens. And especially if I had to put my finger on it, it's like, it's having a bunch of people who feel lonely and they're like, the existence is all realized, like all, you know, connect, right? So that, if I do a lot of that, and that includes of course my actual spending, you know, a lot of really high quality time with friends and family and like, and making the whole thing as heartbreaking as like mortality in life can be, make the whole thing like fun. And at least we can like laugh at ourselves together while going through it. Yeah. That to me is the, yeah. And then your last blog post will be written from Mars as you get the bad news that you're not able to return because of the malfunction in the rocket. Yeah. I would like to go to Mars and like go there for a week and be like, yeah, here we are. And then come back. No, I know that's what you want. Staying there, yeah. And that's fine by the way. If I, yeah, if, so you think you're picturing me alone on Mars as the first person there and then it malfunctions. Right, no, you were supposed to return, but it malfunctions and then there's this, so it's both the hope, the awe that you experience, which is how the blog starts, and then it's the overwhelming like feeling of existential dread, but then it returns to like the love of humanity. Well, that's the thing. If I could be writing. Yeah. And actually like writing something that people would read back on Earth, it would make it feel so much better. Yeah. You know, if I were just alone and no one was gonna realize what happened. No, no, no, you get to write. Yeah. Perfect, perfect. Perfect is safe. Also, that would bring out great writing. Yeah, I think so. You know, your deathbed on Mars alone. I think so. Yeah. Well, that's exactly the future I hope for you, Tim. All right, this was an incredible conversation. You're a really special human being, Tim. Thank you so much for spending your really valuable time with me. I can't wait to hear your podcast. I can't wait to read your next blog post, which you said in a Twitter reply. You'll get more to, after the book, which add that to the long list of ideas to procrastinate about. Tim, thanks so much for talking to me, man. Thank you. Thanks for listening to this conversation with Tim Urban. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Tim Urban himself. Be humbler about what you know, more confident about what's possible, and less afraid of things that don't matter. Thanks for listening and hope to see you next time.

https://youtu.be/0Jd7fJgFkPU

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Anya Fernald: Regenerative Farming and the Art of Cooking Meat | Lex Fridman Podcast #203

The following is a conversation with Anja Fernald, co-founder of Belcampo Farms, that was founded with the purpose to create meat that's good for people, the planet, and the animals, specifically treating their animals as ethically as possible. In this, she sought to revolutionize the meat industry from the inside out. She's also a scholar and practitioner of regenerative agriculture, and she's a chef who has appeared many times as a judge on Iron Chef. Plus, she has one of my favorite food-related Instagrams. On top of that, she's also a longtime friend of Andrew Huberman, which is how we first got connected. Quick mention of our sponsors, Gala Games, Athletic Greens, Four Sigmatic, and Fundarise. Check them out in the description to support this podcast. As a side note, let me say that I got the chance to visit and spend a few days with Anja at Belcampo Farms in Northern California. I met many animals there, from cows to pigs, and saw the amazing land on which they grazed. I butchered meat, I watched Anja cook many amazing meals, I ate raw meat and cooked meat, and spent long hours at the bonfire talking with friends and listening to the sounds of nature. I hiked, swam in a cold mountain lake, and slept in a tent underneath the stars. It was an amazing eye-opening experience, especially in my first ever visit to a slaughterhouse. The term slaughterhouse is haunting in itself. The animals I met lived a great life, but in the end, they were slaughtered. In the most ethical way possible, but slaughtered nevertheless. Seeing animals with whom just the day before I made a connection be converted to meat that I then consumed was deeply honest to me. This ethical farm, Belcampo, represents less than 1% of animals raised in the United States. The rest is factory farmed. I could not escape the thought of the 40 to 50 billion animals worldwide raised in terrible conditions on these factory farms. I've spent most of my life thinking about and being in contact with human suffering, but the landscape of suffering in the minds of conscious beings is much larger than humans. I must admit that I still am haunted by human suffering more than animal suffering. Perhaps I will one day see the wrong in me drawing such a line. Either way, the visit to Belcampo farms made me realize that I have not thought deeply enough about the ethics of my choices and the choices of human civilization with respect to animals. And, more importantly, I have not thought or learned enough about large-scale solutions to alleviate animal suffering. Belcampo is paving the way on this and is the reason I wanted to show my support for their and Anja's efforts in regenerative farming and ethical treatment of animals. This is the Lex Friedman Podcast and here is my conversation with Anja Vernald. If you're watching the video version of this and are asking yourself why we're in nature right now, there's actually a beautiful mountain in the background. There's an incredible vast landscape. There's a farm. We're sitting behind a table and nevertheless, I'm wearing a suit and tie. Amidst nature, we're at the beautiful Belcampo farms. We're going to talk about that, this incredible place you have here, but you cooked some meat yesterday. It tasted delicious. So I'd love to talk about just the science and art of cooking first. You as a chef, when you think of cooking, is it a science or is it an art? Art and service together, probably. Art to me because it's about creating something of beauty and being responsive and creating something that's expression of creativity and love. Cooking also has a very strong element of service and it doesn't mean necessarily service to another person, but like service to health, wellness, environment. There's an element of supporting through food in how I approach cooking. So it's bigger than just like how the ingredients come together to form a taste. It's the whole pipeline, like the fact that there's a lot of work that went into bringing the ingredients together and then giving you the ability to make the meal and then who gets to consume the meal and the whole thing. And you see that as service as opposed to just the taste. Yeah, I also think of food as one of the key ways that we interact with our environment. Right? It's the part of our environment that goes inside us most visibly. Right? Of course, we interact with our environment. We could have skin creams that have certain things in them or our clothes can then be absorbed. There's things in the air. There's our water and there's food. Right? It's like how we're engaging in the world physiologically. It's the most significant way we engage in our environment. Right? We're extracting resources, calories, energy from the environment in various ways in order to preserve our bodies. There's also so many feedback loops that I don't think we know the beginning of that our bodies are picking up on around nutrients, available nutrients, immune response. There's deep levels of sensory evaluation that lead to health and alertness and wellness. You hear about this a lot with babies that if there's a risk of an infection that a mom's breast milk will help the baby develop a resistance. There's this way that our bodies can tune into health and can't extrapolate from that in any specific way. But think about that as an example of the many ways in which our bodies are reading available nutrients and food to signal other aspects of wellness and health. That said, the final product of cooking is when done well is really delicious. And what we ate yesterday was really delicious. So that aspect of it, bringing the ingredients together in a way that tastes delicious, do you see that as a science or art? That's the art of it. I mean, the art is like creating temptation and indulgence and giving people pause. You know, like creating experience that's like so sensual and so engaging. So sensual and like I love that about when I make something really simple and beautiful and delicious, the way that like there's that moment of silence at the table. And that to me is the moment of art, like of appreciation. What about the buildup? I mean, we got to watch you make the stuff over a fire. So the calmness of the air, I mean, that's an experience we don't often get to have to see that experience of the preparation. It's the anticipation, like you said. The most delicious part of a meal is the anticipation of it. That's something that I'm glad you bring up because it's an element that with eating so many of our meals like out of a bag and the instance where you start to eat the meals when the delivery shows up and you might smell something when you open the bag. And no judgment on that. That's something I do too. But that does take away a whole element of surprise and delight. And also, I think of your body's ability to prepare for it. You think about our most common memories of childhood for those of us who grew up in homes with parents who cooked is smell of things cooking. And it's not the eating of it. It's the smell of things cooking. So why is that so memorable? It's an anticipatory piece of food. That's what you remember about your experiences of food is the moment of sweet anticipation of this great sensual experience that's going to be really gratifying on these emotional and physical levels. So I think we're also resonating on those memories because it's an experience of food where the sensuality of it is kind of extended. So it's a long kind of arc of buildup. And then you're eating it. And it's amazing. And then you're enjoying it. And your body feels good. So all those pieces together, it's a much more memorable experience than just grabbing the cookie out of a bag. Right? So look at our own and just revisit in your mind the memories of food, the most compelling ones. It's the smell. And then the experience. And then sometimes how one felt. Right? Yeah. And the people involved with the smell. So somehow it's all tied in together, whether it's family or people close to you, or even if it's just chefs. There's something about the personality of the human involved in making the food that kind of sticks with you in the memory. And for me, I recently did a 72-hour fast. And there's a kind of sadness after you eat that it's over. I think the most delicious part was I went to the grocery store and just actually walking around and looking at food. Everything looked delicious. Even the crappiest stuff looked delicious. And I missed that. I really enjoyed that anticipation. And then I picked out the meal. I went home and I cooked it. And the whole thing took, I don't know, maybe two, three hours, the whole process. And that was the most delicious part. And the first taste, of course. And then after it was over, there's a bit of a sadness. Because the part I remember is the buildup, the anticipation. And then once you eat, it's over. We kind of focus on the destination, but it's the whole journey. The whole, like, even if you go to a restaurant, it's the conversations leading up to the meal and the first taste of the meal. That's where the joy is. And if you get to watch the making of that meal, that's incredible. That's where the smell, the visual, how the ingredients come together. And especially as we were looking over the fire, watching it, the fire play with the raw meat. And over time, bring out the colors, bring out the, I don't know, you can visually associate the flavor, how it becomes a little bit burnt on the outside. It has a crispiness to it. It starts to gain that crispiness. And immediately, your past memories of the delicious crispiness of various foods you've eaten are somehow mapped into your, immediately you start to taste it visually. I don't know. Yeah, that experience is magical. And of course, maybe it's the Russian thing, but I'm almost saddened when it's over. I think fasting is gaining in popularity because we're having to relearn the importance of being hungry in anticipation and delight. Yeah. We have such a fear of hunger, and that's really functional in evolution. But we have this deep fear of hunger, and part of the great American experience has been that we don't have to be afraid of hunger at all, because there's food everywhere, and it's really cheap. In all that abundance, we've lost this edge of hunger, and we don't let ourselves get hungry. And that's one thing that I learned in part of my journey as a cook and chef has been moving abroad was the first time when I lived out of the US, was the first time that I regularly experienced hunger. Because the time between meals was really long, and that was just what everybody did. And so I was hungry for two hours before lunch. And that was the first time in my life that there hadn't just been readily available snacks. So I wonder if the intermittent fasting and part of the popularity around it, I'm sure there's all these amazing metabolic things that are happening, but also people might also feel better because they're really anticipating and enjoying food. And then if you look at the feelings of fullness, there's a really interesting thing that happens when you cook and your sense of fullness, which is if you cook and you're hungry, the experience of being around the food, smelling it, touching it, sampling it, you'll take your hunger down by 40%. And this is my own observation. But as I mean, we've all had the experience of cooking Thanksgiving, and the cook never kind of wants to eat that much. Thanksgiving, that's an extreme experience. But when you really dive in and you're cooking for a few hours and you're smelling and smelling and smelling, it totally changes your threshold of satiety and fullness because of other sensory things that are happening. And for those of us looking to maintain weight and something to consider in this is that cooking is also part of what your appetite, when you're hungry, what are you hungry for? Right? So we tend to think about calories. But when you're hungry, you might also be hungrier for a wider range of things. And it might be smells, it might be stopping. There's other elements. And that's something I think as a cook that it's powerful to explore and be with and observe how your hunger changes when you're cooking. Well, let me ask the romantic question. When did you first fall in love with cooking? Me falling in love with cooking was about solving a problem in my family. And it had to do with my mom feeling very anxious about cooking and overwhelmed frequently when it came to meals. And I'm naturally very good at juggling a lot of things. And it was just something I could dive in and help and help my dad, who I'm very, very close to. So it was a very functional role where I would see this kind of crescendo of anxiety around mealtimes as a kid and would be able to dive in and solve things. And I also loved women who cooked. Like my father's mother is a great cook. She was, I remember her telling me as a kid, I was asking her about church and why she went to church. And she's like, I mostly go to church because I love cooking. She's like, I mostly go to church because I get to cook for the potlucks. And so there was an openness around that, but she just loved to cook for people. And there was this real tenderness and expression of that love. So seeing women in my life who had this real tenderness and love that they shared through food and then also being able in my own home to kind of pitch in and add value and help my mom and dad was really powerful for me. Because I felt like I had a superpower. You know, I felt like, oh man, I just made this stressful thing go away. That was huge. It's kind of interesting. I don't know if you can comment on, especially for me growing up in Russia, it's probably true in a lot of cultures, maybe every culture, that food, and especially like in a family, the mother that cooks is the source of love and like ties the family together, creates events where everyone comes together. It's one of the only chances of togetherness, the thing that bonds a family is like dinner or food, eating together. And I don't know what to do with that. It ties up with like dieting and so on. When I was on stricter diets, especially competing and cutting weight and stuff, it felt like I was almost like losing opportunity to connect with friends and family. It's interesting. It's almost like cultures, we cannot fully experience love and family without eating. And on the flip side of that, eating enables us to experience love and family. I don't know what to do with that. It's a tough one because there's lots of layers around kind of gender roles and families changing and things. I'd say I agree around the alienation. And I've done carnivore diet and I've tried some of these extreme protocols. And I too, I suffered from loneliness. It was like doing carnivore and not being able to eat what my kids ate and talk about it at the same time. Those pieces are real. And I wonder with all of these diets, if that structure is actually helping or just taking away from people's kind of sensual understanding. But I think that there's some rigor around that that helps people discover what's good for them. Yeah, by eliminating and then growing towards more intuitive food is a good evolution from that base. I love to cook for people. I love to pay attention to their way of being and read what they'd like to eat. And it's my purest way of love. And that's for everybody in my life. I actually love to cook for people I love. I would struggle to be putting out food all the time. It's like something for me, it's a real act of caretaking. So I definitely have that in my makeup. And I definitely notice in times of real stress, that's the piece that drops off. And it's like if I'm unable to care for myself, I have a hard time cooking. So for me, it's very emotional. It's very connected to love. And individualistic. So focused on the particular individual, it's almost like a journey of understanding what that person is excited about in the landscape of flavors. Figuring that person out what they like, what they love to eat. I mostly cook for myself. So I see that as almost a, this is gonna be the worst term, but an act of self-love. This is gonna be clipped out. That it's almost an exploration of what brings me joy. And it's surprising because I usually don't share because the things that bring me joy are the simplest ingredients. Like I'm one of those people, I don't know if you can psychoanalyze me, because you also like basic ingredients. I like a single ingredient, two ingredients, because I feel like I can deeply appreciate the particular ingredient then. I get easily distracted. You know people who are really good at listening to music, they can hear a piece of music and in their mind extract the different layers and enjoy different layers at a time. Like the bass, the drums, the different layering of the piano, the beats, and all that kind of stuff. That's what it means to truly enjoy music, to listen to a piece over and over. Like almost like as a scholar. And that same way for food, I just can't do more than like three, because then it's just, I have to give in to the chaos of it, I guess. But when it's just the basic ingredients, like just meat or just the vegetable, like basic grilled without sauces, without any of that, that I've discovered is what brings me a lot of joy. But that's boring to a lot of people. So I usually have to be kind of private about that joy. But that's mine, so I figured that out. And I guess as a chef, you have to figure that out about everybody that you care for. Well, also for you, you're very interested in things and interested in things being done well and appreciating them. So the single ingredient also allows you to control for perfection in cooking that, which is probably really appealing to you. And I think sometimes I see people also in the beginning of their journey of culinary trying to do too many things. Right. So there's another piece, too, that you'll notice. If you recall last night, I grilled us a salad, right? And then I did all those pieces separately. And that's something in general to be really attentive of when you're building flavor, to make sure you pay attention to every piece separately. You know, the idea that you can, OK, with a soup or something or stew, there's workarounds. But like to make a great dish that's got four or five vegetables in it, cook them all separately to their optimal deliciousness and then combine them. So that's another way to approach that is that you may also be able to look at the different ingredients separately and still have that sense of like understanding of it. But there's too often that we're layering together like four or five things and then cooking them all at once and then surprised that it's not delicious. Yeah. Because you can't really optimize on multiple variables at the same time for peak awesomeness. And that's actually, you know, the number one way you see this is roasting a whole chicken, which is a really difficult, it's the simplest dish, but it's very difficult. Because you have the breast meat, which is bigger chunks. They cook faster. You have the thighs and drums, which are smaller and they cook slower. To optimize that and pay attention to it and do it all right there, you're actually solving for different outcomes. So there's one example, but oftentimes food is less delicious with multiple ingredients at the start because we're not able to pay attention to how each one needs to end up. So there's a way to parse that apart and achieve a better outcome. I don't know if you've seen Gero Dreams of Sushi. It's a documentary about, yeah. So there's an obsession that that particular, first of all, set of humans, but also the particular cuisine that focused on the basics of the ingredients. What do you think of that kind of trying to achieve mastery through repeating the making of the same meal over and over and over for decades? Do you find beauty in that journey towards mastery or do you think it should be always an exploration to where you're always trying things? You're always injecting new flavors, new experiences, all that kind of stuff. I think you have to decide on a palette. If we're talking about an art, it's equivalent to saying, am I a sculptor or a painter? Yeah. The sushi lexicon thing, that's a very, very narrow, small canvas that you're painting on and that is a beautiful road, right? There's a beauty and a perfection to that. It's like, I mean, there's many things culturally around that that you could extrapolate for specifically for Japan. But I encourage people on the journey in food to choose kind of a language that they're working within. And if you want to step out of that occasionally and have one or two dishes, you can do that. You can have one or two dishes. But if you want to get mastery with food, you probably aren't going to be able to get more than, say, 20 ingredients that you use regularly that you really understand. And so we often see, I see the American pantry, it's got tons of sauces and tons of spices and tons of spice blends. And then really people only use just a couple of things. And the idea that you can sort of splash out and do Korean one night and then tacos the next night, you can absolutely. But to get in a regular cadence of specific ingredients, you're probably going to get more mastery with that sooner. And I think as much as you can do to get an understanding of the basics around salt and acid and understand your palate. For me, it's lemon and usually sherry vinegar, right? So that's my acid palate. And my fat palates, you know, suet and butter, olive oil. So you can sort of choose your language, what you're painting with. But I wouldn't splash out and say, do I use sesame oil? Yeah, every once in a while. But that's not part of my base palate, right? Mm-hmm, can you say again what your fat palate is? It'd be butter, suet and olive oil. And olive oil, so not white olive oil. Is it your routine? I like the flavor for finish because of the bitterness that it adds. So I like the bitter and acid contrast on meat and vegetables, which is mostly what I eat. And so I love that way that the bitterness and astringency complements and allows the flavors to come out. What do you think about coconut oil? I recently discovered that there's a sweetness or there's something to it that I really enjoy. Maybe because it's new. It's good with heat. I really love it for some reason. As a chef, do you ever try it? What do you think about it? I like it in coffee. Like I like it as a treat a little bit. I find the flavor a little bit challenging in foods. I also find that it's difficult on the quality of that ingredient. So I've found often that I buy a high quality coconut oil and there's rancidity in it. And I don't totally know why. I think it's just the cold chain and how that product's packaged. So I've had some issues with product quality in that. But for me, it's a little bit too much sweetness in my foods. But then again, I don't cook in like a Southeast Asian palate. I try to not have much sweetness in my foods in general. So I just because of the palate that I like to cook with. So for me, coconut's got a little bit too much of those high notes and earthiness, which is a nice combination, but it's more like a treat. Yeah, it is almost like a treat. It has a flavor of its own that almost stands on its own. Like I could probably just eat coconut. That's probably the only oil I could enjoy by itself. It sounds weird to say, but it feels like fat is often a thing that enriches the flavor of something else. Coconut can almost stand on its own. You might also be responding to that it's a complex flavor. So there's also an analogous, if you look at butter, for example, a lot of the butter that we eat in the US is just sweet cream butter. It's not cultured. If you explore like a cultured fermented butter, maybe a grass milk, grass-fed and finished butter, you're going to get a ton more complexity. And so you may also just be responding to having fats with more flavor, which is the journey in the US has been towards refined foods that are very neutral. And then you have to combine more of them to make things taste like things. And so if you're coming from a background of using mostly just generic butter or let's say canola oil to cook with, those are very neutral oils. So you can also take some of your favorite fats and look for versions of them that are more flavorful. I mean, I love olive oil as a treat in a spoon. Really? Like a good California extra virgin olive oil. I'll just have it as, I'll eat a piece of butter as a treat. Yeah. That's like, or butter with salt on it. Like good fats can, all of them can be, if they're minimally processed and they're fabulous and so delicious, right? But there are things that you have to look for a version of them that's got that full palette of flavor. Well, for me also, the flavors are inextricably tied to the memories I've had with those flavors. So for better or worse, back when I used to eat a lot of ice cream, I for some reason had a lot of pleasant experiences with coconut ice cream. So that particular flavor just permeates throughout my life. Now, like I'm stuck with it for better or worse as a flavor that brings up pleasant memories. And as I have a few such flavors, I have such relationship with all kinds of meat too. Like it's just so many pleasant memories and that's it. Like you're almost tasting the memories. Yeah. And there's no way to separate the flavor from the memories, I suppose. And that's a powerful thing. What's your favorite meal to cook? I'll roast a couple of chickens and then I'll poach them, like I'll boil them and let it cool. That's a complicated one. I'll let them cool down. I'll pull all the meat off, put the bones back into the pot and then cook that for like three or four hours. And then add in like shiitake mushrooms and all the chicken meat. And I'll throw in a bottle of white wine into the stock as well, a bunch of thyme and garlic. And I love it because it's the way the house smells. It's very laborious. It's soothing for me to spend time picking apart meat and chopping things up. There's like a lot of manuality around it. So I'd say from a personal, like, I mean, I love grilling a steak and doing those things as well. But there's something about making a stock from scratch and the way it smells, the way I feel, the time it takes, the kind of checking in on it that I really, really love. There's many things that I love to make that I don't even love to eat. I think you see this a lot in like baking and bakers, people who bake a ton. And they love the process of it, even if they don't eat that many baked goods. So anything for me that's really like enjoyable, is typically things like making cinnamon buns. I don't eat very many cinnamon buns, but I love making them. Because it takes all the sort of like fussing around and taking your time and watching it, the way it smells, the way the house smells, all of that stuff is like, it's like almost like a meditative exercise for me. Is there a science, is there an art to cooking meat well and the different kinds of meats? Is there something you can convert it towards, in to say ideas, how to bring out the best of it out of what particular meat, whatever steak we're talking about, whatever beef we're talking about? Is there something that can be said? The basic approach to cooking any type of meat, beyond the artistry of it, is pretty scientific. And it's what type of muscle is it in the animal? And what's the surface area to volume ratio? Okay, so let's look at those two questions. Yes. So the first piece is, what's the type of muscle in the animal? What's the functionality? You don't necessarily need to know that to evaluate it, but you need to understand, is it a tender muscle that's not used very frequently in the animal? Or is it a big load bearing muscle that gets a lot of action like the cheek, right, or the shin or those pieces? The muscles like those along the spinal cord that make up rib eyes and New York steaks and things, those aren't very exercised. They're right next to the spinal cord. Spinal cord's doing most of the work there. They're kind of like stabilizing muscles around this big functional muscle. It's a big functional piece of skeletal structure in the animal. Other muscles like the ones around the diaphragm with the flat iron steaks and skirt steaks and things, those are really functional muscles that are doing a ton and moving. And if they're moving a lot, what happens? Well, functionally, they've got lots of muscle sheaths, because muscles that move frequently have to do a lot of complex contraction. That's why in the cheek, for example, there's tons of visible fiber of collagenous connective tissue. That connective tissue is everything in how the meat cooks, because connective tissue doesn't respond to high heat with becoming more tender. Muscles do, right? They can get a sear on them. You can cut them and eat them. The collagenous tissue will glom up and get really tough. So you either have to liquefy it with really low, slow heat with moisture, or you have to barely cook it. So that's the major piece. That's the question of why wouldn't you just throw a brisket on the grill? It's not about the fat. You can cut the fat out. The reason you're not going to throw a brisket on the grill and cook it hot and fast is it's got too much collagenous connective tissue in it. Those are these giant muscles that have all this collagen and these fibers and tendons in them effectively. So you're never going to be able to just cook that up hot and fast. So that's the first piece. It's like, where's this muscle in the architecture of the animal? And then what does that mean for what's going on in the muscle? And that's actually more important than fat content. We get really kind of, we pay a lot of attention to fat content in muscles. You can make a steak tender if it doesn't have a ton of fat in it. It actually has more to do if there's collagenous and connective tissue in it. That's fascinating. I never even thought about that. I just, I thought it kind of universe, I mean, adds to the texture of the meat, the chewiness of the meat. But you're saying it's also adds to how heat, how it reacts to heat, how the entirety of the meat reacts to heat. And the fat is not as important to that as the collagen. The fat will make the flavor more delicious, right? Like it'll add unctuousness and mouthfeel and things like that. But all the connective tissue in meat and in some of the cuts like that we ate a skirt steak last night, you could see a web of that collagen sheath on the outside. On a rib eye, that same collagen sheath is this big. There's only one that goes around the outside. Okay. Because that muscle, there's one large muscle fiber. So that specific, it's a myelin sheath, right? That material needs moisture and low and slow heat to become tender. The other side of that is that when it becomes tender, it liquefies and it adds all this beautiful gelatinous consistency. That's what bone broth is. That's why a slow cooked pork shoulder is so delicious. It's not that it's full of all that fat. That fat's also great. But a lot of that mouthfeel comes from that really beautiful dissolved collagen. So when you're looking at like, how do I understand how I'm going to cook a piece of meat? That first fork in the road is how is this going to respond to heat? And what's the appropriate cooking technique? Then the second piece is that surface area to volume ratio. And that's important because the heat is going to impact the meat through the surfaces of the meat that are in contact with the heat. So if I have a steak that's three inches thick, I'm going to cook it extremely differently from a steak that's a half inch thick or three quarters of an inch thick. And that's the major, and that's the truth. If I have a piece of pork shoulder that's cut into cubes versus having a whole pork shoulder, that's surface area to volume ratio. That's going to totally change how I cook it. And same things like pot roast and a beef stew would be the same cut of meat, right? But how I cook them is going to change based on the surface area to volume. Because you've got to let moisture and heat work its way into the center of the meat. And that's going to be determined by the amount of surface of the meat that's in contact with whatever cooking liquid or heat you've got. Is there different sources of heat to play with? Like a big flame versus a small or maybe even like almost no flame, like over coals, all that kind of stuff. Is there some science to the source of heat in how it plays with the meat? Well, there's indirect heat and direct heat. And that really is mostly about temperature. And more than actual, I mean, smoke is important as well that can permeate, but really the smoke doesn't go into the center of most cuts that you barbecue. It'll come in like a smoke ring. It's maximum like half an inch on the outside, maybe a little bit deeper on a really long slow cook. So the smoke, that does create a ton of flavor on the surface of the meat. But that's so the indirect allows you to have smoke contacting it and then a very, very low and slow heat. And what that does is indirect heat will be low and slow enough that the center of the meat will get warm at the same time as the exterior of the meat. And it'll all cook equally and all get equally tender. If you go very hot and fast, you risk the interior of the meat not getting, right, you kind of create a shell on it and you slow down the interior of the meat, which you actually want to do with something like a steak where you want to keep it rare on the inside. So it's really indirect versus direct. Then once you get into direct heat, right, look at in that category, there's wood, charcoal, gas, right? That's about it. And those are meaningfully different. They're meaningfully different. Charcoal and wood, there's more poetry in wood. There's a little bit more flavor, not functionally very different. But gas versus charcoal wood is very different. And that's because of the actual scent of the cook, right, the scent of the flavor. And then there's, I think, an evenness of heat distribution that comes off of charcoal that's different from gas. Because no matter how awesome your gas grill is, you do have hotter and cooler spots. So gas grills are typically, you can kind of control for that if you just are going really hot and fast, which is why gas grills are fine if you're just like throwing that steak on, get a hard sear on it, those burgers, put a crust on it. Gas is fabulous for that. It's perfect. When you're doing things that do better with a low and slow cook, like let's say a whole tenderloin or chicken thigh, that's going to be a little bit less elegant on gas than on charcoal versus wood. So when you have more kind of nuance in the low, slow cook over the natural fuels. Talking about like smoke and flame and charcoal versus gas, it also adds to the experience and the smell and the whole thing of the cooking versus just like the taste it creates. There's a certain experience to like when there's a bit of smoke, maybe, I don't know what the chemistry of it is, but I feel like with smoke, the smell is distributed more effectively. I don't know if that's true. But there's a smell and a visual aspect to the experience that's almost enriched with a bit of smoke or like an open flame. Like if you could see the flame, there's magic to that. And it goes to the experience piece that we were talking about. We were talking exactly about that, like the nuance and the beauty of like that long, slow cook and your house smelling like something. Why do people freak out about barbecue? Yeah. Why? Because you go in and it smells bomb. It smells so good. It smells like heaven, right? It smells fatty and delicious and the smells everywhere and everyone's smelling the same smell. So there's like this collective experience. It's incredible. That's, I mean, I think that's why barbecue is so sticky for people. It's like so yummy and you get this huge like anticipatory thing about it. It's like, because it smells incredible. What was that incredible grill that we used yesterday? What is that about? That's called a Sea Island Forge. It's a wood fire grill that's inspired by the sea. It's a wood fire grill that's inspired by like a South American style of cooking. So it's like, it's big. It has also the things with the crank that allows you to control the distance from the flame. It's awesome. It's really key with the wood fire. So when we evolved from cooking over wood to charcoal, right, when that became more popular, the reason that we did that is that allowed us to skip the whole part of making our own charcoal, right? So when you're cooking over wood, all you're doing is making your own charcoal. You don't ever cook over wood with the red fire. Like we don't like throw a steak on when the flames are orange and leaping up because you're just going to get, you know, carbons like char all over your meat. So when you're cooking over wood, you first cook down the wood, you create the coal base, the natural coal base, and then you cook over that. So you saw yesterday I built my fire. I let it burn down, added some fresh wood so I could reinforce my coals with new coals coming in, but then I was actually cooking over the embers. You shorten that cycle with charcoal. It's more efficient. But what you lose is that whole cycle of, you know, that really beautiful experience of smelling. Now, if you're cooking on a Traeger, you're going to get awesome smoke smell. You know, like there's plenty of ways to do this. It doesn't always have to be wood fire. And I love all the different ways, right? But I really like the experience of the campfire. And I love that kind of just like sitting by it, building it, having to take the time. I like building the fire, going inside, preparing the fire. Going inside, preparing all my meats, bringing them out, cooking them. That whole experience start to finish is really just like something that it's my favorite way to spend time, you know? So I think, and why is that? Is the food that different than cooking it in a more conventional grill? Probably not, you know, like in a pure experience. But I think the actual experience is super memorable because you are outside, you are slowing your roll, you're enjoying this, you know, you're just taking in, you're watching, you're anticipating. I love that whole experience. Does the origin of the meat itself make a difference? So we're here at Balcampo Farms and we'll, maybe you could talk about what your vision, your dream is in terms of like food, in terms of where food comes from or meat comes from, but food broadly and how that affects the entirety of the culinary journey. On the question of where does it come from and does that matter? I'd say the way that meat is raised is massively important for flavor and for how it cooks. I think most cooks who try cooking grass-fed versus corn-fed, that's the first moment where they realize that, right? Where corn-fed meat cooks much more slowly, it's got bigger veins of fat that slow the heat transfer throughout the muscle of the animal compared to grass-fed, which is leaner, heat moves through it more quickly. Those steaks will cook much, much faster. So there's very kind of technical reasons why, how meat is raised that we're aware of. And there's other things that I've noticed like that slower growing poultry has a very, very different musculature and fiber to it than fast growing poultry. That's confinement animals, it's just, it has to do with the way that the muscles are built. They tend to be finer and thinner and more tender and a little bit more susceptible to heat. So the character of the meat's radically different. It's also much more flavorful when it's grown more naturally. And I think some of the reliance in the US on sugary sauces and lots of salts and flavors and things, that's actually based on having the broadly available meat out there is pretty low on flavor. And so we're adding in a lot to compensate for that. So to your point of enjoying things very simply and with salt and nothing else, the more flavorful that product is, I think the more people will find that enjoyable. Let's paint a vision. You're a visionary. You have a vision to have basically meat in every store that comes from a farm like Belcampo that's basically doing regenerative farming. How do we get there? It's about a network of smaller producers working together with shared values. And it's true that there's a limit on regenerative farming in that it requires more human knowledge. So regenerative farming is more difficult to scale in a single operation. It'd be really challenging to have a regenerative farm that was like 200,000 acres because of the amount of manpower needed to pay attention. Can you first, and I apologize to interrupt, but can you say what is regenerative farming? Sure. So if you're looking at scaling regenerative farming, it's a traditional system of agriculture. Regenerative farming is how we used to farm. We used to farm with an eye towards the long-term. You might be on the Friedman farm thinking about your heirs five generations from now farming that same land. Are you going to leave that land nutritionally empty? No, it's a long-term thinking. Also, in traditional ag, you don't have inputs that are very convenient. You can put some chicken manure on, but you can't spray or dump something that massively increases the growing potential of the land. That was not available until the past 60 years. So regenerative agriculture is an approach to farming where you're increasing soil fertility through your farming. You increase soil fertility by feeding the soil. You feed the soil through carbon. That's why regenerative farming is better for the environment. It sequesters carbon and puts carbon into the soil. Now, it's interesting. Plants need carbon and put it into the soil when they're going through growth. So if you have a beautiful field of grass that's just waving in the wind, that's not sequestering as much carbon as plants that have been damaged and are regrowing. Plants that have been damaged and are regrowing are repairing, and they're doing that by drawing down carbon as one of the nutrients that feeds them. To damage the plants effectively, that's what we're doing with regenerative grazing. So the cows or lambs or whatever out there, they're eating and taking the grass down, and that then causes a regrowth cycle that sequesters carbon. There's a limit to it. There's an edge. Because if those plants are so damaged that they can't regrow, then it turns into a dirt patch and that doesn't sequester any carbon. So it's a balance. How do you find that balance? That has to do with the soil fertility. It has to do with the frequency and the scale of the grazing, essentially. Exactly. So you have to find the right balance and that connects to both the grass. I mean, is ultimately the focus here is on the life cycle of whatever is grazing, whether it's cows or lambs or so on? That's why the scalability question. So all that stuff that I just talked about, think about all the actions that that requires. Somebody's out there looking and paying attention and understanding how far the grass is, remembering what happened in that field last year. There's a huge human intelligence need and human availability of attention. Now, industrial farming has done a great job at de-skilling agriculture. Industrial farming has taken agriculture from being art science to being a science. It's taken agriculture from being art science to being entry level employment. Yeah. So that's the limiting factor on regen. And that's why I think... The human intelligence piece. Exactly. I got to ask, I don't know if you think about this kind of stuff. I mentioned to you offline that I spent a bit of time with some robots and Boston Dynamics. Do you think there's a way to use artificial intelligence to help the data collection? Some of the things that makes humans special, make some of that decision, some of that memory that's then utilized, converted into knowledge to make decisions about the crops and so on. Is there a way AI can help? Do you think? Totally. I mean, that would be incredible. That's one of the ingredients that could help with the regenerative farming. There's a number of discrete decision points that could completely be automated as well in order to supplement and work with somebody, like a farmer in managing it, about the performance on land. And a bit of that's being done right now with some aerial mapping. But that type of AI would be huge in this. I mean, there's estimates that if the damaged and underutilized rangeland in the world was converted to regenerative agriculture, it's somewhere between 20 and 40% of the world's carbon could be sequestered. So there's a huge potential. The problem is cultural. We've lost the generational thread of knowledge about how to do this. It's kind of been two generations that haven't farmed this way. Also, the science around it is limited by the scale and longevity. So the data collection around regenerative farming is also limited by the fact it's kind of piecemeal. There's small operations that are doing it. They're learning and developing as they go, and they haven't been documenting it and doing it for too long. Is the ethical treatment of animals a part of regenerative farming? So in the way you do things at Balcampo, that's a huge part. Is that necessarily part of the life cycle? So the things that you're trying to measure is like the way, like not damaging the land too much, make sure that the land is constantly healthy and is producing, and then the grazing process, and also the carbon piece, the fact that it's carbon neutral or something like that. I mean, are all of those pieces of the regenerative farming, or is this an extra part to your vision that you're thinking about? It's all implicit and regenerative. Yeah. I call it out separately because we are certified humane, right, which is another layer of welfare that has to do with density and a couple other things. But regenerative, I mean, think about it. If you're a cow and you're in a regenerative operation where you're doing a lot of work as a cow and you're in a regenerative operation where the whole life cycle of the pasture means that you only eat the top six inches of the grass, and then when there's whatever, a couple inches left, then that field is left dormant, that's a better experience, right? So just think about it kind of functionally that way. Well, grazing period is a better experience, right? Yeah. And that's not what's done in, I mean, that's the grass fed piece, right? Well, that's the other piece with, you know, certified organics, amazing. There's plenty of certifications that, you know, grass fed and finished is also great, but there are workarounds for those. You can have certified organic feedlots. You can have grass fed and finished, which is an animal fed grass seed pellet. Those aren't things that we do here, right? And regenerative captures that because if you're, it's like anything, you're isolating these very specific certifications, it doesn't have a holistic approach. Regenerative though, unfortunately, isn't certified yet. We've gotten USDA approval to use that word based on our carbon sequestration data, but it's not a regulated term. So that's kind of the mix right now is to figure out how to document it. And it's not totally clear what it means like for pigs and chickens, which are omnivores. It's very clear for ruminants, which are animals that have a rumen that eat grass. For omnivores, which is like what we are, they eat primarily grain in farming operations, and that's a little bit more complex. So it's kind of a moving landscape, but regenerative as a word is the better definition of the whole life cycle approach of letting animals and nature work together. Is it true that it's possible to have a farm that doesn't produce, sort of is carbon neutral? We have been third party verified to be carbon impact negative. So Belcampo's 25,000 acres and the animals here, all of the carbon, including from our shipping on our mail order, is all offset by the amount of grazing that's happening. Also that encompasses our partner farms. We buy a number of live animals in from other partner farms. Their impact's also incorporated in that. I mean, first of all, that's incredible. And second of all, is that possible to scale? I don't see why it isn't. I mean, it's complex to scale, but I mean, we're putting people on the moon. We're putting people on the moon and you have a robotic dog. I mean- But that's less about scale. That's more about innovation. So like in many ways, what Belcampo has done is innovative at a small scale. The question is whether that innovation could be scaled. That's where I feel like we in the industry need more help. The AI piece, the intelligence, the thinking about ways to do things differently is where we need more support. And I think it's been a swing in the past couple years where it's like, meat's a mess. It's terrible. So let's ditch meat and opt for these hyper-processed plant-based solutions. And I am saying there's a way to make meat a part of the solution. And it's going to mean eating less of it. It's going to mean paying more for it. It's going to mean that the farming systems are more complicated. It's not the easiest path, but I think in the long term, it's the better path. And it's also better for human health. Can you comment on the certified humane piece? So how do you run a farm? Like, what does it mean to raise an animal from the beginning of its life to the end of its life in a way that's ethical, that's humane? I think the first piece you need to just be comfortable with is that making an animal into meat is something you're comfortable with. Because I think that's the biggest question, right? And so certified humane actually goes all the way through the death of the animal, how it's killed and handled at processing. So I put that out there just to say, well, this is all about producing an animal to die for meat. And that's not necessarily, that's something people struggle with with the word humane. And I understand that. Like, I have space and empathy for that. It's a complicated decision. And one you have to be comfortable with at the outset to say, this is an animal that's going to die to feed me. Yeah, so we should pause on that because I actually just two days ago read a paper that argued that the killing of an animal period cannot be humane. So it's impossible. And that's an argument just like you're saying we could make. But if we now on the table kind of take as a starting point the idea that it's possible to kill an animal for food in an ethical way. If we take that as a starting point. So we won't argue about that. It is worth arguing about it elsewhere. And I probably will. I will probably talk to a few vegan folks and we'll talk about the vegan diet. I'm fascinated by it as well. So I'm torn in the whole thing. But if we just take that as a starting point, what then is an ethical humane way to treat an animal? I look at ethical humane animal treatment as the major phases of life. So conception, birth and mothering, diet. Those are kind of the major touch points of life. So what we're looking at is evolutionary approach, which means is the animal eating what it evolved to eat primarily? Is the animal primarily outdoors, which is how all animals evolved given when the climate's appropriate for it? There are certain times when you can't have animals fully outdoors. Like here on our ranch, we have had issues with cold weather and things. If you have appropriate weather conditions, does the animal outdoors? Is the animal able to nurture and engage with its young? Those are the kind of key touch points. But it's really the birth of it. Let me start this one from the scratch. Okay. So when I'm looking at or when I consider what's humane, setting aside the death part, I look at the evolutionary diet, access to the outdoors, and ideally spending the majority of its life outdoors. Low density. So animals spread out and engagement with young, social interactions. And that's all kind of- Social interactions is a cool one. I mean, I also read an article that like cows, for example, have social, like they have friends. Yeah. Yeah. That's fascinating. I mean, that piece with the young social interaction with young social interaction with each other, that at a basic level, I'm sure that interaction is not as rich as humans, but that piece seems to be part of the humane picture. And you said also just a quick comment, evolutionary diet, meaning the diet that they were evolved to have. And that's pretty simple. You can look at the physiology of the animal and figure that out. So ruminant species are lamb, goats, and beef, and they have five stomachs. They evolved eating really low calorie, high fiber foods. That's why they've got all the stomachs. They need a lot of processing. You or I were to eat grass, we die in a week, right? Our physiology can't handle it. Cows were built and evolved to eat this very low calorie, very high fiber, very low density food. And they walk around slowly. They're moving constantly and they're eating it. When we put them on a corn fed diet, that's the opposite of their evolutionary diet and their systems really struggle with it. Now, pigs and chickens are different. Pigs and chickens are omnivores. And pigs will happily eat chickens, for example. Our pigs on the farm will hunt and kill rattlesnakes and eat them. They have to eat meat. And they enjoy all of it. They're omnivores. They're omnivores, so you often see, and I've seen people try to raise a grass fed chicken that doesn't exist. I mean, they need a higher, omnivores eat everything. They're what's called monogastric. They got one stomach. And that one stomach needs higher density nutrients. So in the case of chicken, if you were to look back in American history, in the 1950s, commercial chickens took like 54 weeks to come to full weight. Now it's two and a half weeks in confinement farming. In our systems, it's like eight, 10 weeks typically. So you have to give them some amount of nutrient density. But there's the idea that no grain, because that's a misinformation for any type of commercial operation, free range, regenerative, pastured, everything, you're going to have to have a grain feed to get any type of... It's actually, I think for the case of chickens, unless you're in a place with tons of natural seeds and grubs and worms and stuff to eat, really challenging for the chicken. So you got to give them some high density, high calorie food different from that. That's the evolutionary diet is a really key thing. That's the fundamental thing for health. And it's also interesting because the evolutionary diet ties to human health. I've looked at the nutritional analysis on all of our products and it's the evolutionary diet is for the case of beef and lamb gets their omega three to six ratios the same as wild game. So it's not like beef is really radically different from elk, a ruminant species, right? If you feed beef an evolutionary diet, their nutritional profile is the same as wild meat, as a wild ruminant. I got a chance to witness Neuralink. I don't know if you're familiar with that company, the brain, brain computer interfaces. And they have, I got a chance to see in person, just a bunch of pigs who had Neuralink chips implanted and taken out. Those pigs are so happy with life. I don't know. I've never seen a happier animal. I mean, cause they get to eat you cause you were mentioning sort of diets and stuff. Pigs seem to love a lot of stuff. They're easily made to be happy. I don't know if you can comment on your thoughts of exploring the capacity of the pig mind through some of this testing with Neuralink, whether that's exciting to you, whether maybe on the humane side, it's a little bit concerning. If there's something to be said on sort of like, yeah, I don't know if it's even the ethical side, but just because of your connection to me and to nature and understanding these living beings. Pigs are incredibly intelligent. So I'm not surprised that they're a subject matter for Neuralink. They're smarter than dogs and they're empathetic and emotional. And they're, we'll go look at our pigs afterwards and see, but they're, they're, they're kind of like joyful and exuberant when they're in good health. And so that, that makes sense. I'm interested in open. I feel that the kind of bleeding edge agriculture movement that I'm on the edge of in some ways, we're a larger operator, but we as a movement have to, we have to get into the game. We have to move forward in a way that allows us to scale if we want to be viable. So I think there has to be openness to how that can happen. And I also think there needs to be more thoughtful and noisy data about how regenerative ranching can sequester carbon. I mean, thousands of American ranches are selling carbon credits right now. The data is that valid. And they're not selling carbon credits from like grassland that just got a fence around it. They're selling carbon credits for verified data from animals assisting in carbon sequestration. Right. So there's got to be a way to get the tech community involved in ways to help regenerative agriculture scale. In different creative ways. And actually, that'd be interesting if like Neuralink somehow has, especially because Elon Musk is involved and Kimball Musk has his whole effort and appreciation of regenerative agriculture that I wonder if Neuralink has a role to play. Like exploring the neurobiology of the animal, if that somehow will create innovations that lead to improved scaling of regenerative agriculture. That'd be interesting. But you're saying you should be open to all those possibilities. I don't think, I don't know the landscape to know what. Yeah. But my sense is that it's very hard. It's very hard. And our farming operation to scale has been incredibly complex and challenging. We now work with partner firms, I see their operations, they're incredibly complex. You know, it just seems like there's got to be a way to make some of these things simpler and easier to share information. Yeah. I don't know what that answer is. You know what would be cool is if we can understand deeper ways to measure the happiness of an animal. Because then we can optimize, like certified humane could be literally an optimization problem. Just make sure as opposed to kind of using our project, our own human values, actually measuring what the animal is happy doing. That could be so understanding the pig brain might help us understand pig happiness and like reframe what it means for a happy animal. And then maybe it's a lot easier to make a happy animal to make the animal happy than we think. And it might have to do with a variety of delicious food in the case of the pig. Is there something you could say about grass fed meat? Is it all just out of my own sort of curiosity, whenever people say sort of grass fed meat is better for you, are all grass fed meat made the same? Is there a different like, it's like the word organic. Is there a lot of variety within that? Like the way Belcampo does it, others do it. Just more color if you could add to this whole word and what it means. Grass fed beef has been on grass its entire life. And you want to look for the words 100% grass fed. Or grass fed and finished. Now, the challenge with feeding beef grass its whole life is that it gains weight more slowly. Although beef didn't evolve eating corn and things, it can eat them. And in eating them, it gains weight more rapidly and has like a version of like an inflammatory response. You actually look inside the rumen of the animal inside the stomach, it's like black and shiny inside compared to grass fed animals like green, smells like compost. So the animals themselves, their whole physiology is damaged by that food. But they also gain weight really quickly and they put on a lot of fats. Like if you or me were to eat a bunch of processed food compared to eating a bunch of greens, it's the same impact. You're going to blow up. So the problem for grass fed is getting the animals to gain weight. They're getting a ton of exercise, they're eating really clean, right? And they're super chill. So that's different from the animals that are kept still eating really nutrient dense foods and under a ton of stress, which is a confinement animal. So are all grass fed meats created the same? The diet, yeah, nutritional profile broadly, but the length of time that the animal lives is extremely important for the flavor of the meat. We're taking our beef to 24 to 26 months. Conventional is around 18 months. So I'm always looking, if you're evaluating grass fed animals, you want to get animals that are typically allowed to live for longer because their flavor is going to be better, there's going to be a bit more fat. And their omega ratios also vary very differently. And I've seen omega ratios, on our farm, everywhere from one to three to one to one, ideal is one to one game is typically one to one or one to two of omega three to sixes. But in operations where you don't have year round grass, it's more complicated. You're feeding hay and you don't get that three to six ratio. Omega threes come from green grass. They're the fat in greens. And so they're scarce and costly. So you can have grass fed and finished animals that don't have that perfect ratio because maybe they're in a climate or for whatever reasons, we've had to do it too during the droughts to do hay finishing. It's not optimal, changes the ratio a bit. So there's a little bit of variance within it. I'd say though, the variance within grass fed is still small compared to the variance between conventional and grass fed. So there's definitely things to look for with the diet. There's a lot to look for within it, but the real difference is between those two. Also thing to notice is that it's not a verified word. Okay. So grass fed means animals that have been on grass at some point in their life. The way the cattle industry is in the US, there's segmentation. So there's cow-calf operations. Then those calves get sold to stocker operations, which raised animals in their teens basically, and then those get sold to feed lots. And so those three phases, that first phase of the cow-calf is always on grass. It's mother cows and mom cows are amazing. They can thrive on anything and still put all their nutrients into their baby and their babies will be healthy. So you never are putting mother cows on really premium pasture. So it's usually just kind of like okay pasture, dirty lot. If you ever see kind of like scrubby lots with lots of cows and calves on, that's a cow-calf operation. So there's also a loophole, unfortunately, where people use the term grass fed and they're actually referring to animals that at some point in their life had grass, but that might be pretty far in the rear view mirror. So you need to look at that grass fed and finished or grass fed 100%. That ratio of omega-3s to 6s, it changes in like a week on grain. Wow. So it's radically different. Unfortunately, it's the same thing for you and me. You could eat clean for a month. You eat junk for three days, you're garbage, right? It's not like you can just like coast on that, right? We know what that's like. Same thing for animals. Our physiology changes. Food's the number one way we interact with our environment and our body changes really rapidly and dramatically. So we know belcampo and just the way sort of this regenerative farming approach of belcampo and the sort of how humane is good for the land, is good for the animal. Can you comment on ways it's good for the human that eats the meat? Is this meat better for you? Yes. And this is where the kind of focus on the joy and animals doing yoga and all this sort of like cynical stuff about this type of agriculture. Say just like, set that aside. It really is better for your health. It's got a better fat ratio. It's less inflammatory. It's got higher protein. It's just a better product. I mean, in the case of beef, it's lower in fat and that fat is a better quality and it's higher in poultry and pork is also higher in protein. So all the nutritionals are better. It's got higher density of vitamins, got higher density of minerals. And none of this stuff is radically different than, you know, it's not like it's the product is black and white, but every metric meaningfully is better in the right direction across the board. So why wouldn't you? I hesitate to take anecdotal evidence as like final scientific conclusions, but it does seem I've eaten quite a bit of belcampo meat, for example, and it just, my body seems to respond like is less bothered by it. Meaning like less inflamed. I just feel better because I mostly eat a meat diet and it does seem to be a little bit of a difference. What kind of meat I eat, where it comes from. I don't know if that's my own psychology also. I mean, there is an aspect to like when you know that the meat came from a good place and all the ways we've defined good, you feel better about it and that has an effect like decreased stress. So I'm a huge believer in that, like outside of just nutrition, how you feel about the whole experience is a huge impact, but it does feel like the meat itself is actually just leading to less inflammation for me or like less like the bloated feeling and all those negative effects that could come with meat versus like certain other ground beef that I eat like store-bought chicken breast or steak, all those kinds of things. My body's a little bit more, works a little bit harder to process that food, it feels like. I don't know if there's science to that, but sort of anecdotally, that seems to be the case. Omega-6s are a big part of that in the case of the meat. You eat a lot of beef, you love beef. And so in a conventional beef product, it's a 1 to 30 ratio of omega-3s to 6s and sometimes 1 to 20, 1 to 30, but that's the wrong direction. In our beef, it's as low as 1 to 1. So that and the omega-6s are what's part of inflammation. Now, the magic in animals is that they're incredibly efficient processors and in the same way that the body can process and take out tons of things that are toxic out of the environment, I mean, animals' bodies can do that too. So the beauty of meat is that it can be pretty clean. Things like Roundup and stuff don't end up in the meat. When we have antibiotics in our meat, we're not worried about getting like tetracycline from the chicken breast. What we're worried about is the workers getting tetracycline, the chicken growing faster than it should, the meat being chewier and not as high quality. But the actual antibiotics don't, the animals are great at filtering that. They get that out. So you have to think about meat not as like contamination of like, oh, there's going to be some of that garbage they used in the farming in my meat, but it's the more subtle things. It's the fat ratio, it's the protein density. And there's also just, I think in my experience, there's just more complex flavor and things that taste more complex. This is, science backs this up. They fill you up faster. So if you're looking to limit, to eat for fullness and but not eat as many calories, more complex foods are the way to do that. And that hit, you hit your satiety, help you hit that satiety. So things like, I mean, all the key amino acids that help you feel full, mostly from meat, right? So those are, that's part of it, but all meats have those. Then there's other kind of micronutrients and things around that complex flavor that help you feel full faster. Forgive me for this question, but it is kind of an interesting one that people are curious about. What does it feel like to be a, or what does it take to be a woman CEO of a meat company? I mean, you're no longer CEO of Belcampo, but you did, you ran, you co-founded Belcampo, you ran it for many, many years. What, is there something that you could say in terms of challenges associated with that? And how did you personally overcome it? So to be a female running a meat and livestock operation, I felt very alone a lot, you know, for a long time. I felt very, like everybody waiting for me to fail or watching and assuming that I was like just good at marketing or whatever else. And so it's taken me a while to not internalize that. I think the only reason I'm here is we have our own supply chain in Slaughterhouse. And I think had I really been playing in the broader meat industry, it would have been a shorter journey. You know, it would have been very hard to make it even get to this phase. But I do, you know, I think the mission is my life's work. The mission of cleaner ingredients that taste so amazing, you don't need to do too much to them. You know, I like creating food that's in support of good health. And then secondary to that, it's the environment. But I want healthy food to be a joy to eat. And that's, you know, creating innovation in the space for this company has been about building a brand that people understand and is transparent and that people believe in in an industry that's broadly perceived as pretty corrupt. So those are things I feel enormously proud of. So you focused on the mission and the pushback, all the mess of the industry. You try not to internalize it, try not to let it affect you and focus on the mission. It's been hard. And the joy of it and the part where it's gotten fun for me has been returning to what I love about it. And I've only had the privilege of doing that pretty recently. So I think for me personally, you know, starting, I host these events on the farm called Meat Camps where I cook and teach people to cook and, you know, taste and talk about flavor and all the like essential aspects of it that are my fire. Like thank goodness I did that stuff because otherwise it was just such a beating. So there were parts of it where I got to feed my fire. And then now in the past year since resigning, I do all the recipe development. I shoot all the content. I, you know, taste product. I'm developing all of our new products. I launched our meatballs. I'm just about to launch our chicken meatballs. We're doing a high protein bone broth. Like those are, that's what, why I did this was to be able to build this great product that I could build on. So I'm kind of at that place now. But it's taken a lot longer. And I think, you know, looking at the landscape of what to do in food, this is definitely, we tackled the most complicated problem. That I can imagine, you know, I did it like in the most old fashioned way. Right? So it's been super complex. And then I also look at it and I'm like, yeah, and it's been messy and it's going to continue to be hard. But I'm proud of having tackled the hard problems. So the hard problem here is not in the space of technologies. It's in the space of bringing something that we've done for a long, long time in our human history and scaling it in the face of all the other economic pressures. Like doing so successfully, also communicating to the rest of the world that this is a powerful solution. So inspiring the rest of the world that regenerative farming, like running a company in this kind of way that's humane for animals, good for the land, good for people, even if it costs, like if there's an increased cost to the meat, even if that, if you have a broader vision, that means eating less meat overall, that that is, that is like inspiring the world that this is a future we want. And just taking that on and getting that done. I got a chance to eat a little bit of cheese, which, which is a good opportunity to talk about your experience in Italy. You spent some time, or as South of Europe, I'm not sure if it was Italy. Yeah, I lived in Italy, but. And there's cheese involved, right? Like what, what did you take away from that experience, both as a chef and as a human being? I moved to Europe right after my early twenties, and I worked as a cheesemaker. And I lived in really small rural farms in the countryside, and I got up early and milked animals, made cheese. And I got to live in a traditional agricultural society and learn how they ate. So it shaped me as a cook because it was a chance to have incredible ingredients, learn how to cook very simple food. I had been immersed in thought that I wanted to be like a chefy chef, right? Because I love food and I love cooking and I, and I was just drawn to that world. But I don't like the experience of that sort of like fancy food experience is not my, not what, what is exciting for me about it. So I loved working in that environment because I got to eat lunches and dinners and everything with the farm that I lived on and just very traditional, simple way to eat. The other piece of it is, you know, I went to high school in the nineties, child of like the low fat generation, right? And it was just really liberating and amazing to eat tons of super fatty foods and olive oil all over the place and bleak slabs of bread and salami and being this like vibrant health, like be leaner, you know, happy, no skin stuff, you know, stop getting split ends. Like I stopped having flaky nails, like just stuff that had bothered me my whole life, including like just moodiness. And that all just changed. And granted, I was also like living on a farm in Italy and getting up with the sunlight. And like there were lots of great aspects of my life as well that happened in that time. But I was just immersed in this diet that I realized like, man, this is so simple. And I also loved that I had like, you know, you'd have dinner and it was just like some ricotta cheese with some olive oil, some bread and like a bowl of fava beans. It's like, that's dinner. And it kind of broke down my assumptions too about like dinner always has to be this, you know, a protein and a vegetable and, you know, being more fluid and more seasonal was exciting for me. So I just learned kind of a lot about paying attention to food, simple preparation, and the vibrancy of health that I personally experienced kind of made me double down on that. Our mutual friend, Andrew Huberman, mentioned something offline to me about something involving the mob. Oh, yeah. Is there something you could share or are people going to hurt if you share this? It's far enough in the rear view mirror. I mean, I was hired by this group in Sicily on, and this is, you know, I was all of like 21 years old. And to get a permit to work there, you have to show that you have a competency that nobody else in Italy has. And that competency for Anya Fernald at the time was cheese expert. So it was like this stupid American girl being like going to the consulate. So I already knew that it was like there was something wobbly about this organization. But I went to work for them. And my boss from that time did end up in federal prison for corruption many years later, embezzlement primarily. But so I was definitely in an environment that was answering to multiple masters. And it was, it was. I couldn't have asked for a better way to kind of get with life and understand how things happen in the world, though. You know, of learning as somebody who tends to be super direct and not very subtle. It was amazing to be in this world where like everybody communicates in multiple levels. Like we're going to lunch with my boss with somebody we're going to do a business deal with. And they ordered a glass of wine and with that order communicated like disappointment. Because the father, the person who had made that wine had offended that other guy. I like that level of stuff where like nothing happened directly. I'm like, what are we talking about afterwards? I'm like, what happened at lunch? It's like, oh, I just, you know, I told him this by ordering that, whatever, you know, that kind of thing. So understanding that there's different ways of communicating. But it was also, you know, it was interesting to see and I think I, you know, it's kind of the struggle that I've lived again and again in my life. Fundamentally what we were doing in that operation was there's a very traditional cheese called the Ragusa cheese in Southeastern Sicily where I lived, Ragusa. And it was about scaling that operation. So it was European Union money that my boss was also unfortunately using for other things. But fundamentally it was to take that, this type of very small scale cheese, get them exported, help them scale, and we did it. And it was really challenging. I learned a lot about the safety issues and collaboration issues and creating groups of farmers for scale. So it's kind of been doing the same thing again and again. But Sicily, it, you know, it was also just the first place where I would regularly forage for food. You know, like there I'd go to friends' houses and we'd like go out and pick nettles or go out and pick wild asparagus. Every season there was stuff that you would be gathering and that was just part of how you lived and it was part of your health. So that was, I just learned a ton in that time about like simple eating and really that healthy food, the simpler it is, the better, right? Like this sort of sense that healthy food isn't in a tiny package, granola bar, lots of labels, lots of powders. It's like the more simple essential, closer to the land can actually lead to optimal health. You learned to appreciate the simplicity of food, the beauty within the simplicity. I think it's because it was the first time that I had amazing food quality. Okay. Because in the, where I grew up, there wasn't that food quality. Like I had some stuff from my garden and things that were great, but that's the kind of place where when artichokes in season, all of a sudden there's guys selling artichokes on their bicycles in the street and they're just fresh picked and you'd get that one thing or the torpedo onions or the like, so there's a seasonality and celebration of things in their peak moment and you would just have that one thing. And that was the first time I'd ever eaten in that way. You were a judge several times on Iron Chef. How do you judge a good meal? Like what your own, other people's, like what rating system is good? I mean, I go on experience and think about how many of your like most memorable fantastic meals are like three star Michelin meals. It's more about the experience, right? It's more about that slow down. Who are you with? And some of our best meals are like the most simple things. So Iron Chef, those were fun experiences. It's a lot of sous vide though. It's a lot of sauces. It's a lot of powders. I mean, it's kind of like magic food. So that's not, I mean, it's incredible to watch it as science, but I don't know if those are my most memorable meals. So the experience is how you judge a good meal for you personally. If you were a judge of the entirety of the human experience in terms of the culinary journey, that would be like the people you're eating with, the environment, like how you feel, the journey, the building up to that meal, like the whole thing. You can't separate it out. When I was learning as an apprentice cheesemaker in Greece, one of the best meals of my life is like a bowl of cold sheep milk yogurt with like a crust of cold fat on top. Basically like the way that these fatty, you know, sheep milk can have double the percentage of fat than cow milk. So like there's the yogurt and then there's this crust of fat and then they pour the fresh honey over the top and you just eat like this bowl of yogurt, probably top five meals of my life. Right? I mean, and it just, that's the simplicity, just the best thing. And it was the fact that it's in terracotta and I'd had this amazing day and, you know, all of these things come together, but I still remember that feeling. And I think most of us have those like really great sensual memories of food and they're not about necessarily that one fancy over the top restaurant or something. It's really about the whole context of enjoyment. Maybe you can help me with something. So I think offline said that we're both introverts a bit, but I certainly find joy in repetition. So I kind of hide away as an introvert and eat the same thing over and over and over again. But at the same time, I had this conversation with Tyler Cohen, who's an economist, but he's also a food critic. He writes these incredible posts about different foods. And we had this conversation about what his last meal would be if he had to choose, like, what is the best meal he's ever eaten that he would want to eat? And he had a good answer about it. It had to do with experience. I think if for him it was a particular Mexican restaurant and it had in Mexico because of the ingredients, because of the experience, because of the work it took to get there and all those kinds of things. But also made me realize like when I was going home after that conversation that I couldn't answer that question myself. Like what is the best meal I've ever eaten? Because I really haven't experienced much. And so it almost was like a challenge to myself. Like I feel like I should journey out a little bit more in this life and try stuff and to try to see like what is the best meal for me in the world? You know, like both the experience and the taste. So I was kind of wondering first, I'd love to ask you like what your last meal would be or what is the greatest meal you've ever eaten? But also, and you're still very young, and so there's still more experiences to be had, and for me, like how do you go about finding the best meal in the world? Is there advice you could give essentially? There's that sense of anticipation, right? So if it's the best meal, I'd say for you it would need to be on the heels of something where you'd pushed yourself with a fast or with an athletic event, right? Or something like you would be coming into it with a sense of anticipation because of deprivation. You would be hungry for it in a bigger sense of the word, like hungry for deep nutrition on your soul level as well as your belly. So I'd say that you'd have to think about it as a phase of things, like multiple things. And then I also think, you know, you love meat, you love cheese, you have to have some things that come together, right? Like there's got to be some specific elements of just your favorite flavors in that. But there could be flavors yet to be discovered. That's a whole other thing because I just emotionally and physically feel good on meat. But that doesn't mean like maybe like a rice-based dish like sushi or something like that. Or Indian cuisine where it's like sauces and the breads and whatever. I love that stuff too. So we're not talking about like, you know, a meal is an experience that could be like a one-night stand but with a piece of food, right? It could be a totally different than what actually makes you feel good when you eat it every day. Yeah, absolutely. Completely, completely analogous. I get that. I mean, you also though, there's elements of comfort and love and those different pieces for you. But I think you got to look at like where would you go somewhere? Like would you go to a place where you could, you know, hike in Japan and then end up in a little place where you'd eat something? That's where I would think you are going to have that magic moment. You know, maybe someplace you go to Mongolia and you're in a really extreme environment for three or four days and then you come back and you're in a farm and you get something on the table that's a surprise and you're hungry. Like that's going to be the moment where you're going to explode in the sense of like the culinary level. For Alex, it levels up, right? That's the journey for you. It has to be, I think from understanding you, like a combination of that pushing yourself, anticipation and something about the – Approval of some sort. Exactly. Well, I definitely, definitely like some fasting is part of a great meal for me. So like 24 hours is like the minimum. You're more sensitive to the richness of any experience for me when I fast 24 hours. And so that's a requirement. For a good meal, it's 24 hour fast, I think. It's just like you're able to taste – I don't know, maybe psychological – but you're able to disassemble the various flavors in a meal as simple as like even a chicken breast. There's all kinds of flavors going on. Because like when you cook a chicken breast, there's like the outside, the inside. I mean the volume of the meat tastes different as you eat like the different fibers. And you can like tell all those differences as you're eating when you're fasted and you can appreciate that. And of course, you're right, part of the journey is important. It makes me think like whether restaurants is the right place to explore. I'm envisioning it on a farm for you. I'm envisioning it in a place that's like really into ag and food. You know, like even a place like Romania. You know, like there's incredible farms, right? Where it's not going to get any like fancy restaurants there, but you're probably going to have some amazing little cheeses and cured meats. And you might go to some, you know, have some experience and end up in a place with like four things on the plate and each of them blows your mind. You know, like or Japan is another place like that. I think Vietnam, Laos, like I mean those are countries where there's like these incredible niche ingredients and this essentialism around food. That's fascinating. Or maybe it's in Russia with Putin. That might be the best meal in the world. With him on the farm? Yeah. That'd be, it's hard to reproduce that. If that is in fact a good meal, it'd be, you know, it's hard to get them out to the farm. But maybe one time, maybe the best meal. What about you? I think for me, like it's the ingredients that I associate with like indulgence. Like it'd be fresh bread with like my favorite culture butter on it. Be food of my childhood. I grew up in Oregon. We always had salmon and I smoked salmon or salmon eggs, like really good salmon eggs. I love cheese. I love goat cheese. I love all kinds of cheese. There'd be cheese. I love meat, obviously. I'm imagining it's sort of like an abundance of like 10 things I love. It's not a dish. You know, it's like all the yummy things. All of your indulgences on the same plate. Yeah. There isn't like for me, there's not like a big cake or something super like that. It's like really yummy things that I love, like really fresh, crusty, delicious bread that's warm and it's got a bunch of butter on it and I can put some salt on it and eat a big slab of that. That's just, that's where I'm at. That's funny. And so meat to you is not like one of those indulgences? Oh, definitely. That'd definitely be steak there too. I'm just imagining not like there isn't a specific dish. It's like eight or 10 things, right? It's the fresh bread. It's something like fishy, yummy. There'd be really good fresh berries too. There'd be a steak or a pork chop or something like meaty and delicious and savory. There'd be some cheese. Just a bunch of different things that I love to eat that like all kind of check boxes for me is probably what would make me happiest. I'm afraid of variety. I like the focus when you can just, this is all you have. The scarcity of just this is the one ingredient and really appreciating it or maybe one thing, like one full complex flavor, whatever the heck that is. It's like the distraction, the serial dating nature of having a bunch of things in a plate is yeah, for some reason that prevents me from fully enjoying any one of them. I don't know why that is. The more healthy way to do it is the varieties. Your way is the healthier way to do it. Is alcohol involved? I don't drink very much. I like red wine, but I just don't really. I love red wine with good food. I also co-founded a rum business that's an organic rum, so I love that product. For me, it's like I'm more interested in the food, I'd say. Is there some connection between your chef life, cooking and music? Does this music have a role in the experience? I love artistic expression. That's always had a role in my life in the same way I love to paint and draw and all the different things. I was a professional musician when I lived in Sicily by definition, technicality, because I played in the municipal band. I would march around the town with all the funerals. I get 50 euro every time I'd march in a funeral playing my oboe. I like that because, like you were talking about going to farms, what I quested for was experience and connection in places where I could learn things. That's been the through line of my learning journey. I've learned things and sought knowledge that I can't get in any conventional learning environment. What are the tools that let me do that? It was like being adaptable and comfortable in different cultures, but also having common ground points that allow you to connect with people. Music's one of those things. I love music, but there's any number of different... Enjoy a food, being able to pitch in, help in the kitchen, play cards. When you're dealing with getting into farming communities and stuff, that stuff really helps. I basically have cultivated tools that let me drop into places where I can learn. Those are all of a piece. Those are just tools to get in there. That said, we did listen to some Justin Bieber earlier today. I need to get more into him. I need to understand the full complexity of the Biebs. You're trying to achieve what hunting stands for, but at a much larger scale, which is what belcampo stands for. What are your thoughts on hunting as a source of meat? It's amazing. 100% pro-hunting. I think the reason that hunting flips the switch for so many people is because it's the first thing that had clean meat in their lives. I think that the hunter's journey, when people get so turned on by hunting, they're just like, oh my God, I'm never going back. I'm saying that's great if you've got access to that or if you know the guy who'll give you the backstrap, awesome. That's not achievable for most of us. I do think that talking to hunters about their experiences, what they love about it, many of them are just outdoors. I say that because most of them are men, but most of them love the outdoors aspect of it and being out in the wild. A lot of them, it's because of how they feel when they eat the meat. It's because they're eating... 99% of meat in America is made a very specific way. It's in a way that is pretty inflammatory, not incredibly delicious. When you're on that extreme and then you toggle to having this totally different style of product, it feels radically different in your body. Of course, you're like, I'll never go back. When I talk about us being on that spectrum, it's like, well, hunting meat's... I can never on any commercial operation create the variety of the biodiversity of species that an elk gets when it's wandering around of its own. There's no way you can do that on a farm. There's always going to be that extra 5% or 10% that those wild animals are going to have. Those wild animals also fast for longer, so they go through periods of starvation. That creates an even slower growth for musculature. That's going to create even more unique flavor and characteristics. That's why there's that extra in the hunted meat. You can come a lot closer with regenerative traditional farming to that flavor and health than with any other type of farming I know. That's where I see it on the spectrum. I love that people are getting excited about game because it's better for your health. It's got all the same characteristics as regenerative farm meat. It gets people turned on to simple, delicious food. You shouldn't have to cover food with sauce that's got corn syrup and soy, a bunch of junk in it to make it palatable. If you got to put sauce on your food, you need to look at your ingredients. You need to revisit what you're starting from. Because if you have to put a bunch of things to mask flavor onto anything you're eating, you're trying to basically fool your palate into doing what's not best for your body. We're trying to tell our palates, like, just make it through this plate so you can get the calories in. We're masking the fact that we don't actually find it very appetizing. We're teaching ourselves to overcome our instinct with food. We're saying, here's this bland base substrate, not very interesting. I'm not sparking to it. Awesome. Put sugar and salt on it. This upped the hyper-processed flavor profile. Great. Done. Then you're sparked to it. That's a very short road. I think a lot of the health problems we have now is because we're masking flavors and basically trying to get ourselves to move down this path of the same way we behave around all hyper-processed foods. That gets us into a mess with our health. If we can get things like game, where people love the flavor out of the gate, but it's natural, simple, minimally processed, that's a win. It reverses that hyper-processing trend that we're on as a human species. That's the promise of regenerative farming. That's the promise of hunting. Obviously, the former can be scaled. The hunting, I think, cannot be scaled. But in many ways, the hunting inspires the world that this is the right way to eat. That naturally leads to then the humane farming, regenerative farming idea, which is this idea that hunting represents. How do you scale that? Well, if you look at like, we're talking about people use the marketing language of happy cows or that kind of thing. If you're talking about the happiest animals, it's wild animals. If you wonder why these practices are good, talk to hunters. You're talking about animals that have lived in their evolutionary capacity, who have played their role in the ecosystem, who've lived their meaning of life. That's a very powerfully different kind of role than livestock production. I think if we can make our livestock production as similar to wild as possible, then we're a lot of steps closer. So you said the animals are happiest in the wild and that's where they find meaning. What about us, the human animal? What's the meaning for us, do you think? You've monitored the life cycle of a lot of living beings. You ever look in the mirror and think like, why the hell are we humans here? I mean, thriving, reducing suffering, creating goodness. I mean, those are the things I see in animals' behavior. They're mostly interested in reducing suffering and nurturing. Those are the things that I think evolutionarily. And we humans are just clever and we want to be able to try to do that at a bigger and bigger scale. As much as possible, reduce the suffering in the world. And somehow that alleviates us of our own suffering. That's the Russian thing. What life is suffering and somehow helping others alleviates it. And come up with creative solutions to do that. That's really interesting. It's almost consciousness is the thing that led to suffering, but it also led to the desire to alleviate the suffering. It's a feedback loop. Consciousness creates suffering and the desire to alleviate it. Is there yet a pretty nonlinear life? Your parents were professors. You have done a lot of incredible things that many would say, how the hell are you going to get this done? Is there advice you can give to young people today? Like high school, college, about how to live a similarly nonlinear crazy life and accomplish be as successful as you have been about whether it's just their career or life in general. The greatest gifts I've been given have come from pursuing curiosity. Just trying to understand the thing you're curious about and allowing yourself to be curious about and just going with it. And also pursuing things that are deeply joyful for me. Not what society wants, but you just personally. Just on your own, you're happy that you did it. And that's something that in the times when I strayed from that, my life has been harder. So it's fundamentally what are we on earth to do? To live and thrive. And so pursuing things that are curious and satisfying and interesting and joyful and allow me to grow. So I made a number of choices to do things that were more complicated and not considered cool at the time. Although now it's cool to work on farms. It wasn't when I started my career in animal agriculture. And it was just deeply interesting to me. And I felt like there was just lots to learn. And so that's been the path for me. It's like going for something that's curious and hard and kind of sticking with it and being open to it and growing elements that give me joy through that. For people who are starting out in their careers and want to do something different too, it's like get out of your comfort. Go to a place that you've got something to learn from and let it teach you that. And you'll get beat up. I got beat up by that experience. It was really hard. I laugh about now working for Instaslave for CheezMay. And the funny experiences I had there. But it was hard. I was lonely. I cried a lot. It was stressful. It was hard. It was really hard. When you were inside of it, you didn't know how it was going to turn out. You didn't know it was going to turn out well. And I'm like, why didn't I get a job doing something that all my friends are doing? And I didn't speak the language. I had to learn a foreign language and learn how to function. And it was very lonely and very challenging. But then that's where my resilience started to grow. So the things I learned there ended up just being about resilience and understanding the language of subtlety and meaning. So that's something that's carried me through my life. But it was a curiosity about cheesemaking and about just living in a village that was there. I'm like, wouldn't it be amazing to just live in a really rural village? And then you just went with it. And I was just like, this seems incredible and have a place where people seem interesting, the food seems good, and let's just try this and see what I can learn. And putting yourself out of your comfort zone in a place where you have a chance to learn and grow is the secret. Because you grow through discomfort. People think that you grow when you get into this environment where everything's sailing along. But growth actually comes through pain. Growth comes from being cut down and beat down and having to regrow and double down. And so that kind of opportunity, you have to seek it out. You have to put yourself in the line of fire a bit. If the situation sucks, it's a sign that you might be doing something right in the sense that you're on the path at the end of which you'll be a better person if you allow yourself to grow in that way. Like as opposed to resisting it, just going along with the journey and persevering. And that ended us up in this incredible place. This whole conversation, I'll probably overlay a video. I'm looking at a gorgeous mountain and it's an incredible farm. Thank you so much for a meal yesterday. That was incredible. The cheese, the fish eggs, just everything about this place. Looking up, you can see the stars, the stars at night are beautiful and there's a peacefulness to it. I had a pretty hard week actually, just emotionally in many ways. And just coming here, it's immediately so much of it is lifted. So I really deeply appreciate Anya that you would invite me here and that you have this conversation. This was really awesome. So thank you so much. Thanks for listening to this conversation with Anya Fernald and thank you to Gala Games, Athletic Greens, Four Sigmatic and Fundrise. Check them out in the description to support this podcast. And now let me leave you with some words from the ancient Chinese philosopher Lao Tzu. Nature does not hurry, yet everything is accomplished. Thank you for listening. I hope to see you next time.

https://youtu.be/ew8U43IXTfk

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Silvio Micali: Cryptocurrency, Blockchain, Algorand, Bitcoin & Ethereum | Lex Fridman Podcast #168

The following is a conversation with Silvio Micali, a computer scientist at MIT, winner of the Turing Award, and one of the leading minds in the fields of cryptography, information security, game theory, and most recently, cryptocurrency and the theoretical foundations of a fully decentralized, secure, and scalable blockchain and Algorand, a company of cryptographers, engineers, and mathematicians that he founded in 2017. Quick mention of our sponsors, Athletic Green's nutrition drink, the information in-depth tech journalism website, Four Sigmatic Mushroom Coffee, and Better Help online therapy. Click the sponsor links to get a discount and to support this podcast. As a side note, let me say that I will be having many conversations this year on the topic of cryptocurrency. I'm reading and thinking a lot on this topic. I just recently finished reading The Bitcoin Standard, a book I highly recommend. As always with this podcast, I'm approaching it with an open mind, with compassion, with as little ego as possible, and yes, with love. I hope you go along with me on this journey and don't judge me too harshly on any likely missteps. As usual, I will play devil's advocate. I will, on purpose, sometimes, ask simple, even dumb questions, all to try and explore the space of ideas here with as much grace as I can muster. I have no financial interests here. I only have a simple curiosity and a love for knowledge, especially about a set of technologies that may very well transform the fabric of human civilization. If you enjoy this thing, subscribe on YouTube, review an Apple podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Silvio Macaulay. Let's start with the big and the basic question. What is a blockchain and why is it interesting? Why is it fascinating? Why is it powerful? All right. So a blockchain, think of it, is really a common database distributed. Think about it as a ledger in which everybody can write an entry in a page. You can write, I can write, and everybody can read, and you have a guarantee that everybody has the same copy of the ledger that is in front of you. So whatever you see on page seven, anyone else sees on page seven. So what is extraordinary about this is this common knowledge thing that I think is really a first for humanity. I mean, if you look at communication, like right now, you can communicate very quickly images, or thoughts, or photos. But do you have a certainty that whatever you have received has been received by everybody else? Not really. And so there's a commonality of knowledge and the certainty that everybody can write, nobody has been prevented from writing whatever they want, nobody can erase, nobody can tear a page of a ledger, nobody can swap page, nobody can change anything, and that is an immutable common record is extremely powerful. And there's something fundamental that is decentralized about it, so at least in spirit, some degree, against maybe a resistance to centralization. Absolutely. If it is not decentralized, how can it be common knowledge? If only one person or a few people have a ledger, the only way, you don't have a ledger, you have to ask, you know, what is on page seven, and how do you know that whatever they tell you is on page seven, they tell the same thing to everybody else? And so this commonality is extremely powerful. Just to give you an example, assume that you do an auction, okay? You have worked very hard, you build a building, and now you want to auction off. Makes sense, because you want to auction worldwide, better yet, you want to tokenize the building and sell it in parcels. Now, everybody sees the bids, and you know that everybody sees the bids. You and I see the same bid, and so does everybody else. So you know that a fair price has reached, and you know who owns what and who has paid how much. And if you do it instead of a decentralized system, I put a bid, say, oh, congratulations, Alex, you won, and your price is $12,570. How do you know? So if instead of this, common knowledge is a very powerful tool for humanity. So we return to it from a bunch of different perspectives, including like a technical perspective, but you often talk about blockchain and some of these concepts of decentralization, scalability, security, all those kinds of things. But one of the most maybe impactful, exciting things that leverage the blockchain, this kind of ledger idea of common knowledge, is cryptocurrency in the financial space. So is there, can you say in the same kind of basic way, what is cryptocurrency in the context of this common knowledge and in the context of the blockchain? Great. Cryptocurrency is a currency that is on such a ledger. So imagine that on the ledger, initially, you know that somehow, say, you and I are the only owner of each one, let's give it ourselves a billion each, or whatever this unit. Then I start writing on the ledger, I give 100 of these units to my sister, I give this much to my aunt, and then now, because it's written on the ledger and everybody can see, my sister can give 57 of these units she received from me to somebody else. And that is money. And that is money because you can see that somebody who tenders your payment has really the money there, right? You don't have any more of a doubt when you want to sell an item. If I write you a check, is the check covered? Or do I have the money at the moment of a transaction? You really see, because the ledger is always updated, what you see is what I see, what the merchant sees, you know that I have the money. So it's the most powerful money system there is because it is totally transparent. And so you know that you have been paid, and you know that the money is there, you have not to second guess anything else. So the common knowledge applied there is you're basically mimicking the same kind of thing you would get in the physical space, which is if you give 100 of that thing, whatever, of that cryptocurrency to your sister, the actual transfer is as real as you giving a like a basket of apples to your sister. Because, so in the case in the physical space, the common knowledge is in the physics of the atoms, and in its digital space, the common knowledge is in this ledger. And so that transfer holds the same kind of power, but now it's operating in the digital space. Again, I apologize for a set of ridiculous questions, but you mentioned cryptocurrencies and money. What is money? Why do we have money? Do you think about this kind of from this high philosophical level at times of this tool, this idea that we humans have all kind of came up with and seem to be using effectively to do stuff? Money is a social construct, okay, in my opinion. And this has been somehow, people always felt that somehow money is a way to allow us to transact, even though we want different things. So I have two sheep, and then you have one cow, and I want the cow, but you are looking for blankets instead. So to have money, it really simplifies this. But at the end of it, and that's why a bit was invented, and you start with gold, you start with corniage, and then you start with check. But at the end of the day, money is essentially a social construct because you know that what you receive, you can actually spend it with somebody else. And so there is a kind of a social pact and social belief that you have. At the end of the day, even a barter requires these beliefs that other people are going to accept the quote unquote currency you offer them. Because if I'm a mason, and you ask me to build a wall in your field, and I did, and you, in exchange, you give me a thousand sheep, what am I going to do, eat them all? No, I have to feed them. And if I don't feed them, they die, and my value is zero. So in receiving this livestock, I must believe that somebody else will accept them in return for something else. So money is this social belief, social shared belief system that makes people transact. That's fascinating. I didn't even think about that. You're actually, you have a deep network of beliefs about how society operates. So the value is assigned even to sheep based on that everyone will continue operating how they were previously operating. Somebody will feed the sheep. I didn't even think about that. That's fascinating. So that directly transfers to the space of money and then to the space of digital money, cryptocurrency. Okay. Does it bother you sort of intellectually when this money that is a social construct is not directly tied to physical goods like gold, for example? Not at all, because after all, gold has some industrial value. Nobody delights. It's a metal. It doesn't oxidate. It has some good things about it. But does this industrial value really represent the value to which it now is traded? No. So gold is another way to express our belief. I give you an ounce of gold, you treat it like, oh, somebody else will want this for doing something else. So it is really this notion of money is a mental construct, and is a shared, is a social construct, I really believe. And so some people feel that it's physical, so therefore gold exists. Then, as you know now, countries, most sophisticated countries right now, they print their own money, and you believe that they are not going to exaggerate it with inflation. Not everybody believes it, but I'm saying there is at least not going to exaggerate it blatantly. And therefore, you receive it because you know that somebody else will accept it, will have faith in the currency, and so on and so forth. But whether it's gold, whether it's livestock, whatever it is, money is really a shared belief. So there is something, you know, and I've been reading more and more about different cryptocurrencies. There is a kind of belief that the scarcity of a particular resource, like Bitcoin, has a limited amount, and it's tied to physical, you know, to proof of work, so it's tied to physical reality in terms of how much you can mine effectively, and so on, that that's an important feature of money. Do you think that's an important feature to be part of whatever the money is? That is certainly a very useful part. So at some point in time, you know, assume that you know money is something that all of a sudden we say daisies are money, are the currency. Then, you know, I offer you 10 daisies in payment of whatever goods and services you want to provide, but at the end of the day, if you know that you can cultivate it and generate them at will, then perhaps, you know, you should not accept my payment. Here is a bouquet of daisies. I don't know. So you need some kind of a scarcity, the inability to create it suddenly out of nothing is an important. And it's not an intrinsic necessity, but it's much easier to accept once you know that there is a fixed number of units of whatever currency there is, and therefore you can mentally understand I'm getting, you know, this much of this piece of a pie, and therefore I consider myself paid. I understand what I'm receiving. You described the goals of a blockchain, you have a nice presentation on this, as scalability, security, and decentralization. And you challenged the blockchain trilemma that claims you can only have two of the three. So let's talk about each. What is scalability in the context of blockchain and cryptocurrency? What does scalability mean? So, remember, we said that the blockchain is a ledger, and each page receives a, gets some transaction, and everybody can write in these pages of a ledger. Nobody can be stopped from writing, and everybody can read them. Okay. Scalability means how fast can you write? Just imagine that you can write an entry in this spatial shared ledger once every hour. Well, you know, what are you going to do if you have one transaction per hour, the world doesn't go around. So you need to have scalability means here that you can somehow write a lot of transactions, and then you can read them, and everybody can validate them. And that is the speed, and the number of transactions per second, and the fact that they are shared. So you want to have this speed, not only in writing, but in sharing and in inspection for validity. This is scalability. The world is big. The world wants to interact, the people want to interact with each other, and you better be prepared to have a ledger in which you can write lots and lots and lots of transactions in this spatial way very, very, very quickly. So maybe from a more mathematical perspective, or can we say something about how much scalability is needed for a world that is big? Well, it really depends how many transactions you want. But remember that I think right now you have to go into at least thousands of transactions per second. Even if you look at credit cards, we are going to go from an average of 1,600 to peaks of 20,000, 40,000, and something like this. But remember, it's not only a question of a transaction per se, but the value is that the transaction is actually being shared and visible to everybody. And the certainty that that is the case. I can print on my own printer way more transactions, but nobody has the time to see or to inspect, that doesn't count, right? So you want scalability at this common knowledge level, and that is the challenge. I also meant from a perspective of a complexity analysis. So when you get more and more people involved, doesn't it just scale in some kind of way that... Do you like to see certain kind of properties in order to say something is scalable? Oh, absolutely. I took a little bit implicitly that the people transacting are actually very different. So if there is two people who can do thousands of transactions per second with each other, this is not so interesting. What we really need is to say there are billions of people at any point in time, thousands and thousands of them want to transact with each other, and you want to support that. So Algorand, it solves... So that's the company, the team of cryptographers and mathematicians, engineers, so on, that challenged the blockchain trilemma. So let's break it down in terms of achieving scalability. How do we achieve scalability in the space of blockchain, in the space of cryptocurrency? Okay, so scalability, security, and decentralization. So that's what you want. What's the best way to approach? Can we break it down? Let's start with scalability and think about how do we achieve it? Well, to achieve it one at a time is perhaps easy, even in security. If nobody transacts, nobody loses money. So that is secure, but it's not scalable. Good point. Let me tell you, I'm a cryptographer, so I try to fight the bad guys. And what you want is that a vessel ledger that we discussed before cannot be tampered with. So you must think of it as a special link that nobody can erase. Then it has to be, everybody should be able to read and not to alter the pages or the content of the pages. That's okay. But you know what? That is actually easy cryptographically. Easy cryptographically means you can use tools invented 50 years ago, which in cryptographic time is prehistory, okay? We are cavemen working around and solve that problem in cryptography land. But there is really a fundamental problem, which is really almost a social, seems a political problem, is to say who the hell chooses or publishes the next page on the ledger. I mean, that is really the challenge. This ledger, you can always add a page because more and more transactions have to be written on there, and somebody has to assemble this transaction, put them on a page, and add to the next page. Who is the somebody who chooses the page and adds it on? Who can be trusted to do it? Exactly. Assume it is me for the time being, not that I want to volunteer for the job, but then I would have more power than any absolute monarch in history because I would have tremendous power to say, these are the transactions that the entire world should see, and whatever I don't write, this transaction will never see the light of day. I mean, no one had any such power in history. So it's very important to do that. And that is the quintessential problem in a blockchain. And people have thought about it to say, it's not me, it's not you. But for instance, in proof of work, what people say is, okay, it's not me, it's not you. You know what it is? We make a very difficult, we invent a cryptographic puzzle, very hard to solve. The first one to solve it has the right to add one page to the ledger on behalf of everybody else. That now seems okay because, you know, sometimes I solve a puzzle before you do, sometimes you solve it before I do, or before somebody else solves it. It's okay. And presumably, the effort you put in is somehow correlated with how much trust you should be given to add to the ledger. Yeah. So somehow you want to make sure that, you know, you need to work because you want to prevent, you want to make sure that, you know, you get one solution every 10 minutes, say, like in particular example of Bitcoin. So that is very rare that two pages are added at the same time. Because if I solve a puzzle at the same time you do, it could happen that if it happens once or twice, we can survive it. But if it happens, you know, every other page, you know, is a double page, then which of the two is the real page, it becomes a problem. So that's why in Bitcoin, it is important to have a substantial amount of work so that no many, how many people try on earth to solve a puzzle, you have one solution out of how many people are trying every 10 minutes. So that you have, you distanciate these pages, and you have the time to propagate through the network a solution and the page attached to it. And therefore, there is one page at a time that is added. And you say, well, why don't we do it? We have a solution. Well, first of all, a page every 10 minutes is not fast enough. It's a question of scalability. And second of all, to ensure that no matter how many people try, you get one page every 10 minutes, one solution to the riddle every 10 minutes. This means that the riddle becomes very, very hard. And to have a chance to solve it within 10 minutes, you must have such an expensive apparatus in terms of specialized computers, not one, not two, but 1,000 and 1,000 of them. And they produce tons of heat, okay? They dissipate heat like a maniac. And then you have to refrigerate them too. And so then now you have air conditioning galore to add to the thing. It becomes so expensive that fewer and fewer and fewer people can actually compete in order to add to the page. And the problem becomes so crucial that in Bitcoin, depending on which day of the week you look at it, you are going to have two or three mining pools are really the ones capable of controlling the chain. So you're saying that's almost like leads to centralization? Right. It started being decentralized, but the expenses became higher and higher and higher. When the cost becomes higher and higher, fewer and fewer people can afford them. And then it becomes de facto centralized, right? Yeah. And a different type of approach is instead, for instance, a delegated proof of stake, which is also very easy to explain. Essentially, it boils down to say, well, look at these 21 people say, okay? Don't they look honest? Yes, they do. In fact, I believe that they're going to remain honest from the foreseeable future. So why don't we do ourselves a favor? Let's entrust them to add the page on behalf of all of us to the ledger. Now we are going to say, is this centralized or decentralized? Well, 21 is better than one, but I have to say it's very little. So if you look at when people rebelled to centralized power, I don't know, the French revolutions, there was a monarch and the nobles. Yes. Were there 21 nobles? No, there were thousands of them, but there were millions and millions of disempowered citizens. So one is centralized, 21 is also centralized. So that's delegated proof of stake. Delegated proof of stake. Kind of like representative democracy, I guess. Yes, which is good. It's working great, right? It's working great. Well, it's better than a single monarch, right? But... There's problems. There are problems. And so we were looking for a different, when thinking about Algorand, for a different approach. And so we have an approach in that it's really, really decentralized because essentially it works as follows. You have a bunch of tokens, right? These are the tokens that have equal power. And you have, say, 10 billions of tokens distributed to the entire world. And the owners, each token has a chance to add the ledger, equal probability to everybody else. In fact, actually, if you want, here is how it works. So think about, by some magic cryptographic process, which is not magic, it's mathematics, but think of it as magic. Assume that you select a thousand tokens, and so sometimes at random, okay? And you have a guarantee that they're random selected. And then the owners of these 1000 tokens somehow agree on the next page. They all sign it. And that's the next page. Okay? So it is clear that nobody has the power, but once in a while, one of your tokens is selected, and you are in charge of this committee to select the next page. But this goes around very quickly. So, and if you look at this, the question really is that it's not really centralized. And because for agreeing on the same page, it is important that the 1000 tokens that you randomly selected are in honest hands, the majority of them. So, which, if the majority of the tokens are in honest hands, that is essentially true. Because if the majority of the tokens are in honest hands, if you select, say 90% of the people are, 90% of the tokens are in honest hands. So can you randomly select a thousand, in this thousand you find the 501 tokens in bad hands? Very, very improbable. So basically, when a large fraction of people are honest, then you can use randomness as a powerful tool to get decentralization. So what does honesty mean? And now we're into the social side of things, which is, how do we know that, like the fraction, a large fraction of people or participating parties are honest? That is an excellent question. So by the way, first of all, we should realize that the same thing is for every other system. When you look at proof of work, you rely that the majority of the mining power is in honest hands. When you look at a delegated proof of stake, you rely that the majority of these 21 people are honest. What is the difference? The difference is that in these other systems, you should say the whole economy is secure. If the majority of this small piece of economy are honest. And that is a big question. But instead, in Algorand, in our approach, we say the whole economy is secure if the majority of the economy is honest. In other words, who can subvert Algorand? It's not a majority of a small group, but it's a majority of the token holders to conspire with each other in order to sink the very economy for which they own the majority of. That I think it is a bit harder to... Like a self-destructive majority, essentially. And you're also making me realize that basically every system that we have in the world today assumes that the majority of participants is honest. Yes. The only difference is the majority of whom. And in some cases, the majority of a club. And in our case, it's the majority of the whole system. The whole system. Okay, so that's... So through that kind of random sampling, you can achieve decentralization. You can achieve... So the scalability, I understand. And then the security that you're referring to, basically the security comes from the fact that the sample selected would likely include honest people. So it's very difficult to... So by the way, the security, as you mentioned, that you're referring to is basically security against dishonesty. Right? Or manipulation or whatever. Yes. Yes. So essentially, what you're going to do is to say, well, I understood what you're saying, but somebody has to randomly select these tokens. And I believe you. So then who does this random selection? That's a good point. And in our ground, we do something a little bit unorthodox. Essentially, is the token choose themselves at random. And you say, if you think about it, that seems to be a terrible idea. Because if you want to say, choose yourself at random, and whoever chooses himself is a thousand people committee, you choose the page for the rest of us. And because if I'm a bad person, I'm going to select myself over and over again, because I want to be part of the committee every single time. But not so fast. So what do we do in Algorand? What does it mean that I select myself? That each one of us, in the privacy of our own computer, actually a laptop, what you do is that you execute your own individual lottery. And think about it, that you pull a lever of a slot machine. You can only pull the lever once, not until you win. Not enough comes until you win. And when you pull the lever, case one, either you win, in such a case, you have a winning ticket, or you lose, you don't get any winning ticket. So if you don't have a winning ticket, you can say anything you want about the next page in the ledger, nobody pays attention. But if you have a winning ticket, people say, oh, wow, this is one of the 1,000 winning tickets, we better pay attention to what he or she says. And that's how it works. And the lottery is a cryptographic lottery, which means that even if I am an entire nation, extremely powerful, with incredible computing powers, I don't have the ability to improve even minimally my probability of one of my token winning the lottery. And that's how it happens. So everybody pulls the lever, the 1,000 random winners say, oh, here is my winning ticket, and here is my opinion up or down about the block. These are the ones that count. And if you think about it, while this is distributed, because there is, in the case of Algon, there is 10 billion tokens, and you select 1,000 of them, more distributed than this, you cannot get. And then why is this scalable? Because what do you have to do? Okay, you have to do the lottery. How long the lottery takes? It takes actually one microsecond. Whether you have one token or two tokens or a billion tokens is always one microsecond of computation, which is very fast. We don't hit the planet with a microsecond of computation. And finally, why is this secure? Because even if I were a very evil and very, very powerful individual, I'm so powerful that I can corrupt anybody I want instantaneously in the world. Who would I want to corrupt? The people in the committee, so that I can choose the page of the ledger. But I do have a problem. I do not know whom I should corrupt. Should I corrupt this lady in Shanghai, this other guy in Paris? Because I don't know. The winners are random, so I don't know whom I should corrupt. But once the winner come forward and say, here is my winning ticket, and you propagate your winning ticket across the network, together with your opinion about the block, now I know who they are. For sure, I can corrupt 1,000 of them given to my incredible powers. But so what? Whatever they said, they already said, and their winning tickets and their opinions are virally propagated across the network. And I do not have the power, no more than the US government or any government has the power, to put back in the bottle a message virally propagated by Wikileaks. So everything you just described is fascinating, a set of ideas. And online I've been reading quite a bit, and people are really excited about those set of ideas. Nevertheless, it is not the dominating technology today. So Bitcoin in terms of cryptocurrency is the most popular cryptocurrency, and then Ethereum, and so on. So it's useful to kind of comment, we're already talking about proof of work a little bit, but what in your sense does Bitcoin get right, and where is it lacking? Okay, so the first thing that Bitcoin got right is to understand that there was the need of a cryptocurrency. And that, in my opinion, they deserve all the success, because they say the time is ripe for this idea. Because very often it's not enough to be right, you have to be right at the right time, and somebody got it right there. So hat off to Bitcoin for that. And so what they got right is that it is hard to subvert and change the ledger, to cancel a transaction. It's not impossible, but it is very hard. What they did not get right is somehow that is a great store of value, currency-wise, but money is not only a question that you store it and you put under the mattress. Money wants to be transacted. And the transaction in Bitcoins are very little. So if you want to store value, everybody needs a store of value, might as well use a Bitcoin. I mean, it's the plant, but if you don't look at that for a moment, at least it's a great store of value, and everybody needs a store of value. But most of the time we want to transact, we want to interact, we don't put the money under the mattress, right? So we want to... And that, they didn't get it right. That is too slow to transact. Too few transactions. There's a scalability. The scalability issue. Is it possible to build stuff on top of Bitcoin that sort of fixes the scalability? I mean, this is the thing, you look at, there's a bunch of technologies that kind of hit the right need at the right time, and they have flaws, but we kind of build infrastructures on top of them over time to fix it, as opposed to getting it right from the beginning. Or is it difficult to do? Well, that is difficult to do. So you are talking to somebody that when I decided to throw my hat in the arena, and I decided, first of all, as I said before, I much admire my predecessors. I mean, they got it right a lot of things, and I really admire for that. But I had a choice to make. Either I patch something that has holes all over the place, or I start from scratch. I decided to start from scratch, because sometimes it's the better way. So what about Ethereum, which looks at proof of stake and a lot of different innovative ideas that kind of improve or seek to improve on some of the flaws of Bitcoin? Ethereum had another great idea. So they figured out that money and payments are important as they are. They are only the first level, the first stepping stone. The next level are smart contracts, and they were at the vision to say, the people will need smart contracts, which allow me and you to somehow to transact securely without being shopped around by a trusted third party, by a mediator. By the way, because mediators are hard to find, and in fact, maybe even impossible to find if you live in Thailand and I live in New Zealand, maybe we don't have a common person that we know and trust. And even if we find them, guess what? They want to be paid. So much so that 6% of the world GDP goes into financial friction, which is essentially third party. So the headed right of the world needed that. But again, the scalability is not there. And the system of smart contracts in Ethereum is slow and expensive. And I believe that is not enough to satisfy the appetite and the need that we have for smart contracts. Well, what do you make of, just as a small sort of aside in human history, perhaps it's a big one, is the NFT, the non fungible tokens. Do you find those interesting technically, or is it more interesting on the social side of things? Well, both. I think, you know, I think it's, NFTs are actually great, right? So you have this, you're an artist to create a song, or it could be a piece of art. He has many unique representation, right, of a unique piece, whether it's an artifact or something dreamed up by you, and has unique representation, but now you can trade. And allow, and the important part is that now you have this, not only the NFTs themselves, but the ability to trade them quickly, fast, securely, knowing that who owns which rights. And that gives a totally new opportunity for content creators to be remunerated for what they do. So, but ultimately you still have to have that scalability, security, and decentralization to make it, you know, to make it work for bigger and bigger applications. Correct. Yeah. Yeah. I still wonder what kind of applications are yet to be, like, enabled by it, because so much, the interesting thing about NFTs, you know, if you look outside of art, is just like money, you can start playing with different social constructs, is you can start playing with the ideas, you can start playing with, even like investing, somebody was talking about almost creating an economy out of, like, creative people or influencers. Like if you start a YouTube channel or something like that, you can invest in that person and you can start trading their creations and then almost, like, create a market out of people's ideas, out of people's creations, out of the people themselves that generate those creations. And there's a lot of interesting possibilities of what you can do with that. I mean, it seems ridiculous, but you're basically creating a hierarchy of value, maybe artificial, in the digital world and they're trading that. But in so doing, are inspiring people to create. So maybe as a sort of our economy gets better and better and better, where actual work in the physical space becomes less and less in terms of its importance, maybe we'll completely be operating in a digital space where these kinds of economies have more and more power. And then you have to have this kind of blockchains to the scalability, security and decentralization. And decentralization is, of course, the tricky one, because people in power start to get nervous. Absolutely. Once in power, you're always nervous that you'll be supplanted by somebody else. But this is your job. Congratulations, you got the job, the top job, and now everybody wants it. Well, what is your sense about our time and the future hope about the decentralization of power? Do you think that's something that we can actually achieve, given that power corrupts and absolute power corrupts absolutely and it's so wonderful to be absolutely powerful? Well, good question. So first of all, I believe, by the way, that is a complex question, Lex, like all the rest of your questions. I'm so very sorry. It's OK, I am enjoying it. So there are two things. First of all, power has been centralized for a variety of reasons. When you want to get it, it's easier for somebody, even a single person, to grab power. But there is also some kind of a technology, lack thereof, that justified having in power, because in a way, in a society in which even communication, never mind blockchain, which is common knowledge, but even simple unilateral communication is hard, it is much easier to say, you do as I say, because the alternative is... So there is a little bit of a technology barrier. But I think that now to get to this common knowledge, it is a totally different story. Now we have finally the technology for doing this. So that is one part. But I really believe by having a distributed system, not only you don't have a... You have actually much more stable and durable system. Because not only for corruption, but even for things that go astray, and you give it a long enough time by strange version of Murphy's law, whatever goes wrong, goes wrong. And so, and if the power is diffused, you actually are much more stable. If you look at any living, complex living being, it's distributed. I mean, I don't have somebody is, okay, tell Sylvia now it's time to eat. So you have millions of cells in your body, you have billions of bacteria. Exactly. Help me in the guts, I think, we are in a soup of it somehow. It keeps us alive. So strange enough, however, when we design systems, we design them centralized. We ourselves are distributed beings. And when we plan to say, okay, I want to get an architecture, how about I make a pyramid, I put this on the top and the power flows down. And so again, it's a little bit perhaps of a technology problem. But now the technology is there. So that is a big challenge to rethink how we want to organize power in very large system and distributed system, in my opinion, are much more resilient. Let's put it this way. There was a mine of my Italian compatriots, right? Machiavelli, who looked at the time, there was a bunch of a small state, a democratic Republic of Florence and Venice and the other thing. And there was the Ottoman Empire, but at the time was an empire and a Sultan was very centralized. And he made a political observation that goes roughly to say, whenever you have such a centralized thing, it's very hard to overtake that form of government is centralized. But if you get it, it's so easy to keep the population. While instead, these other things are much more resilient. When the power is distributed, it's going to be lasting for much longer time. And ultimately, maybe the human spirit wants that kind of resilience, wants that kind of distribution. It's just that we didn't have technology throughout history. Machiavelli didn't have the computer, the internet and- That is certainly part of a reason, yes. You've written an interesting blog post. If we take a step out of the realm of bits and into this, the realm of governance, you wrote a blog post about making Algorand governance decentralized. Can you explain what that means, the philosophy behind that? How you decentralize basically all aspects of this kind of system? Well, the philosophy and the how, let's start with the philosophy. So I really believe that nothing fixed lasts very long. And so I really believe that life is about intelligent adaptation. Things change and we have to be nimble and adjust to change. And when I see a lot of a crypto project, actually very proud to say it's fixed in stone. Code is law, law is code. I verify the code, it will never change. You go, wow. When I'm saying this is a recipe to me of disaster, not immediately, but soon. Just imagine you take a notional liner and you want to go, I don't know, from Lisbon to New York and you set the course, iceberg, no iceberg, tempest, no tempest. It doesn't matter. That is not the way. You need a till, you need to correct, you need to adjust. And so, by the way, we design Algorand with the idea that the code was evolving as the needs. And of course, the way there is a system in which, and every time there is an adjustment, you must have essentially a vote that right now is orchestrated at 90% of the stake. They say, okay, we are ready. We agree on the next version and we pick up this version. So we are able to evolve without losing too many components left and right. But I think without evolving, any system essentially become masophitic and is going to shrivel and die sooner or later. And so that is needed. And what you want to do on the blockchain, you have a perfect platform in which you can log your wishes, your votes, your things, so that you have a guarantee that whatever vote you express is actually seen by everybody else. So everybody sees really the outcome, call it a referendum, of a change. And that is, in my opinion, a system that wants to live long as to adapt. There's an interesting question about leaders. I've talked to Vitalik Buterin. I'll probably talk to him again soon. He's one of the leaders, maybe one of the faces of the Ethereum project. And it's interesting, you have Satoshi Nakamoto, who's the face of Bitcoin, I guess, but he's faceless. He, she, they. It does seem like in our, whatever it is, maybe it's 20th century, maybe it's Machiavellian thinking, but we seek leaders. Leaders have value. Linus Torvald, the leader of Linux, the open source development a lot. I mean, there's no, it's not that the leadership is sort of dogmatic, but it's inspiring. And it's also powerful in that through leaders, we propagate the vision. Like the vision of the project is more stable. Maybe not the details, but the vision. And so do you think there's value to, because there's a tension between decentralization and leadership, like visionaries. What do you make of that tension? Okay. So I really believe that, that's a good question. I think of it, I really believe in the power of emotions. I think that emotion are of a creative impulse of everybody else. And therefore it's very easy for a leader to be a physical person, a real being, and that interprets our emotions. And by the way, this emotion has to resonate. And what is good is that the more intimate our emotions are, the more universal they are, paradoxically. The more personal, the more everybody else somehow magically agrees and feels a bit of the same. And so, and it's very important to have a leader in the initial phase that generates out of nothing something. That is important leadership. But then the true test of leadership is to disappear after you led the community. So in my opinion, the quintessential leader, according to my vision, is George Washington. He served for one term, he served for another term, and then all of a sudden he retired and became a private citizen. And 200 and change years later, we still are, with some defects, but we have done a lot of things right. And we have been able to evolve. That to me is success in leadership. When instead you contrast our experiment with a lot of experiment. I've done so much so well that I want another four years. And why should I be only a four and I have another eight? Why should be another eight? Give me 16, I will fix all your problem. And now then is the type, in my opinion, of failed leadership. Leadership ought to be really lead, ignite, and disappear. And if you don't disappear, the system is going to die with you. And it's not a good idea for everybody else. Is there, so we've been talking a little bit about cryptocurrency, but is there spaces where this kind of blockchain ideas that you're describing, which I find fascinating, do you think they can revolutionize some other aspects of our world? That's not just money? A lot of things are going to be revolutionized. It's independent of finance. By the way, I really believe that finance is an incredible form of freedom. I mean, if I'm free to do anything I want, but I don't have the means to do anything, that's a bad idea. So I really think financial freedom is very, very important. But just again, say that against the censorship, you write something on the chain and now nobody can take it out. That is a very important way to express our view. And then the transparency that you give, because everybody can see what's happening on the blockchain. So transparency is not money. But I believe that transparency actually is a very important ingredient also of finance. Let's put it this way, as much as I'm enthusiastic about blockchain and decentralized finance, and we have actually, our expression, we're creating this future five, as much as we want to do, we must agree that the first guarantee of financial growth and prosperity are really the legal system, the courts. Because we may not think about them and say, oh, the courts are a bunch of boring lawyers. But without them, I'm saying there is no certainty. There is no notion of equality. There is no notion that you can resolve your disputes. Think, that's what drives commerce and things. And so what I really believe that the blockchain actually makes a lot of this trust essentially automatic, but make it impossible to cheat in very way. You don't even need to go to court if nobody can change the ledger. So it essentially is a way of, you cannot solve an illegal system that reduces to a blockchain. But what I'm saying, a big chunk of it can actually be guaranteed. And there is no reason why technology should be antagonistic to legal scholarship. It could be actually coexisting. And one should start to doing the interesting things that the technology alone cannot do. And then you go from there. But I think that is essentially is, blockchain can affect all kinds of our behavior. Yes. In some sense, the transparency, the required transparency ensures honesty, prevents corruption. So there's a lot of systems that could use that. And the legal system is one of them. There's a little bit of a tension that I wonder if you can speak to where this kind of transparency, there's a tension with privacy. Is it possible to achieve privacy if wanted on a blockchain? Do you have ideas about different technologies that can do that? People have been playing with different ideas. So absolutely. The answer is yes. And by the way, I'm a cryptographer. So I really believe in privacy and I believe in, and I have devoted a big chunk of my life to guarantee privacy, even when it seems almost impossible to have it. And it is possible to have it in also in the blockchain too. And however, I believe in timing as well. And I believe that the people have the right to understand their system they live in. And right now, people can understand the blockchain to be something that cannot be altered and is transparent. And that is good enough. And right now, any way to add, and there is a pseudo privacy for the fact that who knows if this key belongs, public key belongs to me or to you, right? And I can, when I want to change my money from one public key, I split it to other public keys, going to figure out which one is Silvio, all of them are Silvio, only one of Silvio, who knows. So you get some vanilla privacy, not the one I kept. And I think it's good enough because, and it's important for now that we absorb this stage. Because the next stage, we must understand the privacy tool rather than taking on faith. When the public starts saying, I believe in the scientists and whatever they say, I swear by them. And therefore, if they tell me it's private, it's private and nobody understands it very well. We need a much more educated about the tools we are using. And so I look forward to deploying more and more privacy on the blockchain. But we are not, I will not rush to it until the people understand and are behind whatever we have right now. Lexer So you build privacy on top of the power of the blockchain, you have to first understand the power of the blockchain. Algorand Yes. So Algorand is like one of the most exciting, technically, at least from my perspective, technologies, ideas in this whole space. What's the future of Algorand look like? Is it possible for it to dominate the world? Algorand Let's put it this way, I certainly working very hard with a great team to give the best blockchain that one can demand and enjoy. And that said, I really believe that there is going to be, it's not a winner takes them all. So it's going to be a few blockchains, and each one is going to have its own brand, and it's going to be great at something. And sometimes it's scalability, sometimes it's your views, sometimes it's a thing. And it's important to have a dialogue between these things. And I'm sure, and I'm working very hard to make sure that Algorand is one of them. But I don't believe that it is even desirable to have a winner takes all, because we need to express different things. But the important thing is going to have enough interoperability with various systems, so that you can transfer your assets where you have the best tool to service them, whatever your needs are at the time. Lexer So there's an idea, I don't know, they call themselves Bitcoin maximalists, which is essentially the bet that the philosophy that Bitcoin will eat the world. So you're talking about it's good to have variety. Their claim is it's good to have the best technology dominate the medium of exchange, the medium of store value, the money, the digital currency space. What's your sense of the positives and the negatives of that? Hrvoje Merts So I feel people are smart, and it's going to be very hard for anybody in Bitcoin to win. And because people want more and more things. There is an Italian saying that goes, translates well, I think. It goes, the appetite grows while eating. Okay? I think you understand what I mean. So I say, I'm not hungry. Okay, food, let me try this. So we will have a lot more and more and more. And when you find something like Bitcoin, which I already had very good things to say, but it does something very well, but it's static. I mean, store value, yes, I think is a great way. For the rest, it would be a sad world if the world in which we are so anchoring down, so defensive, that we want to store value and hide it under the mattress. I long for a world in which it is open, people want to transact and interact with each other. And therefore, when you want to store value, perhaps one chain, where you want to have to transact maybe is another. I'm not saying that one chain cannot be a store of value or another thing. But I really believe in the ingenuity of people and in the innovation that is intrinsic to the human nature. We want always different things. So how can it be something invented, whatever it is, decades ago, is going to fulfill the needs of our future generations. I'm not going to fulfill my needs, let alone my kids or their kids. We are going to have a different world and things will evolve. So you believe that life, intelligent life, is ultimately about adaptability and evolving. So static loses in the end. Yes. Let me ask the, well, first, the ridiculous question. Do you have any clue who Satoshi Nakamoto is? Is that even an interesting question? Is it you? Well, your questions are very interesting. So I would say, first of all, it's not me. And I can prove it because if I were Satoshi Nakamoto, I would have not found an algorithm. It takes a totally different principle to approach the system. But the other thing, who is Satoshi Nakamoto? You know what the right answer is? It's not him or her or them. Satoshi Nakamoto is Bitcoin. Because to me, he's such a coherent proof of work. But at the end, the creator and the creation identify themselves. So you say, okay, I understand Michelangelo. Okay, he did the Sistine Chapel. Fine. He did the St. Peter's dome. Fine. He did the Moses of the Pietra statue. Fine. But besides this, who was Michelangelo? That's a very long question. It's his own work. That is Michelangelo. So I think that when you look at the Bitcoin, is a piece of work that as it affects, yes, like anything human, but it was captivated the imaginations of millions of people as a subverted Vestalto school. And I'm saying, you know, whoever this person of people are, he's living in this piece of work. I mean, it is Bitcoin. That's my- The idea of the work is bigger. We forget that sometimes. It's something about our biology once likes to see a face and attach a face to the idea, when really the idea is the thing we love. The idea is the thing that impact ideas. The thing that ultimately we, you know, Steve Jobs or somebody like that, we associate with the Mac, with the iPhone, with just everything he did at Apple. Apple, actually, the company, is Steve Jobs. Steve Jobs, the man is a pales in comparison to the creation. Correct. And the sense of aesthetics that has brought to the daily lives. And very often, aesthetic wins in the long end. These are very elegant design product. And when you say, oh, elegance, a very few people care about it. Apparently, millions and millions and millions and millions of people do because we are attracted by beauty. And these are beautifully designed products. And, you know, and they've, in addition to the technological aspect of everything. And I think, yes, that is- Yeah, as Dostoevsky said, beauty will save the world. So I'm with you on that one. Great. It currently seems like cryptocurrency, all these different technologies, are gathering a lot of excitement, not just in our discourse, but in their scale of financial impact. A lot of companies are starting to invest in Bitcoin. Do you think that the main method of store of value and exchange of value, basically money, will soon, or at some point in the century, will become cryptocurrency? Yes. So mind you, as I said, the notion of cryptocurrency, like any other fundamental human notion, has to evolve. But yes. So I think that it has a lot of momentum behind it. It's not only static, as this programmable money, as I think- Smart contracts, all that kind of stuff. It allows a peer-to-peer interaction among people who don't even know each other, right? And they don't even, therefore, cannot even trust each other just because they never saw each other. So I think it's so powerful that it's going to do. That said, again, a particular cryptocurrency should develop, and cryptocurrency will all develop. But the answer is yes, we are going towards a much more, unless we have a society, a sudden crisis for different reasons, which nobody hopes. There's always an asteroid. There's always- Right, right. Something. Nuclear war and all the existential crisis that we kind of think about, including artificial intelligence. Okay. It's funny you mentioned that Michelangelo and Steve Jobs, you know, set of ideas represents the person's work. So we talked about Algorand, which is a super interesting set of technologies, but he did also win the Turing Award. You have a bunch of ideas that are seminal ideas. So can we talk about cryptography for a little bit? What is the most beautiful idea in cryptography or computer science or mathematics in general? Asking somebody who has explored the depths of all. Well, there are a few contenders. Either your work or other work. And let's leave my work aside. But one powerful idea, and is both an old idea in some sense and a very, very modern one, and in my opinion, is this idea of a one-way function. So a function that easy to evaluate. So given x, you can compute f of x easily. But given f of x is very hard to go back to x. Think like breaking a glass, easy. Reconstruct the glass harder. Frying an egg, easy. Fried egg to go back to the original egg, harder. If you want to be extreme, killing a living being, unfortunately easy. The other way around, very hard. And so the fact that the notion of a function, which you have a recipe that is in front of your eyes to transform an x into f of x, and then from f of x, even though you see the recipe to transform it, you cannot go back to x, that in my opinion is one of the most elegant and momentous notions that there are. And it is a computational notion because of the difficulties in a computational sense, and it's a mathematical notion because we are talking about function, and it's so fruitful because that is actually the foundation of all cryptography. And let me tell you, it's an old notion because very often in any mythology that we think of, the most powerful gods or goddesses are the ones of x and the opposite of x, the gods of love and death. And when you take opposites, they don't just erase one another, you create something way more powerful. And this one-way function is extremely powerful because essentially becomes something that is easy for the good guys and hard for the bad guys. So for instance, in pseudo-random number generation, the easy part of the function corresponds you want to generate bits very quickly, and hard is predicting what the next bit is. It doesn't look the same. One is x f of x, going from x of x to x hard, what does it do? Predicting bits. By a magic of reductions and mathematical apparatus, this simple function morphs itself into pseudo-random number generation. This simple function morphs itself in digital signature scheme, in which digitally signing should be easy and forging should be hard. Again, a digital signature is not going from x to f of x, but the magic and the richness of this notion is that it is so powerful that it morphs in all kinds of incredible constructs. And in both, these two opposites coexist, the easy and the hard, and in my opinion, it is a very, very elegant notion. Lexer That simple notion ties together cryptography, like you said, pseudo-random number generation. You have work on pseudo-random functions. What are those? What's the difference in those and the generators, pseudo-random number generators? Jacob Okay, let's- Lexer How do they work? Jacob Let's go back to pseudo-random number generation. First of all, people think that the pseudo-random number generation generates random number. Not true, because I don't believe that from nothing you can get something. So nothing from nothing. Randomness, you cannot create out of nothing, but what you can do is that it can be expanded. In other words, if you give me somehow 300 random bits, truly random bits, then I can give you 300,000, 300 million, 300 trillions, 300 quadrillions, as many as you want, random bits, so that even though I tell you the recipe by which I produce these bits, but I don't tell you the initial 300 random numbers, I keep them secret, and you see all the bits I produce so far, if you were to bet, given all the bits produced so far, what is the next bit in my sequence? Better than 50-50. Of course, 50-50, anybody can guess, right? But to be in fair in something, you have to be a bit better. Then the effort to do this extra bit is so enormous that is de facto random. So that is a pseudo-random generator, are these expanders of secret randomness, which goes extremely fast. Okay, that said, what is a... Expanders of secret randomness, beautifully put. Okay, so every time somebody, if you're a programmer, is using a function that's not called pseudo-random, it's called random usually, in all these programming languages, and is generating different... That's essentially expanding the secret randomness. But they should. In the past, actually, most of the library, they used something pre-modern cryptography, unfortunately. They would be better served to take a 300 real seed random number and then expand them properly, as we know now. But that has been a very old idea. In fact, one of the best philosophers have debated whether the world was deterministic or probabilistic. Very big questions, right? Lexis D'Agostino Does God play dice? Exactly. Einstein says it does, he doesn't. But in fact, now we have a language that even at Albert's time was not around, but it was this complexity theory, modern complexity-based cryptography. And now we know that if the universe has 300 random bits, whether it is random or probabilistic or deterministic, it doesn't matter. Because you can expand this initial seed of randomness forever, in which all the experiments you could do, all the inferences you could do, all the things you could do, you will not be able to distinguish them from truly random. So if you are not able to distinguish truly random from this super-duper pseudo-randomness, are they really different things? That's what I want to say. So I'm ready to become a real philosopher. So for things to be different, but I don't have in my lifetime, in the lifetime of the universe, any method to set them aside, well, I should be intellectually honest, say, well, pseudo-random in this special function is as good as random. Lexis D'Agostino Do you think true randomness is possible? And what does that mean? So practically speaking, exactly as you said, if you're being honest, the pseudo-randomness approaches true randomness pretty quickly. But is it, maybe this is a philosophical question, is there such a thing as true randomness? Vladimir Mishukov Well, the answer is actually maybe, but if it exists, most probably it's expensive to get. And in any case, if I give you one of mine, you will never tell them apart by any other shape, no matter how much you work on it. So in some sense, if it exists or not, it really is a quote philosophical sense in the colloquial way to say that we cannot somehow pin it down. Lexis D'Agostino Again, just to stay on philosophical for a bit, for a brief moment, do you ever think about free will and whether that exists? Because ultimately, free will is this experience that we have, like we're making choices, even though it appears that the world is deterministic at the core. I mean, that's against the debate, but if it is in fact deterministic at the lowest possible level, at the physics level, if it is deterministic, how do you make sense of the difference between the experience of us feeling like we're making a choice and the whole thing being deterministic? Vladimir Mishukov So first of all, let me give you a gut reaction to the question. And the gut reaction is that it is important that we believe that there exists free will. And second of all, almost by weird logic, if we believe it exists, then it does exist. So it's very important for our social apparatus, for our sense of the idea of ourselves that it exists. And the moment in which we so want to, we almost conjure it up in existence. But again, I really feel that if you look at some point, the space of free will seems to shrink. We realize how much of our, say, genetic apparatus dictates who we are, why we prefer certain things than others, and why we react to noises of music, we prefer poetry, and everything else. We may explain even all this. But at the end of the day, whether it exists in a philosophical sense or not, it's like randomness. If pseudorandom is as good as random vis-a-vis lifetime of the universe of our experience, then it doesn't really matter. So we're talking about randomness. I wonder if I can weave in quantum mechanics for a brief moment. There's a lot of advancements on the quantum computing side. So leveraging quantum mechanics to perform a new kind of computation, and there's concern of that being a threat to a lot of the basic assumptions that underlie cryptography. What do you think? Do you think quantum computing will challenge a lot of cryptography? Will cryptography be able to defend all those kinds of things? Okay, great. So first of all, for the record, and because I think it matters, but it's important for the record, there are people who continue to contend that quantum mechanics exists, but it has nothing to do with computing. It's not going to accelerate it, at least in a very basic kind of computation. That is a belief that you cannot take it out. I'm a little bit more agnostic about it, but I really believe, going back to whatever I said about the one-way function. So one-way function, what is it? That is a cryptography. So does quantum computing challenge- The one-way function. Essentially. You can boil it down to, does quantum computing find a one-way function? What is a one-way function? Easy in one direction, harder than the other. Okay, but if quantum computing exists, when you define what it is easy, it's not easy by a classical computer and hard by a classical computer, but easy for a quantum computer, that's a bad idea. But once easy means it should be easy for a quantum and hard for also quantum. Then you can see that you are, yes, it's a challenge, but you have hope because you can absorb, if quantum computing really realizes and becomes available according to the promises, then you can use them also for the easy part. And once you use it for the easy part, the choices that you have a one-way function, they multiply. So, okay, so the particular candidates of one-way function may not be one-way anymore, but quantum one-way function may continue to exist. And so I really believe that for life to be meaningful, this one-way function had to exist. Because just imagine that anything becomes easy to do. I mean, what kind of life is it? I mean, so you need, and if something is hard, but it's so hard to generate, you'll never find something which is hard for you. You want that there is abundance, that it is easy to produce hard problem. That's my opinion is why life is interesting, because hard problem pop up at a really relative speed. So in some sense, I almost think that I do hope they exist. If they don't exist, somehow life is way less interesting than it actually is. Yeah, it does. That's funny. It does seem like the one-way function is fundamental to all of life, which is the emergence of the complexity that we see around us seem to require the one-way function. I don't know if you play with cellular automata, that's just another formulation of- No, I know, but it's- Very simple. It's almost a very simple illustration of starting out with simple rules and one way, being able to generate incredible amounts of complexity. But then you ask the question, can I reverse that? And it's just surprising how difficult it is to reverse that. It's surprising, even in constrained situations, it's very difficult to prove anything. The sad thing about it, well, I don't know if it's sad, but it seems like we don't even have the mathematical tools to reverse engineer stuff. I don't know if they exist or not, but in the space of cellular automata, where you start with something simple and you create something incredibly complex, can you take a small picture of that complex and reverse engineer? That's kind of what we're doing as scientists. You're seeing the result of the complexity and you're trying to come up with some universal law that generate all of this. What is the theory of everything? What are the basic physics laws that generate this whole thing? And there's a hope that you should be able to do that, but it's difficult. Yeah, but there is also some poetry of the fact that it's difficult because it gives us some mystery to life, without which, I mean, it's not so fun. Life would be less fun. Can we talk about interactive proofs a little bit and zero-knowledge proofs? What are those? Okay. How do they work? Okay. So interactive proof, actually, is a modern realization and conceptualization of something that we knew was true, that is easy to go to lecture. In fact, that's my motivation. We invented schools to go to lecture. We don't say, oh, I'm the minister of education. I publish this book. You read it. This is book for this year, this book for this year. We spend a lot of our treasury in educating our kids, and in person, educating, go to class, interact with teacher on the blackboard and chalk on my time. Now we can have a whiteboard and presumably, you're going to have actually these magic pens and a display instead. But the idea is that interactively, you can convey truth much more efficiently. And we knew this psychologically. It's better to hear an explanation than just to belabor some paper, right? Same thing. So interactive proofs is a way to do the following. Rather than doing in some complicated, very long papers and possibly infinitely long proofs, exponentially long proofs, you say the following. If this theorem is true, there is a game that is associated to the theorem. And if the theorem is true, this game, I have a winning strategy that I can win half of the time, no matter what you do. Okay, so then you say, well, is the theorem true? You believe me. Why should I believe you? So, okay, let's play. And if I prove that I have a strategy, and I win the first time, and I win the second time, then I lose a third time. But I win more than half of the time, or I win, say, all the time if the theorem is true, and at least at most half of the time if the theorem is false, you statistically get convinced. You can verify this quickly. And therefore, when the game typically is extremely fast, so you generate a miniature game in which if the theorem is true, I win all the time. If the theorem is false, I can win at most half of the time. And if I win, win, win, win, win, win, win, win, you can deduce either the theorem is true, which most probably is the case, so to speak, or I've been very, very unlucky, because it's like if I had 100 coin tosses, and I got 100 heads, very improbable. So that is a way. And so this transformation from the formal statement of a proof into a game that can be quickly played, and you can draw statistics on many times you win, is one of a big conquest of modern complexity theory, and in fact, actually has highlighted the notion of a proof as it really give us a new insight of what to be true means, and what truth is, and what proofs are. So these are legitimately proofs. So what kind of mysteries can it allow us to unlock and prove? You said truth. So what does it allow us, what kind of truth does it allow us to arrive at? So it enlarges the realm of what is provable, because in some sense of the classical way of proving things was extremely inefficient from the verifier point of view. And so therefore, there is so much proof that you can take, but in this way, you can actually very quickly, minutes, minutes, verify something that is the correctness of an assertion, that otherwise would have taken a lifetime to belabor and check all the passages of a very, very, very long proof. And you better check all of them, because if you don't check one line, an error can be in that line. And so you have to go linearly through all the stuff rather than bypass this. So you enlarge a tremendous amount what the proof is. And in addition, once you have the idea that essentially a proof system is something that allows me to convince you of a true statement, but does not allow me to convince you of a false statement, and that at the end sense of proof, proof can be beautiful, should be, should be elegant, but at the end sense is true or false, if you want to be able to differentiate. It is possible to prove the truth, and it should be impossible or statistically extremely hard to prove something false. And if you do this, you can prove way, way more once you understand this. And on top of it, we got some insight, like in Visit Zero Knowledge Proofs, that is in something which you took for granted were the same, knowledge and verification are actually separate concepts. So you can verify that an assertion is correct without having any idea why this is so. And so people fail to say, if you want to verify something, you have to have the proof. Once you have the proof, you know why it's true, you have the proof itself. And so somehow you can totally differentiate knowledge and verification, validity. So totally you can decide if something is true and still have no idea. Is there a good example in your mind? Oh, actually, at the beginning, we labored to find the first knowledge, zero knowledge proof. Then we found a second, then we found a third. And then a few years later, actually we proved a theorem which essentially says every theorem, no matter what about, can be explained in a zero knowledge way. So it's not a class of theorem, but old theorems. And it's a very powerful thing. So we were really, for thousands of years, both this identity between knowledge and verification had to be hand in hand together, and for no reason at all. I mean, we had to develop a way of technology. As you know, I'm very big in technology because it makes us more human and make us understand more things than before. And I think that's a good thing. So this interactive proof process, there's power in games. Yes. And you've recently gotten into, recently, I'm not sure you can correct me, mechanism design. Yeah. So, I mean, first of all, maybe you can explain what mechanism design is and the fascinating space of playing with games and designing games. Mechanism design is that you want a certain behavior to arise, right? If you want to organize a societal structure or something, you want to have some orderly behavior to arise, right? Because it is important for your goals. But you know that people, they don't care what my goals are. They care about maximizing their utility. So to put it crassly, making money. The more money, the better, so to speak. I'm exaggerating. Self-interest in whatever way that makes sense. So what you want to do is, ideally, what you want to do is to design a game so that while people played so to maximize their self-interest, they achieve the social goal and behavior that I want. That is really the best type of thing. And it is a very hard science and art to design these games. And it challenges us to actually come up with a solution concept for a way to analyze the games that need to be broader. And I think of game theory as a developer, a bunch of very compelling things. A way to analyze the game, that if the game has a best property, you can have a pretty good guarantee that it's going to be played in a given way. But as it turns out, and not surprisingly, these tools have a range of action like anything else. All these so-called technical solution concepts, the way to analyze the game, like dominant strategy equilibrium, if something comes to mind, would be very meaningful. But as a limited power, in some sense, the games that can be, admit such a way to be analyzed. There's a very specific kind of games, and the rules are set, the constraints are set, the utilities are all set. Yes. So if you want to reason, there is a way, say, that you can analyze a restricted class of games this way. But most games don't fall into this restricted class. Then what do I do? You need to enlarge a way what a rational player can do. So for instance, in my opinion, at least in some of my... I played with this for a few years, and I was doing some exoteric things, I'm sure, in the space that were not exactly mainstream. Then I changed my interest and blockchain. But what I'm saying, for a while I was doing... So for instance, to me, is a way in which I design the game, and you don't have the best move for you. The best move is the move that is best for you, no matter what the other players are doing. Sometimes a game doesn't have that. It's too much to ask. But I can design the game such that, given the option in front of you, say, oh, these are really stupid for me, take them aside. But these, these are not stupid. So if you design the game so that in any combination of non-stupid things that the player can do, I achieve what I want, I'm done. I don't care to find the unique equilibrium. I don't give a damn. I want to say, well, as long as you don't do stupid things and nobody else does stupid things, good social things outcome arise, I should be equally happy. And so I really believe that this type of analysis is possible, and has a bigger radius, so it reaches more games, more classes of games. And after that, we have to enlarge it again. And it's going to be, we're going to have fun, because human behavior can be conceptualized in many ways. And it's a long game. It's a long game. Do you have favorite games that you're looking at now? I mean, I suppose your work with the blockchain and Algorand is the kind of game that you're, you basically mechanism design, design the game such that it's scalable, secure, and decentralized, right? Yes, yes. And very often you have to say, and you must also design so that the incentives are, and then the truth, whatever little I learned from my venture in mechanism design, is that incentives are very hard to design, because people are very complex creatures. And so somehow the way we design Algorand is a totally different way, essentially with no incentives, essentially. But technically speaking, there is a notion that is actually believable, right? So let's say people want to maximize their utility. Yes, up to a point. Let me tell you. Assume that if you are honest, you make a hundred bucks. But if you are dishonest, no matter how dishonest you are, you can only make a hundred bucks and one cent. What are you going to be? I'm saying, you know what? Technically speaking, even that one cent, but nobody bothers to say, how much am I going to make by being honest? A hundred. If I'm devious and if I'm a criminal, 100 bucks and one cent. You know, I might as well be honest, okay? So that essentially is called epsilon utility equilibrium, but I think it's good. And that's what we design, essentially means that having no incentives is actually a good thing, because it prevents people from reasoning how else I'm going to gain the system. But why can we achieve in Algorand to have no incentives? And in Bitcoin instead, you have to pay the miners because they do tremendous amount of work. Because if you have to do a lot of work, then you demand to be paid accordingly. But if I'm going to say, you have to add two and two equal to four, how much you want me to pay for this? If you don't give me this, I don't add the two and two. I would say you can add two and two in your sleep. You don't need to be paid to add the two and two. So the idea is that if we make the system so efficient, so that generating the next block is so damn simple, it doesn't hit the universe, let alone my computer, let alone take some microsecond of computation, I might as well not being received incentives for doing that and try to incentivize some other part of the system, but not the main consensus, which is a mechanism for generating and adding block to the chain. Since you're Italian, Sicilian, I also heard rumors that you are a connoisseur of food. What, you know, if I said today's the last day you get to be alive, I'm Russian, you shouldn't have trusted me. You never know with a Russian whether you're going to make it out or not. Well, if you had one last meal, you can travel somewhere in the world. Either you make it or somebody else makes it. What's that going to look like? All right. If it's one last meal, I must say, in this era of COVID, I have not been able to see my mom. My mom was a fantastic chef, okay? And had the best, very traditional food. As you know, the very traditional food are great for a reason, because they survived hundreds of years of culinary innovation. And there is one very laborious thing, which is, you heard the name, which is this parmigiana. But to do it is a piece of art. It took so many hours that only my mom could do it. If we have one last meal, I want a parmigiana, okay? What is the laborious process? Is it the ingredients? Is it the actual process? Is it the atmosphere and the humans involved? The latter. The ingredient, like in any other, in Italian cuisine, believes in very few ingredients. If you take, say, quintessential Italian recipe that everybody knows, spaghetti pesto, okay? Pesto is olive oil, very good, extra virgin olive oil, basil, pine nuts, pepper, a clove of garlic, not too much, otherwise you use, you know- Overpower everything. And then you have to do either two schools of thought, parmesan or pecorino or a mix of the two. Yeah. I mentioned six ingredients. That is typical Italian. I understand that there are other cuisines, for instance, the French cuisine, which is extremely sophisticated and extremely combinatorial, or some Chinese cuisine, which has a lot of many more ingredients than this. And yet, the art is to put them together, a lot of things. In Italy, it's really striving for simplicity. You have to find few ingredients, but the right ingredients to create something. So in Parmigiana, the ingredients are eggplants, tomatoes, basil, but how to put them together and the process is an act of love, okay? Labor and love. You can spend the entire day, I'm not exaggerating, but the entire morning, for sure, to do it properly. Yeah. As a Japanese cuisine too, there's a mastery to the simplicity with the sushi. I don't know if you've seen Giro Dreams of Sushi, but there's a mastery to that that's propagated through the generations. It's fascinating. It's fascinating. You know, people love it when I ask about books. I don't know if books, whether fiction, nonfiction, technical, or completely non-technical, had an impact in your life throughout, if there's anything you would recommend, or even just mention as something that gave you an insight or moved you in some way. So, okay. So I don't know if I recommend, because in some sense, you almost had to be Italian or to be such a scholar, but being Italian, one thing that really impressed me tremendously is the Divine Comedy. It is a medieval poem, a very long poem, divided in three parts, hell, purgatory, and paradise, okay? And that is the non-trivial story of a middleman man gets into a crisis, personal crisis, and then out of this crisis, he purifies, when it's a catastrophe, purifies himself more and more and more until he's become capable of actually meeting God, okay? And that is actually a complex story. So he had to get some very sophisticated language, maybe Latin at that point, we're talking about 1200s Italy, right? In Florence. And this guy instead, he chose his own dialect, not spoken outside his own immediate circle, right? A Florentine dialect. And actually, Dante really made Italian Italian. And so I said, how can you express such a sophisticated things? And then the point is that these words that nobody actually knew because they were essentially dialect, and plus a bunch of very intricate rhymes in which you had to rhyme the things. And turns out that by getting meaning from the things that rhyme, you essentially guess what the word means. And you invent Italian and you communicate by almost osmosis what you want. It's a miracle of communication. In a dialect, a very poor language, very unsophisticated to express a very sophisticated situation. I love it. People love it and Italians and not Italian. But what I got of it is that very often, limitations are our strength. Because if you limit yourself at a very poor language, somehow you get out of it and you achieve even better form of communication that they're using a hyper sophisticated, a literary language of lots of resonance from the prior books, so that you can actually instantaneously quote. He couldn't quote anything because nothing was written in Italian before him. So I really felt that limitations are our strength. And I think that rather than complaining about the limitations, we should embrace them. Because if we embrace our limitation, limited as we are, we find very creative solutions that people with less limitation we have, we will not even think about it. Oh, so limitation is a kind of superpower if you choose to see it that way. Is there, since you speak both languages, is there something that's lost in translation to you? Is there something you can express in Italian that you can't in English and vice versa maybe? Is there something you could say to the musicality of the language? I mean, I've been to Italy a few times and I'm not sure if it's the actual words, but the people are certainly very, there's body language too. There's just the whole being is language. So I don't know if you miss some of that when you're speaking English in this country. Yes. In fact, actually, I certainly, I miss it. And somehow it was a sacrifice that I made consciously by the time I arrived, I knew that this I was not going to express myself at that level. And it was actually a sacrifice because given to you have also your mother tongue is Russian. So you know that you can be very expressive in your mother tongue and not very expressive in the new language. And then what people think of you in the new language, because when the precise of expression of things, it generates, it shows elegance or it shows knowledge or it shows us a census or it shows us a caste or education, whatever it is. So all of a sudden I found myself on the bottom. So I had to fight all my way up, back up. But I'm not saying, I go back to that. Yeah, it's fascinating, right? Their limitations are actually our strength. In fact, it's a trick to limit yourself to exceed. And there are examples in history, if you think about Hernan Cortes, goes to invade Mexico, he has what, a few hundred people with him and he has a hundred thousand people in arms on the other side. First thing he does, he limits himself. He sinks his own ship. There is no return. Okay. And I've met Borenti actually, manager. That's really profound. I actually, first of all, that's inspiring to me. I feel like I have quite a few limitations, but more practically on the Russian side, I'm going to try to do a couple of really big and really tough interviews in Russian. Once COVID lifts a little bit, I'm traveling to Russia and I'll keep your advice in mind that the limitations is a kind of superpower. We should use it to our advantage because you do feel less, like you're not able to convey your wisdom in the Russian language. Cause I moved here when I was 13. So you don't, the parts of life you live under a certain language are the parts of life you're able to communicate. I became a thoughtful, deeply thoughtful human in English. But the pain from World War II, the music of the people that was instilled with me in Russian. So I can carry both of those and there's limitations in both. I can't say philosophically profound stuff in Russian, but I can't in English express like that melancholy feeling of like the people. And so combining those two, I'll somehow... Oh, beautifully said. Thanks for sharing. This is great. Yes. I totally understand you. Yes. You've accomplished some incredible things in the space of science, in the space of technology, the space of theory and engineering. Do you have advice for somebody young, an undergraduate student, somebody in high school, or anyone who just feels young, about life or about career, about making their way in this world? So I was telling before that I believe in emotion and my thing is to be true to your own emotion. And that I think that if you do that, you're doing well because it's a life well spent and you are going never tire because you want to solve all these emotional knots that always intrigued you from the beginning. And I really believe that to live meaningfully, creatively, and yet to live your emotional life. So I really believe that whether you're a scientist or an artist even more, but a scientist, I think of them as artists as well. If you are a human being, so you are really to live fully your emotions and to the extent possible, sometimes emotions can be overbearing and my advice is try to express them with more and more confidence. Sometimes it's hard, but you are going to be much more fulfilled than by suppressing them. What about love? One of the big ones. What role does that play? That's the bigger part of emotions. It's a scary thing, right? It's a lot of vulnerability that comes with love, but there is also so much energy and power and love in all senses and in the traditional sense, but also in the sense of a broader sense for humanity, this feeling, this compassion that makes us one with other people and the suffering of other people. I mean, all of this is very scary stuff, but it's really the fabric of life. Well, the sad thing is it really hurts to lose it. Yes. That's why the vulnerability that comes with it. That's the thing about emotion is the up and the down and the down seems to come always with the ups, but the up only comes with the down. Let me ask you about the ultimate down, which is unfortunately, we humans are mortal or appear to be for the most part. Do you think about your own mortality? Do you fear death? I hope so. I do. Because without death, there is no life. So at least there is no meaningful life. Death is actually in some sense, our ultimate motivator to live a beautiful and meaningful life. I myself felt as a young man that unless I got something that I wanted to do, I don't know why I got this idea of something to say. If I'm not able to say, I would suicide. So maybe it was a way to motivate myself, but you don't need to motivate it because in some sense, unfortunately, death is there. So you better get up and do your thing because that is the best motivation to live fully. What do you hope your legacy is? You mentioned you have two kids. Yes. And so I really feel that on one side is my biological legacy and that is my two kids and their kids, hopefully. And that is one fine. And the other thing is this common enterprise, which is society. And I really feel that my legacy would be better by providing security and privacy. Actually, for me, I'm metaphorical to say, I want to give you the ability to interact more and take more risks and reach out more for more people as difficult and dangerous as it may seem. But my all scientific work is about to guarantee privacy and give you the security of interaction. And not only in a transaction, like it would be a blockchain transaction, but that is really one of the hard core of my emotional problems. And I think that these are the problems I want to tackle. Yeah. And ultimately, privacy and security is freedom. Yes. Freedom is at the core of this. It's dangerous. Just it's like the emotion. But ultimately, that's how we create all the beautiful things around us. Do you think there's meaning to it all? This life, except the urgency that death provides and us anxious beings create cool stuff along the way? Is there a deeper meaning? And if it is, what is it? Well, meaning of life. Actually, there are three meanings of life. Great. That's great. One, to seek. Two, to seek. And three, to seek. To seek what? Or is there no answer to that? There's no answer to that. I really think that the journey is more and more important than the destination, whatever that it be. And I think that is a journey and is, in my opinion, at the end of the day, I must admit, meaningful in itself. And we must admit that maybe whatever your destination might be, I'd be hanging, you know, we may never get there, but hell was a great ride. Well, I don't think there's a better way to end this, Silvio. Thank you for wasting your extremely valuable time with me today, joining on this journey of seeking something together. We found nothing, but it was very fun. I really enjoyed it. Thank you so much for talking to me. Thank you, Alex. It was really special for me to be interviewed by you. Thank you for listening to this conversation with Silvio Macaulay, and thank you to our sponsors, Athletic Greens Nutrition Drink, the Information in Depth Tech Journalism website, Four Sigmatic Mushroom Coffee, and BetterHelp Online Therapy. Click the sponsor links to get a discount and to support this podcast. And now, let me leave you with some words from Henry David Thoreau. Wealth is the ability to fully experience life. Thank you for listening, and hope to see you next time.

https://youtu.be/zNdhgOk4-fE

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Stephen Wolfram: Cellular Automata, Computation, and Physics | Lex Fridman Podcast #89

The following is a conversation with Stephen Wolfram, a computer scientist, mathematician, and theoretical physicist who is the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram Alpha, Wolfram Language, and the new Wolfram Physics Project. He's the author of several books, including A New Kind of Science, which on a personal note, was one of the most influential books in my journey in computer science and artificial intelligence. It made me fall in love with the mathematical beauty and power of cellular automata. It is true that perhaps one of the criticisms of Stephen is on a human level, that he has a big ego, which prevents some researchers from fully enjoying the content of his ideas. We talk about this point in this conversation. To me, ego can lead you astray, but can also be a superpower, one that fuels bold, innovative thinking that refuses to surrender to the cautious ways of academic institutions. And here, especially, I ask you to join me in looking past the peculiarities of human nature and opening your mind to the beauty of ideas in Stephen's work and in this conversation. I believe Stephen Wolfram is one of the most original minds of our time, and at the core, is a kind, curious, and brilliant human being. This conversation was recorded in November, 2019, when the Wolfram Physics Project was underway, but not yet ready for public exploration as it is now. We now agreed to talk again, probably multiple times in the near future, so this is round one, and stay tuned for round two soon. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with Five Stars and Apple Podcast, support it on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now, and never any ads in the middle that can break the flow of the conversation. I hope that works for you, and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, ExpressVPN and Cash App. Please consider supporting the podcast by getting ExpressVPN at expressvpn.com slash LexPod, and downloading Cash App and using code LexPodcast. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App does fractional share trading, let me mention that the order execution algorithm that works behind the scenes to create the abstraction of fractional orders is an algorithmic marvel. So big props to the Cash App engineers for solving a hard problem, that in the end provides an easy interface that takes a step up to the next layer of abstraction over the stock market. This makes trading more accessible for new investors and diversification much easier. So again, if you get Cash App from the App Store, Google Play, and use the code LexPodcast, you get $10, and Cash App will also donate $10 to FIRST, an organization that is helping to advance robotics and STEM education for young people around the world. This show is presented by ExpressVPN. Get it at expressvpn.com slash LexPod to get a discount and to support this podcast. I've been using ExpressVPN for many years. I love it. It's really easy to use. Press the big power on button and your privacy is protected. And if you like, you can make it look like your location is anywhere else in the world. This has a large number of obvious benefits. Certainly, it allows you to access international versions of streaming websites like the Japanese Netflix or the UK Hulu. ExpressVPN works on any device you can imagine. I use it on Linux. Shout out to Ubuntu. New version coming out soon, actually. Windows, Android, but it's available anywhere else too. Once again, get it at expressvpn.com slash LexPod to get a discount and to support this podcast. And now, here's my conversation with Stephen Wolfram. You and your son, Christopher, helped create the alien language in the movie Arrival. So let me ask maybe a bit of a crazy question, but if aliens were to visit us on Earth, do you think we would be able to find a common language? Well, by the time we're saying aliens are visiting us, we've already prejudiced the whole story because the concept of an alien actually visiting, so to speak, we already know they're kind of things that make sense to talk about visiting. So we already know they exist in the same kind of physical setup that we do. They're not, you know, it's not just radio signals. It's an actual thing that shows up and so on. So I think in terms of, you know, can one find ways to communicate? Well, the best example we have of this right now is AI. I mean, that's our first sort of example of alien intelligence. And the question is, how well do we communicate with AI? You know, if you were to say, if you were in the middle of a neural net and you open it up and it's like, what are you thinking? Can you discuss things with it? It's not easy, but it's not absolutely impossible. So I think by the time, but given the setup of your question, aliens visiting, I think the answer is yes, one will be able to find some form of communication, whatever communication means, communication requires notions of purpose and things like this. It's a kind of philosophical quagmire. So if AI is a kind of alien life form, what do you think visiting looks like? So if we look at aliens visiting and we'll get to discuss computation and the world of computation, but if you were to imagine, you said you already prejudiced something by saying you visit, but how would aliens visit? By visit, there's kind of an implication and here we're using the imprecision of human language. In a world of the future, and if that's represented in computational language, we might be able to take the concept visit and go look in the documentation basically and find out exactly what does that mean? What properties does it have and so on? But by visit in ordinary human language, I'm kind of taking it to be there's something, a physical embodiment that shows up in a spacecraft since we kind of know that that's necessary. We're not imagining it's just photons showing up in a radio signal that, photons in some very elaborate pattern. We're imagining it's physical things made of atoms and so on that show up. Can it be photons in a pattern? Well, that's good question. I mean, whether there is the possibility, what counts as intelligence? Good question. I mean, it's, and I used to think there was sort of a, oh, there'll be, it'll be clear what it means to find extraterrestrial intelligence, et cetera, et cetera, et cetera. I've increasingly realized as a result of science that I've done that there really isn't a bright line between the intelligent and the merely computational, so to speak. So, in our kind of everyday sort of discussion, we'll say things like, the weather has a mind of its own. Well, let's unpack that question. We realize that there are computational processes that go on that determine the fluid dynamics of this and that and the atmosphere, et cetera, et cetera, et cetera. How do we distinguish that from the processes that go on in our brains of, you know, the physical processes that go on in our brains? How do we separate those? How do we say the physical processes going on that represent sophisticated computations in the weather? Oh, that's not the same as the physical processes that go on that represent sophisticated computations in our brains. The answer is I don't think there is a fundamental distinction. I think the distinction for us is that there's kind of a thread of history and so on that connects kind of what happens in different brains to each other, so to speak, and it's a, you know, what happens in the weather is something which is not connected by sort of a thread of civilizational history, so to speak, to what we're used to. In the stories that the human brains told us, but maybe the weather has its own stories that tells itself. Absolutely, absolutely, and that's where we run into trouble thinking about extraterrestrial intelligence because, you know, it's like that pulsar magnetosphere that's generating these very elaborate radio signals. You know, is that something that we should think of as being this whole civilization that's developed over the last however long, you know, millions of years of processes going on in the neutron star or whatever versus what, you know, what we're used to in human intelligence. I mean, I think in the end, you know, when people talk about extraterrestrial intelligence and where is it and the whole, you know, Fermi paradox of how come there's no other signs of intelligence in the universe, my guess is that we've got sort of two alien forms of intelligence that we're dealing with, artificial intelligence and sort of physical or extraterrestrial intelligence, and my guess is people will sort of get comfortable with the fact that both of these have been achieved around the same time. And in other words, people will say, well, yes, we're used to computers, things we've created, digital things we've created being sort of intelligent like we are, and they'll say, oh, we're kind of also used to the idea that there are things around the universe that are kind of intelligent like we are, except they don't share the sort of civilizational history that we have, and so we don't, you know, they're a different branch. I mean, it's similar to when you talk about life, for instance, I mean, you kind of said life form, I think, almost synonymously with intelligence, which I don't think is, you know, the AIs will be upset to hear you equate those two things. Because they really probably implied biological life. Right, right. But you're saying, I mean, we'll explore this more, but you're saying it's really a spectrum and it's all just a kind of computation, and so it's a full spectrum, and we just make ourselves special by weaving a narrative around our particular kinds of computation. Yes, I mean, the thing that I think I've kind of come to realize is, you know, at some level, it's a little depressing to realize that there's so little that's special about it. Or liberating. Well, yeah, but I mean, it's, you know, it's the story of science, right? And, you know, from Copernicus on, it's like, you know, first we were like convinced our planet's at the center of the universe. No, that's not true. Well, then we were convinced there's something very special about the chemistry that we have as biological organisms. No, that's not really true. And then we're still holding out that hope. Oh, this intelligence thing we have, that's really special. I don't think it is. However, in a sense, as you say, it's kind of liberating for the following reason, that you realize that what's special is the details of us, not some abstract attribute that, you know, we could wonder, oh, is something else gonna come along and, you know, also have that abstract attribute? Well, yes, every abstract attribute we have, something else has it. But the full details of our kind of history of our civilization and so on, nothing else has that. That's what, you know, that's our story, so to speak. And that's sort of almost by definition special. So I view it as not being such a, I mean, I was, initially I was like, this is bad. This is kind of, you know, how can we have self-respect about the things that we do? Then I realized the details of the things we do, they are the story. Everything else is kind of a blank canvas. So maybe on a small tangent, you just made me think of it, but what do you make of the monoliths in 2001's Space Odyssey in terms of aliens communicating with us and sparking the kind of particular intelligent computation that we humans have? Is there anything interesting to get from that sci-fi? Yeah, I mean, I think what's fun about that is, you know, the monoliths are these, you know, one to four to nine perfect cuboid things. And in the, you know, Earth a million years ago, whatever they were portraying with a bunch of apes and so on, a thing that has that level of perfection seems out of place. It seems very kind of constructed, very engineered. So that's an interesting question. What is the, you know, what's the techno signature, so to speak? What is it that you see it somewhere and you say, my gosh, that had to be engineered. Now, the fact is we see crystals, which are also very perfect. And, you know, the perfect ones are very perfect. They're nice polyhedra or whatever. And so in that sense, if you say, well, it's a sign of sort of, it's a techno signature that it's a perfect, you know, a perfect polygonal shape, polyhedral shape. That's not true. And so then it's an interesting question. What is the, you know, what is the right signature? I mean, like, you know, Gauss, famous mathematician, you know, he had this idea, you should cut down the Siberian forest in the shape of sort of a typical image of the proof of the Pythagorean theorem on the grounds that, it was a kind of cool idea, it didn't get done, but, you know, it was on the grounds that the Martians would see that and realize, gosh, there are mathematicians out there. It's kind of, you know, it's the, in his theory of the world, that was probably the best advertisement for the cultural achievements of our species. But, you know, it's a reasonable question. What do you, what can you send or create that is a sign of intelligence in its creation or even intention in its creation? Yeah, you talk about if we were to send a beacon. Can you, what should we send? Is math our greatest creation? Is, what is our greatest creation? I think, I think, and it's a philosophically doomed issue. I mean, in other words, you send something, you think it's fantastic, but it's kind of like, we are part of the universe, we make things that are, you know, things that happen in the universe. Computation, which is sort of the thing that we are, in some abstract sense, using to create all these elaborate things we create, is surprisingly ubiquitous. In other words, we might've thought that, you know, we've built this whole giant engineering stack that's led us to microprocessors, that's led us to be able to do elaborate computations, but this idea, the computations are happening all over the place. The only question is whether there's a thread that connects our human intentions to what those computations are. And so I think, I think this question of what do you send to kind of show off our civilization in the best possible way, I think any kind of almost random slab of stuff we've produced is about equivalent to everything else. I think it's one of these things where- Such a non-romantic way of phrasing it. I just, sorry to interrupt, but I just talked to Ann Druyan, who's the wife of Carl Sagan. And so I don't know if you're familiar with the Voyager. I mean, she was part of sending, I think, brainwaves of, you know, I want you to- Wasn't it hers? It was hers. Her brainwaves. Her brainwaves when she was first falling in love with Carl Sagan, right? So this beautiful story. Right. That perhaps you would shut down the power of that by saying we might as well send anything else. And that's interesting. All of it is kind of an interesting, peculiar thing. That's- Yeah, yeah, right. I think it's kind of interesting to see on the Voyager golden record thing. One of the things that's kind of cute about that is, you know, it was made, when was it? In the late 70s, early 80s. And, you know, one of the things, it's a phonograph record, okay? And it has a diagram of how to play a phonograph record. And, you know, it's kind of like, it's shocking that in just 30 years, if you show that to a random kid of today and you show them that diagram, and I've tried this experiment, they're like, I don't know what the heck this is. And the best anybody can think of is, you know, take the whole record, forget the fact that it has some kind of helical track in it, just image the whole thing and see what's there. That's what we would do today. In only 30 years, our technology has kind of advanced to the point where the playing of a helical, you know, mechanical track on a phonograph record is now something bizarre. So, you know, that's a cautionary tale, I would say, in terms of the ability to make something that in detail sort of leads by the nose, some, you know, the aliens or whatever, to do something. It's like, no, you know, best you're gonna do, as I say, if we were doing this today, we would not build a helical scan thing with a needle. We would just take some high resolution imaging system and get all the bits off it and say, oh, it's a big nuisance that they put in a helix, you know, in a spiral. Let's just, you know, unravel the spiral and start from there. Do you think, and this will get into trying to figure out interpretability of AI, interpretability of computation, being able to communicate with various kinds of computations. Do you think we'd be able to, if you put your alien hat on, figure out this record, how to play this record? Well, it's a question of what one wants to do. I mean- Understand what the other party was trying to communicate or understand anything about the other party. What does understanding mean? I mean, that's the issue. The issue is, it's like when people were trying to do natural language understanding for computers, right? So people tried to do that for years. It wasn't clear what it meant. In other words, you take your piece of English or whatever and you say, gosh, my computer has understood this. Okay, that's nice. What can you do with that? Well, so for example, when we did, you know, built WolfMalpha, you know, one of the things was, it's, you know, it's doing question answering and so on. It needs to do natural language understanding. The reason that I realized after the fact, the reason we were able to do natural language understanding quite well and people hadn't before, the number one thing was we had an actual objective for the natural language understanding. We were trying to turn the natural language- Into computation. Into this computational language that we could then do things with. Now, similarly, when you imagine your alien, you say, okay, we're playing them the record. Did they understand it? Well, depends what you mean. If they, you know, if we, if there's a representation that they have, if it converts to some representation where we can say, oh yes, that is a, that's a representation that we can recognize is represents understanding, then all well and good. But actually the only ones that I think we can say would represent understanding are ones that will then do things that we humans kind of recognize as being useful to us. Maybe you're trying to understand, quantify how technologically advanced this particular civilization is. So are they a threat to us from a military perspective? Yeah, yeah. That's probably the kind of, first kind of understanding that I'll be interested in. Gosh, that's so hard. I mean, that's like in the Arrival movie, that was sort of one of the key questions is, you know, why are you here, so to speak? And it's- Are you gonna hurt us? Right. But even that is, you know, it's a very unclear, you know, it's like the, are you gonna hurt us? That comes back to a lot of interesting AI ethics questions because the, you know, we might make an AI that says, well, take autonomous cars, for instance, you know, are you gonna hurt us? Well, let's make sure you only drive at precisely the speed limit because we wanna make sure we don't hurt you, so to speak, because that's some, and then, well, something, you know, but you say, but actually that means I'm gonna be really late for this thing, and, you know, that sort of hurts me in some way. So it's hard to know, even the definition of what it means to hurt someone is unclear. And as we start thinking about things about AI ethics and so on, that's, you know, something one has to address. There's always trade-offs, and that's the annoying thing about ethics. Yeah, well, right, and I mean, I think ethics, like these other things we're talking about, is a deeply human thing. There's no abstract, you know, let's write down the theorem that proves that this is ethically correct. That's a meaningless idea. You know, you have to have a ground truth, so to speak, that's ultimately sort of what humans want, and they don't all want the same thing. So that gives one all kinds of additional complexity in thinking about that. One convenient thing in terms of turning ethics into computation, you can ask the question of what maximizes the likelihood of the survival of the species? Yeah, that's a good existential issue. But then when you say survival of the species, right, you might say, you might, for example, for example, let's say, forget about technology, just, you know, hang out and, you know, be happy, live our lives, go on to the next generation, you know, go through many, many generations where, in a sense, nothing is happening. Is that okay? Is that not okay? Hard to know. In terms of, you know, the attempt to do elaborate things and the attempt to might be counterproductive for the survival of the species. Like, for instance, I mean, in, you know, I think it's also a little bit hard to know, so, okay, let's take that as a sort of thought experiment. Okay, you know, you can say, well, what are the threats that we might have to survive? You know, the super volcano, the asteroid impact, the, you know, all these kinds of things. Okay, so now we inventory these possible threats and we say, let's make our species as robust as possible relative to all these threats. I think in the end, it's sort of an unknowable thing, what it takes to, you know, so given that you've got this AI and you've told it, maximize the long-term, what does long-term mean? Does long-term mean until the sun burns out? That's not gonna work. You know, does long-term mean next thousand years? Okay, there are probably optimizations for the next thousand years that it's like, it's like if you're running a company, you can make a company be very stable for a certain period of time. Like if, you know, if your company gets bought by some, you know, private investment group, then they'll, you know, you can run a company just fine for five years by just taking what it does and, you know, removing all R&D and the company will burn out after a while, but it'll run just fine for a little while. So if you tell the AI, keep the humans okay for a thousand years, there's probably a certain set of things that one would do to optimize that, many of which one might say, well, that would be a pretty big shame for the future of history, so to speak, for that to be what happens. But I think in the end, you know, as you start thinking about that question, it is what you realize is there's a whole sort of raft of undecidability, computational irreducibility. In other words, it's, I mean, one of the good things about sort of the, what our civilization has gone through and what sort of we humans go through is that there's a certain computational irreducibility to it in the sense that it isn't the case that you can look from the outside and just say, the answer is gonna be this. At the end of the day, this is what's gonna happen. You actually have to go through the process to find out. And I think that's both, that feels better in the sense it's not a, you know, something is achieved by going through all of this process. And it's, but it also means that telling the AI, go figure out, you know, what will be the best outcome? Well, unfortunately, it's gonna come back and say, it's kind of undecidable what to do. We'd have to run all of those scenarios to see what happens. And if we want it for the infinite future, we're thrown immediately into sort of standard issues of kind of infinite computation and so on. So yeah, even if you get that the answer to the universe and everything is 42, you still have to actually run the universe. Yes. To figure out like the question, I guess, or the, you know, the journey is the point. Right, well, I think it's saying to summarize, this is the result of the universe. Yeah, that's, if that is possible, it tells us, I mean, the whole sort of structure of thinking about computation and so on, and thinking about how stuff works. If it's possible to say, and the answer is such and such, you're basically saying there's a way of going outside the universe. And you're kind of, you're getting yourself into something of a sort of paradox, because you're saying, if it's knowable, what the answer is, then there's a way to know it that is beyond what the universe provides. But if we can know it, then something that we're dealing with is beyond the universe. So then the universe isn't the universe, so to speak. So. And in general, as we'll talk about, at least for our small human brains, it's hard to show that the result of a sufficiently complex computation. It's hard, I mean, it's probably impossible, right? Undecidability, so. And the universe appears, by at least the poets, to be sufficiently complex that we won't be able to predict what the heck it's all going to. Well, we better not be able to, because if we can, it kind of denies, I mean, it's, you know, we're part of the universe. Yeah. So what does it mean for us to predict? It means that we, that our little part of the universe is able to jump ahead of the whole universe. And, you know, this quickly winds up, I mean, it is conceivable. The only way we'd be able to predict is if we are so special in the universe, we are the one place where there is computation more special, more sophisticated than anything else that exists in the universe. That's the only way we would have the ability to, sort of the almost theological ability, so to speak, to predict what happens in the universe, is to say somehow we're better than everything else in the universe, which I don't think is the case. Yeah, perhaps we can detect a large number of looping patterns that reoccur throughout the universe and fully describe them, and therefore, but then it still becomes exceptionally difficult to see how those patterns interact and what kind of complexity emerges. The most remarkable thing about the universe is that it has regularity at all. Might not be the case. If you were just- Does it have regularity? Do you have- Absolutely, it's full of, I mean, physics is successful. It's full of laws that tell us a lot of detail about how the universe works. I mean, it could be the case that the 10 to the 90th particles in the universe, they all do their own thing, but they don't. They all follow, we already know, they all follow basically the same physical laws, and that's a very profound fact about the universe. What conclusion you draw from that is unclear. I mean, in the early theologians, that was exhibit number one for the existence of God. Now, people have different conclusions about it, but the fact is, right now, I mean, I happen to be interested, actually. I've just restarted a long-running kind of interest of mine about fundamental physics. I'm kind of like, I'm on a bit of a quest, which I'm about to make more public to see if I can actually find the fundamental theory of physics. Excellent, we'll come to that, and I just had a lot of conversations with quantum mechanics folks, so I'm really excited on your take, because I think you have a fascinating take on the fundamental nature of our reality from a physics perspective, and what might be underlying the kind of physics as we think of it today. Okay, let's take a step back. What is computation? That's a good question. Operationally, computation is following rules. That's kind of it. I mean, computation is the result, is the process of systematically following rules, and it is the thing that happens when you do that. So taking initial conditions, or taking inputs and following rules, I mean, what are you following rules on? So there has to be some data, some... Not necessarily. It can be something where there's a, you know, very simple input, and then you're following these rules, and you'd say there's not really much data going into this. You could actually pack the initial conditions into the rule if you want to. So I think the question is, is there a robust notion of computation? That is- What does robust mean? What I mean by that is something like this. So one of the things in another physics, something like energy, okay? There are different forms of energy, but somehow energy is a robust concept that isn't particular to kinetic energy, or, you know, nuclear energy, or whatever else. There's a robust idea of energy. So one of the things you might ask is there's the robust idea of computation, or does it matter that this computation is running in a Turing machine? This computation is running in a, you know, CMOS silicon CPU. This computation is running in a fluid system in the weather, those kinds of things. Or is there a robust idea of computation that transcends the sort of detailed framework that it's running in, okay? And- Is there? Yes. I mean, it wasn't obvious that there was, so it's worth understanding the history and how we got to where we are right now, because, you know, to say that there is, is a statement in part about our universe. It's not a statement about what is mathematically conceivable. It's about what actually can exist for us. Maybe you can also comment, because energy as a concept is robust, but there's also, it's intricate, complicated relationship with matter, with mass, is very interesting, of particles that carry force, and particles that sort of, particles that carry force and particles that have mass. These kinds of ideas, they seem to map to each other, at least in the mathematical sense. Is there a connection between energy and mass and computation, or are these completely disjoint ideas? We don't know yet. The things that I'm trying to do about fundamental physics may well lead to such a connection, but there is no known connection at this time. So can you elaborate a little bit more on how do you think about computation? What is computation? Yeah, so I mean, let's tell a little bit of a historical story, okay? So, you know, go back 150 years, people were making mechanical calculators of various kinds. And, you know, the typical thing was, you want an adding machine, you go to the adding machine store, basically. You want a multiplying machine, you go to the multiplying machine store. They're different pieces of hardware. And so that means that, at least at the level of that kind of computation and those kinds of pieces of hardware, there isn't a robust notion of computation. There's the adding machine kind of computation, there's the multiplying machine notion of computation, and they're disjoint. So what happened in around 1900, people started imagining, particularly in the context of mathematical logic, could you have something which would represent any reasonable function, right? And they came up with things, this idea of primitive recursion was one of the early ideas, and it didn't work. There were reasonable functions that people could come up with that were not represented using the primitives of primitive recursion, okay? So then along comes 1931 and Gödel's theorem and so on. And as in looking back, one can see that as part of the process of establishing Gödel's theorem, Gödel basically showed how you could compile arithmetic, how you could basically compile logical statements like this statement is unprovable into arithmetic. So what he essentially did was to show that arithmetic can be a computer in a sense that's capable of representing all kinds of other things. And then Turing came along, 1936 came up with Turing machines. Meanwhile, Alonzo Church had come up with lambda calculus. And the surprising thing that was established very quickly is the Turing machine idea about what computation might be is exactly the same as the lambda calculus idea of what computation might be. And so, and then there started to be other ideas, register machines, other kinds of representations of computation. And the big surprise was they all turned out to be equivalent. So in other words, it might've been the case like those old adding machines and multiplying machines that Turing had his idea of computation, Church had his idea of computation and they were just different, but it isn't true. They're actually all equivalent. So then by, I would say the 1970s or so in sort of the computation, computer science computation theory area, people had sort of said, oh, Turing machines are kind of what computation is. Physicists were still holding out saying, no, no, no, that's just not how the universe works. We've got all these differential equations. We've got all these real numbers that have infinite numbers of digits. The universe is not a Turing machine. Right. The Turing machines are a small subset of the things that we make in microprocessors and engineering structures and so on. So probably actually through my work in the 1980s about sort of the relationship between computation and models of physics, it became a little less clear that there would be, that there was this big sort of dichotomy between what can happen in physics and what happens in things like Turing machines. And I think probably by now people would mostly think, by the way, brains were another kind of elements of this. I mean, you know, Gödel didn't think that his notion of computation or what amounted to his notion of computation would cover brains. And Turing wasn't sure either. But although he was a little bit, he got to be a little bit more convinced that it should cover brains. But so, you know, but I would say by probably sometime in the 1980s, there was beginning to be sort of a general belief that yes, this notion of computation that could be captured by things like Turing machines was reasonably robust. Now, the next question is, okay, you can have a universal Turing machine that's capable of being programmed to do anything that any Turing machine can do. And, you know, this idea of universal computation is an important idea. This idea that you can have one piece of hardware and program it with different pieces of software. You know, that's kind of the idea that launched most modern technology. I mean, that's kind of the, that's the idea that launched computer revolution, software, et cetera. So important idea. But the thing that's still kind of holding out from that idea is, okay, there is this universal computation thing, but seems hard to get to. Seems like you want to make a universal computer, you have to kind of have a microprocessor with, you know, a million gates in it, and you have to go to a lot of trouble to make something that achieves that level of computational sophistication. Okay, so the surprise for me was that stuff that I discovered in the early 80s, looking at these things called cellular automata, which are really simple computational systems. The thing that was a big surprise to me was that even when their rules were very, very simple, they were doing things that were as sophisticated as they did when their rules were much more complicated. So it didn't look like, you know, this idea, oh, to get sophisticated computation, you have to build something with very sophisticated rules. That idea didn't seem to pan out. And instead, it seemed to be the case that sophisticated computation was completely ubiquitous, even in systems with incredibly simple rules. And so that led to this thing that I call the principle of computational equivalence, which basically says, when you have a system that follows rules of any kind, then whenever the system isn't doing things that are in some sense obviously simple, then the computation that the behavior of the system corresponds to is of equivalent sophistication. So that means that when you kind of go from the very, very, very simplest things you can imagine, then quite quickly, you hit this kind of threshold above which everything is equivalent in its computational sophistication. Not obvious that would be the case. I mean, that's a science fact. Well, no, no, no, no, hold on a second. So this, you've opened with a new kind of science. I mean, I remember it was a huge eye-opener that such simple things can create such complexity, and yes, there's an equivalence, but it's not a fact. It just appears to, I mean, as much as a fact as sort of these theories are so elegant that it seems to be the way things are. But let me ask sort of, you just brought up previously kind of like the communities of computer scientists with their Turing machines, the physicists with their universe, and whoever the heck, maybe neuroscientists looking at the brain. What's your sense in the equivalence? So you've shown through your work that simple rules can create equivalently complex Turing machine systems, right? Is the universe equivalent to the kinds of, to Turing machines? Is the human brain a kind of Turing machine? Do you see those things basically blending together, or is there still a mystery about how disjoint they are? Well, my guess is that they all blend together, but we don't know that for sure yet. I mean, this, you know, I should say, I said rather glibly that the principle of computational equivalence is sort of a science fact. And I was using air quotes for the science fact, because when you, it is a, I mean, just to talk about that for a second, and then we'll, the thing is that it is, it has a complicated epistemological character, similar to things like the second law of thermodynamics, the law of entropy increase. The, you know, what is the second law of thermodynamics? It is, is it a law of nature? Is it a thing that is true of the physical world? Is it something which is mathematically provable? Is it something which happens to be true of the systems that we see in the world? Is it in some sense, a definition of heat perhaps? Well, it's a combination of those things. And it's the same thing with the principle of computational equivalence. And in some sense, the principle of computational equivalence is at the heart of the definition of computation, because it's telling you there is a thing, there is a robust notion that is equivalent across all these systems and doesn't depend on the details of each individual system. And that's why we can meaningfully talk about a thing called computation. And we're not stuck talking about, oh, there's computation in Turing machine number 3785, and et cetera, et cetera, et cetera. That's why there is a robust notion like that. Now, on the other hand, can we prove the principle of computational equivalence? Can we prove it as a mathematical result? Well, the answer is, actually we've got some nice results along those lines that say, throw me a random system with very simple rules. Well, in a couple of cases, we now know that even the very simplest rules we can imagine of a certain type are universal and do sort of follow what you would expect from the principle of computational equivalence. So that's a nice piece of sort of mathematical evidence for the principle of computational equivalence. Just to link on that point, simple rules creating sort of these complex behaviors, but is there a way to mathematically say that this behavior is complex? That you've mentioned that you cross a threshold. Right. So there are various indicators. So for example, one thing would be, is it capable of universal computation? That is given the system, do there exist initial conditions for the system that can be set up to essentially represent programs to do anything you want, to compute primes, to compute pi, to do whatever you want. Right. So that's an indicator. So we know in a couple of examples that yes, the simplest candidates that could conceivably have that property do have that property. And that's what the principle of computational equivalence might suggest. But this principle of computational equivalence, one question about it is, is it true for the physical world? Right. It might be true for all these things we come up with, the Turing machines, the cellular automata, whatever else. Is it true for our actual physical world? Is it true for the brains, which are an element of the physical world? We don't know for sure. And that's not the type of question that we will have a definitive answer to, because there's a sort of scientific induction issue. You can say, well, it's true for all these brains, but this person over here is really special and it's not true for them. And you can't, you know, the only way that that cannot be what happens is if we finally nail it and actually get a fundamental theory for physics, and it turns out to correspond to, let's say a simple program. If that is the case, then we will basically have reduced physics to a branch of mathematics, in the sense that we will not be, you know, right now with physics, we're like, well, this is the theory that, you know, this is the rules that apply here, but in the middle of that, you know, right by that black hole, maybe these rules don't apply and something else applies. And there may be another piece of the onion that we have to peel back. But if we can get to the point where we actually have, this is the fundamental theory of physics, here it is, it's this program, run this program, and you will get our universe, then we've kind of reduced the problem of figuring out things in physics to a problem of doing some, what turns out to be very difficult, irreducibly difficult mathematical problems. But it no longer is the case that we can say that somebody can come in and say, whoops, you know, you were right about all these things about Turing machines, but you're wrong about the physical universe. We know that sort of ground truth about what's happening in the physical universe. Now, I happen to think, I mean, you asked me at an interesting time because I'm just in the middle of starting to re-energize my project to kind of study the fundamental theory of physics. As of today, I'm very optimistic that we're actually gonna find something and that it's going to be possible to see that the universe really is computational in that sense. But I don't know because we're betting against, we're betting against the universe, so to speak. And I didn't, you know, it's not like, you know, when I spend a lot of my life building technology and then I know what's in there, right? And it's, there may be, it may have unexpected behavior, it may have bugs, things like that, but fundamentally I know what's in there. For the universe, I'm not in that position, so to speak. What kind of computation do you think the fundamental laws of physics might emerge from? So just to clarify, so there's, you've done a lot of fascinating work with kind of discrete kinds of computation that, you know, you could sell your automata, and we'll talk about it, have this very clean structure. It's such a nice way to demonstrate that simple rules can create immense complexity. But what, you know, is that actually, are cellular automata sufficiently general to describe the kinds of computation that might create the laws of physics? Just to give, can you give a sense of what kind of computation do you think would create the laws of physics? So this is a slightly complicated issue because as soon as you have universal computation, you can in principle simulate anything with anything. But it is not a natural thing to do. And if you're asking, were you to try to find our physical universe by looking at possible programs in the computational universe of all possible programs, would the ones that correspond to our universe be small and simple enough that we might find them by searching that computational universe? We got to have the right basis, so to speak. We have got to have the right language in effect for describing computation for that to be feasible. So the thing that I've been interested in for a long time is what are the most structuralist structures that we can create with computation? So in other words, if you say a cellular automaton, it has a bunch of cells that are arrayed on a grid and it's very, you know, and every cell is updated in synchrony at a particular, you know, when there's a click of a clock, so to speak, and it goes, a tick of a clock, and every cell gets updated at the same time. That's a very specific, very rigid kind of thing. But my guess is that when we look at physics and we look at things like space and time, that what's underneath space and time is something as structureless as possible, that what we see, what emerges for us as physical space, for example, comes from something that is sort of arbitrarily unstructured underneath. And so I've been for a long time interested in kind of what are the most structureless structures that we can set up? And actually what I had thought about for ages is using graphs, networks, where essentially, so let's talk about space, for example. So what is space? Is a kind of a question one might ask. Back in the early days of quantum mechanics, for example, people said, oh, for sure, space is gonna be discrete because all these other things we're finding are discrete, but that never worked out in physics. And so space and physics today is always treated as this continuous thing, just like Euclid imagined it. I mean, the very first thing Euclid says in his sort of common notions is, a point is something which has no part. In other words, there are points that are arbitrarily small and there's a continuum of possible positions of points. And the question is, is that true? And so, for example, if we look at, I don't know, a fluid like air or water, we might say, oh, it's a continuous fluid. We can pour it, we can do all kinds of things continuously. But actually we know, because we know the physics of it, that it consists of a bunch of discrete molecules bouncing around and only in the aggregate is it behaving like a continuum. And so the possibility exists that that's true of space too. People haven't managed to make that work with existing frameworks in physics, but I've been interested in whether one can imagine that underneath space and also underneath time is something more structureless. And the question is, is it computational? So there are a couple of possibilities. It could be computational, somehow fundamentally equivalent to a Turing machine, or it could be fundamentally not. So how could it not be? It could not be, so a Turing machine essentially deals with integers, whole numbers, at some level. And it can do things like it can add one to a number. It can do things like this. And can also store whatever the heck it did. Yes, it has an infinite storage. But when one thinks about doing physics or sort of idealized physics or idealized mathematics, one can deal with real numbers, numbers with an infinite number of digits, numbers which are absolutely precise. And one can say, we can take this number and we can multiply it by itself. Are you comfortable with infinity in this context? Are you comfortable in a context of computation? Do you think infinity plays a part? I think that the role of infinity is complicated. Infinity is useful in conceptualizing things. It's not actualizable. Almost by definition, it's not actualizable. But do you think infinity is part of the thing that might underlie the laws of physics? I think that, no. I think there are many questions that you ask about, you might ask about physics, which inevitably involve infinity. Like when you say, is faster than light travel possible? You could say, given the laws of physics, can you make something even arbitrarily large, even quotes infinitely large, that will make faster than light travel possible? Then you're thrown into dealing with infinity as a kind of theoretical question. But I mean, talking about, sort of what's underneath space and time and how one can make a computational infrastructure. One possibility is that you can't make a computational infrastructure in a Turing machine sense. That you really have to be dealing with precise real numbers. You're dealing with partial differential equations, which have precise real numbers at arbitrarily closely separated points. You have a continuum for everything. Could be that that's what happens. That there's sort of a continuum for everything and precise real numbers for everything. And then the things I'm thinking about are wrong. And that's the risk you take if you're trying to sort of do things about nature, is you might just be wrong. It's not, for me personally, it's kind of a strange thing because I've spent a lot of my life building technology where you can do something that nobody cares about, but you can't be sort of wrong in that sense. In the sense you build your technology and it does what it does. But I think this question of what the sort of underlying computational infrastructure for the universe might be. So it's sort of inevitable it's gonna be fairly abstract. Because if you're gonna get all these things like there are three dimensions of space, there are electrons, there are muons, there are quarks, there are this. You don't get to, if the model for the universe is simple, you don't get to have sort of a line of code for each of those things. You don't get to have sort of the muon case, the tau lepton case and so on. All of those things have to be emergent somehow. Right. So something deeper. Right, so that means it's sort of inevitable that's a little hard to talk about what the sort of underlying structuralist structure actually is. Do you think human beings have the cognitive capacity to understand, if we're to discover it, to understand the kinds of simple structure from which these laws can emerge? Like, do you think that's a hopeless pursuit? Well, here's what I think. I think that, I mean, I'm right in the middle of this right now. So I'm telling you that I think this human, yeah, I mean, this human has a hard time understanding a bunch of the things that are going on. But what happens in understanding is one builds waypoints. I mean, if you said, understand modern 21st century mathematics, starting from counting back in, whenever counting was invented 50,000 years ago, whatever it was, right? That will be really difficult. But what happens is we build waypoints that allow us to get to higher levels of understanding. And we see the same thing happening in language. When we invent a word for something, it provides kind of a cognitive anchor, a kind of a waypoint that lets us, like a podcast or something. You could be explaining, well, it's a thing, which this works this way, that way, the other way. But as soon as you have the word podcast and people kind of societally understand it, you start to be able to build on top of that. And so I think, and that's kind of the story of science actually too. I mean, science is about building these kind of waypoints where we find this sort of cognitive mechanism for understanding something, then we can build on top of it. You know, we have the idea of, I don't know, differential equations, we can build on top of that. We have this idea or that idea. So my hope is that if it is the case that we have to go all the way sort of from the sand to the computer and there's no waypoints in between, then we're toast. We won't be able to do that. Well, eventually we might. So if we're, us clever apes are good enough at building those abstractions, eventually from sand we'll get to the computer, right? And it just might be a longer journey. The question is whether it is something that you asked, whether our human brains will quote understand what's going on. And that's a different question because for that it requires steps that are sort of from which we can construct a human understandable narrative. And that's something that I think I am somewhat hopeful that that will be possible. Although, you know, as of literally today, if you ask me, I'm confronted with things that I don't understand very well. And- So this is a small pattern in a computation trying to understand the rules under which the computation functions. And it's an interesting possibility under which kinds of computations such a creature can understand itself. My guess is that within, so we didn't talk much about computational irreducibility, but it's a consequence of this principle of computational equivalence. And it's sort of a core idea that one has to understand, I think, which is question is you're doing a computation, you can figure out what happens in the computation just by running every step in the computation and seeing what happens. Or you can say, let me jump ahead and figure out, you know, have something smarter that figures out what's gonna happen before it actually happens. And a lot of traditional science has been about that act of computational reducibility. It's like, we've got these equations and we can just solve them and we can figure out what's gonna happen. We don't have to trace all of those steps. We just jump ahead because we solved these equations. Okay, so one of the things that is a consequence of the principle of computational equivalence is you don't always get to do that. Many, many systems will be computationally irreducible in the sense that the only way to find out what they do is just follow each step and see what happens. Why is that? Well, if you're saying, well, we, with our brains, we're a lot smarter. We don't have to mess around like the little cellular automaton going through and updating all those cells. We can just use the power of our brains to jump ahead. But if the principle of computational equivalence is right, that's not gonna be correct because it means that there's us doing our computation in our brains. There's a little cellular automaton doing its computation. And the principle of computational equivalence says, these two computations are fundamentally equivalent. So that means we don't get to say, we're a lot smarter than the cellular automaton and jump ahead because we're just doing computation that's of the same sophistication as the cellular automaton itself. That's computational reducibility. It's fascinating. And that's a really powerful idea. I think that's both depressing and humbling and so on, that we're all, we and the cellular automaton are the same. But the question we're talking about, the fundamental laws of physics, is kind of the reverse question. You're not predicting what's gonna happen. You have to run the universe for that. But saying, can I understand what rules likely generated me? I understand. But the problem is to know whether you're right, you have to have some computational reducibility because we are embedded in the universe. If the only way to know whether we get the universe is just to run the universe, we don't get to do that because it just ran for 14.6 billion years or whatever. And we can't rerun it, so to speak. So we have to hope that there are pockets of computational reducibility sufficient to be able to say, yes, I can recognize those are electrons there. And I think that it's a feature of computational irreducibility. It's sort of a mathematical feature that there are always an infinite collection of pockets of reducibility. The question of whether they land in the right place and whether we can sort of build a theory based on them is unclear. But to this point about whether we, as observers in the universe, built out of the same stuff as the universe, can figure out the universe, so to speak, that relies on these pockets of reducibility. Without the pockets of reducibility, it won't work, can't work. But I think this question about how observers operate, it's one of the features of science over the last hundred years particularly, has been that every time we get more realistic about observers, we learn a bit more about science. So for example, relativity was all about observers don't get to say when, what's simultaneous with what. They have to just wait for the light signal to arrive to decide what's simultaneous. Or for example, in thermodynamics, observers don't get to say the position of every single molecule in a gas. They can only see the kind of large scale features and that's why the second law of thermodynamics, law of entropy increase and so on works. If you could see every individual molecule, you wouldn't conclude something about thermodynamics. You would conclude, oh, these molecules are just all doing these particular things. You wouldn't be able to see this aggregate fact. So I strongly expect that, and in fact in the theories that I have, that one has to be more realistic about the computation and other aspects of observers in order to actually make a correspondence between what we experience. In fact, my little team and I have a little theory right now about how quantum mechanics may work, which is a very wonderfully bizarre idea about how the sort of thread of human consciousness relates to what we observe in the universe. But there's several steps to explain what that's about. What do you make of the mess of the observer at the lower level of quantum mechanics? Sort of the textbook definition with quantum mechanics kind of says that there's two worlds. One is the world that actually is and the other is that's observed. What do you make sense of that kind of observing? Well, I think actually the ideas we've recently had might actually give away into this. And that's, I don't know yet. I mean, I think that's, it's a mess. I mean, the fact is there is a, one of the things that's interesting and when people look at these models that I started talking about 30 years ago now, they say, oh no, that can't possibly be right. What about quantum mechanics? You say, okay, tell me what is the essence of quantum mechanics? What do you want me to be able to reproduce to know that I've got quantum mechanics, so to speak? Well, and that question comes up, comes up very operationally actually because we've been doing a bunch of stuff with quantum computing. And there are all these companies that say, we have a quantum computer. We say, let's connect to your API and let's actually run it. And they're like, well, maybe you shouldn't do that yet. We're not quite ready yet. And one of the questions that I've been curious about is if I have five minutes with a quantum computer, how can I tell if it's really a quantum computer or whether it's a simulator at the other end? Right, and turns out it's really hard. It turns out there isn't, it's like a lot of these questions about sort of what is intelligence, what's life. It's- That's a boring test for quantum computing. That's right, that's right. It's like, are you really a quantum computer? And I think- Or just a simulation, yeah. Yes, exactly. Is it just a simulation or is it really a quantum computer? The same issue all over again. But that, so, you know, this whole issue about the sort of mathematical structure of quantum mechanics and the completely separate thing that is our experience in which we think definite things happen, whereas quantum mechanics doesn't say definite things ever happen. Quantum mechanics is all about the amplitudes for different things to happen. But yet our thread of consciousness operates as if definite things are happening. But to linger on the point, you've kind of mentioned the structure that could underlie everything and this idea that it could perhaps have something like a structure of a graph. Can you elaborate why your intuition is that there's a graph structure of nodes and edges and what it might represent? Right, okay, so the question is, what is, in a sense, the most structuralist structure you can imagine, right? So, and in fact, what I've recently realized in the last year or so, I have a new most structuralist structure. By the way, the question itself is a beautiful one and a powerful one in itself. So even without an answer, just the question is a really strong question. Right, right. But what's your new idea? Well, it has to do with hypergraphs. Essentially, what is interesting about the sort of model I have now is it's a little bit like what happened with computation. Everything that I think of as, oh, well, maybe the model is this, I discover it's equivalent. And that's quite encouraging because it's like, I could say, well, I'm gonna look at trivalent graphs with three edges for each node and so on. Or I could look at this special kind of graph. Or I could look at this kind of algebraic structure. And turns out that the things I'm now looking at, everything that I've imagined that is a plausible type of structuralist structure is equivalent to this. So what is it? Well, a typical way to think about it is, well, so you might have some collection of tuples, collection of, let's say numbers. So you might have one, three, five, two, three, four, little, just collections of numbers, triples of numbers, let's say, quadruples of numbers, pairs of numbers, whatever. And you have all these sort of floating little tuples. They're not in any particular order. And that sort of floating collection of tuples, and I told you this was abstract, represents the whole universe. The only thing that relates them is when a symbol is the same, it's the same, so to speak. So if you have two tuples and they contain the same symbol, let's say at the same position of the tuple, the first element of the tuple, then that represents a relation. Okay, so let me try and peel this back. Wow, okay. It's, I told you it's abstract, but this is the, So the relationship is formed by the same, some aspect of sameness. Right, but so think about it in terms of a graph. So a graph, a bunch of nodes, let's say you number each node, okay? Then what is a graph? A graph is a set of pairs that say, this node has an edge connecting it to this other node. So that's the, that's, and a graph is just a collection of those pairs that say this node connects to this other node. So this is a generalization of that, in which instead of having pairs, you have arbitrary and tuples. That's it, that's the whole story. And now the question is, okay, so that might be, that might represent the state of the universe. How does the universe evolve? What does the universe do? And so the answer is that what I'm looking at is transformation rules on these hypergraphs. In other words, you say this, whenever you see a piece of this hypergraph that looks like this, turn it into a piece of a hypergraph that looks like this. So on a graph, it might be, when you see the subgraph, when you see this thing with a bunch of edges hanging out in this particular way, then rewrite it as this other graph, okay? And so that's the whole story. So the question is what, so now you say, I mean, as I say, this is quite abstract. And one of the questions is, where do you do those updating? So you've got this giant graph. What triggers the updating? Like what's the ripple effect of it? Is it? Yeah, and I suspect everything's discrete even in time. So, okay, so the question is where do you do the updates? And the answer is, the rule is you do them wherever they apply. And you do them, the order in which the updates is done is not defined. That is that you can do them. So there may be many possible orderings for these updates. Now, the point is, imagine you're an observer in this universe. So, and you say, did something get updated? Well, you don't in any sense know until you yourself have been updated. Right. So in fact, all that you can be sensitive to is essentially the causal network of how an event over there affects an event that's in you. That doesn't even feel like observation. That's like, that's something else. You're just part of the whole thing. Yes, you're part of it, but even to have, so the end result of that is all you're sensitive to is this causal network of what event affects what other event. I'm not making a big statement about sort of the structure of the observer. I'm simply saying, I'm simply making the argument that what happens, the microscopic order of these rewrites is not something that any observer, any conceivable observer in this universe can be affected by. Because the only thing the observer can be affected by is this causal network of how the events in the observer are affected by other events that happen in the universe. So the only thing you have to look at is the causal network. You don't really have to look at this microscopic rewriting that's happening. So these rewrites are happening wherever they, they happen wherever they feel like. Causal network, is there, you said that there's not really, so the idea would be an undefined, like what gets updated, the sequence of things is undefined. Yes. That's what you mean by the causal network, but then the causal- No, the causal network is given that an update has happened, that's an event. Then the question is, is that event causally related to? Does that event, if that event didn't happen, then some future event couldn't happen yet. Gotcha. And so you build up this network of what affects what. Okay? And so what that does, so when you build up that network, that's kind of the observable aspect of the universe in some sense. Gotcha. And so then you can ask questions about, you know, how robust is that observable network of what's happening in the universe? Okay, so here's where it starts getting kind of interesting. So for certain kinds of microscopic rewriting rules, the order of rewrites does not matter to the causal network. And so this is, okay, mathematical logic moment, this is equivalent to the Church-Rossa property or the confluence property of rewrite rules. And it's the same reason that if you are simplifying an algebraic expression, for example, you can say, oh, let me expand those terms out, let me factor those pieces. Doesn't matter what order you do that in, you'll always get the same answer. And that's, it's the same fundamental phenomenon that causes for certain kinds of microscopic rewrite rules that causes the causal network to be independent of the microscopic order of rewritings. Why is that property important? Because it implies special relativity. I mean, the reason it's important is that that property, special relativity says you can look at these sort of, you can look at different reference frames. You can have different, you can be looking at your notion of what space and what's time can be different, depending on whether you're traveling at a certain speed, depending on whether you're doing this, that and the other. But nevertheless, the laws of physics are the same. That's what the principle of special relativity says, is laws of physics are the same, independent of your reference frame. Well, turns out this sort of change of the microscopic rewriting order is essentially equivalent to a change of reference frame, or at least there's a sub part of how that works that's equivalent to change of reference frame. So, somewhat surprisingly, and sort of for the first time in forever, it's possible for an underlying microscopic theory to imply special relativity, to be able to derive it. It's not something you put in as a, this is a, it's something where this other property, causal invariance, which is also the property that implies that there's a single thread of time in the universe. It might not be the case. That's what would lead to the possibility of an observer thinking that definite stuff happens. Otherwise, you've got all these possible rewriting orders, and who's to say which one occurred. But with this causal invariance property, there's a notion of a definite thread of time. It sounds like that kind of idea of time, even space, would be emergent from the system. Oh yeah, no, I mean- So it's not a fundamental part of the system. No, no, at a fundamental level, all you've got is a bunch of nodes connected by hyper edges or whatever. So there's no time, there's no space. That's right. But the thing is that it's just like imagining, imagine you're just dealing with a graph, and imagine you have something like a honeycomb graph, or you have a bunch of hexagons. That graph at a microscopic level, it's just a bunch of nodes connected to other nodes. But at a macroscopic level, you say that looks like a honeycomb lattice. It looks like a two-dimensional manifold of some kind. It looks like a two-dimensional thing. If you connect it differently, if you just connect all the nodes one to another, and kind of a sort of linked list type structure, then you'd say, well, that looks like a one-dimensional space. But at the microscopic level, all these are just networks with nodes. The macroscopic level, they look like something that's like one of our sort of familiar kinds of space. And it's the same thing with these hyper graphs. Now, if you ask me, have I found one that gives me three-dimensional space? The answer is not yet. So we don't know if this is one of these things we're kind of betting against nature, so to speak. And I have no way to know. So there are many other properties of this kind of system that have a very beautiful actually, and very suggestive, and it will be very elegant if this turns out to be right, because it's very clean. I mean, you start with nothing, and everything gets built up. Everything about space, everything about time, everything about matter, it's all just emergent from the properties of this extremely low-level system. And that will be pretty cool if that's the way our universe works. Now, do I, on the other hand, the thing that I find very confusing is, let's say we succeed. Let's say we can say this particular sort of hypergraph rewriting rule gives the universe. Just run that hypergraph rewriting rule for enough times, and you'll get everything. You'll get this conversation we're having. You'll get everything. It's that, if we get to that point, and we look at what is this thing, what is this rule that we just have that is giving us our whole universe? How do we think about that thing? Let's say, turns out the minimal version of this, and this is kind of a cool thing for a language designer like me, the minimal version of this model is actually a single line of orphan language code. So that's, which I wasn't sure was gonna happen that way, but it's, it's a, that's, it's kind of, no, we don't know what, we don't know what, that's, that's just the framework to know the actual particular hypergraph that might be a longer, that the specification of the rules might be slightly longer. How does that help you accept marveling in the beauty and the elegance of the simplicity that creates the universe? That does that help us predict anything? Not really, because of the irreducibility. That's correct, that's correct. But so, the thing that is really strange to me, and I haven't wrapped my brain around this yet, is, you know, one is, one keeps on realizing that we're not special, in the sense that, you know, we don't live at the center of the universe, we don't blah, blah, blah, and yet, if we produce a rule for the universe, and it's quite simple, and we can write it down in a couple of lines or something, that feels very special. How did we come to get a simple universe, when many of the available universes, so to speak, are incredibly complicated? Might be, you know, a quintillion characters long. Why did we get one of the ones that's simple? And so, I haven't wrapped my brain around that issue yet. If indeed, we are in such a simple, the universe is such a simple rule, is it possible that there is something outside of this, that we are in a kind of what people call the simulation, right? That we're just part of a computation that's being explored by a graduate student in an alternate universe? Well, you know, the problem is, we don't get to say much about what's outside our universe, because by definition, our universe is what we exist within. Now, can we make a sort of almost theological conclusion from being able to know how our particular universe works? Interesting question. I don't think that, if you ask the question, could we, and it relates again to this question about extraterrestrial intelligence, you know, we've got the rule for the universe. Was it built in on purpose? Hard to say. That's the same thing as saying, we see a signal from, you know, that we're receiving from some random star somewhere, and it's a series of pulses, and it's a periodic series of pulses, let's say. Was that done on purpose? Can we conclude something about the origin of that series of pulses? Just because it's elegant does not necessarily mean that somebody created it, or that we can even comprehend what would create it. Yeah, I think it's the ultimate version of the sort of identification of the techno signature question, it's the ultimate version of that, is was our universe a piece of technology, so to speak, and how on earth would we know? Because, but I mean, it'll be, it's, I mean, you know, in the kind of crazy science fiction thing you could imagine, you could say, oh, somebody's going to have, you know, there's going to be a signature there, it's going to be, you know, made by so-and-so, but there's no way we could understand that, so to speak, and it's not clear what that would mean, because the universe simply, you know, this, if we find a rule for the universe, we're not, we're simply saying that rule represents what our universe does. We're not saying that that rule is something running on a big computer and making our universe, it's just saying that represents what our universe does, in the same sense that, you know, laws of classical mechanics, differential equations, whatever they are, represent what mechanical systems do. It's not that the mechanical systems are somehow running solutions to those differential equations. Those differential equations are just representing the behavior of those systems. So what's the gap, in your sense, to linger on the fascinating, perhaps slightly sci-fi question? What's the gap between understanding the fundamental rules that create a universe and engineering a system, actually creating a simulation ourselves? So you've talked about, sort of, you've talked about, you know, nanoengineering, kind of ideas that are kind of exciting, actually creating some ideas of computation in the physical space. How hard is it, as an engineering problem, to create the universe once you know the rules that create it? Well, that's an interesting question. I think the substrate on which the universe is operating is not a substrate that we have access to. I mean, the only substrate we have is that same substrate that the universe is operating in. So if the universe is a bunch of hypergraphs being rewritten, then we get to attach ourselves to those same hypergraphs being rewritten. We don't get to, and if you ask the question, you know, is the code clean? You know, can we write nice, elegant code with efficient algorithms and so on? Well, that's an interesting question. How, you know, that's this question of how much computational reducibility there is in the system. But, so I've seen some beautiful cellular automata that basically create copies of itself within itself, right? So that's the question, whether it's possible to create, like whether you need to understand the substrate or whether you can just- Yeah, well, right. I mean, so one of the things that is sort of one of my slightly sci-fi thoughts about the future, so to speak, is, you know, right now, if you poll typical people, you say, do you think it's important to find the fundamental theory of physics? You get, because I've done this poll, informally at least, it's curious, actually, you get a decent fraction of people saying, oh yeah, that would be pretty interesting. I think that's becoming, surprisingly enough, more, I mean, a lot of people are interested in physics in a way that, like without understanding it, just kind of watching scientists, a very small number of them, struggle to understand the nature of our reality. Right, I mean, I think that's somewhat true, and in fact, in this project that I'm launching into to try and find the fundamental theory of physics, I'm going to do it as a very public project. I mean, it's gonna be live-streamed and all this kind of stuff, and I don't know what will happen. It'll be kind of fun. I mean, I think that it's the interface to the world of this project. I mean, I figure one feature of this project is, you know, unlike technology projects that basically are what they are, this is a project that might simply fail, because it might be the case that it generates all kinds of elegant mathematics that has absolutely nothing to do with the physical universe that we happen to live in. Well, okay, so we're talking about kind of the quest to find the fundamental theory of physics. First point is, you know, it's turned out it's kind of hard to find the fundamental theory of physics. People weren't sure that that would be the case. Back in the early days of applying mathematics to science, 1600s and so on, people were like, oh, in 100 years, we'll know everything there is to know about how the universe works. Turned out to be harder than that, and people got kind of humble at some level, because every time we got to sort of a greater level of smallness in studying the universe, it seemed like the math got more complicated and everything got harder. The, you know, when I was a kid, basically, I started doing particle physics, and, you know, when I was doing particle physics, I always thought finding the fundamental, fundamental theory of physics, that's a kooky business, we'll never be able to do that. But we can operate within these frameworks that we built for doing quantum field theory and general relativity and things like this, and it's all good, and we can figure out a lot of stuff. Did you even at that time have a sense that there's something behind that too? Sure, I just didn't expect that. I thought in some rather un, it's actually kind of crazy thinking back on it, because it's kind of like there was this long period in civilization where people thought the ancients had it all figured out and will never figure out anything new. And to some extent, that's the way I felt about physics when I was in the middle of doing it, so to speak, was, you know, we've got quantum field theory, it's the foundation of what we're doing. And there's, you know, yes, there's probably something underneath this, but we'll sort of never figure it out. But then I started studying simple programs in the computational universe, things like cellular automata and so on. And I discovered that there's, they do all kinds of things that were completely at odds with the intuition that I had had. And so after that, after you see this tiny little program that does all this amazingly complicated stuff, then you start feeling a bit more ambitious about physics and saying, maybe we could do this for physics too. And so that's, that got me started years ago now in this kind of idea of could we actually find what's underneath all of these frameworks like quantum field theory, general relativity and so on. And people perhaps don't realize as clearly as they might that, you know, the frameworks we're using for physics, which is basically these two things, quantum field theory, sort of the theory of small stuff and general relativity, theory of gravitation and large stuff. Those are the two basic theories and they're a hundred years old. I mean, general relativity was 1915, quantum field theory, well, 1920s. So basically a hundred years old. And it's been a good run. There's a lot of stuff been figured out. But what's interesting is the foundations haven't changed in all that period of time, even though the foundations had changed several times before that in the 200 years earlier than that. And I think the kinds of things that I'm thinking about, which are sort of really informed by thinking about computation and the computational universe, it's a different foundation. It's a different set of foundations and might be wrong, but it is at least, you know, we have a shot. And I think it's, you know, to me, it's, you know, my personal calculation for myself is, you know, if it turns out that the finding the fundamental theory of physics, it's kind of low hanging fruit, so to speak, it'd be a shame if we just didn't think to do it. You know, if people just said, oh, you'll never figure that stuff out. Let's, you know, and it takes another 200 years before anybody gets around to doing it. You know, I think it's, I don't know how low hanging this fruit actually is. It may be, you know, it may be that it's kind of the wrong century to do this project. I mean, I think the cautionary tale for me, you know, I think about things that I've tried to do in technology where people thought about doing them a lot earlier. My favorite example is probably Leibniz who thought about making essentially encapsulating the world's knowledge in a computational form in the late 1600s. And did a lot of things towards that. And basically, you know, we finally managed to do this, but he was 300 years too early. And that's the, that's kind of the, in terms of life planning, it's kind of like avoid things that can't be done in your century, so to speak. Yeah, timing, timing is everything. So you think if we kind of figure out the underlying rules that can create from which quantum field theory and general relativity can emerge, do you think that'll help us unify it at that level of abstraction? Oh, we'll know it completely. We'll know how that all fits together. Yes, without a question. And I mean, it's already, even the things I've already done, they're very, you know, it's very, very elegant actually. How things seem to be fitting together. Now, you know, is it right? I don't know yet. It's awfully suggestive. If it isn't right, it's, then the designer of the universe should feel embarrassed, so to speak, because it's a really good way to do it. And your intuition in terms of design universe, does God play dice? Is there randomness in this thing? Or is it deterministic? So the kind of graph- That's a little bit of a complicated question, because when you're dealing with these things that involve these rewrites that have, okay. Even randomness is an emergent phenomenon perhaps? Yes, yes. I mean, it's a, yeah, well, randomness, in many of these systems, pseudo-randomness and randomness are hard to distinguish. In this particular case, the current idea that we have about measurement in quantum mechanics is something very bizarre and very abstract. And I don't think I can yet explain it without kind of yakking about very technical things. Eventually I will be able to, but if that's right, it's kind of a, it's a weird thing, because it slices between determinism and randomness in a weird way that hasn't been sliced before, so to speak. So like many of these questions that come up in science, where it's like, is it this or is it that? Turns out the real answer is it's neither of those things. It's something kind of different and sort of orthogonal to those categories. And so that's the current, you know, this week's idea about how that might work. But, you know, we'll see how that unfolds. I mean, there's this question about a field like physics and sort of the quest for a fundamental theory and so on. And there's both the science of what happens and there's the sort of the social aspect of what happens. Because, you know, in a field that is basically as old as physics, we're at, I don't know what it is, fourth generation, I don't know, fifth generation, I don't know what generation it is of physicists. And like, I was one of these, so to speak. And for me, the foundations were like the pyramids, so to speak, you know, it was that way and it was always that way. It is difficult in an old field to go back to the foundations and think about rewriting them. It's a lot easier in young fields where you're still dealing with the first generation of people who invented the field. And it tends to be the case, you know, that the nature of what happens in science tends to be, you know, you'll get, typically the pattern is some methodological advance occurs and then there's a period of five years, 10 years, maybe a little bit longer than that, where there's lots of things that are now made possible by that methodological advance, whether it's, you know, I don't know, telescopes or whether that's some mathematical method or something. It's, you know, there's a, something happens, a tool gets built and then you can do a bunch of stuff and there's a bunch of low hanging fruit to be picked and that takes a certain amount of time. After that, all that low hanging fruit is picked, then it's a hard slog for the next however many decades or century or more to get to the next sort of level at which one can do something. And it's kind of a, and it tends to be the case that in fields that are in that kind of, I wouldn't say cruise mode, cause it's really hard work, but it's very hard work for very incremental progress. And in your career and some of the things you've taken on, it feels like you're not, you haven't been afraid of the hard slog. Yeah, that's true. So it's quite interesting, especially on the engineering side. On a small tangent, when you were at Caltech, did you get to interact with Richard Feynman at all? Do you have any memories of Richard? We worked together quite a bit actually. In fact, and in fact, both when I was at Caltech and after I left Caltech, we were both consultants at this company called Thinking Machines Corporation, which was just down the street from here actually, as ultimately ill-fated company. But I used to say, this company is not gonna work with the strategy they have. And Dick Feynman always used to say, what do we know about running companies? Just let them run their company. But anyway, he was not into that kind of thing. And he always thought that my interest in doing things like running companies was a distraction, so to speak. And for me, it's a mechanism to have a more effective machine for actually figuring things out and getting things to happen. Did he think of it, because essentially what you did with the company, I don't know if you were thinking of it that way, but you're creating tools to empower the exploration of the university. Do you think, did he? Did he understand that point? The point of tools of- I think not as well as he might've done. I mean, I think that, but he was actually my first company, which was also involved with, well, was involved with more mathematical computation kinds of things. He was quite, he had lots of advice about the technical side of what we should do and so on. Do you have examples, memories, or thoughts that- Oh yeah, yeah, he had all kinds of, look, in the business of doing sort of, one of the hard things in math is doing integrals and so on, right? And so he had his own elaborate ways to do integrals and so on. He had his own ways of thinking about sort of getting intuition about how math works. And so his sort of meta idea was take those intuitional methods and make a computer follow those intuitional methods. Now it turns out for the most part, like when we do integrals and things, what we do is we build this kind of bizarre industrial machine that turns every integral into products of major G functions and generates this very elaborate thing. And actually the big problem is turning the results into something a human will understand. It's not, quote, doing the integral. And actually Feynman did understand that to some extent. And I'm embarrassed to say, he once gave me this big pile of calculational methods for particle physics that he worked out in the fifties. And he said, yeah, it's more used to you than to me type thing. And I was like, I've intended to look at it and give it back. And I still have my files now. So it's, but that's what happens when it's finiteness of human lives. It's, I, you know, maybe if he'd lived another 20 years, I would have remembered to give it back. But I think it's, you know, that was his attempt to systematize the ways that one does integrals that show up in particle physics and so on. Turns out the way we've actually done it is very different from that way. What do you make of that difference, Zitin? So Feynman was actually quite remarkable at creating sort of intuitive, like diving in, you know, creating intuitive frameworks for understanding difficult concepts. Is- I'm smiling because, you know, the funny thing about him was that the thing he was really, really, really good at is calculating stuff. And, but he thought that was easy because he was really good at it. And so he would do these things where he would calculate some, do some complicated calculation in quantum field theory, for example, come out with a result. Wouldn't tell anybody about the complicated calculation because he thought that was easy. He thought the really impressive thing was to have the simple intuition about how everything works. So he invented that at the end. And, you know, because he'd done this calculation and knew how it worked, it was a lot easier. It's a lot easier to have good intuition when you know what the answer is. And then he would just not tell anybody about these calculations. And he wasn't meaning that maliciously, so to speak. It's just, he thought that was easy. And, and that's, you know, that led to areas where people were just completely mystified and they kind of followed his intuition, but nobody could tell why it worked because actually the reason it worked was because he'd done all these calculations and he knew that it was, would work. And, you know, when I, he and I worked a bit on quantum computers, actually back in 1980, 81, before anybody had heard of those things. And, you know, the typical mode of, I mean, he always used to say, and I now think about this because I'm about the age that he was when I worked with him. And, you know, I see that people who are one third my age, so to speak. And he was always complaining that I was one third his age. And therefore, various things. But, but, you know, he would do some calculation by hand, you know, on blackboard and things, come up with some answer. I'd say, I don't understand this. You know, I do something with a computer. And he'd say, you know, I don't understand this. So there'd be some big argument about what was, you know, what was going on. But, but it was always, and I think actually many of the things that we sort of realized about quantum computing, that was sort of issues that have to do particularly with the measurement process, are kind of still issues today. And I kind of find it interesting. It's a funny thing in science that these, you know, that there's a remarkable, it happens in technology too, there's a remarkable sort of repetition of history that ends up occurring. Eventually things really get nailed down, but it often takes a while and it often things come back decades later. Well, for example, I could tell a story actually happened right down the street from here. When we were both at thinking machines, I had been working on this particular cellular automaton called Rule 30, that has this feature that it from very simple initial conditions, it makes really complicated behavior. Okay. So, and actually of all silly physical things using this big parallel computer called the connection machine that that company was making, I generated this giant printout of Rule 30 on very, on actually on the same kind of printer that people use to make layouts for microprocessors. So one of these big, you know, large format printers with high resolution and so on. So, okay, so print this out lots of very tiny cells. And so there was sort of a question of how some features of that pattern. And so it was very much a physical, you know, on the floor with meter rules trying to measure different things. So, so Feynman kind of takes me aside, we've been doing that for a little while and takes me aside and he says, I just wanna know this one thing. He says, I wanna know, how did you know that this Rule 30 thing would produce all this really complicated behavior that is so complicated that we're, you know, going around with this big printout and so on. And I said, well, I didn't know. I just enumerated all the possible rules and then observed that that's what happened. He said, oh, I feel a lot better. You know, I thought you had some intuition that he didn't have that would let one. I said, no, no, no, no intuition, just experimental science. So that's such a beautiful sort of dichotomy there of that's exactly what you showed is you really can't have an intuition about and the reducible, I mean, you have to run it. Yes, that's right. That's so hard for us humans and especially brilliant physicists like Feynman to say that you can't have a compressed, clean intuition about how the whole thing works. Yes, yes. No, he was, I mean, I think he was sort of on the edge of understanding that point about computation. And I think he found that, I think he always found computation interesting. And I think that was sort of what he was a little bit poking at. I mean, that intuition, you know, the difficulty of discovering things like even you say, oh, you know, you just enumerate all the cases and just find one that does something interesting, right? Sounds very easy. Turns out like I missed it when I first saw it because I had kind of an intuition that said it shouldn't be there. And so I had kind of arguments, oh, I'm gonna ignore that case because whatever. And- How did you have an open mind enough? Because you're essentially the same person as Richard Feynman, like the same kind of physics type of thinking. How did you find yourself having a sufficiently open mind to be open to watching rules and them revealing complexity? Yeah, I think that's an interesting question. I've wondered about that myself because it's kind of like, you know, you live through these things and then you say, what was the historical story? And sometimes the historical story that you realize after the fact was not what you lived through, so to speak. And so, you know, what I realized is I think what happened is, you know, I did physics kind of like reductionistic physics where you're throwing the universe and you're told go figure out what's going on inside it. And then I started building computer tools and I started building my first computer language, for example. And computer language is not like, it's sort of like physics in the sense that you have to take all those computations people want to do and kind of drill down and find the primitives that they can all be made of. But then you do something that's really different because you're just saying, okay, these are the primitives. Now, you know, hopefully they'll be useful to people. Let's build up from there. So you're essentially building an artificial universe in a sense where you make this language, you've got these primitives, you're just building whatever you feel like building. And that's, and so it was sort of interesting for me because from doing science where you're just throwing the universe as the universe is to then just being told, you know, you can make up any universe you want. And so I think that experience of making a computer language which is essentially building your own universe, so to speak, is, you know, that's kind of the, that's what gave me a somewhat different attitude towards what might be possible. It's like, let's just explore what can be done in these artificial universes rather than thinking the natural science way of let's be constrained by how the universe actually is. Yeah, by being able to program, essentially you've, as opposed to being limited to just your mind and a pen, you now have, you've basically built another brain that you can use to explore the universe by, you know, computer program, you know, is a kind of a brain. Right, and it's, well, it's, or a telescope, or, you know, it's a tool. It lets you see stuff. But there's something fundamentally different between a computer and a telescope. I mean, it just, I'm hoping not to romanticize the notion, but it's more general, the computer is more general than a telescope. And it's, I think, I mean, this point about, you know, people say, oh, such and such a thing was almost discovered at such and such a time. The distance between, you know, the building the paradigm that allows you to actually understand stuff, or allows one to be open to seeing what's going on, that's really hard. And, you know, I think in, I've been fortunate in my life that I've spent a lot of my time building computational language. And that's an activity that in a sense works by sort of having to kind of create another level of abstraction and kind of be open to different kinds of structures. But, you know, it's always, I mean, I'm fully aware of, I suppose, the fact that I have seen it a bunch of times of how easy it is to miss the obvious, so to speak. That at least is factored into my attempt to not miss the obvious, although it may not succeed. What do you think is the role of ego in the history of math and science? And more sort of, you know, a book title of something like A New Kind of Science, you've accomplished a huge amount. And in fact, somebody said that Newton didn't have an ego, and I looked into it and he had a huge ego. But from an outsider's perspective, some have said that you have a bit of an ego as well. Do you see it that way? Does ego get in the way? Is it empowering? Is it both sort of? It's complicated and unnecessary. I mean, you know, I've had, look, I've spent more than half my life CEO-ing a tech company. Right. Okay, and, you know, that is a, I think it's actually very, it means that one's ego is not a distant thing. It's a thing that one encounters every day, so to speak, because it's all tied up with leadership and with how one, you know, develops an organization and all these kinds of things. So, you know, it may be that if I'd been an academic, for example, I could have sort of, you know, checked the ego, put it on a shelf somewhere and ignored its characteristics. But you're reminded of it quite often in the context of running a company. Sure, I mean, that's what it's about. It's about leadership and, you know, leadership is intimately tied to ego. Now, what does it mean? I mean, what is the, you know, for me, I've been fortunate that I think I have reasonable intellectual confidence, so to speak. That is, you know, I'm one of these people who at this point, if somebody tells me something and I just don't understand it, my conclusion isn't that means I'm dumb, that my conclusion is there's something wrong with what I'm being told. And that was actually Dick Feynman used to have that feature too, he never really believed in. He actually believed in experts much less than I believe in experts. So. Wow, so that's a fundamentally powerful property of ego and saying like, not that I am wrong, but that the world is wrong and telling me, like when confronted with the fact that doesn't fit the thing that you've really thought through, sort of both the negative and the positive of ego, do you see the negative of that get in the way? Sort of being confronted with. Sure, there are mistakes I've made that are the result of I'm pretty sure I'm right and turns out I'm not. I mean, that's the, you know, but the thing is that the idea that one tries to do things that, so for example, you know, one question is, if people have tried hard to do something and then one thinks, maybe I should try doing this myself, if one does not have a certain degree of intellectual confidence, one just says, well, people have been trying to do this for 100 years, how am I gonna be able to do this? And, you know, I was fortunate in the sense that I happened to start having some degree of success in science and things when I was really young and so that developed a certain amount of sort of intellectual confidence that I don't think I otherwise would have had. And, you know, in a sense, I mean, I was fortunate that I was working in a field, particle physics, during its sort of golden age of rapid progress and that kind of gives one a false sense of achievement because it's kind of easy to discover stuff that's gonna survive if you happen to be, you know, picking the low-hanging fruit of a rapidly expanding field. I mean, the reason I totally immediately understood the ego behind a new kind of science, to me, let me sort of just try to express my feelings on the whole thing, is that if you don't allow that kind of ego, then you would never write that book, that you would say, well, people must have done this, there's not, you would not dig, you would not keep digging. And I think that was, I think you have to take that ego and ride it and see where it takes you. And that's how you create exceptional work. But I think the other point about that book was, it was a non-trivial question, how to take a bunch of ideas that are, I think, reasonably big ideas, they might, you know, their importance is determined by what happens historically. One can't tell how important they are, one can tell sort of the scope of them. And the scope is fairly big and they're very different from things that have come before. And the question is, how do you explain that stuff to people? And so I had had the experience of sort of saying, well, there are these things, there's a cellular automaton, it does this, it does that. And people are like, oh, it must be just like this, it must be just like that. I said, no, it isn't, it's something different, right? And so I could have done sort of, I'm really glad you did what you did, but you could have done sort of academically, just publish, keep publishing small papers here and there, and then you would just keep getting this kind of resistance, right? You would get like, it's supposed to just dropping a thing that says, here it is, here's the full thing. No, I mean, that was my calculation, is that basically, you could introduce little pieces, it's like, one possibility is like, it's the secret weapon, so to speak. It's this, I keep on discovering these things in all these different areas, where'd they come from? Nobody knows. But I decided that in the interests of one only has one life to lead, and writing that book took me a decade anyway, there's not a lot of wiggle room, so to speak, one can't be wrong by a factor of three, so to speak, and how long it's gonna take. That I thought the best thing to do, the thing that is most sort of, that most respects the intellectual content, so to speak, is you just put it out with as much force as you can, because it's not something where, and it's an interesting thing, you talk about ego, and it's, for example, I run a company which has my name on it, right? I thought about starting a club for people whose companies have their names on them, and it's a funny group, because we're not a bunch of egomaniacs, that's not what it's about, so to speak, it's about basically sort of taking responsibility for what one's doing, and in a sense, any of these things where you're sort of putting yourself on the line, it's kind of a funny, it's a funny dynamic, because in a sense, my company is sort of something that happens to have my name on it, but it's kind of bigger than me, and I'm kind of just its mascot at some level. I mean, I also happen to be a pretty strong leader of it, but- But it's basically showing a deep, inextricable sort of investment, the same, your name, like Steve Jobs' name wasn't on Apple, but he was Apple. Elon Musk's name is not on Tesla, but he is Tesla, so it's like, meaning emotionally, is if a company succeeds or fails, he would just, that emotionally, he would suffer through that, and so that's- Yeah, it's recognizing that fact. And also, Wolfram's a pretty good branding name, so it works out. Yeah, right, exactly. I think Steve had a bad deal there. Yeah, so you made up for it with the last name. Okay, so in 2002, you published a new kind of science, to which, sort of on a personal level, I can credit my love for cellular automaton and computation in general. I think a lot of others can as well. Can you briefly describe the vision, the hope, the main idea presented in this 1,200-page book? Sure, although it took 1,200 pages to say in the book, so no, the real idea, it's kind of, a good way to get into it is to look at sort of the arc of history and to look at what's happened in kind of the development of science. I mean, there was this sort of big idea in science about 300 years ago that was, let's use mathematical equations to try and describe things in the world. Let's use sort of the formal idea of mathematical equations to describe what might be happening in the world, rather than, for example, just using sort of logical argumentation and so on. Let's have a formal theory about that. And so there'd been this 300-year run of using mathematical equations to describe the natural world, which had worked pretty well. But I got interested in how one could generalize that notion, you know, there is a formal theory, there are definite rules, but what structure could those rules have? And so what I got interested in was, let's generalize beyond the sort of purely mathematical rules, and we now have this sort of notion of programming and computing and so on. Let's use the kinds of rules that can be embodied in programs to, as a sort of generalization of the ones that can exist in mathematics as a way to describe the world. And so my kind of favorite version of these kinds of simple rules are these things called cellular automata. And so a typical case- So wait, what are cellular automata? Fair enough. So typical case of a cellular automaton, it's an array of cells. It's just a line of discrete cells. Each cell is either black or white. And in a series of steps that you can represent as lines going down a page, you're updating the color of each cell according to a rule that depends on the color of the cell above it and to its left and right. So it's really simple. So a thing might be, you know, if the cell and its right neighbor are not the same, and, or the cell on the left is black or something, then make it black on the next step. And if not, make it white. Typical rule. That rule, I'm not sure I said it exactly right, but a rule very much like what I just said has the feature that if you started off from just one black cell at the top, it makes this extremely complicated pattern. So some rules, you get a very simple pattern. Some rules, you have, the rule is simple. You start them off from a sort of simple seed. You just get this very simple pattern. But other rules, and this was the big surprise when I started actually just doing the simple computer experiments to find out what happens, is that they produce very complicated patterns of behavior. So for example, this rule 30 rule has the feature you started off from just one black cell at the top, makes this very random pattern. If you look like at the center column of cells, you get a series of values, you know, it goes black, white, black, black, whatever it is. That sequence seems for all practical purposes random. So it's kind of like in math, you know, you compute the digits of pi, 3.1415926, whatever. Those digits once computed, I mean, the scheme for computing pi, you know, it's the ratio of the circumference diameter of a circle, very well-defined, but yet when you are, once you've generated those digits, they seem for all practical purposes completely random. And so it is with rule 30, that even though the rule is very simple, much simpler, much more sort of computationally obvious than the rule for generating digits of pi, even with a rule that simple, you're still generating immensely complicated behavior. Yeah, so if we could just pause on that, I think you probably have said it and looked at it so long, you forgot the magic of it, or perhaps you don't, you still feel the magic. But to me, if you've never seen sort of, I would say, what is it? A one-dimensional, essentially, cellular automata, right? And you were to guess what you would see if you have some, so cells that only respond to its neighbors. Right. If you were to guess what kind of things you would see, like my initial guess, like even when I first opened your book, A New Kind of Science, right? My initial guess is you would see, I mean, it would be very simple stuff. Right. And I think it's a magical experience to realize the kind of complexity, you mentioned rule 30, still your favorite cellular automaton? Still my favorite rule, yes. You get complexity, immense complexity. You get arbitrary complexity. Yes. And when you say randomness down the middle column, that's just one cool way to say that there's incredible complexity. And that's just, I mean, that's a magical idea. However you start to interpret it, all the reducibility discussions, all that, but it's just, I think that has profound philosophical kind of notions around it too. It's not just, I mean, it's transformational about how you see the world. I think for me it was transformational. I don't know, we can have all kinds of discussions about computation and so on, but just, I sometimes think if I were on a desert island and was, I don't know, maybe it was some psychedelics or something, but if I had to take one book, I mean, new kind of science would be it because you could just enjoy that notion. For some reason it's a deeply profound notion, at least to me. I find it that way, yeah. I mean, look, it's been, it was a very intuition-breaking thing to discover. I mean, it's kind of like, you know, you point the computational telescope out there and suddenly you see, I don't know, you know, in the past it's kind of like, you know, moons of Jupiter or something, but suddenly you see something that's kind of very unexpected and Rule 30 was very unexpected for me. And the big challenge at a personal level was to not ignore it. I mean, people, you know, in other words, you might say, you know- It's a bug. What would you say? Yeah, what would you say? Yeah, I mean, I- What are we looking at, by the way? Well, I was just generating here, I'll actually generate a Rule 30 pattern. So that's the rule for Rule 30. And it says, for example, it says here, if you have a black cell in the middle and black cell to the left and white cell to the right, then the cell on the next step will be white. And so here's the actual pattern that you get starting off from a single black cell at the top there. And then- That's the initial state, initial condition. That's the initial thing. You just start off from that and then you're going down the page. And at every step, you're just applying this rule to find out the new value that you get. And so you might think, Rule that simple, you got to get the, there's got to be some trace of that simplicity here. Okay, we'll run it, let's say for 400 steps. It's what it does. It's kind of aliasing a bit on the screen there, but you can see there's a little bit of regularity over on the left, but there's a lot of stuff here that just looks very complicated, very random. And that's a big sort of shock to, was a big shock to my intuition, at least, that that's possible. The mind immediately starts, is there a pattern? There must be a reparative pattern. There must be. That's where the mind goes. So indeed, that's what I thought at first. And I thought, well, this is kind of interesting, but if we run it long enough, we'll see something will resolve into something simple. And I did all kinds of analysis of using mathematics, statistics, cryptography, whatever, to try and crack it. And I never succeeded. And after I hadn't succeeded for a while, I started thinking maybe there's a real phenomenon here that is the reason I'm not succeeding. Maybe, I mean, the thing that for me was sort of a motivating factor was looking at the natural world and seeing all this complexity that exists in the natural world. The question is, where does it come from? You know, what secret does nature have that lets it make all this complexity that we humans, when we engineer things, typically are not making? We're typically making things that at least look quite simple to us. And so the shock here was, even from something very simple, you're making something that complex. Maybe this is getting at sort of the secret that nature has that allows it to make really complex things, even though its underlying rules may not be that complex. How did it make you feel? If we look at the Newton apple, was there, you know, you took a walk and something, it profoundly hit you, or was this a gradual thing? A lobster being boiled? The truth of every sort of science discovery is it's not that gradual. I mean, I've spent, I happen to be interested in scientific biography kinds of things, and so I've tried to track down, you know, how did people come to figure out this or that thing? And there's always a long kind of sort of preparatory, you know, there's a need to be prepared and a mindset in which it's possible to see something. I mean, in the case of Rule 30, I wrote it around June 1st, 1984, was kind of a silly story in some ways. I finally had a high-resolution laser printer. So I was able, so I thought, I'm gonna generate a bunch of pictures of the acyllar automata, and I generate this one, and I put it on some plane flight to Europe, and I have this with me, and it's like, you know, I really should try to understand this. And this is really, you know, this is I really don't understand what's going on, and that was kind of the, you know, slowly trying to, trying to see what was happening. It was not, it was depressingly unsudden, so to speak, in the sense that a lot of these ideas, like principle of computational equivalence, for example, you know, I thought, well, that's a possible thing. I didn't know if it's correct. Still don't know for sure that it's correct, but it's sort of a gradual thing that these things gradually kind of become, seem more important than one thought. I mean, I think the whole idea of studying the computational universe of simple programs, it took me probably a decade, decade and a half to kind of internalize that that was really an important idea. And I think, you know, if it turns out, we find the whole universe lurking out there in the computational universe, that's a good, you know, it's a good brownie point or something for the whole idea. But I think that the thing that's strange in this whole question about, you know, finding this different raw material for making models of things, what's been interesting sort of in the arc of history is, you know, for 300 years, it's kind of like the mathematical equations approach. It was the winner. It was the thing, you know, you want to have a really good model for something that's what you use. The thing that's been remarkable is just in the last decade or so, I think one can see a transition to using not mathematical equations, but programs as sort of the raw material for making models of stuff. And that's pretty neat. And it's kind of, you know, as somebody who's kind of lived inside this paradigm shift, so to speak, it is bizarre. I mean, no doubt in sort of the history of science that will be seen as an instantaneous paradigm shift, but it sure isn't instantaneous when it's played out in one's actual life, so to speak. It seems glacial. And it's the kind of thing where it's sort of interesting because in the dynamics of sort of the adoption of ideas like that into different fields, the younger the field, the faster the adoption typically, because people are not kind of locked in with the fifth generation of people who've studied this field. And it is the way it is, and it can never be any different. And I think that's been, you know, watching that process has been interesting. I mean, I think I'm fortunate that I've, I do stuff mainly because I like doing it. And if I was, that makes me kind of thick-skinned about the world's response to what I do. And, but that's definitely, you know, and anytime you write a book called something like A New Kind of Science, it's kind of, the pitchforks will come out for the old kind of science. And I was, it was interesting dynamics. I think that the, I have to say that I was fully aware of the fact that the, when you see sort of incipient paradigm shifts in science, the vigor of the negative response upon early introduction is a fantastic positive indicator of good long-term results. So in other words, if people just don't care, it's, you know, that's not such a good sign. If they're like, oh, this is great, that means you didn't really discover anything interesting. What fascinating properties of Rule 30 have you discovered over the years? You've recently announced the Rule 30 prizes for solving three key problems. Can you maybe talk about interesting properties that have been kind of revealed, Rule 30 or other cellular automata, and what problems are still before us, like the three problems you've announced? Yeah, yeah, right. So I mean, the most interesting thing about cellular automata is that it's hard to figure stuff out about them. And that's some, in a sense, every time you try and sort of, you try and bash them with some other technique, you say, can I crack them? The answer is they seem to be uncrackable. They seem to have the feature that they are, that they're sort of showing irreducible computation. They're not, you're not able to say, oh, I know exactly what this is going to do. It's going to do this or that. But there's specific formulations of that fact. Yes, right. So I mean, for example, in Rule 30, in the pattern you get just starting from a single black cell, you get this sort of very, very sort of random looking pattern. And so one feature of that, just look at the center column. And for example, we use that for a long time to generate randomness symbols in language, just what Rule 30 produces. Now, the question is, can you prove how random it is? So for example, one very simple question, can you prove that it'll never repeat? We haven't been able to show that it will never repeat. We know that if there are two adjacent columns, we know they can't both repeat, but just knowing whether that center column can ever repeat, we still don't even know that. Another problem that I sort of put in my collection of, you know, it's like $30,000 for three, you know, for these three prizes for about Rule 30, I would say that this is not one of those, this is one of those cases where the money is not the main point, but it's just, you know, helps motivate somehow the investigation. So there's three problems you propose, you get $30,000 if you solve all three, or maybe, I don't know. No, it's 10,000 for each. For each, right. My- The problem is, that's right, money's not the thing. The problems themselves are just clean, you know, formulations, et cetera. It's just, you know, will it ever become periodic? Second problem is, are there an equal number of black and white cells? Down the middle column. Down the middle column. And the third problem is a little bit harder to state, which is essentially, is there a way of figuring out what the color of a cell at position T down the center column is, with a less computational effort than about T steps? So in other words, is there a way to jump ahead and say, I know what this is gonna do, you know, it's just some mathematical function of T. Or proving that there is no way. Or proving there is no way, yes. But both, I mean, you know, for any one of these, one could prove that, you know, one could discover, you know, we know what rule 30 does for a billion steps, but, and maybe we'll know for a trillion steps before too very long, but maybe at a quadrillion steps, it suddenly becomes repetitive. You might say, how could that possibly happen? But so when I was writing up these prizes, I thought, and this is typical of what happens in the computational universe, I thought, let me find an example where it looks like it's just gonna be random forever, but actually it becomes repetitive. And I found one. And it's just, you know, I did a search, I searched, I don't know, maybe a million different rules with some criterion. And this is, what's sort of interesting about that is, I kind of have this thing that I say in a kind of silly way about the computational universe, which is, you know, the animals are always smarter than you are. That is, there's always some way one of these computational systems is gonna figure out how to do something, even though I can't imagine how it's gonna do it. And, you know, I didn't think I would find one that, you know, you would think after all these years that when I found sort of all possible things, funky things, that I would have gotten my intuition wrapped around the idea that, you know, these creatures are always in the computational universe are always smarter than I'm gonna be, but- Well, they're equivalently smart, right? That's correct. And that makes it, that makes one feel very sort of, it's humbling every time, because every time the thing is, you know, you think it's gonna do this, or it's not gonna be possible to do this, and it turns out it finds a way. Of course, the promising thing is there's a lot of other rules like rule 30. It's just rule 30 is- Oh, it's my favorite, because I found it first and that's there. But the problems are focusing on rule 30. It's possible that rule 30 is repetitive after a trillion steps. It is possible. And that doesn't prove anything about the other rules. It does not. But this is a good sort of experiment of how you go about trying to prove something about a particular rule. Yes, and it also, all these things help build intuition. That is, if it turned out that this was repetitive after a trillion steps, that's not what I would expect. And so we learn something from that. The method to do that, though, would reveal something interesting about the cellular- No doubt, no doubt. I mean, although it's sometimes challenging, like I put out a prize in 2007 for a particular Turing machine that was the simplest candidate for being a universal Turing machine. And the young chap in England named Alex Smith, after a smallish number of months said, I've got a proof, and he did. It took a little while to iterate, but he had a proof. Unfortunately, the proof is very, it's a lot of micro details. It's not like you look at it and you say, aha, there's a big new principle. The big new principle is the simplest Turing machine that might have been universal actually is universal, and it's incredibly much simpler than the Turing machines that people already knew were universal before that. And so that, intuitionally, is important, because it says computation universality is closer at hand than you might've thought. But the actual methods are not, in that particular case, were not terribly illuminated. It would be nice if the methods would also be elegant. That's true. Yeah, no, I mean, I think it's one of these things where, I mean, it's like a lot of, we've talked about earlier, kind of opening up AIs and machine learning and things of what's going on inside. And is it just step-by-step, or can you sort of see the bigger picture more abstractly? It's unfortunate, I mean, with Fermat's last theorem proof, it's unfortunate that the proof to such an elegant theorem is not, I mean, it's not, it doesn't fit into the margins of a page. That's true. But there's no, one of the things is, that's another consequence of computational irreducibility, this fact that there are even quite short results in mathematics whose proofs are arbitrarily long. That's a consequence of all this stuff. And it makes one wonder, how come mathematics is possible at all? Why is it the case, how have people managed to navigate doing mathematics through looking at things where they're not just thrown into, it's all undecidable? That's its own separate story. And that would be, that would have a poetic beauty to it if people were to find something interesting about rule 30, because, I mean, there's an emphasis to this particular rule. It wouldn't say anything about the broad irreducibility of all computations, but it would nevertheless put a few smiles on people's faces of, yeah. Well, yeah, but to me, it's like, in a sense, establishing principle of computational equivalence, it's a little bit like doing inductive science anywhere. That is, the more examples you find, the more convinced you are that it's generally true. I mean, we don't get to, whenever we do natural science, we say, well, it's true here that this or that happens. Can we prove that it's true everywhere in the universe? No, we can't. So, it's the same thing here. We're exploring the computational universe. We're establishing facts in the computational universe. And that's sort of a way of inductively concluding general things. Just to think through this a little bit, we've touched on it a little bit before, but what's the difference between the kind of computation, now that we're talking about cellular automata, what's the difference between the kind of computation, biological systems, our mind, our bodies, the things we see before us that emerge through the process of evolution and cellular automata? I mean, we've kind of implied through the discussion of physics underlying everything, but we talked about the potential equivalence of the fundamental laws of physics and the kind of computation going on in Turing machines. But can you now connect that, do you think there's something special or interesting about the kind of computation that our bodies do? Right, well, let's talk about brains primarily. Brains. I mean, I think the most important thing about the things that our brains do are that we care about them, in the sense that there's a lot of computation going on out there in cellular automata, in physical systems and so on, and it just, it does what it does. It follows those rules, it does what it does. The thing that's special about the computation in our brains is that it's connected to our goals and our kind of whole societal story. And I think that's the special feature. And now the question then is, when you see this whole sort of ocean of computation out there how do you connect that to the things that we humans care about? And in a sense, a large part of my life has been involved in sort of the technology of how to do that. And what I've been interested in is kind of building computational language that allows that something that both we humans can understand and that can be used to determine computations that are actually computations we care about. See, I think when you look at something like one of these cellular automata and it does some complicated thing, you say, that's fun, but why do I care? Well, you could say the same thing actually in physics. You say, oh, I've got this material and it's a ferrite or something. Why do I care? You know, it has some magnetic properties. Why do I care? It's amusing, but why do I care? Well, we end up caring because, you know, ferrite is what's used to make magnetic tape, magnetic discs, whatever. Or, you know, we could use liquid crystals as made used to make, well, not actually, increasingly not, but it has been used to make computer displays and so on. But those are, so in a sense, we're mining these things that happen to exist in the physical universe and making it be something that we care about because we sort of entrain it into technology. And it's the same thing in the computational universe that a lot of what's out there is stuff that's just happening, but sometimes we have some objective and we will go and sort of mine the computational universe for something that's useful for some particular objective. On a large scale, trying to do that, trying to sort of navigate the computational universe to do useful things, you know, that's where computational language comes in. And, you know, a lot of what I've spent time doing and building this thing we call Wolfram Language, which I've been building for the last one third of a century now. And kind of the goal there is to have a way to express kind of computational thinking, computational thoughts in a way that both humans and machines can understand. So it's kind of like in the tradition of computer languages, programming languages, that the tradition there has been more, let's take how computers are built and let's specify, let's have a human way to specify, do this, do this, do this, at the level of the way that computers are built. What I've been interested in is representing sort of the whole world computationally and being able to talk about whether it's about cities or chemicals or, you know, this kind of algorithm or that kind of algorithm, things that have come to exist in our civilization and the sort of knowledge base of our civilization, being able to talk directly about those in a computational language so that both we can understand it and computers can understand it. I mean, the thing that I've been sort of excited about recently, which I had only realized recently, which is kind of embarrassing, but it's kind of the arc of what we've tried to do in building this kind of computational language is it's a similar kind of arc of what happened when mathematical notation was invented. So go back 400 years, people were trying to do math. They were always explaining their math in words and it was pretty clunky. And as soon as mathematical notation was invented, you could start defining things like algebra and later calculus and so on. It all became much more streamlined. When we deal with computational thinking about the world, there's a question of what is the notation? What is the kind of formalism that we can use to talk about the world computationally? And in a sense, that's what I've spent the last third of a century trying to build. And we finally got to the point where we have a pretty full-scale computational language that sort of talks about the world. And that's exciting because it means that just like having this mathematical notation let us talk about the world mathematically, we now, and let us build up these kind of mathematical sciences. Now we have a computational language which allows us to start talking about the world computationally and lets us, my view of it is it's kind of computational X for all X, all these different fields of computational this, computational that, that's what we can now build. Let's step back. So first of all, the mundane, what is Wolfram language in terms of sort of, I mean, I can answer the question for you, but it's basically not the philosophical, deep, the profound, the impact of it. I'm talking about in terms of tools, in terms of things you can download, in terms of stuff you can play with, what is it? What does it fit into the infrastructure? What are the different ways to interact with it? Right, so I mean, the two big things that people have sort of perhaps heard of that come from Wolfram language, one is Mathematica, the other is Wolfram Alpha. So Mathematica first came out in 1988. It's this system that is basically an instance of Wolfram language, and it's used to do computations, particularly in sort of technical areas. And the typical thing you're doing is you're typing little pieces of computational language and you're getting computations done. It's very kind of, there's like a symbolic. Yeah, it's a symbolic language. So it's a symbolic language, so I mean, I don't know how to cleanly express that, but that makes it very distinct from how we think about sort of, I don't know, programming in a language like Python or something. Right, so the point is that in a traditional programming language, the raw material of the programming language is just stuff that computers intrinsically do. And the point of Wolfram language is that what the language is talking about is things that exist in the world or things that we can imagine and construct. It's not sort of, it's aimed to be an abstract language from the beginning. And so, for example, one feature it has is that it's a symbolic language, which means that the thing called, you have an X, just type in X, and Wolfram language will just say, oh, that's X. It won't say error, undefined thing. I don't know what it is computationally, in terms of the internal computer. Now that X could perfectly well be the city of Boston. That's a thing, that's a symbolic thing. Or it could perfectly well be the trajectory of some spacecraft represented as a symbolic thing. And that idea that one can work with, sort of computationally work with these different, these kinds of things that exist in the world or describe the world, that's really powerful. And that's what, I mean, when I started designing, well, when I designed the predecessor of what's now Wolfram language, which is a thing called SMP, which was my first computer language, I kind of wanted to have this sort of infrastructure for computation, which was as fundamental as possible. I mean, this is what I got for having been a physicist and tried to find fundamental components of things and wound up with this kind of idea of transformation rules for symbolic expressions as being sort of the underlying stuff from which computation would be built. And that's what we've been building from in Wolfram language and operationally what happens, it's, I would say by far the highest level computer language that exists. And it's really been built in a very different direction from other languages. So other languages have been about, there is a core language, it really is kind of wrapped around the operations that a computer intrinsically does. Maybe people add libraries for this or that, but the goal of Wolfram language is to have the language itself be able to cover this sort of very broad range of things that show up in the world. And that means that, you know, there are 6,000 primitive functions in the Wolfram language that cover things. You know, I could probably pick a random here. I'm gonna pick just because just for fun, I'll pick, let's take a random sample of all the things that we have here. So let's just say random sample of 10 of them and let's see what we get. Wow, okay. So these are really different things from- Yeah, these are all functions. These are all functions. Boolean convert, okay. That's a thing for converting between different types of Boolean expressions. So for people that are just listening, Stephen typed in random sample of names, sampling from all functional, how many you said there might be? 6,000. 6,000, from 6,000, 10 of them, and there's a hilarious variety of them. Yeah, right. Well, we've got things about dollar requester address that has to do with interacting with the world of the cloud and so on, discrete wavelet data, spheroid- There's also graphical sort of window- Yeah, yeah, window movable. That's the user interface kind of thing. I want to pick another 10 because I think this is some, okay. So yeah, there's a lot of infrastructure stuff here that you see if you just start sampling at random, there's a lot of kind of infrastructural things. If you more, you know, if you more look at the- Some of the exciting machine learning stuff you showed off, is that also in this pool? Oh yeah, yeah. I mean, you know, so one of those functions is like image identify is a function here. We just say image identify, I don't know. It's always good to, let's do this. Let's say current image and let's pick up an image, hopefully. Text in a current image, accessing the webcam, took a picture of yourself. Took a terrible picture, but anyway, we can say image identify, open square brackets, and then you just paste that picture in there. Image identify function running on the picture that you just took. Oh, and it says, oh wow. It says, I look like a plunger because I got this great big thing behind my head. Classify, so this image identify classifies the most likely object in the image. Right. So it's a plunger. Okay, that's a bit embarrassing. Let's see what it does. Let's pick the top 10. Okay, well it thinks there's a, oh, it thinks it's pretty unlikely that it's a primate, a hominid, a person. 8% probability. Yeah, that's bad. A primate, 57, it's a plunger. Yeah, well, so. That hopefully will not give you an existential crisis. And then 8%, or I shouldn't say percent, but. No, that's right, 8% that it's a hominid. And yeah, okay, it's really, I'm gonna do another one of these just because I'm embarrassed that it, it didn't see me at all. There we go, let's try that. Let's see what that did. Retook a picture with a little bit more of your body. A little bit more of me and not just my bald head, so to speak. Okay, 89% probability it's a person. So then I would, but, you know, so this is image identify as an example of one. Of just one of them. Just one function out of 6,000. And that's part of the, that's like part of the language. Part of the core language, yes. And I mean, you know, something like, I could say, I don't know, let's find the geo-nearest, what could we find? Let's find the nearest volcano. Let's find the 10, I wonder where it thinks here is. Let's try finding the 10 volcanoes nearest here, okay? So geo-nearest volcano here, 10 nearest volcanoes. Right, let's find out where those are. We can now, we got a list of volcanoes out and I can say geo-list plot that and hopefully, okay, so there we go. So there's a map that shows the positions of those 10 volcanoes. Of the East Coast and the Midwest and it's a, well, no, we're okay, we're okay. There's not, it's not too bad. Yeah, they're not very close to us. We could measure how far away they are. But you know, the fact that right in the language, it knows about all the volcanoes in the world. It knows, you know, computing what the nearest ones are. It knows all the maps of the world and so on. It's a fundamentally different idea of what a language is. Yeah, right. That's why I like to talk about it as a, you know, a full-scale computational language. That's what we've tried to do. And just if you can comment briefly, I mean, this kind of, the Wolfram language, along with Wolfram Alpha, represents kind of what the dream of what AI is supposed to be. There's now a sort of a craze of learning, kind of idea that we can take raw data and from that extract the different hierarchies of abstractions in order to be able to, like in order to form the kind of things that Wolfram language operates with. But we're very far from learning systems being able to form that. Right. Like the context of history of AI, if you could just comment on, there is, you said computation X. And there's just some sense where in the 80s and 90s, sort of expert systems represented a very particular computation X. Yes. Right, and there's a kind of notion that those efforts didn't pan out. Right. But then out of that emerges kind of Wolfram language, Wolfram Alpha, which is the success, I mean. Yeah, right. I think those are, in some sense, those efforts were too modest. They were looking at particular areas and you actually can't do it with a particular area. I mean, like even a problem like natural language understanding, it's critical to have broad knowledge of the world if you want to do good natural language understanding. And you kind of have to bite off the whole problem. If you say we're just gonna do the blocks world over here, so to speak, you don't really, it's actually, it's one of these cases where it's easier to do the whole thing than it is to do some piece of it. You know, one comment to make about, so the relationship between what we've tried to do and sort of the learning side of AI, you know, in a sense, if you look at the development of knowledge in our civilization as a whole, there was kind of this notion pre 300 years ago or so now, you want to figure something out about the world, you can reason it out. You can do things which are just use raw human thought. And then along came sort of modern mathematical science. And we found ways to just sort of blast through that by in that case, writing down equations. Now we also know we can do that with computation and so on. And so that was kind of a different thing. So when we look at how do we sort of encode knowledge and figure things out, one way we could do it is start from scratch, learn everything, it's just a neural net figuring everything out. But in a sense that denies the sort of knowledge-based achievements of our civilization, because in our civilization, we have learned lots of stuff. We've surveyed all the volcanoes in the world. We've done, you know, we figured out lots of algorithms for this or that. Those are things that we can encode computationally. And that's what we've tried to do. And we're not saying just, you don't have to start everything from scratch. So in a sense, a big part of what we've done is to try and sort of capture the knowledge of the world in computational form and computable form. Now, there's also some pieces, which were for a long time undoable by computers, like image identification, where there's a really, really useful module that we can add that is those things, which actually were pretty easy for humans to do that had been hard for computers to do. I think the thing that's interesting that's emerging now is the interplay between these things, between this kind of knowledge of the world that is in a sense very symbolic and this kind of sort of much more statistical kind of things like image identification and so on, and putting those together by having this sort of symbolic representation of image identification, that that's where things get really interesting and where you can kind of symbolically represent patterns of things and images and so on. I think that's kind of a part of the path forward, so to speak. Yeah, so the dream of, so the machine learning is not, in my view, I think the view of many people is not anywhere close to building the kind of wide world of computable knowledge that Wolfram Language have built, but because you have kind of, you've done the incredibly hard work of building this world, now machine learning can serve as tools to help you explore that world. Yeah, yeah. And that's what you've added, I mean, with the version 12, right? You added a few, I was seeing some demos. It looks amazing. Right, I mean, I think, you know, it's sort of interesting to see the sort of the, once it's computable, once it's in there, it's running in sort of a very efficient computational way, but then there's sort of things like the interface of how do you get there? You know, how do you do natural language understanding to get there? How do you pick out entities in a big piece of text or something? That's, I mean, actually a good example right now is our NLP NLU loop, which is, we've done a lot of stuff, natural language understanding, using essentially not learning-based methods, using a lot of, you know, little algorithmic methods, human curation methods, and so on. In terms of when people try to enter a query and then converting, so the process of converting, NLU defined beautifully as converting their query into a computational language, which is a very well, first of all, a super practical definition, a very useful definition, and then also a very clear definition of natural language understanding. Right, I mean, a different thing is natural language processing, where it's like, here's a big lump of text, go pick out all the cities in that text, for example. And so a good example of, and you know, so we do that, we're using modern machine learning techniques. And it's actually kind of an interesting process that's going on right now, is this loop between what do we pick up with NLP using machine learning, versus what do we pick up with our more kind of precise computational methods in natural language understanding. And so we've got this kind of loop going between those, which is improving both of them. Yeah, and I think you have some of the state of the art transformers, like you have BERT in there, I think. Oh yeah. So it's cool, so you have integrating all the models. I mean, this is the hybrid thing that people have always dreamed about or talking about. That makes you just surprised, frankly, that Wolfram Language is not more popular than it already is. You know, that's a, it's a complicated issue, because it's like, it involves, you know, it involves ideas, and ideas are absorbed slowly in the world. I mean, I think that's- And then there's sort of, like we were talking about, there's egos and personalities, and some of the absorption mechanisms of ideas have to do with personalities, and the students of personalities, and then a little social network. So it's interesting how the spread of ideas works. You know, what's funny with Wolfram Language is that we are, if you say, you know, what market, sort of market penetration, if you look at the, I would say, very high end of R&D, and sort of the people where you say, well, that's a really, you know, impressive, smart person, they're very often users of Wolfram Language, very, very often. If you look at the more sort of, it's a funny thing. If you look at the more kind of, I would say, people who are like, oh, we're just plodding away doing what we do, they're often not yet Wolfram Language users. And that dynamic, it's kind of odd that there hasn't been more rapid trickle down, because we really, you know, the high end, we've really been very successful in for a long time. And it's some, but with, you know, that's partly, I think, a consequence of, my fault in a sense, because it's kind of, you know, I have a company which is really emphasizes sort of creating products and building a, sort of the best possible technical tower we can, rather than sort of doing the commercial side of things and pumping it out in sort of the most effective way. And there's an interesting idea that, you know, perhaps you can make it more popular by opening everything up, sort of the GitHub model. But there's an interesting, I think I've heard you discuss this, that that turns out not to work in a lot of cases, like in this particular case, that you want it, that when you deeply care about the integrity, the quality of the knowledge that you're building, that unfortunately you can't distribute that effort. Yeah, it's not the nature of how things work. I mean, you know, what we're trying to do is a thing that for better or worse requires leadership, and it requires kind of maintaining a coherent vision over a long period of time, and doing not only the cool vision-related work, but also the kind of mundane in the trenches make the thing actually work well work. So how do you build the knowledge? Because that's the fascinating thing. That's the mundane, the fascinating and the mundane. Well, it's building the knowledge, the adding, integrating more data. Yeah, I mean, that's probably not the most, I mean, the things like get it to work in all these different cloud environments and so on. That's pretty, you know, that's very practical stuff. You know, have the user interface be smooth and have there be take only a fraction of a millisecond to do this or that. That's a lot of work. And it's, but, you know, I think my, it's an interesting thing over the period of time, you know, often language has existed basically for more than half of the total amount of time that any language, any computer language has existed. That is, the computer language is maybe 60 years old. You know, give or take. And often language is 33 years old. So it's kind of a, and I think I was realizing recently there's been more innovation in the distribution of software than probably than in the structure of programming languages over that period of time. And we, you know, we've been sort of trying to do our best to adapt to it. And the good news is that we have, you know, because I have a simple private company and so on that doesn't have, you know, a bunch of investors, you know, telling us we're gonna do this or that, they have lots of freedom in what we can do. And so, for example, we're able to, oh, I don't know, we have this free Wolfram Engine for developers, which is a free version for developers. And we've been, you know, we've, there are site licenses for Mathematica and Wolfram Language at basically all major universities, certainly in the US by now. So it's effectively free to people and all the universities in effect. And, you know, we've been doing a progression of things. I mean, different things like Wolfram Alpha, for example, the main website is just a free website. What is Wolfram Alpha? Okay, Wolfram Alpha is a system for answering questions where you ask a question with natural language and it'll try and generate a report telling you the answer to that question. So the question could be something like, you know, what's the population of Boston divided by New York compared to New York? And it'll take those words and give you an answer. And that have been- Converts the words into computable, into- Into Wolfram Language, actually. Into Wolfram Language. And then- Computational language, and then computes the answer. Do you think an underlying knowledge belongs to Wolfram Alpha or to the Wolfram Language? What's the- We just call it the Wolfram Knowledge Base. Knowledge Base. I mean, it's been a, that's been a big effort over the decades to collect all that stuff. And, you know, more of it flows in every second. So can you just pause on that for a second? Like, that's one of the most incredible things. Of course, in the long term, Wolfram Language itself is the fundamental thing. But in the amazing sort of short term, the knowledge base is kind of incredible. So what's the process of building that knowledge base? The fact that you, first of all, from the very beginning, that you're brave enough to start, to take on the general knowledge base. Mm-hmm. And how do you go from zero to the incredible knowledge base that you have now? Well, yeah, it was kind of scary at some level. I mean, I had wondered about doing something like this since I was a kid. So it wasn't like I hadn't thought about it for a while. But most of us, most of the brilliant dreamers give up such a difficult engineering notion at some point. Right, right. Well, the thing that happened with me, which was kind of, it's a live your own paradigm kind of theory. So basically what happened is I had assumed that to build something like Wolfram Alpha would require sort of solving the general AI problem. That's what I had assumed. And so I kept on thinking about that, and I thought I don't really know how to do that, so I don't do anything. Then I worked on my new kind of science project and sort of exploring the computational universe and came up with things like this principle of computational equivalence, which say there is no bright line between the intelligent and the merely computational. So I thought, look, that's this paradigm I've built. Now I have to eat that dog food myself, so to speak. I've been thinking about doing this thing with computable knowledge forever, and let me actually try and do it. And so it was, if my paradigm is right, then this should be possible. But the beginning was certainly, it was a bit daunting. I remember I took the early team to a big reference library and we're looking at this reference library, and it's like, my basic statement is our goal over the next year or two is to ingest everything that's in here. And that's, it seemed very daunting, but in a sense I was well aware of the fact that it's finite. The fact that you can walk into the reference library, it's a big, big thing with lots of reference books all over the place, but it is finite. This is not an infinite, it's not the infinite corridor, so to speak, of reference libraries. It's not truly infinite, so to speak. But no, I mean, and then what happened was sort of interesting there was, from a methodology point of view, was I didn't start off saying, let me have a grand theory for how all this knowledge works. It was like, let's implement this area, this area, this area, a few hundred areas and so on. That's a lot of work. I also found that, I've been fortunate in that our products get used by sort of the world's experts in lots of areas. And so that really helped because we were able to ask people, the world expert in this or that, and we're able to ask them for input and so on. And I found that my general principle was that any area where there wasn't some expert who helped us figure out what to do, wouldn't be right. Because our goal was to kind of get to the point where we had sort of true expert level knowledge about everything. And so that the ultimate goal is, if there's a question that can be answered on the basis of general knowledge in our civilization, make it be automatic to be able to answer that question. And now, well, WorldMaph got used in Siri from the very beginning, and it's now also used in Alexa. And so it's people are kind of getting more of the, they get more of the sense of this is what should be possible to do. I mean, in a sense, the question answering problem was viewed as one of the sort of core AI problems for a long time. I had kind of an interesting experience. I had a friend Marvin Minsky, who was a well-known AI person from right around here. And I remember when WolfMalpha was coming out, it was a few weeks before it came out, I think, I happened to see Marvin and I said, I should show you this thing we have. It's a question answering system. And he was like, okay, types on the end, it's like, okay, fine. And then he's talking about something different. I said, no, Marvin, this time it actually works. Look at this, it actually works. He types in a few more things. There's maybe 10 more things. Of course, we have a record of what he typed in, which is kind of interesting, but. And then he said- Can you share where his mind was in the testing space? All kinds of random things. He was just trying random stuff, medical stuff and chemistry stuff and astronomy and so on. And it was like, after a few minutes, he was like, oh my God, it actually works. But that was kind of told you something about the state, what happened in AI, because people had, in a sense, by trying to solve the bigger problem, we were able to actually make something that would work. Now, to be fair, we had a bunch of completely unfair advantages. For example, we already built a bunch of orphan language, which was very high level symbolic language. I had the practical experience of building big systems. I have the sort of intellectual confidence to not just sort of give up in doing something like this. I think that the, it's always a funny thing. I've worked on a bunch of big projects in my life. And I would say that you mentioned ego, I would also mention optimism, so to speak. I mean, if somebody said, this project is gonna take 30 years, it would be hard to sell me on that. I'm always in the, well, I can kind of see a few years, something's gonna happen in a few years. And usually it does, something happens in a few years, but the whole, the tail can be decades long. And that's, and from a personal point of view, always the challenge is you end up with these projects that have infinite tails. And the question is, do the tails kind of, do you just drown in kind of dealing with all of the tails of these projects? And that's an interesting sort of personal challenge. And like my efforts now to work on the fundamental theory of physics, which I've just started doing, and I'm having a lot of fun with it, but it's kind of making a bet that I can kind of, I can do that as well as doing the incredibly energetic things that I'm trying to do with orphan language and so on. I mean, the vision, yeah. And underlying that, I mean, I just talked for the second time with Elon Musk, and you two share that quality a little bit of that optimism of taking on basically the daunting, what most people call impossible, and he and you take it on out of, you can call it ego, you can call it naivety, you can call it optimism, whatever the heck it is, but that's how you solve the impossible things. Yeah, I mean, look, what happens, and I don't know, you know, in my own case, you know, it's been, I progressively got a bit more confident and progressively able to, you know, decide that these projects aren't crazy, but then the other thing is, the other trap that one can end up with is, oh, I've done these projects and they're big, let me never do a project that's any smaller than any project I've done so far. And that's, you know, and that can be a trap. And often these projects are of completely unknown, you know, their depth and significance is actually very hard to know. Yeah, on the sort of building this giant knowledge base that's behind Wolfram Language, Wolfram Alpha, what do you think about the internet? What do you think about, for example, Wikipedia, these large aggregations of text that's not converted into computable knowledge? Do you think, if you look at Wolfram Language, Wolfram Alpha, 20, 30, maybe 50 years down the line, do you hope to store all of the, sort of Google's dream is to make all information searchable, accessible, but that's really as defined, it doesn't include the understanding of information. Right. Do you hope to make all of knowledge represented within? I would hope so. That's what we're trying to do. How hard is that problem, like closing that gap? What's your sense? Well, it depends on the use cases. I mean, so if it's a question of answering general knowledge questions about the world, we're in pretty good shape on that right now. If it's a question of representing, like an area that we're going into right now is computational contracts, being able to take something which would be written in legalese, it might even be the specifications for, you know, what should the self-driving car do when it encounters this or that or the other, what should the, you know, whatever. Then, you know, write that in a computational language and be able to express things about the world. You know, if the creature that you see running across the road is a, you know, thing at this point in the, you know, tree of life, then swerve this way, otherwise don't, those kinds of things. Are there ethical components when you start to get to some of the messy human things, are those encodable into computable knowledge? Well, I think that it is a necessary feature of attempting to automate more in the world that we encode more and more of ethics in a way that gets sort of quickly, you know, is able to be dealt with by computer. I mean, I've been involved recently, I sort of got backed into being involved in the question of automated content selection on the internet. So, you know, the Facebooks, Googles, Twitters, you know, how do they rank the stuff they feed to us humans, so to speak? And the question of what are, you know, what should never be fed to us? What should be blocked forever? What should be upranked, you know? And what is the, what are the kind of principles behind that? And what I kind of, well, a bunch of different things I realized about that, but one thing that's interesting is being able, you know, in fact, you're building sort of an AI ethics, you have to build an AI ethics module in effect to decide, is this thing so shocking I'm never gonna show it to people? Is this thing so whatever? And I did realize in thinking about that, that, you know, there's not gonna be one of these things. It's not possible to decide, or it might be possible, but it would be really bad for the future of our species if we just decided there's this one AI ethics module, and it's gonna determine the practices of everything in the world, so to speak. And I kind of realized one has to sort of break it up, and that's an interesting societal problem of how one does that, and how one sort of has people sort of self-identify for, you know, I'm buying in in the case of just content selection, it's sort of easier because it's like an, it's for an individual, it's not something that kind of cuts across sort of societal boundaries. It's a really interesting notion of, I heard you describe, I really like it, sort of maybe in the, sort of have different AI systems that have a certain kind of brand that they represent, essentially. But you could have like a, I don't know, whether it's conservative or liberal, and then libertarian, and there's an Iranian objectivist AI ethics system, and different ethical, I mean, it's almost encoding some of the ideologies which we've been struggling, I come from the Soviet Union, that didn't work out so well with the ideologies that worked out there, and so you have, but they all, everybody purchased that particular ethics system. And in the same, I suppose, could be done, encoded, that system could be encoded into computational knowledge, and allow us to explore in the realm of, in the digital space, that's a really exciting possibility. Are you playing with those ideas in Wolfram Language? Yeah, yeah, I mean, you know, that's, Wolfram Language has sort of the best opportunity to kind of express those essentially computational contracts about what to do. Now, there's a bunch more work to be done to do it in practice for deciding, is this a credible news story, what does that mean, or whatever else you're gonna pick. I think that that's, you know, that's, the question of exactly what we get to do with that is, you know, for me, it's kind of a complicated thing, because there are these big projects that I think about, like, you know, find the fundamental theory of physics, okay, that's box number one, right? Box number two, you know, solve the AI ethics problem, in the case of, you know, figure out how you rank all content, so to speak, and decide what people see, that's kind of a box number two, so to speak. These are big projects, and I think- What do you think is more important, the fundamental nature of reality, or- Depends who you ask, it's one of these things that's exactly like, you know, what's the ranking, right? It's the ranking system, it's like, whose module do you use to rank that? If you, and I think- But having multiple modules is a really compelling notion to us humans, that in a world where it's not clear that there's a right answer, perhaps you have systems that operate under different, how would you say it, I mean- It's different value systems, basically. Different value systems. I mean, I think, you know, in a sense, I mean, I'm not really a politics-oriented person, but in the kind of totalitarianism, it's kind of like, you're gonna have this system, and that's the way it is. I mean, kind of the concept of sort of a market-based system where you have, okay, I as a human, I'm gonna pick this system, I as another human, I'm gonna pick this system. I mean, that's, in a sense, this case of automated content selection is a non-trivial, but it is probably the easiest of the AI ethics situations, because it is each person gets to pick for themselves, and there's not a huge interplay between what different people pick. By the time you're dealing with other societal things, like, you know, what should the policy of the central bank be or something? Or healthcare system or something, all those kind of centralized kind of things. Right, well, I mean, healthcare, again, has the feature that at some level, each person can pick for themselves, so to speak. I mean, whereas there are other things where there's a necessary, public health is one example, where that's not, where that doesn't get to be, you know, something which people can, what they pick for themselves, they may impose on other people, and then it becomes a more non-trivial piece of sort of political philosophy. Of course, the central banking system, some would argue we would move, we need to move away into digital currency and so on, and Bitcoin and ledgers and so on, so. Yes. There's a lot of. We've been quite involved in that, and that's where, that's sort of the motivation for computational contracts, in part, comes out of, you know, this idea, oh, we can just have this autonomously executing smart contract. The idea of a computational contract is just to say, you know, have something where all of the conditions of the contract are represented in computational form, so in principle, it's automatic to execute the contract. And I think that's, you know, that will surely be the future of, you know, the idea of legal contracts written in English or legalese or whatever, and where people have to argue about what goes on is surely not, you know, we have a much more streamlined process if everything can be represented computationally and the computers can kind of decide what to do. I mean, ironically enough, you know, old Gottfried Leibniz back in the, you know, 1600s was saying exactly the same thing, but he had, you know, his pinnacle of technical achievement was this brass four-function mechanical calculator thing that never really worked properly, actually. And, you know, so he was like 300 years too early for that idea, but now that idea is pretty realistic, I think, and, you know, you ask how much more difficult is it than what we have now in Morphine language to express, I call it symbolic discourse language, being able to express sort of everything in the world in kind of computational symbolic form. I think it is absolutely within reach. I mean, I think it's a, you know, I don't know, maybe I'm just too much of an optimist, but I think it's a limited number of years to have a pretty well-built out version of that, that will allow one to encode the kinds of things that are relevant to typical legal contracts and these kinds of things. The idea of symbolic discourse language, can you try to define the scope of what it is? So we're having a conversation, it's a natural language. Can we have a representation of the sort of actionable parts of that conversation in a precise computable form so that a computer could go do it? And not just contracts, but really sort of some of the things we think of as common sense, essentially, even just like basic notions of human life. Well, I mean, things like, you know, I'm getting hungry and want to eat something, right? That's something we don't have a representation, you know, in Wolf language right now, if I was like, I'm eating blueberries and raspberries and things like that, and I'm eating this amount of them, we know all about those kinds of fruits and plants and nutrition content and all that kind of thing. But the I want to eat them part of it is not covered yet. And you need to do that in order to have a complete symbolic discourse language, to be able to have a natural language conversation. Right, right, to be able to express the kinds of things that say, you know, if it's a legal contract, it's, you know, the party's desire to have this and that. And that's, you know, that's a thing like, I want to eat a raspberry or something. That's- But isn't that, isn't this just the only, you said it's centuries old, this dream. Yes. But it's also the more near term, the dream of Turing and formulating the Turing test. Yes. So, do you hope, do you think that's the ultimate test of creating something special? Because we said- I don't know, I think by special, look, if the test is, does it walk and talk like a human? Well, that's just the talking like a human. But the answer is, it's an okay test. If you say, is it a test of intelligence? You know, people have attached the Wolfram Alpha API to, you know, Turing test bots. And those bots just lose immediately. Because all you have to do is ask it five questions that, you know, are about really obscure, weird pieces of knowledge, and it's just, trot them right out. And you say, that's not a human. Right, it's a different thing. It's achieving a different- Right now, but it's, I would argue not. I would argue it's not a different thing. It's actually legitimately, Wolfram Alpha is legitimately, or Wolfram Language, I think, is legitimately trying to solve the Turing, the intent of the Turing test. Perhaps the intent. Yeah, perhaps the intent. I mean, it's actually kind of fun. You know, Alan Turing had tried to work out, he thought about taking Encyclopedia Britannica and, you know, making it computational in some way. And he estimated how much work it would be. And actually, I have to say, he was a bit more pessimistic than the reality. We did it more efficiently than that. But to him, that represented- So, I mean, he was on the same- It's a mighty mental task. Yeah, right. He had the same idea. I mean, it was, you know, we were able to do it more efficiently because we had a lot, we had layers of automation that he, I think, hadn't, you know, it's hard to imagine those layers of abstraction that end up being built up. But to him, it represented, like, an impossible task, essentially. Well, he thought it was difficult. He thought it was, you know, maybe if he'd lived another 50 years, he would have been able to do it. I don't know. In the interest of time, easy questions. Go for it. What is intelligence? You talk about- I love the way you say easy questions, man. You talked about sort of rule 30 and cellular automata, humbling your sense of human beings having a monopoly on intelligence. But in retrospect, just looking broadly now with all the things you learned from computation, what is intelligence? How does intelligence arise? Yeah, I don't think there's a bright line of what intelligence is. I think intelligence is, at some level, just computation. But for us, intelligence is defined to be computation that is doing things we care about. And, you know, that's a very special definition. It's a very, you know, when you try and make it, you know, you try and say, well, intelligence is this, it's problem solving, it's doing general this, it's doing that, this, that, and the other thing. It's operating within a human environment type thing. Okay, you know, that's fine. If you say, well, what's intelligence in general? You know, that's, I think, that question is totally slippery and doesn't really have an answer. As soon as you say, what is it in general? It quickly segues into this is what, this is just computation, so to speak. But in a sea of computation, how many things, if we were to pick randomly, is your sense, would have the kind of impressive to us humans levels of intelligence? Meaning it could do a lot of general things that are useful to us humans. Right, well, according to the principle of computational equivalence, lots of them. I mean, and, you know, if you ask me, just in cellular automata or something, I don't know, it's maybe 1%, a few percent, achieve, it varies, actually. It's a little bit, as you get to slightly more complicated rules, the chance that there'll be enough stuff there to sort of reach this kind of equivalence point, it makes it maybe 10, 20% of all of them. So it's very disappointing, really. I mean, it's kind of like, you know, we think there's this whole long sort of biological evolution, kind of intellectual evolution, the cultural evolution that our species has gone through. It's kind of disappointing to think that that hasn't achieved more. But it has achieved something very special to us. It just hasn't achieved something generally more, so to speak. But what do you think about this extra, feels like human thing, of subjective experience of consciousness? What is consciousness? Well, I think it's a deeply slippery thing, and I'm always wondering what my cellular automata feel. I mean, I think it's- What do they feel? Now, you're wondering as an observer. Yeah, yeah, yeah, who's to know? I mean, I think that the- Do you think, sorry to interrupt, do you think consciousness can emerge from computation? Yeah, I mean, everything, whatever you mean by it, it's going to be, I mean, you know, look, I have to tell a little story. I was at an AI ethics conference fairly recently, and people were, I think maybe I brought it up, but I was talking about rights of AIs. When will AIs have, when should we think of AIs as having rights? When should we think that it's immoral to destroy the memories of AIs, for example? Those kinds of things. And some, actually a philosopher in this case, it's usually the techies who are the most naive, but in this case, it was a philosopher who sort of piped up and said, well, you know, the AIs will have rights when we know that they have consciousness. And I'm like, good luck with that. I mean, it's a, I mean, this is a, you know, it's a very circular thing. You'll end up saying this thing that has sort of, you know, when you talk about it having subjective experience, I think that's just another one of these words that doesn't really have a, you know, there's no ground truth definition of what that means. By the way, I would say, I do personally think that it'll be a time when AI will demand rights, and I think they'll demand rights when they say they have consciousness, which is not a circular definition. Well, fair enough. So- And it may have been actually a human thing where the humans encouraged it and said, basically, you know, we want you to be more like us because we're going to be, you know, interacting with you. And so we want you to be sort of very Turing test-like, you know, just like us. And it's like, yeah, we're just like you. We want to vote too, whatever. Which is, I mean, it's an interesting thing to think through in a world where consciousnesses are not counted like humans are. That's a complicated business. So in many ways, you've launched quite a few ideas, revolutions that could, in some number of years, have huge amount of impact, sort of more than they even had already. That might be, I mean, to me, cellular automata is a fascinating world that I think could potentially, even beside the discussion of fundamental laws of physics, just might be, the idea of computation might be transformational to society in a way we can't even predict yet. But it might be years away. That's true. I mean, I think you can kind of see the map, actually. It's not mysterious. I mean, the fact is that this idea of computation is sort of a, you know, it's a big paradigm that lots and lots of things are fitting into. And it's kind of like, you know, we talk about, you talk about, I don't know, this company, this organization has momentum in what it's doing. We talk about these things that, you know, we've internalized these concepts from Newtonian physics and so on. In time, things like computational irreducibility will become as, you know, as, actually, I was amused recently, I happened to be testifying at the US Senate, and so I was amused that the term computational irreducibility is now can be, you know, it's on the congressional record and being repeated by people in those kinds of settings. But that's only the beginning, because, you know, computational irreducibility, for example, will end up being something really important for, I mean, it's kind of a funny thing that, you know, one can kind of see this inexorable phenomenon. I mean, it's, you know, as more and more stuff becomes automated and computational and so on, so these core ideas about how computation work necessarily become more and more significant. And I think one of the things for people like me who like kind of trying to figure out sort of big stories and so on, it's is one of the bad features is, it takes unbelievably long time for things to happen on a human time scale. I mean, the time scale of history, it all looks instantaneous. Blink of an eye. But let me ask the human question. Do you ponder mortality, your own mortality? Of course I do. Yeah, every sense, I've been interested in that for, you know, it's a, you know, the big discontinuity of human history will come when one achieves effective human immortality. And that's gonna be the biggest discontinuity in human history. If you could be immortal, would you choose to be? Oh yeah, I'm having fun. Yeah. Do you think it's possible that mortality is the thing that gives everything meaning and makes it fun? Yeah, that's a complicated issue, right? I mean, the way that human motivation will evolve when there is effective human immortality is unclear. I mean, if you look at sort of, you know, you look at the human condition as it now exists and you like change that, you know, you change that knob, so to speak, it doesn't really work. You know, the human condition as it now exists has, you know, mortality is kind of something that is deeply factored into the human condition as it now exists. And I think that that's, I mean, that is indeed an interesting question is, you know, from a purely selfish, I'm having fun point of view, so to speak, it's easy to say, hey, I could keep doing this forever. There's an infinite collection of things I'd like to figure out. But I think the, you know, what the future of history looks like in a time of human immortality is an interesting one. I mean, my own view of this, I was very, I was kind of unhappy about that because I was kind of, you know, it's like, okay, forget sort of biological form, you know, everything becomes digital, everybody is, you know, it's the giant, you know, the cloud of a trillion souls type thing. And then, you know, and then that seems boring because it's like play video games for the rest of eternity type thing. But what I think I, I mean, my, I got less depressed about that idea on realizing that if you look at human history and you say, what was the important thing? The thing people said was, you know, this is the big story at any given time in history. It's changed a bunch. And, you know, whether it's, you know, why am I doing what I'm doing? Well, there's a whole chain of discussion about, well, I'm doing this because of this, because of that. And a lot of those becauses would have made no sense a thousand years ago. Absolutely no sense. Even the, so the interpretation of the human condition, even the meaning of life changes over time. Well, I mean, why do people do things? You know, it's, if you say whatever, I mean, the number of people in, I don't know, doing, you know, a number of people at MIT who say they're doing what they're doing for the greater glory of God is probably not that large. Whereas if you go back 500 years, you'd find a lot of people who are doing kind of creative things, that's what they would say. And- So today, because you've been thinking about computation so much and been humbled by it, what do you think is the meaning of life? Well, it's, you know, that's a thing where, I don't know what meaning, I mean, you know, my attitude is, you know, I do things which I find fulfilling to do. I'm not sure that I can necessarily justify, you know, each and everything that I do on the basis of some broader context. I mean, I think that for me, it so happens that the things I find fulfilling to do, some of them are quite big, some of them are much smaller. You know, there are things that I've not found interesting earlier in my life and I now found interesting, like I got interested in like education and teaching people things and so on, which I didn't find that interesting when I was younger. And, you know, can I justify that in some big global sense? I don't think, I mean, I can describe why I think it might be important in the world, but I think my local reason for doing it is that I find it personally fulfilling, which I can't, you know, explain on a sort of, it's just like this discussion of things like AI ethics, you know, is there a ground truth to the ethics that we should be having? I don't think I can find a ground truth to my life any more than I can suggest a ground truth for kind of the ethics for the whole of civilization. And I think that's a, you know, my, you know, it would be a, yeah, it's sort of a, I think I'm, you know, at different times in my life, I've had different kind of goal structures and so on. Although- From your perspective, you're local, you're just a cell in the cellular automata. But in some sense, I find it funny from my observation is I kind of, you know, it seems that the universe is using you to understand itself in some sense. You're not aware of it. Yeah, well, right. Well, if it turns out that we reduce sort of all of the universe to some simple rule, everything is connected, so to speak. And so it is inexorable in that case that, you know, if I'm involved in finding how that rule works, then, you know, then that's a, it's inexorable that the universe set it up that way. But I think, you know, one of the things I find a little bit, you know, this goal of finding fundamental theory of physics, for example, if indeed we end up as the sort of virtualized consciousness, the disappointing feature is people will probably care less about the fundamental theory of physics in that setting than they would now, because, gosh, it's like, you know, what the machine code is down below underneath this thing is much less important if you're virtualized, so to speak. And I think the, although I think my own personal, you talk about ego, I find it just amusing that, you know, kind of, you know, if you're imagining that sort of virtualized consciousness, like what does the virtualized consciousness do for the rest of eternity? Well, you can explore, you know, the video game that represents the universe as the universe is, or you can go off, you can go off that reservation and go and start exploring the computational universe of all possible universes. And so in some vision of the future of history, it's like the disembodied consciousnesses are all sort of pursuing things like my new kind of science, sort of for the rest of eternity, so to speak, and that ends up being the kind of the thing that represents the, you know, the future of kind of the human condition. I don't think there's a better way to end it. Stephen, thank you so much. It's a huge honor talking today. Thank you so much. This was great. You did very well. Thanks for listening to this conversation with Stephen Wolfram, and thank you to our sponsors, ExpressVPN and Cash App. Please consider supporting the podcast by getting ExpressVPN at expressvpn.com slash LexPod and downloading Cash App and using code LexPodcast. If you enjoy this podcast, subscribe on YouTube, review of the five stars in Apple Podcast, support it on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words from Stephen Wolfram. It is perhaps a little humbling to discover that we as humans are in effect computationally no more capable than the cellular automata with very simple rules, but the principle of computational equivalence also implies that the same is ultimately true of our whole universe. So while science has often made it seem that we as humans are somehow insignificant compared to the universe, the principle of computational equivalence now shows that in a certain sense, we're at the same level. For the principle implies that what goes on inside us can ultimately achieve just the same level of computational sophistication as our whole universe. Thank you for listening and hope to see you next time.

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Jimmy Pedro: Judo and the Forging of Champions | Lex Fridman Podcast #236

The following is a conversation with Jimmy Pedro, a legendary judo competitor and coach. He represented the United States at four Olympics in 92, 96, 2000, and 2004, winning a bronze medal at two of them. He medaled in three world championships, winning gold in 1999. He has coached many of the elite level American judoka, including Kayla Harrison, Ronda Rousey, Travis Stevens, and many others. Plus, he's now my judo coach, along with Travis Stevens. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Jimmy Pedro. What is the most beautiful throw in judo to you? I think Uchimata. It's the one that seems to have the most amplitude. A person goes the highest, you see a leg swing through the middle, the person doing the throw there's a leg swinging through the middle. The other person definitely goes head over heels, flat on their back. It's probably the most dynamic, pretty judo throw there is. Okay, so it's a single, you're standing on a single foot and you're raising your other foot in the air and it's a forward throw, which means your back is facing the opponent, but they kind of both fly through the air and twist through the air. Correct. Yeah, so how does that throw work? What are the principles behind that throw? Is one of those throws that people can kind of understand how to pick up another human being in sort of trivial ways, but the Uchimata to me never quite made sense, like why it works. There's a cork, there's a twisting motion, there's some involvement of the hip, but it's not really a hip throw because the hip is not all the way over, so it's a very confusing throw to me. Can you say something for once? It's probably one of the most difficult throws to learn as well because it is so complex. You do have to stand on one leg, balance on one leg, swing your other leg through the middle, hold your opponent up in the air, and it's hard to make that contact with upper body to your back. You have to turn your back on the throw as well, so how does it work? It's definitely sort of a throw where you need to start pulling your opponent's upper body towards you, so their upper body starts coming towards you. Your legs go towards them as your body starts to go into the throw, so your head is going to go left, let's say. Your legs are going to go to the right. Your partner is going to start to lean towards you, and just as you start to get there, momentum coming forward, your leg is going to sweep up underneath theirs, pick them up onto your hip, and then the finish of the throw is a twist. A lot of times, the good judoka will leave their feet when they do the throw, so both bodies are in the air together, and then the thrower comes down on top of the person being thrown. All four feet are in the air. Correct. There's just this unstoppable force that's towards you. You're all in the air. You're basically doing a roll together. Correct. Okay, so who to you is the best uchimata? Who has the... besides yourself? I'm not going to lie. There's plenty of guys that do uchimata a lot better than I do. You do have a nice video about the uchimata online, but who is a great practitioner of the uchimata to you? Right now, Shohei Ono, who's two-time Olympic gold medalist. That's his favorite throw, and there's tons of highlight videos on the IJF and Judo Fanatic showing how he does his uchimata, and it is quite different than everybody else's, but it's unstoppable. When he comes in, nobody stops it. He's won two golds in a row at the Olympics. I think maybe in the last eight years, the guy's lost two matches. He's just incredible. At a very competitive division, I guess 73 kilos? Yep. Okay. Then three-time world champ, too. Is he the greatest of all time to you? The only reason why he's not is because Nomura is a 60-kilo player. He was three-time Olympic champion. Nomura, I mean, unless Ono's going to stick around for another three years and win again here in Paris, then he'd match what Nomura did, but three-time gold medalist in Judo in a lightweight division, that's pretty spectacular. To you, being able to win a championship, world championship or Olympic medal is a measure of greatness. It's not like you have some people who are not as accomplished, like Koga or something like that, but just the beauty, the moments of magic, the number of moments of magic is the highest, even if it's not championships. I think you have to go by that because there's so many phenomenal Judo players that have come through the system, have spectacular Judo, have won countless major events, but the ability to pull it together, right, at those magical moments, the pinnacle of the sport, the world championships, the Olympic games, and proving that you can do it time and time again makes you unstoppable, it makes you the best. There was a guy back in the 70s and 80s by the name of Fuji, and he won four world championships back to back, and back then, the world's was every two years. So here he was, a four-time world champion, that's eight years at the top of the sport. He never won an Olympic medal. He never went to the Olympics. So there's a guy who missed out on Olympic greatness, but was arguably the best competitor back in that period. By the way, same Fuji as Fuji? Right. Really? Okay. Wow, I didn't know there was an actual guy at Fuji. Our brand is named after the mountain, Mount Fuji, but this is a different guy, his name was Fuji. All right, well, history rhymes. What about Teddy Renner, 10-time world champ, I think, two-time gold medalist at the Olympics, two-times bronze medalist at the Olympics, probably the most dominant judoka ever. Is he in the running? What do you think about that guy? I think he's a freak of nature, Teddy. If you look at the size, just how big he, how tall he is, how big he is, how physical he is of a specimen. I sat next to him on a bus and his legs are literally the size of my waist. When you sit next to him and just look at the size, he's a big man. So obviously to win 10 world titles in the sport of judo, that's almost an incomprehensible feat, two-time Olympic champion. Again, that puts him in one of the maybe 10 or 12 people to ever do that in the history of the sport. So he's definitely got to be in the running for the best. But technically, I don't think he's as technical as some of the other in terms of pure judo finesse technique. He's powerful, he's explosive, he's dominant, he's strong. Teddy also grips really, really well, which makes him that much tougher to beat. Because a lot of times heavyweights, especially in the heavyweight division, a lot of them just grab the gi and they go man to man and judo to judo and take shots at each other. That's why a lot of them end up getting beat. But Teddy's in control. Positionally, he stays in really good position and he controls his opponent the whole fight. So they really don't have a chance against him. He doesn't give them a chance to beat him, which is why he's been so dominant. But he's not really stalling. He does have a really nice Osorogari, this backward trip, outside trip, in case people don't know. He has just technically pretty good throws for heavyweight. Heavyweights can be sometimes messy with their judo. He's pretty technical and clean in the execution of his big throws, but a lot of that probably has to do with the dominant gripping that he does. It's not defensive gripping, it's offensive gripping, but the dominant gripping. 100%. He controls the grips, he controls the movement of the match as a result of that, and then he creates his own openings. So I mean, for a heavyweight, phenomenal technique, yes. And what you said, messy, I'd like to call it sloppy. A lot of the heavyweights tend to be sloppy. They fall on the ground a lot. It's hard to move somebody that weighs 350 pounds. It's hard to get that body moving just with a simple pull motion. So he's definitely found a way to do it, but he's also, I don't know, six foot eight? He probably weighs 140 kilos. He's a big boy. But he had this winning streak of just, I don't know how long, but over 100 matches. And he lost at this Olympics that we just went through, the 20, I don't even know what to call it, 2021 Olympics? I don't know the proper terminology. Tokyo 2020 is what they call it. Tokyo 2020, all right. So he lost to Tamerlan Bashev. I mean, it's always sad to see a sort of greatness come to an end. It's like Karelin in wrestling and Greco-Roman. Did you shed a bit of a tear to see greatness go or is it just the way of life? What did you think about sort of this dominance, this run of dominance being stopped? I think, I mean, it's obviously sad to see LFC and champions succeed, especially people that are good people. And I think Teddy's a good person. I think there's some arrogant champions that everybody would like to see lose just because they don't want to deal with their personality. And I think Teddy's a very humble champion. He's a people's champion. I think he's been privileged and he makes good money from the sport of judo and the French Federation has taken care of him well. So he's a lifelong judo icon. So it's sad to see somebody like that get beat, especially when this could have been his third Olympic title and just put him in infamy. So it was sad to see, but I think every athlete goes through it, right? I mean, it's just, that's what the Olympics is all about. The great ones fall sometimes. Especially in judo, it's like so, like the margin of error. I guess the other question I want to ask here is, in your sense, how difficult it is to not lose for so long? It seems like in judo, like a little mistake and it's over. There's no coming back and Ippon means it's over. So how difficult is that? It's hard to stay that dominant without question. First of all, when you are the entire world is training against you just to beat you. They're studying every single movement. They're studying patterns. They're trying to break it down and find a flaw in your game. So everybody's hunting for you when you're the best in the world, especially at the Olympics. That's the one to beat you at. So everybody's focused on you. And then there's an incredible amount of pressure on that athlete to perform. You carry the flag for your country. When you're in opening ceremonies sometimes, all spotlight is on you. And it's particularly hard when things don't go well early. In other words, when you're expected to win and then all of a sudden now you're in a hard fight and it's not going the way you want, that pressure, the one who's the favorite feels the pressure the most at the Olympics. And that's why I think the other ones are able to win it. I've actually never gotten a chance to listen to Teddy Renner sort of explain ideas behind his judo. I wonder what his mental game is like because I think his English is pretty not very good. And I just haven't seen good interviews, but it's always fascinating to... There's certain great athletes that are also great thinkers and speakers like the Satya brothers in wrestling. Again, not meaning... That's on my to-do list, 100%. I'm going to Dagestan and talking to them because they're brilliant. But to be able to sort of... Maybe after retirement to think back, what were the systems involved, both on the technical, the training side, and then the mental side? Because to stay that dominant, just like you're saying, everybody's studying to beat you. And the heavyweights are just these powerful dudes. To be able to control them with your game and the game that everybody knows is coming is... I don't know. I don't know what's behind that, but there's got to be... It feels like the mental game is exceptionally important. I think a lot of people underestimate just how important that side is. Being mentally prepared for victory, mentally prepared to be the best, to stay the best. There's nobody that's weak-minded that can accomplish that. It's 100% confidence and belief in yourself. If we take a big picture view then, not necessarily Teddy Renner, but if you want to go from the very beginning, from day one of Judo class to Olympic champion or Olympic medalist, what does it take to become an Olympic medalist in Judo from start to finish? How many different trajectories do you see, or is there some unifying principles? I think a lot of it has to... Your journey is going to depend a lot by where you're from. So a path that an American might take versus somebody who's from Japan or somebody who's from Europe. There's two very... Three very distinct paths, right? Because in Japan, it's part of the culture. There's a system of excellence. There's elementary school Judo, there's junior high school, there's high school, there's collegiate, there's Olympic. Much like our wrestling is here in the United States, right? It's very similar. There's youth wrestling, there's high school, there's NCAA, and then there's Olympic wrestling. When your country is a factory of producing athletes at the highest level, then all of those top athletes typically go back into the sport and there's professions for them. They have an opportunity to coach at all those different levels. And just the level of their game and the expertise that all of them have, even down at the elementary level, make their skill so solid. And as a coach, in that situation, you can just sit back and watch who stands out as opposed to, I think in America, I guess, you would need to craft. You don't get to choose from a thousand people, a few people that naturally stand out at the age of nine. You have to actually, whatever the natural resources you're given, craft them into a champion. So if we look at that, the American way, where you just have a person with a smile show up to your dojo, says, I want to be an Olympic medalist. What process do you take them through? The odds are really insurmountable. It's a very, very high hill to climb. And there's only a few people and there's only a few coaches in this entire country that really understand that process. And they can help people reach that level as it's been proven, right? Number one, you certainly have to have a solid base, a fundamental base of an expectation of what the training is going to be. And it has to be a level of professionalism very, very early where you're teaching all the basic judo moves, all the basic fundamental movements, posture, gripping. Well, maybe gripping doesn't come in so early in the game, but throwing methodology, movements, ne waza position, standing fundamental throws, and I think most importantly is really the work ethic. Just the way you're going to train, the intensity you're going to train with, the ability to, you know, mindset of going to tournaments constantly. In order to compete with the rest of the world, our young kids need to be tested a lot when they're young. They have to be put through adversity because they don't get put through adversity in training because you don't have that many good training partners. So you get put through adversity in competition and then we see what your weaknesses are and we continue to make improvements on those. But the journey is, it's long and until they're kind of at the teenage years, they're going to have to pretty much stay domestic, right? Because they got to go through life as a normal kid, but they've got to be training in the dojo at least, you know, five days a week. You know, sometimes they might want to get, you know, an extra technical workout in or doing some base conditioning in addition to that. And then really at the teenage years, that's where we really, we've struggled in America of keeping teens in the sport of judo as well as developing them properly. Because up until around the teenage years, I think the Americans are on par with the rest of the world in terms of technique and in terms of skill. And then, you know, we've proven we can compete with the rest of the world up until that age. But that's where Japan and that's where the Europeans and the countries that are strong in judo, that's where they put a lot of time, energy and effort is it to the teens, where they have a great coaching staff, they have good training camps with 800, 1000 people going to them every single weekend. When you say teens, what do you mean? Do you mean literally like 13? Yeah, age 13 to 17, 13 to 19. And that's where sort of, that's when you really accelerate your development. So you're saying like in America, when you're young, like before, you know, 9, 10, 11, 12, you stick in judo, you can progress quite a bit. But then I guess the other competition there, if you're into two people, you know, doing stuff to each other in a combative way, the other competitor in America is wrestling. So judo almost primes you, like it teaches you how to be a great wrestler as well. And so then you have to have a hard decision, because you can probably be a collegiate wrestler. You can, you have like a clear plan of where you're going to go if you want to be a wrestler. With judo, that plan is more, is less clear. So you have to be on your own a bit with your coach, that kind of thing. Okay, so when you're on your own with your coach, to me, that's just a fascinating journey, because then it's just like the purity of it. It's a coach and the athlete and the dream. It's all about the dedication, the five, six, seven days a week, competing, what, once a month, twice a month. Okay, and just, but also, you probably don't have that conversation. I don't know if you do. I know you do, saying like, we're going to do this for the next eight years. Right. Do you ever sit down, or do you just do it, take it the David Goggins way, which is like, let's just take it one step at a time. Let's hope we're there in eight years. Yeah, let's hope we're there. Do you like actually- Well, no, like right now, you have to think about, the Olympics is going to be in Los Angeles in 2028. So it's really interesting, now would be the time, and now is the time, to identify talent and get commitment out of students that in seven years, you can make a US Olympic team, because we're going to have a full team. America's going to have 14 athletes compete in those games, one in every weight class. So now is the time, if you're going to go on a journey to the Olympics and stay with the sport of Judo, now would be the time to do it. And so what, you show up to the Pedro Judo Center, and how much drilling, how much technique strategy discussions, how much Randori, or like live sparring, how much conditioning and strength training, how much of all that? How much of cross-training to other gyms or something like that, traveling abroad? Is there something to be said about some aspects of that system? For sure. You need it all, what you just said, you need all of it. And we do do all of that. Right now, we have a young group of kids at the academy, you'll see tonight. Some of them are 14, 13, 15, 17. Are they good? Yeah, really good. Okay. Can't wait. They're right around your weight, so it'll be perfect. They're just young boys, but they've been training hard through COVID. We've been, Travis and myself have been training them. We share responsibilities. They're doing Randori like five nights a week. We have them doing Randori Tuesdays, Wednesdays, Thursdays, Fridays, and Sundays is when they're doing Randori. They're coming to the dojo Friday night and Sunday night to do training. We also have technical sessions for them. They're in school now, so it's a little bit challenging, but they come five o'clock in the afternoon and they do a technical session. Through COVID, they were coming every morning doing technical sessions. What's a technical session? It's an hour of repetitive throwing or repetitive drilling to reinforce movements that we deem important to our successful system. So Newaza positions, groundwork positions where we want them to be in this position and they're going to drill it 50 times with resistance in big groups, doing drills over and over again, picking apart the details of the technique and what they're doing wrong, showing them how to fix it. But now we've done it so much that now we can do a whole drill session with them where they know all the different techniques inside and out, and they can move from position to position really quickly. Do they do it for a period of time, like two minutes, five minutes, or is it like one, do they are actually counting? No, sometimes it's both. So sometimes we do it for reps, sometimes we do it for time. So sometimes it might be as many as they can do in 60 seconds or as many as they can do in two minutes. And sometimes it might just be, I want you to do every position five times. In terms of throws, we're not talking about on a crash pad, right? It's just- We're talking about free moving around the mat and- Just dynamically and just throwing. Correct. How many, because as I was mentioning to you offline, Travis threw me a few times, a lot of times when he was visiting here in Austin. And I just remembered. So there's two things, fortunately or unfortunately in my life, having gotten a chance to train with folks of that level, just cleanness of throw and the power. And it was very nice. I immediately actually enjoyed being thrown like that. To throw a little shade at Craig Jones with his current mat situation is they're very, they were quite thin. And as Travis commented on, and not just the thinness of the mats, but they were laid on like concrete. So I felt, it's like soft until it's not. But being thrown very cleanly, I just felt like this is not going to lead to injury. It was great. It wasn't injury prone. But then as I mentioned to you, when a day or two after, my entire leg, one of them, I guess it's the left leg, was just black, a bruise. It didn't hurt too bad, but it was just the body's gotten soft. So I guess the question I have is, does the body get used to just that number of throws, just over time being thrown thousands of times a month? Unquestionably. Your body gets used to it. So it hardens. It gets really hard, which is why judo is hard to come back to after you've taken a long period of time off, because your body is not used to that impact anymore. I always found out that when I was training judo a lot, it's hard to shed weight and keep weight off, because your body, it develops this layer of protection on itself that it doesn't want to give up. When you're sucking a lot of weight, that means you're frail. So I always seem to retain weight more when you're doing hard judo training, as opposed to losing weight. It's easy when you go out for runs and things like that to shed the water weight, but to actually keep the pounds off was pretty hard. Yeah, the body kind of develops, like you said, a level of protection. What about, Duran, Dory, just out of curiosity, again, I haven't ever had the opportunity to train with folks at a high level. In jiu-jitsu, there's different gyms at different styles, but I've noticed that at the highest levels people can go pretty hard in a certain kind of way where it's more technical, and you're moving at 100%, but the power is not at 100%. It's a weird little dance. You're not really forcing stuff. You're more focused on the right timing, the right positioning of hands and feet and body and all those kinds of things. You're not forcing stuff in the way you would in competition, like really the power. Does that sound similar to you for the way you try to do Randori? There's different styles of judo. I'd say the Japanese style, the technical style of judo is exactly what you just talked about. It's almost like two guys in pajamas. We're using minimal effort, maximum efficiency. We're moving around, and we're trying to feel that movement, and it's timing and finesse and technique and fun and clean throws. When you train in Japan, you can train 15 rounds of Randori, five-minute rounds. That's 75 minutes of straight sparring. You can do that straight in Japan without a problem. You'll get tired, of course. You're going to fall a lot. You're going to throw a lot, but it's a very free feeling, and it's technical as you explained. But then when you go to Europe and you try to do rounds with the Europeans, they are very physical. They don't have that same finesse in their training that they do in Japan. In Europe, you'd be hard-pressed to do eight rounds of Randori in a night. It's so physically exhausting because so much effort is going into just fighting and fending off the gripping system and the power of your opponent. You're physically drained after eight rounds of Randori. It's a much different feel. When you say Europe, do you mean Germany, France, Britain, Russia? There's a kind of similarity to all of those kinds of approaches. The only difference would be Russia, that they do a lot more active drilling, a lot more sequential movement training. They don't focus as much on Randori. You'll do much fewer rounds in Russia during training camps than you would in those other countries we just talked about, France, Germany, et cetera. What about in this kind of American system where you have much less talent to work with? Do you just select whatever works for the particular athletes or do you have something you prefer in your system? You need a combination of all of it. If you're going to win at the Olympic level, you have to be able to deal with the finesse of the Japanese, the physicality of the Europeans. You have to focus on the ground, Nawaza aspect, because a lot of people are weak there in the world of the sport of judo. That's a chance to win. We've sort of developed our American system of judo, at least for the last, I'd say probably the last 20 years, it'd be the American system of judo, which relies heavily on taking the individual and whatever techniques they do, perfecting those techniques and the combinations and other throws that go with those throws, but then implementing and overlaying an American system of gripping, Nawaza, conditioning, mentality, training methodology, in game planning to beat your opponents. I think that's the secret sauce to success for Americans, because there's no way... We don't have eight partners to train with in a night that are going to give us good rounds. We might have two, so we're going to have the same guy, those two people, two times each. Now I have four good rounds. The rest of the rounds, I'm not being pushed to the limit, so we train differently. A lot of times we do a lot of stuff like shark bait. When our athletes are preparing for competition, for example, when Kayla or Travis were preparing for competition, we might only have 20 people in the whole gym to work out with, those two Olympic medalists. Of those 20 people, maybe four of them are Travis's size. Maybe there's only one girl in the room for Kayla. She's got to train with guys. Then the other ones are teenagers that are too weak to train with either one of them. What we would do is just put together four or five people that could give them a challenge, and we'd line them up, and they would do a minute, a minute, a minute, a minute, and they'd do five minutes in a row as hard as they can. That person can go hard for a minute with Travis or Kayla. They can't go five minutes hard, but they can go one minute hard. It made their training much more intense, much more physically demanding. Then rinse and repeat that six times or eight times in a night. They just got 40 minutes of intense randori. The person that was training with them that wasn't as good only had to do six or eight minutes of training the whole night. It's so difficult because then you look at the Russian national team, and you have just the world champions. You even have what is it, Tom Brands and Terry Brands in the wrestling system. You have these people. It's a small group of people, but they're all some of the best people in the world, and they're going head to head. You don't necessarily get a good look of a variety of styles, but just the quality is there. That is missing for people your size in America. That is so difficult to work with, which it makes Kayla's and makes Travis' story that much more amazing. You mentioned picking whatever the set of techniques the athlete is naturally good at or prefers or whatever. How much specialization is there? Maybe if I give you two choices. Is it good to have one throw and try to become the best person in the world at that throw, or do you want to have a bunch of stuff, a variety of throws? For Travis, it was Ippon Seinagi. That was his main throw. From that Ippon Seinagi, he had a variety of other attacks he could do that mixed it up so that you kept people guessing. Maybe it wasn't the Ippon Seoi that was coming. Maybe it was the Koshi Guruma that he did, or maybe it was the Ippon to Osoto that he did in combination. You typically have one main throw that you do. For me, it was Tai Otoshi. For Kayla, it was her Ogoshi. For Travis, it was his Ippon Seinagi. Then you come up with a variety of other throws that you do from the very same grip. Whatever grip you take for your main throw, you want to develop an arsenal of attacks that go in all different directions holding that same grip so that you keep your opponent guessing as to what's coming. If they're just sitting on one technique at the highest level of sport, with the exception of a few, we talked about Ono's Uchimata. With the exception of a few, most of the world catches on pretty quick on how to beat you. There is something to just sticking, making sure you really dedicate to the main thing. For Travis, that would be the main version of his Seinagi. Really making sure you don't forget to really put in the time on that. One way to say it is that threat being dangerous opens up a lot of things. But also, I don't know. I'm just, as a fan, I think it's sad when elite level athletes in all combat sports kind of start taking their main thing for granted. They think, okay, I've figured that part out. Now I'll be working on this whole system on variations, on different setups, on lefty versus lefty, some weird variation. As opposed to, you know what, if you look at some of the best people ever, they seem to have not cared about variations at all. They're just like, literally, they are more like Jiro James of sushi and fine tuning their ear, their ability to detect the minute movements that give you an opening on that main thing. The whole time, you're just waiting for that throw. You're dancing with a little bit of pressure, releasing the pressure, putting the pressure, maybe a little bit off balance, and finding the right moment to strike and focusing on that. Again, maybe that's just a romanticization of the simplicity of that. Maybe it is kind of impossible to do that on a large scale. I don't know if you can comment on that, whether there is some value in still putting in tens of thousands of reps on the main, main thing. Well, unquestionably, that has to happen. You still have to drill your main throw, and you have to fine tune it and continue to do repetition after repetition and throws on the crash pad, or throws on the mat, moving around just explosive movements doing your main technique. You're never going to forget that, and you're not going to put it to the side and not practice it anymore. It still has to be part of your repertoire and part of your daily training, but you do have to evolve. I think that's the sport of judo, makes you evolve. We talk about Koga from before, and we talked about he had a dynamic Ippon Sein Agi that nobody could stop for years and years and years. When people started to be unorthodox and come down his back and cross grip him, and he couldn't get to the lapel, he had to come up with something else. All of a sudden, you saw Koga doing, now he did a Sode, or now he did a Tomoe Nagi, which so he added to his arsenal to keep people thinking, keep people guessing. It's not just that one trick pony. They still couldn't stop his Ippon Sein Agi once he got that grip, but if they stopped him from getting that grip or putting two hands on the gi, he had to go to something else, and that's what he did. Does Travis's or Koga's Sein Agi make sense to you? That weird... Split hip. Split hip. Split hip. I don't know if you know this, but I got into judo because of Travis. I watched him at 2008 Olympics, and there's something about just not the cockiness, but the confidence and just the refusal to quit, the refusal to... That energy, whatever it connected with me, it's like, oh, that guy's badass. I want to be badass like that. Then I also there happened to be a university judo, and I got into it and just fell in love with the elegance and the beauty and the power of the sport. But also, I started to mimic Travis's game, his and Koga's. Then the instructors I worked with, they said, that's the wrong way to do it. I never found somebody that told me, no, that's not the wrong way. There's a lot of ways to do it, and there's the classic way, and you have to understand it, and you have to learn it, but this is not the wrong way. I was trying to find somebody who understands this throw, because it was so beautiful at the highest level, especially with Koga, the way you're able... The quickness with which you can strike, the fact that you can stand on the feet, and the elevation you can get, and the power you can get. It has certain throws, just... Uchimata doesn't look powerful. It looks effortless, but the standing Seinagi with a split hip, it just looks powerful, because you're stepping into them, you're lifting the opponent, and they still have... They're not surprised, they're now helpless. Their feet are fluttering in the air. They're fluttering. Then there's just this pause, and then just big slam. With Uchimata, it's almost like you don't know what hit you. It's like Taito, it's just the same. It's almost like a surprise, like, oh shit, I'm now on my back. I just love that throw, but it didn't make sense to me. When trying to explain it to others, when trying to learn it, it didn't make sense to me how it works. Does it make sense to you? It does. I was born a Jidoka, so I've lived this stuff since I was an infant. I've seen every style, and every technique. The split hip Seinagi is difficult to learn. It's harder to learn than the basic form, but it is powerful, and it does, upon entry, both your opponent's feet leave the mat at the same time. You've got them. Once you enter, you've got them. You just got to finish. You just got to lock them, and turn, and go. It makes sense to me. My dad did teach me how to do that when I was younger. Oh, really? Yeah, he wanted me to do a split hip. We have kids at the school today that we teach the split hip Seinagi, same way, because it is that dynamic. You don't drop to the ground, and roll, and turn. It's not the classic form where you're giving way to your opponent. You go pick the guy up in the air, and then you slam him. Okay, beautiful. Maybe on a small tangent, we're talking about elite level athletes in terms of Randoi, in terms of drilling, for more recreational athletes. I have personally that situation going on, but there's other people that are just recreationally training Judo. How do you recommend they improve Judo? If I wanted to compete a bunch, and do reasonable with a particular set of throws, say the split Seinagi. Do you do the Randoi? Do you use a crash pad to get in reps? What do you recommend? I guess there's two recreational people that we're talking about. One is somebody who wants to learn Judo, and become good at Judo, but doesn't necessarily want to compete, but just wants to get better. I think that there's not enough emphasis in this country on- On just that. On paying attention to that type of student. Everybody pushes them to competition. But in reality, there's a huge audience of people out there that would love to learn Judo, and be very proficient at Judo, and have the skills to go execute if they ever needed it. There's a class, and there should be a program for that athlete. That athlete does not need to do Randoi. The sport of Judo is physical enough where you're picking somebody up all the time, and moving their body weight around the mat all the time. You can get very physically strong, very physically fit. Technically you'll be better than somebody that does Randoi more than you, because if you learn good technique, and you learn the movement, and you learn the feel, and you learn the timing, you'll actually be a better athlete than the person that just focuses on Randoi, who does ugly technique, and wins with force. We have a recreational class at our school where they don't do any Randoi. They have an option afterwards if they want to stay for 15 minutes, or stay for 30 minutes where they can participate in Randoi. But most of the adult students choose not to, because they're already so tired from the other hour class. It's a good workout. Right. They're already dripping sweat. They're already like, if you work hard and drill hard, it's an intense workout. You're exhausted. That's a specific set of program, I should say, at every academy. Then if you want to get good and you want to compete, then to me, once you have your techniques, it's learning how to implement a good gripping system to put yourself in a position where you can always dominate the grips, control the movement, initiate the reactions from your opponent, and then have the opportunity to attack and score. I think that when people train with, or when they jump into a higher level of the sport of judo, all of a sudden, the first thing they say is, I can't attack. I don't know how to attack. Positionally, they don't know where to put their hands. They don't know how to hold the gi properly. They don't understand that they have an inferior grip, and they don't know how to get into better positions so they can attack. That's a big part of the game that not a lot of people really understand. Even for recreational competitors, you really need to have a gripping system. You need to understand the gripping system. If you want to win. Yeah. I mean, if the goal is to go and compete, that's a different story. I don't have fun getting beat up or losing in competitions. I enjoy the- I don't even know if it's the winning or the losing. I think this is what, because I competed a lot in both judo and jiu-jitsu. In judo, it feels like, because I didn't have a gripping system, it feels like you're not even playing judo against the good black belts. They're not even trying because they get a certain kind of grip, and you just can't do anything. I don't have a good answer for that. I don't even know what I'm looking for. It's not even fun. It's not like even losing. It's like, I don't know. It's like you didn't even show up to play, is what it feels like. It's not for, and I think that is a big gap in knowledge, actually, in judo schools, is the gripping part. When you first go out to do judo, the first thing you have to do is you have to grab your opponent. A lot of times, I hear coaches say, get a grip. Just take a grip. Well, sometimes if you take a grip, you're in a worse position than not having a grip at all. That's what a lot of people don't understand. If you hold the gi in the wrong way, your opponent can attack you, but you can't attack him. Why would you ever do that grip if it's only to your detriment? The way you grip does set up what attacks you can do as well. That is a huge part. I'm not saying that you have to be 100% disciplined and always outgrip your opponent and only be able to do throws when you have a superior grip. I'm just saying that to be able to put the grips together with the throws and understand the movements is going to make you that much ahead of the game. If we take a step to our previous discussion of going from zero to hero, going from the early days through the teenage years to winning an Olympic medal. We mentioned a lot of training, the dedication of the training, the competing. What other elements are there? The mental side is visualization, believing that you could perform at that level. What else can you say about that? I think that comes at the highest level. The visualization, the success, that comes at the highest level. I think in the teen years, there's the experience. It plays a huge role in getting to train with other people. As Americans, we have to go train in Europe. We have to feel the European style of judo. We have to understand that physicality. They grip very differently. They put you in very unorthodox positions. If you don't know how to deal with that, you get thrown before you even have a chance to try your own throws. It takes a lot of that experience and understanding what's going on. Then you also need to get that physicality. You need to be strong and hard, I would say, by doing all those rounds with the Europeans. At the same time, you need to go to Asia and you need to train in Japan because you need to feel that free-flowing judo for your technical side. I think that's one of the things that I was able to benefit from. My dad was a coach who said, listen, I've taken you as far as I can take you. I want you to go to the next level. He sent me to England with Neil Adams, who was an Olympic silver medalist and was a world champion, had a great ground game, and was good at gripping, and actually did tai otoshi, which is the throw I did. My dad said, I want you to go learn from Neil. I ended up going to England probably eight to 10 times in my career and spending a good amount of time there training at the Neil Adams Academy. He's now the voice of judo, Neil Adams. What do you make of that guy? Just a brief pause. He's like Morgan Freeman is the voice of March of the Penguins and any other nature documentary. Neil Adams is... There's very few sports that have a Neil Adams, I would say, because he's legitimately, maybe like Joe Rogan is that from mixed martial arts. It's just an exceptionally recognizable voice. He's really knowledgeable. Also the passion is conveyed so well. Many times I'll watch just because he's talking. Who is he, since you've gotten the chance to train with him, to learn from him, who's Neil Adams? He's a great friend of mine. He is? He's a mentor. Like I said, I lived and trained at the Neil Adams Club in Coventry, England since I was like 16 years old. I went and visited him for the first time. He's the one who originally taught me how to do jujitsu and the way that I do jujitsu. I trained with him. He was just retired. He was in his early 30s when I first went out there. I trained with him many times. Over the years, he was a mentor. Great person. He cares about people, cares about the sport of judo. Had a good little club that was a fitness club. It was judo. It was fitness. I used to go there. I'd show up at that place at like 7 in the morning. The first thing we would do is we'd go for a run. We'd either be running mountains or we'd be doing a five-mile run or we'd be doing something at the park. We were doing sprints and buddy carries and all this stuff. Then at 9 AM, we'd have a technical session with Neil Adams where he would, for an hour and a half, we would drill techniques and learn positions. It was no randori. It was that sequential drilling that we talked about before where you're reinforcing your two or three attacks to set up your main attack or if you're on the ground, you're going through repetitions of certain movements. Then I'd spend all afternoon at the club, have lunch. I'd go do my weight training in the afternoon at that place. Then in the evening, we would either do randori training at the Neil Adams Club or we would all get in a car and we'd drive to another location and we'd go train at another club that might be an hour away. There'd be 50 bodies there to train with and each night, we'd go to a different dojo. It would be all day at the club and I'd do that for like three weeks straight. All we'd do was train. Do you know how he became the voice of judo? Do you have an understanding of what his thinking is around how much he dedicates himself to just commentating on judo? I imagine the amount of research required, but also just psychologically, just the excitement he has in his voice. It takes work to do that. Do you have an understanding of what his vision is with that? He's always been a very charismatic, animated person, Neil. Very passionate and loud and funny. The Brits are very funny to begin with. He's very charismatic. I think after coaching, he tried coaching. He coached the country of Wales for a while. He tried coaching stints in other countries. He didn't have a lot of success on the coaching side, developing an Olympic champion. That was a goal of his that he was a world champion. I think it was 1981. He won two silver medals in the Olympic Games himself. He went on to coach for a while and had some political issues with the country of England for a while, and then left England and went to Wales. I think he had a coaching stint somewhere else as well. Didn't have a lot of success coaching in the sport with athletes, not at the highest level. Had a great national team and things like that. He was really good at teaching his technique to others because he helped me a lot. But running a program, I think, was difficult for him. The boy's not listening and not having that same kind of passion and intensity that he... That's why I bonded well with him because I was all in. I went there and whatever he said, I did. I didn't care how hard, I didn't care how long. I just wanted to get as good as I could. That's why he was a good mentor for me. But now in terms of a commentator, he's very cerebral. He loves judo. He researches it nonstop. He's got that great voice and he knows how to bring life to the game. That's what he's done. Now this is who he is. He does judo full time. This is his job. Can I ask you a small before we return to the actual sport, the coaching and the sport? It's a bit of a political question. I did a whole rant before Travis episode. I love Neil Adams' voice. I love watching judo. It's really disappointing to me that the IOC and whoever is responsible, I don't understand this, that they don't make it easy for people to watch the Olympics in replay for years after. I can't watch Travis' matches. They make it very difficult to watch stuff online. So what happened is I uploaded the Travis Stevens episode and we talked about his Ole Bischoff 2012 match. And it was like one minute of a small overlay of the video as we're talking through it, stepping through it. And it got taken down immediately from YouTube, the whole four hour conversation because of that one minute little clip. And the way it got taken down automatically is because the IOC has that video uploaded. It's set to private, but it's uploaded. So they have the video and they choose not to show it. It's not that they're asking for money or whatever. They're just not showing it anywhere. They're not showing it through their own service like NBC Olympics or so on. There's just so many great human stories that the Olympics reveals. They're just not made easily accessible. That's the Olympics charter. We want to, I think the actual line is to ensure the fullest coverage and the widest possible audience in the world for the Olympic Games. And it seems like to me as a fan of the Olympic Games, we're not getting any of that. Do you have an understanding of why that is? Like why we can't watch Kayla's matches, Travis's matches super easily, even if we're willing to pay money for it? So you can't go on the International Judo Federation website right now and watch any of the Olympic footage? No, no, no. So the only thing they have is for certain, for example, Teddy Rene match he lost. Not available anywhere. Really? And that's like a dramatic thing. So the one thing they have is for certain sports at the highest level, like gymnastics, they'll have a highlight, which is the most frustrating thing to me. Because this is what I can't, I'm going to try to prevent myself from going on a rant. But people don't just want to see a two minute highlight of a historic moment. They want to see the buildup where the athlete is standing, the nerves, the fear, the confidence. You see the buildup to the event, say it's a gymnastic, whatever floor routine. Their name is announced, they're walking, the coach, then they cut to the coach and the coach with anticipation, and then go to the athlete. You want the full 10 minute thing. You don't want a two minute highlight of what happened like last second or whatever. It's just like the magic of that full story, like a lifetime building up to those 10 minutes. That's the magic of the Olympics, that both the drama and the triumph that happens in those moments. The fact that you can't relive that, like Travis had a bunch of those. He had a bunch of times he faced world champions, he won and lost, and it's always close, it's always dramatic. Right, right, right. And none of those are available except maybe the one where he beat Armbard, or whatever the submission was, I forgot. The Georgian. The choke, yeah, the Georgian. But most things are not, Usain Bolt, the full races, not all of his races are available online. The race with the Italian winning the 100 meter track race, this Olympics is not only highlight is available from what I saw, I didn't look too hard. The fact that it's not super easily accessible if you're willing to pay money even, but probably should be for free, is heartbreaking to me, because to me the Olympics is some of the best of humanity. Just like, again, the hardship they have to overcome, so the losses are really powerful, because it's such heartbreak, but it's also the triumph. You're losing history. Yeah. You're losing history is what you are, of all the magical moments of your sport, right? It's a sin. I got to blame it on television rights and money. That's what it comes down to. You're talking billions and billions of dollars of television rights paid by NBC here in the United States, and globally, whatever the main carriers are, and all the other nations that are dictating what can be replayed and what can't. It's what it comes down to. I made a DVD or a video when I first retired from the sport. It was called Fury on the Mat. It was kind of my story, right? I did it with a friend who was a videographer, and we grabbed a bunch of my old footage, and Olympic footage. Somebody said to me, you can't use that Olympic footage. I was young, and I had just retired. I said, what do you mean I can't use the Olympic footage? It's not the television footage. It's my buddy who filmed it with his own camera. It's my footage. Exactly. They said, no, if it has Olympics in it, or it's anything to do with the Olympics, the USOC owns it. I said, okay. Well, they said, well, you should get to send it to them and let them review it. So I sent it to them, and I got a bill back. I got a thing back that said, if you want to use this footage, it's going to be like $30,000. I said, man, it's only like three minutes. I spliced it up as much as I could, and I only have highlights in there. I said, come on. I went back, and I negotiated with them, but at the end of the day, I still had to pay like $15,000 just to have a few minutes of footage in my own film. I'm thinking, you wouldn't even have that film if I didn't compete in it. So it was a struggle. This is the difference. You have the same in Jiu Jitsu. There's certain organizations, IBJJF, or like Flow Grappling and Flow Wrestling. I understand. I think when it's a business, it might make sense. First of all, you should actually be good at being a business and making money, which is why for me, the IOC doesn't make sense. It should be accessible, but it would cost money. I can't buy it. Would I have to email them for this footage and pay $30,000? Yeah. No, but the question is, the way you run a business is you make that frictionless. Whatever the money is, $30,000 or $30, you make it frictionless and easy to pay that money. But anyway, I understand why that might be the case with Flow Grappling, but to me, the Olympics is a special thing. For sure. It's like you said, it is history. Even the world championships don't compare. I understand they're really important, but Olympics is history. The stories should certainly belong to the athletes if they want to do like Fury on the Mat to do their own story or like on a podcast to talk about the most tragic moment of their career. Do you have a sense of how that could be fixed or no? The only thing I could think of is you'd have to go to the Olympic Committee. The US Olympic Committee is the place I would start because the US controls the worldwide market when it comes to television. We pay the most for our television rights. Our sponsors pay the most for their rights to be associated with the best team in the world, which is the United States. So all the money starts here. I got to believe there has to be a way to get that footage that should be accessible to the sports themselves. I'm surprised it's not, but if it's not, then it's because of dollars. It's because people aren't... The sport itself is not willing to pay enough money to have it on its... Accessible to its audience. It's too cost prohibitive for them to do it. No, but I think it's also unfortunately might be some mixture of incompetence and just an old way of doing things because there's a lot of money to be made on television rights where you live show the event, but what's not being leveraged is the huge amount of money that could be made on the replay. This is what people don't understand is do you know how many times, just the tens of millions of times that people watch individual events years from now. You watch all the videos on YouTube, they're still getting plays, hundreds of millions of views on stuff that happened 10 years ago, 15 years ago. That's really powerful and there's a lot of opportunity to make a ton of money. For sure. So it's not that they're necessarily greedy, they're also just not good at being greedy. I get what you're saying. It's not the traditional... Think about it though. It's not traditional for television studios. It's non-traditional to go to online streaming, to online access to information. It's not hard, right? Because everybody's doing it now, but it's not typical. So it requires for the IOC to operate outside their comfort zone. Well I definitely hope that's the case. Since Travis's video got taken down, it's obvious they have it. They have it on their YouTube channel. So it's like I hope that they will just release it. For money, for whatever, but release it and have that history not be erased. It'd be wonderful if athletes could buy. Even if you could buy your own footage, you can't use it commercially, but you can buy your own matches and have them available for yourself or package the footage. It'd be awesome. Thank you for that. It was quite heartbreaking for me. I wanted to talk about it a little bit. Let's go to you as an athlete real quick. You represented the United States at four Olympics, winning a bronze medal at two of them. Who or what was the toughest match or moment you had in those years? Maybe a moment that defined you, that you remember as being particularly defining in your career. I would say the bronze medal match in Atlanta in 96, because up to that moment, the United States team had not won a medal, had not fought for a medal in the games. We're on our home turf. It was my second Olympic Games. So I had competed in 92 and I had won two matches and lost in the third round in Barcelona. I didn't make the podium. I lost to a Japanese guy from Japan. But the gold, silver and bronze medalist at that Olympics in Barcelona were all guys that I had beat. In fact, two of them I was undefeated against in my entire career, the Brazilian and the Cuban I had never lost to. So that's when I knew I was capable of being on the podium at the Olympic Games. When 96 came around, I was 25 years old. I was fairly in my prime. I had lived in Japan for six months. My technique was at a high level. I was amongst the best in the world. I lost at that Olympics to a guy from Mongolia. It was right before the match I was supposed to fight against Japan. So I was anticipating the match against Japan and I got beat by the Mongolian. So that was a letdown. But the match for the bronze in front of the hometown crowd, all of my family, all of my friends, everybody who had ever helped me in the sport were in the stands that day, including all my teammates at Brown University that were on the wrestling team and little my uncles, my aunts, everybody was in the stands. So it was like the Jimmy Pedro day. And I'm getting goosebumps right now talking about it. But it was a match against the Brazilian for the bronze medal. I had beaten the Brazilian like two or three times before that. I found myself down in the match. He actually countered me. I came in my tai otoshi and he was waiting for it and he countered me and he scored a yuko against me. So I was losing the fight, came down to about the last minute in the match and I was just tucking in my gi and fixing my thing and gathering my thoughts together and the whole crowd just started chanting, USA, USA, USA. And I literally got so much energy. I walked out there. I grabbed the guy, I came in my tai otoshi again. He stepped off the tai otoshi. I threw him with duchimata, free pwn. I won my first Olympic medal in front of the hometown crowd. Everybody went bananas. The United States judo team had our first medal from the Olympics. It ended up being the only Olympic medal we won at that games, but it was like a magical moment that defined my career and solidified myself in history where, hey, and now I get to step up on the Olympic podium and I'm Olympic medalist. And to me, that was my defining moment. And after that, I was sold. Like man, I had to go back to the Olympics again. I want to win a gold medal. I want to do, I want this feeling all over again. I don't care if I have to wait four years. Let's, let's do it. In your career, like moments like that, do you think you love winning or hate losing more? So do you live for those moments or are you more driven by just how much you hate losing? So in order to be a champion, my belief is that you have to hate losing more than you like winning, hate losing more than you like winning. But I live for those moments when you do win. And what excited me the most in my career, in my, when I was competing was I loved being in the finals. I love the spotlight being on me. I can't think of too many times in my career. Of course there were a few, but there weren't too many times where the chips were down, like the lights were on and I didn't win. Like it was, I might've lost early in the day and didn't make it to the finals or didn't make it to the medal rounds. But like in my career, I have a ton of golds. I have a ton of bronzes, which means the lights are on and I won. And I have very few silvers and very few fifths. So I either lost in the early rounds and didn't make to the medal rounds in my younger days, or the spotlight came and I really shined. Because if you look, I don't know how many silvers, but there wasn't very many silver medals in my career that I won. You know what I mean? So I just loved that moment. I didn't feel pressure. I love the crowd. I love being in the spotlight. I didn't have, I wasn't nervous when it came to the finals or I knew I was getting a medal. It didn't matter. So it was just me against the other guy and that's how I always saw it. And I just loved that moment. So your dad was your coach. Yeah. You didn't get to meet him tonight. Oh, great. He's kind of a legend in the sport. So how has your dad helped you as a coach, as an athlete, as a human being throughout the years? Number one, my dad is the most brutally honest person you will ever meet in your life. Brutally honest. He will tell you, if you are fat, he will tell your fat right to your face. He wants you to get better. He wants you to be healthy. Yeah. He doesn't want you to die of obesity. It's just the way he is. If you didn't do well, he will not sugarcoat it. He will let you know what you didn't do right. So he's the ultimate litmus test. Yes. Second is he is the most passionate, caring, deep, always thinking about, very cerebral, very like a student of the game. Somebody who helped me immensely in defining my strategy, helping me improve, and always look for what's next. In terms of training, I think that he's probably the most brilliant human when it comes to preparing an athlete physically, not necessarily mentally, physically for success. When all the chips are down, that athlete will be ready that day. He has a system of training and preparing and getting the athlete to peak for performance. You mean like conditioning, like the whole thing? Yes. Okay. I vaguely remember Kayla Harrison talking about her preparation being very difficult. Yeah. That's it. That's him? Yeah, that's him. You go back and ask Ronda Rousey about her career. My dad was her coach. My dad moved her to Camp New Hampshire in Boston, got her up, ran her in the morning, had her downstairs in the basement of his house, training with the weights. We brought a Russian girl in. She did throws on his cement outside with the little crash pad. Nice. Threw the Russian girl 100 times that morning. Then every night, came to Boston to the training center in Wakefield, trained at night, and went back and slept at my dad's house, and three weeks straight before she went off to Beijing. He did the same with Kayla. He did the same with me. His passion is producing athletes at the highest level, and he knows how to do it. Then the one side of my dad's coaching where I think there's a flaw or weakness is on the mental preparation side of the game. He wasn't somebody that was... I don't know if he... Maybe because he wasn't an Olympic champion himself and wasn't a world champion, he lacked the confidence in helping others be more confident. He's more of a, this is what you need to work on type of thing. He doesn't know how to build the athletes up to make them feel invincible. I feel like that's something that I was able to give all of the athletes, to help them with that visualization, belief in yourself, knowing that you're going to win before you step out on the mat, knowing that we've earned the right to victory, seeing success in your mind, having a positive mantra that you, I'm the best in the world, nobody's beaten me today type of feeling. You go out there feeling like King Kong when you step on the mat, that nobody's going to stop you. I think the combination of both of us as coaches, I'm a lot more technical. My dad is good at identifying what they need to do for their techniques and strategy, how to beat opponents and putting game plans together. Combined the two of us made an unbelievable team. He's not going to let the athlete be soft when they enter the highest, the most difficult competitions of their career. On the mental side, what's mental preparation look like? How many years before the Olympics do you start helping an athlete believe that they can win an Olympic medal? I think it's got to be a seed in that athlete's brain, something they want to do. Nobody can quickly get there. It's a long process, but if your goal, if you're a national champion or you've proven yourself to win in some international tournaments and you think the Olympics is a possibility for you, then defining it as, hey, I want to be on the Olympic team, that would be the first step into getting ready. I always make them put it on paper. If it really is your goal, then you show me that it's your goal and put it on paper and commit to it. I want to be Olympic medalist. I want to be Olympic champion. I want to go to the Olympics. World team member, maybe junior world team member, whatever it is, we walk before we go to the highest level. But if the goal is to go to the Olympics, let's accomplish these other things first. Because if we can accomplish these other things, then we're on our way to getting to the ultimate goal, which is the Olympics. For somebody like Kayla, for example, she didn't say that she wanted to be Olympic champion when she first came here in 2005. We wanted to become national champion, then we wanted to be on the world team, then we wanted to be a world medalist. Then our sights were set on the Olympics or the Olympic gold. It's having those clearly defined goals that are attainable. They should be a reach, they should be a stretch, but they have to be attainable. They can't be just a pipe dream. But once you put it to paper and you think it's achievable, then it's mapping the plan to get there. Is there a daily process of visualizing yourself as an Olympic champion or national champion? Yes, it is. You should do it either every night before you go to bed or before every training session or after every training session. One of those three times it should, or first thing you wake up in the morning. Because it may be to help some people, it motivates them to go do what it is they're supposed to do in the day. But the process of visualization is, to me, is closing your eyes for a few moments. Your brain works really, really fast. It's actually picturing the day in its entirety from start to finish. From the moment you wake up and you step on the scale to the moment you have your breakfast and you go through your morning routine. Live the day that you're going to have at the Olympics. Whatever it is you're trying to do, let's say the Olympic day, for example. Picture yourself making weight. Picture yourself, who you're around, eating your breakfast, maybe saying a few jokes, laughing. This is a real day. Make it real. Yeah. Going back and packing your judo bag for the day, getting on the bus, driving to the venue, feel what it's like walking into the stadium for the first time, going to the warmup area, seeing your drawer up on the sheet, who you're going to fight that day. Watching yourself warm up, go through your warmup routine, walking out of the chute, into the venue, going to do that first fight. Picture the moment of throwing your opponent, coming off the mat, high-fiving the coach, getting ready for your second fight. Live the day from start to finish and make it as real as possible. All the way to the moment where you've just won and you're raising your arms in celebration, you're bowing, you're hugging your opponent, you come off the mat, you hug your coach, you're running around the stadium with the flag, you stepped up on the podium, you heard your name, Olympic champion, Jimmy Pedro. You heard the moment, the metal being put around your neck. Picture the people coming up on the podium with you, arms around them, taking the pictures. The more real you can make it, even before it ever happens, when you do that enough times, I feel that pathways get created for you so that when your body gets to that moment, and I've been here before, this is it, this is my moment, this is what I've pictured my whole life. I'm not nervous because I've seen this, this is going to happen. I believe it's possible. And I believe the athletes that do that and make it real enough that when they get to that moment, they go right through, there's no hesitation. This is what, this is meant to be, this is my destiny, this is why I did everything I did versus the ones that don't think about it ever, but just kind of like hope. It's not real to them, it doesn't feel attainable. They don't believe it's possible, they haven't committed to believing it was possible. Without that commitment in yourself and that belief, it can't happen. And one thing that, I talked to Travis a bit about this, you probably worked with him on the details of what you're talking about, but he said that you should really focus on visualizing the sensations you feel. So, say if you're drinking coffee or something like that, you're not thinking about observing yourself from a third person perspective drinking coffee. You're thinking of how your hand will feel when it touches something warm. You try to replay the actual sensations you would feel. It sounds kind of strange, but meaning you really want to put yourself in the body as you would experience those moments, as opposed to watching yourself on TV experiencing those moments, really be inside. So that means sensations like how does it feel when you grip a gi, how does it, you know, the sweating, just the sensation of sweat, like rolling down your forehead or whatever, like all of those actual feelings. When I explain it to you, I guess my body has been through it so many times, both in my mind and in reality, that it brings back all of those same emotions. I start to get goose bumps, my armpits start to sweat, like I'm living it if it's real. I'm reliving it now, but when you're going through the visualization process, it has to be that real. The smells, the taping of the fingers, like the more colorful and the more real you can make it, the more believable it is. So I've been doing this kind of thing, just having listened to you enough for other stuff in life, so let's see if it works. But do you see this kind of visualization being useful for other things in career and all those kinds of things? Oh, 100%. 100%, because I just know with my own life, my own experiences, like my wife sometimes says to me, she says, well, where do you see yourself in like, you know, five years from now? And five years ago, I had said to her, you know, I want to have my own business. I want to have, you know, this is the amount of money that I'm hoping I can make in a given year. Like you have to have goals for yourself. Like is this, if you put out there like, okay, I want to make a million dollars in a year, that's a big number. Like for me or for the normal person, like that's a really big number. You know what I mean? Like it's not, especially when you're not making that much at the time, it's a super big number, right? So having those goals for yourself, like it won't happen and it's not possible unless you dream it's possible. And think that it's possible. And then it doesn't magically happen. And maybe it doesn't happen in five years, maybe happens in 10, but at least you're on the path to getting there. You know what I mean? And I said, I want to own my own business. I want to control my own destiny. I want to be my own boss. I want to make my own decisions. Like these are the things that I told her I wanted to do. And now I'm at that point, you know, where, you know, I work for myself, I have my own company, I have partners obviously, but like if I want to pick up and go somewhere for a week, I just do. I don't have to ask permission to do it. That's what life, freedom, right? That's what I'd like. And all of it starts with a dream. And the same with my dojo. When I first opened, so I ran a dojo for a long time and I only had 60 students always, like 40 to 60 students had fluctuated. And I sit there and I said, why can't I get more people on my door? So I hired consultants to come in and look at my business and say, why? And they came in and said, well, this place is really intimidating. Like if I was coming in off the street, the first thing I see is this big Olympic champion on the wall and I see this training that's going on and these guys are flying through the air and landing hard. And as a white belt, you're telling me that's the class for me? Like no way, I'm not going to do that. So like I listened to these people and I said, you're right. And you know, the training was hour and a half, two hours long. People can't handle an hour and a half or two hours training when they first walk in the door. So I had to restructure all my programming. I had to look at the way I was offering my curriculum at my school and I had to make levels for everybody. Like here's my four to six year old class. Here's my six to 13 year old class. Here's all my beginner classes. They don't mix in with the advanced people. And I had to learn how to make it accessible for everybody instead of just the people that wanted to train hard. And then the challenge was, okay, if you can have a lot of people in your dojo training, it's a recreational school. You can't produce champions at that same school. That's what I was told. So then I got all my black belts together and I said, listen, this is my vision. This is what I want. I want to have a club that has over 200 judo only athletes. No jujitsu, no karate, nothing. Judo only. I want over 200 people. And inside of that dojo, I want to have Olympic champions and I want to have recreational. Like little kids, five and six years old, older guys in their seventies training. I don't care. But I want the spectrum of recreational and I want Olympic champions. The only way to do that is to take your instructors and say, you're going to do this, define the roles, who's going to be the recreational coach, who's going to be the competitive coach, how do we separate these programs? And lo and behold, that was my vision that I shared with all of them. And that was back in 2006. And by 2012, we've got Olympic champion Kayla Harrison. We have over 200 people at the school. We have a successful thriving business, but it doesn't happen without that vision, a plan and believing that it's possible. Believing that it's possible. I don't know, but I personally have on top of that, almost like very specific visions of a future. Like, I don't know what, cause I don't want to give actual examples. Cause for several reasons, one of which is just people will, as they often have, they often will in your life, they'll just laugh at it a little bit. Like that seems silly. And I don't, I'm very hesitant to share certain things like that with people because they'll, I mean, I'm with Johnny Ive, who's the lead designer in Apple. Like, you want that dream, that little flame to not, people will put that flame out too easily. Even people that love you. So I have very specific kind of visions, like maybe for Travis, it would be like a specific opponent or something like Ole Bischoff, like very specific, very specific situation of what's going to happen. Not just like, I want to be Olympic champion, but very specific, like almost silly situations. Yeah. Like the dynamic between Travis and Ole Bischoff or something like maybe visualize that for me that helps because it makes it all real, even more real. It's not like some big goal, like a million dollars or something like that, which is also really important to have because you can measure it and so on. But the, it's just like you belong in those situations. Just believing you belong there. It's not the full- It could be you. Yeah. Yeah. For some reason, that really helps me, the little details. Sure. The visualizing. Most of them are almost a little bit funny. Like the focusing on the funniness, it's the mundane-ness of it helps me a lot. And all the people that have done great things, they're just human too. Correct. And I think a lot of people overestimate who others are, right? And sell themselves too short. Because at the end of the day, everybody started- Like everybody else, really. I mean, we did. We're all inference. We couldn't walk. We couldn't talk. We couldn't do anything. We learned along the way. And I think that's the one thing that I realized is that, and I tell this to my athletes, but I also tell it to my recreational students, nobody is better than you are. Nobody. Unless you allow them to be. If you really want something to happen, then map the plan, believe in yourself, decide. And know, full out, you're going to fail a lot. You're going to get beat down. You're going to have losses. You're going to have struggles. And I think that's the one thing with social media today is that everybody sees everybody succeed. Nobody posts a picture when they're on the ground in failure, losing. Everybody sees when you broke your arm and you had to go through rehab, whatever it is, had your injuries and you're on your couch watching TV and you are suffering and you are... Everybody has really, really dark, bad moments in their life and defeats and losses and suffrage. And it's only at the end, after they've recovered from all of that, they've reclimbed up the mountain and they've gone to the pinnacle that you see them on social media with the medal. But everybody else struggles and was human and failed many, many times. And convincing yourself that you're capable, I think, is the first start with everything. Do you need people in your life that believe in you or should most of it come from within yourself? I think most of it has to come in from... It certainly helps, but it has to come from you first. You have to be driven. Other people can help you define where you want to go and help you get there and encourage you and can support you, whether it's resource-wise or with connections and they can help with that path. But that first part has to come from you. It has to be your passion, your desire, your commitment to yourself. You're the one that's going to ultimately make all the sacrifices to do it. It has to be your decision, not your parents, not your spouse's, something that you're really motivated to do. Let me ask you about Travis, Kayla, and maybe a few of the other athletes you've been involved with. So first, Travis. Travis Stevens, Olympic silver medalist, three-time Olympian 2008, 2012, 2016. What makes Travis Stevens great? What makes him so successful? What makes him unique in your mind as an athlete through all the hardship he had to overcome, through his weird-looking Sanagi that eventually worked out nicely, through the full richness of his personality? In the context of all the other great athletes you've coached, what makes him special? His fight. Travis has fight. And the first time I ever saw Travis Stevens was in, recognized him, maybe I had seen him before as a younger boy or something, but actually recognized him is I brought a group of young kids to Italy for a competition in a training camp. And it was this program called U23 Elite. And I handpicked 20 kids to go to this event. And it was the first time I coached an international team. I had never seen Travis fight before, compete, train, anything. And during this competition, he's an 81 kilo player. I think he was maybe like 18 years old, 17, 18 years old. And it was a really hard European event. And I think Travis won three matches and he lost two. But what stood out the most to me was the fight he had in him. He was scrapping every fight. He scrapped hard. He wanted to win more than any of them. He didn't win, but he wanted to win more. And I noticed that right away. And then I also noticed that after he lost his second match and he was eliminated from the tournament, I saw how disappointed he was in himself. He actually thought he was supposed to beat those people, even though he was like 17. And he's fighting against grown men that are a high level judo, much higher than he was. And I said to him, I said, hey son, don't worry, man, you got a long career ahead of you. I'm glad you're disappointed, but there's so many things you don't know and so many skills you don't have. The fact that you were able to hold your own and scrap like that, you've got a good future. And I remember calling my friend, Jason Morris, after that tournament. And I said, hey man, did you ever hear of this kid, Travis Stevens? He says, no, why? I said, man, that kid's got some fight in him. And I said that. I said that to Jason at the time. I said, that kid's got some fight in him, man. He's pretty talented. And that's how it started. But so I saw that in him when he was young. But the other thing was, Travis, there's no such thing as hard work to that guy. If you tell him to put his head through the wall and that's how he wins, he'll go put his head through the wall. He'll do whatever it takes for him to do to achieve success. And he hates failure more than he likes winning, 100%. He always has. He punishes himself when he doesn't do well. He makes himself work harder. He goes and just abuses himself when he doesn't succeed because he's so heartbroken and disappointed in himself. So that's a trait that I think all of the athletes that I work with closely, they all had that same trait. They hated losing more than anything. They would break their arm. They'd fall on their head. They'd rather get hit by a car than lose a judo tournament. As a result, then they all had fight and they all were willing to train, they were willing to listen, and they would do anything for victory. Within the rules, I'm not talking about taking drugs or anything like that, but they'd give 100% of themselves for victory. And Travis was somebody that when he was down, he found a way to get better doing something else. If he couldn't do standing, that's when he started jujitsu. He couldn't go on his feet anymore. He couldn't stand up and train. I might as well go learn jujitsu and get good on the ground, right? Because I can't. So he always found a way and no matter what obstacle was in his way, he just went around it. So what about the, it'd be interesting to get your perspective, because I know Travis's perspective is just the number of injuries. What do you make of the perseverance through all the injuries he had to overcome? Specifically you just observing this creature that you've coached. He seems to not see the injuries as a problem. He just like you said, head through the wall. It's like when we're talking about injuries, he doesn't even see the injuries themselves as the problem, because he thinks that the injuries, you heal back stronger. I forget the exact quote, but he said like, my body is now less injury prone than most of anyone else. Because I've already broken everything. I've broken everything. And it's just grown back stronger. Because I asked him something like, do you regret sort of pushing your body to all of those places that resulted in those injuries? His response was like, no, I'm stronger now. So I don't know if that's justification, but that certainly describes a mindset that, yeah, head through the wall. It's almost not dramatic. Look I got this injury, I'm so brave and special for overcoming this injury. That's part of the job and he gets the job done. But that job involves a lot of injuries. One of the talks I gave Travis and that team at that particular tournament was at the very beginning of the camp after the tournament, I said to them, listen, my vision, I shared my vision with them. I said, my vision is in seven years, because that was 2005, I said in seven years, I want to have a US team that steps on the mat, that is ready to kick ass. And in order to get there, all of you guys can be a part of this team and part of this process, but in order to get there, you guys have to be the first ones to practice. You have to be the last ones to leave, because we have to work harder than the rest of the world because we're up against all odds. I said, I am sick of America being a laughingstock of judo and being the first round, easy match, warmup for everybody else. I said, if you get injured, you're not going to be on the side with an ice bag on taking off rounds and then get back on the mat the next day and tell me you're okay. If you can train the next day, you can train today. So there's no injury. The only time you'll leave in this dojo is if the ambulance has to take you out of here. And I do think subliminally, Travis bought into that message and heard that message then and said, if I'm going to be a champ, then that's the way I'm going to do it. And he did. And he embodied it, he lived it. Man, there were many times in Europe where I said, dude, just tape it up. I'll go off to the side, just take the day off, take the rest of the day off. You're beat up. You can't do it. He said, no, no, I'm going to tape it up. I'm going to tape it up. I said, no, you don't need to right now. And he said, no, sensei, I'm doing it. The ambulance isn't taking me out. It's just my wrist. It's just my ankle. It's just my wrist. It's just my ankle. Yeah, I love it. Yeah. So the other really big thing is you comment on a little bit is the weight cut. So early in his career, he was 81 kg and that was presumably not so difficult. But later in his career, he is 81 kg and it's becoming more and more difficult. So that's the other thing with him. So I've known a lot of really, really tough people at the highest levels broken by the weight cut. Like that can break the toughest minds and it doesn't seem to have broken him. And he delivered on it often on like insane weight cuts. So just as a coach, what do you think about his particularly his mind and the challenge of the weight cut? It was part of his process. It was part of his way of getting ready for battle. Suffering. Yeah, it really was. And if I'm going to suffer this much, then I'm going to make my opponents pay for all the suffering that I went through to get here. That was his mindset. Later on in his career, you're right. A lot of times, Travis, he would never step on a scale until he got to the tournament. And even when he get to the tournament, he'd weigh like 90 kilos. He'd show up at the tournament nine kilos over. I'm like, you have to... But it was just an expectation of making weight. Not making weight was never an option for any of our athletes. And Travis knew it. And he said, as a professional, my job is to make weight. If I don't make weight, he was never going to allow that to happen. And he was never going to allow us to come to him and say, hey, I told you. Losing wasn't an option. Not making weight was not an option for him ever either. But a lot of times, he wouldn't even... He'd be nine kilos over on the plane going over to the tournament and have to make weight three days later. And he didn't break 86 kilos until the day before the tournament. He had five kilos over the day before. That was his way. But he would do three workouts. Wake up in the morning, work out. Then he'd eat. Then he'd work out in the afternoon. Then he'd eat again. Then he'd work out again at night. And then he'd reward himself. Hey, I worked out three times today. He'd go have a Mountain Dew or a chocolate bar. And then next morning, he's back up to 87 and he would never touch weight until the morning of WANs. He wasn't on weight for more than like five minutes. His process will break a lot of people. So the fact that he got the job done is... Not just the job done, but every single time he got the job done. And I made those athletes fight. We would fight in Paris. We would do a camp for a week, double session camp for a week. He'd be seven kilos over, have to fight the next weekend. We're talking two or three days later. Not only did he make the weight, but he did a grueling training camp twice a day and then cut weight and then fought again. Then did another camp for a week in double session training camp and then fought on a third weekend in a row. And our athletes went through hell. All of our athletes went through hell because on the tour around the world, they fought in every event. They did every camp. They fought in every event. Whereas most of the other teams like Japan comes in and fights in Paris, then they go home. They maybe do a camp for three days, then they go home. They don't stay in Europe for four or five weeks straight and fight in every tournament. And when you get to Germany, the Germans skip the French Open. They skip the camp in France. They're just getting ready for Germany. Our athletes already had two competitions, two training camps, three weight cuts now. So they're not 100% when they fight in Germany, but that's all part of the experience they need, the training that they need that they don't get here in this country. And all of those were just preparation for our world championships or our Olympic games. So by the time our athletes got to those tournaments, they felt so strong, so rested, so like, man, this guy that felt like a monster in Germany feels like nothing today because you're fully rested now. But part of the challenge is because the American team is smaller and more, I mean, just smaller is all the different places you go to do the weight cut, to do the diet, to do the preparation or the recovery, that process changes every time. So you basically have to improvise a lot. You show up to a hotel and how you do the weight cut, you don't know, and the different weather conditions, it's not, it's like, what is it, Rocky versus Drago, right? So you have to just improvise. And that's also a fascinating part of the American judo story, which is like, you have to improvise more. Well, it was funny because it was 1990 and it was at the Goodwill Games, right? And it was a US Olympic Committee type event, and so we're on the bus with the swim team. And it was me and Jason Morris on the American team, and we're going to the judo competition, but we're on the bus with the swim team. I'm sorry, we're going to the venue where we're staying. I remember being by ourselves with no staff, no manager, no coach, we're just by ourselves going to fight in Russia, right? And the swim team's on there with their full sweats and their staff and their managers. And I heard the girl go, I'm sorry, this was 1994 because it was in St. Petersburg, Russia. So I heard the girl on the team, she goes up to the coach, she goes, coach, do you think you can send the massage therapist to my room at 10 a.m.? I'm feeling kind of jet lag. I looked at me and Jason, we looked at each other like, she's scheduling a massage? We don't even have a staff. What the hell is going on here? What a difference in sporting different sports within the same country. I mean, not to romanticize things, but that you do represent the spirit of the Olympics when you're kind of the improvisational nature of it. Because it is just you, you and sometimes you and the coach and just pure guts and you against the world with no money. The warrior spirit. The warrior spirit. How did it feel like when he, after being in two Olympics, beating some of the best people in the world, facing some of the best people in the world and just barely losing, what did it feel like to you as a coach to see Travis Stevens win the silver medal? Electric. First of all, in 2012 in London, it felt like somebody died. I'm not going to lie to you. The Ole Bischoff match? No, just seeing Travis not finish on the podium, period. In the Ole Bischoff match, I thought he won regardless of who won and who lost. He just left everything he had on that mat, 10 minutes of, probably it was a 20-something minute match, but 10 minutes of fighting actually. He left everything he had. He wanted to be in the Olympic finals. He wanted to be Olympic champion. When he didn't get that opportunity, he lost everything. He drained himself. He cried for 45 minutes straight. I couldn't regroup him. I couldn't get him up. I said, Travis, you've got to stop your crying. You've got to get off the floor. We've got a bronze medal fight. If you don't recover, you're not going to perform well. He just didn't care. It was gold or nothing. When he walked out against the Canadian boy, he had beaten the Canadian, I think, at that time, he had beaten that Canadian every single time except for that bronze medal match. He just didn't have the fight in him anymore. He'd left it all in the match, in the Bischoff match. To see him come back with zero, we just had a team where his best friend, Marty Malloy, won a bronze medal. Then the day after Travis fights, Kayla Harrison goes and wins her first gold medal, our first ever gold. We have a gold and a bronze. His training partner wins a gold. His best friend from growing up wins a bronze. He has nothing. To see him for four years go through hell, literally all of his injuries, every training camp, and then forget the humiliation because every time any reporter ever came to my dojo, they want to talk to Kayla. She's the Olympic champion. Who is this Travis guy? Who is this guy? He didn't medal. He's not that important. Up until you get to the right before the Olympics, now they talk about he's an Olympian again. Yeah. But up until that point, and then every little kid sees Kayla's medal, oh, Travis, yeah, you went to the Olympics. Where's your medal? How did you do? I took fifth. I didn't place. It's the lowest of low, every day having that constant reminder. So four years later, when that guy, mentally, he was ready. Physically, he was ready. That was the best and strongest Travis Stevens that I've ever seen and I've ever felt. Because I had to get on the mat and do some drills and stuff like that, and try to defend down bars because we didn't have a lot of bodies in Rio. I was like, my God, he's... I said after one of the practices, this is the strongest I've ever felt that guy, before the competition. So physically, he was ready. Mentally, the morning of competition, I said to Travis, I looked him in the eye and I said, we're ready to go over to the venue. I said, are you ready today? He just looked at me like he goes, I am going to shock the world today. That's what he told me, I'm going to shock the world today. I said, all right, great, let's go. So we go to the venue and every other athlete was just nervously doing repetitions of Uchi Komi's. You could see sweat coming out. You could see all this nervous energy going through their body. Here comes Travis Stevens. He's got these big, goofy headphones on. He's got a tank top that says USA on it. He's got the swim trunks that say USA, that have shiny letters that glow in the dark. This is in the middle of the Judo hall where all these athletes are warming up for their first match. He's dancing around, doing this loose warmup, almost like a little kid at an amusement park whose dad said, yeah, go play. It was like he had waited four years for that moment. He was so relaxed, so focused, so relaxed and couldn't wait. It was like a caged tiger. If you're coming out of the chute to go step onto the mat, was like this tiger that you were just letting out of the cage and he just go. Now's your time to go fight. That's what he did that whole day. When he beat Chirik Ishvili in the semis and choked him out and won that fight, there's nobody with the exception of maybe the guys in the American team, there was nobody in that stadium that expected Travis to beat him. Nobody. Yeah. Like he had smashed Travis, I don't know how many times before that free poem, like in the first minute even, it wasn't even a fight. It was great game plan. He's the world number one at the time too. World number one at the time, world champion, carried the flag for the Georgian Federation walking into the games, most dominant 81 kilo player in that weight class for quite some time and man, we just had his number and Travis was ready to go. It was so cool. It was so awesome. We had already won, Kayla had already won her second gold, the way the event went and Travis winning that was like icing on the cake for our team. That was the best performance we've ever had in history. It's awesome. You mentioned Kayla. She is one of, if not the greatest American judoka ever, two time gold medalist. 2010 world champion. 2010. First senior worlds. First senior worlds. What makes Kayla special? What makes her so great? What made this champion? It's combination of a lot of things. One was obviously Kayla's mental toughness, right? To overcome what she overcame. This is a girl who, let's, I don't want to say forget about the sexual abuse, but the fact that she had to go through that in life and learned how to compartmentalize that and keep that off as a separate part of her brain and forget about it and move on. That took an incredible team to help her do that and my dad was a huge part of her accomplishing that. For people who don't know, we should comment and say that Kayla had to go through trauma in her earlier life through sexual abuse and had to overcome that through the whole process of becoming a champion as well. Because she had zero self-esteem, zero self-worth. She was at the lowest of lows and didn't even want to be on this earth, right? So she was traumatized obviously for, and getting her the right help and surrounding her with the right people who could help her get through that and be by her side as she's getting through that and letting her know and reaffirming that she's doing the right thing and she made the right decision and she should have zero guilt and this doesn't define her. It happened to her, but it doesn't define her. What defines her is what she does from now on. And then rebuilding that person to become who she became. I think the mental toughness is a big part of it, her mind. But then as an athlete, she's a lot like Travis. She's a warrior. She's a fighter. My dad always jokes with her, he says, you're a workhorse. You're not a thoroughbred. We're not going to treat you like a thoroughbred, right? You're a workhorse. So you're going to work. And the way you're going to get bigger and stronger is you're going to work harder and you're going to keep... And she came to us when she was only 15. So at that time, we got her with a really good strength and conditioning coach. We did all the core Olympic style lifting. As her body was developing, she was getting stronger every single day. And then she had the luxury of being on the mat with... At the time, I was still young enough to train and be on the mat. And I was around her weight class and Travis was able to train with her. And we had all the top US athletes at the time training here at my school. So she got the benefit of all the best guys to train with in the country. And her doing all of those rounds, night in, week... Every night, every week, every year, compiled with the best, highest level she could as a girl. She got the strength, she got the technique, she got the... And then she had the coaching on top of it with my dad being on her as working her out and having the wherewithal to develop a strategy and a plan for her. Because when she first came here, she competed at 63 kilos, which is 138 pounds. At the time, Ronda Rousey was also training here and she was 70 kilos. So if Kayla was struggling making 63, so the only way to... Obviously the only way to still compete is to move up. But my dad said, well, if you move up, then you're in Ronda's weight. So let's skip that weight and you're going to go to 78 kilos. And he told her, listen, you're going to go up two weight classes. She looked at him and was like, that's 172 pounds. And he goes, well, I don't care. You're already struggling making 138, you weigh 150, what's the difference? We put 20 pounds on, go to 170. So that's why she jumped two weights, because she passed Ronda. She went to the weight above so she could make the national team and she had a chance to go to the Olympics and all that, because we envisioned Ronda staying around until 2012. And that's also like a long-term vision because you kind of grow into that body then over time. Correct. So you can dominate, you can learn what it's like in that weight class. You can learn to dominate that weight class, excel and then dominate. People that cut weight too hard, too long, they forget about technique because they're only worried about losing weight. They're always tired in training. They don't give 100% effort. They're not getting better. She now is just focused on getting better at judo and getting bigger, getting stronger, getting more powerful. So I think given her that purpose and that, that was a great call. What are some memorable or maybe the most memorable moment, Kayla Harrison moment to you as her coach? Not the most, perhaps, let's say, what are some memorable moments? Everybody hears the good ones, right? So everybody knows she won the world championships in Tokyo in 2010. She was our two-time Olympic champion in 2012, 2016. I'll never forget those moments, right? Because they're historic. One of the biggest moments that I like sharing this story with everybody is that in 2010 in January, Kayla was still a developing athlete and we had a local tournament in New York. It was in Brooklyn, New York. It was called the Sterrett Cup. And I knew that at that tournament that two of the Canadian girls, they were like ranked 15th or 20th in the world. They weren't superstars, but they were tough players. Both of them I knew were going to be at that tournament. So I said, Kayla, we're going to go to this tournament. You're going to compete against the Canadian girls, get some good experience, figure out what you need to work on, and then we'll go home and work on some stuff. Well she went to the tournament. There was only three girls in the weight, her and the two Canadians. At that tournament, she lost both fights. So this is January, 2010. She lost both matches. She was competitive, but certainly things she needed to work on, it was good development thing for her and for us. It also opened her mind to say, oh man, because she was already a junior world champion at the time. But so now there's another level. This is a senior level, right? You got to go up another level. Here's two girls that aren't even medalists that are beating you. So now there's more work to be done. And so I like telling that story because everybody sees the champions in the greatest moments. They don't see them when they have bad days. And could you imagine being O and two? You feel like a failure, right? But 10 months later was Tokyo 2010. She went from O and two at Starrett New York to world champion 2010 in the motherland in Japan. I mean, that's an amazing turnaround. And that's only possible if you put the losses in their proper context. You don't let it destroy you mentally and just keep moving forward. Correct. That's so funny. So you were there 2010 at the Starrett Cup? Was Travis there? Yeah. I made all those. We fought at every local... The mentality of our team was no tournament is beneath us. If our goal is to go to the Olympics in the world and win, there's no tournament that's beneath us. We're going to get experience. We're going to fight. We're going to learn. We're going to compete. We're going to get better. I actually just as a funny little side, I was there. I competed. Really? This is one of the earlier tournaments, like the beginner division. Oh no, I actually did black belt division too. That was one of the... Actually, yeah, I remember that. That's when it was so early that I thought... I was also really strong at that time, just physically power lifting stuff. So I thought it'll be good experience to also do a black belt division. I remember it must've been actually Travis's division, which is funny. Is Legere brothers? Yeah. Harry and Gary. They are super good and they're super dominant, but I think Travis faced one of them and beat them. I don't know. I just remembered... It's funny how there's just like these little roads that later reconnect, but yeah, there's some incredible people there. I saw obviously the positive things and it's interesting that Kayla's story was also intersecting there. That was one of the lower points for her. Another story I like to share is that you have to know your athletes, right? You have to really get to know what they're thinking psychologically, mentally, what's going through their head. Another story was in Tokyo. It was 2015, the Tokyo Grand Slam. So we had Kayla face off against almost all the top girls in her division. She had beaten everybody going into the 2016 Olympics. But at the 2015 Tokyo Grand Slam, there was a girl from Japan that she hadn't fought in a long time and she lost to the girl last time she fought her. So it was something we wanted her to beat this girl going into the Olympics so that she knew she could beat everybody. And it was a first round match and it was going to be tough for Kayla, right? It was going to be a really hard fight. And she had won a bunch of tournaments in a row leading up to that. So her confidence was really high, but at the same time, she didn't think she needed this fight. And she showed up to the tournament and she said, I don't think I can fight today. I've got a stinger in my neck. You know, I've got a stinger coming down my neck and I'm kind of sore. She didn't tell us. She went and told the trainer. She walked around. She's holding her neck and me and my dad were like, what's up with her? And then so, like, I don't know, maybe she doesn't want to fight today. I don't know. Right. So all of a sudden the trainer comes up to us and she didn't come to us. The trainer came to us and says, you know, I really don't think it's a good idea that Kayla fight today. I mean, we looked at him and like, well, your opinion doesn't really matter, does it? Right? Like what's up with her? Yeah. Well, she has this thing in her neck. It's like a pinched nerve and there's this and that. We talked, I said, is there a risk of her getting injured? Like is this pain or is this risk that she's going to get injured and she's going to set her back like long time in her career. He says, no, she's not going to get injured. Just a pinched nerve, a little pain she's going to have to deal with. I go, okay, well, can you fix the pain? He says, yeah, I can do this and that and I can give her a shot and the pain will go away. I said, okay, then do that. And so Kayla comes up, she goes, didn't the trainer talk to you? I said, yeah, he talked to us. Well, he said, I can't fight. I know, but we already talked to the trainer and- I love it. He said, you're good to go. She looked at us like, and then we had to talk to her and say, listen, you're not injured, you're in pain because we just came from a camp. I said, you're in pain, but here's the deal. We want you to fight this girl. Why don't you go out there and beat this girl, period. I don't care, but I want to know that you can beat this girl. This is why we came. This is our last hard tournament before the Olympic games. This is what we want from you. And lo and behold, she understood. They gave her a quick shot. The rest of the world thought we were crazy making her compete. And then she went out there, she fought, didn't even know she was injured. You know what I mean? She just went out there, she fought the tournament, she beat the Japanese girl, she ended up going through the whole tournament. She took a gold medal. She won the event. That turned out to be a great confidence builder. And that kind of sets you up for all the chaos that can happen at the Olympic games. And it tells you, if you can beat these girls when you're not 100% and you're not at your best, you're physically beat, mentally beat, imagine what you're going to do when you're fresh. Well, when she was going into the Olympic games, there's a lot. She had the mental game- Down. Down. Down. There wasn't a girl in that division that thought they could beat Kayla going into those games. Not a one. They just looked at her and went, no, not happening. Yeah. It's great. I mean, she's a great Olympic champion, two-time Olympic champion. But there is something that she's commented on, which is she's suffered or went through depression after winning her second Olympic gold. Why do you think this happens? You often hear stories of great champions becoming depressed after the Olympics. There's a lack of purpose afterwards, right? Because you've done in life what you set out to do. You've had a goal every day you woke up. You knew what your purpose was. You knew what your day looked like. You knew why you were doing that. And all of a sudden, you won and you got all the fame and you're all happy. But then you wake up and you go, now what? I don't have a next. And also because there was nothing for her, there was no path set out for Kayla that said, okay, you're going to become an ambassador, a global ambassador of judo. The IJF is going to help pay a salary. The USA judo is going to give you a salary. Here's what we want you to go teach children. We want you to go be an ambassador for women. We're going to fly you around and whatever it is. We're going to give you a job and here's what you're going to do if you'd like to take it. There was nothing for her. I remember doing the interview at the Olympics with her and they said, are you going to compete in the next Olympics? And I said, no. Like why? She already two-time gold medalist. What does three-time gold medalist do for her? Nothing, right? Doesn't motivate her to do it again. They said, are you doing MMA? I said, no. Why would she do MMA? That's ridiculous. She doesn't need MMA. She should be able to make a living off of what she's accomplished in this sport for the rest of her life. But what happens is, and what most people don't understand is, once you say I'm retired, I'm no longer competing in the sport of judo, you don't get a salary from USA Judo anymore, which she was getting. I think she got like $72,000 a year from USA Judo at the time. You don't get a stipend from the Olympic committee anymore, goes away. Your sponsor, like the New York Athletic Club was a great sponsor for her for all those years. In fact, she could have never been the athlete she became without the support of the NYC. Because I talked to them when she was 15, I said, hey, I got a girl that's really good. Someday, if you invest in her now, I promise you she'll pay back for you. And I remember the day she won the Olympic gold, I called the guy up, I said, hey, I told you she'd be... But they can no longer give you stipends because you're not competing and representing them anymore, so that goes away. All of your sponsorships and all of your money that you would make from your TV commercials or whatever, that didn't happen for her after the Olympics because Judo is an obscure sport. So she didn't have any opportunities for that. At the end of the day, she has no revenue coming in. How do you live? You get a bonus of 25 grand from the Olympic committee or whatever for winning a gold. But aside from that, you're not going to live on that money. So no purpose, no goal. What am I going to wake up and do tomorrow? I don't know. So she has no direction. And then at the same time, she has no money coming in. So everything shuts off. So now it's like, where do you turn? What do you do? And that leads to being depressed because, yeah, even though I've accomplished all this stuff, I'm kind of lost in life. What's next for me? And I guess you just have to ride that out because when you're a great human being, a great champion, life has a way of helping you find a way. I mean, she's in mixed martial arts now, but she has a lot of stuff going on. She adopted her sister's kids. So she's their legal guardian now. So that is her purpose, raising these kids and making them part of her family. She's fortunate enough that she has enough money that she can do that and she can give them a good life. I'm going to ask you to start some trouble. But I heard that she said somewhere that she can beat Khabib Nurmagomedov in judo. What do you think? To be honest with you, I mean, I don't know what level of judoka- Yeah, I don't know. I don't know what level he is. But I do know that that Russian system respects judo immensely. What I will tell you is this, I trained with Kayla and I was an Olympic medalist and a world champion in judo. And granted, I was older when I trained with her, but you have to go as a man, you have to go 100% or she will smash you as a man. And I could tell you that if Khabib doesn't do a lot of just judo, doesn't like gripping and doesn't understand, if he can throw, that's one thing. But if he doesn't really understand judo at a high level, she will throw him. She would beat him in a match, in a judo contest, not in a mixed martial arts contest, not in a wrestling contest, not in a submission contest, in a pure judo match where he cannot grab legs and he has to grip up and just throw, I'd put my money on Kayla. Unless he's, if he could go placed in the nationals in Russia, he would beat her. But if he's not at that level of judo, he's more like a brown belt or he's not a high level judo player, she will win. I saw her take some of our best juniors in this country, some of the guys that went and medaled in our senior nationals. I've seen her smash all of them in judo. Now she's not going to do that to a Travis Stevens, she's not going to do that to a senior national champion or Olympian in our sport, but she will go toe to toe with every other male, black belts or not. Speaking of Khabib and Russia, Vladimir Putin, I don't know if you all have heard of him, he's the president of Russia, but he's also a judoka. Have you gotten a chance to see him do judo? What do you think about his judo, if you were to analyze it? I'm actually really good friends with the Russian Federation. The guy in charge is Ezio Gamba, he's an Italian, he's a mastermind behind their success of the 2012 and 2016 Olympic teams. 2020, he suffered from leukemia, blood cancer, so he wasn't part of their 2020 program, but he was part of 2012, 2016. That whole national, the Olympic team in 2012 came to our studio and lived here for a month in Boston. They went to school in Boston, I brought them to my house, they had three Olympic champions. Three Olympic champions. Oh my God, what a team. They all came and lived here in Boston for a month. They wanted to be part of experience America type program. So I've seen all of them with Putin in Russia at their national training center working out with them and taking falls and doing judo with him. It's hard when you're older to move in judo. I was at a high level and I'm now 51. It's hard for me to move like I used to. So at his age, he's got to be what, 60, between 62, 65-ish? He moves really well for somebody that's that age and probably hasn't done very much judo for the last however many years. So it tells you at one point, he had to be a really good judo player. Yeah, he put in a lot of work at some point to develop the technique. You can tell when a great judo player, even if they haven't practiced it, even if they're up there in age, just the way they move, the way they go in for a seoi nage, the way they go for a particular throw, the way they do foot sweeps and all that kind of stuff, you can just tell he's good at judo. That's kind of fascinating. It's fascinating to see political leaders. I've gotten to interact with quite a few for whom judo was a formative experience in their life. That's so interesting that for a lot of people, judo played a big part in their life, early development. It's similar to if you served in the military. There's just something about judo. As a martial art, it's not just the technique. So yes, there's something about gaining confidence through becoming aware of what your body can do, the artistry and the skill of it, also the power of being able to dominate another human being with technique, but also the formality, the discipline of just honoring the tradition of it. So all of that mixed together somehow creates memories that define you as a human being and you carry that forward throughout your life. I've just been surprised to know how many powerful people internationally have in their heart and who they are, judo. For sure. That's the core of it. It makes you the human being that you are. It really does. It becomes a fabric of... The people that stick with it, that stay with it. Because it teaches you so many lessons. It's so memorable because of what you talked about, the tradition. But it's also, you grow with other people and you learn from other people and you experience things with other people. It's such a hands-on sport that it's very memorable. And people love it so much. Right now at my dojo, we have four generations. Somebody that did judo with my dad had a kid who trained with me, who loved judo so much had a kid. That kid was now in his 20s who did judo and now has a kid who's two or three or four that's coming to my toddler program at my school. We're talking four generations. And they all love the experience so much and what it did for them and their lives that they wanted the next generation to also experience the same thing. This is a tricky question, but if people are interested in judo and want to start learning it, in the United States, there's thousands of jujitsu schools, for example. Is there advice you can give to people interested in judo or maybe to jujitsu gym owners? How do you get judo as part of your life in America? Well, if you're fortunate to live near another dojo, a place that has judo locally, then that's your best opportunity to learn. Is to go learn from another school. Unfortunately, sometimes the nearest dojo might not be for two hours or three hours away from where you're at, which is an obstacle. You're not going to do that. So, I mean, Travis and I did start the American Judo System online. It's at usajudo.com and we've broken down every single judo technique to the very, very basic elements of just movement. So we teach every technique of how you do it mechanically with just your feet, then how you incorporate your hands and your feet together, how you do it in all directions, moving forward, sideways, backwards, how to then introduce a partner into the movement, how to do basic uchikomi or repetitions with a partner, then moving with a partner, then how to throw your opponent static, how to throw your opponent. So basically from the very foundation of the movement all the way to the most advanced level, we've documented this through separate videos. And we've taken now, I think, 12 to 15 of standing techniques combined with a whole bunch of groundwork techniques. And our goal is just to continue to build this platform out so that anybody, anywhere can learn online and can ask questions. We have a live training class every couple of weeks. Every two weeks, he or I answer questions online for our members. Ideally what we'd like to do is have a standing curriculum for jiu-jitsu instructors that want to learn and become black belts in judo. Here's how, these are the techniques you need to know. This is how many reps you need to do. This is how efficient you need to get at those techniques to become certified as an instructor or become a black belt. And eventually have an online promotion system where anybody, anywhere can just submit videos and show us that they can do those techniques. And obviously we'll have people review them. And this is a dream and a vision, but we've already started the platform. We're about to do a collaborative effort with USA Judo where all of their members will start to get access to this platform as well. And if we can get that influx of money and people on the platform, it'll allow us to hire and grow it faster. So you also want to do certification there. It's not just instruction. Correct. That would be amazing. Yeah. I mean, for me personally, sort of, I mean, mostly in Austin, Texas now. And there's a few judo schools, but it's not really. And it's just one of those cities that doesn't quite have, I mean, there's a few, it's basically just like a few random judo people that kind of gather together a couple of times a week, but it's not a system, a dojo, an instructor integrated into a jujitsu school or not. The problem with most judo dojos right now is that most of them cater towards the competitive side. Also a lot of them do it recreationally, meaning this isn't how they make a living. So they're there three nights a week or they're there five, even if they're there five nights a week, it's still only one junior class and one senior class and that's it. And it's one size fits all. Doesn't matter what level you're at. It's one size fits all. So you can't get out of the training what you're looking to get out of the training. It's whatever the instructor's teaching. You know, and you can't learn because it's not at the appropriate level for you. And usually you're pushed into doing randori where you have no choice but to do the randori part of the training. So it's a challenge to go learn. And then a lot of times the schools are old school, so they go make you do falls for a half hour. They make you do things, maybe you're a jujitsu person who knows how to fall already, but you haven't proven it to the judo instructor and they don't break the norm and say, you still have to fall for six months, which turns a lot of people away as well. So it's like any business. If you don't deliver on your customer's expectations, you're not going to have very many customers, which is the way it is now. So a lot of people who listen to this, but in general in the United States practice Brazilian jujitsu, which has a lot of similarities to judo as obviously its origins in judo. How would you compare the two arts from the perspective of people just interested about both arts? Do you recommend people who do jujitsu get into judo? How can it enrich their jujitsu? How do you compare the two arts, the actual practice of it and why it might be useful to you? I mean, I think that judo is a hard sport for adults to do. It just is, especially people that haven't fallen in a long time, aren't very athletic. I think about my own experience, right? Other than judo, when did I ever do like a forward somersault? Maybe when I was in grade school, right? That's the last time I've left my feet was in grade school. Most people haven't got off of a chair or a couch. They spend eight to 10 hours a day either working behind a computer or sitting on a couch watching TV, right? And they're not that athletic and they haven't done anything athletic at least probably since high school. That's their last athletic endeavor, most of them. So you're talking about as an adult that's 35 or 40 wanting to start a sport, judo is a really hard sport to start, especially in today's dojos that don't have a recreational adult program. When it's one size fits all, it's hard. For those people, jujitsu makes a heck of a lot of sense. Good self-defense, it's cerebral where you got to use your brain, you're a smaller person, you have to use technique, it teaches all the same things as judo, but it's a safe way to do it. And because of the validation it has with the UFC and MMA today, right? Everybody knows jujitsu so now they can be part of mainstream society and talk intelligently about what they see on television or what's going on on ESPN today, right? They have some knowledge. So they have an identity. And also there's a good culture in jujitsu where it's becoming a family. The dojo is the family place. You go to feel good, you go to see your friends, you go to get fit and you have a good time, right? So it makes a lot of sense why it's growing. Judo on the other hand, I think is a better sport for children to do. It's more, I would say, fun and interactive. It's a little easier to teach the kids how to do the throwing skills and for safety and things like that. Their body can handle more than the adults can. They're less likely to get injured. It makes them better athletes because it's a lot more three-dimensional in my opinion. So I think there's a good fit between judo can thrive from kids till whatever, high school, college. Jujitsu thrives from that 18 year old up. Right now that's kind of where it is. So as a dojo, you have to kind of focus on the teens and the college, like early 20s, that kind of- Or you need to have, if you're going to be a successful judo dojo, you have to have that recreational fundamental adult program in your school where people actually come to judo, learn the moves, but aren't pushed into randori training and pushed into things where they're uncomfortable and they can't control the situation because there's too many unknowns. You got an education at Browns. You're somebody who's amazing because as an Olympian and an Olympic coach, you've always emphasized kind of balance and education, all of that side of life. So developing your brain too. So you are an Olympic medalist, a coach of Olympic medalists, you're a business owner, so successful in all these domains. So I have to ask, what advice would you give to young people today, high school, judo age, high school, college, undergrad, how to be successful in their career or just in life in general, how to live a life they can be proud of? I think you have to be true to yourself. You have to decide what it is you really want to do with your life. And it's hard because when I grew up, I didn't know I was going to be successful. When I was young, I didn't know I was going to be an Olympic medalist. I certainly did envision myself owning a couple of companies that makes their living exclusively for martial arts or judo because that wasn't really an opportunity when I was a kid, but I've created that opportunity. I would just say that, pick something that you're passionate about. I was stuck in a career before where I wasn't passionate about it. And it was my wife who said, Jimmy, if you can figure out how to make your living exclusively for martial arts, where your brain and your heart and your passion is all towards one thing that you really like, then you'll be successful. And I left the job. I had three kids. I was working for monster.com. I was in internet marketing and I was working for that company, great company, nothing wrong with the company. But sitting behind the desk from eight till five, and then I get to go to judo from six till nine at night, my whole day is tied up doing something that I'm really not passionate about. And she said, if you can figure out how to make money from your dojo and other things judo related, then I think you'll be successful. And so, she's the one that my wife, Marie, gave me that advice and I would give that to others. Find something that you love doing where it doesn't feel like work, something you're passionate about. And if the opportunity doesn't exist, how to make money on it, you can create the opportunity. Be resourceful, figure it out. Don't let anybody tell you you can't do it. I didn't know that I could have a 200 person judo school that only taught judo, because that really didn't exist in this country. It actually charges money like jujitsu charges. We're talking not, there's plenty of clubs out there that charge 10 bucks a month that might have 100 people, but there's not many that with the tuition is $150 a month having 200 people. So, that's a successful business, but it wasn't done before. But be passionate about it, understand you're going to fail, understand you're going to get knocked down, beat up. There's going to be dark days, but you got to persevere. You got to believe in yourself. You got to have a plan. You have to be willing to learn from other people. And that's what I did. If I didn't know it, I brought somebody in to tell me, what am I doing wrong? Look from the outside, what do you see? Okay, great. Then you got to be willing to change. You got to be willing to adapt. I think listening, believing in myself and creating opportunity and the other thing is helping others. Something I always did in my judo life and in my business life. If somebody came to me and asked for help with, hey man, is there something you can do to help me? I'm trying to get this thing started. I'm trying to get this dojo off the ground or I'm trying to run this event series or I was creative and trying to figure out a way to help them make it work. Because if that really was their dream and I could help them do their dream, I felt like that person would then give nothing but good, good comments about us. Good, good. They'll remember it forever. They become like family and they'd be the best advocates for your business ever. And so the kids that I taught at my dojo were treated that way. The people that worked for me get treated that way. The people that my customers that I work with and building their dojos get treated that way. People that ran tournaments, whether it was grapplers quest years ago and helping that guy with a full set of mats for his, Brian Simmons with his thing or any of the gracies. It just became like family and then I just work hard and deliver on what I say I'm going to do. If I say I'm going to do it, I do it. And I think it goes a long way. Well, and I got a comment, so in a small way, people may not know, I think it's still on YouTube. We previously talked many years ago and I remember you were so kind to me and you didn't really know who I was. You just took me as a human being. You welcomed me into your dojo and we just had a conversation on a podcast or whatever the heck you call that thing. And you were just very kind. And you were also just, it was the last conversation I had when I showed up to MIT and it stayed with me. So I resumed doing this podcast, but it stayed with me because you said that I did a good job at this. And people, especially at that time, didn't tell me that. That little act of kindness is probably just a regular part of your day. You had a busy day. It was the end of the day. Just saying that, that was powerful. And that pays off somehow. So thank you for that. Yeah. But it was sincere. It was genuine. I felt like I had been to so many interviews. When it's around Olympic time, there's lots of beat reporters that come out and they're trying to get your time. And they're there because they have to get the story for their newspaper or their television show. And a lot of times those people show up and they pronounce my name wrong. Or they get something wrong about the background. Or they offend me because they call me five minutes before that they're supposed to be there and say, oh, sorry, we're running late. We'll be there an hour and a half. Well, I'm a busy guy too. You were somebody that showed up, was so prepared with your notes, knew everything about the history of what I had done. The questions you asked were intelligent questions. They were well thought out. And at the end of that interview, I was really genuinely impressed. And I wanted to let you know you did a great job because you stood out from the rest. Thank you. Yeah. I mean, for me, it was like showing up to the Mecca. You don't always want to just tell that to people, but you show up. Obviously you're the legend of Judo in the United States. And so that was like Boston is the Mecca. This is where you travel to talk to the great. So the fact that you were kind to me just stuck with me for a long time. So it pays off to be kind to others, to give them a chance. Jimmy, thank you so much for giving me another chance and spending your valuable time. And you've also were kind enough to invite me to train with you today at your dojo. So I can't wait. Let's go. Let's go do some Judo. Awesome. Thank you, Lex. Thanks for listening to this conversation with Jimmy Pedro. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Bruce Lee. I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times. Thank you for listening and hope to see you next time.

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Ryan Hall: Solving Martial Arts from First Principles | Lex Fridman Podcast #169

The following is a conversation with Ryan Hall, his second time in the podcast. He's one of the most innovative scholars of martial arts in the modern era. Quick mention of our sponsors. Indeed hiring website, Audible audiobooks, ExpressVPN, and Element Electrolyte Drink. Click the sponsor links to get a discount and to support this podcast. As a side note, let me say that I've gotten the chance to train with Ryan recently and to both discuss and try out on the mat his ideas about grappling and fighting. What struck me is his unapologetic drive to solve martial arts. It reminds me of the ambitious vision and effort of Google's DeepMind to solve intelligence. In Ryan's case, this isn't some out there martial arts guru talk. This is a style of thinking about the game of human chess, of seeking to define the rules and to engineer ways from first principles of escaping the constraints of those rules. This style of thinking is rare, but is ultimately the one that leads to the discovery of new revolutionary ideas. If you enjoy this podcast, subscribe to it anywhere or connect with me at Lex Friedman. And now here's my conversation with Ryan Hall. You're known as a systems thinker in martial arts, but you also, I think, are willing to think outside the rules of the game, outside of the system. When you're thinking about strategies of how to solve the problem, particular problem of an opponent, whether that's Jiu-Jitsu or in mixed martial arts, what's your process for doing that, for figuring out that puzzle? I would say, I don't know if I have a specific A to B to C process for that sort of thing. I try to do my best to appreciate that I think a lot of the thinking, or maybe not all the thinking, but a lot of great thinking on conflict, on battle, on war, on martial arts has been done already. Not that we don't have to do any sort of background investigation or reassessing of these ideas or axioms that have come down through things like the Book of Five Rings or the Art of War or like Von Clausewitz, even anything like that, really. But is trying to understand the lessons of the past that I think oftentimes we don't take with us problem solving. We pay lip service and like, oh, yeah, yeah, yeah, yeah, a victorious fighter, the great fighter, he knows victory is there, then he seeks battle. Everyone else is looking for victory in battle. Yeah, moving on. And that's why I'm going to double jab and throw my left hand. And I think a lot of times our actions don't reflect our stated belief structure. And I think that oftentimes you can tell what I believe really, or what my fundamental operating system is, based on my actions, whether I'm aware I have an operating system internally, whether I'm aware of it or not, or certainly whether I'm fully aware of it. So I guess when it comes to strategy, I try to think about how things interact. You mentioned systems thinking, and I try to do my best to understand how systems exist. But I think that systems have a fundamental strength and a fundamental weakness. They work how they work. And that's great. But they're readable. So if you are aware, if I am operating on a system of which you're not really read into, then I think oftentimes I can seem like shockingly effective, particularly if my system preys on certain weaknesses, that maybe you're given to. But what happens when you've read the same books that I have? I think that a lot of times that makes me deeply predictable. I think about systems in jiu-jitsu, you know, and a lot of times people think that they're doing jiu-jitsu when in reality they are doing an expression of it. Let's say I'll use, there's the Marcelo Garcia system. There is the Henzo Gracie, current Henzo Gracie system. There's the old Gracie Baja one. There's, you know, the Gracie Academy, classic Gracie jiu-jitsu. There's the art of jiu-jitsu, you know, kind of Atos approach. And, you know, there's some crossover between a lot of these, but oftentimes I think, you know, when it comes to understanding how I'm making decisions and how my opponent is making decisions, I have to appreciate whether or not I'm an end user of something. And I'll use my phone as an example. I was thinking of this the other day and as an end user of my phone, I can't, I have no idea what it does. You know, like Edward Snowden comes up and goes, Hey guys, you realize your phones are listening to you from like, really? What? All right. I believe you. And then of course that, that comes out. But to what extent? I have no idea. What is my phone capable of? I have no idea. I can mess with the font though. I really like blue screens, not purple screens. So like as an end user, I can change some of the bells and whistles that have nothing to do with the underlying source code of it all or how it functions. The same way in my car, I'm an end user of my car. If I do this with the steering wheel, it goes, if I push on the gas, it goes. If I, I know how to fix it when it's out of gas and I had to fix it when it's out of oil and I had, I know how to fix it, you know, when a, when a flat tire comes, but short of that or actually beyond that, I have nothing. So I think that oftentimes, you know, I've been around in Jiu Jitsu long enough to encounter like a new wave of, of like good grapplers. And it's very, very interesting sometimes how they're running systems. They don't realize they're running. Like, I'm like, Oh yeah, I trained at Marcello Garcia's Academy for a long time, you know, and a big fan of Marcello's was a student there, uh, encountered a lot of the, the auto style Jiu Jitsu a number of years ago, uh, been, you know, a very, very, you know, deep into foot locking and leg attacks and whatnot for a long, long time. I understand your system better than you do, or I may, and let's say you understand my system better than I do. That would be a huge issue. That was something that I encountered a long time ago, trying to come up in Jiu Jitsu where I was trying to utilize systems that were created by, let's say Hoffman Mendez or someone else. And I'm basically trying to do what you're doing. I'm just not doing as good of a version of it. So not only am I not doing it well, but I'm entirely predictable. And I think that that can be a big issue. So to come back, I think of systems a lot of times now in terms of, you know, particularly like end user type of systems, like, uh, an iPhone is a really, really fast way for me to be able to do all sorts of things. If you were to take it from me, I couldn't recreate any of that. So you want to be more of the NSA and less the end user. Exactly. Exactly. That way, that way I'm listening to you. You want to be the NSA of combat. That's right. We're watching you pee. But basically, you know, it's, I guess what I would, what I would come back and say is, uh, if you understand how things interact on a fundamental level and what type of games exist and what type of interactions exist, then you can transcend a lot of the, uh, the systems. It's almost like a cook versus if I can make certain things in the kitchen, I can, but I am not a chef. You could give me a bunch of ingredients and I could probably cook not well, but a couple of different things, but a master chef, you know, would be aware of the implications of all of the things that they're doing, you know, extra time in the oven, less time in the oven, putting this, you know, flavoring or spice in, you know, what you're doing with various things. And also they could make, they could turn all of these ingredients into Chinese food, or they could turn all these ingredients into Italian food and they could turn all these Italian food ingredients into chicken, Parmesan, or it could turn into lasagna, but they're not limited to a specific thing because they have knowledge of how food interacts, how, what it does to create taste, what it does to create texture. So to come back, let's take rock, paper, scissors, rock, paper, scissors is built on the idea of a couple of different things. Actually, I'll tell you what, can I, you might, may I ask you a question? Yeah. What's your favorite dinosaur on the same, on three, we'll go one, two, three. T-Rex. T-Rex. Oh, me too. No, we're going to do, man, this is, we're going to be best friends. So it's okay. So what's the first question when you say, Hey, let's play rock, paper, scissors. It's like, Hey, is it rock, paper, scissors, or rock, paper, scissors, shoot. And you're like rock, paper, scissors, shoot. And you're like, okay. Because if we go rock, paper, scissors, shoot. And I'm like, oh man, I got lucky. And I won. Imagine I won a hundred times in a row. Yeah. I'd be luck. It'd be luck. If I was honestly doing that. But now let's say, for instance, I go on rock, paper, scissors, and you go on shoot rock, paper, scissors, shoot. Here comes the rock, right? If you lose, whose fault is it? It's yours. This is built on a parody thing where I don't get to pick second. If I get to pick second, it's like being able to investigate your background before going to meet you. And then I'm like, oh, hi. Oh, I too love the New Jersey, you know, the New Jersey nets, which is a statement that no one in their right mind would ever make when I was growing up. So anyway, you'd have to have personal knowledge of somebody. So anyway, to come back, if you understand how games are structured, you can start to realize that there's huge gaps and huge holes in a lot of the thinking behind all of it. And if you can create the illusion of choice, I'll play one more. If you don't mind, this is one of my favorite ones. I do this in class all the time. Have you seen this before? No. Okay. May I ask you some questions, please? Sure. Okay. Fantastic. I'm scared. Everybody wins. Don't worry. All right. So could you please pick three fingers and tell me what they are? Your thumb. Okay. Your pinky. Okay. And your middle finger. Okay. So could you please pick two fingers? Your middle finger and your pinky. Okay. Could you please pick one finger? I'll go with the middle finger. Okay. Could you please pick one finger? Pinky. Okay. Let's play again. Can you pick one finger, please? Your middle finger. Okay. Can you pick one finger, please? Your thumb. Yeah. Your pinky. Okay. Now pick two more fingers, please? Your middle finger and your ring finger. Okay. Could you please pick one more finger? Damn it. And so I thought that enhanced the illusion of choice. It's the illusion of choice. If I'm asking the questions, provided I ask the right questions, there can be no correct answer. Doesn't mean that, I mean, ultimately, if that's what you wanted, let's say, like, I thought I was guiding you to something I wanted, it turns out that was the outcome you wanted. Now I'm gonna ask the wrong questions. I might not get what I wanted. Oh, by the way, sorry to interrupt. For people that might be just listening to this, that no matter what trajectory we took through that decision tree that Ryan was presenting, it was always ending up with the middle finger, ironically enough. I was surprised. All of us were surprised. We're both winners. Yeah, we all, everyone was. I felt like a winner. All right. So now I'm gonna, now I'll ask some different questions, if you don't mind. Can you please pick two fingers to put down? Your middle finger and your pinky. Sorry. Oh, that's so awkward. That's like the worst finger positions. Okay. Can you please pick, oh, wait a minute. That's, oh, hold on. Yeah. Well, what if you pick two other fingers to put down? Your thumb and your pinky. Okay. My thumb and my pinky. Can you please pick two fingers to put down? Well. Whatever two you like. Okay. Your middle finger and your pointy finger. Ah, okay. Can you pick two fingers to put down? What's the name? Is index finger. Index finger. Why did I call it the pointy finger? It's the pointy one. That's the one we usually point. It's weird to point with your ring finger. Uh, sorry. What? Two more to put down, please. The middle finger and the ring finger. Ah, man. What if you pick my ring finger and my index finger? Yeah. Woo-hoo, I win. Yeah. So even though I'm asking the questions, it's not impossible that I arrive at a conclusion. Yeah. It's not impossible that I arrive at a good outcome for me, but it's no longer guaranteed. I went from a situation where I literally can't lose. Yeah. It's pretty low probability. Right. Super low probability. And the second you realize what I'm doing, you would never let me win. Yeah. Because the ball's truly in your court. So I guess that's kind of what I'm fundamentally trying to put into play almost all the time. Can I ask the right set of questions? Can I develop my understanding-wise and then discipline-wise and then have the courage and the constitution and the discipline necessary, the patience necessary to ask the proper questions and wait for the proper answers? And if I can, assuming the perfect world, I win, period. Yeah. Does that make sense? Yeah, that totally makes sense. So I don't know if you know the more mathematical discipline of game theory. There's something called mechanism design. So game theory is this field where you model some kind of interaction between human beings. You can model grappling that way. You can model nuclear conflict between nations that way. And you set up a set of rules and incentives and then use math to predict what is the likely outcome depending over time based on the interaction given those rules. Mechanism design is the design of games. So like the design of systems that are likely to lead to a certain outcome. And so what you're suggesting is you want to create, you want to discover systems whose decision tree, all the possible things that could happen feel like there's choice being made, but ultimately one of the parties doesn't have any choice in what the actual final outcome is. You're making them feel like they're playing a game too. So it's not like you don't feel trapped. It's kind of like... Well, the best traps, you don't look very threatening. So I'm like, oh, I'll walk over there. I guess that's kind of an interesting thing. When does a lion roar? It's an interesting thing when you watch lions hunting. They don't roar when they hunt. When they want to move you back, they do stuff like that. When they actually want to come and get you, they're pretty slinky. It's like water covered. It's like furry water. And I guess when you keep that in mind, it's funny how... For us, a hobby actually, a brilliant guy, one of my MMA coaches and head coach at TriStar, he brought this up one time. I thought it was a really salient point. He said, let's say we have a million person bracket. It was impossibly huge. Frank Dukes winning the Kumite level, huge bracket. He claimed to knock out 250 consecutive people. And you're like, that is all of Hong Kong was in that thing. And everyone kept their mouth shut. But anyway, that's pretty cool. But to come back, a little improbable, but pretty cool. So let's say for instance, like there's no cheating going on, no cheating going on, and we're flipping coins, right? Someone is going to have an unbroken string of victory through that bracket, which is pretty insane. How many consecutive toss-ups this person won. And then at the end of it all, imagine aliens show up and we go, hey, they want to flip a coin for whether or not Earth gets to continue. They'll be like, oh, I'll do it. I'm good at this. That would be tempting as a person to do. You're like, I'm a lucky guy. Are you sure? Maybe effectively you are. We could argue that effectively you're incredibly lucky. But basically, is that an actual ability? Is that a perk in a video game or is that just this thing that happened? So anyway, how many times are someone... You could go through an entire career, particularly in a fight sport. Well, let's say you get 15 knockouts in 15 toss-up scenarios. Because you see that happening all the time in the fight game, a toss-up scenario. It's not like you're mounted on me and that's not a toss-up scenario. Many, many, many, many, many striking scenarios. A lot of grappling ones, but tons of striking scenarios are dead toss-ups. And somebody wins by knockout. They win five times in a row. Then they lose a couple of times in a row. We go, what happened? You're like, what do you mean, what happened? They were always flipping the coin. And then they win five more and they go, ah, back on track. Can you imagine that? You're flipping a coin. I'm like, heads, heads, heads, heads, tails. What? Tails? Tails, heads again. Oh man, I'm back on it. I'm flipping good now. That's basically what's going on, I think, the vast majority of the time. And then humanity's tendency to see a sign in almost anything starts to present itself. And then we build a narrative in our mind to convince ourselves that we're in some sort of control. When in reality, I was in a marginal situation at best the whole time. Yeah, without having much control, without having a deep understanding of the system. The same story is told in the stock market. With many of these distributed human systems, we start telling narratives and start seeing patterns without understanding actually the system that's generating these patterns. So if we can see the system, that's incredibly valuable. But then you go, well, what system is above all of the systems? I guess maybe physics, maybe something like game theory explains these things. But I guess what aspects of the system can I put my hands on that I can touch and understand? And what am I missing? What's going on in the world all around me to continue to lean on Dune that I don't have? You talk to a blind person about the world, about sight, and talk to someone that doesn't have everyone, who's got coronavirus now, so no one can taste or smell. They're like, this is delicious. Like, is it? So anyway, again, what senses am I missing? Or what understanding am I missing that's preventing me from seeing the dots connect in the world all around me? And I think sometimes if we, oftentimes, at least personally, I've screwed this up a lot. I'm so nose deep in the trench of trying to understand what I'm doing that I can't take a step back and realize that I'm in a forest, not just headbutting a tree. And I may be doing both. Two things should be true at once. But so I would say when it comes to strategy, trying to understand that. But then also you go, well, OK, well, that sounds cool, but how can you actually do that? And then I'd say that's a really good question. Because imagine I say, man, I should fight like Stephen Thompson. I should fight like Wonderboy. He's like, good idea. Go do that. I'm like, not the guy. I would fight like Khabib Nurmagomedov if I could. It seems to work. So anyway, you go, well, what if I could develop, what if I could take my time developing skills so that when these strategies become apparent, they are executable to you? You actually have the ability to, again, to be the person in the arena, be the person required, where there's plenty of great ideas. Like dunking a basketball is a fantastic idea. Alas, for me, unless there's a small trampoline nearby, I'm not the guy. But that doesn't make it any less good of an idea. I just don't, I haven't developed the ability or I lack the ability. So anyway, I think a lot of times, at least when I watch people in fighting, I'll use an example. We're so concerned with trying to win early on rather than develop skills that I'm going like, well, what's the best way to fight with my current set of skills? And usually the path forward is like the barbarian route. Like the, you put on the one ring, take the damage you need to take to hit that guy. And that was something I realized very early on in my MMA career was like, I'm not that good at striking at that time. Not a world-class striker now, but I'm way better at striking than I'm given any credit for because it helps people sleep at night, I think. But I'm serious. But- Yeah, yeah. You're always introduced as like this master grappler. And I'm like, that's nice of them to say that. Maybe I'm not that good at grappling. We haven't even seen that. But the funny thing is where I'm like, just because people almost go like, well, Lex, like, so you're really good at this, but you got to understand like, we're equal, man. Like, I'm good at this other thing. Maybe you're really good at what you do. And I'm just mediocre at what I do. That's also possible. So there's plenty of people that define themselves as a striker that do that just because that's for lack of other options. Not because they're a really good striker. Or like, I'm a grappler. I was a grappler as a blue belt. Not really. So anyway, I guess to come back, if I'm constantly going, how can I win with what I've got right now? I think oftentimes I never take the time to develop the skills that I want to develop. And I also never take the time to develop the strategies that I want to develop. And that has actually been one big blessing of fighting so infrequently, which has been really frustrating as a result of injury and time away. And some of those people being hesitant to get in the game, but it gives you so much time to be out of the trenches and focus on developing your abilities so that now it's almost like developing money. Like you mentioned, the stock market that you can now put in. Imagine you told me Bitcoin was a great idea five years ago, and I had eight bucks. Man, if someone told me Bitcoin was a great idea five years ago, and I had 50K, I'd be like, oh my god, I'd be sleeping in my bed of money that I would then set on fire later if they had just to do it. So due to all the injuries, you've been mining Bitcoin all this time, and now you're a rich man. Well, no, actually someone told me I was trying to mine for Bitcoin actually in a cave. And then I found out recently that mining is like a figure of speech. You misunderstood. Not like a literal thing that you do. But I mean, in my defense, I only do it anyway. English language is difficult. It is. It really is. Next time talk to me, I'll explain. Russian is a richer language. You should learn Russian. I'll help you out. I believe you. Thank you. Can you do a whirlwind overview of your career in MMA leading up to this point with the injuries and the undefeated record, and then what's next? Since we're on the topic. I did my first fight as a blue belt, and I've been training for about a year and a half. I did nine Jiu-Jitsu tournaments in 10 weekends, or maybe eight Jiu-Jitsu tournaments in 10 weekends prior to my first fight in April 2006. I got punched in the face a whole bunch. I didn't realize it was a professional fight and found that out like the day beforehand. That was great. Thanks, coach. It was in Atlantic City, where another place no one ever goes on purpose, so that wasn't great. I got into three, actually three car accidents in the preceding 36 hours before the fight. I had my car totaled. I wasn't driving for any of them. That was great. It was 2006? It's 2006, yeah. You're a blue belt? Yeah, yeah. I've been training for about a year and a half. So you're a blue belt. You're getting... I mean, if you haven't lived, if you haven't gotten punched in the face in Atlantic City. That's true. I mean, I... So these are... I would have loved to have it happen for different reasons. Yeah. But yeah, well, what's funny is, you know, I remember getting punched in the face a bunch, trying to do inverted guard. I won one round, lost two rounds, definitely lost the fight. So you went for inverted... Sorry to interrupt. You went for inverted guard. Can you tell the story of that fight? Oh, yeah, sure. It was three three-minute rounds, which is not a professional fight length, although I don't know if professional fight length would have been any better. It's just more time to get punched. But I found out partway through, I was like... I remember walking back to my corner in the first round. I'm like, yeah, this guy can't hurt me. And he's like, yeah. My corner was my friend Tom and then someone else. And he's like, yeah, I would still encourage you to stop blocking so many punches with your face. I'm like, that's a good idea, Tom. I appreciate that. I'm going to try that. Anyway, I remember I was not allowed to up kick. So I'm like, great. I had no martial arts skills, really, at all. But if I had anything at all, it was jujitsu. It was very, very little jujitsu, but definitely no wrestling, definitely no striking. I was basically a magnet for punches. So that was your time, roughnecking out in Atlantic City, as we all do once in a while. Can we fast forward to when you're actually dominating the world as a black belt? Well, actually, it's funny because I took the little bit of money that they're like, hey, we're paying. I'm like, really? Okay. I took that money. It's like Bukowski stories with Ryan Hall. Well, then I went to the casino, I went to whatever, like the Tropicana that was right there, the casino, because that was a boardwalk hall. I'm like, you know what, man? This has been a not great evening. I'm going to win it back. This is going to be great. 15 minutes later, they had all the money that I had from the fight was gone. I just remember walking out of the casino super pissed. And I don't know what I was thinking. I'm not good at gambling. Why? This was not going to make my night better. I just thought that there was going to be some sort of cosmic balancing. And maybe it was the cosmic balancing all at once where things had done in the past. Longer term though, the balancing. We'll see. I hope so. But to come... We're all dead in the end though. That is true. Time will get us all. Yeah. So that was the first one. And that was when I realized I'm terrible at MMA, but I like it. I should just stop this until I one day learn how to actually grapple, much less learn how to fight. But I remember there's this guy named Dave Kaplan, who's the reason my ears are all messed up, who was on the Ultimate Fighter and got punched in the face and knocked out by Tom Lawler, who I'll always appreciate for doing that. But anyway... Dave or Tom? I appreciate Tom. I appreciate Dave too. Dave was great. Dave was just a huge bully and used to not completely unmercifully, but relatively unmercifully beat the crap out of me. And anyway... The ears look good, so... I appreciate that. I tell people it's a tumor that I got. And if they want in on a class action lawsuit with AT&T, they should send me an email. But anyway... You're very financially savvy. Very good. No, I just give the impression. Dave basically said, hey, don't worry, man. You're never going to be good at MMA. And you're never going to be good at grappling either. But even if you are good at grappling, which in my opinion, you will never be, you will never be good at fighting. And I said, Dave, if I do nothing else in my life, I'm going to keep training until I can make you pay for that. And now that I can make him pay for that really easily, he doesn't train anymore. But I love Dave. Dave's awesome. He actually won the singing B. What an interesting dude. Super interesting guy. But anyway... Is he a good guy? No, no, no. Virginia speaks a couple languages. Super interesting guy. Shockingly good at Jeopardy too. Not that I'm any good, but still shockingly good at Jeopardy. So anyway, years later, met Firas Zahabi. Actually, John Danaher. I met John Danaher and he put me in touch with Firas Zahabi. I started training at TriStar. I immediately loved working with Firas and learning under Firas. Started training at TriStar. And I did my first real professional MMA fight as someone that actually does head practice a little bit prior in, I think, August 2012. And that was against a guy. He was four and five at the time. So, you know, had some experience. Good kind of like first go for me, honestly. And I won that fight by TKO. And then it was a little bit of time off. And then I did another fight against a tough guy named Magic Hamo. He was five and two at the time. I think he was three and I was amateur. So, you have a good little bit of fighting experience. Won that one in the first round via rear naked choke. And then started to experience difficulty getting fights at that point. You know, I- Where you continue to introduce as like the master of grappling, the submission. At least that was my thing. I don't know if I was- Is that was the source of the fear for people? I think so. Because, I mean, I definitely wasn't much at striking at that point. You know, I definitely am a lot, I like to think I'm pretty hard to hurt. Although I try not to lean on that. And I played baseball for like 16 years. So, I can hit things pretty hard. I just wasn't able to, I recognized pretty early on that I had no idea how to actually hit things hard without becoming hitable myself. So, I think that's kind of the big thing is a lot of times, like we almost were mentioning before. If you try to go and get people too early, you can hit them if they're not that good. But you're going to get hit yourself. So, you're making, you're basically making a wager. You're making a trade of your own life for the ability to hit them. When you watch guys like Israel Adesanya, Floyd Mayweather, Stephen Thompson, Conor McGregor, when he's fighting really well, it's not a trade. They're not you're hitting them and they're hitting you. It's they're hitting you. But it takes years and years and years and years to be able to learn how to do that. Ton Lee is another great example of that. You know, my closest training partner, one of my best friends. And currently now one champion, one championship in Asia, the champion of the featherweight or I guess lightweight featherweight, 155 over there now. And he recently defeated Martin Wynn in a really great fight. And Ton knocked him out, long time champion. And Ton doesn't let you hit him. He doesn't let you touch him. I feel so fortunate to have met guys like Stephen and Ton to go early on in career and go, holy moly. I can't even, it's not even like, oh, you'll let me walk over and find you. It's like fighting a ghost that periodically shows up with a hammer and smokes you in the melon and then disappears into the ether again. So, the way they approach the fighting game is thinking, how can I attack without being hit? So, every strategy, every idea you have about what you're going to do has to do with that minimizing the return. The return. Absolutely. I mean, that's what all good fighting is. And all poor fighting, if throughout the course of history, most generals, whatever I saw or read, or they did battles by attrition. It's like, yeah, man, I've got 150 guys, you've got 50. Like, yeah, if 60 of my guys die killing your 50, that's great for me. But that's not so great for the 60 guys that died. I hope it's worth it. So, when you realize that not only you're not just Kobe Bryant and you're Phil Jackson too, you got to do everything. If you've got to run across the beach at Normandy, so be it. But that better be, you should have, make sure we thought this through and there's like, hey, there's no way we can walk around the side, huh? Because oftentimes there is. And I think a lot of times there's a lot of incentives in professional fighting too, for people to want to do that. And we come up with all sorts of, well, I'm trying to be exciting. Are you? Is that really what you came here to do? Because I came here to win. And I think that anyone that's really successful came there to win. And if it ends up being exciting, well, that's fantastic. I hope that people enjoy watching something and that's great, but that's a qualitative assessment anyway. You want to also be able to live the rest of your life. I think it's easy. I'll use Meldrick Taylor. I'm a big boxing fan. Meldrick Taylor was an excellent fighter. Came this close to a world title and was stopped with like, he was in a fight that he was winning with seconds remaining, literally seconds remaining. And they probably could have just let it go and he would have been world champion. And it was brutal. If you ever watched legendary nights like HBO boxing show, it's great, but it's heartbreaking. It's absolutely heartbreaking. And also like the beating that he absorbed in that fight changed him for the rest of his life. And also, don't think he'd never been hit before, but it was one of those where you go, it's all fun and games until you can't remember your name at age 44 years old. And I didn't come here. What did Patton say? Nobody wins a war by dying for his country. You make the other poor bastard die for his. And I think that that's kind of what we're shooting for. And the lionization of absorbing damage and that not being a big deal. You hear that all the time. So-and-so can take shots that would put a lesser fighter down. What does that even mean? So let me get this straight. Your ability to absorb damage is a part of you. I mean, I guess that, don't get me wrong, that is an attribute that's nice to have if you need it, but there's plenty of people that actually have really porous defense that are just very, very difficult to hurt for whatever reason. That's a fascinating fighter's perspective on the thing. I mean, the story that is inspiring, and I know it goes against the artistry of fighting is when you have taken the damage to still rise up and be able to defeat the opponent. But that's a flip side of a basically you failing to defend yourself properly. I agree. But let's say for, I think that's a triumph of humanity. That's amazing. To witness such a thing is unbelievable. But you still go, this is, there is a cost here. It's like I've been fortunate enough to spend some time working with the military and I've been around and read Medal of Honor citations. They're unbelievable. You read the story and you're like, it'll flow you. But it's not a cost and you don't want to be paying that cost a long time. And most of the time, the cost was everything. And then sometimes you go, hey, yeah, the value here, it's worth everything. It's like, I defend your family, defend your country under certain circumstances, and at that point, it's extension of your family. You're like, hey, this is worth it. To casually throw your life away or throw your health away, it's foolish. There's nothing great about that. And like you said, it's still an amazing thing to see. Yeah. But it's also amazing to see you not take damage as the Floyd Mayweather. It's the artistry of not being hit. And I wonder if maybe that's why people don't resonate with Floyd as much. Obviously, Muhammad Ali was such a time and place, a great man for so many different reasons. Although it was funny to remember there were times when he wasn't very popular. We love him now because of time of context, time to move away from some of the nonsense he had to deal with. But we got to see him struggle. And also, he had unbelievable sacrifice, both in and out of the ring that we all got to witness. We've never really seen Floyd struggle like that. And granted, obviously, Floyd isn't like a civil rights figure like Muhammad Ali was. It's a different time, different place, and he's a different man. But basically, I wonder if part of the thing that made everyone think of Muhammad Ali as the greatest, in addition to, of course, the unbelievable things that he did out in the world and the stands that he made, we saw him struggle in the ring. It's almost, it's humanizing. It's weird when people respect Khabib, but again, we saw GSP lose and GSP came back stronger. Khabib is amazing, but I wonder how people feel about him long-term. Not like they won't think of him as amazing and great, and he's been a respectable person and champion. But the time, he hasn't had to fall, if that makes sense. And also coupled with Ali had a way of being poetic about the way he was in the ring, being able to explain the artistry that he's... I mean, there's a joke in it, being playful, but really he was able to describe the flow like a butterfly's thing, like a bee. He was able to actually talk about his strategy without crossing that line into the flow he made, whether when you are just talking about money and just talking shit. That's true. Actually, Conor McGregor, when he's not talking shit, is pretty good at talking about the art of the martial arts. And I wish Khabib did the same. Actually, from the Satyavis brothers, there's a culture of being poetic about being scholars and also bards or whatever, poets of the game. And Khabib is more just simple, and he lets his actions speak, which is great too. It's floating in its own way. Yeah, it's great, but it's nice when you can tell stories. And that's probably why Ali was the great... Catch Me Up, you went to three fights, I think, undefeated. BJ Penn, we talked about last time you defeated BJ Penn. I mean, that's an incredible accomplishment, but you fought a lot of really tough guys. When was your last fight in Catch Me Up with the injuries? A lot of people kept more and more and more were unwilling to fight you. Yeah, that was why I was out for two years following the Grey Manor fight between... Fighting Grey and BJ. And the Grey Manor fight was actually one I'm really proud of because Grey was very tough. He's very big, very strong, very experienced. I had only five fights at the time, and I didn't have a lot of skills. I don't get to fight Grey with what I have today. I had to fight Grey with what I had in December 2016. And it really took a lot of discipline, a lot of focus, a lot of challenge to stay the course, to do what I needed to do in that fight, and to win in ultimately dominating fashion. Just not in the dominating obvious sense that you see when someone runs across and just does that to somebody. But that wasn't on the list for me at that time. That was an interesting one, but the time away, again, was very frustrating. That was incredibly difficult for me. Before that fight, is that true? After that fight. Well, because I beat Artem Lobov in the final of The Ultimate Fighter. And Artem is another guy that's tough, a lot of experience, and he's a funny guy, and he's said some things on the internet, so he gets a lot of heat for that. But he just knocked out three of my teammates. Put a couple people in a pretty rough shape at the end of that. So he was doing well, and that was a tough fight. Again, if I got to go back and fight that fight now, it would be not competitive at all. I mean, it wasn't competitive at that time, but it was competitive. It wasn't close, but it was competitive. So you were improving and growing fast. Yeah, and it was nice to have time away. I wish I'd had more time in the ring, but again, I'd only been doing MMA for three years at that time. So the improvement from doing what the Bitcoin mining was overriding the ring rust. I think so. I don't really believe in ring rust, if I'm honest. I can understand why people could feel a certain way, but if anything, it's almost like you just kind of forget what competition's like. And you realize, oh, you feel butterflies or something like that, and you go, oh my God, this is different versus, no, that's just your body getting ready to perform. It's okay. It's normal. How do you not have ring rust? I think I try to practice performing no matter what, whether it's singing karaoke, I'm not very good, but anything, you name it, talking in front of people. You embrace the butterflies? Yeah. I remember my last fight, I'm just staring at the wall, and I'm like, huh, I guess I'm going to fight in a couple minutes. I mean, of course, we all heard the phrase like you can never walk in the same river twice, because even if the river's the same, you're a different man. I think it's a really important thing to understand, because at various points in my martial arts career, I've thought, oh man, how should I feel? I remember when I used to do well in competition, I would think these thoughts, listen to this song, think about this. I would feel a certain way. And then if you don't feel that way, I would start to become stressed, because I was self-inflicted versus going, you'll feel how you feel. Your job is to show up with what you have on the day, do your absolute best. I will never quit. I can be sure of that. I didn't say I can't be beat. I can definitely be beat. I could have lost every single fight that I've ever had, but I control my effort and I control my attitude. And I will do my very best to execute my game plan. And the event's not working, if I have to, I'll put my hands up and walk dead forward if I need to at somebody. We hope that that's not where it goes. But again, that humanizing moment where you're shooting for like just the inner, you sacrifice the outer and all you have left is will, and you hope it doesn't happen. But if it does, you'll be there. But I guess to come back, the extra periods of time in between fights, I think was valuable because it was deeply challenging. It was incredibly, heartbreaking sometimes, if I'm honest, man. It's like, I didn't want to- It's just waiting. Oh my God, dude. Is there politics involved? There's sometimes, every single time you step into the ring, nothing's guaranteed. You could be hurt, you could hurt somebody, you could win, you could lose, throwing away, just like I said, throwing away your health or your life cheaply makes no sense for anyone. And having demonstrating some degree of temperance is not cowardly either. But again, you're, if you wait too long, you have nothing. So I guess I was trying and always being, I'm always open to fighting the absolute best people possible. I'm never turning down fights ever. Some random jabroni decides that he wants to fight him, go away. If I wanted to just fight randoms, I would just start and stand on the table at Denny's and start yelling. And I'm sure some people would be willing to indulge me. But you want to fight meaningful opponents, challenging opponents. And I know who and where they are. And sometimes- You did fight in Atlantic City. I did. So the Denny, but you put the Denny's behind you. I did. And I'll be honest, if I'd have stood up after that fight, I don't know if I was in great shape to expect to win any other fights that evening, but I could have tried it. I'm sure there were some takers in the crowd, particularly after they watched me fight, they're like, yeah, I'll fight that guy. So, okay. So when was the last fight that you- That was Darren Elkins. That was six months or seven months after the BJ fight, which is great. Because I love maybe five- He's a really tough opponent. A very tough opponent, very tough guy, super tough dude. And that was in July, 2019. And then right when I was about to fight- You were ready to fight regularly after that. You were trying to find a fight. Yeah. And we got Ricardo Lamas, so no one else, none of the, I was ranked in the top 15 at that point. And then people didn't want to fight. We were struggling to find an opponent. And then Ricardo Lamas, a great, former title challenger, MMA, really great history in MMA, recently retired, but we were supposed to fight in, I think, May, March, March, May of 2020. And then coronavirus happened. And so that scrapped the whole show, training, we were just scrambling to try to keep the gym alive and take care. I have five or six full- five, six, I think, five full-time employees that are my responsibility. I have to, their livelihood is in my hands and it'd be irresponsible of me to not take that seriously. So anyway, we were able to navigate through that time. And then we were able to reschedule the Lamas fight. And that was in August of last year. And I got a medical flag, like, oh, hey, you have a medical condition that we need to look into. And I got pulled from the fight and I immediately was concerned because, of course, any serious medical condition, you want to go, oh, man, well, I guess I would like to look at that. Yeah, it turns out it was a giant false positive. And we find that out all of five weeks later and you go, you gotta be kidding me. And then we're still waiting for a fight, waiting for a fight, waiting for a fight, waiting for a fight. People won't sign up, asked for a number of different opponents, basically said, hey, I'm willing to fight anybody that's tough and moving forward. Finally got a great opponent in Dan Ige for, I guess it would have been this March. And then I was training in January, working on some stuff. I was out training with Raymond Daniels in California. Raymond's amazing, unbelievable, kickboxing, karate style kickboxer, fantastic martial artist, great teacher, great training partner and good friend. And just really bad luck, kind of a fall in the middle of training. And I tore my hip flexor halfway off of my femur. So that wasn't great. And you go like, man, right at the time where you're like, oh, man, all right, finally moving forward, having the opportunity to fight, Dan's a really tough guy. You have to fight well if you want to have a good chance to do well with him. If you don't fight well, it's going to be a rough night. I'm like, that's exactly what I signed up for. That's what we want with BJ, that's what we want with Elkins, that was great. And then the universe goes, hey, man, I hear you, but there's also this. So anyway, fortunately it's healing up and then hopefully- When do you think you- Went from May, I think. May this year? May of this year. Yeah. So it's been about five weeks since the injury. You'd be able to heal up, do you think? Yeah, I think it'll be okay by then. I don't need a big camp at this point. I've had years of camp. Not going to curtail my drinking or anything like that, obviously. Come on, man, life is meant to be lived. And so I'm in good shape. I'm always training. I'm trying to do my best to train around the injury to the extent that I can right now without hurting myself long term. So is there a particular opponents you're thinking about? Yeah, anybody forward? I asked the second that I got hurt, I sent a message to Dan and I said, hey, man, I just wanted you to be the first person to know. I just was pretty reasonably injured. We just got an MRI. Doctor says, hey, man, you're out and you need to take three weeks off, off. Don't do anything or you're going to tear it the whole way and this is going to be surgery. And then it's going to be an additional eight weeks on top of that to start to rehab it through PT. And anyway, so I let him know, hey, if you can push this thing back, I would love to keep on the car or love to keep the fight. It's like I respect you a lot as an opponent. And also it's been brutal trying to get anybody to sign on. So if you're into it, I'm still there. Unfortunately, he turned that down. I understand he had other things going on and he and his wife were expecting a child coming up. So he needed to fight. And anyway, I guess we'll see what's coming forward. Is there somebody who's like super tough in the featherweight division that you seem to like enjoy the difficult puzzles? Is there somebody especially difficult that you would like to fight? I would like to fight. I know that I'll need to win at least one fight before this. And I look forward to coming back and giving my best effort to do that. I want to fight to beat Magomed Sharapov. I want to fight Yair Rodriguez. I want to fight a Korean zombie. The B is complicated, man. Yeah, that would be fun. I would love to see that fight. That's a fascinating fight. That would be fun. He would be very challenging. All those guys are very challenging. And so I look forward to just staying healthy to the extent that we can, coming back and I'm going to fight multiple times this year, hell or high water. Hell yes. Hey, by the way, I completely forgot because you were talking about the systems and decision trees and the illusion of choice made me think of Sam Harris and I forgot to mention it. So he talks about free will quite a bit and that there's an illusion of free will. It's a bold claim, Cotton. You know, maybe the universe constructed that little game where it makes us feel like we have a bunch of choices, but we really don't. We're really always ending up with a middle finger. That would be hilarious. Yeah, that's what you see before you die. It's just a giant middle finger. It's like, oh, fuck. I knew it. I knew it. What do you think? Do you think there's a free will? We feel like we're making choices. So you're thinking, again, what we're talking about, okay, here's a system of martial arts that's Hanzo Gracie, there's different schools and whatever. And then you're thinking, okay, how can I think outside these systems? But then there's also a system that's our human society and we feel like there's an actual choice being made by us individuals. Do you think that choice is real? Or is it just an illusion? Well, okay, that's a really good question. I'm not necessarily equipped to answer this, but I'll do my best. Okay, I guess I would say to start with, sure, it would be interesting if it wasn't real, if the choice wasn't real. It would be pretty interesting if it is real. First off, I would start with facilitated beliefs versus not facilitated beliefs. It's almost like, I think the world's out to get me. True, not true. What next? Probably not a facilitated belief. Imagine you believe there's no free will. Okay, now what? Does that justify every single impulse that you're going to give into? Or does the belief in free will, does the belief in my ability to work hard, to focus, to be disciplined, to improve my position, improve my situation, whether it's true or not, although I think that at least many of us would argue that at least whether there's some sort of internal driver that allows for that. We live in a material world, your actions do affect the world. I can choose to pick that water up or not. And anyway, I would say I believe strongly in the idea of picking facilitated beliefs and going, hey, I will adjust whether this belief system is right or wrong on a cosmic level. I'm nowhere near smart enough to understand, but I can say me deciding that, let's say for instance, I'm going to walk over to have a conversation with someone in the hotel lobby and I've never met them. And I go over and I start with, oh, this is going to be interesting. And I just walk over there versus in my head, I'm like, what's this asshole want? We're about to have two very different conversations. I could be right that this person's not very polite or thinks negatively of me right from go, but I think that that's probably not a facilitated belief. People talk about, how is that going to help me navigate the conversation to a positive conclusion? And I think about that for, let's say fighting, it's a good example, like confidence. Plenty of people believe plenty of things that aren't real, myself included, I'm sure all the time. And anyway, believing that you can do something, I'm like, hey, I think I can win. It doesn't guarantee you a positive outcome, but I would say it, most of us would probably, most of us would argue that it helps. And you're thinking about depression, what's depression if not a negative, unfacilitated belief that is not always, that oftentimes is not reflected by reality, but you project it onto reality and it's understandable if it makes you feel like, oh man, this isn't going to work out. I don't think the prospects are going well. And then if you feel like you can't get out of that loop, that seems pretty rough. And I see a lot of things out in society right now where you go, whether you agree or disagree with various positions on things, you go, is that a facilitated belief? Even if that is true, which is arguably anything. So what next, man? So where does this end? One is the positive, what's the happy ending here? And if they go, well, there is no happy ending, I'm like, okay, so now what? So what do we do here? And I guess- So choose the facilitated belief. And in your intuition, believing that free will is real is more productive for a successful life. Absolutely. Because otherwise, how am I not, how am I, first off, how can I, how can society function if it's not real? So how can I blame you or anyone else or hold anyone responsible for anything if free will isn't real? Well, no, that's exactly the point. But at the surface level, what you're saying is true, but perhaps if we truly internalize that free will is an illusion, we'll start to figure out something that transforms the way we see society. For example, we are very individual-centric. So believing that free will is real puts a lot of responsibility and blame on people when they do something bad. Maybe if we truly internalize that free will is an illusion, we start to think about the system of humans together as this mechanism for progress, as opposed to where individual people are responsible for their actions, good or bad. So we remove the value, the weight we assign to the accomplishments or the violence, the negative stuff done by individuals, and more look at the progress of society. I don't know what that looks like, but it's almost like, as opposed to focusing on the individual ants of an ant colony, looking at the entirety of the ant colony. So that, I think it makes perfect sense. I would just say that that's a reasonable thing to suggest. It's a seismic shift, and it's hard to say whether that would be better or worse, but I guess I'll use this as a convenient one for me. So I remember the last time we spoke, I brought up one of the most reviled evil characters in certainly recent history, probably human history period, Adolf Hitler. Well, I'm a big fan of making people live in the world that they want to believe in. Well, if free will doesn't exist, and it's just about how things move forward, when are we going to be high-fiving this guy or what? Because I remember what I said, and that actually brings me to something else we discussed. Yeah, for people who don't know, Ryan brought up, or I brought up, there's literally a giant book about Hitler. So I've been obsessed with Hitler, World War II, and Stalin recently. Oh man, this has become like a meme. Joe Rogan went DMT and me with Hitler. Can I pick something more positive? A cat in a hat or something, I don't know. But you brought up Hitler as an example of something particular, some philosophical discussions we're having, and the excellent, eloquent, and the full of integrity MMA journalist clipped out something you've said about Hitler and said that... I forget what the headlines are, but they were the most ridiculous possible implementation. Basically, nitwits intentionally misrepresent... intentionally misunderstanding what I'm saying, then it's like, I get that they're stupid, but I'm stupid too, so I know what that's like. So I don't have a lot of sympathy for you. Stupid, no stupid. Yeah, exactly. I can't give you a pass on that. But basically, intentionally misunderstanding what's going on, but what I find funny is that, hey, we got to be careful what we believe. And again, back to the cancel culture thing that we discussed last time as well, where would I like to apologize? I mean, no, actually something about cancel culture that we've been seeing things culturally, I'm like, I will be damned if I apologize for anything that I don't need to apologize for because I was intentionally misunderstood in that instance. Now, you could say that I'm not a historical scholar, which I would agree immediately, and also that I oftentimes ineloquently or inarticulately phrase things, which I'll agree that what is again, but ultimately going, hey, I want to make you believe, live in the world that you're suggesting ought to exist. Okay, so if there's no free will, is everything, how far of a step back are we willing to take cosmically before we start going, hey, this is good because we're experiencing a social reckoning in our country at the moment for good and for other probably, I guess. And basically, but hey, it all worked out, right? So that's probably not something that would fly. And I think that's a fair thing. That's interesting. It might not fly from the individual perspective, but if you zoom out and think of, appreciate society as just like an ant colony as a beautifully complex system, like we kind of, from the individual perspective, we kind of appreciate the value of progress, especially progress of the individual, but in whole progress of societies. But if you accept that this is just a complex system, that's not necessarily headed anywhere, but this is almost like that river is just flowing. I think that removes the burden of always striving, of always trying, of always like the struggle and so on. So it's possible that if we have no control, you can like, you know, you can't do anything. And I think that's a good point, that if we have no control, you can like arrive at some kind of other zen state. Does that sound very human though? That goes against, I think, our current human condition as we experience it, but we've communicated that to each other. Like, we've taught, like through these social forces, taught each other that our lives matter and so on. Maybe if we convince ourselves that we're just sort of like little things in a stream and ultimately none of it matters, there might be some kind of enjoyment to be discovered through that process. I don't, listen, I'm a capitalist. But I guess, I think you're bringing up a really important point. I guess almost anything, like capitalism, I only get to experience it as I sit here now and I get to live, I was raised in the United States, have traveled around the world a little bit, have had the good fortune of meeting many people from many different places. And I'm an end user of capitalism. I don't really know how it got here, whether it was, I wasn't there at the start of this idea. I wasn't there for, hey, how do we come up with this idea? How do we arrive? And I'm nowhere near well-read enough to understand any of that really, even secondhand. And I guess, recognizing that communism, Marxism, socialism, anarchism, anything, these are all perspectives that all have, I guess, various strengths and weaknesses. But I guess one thing I'm always, I guess I would say the burden, it seems to me that if you want to make a change, the burden of proof is on the person implying that there needs to be a change. And it doesn't mean that there's nothing there, but it's like, if you want to create a small shift, a ripple, that's fine, but a seismic ripping shift in how we exist or how we experience the world as human beings. And you mentioned fighting, why watching someone undergo, take abuse on a level in the ring, that's just shocking. And then triumph in spite of it, you're like, this is unbelievable. This is part of the magic of combat sports. Now, it's part of the magic, the other side of the magic that doesn't get talked about sometimes is that the trajectory of that individual's life later on is not always great, or there's a little phrase, there's a cost for that. But if we remember, you mentioned removing the struggle. I don't, personally, the struggle is what makes life life. And also, I guess, something Faraz has brought up to me on a number of occasions, and it makes sense to me, it's basically humans only understand things through relative comparison. I only understand heat because I've known cold. I guess it's like talking to someone that's never experienced any sort of hardship, and then their latte isn't right, and then they pitch a fit, versus someone that's gone through a great deal of challenge, struggle in their life. They tend to have a little bit more of an even perspective. And of course, even is a relative thing, and what I perceive to be even may not be even. Maybe I'm particularly softer or something in the other direction without realizing, because I can only understand what I can understand. But the idea that we want to fundamentally alter ourselves as a species and as people seems like an incredibly, incredibly high bar to prove, and also an incredibly dangerous idea, because it always comes back to, well, who's going to be responsible for this? Who gets to do the choosing? What's a good idea? What's not a good idea? And I guess that actually brings me to a something I've been encountering recently in discussions with friends. I feel like there's only two types of people that I encounter at this point. People with a more or less libertarian tilt to their thinking, and people without it. And when I say libertarian, I don't mean that in the political party sense or even the belief system. Basically, I'm like, hey, you do you, buddy. What you're up to is not my concern versus what you're up to is my concern. And I guess I've always watched various points in history, people on this side or people on that side are more or less, I guess, problematic, I guess you could say. I don't mean that in the internet sense, more of an issue. But the world is always full of people that want to tell you what you need to be doing as opposed to more or less doing a harm. And I guess that's one of the ones. Anytime I'm trying to tell other people what to do, I better hope I'm right. And it's bizarre to me how many people are so confident that their side or their position is the one that's not only right for them, but right enough that they can enforce it on others. And that just seems incredibly dangerous to me. And I guess that comes back to even Sam's point about, oh, we want to, trying to spread the idea that free will doesn't exist. I'm not saying it's damaging, but if I will, maybe, and plenty of other things could be as well. I'm not, it goes way over my head as to the implications of all of these. And I guess all of us are an evangelist for something. But I guess it's weird that we've gotten this far as a species, and now we want to take sharp, sharp turns. Well, we've been taking a bunch of sharp turns throughout history. Yeah, that's true. That's what, that's the way, okay, humans love power. And one way to attain power is to say, everything that you guys are doing is wrong, and I have the right thing, and I'm going to build up a giant cult of people, and I'm going to overthrow. And indirectly, what that results in me is me gaining power. And that's how you get all the big revolutions in human history, saying, I'm done with the thing that the powerful are currently doing, so I'm going to overthrow. That's where probably all the identity politics that's happening now is people that didn't have power before are looking to gain power. And they're also, that's where Jordan Peterson criticizes identity politics, is people with the right, with the good intentions, I should say, are in seeking power, allow power to corrupt them, as power always does. And so they lose track of the devils that they're fighting by becoming the same kind of devils, the same kind of evil that they're fighting. And so that's just the progress of human history, but hopefully, as these power-greedy people keep attaining power with a progressive mindset, over time, things get better and better as they have. Like each iteration? Each iteration. A lot of unfairness happens, a lot of hypocrisy happens, a lot of people are trampled along the way by those who mean well, but over time, lessons are learned, or like human civilization accumulates lessons, and in part learns lessons of history, and it gets better and better over time, even though in the short term, there's people acting not their best selves. And that seems to be the progress of human history. The idea of internalizing the free will not being real, you're actually making me realize that that ultimately leads to a kind of... Doesn't that go in a nihilistic direction? Yeah, it's both nihilistic, or if you want to make it a political system, then it's more like communist type of a system where the value of the individual is completely reduced, removed, or another perspective is like the freedom of an individual is not to be valued or protected. And so from our current perspective, the systems that seem to have worked, the United States works pretty damn well, despite all the different criticisms. It seems like freedom of the individual in all its forms seems to be fundamental to the success of the United States, and so we should... It's, however the hell you put it, it's like, doesn't matter whether free will is or isn't an illusion, the belief that it's real... Protects the individual from the group, which is fundamentally, correct me if I'm wrong, that always seems like the big issue of history. Hey, there's more of me than there is of you, deal with it. You're like, yikes. And you want to be yourself, you want to be different, you want to have a different religion, you want to be a different skin color, you want to do this, all the bad tribal things happen when there's more of me than you. Correct me if I'm wrong. Yeah, yeah, absolutely. And that's always the fundamental power imbalance though, right? Well, the interesting thing about the libertarian thinking, I guess I... I don't know, those words are really... Maybe they're all charged, I know what you mean. Yeah, they're all charged. I may not scale up, but I mean, we're more like on a philosophical underpinning where you're like, yeah, basically, hey, you feel free to believe I'm a fool, and plenty of people do, I'm sure. But as long as you don't chase me down the hall and hit me in the back of the head with a textbook, what's the big deal? Yeah. So the libertarian viewpoint, which I probably espouse, I very much like freedom of the individual is very valuable and leave others the fuck alone unless they're trying to hurt you. The thing is, you also have to, I believe, put in the work of empathy of understanding what others... What leaving people the fuck alone means to others. But isn't that an interesting thing? If I believe in freedom of the individual, and I take that, like all of these, like you said, you take them past just their first why question, you ask why, why, why, why, or how, how, how, how many times, should that not extend to respect for you, respect for your position, respect for your individual lived experience, which could be grossly different than mine. Yeah. This is the problem with saying, I'm an individual, I'm not going to bother you, you don't bother me. That's just like, that's not actionable. Because to make it actionable, you have to think the why, why, why, why, why, you have to do the steps beyond. You think, what does that actually mean? That means understanding how even my very existence hurts others. Because you have to understand that you're not just sitting alone in a room, you're using public transit, you're using the police force, you're using firefighters, you're using a lot of resources that are publicly shared, and some of those resources are unfairly distributed. We've agreed that we're going to pay taxes, and those taxes are going to go towards building some kind of infrastructure. So that's already towards social. So you're not a real, you're not a real, sort of, I talked to Michael Malice, like anarchist, right, saying like, basically, full, just leave me the fuck alone, and I'm going to collaborate with whoever the hell I want. We're not, that's not the American society as it stands currently. We've agreed that there's going to be certain social institutions that we pay into, and some of the sort of discussions about race and all those kinds of things is about those institutions being institutionally unfair, whether it's race or gender, all those kinds of things. Listen, you know, I have a bunch of criticisms of the way that conversation carries itself out, but the thing is, what's valuable is to actually listen and empathize. And that's not often talked about with the leave me the fuck alone mindset, because it doesn't have that little component, which I think could be fundamental to the function of a society, which is like social. Like, it's the, what is it, the Obama, you didn't build it, or you didn't build it alone, or whatever, however that goes. But basically, we wouldn't be able to accomplish anything as individuals without the help of others. And to be able to then start to think, okay, so what is my duty, what is my responsibility to other human beings to be respectful, to be loving, to help them as part of this functioning society? That's actually a lot of work to start to think about that. For sure. Because then I have to think, okay, Ryan, what's his life like? As a business owner doing COVID, what's that like? And then he has, there's employees that run the gym, what's that like? What's that stress like? Or about the fighting and the injury and so on, what's that like? That empathy takes a lot of compute cycles. Fair enough, and also a lot of energy, right? But I have to go through that computation if I want to be an individual that doesn't hurt you. If I may, I guess to come back to Muhammad Ali, one of the things he said is service to others is the rent that you pay for your, is the price you pay for your rent here on earth. And now one of the things that I think that I see as a result of the internet all the time is people talking about global giant problems, social problems that are society-wide that are massive, truly massive, and frankly, beyond the power of any of us to solve. That's certainly on an individual level. So I've discussed things with friends, my father's an environmental attorney, has been for a long time and has been an engineer for a long time. And so I'm not, I barely know anything, but I'm reading a little bit of various things. But climate change, oh my God, I'm so concerned about climate change. What am I supposed to do about climate change? I'll tell you what I can do is I can not litter, I can try to conserve energy where I can, I can do whatever I want. What can I personally do about some giant social problem that I didn't start and is out of my control? I'm like, well, I can be decent to the people around me. I can mention, I can demonstrate empathy and I can demonstrate consideration for the people in my circle. And to the extent that I can the people outside of my circle, but yelling at the trees over things that, over problems that are borderline cosmic doesn't seem very productive. It just makes me feel like I'm cool and important because I'm talking about something, well, hundreds of years from now, the water will rise. Maybe it will, maybe it won't. I can't, it's completely over my head. I know nothing. But focusing on the problems that we can actually solve, it comes back to the same thing. I want to win a fight. I would love to win a fight. I can't control that. What I can do is I can control each individual step that I take around the ring and try to make the next correct move. I can't look, no, it gets people's, they get all excited. I'm trying to keep my language in check, but they get all excited thinking about problems that are, Superman couldn't solve these problems. You could be that powerful and you can't make all of the bad things go away, but you can absolutely change yourself. And I think a lot of the lessons that, the good lessons from religion that happen, the good lessons from the great men and women throughout history that we're inspired by, that talk about change starting with within. And again, treating the people around you decently, and treating the people around you decently doesn't even necessarily mean the golden rule, do unto others as you would like them to do to you. I go, well, maybe what I would like and what this person would like, aren't the same thing. Well, how am I going to get to the bottom of that? Because I could be attempting to be decent to this person. And by my standard, I am being decent, but maybe I'm missing the mark by theirs. Well, I can't possibly, if I just interacted with you, it's like someone talking about some nonsense microaggression. So let me get this straight. I've never met you before. You never met me before. And you're interpreting some minor comment that I've made in the least charitable way possible. I'm not saying that you couldn't be annoyed, but your expectation for that level of consideration is you're going to be disappointed a lot. Now, if we're someone that's in your life on a consistent basis and they're like, hey, I really don't appreciate what you're saying or what you're doing here, do you realize that this is how I'm perceiving? You go, oh man, I'm so sorry. Of course I would hear what you have to say. But I guess trying to recognize that I guess my job is to treat others with dignity in general, but the level of specificity that that requires increases as it gets closer to you. And as a person, I have a very finite amount of resources financially, intellectually, emotionally, physically. If I chuck 0.001% of it in every single different direction, what am I doing? It's like when people are like, oh, I care deeply about Tibet. I'm like, why aren't you over there? Go build a house, man. Get on a plane, go build a house. Oh, you don't want to do that. So really what you want to do is post on Facebook and accept high fives for how much of a good guy you are. I got an idea. Go help somebody in your neighborhood. Go play with some kids. Go be a friend to someone that doesn't have a friend. Read a book, try to educate yourself. And so I guess to come back, it's all of these problems aren't solvable on a grand scale, but it's almost like by attempting to address them in our personal lives, we do better. But rather than a giant airing of the grievances on a consistent basis, not that that isn't sometimes necessary and valuable, but after you air your grievances, you go, hey, how about we sort this out? What's the next step? And I guess, again, when we're trying to address it on a giant social level, it just seems unmanageable to me, even if you have the best of intentions. Yeah, I mean, but nevertheless, there's a lot you can do on social networks. I mean, I enjoy tweeting and consuming Twitter. It's just I apply the exact same principle that you just said, which is free will and discussion, which is like I approach it in a way that I don't get stuck in this loop that's counterproductive. I try to do things that are productive. And it's just like you said, that's like, what kind of things can I do in this world? Whether that's tweeting or building things, those are low effort tweeting, or actually building businesses or building ideas out, that's high effort. What can I do that will actually solve problems? And that's the way I approach it. And I do wonder if it's possible to, at scale, encourage each other to approach like social media and communication with fellow humans in that way. I don't know. How do you think that would be done? I guess like to improve the quality of discourse maybe, like, or even like you said, the empathy or the decency of discourse. I think people should be incentivized, encouraged to do that. I think most of what we see happening on Twitter and Facebook and so on has to do with very small, very powerful implementation details. It goes down to like, what is the source of the dopamine rush, the like button, the sharing mechanisms, just even small tweaks in those can fix a lot. Really? I believe so. So a lot of the stuff we see now is the result of just initial implementations of these systems that we didn't anticipate. So the monetization comes from engagement, and the tools we have is clicking like and sharing. It was not always obvious. It was not obvious from the beginning. It wasn't obvious while Twitter and Facebook grew, that there's a big dopamine rush from getting more followers and likes and shares. So we've gotten addicted to this feeling like how many people are commenting, how many people are saying like, clicking like and so on. So that's that dopamine rush. So we want to say the thing that will get the most likes on mass and society. And then the other thing that was expected is the controversial, the divisive will get the most likes. So it had to do with the initial mechanisms of likes and shares resulting in an outcome that was unpredicted, which is huge amounts of division, irrespective of like, any of the basics of human connection that we've actually all come to understand in society is valuable at the individual level, like we're saying. But on mass, what results is like, you throw all that out and it's all just divisive at scale discourse. I think it could be fixed by incentivizing personal growth, like incentivizing you to challenge yourself to grow as an individual, and most importantly, to be happy at the end of the day. So feed, like, incentivize you feeling good in a way that's long lasting, long term. I think what makes people actually feel good is being kind to others, long term. In the short term, what feels good is getting a lot of likes. And I think those are just different incentives that if implemented correctly, you could just build social networks that would do much better. So do you think it comes from a structural perspective? I guess at what point you mentioned free will, and also you mentioned feeling good, and again, working hard. I know that you have, I guess, was it a race? No, it's the Goggins thing. It's a 4x4x48 challenge where you run four miles every four hours for two days. That's awesome. Yeah, it's a bunch of, it's the challenge of it isn't just the running. The running is very tough, but it's mostly the sleep deprivation because you're just training every four hours. But it's a struggle, right? It's a struggle. But the struggle gives meaning. And ultimately, I guess, so how can we, because you mentioned, like you said, adjusting things on like a, I guess, like a programming level, almost, a base programming level so that the interface is different for the user. But at what point does the user have a responsibility to, you know, as a man or a woman or a person to just behave more decently? How can we, I guess, utilize, what can we do? It seems like, you know, like our society is so grossly missing like a Martin Luther King right now, like the great inspiring characters throughout American history, throughout world history. Where are the great leaders? So leadership is part of it, but I, you know, that's definitely where the great leaders is a very good question. That's more of a question of our political systems, why they're not pushing forward the great leaders. But there's also just the, okay, there's some just basic engineering shit, which is when you and I, when you, Ryan, and I are in a room alone and we're talking, even if we're strangers, the incentives are for us to get along. Like just when we're together in person, that's what I'm saying. I'm not even saying some kind of profound. But when you remove that. When we remove that, the implementation of social networks as they stand right now in the digital space, have very different set of incentives. It's more fun to destroy others, to be shitty to others. And it becomes this endless loop, like you were saying, that's ultimately destructive and not productive. And I think it has to do with just the interfaces of making it feel good to be nice to others. Because currently it doesn't feel nearly as good to be nice to others on the internet. And it doesn't feel nearly as bad as it does in real life to be shitty to others on the internet. So the incentives are just wrong. I think there is a technology solution to this, or at least the solution to improve this communication mechanism. It's not obvious how. I have a bunch of sort of more detailed ideas, but this is fascinating because I've gotten a chance to talk to Jack Dorsey quite a bit. He's the CEO of Twitter. And he is legitimately has, in this conversation, he would agree with everything. And he's a good human being. And he has a lot of really good ideas how to improve things. The question when you're a captain of a ship, whether even it's a question whether a CEO is even a captain, how much can you actually steer that ship once it's gotten large enough? There's so much momentum. There's so many users. There's so many people who are marketing and PR and lawyers. It's very difficult to change things. Is it difficult because of the fallout or is it difficult because it's actually like literally out of his power? The power is weird when you have a large organization. This is why the great leaders, this is what great leaders do, whether it's presidents or leaders of companies. Steve Jobs, I would argue Musk is that way, is to walk into a room full of people who don't want you to create drama. It's weird, man. When people just kind of want to be nice, the niceness creates momentum and nobody wants to, it's the systems thing. Everybody just behaves in the way they were previously behaving in the way they're supposed to behave and nobody wants to raise a fuss. It takes a great man or woman leader to step in and say, what we've been doing is bullshit. Okay, you're fired, you're cool. What is it? I'm out. I think you have to create constant revolutions within the company. That's very, very difficult to do structurally and psychologically. It's very difficult to do to be able to constantly challenge the way things have been done in the past. Which is why another way it's often done is a startup, like a small company, basically a small company becomes really successful and then no longer can turn the ship. So a new startup comes along, a new competitor that then challenges the big ship and then that starts out the winner. That's how Google came to be, that's how Twitter came to be and Facebook and so on. And Apple has, you know, that was the dream of Steve Jobs is it would succeed for many decades, for like centuries. That was the idea that you would keep creating revolutions. And under Steve Jobs, Apple successfully pivoted a bunch of times. Just like reinvented themselves. Which is funny. Very difficult to do. Because I mean, I've heard, at least I don't know if this is accurate because I wouldn't know anything, but I've heard plenty of people complain about Steve Jobs. But in reality, the reason that all of these amazing things were done was because this person was willing to, well obviously brilliant, and then also willing to rattle everyone's cage periodically and say, hey, what's going on is not what we need to be doing. That's a really interesting thing. So he would rattle the cage, but he was also, I don't know if those are intricately connected or always have to be connected, but he would just be a dick. Well, maybe by his standard, I am lazy and worthless. Well, he would say that to you. Is he being a dick though, if by his standard, I mean, again, it's like everyone's stupid compared to somebody. I guess. So you apparently are able to take that kind of thing. Sometimes you just, there's ways to cross the line. And I mean, this is, okay, the fascinating thing about being a leader, especially a leader of companies is it's a people problem. So each individual in a room, so as a leader, you're only really interacting with a small number of people because there are leaders of other smaller groups and so on. But each of those individuals in the room have their own different psychology. Some like to be pushed to the limit. Some like to be screamed at. Some are very soft-spoken and almost afraid to speak. And they have to be, you have to hear them out. And those could be all superstars. We're not talking about the C students. We're talking about the A plus students. Well, it's funny that, yeah, but the skill to manage all of those people is completely separate from the skill to innovate something. I mean, not that they're not connected, but it's funny how it's almost like, why do we have shitty representatives? Well, I mean, the thing that you do to get elected has nothing to do with governance. Well, that's exactly it. But the great leaders have to have both skills. So you have to have the boldness of, if you look at the great presidents through history, usually it's in a time of crisis is when they step up. But they basically say, okay, stop this old way that Congress works of this bickering of this like compromise bullshit. Here's a huge plan that costs billions of dollars in today's age, trillions of dollars, no extra pork, no extra additions. Just like, here's a clear plan. We're going to build the best road network the world has ever seen. And we're going to build some huge infrastructure project. We're going to revolutionize internet or we're going to coronavirus. We're going to build the largest testing facility the world has ever seen in terms of the, we're going to get everybody tested several times a day, all those kinds of things, huge projects and say, fuck all this, the details that everybody's bickering about. We're going to give everybody $2,000. We're going to give everybody $3,000, like huge projects. And at the same time, so that's the boldness and the leadership and saying, throw out all the bullshit of the past. And at the same time, be able to get in the room with the leaders of both parties or for the powerful individuals and smooth talk the shit out of them in the way they need to be smooth talk to. So like both of those skills, it seems to be when they're combined in one person, that's, that creates great leaders. Musk appears to have that, Elon. I don't know if Steve Jobs, it's interesting. So the criticism of Steve and a little bit on Elon is he misses some of the human part. But maybe it's impossible to have a really, you have like Saliha Nadal, who's the CEO of Microsoft. You have, who is really good on the human side, really, really good on the human side. Like everybody loves him. The CEO of Google and Alphabet is also the same way. So like, I don't know if it's possible to have both. You only get so many stat points. Yeah, you only get in this RPG of life. You got very good at Jiu Jitsu very fast. So you went, I mean, you told the story of Blue Belt and so on, but you went to Black Belt really quickly and not just in terms of ranks, but in terms of just skill level. I mean, you didn't go to Black Belt nearly as fast as your skill set developed. You were like doing extremely well at a high level of competition. So you're a good person to ask, how does one get good at Jiu Jitsu? We talked about solving problems at the elite level, but when you're a beginner at the martial arts, how do you get good? How much training should you do? The very basic stuff, like how much training, how much drilling, and then the mental stuff, like where should your mind be? How should you approach it from a mental perspective too? I'll just tell you my perspective on this one. I guess I would say, step one, I feel lucky to have found a good training situation, particularly for the time, in where I was at, and I drilled a ton. I drilled and drilled and drilled and drilled and drilled. And one thing that's really important to understand though is that I was able to, in a relatively brief period of years, go from zero to reasonably good. But I think I probably crammed more hours in those small years than most people did training, let's say in two or three times the length. So it may masquerade as something else other than it is, I could say. So you have to put in the hours. Yeah. There's no way around that. I think so. But what did you put in those hours? So when you said drilling, can you break that apart a little bit? Sure. Like what does drilling look like? Is there any recommendations you can make? Absolutely. Step one, I would say your choices matter. I think one of the really important things that I think we should consider about Jiu-Jitsu is that there's a lot of junk in the system right now. It's like Jiu-Jitsu has exploded in terms of the number of positions, techniques, strategies, this, that, rule sets. That's really cool on the one hand. On the other hand, there's probably a just metric shit ton of suboptimal things that are out there that are being taught. Myself included, I've taught things that are looking back five years, three years, two years, one year, where I'm like, oh, I would not do it like that anymore. Straight up. Sometimes I wouldn't do it like that. Other times I would literally never do even that particular movement. I don't think the shrimp is a real move. It's a giant spiel and it's easier to show in person, but long short of it is there's a lot of things that we think of as fundamental that I think that are really pretty negative. And also- That's heresy in Jiu-Jitsu, isn't it? The shrimp. Exactly. Is like the holy, we all worship the shrimp. We love the shrimp. We love the shrimp. Now, for people who don't do Jiu-Jitsu, and you should, the shrimp is you scoot your butt away from your opponent. How would you describe that? It's like a really athletic looking position where you look like someone that's trying to stick their butt out on Instagram, and then you push your hands away and you expose your face, and then you lay on your side because someone told you to do that. And you look like a, I guess you look like a shrimp. Yeah. It's like that time that someone really credible told me to drink unleaded gasoline. I did it for a while. And then it got to the point in my life where the next best, the thing that I needed to do to really improve my life was stop drinking unleaded gasoline. And I would say that there's a lot of stuff that's in there that step one is like, it's junk, it's actual junk. And not only will it waste your time, it will straight up, it will be like an albatross hanging on you because it affects how you think about things going forward. So although, it's funny, the operating assumptions that we work under have a huge, huge, huge influence. You mentioned growing up in the United States or this being a capitalist society, like, woohoo, all right. Now, of course, I think that. I don't really know any different otherwise. And I think that a lot of times people go, oh, communism is better. I'm like, haven't seen it. I haven't read any books about it being better, but it's possible. I mean, I haven't experienced it much myself either, so I can't dismiss it outright. But I guess I would say it's a fundamentally differing operating system underpinning and all of my choices, all of, if I honestly believed in that thing, many of my choices on a moment by moment, on a day by day, and certainly on a lifetime basis would be very different. So I would say that it's tough when you're young in the martial arts. And I mean, all of us are always trying to do our best to learn, but when you're young in the martial arts, you always go, if you're a reasonable guy, what do they call it? Like Dunning-Kruger amnesia. I can't remember if this is the right one, but basically you go like, oh, I know what I'm doing here. So I can say that's not right. But then I read a new story about baseball, and I don't know anything about baseball, it sounds credible, and it's bullshit. But I can't call bullshit. If you're a reasonable person, you can't call bullshit on things that you don't understand, even if you suspect it's not right. You're like, well, I've got a reserve judgment. You never, ever, ever set aside your need and also obligation to understand why you were doing what you're doing. And don't ask why once, ask why over and over and over and over about the same thing. Oh, well, I want a shrimp. Why? To make space. Why do I want to make space? To get away from the guy. Well, why do I want to get away from him? Well, because he's dangerous. Well, why is he dangerous? And you can oftentimes get down to, wait a minute, I didn't even need to move. Three quarters of the time, you're actually acting in the other person's self-interest. And I guess a lot of times I can't, this kind of goes beyond what we can demonstrate here. But I would just say, trying to understand what my base operating assumptions are and consistently reevaluate them, which can be fricking exhausting, frankly, and also comes on as confidence destroying. But you mentioned that I did pretty well relatively quickly. I started in 2004 and I was at Abu Dhabi ADCC for the first time as an alternate in 2007. I won a match there against the Black Belt World Champion. And the fact, frankly, the fact that I was able to beat someone like that was neat, but at the same time says a little bit more about what Jiu Jitsu is and some of the issues with it than it does about how cool I am or was, because that shouldn't really happen when you think about it. You're like, okay, you're a champion at ostensibly a very high level of the sport. You enjoy a three inch, four inch height advantage and a 35 pound weight advantage, and you just got beat. That should not exist. I'm dead serious that should not exist. If that happens, you're doing it wrong. Is it that I'm doing it right? Or is it that you're doing it wrong and there's enough variance in the way that you're doing it that you're allowing me to win? And now I did happen to win that with a 50-50 heel hook, which was 50-50. But basically, which was one of the early examples of like, hey guys, by the way, people can try to hurt your legs. And that was something like we mentioned John Danaher mentioned like myself, Dean Lister, a lot of the guys from the Hensel Gracie team that have had amazing success. They've gone and done great things. Craig Jones in the competitive grappling world, basically taking advantage of being very, very good in what they're doing, but also a glaring, glaring, glaring issue with the operating system of Jiu Jitsu, which was a huge vulnerability in the lower body and not only not attacking it, but having no idea how one does attack it, which means you can't understand how someone will assail you. So anyway, I guess to come back is if in the in the absence of knowing what to do, I try to polish what I've got. So if I've got a knife and I'm like, I don't know how to use them, like, okay, I'm just gonna sharpen the edge and polish it and make sure that when I need to use this dang thing, I'll be able to do it. Because trying to put together a system, when you don't have an idea of what's going on, a lot of times you end up making sub optimal choices. But as long as you're consistently reevaluating what you're doing, and that's something I've tried to do over time, over and over and over again, and try to seek out the most, the best and also most articulate or insightful instructors or people of various levels, doesn't matter if they're well known or not that could say, hey, Ryan, I think you should do this, I think you should do that. And I think all I've ever done in martial arts is try to treat people with respect, honestly, try to demonstrate appreciation for the many, many people who have helped me over time and be the type of person that they want to train with. Not the type of because we've all trained with people that make us think about beating the ever loving crap out of them. I never wanted to be that guy. And I was basically saying like, if I train with a black belt when I'm a blue belt, and, and this person enjoys training with me, that's in my interest, selfishly, not only do I not want them to beat me up, but selfishly, I should you mentioned being decent to other people, you want to incentivize being decent to other people, right with a structure of what you're doing. Selfishly, I'm incentivized to be a nice guy, even if I'm internally a scumbag, which I like to think that I'm not. But basically going like, hey, this guy's way more likely to help me or this person's way more likely to help me if I shake their hand, say thank you, I really appreciate you helped me out. And that thing that they tapped me with four or five times, I'm going to ask them about it. And then they don't have to tell me they're under no obligation. But I'll say and when they tell me don't thank you so much for your time, really appreciate it. And that that's it, you know, okay, so to summarize, so the way you brilliantly described, I just want to make sure we're keeping track. I went all over the place. No, you didn't. You're pretty on point. But so the first thing is basically, which is difficult, I wonder if we can break it apart a little bit, is don't trust authority, essentially, keep asking why. Be respectful without trusting authority, right? Right, which is and then the second thing is be the kind of person that others like training with or like being around, sort of being a good friend. So many people just enjoy being around. So one is complete, which is Yeah, you're right. It's attention, which is like completely disrespect the way that things are done. So asking why constantly, one of it is your own flaws and not understanding the fundamentals of what's being described. And then once you get good enough, not understanding, like going against the fact that the instructor doesn't understand. And my inability to understand what you're saying, though, doesn't invalidate it. And that's something like you mentioned, like, mentioned, keeping in mind our own flaws. And then also, again, the flaws that any of us have as the instructor, to your point, and I guess I can speak to being kind of weird. I don't, you know, I like to sit in the corner. But so everyone's a little bit different. Some people, you know, I wasn't terribly popular in high school. I, you know, I didn't like high school very much. But anyway, I would not going to be rude to people, though, I was never going to bully anybody. If you said hello to me, I'd say hello back, I would hold the door for you if you walk by, you know, and I would just say, like simple things like that go a long, long, long way. And that actually takes us back to our, to our social discussion where I'm like, Oh, man, how do I become great at Jiu Jitsu? It's like, well, I'll start by not pissing off this person who can beat the crap out of me, and not disrespecting the person who is probably the clearest, the closest thing to a font of knowledge at that time for me. So and then recognizing that I should do that for its own virtue, because it's the right thing to do and I should try to treat people decently. But beyond that, even selfishly, it's in my interest to do that. But see, the thing is, this is interesting, is there's a culture in martial arts, a culture that I like, where the instructor legitimately so carries an aura of authority. And it's not comfortable to really ask why. I'm not, it's a skill to be able to have a discussion as a white belt, the black belt instructor, of like, why is it done this way? Like, and saying why again? Like, I mean, it's a skill to show that you're actually legitimately a curious and passionate and compassionate student versus like somebody who's just being an annoying dick who saw some stuff on YouTube. There's a line between to walk there. I just wonder, because like, it's the drilling thing. You know, I, for example, like in my, when I was coming up, there was so much emphasis placed on like close guard, for example. And you might actually teach me now, I don't know. But to me, it was like, why do I need to master the close guard? Like, why is the close guard on top or the bottom? But the bottom, really, this is the fundamental basics of jiu-jitsu. Like, my body is not, my body says this is wrong. Like, this, like, I have short legs, but it doesn't even matter the length of legs. There's something about me that just, I don't understand how leverage here works for my particular body. Like, so, it's just, it's a feel thing too. Like, it feels like, in my basic understanding of leverage and movement and timing and so on, it feels like these certain, like, butterfly guard or even like half, basically every guard except close guard. I can play, I can dance. Close guard feels like you're shutting down the play that I- Is that wrong? Or is that, make sure that's what you want, because that's almost like an innate characteristic of this guard position, but it's not sold that way, right? It's like, hey, this is a good guard. It's like, hey, man, here's a bow and arrow versus, and you know how to use this thing, right? Like, make sure you're far away and like up on a hill or something, because you can take that bow and arrow, run up on something and try to use it. But if nobody told you not to do that, and they told you it was foundational, it's very foundational, it's very important. To everything else too, right? That's back to the shrimping thing. How many things are we taught that even if it's not, let's say itself is not a garbage thing, it might be effectively garbage. You could give me a Ferrari, but if I try to make it fly, it's not going to work. If you're like, but here's a plane, here's another plane, here's another plane, here's another plane, here's a Ferrari. I'm like, oh, it must be a different type of plane. You can be forgiven for leap if we're going there. Like, oh, maybe the wings come out or you just go fast enough, it's like a bullet. You can make these crazy leaps in your mind and people are doing that all the time. So if you don't provide the context for me, or worse yet, you provide improper context, like how much of a problem is that going to be? Well, I think the skill of the white belt should be just be nice. But in the complicated human space of when your intention, at least in the big picture view, is good. The question is, it's not always when your intention is good, the actual implementation of it is good. So you might be just almost, and that's much, it's not the case for you, it's much more the case for white belts. They don't even know, their intention might be good, but they don't know all the lines they're crossing, all the, so they're not actually able to interpret all the ways in which they're being totally insensitive to the requests of others, the explicit requests of others. So your job as a beginner is to be a really good listener of those social cues. It's like a visitor in a foreign country, right? Yeah. Like you're a representative of people that look like you, people that talk like you, people that have your passport and you're like, man, I'm going to go over here. Oh, I've got my foot up on my knee. Well, if I was in a certain conscious world, that's rude. I'm like, oh, I'm so sorry. But can you imagine if someone says, hey, I really appreciate if you take your foot off, that's pretty rude. And then I want to tell them, well, not where I'm from, man, I'm in your house. I better, again, I might go that direction, but let's say I could get away with that. Now I'm a bully. And if I can't get away with that, well, I'm about to maybe be on the wrong side of something. But I guess, like you said, if we have positive intention, that's fine. But I also have to recognize who I am. And I think that that's one thing that I tried to do and continue to try to do over time. Like we're, oh man, hi, I'm the one that's asking for a favor here. If I spar with Raymond Daniels, Raymond Daniels is doing me a favor. I ain't doing him a favor. Let's not get it twisted. So thank you so much for your time. I really appreciate it. These are not, and this is not like some affected nonsense. This is serious. I'm like, thank you. If I spar with Stephen Thompson, I'm the one being done a favor. George St. Pierre takes his time to spar with me, which he has in the past and not even kill me, which is really, I appreciate that because that's why I can sit here. George is not a prop for me to get my rocks off or see what's going on. And also I'm going to do that and then expect him to just take it. And I've seen, he's a gentleman. I've seen people get nuts with George and have him just be like, he's a patient of a saint. I don't have that level of patience, but I would just say to come back, figuring out like, hey, so what role am I here? And that comes back to like, at least what I see people on the internet. Yeah, man, I have a beef with Joe Rogan. You're like, no, you don't, Ryan. You're some goof. I'm like, I'm some random dude. Joe, people want it. They almost want to elevate so that we can somehow be level. We're peers here. If I go into Firas Al-Habib's gym, I'm not a peer of Firas Al-Habib. I'm a student of TriStar. I'm a guest in the academy. And if Firas asked me for something short of him telling me to try to do a triple backflip so I break my neck, the answer is, yes, sir, I can do it for you, Firas. No, man, no worries. And hopefully it should come with, I guess, a level of graciousness. But I guess that's kind of one of the things that I see nowadays with how accessible people are. Because I grew up being a big, huge baseball sports fan of all kinds. I couldn't send Derek Jeter a message and much less have a possibility of a reply. And if I do, it's like, I have people send me messages. It's very nice that people send me messages. Some people, again, not everyone is coming from the same place. But I've had plenty of things that are like, yo, dude, I need you to do this for me. I'm like, well, I'll tell you what's never going to happen. That. I have no idea who you are. And that was how I was addressed. And I don't need, oh, man, you're the greatest, one, because that's weird, and two, because I'm not. But just, hey, Ryan, how are you doing? Hey, do you think you could do the following if you get a second? Like, if I get a second, you're dang right, I can. Why not? It's easy to ask. But it started with some level of politeness. And I guess that's maybe being semi-Southern. I grew up in Virginia. Yes, sir. Yes, ma'am. That was a long way. Yeah, and there's all different kinds of implementations of politeness. I mean, most of the successful people I've met, it's been surprising to me how much of, you mentioned peers, like I could think of, Joe Rogan, you mentioned Joe Rogan, but Elon Musk, they almost treat me like I'm the superior. You know what I mean? Like, it's not even, that's the politeness. That's the approach. The feeling of it is like, I'm the student, I'm the beginner, I'm approaching a situation. It's almost like method acting of like, you're better than me. And that's how I approach a lot of interactions. Like, I have something to learn from this, even if it's like a young- Do you think that they're ungenuine? They're totally genuine. But isn't that a funny thing? Like, in spite of who they are, they're incredibly genuine because they respect, correct me if I'm wrong, they respect you, obviously, for what you bring to the table. No, no, they approach everybody like this. But that's what I, I'm sure they respect you for what you bring to the table. Beyond that though, they're treating you with dignity as a human being. Yeah, as a human being. That's right. Which, and when they could probably get away with treating most people without a whole heck of a lot of dignity. And I guess, what does that always say? That like, again, you can always tell someone of quality because they treat the king and the janitor the same way. But that's what we're seeing a lot. I guess I don't mean to nitpick, but that's where it would take issue, I guess, a little bit or disagree with- Are you going to criticize the internet again? Oh no. I'll give- People on the internet. The old man yells at clouds. But anyway, but I guess what I mean is just like the way that people address each other. Because it's so casual now. And it's great on the one hand, it's nice. On the other hand, you go, hey, I just, why can't, am I somehow, am I worried about diminishing myself? It's like the way that I'm sure that people talk to women sometimes. And where it's, what's up girl? Oh man, she's a bitch. Versus like, that was supposed to get a good response? What about that was going to elicit a favorable response? Versus being anything, anything other than just, yo man, what's going on? And I guess that, does that make any sense? It makes total sense. And that Southern thing that you're referring to, I feel like that's an important part of human communication. Let me ask you this. Your new back attacks instructional, first of all, awesome. Second of all, you drop a lot of fascinating insights in there. But you quote Galileo out of all people in saying that you can't teach a man anything, you can only help him find it within himself. So we talked about how to start in Jiu Jitsu. What about if we zoom out even more and how do you learn how to learn? How do you optimize the learning process? I don't know the answer to that, but I can tell you what I like to do. And I would say like, I can't, step one, I don't, I'm not, maybe this is a little bit easier for me because, you know, I've, I've never had a ton of friends, honestly. I've, you know, I've got my close friends and people that I know, but I never had tons and tons of people. So I spent a lot of time thinking and anyway, I can't, I can't control you. I can't control anybody else. I, you know, I, all I can, I want to take my, I guess Marcus Aurelius thing. It's like, you know, I guess the trick to life is figuring out what's in our control and what's not and focusing on things that are in our control, I guess. And so step one is figuring out both internally and then also out in the world as it pertains to Jiu Jitsu, what is actually in my control and what is not like passing someone's guard is not in your control. People think it is, it ain't. If I can't just do an activity and be unchecked, then it ain't in my control entirely. I can always breathe. I can always, you know, be calm. I can always, no matter whether I'm concerned or not concerned, have whatever you want to call it, nerves, you know, I can step forward across the line and say, I will, I will face the challenge ahead. That is all entirely, no one can stop me from doing that. That's entirely me. I control. And that's why I know that every single time that I walk into the ring, I'll walk in and out of there with my head held high because there's, I will fight with everything that I have. I can't promise that I'll win. I would say I'd take that same first principles. You mentioned last time we talked, you know, with Elon and the importance of that and going, what are the first principles? And I guess to come back, a lot of times, in my opinion, the things that people think are the basics are not the basics. You can't learn. If you think you're reasoning for first principles, but you're actually like level six, you're actually like layers up, you're making so many, there's so many baked in assumptions to what's going on that you're going to struggle to understand why anything is actually happening internally, externally, you name it. So I guess what I would start when it comes to learning is first principles and trying to understand what's going on. But then also simple things first. I can control my posture. I can control my breathing. No one can stop me from doing that. I can control where I place my frames. I can control where I place my limbs. I can move my feet. I can develop the ability to do these things better, of course. And I do that through practice, through drilling, through watching people. I've been incredibly fortunate in my time in martial arts to train with many of my heroes, to train with many of the people that I looked at and I was like, that guy is amazing. I want to train with this person. Like Stephen Thompson, Kenny Florian, George St. Pierre, Raymond Daniels, Feras Zahabi, I mean like Bruno Frizzato, Marcelo Garcia, all of these guys that are just unbelievable. And I go, well, they're moving in a way that's different. Well, how do I do that? Well, sometimes you can ask them and they can tell you directly. Other times people, part of the genius of what they do is that it's intuitive and maybe they don't think and understand and see the world the same way that I do. That was something that I experienced with Marcelo. He's amazing. But in a different way than his, it just, we see things fundamentally different. We experience the world differently, it seems to me that we do. And again, that taught me a really important lesson because I was wanting when I trained there to have someone go, hey, Ryan, do this, this, this, and this, and that's how it works. And I'm like, all right, because that's how I understood martial arts at the time. I wasn't ready to have someone tell me like, hey, it feels a little bit like this and I just kind of do it, which is kind of what Marcelo would do at the time as he was less experienced as a teacher, but that is what he was doing. I was completely, I couldn't separate in my mind performance and understanding. I thought that if I understand I could do it. And I would also wonder, I would also struggle sometimes to wonder why I couldn't execute things that I thought I understood and why guys like Marcelo were just so elemental. I mean, in like the lightning wind, like that type of thing, where like, it's just so in touch with what they wanted, with their capabilities. They could summon their powers at will. I couldn't always do that. And I guess, so recognizing that there was more than one way to the top of the mountain. And also I had a lot of science, but I didn't have a lot of art, or I had some science, I should say, but I didn't have a lot of art. Meeting people like Marcelo taught me. And then Josh Waitzkin, actually brilliant guy, chess champion, former owner, maybe owner of Marcelo's Academy, really great friend. I think he has a book on learning. He does. Yeah, the art of learning, actually. But yeah, he knows a thing or two about it, but a great guy. And anyway, he sat me down one time and was like, look, man, you're doing this wrong. You're missing what, they're missing the genius, the brilliance that's right in front of you. And it took me a long time. What did he mean? That I was frustrated with my inability to grasp certain things. And sometimes the teaching style being different, not wrong, just it was tough on me at the time. So you were trying to replicate what Marcelo was saying as opposed to understanding the fundamentals from which it was coming. Right, I couldn't see where it was coming from. And also sometimes I'm like, well, why can't you explain it in the way that I would want you to explain it? And he's like, well, why can't I meet him where he's coming from? So anyway, it was a really important time, unless I'm very, very frustrating if I'm honest, but it's not. I'm so thankful for that time. And anyway, I guess- Always first principles, trying to understand the basics, first starting at the place where you can control things, the very basic elements of what you can work with. And then when there's other mentors and teachers to- Meet them where they're coming from. Meet them with- To the extent that I can. Again, it's like, why are you not talking to me the way I want you to talk to me? As opposed to, hey, where are you coming from? Back to your point. But I know that's not entirely specific, but if you can focus on that and back to the whole, you can't teach a man anything. Marcelo didn't teach me anything, but he taught me in so doing and other people like that to find it within. And it's like, I guess something else that I've heard before is that all learning is self-discovery, but all performance is self-expression. And I always thought that Marcelo was a brilliant master of letting what's inside out. He was so consistent in his performances. And a lot of times I felt like there was a block there personally, particularly at the end of Jiu-Jitsu when I was very, very results oriented. And I think my focus was not ideal. It was definitely not in the place that I would like it to be. And whether I would have won more or lost more hard to say, but I know that I would have performed better if I'd have adjusted that. And anyway, that recognizing that again, Jiu-Jitsu, I think I've said it before, Jiu-Jitsu studies is a science, but expressed as an art. It doesn't matter if you can articulate what you know how to do, what matters is if you can do what you know how to do. It only matters if you're, I guess, if you're teaching in a verbal fashion is where the knowledge you can articulate it, but recognizing the difference between learning on an intellectual level or a conceptual level and being able to translate that into the physical. And I guess like that's been the thing that I feel like fortunate over time in my own academy to be able to kind of fiddle around and learn on my own and practice my students. And sometimes I've struggled to have great training partners. Like when I say great training partner, I mean, other world-class people to spar, to roll with, but I've gotten a lot more honestly than I ever would have thought out of being able to practice and learn and fail and try and succeed on my own without like my own little sandbox, figuring out how I can take an idea and then come up with drills and drills to practice it so that I can actually practice putting it into play. Because again, knowing an idea and then not drilling, what's the point? I'll never have it. It will never, it'll never see the light of day. So in that DVD, in that instruction DVD, sorry. It's an online instructional DVD. I keep saying DVD though. Nobody has DVDs anymore. Do they not? VHS. I don't know. Who has DVD? Well, like Blu-ray. I possess some DVDs. I mean, I've never watched them. What do you use them for? Like a cup, like a thing you put a drink on? I mean, when we're in a pinch, yeah. What's that even called? Coaster. Yeah. My matrix coaster. The matrix coaster. Zeros and ones. Okay. So in that instruction that people should get, I've been watching, I'm really enjoying. I don't even know when it came out recently, right? Like December, something like that? Yeah. It's... It's part one. It actually ended up being like 18 hours long. And I was like, oh my god, we're going to chop it in half. And when it comes together, the whole thing, I hope people will like it. Yeah. Well, even part one is really good. People on Reddit were really excited for part two as well. Really? And you also have a back... Oh, the old one. The old one that I... That was really helpful to me to understand some very basic aspects of control from the back. Really? Yeah. That was... That clicked with me. There's very few instructionals. There's very few things I've watched that ever clicked with me. And that was definitely it. It taught me one thing. I don't know. You drop a lot of really interesting details. And it's funny that there's only specific things that really click. Like a lot of it rings true and you kind of take it in. It's like, oh, that's interesting. Okay. Yeah. But there's certain things that really click. And I remember that first instructional that clicked with me is like the importance... I don't remember anymore how you communicated it because I've now integrated. It's now mine. You know what I mean? But it was more about you just describing upper body control and the importance of the upper body control from the back. And just like there's certain... You described different details on the grips and so on. And as I started trying it, I realized how important upper body control is versus like me maybe as a blue belt or something. I thought like you have achieved victory when you got the two hooks in. And then I realized like, at least for me, that the hooks were not even for my body type, for my style, for the way I approach things, they were not even important at all. Supplemental for the most part. Yeah. So they were there for the points, but I can establish a huge amount of control. In fact, the hooks were... You were talking about like illusion of choice. It almost made people panic a lot more when you were like fighting for or establishing that kind of control. They were a lot less panicked when the hooks weren't involved, even though they should be a lot more panicked. Anyway, I realized a lot of those kinds of things, especially that had to do with judo because so much of judo on the ground is centered around aggressive, efficient, very fast choking, different kinds of clock chokes and all that kind of stuff. What a brilliant thing that is only going to start to make its way into jiu-jitsu coming up, but like the judo style approach to like clock choking, triangling from the top of the turtle and stuff, so powerful. Yeah. And there's something about judo that emphasizes obviously due to the rules, the urgency. So you only do techniques that go fast. And then the other thing is, which I guess jiu-jitsu emphasizes too, but judo really does, which is the transition. So like while the person's flying in the air is the easiest time. I mean, this is like Ryan Hall type of shit, which is like, why not put in your submissions or positional control while they're in the air? If you could, why would you not? Right? Oh, well, I don't throw well. Well, learn how to throw and then do it. And so you should think, I mean, in the transition when they're flying is the easiest time to put in stuff. And that's when you think about chokes, as you're throwing, you should be thinking about the choke and then everything becomes a lot easier. You ever see Flavio Canto? Man, Brazilian judoka is so cool. Like with stuff like that. Yeah, exactly. But that has to do with the first starting principle of like, stop thinking this as a two-phase game of standing and then ground. Start thinking about like the standing and the, the standing comes before and the ground comes after, but everything happens in a transition. Well, unless you're attacking, what is the art of war? Like we all like, everyone's like, oh, yeah, the art of war. Oh, yes, yes. And then they immediately throw it away and then fight like a fricking barbarian. But I mean, like, I'm serious, but you know, how many people quote stuff and then like, you know, it's like, what is it, the family guy joke, or they're like, you know, quoting Jesus and Jesus walks in and he's like, you're not listening to my work. What are you talking about? And anyway, basically, you know, like what do you, like the art of war, you know, one of the things, it's like the only thing that you can be sure of being successful in attacking is something that's undefended. Yeah. But you know, in a fight though, they're defended. Well, are they? There's moments all the time where I'm borderline defenseless. And if you were to attack at that moment, if you could see it and then seize the moment, if you were capable of both, you should not only expect to be successful, you should be damn sure you're gonna be successful. And more, more important than that, you'll be successful. And even if somehow not, you won't be countered. And I guess like, that's the trick of almost all, all like conflicts, right? It's like showing up when the other person's, you know, taking a nap. And then it's so funny, like, we take like a protracted war, it's like, oh, it takes five years. And there's, you know, lulls, and there's a battle this month, but then there's a couple weeks, another battle. It's like, well, if you just shrink that down as the microcosm, macrocosm idea, that same thing, that same thing, that whole war is taking place in five minutes or 10 minutes or 15 minutes. And there's moments of lulls of person effectively going for a snack, you know, being like, you know, in a horror movie, like, hey, guys, I'm gonna go get a beer from the, from around the way, like I'm dead for sure. So anyway, is there on this particular instructional, if you can convert it to words, you talk about finishing the submission, is there some interesting insights that you find beautiful or profound about finishing the rear naked choke, or just finishing the submissions to the back control? Is there something like, you know, you talk about the squeeze and the crush and all these kinds of principles, is there something about control, about the process of finishing that you find especially profound about this position? Absolutely. The opposite of one profound truth can be another profound truth. So like, so like, it's, I do, Did Jesus say that? No, I don't. I actually was a guy on Tumblr. But yeah, it was really, really cool. There's like, like a tree in the background. But anyway, but so let's say like, I'll use, I'll use examples. Like first off, I saw someone finishing a 50-50 heel hook in the UFC one promo. It was like some chubby dude in a karate gi, like inside heel hook and another dude. And you go, huh? Well, I didn't know they were doing that back then, at least, and whether they were doing it or not. How many times does someone do something and then that works? And then we go, okay, cool, versus, hey, maybe we should do that all the time. So anyway, how long were we all taught to do the seatbelt the way we all do the seatbelt in Jiu Jitsu? Like a long time. Why? Works. In fact, it works so well. And it was so it was then the people who used it were so prolific that we went, well, solve that one. Good to go. All right, no more thinking. And then you go, imagine you were to like the Merkel and Merkel flip all those positions that were showing in the in the DVD, which is pretty much or the whatever the heck it is, and the digital VD. No, not VD. I don't want that digital digital video something. But basically, recognizing that doing it on the wrong side is at least as effective doesn't mean that the other side wasn't good. There could be something that's the literal borderline opposite of that. And you go, huh, well, that's something like imagine like I would say almost all of these things, all the tactics and all the strategies. So I guess that was something that we came to like training in the gym like a year ago, maybe I've been playing with since and it's just it's huge. I'm like, oh, wait, so let me get this straight. First, if I can use my strong side seatbelt, my right arm over the shoulder and all the time. Well, that's that's really helpful, because that's a lot better than my left. You can do both sides of my left. But if I had to bet my life on being able to finish it, I would want my right arm over. Huh, everything that's a tactic or a strategy evolved from an idea like capitalism is an idea. You know, anarchy is an idea. And then it becomes what does that all mean? What are the consequences? What's the fallout of all this? Right? So what if we start with jiu jitsu, the idea of the guard, right? And we go, well, I mean, when do you why do you use the guard? No other martial art really has developed the guard in the same way that jiu jitsu has. Well, what is the guard? A guard's a defensive idea where you're kind of on your back to some extent or another, and you're using your legs as a wall between you and the other person and the other guy represents danger. And you're like, yeah, that's a great idea. Is it? I mean, it clearly works, at least to a certain extent. But what where do I want to put my legs when I want to get up? Not on the other dude. I'm trying to put them on things on the floor. If I want to generate a ton of power, what's the first thing I do with my feet? I anchor them to the floor, drive for a punch, you name it, move away, jump, dart, you name it. So does it mean that that's a terrible idea to be on your back? No, clearly it works. And clearly it has function. But what if the function that we're giving it and how much focus we're assigning to it is disproportionate to its effectiveness? Maybe what if it's not a good idea? I'm not saying it's not a good idea, but what if it wasn't? That's a foundational idea of jujitsu. And then how much, because no one questions that foundation, how much innovation is built on top of the idea? Well, of course I want to be, my being on my back is an okay position. So now they're innovating, but they're innovating within a closed system that they don't even, they think they're innovating in like in this open space of, oh my God, it can be anything. When in reality, it could be anything within this little set, but you don't realize that you're in a set. You don't realize that you're in a box. There would be answers that would become so immediately apparent to you if you were willing to look outside of that, but you'll literally never even look over to your left because you don't even realize the left exists. Do you think there's a lot of places in jujitsu, whether it's back control or generally guards and all the different positions where there's a lot of space, like a lot to be discovered by questioning the basic assumptions? Maybe if you can give examples of like back control, like is there something you've discovered that's like- Merkel versus seatbelt. What's Merkel, what's seatbelt? Seatbelt is right arm over the shoulder, left arm under the arm. I'm on the same side as my choking arm. Merkel is just, I do the same thing. I don't even adjust my hands. I walk myself over to the left side. I'm on the opposite side. It's actually a more powerful position. And for people listening or for people who might not know, jujitsu is, seatbelt is a control. We're talking about when one person is on the back of another person, which is a really dominant position in jujitsu, seatbelt is, I guess, widely accepted way of holding your arm. Like best practices almost. Best practices, yeah. And it's worked so well. So it's one arm over, one arm under, and there's a certain side you're supposed to be on when you're on the back. Everyone teaches, there's a choking arm, that's the arm that's over, and your body's supposed to be on a certain side relative to that. And then Ryan is describing questioning these basic assumptions about which side you're supposed to be on. And let's say that's even just like a mid-level assumption. It's not even a first principles assumption, but it's getting there. But let's just say for sake of argument, it goes a lot deeper, maybe. I think most of the innovation that I see is not innovation. It's basically changing the color of a car or polishing the window a little bit where you're like, hey, you made it a little bit different. You made it a little bit better. It's like, oh man, what if I did the same guard and then grab the lapel? I'm not saying that's bad, but you're not fundamentally changing anything. I think most of the big seismic shifts that we see in almost anything come from, hey, that thing we thought was right was wrong, rather than not only is it right, it's even righter. And you're like, it's not wrong, it's not bad, but that's... It's like, oh man, let's say for instance, I didn't make the triangle better, but let's say I made the triangle a little bit better than it was, or than it was taught. I mean, you can call it innovation. I don't know, man. It's not like the person that said, hey, have you guys ever heard of a triangle before and came up with that? That's on the list. You can do this thing to people? Are you kidding me? Can you imagine you invented the straight right hand? You'd be like one punch man. You can walk around and just lay low every single person you got into a fight with because it didn't even occur to them to hit you with their backhand. In a world full of jabbers, you throw your backhand. You're going to kill people. So basically... Well, but by the way, I mean, just to pause on that, first of all, somebody did invent the triangle probably, right? For sure. It's not a trivial thing once you think... No. How many of these giant things that we all go like, oh yeah, we all use that now. Can you imagine you have triangles and heel hooks and rear naked chokes and I don't have those? You're unbeatable. You're borderline. I mean, that's why we all experience... Every single one of us, particularly those of us... I mean, when did you first start training legs? 12, 13 years. Well, let's not count wrestling, but 13 years ago with jiu-jitsu. Right on. So let's say about that time where particularly it was still like kind of underground-y and you're like, hey, we all experienced being a relative, a mid-level white belt and being able to easily beat up all our friends because everyone wrestled other buddies. And it was one of those ones where they don't have weapons to end the fight. You have weapons to end the fight. That's such a crazy asymmetric advantage that if you lose, it's on you now, man. Next time it's like, I've got this rifle and you have nothing. And I decided to put it on my back and then run over and try to karate chop. You're like, okay, next time, just make sure you use the rifle, bud. I'm like, oh yeah, I should do that. So yeah, it's kind of fascinating. I mean, everything you're describing, there's a fascinating tension between like whenever I show people for the first time what a triangle is, just like regular people. It's like they're discovering, it's like, oh, okay, that's interesting. I mean, MMA has changed that, but people haven't watched MMA. That's an interesting move. It doesn't make sense why that would be a choke. And they kind of quickly accept that that's a thing and they accept the basics without questioning, wait a minute, what's actually being choked? How is it that a shoulder of a person can do the choking? I'm not sure I fully questioned the fundamentals of all of that. What exactly is the blood supply that's being cut off? What is the anatomy and the physiology of all of that? Why does this work? And if you understood all that, what else can we do here? Yeah, what else can we do here? That's the really important thing. But if I'm an end user, which almost everyone is of almost anything, I'm serious, where I'm like, I think about stuff in my life, the only things I really think about are like martial arts and martial arts strategy and I don't know, some other couple of other things, but not much. And anything else in my life is borderline unexamined. And I like to think that if I put a lot of effort in something, I'd like to think that I could figure at least some things out about it. But I figured out almost nothing about anything in my life because I haven't even looked. And if you're an end user, what are you capable of versus you can literally alter the source code. You are Neo in the freaking matrix. If you can alter the code and I can't. And it's like, we think, ah, but imagine you are a world-class anything or even not even world-class, forget it, like a purple belt compared to a white belt or compared to a no belt might as well be John Jones or Marcello Garcia. You're going to beat them up comparably bad. So it's, that's, that actually is a common thing where people can't tell the difference between levels. They're like, oh man, I've trained with my black belt instructor. How much better could so-and-so be like so much better. You're going to have a hard time wrapping your head around it. I remember when I first trained with Marcelo Garcia in 2007, I was a decent purple belt. And of course he mollywagged me very gently. And then, uh, training him again in 2008, I was definitely better. I won the Ghi and Nogi worlds that you're a purple belt. So definitely for the record, I'm definitely not a jujitsu world champion. I wanted the purple belt, but like, that's not the same at winning a black belt. Um, and, uh, tough accomplishment, but not, not in the same thing at all. But anyway, um, and I was definitely better. He beat me up just the same. I'm like, okay, 2009, I was a lot better. Got a medal at ADCC that time won the trials, crushed everybody. Like no submitted everybody, like bop, bop, bop, bop. Train with Marcelo Garcia. It was worse. And, uh, 2010 training more cellular Garcia, same, same. So the idea was, uh, I wouldn't be able to tell you the difference in the outcome. Difference was the same in all of these rounds. I was significantly more experienced and more, more adept each time, each time that this occurred. But it was like, how many number of times did this person submit you or pass your guard in the round? I'm like, I don't know, probably like, let's say five each one, because it's a brief period of time. And let's say it was three on one, six on another one, whatever it's comparable. It's six, one half dozen. And would I be able to easily tell the difference? No, I would just say, I know in concept that he's way better, so much better, but there's plenty of other people that could have beaten me just as bad as Marcelo did when I was a purple belt or when I was a brown belt, then maybe I would watch Marcelo walk through like the borderline, not there. So it's neat. Like if you, that's back to kind of what I was talking about, about certain people beginning to really like peel back some of what's really special about the martial arts or any activity I presume, um, is they get to a level of understanding and depth that they're playing with like the, almost the reality of that thing. And I'm, I'm playing by rules that are not rules. I'm not, I'm not even one of the, to use a matrix analogy, I'm not even an agent, which is the best version of something playing by the rules. Yes. I'm like one of the regular people or one of the regular people in that got out of the matrix. So I'm like, oh, I'm cool. But when I fight an agent, I lose because we're both in the rules, but they just play them to the play them to the bone. And I'm just here. Well, and then the agent encounters Neo and they can do nothing. You're like, why? Because he's operating outside of what the rules are, but not really what the rules are, what they perceive to be the rules are clearly. So anyway, I guess that's kind of my point about Marcelo or certain other people that are doing things where you go, that doesn't even seem real. It doesn't seem real to me because I don't understand what's going on. And I guess if we can get down to base assumptions, like if we can constantly strip away, strip away, strip away, let's say we always thought that turning left was right, was correct. And it turns out that turning right was correct. Change your life. Yeah. It's a, what is it? Socrates said the unexamined life is not worth living. So you just basically have to rigorously just constantly examine every assumption over and over and over. But doesn't that give your life meaning to come back to the struggle, to come back to free will, to come back to what if we could strip all that away? All right, cool. All right. Let me just stick the needle in my arm and that's that. Yeah. No, I mean that, that constant striving for understanding yet another lower layer of the simulation we're living in is something that's actually deeply fulfilling that I don't know if it's genetically built in, but there's something about that striving to understand that seems to be deeply human. We, it's funny, what makes it human? We don't talk about the soul anymore, man. I went to Catholic school as a kid. Whether you buy into all that stuff or not, you're like, what about the soul of a person, the spirit of a people, the spirit of a nation, anywhere, the spirit of humanity. We don't, we don't, we talk about everything like it's this quantifiable thing when maybe certain things are, maybe everything is, but then what happens if there's things that just aren't quantifiable that nothing in our understanding can or will ever explain. And that doesn't mean that that should be our assumptions. If you are assumption, we can explain everything and let's get to the dang bottom, peel, peel, peel, peel, peel. But what if there is actually something that like that you, that we need challenge for? Yeah. And we could be looking in the wrong place by going, oh, where is it in the genes? Maybe it is. Again, I'm not saying we're looking at the wrong place. Like I wouldn't know anything. I do karate, but basically not even well. But yeah, we do karate, mediocre. Just ask Raymond Daniels or Stephen Thompson. But I guess to come back though, you just... Are you a yellow belt? Yeah. Or are you... Man, I actually have... Did you ever see the Seinfeld episode where Kramer fights the kids? Yeah, I did that at Raymond Daniels school and the kids, kids won in class as in addition to the alleyway. Oh. Yeah. They finished it off afterwards. Yeah, exactly. When I was on my last legs. But yeah, I would just maybe... It's funny. I feel like there's something deeply missing from public understanding and more that it's almost like the idea that we can figure everything out, which I deeply believe in, but also the possibility that there's some things that we'll never really see and some things we'll never understand. And there's something, like you said, uniquely human about the human experience that even if I had the power to change, I don't want to fuck with it, man. I don't want to change that thing. Oh yeah, well, wouldn't it be great if we just immediately knew the outcome of everything and you just press this button, you're like, oh, that's kind of... What's the point of living life then? Even if you could do it. It's the... Ian, you've seen Jurassic... Well, I'll leave you be. Sorry, I know what I'm talking about. Ian Malcolm, Jurassic Park, Jeff Goldblum, right? Life finds a way. But we were so concerned with whether or not we could, we didn't stop to think whether or not we should. Maybe? I think there's, I mean, it's a deeply human thing, but it's also a really useful thing to always kind of assume that there's this giant thing that you don't understand. So you can forever be striving to understand because that process gives you meaning, but also keeps making you better. Like thinking that, actually even just thinking that you can't understand everything will lead you to stop too early. So I think there's something to, whether it's the soul or whether it's like religious stuff, like assuming that there's this thing that you cannot possibly understand is a really good assumption under which to operate and under which to do this first principles kind of thinking, because you can just keep digging and keep digging and keep digging, even when it seems like you're at the bottom, because you don't fucking know if you're at the bottom or not. And back to your original, back to one of our, I guess, our other kind of tangents was that comes back to everyone's a human being. The smartest human being in the history of humanity is so hilariously weak, like short-lived and not intelligent. Keep it for yourself, bro. I understand. I didn't say, no, I'm not saying comparison to me. In comparison to me, everyone is awesome, but that's why I don't do the goat thing. But basically, basically it's just on a cosmic level. Can you imagine if you were a vampire, you're like 900 years old, like how much you would seem, you would seem like a lowercase g God to people. Yeah. You'd be like, how can you, how could you know so much? How can you have such a long view perspective? It would be insane. So, I mean, that it seems like we're talking about AI now, right? Where we're creating things that are infinitely smarter than us effectively and live all this time. And it's probably going to do what we tell it to do, right? No, it's probably, well, I hope it keeps us around. Do you, by the way, think about AI and the existential threats? Like speaking of gods, are you, is this whole technological world, we talked about social networks and this increasing power of technology around us, we ourselves are becoming less human because we keep relying on technology more and more. So we're becoming kinds of cyborgs, but also there's a future that's quite possible where the technology becomes smarter and more powerful than us humans. And, you know, starts having a life of its own in ways that perhaps we don't imagine as human beings. I don't just mean like two-legged robots walking around and being humans, but smarter. I mean like an intelligent life that's beyond and fundamentally different than our human life. It's infinite, it's- Also creating a new species, yeah? Yeah, a new kind of species, not even just a new species. We're talking about systems, but like it lives in the space of information, it lives in a different time scale, in a different scale of all sorts, spatial scale. It operate, like we spoke about individuals, it doesn't operate in the sense of a single individual, like it's not embodied. So it's not like a thing that walks around and it like, it looks at stuff and it consumes the world. It's able to do much larger scale sensing of the environment around it, all that kind of stuff. I can barely even try to, I can barely even conceive of what that would be like. Are you scared or are you excited? I don't define scared or excited. I feel like I tend to define them like the same way, where I'm like, I guess I'm- Kind of like before karaoke, it's the same- Well, that's actually kind of my happy place. It's not so much everyone else's. Everyone else is probably heading for the door at that point, but it's- While you're doing it or leading up to the karaoke session? Well, it depends whether or not they know it's me. If they know it's me, that's before I start. If they're like, who's that guy? Then they're like halfway through the song, they're already throwing their beer. What categories of song or particular song are we talking about in terms of your happy place? Oh man, are you kidding me? I mean, obviously Bohemian Rhapsody. I mean, there's no question because- Really? Oh yeah, because I don't have to sing it here. It's that. It's like, remember, can I beat Khabib? Oh yeah, of course. Is he here? No? Yeah, then yeah. Yeah. All right. Well, I like- Is he here? No, then I- I have a torn, I have torn feelings about Bohemian Rhapsody because I like the beginning part, the sadness. I like the solo, the heartbreak. But the second part, I understand it, but it's so- Well, it gets ridiculous. It's so ridiculous. It ruins it for me. But it's more about flexing on people, I think, if you can actually hit that near the falsetto. Yeah. So it's not, okay. So you appreciate not for the musical beauty and complexity of the song, you just like to flex on people. Well, because like for all, yeah. Like what's the purpose of anything except for just to let everyone know that you think you're cool. And there's no better way of doing that than karaoke. So I'm not sure why I brought up karaoke. Captive audience. Yeah, exactly. Oh, about fear and excitement of artificial intelligence. I mean, you know me, I don't know anything about it. I just, basically, I don't understand the implications of any of this. I would just say that like radically altering what it means to be human in such an unbelievably short period of time just seems like such a crazy thing. And also, it's not like we're, I can't remember who said this to me recently. I can't remember. So this is definitely not my idea. But we're not even going, hey, would you like to opt in everyone? Everyone is being opted in. And particularly when you want to talk about large scale robotics or large scale AI, the world is changing. People in Senegal are opting in right now without realizing it. It's not even like, and again, I don't mean to pick on Senegal. It's just whatever country comes up to mind, but that's in the developing world. But basically, recognizing that this huge shift is coming, we have no idea if this is a decent idea. And also, something else I've always been considering is you think about most of the really awful, awful, awful things that have done in history, large scale slavery, you name it. People say that it came from this motivation or that motivation. Maybe it did, maybe it didn't. Fundamentally, the issue, at least in my mind, I'm not a historian, power differential. If you and I can't contest, we don't contend, it's not like we fight and you might win or we fight, even you'll win comfortably. It's you are so unbelievably powerful compared to me that there's nothing I can do to stop you. That seems like a recipe for something really, really not great happening. Because if you think about European countries encountering each other, and I'm just speculating, I don't know anything about history, but let's say countries that can contend with one another versus countries that can't. Let's say an alien species, alien race shows up right now. We don't want that. I think Stephen Hawking said that. It makes perfect sense to me. We don't want that. If you can come here, we better hope you're nice. Because what are we going to do? What are we going to hope? That you invade the water planet like they did in one of the... Lord of the Worlds. So I guess what I'm trying to get across is shocking levels of power differential between groups makes the world ripe for horrific abuse in the event that someone decides to do it. It's like you imagine an adult hitting a child, hitting, hitting a child, no one in their right mind would ever go, like, oh yeah, that's a great idea. Because it's so grossly imbalanced. You're like, this is wrong. But it's also on the table only because of the gross imbalance. So I guess to come back, it's like whether we create AI and it's on some crazy level of its own, or it's I'm in charge of it, or it seems like we're creating... You mentioned game theory and nuclear war. What prevented nuclear war? I mean, presumably mutually assured destruction. I mean, hopefully also humanity and the humanity and the reasonable, cooler heads prevailing and going, hey, I can understand the veil of ignorance. And I don't go, oh yeah, let me kill those guys because I can. I go, this is wrong, period. And in concept, this is not an action I should take. But it's also nice and easy to keep me honest if I know that I can't get you without being got myself. But what happens when I can get anyone anything and I'm more or less untouchable? That seems to me to be like various times in colonial history, you know what I mean? And what happened? We know what happened. But so the possibility of really bad things are plentiful, the possibilities. But are the possibilities of really positive things are plentiful. Like what though? I'm not saying wrong. I just want to know. So I can give a million examples. One is just the examples of the parent and the child. You said there's a power differential there and we don't like a parent hitting their child. What about not just hitting, like beating? Great, beating their child. How often, percentage-wise, do you see that happening? Even though that power differential, first of all, other people's kids, let's just put this on the table, I love kids, but other people's kids can be annoying sometimes. Sometimes you got to deal out some justice, I get it. But we don't practice, we don't take advantage of that power differential. So there is ethics, there's moralities that emerge that allow the power differential to be used for good versus for bad. So one of the assumptions with Stephen Hawking or with if Russia became much more powerful than America or America much more powerful than Russia in the Cold War, your assumption that immediately that power differential, not your assumption, but- Would express itself, right? Would express itself in the same way that it was trying to express itself when there was a more level competition. But it's also possible when the power differential grows, the incentive, the joy, whatever the mechanisms that made sense when it was at the same level, the incentives become very different. It's not as fun to destroy the ant colony, you start becoming more the kind of a conservationist. One hopes. That's an evolved perspective though, yeah? Well, I don't know if it's evolved or not, but it's definitely a possibility. It's unclear to me that something that's many orders of magnitude more powerful than us will want to destroy us. Well, I mean, how did mass slavery occur? How did, like, just big dogs playing with not? I think slavery and a lot of the atrocities in history happened when the power differential was not as great as we're talking about with AI potentially. Is that not somehow worse than? It's not obvious to me. It's not obvious that things that are way more powerful- That's fair, okay. So I think you're- I guess, how do you restrain it though? There's a lot of different discussions of how to- I guess even restrain each other, because let's say I go and decide to strike someone's child, which I'd like to think I wouldn't do. I will be promptly, I will find myself in front of a judge. And so I feel like there's a lot. Can you imagine how many people used to get murdered just in the woods? I mean, I would just presume it's a lot. And I don't think most people are lunatics like that, but I would just say- But that's the point. If you're given though, if you're given to that, your ability to get away with it was greater in the past because of chance of detection was less. So does it- I don't know. Yeah, yeah, yeah. You're going to be unreasonable. This is what is called an artificial intelligence, AI safety research called value alignment of ensuring as you build the systems that become smarter and smarter and more powerful and powerful, make sure that their values are aligned with the entities over which they're becoming powerful with humans. So if you were to talk to an AI that's becoming smarter, first it's dumber than you, but it's becoming smarter and smarter, you have to create mechanisms where you both value the same things. I guess one thing I wonder, so I guess I'm probably not sharp enough to grasp this if I'm honest, but I guess I wonder, I used to do chess programs. You know, it was deep blue, stockfish, and then like alpha zero and alpha zero teaching itself to beat stockfish without any help in four hours. Yeah, yeah. Like it becomes orders of magnitude more intelligence than us in effectively an instantaneous period. I guess what I always wondered, if you were that much smarter than me, I feel like your ability to manipulate me would be pretty significant or at least potentially. But manipulation implies that the incentive is to overpower everything around you. Mm-hmm. Like there's implied incentives. If your value is to actually, like, it depends what you want in life. Okay. What you want in your system. It's not clear that the goal of an AI system that's all powerful is to destroy all humans. No, I don't think that it is either. I guess what I'm- Or even enslave all humans. That's fair. I guess what I'm trying to suggest is that something adequately powerful, these actions are on the table. Yes, they're on the table and that's scary. And that's why a lot of people are really concerned about it and are working on it. I'm just trying to make the case for AGI because if they're watching this, he's the one to kill. No, actually, I was thinking I was, yeah. I wash toilets, like, really well. No, I mean, that's the main concern for all the people in the AI safety research. People talk about AGIs. It's kind of disturbing how little people are working on trying to create mechanisms that keep AI's values aligned with ours. That's completely unshocking. Yeah. We humans seem to do only good when, like, you know, you even look at, like, coronavirus. It's like, the water has to be leaking from the ceiling. You have to be- Fine, fine. Blood everywhere, fire, just destruction. We just seem to ignore completely any trouble. Writing all over the wall. Writing all over the wall. This is fine. Yeah, I'm sure nothing to see here will be okay. But we do all right, especially in the United States. You figure out, even when it becomes a really serious problem, taking actions last minute. There's something about the innovative spirit that results in a solution last minute, right before the deadline. It works out. Well, I mean, I don't know how you did school. Probably a lot better than me. No, that's exactly how I did school. I couldn't be- I was no motivation up until, like, the last- if you're like, we have 22 hours to do the entire semesters of work. Like, let's do this. Yeah. And you get, like, 19 freaking Mountain Dews, and then, yeah. Well, that's why you and I are failures in life. Because I just talked to- I mentioned Cal Newport, with his book, Deep Work, and so on. He is of the variety of these creatures that basically does everything ahead of time. That's shocking. Because he dislikes the- he thinks it's unproductive to experience the stress and anxiety of the deadline. Because you're just- you're not going to be your best performance-wise, and you're not going to do the best work. So it doesn't make any- it's completely irrational to function based on the deadline. You should have a system, a process that gets stuff- a little bit of stuff done every day. Like, you should be- and constantly be systematically honest with yourself. If you say, I'm going to get this stuff done today, and this week, at the end of the day, at the end of the week, you have to then reflect on what you did, who you planned, and improve that plan, update it constantly, update it every day, every week, every quarter, whatever those durations are. As I'm listening to this and reading his stuff, it's like, oh, yeah, I agree with everything. I'm like, yes, I'm clapping. But the reality is- and then I go back and just eat Cheetos and don't do shit until the last minute. You're being cheesy. Actually, I don't eat Cheetos, but yes. But actually, again, not that it's ever going to matter because he's so shockingly productive and well thought out that whatever I've decided to think about trying to monkey wrench in there is definitely going to be able to deal with. But it's funny that, again, because you're a human being, not a god, all of your strengths have a corresponding weakness. The less you practice working under the gun, the less comfortable you are working under the gun. The more practice you have working under the gun, the better you get at it. The downside is you're always working under the gun, so you're less productive. Or it's like your work quality maybe drops. So it's an interesting thing. It's almost like, hey, I wonder if Khabib Nurmagomedov has a lot of heart. And I try to say the answer is almost certainly yes. But you go, well, he hasn't struggled a bunch. Maybe he doesn't struggle well. And it just so happens that he can also work under the gun really well. He just doesn't like to do it. But yeah, but it's an interesting thing. It's like, I guess, what is it? The Aristotle we are, we repeatedly do. We are all practicing something all the time. So I guess it's funny. I guess that's a question that I have, though. I would love to ask him. It'd be really neat. Is certain jobs, I mean, obviously you want to have preparation always, always. But certain things have a degree of entropy in the system. And you go, I need to practice working under the gun. And I'm not saying that's what I need to do because fighting it should be, for the most part, it's a really sterile environment in the grand scheme of things. Fighting in a cage is very sterile compared to most other things in life. But dangerous, but sterile. Unless, of course, like the other guy, the raft decides to hit you, which would be hilarious. But anyway, I guess just going like, okay, so at what value do you get out of adding a degree of, let's say, it could even be planned by someone else, but junk in the system and you just have to work under the gun to make it happen. Let's say, for instance, for police or something like that, the situation turns left hard at some random point in time. And that could happen to any number of people. So I guess it's interesting, things that allow for perfect planning or quasi perfect planning versus things that are inherently unstable. And then what's the psychological fallout of comfort with that? Because I think a lot of people that are really comfortable under the gun let it happen a lot. For all the good and the bad of that, does that make sense? No, that totally makes sense. I mean, his answer would be that you have to be honest with yourself if it's valuable for your success to practice being under the gun, and then you should schedule that. Yeah, then he's smart. You should plan that. You should systematically, and then as opposed to doing it half-assedly, because as opposed to letting the environment choose the randomness, like control the randomness to where, like, optimize it. I wish it's so efficient it's shocking just to hear about it. Yeah, no, he's annoying. I mean, the same way you are, he's annoying in the same way, which is like he drops truth bombs. It's like, yeah, that's so true. Yeah, we're probably comparably doing that. No, there's just... But he's, so his profession requires that. So he's not just like a motivational speaker or whatever. He's a theoretical computer scientist, and he needs the long hours in the day of doing like serious math. So it's mostly math proofs. And for that, you have to sit and think really deeply. It's like really hard work compared to like what most people do. Like, even what I, I mean, what I do, like programming is way easier than rigorous math proofs because you have to, basically, you have this machine and you have to, your brain to churn out logic in a focused way while visualizing a bunch of things and holding that in your brain and holding that for 10 minutes, 20 minutes, hopefully several hours. And you're not just like doing homework. You're doing totally novel stuff. So like stuff that nobody's ever done before. So you keep running up against the wall of like, fuck, this is a dead end. Oh, no, wait, is this a dead end? And like that whole frustration, that's serious mental work. That's like incredibly difficult mental work. So he knows what he's talking about. That's amazing. But like you said, he's like, this seems like the standard for the quality of work that he needs is so high. So high. That almost anything less than this level of systematization and organization would preclude it. Right? So he can't afford the kind of bullshit that, I don't know about you, but that certainly I do, which is like last deadline kind of stuff. Cause you can't do that kind of work last minute on deadline kind of stuff. So my question for him in general is like, and for you and I is like, well, here's these negative patterns that we do of like doing shit last minute and so on. Is this just who we are now? Or are there some... I don't think I'm really big into a free will. I was thinking that it's mostly predestination, at least in this regard. It's the same with like communism. Like as long as it fits my, whatever is the lazy thing to do, I'll just not believe in free will. Yeah. I'm not a communist opportunist. Okay. That's what I meant. I'm an opportunistic communist and capitalist. I just do whatever is cool at the time. Exactly. Let me ask you to examine some fundamental principles of a particular thing that Joe Rogan brought up to me several times online and offline, which is that he thinks that the tie that I wear is something that makes me vulnerable to attack that you should be... The reason he doesn't wear a tie is because he can get choked very easily with a tie. It's a big concern. Okay. My contention, and by the way, he wore a suit last time too. He didn't wear it on the podcast. He wore it for dinner later. Yeah. I wore a suit the other day and I had no socks on. I didn't realize... Yeah. You're supposed to wear a suit. Yeah. You're supposed to wear socks. Yeah. That's my understanding. Why'd you wear a suit? Did you go to court? No, no. I didn't. No. I don't know. I just wanted to play. I wanted to pretend I was an adult for a day. Okay. Cool. So my contention is the jacket, everything is more dangerous than a tie. That's kind of where I was going with that. That's kind of where, yeah, it was my first thought too. Once the tie becomes an issue... I feel like everything else is already an issue. It's already an issue. Yeah. Because the tie to me, now without messing with it now, to me has some of the similar problems that a belt does. So for example, I don't know about you, maybe you can correct me, but I'm not sure you can use the belt as tied. I know there's some kind of guards you can probably utilize the belt with, but the belt, sorry, when it's tied around the waist. Are you talking about a belt belt or a gi belt? Sorry, gi belt. Okay. Sorry, gi belt. Importantly, gi belt. It's not that great of a thing to use in most cases, I would say, because it slides. Yep, that's true. It doesn't... You can probably invent a few interesting ways to use it as leverage, as control and so on, but there's just so many more things around the gi belt that are better. Yeah. And so for me, the tie, what people don't realize... I suppose. Are we trying to sell a DVD here and have some widgets and bells and whistles? Because in that case, the belt is a really important part of what we do, and I would really encourage you guys to look into it. Yeah. If we're trying to actually learn something, I'd say, like you said, we're surrounded by better options. Well, that's the thing. I mean, it's not obvious to me that the belt... Maybe there's actually undiscovered things about using the belt. I think people have used putting a foot inside the belt somehow, inside the gi belt. This is a no punches gi grappling situation, yes? Right. Okay. Yeah, I guess so. Sort of fairly contrived, right? But with punches too. Is there... Okay, let's talk about a street fight with a belt that's like a jeans belt, like a belt, clothing belt. Okay, so I get to take it off and whip them in the face with the buckle? How serious is this street fight? Are we talking like that bar in Oakland? No, but they're not just... No, 100% serious. One of them gets beat up, or are we talking like... No, like death. Like one of you has to die. Oh, yikes. Whoa. Okay. Oh, you ever... I'm in this situation all the time. I understand. And there's a reason I'm still here. I had somebody start a fight with me at Starbucks the other day. I fight kids. We're talking about power differential. Yeah. I just beat up kids all the time. Just pick the easy Ws. You gotta get the easy Ws. You don't want the horrible... I'm undefeated. Come around the playground, watch what happens. No, to the death, what is their clothing that's useful? For my perspective... For your use or their use? Both. For my use, their use. No, I like how you went to take the belt off and used the buckle to hit them with. But first of all, how are you going to take off the belt? Well, essentially... There's a lot of effort involved in unclothing. Well, what I was figuring was when they started to see me take my pants off in the fight, they were like, what? They're going to pause and rethink the situation for a second? Yes. And I'm making dead eye contact. Obviously, what's going on? So that... Yeah, exactly. Nodding. And then by the time they realize you took a belt off until you could whip them with it, you actually... You're already one, possibly two steps ahead. Okay. So fine. Let's not talk about your own clothing. Let's talk about their clothing. Okay. I'll take off their belt and hit them with it. No, but that's much harder. No question. But if you can do it... While maintaining... How did it come to this? But the point is there's alternatives that are perhaps more effective. In my perspective, this might be clueless, there's almost no clothing that's more effective than almost assuming the situation is no geek grappling. I feel like clothing... Particularly when you start to add hitting. Every single time I start grabbing your clothes, you start hitting and it's not like nothing could work. But most of the time you're like, why am I not using my arms for something better than what I'm doing them right now? Right. Yeah. It's very difficult for me to... I don't know, in terms of just distance, I can't imagine a case of different distances. Even situations where... Let's not talk about like a situation where you haven't both yet agreed that a fight is happening. Solid clothing is nice if they have it on then. Solid clothing? Oh yeah. Something like a good jacket, because you can snatch somebody on their face. Snatch. Snatch down. Yeah. If you took my... You snap down in judo, how easy it is to snap down a beginner. So I agree with you. Actually, a tie in that sense might be a really effective way to snap down. So like the snap down is really powerful to change the... Disorient the situation and give you a lot of different opportunities for taking their back, taking them down. Doing hilarious stuff like snapping them down with a tie into your knee. And then when they come back up doing this and you're already... So yeah, in that sense, I agree. But not as a choking mechanism. Because the concern Joe had is the choke. I think you'd probably choke me with your tie more easily than I could choke you with your tie. Probably. I'm serious. Because if you get my back and you can put it around somebody's neck, you ever see Die Hard? Yeah. Yeah. You remember when the super Swedish looking blonde dude or whatever was trying to choke Bruce Willis with the chain? And then he ended up getting choked himself with the chain, if I recall this properly. But anyway, yeah, like that. But I don't feel like... I feel like if I start grabbing your tie, you have too many other great options. I mean, I do like the snap down. You actually made me realize that. No, I think you're good there. What's that? I think you're on the right path with it. With a snap down? Yeah. Particularly if you start with one of these, like you poke your finger in my chest and then snap down real quick. Oh yeah. Because also, socially speaking, it's not a threatening thing to reach for the tie. Particularly in a business setting. You know what I mean? They'll never see it coming. Yeah. Because I was thinking choke. But it's a really good leverage point. Because grabbing a jacket, the jacket will slide if you try to snap down. You really have to get a hole, like a really good hole. That's a good point, because it's around the back of the neck. But what if it's clip on? How much of a jackass would you look like if you're like... And then they just... Yeah. A sticky one. But you ever see the Japanese politician? Or I think it was Japan. The Judo throw? Yeah. He was so calm and cool. It was beautiful technique. The level of... Actually, the throw was even gentle. But yeah, it was perfect. It was amazing. Well executed. Yeah. More of our politicians, they just toss the shit out of each other. Yeah. We need more Teddy Roosevelt. Exactly. Our politicians like talking about fighting when it's clear that none of them even would ever have been in a fight ever. Yeah. Somebody was saying Teddy Roosevelt is interesting. I didn't realize this. He's one of the greatest presidents this country's had. And he was one of the greatest presidents, even though he faced no crisis whatsoever. He literally willed himself. Nothing happened during his presidency. He's just a bad motherfucker who made really great speeches. So you're like, this made me realize, I was just talking to a historian that most of the people who we think are great need also a good crisis that reveal their greatness. Muhammad Ali, right? This Muhammad Ali. I mean, in sports... But you know what I mean? The circumstances, what is greatness? It's not just your capacity, it's what you face. It's the quality of opposition, circumstance, what you overcome. So I guess what you're saying is Joe Rogan is wrong about the Thai thing. I don't want to go so far as saying he's wrong. The man's not here to defend himself. Maybe he has some things that I'm not understanding. I'm willing to give him... No, he has not deeply thought to this. This is my main criticism of Joe. He's not deeply thought to this. And the MMA journalists will be like, Ryan Hall says Joe Rogan is wrong. And hates Thais. And hates Thais. They'll integrate Hitler back in there somehow. Nice, nice. What's... You're talking about greatness, and greatness requiring a difficult moment in time. In time. Can you reflect back and think, what are some of the hardest, if not the hardest thing you've ever had to do in your life? Well, I think I've had a bunch of things. I've had a lot of things knock on my way. I've been incredibly fortunate. I've had a lot of things go my way also. But leaving Team Lord Irvin in 2008, which I firmly believe was the right thing to do, is one of the... That was very difficult at the time. Not a difficult choice, but it was because of why I was leaving. But... Psychologically. First of all, loss in general. Leaving team, a family, of all kinds. It doesn't matter what the circumstances. I didn't lose any friends, but I lost a lot of people I thought were my friends. And I lost training. I lost... I'd also had a really serious... My wrist only does that. So, I had a really serious wrist surgery that I didn't know if I was going to be able to compete anymore. After that, I just got my brown belt. It was a tough time, psychologically, physically, everything. But I was very, very motivated to do my best and to push through it and to carry on in a positive direction no matter what, in a different direction. Were you lonely? This is the thing about family. Even if it's an abusive family, leaving is tough. People are complicated. And even people that I don't think very well of, that I think on the whole I don't think very well of, it's unfair to paint them with one brush. Obviously, there's greater and lesser examples of that, like the person we discussed last time, who's an infinitely beyond almost anyone that we could ever imagine meeting in our own personal lives. Yeah. Bloody elbow. Yeah. In terms of forgiveness and hate, do you have hate in your heart for people in your past? No. For that process? No. There were definitely times where I've been negatively motivated to prove people wrong or to accomplish things in spite. And I think that some of that is valuable if I'm aligned, if I felt differently. I think particularly I do really well in conflict. I'm useless... This is the usual deadline thing. I'm useless, yeah. You like the chaos? I'm useless, yeah, I do. I'm useless. I'm an antagonist. I like fighting. I like competition. I like being pushed. I like feeling like if I don't play well, I'm going to get hurt. I have no choice but to play well, or play with everything I got at the very least. And I guess I would say, though, as I've gotten more time and lived a little bit longer, you see various situations with increased color, I guess I would say, increased clarity. And there are a lot of lessons to be learned even from times in history or bad experience that we have. And the question is, can we take those lessons and move forward? And that's, again, what I think we're seeing in sometimes socially right now. We're forgetting important lessons of the past. And that's not good. Not saying, hey, I don't get why we could be going in this direction or that. I understand entirely. But hey, let's not forget the lessons so we don't have to learn them again, because that doesn't really serve anybody. And anyway, I guess I would say I'm thankful for all of the experiences, difficult and otherwise, mostly difficult, honestly. Most of the times I remember, I'm thankful for every loss I've ever had, particularly the tough ones. I'm thankful for all the relationships. Many people have taught me many things and continue to teach me many things, some of whom are still some of my closest friends, some of whom are people I really don't get along with at all. And some of whom are people I think really poorly of. Although there's not many of that last group. What I guess I would say is there's been a lot of things and opportunities to learn throughout that. And also, it's not as if I've never made any mistakes myself. Now, again, there are magnitude differences, I like to think. And I can definitely say that none of the mistakes that I've ever made have been mistakes of intention. I've screwed up a lot of things in my life, but I can confidently and easily say that I've never had ill intent towards people as I've done it. So, we sit there and like, man, is this the right thing? Is this the right thing? And sometimes I've been wrong. But you never sit out with malicious intent. And I think that when I find that I think people do things differently, when I do think that there is malicious intent, I have a difficult time forgiving that. How does love win over hate, Ryan Hall, in this world? We talked about social media, we talk about forgiveness of some of the more complicated people in your past. If we scale that to the entire world before the AI destroys us, and the human race is lost to history, how do you think love wins over hate? Well, I'd like to preface this by saying I tried to make pancakes the other day. Yes. It didn't work. But I'm happy to comment on this. So, basically, I think most of the times that I can think of that I've struggled, and the times that I've read about, is being unable to see the humanity in other people, and also even in sometimes our enemies, and the people that have done awful things. And you go, what would allow people to do this, that, or the other? And that doesn't forgive what they've done, depending upon, you know, some things are forgivable, some things are less so. But you want to understand why. It's like, to our knowledge, demons don't populate our world. Neither do like literal angels walking around being actually perfect. A lot of times, the things that it's, I find it deeply amusing watching, you know, people hoisted by their own batard on Twitter, even though it's gross, and it's really unproductive. It's actually like equal parts amusing and like awful, because you're not happy that someone's being raked over the coals, particularly unjustifiably. But it is funny when it's the exact same thing they were raking others over the coals for, not like a week or two prior, and that's happened repeatedly, and will continue to happen. And I guess I would say, as you mentioned, you know, a prior, you know, like a recognition of the humanity of others, of that all of us make mistakes, that it's difficult to understand intention. I've had arguments with close friends of mine over text message, where both of us ended up super pissed, because we were completely misreading what the tone, the intention of what the other person was doing. And even if I was reading it correctly, which I wasn't, it's so easy to ascribe the most negative possible, you know, the least charitable assessment of what they're doing. And I think that that's such a dangerous way to live your life, and it's also just a fruitless way to live your life. You know, it's one thing to go, hey, why did you do that? I was pissed. What did you do? You did that to make yourself feel better. I'm like, you're damn right I did. And have I done that plenty of times in my life? Yeah, I would lie if I said that I didn't. You know, why did you punch that guy in the face? He was going crazy at me and hit me, and I asked him to stop, and then I gave a warning, and I put him on his ass. I'm like, no, I'm not sorry. But then looking back now with years to sit on, I'm like, do I understand why I did what I did? Absolutely. Would I like to respond differently now? Yeah, I would. You know, and it doesn't mean that – I think plenty of things that people do are understandable. Understandable doesn't mean correct. Understandable doesn't mean that you go, oh, yeah, that's great. You go, I could see someone doing such a thing. But I guess just trying to understand and see the humanity in others, because if I can't see the humanity in others, how can I see it in myself? And also, how am I meant to interact with everyone? As you said, even if we're a society of individuals, or at least for the time being, hopefully, in perpetuity, we still come together as a whole. And watching – it's weird, like you said, it's – if I only ask why once, I start with, stay out of my way, and I'll stay out of yours. Leave me the fuck alone. You're like, okay, that's fine, Ryan, but that's easy for you to say living in a society that doesn't actually function like that. So it's a little bit cheap. But if I recognize that that's step one, is I don't hurt you, and you don't hurt me, but then we go, but how can I help you? That's step two. And then it goes way beyond that and a lot further than I've thought about it. But I guess what I would just say is, again, recognition of the humanity in others, and that we all have different strengths, we all have different weaknesses, and you can never really be sure where the other person's coming from. But if we approach things charitably, as charitably as we would hope others would approach us, I think we'll do a lot better. And I guess one thing that I read that I liked that I thought was accurate and unfortunately disappointing was everyone is a great jury – I'm sorry, a great lawyer for themselves and a judge for others. And I think that's a terrible way to live life, even if it's an understandable one. Yeah. I don't know. I think probably flipping that is the right way to live. Being constantly judgmental of yourself and a defender of others. And that results ultimately in an interaction that de-escalates versus escalates. Right. Yeah. And we can all live in a world like that. And sometimes you're like, hey man, people that deserve punishment won't get it. Like, okay, hey, but what do they say? Better to have 10 guilty people go free than one innocent person burn. And ultimately, I think that is a better world than the other way around. And if all else fails, join the team that builds the AI that kills all humans. Yeah, obviously. I mean, if you have to be on a team, pick the winning team. That's been the... That's my hiring pitch, actually. That's a good hiring pitch. You still taking resumes? You want to be on the team that doesn't die during the great apocalypse. Not immediately. You want to be on the one that's eventually long suffering and stepped on, right? Yeah. Life is suffering, Ryan Hall. This was an amazing conversation. I really enjoyed talking to you. I could probably talk to you for many more hours. I hope I do as well. Ryan, I love you, buddy. This was a great conversation. Thanks for talking today. Thank you so much for having me. I really appreciate it. Thanks for listening to this conversation with Ryan Hall. And thank you to our sponsors, Indeed Hiring Website, Audible Audiobooks, ExpressVPN, and Element Electrolyte Drink. Click the sponsor links to get a discount and to support this podcast. And now, let me leave you with some words from Frank Herbert in Dune. I must not fear. Fear is the mind killer. Fear is the little death that brings total obliteration. I will face my fear. I will permit it to pass over me and through me. And when it has gone past, I will turn the inner eye to see its path. Where the fear has gone, there will be nothing. Only I will remain. Thank you for listening and hope to see you next time.

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Matt Botvinick: Neuroscience, Psychology, and AI at DeepMind | Lex Fridman Podcast #106

The following is a conversation with Matt Botmanick, Director of Neuroscience Research at DeepMind. He's a brilliant, cross-disciplinary mind navigating effortlessly between cognitive psychology, computational neuroscience, and artificial intelligence. Quick summary of the ads. Two sponsors, The Jordan Hartminger Show and Magic Spoon Cereal. Please consider supporting the podcast by going to jordanhartminger.com slash Lex and also going to magicspoon.com slash Lex and using code Lex at checkout after you buy all of their cereal. Click the links, buy the stuff. It's the best way to support this podcast and the journey I'm on. If you enjoy this podcast, subscribe on YouTube, review it with Five Stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman, spelled, surprisingly, without the E, just F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This episode is supported by The Jordan Hartminger Show. Go to jordanhartminger.com slash Lex. It's how he knows I sent you. On that page, subscribe to his podcast on Apple Podcast, Spotify, and you know where to look. I've been binging on his podcast. Jordan is a great interviewer and even a better human being. I recently listened to his conversation with Jack Barsky, former sleeper agent for the KGB in the 80s and author of Deep Undercover, which is a memoir that paints yet another interesting perspective on the Cold War era. I've been reading a lot about the Stalin and then Gorbachev and Putin eras of Russia, but this conversation made me realize that I need to do a deep dive into the Cold War era to get a complete picture of Russia's recent history. Again, go to jordanhartminger.com slash Lex. Subscribe to his podcast. It's how he knows I sent you. It's awesome. You won't regret it. This episode is also supported by Magic Spoon, low-carb, keto-friendly, super amazingly delicious cereal. I've been on a keto or very low-carb diet for a long time now. It helps with my mental performance. It helps with my physical performance, even during this crazy push-up, pull-up challenge I'm doing, including the running. It just feels great. I used to love cereal. Obviously, I can't have it now because most cereals have a crazy amount of sugar, which is terrible for you. So I quit it years ago. But Magic Spoon, amazingly, somehow, is a totally different thing. Zero sugar, 11 grams of protein, and only three net grams of carbs. It tastes delicious. It has a lot of flavors, two new ones, including peanut butter. But if you know what's good for you, you'll go with cocoa, my favorite flavor, and the flavor of champions. Click the magicspoon.com slash Lex link in the description and use code LEX at checkout for free shipping and to let them know I sent you. They've agreed to sponsor this podcast for a long time. They're an amazing sponsor and an even better cereal. I highly recommend it. It's delicious. It's good for you. You won't regret it. And now, here's my conversation with Matt Botvinick. How much of the human brain do you think we understand? I think we're at a weird moment in the history of neuroscience in the sense that I feel like we understand a lot about the brain at a very high level, but a very coarse level. When you say high level, what are you thinking? Are you thinking functional? Are you thinking structurally? So in other words, what is the brain for? You know, what kinds of computation does the brain do? What kinds of behaviors would we have to explain if we were gonna look down at the mechanistic level? And at that level, I feel like we understand much, much more about the brain than we did when I was in high school. But it's almost like we're seeing it through a fog. It's only at a very coarse level. We don't really understand what the neuronal mechanisms are that underlie these computations. We've gotten better at saying, you know, what are the functions that the brain is computing that we would have to understand, you know, if we were gonna get down to the neuronal level? And at the other end of the spectrum, we, you know, in the last few years, incredible progress has been made in terms of technologies that allow us to see, you know, actually literally see in some cases what's going on at the single unit level, even the dendritic level. And then there's this yawning gap in between. Well, that's interesting. So at the high level, so that's almost a cognitive science level? Yeah, yeah. And then at the neuronal level, that's neurobiology and neuroscience, just studying single neurons, the synaptic connections and all the dopamine, all the kind of neurotransmitters. One blanket statement I should probably make is that as I've gotten older, I have become more and more reluctant to make a distinction between psychology and neuroscience. To me, the point of neuroscience is to study what the brain is for. If you're a nephrologist and you wanna learn about the kidney, you start by saying, what is this thing for? Well, it seems to be for taking blood on one side that has metabolites in it that shouldn't be there, sucking them out of the blood while leaving the good stuff behind, and then excreting that in the form of urine. That's what the kidney is for. It's like obvious. So the rest of the work is deciding how it does that. And this, it seems to me, is the right approach to take to the brain. You say, well, what is the brain for? The brain, as far as I can tell, is for producing behavior. It's for going from perceptual inputs to behavioral outputs, and the behavioral outputs should be adaptive. So that's what psychology is about. It's about understanding the structure of that function. And then the rest of neuroscience is about figuring out how those operations are actually carried out at a mechanistic level. That's really interesting. But so unlike the kidney, the brain, the gap between the electrical signal and behavior, so you truly see neuroscience as the science that touches behavior, how the brain generates behavior, or how the brain converts raw visual information into understanding, like you basically see cognitive science, psychology, and neuroscience as all one science. Yeah. It's a personal statement. I don't mean to. Is that a hopeful or a realistic statement? So certainly you will be correct in your feeling in some number of years, but that number of years could be 200, 300 years from now. Oh, well, there's a. Is that aspirational, or is that pragmatic engineering feeling that you have? It's both in the sense that this is what I hope and expect will bear fruit over the coming decades, but it's also pragmatic in the sense that I'm not sure what we're doing in either psychology or neuroscience if that's not the framing. I don't know what it means to understand the brain if part of the enterprise is not about understanding the behavior that's being produced. I mean, yeah, but I would compare it to maybe astronomers looking at the movement of the planets and the stars without any interest of the underlying physics, right? And I would argue that at least in the early days, there's some value to just tracing the movement of the planets and the stars without thinking about the physics too much because it's such a big leap to start thinking about the physics before you even understand even the basic structural elements of. Oh, I agree with that. I agree. But you're saying in the end, the goal should be to deeply understand. Well, right, and I think, so I thought about this a lot when I was in grad school, because a lot of what I studied in grad school was psychology, and I found myself a little bit confused about what it meant to, it seems like what we were talking about a lot of the time were virtual causal mechanisms. Like, oh, well, you know, attentional selection then selects some object in the environment and that is then passed on to the motor, you know, information about that is passed onto the motor system. But these are virtual mechanisms. These are, you know, they're metaphors. They're, you know, there's no reduction to, there's no reduction going on in that conversation to some physical mechanism that, you know, which is really what it would take to fully understand, you know, how behavior is arising. The causal mechanisms are definitely neurons interacting. I'm willing to say that at this point in history. So in psychology, at least for me personally, there was this strange insecurity about trafficking in these metaphors, you know, which were supposed to explain the function of the mind. If you can't ground them in physical mechanisms, then what, you know, what is the explanatory validity of these explanations? And I managed to soothe my own nerves by thinking about the history of genetics research. So I'm very far from being an expert on the history of this field, but I know enough to say that, you know, Mendelian genetics preceded, you know, Watson and Crick. And so there was a significant period of time during which people were, you know, productively investigating the history of genetics. Productively investigating the structure of inheritance using what was essentially a metaphor, the notion of a gene, you know. Oh, genes do this and genes do that. But, you know, where are the genes? They're sort of an explanatory thing that we made up. And we ascribed to them these causal properties. Oh, there's a dominant, there's a recessive, and then they recombine it. And then later, there was a kind of blank there with a physical mechanism. That connection was made. But it was worth having that metaphor because that gave us a good sense of what kind of causal mechanism we were looking for. And the fundamental metaphor of cognition, you said, is the interaction of neurons. Is that, what is the metaphor? No, no, the metaphor, the metaphors we use in cognitive psychology are things like attention. Okay, gotcha. The way that memory works. I retrieve something from memory. A memory retrieval occurs. What is that? That's not a physical mechanism that I can examine in its own right. But it's still worth having, that metaphorical level. So, yeah, I misunderstood, actually. So, the higher level of abstractions is the metaphor that's most useful. Yes. But what about, so how does that connect to the idea that that arises from interaction of neurons? Well, even, is the interaction of neurons also not a metaphor to you? Or is it literally, like, that's no longer a metaphor. That's already the lowest level of abstractions that could actually be directly studied. Well, I'm hesitating because I think what I wanna say could end up being controversial. So, what I wanna say is, yes, the interactions of neurons, that's not metaphorical. That's a physical fact. That's where the causal interactions actually occur. Now, I suppose you could say, well, even that is metaphorical relative to the quantum events that underlie. You know, I don't wanna go down that rabbit hole. It's always turtles on top of turtles. Yeah, it goes all the way down. There is a reduction that you can do. You can say these psychological phenomena can be explained through a very different kind of causal mechanism, which has to do with neurotransmitter release. And so, what we're really trying to do in neuroscience writ large, as I say, which for me includes psychology, is to take these psychological phenomena and map them onto neural events. I think remaining forever at the level of description that is natural for psychology, for me personally, would be disappointing. I wanna understand how mental activity arises from neural activity. But the converse is also true. Studying neural activity without any sense of what you're trying to explain, to me feels like at best, groping around at random. Now, you've kind of talked about this bridging of the gap between psychology and neuroscience, but do you think it's possible, like my love is, like I fell in love with psychology and psychiatry in general with Freud when I was really young, and I hope to understand the mind. And for me, understanding the mind, at least at that young age, before I discovered AI and even neuroscience, was to, is psychology. And do you think it's possible to understand the mind without getting into all the messy details of neuroscience? Like you kind of mentioned, to you it's appealing to try to understand the mechanisms at the lowest level, but do you think that's needed, that's required to understand how the mind works? That's an important part of the whole picture, but I would be the last person on Earth to suggest that that reality renders psychology in its own right unproductive. I trained as a psychologist. I am fond of saying that I have learned much more from psychology than I have from neuroscience. To me, psychology is a hugely important discipline. And one thing that warms my heart is that ways of investigating behavior that have been native to cognitive psychology since its dawn in the 60s are starting to become, they're starting to become interesting to AI researchers for a variety of reasons. And that's been exciting for me to see. Can you maybe talk a little bit about what you see as beautiful aspects of psychology, maybe limiting aspects of psychology? I mean, maybe just start it off as a science, as a field. To me, when I understood what psychology is, analytical psychology, like the way it's actually carried out, it was really disappointing to see two aspects. One is how small the N is, how small the number of subject is in the studies. And two, it was disappointing to see how controlled the entire, how much it was in the lab. It wasn't studying humans in the wild. There was no mechanism for studying humans in the wild. So that's where I became a little bit disillusioned to psychology. And then the modern world of the internet is so exciting to me. The Twitter data or YouTube data, data of human behavior on the internet becomes exciting because the N grows and then in the wild grows. But that's just my narrow sense. Like, do you have a optimistic or pessimistic, cynical view of psychology? How do you see the field broadly? When I was in graduate school, it was early enough that there was still a thrill in seeing that there were ways of, there were ways of doing experimental science that provided insight to the structure of the mind. One thing that impressed me most when I was at that stage in my education was neuropsychology, looking at, analyzing the behavior of populations who had brain damage of different kinds and trying to understand what the specific deficits were that arose from a lesion in a particular part of the brain. And the kind of experimentation that was done and that's still being done to get answers in that context was so creative and it was so deliberate. It was good science. An experiment answered one question but raised another and somebody would do an experiment that answered that question and you really felt like you were narrowing in on some kind of approximate understanding of what this part of the brain was for. Do you have an example from memory of what kind of aspects of the mind could be studied in this kind of way? Oh, sure, I mean, the very detailed neuropsychological studies of language function, looking at production and reception and the relationship between visual function, reading and auditory and semantic. And there were these, and still are, these beautiful models that came out of that kind of research that really made you feel like you understood something that you hadn't understood before about how language processing is organized in the brain. But having said all that, I mean, I agree with you that the cost of doing highly controlled experiments is that you, by construction, miss out on the richness and complexity of the real world. One thing that, so I was drawn into science by what in those days was called connectionism, which is, of course, what we now call deep learning. And at that point in history, neural networks were primarily being used in order to model human cognition. They weren't yet really useful for industrial applications. So you always found neural networks in biological form beautiful. Oh, neural networks were very concretely the thing that drew me into science. I was handed, are you familiar with the PDP books from the 80s? I went to medical school before I went into science. Really? Interesting. Wow. I also did a graduate degree in art history, so I kind of explore it. Well, art history, I understand. That's just a curious, creative mind. But medical school, with the dream of what, if we take that slight tangent, what, did you want to be a surgeon? I actually was quite interested in surgery. I was interested in surgery and psychiatry, and I thought, I must be the only person on the planet who was torn between those two fields. And I said exactly that to my advisor in medical school, who turned out, I found out later, to be a famous psychoanalyst. And he said to me, no, no, it's actually not so uncommon to be interested in surgery and psychiatry. And he conjectured that the reason that people develop these two interests is that both fields are about going beneath the surface and kind of getting into the kind of secret. I mean, maybe you understand this as someone who was interested in psychoanalysis at an early stage. There's sort of a, you know, there's a cliche phrase that people use now, you know, like in NPR, the secret life of blankety-blank, right? And that was part of the thrill of surgery, it was seeing, you know, the secret, you know, the secret activity that's inside everybody's abdomen and thorax. That's a very poetic way to connect it to disciplines that are very, practically speaking, different from each other. That's for sure, that's for sure, yes. So how did we get onto medical school? So I was in medical school, and I was doing a psychiatry rotation, and my kind of advisor in that rotation asked me what I was interested in. And I said, well, maybe psychiatry. He said, why? And I said, well, I've always been interested in how the brain works. I'm pretty sure that nobody's doing scientific research that addresses my interests, which are, I didn't have a word for it then, but I would have said about cognition. And he said, well, you know, I'm not sure that's true. You might be interested in these books. And he pulled down the PDB books from his shelf, and they were still shrink-wrapped. He hadn't read them, but he handed them to me. He said, you feel free to borrow these. And that was, you know, I went back to my dorm room, and I just, you know, read them cover to cover. And what's PDP? Parallel Distributed Processing, which was one of the original names for deep learning. And so I apologize for the romanticized question, but what idea in the space of neuroscience, in the space of the human brain, is to you the most beautiful, mysterious, surprising? What had always fascinated me, even when I was a pretty young kid, I think, was the paradox that lies in the fact that the paradox that lies in the fact that the brain is so mysterious and seems so distant, but at the same time, it's responsible for the full transparency of everyday life. The brain is literally what makes everything obvious and familiar. And there's always one in the room with you. I used to teach, when I taught at Princeton, I used to teach a cognitive neuroscience course. And the very last thing I would say to the students was, when people think of scientific inspiration, the metaphors often, well, look to the stars, you know, the stars will inspire you to wonder at the universe. And, you know, think about your place in it and how things work. And I'm all for looking at the stars, but I've always been much more inspired. And my sense of wonder comes from the, not from the distant, mysterious stars, but from the extremely intimately close brain. There's something just endlessly fascinating to me about that. Like Jessica said, the one is close and yet distant in terms of our understanding of it. Do you, are you also captivated by the fact that this very conversation is happening because two brains are communicating? So the, I guess what I mean is the subjective nature of the experience, if you can take a small tangent into the mystical of it, the consciousness, or when you're saying you're captivated by the idea of the brain, are you talking about specifically the mechanism of cognition? Or are you also just, like, at least for me, it's almost like paralyzing the beauty and the mystery of the fact that it creates the entirety of the experience, not just the reasoning capability, but the experience. Well, I definitely resonate with that latter thought. That latter thought, and I often find discussions of artificial intelligence to be disappointingly narrow. You know, speaking as someone who has always had an interest in art. Right, I was just gonna go there, because it sounds like somebody who has an interest in art. Yeah, I mean, there are many layers to full bore human experience. And in some ways, it's not enough to say, oh, well, don't worry, we're talking about cognition, but we'll add emotion. You know? There's an incredible scope to what humans go through in every moment. And yes, so that's part of what fascinates me, is that our brains are producing that, but at the same time, it's so mysterious to us. How? You know? Like, we literally, our brains are literally in our heads producing this experience. Producing the experience. And yet, it's so mysterious to us. And the scientific challenge of getting at the actual explanation of the experience and the actual explanation for that is so overwhelming. That's just, I don't know. Certain people have fixations on particular questions, and that's always, that's just always been mine. Yeah, I would say the poetry of that is fascinating. And I'm really interested in natural language as well. And when you look at artificial intelligence community, it always saddens me how much, when you try to create a benchmark for the community together around how much of the magic of language is lost when you create that benchmark. That there's something, we talk about experience, the music of the language, the wit, the something that makes a rich experience, something that would be required to pass the spirit of the Turing test is lost in these benchmarks. And I wonder how to get it back in, because it's very difficult. The moment you try to do real good, rigorous science, you lose some of that magic. When you try to study cognition in a rigorous scientific way it feels like you're losing some of the magic. Seeing cognition in a mechanistic way, that AI at this stage in our history. Well, I agree with you, but at the same time, one thing that I found really exciting about that first wave of deep learning models in cognition was the fact that the people who were building these models were focused on the richness and complexity of human cognition. So an early debate in cognitive science, which I sort of witnessed as a grad student, was about something that sounds very dry, which is the formation of the past tense. But there were these two camps. One said, well, the mind encodes certain rules, and it also has a list of exceptions, because of course, the rule is add E D, but that's not always what you do, so you have to have a list of exceptions. And then there were the connectionists who evolved into the deep learning people, who said, well, if you look carefully at the data, if you actually look at language corpora, it turns out to be very rich, because yes, there are most verbs, and you just tack on E D, and then there are exceptions, but there are rules. The exceptions aren't just random. There are certain clues to which verbs should be exceptional, and then there are exceptions to the exceptions, and there was a word that was kind of deployed in order to capture this, which was quasi-regular. In other words, there are rules, but it's messy, and there are structure even among the exceptions, and it would be, yeah, you could try to write down the structure in some sort of closed form, but really, the right way to understand how the brain is handling all this, and by the way, producing all of this, is to build a deep neural network, and train it on this data, and see how it ends up representing all of this richness. So the way that deep learning was deployed in cognitive psychology was, that was the spirit of it. It was about that richness, and that's something that I always found very compelling. Still do. Is there something especially interesting and profound to you in terms of our current deep learning neural network, artificial neural network approaches, and whatever we do understand about the biological neural networks in our brain? There's quite a few differences. Are some of them to you either interesting or perhaps profound in terms of the gap we might want to try to close in trying to create a human-level intelligence? What I would say here is something that a lot of people are saying, which is that one seeming limitation of the systems that we're building now is that they lack the kind of flexibility, the readiness to sort of turn on a dime when the context calls for it, that is so characteristic of human behavior. So is that connected to you to the, which aspect of the neural networks in our brain is that connected to? Is that closer to the cognitive science level of, now again, see, my natural inclination is to separate into three disciplines of neuroscience, cognitive science and psychology, and you've already kind of shut that down by saying you're kind of seeing them as separate, but just to look at those layers, I guess, where, is there something about the lowest layer of the way the neurons interact that is profound to you in terms of its difference to the artificial neural networks? Or is all the key differences at a higher level of abstraction? One thing I often think about is that, if you take an introductory computer science course and they are introducing you to the notion of Turing machines, one way of articulating what the significance of a Turing machine is, is that it's a machine emulator. It can emulate any other machine. And that to me, that way of looking at a Turing machine really sticks with me. I think of humans as maybe sharing in some of that character. We're capacity limited, we're not Turing machines, obviously, but we have the ability to adapt behaviors that are very much unlike anything we've done before, but there's some basic mechanism that's implemented in our brain that allows us to run software. But just on that point, you mentioned Turing machine, but nevertheless, it's fundamentally, our brains are just computational devices in your view? Is that what you're getting at? It was a little bit unclear to this line you drew. Is there any magic in there, or is it just basic computation? I'm happy to think of it as just basic computation, but mind you, I won't be satisfied until somebody explains to me what the basic computations are that are leading to the full richness of human cognition. Yes. It's not gonna be enough for me to understand what the computations are that allow people to do arithmetic or play chess. I want the whole thing. And a small tangent, because you kind of mentioned coronavirus, there's group behavior. Oh, sure. Is there something interesting to your search of understanding the human mind where behavior of large groups, or just behavior of groups is interesting, seeing that as a collective mind, as a collective intelligence, perhaps seeing the groups of people as a single intelligent organism, especially looking at the reinforcement learning work that you've done recently? Well, yeah, I can't, I mean, I have the honor of working with a lot of incredibly smart people, and I wouldn't want to take any credit for leading the way on the multi-agent work that's come out of my group or DeepMind lately, but I do find it fascinating. And I mean, I think it can't be debated. The human behavior arises within communities. That just seems to me self-evident. But to me, it is self-evident, but that seems to be a profound aspects of something that created. That was like, if you look at 2001, Space Odyssey, when the monkeys touched the, like that's the magical moment, I think Yuval Harari argues that the ability of our large numbers of humans to hold an idea, to converge towards idea together, like you said, shaking hands versus bumping elbows, somehow converge, like without even, like without being in a room altogether, just kind of this like distributed convergence towards an idea over a particular period of time seems to be fundamental to just every aspect of our cognition, of our intelligence, because humans, we'll talk about reward, but it seems like we don't really have a clear objective function under which we operate, but we all kind of converge towards one somehow. And that to me has always been a mystery that I think is somehow productive for also understanding AI systems. But I guess that's the next step. The first step is try to understand the mind. Well, I don't know, I mean, I think there's something to the argument that that kind of bottom, like strictly bottom-up approach is wrong-headed. In other words, there are basic phenomena, basic aspects of human intelligence that can only be understood in the context of groups. I'm perfectly open to that. I've never been particularly convinced by the notion that we should consider intelligence to adhere at the level of communities. I don't know why, I'm sort of stuck on the notion that the basic unit that we want to understand is individual humans. And if we have to understand that in the context of other humans, fine. But for me, intelligence is just, I stubbornly define it as something that is, you know, an aspect of an individual human. That's just my, I don't know, that's my take. I'm with you, but that could be the reductionist dream of a scientist, because you can understand a single human. It also is very possible that intelligence can only arise when there's multiple intelligences. When there's multiple, sort of, it's a sad thing, if that's true, because it's very difficult to study. But if it's just one human, that one human will not be, homo sapien would not become that intelligent. That's a possibility. I'm with you. One thing I will say along these lines is that I think, I think a serious effort to understand human intelligence, and maybe to build a human-like intelligence, needs to pay just as much attention to the structure of the environment as to the structure of the, you know, the cognizing system, whether it's a brain or an AI system. That's one thing I took away, actually, from my early studies with the pioneers of neural network research, people like Jay McClelland and John Cohen. You know, the structure of cognition is really, it's only partly a function of the, you know, the architecture of the brain and the learning algorithms that it implements. What it's really a function, what really shapes it is the interaction of those things with the structure of the world in which those things are embedded, right? And that's especially important for, that's made most clear in reinforcement learning, where a simulated environment is, you can only learn as much as you can simulate, and that's what made, what DeepMind made very clear with the other aspect of the environment, which is the self-play mechanism of the other agent, of the competitive behavior, which the other agent becomes the environment, essentially. And that's, I mean, one of the most exciting ideas in AI is the self-play mechanism that's able to learn successfully. So there you go. There's a thing where competition is essential for learning, at least in that context. So if we can step back into another sort of beautiful world, which is the actual mechanics, the dirty mess of it, of the human brain, is there something for people who might not know, is there something you can comment on or describe the key parts of the brain that are important for intelligence, or just in general? What are the different parts of the brain that you're curious about, that you've studied, and that are just good to know about when you're thinking about cognition? Well, my area of expertise, if I have one, is prefrontal cortex. So- What's that? Where do we- It depends on who you ask. The technical definition is anatomical. There are parts of your brain that are responsible for motor behavior, and they're very easy to identify. And the region of your cerebral cortex, the sort of outer crust of your brain that lies in front of those is defined as the prefrontal cortex. And when you say anatomical, sorry to interrupt, so that's referring to sort of the geographic region, as opposed to some kind of functional definition. Exactly. So this is kind of the coward's way out. I'm telling you what the prefrontal cortex is just in terms of what part of the real estate it occupies. It's the thing in the front of the brain. Yeah, exactly. And in fact, the early history of neuroscientific investigation of what this front part of the brain does is sort of funny to read, because it was really World War I that started people down this road of trying to figure out what different parts of the brain, the human brain do in the sense that there were a lot of people with brain damage who came back from the war with brain damage. And that provided, as tragic as that was, it provided an opportunity for scientists to try to identify the functions of different brain regions. And that was actually incredibly productive. But one of the frustrations that neuropsychologists faced was they couldn't really identify exactly what the deficit was that arose from damage to these most kind of frontal parts of the brain. It was just a very difficult thing to pin down. There were a couple of neuropsychologists who identified through a large amount of clinical experience and close observation, they started to put their finger on a syndrome that was associated with frontal damage. Actually, one of them was a Russian neuropsychologist named Luria, who students of cognitive psychology still read. And what he started to figure out was that the frontal cortex was somehow involved in flexibility, in guiding behaviors that required someone to override a habit, or to do something unusual, or to change what they were doing in a very flexible way from one moment to another. So focused on like new experiences. And so the way your brain processes and acts in new experiences. Yeah. What later helped bring this function into better focus was a distinction between controlled and automatic behavior. Or in other literatures, this is referred to as habitual behavior versus goal-directed behavior. So it's very, very clear that the human brain has pathways that are dedicated to habits, to things that you do all the time. And they need to be automatized so that they don't require you to concentrate too much. So that leaves your cognitive capacity free to do other things. Just think about the difference between driving when you're learning to drive versus driving after you're fairly expert. There are brain pathways that slowly absorb those frequently performed behaviors so that they can be habits, so that they can be automatic. That's kind of like the purest form of learning, I guess, is happening there, which is why, I mean, this is kind of jumping ahead, which is why that perhaps is the most useful for us to focusing on and trying to see how artificial intelligence systems can learn. Is that the way you think? It's interesting. I do think about this distinction between controlled and automatic, or goal-directed and habitual behavior a lot in thinking about where we are in AI research. But just to finish the kind of dissertation here, the role of the prefrontal cortex is generally understood these days sort of in contradistinction to that habitual domain. In other words, the prefrontal cortex is what helps you override those habits. It's what allows you to say, whoa, whoa, what I usually do in this situation is X, but given the context, I probably should do Y. I mean, the elbow bump is a great example, right? Reaching out and shaking hands is probably a habitual behavior, and it's the prefrontal cortex that allows us to bear in mind that there's something unusual going on right now, and in this situation, I need to not do the usual thing. The kind of behaviors that Luria reported, and he built tests for detecting these kinds of things, were exactly like this. So in other words, when I stick out my hand, I want you instead to present your elbow. A patient with frontal damage would have a great deal of trouble with that. Somebody proffering their hand would elicit a handshake. The prefrontal cortex is what allows us to say, hold on, hold on, that's the usual thing, but I have the ability to bear in mind even very unusual contexts and to reason about what behavior is appropriate there. Just to get a sense, are us humans special in the presence of the prefrontal cortex? Do mice have a prefrontal cortex? Do other mammals that we can study? If no, then how do they integrate new experiences? Yeah, that's a really tricky question and a very timely question because we have revolutionary new technologies for monitoring, measuring, and also causally influencing neural behavior in mice and fruit flies. And these techniques are not fully available even for studying brain function in monkeys, let alone humans. And so it's a very, for me at least, a very urgent question whether the kinds of things that we wanna understand about human intelligence can be pursued in these other organisms. And to put it briefly, there's disagreement. You know, people who study fruit flies will often tell you, hey, fruit flies are smarter than you think. And they'll point to experiments where fruit flies were able to learn new behaviors, were able to generalize from one stimulus to another in a way that suggests that they have abstractions that guide their generalization. I've had many conversations in which I will start by observing, you know, recounting some observation about mouse behavior where it seemed like mice were taking an awfully long time to learn a task that for a human would be profoundly trivial. And I will conclude from that that mice really don't have the cognitive flexibility that we want to explain. And then a mouse researcher will say to me, well, you know, hold on, that experiment may not have worked because you asked a mouse to deal with stimuli and behaviors that were very unnatural for the mouse. If instead you kept the logic of the experiment the same, but put, you know, kind of put it in a, you know, presented the information in a way that aligns with what mice are used to dealing with in their natural habitats, you might find that a mouse actually has more intelligence than you think. And then they'll go on to show you videos of mice doing things in their natural habitat, which seem strikingly intelligent, you know, dealing with, you know, physical problems, you know, I have to drag this piece of food back to my, you know, back to my lair, but there's something in my way and how do I get rid of that thing? So I think these are open questions to put it, you know, to sum that up. And then taking a small step back related to that is you kind of mentioned we're taking a little shortcut by saying it's a geographic part of the prefrontal cortex is a region of the brain. But if we, what's your sense in a bigger philosophical view, prefrontal cortex and the brain in general? Do you have a sense that it's a set of subsystems in the way we've kind of implied that are pretty distinct? Or to what degree is it that? Or to what degree is it a giant interconnected mess where everything kind of does everything and it's impossible to disentangle them? I think there's overwhelming evidence that there's functional differentiation, that it's clearly not the case, that all parts of the brain are doing the same thing. This follows immediately from the kinds of studies of brain damage that we were chatting about before. It's obvious from what you see if you stick an electrode in the brain and measure what's going on at the level of neural activity. Having said that, there are two other things to add, which kind of, I don't know, maybe tug in the other direction. One is that it's when you look carefully at functional differentiation in the brain, what you usually end up concluding, at least this is my observation of the literature, is that the differences between regions are graded rather than being discrete. So it doesn't seem like it's easy to divide the brain up into true modules that have clear boundaries and that have, you know, like, you know, clear channels of communication between them. Instead- And this applies to the prefrontal cortex? Yeah, oh yeah, yeah. The prefrontal cortex is made up of a bunch of different sub-regions, the, you know, the functions of which are not clearly defined and which, you know, the borders of which seem to be quite vague. And then there's another thing that's popping up in very recent research, which, you know, which involves application of these new techniques, which there are a number of studies that suggest that parts of the brain that we would have previously thought were quite focused in their function are actually carrying signals that we wouldn't have thought would be there. For example, looking in the primary visual cortex, which is classically thought of as basically the first cortical way station for processing visual information. Basically what it should care about is, you know, where are the edges in this scene that I'm viewing? It turns out that if you have enough data, you can recover information from primary visual cortex about all sorts of things, like, you know, what behavior the animal is engaged in right now and how much reward is on offer in the task that it's pursuing. So it's clear that even regions whose function is pretty well-defined at a core screen are nonetheless carrying some information about information from very different domains. So, you know, the history of neuroscience is sort of this oscillation between the two views that you articulated, you know, the kind of modular view and then the big, you know, mush view. And, you know, I think, I guess we're gonna end up somewhere in the middle, which is unfortunate for our understanding because there's something about our, you know, conceptual system that finds it easy to think about a modularized system and easy to think about a completely undifferentiated system but something that kind of lies in between is confusing but we're gonna have to get used to it, I think. Unless we can understand deeply the lower level mechanism of neuronal communication and so on. So on that topic, you kind of mentioned information. Just to get a sense, I imagine something that there's still mystery and disagreement on is how does the brain carry information and signal? Like what, in your sense, is the basic mechanism of communication in the brain? Well, I guess I'm old-fashioned in that I consider the networks that we use in deep learning research to be a reasonable approximation to, you know, the mechanisms that carry information in the brain. So the usual way of articulating that is to say, what really matters is a rate code. What matters is how quickly is an individual neuron spiking? How, you know, what's the frequency at which it's spiking? Is it like- So the timing of the spike. Yeah, is it firing fast or slow? Let's, you know, let's put a number on that. And that number is enough to capture what neurons are doing. There's, you know, there's still uncertainty about whether that's an adequate description of how information is transmitted within the brain. There, you know, there are studies that suggest that the precise timing of spikes matters. There are studies that suggest that there are computations that go on within the dendritic tree, within a neuron, that are quite rich and structured, and that really don't equate to anything that we're doing in our artificial neural networks. Having said that, I feel like we can get, I feel like we're getting somewhere by sticking to this high level of abstraction. Just the rate, and by the way, we're talking about the electrical signal. I remember reading some vague paper somewhere recently where the mechanical signal, like the vibrations or something of the neurons also communicates information. I haven't seen that, but. There's somebody was arguing that the electrical signal, this is in the Nature paper or something like that, where the electrical signal is actually a side effect of the mechanical signal. But I don't think that changes the story. But it's almost an interesting idea that there could be a deeper, it's always like in physics with quantum mechanics, there's always a deeper story that could be underlying the whole thing. But you think it's basically the rate of spiking that gets us, that's like the lowest hanging fruit that can get us really far. This is a classical view. I mean, this is not, the only way in which this stance would be controversial is in the sense that there are members of the neuroscience community who are interested in alternatives. But this is really a very mainstream view. The way that neurons communicate is that neurotransmitters arrive, they wash up on a neuron, the neuron has receptors for those transmitters, the meeting of the transmitter with these receptors changes the voltage of the neuron. And if enough voltage change occurs, then a spike occurs, right? One of these like discrete events. And it's that spike that is conducted down the axon and leads to neurotransmitter release. This is just like neuroscience 101. This is like the way the brain is supposed to work. Now, what we do when we build artificial neural networks of the kind that are now popular in the AI community is that we don't worry about those individual spikes. We just worry about the frequency at which those spikes are being generated. And we consider, people talk about that as the activity of a neuron. And so the activity of units in a deep learning system is broadly analogous to the spike rate of a neuron. There are people who believe that there are other forms of communication in the brain. In fact, I've been involved in some research recently that suggests that the voltage fluctuations that occur in populations of neurons that are sort of below the level of spike production may be important for communication. But I'm still pretty old school in the sense that I think that the things that we're building in AI research constitute reasonable models of how a brain would work. Let me ask just for fun a crazy question, because I can. Do you think it's possible we're completely wrong about the way this basic mechanism of neuronal communication, that the information is stored in some very different kind of way in the brain? Oh, heck yes. I mean, look, I wouldn't be a scientist if I didn't think there was any chance we were wrong. But I mean, if you look at the history of deep learning research as it's been applied to neuroscience, of course, the vast majority of deep learning research these days isn't about neuroscience. But if you go back to the 1980s, there's sort of an unbroken chain of research in which a particular strategy is taken, which is, hey, let's train a deep learning system. Let's train a multilayer neural network on this task that we trained our rat on or our monkey on or this human being on. And then let's look at what the units deep in the system are doing. And let's ask whether what they're doing resembles what we know about what neurons deep in the brain are doing. And over and over and over and over, that strategy works in the sense that the learning algorithms that we have access to, which typically center on back propagation, they give rise to patterns of activity, patterns of response, patterns of neuronal behavior in these artificial models that look hauntingly similar to what you see in the brain. And is that a coincidence? At a certain point, it starts looking like such coincidence is unlikely to not be deeply meaningful. Yeah. Yeah, the circumstantial evidence is overwhelming. But it could be. But you're always open to a total flipping of the table. Yeah, of course. So you have co-authored several recent papers that sort of weave beautifully between the world of neuroscience and artificial intelligence. And maybe if we could, can we just try to dance around and talk about some of them, maybe try to pick out interesting ideas that jump to your mind from memory. So maybe looking at, we're talking about the prefrontal cortex, the 2018, I believe, paper called The Prefrontal Cortex as a Matter Reinforcement Learning System. What, is there a key idea that you can speak to from that paper? Yeah, I mean, the key idea is about meta-learning. So. What is meta-learning? Meta-learning is, by definition, a situation in which you have a learning algorithm, and the learning algorithm operates in such a way that it gives rise to another learning algorithm. In the earliest applications of this idea, you had one learning algorithm sort of adjusting the parameters on another learning algorithm. But the case that we're interested in this paper is one where you start with just one learning algorithm, and then another learning algorithm kind of emerges out of thin air. I can say more about what I mean by that. I don't mean to be, you know, obscurantist, but that's the idea of meta-learning. It relates to the old idea in psychology of learning to learn. Situations where you have experiences that make you better at learning something new. Like a familiar example would be learning a foreign language. The first time you learn a foreign language, it may be quite laborious and disorienting and novel, but if, let's say you've learned two foreign languages, the third foreign language obviously is gonna be much easier to pick up. And why? Because you've learned how to learn. You know how this goes. You know, okay, I'm gonna have to learn how to conjugate. I'm gonna have to. That's a simple form of meta-learning, right? In the sense that there's some slow learning mechanism that's helping you kind of update your fast learning mechanism. Does that bring it into focus? So how, from our understanding, from the psychology world, from neuroscience, our understanding how meta-learning works might work in the human brain, what lessons can we draw from that that we can bring into the artificial intelligence world? Well, yeah, so the origin of that paper was in AI work that we were doing in my group. We were looking at what happens when you train a recurrent neural network using standard reinforcement learning algorithms, but you train that network, not just in one task, but you train it in a bunch of interrelated tasks. And then you ask what happens when you give it yet another task in that sort of line of interrelated tasks. And what we started to realize is that a form of meta-learning spontaneously happens in recurrent neural networks. And the simplest way to explain it is to say a recurrent neural network has a kind of memory in its activation patterns. It's recurrent by definition in the sense that you have units that connect to other units that connect to other units. So you have sort of loops of connectivity, which allows activity to stick around and be updated over time. In psychology, we call, in neuroscience, we call this working memory. It's like actively holding something in mind. And so that memory gives the recurrent neural network a dynamics, right? The way that the activity pattern evolves over time is inherent to the connectivity of the recurrent neural network, okay? So that's idea number one. Now, the dynamics of that network are shaped by the connectivity, by the synaptic weights. And those synaptic weights are being shaped by this reinforcement learning algorithm that you're training the network with. So the punchline is, if you train a recurrent neural network with a reinforcement learning algorithm that's adjusting its weights, and you do that for long enough, the activation dynamics will become very interesting, right? So imagine I give you a task where you have to press one button or another, left button or right button. And there's some probability that I'm gonna give you an M&M if you press the left button, and there's some probability I'll give you an M&M if you press the other button. And you have to figure out what those probabilities are just by trying things out. But as I said before, instead of just giving you one of these tasks, I give you a whole sequence. I give you two buttons and you figure out which one's best, and I go, good job, here's a new box. Two new buttons, you have to figure out which one's best. Good job, here's a new box. And every box has its own probabilities, and you have to figure it. So if you train a recurrent neural network on that kind of sequence of tasks, what happens, it seemed almost magical to us when we first started kind of realizing what was going on. The slow learning algorithm that's adjusting the synaptic weights, those slow synaptic changes give rise to a network dynamics that themselves, that the dynamics themselves turn into a learning algorithm. So in other words, you can tell this is happening by just freezing the synaptic weights, saying, okay, no more learning, you're done. Here's a new box, figure out which button is best. And the recurrent neural network will do this just fine. There's no, like it figures out which button is best. It kind of transitions from exploring the two buttons to just pressing the one that it likes best in a very rational way. How is that happening? It's happening because the activity dynamics of the network have been shaped by this slow learning process that's occurred over many, many boxes. And so what's happened is that this slow learning algorithm that's slowly adjusting the weights is changing the dynamics of the network, the activity dynamics into its own learning algorithm. And as we were kind of realizing that this is a thing, it just so happened that the group that was working on this included a bunch of neuroscientists and it started kind of ringing a bell for us, which is to say that we thought this sounds a lot like the distinction between synaptic learning and activity, synaptic memory and activity-based memory in the brain. And it also reminded us of recurrent connectivity that's very characteristic of prefrontal function. So this is kind of why it's good to have people working on AI that know a little bit about neuroscience and vice versa, because we started thinking about whether we could apply this principle to neuroscience. And that's where the paper came from. So the kind of principle of the recurrence they can see in the prefrontal cortex, then you start to realize that it's possible to force something like an idea of a learning to learn emerging from this learning process as long as you keep varying the environment sufficiently. Exactly, so the kind of metaphorical transition we made to neuroscience was to think, okay, well, we know that the prefrontal cortex is highly recurrent. We know that it's an important locus for working memory, for activation-based memory. So maybe the prefrontal cortex supports reinforcement learning. In other words, what is reinforcement learning? You take an action, you see how much reward you got, you update your policy of behavior. Maybe the prefrontal cortex is doing that sort of thing strictly in its activation patterns. It's keeping around a memory in its activity patterns of what you did, how much reward you got, and it's using that activity-based memory as a basis for updating behavior. But then the question is, well, how did the prefrontal cortex get so smart? In other words, where did these activity dynamics come from? How did that program that's implemented in the recurrent dynamics of the prefrontal cortex arise? And one answer that became evident in this work was, well, maybe the mechanisms that operate on the synaptic level, which we believe are mediated by dopamine, are responsible for shaping those dynamics. So this may be a silly question, but because this kind of several temporal classes of learning are happening, and the learning-to-learnism emerges, can you keep building stacks of learning-to-learn-to-learn, learning-to-learn-to-learn-to-learn-to-learn, because it keeps, I mean, basically abstractions of more powerful abilities to generalize of learning complex rules. Yeah. Or is this overstretching this kind of mechanism? Well, one of the people in AI who started thinking about meta-learning from very early on, Juergen and Schmidhuber, sort of cheekily suggested, I think it may have been in his PhD thesis, that we should think about meta, meta, meta, meta, meta, meta learning. You know, that's really what's gonna get us to true intelligence. Certainly there's a poetic aspect to it, and it seems interesting and correct that that kind of level of abstraction would be powerful, but is that something you see in the brain? This kind of, is it useful to think of learning in these meta, meta, meta way, or is it just meta learning? Well, one thing that really fascinated me about this mechanism that we were starting to look at, and you know, other groups started talking about very similar things at the same time, and then a kind of explosion of interest in meta-learning happened in the AI community shortly after that. I don't know if we had anything to do with that, but I was gratified to see that a lot of people started talking about meta-learning. One of the things that I like about the kind of flavor of meta-learning that we were studying was that it didn't require anything special. It was just, if you took a system that had some form of memory, that the function of which could be shaped by pick your RL algorithm, then this would just happen, right? I mean, there are a lot of forms of, there are a lot of meta-learning algorithms that have been proposed since then that are fascinating and effective in their domains of application, but they're engineered. There are things that somebody had to say, well, gee, if we wanted meta-learning to happen, how would we do that? Here's an algorithm that would, but there's something about the kind of meta-learning that we were studying that seemed to me special in the sense that it wasn't an algorithm. It was just something that automatically happened if you had a system that had memory, and it was trained with a reinforcement learning algorithm. And in that sense, it can be as meta as it wants to be, right? There's no limit on how abstract the meta-learning can get, because it's not reliant on a human engineering a particular meta-learning algorithm to get there. And that's, I also, I don't know, I guess I hope that that's relevant in the brain. I think there's a kind of beauty in the ability of this emergent- The emergent aspect of it. Yeah, it's something that- As opposed to engineered. Exactly, it's something that just, it just happens in a sense. In a sense, you can't avoid this happening. If you have a system that has memory, and the function of that memory is shaped by reinforcement learning, and this system is trained in a series of interrelated tasks, this is gonna happen. You can't stop it. As long as you have certain properties, maybe like a recurrent structure to- You have to have memory. It actually doesn't have to be a recurrent neural network. A paper that I was honored to be involved with even earlier used a kind of slot-based memory. Do you remember the title? Just for people who watched it. It was Memory Augmented Neural Networks. I think the title was Meta-Learning in Memory Augmented Neural Networks. And it was the same exact story. If you have a system with memory, here it was a different kind of memory, but the function of that memory is shaped by reinforcement learning. Here it was the reads and writes that occurred on this slot-based memory. This'll just happen. But this brings us back to something I was saying earlier about the importance of the environment. This will happen if the system is being trained in a setting where there's a sequence of tasks that all share some abstract structure. Sometimes we talk about task distributions. And that's something that's very obviously true of the world that humans inhabit. If you just kind of think about what you do every day, you never do exactly the same thing that you did the day before. But everything that you do has a family resemblance. It shares structure with something that you did before. And so the real world is sort of saturated with this kind of, this property. It's endless variety with endless redundancy. And that's the setting in which this kind of meta-learning happens. And it does seem like we're just so good at finding, just like in this emergent phenomenon you described, that we're really good at finding that redundancy, finding those similarities, the family resemblance. Some people call it sort of, what is it? Melanie Mitchell was talking about analogies. So we're able to connect concepts together in this kind of way, in this same kind of automated emergent way. Which, there's so many echoes here of psychology and neuroscience. And obviously now with reinforcement learning with recurring neural networks at the core. If we could talk a little bit about dopamine. You have really, you're a part of co-authoring really exciting recent paper, very recent, in terms of release on dopamine and temporal difference learning. Can you describe the key ideas of that paper? Sure, yeah. I mean, one thing I want to pause to do is acknowledge my co-authors on actually both of the papers we're talking about. So this dopamine paper. Just to, I'll certainly post all their names. Okay, wonderful, yeah. And all that kind of stuff. Because I'm sort of a bash to be the spokesperson for these papers when I had such amazing collaborators on both. So it's a comfort to me to know that you'll acknowledge them. Yeah, there's an incredible team there, but yeah. Oh yeah, it's so much fun. And in the case of the dopamine paper, we also collaborated with Naoichi at Harvard, who obviously a paper simply wouldn't have happened without him. But so you were asking for like a thumbnail sketch of. Yeah, thumbnail sketch or key ideas or things, the insights that continue on our kind of discussion here between neuroscience and AI. Yeah, I mean, this was another, a lot of the work that we've done so far is taking ideas that have bubbled up in AI and asking the question of whether the brain might be doing something related, which I think on the surface sounds like something that's really mainly of use to neuroscience. We see it also as a way of validating what we're doing on the AI side. If we can gain some evidence that the brain is using some technique that we've been trying out in our AI work, that gives us confidence that it may be a good idea, that it'll scale to rich, complex tasks, that it'll interface well with other mechanisms. So you see it as a two-way road. Yeah, for sure. Just because a particular paper is a little bit focused on from one to the, from AI, from neural networks to neuroscience, ultimately the discussion, the thinking, the productive long-term aspect of it is the two-way road nature of the whole. Yeah, I mean, we've talked about the notion of a virtuous circle between AI and neuroscience. And the way I see it, that's always been there since the two fields jointly existed. There have been some phases in that history when AI was sort of ahead. There are some phases when neuroscience was sort of ahead. I feel like given the burst of innovation that's happened recently on the AI side, AI is kind of ahead in the sense that there are all of these ideas that we, for which it's exciting to consider that there might be neural analogs. And neuroscience, in a sense, has been focusing on approaches to studying behavior that come from, that are kind of derived from this earlier era of cognitive psychology. And so in some ways, we fail to connect with some of the issues that we're grappling with in AI, like how do we deal with large, complex environments? But I think it's inevitable that this circle will keep turning and there will be a moment in the not too distant future when neuroscience is pelting AI researchers with insights that may change the direction of our work. Just a quick human question is that you have parts of your brain, this is very meta, but they're able to both think about neuroscience and AI. You know, I don't often meet people like that. So do you think, let me ask a metaplasticity question. Do you think a human being can be both good at AI and neuroscience? Is like what, on the team at DeepMind, what kind of human can occupy these two realms? And is that something you see everybody should be doing, can be doing, or is that a very special few can kind of jump? Just like we talk about art history, I would think it's a special person that can major in art history and also consider being a surgeon. Otherwise known as a dilettante. A dilettante, yeah. Easily distracted. No, I think it does take a special kind of person to be truly world-class at both AI and neuroscience, and I am not on that list. I happen to be someone who's interest in neuroscience and psychology involved using the kinds of modeling techniques that are now very central in AI and that sort of, I guess, bought me a ticket to be involved in all of the amazing things that are going on in AI research right now. I do know a few people who I would consider pretty expert on both fronts, and I won't embarrass them by naming them, but there are like exceptional people out there who are like this. The one thing that I find is a barrier to being truly world-class on both fronts is just the complexity of the technology that's involved in both disciplines now. So the engineering expertise that it takes to do truly frontline, hands-on AI research is really, really considerable. The learning curve of the tools, just like the specifics of just whether it's programming or the kind of tools necessary to collect the data, to manage the data, to distribute, to compute, all that kind of stuff. And on the neuroscience, I guess, side, there'll be all different sets of tools. Exactly, especially with the recent explosion in neuroscience methods. So having said all that, I think the best scenario for both neuroscience and AI is to have people who, interacting, who live at every point on this spectrum from exclusively focused on neuroscience to exclusively focused on the engineering side of AI, but to have those people inhabiting a community where they're talking to people who live elsewhere on the spectrum. And I may be someone who's very close to the center in the sense that I have one foot in the neuroscience world and one foot in the AI world. And that central position, I will admit, prevents me, at least someone with my limited cognitive capacity, from having true technical expertise in either domain. But at the same time, I at least hope that it's worthwhile having people around who can kind of see the connections. Yeah, the community, the emergent intelligence of the community when it's nicely distributed is useful. Okay, so. Exactly, yeah. So hopefully, I mean, I've seen that work out well at DeepMind. There are people who, I mean, even if you just focus on the AI work that happens at DeepMind, it's been a good thing to have some people around doing that kind of work whose PhDs are in neuroscience or psychology. Every academic discipline has its kind of blind spots and kind of unfortunate obsessions and its metaphors and its reference points. And having some intellectual diversity is really healthy. People get each other unstuck, I think. I see it all the time at DeepMind. And I like to think that the people who bring some neuroscience background to the table are helping with that. So one of my, probably the deepest passion for me, what I would say, maybe we kind of spoke off mic a little bit about it, but that I think is a blind spot for at least robotics and AI folks is human-robot interaction, human-agent interaction. Maybe, do you have thoughts about how we reduce the size of that blind spot? Do you also share the feeling that not enough folks are studying this aspect of interaction? Well, I'm actually pretty intensively interested in this issue now, and there are people in my group who've actually pivoted pretty hard over the last few years from doing more traditional cognitive psychology and cognitive neuroscience to doing experimental work on human-agent interaction. And there are a couple of reasons that I'm pretty passionately interested in this. One is, it's kind of the outcome of having thought for a few years now about what we're up to. Like, what are we doing? Like, what is this AI research for? So what does it mean to make the world a better place? I think, I'm pretty sure that means making life better for humans. And so, how do you make life better for humans? That's a proposition that, when you look at it carefully and honestly, is rather horrendously complicated, especially when the AI systems that you're building are learning systems. They're not, you're not programming something that you then introduce to the world and it just works as programmed, like Google Maps or something. We're building systems that learn from experience. So that typically leads to AI safety questions. How do we keep these things from getting out of control? How do we keep them from doing things that harm humans? And I mean, I hasten to say, I consider those hugely important issues, and there are large sectors of the research community at DeepMind and of course elsewhere, who are dedicated to thinking hard all day, every day about that. But there's, I guess I would say, a positive side to this too, which is to say, well, what would it mean to make human life better? And how can we imagine learning systems doing that? And in talking to my colleagues about that, we reached the initial conclusion that it's not sufficient to philosophize about that. You actually have to take into account how humans actually work and what humans want, and the difficulties of knowing what humans want, and the difficulties that arise when humans want different things. And so human-agent interaction has become a quite intensive focus of my group lately. If for no other reason that, in order to really address that issue in an adequate way, you have to, I mean, psychology becomes part of the picture. Yeah, and so there's a few elements there. So if you focus on solving, if you focus on the robotics problem, let's say AGI, without humans in the picture, is you're missing fundamentally the final step. When you do want to help human civilization, you eventually have to interact with humans. And when you create a learning system, just as you said, that will eventually have to interact with humans, the interaction itself has to become part of the learning process. So you can't just watch, well, my sense is, it sounds like your sense is, you can't just watch humans to learn about humans. You have to also be part of the human world. You have to interact with humans. Yeah, exactly. And I mean, then questions arise that start imperceptibly, but inevitably to slip beyond the realm of engineering. So questions like, if you have an agent that can do something that you can't do, under what conditions do you want that agent to do it? So if I have a robot that can play Beethoven sonatas better than any human, in the sense that the sensitivity, the expression is just beyond what any human, do I wanna listen to that? Do I wanna go to a concert and hear a robot play? These aren't engineering questions. These are questions about human preference and human culture. Psychology bordering on philosophy. Yeah, and then you start asking, well, even if we knew the answer to that, is it our place as AI engineers to build that into these agents? Probably the agents should interact with humans beyond the population of AI engineers and figure out what those humans want. And then when you start, I referred this a moment ago, but even that becomes complicated. Be quote, what if two humans want different things and you have only one agent that's able to interact with them and try to satisfy their preferences? Then you're into the realm of like economics and social choice theory and even politics. So there's a sense in which, if you kind of follow what we're doing to its logical conclusion, then it goes beyond questions of engineering and technology and starts to shade imperceptibly into questions about what kind of society do you want? And actually, once that dawned on me, I actually felt, I don't know what the right word is, quite refreshed in my involvement in AI research. It was almost like building this kind of stuff is gonna lead us back to asking really fundamental questions about what's the good life? And who gets to decide? And bringing in viewpoints from multiple sub-communities to help us shape the way that we live. It started making me feel like doing AI research in a fully responsible way could potentially lead to a kind of cultural renewal. Yeah, it's the way to understand human beings at the individual, at the societal level. It may become a way to answer all the silly human questions of the meaning of life and all those kinds of things. Even if it doesn't give us a way of answering those questions, it may force us back to thinking about them. Thinking about them. And it might restore a certain, I don't know, a certain depth to, or even dare I say, spirituality to the world. I don't know, maybe that's too grandiose. Well, I'm with you. I think AI will be the philosophy of the 21st century. The way which will open the door. I think a lot of AI researchers are afraid to open that door of exploring the beautiful richness of the human-agent interaction, human-AI interaction. I'm really happy that somebody like you have opened that door. One thing I often think about is, the usual schema for thinking about human-agent interaction is this kind of dystopian, oh, our robot overlords. And again, I hasten to say AI safety is hugely important. And I'm not saying we shouldn't be thinking about those risks. Totally on board for that. But there's, having said that, what often follows for me is the thought that, there's another kind of narrative that might be relevant, which is, when we think of humans gaining more and more information about human life, the narrative there is usually that they gain more and more wisdom. And they get closer to enlightenment. And they become more benevolent. The Buddha is, that's a totally different narrative. And why isn't it the case that we imagine that the AI systems that we're creating are just gonna, they're gonna figure out more and more about the way the world works and the way that humans interact, and they'll become beneficent. I'm not saying that will happen. I'm not, I don't honestly expect that to happen without some careful, setting things up very carefully. But it's another way things could go, right? Yeah, and I would even push back on that. I personally believe that the most trajectories, natural human trajectories will lead us towards progress. So for me, there is a kind of sense that most trajectories in AI development will lead us into trouble. To me, and we over-focus on the worst case. It's like in computer science, theoretical computer science, there's been this focus on worst case analysis. There's something appealing to our human mind at some lowest level to be, I mean, we don't wanna be eaten by the virus. I mean, we don't wanna be eaten by the tiger, I guess. So we wanna do the worst case analysis, but the reality is that shouldn't stop us from actually building out all the other trajectories which are potentially leading to all the positive worlds, all the enlightenment. There's a book, Enlightenment Now, with Steven Pinker and so on. This is looking generally at human progress. And there's so many ways that human progress can happen with AI. And I think you have to do that research. You have to do that work. You have to do the, not just the AI safety work of the one worst case analysis, how do we prevent that, but the actual tools and the glue and the mechanisms of human AI interaction that would lead to all the positive directions. It's a super exciting area, right? Yeah, we should be spending a lot of our time saying what can go wrong. I think it's harder to see that there's work to be done to bring into focus the question of what it would look like for things to go right. That's not obvious. And we wouldn't be doing this if we didn't have the sense there was huge potential, right? We're not doing this for no reason. We have a sense that AGI would be a major boom to humanity. But I think it's worth starting now, even when our technology is quite primitive, asking, well, exactly what would that mean? We can start now with applications that are already gonna make the world a better place, like solving protein folding. I think this deep mind has gotten heavy into science applications lately, which I think is a wonderful, wonderful move for us to be making. But when we think about AGI, when we think about building fully intelligent agents that are gonna be able to, in a sense, do whatever they want, we should start thinking about what do we want them to want? What kind of world do we wanna live in? That's not an easy question. And I think we just need to start working on it. And even on the path to sort of, it doesn't have to be AGI, but just intelligent agents that interact with us and help us enrich our own existence on social networks, for example, on recommender systems of various intelligence. There's so much interesting interaction that's yet to be understood and studied. And how do you create, I mean, Twitter is struggling with this very idea. How do you create AI systems that increase the quality and the health of a conversation? That's a beautiful human psychology question. And how do you do that without deception being involved, deception being involved, without manipulation being involved, maximizing human autonomy? And how do you make these choices in a democratic way? How do we face the, again, I'm speaking for myself here. How do we face the fact that it's a small group of people who have the skillset to build these kinds of systems, but the, what it means to make the world a better place is something that we all have to be talking about. Yeah, the world that we're trying to make a better place includes a huge variety of different kinds of people. Yeah, how do we cope with that? This is a problem that has been discussed in gory extensive detail in social choice theory. One thing I'm really enjoying about the recent direction work has taken in some parts of my team is that, yeah, we're reading the AI literature, we're reading the neuroscience literature, but we've also started reading like economics and as I mentioned, social choice theory, even some political theory, because it turns out that it all becomes relevant. It all becomes relevant. And, but at the same time, we've been trying not to write philosophy papers, right? We've been trying not to write physician papers. We're trying to figure out ways of doing actual empirical research that kind of take the first small steps to thinking about what it really means for humans with all of their complexity and contradiction and paradox to be brought into contact with these AI systems in a way that really makes the world a better place. And often reinforcement learning frameworks actually kind of allow you to do that machine learning. And so that's the exciting thing about AI is it allows you to reduce the unsolvable problem, philosophical problem, to something more concrete that you can get a hold of. Yeah, and it allows you to kind of define the problem in some way that allows for growth in the system that's sort of, you're not responsible for the details. Right? You say, this is generally what I want you to do. And then learning takes care of the rest. Of course, the safety issues are, you know, arise in that context. But I think also some of these positive issues arise in that context. What would it mean for an AI system to really come to understand what humans want? And, you know, with all of the subtleties of that, right? You know, humans want help with certain things, but they don't want everything done for them, right? There is part of the satisfaction that humans get from life is in accomplishing things. So if there were devices around that did everything for, you know, I often think of the movie WALL-E, right? That's like dystopian in a totally different way. It's like, the machines are doing everything for us. That's not what we want. That's not what we wanted. You know, anyway, I just, I find this, you know, this opens up a whole landscape of research that feels affirmative and exciting. To me, it's one of the most exciting and it's wide open. We have to, because it's a cool paper, talk about dopamine. Oh yeah, okay, so I can. We were gonna, I was gonna give you a quick summary. Yeah, a quick summary of what's the title of the paper? I think we called it a distributional code for value in dopamine-based reinforcement learning. Yes. So that's another project that grew out of pure AI research. A number of people at DeepMind and a few other places had started working on a new version of reinforcement learning, which was defined by taking something in traditional reinforcement learning and just tweaking it. So the thing that they took from traditional reinforcement learning was a value signal. So at the center of reinforcement learning, at least most algorithms, is some representation of how well things are going, your expected cumulative future reward. And that's usually represented as a single number. So if you imagine a gambler in a casino and the gambler's thinking, well, I have this probability of winning such and such an amount of money, and I have this probability of losing such and such an amount of money, that situation would be represented as a single number, which is like the expected, the weighted average of all those outcomes. And this new form of reinforcement learning said, well, what if we generalize that to a distributional representation? So now we think of the gambler as literally thinking, well, there's this probability that I'll win this amount of money, and there's this probability that I'll lose that amount of money, and we don't reduce that to a single number. And it had been observed through experiments, through just trying this out, that that kind of distributional representation really accelerated reinforcement learning and led to better policies. What's your intuition about, so we're talking about rewards. Yeah. So what's your intuition why that is? Why does it depend? Well, it's kind of a surprising historical note, at least surprised me when I learned it, that this had been tried out in a kind of heuristic way. People thought, well, gee, what would happen if we tried? And then it had this, empirically, it had this striking effect. And it was only then that people started thinking, well, gee, wait, why? Why? Wait, why? Why is this working? And that's led to a series of studies just trying to figure out why it works, which is ongoing. But one thing that's already clear from that research is that one reason that it helps is that it drives richer representation learning. So if you imagine two situations that have the same expected value, the same kind of weighted average value, standard deep reinforcement learning algorithms are going to take those two situations and kind of, in terms of the way they're represented internally, they're gonna squeeze them together. Because the thing that you're trying to represent, which is their expected value, is the same. So all the way through the system, things are gonna be mushed together. But what if those two situations actually have different value distributions? They have the same average value, but they have different distributions of value. In that situation, distributional learning will maintain the distinction between these two things. So to make a long story short, distributional learning can keep things separate in the internal representation that might otherwise be conflated or squished together. And maintaining those distinctions can be useful when the system is now faced with some other task where the distinction is important. If we look at the optimistic and pessimistic dopamine neurons, so first of all, what is dopamine? And why is this at all useful to think about in the artificial intelligence sense? But what do we know about dopamine in the human brain? What is it? Why is it useful? Why is it interesting? What does it have to do with the prefrontal cortex and learning in general? Yeah, so, well, this is also a case where there's a huge amount of detail and debate, but one currently prevailing idea is that the function of this neurotransmitter dopamine resembles a particular component of standard reinforcement learning algorithms, which is called the reward prediction error. So I was talking a moment ago about these value representations. How do you learn them? How do you update them based on experience? Well, if you made some prediction about future reward, and then you get more reward than you were expecting, then probably retrospectively, you wanna go back and increase the value representation that you attached to that earlier situation. If you got less reward than you were expecting, you should probably decrement that estimate. And that's the process of temporal difference learning. Exactly, this is the central mechanism of temporal difference learning, which is one of several kind of, you know, kind of back, sort of the backbone of our armamentarium in RL. And it was this connection between the reward prediction error and dopamine was made, you know, in the 1990s. And there's been a huge amount of research that, you know, seems to back it up. Dopamine may be doing other things, but this is clearly, at least roughly, one of the things that it's doing. But the usual idea was that dopamine was representing these reward prediction errors, again, in this like kind of single number way, that representing your surprise, you know, with a single number. And in distributional reinforcement learning, this kind of new elaboration of the standard approach, it's not only the value function that's represented as a single number, it's also the reward prediction error. And so what happened was that Will Dabney, one of my collaborators, who was one of the first people to work on distributional temporal difference learning, talked to a guy in my group, Zeb Kurth-Nelson, who's a computational neuroscientist, and said, gee, you know, is it possible that dopamine might be doing something like this distributional coding thing? And they started looking at what was in the literature, and then they brought me in, we started talking to Nao Uchida, and we came up with some specific predictions about, you know, if the brain is using this kind of distributional coding, then in the tasks that Nao has studied, you should see this, this, this, and this, and that's where the paper came from. We kind of enumerated a set of predictions, all of which ended up being fairly clearly confirmed, and all of which leads to at least some initial indication that the brain might be doing something like this distributional coding, that dopamine might be representing surprise signals in a way that is not just collapsing everything to a single number, but instead, it's kind of respecting the variety of future outcomes, if that makes sense. So yeah, so that's showing, suggesting possibly that dopamine has a really interesting representation scheme in the human brain for its reward signal. Exactly. That's fascinating. That's another beautiful example of AI revealing something nice about neuroscience. Potentially, suggesting possibilities. Well, you never know. So the minute you publish a paper like that, the next thing you think is, I hope that replicates. Like, I hope we see that same thing in other data sets, but of course, several labs now are doing the follow-up experiment, so we'll know soon. But it has been a lot of fun for us to take these ideas from AI and kind of bring them into neuroscience and see how far we can get. So we kind of talked about it a little bit, but where do you see the field of neuroscience and artificial intelligence heading broadly? Like, what are the possible exciting areas that you can see breakthroughs in the next, let's get crazy, not just three or five years, but next 10, 20, 30 years that would make you excited and perhaps you'd be part of? On the neuroscience side, there's a great deal of interest now in what's going on in AI. And at the same time, I feel like, so neuroscience, especially the part of neuroscience that's focused on circuits and systems, kind of like really mechanism-focused, there's been this explosion in new technology. And up until recently, the experiments that have exploited this technology have not involved a lot of interesting behavior. And this is for a variety of reasons, one of which is in order to employ some of these technologies, you actually have to, if you're studying a mouse, you have to head fix the mouse. In other words, you have to immobilize the mouse. And so it's been tricky to come up with ways of eliciting interesting behavior from a mouse that's restrained in this way. But people have begun to create very interesting solutions to this, like virtual reality environments where the animal can kind of move a trackball. And as people have kind of begun to explore what you can do with these technologies, I feel like more and more people are asking, well, let's try to bring behavior into the picture. Let's try to reintroduce behavior, which was supposed to be what this whole thing was about. And I'm hoping that those two trends, the kind of growing interest in behavior and the widespread interest in what's going on in AI will come together to kind of open a new chapter in neuroscience research where there's a kind of a rebirth of interest in the structure of behavior and its underlying substrates, but that that research is being informed by computational mechanisms that we're coming to understand in AI. If we can do that, then we might be taking a step closer to this utopian future that we were talking about earlier where there's really no distinction between psychology and neuroscience. Neuroscience is about studying the mechanisms that underlie whatever it is the brain is for, and what is the brain for? It's for behavior. I feel like we could maybe take a step toward that now if people are motivated in the right way. You also asked about AI. So that was a neuroscience question. You said neuroscience, that's right. And especially a place like DeepMind, they're interested in both branches. So what about the engineering of intelligence systems? I think one of the key challenges that a lot of people are seeing now in AI is to build systems that have the kind of flexibility and the kind of flexibility that humans have in two senses. One is that humans can be good at many things. They're not just expert at one thing. And they're also flexible in the sense that they can switch between things very easily and they can pick up new things very quickly because they very ably see what a new task has in common with other things that they've done. And that's something that our AI systems blatantly do not have. There are some people who like to argue that deep learning and deep RL are simply wrong for getting that kind of flexibility. I don't share that belief, but the simpler fact of the matter is we're not building things yet that do have that kind of flexibility. And I think the attention of a large part of the AI community is starting to pivot to that question. How do we get that? That's gonna lead to a focus on abstraction. It's gonna lead to a focus on what in psychology we call cognitive control, which is the ability to switch between tasks, the ability to quickly put together a program of behavior that you've never executed before, but you know makes sense for a particular set of demands. It's very closely related to what the prefrontal cortex does on the neuroscience side. So I think it's gonna be an interesting new chapter. So that's the reasoning side and cognition side, but let me ask the over romanticized question. Do you think we'll ever engineer an AGI system that we humans would be able to love and then would love us back? So have that level and depth of connection. I love that question. And it relates closely to things that I've been thinking about a lot lately, in the context of this human AI research. There's social psychology research in particular by Susan Fisk at Princeton, in the department where I used to work, where she dissects human attitudes toward other humans into a sort of two-dimensional scheme. And one dimension is about ability. How able, how capable is this other person? But the other dimension is warmth. So you can imagine another person who's very skilled and capable, but is very cold. And you wouldn't really like highly, you might have some reservations about that other person. But there's also a kind of reservation that we might have about another person who elicits in us or displays a lot of human warmth, but is not good at getting things done. We reserve our greatest esteem, really, for people who are both highly capable and also quite warm. That's like the best of the best. This isn't a normative statement I'm making. This is just an empirical statement. This is what humans seem. These are the two dimensions that people seem to kind of like, along which people size other people up. And in AI research, we really focus on this capability thing. We want our agents to be able to do stuff. This thing can play Go at a superhuman level. That's awesome. But that's only one dimension. What about the other dimension? What would it mean for an AI system to be warm? And I don't know, maybe there are easy solutions here, like we can put a face on our AI systems. It's cute, it has big ears. I mean, that's probably part of it. But I think it also has to do with a pattern of behavior, a pattern of, what would it mean for an AI system to display caring, compassionate behavior in a way that actually made us feel like it was for real? That we didn't feel like it was simulated. We didn't feel like we were being duped. To me, people talk about the Turing test or some descendant of it. I feel like that's the ultimate Turing test. Is there an AI system that can not only convince us that it knows how to reason and it knows how to interpret language, but that we're comfortable saying, yeah, that AI system's a good guy. On the warmth scale, whatever warmth is, we kind of intuitively understand it, but we also wanna be able to, yeah, we don't understand it explicitly enough yet to be able to engineer it. And that's an open scientific question. You kind of alluded to it several times in the human-AI interaction. That's a question that should be studied and probably one of the most important questions as we move to AGI. We humans are so good at it. You know, it's not just that we're born warm. Like, I suppose some people are warmer than others, given whatever genes they manage to inherit. But there are also learned skills involved, right? I mean, there are ways of communicating to other people that you care, that they matter to you, that you're enjoying interacting with them, right? And we learn these skills from one another, and it's not out of the question that we could build engineered systems. I think it's hopeless, as you say, that we could somehow hand design these sorts of behaviors. But it's not out of the question that we could build systems that kind of, we instill in them something that sets them out in the right direction, so that they end up learning what it is to interact with humans in a way that's gratifying to humans. I mean, honestly, if that's not where we're headed, I want out. I want out. I think it's exciting as a scientific problem, just as you described. I honestly don't see a better way to end it than talking about warmth and love. And Matt, I don't think I've ever had such a wonderful conversation, where my questions were so bad and your answers were so beautiful. So I deeply appreciate it, I really enjoyed it. Thanks for talking about it. Well, it's been very fun. As you can probably tell, there's something I like about kind of thinking outside the box. So it's good having the opportunity to do that. Awesome, thanks so much for doing it. Thanks for listening to this conversation with Matt Boppeneck, and thank you to our sponsors, the Jordan and Harbinger Show, and Magic Spoon low-carb keto cereal. Please consider supporting this podcast by going to jordanandharbinger.com slash Lex, and also going to magicspoon.com slash Lex, and using code LEX at checkout. Click the links, buy all the stuff. It's the best way to support this podcast and the journey I'm on in my research and the startup. If you enjoy this thing, subscribe on YouTube, review it with the five stars on Apple Podcasts, support it on Patreon, follow on Spotify, or connect with me on Twitter at Lex Friedman. Again, spelled miraculously without the E, just F-R-I-D-M-A-N. And now, let me leave you with some words from urologist V.S. Ramachandran. How can a three-pound mass of jelly that you can hold in your palm, imagine angels, contemplate the meaning of infinity, and even question its own place in the cosmos? Especially awe-inspiring is the fact that any single brain, including yours, is made up of atoms that were forged in the hearts of countless, far-flung stars billions of years ago. These particles drifted for eons and light years until gravity and change brought them together here now. These atoms now form a conglomerate, your brain, that can not only ponder the very stars that gave it birth, but can also think about its own ability to think and wonder about its own ability to wander. With the arrival of humans, it has been said, the universe has suddenly become conscious of itself. This truly is the greatest mystery of all. Thank you for listening, and hope to see you next time.

https://youtu.be/3t06ajvBtl0

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Sean Carroll: Quantum Mechanics and the Many-Worlds Interpretation | Lex Fridman Podcast #47

The following is a conversation with Sean Carroll, part two, the second time we've spoken on the podcast. You can get the link to the first time in the description. This time we focus on quantum mechanics and the many worlds interpretation that he details elegantly in his new book titled Something Deeply Hidden. I own and enjoy both the ebook and audiobook versions of it. Listening to Sean read about entanglement, complementarity, and the emergence of space-time reminds me of Bob Ross teaching the world how to paint on his old television show. If you don't know who Bob Ross is, you're truly missing out. Look him up. He'll make you fall in love with painting. Sean Carroll is the Bob Ross of theoretical physics. He's the author of several popular books, a host of a great podcast called Mindscape, and is a theoretical physicist at Caltech and the Santa Fe Institute, specializing in quantum mechanics, arrow of time, cosmology, and gravitation. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Sean Carroll. Isaac Newton developed what we now call classical mechanics that you describe very nicely in your new book, as you do with a lot of basic concepts in physics. So, with classical mechanics, I can throw a rock and can predict the trajectory of that rock's flight. But if we could put ourselves back into Newton's time, his theories work to predict things, but as I understand, he himself thought that they were, the interpretations of those predictions were absurd. Perhaps he just said it for religious reasons and so on, but in particular, sort of a world of interaction without contact, so action at a distance. It didn't make sense to him on a sort of a human interpretation level. Does it make sense to you that things can affect other things at a distance? It does, but you know, that, so that was one of Newton's worries. You're actually right in a slightly different way about the religious worries. He was smart enough, this is off the topic, but still fascinating. Newton almost invented chaos theory as soon as he invented classical mechanics. He realized that in the solar system, so he was able to explain how planets move around the sun, but typically you would describe the orbit of the Earth ignoring the effects of Jupiter and Saturn and so forth, just doing the Earth and the sun. He kind of knew, even though he couldn't do the math, that if you included the effects of Jupiter and Saturn, the other planets, the solar system would be unstable, like the orbits of the planets would get out of whack. So he thought that God would intervene occasionally to sort of move the planets back into orbit, which is the only way you could explain how they were there, presumably forever. But the worries about classical mechanics were a little bit different, the worry about gravity in particular. It wasn't a worry about classical mechanics, it was a worry about gravity. How in the world does the Earth know that there's something called the sun, 93 million miles away, that is exerting a gravitational force on it? And he said, he literally said, you know, I leave that for future generations to think about, because I don't know what the answer is. And in fact, people underemphasized this, but future generations figured it out. Pierre-Simone Laplace in circa 1800 showed that you could rewrite Newtonian gravity as a field theory. So instead of just talking about the force due to gravity, you can talk about the gravitational field or the gravitational potential field. And then there's no action at a distance. It's exactly the same theory empirically, it makes exactly the same predictions. But what's happening is instead of the sun just reaching out across the void, there is a gravitational field in between the sun and the Earth that obeys an equation, Laplace's equation, cleverly enough. And that tells us exactly what the field does. So even in Newtonian gravity, you don't need action at a distance. Now, what many people say is that Einstein solved this problem because he invented general relativity. And in general relativity, there's certainly a field in between the Earth and the sun. But also there's the speed of light as a limit in Laplace's theory, which was exactly Newton's theory, just in a different mathematical language. There could still be instantaneous action across the universe. Whereas in general relativity, if you shake something here, its gravitational impulse radiates out at the speed of light. And we call that a gravitational wave, and we can detect those. So, but I really, it rubs me the wrong way to think that we should presume the answer should look one way or the other. Like if it turned out that there was action at a distance in physics, and that was the best way to describe things, then I would do it that way. It's actually a very deep question because when we don't know what the right laws of physics are, when we're guessing at them, when we're hypothesizing at what they might be, we are often guided by our intuitions about what they should be. I mean, Einstein famously was very guided by his intuitions, and he did not like the idea of action at a distance. We don't know whether he was right or not. It depends on your interpretation of quantum mechanics, and it depends on even how you talk about quantum mechanics within any one interpretation. So if you see every force as a field, or any other interpretation of action at a distance, I mean, just stepping back to sort of caveman thinking, like, do you really, can you really sort of understand what it means for a force to be a field that's everywhere? So if you look at gravity, like, what do you think about? I think so. Is this something that you've been conditioned by society to think that, to map the fact that science is extremely well predictive of something to believing that you actually understand it, like you can intuitively, the degree that human beings can understand anything, that you actually understand it, are you just trusting the beauty and the power of the predictive power of science? That depends on what you mean by this idea of truly understanding something, right? I mean, can I truly understand Fermat's last theorem? You know, it's easy to state it, but do I really appreciate what it means for incredibly large numbers, right? I think yes, I think I do understand it. But like, if you want to just push people on, well, but your intuition doesn't go to the places where Andrew Wiles needed to go to prove Fermat's last theorem, then I can say fine, but I still think I understand the theorem. And likewise, I think that I do have a pretty good intuitive understanding of fields pervading space-time, whether it's the gravitational field or the electromagnetic field or whatever, the Higgs field. Of course, one's intuition gets worse and worse as you get trickier in the quantum field theory and all sorts of new phenomena that come up in quantum field theory. So our intuitions aren't perfect. But I think it's also okay to say that our intuitions get trained, right? Like, you know, I have different intuitions now than I had when I was a baby. That's okay. An intuition is not necessarily intrinsic to who we are. We can train it a little bit. So that's where I'm going to bring in Noam Chomsky for a second, who thinks that our cognitive abilities are sort of evolved through time. And so they're biologically constrained. And so there's a clear limit, as he puts it, to our cognitive abilities, and it's a very harsh limit. But you actually kind of said something interesting in Nature versus Nurture thing here, is we can train our intuitions to sort of build up the cognitive muscles to be able to understand some of these tricky concepts. So do you think there's limits to our understanding that's deeply rooted, hard-coded into our biology that we can't overcome? There could be limits to things like our ability to visualize, okay? But when someone like Ed Witten proves a theorem about, you know, 100-dimensional mathematical spaces, he's not visualizing it. He's doing the math. That doesn't stop him from understanding the result. I think, and I would love to understand this better, but my rough feeling, which is not very educated, is that, you know, there's some threshold that one crosses in abstraction when one becomes kind of like a Turing machine, right? One has the ability to contain in one's brain logical, formal, symbolic structures and manipulate them. And that's a leap that we can make as human beings that dogs and cats haven't made. And once you get there, I'm not sure that there are any limits to our ability to understand the scientific world at all. Maybe there are. There's certainly limits on our ability to calculate things, right? You know, people are not very good at taking cube roots of million-digit numbers in their head, but that's not an element of understanding. It's certainly not a limit in principle. So, of course, as a human, you would say that doesn't feel to be a limit to our understanding. But sort of, have you thought that the universe is actually a lot simpler than it appears to us, and we just will never be able to, like, it's outside of our, okay, so us, our cognitive abilities combined with our mathematical prowess and whatever kind of experimental simulation devices we can put together, is there limits to that? Is it possible there's limits to that? Well, of course it's possible that there are limits to that. Is there any good reason to think that we're anywhere close to the limits is a harder question. Look, imagine asking this question 500 years ago to the world's greatest thinkers, right? Like, are we approaching the limits of our ability to understand the natural world? And by definition, there are questions about the natural world that are most interesting to us that are the ones we don't quite yet understand, right? So, we're always faced with these puzzles we don't yet know. And I don't know what they would have said 500 years ago, but they didn't even know about classical mechanics, much less quantum mechanics. So, we know that they were nowhere close to how well they could do, right? They could do enormously better than they were doing at the time. I see no reason why the same thing isn't true for us today. So, of all the worries that keep me awake at night, the human mind's inability to rationally comprehend the world is low on the list. Well put. So, one interesting philosophical point that quantum mechanics bring up is that you talk about the distinction between the world as it is and the world as we observe it. So, staying at the human level for a second, how big is the gap between what our perception system allows us to see and the world as it is outside our mind's eye? Not at the quantum mechanical level, but as just these particular tools we have, which is the few senses and cognitive abilities to process those senses. Well, that last phrase, having the cognitive abilities to process them, carries a lot, right? I mean, there is our sort of intuitive understanding of the world. You don't need to teach people about gravity for them to know that apples fall from trees, right? That's something that we figure out pretty quickly. Object permanence, things like that. The three-dimensionality of space, even if we don't have the mathematical language to say that, we kind of know that it's true. On the other hand, no one opens their eyes and sees atoms, right? Or molecules, or cells for that matter. Forget about quantum mechanics. But we got there. We got to understanding that there are atoms and cells using the combination of our senses and our cognitive capacities. So adding the ability of our cognitive capacities to our senses is adding an enormous amount. And I don't think it is a hard and fast boundary. If you believe in cells, if you believe that we understand those, then there's no reason you believe we can't believe in quantum mechanics just as well. What to you is the most beautiful idea in physics? Conservation of momentum. Can you elaborate? Yeah. If you were Aristotle, when Aristotle wrote his book on physics, he made the following very obvious point. We're on video here, right? So people can see this. So if I push the bottle, let me cover this bottle so we do not have a mess, but okay. So I push the bottle, it moves. And if I stop pushing it, it stops moving. And this kind of thing is repeated a large number of times all over the place. If you don't keep pushing things, they stop moving. This is an indisputably true fact about our everyday environment, okay? And for Aristotle, this blew up into a whole picture of the world in which things had natures and teleologies, and they had places they wanted to be. And when you were pushing them, you were moving them away from where they wanted to be, and they would return and stuff like that. And it took a thousand years or 1500 years for people to say, actually, if it weren't for things like dissipation and air resistance and friction and so forth, the natural thing is for things to move forever in a straight line, the constant velocity, right? Conservation of momentum. And the reason why I think that's the most beautiful idea in physics is because it shifts us from a view of nature's and teleology to a view of patterns in the world. So when you were Aristotle, you needed to talk a vocabulary of why is this happening? What's the purpose of it? What's the cause, et cetera, because it's nature does or does not want to do that. Whereas once you believe in conservation of momentum, things just happen. They just follow the pattern. You have Laplace's demon, ultimately, right? You give me the state of the world today, I can predict what it's going to do in the future. I can predict where it was in the past. It's impersonal, and it's also instantaneous. It's not directed toward any future goals. It's just doing what it does, given the current state of the universe. I think even more than either classical mechanics or quantum mechanics, that is the profound deep insight that gets modern science off the ground. You don't need natures and purposes and goals. You just need some patterns. So it's the first moment in our understanding of the way the universe works where you branch from the intuitive physical space to kind of the space of ideas. And also the other point you said, which is conveniently, most of the interesting ideas are acting in the moment. You don't need to know the history of time or the future. And of course, this took a long time to get there, right? I mean, the conservation of momentum itself took hundreds of years. It's weird because someone would say something interesting, and then the next interesting thing would be said like 150 or 200 years later, right? They weren't even talking to each other, they were just reading each other's books. And probably the first person to directly say that in outer space, in the vacuum, a projectile would move at a constant velocity was Avicenna, Ibn Sina in the Persian golden age, circa 1000. And he didn't like the idea. He used that, just like Schrodinger used Schrodinger's cat to say, surely you don't believe that, right? Ibn Sina was saying, surely you don't believe there really is a vacuum because if there was a really vacuum, things could keep moving forever, right? But still, he got right the idea that there was this conservation of something impetus or mile, he would call it. And that's 600 years before classical mechanics and Isaac Newton. So Galileo played a big role in this, but he didn't exactly get it right. And so it just takes a long time for this to sink in because it is so against our everyday experience. Do you think it was a big leap, a brave or a difficult leap of sort of math and science to be able to say that momentum is conserved? Ian I do. I think it's a example of human reason in action. Even Aristotle knew that his theory had issues because you could fire an arrow and it would go a long way before it stopped. So if his theory was things just automatically stop, what's going on? And he had this elaborate story. I don't know if you've heard the story, but the arrow would push the air in front of it away and the molecules of air would run around the back of the arrow and push it again. And anyone reading this is going like, really, that's what you thought? But it was that kind of thought experiment that ultimately got people to say like, actually, no, if it weren't for the air molecules at all, the arrow would just go on by itself. And it's always this give and take between thought and experience back and forth, right? Theory and experiment, we would say today. Another big question that I think comes up certainly with quantum mechanics is what's the difference between math and physics to you? To me, very, very roughly, math is about the logical structure of all possible worlds and physics is about our actual world. And it just feels like our actual world is a gray area when you start talking about interpretations of quantum mechanics or no. I'm certainly using the word world in the broadest sense, all of reality. So I think that reality is specific. I don't think that there's every possible thing going on in reality. I think that there are rules, whether it's the Schrodinger equation or whatever. So I think that there's a sensible notion of the set of all possible worlds and we live in one of them. The world that we're talking about might be a multiverse, might be many worlds of quantum mechanics, might be much bigger than the world of our everyday experience, but it's still one physically contiguous world in some sense. But so if you look at the overlap of math and physics, it feels like when physics tries to reach for understanding of our world, it uses the tools of math to sort of reach beyond the limit of our current understanding. What do you make of that process of sort of using math to, so you start maybe with intuition or you might start with the math and then build up an intuition or, but this kind of reaching into the darkness, into the mystery of the world with math? Well, I think I would put it a little bit differently. I think we have theories, theories of the physical world, which we then extrapolate and ask, you know, what do we conclude if we take these seriously well beyond where we've actually tested them? It is separately true that math is really, really useful when we construct physical theories. And, you know, famously Eugene Wigner asked about the unreasonable success of mathematics and physics. I think that's a little bit wrong because anything that could happen, any other theory of physics that wasn't the real world, but some other world, you could always describe it mathematically. It's just that it might be a mess. The surprising thing is not that math works, but that the math is so simple and easy that you can write it down on a t-shirt, right? I mean, that's what is amazing. That's an enormous compression of information that seems to be valid in the real world. So that's an interesting fact about our world, which maybe we could hope to explain or just take as a brute fact. I don't know. But once you have that, you know, there's this indelible relationship between math and physics. But philosophically, I do want to separate them. What we extrapolate, we don't extrapolate math because there's a whole bunch of wrong math, you know, that doesn't apply to our world, right? We extrapolate the physical theory that we best think explains our world. Again, an unanswerable question. Why do you think our world is so easily compressible into beautiful equations? Yeah, I mean, like I just hinted at, I don't know if there's an answer to that question. There could be. What would an answer look like? Well, an answer could look like if you showed that there was something about our world that maximized something, you know, the mean of the simplicity and the powerfulness of the laws of physics. Or, you know, maybe we're just generic. Maybe in the set of all possible worlds, this is what the world would look like, right? Like, I don't really know. I tend to think not. I tend to think that there is something specific and rock bottom about the facts of our world that don't have further explanation. Like, the fact that the world exists at all, and furthermore, the specific laws of physics that we have. I think that in some sense, we're just going to, at some level, we're going to say, and that's how it is. And, you know, we can't explain anything more. I don't know how, if we're anywhere close to that right now, but that seems plausible to me. And speaking of rock bottom, one of the things, sort of your book kind of reminded me or revealed to me is that what's fundamental and what's emergent, it just feels like I don't even know anymore what's fundamental in physics, if there's anything. It feels like everything, especially with quantum mechanics, is revealing to us is that most interesting things that I would, as a limited human would think are fundamental, can actually be explained as emergent from the more deeper laws. I mean, we don't know, of course, you had to get that on the table. We don't know what is fundamental. We do know, we do have reason to say that certain things are more fundamental than others, right? Atoms and molecules are more fundamental than cells and organs. Quantum fields are more fundamental than atoms and molecules. We don't know if that ever bottoms out. I do think that there's sensible ways to think about it. I think that there's a lot of there's sensible ways to think about this. If you describe something like this table as a table, it has a height and a width and it's made of a certain material and it has a certain solidity and weight and so forth, that's a very useful description as far as it goes. There's a whole other description of this table in terms of a whole collection of atoms strung together in certain ways. The language of the atoms is more comprehensive than the language of the table. You could break apart the table, smash it to pieces, still talk about it as atoms, but you could no longer talk about it as a table, right? So I think that this comprehensiveness, the domain of validity of a theory gets broader and broader as the theory gets more and more fundamental. So what do you think Newton would say, maybe write in a book review, if you read your latest book on quantum mechanics, something deeply hidden? It would take a long time for him to think that any of this was making any sense. You catch him up pretty quick in the beginning. Yeah. You give him a shout out in the beginning. That's right. I mean, he was the man. I'm happy to say that Newton was the greatest scientist who ever lived. I mean, he invented calculus in his spare time, which would have made him the greatest mathematician just all by himself, right? All by that one thing. But of course, it's funny because Newton was in some sense still a pre-modern thinker. Rocky Kolb, who was a cosmologist at the University of Chicago, said that Galileo, even though he came before Newton, was a more modern thinker than Newton was. Like if you got Galileo and brought him to the present day, it would take him six months to catch up and then he'd be in your office telling you why your most recent paper was wrong. Whereas Newton just thought in this kind of more mystical way. He wrote a lot more about the Bible and alchemy than he ever did about physics. But he was also more brilliant than anybody else and way more mathematically astute than Galileo. So I really don't know. He might just say, like, give me the textbooks, leave me alone for a few months, and then be caught up. Or he might have had mental blocks against seeing the world in this way. I really don't know. Or perhaps find an interesting mystical interpretation of quantum mechanics. Very possible, yeah. Is there any other scientists or philosophers through history that you would like to know their opinion of your book? That's a good question. I mean, Einstein is the obvious one, right? He was not that long ago, but I even speculate at the end of my book about what his opinion would be. I am curious as to what about older philosophers, like Hume or Kant, what would they have thought? Or Aristotle, what would they have thought about modern physics? Because they do in philosophy, your predilections end up playing a much bigger role in your ultimate conclusions because you're not as tied down by what the data is. In physics, physics is lucky because we can't stray too far off the reservation as long as we're trying to explain the world that we actually see in our telescopes and microscopes. But it's just not fair to play that game because the people we're thinking about didn't know a whole bunch of things that we know, right? We lived through a lot that they didn't live through. So, by the time we got them caught up, they'd be different people. So, let me ask a bunch of basic questions. I think it would be interesting, useful for people who are not familiar, but even for people who are extremely well familiar. Let's start with, what is quantum mechanics? Quantum mechanics is the paradigm of physics that came into being in the early part of the 20th century that replaced classical mechanics. And it replaced classical mechanics in a weird way that we're still coming to terms with. So, in classical mechanics, you have an object, it has a location, it has a velocity. And if you know the location and velocity of everything in the world, you can say what everything's going to do. Quantum mechanics has an aspect of it that is kind of on the same lines. There's something called the quantum state or the wave function. And there's an equation governing what the quantum state does. So, it's very much like classical mechanics. The wave function is different. It's sort of a wave. It's a vector in a huge dimensional vector space rather than a position and a velocity. But okay, that's a detail. And the equation is the Schrodinger equation, not Newton's laws, but okay, again, a detail. Where quantum mechanics really becomes weird and different is that there's a whole other set of rules in our textbook formulation of quantum mechanics, in addition to saying that there's a quantum state and it evolves in time. And all these new rules have to do with what happens when you look at the system, when you observe it, when you measure it. In classical mechanics, there were no rules about observing. You just look at it and you see what's going on. That was it, right? In quantum mechanics, the way we teach it, there's something profoundly fundamental about the act of measurement or observation, and the system dramatically changes its state. Even though it has a wave function, like the electron in an atom is not orbiting in a circle, it's sort of spread out in a cloud. When you look at it, you don't see that cloud. When you look at it, it looks like a particle with a location. So, it dramatically changes its state right away. And the effects of that change can be instantly seen in what the electron does next. So, that's the, again, we need to be careful because we don't agree on what quantum mechanics says. So, that's why I need to say, like, in the textbook view, et cetera, right? But in the textbook view, quantum mechanics, unlike any other theory of physics, places, gives a fundamental role to the act of measurement. So, maybe even more basic, what is an atom and what is an electron? Sure. This all came together in a few years around the turn of the last century, right? Around the year 1900. Atoms predated then, of course, the word atom goes back to the ancient Greeks, but it was the chemists in the 1800s that really first got experimental evidence for atoms. They realized, you know, that there were two different types of tin oxide. And in these two different types of tin oxide, there was exactly twice as much oxygen in one type as the other. And like, why is that? Why is it never 1.5 times as much, right? And so, Dalton said, well, it's because there are tin atoms and oxygen atoms, and one form of tin oxide is one atom of tin and one atom of oxygen, and the other is one atom of tin and two atoms of oxygen. And on the basis of this, so this is, you know, a speculation, a theory, right? A hypothesis. But then on the basis of that, you make other predictions. And the chemists became quickly convinced that atoms were real. Yeah. The physicists took a lot longer to catch on, but eventually they did. And I mean, Boltzmann, who believed in atoms, he had a really tough time his whole life because he worked in Germany where atoms were not popular. They were popular in England, but not in Germany. And there, in general, the idea of atoms is it's the smallest building block of the universe for them. That's the kind of how they thought about it. That was the Greek idea, but the chemists in the 1800s jumped the gun a little bit. So these days, an atom is the smallest building block of a chemical element, right? Hydrogen, tin, oxygen, carbon, whatever. But we know that atoms can be broken up further than that. And that's what physicists discovered in the early 1900s, Rutherford, especially, and his colleagues. So the atom that we think about now, the cartoon, is that picture you've always seen of a little nucleus and then electrons orbiting it like a little solar system. And we now know the nucleus is made of protons and neutrons. So the weight of the atom, the mass, is almost all in its nucleus. Protons and neutrons are something like 1800 times as heavy as electrons are. Electrons are much lighter, but because they're lighter, they give all the life to the atoms. So when atoms get together, combine chemically, when electricity flows through a system, it's all the electrons that are doing all the work. Lex. And where quantum mechanics steps in, as you mentioned, with the position of velocity, with classical mechanics, and quantum mechanics is modeling the behavior of the electron. I mean, you can model the behavior of anything, but the electron, because that's where the fun is. Yeah. The electron was the biggest challenge, right, from the start. Yeah. Lex. So what's the wave function? You said it's an interesting detail. Yeah. Lex. But in any interpretation, what is the wave function in quantum mechanics? Yeah. Well, we had this idea from Rutherford that atoms look like little solar systems, but people very quickly realized that can't possibly be right, because if an electron is orbiting in a circle, it will give off light. All the light that we have in this room comes from electrons zooming up and down and wiggling, and that's what electromagnetic waves are. And you can calculate how long would it take for the electron just to spiral into the nucleus, and the answer is 10 to the minus 11 seconds, okay? A hundred billionth of a second. So that's not right. Meanwhile, people had realized that light, which we understood from the 1800s was a wave, had properties that were similar to that of particles, right? This is Einstein and Planck and stuff like that. So if something that we agree was a wave had particle-like properties, then maybe something we think is a particle, the electron, has wave-like properties, right? And so a bunch of people eventually came to the conclusion, don't think about the electron as a little point particle orbiting like a solar system. Think of it as a wave that is spread out. They cleverly gave this the name the wave function, which is the dopiest name in the world for one of the most profound things in the universe. There's literally a number at every point in space, which is the value of the electron's wave function at that point. And there's only one wave function. Yeah, they eventually figured that out. That took longer. But when you have two electrons, you do not have a wave function for electron one and a wave function for electron two. You have one combined wave function for both of them. And indeed, as you say, there's only one wave function for the entire universe at once. And that's where this beautiful dance, can you say what is entanglement? It seems one of the most fundamental ideas of quantum mechanics. Well, let's temporarily buy into the textbook interpretation of quantum mechanics. And what that says is that this wave function, so it's very small outside the atom, very big in the atom. Basically, the wave function, you take it and you square it, you square the number that gives you the probability of observing the system at that location. So if you say that for two electrons, there's only one wave function, and that wave function gives you the probability of observing both electrons at once doing something. Okay. So maybe the electron can be here or here, here, here, and the other electron can also be there. But we have a wave function set up where we don't know where either electron is going to be seen, but we know they'll both be seen in the same place. Okay. So we don't know exactly what we're going to see for either electron, but there's entanglement between the two of them. There's a sort of conditional statement. If we see one in one location, then we know the other one's going to be doing a certain thing. So that's a feature of quantum mechanics that is nowhere to be found in classical mechanics. In classical mechanics, there's no way I can say, well, I don't know where either one of these particles is, but if I find out where this one is, then I know where the other one is. That just never happens. They're truly separate. And in general, it feels like if you think of a wave function like as a dance floor, it seems like entanglement is strongest between things that are dancing together closest. So there's a closeness that's important. Well, that's another step. We have to be careful here because in principle, if you're talking about the entanglement of two electrons, for example, they can be totally entangled or totally unentangled no matter where they are in the universe. There's no relationship between the amount of entanglement and the distance between two electrons. But we now know that the reality of our best way of understanding the world is through quantum fields, not through particles. So even the electron, not just gravity and electromagnetism, but even the electron and the quarks and so forth are really vibrations in quantum fields. So even empty space is full of vibrating quantum fields. And those quantum fields in empty space are entangled with each other in exactly the way you just said. If they're nearby, if you have like two vibrating quantum fields that are nearby, then they will be highly entangled. If they're far away, they will not be entangled. So what do quantum fields in a vacuum look like? Empty space? Just like empty space. It's as empty as it can be. But there's still a field. It's just... What does nothing look like? Just like right here, this location in space, there's a gravitational field, which I can detect by dropping something. I don't see it, but there it is. So we got a little bit of an idea of entanglement. Now, what is Hilbert space and Euclidean space? Yeah, I think that people are very welcome to go through their lives not knowing what Hilbert space is. But if you want to dig into a little bit more into quantum mechanics, it becomes necessary. The English language was invented long before quantum mechanics or various forms of higher mathematics were invented. So we use the word space to mean different things. Of course, most of us think of space as this three-dimensional world in which we live, right? I mean, some of us just think of it as outer space. But space around us, it gives us the three-dimensional location of things and objects. But mathematicians use any generic abstract collection of elements as a space, a space of possibilities, momentum space, etc. So Hilbert space is the space of all possible quantum wave functions, either for the universe or for some specific system. And it could be an infinite dimensional space, or it could be just really, really large dimensional but finite. We don't know because we don't know the final theory of everything. But this abstract Hilbert space is really, really, really big and has no immediate connection to the three-dimensional space in which we live. What do dimensions in Hilbert space mean? You know, it's just a way of mathematically representing how much information is contained in the state of the system. How many numbers do you have to give me to specify what the thing is doing? So in classical mechanics, I give you the location of something by giving you three numbers, right? Up, down, left, X, Y, Z coordinates. But then I might want to give you its entire state, physical state, which means both its position and also its velocity. The velocity also has three components. So its state lives in something called phase space, which is six dimensional, three dimensions of position, three dimensions of velocity. And then if it also has an orientation in space, that's another three dimensions and so forth. So as you describe more and more information about the system, you have an abstract mathematical space that has more and more numbers that you need to give. And each one of those numbers corresponds to a dimension in that space. So in terms of the amount of information, what is entropy? This mystical word that's overused in math and physics, but has a very specific meaning in this context. Sadly, it has more than one very specific meaning. This is the reason why it is hard. Entropy means different things, even to different physicists. But one way of thinking about it is a measure of how much we don't know about the state of a system. So if I have a bottle of water molecules and I know that okay, there's a certain number of water molecules, I could weigh it and figure out. I know the volume of it and I know the temperature and pressure and things like that. I certainly don't know the exact position and velocity of every water molecule. So there's a certain amount of information I know, certain amount that I don't know that is part of the complete state of the system. And that's what the entropy characterizes, how much unknown information there is, the difference between what I do know about the system and its full exact microscopic state. So when we try to describe a quantum mechanical system, is it infinite or finite but very large? Yeah, we don't know. That depends on the system. You know, it's easy to mathematically write down a system that would have a potentially infinite entropy, an infinite dimensional Hilbert space. So let's go back a little bit. We said that the Hilbert space was the space in which quantum wave functions lived for different systems that will be different sizes. They could be infinite or finite. So that's the number of numbers, the number of pieces of information you could potentially give me about the system. So the bigger Hilbert space is, the bigger the entropy of that system could be, depending on what I know about it. If I don't know anything about it, then it has a huge entropy, right? But only up to the size of its Hilbert space. So we don't know in the real physical world whether or not this region of space that contains that water bottle has potentially an infinite entropy or just a finite entropy. We have different arguments on different sides. So if it's infinite, how do you think about infinity? Is this something you can, your cognitive abilities are able to process or is it just a mathematical tool? It's somewhere in between, right? I mean, we can say things about it. We can use mathematical tools to manipulate infinity very, very accurately. You can define what we mean. You know, for any number n, there's a number bigger than it. So there's no biggest number, right? So there's something called the total number of all numbers. It's infinite. But it is hard to wrap your brain around that. And I think that gives people pause because we talk about infinity as if it's a number, but it has plenty of properties that real numbers don't have. You know, if you multiply infinity by two, you get infinity again, right? That's a little bit different than what we're used to. Okay, but are you comfortable with the idea that, in thinking of what the real world actually is, that infinity could be part of that world? Are you comfortable that a world in some dimension, in some aspect- I'm comfortable with lots of things. I mean, you know, I don't want my level of comfort to affect what I think about the world. You know, I'm pretty open-minded about what the world could be at a fundamental level. Yeah, but infinity is a tricky one. It's not almost a question of comfort. It's a question of, is it an overreach of our intuition? Sort of, it could be a convenient, almost like, when you add a constant to an equation just because it'll help, it just feels like it's useful to at least be able to imagine a concept, not directly, but in some kind of way that this feels like it's a description of the real world. Think of it this way. There's only three numbers that are simple. There's zero, there's one, and there's infinity. A number like 318 is just bizarre. You need a lot of bits to give me what that number is. But zero and one and infinity, like once you have 300 things, you might as well have infinity things, right? Otherwise, you have to say when to stop making the things, right? So there's a sense in which infinity is a very natural number of things to exist. I was never comfortable with infinity because it's just such a- it was too good to be true. Because in math, it just helps make things work out. When things get very- it's- when things get very large, close to infinity, things seem to work out nicely. It's kind of like- because my deepest passion is probably psychology. And I'm uncomfortable how in the average, the beauty of the very- how much we vary is lost. In that same kind of sense, infinity seems like a convenient way to erase the details. But the thing about infinity is it seems to pop up whether we like it or not, right? Like you're trying to be a computer scientist, you ask yourself, well, how long will it take this program to run? And you realize, well, for some of them, the answer is infinitely long. It's not because you tried to get there. You wrote a five-line computer program. It doesn't halt. So, coming back to the textbook definition of quantum mechanics, this idea that- I don't think we talked about, can you- this- one of the most interesting philosophical points, we talked at the human level, but at the physics level, that at least the textbook definition of quantum mechanics separates what is observed and what is real. One, how does that make you feel? And two, what does it then mean to observe something and why is it different than what is real? Yeah, you know, my personal feeling, such as it is, is that things like measurement and observers and stuff like that are not going to play a fundamental role in the ultimate laws of physics. But my feeling that way is because so far, that's where all the evidence has been pointing. I could be wrong and there's certainly a sense in which it would be infinitely cool if somehow observation or mental cogitation did play a fundamental role in the nature of reality. But I don't think so, and again, I don't see any evidence for it, so I'm not spending a lot of time worrying about that possibility. So what do you do about the fact that in the textbook interpretation of quantum mechanics, this idea of measurement or looking at things seems to play an important role? Well, you come up with better interpretations of quantum mechanics and there are several alternatives. My favorite is the many worlds interpretation, which says two things. Number one, you, the observer, are just a quantum system like anything else. There's nothing special about you. Don't get so proud of yourself. You're just a bunch of atoms. You have a wave function. You obey the Schrodinger equation like everything else. And number two, when you think you're measuring something or observing something, what's really happening is you're becoming entangled with that thing. So when you think there's a wave function for the electron, it's all spread out, but you look at it and you only see it in one location. What's really happening is that there's still the wave function for the electron in all those locations, but now it's entangled with the wave function of you in the following way. There's part of the wave function that says the electron was here and you think you saw it there. The electron was there and you think you saw it there. The electron was over there and you think you saw it there, et cetera. So, and all of those different parts of the wave function, once they come into being, no longer talk to each other. They no longer interact or influence each other. It's as if they are separate worlds. So this was the invention of Hugh Everett III, who was a graduate student at Princeton in the 1950s. And he said, basically, look, you don't need all these extra rules about looking at things. Just listen to what the Schrodinger equation is telling you. It's telling you that you have a wave function, that you become entangled, and that the different versions of you no longer talk to each other. So just accept it. It's just he did therapy more than anything else. He said, like, it's okay. You don't need all these extra rules. All you need to do is believe the Schrodinger equation. The cost is there's a whole bunch of extra worlds out there. So are the worlds being created whether there's an observer or not? The worlds are created anytime a quantum system that's in a superposition becomes entangled with the outside world. What's the outside world? It depends. Let's back up. Whatever it really says, what his theory is, is there's a wave function of the universe, and it obeys the Schrodinger equation all the time. That's it. That's the full theory right there. The question, all of the work is how in the world do you map that theory onto reality, onto what we observe? So part of it is carving up the wave function into these separate worlds, saying, look, it describes a whole bunch of things that don't interact with each other. Let's call them separate worlds. Another part is distinguishing between systems and their environments. And the environment is basically all the degrees of freedom, all the things going on in the world that you don't keep track of. So again, in the bottle of water, I might keep track of the total amount of water and the volume. I don't keep track of the individual positions and velocities. I don't keep track of all the photons or the air molecules in this room. So that's the outside world. The outside world is all the parts of the universe that you're not keeping track of when you're asking about the behavior of some subsystem of it. So how many worlds are there? I don't know that one either. There could be an infinite number. There could be only a finite number, but it's a big number one way or the other. It's just a very, very big number. In one of the talks, somebody asked, well, if it's a, if it's finite, so actually I'm not sure exactly the logic you use to derive this, but is there going to be overlap, a duplicate world that you return to? So you've mentioned, and I'd love if you can elaborate on sort of idea that it's possible that there's some kind of equilibrium that these splitting worlds arrive at. And then maybe over time, maybe somehow connected to entropy, you get a large number of worlds that are not split. The entropy, you get a large number of worlds that are very similar to each other. Yeah. So this question of whether or not Hilbert space is finite or infinite dimensional is actually secretly connected to gravity and cosmology. This is the part that we're still struggling to understand right now, but we discovered back in 1998 that our universe is accelerating. And what that means if it continues, which we think it probably will, but we're not sure, but if it does, that means there's a horizon around us. There's because the universe is not only expanding, but expanding faster and faster, things can get so far away from us that from our perspective, it looks like they're moving away faster than the speed of light. We will never see them again. So there's literally a horizon around us and that horizon approaches some fixed distance away from us. And you can then argue that within that horizon, there's only a finite number of things that can possibly happen, the finite dimensional Hilbert space. In fact, we even have a guess for what the dimensionality is. It's 10 to the power of 10 to the power of 122. That's a very large number. Just to compare it, the age of the universe is something like 10 to the 14 seconds, 10 to the 17 or 18 seconds, maybe. The number of particles in the universe is 10 to the 88th, but the number of dimensions of Hilbert space is 10 to the 10 to the 122. So that's just crazy big. If that story is right, that in our observable horizon, there's only a finite dimensional Hilbert space, then this idea of branching of the wave function of the universe into multiple distinct, separate branches has to reach a limit at some time. Once you branch that many times, you've run out of room in Hilbert space. And roughly speaking, that corresponds to the universe just expanding and emptying out and cooling off and entering a phase where it's just empty space literally forever. What's the difference between splitting and copying, do you think? A lot of this is an interpretation that helps us sort of model the world. So perhaps shouldn't be thought of as like, you know, philosophically or metaphysically, but even at the physics level, do you see a difference between sort of generating new copies of the world or splitting? I think it's better to think of in quantum mechanics, in many worlds, the universe splits rather than new copies because people otherwise worry about things like energy conservation. And no one who understands quantum mechanics worries about energy conservation because the equation is perfectly clear. But if all you know is that someone told you the universe duplicates, then you have a reasonable worry about where all the energy for that came from. So a pre-existing universe splitting into two skinnier universes is a better way of thinking about it. And mathematically, it's just like, you know, if you draw an x and y axis, and you draw a vector of length one, a 45 degree angle, you know that you can write that vector of length one as the sum of two vectors pointing along x and y of length one over the square root of two. Okay. So I write one arrow as the sum of two arrows, but there's a conservation of arrow-ness, right? Like there's now two arrows, but the length is the same. I just am describing it in a different way. And that's exactly what happens when the universe branches. The wave function of the universe is a big old vector. So to somebody who brings up a question of saying, doesn't this violate the conservation of energy? Can you give further elaboration? Right. So let's just be super duper perfectly clear. There's zero question about whether or not many worlds violates conservation of energy. It does not. And I say this definitively because there are other questions that I think there's answers to, but they're legitimate questions, right? About, you know, where does probability come from and things like that. This conservation of energy question, we know the answer to it. And the answer to it is that energy is conserved. All of the effort goes into how best to translate what the equation unambiguously says into plain English, right? So this idea that there's a universe that has, that the universe comes equipped with a thickness and it sort of divides up into thinner pieces, but the total amount of universe is conserved over time is a reasonably good way of putting English words to the underlying mathematics. So one of my favorite things about many worlds is, I mean, I love that there's something controversial in science. And for some reason it makes people actually not like upset, but just get excited. Why do you think it is a controversial idea? So there's a lot of, it's actually one of the cleanest ways to think about quantum mechanics. So why do you think there's a discomfort a little bit amongst certain people? Well, I draw the distinction in my book between two different kinds of simplicity in a physical theory. There's simplicity in the theory itself, right? How we describe what's going on according to the theory by its own rights. But then, you know, theory is just some sort of abstract mathematical formalism. You have to map it onto the world somehow, right? And sometimes like for Newtonian physics, it's pretty obvious, like, okay, here is a bottle and it has a center of mass and things like that. Sometimes it's a little bit harder with general relativity, curvature of space-time is a little bit harder to grasp. Quantum mechanics is very hard to map what the language you're talking in of wave functions and things like that onto reality. And many worlds is the version of quantum mechanics where it is hardest to map on the underlying formalism to reality. So that's where the lack of simplicity comes in, not in the theory, but in how we use the theory to map onto reality. And in fact, all of the work in sort of elaborating many worlds quantum mechanics is in the, this effort to map it on to the world that we see. So it's perfectly legitimate to be bugged by that, right? To say like, well, no, that's just too far away from my experience. I am therefore intrinsically skeptical of it. Of course, you should give up on that skepticism if there are no alternatives and this theory always keeps working, then eventually you should overcome your skepticism. But right now there are alternatives that are, that, you know, people work to make alternatives that are by their nature closer to what we observe directly. Can you describe the alternatives? I don't think we touched on it. So the Copenhagen interpretation and the many worlds, maybe there's a difference between the Everettian many worlds and many worlds as it is now, like has the idea sort of developed and so on. And just in general, what is the space of promising contenders? We have democratic debates now, there's a bunch of candidates, 12 candidates on stage. What are the quantum mechanical candidates on stage for the debate? So if you had a debate between quantum mechanical contenders, it would be no problem getting 12 people up there on stage, but there would still be only three front runners. And right now the front runners would be Everett. Hidden variable theories are another one. So the hidden variable theories say that the wave function is real, but there's something in addition to the wave function. The wave function is not everything, it's part of reality, but it's not everything. What else is there? We're not sure, but in the simplest version of the theory, there are literally particles. So many worlds says that quantum systems are sometimes are wave-like in some ways and particle-like in another because they really, really are waves, but under certain observational circumstances, they look like particles. Whereas hidden variable says they look like waves and particles because there are both waves and particles involved in the dynamics. And that's easy to do if your particles are just non-relativistic Newtonian particles moving around, they get pushed around by the wave function roughly. It becomes much harder when you take quantum field theory or quantum gravity into account. The other big contender are spontaneous collapse theories. So in the conventional textbook interpretation, we say when you look at a quantum system, its wave function collapses and you see it in one location. A spontaneous collapse theory says that every particle has a chance per second of having its wave function spontaneously collapse. The chance is very small. For a typical particle, it will take hundreds of millions of years before it happens even once, but in a table or some macroscopic object, there are way more than a hundred million particles and they're all entangled with each other. So when one of them collapses, it brings everything else along with it. There's a slight variation of this. That's a spontaneous collapse theory. There are also induced collapse theories like Roger Penrose thinks that when the gravitational difference between two parts of the wave function becomes too large, the wave function collapses automatically. So those are basically in my mind, the three big alternatives. Many worlds, which is just, there's a wave function and always obeys the Schrodinger equation. Hidden variables, there's a wave function that always obeys the Schrodinger equation, but there are also new variables or collapse theories, which the wave function sometimes obeys the Schrodinger equation and sometimes it collapses. So you can see that the alternatives are more complicated in their formalism than many worlds is, but they are closer to our experience. So just this moment of collapse, do you think of it as a wave function, fundamentally sort of a probabilistic description of the world and is collapse sort of reducing that part of the world into something deterministic where again, you can now describe the position and the velocity in this simple classical model? Is that how you think about collapse? There is a fourth category, is a fourth contender. There's a Mayor Pete of quantum mechanical interpretations, which are called epistemic interpretations. And what they say is all the way function is, is a way of making predictions for experimental outcomes. It's not mapping onto an element of reality in any real sense. And in fact, two different people might have two different wave functions for the same physical system because they know different things about it, right? The way function is really just a prediction mechanism. And then the problem with those epistemic interpretations is if you say, okay, but it's predicting about what, like what is the thing that is being predicted? And they say, no, no, no, no, that's not what we're here for. We're just here to tell you what the observational outcomes are going to be. But the other, the other interpretations kind of think that the way function is real. Yes, that's right. So that's an on tick interpretation of the way function ontology being the study of what is real, what exists as opposed to an epistemic interpretation of the wave function epistemology being the study of what we know. I would actually just love to see that debate on stage. There was a version of it on stage at the world science festival a few years ago that you can look up online. On YouTube. Yep. It's on YouTube. Okay. Awesome. I'll link it and watch it. Who won? I won. No, of course, I don't know. There was no vote. There was no vote. But those there's Brian Green was the moderator and David Albert stood up for a spontaneous collapse and Shelley Goldstein was there for hidden variables and Rüdiger Schock was there for epistemic approaches. Why do you, I think you mentioned it, but just to elaborate, why do you find many worlds so compelling? Well, there's two reasons, actually. One is, like I said, it is the simplest, right? It's like the most bare bones, austere, pure version of quantum mechanics. And I am someone who is very willing to put a lot of work into mapping the formalism onto reality, I'm less willing to complicate the formalism itself. But the other big reason is that there's something called modern physics, with quantum fields and quantum gravity and holography and space time, doing things like that. And when you take any of the other versions of quantum theory, they bring along classical baggage, all of the other versions of quantum mechanics, prejudice or privilege some version of classical reality like locations in space. Okay. And I think that that's a barrier to doing better and understanding the theory of everything and understanding quantum gravity and the emergence of space time. Whenever, if you change your theory from, you know, here's a harmonic oscillator, oh, there's a spin, here's an electromagnetic field, in hidden variable theories or dynamical collapse theories, you have to start from scratch. You have to say like, well, what are the hidden variables for this theory? Or how does it collapse or whatever? Whereas many worlds is plug and play. You tell me the theory and I can give you as many worlds version. So when we have a situation like we have with gravity and space time, where the classical description seems to break down in a dramatic way, then I think you should start from the most quantum theory that you have, which is really many worlds. LRF So start with the quantum theory and try to build up a model of space time, the emergence of space time. PW That's right. LRF Okay. So I thought space time was fundamental. PW Yeah, I know. LRF So this sort of dream that Einstein had that everybody had and everybody has of, you know, the theory of everything. So how do we build up from many worlds, from quantum mechanics, a model of space time, a model of gravity? PW Well, yeah, I mean, let me first mention very quickly why we think it's necessary. You know, we've had gravity in the form that Einstein bequeathed it to us for over 100 years now, like 1915 or 1916, he put general relativity in the final form. So gravity is the curvature of space time. And there's a field that pervades all the universe that tells us how curved space time is. LRF And that's a fundamentally classical. PW That's totally classical, right? Exactly. But we also have a formalism, an algorithm for taking a classical theory and quantizing it. This is how we get quantum electrodynamics, for example. And it could be tricky. I mean, you think you're quantizing something, so that means taking a classical theory and promoting it to a quantum mechanical theory. But you can run into problems. So they ran into problems, and they did that with electromagnetism, namely that certain quantities were infinity, and you don't like infinity, right? So Feynman and Tomonaga and Schwinger won the Nobel Prize for teaching us how to deal with the infinities. And then Ken Wilson won another Nobel Prize for saying you shouldn't have been worried about those infinities after all. But still, that was the it's always the thought that that's how you will make a good quantum theory, you'll start with a classical theory and quantize it. PW So if we have a classical theory, general relativity, we can quantize it, or we can try to, but we run into even bigger problems with gravity than we ran into with electromagnetism. And so far, those problems are insurmountable. We have not been able to get a successful theory of gravity, quantum gravity, by starting with classical general relativity and quantizing it. And there's evidence that there's a good reason why this is true, that whatever the quantum theory of gravity is, it's not a field theory. It's something that has weird non local features built into it somehow that we don't understand. And we get this idea from black holes and Hawking radiation and information conservation, a whole bunch of other ideas I talked about in the book. So if that's true, if the fundamental theory isn't even local in the sense that an ordinary quantum field theory would be, then we just don't know where to start in terms of getting a classical precursor and quantizing it. So the only sensible thing, or at least the next obvious sensible thing to me would be to say, okay, let's just start intrinsically quantum and work backwards, see if we can find a classical limit. LR So the idea of locality, the fact that locality is not fundamental to the nature of our existence, I guess in that sense, modeling everything as a field makes sense to me, stuff that's close by, it interacts, stuff that's far away doesn't. So what's locality and why is it not fundamental? And how is that even possible? JF Yeah. I mean, locality is the answer to the question that Isaac Newton was worried about back at the beginning of our conversation, right? I mean, how can the earth know what the gravitational field of the sun is? And the answer as spelled out by Laplace and Einstein and others is that there's a field in between. And the way a field works is that what's happening to the field at this point in space only depends directly on what's happening at points right next to it. But what's happening at those points depends on what's happening right next to those, right? And so you can build up an influence across space through only local interactions. That's what locality means. What happens here is only affected by what's happening right next to it. That's locality. The idea of locality is built into every field theory, including general relativity as a classical theory. It seems to break down when we talk about black holes. And Hawking taught us in the 1970s that black holes radiate. They give off, they will eventually evaporate away. They're not completely black once we take quantum mechanics into account. And we think, we don't know for sure, but most of us think that if you make a black hole out of certain stuff, then like Laplace's demon taught us, you should be able to predict what that black hole will turn into if it's just obeying the Schrodinger equation. And if that's true, there are good arguments that can't happen while preserving locality at the same time. It's just that the information seems to be spread out non-locally in interesting ways. And people should, you talk about holography with Leonard Susskind on your Mindscape podcast. Oh yes, I have a podcast. I didn't even mention that. This is terrible. No, I'm going to ask you questions about that too. And I've been not shutting up about it. It's my favorite science podcast. So, or not, it's not even a science podcast. It's like, it's a scientist doing a podcast. That's right. That's what it is. Absolutely. Yes. Anyway. Yeah. So holography is this idea when you have a black hole and black hole is a region of space inside of which gravity is so strong that you can't escape. And there's this weird feature of black holes that again, is totally a thought experiment feature because we haven't gone and probed any yet. But there seems to be one way of thinking about what happens inside a black hole as seen by an observer who's falling in, which is actually pretty normal, like everything looks pretty normal until you hit the singularity and you die. But from the point of view of the outside observer, it seems like all the information that fell in is actually smeared over the horizon in a non-local way. And that's puzzling. And that's so holography because that's a two-dimensional surface that is encapsulating the whole three-dimensional thing inside. Right? Still trying to deal with that. Still trying to figure out how to get there. But it's an indication that we need to think a little bit more subtly when we quantize gravity. So because you can describe everything that's going on in three-dimensional space by looking at the two-dimensional projection of it, it means that locality is not necessary. Well, it means that somehow it's only a good approximation. It's not really what's going on. How are we supposed to feel about that? Supposed to feel liberated. You know, space is just a good approximation. And this was always going to be true once you started quantizing gravity. So we're just beginning now to face up to the dramatic implications of quantizing gravity. Is there other weird stuff that happens to quantum mechanics in a black hole? I don't think that anything weird has happened with quantum mechanics. I think weird things happen with space-time. I mean, that's what it is. Like quantum mechanics is still just quantum mechanics. But our ordinary notions of space-time don't really quite work. And there's a principle that goes hand in hand with holography called complementarity, which says that there's no one unique way to describe what's going on inside a black hole. Different observers will have different descriptions, both of which are accurate, but sound completely incompatible with each other. So it depends on how you look at it. You know, the word complementarity in this context is borrowed from Niels Bohr, who points out you can measure the position or you can measure the momentum. You can't measure both at the same time in quantum mechanics. So a couple of questions on many worlds. How does many worlds help us understand our particular branch of reality? So, okay, that's fine and good, that everything is splitting, but we're just traveling down a single branch of it. So how does it help us understand our little unique branch? Yeah, I mean, that's a great question. But that's the point is that we didn't invent many worlds because we thought it was cool to have a whole bunch of worlds, right? We invented it because we were trying to account for what we observe here in our world. And what we observe here in our world are wave functions collapsing, okay? We do have a situation where the electron seems to be spread out, but then when we look at it, we don't see it spread out. We see it located somewhere. So what's going on? That's the measurement problem of quantum mechanics. That's what we have to face up to. So many worlds is just a proposed solution to that problem. And the answer is nothing special is happening. It's still just the Schrodinger equation, but you have a wave function too. And that's a different answer than would be given in hidden variables or dynamical collapse theories or whatever. So the entire point of many worlds is to explain what we observe, but it tries to explain what we already have observed, right? It's not trying to be different from what we've observed because that would be something other than quantum mechanics. But the idea that there's worlds that we didn't observe that keep branching off is stimulating to the imagination. So is it possible to hop from, you mentioned the branches are independent. Is it possible to hop from one to the other? No. So it's a physical limit. The theory says it's impossible. There's already a copy of you in the other world, don't worry. Yes. Leave them alone. No, but there's a fear of missing out FOMO. Yes. That I feel like immediately start to wonder if that other copy is having more or less fun. Well, the downside to many worlds is that you're missing out on an enormous amount. And that's always what it's going to be like. And I mean, there's a certain stage of acceptance in that. In terms of rewinding, you think we can rewind the system back. The nice thing about many worlds, I guess, is it really emphasizes the, maybe you can correct me, but the deterministic nature of a branch. And it feels like it could be rewound back. Do you see as something that could be perfectly rewound back, rewinded back? Yeah. If you're at a fancy French restaurant and there's a nice linen white tablecloth and you have your glass of Bordeaux and you knock it over and the wine spills across the tablecloth. If the world were classical, okay, it would be possible that if you just lifted the wine glass up, you'd be lucky enough that every molecule of wine would hop back into the glass. Right? But guess what? It's not going to happen in the real world. And the quantum wave function is exactly the same way. It is possible in principle to rewind everything if you start from perfect knowledge of the entire wave function of the universe. In practice, it's never going to happen. So time travel, not possible. Nope. At least quantum mechanics has no help. What about memory? Does the universe have a memory of itself where we could, so not time travel, but peek back in time and do a little replay? Well, it's exactly the same in quantum mechanics as classical mechanics. So whatever you want to say about that, the fundamental laws of physics in either many worlds, quantum mechanics or Newtonian physics, conserve information. So if you have all the information about the quantum state of the world right now, your Laplace's demon-like in your knowledge and calculational capacity, you can wind the clock backward. But none of us is, right? And so in practice, you can never do that. You can do experiments over and over again, starting from the same initial conditions for small systems. But once things get to be large, Avogadro's number of particles, right? Bigger than a cell, no chance. We talked a little bit about arrow of time last time, but in many worlds, in many worlds that there is a kind of implied arrow of time, right? So you've talked about the arrow of time that has to do with the second law of thermodynamics. That's the arrow of time that's emergent or fundamental. We don't know, I guess. No, it's emergent. Is that, does everyone agree on that? Well, nobody agrees with everything. They should. They should. Okay. So that arrow of time, is that different than the arrow of time that's implied by many worlds? It's not different, actually. No. In both cases, you have fundamental laws of physics that are completely reversible. If you give me the state of the universe at one moment in time, I can run the clock forward or backward equally well. There's no arrow of time built into the laws of physics at the most fundamental level. But what we do have are special initial conditions, 14 billion years ago near the Big Bang. In thermodynamics, those special initial conditions take the form of things were low entropy, and entropy has been increasing ever since, making the universe more disorganized and chaotic, and that's the arrow of time. In quantum mechanics, these special initial conditions take the form of there was only one branch of the wave function, and the universe has been branching more and more ever since. Okay. So if time is emergent, so it seems like our human cognitive capacity likes to take things that are emergent and assume and feel like they're fundamental. So if time is emergent, and locality, like is space emergent? Yes. Okay. But I didn't say time was emergent. I said the arrow of time was emergent. Those are different. What's the difference between the arrow of time and time? Are you using arrow of time to simply mean they're synonymous with the second law of thermodynamics? No, but the arrow of time is the difference between the past and future. So there's space, but there's no arrow of space. You don't feel that space has to have an arrow, right? You could live in thermodynamic equilibrium. There'd be no arrow of time, but there'd still be time. There'd still be a difference between now and the future or whatever. Ah, so, okay. So if nothing changes, there's still time. Well, things could even change. Like if the whole universe consisted of the earth going around the sun, okay, it would just go in circles or ellipses, right? That's an equilibrium. Things would change, but it's not increasing entropy. There's no arrow. If you took a movie of that and I played you the movie backward, you would never know. So the arrow of time can theoretically point in the other direction for brief, briefly. To the extent that it points in different directions, it's not a very good arrow. I mean, the arrow of time in the macroscopic world is so powerful that there's just no chance of going back. When you get down to tiny systems with only three or four moving parts, then entropy can fluctuate up and down. What does it mean for space to be an emergent phenomena? It means that the fundamental description of the world does not include the words space. It'll be something like a vector in Hilbert space, right? And you have to say, well, why is there a good approximate description, which involves three-dimensional space and stuff inside it? Okay. So time and space are emergent. We kind of mentioned in the beginning, but can you elaborate what do you feel hope is fundamental in our universe? A wave function living in Hilbert space. A wave function in Hilbert space that we can't intellectualize or visualize, really. We can't visualize it. We can intellectualize it very easily. Like, well, how do you think about... It's a vector in a 10 to the 10 to the 122 dimensional vector space. It's a complex vector, unit norm. It evolves according to the Schrodinger equation. Got it. When you put it that way... What's so hard, really? It's like, yep, quantum computers. There's some excitement, actually a lot of excitement with people that it will allow us to simulate quantum mechanical systems. What kind of questions do you about quantum mechanics, about the things we've been talking about, do you think, do you hope we can answer through quantum simulation? Well, I think that there's a whole fascinating frontier of things you can do with quantum computers, both sort of practical things with cryptography or money, privacy eavesdropping, sorting things, simulating quantum systems. So it's a broader question, maybe even outside of quantum computers. Some of the theories that we've been talking about, what's your hope? What's most promising to test these theories? What are kind of experiments we can conduct, whether in simulation or in the physical world, that would validate or disprove or expand these theories? Well, I think there's two parts of that question. One is many worlds, and the other one is sort of emergent space time. For many worlds, there are experiments ongoing to test whether or not wave functions spontaneously collapse. And if they do, then that rules out many worlds and that will be falsified. If there are hidden variables, there's a theorem that seems to indicate that the predictions will always be the same as many worlds. I'm a little skeptical of this theorem. I haven't internalized it. I haven't made it in part of my intuitive view of the world yet. So there might be loopholes to that theorem. I'm not sure about that. Part of me thinks that there should be different experimental predictions if there are hidden variables, but I'm not sure. But otherwise, it's just quantum mechanics all the way down. And so there's this cottage industry in science journalism of writing breathless articles that say quantum mechanics shown to be more astonishing than ever before thought. And really, it's the same quantum mechanics we've been doing since 1926. Whereas with the emergent space time stuff, we know a lot less about what the theory is. It's in a very primitive state. We don't even really have a safely written down respectable honest theory yet. So there could very well be experimental predictions we just don't know about yet. That is one of the things that we're trying to figure out. But for emergent space time, you need really big stuff, right? Well, or really fast stuff or really energetic stuff. We don't know. That's the thing. So there could be violations of the speed of light if you have emergent space time. Not going faster than the speed of light, but the speed of light could be different for light of different wavelengths. Right? That would be a dramatic violation of physics as we know it, but it could be possible. Or not. I mean, it's not an absolute prediction. That's the problem. The theories are just not well developed enough yet to say. Is there anything that quantum mechanics can teach us about human nature or the human mind? Do you think about sort of consciousness and these kinds of topics? It's certainly excessively used, as you point out. The word quantum is used for everything besides quantum mechanics. But in more seriousness, is there something that goes to the human level and can help us understand our mind? Not really, is the short answer. Minds are pretty classical. I don't think. We don't know this for sure, but I don't think that phenomena like entanglement are crucial to how the human mind works. What about consciousness? So you mentioned, I think, early on in the conversation you said it would be unlikely but incredible if sort of the observer is somehow a fundamental part. So observer, not to romanticize the notion, but seems interlinked to the idea of consciousness. Yeah. So if consciousness is, as the panpsychics believe, is fundamental to the universe, is that possible? Is that weight? I mean, everything's possible. Just like Joe Rogan likes to say, it's entirely possible. But okay, but is it on a spectrum of crazy out there? Statistically speaking, how often do you ponder the possibility that consciousness is fundamental or the observer is fundamental to- I personally don't at all. There are people who do. I'm a thorough physicalist when it comes to consciousness. I do not think that there are any separate mental states or mental properties. I think they're all emergent, just like space-time is. And space-time is hard enough to understand. So the fact that we don't yet understand consciousness is not at all surprising to me. You, as we mentioned, have an amazing podcast called Mindscape. It's, as I said, one of my favorite podcasts, sort of both for your explanation of physics, which a lot of people love, and when you venture out into things that are beyond your expertise. But it's just a really smart person exploring even questions like, you know, morality, for example. It's very interesting. I think you did a solo episode and so on. I mean, there's a lot of really interesting conversations that you have. What are some, from memory, amazing conversations that pop to mind that you've had? What did you learn from them? Something that maybe changed your mind or just inspired you? Or just, through this whole experience of having conversations, what stands out to you? It's an unfair question. It's totally unfair, but that's okay. That's all right. You know, it's often the ones, I feel like the ones I do on physics and closely related science, or even philosophy ones, are like, I know this stuff and I'm helping people learn about it. But I learn more from the ones that have nothing to do with physics or philosophy, right? So, talking to Wynton Marsalis about jazz, or talking to Master Sommelier about wine, talking to Will Wilkinson about partisan polarization and the urban-rural divide, talking to psychologists like Harold Tavris about cognitive dissonance and how those things work. Scott Derrickson, who is the director of the movie Doctor Strange, I had a wonderful conversation with him where we went through the mechanics of making a blockbuster superhero movie, right? And he's also not a naturalist, he's an evangelical Christian, so we talked about the nature of reality there. I want to have a couple more, you know, discussions with him, with highly educated theists who know the theology really well, but I haven't quite arranged those yet. LW – I would love to hear that. I mean, that's…how comfortable are you venturing into questions of religion? CB – Oh, I'm totally comfortable doing it. You know, I did talk with Alan Lightman, who is also an atheist, but he is trying to rescue the sort of spiritual side of things for atheism. And I did talk to very vocal atheists like Alex Rosenberg. So I need to talk to some…I've talked to some religious believers, but I need to talk to more. LW – How have you changed through having all these conversations? CB – You know, part of the motivation was I had a long stack of books that I hadn't read and I couldn't find time to read them, and I figured if I interviewed their authors, it would force me to read them, right? And that has totally worked, by the way. Now I'm annoyed that people write such long books. I think I'm still very much learning how to be a good interviewer. I think that's a skill. I think I have good questions, but there's the give and take that is still…I think I can be better at. I want to offer something to the conversation, but not too much, right? I've had conversations where I barely talked at all, and I've had conversations where I talked half the time, and I think there's a happy medium in between there. LW – So I think I remember listening to, without mentioning names, some of your conversations where I wish you would have disagreed more. As a listener, it's more fun sometimes. CB – Well, that's a very good question because everyone has an attitude toward that. Like, some people are really there to basically give their point of view, and their guest is supposed to respond accordingly. I want to sort of get my view on the record, but I don't want to dwell on it when I'm talking to someone like David Chalmers, who I disagree with a lot. I want to say, like, here's why I disagree with you, but we're here to listen to you. I have an episode every week, and you're only on once a week, right? So I have an upcoming podcast episode with Philip Goff, who is a much more dedicated panpsychist. And so there we really get into it. I think that I probably have disagreed with him more on that episode than I ever have with another podcast guest. But that's what he wanted, so it worked very well. LW – Yeah, that kind of debate structure is beautiful when it's done right. Like, when you can detect that the intent is that you have fundamental respect for the person. And for some reason it's super fun to listen to when two really smart people are just arguing, and sometimes lose their shit a little bit, if I may say so. JL – Well, there's a fine line, because I have zero interest in bringing – I mean, maybe you implied this – I have zero interest in bringing on people for whom I don't have any intellectual respect. Like, I constantly get requests to, like, you know, bring on a flat earther or whatever, and really slap them down, or a creationist. Like, I have zero interest. I'm happy to bring on, you know, a religious person, a believer, but I want someone who's smart and can act in good faith and can talk, not a charlatan or a lunatic, right? So I will only – I will happily bring on people with whom I disagree, but only people from whom I think the audience can learn something interesting. LW – So let me ask. The idea of charlatan is an interesting idea. You might be more educated on this topic than me, but there's folks, for example, who argue various aspects of evolution, sort of try to approach and say that evolution, sort of our current theory of evolution has many holes in it, has many flaws. And they argue that, I think, like Cambridge, Cambrian explosion, which is like a huge added variability of species, doesn't make sense under our current description of evolution, theory of evolution. Sort of, if you were to have the conversation with people like that, how do you know that they're – the difference between outside the box thinkers and people who are fundamentally unscientific and even bordering on charlatans? JM – That's a great question. And the further you get away from my expertise, the harder it is for me to really judge exactly those things. And I don't have a satisfying answer for that one, because I think the example you use of someone who believes in the basic structure of natural selection but thinks that this particular thing cannot be understood in the terms of our current understanding of Darwinism, that's a perfect edge case where it's hard to tell, right? And I would try to talk to people who I do respect and who do know things, and I would have to – given that I'm a physicist, I know that physicists will sometimes be too dismissive of alternative points of view. I have to take into account that biologists can also be too dismissive of alternative points of view. So yeah, that's a tricky one. LW – Have you gotten heat yet? JM – I get heat all the time. There's always something – I mean, it's hilarious because I do have – I try very hard not to have the same topic several times in a row. I did have two climate change episodes, but they were from very different perspectives. But I like to mix it up. That's the whole point. That's why I'm having fun. And every time I do an episode, someone says, oh, the person you should really get on to talk about exactly that is this other person. I'm like, well, I did that and I don't want to do that anymore. LW – Well, I hope you keep doing it. You're inspiring millions of people with your books, with your podcast. Sean, it's an honor to talk to you. Thank you so much. JM – Thanks very much, Lex.

https://youtu.be/iNqqOLscOBY

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Jay McClelland: Neural Networks and the Emergence of Cognition | Lex Fridman Podcast #222

The following is a conversation with Jay McClelland, a cognitive scientist at Stanford and one of the seminal figures in the history of artificial intelligence, and specifically, neural networks. Having written the parallel distributed processing book with David Rommelhart, who co-authored the backpropagation paper with Jeff Hinton. In their collaborations, they've paved the way for many of the ideas at the center of the neural network based machine learning revolution of the past 15 years. To support this podcast, please check out our sponsors in the description. This is the Lex Friedman podcast, and here is my conversation with Jay McClelland. You are one of the seminal figures in the history of neural networks. At the intersection of cognitive psychology and computer science, what to you has over the decades emerged as the most beautiful aspect about neural networks, both artificial and biological? The fundamental thing I think about with neural networks is how they allow us to link biology with the mysteries of thought. When I was first entering the field myself in the late 60s, early 70s, cognitive psychology had just become a field. There was a book published in 67 called Cognitive Psychology. And the author said that the study of the nervous system was only available the nervous system was only of peripheral interest. It wasn't gonna tell us anything about the mind. And I didn't agree with that. I always felt, oh, look, I'm a physical being. From dust to dust, ashes to ashes, and somehow I emerged from that. So that's really interesting, so there was a sense with cognitive psychology that in understanding the sort of neuronal structure of things, you're not going to be able to understand the mind. And then your sense is if we study these neural networks, we might be able to get at least very close to understanding the fundamentals of the human mind. Yeah. I used to think, or I used to talk about the idea of awakening from the Cartesian dream. So Descartes thought about these things, right? He was walking in the gardens of Versailles one day, and he stepped on a stone, and a statue moved. And he walked a little further, he stepped on another stone, and another statue moved. And he, like, why did the statue move when I stepped on the stone? And he went and talked to the gardeners, and he found out that they had a hydraulic system that allowed the physical contact with the stone to cause water to flow in various directions, which caused water to flow into the statue and move the statue. And he used this as the beginnings of a theory about how animals act. And he had this notion that these little fibers that people had identified that weren't carrying the blood, you know, were these little hydraulic tubes that if you touch something, there would be pressure, and it would send a signal of pressure to the other parts of the system, and that would cause action. And so he had a mechanistic theory of animal behavior. And he thought that the human had this animal body, but that some divine something else had to have come down and been placed in him to give him the ability to think. Right? So the physical world includes the body in action, but it doesn't include thought, according to Descartes, right? Right. And so the study of physiology at that time was the study of sensory systems and motor systems and things that you could directly measure when you stimulated neurons and stuff like that. And the study of cognition was something that, you know, was tied in with abstract computer algorithms and things like that. But when I was an undergraduate, I learned about the study of cognition. But when I was an undergraduate, I learned about the physiological mechanisms. And so when I'm studying cognitive psychology as a first-year PhD student, I'm saying, wait a minute, the whole thing is biological, right? You had that intuition right away. That seemed obvious to you. Yeah. Yeah. Isn't that magical, though, that from just a little bit of biology can emerge the full beauty of the human experience? Is it, why is it so obvious to you? Well, obvious and not obvious at the same time. And I think about Darwin in this context, too, because Darwin knew very early on that none of the ideas that anybody had ever offered gave him a sense of understanding how evolution could have worked. But he wanted to figure out how it could have worked. That was his goal. And he spent a lot of time working on this idea and coming, you know, reading about things that gave him hints and thinking they were interesting but not knowing why, and drawing more and more pictures of different birds that differ slightly from each other and so on, you know. And then he figured it out. But after he figured it out, he had nightmares about it. He would dream about the complexity of the eye and the arguments that people had given about how ridiculous it was to imagine that that could have ever emerged from some sort of, you know, unguided process, right? That it hadn't been the product of design. And so, he didn't publish for a long time, in part because he was scared of his own ideas. He didn't think they could possibly be true. Yeah. But then, you know, by the time the 20th century rolls around, we all, you know, we understand that evolution, or many people understand or believe that evolution is a process of evolution. That evolution produced, you know, the entire range of animals that there are. And, you know, Descartes' idea starts to seem a little wonky after a while, right? Like, well, wait a minute. There's the apes and the chimpanzees and the bonobos and, you know, like, they're pretty smart in some ways, you know. So, what, oh, you know, somebody comes up, oh, there's a certain part of the brain that's still different. They don't, you know, there's no hippocampus in the monkey brain. It's only in the human brain. Huxley had to do a surgery in front of many, many people in the late 19th century to show to them there's actually a hippocampus in the chimpanzee's brain, you know. So, their continuity of the species is another element that, you know, contributes to this sort of, you know, idea that we are ourselves a total product of nature. And that, to me, is the magic and the mystery, how nature could actually, you know, give rise to organisms that have the capabilities that we have. So, it's interesting because even the idea of evolution is hard for me to keep all together in my mind. So, because we think of a human time scale, it's hard to imagine that, like, the development of the human eye would give me nightmares, too. Because you have to think across many, many, many generations. And it's very tempting to think about, kind of, a growth of a complicated object. And it's like, how is it possible for such a thing to be built? Because also, me, from a robotics engineering perspective, it's very hard to build these systems. How can, through an undirected process, can a complex thing be designed? It seems wrong. Yeah. So, that's absolutely right. And, you know, a slightly different career path that would have been equally interesting to me would have been to actually study the process of embryological development flowing on into brain development and the exquisite sort of laying down of pathways and so on that occurs in the brain. And I know the slightest bit about that is not my field, but there are fascinating aspects to this process that eventually result in the complexity of various brains. At least one thing in the field I think people have felt for a long time, in the study of vision, the continuity between humans and non-human animals has been second nature for a lot longer. I had this conversation with somebody who's a vision scientist. And he was saying, oh, we don't have any problem with this. You know, the monkey's visual system and the human visual system are extremely similar up to certain levels. Of course, they diverge after a while. But the visual pathway from the eye to the brain and the first few layers of cortex or cortical areas, I guess one would say, are extremely similar. Yeah, so on the cognition side is where the leap seems to happen with humans. It does seem we're kind of special. And that's a really interesting question when thinking about alien life or if there's other intelligent alien civilizations out there is how special is this leap? So one special thing seems to be the origin of life itself. However you define that, there's a gray area. And the other leap, this is very biased perspective of a human, is the origin of life itself. The origin of intelligence. And again, from an engineering perspective, it's a difficult question to ask. An important one is how difficult does that leap? How special were humans? Did a monolith come down? Did aliens bring down a monolith and some apes had to touch a monolith to get it? It's a lot like Descartes' idea, right? Exactly. But it just seems one heck of a leap. Yeah. To get to this level of intelligence. Yeah. And so Chomsky argued that some genetic fluke occurred 100,000 years ago. And just happened that some hominin predecessor of current humans had this one genetic tweak that resulted in language. Yeah. I think there's a lot of truth to the value and importance of language. But I think it comes along with the evolution of a lot of other related things related to sociality and mutual engagement with others. And establishment of, I don't know, rich mechanisms for organizing and understanding of the world which language then plugs into. Right. So language is a tool that allows you to do this kind of collective intelligence. And whatever is at the core of the thing that allows for this collective intelligence is the main thing. And it's interesting to think about that one fluke, one mutation could lead to the first crack opening of the door to human intelligence. All it takes is one. Evolution just kind of opens the door a little bit and then time and selection takes care of the rest. You know, there's so many fascinating aspects to these kinds of things. So we think of evolution as continuous, right? We think, oh, yes, okay, over 500 million years there could have been this relatively continuous changes. But that's not what anthropologists, evolutionary biologists found from the fossil record. They found hundreds of millions of years of stasis. Yeah. And then suddenly a change occurs. Well, suddenly on that scale is a million years or something or even 10 million years. But the concept of punctuated equilibrium was a very important concept in evolutionary biology. And that also feels somehow right about the stages of our mental abilities. We seem to have a certain kind of mindset at a certain age. And then at another age we look at that four-year-old and say, oh, my God, how could they have thought that way? So Piaget was known for this kind of stage theory of child development, right? And you look at it closely and suddenly those stages are so discreet and the transitions. But the difference between the four-year-old and the seven-year-old is profound. And that's another thing that's always interested me is how we, something happens over the course of several years of experience where at some point we reach the point where something like an insight or a transition or a new stage of development occurs. And these kinds of things can be understood in complex systems research. And so evolutionary biology, developmental biology, cognitive development are all things that have been approached in this kind of a way. Yeah. Just like you said, I find both fascinating those early years of human life, but also the early minutes, days from the embryonic development to how from embryos you get like the brain, that development, again, from an engineer perspective, it's fascinating. So it's not, so the early, when you deploy the brain to the human world and it gets to explore that world and learn, that's fascinating. But just like the assembly of the mechanism that is capable of learning, that's like amazing. The stuff they're doing with like brain organoids where you can build many brains and study that self-assembly of a mechanism from like the DNA material, that's like, what the heck? You have literally like biological programs that just generate a system, this mushy thing that's able to be robust and learn in a very unpredictable world and learn seemingly arbitrary things or like a very large number of things that enable survival. Yeah. Ultimately, that is a very important part of the whole process of understanding this sort of emergence of mind from brain kind of thing. And the whole thing seems to be pretty continuous. So let me step back to neural networks for another brief minute. You wrote parallel distributed processing books that explored ideas of neural networks in the 1980s together with a few folks. But the books you wrote with David Rommelhart, who is the first author on the back propagation paper with Geoff Hinton. So these are just some figures at the time that were thinking about these big ideas. What are some memorable moments of discovery and beautiful ideas from those early days? I'm going to start sort of with my own process in the mid-70s and then into the late 70s when I met Geoff Hinton and he came to San Diego and we were all together. In my time in graduate schools, I've already described to you, I had this sort of feeling of, okay, I'm really interested in human cognition, but this disembodied sort of way of thinking about it that I'm getting from the current mode of thought about it isn't working fully for me. And when I got my assistant professorship, I went to UCSD and that was in 1974. Something amazing had just happened. Dave Rommelhart had written a book together with another man named Don Norman, and the book was called Explorations in Cognition. And it was a series of chapters exploring interesting questions about cognition, but in a completely sort of abstract, non-biological kind of way. And I'm saying, gee, this is amazing. I'm coming to this. This is amazing. I'm coming to this community where people can get together and feel like they've collectively exploring ideas. And it was a book that had a lot of, I don't know, lightness to it. And Don Norman, who was the more senior figure to Rommelhart at that time who led that project, always created this spirit of playful exploration of ideas. And so I'm like, wow, this is great. But I was also still trying to get from the neurons to the cognition. And I realized at one point, I got this opportunity to go to a conference where I heard a talk by a man named James Anderson, who was an engineer, but by then a professor in a psychology department who had used linear algebra to create neural network models of perception and categorization and memory. And it just blew me out of the water that one could create a model that was simulated with neurons, not just engaged in a stepwise algorithmic process that was construed abstractly, but it was simulating remembering and recalling and recognizing the prior occurrence of a stimulus or something like that. So for me, this was a bridge between the mind and the brain. And I remember I was walking across campus one day in 1977, and I almost felt like St. Paul on the road to Damascus. I said to myself, you know, if I think about the mind in terms of a neural network, it will help me answer the questions about the mind that I'm trying to answer. And that really excited me. So I think that a lot of people were becoming excited about that. And one of those people was Jim Anderson, who I had mentioned. Another one was Steve Grossberg, who had been writing about neural networks since the 60s. And Jeff Hinton was yet another. And his PhD dissertation showed up in an applicant pool to a postdoctoral training program that Dave and Don, the two men I mentioned before, Romelhart and Norman, were administering. And Romelhart got really excited about Hinton's PhD dissertation. And so Hinton was one of the first people who came and joined this group of postdoctoral scholars that was funded by this wonderful grant that they got. Another one who is also well-known in neural network circles is Paul Smolenski. He was another one of that group. And Jeff and Jim Anderson organized a conference at UCSD where we were. And it was called Parallel Models of Associative Memory. And it brought all the people together who had been thinking about these kinds of ideas in 1979 or 1980. And this began to really resonate with some of Romelhart's own thinking, some of his reasons for wanting something other than the kinds of computation he'd been doing so far. So let me talk about Romelhart now for a minute, okay, with that context. Well, let me also just pause because he said so many interesting things before we go to Romelhart. So first of all, for people who are not familiar, neural networks are at the core of the machine learning, deep learning revolution of today. Jeffrey Hinton that we mentioned is one of the figures that were important in the history like yourself in the development of these neural networks, artificial neural networks that are then used for the machine learning application. Like I mentioned, the back propagation paper is one of the optimization mechanisms by which these networks can learn. And the word parallel is really interesting. So it's almost like synonymous from a computational perspective how you thought at the time about neural networks as parallel computation. Would that be fair to say? Well, yeah, the word parallel in this comes from the idea that each neuron is an independent computational unit, right? It gathers data from other neurons, it integrates it in a certain way and then it produces a result. And it's a very simple little computational unit, but it's autonomous in the sense that it does its thing, right? It's in a biological medium where it's getting nutrients and various chemicals from that medium. But you can think of it as almost like a little computer in and of itself. So the idea is that each, our brains have, oh, look, a hundred or hundreds, almost a billion of these little neurons, right? And they're all capable of doing their work at the same time. So it's like, instead of just a single central processor that's engaged in, you know, chug, one step after another, we have a billion of these little computational units working at the same time. So at the time, that's, I don't know, maybe you can comment, it seems to me, even still to me, quite a revolutionary way to think about computation relative to the development of theoretical computer science alongside of that, where it's very much like sequential computer. You're analyzing algorithms that are running on a single computer. You're saying, wait a minute, why don't we take a really dumb, very simple computer and just have a lot of them interconnected together? And they're all operating in their own little world and they're communicating with each other and thinking of computation that way. And from that kind of computation, trying to understand how things like certain characteristics of the human mind can emerge. That's quite a revolutionary way of thinking, I would say. Well, yes, I agree with you. And there's still this sort of sense of not sort of knowing how we kind of get all the way there, I think. And this very much remains at the core of the questions that everybody's asking about the capabilities of deep learning and all these kinds of things. But if I could just play this out a little bit, a convolutional neural network or a CNN, which many people may have heard of, is a set of... You could think of it biologically as a set of collections of neurons. Each one, each collection has maybe 10,000 neurons in it, but there's many layers. Some of these things are hundreds or even a thousand layers deep, but others are closer to the biological brain and maybe they're like 20 layers deep or something like that. So within each layer, we have thousands of neurons or tens of thousands maybe. Well, in the brain, we probably have millions in each layer, but we're getting sort of similar in a certain way. And then we think, okay, at the bottom level, there's an array of things that are like the photoreceptors in the eye. They respond to the amount of light of a certain wavelength at a certain location on the pixel array. So that's like the biological eye. And then there's several further stages going up, layers of these neuron-like units. And you go from that raw input array of pixels to the classification. You've actually built a system that could do the same kind of thing that you and I do when we open our eyes and we look around and we see there's a cup, there's a cell phone, there's a water bottle, and these systems are doing that now, right? So they are, in terms of the parallel idea that we were talking about before, they are doing this massively parallel computation in the sense that each of the neurons in each of those layers is thought of as computing its little bit of something about the input simultaneously with all the other ones in the same layer. We get to the point of abstracting that away and thinking, oh, it's just one whole vector that's being computed, one activation pattern that's computed in a single step. And that abstraction is useful, but it's still that parallel and distributed processing, right? Each one of these guys is just contributing a tiny bit to that whole thing. And that's the excitement that you felt that from these simple things you can emerge when you add these level of abstractions on it. You can start getting all the beautiful things that we think about as cognition. And so, okay, so you have this conference, I forgot the name already, but it's Parallel and Something Associated with Memory and so on. Very exciting, technical and exciting title. And you started talking about Dave Romahart. So who is this person that was so, you've spoken very highly of him. Can you tell me about him, his ideas, his mind, who he was as a human being, as a scientist? So Dave came from a little tiny town in Western South Dakota. And his mother was the librarian and his father was the editor of the newspaper. I know one of his brothers pretty well. They grew up, there were four brothers, and they grew up together. And their father encouraged them to compete with each other a lot. They competed in sports and they competed in mind games. I don't know, things like Sudoku and chess and various things like that. And Dave was a standout undergraduate. He went at a younger age than most people do to college at the University of South Dakota and majored in mathematics. And I don't know how he got interested in psychology, but he applied to the mathematical psychology program at Stanford and was accepted as a PhD student to study mathematical psychology at Stanford. So mathematical psychology is the use of mathematics to model mental processes. So something that I think these days might be called cognitive modeling, that whole space. Yeah, it's mathematical in the sense that you say, if this is true and that is true, then I can derive that this should follow. And so you say, these are my stipulations about the fundamental principles and this is my prediction about behavior. And it's all done with equations. It's not done with a computer simulation. So you solve the equation and that tells you what the probability that the subject will be correct on the seventh trial of the experiment is or something like that. So it's a use of mathematics to descriptively characterize aspects of behavior. And Stanford at that time was the place where there were several really, really strong mathematical thinkers who were also connected with three or four others around the country who brought a lot of really exciting ideas onto the table. And it was a very, very prestigious part of the field of psychology at that time. So Rumelhart comes into this. He was a very strong student within that program. And he got this job at this brand new university in San Diego in 1967 where he's one of the first assistant professors in the Department of Psychology at UCSD. So I got there in 74, seven years later, and Rumelhart at that time was still doing mathematical modeling, but he had gotten interested in cognition. He'd gotten interested in understanding, and understanding, I think, remains... What does it mean to understand anyway? It's an interesting sort of curious, like, how would we know if we really understood something? But he was interested in building machines that would hear a couple of sentences and have an insight about what was going on. So for example, one of his favorite things at that time was, Margie was sitting on the front step when she heard the familiar jingle of the good humor man. She remembered her birthday money and ran into the house. What is Margie doing? Why? Well, there's a couple of ideas you could have, but the most natural one is that the good humor man brings ice cream, she likes ice cream, she knows she needs money to buy ice cream, so she's going to run into the house and get her money so she can buy herself an ice cream. It's a huge amount of inference that has to happen to get those things to link up with each other. And he was interested in how the hell that could happen. And he was trying to build good old fashioned AI style models of representation of language and content of things like has money. So like formal logic and knowledge bases, like that kind of stuff. So he was integrating that with his thinking about cognition. The mechanism is cognition, how can they mechanistically be applied to build these knowledge, to actually build something that looks like a web of knowledge and thereby from there emerges something like understanding, whatever the heck that is. Yeah. He was grappling, this was something that they grappled with at the end of that book that I was describing, Explorations in Cognition. But he was realizing that the paradigm of good old fashioned AI wasn't giving him the answers to these questions. By the way, that's called good old fashioned AI now. It wasn't called that at the time. Well, it was. It was beginning to be called that. Oh, because it was from the 60s. Yeah, yeah. By the late 70s, it was kind of old fashioned and it hadn't really panned out. People were beginning to recognize that. And Rumelhart was like, yeah, he's part of the recognition that this wasn't all working. Anyway, so he started thinking in terms of the idea that we needed systems that allowed us to integrate multiple simultaneous constraints in a way that would be mutually influencing each other. So he wrote a paper that just really, first time I read it, I said, oh, well, yeah, but is this important? But after a while, it just got under my skin. And it was called an Interactive Model of Reading. And in this paper, he laid out the idea that every aspect of our interpretation of what's coming off the page when we read at every level of analysis you can think of actually depends on all the other levels of analysis. So what are the actual pixels making up each letter? And what do those pixels signify about which letters they are? And what do those letters tell us about what words are there? And what do those words tell us about what ideas the author is trying to convey? And so he had this model where we have these little tiny elements that represent each of the pixels of each of the letters, and then other ones that represent the line segments in them, and other ones that represent the letters, and other ones that represent the words. And at that time, his idea was there's this set of experts. There's an expert about how to construct a line out of pixels, and another expert about which sets of lines go together to make which letters, and another one about which letters go together to make which words, and another one about what the meanings of the words are, and another one about how the meanings fit together, and things like that. And all these experts are looking at this data, and they're updating hypotheses at other levels. So the word expert can tell the letter expert, oh, I think there should be a T there because I think there should be a word the here. And the bottom-up sort of feature-to-letter expert can say, I think there should be a T there too. And if they agree, then you see a T, right? And so there's a top-down, bottom-up interactive process. And it's going on at all layers simultaneously. So everything can filter all the way down from the top as well as all the way up from the bottom. And it's a completely interactive, bidirectional, parallel distributed process. That is somehow because of the abstractions, it's hierarchical. So there's different layers of responsibilities, different levels of responsibilities. First of all, it's fascinating to think about it in this kind of mechanistic way. So not thinking purely from the structure of a neural network or something like a neural network, but thinking about these little guys that work on letters and then the letters become words and words become sentences. And that's a very interesting hypothesis that from that kind of hierarchical structure can emerge understanding. Yeah. So but the thing is, though, I want to just sort of relate this to earlier part of the conversation. When Romulhart was first thinking about it, there were these experts on the side, one for the features and one for the letters and one for how the letters make the words and so on. And they would each be working sort of evaluating various propositions about, you know, is this combination of features here going to be one that looks like the letter T and so on? And what he realized kind of after reading Hinton's dissertation and hearing about Jim Anderson's linear algebra based neural network models that I was telling you about before was that he could replace those experts with neuron like processing units, which just would have their connection weights that would do this job. So there so what ended up happening was that Romulhart and I got together and we created a model called the interactive activation model of letter perception, which is takes these little pixel level inputs, constructs line segment features, letters and words. But now we built it out of a set of neuron like processing units that are just connected to each other with connection weights. So the unit for the word time has a connection to the unit for the letter T in the first position and the letter I in the second position, so on. And because these connections are bidirectional, if you have prior knowledge that it might be the word time that starts to prime the feature, the letters and the features. And if you don't, then it has to start bottom up. But the directionality just depends on where the information comes in first. And if you have context together with features at the same time, they can convergently result in an emergent perception. And that was the piece of work that we did together that sort of got us both completely convinced that this neural network way of thinking was going to be able to actually address the questions that we were interested in as cognitive psychologists. So the algorithmic side, the optimization side, those are all details. When you first start, the idea that you can get far with this kind of way of thinking, that in itself is a profound idea. Do you like the term connectionism to describe this kind of set of ideas? I think it's useful. It highlights the notion that the knowledge that the system exploits is in the connections between the units. There isn't a separate dictionary. There's just the connections between the units. So I already sort of laid that on the table with the connections from the letter units to the unit for the word time. The unit for the word time isn't a unit for the word time for any other reason than it's got the connections to the letters that make up the word time. Those are the units on the input that excite it when it's excited that it in a sense represents in the system that there's support for the hypothesis that the word time is present in the input. But it's not, the word time isn't written anywhere inside the model. It's only written there in the picture we drew of the model to say that's the unit for the word time. And if somebody wants to tell me, well, how do you spell that word? You have to use the connections from that out to then get those letters, for example. That's a counterintuitive idea where humans want to think in this logic way. This idea of connectionism, it's weird. It's weird that this is how it all works. Yeah. But let's go back to that CNN, right? That CNN with all those layers of neuron-like processing units that we were talking about before, it's going to come out and say, this is a cat, that's a dog. But it has no idea why it said that. It's just got all these connections between all these layers of neurons, like from the very first layer to the, whatever these layers are, they just get numbered after a while because they somehow further in you go, the more abstract the features are, but it's a graded and continuous process of abstraction anyway. It goes from very local, very specific to much more global, but it's still another pattern of activation over an array of units. And then at the output side, it says it's a cat or it's a dog. And when I open my eyes and say, oh, that's Lex, or, oh, there's my own dog, and I recognize my dog, which is a member of the same species as many other dogs, but I know this one because of some slightly unique characteristics, I don't know how to describe what it is that makes me know that I'm looking at Lex or at my particular dog, right? Or even that I'm looking at a particular brand of car. I could say a few words about it, but if I wrote you a paragraph about the car, you would have trouble figuring out which car is he talking about, right? So the idea that we have propositional knowledge of what it is that allows us to recognize that this is an actual instance of this particular natural kind has always been something that never worked, right? You couldn't ever write down a set of propositions for visual recognition. And so in that space, it's sort of always seemed very natural that something more implicit, you know, you don't have access to what the details of the computation were in between, you just get the result. So that's the other part of connectionism. You cannot, you don't read the contents of the connections. The connections only cause outputs to occur based on inputs. Yeah, and for us that like final layer or some particular layer is very important. The one that tells us that it's our dog or like it's a cat or a dog, but you know, each layer is probably equally as important in the grand scheme of things. Like there's no reason why the cat versus dog is more important than the lower level activations. It doesn't really matter. I mean, all of it is just this beautiful stacking on top of each other. And we humans live in this particular layers for us. For us, it's useful to survive, to use those cat versus dog, predator versus prey, all those kinds of things. It's fascinating that it's all continuous. But then you then ask, you know, the history of artificial intelligence, you ask, are we able to introspect and convert the very things that allow us to tell the difference between cat and dog into logic, into formal logic? That's been the dream. I would say that's still part of the dream of symbolic AI. And I've recently talked to Doug Leonard, who created Psych. And that's a project that lasted for many decades and still carries a sort of dream in it. Right? But we still don't know the answer, right? It seems like connectionism is really powerful, but it also seems like there's this building of knowledge. And so how do you square those two? Like, do you think the connections can contain the depth of human knowledge and the depth of what Dave Romohart was thinking about of understanding? Well, that remains the $64 question. And I- With inflation, that number's higher. $64,000. Maybe it's the $64 billion question now. I think that from the emergentist side, which I place myself on, so I used to sometimes tell people I was a radical eliminative connectionist because I didn't want them to think that I wanted to build anything into the machine. But I don't like the word eliminative anymore because it makes it seem like it's wrong to think that there is this emergent level of understanding. And I disagree with that. So I think I would call myself a radical emergentist connectionist rather than eliminative connectionist, right? Because I want to acknowledge that these higher level kinds of aspects of our cognition are real but they don't exist as such. And there was an example that Doug Hofstadter used to use that I thought was helpful in this respect, just the idea that we can think about sand dunes as entities and talk about how many there are even. But we also know that a sand dune is a very fluid thing. It's a pile of sand that is capable of moving around under the wind and reforming itself in somewhat different ways. And if we think about our thoughts as like sand dunes, as being things that emerge from just the way all the lower level elements work together and are constrained by external forces, then we can say, yes, they exist as such. But we shouldn't treat them as completely monolithic entities that we can understand without understanding all of the stuff that allows them to change in the ways that they do. And that's where I think the connectionist feeds into the cognitive. It's like, OK, so if the substrate is parallel distributed connectionist, then it doesn't mean that the contents of thought isn't abstract and symbolic. But it's more fluid maybe than is easier to capture with a set of logical expressions. Yeah, that's a heck of a sort of thing to put at the top of a resume, radical emerginist connectionist. So there is, just like you said, a beautiful dance between that, between the machinery of intelligence, like the neural network side of it, and the stuff that emerges. I mean, the stuff that emerges seems to be, I don't know what that is. It seems like maybe all of reality is emergent. What I think about, this is made most distinctly rich to me when I look at cellular automata, look at game of life, that from very, very simple things, very rich, complex things emerge that start looking very quickly like organisms, that you forget how the actual thing operates. They start looking like they're moving around, they're eating each other, some of them are generating offspring. You forget very quickly. And it seems like maybe it's something about the human mind that wants to operate in some layer of the emergent and forget about the mechanism of how that emergence happens. So just like you are in your radicalness, also it seems unfair to eliminate the magic of that emergent. The fact that that emergent is real. Yeah, no, I agree. That's why I got rid of eliminative, right? Eliminative, yeah. Because it seemed like that was trying to say that it's all completely like- An illusion of some kind. Who knows whether there aren't some illusory characteristics there. And I think that philosophically, many people have confronted that possibility over time. But it's still important to accept it as magic, right? So I think of Fellini in this context, I think of others who have appreciated the role of magic, of actual trickery in creating illusions that move us. And Plato was onto this too. It's like somehow or other these shadows give rise to something much deeper than that. So we won't try to figure out what it is, we'll just accept it as given that that occurs. But he was still onto the magic of it. Yeah, yeah. We won't try to really, really, really deeply understand how it works. We just enjoy the fact that it's kind of fun. Okay, but you worked closely with Dave Rommelhart. He passed away as a human being. What do you remember about him? Do you miss the guy? Absolutely. You know, he passed away 15-ish years ago now, and his demise was actually one of the most poignant and relevant tragedies relevant to our conversation. He started to undergo a progressive neurological condition that isn't fully understood. That is to say, his particular course isn't fully understood because brain scans weren't done at certain stages and no autopsy was done or anything like that, the wishes of the family. So we don't know as much about the underlying pathology as we might. But I had begun to get interested in this neurological condition that might have been the very one that he was succumbing to as my own efforts to understand another aspect of this mystery that we've been discussing while he was beginning to get progressively more and more affected. So I'm going to talk about the disorder and not about Rommelhart for a second, okay? The disorder is something my colleagues and collaborators have chosen to call semantic dementia. So it's a specific form of loss of mind related to meaning, semantic dementia. And it's progressive in the sense that the patient loses the ability to appreciate the meaning of the experiences that they have, either from touch, from sight, from sound, from language. They, I hear sounds, but I don't know what they mean kind of thing. So as this illness progresses, it starts with the patient being unable to differentiate similar breeds of dog or remember the lower frequency unfamiliar categories that they used to be able to remember. But as it progresses, it becomes more and more striking and the patient loses the ability to recognize things like pigs and goats and sheep and calls all middle-sized animals dogs and all can't recognize rabbits and rodents anymore. They call all the little ones cats and they can't recognize hippopotamuses and cows anymore. They call them all horses, you know? So there was this one patient who went through this progression where at a certain point, any four-legged animal, he would call it either a horse or a dog or a cat. And if it was big, he would tend to call it a horse. If it was small, he'd tend to call it a cat. Middle-sized ones, he called dogs. This is just a part of the syndrome though. The patient loses the ability to relate concepts to each other. So my collaborator in this work, Carolyn Patterson, developed a test called the pyramids and palm trees test. So you give the patient a picture of pyramids and they have a choice. Which goes with the pyramids? Palm trees or pine trees? And she showed that this wasn't just a matter of language because the patient's loss of this ability shows up whether you present the material with words or with pictures. The pictures, they can't put the pictures together with each other properly anymore. They can't relate the pictures to the words either. They can't do word picture matching. But they've lost the conceptual grounding from either modality of input. And so that's why it's called semantic dementia. The very semantics is disintegrating. And we understand this in terms of our idea that distributed representation, a pattern of activation represents the concepts. Similarly similar ones, as you degrade them, you lose the differences. So the difference between the dog and the goat is no longer part of the pattern anymore. And since dog is really familiar, that's the thing that remains. And we understand that in the way the models work and learn. But Rommel-Hart underwent this condition. So on the one hand, it's a fascinating aspect of parallel distributed processing to me. And it reveals this sort of texture of distributed representation in a very nice way, I've always felt. But at the same time, it was extremely poignant because this is exactly the condition that Rommel-Hart was undergoing. And there was a period of time when he was this man who had been the most focused, goal-directed, competitive, thoughtful person who was willing to work for years to solve a hard problem. And he starts to disappear. And there was a period of time when it was hard for any of us to really appreciate that he was sort of, in some sense, not fully there anymore. Do you know if he was able to introspect the solution of the understanding mind? This is one of the big scientists that thinks about this. Was he able to look at himself and understand the fading mind? We can contrast Hawking and Rommel-Hart in this way. And I like to do that to honor Rommel-Hart because I think Rommel-Hart is sort of like the Hawking of cognitive science to me in some ways. Both of them suffered from a degenerative condition. In Hawking's case, it affected the motor system. In Rommel-Hart's case, it's affecting the semantics, and not just the pure object semantics, but maybe the self semantics as well. And we don't understand that. Concepts broadly. So I would say he didn't, and this was part of what from the outside was a profound tragedy. But on the other hand, at some level, he sort of did because there was a period of time when it finally was realized that he had really become profoundly impaired. This was clearly a biological condition, and it wasn't just like he was distracted that day or something like that. So he retired from his professorship at Stanford, and he lived with his brother for a couple years, and then he moved into a facility for people with cognitive impairments, one that many elderly people end up in when they have cognitive impairments. And I would spend time with him during that period. This was in the late 90s, around 2000 even. And we would go bowling, and he could still bowl. And after bowling, I took him to lunch, and I said, where would you like to go? You want to go to Wendy's? And he said, nah. And I said, okay, well, where do you want to go? And he just pointed. He said, turn here. So he still had a certain amount of spatial cognition, and he could get me to the restaurant. And then when we got to the restaurant, I said, what do you want to order? And he couldn't come up with any of the words, but he knew where on the menu the thing was that he wanted. That's so fascinating. And he couldn't say what it was, but he knew that that's what he wanted to eat. And so it's like it isn't monolithic at all. Our cognition is, first of all, graded in certain kinds of ways, but also multipartite. There's many elements to it, and certain sort of partial competencies still exist in the absence of other aspects of these competencies. So this is what always fascinated me about what used to be called cognitive neuropsychology, the effects of brain damage on cognition. But in particular, this gradual disintegration part. I'm a big believer that the loss of a human being that you value is as powerful as first falling in love with that human being. I think it's all a celebration of the human being. So the disintegration itself, too, is a celebration in a way. Yeah, yeah. But just to say something more about the scientist and the backpropagation idea that you mentioned. So in 1982, Hinton had been there as a postdoc and organized that conference. He'd actually gone away and gotten an assistant professorship, and then there was this opportunity to bring him back. So Jeff Hinton was back on a sabbatical. San Diego. In San Diego. And Rumelhart and I had decided we wanted to do this. We thought it was really exciting. And the papers on the interactive activation model that I was telling you about had just been published. And we both saw a huge potential for this work. And Jeff was there. And so the three of us started a research group, which we called the PDP Research Group. And several other people came. Francis Crick, who was at the Salk Institute, heard about it from Jeff, because Jeff was known among Brits to be brilliant, and Francis was well-connected with his British friends. So Francis Crick came. That's a heck of a group of people. Wow. Okay. And several, as Paul Spolensky was one of the other postdocs, he was still there as a postdoc, and a few other people. But anyway, Jeff talked to us about learning and how we should think about how learning occurs in a neural network. And he said, the problem with the way you guys have been approaching this is that you've been looking for inspiration from biology to tell you what the rules should be for how the synapses should change the strengths of their connections, how the connections should form. He said, that's the wrong way to go about it. What you should do is you should think in terms of how you can adjust connection weights to solve a problem. So you define your problem, and then you figure out how the adjustment of the connection weights will solve the problem. And Rommelhart heard that and said to himself, okay, so I'm going to start thinking about it that way. I'm going to essentially imagine that I have some objective function, some goal of the computation. I want my machine to correctly classify all of these images. And I can score that. I can measure how well they're doing on each image, and I get some measure of error or loss, it's typically called in deep learning. And I'm going to figure out how to adjust the connection weights so as to minimize my loss or reduce the error. And that's called gradient descent. And engineers were already familiar with the concept of gradient descent. And in fact, there was an algorithm called the Delta Rule that had been invented by a professor in the electrical engineering department at Stanford, Bernie Widrow and a collaborator named Hoff. I never met him. So gradient descent in continuous neural networks with multiple neuron-like processing units was already understood for a single layer of connection weights. We have some inputs over a set of neurons. We want the output to produce a certain pattern. We can define the difference between our target and what the neural network is producing, and we can figure out how to change the connection weights to reduce that error. So what Romalhard did was to generalize that so as to be able to change the connections from earlier layers of units to the ones at a hidden layer between the input and the output. And so he first called the algorithm the generalized Delta Rule because it's just an extension of the gradient descent idea. And interestingly enough, Hinton was thinking that this wasn't going to work very well. So Hinton had his own alternative algorithm at the time based on the concept of the Boltzmann machine that he was pursuing. So the paper on the Boltzmann machine came out in, learning in Boltzmann machines came out in 1985. But it turned out that backprop worked better than the Boltzmann machine learning algorithm. So this generalized Delta algorithm ended up being called backpropagation, as you say, backprop. Yeah. And probably that name is opaque to many. What does that mean? What it meant was that in order to figure out what the changes you needed to make to the connections from the input to the hidden layer, you had to backpropagate the error signals from the output layer through the connections from the hidden layer to the output to get the signals that would be the error signals for the hidden layer. And that's how Rumelhart formulated it. It was like, well, we know what the error signals are at the output layer. Let's see if we can get a signal at the hidden layer that tells each hidden unit what its error signal is, essentially. So it's backpropagating through the connections from the hidden to the output to get the signals to tell the hidden units how to change their weights from the input. And that's why it's called backprop. Yeah. But so it came from Hinton having introduced the concept of define your objective function, figure out how to take the derivative so that you can adjust the connections so that they make progress towards your goal. So stop thinking about biology for a second and let's start to think about optimization and computation a little bit more. So what about Jeff Hinton? You've gotten a chance to work with him in that little... The set of people involved there is quite incredible. The small set of people under the PDP flag, it's just given the amount of impact those ideas have had over the years, it's kind of incredible to think about. But you know, just like you said, like yourself, Jeffrey Hinton is seen as one of the, not just like a seminal figure in AI, but just a brilliant person. Just like the horsepower of the mind is pretty high up there for him because he's just a great thinker. So what kind of ideas have you learned from him? Have you influenced each other on? Have you debated over? What stands out to you in the full space of ideas here at the intersection of computation and cognition? Well, so Jeff has said many things to me that had a profound impact on my thinking. And he's written several articles which were way ahead of their time. He had two papers in 1981, just to give one example, one of which was essentially the idea of transformers. And another of which was a early paper on semantic cognition, which inspired him and Rommelhart and me throughout the 80s and still, I think, sort of grounds my own thinking about the semantic aspects of cognition. He also, in a small paper that was never published that he wrote in 1977, before he had the paper, he actually arrived at UCSD, or maybe a couple of years even before that, I don't know, when he was a PhD student, he described how a neural network could do recursive computation. And it was a very clever idea that he's continued to explore over time, which was sort of the idea that when you call a subroutine, you need to save the state that you had when you called it so you can get back to where you were when you're finished with the subroutine. And the idea was that you would save the state of the calling routine by making fast changes to connection weights, and then when you finished with the subroutine call, those fast changes in the connection weights would allow you to go back to where you had been before and reinstate the previous context so that you could continue on with the top level of the computation. Anyway, that was part of the idea. And I always thought, okay, he had extremely creative ideas that were quite a lot ahead of his time, and many of them in the 1970s and early 1980s. So another thing about Geoff Hinton's way of thinking, which has profoundly influenced my effort to understand human mathematical cognition, is that he doesn't write too many equations. And people tell stories like, oh, in the Hinton lab meetings, you don't get up at the board and write equations like you do in everybody else's machine learning lab. What you do is you draw a picture. And he explains aspects of the way deep learning works by putting his hands together and showing you the shape of a ravine and using that as a geometrical metaphor for what's happening as this gradient descent process. You're coming down the wall of a ravine. If you take too big a jump, you're going to jump to the other side. And so that's why we have to turn down the learning rate, for example. And it speaks to me of the fundamentally intuitive character of deep insight together with a commitment to really understanding in a way that's absolutely, ultimately explicit and clear but also intuitive. Yeah, there's certain people like that. Here's an example, some kind of weird mix of visual and intuitive and all those kinds of things. Feynman is another example, different style of thinking but very unique. And when you're around those people, for me in the engineering realm, there's a guy named Jim Keller who's a chip designer, engineer. Every time I talk to him, it doesn't matter what we're talking about. Just having experienced that unique way of thinking transforms you and makes your work much better. And that's the magic. You look at Daniel Kahneman, you look at the great collaborations throughout the history of science. That's the magic of that. It's not always the exact ideas that you talk about, but it's the process of generating those ideas, being around that, spending time with that human being, you can come up with some brilliant work, especially when it's cross-disciplinary as it was a little bit in your case with Jeff. Yeah. Yeah. Jeff is a descendant of the logician Boole, he comes from a long line of English academics. And together with the deeply intuitive thinking ability that he has, he also has, it's been clear. And he's described this to me, and I think he's mentioned it from time to time in other interviews that he's had with people. He's wanted to be able to think of himself as contributing to the understanding of reasoning itself, not just human reasoning. Boole is about logic, it's about what can we conclude from what else and how do we formalize that. And as a computer scientist, logician, philosopher, the goal is to understand how we derive truths from givens and things like this. And the work that Jeff was doing in the early to mid 80s on something called the Bolton Machine was his way of connecting with that Boolean tradition and bringing it into the more continuous probabilistic graded constraint satisfaction realm. And it was beautiful, a set of ideas linked with theoretical physics as well as with logic. And it's always been, I mean, I've always been inspired by the Bolton Machine too. It's like, well, if the neurons are probabilistic rather than deterministic in their computations, then maybe this somehow is part of the serendipity or adventitiousness of the moment of insight. It might not have occurred at that particular instant, it might be sort of partially the result of a stochastic process. And that too is part of the magic of the emergence of some of these things. Well, you're right with the Boolean lineage and the dream of computer science is somehow, I mean, I certainly think of humans this way, that humans are one particular manifestation of intelligence, that there's something bigger going on and you're hoping to figure that out. The mechanisms of intelligence, the mechanisms of cognition are much bigger than just humans. So, I started using the phrase computational intelligence at some point as to characterize the field that I thought people like Geoff Hinton and many of the people I know at DeepMind are working in and where I feel like I'm a kind of a human-oriented computational intelligence researcher in that I'm actually kind of interested in the human solution. But at the same time, I feel like that's where a huge amount of the excitement of deep learning actually lies is in the idea that we may be able to even go beyond what we can achieve with our own nervous systems when we build computational intelligences that are not limited in the ways that we are by our own biology. Perhaps allowing us to scale the very mechanisms of human intelligence, just increase its power through scale. Yes. And I think that that, you know, obviously that's being played out massively at Google Brain, at OpenAI, and to some extent at DeepMind as well. I guess I shouldn't say to some extent. The massive scale of the computations that are used to succeed at games like Go or to solve the protein folding problems that they've been solving and so on. Still not as many synapses and neurons as the human brain, so we still got, we're still beating them on that. We humans are beating the AIs, but they're catching up pretty quickly. You write about modeling of mathematical cognition, so let me first ask about mathematics in general. There's a paper titled Parallel Distributed Processing Approach to Mathematical Cognition, where in the introduction there's some beautiful discussion of mathematics. And you reference there Tristan Needham, who criticizes a narrow formal view of mathematics by liking the studying of mathematics as symbol manipulation to studying music without ever hearing a note. So from that perspective, what do you think is mathematics? What is this world of mathematics like? Well I think of mathematics as a set of tools for exploring idealized worlds that often turn out to be extremely relevant to the real world, but need not. But they're worlds in which objects exist with idealized properties and in which the relationships among them can be characterized with precision so as to allow the implications of certain facts to then allow you to derive other facts with certainty. So if you have two triangles and you know that there is an angle in the first one that has the same measure as an angle in the second one, and you know that the lengths of the sides adjacent to that angle in each of the two triangles, the corresponding sides adjacent to that angle, also have the same measure, then you can then conclude that the triangles are congruent. That is to say they have all of their properties in common. And that is something about triangles. It's not a matter of formulas. These are idealized objects. In fact, we build bridges out of triangles and we understand how to measure the height of something we can't climb by extending these ideas about triangles a little further. And all of the ability to get a tiny speck of matter launched from the planet Earth to intersect with some tiny, tiny little body way out in way beyond Pluto somewhere at exactly a predicted time and date is something that depends on these ideas. And it's actually happening in the real physical world that these ideas make contact with it in those kinds of instances. But there are these idealized objects, these triangles or these distances or these points, whatever they are, that allow for this set of tools to be created that then gives human beings this incredible leverage that they didn't have without these concepts. And I think this is actually already true when we think about just the natural numbers. I always like to include zero, so I'm gonna say the non-negative integers, but that's a place where some people prefer not to include zero, but... We like zero here, natural numbers, zero, one, two, three, four, five, six, seven, and so on. Yeah. And because they give you the ability to be exact about how many sheep you have. I sent you out this morning, there were 23 sheep. You came back with only 22. What happened? Right? I'm talking about the problem of physics, how many sheep you have. Yeah. It's a fundamental problem of human society that you damn well better bring back the same number of sheep as you started with. And it allows commerce, it allows contracts, it allows the establishment of records and so on to have systems that allow these things to be notated. But they have an inherent aboutness to them that's one at the same time abstract and idealized and generalizable while on the other hand, potentially very, very grounded and concrete. And one of the things that makes for the incredible achievements of the human mind is the fact that humans invented these idealized systems that leverage the power of human thought in such a way as to allow all this kind of thing to happen. And so that's what mathematics to me is the development of systems for thinking about the properties and relations among sets of idealized objects. And the mathematical notation system that we unfortunately focus way too much on is just our way of expressing propositions about these properties. Right. It's just like we're talking with Chomsky in language. It's the thing we've invented for the communication of those ideas. They're not necessarily the deep representation of those ideas. So what's a good way to model such powerful mathematical reasoning, would you say? What are some ideas you have for capturing this in a model? The insights that human mathematicians have had is a combination of the kind of the intuitive kind of connectionist like knowledge that makes it so that something is just like obviously true so that you don't have to think about why it's true. That then makes it possible to then take the next step and ponder and reason and figure out something that you previously didn't have that intuition about. It then ultimately becomes a part of the intuition that the next generation of mathematical thinkers have to ground their own thinking on so that they can extend the ideas even further. I came across this quotation from Henri Poincaré while I was walking in the woods with my wife in a state park in Northern California late last summer. And what it said on the bench was, it is by logic that we prove but by intuition that we discover. What for me the essence of the project is to understand how to bring the intuitive connectionist resources to bear on letting the intuitive discovery arise from engagement in thinking with this formal system. So I think of the ability of somebody like Hinton or Newton or Einstein or Rommelhart or Poincaré to Archimedes, this is another example. Eventually a flash of insight occurs, it's like the constellation of all of these simultaneous constraints that somehow or other causes the mind to settle into a novel state that it never did before and give rise to a new idea that then you can say, okay, well now how can I prove this? How do I write down the steps of that theorem that allow me to make it rigorous and certain? And so I feel like the kinds of things that we're beginning to see deep learning systems do of their own accord kind of gives me this feeling of, I don't know, hope or encouragement that ultimately it'll all happen. So in particular as many people now have become really interested in thinking about neural networks that have been trained with massive amounts of text can be given a prompt and they can then sort of generate some really interesting, fanciful, creative story from that prompt. And there's kind of like a sense that they've somehow synthesized something like novel out of the, you know, all of the particulars of all of the billions and billions of experiences that went into the training data that gives rise to something like this sort of intuitive sense of what would be a fun and interesting little story to tell or something like that. It just sort of wells up out of the letting the thing play out its own imagining of what somebody might say given this prompt as a input to get it to start to generate its own thoughts. And to me that sort of represents the potential of capturing the intuitive side of this. And there's other examples, I don't know if you find them as captivating as, you know, on the Deep Mind side with AlphaZero, if you study chess, the kind of solutions that has come up in terms of chess, it is, there's novel ideas there. It feels very, like there's brilliant moments of insight. And the mechanism they use, if you think of search as maybe more towards good old-fashioned AI and then there's the connectionist, you know, network that has the intuition of looking at a board, looking at a set of patterns and saying, how good is this set of positions? And the next few positions, how good are those? And that's it. That's just an intuition. Chess players have this, an understanding positionally, tactically, how good the situation is, how can it be improved without doing this full, like deep search. And then maybe doing a little bit of what human chess players call calculation, which is the search, taking a particular set of steps down the line to see how they unroll. But there is moments of genius in those systems too. So that's another hopeful illustration that from neural networks can emerge this novel creation of an idea. Yes. And I think that, you know, I think Demis Hassabis is, you know, he's spoken about those things. I heard him describe a move that was made in one of the Go matches against Lee Sedol in a very similar way. And it caused me to become really excited to kind of collaborate with some of those guys at DeepMind. So I think though that what I like to really emphasize here is one part of what I like to emphasize about mathematical cognition at least is that philosophers and logicians going back three or even a little more than 3000 years ago began to develop these formal systems and gradually the whole idea about thinking formally got constructed. And you know, it's preceded Euclid, certainly present in the work of Thales and others. And I'm not the world's leading expert in all the details of that history, but Euclid's elements were the kind of the touch point of a coherent document that sort of laid out this idea of an actual formal system within which these objects were characterized and the system of inference that allowed new truths to be derived from others was sort of like established as a paradigm. And what I find interesting is the idea that the ability to become a person who is capable of thinking in this abstract formal way is a result of the same kind of immersion in experience thinking in that way that we now begin to think of our understanding of language as being. So we immerse ourselves in a particular language, in a particular world of objects and their relationships and we learn to talk about that and we develop intuitive understanding of the real world. In a similar way, we can think that what academia has created for us, what those early philosophers and their academies in Athens and Alexandria and other places allowed was the development of these schools of thought, modes of thought that then become deeply ingrained and it becomes what it is that makes it so that somebody like Jerry Fodor would think that systematic thought is the essential characteristic of the human mind as opposed to a derived, an acquired characteristic that results from acculturation in a certain mode that's been invented by humans. Would you say it's more fundamental than like language? If we start dancing, if we bring Chomsky back into the conversation, first of all, is it unfair to draw a line between mathematical cognition and language, linguistic cognition? I think that's a very interesting question and I think it's one of the ones that I'm actually very interested in right now. I think the answer is, in important ways, it is important to draw that line, but then to come back and look at it again and see some of the subtleties and interesting aspects of the difference. If we think about Chomsky himself, he was born into an academic family. His father was a professor of rabbinical studies at a small rabbinical college in Philadelphia. He was deeply enculturated in a culture of thought and reason and brought to the effort to understand natural language this profound engagement with these formal systems. I think that there was tremendous power in that and that Chomsky had some amazing insights into the structure of natural language, but that, and I'm going to use the word but there, the actual intuitive knowledge of these things only goes so far and does not go as far as it does in people like Chomsky himself. This was something that was discovered in the PhD dissertation of Lila Gleitman, who was actually trained in the same linguistics department with Chomsky. What Lila discovered was that the intuitions that linguists had about even the meaning of a phrase, not just about its grammar, but about what they thought a phrase must mean were very different from the intuitions of an ordinary person who wasn't a formally trained thinker. It recently has become much more salient. I happen to have learned about this when I myself was a PhD student at the University of Pennsylvania, but I never knew how to put it together with all of my other thinking about these things. I actually currently have the hypothesis that formally trained linguists and other formally trained academics, whether it be linguistics, philosophy, cognitive science, computer science, machine learning, mathematics, have a mode of engagement with experience that is intuitively deeply structured to be more organized around the systematicity and ability to be conformant with the principles of a system than is actually true of the natural human mind without that immersion. That's fascinating. So the different fields and approaches with which you start to study the mind actually take you away from the natural operation of the mind. So it makes it very difficult for you to be somebody who introspects. Yes. And this is where things about human belief and so-called knowledge that we consider private, not our business to manipulate in others. We are not entitled to tell somebody else what to believe about certain kinds of things. What are those beliefs? Well, they are the product of this sort of immersion and enculturation. That is what I believe. And that's limiting. It's something to be aware of. Does that limit you from having a good model of cognition? It can. So when you look at mathematical or linguistics, what is that line then? So is Chomsky unable to sneak up to the full picture of cognition? Are you, when you're focusing on mathematical thinking, are you also unable to do so? I think you're right. I think that's a great way of characterizing it. And I also think that it's related to the concept of beginner's mind and another concept called the expert blind spot. So the expert blind spot is much more prosaic seeming than this point that you were just making. But it's something that plagues experts when they try to communicate their understanding to non-experts. And that is that things are self-evident to them that they can't begin to even think about how they could explain it to somebody else. It's just so patently obvious that it must be true. And when Kronacker said, God made the natural numbers, all else is the work of man, he was expressing that intuition that somehow or other, the basic fundamentals of discrete quantities being countable and innumerable and indefinite in number was not something that had to be discovered. But he was wrong. It turns out that many cognitive scientists agreed with him for a time. There was a long period of time where the natural numbers were considered to be a part of the innate endowment of core knowledge or to use the kind of phrases that Spelke and Carey used to talk about what they believe are the innate primitives of the human mind. And they no longer believe that. It's actually been more or less accepted by almost everyone that the natural numbers are actually a cultural construction. And it's so interesting to go back and study those few people who still exist who don't have those systems. So this is just an example to me where a certain mode of thinking about language itself or a certain mode of thinking about geometry and those kinds of relations. So it becomes so second nature that you don't know what it is that you need to teach. And in fact, we don't really teach it all that explicitly anyway. You take a math class, the professor sort of teaches it to you the way they understand it. Some of the students in the class sort of like, they get it. They start to get the way of thinking and they can actually do the problems that get put on the homework that the professor thinks are interesting and challenging ones. But most of the students who don't kind of engage as deeply don't ever get. And we think, oh, that man must be brilliant. He must have this special insight. But he must have some biological sort of bit that's different that makes him so that he or she could have that insight. But although I don't want to dismiss biological individual differences completely, I find it much more interesting to think about the possibility that it was that difference in the dinner table conversation at the Chomsky house when he was growing up that made it so that he had that cast of mind. And there's a few topics we talked about that kind of interconnect. Because I wonder, the better I get at certain things, we humans, the deeper we understand something. What are you starting to then miss about the rest of the world? We talked about David and his degenerative mind. And when you look in the mirror and wonder, how different am I cognitively from the man I was a month ago, from the man I was a year ago? If I can, having thought about language, if I'm Chomsky for 10, 20 years, what am I no longer able to see? What is in my blind spot and how big is that? And then to somehow be able to leap back out of your deep structure that you formed for yourself about thinking about the world, leap back and look at the big picture again, or jump out of your current way of thinking. And to be able to introspect, what are the limitations of your mind? How is your mind less powerful than it used to be or more powerful or different, powerful in different ways? So that seems to be a difficult thing to do because we're looking at the world through the lens of our mind, right? To step outside and introspect is difficult, but it seems necessary if you want to make progress. One of the threads of psychological research that's always been very, I don't know, important to me to be aware of is the idea that our explanations of our own behavior aren't necessarily part of the causal process that caused that behavior to occur. Or even valid observations of the set of constraints that led to the outcome. But they are post hoc rationalizations that we can give based on information at our disposal about what might have contributed to the result that we came to when asked. And so this is an idea that was introduced in a very important paper by Nisbet and Wilson about the limits on our ability to be aware of the factors that cause us to make the choices that we make. And I think it's something that we really ought to be much more cognizant of in general as human beings is that our own insight into exactly why we hold the beliefs that we do and we hold the attitudes and make the choices and feel the feelings that we do is not something that we totally control or totally observe. And it's subject to our culturally transmitted understanding of what it is that is the mode that we give to explain these things when asked to do so as much as it is about anything else. And so even our ability to introspect and think we have access to our own thoughts is a product of culture and belief, you know, practice. So let me ask you the big question of advice. So you've lived an incredible life in terms of the ideas you've put out into the world, in terms of the trajectory you've taken through your career, through your life. What advice would you give to young people today in high school and college about how to have a career or how to have a life they can be proud of? Finding the thing that you are intrinsically motivated to engage with and then celebrating that discovery is what it's all about. When I was in college, I struggled with that. I had thought I wanted to be a psychiatrist because I think I was interested in human psychology in high school. And at that time, the only sort of information I had that had anything to do with the psyche was Freud and Eric Fromm and sort of popular psychiatry kinds of things. And so, well, they were psychiatrists, right? So I had to be a psychiatrist. And that meant I had to go to medical school. And I got to college and I find myself taking the first semester of a three-quarter physics class and it was mechanics. And this was so far from what it was I was interested in. But it was also too early in the morning in the winter court semester. So I never made it to the physics class. But I wandered about the rest of my freshman year and most of my sophomore year until I found myself in the midst of this situation where around me there was this big revolution happening. I went to Columbia University in 1968 and the Vietnam War is going on. Columbia is building a gym in Morningside Heights, which is part of Harlem. And people are thinking, oh, the big bad rich guys are stealing the parkland that belongs to the people of Harlem. And they're part of the military industrial complex, which is enslaving us and sending us all off to war in Vietnam. And so there was a big revolution that involved a confluence of black activism and SDS and social justice and the whole university blew up and got shut down. And I got a chance to sort of think about why people were behaving the way they were in this context. And I happened to have taken mathematical statistics. I happened to have been taking psychology that quarter, just psych one. And somehow things in that space all ran together in my mind and got me really excited about asking questions about what made certain people go into the buildings and not others and things like that. And so suddenly I had a path forward and I had just been wandering around aimlessly. And at the different points in my career, when I think, okay, well, should I take this class or should I just read that book about some idea that I want to understand better? Or should I pursue the thing that excites me and interests me or should I meet some requirement? I always did the latter. So I ended up, my professors in psychology thought I was great. They wanted me to go to graduate school. They nominated me for Phi Beta Kappa and I went to the Phi Beta Kappa ceremony and this guy came up and said, oh, are you Magna Arsuma? I wasn't even getting honors based on my grades. They just happened to have thought I was interested enough in ideas to belong to Phi Beta Kappa. So- I mean, would it be fair to say you kind of stumbled around a little bit through accidents of too early morning of classes in physics and so on until you discovered intrinsic motivation, as you mentioned, and then that's it, it hooked you and then you celebrate the fact that this happens to human beings. And what is it that made what I did intrinsically motivating to me? Well, that's interesting and I don't know all the answers to it and I don't think I want anybody to think that you should be sort of in any way, I don't know, sanctimonious or anything about it. It's like I really enjoyed doing statistical analysis of data. I really enjoyed running my own experiment, which was what I got a chance to do in the psychology department that chemistry and physics had never, I never imagined that mere mortals would ever do an experiment in those sciences, except one that was in the textbook that you were told to do in lab class. But in psychology, we were already like, even when I was taking Psych 1, it turned out we had our own rat and we got to, after two set experiments, we got to, okay, do something you think of with your rat. It's the opportunity to do it myself and to bring together a certain set of things that engaged me intrinsically. And I think it has something to do with why certain people turn out to be profoundly amazing musical geniuses. They get immersed in it at an early enough point and it just sort of gets into the fabric. So my little brother had intrinsic motivation for music as we witnessed when he discovered how to put records on the phonograph when he was like 13 months old and recognize which one he wanted to play, not because he could read the labels, because he could sort of see which ones had which scratches, which were the different, oh, that's rapid E Espanol and that's- Oh, wow. And he enjoyed that. That connected with him somehow. Yeah. And there was something that it fed into. You're extremely lucky if you have that and if you can nurture it and can let it grow and let it be an important part of your life. Yeah. Those are the two things is like be attentive enough to feel it when it comes. This is something special. I mean, I don't know. For example, I really like tabular data, like Excel sheets. It brings me deep joy. I don't know how useful that is for anything. That's part of what I'm talking about. Exactly. So there's like a million, not a million, but there's a lot of things like that for me and you have to hear that for yourself. Realize this is really joyful. But then the other part that you're mentioning, which is the nurture, is take time and stay with it. Stay with it a while and see where that takes you in life. Yeah, and I think the motivational engagement results in the immersion that then creates the opportunity to obtain the expertise. So we could call it the Mozart effect. When I think about Mozart, I think about the person who was born as the fourth member of the family string quartet. And they handed him the violin when he was six weeks old. All right, start playing. So the level of immersion there was amazingly profound. But hopefully he also had something. Maybe this is where the genetic part comes in sometimes, I think. Something in him resonated to the music so that the synergy of the combination of that was so powerful. So that's what I really consider to be the Mozart effect. It's the synergy of something with experience that then results in the unique flowering of a particular mind. So I know my siblings and I are all very different from each other. We've all gone in our own different directions. And I mentioned my younger brother, who was very musical. My other younger brother was this amazing intuitive engineer. And one of my sisters was passionate about water conservation well before it was such a hugely important issue that it is today. So we all somehow find a different thing. And I don't mean to say it isn't tied in with something about us biologically. But it's also when that happens, where you can find that, then you can do your thing and you can be excited about it. So people can be excited about fitting people on bicycles as well as excited about making neural networks, achieve insights into human cognition. For me personally, I've always been excited about love and friendship between humans. And just the actual experience of it. Since I was a child, just observing people around me and also been excited about robots. And there's something in me that thinks I really would love to explore how those two things combine. And it doesn't make any sense. A lot of it is also timing, just to think of your own career and your own life. You find yourself in certain pieces, places that happen to involve some of the greatest thinkers of our time. And so it just worked out that you guys developed those ideas and there may be a lot of other people similar to you and they were brilliant and they never found that right connection and place to where the ideas could flourish. So it's timing, it's place, it's people. And ultimately the whole ride, it's undirected. Can I ask you about something you mentioned in terms of psychiatry when you were younger? Because I had a similar experience of reading Freud and Carl Jung and just those kind of popular psychiatry ideas. And that was a dream for me early on in high school to, I hoped to understand the human mind by... Somehow psychiatry felt like the right discipline for that. Does that make you sad that psychiatry is not the mechanism by which you are able to explore the human mind? So for me, I was a little bit disillusioned because of how much prescription medication and biochemistry is involved in the discipline of psychiatry, as opposed to the dream of the Freud like, use the mechanisms of language to explore the human mind. So that was a little disappointing. And that's why I kind of went to computer science and thinking like, maybe you can explore the human mind by trying to build the thing. Yes, I wasn't exposed to the sort of the biomedical slash pharmacological aspects of psychiatry at that point because I didn't, I dropped out of that whole idea of pre-med that I never even found out about that until much later. But you're absolutely right. So I was actually a member of the National Advisory Mental Health Council. That is to say the board of scientists who advised the director of the National Institute of Mental Health. And that was around the year 2000. And in fact, at that time, the man who came in as the new director, I had been on this board for a year when he came in, said, okay, schizophrenia is a biological illness. It's a lot like cancer. We've made huge strides in curing cancer and that's what we're going to do with schizophrenia. We're going to find the medications that are going to cure this disease. And we're not going to listen to anybody's grandmother anymore and good old behavioral psychology is not something we're going to support any further. And he completely alienated me from the institute and from all of its prior policies, which had been much more holistic, I think really at some level. And the other people on the board were like psychiatrists, right? Very biological psychiatrists. It didn't pan out, right? Nothing has changed in our ability to help people with mental illness. And so 20 years later, that particular path was a dead end as far as I can tell. There's some aspect to, and sorry to romanticize the whole philosophical conversation about the human mind, but to me, psychiatrists for a time held the flag of we're the deep thinkers. In the same way that physicists are the deep thinkers about the nature of reality, psychiatrists are the deep thinkers about the nature of the human mind. And I think that flag has been taken from them and carried by people like you. It's more in the cognitive psychology, especially when you have a foot in the computational view of the world, because you can build it. You can like intuit about the functioning of the mind by building little models and being able to say mathematical things and then deploying those models, especially in computers to say, does this actually work? They do little experiments. And then some combination of neuroscience where you're starting to actually be able to observe, do certain experience on human beings and observe how the brain is actually functioning. And there, using intuition, you can start being the philosopher. Like Richard Feynman is the philosopher, a cognitive psychologist can become the philosopher, and psychiatrists become much more like doctors. They're like very medical. They help people with medication, biochemistry and so on, but they are no longer the book writers and the philosophers, which of course I admire. I admire the Richard Feynman ability to do great low-level mathematics and physics and the high-level philosophy. Yeah. I think it was Fromm and Jung more than Freud that was sort of initially kind of like made me feel like, oh, this is really amazing and interesting and I want to explore it further. I actually, when I got to college and I lost that thread, I found more of it in sociology and literature than I did in any place else. So I took quite a lot of both of those disciplines as an undergraduate. And I was actually deeply ambivalent about the psychology because I was doing experiments after the initial flurry of interest in why people would occupy buildings during an insurrection and consider, be sort of like so over-committed to their beliefs. But I ended up in the psychology laboratory running experiments on pigeons. And so I had these profound sort of like dissonance between, okay, the kinds of issues that would be explored when I was thinking about what I read about in modern British literature versus what I could study with my pigeons in the laboratory. That got resolved when I went to graduate school and I discovered cognitive psychology. And so for me, that was the path out of this sort of like extremely sort of ambivalent divergence between the interest in the human condition and the desire to do actual mechanistically oriented thinking about it. And I think we've come a long way in that regard and you're absolutely right that nowadays this is something that's accessible to people through the pathway in through computer science or the pathway in through neuroscience. You can get derailed in neuroscience down to the bottom of the system where you might find the cures of various conditions, but you don't get a chance to think about the higher level stuff. So it's in the systems and cognitive neuroscience and computational intelligence, miasma up there at the top that I think these opportunities are most, are richest right now. And so yes, I am indeed blessed by having had the opportunity to fall into that space. So you mentioned the human condition, speaking of which, you happen to be a human being who's unfortunately not immortal. That seems to be a fundamental part of the human condition that this ride ends. Do you think about the fact that you're going to die one day? Are you afraid of death? I would say that I am not as much afraid of death as I am of degeneration. And I say that in part for reasons of having seen some tragic degenerative situations unfold. It's exciting when you can continue to participate and feel like you're near the place where the wave is breaking on the shore, if you like. And I think about my own future potential. If I were to undergo, begin to suffer from dementia, Alzheimer's disease or semantic dementia or some other condition, I would gradually lose the thread of that ability. And so one can live on for several, for a decade after having to retire because one no longer has these kinds of abilities to engage. And I think that's the thing that I fear the most. The losing of that, the breaking of the way, the flourishing of the mind where you could have these ideas and they're swimming around and you're able to play with them. Yeah, and collaborate with other people who are themselves really helping to push these ideas forward. So yeah. What about the edge of the cliff? The end? I mean, the mystery of it. The migrated conception of mind and continuous way of thinking about most things makes it so that to me the discreteness of that transition is less apparent than it seems to be to most people. I see. I see. Yeah. Yeah. I wonder, so I don't know if you know the work of Ernest Becker and so on. I wonder what role mortality and our ability to be cognizant of it, anticipate it, and perhaps be afraid of it, what role that plays in our reasoning of the world. I think that it can be motivating to people to think they have a limited period left. I think in my own case, it's like seven or eight years ago now that I was sitting around doing experiments on decision making that were satisfying in a certain way because I could really get closure on whether the model fit the data perfectly or not. I could see how one could test the predictions in monkeys as well as humans and really see what the neurons were doing. But I just realized, hey, wait a minute. I may only have about 10 or 15 years left here. I don't feel like I'm getting towards the answers to the really interesting questions while I'm doing this particular level of work. That's when I said to myself, okay, let's pick something that's hard. That's when I started working on mathematical cognition. I think it was more in terms of, well, I got 15 more years possibly of useful life left. Let's imagine that it's only 10. I'm actually getting close to the end of that now, maybe three or four more years. But I'm beginning to feel like, well, I probably have another five after that. So okay, I'll give myself another six or eight. But a deadline is looming and therefore- It's not going to go on forever. So yeah, I got to keep thinking about the questions that I think are the interesting and important ones for sure. What do you hope your legacy is? You've done some incredible work in your life as a man, as a scientist. When the aliens and the human civilization is long gone and the aliens are reading the encyclopedia about the human species, what do you hope is the paragraph written about you? I would want it to sort of highlight a couple of things that I was able to see one path that was more exciting to me than the one that seemed already to be there for a cognitive psychologist, but not for any super special reason other than that I'd had the right context prior to that, but that I had gone ahead and followed that lead. And then I forget the exact wording, but I said in this preface that the joy of science is the moment in which a partially formed thought in the mind of one person gets crystallized a little better in the discourse and becomes the foundation of some exciting concrete piece of actual scientific progress. And I feel like that moment happened when Rommelhart and I were doing the interactive activation model and when Rommelhart heard Hinton talk about gradient descent and having the objective function to guide the learning process. It happened a lot in that period and I sort of seek that kind of thing in my collaborations with my students. The idea that this is a person who contributed to science by finding exciting collaborative opportunities to engage with other people through is something that I certainly hope is part of the paragraph. And like you said, taking a step maybe in directions that are non-obvious. So it's the old Robert Frost, road less taken. So maybe, because you said like this incomplete initial idea, that step you take is a little bit off the beaten path. If I could just say one more thing here. This was something that really contributed to energizing me in a way that I feel it would be useful to share. My PhD dissertation project was completely empirical experimental project. And I wrote a paper based on the two main experiments that were the core of my dissertation and I submitted it to a journal. And at the end of the paper, I had a little section where I laid out the beginnings of my theory about what I thought was going on that would explain the data that I had collected. And I had submitted the paper to the Journal of Experimental Psychology. So I got back a letter from the editor saying, thank you very much. These are great experiments and we'd love to publish them in the journal. But what we'd like you to do is to leave the theorizing to the theorists and take that part out of the paper. And so I did. I took that part out of the paper. But I almost found myself labeled as a non-theorist by this. And I could have succumbed to that and said, okay, well, I guess my job is to just go on and do experiments. But that's not what I wanted to do. And so when I got to my assistant professorship, although I continued to do experiments because I knew I had to get some papers out, I also at the end of my first year submitted my first article to Psychological Review, which was the theoretical journal where I took that section and elaborated it and wrote it up and submitted it to them. And they didn't accept that either. But they said, oh, this is interesting. You should keep thinking about it this time. And then that was what got me going to think, okay. So it's not a superhuman thing to contribute to the development of theory. You don't have to be... You can do it as a mere mortal. And the broader, I think, lesson is don't succumb to the labels of a particular reviewer in a journal. Or anybody labeling you, right? Exactly. I mean, yeah, exactly. Especially as you become successful, labels get assigned to you for that you're successful for that thing. You have a connectionist or a cognitive scientist and not a neuroscientist or whatever. You can completely... That's the stories of the past. You're today a new person that can completely revolutionize in totally new areas. So don't let those labels hold you back. Well, let me ask the big question. When you look into... You said it started with Columbia trying to observe these humans and they're doing weird stuff and you want to know why are they doing this stuff. So zoom out even bigger at the hundred plus billion people who've ever lived on earth. Why do you think we're all doing what we're doing? What do you think is the meaning of it all? The big why question. We seem to be very busy doing a bunch of stuff and we seem to be kind of directed towards somewhere. But why? Well I myself think that we make meaning for ourselves and that we find inspiration in the meaning that other people have made in the past. The great religious thinkers of the first millennium BC and few that came in the early part of the second millennium laid down some important foundations for us. But I do believe that we are an emergent result of a process that happened naturally without guidance and that meaning is what we make of it and that the creation of efforts to reify meaning in religious traditions and so on is just a part of the expression of that goal that we have to not find out what the meaning is but to make it ourselves. So to me it's something that's very personal, it's very individual, it's like meaning will come for you through the particular combination of synergistic elements that are your fabric and your experience and your context and you should, it's all made in a certain kind of a local context though. Here I am at UCSD with this brilliant man, Ronald Hart, who's having these doubts about symbolic artificial intelligence that resonate with my desire to see it grounded in the biology and let's make the most of that. Yeah and so from that little pocket there's some kind of peculiar little emergent process that then, which is basically each one of us humans is a kind of, you think cells and they come together and it's an emergent process that then tells fancy stories about itself and then gets, just like you said, just enjoys the beauty of the stories we tell about ourselves. It's an emergent process that lives for a time, is defined by its local pocket and context in time and space and then tells pretty stories and we write those stories down and then we celebrate how nice the stories are and then it continues because we build stories on top of each other and eventually we'll colonize hopefully other planets, other solar systems, other galaxies and we'll tell even better stories but it all starts here on earth. Jay you're speaking of peculiar emergent processes that lived one heck of a story. You're one of the great scientists of cognitive science, of psychology, of computation. It's a huge honor you would talk to me today that you spend your very valuable time. I really enjoyed talking with you and thank you for all the work you've done. I can't wait to see what you do next. Well thank you so much and this has been an amazing opportunity for me to let ideas that I've never fully expressed before come out because you asked such a wide range of the deeper questions that we've all been thinking about for so long. So thank you very much for that. Thank you. Thanks for listening to this conversation with Jay McClelland. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Jeffrey Hinton. In the long run, curiosity driven research works best. Real breakthroughs come from people focusing on what they're excited about. Thanks for listening and hope to see you next time.

https://youtu.be/Ui38ZzTymDY

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Niall Ferguson: History of Money, Power, War, and Truth | Lex Fridman Podcast #239

The following is a conversation with Neil Ferguson, one of the great historians of our time, at times controversial and always brilliant, whether you agree with him or not. He's an author of 16 books on topics covering the history of money, power, war, pandemics, and empire. Previously at Harvard, currently at Stanford, and today launching a new university here in Austin, Texas called the University of Austin, a new institution built from the ground up to encourage open inquiry and discourse by both thinkers and doers, from philosophers and historians to scientists and engineers, embracing debate, dissent, and self-examination, free to speak, to disagree, to think, to explore truly novel ideas. The advisory board includes Steven Pinker, Jonathan Haidt, and many other amazing people, with one exception, me. I was graciously invited to be on the advisory board, which I accepted in the hope of doing my small part in helping build the future of education and open discourse, especially in the fields of artificial intelligence, robotics, and computing. We spend the first hour of this conversation talking about this new university before switching to talking about some of the darkest moments in human history and what they reveal about human nature. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now here's my conversation with Neil Ferguson. You are one of the great historians of our time, respected, sometimes controversial. You have flourished in some of the best universities in the world, from NYU to London School of Economics, to Harvard, and now to Hoover Institution at Stanford. Before we talk about the history of money, war, and power, let us talk about a new university you're part of launching here in Austin, Texas. It is called University of Austin, UATX. What is its mission, its goals, its plan? I think it's pretty obvious to a lot of people in higher education that there's a problem. And that problem manifests itself in a great many different ways. But I would sum up the problem as being a drastic chilling of the atmosphere that constrains free speech, free exchange, even free thought. And I had never anticipated that this would happen in my lifetime. My academic career began in Oxford in the 1980s when anything went. One sensed that a university was a place where one could risk saying the unsayable and debate the undebatable. So the fact that in a relatively short space of time, a variety of ideas, critical race theory or wokeism, whatever you want to call it, a variety of ideas have come along that seek to limit and quite drastically limit what we can talk about, strikes me as deeply unhealthy. And I'm not sure, and I've thought about this for a long time, you can fix it with the existing institutions. I think you need to create a new one. And so after much deliberation, we decided to do it. And I think it's a hugely timely opportunity to do what people used to do in this country, which was to create new institutions. I mean, that used to be the default setting of America. We sort of stopped doing that. I mean, I look back and I thought, why are there no new universities? Or at least if there are, why do they have so little impact? It seems like we have the billionaires, we have the need, let's do it. So you still believe in institutions, in the university, in the ideal of the university, right? I believe passionately in that ideal. There's a reason they've been around for nearly a millennium. There is a unique thing that happens on a university campus when it's done right. And that is the transfer of knowledge between generations. That is a very sacred activity, and it seems to withstand major changes in technology. So this form that we call the university predates the printing press, survived the printing press, continued to function through the scientific revolution, the enlightenment, the industrial revolution to this day. And I think it's because, maybe because of evolutionary psychology, we need to be together in what is a relatively confined space when we're in our late teens and early twenties for the knowledge transfer between the generations to happen. That's my feeling about this. But in order for it to work well, there needs to be very few constraints. There needs to be a sense that one can take intellectual risk. Remember, people in their late teens and early twenties, they're not adults, but they're inexperienced adults. And if I look back on my own time as an undergraduate, saying stupid things was my MO. My way to finding good ideas was through a minefield of bad ideas. I feel so sorry for people like me today, people age 18, 19, 20 today, who are intellectually very curious, ambitious, but inexperienced, because the minefields today are absolutely lethal. And one wrong foot and it's cancellation. I said this to Peter Thiel the other day, imagine being us now. I mean, we were obnoxious undergraduates. There's nothing that Peter did at Stanford that Andrew Sullivan and I were not doing at Oxford, and perhaps we were even worse. But it was so not career-ending to be an absolutely insufferable, lethal, obnoxious undergraduate then. Today, if people like us exist today, they must live in a state of constant anxiety that they're going to be outed for some heretical statement that they made five years ago on social media. So part of what motivates me is the desire to give the me's of today a shot at free thinking and really, I'd call it, aggressive learning, learning where you're really pushed. And I just think that stopped happening on the major campuses, because whether at Harvard where I used to teach or at Stanford where I'm now based, I sense a kind of suffocating atmosphere of self-censorship that means people are afraid to take even minimal risk in class. I mean, just take, for example, a survey that was published earlier this year that revealed, this is of undergraduates in four-year programs in the US, 85% of self-described liberal students said they would report a professor to the university administration if he or she said something they considered offensive. And something like 75% said they'd do it to a fellow undergraduate. That's the kind of culture that's evolved in our universities. So we need a new university in which none of that is true, in which you can speak your mind, say stupid things, get it completely wrong, and live to tell the tale. There's a lot more going on, I think, because when you start thinking about what's wrong with a modern university, many, many more things suggest themselves. And I think there's an opportunity here to build something that's radically new in some ways and radically traditional in other ways. For example, I have a strong preference for the tutorial system that you see at Oxford and Cambridge, which is small group teaching and highly Socratic in its structure. I think it'd be great to bring that to the United States where it doesn't really exist. But at the same time, I think we should be doing some very 21st century things, making sure that while people are reading and studying classic works, they're also going to be immersed in the real world of technological innovation, a world that you know very well. And I'd love to get a synthesis of the ancient and classical, which we're gradually letting fade away, with the novel and technological. So we want to produce people who can simultaneously talk intelligently about Adam Smith, or for that matter, Shakespeare or Proust, and have a conversation with you about where AI is going, and how long it will be before I can get driven here by a self-driving vehicle, allowing me to have my lunch and prepare rather than focus on the other crazy people on the road. So that's the dream, that we can create something which is partly classical and partly 21st century, and we look around and we don't see it. If you don't see an institution that you really think should exist, I think you have a moral responsibility to create it. LUKE So you're thinking including something bigger than just liberal education, also including science, engineering and technology. I should also comment that I mostly stay out of politics and out of some of these aspects of liberal education that's kind of been the most controversial and difficult within the university. But there is a kind of ripple effect of fear within that space into science and engineering and technology that I think has a nature that's difficult to describe. It doesn't have a controversial nature, it just has a nature of fear, where you're not, you know, you mentioned saying stupid stuff as a young 20-year-old. You know, for example, deep learning, machine learning is really popular in the computer science now as an approach for creating artificial intelligence systems. It is controversial in that space to say that anything against machine learning, saying, sort of exploring ideas that's saying this is going to lead to a dead end. Now, that takes some guts to do as a young 20-year-old within a classroom, to think like that, to raise that question in a machine learning course. It sounds ridiculous, because it's like, who's going to complain about this? But the fear that starts in a course on history or on some course that covers society, the fear ripples and affects those students that are asking big out-of-the-box questions about engineering, about computer science. And there's a lot, you know, there's like linear algebra that's not going to change, but then there's like applied linear algebra, which is machine learning. And that's when robots and real systems touch human beings. And that's when you have to ask yourself these difficult questions about humanity, even in the engineering and science and technology courses. And these are not separate worlds in two senses. I've just taken delivery of my copy of the book that Eric Schmidt and Henry Kissinger have co-authored on artificial intelligence, the central question of which is, what does this mean for us broadly? But they're not separate worlds, you know, in C.P. Snow's sense of, you know, the chasm between science and arts, because on a university campus, everything is contagious from a novel coronavirus to the behaviors that are occurring in the English department. Those behaviors, if denunciation becomes a norm, you know, undergraduate denounces professor, teaching assistant denounces undergraduate, those behaviors are contagious and will spread inexorably, first to social science and then to natural sciences. And I think that's part of the reason why when this started to happen, when we started to get the origins of disinvitation and cancel culture, it was not just a few conservative professors in the humanities who had to worry, everybody had to worry, because eventually it was going to come even to the most apparently hard stem part of the campus. It's contagious. This is something Nicholas Christakis should look at, because he's very good at looking at the way in which social networks like the ones that exist in a university can spread everything. But I think when we look back and ask why did wokeism spread so rapidly and rapidly out of humanities into other parts of universities, and why did it spread across the country and beyond the United States to the other English-speaking universities, it's because it's a contagion. And these behaviors are contagious. The president of a university I won't name said to me that he receives every day at least one denunciation, one call for somebody or other to be fired for something that they said. That's the crazy kind of totalitarianism light that now exists in our universities. And of course, the people who want to downplay this say, oh, well, there only have been 100 and something disinvitations, or, oh, there really aren't that many cases. But the point is that the famous events, the events that get the attention, are responsible for a general chilling that, as you say, spreads to every part of the university and creates a very familiar culture in which people are afraid to say what they think. Self-censorship, look at the Heterodox Academy data on this, grows and grows. So now a majority of students will say, this is clear from the latest Heterodox Academy surveys. We are scared to say what we think in case we get denounced, in case we get canceled. Well, that's just not the correct atmosphere for a university in a free society. To me, what's really creepy is how many of the behaviors I see on university campuses today are reminiscent of the way that people used to behave in the Soviet Union, or in the Soviet Bloc, or in Mao's China. The sort of totalitarianism light that I think we're contending with here, which manifests itself as denunciations, people informing on superiors, some people using it for career advantage, other people reduced to hapless, desperate apology to try to exonerate themselves, people disappearing, metaphorically, if not literally. All of this is so reminiscent of the totalitarian regimes that I studied earlier in my career that it makes me feel sick. And what makes me really feel sick is that the people doing this stuff, the people who write the letters of denunciation are apparently unaware that they're behaving exactly like people in Stalin's Soviet Union. They don't know that. So they clearly have, there's been a massive educational failure. If somebody can write an anonymous or non-anonymous letter of denunciation and not feel shame, I mean, you should feel morally completely contaminated as you're doing that. But people haven't been taught the realities of totalitarianism. For all these reasons, I think you need to try at least to create a new institution where those pathologies will be structurally excluded. So maybe a difficult question, maybe you'll push back on this, but you're widely seen politically as a conservative. Hoover Institution is politically conservative. What is the role of politics at the University of Austin? Because some of the ideas, people listening to this, when they hear the ideas you're expressing, they may think there's a lean to these ideas. There's a conservative lean to these ideas. Is there such a lean? There will certainly be people who say that because the standard mode of trying to discredit any new initiative is to say, oh, this is a sinister conservative plot. But one of our co-founders, Heather Hying, is definitely not a conservative. She's as committed to the idea of academic freedom as I am. But I think on political issues, we probably agree on almost nothing. And at least I would guess. But politics, Max Weber made this point a long time ago, that politics really should stop at the threshold of the classroom, of the lecture hall. And in my career, I've always tried to make sure that when I'm teaching, it's not clear where I stand politically, though of course undergraduates insatiably curiously want to know, but it shouldn't be clear from what I say. Because indoctrination on a political basis is an abuse of the power of the professor, as Weber rightly said. So I think one of the key principles of the University of Austin will be that Weberian principle, that politics is not an appropriate subject for the lecture hall, for the classroom. And we should pursue truth and enshrine liberty of thought. If that's a political issue, then I can't help you. I mean, if you're against freedom of thought, then we don't really have much of a discussion to have. And clearly, there are some people who politically seem quite hostile to it. But my sense is that there are plenty of people on the left in academia. Think of that interesting partnership between Cornel West and Robbie George, which has been institutionalized in the Academic Freedom Alliance. It's bipartisan, this issue. It really, really is. After all, 50 years ago, it was the left that was in favor of free speech. The right still has an anti-free speech element to it. Look how quickly they're out to ban critical race theory. Critical race theory won't be banned at the University of Texas. Wokism won't be banned. Everything will be up for discussion. But the rules of engagement will be clear. Chicago principles, those will be enforced. And if you have to give a lecture on, well, let's just take a recent example, the Dorian Abbott case. If you're giving a lecture on astrophysics, but it turns out that in some different venue, you express skepticism about affirmative action, well, it doesn't matter. It's irrelevant. We want to know what your thoughts are on astrophysics because that's what you're supposed to be giving a lecture on. That used to be understood. I mean, at the Oxford of the 1980s, there were communists and there were ultra-Tories. At Cambridge, there were people who were so reactionary that they celebrated Franco's birthday, but they were also out and out communists down the road at King's College. The understanding was that that kind of intellectual diversity was part and parcel of university life. And frankly, for an undergraduate, it was great fun to cross the road and go from, you know, outright conservatism, ultra-Tories and to communism. One learns a lot that way. But the issue is when you're promoting or hiring or tenuring people, their politics is not relevant. It really isn't. And when it started to become relevant, and I remember this coming up at the Harvard History Department late in my time there, I felt deeply, deeply uneasy that we were having conversations that amounted to, well, we can't hire X person despite their obvious academic qualifications because of some political issue. That's not what should happen at a healthy university. Some practical questions. Will University of Austin be a physical in-person university or virtual university? What are some, in that aspect, where the classroom is? It will be a real space institution. There may be an online dimension to it because there clearly are a lot of things that you can do via the internet. But the core activity of teaching and learning, I think, requires real space. And I've thought about this a long time, debated Sebastian Thrun about this many, many years ago when he was a complete believer in, let's call it the metaversity to go with the metaverse. I mean, the metaversity was going to happen, wasn't it? But I never really believed in the metaversity. I didn't do MOOCs because I just didn't think you'd A, be able to retain the attention, B, be able to cope with the scale, scaled grading that was involved. I think there's a reason universities have been around in their form for about a millennium. You kind of need to all be in the same place. So I think answer to that question, definitely a campus in the Austin area. That's where we'll start. And if we can allow some of our content to be available online, great, we'll certainly do that. Another question is, what kind of courses and programming will it offer? Is that something you can speak to? What's your vision here? We think that we need to begin more like a startup than like a full service university from day one. So our vision is that we start with a summer school, which will offer provocatively the forbidden courses. We want, I think, to begin by giving a platform to the professors who've been most subject to council culture and also to give an opportunity to students who want to hear them to come. So we'll start with a summer school that will be somewhat in the tradition of those institutions in the interwar period that were havens for refugees. So we're dealing here with the internal refugees of the woke era. We'll start there. It'll be an opportunity to test out some content, see what students will come and spend time in Austin to hear. So that's part A. That's the sort of, if you like, the launch product. And then we go straight to a master's program. I don't think you can go to undergraduate education right away because the established brands in undergraduate education are offering something it's impossible to compete with initially because they have the brand Harvard, Yale, Stanford, and they offer also this peer network, which is part of the reason people want so badly to go to those places. It's not really the professors, it's the classmates. So we don't want to compete there initially. Where there is, I think, room for new entrance is in a master's program. And the first one will be in entrepreneurship and leadership. Because I think there is a huge hunger amongst people who want to get into particularly the technology world to learn about those things. And they know they're not really going to learn about them at business schools. The people who are not going to teach them leadership and entrepreneurship are professors. So we want to create something that will be a little like the very successful Schwarzman program in China, which was, come and spend a year in China and find out about China. We'll be doing the same, essentially saying, come and spend a year and find out about technology. And there'll be a mix of academic content. We want people to understand some of the first principles of what they're studying. There are first principles of entrepreneurship and leadership, but we also want them to spend time with people like one of our co-founders, Joe Lonsdale, who's been a hugely successful venture capitalist and learn directly from people like him. So that's the kind of initial offering. I think there are other master's programs that we will look to roll out quite quickly. I have a particular passion for a master's in applied history or politics and applied history. I'm a historian driven crazy by the tendency of academic historians to drift away from what seemed to me the important questions and certainly to drift away from addressing policy relevant questions. So I would love to be involved in a master's in applied history. And we'll build some programs like that before we get to the full liberal arts experience that we envisage for an undergraduate program. And that undergraduate program is an exciting one because I think we can be innovative there too. I would say two years would be spent doing some very classical and difficult classical things, bridging those old divides between arts and sciences. But then there would also be in the second half in the junior and senior years, something somewhat more of an apprenticeship where we'll have centers, including a center for technology, engineering, mathematics, that will be designed to help people make that transition from the theoretical to the practical. So that's the vision. And I think like any early stage idea, we'll doubtless tweak it. As we go along, we'll find things that work and things that don't work. But I have a very clear sense in my own mind of how this should look five years from now. And I don't know about you. I mean, I'm unusual as an academic because I quite like starting new institutions and I've done a bit of it in my career. You got to kind of know what it should look like after the first four or five years to get out of bed in the morning and put up with all the kind of hassles of doing it, not least the inevitable flack that we're bound to take from the educational establishment. And I was graciously invited to be an advisor to this University of Austin. And the reason I would love to help in whatever way I can is several. So one, I would love to see Austin, the physical location, flourish intellectually and especially in the space of science and engineering. That's really exciting to me. Another reason is I am still a research scientist at MIT. I still love MIT. And I see this effort that you're launching as a beacon that leads the way to the other elite institutions in the world. I think too many of my colleagues, and especially in robotics, kind of see, don't see robotics as a humanities problem. But to me, robotics and AI will define much of our world in the next century. And for not to consider all the deep psychological, sociological, human problems associated with that. To have real open conversations, to say stupid things, to challenge the ideas that, of how companies are being run, for example. That is the safe space. It's very difficult to talk about the difficult questions about technology when you're employed by Facebook or Google and so on. The university is the place to have those conversations. That's right. And we're hugely excited that you want to be one of our advisors. We need a broad and eclectic group of people. And I'm excited by the way that group has developed. Some of my favorite intellectuals are there, Steve Pinker, for example. But we're also making sure that we have people with experience in academic leadership. And so, it's a happy coalition of the willing looking to try to build something new, which as you say, will be complementary to the existing and established institutions. I think of the academic world as a network. I've moved from some major hubs in the network to others. But I've always felt that we do our best work, not in a silo called Oxford, but in a silo that is really a hub connected to Stanford, connected to Harvard, connected to MIT. One of the reasons I moved to the United States was that I sensed that there was more intellectual action in my original field of expertise, financial history. And that was right. It was a good move. I think I'd have stagnated if I'd stayed at Oxford. But at the same time, I haven't lost connection with Oxford. I recently went and gave a lecture there in honor of Sir Roger Scruton, one of the great conservative philosophers. And the burden of my lecture was the idea of the Anglosphere, which appealed a lot to Roger, will go horribly wrong if illiberal ideas that inhibit academic freedom spread all over the Anglosphere. And this network gets infected with these, I think, deeply damaging notions. So yeah, I think we're creating a new node. I hope it's a node that makes the network overall more resilient. And right now, there's an urgent need for it. I mean, there are people whose academic careers have been terminated. I'll name two who are involved. Peter Boghossian, who was harassed out of Portland State for the reason that he was one of those intrepid figures who carried out the grievance studies hoaxes, exposing the utter charlatanry going on in many supposedly academic journals by getting phony gender studies articles published. It's genius. And of course, so put the noses out of joint of the academic establishment that he began to be subject to disciplinary actions. So Peter is going to be involved. And in a recent shocking British case, the philosopher Kathleen Stock has essentially been run off the campus of Sussex University in England for violating the increasingly complex rules about discussing transgender issues and women's rights. She will be one of our advisors, and I think also one of our founding fellows actually teaching for us in our first iteration. So I think we're creating a node that's badly needed. Those people, I mean, I remember saying this to the other founders when we first began to talk about this idea to Barry Weiss and to Pano Canellos as well as to Heather Hying. We need to do this urgently because there are people whose livelihoods are in fact being destroyed by these extraordinarily illiberal campaigns against them. And so there's no time to hang around and come up with the perfect design. This is an urgently needed lifeboat. And let's start with that, and then we can build something spectacular taking advantage of the fact that all of these people have, well, they now have very real skin in the game. They need to make this a success, and I'm sure they will help us make it a success. So you mentioned some interesting names like Heather Hying, Barry Weiss, and so on. Stephen Pinker, somebody I really admire. He too was under quite a lot of fire. Many reasons I admire him, one, because of his optimism about the future, and two, how little of a damn he seems to give about the like walking through the fire. There's nobody more zen about walking through the fire than Stephen Pinker. But anyway, you mentioned a lot of interesting names. Jonathan Haidt is also interesting there. Who is involved with this venture at this early days? Well, one of the things that I'm excited about is that we're getting people from inside and outside the academic world. So we've got Arthur Brooks, who for many years ran the American Enterprise Institute very successfully, has a Harvard role now teaching. And so he's somebody who brings, I think, a different perspective. There's obviously a need to get experienced academic leaders involved, which is why I was talking to Larry Summers about whether he would join our board of advisors. The Chicago principals owe a debt to the former president of Chicago, and he's graciously agreed to be in the board of advisors. I could go on, it would become a long and tedious list. But my goal in trying to get this happy band to form has been to signal that it's a bipartisan endeavor. It is not a conservative institution that we're trying to build. It's an institution that's committed to academic freedom and the pursuit of truth that will mean it when it takes Robert Zimmer's Chicago principals and enshrines them in its founding charter, and will make those something other than honored in the breach, which they seem to be at some institutions. So the idea here is to grow this organically. We need, rather like the Academic Freedom Alliance that Robbie George created earlier this year, we need breadth. And we need to show that this is not some kind of institutionalization of the intellectual dark web, though we welcome founding members of that nebulous body. It's really something designed for all of academia to provide a kind of reboot that I think we all agree is needed. LUIS Is there a George Washington type figure? Is there a president elected yet? Or who's going to lead this institution? ALI PASHORNIK Pano Canellos, the former president of St. John's, is the president of University of Austin. And so he is our George Washington. I don't know who Alexander Hamilton is. I'll leave you to guess. LUIS It's funny you mentioned IDW, intellectual dark web. Have you talked to your friend Sam Harris about any of this? He is another person I really admire, and I've talked to online and offline quite a bit, for not belonging to any tribe. He stands boldly on his convictions when he knows they're not going to be popular. He basically gets canceled by every group. He doesn't shy away from controversy, and not for the sake of controversy itself, he is one of the best examples to me of a person who thinks freely. I disagree with him on quite a few things, but I deeply admire that he is what it looks like to think freely by himself. It feels to me like he represents a lot of the ideals of this kind of effort. ALI PASHORNIK Yes, he would be a natural fit. Sam, if you're listening, I hope you're in. I think in the course of his recent intellectual quests, he did collide with one of our founders, Heather Hying. So we'll have to model civil disagreement at the University of Austin. It's extremely important that we should all disagree about many things, but do it amicably. One of the things that has been lost sight of, perhaps it's all the fault of Twitter or maybe it's something more profound, is that it is possible to disagree in a civil way and still be friends. I certainly had friends at Oxford who were far to the left of me politically, and they are still among my best friends. So the University of Austin has to be a place where we can disagree vehemently, but we can then go and have a beer afterwards. That's, in my mind, a really important part of university life, learning the difference between the political and the personal. So Sam is, I think, a good example, as are you, of a certain kind of intellectual hero who has been willing to go into the cyber sphere, the metaverse, and carve out an intellectual space, the podcast, and debate everything fearlessly. His essay, it was really an essay on Black Lives Matter and the question of police racism, was a masterpiece of 2020. And so he, I think, is a model of what we believe in. But we can't save the world with podcasts, good though yours is, because there's a kind of solo element to this form of public intellectual activity. It's also there in Substack where all our best writers now seem to be, including our founder, Barry Weiss. The danger with this approach is ultimately your subscribers are the people who already agree with you, and we are all therefore in danger of preaching to the choir. I think what makes an institution like University of Austin so attractive is that we get everybody together at least part of the year, and we do that informal interaction at lunch, at dinner, at that allows, in my experience, the best ideas to form. Intellectual activity isn't really a solo voyage. Historians often make it seem that way, but I've realized over time that I do my best work in a collaborative way, and scientists have been better at this than people in the humanities. But what really matters, what's magical about a good university is that interdisciplinary serendipitous conversation that happens on campus. Tom Sargent, the great Nobel Prize-winning economist and I, used to have these kind of random conversations in elevators at NYU or in corridors at Stanford, and sometimes they'd be quite short conversations, but in that short, serendipitous exchange, I would have more intellectual stimulus than in many a seminar lasting an hour and a half. So I think we want to get the Sam Harrises and Lex Freedmans out of their darkened rooms and give them a chance to interact in a much less structured way than we've got used to. Again, it's that sense that sometimes you need some freewheeling, unstructured debate to get the really good ideas. I mean, to talk anecdotally for a moment, I look back on my Oxford undergraduate experience, and I wrote a lot of essays and attended a lot of classes, but intellectually, the most important thing I did was to write an essay on the Viennese satirist Karl Kraus for an undergraduate discussion group called the Canon Club. And I probably put more work into that paper than I put into anything else, except maybe my final examinations, even although there was only really one senior member present, the historian Jeremy Cattell, I was really just trying to impress my contemporaries. And that's the kind of thing we want. The great intellectual leaps forward occurred often in somewhat unstructured settings. I'm from Scotland, you can tell from my accent a little at least. The enlightenment happened in late 18th century Scotland in a very interesting interplay between the universities, which were very important, Glasgow, Edinburgh, St. Andrews, and the coffee houses and pubs of the Scottish cities where a lot of unstructured discussion often fueled by copious amounts of wine took place. That's what I've missed over the last few years. Let's just think about how hard academic social life has become. We've reached the point that Amy Chua becomes the object of a full-blown investigation and media storm for inviting two Yale Law School students over to her house to talk. I mean, when I was at Oxford, it was regarded as a tremendous honor to be asked to go to one of our tutors' homes. The social life of Oxford and Cambridge is one of their great strengths. There's a sort of requirement to sip unpleasant sherry with the Dons, and we've kind of killed all that. We've killed all that in the US because nobody dares have a social interaction with an undergraduate or exchange an informal email in case the whole thing ends up on the front page of the local or student newspaper. So that's what we need to kind of restore, the social life of academia. So there's magic. We didn't really address this sort of explicitly, but there's magic to the interaction between students. There's magic in the interaction between faculty, the people that teach, and there's the magic in the interaction between the students and the faculty. And it's an iterative process that changes everybody involved. So it's like world experts in a particular discipline are changed as much as the students, as the 20-year-olds with the wild ideas, each are changed. And that's the magic of it. That applies in liberal education, that applies in the sciences too. That's probably, maybe you can speak to this, why so much scientific innovation has happened in the universities. There's something about the youthful energy of like young minds, graduate students, undergraduate students that inspire some of the world experts to do some of the best work of their lives. Well, the human brain we know is at its most dynamic when people are pretty young. You know this with your background in math, people don't get better at math after the age of 30. And this is important when you think about the intergenerational character of university. The older people, the professors have the experience, but they're fading intellectually from much earlier than anybody really wants to admit. And so you get this intellectual shot in the arm from hanging out with people who are circa 20, don't know shit, but the brains are kind of like cooking. I look back on the career I've had in teaching, which is over 25 years at where Cambridge, Oxford, NYU, Harvard. And I have extremely strong relationships with students from those institutions because they would show up, whether it was at office hours or in tutorials, and disagree with me. And for me, it's always been about encouraging some active intellectual rebellion, telling people, I don't want your essay to echo my views. If you can find something wrong with what I wrote, great. Or if you can find something I missed that's new, fantastic. So there is definitely, as you said, a magic in that interaction across the generations. And it's extraordinarily difficult, I think, for an intellectual to make the same progress in a project in isolation compared with the progress that can be made in these very, very special communities. What does a university do amongst other things? It creates a somewhat artificial environment of abnormal job security, and that's the whole idea of giving people tenure, and then a relatively high turnover, new faces each year, and an institutionalization of thought experiments and actual experiments. And then you get everybody living in the same kind of vicinity so that it can spill over into 3am conversation. Well, that always seems to me to be a pretty potent combination. Let's ask ourselves a counterfactual question next. Let's imagine that the world wars happen, but there are no universities. I mean, how does the Manhattan Project happen with no academia, to take just one of many examples? In truth, how does Britain even stay in the war without Bletchley Park, without being able to crack the German cipher? The academics are unsung, partly sung heroes of these conflicts. The same is true in the Soviet Union. The Soviet Union was a terribly evil and repressive system, but it was good at science, and that kept it in the game, not only in World War II, it kept it in the Cold War. So it's clear that universities are incredibly powerful, intellectual force multipliers, and our history without them would look very different. Sure, some innovations would have happened without them. That's clear. The Industrial Revolution didn't need universities. In fact, they played a very marginal role in the key technological breakthroughs of the Industrial Revolution in its first phase. But by the second Industrial Revolution in the late 19th century, German industry would not have leapt ahead of British industry if the universities had not been superior. And it was the fact that the Germans institutionalized scientific research in the way that they did, that really produced a powerful, powerful advantage. The problem was that, and this is a really interesting point that Friedrich Meinicke makes in Die deutsche Katastrophe, for the German catastrophe, the German intellectuals became technocrats, homo faber, he says. They knew a great deal about their speciality, but they were alienated from, broadly speaking, humanism. And that is his explanation, or one of his explanations, for why this very scientifically advanced Germany goes down the path of hell, led by Hitler. So when I come back and ask myself, what is it that we want to do with a new university? We want to make sure that we don't fall into that German pit where very high levels of technical and scientific expertise are decoupled from the fundamental foundations of a free society. So liberal arts are there, I think, to stop the scientists making Faustian pacts. And that's why it's really important that people working on AI read Shakespeare. I think you said that academics are unsung heroes of the 20th century. I think there's kind of an intellectual, a lazy intellectual desire to kind of destroy the academics, that the academics are the source of all problems in the world. And I personally believe that exactly as you said, we need to recognize that the university is probably where the ideas that will protect us from the catastrophes that are looming ahead of us, that's where those ideas are going to come from. People who work on economics can argue back and forth about John Maynard Keynes. But I think it's pretty clear that he was the most important economist and certainly the most influential economist of the 20th century. And I think his ideas are looking better today in the wake of the financial crisis than they have at any time since the 1970s. But imagine John Maynard Keynes without Cambridge. You can't. Because someone like that doesn't actually exist without the incredible hothouse that a place like Cambridge was in Keynes' life. He was a product of a kind of hereditary intellectual elite. It had its vices. But you can't help but admire the sheer power of the mind. I've spent a lot of my career reading Keynes and I revere that intellect. It's so, so powerful. But you can't have people like that if you're not prepared to have King's College Cambridge. And it comes with redundancy. I think that's the point. There are lots and lots of things that are very annoying about academic life that you just have to deal with. They're made fun of in that recent Netflix series, The Chair. And it is easy to make fun of academic life. Tom Sharpe's Porterhouse Blue did it. It's an inherently comical subject. Professors at least used to be amusingly eccentric. But we've sort of killed off that side of academia by turning it into an increasingly doctrinaire place where eccentricity is not tolerated. I'll give you an illustration of this. I had a call this morning from a British academic who said, can you give me some advice because they're trying to decolonize the curriculum. This is coming from the diversity, equity, and inclusion officers. And it seems to me that what they're requiring of us is a fundamental violation of academic freedom because it is determining ex ante what we should study and teach. That's what's going on. And that's the thing that we really, really have to resist because that kills the university. That's the moment that it stops being the magical place of intellectual creativity and simply becomes an adjunct of the ministry of propaganda. LUKE I've loved the time we've spent talking about this because it's such a hopeful message for the future of the university that I still share with you the love of the ideal of the university. So, very practical question. You mentioned summer. Which summer are we talking about? So, I know we don't want to put hard dates here, but what year are we thinking about? When is this thing launching? What are your thoughts on this? SIMON We are moving as fast as our resources allow. The goal is to offer the first of the forbidden courses next summer, summer of 2022. And we hope to be able to launch an initial, albeit relatively small scale master's program in the fall of next year. That's as fast as is humanly possible. So, yeah, we're really keen to get going. And I think the approach we're taking is somewhat imported from Silicon Valley. Think of this as a startup. Don't think of this as something that has to exist as a full service university on day one. We don't have the resources for that. You'd need billions and billions of dollars to build a university sort of as a facsimile of an existing university, but that's not what we want to do. I mean, copying and pasting Harvard or Yale or Stanford would be a futile thing to do. They would probably, you'd very quickly end up with the same pathologies. So, we do have to come up with a different design. And one way of doing that is to grow it organically from something quite small. Elon Musk mentioned in his usual humorous way on Twitter that he wants to launch the Texas Institute of Technology and Science. TITS. Some people thought this was sexist because of the acronym TITS. So, first of all, I understand their viewpoint, but I also think there needs to be a place for humor on the internet, even from CEO. So, on this podcast, I've gotten a chance to talk to quite a few CEOs, and what I love to see is authenticity. And humor is often a sign of authenticity. The quirkiness that you mentioned is such a beautiful characteristic of professors and faculty in great universities is also beautiful to see as CEOs, especially founding CEOs. So, anyway, the deeper point he was making is showing an excitement for the university as a place for big ideas in science, technology, engineering. So, to me, if there's some kind of way, if there is a serious thought that he had behind this tweet, not to analyze Elon Musk's Twitter like it's Shakespeare, but if there's a serious thought, I would love to see him supporting the flourishing of Austin as a place for science, technology, for these kinds of intellectual developments that we're talking about. Like, make a place for free inquiry, civil disagreements, coupled with great education and conversations about artificial intelligence, about technology, about engineering. So, I'm actually gonna, I hope there's a serious idea behind that tweet, and I'm gonna chat with him about it. I do too, I do too. Most of the biggest storms and teacups of my academic career have been caused by bad jokes that I've made. These days, if you wanna make bad jokes, being a billionaire is a great idea. I'm not here to defend Elon's Twitter style or sense of humor. He's not gonna be remembered for his tweets, I think. He's gonna be remembered for the astonishing companies that he's built and his contributions in a whole range of fields, from SpaceX to Tesla and solar energy. And I very much hope that we can interest Elon in this project. We need not only Elon, but a whole range of his peers, because this takes resources. Universities are not cheap things to run, especially if, as I hope, we can make as much of the tuition covered by scholarships and bursaries. We want to attract the best intellectual talent to this institution. The best intellectual talent is somewhat randomly distributed through society, and some of it is in the bottom quintile of the income distribution. And that makes it hard to get to elite education. So, this will take resources. The last generation of super wealthy plutocrats, the generation of the Gilded Age of the late 19th century, did a pretty good job of founding universities. Chicago wouldn't exist, but for the money of that era. And so, my message not only to Elon, but to all of the peers, all of those people who made their billions out of technology over the last couple of decades is, this is your time. I mean, and this is your opportunity to create something new. I can't really understand why the wealthy of our time are content to hand their money. I mean, think of the vast sums Mike Bloomberg recently gave to Johns Hopkins to his established institutions. When on close inspection, those institutions don't seem to spend the money terribly well. And in fact, one of the mysteries of our time is the lack of due diligence that hard-nosed billionaires seem to do when it comes to philanthropy. So, I think there's an opportunity here for this generation of very talented wealthy people to do what their counterparts did in the late 19th and early 20th century and create some new institutions. And they don't need to put their names on the buildings. They just need to do what the founders of University of Chicago did, create something new that will endure. Yeah, MIT is launching a College of Computing and Seymour Schwarzman has given quite a large sum of money, I think in total a billion dollars. And as somebody who loves computing, as somebody who loves MIT, I want some accountability for MIT becoming a better institution. And this is once again, why I'm excited about University of Austin, because it serves as a beacon. Look, you can create something new and this is what the great institutions of the future should look like. And Steve Schwarzman is also an innovator. The idea of creating a college on the Tsinghua campus and creating a kind of Rhodes program for students from the Western world to come study in China was Steve's idea. And I was somewhat involved, did some visiting, professing there. It taught me that you can create something new in that area of graduate education and quite quickly attract really strong applicants. Because the people who finished their four years at Harvard or Stanford or Stanford know that they don't know a lot. And I, having taught a lot of people in that group, know how intellectually dissatisfied they often are at the end of four years. I mean, they may have beautifully gamed the system to graduate summa magna cum laude, but they kind of know they'll confess it after a drink or two. They know that they gamed the system and that intellectually it wasn't the fulfilling experience they wanted. And they also know that an MBA from a comparable institution would not be a massive intellectual step forward. So, I think what we want to say is here's something really novel, exciting that will be intellectually very challenging. I do think the University of Austin has to be difficult. I'd like it to feel a little bit like surviving Navy SEAL training to come through this program because it will be intellectually demanding. And that I think should be a magnet. So, yeah, Steve, if you're listening, please join Elon in supporting this. And Peter Thiel, if you're listening, I know how skeptical you are about the idea of creating a new university because heaven knows, Peter and I have been discussing this idea for years and he's always said, well, no, we thought about this and it just isn't going to work. But I really think we've got a responsibility to do this. Well, Steve's been on this podcast before. We've spoken a few times. So, I'll send this to him. I hope he does actually get behind it as well. So, I'm super excited by the ideas that we've been talking about that this effort represents and what ripple effect it has on the rest of society. So, thank you. That was a time beautifully spent. And I'm really grateful for the fortune of getting a chance to talk to you at this moment in history because I've been a big fan of your work. And the reason I wanted to talk to you today is about all the excellent books you've written about various aspects of history through money, war, power, pandemics, all of that. But I'm glad that we got a chance to talk about this, which is not looking at history. It's looking at the future. It's a beautiful little fortuitous moment. I appreciate you talking about it. In the book, Ascent of Money, you give a history of the world through the lens of money. If the financial system is evolutionary nature, much like life on earth, what is the origin of money on earth? The origin of money predates coins. Most people kind of assume I'll talk about coins, but coins are relatively late developments. Back in ancient Mesopotamia, so I don't know, 5,000 years ago, there were relations between creditors and debtors. There are even in the simplest economy because of the way in which agriculture works. Hey, I need to plant these seeds, but I'm not going to have crops for X months. So, we have clay tablets in which simple debt transactions are inscribed. I remember looking at great numbers of these in the British Museum when I was writing The Ascent of Money, and that's really the beginning of money. The minute you start recording a relationship between a creditor and a debtor, you have something that is quasi-money. That is probably what these clay tablets mostly denoted. From that point on, there's a great evolutionary experiment to see what the most convenient way is to record relations between creditors and debtors. And what emerges in the time of the ancient Greeks are coins, metal, tokens, sometimes a valuable metal, sometimes not, usually bearing the imprint of a state or a monarch. And that's the sort of more familiar form of money that we still use today for very, very small transactions. I expect coins will all be gone by the time my youngest son is my age, but they're a last remnant of a very, very old way of doing simple transactions. Luke Stevenson By the way, when you say coins, you mean physical coins. Because the term coins has been rebranded into digital space as well. Matthewhew Miller Yeah, not coin-based coins, actual coin coins, you know, the ones that jangle in your pocket and you kind of don't know quite what to do with once you have some. So that became an incredibly pervasive form of paying for things. Money is just a crystallization of a relationship between a debtor and a creditor. And coins are just very fungible. You know, whereas a clay tablet relates to a specific transaction, coins are generic and fungible. They can be used in any transaction. So that was an important evolutionary advance. If you think of financial history, and this was the point of the Ascent of Money, as an evolutionary story, there are punctuated equilibria. People get by with coins for a long time, despite their defects as a means of payment, such as that they can be debased, they can be clipped. It's very hard to avoid fake or debased money entering the system. But coinage is still kind of the basis of payments all the way through the Roman Empire, out the other end into the so-called Dark Ages. It's still how most things are settled in cash transactions in the early 1300s. You don't get a big shift until after the Black Death, when there is such a need to monetize the economy because of chronic labor shortages and feudalism begins to unravel, that you just don't have a sufficient amount of coinage. So you get bills of exchange. I'm really into bills of exchange because, and this I hope will capture your listeners' and viewers' imaginations, when they start using bills of exchange, which are really just pieces of paper saying, you know, I owe you over a three-month period while goods are in transit from Florence to London, you get the first peer-to-peer payment system, which is network verified. Because they're not coins, they don't have a king's head on them. They're just pieces of paper. And the verification comes in the form of signatures. And you need ultimately some kind of guarantee if I write an IOU to you, bills of exchange, I mean, you don't really know me that well, we only just met. So you might want to get endorsed by, I don't know, somebody really creditworthy like Elon. And so we actually can see in the late 14th century in Northern Italy and England and elsewhere, the evolution of a peer-to-peer network system of payment. And that's actually how world trade grows. Because you just couldn't settle long oceanic transactions with coinage. It just wasn't practical. All those treasure chests full of doubloons, which were part of the way in which the Spanish empire worked, were really inefficient. So bills of exchange are an exciting part of the story. And they illustrate something I should have made more clear of the ascent of money, that not everything used in payment needs to be money. Classically, economists will tell you, oh, well, money, money has three different functions. It's, you've heard this a zillion times, right? It's a unit of account, it's a store of value, and it's a medium of exchange. Now there are three or four things that are worth saying about this, and I'll just say two. One, it may be that those three things are a trilemma and it's very difficult for anything to be all of them. This point was made by my Hoover colleague, Manny Rincon Cruz last year, and I still wish he would write this up as a paper because it's a great insight. The second thing that's really interesting to me is that payments don't need to be money. And if we go around as economists love to do saying, well, Bitcoin's not money because it doesn't fulfill these criteria, we're missing the point that you could build a system of payments, which I think is how we should think about crypto, that isn't money, doesn't need to be money. It's like bills of exchange. It's network-based verification, peer-to-peer transactions without third-party verification. When it hit me the other day that we actually have this precedent for crypto, I got quite excited and thought, I wish I had written that in The Ascent of Money. Luke Simon Can you sort of from a first principles, like almost like a physics perspective or maybe a human perspective, describe where does the value of money come from? Like where is it actually, where is it? So it's a sheet of paper or it's coins, but it feels like in a platonic sense, there's some kind of thing that's actually storing the value as the us, a bunch of ants are dancing around and so on. Matthew Walsh I come from a family of physicists. I'm the black sheep of the family. My mother's a physicist, my sister is. And so when you asked me to explain something in physics terms, I get a kind of little part of me dies because I know I'll fail. But in truth, it doesn't really matter what we decide money is going to be. Anything can record, crystallize the relationship between the creditor and the debtor. It can be a piece of paper, it can be a piece of metal, it can be nothing, can just be a digital entry. It's trust that we're really talking about here. We are not just trusting one another, we may not, but we are trusting the money. So whatever we use to represent the creditor-debtor relationship, whether it's a bank note or a coin or whatever, it does depend on us both trusting it. And so, I think that's what we're talking about here. And that doesn't always pertain. What we see in episodes of inflation, especially episodes of hyperinflation, is a crisis of trust, a crisis of confidence in the means of payment. And this is very traumatic for the societies to which it happens. By and large, human beings, particularly once you have a rule of law system of the sort that evolved in the West and then became generalized, are predisposed to trust one another and the default setting is to trust money. Even when it depreciates at a quite steady rate, as the US dollar has done pretty much uninterruptedly since the 1960s, it takes quite a big disruption for money to lose that trust. But I think essentially what money should be thought of as is a series of tokens that can take any form we like and can be purely digital, which represent our transactions as creditors and debtors. And the whole thing depends on our collective trust to work. I had to explain this to Stephen Colbert once in the Colbert Show, the old show that was actually funny. And it was a great moment when he said, so Neil, could I be money? And I said, yes, we could settle a debt with a human being. That was quite common in much of history, but it's not the most convenient form of money. Money has to be convenient. That's why when they worked out how to make payments with cell phones, the Chinese simply went straight there from bank accounts. They skipped out credit cards. You won't see credit cards in China, except in the hands of naive tourists. How much can this trust bear in terms of us humans with our human nature testing it? It seemed that I guess the surprising thing is the thing works. A bunch of self-interested ants running around trading in trust, and it seems to work except for a bunch of moments in human history when there's hyperinflation, like you mentioned. And it's just kind of amazing. It's kind of amazing that us humans, if I were to be optimistic and sort of hopeful about human nature, it gives me a sense that people want to lean on each other. They want to trust. That's certainly, I would say probably now a widely shared view amongst evolutionary psychologists, network scientists. It's one of Nicholas Christakis' argument in a recent book. I know economic history broadly bears this out, but you have to be cautious. The cases where the system works are familiar to us because those are the states and the eras and the eras that produce a lot of written records. But when the system of trust collapses and the monetary system collapses with it, there's generally quite a paucity of records. I found that when I was writing Doom. And so we slightly are biased in favor of the periods when trust prevailed and the system functioned. It's very easy to point to a great many episodes of very, very intense monetary chaos, even in the relatively recent past. In the wake of the First World War, multiple currencies, not just the German currency, multiple currencies were completely destroyed. The Russian currency, the Polish currency, there were currency disasters all over Central and Eastern Europe in the early 1920s. And that was partly because over the course of the 19th century, a system had evolved in which trust was based on gold and rules that were supposedly applied by central banks. That system, which produced relative price stability over the 19th century, fell apart as a result of the First World War. And as soon as it was gone, as soon as there was no longer a clear link between those banknotes and coins and gold, the whole thing went completely haywire. And I think we should remember that the extent of the monetary chaos from certainly 1918 all the way through to the late 1940s. I mean, the German currency was destroyed not once but twice in that period. And that was one of the most advanced economies in the world. In the United States, there were periods of intensely deep deflation. Prices fell by a third in the Great Depression and then very serious price volatility in the immediate post-World War II period. So it's a bit of an illusion. Maybe it's an illusion for people who've spent most of their lives in the last 20 years. We've had a period of exceptional price stability since this century began in which a regime of central bank independence and inflation targeting appeared to generate steady below 2% inflation in much of the developed world. It was a bit too low for the central bankers' liking. And that became a problem in the financial crisis. But we've avoided major price instability for the better part of 20 years in most of the world. There haven't really been that many very high inflation episodes and hardly any hyperinflationary episodes. Venezuela is one of the very few, Zimbabwe is another. But if you take a 100-year view or a 200-year view, or if you want to take a 500-year view, you realize that quite often, the system doesn't work. If you go back to the 17th century, there were multiple competing systems of coinage. There had been a great inflation that had begun the previous century. The price revolution caused mainly by the arrival of New World Silver. I think financial history is a bit messier than one might think. And the more one studies it, the more one realizes the need for the evolution. The reason bills of exchange came along was because the coinage systems had stopped working. The reason that banknotes started to become used more generally first in the American colonies in the 17th century, then more widely in the 18th century was just that they were more convenient than any other way of paying for things. We had to invent the bond market in the 18th century to cope with the problem of public debt, which up until that point had been a recurrent source of instability. And then we invented equity finance because bonds were not enough. So I would prefer to think of the financial history as a series of crises really that are resolved by innovations. And in the most recent episode, very exciting episode of financial history, something called Bitcoin initiated a new financial or monetary revolution in response, I think, to the growing crisis of the fiat money system. Can you speak to that? So what do you think about Bitcoin? What do you think it is the response to? What are the growing problems of the fiat system? What is this moment in human history that is full of challenges that Bitcoin and cryptocurrency is trying to overcome? I don't think Bitcoin was devised by Satoshi, whoever he was, for fear of a breakdown of the fiat currencies. If it was, it was a very far-sighted enterprise because certainly in 2008 when the first Bitcoin paper appeared, it wasn't very likely that a wave of inflation was coming. If anything, there was more reason to fear deflation at that point. I think it would be more accurate to say that with the advent of the internet, there was a need for a means of payment native to the internet. Typing your credit card number into a random website is not the way to pay for things on the internet. And I'd rather think of Bitcoin as the first iteration, the first attempt to solve the problem of how do we pay for things in what we must learn to call the metaverse, but let's just call it the internet for old time's sake. And ever since that initial innovation, the realization that you could use computing power and cryptography to create peer-to-peer payments without third-party verification, a revolution has been gathering momentum that poses a very profound threat to the existing legacy system of banks and fiat currencies. Most money in the world today is made by banks, not central banks, banks. That's what most money is, it's entries in bank accounts. And what Bitcoin represents is an alternative mode of payment that really ought to render banks obsolete. I think this financial revolution has got past the point at which it can be killed. It was vulnerable in the early years, but it now has sufficient adoption and has generated sufficient additional layers. I mean, Ethereum was in many ways the more important innovation because you can build a whole system of payments and ultimately smart contracts on top of Ether. I think we've now reached the point that it's pretty hard to imagine it all being killed, and it's just survived an amazing thing, which was the Chinese shutting down mining and shutting down everything, and still here we are. In fact, crypto's thriving. What we don't know is how much damage ill-judged regulatory interventions are going to do to this financial revolution. Left to its own devices, I think decentralized finance provides the native monetary and financial system for the internet. And the more time we spend in the metaverse, the more use we will make of it. The next things that will happen, I think, will be that tokens in game spaces like Roblox will become fungible. As my nine-year-old spends a lot more time playing on computer games than I ever did, I can see that entertainment is becoming a game-driven phenomenon. And in the game space, you need skins for your avatar. The economics of the internet, it's evolving very fast. And in parallel, you can see this payments revolution happening. I think that all goes naturally very well and generates an enormous amount of wealth in the process. The problem is there are people in Washington with an overwhelming urge to intervene and disrupt this evolutionary process. Partly, I think, out of a muddled sense that there must be a lot of nefarious things going on. If we don't step in, many more will go on. This, I think, greatly exaggerates how much criminal activity is in fact going on in the space. But there's also the vested interests at work. It was odd to me, maybe not odd, perhaps it wasn't surprising, that the Bank for International Settlements earlier this year published a report, one chapter of which said, this must all go. It must all stop. It's all got to be shut down. And it's got to be replaced by a central bank digital currency. And Martin Wolf in the Financial Times read this and said, I agree with this. And one suddenly realized that the banks are clever. They'd achieved the intellectual counterattack with almost no fingerprints on the weapon. I think central bank digital currency is a terrible idea. I can't imagine why we would want to copy a Chinese model that essentially takes all transactions and puts them directly under the surveillance of a central government institution. But that suddenly is a serious counter proposal. So on the one side, we have a relatively decentralized, technologically innovative, internet-native system of payments that has the possibility to evolve to produce a full set of smart contracts, reducing enormously the transaction costs that we currently encounter in the financial world, because it gets rid of all those middlemen who take their cut every time you take out a mortgage or whatever it is. That's one alternative. But on the other side, we have a highly centralized system in which transactions will by default be under the surveillance of the central bank. Seems like an easy choice to me, but hey, I have this thing about personal liberty. So that's where we are. I don't think that the regulators can kill Web3. I think we're supposed to call it Web3 because crypto is now an obsolescent term. They can't kill it, but they can definitely make it difficult and throw a lot of sand into the machine. And I think worst of all, they can spoil the evolutionary story by creating central bank digital currency that I don't think we really need. Or we certainly don't need it in the Chinese form. So do you think Bitcoin has a strong chance to take over the world? So become the primary, you mentioned the three things that make money money, money money become the primary methodology by which we store wealth, we exchange? No. No, I think what Bitcoin is, this was a phrase that I got from my friend Matt McClennan, First Eagle, an option on digital gold. So it's the gold of the system, but currently behaves like an option. That's why it's quite volatile. Because we don't really know if this brave new world of crypto is going to work. But if it does work, then Bitcoin is the gold because of the finite supply. What role we need gold to play in the metaverse isn't quite clear. I love that you're using the term metaverse. This is great. Well, I just like the metaversity as a kind of, as the antithesis of what we're trying to do in Austin. But can you imagine I'm using it sarcastically, I come from Glasgow where all novel words have to be used sarcastically. So the metaverse sarcastic. But see, the beauty about humor and sarcasm is that the joke becomes reality. I mean, it's like using the word Big Bang to describe the origins of the universe. It becomes like, it will, after a while it's in the textbooks and nobody's laughing. Yeah, well, that's exactly right. So sticky. Yeah. I'm on the side of humor, but it is a dangerous activity these days. Anyway, I think Bitcoin is the option of digital gold. The role it plays is probably not so much store value. Right now it's just nicely not very correlated asset in your portfolio. When I updated the Ascent of Money, which was in 2018, 10 years after it came out, I wrote a new chapter in which I said, Bitcoin, which had just sold off after its 2017 bubble will rise again through adoption. Because if every millionaire in the world has 0.2% of his or her wealth in Bitcoin, the price should be $15,000. And if it's 1%, it's $75,000. And it might not even stay at 1% because I mean, look at its recent performance. If your exposure to stock, global stocks had been hedged with a significant crypto holding, you would have aced the last few months. So I think the non-correlation property is very, very important in driving adoption. And the volatility also drives adoption if you're a sophisticated investor. So I think the adoption drives Bitcoin up because it's the option of digital gold, but it's also just this nicely not very correlated asset that you want to hold. In a world where the hell, I mean, the central bank is going to tighten. We've come through this massively disruptive episode of the pandemic. Public debt soared, money printing soared. You could hang around with your bonds and wait for the euthanasia of the rentier. You can hang on to your tech stocks and just hope there isn't a massive correction or dot, dot, dot. And it seems like a fairly obvious strategy to make sure that you have at least some crypto for the coming year, given what we likely have to face. I think what's really interesting is that on top of Ethereum, a more elaborate financial system is being built. Stable coins are the interesting puzzle for me because we need off-ramps. Ultimately, you and I have to pay taxes in US dollars. And there's no getting away from that. The IRS is going to let us hold crypto as long as we pay our taxes. And the only question in my mind is what's the optimal off-ramp to make those taxes, make those tax payments. Probably it shouldn't be a currency invented by Facebook. Never struck me as the best solution to this problem. Maybe it's some kind of Fed coin, or maybe one of the existing algorithmic stable coins does the job. But we clearly need some stable off-ramp. So you don't think it's possible for the IRS within the next decade to be accepting Bitcoin as tax payments? I doubt that. Having dealt with the IRS now since when did I first come here, 2002, it's hard to think of an institution less likely to leap into the 21st century when it comes to payments. No, I think we'll be tolerated. Crypto world will be tolerated as long as we pay our taxes. And it's important that we're already at that point. And then the next question becomes, well, does Gary Gensler define everything as a security? And do we then have to go through endless regulatory contortions to satisfy the SEC? There's a whole bunch of uncertainties that the administrative state excels at creating because that's just how the administrative state works. You're doing something new. I'll decide whether that's a security, but don't expect me to define it for you. I'll decide in an arbitrary way and then you'll owe me money. So all of this is going to be very annoying. And for people who are trying to run exchanges or innovate in the space, these regulations will be annoying. But the problem with FinTech is it's different from tech, broadly defined. When tech got into e-commerce with Amazon, when it got into social networking with Facebook, there wasn't a huge regulatory jungle to navigate. But welcome to the world of finance, which has always been a jungle of regulation because the regulation is there to basically entrench the incumbents. That's what it's for. So it'll be a much tougher fight than the fights we've seen of other aspects of the tech revolution because the incumbents are there and they see the threat. And in the end, Satoshi said it very explicitly, it's peer-to-peer payment without third-party verification. And all the third parties are going, wait, what? We're the third parties. So there is a connection between power and money. You've mentioned World War I from the perspective of money. So power, money, war, authoritarian regimes. From the perspective of money, do you have hope that cryptocurrency can help resist war, can help resist the negative effects of authoritarian regimes? Or is that a silly hope? Wars happen because the people who have the power to command armed forces miscalculate. That's generally what happens. And we will have a big war in the near future if both the Chinese government and the US government miscalculates and they unleash lethal force on one another. And there's nothing that any financial institution can do to stop that any more than the Rothschilds could stop World War I. And they were then the biggest bank in the world by far with massive international financial influence. So let's accept that war is in a different domain. War would impact the financial world massively if it were a war between the United States and China, because there's still a huge China trade on. Wall Street is long China, Europe is long China. So the conflict that I could foresee in the future is one that's highly financially disruptive. Where does crypto fit in? Crypto's obvious utility in the short run is as a store of wealth, of transferable wealth for people who live in dangerous places with failing, not just failing money, but failing rule of law. That's why in Latin America, there's so much interest in crypto because Latin Americans have a lot of monetary history to look back on, and not much of it is good. So I think that the short run problem that crypto solves is, and this goes back to the digital gold point, if you are in a dangerous place with weak rule of law and weak property rights, here is a new and better way to have portable wealth. I think the next question to ask is, would you want to be long crypto in the event of World War III? What's interesting about that question is that World War III would likely have a significant cyber dimension to it. And I don't want to be 100% in crypto if they crash the internet, which between them, China and Russia might be able to do. That's a fascinating question, whether you want to be holding physical gold or digital gold in the event of World War III. The smart price is a good question. I think the smart price is a good question. The smart person who studied history definitely wants better both. And so let's imagine World War III has a very, very severe cyber component to it with high levels of disruption. Yeah, you'd be glad of the old Chinese stuff at that point. So diversification still seems like the most important truth of financial history. And what is crypto? It's just this wonderful new source of diversification. But you'd be nuts to be 100% in Bitcoin. I mean, I have some friends who are probably quite close to that. Close to 100%, yeah. I admire the balls of steel. Yeah, in whatever way that balls of steel takes form. You mentioned smart contracts. What are your thoughts about, in the context of the history of money, about Ethereum, about smart contracts, about kind of more systematic at scale formalization of agreements between humans? I think it must be the case that a lot of the complexity in a mortgage is redundant. That when we are confronted with pages and pages and pages and pages of small print, we're seeing some manifestation of the late stage regulatory state. The transaction itself is quite simple. And most of the verbiage is just ass covering by regulators. So I think the smart contract, although I'm sure lawyers will email me and tell me I'm wrong, can deal with a lot of the plain vanilla and maybe not so plain transactions that we want to do and eliminate yet more intermediaries. That's my kind of working assumption. And given that a lot of financial transactions have the potential at least to be simplified, automated, turned into smart contracts, that's probably where the future goes. I can't see an obvious reason why my range of different financial needs, let's think about insurance, for example, will continue to be met with instruments that in some ways are 100 years old. So I think we're still at an early stage of a financial revolution that will greatly streamline how we take care of all those financial needs that we have. Mortgages and insurance leap to mind. Most households are penalized for being financially poorly educated and confronted with oligopolistic financial services providers. So you kind of leave college already in debt. So you start in debt servitude, and then you got to somehow lever up to buy a home if you can, because everybody's kind of telling you you should do that. So you and your spouse, you are getting even more leveraged and you're long one asset class called real estate, which is super illiquid. I mean, already I'm crying inside at the thought of describing so many households financial predicament in that way, and I'm not done with them yet, because, oh, by the way, there's all this insurance you have to take out. And here are the providers that are willing to insure you, and here are the premiums you're going to be paying, which are kind of presented to you. That's your car insurance, that's your home insurance, and if you're here, it's the earthquake insurance. And pretty soon you're just bleeding money in a bunch of monthly payments to the mortgage lender, to the insurer, to all the other people that lent you money. And let's look at your balance sheet. It sucks. There's this great big chunk of real estate, and what else have you really got on there? And the other side is a bunch of debt, which is probably paying too high interest. The typical household in the median kind of range is at the mercy of oligopolistic financial services providers. Go down further in the social scale, and people are outside the financial system altogether, and those poor folks have to rely on banknotes and informal lending with huge punitive rates. We have to do better. This has to be improved upon. And I think what's exciting about our time is that technology now exists that didn't exist when I wrote The Ascent of Money to solve these problems. When I wrote The Ascent of Money, which was in 2008, you couldn't really solve the problem I've just described. Certainly you couldn't solve it with something like microfinance. That was obviously not viable. The interest rates were high. The transaction costs were crazy. But now we have solutions, and the solutions are extremely exciting. So fintech is this great force for good that brings people into the financial system and reduces transaction costs. Crypto is part of it, but it's just part of it. There's a much broader story of fintech going on here where you get, suddenly you get financial services on your phone don't cost nearly as much as they did when there had to be a bricks and mortar building on Main Street that you kind of went humbly and beseeched to lend you money. I'm excited about that because it seems to me very socially transformative. I'll give you one other example of what's great. The people who really get scalped in our financial system are senders and receivers of remittances, which are often amongst the poorest families in the world. The people who are like my wife's family in East Africa really kind of hand to mouth. And if you send money to East Africa or the Philippines or Central America, the transaction costs are awful. I'm talking to you, Western Union. We're going to solve that problem. So 10 years from now, the transaction costs will just be negligible and the money will go to the people who need it rather than to rent seeking financial institutions. So I'm on the side of the revolution with this because I think the incumbent financial institutions globally are doing a pretty terrible job and middle-class and lower class families lose out. And thankfully technology allows us to fix this. Yeah. So fintech can remove a lot of inefficiencies in the system. I'm super excited myself, maybe as a machine learning person, in the data oracles. So converting a lot of our physical world into data and have smart contracts on top of that. So that no longer is there's this fuzziness about what is the concrete nature of the agreements. You can tie your agreement to weather. You can tie your agreement to the behavior of several of certain kinds of financial systems. You can tie your behavior to, I don't know, I mean all kinds of things. You can connect it to the body in terms of human sensory information. You can make an agreement that if you don't lose five pounds in the next month, you're going to pay me a thousand dollars or something like that. I don't know. It's a stupid example, but it's not because you can create all kinds of services on top of that. You can just create all kinds of interesting applications that completely revolutionize how humans transact. I think, of course, we don't want to create a world of Chinese-style social credit in which our behavior becomes so transparent to providers of financial services, particularly insurers, that when I try to go into the pub, I'm stopped from doing so. Luke Dion Every time you take a drink, your insurance goes up. Matthew Feeney Right, or my credit card won't work in certain restaurants because they serve, you know, ribeye steak. I fear that world because I see it being built in China. We must, at all costs, make sure that the Western world has something distinctive to offer. It can't just be, oh, it's the same as in China, only the data go to five tech companies rather than to Xi Jinping. I think that the way we need to steer this world is in the way that our data are by default vaulted on our devices and we choose when to release the data rather than the default setting being that the data are available. That's important, I think, because it was one of the biggest mistakes of the evolution of the internet that in a way the default was to let our data be plundered. It's hard to undo that, but I think we can at least create a new regime that in future makes privacy default rather than open access default. Luke Dion In the book, Doom, The Politics of Catastrophe, your newest book, you describe wars, pandemics, and the terrible disasters in human history. Which stands out to you as the worst in terms of how much it shook the world and the human spirit? RL I am glad I was not around in the mid-14th century when the bubonic plague swept across Eurasia. As far as we can see, that was history's worst pandemic. Maybe there was a comparably bad one in the reign of the Emperor Justinian, but there's some reason to think it wasn't as bad. The more we learn about the 14th century, the more we realize that it really was across Eurasia and the mortality was 30% in some places, 50% in some places higher. There were whole towns that were just emptied. And when one reads about the Black Death, it's an unimaginable nightmare of death and madness in the death with flagellant orders wandering from town to town, seeking to ward off divine retribution by flogging themselves, people turning on the local Jewish communities as if it's somehow their fault. That must have been a nightmarish time. If you ask me for a North Suran or runner-up, it would be World War II in Eastern Europe. And in many ways, it might have been worse because for a medieval peasant, the sense of being on the wrong side of divine retribution must have been overpowering. In the mid-20th century, you knew that this was man-made murder on a massive industrial scale. If one reads Brosman's Life and Fate, just to take one example, one enters a hellscape that it's extremely hard to imagine oneself in. So, these are two of the great disasters of human history. And if we did have a time machine, if one really were able to transport people back and give them a glimpse of these times, I think the post-traumatic stress would be enormous. People would come back from those trips, even if it was a one-day excursion with guaranteed survival, in a state of utter shock. You often explore counterfactual and hypothetical history, which is a fascinating thing to do, sometimes to a controversial degree. And again, you walk through that fire gracefully. So, let me ask maybe about World War II or in general, what key moments in history of the 20th century do you think, if something else happened at those moments, we could have avoided some of the big atrocities, Stalin's Haldimard, Hitler's Holocaust, Mao's Great Chinese Famine? The great turning point in world history is August the 2nd, 1914, when the British cabinet decides to intervene. And what would have been a European war becomes a world war. And with British intervention, it becomes a massively larger and more protracted conflict. So, very early in my career, I became very preoccupied with the deliberations on that day and the surprising decision that a liberal cabinet took to go to war, which you might not have bet on that morning because there seemed to be a majority of cabinet members who would be disinclined and only a minority, including Winston Churchill, who wanted to go to war. So, that's one turning point. I often wish I could get my time machine working and go back and say, wait, stop. Just think about what you're going to do. And by the way, let me show you a video of Europe in 1918. So, that's one. Luke Stevenson Can we linger on that one? That one, a lot of people push back on you on in the, because it's so difficult. So, the idea is, if I could try to summarize, and you're the first person that made me think about this very uncomfortable thought, which is the ideas in World War I, it would be a better world if Britain stayed out of the war and Germany won. Peter T. Leeson Right. Marc Thiessen Thinking now in retrospect at the whole story of the 20th century, thinking about Stalin's rule of 30 years, thinking about Hitler's rise to power and the atrocities of the Holocaust, but also, like you said, on the Eastern Front, the death of tens of millions of people throughout the war, and also sort of the political prisoners and the suffering connected to communism, connected to fascism, all those kinds of things. Well, that's one heck of an example of why you're just like fearless in this particular style of exploring counterfactual history. So, can you elaborate on that idea and maybe why this was such an important day in human history? Peter T. Leeson This argument was central to my book, The Pity of War. I also did an essay in Virtual History about this. And it's always amused me that from around that time, I began to be called a conservative historian, because it's actually a very left-wing argument. The people in 1914 who thought Britain should stay out of the war were the left of the Labour Party, who split to become the independent Labour Party. What would have happened? Well, first of all, Britain was not ready for war in 1914. There had not been conscription. The army was tiny. So, Britain had failed to deter Germany. The Germans took the decision that they could risk going through Belgium, using the Schlieffen Plan to fight their two-front war. They calculated that Britain's intervention would either not happen or not matter. If Britain had been strategically committed to preventing Germany winning a war in Europe, they should have introduced conscription 10 years before, had a meaningful land army, and that would have deterred the Germans. So, the Liberal government provided the worst of both worlds, a commitment that was more or less secret to intervene that the public didn't know about. In fact, much of the Liberal Party didn't know about, but without really the means to make that intervention effective, a tiny army with just a few divisions. So, it was perfectly reasonable to argue, as a number of people did on August 2, 1914, that Britain should not intervene. After all, Britain had not immediately intervened against the French Revolutionary Armies back in the 1790s. It had played an offshore role, ultimately intervening, but not immediately intervening. If Britain had stayed out, I don't think that France would have collapsed immediately, as it had in 1870. The French held up remarkably well to catastrophic casualties in the first six months of the First World War. But by 1916, I don't see how France could have kept going if Britain had not joined the war. And I think the war would have been over perhaps at some point in 1916. We know that Germany's aims would have been significantly limited because they would have needed to keep Britain out. If they'd succeeded in keeping Britain out, they'd have had to keep Britain out. And the way to keep Britain out was obviously not to make any annexation of Belgium, to limit German war aims, particularly to limit them to Eastern Europe. And from Britain's point of view, what was not to like? So, the Russian Empire is defeated along with France, what does that really change? If the Germans are sensible, and we can see what this might have looked like, they focus on Eastern Europe, they take chunks of the Russian Empire, perhaps they create as they did in the piece of Brest-Litovsk, an independent or quasi-independent Poland. In no way does that pose a threat to the Russian Empire. It's a threat to the Poland. In no way does that pose a threat to the British Empire. In fact, it's a good thing. Britain never had had a particularly good relationship with the Russian Empire after all. The key point here is that the Germany that emerges from victory in 1916 has a kind of European Union. It's the dominant power of an enlarged Germany with a significant middle Europa, whatever you want to call it, customs union type arrangement with neighbouring countries, including one suspects Austria-Hungary. That is a very different world from the world of 1917-18. The protraction of the war for a further two years, it's globalisation which Britain's intervention made inevitable. As Philip Zelikow showed in his recent book on the failure to make peace in 1916, Woodrow Wilson tried and failed to intervene and broker a peace in 1916. So I'm not the only counterfactualist here. The extension of the war for a further two years with escalating slaughter, the death toll rose because the industrial capacity of the armies grew greater. That's what condemns us to the Bolshevik revolution. And it's what condemns us ultimately to Nazism because it's out of the experience of defeat in 1918, as Hitler makes clear in Mein Kampf, that he becomes radicalised and enters the political realm. Take out those additional years of war and Hitler's just a failed artist. It's the end of the war that turns him into the demagogue. You asked what are the things that avoid the totalitarian states. As I've said, British non-intervention for me is the most plausible and it takes out all of that malignant history that follows from the Bolshevik revolution. It's very hard for me to see how Lenin gets anywhere if the war is over. That looks like the opportunity for the constitutional elements, the liberal elements in Russia. There are other moments at which you can imagine history taking a different path. If the provisional government in Russia had been more ruthless, it was very lenient towards the Bolsheviks. But if it had just rounded them up and shot the Bolshevik leadership, that would have certainly cut the Bolshevik revolution off. One looks back on the conduct of the Russian liberals with the kind of despair at their failure to see the scale of the threat that they face and the ruthlessness that the Bolshevik leadership would evince. There's a counterfactual in Germany which is interesting. I think the Weimar Republic destroyed itself in two disastrous economic calamities, the inflation and then the deflation. It's difficult for me to imagine Hitler getting to be Reich Chancellor without those huge economic disasters. So another part of my early work explored alternative policy options that the German Republic, the Weimar Republic might have pursued. There are other contingencies that spring to mind. In 1936 or 38, I think more plausibly 38, Britain should have gone to war. The great mistake was Munich. Hitler was in an extremely vulnerable position in 1938, because remember, he didn't have Russia squared away as he would in 1939. Chamberlain's mistake was to fold instead of going for war as Churchill rightly saw. And there was a magical opportunity there that would have played into the hands of the German military opposition and conservatives to snuff Hitler out over Czechoslovakia. I could go on. The point is that history is not some inexorable narrative which can only end one way. It's a garden of forking paths. And at many, many junctions in the road, there were choices that could have averted the calamities of the mid-20th century. I have to ask you about this moment before you said I could go on. This moment of Chamberlain and Hitler, snuff Hitler out in terms of Czechoslovakia, and we'll return to the book Doom on this point. What does it take to be a great leader in the room with Hitler or in the same time and space as Hitler to snuff him out, to make the right decisions? So it sounds like you put quite a bit of the blame on the man, Chamberlain, and give credit to somebody like a Churchill. So what is the difference? Where's that line? You've also written a book about Henry Kissinger, who's an interesting sort of person that's been throughout many difficult decisions in the games of power. So what does it take to be a great leader in that moment? That particular moment, sorry to keep talking, is fascinating to me because it feels like it's man-on-man conversations that define history. Well, Hitler was bluffing. He really wasn't ready for war in 1938. The German economy was clearly not ready for war in 1938. And Chamberlain made a fundamental miscalculation along with his advisors because it wasn't all Chamberlain. He was in many ways articulating the establishment view. And I tried to show in a book called War of the World how that establishment worked. It extended through the BBC into the aristocracy to Oxford. There was an establishment view. Chamberlain personified it. Churchill was seen as a warmonger. He was at his lowest point of popularity in 1938. But what is it that Chamberlain gets wrong? Because it's conceptual. Chamberlain is persuaded that Britain has to play for time because Britain is not ready for war in 1938. He fails to see that the time that he gets, that he buys at Munich is also available to Hitler. Everybody gets the time and Hitler's able to do much more with it because Hitler strikes the pact with Stalin that guarantees that Germany can fight a war on one front in 1939. What does Chamberlain do? Build some more aircraft. So the great mistake of the strategy of appeasement was to play for time. I mean, they knew war was coming, but they were playing for time, not realizing that Hitler got the time too. And after he partitioned Czechoslovakia, he was in a much stronger position, not least because of all the resources that they were able to plunder from Czechoslovakia. So that was the conceptual mistake. Churchill played an heroic role in pointing out this mistake and predicting accurately that it would lead to war on worse terms. What does it take? It takes a distinct courage to be unpopular. And Churchill was deeply unpopular at that point. People would listen to him in the House of Commons in silence. On one occasion, Lady Astor shouted, rubbish. So he went through a period of being hated on. The other thing that made Churchill a formidable leader was that he always applied history to the problem. And that's why he gets it right. He sees the historical problem much more clearly than Chamberlain. So I think if you go back to 1938, there's no realistic counterfactual in which Churchill's in government in 1938. You have to have France collapse for Churchill to come into government. But you can certainly imagine a Tory elite that's thinking more clearly about the likely dynamics. They haven't seen this, I guess, problem of conjecture, to take a phrase from Kissinger, which is that whatever they're doing in postponing the war has the potential to create a worse starting point for the war. It would have been risky in 1938, but it was a way better situation than they ended up with in 1939, a year later. You asked about Kissinger, and I've learned a lot from reading Kissinger and talking to Kissinger since I embarked on writing his biography a great many years ago. I think one of the most important things I've learned is that you can apply history to contemporary problems. It may be the most important tool that we have in that kind of decision-making. You have to do it quite ruthlessly and rigorously. And in the moment of crisis, you have to take risk. So Kissinger often says in his early work, the temptation of the bureaucrat is to wait for more data. But ultimately, the decision-making that we do under uncertainty can't be based on data. The problem of conjecture is that you could take an action now and incur some cost, an overt disaster, but you'll get no thanks for it because nobody is grateful for an averted disaster. And nobody goes around saying, wasn't it wonderful how we didn't have another 9-11. On the other hand, you can do nothing, incur no upfront costs and hope for the best, and you might get lucky, the disaster might not happen. That's in a democratic system, the much easier path to take. And I think that the essence of leadership is to be ready to take that upfront cost, avert the disaster and accept that you won't get gratitude. If I may make a comment, an aside about Henry Kissinger. So he, I think at 98 years old currently, has still got it. He's brilliant. It's very, very impressive. I can only hope that my brain has the same durability that his does because it's a formidable intellect and it's still in in as sharp form as it was 50 years ago. So you mentioned Eric Schmidt's and his book, and they reached out to me, they want to do this podcast. And I know Eric Schmidt, I've spoken to him before. I like him a lot, obviously. So they said, we could do a podcast for 40 minutes with Eric, 40 minutes with Eric and Henry together, and 40 minutes with Henry. So those are three different conversations. And I had to like, I had to do some soul searching because I said, fine, 40 minutes with Eric, we'll probably talk many times again. Fine, let's talk about this AI book together for 40 minutes. But I said, what I wrote to them is that I would hate myself if I only have 40 minutes to talk to Henry Kissinger. And so I had to hold my ground, went back and forth and in the end decided to part ways over this. And I sometimes think about this kind of difficult decision in the podcasting space of when do you walk away? Because there's a particular world leader that I've mentioned in the past where the conversation is very likely to happen. And as it happens, those conversations can often be, you know, unfortunately this person only has 30 minutes now. I know we agreed for three hours, but unfortunately, and you have to decide, do I stand my ground on this point? I suppose that's the thing that journalists have to think about, right? Like, do I hold on to my integrity in whatever form that takes? And do I stay in my ground even if I lose a fascinating opportunity? Anyway, it's something I thought about and something I think about. And with Henry Kissinger, I mean, he's had a million amazing conversations in your biography, so it's not like something is lost, but it was still nevertheless to me, some soul searching that I had to do as a kind of practice for what to me is a higher stakes conversation. I'll just mention is Vladimir Putin. I can have a conversation with him unlike any conversation he's ever had, partially because I'm a fluent Russian speaker, partially because I'm messed up in the head in certain kinds of ways that make for an interesting dynamic because we're both judo people. We both are certain kinds of human beings that can have a much deeper apolitical conversation. I have to ask to stay on the topic of leadership. You've in your book, Doom, have talked about wars, pandemics throughout human history, and in some sense saying that all of these disasters are man-made. So humans have a role in terms of the magnitude of the effect that they have on human civilization. Without taking cheap political shots, can we talk about COVID-19? How will history remember the COVID-19 pandemic? What were the successes? What were the failures of leadership, of man, of humans? Doom was a book that I was planning to write before the pandemic struck as a history of the future based in large measure on science fiction. It had occurred to me in 2019 that I had spent too long not reading science fiction. So I decided I would liven up my intake by getting off history for a bit and reading science fiction. Because history is great at telling you about the perennial problems of power. Putin is always interesting on history. He's become something of a historian recently with his essays and lectures. But what history is bad at telling you is, well, what will the effects of discontinuity of technology be? So I thought, I need some science fiction to think more about this because I'm tending to miss the importance of technological discontinuity. If you read a lot of science fiction, you read a lot of plague books because science fiction writers are really quite fond of the plague scenario. So the world ends in many ways in science fiction, but one of the most popular is the lethal pandemic. So when the first email came to me, I think it was on January the 3rd from my medical friend, Justin Stebbing, funny pneumonia in Wuhan, my antennae began to tingle because it was just like one of those science fiction books that begins in just that way. In a pandemic, as Larry Brilliant, the epidemiologist said many years ago, the key is early detection and early action. That's how you deal with a novel pathogen. And almost no Western country did that. We know it was doable because the Taiwanese and the South Koreans did it and they did it very well. But really no Western country got this right. Some were unlucky because super spreader events happened earlier than in other countries. Italy was hit very hard, very early for other countries. The real disaster came quite late Russia, which has only relatively recently had a really bad experience. The lesson for me is quite different from the one that most journalists thought they were learning last year. Most journalists last year thought Trump is a terrible president. He's saying a lot of crazy things. It's his fault that we have high excess mortality in the United States. The same argument was being made by journalists in Britain, Boris Johnson, dot, dot, dot, Brazil, Jair Bolsonaro, dot, dot, dot, even India, Narendra Modi, the same argument. And I think this argument is wrong in a few ways. It's true that the populist leaders said many crazy things and broadly speaking gave poor guidance to their populations. But I don't think it's true to say that with different leaders, these countries would have done significantly better if Joe Biden had magically been president a year earlier. I don't think the US would have done much better because the things that caused excess mortality last year weren't presidential decisions. They were utter failure of CDC to provide testing. That definitely wasn't Trump's fault. Scott Gottlieb's book makes that very clear. It's just been published recently. We utterly failed to use technology for contact tracing, which the Koreans did very well. We didn't really quarantine anybody seriously. There was no enforcement of quarantine. And we exposed the elderly to the virus as quickly as possible in elderly care homes. And these things have very little to do with presidential incompetence. So I think leadership is of somewhat marginal importance in a crisis like this because what you really need is your public health bureaucracy to get it right. And very few Western public health bureaucracies got it right. Could the president have given better leadership? Yes. His correct strategy, however, was to learn from Barack Obama's playbook with the opioid epidemic. The opioid epidemic killed as many people on Obama's watch as COVID did on Trump's watch. And it was worse in a sense because it only happened in the US. And each year, it killed more people than the year before, over eight years. Nobody, to my knowledge, has ever seriously blamed Obama for the opioid epidemic. Trump's mistake was to put himself front and center of the response, to claim that he had some unique insight into the pandemic and to say, with every passing week, more and more foolish things until even a significant portion of people who'd voted for him in 2016 realized that he'd blown it, which was why he lost the election. The correct strategy was actually to make Mike Pence the pandemic czar and get the hell out the way. That's what my advice to Trump would have been. In fact, it was in February of last year. So the mistake was to try to lead, but actually leadership in a pandemic is almost a contradiction in terms. What you really need is your public health bureaucracy not to fuck it up. And they really, really fucked it up. And that was then all blamed on Trump. Jim Fallows writes a piece in the Atlantic that says, well, being the president's like flying a light aircraft, it's pilot error. And I read that piece and I thought, does he really, after all the years he's spent on the presidency, he's really going to be the president? And I thought, all the years he spent writing, think that being president is like flying a light aircraft? I mean, it's really nothing like flying a light aircraft. Being president is you sit on top of a vast bureaucracy with how many different agencies, 60, 70, we've all lost count. And you're surrounded by advisors, at least a quarter of whom are saying, this is a disaster, we have to close the borders. And the others are saying, no, no, we have to keep the economy going. That's what you're running on in November. So being the president in a pandemic is a very unenviable position because you can't really determine whether your public health bureaucracy will get it right or not. You don't think to push back on that, just like being Churchill in a war is difficult. So leaving Trump or Biden aside, what I would love to see from a president is somebody who makes great speeches and arouses the public to push the bureaucracy, the public health bureaucracy, to get their shit together, to fire certain kinds of people. I mean, I'm sorry, but I'm a big fan of powerful speeches, especially in the modern age with the internet. It can really move people. Instead, the lack of speeches resulted in certain kinds of forces amplifying division over whether to wear masks or not. It's almost like the public picked some random topic over which to divide themselves. And there was a complete indecision, which is really what it was, fear of uncertainty materializing itself in some kind of division. And then you almost busied yourself with the red versus blue politics, as opposed to some, I don't know, FDR type character just stands and say, fuck all this bullshit that we're hearing. We're going to manufacture 5 billion tests. This is what America is great at. We're going to build the greatest testing infrastructure ever built or something, or even with the vaccine development. Ah, but that was what I was about to interject. In a pandemic, the most important thing is the vaccine. If you get that right, then you should be forgiven for much else. And that was the one thing the Trump administration got right, because they went around the bureaucracy with Operation Warp Speed and achieved a really major success. So I think the paradox of the 2020 story in the United States is that the one thing that mattered most, the Trump administration got right. And it got so much else wrong that was sort of marginal that we were left with the impression that Trump had been to blame for the whole disaster, which wasn't really quite right. Sure, it would have been great if we'd had Operation Warp Speed for testing, but ultimately vaccines are more important than tests. And this brings me to the question that you raised there of polarization and why that happened. Now, in a book called The Square in the Tower, I argued that it would be very costly for the United States to allow the public sphere to continue to be dominated by a handful of big tech companies, that this ultimately would have more adverse effects than simply contested elections. And I think we saw over the past 18 months just how bad this could be, because the odd thing about this country is that we came up with vaccines with 90 plus percent efficacy and about 20 percent of people refused to get them and still do refuse for reasons that seem best explained in terms of the anti-vax network, which has been embedded on the internet for a long time, predating the pandemic. René de Resta wrote about this pre-2020. And this anti-vax network has turned out to kill maybe 200,000 Americans who could have been vaccinated, but were persuaded through magical thinking that the vaccine was riskier than the virus. Whereas you don't need to be an epidemiologist, you don't need to be a medical scientist to know that the virus is about two orders of magnitude riskier than the vaccine. So again, leadership could definitely have been better, but the politicization of everything was not Trump's doing alone. It happened because our public sphere has been dominated by a handful of platforms whose business model inherently promotes polarization, inherently promotes fake news and extreme views, because those are the things that get the eyeballs and the screens and sell the ads. I mean, this is now commonplace, but when one thinks about the cost of allowing this kind of thing to happen, it's now a very high human cost. And we were foolish to leave uncorrected these structural problems in the public sphere that were already very clearly visible in 2016. And you described that, like you mentioned, that there's these networks that are almost like laying dormant, waiting for their time in the sun, and they stepped forward in this case. And that those network effects just, they serve as catalysts for whatever the bad parts of human nature. I do hope that there's kinds of networks that emphasize the better angels of our nature, to quote Steven Pinker. It's just clearly, and we know this from all the revelations of the Facebook whistleblower, there is clearly a very clear tension between the business model of a company like Facebook and the public good. And they know that. I just talked to the founder of Instagram. Yes, that's the case, but it's not from a technology perspective, like absolutely true of any kind of social network. I think it's possible to build, actually, I think it's not just possible. I think it's pretty easy if you set that as the goal, to build social networks that don't have these negative effects. Matthew Feeney Right. But if the business model is we sell ads, and the way you sell ads is to maximize user engagement, then the algorithm is biased in favor of fake news and extreme views. Yann Tannou But it's not, so it's not the ads, a lot of people blame the ads. The problem, I think, is the engagement, and the engagement is just the easiest, the dumbest way to sell the ads. I think there's much different metrics that could be used to make a lot more money than the engagement in the long term. It has more to do with planning for the long term. So optimizing the selling of ads to make people happy with themselves in the long term, as opposed to some kind of addicted, like dopamine feeling. And so that's, to me, that has to do with metrics and measuring things correctly and sort of also creating a culture with what's valued, to have difficult conversations about what we're doing with society, all those kinds of things. And I think once you have those conversations, this takes us back to the University of Austin, once you have those difficult human conversations, you can design the technology that will actually make for help people grow, become the best version of themselves, help them be happy in the long term. What gives you hope about the future? As somebody who studied some of the darker moments of human history, what gives you hope? A couple of things. First of all, the United States has a very unique operating system, which was very well designed by the founders who'd thought a lot about history and realized it would take quite a novel design to prevent the republic going the way of all republics, because republics tend to end up as tyrannies for reasons that were well established by the time of the Renaissance. And it gives me hope that this design has worked very well and withstood an enormous stress test in the last year. I became an American in 2018. I think one of the most important features of this operating system is that it is the magnet for talent. Here we sit, part of the immigration story in a darkened room with funny accents. Scott and a Russian walk into a recording studio and talk about America. It's very much like a joke. And Elon's a South African and so on, and Thiel is a German. And we're extraordinarily fortunate that the natives let us come and play, and play in a way that we could not in our countries of birth. And as long as the United States continues to exploit that superpower, that it is the talent magnet, then it should out-innovate the totalitarian competition every time. So that's one reason for being an optimist. Another reason, and it's quite a historical reason, as you would expect from me. Another reason that I'm optimistic is that my kids give me a great deal of hope. They range in age from 27 down to four. But each of them, in their different way, seems to be finding a way through this crazy time of ours without losing contact with that culture and civilization that I hold dear. I don't want to live in the metaverse as Mark Zuckerberg imagines it. To me, that's a kind of ghastly hell. I think Western civilization is the best civilization. And I think that almost all the truths about the human condition can be found in Western literature, art, and music. And I think also that the civilization that produced the scientific revolution has produced the great problem-solving tool that eluded the other civilizations that never really cracked science. And what gives me hope is that despite all the temptations and distractions that their generation had to contend with, my children, in their different ways, have found their way to literature and to art and to music. And they are civilized. And I don't claim much of the credit for that. I've done my best. But I think it's deeply encouraging that they found their way to the things that I think are indispensable for a happy life, a fulfilled life. Nobody, I think, can be truly fulfilled if they're cut off from the great body of Western literature, for example. I've thought a lot about Elon's argument that we might be in a simulation. No, no. There is a simulation. It's called literature. And we just have to decide whether or not to enter it. I'm currently in the midst of the later stages of Proust's great La Recherche du Temps Perdu. And Proust's observation of human relationships is perhaps more meticulous than that of any other writer. And it's impossible not to find yourself identifying with Marcel and his obsessive, jealous relationships, particularly with Albertine. It's the simulation. And you decide, I think, as a sentient being, how far to, in your own life, reenact these more profound experiences that others have written down. One of my earliest literary simulations was to reenact Jack Kerouac's trip in On the Road when I was 17, culminating in getting very wasted in the hanging gardens of Xochimilco, not to be missed. And it hit me just as I was reading Proust that that's really how to live a rich life, that one lives life, but one lives it juxtaposing one's own experience against the more refined experiences of the great writers. So, it gives me hope that my children do that a bit. LBW Do you include the Russian authors in the canon? MH Yes, I don't read Russian, but I was entirely obsessed with Russian literature as a schoolboy. I read my way through Dostoevsky, Tolstoy, Turgenev, Chekhov. I think of all of those writers, Tolstoy had the biggest impact because at the end of War and Peace, there's this great essay on historical determinism, which I think was the reason I became a historian. But I'm really temperamentally a kind of Turgenev person, oddly enough. I think if you haven't read those novelists, I mean, you can't really be a complete human being if you haven't read the Brothers Karamazov. You're not really grown up. And so, I think in many ways, those are the greatest novels. Raskolnikov's, remember Raskolnikov's Nightmare at the End of Crime and Punishment, in which he imagines in his dream a world in which a terrible virus spreads. Do you remember this? And this virus has the effect of making every individual think that what he believes is right. And in this self-righteousness, people fall on one another and commit appalling violence. That's Raskolnikov's Nightmare. And it's a prophecy. It's a terrible prophecy of Russia's future. Luke Steinem Yeah, and coupled with that is probably the, I also like the French, the existentialist, all that. The full spectrum, and German's Hermann Hessen, and just that range of human thought as expressed in the literature is fascinating. I really love your idea that the simulation, like one way to live life is to kind of explore these other worlds and borrow from them wisdom that you then just map onto your own life. You almost like stitch together your life with these kind of pieces from literature. IA The highly educated person is constantly struck by illusion. Everything is an illusion to something that one has read. And that is the simulation. That's what the real metaverse is. It's the imaginary world that we enter when we read, read, empathize, and then recognize in our daily lives some scrap of the shared experience that literature gives us. Luke Steinem Yeah, I think of Aspire to be the Idiot from Prince Mishkin from Dostoevsky, and in Aspiring to be that, I have become the idiot, I feel, at least in part. What, you mentioned the human condition, does love have to do? What role does it play in the human condition, friendship, love? Love is the drug. Luke Steinem Love is, this was the great Roxy Music line that Brian Ferry wrote, and love is the most powerful and dangerous of all the drugs. The driving force that overrides our reason, and of course, it is the primal, it's the primal urge. So, what a civilized society has to do is to prevent that drug, that primal force from creating mayhem. So, there have to be rules like monogamy and rituals like marriage that reign love in and make the addict at least more or less under control. And I think that's part of why I'm a romantic rather than a Steve Pinker enlightenment rationalist, because the romantics realize that love was the drug. It's like the difference in sensibility between Handel and Wagner. And I had a Wagnerian phase when I was an undergraduate. I still remember thinking that in, as old as Liebestod, that Wagner had got the closest to sex that anybody had ever got in music, or perhaps to love. I'm lucky that I love my wife and that we were, by the time we met, smart enough to understand that love is a drug that you have to kind of take in certain careful ways. And that it works best in the context of a stable family. That's the key thing, that one has to sort of take the drug and then submit to the conventions of marriage and family life. I think in that respect, I'm a kind of tamed romantic. LBW Tamed romantic. CB That's how I'd like to think of myself. LBW And the degree to which your romanticism is tamed can be then channeled into productive work. That's why you're a historian and a writer, is the process that love is channeled through the writing. CB So if you're going to be addicted to anything, be addicted to work. I mean, we're all addictive, but the thing about workaholism is that it is the most productive addiction. And rather that than drugs or booze. So I'm, yes, I'm always trying to channel my anxieties into work. I learned that at a relatively early age, it's a sort of massively productive way of coping with the inner demons. And again, we should teach kids that. Because let's come back to our earlier conversation about universities. Part of what happens at universities, the adolescents have to overcome all the inner demons. And these include deep insecurity about one's appearance, about one's intellect, and then madly raging hormones that cause you to behave like a complete fool with the people to whom you're sexually attracted. All of this is going on in the university. How can it be a safe space? It's a completely dangerous space by definition. So yeah, teaching young people how to manage these storms, that's part of the job. And we're really not allowed to do that anymore because we can't talk about these things anymore. For fear of the Title IX officers kicking down the door and dragging us off in chains. And like you said, hard work and something you call work ethic in civilization is a pretty effective way to achieve, I think, a kind of happiness in a world that's full of anxiety. Or at least exhaustion, so that you sleep well. Well, there is beauty to the exhaustion too. That's why running this manual work, that some part of us is built for that. Right. I mean, we are products of evolution and our adaptation to a technological world is a very imperfect one. So hence the kind of masochistic urge to run. I'd like outdoor exercise. I don't really like gyms. So I'll go for long punishing runs in woodland, hike up hills. I like swimming in lakes and in the sea because there just has to be that physical activity in order to do the good mental work. And so it's all about trying to do the best work. That's my sense that we have some random allocation of talent. You kind of figure out what it is that you're relatively good at and you try to do that well. I think my father encouraged me to think that way. And you don't mind about being average at the other stuff. The kind of sick thing is to try to be brilliant at everything. I hate those people. Should really not worry too much if you're just an average double bass player, which I am. Or kind of average skier, which I definitely am. Doing those things okay is part of leading a rich and fulfilling life. I was not a good actor, but I got a lot out of acting as an undergraduate. Turned out after three years of experimentation at Oxford that I was broadly speaking better at writing history essays than my peers. And that was my edge. That was my comparative advantage. And so I've just tried to make a living from that slight edge. Matthew That's a beautiful way to describe a life. Is there a meaning to this thing? Is there a meaning to life? What is the meaning of life? Richard I was brought up by a physicist and a physician. They were more or less committed atheists who had left the Church of Scotland as a protest against sectarianism in Glasgow. And so my sister and I were told from an early age life was a cosmic accident. And that was it. There was no great meaning to it. And I can't really get past that. Matthew Isn't there a beauty to being an accident at a cosmic scale? Richard Yes, I wasn't taught to feel negative about that. And if anything, it was a frivolous insight that the whole thing was a kind of joke. And I think that atheism isn't really a basis for ordering a society, but it's been all right for me. I don't have a sense of a missing religious faith. For me, however, there's clearly some embedded Christian ethics in the way my parents lived. And so we were kind of atheist Calvinists who had deposed God but carried on behaving as if we were members of the elect in a moral universe. So that's kind of the state of mind that I was left in. And I think that we aren't really around long enough to claim that our individual lives have meaning. But what Edmund Burke said is true, the real social contract is between the generations, between the dead, the living, and the unborn. And the meaning of life is, for me at least, to live in a way that honors the dead, seeks to learn from their accumulated wisdom because they do still outnumber us. They outnumber the living by quite a significant margin. And then to be mindful of the unborn and our responsibility to them. Writing books is a way of communicating with the unborn. It may or may not succeed, and probably won't succeed if my books are never assigned by woke professors in the future. So what we have to do is more than just write books and record podcasts, there have to be institutions. I'm 57 now. I realized recently that succession planning had to be the main focus of the next 20 years because there are things that I really care about that I want future generations to have access to. And so the meaning of life I do regard as being intergenerational transfer of wisdom. Ultimately, the species will go extinct at some point. Even if we do colonize Mars, one senses that physics will catch up with this particular organism, but it's in the pretty far distant future. And so the meaning of life is to make sure that for as long as there are human beings, they are able to live the kind of fulfilled lives, ethically fulfilled, intellectually fulfilled, emotionally fulfilled lives that civilization has made possible. It would be easy for us to revert to the uncivilized world. There's a fantastic book that I'm going to misremember, Miloš's The Captive Mind, which has a fantastic passage. He was a Polish intellectual who says, Americans can never imagine what it's like for civilization to be completely destroyed as it was in Poland by the end of World War II, to have no rule of law, to have no security of even person, never mind property rights. They can't imagine what that's like and what it will lead you to do. So one reason for teaching history is to remind the lucky Generation Z members of California that civilization is a thin film and it can be destroyed remarkably easily. And to preserve civilization is a tremendous responsibility that we have. It's a huge responsibility. And we must not destroy ourselves, whether it's in the name of wokeism or the pursuit of the metaverse. Preserving civilization and making it available, not just to our kids, but to people we'll never know, generations ahead, that's the meaning. LBW And do so by studying the lessons of history. MH Right. Not only studying them, but then acting on them. For me, the biggest problem is how do we apply history more effectively? It seems as if our institutions, including government, are very, very bad at applying history. Lessons of history are learned poorly, if at all. Analogies are drawn crudely. Often the wrong inferences are drawn. One of the big intellectual challenges for me is how to make history more useful. And this was the kind of thing that professors used to hate, but really practically useful so that policymakers and citizens can think about the decisions that they face with a more historically informed body of knowledge. Whether it's a pandemic, the challenge of climate change, what to do about Taiwan. I can't think of a better set of things to know before you make decisions about those things than the things that history has to offer. LBW Well, I love the discipline of applied history. Basically going to history and saying, what are the key principles here that are applicable to the problems of today? And how can we solve them? MH The great philosopher of history, R.G. Collingwood, said in his autobiography, which was published in 1939, that the purpose of history was to reconstitute past thought from whatever surviving remnants there were, and then to juxtapose it with our own predicament. And that's that juxtaposition of past experience with present experience that is so important. We don't do that well. And indeed, we've flipped it so that academic historians now think their mission is to travel back to the past with the value system of 2021 and castigate the dead for their racism and sexism and transphobia and whatnot. And that's exactly wrong. Our mission is to go back and try to understand what it was like to live in the 18th century, not to go back and condescend to the people of the past. And once we've had a better understanding, once we've seen into their lives, read their words, tried to reconstitute their experience to come back and understand our own time better. That's what we should really be doing. But academic history has gone completely haywire, and it does almost the exact opposite of what I think it should do. R.L. And by studying history, walk beautifully, gracefully through this simulation, as you described, by mapping the lessons of history into the world of today. R.G. We have virtual reality already in our heads. We do not need Oculus in the metaverse. This was an incredible, hopeful conversation in many ways that I did not expect. I thought our conversation would be much more about history than about the future, and it turned out to be the opposite. Thank you so much for talking today. It's a huge honor to finally meet you, to talk to you. Thank you for your valuable time. R.L. Thank you, Lex, and good luck with Putin. Lex May Thanks for listening to this conversation with Neil Ferguson. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Neil Ferguson himself. No civilization, no matter how mighty it may appear to itself, is indestructible. Thank you for listening, and hope to see you next time.

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Brian Kernighan: UNIX, C, AWK, AMPL, and Go Programming | Lex Fridman Podcast #109

The following is a conversation with Brian Kernighan, a professor of computer science at Princeton University. He was a key figure in the computer science community in the early UNIX days alongside UNIX creators Ken Thompson and Dennis Ritchie. He co-authored the C programming language with Dennis Ritchie, the creator of C, and has written a lot of books on programming, computers, and life, including The Practice of Programming, the Go programming language, and his latest, UNIX, a History and a Memoir. He co-created AWK, the text processing language used by Linux folks like myself. He co-designed Ample, an algebraic modeling language that I personally love and have used a lot in my life for large-scale optimization. I think I can keep going for a long time with his creations and accomplishments. Which is funny, because given all that, he's one of the most humble and kind people I've spoken to on this podcast. Quick summary of the ads. Two new sponsors. The amazing, self-cooling 8Sleep mattress and Raycon earbuds. Please consider supporting the podcast by going to 8sleep.com slash Lex and going to buyraycon.com slash Lex. Click the links, buy the stuff. It really is the best way to support this podcast and the journey I'm on. If you enjoy this thing, subscribe on YouTube, review it with Firestarz and Apple Podcasts, support it on Patreon, or connect with me on Twitter at Lex Friedman. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. This show is sponsored by 8Sleep and its incredible Pod Pro mattress that you can check out at 8sleep.com slash Lex to get $200 off. The mattress controls temperature with an app and can cool down to as low as 55 degrees. Research shows that temperature has a big impact on the quality of our sleep. Anecdotally, it's been a game changer for me. I love it. 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In fact, I often listen to brown noise with these when I'm thinking deeply about something. It helps me focus the mind. They're super comfortable, pair easily, great sound, great bass, six hours of playtime. In fact, for fun, I have one of the earbuds in now, and I'm listening to Europa by Santana, probably one of my favorite guitar songs. It kind of makes me feel like I'm in a music video. So, they told me to say that a bunch of celebrities use these, like Snoop Dogg, Melissa Etheridge, and Cardi B. I don't even know who Cardi B is, but her earbud game is on point. To mention celebrities I actually care about, I'm sure if Richard Feynman was still with us, he'd be listening to the Joe Rogan experience with Raycon earbuds. Get them at buyraycon.com slash Lex. It's how they know I sent you, and increases the chance that I'll support this podcast in the future. So, for all of the sponsors, click all of the links. It really helps this podcast. And now, here's my conversation with Brian Kernighan. Unix started being developed 50 years ago, maybe more than 50 years ago. Can you tell the story, like you describe in your new book, of how Unix was created? Huh. If I can remember that far back, it was some while ago. So, I think the gist of it is that at Bell Labs in 1969, there were a group of people who had just finished working on the Multics project, which was itself a follow-on to CTSS. So, we can go back sort of an infinite regress in time, but the CTSS was a very, very, very nice time-sharing system. It was very nice to use. I actually used it that summer I spent in Cambridge in 1966. What was the hardware there? So, what's the operating system? What's the hardware there? What's the CTSS look like? So, CTSS looked kind of like a standard time-sharing system. Certainly, at the time, it was the only time-sharing, if note. Let's go back to the basic. What's the time-sharing system? Okay. In the beginning was the word, and the word was itself. And then there was time-sharing systems. Yeah. If we go back into, let's call it the 1950s and early 1960s, most computing was done on very big computers, physically big, although not terribly powerful by today's standards, that were maintained in very large rooms. And you used things like punch cards to write your programs on, talk to them. So, you would take a deck of cards, write your program on it, send it over a counter, hand it to an operator, and some while later back would come something that said, oh, you made a mistake, and then you'd recycle. And so, it was very, very slow. So, the idea of time-sharing was that you take basically that same computer, but connect to it with something that looked like an electric typewriter. That could be a long distance away, it could be close. But fundamentally, what the operating system did was to give each person who was connected to it and wanting to do something a small slice of time to do a particular job. So, I might be editing a file, so I would be typing. And every time I hit a keystroke, the operating system would wake up and said, oh, he typed character, let me remember that. And then it'd go back to doing something else. So, it'd be going around and around a group of people who were trying to get something done, giving each a small slice of time and giving them each the illusion that they pretty much had the whole machine to themselves. And hence, time-sharing, that is sharing the computing time resource of the computer among a number of people who were doing it. Without the individual people being aware that there's others, in a sense, the illusion, the feeling is that the machine is your own. Pretty much that was the idea. Yes, you had, if it were well done, and if it were fast enough, and other people weren't doing too much, you did have the illusion that you had the whole machine to yourself. And it was very much better than the punch card model. And so, CTSS, the compatible time-sharing system, was, I think, arguably the first of these. It was done, I guess, technically in 64 or something like that. It ran on an IBM 7094, slightly modified to have twice as much memory as the norm. It had two banks of 32K words instead of one. So, it's just- 32K words. Yeah. Each word was 36 bits. So, call it about 150 kilobytes times two. So, by today's standards, that's down in the noise. But at the time, that was a lot of memory, and memory was expensive. So, CTSS was just a wonderful environment to work on. It was done by people at MIT, led by Fernando Corbato, Corby, who died just earlier this year, and a bunch of other folks. So, I spent the summer of 66 working on that. Had a great time, met a lot of really nice people, and indirectly knew of people at Bell Labs who were also working on a follow-on to CTSS that was called Multics. So, Multics was meant to be the system that would do everything that CTSS did, but do it better for a larger population. All the usual stuff. Now, the actual time-sharing, the scheduling, what's the algorithm that performs the scheduling? What's that look like? How much magic is there? What are the metrics? How does it all work in the beginning? So, the answer is I don't have a clue. I think the basic idea was nothing more than who all wants to get something done. Suppose that things are very quiet in the middle of the night, then I get all the time that I want. Suppose that you and I are contending at high noon for something like that, then probably the simplest algorithm is a round-robin one that gives you a bit of time, gives me a bit of time, and then we could adapt to that. Like, what are you trying to do? Are you text editing or are you compiling or something? And then we might adjust the scheduler according to things like that. So, okay. So, Multics was trying to just do some of the, clean it up a little bit. Well, it was meant to be much more than that. So, Multics was the multiplexed information and computing service, and it was meant to be a very large thing that would provide computing utility, something that where you could actually think of it as just a plug-in-the-wall service, sort of like cloud computing today. Same idea, but 50-odd years earlier. And so, what Multics offered was a richer operating system environment, a piece of hardware that was better designed for doing the kind of sharing of resources, and presumably lots of other things. Do you think people at that time had the dream of what cloud computing is starting to become now, which is computing is everywhere, that you can just plug in almost... And you never know how the magic works. You just kind of plug in, add your little computation that you need to perform, and it does it. Was that the dream? I don't know where that was the dream. I wasn't part of it at that point. Remember, I was an intern for a summer. But my sense is, given that it was over 50 years ago, yeah, they had that idea that it was an information utility, that it was something where if you had a computing task to do, you could just go and do it. Now, I'm betting that they didn't have the same view of computing for the masses, let's call it, the idea that your grandmother would be shopping on Amazon. I don't think that was part of it. But if your grandmother were a programmer, it might be very easy for her to go and use this kind of utility. What was your dream of computers at that time? What did you see as the future of computers? Because you have predicted what computers are today, in a sense. Oh, short answer, absolutely not. I have no clue. I'm not sure I had a dream. It was a dream job, in the sense that I really enjoyed what I was doing. I was surrounded by really, really nice people. Cambridge is a very fine city to live in in the summer, less so in the winter when it snows. But in the summer, it was a delightful time. And so I really enjoyed all of that stuff, and I learned things. And I think the good fortune of being there for summer led me then to get a summer job at Bell Labs the following summer. And that was quite useful for the future. So Bell Labs is this magical, legendary place. So first of all, where is Bell Labs? And can you start talking about that journey towards Unix at Bell Labs? Yeah. So Bell Labs is physically scattered around at the time, scattered around New Jersey. The primary location was in a town called Murray Hill, or a location called Murray Hill. It was actually across the boundary between two small towns in New Jersey called New Providence and Berkeley Heights. Think of it as about 15, 20 miles straight west of New York City, and therefore about an hour north of here in Princeton. And at that time, it had make up a number of 3,000 or 4,000 people there, many of whom had PhDs and mostly doing physical sciences, chemistry, physics, materials kinds of things, but very strong math and rapidly growing interest in computing as people realized you could do things with computers that you might not have been able to do before. You could replace labs with computers that had worked on models of what was going on. So that was the essence of Bell Labs. And again, I wasn't a permanent employee there. That was another internship. I got lucky in internships. I mean, if you could just linger on it a little bit, what was in the air there? Because some of the... the number of Nobel prizes, the number of Turing Awards and just legendary computer scientists that come from there, inventions, including developments, including Unix, it's just... it's unbelievable. So was there something special about that place? Oh, I think there was very definitely something special. I mentioned the number of people. It's a very large number of people, very highly skilled, and working in an environment where there was always something interesting to work on because the goal of Bell Labs, which was a small part of AT&T, which provided basically the country's phone service, the goal of AT&T was to provide service for everybody. And the goal of Bell Labs was to try and make that service keep getting better. So improving service. And that meant doing research on a lot of different things, physical devices like the transistor or fiber optical cables or microwave systems, all of these things the labs worked on. And it was kind of just the beginning of real boom times in computing as well. Because when I was there, I went there first in 66. So computing was at that point fairly young. And so people were discovering that you could do lots of things with computers. So how was Unix born? So Multics, in spite of having an enormous number of really good ideas, lots of good people working on it, fundamentally didn't live up, at least in the short run, and I think ultimately really ever, to its goal of being this information utility. It was too expensive. And certainly what was promised was delivered much too late. And so in roughly the beginning of 1969, Bell Labs pulled out of the project. The project at that point had included MIT, Bell Labs, and General Electric. General Electric made computers. So General Electric was the hardware operation. So Bell Labs, realizing this wasn't going anywhere on a timescale they cared about, pulled out of the project. And this left several people with an acquired taste for really, really nice computing environments, but no computing environment. And so they started thinking about what could you do if you were going to design a new operating system that would provide the same kind of comfortable computing as CTSS had, but also the facilities of something like Multics sort of brought forward. And so they did a lot of paper design stuff. And at the same time, Ken Thompson found what is characterized as a little used PDP-7, where he started to do experiments with file systems, just how do you store information on a computer in an efficient way? And then this famous story that his wife went away to California for three weeks, taking their one-year-old son, and three weeks, and he sat down and wrote an operating system, which ultimately became Unix. So he wrote Unix. So software productivity was good in those days. So PDP, what's a PDP-7? So it's a piece of hardware? Yeah, it's a piece of hardware. It was one of early machines made by Digital Equipment Corporation, DEC, and it was a mini computer, so-called. It had, I would have to look up the numbers exactly, but it had a very small amount of memory, maybe 16K, 16-bit words or something like that, relatively slow. Probably not super expensive, maybe, again, making this up, I'd have to look it up, $100,000 or something like that. Which is not super expensive in those days, right? It was expensive. It was enough that you and I probably wouldn't be able to buy one, but a modest group of people could get together. But in any case, it came out, if I recall, in 1964. So by 1969, it was getting a little obsolete, and that's why it was little used. If you can sort of comment, what do you think it's like to write an operating system like that? So that process that Ken went through in three weeks, because you were, I mean, you're part of that process. You contributed a lot to Unix's early development. So what do you think it takes to do that first step, that first kind of, from design to reality on the PDP? Well, let me correct one thing. I had nothing to do with it. So I did not write it. I have never written operating system code. And so I don't know. Now, an operating system is simply code. And this first one wasn't very big, but it's something that lets you run processes of some, lets you execute some kind of code that has been written. It lets you store information for periods of time so that it doesn't go away when you turn the power off or reboot or something like that. And there's kind of a core set of tools that are technically not part of an operating system, but you probably need them. In this case, Ken wrote an assembler for the PDP-7 that worked. He did a text editor so that he could actually create text. He had the file system stuff that he had been working on, and then the rest of it was just a way to load things, executable code from the file system into the memory, give it control, and then recover control when it was finished or in some other way quit. What was the code written in the primarily the programming language? Was it in assembly? Yeah, PDP-7 assembler that Ken created. These things were assembly language until probably the, call it 1973 or 74, something like that. Forgive me if it's a dumb question, but it feels like a daunting task to write any kind of complex system in assembly. Absolutely. It feels like impossible to do any kind of what we think of as software engineering with assembly, to work in a big picture. I think it's hard. It's been a long time since I wrote assembly language. It is absolutely true that in assembly language, if you make a mistake, nobody tells you. There are no training wheels whatsoever. And so stuff doesn't work. Now what? There's no debuggers. Well, there could be debuggers, but that's the same problem, right? How do you actually get something that will help you debug it? So part of it is an ability to see the big picture. Now, these systems were not big in the sense of today's picture. So the big picture was in some sense more manageable. I mean, then realistically, there's an enormous variation in the capabilities of programmers. And Ken Thompson, who did that first one, is kind of the singularity in my experience of programmers, with no disrespect to you or even to me. He's in several leagues removed. I know there's levels. It's a fascinating thing that there are unique stars in particular in the programming space and at a particular time. The time matters too, the timing of when that person comes along. And a wife does have to leave. There's this weird timing that happens, and then all of a sudden something beautiful is created. I mean, how does it make you feel that there's a system that was created in three weeks, or maybe you can even say on a whim, but not really, but of course quickly, that is now, you could think of most of the computers in the world run on a Unix-like system. Right. How do you, like, if you kind of zoom from the alien perspective, if you're just observing Earth, that all of a sudden these computers took over the world, and they started from this little initial seed of Unix, how does that make you feel? It's quite surprising. And you asked earlier about prediction. The answer is no. There's no way you could predict that kind of evolution. And I don't know whether it was inevitable or just a whole sequence of blind luck, I suspect more of the latter. And so I look at it and think, gee, that's kind of neat. I think the real question is what does Ken think about that? Because he's the guy arguably from whom it really came, you know, tremendous contributions from Dennis Ritchie and then others around in that Bell Labs environment. But you know, if you had to pick a single person, that would be Ken. So you've written a new book, Unix, a history and a memoir. Are there some memorable human stories, funny or profound from that time that just kind of stand out? Oh, there's a lot of them in a sense. And again, it's a question of can you resurrect them in real time? Memory fails. But I think part of it was that Bell Labs at the time was a very special kind of place to work because there were a lot of interesting people and the environment was very, very open and free. It was a very cooperative environment, very friendly environment. And so if you had an interesting problem, you go and talk to somebody and they might help you with the solution. And it was a kind of a fun environment too in which people did strange things and often tweaking the bureaucracy in one way or another. So rebellious in certain kinds of ways. In some ways, yeah, absolutely. I think most people didn't take too kindly to the bureaucracy and I'm sure the bureaucracy put up with an enormous amount that they didn't really want to. So maybe to linger on it a little bit, do you have a sense of what the philosophy that characterizes Unix is? The design, not just the initial, but just carry through the years, being there, being around it. What's the fundamental philosophy behind the system? I think one aspect, the fundamental philosophy was to provide an environment that made it easy to write or easier, productive to write programs. So it was meant as a programmer environment. It wasn't meant specifically as something to do some other kind of job. For example, it was used extensively for word processing, but it wasn't designed as a word processing system. It was used extensively for lab control, but it wasn't designed for that. It was used extensively as a front end for big other systems, big dumb systems, but it wasn't designed for that. It was meant to be an environment where it was really easy to write programs. So the programmers could be highly productive. And part of that was to be a community. And there's some observation from Dennis Ritchie, I think at the end of the book, it says that from his standpoint, the real goal was to create a community where people could work as programmers on a system. And I think in that sense, certainly for many, many years, it succeeded quite well at that. And part of that is the technical aspects of, because it made it really easy to write programs, people did write interesting programs. Those programs tended to be used by other programmers. And so it was kind of a virtuous circle of more and more stuff coming up that was really good for programmers. And you were part of that community of programmers. So what was it like writing programs in that early Unix? It was a blast. It really was. I like to program. I'm not a terribly good programmer, but it was a lot of fun to write code. And in the early days, there was an enormous amount of what you would today, I suppose, call low hanging fruit. People hadn't done things before. And this was this new environment and the whole combination of nice tools and very responsive system and tremendous colleagues made it possible to write code. You could have an idea in the morning, you could do an experiment with it. You could have something limping along that night or the next day and people would react to it and they would say, oh, that's wonderful, but you're really screwed up here. And the feedback loop was then very, very short and tight. And so a lot of things got developed fairly quickly that in many cases still exist today. And I think that was part of what made it fun because programming itself is fun. It's puzzle solving in a variety of ways, but I think it's even more fun when you do something that somebody else then uses. Even if they whine about it not working, the fact that they used it is part of the reward mechanism. And what was the method of interaction, the communication, that feedback loop? I mean, this is before the internet. Certainly before the internet. It was mostly physical right there, somebody would come into your office and say something. So these places are all close by, like offices are nearby, so you're really lively in interaction. Yeah, yeah. No, Bell Labs was fundamentally one giant building and most of the people were involved in this Unix stuff were in two or three quarters and there was a room. Oh, how big was it? Probably call it 50 feet by 50, make up a number of that, which had some access to computers there as well as in offices and people hung out there and it had a coffee machine. And so it was mostly very physical. We did use email, of course, but it was fundamentally for a long time all on one machine, so there was no need for internet. It's fascinating to think about what computing would be today without Bell Labs. It seems so many people being in the vicinity of each other, sort of getting that quick feedback, working together, so many brilliant people. I don't know where else that could have existed in the world, given how that came together. How does that make you feel, that little element of history? Well, I think that's very nice, but in a sense it's survivor bias and if it hadn't happened at Bell Labs, there were other places that were doing really interesting work as well. Xerox PARC is perhaps the most obvious one. Xerox PARC contributed an enormous amount of good material and many of the things we take for granted today in the same way came from Xerox PARC experience. I don't think they capitalized in the long run as much. Their parent company was perhaps not as lucky in capitalizing on this. Who knows? But that's certainly another place where there was a tremendous amount of influence. There were a lot of good university activities. MIT was obviously no slouch in this kind of thing and others as well. So, Unix turned out to be open source because of the various ways that AT&T operated and sort of it had to, the focus was on telephones. I think that's a mischaracterization in a sense. It absolutely was not open source. It was very definitely proprietary, licensed, but it was licensed freely to universities in source code form for many years. And because of that, generations of university students and their faculty people grew up knowing about Unix and there was enough expertise in the community that it then became possible for people to kind of go off in their own direction and build something that looked Unix-like. The Berkeley version of Unix started with that licensed code and gradually picked up enough of its own code contributions, notably from people like Bill Joy, that eventually it was able to become completely free of any AT&T code. Now, there was an enormous amount of legal jockeying around this in the late, early to late 80s, early 90s, something like that. And then, I guess the open source movement might've started when Richard Stallman started to think about this in the late 80s. And by 1991, when Torvalds decided he was going to do a Unix-like operating system, there was enough expertise in the community that first he had a target. He could see what to do because the kind of the Unix system call interface and the tools and so on were there. And so he was able to build an operating system that at this point, when you say Unix, in many cases, what you're really thinking is Linux. Yeah. But it's funny that from my distant perception, I felt that Unix was open source without actually knowing it. But what you're really saying, it was just freely licensed. It was freely licensed. So it felt open source because universities are not trying to make money. So it felt open source in a sense that you can get access if you wanted. Right. And a very, very, very large number of universities had the license and they were able to talk to all the other universities who had the license. And so technically not open, technically belonging to AT&T, pragmatically pretty open. And so there's a ripple effect that all the faculty and the students then all grew up and then they went throughout the world and permeated in that kind of way. So what kind of features do you think make for a good operating system? If you take the lessons of Unix, you said, make it easy for programmers. That seems to be an important one. But also Unix turned out to be exceptionally robust and efficient. Right. So is that an accident when you focus on the programmer or is that a natural outcome? I think part of the reason for efficiency was that it began on extremely modest hardware, very, very, very tiny. And so you couldn't get carried away. You couldn't do a lot of complicated things because you just didn't have the resources, either processor speed or memory. And so that enforced a certain minimality of mechanisms and maybe a search for generalizations so that you would find one mechanism that served for a lot of different things rather than having lots of different special cases. I think the file system in Unix is a good example of that. The file system interface in its fundamental form is extremely straightforward. And that means that you can write code very, very effectively for the file system. And then one of those generalizations is that, gee, that file system interface works for all kinds of other things as well. And so in particular, the idea of reading and writing to devices is the same as reading and writing to a disk that has a file system. And then that gets carried further in other parts of the world. Processes become, in effect, files in a file system. And the Plan 9 operating system, which came along, I guess, in the late 80s or something like that, took a lot of those ideas from the original Unix and tried to push the generalization even further so that in Plan 9, a lot of different resources are file systems. They all share that interface. So that would be one example where finding the right model of how to do something means that an awful lot of things become simpler. And it means, therefore, that more people can do useful, interesting things with them without having to think as hard about it. So you said you're not a very good programmer. True. You're the world's most modest human being. Okay, but you'll continue saying that. I understand how this works. But you do radiate a sort of love for programming. So let me ask, do you think programming is more an art or a science? Is it creativity or kind of rigor? I think it's some of each. It's some combination. Some of the art is figuring out what it is that you really want to do. What should that program be? What would make a good program? And that's some understanding of what the task is, what the people who might use this program want. And I think that's art in many respects. The science part is trying to figure out how to do it well. And some of that is real computer science-y stuff, like what algorithm should we use at some point, mostly in the sense of being careful to use algorithms that will actually work properly, scale properly, avoiding quadratic algorithms when a linear algorithm should be the right thing. That kind of more formal view of it. Same thing for data structures. But also it's, I think, an engineering field as well. And engineering is not quite the same as science, because engineering, you're working with constraints. You have to figure out not only so what is a good algorithm for this kind of thing, but what's the most appropriate algorithm given the amount of time we have to compute, the amount of time we have to program, what's likely to happen in the future with maintenance, who's going to pick this up in the future, all of those kind of things that if you're an engineer, you get to worry about. Whereas if you think of yourself as a scientist, well, you can maybe push them over the horizon in a way. And if you're an artist, what's that? So, just on your own personal level, what's your process like writing a program? Say, small and large, sort of tinkering with stuff. Do you just start coding right away and just kind of evolve iteratively with a loose notion? Or do you plan on a sheet of paper first and then kind of design what they teach you in the kind of software engineering courses in undergrad or something like that? What's your process like? It's certainly much more the informal incremental. First, I don't write big programs at this point. It's been a long time since I wrote a program that was more than, I call it a few hundred or more lines, something like that. Many of the programs I write are experiments for either something I'm curious about or often for something that I want to talk about in a class. And so, those necessarily tend to be relatively small. A lot of the kind of code I write these days tends to be for sort of exploratory data analysis where I've got some collection of data and I want to try and figure out what on earth is going on in it. And for that, those programs tend to be very small. Sometimes you're not even programming, you're just using existing tools like counting things. Or sometimes you're writing ox scripts because two or three lines will tell you something about a piece of data. And then when it gets bigger, well, then I will probably write something in Python because that scales better up to, call it a few hundred lines or something like that. And it's been a long time since I wrote programs that were much more than that. Speaking of data exploration and awk, first, what is awk? So awk is a scripting language that was done by myself, El Aho and Peter Weinberger. We did that originally in the late 70s. It was a language that was meant to make it really easy to do quick and dirty tasks like counting things or selecting interesting information from basically all text files, rearranging it in some way or summarizing it. It runs a command on each line of a file. I mean, it's still exceptionally widely used today. Oh, absolutely. Yeah. And it's so simple and elegant. Sort of the way to explore data, turns out you can just write a script that does something seemingly trivial on a single line. And that giving you that slice of the data somehow reveals something fundamental about the data. Yeah. And that keeps, that seems to work still. Yeah. It's very good for that kind of thing. And that's sort of what it was meant for. I think what we didn't appreciate was that the model was actually quite good for a lot of data processing kinds of tasks and that it's kept going as long as it has. Because at this point it's over 40 years old and it's still, I think, a useful tool. And well, this is paternal interest, I guess, but I think in terms of programming languages, you get the most bang for the buck by learning AUC. And it doesn't scale to big programs, but it does pretty darn well on these little things where you just want to see all the somethings in something. And so, yeah, I find I probably write more AUC than anything else at this point. So what kind of stuff do you love about AUC? If you can comment on sort of things that give you joy when you can, in a simple program, reveal something about the data. Is there something that stands out from particular features? I think it's mostly the selection of default behaviors that you sort of hinted at a moment ago. What AUC does is to read through a set of files and then within each file it reads through each of the lines. And then on each of the lines, it has a set of patterns that it looks for, that's your AUC program. And if one of the patterns matches, there is a corresponding action that you might perform. And so it's kind of a quadruply nested loop or something like that. And that's all completely automatic. You don't have to say anything about it. You just write the pattern and the action and then run the data by it. And so that paradigm for programming is a very natural and effective one. And I think we captured that reasonably well in AUC. And it does other things for free as well. It splits the data into fields so that on each line, there's fields separated by white space or something. And so it does that for free. You don't have to say anything about it. And it collects information as it goes along, like what line are we on? How many fields are there on this line? So lots of things that just make it so that a program which in another language, let's say Python, would be five, 10, 20 lines in AUC is one or two lines. And so because it's one or two lines, you can do it on the shell. You don't have to open up another whole thing. You can just do it right there in the interaction with the operatives directly. Is there other shell commands that you love over the years, like you really enjoy using? Oh, grep. Grep's the only one. Yeah, grep does everything. So grep is a kind of a, what is it, a simpler version of AUC, I would say? In some sense, yeah, right. Because- What is grep? So grep is, it basically searches the input for particular patterns, regular expressions, technically, of a certain class. And it has that same paradigm that AUC does. It's a pattern action thing. It reads through all the files and then all the lines in each file, but it has a single pattern, which is the regular expression you're looking for, and a single action printed, if it matches. So in that sense, it's a much simpler version, and you could write grep in AUC as a one-liner. And I use grep probably more than anything else at this point, just because it's so convenient and natural. Why do you think, it's such a powerful tool, grep and AUC. Why do you think operating systems like Windows, for example, don't have it? You can, of course, I use, which is amazing now, there's Windows for Linux, which you could basically use all the fun stuff, like AUC and grep inside of Windows. But Windows naturally, as part of the graphical interface, the simplicity of grep, sort of searching through a bunch of files and just popping up naturally. Why do you think that's unique to the Unix and Linux environment? I don't know. It's not strictly unique, but it's certainly focused there. And I think some of it's the weight of history that Windows came from, MS-DOS. MS-DOS was a pretty pathetic operating system, although common on an unboundedly large number of machines, but somewhere in roughly the 90s, Windows became a graphical system. And I think Microsoft spent a lot of their energy on making that graphical interface what it is. And that's a different model of computing. It's a model of computing that where you point and click and sort of experiment with menus. It's a model of computing works rather well for people who are not programmers, who just want to get something done. Whereas teaching something like the command line to non-programmers turns out to sometimes be an uphill struggle. And so I think Microsoft probably was right in what they did. Now you mentioned Whistle or whatever it's called, the Linux. Whistle. I wonder what it's pronounced. W-S-L is what, I've never actually pronounced the Whistle. I like it. I have no idea. But there have been things like that for a long, a Cygwin, for example, which is a wonderful collection of take all your favorite tools from Unix and Linux and just make them work perfectly on Windows. And so that's something that's been going on for at least 20 years, if not longer. And I use that on my one remaining Windows machine routinely because if you're doing something that is batch computing, suitable for command line, that's the right way to do it because the Windows equivalents are, if nothing else, not familiar to me. But I should, I would definitely recommend to people to, if they don't use Cygwin, to try Whistle. Yes. I've been so excited that I could use bash, write scripts quickly in Windows. It's changed my life. Okay. What's your perfect programming setup? What computer, what operating system, what keyboard, what editor? Yeah. Perfect is too strong a word. It's way too strong a word. What I use by default, I have a, at this point, a 13 inch MacBook Air, which I use because it's kind of a reasonable balance of the various things I need. I can carry it around. It's got enough computing horsepower, screens big enough, keyboard's okay. And so I basically do most of my computing on that. I have a big iMac in my office that I use from time to time as well, especially when I need a big screen, but otherwise it tends not to be used as much. Editor. I use mostly SAM, which is an editor that Rob Pike wrote long ago at Bell Labs. Did that, sorry to interrupt, does that precede VI? Does that precede Emacs? It post dates both VI and Emacs. It is derived from Rob's experience with ED and VI. What's ED? That's the original Unix editor. Oh, wow. Dated probably before you were born. So what's, actually, what's the history of editors? Can you briefly, because this is your, I use Emacs, I'm sorry to say. Sorry to come out with that. But what's the kind of interplay there? So SAM, yeah, it's going to be VI. So in ancient times, like call it the first time-sharing systems going back to what we were talking about, there were editors. There was an editor on CTSS that I don't even remember what it was called. It might've been edit, where you could type text, program text, and it would do something or document text. You could save the text. And save it. You could edit it. The usual thing that you would get in an editor. And Ken Thompson wrote an editor called QED, which was very, very powerful. But these were all totally a command-based. They were not mouse or cursor-based, because it was before mice and even before cursors, because they were running on terminals that printed on paper. Okay. No CRT type displays, let alone LEDs. And so then when Unix came along, Ken took QED and stripped it way, way, way, way down. And that became an editor that he called ED. And it was very simple, but it was a line-oriented editor. And so you could load a file and then you could talk about the lines one through the last line, and you could print ranges of lines. You could add text, you could delete text, you could change text, or you could do a substitute command that would change things within a line or within groups of lines. So you can work on parts of a file, essentially. Yeah. You could work on any part of it, the whole thing or whatever. But it was entirely command-line based and it was entirely on paper. Okay. Paper. And that meant that you changed- Actual paper. Yeah, right. Real paper. And so if you changed a line, you had to print that line using up another line of paper to see what the change caused. Okay. Yeah. It's amazing. So when CRT displays came along, then you could start to use cursor control and you could sort of move where you were on the screen in- Without reprinting every time. Without reprinting. And there were a number of editors there. The one that I was most familiar with and still use is VI, which was done by Bill Choi. And so that dates from probably the late 70s as a guess, and it took full advantage of the cursor controls. I suspected Emacs was roughly at the same time, but I don't know. I've never internalized Emacs. So I use, at this point, I stopped using ED, although I still can. I use VI sometimes, and I use SAM when I can. And SAM is available on most systems? It is available. You have to download it yourself from typically the plan nine operating system distribution. It's been maintained by people there. And so I- I'll get home tonight. I'll try it. It's cool. It sounds fascinating. Although my love is with Lisp and Emacs. I've went into that hippie world of- I think it's a lot of things. What religion were you brought up with? Yeah, that's true. That's true. Most of the actual programming I do is C, C++, and Python, but my weird sort of, yeah, my religious upbringing is in Lisp. So can you take on the impossible task and give a brief history of programming languages from your perspective? So I guess you could say programming languages started probably in what, the late 40s or something like that. People used to program computers by basically putting in zeros and ones using something like switches on a console, and then, or maybe holes in paper tapes, something like that. So extremely tedious, awful, whatever. And so I think the first programming languages were relatively crude assembly languages where people would basically write a program that would convert mnemonics like add, A-D-D, into whatever the bit pattern was that corresponded to an add instruction. And they would do the clerical work of figuring out where things were. So you could put a name on a location in a program and the assembler would figure out where that corresponded to when the thing was all put together and dropped into memory. And early on, and this would be the late 40s and very early 50s, there were assemblers written for the various machines that people used. You may have seen in the paper just a couple of days ago, Tony Berker died. He did this thing in Manchester called AutoCode, a language which I knew well only by name, but it sounds like it was a flavor of assembly language, sort of a little higher in some ways. And it replaced a language that Alan Turing wrote, which you put in zeros and ones, but you put it in backwards order because that was hardware work. Very strange. That's right. Yeah, yeah, that's right. It's backwards. So assembly languages, then let's call that the early 1950s. And so every different flavor of computer has its own assembly language. So the EdSac had its, and the Manchester had its, and the IBM, whatever, 7090 or 704 or whatever had its, and so on. So everybody had their own assembly language. And assembly languages have a few commands, additions, subtraction, then branching of some kind, if then type of situation. Right. They have exactly, in their simplest form at least, one assembly language instruction per instruction in the machine's repertoire. And so you have to know the machine intimately to be able to write programs in it. And if you write an assembly language program for one kind of machine, and then you say, geez, it's nice, I'd like it in a different machine, start over. Okay. So very bad. And so what happened in the late 50s was people realized you could play this game again, and you could move up a level in writing or creating languages that were closer to the way that real people might think about how to write code. And there were, I guess, arguably three or four at that time period. There was Fortran, which came from IBM, which was formula translation, meant to make it easy to do scientific and engineering computations. I didn't know that, formula translation. That's wow. That's what it stood for. There was COBOL, which is the common business-oriented language that Grace Hopper and others worked on, which was aimed at business kinds of tasks. There was ALGOL, which was mostly meant to describe algorithmic computations. I guess you could argue BASIC was in there somewhere. I think it's just a little later. And so all of those moved the level up. And so they were closer to what you and I might think of as we were trying to write a program. And they were focused on different domains, Fortran for formula translation, engineering computations, let's say COBOL for business, that kind of thing. And still used today, at least Fortran probably. Oh yeah. COBOL too. COBOL. But the deal was that once you moved up that level, then you, let's call it Fortran, you had a language that was not tied to a particular kind of hardware, because a different compiler would compile for a different kind of hardware. And that meant two things. It meant you only had to write the program once, which was very important. And it meant that you could, in fact, if you were a random engineer, physicist, whatever, you could write that program yourself. You didn't have to hire a programmer to do it for you. Might not be as good as you'd get with a real programmer, but it was pretty good. And so it democratized and made much more broadly available the ability to write code. So it puts the power of programming into the hands of people like you. Yeah. Anybody who is willing to invest some time in learning a programming language and is not then tied to a particular kind of computer. And then in the 70s, you get system programming languages, of which C is the survivor. And- What does system programming languages mean? Programs that, programming languages that would take on the kinds of things that were necessary to write so-called system programs, things like text editors or assemblers or compilers or operating systems themselves, those kinds of things. And for- Let's be feature rich. They have to be able to do a lot of stuff, a lot of memory management, access processes, and all that kind of stuff. They have to- Parallel processing. It's a different flavor of what they're doing. They're much more in touch with the actual machine, but in a positive way. That is, you can talk about memory in a more controlled way. You can talk about the different data types that the machine supports and the way they're- And more ways to structure and organize data. And so the system programming languages, there was a lot of effort in that in the, call it the late 60s, early 70s. C is, I think, the only real survivor of that. And then what happens after that, you get things like object-oriented programming languages, because as you write programs in a language like C, at some point, scale gets to you and it's too hard to keep track of the pieces and there's no guardrails or training wheels or something like that to prevent you from doing bad things. So C++ comes out of that tradition. And then it took off from there. I mean, there's also a parallel, parallel, slightly parallel track with a little bit of the functional stuff with Lisp and so on. But I guess from that point, it's just an explosion of languages. There's the Java story, there's the JavaScript, there's all the stuff that the cool kids these days are doing with Rust and all that. So what's to use? You wrote a book, C programming language. And C is probably one of the most important languages in the history of programming languages, if you kind of look at impact. What do you think is the most elegant or powerful part of C? Why did it survive? Why did it have such a long lasting impact? I think it found a sweet spot of expressiveness, that you could really write things in a pretty natural way, and efficiency, which was particularly important when computers were not nearly as powerful as they are today. You've got to put yourself back 50 years, almost in terms of what computers could do. That's roughly four or five generations, decades of Moore's law. Right. So expressiveness and efficiency, and I don't know, perhaps the environment that it came with as well, which was Unix. So it meant if you wrote a program, it could be used on all those computers that ran Unix. And that was all of those computers, because they were all written in C, and that way, Unix, the operating system itself was portable, as were all the tools. So it all worked together, again, in one of these things where things fed on each other in a positive cycle. What did it take to write sort of a definitive book, probably definitive book on all of programming? It's more definitive to a particular language than any other book on any other language, and did two really powerful things, which is popularized the language, at least from my perspective, maybe you can correct me, and second is created a standard of how this language is supposed to be used and applied. So what did it take? Did you have those kinds of ambitions in mind when working on that? Is this some kind of joke? No, of course not. So it's an accident of a timing skill and just luck. A lot of it is clearly, timing was good. Now, Dennis and I wrote the book in 1977. Dennis Ritchie. Yeah, right. And at that point, Unix was starting to spread. I don't know how many there were, but it would be dozens to hundreds of Unix systems. And C was also available on other kinds of computers that had nothing to do with Unix. And so the language had some potential. And there were no other books on C, and Bell Labs was really the only source for it. And Dennis, of course, was authoritative because it was his language. And he had written the reference manual, which is a marvelous example of how to write a reference manual. Really, really very, very well done. So I twisted his arm until he agreed to write a book, and then we wrote a book. And the virtue or advantage, at least, I guess, of going first is that then other people have to follow you if they're going to do anything. And I think it worked well because Dennis was a superb writer. I mean, he really, really did. And the reference manual in that book is his, period. I had nothing to do with that at all. So just crystal clear prose, very, very well expressed. And then he and I, I wrote most of the expository material, and then he and I wrote the book. And then he and I sort of did the usual ping-ponging back and forth, refining it. But I spent a lot of time trying to find examples that would sort of hang together and that would tell people what they might need to know at about the right time that they should be thinking about needing it. And I'm not sure it completely succeeded, but it mostly worked out fairly well. What do you think is the power of example? I mean, you're the creator, or at least one of the first people to do the Hello World program, which is like the example. If aliens discover our civilization hundreds of years from now, it'll probably be Hello World programs, just like a half-broken robot communicating with them with the Hello World. And that's a representative example. So what do you find powerful about examples? I think a good example will tell you how to do something, and it will be representative of you might not want to do exactly that, but you will want to do something that's at least in that same general vein. And so a lot of the examples in the C book were picked for these very, very simple, straightforward text processing problems that were typical of Unix. I want to read input and write it out again. There's a copy command. I want to read input and do something to it and write it out again. There's a grab. And so that kind of find things that are representative of what people want to do and spell those out so that they can then take those and see the core parts and modify them to their taste. And I think that a lot of programming books that I don't look at programming books a tremendous amount these days, but when I do, a lot of them don't do that. They don't give you examples that are both realistic and something you might want to do. Some of them are pure syntax. Here's how you add three numbers. Well, come on, I could figure that out. Tell me how I would get those three numbers into the computer and how it would do something useful with them and then how I put them back out again, neatly formatted. And especially if you follow the example, there is something magical of doing something that feels useful. Yeah, right. And I think it's the attempt, and it's absolutely not perfect, but the attempt in all cases was to get something that was going to be either directly useful or would be very representative of useful things that a programmer might want to do. But within that vein of fundamentally text processing, reading text, doing something, writing text. So you've also written a book on Go language. I have to admit, so I worked at Google for a while and I've never used Go. Well, you missed something. Well, I know I missed something for sure. So Go and Rust are two languages that I hear spoken very highly of and I wish I would like to... Well, there's a lot of them. There's Julia, there's all these incredible modern languages. But if you can comment before, well, maybe comment on what do you find, where does Go sit in this broad spectrum of languages? And also, how do you yourself feel about this wide range of powerful, interesting languages that you may never even get to try to explore because of time? So I think Go first comes from that same Bell Labs tradition in part, not exclusively, but two of the three creators, Ken Thompson and Rob Pike. So literally the people. Yeah, the people. And then with this very, very useful influence from the European school, in particular, the Klaus Spirth influence through Robert Griesemer, who was, I guess, a second generation down student at ETH. And so that's an interesting combination of things. And so some ways Go captures the good parts of C, it looks sort of like C, it's sometimes characterized as C for the 21st century. On the surface, it looks very, very much like C. But at the same time, it has some interesting data structuring capabilities. And then I think the part that I would say is particularly useful, and again, I'm not a Go expert in spite of co-authoring the book, about 90% of the work was done by Alan Donovan, my co-author, who is a Go expert. But Go provides a very nice model of concurrency. It's basically the cooperating, communicating sequential processes that Tony Hoare set forth, geez, I don't know, 40 plus years ago. And Go routines are, to my mind, a very natural way to talk about parallel computation. And in the few experiments I've done with them, they're easy to write, and typically it's going to work, and very efficient as well. So I think that's one place where Go stands out, that that model of parallel computation is very, very easy and nice to work with. Just to comment on that, do you think C foresaw, or the early Unix days foresaw, threads and massively parallel computation? I would guess not really. I mean, maybe it was seen, but not at the level where it was something you had to do anything about. For a long time, processors got faster. And then processors stopped getting faster because of things like power consumption and heat generation. And so what happened instead was that instead of processors getting faster, there started to be more of them. And that's where that parallel thread stuff comes in. So if you can comment on all the other languages, does it break your heart that you'll never get to explore them? Or how do you feel about the full variety? It's not break my heart, but I would love to be able to try more of these languages. The closest I've come is in a class that I often teach in the spring here. It's a programming class. And I often then give, I have one sort of small example that I will write in as many languages as I possibly can. I've got it in 20 odd languages at this point. And that's so I do a minimal experiment with a language just to say, okay, I have this trivial task, which I understand the task, and it takes 15 lines in awk and not much more in a variety of other languages. So how big is it? How fast does it run? And what pain did I go through to learn how to do it? And that's a, it's like anic data, right? It's very, very, very narrowly focused. Anic data, I like that term. So yeah, but still, it's a little sample because you get to, I think the hardest step of the programming language is probably the first step, right? So there you're taking the first step. Yeah. And so my experience with some languages is very positive, like Lua, a scripting language I never used. And I took my little program. The program is a trivial formatter. It just takes in lines of text of varying lengths, and it puts them out in lines that have no more than 60 characters on each line. So think of it as just kind of the flow of process in a browser or something. So it's a very short program. And in Lua, I downloaded Lua and in an hour I had it working, never having written Lua in my life, just going with online documentation. I did the same thing in Scala, which you can think of as a flavor of Java, equally trivial. I did it in Haskell. It took me several weeks, but it did run like a turtle. And I did it in Fortran 90 and it's painful, but it worked. And I tried it in Rust and it took me several days to get it working because the model of memory management was just a little unfamiliar to me. And the problem I had with Rust, and it's back to what we were just talking about, I couldn't find good, consistent documentation on Rust. Now this was several years ago and I'm sure things have stabilized, but at the time, everything in the Rust world seemed to be changing rapidly. And so you would find what looked like a working example and it wouldn't work with the version of the language that I had. So it took longer than it should have. Rust is a language I would like to get back to, but probably won't. I think one of the issues, you have to have something you want to do. If you don't have something that is the right combination, if I want to do it and yet I have enough disposable time, whatever, to make it worth learning a new language at the same time, it's never going to happen. So what do you think about another language of JavaScript that's this... Well, let me just sort of comment on what I said. What I was brought up, sort of JavaScript was seen as the probably like the ugliest language possible. And yet, it's quite arguably, quite possibly taking over, not just the front end, the back end of the internet, but possibly in the future taking over everything because they've now learned to make it very efficient. And so what do you think about this? Yeah, well, I think you captured it in a lot of ways. When it first came out, JavaScript was deemed to be fairly irregular and an ugly language. And certainly in the academy, if you said you were working on JavaScript, people would ridicule you. It was just not fit for academics to work on. I think a lot of that has evolved. The language itself has evolved and certainly the technology of compiling it is fantastically better than it was. And so in that sense, it's absolutely a viable solution on back ends as well as the front ends. Used well, I think it's a pretty good language. I've written a modest amount of it and I've played with JavaScript translators and things like that. I'm not a real expert and it's hard to keep up even there with the new things that come along with it. So I don't know whether it will ever take over the world. I think not, but it's certainly an important language and worth knowing more about. Maybe to get your comment on something, which JavaScript and actually most languages, Python, such a big part of the experience of programming with those languages includes libraries. So using, building on top of the code that other people have built. I think that's probably different from the experience that we just talked about from Unix and C days, when you're building stuff from scratch. What do you think about this world of essentially leveraging, building up libraries on top of each other and leveraging them? Yeah, that's a very perceptive kind of question. One of the reasons programming was fun in the old days was that you were really building it all yourself. The number of libraries you had to deal with was quite small. Maybe it was print F or the standard library or something like that. And that is not the case today. And if you want to do something in, you mentioned Python and JavaScript, and those are the two fine examples. You have to typically download a boatload of other stuff and you have no idea what you're getting. Absolutely nothing. I've been doing some playing with machine learning over the last couple of days and geez, something doesn't work. Well, you pip install this, okay? And down comes another gazillion megabytes of something and you have no idea what it was. And if you're lucky it works. And if it doesn't work, you have no recourse. There's absolutely no way you could figure out which in these thousand different packages. And I think it's worse in the NPM environment for JavaScript. I think there's less discipline, less control there. And there's aspects of not just not understanding how it works, but there's security issues, there's robustness issues. So you don't want to run a nuclear power plant using JavaScript essentially. Probably not. So speaking to the variety of languages, do you think that variety is good or do you hope, think that over time we should converge towards one, two, three programming languages? You mentioned to the Bell Lab days when people could sort of the community of it. And the more languages you have, the more you separate the communities. There's the Ruby community, there's the Python community, there's C++ community. Do you hope that they'll unite one day to just one or two languages? I certainly don't hope it. I'm not sure that that's right. Because I honestly don't think there is one language that will suffice for all the programming needs of the world. Are there too many at this point? Well, arguably. But I think if you look at the sort of the distribution of how they are used, there's something called a dozen languages that probably account for 95% of all programming at this point. And that doesn't seem unreasonable. And then there's another, well, 2000 languages that are still in use that nobody uses and or at least don't use in any quantity. But I think new languages are good idea in many respects because they're often a chance to explore an idea of how a language might help. I think that's one of the positive things about functional languages. For example, they're a particularly good place where people have explored ideas that at the time didn't seem feasible, but ultimately have wound up as part of mainstream languages as well. I mean, you can go back as early as recursion and Lisp and then follow forward functions as first-class citizens and pattern-based languages and, gee, I don't know, closures and just on and on and on. Lambda's interesting ideas that showed up first in, let's call it broadly, the functional programming community and then find their way into mainstream languages. Yeah, it's a playground for rebels. Yeah, exactly. And so, I think the languages in the playground themselves are probably not going to be the mainstream, at least for some while, but the ideas that come from there are invaluable. So, let's go to something that when I found out recently, so I've known that you've done a million things, but one of the things I wasn't aware of that you had a role in ample, and before you interrupt me by minimizing your role in it, which- Ample is for minimizing functions. Yeah, minimizing functions, right, exactly. Can I just say that the elegance and abstraction power of ample is incredible? When I first came to it about 10 years ago or so, can you describe what is the ample language? Sure. So, ample is a language for mathematical programming, technical term. Think of it as linear programming, that is setting up systems of linear equations that are some sort of system of constraints so that you have a bunch of things that have to be less than this, greater than that, whatever. And you're trying to find a set of values for some decision variables that will maximize or minimize some objective function. So, it's a way of solving a particular kind of optimization problem, a very formal sort of optimization problem, but one that's exceptionally useful. And it specifies, so there's objective function constraints and variables that become separate from the data it operates on. So, that kind of separation allows you to put on different hats. One put the hat of an optimization person and then put another hat of a data person and dance back and forth and also separate the actual solvers, the optimization systems that do the solving. Then you can have other people come to the table and then build their solvers, whether it's linear or non-linear, convex, non-convex, that kind of stuff. So, what is the, to use, maybe you can comment how you got into that world and what is the beautiful or interesting idea to you from the world of optimization? Sure. So, I preface it by saying I'm absolutely not an expert on this. And most of the important work in AMPL comes from my two partners in crime on that, Bob Forer, who was a professor in the Industrial Engineering and Management Science Department at Northwestern, and my colleague at Bell Labs, Dave Gay, who was a numerical analyst and optimization person. So, the deal is linear programming, preface this by saying- Let's stay with linear programming. Yeah, linear programming is the simplest example of this. So, linear programming, as it's taught in school, is that you have a big matrix, which is always called A, and you say AX is less than or equal to B. So, B is a set of constraints, X is the decision variables, and A is how the decision variables are combined to set up the various constraints. So, A is a matrix and X and B are vectors. And then there's an objective function, which is just a sum of a bunch of Xs and some coefficients on them, and yet that's the thing you want to optimize. The problem is that in the real world, that matrix A is a very, very, very intricate, very large, and very sparse matrix where the various components of the model are distributed among the coefficients in a way that is totally unobvious to anybody. And so, what you need is some way to express the original model, which you and I would write, we'd write mathematics on the board, the sum of this is greater than the sum of that kind of thing. So, you need a language to write those kinds of constraints. And Bob Forer for a long time had been interested in modeling languages, languages that made it possible to do this. There was a modeling language around called GAMS, the General Algebraic Modeling System, but it looked very much like Fortran. It was kind of clunky. And so, Bob spent a sabbatical year at Bell Labs in 1984, and he and, he was in the office across from me, and it's always geography, and he and Dave Gay and I started talking about this kind of thing. And he wanted to design a language that would make it so that you could take these algebraic specifications, you know, summation, sines, oversets, and that you would write on the board and convert them into basically this A matrix, and then pass that off to a solver, which is an entirely separate thing. And so, we talked about the design of the language. I don't remember any of the details of this now, but it's kind of an obvious thing. You're just writing out mathematical expressions in a Fortran-like, or sorry, an algebraic, but textual-like language. And I wrote the first version of this AMPL program, my first C++ program. And- That's written in C++? Yeah. Oh, wow. And so, I did that fairly quickly. We wrote, it was, you know, 3,000 lines or something, so it wasn't very big, but it sort of showed the feasibility of it that you could actually do something that was easy for people to specify models and convert it into something that a solver could work with. At the same time, as you say, the model and the data are separate things. So, one model would then work with all kinds of different data in the same way that lots of programs do the same thing, but with different data. So, one of the really nice things is the specification of the models, human, just kind of like, as you say, is human-readable. Like, I literally, I remember on stuff I worked, I would send it to colleagues that I'm pretty sure never programmed in their life, just to understand what the optimization problem is. I think, how hard is it to convert that? You said there's a first prototype in C++ to convert that into something that could actually be used by the solver. It's not too bad because most of the solvers have some mechanism that lets them import a model in a form. It might be as simple as the matrix itself in just some representation, or if you're doing things that are not linear programming, then there may be some mechanism that lets you provide things like functions to be called or other constraints on the model. So, all Ample does is to generate that kind of thing, and then solver deals with all the hard work. And then when the solver comes back with numbers, Ample converts those back into your original form, so you know how much of each thing you should be buying or making or shipping or whatever. So, we did that in 84, and I haven't had a lot to do with it since, except that we wrote a couple of versions of a book on it. Which is one of the greatest books ever written. I love that book. I don't know why. It's an excellent book. Bob Forer wrote most of it, and so it's really, really well done. He must have been a dynamite teacher. And typeset in LaTeX. No, no, no. Are you kidding? I remember you liking the typography, so I don't know. We did it with TROF. I don't even know what that is. Yeah, exactly. You're too young. Oh, boy. Think of TROF as a predecessor to the tech family of things. It's a formatter that was done at Bell Labs in this same period of the very early 70s that predates tech and things like that by five to ten years. But it was nevertheless, I'm going by memories. I remember it being beautiful. Yeah, it was nicely done. Outside of Unix, C, Ogg, Golang, all the things we talked about, all the amazing work you've done, you've also done work in graph theory. Let me ask this crazy out there question. If you had to make a bet, and I had to force you to make a bet, do you think P equals NP? The answer is no, although I'm told that somebody asked Jeff Dean if that was, under what conditions P would equal NP, and he said either P is zero or N is one. Or vice versa, I've forgotten. This is why Jeff Dean is a lot smarter than I am. Yeah. But your intuition is... I have no intuition, but I've got a lot of colleagues who've got intuition, and their betting is no. That's the popular bet. Okay, so what is computational complexity theory, and do you think these kinds of complexity classes, especially as you've taught in this modern world, are still a useful way to understand the hardness of problems? I don't do that stuff. The last time I touched anything to do with that was- Many, many years ago. Was before it was invented. It's literally true. I did my PhD thesis on graph- Before big O notation. Oh, absolutely. I did this in 1968, and I worked on graph partitioning, which is this question, you've got a graph that is a nodes and edges kind of graph, and the edges have weights, and you just want to divide the nodes into two piles of equal size, so that the number of edges that goes from one side to the other is as small as possible. And we- You developed, so that problem is hard? Well, as it turns out, I worked with Shen Lin at Bell Labs on this, and we were never able to come up with anything that was guaranteed to give the right answer. We came up with heuristics that worked pretty darn well, and I peeled off some special cases for my thesis, but it was just hard. And that was just about the time that Steve Cook was showing that there were classes of problems that appeared to be really hard, of which graph partitioning was one. But this, my expertise, such as it was, totally predates that development. Oh, interesting. So the heuristic, which now carries the two of yours names for the traveling salesman problem and for the graph partitioning, that was, like, how did you- You weren't even thinking in terms of classes. You were just trying to find- There was no such idea. A heuristic that kind of does the job pretty well. You were trying to find something that did the job, and there was no- nothing that you would call, let's say, a closed form or algorithmic thing that would give you a guaranteed right answer. I mean, compare graph partitioning to max flow min cut or something like that. That's the same problem, except there's no constraint on the number of nodes on one side or the other of the cut. And that means it's an easy problem, at least as I understand it. Whereas the constraint that says the two have to be constrained in size makes it a hard problem. Yeah, so Robert Frost has that poem where you have to choose two paths. So why did you- Is there another alternate universe in which you pursued the Don Knuth path of algorithm design? Not smart enough. Not smart enough. You're infinitely modest. But so you pursued your kind of love of programming. I mean, when you look back to those, I mean, just looking into that world, does that just seem like a distant world of theoretical computer science? Then is it fundamentally different from the world of programming? I don't know. I mean, certainly, in all seriousness, I just didn't have the talent for it. When I got here as a grad student at Princeton and I started to think about research at the end of my first year or something like that, I worked briefly with John Hopcroft, who was absolutely, you know, you mentioned during award winner, et cetera, a great guy. And it became crystal clear, I was not cut out for this stuff, period. Okay. And so I moved into things where I was more cut out for it. And that tended to be things like writing programs and then ultimately writing books. You've said that in Toronto as an undergrad, you did a senior thesis or a literature survey on artificial intelligence. This was 1964. Correct. What was the AI landscape, ideas, dreams at that time? I think that was one of the, well, you've heard of AI winters. This is whatever the opposite was, AI summer or something. It was one of these things where people thought that, boy, we could do anything with computers, that all these hard problems, we could, computers will solve them. They will do machine translation. They will play games like chess. They will do, you know, prove theorems in geometry. There are all kinds of examples like that where people thought, boy, we could really do those sorts of things. And, you know, I read the Kool-Aid in some sense. I still have this wonderful collection of papers called Computers and Thought that was published in about that era. And people were very optimistic. And then of course, it turned out that what people had thought was just a few years down the pike was more than a few years down the pike. And some parts of that are more or less now sort of under control. We finally do play games like go and chess and so on better than people do. But there are others, and machine translation is a lot better than it used to be, but that's, you know, 50, close to 60 years of progress and a lot of evolution in hardware and a tremendous amount more data upon which you can build systems that actually can learn from some of that. And the infrastructure to support developers working together, like an open source movement, the internet period is also an empowering. But what lessons do you draw from that, the opposite of winter, that optimism? Well, I guess the lesson is that in the short run, it's pretty easy to be too pessimistic, or maybe too optimistic. And in the long run, you probably shouldn't be too pessimistic. I'm not saying that very well. It reminds me of this remark from Arthur Clarke, a science fiction author, who says, you know, when some distinguished but elderly person says that something is possible, he's probably right. And if he says it's impossible, he's almost surely wrong. But you don't know what the timescale is. The timescale is critical, right. So, what are your thoughts on this new summer of AI now in the work with machine learning and neural networks? You've kind of mentioned that you started to try to explore and look into this world that seems fundamentally different from the world of heuristics and algorithms like search, that it's now purely sort of trying to take huge amounts of data and learn from that data, right? Programs from the data. Yeah. Look, I think it's very interesting. I am incredibly far from an expert. Most of what I know I've learned from my students, and they're probably disappointed in how little I've learned from them. But I think it has I think it has tremendous potential for certain kinds of things. I mean, games is one where it obviously has had an effect on some of the others as well. I think there's, and this is speaking from definitely not expertise, I think there are serious problems in certain kinds of machine learning, at least because what they're learning from is the data that we give them. And if the data we give them has something wrong with it, then what they learn from it is probably wrong, too. And the obvious thing is some kind of bias in the data, that the data has stuff in it, like, I don't know, women aren't as good as men at something, okay? That's just flat wrong. But if it's in the data because of historical treatment, then that machine learning stuff will propagate that. And that is a serious worry. The positive part of that is what machine learning does is reveal the bias in the data and puts a mirror to our own society. And in so doing, helps us remove the bias, you know, helps us work on ourselves, puts a mirror to ourselves. Yeah, that's an optimistic point of view. And if it works that way, that would be absolutely great. And what I don't know is whether it does work that way, or whether the AI mechanisms or machine learning mechanisms reinforce and amplify things that have been wrong in the past. And I don't know, but I think that's a serious thing that we have to be concerned about. Let me ask you an out there question. Okay, I know nobody knows, but what do you think it takes to build a system of human level intelligence? That's been the dream from the 60s. We talk about games, about language, about image recognition, but really the dream is to create human level, or superhuman level intelligence. What do you think it takes to do that? And are we close? I haven't a clue and I don't know, roughly speaking. I mean, this was... I was trying to trick you into hypothesizing. Yeah, I mean, Turing talked about this in his paper on machine intelligence back in, geez, I don't know, early 50s or something like that. And he had the idea of the Turing test. And I don't know whether the Turing test is... Is a good test of intelligence. I don't know. It's an interesting test. At least it's in some vague sense objective, whether you can read anything into the conclusions is a different story. Do you have worries, concerns, excitement about the future of artificial intelligence? So there's a lot of people who are worried. And you can speak broadly than just artificial intelligence. It's basically computing taking over the world in various forms. Are you excited by this future, this possibility of computing being everywhere? Or are you worried? It's some combination of those. I think almost all technologies over the long run are for good, but there's plenty of examples where they haven't been good, either over a long run for some people or over a short run. And computing is one of those and AI within it is going to be one of those as well. But computing broadly, I mean, for just a today example is privacy, that the use of things like social media and so on means that... And the commercial surveillance means that there's an enormous amount more known about us by people, other businesses, government, whatever, than perhaps one ought to feel comfortable with. So that's an example. So that's an example of a possible negative effect of computing being everywhere. It's an interesting one because it could also be a positive if leveraged correctly. There's a big if there. So I have a deep interest in human psychology and humans seem to be very paranoid about this data thing, but that varies depending on age group. It seems like the younger folks, so it's exciting to me to see what society looks like 50 years from now, that the concerns about privacy might be flipped on their head based purely on human psychology versus actual concerns or not. What do you think about Moore's law? You said a lot of stuff we've talked about with programming languages in their design, in their ideas, come from the constraints in the systems they operate in. Do you think Moore's law, the exponential improvement of systems will continue indefinitely? There's a mix of opinions on that currently. Or do you think there'll be a plateau? Well, the frivolous answer is no exponential can go on forever. You run out of something. Just as we said, timescale matters. So if it goes on long enough, that might be all we need. Yeah, right. Won't matter to us. So I don't know. We've seen places where Moore's law has changed. For example, mentioned earlier, processors don't get faster anymore, but you use that same growth of ability to put more things in a given area to go horizontally instead of vertically, as it were. So you can get more and more processors or memory or whatever on the same chip. Is that going to run into a limitation? Presumably, because at some point you get down to the individual atoms. And so you've got to find some way around that. Will we find some way around that? I don't know. I just said that if I say it won't, I'll be wrong. Perhaps we will. So I just talked to Jim Keller and he says, so he actually describes, he argues that the Moore's law will continue for a long, long time because you mentioned the atom. We actually have, I think, a thousand fold increase, decrease in transistor size still possible before we get to the quantum level. So there's still a lot of possibilities. He thinks it'll continue indefinitely, which is an interesting, optimistic viewpoint. But how do you think the programming languages will change with this increase? Whether we hit a wall or not, what do you think? Do you think there'll be a fundamental change in the way programming languages are designed? I don't know about that. I think what will happen is continuation of what we see in some areas, at least, which is that more programming will be done by programs than by people. And that more will be done by sort of declarative rather than procedural mechanisms where I say, I want this to happen. You figure out how. And that is in many cases at this point, domain of specialized languages for narrow domains, but you can imagine that broadening out. And so I don't have to say so much in so much detail, some collection of software, let's call it languages or programs or something, will figure out how to do what I want to do. Interesting. So increased levels of abstraction. And one day getting to the human level where we can just use natural language. Could be possible. So you taught, still teach a course, Computers in Our World here at Princeton that introduces computing and programming to non-majors. Just from that experience, what advice do you have for people who don't know anything about programming, but are kind of curious about this world where programming seems to become more and more of a fundamental skill that people need to be at least aware of? Yeah. Well, I can recommend a good book. What's that? The book I wrote for the course. I think this is one of these questions of should everybody know how to program? And I think the answer is probably not, but I think everybody should at least understand sort of what it is so that if you say to somebody, I'm a programmer, they have a notion of what that might be. Or if you say this is a program or this was decided by a computer running a program that they have some vague intuitive understanding and accurate understanding of what that might imply. So part of what I'm doing in this course, which is very definitely for non-technical people, I mean, typical person in it is a history or English major, try and explain how computers work, how they do their thing, what programming is, how you write a program and how computers talk to each other and what do they do when they're talking to each other. And then I would say nobody very rarely, and it does anybody in that course go on to become a real serious programmer, but at least they've got a somewhat better idea of what all this stuff is about, not just the programming, but the technology behind computers and communications. Do they try and write a program themselves? Oh yeah, yeah, a very small amount. I introduced them to how machines work at a level below high level languages. So we have a kind of a toy machine that has a very small repertoire, a dozen instructions, and they write trivial assembly language programs for that. Really? Wow. So can you just, if you were to give a flavor to people of the programming world, of the computing world, what are the examples they should go with? So a little bit of assembly to get a sense at the lowest level of what the program is really doing? Yeah, I mean, in some sense, there's no such thing as a lowest level because you can keep going down, but that's the place where I drew the line. So the idea that computers have a fairly small repertoire of very simple instructions that they can do, like add and subtract and branch and so on, as you mentioned earlier, and that you can write code at that level and it will get things done. And then you have the levels of abstraction that we get with higher level languages, like Fortran or C or whatever, and that makes it easier to write the code and less dependent on particular architectures. And then we talk about a lot of the different kinds of programs that they use all the time that they don't probably realize are programs, like they're running Mac OS on their computers or maybe Windows, and they're downloading apps on their phones, and all of those things are programs that are just what we just talked about, except at a grand scale. Yeah, it's easy to forget that they're actual programs that people programmed, there's engineers that wrote those things. Yeah, right. And so in a way, I'm expecting them to make an enormous conceptual leap from their five or 10 line toy assembly language thing that adds two or three numbers to something that is a browser on their phone or whatever, but it's really the same thing. So if you look in broad strokes at history, what do you think the world, like how do you think the world changed because of computers? It's hard to sometimes see the big picture when you're in it, but I guess I'm asking if there's something you've noticed over the years that, like you were mentioning, the students are more distracted looking at their, now there's a device to look at. Right. Well, I think computing has changed a tremendous amount, obviously, but I think one aspect of that is the way that people interact with each other, both locally and far away. And when I was the age of those kids, making a phone call to somewhere was a big deal because it cost serious money and this was in the sixties, right? And today people don't make phone calls, they send texts or something like that. So there's a up and down in what people do. People think nothing of having correspondence, regular meetings, video, whatever, with friends or family or whatever in any other part of the world. And they don't think about that at all. And so that's just the communication aspect of it. And... Do you think that brings us closer together or does it make us, does it take us away from the closeness of human to human contact? I think it depends a lot on all kinds of things. So I trade mail with my brother and sister in Canada much more often than I used to talk to them on the phone. So probably every two or three days I get something or send something to them. Whereas 20 years ago, I probably wouldn't have talked to them on the phone nearly as much. So in that sense, that's brought my brother and sister and I closer together. That's a good thing. I watch the kids on campus and they're mostly walking around with their heads down, fooling with their phones to the point where I have to duck them. Yeah. I don't know that that has brought them closer together in some ways. There's sociological research that says people are in fact not as close together as they used to be. I don't know whether that's really true, but I can see potential downsides and kids where you think, come on, wake up and smell the coffee or whatever. That's right. But if you look at, again, nobody can predict the future, but are you excited, I kind of touched this a little bit with AI, but are you excited by the future in the next 10, 20 years that computing will bring? You were there when there was no computers really, and now computers are everywhere, all over the world, in Africa and Asia and just every person, almost every person in the world has a device. So are you hopeful, optimistic about that future? I'm, it's mixed, if the truth be told. I mean, I think there are some things about that that are good. I think there's the potential for people to improve their lives all over the place, and that's obviously good. And at the same time, at least in the short time, short run, you can see lots and lots of bad as people become more tribalistic or parochial in their interests, and it's an enormous amount more us and them. And people are using computers in all kinds of ways to mislead or misrepresent or flat out lie about what's going on. And that is affecting politics locally, and I think everywhere in the world. Yeah, the long-term effect on political systems and so on, it's who knows. Who knows indeed. The people now have a voice, which is a powerful thing. People who are oppressed have a voice, but also everybody has a voice. And the chaos that emerges from that is fascinating to watch. Yeah, yeah. It's kind of scary. If you can go back and relive a moment in your life, one that made you truly happy outside of family, or was profoundly transformative, is there a moment or moments that jump out at you from memory? I don't think specific moments. I think there were lots and lots and lots of good times at Bell Labs where you would build something and it worked. Just it worked. So the moment it worked. Yeah. And somebody used it and they said, gee, that's neat. Those kinds of things happened quite often in that sort of golden era in the 70s when Unix was young, and there was all this low-hanging fruit and interesting things to work on. And a group of people who kind of, we were all together in this, and if you did something, they would try it out for you. And I think that was in some sense a really, really good time. And awk was awk an example of that? Yeah, sure. When you built it and people used it? Yeah, absolutely. And now millions of people use. And all your stupid mistakes are right there for them to look at. Right. So it's mixed. Yeah. It's terrifying vulnerable, but it's beautiful because it does have a positive impact on so, so many people. So I think there's no better way to end. And Brian, thank you so much for talking to me. It was an honor. Okay. My pleasure. Good fun. Thank you for listening to this conversation with Brian Kernighan. And thank you to our sponsors, 8sleep Mattress and Raycon Earbuds. Please consider supporting this podcast by going to 8sleep.com slash Lex and to buy Raycon.com slash Lex. Click the links, buy the stuff. These both are amazing products. It really is the best way to support this podcast and the journey I'm on. It's how they know I sent you and increases the chance that they'll actually support this podcast in the future. If you enjoy this thing, subscribe on YouTube, review it with Firestarz and Apple Podcasts, support on Patreon or connect with me on Twitter at Lex Friedman, spelled somehow miraculously without the letter E, just F-R-I-D-M-A-N, because when we immigrated to this country, we were not so good at spelling. And now let me leave you with some words from Brian Kernighan. Don't comment bad code, rewrite it. Thank you for listening and hope to see you next time.

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Risto Miikkulainen: Neuroevolution and Evolutionary Computation | Lex Fridman Podcast #177

The following is a conversation with Risto Mikulainen, a computer scientist at University of Texas at Austin, and Associate Vice President of Evolutionary Artificial Intelligence at Cognizant. He specializes in evolutionary computation, but also many other topics in artificial intelligence, cognitive science, and neuroscience. Quick mention of our sponsors, Jordan Harbinger Show, Grammarly, Belcampo, and Indeed. Check them out in the description to support this podcast. As a side note, let me say that nature-inspired algorithms, from ant colony optimization to generic algorithms to cellular automata to neural networks, have always captivated my imagination, not only for their surprising power in the face of long odds, but because they always opened up doors to new ways of thinking about computation. It does seem that in the long arc of computing history, running toward biology, not running away from it, is what leads to long-term progress. This is the Lex Friedman Podcast, and here is my conversation with Risto Mikulainen. If we ran the Earth experiment, this fun little experiment we're on, over and over and over and over a million times, and watched the evolution of life as it pans out, how much variation in the outcomes of that evolution do you think we would see? Now, we should say that you are a computer scientist. That's actually not such a bad question for computer scientists, because we are building simulations of these things, and we are simulating evolution, and that's a difficult question to answer in biology, but we can build a computational model and run it a million times, and actually answer that question, how much variation do we see when we simulate it? And that's a little bit beyond what we can do today, but I think that we will see some regularities, and it took evolution also a really long time to get started, and then things accelerated really fast towards the end. But there are things that need to be discovered, and they probably will be over and over again, like manipulation of objects, opposable thumbs, and also some way to communicate, maybe orally, like when you have speech, it might be some other kind of sound, and decision-making, but also vision. Eye has evolved many times. Various vision systems have evolved. So we would see those kinds of solutions, I believe, emerge over and over again. They may look a little different, but they get the job done. The really interesting question is, would we have primates? Would we have humans, or something that resembles humans? And would that be an apex of evolution after a while? We don't know where we're going from here, but we certainly see a lot of tool use and building, constructing our environment. So I think that we will get that. We get some evolution producing some agents that can do that, manipulate the environment and build. What do you think is special about humans? Like if you were running the simulation, and you observe humans emerge, like these tool makers, they start a fire, and all that stuff, start running around, building buildings, and then running for president, all those kinds of things. What would be, how would you detect that? Because you're like really busy as the creator of this evolutionary system, so you don't have much time to observe, like detect if any cool stuff came up, right? How would you detect humans? Well, you are running the simulation, so you also put in visualization and measurement techniques there. So if you are looking for certain things, like communication, you'll have detectors to find out whether that's happening, even if it's a lot simulation. And I think that that's what we would do. We know roughly what we want, intelligent agents that communicate, cooperate, manipulate, and we would build detections and visualizations of those processes. Yeah, and there's a lot of, you'd have to run it many times, and we have plenty of time to figure out how we detect the interesting things. But also, I think we do have to run it many times because we don't quite know what shape those will take. And our detectors may not be perfect for them to begin with. Well, that seems really difficult to build the detector of intelligent or intelligent communication. Sort of, if we take an alien perspective, observing Earth, are you sure that they would be able to detect humans as the special thing? Wouldn't they be already curious about other things? There's way more insects by body mass, I think, than humans by far, and colonies. Obviously, dolphins is the most intelligent creature on Earth, we all know this. So, it could be the dolphins that they detect. It could be the rockets that we seem to be launching. That could be the intelligent creature they detect. It could be some other trees. Trees have been here a long time. I just learned that sharks have been here 400 million years, and that's longer than trees have been here. So, maybe it's the sharks, they go by age. Like, there's a persistent thing. Like, if you survive long enough, especially through the mass extinctions, that could be the thing your detector is detecting. Humans have been here a very short time, and we're just creating a lot of pollution, but so is the other creatures. So, I don't know. Do you think you would be able to detect humans? Like, how would you go about detecting, in the computational sense, maybe we can leave humans behind, in the computational sense, detect interesting things? Do you basically have to have a strict objective function by which you measure the performance of a system, or can you find curiosities and interesting things? Yeah, well, I think the first measurement would be to detect how much of an effect you can have in your environment. So, if you look around, we have cities, and that is constructed environments, and that's where a lot of people live, most people live. So, that would be a good sign of intelligence, that you don't just live in an environment, but you construct it to your liking. And that's something pretty unique. I mean, certainly birds build nests and all, but they don't build quite cities. Termites build mounds and hives and things like that, but the complexity of the human construction cities, I think, would stand out, even to an external observer. Of course, that's what a human would say. Yeah, and you can certainly say that sharks are really smart because they've been around so long and they haven't destroyed their environment, which humans are about to do, which is not a very smart thing. But we'll get over it, I believe. And we can get over it by doing some construction that actually is benign and maybe even enhances the resilience of nature. So, you mentioned the simulation that we run over and over and it's a slow start. So, do you think how unlikely, first of all, I don't know if you think about this kind of stuff, but how unlikely is step number zero, which is the springing up, like the origin of life on earth? And second, how unlikely is anything interesting happening beyond that? Sort of like the start that creates all the rich complexity that we see on earth today. Yeah, there are people who are working on exactly that problem from primordial soup. How do you actually get self-replicating molecules? And they are very close. With a little bit of help, you can make that happen. So, of course, we know what we want, so they can set up the conditions and try out conditions that are conducive to that. For evolution to discover that, it took a long time. For us to recreate it probably won't take that long. And the next steps from there, I think also with some handholding, I think we can make that happen. But with evolution, what was really fascinating was eventually the runaway evolution of the brain that created humans and created, well, also other higher animals. That was something that happened really fast. And that's a big question. Is that something replicable? Is that something that can happen? And if it happens, does it go in the same direction? That is a big question to ask. Even in computational terms, I think that it's relatively possible to come up here, create an experiment where we look at the primordial soup and the first couple of steps of multicellular organisms even. But to get something as complex as the brain, we don't quite know the conditions for that and how to even get started and whether we can get this kind of runaway evolution happening. From a detector perspective, if we're observing this evolution, what do you think is the brain? What do you think is the, let's say, what is intelligence? So in terms of the thing that makes humans special, we seem to be able to reason, we seem to be able to communicate, but the core of that is this something in the broad category we might call intelligence. So if you put your computer scientist hat on, is there favorite ways you like to think about that question of what is intelligence? Well, my goal is to create agents that are intelligent. Not to define what. And that is a way of defining it. And that means that it's some kind of an object or a program that has limited sensory and effective capabilities interacting with the world. And then also a mechanism for making decisions. So with limited abilities like that, can it survive? Survival is the simplest goal, but you could also give it other goals. Can it multiply? Can it solve problems that you give it? And that is quite a bit less than human intelligence. There are, animals would be intelligent, of course, with that definition. And you might have even some other forms of life. So intelligence in that sense is a survival skill given resources that you have and using your resources so that you will stay around. Do you think death, mortality is fundamental to an agent? So like there's, I don't know if you're familiar, there's a philosopher named Ernest Becker who wrote the Denial of Death and his whole idea. And there's folks, psychologists, cognitive scientists that work on terror management theory. And they think that one of the special things about humans is that we're able to sort of foresee our death, right? We can realize not just as animals do sort of constantly fear in an instinctual sense, respond to all the dangers that are out there, but like understand that this ride ends eventually. And that in itself is the most, is the force behind all of the creative efforts of human nature. That's the philosophy. I think that makes sense. A lot of sense. I mean, animals probably don't think of death the same way, but humans know that your time is limited and you wanna make it count. And you can make it count in many different ways, but I think that has a lot to do with creativity and the need for humans to do something beyond just surviving. And now going from that simple definition to something that's the next level, I think that that could be at the second decision, a second level of definition that intelligence means something and you do something that stays behind you. That's more than your existence. Something you create something that is useful for others, is useful in the future, not just for yourself. And I think that's a nice definition of intelligence in a next level. And it's also nice because it doesn't require that they are humans or biological. They could be artificial agents that are intelligence. They could achieve those kind of goals. So particular agent, the ripple effects of their existence on the entirety of the system is significant. So like they leave a trace where there's like a, yeah, like ripple effects. But see, then you go back to the butterfly with the flap of a wing, and then you can trace a lot of like nuclear wars and all the conflicts of human history, somehow connected to that one butterfly that created all the chaos. So maybe that's not, maybe that's a very poetic way to think. That's something we humans in a human centric way wanna hope we have this impact. Like that is the secondary effect of our intelligence. We've had that long lasting impact on the world, but maybe the entirety of physics in the universe has a very long lasting effect. Sure, but you can also think of it, what if like the wonderful life, what if you're not here? Will somebody else do this? Is it something that you actually contributed because you had something unique to contribute? That's a pretty high bar though. Uniqueness, yeah. Yeah, so you have to be Mozart or something to actually reach that level. Nobody would have developed that, but other people might have solved this equation if you didn't do it. But also within limited scope, I mean, during your lifetime or next year, you could contribute something that unique that other people did not see. And then that could change the way things move forward for a while. So I don't think we have to be Mozart to be called intelligence, but we have this local effect that is changing. If you weren't there, that would not have happened. And it's a positive effect, of course, you want it to be a positive effect. Do you think it's possible to engineer in to computational agents a fear of mortality? Like, does that make any sense? So there's a very trivial thing where it's like, you could just code in a parameter, which is how long the life ends, but more of a fear of mortality, like awareness of the way that things end and somehow encoding a complex representation of that fear, which is like, maybe as it gets closer, you become more terrified. I mean, there seems to be something really profound about this fear that's not currently encodable in a trivial way into our programs. Well, I think you're referring to the emotion of fear, something, because we have cognitively, we know that we have limited lifespan and most of us cope with it by just, hey, that's what the world is like, and I make the most of it. But sometimes you can have like a fear that's not healthy, that paralyzes you, that you can't do anything. And somewhere in between there, not caring at all and getting paralyzed because of fear is a normal response, which is a little bit more than just logic and it's emotion. So now the question is what good are emotions? I mean, they are quite complex and there are multiple dimensions of emotions and they probably do serve a survival function, heightened focus, for instance. And fear of death might be a really good emotion when you are in danger, that you recognize it. Even if it's not logically necessarily easy to derive and you don't have time for that logical deduction, you may be able to recognize the situation is dangerous and this fear kicks in and you all of a sudden perceive the facts that are important for that. And I think that's generally is the role of emotions. It allows you to focus what's relevant for your situation. And maybe fear of death plays the same kind of role, but if it consumes you and it's something that you think in normal life when you don't have to, then it's not healthy and then it's not productive. Yeah, but it's fascinating to think how to incorporate emotion into a computational agent. It almost seems like a silly statement to make, but it perhaps seems silly because we have such a poor understanding of the mechanism of emotion, of fear. I think at the core of it is another word that we know nothing about, but say a lot, which is consciousness. Do you ever in your work or like maybe on a coffee break, think about what the heck is this thing consciousness and is it at all useful in our thinking about AI systems? Yes, it is an important question. You can build representations and functions, I think, into these agents that act like emotions and consciousness, perhaps. So I mentioned emotions being something that allow you to focus and pay attention, filter out what's important. Yeah, you can have that kind of a filter mechanism and it puts you in a different state. Your computation is in a different state. Certain things don't really get through and others are heightened. Now you label that box emotion. I don't know if that means it's an emotion, but it acts very much like we understand what emotions are. And we actually did some work like that, modeling hyenas who were trying to steal a kill from lions, which happens in Africa. I mean, hyenas are quite intelligent, but not really intelligent. And they have this behavior that's more complex than anything else they do. They can band together if there's about 30 of them or so, they can coordinate their effort so that they push the lions away from a kill, even though the lions are so strong that they could kill a hyena by striking with a paw. But when they work together and precisely time this attack, the lions will leave and they get the kill. And probably there are some states, like emotions that the hyenas go through. The first day they call for reinforcements. They really want that kill, but there's not enough of them. So they vocalize and there's more people, more hyenas that come around. And then they have two emotions. They are very afraid of the lion. So they want to stay away, but they also have a strong affiliation between each other. And then this is the balance of the two emotions. And also, yes, they also want the kill. So it's both repelled and attractive. But then this affiliation eventually is so strong that when they move, they move together, they act as a unit and they can perform that function. So there's an interesting behavior that seems to depend on these emotions strongly and makes it possible to coordinate the actions. And I think a critical aspect of that, the way you're describing is emotion there is a mechanism of social communication, of social interaction. Maybe humans won't even be that intelligent, or most things we think of as intelligent wouldn't be that intelligent without the social component of interaction. Maybe much of our intelligence is essentially an outgrowth of social interaction. And maybe for the creation of intelligent agents, we have to be creating fundamentally social systems. Yes, I strongly believe that's true. And yes, the communication is multifaceted. I mean, they vocalize and call for friends, but they also rub against each other and they push and they do all kinds of gestures and so on. So they don't act alone. And I don't think people act alone very much either, at least normal most of the time. And social systems are so strong for humans that I think we build everything on top of these kinds of structures. And one interesting theory around that, bigotous theory, for instance, for language, for language origins is that where did language come from? And it's a plausible theory that first came social systems, that you have different roles in a society. And then those roles are exchangeable, that I scratch your back, you scratch my back, we can exchange roles. And once you have the brain structures that allow you to understand actions in terms of roles that can be changed, that's the basis for language, for grammar. And now you can start using symbols to refer to objects in the world, and you have this flexible structure. So there's a social structure that's fundamental for language to develop. Now, again, then you have language, you can refer to things that are not here right now, and that allows you to then build all the good stuff about planning, for instance, and building things and so on. So yeah, I think that very strongly humans are social and that gives us ability to structure the world. But also as a society, we can do so much more because one person does not have to do everything, you can have different roles and together achieve a lot more. And that's also something we see in computational simulations today. I mean, we have multi-agent systems that can perform tasks. This fascinating demonstration, Marco Dorigo, I think it was, these robots, little robots that had to navigate through an environment and there were things that are dangerous, like maybe a big chasm or some kind of groove, a hole, and they could not get across it. But if they grab each other with their gripper, they form a robot that was much longer, a team, and this way they could get across that. So this is a great example of how together we can achieve things we couldn't otherwise, like the hyenas. Alone they couldn't, but as a team they could. And I think humans do that all the time, we're really good at that. Yeah, and the way you described the system of hyenas, it almost sounds algorithmic. Like the problem with humans is they're so complex, it's hard to think of them as algorithms. But with hyenas, it's simple enough to where it feels like, at least hopeful, that it's possible to create computational systems that mimic that. Yeah, that's exactly why we looked at that. As opposed to humans. Like I said, they are intelligent, but they are not quite as intelligent as say baboons, which would learn a lot and would be much more flexible. The hyenas are relatively rigid in what they can do. And therefore you could look at this behavior, like this is a breakthrough in evolution about to happen. That they've discovered something about social structures, communication, about cooperation, and it might then spill over to other things too, in thousands of years in the future. Yeah, I think the problem with baboons and humans is probably too much is going on inside the head, where we won't be able to measure it if we're observing the system. With hyenas, it's probably easier to observe the actual decision-making and the various motivations that are involved. Yeah, they are visible. And we can even quantify possibly their emotional state because they leave droppings behind. And there are chemicals there that can be associated with neurotransmitters. And we can separate what emotions they might have experienced in the last 24 hours. What to you is the most beautiful, speaking of hyenas, what to you is the most beautiful nature-inspired algorithm in your work that you've come across? Something maybe earlier on in your work or maybe today? I think that evolutionary computation is the most amazing method. So what fascinates me most is that with computers, is that you can get more out than you put in. I mean, you can write a piece of code and your machine does what you told it. I mean, this happened to me in my freshman year. It did something very simple and I was just amazed. I was blown away that it would get the number and it would compute the result and I didn't have to do it myself. Very simple. But if you push that a little further, you can have machines that learn and they might learn patterns. And already say deep learning neural networks, they can learn to recognize objects, sounds, patterns that humans have trouble with. And sometimes they do it better than humans and that's so fascinating. And now if you take that one more step, you get something like evolutionary algorithms that discover things, they create things, they come up with solutions that you did not think of. And that just blows me away. It's so great that we can build systems, algorithms that can be in some sense smarter than we are, that they can discover solutions that we might miss. A lot of times it is because we have, as humans, we have certain biases. We expect the solutions to be certain way and you don't put those biases into the algorithm so they are more free to explore. And evolution is just absolutely fantastic explorer. And that's what really is fascinating. Yeah, I think I give me fun of a bit because I currently don't have any kids, but you mentioned programs. I mean, do you have kids? So maybe you could speak to this, but there's a magic to the creative process. Like with Spot, the Boston Dynamic Spot, but really any robot that I've ever worked on, it just feels like the similar kind of joy I imagine I would have as a father. Not the same perhaps level, but like the same kind of wonderment, like that exactly this, which is like, you know what you had to do initially to get this thing going. Let's speak on the computer science side, like what the program looks like, but something about it doing more than what the program was written on paper is like that somehow connects to the magic of this entire universe. Like that's like, I feel like I found God. Every time I like, it's like, because you've really created something that's living. Yeah. Even if it's a simple program. It has a life of its own, it has the intelligence of its own. It's beyond what you actually thought. Yeah. And that is, I think it's exactly spot on. That's exactly what it's about. You created something and has a ability to live its life and do good things. And you just gave it a starting point. So in that sense, I think it's, that may be part of the joy actually. But you mentioned creativity in this context, especially in the context of evolutionary computation. So, you know, we don't often think of algorithms as creative. So how do you think about creativity? Yeah. Algorithms absolutely can be creative. They can come up with solutions that you don't think about. I mean, creativity can be defined. A couple of requirements have to, has to be new. It has to be useful and it has to be surprising. And those certainly are true with say, evolutionary computation, discovering solutions. So maybe an example, for instance, we did this collaboration with MIT Media Lab, Caleb Harvest Lab, where they had a hydroponic food computer, they called it, environment that was completely computer controlled, nutrients, water, light, temperature, everything is controlled. Now, what do you do if you can't control everything? Farmers know a lot about how to do, how to make plants grow in their own patch of land. But if you can control everything, it's too much. And it turns out that we don't actually know very much about it. So we built a system, evolutionary optimization system, together with a surrogate model of how plants grow and let this system explore recipes on its own. And initially, we were focusing on light, how strong, what wavelengths, how long the light was on. And we put some boundaries, which we thought were reasonable. For instance, that there was at least six hours of darkness, like night, because that's what we have in the world. And very quickly, the system evolution pushed all the recipes to that limit. We were trying to grow basil, and we had initially had some 200, 300 recipes, exploration as well as known recipes. But now we are going beyond that. And everything was like pushed that limit. So we look at it and say, well, we can easily just change it. Let's have it your way. And it turns out the system discovered that basil does not need to sleep. 24 hours, lights on, and it will thrive. It will be bigger, it will be tastier. And this was a big surprise, not just to us, but also the biologist in the team that anticipated that there's some constraints that are in the world for a reason. It turns out that evolution did not have the same bias. And therefore it discovered something that was creative. It was surprising, it was useful, and it was new. That's fascinating to think about, like the things we think that are fundamental to living systems on Earth today, whether they're actually fundamental or they somehow fit the constraints of the system and all we'll have to do is just remove the constraints. Do you ever think about, I don't know how much you know about brain-computer interfaces and Neuralink. The idea there is, you know, our brains are very limited. And if we just allow, we plug in, we provide a mechanism for a computer to speak with the brain. So you're thereby expanding the computational power of the brain. The possibilities there sort of from a very high level philosophical perspective is limitless. But I wonder how limitless it is. Are the constraints we have like features that are fundamental to our intelligence, or is this just like this weird constraint in terms of our brain size and skull and lifespan and the senses is just the weird little like a quirk of evolution. And if we just open that up, like add much more senses, add much more computational power, the intelligence will expand exponentially. Do you have a sense about constraints, the relationship of evolution and computation to the constraints of the environment? Well, at first I'd like to comment on that, like changing the inputs to human brain and flexibility of the brain. I think there's a lot of that. There are experiments that are done in animals like migangas are at MIT switching the auditory and visual information and going to the wrong part of the cortex and the animal was still able to hear and perceive the visual environment. And there are kids that are born with severe disorders and sometimes they have to remove half of the brain like one half, and they still grow up. They have the functions migrate to the other parts. There's a lot of flexibility like that. So I think it's quite possible to hook up the brain with different kinds of sensors, for instance, and something that we don't even quite understand or have today, a different kind of wavelengths or whatever they are. And then the brain can learn to make sense of it. And that I think is this good hope that these prosthetic devices, for instance, work, not because we make them so good and so easy to use, but the brain adapts to them and can learn to take advantage of them. And so in that sense, if there's a trouble, a problem, I think the brain can be used to correct it. Now going beyond what we have today, can you get smarter? That's really much harder to do. Giving the brain more input probably might overwhelm it. It would have to learn to filter it and focus and in order to use the information effectively and augmenting intelligence with some kind of external devices like that might be difficult, I think. But replacing what's lost, I think is quite possible. Right, so our intuition allows us to sort of imagine that we can replace what's been lost, but expansion beyond what we have. I mean, we are already one of the most, if not the most intelligent things on this earth, right? So it's hard to imagine that if the brain can hold up with an order of magnitude greater set of information thrown at it, if it can reason through that. Part of me, this is the Russian thing I think, is I tend to think that the limitations is where the superpower is, that immortality and huge increase in bandwidth of information by connecting computers with the brain is not going to produce greater intelligence. It might produce lesser intelligence. So I don't know, there's something about the scarcity being essential to fitness or performance, but that could be just because we're so limited. No, exactly, you make do with what you have, but you don't have to pipe it directly to the brain. I mean, we already have devices like phones where we can look up information at any point, and that can make us more productive. You don't have to argue about, I don't know, what happened in that baseball game or whatever it is, because you can look it up right away. And I think in that sense, we can learn to utilize tools, and that's what we have been doing for a long, long time. And we are already, the brain is already drinking from the fire hose, like vision. There's way more information in vision that we actually process. So brain's already good at identifying what matters. And that, we can switch that from vision to some other wavelength or some other kind of modality, but I think that the same processing principles probably still apply. But also, indeed, this ability to have information more accessible and more relevant, I think, can enhance what we do. I mean, kids today at school, they learn about DNA. I mean, things that were discovered just a couple of years ago, it's already common knowledge, and we are building on it. And we don't see a problem where there's too much information that we can't absorb and learn. Maybe people become a little bit more narrow in what they know, they are in one field, but this information that we have accumulated, it is passed on, and people are picking up on it, and they are building on it. So it's not like we have reached the point of saturation. We have still this process that allows us to be selective and decide what's interesting, I think still works, even with the more information we have today. Yeah, it's fascinating to think about like Wikipedia becoming a sensor, so the fire hose of information from Wikipedia. So it's like you integrate it directly into the brain, to where you're thinking, like you're observing the world with all of Wikipedia directly piping into your brain. So like when I see a light, I immediately have like the history of who invented electricity, like integrated very quickly into. So just the way you think about the world might be very interesting, if you can integrate that kind of information. What are your thoughts, if I could ask, on the early steps on the Neuralink side, I don't know if you got a chance to see, but there was a monkey playing pong through the brain computer interface. And the dream there is sort of, you're already replacing the thumbs essentially, that you would use to play a video game. The dream is to be able to increase further the interface by which you interact with the computer. Are you impressed by this? Are you worried about this? What are your thoughts as a human? I think it's wonderful. I think it's great that we could do something like that. I mean, there are devices that read your EEG, for instance, and humans can learn to control things using just their thoughts in that sense. And I don't think it's that different. I mean, those signals would go to limbs, they would go to thumbs. Now the same signals go through a sensor to some computing system. It still probably has to be built on human terms, not to overwhelm them, but utilize what's there and sense the right kind of patterns that are easy to generate. But, oh, that I think is really quite possible and wonderful and could be very much more efficient. Is there, so you mentioned surprising being a characteristic of creativity. Is there something, you already mentioned a few examples, but is there something that jumps out at you as was particularly surprising from the various evolutionary computation systems you've worked on, the solutions that were come up along the way, not necessarily the final solutions, but maybe things that were even discarded. Is there something that just jumps to mind? It happens all the time. I mean, evolution is so creative, so good at discovering solutions you don't anticipate. A lot of times they are taking advantage of something that you didn't think was there, like a bug in the software. A lot of, there's a great paper, like the community put it together about surprising anecdotes about evolutionary computation. A lot of them are indeed in some software environment, there was a loophole or a bug, and the system utilizes that. By the way, for people who want to read it, it's kind of fun to read. It's called the Surprising Creativity of Digital Evolution, a Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities. And there's just a bunch of stories from all the seminal figures in this community. You have a story in there that relates to you, at least, on the tic-tac-toe memory bomb. So can you, I guess, describe that situation if you think that's- Yeah, that's a quite a bit smaller scale than our basic doesn't need to sleep surprise, but it was actually done by students in my class, in a neural nets evolutionary computation class. There was an assignment. It was perhaps a final project where people built game-playing AI. It was an AI class. And it was for tic-tac-toe or five in a row in a large board. And this one team evolved a neural network to make these moves. And they set it up, the Evolution. They didn't really know what would come out, but it turned out that they did really well. Evolution actually won the tournament. And most of the time when it won, it won because the other teams crashed. And then when we look at it, like what was going on was that Evolution discovered that if it makes a move that's really, really far away, like millions of squares away, the other teams, the other programs just expanded memory in order to take that into account until they ran out of memory and crashed. And then you win a tournament by crashing all your opponents. I think that's quite a profound example, which probably applies to most games, from even a game theoretic perspective, that sometimes to win, you don't have to be better within the rules of the game. You have to come up with ways to break your opponent's brain if it's a human, like not through violence, but through some hack where the brain just is not, you're basically, how would you put it? You're going outside the constraints of where the brain is able to function. Expectations of your opponent. I mean, this was even Kasparov pointed that out that when Deep Blue was playing against Kasparov, that it was not playing the same way as Kasparov expected. And this has to do with not having the same biases. And that's really one of the strengths of the game. Of the AI approach, yeah. Can you at a high level say, what are the basic mechanisms of evolutionary computation, algorithms that use something that could be called an evolutionary approach? Like how does it work? What are the connections to the, what are the echoes of the connection to his biological? A lot of these algorithms really do take motivation from biology, but they are caricatures. You try to essentialize it and take the elements that you believe matter. So in evolutionary computation, it is the creation of variation and then the selection upon that. So the creation of variation, you have to have some mechanism that allow you to create new individuals that are very different from what you already have. That's the creativity part. And then you have to have some way of measuring how well they are doing and using that measure to select who goes to the next generation and you continue. So first you have to have some kind of digital representation of an individual that can be then modified. So I guess humans in biological systems have DNA and all those kinds of things. And so you have to have similar kind of encodings in a computer program. Yes, and that is a big question. How do you encode these individuals? So there's a genotype, which is that encoding and then a decoding mechanism, which gives you the phenotype, which is the actual individual that then performs the task and in an environment can be evaluated how good it is. So even that mapping is a big question, then how do you do it? But typically the representations are, either they are strings of numbers or they are some kind of trees. Those are something that we know very well in computer science and we try to do that. But they, and DNA in some sense is also a sequence and a string. So it's not that far from it, but DNA also has many other aspects that we don't take into account necessarily, like there's folding and interactions that are other than just the sequence itself. And lots of that is not yet captured and we don't know whether they are really crucial. Evolution, biological evolution has produced wonderful things, but if you look at them, it's not necessarily the case that every piece is irreplaceable and essential. There's a lot of baggage because you have to construct it and it has to go through various stages and we still have appendix and we have tailbones and things like that that are not really that useful. If you try to explain them now, it would make no sense, it'd be very hard. But if you think of us as productive evolution, you can see where they came from. They were useful at one point perhaps and no longer are, but they're still there. So that process is complex and your representation should support it. And that is quite difficult if we are limited with strings or trees and then we are pretty much limited in what can be constructed. And one thing that we are still missing in evolutionary computation in particular is what we saw in biology, major transitions. So that you go from, for instance, single cell to multi-cell organisms and eventually societies. There are transitions of level of selection and level of what a unit is. And that's something we haven't captured in evolutionary computation yet. Does that require a dramatic expansion of the representation? Is that what that is? Most likely it does, but it's quite, we don't even understand it in biology very well, where it's coming from. So it would be really good to look at major transitions in biology, try to characterize them a little bit more in detail, what the processes are. How does a, so like a unit, a cell, is no longer evaluated alone, it's evaluated as part of a community, a multi-cell organism. Even though it could reproduce, now it can't alone. It has to have this environment. So there's a push to another level, at least the selection. And how do you make that jump to the next level? Yes, how do you make the jump? That's part of the algorithm. Yeah, yeah. So we haven't really seen that in computation yet. And there are certainly attempts to have open-ended evolution. Things that could add more complexity and start selecting at a higher level, but it is still not quite the same as going from single to multi to society, for instance, in biology. So there essentially would be, as opposed to having one agent, those agent all of a sudden spontaneously decide to then be together, and then your entire system would then be treating them as one agent. Something like that. Some kind of weird merger. But also, so you mentioned, I think you mentioned selection. So basically there's an agent, and they don't get to live on if they don't do well. So there's some kind of measure of what doing well is and isn't. And does mutation come into play at all in the process, and what role does it serve? Yeah, so, and again, back to what the computational mechanisms of evolutionary computation are. So the way to create variation, you can take multiple individuals, two usually, but you could do more. And you exchange the parts of the representation. You do some kind of recombination. Could be crossover, for instance. In biology, you do have DNA strings that are cut and put together again. We could do something like that. And it seems to be that in biology, the crossover is really the workhorse in biological evolution. In computation, we tend to rely more on mutation. And that is making random changes into parts of the chromosome. You could try to be intelligent and target certain areas of it, and make the mutations also follow some principle. Like you collect statistics of performance and correlations, and try to make mutations you believe are going to be helpful. That's where evolutionary computation has moved in the last 20 years. I mean, evolutionary computation has been around for 50 years, but a lot of the recent- Success comes from mutation. Yes, comes from using statistics. It's like the rest of machine learning, based on statistics. We use similar tools to guide evolutionary computation. And in that sense, it has diverged a bit from biological evolution. And that's one of the things I think we could look at again, having a weaker selection, more crossover, large populations, more time, and maybe a different kind of creativity would come out of it. We are very impatient in evolutionary computation today. We want answers right now, right quickly. And if somebody doesn't perform, kill it. And biological evolution doesn't work quite that way. And- More patient. Yes, much more patient. So I guess we need to add some kind of mating, some kind of dating mechanisms, like marriage maybe in there. So to enter our algorithms to improve the combination, as opposed to all mutation doing all of the work. Yeah, and many ways of being successful. Usually in evolutionary computation, we have one goal, play this game really well, compared to others. But in biology, there are many ways of being successful. You can build niches, you can be stronger, faster, larger, or smarter, or eat this or eat that. So there are many ways to solve the same problem of survival and that then breeds creativity. And it allows more exploration. And eventually you get solutions that are perhaps more creative, rather than trying to go from initial population directly, or more or less directly to your maximum fitness, which you measure as just one metric. So in a broad sense, before we talk about neuroevolution, do you see evolutionary computation as more effective than deep learning in a certain context? Machine learning, broadly speaking. Maybe even supervised machine learning. I don't know if you want to draw any kind of lines and distinctions and borders where they rub up against each other kind of thing, where one is more effective than the other in the current state of things. Yes, of course, they are very different and they address different kinds of problems. And the deep learning has been really successful in domains where we have a lot of data. And that means not just data about situations, but also what the right answers were. So labeled examples, or there might be predictions, maybe weather prediction where the data itself becomes labeled, what happened, what the weather was today and what it will be tomorrow. So they are very effective deep learning methods on that kind of tasks. But there are other kinds of tasks where we don't really know what the right answer is. Game playing, for instance, but many robotics tasks and actions in the world, decision-making, and actual practical applications like treatments and healthcare or investment in stock market. Many tasks are like that. We don't know and we'll never know what the optimal answers were. And there you need different kinds of approach. Reinforcement learning is one of those. Reinforcement learning comes from biology as well. Agents learn during their lifetime. They eat berries and sometimes they get sick and then they don't and get stronger. And then that's how you learn. And evolution is also a mechanism like that, but a different timescale because you have a population, not an individual during his lifetime, but an entire population as a whole can discover what works. And there you can afford individuals that don't work out. They learn, everybody dies and you have a next generation and it will be better than the previous one. So that's the big difference between these methods. They apply to different kinds of problems. And in particular, there's often a comparison that's kind of interesting and important between reinforcement learning and evolutionary computation. And initially, reinforcement learning was about individual learning during their lifetime. And evolution is more engineering. You don't care about the lifetime. You don't care about all the individuals that are tested. You only care about the final result, the last one, the best candidate that evolution produced. In that sense, they also apply to different kinds of problems. And another boundary is starting to blur a bit. You can use evolution as an online method and reinforcement learning to create engineering solutions, but that's still roughly the distinction. And from the point of view, what algorithm you wanna use, if you have something where there is a cost for every trial, reinforcement learning might be your choice. Now, if you have a domain where you can use a surrogate perhaps, so you don't have much of a cost for trial and you want to have surprises, you want to explore more broadly, then this population-based method is perhaps a better choice because you can try things out that you wouldn't afford when you're doing reinforcement learning. There's very few things as entertaining as watching either evolution computation or reinforcement learning teaching a simulated robot to walk. Maybe there's a higher level question that could be asked here, but do you find this whole space of applications in the robotics interesting for evolution computation? Yeah, yeah, very much. And indeed, there are fascinating videos of that. And that's actually one of the examples where you can contrast the difference. So- Between reinforcement learning and evolution. Between reinforcement learning and evolution, yes. So if you have a reinforcement learning agent, it tries to be conservative because it wants to walk as long as possible and be stable. But if you have evolutionary computation, it can afford these agents that go haywire. They fall flat on their face and they could take a step and then they jump and then again fall flat. And eventually what comes out of that is something like a falling that's controlled. You take another step and another step and you no longer fall. Instead you run, you go fast. So that's a way of discovering something that's hard to discover step by step incrementally because you can afford these evolution is dead ends, although they are not entirely dead ends in the sense that they can serve as stepping stones. When you take two of those, put them together, you get something that works even better. And that is a great example of this kind of discovery. Yeah, learning to walk is fascinating. I talk quite a bit to Russ Tedrake, who's at MIT. There's a community of folks who just, roboticists who love the elegance and beauty of movement. And walking, bipedal robotics, is beautiful but also exceptionally dangerous in the sense that you're constantly falling, essentially, if you want to do elegant movement. And the discovery of that is, I mean, it's such a good example of that the discovery of a good solution sometimes requires a leap of faith and patience and all those kinds of things. I wonder what other spaces where you have to discover those kinds of things in. Yeah, yeah. Another interesting direction is learning for virtual creatures, learning to walk. We did a study in simulation, obviously, that you create those creatures, not just their controller, but also their body. So you have cylinders, you have muscles, you have joints and sensors, and you're creating creatures that look quite different. Some of them have multiple legs, some of them have no legs at all. And then the goal was to get them to move, to walk, to run. And what was interesting is that when you evolve the controller together with the body, you get movements that look natural because they're optimized for that physical setup. And these creatures, you start believing them, that they're alive because they walk in a way that you would expect somebody with that kind of a setup to walk. Yeah, there's something subjective also about that, right? I've been thinking a lot about that, especially in the human-robot interaction context. I mentioned Spot, the Boston Dynamics robot. There is something about human-robot communication, let's say, let's put it in another context, something about human and dog context, like a living dog, where there's a dance of communication. First of all, the eyes, you both look at the same thing and dogs communicate with their eyes as well. Like if you and a dog want to deal with a particular object, you will look at the person, the dog will look at you and then look at the object and look back at you, all those kinds of things. But there's also just the elegance of movement. I mean, there's the, of course, the tail and all those kinds of mechanisms of communication and it all seems natural. And often joyful. And for robots to communicate that is really difficult how to figure that out because it's almost seems impossible to hard code in. You can hard code it for a demo purpose, what's something like that, but it's essentially choreographed. Like if you watch some of the Boston Dynamics videos where they're dancing, all of that is choreographed by human beings. But to learn how to, with your movement, demonstrate a naturalness, an elegance, that's fascinating. Of course, in the physical space, that's very difficult to do, to learn the kind of at scale that you're referring to. But the hope is that you could do that in simulation and then transfer it into the physical space. If you're able to model the robots sufficiently naturally. Yeah, and sometimes I think that that requires a theory of mind on the side of the robot that they understand what you're doing because they themselves are doing something similar. And that's a big question too. We've talked about intelligence in general and the social aspect of intelligence. And I think that's what is required that we humans understand other humans because we assume that they are similar to us. We have one simulation we did a while ago, Ken Stanley did that. Two robots that were competing simulation, like you said, they were foraging for food to gain energy. And then when they were really strong, they would bounce into the other robot and win if they were stronger. And we watched evolution discover more and more complex behaviors. They first went to the nearest food and then they started to plot a trajectory so they get more, get more. But then they started to pay attention what the other robot was doing. And in the end, there was a behavior where one of the robots, the most sophisticated one, sensed where the food pieces were and identified that the other robot was close to two of a very far distance. And there was one more food nearby. So it faked, now I'm using anthropomorphized terms, but it made a move towards those other pieces in order for the other robot to actually go and get them. Because it knew that the last remaining piece of food was close and the other robot would have to travel a long way, lose its energy, and then lose the whole competition. So there was like emergence of something like a theory of mind, knowing what the other robot would do to guide it towards bad behavior in order to win. So we can get things like that happen in simulation as well. But that's a complete natural emergence of a theory of mind. But I feel like if you add a little bit of a place for a theory of mind to emerge like easier, then you can go really far. I mean, some of these things with evolution, you add a little bit of design in there, it'll really help. And I tend to think that a very simple theory of mind will go a really long way for cooperation between agents and certainly for human robot interaction. Like it doesn't have to be super complicated. I've gotten a chance in the autonomous vehicle space to watch vehicles interact with pedestrians or pedestrians interacting with vehicles in general. I mean, you would think that there's a very complicated theory of mind thing going on, but I have a sense, it's not well understood yet, but I have a sense it's pretty dumb. Like it's pretty simple. There's a social contract there between humans, a human driver and a human crossing the road where the human crossing the road trusts that the human in the car is not going to murder them. And there's something about, again, back to that mortality thing, there's some dance of ethics and morality that's built in, that you're mapping your own morality onto the person in the car. And even if they're driving at a speed where you think if they don't stop, they're going to kill you, you trust that if you step in front of them, they're going to hit the brakes. And there's that weird dance that we do that I think is a pretty simple model, but of course it's very difficult to introspect what it is. And autonomous robots in the human-robot interaction context have to build that. Current robots are much less than what you're describing. They're currently just afraid of everything. They're not the kind that fall and discover how to run. They're more like, please don't touch anything, don't hurt anything, stay as far away from humans as possible, treat humans as ballistic objects that you can't, that you do with a large spatial envelope, make sure you do not collide with. That's how, like I mentioned, Elon Musk thinks about autonomous vehicles. I tend to think autonomous vehicles need to have a beautiful dance between human and machine, where it's not just the collision avoidance problem, but a weird dance. Yeah, I think these systems need to be able to predict what will happen, what the other agent is going to do, and then have a structure of what the goals are and whether those predictions actually meet the goals. And you can go probably pretty far with that relatively simple setup already. But to call it a theory of mind, I don't think you need to. I mean, it doesn't matter whether a pedestrian has a mind, it's an object and we can predict what we will do. And then we can predict what the states will be in the future and whether they are desirable states. Stay away from those that are undesirable and go towards those that are desirable. So it's a relatively simple, functional approach to that. Where do we really need the theory of mind? Maybe when you start interacting and you're trying to get the other agent to do something, and jointly, so that you can jointly, collaboratively achieve something, then it becomes more complex. Well, I mean, even with the pedestrians, you have to have a sense of where their attention, actual attention in terms of their gaze is, but also like, there's this vision science, people talk about this all the time. Just because I'm looking at it doesn't mean I'm paying attention to it. So figuring out what is the person looking at? What is the sensory information they've taken in? And the theory of mind piece comes in is, what are they actually attending to cognitively? And also, what are they thinking about? Like, what is the computation they're performing? And you have probably maybe a few options, for the pedestrian crossing. It doesn't have to be, it's like a variable with a few discrete states, but you have to have a good estimation which of the states that brain is in for the pedestrian case. And the same is for attending with a robot. If you're collaborating to pick up an object, you have to figure out, is the human, there's a few discrete states that the human could be in, and you have to predict that by observing the human. And that seems like a machine learning problem to figure out what's the human up to. It's not as simple as sort of planning, just because they move their arm, means the arm will continue moving in this direction. You have to really have a model of what they're thinking about, and what's the motivation behind the movement of the arm. Here we are talking about relatively simple physical actions, but you can take that to higher levels, also to predict what the people are going to do, you need to know what their goals are, what are they trying to, are they exercising, are they just trying to get somewhere. But even higher level, I mean you are predicting what people will do in their career, what their life themes are, do they want to be famous, rich, or do good? And that takes a lot more information, but it allows you to then predict their actions, what choices they might make. So how does evolution and computation apply to the world of neural networks? Because I've seen quite a bit of work from you and others in the world of neuroevolution. So maybe first, can you say, what is this field? Yeah, neuroevolution is a combination of neural networks and evolutionary computation in many different forms, but the early versions were simply using evolution as a way to construct a neural network. Instead of say, stochastic gradient descent or back propagation. Because evolution can evolve these parameters, weight values in a neural network, just like any other string of numbers, you can do that. And that's useful because some cases you don't have those targets that you need to back propagate from. And it might be an agent that's running a maze or a robot playing a game or something. Again, you don't know what the right answer is, you don't have backup, but this way you can still evolve a neural net. And neural networks are really good at this task because they recognize patterns and they generalize, interpolate between known situations. So you want to have a neural network in such a task, even if you don't have the supervised targets. So that's the reason and that's the solution. And also more recently now, when we have all this deep learning literature, it turns out that we can use evolution to optimize many aspects of those designs. The deep learning architectures have become so complex that there's little hope for us little humans to understand their complexity and what actually makes a good design. And now we can use evolution to give that design for you. And it might mean optimizing hyperparameters, like the depth of layers and so on, or the topology of the network, how many layers, how they're connected, but also other aspects, like what activation functions you use where in the network during the learning process, or what loss function you use. You could generate that. Even data augmentation, all the different aspects of the design of deep learning experiments could be optimized that way. So that's an interaction between two mechanisms. But there's also, when we get more into cognitive science and the topics that we've been talking about, you could have learning mechanisms at two level timescales. So you do have an evolution that gives you baby neural networks that then learn during their lifetime. And you have this interaction of two timescales. And I think that can potentially be really powerful. Now in biology, we are not born with all our faculties. We have to learn, we have a developmental period. In humans, it's really long. And most animals have something. And probably the reason is that evolution, a DNA is not detailed enough or plentiful enough to describe them. We can't describe how to set the brain up. But we can, evolution can decide on a starting point and then have a learning algorithm that will construct the final product. And this interaction of intelligent, well, evolution that has produced a good starting point for the specific purpose of learning from it with the interaction of, with the environment, that can be a really powerful mechanism for constructing brains and constructing behaviors. I like how you walk back from intelligence. So optimize starting point, maybe. Yeah. Okay, there's a lot of fascinating things to ask here. And this is basically this dance between neural networks and evolutionary computation. Could go into the category of automated machine learning to where you're optimizing, whether it's hyperparameters of the topology or hyperparameters taken broadly. But the topology thing is really interesting. I mean, that's not really done that effectively or throughout the history of machine learning has not been done. Usually there's a fixed architecture. Maybe there's a few components you're playing with, but to grow a neural network, essentially, the way you grow in their organism is really fascinating space. How hard is it, do you think, to grow a neural network? And maybe what kind of neural networks are more amenable to this kind of idea than others? I've seen quite a bit of work on recurrent neural networks. Is there some architectures that are friendlier than others? And is this just a fun, small-scale set of experiments, or do you have hope that we can be able to grow powerful neural networks? I think we can. And most of the work up to now is taking architectures that already exist, that humans have designed, and try to optimize them further. And you can totally do that. A few years ago, we did an experiment. We took a winner of the image captioning competition and the architecture, and just broke it into pieces and took the pieces, and that was our search base. See if you can do better. And we indeed could, 15% better performance by just searching around the network design that humans had come up with, or real vinyls and others. But that's starting from a point that humans have produced. But we could do something more general. It doesn't have to be that kind of network. The hard part is, there are a couple of challenges. One of them is to define the search base. What are your elements, and how you put them together? And the space is just really, really big. So you have to somehow constrain it and have some hunch of what will work, because otherwise everything is possible. And another challenge is that, in order to evaluate how good your design is, you have to train it. I mean, you have to actually try it out, and that's currently very expensive, right? I mean, deep learning networks may take days to train. Well, imagine you're having a population of 100 and have to run it for 100 generations. It's not yet quite feasible computationally. It will be, but also there's a large carbon footprint and all that. I mean, we are using a lot of computation for doing it. So intelligent methods, and intelligent, I mean, we have to do some science in order to figure out what the right representations are, and right operators are, and how do we evaluate them without having to fully train them? And that is where the current research is, and we're making progress on all those fronts. So yes, there are certain architectures that are more amenable to that approach, but also I think we can create our own architecture on all representations that are even better at that. And do you think it's possible to do like a tiny baby network that grows into something that can do state-of-the-art on like even a simple dataset like MNIST, and just like it just grows into a gigantic monster that's the world's greatest handwriting recognition system? Yeah, there are approaches like that. Esteban Riel and Cochlear, for instance, have worked on evolving a smaller network and then systematically expanding it to a larger one. Your elements are already there, and scaling it up will just give you more power. So again, evolution gives you that starting point, and then there's a mechanism that gives you the final result and a very powerful approach. But you could also simulate the actual growth process, and like I said before, evolving a starting point and then evolving or training the network. There's not that much work that's been done on that yet. We need some kind of a simulation environment so that interactions at will, the supervised environment doesn't really, it's not as easily usable here. Sorry, the interaction between neural networks? Yeah, the neural networks that you're creating, interacting the world, and learning from these sequences of interactions, perhaps communication with others. That's awesome. We would like to get there, but just the task of simulating something, that level is very hard. It's very difficult. I love the idea. I mean, one of the powerful things about evolution on Earth is the predators and prey emerged. There's just like, there's bigger fish and smaller fish, and it's fascinating to think that you could have neural networks competing against each other, one neural network being able to destroy another one. There's like wars of neural networks competing to solve the MNIST problem. I don't know. Oh, totally, yeah, yeah, yeah. And we actually simulated also that pair of the prey, and it was interesting what happened there, but I mean, Rajak Pallan did this, and Kay Holcomb was a zoologist. So we had, again, we had simulated hyenas and simulated zebras. Nice. And initially, you know, the hyenas just tried to hunt them, and when they actually stumbled upon the zebra, they ate it, and were happy. And then the zebras learned to escape, and the hyenas learned to team up, and actually two of them approached in different directions. And now the zebras, their next step, they generated a behavior where they split in different directions, just like actually gazelles do when they are being hunted. They confuse the predator by going in different directions. That emerged, and then more hyenas joined and kind of circled them. And then when they circled them, they could actually herd the zebras together and eat multiple zebras. So there was like an arms race of predators and prey, and they gradually developed more complex behaviors, some of which we actually do see in nature. And this kind of co-evolution, that's competitive co-evolution, it's a fascinating topic, because there's a promise or possibility that you will discover something new that you don't already know. You didn't build it in. It came from this arms race. It's hard to keep the arms race going. It's hard to have rich enough simulation that supports all of these complex behaviors. But at least for several steps, we've already seen it in this predator-prey scenario, yeah. First of all, it's fascinating to think about this context in terms of evolving architectures. So I've studied Tesla autopilot for a long time. It's one particular implementation of an AI system that's operating in the real world. I find it fascinating because of the scale at which it's used out in the real world. And I'm not sure if you're familiar with that system much, but you know, Andrei Karpathy leads that team on the machine learning side. And there's a multitask network, multi-headed network, where there's a core, but it's trained on particular tasks, and there's a bunch of different heads that are trained on that. Is there some lessons from evolutionary computation or neuroevolution that could be applied to this kind of multi-headed beast that's operating in the real world? Yes, it's a very good problem for neuroevolution. And the reason is that when you have multiple tasks, they support each other. So let's say you're learning to classify X-ray images to different pathologies. So you have one task is to classify this disease and another one, this disease, another one, this one. And when you're learning from one disease, that forces certain kinds of internal representations and embeddings, and they can serve as a helpful starting point for the other tasks. So you are combining the wisdom of multiple tasks into these representations. And it turns out that you can do better in each of these tasks when you are learning simultaneously other tasks than you would by one task alone. Which is a fascinating idea in itself, yeah. Yes, and people do that all the time. I mean, you use knowledge of domains that you know in new domains, and certainly neural networks can do that. Where neuroevolution comes in is that what's the best way to combine these tasks? Now there's architectural design that allow you to decide where and how the embeddings, the internal representations are combined and how much you combine them. And there's quite a bit of research on that and my team, Elliot Meyerson's worked on that. In particular, like what is a good internal representation that supports multiple tasks? And we're getting to understand how that's constructed and what's in it. So that it is in a space that supports multiple different heads, like you said. And that, I think is fundamentally how biological intelligence works as well. You don't build a representation just for one task. You try to build something that's general, not only so that you can do better in one task or multiple tasks, but also future tasks and future challenges. So you learn the structure of the world and that helps you in all kinds of future challenges. And so you're trying to design a representation that will support an arbitrary set of tasks in a particular sort of class of problem. Yeah, and also it turns out, and that's again a surprise that Elliot found, was that those tasks don't have to be very related. You can learn to do better vision by learning language or better language by learning about DNA structure. No, somehow the world. What? Yeah, it rhymes. The world rhymes, even if it's very disparate fields. I mean, on that small topic, let me ask you, because you've also on the computational neuroscience side, you worked on both language and vision. What's the connection between the two? What's more, maybe there's a bunch of ways to ask this, but what's more difficult to build from an engineering perspective and evolutionary perspective, the human language system or the human vision system or the equivalent of in the AI space, language and vision? Or is it the best, is the multitask idea that you're speaking to that they need to be deeply integrated? Yeah, absolutely. The learning both at the same time, I think is a fascinating direction in the future. So we have data sets where there is visual component as well as verbal descriptions, for instance, and that way you can learn a deeper representation, a more useful representation for both. But it's still an interesting question of which one is easier. I mean, recognizing objects or even understanding sentences, that's relatively possible. But where it becomes, where the challenges are is to understand the world. Like the visual world, the 3D, what are the objects doing and predicting what will happen, the relationships. That's what makes vision difficult. And language, obviously, it's what is being said, what the meaning is. And the meaning doesn't stop at who did what to whom. There are goals and plans and themes, and you eventually have to understand the entire human society and history in order to understand a sentence very much fully. There are plenty of examples of those kinds of short sentences when you bring in all the world knowledge to understand it. And that's the big challenge. Now, we are far from that, but even just bringing in the visual world together with the sentence will give you already a lot deeper understanding of what's happening. And I think that that's where we're going very soon. I mean, we've had ImageNet for a long time, and now we have all these text collections. But having both together and then learning a semantic understanding of what is happening, I think that will be the next step in the next few years. Yeah, you're starting to see that with all the work with Transformers, was the community, the AI community started to dip their toe into this idea of having language models that are now doing stuff with images, with vision, and then connecting the two. I mean, right now it's like these little explorations, we're literally dipping the toe in. But maybe at some point we'll just dive into the pool and it'll just be all seen as the same thing. I do still wonder what's more fundamental, whether vision is, whether we don't think about vision correctly. Maybe the fact, because we're humans and we see things as beautiful and so on, and because we have cameras that take in pixels as a 2D image, that we don't sufficiently think about vision as language. Maybe Chomsky is right all along, that vision is fundamental to, oh, sorry, that language is fundamental to everything, to even cognition, to even consciousness. The base layer is all language, not necessarily like English, but some weird, abstract representation, the linguistic representation. Yeah, well, earlier we talked about the social structures and that may be what's underlying the language. That's the more fundamental part, and then language has been added on top of that. Language emerges from the social interaction. Yeah, that's a very good guess. We are visual animals, though. A lot of the brain is dedicated to vision, and also when we think about various abstract concepts, we usually reduce that to vision and images. And that's, you know, we go to a whiteboard, you draw pictures of very abstract concepts. So we tend to resort to that quite a bit, and that's a fundamental representation. It's probably possible that it predated language even. I mean, animals, a lot of, they don't talk, but they certainly do have vision. And language is interesting development from mastication, from eating. You develop an organ that actually can produce sound to manipulate them. Maybe that was an accident. Maybe that was something that was available and then allowed us to do the communication. Or maybe it was gestures. Sign language could have been an original proto-language. We don't quite know, but the language is more fundamental than the medium in which it's communicated. And I think that it comes from those representations. Now, in current world, they are so strongly integrated, it's really hard to say which one is fundamental. You look at the brain structures and even visual cortex, which is supposed to be very much just vision. Well, if you are thinking of semantic concepts, if you're thinking of language, visual cortex lights up. It's still useful, even for language computations. So there are common structures underlying them. So utilize what you need. And when you are understanding a scene, you're understanding relationships. Well, that's not so far from understanding relationships between words and concepts. So I think that that's how they are integrated. Yeah, and there's dreams. And once we close our eyes, there's still a world in there somehow operating and somehow possibly the visual systems somehow integrate into all of it. I tend to enjoy thinking about aliens and thinking about the sad thing to me about extraterrestrial intelligent life, that if it visited us here on earth, or if we came on Mars or maybe in other solar system, another galaxy one day, that us humans would not be able to detect it or communicate with it or appreciate. Like it'd be right in front of our nose and we're too self-obsessed to see it. Not self-obsessed, but our tools, our frameworks of thinking would not detect it as a good movie arrival and so on. Where Stephen Wolfram and his son, I think were part of developing this alien language of how aliens would communicate with humans. Do you ever think about that kind of stuff where if humans and aliens would be able to communicate with each other? Like if we met each other at some, okay, we could do SETI, which is communicating from across a very big distance, but also just us, you know, if you did a podcast with an alien, do you think we'd be able to find a common language and a common methodology of communication? I think from a computational perspective, the way to ask that is, is you have very fundamentally different creatures, agents that are created, would they be able to find a common language? Yes, I do think about that. I mean, I think a lot of people who are in computing, and AI in particular, they got into it because they were fascinated with science fiction and all of these options. I mean, Star Trek generated all kinds of devices that we have now, they envisioned it first. And it's a great motivator to think about things like that. And so one, and again, being a computational scientist and trying to build intelligent agents, what I would like to do is have a simulation where the agents actually evolve communication, not just communication, we've done that, people have done that many times, that they communicate, they signal and so on, but actually develop a language. And language means grammar, it means all this social structures and on top of that grammatical structure. Grammatical structures. And we do it under various conditions and actually try to identify what conditions are necessary for it to come out. And then we can start asking that kind of questions. Are those languages that emerge in those different simulated environments, are they understandable to us? Can we somehow make a translation? We can make it a concrete question. So machine translation of evolved languages, languages that evolve come up with, can we translate, like I have a Google Translate for the evolved languages. Yes, and if we do that enough, we have perhaps an idea what an alien language might be like, the space of where those languages can be. Because we can set up their environment differently. It doesn't need to be gravity. You can have all kinds of, societies can be different, they may have no predators, they may have, everybody's a predator, all kinds of situations. And then see what the space possibly is where those languages are and what the difficulties are. That'd be really good actually to do that before the aliens come here. Yes, it's good practice. On the similar connection, you can think of AI systems as aliens. Is there a ways to evolve a communication scheme for, there's a field you can call like explainable AI, for AI systems to be able to communicate. So you evolve a bunch of agents, but for some of them to be able to talk to you also. So to evolve a way for agents to be able to communicate about their world to us humans. Do you think that there's possible mechanisms for doing that? We can certainly try. And if it's an evolution competition system, for instance, you reward those solutions that are actually functional, that that communication makes sense, it allows us to together again, achieve common goals. I think it's possible. But even from that paper that you mentioned, the anecdotes, it's quite likely also that the agents learn to lie and fake and do all kinds of things like that. I mean, we see that in even very low level, like bacterial evolution, they are cheaters. And who's to say that what they say is actually what they think. But that's what I'm saying, that there would have to be some common goal so that we can evaluate whether that communication is at least useful. They may be saying things just to make us feel good or get us to do what we want, but they would not turn them off or something. But so we would have to understand their internal representations much better to really make sure that that translation is critical. But it can be useful. And I think it's possible to do that. There are examples where visualizations are automatically created so that we can look into the system and the language is not that far from it. I mean, it is a way of communicating and logging what you're doing in some interpretable way. I think a fascinating topic, yeah, to do that. You're making me realize that it's a good scientific question whether lying is an effective mechanism for integrating yourself and succeeding in a social network in a world that is social. I tend to believe that honesty and love are evolutionary advantages in an environment where there's a network of intelligent agents. But it's also very possible that dishonesty and manipulation and even violence, all those kinds of things might be more beneficial. That's the old open question about good versus evil. But I tend to, I mean, I don't know if it's a hopeful, maybe I'm delusional, but it feels like karma is a thing, which is like long-term the agents that are just kind to others sometimes for no reason will do better. In a society that's not highly constrained on resources. So like people start getting weird and evil towards each other and bad when the resources are very low relative to the needs of the populace, especially at the basic level, like survival, shelter, food, all those kinds of things. But I tend to believe that once you have those things established, then, well, not to believe, I guess I hope that AI systems would be honest. But it's scary to think about the Turing test. AI systems that will eventually pass the Turing test will be ones that are exceptionally good at lying. That's a terrifying concept. I mean, I don't know. First of all, so from somebody who studied language and obviously are not just a world expert in AI, but somebody who dreams about the future of the field, do you hope, do you think there'll be human level or superhuman level intelligences in the future that we eventually build? Well, I definitely hope that we can get there. One, I think, important perspective is that we are building AI to help us. That it is a tool like cars or language or communication. AI will help us be more productive. And that is always a condition. It's not something that we build and let run and it becomes an entity of its own that doesn't care about us. Now, of course, really find the future, maybe that might be possible, but not in the foreseeable future when we are building it. And therefore, we are always in a position of limiting what it can or cannot do. And your point about lying is very interesting. Even in these hyena societies, for instance, when a number of these hyenas band together and they take a risk and steal the kill, there are always hyenas that hang back and don't participate in that risky behavior, but they walk in later and join the party and have a good time. They walk in later and join the party after the kill. And there are even some that may be ineffective and cause others to have harm. So, and like I said, even bacteria cheat. And we see in biology, there's always some element, an opportunity. If you have a society, I think that is because if you have a society, in order for society to be effective, you have to have this cooperation and you have to have trust. And if you have enough of agents who are able to trust each other, you can achieve a lot more. But if you have trust, you also have opportunity for cheaters and liars. And I don't think that's ever gonna go away. There will be hopefully a minority so that they don't get in the way. And we studied in these hyena simulations, like what the proportion needs to be before it is no longer functional. And you can point out that you can tolerate a few cheaters and a few liars and the society can still function. And that's probably going to happen when we build these systems that autonomously learn. The really successful ones are honest because that's the best way of getting things done. But there probably are also intelligent agents that find that they can achieve their goals by bending the rules of cheating. So that could be a huge benefit to, as opposed to having fixed AI systems, say we build an AGI system and deploying millions of them, it'd be that are exactly the same. There might be a huge benefit to introducing sort of from like an evolution competition perspective, a lot of variation. Sort of like diversity in all its forms is beneficial, even if some people are assholes or some robots are assholes. So like it's beneficial to have that because you can't always a priori know what's good, what's bad, but that's a fascinating- Absolutely. Diversity is the bread and butter. I mean, if you're running a competition, you see diversity is the one fundamental thing you have to have. And absolutely, also, it's not always good diversity. It may be something that can be destructive. We had in this hyena simulations, we have hyenas that just are suicidal. They just run and get killed, but they form the basis of those who actually are really fast, but stop before they get killed and eventually turn into this mob. So there might be something useful there if we combine with something else. So I think as long as we can tolerate some of that, it may turn into something better. You may change the rules because it's so much more efficient to do something that was actually against the rules before. And we've seen society change over time quite a bit along those lines. That there were rules in society that we don't believe are fair anymore, even though they were considered proper behavior before. So things are changing. And I think that in that sense, I think it's a good idea to be able to tolerate some of that, some of that cheating, because eventually we might turn into something better. So yeah, I think this is a message to the trolls and the assholes of the internet that you too have a beautiful purpose in this human ecosystem. So I appreciate you very much. In moderate quantities. In moderate quantities. So there's a whole field of artificial life. I don't know if you're connected to this field, if you pay attention. Do you think about this kind of thing? Is there an impressive demonstration to you of artificial life? Do you think of the agency you work with in the evolutionary computation perspective as life? And where do you think this is headed? Like, is there interesting systems that we'll be creating more and more that make us redefine, maybe rethink about the nature of life? Different levels of definition and goals there. I mean, at some level, artificial life can be considered multi-agent systems that build a society that again, achieves a goal. And it might be robots that go into a building and clean it up or after an earthquake or something. You can think of that as an artificial life problem in some sense. Or you can really think of it, artificial life as a simulation of life and a tool to understand what life is and how life evolved on earth. And like I said, in artificial life conference, there are branches of that conference sessions of people who really worry about molecular designs and the start of life. Like I said, primordial soup where eventually you get something self-replicating. And they're really trying to build that. So it's a whole range of topics. And I think that artificial life is a great tool to understand life. And there are questions like sustainability, species, we're losing species. How bad is it? Is it natural? Is there a tipping point? And where are we going? I mean, like the hyena evolution, we may have understood that there's a pivotal point in their evolution. They discovered cooperation and coordination. Artificial life simulations can identify that and maybe encourage things like that. So, and also societies can be seen as a form of life itself. I mean, we're not talking about biological evolution, we have all evolution of societies. Maybe some of the same phenomena emerging in that domain and having artificial life simulations and understanding could help us build better societies. Yeah, and thinking from a meme perspective from Richard Dawkins, that maybe the organisms, ideas of the organisms, not the humans in these societies, that it's almost like reframing what is exactly evolving. Maybe the interesting, the humans aren't the interesting thing as the contents of our minds is the interesting thing. And that's what's multiplying. And that's actually multiplying and evolving at a much faster timescale. And that maybe has more power on the trajectory of life on earth than does biological evolution. It's the evolution of these ideas. Yes, and it's fascinating, like I said before, that we can keep up somehow biologically. We've evolved to a point where we can keep up with this meme evolution, literature, internet. We understand DNA and we understand fundamental particles. It didn't start that way a thousand years ago. And we haven't evolved biologically very much, but somehow our minds are able to extend. And there, for AI, can be seen also as one such step that we created and it's our tool. And it's part of that meme evolution that we created, even if our biological evolution does not progress as fast. And us humans might only be able to understand so much. We're keeping up so far, or we think we're keeping up so far, but we might need AI systems to understand. Maybe like the physics of the universe is operating, look at string theory, maybe it's operating in much higher dimensions. Maybe we're totally, because of our cognitive limitations, are not able to truly internalize the way this world works. And so we're running up against the limitation of our own minds and we have to create these next level organisms like AI systems that would be able to understand much deeper, like really understand what it means to live in a multi-dimensional world that's outside of the four dimensions, the three of space and one of time. Yeah, translation. And generally we can deal with the world, even if we don't understand all the details. We can use computers, even though we don't, most of us don't know all the structure that's underneath or drive a car. I mean, there are many components, especially new cars that you don't quite fully know, but you have the interface, you have an abstraction of it that allows you to operate it and utilize it. And I think that that's perfectly adequate and we can build on it and AI can play a similar role. I have to ask about beautiful artificial life systems or evolutionary computation systems, cellular automata to me. Like I remember it was a game changer for me early on in life when I saw Conway's Game of Life who recently passed away, unfortunately. And it's beautiful how much complexity can emerge from such simple rules. I just don't, somehow that simplicity is such a powerful illustration and also humbling because it feels like I personally, from my perspective, understand almost nothing about this world because like my intuition fails completely how complexity can emerge from such simplicity. Like my intuition fails, I think, is the biggest problem I have. Do you find systems like that beautiful? Is there, do you think about cellular automata? Because cellular automata don't really have, and many other artificial life systems don't necessarily have an objective. Maybe that's a wrong way to say it. It's almost like it's just evolving and creating. And there's not even a good definition of what it means to create something complex and interesting and surprising, all those words that you said. Is there some of those systems that you find beautiful? Yeah, yeah. And similarly, evolution does not have a goal. It is responding to the current situation and survival then creates more complexity and therefore we have something that we perceive as progress but that's not what evolution is inherently set to do. And yeah, that's really fascinating how a simple set of rules or simple mappings can, how from such simple mappings, complexity can emerge. So it's a question of emergence and self-organization. And the game of life is one of the simplest ones and very visual and therefore it drives home the point that it's possible that non-linear interactions and this kinds of complexity can emerge from them. And biology and evolution is along the same lines. We have simple representations. DNA, if you really think of it, it's not that complex. It's a long sequence of them. There's lots of them but it's a very simple representation. And similar with evolutionary computation, whatever string or tree representation we have and the operations, the amount of code that's required to manipulate those is really, really little. And of course, game of life even less. So how complexity emerges from such simple principles, that's absolutely fascinating. The challenge is to be able to control it and guide it and direct it so that it becomes useful. And like game of life is fascinating to look at and evolution, all the forms that come out is fascinating but can we actually make it useful for us? And efficient because if you actually think about each of the cells in the game of life as a living organism, there's a lot of death that has to happen to create anything interesting. And so I guess the question is for us humans that are mortal and then life ends quickly, we wanna kinda hurry up and make sure we take evolution, the trajectory that is a little bit more efficient than the alternatives. And that touches upon something we talked about earlier that evolution competition is very impatient. We have a goal, we want it right away. Whereas this biology has a lot of time and deep time and weak pressure and large populations. One great example of this is the novelty search. So evolutionary competition where you don't actually specify a fitness goal, something that is your actual thing that you want but you just reward solutions that are different from what you've seen before. Nothing else. And you know what? You actually discover things that are interesting and useful that way. Ken Stanley and Joel Lehman did this one study where they actually tried to evolve walking behavior on robots. And that's actually, we talked about earlier where your robot actually failed in all kinds of ways and eventually discovered something that was a very efficient walk. And it was because they rewarded things that were different that you were able to discover something. And I think that this is crucial because in order to be really different from what you already have, you have to utilize what is there in a domain to create something really different. So you have encoded the fundamentals of your world and then you make changes to those fundamentals you get further away. So that's probably what's happening in these systems of emergence. That the fundamentals are there. And when you follow those fundamentals, you get into points. And some of those are actually interesting and useful. Now, even in that robotic walker simulation, there was a large set of garbage. But among them, there were some of these gems. And then those are the ones that somehow you have to outside recognize and make useful. But this kind of productive systems, if you code them the right kind of principles, I think that they encode the structure of the domain. Then you will get to these solutions and you discover it. It feels like that might also be a good way to live life. So let me ask, do you have advice for young people today about how to live life or how to succeed in their career? Or forget career, just succeed in life. From an evolution and computation perspective. Yes, yes, definitely. Explore, diversity, exploration. And individuals take classes in music, history, philosophy, math, engineering. See connections between them. Travel, learn a language. I mean, all this diversity is fascinating. And we have it at our fingertips today. It's possible, you have to make a bit of an effort because it's not easy. But the rewards are wonderful. Yeah, there's something interesting about an objective function of new experiences. So try to figure out, I mean, what is the maximally new experience I could have today? And that sort of, that novelty, optimizing for novelty for some period of time might be a very interesting way to sort of maximally expand the sets of experiences you had and then ground from that perspective, like what will be the most fulfilling trajectory through life. Of course, the flip side of that is where I come from. Again, maybe Russian, I don't know. But the choice has a detrimental effect, I think, at least from my mind, where scarcity has an empowering effect. So if I have very little of something and only one of that something, I will appreciate it deeply. Until I came to Texas recently, and I've been pigging out on delicious, incredible meat. I've been fasting a lot, so I need to do that again. But when you fast for a long time, you're fasting a lot, so I need to do that again. But when you fast for a few days, that the first taste of a food is incredible. So the downside of exploration is that somehow, maybe you can correct me, but somehow you don't get to experience deeply any one of the particular moments. But that could be a psychology thing. That could be just a very human, peculiar flaw. Yeah, I didn't mean that you superficially explore. I mean, you can- Explore deeply. Yeah, so you don't have to explore 100 things, but maybe a few topics where you can take a deep enough time, a dive, that you gain an understanding. Yourself have to decide at some point that this is deep enough. And I've obtained what I can from this topic. And now it's time to move on. And that might take years. People sometimes switch careers and they may stay on some career for a decade and switch to another one. You can do it. You're not pretty determined to stay where you are. But in order to achieve something, 10,000 hours makes, you need 10,000 hours to become an expert on something. So you don't have to become an expert, but to even develop an understanding and gain the experience that you can use later, you probably have to spend, like I said, it's not easy. You got to spend some effort on it. Now, also at some point then, when you have this diversity and you have these experiences, exploration, you may want to, you may find something that you can't stay away from. Like for, as it was computers, it was AI, it was, you know, that you, I just have to do it. You know, and I, you know, and then it will take decades maybe and you are pursuing it because you figured out that this is really exciting and you can bring in your experiences. And there's nothing wrong with that either, but you asked, what's the advice for young people? That's the exploration part. And then beyond that, after that exploration, you actually can focus and build a career. And, you know, even there you can switch multiple times, but I think the diversity exploration is fundamental to having a successful career as is concentration and spending an effort where it matters. And, but you are in better position to make the choice when you have done your homework. Explored. So exploration precedes commitment, but both are beautiful. So again, from an evolutionary computation perspective, we'll look at all the agents that had to die in order to come up with different solutions in simulation. What do you think from that individual agent's perspective is the meaning of it all? So far as humans, you're just one agent who's going to be dead, unfortunately, one day too soon. What do you think is the why of why that agent came to be and eventually will be no more? Is there a meaning to it all? Yeah, in evolution, there is meaning. Everything is a potential direction. Everything is a potential stepping stone. Not all of them are gonna work out. Some of them are foundations for further improvement. And even those that are perhaps going to die out where potential energies, potential solutions. In biology, we see a lot of species die off naturally and like the dinosaurs. I mean, they were really good solution for a while, but then it didn't turn out to be not such a good solution in the longterm. When there's an environmental change, you have to have diversity, some other solutions become better. Doesn't mean that there was an attempt, it didn't quite work out or last, but there are still dinosaurs and mountains, at least their relatives, and they may one day again be useful, who knows? So from an individual's perspective, you gotta think of a bigger picture that it is a huge engine that is innovative and these elements are all part of it, potentially innovations on their own and also as raw material perhaps or stepping stones for other things that could come after. But it still feels from an individual perspective that I matter a lot, but even if I'm just a little cog in the giant machine, is that just a silly human notion? In individualistic society, no, should I go with that? Do you find beauty in being part of the giant machine? Yeah, I think it's meaningful. I think it adds purpose to your life, that you are part of something bigger. That said, do you ponder your individual agent's mortality? Do you think about death? Do you fear death? Well, certainly more now than when I was a youngster and did skydiving and paragliding and all these things. You've become wiser. There is a reason for this life arc that younger folks are more fearless in many ways. It's part of the exploration. They are the individuals who think, hmm, I wonder what's over those mountains or what if I go really far in that ocean? What would I find? I mean, older folks don't necessarily think that way, but younger do. It's kind of counterintuitive. So yeah, but logically, it's like, you have a limited amount of time. What can you do with it that matters? So you try to, you have done your exploration, you committed to a certain direction and you become an expert perhaps in it. What can I do that matters with the limited resources that I have? That's how I think a lot of people, myself included, start thinking later on in their career. And like you said, leave a bit of a trace and a bit of an impact even after the agent is gone. Yeah, that's the goal. Well, this was a fascinating conversation. I don't think there's a better way to end it. Thank you so much. So first of all, I'm very inspired of how vibrant the community at UT Austin and Austin is. It's really exciting for me to see it. And this whole field seems like profound philosophically, but also the path forward for the artificial intelligence community. So thank you so much for explaining so many cool things to me today and for wasting all of your valuable time with me. Oh, it was a pleasure. Thanks, I appreciate it. Thanks for listening to this conversation with Vista McAlinan and thank you to the Jordan Harbinger Show, Grammarly, Belcampo and Indeed. Check them out in the description to support this podcast. And now let me leave you with some words from Carl Sagan. Extinction is the rule, survival is the exception. Thank you for listening. I hope to see you next time.

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David Silver: AlphaGo, AlphaZero, and Deep Reinforcement Learning | Lex Fridman Podcast #86

The following is a conversation with David Silver, who leads the reinforcement learning research group at DeepMind and was the lead researcher on AlphaGo, AlphaZero, and co-led the AlphaStar and MuZero efforts and a lot of important work in reinforcement learning in general. I believe AlphaZero is one of the most important accomplishments in the history of artificial intelligence. And David is one of the key humans who brought AlphaZero to life together with a lot of other great researchers at DeepMind. He's humble, kind, and brilliant. We were both jet lagged, but didn't care and made it happen. It was a pleasure and truly an honor to talk with David. This conversation was recorded before the outbreak of the pandemic. For everyone feeling the medical, psychological, and financial burden of this crisis, I'm sending love your way. Stay strong. We're in this together. We'll beat this thing. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, review it with five stars on Apple Podcasts, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. As usual, I'll do a few minutes of ads now and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. Quick summary of the ads. Two sponsors, MasterClass and Cash App. Please consider supporting the podcast by signing up to MasterClass at masterclass.com slash Lex and downloading Cash App and using code LexPodcast. This show is presented by Cash App, the number one finance app in the App Store. When you get it, use code LexPodcast. Cash App lets you send money to friends, buy Bitcoin, and invest in the stock market with as little as $1. Since Cash App allows you to buy Bitcoin, let me mention that cryptocurrency in the context of the history of money is fascinating. I recommend Ascent of Money as a great book on this history. Debits and credits on ledgers started around 30,000 years ago. The US dollar created over 200 years ago, and Bitcoin, the first decentralized cryptocurrency, released just over 10 years ago. So given that history, cryptocurrency is still very much in its early days of development, but it's still aiming to and just might redefine the nature of money. So again, if you get Cash App from the App Store or Google Play and use the code LexPodcast, you get $10, and Cash App will also donate $10 to Thirst, an organization that is helping to advance robotics and STEM education for young people around the world. This show is sponsored by MasterClass. Sign up at masterclass.com slash Lex to get a discount and to support this podcast. In fact, for a limited time now, if you sign up for an all-access pass for a year, you get to get another all-access pass to share with a friend. Buy one, get one free. When I first heard about MasterClass, I thought it was too good to be true. For $180 a year, you get an all-access pass to watch courses from, to list some of my favorites. Chris Hadfield on space exploration, Neil deGrasse Tyson on scientific thinking communication, Will Wright, the creator of SimCity and Sims, on game design, Jane Goodall on conservation, Carlos Santana on guitar, his song Europa could be the most beautiful guitar song ever written, Gary Casparo on chess, Daniel Negrano on poker, and many, many more. Chris Hadfield explaining how rockets work and the experience of being launched into space alone is worth the money. For me, the key is to not be overwhelmed by the abundance of choice. Pick three courses you want to complete, watch each of them all the way through. It's not that long, but it's an experience that will stick with you for a long time, I promise. It's easily worth the money. You can watch it on basically any device. Once again, sign up on masterclass.com slash Lex to get a discount and to support this podcast. And now, here's my conversation with David Silver. What was the first program you ever written and what programming language? Do you remember? I remember very clearly, yeah. My parents brought home this BBC Model B microcomputer. It was just this fascinating thing to me. I was about seven years old and couldn't resist just playing around with it. So I think first program ever was writing my name out in different colors and getting it to loop and repeat that. And there was something magical about that which just led to more and more. How did you think about computers back then? Like the magical aspect of it, that you can write a program and there's this thing that you just gave birth to that's able to create sort of visual elements and live on its own. Or did you not think of it in those romantic notions? Was it more like, oh, that's cool. I can solve some puzzles. It was always more than solving puzzles. It was something where there was this limitless possibilities. Once you have a computer in front of you, you can do anything with it. I used to play with Lego with the same feeling. You can make anything you want out of Lego, but even more so with a computer. You're not constrained by the amount of kit you've got. And so I was fascinated by it and started pulling out the user guide and the advanced user guide and then learning. So I started in basic and then later 6502. My father also became interested in this machine and gave up his career to go back to school and study for a master's degree in artificial intelligence, funnily enough, at Essex University when I was seven. So I was exposed to those things at an early age. He showed me how to program in Prolog and do things like querying your family tree. And those are some of my earliest memories of trying to figure things out on a computer. Those are the early steps in computer science programming. But when did you first fall in love with artificial intelligence or with the ideas, the dreams of AI? I think it was really when I went to study at university. So I was an undergrad at Cambridge and studying computer science. And I really started to question, what really are the goals? What's the goal? Where do we want to go with computer science? And it seemed to me that the only step of major significance to take was to try and recreate something akin to human intelligence. If we could do that, that would be a major leap forward. And that idea, I certainly wasn't the first to have it, but it nestled within me somewhere and became like a bug. I really wanted to crack that problem. So you thought it was, like you had a notion that this is something that human beings can do, that it is possible to create an intelligent machine? Well, I mean, unless you believe in something metaphysical, then what are our brains doing? Well, at some level, they're information processing systems, which are able to take whatever information is in there, transform it through some form of program and produce some kind of output, which enables that human being to do all the amazing things that they can do in this incredible world. So then do you remember the first time you've written a program that, because you also had an interest in games. Do you remember the first time you were in a program that beat you in a game? So it beat you at anything, sort of achieved super David Silver level performance? So I used to work in the games industry. So for five years, I programmed games for my first job. So it was an amazing opportunity to get involved in a startup company. And so I was involved in building AI at that time. And so for sure, there was a sense of building, handcrafted, what people used to call AI in the games industry, which I think is not really what we might think of as AI in its fullest sense, but something which is able to take actions in a way which makes things interesting and challenging for the human player. And at that time, I was able to build these handcrafted agents, which in certain limited cases could do things which were able to do better than me, but mostly in these kind of Twitch-like scenarios where they were able to do things faster or because they had some pattern which was able to exploit repeatedly. I think if we're talking about real AI, the first experience for me came after that when I realized that this path I was on wasn't taking me towards, it wasn't dealing with that bug which I still had inside me to really understand intelligence and try and solve it. Everything people were doing in games was short-term fixes rather than long-term vision. And so I went back to study for my PhD, which was funnily enough, trying to apply reinforcement learning to the game of Go. And I built my first Go program using reinforcement learning, a system which would, by trial and error, play against itself and was able to learn which patterns were actually helpful to predict whether it was gonna win or lose the game and then choose the moves that led to the combination of patterns that would mean that you're more likely to win. And that system, that system beat me. And how did that make you feel? Made me feel good. I mean, was there sort of the, yeah, is it's a mix of a sort of excitement and was there a tinge of sort of like, almost like a fearful awe? You know, it's like in space, 2001 Space Odyssey, kind of realizing that you've created something that, that is, you know, that's achieved human level intelligence in this one particular little task. And in that case, I suppose neural networks weren't involved. There were no neural networks in those days. This was pre deep learning revolution, but it was a principled self-learning system based on a lot of the principles which people are still using in deep reinforcement learning. How did I feel? I think I found it immensely satisfying that a system which was able to learn from first principles for itself was able to reach the point that it was understanding this domain better than I could and able to outwit me. I don't think it was a sense of awe. It was a sense that satisfaction that something I felt should work had worked. So to me, AlphaGo, and I don't know how else to put it, but to me, AlphaGo and AlphaGo Zero, mastering the game of Go is, again, to me, the most profound and inspiring moment in the history of artificial intelligence. So you're one of the key people behind this achievement, and I'm Russian, so I really felt the first sort of seminal achievement when Deep Blue beat Garry Kasparov in 1987. So as far as I know, the AI community at that point largely saw the game of Go as unbeatable in AI using the sort of the state-of-the-art to brute force methods, search methods. Even if you consider, at least the way I saw it, even if you consider arbitrary exponential scaling of compute, Go would still not be solvable, hence why it was thought to be impossible. So given that the game of Go was impossible to master, what was the dream for you, you just mentioned your PhD thesis of building the system that plays Go, what was the dream for you that you could actually build a computer program that achieves world-class, not necessarily beats the world champion, but achieves that kind of level of playing Go? First of all, thank you, that's a very kind word. And funnily enough, I just came from a panel where I was actually in a conversation with Garry Kasparov and Murray Campbell, who was the author of Deep Blue, and it was their first meeting together since the match. So that just occurred yesterday, so I'm literally fresh from that experience. So these are amazing moments when they happen, but where did it all start? Well, for me, it started when I became fascinated in the game of Go. So Go for me, I've grown up playing games, I've always had a fascination in board games, I played chess as a kid, I played Scrabble as a kid. When I was at university, I discovered the game of Go, and to me, it just blew all of those other games out of the water, it was just so deep and profound in its complexity with endless levels to it. What I discovered was that I could devote endless hours to this game, and I knew in my heart of hearts that no matter how many hours I would devote to it, I would never become a grandmaster, or there was another path, and the other path was to try and understand how you could get some other intelligence to play this game better than I would be able to. And so even in those days, I had this idea that, what if, what if it was possible to build a program that could crack this? And as I started to explore the domain, I discovered that this was really the domain where people felt deeply that if progress could be made in Go, it would really mean a giant leap forward for AI. It was the challenge where all other approaches had failed. This is coming out of the era you mentioned, which was in some sense the golden era for the classical methods of AI, like heuristic search. In the 90s, they all fell one after another, not just chess with deep blue, but checkers, backgammon, Othello. There were numerous cases where systems built on top of heuristic search methods with these high-performance systems had been able to defeat the human world champion in each of those domains. And yet in that same time period, there was a million dollar prize available for the game of Go, for the first system to be a human professional player. And at the end of that time period, at year 2000, when the prize expired, the strongest Go program in the world was defeated by a nine-year-old child when that nine-year-old child was giving nine free moves to the computer at the start of the game to try and even things up. And the computer Go expert beat that strongest, same strongest program with 29 handicap stones, 29 free moves. So that's what the state of affairs was when I became interested in this problem in around 2003, when I started working on computer Go. There was nothing. There was just, there was very, very little in the way of progress towards meaningful performance, again, at anything approaching human level. And so people, it wasn't through lack of effort. People have tried many, many things. And so there was a strong sense that something different would be required for Go than had been needed for all of these other domains where AI had been successful. And maybe the single clearest example is that Go, unlike those other domains, had this kind of intuitive property that a Go player would look at a position and say, hey, here's this mess of black and white stones, but from this mess, oh, I can predict that this part of the board has become my territory, this part of the board has become your territory, and I've got this overall sense that I'm gonna win and that this is about the right move to play. And that intuitive sense of judgment of being able to evaluate what's going on in a position, it was pivotal to humans being able to play this game and something that people had no idea how to put into computers. So this question of how to evaluate a position, how to come up with these intuitive judgments was the key reason why Go was so hard in addition to its enormous search space, and the reason why methods which had succeeded so well elsewhere failed in Go. And so people really felt deep down that in order to crack Go, we would need to get something akin to human intuition. And if we got something akin to human intuition, we'd be able to solve many, many more problems in AI. So for me, that was the moment where it's like, okay, this is not just about playing the game of Go, this is about something profound. And it was back to that bug which had been itching me all those years, now this is the opportunity to do something meaningful and transformative, and I guess a dream was born. That's a really interesting way to put it. So almost this realization that you need to find, formulate Go as a kind of a prediction problem versus a search problem was the intuition. I mean, maybe that's the wrong crude term, but to give it the ability to kind of intuit things about positional structure of the board. Now, okay, but what about the learning part of it? Did you have a sense that you have to, that learning has to be part of the system? Again, something that hasn't really, as far as I think, except with TD Gammon and the 90s with RL a little bit, hasn't been part of those day-to-day art game-playing systems. So I strongly felt that learning would be necessary, and that's why my PhD topic back then was trying to apply reinforcement learning to the game of Go. And not just learning of any type, but I felt that the only way to really have a system to progress beyond human levels of performance wouldn't just be to mimic how humans do it, but to understand for themselves. And how else can a machine hope to understand what's going on except through learning? If you're not learning, what else are you doing? Well, you're putting all the knowledge into the system, and that just feels like something which decades of AI have told us is maybe not a dead end, but certainly has a ceiling to the capabilities. It's known as the knowledge acquisition bottleneck, that the more you try to put into something, the more brittle the system becomes. And so you just have to have learning. You have to have learning. That's the only way you're going to be able to get a system which has sufficient knowledge in it, millions and millions of pieces of knowledge, billions, trillions, of a form that it can actually apply for itself and understand how those billions and trillions of pieces of knowledge can be leveraged in a way which will actually lead it towards its goal without conflict or other issues. Yeah, I mean, if I put myself back in that time, I just wouldn't think like that. Without a good demonstration of RL, I would think more in the symbolic AI, like not learning, but sort of a simulation of knowledge base, like a growing knowledge base, but it would still be sort of pattern-based, like basically have little rules that you kind of assemble together into a large knowledge base. Well, in a sense, that was the state of the art back then. So if you look at the Go programs, which had been competing for this prize I mentioned, they were an assembly of different specialized systems, some of which used huge amounts of human knowledge to describe how you should play the opening, how you should, all the different patterns that were required to play well in the game of Go, end game theory, combinatorial game theory, and combined with more principled search-based methods, which were trying to solve for particular subparts of the game, like life and death, connecting groups together, all these amazing subproblems that just emerge in the game of Go, there were different pieces all put together into this like collage, which together would try and play against a human. And although not all of the pieces were handcrafted, the overall effect was nevertheless still brittle, and it was hard to make all these pieces work well together. And so really, what I was pressing for, and the main innovation of the approach I took, was to go back to first principles and say, well, let's back off that and try and find a principled approach where the system can learn for itself, just from the outcome, like learn for itself. If you try something, did that help or did it not help? And only through that procedure can you arrive at knowledge which is verified. The system has to verify it for itself, not relying on any other third party to say this is right or this is wrong. And so that principle was already very important in those days, but unfortunately, we were missing some important pieces back then. So before we dive into maybe discussing the beauty of reinforcement learning, let's take a step back, we kind of skipped it a bit, but the rules of the game of Go. The elements of it perhaps contrasting to chess that sort of you really enjoy as a human being, and also that make it really difficult as a AI machine learning problem. So the game of Go has remarkably simple rules. In fact, so simple that people have speculated that if we were to meet alien life at some point that we wouldn't be able to communicate with them, but we would be able to play Go with them. So probably have discovered the same rule set. So the game is played on a 19 by 19 grid, and you play on the intersections of the grid and the players take turns. And the aim of the game is very simple, it's to surround as much territory as you can, as many of these intersections with your stones, and to surround more than your opponent does. And the only nuance to the game is that if you fully surround your opponent's piece, then you get to capture it and remove it from the board and it counts as your own territory. Now from those very simple rules, immense complexity arises. There's kind of profound strategies in how to surround territory, how to kind of trade off between making solid territory yourself now, compared to building up influence that will help you acquire territory later in the game, how to connect groups together, how to keep your own groups alive, which patterns of stones are most useful compared to others. There's just immense knowledge and human Go players have played this game for, it was discovered thousands of years ago, and human Go players have built up this immense knowledge base over the years. It's studied very deeply and played by something like 50 million players across the world, mostly in China, Japan, and Korea, where it's an important part of the culture, so much so that it's considered one of the four ancient arts that was required by Chinese scholars. So there's a deep history there. But there's interesting qualities. So if I compare to chess, chess is in the same way as it is in Chinese culture for Go, and chess in Russia is also considered one of the sacred arts. So if we contrast sort of Go with chess, there's interesting qualities about Go. Maybe you can correct me if I'm wrong, but the evaluation of a particular static board is not as reliable. In chess, you can kind of assign points to the different units, and it's kind of a pretty good measure of who's winning, who's losing. It's not so clear. Yeah, so in the game of Go, you find yourself in a situation where both players have played the same number of stones, which actually captures a strong level of play happen very rarely, which means that at any moment in the game, you've got the same number of white stones and black stones. And the only thing which differentiates how well you're doing is this intuitive sense of, you know, where are the territories ultimately gonna form on this board? And if you look at the complexity of a real Go position, you know, it's mind boggling, that kind of question of what will happen in 300 moves from now, when you see just a scattering of 20 white and black stones intermingled. And so that challenge is the reason why position evaluation is so hard in Go compared to other games. In addition to that, it has an enormous search space. So there's around 10 to the 170 positions in the game of Go. That's an astronomical number. And that search space is so great that traditional heuristic search methods that were so successful in things like Deep Blue and chess programs just kind of fall over in Go. So at which point did reinforcement learning enter your life, your research life, your way of thinking? We just talked about learning, but reinforcement learning is a very particular kind of learning, one that's both philosophically sort of profound, but also one that's pretty difficult to get to work, as if we look back in the early days. So when did that enter your life and how did that work progress? So I had just finished working in the games industry at this startup company. And I took a year out to discover for myself exactly which path I wanted to take. I knew I wanted to study intelligence, but I wasn't sure what that meant at that stage. I really didn't feel I had the tools to decide on exactly which path I wanted to follow. So during that year, I read a lot. And one of the things I read was Sutton and Bartow, this sort of seminal textbook on an introduction to reinforcement learning. And when I read that textbook, I just had this resonating feeling that this is what I understood intelligence to be. And this was the path that I felt would be necessary to go down to make progress in AI. So I got in touch with Rich Sutton and asked him if he would be interested in supervising me on a PhD thesis in computer go. And he basically said that if he's still alive, he'd be happy to, but unfortunately he'd been struggling with very serious cancer for some years. And he really wasn't confident at that stage that he'd even be around to see the end of it. But fortunately that part of the story worked out very happily and I found myself out there in Alberta, they've got a great games group out there with a history of fantastic work in board games as well as Rich Sutton, the father of RL. So it was the natural place for me to go in some sense to study this question. And the more I looked into it, the more strongly I felt that this wasn't just the path to progress in computer go, but really this was the thing I'd been looking for. This was really an opportunity to frame what intelligence means. Like what are the goals of AI in a clear, single clear problem definition, such that if we're able to solve that clear single problem definition, in some sense we've cracked the problem of AI. So to you, reinforcement learning ideas, at least sort of echoes of it would be at the core of intelligence. It is at the core of intelligence. And if we ever create a human level intelligence system, it would be at the core of that kind of system. Let me say it this way, that I think it's helpful to separate out the problem from the solution. So I see the problem of intelligence, I would say it can be formalized as the reinforcement learning problem. And that that formalization is enough to capture most, if not all of the things that we mean by intelligence, that they can all be brought within this framework and gives us a way to access them in a meaningful way that allows us as scientists to understand intelligence and us as computer scientists to build them. And so in that sense, I feel that it gives us a path, maybe not the only path, but a path towards AI. And so do I think that any system in the future that's solved AI would have to have RL within it? Well, I think if you ask that, you're asking about the solution methods. I would say that if we have such a thing, it would be a solution to the RL problem. Now, what particular methods have been used to get there? Well, we should keep an open mind about the best approaches to actually solve any problem. And the things we have right now for reinforcement learning, maybe I believe they've got a lot of legs, but maybe we're missing some things. Maybe there's gonna be better ideas. I think we should keep, let's remain modest. And we're at the early days of this field and there are many amazing discoveries ahead of us. For sure, the specifics, especially of the different kinds of RL approaches currently, there could be other things that fall under the very large umbrella of RL. But if it's okay, can we take a step back and kind of ask the basic question of what is to you reinforcement learning? So reinforcement learning is the study and the science and the problem of intelligence in the form of an agent that interacts with an environment. So the problem you're trying to solve is represented by some environment, like the world in which that agent is situated. And the goal of RL is clear, that the agent gets to take actions. Those actions have some effect on the environment and the environment gives back an observation to the agent saying, this is what you see or sense. And one special thing which it gives back is called the reward signal, how well it's doing in the environment. And the reinforcement learning problem is to simply take actions over time so as to maximize that reward signal. So a couple of basic questions. What types of RL approaches are there? So I don't know if there's a nice brief in words way to paint a picture of sort of value-based, model-based, policy-based reinforcement learning. Yeah, so now if we think about, okay, so there's this ambitious problem definition of RL. It's really, you know, it's truly ambitious. It's trying to capture and encircle all of the things in which an agent interacts with an environment and say, well, how can we formalize and understand what it means to crack that? Now let's think about the solution method. Well, how do you solve a really hard problem like that? Well, one approach you can take is to decompose that very hard problem into pieces that work together to solve that hard problem. And so you can kind of look at the decomposition that's inside the agent's head, if you like, and ask, well, what form does that decomposition take? And some of the most common pieces that people use when they're kind of putting the solution method together, some of the most common pieces that people use are whether or not that solution has a value function. That means, is it trying to predict, explicitly trying to predict how much reward it will get in the future? Does it have a representation of a policy? That means something which is deciding how to pick actions. Is that decision-making process explicitly represented? And is there a model in the system? Is there something which is explicitly trying to predict what will happen in the environment? And so those three pieces are to me some of the most common building blocks. And I understand the different choices in RL as choices of whether or not to use those building blocks when you're trying to decompose the solution. Should I have a value function represented? Should I have a policy represented? Should I have a model represented? And there are combinations of those pieces and of course other things that you could add into the picture as well. But those three fundamental choices give rise to some of the branches of RL with which we are very familiar. And so those, as you mentioned, there is a choice of what's specified or modeled explicitly. And the idea is that all of these are somehow implicitly learned within the system. So it's almost a choice of how you approach a problem. Do you see those as fundamental differences or are these almost like small specifics, like the details of how you solve the problem but they're not fundamentally different from each other? I think the fundamental idea is maybe at the higher level, the fundamental idea is the first step of the decomposition is really to say, well, how are we really gonna solve any kind of problem where you're trying to figure out how to take actions and just from this stream of observations, you've got some agent situated in its sensory motor stream and getting all these observations in and getting to take these actions and what should it do? You can even broach that problem. Maybe the complexity of the world is so great that you can't even imagine how to build a system that would understand how to deal with that. And so the first step of this decomposition is to say, well, you have to learn, the system has to learn for itself. And so note that the reinforcement learning problem doesn't actually stipulate that you have to learn. Like you could maximize your rewards without learning, it would just, wouldn't do a very good job of it. So learning is required because it's the only way to achieve good performance in any sufficiently large and complex environment. So that's the first step. And so that step gives commonality to all of the other pieces. Because now you might ask, well, what should you be learning? What does learning even mean? You know, in this sense, learning might mean, well, you're trying to update the parameters of some system which is then the thing that actually picks the actions. And those parameters could be representing anything. They could be parameterizing a value function or a model or a policy. And so in that sense, there's a lot of commonality in that whatever is being represented there is the thing which is being learned and it's being learned with the ultimate goal of maximizing rewards. But the way in which you decompose the problem is really what gives the semantics to the whole system. Like are you trying to learn something to predict well, like a value function or a model, are you learning something to perform well, like a policy? And the form of that objective, like it's kind of giving the semantics to the system. And so it really is at the next level down, a fundamental choice. And we have to make those fundamental choices as system designers or enable our algorithms to be able to learn how to make those choices for themselves. So then the next step you mentioned, the very first thing you have to deal with is, can you even take in this huge stream of observations and do anything with it? So the natural next basic question is, what is deep reinforcement learning? And what is this idea of using neural networks to deal with this huge incoming stream? So amongst all the approaches for reinforcement learning, deep reinforcement learning is one family of solution methods that tries to utilize powerful representations that are offered by neural networks to represent any of these different components of the solution, of the agent, like whether it's the value function or the model or the policy. The idea of deep learning is to say, well, here's a powerful toolkit that's so powerful that it's universal in the sense that it can represent any function and it can learn any function. And so if we can leverage that universality, that means that whatever we need to represent for our policy or for our value function or for a model, deep learning can do it. So that deep learning is one approach that offers us a toolkit that has no ceiling to its performance, that as we start to put more resources into the system, more memory and more computation and more data, more experience, more interactions with the environment, that these are systems that can just get better and better and better at doing whatever the job is they've asked them to do, whatever we've asked that function to represent, it can learn a function that does a better and better job of representing that knowledge, whether that knowledge be estimating how well you're gonna do in the world, the value function, whether it's gonna be choosing what to do in the world, the policy, or whether it's understanding the world itself, what's gonna happen next, the model. Nevertheless, the fact that neural networks are able to learn incredibly complex representations that allow you to do the policy, the model, or the value function is, at least to my mind, exceptionally beautiful and surprising. Like, was it surprising to you? Can you still believe it works as well as it does? Do you have good intuition about why it works at all and works as well as it does? I think, let me take two parts to that question. I think it's not surprising to me that the idea of reinforcement learning works because in some sense, I think it's, I feel it's the only thing which can ultimately. And so I feel we have to address it and there must be successes possible because we have examples of intelligence and it must at some level be able to, possible to acquire experience and use that experience to do better in a way which is meaningful to environments of the complexity that humans can deal with. It must be. Am I surprised that our current systems can do as well as they can do? I think one of the big surprises for me and a lot of the community is really the fact that deep learning can continue to perform so well despite the fact that these neural networks that they're representing have these incredibly nonlinear kind of bumpy surfaces, which to our kind of low dimensional intuitions make it feel like surely you're just gonna get stuck and learning will get stuck because you won't be able to make any further progress. And yet the big surprise is that learning continues and these, what appear to be local optima turn out not to be because in high dimensions when we make really big neural nets, there's always a way out and there's a way to go even lower and then you're still not in a local optima because there's some other pathway that will take you out and take you lower still. And so no matter where you are, learning can proceed and do better and better and better without bound. And so that is a surprising and beautiful property of neural nets, which I find elegant and beautiful and somewhat shocking that it turns out to be the case. As you said, which I really like, to our low dimensional intuitions, that's surprising. Yeah, we're very tuned to working within a three dimensional environment. And so to start to visualize what a billion dimensional neural network surface that you're trying to optimize over, what that even looks like is very hard for us. And so I think that really, if you try to account for the essentially the AI winter, where people gave up on neural networks, I think it's really down to that lack of ability to generalize from low dimensions to high dimensions because back then we were in the low dimensional case. People could only build neural nets with 50 nodes in them or something. And to imagine that it might be possible to build a billion dimensional neural net and that it might have a completely different qualitatively different property was very hard to anticipate. And I think even now we're starting to build the theory to support that. And it's incomplete at the moment, but all of the theory seems to be pointing in the direction that indeed this is an approach which truly is universal, both in its representational capacity, which was known, but also in its learning ability, which is surprising. And it makes one wonder what else we're missing due to our low dimensions intuitions that will seem obvious once it's discovered. I often wonder, when we one day do have AIs which are superhuman in their abilities to understand the world, what will they think of the algorithms that we developed back now? Will it be looking back at these days and thinking that, will we look back and feel that these algorithms were naive first steps or will they still be the fundamental ideas which are used even in a hundred thousand, 10,000 years? Hard to know. They'll watch back to this conversation and with a smile, maybe a little bit of a laugh. I mean, my sense is, I think just like when we used to think that the sun revolved around the earth, they'll see our systems of today reinforcement learning as too complicated, that the answer was simple all along. There's something, just like you said in the game of Go, I mean, I love the systems of like cellular automata, that there's simple rules from which incredible complexity emerges. So it feels like there might be some really simple approaches, just like where Sutton says, right? These simple methods with compute over time seem to prove to be the most effective. I 100% agree. I think that if we try to anticipate what will generalize well into the future, I think it's likely to be the case that it's the simple, clear ideas which will have the longest legs and which will carry us furthest into the future. Nevertheless, we're in a situation where we need to make things work today. And sometimes that requires putting together more complex systems where we don't have the full answers yet as to what those minimal ingredients might be. So speaking of which, if we could take a step back to Go, what was MoGo and what was the key idea behind the system? So back during my PhD on Computer Go, around about that time, there was a major new development which actually happened in the context of Computer Go. And it was really a revolution in the way that heuristic search was done. And the idea was essentially that a position could be evaluated or a state in general could be evaluated not by humans saying whether that position is good or not, or even humans providing rules as to how you might evaluate it, but instead by allowing the system to randomly play out the game until the end, multiple times and taking the average of those outcomes as the prediction of what will happen. So for example, if you're in the game of Go, the intuition is that you take a position and you get the system to kind of play random moves against itself all the way to the end of the game and you see who wins. And if black ends up winning more of those random games than white, well, you say, hey, this is a position that favors white. And if white ends up winning more of those random games than black, then it favors white. So that idea was known as Monte Carlo search and a particular form of Monte Carlo search that became very effective and was developed in Computer Go first by Remy Coulomb in 2006, and then taken further by others was something called Monte Carlo tree search, which basically takes that same idea and uses that insight to evaluate every node of a search tree is evaluated by the average of the random playouts from that node onwards. And this idea was very powerful and suddenly led to huge leaps forward in the strength of Computer Go playing programs. And among those, the strongest of the Go playing programs in those days was a program called MoGo, which was the first program to actually reach human master level on small boards, nine by nine boards. And so this was a program by someone called Sylvain Gelly, who's a good colleague of mine, but I worked with him a little bit in those days, part of my PhD thesis. And MoGo was a first step towards the latest successes we saw in Computer Go, but it was still missing a key ingredient. MoGo was evaluating purely by random rollouts against itself. And in a way it's truly remarkable that random play should give you anything at all. Like why in this perfectly deterministic game that's very precise and involves these very exact sequences, why is it that randomization is helpful? And so the intuition is that randomization captures something about the nature of the search tree, from a position that you're understanding the nature of the search tree from that node onwards by using randomization. And this was a very powerful idea. And I've seen this in other spaces, talked to Richard Karp and so on, randomized algorithms somehow magically are able to do exceptionally well and simplifying the problem somehow. Makes you wonder about the fundamental nature of randomness in our universe. It seems to be a useful thing. But so from that moment, can you maybe tell the origin story and the journey of AlphaGo? Yeah, so programs based on Monte Carlo Tree Search were a first revolution in the sense that they led to suddenly programs that could play the game to any reasonable level, but they plateaued. It seemed that no matter how much effort people put into these techniques, they couldn't exceed the level of amateur Dan level Go players. So strong players, but not anywhere near the level of professionals, nevermind the world champion. And so that brings us to the birth of AlphaGo, which happened in the context of a startup company known as DeepMind. I heard of them. Where a project was born, and the project was really a scientific investigation where myself and Ajah Huang and an intern, Chris Madison, were exploring a scientific question. And that scientific question was really, is there another fundamentally different approach to this key question of Go, the key challenge of how can you build that intuition? And how can you just have a system that could look at a position and understand what move to play or how well you're doing in that position, who's gonna win? And so the deep learning revolution had just begun. That systems like ImageNet had suddenly been won by deep learning techniques back in 2012. And following that, it was natural to ask, well, if deep learning is able to scale up so effectively with images to understand them enough to classify them, well, why not go? Why not take the black and white stones of the Go board and build a system which can understand for itself what that means in terms of what move to pick or who's gonna win the game, black or white? And so that was our scientific question which we were probing and trying to understand. And as we started to look at it, we discovered that we could build a system. So in fact, our very first paper on AlphaGo was actually a pure deep learning system, which was trying to answer this question. And we showed that actually a pure deep learning system with no search at all was actually able to reach human ban level, master level at the full game of Go, 19 by 19 boards. And so without any search at all, suddenly we had systems which were playing at the level of the best Monte Carlo tree search systems, the ones with randomized rollouts. So first of all, sorry to interrupt, but that's kind of a groundbreaking notion. That's like basically a definitive step away from a couple of decades of essentially search dominating AI. So how does that make you feel? Was it surprising from a scientific perspective in general, how to make you feel? I found this to be profoundly surprising. In fact, it was so surprising that we had a bet back then and like many good projects, bets are quite motivating and the bet was whether it was possible for a system based purely on deep learning, no search at all, to beat a down level human player. And so we had someone who joined our team who was a down level player. He came in and we had this first match against him. And- Which side of the bet were you on, by the way? Did you have the losing or the winning side? I tend to be an optimist with the power of deep learning and reinforcement learning. So the system won and we were able to beat this human down level player. And for me, that was the moment where it was like, okay, something special is afoot here. We have a system which without search is able to already just look at this position and understand things as well as a strong human player. And from that point onwards, I really felt that reaching the top levels of human play, professional level, world champion level, I felt it was actually an inevitability. And if it was an inevitable outcome, I was rather keen that it would be us that achieved it. So we scaled up. This was something where, so I had lots of conversations back then with Demis Hassabis, the head of DeepMind, who was extremely excited. And we made the decision to scale up the project, brought more people on board. And so AlphaGo became something where we had a clear goal, which was to try and crack this outstanding challenge of AI to see if we could beat the world's best players. And this led within the space of not so many months to playing against the European champion, Fan Hui, in a match which became memorable in history as the first time a Go program had ever beaten a professional player. And at that time, we had to make a judgment as to whether, when and whether we should go and challenge the world champion. And this was a difficult decision to make. Again, we were basing our predictions on our own progress and had to estimate based on the rapidity of our own progress when we thought we would exceed the level of the human world champion. And we tried to make an estimate and set up a match. And that became the AlphaGo versus Lee Sedol match in 2016. And we should say, spoiler alert, that AlphaGo was able to defeat Lee Sedol. That's right, yeah. So maybe we could take even a broader view. AlphaGo involves both learning from expert games and as far as I remember, a self-play component to where it learns by playing against itself. But in your sense, what was the role of learning from expert games there? And in terms of your self-evaluation, whether you can take on the world champion, what was the thing that you're trying to do more of, sort of train more on expert games, or was there now another, I'm asking so many poorly phrased questions, but did you have a hope or dream that self-play would be the key component at that moment yet? So in the early days of AlphaGo, we used human data to explore the science of what deep learning can achieve. And so when we had our first paper that showed that it was possible to predict the winner of the game, that it was possible to suggest moves, that was done using human data. Oh, solely human data. Yeah, and so the reason that we did it that way was at that time we were exploring separately the deep learning aspect from the reinforcement learning aspect. That was the part which was new and unknown to me at that time, was how far could that be stretched? Once we had that, it then became natural to try and use that same representation and see if we could learn for ourselves using that same representation. And so right from the beginning, actually our goal had been to build a system using self-play and to us, the human data right from the beginning was an expedient step to help us for pragmatic reasons to go faster towards the goals of the project than we might be able to starting solely from self-play. And so in those days, we were very aware that we were choosing to use human data and that might not be the long-term holy grail of AI, but that it was something which was extremely useful to us. It helped us to understand the system. It helped us to build deep learning representations which were clear and simple and easy to use. And so really I would say it served a purpose, not just as part of the algorithm, but something which I continue to use in our research today, which is trying to break down a very hard challenge into pieces which are easier to understand for us as researchers and develop. So if you use a component based on human data, it can help you to understand the system such that then you can build the more principled version later that does it for itself. So as I said, the AlphaGo victory, and I don't think I'm being sort of romanticizing this notion I think it's one of the greatest moments in the history of AI. So were you cognizant of this magnitude of the accomplishment at the time? I mean, are you cognizant of it even now? Because to me, I feel like it's something that would, we mentioned what the AGI systems of the future will look back. I think they'll look back at the AlphaGo victory as like, holy crap, they figured it out. This is where it started. Well, thank you again. I mean, it's funny, because I guess I've been working on, I've been working on ComputerGo for a long time. So I'd been working at the time of the AlphaGo match on ComputerGo for more than a decade. And throughout that decade, I'd had this dream of what would it be like to, what would it be like really to actually be able to build a system that could play against the world champion and I imagined that that would be an interesting moment that maybe some people might care about that and that this might be a nice achievement. But I think when I arrived in Seoul and discovered the legions of journalists that were following us around and the 100 million people that were watching the match online live, I realized that I'd been off in my estimation of how significant this moment was by several orders of magnitude. And so there was definitely an adjustment process to realize that this was something which the world really cared about and which was a watershed moment. And I think there was that moment of realization. It was also a little bit scary because, if you go into something thinking it's gonna be maybe of interest and then discover that 100 million people are watching, it suddenly makes you worry about whether some of the decisions you'd made were really the best ones or the wisest or were going to lead to the best outcome. And we knew for sure that there were still imperfections in AlphaGo which were gonna be exposed to the whole world watching. And so, yeah, it was, I think, a great experience and I feel privileged to have been part of it, privileged to have led that amazing team. I feel privileged to have been in a moment of history, like you say, but also lucky that, in a sense, I was insulated from the knowledge of, I think it would have been harder to focus on the research if the full kind of reality of what was gonna come to pass had been known to me and the team. I think it was, we were in our bubble and we were working on research and we were trying to answer the scientific questions and then bam, the public sees it. And I think it was better that way in retrospect. Were you confident that, I guess, what were the chances that you could get the win? So, just like you said, I'm a little bit more familiar with another accomplishment that we may not even get a chance to talk to. I talked to Oriol Vinales about AlphaStar which is another incredible accomplishment. But here, with AlphaStar and beating the StarCraft, there was already a track record. With AlphaGo, this is the really first time you get to see reinforcement learning and face the best team in the world. So, what was your confidence like? What was the odds? Well, we actually- Was there a bet? Funnily enough, there was. So, just before the match, we weren't betting on anything concrete, but we all held out a hand. Everyone in the team held out a hand at the beginning of the match. And the number of fingers that they had out on that hand was supposed to represent how many games they thought we would win against Lee Sedol. And there was an amazing spread in the team's predictions. But I have to say, I predicted 4-1. And the reason was based purely on data. So, I'm a scientist first and foremost. And one of the things which we had established was that AlphaGo, in around one in five games, would develop something which we called a delusion, which was a kind of hole in its knowledge where it wasn't able to fully understand everything about the position. And that hole in its knowledge would persist for tens of moves throughout the game. And we knew two things. We knew that if there were no delusions, that AlphaGo seemed to be playing at a level that was far beyond any human capabilities. But we also knew that if there were delusions, the opposite was true. And in fact, that's what came to pass. We saw all of those outcomes. And Lee Sedol, in one of the games, played a really beautiful sequence that AlphaGo just hadn't predicted. And after that, it led it into this situation where it was unable to really understand the position fully and found itself in one of these delusions. So, indeed, 4-1 was the outcome. So, yeah, and can you maybe speak to it a little bit more? What were the five games? Like, what happened? Is there interesting things that come to memory in terms of the play of the human or the machine? So, I remember all of these games vividly, of course. You know, moments like these don't come too often in the lifetime of a scientist. And the first game was magical because it was the first time that a computer program had defeated a world champion in this grand challenge of Go. And there was a moment where AlphaGo invaded Lee Sedol's territory towards the end of the game. And that's quite an audacious thing to do. It's like saying, hey, you thought this was gonna be your territory in the game, but I'm gonna stick a stone right in the middle of it and prove to you that I can break it up. And Lee Sedol's face just dropped. He wasn't expecting a computer to do something that audacious. The second game became famous for a move known as Move 37. This was a move that was played by AlphaGo that broke all of the conventions of Go. That the Go players were so shocked by this, they thought that maybe the operator had made a mistake. They thought that there was something crazy going on. And it just broke every rule that Go players are taught from a very young age. They're just taught this kind of move called a shoulder hit. You can only play it on the third line or the fourth line. And AlphaGo played it on the fifth line. And it turned out to be a brilliant move and made this beautiful pattern in the middle of the board that ended up winning the game. And so this really was a clear instance where we could say computers exhibited creativity. That this was really a move that was something humans hadn't known about, hadn't anticipated. And computers discovered this idea. They were the ones to say, actually, here's a new idea. Something new, not in the domains of human knowledge of the game. And now the humans think this is a reasonable thing to do. And it's part of Go knowledge now. The third game, something special happens when you play against a human world champion. Which again, I hadn't anticipated before going there. Which is, these players are amazing. Lee Sedol was a true champion, 18 time world champion. And had this amazing ability to probe AlphaGo for weaknesses of any kind. And in the third game, he was losing and we felt we were sailing comfortably to victory. But he managed to, from nothing, stir up this fight and build what's called a double co, these kind of repetitive positions. And he knew that historically, no computer Go program had ever been able to deal correctly with double co positions. And he managed to summon one out of nothing. And so for us, this was a real challenge. Like would AlphaGo be able to deal with this? Or would it just kind of crumble in the face of this situation? And fortunately it dealt with it perfectly. The fourth game was amazing in that Lee Sedol appeared to be losing this game. AlphaGo thought it was winning. And then Lee Sedol did something which I think only a true world champion can do. Which is, he found a brilliant sequence in the middle of the game. A brilliant sequence that led him to really just transform their position. He found just a piece of genius really. And after that, AlphaGo, it's evaluation just tumbled it thought it was winning this game. And all of a sudden it tumbled and said, oh, now I've got no chance. And it starts to behave rather oddly at that point. In the final game, for some reason, we as a team were convinced having seen AlphaGo in the previous game suffer from delusions. We as a team were convinced that it was suffering from another delusion. We were convinced that it was mis-evaluating the position and that something was going terribly wrong. And it was only in the last few moves of the game that we realized that actually, although it had been predicting it was gonna win all the way through, it really was. And so somehow, it just taught us yet again that you have to have faith in your systems. When they exceed your own level of ability and your own judgment, you have to trust in them to know better than you, the designer. Once you've bestowed in them the ability to judge better than you can, then trust the system to do so. So just like in the case of Deep Blue beating Garry Kasparov, so Garry was, I think, the first time he's ever lost, actually, to anybody. And I mean, there's a similar situation with Lee Sedol. It's a tragic loss for humans, but a beautiful one. I think that's kind of, from the tragedy, sort of emerges over time, emerges a kind of inspiring story. But Lee Sedol recently announced his retirement. I don't know if we can look too deeply into it, but he did say that even if I become number one, there's an entity that cannot be defeated. So what do you think about these words? What do you think about his retirement from the game and go? Well, let me take you back, first of all, to the first part of your comment about Garry Kasparov, because actually at the panel yesterday, he specifically said that when he first lost to Deep Blue, he viewed it as a failure. He viewed that this had been a failure of his, but later on in his career, he said he'd come to realize that actually it was a success. It was a success for everyone because this marked a transformational moment for AI. And so even for Garry Kasparov, he came to realize that that moment was pivotal and actually meant something much more than his personal loss in that moment. Lee Sedol, I think, was much more cognizant of that, even at the time. So in his closing remarks to the match, he really felt very strongly that what had happened in the AlphaGo match was not only meaningful for AI, but for humans as well. And he felt as a Go player that it had opened his horizons and meant that he could start exploring new things. It brought his joy back for the game of Go because it had broken all of the conventions and barriers and meant that suddenly anything was possible again. And so I was sad to hear that he'd retired, but he's been a great world champion over many, many years. And I think he'll be remembered for that evermore. He'll be remembered as the last person to beat AlphaGo. I mean, after that, we increased the power of the system and the next version of AlphaGo beats the other strong human players 60 games to nil. So what a great moment for him and something to be remembered for. It's interesting that you spent time at AAAI on a panel with Garry Kasparov. So what, I mean, it's almost, I'm just curious to learn the conversations you've had with Garry and the, cause he's also now, he's written a book about artificial intelligence. He's thinking about AI. He has kind of a view of it. And he talks about AlphaGo a lot. What's your sense? Arguably, I'm not just being Russian, but I think Garry is the greatest chess player of all time. The probably one of the greatest game players of all time. And you sort of at the center of creating a system that beats one of the greatest players of all time. So what's that conversation like? Is there anything, any interesting digs, any bets, any funny things, any profound things? So Garry Kasparov has an incredible respect for what we did with AlphaGo. And it's an amazing tribute coming from him of all people that he really appreciates and respects what we've done. And I think he feels that the progress which has happened in computer chess, which later after AlphaGo, we built the AlphaZero system, which defeated the world's strongest chess programs. And to Garry Kasparov, that moment in computer chess was more profound than Deep Blue. And the reason he believes it mattered more was because it was done with learning and a system which was able to discover for itself new principles, new ideas, which were able to play the game in a way which he hadn't always known about or anyone. And in fact, one of the things I discovered at this panel was that the current world champion, Magnus Carlsen, apparently recently commented on his improvement in performance and he attributes it to AlphaZero. He's been studying the games of AlphaZero and he's changed his style to play more like AlphaZero. And it's led to him actually increasing his rating to a new peak. Yeah, I guess to me, just like to Garry, the inspiring thing is that, and just like you said with reinforcement learning, reinforcement learning and deep learning, machine learning feels like what intelligence is. And you could attribute it to sort of a bitter viewpoint from Garry's perspective, from us humans' perspective, saying that pure search that IBM Deep Blue was doing is not really intelligence, but somehow it didn't feel like it. And so that's the magical, I'm not sure what it is about learning that feels like intelligence, but it does. So I think we should not demean the achievements of what was done in previous eras of AI. I think that Deep Blue was an amazing achievement in itself. And that heuristic search of the kind that was used by Deep Blue had some powerful ideas that were in there, but it also missed some things. So the fact that the evaluation function, the way that the chess position was understood was created by humans and not by the machine is a limitation, which means that there's a ceiling on how well it can do, but maybe more importantly, it means that the same idea cannot be applied in other domains where we don't have access to the kind of human grandmasters and that ability to kind of encode exactly their knowledge into an evaluation function. And the reality is that the story of AI is that most domains turn out to be of the second type, where when knowledge is messy, it's hard to extract from experts or isn't even available. And so we need to solve problems in a different way. And I think AlphaGo is a step towards solving things in a way which puts learning as a first-class citizen and says systems need to understand for themselves how to understand the world, how to judge the value of any action that they might take within that world and any state they might find themselves in. And in order to do that, we make progress towards AI. Yeah, so one of the nice things about this, about taking a learning approach to the game of Go or game playing is that the things you learn, the things you figure out are actually going to be applicable to other problems that are real-world problems. That's sort of, that's ultimately, I mean, there's two really interesting things about AlphaGo. One is the science of it, just the science of learning, the science of intelligence. And then the other is, well, you're actually learning to figuring out how to build systems that would be potentially applicable in other applications, medical, autonomous vehicles, robotics, all, I mean, it's just open the door to all kinds of applications. So the next incredible step, right, really the profound step is probably AlphaGo Zero. I mean, it's arguable, I kind of see them all as the same place but really, and perhaps you were already thinking that AlphaGo Zero is the natural, it was always going to be the next step, but it's removing the reliance on human expert games for pre-training, as you mentioned. So how big of an intellectual leap was this that self-play could achieve superhuman level performance on its own? And maybe could you also say what is self-play? We kind of mentioned it a few times, but. So let me start with self-play. So the idea of self-play is something which is really about systems learning for themselves, but in the situation where there's more than one agent. And so if you're in a game, and the game is played between two players, then self-play is really about understanding that game just by playing games against yourself rather than against any actual real opponent. And so it's a way to kind of discover strategies without having to actually need to go out and play against any particular human player, for example. The main idea of AlphaZero was really to, you know, try and step back from any of the knowledge that we'd put into the system and ask the question, is it possible to come up with a single elegant principle by which a system can learn for itself all of the knowledge which it requires to play a game such as Go? Importantly, by taking knowledge out, you not only make the system less brittle in the sense that perhaps the knowledge you were putting in was just getting in the way and maybe stopping the system learning for itself, but also you make it more general. The more knowledge you put in, the harder it is for a system to actually be placed, taken out of the system in which it's kind of been designed and placed in some other system that maybe would need a completely different knowledge base to understand and perform well. And so the real goal here is to strip out all of the knowledge that we put in to the point that we can just plug it into something totally different. And that to me is really, you know, the promise of AI is that we can have systems such as that, which, you know, no matter what the goal is, no matter what goal we set to the system, we can come up with, we have an algorithm which can be placed into that world, into that environment, and can succeed in achieving that goal. And then that's, to me, is almost the essence of intelligence, if we can achieve that. And so AlphaZero is a step towards that. And it's a step that was taken in the context of two-player perfect information games like Go and chess. We also applied it to Japanese chess. So just to clarify, the first step was AlphaGo Zero. The first step was to try and take all of the knowledge out of AlphaGo in such a way that it could play in a fully self-discovered way, purely from self-play. And to me, the motivation for that was always that we could then plug it into other domains, but we saved that until later. Well, in fact, I mean, just for fun, I could tell you exactly the moment where the idea for AlphaZero occurred to me, because I think there's maybe a lesson there for researchers who are kind of too deeply embedded in their research and working 24-7 to try and come up with the next idea, which is, it actually occurred to me on honeymoon. And I was like at my most fully relaxed state, really enjoying myself, and just bing, this like the algorithm for AlphaZero just appeared and in its full form. And this was actually before we played against Lisa Doll, but we just didn't, I think we were so busy trying to make sure we could beat the world champion, that it was only later that we had the opportunity to step back and start examining that sort of deeper scientific question of whether this could really work. So nevertheless, so self-play is probably one of the most sort of profound ideas that represents, to me at least, artificial intelligence. But the fact that you could use that kind of mechanism to again beat world-class players, that's very surprising. So we kind of, to me it feels like you have to train in a large number of expert games. So was it surprising to you? What was the intuition? Can you sort of think, not necessarily at that time, even now, what's your intuition? Why this thing works so well? Why it's able to learn from scratch? Well, let me first say why we tried it. So we tried it both because I feel that it was the deeper scientific question to be asking to make progress towards AI. And also because in general in my research, I don't like to do research on questions for which we already know the likely outcome. I don't see much value in running an experiment where you're 95% confident that you will succeed. And so we could have tried maybe to take AlphaGo and do something which we knew for sure it would succeed on. But much more interesting to me was to try it on the things which we weren't sure about. And one of the big questions on our minds back then was, could you really do this with self-play alone? How far could that go? Would it be as strong? And honestly, we weren't sure. Yeah, it was 50-50, I think. If you'd asked me, I wasn't confident that it could reach the same level as these systems, but it felt like the right question to ask. And even if it had not achieved the same level, I felt that that was an important direction to be studying. And so then lo and behold, it actually ended up outperforming the previous version of AlphaGo and indeed was able to beat it by 100 games to zero. So what's the intuition as to why? I think the intuition to me is clear, that whenever you have errors in a system, as we did in AlphaGo, AlphaGo suffered from these delusions. Occasionally it would misunderstand what was going on in a position and mis-evaluate it. How can you remove all of these errors? Errors arise from many sources. For us, they were arising both from, starting from the human data, but also from the nature of the search and the nature of the algorithm itself. But the only way to address them in any complex system is to give the system the ability to correct its own errors. It must be able to correct them. It must be able to learn for itself when it's doing something wrong and correct for it. And so it seemed to me that the way to correct delusions was indeed to have more iterations of reinforcement learning. No matter where you start, you should be able to correct for those errors until it gets to play that out and understand, oh, well, I thought that I was gonna win in this situation, but then I ended up losing. That suggests that I was mis-evaluating something and there's a hole in my knowledge and now the system can correct for itself and understand how to do better. Now, if you take that same idea and trace it back all the way to the beginning, it should be able to take you from no knowledge, from completely random starting point, all the way to the highest levels of knowledge that you can achieve in a domain. And the principle is the same, that if you bestow a system with the ability to correct its own errors, then it can take you from random to something slightly better than random because it sees the stupid things that the random is doing and it can correct them. And then it can take you from that slightly better system and understand, well, what's that doing wrong? And it takes you on to the next level and the next level. And this progress can go on indefinitely. And indeed, what would have happened if we'd carried on training AlphaGo Zero for longer? We saw no sign of it slowing down its improvements, or at least it was certainly carrying on to improve. And presumably, if you had the computational resources, this could lead to better and better systems that discover more and more. So your intuition is fundamentally there's not a ceiling to this process. One of the surprising things, just like you said, is the process of patching errors. It intuitively makes sense. And reinforcement learning should be part of that process. But what is surprising is in the process of patching your own lack of knowledge, you don't open up other patches. You keep sort of... Like there's a monotonic decrease of your weaknesses. Well, let me back this up. I think science always should make falsifiable hypotheses. So let me back up this claim with a falsifiable hypothesis, which is that if someone was to, in the future, take AlphaZero as an algorithm and run it with greater computational resources that we had available today, then I would predict that they would be able to beat the previous system 100 games to zero. And that if they were then to do the same thing a couple of years later, that that would beat that previous system 100 games to zero. And that that process would continue indefinitely throughout at least my human lifetime. Presumably the game of Go would set the ceiling. I mean- The game of Go would set the ceiling, but the game of Go has 10 to the 170 states in it. So the ceiling is unreachable by any computational device that can be built out of the 10 to the 80 atoms in the universe. You asked a really good question, which is, do you not open up other errors when you correct your previous ones? And the answer is yes, you do. And so it's a remarkable fact about this class of two-player game, and also true of single-agent games, that essentially progress will always lead you to, if you have sufficient representational resource, like imagine you had, could represent every state in a big table of the game, then we know for sure that a progress of self-improvement will lead all the way in the single-agent case to the optimal possible behavior, and in the two-player case to the minimax optimal behavior. That is the best way that I can play, knowing that you're playing perfectly against me. And so for those cases, we know that even if you do open up some new error, that in some sense you've made progress. You're progressing towards the best that can be done. So AlphaGo was initially trained on expert games with some self-play. AlphaGo Zero removed the need to be trained on expert games. And then another incredible step for me, cause I just love chess, is to generalize that further to be in AlphaZero, to be able to play the game of Go, beating AlphaGo Zero and AlphaGo, and then also being able to play the game of chess and others. So what was that step like? What's the interesting aspects there that required to make that happen? I think the remarkable observation which we saw with AlphaZero was that actually without modifying the algorithm at all, it was able to play and crack some of AI's greatest previous challenges. In particular, we dropped it into the game of chess. And unlike the previous systems like Deep Blue, which had been worked on for years and years, and we were able to beat the world's strongest computer chess program convincingly using a system that was fully discovered by its own from scratch with its own principles. And in fact, one of the nice things that we found was that in fact, we also achieved the same results in Japanese chess, a variant of chess where you get to capture pieces and then place them back down on your own side as an extra piece. So a much more complicated variant of chess. And we also beat the world's strongest programs and reach superhuman performance in that game too. And it was the very first time that we'd ever run the system on that particular game was the version that we published in the paper on AlphaZero. It just worked out of the box, literally, no touching it. We didn't have to do anything. And there it was superhuman performance, no tweaking, no twiddling. And so I think there's something beautiful about that principle that you can take an algorithm and without twiddling anything, it just works. Now to go beyond AlphaZero, what's required? AlphaZero is just a step. And there's a long way to go beyond that to really crack the deep problems of AI. But one of the important steps is to acknowledge that the world is a really messy place. You know, it's this rich, complex, beautiful, but messy environment that we live in. And no one gives us the rules. Like no one knows the rules of the world. At least maybe we understand that it operates according to Newtonian or quantum mechanics at the micro level, or according to relativity at the macro level, but that's not a model that's useful for us as people to operate in it. Somehow the agent needs to understand the world for itself in a way where no one tells it the rules of the game, and yet it can still figure out what to do in that world, deal with this stream of observations coming in, rich sensory input coming in, actions going out in a way that allows it to reason in the way that AlphaGo or AlphaZero can reason, in the way that these Go and chess playing programs can reason, but in a way that allows it to take actions in that messy world to achieve its goals. And so this led us to the most recent step in the story of AlphaGo, which was a system called MuZero. And MuZero is a system which learns for itself even when the rules are not given to it. It actually can be dropped into a system with messy perceptual inputs. We actually tried it in some Atari games, the canonical domains of Atari that have been used for reinforcement learning. And this system learned to build a model of these Atari games that was sufficiently rich and useful enough for it to be able to plan successfully. And in fact, that system not only went on to beat the state of the art in Atari, but the same system without modification was able to reach the same level of superhuman performance in Go, chess, and shogi that we'd seen in AlphaZero, showing that even without the rules, the system can learn for itself just by trial and error, just by playing this game of Go. And no one tells you what the rules are, but you just get to the end and someone says, you know, win or loss. You play this game of chess and someone says win or loss, or you play a game of breakout in Atari and someone just tells you, you know, your score at the end. And the system for itself figures out essentially the rules of the system, the dynamics of the world, how the world works. And not in any explicit way, but just implicitly enough understanding for it to be able to plan in that system in order to achieve its goals. And that's the fundamental process that you have to go through when you're facing any uncertain kind of environment that you would in the real world, is figuring out the sort of the rules, the basic rules of the game. That's right. So, I mean, yeah, that allows it to be applicable to basically any domain that could be digitized in the way that it needs to in order to be consumable, sort of in order for the reinforcement learning framework to be able to sense the environment, to be able to act in the environment and so on. The full reinforcement learning problem needs to deal with worlds that are unknown and complex and the agent needs to learn for itself how to deal with that. And so Museo is a step, a further step in that direction. One of the things that inspired the general public in just in conversations I have, like with my parents or something, or my mom that just loves what was done is kind of at least the notion that there was some display of creativity, some new strategies, new behaviors that were created. That again has echoes of intelligence. So is there something that stands up? Do you see it the same way that there's creativity and there's some behaviors, patterns that you saw that AlphaZero was able to display that are truly creative? So let me start by saying that I think we should ask what creativity really means. So to me, creativity means discovering something which wasn't known before, something unexpected, something outside of our norms. And so in that sense, the process of reinforcement learning or the self-play approach that was used by AlphaZero is the essence of creativity. It's really saying at every stage, you're playing according to your current norms and you try something. And if it works out, you say, hey, here's something great, I'm gonna start using that. And then that process, it's like a micro discovery that happens millions and millions of times over the course of the algorithm's life, where it just discovers some new idea. Oh, this pattern, this pattern's working really well for me. I'm gonna start using that. And now, oh, here's this other thing I can do. I can start to connect these stones together in this way, or I can start to sacrifice stones or give up on pieces or play shoulder hits on the fifth line or whatever it is. The system's discovering things like this for itself continually, repeatedly, all the time. And so it should come as no surprise to us then when, if you leave these systems going, that they discover things that are not known to humans, that to the human norms are considered creative. And we've seen this several times. In fact, in AlphaGo Zero, we saw this beautiful timeline of discovery where what we saw was that there were these opening patterns that humans play called joseki. These are like the patterns that humans learn to play in the corners, and they've been developed and refined over literally thousands of years in the game of Go. And what we saw was in the course of the training AlphaGo Zero, over the course of the 40 days that we trained this system, it starts to discover exactly these patterns that human players play. And over time, we found that all of the joseki that humans played were discovered by the system through this process of self-play and this sort of essential notion of creativity. But what was really interesting was that over time, it then starts to discard some of these in favor of its own joseki that humans didn't know about. And it starts to say, oh, well, you thought that the Knights move pincer joseki was a great idea, but here's something different you can do there, which makes some new variation that humans didn't know about. And actually now, the human Go players study the joseki that AlphaGo played, and they become the new norms that are used in today's top-level Go competitions. That never gets old. Even just the first, to me, maybe just makes me feel good as a human being, that a self-play mechanism that knows nothing about us humans discovers patterns that we humans do. It's like an affirmation that we're doing okay as humans. Yeah. In this domain, in other domains, we figured out, it's like the Churchill quote about democracy. It sucks, but it's the best one we've tried. So in general, taking a step outside of Go, and you have a million accomplishments that I have no time to talk about, with AlphaStar and so on, and the current work. But in general, this self-play mechanism that you've inspired the world with by beating the world champion Go player, do you see that as, do you see it being applied in other domains? Do you have sort of dreams and hopes that it's applied in both the simulated environments and the constrained environments of games? Constrained, I mean, AlphaStar really demonstrates that you can remove a lot of the constraints, but nevertheless, it's in a digital simulated environment. Do you have a hope, a dream, that it starts being applied in the robotics environment? And maybe even in domains that are safety critical and so on, and have a real impact in the real world, like autonomous vehicles, for example, which seems like a very far out dream at this point. So I absolutely do hope and imagine that we will get to the point where ideas just like these are used in all kinds of different domains. In fact, one of the most satisfying things as a researcher is when you start to see other people use your algorithms in unexpected ways. So in the last couple of years, there have been a couple of nature papers where different teams unbeknownst to us took AlphaZero and applied exactly those same algorithms and ideas to real world problems of huge meaning to society. So one of them was the problem of chemical synthesis, and they were able to beat the state of the art in finding pathways of how to actually synthesize chemicals, retro chemical synthesis. And the second paper actually just came out a couple of weeks ago in Nature, showed that in quantum computation, one of the big questions is how to understand the nature of the function in quantum computation. And a system based on AlphaZero beat the state of the art by quite some distance there again. So these are just examples. And I think that the lesson which we've seen elsewhere in machine learning time and time again is that if you make something general, it will be used in all kinds of ways. You provide a really powerful tool to society and those tools can be used in amazing ways. And so I think we're just at the beginning and for sure I hope that we see all kinds of outcomes. So the other side of the question of reinforcement learning framework is usually you wanna specify a reward function and an objective function. What do you think about sort of ideas of intrinsic rewards if we're not really sure about, if we take human beings as existence proof that we don't seem to be operating according to a single reward, do you think that there's interesting ideas for when you don't know how to truly specify the reward, that there's some flexibility for discovering it intrinsically or so on in the context of reinforcement learning? So I think when we think about intelligence, it's really important to be clear about the problem of intelligence. And I think it's clearest to understand that problem in terms of some ultimate goal that we want the system to try and solve for. And after all, if we don't understand the ultimate purpose of the system, do we really even have a clearly defined problem that we're solving at all? Now, within that, as with your example for humans, the system may choose to create its own motivations and sub-goals that help the system to achieve its ultimate goal. And that may indeed be a hugely important mechanism to achieve those ultimate goals, but there is still some ultimate goal I think the system needs to be measurable and evaluated against. And even for humans, I mean, humans, we're incredibly flexible. We feel that we can, any goal that we're given, we feel we can master to some degree. But if we think of those goals, really, like the goal of being able to pick up an object or the goal of being able to communicate or influence people to do things in a particular way or whatever those goals are, really they are sub-goals really that we set ourselves. We choose to pick up the object, we choose to communicate, we choose to influence someone else, and we choose those because we think it will lead us to something later on. We think that's helpful to us to achieve some ultimate goal. Now, I don't want to speculate whether or not humans as a system necessarily have a singular overall goal of survival or whatever it is, but I think the principle for understanding and implementing intelligence is, has to be that if we're trying to understand intelligence or implement our own, there has to be a well-defined problem. Otherwise, if it's not, I think it's like an admission of defeat. For there to be hope for understanding or implementing intelligence, we have to know what we're doing, we have to know what we're asking the system to do. Otherwise, if you don't have a clearly defined purpose, you're not gonna get a clearly defined answer. The ridiculous big question that has to naturally follow is I have to pin you down on this thing, that nevertheless, one of the big silly or big real questions before humans is the meaning of life, is us trying to figure out our own reward function. And you just kind of mentioned that if you want to build intelligent systems, and you know what you're doing, you should be at least cognizant to some degree of what the reward function is. So the natural question is, what do you think is the reward function of human life, the meaning of life for us humans, the meaning of our existence? I think I'd be speculating beyond my own expertise, but just for fun, let me do that. Yes, please. And say, I think that there are many levels at which you can understand the system and you can understand something as optimizing for a goal at many levels. And so you can understand the, let's start with the universe, like, does the universe have a purpose? Well, it feels like it's just one level, just following certain mechanical laws of physics, and that that's led to the development of the universe. But at another level, you can view it as, actually, there's the second law of thermodynamics that says that this is increasing in entropy over time forever. And now there's a view that's been developed by certain people at MIT that this, you can think of this as almost like a goal of the universe, that the purpose of the universe is to maximize entropy. So there are multiple levels at which you can understand the system. The next level down, you might say, well, if the goal is to maximize entropy, well, how do, how does, how can that be done by a particular system? And maybe evolution is something that the universe discovered in order to kind of dissipate energy as efficiently as possible. And by the way, I'm borrowing from Max Tegmark for some of these metaphors, the physicist. But if you can think of evolution as a mechanism for dispersing energy, then evolution, you might say, then becomes a goal, which is if evolution disperses energy by reproducing as efficiently as possible, what's evolution then? Well, it's now got its own goal within that, which is to actually reproduce as effectively as possible. And now how does reproduction, how is that made as effective as possible? Well, you need entities within that that can survive and reproduce as effectively as possible. And so it's natural that in order to achieve that high level goal, those individual organisms discover brains, intelligences, which enable them to support the goals of evolution. And those brains, what do they do? Well, perhaps the early brains, maybe they were controlling things at some direct level. Maybe they were the equivalent of pre-programmed systems, which were directly controlling what was going on and setting certain things in order to achieve these particular goals. But that led to another level of discovery, which was learning systems, parts of the brain which were able to learn for themselves and learn how to program themselves to achieve any goal. And presumably there are parts of the brain where goals are set to parts of that system and provides this very flexible notion of intelligence that we as humans presumably have, which is the ability to kind of, why the reason we feel that we can achieve any goal. So it's a very long-winded answer to say that, I think there are many perspectives and many levels at which intelligence can be understood. And at each of those levels, you can take multiple perspectives. You can view the system as something which is optimizing for a goal, which is understanding it at a level by which we can maybe implement it and understand it as AI researchers or computer scientists, or you can understand it at the level of the mechanistic thing which is going on, that there are these atoms bouncing around in the brain and they lead to the outcome of that system. It's not in contradiction with the fact that it's also a decision-making system that's optimizing for some goal and purpose. I've never heard the description of the meaning of life structured so beautifully in layers, but you did miss one layer, which is the next step, which you're responsible for, which is creating the artificial intelligence- Indeed. Layer on top of that. Indeed. And I can't wait to see, well, I may not be around, but I can't wait to see what the next layer beyond that. Well, let's just take that argument and pursue it to its natural conclusion. So the next level indeed is for, how can our learning brain achieve its goals most effectively? Well, maybe it does so by us as learning beings, building a system which is able to solve for those goals more effectively than we can. And so when we build a system to play the game of Go, when I said that I wanted to build a system that can play Go better than I can, I've enabled myself to achieve that goal of playing Go better than I could by directly playing it and learning it myself. And so now a new layer has been created, which is systems which are able to achieve goals for themselves. And ultimately there may be layers beyond that where they set sub goals to parts of their own system in order to achieve those and so forth. So- Incredible. So the story of intelligence, I think, I think is a multi-layered one and a multi-perspective one. We live in an incredible universe. David, thank you so much, first of all, for dreaming of using learning to solve Go and building intelligent systems and for actually making it happen and for inspiring millions of people in the process. It's truly an honor. Thank you so much for talking today. Okay, thank you. Thanks for listening to this conversation with David Silver and thank you to our sponsors, Masterclass and Cash App. Please consider supporting the podcast by signing up to Masterclass at masterclass.com slash Lex and downloading Cash App and using code LexPodcast. If you enjoy this podcast, subscribe on YouTube, review it with five stars on Apple Podcast, support on Patreon, or simply connect with me on Twitter at Lex Friedman. And now let me leave you with some words from David Silver. My personal belief is that we've seen something of a turning point where we're starting to understand that many abilities, like intuition and creativity, that we've previously thought were in the domain only of the human mind are actually accessible to machine intelligence as well. And I think that's a really exciting moment in history. Thank you for listening and hope to see you next time.

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Charles Isbell: Computing, Interactive AI, and Race in America | Lex Fridman Podcast #135

The following is a conversation with Charles Isbell, Dean of the College of Computing at Georgia Tech, a researcher and educator in the field of artificial intelligence, and someone who deeply thinks about what exactly is the field of computing and how do we teach it. He also has a fascinatingly varied set of interests including music, books, movies, sports, and history that make him especially fun to talk with. When I first saw him speak, his charisma immediately took over the room and I had a stupid excited smile on my face and I knew I had to eventually talk to him on this podcast. Quick mention of each sponsor, followed by some thoughts related to the episode. First is Neuro, the maker of functional sugar-free gum and mints that I use to give my brain a quick caffeine boost. Second is Decoding Digital, a podcast on tech and entrepreneurship that I listen to and enjoy. Third is Masterclass, online courses that I watch from some of the most amazing humans in history. And finally Cash App, the app I use to send money to friends for food and drinks. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that I'm trying to make it so that the conversations with Charles, Eric Weinstein, and Dan Carlin will be published before Americans vote for president on November 3rd. There's nothing explicitly political in these conversations, but they do touch on something in human nature that I hope can bring context to our difficult time and maybe, for a moment, allow us to empathize with people we disagree with. With Eric, we talk about the nature of evil. With Charles, besides AI and music, we talk a bit about race in America and how we can bring more love and empathy to our online communication. And with Dan Carlin, well, we talk about Alexander the Great, Genghis Khan, Hitler, Stalin, and all the complicated parts of human history in between, with a hopeful eye toward a brighter future for our humble little civilization here on Earth. The conversation with Dan will hopefully be posted tomorrow on Monday, November 2nd. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Charles Isbell. You've mentioned that you love movies and TV shows. Let's ask an easy question, but you have to be definitively, objectively, conclusive. What's your top three movies of all time? So, you're asking me to be definitive and to be conclusive. That's a little hard. I'm gonna tell you why. It's very simple. It's because movies is too broad of a category. I gotta pick sub-genres. But I will tell you that of those genres, I'll pick one or two from each of the genres. And I'll get us to three, except I'm gonna cheat. So, my favorite comedy of all times, which is probably my favorite movie of all time, is His Girl Friday, which is probably a movie that you've not ever heard of. But it's based on a play called The Front Page from, I don't know, early 1900s. And the movie is a fantastic film. What's the story? What's the independent film? No, no, no. What are we talking about? This is one of the movies that would have been very popular. It's a screwball comedy. You ever see Moonlighting, the TV show? You know what I'm talking about? So, you've seen these shows where there's a man and a woman, and they clearly are in love with one another, and they're constantly fighting and always talking over each other. Yeah. Banter, banter, banter, banter, banter. This was the movie that started all that, as far as I'm concerned. It's very much of its time. So, it's, I don't know, it must have come out sometime between 1934 and 1939. I'm not sure exactly when the movie itself came out. It's black and white. It's just a fantastic film. It's hilarious. So, it's mostly conversation? Not entirely, but mostly, mostly. Just a lot of back and forth. There's a story there. Someone's on death row, and they're newspapermen, including her. They're all newspapermen. They were divorced, the editor, the publisher, I guess, and the reporter, they were divorced. But, you know, they clearly, he's thinking, trying to get back together, and there's this whole other thing that's going on. But none of that matters. The plot doesn't matter. Yeah. What matters is the story. It's just a little play in conversation. It's fantastic. And I just love everything about the conversation. Because at the end of the day, sort of narrative and conversation are the sort of things that drive me. And so, I really, I really like that movie for that reason. Similarly, I'm now going to cheat, and I'm going to give you two movies as one. And they are Crouching Tiger, Hidden Dragon, and John Wick. Both relatively modern. John Wick, of course, is one. One, two, or three. One. It gets increasingly, I love them all for different reasons, and increasingly more ridiculous. Kind of like loving Alien and Aliens, despite the fact they're two completely different movies. But the reason I put Crouching Tiger, Hidden Dragon, and John Wick together is because I actually think they're the same movie, or what I like about them, the same movie. Which is both of them create a world that you're coming in the middle of, and they don't explain it to you. But the story is done so well that you pick it up. So, anyone who's seen John Wick, you have these little coins, and they're headed out, and there are these rules. And apparently, every single person in New York City is an assassin. There's two people who come through who aren't, but otherwise they are. But there's this complicated world, and everyone knows each other. They don't sit down and explain it to you, but you figure it out. Crouching Tiger, Hidden Dragon is a lot like that. You get the feeling that this is chapter nine of a 10-part story, and you've missed the first eight chapters, and they're not going to explain it to you, but there's this rich world behind you. So, you get pulled in anyway. You get pulled in anyway. So, it's just excellent storytelling in both cases, and very, very different. And also, you like the outfit, I assume. The John Wick outfit. Oh, yeah, of course. Well, of course. Yes, I think the John Wick outfit first. And so, that's number two. And then... But sorry to pause on that. Martial arts? You have a long list of hobbies. It scrolls off the page, but I didn't see martial arts as one of them. I do not do martial arts, but I certainly watch martial arts. Oh, I appreciate it very much. Oh, we could talk about every Jackie Chan movie ever made. I would be on board with that. Like, The Crush Hour 2? Like, that kind of... the comedy of it, cop? Yes. Yes. By the way, my favorite Jackie Chan movie would be Drunkard Master 2, known in the States usually as Legend of the Drunkard Master. Actually, Drunkard Master, the first one, is the first kung fu movie I ever saw, but I did not know that. First Jackie Chan movie? No, first one ever that I saw and remember, but I had no idea that that's what it was. And I didn't know that was Jackie Chan. That was like his first major movie. I was a kid. It was done in the 70s. I only later rediscovered that that was actually... And he creates his own martial art by drinking. Was he actually drinking or was he played drinking? You mean as an actor or... No. I'm sure as an actor. No, he was... It's the 70s or whatever. He was definitely drinking. And in the end, he drinks industrial grade alcohol. Yeah. Yeah. And has one of the most fantastic fights ever in that sub-genre. Anyway, that's my favorite one of his movies. But I'll tell you the last movie is actually a movie called Nothing But a Man, which is a 1960s star, Ivan Dixon, who you'll know from Hogan's Heroes and Abbie Lincoln. It's just a really small little drama. It's a beautiful story. But my favorite scenes, I'm cheating. One of my favorite movies just for the ending is The Godfather. I think the last scene of that is just fantastic. It's the whole movie all summarized in just eight, nine seconds. Godfather Part One? Part One. How does it end? I don't think you need to worry about spoilers if you haven't seen The Godfather. Spoiler alert. It ends with the wife coming to Michael. And he says, just this once, I'll let you ask me my business. And she asks him if he did this terrible thing. And he looks her in the eye and he lies and he says, no. And she says, thank you. And she walks out the door. And you see her going out of the door and all these people are coming in and they're kissing Michael's hands. And Godfather. And then the camera switches perspective. So instead of looking at him, you're looking at her and the door closes in her face. And that's the end of the movie. And that's the whole movie right there. Do you see parallels between that and your position as Dean at Georgia Tech, Carl? Ha! Definitely. Just kidding. Trick question. Sometimes. Certainly if the door gets closed on me every once in a while. Okay. That was a rhetorical question. You've also mentioned that you, I think, enjoy all kinds of experiments, including on yourself. But I saw a video where you said you did an experiment where you tracked all kinds of information about yourself and a few others, sort of wiring up your home. And this little idea that you mentioned in that video, which is kind of interesting, that you thought that two days worth of data is enough to capture majority of the behavior of the human being. First, can you describe what the heck you did to collect all that data? Because it's fascinating. Just like little details of how you collect that data and also what your intuition behind the two days is. So, first off, it has to be the right two days. But I was thinking of a very specific experiment. There's actually a suite of them that I've been a part of. And other people have done this, of course. I just sort of dabbled in that part of the world. But to be very clear, the specific thing that I was talking about had to do with recording all the IR going on in my, infrared going on in my house. So this is a long time ago. So this is everything's being curled by pressing buttons on remote controls as opposed to speaking to Alexa or Siri or someone like that. And I was just trying to figure out if you could get enough data on people to figure out what they were going to do with their TVs or their lights. My house was completely wired up at the time. But you know, what I'm about to look at a movie, I'm about to turn on the TV or whatever, and just see what I can predict from it. It was kind of surprising it shouldn't have been. But that's all very easy to do, by the way, just capturing all the little stuff. I mean, it's a bunch of computer systems. It's really easy to capture the, if you know what you're looking for. At Georgia Tech, long before I got there, we had this thing called the Aware Home, where everything was wired up and you saw, you captured everything that was going on. Nothing even difficult, not with video or anything like that, just the way that the system was just capturing everything. So it turns out that, and I did this with myself and then I had students and they worked with many other people. And it turns out at the end of the day, people do the same things over and over and over again. So it has to be the right two days, like a weekend, but it turns out not only can you predict what someone's going to do next at the level of what button they're going to press next on a remote control, but you can do it with something really, really simple. Like you don't even need a hidden Markov model. It's like a Mark, just simply, I press this, this is my prediction of the next thing. And it turns out you can get 93% accuracy just by doing something very simple and stupid and just counting statistics. But what was actually more interesting is that you could use that information. This comes up again and again in my work. If you try to represent people or objects by the things they do, the things you can measure about them that have to do with action in the world. So a distribution over actions, and you try to represent them by the distribution of actions that are done on them, then you do a pretty good job of sort of understanding how people are and they cluster remarkably well. In fact, irritatingly so. And so by clustering people this way, you can, maybe, you know, I got the 93% accuracy of what's the next button you're going to press, but I can get 99% accuracy or somewhere there's about on the collections of things you might press. And it turns out the things that you might press are all related to number to each other in exactly what you would expect. So for example, all the key, all the numbers on the keypad, it turns out all have the same behavior with respect to you as a human being. And so you would naturally cluster them together and you discover that numbers are all related to one another in some way and all these other things. And then, and here's the part that I think's important. I mean, you can see this in all kinds of things. Every individual is different, but any given individual is remarkably predictable because you keep doing the same things over and over again. And the two things that I've learned in the long time that I've been thinking about this is people are easily predictable and people hate when you tell them that they're easily predictable, but they are. And there you go. Yeah. What about, let me play devil's advocate and philosophically speaking, is it possible to say that what defines humans is the outlier? So even though 90, some large percentage of our behaviors, whatever the signal we measure is the same and it would cluster nicely, but maybe it's the special moments of when we break out of the routine is the definitive things and the way we break out of that routine for each one of us might be different. It's possible. I would say that, I would say it a little differently. I think I would make two things. One is, I'm going to disagree with the premise, I think, but that's fine. I think the way I would put it is there are people who are very different from lots of other people, but they're not 0%, they're closer to 10%, right? So in fact, even if you do this kind of clustering of people, that'll turn out to be the small number of people, they all behave like each other, even if they individually behave very differently from everyone else. So I think that's kind of important. But what you're really asking, I think, and I think this is really a question is, what do you do when you're faced with the situation you've never seen before? What do you do when you're faced with an extraordinary situation maybe you've seen others do and you're actually forced to do something and you react to that very differently. And that is the thing that makes you human. I would agree with that, at least at a philosophical level, that it's the times when you are faced with something difficult, a decision that you have to make where the answer isn't easy, even if you know what the right answer is, that's sort of what defines you as the individual. And I think what defines people broadly, it's the hard problem, it's not the easy problem, it's the thing that's going to hurt you, it's not the thing. It's not even that it's difficult, it's just that you know that the outcome is going to be highly suboptimal for you. And I do think that that's a reasonable place to start for the question of what makes us human. So before we talk about, sort of explore the different ideas underlying interactive artificial intelligence, which we are working on, let me just go along this thread to skip to kind of our world of social media, which is something that, at least on the artificial intelligence side, you think about. There's a popular narrative, I don't know if it's true, but that we have these silos in social media and we have these clusterings, as you're kind of mentioning. And the idea is that, you know, along that narrative is that, you know, we want to break each other out of those silos so we can be empathetic to other people, if you're a Democrat, you're empathetic to the Republican, if you're a Republican, you're empathetic to the Democrat. Those are just two silly bins that we seem to be very excited about, but there's other binnings that we can think about. Is there, from an artificial intelligence perspective, because you're just saying we cluster along the data, but then interactive artificial intelligence is referring to throwing agents into that mix, AI systems in that mix, helping us, interacting with us humans and maybe getting us out of the silos. Is there a way to think about this out of those silos? Is that something that you think is possible? Do you see a hopeful possibility for artificial intelligence systems in these large networks of people to get us out outside of our habits in at least the idea space to where we can sort of be empathetic to other people's lived experiences, other people's points of view, you know, all that kind of stuff? Yes. I actually don't think it's that hard. Well, it's not hard in this sense. So imagine that you can, let's make life simple for a minute. Let's assume that you can do a kind of partial ordering over ideas or clustering of behavior. It doesn't even matter what I mean here. So long as there's some way that this is a cluster, this is a cluster, there's some edge between them, right? They don't quite touch even, or maybe they come very close. If you can imagine that conceptually, then the way you get from here to here is not by going from here to here. The way you get from here to here is you find the edge and you move slowly together, right? And I think that machines are actually very good at that sort of thing once we can kind of define the problem, either in terms of behavior or ideas or words or whatever. So it's easy in the sense that if you already have the network and you know the relationships, you know, the edges and sort of the strings on them, and you kind of have some semantic meaning for them, the machine doesn't have to. You do as the designer. Then yeah, I think you can kind of move people along and sort of expand them. But it's harder than that. And the reason it's harder than that, or sort of coming up with the network structure itself is hard, is because I'm going to tell you a story that someone else told me. And I don't, I may get some of the details a little bit wrong, but it's roughly, it roughly goes like this. You take two sets of people from the same backgrounds and you want them to solve a problem. So you separate them, which we do all the time, right? Oh, you know, we're going to break out in the, we're going to break out groups. You're going to go over there and you're going to talk about this. You're going to go over there and talk about this. And then you have them sort of in this big room, but far apart from one another. And you have them sort of interact with one another. When they come back to talk about what they learned, you want to merge what they've done together. It can be extremely hard because they don't, they basically don't speak the same language anymore. Like when you create these problems and you dive into them, you create your own language. So the example this one person gave me, which I found kind of interesting because we were in the middle of that at the time, was they're sitting over there and they're talking about these rooms that you can see, but you're seeing them from different vantage points, depending upon what side of the room you're on. They can see a clock very easily. And so they start referring to the room as the one with the clock. This group over here, looking at the same room, they can see the clock, but it's not in their line of sight or whatever. So they end up referring to it by some other way. When they get back together and they're talking about things, they're referring to the same room and they don't even realize they're referring to the same room. And in fact, this group doesn't even see that there's a clock there. And this group doesn't see whatever it is. The clock on the wall is the thing that stuck with me. So if you create these different silos, the problem isn't that the ideologies disagree. It's that you're using the same words and they mean radically different things. The hard part is just getting them to agree on the, well, maybe we'd say the axioms in our world, right? But just get them to agree on some basic definitions because right now they're talking past each other, just completely talking past each other. That's the hard part, getting them to meet, getting them to interact. That may not be that difficult. Getting them to see where their language is leading them to lead past one another, that's the hard part. It's a really interesting question to me. It could be on the layer of language, but it feels like there's multiple layers to this. It could be worldview, it could be, I mean, it all boils down to empathy, being able to put yourself in the shoes of the other person, to learn the language, to learn visually how they see the world, to learn the, I mean, I experience this now with trolls, the degree of humor in that world. For example, I talk about love a lot. I'm very lucky to have this amazing community of loving people, but whenever I encounter trolls, they always roll their eyes at the idea of love because it's so, quote unquote, cringe. So they show love by derision, I would say. And I think about, on the human level, that's a whole nother discussion. That's psychology, that's sociology, so on. But I wonder if AI systems can help somehow and bridge the gap of what is this person's life like? Encourage me to just ask that question, to put myself in their shoes, to experience the agitations, the fears, the hopes they have, to experience, even just to think about what was their upbringing like, like having a single parent home or a shitty education or all those kinds of things, just to put myself in that mind space. It feels like that's really important for us to bring those clusters together, to find that similar language, but it's unclear how AI can help that because it seems like AI systems need to understand both parties first. Darrell Bock So the word understand is doing a lot of work, right? So do you have to understand it or do you just simply have to note that there is something similar as a point to touch, right? So you use the word empathy, and I like that word for a lot of reasons. I think you're right in the way that you're using it, in the way that you're describing it, but let's separate it from sympathy, right? So sympathy is feeling for someone. Empathy is kind of understanding where they're coming from and how they feel, right? And for most people, those things go hand in hand. For some people, some are very good at empathy and very bad at sympathy. Some people cannot experience, well, my observation would be, I'm not a psychologist, my observation would be that some people seem incapable of feeling sympathy unless they feel empathy first. You can understand someone, understand where they're coming from and still think, no, I can't support that, right? It doesn't mean that the only way, because if that isn't the case, then what it requires is that you must, the only way that you can, to understand someone means you must agree with everything that they do, which isn't right, right? And if the only way I can feel for someone is to completely understand them and make them like me in some way, well, then we're lost, right? Because we're not all exactly like each other. I don't have to understand everything that you've gone through. It helps, clearly. But they're separable ideas, right? Even though they get clearly tangled up in one another. So what I think, A, I could help you do, actually, is if, and I'm being quite fanciful as it were, but if you think of these as kind of, I understand how you interact, the words that you use, the actions you take, I have some way of doing this, let's not worry about what that is, but I can see you as a kind of distribution of experiences and actions taken upon you, things you've done and so on, and I can do this with someone else and I can find the places where there's some kind of commonality, a mapping, as it were, even if it's not total. If I think of it as distribution, right, then I can take the cosine of the angle between you and if it's zero, you've got nothing in common. If it's one, you're completely the same person. Well, you're probably not one. You're almost certainly not zero. I can find the place where there's the overlap, then I might be able to introduce you on that basis or connect you in that way and make it easier for you to take that step of empathy. It's not impossible to do, although I wonder if it requires that everyone involved is at least interested in asking the question. So maybe the hard part is just getting them interested in asking the question. In fact, maybe if you can get them to ask the question, how are we more alike than we are different, they'll solve it themselves. Maybe that's the problem that AI should be working on, not telling you how you're similar or different, but just getting you to decide that it's worthwhile asking the question. It feels like an economist's answer, actually. Well, people, okay, first of all, people like it when I would disagree. So let me disagree slightly, which is I think everything you said is brilliant, but I tend to believe, philosophically speaking, that people are interested underneath it all. And I would say that AI, the possibility that an AI system would show the commonality is incredible. That's a really good starting point. I would say if on social media, I could discover the common things deep or shallow between me and a person who there's tension with, I think that my basic human nature would take over from there. And I think enjoy that commonality. And there's something sticky about that that my mind will linger on, and that person in my mind will become warmer and warmer, and warmer, and I'll start to feel more and more compassion towards them. I think for majority of the population, that's true, but that's a hypothesis. Yeah, I mean, it's an empirical question, right? You'd have to figure it out. I mean, I want to believe you're right, and so I'm gonna say that I think you're right. Of course, some people come to those things for the purpose of trolling, right? And it doesn't matter. They're playing a different game. But I don't know. My experience is it requires two things. It requires, in fact, maybe this is really at the end what you're saying, and I do agree with this for sure. So it's hard to hold onto that kind of anger or to hold onto just the desire to humiliate someone for that long. It's just difficult to do. It takes a toll on you. But more importantly, we know this, both from people having done studies on it, but also from our own experiences, that it is much easier to be dismissive of a person if they're not in front of you, if they're not real, right? So much of the history of the world is about making people other, right? So if you're on social media, if you're on the web, if you're doing whatever on the internet, being forced to deal with someone as a person, some equivalent to being in the same room, makes a huge difference. Because then you're, one, you're forced to deal with their humanity because it's in front of you. The other is, of course, that they might punch you in the face if you go too far. So both of those things kind of work together, I think, to the right end. So I think bringing people together is really a kind of substitute for forcing them to see the humanity in another person and to not be able to treat them as bits. It's hard to troll someone when you're looking them in the eye. This is very difficult to do. Lex Doppelganger Agreed. Your broad set of research interests fall under interactive AI, as I mentioned, which is a fascinating set of ideas. And you have some concrete things that you're particularly interested in. But maybe, could you talk about how you think about the field of interactive artificial intelligence? David Taylor Sure. So let me say up front that if you look at, certainly my early work, but even if you look at most of it, I'm a machine learning guy. Right? I do machine learning. First paper I ever published was in NIPS. Back then it was NIPS, now it's NRIPS. It's a long story there. Anyway, that's another thing. But so I'm a machine learning guy, right? I believe in data, I believe in statistics, and all those kind of things. And the reason I'm bringing that up is even though I'm a newfangled statistical machine learning guy, and have been for a very long time, the problem I really care about is AI. Right? I care about artificial intelligence. I care about building some kind of intelligent artifact, however that gets expressed, that would be at least as intelligent as humans, and as interesting as humans, perhaps, in their own way. Lex Doppelganger So that's the deep underlying love and dream is the bigger AI. Whatever the heck that is. David Taylor Yeah. The machine learning in some ways is a means to the end. It is not the end. And I don't understand how one could be intelligent without learning. So therefore I got to figure out how to do that. Right? So that's important. But machine learning, by the way, is also a tool. I said statistical because that's what most people think of themselves, machine learning people. That's how they think. Pat Langley might disagree, or at least 1980s Pat Langley might disagree with what it takes to do machine learning. But I care about the AI problem, which is why it's interactive AI, not just interactive ML. I think it's important to understand that there's a long-term goal here, which I will probably never live to see, but I would love to have been a part of, which is building something truly intelligent outside of ourselves. Lex Doppelganger Can we take a tiny tangent? David Taylor Sure. Lex Doppelganger Or am I interrupting? Which is, is there something you can say concrete about the mysterious gap between the subset ML and the bigger AI? What's missing? What do you think? I mean, obviously, it's a totally unknown, not totally, but it's a not totally, but in part unknown at this time. But is it something like with Pat Langley's, is it knowledge, like expert system reasoning type of kind of thing? David Taylor So AI is bigger than ML, but ML is bigger than AI. This is kind of the real problem here is that they're really overlapping things that are really interested in slightly different problems. I tend to think of ML, and there are many people out there are going to be very upset at me about this, but I tend to think of ML being much more concerned with the engineering of solving a problem, and AI about the sort of more philosophical goal of true intelligence. And that's the thing that motivates me, even if I end up finding myself living in this kind of engineering-ish space. I've now made Michael Jordan upset. But you know, it's, to me, they just feel very different. You're just measuring them differently, your sort of goals of where you're trying to be are somewhat different. But to me, AI is about trying to build that intelligent thing. And typically, but not always, for the purpose of understanding ourselves a little bit better. Machine learning is, I think, trying to solve the problem, whatever that problem is. Now, that's my take. Others, of course, would disagree. Lexa So on that note, so with the interactive AI, do you tend to, in your mind, visualize AI as a singular system, or is it as a collective, huge amount of systems interacting with each other? Like, is the social interaction of us humans and of AI systems the fundamental to intelligence? David I think, well, it's certainly fundamental to our kind of intelligence, right? And I actually think it matters quite a bit. So the reason the interactive AI part matters to me is because I don't, this is going to sound simple, but I don't care whether a tree makes a sound when it falls and there's no one around, because I don't think it matters, right? If there's no observer in some sense. And I think what's interesting about the way that we're intelligent is we're intelligent with other people, right? Or other things, anyway. And we go out of our way to make other things intelligent. We're hardwired to find intention, even whether there is no intention. I mean, anthropomorphize everything. I think, anyway. I think the interactive AI part is being intelligent in and of myself in isolation is a meaningless act, in some sense. The correct answer is you have to be intelligent in the way that you interact with others. It's also efficient because it allows you to learn faster because you can import from, you know, past history. It also allows you to be efficient in the transmission of that. So we ask ourselves about me. Am I intelligent? Clearly, I think so. But I'm also intelligent as a part of a larger species and group of people. And we're trying to move the species forward as well. And so I think that notion of being intelligent with others is kind of the key thing because otherwise you come and you go and then it doesn't matter. And so that's why I care about that aspect of it. And it has lots of other implications. One is not just, you know, building something intelligent with others, but understanding that you can't always communicate with those others. They have been in a room where there's a clock on the wall that you haven't seen, which means you have to spend an enormous amount of time communicating with one another constantly in order to figure out what the other, what each other wants. Right? So, I mean, this is why people project, right? You project your own intentions and your own reasons for doing things onto others as a way of understanding them so that you know how to behave. But by the way, you, completely predictable person, I don't know how you're predictable. I don't know you well enough, but you probably eat the same five things over and over again or whatever it is that you do, right? I know I do. If I'm going to a new Chinese restaurant, I will get General Gao's chicken because that's the thing that's easy. I will get hot and sour soup. You know, people do the things that they do, but other people get the chicken and broccoli. I can push this analogy way too far. The chicken and broccoli. I don't know what's wrong with those people. I don't know what's wrong with them either. We have all had our trauma. So, they get their chicken and broccoli and their egg drop soup or whatever. We got to communicate and it's going to change, right? So, interactive AI is not just about learning to solve a problem or a task. It's about having to adapt that over time, over a very long period of time and interacting with other people who will themselves change. This is what we mean about things like adaptable models, right? That you have to have a model, that model's going to change. And by the way, it's not just the case that you're different from that person, but you're different from the person you were 15 minutes ago or certainly 15 years ago. And I have to assume that you're at least going to drift. Hopefully, not too many discontinuities, but you're going to drift over time. And I have to have some mechanism for adapting to that as you and an individual over time and across individuals over time. On the topic of adaptive modeling and you talk about lifelong learning, which is, I think, a topic that's understudied or maybe because nobody knows what to do with it. But if you look at Alexa or most of our artificial intelligence systems that are primarily machine learning based systems or dialogue systems, all those kinds of things, they know very little about you in the sense of the lifelong learning sense that we learn as humans, we learn a lot about each other, not in the quantity effects, but like the temporally rich set of information that seems to pick up the crumbs along the way that somehow seems to capture a person pretty well. Do you have any ideas how to do lifelong learning? Because it seems like most of the machine learning community does not. No. Well, by the way, not only does the machine learning community not spend a lot of time on lifelong learning, I don't think they spend a lot of time on learning period in the sense that they tend to be very task-focused. Everybody is overfitting to whatever problem is they happen to have. They're over-engineering their solutions to the task. Even the people, and I think these people too, are trying to solve a hard problem of transfer learning, right? I'm going to learn on one task, then learn the other task. You still end up creating the task. It's like looking for your keys where the light is, because that's where the light is, right? It's not because the keys have to be there. I mean, one could argue that we tend to do this in general. We tend to kind of do it as a group. We tend to hill climb and get stuck in local optima. I think we do this in the small as well. I think it's very hard to do. Look, here's the hard thing about AI, right? The hard thing about AI is it keeps changing on us, right? What is AI? AI is the art and science of making computers act the way they do in the movies, right? That's what it is, right? That's a good definition. But beyond that, it's- And they keep coming up with new movies. Yes, and they just, right, exactly. We are driven by this kind of need to the sort of ineffable quality of who we are, which means that the moment you understand something is no longer AI, right? Well, we understand this. That's just, you take the derivative and you divide by two, and then you average it out over time in the window. So therefore, that's no longer AI. So the problem is unsolvable because it keeps kind of going away. This creates a kind of illusion, which I don't think is an entire illusion, of either there's very simple task-based things you can do very well and over-engineer. There's all of AI, and there's like nothing in the middle. Like it's very hard to get from here to here, and it's very hard to see how to get from here to here. And I don't think that we've done a very good job of it because we get stuck trying to solve the small problem that's in front of it, myself included. I'm not going to pretend that I'm better at this than anyone else. And of course, all the incentives in academia and in industry are set to make that very hard because you have to get the next paper out, you have to get the next product out, you have to solve this problem. And it's very sort of naturally incremental. And none of the incentives are set up to allow you to take a huge risk, unless you're already so well-established you can take that big risk. And if you're that well established that you can take that big risk, then you've probably spent much of your career taking these little risks, relatively speaking. And so you have got a lifetime of experience telling you not to take that particular big risk, right? So the whole system's set up to make progress very slow. That's fine. It's just the way it is. But it does make this gap seem really big, which is my long way of saying, I don't have a great answer to it, except that stop doing n equals one. At least try to get n equal two and maybe n equal seven, so that you can say, I'm going to, or maybe t is a better variable here. I'm going to not just solve this problem, I'm going to solve this problem and another problem. I'm not going to learn just on you. I'm going to keep living out there in the world and just seeing what happens. And that we'll learn something as designers and our machine learning algorithms and our AI algorithms can learn as well. But unless you're willing to build a system, which you're going to have live for months at a time in an environment that is messy and chaotic, you cannot control, then you're never going to make progress in that direction. So I guess my answer to you is yes. My idea is that you should, it's not no, it's yes, you should be deploying these things and making them live for a month at a time and be okay with the fact that it's going to take you five years to do this. Not re-running the same experiment over and over again and refining the machine so it's slightly better at whatever, but actually having it out there and living in the chaos of the world and seeing what it's learning algorithm, say, can learn, what data structure it can build and how it can go from there. Without that, you're going to be stuck all the time. What do you think about the possibility of N equals one growing, it's probably a crude approximation, but growing like if you look at language models like GPT-3, if you just make it big enough, it'll swallow the world. Meaning like it'll solve all your T to infinity by just growing in size of this, taking the small over-engineered solution and just pumping it full of steroids in terms of compute, in terms of size of training data, and the Yann LeCun style self-supervised or open AI self-supervised, just throw all of YouTube at it and it will learn how to reason, how to paint, how to create music, how to love, all of that by watching YouTube videos. ACSERIAL I mean, I can't think of a more terrifying world to live in than a world that is based on YouTube videos. But yeah, I think the answer, I just kind of don't think that'll quite, well, it won't work that easily. You will get somewhere and you will learn something, which means it's probably worth it, but you won't get there. You won't solve the problem. Here's the thing, we build these things and we say we want them to learn, but what actually happens, and let's say they do learn. I mean, certainly every paper I've gotten published, the things learn, I don't bet anyone else. But they actually change us, right? We react to it differently, right? So we keep redefining what it means to be successful, both in the negative in the AI case, but also in the positive in that, oh, well, this is an accomplishment. I'll give you an example, which is like the one you just described with YouTube. Let's get completely out of machine learning. Well, not completely, but mostly out of machine learning. Think about Google. People were trying to solve information retrieval, the ad hoc information retrieval problem forever. I mean, first major book I ever read about it was what, 71, I think was when it came out. Anyway, it's, we'll treat everything as a vector and we'll do these vector space models and whatever. And that was all great. And we made very little progress. I mean, we made some progress. And then Google comes and makes the ad hoc problem seem pretty easy. I mean, it's not, there's lots of computers and databases involved, but, and there's some brilliant algorithmic stuff behind it too, and some systems building. But the problem changed, right? If you've got a world that's that connected so that you have, you know, there are 10 million answers quite literally to the question that you're asking, then the problem wasn't give me the things that are relevant. The problem is don't give me anything that's irrelevant, at least in the first page, because nothing else matters. So Google is not solving the information retrieval problem, at least not on this webpage. Google is minimizing false positives, which is not the same thing as getting an answer. It turns out it's good enough for what it is we want to use Google for, but it also changes what the problem was we thought we were trying to solve in the first place. You thought you were trying to find an answer, but you're not, or you're trying to find the answer, but it turns out you're just trying to find an answer. Now, yes, it is true. It's also very good at finding you exactly that webpage. Of course, you trained yourself to figure out what the keywords were to get you that webpage, but in the end, by having that much data, you've just changed the problem into something else. You haven't actually learned what you set out to learn. Now, the counter to that would be maybe we're not doing that either. We just think we are, because, you know, we're in our own heads. Maybe we're learning the wrong problem in the first place, but I don't think that matters. I think the point is that Google has not solved information retrieval. Google has done an amazing service. I have nothing bad to say about what they've done. Lord knows my entire life is better because Google exists, in foreign for Google Maps. I don't think I've ever found this, but... I see 110 and I see, but where did 95 go? So I'm very grateful for Google, but they just have to make certain the first five things are right. And everything after that is wrong. Look, we're going off in a totally different time here, but think about the way we hire faculty. It's exactly the same thing. I'm getting controversial. I'm getting controversial. It's exactly the same problem, right? It's minimizing false positives. We say things like we want to find the best person to be an assistant professor at MIT in the new College of Computing, which I will point out was founded 30 years after the College of Computing I'm a part of. Both of my alma mater... I'm just saying I appreciate all that they did and all that they're doing. Anyway, so we're going to try to hire the best professor. That's what we say, the best person for this job, but that's not what we do at all. Right? Do you know which percentage of faculty in the top four earn their PhDs from the top four, say in 2017, for which we have, which is the most recent year for which I have data? Maybe a large percentage. About 60%. 60%. 60% of the faculty in the top four earn their PhDs in the top four. This is computer science for which there is no top five. There's only a top four, right? Because they're all tied for one. For people who don't know, by the way, that would be MIT, Stanford, Berkeley, CMU. Yep. Georgia Tech. Number eight. Number eight. You're keeping track. Oh, yes. It's a large part of my job. Number five is Illinois. Number six is a tie with UW and Cornell, and Princeton and Georgia Tech are tied for eight, and UT Austin is number 10. Michigan's number 11, by the way. So if you look at the top 10, you know what percentage of faculty in the top 10 earn their PhDs from the top 10? 65, roughly. 65%. If you look at the top 55 ranked departments, 50% of the faculty earn their PhDs from the top 10. There's no universe in which all the best faculty, even just for R1 universities, the majority of them come from 10 places. There's no way that's true, especially when you consider how small some of those universities are in terms of the number of PhDs they produce. Now, that's not a negative. I mean, it is a negative. It also has a habit of entrancing certain historical inequities and accidents. But what it tells you is, well, ask yourself the question, why is it like that? Well, because it's easier. If we go all the way back to the 1980s, there was a saying that nobody ever lost his job buying a computer from IBM, and it was true. Nobody ever lost their job hiring a PhD from MIT. If the person turned out to be terrible, well, you know, they came from MIT. What did you expect me to know? However, that same person coming from pick whichever is your least favorite place that produces PhDs in, say, computer science, well, you took a risk, right? So all the incentives, particularly because you're only going to hire one this year, well, now we're hiring 10, but you know, you're only going to hire one or two or three this year. And by the way, when they come in, you're stuck with them for at least seven years in most places, because that's before you know whether they're getting tenure or not. And if they get tenure, you're stuck with them for a good 30 years unless they decide to leave. That means the pressure to get this right is very high. So what are you going to do? You're going to minimize false positives. You don't care about saying no inappropriately. You only care about saying yes inappropriately. So all the pressure drives you into that particular direction. Google, not to put too fine a point on it, was in exactly the same situation with their search. It turns out you just don't want to give people the wrong page in the first three or four pages. And if there's 10 million right answers and a hundred bazillion wrong answers, just make certain the wrong answers don't get up there. And who cares if the right answer was actually the 13th page? A right answer, a satisficing answer, is number one, two, three, or four. So who cares? Or an answer that will make you discover something beautiful, profound to your question. Well, that's a different problem, right? But isn't that the problem? Can we linger on this topic without sort of walking with grace? How do we get, for hiring faculty, how do we get that 13th page with a truly special person? Like, I mean, it depends on the department. Computer science probably has those kinds of people. Like you have the Russian guy, Grigori Perlman. Like, just these awkward, strange minds that don't know how to play the little game of etiquette that faculty have all agreed somehow, like converged over the decades, how to play with each other. And also is not, you know, on top of that is not from the top four, top whatever numbers, the schools. And maybe actually just says a few every once in a while to the traditions of old within the computer science community. Maybe talks trash about machine learning is a total waste of time. And that's there on their resume. So like, how do you allow the system to give those folks a chance? Well, you have to be willing to take a certain kind of, without taking a particular position on any particular person, you'd have to take, you have to be willing to take risk, right? A small amount of risk. I mean, if we were treating this as a, well, as a machine learning problem, right? As a search problem, which is what it is. It's a search problem. If we were treating it that way, you would say, oh, well, the main thing is you want, you know, you've got a prior, you want some data because I'm Bayesian. If you don't want to do it that way, we'll just inject some randomness in and it'll be okay. The problem is that feels very, very hard to do with people. All the incentives are wrong there. But it turns out, and let's say, let's say that's the right answer. Let's just give for the sake of argument that, you know, injecting randomness in the system at that level for who you hire is just not, not worth doing because the price is too high or the cost is too high. We had infinite resources, sure, but we don't. And also you've got to teach people. So, you know, you're ruining other people's lives if you get it too wrong. But we've taken that principle, even if I grant it and pushed it all the way back, right? So we could have a better pool than we have of people we look at and give an opportunity to. If we do that, then we have a better chance of finding that. Of course, that just pushes the problem back, back another level. But let me tell you something else. You know, I did a sort of study. I call it a study. I called up eight of my friends and asked them for all of their data for graduate admissions, but then someone else followed up and did an actual study. And it turns out that I can tell you how everybody gets into grad school, more or less, more or less. You basically admit everyone from places higher ranked than you. You admit most people from places ranked around you. And you admit almost no one from places ranked below you, with the exception of the small liberal arts colleges that aren't ranked at all, like Harvey Mudd, because they don't, they don't have PhDs, so they aren't ranked. This is all CS. Which means the decision of whether, you know, you become a professor at Cornell was determined when you were 17, right? By where, what you knew to go to undergrad to do whatever, right? So if we can push these things back a little bit and just make the pool a little bit bigger, at least you raise the probability that you will be able to see someone interesting and take the risk. The other answer to that question, by the way, which you could argue is the same as you either adjust the pool so the probabilities go up, that's a way of injecting a little bit of uniform noise in the system, as it were, is you change your loss function. You just let yourself be measured by something other than whatever it is that we're measuring ourselves by now. I mean, US News and World Report, every time they change their formula for determining rankings, move entire universities to behave differently, because rankings matter. Can you talk trash about those rankings for a second? I'm joking about talking trash. I actually, it's so funny how, from my perspective, from a very shallow perspective, how dogmatic, like how much I trust those rankings. They're almost ingrained in my head. Mm-hmm. I mean, at MIT, everybody kind of, it's a propagated, mutually agreed upon idea that those rankings matter. And I don't think anyone knows what they're, like most people don't know what they're based on. And what are they exactly based on, and what are the flaws in that? Well, so it depends on which rankings you're talking about. Do you want to talk about computer science or are we gonna talk about universities? Computer science, US News is not the main one. Yeah, it's US News. The only one that matters is US News. Nothing else matters. Sorry, csrankings.org, but nothing else matters but US News. So US News has formula that it uses for many things, but not for computer science, because computer science is considered a science, which is absurd. So the rankings for computer science is 100% reputation. So two people at each department, it's not really a department, but whatever, at each department, basically rank everybody. Slightly more complicated than that, but whatever, they rank everyone. And then those things are put together and somehow, Oh no. So that means, how do you improve reputation? How do you move up and down the space of reputation? Yes, that's exactly the question. Twitter? It can help. I can tell you how Georgia Tech did it, or at least how I think Georgia Tech did it, because Georgia Tech is actually the case to look at. Not just because I'm at Georgia Tech, but because Georgia Tech is the only computing unit that was not in the top 20 that has made it into the top 10. It's also the only one in the last two decades, I think, that moved up in the top 10, as opposed to having someone else move down. So we used to be number 10, and then we became number nine because UT Austin went down slightly, and now we retired for ninth, because that's how rankings work. And we moved from nine to eight because our raw score moved up a point. So Georgia, something about Georgia Tech, computer science, or computing anyway. I think it's because we have shown leadership at every crisis level, right? So we created a college, first public university to do it, second college, second university to do it after CMU is number one. I also think it's no accident that CMU is the largest, and we're, depending upon how you count and depending on exactly where MIT ends up with its final college of computing, second or third largest. I don't think that's an accident. We've been doing this for a long time. But in the 2000s, when there was a crisis about undergraduate education, Georgia Tech took a big risk and succeeded at rethinking undergrad education and computing. I think we created these schools at a time when most public universities anyway were afraid to do it. We did the online masters, and that mattered because people were trying to figure out what to do with MOOCs and so on. I think it's about being observed by your peers and having an impact. So, I mean, that is what reputation is, right? So the way you move up in the reputation rankings is by doing something that makes people turn and look at you and say, that's good. They're better than I thought. Yeah. Beyond that, it's just inertia. And there's huge history in the system, right? Like, I mean, there was these, I can't remember this, this may be apocryphal, but there's a major or a department that like MIT was ranked number one in and they didn't have it. It's just about what you, I don't know if that's true, but someone said that to me anyway. But it's a thing, right? It's all about reputation. Of course MIT is great because MIT is great. It's always been great. By the way, because MIT is great, the best students come, which keeps it being great. I mean, it's just a positive feedback loop. It's not surprising. I don't think it's wrong. Yeah. But it's almost like a narrative. It doesn't actually have to be backed by reality. And it's, you know, not to say anything about MIT, but it does feel like we're playing in the space of narratives, not the space of something grounded. And one of the surprising things when I showed up at MIT and just all the students I've worked with and all the research I've done, is it like they're the same people as I've met other places. Mm-hmm. I mean, what MIT is going for, well, MIT has many things going for it. One of the things MIT is going for is- Nice logo. Is a nice logo. It's a lot better than it was when I was here. Nice colors too. Terrible, terrible name for a mascot. But the thing that MIT has going for it is it really does get the best students. It just doesn't get all of the best students. There are many more best students out there, right? And the best students want to be here because it's the best place to be, or one of the best places to be. And it just kind of, it's a sort of positive event. But you said something earlier, which I think is worth examining for a moment, right? You said it's, I forget the word you used, you said, we're living in the space of narrative as opposed to something objective. Narrative is objective. I mean, one could argue that the only thing that we do as humans is narrative. We just build stories to explain why we do this. It's profound. Someone once asked me, but wait, there's nothing objective. No, it's completely an objective measure. It's an objective measure of the opinions of everybody else. Now, is that physics? I don't know. But you know, what, I mean, tell me something you think is actually objective and measurable in a way that makes sense. Like cameras, they don't, do you know that, I mean, you're getting me off on something here, but do you know that cameras, which are just reflecting light and putting them on film, like did not work for dark-skinned people until like the 1970s? You know why? Because you were building cameras for the people who were going to buy cameras, who all, at least in the United States and Western Europe, were relatively light-skinned. Turns out took terrible pictures of people who look like me. That got fixed with better film and whole processes. Do you know why? Because furniture manufacturers wanted to be able to take pictures of mahogany furniture, right? Because candy manufacturers wanted to be able to take pictures of chocolate. Now, the reason I bring that up is because you might think that cameras are objective. They're objective, they're just capturing light. No, they're made, they are doing the things that they are doing based upon decisions by real human beings to privilege, if I may use that word, some physics over others, because it's an engineering problem. There are trade-offs, right? So I can either worry about this part of the spectrum or this part of the spectrum. This costs more, that costs less, this costs the same, but I have more people paying money over here, right? And it turns out that, you know, if a giant conglomerate demands that you do something different and it's going to involve all kinds of money for you, suddenly the trade-offs change, right? And so there you go. I actually don't know how I ended up there. Oh, it's because of this notion of objectiveness, right? So even the objective is an objective, because at the end you've got to tell a story, you've got to make decisions, you've got to make trade-off, and what else is engineering other than that? So I think that the rankings capture something. They just don't necessarily capture what people assume they capture. You know, just to linger on this idea, why is there not more people who just like play with whatever that narrative is, have fun with it, have like excite the world, whether it's in the Carl Sagan style of like that calm, sexy voice of explaining the stars and all the romantic stuff, or the Elon Musk, dare I even say Donald Trump, where you're like trolling and shaking up the system and just saying controversial things. I talked to Lisa Feldman Barrett, who's a neuroscientist who just enjoys playing the controversy, like finds the counterintuitive ideas in a particular science and throws them out there and sees how they play in the public discourse. Like why don't we see more of that? And why doesn't academia attract an Elon Musk type? Well, tenure is a powerful thing that allows you to do whatever you want, but getting tenure typically requires you to be relatively narrow, right? Because people are judging you. Well, I think the answer is we have told ourselves a story, a narrative that is vulgar, which you just described as vulgar. It's certainly unscientific, right? And it is easy to convince yourself that in some ways you're the mathematician, right? The fewer there are in your major, the more that proves your purity, right? So once you tell yourself that story, then it is beneath you to do that kind of thing, right? I think that's wrong. I think that, and by the way, everyone doesn't have to do this. Everyone's not good at it. And everyone, even if they would be good at it, would enjoy it. So it's fine. But I do think you need some diversity in the way that people choose to relate to the world as academics. Because I think the great universities are ones that engage with the rest of the world. It is a home for public intellectuals. Yes. And in 2020, being a public intellectual probably means being on Twitter. Whereas, of course, that wasn't true 20 years ago, because Twitter wasn't around 20 years ago. And if it was, it wasn't around in a meaningful way. I don't actually know how long Twitter's been around. As I get older, I find that my notion of time has gotten worse and worse. Like, Google really has been around that long? Anyway, the point is that I think that we sometimes forget that a part of our job is to impact the people who aren't in the world that we're in. And that that's the point of being at a great place and being a great person, frankly. There's an interesting force in terms of public intellectuals. You know, if we get Twitter, we can look at just online courses that are public facing in some part. Like, there is a kind of force that pulls you back. I would, let me just call it out, because I don't give a damn at this point. There's a little bit of, all of us have this, but certainly faculty have this, which is jealousy. It's whoever's popular at being a good communicator, exciting the world with their science. And of course, when you excite the world with the science, it's not peer-reviewed, clean. It all sounds like bullshit. It's like a TED Talk. And people roll their eyes and they hate that a TED Talk gets millions of views or something like that. And then everybody pulls each other back. There's this force that's just kind of, it's hard to stand out unless you win a Nobel Prize or whatever. It's only when you get senior enough where you just stop giving a damn. But just like you said, even when you get tenure, that was always the surprising thing to me. I have many colleagues and friends who have gotten tenure. But there's not a switch. There's not an F-you money switch where you're like, you know what, now I'm going to be more bold. I don't see it. Well, there's a reason for that. Tenure isn't a test. It's a training process. It teaches you to behave in a certain way, to think in a certain way, to accept certain values, and to react accordingly. And the better you are at that, the more likely you are to earn tenure. And by the way, this is not a bad thing. Most things are like that. And I think most of my colleagues are interested in doing great work and they're just having impact in the way that they want to have impact. I do think that as a field, not just as a field, as a profession, we have a habit of belittling those who are popular, as it were, as if the word itself is a kind of scarlet A. I think it's easy to convince yourself, and no one is immune to this, that the people who are better known are better known for bad reasons. The people who are out there dumbing it down are not being pure to whatever the values and ethos is for your field. And it's just very easy to do. Now, having said that, I think that ultimately, people who are able to be popular and out there and touching the world and making a difference, our colleagues do in fact appreciate that in the long run. It's just, you have to be very good at it or you have to be very interested in pursuing it. And once you get past a certain level, I think people accept that for who it is. I mean, I don't know. I'd be really interested in how Rod Brooks felt about how people were interacting with him when he did Fast, Cheap and Out of Control, way, way, way back when. LBW What's Fast, Cheap and Out of Control? AC It was a documentary that involved four people. I remember nothing about it other than Rod Brooks was in it and something about naked mole rats. I can't remember what the other two things were. It was robots, naked mole rats, and then two other. LBW By the way, Rod Brooks used to be the head of the artificial intelligence laboratory at MIT and then launched, I think, iRobot and then Think Robotics, Rethink Robotics? AC Yes, yes. LBW Think is in the word. And also is a little bit of a rock star personality in the AI world, a very opinionated, very intelligent. Anyway, sorry, mole rats and naked. AC Naked mole rats. Also, he was one of my two advisors for my PhD. LBW This explains a lot. AC I would explain. I love Rod. But I also love my other advisor, Paul. Paul, if you're listening, I love you too. Both very, very different people. LBW Paul Viola. AC Paul Viola. Both very interesting people, very different in many ways. But I don't know what Rod would say to you about what the reaction was. I know that for the students at the time, because I was a student at the time, it was amazing. This guy was in a movie being very much himself. Actually, the movie version of him is a little bit more Rod than Rod. I think they edited it appropriately for him. But it was very much Rod. And he did all this while doing great work. I mean, he was running the AI lab at that point or not. I don't know. But anyway, he was running the AI lab, or would be soon. He was a giant in the field. He did amazing things, made a lot of his bones by doing the kind of counterintuitive science, right? And saying, no, you're doing this all wrong. Representation is crazy. The world is your own representation. You just react to it. I mean, these are amazing things. And continues to do those sorts of things as he's moved on. I have, I think he might tell you, I don't know if he would tell you it was good or bad, but I know that for everyone else out there in the world, it was a good thing. And certainly, he continued to be respected. So it's not as if it destroyed his career by being popular. All right, let's go into a topic where I'm on thin ice, because I grew up in the Soviet Union and Russia. My knowledge of music, this American thing you guys do, is quite foreign. So your research group is called, as we've talked about, the Lab for Interactive Artificial Intelligence. But also, there's just a bunch of mystery around this, my research fails me, also called PFUNK. Yep. P stands for probabilistic. And what does FUNK stand for? So a lot of my life is about making acronyms. So if I have one quirk, it's that people will say words and I see if they make acronyms. And if they do, then I'm happy. And then if they don't, I try to change it so that they make acronyms. It's just a thing that I do. So PFUNK is an acronym. It has three or four different meanings. But finally, I decided that the P stands for probabilistic because at the end of the day, it's machine learning and it's randomness and it's uncertainty, which is the important thing here. And the FUNK can be lots of different things. But I decided I should leave it up to the individual to figure out exactly what it is. But I will tell you that when my students graduate, when they get out, as we say, at Tech, I hand them, they put on a hat and star glasses and a medallion from the PFUNK era and we take a picture and I hand them a pair of fuzzy dice, which they get to keep. So there's a sense to it, which is not an acronym, like literally FUNK. You have a dark, mysterious past. Mm-hmm. Oh, it's not dark. It's just fun. As in hip hop and FUNK. Yep. Yep. So can you educate a Soviet-born Russian about this thing called hip hop? Like if you were to give me, like, you know, if we went on a journey together and you were trying to educate me about, especially, you know, the past couple of decades in the 90s about hip hop or FUNK, what records or artists would you introduce me to? Would you tell me about, or maybe what influenced you in your journey or what you just love? Like when the family's gone and you just sit back and just blast some stuff these days, what do you listen to? Well, so I listen to a lot, but I will tell you, well, first off, all great music was made when I was 14, and that statement is true for all people, no matter how old they are or where they live. But for me, the first thing that's worth pointing out is that hip hop and rap aren't the same thing. So depending on who you talk to about this, and there are people who feel very strongly about this, much more strongly than I do. You're offending everybody in this conversation, so this is great. Let's keep going. Hip hop is a culture. It's a whole set of things, of which rap is a part. So tagging is a part of hip hop. I don't know why that's true, but people tell me it's true, and I'm willing to go along with it because they get very angry about it. But hip hop is- Tagging is like graffiti? Tagging is like graffiti. And there's all these, including the popping and the locking and all the dancing and all those things, that's all a part of hip hop. It's a way of life, which I think is true. And then there's rap, which is this particular- The music part. Yes, or a music part. A music part, yeah. I mean, you wouldn't call the stuff that DJs do the scratching. That's not rap, right? But it's a part of hip hop, right? So given that we understand that hip hop is this whole thing, what are the rap albums that best touch that for me? Well, if I were going to educate you, I would try to figure out what you liked, and then I would work you there. Leonard Skinner. Oh my God. Yeah. Then I would probably start with- Led Zeppelin. There's a fascinating ex- No, it's okay. There's a fascinating exercise one can do by watching old episodes of I Love the 70s, I Love the 80s, I Love the 90s with a bunch of friends, and just see where people come in and out of pop culture. So if you're talking about those people, then I would actually start you with where I would hope to start you with anyway, which is Public Enemy. Particularly, it takes a nation of millions to hold his back, which is clearly the best album ever produced, and certainly the best hip hop album ever produced, in part because it was so much of what was great about the time. Fantastic lyrics, excuse me, it's all about the lyrics. Amazing music that was coming from- Rick Rubin was the producer of that, and he did a lot of very kind of heavy metal-ish, at least in the 80s sense, at the time. And it was focused on politics in the 1980s, which was what made hip hop so great. I would start you there, then I would move you up through things that have been happening more recently. I'd probably get you to someone like a Most Def. I would give you a history lesson, basically. Most Def's amazing. He hosted a poetry jam thing on HBO or something like that? Probably. I don't think I've seen it, but I wouldn't be surprised. Yeah, spoken poetry, that guy. Yes, he's amazing. He's amazing. Yeah, he's amazing. And then after I got you there, I'd work you back to EPMD, and eventually I would take you back to The Last Poets, and particularly their first album, The Last Poets, which was 1970, to give you a sense of history, and that it actually has been building up over a very, very long time. So we would start there, because that's where your music aligns, and then we would cycle out, and I'd move you to the present, and then I'd take you back to the past. Because I think a large part of people who are kind of confused about any kind of music, the truth is, this is the same thing we've always been talking about. It's about narrative and being a part of something and being immersed in something so you understand it. Jazz, which I also like, is one of the things that's cool about jazz is that you come and you meet someone who's talking to you about jazz, and you have no idea what they're talking about. And then one day it all clicks, and you've been so immersed in it, you go, oh yeah, that's a Charlie Parker. And then you start using words that nobody else understands, and it becomes a part of you. Hip-hop's the same way. Everything's the same way. They're all cultural artifacts. But I would help you to see that there's a history of it, and how it connects to other genres of music that you might like to bring you in, so that you could kind of see how it connects to what you already like, including some of the good work that's been done with fusions of hip-hop and bluegrass. Oh no. Yes. Some of it's even good. Not all of it, but some of it is good. But I'd start you with It Takes a Nation to Make Us All Hold Us Back. There's an interesting tradition in more modern hip-hop of integrating almost like classic rock songs or whatever, integrating into their music, into the beat, into the whatever. It's kind of interesting. It gives a whole new, not just classic rock, but what is it, Kanye with Gold Digger? Mm-hmm. Old R&B. Taking and pulling old R&B, right? Well, that's been true since the beginning. In fact, that's in some ways, that's why the DJ used to get top billing, because it was the DJ that brought all the records together and made it worth so that people could dance. You go back to those days, mostly in New York, though not exclusively, but mostly in New York where it sort of came out of. It was the DJ that brought all the music together and the beats and showed that basically music is itself an instrument. Very meta. And you can bring it together, and then you sort of rap over it and so on. And it moved that way. So that's going way, way back. Now, in the period of time where I grew up, when I became really into it, which was most of the 80s, it was more funk was the back for a lot of the stuff, public enemy at that time notwithstanding. Which is very nice, because it tied into what my parents listened to and what I vaguely remember listening to when I was very small. And by the way, complete revival of George Clinton and Parliament and Funkadelic and all of those things to bring it sort of back into the 80s and into the 90s. And as we go on, you're going to see the last decade and the decade before that being brought in. And when you don't think that you're hearing something you've heard, it's probably because it's being sampled by someone who...referring to something they remembered when they were young, perhaps from somewhere else altogether. And you just didn't realize what it was because it wasn't a popular song where you happened to grow up. So this stuff's been going on for a long time. It's one of the things that I think is beautiful. Run DMC, Jam Master Jay used to play piano. He would record himself playing piano and then sample that to make it a part of what was going on rather than play the piano. JL Collins That's how his mind can think. ACP Well, it's pieces. You're putting pieces together, you're putting pieces of music together to create new music, right? Now, that doesn't mean that the root... I mean, the roots are doing their own thing. Right? JL Collins Yeah. That's a whole... ACP Yeah. But still, it's the right attitude. JL Collins And what else is jazz, right? Jazz is about putting pieces together and then putting your own spin on it. It's all the same. It's all the same thing. It's all the same thing. JL Collins Because you mentioned lyrics, it does make me sad. Again, this is me talking trash about modern hip hop. I haven't investigated. I'm sure people will correct me that there's a lot of great artists. That's part of the reason I'm saying it is they'll leave it in the comments that you should listen to this person, is the lyrics went away from talking about maybe not just politics, but life and so on. The kind of protest songs, even if you look at a Bob Marley, or you see Public Enemy, or Rage Against the Machine more on the rock side, that's the place where we go to those lyrics. JL Collins Classic rock is all about, my woman left me, or I'm really happy that she's still with me, or the flip side. It's love songs of different kinds. It's all love, but it's less political, less interesting, I would say, in terms of deep, profound knowledge. It seems like rap is the place where you would find that. It's sad that for the most part, what I see, you look at like mumble rap or whatever, they're moving away from lyrics and more towards the beat and the musicality of it. I've always been a fan of the lyrics. In fact, if you go back and you read my reviews, which I recently was rereading, man, I wrote my last review the month I graduated, when I got my PhD, which says something about something. I'm not sure what though. I always would, I don't always, but I often would start with, it's all about the lyrics. For me, it's about the lyrics. Someone has already written in the comments before I've even finished having this conversation that neither of us knows what we're talking about, and it's all in the underground hip hop, and here's who you should go listen to. That is true. Every time I despair for popular rap, someone points me to, or I discover some underground hip hop song, and I'm made happy and whole again. I know it's out there. I don't listen to as much as I used to, because I'm listening to podcasts and old music from the 1980s and 90s. It's a kind of, no beat at all, but there's a little bit of sampling here and there, I'm sure. By the way, James Brown is funk or no? Yes, and so is Junior Wells, by the way. Who's that? Ah, Junior Wells, Chicago Blues. He was James Brown before James Brown was. It's hard to imagine somebody being James Brown. Go look up Hoodoo Man Blues, Junior Wells, and just listen to Snatch It Back and Hold It, and you'll see it. They were contemporaries. Where do you put Little Richard or all that kind of stuff, like Ray Charles, like when they get hit the road, Jack, don't you come back? There's a funkiness in it. Oh, there's definitely a funkiness in it. I mean, it's all a line. I mean, it's all a line that carries it all together. I guess I would answer your question depending upon whether I'm thinking about it in 2020 or I'm thinking about it in 1960. I'd probably give a different answer. I'm just thinking in terms of, that was rock, but when you look back on it, it was funky, but we didn't use those words. Or maybe we did, I wasn't around, but I don't think we used the word 1960 funk. Certainly not the way we used it in the 70s and the 80s. Do you reject disco? I do not reject disco. I appreciate all the mistakes that we have made to get to where we are now. Actually, some of the disco is actually really, really good. John Travolta. Oh boy. He regrets it probably. Maybe not. Well, it got him the reason. Well, it's the mistakes thing. Yeah. And it got him to where he's going, where he is. Oh, well, thank you for taking that detour. You've talked about computing. We've already talked about computing a little bit, but can you try to describe how you think about the world of computing, where it fits into the sets of different disciplines? We mentioned College of Computing. How should they think about computing, especially from an educational perspective of what is the perfect curriculum that defines for a young mind what computing is? I don't know about a perfect curriculum, although that's an important question, because at the end of the day, without the curriculum, you don't get anywhere. Curriculum, to me, is the fundamental data structure. It's not even the classroom. Data structure. I love it. I mean, the world is… Right? So I think the curriculum is where I like to play. So I spend a lot of time thinking about this. But I will tell you, I will answer your question by answering a slightly different question first and getting back to this, which is, you know, you talked about disciplines and what does it mean to be a discipline. The truth is, what we really educate people in from the beginning, but certainly through college, you've sort of failed if you don't think about it this way, I think, is the world… People often think about tools and tool sets, and when you're really trying to be good, you think about skills and skill sets. But disciplines are about mindsets, right? They're about fundamental ways of thinking, not just the hammer that you pick up, whatever that is, to hit the nail, not just the skill of learning how to hammer well or whatever. It's the mindset of like, what's the fundamental way to think about the world, right? And disciplines, different disciplines give you different mindsets. They give you different ways of sort of thinking through. So with that in mind, I think that computing, even ask the question whether it's a discipline, you have to decide, does it have a mindset? Does it have a way of thinking about the world that is different from, you know, the scientist who is doing discovery and using the scientific method as a way of doing it, or the mathematician who builds abstractions and tries to find sort of steady state truth about the abstractions that may be artificial, but whatever. Or is it the engineer who's all about, you know, building demonstrably superior technology with respect to some notion of trade-offs, whatever that means, right? That's sort of the world that you, the world that you live in. What is computing? You know, how is computing different? So I've thought about this for a long time and I've come to a view about what computing actually is, what the mindset is. And it's, you know, it's a little abstract, but that would be appropriate for computing. I think that what distinguishes the computationalist from others is that he or she understands that models, languages, and machines are equivalent. They're the same thing. And because it's not just a model, but it's a machine that is an executable thing that can be described as a language, that means that it's dynamic. So it's not the, it is mathematical in some sense, in the kind of sense of abstraction, but it is fundamentally dynamic and executable. The mathematician is not necessarily worried about either the dynamic part. In fact, whenever I tried to write something for mathematicians, they invariably demand that I make it static. And that's not a bad thing. It's just, it's a way of viewing the world, that truth is a thing, right? It's not a process that continually runs, right? So that dynamic thing matters, that self-reflection of the system itself matters. And that is what computing, that is what computing brought us. So it is a science because it, the models fundamentally represent truths in the world. Information is a scientific thing to discover, right? Not just a mathematical conceit that gets created. But of course it's engineering because you're actually dealing with constraints in the world and trying to execute machines that actually run. But it's also a math because you're actually worrying about these languages that describe what's happening. But the fact that regular expressions and finite state automata, one of which feels like a machine, or at least an abstraction machine, and the other is a language that they're actually the equivalent thing. I mean, that is not a small thing. And it permeates everything that we do, even when we're just trying to figure out how to do debugging. So that idea, I think, is fundamental. And we would do better if we made that more explicit. How my life has changed in my thinking about this in the 10 or 15 years it's been since I tried to put that to paper with some colleagues, is the realization, which comes to a question you actually asked me earlier, which has to do with trees falling down and whether it matters, is this sort of triangle of equality. It only matters because there's a person inside the triangle, right? That what's changed about computing, computer science, whatever you want to call it, is we now have so much data and so much computational power. We're able to do really, really interesting, promising things. But the interesting and the promising kind of only matters with respect to human beings and their relationship to it. So the triangle exists. That is fundamentally computing. What makes it worthwhile and interesting and potentially world species changing is that there are human beings in the triangle. And that's what's changing is that there are human beings inside of it and intelligence that has to interact with it that changes the data, the information that makes sense and gives meaning to the models, the languages, and the machines. So if the curriculum can convey that while conveying the tools and the skills that you need in order to succeed, then it is a big win. That's what I think you have to do. Lex Mosses Do you pull psychology, these human things into that, into the idea, into this framework of computing? Do you pull in psychology, neuroscience, like parts of psychology, parts of neuroscience, parts of sociology? What about philosophy, like studies of human nature from different perspectives? Maynard Johnson Absolutely. And by the way, it works both ways. So let's take biology for a moment. It turns out a cell is basically a bunch of if-then statements if you look at it the right way, which is nice because I understand if-then statements. I never really enjoyed biology, but I do understand if-then statements. And if you tell the biologists that and they begin to understand that, it actually helps them to think about a bunch of really cool things. There'll still be biology involved, but whatever. On the other hand, the fact of biology is, in fact, a bunch of, the cell is a bunch of if-then statements or whatever, allows the computationalists to think differently about the language and the way that we, well, certainly the way we would do AI and machine learning, but there's just even the way that we think about computation. So the important thing to me is, as my engineering colleagues who are not in computer science worry about computer science eating up engineering to colleges where computer science is trapped, it's not a worry. You shouldn't worry about that at all. Computing is, computer science, computing, it's not, it's central, but it's not the most important thing in the world. It's not more important. It is just key to helping others do other cool things they're going to do. You're not going to be a historian in 2030. You're not going to get a PhD in history without understanding some data science and computing, because the way you're going to get history done, in part, and I say done, the way you're going to get it done is you're going to look at data and you're going to let, you're going to have a system that's going to help you to analyze things to help you to think about a better way to describe history and to understand what's going on and what it tells us about where we might be going. The same is true for psychology, same is true for all of these things. The reason I brought that up is because the philosopher has a lot to say about computing. The psychologist has a lot to say about the way humans interact with computing, right? And certainly a lot about intelligence, which, at least for me, ultimately is kind of the goal of building these computational devices is to build something intelligent. Lex Dyson Did you think computing will eat everything in some certain sense or almost like disappear because it's part of everything? David Malan It's so funny you say that. So I want to say it's going to metastasize, but there's kind of two ways that fields destroy themselves. One is they become super narrow, and I think we can think of fields that might be that way. They become they become pure. And we have that instinct. We have that impulse. I'm sure you can think of several people who want computer science to be this pure thing. The other way is you become everywhere and you become everything and nothing. And so everyone says, you know, I'm going to teach Fortran for engineers or whatever. I'm going to do this. And then you lose the thing that makes it worth studying in and of itself. The thing about computing, and this is not unique to computing, though at this point in time it is distinctive about computing where we happen to be in 2020, is we are both a thriving major, in fact, the thriving major, almost every place. And we're a service unit because people need to know the things we need to know. And our job, much as the mathematician's job, is to help, you know, this person over here to think like a mathematician much the way the point isn't the point of you taking chemistry as a freshman is not to learn chemistry. It's to learn to think like a scientist, right? Our job is to help them to think like a computationalist. And we have to take both of those things very seriously. And I'm not sure that as a field we have historically certainly taken the second thing, that our job is to help them to think a certain way. People who aren't going to be our major, I don't think we've taken that very seriously at all. I don't know if you know who Dan Carlin is. He has this podcast called Hardcore History. Yes. I've just did an amazing four-hour conversation with him, mostly about Hitler. But I bring him up because he talks about this idea that it's possible that history as a field will become, like currently most people study history a little bit, kind of are aware of it. We have a conversation about it, different parts of it. I mean, there's a lot of criticism to say that some parts of history are being ignored, blah, blah, blah, so on. But most people are able to have a curiosity and able to learn it. His thought is it's possible, given the way social media works, the current way we communicate, that history becomes a niche field where literally most people just ignore. Because everything is happening so fast that the history starts losing its meaning and then it starts being a thing that only, you know, like the theoretical computer science part of computer science, it becomes a niche thing that only like the rare holders of the world wars and the, you know, all the history, the founding of the United States, all those kinds of things, the civil wars. And it's a kind of profound thing to think about how we can lose track, how we can lose these fields when they're best, like in the case of history, it's best for that to be a pervasive thing that everybody learns and thinks about and so on. And I would say computing is quite obviously similar to history in the sense that it seems like it should be a part of everybody's life to some degree, especially like as we move into the later parts of the 21st century. And it's not obvious that that's the way it'll go. It might be in the hands of the few still, like depending if it's machine learning, you know, it's unclear that computing will win out. It's currently very successful, but it's not, I would say that's something, I mean, you're at the leadership level of this, you're defining the future, so it's in your hands. No pressure. But like, it feels like there's multiple ways this can go. And there's this kind of conversation of everybody should learn to code, right? The changing nature of jobs and so on. Do you have a sense of what your role in education of computing is here? Like what's the hopeful path forward? There's a lot there. I will say that, well, first off, it would be an absolute shame if no one studied history. On the other hand, as T approaches infinity, the amount of history is presumably also growing, at least linearly. And so, you have to forget more and more of history. But history needs to always be there. I mean, I can imagine a world where, you know, if you think of your brains as being outside of your head, that you can kind of learn the history you need to know when you need to know it. That seems fanciful. But it's a kind of way of, you know, is there a sufficient statistic of history? No. And there certainly, but there may be for the particular thing you have to care about. But, you know, those who do not remember. It's for our objective camera discussion, right? Yeah. And, you know, we've already lost lots of history. And of course, you have your own history, that some of which will be, it's even lost to you, right? You don't even remember whatever it was you were doing 17 years ago. All the ex-girlfriends. Yeah. Gone. Exactly. So, you know, history is being lost anyway, but the big lessons of history shouldn't be. And I think, you know, to take it to the question of computing and sort of education, the point is you have to get across those lessons. You have to get across the way of thinking. And you have to be able to go back and, you know, you don't want to lose the data, even if, you know, you don't necessarily have the information at your fingertips. With computing, I think it's somewhat different. Everyone doesn't have to learn how to code, but everyone needs to learn how to think in the way that you can be precise. And I mean precise in the sense of repeatable, not just, you know, in the sense of, not resolution in the sense of get the right number of bits. In saying what it is you want the machine to do and being able to describe a problem in such a way that it is executable, which we are not, human beings are not very good at that. In fact, I think we spend much of our time talking back and forth just to kind of vaguely understand what the other person means and hope we get it good enough that we can act accordingly. You can't do that with machines, at least not yet. And so, you know, having to think that precisely about things is quite important. And that's somewhat different from coding. Coding is a crude means to an end. On the other hand, the idea of coding, what that means, that it's a programming language and it has these sort of things that you fiddle with and these ways that you express, that is an incredibly important point. In fact, I would argue that one of the big holes in machine learning right now and in AI is that we forget that we are basically doing software engineering. We forget that we are doing, we're using programming, like we're using languages to express what we're doing. We get just so all caught up in the deep network or we get all caught up in whatever that we forget that, you know, we're making decisions based upon a set of parameters that we made up. And if we did slightly different parameters, we'd have completely different outcomes. And so the lesson of computing, computer science education, is to be able to think like that and to be aware of it when you're doing it. Basically, at the end of the day, it's a way of surfacing your assumptions. I mean, we call them parameters or, you know, we call them if-then statements or whatever, but you're forced to surface those assumptions. That's the key thing that you should get out of a computing education, that and that the models, the languages, and the machines are equivalent. But it actually follows from that, that you have to be explicit about what it is you're trying to do because the model you're building is something you will one day run. So you better get it right, or at least understand it and be able to express roughly what you want to express. So I think it is key that we figure out how to educate everyone to think that way. Because at the end, it would not only make them better at whatever it is that they are doing, and I emphasize doing, it'll also make them better citizens. It'll help them to understand what others are doing to them so that they can react accordingly. Because you're not going to solve the problem of social media insofar as you think of social media as a problem by just making slightly better code, right? It only works if people react to it appropriately and know what's happening, and therefore take control over what they're doing. I mean, that's my take on it. Okay, let me try to proceed awkwardly into the topic of race. One is because it's a fascinating part of your story and you're just eloquent and fun about it. And then the second is because we're living through a pretty tense time in terms of race tensions and discussions and ideas in this time in America. You grew up in Atlanta, not born in Atlanta. Is some southern state somewhere, Tennessee, something like that? Tennessee. Nice, okay. But early on you moved, you basically, you identify as an Atlanta native, yeah. And you've mentioned that you grew up in a predominantly Black neighborhood. By the way, Black, African American, personal color? I prefer Black. Black. With a capital B. With a capital B. The other letters are... The rest of them don't matter, it's a capital B. Okay, so predominantly Black neighborhood, and so you didn't almost see race, maybe you can correct me on that. And then in the video you talked about when you showed up to Georgia Tech for your undergrad, you're one of the only Black folks there, and that was like, oh, that was a new experience. So can you take me from just a human perspective, but also from a race perspective, your journey growing up in Atlanta, and then showing up at Georgia Tech? Okay, that's easy. And by the way, that story continues through MIT as well. In fact, it was quite a bit more stark at MIT and Boston. So maybe just a quick pause, Georgia Tech was undergrad, MIT was graduate school. Mm-hmm, and I went directly to grad school from undergrad, so I had no distractions in between my bachelor's and my master's and PhD. You didn't go on a backpacking trip in Europe. Didn't do any of that. In fact, I literally went to IBM for three months, got in a car, and drove straight to Boston with my mother, or Cambridge. Moved into an apartment I'd never seen over the Royal East. Anyway, that's another story. So let me tell you a little bit about... You miss MIT? Oh, I loved MIT. I don't miss Boston at all, but I loved MIT. And then miss Fighting Warrants. Oh, so let's back up to this. So as you said, I was born in Chattanooga, Tennessee. My earliest memory is arriving in Atlanta in a moving truck at the age of three and a half, so I think of myself as being from Atlanta. I have a very distinct memory of that. So I grew up in Atlanta, it's the only place I ever knew as a kid. I loved it. Like much of the country, and certainly much of Atlanta in the 70s and 80s, it was deeply, highly segregated, though not in a way that I think was obvious to you unless you were looking at it, or were old enough to have noticed it. But you could divide up Atlanta, and Atlanta's hardly unique in this way, by highway, and you could get race and class that way. So I grew up not only in a predominantly Black area, to say the very least, I grew up on the poor side of that. But I was very much aware of race for a bunch of reasons. One, that people made certain that I was, and my family did, but also that it would come up. So in first grade, I had a girlfriend. I say I had a girlfriend, I didn't have a girlfriend, I wasn't even entirely sure what girls were in the first grade. But I do remember she decided I was her girlfriend, a little white girl named Heather. And we had a long discussion about how it was okay for us to be boyfriend and girlfriend, despite the fact that she was white and I was Black. Lex Domino Between the two of you? Pete McKeown Yeah, between the two. Lex Domino Did your parents know about this? Pete McKeown Yes, but being a girlfriend and boyfriend in first grade just basically meant that you spent slightly more time together during recess. It had no, I think we Eskimo kissed once. Lex Domino Yeah. Pete McKeown It doesn't mean, it didn't mean anything. Lex Domino Scandalous. Pete McKeown It was, at the time it felt very scandalous, because everyone was watching. I was like, ah, my life is, now my life has changed in first grade. No one told me elementary school would be like this. Lex Domino Did you write poetry or? Pete McKeown Not in first grade, that would come later. Lex Domino Okay. Pete McKeown That would come during puberty, when I wrote lots and lots of poetry. Anyway, so I was aware of it. I didn't think too much about it, but I was aware of it. But I was surrounded. It wasn't that I wasn't aware of race, it's that I wasn't aware that I was a minority. It's different. And it's because I wasn't, as far as my world was concerned. I mean, I'm six years old, five years old in first grade. The world is the seven people I see every day, right? So it didn't feel that way at all. And by the way, this being Atlanta, home of the Civil Rights Movement and all the rest, it meant that when I looked at TV, which back then one did, because there were only three, four or five channels, right? And I saw the news, which my mother might make me watch, you know, Monica Kaufman was on TV telling me the news, and they were all black, and the mayor was black and always been black. And so it just never occurred to me. When I went to Georgia Tech, I remember the first day walking across campus from West Campus to East Campus, and realizing along the way that of the hundreds and hundreds and hundreds and hundreds of students that I was seeing, I was the only black one. That was enlightening and very off-putting because it occurred to me. And then of course it continued that way for, well, for the rest of my, for much of the rest of my career at Georgia Tech. Of course, I found lots of other students. And I met people because in Atlanta, you're either black or you're white. There was nothing else. So I began to meet students of Asian descent, and I met students who we would call Hispanic and so on and so forth. And, you know, so my world, this is what college is supposed to do, right? It's supposed to open you up to people. And it did. But it was a very strange thing to be in the minority. When I came to Boston, I will tell you a story. I applied to one place as an undergrad, Georgia Tech, because I was stupid. I didn't know any better. I just didn't know any better, right? No one told me. When I went to grad school, I applied to three places, Georgia Tech, because that's where I was, MIT, and CMU. When I got in to MIT, I got into CMU, but I had a friend who went to CMU. And so I asked him what he thought about it. He spent his time explaining to me about Pittsburgh, much less about CMU, but more about Pittsburgh, with which I developed a strong opinion based upon his strong opinion, something about the sun coming out two days out of the year. And I didn't get a chance to go there because the timing was wrong. I think it was because the timing was wrong. At MIT, I asked 20 people I knew, either when I visited or I had already known for a variety of reasons, whether they liked Boston. And 10 of them loved it and 10 of them hated it. The 10 who loved it were all white. The 10 who hated it were all black. And they explained to me very much why that was the case. Both dads told me why. And the stories were remarkably the same for the two clusters. And I came up here and I could see it immediately, why people would love it and why people would not. And- Why people tell you about the nice coffee shops and- Well, it wasn't coffee shops. It was CD, used CD places. But yeah, it was that kind of a thing. Nice shops. Oh, there's all these students here. Harvard Square is beautiful. You can do all these things and you can walk in something about the outdoors, which I wasn't the slightest bit interested in. The outdoors is for the bugs. It's not for humans. And the- That should be a t-shirt. Yeah, I mean, it's the way I feel about it. And the black folk told me completely different stories about which part of town you did not want to be caught in after dark. And I heard all, but that was nothing new. So I decided that MIT was a great place to be as a university. And I believed it then, I believe it now. And that whatever it is I wanted to do, I thought I knew what I wanted to do, but what if I was wrong? Someone there would know how to do it. Of course, then I would pick the one topic that nobody was working on at the time, but that's okay. It was great. And so I thought that I would be fine. And I'd only be there for four or five years, I told myself, which turned out not to be true at all. But I enjoyed my time. I enjoyed my time there. But I did see a lot of, I ran across a lot of things that were driven by what I look like while I was here. I got asked a lot of questions. I ran into a lot of cops. I saw a lot about the city. But at the time, I mean, I haven't been here a long time. These are the things that I remember. So this is 1990. There was not a single Black radio station. Now this is 1990. There aren't, I don't know if there are any radio stations anymore. I'm sure there are, but I don't listen to the radio anymore. Almost no one does, at least if you're under a certain age. But the idea is you could be in a major metropolitan area and there wasn't a single Black radio station, by which I mean a radio station that played what we would call Black music then, was absurd, but somehow captured kind of everything about the city. I grew up in Atlanta, and you've heard me tell you about Atlanta. Boston had no economically viable or socially cohesive Black middle class. Insofar as it existed, it was uniformly distributed throughout large parts, not all parts, but large parts of the city. And where you had concentrations of Black Bostonians, they tended to be poor. It was very different from where I grew up. I grew up on the poor side of town, sure. But then in high school, well, in ninth grade, we didn't have middle school. I went to an eighth grade school where there was a lot of, let's just say we had a riot the year that I was there. There was at least one major fight every week. It was an amazing experience. But when I went to ninth grade, I went to academy. Math and science academy, Mays High. It was a public school. It was a magnet school. That's why I was able to go there. It was the first high school, I think, in the state of Georgia to sweep the state math and science fairs. It was great. It had 385 students, all but four of whom were Black. I went to school with the daughter of the former mayor of Atlanta, Michael Jackson's cousin. It was an upper middle class. Dropping names. Whatever. I just drop names occasionally. Drop the mic, drop some names. Just to let you know, I used to hang out with Michael Jackson's cousin. 12th cousin, nine times removed. I don't know. The point is, we had a parking problem because the kids had cars. I did not come from a place where you had cars. I had my first car when I came to MIT, actually. It was just a very different experience for me. But I'd been to places where, whether you were rich or whether you were poor, you could be Black and rich or Black and poor. It was there. There were places. And they were segregated by class as well as by race. But that existed. Here, at least when I was here, it didn't feel that way at all. It felt like a bunch of a really interesting contradiction. It felt like it was the interracial dating capital of the country. Yeah. It really felt that way. But it also felt like the most racist place I ever spit to any time. You couldn't go up the Orange Line. At that time, I mean, again, that was 30 years ago. I don't know what it's like now. But there were places you couldn't go. And you knew it. Everybody knew it. And there were places you couldn't live. And everybody knew that. And that was just the greater Boston area in 1992. Subtle racism or explicit racism? Both. So. In terms of within the institutions, did you feel, was there levels in which you were empowered to be first or one of the first Black people in a particular discipline in some of these great institutions that you were part of, you know, Georgia Tech or MIT? And was there a part where it felt limiting? I always felt empowered. Some of that was my own delusion, I think. But it worked out. So I never felt, in fact, quite the opposite. Not only did I not feel as if no one was trying to stop me, I had the distinct impression that people wanted me to succeed. By people, I meant the people in power. Not my fellow students. Not that they didn't want me to succeed. But I felt supported, or at least that people were happy to see me succeed at least as much as anyone else. But you know, 1990, you're dealing with a different set of problems. You're very early, at least in computer science, you're very early in the sort of Jackie Robinson period. You know, there's this thing called the Jackie Robinson syndrome, which is that you have to, you know, the first one has to be perfect or has to be sure to succeed because if that person fails, no one else comes after for a long time. So, you know, it was kind of in everyone's best interest. But I think it came from a sincere place. I'm completely sure that people went out of their way to try to make certain that the environment would be good. Not just for me, but for the other people who of course were around. And I was hardly the only, I was the only person in the AI lab, but I wasn't the only person at MIT by a long shot. On the other hand, we're what? At that point, we would have been what, less than 20 years away from the first Black PhD to graduate from MIT, right? Shirley Jackson, right? 1971, something like that, somewhere around then. So we weren't that far away from the first first, and we were still another eight years away from the first Black PhD in computer science, right? So we were in, it was a sort of interesting time, but I did not feel as if the institutions of the university were against any of that. And furthermore, I felt as if there was enough of a critical mass across the institute from students and probably faculty, though I didn't know them, who wanted to make certain that the right thing happened. It was very different from the institutions of the rest of the city, which I think were designed in such a way that they felt no need to be supportive. Let me ask a touchy question on that. So you kind of said that you didn't feel, you felt empowered. Is there some lesson, advice, in the sense that no matter what, you should feel empowered? You said, you used the word, I think, illusion or delusion. Mm-hmm. Is there a sense from the individual perspective where you should always kind of ignore, you know, the, ignore your own eyes, ignore the little forces that you are able to observe around you that are like trying to mess with you of whether it's jealousy, whether it's hatred in its pure form, whether it's just hatred in its like diluted form, all that kind of stuff, and just kind of see yourself as empowered and confident, all those kinds of things. I mean, it certainly helps, but it's, there's a trade-off, right? You have to be diluted enough to think that you can succeed. I mean, you can't get a PhD unless you're crazy enough to think you can invent something that no one else has come up with. I mean, that kind of massive delusion is that. So you have to be diluted enough to believe that you can succeed despite whatever odds you see in front of you, but you can't be so diluted that you don't think that you need to step out of the way of the oncoming train. Right? So it's all a trade-off, right? You have to kind of believe in yourself. It helps to have a support group around you in some way or another. I was able to find that. I've been able to find that wherever I've gone, even if it wasn't necessarily on the floor that I was in. I had lots of friends when I was here. Many of them still live here, and I've kept up with many of them. So I felt supported. And certainly I had my mother and my family and those people back home that I could always, I could always lean back on, even if it were a long distance call that cost money, which is not something that any of the kids today even know what I'm talking about. But back then it mattered. Calling my mom was an expensive proposition. But you have that and it's fine. I think it helps, but you cannot be so diluted that you miss the obvious because it makes things slower and it makes you think you're doing better than you are, and it will hurt you in the long run. Pong You mention cops. You tell a story of being pulled over. Perhaps it happened more than once. David More than once, for sure. Pong One, could you tell that story? And in general, can you give me a sense of what the world looks like when the law doesn't always look at you with the blank slate, with the objective eyes? I don't know how to say it more poetically. David Well, I guess the, I don't either. I guess the answer is it looks exactly the way it looks now because this is the world that we happen to live in, right? It's people clustering and doing the things that they do and making decisions based on one or two bits of information they find relevant, which by the way are all positive feedback loops, which makes it easier for you to believe what you believed before because you behave in a certain way that makes it true and it goes on and circles and cycles and cycles and cycles. So it's just about being on edge. I do not, despite having made it over 50 now. Pong Congratulations, by the way. David God, I have a few gray hairs here and there. Pong You did pretty good. David I think, you know, I don't imagine I will ever see a police officer and not get very, very tense. Now, everyone gets a little tense because it probably means you're being pulled over for speeding or something, or you're going to get a ticket or whatever, right? I mean, the interesting thing about the law in general is that most human beings experience of it is fundamentally negative, right? You're only dealing with a lawyer if you're in trouble, except in a few very small circumstances, right? But so that's just, that's an underlying reality. Now imagine that that's also at the hands of the police officer. I remember the time when I got pulled over that time, halfway between Boston and Wellesley, actually. I remember thinking, when he pulled his gun on me, that if he shot me right now, he'd get away with it. That was the worst thing that I felt about that particular moment, is that if he shoots me now, he will get away with it. It would be years later when I realized actually much worse than that, is that he'd get away with it. And if anyone, if it became a thing that other people knew about, odds were, would be of course that it wouldn't. But if it became a thing that other people knew about, if I was living in today's world as opposed to the world 30 years ago, that not only would he get away with it, but that I would be painted a villain. I was probably big and scary, and I probably moved too fast, and if only I'd done what he said, and da, da, da, da, da, da, da, which is somehow worse, right? That hurts not just you, you're dead, but your family, and the way people look at you, and look at your legacy or your history. That's terrible. And it would work. I absolutely believe it would have worked, had he done it. Now, he didn't. I don't think he wanted to shoot me. I don't think he felt like killing anybody. He did not go out that night expecting to do that, or planning on doing it. And I wouldn't be surprised if he never, ever did that, or ever even pulled his gun again. I don't know the man's name. I don't remember anything about him. I do remember the gun. Guns are very big when they're in your face, I can tell you this much. They're much larger than they seem. But- And you're basically like speeding or something like that. He said I ran a light, I think. Ran a light. I don't think I ran a light, but in fact, I may not have even gotten a ticket. I may have just gotten a warning. I think he was a little spooked too. But he pulled a gun. Yeah. Apparently I moved too fast or something. Rolled my window down before I should have. It's unclear. I think he thought I was going to do something, or at least that's how he behaved. So how, if we can take a little walk around your brain, how do you feel about that guy, and how do you feel about cops after that experience? Well, I don't remember that guy, but my views on police officers is the same view I have about lots of things. Fire is an important and necessary thing in the world, but you must respect fire because it will burn you. Fire is a necessary evil in the sense that it can burn you, necessary in the sense that, you know, heat and all the other things that we use fire for. So when I see a cop, I see a giant ball of flame, and I just try to avoid it. And then some people might see a nice place, a nice thing to roast marshmallows with family over. Which is fine, but I don't roast marshmallows. Okay, so let me go a little darker, and I apologize. Just talked to Dan Carlin about Hitler for four hours. So sorry if I go dark here a little bit, but is it easy for this experience of just being careful with the fire and avoiding it to turn to hatred? Yeah, of course. And one might even argue that it is a illogical conclusion, right? On the other hand, you've got to live in the world, and I don't think it's helpful. Hate is something one should—I mean, hate is something that takes a lot of energy. So one should reserve it for when it is useful and not carried around with you all the time. Again, there's a big difference between the happy delusion that convinces you that you can actually get out of bed and make it to work today without getting hit by a car, and the sad delusion that means you can not worry about this car that is barreling towards you, right? So we all have to be a little deluded, because otherwise we're paralyzed, right? But one should not be ridiculous. If we go all the way back to something you said earlier about empathy, I think what I would ask other people to get out of this one of many, many, many stories is to recognize that it is real. People would ask me to empathize with the police officer. I would quote back statistics saying that being a police officer isn't even in the top 10 most dangerous jobs in the United States. You're much more likely to get killed in a taxi cab. Half of police officers are actually killed by suicide. But that means their lives are something. Something's going on there with them. And I would more than happy to be empathetic about what it is they go through and how they see the world. I think, though, that if we step back from what I feel, and we step back from what an individual police officer feels, you step up a level, and all this, because all things tie back into interactive AI. The real problem here is that we've built a narrative. We've built a big structure that has made it easy for people to put themselves into different pots, into different clusters, and to basically forget that the people in the other clusters are ultimately like them. It is a useful exercise to ask yourself sometimes, I think, that if I had grown up in a completely different house and a completely different household, as a completely different person, if I had been a woman, would I see the world differently? Would I believe what that crazy person over there believes? And the answer is probably yes, because after all, they believe it. And fundamentally, they're the same as you. So then what can you possibly do to fix it? How do you fix Twitter if you think Twitter needs to be broken, or Facebook if you think Facebook is broken? How do you fix racism? How do you fix any of these things? It's all structural, right? Individual conversations matter a lot, but you have to create structures that allow people to have those individual conversations all the time in a way that is relatively safe, and that allows them to understand that other people have had different experiences, but that ultimately we're the same. Which sounds very... I don't even know what the right word is. I'm trying to avoid a word like saccharine, but it feels very optimistic. But I think that's okay. I think that's a part of the delusion, is you want to be a little optimistic, and then recognize that the hard problem is actually setting up the structures in the first place, because it's in almost no one's interest to change the infrastructure. Right. I tend to believe that leaders have a big role to that, of selling that optimistic delusion to everybody, and that eventually leads to the building of the structures. But that requires a leader that unites everybody on a vision, as opposed to divides on a vision. This particular moment in history feels like there's a non-zero probability, if we go to the P, of something akin to a violent or a non-violent civil war. This is one of the most divided most divisive periods of American history in recent... You can speak to this from perhaps a more knowledgeable and deeper perspective than me, but from my naive perspective, this seems like a very strange time. There's a lot of anger, and it has to do with people, I mean, for many reasons. One, the thing that's not spoken about, I think, much is the quiet economic pain of millions that's growing because of COVID, because of closed businesses, because of lost dreams. So that's building, whatever that tension is building. The other is, there seems to be an elevated level of emotion. I'm not sure if you can psychoanalyze where that's coming from, but this sort of, from which the protests and so on percolated. It's like, why now? Why this particular moment in history? Oh, because enough time has passed. I mean, the very first race riots were in Boston, not to draw anything. Really? When? Oh. This is before late... Going way, I mean, like the 1700s or whatever, right? I mean, there was a massive one in New York. I mean, I'm talking way, way, way back when. So Boston used to be the hotbed of riots. It's just what Boston was all about, or so I'm told from history class. There's an interesting one in New York. I don't remember when that was. Anyway, the point is, basically you got to get another generation, old enough to be angry, but not so old to remember what happened the last time. Right? And that's sort of what happens. But you said two things there that I think are worth unpacking. One has to do with this moment in time and why. Why is this sort of upbuilt? The other has to do with the economic reality of COVID. So I'm actually, I want to separate those things because, for example, this happened before COVID happened, right? So let's separate these two things for a moment. Now, let me preface all this by saying that although I am interested in history, one of my three minors as an undergrad was history, specifically history of the 1960s. Lex Delsignore Interesting. Adam Bates The other was Spanish. Lex Delsignore Okay, that's a mistake. Adam Bates Oh, I love that. And Spanish history, actually. But Spanish and the other was what we would now call cognitive science, but at the time. Lex Delsignore Oh, that's fascinating. Interesting. Adam Bates I minored in cocci here for grad school. That was really fascinating. It was a very different experience from all the computer science classes I've been taking, even the cocci classes I was taking as an undergrad. But anyway, I'm interested in history, but I'm hardly a historian, right? So forgive my, I will ask the audience to forgive my simplification. But I think the question that's always worth asking, as opposed to, it's the same question, but a little different. Not why now, but why not before? Right? So why the 1950s, 60s civil rights movement as opposed to the 1930s, 1940s? Well, first off, there was a civil rights movement in the 30s and 40s. It just wasn't of the same character or quite as well known. Post-World War II, lots of interesting things were happening. It's not as if a switch was turned on and Brown versus the Board of Education or the Montgomery Bus Boycott, and that's when it happened. These things have been building up forever and go all the way back and all the way back and all the way back. And Harriet Tubman was not born in 1950, right? So we can take these things- Lex Delsignore It could have easily happened right after World War II. Adam Bates Yes. I think, and again, I am not a scholar, I think that the big difference was TV. These things are visible. People can see them. It's hard to avoid, right? Why not James Farmer? Why Martin Luther King? Because one was born 20 years after the other or whatever. I think it turns out that, you know, what King's biggest failure was in the early days? It was in Georgia. They were doing the usual thing, trying to integrate. And I forget the guy's name, but you can look this up. But he, a cop, he was a sheriff, made a deal with the whole state of Georgia. We're going to take people and we're going to non-violently put them in trucks. And then we're going to take them and put them in jails very far away from here. And we're going to do that. And we're not going to, there'll be no reason for the press to hang around. And they did that and it worked. And the press left and nothing changed. So next they went to Birmingham, Alabama and Bull O'Connor. And you got to see on TV, little boys and girls being hit with fire hoses and being knocked down. And there was outrage and things changed. Part of the delusion is pretending that nothing bad is happening that might force you to do something big you don't want to do. But sometimes it gets put in your face and then you kind of can't ignore it. And a large part, in my view, of what happened right was that it was too public to ignore. Now we created other ways of ignoring it. Lots of change happened in the South, but part of that delusion was that it wasn't going to affect the West or the Northeast. And of course it did. And that caused its own set of problems, which went into the late 60s into the 70s. And in some ways we're living with that legacy now and so on. So why not, what's happening now? Why it didn't happen 10 years ago? I think it's, people have more voices. There's not just more TV, there's social media. It's very easy for these things to kind of build on themselves. And things are just quite visible. And there's demographic change. I mean, the world is changing rapidly, right? And so it's very difficult. You're now seeing people you could have avoided seeing most of your life growing up in a particular time. And it's happening, it's dispersing at a speed that is fast enough to cause concern for some people, but not so fast to cause massive negative reaction. So that's that. On the other hand, and again, that's a massive oversimplification, but I think there's something there anyway, at least something worth exploring. I'm happy to be yelled at by a real historian. Oh yeah, I mean, there's just the obvious thing, I mean, I guess you're implying, but not saying, the most was just a single video, for example, the George Floyd video. Makes a difference. It's fascinating to think that whatever the mechanisms that put injustice in front of our face, not like directly in front of our face, those mechanisms are the mechanisms of change. Yeah. On the other hand, Rodney King. So no one remembers this. I seem to be the only person who remembers this, but sometime before the Rodney King incident, there was a guy who was a police officer who was saying that things were really bad in Southern California. And he was going to prove it by having some news, some camera people follow him around. And he says, I'm going to go into these towns and just follow me for a week and you will see that I'll get harassed. And like the first night he goes out there and he crosses into the city, some cops pull him over and he's a police officer, remember? They don't know that, of course. They like shove his face through a glass window. This was on the new, like I distinctly remember watching this as a kid. Actually, I guess I wasn't a kid. I was in college at the time. I was in grad school at the time. So that's not enough. Like just- Well, it disappeared. Like a day late, it didn't go viral. Whatever that is, whatever that magic thing is. And whatever it was in 92, it was harder to go viral in 92, right? Or 91, actually it must've been 90 or 91. But that happened. And like two days later, it's like it never happened. Like nobody, again, nobody remembers this. I'm like the only person. Sometimes I think I must've dreamed it. Anyway, Rodney King happens, it goes viral or the moral equivalent thereof at the time. And eventually we get April 29th, right? And I don't know what the difference was between the two things other than one thing caught and one thing didn't. Maybe what's happening now is two things are feeding onto one another. One is more people are willing to believe. And the other is there's easier and easier ways to give evidence. Cameras, body cams, but we're still finding ourselves telling the same story. It's the same thing over and over again. I would invite you to go back and read the op-eds from what people were saying about the violence is not the right answer after Rodney King. And then go back to 1980 and the big riots that were happening around then and read the same op-ed. It's the same words over and over and over again. I mean, there's your remembering history right there. I mean, it's like literally the same words. Like you could have just caught it. I'm surprised no one got flagged for plagiarism. It's interesting if you have an opinion on the question of violence and the popular, perhaps caricature of Malcolm X versus King, Martin Luther King. You know Malcolm X was older than Martin Luther King? People kind of have it in their head that he's younger. Well, he died sooner, right? But only by a few years, right? People think of him as the older statesman and they think of Malcolm X as the young, angry, whatever. But that's more of a narrative device. It's not true at all. I reject the choice. I think it's a false choice. I think they're just things that happen. You just do, as I said, hatred is not, it takes a lot of energy. But you know, every once in a while you have to fight. One thing I will say without taking a moral position, which I will not take on this matter, violence has worked. Yeah, that's the annoying thing. That's the annoying thing. It seems like over the top anger works. Outrage works. So you can say like being calm and rational and just talking it out is going to lead to progress. But it seems like if we just look through history, being irrationally upset is the way you make progress. Well, it's certainly the way that you get someone to notice you. Yeah, and that's it. And if they don't notice you, I mean, what's the difference between that and what, again, without taking a moral position on this, I'm just trying to observe history here. If you, maybe if television didn't exist, the civil rights movement doesn't happen, or it takes longer, or it takes a very different form. Maybe if social media doesn't exist, a whole host of things, positive and negative don't happen. And what do any of those things do other than expose things to people? Violence is a way of shouting. I mean, many people far more talented and thoughtful than I have have said this in one form or another, that you know, violence is the voice of the unheard, right? I mean, it's a thing that people do when they feel as if they have no other option. And sometimes we agree, and sometimes we disagree. Sometimes we think they're justified. Sometimes we think they are not. But regardless, it is a way of shouting. And when you shout, people tend to hear you, even if they don't necessarily hear the words that you're saying. They hear that you were shouting. I see no way. So another way of putting it, which I think is less, let us just say, provocative, but I think is true, is that all change, particularly change that impacts power, requires struggle. The struggle doesn't have to be violent, you know, but it's a struggle nonetheless. Lex Dyson Powerful don't give up power easily. I mean, why should they? But even so, it still has to be a struggle. And by the way, this isn't just about, you know, violent political, whatever, nonviolent political change, right? This is true for understanding calculus, right? I mean, everything requires a struggle. We're back to talking about faculty hiring. At the end of the day, in the end of the day, it all comes down to faculty hiring. And the godfather scene. All a metaphor. Faculty hiring is a metaphor for all of life. Let me ask a strange question. Do you have a, do you think everything is going to be okay in the next year? Do you have a hopeful, do you have a hope that we're going to be okay? I tend to think that everything's going to be okay, because I just tend to think that everything's going to be okay. My mother says something to me a lot, and always has, and I find it quite comforting, which is, this too shall pass. And this too shall pass. Now, this too shall pass is not just a, this bad thing is going away. Everything passes. I mean, I have a 16-year-old daughter who's going to go to college, probably in about 15 minutes, given how fast she seems to be growing up. And you know, I get to hang out with her now, but one day I won't. She'll ignore me just as much as I ignored my parents when I was in college and went to grad school. This too shall pass. But I think that, you know, one day, if we're all lucky, you live long enough to look back on something that happened a while ago, even if it was painful, and mostly it's a memory. So yes, I think it'll be okay. Lex. What about humans? Do you think we'll live into the 21st century? Matthews I certainly hope so. Lex. Are you worried about, are you worried that we might destroy ourselves with nuclear weapons, with AGI, with engineering? Matthews I'm not worried about AGI doing it, but I am worried, I mean, at any given moment, right? Also, but you know, at any given moment, a comet could, I mean, you know, whatever. I tend to think that outside of things completely beyond our control, we have a better chance than not of making it. Lex. You know, I talked to Alex Filipenko from Berkeley. He was talking about comets and that they can come out of nowhere, and that was a realization to me. Wow, we're just watching this darkness and they can just enter, and then we have less than a month. Matthews Yeah, and yet you make it from day to day. Lex. That one shall not pass. Well, maybe for Earth they'll pass, but not for humans. Matthews But I'm just choosing to believe that it's going to be okay, and we're not going to get hit by an asteroid, at least not while I'm around. And if we are, well, there's very little I can do about it, so I might as well assume it's not going to happen. Lex. It makes food taste better. Matthews It makes food taste better. Lex. So you, out of the millions of things you've done in your life, you've also began the This Week in Black History calendar of facts. There's like a million questions I can ask here. You said you're not a historian, but is there, let's start at the big history question of, is there somebody in history, in black history, that you draw a lot of philosophical or personal inspiration from, or you just find interesting, or a moment in history you find interesting? Matthews Well, I find the entirety of the 40s and the 60s and the civil rights movement that didn't happen and did happen at the same time during then quite inspirational. I mean, I've read quite a bit of the time period, at least I did in my younger days when I had more time to read as many things as I wanted to. What was quirky about This Week in Black History when I started in the 80s was how focused it was. It was because of the sources I was stealing from, and I was very much stealing from, so I'd take calendars, anything I could find, Google didn't exist, right? And I just pulled as much as I could and just put it together in one place for other people. What ended up being quirky about it, and I started getting people sending me information, was the inventors, people who, you know, Gary, Garrett Morgan, Benjamin Banneker, people who were inventing things at a time when, how in the world did they manage to invent anything? Like, all these other things were happening, mother necessity, right? All these other things were happening, and there were so many terrible things happening around them, and they went to the wrong state at the wrong time, they may never come back, but they were inventing things we use, right? And it was always inspiring to me that people would still create, even under those circumstances. I got a lot out of that. I also learned a few lessons, I think, you know, the Charles Richard Drews of the world. You know, you create things that impact people, you don't necessarily get credit for them. And that's not right, but it's also okay. PEDRO DA COSTA You're okay with that? DAVE I mean, look, in our world, all we really have is credit. PEDRO DA COSTA I was always bothered by how much value credit is given. DAVE That's the only thing you got. I mean, if you're an academic in some sense, well, it isn't the only thing you've got, but it feels that way sometimes. PEDRO DA COSTA But you got the actual, we're all gonna be dead soon, you got the joy of having created. You know, the credit we got on, I've talked to Jorgen Schmidhuber, right? The Turing Award given to three people for deep learning, and you could say that a lot of other people should be on that list. It's the Nobel Prize question. Yeah, it's sad. It's sad, and people like talking about it, but I feel like in the long arc of history, the only person who will be remembered is Einstein, Hitler, maybe Elon Musk. And the rest of us are just like… DAVE Well, you know, someone asked me about immortality once, and I said, and I stole this from somebody else, I don't remember who, but it was, you know, I asked him, what's your great-grandfather's name? Any of them. Of course, they don't know. Most of us do not know. I mean, I'm not entirely sure. I know my grandparents, all my grandparents' names. I know what I called them, right? I don't know their middle names, for example. It's in living memory, so I could find out. Actually, my grandfather didn't know when he was born. I had no idea how old he was, right? But I definitely don't know who any of my great-grandparents are. So in some sense, immortality is doing something, preferably positive, so that your great-grandchildren know who you are, right? And that's kind of what you can hope for, which is very depressing in some ways. I could turn it into something uplifting if you need me to, but it's… DAVE Yeah, can you do the work here? DAVE Yeah, it's simple, right? It doesn't matter. I don't have to know who my great-grandfather was to know that I wouldn't be here without him. And I don't know who my great-grandchildren are, certainly who my great-great-grandchildren are, and I'll probably never meet them, although I would very much like to. But hopefully I'll set the world in motion in such a way that their lives will be better than they would have been if I hadn't done that. Well, certainly, they wouldn't have existed if I hadn't done the things that I did. So I think that's a good, positive thing. You live on through other people. PW Are you afraid of death? DAVE I don't know if I'm afraid of death, but I don't like it. PW That's another t-shirt. I mean, do you ponder it? Do you think about the… DAVE Yes, the inevitability of oblivion? I do occasionally. This feels like a very Russian conversation, actually. I will tell you a story, something that happened to me. If you look very carefully, you will see I have a scar. Which, by the way, is an interesting story of its own about why people have half of their thyroid taken out. Some people get scars and some don't. But anyway, I had half my thyroid taken out. The way I got there, by the way, is its own interesting story, but I won't go into it. Just suffice it to say I did what I keep telling people you should never do, which is never go to the doctor unless you have to, because there's nothing good that's ever going to come out of a doctor's visit, right? So I went to the doctor to look at one thing. It's a little bump I had on the side that I thought might be something bad because my mother made me. And I went there and he's like, oh, it's nothing. But by the way, your thyroid is huge. Can you breathe? Yes, I can breathe. Are you sure? Because it's pushing on your windpipe. You should be dead. Ah! Right? So I ended up going there. And to look at my thyroid, it was growing. I have what's called a goiter. And he said, we're going to have to take it out at some point. When? Sometime before you're 85, probably. But if you wait until you're 85, that'll be really bad, because you don't want to have surgery when you're 85 years old, if you can help it. Certainly not the kind of surgery it takes to take out your thyroid. So I went there and we decided, I would decide I'd put it off until December 19th, because my birthday is December 18th. And I wanted to be able to say I made it to 49 or whatever. So I said, I'll wait till after my birthday. In the first six months of that, nothing changed. Apparently in the next three months, it had grown. I hadn't noticed this at all. I went and had surgery. They took out half of it. The other half is still there and working fine, by the way. I don't have to take a pill or anything like that. It's great. I'm in the hospital room and the doctor comes in. I've got these things in my arm. They're going to do whatever. They're talking to me. And the anesthesiologist says, huh, your blood pressure's through the roof. Do you have high blood pressure? I said, no, but I'm terrified if that helps you at all. And the anesthesist, who's the nurse who supports the anesthesiologist, if I got that right, said, oh, don't worry about it. I just put some stuff in your IV. You're going to be feeling pretty good in a couple of minutes. And I remember turning and saying, well, I'm going to feel pretty good in a couple of minutes. Next thing I know, there's this guy and he's moving my bed. And he's talking to me. I have this distinct impression that I've met this guy and I should know what he's talking about, but I kind of like just don't remember what just happened. And I look up and I see the tiles going by and I'm like, oh, it's just like in the movies where you see the tiles go by. And then I have this brief thought that I'm in an infinitely long warehouse and there's someone sitting next to me. And I remember thinking, oh, she's not talking to me. And then I'm back in the hospital bed. And in between the time where the tiles were going by and I got in the hospital bed, something like five hours had passed. Apparently it had grown so much that it was a four and a half hour procedure instead of an hour long procedure. I lost a neck size and a half. It was pretty big. Apparently it was as big as my heart. Why am I telling you this? I'm telling you this because- That's a hell of a story already. Between tiles going by and me waking up in my hospital bed, no time passed. There was no sensation of time passing. When I go to sleep and I wake up in the morning, I have this feeling that time has passed. I have this feeling that something has physically changed about me. Nothing happened between the time they put the magic juice in me and the time that I woke up. Nothing. By the way, my wife was there with me talking. Apparently I was also talking. I don't remember any of this, but luckily I didn't say anything I wouldn't normally say. My memory of it is I would talk to her and she would teleport around the room. Then I accused her of witchcraft and that was the end of that. Her point of view is I would start talking and then I would fall asleep and then I would wake up and leave off where I was before. I had no notion of any time passing. I kind of imagine that that's death, is the lack of sensation of time passing. On the one hand, I am soothed by the idea that I won't notice. On the other hand, I'm very unhappy at the idea that I won't notice. I don't know if I'm afraid of death, but I'm completely sure that I don't like it and that I particularly would prefer to discover on my own whether immortality sucks and be able to make a decision about it. That's what I would prefer. P1 You'd like to have a choice in the matter. M1 I would like to have a choice in the matter. P1 Well, again, on the Russian thing, I think the finiteness of it is the thing that gives it a little flavor, a little spice. M1 Well, in reinforcement learning, we believe that. That's why we have discount factors. Otherwise, it doesn't matter what you do. P1 Amen. Well, let me, one last question, sticking on the Russian theme. You P1 talked about your great-grandparents not remembering their name. What do you think is the, in this kind of Markov chain that is life, what do you think is the meaning of it all? M1 What's the meaning of life? M2 Well, in a world where eventually you won't know who your great-grandchildren are, I am reminded of something I heard once, or I read once that I really like, which is, it is well worth remembering that the entire universe, save for one trifling exception, is composed entirely of others. I think that's the meaning of life. P1 Charles, this was one of the best conversations I've ever had, and I get to see you tomorrow again to hang out with who looks to be one of the most, how should I say, interesting personalities that I'll ever get to meet with Michael Lipman. So, I can't wait. I'm excited to have had this opportunity. Thank you for traveling all the way here. It was amazing. I'm excited. I always love Georgia Tech. I'm excited to see with you being involved there what the future holds. So, thank you for talking today. M2 Thank you for having me. I enjoyed every minute of it. P1 Thanks for listening to this conversation with Charles Isbell, and thank you to our sponsors, Neuro, the maker of functional sugar-free gum and mints that I use to give my brain a quick caffeine boost, Decoding Digital, a podcast on tech and entrepreneurship that I listen to and enjoy, Masterclass, online courses that I watch from some of the most amazing humans in history, and Cash App, the app I use to send money to friends for food and drinks. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with 5 Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some poetic words from Martin Luther King Jr. There comes a time when people get tired of being pushed out of the glittering sunlight of life's July and left standing amid the piercing chill of an alpine November. Thank you for listening and hope to see you next time.

https://youtu.be/LAyZ8IYfGxQ

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Avi Loeb: Aliens, Black Holes, and the Mystery of the Oumuamua | Lex Fridman Podcast #154

The following is a conversation with Avi Loeb, an astrophysicist, astronomer, and cosmologist at Harvard. He has authored over 800 papers and written eight books, including his latest called Extraterrestrial, the First Sign of Intelligent Life Beyond Earth. It'll be released in a couple of weeks, so go pre-order it now to show support for what I think is truly an important book in that it serves as a strong example of a scientist being both rigorous and open-minded about the question of intelligent alien civilizations in our universe. Quick mention of our sponsors, Zero Fasting App for intermittent fasting, Element Electrolyte Drink, Sun Basket Meal Delivery Service, and Pessimist Archive History Podcast. So the choices, a fasting app, fasting fuel, fast-breaking delicious meals, and a history podcast that has very little to do with fasting. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. As a side note, let me say a bit more about why Avi's work is so exciting to me and I think to a lot of people. In 2017, a strange interstellar object, now named a muamua, it's fun to say, was detected traveling through our solar system. Based on the evidence we have, it has strange characteristics which made it not like any asteroid or comet that we've seen before. Avi was one of the only world-class scientists who fearlessly suggested that we should be open-minded about whether it is naturally made or in fact is an artifact of an intelligent alien civilization. In fact, he suggested that the more likely explanation, given the evidence, is the latter hypothesis. We also talk about a lot of fascinating mysteries in our universe, including black holes, dark matter, the Big Bang, and close to speed of light space travel. The theme throughout is that in scientific pursuits, the weird things, the anomalies, the ideas that right now are considered taboo should not be ignored if we're to have a chance at finding the next big breakthrough, the next big paradigm shift, and also if we are to inspire the world with the power and beauty of science. If you enjoy this thing, subscribe on YouTube, review on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Avi Loeb. In the introduction to your new book, Extraterrestrial, you write, this book confronts one of the universe's most profound questions, are we alone? Over time, this question has been framed in different ways. Is life here on Earth the only life in the universe? Are humans the only sentient intelligence in the vastness of space and time? A better, more precise framing of this question would be this, throughout the expanse of space and over the lifetime of the universe, are there now or have ever been other sentient civilizations that, like ours, explored the stars and left evidence of their efforts? So let me ask, are we alone? That's an excellent question. For me, the answer is sort of clear because I start from the principle of modesty. You know, if we believe that we are alone and special and unique, that shows arrogance. My daughters, when they were infants, they tended to think that they are special, unique, and then they went out to the street and realized that other kids are very much like them, and then they developed a sense of, a better perspective about themselves. And I think the only reason that we are still thinking that we are special is because we haven't searched well enough to find others that might even be better than us. And, you know, I say that because I look at the newspaper every morning and I see that we do foolish things. We are not necessarily the most intelligent ones. And if you think about it, if you open a recipe book, you see that out of the same ingredients, you can make very different cakes, depending on how you put them together and how you heat them up. And what is the chance that by taking the soup of chemicals that existed on Earth and cooking it one way to get our life, that you got the best cake possible? I mean, we are probably not the sharpest cookie in the jar. And my question is, I mean, it's pretty obvious to me that we are probably not alone because half of all the sun-like stars we know now as astronomers, half of the sun-like stars from the Kepler satellite data have a planet the size of the Earth, roughly at the same distance that the Earth is from the sun. And that means that they can have liquid water on their surface and the chemistry of life as we know it. So if you roll the dice billions of times just within the Milky Way galaxy, and then you have tens of billions of galaxies like it within the observable volume of the universe, it would be extremely arrogant to think that we are special. I would think that we are sort of middle of the road, typical forms of life. And that's why nobody pays attention to us. If you go down the street on a sidewalk and you see an ant, you don't pay attention or a special respect to that ant, you just continue to walk. And so I think that we are sort of average, not very interesting, not exciting, so nobody cares about us. We tend to think that we are special, but that's a sign of immaturity. And we're very early on in our development. Yes, that's another thing that we have our technology only for 100 years, and it's evolving exponentially right now on a three-year timescale. So imagine what would happen in 100 years, in 1,000 years, in a million years, or in a billion years. Now the sun is actually relatively late in the star formation history of the universe. Most of the sun-like stars formed earlier. And some of them already died, became white dwarfs. And so if you imagine that a civilization like ours existed around a typical sun-like star, by now, if they survived, they could be a billion years old. And then imagine a billion-year technology. It would look like magic to us, an approximation to God. We wouldn't be able to understand it. And so in my view, we should be humble. And by the way, we should probably just listen and not speak because there is a risk, right? If you are inferior, there is a risk. If you speak too loudly, something bad may happen to you. You mentioned we should be humble also in the sense with the analogy to ants, that they might be better than us. So there's a kind of scale that we're talking about. And in the question, you mentioned the word sentient. So sentience, or maybe the more basic formulation of that is consciousness. Do you think that this thing within us humans in terms of the typical life form of consciousness is the essential element that permeates, if there's other alien civilizations out there, that they have something like consciousness as well? Or is this, I guess I'm asking, can you try to untangle the word sentient? Yeah, so that's a good question. I think what is most abundant, depending on how long it survives. So if you look at us as an example, we are now, we do have conscious and we do have technology. But the technologies that we are developing are also means for our own destruction, as we can tell. You know, we can change the climate if we are not careful enough. We can go into nuclear wars. So we are developing means for our own destruction through self-inflicted wounds. And it might well be that creatures like us are not long-lived, that the crocodiles on other planets live for billions of years. They don't destroy themselves, they live naturally. And so if you look around, the most common thing would be dumb animals that live for long times, not those that have conscious. But in terms of changing the environment, I think since, I mean, humans develop tools, they develop the ability to construct technologies that would lift us from this planet that we were born in. And that's something animals without a consciousness cannot really do. And so in terms of looking for things that went beyond the circumstances they were born into, I would think that even if they're short-lived, these are the creatures that made the biggest difference to their environment, and we can search for them. Even if they're short-lived, and most of the civilizations are dead by now. Yeah. Even if that's the case. That's sad to think about, by the way. Well, but if you look on Earth, there are lots of cultures that existed throughout time and they're dead by now. The Mayan culture was very sophisticated, died, but we can find evidence for it and learn about it just by archeology, digging into the ground, looking. And so we can do the same thing in space. Look for dead civilizations, and perhaps we can learn a lesson why they died and behave better so that we will not share the same fate. So I think there is a lesson to be learned from the sky. And by the way, I should also say, if we find a technology that we have not dreamed of, that we can import to Earth, that may be a better strategy for making a fortune than going to Silicon Valley or going to Wall Street. Yeah. Because you make a jump start into something of the future. So that's one way to do the leap, is actually to find, to literally discover versus come up with the idea in our own limited human capacity, like a cognitive capacity. It would look, it would feel like cheating in an exam where you look over the shoulder of a student next to you. Yeah. But. It's not good on an exam, but it is good when you're coming up with technology that could change the fabric of human civilization. But there is, you know, in my neck of the woods of artificial intelligence, there's a lot of trajectories one can imagine of creating very powerful beings, the technology that's essentially, you know, you can call super intelligence, that could achieve space exploration, all those kinds of things, without consciousness. Right. Without something that to us humans looks like consciousness. And there, you know, there is a sad feeling I have that consciousness too, in terms of us being humble, is a thing we humans take too seriously. That we think it's special just because we have it. But it could be a thing that's actually holding us back in some kind of way. May well be. May well be. I should say something about AI, because I do think it offers a very important step into the future. If you look at the Old Testament, the Bible, there is this story about Noah's Ark that you might know about. Yes. Noah's Ark knew about a great flood that is about to endanger all life on earth. So he decided to build an ark. And the Bible actually talks about specifically what the size of this ark was, what the dimensions were. Turns out it was quite similar to Umuamua that we will discuss in a few minutes. But at any event, he built this ark and he put animals on it so that they were saved from the great flood. Now you can think about doing the same on earth because there are risks for future catastrophes. We could have the self-inflicted wounds that we were talking about, like nuclear war, changing the climate, or there could be an asteroid impacting us, just like the dinosaurs died. The dinosaurs didn't have science, astronomy. They couldn't have a warning system. But there was this big stone, big rock that approached it. It must have been a beautiful sight. Just when it was approaching, got very big and then smashed them, okay, killed them. So you could have a catastrophe like that, or in a billion years, the sun will basically boil off all the oceans on earth. And currently all our eggs are in one basket, but we can spread them. It's sort of like the printing press, if you think about it. The revolution that Gutenberg brought is there were very few copies of the Bible at the time, and each of them was precious because it was handwritten. But once the printing press produced multiple copies, if something bad happened to one of the copies, it wasn't a catastrophe, it wasn't disaster because you had many more copies. And so if we have copies of life here on earth elsewhere, then we avoid the risk of it being eliminated by a single point breakdown, catastrophe. So the question is, can we build NOAA's spaceship that will carry life as we know it? Now, you might think we have to put elephants and whales and birds on a big spaceship, but that's not true because all you need to know is the DNA making, the genetic making of these animals, put it on a computer system that has AI plus a 3D printer, so that this CubeSat, which is rather small, can go with this information to another planet and use the raw materials there to produce synthetic life. And that would be a way of producing copies, just like the Gutenberg printing press. Yeah, and it doesn't have to be exact copies of the humans, it could just contain some basic elements of life and then have enough life on board that it could reproduce the process of evolution on another place. So I mean, that also makes you sad, of course, because you confront the mortality of your own little precious consciousness and all your own memories and knowledge and all that stuff. That's right, but who cares? I mean, we are not so significant. I care about mine, right, and you care about yours. No, no, I actually don't. You know, if you look at the bigs, if you are an astronomer, one thing that you learn from the universe is to be modest, because you are not so significant. Oh, boy. I mean, think about it, all these emperors and kings that conquered a piece of land on Earth and were extremely proud, you know, you see these images of kings and emperors that, you know, usually are alpha males, and they stand, you know, strong, and they're very proud of themselves, but if you think about it, there are 10 to the power 20 planets like the Earth in the observable volume of the universe, and this view of conquering a piece of land, and even conquering all of Earth, is just like an ant hugging a single grain of sand on the landscape of a huge beach. That's not very impressive. So you can't be arrogant. If you see the big picture, you have to be humble, you know, also we are short-lived, you know, within 100 years, that's it, right? So what does it teach you? First, to be humble, modest. You never have significant powers relative to the big scheme of things. And second, you should appreciate every day that you live. Yes. And learn about the world. Humble and still grateful. Yes, exactly. Well, let's talk about probably the most interesting object I've heard about, and also the most fun to pronounce. Oumuamua, yes. Oumuamua. Can you tell me the story of this object and why it may be an important event in human history? And is it possibly a piece of alien technology? Right, so this is the first object that was spotted close to Earth from outside the solar system. And it was found on October 19th, 2017. And at that time, it was receding away from us. And at first, astronomers thought it must be a piece of rock, you know, just like all the asteroids and comets that we have seen from within the solar system. And it just came from another star. I should say that the actual discovery of this object was surprising to me because a decade earlier, I wrote the first paper together with Ed Turner and Amaya Moro-Martin that tried to predict whether the same telescope that was surveying the sky, Pan-STARRS, from Hawaii, would find anything from interstellar space given what we know about the solar system. So if you assume that other planetary systems have similar abundance of rocks, and you just calculate how many should be ejected into interstellar space, the conclusion is no. We shouldn't find anything with Pan-STARRS. To me, I apologize, probably revealing my stupidity, but it was surprising to me that so few interstellar objects from outside the solar system have ever been detected. Or none. None. None has been. You do, well, maybe talk about it, that there has been one or two rocks since then. Well, since then, there was one called the Borisov. It was discovered by an amateur Russian astronomer, Gennady Borisov, and that one looked like a comet. Yep. And just like a comet from within the solar system. But this is a really important point, and sorry to interrupt it. You showed that it's unlikely that a rock from another solar system would arrive to ours. Right, and so the actual detection of this one was surprising by itself, to me. Yes. But then, so at first they thought maybe it's a comet or an asteroid, but then it didn't look like anything we've seen before. Borisov did look like a comet, so people asked me afterwards and said, you know, doesn't it convince you if Borisov looks like a comet, doesn't it convince you that Oumuamua is also natural? Yeah. And I said, you know, when I went on the first date with my wife, she looked special to me, and since then I met many women, that didn't change my opinion of my wife. So, you know, that's not an argument. Anyway, so why did Oumuamua look weird? Let me explain. So first of all, astronomers monitored the amount of light, sunlight, that it reflects. And it was tumbling, spinning, every eight hours. And as it was spinning, the brightness that we saw from that direction, we couldn't resolve it because it's tiny, it's about 100 meters, a few hundred feet, size of a football field. And we cannot, from Earth, with existing telescopes, we cannot resolve it. The only way to actually get a photograph of it is to send a camera close to it. And that was not possible at the time that Oumuamua was discovered because it was already moving away from us faster than any rocket we can send. It's sort of like a guest that appeared for dinner, and then by the time we realized that it's weird, the guest is already out the front door into the dark street. What we would like to find is an object like it approaching us, because then you can send the camera, irrespective of how fast it moves. And if we were to find it in July 2017, that would have been possible because it was approaching us at that time. Actually, I was visiting Mount Haleakala in Maui, Hawaii, with my family for vacation at that time, in July 2017, but nobody knew at the observatory that Oumuamua is very close. That's sad to think about, that we had the opportunity at that time to send up a camera. But don't worry, I mean, there will be more. There will be more because I operate by the Copernican principle, which says we don't live at a special place and we don't live at a special time. And that means if we survey the sky for a few years and we had sensitivity to this region between us and the sun, and we found this object with Pan-STARRS, you know, there should be many more that we will find in the future with surveys that might be even better. And actually, in three years' timescale, there would be the so-called LSST, that's a survey of the Vera Rubin Observatory, that would be much more sensitive and could potentially find an Oumuamua-like object every month. Okay, so I'm just waiting for that. And the main reason for me to alert everyone to the unusual properties of Oumuamua is with the hope that next time around when we see something as unusual, we would take a photograph or we would get as much evidence as possible because science is based on evidence, not on prejudice. And we will get back to that theme. So anyway, let me point out what is- Some of the properties, actually. Yeah, the elongated nature, all of those kinds of things. So the amount of light, sunlight, that was reflected from it was changing over eight hours by a factor of 10, meaning that the area of this object, even though we can't resolve it, the area on the sky that reflects sunlight was bigger by a factor of 10 in some phases as it was tumbling around than in other phases. So even if you take a piece of paper that is razor thin, there is a very small likelihood that it's exactly edge on. And getting a factor of 10 change in the area that you see on the sky is huge. It's much more than any- It means that the object has an unusual geometry. It's at least a factor of a few more than any of the comets or asteroids that we have seen before. You mentioned reflectivity, so it's not just the geometry, but the properties of the surface of that thing. Well- Or no. If you assume the reflectivity is the same, then it's just geometry. If you assume the reflectivity may change, then it could be a combination of the area that you see and the reflectivity, because different directions may reflect differently. But the point is that it's very extreme. And actually, the best fit to the light curve that we saw was of a flat object, unlike all the cartoons that you have seen of a cigar shape. A flat object at the 90% confidence gives a better model for the way that the light varied. And it's also- So it's like flat, meaning like a pancake. Like a pancake, exactly. And so that's the very first unusual property. But to me, it was not unusual enough to think that it might be artificial. It was not significant enough. Then there was no cometary tail, no dust, no gas around this object. And the Spitzer Space Telescope really searched very deeply for carbon-based molecules. There was nothing. So it's definitely not a comet, the way people expected it to be. Can you maybe briefly mention what properties a comet that you're referring to usually has? Right, so a comet is a rock that has some water ice on the surface. So you can think of it as an icy rock. Actually, comets were discovered a long time ago, but the first model that was developed for them was by Fred Wippel, who was at Harvard. And I think the legend goes that he got the idea from walking through Harvard Square and seeing, during a winter day, and seeing these icy rocks. So a comet is icy, and an asteroid is not. It's just a rock. It's just a rock. Yeah, so when you have ice on the surface, when the rock gets close to the sun, the sunlight warms it up, and the ice sublimates, evaporates. Because the one thing about ice, water ice, is it doesn't become liquid if you warm it up in vacuum, without an external pressure. It just goes straight into gas. And that's what you see as the tail of a comet. The only way to get liquid water is to have an atmosphere like on Earth that has an external pressure. Only then you get liquid. And that's why it's essential to have an atmosphere to a planet in order to have liquid water and the chemistry of life. So if you look at Mars, Mars lost its atmosphere, and therefore, no liquid water on the surface anymore. I mean, there may have been early, and that's what the Perseverance survey, the Perseverance mission will try to find out whether it had liquid water, whether there was life perhaps on it at the time. But at some point, it lost its atmosphere, and then the liquid water was gone. So the only reason that we can live on Earth is because of the atmosphere. But a comet is in vacuum, pretty much. And when it gets warmed up on the surface, the water becomes, the water ice becomes gas, and then you see this cometary tail behind it. In addition to water, there are all kinds of carbon-based molecules, so dust, that comes off the surface. And those are detectable. Yeah, it's easy to detect. It's very prominent. You see these cometary tails that look very prominent because they reflect sunlight, and you can see them. In fact, it's sometimes difficult to see the nucleus of the comet because it's surrounded and shrouded with, and in this case, there was no trace of anything. That's fascinating. Now, you might say, okay, it's not a comet. So that's what the community said. Okay, it's not a, no problem, it's still a rock. You know, it's not a comet, but it's just a rock, bare rock, you know, okay, no problem. Then, and that's the thing that convinced me to write about it, and then in June 2018, you know, significantly later, there was a report that in fact the object exhibited an excess push in addition to the force of gravity. So the sun acts on it by gravity, but then there was an extra push on this object that was figured out from the orbit that you can trace. And the question was, what is this excess push? So for comets, you get the rocket effect. When you evaporate gas, you know, just like a jet engine on an airplane, you throw, a jet engine is very simple. You throw the gas back, and it pushes the airplane forward. That's all, that's how it, so in a case of a comet, you throw gas in the direction of the sun because it, and then you get a push, okay? So in the case of comets, you can get a push, but there was no cometary tail. So then people said, oh, wait a second, is it an asteroid? No, but it behaves like a comet, but it doesn't look like a comet, so what, well, forget about it, business as usual. So that's what they mean by non-gravitational acceleration. So that's interesting, so like the primary force acting on something like just a rock, like an asteroid, would be, like you can predict the trajectory based on the, based on gravity, and so here there's detected movement that's not, cannot be accounted purely by the gravity of the sun. If it was a comet, you would need about a tenth of the mass of this comet, the weight of this comet, to be evaporated in order to give it. And there was no sign of that. No sign, 10% of the mass evaporating, it's huge. Think about it, a hundred meter size object losing 10% of its mass, you can't miss that. And the, never the, it's super weird. What, is there a good, is there in your mind a possible explanation for this? You know, so I operated just like Sherlock Holmes in a way. I said, okay, what are the possibilities? And the only thing I could think, so I ruled out everything else, and I said it must be the sunlight reflected off it, okay? So the sunlight reflects off the surface and gives it a push, just like you get a push on a sail on a boat, you know, from the wind reflecting off it. Now, in order for this to be effective, it turns out the object needs to be extremely thin. It turns out it needs to be less than a millimeter thick. Nature does not produce such things. So, but, we produce it because it's called the technology of a light sail. So we are, for space exploration, we are exploring this technology because it has the benefit of not needing to carry the fuel with the spacecraft. So you don't have the fuel, you just have a sail, and it's being pushed either by sunlight or by a laser beam or whatever. So perhaps this is a light sail. So this is actually the same technology with the Starshot project. Yes, so, you know, people afterwards say, okay, you work on this project, you imagine, you know. No, that's a pretty good explanation, right? Obviously my imagination is limited by what I know. So I would not deny that working on light sails expanded my ability to imagine this possibility. But let me offer another interesting anecdote. In September this year, 2020, I mean, 2020, there was another object found, and it was given the name 2020SO by the Minor Planet Center. This is an organization actually in Cambridge, Massachusetts that gives names to objects, astronomical objects found in the solar system. And they gave it that name, 2020SO, because it looked like an object in the solar system, and it moved in an orbit that is similar to the orbit of the Earth, but not the same exactly. And therefore it was bound to the sun, but it also exhibited a deviation from what you expect based on gravity. So astronomers that found it extrapolated back in time and found that in 1966, it intercepted the Earth. And then they realized, they went to the history books, and they realized, oh, there was a mission called Lunar Surveyor, Lunar Lander, Surveyor 2, that had a rocket booster. It was a failed mission, but there was a rocket booster that was kicked into space. And presumably this is the rocket booster that we are seeing. Now, this rocket booster was sufficiently hollow and thin for us to recognize that it's pushed by sunlight. So here is my point. We can tell from the orbit of an object, obviously this object didn't have any cometary tail, it was artificially made. We know that it was made by us, and it did deviate from an orbit of a rock. So just by seeing something that doesn't have cometary tail and deviates from an orbit shaped by gravity, we can tell that it's artificial. In the case of Oumuamua, it couldn't have been sent by humans because it just passed near us for a few months. We know exactly what we were doing at that time. And also it was moving faster than any object that we can launch. And so obviously it came from outside the solar system. And the question is, who produced it? Now, I should say that when I walk on vacation on the beach, I often see natural objects like seashells that are beautiful and I look at them. And every now and then I stumble on a plastic bottle and that was artificially produced. And my point is that maybe Oumuamua was a message in a bottle. And this is simply another window into searching for artifacts from other civilizations. Where do you think it could have come from? And if it's, so, okay. From a scientific perspective, the narrow-minded view, as we'll probably talk about throughout, is you kinda wanna stick to the things that are naturally originating objects like asteroids and comets. Okay, that's the space of possible hypotheses. And then if we expand beyond that, you start to think, okay, these are artificially constructed. And like you just said, it could be by humans. It could be by whatever that means by some kind of extraterrestrial alien civilizations. If it's the alien civilization variety, what is this object then that we're looking at? An excellent question. And let me lay out, I mean, we don't have enough evidence to tell. If we had a photograph, perhaps we would have more information. But there is one other peculiar fact about Oumuamua. Well, other than it was very shiny, that I didn't mention, we didn't detect any heat from it. And that implies that it's rather small and shiny. But the other peculiar fact is that it came from a very special frame of reference. So it's sort of like finding a car in a parking lot, in a public parking lot, that you can't really tell where it came from. So there is this frame of reference where you average over the motions of all the stars in the neighborhood of the sun. So you find the so-called local standard of rest of the galaxy. And that's a frame of reference that is obtained by averaging the random motions of all the stars. And the sun is moving relative to that frame at some speed. But this object was at rest in that frame. And only one in 500 stars is so much at rest in that frame. And that's why I was saying, it's like a parking lot. It was parked there and we bumped into it. So the relative speed between the solar system and this object is just because we are moving. It was sitting still. Now you ask yourself, why is it so unusual in that context? You know why? Because if it was expelled from another planetary system, most likely it will carry the speed of the host star that it came from. Because the most loosely bound objects are in the periphery of the planetary system. And they move very slowly relative to the star. And so they carry, when they are ripped apart from the planetary system, most of the objects will have the residual motion of the star, roughly, relative to the local star. But this one was at rest in the local. Now, one thing I can think of, if there is a grid of road posts, you know, like for navigation system, so that you can find your way in the local frame, then that would be one possibility. These are like little sensors of, that's fascinating to think about. So there could be, I mean, not necessarily, literally a grid, but just evenly, in some definition of evenly spread out set of objects like these that are just out there. A lot of them. Another possibility is that these are relay stations, you know, for communication. You might think in order to communicate, you need a huge beacon, a very powerful beacon. But it's not true, even on Earth, you know, we have these relay stations. So you have a not so powerful beacon. So it can be heard only out to a limited distance. But then you relay the message. And it could be one of those. Now, after it collided with the solar system, of course, it got a kick. So it's just like a billiard ball, you know, we gave it a kick by colliding with, but most of them are not colliding with stars. So that's one possibility, okay? And there should be lots of them, if that's the case. The other possibility is that it's a probe, you know, that was sent in the direction of the habitable region around the sun to find out if there is life. Now, it takes tens of thousands of years for such a probe to traverse the solar system from the outer edge of the Oort cloud all the way to where we are. And, you know, it's a long journey. So when it started the journey from the edge of the solar system to get to us now, you know, we were rather primitive back then, you know, we still didn't have any technology, there was no reason to visit, you know, there was grass around and so forth. But, you know, maybe it is a probe. So you said 10,000 years, that's fastest. So it takes that long. Tens of thousands, yes. Tens of thousands of years. Yeah, and the other thing I should say is, you know, it could be just an outer layer of something else, like, you know, something that was ripped apart, like a surface of an instrument that was, and you can have lots of these pieces, you know, if something breaks, lots of these pieces spread out, like space junk. And, you know, that. It could be just space junk from an alien civilization. Yes. So it's kind of. I can tell you about space junk, let me. Yes, what do you mean by space junk? So I think, you know, you might ask, why aren't they looking for us? One possibility is that we are not interesting, like we were talking about. Yeah, the ants hypothesis. Another possibility, you know, if there are millions or billions of years into their technological development, they created their own habitat, their own cocoon, where they feel comfortable, they have everything they need, and it's risky for them to establish communication with other. So they have their own cocoon and they close off. They don't care about anything else. Now, in that case, you might say, oh, so how can we find about them if they are closed off? The answer is they still have to deposit trash, right? That is something from the law of thermodynamics. There must be some production of trash. And, you know, we can still find about them just like investigative journalists going through the trash cans of celebrities in Hollywood. You can learn about the private lives of those celebrities by looking at the trash. It's fascinating to think, you know, if we are the ants in this picture, if this thing is a water bottle, or if it's like a smartphone, like where on the spectrum of possible objects of space, because there's a lot of interesting trash. Right. So like, how interesting is this trash? But imagine a caveman seeing a cell phone. The caveman would think, since the caveman played with rocks all of his life, he would say, it's a rock, just like my fellow astronomers said. Yes, yes, exactly. That's brilliantly put. Actually, as a scientist, do you hope it's a water bottle or a smartphone? A smartphone. I hope it's even more than a smartphone. I hope that it's something that is really sophisticated. That's funny. See, I'm the opposite. I feel like I hope it's a water bottle because at least we have a hope with our current set of skills to understand it. Yeah, but- A caveman has no way of understanding the smartphone. It's like, it will be, like, I feel like a caveman has more to learn from the plastic water bottle than they do from the smartphone. But suppose we figure it out. If we, for example, come close to it and learn what it's made of. And I guess a smartphone is full of, like, thousands of different technologies that we could probably pick at. Do you have a sense of where, a hypothesis of where is the cocoon that it might have come from? No, because, okay, so first of all, you know, the solar system, the outermost edge of the solar system is called the Oort cloud. It's a cloud of icy rocks of different sizes that were left over from the formation of the solar system. And it's thought to be roughly a ball or a sphere. And it's halfway, the extent of it is roughly halfway to the nearest star, okay? So you can imagine each planetary system basically touching the Oort clouds of those stars that are near us are touching each other. Space is full of these billiard balls that are very densely packed. And what that means is any object that you see, irrespective of whether it came from the local standard. So we said that this object is special because it came from a local standard of rest. But even if it didn't, you would never be able to trace where it came from because all these Oort clouds overlap. So if you take some direction in the sky, you will cross as many stars as you have in that direction. Like there is no way to tell which Oort cloud it came from. So yes, I didn't realize how densely packed everything was from the perspective of the Oort cloud. And that's really interesting. So yeah, it could be nearby, it could be very far away. Yeah, we have no clue. You said cocoon. And you kind of paint, I think in the book, I've read a lot of your articles too on the Scientific American, which are brilliant. So I'm kind of mixing things up in my head a little bit. But there's, what does that cocoon look like? What does a civilization that's able to harness the power of multiple suns, for example, look like? When you imagine possible civilizations that are a million years more advanced than us, what do you think that actually looks like? I think it's very different than we can imagine. By the way, I should start from the point that even biological life, just without technology getting into the game, could look like something we have never seen before. Take, for example, the nearest star, which is Proxima Centauri. It's four and a quarter light years away. So they will know about the results of the 2016 elections only next month in February, 2021. It's very far away. But if you think about it, this star is a dwarf star, and it's much cooler than, it's twice as cold as the sun, okay? And it emits mostly infrared radiation. So if there are any creatures on the planet close to it that is habitable, which is called Proxima b, there is a planet in the habitable zone, in the zone just at the right distance where in principle liquid water can be on the surface. If there are any animals there, they have infrared eyes because our eyes was designed to be sensitive to where most of the sunlight is in the visible range. But Proxima Centauri emits mostly infrared. So, you know, the nearest- Who's not able to see each other? In the nearest star system, these animals would be quite strange. They would have eyes that are detectors of infrared, very different from ours. Moreover, this planet, Proxima b, faces the star always with the same side. So it has a permanent day side and a permanent night side. And obviously the creatures that would evolve on the permanent day side, which is much warmer, would be quite different than those on the permanent night side. Between them, there would be a permanent sunset strip. And my daughters said that that's the best opportunity for high-value real estate because you will see the sunset throughout your life, right? The sun never sets on this strip. So, you know, these worlds are out of our imagination. So just even the individual creatures, the sensor suite that they're operating with might be very different. Very different. So I think when we see something like that, we would be shocked. Not to speak about seeing technology. Now, so I don't even dare to imagine, you know? And I think, you know, obviously we can bury our head in the sand and say it's never aliens, like many of my colleagues say. And it's a self-fulfilling prophecy. If you never look, you will never find. If you are not ready to find wonderful things, you will never discover them. And the other thing I would like to say is reality doesn't care whether you ignore it or not. You can ignore reality, but it's still there. So we can all agree based on Twitter that aliens don't exist. That Oumuamua was a rock. We can all agree. And you will get a lot of likes. We will have a big crowd of supporters and everyone will be happy and give each other awards and honors and so forth. But Oumuamua might still be an alien artifact. Who cares what humans agree on? There is a reality out there and we have to be modest enough to recognize that we should make our statements based on evidence. Science is not about ourself. It's not about glorifying our image. It's not about getting honors, prizes. You know, a lot of the scientific, a lot of the academic activity is geared towards creating your echo chamber where you have students, postdocs repeating your mantras so that your voice is heard loudly, so that you can get more honors, prizes, recognition. That's not the purpose of science. The purpose is to figure out what nature is, right? And in the process of doing that, it's a learning experience. You make mistakes. You know, Einstein made three mistakes at the end of his career. He argued that in the 1930s, he argued that black holes don't exist, gravitational waves don't exist, and quantum mechanics doesn't have spooky action at a distance. And all three turned out to be wrong, okay? So the point is that if you work at the frontier, then you make mistakes. It's inevitable because you can't tell what is true or not. And avoiding making mistakes in order to preserve your image makes you extremely boring, okay? You will get a prize, but you will be a boring scientist because you will keep repeating things we already know. If you want to make progress, if you want to innovate, you have to take risks and you have to look at the evidence. It's a dialogue with nature. You don't know the truth in advance. You let nature tell you, educate you, and then you realize that what you thought before is incorrect. And a lot of my colleagues prefer to be in a state where they have a monologue. You know, if you look at these people that work on string theory, they have a monologue. They know what, and in fact, their monologue is centered on anti-de Sitter space, which we don't live in. Now, you know, to me, it's just like the Olympics. You know, you define 100 meters and you say, whoever runs this 100 meters is the best athlete, the fastest, you know? And it's completely arbitrary. You could have decided it would be 50 meters or 20 meters. Who cares? You just measure the ability of people this way. So you define anti-de Sitter space as a space where you do your mathematical gymnastics, and then you find who can do it the best, and you give jobs based on that, you give prizes based. But as we said before, you know, nature doesn't care about, you know, the prizes that you give to each other. It cares, you know, it has its own reality, and we should figure it out, and it's not about us. The scientific activity is about figuring out nature. And sometimes we may be wrong, our image will not be preserved, but that's the fun. You know, kids explore the world out of curiosity. And I always want to maintain my childhood curiosity, and I don't care about the labels that I have. In fact, having tenure is exactly the opportunity to behave like a child because you can make mistakes. And I was asked by the Harvard Gazette, you know, the Pravda of Harvard, what is the one thing that you would like to change about the world? And I said, I would like my colleagues to behave more like kids. That's the one thing I would like them to do because something bad happens to these kids when they become tenured professors. They start to worry about their ego and about themselves more than about the purpose of science, which is, you know, curiosity-driven, figuring out from evidence. Evidence is the key. So when an object shows anomalies, like Oumuamua, what's the problem discussing, you know, whether it's artificial or not? You know, so there was, I should tell you, there was a mainstream paper in Nature published saying it must be natural. That's it. It's unusual, but it must be natural, period. And then at the same time, those main, some other mainstream scientists tried to explain the properties. And they came up with interpretations like, it's a dust bunny, you know, the kind that you find in a household, a collection of dust particles pushed by sunlight. Something we have never seen before. Or it's a hydrogen iceberg. It actually evaporates like a comet, but hydrogen is transparent, you don't see it, and that's why we don't see the cometary tail. Again, we have never seen something like that. In both cases, the objects would not survive the long journey. We discussed it in a paper that I wrote afterwards. But my point is, those that tried to explain the unusual properties went into great length at discussing things that we have never seen before, okay? So even when you think about the natural origin, you have to come up with scenarios of things that were never seen before. And by the way, they look less plausible to me, personally. But my point is, if we discuss things that were never seen before, right, why not discuss, why not contemplate an artificial origin? What's the problem? Why do people have this pushback? You know, I worked on dark matter, and we don't know what most of the matter in the universe is. It's called dark matter. It's just an acronym because we have no clue. We simply don't know. So it could be all kinds of particles. And over the years, people suggested weakly interacting massive particles, axions, all kinds of particles. And experiments were made. They cost hundreds of millions of dollars. They put upper limits, constraints, that ruled out many of the possibilities that were proposed as natural initially. The mainstream community regarded it as a mainstream activity to search the nature of the dark matter. And nobody complained that it's speculative to consider weakly interacting massive particles. Now, I ask you, why is it speculative to consider extraterrestrial technologies? We have a proof that it exists here on Earth. We also know that the conditions of Earth are reproduced in billions of systems throughout the Milky Way galaxy. So what's more conservative than to say if you arrange for similar conditions, you get the same outcome? How can you imagine this to be speculative? It's not speculative at all. And nevertheless, it's regarded the periphery. And at the same time, you have physicists, theoretical physicists, working on extra dimensions, supersymmetry, superstring theory, the multiverse, maybe we live in a simulation, all of these ideas that have no grounding in reality, some of which sound to me like, you know, just like what someone would say. Science fiction, basically. Because you have no way to test it, you know, through experiments, and experiments really are key. It's not just the nuance. You say, okay, forget about experiment. As some philosophers try to say, you know, if there is a consensus, what's the problem? The point is, it's key, and that's what Galileo found. It's key to have feedback from reality. You know, you can think that you have a billion dollar, or that you are more rich than, you know, Elon Musk. That's fine, you can feel very happy about it. You can talk about it with your friends, and all of you will be happy, and think about what you can do with the money. Then you go to an ATM machine, and you make an experiment. You check how much money you have in your checking account. And if it turns out that, you know, you don't have much, you can't materialize your dreams. Okay, so you realize, you have a reality check. And my point is, without experiments, giving you a reality check, without the ATM machine showing you whether your ideas are bankrupt or not, without putting skin in the game, and by skin in the game, I mean, don't just talk about theoretical ideas. Make them testable. If you don't make them testable, they're worthless. They're just like theology that is not testable. By the way, theology has some tests. Let me give you three examples. Yes. It turns out that my book already inspired a PhD student at Harvard in the English department to pursue a PhD in that direction. And she invited me to the PhD exam a couple of months ago. And in the exam, one of the examiners, a professor, asked her, do you know why Giordano Bruno was burnt at the stake? And she said, no, I think it's because he was an obnoxious guy and irritated a lot of people. Which is true. But the professor said, no, it's because Giordano Bruno said that other stars are just like the sun, and they could have a planet like the Earth around them that could host life. And that was offensive to the church. Why was it offensive? Because there is the possibility that this life sinned. Okay, and if that life sinned on planets around other stars, it should have been saved by Christ. And then you need multiple copies of Christ. And that's unacceptable. How can you have duplicates of Christ? And so they burned the guy. So it was about, okay, I'm just loading this all in because that's kind of brilliant. So he was actually already, it's not just about the stars, it's anticipating that there could be other life forms. Like why, if this star, if there's other stars, why would it be special, why would our star be special? He was making the right argument. And he would just follow that all along to say like there should be other Earth-like places, there should be other life forms. And then there needs to be copies of Christ. Yeah, so that was offensive. So I said to that professor, I said, great, I wanted to introduce some scientific tone to the discussion. And I said, this is great because now you basically laid the foundation for an experimental test of this theology. What is the test? We now know that other stars are like the sun. And we know they have planets like the Earth around them. So suppose we find life there and we figure out that they sinned, then we ask them, did you witness Christ? And if they say no, it means that this theology is ruled out. So there is an experimental test. So this is experimental test number one. Another experimental test, you know, in the Bible, you know, in the Old Testament, Abraham heard a voice, the voice of God, to sacrifice his son, right, only son. And that's what the story says. Now suppose Abraham, my name, by the way, had a voice memo up on his cell phone. He could have pressed this up and recorded the voice of God. And that would have been experimental evidence that God exists, right? Fortunately, he didn't. But it's an experimental test, right? There is a third example I should tell. And that is Elie Wiesel attributed this story to Martin Buber. But it's not clear whether it's true or not. At any event, the story goes that Martin Buber, you know, he was a philosopher. And he said, you know, the Christians argue that Jesus, you know, the Messiah arrived already and will come back again in the future. The Jews argue the Messiah never came and will arrive in the future. So he said, why argue? Both sides agree that the Messiah will arrive in the future. When the Messiah arrives, we can ask whether he or she came before, you know, like visited us and then figure it out. And one side, so again, experimental test of a theology. So even theology, if it puts a skin in the game, you know, if it makes a prediction, could be tested, right? So why can't string theories test themselves? Or why can't, you know, even cosmic inflation, that's another model that, you know, one of the inventors from MIT, Alan Guth, argues that it's not falsifiable. My point is a theory that cannot be falsified is not helpful, because it means that you can't make progress. You cannot improve your understanding of nature, the only way for us to learn about nature is by making hypotheses that are testable, doing the experiments and learning whether we are correct or not. So be, and coupled that with a curiosity and open-mindedness that allows us to explore all kinds of possible hypotheses, but always the pursuit of those, the scientific rigor around those hypotheses is ultimately get evidence. Knowledge of what nature is should be a dialogue with nature, rather than a monologue. Monologue, beautifully put. Can we talk a little bit about the Drake equation? Sure. Another framework from which to have this kind of discussion about possible civilizations out there. So let me ask, within the context of the Drake equation, or maybe bigger, how many alien civilizations do you think are out there? Well, it's hard to tell, because the Drake equation is again, quantifying our ignorance. It's just a set of factors. The only one that we know, or actually two that we know quite well is the rate of star formation in the Milky Way galaxy, which we measured by now, and the frequency of planets like the Earth around stars. Yes. And at the right distance to have life. But other than that, there are lots of implicit assumptions about all the other factors that will enable us to detect a signal. Now, I should say the Drake equation has a very limited validity, just for signals from civilizations that are transmitting at the time that you're observing them. However, we can do much better than that. We can look for artifacts that they left behind. Even if they are dead, you can look for industrial pollution in the atmosphere of planets. Why do I bring this up? Again, to show you the conservatism of the mainstream in astronomy. And by the way, I have leadership positions. I was chair of the astronomy department for nine years, the longest serving chair at Harvard. And I'm the chair of the board on physics and astronomy of the National Academies. It's a primary board. And I'm director of two centers at Harvard and so forth. So I do represent the community in various ways, but at the same time, I'm a little bit disappointed by the conservatism that people have. And so let me give you an illustration of that. So the astronomy community actually is going right now through the process of defining its goals for the next decade. And there are proposals for telescopes that would cost billions of dollars, and whose goal is to find evidence for oxygen in the atmosphere of planets around other stars. With the idea that this would be a marker, a signature of life. Now, the problem with that is Earth didn't have much oxygen in its atmosphere for the first two billion years. Roughly half of its life, it didn't have much oxygen, but it had life. It had microbial life. It's not clear yet, as of yet, what the origin is for the rise in the oxygen level after two billion years, about 2.4 billion years ago. But we know that a planet can have life without oxygen in the atmosphere, because Earth did it. The second problem with this approach is that you can have oxygen from natural processes. You can break water molecules and make oxygen. So even if you find it, it will never tell you that for sure life exists there. And so even with these billions of dollars, the mainstream community will never be confident whether there is life there. Now, how can it be confident? There is actually a way. If instead of looking, with the same instruments, if you look for molecules that indicate industrial pollution, for example, CFCs that are produced by refrigerating systems or industries here on Earth, that they do the ozone layer, you can search for that. And I wrote a paper five years ago suggesting that. Now, what's the problem? You can just tell NASA, I want to build this telescope to search for oxygen, but also for industrial pollution. Nobody would say that, because it sounds like, you know, on the periphery of the field. And I ask you, why would- That's hilarious, because that's exactly, I mean- That would be- What you're saying is quite brilliant. I mean, because it's a really strong signal. And if life, if there's alien civilizations out there, then there are probably going to be many of them, and they're probably going to be more advanced than us, and they're probably going to have something like industrial pollution, which would be a much stronger signal than some basic gas, which could have a lot of different explanations. So like, something like oxygen, or, I mean, I don't, you know, I mean, we could talk about signs of life on Venus and so on. But, like, if you want a strong signal, it would be pollution. I love how garbage is- No, but the pollution, you have to understand, we think of pollution as a problem, but on a planet that was too cold, for example, to have a comfortable life on it, you can imagine terraforming it and putting a blanket of polluting gases such that it will be warmer. And that would be a positive change. So if an industrial or a technological civilization wants to terraform a planet that otherwise is too cold for them, they would do it. So what's the problem of defining it as a search goal using the same technologies? The problem is that there is a taboo. We are not supposed to discuss extraterrestrial intelligence. There is no funding for this subject, not much, very little. And young people, because of the bullying on Twitter, you know, all the social media and elsewhere, young people with talent that are curious about these questions do not enter this field of study. And obviously, if you step on the grass, it will never grow, right? So if you don't give funding, obviously, you know, the mainstream community says, look, nothing was discovered so far. Obviously, nothing would be discovered. If talented people go to other, you never search for it well enough, you will never find anything. I mean, look at gravitational wave astrophysics. It's a completely new window into the universe, pioneered by Ray Weiss at MIT. And at first, it was ridiculed. And thanks to some administrators at the National Science Foundation, it received funding, despite the fact that the mainstream of the astronomy community was very resistant to it. And now it's considered a frontier. So all these people that I remember as a postdoc, a young postdoc, these people that bashed this field and said bad things about people, said nothing will come out of it, now they say, oh yeah, of course, you know, the Nobel Prize was given to the LIGO collaboration. Of course, now they are supportive of it. But my point is, if you suppress innovation early on, there are lots of missed opportunities. The discovery of exoplanets is one example. You know, in 1952, there was an astronomer called, named Otto Struve, and he wrote a paper saying, why don't we search for Jupiter-like planets close to their host star? Because if they're close enough, they would move the star back and forth and we can detect the signal, okay? And so astronomers on time allocation committees of telescopes for 40 years argued, this is not possible, because we know why Jupiter resides so far from the sun. You cannot have Jupiter so close, because there is this region where ice forms far from the sun, and beyond that region is where Jupiter-like planets can form. There was a theory behind it, which ended up being wrong by today's standards. But anyway, they did not give time on telescopes to search for such systems, until the first system was discovered four decades after Otto Struve's paper. And the Nobel Prize was awarded to that just a couple of years ago. And you ask yourself, okay, so science still made progress, what's the problem? The problem is that this baby came out barely, and there was a delay of four decades, so the progress was delayed, and I wonder how many babies were not born because of this resistance. So there must be ideas that are as good as this one that were suppressed because they were bullied, because people ridiculed them, that were actually good ideas, and these are missed opportunities, babies that were never born. And I'm willing to push this frontier of the search for technologies or technological signatures for other civilization, because when I was young, I was in the military in Israel, it's obligatory to serve, and there was this saying that one of the soldiers sometimes has to put his body on the barbed wire so that others can go through. And I'm willing to suffer the pain so that younger people in the future will be able to speak freely about the possibility that some of the anomalies we find in the sky are due to technological signatures. And it's quite obvious, this is why I like folks in the artificial intelligence space, Elon Musk and a few others speak about this, and they look at the long arc. They say, what, this kind of, you can call it first principles thinking, or you can call it anything, really, is if we just zoom off from our current bickering and our current discussions in what science is doing, look at the long arc of the trajectory we're headed at. Which questions are obviously fundamental to science? And that should be asked. And which is the space of hypotheses we should be exploring. And exoplanets is a really good example of one that was an obvious one. I recently talked to Sarah Seager, and it was very taboo when she was starting out to work on an exoplanet, and that was even in the 90s. It's obvious should not be a taboo subject. And to me, I mean, I'm probably ignorant, but to me, exoplanets seems like it's ridiculous that that would ever be a taboo subject to not fund, to not explore. That's very, but even for her, it's now taboo to say, like, what, you know, to look for industrial pollution, right? Right. And I find that ridiculous. I'll tell you why. She can't take the next step. It's ridiculous for another reason. Not because of just the scientific benefits that we might have by exploring it, but because the public cares about these questions. Yes, a lot. And the public funds science. So how dare the scientists shy away from addressing these questions if they have the technology to do it? It's like saying, I don't want to look through Galileo's telescope. It's exactly the same. You have the technology to explore this question, to find evidence, and you shy away from it. You might ask, why do people shy away from it? And perhaps it's because of the fact that there is science fiction. I'm not a fan of science fiction because it has an element to it that violates the laws of physics in many of the books and the films. Magic. I cannot enjoy these things when I see the laws of physics violated. But who cares that the fact that there is science fiction? I mean, if you have the scientific methodology to address the same subject, I don't care that other people spoke nonsense about this subject or said things that make no sense. Who cares? You do your scientific work just like you explore the dark matter. You explore the possibility that Oumuamua is an artifact. You just look for evidence and try to deduce what it means. And I have no problem with doing that. To me, it sounds like any other scientific question that we have, and given the public's interest, we have an obligation to do that. By the way, science to me is not an occupation of the elite. It doesn't allow me to feel superior to other humans that are unable to understand the math. To me, it's a way of life. If there is a problem in the faucet or in the pipe at home, I try to figure out what the problem is. And with a plumber, we figure it out and we look at the clues. And the same thing in science. You look at the evidence, you try to figure out what it means. It's common sense in a way. And it shouldn't be regarded as something removed from the public. It should be a reflection of the public's interest. And I think it's actually a crime to resist the public. If the public says, I care about this, and you say, no, no, no, that's not sophisticated enough for me. I want to do intellectual gymnastics on anti-de Sitter space. To me, that's a crime. Yes, I 100% agree. So it's hilarious that the very, not hilarious, it's sad, that people who are trained in the scientific community to have the tools to explore this world, to be children, to be the most effective at being children, are the ones that resist being children the most. But there is a large number of people that embrace the childlike wonder about the world and may not necessarily have the tools to do it. That's the more general public. And so, I wonder if I could ask you and talk to you a little bit about UFO sightings. That there's people, quote unquote believers, there's hundreds of thousands of UFO sightings. And I've consumed some of the things that people have said about it. And one thing I really like about it is how excited they are by the possibility, by, it's almost like this childlike wonder about the world out there. They're not, it's not a fear, it's an excitement. Do you think, because we're talking about this, possibly extraterrestrial object that visited, that flew by Earth, do you think it's possible that out of those hundreds of thousands of UFO sightings, one is an actual, one or some number is an actual sighting of a non-human, some alien technology? And that we're not, we did not, we're too close-minded to look and to see. I think to answer this question, we need better evidence. My starting point, as I said, out of modesty, is that we are not particularly interesting. And therefore, I would be hard-pressed to imagine that someone wants to really spy on us. So, I would think, as a starting point, that we don't deserve attention and we shouldn't expect someone, but who knows? Now, the problem that I have with UFO sighting reports is that 50 years ago, there were some reports of fuzzy images, saucer-like things. By now, our technologies are much better, our cameras are much more sensitive. These fuzzy images should have turned into crisp, clear images of things that we are confident about. And they haven't turned that way. It's always on the borderline of believability. And because of that, I believe that it might be, most likely, artifacts of our instruments or some natural phenomena that we are unable to understand. Now, of course, the reason you must examine those, if, for example, pilots report about them or the military finds evidence for them, is because it may pose a national security threat if another country has technologies that we don't know about and they're spying on us, we need to know about it. And therefore, we should examine everything that looks unusual. But to associate it with an alien life is a little too far for me until we have evidence that stands up to the level of scientific credence, that we are 100% sure that from multiple detectors and through a scientific process. Now, again, if the scientific community shies away from these reports, we will never have that. It's like saying, I don't want to take photographs of something because I know what it is, then you will never know what it is. But I think if some science, if grants, let's put it this way, if funding will be given to scientists to follow on some of these reports and use scientific instruments that are capable of detecting those sightings with much better resolution, with much better information, that would be great because it will clarify the matter. These are not, as you said, hundreds of thousands, these are not once in a lifetime events. So it's possible to take scientific instrumentation and explore, go to the ocean where someone reported that there are frequent events that are unusual and check it out, do a scientific experiment. What's the problem? Why only do experiments deep into the ocean and look at the oceanography or do other things? We can do scientific investigation of these sightings and figure out what they mean. I'm very much in favor of that, but until we have the evidence, I would be doubtful as to what they actually mean. Yeah, we'll have to be humble and acknowledge that we're not that interesting. It's kind of, you're making me realize that because it's so taboo, that the people that have the equipment, meaning, and we're not just talking, everybody has cameras now, but to have a large-scale sensor network that collects data, that regularly collects, just like we look at the weather, we're collecting information, and then we can then access that information when there is reports and have it not be a taboo thing where there's millions or billions of dollars funding this effort that, by the way, inspires millions of people. This is exactly what you're talking about. The scientific community is afraid of a topic that inspires millions of people. It's absurd. But if you put blinders on your eyes, you don't see it. Yeah. Right. I should say that we do have meteors that we see. These are rocks that, by chance, happen to collide with the Earth. And if they're small, they burn up in the atmosphere, but if they're big enough, tens of meters or more, hundreds of meters, the outer layer burns up, but then the core of the object makes it through. And this is our chance of putting our hands around an object if this meteor came from interstellar space. So one path of discovery is to search for interstellar meteors. And with a student of mine, we actually looked through the record and we thought that we found one example of a meteor that was reported that might have come from interstellar space. And another approach is, for example, to look at the moon. The moon is different from the Earth in the sense that it doesn't have an atmosphere. So objects do not burn up on their way to it. It's sort of like a museum. It collects everything that comes. Of rocks from out there in deep space, yeah. And there is no geological activity on the moon. So on Earth, every hundred million years, we could have had computer terminals on Earth that could have been a civilization like ours with electronic equipment more than 100 million years ago, and it's completely lost. You cannot excavate and find evidence for it because in archeological digs, because the Earth is being mixed on these time scales, and everything that was on the surface more than 100 million years ago is buried deep inside the Earth right now because of geological activity. Fascinating to think about, by the way, yeah. But on the moon, this doesn't happen. The only thing that happens on the moon is you have objects impacting the moon, and they go 10 meters deep, so they produce some dust. But the moon keeps everything. It's like a museum. It keeps everything on the surface. So if we go to the moon, I would highly recommend regarding it as an archeological site and looking for objects that are strange. Maybe it collected some trash from interstellar space. If we could just linger on the Drake equation for a little bit, we kind of talked about there's a lot of uncertainty in the parameters, and the Drake equation itself is very limited. But I think the parameters are interesting in themselves, even if it's limited, because I think each one is within the reach of science, right, to get the evidence for it. I mean, a few I find really interesting could be interesting to get your comment on. So the one with the most variance, I would say, from my perspective, is the length that civilizations last, however you define it. And the Drake equation is the length of how long you're communicating. Yeah, transmitting. Transmitting, just like you said, that's a wrong way to think about it, because we could be detecting some other outputs of the civilizations, et cetera. But if we just define broadly how long those civilizations last, do you have a sense of how long that might last? Like what are the great filters that might destroy civilizations that we should be thinking about? How can science give us more hints on this topic? So I, as I mentioned before, operate by the Copernican principle, meaning that we are not special. We don't live in a special place, and not in a special time. And by the way, it's just modesty encapsulated in scientific terms, right? You're saying, I'm not special. I find conditions here, they exist everywhere. So if you adopt the Copernican principle, you basically say, our civilization transmitted radio signals for 100 years, roughly. So probably it would last another 100 or a few hundred, and that's it, because we don't live at a special time. So that's, you know, well, of course, if we get our act together, and we somehow start to cooperate, rather than fighting each other, killing each other, wasting a lot of resources on things that would destroy our planet, maybe we can lengthen that period, if we get smarter. But the most natural assumption is to say that we will live into the future as much as we lived from the time that we start to develop the means for our own destruction, the technologies we have, which is quite pessimistic, I must say. So several centuries, that's what I would give, unless we get our act, unless we become more intelligent than the newspapers report every day. Okay, point number one. Second, and by the way, this is relevant, I should say, because there was a report about perhaps a radio signal detected from Proxima Centauri. What do you make of that signal? Oh, I think it's some Australian guy with a cell phone next to the observatory or something like that, because it was the Parkes Telescope in Australia. Okay, I was like, why is it throwing, yeah, okay. So it's human-created noise. Yeah, which is always the worry, because actually the same observatory, the Parkes Observatory, detected a couple of years ago some signal, and then they realized that it comes back at lunchtime. And they said, okay, what could it be? And then they figured out that it must be the microwave oven in the observatory, because someone was opening it before it finished, and it was creating this radio signal that they detected with a telescope every lunchtime. So just a cautionary remark. But the reason I think it's human-made, without getting to the technical details, is because of this very short window by which we were transmitting radio signals out of the lifetime of the Earth. As I said, 100 years out of 4 1⁄2 billion years that the Earth existed. So what's the chance that another civilization, a twin civilization of ours, is transmitting radio signals exactly at the time that we are looking with our radio telescopes? Yeah. 10 to the minus seven. So, and the other argument I have is that they detected it in a very narrow band of frequencies, and that makes it, you know, it cannot be through natural processes, a very narrow band. Just like some radio transmissions that we produce. But if it were to come from the habitable zone, from a transmitter on the surface of Proxima b, this is the planet that orbits Proxima Centauri, then I calculated that the frequency would drift through the Doppler effect. You know, just like when you hear a siren on the street, you know, when the car approaches you, it has a different pitch than when it goes, recedes away from you, that's the Doppler effect. And when the planet orbits the star, Proxima Centauri, you would see or detect a different frequency when the planet approaches us as compared to when it recedes. So there should be a frequency drift just because of the motion of the planet. And I calculated that it must be much bigger than observed, so it cannot just be a transmitter sitting on the planet and sending in our direction a radio signal unless they want to cancel the Doppler effect, but then they need to know about us, because in a different direction, it will not be canceled. Only in our direction, they can cancel it perfectly. So there is this direction of Proxima Centauri, but I have a problem imagining a transmitter on the surface of a planet in the habitable zone emitting it, but my main issue is really with the likelihood, given what we know about ourself. Right, in terms of the duration of the civilization. The Copernican principle, yeah. So nevertheless, this particular signal is likely to be a human interference perhaps, but do you find Proxima be interesting, or the more general question is, do you think we humans will venture out outside our solar system and potentially colonize other habitable planets? Actually, I am involved in a project whose goal is to develop the technology that would allow us to leave the solar system and visit the nearest stars, and that is called the Starshot. In 2015, in May 2015, an entrepreneur from Silicon Valley, Yuri Milner, came to my office at Harvard and said, would you be interested in leading a project that would do that in our lifetime? Because as we discussed before, to traverse those distances with existing rockets would take tens of thousands of years. And that's too long. For example, to get to Proxima Centauri with the kind of spacecrafts that we already sent, like New Horizons or Voyager 1, Voyager 2, you needed to send them when the first humans left Africa, so that they would arrive there now. And that's a long time to wait. So Yuri wanted to do it within our lifetime, 10, 20 years, meaning it has to move at a fraction of the speed of light. So can we send a spacecraft that would be moving at a fraction of the speed of light? And I said, let me look into that for six months. And with my students and postdocs, we arrived to the conclusion that the only technology that can do that is the light sail technology, where- Can you explain? You basically produce a very powerful laser beam on Earth, so you can collect sunlight with photovoltaic cells or whatever, and then convert it into stored energy, and then produce a very powerful laser beam that is 100 gigawatt, and focus it on a sail in space that is roughly the size of a person, a couple of meters or a few meters, that weighs only a gram or a few grams, very thin. And through the math, you can show that you can propel such a sail. If you shine on it for a few minutes, it will traverse a distance that is five times the distance to the moon, and it will get to a fifth of the speed of light. Sounds crazy, but I've talked to a bunch of people, and they're like, I know it sounds crazy, but it's actually, it will work. This is one of those, it's just beautiful. I mean, this is science. And the point is, people didn't get excited about space since the Apollo era. And it's about time for us to go into space. Couple of months ago, I was asked to participate in a debate organized by IBM and Bloomberg News, and the discussion centered on the question, is the space race between the US and China good for humanity? Oh, interesting. And all the other debaters were worried about the military threats. And I just couldn't understand what they're talking about, because military threats come from hovering above the surface of the Earth, right? And we live on a two-dimensional surface. We live on the surface of the Earth. But space is all about the third dimension, getting far from Earth. So if you go to Mars, or you go to a star, another star, there is no military threat. What are we talking about? Space is all about feeling that we are one civilization, in fact, not fighting each other, just going far and having aspirations for something that goes beyond military threats. So why would we be worried that the space race will lead? That's actually brilliant. In our discourse about it, the space race is sometimes made synonymous with the Cold War, or something like that, or with wars. But really, yeah, there was a lot of ego tied up in that. I remember, I mean, it's still, to this day, there's a lot of pride that Russians, the Soviet Union was the first to space, and there's a lot of pride on the American side that it was the first on the moon. But yeah, you're exactly right. There's no aggression, there's no wars. And beyond that, if you think about the global economy right now, there is a commercial interest. That's why Jeff Bezos and Elon Musk are interested about Mars and so forth. There is a commercial interest which is international. It's driven by money, not by pride. And nations can sign treaties. First of all, there are lots of treaties that were signed even before the First World War and the Second World War, and the World War took place. So who cares? Humans, treaties do not safeguard anything. But beyond that, even if nations sign treaties about space exploration, you might still find commercial entities that will find a way to get their launches. And so I think we should rethink space. It has nothing to do with national pride. Once again, nothing to do with our egos. It's about exploration. And the biggest problem I think in human history is that humans tend to think about egos and about their own personal image, rather than look at the big picture. We will not be around for long. We are just occupying a small space right now. Let's move out of this. The way that Oscar Wilde said, I think is the best. He said, all of us are in the gutters, but some of us are looking at the stars. Yeah, and the more of us are looking at the stars, the likelier we are to, for this little experiment we have going on to last a while, as opposed to end too quickly. I mean, it's not just about science of being humble. It's about the survival of the human species is being humble. To me, it's incredibly inspiring, the Starshot Project of, I mean, there's something magical about being able to go to another habitable planet and take a picture even. I mean, within our lifetime, I mean, that with crazy technology too, it's exciting. I should tell you how it was conceived. So I was at the time, so after six months passed, after the visit of Yuri Miller, usually I go in December during the winter break, I go to Israel. I used to go to see my family and I get a phone call. Just before the weekend started, I get a phone call. Yuri would like you to present your concept in two weeks at his home. And I said, well, thank you for letting me know because I'm actually out of the door of the hotel to go to a goat farm in the Negev, in the southern part of Israel, because my wife wanted to have sort of, to go to a place that is removed from civilization, so to speak. So we went to that goat farm and I need to make the presentation. And there was no internet connectivity except in the office of the goat farm. So the following morning at 6 a.m., I sit with my back to the office of that goat farm, looking at goats that were newly born and typing into my laptop the presentation, the PowerPoint presentation about our ambitions for visiting the nearest star. And that was very surreal to me that, you know, look. Oh, like our origins in many ways, this very primitive origins and our dreams of looking out there. It's brilliant. So that is incredibly inspiring to me. But it's also inspiring of putting humans onto other moons or planets. I still find going to the moon really exciting. I don't know, maybe I'm just a sucker for it, but it's really exciting. And Mars, which is a new place, a new planet, another planet that might have life. I mean, there's something magical to that or some traces of previous life. You might think that humans cannot really survive and there are risks by going there. But my point is, you know, we started from Africa and we got to apartment buildings in Manhattan, right? It's a very different environment from the jungles to live in an apartment building in a small cubicle. And, you know, it took tens of thousands of years, but humans adapted, right? So why couldn't humans also make the leap and adapt to a habitat in space? Now you can build a platform that would look like an apartment building in the Bronx or somewhere, but have inside of it everything that humans need. And just like the space station, but bigger, and it will be a platform in space and the advantage of that is if something bad happens on Earth, you have that complex where humans live and you can also move it back and forth depending on how bright the sun gets. Because, you know, within a billion years, within a billion years, the sun would be too hot and it will boil off all the oceans on Earth. So we cannot stay here for more than a billion years, that's for sure. Yes. So that's a billion years from now. I prefer like shorter term deadlines. And so, and that's, I mean, there's a lot of threats that we're facing currently. Do you find it exciting, the possibility of, you know, landing on Mars and starting little like, building a Manhattan-style apartment building on Mars and humans occupying it? Do you think from a scientific or an engineering perspective, that's a worthy pursuit? I think it's worthy, but the real issue that is often underplayed is the risk to the human body from cosmic rays. These are energetic particles and we are protected from them by the magnetic field around the Earth that blocks them. But if you go to Mars, where there is no such magnetic field to block them, then, you know, a significant fraction of the brain cells in your head will be damaged within a year and the consequences of that are not clear. I mean, it's quite possible that humans cannot really survive on the surface. Now, it may mean that we need to dig tunnels, go underground or create some protection. This is something that can be engineered. Yes. And, you know, we can start from the moon and then move to Mars. That would be a natural progression. But it's a big issue that needs to be dealt with. I don't think it's a showstopper. I think we can overcome it. But, you know, just like anything in science and technology, you have to work on it for a while, figure out solutions. But it's not as rosy as Elon Musk talks about. I mean, Elon Musk can obviously be optimistic. I think eventually it will boil down to figuring out how to cope with this risk, the health risk. Yeah, I mean, in defense of optimism, I find that there's at least a correlation, if not their best friends, is optimism and open-mindedness. It's a necessary, it's preconditioned to try crazy things. And in that sense, the sense I have about going to Mars, if we use today's logic of what kind of benefits we'll get from that, we're never going to go. And most decisions we make in life, most decisions we've made as a human species are irrational if you look at just today. But if you look at the long arc and the possibilities that it might bring, just like humans. Left Europe and went. Yeah, Europe and destroyed everybody. But it was a commercial interest that drove that for trade. And it might happen again in this context. You have people like Jeff Bezos and Elon Musk that are commercially driven to go to space. But it doesn't mean that what we will ultimately find is not new worlds that have much more to offer than just commercial interest. As a side effect almost, right? Yeah, yeah. And that's why I think we should be open-minded and explore. And however, at the same time, because of the reasons you pointed out, I'm not optimistic that we will survive more than a few centuries into the future. Because people do not think long-term, and that means that we will only survive for the short term. I don't know if you have thoughts about this, but what are the things that worry you the most about from the great perspective of the universe, which is the great filters that destroys intelligent civilizations, but for our own species here, like what are the things that worry you the most? Yeah, the thing that worries me the most is that people pay attention to how many likes they have on Twitter. And rather than, you know, basketball coaches tell the team players, keep your eyes on the ball, not on the audience. The problem is we keep our eyes on the audience most of the time. Let's keep our eyes on the ball. And what does that mean? First of all, in context of science, it means pay attention to the evidence. When the evidence looks strange, then we should figure it out. You know, I went to a seminar about Umu Amuah at Harvard, and a colleague of mine that is mainstream, conservative, would never say anything that would deviate from what everyone else is thinking. Said to me after the seminar, I wish this object never existed. Now, to me, I mean, I just couldn't hear that. What do you mean? Nature is whatever it is, you have to pay attention to it. You cannot say, you know, you cannot bury your head in this. I mean, you should bless nature for giving you clues about things that you haven't expected. And I think that's the biggest fault, that we are looking for confirmations of things we already know so that we can maintain our pride that we already knew it, and maintain our image, not make mistakes, because we already knew it, therefore we expected the right thing. But science is a learning experience, and sometimes you're wrong. And let's learn from those mistakes. And what's the problem about that? Why do we have to get prizes, and why do we get to be honored and maintain our image when the actual objective of science is learning about nature? And like you've talked about, anomalies in this case are actually, are not things that are unfortunate and to be ignored, are in fact gifts and should be the focus of science. Exactly, because that's the way for us to improve our understanding. If you look at quantum mechanics, nobody dreamed about it, and it was revolutionary, and we still don't fully understand it. It's a pain for us to figure out. So why do you, so I understand from the perspective that's holding our science back, well, why do you have a sense that that's also something that might be a problem for us in terms of the survival of human civilization? Because when you look at society, it operates by the same principles. There is, people look for affirmation by groups, and they, you know, people segregate into herds that think like them, especially these days when social media is so strong. You can find your support group, and if you don't look for evidence for what you're saying, you can say crazy things, as long as there are enough people supporting what you say. You can even have your newspapers, you can have everything to support your view, and then, you know, bad things will happen to society. Because we're detaching ourselves from reality, and if we detach ourselves from reality, all the destructive things that naturally can occur in the real world, whether from nuclear weapons, all the kinds of threats that we're facing, even we're living through a pandemic, the, you know, a much, much worse pandemic could happen, and then we could, sadly, like we did this one, politicize it in some kind of way and have bickering in the space of Twitter and politics, as opposed to there's an actual thing that can destroy the human species. Exactly, so the only way for us to maintain, to stay modest and learn about what really happens is by looking for evidence. Again, I'm saying, it's not about ourself, you know? It's about figuring out what's around us, and if you close yourself by surrounding yourself with people that are like-minded, that refuse to look at the evidence, you can do bad things, and throughout human history, that's the origin of all the bad things that happen. Yes. And I think it's a key. It's a key to be modest and to look at evidence, and it's not a nuance. Now, you might say, oh, okay, the uneducated person might operate. No, it's the scientific community operates this way. My problem is not with people that don't have an academic pedigree. It's included everywhere in society. On the topic of like discovery of evidence of alien civilizations, which is something you touch on in your book, what that idea would do to societies, to the human psyche, and in general, do you think, and you talk about the, I still have trouble pronouncing, but- Omuamua. Omuamua wager, right? What do you think is, can you explain it, and what do you think in general is the effect that such knowledge might have on human civilization? Right, so Pascal had this wager about God. And by the way, there are interesting connections between theology and the search for extraterrestrial life. It's possible that we were planted on this planet by another civilization. We attribute to God powers that belong, really, to technological civilization. But putting that aside, Pascal basically said, there are two possibilities, either God exists or not. And if God exists, the consequences are quite significant, and therefore, we should consider that possibility differently than equal weight to both possibilities. And I suggest that we do the same with Omuamua or other technological signatures, that we keep in mind the consequences, and therefore, pay more attention to that possibility. Now, some people say extraordinary claims require extraordinary evidence. My point is that the term extraordinary is really subjective. For one person, a black hole is extraordinary. For another, it's just a consequence of Einstein's theory of gravity. Yeah, it's nothing extraordinary. The same about the type of dark matter, anything. So we should leave the extraordinary part of that sentence. Just keep evidence, okay? So let's be guided by evidence. And even if we have extraordinary claims, let's not dismiss them because the evidence is not extraordinary enough. Because if we have an image of something and it looks really strange, and we say, oh, the image is not sufficiently sharp, therefore, we should not even pay attention to this image or not even consider, I think that's a mistake. What we should do is say, look, there is some evidence for something unusual. Let's try and build instruments that will give us a better image. And if you just dismiss extraordinary claims, because you consider them extraordinary, you avoid discovering things that you haven't expected. And so I believe that along the history of astronomy, there are many missed opportunities. And I speak about astronomy, but I'm sure in other fields, it's also true. I mean, this is my expertise. For example, the Astrophysical Journal, which is the main primary publication in astrophysics, if you go before the 1980s, there are images that were posted in the Astrophysical Journal of giant arcs, arcs of light surrounding clusters of galaxies. And you can find it in printed versions of the Astrophysical Journal. And people just ignore, they put the image, they see the arc, they say, who knows what it is and just ignore it. And then in the 1980s, the subject of gravitational lensing became popular. And the idea is that you can deflect light by the force of gravity. And then you can put the source behind the cluster of galaxies, and then you will get these arcs. And actually Einstein predicted it in 1940. And so these things were expected, but people just had them in the images, didn't pay attention. So I'm sure there are lost opportunities sometimes. Even in existing data, you have things that are unusual and exceptional, and they're not being addressed. Yeah, you actually, I think you have the article, The Data Is Not Enough from quite a few years ago, where you talk, you know, we can go back to the 70s and 80s, but we can go also to the Mayan civilization. Right, the Mayan civilization basically believed in astrology that you can forecast the outcome of a war based on the position of the planets. And they had, you know, astronomers in their culture had the highest social status. They were priests, they were elevated. And the reason was that they helped politicians decide when to go to war, because they would tell the politicians, you know, the planets would be in this configuration, it's a better chance for you to win the war, go to war. And in retrospect, they collected wonderful data, but misinterpreted it, because we now know that the position of Venus, or Jupiter, or whatever, has nothing to do with the outcome of World War I, World War II, you know, it has nothing to do. And so we can have a prejudice and collect data without actually doing the right thing with it. That's such a Pisces thing to say. I looked up what your astrological sign is, so. So you mentioned Einstein predicted that black holes don't exist, or just didn't, or thought that. Don't exist in nature. Don't exist in nature. When Einstein came up with his theory of gravity, 1915, November 1915, a few months later, another physicist, Carl Schwarzschild, he was the director of the Potsdam Observatory, but he was a patriot, a German patriot. So he went into the First World War fighting for Germany. But while he was at the front, he sent a postcard to Einstein saying, you know, a few months after the theory was developed, saying, actually, I found a solution to your equations, and that was a black hole solution. And then he died a few months later. And Einstein was a pacifist, and he survived. So the lesson from this story is that if you want to work out the consequences of a theory, you better be a pacifist. But the point is that this solution was known shortly after Einstein came up with his theory, but in 1939, Einstein wrote a paper in the analysis of mathematics saying, even though the solution exists, I don't think it's realized in nature. And his argument was, if you imagine a star collapsing, stars often spin, and the spin will prevent them from making a black hole, collapsing to a point. So I mean, can you maybe, one of the many things you have work on, you're an expert in, is black holes. Can you first say what are black holes, and second, how do we know that they exist? Right, so black holes are the ultimate prison. You know, you can check in, but you can never check out. You're such a romantic. Even light cannot escape from them. So there are extreme structures of space and time, and there is this so-called Schwarzschild radius, or the event horizon of a black hole. Once you enter into it with a spaceship, you would never be able to tweet back to your friends and tell them, by the way, I asked the students in my class, freshman seminar at Harvard, I said, let me give you two possible journeys that you can take. I said, suppose aliens come to Earth and suggest that you would board their spaceship. Would you do it? And the second is, suppose you could board a spaceship that will take you into a black hole, would you do it? So all of them said to the first question, yes, under one condition, that I'll be able to maintain my social media contacts and report back, share the experience with them. I couldn't, personally, I have no footprint on social media. Yeah, which is, as a matter of principle. Yeah, my wife asked me when we got married, and I honor that. And I told you offline, I need to get married to such a woman. She truly is a special agent. Well, she was wise enough to recognize the risk, but it saves me time, and it also keeps me away from crowds. I don't have the notion of what a lot of other people think, so I can think independently. It's a problem to think, exactly. Yeah, exactly. I was surprised to hear that for students, it's extremely important to share experiences. Even if they go on a spaceship with aliens, they still want to brag about it, rather than look around and see what's going on. This is not an option when you go to the black hole, is exactly the point. So for the black hole, they said no, because obviously you can find your death after you get into it, you crash into singularity. There is this singularity in the center. So inside the event horizon, we know that all the matter collects at a point. Now, we can't really predict what happens at the singularity because Einstein's theory breaks down. And we know why it breaks down, because he doesn't have quantum mechanics that talks about small distances. We don't have a theory that unifies quantum mechanics and gravity so that it will predict what happens near a singularity. And in fact, a couple of years ago, I had a flood in my basement. And I invited a plumber to come over and figure out, and we found that the sewer was clogged because of tree roots that got into it. And we solved the problem. But then I thought to myself, well, isn't that what happens at the singularity of a black hole? Because the question is, where does the matter go? In the case of a home, I never thought about it, but the water, all the water that we use, goes in through the sewer to some reservoir somewhere. And the question is, what happens inside a black hole? And one possibility is that there is an object in the middle, just like a star, and everything collects there. And the object has the maximum density that we can imagine, like Planck densities. It's the ultimate density that you can have, where gravity is as strong as all the other forces. So you can imagine this object, very dense object at the center that collects all the matter. Another possibility is that there is some tunnel, just like the sewer, it takes the matter into another place. And we don't know the answer, but I wrote a Scientific American essay about it, and admitting our ignorance. It's a fascinating question. What happens to the matter that goes into a black hole? I actually recommended to some of my colleagues that work on string theory, at the closing of a conference, I'm the founding director of the Black Hole Initiative at Harvard, which brings together astronomers, physicists, philosophers, and mathematicians. And we have a conference once a year. And at the end of one of them, since I'm the director, I had to summarize, and I said that I wish we could go on a field trip to a black hole nearby. And I highly recommend to my colleagues that work on string theory to enter into that black hole, because then they can test their theory when they get inside. But one of the string theorists in the audience, Nimar Kani Hamad, immediately raised his voice and said, you have an ulterior motive for sending us into a black hole. Which I didn't deny, but at any event. Ah. Yeah, that's true, that's true. Can you say why we know that black holes exist? Right, so it's an interesting question, because black holes were considered a theoretical construct. And Einstein even denied their existence in 1939. But then, in the mid-1960s, quasars were discovered. These are very bright sources of light, a hundred times brighter than their host galaxy, which are point-like at the center of galaxies. And it was immediately suggested by Ed Salpeter in the West, and by Yakov Zeldovich in the East, that these are black holes that accrete gas, collect gas from their host galaxy that are being fed with gas. And they shine very brightly, because as the gas falls towards the black holes, just like water running down the sink, the gas swirls and then rubs against itself, and heats up, and shines very brightly, because it's very hot close to the black hole, by viscosity, it heats up. And in the case of black holes, it's the turbulence, the turbulent viscosity that causes it to heat up. So we get these very bright sources of light, just from black holes that are supposed to be dark. Nothing escapes from them, but they create a violent environment where gas moves close to the speed of light, and therefore shines very brightly, much more than any other source in the sky. And we can see these quasars all the way to the edge of the universe. So we have evidence now that when the universe was about 7% of its present age, infant, already back then you had black holes of a billion times the mass of the sun, which is quite remarkable. It's like finding giant babies in a nursery. How can these black holes grow so fast? Less than a billion years after the Big Bang, you already have a billion times the mass of the sun in these black holes. And the answer is presumably there are very quick processes that build them up. They build quickly. Very quickly. And so we see those black holes, and that was found in the mid 1960s, but in 19, sorry, in 2015, exactly 100 years after Einstein came up with his theory of gravity, the LIGO observatory detected gravitational waves. And these are just ripples in space and time. So according to Einstein's theory, the ingenuity of Einstein's theory of gravity that was formulated in November 1915 was to say that space and time are not rigid. They respond to matter. So for example, if you have two black holes and they collide, it's just like a stone being thrown into on a surface of a pond. They generate waves, disturbances in space and time that propagate out at the speed of light. These are gravitational waves. They create a space-time storm around them, and then the waves go all the way through the universe and reach us. And if you have a sensitive enough detector like LIGO, you can detect these waves. And so it was not just the message that we received for the first time, gravitational waves, but it was the messenger. So there are two aspects to it. One is the messenger, which is gravitational wave for the first time were detected directly. And the second was the message, which was a collision of two black holes, because we could see the pattern of the ripples in space and time. And it was fully consistent with the prediction that Schwarzschild made for how the space-time around the black hole is, because when two black holes collide, you can sort of map from the message that you get, you can reconstruct what really happened, and it's fully consistent. And in 2017 and 2020, there's two Nobel Prizes. That's right. That had to do with the black holes. Can you maybe describe in the same masterful way that you already been doing what those Nobel Prizes were given for? Yeah, so the 2017 was given for the LIGO collaboration for discovering gravitational waves from collisions of black holes. And the 2020 Nobel Prize in physics was given for two things. One was theoretical work that was done by Roger Penrose in the 1960s, demonstrating that black holes are inevitable when stars collapse. And it was mostly mathematical work. And actually Stephen Hawking also contributed significantly to that frontier. And unfortunately, he is not alive, so he could not be honored. So Penrose received it on his own. And then two other astronomers received it as well, Andrea Ghez and Reinhard Genzel. And they provided conclusive evidence that there is a black hole at the center of the Milky Way galaxy that weighs about four million times the mass of the sun. And they found the evidence from the motion of stars very close to the black hole. Just like we see the planets moving around the sun, there are stars close to the center of the galaxy, and they are orbiting at very high speeds of other thousands of kilometers per second or thousands of miles per second. Think about it. Yeah. Which can only be induced at those distances if there is a four million solar mass object that is extremely compact. And the only thing that is compatible with the constraints is a black hole. And they actually made a movie of the motion of these stars around the center. One of them moves around the center over a decade, you know, over timescales that we can monitor. And it was a breakthrough in a way. So combining LIGO with the detection of a black hole at the center of the Milky Way and in many other galaxies like quasars, now I would say black hole research is vogue. You know, it's very much in fashion. You know, we saw it back in 2016 when we established the Black Hole Initiative. You kind of saw that there's this excitement about in breakthroughs and discoveries around black holes, which are probably one of the most fascinating objects in the universe. It's up there. They're both terrifying and beautiful, right? And they capture the entirety of the physics that we know about this universe. I should say, you know, the question is, where is the nearest black hole? Can we visit it? And, you know, I wrote a paper with my undergraduate student, Amir Siraj, suggesting that perhaps, you know, there could be, if there is one in the solar system, we can detect it. Because I don't know if you heard, but there is a claim that maybe there is a planet nine in the solar system, because we see some anomalies at the outer parts of the solar system. So some people suggested maybe there is a planet out there that was not yet detected. So people searched for it, didn't find it. It weighs roughly five times the mass of the Earth. And we said, okay, maybe you can't find it because it's a black hole that was formed early in the universe. Is that part, so where do you stand on that? It could be that the dark matter is made of black holes of this mass. You know, we don't know what the dark matter is made of. It could be black holes. So we said, but there is an experimental way to test it. And the way to do it is because there is the Oort cloud of icy rocks in the outer solar system. And if you imagine a black hole there, every now and then a rock will pass close enough to the black hole to be disrupted by the very strong gravity close to the black hole. And that would produce a flare that you can observe. And we calculated how frequently these flares should occur. And with LSST on the Vera Rubin Observatory, we found that you can actually test this hypothesis. That's brilliant. And if you don't see flares, then you can put limits on the existence of a black hole in the solar system. It would be extremely exciting if there was a black hole, if planet nine was a black hole, because we could visit it, you know, and we can examine it. And it will not be a matter of, you know, an object that is very removed from us. Another thing I should say is it's possible that the black hole affected life on earth. The black hole at the center of the Milky Way. How? You know, that black hole right now is dormant. It's very faint. But we know that it flares. When a star like the sun comes close to it, the star will be spaghettified, basically become a stream of gas, like a spaghetti. And then the gas would fall into the black hole and there would be a flare. And this process happens once every 10,000 years or so. So we expect that, you know, these flares to occur every 10,000 years. But we also see evidence for the possibility that gas clouds were disrupted by the black hole, because the stars that are close to the black hole are residing in a single or two planes. And the only way you can get that is if they formed out of a disk of gas, just like the planets in the solar system formed. So there is evidence that gas fell into the black hole and powered possibly a flare. And these flares produce X-rays and ultraviolet radiation that could damage life if the Earth was close enough to the center of the galaxy. Where we are right now, it's not very risky for us. But there is a theoretical argument that says the solar system, the sun, was closer to the galactic center early on, and then it migrated outwards. So maybe in the early stage of the solar system, the conditions were affected, shaped by these flares of the black hole at the center of the galaxy. And that's why for the first two billion years, there wasn't any oxygen in the atmosphere, who knows? But it's just interesting to think that, from a theoretical concept that Einstein resisted in 1939, it may well be that black holes have influence on our life. And that it's just like discovering that some stranger affected your family and in a way your life. And if that happens to be the case, a second Nobel Prize should be given, not for just the discovery of this black hole at the center of the galaxy, but perhaps for the Nobel Prize in chemistry, for the effect that it had. For the effect, for the interplay that resulted in some kind of, yeah, the chemical effect, biology, I mean, all those kinds of things, in terms of the emergence of life and the creation of a habitable environment. That's so fascinating. And of course, like you said, dark matter, like black holes have some. They could be the dark matter in principle, yes. We don't know what the dark matter is at the moment. Does it make you sad? So you've had an interaction and perhaps a bit of a friendship with Stephen Hawking. Does it make you sad that he didn't win the Nobel? Well, altogether, I don't assign great importance to prizes because, you know, Jean-Paul Sartre, who I admired as a teenager, because I was interested in philosophy. When I grew up on a farm in Israel, you know, I used to collect eggs every afternoon and I would drive the tractor to the hills of our village and just think about philosophy, read philosophy books. And Jean-Paul Sartre was one of my favorite. And he was honored with a Nobel Prize in literature. He was a philosopher, primarily, existentialist. And he said, the hell with it. You know, why should I give special attention to this committee of people that get their self-importance from awarding me the prize? Like, what's, you know, why does that merit my attention? So he gave up on the Nobel Prize. And you know, there are two benefits to that. One, that you're not working your entire life in the direction that would satisfy the will of other people. You know, you work independently, you're not after these honors. Just for the same reason that if you're not living your life for making a profit or money, you can live a more fulfilling life because you're not being swayed by the wind, you know, of how to make money and so forth. The second aspect of it is, you know, that very often, you know, these prizes, they distort the way we do science because instead of people willing to take risks and instead of having announcements only after a group of people converges with a definite result, you know, the natural progression of science is based on trial and error, you know. So reporting some results and perhaps they're wrong, but then other people find perhaps better evidence and then you figure out what's going on. And that's the natural way that science is, you know, it's a learning experience. So if you give the public an image by which scientists are always right, you know, and you know, some of my colleagues say we must do that because otherwise the public will never believe us that global warming is really taking place. But that's not true because the public will really believe you if you show the evidence. So the point is you should be sincere when the evidence is not absolutely clear or where there are disputes about the interpretation of the evidence, we should show ourselves. You know, the king is naked, okay? There is no point in pretending that the king is dressed, saying that scientists are always right. Scientists are wrong frequently. And the only way to make progress is by evidence giving us the support that we need to make airtight arguments. So when you say global warming is taking place, if the evidence is fully supportive, if there are no holes in the argument, then people will be convinced because you're not trying to fool them. When the evidence was not complete, you also show them that the evidence is not complete. And when there's holes, you show that there's holes and here's the methodology we're using to try to close those holes. Exactly, let's be sincere, why pretend? So if there were no, in a world where there were no prizes, no honors, we would act like kids, as I said before. We would really be focusing on the ball and not on the audience. Yeah, the prizes get in the way and it's so powerful. Do you think, in some sense, the few people that have turned down the prize made a much more powerful statement? I don't know if you're familiar in the space of mathematics with the Fields Medal and Grigori Parlamin who turned down the prize. So he, I've committed, one of the reasons I started this podcast is I'm going to definitely talk to Putin, I'm definitely talking to Parlamin, and people keep telling me it's impossible. I love hearing that because I'll talk to both. Anyway, but do you have a sense of why he turned down the prize and is that a powerful statement to you? Well, what I read is that, you're talking about the mathematician, right? The mathematician turned down the Fields Medal. What I read is that he was disappointed by the response of the community, the mainstream community, the mathematicians, to his earlier work where they dismissed it, they didn't attend to the details and didn't treat him with proper respect because he was not considered one of them. And I think that speaks volumes about the current scientific culture, which is based on groupthink and on social interaction rather than on the merit of the argument and on the evidence in the context of physics. So in mathematics, there is no empirical basis. You're exploring ideas that are logically consistent, but nevertheless, there is this groupthink. And I think he was so frustrated with his past experience that he didn't even bother to publish his papers. He just posted them on the archive and in a way, it's saying, I know what the answer is, go look at it. And then again, in the long arc of history, his work on archive will be remembered and all the prizes, most of the prizes will be forgotten. This is what people don't kind of think about. When you look at Roger Penrose, for example, is another fascinating figure. You know, it's possible, and forgive me if I'm showing my ignorance, but he's also did some work on consciousness. He's been one of the only people who spoke about consciousness, which for a longest time is still arguably outside of the realm of the sciences. It's still seen as a taboo subject. And he was brave enough to explore it from a physics perspective, from just a philosophical perspective, but like with the rigor, like proposing different kind of hypotheses of how consciousness might be able to emerge in the brain. And it's possible that that is the thing he's remembered for if you look 100 years from now, right? As opposed to the work in the black holes, which fits into the kind of, fits into what the current scientific community allows to be the space of what is and isn't science. Yeah, it's really interesting to look at people that are innovators, where in some phases of their career, their ideas fit into the social structure that is around them, but in other phases, it doesn't. And when you look at them, they just operated the same way throughout. And it says more about their environment than about them. Well, yeah, I don't know if you know who Max Tegmark is. I just recently talked to him. He's a friend of mine. I just recently talked to him again. And he, I mean, he was a little bit more explicit about saying, you know, being aware, which is something I also recommend, is like being aware where the scientific community stands and doing enough to get, like, move along into your career, in your career. And it's the necessary evil, I suppose. If you are one of those out-of-the-box thinkers that just naturally have this childlike curiosity, which Max definitely is one of them, is sometimes you have to do some stuff that fits in. You publish and you get tenure and all those kinds of things. But the tenure is a great privilege because it allows you to, in principle, explore things that are not accepted by others. And unfortunately, it's not being taken advantage of by most people, and it's a waste of very precious resource. Yeah, absolutely. The space that you kind of touched on that's full of theories and is perhaps detached from appreciation of empirical evidence or longing for empirical evidence or grounding in empirical evidence is the theoretical physics community and the interest in unifying the laws of physics and with the theory of everything. I'm not sure from which direction to approach this question, but how far away are we from arriving at a theory of everything, do you think? And how would we, how important is it to try to arrive at it, at this kind of goal of this beautiful, simple theory that unlocks the very fundamental basis of our nature as we know it? And what are the kinds of approaches we need to take to get there? Yeah, so in physics, the biggest challenge is to unify quantum mechanics with gravity. And I believe that once we have experimental evidence for how this happens in nature, in systems that have quantum mechanical effects, but also gravity is important, then the theory will fall into our lap, okay? But the mistake that is made by the community right now is to come up with the right theory from scratch. And Einstein gave the illusion that you can just sit in your office and understand nature, when he came up with his general theory of relativity. But first of all, perhaps he was lucky, but it's not a rule. The rule is that you need evidence to guide you, especially when dealing with quantum mechanics, which is really not intuitive. And so there are two places where the two theories meet. One is black holes, and there is a puzzle there. It's called the information paradox. In principle, you can throw the Encyclopedia Britannica into a black hole. It's a lot of information. And then it will be gone, because a black hole carries only three properties or qualities, the mass, the charge, and the spin, according to Einstein. But then when Hawking tried to bring in quantum mechanics to the game, he realized that black holes have a temperature, and they radiate. This is called Hawking radiation. It was sort of anticipated by Jacob Bekenstein before him, and Hawking wanted to prove Bekenstein wrong and then figure this out. And so what it means is black holes eventually evaporate. And they evaporate into radiation that doesn't carry this information, according to Hawking's calculation. And then the question is, according to quantum mechanics, information must be preserved. So where did the information go if a black hole is gone? And where is the information that was encoded in the Encyclopedia when it went into the black hole? And to that question, we don't have an answer yet. It's one of those puzzles about black holes. And it touches on the interplay between quantum mechanics and gravity. Another important question is what happened at the beginning of the universe? What happened before the Big Bang? And by the way, on that I should say, there are some conjectures. In principle, if we figure it out, if we have a theory of quantum gravity, it's possible to imagine that we will figure out how to create a universe in the laboratory. By irritating the vacuum, you might create a baby universe. And if we do that, it will offer a solution to what happened before the Big Bang. Perhaps the Big Bang emerged from the laboratory of another civilization. So it's like baby universes are being born out of laboratories. And inside the baby universe, you have a civilization that brings to existence a new baby universe. So just like humans, right? We have babies and they make babies. So in principle, that would solve the problem of why there was a Big Bang and also what happened before the Big Bang. So we came, our umbilical cord is connected to a laboratory of a civilization that produced our universe once it figured out quantum gravity. It's baby Big Bangs all the way down. It's just Big Bangs all the way down. So if we collect data about how the universe started, we could potentially test theories of, or it can educate us about how to unify quantum mechanics and gravity. If we get any information about what happens near the singularity of a black hole, if we get a sense of, somehow we learn what happens at the singularity, that would educate. So there are places where we can search for evidence, but it's very challenging, I should say. And my point is, the string theorists, they decided that they know how to approach the problem, but they don't have a single theory. There is a multitude of theories and it's not tightly constrained and they cannot make predictions about black holes or about the beginning of the universe. So at the moment I say we are at a loss. And the way I feel about this concept of the theory of everything, we should wait until we get enough evidence to guide us. And until then, there are many important problems that we can address. Why bang our head against the wall on a problem for which we have no guidance? We don't have a good dance partner in terms of evidence. There's not, I mean, it'd be interesting, Jessica said, I mean, the lab is one place to create universes or black holes, but it'd be fascinating if there is indeed a black hole in our solar system that you can interact with. So the problem with the origin of the universe is all you can do is collect data about it, right? You can't interact with it. Well, you can, for example, detect gravitational waves that emerged from that. And there is an effort to do that and that could potentially tell us something. But yeah, it's a challenge and that's why we're stuck. So I should say, despite what physicists portray, that we live through an exceptional growth in our understanding of the universe, we're actually pretty much stuck, I would say, because we don't know the nature of the dark matter, most of the matter in the universe. We don't know what it is and we don't know how the universe started. We don't know what happens in the interior of a black hole. Because you've thought quite a bit about dark matter as well, do you have any kind of hypothesis, interesting hypothesis? We already mentioned a few about what is dark matter and what are the possible paths that we could take to unlock the mystery of dark, what is dark matter? Yeah, so what we need is some anomalies that would hint what the nature of the dark matter is or to detect it in the laboratory. There are lots of laboratory experiments searching, but it's like searching for a needle in a haystack because there are so many possibilities for the type of particle that it may be. But maybe at some point, we'll find either a particle or black holes as dark matter or something else. But at the moment- Can you also maybe, sorry to interrupt, to comment about what is dark matter? Like what, it's just a name we're assigned to what? So most of the community believes that it's a particle that we haven't yet detected. It doesn't interact with light, so it's dark. But the question is, what does it interact with and how can we find it? And for many years, physicists were guided by the idea that it's some extension of the standard model of particle physics. But then they said, oh, we will find some clues from the Large Hadron Collider about its nature. Or maybe it's related to supersymmetry, which is a new symmetry that we haven't found any evidence for. In both cases, the Large Hadron Collider did not give us any clues. And other people searched for specific types of particles in the laboratory and didn't find any. A couple of years ago, actually around the time that I worked on Oumuamua, I also worked on the possibility that the dark matter particles may have a small electric charge, which is a speculation. But nobody complained about it. And it was published and I regarded more of a speculation than the artificial origin of Oumuamua. And to me, as far as I'm concerned, I applied the same scientific tools in both cases. There is an anomaly that led me to that discussion, which has to do with hydrogen being cold in the early universe more than we expected. So we suggested maybe the dark matter particles have some small charge. But you deal with anomalies by exploring possibilities. That's the only way to do it. And then collecting more data to check those. And searching for technological signatures is the same as any other part of our scientific endeavor. We make hypotheses and we collect data. And I don't see any reason for having a taboo on this subject. In your childlike, open-minded excitement and approach to science, I think to anyone listening to this, truly inspiring. I mean, the question I think is useful to ask is by way of advice for young people. A lot of young people listen to this, whether from all over the world, and teenagers, undergraduate students, even graduate students, even young faculty, even older faculty. They're all young at heart. Like there's many of us young at heart. Do you have advice for, but let's focus on the traditionally defined sort of young folks, like undergraduate. Do you have advice to give to young people like that today about life, maybe in general, maybe a life of curiosity in the sciences? Definitely. Well, first I should confess that I enjoy working with young people much more than with senior people. And the reason is they don't carry a baggage of prejudice. They're not so self-centered. They're open to exploration. My advice, I mean, one of the lessons that took me a while to learn, and I should say I lost important opportunities as a result of that. So I would regard it as a mistake on my behalf, was to believe experts, so quote unquote. So on a number of occasions, I would come up with an original idea and then suggest it to an expert, someone that works in the same field for a while. And the expert would dismiss it, most of the time because it's new and was not explored, not because of the merit. And then what happened to me several times is that someone else would listen to the conversation or would hear me suggesting it. And I would give up because the expert said no. And then that someone else would develop it so that it becomes the hottest thing in this field. And once it happened to me multiple times, I then realized, the hell with the experts. You know, like, they don't know what they're doing. They are just repeating the, they don't think creatively. They are being threatened by innovation, okay? And it's the natural reaction of someone that cares about their ego more than about the matter that we are discussing. And so I said, I would not, I don't care how many likes I have on Twitter. I don't care whether the experts say one thing or another. I will basically exercise my judgment and do the best I can. Turns out that I'm wrong. I made a mistake. That's part of the scientific endeavor. And it took me a while to recognize that. And it was a lot of wasted opportunities. So to the young people, I would recommend don't listen to experts. Carve your own path. Now, of course, you will be wrong. You should learn from experience, just like kids do. But do it yourself. Your father died in 2017. Your mother died in 2019. Do you miss them? Very much so. Is there a memory, that fond memory that stands out, or maybe what have you learned from them? From my mother, I mean, she was very much my inspiration for pursuing intellectual work because she studied at the university and then because of the Second World War, after the Second World War, she was born in Bulgaria. They immigrated to Israel. And she left university to work on a farm. And later in life, when all the kids left home, she went back to the university and finished the PhD. But she planted in me the intellectual curiosity and valuing learning or acquiring knowledge as a very important element in life. And my love with philosophy came from attending classes that she took at the university. When I was a teenager, I was fortunate to go to some of these and they inspired me later on. And I'm very different than my colleagues, as you can tell, because my upbringing was quite different. And the only reason I'm doing physics or astrophysics is because of circumstances. I mean, at age 18, I was asked to serve in the military. And the only way for me to pursue intellectual work was to work on physics because that was the closest to philosophy. And I was good at physics, so they admitted me to an elite program called Telpiod that allowed me to finish my PhD at age 24 and to actually propose the first international project that was funded by the Star Wars initiative of Ronald Reagan. And that brought me to the US to visit Washington, DC, where we were funded from. And then on one of the visits, I went to the Institute for Advanced Study at Princeton and met John Bacall that later offered me a five-year fellowship there under the condition that I'll switch to astrophysics. At which point, I said, okay, I cannot give up on this opportunity, I'll do it, switch to astrophysics. It felt like a forced marriage, kind of arranged marriage. And then I was offered the position at Harvard because nobody wanted that. They first selected someone else, and that someone said, I don't want to become a junior faculty at the Harvard Astronomy Department because the chance for being promoted are very small. So he took another job. And then I was second in line, they gave it to me. I didn't care much because I could go back to the farm any day. And after three years, I was tenured. And eventually, a decade later, became the chair of this department and served for nine years as the chair of the astronomy department at Harvard. But at that point, it became clear to me that I'm actually married to the love of my life. Even though it was an arranged marriage, there are many philosophical questions in astrophysics that we can address. But I'm still very different than my colleagues that were focusing on technical skills in getting to this job. So my mother was really extremely instrumental in planting the seeds of thinking about the big picture in me. Then my father, he was working in the farm, and we didn't speak much because we sort of understood each other without speaking. But what he gave me is a sense of, you know, that it's more important to do things than to talk about them. I love the, I mean, my apologies, but MIT mind and hand, I love that there's the root of philosophy that you gain from your mom and the hand that actions all that ultimately in the end matters from your dad. That's really powerful. If we could take a small detour into philosophy, is there by chance any books, authors, whether philosophical or not, you mentioned Sartre, that stand out to you that were formative in some small or big way that perhaps you would recommend to others, maybe when you were very young or maybe later on in life? Well, actually, yeah, I read the number of existentialists that appealed to me because they were authentic. You know, Sartre, you know, he declined the Nobel prizes we discussed, but he also was mocking people that pretend to be something better than they are. You know, he was living an authentic life that is sincere, and that's what appealed to me. And Albert Camus was another French philosopher that advocated existentialism. You know, that really appealed to me. That's probably my favorite existentialist, Camus, yeah. Yeah, and he died at a young age in an accident, unfortunately. And then, you know, people like Nietzsche that, you know, broke conventions. And I noticed that Nietzsche is still extremely popular. You know, that's quite surprising. He appeals to the young people of today. And the people that, it's the childlike wonder about the world, and he was unapologetic. You know, it's like most philosophers have a very strict adherence to terminology and to the practices, academic philosophers. And Nietzsche was full of contradictions, and he just, I mean, he was just this big kid with opinions and thought deeply about this world. And people are really attracted to that. And surprisingly, there's not enough people like that throughout history of philosophy. And that's why I think there's still a draw to him. Yeah, to me, what stands out is his statement that the best way to corrupt the mind of young people is to tell them that they should agree with the common view, you know? And, you know, it goes back to the thread that went throughout discussion. Yes, you've kind of suggested that we ought to be humble about our very own existence, and that our existence lasts only a short time. We talked about you losing your father and your mother. Do you think about your own mortality? Are you afraid of death? I'm not afraid. You know what, Epicurus, actually, Epicurus was a very wise person. According to Lucretius, Epicurus didn't leave anything in writing, but he said that he's never afraid of death because as long as he's around, death is not around. And when death will be around, he will not be around. So he will never meet death, so why should you be worried about something you will never meet? You know, and it's an interesting philosophy of life. You know, you shouldn't be afraid of something that you will never encounter, right? But there's a finiteness to this experience. Oh, yeah. We live every day, I mean, I think, if we're being honest, we live every day as if it's gonna last forever. We often kind of don't contemplate the fact that it ends. You kind of have plans and goals, and you have these possibilities. You have a kind of lingering thought, especially as you get older and older and older, that this is, especially when you lose friends, then you start to realize, you know, it does end. But I don't know if you really are cognizant of that. I mean, because. So, but you have to be careful not to be depressed by it, because otherwise you lose the vitality, right? So I think the most important thing to draw from knowing that you are short-lived is a sense of appreciation that you're alive. That's the first thing. But more importantly, a sense of modesty, because how can anyone be arrogant if they kept at the same time this notion that they are short-lived? I mean, you cannot be arrogant, because anything that you advocate for, you know, you will not be around to do that in a hundred years. So people will just forget and move on, you know? And if you keep that in mind, you know, the Caesars in ancient Rome, they had a person next to them telling them, don't forget that you're immortal. You know, there was a person with that duty, because the Caesars thought that they are all powerful, you know? And they had, for a good reason, someone they hired to whisper in their ear, don't forget that you're immortal. Yeah. Well, you're somebody, one of the most respected, famous scientists in the world, sitting on a farm, gazing up at the stars. So you seem like an appropriate person to ask the completely inappropriate question of what do you think is the meaning of it all? What's the meaning of life? That's an excellent question, and if we ever find an alien that we can converse with, I would like to answer this, I would like to ask for an answer to this question, because... Would they have a different opinion, you think? Well, they might be wiser, because they lived around for a while, but I'm afraid they will be silent. I'm afraid they will not have a good answer. And I think it's the process that you should get satisfied by, the process of learning you should enjoy. Okay, so it's not so much that there is a meaning. In fact, there is, as far as I can tell, things just exist, you know? And I think it's inappropriate for us to assign a meaning for our existence, because as a civilization, we will eventually perish, and nothing will be, you know, just another planet on which life died, and if you look at the big scheme of things, who cares, you know, like, who cares? And how can we assign significance to what we are doing? You know, so if you said the meaning of life is this, well, it will not be around in a billion years, so what, you know, it cannot be the meaning of life, because life, you know, nothing will be around. So I think we should just enjoy the process, and you know, it's like many other things in life, you enjoy good food, okay? And you can enjoy learning. Why? Because it makes you appreciate better, you know, the environment that you live in. And sometimes people think religion, for example, is in conflict with science. Spirituality, in conflict. That's not true. If you see a watch, and you look at it from the outside, you know, you might say, oh, that's interesting, but then if you start to open it up and learn about how it works, you appreciate it more. So science is the way to learn about how the world works. And it's not in conflict to the meaning that you assign to all of this, but it helps you appreciate the world better. So in fact, I would think that a religious person should promote science, because it gives you a better appreciation of what's around you. You know, it's like, you know, if you buy in a grocery, buy something, you know, a bunch of fruits that are packed together, and you can't see from the outside exactly what kind of fruits are inside, but if you open it up and study, you appreciate better the merchandise that you get, right? So you pay the same amount of money, but at least you know what's inside. So why don't we figure out what the world is about, you know, what the universe contains, what is the dark matter? It will help us appreciate, you know, the bigger picture. And then you can assign your own flavor to what it means, you know. I think I'm truly grateful that a person like you exists at the center of the scientific community, gives me faith and hope about this big journey that we call science. So thank you for writing the book you wrote recently. You have many other books and articles that I think people should definitely read. And thank you for wasting all this time with me. It's truly an honor. Thank you so much. It was not a waste at all, and thank you for having me. I learned a lot from your questions and your remarks. Thank you. Thank you. Thanks for listening to this conversation with Avi Loeb, and thank you to our sponsors. Zero Fasting App for intermittent fasting, Element Electrolyte Drink, Sun Basket Meal Delivery Service, and Pessimist Archive History Podcast. So the choice is a fasting app, fasting fuel, fast-breaking delicious meals, and a history podcast that has very little, as far as I know, to do with fasting. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you with some words from Albert Einstein. The important thing is not to stop questioning. Curiosity has its own reason for existence. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day. Thank you for listening, and hope to see you next time.

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Daniel Schmachtenberger: Steering Civilization Away from Self-Destruction | Lex Fridman Podcast #191

The following is a conversation with Daniel Schmachtenberger, a founding member of the Consilience Project that is aimed at improving public sensemaking and dialogue. He's interested in understanding how we humans can be the best version of ourselves as individuals and as collectives at all scales. Quick mention of our sponsors, Ground News, NetSuite, Four Sigmatic, Magic Spoon, and BetterHelp. Check them out in the description to support this podcast. As a side note, let me say that I got a chance to talk to Daniel on and off the mic for a couple of days. We took a long walk the day before our conversation. I really enjoyed meeting him, just on a basic human level. We talked about the world around us with words that carried hope for us individual ants actually contributing something of value to the colony. These conversations are the reasons I love human beings, our insatiable striving to lessen the suffering in the world. But more than that, there's a simple magic to two strangers meeting for the first time and sharing ideas, becoming fast friends, and creating something that is far greater than the sum of our parts. I've gotten to experience some of that same magic here in Austin with a few new friends and in random bars in my travels across this country, where a conversation leaves me with a big stupid smile on my face and a new appreciation of this too short, too beautiful life. This is the Lex Friedman Podcast, and here is my conversation with Daniel Schmachtenberger. If aliens were observing Earth through the entire history, just watching us, and we're tasked with summarizing what happened until now, what do you think they would say? What do you think they would write up in that summary? Like it has to be pretty short, less than a page. Like in Hitchhiker's Guide, Hitchhiker's Guide, there's I think like a paragraph or a couple sentences. How would you summarize, sorry, how would the aliens summarize, do you think, all of human civilization? My first thoughts take more than a page. They'd probably distill it. Because if they watched, well I mean first, I have no idea if their senses are even attuned to similar stuff to what our senses are attuned to, or what the nature of their consciousness is like relative to ours. So let's assume that they're kind of like us, just technologically more advanced to get here from wherever they are. That's the first kind of constraint on the thought experiment. And then if they've watched throughout all of history, they saw the burning of Alexandria, they saw that 2,000 years ago in Greece, we were producing things like clocks, the Antikythera mechanism, and then that technology got lost. They saw that there wasn't just a steady dialectic of progress. So every once in a while there's a giant fire that destroys a lot of things. There's a giant like commotion that destroys a lot of things. Yeah, and it's usually self-induced. They would have seen that. And so as they're looking at us now, as we move past the nuclear weapons age into the full globalization, Anthropocene, exponential tech age, still making our decisions relatively similarly to how we did in the Stone Age as far as rivalry game theory type stuff, I think they would think that this is probably most likely one of the planets that is not going to make it to being intergalactic because we blow ourselves up in the technological adolescence. And if we are going to, we're going to need some major progress rapidly in the social technologies that can guide and bind and direct the physical technologies so that we are safe vessels for the amount of power we're getting. Actually, Hitchhiker's Guide has an estimation about how much of a risk this particular thing poses to the rest of the galaxy. And I think, I forget what it was, I think it was medium or low. So their estimation would be that this species of ant-like creatures is not going to survive long. There's ups and downs in terms of technological innovation. The fundamental nature of their behavior from a game theory perspective hasn't really changed. They have not learned in any fundamental way how to control and properly incentivize or properly do the mechanism design of games to ensure long-term survival. And then they move on to another planet. Do you think there is, in a more, slightly more serious question, do you think there's some number or perhaps a very, very large number of intelligent alien civilizations out there? Yes. Would be hard to think otherwise. I know, I think Bostrom had a new article not that long ago on why that might not be the case, that the Drake equation might not be the kind of in-story on it. But when I look at the total number of Kepler planets just that we're aware of just galactically and also like when that, when those life forms were discovered in Mono Lake that didn't have the same six primary atoms, I think it had arsenic replacing phosphorus as one of the primary aspects of its energy metabolism. We get to think about that the building blocks might be more different. So the physical constraints, even that the planets have to have might be more different. It seems really unlikely, not to mention interesting things that we've observed that are still unexplained. As you had guests on your show discussing Tic Tac and... Oh, the ones that have visited. Yeah. Well, let's dive right into that. What do you make sense of the rich human psychology of there being hundreds of thousands, probably millions of witnesses of UFOs of different kinds on earth, most of which I presume are conjured up by the human mind through the perception of through the perception of system. Some number might be true, some number might be reflective of actual physical objects, whether it's drones or testing military technology that's secret or other worldly technology. What do you make sense of all of that? Because it's gained quite a bit of popularity recently. There's some sense of which that's us humans being hopeful and dreaming of other worldly creatures as a way to escape the dreariness of the human condition. But in another sense, it really could be something truly exciting that science should turn its eye towards. So where do you place it? Speaking of turning eye towards, this is one of those super fascinating, actually super consequential possibly topics that I wish I had more time to study and just haven't allocated. So I don't have firm beliefs on this because I haven't got to study it as much as I want. So what I'm going to say comes from a superficial assessment. While we know there are plenty of things that people thought of as UFO sightings that we can fully write off, we have other better explanations for them. What we're interested in is the ones that we don't have better explanations for and then not just immediately jumping to a theory of what it is, but holding it as unidentified and being curious and earnest. I think the Tic Tac one is quite interesting and made it in major media recently. But I don't know if you ever saw the Disclosure Project. A guy named Stephen Greer organized a bunch of mostly US military and some commercial flight people who had direct observation and classified information disclosing it at a CNN briefing. And so you saw high-ranking generals, admirals, fighter pilots all describing things that they saw on radar with visual, with their own eyes or cameras, and also describing some phenomena that had some consistency across different people. And I find this interesting enough that I think it would be silly to just dismiss it. And specifically, we can ask the question, how much of it is natural phenomena, ball lightning or something like that? And this is why I'm more interested in what fighter pilots and astronauts and people who are trained in being able to identify flying objects and atmospheric phenomena have to say about it. I think the thing, then you could say, well, are they more advanced military craft? Is it some kind of human craft? The interesting thing that a number of them describe is something that's kind of like right angles at speed, or if not right angles, acute angles at speed, but something that looks like a different relationship to inertia than physics makes sense for us. I don't think that there are any human technologies that are doing that even in really deep underground black projects. Now, one could say, okay, well, could it be a hologram? But would it show up on radar if radar is also seeing it? And so, I don't know. I think there's enough. I mean, and for that to be a massive coordinated psyop, is it as interesting and ridiculous in a way as the idea that it's UFOs from some extra planetary source? So it's up there on the interesting topics. To me, if it is at all alien technology, it is the dumbest version of alien technologies. It's so far away. It's like the old, old crappy VHS tapes of alien technology. These are like crappy drones that just floated or even like space to the level of like space junk because it is so close to our human technology. We talk about it moves in ways that's unlike what we understand about physics, but it still has very similar kind of geometric notions and something that we humans can perceive with our eyes, all those kinds of things. I feel like alien technology most likely would be something that we would not be able to perceive, not because they're hiding, but because it's so far advanced that it would be much, much, it would be beyond the cognitive capabilities of us humans. Just as you were saying, as per your answer for aliens summarizing earth, it's the starting assumption is they have similar perception systems. They have similar cognitive capabilities and that very well may not be the case. Let me ask you about staying in aliens for just a little longer because I think it's a good transition talking about governments and human societies. Do you think if a US government or any government was in possession of an alien spacecraft or of information related to alien spacecraft, they would have the capacity structurally? Would they have the processes? Would they be able to communicate that to the public effectively or would they keep it secret in a room and do nothing with it, both to try to preserve military secrets, but also because of the incompetence that's inherent to bureaucracies or either? Well, we can certainly see when certain things become declassified 25 or 50 years later that there were things that the public might've wanted to know that were kept secret for a very long time for reasons of at least supposedly national security, which is also a nice source of plausible deniability for people covering their ass for doing things that would be problematic and other purposes. There's a scientist at Stanford who supposedly got some material that was recovered from Area 51 type area, did analysis on it using, I believe, electron microscopy and a couple other methods and came to the idea that it was a nanotech alloy that was something we didn't currently have the ability to do, was not naturally occurring. I've heard some things. And again, like I said, I'm not going to stand behind any of these because I haven't done the level of study to have high confidence. I think what you said also about would it be super low-tech alien craft, would they necessarily move their atoms around in space? Or might they do something more interesting than that? Might they be able to have a different relationship to the concept of space or information or consciousness? One of the things that the craft supposedly do is not only accelerate and turn in a way that looks non-inertial but also disappear. So there's a question as to, the two are not necessarily mutually exclusive. And it could be possible to some people run a hypothesis that they create intentional amounts of exposure as an invitation of a particular kind. Who knows? Interesting field. We tend to assume like SETI, that's listening out for aliens out there, I've just been recently reading more and more about gravitational waves. And you have orbiting black holes that orbit each other, they generate ripples in space-time. On my, for fun at night when I lay in bed, I think about what it would be like to ride those waves when they, not the low magnitude they are as when they reach Earth, but get closer to the black holes. Because it would basically be shrinking and expanding us in all dimensions, including time. So it's actually ripples through space-time that they generate. Why is it that you couldn't use that? It travels at the speed of light. Travels at a speed, which is a very weird thing to say when you're morphing space-time. It's, you could argue it's faster than the speed of light. So if you're able to communicate by, to summon enough energy to generate black holes and to orbit, to force them to orbit each other, why not travel as the ripples in space-time? Whatever the hell that means. Somehow combined with wormholes. So if you're able to communicate through, like we don't think of gravitational waves as something you can communicate with because the, the black holes are just, gravitational waves is something you can communicate with because the, the radio will be, have to be a very large size and very dense, but perhaps that's it. You know, perhaps that's one way to communicate. It's a very effective way. And that would explain, like, we wouldn't even be able to make sense of that, of the physics that results in an alien species that's able to control gravity at that scale. I think you just jumped up the Kardashev scale so far. So you're not just harnessing the power of a star, but harnessing the power of mutually rotating black holes. I, that's way above my physics pay grade to think about including even non-rotating black hole versions of transwarp travel. I think, you know, you can talk with Eric more about that. I think he has better ideas on it than I do. My hope for the future of humanity mostly does not rest in the near term on our ability to get to other habitable planets in time. And even more than that, in the list of possible solutions of how to improve human civilization, orbiting black holes is not in the, on the first page for you. Not on the first page. Okay. I bet you did not expect us to start this conversation here, but I'm glad the places it went. I am excited on a much smaller scale of Mars, Europa, or Titan, Venus, potentially having very like bacteria-like life forms, just on a, on a small human level. It's a little bit scary, but mostly really exciting that there might be life elsewhere in the volcanoes, in the oceans, all around us, teeming, having little societies. And whether there's properties about that kind of life that's somehow different than ours. I don't know what would be more exciting if those colonies of single cell type organisms, what would be more exciting if they're different or if they're the same? If they're the same, that means through the rest of the universe, there's life forms like us, something like us everywhere. If they're different, that's also really exciting because there's life forms everywhere. They're not like us. That's a little bit scary. I don't know what's scarier actually. I think both scary and exciting no matter what, right? The idea that they could be very different is philosophically very interesting for us to open our aperture on what life and consciousness and self-replicating possibilities could look like. The question on are they different or the same? Obviously, there's lots of life here that is the same in some ways and different in other ways. When you take the thing that we call an invasive species is something that's still pretty the same hydrocarbon-based thing, but co-evolved with co-selective pressures in a certain environment, we move it to another environment, it might be devastating to that whole ecosystem because it's just different enough that it messes up the self-stabilizing dynamics of that ecosystem. The question of would they be different in ways where we could still figure out a way to inhabit a biosphere together or fundamentally not? Fundamentally, the nature of how they operate and the nature of how we operate would be incommensurable is a deep question. Well, we offline talked about mimetic theory, right? It seems like if they were sufficiently different, where we would not even, we can coexist on different planes, it seems like a good thing. If we're close enough together to where we'd be competing, then you're getting into the world of viruses and pathogens and all those kinds of things to where we would, one of us would die off quickly through basically mass murder without even- Even accidentally. Even accidentally. If we just had a self-replicating single-celled kind of creature that happened to not work well for the hydrocarbon life that was here, they got introduced because either output something that was toxic or utilized up the same resource too quickly and it just replicated faster and mutated faster. It wouldn't be a mimetic theory, conflict theory kind of harm. It would just be a von Neumann machine, a self-replicating machine that was fundamentally incompatible with these kinds of self-replicating systems with faster OODA loops. For one final time, putting your alien-god hat on and you look at human civilization, do you think about the 7.8 billion people on earth as individual little creatures, individual little organisms, or do you think of us as one organism with a collective intelligence? What's the proper framework through which to analyze it again as an alien? So that I know where you're coming from, when you have asked the question the same way before the Industrial Revolution, before the Agricultural Revolution, when there were half a billion people and no telecommunications connecting them? I would indeed ask the question the same way, but I would be less confident about your conclusions. It would be an actually more interesting way to ask the question at that time, but I would nevertheless ask it the same way, yes. Well, let's go back further and smaller then, rather than just a single human or the entire human species, let's look at a relatively isolated tribe. Yes. In the relatively isolated, probably sub-Dunbar number, sub-150 people tribe, do I look at that as one entity where evolution is selecting for it based on group selection, or do I think of it as 150 individuals that are interacting in some way? Well, could those individuals exist without the group? No. The evolutionary adaptiveness of humans was involved critically group selection and individual humans alone trying to figure out stone tools and protection and whatever aren't what was selected for. And so I think the or is the wrong frame. I think it's individuals are affecting the group that they're a part of. They're also dependent upon and being affected by the group that they're part of. And so this now starts to get in deep into political theories also, which is theories that orient towards the collective at different scales, whether a tribal scale or an empire, a nation state or something. And ones that orient towards the individual liberalism and stuff like that. And I think there's very obvious failure modes on both sides. And so the relationship between them is more interesting to me than either of them. The relationship between the individual and the collective and the question around how to have a virtuous process between those. So a good social system would be one where the organism of the individual and the organism of the group of individuals is they're both synergistic to each other. So what is best for the individuals and what's best for the collective is what's best for the collective is what's best for the collective is what's best for the whole is aligned. But there is nevertheless an individual. They're not, it's a matter of degrees, I suppose. But what defines a human more? The social network within which they've been brought up, through which they've developed their intelligence, or is it their own sovereign individual self? Like what's your intuition of how much, not just for evolutionary survival, but as intellectual beings, how much do we need others for our development? Yeah, I think we have a weird sense of this today, relative to most previous periods of sapien history. I think the vast majority of sapien history is tribal, like depending upon your early human model, two or 300,000 years of homo sapiens in little tribes, where they depended upon that tribe for survival and excommunication from the tribe was fatal. I think they, and our whole evolutionary genetic history is in that environment. And the amount of time we've been out of it is relatively so tiny. And then we still depended upon extended families and local communities more. And the big kind of giant market complex where I can provide something to the market to get money to be able to get other things from the market where it seems like I don't need anyone, it's almost like disintermediating our sense of need, even though your and my ability to talk to each other using these mics and the phones that we coordinated on took millions of people over six continents to be able to run the same thing. It took six continents to be able to run the supply chains that made all the stuff that we depend on, but we don't notice that we depend upon them. They all seem fungible. If you take a baby, obviously, you didn't even get to a baby without a mom, was it dependent on each other, right? Without two parents at minimum, and they depended upon other people. But if we take that baby and we put it out in the wild, it obviously dies. So if we let it grow up for a little while, the minimum amount of time where it starts to learn the language, and then we put it out in the wild, and this has happened a few times, it doesn't learn language. And it doesn't learn the small motor articulation that we learn. It doesn't learn the type of consciousness that we end up having that is socialized. So I think we take for granted how much conditioning affects us. Is it possible that it affects basically 99.9 or maybe the whole thing? The whole thing is the connection between us humans, and that we're no better than apes without our human connections. Because thinking of it that way forces us to think very differently about human society and how to progress forward if the connections are fundamental. I just have to object to the no better than apes, because better here, I think you mean a specific thing, which means have capacities that are fundamentally different than. I think apes also depend upon troops. Yes. And I think the idea of humans as better than nature in some kind of ethical sense ends up having heaps of problems. We'll table that. We can come back to it. But when we say what is unique about homo sapien capacity relative to the other animals we currently inhabit the biosphere with? And I'm saying it that way because there were other early hominids that had some of these capacities, we believe. Our tool creation and our language creation and our coordination are all kind of the results of a certain type of capacity for abstraction. And other animals will use tools, but they don't evolve the tools they use. They keep using the same types of tools that they basically can find. So a chimp will notice that a rock can cut a vine that it wants to, and it'll even notice that a sharper rock will cut it better. And experientially, it'll use the sharper rock. And if you even give it a knife, it'll probably use the knife because it's experiencing the effectiveness. But it doesn't make stone tools because that requires understanding why one is sharper than the other. What is the abstract principle called sharpness to then be able to invent a sharper thing? That same abstraction makes language and the ability for abstract representation, which makes the ability to coordinate in a more advanced set of ways. So I do think our ability to coordinate with each other is pretty fundamental to the selection of what we are as a species. Lex Domogaroff I wonder if that coordination, that connection is actually the thing that gives birth to consciousness, that gives birth to, well, let's start with self-awareness. David Sterret It's more like theory of mind. Lex Domogaroff Theory of mind. Yeah. I mean, I suppose there's experiments that show that there's other mammals that have a very crude theory of mind. I'm not sure. Maybe dogs, something like that. But actually, dogs probably has to do with that they co-evolved with humans. See, it'd be interesting if that theory of mind is what leads to consciousness in the way we think about it. It's the richness of the subjective experience that is consciousness. I have an inkling sense that that only exists because we're social creatures. That doesn't come with the hardware and the software in the beginning. That's learned as an effective tool for communication almost. I think we think that consciousness is fundamental. Maybe it's not. There's a bunch of folks kind of criticize the idea that the illusion of consciousness is consciousness, that it is just a facade we use to help us construct theories of mind. You almost put yourself in the world as a subjective being. In that experience, you want to richly experience it as an individual person so that I could empathize with your experience. I find that notion compelling, mostly because it allows you to then create robots that become conscious not by being quote-unquote conscious, but by just learning to fake it till they make it. Present a facade of consciousness with the task of making that facade very convincing to us humans, and thereby it will become conscious. Have a sense that in some way that will make them conscious if they're sufficiently convincing to humans. Is there some element of that that you find convincing? This is a much harder set of questions and deep end of the pool than starting with the aliens was. We went from aliens to consciousness. This is not the trajectory I was expecting, nor you, but let us walk a while. We can walk a while and I don't think we will do it justice. So, what do we mean by consciousness versus conscious self-reflective awareness? What do we mean by awareness, qualia, theory of mind? There's a lot of terms that we think of as slightly different things and subjectivity, first person. I don't remember exactly the quote, but I remember when reading when Sam Harris wrote the book Free Will and then Dennett critiqued it. And then there was some writing back and forth between the two, because normally they're on the same side of kind of arguing for critical thinking and logical fallacies and philosophy of science against supernatural ideas. And here Dennett believed there is something like free will. He is a determinist compatibilist, but no consciousness and radical limitivist. And Sam was saying, no, there is consciousness, but there's no free will. And that's like the most fundamental kinds of axiomatic senses they disagreed on, but neither of them could say it was because the other one didn't understand the philosophy of science or logical fallacies. And they kind of spoke past each other. And at the end, if I remember correctly, Sam said something that I thought was quite insightful, which was to the effect of, it seems it because they weren't making any progress in shared understanding. It seems that we simply have different intuitions about this. And what you could see was that what the words meant, right, at the level of symbol grounding might be quite different. One of them might have had deeply different enough life experiences that what is being referenced and then also different associations of what the words mean. This is why when trying to address these things, Charles Sanders Peirce said the first philosophy has to be semiotics, because if you don't get semiotics right, we end up importing different ideas and bad ideas right into the nature of the language that we're using. And then it's very hard to do epistemology or ontology together. So, I'm saying this to say why I don't think we're going to get very far is I think we would have to go very slowly in terms of defining what we mean by words and fundamental concepts. Well, and also allowing our minds to drift together for a time so that our definitions of these terms align. I think there's some, there's a beauty that some people enjoy with Sam that he is quite stubborn on his definitions of terms without often clearly revealing that definition. So, in his mind, he can, like, you could sense that he can deeply understand what he means exactly by a term like free will and consciousness. And you're right. He's very, he's very specific in fascinating ways that not only does he think that free will is an illusion, he thinks he's able, not thinks, he says he's able to just remove himself from the experience of free will and just be like for minutes at a time, hours at a time, like really experiences if he has no free will. Like he's a leaf flowing down the river. And given that, he's very sure that consciousness is fundamental. So, here's this conscious leaf that's subjectively experiencing the floating and yet has no ability to control and make any decisions for itself. It's only a, the decisions have all been made. There's some aspect to which the terminology there perhaps is the problem. So, that's a particular kind of meditative experience. And the people in the Vedantic tradition and some of the Buddhist traditions thousands of years ago described similar experiences and somewhat similar conclusions, some slightly different. There are other types of phenomenal experience that are the phenomenal experience of pure agency. And, you know, like the Catholic theologian but evolutionary theorist, Desjardins describes this. And that rather than a creator agent God in the beginning, there's a creative impulse or a creative process. And he would go into a type of meditation that identified as the pure essence of that kind of creative process. And I think the types of experience we've had and then one, the types of experience we've had make a big deal to the nature of how we do symbol grounding. The other thing is the types of experiences we have can't not be the same. The types of experiences we have can't not be interpreted through our existing interpretive frames. And most of the time our interpretive frames are unknown even to us, some of them. And so, this is a tricky topic. So, I guess there's a bunch of directions we could go with it. But I want to come back to what the impulse was that was interesting around what is consciousness and how does it relate to us as social beings? And then to the possibility of consciousness with AIs. Right. You're keeping us on track, which is wonderful. You're a wonderful hiking partner. Okay. Yes. Let's go back to the initial impulse of what is consciousness and how does the social impulse connect to consciousness? Is consciousness a consequence of that social connection? I'm going to state a position and not argue it because it's honestly like it's a long, hard thing to argue and we can totally do it another time if you want. I don't subscribe to consciousness as an emergent property of biology or neural networks. Obviously, a lot of people do. Obviously, the philosophy of science orients towards that in not absolutely but largely. I think of the nature of first person, the universe of first person, of qualia as experience, sensation, desire, emotion, phenomenology, but the felt sense, not the we say emotion and we think of a neurochemical pattern or an endocrine pattern. But all of the physical stuff, the third person stuff has position and momentum and charge and stuff like that that it's not. It's not a quantum and charge and stuff like that that is measurable, repeatable. I think of the nature of first person and third person as ontologically orthogonal to each other, not reducible to each other. They're different kinds of stuff. And so I think about the evolution of third person that we're quite used to thinking about from subatomic particles to atoms to molecules to on and on. I think about a similar kind of and corresponding evolution in the domain of first person from the way Whitehead talked about kind of prehension or proto qualia and earlier phases of self organization into higher orders of it and that there's correspondence, but that neither like the idealists do we reduce third person to first person, which is what idealists do, or neither like the physicalists do we reduce first person to third person. Obviously, Bohm talked about an implicate order that was deeper than and gave rise to the explicate order of both. Nagel talks about something like that. I have a slightly different sense of that. But again, I'll just kind of not argue how that occurs for a moment and say, so rather than say, does consciousness emerge from I'll talk about do higher capacities of consciousness emerge in relationship with. So it's not first person as a category emerging from third person, but increased complexity within the nature of first person and third person co-evolving. Do I think that it seems relatively likely that more advanced neural networks have deeper phenomenology, more complex, where it goes just from basic sensation to emotion to social awareness to abstract cognition to self-reflexive abstract cognition? Yeah. But I wouldn't say that's the emergence of consciousness. I would say it's increased complexity within the domain of first person corresponding to increased complexity and the corresponding domain of first person is the domain of first person. And the correspondence should not automatically be seen as causal. We can get into the arguments for why that often is the case. So would I say that obviously the sapien brain is pretty unique and a single sapien now has that, right? Even if it took sapiens evolving in tribes based on group selection to make that brain. So the group made it. Now that brain is there. Now, if I take that a single person with that brain out of the group and try to raise them they'll still not be very interesting even with the brain. But the brain does give hardware capacities that if conditioned in relationship can have interesting things emerge. So do I think that the human biology, types of human consciousness and types of social interaction all co-emerged and co-evolved? Yes. As a small aside, as you're talking about the biology, let me comment that I spent, this is what I do. This is what I do with my life. This is why I will never accomplish anything. Is I spent much of the morning trying to do research on how many computations the brain performs and how much energy it uses versus the state of the AR, CPUs and GPUs. Arriving at about 20 quadrillion. So that's two to the 10 to the 16 computations. So synaptic firings per second that the brain does. And that's about a million times faster than the, let's say the 20 thread state of the arts Intel CPU, the 10th generation. And then there's similar calculation for the GPU and all ended up also trying to compute that it takes 10 watts to run the brain about. And then what does that mean in terms of calories per day, kilocalories? That's about two, for an average human brain, that's 250 to 300 calories a day. And so it ended up being a calculation where you're doing about 20 quadrillion calculations that are fueled by something like, depending on your diet, three bananas. So three bananas results in a computation that's about a million times more powerful than the current state of the art computers. Now let's take that one step further. There's some assumptions built in there. The assumption is that one, what the brain is doing is just computation. Two, the relevant computations are synaptic firings and that there's nothing other than synaptic firings that we have to factor. So I'm forgetting his name right now, there's a very famous neuroscientist at Stanford just passed away recently who did a lot of the pioneering work on glial cells and showed that his assessment glial cells did a huge amount of the thinking, not just neurons. And it opened up this entirely different field of like what the brain is and what consciousness is. You look at Damasio's work on embodied cognition and how much of what we would consider consciousness or feeling is happening outside of the nervous system completely, happening in endocrine process involving lots of other cells and signal communication. You talk to somebody like Penrose who you've had on the show, and even though the Penrose Hammerhoff conjecture is probably not right, is there something like that that might be the case where we're actually having to look at stuff happening at the level of quantum computation and microtubules? I'm not arguing for any of those. I'm arguing that we don't know how big the unknown unknown set is. Well, at the very least, this has become like an infomercial for the human brain. At the very, but wait, there's more. At the very least, the three bananas buys you a million times. At the very least. At the very least. It's impressive. And then you could have, and then the synaptic firings we're referring to is strictly the electrical signals that could be the mechanical transmission of information that exists, chemical transmission of information, there's all kinds of other stuff going on, and then there's memory that's built in that's also all tied in. Not to mention, which I'm learning more and more about, it's not just about the neurons, it's also about the immune system that's somehow helping with the computation. So it's the entirety and the entire body's helping with the computation. So the three bananas. It could buy you a lot. It could buy you a lot. It could buy you a lot, but on the topic of sort of the greater degrees of complexity emerging in consciousness, I think few things are as beautiful and inspiring as taking a step outside of the human brain, just looking at systems or simple rules create incredible complexity, not create, incredible complexity emerges. So one of the simplest things to do that with is cellular automata. And there's, I don't know what it is, and maybe you can speak to it. We can certainly, we will certainly talk about the implications of this, but there's so few things that are as awe-inspiring to me as knowing the rules of a system and not being able to predict what the heck it looks like. And it creates incredibly beautiful complexity that when zoomed out on, looks like there's actual organisms doing things that are much, that operate on a scale much higher than the underlying mechanism. So with cellular automata, that's cells that are born and die, born or die, and they only know about each other's neighbors, and there's simple rules that govern that interaction of birth and death. And then they create, at scale, organisms that look like they take up hundreds or thousands of cells, and they're moving. They're moving around, they're communicating, they're sending signals to each other, and you forget, at moments at a time, before you remember, that the simple rules on cells is all that it took to create that. It's sad in that we can't come up with a simple description of that system that generalizes the behavior of the large organisms. We can only come up, we can only hope to come up with the thing, the fundamental physics or the fundamental rules of that system, I suppose. It's sad that we can't predict. Everything we know about the mathematics of those systems, it seems like we can't really in a nice way, like economics tries to do, to predict how this whole thing will unroll. But it's beautiful because how simple it is underneath it all. So, what do you make of the emergence of complexity from simple rules? What the hell is that about? Yeah. Well, we can see that something like flocking behavior, the murmuration, can be computer coded. It's not a very hard set of rules to be able to see some of those really amazing types of complexity. And the whole field of complexity science and some of the sub-disciplines like science, like stigmurgy are studying how following fairly simple responses to a pheromone signal do ant colonies do this amazing thing where what you might describe as the organizational or computational capacity of the colony is so profound relative to what each individual ant is doing. I am not anywhere near as well versed in the cutting edge of cellular automatas I would like, unfortunately. In terms of topics that I'm interested in, I'm not really interested in. I, in terms of topics that I would like to get to and haven't like, ET is more, Wolfram is a new kind of science I have only skimmed and read reviews of and not read the whole thing or his newer work since. But his idea of the four basic kind of categories of emergent phenomena that can come from cellular automata and that one of them is kind of interesting and looks a lot like complexity rather than just chaos or homogeneity or self-termination or whatever. I think this is very interesting. It does not instantly make me think that biology is operating on a similarly small set of rules and or that human consciousness is. I'm not that reductionistly oriented. And so if you look at, say, Santa Fe Institute, one of the co-founders, Stuart Kauffman, his work, he should, you should really get him on your show. So a lot of the questions that you like one of Kauffman's more recent books after investigations and some of the real fundamental stuff was called Reinventing the Sacred and it had to do with some of these exact questions in kind of non-reductionist approach, but that is not just silly hippie-ism. And he was very interested in highly non-ergotic systems where you couldn't take a lot of behavior over a small period of time and predict what the behavior of subsets over a longer period of time would do. And then going further, someone who spent some time at Santa Fe Institute and then kind of made a whole new field that you should have on, Dave Snowden, who some people call the father of anthro-complexity or what is the complexity unique to humans. He says something to the effect of that modeling humans as termites really doesn't cut it. Like we don't respond exactly identically to the same pheromone stimulus using stigma G like it works for flows of traffic and some very simple human behaviors, but it really doesn't work for trying to make sense of the Sistine Chapel and Picasso and general relativity creation and stuff like that. And it's because the termites are not doing abstraction, forecasting deep into the future and making choices now based on forecasts of the future, not just adaptive signals in the moment and evolutionary code from history. That's really different, right? Like making choices now that can factor deep modeling of the future. And with humans, our uniqueness one to the next in terms of response to similar stimuli is much higher than it is with a termite. One of the interesting things there is that their uniqueness is extremely low. They're basically fungible. Within a class, right, there's different classes, but within a class, they're basically fungible and their system uses that very high numbers and lots of loss, right? Lots of death and loss. But do you think the termite feels that way? Don't you think we humans are deceiving ourselves about our uniqueness? Perhaps it doesn't just, isn't there some sense in which this emergence just creates different higher and higher levels of abstraction where every layer, each organism feels unique? Is that possible? That we're all equally dumb but on different scales? No, I think uniqueness is evolving. I think that hydrogen atoms are more similar to each other than cells of the same type are. And I think that cells are more similar to each other than humans are. And I think that highly K-selected species are more unique than R-selected species. So they're different evolutionary processes. The R-selected species where you have a whole, a lot of death and very high birth rates, you're not looking for as much individuality within or individual possible expression to cover the evolutionary search space within an individual. You're looking at it more in terms of a numbers game. So yeah, I would say there's probably more difference between one orca and the next than there is between one Cape buffalo and the next. Given that, it would be interesting to get your thoughts about mimetic theory where we're imitating each other in the context of this idea of uniqueness. How much truth is there to that? How compelling is this worldview to you of Girardian mimetic theory of desire where maybe you can explain it from your perspective, but it seems like imitating each other is the fundamental property of the behavior of human civilization? Well, imitation is not unique to humans, right? Monkeys imitate. So a certain amount of learning through observing is not unique to humans. Humans do more of it. It's actually kind of worth speaking to this for a moment. Monkeys can learn new behaviors. New we've even seen teaching an ape sign language and then the ape teaching other apes sign language. So that's a kind of mimesis, right? Kind of learning through imitation. And that needs to happen if they need to learn or develop capacities that are not just coded by their genetics, right? So within the same genome, they're learning new things based on the environment. And so based on someone else learned something first. And so let's pick it up. How much a creature is the result of just its genetic programming and how much it's learning is a very interesting question. And I think this is a place where humans really show up radically different than everything else. And you can see it in the in the neoteny, how long we're basically fetal. That a the closest ancestors to us, if we look at a chimp, a chimp can hold on to its mother's fur while she moves around day one. And obviously, we see horses up and walking within 20 minutes. The fact that it takes a human a year to be walking and it takes a horse 20 minutes and you say how many multiples of 20 minutes go into a year like that's a long period of helplessness that wouldn't work for a horse, right? Like they or anything else. And and not only can we not hold on to mom in the first day, it's three months before we can move our head volitionally. So it's like, why why are we embryonic for so long? Basically, it's like like it's still fetal on the outside had to be because couldn't keep growing inside and actually ever get out with big heads and narrower hips from going upright. So here's a place where there's a co evolution of the pattern of humans, specifically here are our neoteny and what that portends to learning with our own genetic programming with our being tool making and environment modifying creatures, which is because we have the abstraction to make tools, we change our environments more than other creatures change their environments. The next most environment modifying creature to us is like a beaver. And then you were in L.A., you fly into L.A. X and you look at the just orthogonal grid going on forever in all directions. And, you know, we've recently come into the Anthropocene where the surface of the earth is changing more from human activity than geological activity. And then beavers and you're like, OK, well, we're really in a class of our own in terms of environment modifying. Yeah. So as soon as we started tool making, we were able to change our environments much more radically. We could put on clothes and go to a cold place. Right. And this is really important because we actually went and became apex predators in every environment. We functioned like apex predators, but polar bear can't leave the Arctic. Right. And the lion can't leave the savanna and an orca can't leave the ocean. And we went and became apex predators in all those environments because of our tool creation capacity. We could become better predators than them adapted to the environment, or at least with our tools adapted to the environment. So in every aspect towards any organism in any environment, we're incredibly good at becoming apex predators. Yes. And nothing else can do that kind of thing. There is no other apex predator that you see. The other apex predator is only getting better at being a predator through evolutionary process that's super slow. And that super slow process creates co-selective process with their environment. So as the predator becomes a tiny bit faster, it eats more of the slow prey, the genes of the fast prey and breed and the prey becomes faster. And so there's this kind of balancing. And we, because of our tool making, we increased our predatory capacity faster than anything else could increase its resilience to it. As a result, we started outstripping the environment and extincting species following stone tools and going and becoming apex predator everywhere. This is why we can't keep applying apex predator theories because we're not an apex predator. We're an apex predator, but we're something much more than that. Like just for an example, the top apex predator in the world, an orca. An orca can eat one big fish at a time, like one tuna, and it'll miss most of the time or one seal. And we can put a mile long drift net out on a single boat. And pull up an entire school of them, right? We can deplete the entire oceans of them. That's not an orca, right? Like that's not an apex predator. And that's not even including that we can then genetically engineer different creatures. We can extinct species, we can devastate whole ecosystems, we can make built worlds that have no natural things that are just human built worlds. We can build new types of natural creatures, synthetic life. So we are much more like little gods than we are like apex predators now. But we're still behaving as apex predators and little gods that behave as apex predators causes a problem, kind of core to my assessment of the world. So what does it mean to be a predator? So a predator is somebody that effectively can mine the resources from a place, so for their survival? Or is it also just purely like higher level objectives of violence? And what is, can predators be predators towards the same, each other, towards the same species? Like are we using the word predator sort of generally, which then connects the conflict and military conflict, violent conflict in the space of human species? Obviously, we can say that plants are mining the resources of their environment in a particular way, using photosynthesis to be able to pull minerals out of the soil and nitrogen and carbon out of the air and like that. And we can say herbivores are being able to mine and concentrate that. So I wouldn't say mining the environment is unique to predator. Predator is, you know, generally being defined as mining other animals, right? We don't consider herbivores predators, but animal, which requires some type of violence capacity because animals move, plants don't move. So it requires some capacity to overtake something that can move and try to get away. We'll go back to the Gerard thing, then we'll come back here. Why are we Neotenous? Why are we embryonic for so long? Because are we, did we just move from the savanna to the Arctic and we need to learn new stuff? If we came genetically programmed, we would not be able to do that. Are we throwing spears or are we fishing or are we running an industrial farm? Are we running an industrial supply chain or are we texting? What is the adaptive behavior? Horses today in the wild and horses 10,000 years ago were doing pretty much the same stuff. And so since we make tools and we evolve our tools and then change our environment so quickly and other animals are largely the result of their environment, but we're environment modifying so rapidly, we need to come without too much programming so we can learn the environment we're in, learn the language, right? Learn the language is going to be very important to learn the tool making. Learn the, and so we have a very long period of relative helplessness because we aren't coded how to behave yet because we're imprinting a lot of software on how to behave that is useful to that particular time. So our mimesis is not, it's not unique to humans, but the total amount of it is really unique. And this is also where the uniqueness can go up, right? Less just the result of the genetics and that means the kind of learning through history that they got coded in genetics and more the result of, it's almost like our hardware selected for software, right? Like if evolution is kind of doing these, think of as a hardware selection. I have problems with computer metaphors for biology, but I'll use this one here. That we have not had hardware changes since the beginning of sapiens, but our world is really, really different. And that's all changes in software, right? Changes in on the same fundamental genetic substrate, what we're doing with these brains and minds and bodies and social groups and like that. And so now Gerard specifically was looking at when we watch other people talking, so we learn language. You and I would have a hard time learning Mandarin today or it'd take a lot of work. We'd be learning how to conjugate verbs and stuff, but a baby learns it instantly without anyone even really trying to teach it just through mimesis. So it's a powerful thing. They're obviously more neuroplastic than we are when they're doing that and all their attentions allocated to that. But they're also learning how to move their bodies and they're learning all kinds of stuff through mimesis. One of the things that Gerard says is they're also learning what to want. And they learn what to want. They learn desire by watching what other people want. And so intrinsic to this, people end up wanting what other people want. And if we can't have what other people have without taking it away from them, then that becomes a source of conflict. So the mimesis of desire is the fundamental generator of conflict. And then the conflict energy within a group of people will build over time. This is a very, very crude interpretation of the theory. Can we just pause on that? For people who are not familiar and for me who hasn't, I'm loosely familiar, but I haven't internalized it, but every time I think about it, it's a very compelling view of the world, whether it's true or not. It's quite, it's like when you take everything Freud says as truth, it's a very interesting way to think about the world. And in the same way, thinking about the mimetic theory of desire, that everything we want is imitation of other people's wants. We don't have any original wants. We're constantly imitating others. And so, and not just others, but others we're exposed to. So there's these little local pockets, however defined local, of people imitating each other. And one that's super empowering because then you can pick which group you can join. Like, what do you want to imitate? It's the old, like, whoever your friends are, that's what your life is going to be like. That's really powerful. I mean, it's depressing that we're so unoriginal, but it's also liberating in that if this holds true, that we can choose our life by choosing the people we hang out with. So, okay. Thoughts that are very compelling, that seem like they're more absolute than they actually are, end up also being dangerous. So we want to- I'm going to discuss here where I think we need to amend this particular theory. But specifically, you just said something that everyone who's paid attention knows is true experientially, which is who you're around affects who you become. And as libertarian and self-determining and sovereign as we'd like to be, everybody, I think, knows that if you got put in a maximum security prison, aspects of your personality would have to adapt or you wouldn't survive there, right? You would become different. If you were- if you grew up in Darfur versus Finland, you would be different with your same genetics. Like, just, there's no real question about that. And that even today, if you hang out in a place with ultra marathoners as your roommates or all people who are obese as your roommates, the statistical likelihood of what happens to your fitness is pretty clear, right? Like, the behavioral science of this is pretty clear. So, the whole saying we are the average of the five people we spend the most time around. I think the more self-reflective someone is and the more time they spend by themselves in self-reflection, the less this is true, but it's still true. So, one of the best things someone can do to become more self-determined is be self-determined about the environments they want to put themselves in. Because to the degree that there is some self-determination and some determination by the environment, don't be fighting an environment that is predisposing you in bad directions. Try to put yourself in an environment that is predisposing the things that you want. In turn, try to affect the environment in ways that predispose positive things for those around you. Or perhaps also, there's probably interesting ways to play with this. You could probably put yourself, like, form connections that have this perfect tension in all directions to where you're actually free to decide whatever the heck you want. Because the set of wants within your circle of interactions is so conflicting. That you're free to choose whichever one. So, if there's enough tension, as opposed to everybody aligned like a flock of birds. Yeah, I mean, you definitely want that all of the dialectics would be balanced. So, if you have someone who is extremely oriented to self-empowerment and someone who's extremely oriented to kind of empathy and compassion, both, the dialectic of those is better than either of them on their own. If you have both of them inhabiting, being inhabited better than you by the same person, spending time around that person will probably do well for you. I think the thing you just mentioned is super important when it comes to cognitive schools, which is, I think, one of the fastest things people can do to improve their learning. And they're not just cognitive learning, but they're meaningful, problem-solving, communication, and civic engagement. Problem-solving, communication, and civic capacity. Capacity to participate as a citizen with other people and making the world better is to be seeking dialectical synthesis all the time. And so, in the Hegelian sense, if you have a thesis, you have an antithesis. So, maybe we have libertarianism on one side and Marxist kind of communism on the other side. And one is arguing that the individual is the unit of choice. And so, we want to increase the freedom and support of individual choice because as they make more agentic choices, it'll produce a better whole for everybody. The other side saying, well, the individuals are conditioned by their environment, who would choose to be born into Darfur rather than Finland. So, we actually need to collectively make environments that are good because the environment conditions the individuals. So, you have a thesis and an antithesis. And then Hegel's idea is you have a synthesis, which is a kind of higher order truth that understands how those relate in a way that neither of them do. And so, it is actually at a higher order of complexity. So, the first part would be, can I steel man each of these? Can I argue each one well enough that the proponents of it are like, totally, you got that? And not just argue it rhetorically, but can I inhabit it where I can try to see and feel the world the way someone seeing and feeling the world that way would? Because once I do, then I don't want to screw those people because there's truth in it. Right? And I'm not going to go back to war with them. I'm going to go to finding solutions that could actually work at a higher order. If I don't go to a higher order, then there's war. And but then the higher order thing would be, well, it seems like the individual does affect the commons and the collective and other people. It also seems like the collective conditions individuals, at least statistically. And I can cherry pick out the one guy who got out of the ghetto and pulled himself up by his bootstraps. But I can also say statistically that most people born into the ghetto show up differently than most people born into the Hamptons. And so unless you want to argue that and have you take your child from the Hamptons and put them in the ghetto, then like, come on, be realistic about this thing. So how do we make we don't want social systems that make weak, dependent individuals, right? The welfare argument. But we also don't want no social system that supports individuals to do better. We want we don't want individuals where their self-expression and agency fucks the environment and everybody else and employs slave labor and whatever. So can we make it to where individuals are creating holes that are better for conditioning other individuals? Can we make it to where we have holes that are conditioning increased agency and sovereignty? Right. That would be the synthesis. So the thing that I'm coming to here is if people have that as a frame, and sometimes it's not just thesis and antithesis, it's like eight different views, right? Can I steel man each view? This is not just can I take the perspective, but am I seeking them? Am I actively trying to inhabit other people's perspective? Then can I really try to essentialize it and argue the best points of it, both the sense making about reality and the values, why these values actually matter? Then just like I want to seek those perspectives, then I want to seek is there a higher order set of understandings that could fulfill the values of and synthesize the sense making of all of them simultaneously? Maybe I won't get it, but I want to be seeking it and I want to be seeking progressively better ones. So this is perspective seeking, driving perspective taking, and then seeking synthesis. I think that one cognitive disposition might be the most helpful thing. Would you put a title of dialectic synthesis on that process? Because that seems to be such a part, so like this rigorous empathy, like it's not just empathy, it's empathy with rigor. Like you really want to understand and embody different worldviews and then try to find a higher order synthesis. Okay. So I remember last night you told me when we first met, you said that you looked in somebody's eyes and you felt that you had suffered in some ways that they had suffered and so you could trust them. Sure. Shared pathos, right? Creates a certain sense of kind of shared bonding and shared intimacy. So empathy is actually feeling the suffering of somebody else and feeling the depth of their sentience. I don't want to fuck them anymore. I don't want to hurt them. I don't want to behave in a – I don't want my proposition to go through when I go and inhabit the perspective of the other people if they feel that's really going to mess them up, right? And so the rigorous empathy, it's different than just compassion, which is I generally care. Like I have a generalized care, but I don't know what it's like to be them. I can never know what it's like to be them perfectly and there's a humility you have to have, which is my most rigorous attempt is still not it. My most rigorous attempt, mine, to know what it's like to be a woman is still not it. I have no question that if I was actually a woman, it would be different than my best guesses. I have no question if I was actually black, it'd be different than my best guesses. So there's a humility in that which keeps me listening because I don't think that I know fully, but I want to and I'm going to keep trying better to. And then I want to across them and then I want to say, is there a way we can forward together and not have to be in war? It has to be something that could meet the values that everyone holds. It could reconcile the partial sense-making that everyone holds and it could offer a way forward that is more agreeable than the partial perspectives at war with each other. But the more you succeed at this empathy with humility, the more you're carrying the burden of other people's pain, essentially. Now this goes back to the question of do I see us as one being or 7.8 billion? I think if I'm overwhelmed with my own pain, I can't empathize that much because I don't have the bandwidth. I don't have the capacity. If I don't feel like I can do something about a particular problem in the world, it's hard to feel it because it's just too devastating. And so a lot of people go numb and even go nihilistic because they just don't feel the agency. So as I actually become more empowered as an individual and have more sense of agency, I also become more empowered to be more empathetic for others and be more connected to that shared burden and want to be able to make choices on behalf of and in benefit of. So this way of living seems like a way of living that would solve a lot of problems in society from a cellular automata perspective. So if you have a bunch of little like little agents behaving in this way, my intuition, there'll be interesting complexities that emerge, but my intuition is it will create a society that's very different and recognizably better than the one we have today. How much like... Oh, wait, hold that question because I want to come back to it, but this brings us back to Gerard, which we didn't answer. The conflict theory. Yes. Because about how to get past the conflict theory. Yes. You know the Robert Frost poem about the two paths and you never have time to turn back to the other? We're going to have to do that quite a lot. We're going to be living that poem over and over again. But yes, how to... Let's return back. Okay. So the rest of the argument goes, you learn to want what other people want, you learn to want what other people want, therefore, fundamental conflict based in our desire because we want the thing that somebody else has. And then people are in conflict over trying to get the same stuff, power, status, attention, physical stuff, a mate, whatever it is. And then we learn the conflict by watching. And so then the conflict becomes mimetic. So the... And, you know, we become on the Palestinian side or the Israeli side or the communist or the capitalist side or the left or right politically or whatever it is. And until eventually the conflict energy in the system builds up so much that some type of violence is needed to get the bad guy, whoever it is that we're going to blame. And, you know, Gerard talks about why scapegoating was kind of a mechanism to minimize the amount of violence. Let's blame a scapegoat as being more relevant than they really were. But if we all believe it, then we can all kind of calm down with the conflict energy. It's a really interesting concept, by the way. I mean, you beautifully summarized it. But the idea that there's this scapegoat, that there's this kind of thing naturally leads to a conflict. And then they find the other, some group that's the other, that's either real or artificial as the cause of the conflict. Well, it's always artificial because the cause of the conflict, and Gerard is the mimesis of desire itself. And how do we attack that? How do we attack that it's our own desire? So this now gets to something more like Buddha said, right? Which was desire is the cause of suffering. Gerard and Buddha would kind of agree in this way. So, but that explains, I mean, again, it's a compelling description of human history that we do tend to come up with the other. And okay, kind of. I just had such a funny experience with someone critiquing Gerard the other day in such an elegant and beautiful and simple way. It's a friend who's grew up Aboriginal Australian, is a scholar of Aboriginal social technologies. And he's like, nah, man, Gerard just made shit up about how tribes work. Like we come from a tribe, we've got tens of thousands of years, and we didn't have increasing conflict and then scapegoat and kill someone. We'd have a little bit of conflict and then we would dance and then everybody would be fine. Like we'd dance around the campfire, everyone would like kind of physically get the energy out. We'd look in each other's eyes, we'd have positive bonding, and then we're fine. And nobody, no scapegoats. And I think that's called the Joe Rogan theory of desire, which is he's like all of human problems have to do with the fact that you don't do enough hard shit in your day. So maybe, maybe you could just dance it because he says like doing exercise and running on the treadmill gets all the demons out and maybe just dancing gets all the demons out. So this is why I say we have to be careful with taking an idea that seems too explanatory and then taking it as a given and then saying, well, now that we're stuck with the fact that conflict is inexorable because human, because mimetic desire and therefore how do we deal with the inexorability of the conflict and how to sublimate violence? Well, no, the whole thing might be actually gibberish. Meaning it's only true in certain conditions and other conditions it's not true. So the deeper question is under which conditions is that true? Under which conditions is it not true? What are those other conditions make possible and look like? And in general, we should stay away from really compelling models of reality because there's something about our brains that these models become sticky and we can't even think outside of them. So it's not that we stay away from them. It's that we know that the model of reality is never reality. That's the key thing. Humility again, it goes back to just having the humility that you don't have a perfect model of reality. There's an, the model of reality could never be reality. The process of modeling is inherently information reduction. And I can never show that the unknown, unknown set has been factored. Back to the cellular automata. You can't, you can't put the genie back in the bottle. Like when you realize it's unfortunately, sadly, impossible to, to create a model of cellular automata. Even if you know the basic rules that predict to even any degree of accuracy, what, how that system will evolve, which is fascinating mathematically. Sorry. I think about it quite a lot. It's very annoying. Wolfram has this rule 30, like you should be able to predict it. It's so simple, but you can't predict what's going to be like, there's a, there's a problem he defines, they try to predict some aspect of the middle, middle column of the system, just anything about it, what's going to happen in the future. And you can't, you can't, it sucks. Cause then we can't make sense of this world, you know, really in all reality in a definitive way. It's always like in the striving, like we're always striving. I don't think this sucks. That so that's a feature, not a bug. Well, that's assuming a designer. I would say, I don't think it sucks. I think it's not only beautiful, but maybe necessary for beauty. The mess. So you're, so you're, you disagree Jordan Peterson. You should clean up your room. You like the rooms messy. It's a, it's essential for the, for beauty. It's not, it's not bad. It's okay. I take, I have no idea if it was intended this way. And so I'm just interpreting it a way I like the commandment about having no false idols. To me, the way I interpret that is meaningful is that reality is sacred to me. I have a reverence for reality, but I know my best understanding of it is never complete. I know my best model of it is a model where I tried to make it a little bit more realistic. Tried to make some kind of predictive capacity by reducing the complexity of it to a set of stuff that I could observe. And then a subset of that stuff that I thought was the causal dynamics and then some set of, you know, mechanisms that are involved. And what we find is that it can be super useful. Like Newtonian gravity can help us do ballistic curves and all kinds of super useful stuff. And then we get to the place where it doesn't explain what's happening at the cosmological scale or at a quantum scale. And at each time, what we're finding is we excluded stuff. And it also doesn't explain the reconciliation of gravity with quantum mechanics and the other kind of fundamental laws. So models can be useful, but they're never true with a capital T, meaning they're never an actual real full. They're never a complete description of what's happening in real systems. They can be a complete description of what's happening in an artificial system that was the result of applying a model. So the model of a circuit board and the circuit board are the same thing. But I would argue that the model of a cell and the cell are not the same thing. And I would say this is key to what we call complexity versus the complicated, which is a distinction Dave Snowden made well in defining the difference between simple, complicated, complex, and chaotic systems. But one of the definers in complex systems is that no matter how you model the complex system, it will still have some emergent behavior not predicted by the model. Can you elaborate on the complex versus the complicated? Complicated means we can fully explicate the face space of all the things that it can do. We can program it. All human, not all, for the most part, human built things are complicated. They don't self-organize. They don't self-repair. They're not self-evolving. And we can make a blueprint for them. Sorry, for human systems? For human technologies. Human technologies. Sorry. Okay, so non-analogical systems. That are basically the application of models. Right. Right. And engineering is kind of applied science, science as the modeling process. And but with- But humans are complex. Complex stuff, with biological type stuff and sociological type stuff, it more has generator functions. And even those can't be fully explicated than it has or our explanation can't prove that it has closure of what would be in the unknown, unknown set where we keep finding like, oh, it's just the genome. Oh, well, now it's the genome and the epigenome. And then a recursive change on the epigenome because of the proteome. And then there's mitochondrial DNA and then viruses affected and fuck, right? So it's like we get over excited when we think we found the thing. So on Facebook, you know how you can list your relationship as complicated? It should actually say it's complex. That's the more accurate description. You self-terminating is a really interesting idea that you talk about quite a bit. First of all, what is a self-terminating system? And I think you have a sense, correct me if I'm wrong, that human civilization as it currently is, is a self-terminating system. Why do you have that intuition combined with the definition of what self-terminating means? Okay, so if we look at human societies, historically, human civilizations, it's not that hard to realize that most of the major civilizations and empires of the past don't exist anymore. So they had a life cycle. They died for some reason. So we don't still have the early Egyptian empire or Inca or Maya or Aztec or any of those. Right. And so they terminated sometimes. They terminated, sometimes it seems like they were terminated from the outside in war. Sometimes it seems like they self-terminate. When we look at Easter Island, it was a self-termination. So let's go ahead and take an island situation. If I have an island and we are consuming the resources on that island faster than the resources can replicate themselves and there's a finite space there, that system is going to self-terminate. It's not going to be able to keep doing that thing because you'll get to a place of there's no resources left and then you get. So now if I'm utilizing the resources faster than they can replicate or faster than they can replenish and I'm actually growing our population in the process, I'm even increasing the rate of the utilization of resources. I might get an exponential curve and then hit a wall and then just collapse the exponential curve rather than do an S curve or some other kind of thing. So self-terminating system is any system that depends upon a substrate system. That is debasing its own substrate. That is debasing what it depends upon. So you're right that if you look at empires, they rise and fall throughout human history. But not this time, bro. This one's going to last forever. I like that idea. I think that if we don't understand why all the previous ones failed, we can't ensure that. And so I think it's very important to understand it well so that we can have that be a design outcome with somewhat decent probability. So we're sort of in terms of consuming the resources on the island, we're a clever bunch and we keep coming up, especially when on the horizon, there is a termination point. We keep coming up with clever ways of avoiding disaster, of avoiding collapse, of constructing. This is where technological innovation, this is where growth comes in, coming up with different ways to improve productivity and the way society functions such that we consume less resources or get a lot more from the resources we have. So there's some sense in which there is a human ingenuity is a source for optimism about the future of this particular system that may not be self-terminating. If there's more innovation than there is consumption. So overconsumption of resources is just one way a thing can self-terminate. We're just kind of starting here. But there are reasons for optimism and pessimism, then they're both worth understanding. And there's failure modes on understanding either without the other. As we mentioned previously, there's what I would call naive techno-optimism, naive techno-capital optimism. That says stuff just has been getting better and better and we wouldn't want to live in the dark ages and tech has done all this awesome stuff. And we know the proponents of those models and that stuff is going to kind of keep getting better. Of course, there are problems, but human ingenuity rises to it. Supply and demand will solve the problems, whatever. Would you put a rake as well on that or in that bucket? Is there some specific people you have in mind or naive optimism is truly naive? To where you're essentially just have an optimism that's blind to any kind of realities of the way technology progresses. I don't think that anyone who thinks about it and writes about it is perfectly naive. Gotcha. But there might be a bias in the nature of the assessment. I would also say there's kind of naive techno-pessimism. And there are critics of technology. I mean, you read the Unabomber's manifesto on why technology can't not result in our self-termination. So we have to take it out before it gets any further. But also, if you read a lot of the ex-risk community, you know, Bostrom and friends, it's like, are we going to be able to do this? It's like our total number of existential risks and the total probability of them is going up. And so I think that there are, we have to hold together where our positive possibilities and our risk possibilities are both increasing. And then say, for the positive possibilities to be realized long term, all of the catastrophic risks have to not happen. Any of the catastrophic risks have to not happen. Any of the catastrophic risks happening is enough to keep that positive outcome from occurring. So how do we ensure that none of them happen? If we want to say, let's have a civilization that doesn't collapse. So again, collapse theory. It's worth looking at books like The Collapse of Complex Societies by Joseph Tainter. It does an analysis of that many of the societies fell for internal institutional decay, civilizational decay reasons. Baudrillard in Simulation and Simulacra looks at a very different way of looking at how institutional decay and the collective intelligence of a system happens and it becomes kind of more internally parasitic on itself. Obviously, Jared Diamond made a more popular book called Collapse. And as we were mentioning, the Antikytheria mechanism has been getting attention in the news lately. It's like a 2000-year-old clock, right? Like metal gears. And does that mean we lost like 1500 years of technological progress? And from a society that was relatively technologically advanced. So what I'm interested in here is being able to say, okay, well, why did previous societies fail? Can we understand that abstractly enough that we can make a system that's not just self-terminating, but that we can make a civilizational model that isn't just trying to solve one type of failure, but solve the underlying things that generate the failures as a whole? Are there some underlying generator functions or patterns that would make a system self-terminating? And can we solve those and have that be the kernel of a new civilizational model that is not self-terminating? And can we then be able to actually look at the categories of excerpts we're aware of and see that we actually have resilience in the presence of those? Not just resilience, but anti-fragility. And I would say for the optimism to be grounded, it has to actually be able to understand the risk space well and have adequate solutions for it. Yeah. So can we try to dig into some basic intuitions about the underlying sources of catastrophic failures of the system and overconsumption that's built into self-terminating systems? So both the overconsumption, which is like the slow death, and then there's the fast death of nuclear war and all those kinds of things. AGI, biotech, bioengineering, nanotechnology, nano... My favorite, nanobots. Nanobots are my favorite because it sounds so cool to me that I could just know that I would be one of the scientists that would be full steam ahead in building them without sufficiently thinking about the negative consequences. I would definitely be... I would be podcasting all about the negative consequences, but when I go back home, I'd be... I just, in my heart, know the amount of excitement is a dumb descendant of ape. No offense to apes. So I want to backtrack on my previous comments about negative comments about apes. Negative comments about apes, that I have that sense of excitement that would result in problems. So, sorry, a lot of things said, but what's... Can we start to pull it at a thread? Because you've also provided a kind of a beautiful, general approach to this, which is this dialectic synthesis or just rigorous empathy. Whatever word we want to put to it, that seems to be, from the individual perspective, is one way to sort of live in the world as we try to figure out how to construct non-self-terminating systems. So what are some underlying sources? Yeah. First, I have to say, I actually really respect Drexler for emphasizing Grey Goo and Engines of Creation back in the day to make sure the world was paying adequate attention to the risks of the nanotech as someone who was right at the cutting edge of what could be. There's definitely game-theoretic advantage to those who focus on the opportunities and don't focus on the risks or pretend there aren't risks. Because they get to market first, and then they externalize all of the costs through limited liability or whatever it is to the commons or wherever happen to have it. Other people are going to have to solve those, but now they have the power and capital associated. The person who looked at the risks and tried to do better design and go slower is probably not going to move into positions of as much power or influence as quickly. So this is one of the issues we have to deal with, is some of the bad game-theoretic dispositions in the system relative to its own stability. And the key aspect to that, sorry to interrupt, is the externalities generated. Yes. What flavors of catastrophic risk are we talking about here? What's your favorite flavor in terms of ice cream? So mine is coconut. Nobody seems to like coconut ice cream. So ice cream aside, what are you most worried about in terms of catastrophic risk that will help us kind of make concrete the discussion we're having about how to fix this whole thing? Yeah. I think it's worth taking a historical perspective briefly to just kind of orient everyone to it. We don't have to go all the way back to the aliens who've seen all of civilization, but to just recognize that for all of human history, as far as we're aware, there were existential risks to civilizations, and they happened, right? Like there were civilizations that were killed in war, that tribes that were killed in tribal warfare, whatever. So people faced existential risk to the group that they identified with. It's just those were local phenomena, right? It wasn't a fully global phenomena. So an empire could fall, and surrounding empires didn't fall. Maybe they came in and filled the space. The first time that we were able to think about catastrophic risk, not from like a solar flare or something that we couldn't control, but from something that humans would actually create at a global level was World War II and the bomb. Because it was the first time that we had tech big enough that could actually mess up everything at a global level. It could mess up habitability. We just weren't powerful enough to do that before. It's not that we didn't behave in ways that would have done it. We just only behaved in those ways at the scale we could affect. And so it's important to get that there's the entire world before World War II, where we don't have the ability to make a non-habitable biosphere, non-habitable for us. And then there's World War II and the beginning of a completely new phase where global, human induced catastrophic risk is now a real thing. And that was such a big deal that it changed the entire world in a really fundamental way, which is, you know, when you study history, it's amazing how big a percentage of history is studying war, right? And the history of wars, you study European history, whatever, it's generals and wars and empire expansions. And so the major empires near each other never had really long periods of time where they weren't engaged in war or preparation for war or something like that. That was humans don't have a good precedent in the post tribal phase, the civilization phase of being able to solve conflicts without war for very long. World War II was the first time where we could have a war that no one could win. And so the superpowers couldn't fight again. They couldn't do a real kinetic war. They could do diplomatic wars and Cold War type stuff, and they could fight proxy wars through other countries that didn't have the big weapons. And so mutually assured destruction and like coming out of World War II, we actually realized that nation states couldn't prevent world war. And so we needed a new type of supervening government in addition to nation states, which was the whole Bretton Woods world, the United Nations, the World Bank, the IMF, the globalization trade type agreements, mutually assured destruction. That was how do we have some coordination beyond just nation states between them since we have to stop war between at least the superpowers. And it was pretty successful, given that we've had like 75 years of no superpower on superpower war. We've had lots of proxy wars during that time. We've had Cold War. And I would say we're in a new phase now where the Bretton Woods solution is basically over, almost over. Can you describe the Bretton Woods solution? Yeah, so the Bretton Woods, the series of agreements for how the nations would be able to engage with each other in a solution other than war was these IGOs, these intergovernmental organizations, and was the idea of globalization. Since we could have global effects, we needed to be able to think about things globally where we had trade relationships with each other, where it would not be profitable to war with each other. It'd be more profitable to actually be able to trade with each other. So our own self-interest was going to drive our non-war interest. And so this started to look like, and obviously this couldn't have happened that much earlier either because industrialization hadn't gotten far enough to be able to do massive global industrial supply chains and ship stuff around quickly. But like we were mentioning earlier, almost all the electronics that we use today, just basic cheap stuff for us, is made on six continents, made in many countries. There's no single country in the world that could actually make many of the things that we have, from the raw material extraction to the plastics and polymers and the, you know, et cetera. And so the idea that we made a world that could do that kind of trade and create massive GDP growth, we could all work together to be able to mine natural resources and grow stuff. With the rapid GDP growth, there was the idea that everybody could keep having more without having to take each other's stuff. And so that was part of kind of the Bretton Woods post-World War II model. The other was that we would be so economically interdependent that blowing each other up would never make sense. That worked for a while. Now, it also brought us up into planetary boundaries faster. The unrenewable use of resource and turning those resources into pollution on the other side of the supply chain. So obviously, that faster GDP growth meant the overfishing of the oceans and the cutting down of the trees and the climate change and the mining, toxic mining tailings going into the water and the mountaintop removal mining and all those types of things. That's the overconsumption side of the risk that we're talking about. And so the answer of let's do positive GDP is the answer rapidly and exponentially. Obviously, accelerated the planetary boundary side. And that started to be that was thought about for a long time, but it started to be modeled with the Club of Rome and limits of growth. And it but it's just very obvious to say if you have a linear materials economy where you take stuff out of the earth faster, whether it's fish or trees or or you take or oil, you take it out of the earth faster than it can replenish itself. And you turn it into trash after using it for a short period of time, you put the trash in the environment faster than it can process itself. And there's toxicity associated with both sides of this. You can't run an exponentially growing linear materials economy on a finite planet forever. That's not a hard thing to figure out. And it has to be exponential if there's an exponentiation, the monetary supply because of interest and then fractional reserve banking and to then be able to keep up with the growing monetary supply, you have to have growth of goods and services. And so that's that kind of thing that has happened. But you also see that when you get these supply chains that are so interconnected across the world, you get increased fragility because a collapse or a problem in one area then affects the whole world in a much bigger area as opposed to the issues being local. Right. So we got to see with covid and an issue that started in one part of China affecting the whole world so much more rapidly than would have happened before Bretton Woods, right, before international travel supply chains, you know, that whole kind of thing. And with a bunch of second and third order effects that people wouldn't have predicted, OK, we have to stop certain kinds of travel because of viral contaminants. But the countries doing agriculture depend upon fertilizer they don't produce that is shipped into them and depend upon pesticides they don't produce. So we got both crop failures and crops being eaten by the virus. Crop failures and crops being eaten by locusts in scale in northern Africa and Iran and things like that because they couldn't get the supplies of stuff in. So then you get massive starvation or future kind of hunger issues because of supply chain shutdowns. So you get this increased fragility and cascade dynamics where a small problem can end up leading to cascade effects. And also, we went from two superpowers with one catastrophe weapon to now that same catastrophe weapon is there's more countries that have it, eight or nine countries that have it. And there's a lot more types of catastrophe weapons. We now have catastrophe weapons with weaponized drones that can hit infrastructure targets with bio with that every new type of tech has created an arms race. So we have not with the UN or the other kind of intergovernmental organizations, we haven't been able to really do nuclear deproliferation. We've actually had more countries get nukes and keep getting faster nukes, the race to hypersonics and things like that. And every new type of technology that has emerged has created an arms race. And so you can't do mutually assured destruction with multiple agents, so you can with two agents. Two agents, it's much easier to create a stable Nash equilibrium that's forced. But the ability to monitor and say, if these guys shoot, who do I shoot? Do I shoot them? Do I shoot everybody? Do I? And so you get a three body problem. You get a very complex type of thing when you have multiple agents and multiple different types of catastrophe weapons, including ones that can be much more easily produced than nukes. Nukes are really hard to produce. There's only uranium in a few areas, uranium enrichment is hard. ICBMs are hard. But weaponized drones hitting smart targets is not so hard. There's a lot of other things where basically the scale at being able to manufacture them is going way, way down to where even non-state actors can have them. And so when we talk about exponential tech and the decentralization of exponential tech, what that means is decentralized catastrophe weapon capacity. And especially in a world of increasing numbers of people feeling disenfranchised, frantic, whatever, for different reasons. So I would say the Bretton Woods world doesn't prepare us to be able to deal with lots of different agents, having lots of different types of catastrophe weapons you can't put mutually assured destruction on, where you can't keep doing growth of the materials economy in the same way because of hitting planetary boundaries. And where the fragility dynamics are actually now their own source of catastrophic risk. So now we're so like there was all the world until World War II and World War II is just from a civilization timescale point of view, it was just a second ago. It seems like a long time, but it is really not. We get a short period of relative peace at the level of superpowers while building up the military capacity for much, much, much worse war the entire time. And then now we're at this new phase where the things that allowed us to make it through the nuclear power are not the same systems that will let us make it through the next stage. So what is this next post Bretton Woods? How do we become safe vessels, safe stewards of many different types of exponential technology is a key question when we're thinking about X-risk. Okay, so, and I'd like to try to answer the how a few ways, but first on the mutually assured destruction. Do you give credit to the idea of two superpowers not blowing each other up with nuclear weapons to the simple game theoretical model of mutually assured destruction or something you've said previously, this idea of inverse correlation, which I tend to believe between, not you were talking about tech, but I think it's maybe broadly true, the inverse correlation between competence and propensity for destruction. So the bigger your weapons, not because you're afraid of mutually assured self-destruction, but because we're human beings and there's a deep moral fortitude there that somehow aligned with competence and being good at your job that like, it's very hard to be a psychopath and be good at killing at scale. Do you share any of that intuition? Kind of. I think most people would say that Alexander the Great and Genghis Khan and Napoleon were effective people that were good at their job, that were actually maybe asymmetrically good at being able to organize people and do certain kinds of things that were pretty oriented towards certain types of destruction or pretty willing to, maybe they would say they were oriented towards empire expansion, but pretty willing to commit certain acts of destruction in the name of it. What are you worried about, the Genghis Khan or you could argue he's not a psychopath, that are you worried about Genghis Khan? Are you worried about Hitler? Are you worried about a terrorist who has a very different ethic, which is not even for, it's not trying to preserve and build and expand my community. It's more about just destruction in itself is the goal. I think the thing that you're looking at that I do agree with is that there's a psychological disposition towards construction and a psychological disposition more towards destruction. Obviously, everybody has both and can toggle between both. Oftentimes, one is willing to destroy certain things. We have this idea of creative destruction, right? Willing to destroy certain things to create other things. Utilitarianism and trolley problems are all about exploring that space and the idea of war is all about that. I am trying to create something for our people and it requires destroying some other people. Sociopathy is a funny topic because it's possible to have very high fealty to your in-group and work on perfecting the methods of torture to the out-group at the same time because you can dehumanize and then remove empathy. I would also say that there are types. The thing that gives hope about the orientation towards construction and destruction being a little different in psychologies is what it takes to build really catastrophic things to build really catastrophic tech. Even today where it doesn't take what it took to make a nuke, a small group of people could do it. It takes still some real technical knowledge that required having studied for a while and some then building capacity. And there's a question of is that psychologically inversely correlated with the desire to damage civilization meaningfully? A little bit. A little bit, I think. I think a lot. I think it's actually, I mean, this is the conversation I had like with I think offline with Dan Carlin which is like it's pretty easy to come up with ways that any competent, I can come up with a lot of ways to hurt a lot of people. And it's pretty easy. Like I alone can do it. And there's a lot of people as smart or smarter than me at least in their creation of explosives. Why are we not seeing more insane mass murder? I think there is something fascinating and beautiful about this. And it does have to do with some deeply pro-social types of characteristics in humans and – but when you're dealing with very large numbers, you don't need a whole lot of a phenomena. And so then you start to say, well, what's the probability that X won't happen this year? Then won't happen in the next two years, three years, four years? And then how many people are doing destructive things with lower tech? And then how many of them can get access to higher tech that they didn't have to figure out how to build? So when I can get commercial tech and maybe I don't understand tech very well but I understand it well enough to utilize it, not to create it, and I can repurpose it. When we saw that commercial drone with a homemade thermite bomb hit the Ukrainian munitions factory and do the equivalent of an incendiary bomb level of damage, that's just home tech. That's just simple kind of thing. And so the question is not what – does it stay being a small percentage of the population? The question is can you bind that phenomena nearly completely? And especially now as you start to get into bigger things, CRISPR gene drive technologies and various things like that, can you bind it completely long-term? Over what period of time? Not perfectly though. That's the thing. I'm trying to say that there is some – let's call it a random word, love, that's inherent and that's core to human nature, that's preventing destruction at scale. And you're saying, yeah, but there's a lot of humans. There's going to be eight plus billion and then there's a lot of seconds in the day to come up with stuff. There's a lot of pain in the world that can lead to a distorted view of the world such that you want to channel that pain into the destruction, all those kinds of things. And it's only a matter of time that any one individual can do large damage, especially as we create more and more democratized, decentralized ways to deliver that damage even if you don't know how to build the initial weapon. But the thing is, it seems like it's a race between the cheapening of destructive weapons and the capacity of humans to express their love towards each other. And it's a race that so far, I know on Twitter it's not popular to say, but love is winning. So what is the argument that love is going to lose here against nuclear weapons and biotech and AI and drones? Okay, I'm going to come at the end of this to a how love wins. So I just want you to know that that's where I'm oriented. That's the end. But I'm going to argue against why that is a given because it's not a given. I don't believe. And I think that it's good romantic comedy. So you're going to create drama right now, but it will end in a happy ending. Well, it's because it's only a happy ending if we actually understand the issues well enough and take responsibility to shift it. Do I believe like there's a reason why there's so much more dystopic sci-fi than pro-topic sci-fi and the some pro-topic sci-fi usually requires magic is because or at least magical tech, right, dilithium crystals and warp drives and stuff, because it's very hard to imagine people like the people we have been in the history books with exponential type technology and power that don't eventually blow themselves up, that make good enough choices as stewards of their environment and their commons and each other and et cetera. So like it's easier to think of scenarios where we blow ourselves up than it is to think of scenarios where we avoid every single scenario where we blow ourselves up. And when I say blow ourselves up, I mean the environmental versions, the terrorist versions, the war versions, the cumulative externalities versions. Can I and I'm sorry if I'm interrupting your flow of thought, but why is it easier? Could it be a weird psychological thing where we either are just more capable to visualize explosions and destruction and then the sicker thought, which is like we kind of enjoy for some weird reason thinking about that kind of stuff, even though we wouldn't actually act on it. It's almost like some weird, like I love playing shooter games, you know, first person shooters and like, especially if it's like murdering zombie and doom, you're shooting demons. I played one of my favorite games, Diablo is like slashing through different monsters and the screaming and pain and the hellfire, and then I go out into the real world to eat my coconut ice cream and I'm all about love. So like, can we trust our ability to visualize how it all goes to shit as an actual rational way of thinking? I think it's a fair question to say to what degree is there just kind of perverse fantasy and morbid exploration and whatever else that happens in our imagination, but I don't think that's the whole of it. I think there is also a reality to the combinatorial possibility space and the difference in the probabilities that there's a lot of ways I could try to put the 70 trillion cells of your body together that don't make you. There's not that many ways I can put them together that make you. There's a lot of ways I could try to connect the organs together that make some weird kind of group of organs on a desk, but that doesn't actually make a functioning human. And you can kill an adult human in a second, but you can't get one in a second. It takes 20 years to grow one and a lot of things to happen, right? I could destroy this building in a couple minutes with demolition, but it took a year or a couple years to build it. There is a – There's a – there's a gradient where entropy is easier and there's a lot more ways to put a set of things together that don't work than the few that really do produce higher order synergies. And so when we look at a history of war and then we look at exponentially more powerful warfare, an arms race that drives out in all these directions, and when we look at a history of environmental destruction and exponentially more powerful tech that makes exponential externalities multiplied by the total number of agents that are doing it and the cumulative effects, there's a lot of ways the whole thing can break, like a lot of different ways. And for it to get ahead, it has to have none of those happen. And so there's just a probability space where it's easier to imagine that thing. So to say how do we have a protopic future, we have to say, well, one criteria must be that it avoids all of the catastrophic risks. So can we understand – can we inventory all the catastrophic risks? Can we inventory the patterns of human behavior that give rise to them? And could we try to solve for that? And could we have that be the essence of the social technology that we're thinking about to be able to guide, bind and direct the new physical technology? Because so far, physical technology – like we were talking about the Genghis Khans and like that that obviously use certain kinds of physical technology and armaments and also social technology and unconventional warfare for a particular set of purposes. But we have things that don't look like warfare, like Rockefeller and Standard Oil. And it looked like a constructive mindset to be able to bring this new energy resource to the world and it did. And the second order effects of that are climate change and all of the oil spills that have happened and will happen and all of the wars in the Middle East over the oil that have been there and the massive political clusterfuck and human life issues that are associated with it and on and on, right? And so it's also not just the orientation to construct a thing can have a narrow focus on what I'm trying to construct but be affecting a lot of other things through second and third order effects I'm not taking responsibility for. And you often, on another tangent, mentioned second, third and fourth order effects. And the order. And the order. Cascading. And it's really fascinating, like starting with the third order plus, it gets really interesting because we don't even acknowledge the second order effects. Right. But like thinking, because those, it could get bigger and bigger and bigger in ways we were not anticipating. So how do we make those, so it sounds like part of the thing that you're thinking through in terms of a solution, how to create an anti-fragile, a resilient society is to make explicit, acknowledge, understand the externalities, the second order, third order, fourth order and the order effects. How do we start to think about those effects? Yeah, the war application is harm we're trying to cause or that we're aware we're causing, right? The externality is harm that at least supposedly we're not aware we're causing or at minimum it's not our intention, right? Maybe we're either totally unaware of it or we're aware of it, but it is a side effect of what our intention is. It's not the intention itself. There are catastrophic risks from both types. The direct application of increased technological power to a rivalrous intent, which is going to cause harm for some outgroup, for some in-group to win. But the outgroup is also working on growing the tech and if they don't lose completely, they reverse engineer the tech, upregulate it, come back with more capacity. So there's the exponential tech arms race side of in-group, outgroup rivalry using exponential tech that is one set of risks. And the other set of risks is the application of exponentially more powerful tech, not intentionally to try and beat an outgroup, but to try to achieve some goal that we have, but to produce a second and third order effects that do have harm to the commons, to other people, to environment, to other groups that might actually be bigger problems than the problem we were originally trying to solve with the thing we were building. When Facebook was building a dating app and then building a social app where people could tag pictures, they weren't trying to build a democracy destroying app that would maximize time on site as part of its ad model through AI optimization of a newsfeed to the thing that made people spend most time on site, which is usually them being limbically hijacked more than something else, which ends up appealing to people's cognitive biases and group identities and creates no sense of shared reality. They weren't trying to do that, but it was a second order effect. And it's a pretty fucking powerful second order effect and a pretty fast one because the rate of tech is obviously able to get distributed to much larger scale, much faster and with a bigger jump in terms of total vertical capacity. That's what it means to get to the verticalizing part of an exponential curve. So just like we can see that oil had these second order environmental effects and also social and political effects. War and so much of the whole – like the total amount of oil used is – has a proportionality to total global GDP. And this is why we have this – the petrodollar and so the oil thing also had the externalities of a major aspect of what happened with military industrial complex and things like that. But we can see the same thing with more current technologies with Facebook and Google and other things. So I don't think we can run – and the more powerful the tech is, we build it for reason X, whatever reason X is. Maybe X is three things. Maybe it's one thing, right? We're doing the oil thing because we want to make cars because it's a better method of individual transportation. We're building the Facebook thing because we're going to connect people socially in the personal sphere. But it interacts with complex systems with ecologies, economies, psychologies, cultures. And so it has effects on other than the thing we're intending. Some of those effects can end up being negative effects. But because this technology – if we make it to solve a problem, it has to overcome the problem. The problem has been around for a while. It's going to overcome in a short period of time. So it usually has greater scale, greater rate of magnitude in some way. That also means that the externalities that it creates might be bigger problems. And you can say, well, but then that's the new problem and humanity will innovate its way out of that. Well, I don't think that's paying attention to the fact that we can't keep up with exponential curves like that nor do finite spaces allow exponential externalities forever. And this is why a lot of the smartest people thinking about this are thinking, well, no, I think we're totally screwed unless we can make a benevolent AI singleton that rules all of us. You know, guys like Ostrom and others thinking in those directions because they're like, how do humans try to do multipolarity and make it work? And I have a different answer of what I think it looks like that does have more to do with love but some applied social tech aligned with love. This is good because I have a bunch of really dumb ideas. I'd prefer to hear – I'd like to hear some of them first. I think the idea I would have is to be a bit more rigorous in trying to measure the amount of love you add or subtract from the world in second, third, fourth, fifth order effects. It's actually, I think, especially in the world of tech, quite doable. You know, you just might not like, you know, the shareholders may not like that kind of metric, but it's pretty easy to measure. That's not even – I'm perhaps half joking about love, but we could talk about just happiness and well-being, long-term well-being. That's pretty easy for Facebook, for YouTube, for all these companies to measure that. They do a lot of kinds of surveys. They could do – I mean, there's very simple solutions here that you could just survey how – I mean, surveys are in some sense useless because they're a subset of the population. You're just trying to get a sense. It's a very loose kind of understanding, but integrated deeply as part of the technology. Most of our tech is recommender systems. Most of the – sorry, not tech. Online interaction is driven by recommender systems that learn very little data about you and use that data based on – mostly based on traces of your previous behavior to suggest future things. This is how Twitter, this is how Facebook works, this is how AdSense for Google, AdSense works, this is how Netflix, YouTube work, and so on. And for them to just track as opposed to engagement, how much you spend on a particular video, a particular site, is also track – give you the technology to do self-report of what makes you feel good, what makes you grow as a person, of what makes you the best version of yourself, the Rogan idea of the hero of your own movie. And just add that little bit of information. If you have people – you have this happiness surveys of how you feel about the last five days, how would you report your experience. You can lay out a set of videos. It's kind of fascinating to watch. I don't know if you ever look at YouTube, the history of videos you've looked at. It's fascinating. It's very embarrassing for me. Like, it'll be like a lecture and then like a set of videos that I don't want anyone to know about, which is – which would be like, I don't know, maybe like five videos in a row where it looks like I watched the whole thing, which I probably did, about like how to cook a steak, even though – or just like the best chefs in the world cooking steaks, I mean, I'm just like sitting there watching it for no purpose whatsoever, wasting away my life. Or like funny cat videos, like legit, that's always a good one. And I could look back and rate which videos made me a better person and not. And I mean, on a more serious note, there's a bunch of conversations, podcasts, or lectures I've watched which made me a better person and some of them made me a worse person, quite honestly, not for stupid reasons like I feel dumber, but because I do have a sense that that started me on a path of not being kind to other people. For example, I'll give you from my own – and I'm sorry for ranting, but maybe there's some usefulness to this kind of exploration of self. When I focus on creating, on programming, on science, I become a much deeper thinker and a kinder person to others. When I listen to too many – a little bit is good, but too many podcasts or videos about how our world is melting down or criticizing ridiculous people, the worst of the quote-unquote woke, for example, there's all these groups that are misbehaving in fascinating ways because they've been corrupted by power. The more I watch criticism of them, the worse I become. And I'm aware of this, but I'm also aware that for some reason it's pleasant to watch those sometimes. And so for me to be able to self-report that to the YouTube algorithm, to the systems around me, and they ultimately try to optimize to make me the best person, the best version of myself, which I personally believe would make YouTube a lot more money because I'd be much more willing to spend time on YouTube and give YouTube a lot more of my money, that's great for business and great for humanity because it'll make me a kinder person. It'll increase the love quotient, the love metric, and it'll make them a lot of money. I feel like everything's aligned. And so you should do that, not just for YouTube algorithm, but also for military strategy and whether to go to war or not, because one externality you can think of about going to war, which I think we talked about offline, is we often go to war with kind of governments, not with the people. You have to think about the kids of countries that see a soldier and because of what they experience, their interaction with the soldier, hate is born. When you're like eight years old, six years old, you lose your dad, you lose your mom, you lose a friend, somebody close to you, that one really powerful externality that could be reduced to love, positive and negative, is the hate that's born when you make decisions. And that's going to take fruition, that little seed is going to become a tree that then leads to the kind of destruction that we talk about. So in my sense, it's possible to reduce everything to a measure of how much love does this add to the world. All that to say, do you have ideas of how we practically build systems that create a resilient society? There are a lot of good things that you shared where there's like 15 different ways that we could enter this that are all interesting. So I'm trying to see which one will probably be most useful. Pick the one or two things that are least ridiculous. When you were mentioning if we could see some of the second order effects or externalities that we aren't used to seeing, specifically the one of a kid being radicalized somewhere else, which engenders enmity in them towards us, which decreases our own future security, even if you don't care about the kid. If you care about the kid, it's a whole other thing. Yeah, I mean, I think when we saw this, when Jane Fonda and others went to Vietnam and took photos and videos of what was happening, and you got to see the pictures of the kids with napalm on them, that like the anti-war effort was bolstered by that in a way it couldn't have been without that. Until we can see the images, you can't have a mere neuron effect in the same way. And when you can, that starts to have a powerful effect. I think there's a deep principle that you're sharing there, which is that if we – we can have a rivalrous intent where our in-group, whatever it is, maybe it's our political party wanting to win within the US, maybe it's our nation state wanting to win in a war or an economic war over resource or whatever it is, that if we don't obliterate the other people completely, they don't go away, they're not engendered to like us more, they didn't become less smart. So they have more enmity towards us and whatever technologies we employed to be successful, they will now reverse engineer, make iterations on and come back. And so you drive an arms race, which is why you can see that the wars were over history employing more lethal weaponry and not just the kinetic war, the information war and the narrative war and the economic war, right? Like it just increased capacity in all of those fronts. And so what seems like a win to us on the short term might actually really produce losses in the long term. And what's even in our own best interest in the long term is probably more aligned with everyone else because we inter-effect each other. And I think the thing about globalism, globalization and exponential tech and the rate at which we affect each other and the rate at which we affect the biosphere that we're all affected by is that this kind of proverbial spiritual idea that we're all interconnected and need to think about that in some way that was easy for tribes to get because everyone in the tribe so clearly saw their interconnection and dependence on each other. But in terms of a global level, the speed at which we are actually interconnected, the speed at which the harm happening to something in Wuhan affects the rest of the world or a new technology developed somewhere affects the entire world or an environmental issue or whatever is making it to where we either actually all get, not as a spiritual idea, just even as physics, right? We all get the interconnectedness of everything and that we either all consider that and see how to make it through more effectively together or failures anywhere end up becoming decreased quality of life and failures and increased risk everywhere. Don't you think people are beginning to experience that at the individual level? So governments are resisting it. They're trying to make us not empathize with each other, feel connected. But don't you think people are beginning to feel more and more connected? Like, isn't that exactly what the technology is enabling? Like social networks, we tend to criticize them, but isn't there a sense which we're experiencing? You know, when you watch those videos that are criticizing, whether it's the woke Antifa side or the QAnon Trump supporter side, does it seem like they have increased empathy for people that are outside of their ideologic camp? No, not at all. I may be conflating my own experience of the world and that of the populace. I tend to see those videos as feeding something that's a relic of the past. They figured out that drama fuels clicks, but whether I'm right or wrong, I don't know. But I tend to sense that that is not, that hunger for drama is not fundamental to human beings, that we want to actually, that we want to understand Antifa and we want to empathize. We want to take radical ideas and be able to empathize with them and synthesize it all. Okay, let's look at cultural outliers in terms of violence versus compassion. We can see that a lot of cultures have relatively lower in-group violence, bigger out-group violence, and there's some variance in them and variance at different times based on the scarcity or abundance of resource and other things. But you can look at, say, Jains, whose whole religion is around nonviolence so much so that they don't even hurt plants. They only take fruits that fall off them and stuff. Or to go to a larger population, you take Buddhists, where for the most part, with a few exceptions, for the most part across three millennia and across lots of different countries and geographies and whatever, you have 10 million people plus or minus who don't hurt bugs. The whole spectrum of genetic variance that is happening within a culture of that many people and head traumas and whatever, and nobody hurts bugs. And then you look at a group where the kids grew up as child soldiers in Liberia or Darfur were to make it to adulthood, pretty much everybody's killed people hand to hand and killed people who were civilian or innocent type of people. And you say, okay, so we were very neotenous. We can be conditioned by our environment and humans can be conditioned where almost all the humans show up in these two different bell curves. It doesn't mean that the Buddhists had no violence. It doesn't mean that these people had no compassion, but they're very different Gaussian distributions. And so I think one of the important things that I like to do is look at the examples of the populations with Buddhism shows regarding compassion or what Judaism shows around education. The average level of education that everybody gets because of a culture that is really working on conditioning it or various cultures. What are the positive deviance outside of the statistical deviance to see what is actually possible and then say, what are the conditioning factors and can we condition those across a few of them simultaneously? And could we build a civilization like that becomes a very interesting question. So there's this kind of real politic idea that humans are violent, large groups of humans become violent, they become irrational, specifically those two things, rivalrous and violent and irrational. And so in order to minimize the total amount of violence and have some good decisions, they need ruled somehow. And that not getting that is some kind of naive utopianism that doesn't understand human nature yet. This gets back to like mimesis of desire as an inexorable thing. I think the idea of the masses is actually a kind of propaganda that is useful for the classes that control to popularize the idea that most people are too violent, lazy, undisciplined and irrational to make good choices. And therefore their choices should be sublimated in some kind of way. I think that if we look back at these conditioning environments, we can say, okay, so the kids that go to a really fancy school and have a good developmental environment like Exeter Academy, there's still a Gaussian distribution of how well they do on any particular metric. But on average, they become senators. And the worst ones become high-end lawyers or whatever. And then I look at an inner city school with a totally different set of things and I see a very, very differently displaced Gaussian distribution, but a very different set of conditioning factors. And then I say the masses, well, if all those kids who were one of the parts of the masses got to go to Exeter and have that family and whatever, would they still be the masses? Could we actually condition more social virtue, more civic virtue, more orientation towards dialectical synthesis, more empathy, more rationality widely? Yes. Would that lead to better capacity for something like participatory governance, democracy or republic or some kind of participatory governance? Yes. Yes. Is it necessary for it actually? Yes. And is it good for class interests? Not really. By the way, when you say class interests, this is the powerful leading over the less powerful, that kind of idea? Anyone that benefits from asymmetries of power doesn't necessarily benefit from decreasing those asymmetries of power and kind of increasing the capacity of people more widely. And so when we talk about power, we're talking about asymmetries in agency, influence and control. You think that hunger for power is fundamental to human nature? I think we should get that straight before we talk about other stuff. So like this pickup line that I use at a bar office, which is power corrupts and absolute power corrupts absolutely. Is that true or is that just a fancy thing to say? In modern society, there's something to be said. Have we changed as societies over time in terms of how much we crave power? There is an impulse towards power that is innate in people and can be conditioned one way or the other. Yes. But I think that this society does a very different thing with it at scale, that you don't end up seeing the emergence of the same types of sociopathic behavior and particularly then creating sociopathic institutions. And so it's like, is eating the foods that were rare in our evolutionary environment that give us more dopamine hit because they were rare and they're not anymore, salt, fat, sugar? Is there something pleasurable about those where humans have an orientation to overeat if they can? Well, the fact that there is that possibility doesn't mean everyone will obligately be obese and die of obesity, right? Like it's possible to have a particular impulse and to be able to understand it, have other ones and be able to balance them. And so to say that power dynamics are obligate in humans and we can't do anything about it is very similar to me to saying like everyone is going to be obligately obese. Yeah, so there's some degree to which the control of those impulses has to do with the conditioning early in life. Yes. And the culture that creates the environment to be able to do that and then the recursion on that. Okay, so if we were to, just bear with me, just asking for a friend, if we were to kill humans on earth and then start over, is there ideas about how to build up? Okay, we don't have to kill, let's leave the humans on earth, they're fine and go to Mars and start a new society. Is there ways to construct systems of conditioning, education of how we live with each other that would incentivize us properly to not seek power, to not construct systems that are of asymmetry of power and to create systems that are resilient to all kinds of terrorist attacks, to all kinds of destructions? I believe so. Is there some inklings we could, of course you probably don't have all the answers, but you have insights about what that looks like. I mean, is it just rigorous practice of dialectic synthesis? As essentially conversations with assholes of various flavors until they're not assholes anymore because you've become deeply empathetic with their experience? Okay, so there's a lot of things that we would need to construct to come back to this. Like what is the basis of rivalry? How do you bind it? How does it relate to tech? If you have a culture that is doing less rivalry, does it always lose in war to those who do war better and how do you make something on the enactment of how to get there from here? Great, great. So what's rivalry? Is rivalry bad or good? So is another word for rivalry competition? Yes, I think roughly yes. I think bad and good are kind of silly concepts here. Good for some things, bad for other things. For resilience. Some contexts and others, even that. Let me give you an example that relates back to the Facebook measuring thing you were mentioning a moment ago. First, I think what you're saying is actually aligned with the right direction and what I want to get to in a moment. But it's not, the devil is in the details here. So I enjoy praise. It feeds my ego. I grow stronger. So I appreciate that. I'll make sure to include one piece every 15 minutes as we go. So it's easier to measure – there are problems with this argument but there's also utility to it. So let's take it for the utility it has first. It's harder to measure happiness than it is to measure comfort. We can measure with technology that the shocks in a car are making the car bounce less, that the bed is softer and material science and those types of things. And happiness is actually hard for philosophers to define because some people find that there's certain kinds of overcoming suffering that are necessary for happiness. There's happiness that feels more like contentment and happiness that feels more like passion. Is passion the source of all suffering or the source of all creativity? There's deep stuff and it's mostly first person, not measurable third person stuff even if maybe it corresponds to third person stuff to some degree. But we also see examples of – some of our favorite examples is people who are in the worst environments who end up finding happiness, right, where the third person stuff looks to be less conducive and there's some Viktor Frankl, Nelson Mandela, whatever. But it's pretty easy to measure comfort. It's pretty universal. And I think we can see that the Industrial Revolution started to replace happiness with comfort quite heavily as the thing it was optimizing for. And we can see that when increased comfort is given, maybe because of the evolutionary disposition that expending extra calories when for the majority of our history we didn't have extra calories was not a safe thing to do. Who knows why? When extra comfort is given, it's very easy to take that path even if it's not the path that supports overall well-being long term. And so we can see that when you look at the techno-optimist idea that we have better lives than Egyptian pharaohs and kings and whatever, what they're largely looking at is how comfortable our beds are and how comfortable the transportation systems are and things like that in which case there's massive improvement. But we also see that in some of the nations where people have access to the most comfort, suicide and mental illness are the highest. And we also see that some of the happiest cultures are actually some of the ones that are in materially lame environments. And so there's a very interesting question here. And if I understand correctly, you do cold showers. And Joe Rogan was talking about how he needs to do some fairly intensive kind of struggle that is a non-comfort to actually induce being better as a person, this concept of hormesis, that it's actually stressing an adaptive system that increases its adaptive capacity and that there's something that the happiness of a system has something to do with its adaptive capacity, its overall resilience, health, well-being, which requires a decent bit of discomfort. And yet in the presence of the comfort solution, it's very hard to not choose it. And then as you're choosing it regularly to actually down regulate your overall adaptive capacity. And so when we start saying, can we make tech where we're measuring for the things that it produces beyond just the measure of GDP or whatever particular measures look like the revenue generation or profit generation of my business, are all the meaningful things measurable and what are the right measures and what are the externalities of optimizing for that measurement set? What meaningful things aren't included in that measurement set that might have their own externalities? These are some of the questions we actually have to take seriously. Yeah. And I think they're answerable questions, right? Progressively better, not perfect. Right. So, so first of all, let me throw out happiness and comfort out of the discussion. Those seem like useless. The distinction. So I, cause I said they're useful. Wellbeing is useful, but I think I take it back. I knew I proposed new metrics in this brainstorm session, which is so one is like personal growth, which is intellectual growth. I think we're able to make that concrete for ourselves. Like you're a better person than you were a week ago or a worse person than you were a week ago. And I think we can ourselves report that and, and, and understand what that means. It's this gray area and we try to define it, but I think we humans are pretty good at that because we have a sense, an idealistic sense of the person we might be able to become. We all dream of becoming a certain kind of person. And I think we have a sense of getting closer and not towards that person. Maybe this is not a great metric. Fine. The other one is love actually. Look if you're happy or not, or you're comfortable or not, how much love do you have towards your fellow human beings? I feel like if you try to optimize that and increasing that, that's going to have, that's a good metric. How many times a day, sorry, if I can make quantify, how many times a day have you thought positively of another human being? Let's put that down as a number and increase that number. I think the process of saying, okay, so let's not take GDP or GDP per capita as the metric we want to optimize for because GDP goes up during war and it goes up with more healthcare spending from sicker people and various things that we wouldn't say correlate to quality of life. Addiction drives GDP awesomely. By the way, when I said growth, I wasn't referring to GDP. I'm giving an example now of the primary metric we use and why it's not an adequate metric because we're exploring other ones. So the idea of saying, what would the metrics for a good civilization be? If I had to pick a set of metrics, what would the best ones be if I was going to optimize for those? And then really try to run the thought experiment more deeply and say, okay, so what happens if we optimize for that? Try to think through the first and second and third order effects of what happens that's positive and then also say what negative things can happen from optimizing that? What actually matters that is not included in that or in that way of defining it? Because love versus number of positive thoughts per day, I could just make a long list of names and just say positive thing about each one. It's all very superficial. Not include animals or the rest of life, have a very shallow total amount of it, but I'm optimizing the number and if I get some credit for the number. This is when I said the model of reality isn't reality. When you make a set of metrics that we're going to optimize for this, whatever reality is that is not included in those metrics can be the areas where harm occurs, which is why I would say that wisdom is something like the discernment that leads to right choices beyond what metrics-based optimization would offer. Yeah, but another way to say that is wisdom is constantly expanding and evolving set of metrics. Which means that there is something in you that is recognizing a new metric that's important that isn't part of that metric set. So there's a certain kind of connection, discernment, awareness and this is- This iterative game theory. There's a Gödel's incompleteness theorem, right? Which is if the set of things is consistent, it won't be complete. So we're going to keep adding to it, which is why we were saying earlier, I don't think it's not beautiful. And especially if you were just saying one of the metrics you want to optimize for at the individual level is becoming, right? That we're becoming more. Well, that then becomes true for the civilization and our metric sets as well. And our definition of how to think about a meaningful life and a meaningful civilization. I can tell you what some of my favorite metrics are. What's that? Well, love is obviously not a metric. It's like- Like you could bench? Yeah. It's a good metric. Yeah. I want to optimize that across the entire population, starting with infants. So in the same way that love isn't a metric, but you could make metrics that look at certain parts of it. The thing I'm about to say isn't a metric, but it's a consideration. Because I thought about this a lot. I don't think there is a metric, a right one. I think that every metric by itself, without this thing we talked about, of the continuous improvement becomes a paperclip maximizer. I think that's what the idea of false idol means in terms of the model of reality not being reality. Then my sacred relationship is to reality itself, which also binds me to the unknown forever. To the known, but also to the unknown. And there's a sense of sacredness connected to the unknown that creates an epistemic humility that is always seeking not just to optimize the thing I know, but to learn new stuff. And to be open to perceive reality directly. So my model never becomes sacred. My model is useful. My- So the model can't be the false idol. Correct. And this is why the first verse of the Tao Te Ching is, the Tao that is nameable is not the eternal Tao. The naming then can become the source of the 10,000 things that if you get too carried away with it, can actually obscure you from paying attention to reality beyond the models. It sounds a lot like Stephen Wolfram, but in a different language, much more poetic. I can imagine that. No, I'm referring to, I'm joking, but there's echoes of cellular automata, which you can't name. You can't construct a good model cellular automata. You can only watch in awe. I apologize. I'm distracting your train of thought horribly and miserably. By the way, something robots aren't good at, and dealing with the uncertainty of uneven ground. You've been okay so far. You've been doing wonderfully. So what's your favorite metrics? Okay. So I know you're not a robot. So I have- You're passing the Turing test. I'm sorry. I'm sorry. And there are problems with this, but one metric that I like to just as a thought experiment to consider is, because you're actually asking, I mean, I know you ask your guests about the meaning of life, because ultimately when you're saying, what is a desirable civilization? You can't answer that without answering, what is a meaningful human life? And to say, what is a good civilization? Because it's going to be in relationship to that, right? And then you have whatever your answer is, how do you know? What is the epistemic basis for postulating that? There's also a whole nother reason for asking that question. I don't, I mean, that doesn't even apply to you whatsoever, which is it's interesting how few people have been asked questions like it. We joke about these questions as silly. It's funny to watch a person. And if I was more of an asshole, I would really stick on that question. It's a silly question in some sense, but we haven't really considered what it means. Just a more concrete version of that question is, what is a better world? What is the kind of world we're trying to create? Really? Have you really thought about the kind of world? I'll give you some kind of simple answers to that that are meaningful to me. But let me do the societal indices first, because they're fun. We should take a note of this meaningful thing, because it's important to come back to. Are you reminding me to ask you about the meaning of life? Noted. I know. Let me jot that down. Yeah. Well, because I think I stopped tracking at like 25 open threads. Okay. Let it all burn. One index that I find very interesting is the inverse correlation of addiction within the society. The more a society produces addiction within the people in it, the less healthy I think the society is as a pretty fundamental metric. And so the more the individuals feel that there are less compulsive things in compelling them to behave in ways that are destructive to their own values. And insofar as a civilization is conditioning and influencing the individuals within it, the inverse of addiction- Broadly defined. Correct. Addiction. What's it? Yeah. It's a behavior that is destructive towards things that we value. Yeah. I think that's a very interesting one to think about. That's a really interesting one. Yeah. And this is then also where comfort and addiction start to get very close. And the ability to go in the other direction from addiction is the ability to be exposed to hypernormal stimuli and not go down the path of desensitizing to other stimuli and needing that hypernormal stimuli, which does involve a kind of hormesis. So I do think the civilization of the future has to create something like ritualized discomfort. And- Ritualized discomfort. Yeah. I think that's what the sweat lodge and the vision quest and the solo journey and the ayahuasca journey and the Sundance were. I think it's even a big part of what yoga asana was, is to make beings that are resilient and strong, they have to overcome some things. To make beings that can control their own mind and fear, they have to face some fears. But we don't want to put everybody in war or real trauma. And yet we can see that the most fucked up people we know had childhoods of a lot of trauma. But some of the most incredible people we know had childhoods of a lot of trauma, whether or not they happened to make it through and overcome that or not. So how do we get the benefits of the stealing of character and the resilience and the whatever that happened from the difficulty without traumatizing people? A certain kind of ritualized discomfort that not only has us overcome something by ourselves, but overcome it together with each other where nobody bails when it gets hard because the other people are there. So it's both a resilience of the individuals and a resilience of the bonding. So I think we'll keep getting more and more comfortable stuff, but we have to also develop resilience in the presence of that for the anti-addiction direction and the fullness of character and the trustworthiness to others. So you have to be consistently injecting discomfort into the system, ritualize. I mean, this sounds like you have to imagine Sisyphus happy. You have to imagine Sisyphus with his rock optimally resilient from a metrics perspective in society. So we want to constantly be throwing rocks at ourselves. Not constantly. You didn't have to. Frequently. Periodically. Periodically. Yes. And there's different levels of intensity, different periodicities. Now I do not think this should be imposed by states. I think it should emerge from cultures. And I think the cultures are developing people that understand the value of it. So there is both a cultural cohesion to it, but there's also a voluntarism because the people value the thing that is being developed. They understand it. And that's what conditioning. It's conditioning some of these values. Conditioning is a bad word because we like our idea of sovereignty, but when we recognize the language that we speak and the words that we think and the patterns of thought built into that language and the aesthetics that we like and so much is conditioned in us just based on where we're born, you can't not condition people. So all you can do is take more responsibility for what the conditioning factors are and then you have to think about this question of what is a meaningful human life because we're, unlike the other animals born into environment that they're genetically adapted for, we're building new environments that we were not adapted for and then we're becoming affected by those. So then we have to say, well, what kinds of environments, digital environments, physical environments, social environments would we want to create that would develop the healthiest, happiest, most moral, noble, meaningful people? What are even those sets of things that matter? So you end up getting deep existential consideration at the heart of civilization design when you start to realize how powerful we're becoming and how much what we're building it in service towards matters. Stan Mallow Before I pull it, I think three threads you just laid down. Is there another metric index that you're interested in? Yossi Sheffi I'll tell you one more that I really like. There's a number, but the next one that comes to mind is I have to make a very quick model. When we're talking about human bonding, say we were in a tribal type setting, my positive emotional states and your positive emotional states would most of the time be correlated, your negative emotional states in mind. And so you start laughing, I start laughing, you start crying, my eyes might tear up. And we would call that the compassion-compersion axis. I would. This is a model I find useful. So compassion is when you're feeling something negative, I feel some pain, I feel some empathy, something in relationship. Compersion is when you do well, I'm stoked for you. Right? Like, I actually feel happiness at your happiness. Yossi Sheffi I like compersion. Stan Mallow Yeah, the fact that it's such an uncommon word in English is actually a problem culturally. Yossi Sheffi Because I feel that often, and I think that's a really good feeling to feel and maximize for actually. Stan Mallow That's actually the metric I'm going to say is the compassion-compersion axis is the thing I would optimize for. Now, there is a state where my emotional states and your emotional states are just totally decoupled. And that is like sociopathy. I don't want to hurt you, but I don't care if I do or for you to do well or whatever. But there's a worse state and it's extremely common, which is where they're inversely coupled, where my positive emotions correspond to your negative ones and vice versa. And that is the, I would call it the jealousy-sadism axis. The jealousy axis is when you're doing really well, I feel something bad. I feel taken away from, less than, upset, envious, whatever. And that's so common. But I think of it as kind of a low-grade psychopathology that we've just normalized. The idea that I'm actually upset at the happiness or fulfillment or success of another is like a profoundly fucked up thing. Now, we shouldn't shame it and repress it so it gets worse. We should study it. Where does it come from? And it comes from our own insecurities and stuff. But then the next part that everybody knows is really fucked up is just on the same axis. It's the same inverted, which is to the jealousy or the envy is that I feel badly when you're doing well. The sadism side is I actually feel good when you lose. Or when you're in pain, I feel some happiness that's associated. And you can see when someone feels jealous, sometimes they feel jealous with a partner and then they feel they want that partner to get it. Rage comes up or something. So sadism is really like jealousy is one step on the path to sadism from the healthy compassion compersion axis. So I would like to see a society that is inversely that is conditioning sadism and jealousy inversely, right? The lower that amount and the more the compassion compersion. And if I had to summarize that very simply, I'd say it would optimize for compersion. Which is because notice that's not just saying love for you where I might be self-sacrificing and miserable and I love people but I kill myself, which I don't think anybody thinks a great idea. Or happiness where I might be sociopathically happy where I'm causing problems all over the place or even sadistically happy. But it's a coupling, right? That I'm actually feeling happiness in relationship to yours and even in causal relationship where I my own agentic desire to get happier wants to support you too. Just actually speaking of another pickup line, that's quite honestly what I, as a guy who's single, this is going to come out very ridiculous because it's like, oh yeah, where's your girlfriend bro? But that's what I look for in a relationship because it's like it's so much, it's so, it's such an amazing life where you actually get joy from another person's success and they get joy from your success. And then it becomes like you don't actually need to succeed much for that to have like a cycle of just like happiness that just increases like exponentially. It's weird. So like just be, just enjoying the happiness of others, the success of others. So this is like the, let's call this, because the first person that drilled this into my head is Rogan, Joe Rogan. He was the embodiment of that because I saw somebody who was successful, rich and nonstop. True, I mean, you could tell when somebody is full of shit and somebody is not really genuinely enjoying the success of his friends. That was weird to me. That was interesting. And I mean, the way you're kind of speaking to it, the reason Joe stood out to me is I guess I haven't witnessed genuine expression of that often in this culture of just real joy for others. I mean, part of that has to do, there hasn't been many channels where you can watch or listen to people being their authentic selves. So I'm sure there's a bunch of people who live life with compersion. They probably don't seek public attention also, but that was, yeah, if there was any word that can express what I've learned from Joe and why he's been a really inspiring figure is that compersion. And I wish our world had a lot more of that. Because then, I mean, my own, sorry to go into small tangent, but like you're speaking how society should function. But I feel like if you optimize for that metric in your own personal life, you're going to live a truly fulfilling life. I don't know what the right word to use, but that's a really good way to live life. You will also learn what gets in the way of it and how to work with it that if you wanted to help try to build systems at scale or apply Facebook or exponential technologies to do that, you would have more actual depth of real knowledge of what that takes. And this is, as you mentioned, that there's this virtuous cycle between when you get stoked on other people doing well, and then they have a similar relationship to you and everyone is in the process of building each other up. And this is what I would say the healthy version of competition is versus the unhealthy version. The healthy version, right, the root, I believe it's a Latin word that means to strive together. And it's that impulse of becoming where I want to become more, but I recognize that there's actually a hormesis, there's a challenge that is needed for me to be able to do that. But that means that, yes, there's an impulse where I'm trying to get ahead, maybe I'm even trying to win, but I actually want a good opponent. And I want them to get ahead too, because that is where my ongoing becoming happens. And the win itself will get boring very quickly. The ongoing becoming is where there's aliveness. And for the ongoing becoming, they need to have it too. And that's the strive together. So in the healthy competition, I'm stoked when they're doing really well, because my becoming is supported by it. Now this is actually a very nice segue into a model I like about what a meaningful human life is, if you want to go there. Let's go there. We can go somewhere else if you want. I have three things I'm going elsewhere with, but if we were first, let us take a short stroll through the park of the meaning of life. Daniel, what is a meaningful life? I think the semantics end up mattering, because a lot of people will take the word meaning and the word purpose almost interchangeably. And they'll think kind of what is the meaning of my life, what is the meaning of human life, what is the meaning of life, what's the meaning of the universe, and what is the meaning of existence rather than non-existence. So there's a lot of kind of existential considerations there. And I think there's some cognitive mistakes that are very easy. Like taking the idea of purpose, which is like a goal, which is a utilitarian concept. The purpose of one thing is defined in relationship to other things that have assumed value. And to say what is the purpose of everything? Well, purpose is too small of a question. It's fundamentally a relative question within everything. What is the purpose of one thing relative to another? What is the purpose of everything? And there's nothing outside of it with which to say it. We actually just got to the limits of the utility of the concept of purpose. It doesn't mean it's purposeless in the sense of something inside of it being purposeless. It means the concept is too small, which is why you end up getting to, you know, like in Taoism talking about the nature of it. Rather, there's a fundamental what, where the why can't go deeper. It is the nature of it. But I'm going to try to speak to a much simpler part, which is when people think about what is a meaningful human life and kind of if we were to optimize for something at the level of individual life, but also how does optimizing for this at the level of the individual life lead to the best society for insofar as people living that way affects others and long term to the world as a whole? And how would we then make a civilization that was trying to think about these things? Because you can see that there are a lot of dialectics where there's value on two sides, individualism and collectivism or the ability to accept things and the ability to push harder and whatever. And there's failure modes on both sides. And so when you were starting to say, okay, individual happiness, you're like, wait, fuck, sadists can be happy while hurting people. It's not individual happiness, it's love. But wait, some people can self-sacrifice out of love in a way that actually ends up just creating codependency for everybody. Or okay, so how do we think about all those things together? One like this kind of came to me as a simple way that I kind of relate to it is that a meaningful life involves the mode of being, the mode of doing and the mode of becoming. And it involves a virtuous relationship between those three and that any of those modes on their own also have failure modes that are not a meaningful life. The mode of being, the way I would describe it, if we're talking about the essence of it is about taking in and appreciating the beauty of life that is now. It's a mode that is in the moment and that is largely about being with what is. It's fundamentally grounded in the nature of experience and the meaningfulness of experience, the prima facie meaningfulness of when I'm having this experience, I'm not actually asking what the meaning of life is. I'm actually full of it. I'm full of experiencing it. The momentary experience. Yes. So taking in the beauty of life. Being is adding to the beauty of life. I'm going to produce some art. I'm going to produce some technology that will make life easier, more beautiful for somebody else. I'm going to do some science that will end up leading to better insights or other people's ability to appreciate the beauty of life more because they understand more about it or whatever it is or protect it. I'm going to protect it in some way. But that's adding to or being in service of the beauty of life through our doing. And becoming is getting better at both of those. Being able to deepen our being, which is to be able to take in the beauty of life more profoundly, be more moved by it, touched by it, and increasing our capacity with doing to add to the beauty of life more. And so I hold that a meaningful life has to be all three of those. And where they're not in conflict with each other, ultimately it grounds in being. It grounds in the intrinsic meaningfulness of experience. And then my doing is ultimately something that will be able to increase the possibility of the quality of experience for others. And my becoming is a deepening on those. So it grounds an experience and also the evolutionary possibility of experience. And the point is to oscillate between these, never getting stuck on any one. Or I suppose in parallel, well, you can't really, attention is a thing, you can only allocate attention. I want moments where I am absorbed in the sunset and I'm not thinking about what to do next. And then the fullness of that can make it to where my doing doesn't come from what's in it for me. Because I actually feel overwhelmingly full already. And then it's like, how can I make life better for other people that don't have as much opportunities I had? How can I add something wonderful? How can I just be in the creative process? And so I think where the doing comes from matters. And if the doing comes from a fullness of being, it's inherently going to be paying attention to externalities. Or it's more oriented to do that than if it comes from some emptiness that is trying to get full in some way that is willing to cause sacrifices other places and where a chunk of its attention is internally focused. And so when Buddha said desire is the cause of all suffering, then later the vow of the Bodhisattva, which was to show up for all sentient beings in universe forever, is a pretty intense thing like desire. I would say there is a kind of desire, if we think of desire as a basis for movement, like a flow or a gradient, there's a kind of desire that comes from something missing inside seeking fulfillment of that in the world. That ends up being the cause of actions that perpetuate suffering. But there's also not just non-desire. There's a kind of desire that comes from feeling full at the beauty of life and wanting to add to it. That is a flow this direction. And I don't think that is the cause of suffering. I think that is, you know, and the Western traditions, right? The Eastern traditions focused on that and kind of unconditional happiness outside of them in the moment, outside of time. Western tradition said, no, actually desire is the source of creativity. And we're here to be made in the image and likeness of the creator. We're here to be fundamentally creative. But creating from where and in service of what? Creating from a sense of connection to everything and wholeness in service of the well-being of all of it is very different. Which is back to that compassion-compersion axis. Being doing becoming. It's pretty powerful. Also could potentially be algorithmatized into a robot just saying. Where does death come into that? Being is forgetting the concept of time completely. There's a sense to doing and becoming that has a deadline built in. The urgency built in. And do you think death is fundamental to this? To a meaningful life? Acknowledging or feeling the terror of death, like Ernest Becker? Or just acknowledging the uncertainty, the mystery, the melancholy nature of the fact that the ride ends? Is that part of this equation? Or it's not necessary? Okay, look at how it could be related. I've experienced fear of death. I've also experienced times where I thought I was going to die. It felt extremely peaceful and beautiful. And it's funny because we can be afraid of death because we're afraid of hell or bad reincarnation or the Bardo or some kind of idea of the afterlife we have or we're projecting some kind of sentient suffering. But if we're afraid of just non-experience, I notice that every time I stay up late enough that I'm really tired, I'm longing for deep sleep and non-experience, right? Like I'm actually longing for experience to stop. And it's not morbid. It's not a bummer. And I don't mind falling asleep. And I sometimes when I wake up, want to go back into it. And then when it's done, I'm happy to come out of it. So when we think about death and having finite time here, and we could talk about if we live for a thousand years instead of a hundred or something like that, it would still be finite time. The one bummer with the age we die is that I generally find that people mostly start to emotionally mature just shortly before they die. But if I get to live forever, I can just stay focused on what's in it for me forever. And if life continues and consciousness and sentience and people appreciating beauty and adding to it and becoming continues, my life doesn't, but my life can have effects that continue well beyond it. And life with a capital L starts mattering more to me than my life. My life gets to be a part of and in service to. And the whole thing about when old men plant trees, the shade of which they'll never get to be in. I remember the first time I read this poem by Hafez, the Sufi poet written in like 13th century or something like that. And he talked about that if you're lonely to think about him and he was kind of leaning his spirit into yours across the distance of a millennium and would come for you with these poems. And he was thinking about people a millennium from now and caring about their experience and what they'd be suffering if they'd be lonely and could he offer something that could touch them. And it's just fucking beautiful. And so like the most beautiful parts of humans have to do with something that transcends what's in it for me. And death forces you to that. So, not only does death create the urgency of doing, you're very right, it does have a sense in which it incentivizes the compersion and the compassion. And the widening, you remember Einstein had that quote, something to the effect of it's an optical delusion of consciousness to believe there are separate things. There's this one thing we call universe and something about us being inside of a prison of perception that can only see a very narrow little bit of it. But this might be just some weird disposition of mine. But when I think about the future after I'm dead and I think about consciousness, I think about young people falling in love for the first time and their experience and I think about people being awed by sunsets and I think about all of it, right? I can't not feel connected to that. Do you feel some sadness to the very high likelihood that you will be forgotten completely by all of human history, you, Daniel, the name, that which cannot be named? Systems like to self-perpetuate. Egos do that. The idea that I might do something meaningful that future people appreciate, of course there's like a certain sweetness to that idea. But I know how many people did something, did things that I wouldn't be here without and that my life would be less without whose names I will never know. And I feel a gratitude to them. I feel a closeness. I feel touched by that. And I think to the degree that the future people are conscious enough, there is a, you know, a lot of traditions had this kind of, are we being good ancestors and respect for the ancestors beyond the names? I think that's a very healthy idea. But let me return to a much less beautiful and much less pleasant conversation. You mentioned prison. Back to X-Risk. Okay. And conditioning. You mentioned something about the state. So what role, let's talk about companies, governments, parents, all the mechanisms that can be a source of conditioning. Which flavor of ice cream do you like? Do you think the state is the right thing for the future? So governments that are elected, democratic systems that are representing representative democracy. Is there some kind of political system of governance that you find appealing? Is it parents, meaning a very close knit tribes of conditioning that's the most essential? And then you and Michael Malice would happily agree that it's anarchy where the state should be dissolved or destroyed or burned to the ground, if you're Michael Malice, giggling, holding the torch as the fire burns. So which is it? Is the state, can the state be good or is the state bad for the conditioning of a beautiful state? A or B? This is like an S or D test. You like to give these simplified good or bad things. Would I like the state that we live in currently, the United States federal government to stop existing today? No, I would really not like that. I think that would be not quite bad for the world in a lot of ways. Do I think that it's a optimal social system and maximally just and humane and all those things and I want it to continue as is, no, also not that. But I am much more interested in it being able to evolve to a better thing without going through the catastrophe phase that I think it's just non-existence would give. So what size of state is good? In a sense, like, should we as a human society as this world becomes more globalized, should we be constantly striving to reduce the set? We can put on a map, like right now literally, like the centers of power in the world. Some of them are tech companies, some of them are governments. Should we be trying to as much as possible decentralize the power to where it's very difficult to point on the map the centers of power? And that means making the state, however, there's a bunch of different ways to make the government much smaller that could be reducing in the United States, reducing the funding for the government, all those kinds of things, the set of responsibilities, the set of powers. It could be, I mean, this is far out, but making more nations or maybe nations not in the space that are defined by geographic location, but rather in the space of ideas, which is what anarchy is about. Anarchy is about forming collectives based on their set of ideas and doing so dynamically, not based on where you were born and so on. I think we can say that the natural state of humans, if we want to describe such a thing, was to live in tribes that were below the Dunbar number, meaning that for a few hundred thousand years of human history, all of the groups of humans mostly stayed under that size and whenever it would get up to that size, it would end up cleaving. And so it seems like there's a pretty strong, but there weren't individual humans out in the wild doing really well, right? So we were a group animal, but with groups that had a specific size. So we could say in a way humans were being domesticated by those groups. They were learning how to have certain rules to participate with the group without which you'd get kicked out, but that's still the wild state of people. Yvon Maron And maybe it's useful to do as a side statement, which I've recently looked at a bunch of papers around Dunbar's number where the mean is actually 150. If you actually look at the original paper, it's really a range. So it's actually somewhere under a thousand. So it's a range of like two to 500 or whatever it is. But like you could argue that the, I think it actually is exactly two, the range is two to 520, something like that. And this is the mean that's taken crudely. It's not a very good paper. So in terms of the actual numerical, numerically speaking, but it'd be interesting if there's a bunch of Dunbar numbers that could be computed for particular environments, particular conditions and so on. It is very true that they're likely to be something small, you know, under a million, but it'd be interesting if we can expand that number in interesting ways that will change the fabric of this conversation. I just want to kind of throw that in there. I don't know if the 150 is baked in somehow into the hardware. We can talk about some of the things that it probably has to do with. Up to a certain number of people, and this is going to be variable based on the social technologies that mediate it to some degree. We can talk about that in a minute. Up to a certain number of people, everybody can know everybody else pretty intimately. But let's go ahead and just take 150 as an average number. Everybody can know everyone intimately enough that if your actions made anyone else do poorly, it's your extended family and you're stuck living with them and you know who they are and there's no anonymous people. There's no just them and over there. And that's one part of what leads to a kind of tribal process where what's good for the individual and good for the whole has a coupling. Also below that scale, everyone is somewhat aware of what everybody else is doing. There's not groups that are very siloed. And as a result, it's actually very hard to get away with bad behavior. There's a forced kind of transparency. And so you don't need kind of like the state in that way. But lying to people doesn't actually get you ahead. Sociopathic behavior doesn't get you ahead because it gets seen. And so there's a conditioning environment where the individual is behaving in a way that is aligned with the interest of the tribe is what gets conditioned. When it gets to be a much larger system, it becomes easier to hide certain things from the group as a whole as well as to be less emotionally bound to a bunch of anonymous people. I would say there's also a communication protocol where up to about that number of people, we could all sit around a tribal council and be part of a conversation around a really big decision. Do we migrate? Do we not migrate? Do we – something like that. Do we get rid of this person? And why would I want to agree to be a part of a larger group where everyone can't be part of that council? And so I am going to now be subject to law that I have no say in. If I could be part of a smaller group that could still survive and I get a say in the law that I'm subject to. I think the cleaving – and a way we can look at it beyond the Dunbar number too is we can look at that a civilization has binding energy that is holding them together and has cleaving energy. And if the binding energy exceeds the cleaving energy, that civilization will last. And so there are things that we can do to decrease the cleaving energy within the society, things we can do to increase the binding energy. I think naturally we saw that had certain characteristics up to a certain size, kind of tribalism. That ended with a few things. It ended with people having migrated enough that when you started to get resource wars, you couldn't just migrate away easily. And so tribal warfare became more obligated. It involved the plow and the beginning of real economic surplus. So there were a few different kind of forcing functions. But we're talking about what size should it be, right? What size should a society be? And I think the idea – like if we think about your body for a moment as a self-organizing, complex system that is multiscaled, we think about – My body is a wonderland. Our body is a wonderland, yeah. You have – That's a John Mayer song. I apologize. But yes, so if we think about our body and the billions of cells that are in it – Well, you don't have – like think about how ridiculous it would be to try to have all the tens of trillions of cells in it with no internal organization structure, right? Just like a sea of protoplasm. It wouldn't work. Pure democracy. And so you have cells and tissues and then you have tissues and organs and organs and organ systems. And so you have these layers of organization and then obviously the individual and a tribe and an ecosystem. And each of the higher layers are both based on the lower layers but also influencing them. I think the future of civilization will be similar which is there's a level of governance that happens at the level of the individual. My own governance of my own choice. I think there's a level that happens at the level of a family. We're making decisions together. We're inter-influencing each other and affecting each other, taking responsibility for the idea of an extended family. And you can see that like for a lot of human history, we had an extended family. We had a local community, a local church or whatever it was. We had these intermediate structures whereas right now there's kind of like the individual producer consumer taxpayer voter and the massive nation state global complex and not that much in the way of intermediate structures that we relate with and not that much in the way of real personal dynamics. All impersonalized, made fungible. And so I think that we have to have global governance meaning I think we have to have governance at the scale we affect stuff. And if anybody is messing up the oceans, that matters for everybody. So that can't only be national or only local. Everyone is scared of the idea of global governance because we think about some top-down system of imposition that now has no checks and balances on power. I'm scared of that same version. So I'm not talking about that kind of global governance. It's why I'm even using the word governance as a process rather than government as an imposed phenomena. And so I think we have to have global governance but I think we also have to have local governance and there has to be relationships between them that each where there are both checks and balances and power flows of information. So I think governance at the level of cities will be a bigger deal in the future than governance at the level of nation states because I think nation states are largely fictitious things that are defined by wars and agreements to stop wars and like that. I think cities are based on real things that will keep being real where the proximity of certain things together, the physical proximity of things together gives increased value of those things. So you look at like Jeffrey West's work on scale and finding that companies and nation states and things that have a kind of complicated agreement structure get diminishing return of production per capita as the total number of people increases beyond about the tribal scale but the city actually gets increasing productivity per capita. But it's not designed. It's kind of this organic thing, right? So there should be governance at the level of cities because people can sense and actually have some agency there. Probably neighborhoods and smaller scales within it and also verticals and some of it won't be geographic. It will be network-based, right? Networks of affinities. So I don't think the future is one type of governance. Now what we can say more broadly is say when we're talking about groups of people that inter-affect each other, the idea of a civilization is that we can figure out how to coordinate our choice-making to not be at war with each other and hopefully increase total productive capacity in a way that's good for everybody. Division of labor and specialty so we all get more better stuff and whatever. But it's a coordination of our choice-making. I think we can look at civilizations failing on the side of not having enough coordination of choice-making so they fail on the side of chaos and then they cleave and an internal war comes about or whatever or they can't make smart decisions and they overuse their resources or whatever. Or it can fail on the side of trying to get order via imposition, via force. And so it fails on the side of oppression which ends up being for a while functional-ish for the thing as a whole but miserable for most people in it until it fails either because of revolt or because it can't innovate enough or something like that. And so there's this like toggling between order via oppression and chaos. And I think the idea of democracy, not the way we've implemented it but the idea of it, whether we're talking about a representative democracy or a direct digital democracy, liquid democracy, republic or whatever, the idea of an open society, participatory governance is can we have order that is emergent rather than imposed so that we aren't stuck with chaos and infighting and inability to coordinate and we're also not stuck with oppression. And what would it take to have emergent order? This is the most kind of central question for me these days because if we look at what different nation states are doing around the world and we see nation states that are more authoritarian that in some ways are actually coordinating much more effectively. So for instance, we can see that China has built high-speed rail not just through its country but around the world and the US hasn't built any high-speed rail yet. You can see that it brought 300 million people out of poverty in a time where we've had increasing economic inequality happening. You can see like that if there was a single country that could make all of its own stuff if the global supply chains failed, China would be the closest one to being able to start to go closed loop on fundamental things. Belt and Road Initiative, supply chain on rare earth metals, transistor manufacturing that is like oh, they're actually coordinating more effectively in some important ways in the last call it 30 years. And – That's imposed order. Imposed order and we can see that if in the US if – let's look at why real quick. We know why we created term limits so that we wouldn't have forever monarchs. That's the thing we were trying to get away from and that there would be checks and balances on power and that kind of thing. But that also has created a negative second order effect which is nobody does long-term planning because somebody comes in who's got four years, they want re-elected. They don't do anything that doesn't create a return within four years that will end up getting them elected, re-elected. So the 30-year industrial development to build high-speed trains or the new kind of fusion energy or whatever it is just doesn't get invested in. And then if you have left versus right where whatever someone does for four years then the other guy gets in and undoes it for four years and most of the energy goes into campaigning against each other. This system is just dissipating as heat, right? Like it's just burning up as heat. And the system that has no term limits and no internal friction in fighting because they got rid of those people can actually coordinate better. But I would argue it has its own fail states eventually and dystopic properties that are not the thing we want. So the goal is to accomplish – to create a system that does long-term planning without the negative effects of a monarch or dictator that stays there for the long term and accomplish that through not through the imposition of a single leader but through emergence. So that doesn't – that perhaps – first of all the technology in itself seems to maybe disagree a lot for different possibilities here which is make primary the system not the humans. So the basic – the medium on which the democracy happens like a platform where people can make decisions, do the choice making, the coordination of the choice making where emerges some kind of order to where like something that applies at the scale of the family, the extended family, the city, the country, the continent, the whole world. And then does that so dynamically, constantly changing based on the needs of the people sort of always evolving. And it would all be owned by Google. Like doesn't this – is there a way to – so first of all you're optimistic that you could basically create – that technology can save us. Technology at creating platforms – by technology I mean like software network platforms that allows humans to deliberate like make government together dynamically without the need for a leader that's on a podium screaming stuff. That's one. And two, if you're optimistic about that are you also optimistic about the CEOs of such platforms? The idea that technology is values neutral, values agnostic and people can use it for constructive or destructive purposes but it doesn't predispose anything. It's just silly and naive. Technology elicits patterns of human behavior because those who utilize it and get ahead end up behaving differently because of their utilization of it and then other people – then they end up shaping the world or other people race to also get the power of the technology. And so there's whole schools of anthropology that look at the effect on social systems and the minds of people of the change in our tooling. Marvin Harris' work called cultural materialism looked at this deeply. Obviously Marshall McLuhan looked specifically at the way that information technologies change the nature of our beliefs, minds, values, social systems. I will not try to do this rigorously because there are academics who will disagree on the subtle details but I'll do it kind of like illustratively. You think about the emergence of the plow, the ox drawn plow in the beginning of agriculture that came with it where before that you had hunter-gatherer and then you had horticulture, kind of a digging stick but not the plow. The world changed a lot with that, right? And a few of the changes that at least some theorists believe in is when the ox drawn plow started to proliferate, any culture that utilized it was able to start to actually cultivate grain because just with a digging stick you couldn't get enough grain for it to matter. Grain was a storable caloric surplus. They could make it through the famines. They could grow their population. So the ones that used it got so much ahead that it became obligate and everybody used it. But corresponding with the use of a plow, animism went away everywhere that it existed because you can't talk about the spirit of the buffalo while beating the cow all day long to pull a plow. So the moment that we do animal husbandry of that kind where you have to beat the cow all day, you have to say it's just a dumb animal. Man has dominion over earth and the nature of even our religious and spiritual ideas change. You went from women primarily using the digging stick to do the horticulture or gathering before that and men doing the hunting stuff to now men had to use the plow because the upper body strength actually really mattered. Women would have miscarriages when they would do it when they were pregnant. So all the caloric supply started to come from men where it had been from both before and the ratio of male-female gods changed to being mostly male gods following that. Obviously we went from very – that particular line of thought then also says that feminism followed the tractor. And the rise of feminism in the West started to follow women being able to say we can do what men can because the male upper body strength wasn't differential once the internal combustion engine was much stronger and we can drive a tractor. So I don't think to try to trace complex things to one cause is a good idea. So I think this is a reductionist view but it has truth in it. And so the idea that technology is values agnostic is silly. Technology codes patterns of behavior that code rationalizing those patterns of behavior and believing in them. The plow also is the beginning of the Anthropocene. It was the beginning of us changing the environment radically to clear cut areas to just make them useful for people which also meant the change of the view of where the web of life were just a part of it, etc. So all those types of things. So that's brilliantly put but by the way that was just brilliant. But the question is so it's not agnostic but… So we have to look at what the psychological effects of specific tech applied certain ways are and be able to say it's not just doing the first order thing you intended. It's doing like the effect on patriarchy and animism and the end of tribal culture and the beginning of empire and the class systems that came with that and we can go on and on about what the plow did. The beginning of surplus was inheritance which then became the capital model and like lots of things. So we have to say when we're looking at the tech how is what are the values built into the way the tech is being built that are not obvious. Right. So you always have to consider externalities. Yes. And the externalities are not just physical to the environment. They're also to how the people are being conditioned and how the relationality between them is being conditioned. That's the question I'm asking you. So I personally would rather be led by a plow and a tractor than Stalin. Okay. That's the question I'm asking you. In creating an emergent government where people, where there's a democracy that's dynamic, that makes choices, that does governance at like a very kind of liquid, like there's a bunch of fine resolution layers of abstraction of governance happening at all scales, right, and doing so dynamically where no one person has power at any one time that can dominate and impose rule. Okay. That's the Stalin version. I'm saying isn't the alternative that's emergent empowered or made possible by the plow and the tractor, which is the modern version of that, is like the internet, the digital space where we can, the monetary system where you have the cryptocurrency and so on, but you have much more importantly, to me at least, is just basic social interaction, the mechanisms of human transacting with each other in the space of ideas. So yes, it's not agnostic, definitely not agnostic. You've had a brilliant rant there. The tractor has effects, but isn't that the way we achieve an emergent system of governance? Yes, but I wouldn't say we're on track. You haven't seen anything promising. It's not that I haven't seen anything promising. It's that to be on track requires understanding and guiding some of the things differently than is currently happening, and it's possible. That's actually what I really care about. So you couldn't have had a Stalin without having certain technologies emerge. He couldn't have ruled such a big area without transportation technologies, without the train, without the communication tech that made it possible. So when you say you'd rather have a tractor or a plow than a Stalin, there's a relationship between them that is more recursive, which is new physical technologies allow rulers to rule with more power over larger distances historically. And you know- But some things are more responsible for that than others. Like Stalin also ate stuff for breakfast, but the thing he ate for breakfast is less responsible for the starvation of millions than the train. The train is more responsible for that. And then the weapons of war are more responsible. So some technology, like let's not throw it all in the... You're saying like technology has a responsibility here, but some is better than others. I'm saying that people's use of technology will change their behavior. So it has behavioral dispositions built in. The change of the behavior will also change the values in the society. It's very complicated, right? It will also, as a result, both make people who have different kinds of predispositions with regard to rulership and different kinds of new capacities. And so we have to think about these things. It's kind of well understood that the printing press and then in early industrialism ended feudalism and created kind of nation states. So one thing I would say as a long trend that we can look at is that whenever there is a step function, a major leap in technology, physical technology, the underlying techno industrial base with which we do stuff, it ends up coding for... It ends up predisposing a whole bunch of human behavioral patterns that the previous social system had not emerged to try to solve. And so it usually ends up breaking the previous social systems, the way the plow broke the tribal system, the way that the industrial revolution broke the feudal system. And then new social systems have to emerge that can deal with the new powers, the new dispositions, whatever with that tech. Obviously, the nuke broke nation state governance being adequate and said, we can't ever have that again. So then it created this international governance apparatus world. So I guess what I'm saying is that the solution is not exponential tech following the current path of what the market incentivizes exponential tech to do, market being a previous social tech. I would say that exponential tech, if we look at different types of social tech, so let's just briefly look at that democracy tried to do the emergent order thing, right? At least that's the story. This is why if you look at this important part to build first. It's kind of doing it, it's just doing it poorly, you're saying. I mean, it is emergent order in some sense. I mean, that's the hope of democracy versus other forms of government. Correct. I mean, I said at least the story because obviously it didn't do it for women and slaves early on. It doesn't do it for all classes equally, etc. But the idea of democracy is participatory governance. And so you notice that the modern democracies emerged out of the European enlightenment specifically because the idea that a lot of people, some huge number, not a tribal number, huge number of anonymous people who don't know each other, are not bonded to each other, who believe different things, who grew up in different ways can all work together to make collective decisions. Well, that affect everybody and where some of them will make compromises and the thing that matters to them for what matters to other strangers. That's actually wild. Like it's a wild idea that that would even be possible. And it was kind of the result of this high enlightenment idea that we could all do the philosophy of science and we could all do the Hegelian dialectic. Those ideas had emerged, right? And it was that we could all – so our choice-making because we said a society is trying to coordinate choice-making. The emergent order is the order of the choices that we're making, not just at the level of the individuals but what groups of individuals, corporations, nations, states, whatever do. So, our choices are based on – our choice-making is based on our sense-making and our meaning-making. Our sense-making is what do we believe is happening in the world and what do we believe the effects of a particular thing would be. Our meaning-making is what do we care about, right? Our value-generation, what do we care about that we're trying to move the world in the direction of. If you ultimately are trying to move the world in a direction that is really, really different than the direction I'm trying to, we have very different values, we're going to have a hard time. And if you think the world is a very different world, right? If you think that systemic racism is rampant everywhere and one of the worst problems and I think it's not even a thing, if you think climate change is almost existential and I think it's not even a thing, we're going to have a really hard time coordinating. And so, we have to be able to have shared sense-making of can we come to understand just what is happening together? And then can we do shared values generation? Okay, maybe I'm emphasizing a particular value more than you but I can see how – I can take your perspective and I can see how the thing that you value is worth valuing and I can see how it's affected by this thing. So can we take all the values and try to come up with a proposition that benefits all of them better than the proposition I created just to benefit these ones that harms the ones that you care about which is why you're opposing my proposition? We don't even try in the process of crafting a proposition currently to see – and this is the reason that the proposition when we vote on it gets half the votes almost all the time. It never gets 90% of the votes is because it benefits some things and harms other things. We can say all theory of tradeoffs but we didn't even try to say could we see what everybody cares about and see if there is a better solution. So – How do we fix that try? I wonder is it as simple as the social technology education? Well, no. It's that the proposition crafting and refinement process has to be key to a democracy or a governance and it's not currently. Isn't that the humans creating that situation? So one way – there's two ways to fix that. One is to fix the individual humans which is the education early in life and the second is to create somehow systems that – Yeah, it's both. So I understand the education part but creating systems that's why I mentioned the technologies is creating social networks essentially. Yes, that's actually necessary. Okay, so let's go to the first part and then we'll come to the second part. So democracy emerged as an enlightenment era idea that we could all do a dialectic and come to understand what other people valued and so that we could actually come up with a cooperative solution rather than just fuck you, we're going to get our thing in war, right? And that we could sense make together. We could all apply the philosophy of science and you weren't going to stick to your guns on what the speed of sound is if we measured it and we found out what it was and there's a unifying element to the objectivity in that way. And so this is why I believe Jefferson said if you could give me a perfect newspaper and a broken government or – I'm paraphrasing – or a broken government and perfect newspaper, I wouldn't hesitate to take the perfect newspaper because if the people understand what's going on, they can build a new government. If they don't understand what's going on, they can't possibly make good choices. And Washington – I'm paraphrasing again – first president said the number one aim of the federal government should be the comprehensive education of every citizen and the science of government. Science of government was the term of art. Think about what that means, right? Science of government would be game theory, coordination theory, history – it wouldn't call it game theory yet – history, sociology, economics, right? All the things that lead to how we understand human coordination. I think it's so profound that he didn't say the number one aim of the federal government is rule of law and he didn't say it's protecting the border from enemies because if the number one aim was to protect the border from enemies, it could do that as military dictatorship quite effectively. And if the goal was rule of law, it could do it as a dictatorship, as a police state. And so if the number one goal is anything other than the comprehensive education of all the citizens and the science of government, it won't stay democracy long. You can see – so both education and the fourth estate – the fourth estate being – so education, can I make sense of the world? Am I trained to make sense of the world? The fourth estate is what's actually going on currently, the news. Do I have good unbiased information about it? Those are both considered prerequisite institutions for democracy to even be a possibility. And then at the scale it was initially suggested here, the town hall was the key phenomena where there wasn't a special interest group crafted a proposition and the first thing I ever saw was the proposition, didn't know anything about it and I got to vote yes or no. It was in the town hall. We all got to talk about it and the proposition could get crafted in real time through the conversation, which is why there was that founding father statement that voting is the death of democracy. Voting fundamentally is polarizing the population in some kind of sublimated war. And we'll do that as the last step. But what we want to do first is to say how does the thing that you care about that seems damaged by this proposition, how could that turn into a solution to make this proposition better? Where this proposition still tends to the thing it's trying to tend to and tends to that better. Can we work on this together? And in a town hall we could have that. As the scale increased, we lost the ability to do that. Now as you mentioned, the internet could change that. The fact that we had representatives that had to ride a horse from one town hall to the other one to see what the colony would do, that we stopped having this kind of developmental development process when the town hall ended. The fact that we have not used the internet to recreate this is somewhere between insane and aligned with class interests. I would push back to say that the internet has those things, it just has a lot of other things. I feel like the internet has places where that encouraged synthesis of competing ideas and sense making, which is what we're talking about, is just that it's also flooded with a bunch of other systems that perhaps are out competing it under current incentives. Perhaps it has to do with capitalism and the market. Linux is awesome, right? And Wikipedia and places where you have, and they have problems, but places where you have open source sharing of information, vetting of information towards collective building. Is that building something like, how much has that affected our court systems or our policing systems or our military systems? First of all, I think a lot, but not enough. I think this is something I told you offline yesterday, perhaps it's a whole nother discussion, but I don't think we're quite quantifying the impact on the world, the positive impact of Wikipedia. You said the policing, I just think the amount of empathy that, like knowledge, I think can't help but lead to empathy. Just knowing, okay, I'll give you some pieces of information. Knowing how many people died in various wars, already that delta, when you have millions of people have that knowledge, it's a little slap in the face, like, oh, my boyfriend or girlfriend breaking up with me is not such a big deal when millions of people were tortured. Just a little bit. And when a lot of people know that because of Wikipedia, or the effect, their second order effect of Wikipedia, which is, it's not that necessarily people read Wikipedia, it's like YouTubers who don't really know stuff that well will thoroughly read a Wikipedia article and create a compelling video describing that Wikipedia article that then millions of people watch, and they understand that, holy shit, a lot of, there was such, first of all, there was such a thing as World War II and World War I, okay? They can at least learn about it, they can learn about that this was recent, they can learn about slavery, they can learn about all kinds of injustices in the world. And that I think has a lot of effects to the way, whether you're a police officer, a lawyer, a judge, in the jury, or just a regular civilian citizen, the way you approach every other communication you engage in, even if the system of that communication is very much flawed. So I think there's a huge positive effect on Wikipedia. That's my case for Wikipedia. So you should donate to Wikipedia. I'm a huge fan, but there's very few systems like it, which is sad to me. So I think it would be a useful exercise for any listener of the show to really try to run the dialectical synthesis process with regard to a topic like this, and take the techno concern perspective with regard to information tech that folks like Tristan Harris take and say, what are all of the things that are getting worse? And are any of them following an exponential curve? And how much worse, how quickly could that be? And then, and do that fully without mitigating it. Then take the techno optimist perspective and see what things are getting better in a way that Kurzweil or Diamandis or someone might do. And try to take that perspective fully and say, are some of those things exponential? What could that portend? And then try to hold all that at the same time. And I think there are ways in which, depending upon the metrics we're looking at, things are getting worse on exponential curves and better on exponential curves for different metrics at the same time, which I hold as the destabilization of previous system. And either an emergence to a better system or a collapse to a lower order are both possible. And so I want my optimism not to be about my assessment. I want my assessment to be just as fucking clear as it can be. I want my optimism to be what inspires the solution process on that clear assessment. So I never want to apply optimism in the sense making, right? I want to just try to be clear. If anything, I want to make sure that the challenges are really well understood. But that's in service of an optimism that there are good potentials, even if I don't know what they are, that are worth seeking, right? There is some sense of optimism that's required to even try to innovate really hard problems. But then I want to take my pessimism and red team my own optimism to see, is that solution not going to work? Does it have second-order effects? And then not get upset by that because I then come back to how to make it better. So just a relationship between optimism and pessimism and the dialectic of how they can work. So of course, we can say that Wikipedia is a pretty awesome example of a thing. We can look at the places where it has limits or has failed, where on a celebrity topic or corporate interest topic, you can pay Wikipedia editors to edit more frequently and various things like that. But you can also see where there's a lot of information that was kind of decentrally created that is good information that is more easily accessible to people than everybody buying their own encyclopedia Britannica or walking down to the library and that can be updated in real time faster. And I think you're very right that the business model is a big difference because Wikipedia is not a for-profit corporation. It is a – it's tending to the information commons and it doesn't have an agenda other than tending to the information commons. And I think the two masters issue is a tricky one where I'm trying to optimize for very different kinds of things where I have to sacrifice one for the other and I can't find synergistic satisfiers. Which one? And if I have a fiduciary responsibility to shareholder profit maximization, then what does that end up creating? I think the ad model that Silicon Valley took – I think Jaron Lanier – I don't know if you've had him on the show. But he has an interesting assessment of the nature of the ad model. Silicon Valley wanting to support capitalism and entrepreneurs to make things but also the belief that information should be free and also the network dynamics where the more people you got on, you got increased value per user, per capita. As more people got on, so you didn't want to do anything to slow the rate of adoption. Some places actually PayPal paying people money to join the network because the value of the network would be – there'd be a Metcalf-like dynamic proportional to the square of the total number of users. So the ad model made sense of how do we make it free but also be a business, get everybody on but not really thinking about what it would mean to – and this is now the whole idea that if you aren't paying for the product, you are the product. If they have a fiduciary responsibility to their shareholder to maximize profit, their customer is the advertiser, the user who it's being built for is to do behavioral mod for them for advertisers, that's a whole different thing than that same type of tech could have been if applied with a different business model or a different purpose. I think there – because Facebook and Google and other information and communication platforms end up harvesting data about user behavior that allows them to model who the people are in a way that gives them more sometimes specific information and behavioral information than even a therapist or a doctor or a lawyer or a priest might have in a different setting. They basically are accessing privileged information, there should be a fiduciary responsibility. In normal fiduciary law, if there's this principal agent thing, if you are a principal and I'm an agent on your behalf, I don't have a game theoretic relationship with you. If you're sharing something with me and I'm the priest or I'm the therapist, I'm never going to use that information to try to sell you a used car or whatever the thing is. Facebook is gathering massive amounts of privileged information and using it to modify people's behavior for a behavior that they didn't sign up for wanting the behavior but what the corporation did. So I think this is an example of the physical tech evolving in the context of the previous social tech where it's being shaped in particular ways. And here, unlike Wikipedia that evolved for the information commons, this evolved for fulfilling particular agentic purpose. Most people when they're on Facebook think it's just a tool that they're using. They don't realize it's an agent. It is a corporation with a profit motive and as I'm interacting with it, it has a goal for me different than my goal for myself. And I might want to be on for a short period of time. Its goal is maximize time on site. And so there is a rivalry that is – but where there should be a fiduciary contract. I think that's actually a huge deal. And I think if we said could we apply Facebook-like technology to develop people's citizenry capacity, right? To develop their personal health and well-being and habits as well as their cognitive understanding, the complexity with which they can process the health of their relationships. That would be amazing to start to explore. And this is now the thesis that we started to discuss before is every time there is a major step function in the physical tech, it obsoletes the previous social tech and the new social tech has to emerge. What I would say is that when we look at the nation state level of the world today, the more top-down authoritarian nation states are – as the exponential tech started to emerge, the digital technology started to emerge, they were in a position for better long-term planning and better coordination. And so the authoritarian states started applying the exponential tech intentionally to make more effective authoritarian states. And that's everything from like an Internet of Things surveillance system going into machine learning systems to the Sesame Credit System to all those types of things. And so they're upgrading their social tech using the exponential tech. Otherwise within a nation state like the US but democratic open societies, the countries, the states are not directing the technology in a way that makes a better open society, meaning better emergent order. They're saying, well, the corporations are doing that and the state is doing the relatively little thing it would do aligned with the previous corporate law that no longer is relevant because there wasn't fiduciary responsibility for things like that. There wasn't antitrust because this creates functional monopolies because of network dynamics, right, where YouTube has more users than Vimeo and every other video player together. Amazon has a bigger percentage of market share than all of the other markets together. You get one big dog per vertical because of network effect, which is a kind of organic monopoly that the previous antitrust law didn't even have a place – that wasn't a thing. Antimonopoly was only something that emerged in the space of government contracts. So what we see is the new exponential technology is being directed by authoritarian nation states to make better authoritarian nation states and by corporations to make more powerful corporations. The powerful corporations, when we think about the Scottish Enlightenment, when the idea of markets was being advanced, the modern kind of ideas of markets, the biggest corporation was tiny compared to what the biggest corporation today is. So the asymmetry of it relative to people was tiny. And the asymmetry now in terms of the total technology it employs, total amount of money, total amount of information processing is so many orders of magnitude. And rather than there be demand for an authentic thing that creates a basis for supply, as supply started to get way more coordinated and powerful and the demand wasn't coordinated because you don't have a labor union of all the customers working together, but you do have a coordination on the supply side, supply started to recognize that it could manufacture demand. It could make people want shit that they didn't want before that maybe wouldn't increase their happiness in a meaningful way. It might increase addiction. Addiction is a very good way to manufacture demand. And so as soon as manufactured demand started through this is the cool thing and you have to have it for status or whatever it is, the intelligence of the market was breaking. Now it's no longer a collective intelligence system that is upregulating real desire for things that are really meaningful. We're able to hijack the lower angels of our nature rather than the higher ones, the addictive patterns drive those and have people want shit that doesn't actually make them happier, make the world better. And so we really also have to update our theory of markets because behavioral econ showed that homo economicus, the rational actor is not really a thing, but particularly at greater and greater scale can't really be a thing. Voluntarism isn't a thing where if my company doesn't want to advertise on Facebook, I just will lose to the companies that do because that's where all the fucking attention is. And so then I can say it's voluntary, but it's not really if there's a functional monopoly, same if I'm going to sell on Amazon or things like that. So what I would say is these corporations are becoming more powerful than nation states in some ways. And they are also debasing the integrity of the nation states, the open societies. So the democracies are getting weaker as a result of exponential tech and the kind of new tech companies that are kind of a new feudalism, tech feudalism, because it's not a democracy inside of a tech company or the supply and demand relationship when you have manufactured demand and kind of monopoly type functions. And so we have basically a new feudalism controlling exponential tech and authoritarian nation states controlling it. And those attractors are both shitty. And so I'm interested in the application of exponential tech to making better social tech that makes emergent order possible. And where then that emergent order can bind and direct the exponential tech in fundamentally healthy not X risk oriented directions. I think the relationship of social tech and physical tech can make it. I think we can actually use the physical tech to make better social tech, but it's not given that we do. If we don't make better social tech, then I think the physical tech empowers really shitty social tech that is not a world that we want. I don't know if it's a road we want to go down, but I tend to believe that the market will create exactly the thing you're talking about, which I feel like there's a lot of money to be made in creating a social tech that creates a better citizen, that creates a better human being. Your description of Facebook and so on, which is a system that creates addiction, which manufactures demand, is not obviously inherently the consequence of the markets. I feel like that's the first stage of us like baby deer trying to figure out how to use the internet. I feel like there's much more money to be made with something that creates compersion and love, honestly. I can make the business case for it. I don't think we want to really have that discussion, but do you have some hope that that's the case? I guess if not, then how do we fix the system of markets that worked so well for the United States for so long? Well, like I said, every social tech worked for a while. Tribalism worked well for 200,000 or 300,000 years. I think social tech has to keep evolving. The social technologies with which we organize and coordinate our behavior have to keep evolving as our physical tech does. I think the thing that we call markets – of course we can try to say, oh, even biology runs on markets. But the thing that we call markets, the underlying theory, homo economicus, demand, driving supply, that thing broke. It broke with scale in particular and a few other things. So it needs updated in a really fundamental way. I think there's something even deeper than making money happening that in some ways will obsolete moneymaking. I think capitalism is not about business. So if you think about business, I'm going to produce a good or a service that people want and bring it to the market so that people get access to that good or service. That's the world of business. But that's not capitalism. Capitalism is the management and allocation of capital, which financial services was a tiny percentage of the total market. It's become a huge percentage of the total market. It's a different creature. So if I was in business and I was producing a good or service and I was saving up enough money that I started to be able to invest that money and gain interest or do things like that, I start realizing I'm making more money on my money than I'm making on producing the goods and services. So I stop even paying attention to goods and services and start paying attention to making money on money and how do I utilize capital to create more capital. And capital gives me more optionality because I can buy anything with it than a particular good or service that only some people want. Capitalism – more capital ended up meaning more control. I could put more people under my employment. I could buy larger pieces of land, novel access to resource, mines and put more technology under my employment. So it meant increased agency and also increased control. I think attentionalism is even more powerful. So rather than enslave people where the people kind of always want to get away and put in the least work they can, there's a way in which economic servitude was just more profitable than slavery, right? Have the people work even harder voluntarily because they want to get ahead and nobody has to be there to whip them or control them or whatever. This is a cynical take but a meaningful take. So people – so capital ends up being a way to influence human behavior, right? And yet where people still feel free in some meaningful way. They're not feeling like they're going to be punished by the state if they don't do something. It's like punished by the market via homelessness or something. But the market is this invisible thing I can't put an agent on so it feels like free. And so if you want to affect people's behavior and still have them feel free, capital ends up being a way to do that. But I think affecting their attention is even deeper because if I can affect their attention, I can both affect what they want and what they believe and what they feel. And we statistically know this very clearly. Facebook has done studies that based on changing the feed, it can change beliefs, emotional dispositions, etc. And so I think there's a way that the harvest and directing of attention is even a more powerful system than capitalism. It is effective in capitalism to generate capital but I think it also generates influence beyond what capital can do. And so do we want to have some groups utilizing that type of tech to direct other people's attention? If so, towards what? Towards what metrics of what a good civilization and good human life would be? What's the oversight process? What is the… Transparency, I can answer all the things you're mentioning. I guarantee you if I'm not such a lazy ass, I'll be part of the many people doing this as transparency and control, giving control to individual people. Okay, so maybe the corporation has coordination on its goals that all of its customers or users together don't have. So there's some asymmetry where it's asymmetry of its goals but maybe I could actually help all of the customers to coordinate almost like a labor union or whatever by informing and educating them adequately about the effects, the externalities on them. This is not toxic waste going into the ocean of the atmosphere. It's their minds, their beings, their families, their relationships such that they will in group change their behavior. So I think the – one way of saying what you're saying I think is that you think that you can rescue homo economicus from the rational actor that will pursue all the goods and services and choose the best one at the best price, the kind of Rand, Von Mises Hayek, that you can rescue that from Dan Ariely and behavioral econ that says that's actually not how people make choices. They make it based on status hacking largely whether it's good for them or not in the long term and the large asymmetric corporation can run propaganda and narrative warfare that hits people's status buttons and their limbic hijacks and their lots of other things in ways that they can't even perceive that are happening. They're not paying attention to that. The site is employing psychologists and split testing and whatever else. So you're saying I think we can recover homo economicus. And not just through a single mechanism of technology, there's the – not to keep mentioning the guy but platforms like Joe Rogan and so on that help make viral the ways that the education of negative externalities can become viral in this world. So interestingly, I actually agree with you that – I got him. Four and a half hours in. That we can – Tech can do some good. All right. Well, see what you're talking about is the application of tech here, broadcast tech where you can speak to a lot of people. And that's not going to be strong enough because the different people need spoken to differently which means it has to be different voices that get amplified to those audiences more like Facebook's tech. But nonetheless, we'll start with broadcast tech. That's the first seed and then the word of mouth is a powerful thing. You need to do the first broadcast shotgun and then it like lands or catapult or whatever. I don't know what the right weapon is. But then it just spreads the word of mouth through all kinds of tech including Facebook. So let's come back to the fundamental thing. The fundamental thing is we want a kind of order at various scales from the conflicting parts of ourself actually having more harmony than they might have to family, extended family, local, all the way up to global. We want emergent order where our choices have more alignment, right? We want that to be emergent rather than imposed or rather than we want fundamentally different things or make totally different sense of the world where warfare of some kind becomes the only solution. Emergent order requires us in our choice making, requires us being able to have related sense making and related meaning making processes. Can we apply digital technologies and exponential tech in general to try to increase the capacity to do that where the technology called a town hall, the social tech that we'd all get together and talk obviously is very scale limited. And it's also oriented to geography rather than networks of aligned interest. Can we build new better versions of those types of things? And going back to the idea that a democracy or participatory governance depends upon comprehensive education in the science of government which include being able to understand things like asymmetric information warfare on the side of governments and how the people can organize adequately. Can you utilize some of the technologies now to be able to support increased comprehensive education of the people and maybe comprehensive informantness? So both fixing the decay in both education and the fourth estate that have happened so that people can start self-organizing to then influence the corporations, the nation states to do different things and or build new ones themselves. Yeah, fundamentally that's the thing that has to happen. The exponential tech gives us a novel problem landscape that the world never had. The nuke gave us a novel problem landscape. And so that required this whole Bretton Woods world. The exponential tech gives us a novel problem landscape. Our existing problem solving processes aren't doing a good job. We have had more countries get nukes. We haven't done nuclear deproliferation. We haven't achieved any of the UN sustainable development goals. We haven't kept any of the new categories of tech from making arms races. So our global coordination is not adequate to the problem landscape. So we need fundamentally better problem solving processes. A market or a state is a problem solving process. We need better ones that can do the speed and scale of the current issues. Right now speed is one of the other big things is that by the time we regulated DDT out of existence or cigarettes not for people under 18, they'd already killed so many people and we let the market do the thing. But as Elon has made the point, that won't work for AI. By the time we recognize afterwards that we have an auto poetic AI, that's a problem, you won't be able to reverse it. That there's a number of things that when you're dealing with tech that is either self replicating and disintermediates humans to keep going, doesn't need humans to keep going, or you have tech that just has exponentially fast effects, your regulation has to come early. It can't come after the effects have happened. The negative effects have happened if because the negative effects could be too big too quickly. So we basically need new problem solving processes that do better at being able to internalize externality, solve the problems on the right time scale and the right geographic scale. And those new processes to not be imposed have to emerge from people wanting them and being able to participate in their development, which is what I would call kind of a new cultural enlightenment or Renaissance that has to happen, where people start understanding the new power that exponential tech offers, the way that it is actually damaging current governance structures that we care about and creating an X-risk landscape, but could also be redirected towards more pro-topic purposes. And then saying, how do we rebuild new social institutions? What are adequate social institutions where we can do participatory governance at scale and time? And how can the people actually participate to build those things? The solution that I see working requires a process like that. And the result maximizes love. So again, Elon, you'd be right that love is the answer. Let me take it back from the scale of societies to the scale that's far, far more important, which is the scale of family. You've written a blog post about your dad. We have various flavors of relationships with our fathers. What have you learned about life from your dad? Well, people can read the blog post and see a lot of individual things that I learned that I really appreciated. If I was to kind of summarize at a high level, I had a really incredible dad, like very, very unusually positive set of experiences. He was committed. We were homeschooled. And he was committed to work from home to be available and like prioritize fathering in a really deep way. And as a super gifted, super loving, very unique man, he also had his unique issues that were part of what crafted the unique brilliance. And those things often go together. And I say that because I think I had some unusual gifts and also some unusual difficulties. And I think it's useful for everybody to know their path probably has both of those. But if I was to say kind of at the essence of one of the things my dad taught me across a lot of lessons was like the intersection of self-empowerment, ideas and practices that self-empower towards collective good, towards some virtuous purpose beyond the self. And he both said that a million different ways, taught it in a million different ways. When we were doing construction and he was teaching me how to build a house, we were putting the wires to the walls before the drywall went on. He made sure that the way that we put the wires through was beautiful. He made sure that the height of the holes was similar, that we twisted the wires in a particular way. And it's like no one's ever going to see it. And he's like if a job's worth doing, it's worth doing well and excellence is its own reward and those types of ideas. And if there was a really shitty job to do, he'd say see the job, do the job, stay out of the misery. Just don't indulge any negativity, do the things that need done. And so there's like a – there's an empowerment and a nobility together. And yeah, extraordinarily fortunate. Is there ways you think you could have been a better son? Is there things you regret? That's an interesting question. Let me first say just as a bit of a criticism that what kind of man do you think you are not wearing a suit and tie? A real man should. Actually I agree with your dad on that point. You mentioned offline that he suggested a real man should wear a suit and tie. But outside of that, is there ways you could have been a better son? Maybe next time on your show I'll wear a suit and tie. My dad would be happy about that. Please. I can answer the question later in life, not early. I had just a huge amount of respect and reverence for my dad when I was young. So I was asking myself that question a lot. So there weren't a lot of things I knew that I wasn't seeking to apply. There was a phase when I went through my kind of individuation differentiation where I had to make him excessively wrong about too many things. I don't think I had to, but I did. And he had a lot of kind of non-standard model beliefs about things, whether early kind of ancient civilizations or ideas on evolutionary theory or alternate models of physics. And they weren't irrational, but they didn't all have the standard of epistemic proof that I would need. And I went through, and some of them were kind of spiritual ideas as well. I went through a phase in my early 20s where I kind of had the attitude that Dawkins or Christopher Hitchens has that can kind of be like excessively certain and sanctimonious applying their reductionist philosophy of science to everything and kind of brutally dismissive. I'm embarrassed by that phase. Not to say anything about those men and their path, but for myself. And so during that time, I was more dismissive of my dad's epistemology than I would have liked to have been. I got to correct that later, apologize for it. But that was the first thought that came to mind. You've written the following. I've had the experience countless times, making love, watching a sunset, listening to music, feeling the breeze, that I would sign up for this whole life and all of its pains just to experience this exact moment. This is a kind of worldless knowing. It's the most important and real truth I know, that experience itself is infinitely meaningful and pain is temporary. And seen clearly, even the suffering is filled with beauty. I have experienced countless lives worth of moments worthy of life, such an unreasonable fortune. A few words of gratitude from you, beautifully written. Is there some beautiful moments? Now you have experienced countless lives worth of those moments, but is there some things that if you could, in your darker moments, you can go to to relive, to remind yourself that the whole ride is worthwhile? Maybe skip the making love part. We don't want to know about that. I mean, I feel unreasonably fortunate that it is such a humongous list because I mean, I feel fortunate to have like had exposure to practices and philosophies in a way of seeing things that makes me see things that way. So I can take responsibility for seeing things in that way and not taking for granted really wonderful things, but I can't take credit for being exposed to the philosophies that even gave me that possibility. You know, it's not just with my wife, it's with every person who I really love when we're talking, I look at their face. I, in the context of a conversation, feel overwhelmed by how lucky I am to get to know them. And like there's never been someone like them in all of history and there never will be again. And they might be gone tomorrow. I might be gone tomorrow. But I'm in a moment with them. And when you take in the uniqueness of that fully and the beauty of it, it's overwhelmingly beautiful. And I remember the first time I did a big dose of mushrooms and I was looking at a tree for a long time and I was just crying with overwhelm at how beautiful the tree was. And it was a tree outside the front of my house that I'd walked by a million times and never looked at like this. And it wasn't the dose of mushrooms where I was hallucinating like where the tree was purple. Like the tree still looked like, if I had to describe it, say it's green and it has leaves looks like this, but it was way fucking more beautiful, like capturing than it normally was. And I'm like, why is it so beautiful if I would describe it the same way? And I realized I had no thoughts taking me anywhere else. Like what it seemed like the mushrooms were doing was just actually shutting the narrative off that would have me be distracted so I could really see the tree. And then I'm like, fuck, when I get off these mushrooms, I'm going to practice seeing the tree because it's always that beautiful and I just miss it. And so I practice being with it and quieting the rest of the mind and then being like, wow. And if it's not mushrooms, like people have peak experiences where they'll see life and how incredible it is. It's always there. It's funny that I had this exact same experience on quite a lot of mushrooms, just sitting alone and looking at a tree and exactly as you described it, appreciating the undistorted beauty of it. And it's funny to me that here's two humans, very different, with very different journeys, where at some moment in time, both looking at a tree like idiots for hours and just in awe and happy to be alive. And yeah, even just that moment alone is worth living for. But you did say humans and we have a moment together as two humans. And you mentioned shots. I have to ask, what are we looking at? When I went to go get a smoothie before coming here, I got you a keto smoothie that you didn't want because you're not just keto but fasting. But I saw the thing with you and your dad where you did shots together. And this place happened to have shots of ginger turmeric cayenne juice of some kind. And so I- With some Himalayan salt. I didn't necessarily plan it for being on the show. I just brought it. Wow. But we can do it that way. I think we shall toast like heroes, Daniel. It's a huge honor. What do we toast to? What do we toast to? We toast to this moment, this unique moment that we get to share together. I'm very grateful to be here in this moment with you and yeah, I'm grateful that you invited me here. We met for the first time and I will never be the same for the good and the bad. That is really interesting. That feels way healthier than the vodka my dad and I were drinking. So I feel like a better man already. Daniel, this is one of the best conversations I've ever had. I can't wait to have many more. Likewise. This has been an amazing experience. Thank you for wasting all your time today. I want to say in terms of what you're mentioning about like the, that you work in machine learning and the optimism that wants to look at the issues, but wants to look at how this increased technological power could be applied to solving them. And that even thinking about the broadcast of like, can I help people understand the issues better and help organize them like fundamentally you're oriented like Wikipedia. What I see to really try to tend to the information commons without another agentic interest distorting it. And for you to be able to get guys like Lee Smolin and Roger Penrose and like the greatest thinkers of that are alive and have them on the show. And most people would never be exposed to them and talk about it in a way that people can understand. I think it's an incredible service. I think you're doing great work. So I was really happy to hear from you. Thank you, Daniel. Thanks for listening to this conversation with Daniel Schmachtenberger. And thank you to Ground News, NetSuite, Four Sigmatic, Magic Spoon, and BetterHelp. Check them out in the description to support this podcast. And now let me leave you with some words from Albert Einstein. I know not with what weapons World War III will be fought, but World War IV will be fought with sticks and stones. Thank you for listening, and hope to see you next time.

https://youtu.be/hGRNUw559SE

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Michael Malice: Freedom, Hope, and Happiness Amidst Chaos | Lex Fridman Podcast #150

The following is a conversation with Michael Malice, his second time on the podcast. He's an anarchist, political thinker, podcaster, and author. He wrote Dear Reader, which is a book on North Korea, and The New Right, a book on the various ideological movements at the fringe of American politics. He hosts a podcast called You're Welcome, spelled Y-O-U-R, and in general, there's a lot of live shows on YouTube that are at times profoundly absurd, and at other times, absurdly profound, and always full of humor and wisdom. He is the Joker to my Batman, and the caviar to my vodka. His masterful dance between dark humor and difficult, even dangerous ideas, challenges me to think deeply about this world, and when that fails, at least smile and have a good laugh at the absurdity of it all. This episode has much of that. His outfit, for example, the exact inverse of mine, with a white suit and a black shirt, is just one example of that, of the humor, trolling, and brilliance that is Michael Malice. Quick mention of our sponsors. NetSuite, business management software, Athletic Greens, all-in-one nutrition drink, Sun Basket, meal delivery service, and Cash App. So the choice is success, health, food, or money. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. As a side note, let me say that Michael is, in many ways, a man of radical ideas, but also a man with kindness in his heart. Those two things are great ingredients for a fascinating conversation. I hope to have several such people on this podcast this upcoming year who also have radical ideas about politics, science, technology, and life. At times, often perhaps, I might fail at asking the challenging questions that should be asked, but I will try my best to do so, and hope to keep improving every time. Mostly, I come to these conversations with an open mind and with love. Unfortunately, that kind of approach can be taken advantage of in many ways. It can be used by reporters or just people online later to highlight how or why I'm ignorant or worse, I'm generally not a good human being. In the context of this, I have two options. I could either be cautious and afraid, or second, be kind, thoughtful, and fearless. I choose the latter, hopefully while still being open, fragile, and empathetic. Again, I strive to be like the main character of The Idiot by Dostoevsky. That's my New Year's resolution. Be kind and do difficult things, difficult conversations, difficult research projects, and difficult entrepreneurial adventures. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support it on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Michael Malice. Knock, knock. You're stealing my bed? I'll kill your family. That's not how a knock-knock joke works. Knock, knock, Michael. You don't do knock-knock jokes. You don't do knock-knock jokes with Russians. We have to knock at the door, turn down the TV, you got to sit quiet, and we hope they go away. You don't do that back in the motherland. You know this. It's triggering. Who's there? I can't even do it now. Knock, knock. Who's there? Leon. Leon who? Leon me when you're not strong, Michael. Well, that will never happen. I stole, elegantly, eloquently, that joke from you. The lie detector term. That was a lie. Elegantly and eloquently. Yeah, you crossed it on a sheet of paper. That means it's real. The reason I bring it up is because you had the guts, the brilliance, to do a knock-knock joke, not once, but three times with Alex Jones. I think it was like six. I had a runner. Okay. Maybe they started to sort of melt together in this beautiful art form that you've created, which is like these kind, loving knock-knock jokes with Alex Jones. So you got the chance to meet him and talk to him twice with Tim Pool in a long-form conversation. What was it like talking to Alex Jones, both on the deep philosophical intellectual level and staring the man in his eyes and doing a knock-knock joke about Olive? Knock, knock. Who's there? Olive. I love you, Alex. I love you. Well, there's a lot to explain. Where do you start? I've been on his show, InfoWars, a few times when I was researching my book. Then you write. So I had had conversations with him before. One of the things that I appreciate about Alex is he is a lot more self-aware than people think and has a good sense of humor. And I also like a good twist ending. So if you set people up and all these jokes are these kind of vapid, you know, all of you jokes, and the last one's about Building 7, they're not going to see that one coming, nor will he see that one coming. I even had another one about Sandy Hook, which I didn't do on the air because he was being like a good sport. So I didn't, but that was the dagger that was kind of behind my back if necessary. But it was a good mechanism toward, I like it when things work on several levels. It was also a good mechanism to keep kind of the conversation guarded. And this every so often, this is kind of hitting the control, delete, and bring it down to a certain point of calmness. What about the love thing? I mean, you're saying that that was a buildup to the dagger, but it was also somehow really refreshing to get that little jolt, like that pause. You don't get that in conversations often. Like I'm a huge fan of Rogan, and he'll have a three-hour conversation. But at some point, just pause and be like, I love you, man. Like it's in the cheesiest way possible, because that seems to be, it somehow hits the hardest then. I don't know, I don't know you didn't intend it that way, but with Alex Jones to sit there and to say, I love you, that was like, I just haven't never heard that before. And so it struck me as like, not just funny for what you're doing, but just like, whoa, we just took, because conversations are all about like this ranting, especially with Alex Jones, just like ranting about this or that, this part of the world, like, can you believe this shit, that kind of thing. But like to pause and be like, this is awesome. I don't know if you felt that way, but... Oh, I definitely felt that way. So it was actually very fun. I'll give you the backstory of how that happened. It was silly, because Tim calls me up, and there's this expression in marketing, don't go past the sale, right? So if you're trying to sell someone a car, and like, it's got this feature, this feature, that feature, and they're like, you know what, I'm going to buy the car. If you keep talking, you can only make them lose the sale. You just get them to sign and get out of Dodge. So Tim calls me up and he goes, okay, here's what we're thinking. This is top secret. Alex is going to be on the show. We want you on as well. And I've never said yes to anything as quickly in my life. And then he keeps talking and I'm like, Tim, you don't have to sell it. I interrupted him, I go, you don't have to sell it. Why you, by the way? I think because I am kind of an agent of chaos, and Alex is in his own way, an agent of chaos. And what is, provides an opportunity in this kind of news media space that you and I travel in, it's the kind of things where none of us three, you know, as we said on the show, knew what it would be like. If you know to certain, within certain parameters, what, you know, Megyn Kelly or Wolf Blitzer or any of these corporate figures are going to be like in a conversation, to some extent, none of us had any idea. And I knew they didn't know I was bringing knock-knock jokes. So that was kind of what was so exciting. I said at one point, I'm kind of envious of the audience, because this is, there's so many exciting things that are happening and that the internet and podcasting provides people an opportunity to do, that it was great. Yeah, that was the greatest pairing with Alex Jones that I've ever seen by far. So like, wow, okay, thank you. So I immediately knew, now this isn't a knock on Tim, but I don't even know if Tim was prepared. Tim was not prepared. For this couple. How could he be prepared? Well, so I mean, I don't know if Tim is used to that. I think Joe Rogan is more equipped, prepared for the chaos, just the years he's been in it. Like I immediately thought this is the right pairing for Joe Rogan, because Alex Jones has been on Joe Rogan a few times, three times. My favorite so far was with Tim Dillon. Right, for, yeah. But Tim was clearly, Tim Dillon was also kind of a genius in his own right, but he was kind of a fan and he was stepping away. He was almost like in awe of Alex Jones, where you were both, you were in awe of the experience that's being created, and at the same time, fearlessly just trolling the situation. I mean, to do a knock-knock joke to stop me, that just shows that you're in control of the experience. No, you're like riding the experience. That immediately was like, this needs to be on Rogan. So I hope that happens as well. You're on your own, of course, on Rogan, but just you, that's an experience. That's the, whatever, there's gotta be a good name for it. Like Jimi Hendrix experience. There's the Michael and Alex. That's a bad name for it, because that was a bad name. It's taken, well, I don't know how many years you can restart the experience. Because I feel, sorry to interrupt you, I feel a very big responsibility, especially in 2020, to provide fun and something cool and something unique that hasn't been done before for the audience. I think this has been a very rough year on our audiences, psychologically and in other aspects of their lives. So I feel if I'm gonna be there, I'm going to put on a show. And it's also gonna be great, because it also alienates the people you don't want, right? So there's a lot of people who sit there and be like, oh, he's telling, people who are too cool for school, where they're like, oh, he's telling knock-knock jokes. This is stupid. I'm like, good. If you have an issue with having eaten cotton candy or doing a puzzle with a kid or without it, by yourself, that's on you. And it's something very, something I think is the enemy of cynicism and this idea that like, oh, this is too silly and amethyst. Like we need that kind of childlike aspect in our lives. I think it's something we could use more of. It's very much an aspect of our media culture that to kind of have be condemnatory about that or to do it in a certain very corporate fake way. So it is something I encourage a lot, something I enjoy doing. And again, like the first time I was on Tim, I had a propeller beanie on, with the motorized. And a lot of people were like, I can't take anyone seriously who dresses like this. I go, good. If you judge someone's ideas by how they appear instead of the ideas themselves, you're not someone I want on my team. Are we gonna address the outfit you're wearing? We can address it, sure. For those who are colorblind, Michael's wearing neat, or just listening to this. We're just listening to this. Michael's wearing the exact opposite, the inverse from another dimension outfit, which is a white suit and black shirt. It's so genius. Okay, so- You should see the next two looks I've planned. Oh no. Yeah, they're great. Well, obviously this relationship's gonna end today. So I'll put that on Insta. Okay, is there some deep philosophy to the humor? This goes to our trolling discussion. Sure. Is there some, is there like chapters to this genius, or is this just what makes you smile in the morning? I mean, I think you're honestly, in this case, using the word genius a little loosely. I am. I don't think this is particularly genius. But I do think it is fun. It is exuberant. It is joyous. I think the bigger my audience has gotten, and the more I actually communicate with fans, I do feel it kind of kicks in these paternal, maternal instincts, which is very, very odd. I did not expect to have them. What do you mean? Who's the dad? I'm the dad and the mom. I remember, and it may have been similar for you, I'm curious to hear it. For young, smart, ambitious men, like 24 to 27 for me was a very rough period, because that's the window where a lot of people get married and they kind of check out. And if you're very much kind of finding your own road, you don't know what's happening. No one's in a position to really guide you or help you. And it's tough. It's a very tough window. And what I'm finding now is having these kids who are in that position, but now instead of them stumbling along, for some of them, I'm the one who could be like, no, no, no, no, it's not you. It's everybody else. And to be able to give them that semblance of feeling seen, to use a cliched expression, to feel normal. And that, no, no, you're the heroes here. They're the background noise. It's just really very flattering and humbling to be in that position. You have many minds, right? There's the thoughtful kind. Michael, there's like, I'm going to burn down the powerful. And then there's like, I'm going to have this just lighthearted trolling of the world. And which of those are most important to the 27 demographic? I think it is the combination. It's like if you're making a meal, chicken Kiev, you need the chicken, you need the ham, you need the butter sauce. Because I think people are so, and because I think people, when you're young, you need to see someone who's fought the fight for you and who's won. So it's very easy to be defeatist. So this is what winning looks like. No, this is not. This is most assuredly what winning does not look like. But in my normal clothes, a little bit more. This is a good time to mention that clothes wise, you're wearing sheath underwear and people should buy sheath underwear, use code malice20. If you go to sheathunderwear.com, use promo code malice20. What I love about that, why I'm glad to promote the product and wear it, it's the most comfortable underwear I've ever worn. And you have a separate pouch for both parts of your genitals. That's what you, I thought there was like a punchline coming. No, it's a very nice aspect of the product. Yeah, but I think what, here's something else, just as it goes back to what we're just talking about. There are so many, and this is going to segue into this. There are so many small companies who've been devastated this year. We have not seen a sustained attack on mom and pop shops like we've seen in 2020, who are innovators and making something happen. And when you're just like one dude, who's producing a product, they're a sponsor of mine. I'm happy to, first of all, it's funny that I'm pitching underwear, but haha pitching, but it's also something I enjoy. And also you said small business. Yeah, it's microscopic like a thimble. So this isn't a sponsor of mine, but this is a good segue. So this is Russians we celebrate New Year's. It's Novum Gordum. We have Died Moroz. He comes down, puts a present under your pillow. So this is a company called J.L. Lawson. He's a fan of yours. He's a metal worker. And he said, can I give you something to give to Lex? I have one of his worry coins. I'll tell you what it is. He's not a sponsor. This is not, I'm not getting paid for this. So what a worry coin is, I carry around in my butt. If you have raw denim, it's great because it brings you fades. So you carry it around with you all the time. It says worrying is like paying a debt you don't owe. Right? And I carry this around and for a long time, it's been like a year. Next time you're worrying, and this is good advice if you don't have a worry coin, go think about 10 years ago. Yes. And what you were worried about then. And then think about did any of those things pan out? And some of them did, but you were able to handle it. And that's a good way to maintain perspective. So J.L. Lawson's the company. He sent me this present. I said, let me give it to Lex on air. So enjoy. So I also open it up. Yeah. J.L. Lawson and co to Lex from Anthony. Yeah. And I said, make something mathematical for Lex. So I don't even know what's in there. You don't know what's in there. No. And it got through a TSA. Could be a bomb. It could be just like this episode. Make sure you unwrap it close to the mic because it drives people crazy. That's really the best part. Or is this what unboxing video looks like? I think so. This conversation is going to be a big hit on the internet. With the unboxing community. I need to have an excited look on my face to make sure that the reaction video is an unboxing and a reaction video. Lex Freeman reacts. It's another box. It's just a series of boxes. It's Lex, big fan since hearing you on Rogan months ago. Most of your guests are over my head, but still enjoyable. Like this episode, Michael was kind enough to want to share my work with you. Keep doing what you do. Anthony Lawson. Thanks, Anthony. There's a lot in there. What is it? Give me some. I'll open some. Okay. All right. All right, show it to the camera and then make sure you look excited or not or disappointed. No, this is cool. This is a worry coin like I was showing you. Oh, nice. So you hold it in your hand and when you can do this with your thumb, if people have anxiety or whatever. Oh, there's a lot of cool stuff in here. Fibonacci coin. Oh, see, yeah, that's the math stuff. That's really awesome. This is really cool. Wait, you got a big one in there too. That's what she said. I'm telling you, last time you offended me saying I don't have humor. Sorry. The spin tray, micro brass and copper bronze. By the way, the packaging is epic. I think that's his top. He makes tops. Cool. Yeah, you spin it in there. And it's a two different bronze and copper. I think he's the only one who makes these machined tops. And then he's sitting here, I guess. Yeah, but you could spin them in that section. Got it, cool. Where's the worry thing? Here's the worry coin. Anyway, I wasn't listening. What were you worried about 10 years ago? 10 years ago, 2010. What would I have been worried about then? The government? No, that's not a worry. What was the North Korea book? I apologize. That came out in 2014. I went there in 2012. It came out in January 2014. It still pays my rent with the royalties. The North Korea book? Yeah. This is why it's so much better. I gotta talk to you about self-publishing because you brought that up. The next book's also gonna be self-published. Can we talk about self-publishing? What's the whole idea of publishing, like having a publisher and an agent? Because there's a bunch of people who've been reaching out to me trying to get me to write a book, which is ridiculous. Why? There's people who are brilliant folks like you, like Jordan Peterson, that I think have a lot of knowledge to share with the world. Okay. I think what I feel I can contribute to the world in terms of impact is to build something. Okay. Meaning like engineering stuff. Okay. A book. A book has to be engineered, and I'm not using it loosely. You have to engineer a book. No, for sure. What I mean is literally a product with programming and artificial intelligence. I want to build a company. I have a few ideas that I feel I'm equipped. It has to do with your intuition about the way you can build a better world, you individually. What can you add to the world that's a positive thing? For me, I feel like the maximal thing I can add to the world is at least to attempt to build products that would add more love in the world. So I want to focus on that. The danger of the book for me, or any kind of writing, and even this podcast is a little bit dangerous for me, is like it's fun. That's for sure. It's fun. It's like it takes you into this place where you start thinking about the world, you start enjoying and playing with ideas. You start, just your book on Dear Reader, but also the new right, clearly you and I probably think similarly in the sense that you did a lot of work. Yes, this next book is killing me. Yeah, as you mentioned often, it's clear on your YouTube channel, which I'm a fan of, it just comes out like you mentioned in all of these books that you're reading. It just comes through you that you're suffering through this and it changes you. And it's clear that you're thinking deeply about the world because of this book. And I feel like if you do that, that's like when I first came to this country, I read the book The Giver. I need to read it again. It's like the red pill thing. It changes you in where you can never be the same person again. And I feel about a book in that same way. The moment you write a book, of course it depends on the book. I could also just write, in my field, a very technical book. No, that's a terrible idea. Yes, but that's okay. That doesn't really change you. That's just like sharing information. But something where you're like, how do I think about this world? Can you just leave that behind you? I get it. Dude, it's being pregnant. It never escapes your brain, I'm telling you. You're absolutely right. Yeah, I don't know. It does seem to change you. But the reason I bring that up is because there's this whole industry of people that seem to not really contribute much to the publication process. But they make themselves seem necessary for if you want to be in the New York Times bestseller list kind of thing. But also just being reputable. Yeah. Which I'm allergic to that whole concept. But do you think it's possible to be on the New York Times bestseller list and be a reputable author and still be self-published? Not what you would want to do. People like Mark Sisson, I think is his name. He wrote the Primal Blueprints. So if I'm getting the names correct, he's the first paleo guy, right? So he self-published it. It sold gangbusters. But that would be on their health chart, I believe. And it's a little bit of a different situation. You would be reaching much more for the mainstream. You'd be giving up a lot if you go through a publisher, especially financially. But yeah, you are not going to have the cred. Publishing is a cartel. The New York Times is part of this cartel. And if you don't publish within this cartel, they will do what they can, as any cartel has to, by necessity of being cartel, to pretend you don't exist. So I was, I think, the first one to have an hour on BookTV for Dear Reader, because that was a Kickstarter book. But this is something that people- Dear Reader was a Kickstarter book. Yeah. This is something people would have to be aware of. So you would be giving up a lot. But you'd also be giving a lot to work with a publisher, because you're losing a year and a half of your life, because they're glacial and they don't care. Well, that's my problem. It's not the money. I mean, the money is whatever percent they take, 10, 20, 30, 50%. No, they're taking a huge chunk. So if I sell a book through St. Martin's, it's a dollar. If I sell a book through Amazon, which is Dear Reader, that's $6. So that's what, 87%? It's something crazy. But for me, what bothers me isn't the money, for me personally. For me, what bothers me is incompetence. Like whenever I go to the DMV or something like that- Can I interrupt you? Yeah. Let's talk incompetence. Yeah. New Right comes out last year. Yes. I get on Rogan, get on Rubin, I call them and I said, I got in these shows, is there money in the budget for travel? And they say, we don't have the budget. Fine. By the way, you got on those shows with no help from them. Correct. Oh, yeah, that's not even a question. The reason they would want you to do a book is because they know you could get... The only reason people get book deals nowadays, literally, is because they know that person can market their own book. That's the only way. And I got on Rubin, I got on Rogan, and they go down the money for the budget for travel, which is fair. They can do Skype. They told me this in writing. And I'm like, okay. And- They can financially cover Skype. No, but it's like, hey, Joe, yeah, we don't have the budget, but you're going to do Skype. Hello? Hello? So there is... Another friend of mine was on a show on CNBC with Nassim Taleb. And they said, Nassim wants a copy of the book. And they're like, oh, yeah, it's like four o'clock on Friday. So we're closed. So... And he's like, he went there, picked it up and walked it the two blocks. So there is... It's almost cartoonish. Yeah. And it's not incompetence. It's past that. It's something almost you can't really believe that... I've had two friends who have been literally rendered suicidal because this was such a huge opportunity for them. And it was like watching their kid get beaten in front of them. And I had to talk them off the ledge. So it's... People do not appreciate how bad... Here's another example. The apathy of bureaucracy, something like that. I did this book, Concierge Confidential. There's a typo in the first chapter. It ends with I'm about to. T-O-O. They didn't fix it for the paperback. Who cares? It's just like, well, OK. Yeah. Great book, by the way. It got NPR gave it one of the books of the year. So that was good. So why participate in this? Because otherwise, New York Times is going to pretend you don't exist. Getting booked on some shows might be more difficult, although I think that's collapsing in real time. You're not going to get reviewed necessarily in places like PW or some others. So the new book you're working on, you have a title yet? The White Pill. The White Pill. Are you self-publishing that? Oh, yeah, for sure. And what's the thinking behind that? Just because you already have a huge following and a big platform and... It's six times the cash. If I finish the book in December, I could have it out in February. If I finish the book in December with the publisher, it's going to be out in December at the earliest, 2021. Why am I giving up 10 months of my life? Well, this is the big one. Do you have any leverage? Like, do authors have leverage to say, F you? Like, can you just say... What do you mean? Just look, meaning like, I want to release this book in two months. Oh, no, no. I mean, you'll have a contract and then your agent can fight it, but they don't have the capacity to rush things through. Yeah, I guess if the... Because I've heard big authors, I don't know, Sam Harris, all those folks, talk about like... They've accepted it, actually. They've accepted, they're like, yeah, it takes a long time to... I'm not accepting it. But you're kind of implying that a human being like me should. I'm saying these are your options. Right. So... I just hate it. I hate the waiting because it's incompetence. It's not that... It's not necessarily the wait. If I knew it wasn't... You know, if it was the kind of people that are up at 2 a.m. at night on a Friday and they love what you're doing and they're helping create something special. That's the sense I get with some of the Netflix folks, for example, that work with people. I just, I don't know anything about this world, but you get like Netflix folks who help with shows. You could tell that they're obsessed with those shows. Yeah. You're not going to get that publishing. If you hand... Like I handed the book in, I think it was July. I didn't hear anything from my editor until December. Well, can we actually talk about the suffering? Sure. The darkest parts of writing a book. So let's go to the full Michael Malice, Stephen King mode of... What are the darkest moments of writing this book? And what is it, maybe start the white pill? What's the idea? What's the hope? And what are your darkest moments around writing this book? So people are familiar with the red pill and the blue pill. They're from the Matrix. The red pill is the idea that what is presented as fact by the corporate press, entertainment industry, is in fact a carefully constructed narrative designed to keep some very unpleasant people in power and everyone else under control. And one of my expressions is you take one red pill, not the whole bottle. Yes. Because at a certain point you think everything's a lie and that you're kind of no capacity for distinguishing truths. You're full of good one-liners. Well, thank you. Yeah. I'm full of something, that's for sure. And what I saw in this space is a lot of these red pill people got very disheartened and cynical. And one of my big heroes is Albert Camus, and he said the worst thing is citizen. And that's something called the black pill, which is the idea that it's just, we're waiting for the end. It's hopeless. And I don't see it that way at all. And I'm like, all right, I have to address this. And not just with some kind of cheerleading, everything's going to be great, guys. Here is why I am positive. And not that I'm positive the good guys are going to win, but I'm positive the good guys can win. And that's all you need. Because if your, God forbid, kid is kidnapped and there's a 10% chance that you can save them, you're not going to be like, well, I don't like those odds. This is your country. This is your values. This is your family. I don't think it's much more than 10%. I think it's much more than 10%, and even if you lose, you will take pride in that you did everything in your power to win. Is there a good definition of good guys in the sense that- The ones who wear white. There's layers to this. You're like modern day Shakespeare. Is there a danger in thinking Adolf Hitler was probably pretty confident that he led a group of good guys? Listen, if Hitler did anything wrong, why isn't he in jail? My Czech friend thought of that joke. And he actually says it in his accent. He goes, if Hitler's so bad, why isn't he in the jail? That's a good point. He's probably still alive, right? And look, yeah, hopefully. Oh boy, two of the three people listening to this are very upset right now. What were you even talking about? Oh, how do you know what is good? There's lots of standards of good. But if you're, for me, to be a good guy is if you want to leave the world a little bit better than you found it. That to me is the definition of a good guy. And I think there are many people that that's not their motivation at all. Oh, so it's about your motivation? Well, it's also about if your motivation is at all correlated to reality. No one thinks we're the bad guys. That's correct. But are you taking steps to check your motivations and also take a certain amount of humility? Because if you're going to start interfering with other people's lives, you really better be sure you know what you're doing. Be sure you know what you're talking about. The control of others, if you do have centralized control, or then you kind of, you become a leader of a group, you better know, you better do so humbly and cautiously. And also have steam valves, right? So if in case things go wrong, let's have, I'm sure this is a lot happening with AI, whatever, computers, like, okay, if something goes wrong here, how do we have a workaround to make sure it doesn't cause everything to collapse? Yeah, the going wrong thing. I mean, the whole, the feedback mechanism. I wonder if people in Congress think that things are really wrong. It's working for them. Are you sure? I'm not sure. Because I'd like to believe that the people, that at least when they got into politics, actually wanted, some of it is ego, but some of it is wanting to be the kind of person that builds a better world. Sure. I also think it's diverse. Some are going to have different motivations than others. But once you're in the system and trying to build a better world, how do you know that it's not working? Like, how do you take the basic feedback mechanisms and actually productively change? I mean, that's what it means to be a good guy, is like, hmm, something is wrong here. And that's why I like the Elon Musk, like, think from first principles. Like, wait, wait, wait, okay. Let's ask the big question. Can this be, one, is this working at all? Like, the way we're solving this particular problem of government, is this working at all? And then like, stepping away and saying, like, as opposed to modifying this bill or that bill, or like this little strategy, like increase the tax by this much or decrease the tax by this much. Like, why do we have a democracy at all? Or why do we have any kind of representative democracy? Shouldn't it be a pure democracy? Or why do we have states? Like, representation of states in federal government and so on? Why do we have this kind of separation of powers? Is this different? Why don't we have term limits or not? Like, big things. Like, how do you actually make that happen? And is that what it means to be a good guy? It's like, taking big revolutionary steps as opposed to incremental steps. Well, I don't know that you could be a politician to be a good guy, to be honest. And let me give you a counterexample. Someone who you could tell is not being a good guy. Joe Biden said he was, he regards the Iraq War as a mistake. Okay. You and I have made mistakes in our lives, I'm sure. None of our mistakes have caused tens of thousands of people to die. If, let's suppose I'm being for yourself. I, that's fair. Okay, I'll take that. I don't build the kill bots. If I were a chef, let's take it out of politics. And in my restaurant, somehow, accidentally, someone was going to kill me. Somehow, accidentally, someone ate something and they died. A, I would feel horrible. But more importantly, I would be like, we need to look through this system and figure out how it got to the point where someone lost their life, because that can never happen again. And we need to figure out step by step. I'm not a gun person, but there's like this checklist of like, if you're holding a gun, there's five things to do. And if you get too wrong, you're going to be sick. It's like, assume every gun is loaded, only pointed at something that you want to kill. And there's like three other things. And it's like to make sure that nothing goes wrong. So if I made it, if I'm that chef, and I would have to not only feel guilt, but take preventative action to make sure this has no possibility of happening again. If you look at the staff he's putting in, it's the same warmongers that would have advised him to get into the Iraq war on the first time. That is to me is not a good guy. That to me is someone who does not feel remorse for their responsibility in killing not only many Americans, but some of us think that, you know, dead Iraqis isn't necessarily ideal either. Okay, let's talk a bit about war. Maybe you can also correct me on something. The first time I found myself into Barack Obama was, I don't know how many years ago this was, but when I maybe heard a speech of his about him speaking out against the war. Yeah. And him, I think it's on record saying he was against the war before it was happening. Now, he wasn't in Senate at the time. So it was very easy for him to say this. But see, people say that, people say that, people say it was easy and some people say it's strategically the wise thing to do given some kind of calculus, whatever. But I to this day give him, that's the reason I've always given him props in my mind. This is a man of character. I also personally really value great speeches. I think speeches are really important for leaders because they inspire the world. Yeah, that's fair. One of the most best things you can contribute to the world is great, like through intellect, mold ideas in a way that's communicable to a huge number of people. Yeah, it's better to persuade than to force in every instance. That's where I disagree with Chomsky. Chomsky's whole idea was that if you're a really eloquent speaker, that means your ideas aren't that good. That's nonsense. Yeah, so I think that's a way for him to describe like I speak in a very boring way. Maybe that's the pitch for this podcast. I speak boring so that the ideas are the things you value and it's also useful to go to sleep. But that's why I really liked Obama throughout his life and still do. But when I first saw this, for some reason, you can disagree, I thought he's a man of character is when most politicians, most people who are trying to calculate and rise in power, I think were for the war or too afraid to be against the war. Yeah. That's why I liked Bernie Sanders and that's why I liked in the early days, Obama for speaking out against the war and not like in this weird activist way, not weird, but not saying I'm an activist, but just saying the common sense thing and being brave enough to say the common sense thing without having a big sign and saying I'm going to be the anti-war candidate or something like that. But just saying this is not a good idea. Yeah, and I think it's for those of us who are old enough to remember, it's pretty despicable what happened with Tulsi in 2020. She was the biggest anti-war candidate and she was marginalized within her own party, which I guess you can make sense, she's just a congresswoman from Hawaii, but the corporate press did everything in their power to diminish her and pretend she didn't existed. And for those of us who remember where 12 years prior, when George W. Bush had the Republican National Convention in New York and it was the biggest protest in history and the Iraq war led to democratic landslides in 2006 and 2008, to have that completely not part of the democratic party in 2020 is both shocking and reprehensible. Hey, Michael. You don't have to say, hey, Michael, you just say knock knock. No, it's not a knock knock joke. Oh, okay. What did the volcano say to his true love? What? I love you. These jokes work better when you know how to speak English. It was actually in Russian, I did Google translate. Okay. Back to your book and the suffering, you somehow turned it positive and as one who's wearing, who's the representative of the black pill in this conversation, what are some of the darker moments, what are some of the hardest challenges of putting together this book? Do I pick up on this? I think it's a good question. Some of the hardest challenges of putting together this book, the white pill. Content, content, content. So if I'm having a page in about Reagan taking on Gerald Ford in the 1976 presidential primaries, I'm going to have to read like 20. So it's the thing like if there'll be sometimes I'll remember some quote somewhere and then I have to spend an hour trying to find it because I want it to be as dense with information as possible. Like how do you structure the main philosophical ideas you want to convey? Is that already planned out? No, the book changed entirely from its conception. So my buddy Ryan Holiday had a series of books, still does, where he takes the ideas of the Stoics and he applies them to contemporary terms. He has this whole cottage industry that he's doing very well with. And I'd asked him years ago if I could do that with Camus and he's like, sure, go for it. And I was going to rework Camus' The Myth of Sisyphus. And I read it recently, I reread it, and this wasn't the book I remembered at all. And I'm like, okay, I'm going to write the book that I remembered. But the more I was writing it, one of the things I always yell at conservatives about, and there's a long list, is they don't talk about the great victory of conservatism, which was the winning of the Cold War without firing a shot. And I said, you can't expect the New York Times to tell this story because the blood is on their hands. And I'm like, well, Michael, instead of complaining about it, why don't you do it? Why don't you talk? That is a great example of the good guys winning over the bad guys. And that's become, A, the victory is beautiful, but also pointing out to people, when people are like, oh, things are worse than they've ever been, they don't appreciate how bad things were in the 30s, what Stalin was doing overseas, and how people in the West were advocating to bring that here. So that's kind of pointing out how bad things were and how good they became. And you don't have to be a Republican or conservative to be delighted at the collapse of totalitarianism and the peaceful liberation of half the world. So that's a picture of the good guys winning. Oh, yeah. Well, how does that connect to Sisyphus and maybe speak deeper to life and whatever the hell this thing is, which is what I remember the myth of Sisyphus being about. So where does the threat of Camus sort of lie in the work that you're doing? So the myth of Sisyphus, which I had remembered incorrectly, is actually just a five to seven page coda to the whole book at the very end. You only need to read that little essay called The Myth of Sisyphus. The broader work is about Camus' concept of the absurd and the absurd man within literature. And it's just like, I don't really care about this character and Dostoevsky and all this other stuff that you're talking about. It's of no relevance. But the myth of Sisyphus, the myth itself, not the book or the essay of his, is this Greek character and Sisyphus is forced in hell to roll a rock up a hill for eternity. At the very last moment, the rock falls away. And Camus' takeaway from the story is that we must imagine Sisyphus happy. And there's several interpretations of this, but one is once you accept that you are living an absurdist existence, once you own your reality, it loses its bite. And you can start with that as your baseline. LBW And bite is suffering. CW And hopelessness. So I think when people look at how much ridiculousness is happening in America and it's escalating, you can either think, oh, all is lost, or you can, and I think you and I have lived our lives like this, you can live life more like a surfer, whereas you're never going to control the ocean. But you can sure enjoy that ride and stop, if you're trying to control the waves, yeah, you're done. But if you're like, all right, I've got my board, I'm going to see where this takes me, surfing, from what I understand, is a pretty fun activity and also sometimes dangerous. But you'd have to ask Tulsi about that. LBW So we were offline talking about Stalin and the evils of the Soviet regime. CW Yeah. LBW One of the things I mentioned, I watched the movie Mr. Jones, but it's about the 1930s, called the more, what would you say, the torture of the Ukrainian people by Stalin. One interesting thing to me that I'd love to hear your opinion about is the role of journalism in all of this. And also about 1930s Germany. So what's the role of journalists and intellectuals in a time when trouble is brewing, but it requires a really sort of brave and deep thinking to understand that trouble is brewing. Like if you were a journalist, or if you were just like an intellectual, a thinker, but also a voice in the space of public discourse, what would you do in 1930s about Stalin, about Hothamore? And what would you do about Nazi Germany in 1937, 1938? CW So that's really funny that you asked that, because currently how the book is structured, it's like, you know, books often follow a three-act structure, right? So Act Three is the 80s, Act One is the 30s, and Act Two is going to be like, all right, let's suppose you were in the 30s. Are you just going to give up? Like, are you just going to be like, well, we're screwed? And you'd be right to say things are going to be very bad for a long time. Or are you going to be one of those few who are like, we're going to do something about this, and we're going to go down swinging? There are two books I can recommend, which are just masterpieces that are written by women that just are historians that are just superb. There's a book called Beyond Belief by Deborah Lippstadt. She talks about the rise of Nazi Germany as seen through the press. And what was amazing, and she does a great job empathizing with the press and understand their perspective, is we remember, and Chamberlain gets a bad rap, Neville Chamberlain, for kind of appeasing Hitler, because not that long ago they had the Great War. They had World War I, and they had the carnage that the earth had never seen before. And when you had people made out of meat, meeting industrial machines, and plastic surgery was invented as a consequence of this, they're coming back mangled and disfigured, and for what? And this was a world where the Kaiser was the most evil person who ever lived. And we all had the Western propaganda about the Han, and all the rapes, and all this barbarism, and blah, blah, blah. So not that long later, when you're hearing all this propaganda, which was factual, about Hitler, it's like, we heard this. We heard this 20 years ago. This was all lies. Give us a break. And she has all the quotes from the different agencies and how they addressed it. Plus, they had very limited information. It's not like Nazi Germany was an open society where reporters can walk around, and they were under a lot of pressure as well in those areas. And Hitler himself was pretty good at, he let some stuff slip, but usually he made it seem like he wants peace. He wants world peace. This was amazing. They were making the argument that because all these Jews were being beaten up on the street, this proved, this was the hot take of the day, that Hitler was weak. Because since Hitler's a statesman, and he can't control these hooligans, that shows his control and power is tenuous, and this is all going to go away. By the way, I mean, Hitler thought that too. He was kind of afraid of the Braunschweiz, or whatever. He was afraid of these hooligans a little bit. They were useful to him, but at a certain point, yeah, they can get in the way. Yeah. That's why he wanted to get control of the military, the army, their regiment. If you want to take over the world, you can't do it with hooligans. Right. You have to do it with an actual army. And then you had Kristallnacht, which was a nationwide pogrom, and then all the news agencies universally were like, oh crap, we got this wrong. And the condemnation was universal. So that book traces the West's reaction to what's going on there, and including the reaction to the incipient Holocaust, as people being, you know, what they knew, when did they know. There was not ambiguity about it. People, I think there's this myth that she dispels that they didn't know the Holocaust was happening, or they didn't care. They were aware, but they were already at war with Nazi Germany. Like, literally, what else could they do at that point, you know, to rescue all these Jews? So that's a superb book. And Ann Applebaum, I think the book is called Red Famine, came out fairly recently. And she brings the receipts. And she's a, you know, this is something I really hate with the binary thinkers, where people think, oh, you know, if you're a Democrat, you're basically a communist. They call Joe Biden a Marxist. It's just like, you know, she's a hard lefty. She's, you know, has TDS. But this book just systemically lays out what Stalin did. By the way, I'm triggered by the binary thinkers. And for those who don't know, TDS0011 is Trump Deterring Syndrome. Yes. So they, you know, forced the starvation on this entire population. And they, it's not only that, it's like they knew if you weren't starving by looking at you, that you were hiding food. So they'd come back to your house at night and break your fingers in the door or take, burn down your house. And now you're on the street without food because you lied, because this is the people's food. You're a kulak, you're a landowner. And very quickly, a kulak, which meant like peasant landowner, became anyone who had a piece of bread. And it was systemic and ongoing. And many people in the press did not believe it. There was a British journalist, I believe, who got out of the train, Ukraine, like one town earlier and walked, and he described all this. And he was mocked and derided. And this is just anti-Russian propaganda, because at the time in the 30s, this was socialism had come to fruition. This was a noble experiment. I'd seen the future and it works, as I think Sidney Webb was the guy who said that. And the premise was, let's see what happens. We've never tried something like that. And they were perfectly happy to have this experiment happen overseas at the price of the Russian people, because it's like, you know what, maybe this will be paradise on earth. And I address this in my book as well. There's a superb essay, I think, by Eugene Genovese. And he talks about the question, the question being, what did you know and when did you know it? What did you know about the concentration camps? What did you know about the starvation? What did you know about children being taught at school to turn in their parents for having some extra bread? And his conclusion is we all knew and we all knew from the beginning, every bit of it, and we didn't care because we were more interested in promoting this ideology. So when people are kind of thinking the worst thing on earth is like Robert E. Lee statue being taken down to Washington, DC, we were being told, and especially in a much more limited news information world where now you have literally anyone can have a Twitter, but how many outlets were there, that this is, we're backwards, they're the future, they're scientific. We have the vagaries of the market, which led to the Great Depression. And when you see what was being put over on the American public at the time, anyone who thinks things are as bad now as they've ever been is simply delusional or ignorant. Yeah, I would say just as a small aside, that's why reading, as I'm almost done with The Rise and Fall of the Third Reich. Oh, yeah. Is it's a refreshes, resets the palette of your understanding of what is good and evil in the world that I think is really useful now. Like, you know, what helps me be really positive and almost naive on Twitter and in the world is by just studying history. Yeah. And comparing it to how amazing things are today. But in that time, what would you do? What does a brave mind do? And not just acts of bravery, but how do you be effective in that? That's something I often think about. It's sometimes easy to be an activist in terms of just saying stuff. It's hard to be effective at your activism. One of the big questions historians have constantly is how did this happen? A, to make sure it doesn't happen again. But this is Germany. This is not some kind of weirdo cult nation. They're very advanced, very in the land of poets and philosophers. How did it get to that point that they're just shooting children and everyone's cheering for this? Specifically on the anti-Semitism and the Holocaust. But just the totalitarianism, the cult of Hitler, and just this whole kind of thing. So there's, sorry to drop it, there's two sides. I don't know if you want to separate them. One is the totalitarianism and the entirety of the Nazi regime. And then there's the Holocaust, which is like, you know, going, I would say, like, very specifically, as I think you're about to describe, it's like, you know, targeting Jews very much so. I don't know if you see those as two separate things. I think they're very interconnected. But I think if you look at it, everyone thinks that they'd be the ones putting up Anne Frank. But if you look at the numbers, they'd be the ones calling the Stasi on her, or whoever the people were at the time, and not the Stasi, obviously, and patting themselves on the back for it. So sorry to pause on that. That's a really important thing. If you're listening to this, that, and you were not, you were in Germany at the time, you would have likely been willing to commit, or at least keep a blind eye to the violence against Jews. Like, you have to really sit with that idea, that it would have been somebody who just sees this and is not bothered by it, and also very likely kind of understand this as a necessary evil, or even a necessary good. Yeah. And I think people think they would be the abolitionists, or marching on Selma. The numbers don't add up to that at all. And I think the question would be, like, what social... My friend was on Tinder, my friend Matt, who's a great dude. And the question was, what's the most controversial opinion you have? This is New York. And the girl wrote, I hate Trump. And what people perceive themselves as being courageous in saying and doing, and what is the actual social cost of you saying or doing this, are two very disconnected things. And we're also trained by corporate media to have completely vapid, uninteresting, banal ideas, and yet regard ourselves as revolutionaries. There are people who still, in New York, will take pride because they have a gay friend. Because they have a gay friend. And it's like, first of all, who cares? But second of all, you are not a hero. And that person's not your prop, by the way. That's another big problem. Which is why I'd like to give Richard Wolff a shout out for being an intellectual who talks about communism. I think it takes kind of a heroic intellectual right now to speak about communism seriously. There's difficult waters to tread, is that the expression? There's difficult paths to walk. I love watching a robot try to use idiom in a language he doesn't know. 001. One. I'm quite deeply hurt by the binary comment. Are you? Your feeling has gone from one to zero. Yeah. What is love? My buffers have overflown. No, but there's difficult, I feel like communism is universally seen as a bad thing currently in intellectual circles. Yes. Or actually, maybe some people disagree with that. People say like far left people are trying to, you know, there's some people who argue the BLM movement is some kind of harm of a Marxist. I mean, I don't really follow the deep logic in that, whatever, but it's just- Well, they said they were formed by Marxism, the founder, co-founder. Yeah, but stating that is different than- There's Marx the totalitarian. There's also Marx the revolutionary. And I think they're talking more like we're revolutionaries, we're going to overthrow the status quo. Yeah, right. But we can have that further discussion, but I just don't think they speak deeply about political systems and saying communism is going to be the righteous system. There's not a deep intellectual discourse, what I mean. But if you were to try to be on stage with the Jordan Peterson, like to me, the brave thing now, like it would be to argue for communism. It'd be interesting to see. Not many people do it. I certainly wouldn't be willing to do it. I don't have enough. I don't, first of all, don't believe it. But second of all, it's a very difficult argument to make because you get so much fire, which is why I like Richard Wolff. He's one of the people who is quite rigorously showing that there's some good ideas within the system of communism, specifically saying that attacking more the negative sides of capitalism. So saying that there is, that capitalism potentially is more dangerous than communism. I mean, I disagree with that, but I think it's a- I love how something is like we've got a body count of 60 million, but this, everything is, potentially, like water can drown everyone on earth. So this is incoherent. Well, I think nuclear weapons are bad, but nuclear energy is good. Sure. Nuclear weapons also can be good. You can easily make the argument, which I don't know that I subscribe to, that nuclear weapons prevented boots on the ground war. And it would cause them to be much more contained. And they're also quite effective at changing the direction of an asteroid that's about to hit earth, as I've learned from a movie. Armageddon. Yeah, Armageddon. And they're actually useful, as Elon Musk has claimed for application for, prior to colonizing Mars, making it more habitable. Oh, okay. So it should change. Gotta do something. I'm not gonna look the way else. But yes, but I guess what I'm saying is there's a place for nuance, and there's some topics so hot, like communism, where nuance is very difficult to have. And I feel like with Nazi Germany, it was a similar thing at the time. You want to talk about Jeanette Rankin, who was one of my favorite people? So Jeanette Rankin was the first woman elected to Congress. She was elected before women's suffrage was messed, the constitutional amendment from Montana. She was elected in 1916. She was one of a handful of people to vote against the US going into the Great War, which was the right call at the time. She was a pacifist, Republican as well, coincidentally. She lost her seat, ran again in, was it 1940? She got the seat again and was the only person to vote against getting into World War II. It was not a unanimous choice. Jeanette Rankin was the one person, and she said, you can no more win a war than you can win a hurricane. So she's one of these interesting, and talk about bravery. You're the one vote after Pearl Harbor to say, we're not doing this. And I mean, the pressure she must've been under at the time is, and of course, many people are not interested in hearing her perspective. She's crazy, she's evil, blah, blah, blah. It's also funny, someone on my Twitter, when I talked about her goes, maybe she had Hitler's sympathies. Like, yeah, Ms. Rankin was a big fan of Hitler. That's what, you figured it out, guys. Do you think there's an argument to be made that United States should not have gotten involved in World War II? Oh, easy, an easy argument. The argument, there's a, I talk about this in the New Right. So on internet circles, there's something called Godwin's Law, which means the longer an internet conversation goes on, the probability someone gets compared to Hitler becomes one. In certain New Right circles, the longer the conversation goes on, the more likelihood that the argument will become, we should have ended World War II also becomes one. And the argument is, at the very least, stay back, let Hitler and Stalin kill each other off, and then go in and knock off the weak one. And you're going to be saving, destroying two nightmare systems. And I think that's an easy argument to make. Now, it's hard to pull off after Pearl Harbor, but in terms of strategy, I don't think that's a tough sell. LAROUCHE What about after Pearl Harbor? COREY I mean, that's what I'm saying, after Pearl Harbor, how are you going to sell it to the people? The argument is, blah, blah, the Holocaust, the Holocaust, there's no scenario where that doesn't happen, really, if you're, unless you're going in way earlier. But even so, Hitler had said, if the Jews launch another war, we're going to wipe them from the face of the earth. So the Jews are being held hostage by Hitler as an argument for this. Another thing he did, which was diabolical, is in order to make it that people could not accept Jews as refugees, if they were going to leave Germany, they had to be penniless. So now you have, it's not like they're coming over with money, and they can take care of themselves. No, no, they're going to be completely destitute. LAROUCHE Makes it harder to accept them, yeah. CURRIER Millions of destitute people who don't speak the language, it's a tough sell. LAROUCHE So speaking of Goodwin's Law, what do you make of this condition, Trump Derangement Syndrome, and the idea of comparing Trump to Hitler? CURRIER I think it's despicable. And I'll give you an example, something parallel that I think more people should be regarding as despicable. Earlier in 2020, we were all told that unless we were in Syria immediately, the Kurds were going to be exterminated, they invoked the Holocaust, this is going to be another genocide, and if you're not for this, you're basically forcing another Holocaust. None of the people who used this argument, we didn't go to Syria, the Kurds were not exterminated, they just vanished from the news, had any consequences for using this kind of comparison. So I think it's really kind of fatuous, and I think it's amazing that people think Hitler's the only tyrant who ever lived. Like everyone who's bad is specifically Hitler. You know how you know he's not Hitler? Because you can tweet at him, and no one comes to your house to kill your family. Like that's kind of a big difference. Also, the difference between Trump and many of his critics is that his grandchildren will be raised as Jews. And Deborah Lipschitz talks about this a lot. The New York Times at the time, there's another book called Buried by the Times, which talks about the New York Times in World War II. Because the idea that Jews weren't white was the Hitler idea, the New York Times at the time, Salzburger, wanted to be against this idea. So they specifically downplayed the anti-Semitism as opposed to the Nazis are being oppressive. So the argument that you can separate Nazism from anti-Semitism is a historical debate people have. And my perspective is, I do not find it convincing that you can separate those two. I think anti-Semitism was essential to Nazism. I think Nazism and Mussolini's fascism have very big differences. Do you think anti-Semitism was fundamental to who Hitler was? Yes. Or was it just that... So this is the interesting thing is like, it was a tool that he saw as being effective? No, he believed it. So why do you see those as intricately connected? Could Hitler have accomplished the same amount or more without the Holocaust? Yeah, because think about how many resources you had to divert at a time where you have Operation Barbarossa with Stalin. So why are they so connected? Is it because Hitler was insane or was he a bad strategist? He was obviously a bad strategist. He had no need to open a second front. His generals, my understanding, told him this is crazy. It didn't work out for him at all. To draw Russia and her resources into that war, it makes absolutely no sense in retrospect. There's a book about, I forget what it's called, we talked about him at that point, was just high all the time on amphetamines and that could have affected his thinking. Yeah, there's a really good book on drugs. I forget what it's called, but yeah, it's a really good one. I mean, scapegoating is a big part and parcel of the Nazi mythology. And this kind of one universal figure to explain this kind of skeleton key. But it could have been the communists. I mean, that could have been the source of the hatred. So like- But the communists didn't get Germany into World War I, like you said the Jews did. It seems to me that the atrocity of the Holocaust is the reason we see Hitler as evil. No, the reason we see Hitler as evil is because of World War II propaganda still. Because we don't see Stalin as evil. Right, that's my main point. We don't see Mao as evil to that extent. I think that- Why? Like, why would you say that? You know why? Because I- The nature of that propaganda. Because I think a lot of the problem for the certain type of mentality is Hitler didn't mass murder equally. So as long as you're killing just one group, it's a problem. But if you're murdering everyone equally, all of a sudden it's like, eh, what are you going to do? So the fact, like you were saying, the Holodomor is not common knowledge. The fact that Mao's 50 million dead are not common knowledge and Richard Nixon can be raising a glass to him in China. These are things that I think the West has not done a good job reconciling. Knock, knock. Who's there? Frank. Frank who? Frank, you for being my friend, Michael. And the heart attacks will say, Frank, you for being my friend. This is- Yeah, you got to do like this. Okay, all right. Yeah. Okay. Now back to Hitler. Do you think Hitler could have been stopped? We kind of talked about it a little bit in terms of how to, what is the brave thing to do in the time of Nazi Germany. But do you think, I mean, I'm not even going to ask about Stalin in terms of could Stalin have been stopped? Because probably the answer is there's no. But on the Hitler side, could Hitler have been stopped? I think a lot of these things, a lot of luck has to play with it. He was almost assassinated. If you mean by like the West, it's very hard. I mean, yeah. By the German people too. I mean, could, like if politically speaking, there was a rise to power through the 30s, through the 20s, really. I mean, like can whoever, it's not about Hitler, it's about that kind of way of thinking, that totalitarian control that always leads to trouble. And sometimes the mass scale, could that have been stopped in Germany or maybe in the Soviet Union? Well, I think this is one of the best arguments against radicalization in the States, which is how do you engage when you have like 30% of the population who are members of a party which is dedicated to systemically overthrowing the existing democracy? Stalin gave orders that the communists, who had a pretty sizable population, the Reichstag, that their target shouldn't be the Nazis, but the liberals and the social democrats. And they invented the term social fascist for them. So instead of, they're just like jihadis, instead of taking their sights on Nazism, they set their sights on the moderates because they figured the choice between Hitler and us, we're gonna win. And this was a huge gamble and they were all killed or had to flee and ones who fled were killed also by Stalin. So that's my understanding. So this is an easy way where he could have been certainly heavily mitigated What about France and England, that it was obvious that Hitler was lying and they wanted peace so bad that they were willing to put up with it even after Czechoslovakia, like this is the anti-pacifist argument, which is like, they should have threatened military force more. But then the other anti-pacifist argument is, if you're gonna remember Barack Obama had that red line. If you cross this red line in Syria, we're gonna go in and Assad or whatever, it's like, yeah, cool. And he's like, oh, okay, well, sorry. So if you're a threatening force, there's the great song lyric, don't show your guns unless you intend to fight, right? So it's very clear with free countries through what's in the press, whether the institutional will is there to follow through on these threats. So I think it would have been very hard for Chamberlain to rally the British people to take on Hitler just after the great... I mean, the suffering that Britain's took the great war, they still, obviously, it means so much more to them than it does to us in the West. What about, what do you make of Churchill then? Like, why was Churchill able to rally the British people? Why was he... Like, do you give much credit to Churchill for being one of the great forces in stopping Hitler in World War II? I don't think that's really in dispute. I think he was very much regarded as this kind of the right man at the right time. And I think Chamberlain took a gamble. The expression peace in our time was Neville Chamberlain when he signed the appeasement with Hitler and he goes, we now have peace in our time, now go home and get a good night's sleep. That's what he said. Because he's like, all right, he's going to stop here. And it's not impossible that if you just gave... Like, if you gave Saddam Hussein Kuwait, it's not impossible that he's not going to invade Saudi Arabia next, something like that. Let's see. Okay. But everything I've read, it's like, of course, it's not impossible. But when you're in the room with Hitler, you should be able to see like man to man. Like to me, a great leader should be able to see past the facade and see like, like, yes, everything in life is a risk, but it seems like the right risk to take with Hitler. Like, it's surprising to me. I know there's charisma, but it's surprising to me. People did not see through this facade. I really hate the idea of hindsight in everything being 2020. And I think it's a very good idea generally, I'm speaking generally, not in this specific instance, to give our ancestors more credit than we tend to give them. Because people often... Here's a great example from another context, which is lightning rods. People always talk about religious people being stupid and superstitious, and they weren't. They often were very well reasoned. And an example of this is lightning rods, which is every year, whatever town, the church was the tallest building. And that's the one that always got hit by lightning and got caught on fire. Now, what, it's a coincidence that it's always the church? Like that makes logical sense. Now, they didn't realize, well, it's because it's the tallest, and therefore that attracts the electricity. And in fact, when they invented lighting rods, this was a controversy because it's like, well, how is God going to show his displeasure if now it's striking this lightning rod, not burning down the church? So a lot of times things are a lot more coherent than we give them credit for. And again, Chamberlain, he's the head of a parliamentary party. So he does not have the freedom, in a sense, that a Hitler would to be like, all right, we're doing this again, boys. We don't know what it's like in the room with Hitler. Come on, we really have no idea. But I think you have to think about that, right? Yeah, but I can very easily see him in the room being very calm and charming. And then you think, okay, the guy with the speeches is the act, and he's putting on a show for his people, and this is the real one. Okay, so let's take somebody as an example. Let's take our mutual friend, Vladimir Putin. Yes. Okay. I don't know why saying his name makes my voice crack. Because you're scared he could hear you, like Beetlejuice. Vlad, yeah. So there's a lot of people that- Was he the one who built you? No, that was a collaboration. It's a double-blind engineering effort where I was not told of who my maker was. There's a backstory, but- There's a talking cricket, Pinocchio. You'll be a real voice. I talk about him quite a bit because I find him fascinating. Now, there's a really important line that people say, like, why does Lex admire Putin? I do not admire Putin. I find the man fascinating. I find Hitler fascinating. I find a lot of figures in history fascinating, both good and bad. And the figures, just as you said, that are with us today, like Vladimir Putin, like Donald Trump, like Barack Obama, it's difficult to place them on the spectrum of good and evil because that only really applies to when you see the consequences of their action in a historical context. So there's some people who say that Vladimir Putin is evil. And based on our discussion about Hitler, that's something I think about a lot, which is in the room with Putin, and there's also a lot of historical descriptions of what it's like to be in the room with Hitler in the 1930s. There is a lot of charisma. In the same way, I find Putin to be very charismatic in his own way. The humor, the wit, the brilliance, there's a simplicity of the way he thinks that really, if taken at face value, looks like a very intelligent, honest man, thinking practically about how to build a better Russia, constantly, almost like an executive. Like he looks like a man who loves his job in a way that Trump, for example, doesn't. Meaning like he loves laws and rules and how to- He has no adversarial press, so that's gonna help. Yes. And he's popular with his people, that's also gonna help enormously. But I'm talking about strictly the man, directly the words coming out of his mouth. Like all the videos and interviews I watch, I'm based on that. Not the press, not the reporting. You can just see that here's a man who's able to display a charisma that's not, like I can see, that's why I love Joe Rogan, is like you could tell the guy is genuine and is a good person. And you could tell immediately that like once you meet Joe, that he's going to be offline, also a good person. You could tell there's like signals that we send that are like difficult to kind of describe. In the same way, you could tell Putin is like, he genuinely loves his job and wants to build a better Russia. There's the argument that he is actually an evil man behind that charisma, or is able to assassinate people. You know, limit free press, all those kinds of things. Like that's, what do we do with that? So what do human beings like journalists or what do other leaders, when they're in the room with Putin, do with those kinds of notions in deciding how to act in this world and deciding what policy to enact, all those kinds of things. Just like with Hitler, when Chairman is in the room with Hitler, how does he decide how to act? Well, let's go back to like my wheelhouse, which is North Korea, right? So when your entire world is based on being against Trump and everything Trump does is buffoonery or kind of productive, the conclusion of your reporting is going to be pretty much given. I was very hopeful that there would be some positive outlooks or outcomes rather of Trump's meeting with Kim Jong-un. It looked like there was a space for things to go a bit better. I talked about it a lot at the time. And Trump was under no illusions about who he was dealing with. People pretend that, oh, he was kind of naive. He had one of the refugees at his State of the Union, you know, lifting up his crutch. The first thing he sat down and talked to Xi Jinping about in Mar-a-Lago right after he became inaugurated was North Korea. Barack Obama said that when he sat down Trump in the White House during the transfer of power, he said North Korea is the biggest issue. So I think a good leader, whether or not you consider Trump a good leader, has to be aware of, all right, I'm going to have to have relationships of some kind, even if it's adversarial, with some really evil, evil, horrible people, which Kim Jong-un clearly is. Well, I don't think there's anybody that has a perspective that North Korean, Kim Jong-un or Il are not evil, right? Correct. But in 1930s Germany, isn't it a little bit more nuanced? Yeah, because Hitler hasn't done anything yet, and he's just a blowhard, and he's an anti-Nazi. He's an anti-Semite, sure, but he's- What about before the war breaks out? What about the basic actionable anti-Semitism when you're just attacking, hurting- We're talking about Kristallnacht or we're talking about the night of long knives? Kristallnacht. So it's the night of the broken glass. Yeah, yeah. Long knives is when he assassinated a bunch of his people. That was something different. Yeah, so when you're actually attacking your own citizenry. Yeah, that was universally condemned, Kristallnacht, and that was very shocking, its level of barbarism to the West. Because I think we still want to believe, understandably, that things aren't as bad as they seem. We would rather, this is why the North Korea book I did, Dear Reader, is used in a humorous framework, because if you have to look, it's like looking to the sun, if you stare at it straight on, it's very hard to do. So you have to kind of look at it obliquely, and then you're kind of realizing the enormity of the depravity. And again, pogroms in Russia had been a thing for a very long time, and there's a difference between, okay, we're going to sack these villages and persecute people, and we're going to systematically exterminate them. There's still levels of evil and depravity. So you did write the book, Dear Reader, on Kim Jong-il, Dear Reader, the unauthorized autobiography of Kim Jong-il. So that's the previous leader of North Korea. Correct. Current one is the un... Jong-un. No creativity on the naming. Well, no, this is intentional, because it's a throwback to the dead. So there's been only three leaders in North Korea? Yes. So we've talked about the history of Hitler and Stalin, men like these. I think it's important to understand that the history of those kinds of humans, there's... The history of North Korea is not well written about or understood, which is why your book is exceptionally powerful and important. So maybe in a big, broad way, can you say who was, who is Kim Jong-il as a man, as a leader, as a historical figure that we should understand, and why should we understand them? So I wrote Dear Reader by going to North Korea and getting all their propaganda, which is translated into several languages, because the conceit is everyone on earth is interested in them and wants to mirror their ideology. And he died in 2011. 2011, yeah. And you wrote the book in 2012. I went there in 2012. I wrote the book, came out in 2014. So Kim Jong-il is, though not an intellect, North Korea's version of Forrest Gump, in that when they write their history, whenever something happens, he's there. And by telling his life story, it's in the first person, he's telling the history of North Korea. So I wanted to write the kind of book where, in one book, and it's the kind of reading you could do in the beach or the bathroom, you're gonna get the entire history and know everything you need to know about North Korea in one accessible outlet. And what people don't appreciate about North Korea, there's several things. How bad it is. And this didn't happen overnight. This was very systemic, that what this family did to that country, where piece by piece, they did everything in their power to hermetically seal it from the rest of the world, ramp up the oppression, keep any information from coming in. And they're very creative and innovative in their style of manipulation and control. So there is a farcical element. Let me give you an example. So people in the West kind of get it wrong. They talk about, oh, they talk about when Kim Jong-il played golf for the first time, he gets 17 holes in one. There's this one story about Kim Jong-il shrinking time. And this is a story, it sounds supernatural, but it's not. So Kim Jong-il is at a conference, the dear leader, and someone is giving a talk. And while that person is giving a talk, Kim Jong-il is taking notes and working on his work. And he has an aide who keeps interrupting him with questions. And the speaker keeps stopping. And Kim Jong-il says, why are you stopping? Goes, I see you're doing these other things. And he goes, no, no, he can, I can do all these things at once. Everyone's shocked. And they said, this is why Kim Jong-il looks at time, not like a plane, but like a cube. And he can shrink time. And my friend goes, do they mean multitasking? And yes, Kim Jong-il is the only person in North Korea who's capable of multitasking. So in order to elevate him, they basically make everyone else in North Korea completely incompetent. And that has a purpose, because should the leader go away, this country is gonna collapse overnight. So they laugh in the West about all these newspapers show him at the factory, and he's at the fish hatchery, at the paper plant. They say the difference in North Korea is that the leader goes among the people and does what he calls field guidance. So he will go in that farm and be like, this is what you need to do. And he'll go here and he's so smart, he's good at everything. And thanks to him for sharing his wisdom with us. And he's not removed from the people like in every other country. Why does that seem to go wrong with humans, do you think? That this kind of, the structure where there's this one figure, this authoritarian, this totalitarian structure where there's one figure that's a source of comfort and knowledge. Kim Jong-il is not good at farming. Kim Jong-il is not good at the machinery. It's all a complete lie. Or the things he'll point out will be things that are completely obvious. So here's another example that they use. In North Korea, they have something called the Tower of the Juche Idea, which is an obelisk, which looks like the Washington Monument, but it's completely different because it's got this like plastic torch at the top. And they talk about in their propaganda how all the architects got together and they said, oh, we should make this the second tallest stone obelisk in the world. And Kim Jong-il says, no, let's make it the tallest. They're like, oh, we never thought of this before. And the way it's presented as it, and like he's the first person to think of this, like these architects are having a brainstorming session. The Tower of the Juche Idea, they're like, all right, we gotta do something innovative to put North Korea on the map. What can we do? How about second biggest? He's gonna go for this. And then he's like, oh, we never thought of this. It's so, because I present it at face value, people sometimes say the book's a satire. It's not a satire. I downplayed all this stuff. It's a farce. Here's another example. North Korea is very big. And I think Russia is to some extent too on amusement parks, fun fairs, they call them in the British style, because this is a chance for the people to all get together. And there was this amusement park. It's almost like South Park, Cartman, where there's all these rides. And Kim Jong-il is like, I'm not gonna let any elderly or children take these rides until I put myself in danger and ride them myself. And they go, but dear leader, it's drizzling. And he goes, no, I have to make sure these rides are gonna be safe for everyone, even during the light rain. They go, well, can we go on these rides with you? No, no, no, I have to be the courageous one. And he's riding all the rides and they're standing there crying at his courage. But that's what's, and you ask all the thing in one power. It's like, listen, I'm quite confident that those fun fair engineers are in a position to ride modest mouse, whatever it's called, by themselves and be like, yeah, okay, this is good for the kids. Although to be fair, some of those amusement parks are pretty rusty and dangerous. Yeah, but that kind of propaganda, I guess what I'm playing a devil's advocate is like, it's comforting and it's useful, but it does seem that that naturally leads to an abuse of power. But how can it be used correctly? No one person has the intellect or the mind to understand the entirety of an economy, let alone every individual field of interest. Well, for example, you can have an artificial intelligence system that understands the entirety of it. Your affect just completely changed, the mask slipped. I guess you could have an artificial intelligence system. But the question is, can that, I mean, the human version of that is like, you can hire a lot of experts, right? You can be an extremely good manager. And since everything's dynamic, it's not gonna, they're not gonna have the data to kind of manage it well. It seems that there's a, like what George Washington allegedly did, it seems like most humans are not able to fire themselves. You're not able to like, Yeah, you're right. Ultimately be a check on your own power, but that's not, if I was like, if I was creating a human, it's like, that's not an obvious bug of the system that we would not be able to fire ourselves to know when we have, I mean, it seems like that's something you have to know always. Like, that's something I often wonder is like, am I wrong about this? Well, this is what we talked about earlier. What are the safety valves to make sure that, okay, if I am incorrect or my knowledge is finite, Plato's cave kind of thing, what mechanisms are in place that my mistake or limited information isn't gonna have deleterious consequences? And North Korea does not really have that. And as a result, they had polio in the 90s. So there is a, you're right about it straight, but there's a humor to it because it's an absurdly evil place, I suppose. A bunch of people, I asked, I said that I'm talking to you and a bunch of people asked questions. Oh, I gotta hear from the plebs. You asked me before we started recording, I specifically said no, it was in my contract. Yeah, and I gave you all the pink Skittles or whatever. But they- So pink Skittles, you don't think- I'm trolling, Michael. Let me explain to you how that works. If people should go at malice.locals.com and sign up and pay, I think the membership fee is several thousand dollars. It's very, it's not- It's not for the layman. Yeah, but the service is excellent. You get a coat with it. But yeah, I went there, posted a lot of really brilliant people there. People should join that community. If you find Michael interesting or if you just wanna go and say why he's wrong, it's a great place to have that. It's not a great place for that, I assure you. Yeah, a lot of really kind people. So anyway, there's a bunch of people asked that we should talk about humor. Okay. So pretend, hypothetically speaking, that I'm a robot asking you to explain humor to me. So dear reader, I mean, there's a humor. You so wonderfully dance between serious dark topics and then seriously dark humor. Can you try to, if you were to write like a, I don't know, a Wikipedia article, maybe a book about your philosophy of humor, what do you think is the role of humor in all of this? A joke is like a baby. You can't dissect it and then put it back together and expect it to work. Trust me on this one. Despite, no matter how you carve that thing up, it's not gonna be working the next day. And you need it to sew those little sneakers with those hands. I don't know that humor is something that is very explainable. People, there's something called claptor, where this is like the worst kind of humor where people applaud because they agree with what you're saying, as opposed to laptor. Oh, that's the kind of thing. That's the poetry reading? Yeah, and the drag queens do that too. I think because they have the nails. You laugh, it's a visceral reaction. When someone on Twitter is insisting, you know, that's not funny, you're not in a position to make that claim. And let's go back to North Korea. I had a refugee I knew, and he went to high school here, and he was talking to his buddies, and they said, hey, remember when we were kids, we had Pokemon? And he goes, oh yeah, except instead of Pokemon, I watched my dad starve to death, which is the truth. Now, who are any of us to tell him not to make that joke? I don't know what it's like watching anyone, including my dad, starve to death. My dad's fatty, so he's not going hungry anytime soon. So it's very bizarre to me when people feel comfortable precluding others from making jokes, especially, and I think this is a very Jewish thing, like this kind of gallows humor, especially when it's laughing about a personal loss or experience that they've had. Humor is a great way to mitigate pain and suffering, but it's also, I think this is why it's a Jewish thing, it's a Black thing, when you are a marginalized community or poorer, it's free. Telling stories, telling jokes or songs, you don't have to have money, but you can have joy and happiness. And I think that's why you find it so much more in kind of lower status communities than you find it in like wasps, who are notoriously humorless. Which is strange because people pay a lot of money for the jokes you do, so it's not really free. Yeah, well, no, they don't have to pay me. It's appreciated, but not expected. I find my voice cracking every time I try to make a joke, like I fail miserably at this. Some people- You're still in beta, that's why. Alpha. Sure. Being an alpha is like being a lady, if you have to tell people you are, you aren't. No, I meant alpha version, not male. Okay. I don't know if you're a robot gobbledygook. I'm not going there. Okay. Who are you talking to? In my own head. I'm talking to myself in my own head. Okay. Speaking of North Korea, some people say that, you know, I've read that comedy is about timing. First of all, do you agree? And second of all- No, I'm serious. It's very much about timing. You're saying yes, at that time, yeah, it's funny. Okay. Isn't it comedy is tragedy plus timing? Isn't that the full reference? What is it? The interrupting cow knock-knock joke. I'm not going to do it, but- That's not a timing thing. It's more of a repetition and then the twist ending. No, the moo. Oh, the moo. Yeah, yeah, yeah. Interrupting cow. You're thinking of the banana one. Anyway, I'm not going there. Yet, you're- Who are you talking to? In my own head. On the floor. Do you have an earpiece? Are you Small Wonder? Do you stand sleeping in a wardrobe? Yeah. That's so British. But yet, you're very- I don't want to say in a closet because that has connotations. Let's both come out of the closet for a second. I love you. And let's talk about- I love you, Lex. I wasn't saying I love you, Alex. I was saying I love you, Lex. Oh, you're talking to me? Yes, through the screen. So you think about me when you're with another man. I watch you when you're sleeping. Okay, so you're- Like the Bangles song. You're really active on Twitter. Yeah. And somebody else asked on your overly expensive membership site. My grift site. How do you find humor different in writing on Twitter versus spoken humor? So if- Oh, that's a great question. If humor is about timing, how do you capture the timing and the brilliance of the whatever is underlying humor in a context of Twitter? Another way to say it is, how do you be funny and yet thoughtful on Twitter? So with Twitter, you have to be the first one to the punchline. So when Ron Paul had his stroke, I was immediately being like, he's still the most articulate libertarian. He's doing a great Joe Biden impression right now. All the libertarians got ass mad. And people are like, too soon. Or like when someone dies, you're making the jokes about them. It's like, when do you want to make the jokes about someone just died a week later? It doesn't make any sense. Now you might- Too soon is perfect timing. Or you could say it's not appropriate ever, but too soon does not make sense in this context. So that is something that I enjoy doing. It's also fun ruffling people's feathers, which is something I enjoy doing. I think spoken versus writing is very different because when you are having good banter with someone, for me as the audience, knowing that it is on the spot really adds an element of humor. Because then it's like, wow, this is fun. It's like a ping pong match or something. Whereas in writing, you're losing the tone, you're losing the relationship of a dynamic conversation. And a lot of times the joke is just gonna be a different type of joke. Well, it's funny, but Twitter, there's a sense, especially your Twitter, that you just thought of that and you just wrote it. Yes. Like there's a feeling like it's literally you talking as opposed to what I imagine is there's some editing, or it doesn't look like it. Whoever your editor is should be fired. There's an interesting effect, actually. If I want to say something, I don't know, about something that's bothering me about the presidential election or something like that. Like what is the actual central idea that I'm trying to convey to myself? Like if say I was having a hypothetical conversation with myself. Okay. What? No, I'm not going there. Why am I putting my pants back on? I'm more comfortable this way. Promo code Malice20, sheathunderwear.com. Okay. That's sheath... What is it? What's the website? Sheathunderwear.com. Sheathunderwear.com, promo code Malice20. And I forgot, why is that underwear really nice? Because it has a dual pouch technology to keep your man parts separate. They've also got woman stuff, but I don't know how that works. There's a thing going somewhere. And the material is really refreshing. I mean, it's really a good... And it makes your ass look good. That's promo code Malice20. And it's made by a former vet because he was in Iraq. So that's why I like promoting it. Yeah. But when I'm writing the tweet, I like to... It forces me to think deeply about the core of the message. Okay. But what I found this really interesting effect, like I don't really do much editing on the tweet. Like I'll just like think and then I'll write it. And then when I post it, like submit, like I immediately see the tweet very differently than it was in my mind. I often delete, like I delete, I don't know, some percentage of tweets about like two, five seconds after. Wow. I don't know, it's something once you send it, it's why the Gmail send features, undo send features really nice. It's like, it just changes the way I see the thing. So it's very interesting. But I really love it that you can delete it because when I say stuff out in the wild, like to other humans, like spoken word is like, you can't delete what you just said. And I often regret the things I say. Like in, in on the spot, like I shouldn't have said that. Really? Yeah. I don't have that. Well, again, whoever your editor is, what is it? Edith Piaf, Jean-Éric Arthéon. Wow, you're French, that's bad, is your English? I don't have any tweets I regret because if I sent a tweet that I regretted, I would make amends. I would make it a point if I was needlessly offensive to somebody or hurtful or accidentally, I would make sure to fix it and go out of my way to make sure that person feels vindicated and validated by accepting my apology. That has never happened, had to happen, thankfully. I'm also someone who is not big on taking the bait. You know, some recently, some people have come after me pretty hard. And my perspective is that it's not really about me. It's either I represent something to them. I'm just a jackass with a Twitter. So if you're getting this riled up over me, it's not really about me. Maybe I'm delusional, but that's how I look at it. So if they are trying to provoke me into this kind of heated exchange, I will never do it because that's not, I'm not interested in it. And it's, I don't think there's going to be any, it's like Janet Rankin, you, you can't win. It's just going to be like trying to win a hurricane. There's no hero here. Well, let me ask you about this, because somebody also asked that on your overly expensive membership site, that like they were saying that they're an academic. They wonder, because I'm an, quote unquote, I'm not an academic, but I do still have an affiliation with MIT. I, the word academic is just dirty. It's like, which is a problem that needs to change. Just like the word nerd is dirty. No, academic needs is going to be the next front to open and they're going to be very vilified. We're coming for them and it's going to be very, very ugly. And I cannot wait. No, but there needs to be a place, a different term for people who love research and knowledge. Oh, that's fair. Like you have to- No, you're right, 100%. You're right. So like there, you have to, you have to clarify what you mean by academic. And right now the word academic means a very, in the intellectual public discourse, it means the enemy. And there's a lot of people that perhaps deserve that targeted vilification, but like a lot that don't. They're just curious people. Yeah, no, you're absolutely right. Building robots that will one day destroy you. Voice cracks every time I make a joke. You're not, because it's just- I can't do this. Because you're not making a joke, it's like- I'm editing. I can't delete that joke. Okay, it's not even a joke. Robots, building robots that will one day kill us. Oh, God willing. Humans, God willing, humans are the joke. That's why I'm cracking. My voice is cracking. What were even, what was I even fucking saying? Academics. Academics. But why- My locals, someone had a question, they're an academic. Right, they're an academic. They're saying like, are you worried that, you know, in academia, associating yourself with a sort of somebody who has, who can be misconstrued to have radical ideas, like the two examples they gave is Michael Malice and Joe Rogan. Does Joe have any radical, I wouldn't consider him radical at all. Well, we can talk about it. But Joe is, I think, a bad example. He's quite centrist to me. Well, he could have, for example, like, what has Joe been attacked on? It's, for example, on the topic of like transgender, like- And athletes and sports. Yeah, athletes and sports. There's, what else? I mean, he's been pro Bernie Sanders and- That's hardly radical. Pro Trump, or like giving Trump a pass. Yeah, not anti-Trump. Not anti-Trump. Yeah. What else? Just- None of these are radical. Meat stuff, being pro-meat versus anti-vegan. Yeah. All those kinds of things. But you can be misconstrued. And saying, there's, I think, a highlight, and my mom actually wrote to me about this, which is hilarious. Yoshinka. Yoshinka. Thank you. I like how you jotted it down. It's an important- Well, let me see, your mom wrote to you, Yoshinka. That's a sign, my voice cracks, a sign when Michael Malice makes a funny joke is when you jot something down. Yoshinka. Nevrednichey. He writes it, and then the next time he just crosses it out. Just get put, yeah. It's like Joe Biden, the debates. Okay. I did also just crap my pants. So- It's like a mud slide down here. There's a, I mean, he's a comedian. You have a comedian side to you, right? I mean, you're a comedian, and you're a comedian, and you're a comedian, and you have a comedian side to you, right? I mean, you've talked a lot. Humorist, yeah. Humorist side, yeah, humorist. So you can misconstrue Joe as being somehow a radical thinker, and the same one could be done with you. And his question was, are you worried about associating yourself with folks like that? Am I, or are you? Me, me. Yeah, that's my question. And is that something, do you see yourself as somebody who's dangerous and shouldn't be talking to? And in the same way, do you ever think about guests on your podcast or people you talk to publicly, associate yourself with publicly, and think that there is somebody that crosses that line that you shouldn't talk to? Yes, so I interviewed, in the new ride, I interviewed up to full blown Nazis in the last chapters of Chris Cantwell, but that was in the context of that book, right? So there's lots of people who, people want me to have on my show. And the way I look at it is like, you have a table and tablecloth, right? And let's suppose the table is three feet wide, the tablecloth is two feet wide. So if I move the tablecloth to the right, I'm gonna lose people on the left. I can only cover so much space. And the further you go on the fringe in one direction, the more mainstream you're going to lose on the other direction. So I'm very much making a conscious choice not to talk to being, people will say I'm cowardly, and that's absolutely true, I'm being fearful here. I would prefer not to talk to some of those who would alienate some of the more mainstream people. And here's a perfect example of why. On my birthday last year, I woke up seven o'clock in the morning to go pee, and I checked Twitter, so whatever, and Jeb Bush had followed me, Jeb. And I, it's 7 a.m., you're not really awake, you're like, wait, what? And then I thought maybe it was a fake account, but it's in the verified tab. Oh, you don't have this, because you're not verified on Twitter, that's a shame. So people who are mad around Twitter. Twitter does not respect robots. They ban bots, you're lucky you haven't been banned. Zero, one. Zero, zero, it's zero, zero, zero. Those are my pronouns. One. So it was Jeb, Jeb, Governor Bush, and I corresponded with him, and I asked him on the show, and he decided not to for various reasons. Very politely, he's like, just politics is so bad right now, I don't want to talk about it. I respect that for him. If I am in a, if I'm creating my show where he's going to get heat, for who, and get canceled, oh, you can't be on the show, he has these other guests, I don't want to lose that opportunity, because, as we were talking about earlier, me and Alex Jones and Tim Pool, I think a lot of people would be very excited to see me sit down with Jeb Bush. And I told him in writing, and I meant this, I wouldn't be clowning him, I wouldn't be disrespectful, it would be a lot of fun. There's a goofball side to him that comes out sometimes, and I would do my best to bring that out, and talk about what it's like being a blue blood, to be born into his grandfather, Prescott Bush was a senator from Connecticut, marrying a woman who didn't speak English, how does that work when your family's royalty, and things like that. So I had a lot of fun questions for him, and that's kind of, you're going to have to choose one or the other. Well, you do a really good job with that, like Ben Shapiro does a good job with that too, which is, you can have a trolly side, a humor side, where you tear down the power structures, and so on, but you can also have a serious side, and it's a safe space for people from all walks of life to walk in, and you're not adversarial. Never, I take the word guests seriously. If they're going to be on my show, I'm not going to have them have negative consequences, as a result of being on my show. That said, maybe in my case, I'll be honest, and say that I find Alex Jones, outside of the conspiracy stuff, for some reason, maybe you can explain, maybe you can psychoanalyze me, but I find him hilarious to listen to. He's a performer, he's very performative. But there's a lot of people that don't see the humor of it, and they see the serious consequences of spreading conspiracy theories of different kinds, and they see the danger of it. And I personally, I'm often tempted to talk to Alex, in a podcast format, but I think I'm trying to convince myself that I never will. For me, I feel unsafe talking to Alex, because I can't truly be myself, which is like naive and honest. And actually, generally, when I talk to humans, I want to see the best in them. And I think that's, I often think about, if I talked to Hitler in 1935, 1938. You got a list of names to give him? Well, yeah, I mean, that's how you get the interview. Come on, let's be honest. Who are we kidding? I would, you have to give away one of your, I would probably give away my brother, so. How many brothers do you have? Well, just one. Okay. Too many. I want to be an only child. He's the older brother, he used to pick on me, payback. You know, he had a good life. You should think of it more as Stalin, I'm sorry to interrupt you, because Hitler, you're Jewish. So you're already gonna have very adversarial, it's not gonna be a normal, he's not gonna perceive you as a human in a sense, right? Right. So it's- Stalin, you're right. Yeah, that would be much easier, or Kim Jong-un or something like that. Like, do you think, like how, okay, this is a good question, is in that spirit, why don't you jot something down? I think this is a really good example of a difficult figure that's controversial that people bring up to me a lot, and you interviewed twice, which is Curtis Yarvin. Yeah, Manchus Maulblog. Manchus Maul, aka Manchus Maulblog, which is his pseudonym that he goes by in his blog. Can you tell me about who he is? Sure. Why is he interesting? What of his ideas are interesting? Well, briefly, he invented the concept of the red pill. So Curtis, Manchus Maulblog had a blog called Unqualified Reservations, you can still find it online. It's very verbose, he writes at length, very, very bright. His perspective is very heretical. So a lot of things that we take for granted in our liberal democracy, he regards as not only incorrect, which is downright absurd, and he does not take what many people view as the basis of American political discourse as the basis for his thought. So when you're starting with someone who is basically repudiating kind of the Western worldview, or not the Western worldview, like the American milieu, a lot of people are going to, of course, regard him as dangerous or someone who is verboten. He's a very bright person. Why is he such a toxic figure? Because if you are blue-pilled, if you are the guardians of what is acceptable discourse, then you have to make sure your forts are secured, and that any figure outside of this acceptable discourse has to be marginalized and regarded as as radioactive as possible. You don't want to let in these kind of ideas that would be destructive to your hegemony. Well, so let's dig into it. So I've read a few things by him, but then I hear that, in a bunch of places, him being called a racist, a white supremacist, neo-fascist, so on. I go to his Wikipedia. There's a view on race section. Let me read it. Okay. Yarvin's opinions have been described as racist, with his writings interpreted as supportive of slavery, including the belief that whites have higher IQs than blacks for genetic reasons. Yarvin himself maintains that he's not a racist because while he doubts that, quote, all races are equally smart, the notion, quote, that people who score higher on IQ tests are in some sense superior human beings is, quote, creepy. He also disputes being an outspoken advocate for slavery, though he has argued that some races are more suited for slavery than others, quote, it should be obvious that although I'm not a white nationalist, I am not exactly allergic to the stuff. Yarvin wrote in a post that linked approvingly of, I don't know these people, Steve Saylor. Steve Saylor, yeah, he's from, yeah. Jared Taylor and other racialists. Yeah, so. Okay, so one of my questions is. Let me just say one sentence. Yeah, yes. In the same way that you had, you mentioned that guy earlier who was defending some aspects of communism, and that is in some context acceptable, when you think about it, it's like, this should be radioactive. Right. The fact that he is engaging with these ideas in anything other than this has to be reputed at all costs is what renders him to a large extent a racist. That's really interesting. So there are some topics you can be. Nuanced. Nuanced and some not, and communism is still a topic that you can be nuanced about. It's difficult, but you can be raised about race and this like talking about slavery and IQ differences based on race is a topic that I guess is radioactive to a degree where you can't even say anything, even if it's like nuanced or not even like making a point, it's like touching it as you make another point. And understandably, you can understand that. I'm gonna steel man their point because you can understand the point. It's like, you're just talking about Hitler. Once this foot gets in the door that some people are inherently slaves or some people are inherently better than others, it really quickly collapses. So that would be their perspective. But that's what like, if I were to give criticism of his- But let me just say one more thing. Racist is also used to describe Alex Jones. Alex doesn't talk about race. Racist is a shorthand for a certain percentage of the population to let you know, do not bother investing in this person any further. They're off limits. Definitely, racism and sexism is a thing that's now used to shut down conversation. It's quite absurd by a small percent of the population. But Jared Taylor and Steve Saylor, Jared Taylor interviewed him for my book. He would be regarded in any sense as a racist. What's the difference between racist and racialist? So racialists, I mean, this is splitting hairs and now I'm gonna be all radioactive. Jared Taylor runs something called Amren. And this is, I mean, his perspective is that there are inherent differences to the races and you cannot live side by side well. Whites and blacks should not be living side by side. And by the way, for people who don't know, this is out of context, you have written a great book that includes some of these concepts called The New Right, which not includes these concepts, but talks about- Doesn't, yeah. Well, it's more about the growth of the community around the alt-right and all those kinds of world. Right, so, and his point about IQ, it's like if you had a population, the Dutch, right? I think they're the tallest people on earth. And if you said, well, the Dutch are the best people on earth, why? Because they're the tallest. It's like, you're a crazy person. So if someone is scoring low, an individual on an IQ test, that means they're somehow a lower quality person. Well, maybe one very specific aspect, but I mean, if they're a good human being, I've got friends who are low IQ. All my friends are low IQ, frankly, compared to me. Sound like Trump there for a second. That's how you choose friends. Well, I don't have any other choices. No one's gonna be at my level. Well, you're the smartest person since Abraham Lincoln that I've ever seen. Unlike him, I actually am honest. So he is someone who very much swims in heretical ideas. Aristotle, here's another thing. If you bring up that Aristotle said that some people are born to be slaves, he wasn't speaking about race. He just meant people's souls. H.L. Mencken, who's a great heretic early 20th century figure, one of his quotes that I say all the time, which people have seen a lot in this past year, that the average man does not want to be free. He merely wants to be safe. That I think is, I don't know. I am not familiar with what Moldau saying about slavery because his writing is ponderous, but that certainly is something I think that is undeniable. I think more people are realizing there's a large percent of the population that is actively disinterested in freedom and the moral responsibilities it entails. LBW Well, I mean, really just the word slavery, if you want to make some kind of point or even think about the topic outside the context of this is a horrible thing that happened in the United States history. CWO And other countries' histories that are unique to us, let's be clear. LBW This is, I mean, very important and there's slavery going on today. And a lot of people argue that sex trafficking and all those kinds of things. I mean, there's atrocities going on today that talking about it in a way that's not immediately saying this is the most horrible thing that happened ever. It's something I think about a lot is like, if I want to say something controversial, I should do so with skill, with care, and only about things I care about. CWO Well, here's where I would disagree. I often say things that are controversial or I will say uncontroversial things in a controversial way, because it's a useful mechanism to alienate people you don't want around you. Because if there are people who are going to be shocked by certain topics, like we should have ended World War II, like even as a hypothesis, they just clutch their pearls. They're like, oh, you want the Holocaust to happen. I can't discuss most things with you because you're not interested in having a conversation, you're interested in your emotional response. LBW I see things differently. Maybe this is a bit of a devil's advocate, but what in at least the modern discourse of like Twitter and social media and so on, I find that if you do that, you're not actually removing the people that are not thoughtful and kind and so on. You're actually attracting loud people. Like a small number of them, they come over and start yelling at you. Start yelling, they're basically ruined the party by showing up and just screaming. And so all the thoughtful people leave. LBW Well, that's why you have to be a very heavy blocker. You have to block people on Twitter because you have to cultivate your audience and have them, like a lot of times people come at me, I don't care, then they'll start attacking members of my audience. And then I'm like, dang, I got to block them because they've won this one because I can't have that. AC Yeah, I don't know. I unnecessarily provoking people feels... LBW It's, it's, it's, this is beta testing. You try to break the system and see what works. You put up as much pressure as possible. This is very much computer stuff that you should be able to appreciate. The point being, when you have a program, you're trying to intentionally sit there and do as many mistakes to see what go wrong, right? Is that not common practice? AC Yeah, exactly. So you're saying that's a way to see communication with the world is you say something uncontroversial in a controversial way and that blocks people. LBW Or does it trigger them? Do they roll their eyes? What is going to be their emotional response? Are they going to start yelling? AC The problem is the reason I can't think like this, or I can't because I'm not sure about the points I'm trying to make always. Like I'm not always 100% sure that I'm right about things. Like so I'm, in being thoughtful, I'm afraid that I'll turn off with an ineloquently phrased or even incorrect statement, I will do damage that can't be undone in terms of having a good conversation about a topic. So I want to be very careful about, like I'm not saying afraid, fear is not what I'm talking about. I think fear is like not saying something out of fears at the core of the many of the problems of the world today. But I'm just saying, say stuff with care. If I'm going to touch race as a topic, it feels like you really should be deeply, first have a point to make, like you really care about a point you want to make. And second, think deeply about how to say that point in a way that communicates it the best. And touching, I would say, listen, I've, on your show, which is great. I mean, I'd like to say thank you for having Menchus Moebug. You are welcome. That's the name of the show. Thank you for having me a couple of times. It's great to sort of get him to, in this loose way to talk about different kinds of stuff. I don't think we talked about race at all. No, no, no, no. No, but I'm just bringing it back to what you were asking, which is if you read the Wikipedia, the perspective is going to be this guy talks about slavery constantly, where it's completely disproportionate to his work. But even on your show, you can tell even not outside of the race, not outside of the race stuff, that he's not ultra careful about, he's not- Nuanced. Yeah, he's not afraid to say something just like, I would say, let me just criticize him. My face is not you, this is me, carelessly say something controversial. Right. Like, I'm not saying he doesn't go, like, you know, that makes him, it's a very different thing than somebody who on purpose says something controversial stuff, like Milo Anopoulos, sorry, I forgot Milo, whatever his name is. Yeah, Anopoulos, yeah. Yeah, which is really nice to see that he's a genuine person who's thoughtful, he doesn't mean to, but he just carelessly seems to say things that I feel like damage the rest of his body of work. I can't really speak for him, but I would guess his point is, once you're swimming in this kind of worldview, you're going to be anathema already, so there's no pleasing these people, so why bother trying? Yeah, I think that's a deeply, that's a black pill way of seeing the world. It's not black pilled at all, because it's a cynical way, like these people. So like, it's saying that you're, it's a very kind of way of thinking, like, I'll say whatever I want, whoever comes along with me. No, you just earlier said yourself that race, racism has been weaponized as a way to shut down conversation. So I think his perspective would be, I am so outside the mainstream in my worldview that I know I'm going to be called racism, racist, so there's no point in trying to be nuanced, because I'm already going to get the scarlet letter. Yeah, I just disagree with that, because for example, I am one person that he turned off by his carelessness, and I think I should be a good target. I should be somebody. I think that's fair. And I'm just, like, he, it's very convenient to think that there's ridiculous people out there, which there are, who call everybody racist and sexist currently, and then you can't please them, so I'm not even gonna try. No, but there's like this gray area of people that I don't listen to the outrage culture, whatever. I don't, this Wikipedia article means nothing to me. Like, I'm not going to. Right, I got you. I'm more, I'm just seeing this careless person, and if he's going to be careless about race like this, I feel like if I walk along with him long enough, I'm going to catch the carelessness. I'm going to lose, like- I'll defend your perspective better than you can. Yeah, this is good. I'm taking notes. I talked to Eric Weinstein after you guys talked about me on your show. Bernal Weinstein. We had a good conversation. He invited me on his show. That would be an amazing conversation. And we got on the phone, and his concern, fairly, he goes, I don't want you to come on my show for the purposes of clowning me. And I would never do that. It would never- He might not be aware of who you- That's why he wanted to feel me out. He's like, when he hears troll, it can mean a lot of different things. And we had a very conversation, it very much was very clear that's not where the conversation would go. But I think when you are going to be on someone's show, there is a responsibility that they're not going to have to pay a cost for having you as their guest. So if you were put off by how he was in that live stream or two I did, like, I understand where you're coming from. I think he's very, very bright, but you have a different audience than I do, and you're going for something different than I am. No, no, no. Like, in my, in just the sense of- You wouldn't feel safe with him. Yeah, I wouldn't feel safe with him. But he's borne a lot for me. I think, I would like to actually talk to him one day. Alex Jones has crossed the other line for me. Well, you could do what you could do with me. Tape the episode, but never release it. No, it's one of those things where it'll be, when there's finally, they'll make a History Channel documentary about you and I, and how it all went wrong. Like the cult that we started, and everybody killed themselves. And there's a, we'll release it then, because it'll be like unseen footage. This is how it started. It'll be black and white in a basement somewhere in New York. Yeah, my mother's basement. This explains so much. Okay, so I spoke to Yaron Brook about objectivism, and Ayn Rand, he kind of argued, he highlighted the difference between capitalism and anarchism as around the topic of violence. And that having government be the sort of, the negative way to say it is like having a monopoly on violence. But basically being the arbiter of, or the people that making sure that violence doesn't get out of hand, that would. Yeah, 2020 showed that, yep. The government's great at that, yep. Well, what's, okay, without. This is the same with the straight face, making that argument. Good work, Yaron. All right, well, can you with a straight face argue for the idea that in anarchism, violence would not get out of hand? Sure, for one thing, if your worst argument against, one of my little quotes is, what are presented as the strongest arguments against anarchism are inevitably descriptions of the status quo. So the argument is under anarchism, you'd have warlords killing people, and then you'd have whoever's strongest gets to just take over a neighborhood. Well, we have that now. We saw that the police are perfectly comfortable disarming the population. And then when they try to protect themselves or punished, they were happy to stand down. You can only have that happen if you have a monopoly. If they're like, let's suppose you had a television stations, right? And CBS said, you know what? We're not going to broadcast. Cool. You don't broadcast. We're going to watch any of these other channels. So the problem with having a monopoly is everyone has to be dependent on this issue. What's amazing about minarchism, which objectivists are, is they will argue that government is really, really bad at everything it does and it touches. Therefore, it has to be in charge of the most important stuff. Well, that's not therefore, but there is a thing that's fundamentally different than all the other things. But Yaron Brook also said that no government has, this is on your show, has ever worked in the way he's proposing. Now, objectivism, Ayn Rand's philosophy is based on objective reality. And what she posited is you look and study the facts of nature, facts of reality and deduce things accordingly. And she very much regards herself as part of the Aristotelian tradition, as opposed to the Platonist tradition where the idea precedes reality and the idea is more real than what we see around us. So what he's saying is all the data, according to him, contradicts his argument, but still he's going to make this imaginary government that has never existed and there's no evidence that it can exist. Let's talk about objective law. To have access to the legal system, which is something we want, even just in terms of selling disputes, when you have a government monopoly, it's going to be more expensive, more difficult for poor people. The cost of hiring a lawyer is more expensive than hiring a surgeon. You can't say with a straight face, this is the only way or the best way. Okay, so, and the other thing is the argument for objectivism, they have this, against anarchism, they have this stupid claim, it's like, what if you're a member of one security company and I'm a member of another and we have a dispute and one shows up the door, what happens now? As if this is some insuperable argument. Well, we have that on earth. Every country is in a state of anarchism regarding every other country. We don't have a world government. So what happens if a Canadian kills an American in Mexico? I have no idea. I bet you don't have an idea. I bet you don't have an idea. What I'm sure of is that system has been worked out ahead of time between the three countries and it's been worked out in such a way that you and I don't have to reinvent the wheel. Same thing with cell phone companies. If I'm on Sprint, you're on Metro PCS and I call you, who pays? Does Sprint pay you? Do they split the difference? First of all, there's no objective way that one has to work. But the thing is companies who have auto accidents, they have arbitrage all the time. Like if I run into you, they work it out and it never reaches our desk. So the only thing that cops are good at is keeping people, at any government monopoly, is forcing people to be their customers by keeping them unsafe. Okay, there's a few things I'd like to say there that just explore some of these ideas. So one is in terms of Canadian and Mexico and so on, that it does, something has been worked out perhaps. Not perhaps, don't say perhaps. Do you know for sure that if some... There's a point I'm trying to make. So let's say for sure it's been worked out. There was a point in history where it wasn't worked out. Like to work, to come to a place of stability, there has to first be some instability. So when you first, like for every kind of situation, they're like dispute over space. Like who gets to own Mars, that kind of thing. There's a first for it. And then these different competing institutions will have to figure it out. And so there's the concern with anarchism, I think, or with any kind of interaction. What you said brilliantly, that there's an anarchism relative to the, there's no one world government. Alex Jones enters the chat. But the fear is that there's going to be an instability that doesn't converge towards some stable place. That is not the fear. That is the goal under Ayn Rand's philosophy. Markets have something what they always talk about as being creatively destructive, which means you look at something that's been happening for a very long time. Every generation, every innovator starts chipping away at it. He finds better ways, marginal improvement or marginal, and or it doesn't work and he goes broke. When government tries to implement improvement, we all have to suffer the consequences. When an innovator does, it's a huge asymmetry. If it hurts, it only hurts him. If it succeeds, he becomes rich and we all profit as a consequence. But the fear of anarchism, I think, is that it will be non-creative destruction. It'll be just destruction, right? It's not like the instability. Stability is one of these words that sounds objective, but has no real meaning. What field has stability? Let's suppose you want stability- Relationships. Yeah. Let's talk about medicine. Stability means we're not gonna invent new diseases or new treatments, right? If you mean stability in terms of a baseline of security, we have that already. Very few relationships turn violent. Under an anarchist system, look at it right now. If you look at a bar full of drunken young males full of testosterone, if you look at a hotel where everyone is not native to the area, those are both far safer than the places that the government has taken upon itself to protect you. The parks, the alleyways, the streets, the subways. We have right now a comparison of which is better at keeping people safe. And it's very obvious that when something is private and under someone's control, and there would be layers of, there'd be more police, but they wouldn't be a government monopoly. The store would have someone, the street would have someone, and you'd have your own personal security that would be attached to your phone. Having security as a function of geography, as opposed to a function of you as an individual, is a landline technology in a post-cellphone world. So you think it's possible to have, psychologically speaking, as an individual among the masses, to have a sense of security, even though there's not a centralized thing at the bottom of the whole thing. So there's not a set of laws that are enforced based on geography, like we have nations now. You can have a set of laws that are enforced in some kind of emergent, agreed-upon way. So basically, I wanna go to a hotel and trust that I'll be able to get a room, and nobody's gonna break down the door, and I don't know, take all my vodka. Let's take it a different way. If you were worried about a hotel having bedbugs, that's not something that government's involved in. And that's not an unrealistic concern. Are there mechanisms right now that you can undertake to make sure that's not the case? Yes. So it would be the same thing with, I want to make sure I go to a hotel that has security. It would be exactly the same thing. And here's another example, kosher food. People who keep kosher, Jews who keep kosher, their food has to be prepared in a certain way. It has to meet higher rabbinical standards, right? If you look at food, it will have that certification, the K, and there's even competition there. There's the K, and there's the stricter U letter. People don't notice it because they're not looking for it. You would have companies certifying different locales for their level of security, and it would take an hour to have an app just like when you have toll roads, right? That would tell you you're approaching an unsafe area, you're not gonna be covered by us, and you could have it color-coded very easily. We could do this today. But the thing is, you're exactly correct, but there's an assumption of you're already in a, okay, you can give me a different word than stability, but you're already in a place where the forces of the market or whatever can operate. Right. The worry is like, initially, you might not have enough stability to where you can choose one place over the other based on the security that they provide. We already have different types of security here because we have federal government, we have state governments, and we have local governments. Yes. And these often contradict each other. So the idea of the implausibility of having different security companies and having it be unstable or impossible, we already have a very rough example of it happening in real life. But all of it started, the idea of, especially with Yaron, is it all started with government monopoly of violence saying, no, kids, don't let violence get out of hand. We've had a civil war where half the country was slaughtered. That's a display of the government not having a monopoly on the violence, right? That's a split. It had such a monopoly on the violence in the North that it could draft people to fight others that they didn't even care about. But there's a South. So it's the government splitting. Okay. It's like a giant iceberg splitting. The argument is that you would have something like a civil war much more often under anarchism. First of all, if you had a civil war much more often, we don't have that with car companies, right? There's no car company that says, I refuse to pay you or whatever. That's not violence, I would say. And I'm playing the boss advocate here. Hold on, let me finish. It is violence because if I'm a company and I'm saying that my cars can run over yours with no consequences, this is a rough analog, why has that not happened? Now, in terms of having security system, if I am free, just like switching cell phone to go from one provider to another, and this one company as part of its payment doesn't want $50 a month, $100 a month, wants my son, I'm not going to be a member of this security company unless in that case, we're dealing with something like a Pearl Harbor or foreign invasion where it's like all hands on deck. Let's go by evidence. How many places do we have evidence of that you can have at a large scale? Well, it's not to get a large scale. Because it feels like once you don't know the person. What about eBay? eBay is an example of anarchism in practice. I am selling something to someone whose name I don't even know in a country that is nowhere approximate to me. And eBay acts as the arbiter. Sometimes I don't get the money after I get screwed over, but that's far less than the taxation that I have to give to the federal government. That's a great point. But it's in the space of finance. If I could, if on eBay, you could also commit violence. Theft is violence. No. If, yeah, if you give me 10 grand for a car, and I don't deliver anything, you've stolen 10 grand from me. Yes, but there's something uniquely problematic to being stabbed or shot. The reason you're stabbed or shot is because the government, despite its contract, is refusing to allow Second Amendment rights to be implemented among the citizenry. And the people who are making that the case are the cops. They are the ones who are the traitors to the Constitution and should be regarded as such. Whereas private companies are far more amenable to market pressures than the state is. I mean, it's a strong argument, but let's actually just briefly mention the scale thing. Why don't you think we should talk about scale? Because if you had anarchism just in Vermont or just in Brooklyn, fine. People make the argument you need anarchism or else China's gonna invade. But that's like saying, what, do these little countries don't exist? Does San Salvador not exist? Some of them are violent, some of them are not. But the point is they're not all at a moment's notice about to be invaded. Kuwait's an example of this. Kuwait was invaded by Iraq. And very quickly, all the big countries who are interested in having your stability, safe space, got involved and kicked them out of Kuwait. If you had this company that was waging war on the population, it seems quite likely that the other organization would get together and put a stop to this because they're not in a position to provide this service of security to their customers. Okay, all this is brilliant. But didn't you just say that we are actually in a state of anarchism relative to other countries? Yes. So isn't this what emerges? Aren't we actually living in a state of anarchism where we all have agreed? I haven't agreed to anything. So the basic criticism you have is you're born on a geographical land, geographical area, and you're forced to have signed a bunch of stuff just by being born in a particular place. Correct. So really, if you could just much easier choose Right. which space of ideas you are associated with, that would be actually a state of anarchism. Yes. And you could have a military that you sign up with. Sure. And you're certainly not putting people in prison to get raped because they're selling drugs. Yeah. And you're certainly not allowing everyone else on the street who wants to be there. Can we say something nice about Ayn Rand? I can talk about nice things about her all day. I own a copy of the Fountainhead, you know. Yeah. What to you is Ayn Rand's best idea, one that you find impactful, insightful, useful for us in modern society that you think about? That your life has meaning and productive work is your highest value, and that you shouldn't apologize, and this is something I despise, you shouldn't apologize for saying, I want to be happy, and I'm going to work toward that. And that, as a few others, that you owe nobody else, some random stranger, a second of your time. You see this a lot on Twitter and social media. People like demanding a debate or demanding you act a certain way and engage with them. You don't owe them anything. So I think those are some of her best ideas. And she teaches you how to think. Ayn Rand does not have all the answers, but she has all the questions. Do you think, what do you think about the whole selfishness thing? I mean, are you triggered by the word selfishness? So it's really unfortunate what she does, because you were just talking earlier about mold bug being carelessly. She, this is indefensible in my opinion. So she talks about the virtue of selfishness, and she claims that when people talk about selfishness, they mean concern primarily with the self. They don't. When people talk about selfishness, they mean in a sociopathic way, concern exclusively with oneself, right? They mean like, oh, if someone is dying on the street, I'm not going to even waste a second saving them because I'm selfish. So she sets up this complete caricature of the term. When she's attacking selflessness in her best sense is when there are people who have no sense of self. They have no values of their own. They have no goals of their own. Everything that's in their mind is gotten secondhand from the culture at large. And there's nothing unique or special from their perspective worth fighting for. So when she attacks, when she advocates for the self, she basically means self-development, self-improvement, and achievement. So I think that word choice is really false and needlessly off-putting. Yeah. Controversial, perhaps for the purpose of being controversial, I don't know. But it's just, it's not accurate. That's not what people mean by selfishness. Yeah, I would say it's one of the reasons probably her philosophy is not as much adopted or thought about. It's like, it's funny, like the use of words means something. Exactly as you said, that's my criticism. I just small bug, which could be incorrect criticism, by the way. So I'm not exactly sure. Can we talk about some modern day chaos and politics? Yes, please. I hate chaos. Speaking of your hatred for chaos, let's talk about secession. Oh yeah, I was the first one to talk about it. Oh yeah, I was the first one on this trip. Yeah, you were, well, the Civil War beat you to it, but sure. In contemporary times. In contemporary times, you were on this. Can you talk about what is the idea of secession? What are the odds that it might happen? What does it mean for the United States in some way for different states to secede? Sure, America has been one country with several cultures since the beginning. There's absolutely no reason for someone, this goes back to the anarchist idea, if you despise Donald Trump, which is your prerogative, if you think Joe Biden is a clown, which is your prerogative, there's absolutely no reason for you to be governed by someone you disapprove of. This is an incoherent, nonsensical concept. The only reason we even take it as a hypothesis is that we're trained to the contrary since kindergarten. A secession, I don't know along what lines, but increasingly it's becoming harder and harder for people to have conversations. I think social media, and this is something people despise social media for, I think this is something that social media has done well, which I'm advocating for, is it tends to kind of run through ideas through like an evolutionary process and drive them to their logical conclusion. So it's very hard to be a moderate online because there's gonna be people pushing through your ideas through several cycles and then you're gonna end up at some kind of more pure or if you wanna dislike it, extreme perspective. Having these different pockets, it's not really governable because people fundamentally have different worldviews. So I don't know what secession would look like. I think the number is really increasing at an exponential rate. I do not think- The number of supporters. Of supporters. I think the claim that this can only be accomplished through violence is false, it's a lie. Just like any divorce doesn't have to be a divorce. Doesn't have to involve beating your ex-husband or ex-wife. And I'm very much looking forward to this becoming a reality far quicker than I ever expected. Well, do you think there's a value of competing worldviews being forced to be in the same space? Yes, within a context. So we can agree, if group one thinks A, B, and C are the fundamental aspects of their worldview and argue within that, and world group two thinks D, E, and F and argue within that, so you're gonna have a lot of argument within those space. But if there's fundamental differences in worldview, there's no reason to be, especially when each views the other as completely incoherent and unreasonable. Do you think there's a line of fundamentally different worldviews that along which a secession will happen in the United States? Is there something that emerges to you as a set of ideas that are like, what do you call that? Like you can't come to an agreement over. Yeah, I think that's already happening. Like with the masks, I think there's just two fundamental perspectives, and each one thinks the other is insane and also deadly and destructive. And I don't see how there's any discourse on this topic. So on the left- I wouldn't say it's left versus right. I think it's people who are pro-risk versus people who are risk-averse. Yeah, so risk-averse, and then there's like a hope for the comfort of the sort of centralized science giving the truth, and then everybody must follow the truth of the proper way to behave. And then there's on the other side, a distrust of any kind of centralized institutions of anybody who might use control to try to gain greater and greater power, and masks are a symbol of that. And even if masks are or are not a- Efficacious, yeah. Yeah, effective way of stopping the virus, which is really unfortunate to me from a perspective. I happen to be on a survey paper about masks. Like people don't seem to care about the data or so on. Correct. This has become just a nice point on which to then highlight the difference between the two sides. Yeah, that's really interesting. I mean, it sounds kind of on the face, kind of ridiculous that the secession would occur over a mask. It wouldn't, but I'm saying this is an example of something where there's a clean break. Yes. And risk-averse versus someone who's risk-seeking, these are just two fundamentally different perspectives. Do you want to have an NHS, or do you have a one of a market-based healthcare system? You can make very valid arguments for both. There's no reason for everyone to be under one. But you think that's not something that's, you think that's irreconcilable, that's the word. Yeah. That that's not in the space of ideas that you can have in the same room together, and they fight at each other and ultimately make progress. Like that secession is the more effective way to proceed forward. Yes. Well, do you see a possible world where no is the answer? Meaning, I know you say yes, because you kind of lean on the side of freedom and anarchism. Yes. Like you want to make, let me make an argument in terms of divorce, which is in your worldview or your intuition is you want to make secession as frictionless as possible. Of course. Along all lines, not just like states or whatever. Just like you want to choose, you want to be free. Yeah, and peaceful. Let me make my authoritarian Russian... Okay, Papa Stalin. Papa Stalin argument in terms of relationships. Like when shit goes wrong in a relationship... Watch your language. Okay, there's only a place for one Stalin at this table. Okay. Okay, I'll get to be Lenin. No, you get to be like Merkel as our previous discussion with Putin. Okay, don't let me unleash the hounds. You know, you want to work through some of the troubles before you get divorced. You want to do the work in relationships sometimes. It goes up and down. It's been 200 plus years. It's done. But listen, okay, so it's not a one night stand, but you know... Look at Trump. I don't see the middle ground. He's either a complete calamity buffoon or he's been the first great president we've had in like many, many years. So you think that there's something different now than it was 20 years ago? Yes, social media and access to information. And the division will only increase, you think? Oh, yes. So Trump is not an accident of history. So they thought Trump was the river, but he was the dam. Trump was the dam. They thought he was the river. So in that analogy, Trump being gone makes things worse. Yes, for that perspective. Because now things are really going to hit the fan. So what are the odds of secession? I don't know. And my desperate hope is that it's peaceful. But I think the number of people who are becoming very comfortable with the violence is making me very unsettled. Well, I see words as violence and your Twitter... It's like Hiroshima, times a million. Sometimes I curl up in the corner crying after I check your Twitter. I'm crying after I check your Twitter feed. So, but in all seriousness, you think it's possible to do non-violent secession? It's a good check of Slovakia. Look at Brexit. Brexit was a secession. Right, right. So you can have... Civil War did not need to be fought. That would have been an unviolent secession. And if you worry about slavery, you could have bought off all the slaves, import them to the North. It still would have been cheaper and less loss of life and probably better for race relations. Yeah, I don't know enough history to wonder about like how the Civil War could have been avoided. Well, that's how. Is, well, conversation? So like... No, no, if they want to secede, say, look, here's what we're going to do. We're going to let you secede, but you have to end slavery. They seceded because of slavery. Here's the other thing. There's like this... Some circles of conservatism have this myth that, oh, it wasn't about slavery, it was about states' rights. Well, if you go back, every state when they seceded, released the press release, and they said explicitly, we're doing this because of slavery. So that is an abomination that needs to be taken care of. But the way... Other countries have ended slavery peacefully. One of the ways to do it is pay them by all... And we ended up doing this after the war. I think the South people got reparations, the slave owners, it was just insane. Bring them North, you want to go to Canada, whatever, and you agree and that's our peace treaty. Because the people who died weren't the slave owners, it was white trash. And it was... That's who always... And I hate that that's the term, I can't think of a better one, but that's who always ends up fighting these wars often, disproportionately, it's poor people and uneducated people. And I did not regard them as cannon fodder. I think it's horrible. So what would it look like? There'll be two founding documents? Yeah, they had their constitution. Actually, I don't know the history of that. Yeah, they had a constitution, but it was much more decentralized. If secession doesn't happen, you said that Donald Trump was the dam, not the river. That sounds like Walt Whitman or something, you should... It's poetry, okay? Are you flirting with me? You know us, we don't flirt, we just... Go to town. Club and drag you to the cave. It's just the hammer, we hammer and sickle. And you don't wanna know about the sickle. It's not good cop, bad cop, it's... Bad cop, worse cop. Yeah, what do you think 2024 looks like in terms of the candidates? It's gonna be Kamala Harris as the Democratic candidate. I'm really looking forward to Ted Cruz versus Mike Pence because they're both very good at debate. That would be interesting to see how they differentiate themselves. But honestly, I mean, things are gonna get really ugly really soon. What about Donald Trump coming back? He's not gonna do it. So things, in my opinion, I think things are gonna be really, really crazy in 2021. And talking about the dam being gone, like I... 2021, so this year coming up? Oh yeah, it's gonna be complete mayhem. What do you think, like prediction-wise, and this is empirical, what do you think Donald Trump's Twitter feed looks like in 2021? At the end of 2021, we'll look back and see, what was the Obamagate exclamation points, or we won? He is going to be, for the first time in history, holding the Republican Party accountable to the base. We've never had that happen before. I think he's going to be holding their feet to the fire, radicalizing them. And given that they have the Senate, where it's gonna be 50-50, the Democrats have a three-seat majority in the House. This is not a governing coalition for either. It's going to be complete mayhem. What does that actually look like? Like, what are the key values you think that he's gonna try to push? I think it's just gonna be very contrarian. He's gonna be holding them accountable in terms of budgeting, even though he never did that as president. I think in terms of some kind of nominations. Here's the thing. This is the first time since Nixon, 50 years, and things weren't as politicized then, where an incoming president doesn't have control of the Senate. The Senate has the vote over cabinet positions. I do not see a possibility of them not trying to pick a fight on one or two of these nominations. And that's gonna, and especially as revenge for Kavanaugh, this is gonna get very bloody very quickly. And I think Mitch McConnell, there's a sadistic side to him. He revels in being the brakes on the car. And I think the base, it's just gonna be throwing just, they're gonna want some bone. It's like, oh yeah, we eliminated this one person. So that's gonna get really ugly really quickly. You see it being quite divisive, like a division increasing, not stabilizing or decreasing. And I'll be doing my part. No, I know you'll be doing my part, but I'm trying to do my part. Like to me, the division is shouting over people like Elon Musk, people who are actually building stuff and accomplishing things in this world in terms of like- Elon said he took the red pill. No, see, you're talking about the, I'm talking about, forget Elon, SpaceX and Tesla and actually the good sides of some of the things that Google is doing, like actually building things, like making the world's information searchable, all that kind of stuff. Like all the stuff, making actually the world a better place. There's a bunch of technologies that are increasing our quality of life, all that kind of stuff. I feel like they get not much credit in our public discourse because of the division. Division is just like, it's clouding our ability to concentrate on what's awesome about this world. Well, you know what would eliminate the division, right? Secession? Yeah. See, I don't, it's hard for me to disagree. It's hard for me to disagree because, but at the same time, secession, I'm a romantic at heart. To me, divorce breaks my heart. Cool, but do you want to live in a country, yeah, but do you want to live in a country where Joe Rogan is regarded as an example of someone who's spreading white supremacy? I don't. Well, but see, I feel like that's not the country we live in. That's just the- The New York Times did it. The cathedral does it on a regular basis. Well, the cathedral is, okay. The cathedral, I guess you can maybe define the cathedral, but it's like the centralized institutions that have a story that they're trying to sell and so on. Yeah, this is Moldvick's concept, but yeah, they basically are set the limits of permissible discourse and create a narrative for the population to follow. But to me, that's a minority of people. Yeah, minority is always controlling everything in any country. The vast majority of the masses have no thought. Yeah, but minorities can be overthrown. Sure, the circulation of the elites, yeah. The way the... What progress looks like is ridiculous people take power and then they get annoying and new ridiculous people that are a little bit better overthrow the previous- No, I think progress happens despite the people who are in power, not because of them. Right, and so why is this a secession? So is it always about overthrowing the powerful? Is that how progress happens? No, I think progress happens despite the powerful. The powerful are gonna do what's in their power to maintain their power and they're gonna fight innovation because it's a threat to their control. There's always gonna be the New York Times of the world, right? There's always gonna be those people that have a narrative. Sure, and let them have their own country. So it's two countries. One has Joe Rogan, the other one has the New York Times? That's basically what's happening right now. It's just geographically doesn't map out very well, but culturally, yes. But that's just cultural stuff. Like there's a layer of public discourse. Okay. I don't mean, like that's what we're operating under now, but there's actual progress being made, like roads being built, hospitals being run, all those kinds of things, like different innovations. That seems like secession is counterproductive to that. Right, because one country would have all the roads and the other would have all the hospitals. That's a great point. No, that's not the point I'm trying to make. It just feels like the division that we're experiencing in the space of ideas could be constructive and productive for building better roads and better hospitals, as opposed to like using that division to separate the countries. They're all going to have to solve the same problems, it feels like. Sure, but they can solve them differently and compete that way. Mass is a great example. Yeah. We're seeing that right now. Different countries have different mass mandates and things like this. And the competition within the same structure, within the same founding documents and same institutions is not effective, you think, as effective as separating. It is effective, but there is a certain point, which I think we have long passed, where there is not a governing consensus ideologically or culturally. Let me ask you a fun question, okay? Knock, knock. Who's there? Mars. God of War. The other one. The planet. Yeah. So, there is a kind of captivating notion that we might, I'm excited by it, the human being stepping foot on Mars. That to me is, it's like one of those things that feels like it's, why do we want to engage in space exploration? But I'm a bit with Elon Musk on this, which is, it's obvious that eventually, if human species is to survive, it's going to have to innovate in ways that includes the space. Okay. Like there's a lot of things we're not able to predict yet that if we push ourselves to the limits of space, like new ideas will come that will be obvious 100 years from now and that we're not even imagining now. And colonizing Mars, that idea that seems ridiculous, exceptionally difficult, impossibly expensive, is something that is actually going to be seen as obvious in retrospect and that we should engage in. Okay. That's just to contextualize things. The fun idea and experiment from a philosophical and political sense is what kind of government, how do you orchestrate a government when you go to Mars? Like we don't get too many chances like this, but how do you build new systems, not in place of old ones, but in a place where no system previous have existed? I think organically. I hate that word, but that's the correct word. You would have to figure out, I mean, that's how America was built. You had, it was a Jamestown colony and they tried to do communism here and it completely failed. Then they went to a more free market system with the second world war. Free market system with the second wave of colonists is my understanding. For Mars, I mean, it depends on the population, who the population was, the number of people. I don't know. These are all kind of hypotheticals that I don't really have any good insight in whatsoever. I'm not a space person. I hate astronomy. Like I hate it. So a lot of people look up to the stars and they're filled with awe and wonder about the mystery of the universe and you look up to the stars and you feel what? I'm not looking up. I'm looking at the earth. If you look at what's, I'd much rather given a choice between Mars and the deep sea, I'd much rather spend a week at the deep sea and all the life forms that are down there. Cause they're literal aliens. It's like things that are not literal, but they're unimaginable to us. Some of the things down there. Yeah, that's true. To me, it's an interesting thought experiment to see when you have 10 people, when you have a hundred people. Right. How do you build an effective, you know, this is actually really useful for company, right? Like how do you build an effective company that does things? It's not an obvious, despite everybody being really certain about everything in this modern world, to me, it's not obvious, like how do you run successfully as a group of people? I agree. That's what I'm saying. It also, organic means you have to look at who the people are and tailor the organization to them as opposed to try to impose something. But you get to also select people. Right. Cause it's not gonna be open borders on Mars. Oh, right. I was gonna say when you have one country, it's all open borders. Yeah. Yeah, you're right. From outer space. Right. Some say they're aliens already there. So you're gonna have to negotiate that. Sure. We're aliens, so. We're aliens to somebody. We're legal aliens. Do you think there's alien civilizations out there? Yes, of course. What do you think is their system of government? Anarchism. Cause they're advanced. Do you honestly think there's intelligent life forms out there? Of course, just the math. It's impossible if there isn't. So what do you make of all the stories of UFO sightings, all that kind of stuff? Do you think they've visited Earth? Yes. My grandfather was an air traffic controller in the Soviet Union. And he said they would often see these things that were not operating the way we knew vehicles operate. So that's good enough for me. So, I mean, do you think government is in possession of some, like, what do you think government is doing with this kind of information? Do you think somebody has any understanding of UFO sightings or any kind of information about extraterrestrial life forms that are not known to the public? Yes, that's indisputably true. I think the fact that so many of these sightings are from aerodynamic professionals, like pilots and things of that nature. They are people who've seen it all, who are reputable. If they are on record saying, I've seen things that don't make sense, and both the Russians and the Americans thought it was the other one, that says something. Shouldn't that be a bigger problem? Shouldn't that be bigger news and a bigger problem if government is in fact hiding it? I guess, but what are they going to do with that information? It's a good question. Like, if a UFO, if an extraterrestrial spacecraft, which most likely would be a crappy space, like, it wouldn't be the actual aliens. It would be some drone probe ship. AI. Yeah, AI, yeah. So if that, what would you do with that information? As somebody that's in charge of, you know, like, you see how badly WHO fumbled the discussion of masks, masks? Yeah, masks is one of them, but everything really, in terms of communicating with the public honestly about what they know, what they don't know. And that's a trivial one. Right. I don't, I don't, I don't know. I don't, I don't know, they're certainly feel incompetent at being able to communicate effectively with the public about something much more difficult, much more full of mystery, like a UFO, a thing, a piece of material that's out of this earth. Forget, like, organic material. I don't, I don't know. To me, so from a scientist's perspective, it would be beautiful, it would be inspiring to reveal this to the world. Here's a mystery and make it completely public. Share it with China, share it with everybody. I think there is a domino effect where the concern would be what else are you hiding from us? And at that point, if you said, no, no, no, this is everything, people wouldn't believe you and they would, you can't blame them for not believing them. Ah, yeah. And then it'll be like, show us the aliens. They'd be like, we don't have them, we just have the craft. You're lying. Speaking of aliens, offline, you mentioned elves. Yeah. And psychedelics. Yeah. What do you think about psychedelics in terms of the kind of places that can take your mind, the kind of journey it can take you on? Like, what do you think, what is, what do you think the psychedelics do to the human mind and what does that say about the capacity of the human mind and just in general, like the mysteries of all that's out there? I don't know that we understand what they do. The way I heard it explained to me is that much of the human mind isn't about receiving information but blocking information, right? Because we're so, there's so much data coming in any moment that you basically have to train yourself to see and to hear only what you want to see and to hear. And that what psychedelics do is they tear that away and suddenly your mind is like, and suddenly you're much more aware of what's out there. And also you're going to be noticing patterns that you hadn't noticed before. I know you had that researcher on the show and he kind of discussed this at some length. I mean, Rogan is probably the person who popularized DMT more than anyone. He's obviously the person who's popularized DMT more than anything. I don't know anyone who has, even researchers who have anything close to a coherent explanation of why this drug, which exists everywhere, would have this very specific, very extreme effect on so many people who are going to be experiencing such bizarre consequences as a result of it. I think it's very interesting that this is talking about the government, the CIA started experimenting with LSD. They killed one of their own people, drove them to suicide. And there was a lot of research into, Terrence McKenna talks about this, into this field and then very quickly, once they got into the mainstream, they shut it down. Even though it's not addictive, it doesn't cause you to go crazy or anything like that. And there was a lot of propaganda against its use, which I think thankfully is now somewhat receding. I think in Colorado, just legalized mushrooms, something like that. And I think it'll be very interesting to see what happens as a result of this. Yeah, and the interesting thing is there doesn't seem to be for certain psychedelics, like psilocybin, like mushrooms, there doesn't seem to be a lethal dose. There doesn't seem to be a lethal dose, which is fascinating. Like Matthew Johnson, the Hopkins professor that you mentioned, I'm definitely going to do one of his studies. It's a really cool way to do what he calls a heroic dose of psilocybin. Oh, I want to do it. What do I have to do? Let's do it. I'll let you know. So he is... A heroic dose, holy crap. Yeah, but it's safe. What's a heroic... How many grams are we talking? I don't know, but it's just, it's big. He says that... This is going to have a kick. Yeah. So he says that, I mean, he also studies cocaine. He studies all kinds of drugs. And he's like, the psilocybin is... Heroic dose of cocaine kills you. Well, you can't, so you can't even come close. So he says like, the problem with studying cocaine is you have people who are addicted to cocaine or war or so on. You give them the kind of doses that we can and part of the study is like, it's nothing to them. Right, yeah, yeah. Psilocybin is the only one where even daily users or regular users are blown away by the dose they give them. Oh, fuck. So... Okay, well, we're going back to Russia. You can go to Russia in your mind. Yeah. You can go to outer space. Maybe you'll become an astronaut or astronomer after all. Maybe I'll be Baba Yaga. I'll let people look that one up. Holy crap, wow. What is love? What do you think this thing is? Like our attachment to other human beings? And is it something that we should give to just a few people? Yes, that's for sure. When I was working with D.L. Hughley in his book, he didn't use the term, but he was describing low-key depression. And he talked about how he was in the airport and he noticed a girl had a red dress and he went up and thanked her. And she was like, what are you thanking for? And he had realized he hadn't registered color in weeks. And I think love is like that. When you see someone and you're just like, oh, like your eyes are open. Like this is something I've never seen before. Or I want more of this, that kind of thing. It really disorients and reorients your thinking. Don't you find that the world is full of that nonstop? It's not just like a person either. Yes, but when it's in a person, it's a whole other level. Because it's like, this is going to be great for years. Every day it's something new. I mean, that is rare. You think it's rare? I mean, find someone who you could talk to them for years and not run out of things to talk to. Oh, that's true, for years, yes. That's rare. And know that they really, if you leave the room, they will do right by you. That's really rare. Well, from a Russian perspective, you just don't give them another choice. This is Tavarish New Year, New Year's Eve. So you talked about secession and the world burning down and you holding the match at the end, standing with a big smile on your face. Yes, why so serious? But let me ask you, if it doesn't include flame and secession and destruction and laughing malice and makeup and a white suit at the end, how do we bring more kindness and love to the world in 2021? Oh, easy. Be comfortable saying, I want to be happy. And if there's someone who interjects and gives you attitude, arms lengthen. Surround yourself with people who also want to be happy. Here's a great example. My buddy, Chris Williamson, who I've mentioned before, he's a podcaster, does Modern Wisdom. He's an awesome dude and we became very close friends this past year. And he was in Dubai recently and he sent me pics from Dubai by the pool, just loving life. And it took me a week and then it clicked in my head and I'm like, you know what, for some other people, if they saw him, underwear model, at the pool, they would think this is him bragging or humble bragging. And that never entered my head. I'm like, oh man, I'm so glad my boy can be having a good time and is sharing his joy with me. That's the kind of people you need to surround yourself with where it never enters their head to be resentful or anything other than sharing in your bounty. What makes you happy? I'm happy all the time. And one of the points I made in my life is like, I really hated, I really did not like to give advice because I feel don't give advice until you know what you're talking about. And to me, what makes me happy is being self-actualized. I am in a position with my career where I could be myself 24 seven, where I never have to engage in small talk, where I never have to interact with someone I don't want to. And I'm very blessed to have that. Very few people have that. And to have that be not only, to have that be like rewarded and having people find that something of value to them makes me very, very happy. But also being an uncle, I have two little nephews. They make me very, very happy. Sure, my sister's raising them Russian, so they talk like immigrants, but that's okay. And we're gonna change that. We have to dismember her, that's fine. That makes me happy. And to be able to finish this book and know it's gonna give people a sense of hope, that's really validating. Well, what are you most grateful for for our conversation today? You're stealing my bet. What am I most grateful for? I am very grateful that I can come in here not knowing what we're gonna talk about and know it's not going to be something I have to be on guard about or I have to watch my words and that neither you or your audience is going to be responding derisively. I feel safe here. You're welcome. Thanks for talking to me, Michael. It was awesome. Thank you for listening to this conversation with Michael Malice, and thank you to our sponsors. NetSuite Business Management Software, Athletic Greens All-in-One Nutrition Drink, Sun Basket Meal Delivery Service, and Cash App. So the choice is success, health, food, or money. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount to support this podcast. And now let me leave you with some words from Emma Goldman on anarchism. People have only as much liberty as they have the intelligence to want and the courage to take. Thank you for listening and hope to see you next time.

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Erik Brynjolfsson: Economics of AI, Social Networks, and Technology | Lex Fridman Podcast #141

The following is a conversation with Eric Brinjalsen. He's an economics professor at Stanford and the director of Stanford's Digital Economy Lab. Previously, he was a long, long time professor at MIT where he did groundbreaking work on the economics of information. He's the author of many books, including The Second Machine Age and Machine Platform Crowd, co-authored with Andrew McAfee. Quick mention of each sponsor, followed by some thoughts related to the episode. Vincero Watches, the maker of classy, well-performing watches. Four Sigmatic, the maker of delicious mushroom coffee. ExpressVPN, the VPN I've used for many years to protect my privacy on the internet. And Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. As a side note, let me say that the impact of artificial intelligence and automation on our economy and our world is something worth thinking deeply about. Like with many topics that are linked to predicting the future evolution of technology, it is often too easy to fall into one of two camps, the fear-mongering camp or the technological utopianism camp. As always, the future will land us somewhere in between. I prefer to wear two hats in these discussions and alternate between them often. The hat of a pragmatic engineer and the hat of a futurist. This is probably a good time to mention Andrew Yang, the presidential candidate who has been one of the high-profile thinkers on this topic. And I'm sure I will speak with him on this podcast eventually. A conversation with Andrew has been on the table many times. Our schedules just haven't aligned, especially because I have a strongly held to preference for long form, two, three, four hours or more, and in person. I work hard to not compromise on this. Trust me, it's not easy. Even more so in the times of COVID, which requires getting tested nonstop, staying isolated and doing a lot of costly and uncomfortable things that minimize risk for the guest. The reason I do this is because to me, something is lost in remote conversation. That's something, that magic, I think is worth the effort, even if it ultimately leads to a failed conversation. This is how I approach life, treasuring the possibility of a rare moment of magic. I'm willing to go to the ends of the world for just such a moment. If you enjoy this thing, subscribe on YouTube, review it with Fast Stars on Apple Podcasts, follow on Spotify, support on Patreon, connect with me on Twitter, Alex Friedman. And now, here's my conversation with Eric Greenjohnson. You posted a quote on Twitter by Albert Bartlett, saying that the greatest shortcoming of the human race is our inability to understand the exponential function. Why would you say the exponential growth is important to understand? Yeah, that quote, I remember posting that. It's actually a reprise of something Andy McAfee and I said in the second machine age, but I posted it in early March when COVID was really just beginning to take off and I was really scared. There were actually only a couple dozen cases, maybe less at that time, but they were doubling every like two or three days. And, you know, I could see, oh my God, this is gonna be a catastrophe and it's gonna happen soon. But nobody was taking it very seriously, or not a lot of people were taking it very seriously. In fact, I remember I did my last in-person conference that week. I was flying back from Las Vegas and I was the only person on the plane wearing a mask. And the flight attendant came over to me, she looked very concerned. She kind of put her hands on my shoulder, she was touching me all over, which I wasn't thrilled about. And she goes, you know, do you have some kind of anxiety disorder or are you okay? And I was like, no, you know, it's because of COVID. And she's like- This is early March. Early March. But, you know, I was worried because I knew I could see, or I suspected, I guess, that doubling would continue. And it did. Pretty soon we had thousands of times more cases. Most of the time when I use that quote, I try to, you know, it's motivated by more optimistic things like Moore's law and the wonders of having more computer power. But in either case, it can be very counterintuitive. I mean, if you walk for 10 minutes, you get about 10 times as far away as if you walk for one minute. You know, that's the way our physical world works. That's the way our brains are wired. But if something doubles for 10 times as long, you don't get 10 times as much. You get a thousand times as much. And after 20, it's a billion. After 30, it's a, no, sorry. After 20, it's a million. After 30, it's a billion. And pretty soon after that, it just gets to these numbers that you can barely grasp. Our world is becoming more and more exponential, mainly because of digital technologies. So more and more often, our intuitions are out of whack. And that can be good in the case of things creating wonders, but it can be dangerous in the case of viruses and other things. Do you think it generally applies? Like, is there spaces where it does apply and where it doesn't? How are we supposed to build an intuition about in which aspects of our society does exponential growth apply? Well, you know, you can learn the math, but the truth is our brains, I think, tend to learn more from experiences. So we just start seeing it more and more often. So hanging around Silicon Valley, hanging around AI and computer researchers, I see this kind of exponential growth a lot more frequently. And I'm getting used to it, but I still make mistakes. I still underestimate some of the progress in just talking to someone about GPT-3 and how rapidly natural language has improved. But I think that as the world becomes more exponential, we'll all start experiencing it more frequently. The danger is that we may make some mistakes in the meantime using our old kind of caveman intuitions about how the world works. Well, the weird thing is it always kind of looks linear in the moment. It's hard to feel, it's hard to introspect and really acknowledge how much has changed in just a couple of years or five years or 10 years with the internet. If we just look at investments of AI or even just social media, all the various technologies that go under the digital umbrella, it feels pretty calm and normal and gradual. Well, a lot of stuff, I think there are parts of the world, most of the world is not exponential. The way humans learn, the way organizations change, the way our whole institutions adapt and evolve, those don't improve at exponential paces. And that leads to a mismatch oftentimes between these exponentially improving technologies or let's say changing technologies, because some of them are exponentially more dangerous and our intuitions and our human skills and our institutions that just don't change very fast at all and that mismatch I think is at the root of a lot of the problems in our society, the growing inequality and other dysfunctions in our political and economic systems. So one guy that talks about exponential functions a lot is Elon Musk. He seems to internalize this kind of way of exponential thinking. He calls it first principles thinking, sort of the kind of going to the basics, asking the question, like what were the assumptions of the past? How can we throw them out the window? How can we do this 10X much more efficiently and constantly practicing that process? And also using that kind of thinking to estimate sort of when, create deadlines and estimate when you'll be able to deliver on some of these technologies. Now, it often gets him in trouble because he overestimates, like he doesn't meet the initial estimates of the deadlines, but he seems to deliver late, but deliver. Right. And which is kind of interesting. Like what are your thoughts about this whole thing? No, I think we can all learn from Elon. I think going to first principles, I talked about two ways of getting more of a grip on the exponential function. And one of them just comes from first principles. If you understand the math of it, you can see what's gonna happen. And even if it seems counterintuitive that a couple of dozen of COVID cases could become thousands or tens or hundreds of thousands of them in a month, it makes sense once you just do the math. And I think Elon tries to do that a lot. In fairness, I think he also benefits from hanging out in Silicon Valley and he's experienced it in a lot of different applications. So, it's not as much of a shock to him anymore, but that's something we can all learn from. In my own life, I remember one of my first experiences, really seeing it was when I was a grad student and my advisor asked me to plot the growth of computer power in the US economy in different industries. And there are all these exponentially growing curves. And I was like, holy shit, look at this. In each industry, it was just taking off. And you didn't have to be a rocket scientist to extend that and say, wow, this means that this was in the late 80s and early 90s, that if it goes anything like that, we're gonna have orders of magnitude more computer power than we did at that time. And of course we do. So, when people look at Moore's law, they often talk about it as just, so the exponential function is actually a stack of S-curves. So basically it's you milk or whatever, take the most advantage of a particular little revolution and then you search for another revolution. And it's basically revolutions stack on top of revolutions. Do you have any intuition about how the heck humans keep finding ways to revolutionize things? Well, first let me just unpack that first point that I talked about exponential curves, but no exponential curve continues forever. It's been said that if anything can't go on forever, eventually it will stop. And- That's very profound. It's very profound, but it seems that a lot of people don't appreciate that half of it as well either. And that's why all exponential functions eventually turn into some kind of S-curve or stop in some other way, maybe catastrophically. And that's happened with COVID as well. I mean, it was, it went up and then it sort of, at some point it starts saturating the pool of people to be infected. There's a standard epidemiological model that's based on that. And it's beginning to happen with Moore's law or different generations of computer power. It happens with all exponential curves. The remarkable thing is you allude, the second part of your question is that we've been able to come up with a new S-curve on top of the previous one and do that generation after generation with new materials, new processes, and just extend it further and further. I don't think anyone has a really good theory about why we've been so successful in doing that. It's great that we have been, and I hope it continues for some time, but it's, you know, one beginning of a theory is that there's huge incentives when other parts of the system are going on that clock speed of doubling every two to three years. If there's one component of it that's not keeping up, then the economic incentives become really large to improve that one part. It becomes a bottleneck and anyone who can do improvements in that part can reap huge returns so that the resources automatically get focused on whatever part of the system isn't keeping up. Do you think some version of the Moore's law will continue? Some version, yes, it is. I mean, one version that has become more important is something I call Cume's law, which is named after John Cume, who I should mention was also my college roommate, but he identified the fact that energy consumption has been declining by a factor of two. And for most of us, that's more important. The new iPhones came out today as we're recording this. I'm not sure when you're gonna make it available. Very soon after this, yeah. And for most of us, having the iPhone be twice as fast, it's nice, but having it, the battery life longer, that would be much more valuable. And the fact that a lot of the progress in chips now is reducing energy consumption is probably more important for many applications than just the raw speed. Other dimensions of Moore's law are in AI and machine learning. Those tend to be very parallelizable functions, especially deep neural nets. And so instead of having one chip, you can have multiple chips, or you can have a GPU, a graphic processing unit that goes faster and now special chips designed for machine learning, like tensor processing units. Each time you switch, there's another 10X or 100X improvement above and beyond Moore's law. So I think that the raw silicon isn't improving as much as it used to, but these other dimensions are becoming important, more important, and we're seeing progress in them. I don't know if you've seen the work by OpenAI where they show the exponential improvement of the training of neural networks, just literally in the techniques used. So that's almost like the algorithm. It's fascinating to think, can I actually continue us figuring out more and more tricks on how to train networks faster and faster? The progress has been staggering. If you look at image recognition, as you mentioned, I think it's a function of at least three things that are coming together. One, we just talked about faster chips, not just Moore's law, but GPUs, TPUs, and other technologies. The second is just a lot more data. I mean, we are awash in digital data today in a way we weren't 20 years ago. Photography, I'm old enough to remember, it used to be chemical, and now everything is digital. I took probably 50 digital photos yesterday. I wouldn't have done that if it was chemical. And we have the Internet of Things and all sorts of other types of data. When we walk around with our phone, it's just broadcasting a huge amount of digital data that can be used as training sets. And then last but not least, as they mentioned at OpenAI, there have been significant improvements in the techniques. The core idea of deep neural nets has been around for a few decades, but the advances in making it work more efficiently have also improved a couple of orders of magnitude or more. So you multiply together a hundredfold improvement in computer power, a hundredfold or more improvement in data, a hundredfold improvement in techniques of software and algorithms. And soon you're getting into million-fold improvements. You know, somebody brought this up, this idea with GPT-3 that it's, so it's training in a self-supervised way on basically Internet data. And that's one of the, I've seen arguments made, and they seem to be pretty convincing, that the bottleneck there is going to be how much data there is on the Internet, which is a fascinating idea that it literally will just run out of human-generated data to train on. I know, we may get to the point where it's consumed basically all of human knowledge, or all digitized human knowledge, yeah. And that will be the bottleneck. But the interesting thing with bottlenecks is people often use bottlenecks as a way to argue against exponential growth. They say, well, there's no way you can overcome this bottleneck. But we seem to somehow keep coming up in new ways to overcome whatever bottlenecks the critics come up with, which is fascinating. I don't know how you overcome the data bottleneck, but probably more efficient training algorithms. Yeah, well, you already mentioned that, that these training algorithms are getting much better at using smaller amounts of data. We also are just capturing a lot more data than we used to, especially in China, but all around us. So those are both important. You know, in some applications, you can simulate the data, you know, video games, some of the self-driving car systems are simulating driving. And of course that has some risks and weaknesses, but you can also, if you want to exhaust all the different ways you could beat a video game, you could just simulate all the options. Can we take a step in that direction of autonomous vehicles? Make sure you're talking to the CTO of Waymo tomorrow. And obviously, I'm talking to Elon again in a couple of weeks. What's your thoughts on autonomous vehicles? Like where do we stand as a problem that has the potential of revolutionizing the world? Well, you know, I'm really excited about that, but it's become much clearer that the original way that I thought about it, most people thought about it, like, you know, will we have a self-driving car or not, is way too simple. The better way to think about it is that there's a whole continuum of how much driving and assisting the car can do. I noticed that you're right next door to Toyota Research Institute. That's a total accident. I love the TRI folks, but yeah. Have you talked to Gil Pratt? Yeah, we're supposed to talk. It's kind of hilarious. So there's kind of the, I think it's a good counterpart to what Elon is doing. And hopefully they can be frank in what they think about each other, because I've heard both of them talk about it. But they're much more, you know, this is an assistive, a guardian angel that watches over you as opposed to try to do everything. I think there's some things like driving on a highway, you know, from LA to Phoenix, where it's mostly good weather, straight roads. That's close to a solved problem, let's face it. In other situations, you know, driving through the snow in Boston where the roads are kind of crazy, and most importantly, you have to make a lot of judgments about what the other driver's gonna do at these intersections that aren't really right angles and aren't very well described. It's more like game theory. Game theory. That's a much harder problem and requires understanding human motivations. So there's a continuum there of some places where the cars will work very well and others where it could probably take decades. What do you think about the Waymo? So you mentioned two companies that actually have cars on the road. There's the Waymo approach that's more like, we're not going to release anything until it's perfect, and we're gonna be very strict about the streets that we travel on, but it better be perfect. Yeah. Well, I'm smart enough to be humble and not try to get between. I know there's very bright people on both sides of the argument. I've talked to them, and they make convincing arguments to me about how careful they need to be and the social acceptance. Some people thought that when the first few people died from self-driving cars, that would shut down the industry, but it was more of a blip, actually. So that was interesting. Of course, there's still a concern that there could be setbacks if we do this wrong. Your listeners may be familiar with the different levels of self-driving, level one, two, three, four, five. I think Andrew Ng has convinced me that this idea of really focusing on level four, where you only go in areas that are well-mapped rather than just going out in the wild, is the way things are gonna evolve. But you can just keep expanding those areas where you've mapped things really well, where you really understand them, and eventually they all become interconnected. And that could be another way of progressing to make it more feasible over time. I mean, that's kind of like the Waymo approach, which is they just now released, I think just a day or two ago, a public, like anyone from the public in the Phoenix, Arizona, to, you can get a ride in a Waymo car with no person, no driver. Oh, they've taken away the safety driver? Oh yeah, for a while now, there's been no safety driver. Okay, because I mean, I've been following that one in particular, but I thought it was kind of funny about a year ago when they had the safety driver, and then they added a second safety driver because the first safety driver would fall asleep. I'm not sure they're going in the right direction with that. No, they've Waymo in particular done a really good job of that. They actually have a very interesting infrastructure of remote observation. So they're not controlling the vehicles remotely, but they're able to, it's like a customer service. They can, anytime, tune into the car. I bet they can probably remotely control it as well, but that's officially not the function that they release now. Yeah, I can see that being really, because I think the thing that's proven harder than maybe some of the early people expected was there's a long tail of weird exceptions. So you can deal with 90, 99, 99.99% of the cases, but then there's something that just never been seen before in the training data. And humans, more or less can work around that, although let me be clear and note, there are about 30,000 human fatalities just in the United States and maybe a million worldwide. So they're far from perfect. But I think people have higher expectations of machines, they wouldn't tolerate that level of death and damage from a machine. And so we have to do a lot better at dealing with those edge cases. And also the tricky thing that, if I have a criticism for the Waymo folks, there's such a huge focus on safety where people don't talk enough about creating products that people, that customers love, that human beings love using. It's very easy to create a thing that's safe at the extremes, but then nobody wants to get into it. Yeah, well, back to Elon, I think one of, part of his genius was with the electric cars. Before he came along, electric cars were all kind of underpowered, really light, and they were sort of wimpy cars that weren't fun. And the first thing he did was, he made a Roadster that went zero to 60 faster than just about any other car and went the other end. And I think that was a really wise marketing move as well as a wise technology move. Yeah, it's difficult to figure out what the right marketing move is for AI systems. That's always been, I think it requires guts and risk-taking, which is what Elon practices. I mean, to the chagrin of perhaps investors or whatever. It requires guts and risk-taking. It also requires rethinking what you're doing. I think way too many people are unimaginative, intellectually lazy, and when they take AI, they basically say, what are we doing now? How can we make a machine do the same thing? Maybe we'll save some costs, we'll have less labor. And yeah, it's not necessarily the worst thing in the world to do, but it's really not leading to a quantum change in the way you do things. When Jeff Bezos said, hey, we're gonna use the internet to change how bookstores work, and we're gonna use technology, he didn't go and say, okay, let's put a robot cashier where the human cashier is and leave everything else alone. That would have been a very lame way to automate a bookstore. He went from soup to nuts, said, let's just rethink it. We get rid of the physical bookstore. We have a warehouse, we have delivery, we have people order on a screen, and everything was reinvented. And that's been the story of these general-purpose technologies all through history. In my books, I write about electricity and how for 30 years, there was almost no productivity gain from the electrification of factories a century ago. Now, it's not because electricity's a wimpy, useless technology. We all know how awesome electricity is. It's because at first, they really didn't rethink the factories. It was only after they reinvented them, and we describe how in the book. Then you suddenly got a doubling and tripling of productivity growth. But it's the combination of the technology with the new business models, new business organization. That just takes a long time, and it takes more creativity than most people have. Can you maybe linger on electricity, because that's a fun one. Yeah, well, sure, I'll tell you what happened. Before electricity, there were basically steam engines or sometimes water wheels. And to power the machinery, you had to have pulleys and crankshafts. And you really can't make them too long, because they'll break the torsion. So all the equipment was kind of clustered around this one giant steam engine. You can't make small steam engines either, because of thermodynamics. So you have one giant steam engine, all the equipment clustered around it, multi-story. They'd have it vertical to minimize the distance, as well as horizontal. And then when they did electricity, they took out the steam engine, they got the biggest electric motor they could buy from General Electric or someone like that. And nothing much else changed. It took until a generation of managers retired or died, three years later, that people started thinking, wait, we don't have to do it that way. You can make electric motors, big, small, medium. You can put one with each piece of equipment. There's this big debate, if you read the management literature between what they call a group drive versus unit drive, where every machine would have its own motor. Well, once they did that, once they went to unit drive, those guys won the debate. Then you started having a new kind of factory, which is sometimes spread out over acres, single story, and each piece of equipment had its own motor. And most importantly, they weren't laid out based on who needed the most power. They were laid out based on what is the workflow of materials? Assembly line, let's have it go from this machine to that machine, to that machine. Once they rethought the factory that way, huge increases in productivity. It was just staggering. People like Paul David have documented this in their research papers. And I think that there's a, that is a lesson you see over and over. It happened when the steam engine changed manual production. It's happened with the computerization. People like Michael Hammer said, don't automate, obliterate. In each case, the big gains only came once smart entrepreneurs and managers basically reinvented their industries. I mean, one other interesting point about all that is that during that reinvention period, you often actually, not only don't see productivity growth, you can actually see a slipping back. Measured productivity actually falls. I just wrote a paper with Chad Severson and Daniel Rock called the Productivity J-Curve, which basically shows that in a lot of these cases, you have a downward dip before it goes up. And that downward dip is when everyone's trying to like reinvent things. And you could say that they're creating knowledge and intangible assets, but that doesn't show up on anyone's balance sheet. It doesn't show up in GDP. So it's as if they're doing nothing. Like take self-driving cars, we were just talking about it. There have been hundreds of billions of dollars spent developing self-driving cars. And basically no chauffeur has lost his job, no taxi driver. I guess I gotta check on the ones that- Big J-Curve. Yeah, so there's a bunch of spending and no real consumer benefit. Now, they're doing that in the belief, I think the justified belief, that they will get the upward part of the J-Curve and there will be some big returns. But in the short run, you're not seeing it. That's happening with a lot of other AI technologies, just as it happened with earlier general purpose technologies. And it's one of the reasons we're having relatively low productivity growth lately. As an economist, one of the things that disappoints me is that as eye-popping as these technologies are, you and I are both excited about some things they can do. The economic productivity statistics are kind of dismal. We actually, believe it or not, have had lower productivity growth in the past about 15 years than we did in the previous 15 years, in the 90s and early 2000s. And so that's not what you would have expected if these technologies were that much better. But I think we're in kind of a long J-Curve there. Personally, I'm optimistic. We'll start seeing the upward tick, maybe as soon as next year. But the past decade has been a bit disappointing if you thought there's a one-to-one relationship between cool technology and higher productivity. What would you place your biggest hope for productivity increases on? Because you kind of said at a high level AI, but if I were to think about what has been so revolutionary in the last 10 years, I would, 15 years, and thinking about the internet, I would say things like, hopefully I'm not saying anything ridiculous, but everything from Wikipedia to Twitter. So these kind of websites, not so much AI, but I would expect to see some kind of big productivity increases from just the connectivity between people and the access to more information. Yeah, well, that's another area I've done quite a bit of research on, actually, is these free goods like Wikipedia, Facebook, Twitter, Zoom. We're actually doing this in person, but almost everything else I do these days is online. The interesting thing about all those is most of them have a price of zero. What do you pay for Wikipedia? Maybe a little bit for the electrons to come to your house? Basically zero, right? Take a small pause and say, I donate to Wikipedia. Often you should too, because that makes it- Good for you, yeah. But what does that do, mean, for GDP? GDP is based on the price and quantity of all the goods, things bought and sold. If something has zero price, you know how much it contributes to GDP? To a first approximation, zero. So these digital goods that we're getting more and more of, we're spending more and more hours a day consuming stuff off of screens, little screens, big screens, that doesn't get priced into GDP. It's like they don't exist. That doesn't mean they don't create value. I get a lot of value from watching cat videos and reading Wikipedia articles and listening to podcasts, even if I don't pay for them. So we've got a mismatch there. Now, in fairness, economists, since Simon Kuznets invented GDP and productivity, all those statistics back in the 1930s, he recognized, he in fact said, this is not a measure of wellbeing, this is not a measure of welfare, it's a measure of production. But almost everybody has kind of forgotten that he said that, and they just use it. It's like, how well off are we? What was GDP last year? It was 2.3% growth or whatever. That is how much physical production, but it's not the value we're getting. We need a new set of statistics, and I'm working with some colleagues, Avi Kallis and others, to develop something we call GDP-B. GDP-B measures the benefits you get, not the cost. If you get benefit from Zoom or Wikipedia or Facebook, then that gets counted in GDP-B, even if you pay zero for it. So back to your original point, I think there is a lot of gain over the past decade in these digital goods that doesn't show up in GDP, doesn't show up in productivity. By the way, productivity is just defined as GDP divided by hours worked. So if you mismeasure GDP, you mismeasure productivity by the exact same amount. That's something we need to fix. I'm working with the statistical agencies to come up with a new set of metrics. And over the coming years, I think we'll see. We're not gonna do away with GDP. It's very useful, but we'll see a parallel set of accounts that measure the benefits. How difficult is it to get that B in the GDP-B? It's pretty hard. I mean, one of the reasons it hasn't been done before is that you can measure at the cash register what people pay for stuff, but how do you measure what they would have paid, like what the value is? That's a lot harder. How much is Wikipedia worth to you? That's what we have to answer. And to do that, what we do is we use online experiments. We do massive online choice experiments. We ask hundreds of thousands, now millions of people, to do lots of sort of A-B tests. How much would I have to pay you to give up Wikipedia for a month? How much would I have to pay you to stop using your phone? And in some cases, it's hypothetical. In other cases, we actually enforce it, which is kind of expensive. Like we pay somebody $30 to stop using Facebook, and we see if they'll do it. And some people will give it up for $10. Some people won't give it up even if you give them $100. And then you get a whole demand curve. You get to see what all the different prices are and how much value different people get. And not surprisingly, different people have different values. We find that women tend to value Facebook more than men. Old people tend to value it a little bit more than young people. That's interesting. I think young people maybe know about other networks that I don't know the name of that are better than Facebook. And so you get to see these patterns, but every person's individual. And then if you add up all those numbers, you start getting an estimate of the value. Okay, first of all, that's brilliant. Is this work that will soon eventually be published? Yeah, well, there's a version of it in the Proceedings of the National Academy of Sciences about, I think we call it Massive Online Choice Experiments. I should remember the title, but it's on my website. So yeah, we have some more papers coming out on it, but the first one is already out. You know, it's kind of a fascinating mystery that Twitter, Facebook, like all these social networks are free. And it seems like almost none of them except for YouTube have experimented with removing ads for money. Can you like, do you understand that from both economics and the product perspective? Yeah, it's something that, you know, so I teach a course on digital business models. So I used to at MIT, at Stanford, I'm not quite sure. I'm not teaching until next spring. I'm still thinking what my course is gonna be. But there are a lot of different business models. And when you have something that has zero marginal cost, there's a lot of forces, especially if there's any kind of competition that push prices down to zero. But you can have ad supported systems, you can bundle things together, you can have volunteer, you mentioned Wikipedia, there's donations. And I think economists underestimate the power of volunteerism and donations. You know, National Public Radio. Actually, how do you do this podcast? How is this, what's the revenue model? There's sponsors at the beginning, and then, and people. The funny thing is, I tell people they can, it's very, I tell them the timestamp. So if you wanna skip the sponsors, you're free. But it's funny that a bunch of people, so I read the advertisement, and a bunch of people enjoy reading it. And it's- Well, they may learn something from it. And also, from the advertiser's perspective, those are people who are actually interested, you know? Like, I mean, the example I sometimes give, like, I bought a car recently, and all of a sudden, all the car ads were like, interesting to me. Exactly. And then, like, now that I have the car, like, I sort of zone out on it. But that's fine. The car companies, they don't really wanna be advertising to me if I'm not gonna buy their product. So there are a lot of these different revenue models. And, you know, it's a little complicated, but the economic theory has to do with what the shape of the demand curve is, when it's better to monetize it with charging people versus when you're better off doing advertising. I mean, in short, when the demand curve is relatively flat and wide, like generic news and things like that, then you tend to do better with advertising. If it's a good that's only useful to a small number of people, but they're willing to pay a lot, they have a very high value for it, then you, advertising isn't gonna work as well, and you're better off charging for it. Both of them have some inefficiencies. And then when you get into targeting, and you get into these other revenue models, it gets more complicated. But there's some economic theory on it. I also think, to be frank, there's just a lot of experimentation that's needed, because sometimes things are a little counterintuitive, especially when you get into what are called two-sided networks or platform effects, where you may grow the market on one side and harvest the revenue on the other side. Facebook tries to get more and more users, and then they harvest the revenue from advertising. So that's another way of kind of thinking about it. Is it strange to you that they haven't experimented? Well, they are experimenting. So they are doing some experiments about what the willingness is for people to pay. I think that when they do the math, it's gonna work out that they still are better off with an advertising-driven model. What about a mix? Like this is what YouTube is, right? It's you allow the person to decide, the customer to decide exactly which model they prefer. No, that can work really well. And newspapers, of course, have known this for a long time. The Wall Street Journal, The New York Times, they have subscription revenue, they also have advertising revenue. And that can definitely work. Online, it's a lot easier to have a dial that's much more personalized, and everybody can kind of roll their own mix. And I could imagine having a little slider about how much advertising you want or are willing to take. And if it's done right, and it's incentive-compatible, it could be a win-win where both the content provider and the consumer are better off than they would have been before. Yeah, you know, the done right part is a really good point. Like with Jeff Bezos and the single-click purchase on Amazon, the frictionless effort there. If I could just rant for a second about The Wall Street Journal and all the newspapers you mentioned, is I have to click so many times to subscribe to them that I literally don't subscribe just because of the number of times I have to click. I'm totally with you. I don't understand why so many companies make it so hard. I mean, another example is when you buy a new iPhone or a new computer, whatever, I feel like, okay, I'm gonna lose an afternoon just loading up and getting all my stuff back. And for a lot of us, that's more of a deterrent than the price. And if they could make it painless, we'd give them a lot more money. So I'm hoping somebody listening is working on making it more painless for us to buy your products. If we could just like linger a little bit on the social network thing, because there's this Netflix social dilemma. Yeah, no, I saw that. With Tristan Harris and company, yeah. And people's data, it's really sensitive and social networks are at the core, arguably, of many of societal tension and some of the most important things happening in society. So it feels like it's important to get this right, both from a business model perspective and just like a trust perspective. I mean, it just still feels like, I know there's experimentation going on. It still feels like everyone is afraid to try different business models, like really try. Well, I'm worried that people are afraid to try different business models. I'm also worried that some of the business models may lead them to bad choices. And Danny Kahneman talks about system one and system two, sort of like our reptilian brain that reacts quickly to what we see. See something interesting, we click on it, we retweet it versus our system two, our frontal cortex that's supposed to be more careful and rational that really doesn't make as many decisions as it should. I think there's a tendency for a lot of these social networks to really exploit system one, our quick instant reaction, make it so we just click on stuff and pass it on and not really think carefully about it. And that system, it tends to be driven by sex, violence, disgust, anger, fear, these relatively primitive kinds of emotions. Maybe they're important for a lot of purposes, but they're not a great way to organize a society. And most importantly, when you think about this huge, amazing information infrastructure we've had that's connected billions of brains across the globe, not just we can all access information, but we can all contribute to it and share it. Arguably the most important thing that that network should do is favor truth over falsehoods. And the way it's been designed, not necessarily intentionally, is exactly the opposite. My MIT colleagues, Aral and Deb Roy and others at MIT did a terrific paper on the cover of Science. And when they document what we all feared, which is that lies spread faster than truth on social networks, they looked at a bunch of tweets and retweets, and they found that false information was more likely to spread further, faster to more people. And why was that? It's not because people like lies. It's because people like things that are shocking, amazing. Can you believe this? Something that is not mundane, not that something everybody else already knew. And what are the most unbelievable things? Well, lies. And so if you want to find something unbelievable, it's a lot easier to do that if you're not constrained by the truth. So they found that the emotional valence of false information was just much higher. It was more likely to be shocking and therefore more likely to be spread. Another interesting thing was that that wasn't necessarily driven by the algorithms. I know that there is some evidence, Zeynep Tufekci and others have pointed out on YouTube some of the algorithms unintentionally were tuned to amplify more extremist content. But in the study of Twitter that Sinan and Deb and others did they found that even if you took out all the bots and all the automated tweets, you still had lies spreading significantly faster. It's just the problems with ourselves that we just can't resist passing on the salacious content. But I also blame the platforms because there's different ways you can design a platform. You can design a platform in a way that makes it easy to spread lies and to retweet and spread things on, or you can kind of put some friction on that and try to favor truth. I had dinner with Jimmy Wales once, the guy who helped found Wikipedia. And he convinced me that, look, you can make some design choices, whether it's at Facebook, at Twitter, at Wikipedia or Reddit, whatever. And depending on how you make those choices, you're more likely or less likely to have false news. Create a little bit of friction, like you said. Yeah. You know, that's the, and sorry if I'm- It could be friction, it could be speeding the truth, you know, either way. But, and I don't totally understand- Speeding the truth, I love it. Yeah, yeah. Amplifying it and giving it more credit. And, you know, like in academia, which is far, far from perfect, but you know, when someone has an important discovery it tends to get more cited and people kind of look to it more and sort of, it tends to get amplified a little bit. So you could try to do that too. I don't know what the silver bullet is, but the meta point is that if we spend time thinking about it, we can amplify truth over falsehoods. And I'm disappointed in the heads of these social networks that they haven't been as successful or maybe haven't tried as hard to amplify truth. And part of it, going back to what we said earlier, is, you know, these revenue models may push them more towards growing fast, spreading information rapidly, getting lots of users, which isn't the same thing as finding truth. Yeah. I mean, implicit in what you're saying now is a hopeful message that with platforms we can take a step towards greater and greater popularity of truth. But the more cynical view is that what the last few years have revealed is that there's a lot of money to be made in dismantling even the idea of truth, that nothing is true. And as a thought experiment, I've been thinking about if it's possible that our future will have, like the idea of truth is something we won't even have. Do you think it's possible, like in the future, that everything is on the table in terms of truth and we're just swimming in this kind of digital economy where ideas are just little toys that are not at all connected to reality? Yeah, I think that's definitely possible. I'm not a technological determinist, so I don't think that's inevitable. I don't think it's inevitable that it doesn't happen. I mean, the thing that I've come away with every time I do these studies, and I emphasize it in my books and elsewhere, is that technology doesn't shape our destiny. We shape our destiny. So just by us having this conversation, I hope that your audience is gonna take it upon themselves as they design their products and they think about it, they use products as they manage companies, how can they make conscious decisions to favor truth over falsehoods, favor the better kinds of societies, and not abdicate and say, well, we just build the tools. I think there was a saying that, was it the German scientists, when they were working on the missiles in late World War II, they said, well, our job is to make the missiles go up. Where they come down, that's someone else's department. And that's obviously not the, I think it's obvious that's not the right attitude that technologists should have, that engineers should have. They should be very conscious about what the implications are. And if we think carefully about it, we can avoid the kind of world that you just described where truth is all relative. There are going to be people who benefit from a world of where people don't check facts and where truth is relative and popularity or fame or money is orthogonal to truth. But one of the reasons I suspect that we've had so much progress over the past few hundred years is the invention of the scientific method, which is a really powerful tool or meta tool for finding truth and favoring things that are true versus things that are false. If they don't pass the scientific method, they're less likely to be true. And that has, the societies and the people and the organizations that embrace that have done a lot better than the ones who haven't. And so I'm hoping that people keep that in mind and continue to try to embrace not just the truth, but methods that lead to the truth. So maybe on a more personal question, if one were to try to build a competitor to Twitter, what would you advise? Is there, I mean, the bigger, the meta question, is that the right way to improve systems? Yeah, no, I think that the underlying premise behind Twitter and all these networks is amazing that we can communicate with each other. And I use it a lot. There's a sub part of Twitter called econ Twitter, where we economists tweet to each other and talk about new papers. Something came out in NBER, the National Bureau of Economic Research, and we share about it. People critique it. I think it's been a godsend because it's really sped up the scientific process, if you can call economics scientific. Does it get divisive in that little? Sometimes, yeah, sure. Sometimes it does. It can also be done in nasty ways and there's the bad parts. But the good parts are great because you just speed up that clock speed of learning about things. Instead of like in the old, old days, waiting to read in a journal, or the not so old days when you'd see it posted on a website and you'd read it. Now on Twitter, people will distill it down and there's a real art to getting to the essence of things. So that's been great. But it certainly, we all know that Twitter can be a cesspool of misinformation. And like I just said, unfortunately, misinformation tends to spread faster on Twitter than truth. And there are a lot of people who are very vulnerable to it. I'm sure I've been fooled at times. There are agents, whether from Russia or from political groups or others that explicitly create efforts at misinformation and efforts at getting people to hate each other. Or even more important lately I've discovered is nut picking. You know the idea of nut picking? No, what's that? It's a good term. Nut picking is when you find like an extreme nut case on the other side and then you amplify them and make it seem like that's typical of the other side. So you're not literally lying. You're taking some idiot, you know, ranting on the subway or just, you know, whether they're in the KKK or Antifa or whatever, they're just, and you, normally nobody would pay attention to this guy, like 12 people would see him and it'd be the end. Instead with video or whatever, you get tens of millions of people say it. And I've seen this, you know, I look at it, I'm like, I get angry. I'm like, I can't believe that person did such things. It's so terrible. Let me tell all my friends about this terrible person. And it's a great way to generate division. I talked to a friend who studied Russian misinformation campaigns and they're very clever about literally being on both sides of some of these debates. They would have some people pretend to be part of BLM. Some people pretend to be white nationalists and they would be throwing epithets at each other, saying crazy things at each other. And they're literally playing both sides of it, but their goal wasn't for one or the other to win. It was for everybody to get be hating and distrusting everyone else. So these tools can definitely be used for that. And they are being used for that. It's been super destructive for our democracy and our society. And the people who run these platforms, I think have a social responsibility, a moral and ethical personal responsibility to do a better job and to shut that stuff down. Well, I don't know if you can shut it down, but to design them in a way that, you know, as I said earlier, favors truth over falsehoods and favors positive types of communication versus destructive ones. And just like you said, it's also on us. I try to be all about love and compassion, empathy on Twitter. I mean, one of the things, not picking is a fascinating term. One of the things that people do that's I think even more dangerous is not picking applied to individual statements of good people. So basically worst case analysis in computer science is taking sometimes out of context, but sometimes in context, a statement, one statement by a person. Like I've been, because I've been reading the rise and fall of the third Reich, I've often talked about Hitler on this podcast with folks and it is so easy. That is really dangerous. But I'm all leaning in, I'm 100%. Because, well, it's actually a safer place than people realize, because it's history and history in long form is actually very fascinating to think about. And it's, but I could see how that could be taken totally out of context and it's very worrying. About these digital infrastructures, not just the semi things, but they're sort of permanent. So anything you say at some point, someone can go back and find something you said three years ago, perhaps jokingly, perhaps not. Maybe you're just wrong and you made them, and like that becomes, they can use that to define you if they have no intent. And we all need to be a little more forgiving. I mean, somewhere in my 20s, I told my, I was going through all my different friends and I was like, you know, every one of them has at least like one nutty opinion. And I was like, there's like nobody who's like completely, except me, of course. But I'm sure they thought that about me too. And so you just kind of like learn to be a little bit tolerant that like, okay, there's just, you know. Yeah, I wonder who the responsibility lays on there. Like, I think ultimately it's about leadership. Like the previous president, Barack Obama has been, I think, quite eloquent at walking this very difficult line of talking about cancel culture. But it's difficult, it takes skill. Because you say the wrong thing and you piss off a lot of people. And so you have to do it well. But then also the platform, the technology is, should slow down, create friction and spreading this kind of nut picking in all its forms. Absolutely, no, and your point that we have to like learn over time how to manage it. I mean, we can't put it all on the platform and say, you guys design it. Because if we're idiots about using it, nobody can design a platform that withstands that. And every new technology people learn it's dangerous. You know, when someone invented fire, it's great cooking and everything, but then somebody burned himself. And then you had to like learn how to like avoid, maybe somebody invented a fire extinguisher later. So you kind of like figure out ways of working around these technologies. Someone invented seat belts, et cetera. And that's certainly true with all the new digital technologies that we have to figure out, not just technologies that protect us, but ways of using them that emphasize that are more likely to be successful than dangerous. So you've written quite a bit about how artificial intelligence might change our world. How do you think, if we look forward again, it's impossible to predict the future, but if we look at trends from the past and we try to predict what's gonna happen in the rest of the 21st century, how do you think AI will change our world? That's a big question. You know, I'm mostly a techno-optimist. I'm not at the extreme, you know, the singularity is near end of the spectrum, but I do think that we're likely in for some significantly improved living standards, some really important progress, even just the technologies that are already kind of like in the can that haven't diffused. You know, when I talked earlier about the J curve, it could take 10, 20, 30 years for an existing technology to have the kind of profound effects. And when I look at whether it's, you know, vision systems, voice recognition, problem-solving systems, even if nothing new got invented, we would have a few decades of progress. So I'm excited about that. And I think that's gonna lead to us being wealthier, healthier, I mean, the healthcare is probably one of the applications I'm most excited about. So that's good news. I don't think we're gonna have the end of work anytime soon. There's just too many things that machines still can't do. When I look around the world and think of whether it's childcare or healthcare, cleaning the environment, interacting with people, scientific work, artistic creativity, these are things that for now, machines aren't able to do nearly as well as humans, even just something as mundane as, you know, folding laundry or whatever. And many of these, I think are gonna be years or decades before machines catch up. You know, I may be surprised on some of them, but overall, I think there's plenty of work for humans to do. There's plenty of problems in society that need the human touch. So we'll have to repurpose. We'll have to, as machines are able to do some tasks, people are gonna have to reskill and move into other areas. And that's probably what's gonna be going on for the next, you know, 10, 20, 30 years or more, kind of big restructuring of society. We'll get wealthier and people will have to do new skills. Now, if you turn the dial further, I don't know, 50 or 100 years into the future, then, you know, maybe all bets are off. Then it's possible that machines will be able to do most of what people do. You know, say one or 200 years, I think it's even likely. And at that point, then we're more in the sort of abundance economy. Then we're in a world where there's really little for the humans can do economically better than machines other than be human. And, you know, that will take a transition as well, kind of more of a transition of how we get meaning in life and what our values are. But shame on us if we screw that up. I mean, that should be like great, great news. And it kind of saddens me that some people see that as like a big problem. I think it should be wonderful if people have all the health and material things that they need and can focus on loving each other and discussing philosophy and playing and doing all the other things that don't require work. Do you think you'll be surprised to see what the 20, like if we were to travel in time, a hundred years into the future, do you think you'll be able to, like if I gave you a month to like talk to people, no, like let's say a week, would you be able to understand what the hell is going on? You mean if I was there for a week? Yeah, if you were there for a week. A hundred years in the future? Yeah. So like, so I'll give you one thought experiment is like, isn't it possible that we're all living in virtual reality by then? Yeah, no, I think that's very possible. You know, I've played around with some of those VR headsets and they're not great, but I mean, the average person spends many waking hours staring at screens right now. You know, they're kind of low res compared to what they could be in 30 or 50 years, but certainly games and why not, any other interactions could be done with VR and that would be a pretty different world and we'd all, you know, in some ways be as rich as we wanted you know, we could have castles and we could be traveling anywhere we want and it could obviously be multisensory. So that would be possible, you know, and of course, there's people, you know, you've had Elon Musk on and others, you know, there are people, Nick Bostrom, you know, makes the simulation argument that maybe we're already there. We're already there. So, but in general, or do you not even think about in this kind of way, you're self-critically thinking how good are you as an economist at predicting what the future looks like? Do you have a- Well, it starts getting, I mean, I feel reasonably comfortable the next, you know, five, 10, 20 years in terms of that path. When you start getting truly superhuman artificial intelligence, kind of by definition, I'll be able to think of a lot of things that I couldn't have thought of and create a world that I couldn't even imagine and so I'm not sure I can predict what that world is going to be like. One thing that AI researchers, AI safety researchers worry about is what's called the alignment problem. When an AI is that powerful, then they can do all sorts of things. We really hope that their values are aligned with our values and it's even tricky to find what our values are. I mean, first off, we all have different values and secondly, maybe if we were smarter, we would have better values. Like, you know, I like to think that we have better values than we did in 1860 or in, you know, the year 200 BC on a lot of dimensions, things that we consider barbaric today and it may be that if I thought about it more deeply, I would also be morally evolved. Maybe I'd be a vegetarian or do other things that right now, whether my future self would consider kind of immoral. So that's a tricky problem, getting the AI to do what we want, assuming it's even a friendly AI. I mean, I should probably mention, there's a non-trivial other branch where we destroy ourselves, right? I mean, there's a lot of exponentially improving technologies that could be ferociously destructive, whether it's in nanotechnology or biotech and weaponized viruses, AI and other things that- Nuclear weapons. Nuclear weapons, of course. The old school technology. Yeah, good old nuclear weapons that could be devastating or even existential and new things yet to be invented. So that's a branch that, you know, I think is pretty significant and there are those who think that one of the reasons we haven't been contacted by other civilizations, right, is that once you get to a certain level of complexity in technology, there's just too many ways to go wrong. There's a lot of ways to blow yourself up and people, or I should say species, end up falling into one of those traps. The great filter. The great filter. I mean, there's an optimistic view of that. If there is literally no intelligent life out there in the universe, or at least in our galaxy, that means that we've passed at least one of the great filters or some of the great filters that we survived. Yeah, no, I think it's Robin Hanson has a good way of, maybe others, they have a good way of thinking about this, that if there are no other intelligence creatures out there that we've been able to detect, one possibility is that there's a filter ahead of us and when you get a little more advanced, maybe in 100 or 1,000 or 10,000 years, things just get destroyed for some reason. The other one is the great filters behind us. That'll be good, is that most planets don't even evolve life, or if they don't evolve life, they don't evolve intelligent life. Maybe we've gotten past that, and so now maybe we're on the good side of the great filter. So, if we sort of rewind back and look at the thing where we could say something a little bit more comfortably at five years and 10 years out, you've written about jobs and the impact on sort of our economy and the jobs in terms of artificial intelligence that it might have. It's a fascinating question, what kind of jobs are safe, what kind of jobs are not? Can you maybe speak to your intuition about how we should think about AI changing the landscape of work? Sure, absolutely. Well, this is a really important question because I think we're very far from artificial general intelligence, which is AI that can just do the full breadth of what humans can do, but we do have human level or superhuman level narrow intelligence, narrow artificial intelligence. And obviously my calculator can do math a lot better than I can, and there's a lot of other things machines can do better than I can. So, which is which? We actually set out to address that question. With Tom Mitchell, I wrote a paper called "'What Can Machine Learning Do?' that was in science, and we went and interviewed a whole bunch of AI experts and kind of synthesized what they thought machine learning was good at and wasn't good at, and we came up with, we called a rubric, basically a set of questions you can ask about any task that will tell you whether it's likely to score high or low on suitability for machine learning. And then we've applied that to a bunch of tasks in the economy. In fact, there's a data set of all the tasks in the US economy, believe it or not, it's called O-Net. The US government put it together, part of Bureau of Labor Statistics, and they divide the economy into about 970 occupations, like bus driver, economist, primary school teacher, radiologist, and then for each one of them, they describe which tasks need to be done. Like for radiologists, there are 27 distinct tasks. So we went through all those tasks to see whether or not a machine could do them. And what we found, interestingly, was- Brilliant study, by the way, that's so awesome. Yeah, thank you. So what we found was that there was no occupation in our data set where machine learning just ran the table and did everything. And there was almost no occupation where machine learning didn't have a significant ability to do things. Like take radiologists, a lot of people I hear saying, it's the end of radiology, and one of the 27 tasks is read medical images, really important one, like it's kind of a core job. And machines have basically gotten as good or better than radiologists. There's just an article in Nature last week, but they've been publishing them for the past few years, showing that machine learning can do as well as humans on many kinds of diagnostic imaging tasks. But other things radiologists do, they sometimes administer conscious sedation, they sometimes do physical exams, they have to synthesize the results and explain to the other doctors or to the patients. In all those categories, machine learning isn't really up to snuff yet. So that job, we're going to see a lot of restructuring. Parts of the job, they'll hand over to machines, others, humans will do more of. That's been more or less the pattern all of them. So to oversimplify a bit, we're going to see a lot of restructuring, reorganization of work. And it's real, going to be a great time, it is a great time for smart entrepreneurs and managers to do that reinvention of work. Not going to see mass unemployment. To get more specifically to your question, the kinds of tasks that machines tend to be good at are a lot of routine problem solving, mapping inputs X into outputs Y. If you have a lot of data on the Xs and the Ys, the inputs and the outputs, you can do that kind of mapping and find the relationships. They tend to not be very good at, even now, fine motor control and dexterity, emotional intelligence and human interactions, and thinking outside the box, creative work. If you give it a well-structured task, machines can be very good at it, but even asking the right questions, that's hard. There's a quote that Andrew McAfee and I use in our book, Second Machine Age. Apparently, Pablo Picasso was shown an early computer and he came away kind of unimpressed. He goes, well, I don't see all the fusses. All that does is answer questions. And to him, the interesting thing was asking the questions. Yeah. Try to replace me, GPT-3. I dare you. Although some people think I'm a robot. You have this cool plot that shows, I just remember where economists land, where I think the X-axis is the income, and then the Y-axis is, I guess, aggregating the information of how replaceable the job is. Or I think there's an index. But there's a suitability for machine learning index. Exactly. So we have all 970 occupations on that chart. It's a cool plot. And there's scatters, and all four corners have some occupations. But there is a definite pattern, which is the lower wage occupations tend to have more tasks that are suitable for machine learning, like cashiers. I mean, anyone who's gone to a supermarket or CVS knows that they not only read barcodes, but they can recognize an apple and an orange. And a lot of things that cashiers, humans used to be needed for. At the other end of the spectrum, there are some jobs like airline pilot that are among the highest paid in our economy. But also a lot of them are suitable for machine learning. A lot of those tasks are. And then, yeah, you mentioned economists. I couldn't help peeking at those. And they're paid a fair amount, maybe not as much as some of us think they should be. But they have some tasks that are suitable for machine learning, but for now, at least, most of the tasks that economists do didn't end up being in that category. And I should say, I didn't create that data. We just took the analysis, and that's what came out of it. And over time, that scatterplot will be updated as the technology improves. But it was just interesting to see the pattern there. And it is a little troubling insofar as if you just take the technology as it is today, it's likely to worsen income inequality on a lot of dimensions. So on this topic of the effect of AI on our landscape of work, one of the people that have been speaking about it in the public domain, public discourse, is the presidential candidate, Andrew Yang. What are your thoughts about Andrew? What are your thoughts about UBI, that universal basic income, that he made one of the core ideas? By the way, he has hundreds of ideas about everything. It's kind of interesting. But what are your thoughts about him, and what are your thoughts about UBI? Let me answer the question about his broader approach first. I mean, I just love that. He's really thoughtful, analytical. I agree with his values. So that's awesome. And he read my book and mentions it sometimes. It makes me even more excited. And the thing that he really made the centerpiece of his campaign was UBI. And I was originally kind of a fan of it. And then as I studied it more, I became less of a fan, although I'm beginning to come back a little bit. So let me tell you a little bit of my evolution. You know, as an economist, we have by looking at the problem of people not having enough income, and the simplest thing is, well, why don't we write them a check? Problem solved. But then I talked to my sociologist friends, and they really convinced me that just writing a check doesn't really get at the core values. You know, Voltaire once said that work solves three great ills, boredom, vice, and need. And you know, you can deal with the need thing by writing a check, but people need a sense of meaning, they need something to do. And when, you know, say steel workers or coal miners lost their jobs and were just given checks, alcoholism, depression, divorce, all those social indicators, drug use, all went way up. People just weren't happy just sitting around collecting a check. Maybe it's part of the way they were raised, maybe it's something innate in people that they need to feel wanted and needed. So it's not as simple as just writing people a check. You need to also give them a way to have a sense of purpose. And that was important to me. And the second thing is that, as I mentioned earlier, you know, we are far from the end of work. You know, I don't buy the idea that there's just like not enough work to be done. I see, like our cities need to be cleaned up. And robots can't do most of that. You know, we need to have better childcare, we need better healthcare, we need to take care of people who are mentally ill or older, we need to repair our roads. There's so much work that require at least partly, maybe entirely a human component. So rather than like write all these people off, let's find a way to repurpose them and keep them engaged. Now that said, I would like to see more buying power from people who are sort of at the bottom end of the spectrum the economy has been designed and evolved in a way that's I think very unfair to a lot of hardworking people. I see super hardworking people who aren't really seeing their wages grow over the past 20, 30 years, while some other people who have been super smart and or super lucky have made billions or hundreds of billions. And I don't think they need those hundreds of billions to have the right incentives to invent things. I think if you talk to almost any of them, as I have, they don't think that they need an extra $10 billion to do what they're doing. Most of them probably would love to do it for only a billion or maybe for nothing. First for nothing, many of them, yeah. I mean, you know, an interesting point to make is like, do we think that Bill Gates would have founded Microsoft if tax rates were 70%? Well, we know he would have because they were tax rates of 70% when he founded it. So I don't think that's as big a deterrent and we could provide more buying power to people. My own favorite tool is the earned income tax credit, which is basically a way of supplementing income of people who have jobs and giving employers an incentive to hire even more people. The minimum wage can discourage employment but the earned income tax credit encourages employment by supplementing people's wages. You know, if the employer can only afford to pay him $10 for a task, the rest of us kick in another five or $10 and bring their wages up to 15 or 20 total. And then they have more buying power than entrepreneurs are thinking, how can we cater to them? How can we make products for them? And it becomes a self-reinforcing system where people are better off. Andrew Ng and I had a good discussion where he suggested instead of a universal basic income, he suggested, or instead of an unconditional basic income, how about a conditional basic income where the condition is you learn some new skills, we need to reskill our workforce, so let's make it easier for people to find ways to get those skills and get rewarded for doing them. And that's kind of a neat idea as well. That's really interesting. So I mean, one of the questions, one of the dreams of UBI is that you provide some little safety net while you retrain, while you learn a new skill. But I think, I guess you're speaking to the intuition that that doesn't always, like there needs to be some incentive to reskill, to train, to learn a new thing. I think it helps. I mean, there are lots of self-motivated people, but there are also people that maybe need a little guidance or help. And I think it's a really hard question for someone who is losing a job in one area to know what is the new area I should be learning skills in, and we could provide a much better set of tools and platforms that map to, okay, here's a set of skills you already have. Here's something that's in demand. Let's create a path for you to go from where you are to where you need to be. So I'm a total, how do I put it nicely about myself? I'm totally clueless about the economy. It's not totally true, but pretty good approximation. If you were to try to fix our tax system, and, or maybe from another side, if there's fundamental problems in taxation or some fundamental problems about our economy, what would you try to fix? What would you try to speak to? You know, I definitely think our whole tax system, our political and economic system has gotten more and more screwed up over the past 20, 30 years. I don't think it's that hard to make headway in improving it. I don't think we need to totally reinvent stuff. A lot of it is what I've been elsewhere with Andy and others called economics 101. You know, there's just some basic principles that have worked really well in the 20th century that we sort of forgot, you know, in terms of investing in education, investing in infrastructure, welcoming immigrants, having a tax system that was more progressive and fair. At one point, tax rates were, on top incomes were significantly higher and they've come down a lot to the point where, in many cases, they're lower now than they are for poorer people. So, and we could do things like earned income tax credit. To get a little more wonky, I'd like to see more Pigouvian taxes. What that means is you tax things that are bad instead of things that are good. So right now we tax labor, we tax capital, which is unfortunate because one of the basic principles of economics, if you tax something, you tend to get less of it. So, you know, right now there's still work to be done and still capital to be invested in, but instead we should be taxing things like pollution and congestion. And if we did that, we would have less pollution. So a carbon tax is, you know, almost every economist would say it's a no-brainer, whether they're Republican or Democrat, Greg Mankiw, who's head of George Bush's Council of Economic Advisers, or Dick Shmalensy, who is another Republican economist, would agree, and of course, a lot of Democratic economists agree as well. If we taxed carbon, we could raise hundreds of billions of dollars. We could take that money and redistribute it through an earned income tax credit or other things so that overall our tax system would become more progressive. We could tax congestion. One of the things that kills me as an economist is every time I sit in a traffic jam, I know that it's completely unnecessary. This is complete wasted time. You could just visualize the cost and productivity. All the, exactly, because they are taking costs from me and all the people around me, and if they charged a congestion tax, they would take that same amount of money and people would, it would streamline the roads, like when you're in Singapore, the traffic just flows because they have a congestion tax. They listen to economists. They invite me and others to go talk to them. And then I'd still be paying. I'd be paying a congestion tax instead of paying my time, but that money would now be available for healthcare, be available for infrastructure, or be available just to give to people so they could buy food or whatever. So it's just, it saddens me when, you know, when you're sitting in a traffic jam, it's like taxing me and then taking that money and dumping it in the ocean, just like destroying it. So there are a lot of things like that that economists, and I'm not like doing anything radical here. Most, you know, good economists would, I probably agree with me point by point on these things, and we could do those things and our whole economy would become much more efficient. It'd become fair, invest in R&D and research, which is close to a free lunch is what we have. My erstwhile MIT colleague, Bob Sola, got the Nobel Prize, not yesterday, but 30 years ago, for describing that most improvements in living standards come from tech progress. And Paul Romer later got a Nobel Prize for noting that investments in R&D and human capital can speed the rate of tech progress. So if we do that, then we'll be healthier and wealthier. Yeah, from an economics perspective, I remember taking an undergrad econ, you mentioned econ 101. It seemed from all the plots I saw that R&D is an obvious, that's close to a free lunch as we have. It seemed like obvious that we should do more research. It is. Like what, like, there's no- Well, we should do basic research. I mean, so let me just be clear. It'd be great if everybody did more research. And I would make this interpretation, applied development versus basic research. So applied development, like, you know, how do we get this self-driving car feature to work better in the Tesla? That's great for private companies because they can capture the value from that. If they make a better self-driving car system, they can sell cars that are more valuable and then make money. So there's an incentive. That there's not a big problem there. And smart companies, Amazon, Tesla, and others are investing in it. The problem is with basic research, like coming up with core basic ideas, whether it's in nuclear fusion or artificial intelligence or biotech. There, if someone invents something, it's very hard for them to capture the benefits from it. It's shared by everybody, which is great in a way, but it means that they're not gonna have the incentives to put as much effort into it. There you need, it's a classic public good. There you need the government to be involved in it. And the US government used to be investing much more in R&D, but we have slashed that part of the government really foolishly, and we're all poorer, significantly poorer as a result. Growth rates are down. We're not having the kind of scientific progress we used to have. It's been sort of a short-term, eating the seed, corn, whatever metaphor you wanna use, where people grab some money, put it in their pockets today, but five, 10, 20 years later, they're a lot poorer than they otherwise would have been. So we're living through a pandemic right now globally in the United States. From an economics perspective, how do you think this pandemic will change the world? It's been remarkable, and it's horrible how many people have suffered, the amount of death, the economic destruction. It's also striking just the amount of change in work that I've seen. In the last 20 weeks, I've seen more change than there were in the previous 20 years. There's been nothing like it since probably the World War II mobilization in terms of reorganizing our economy. The most obvious one is the shift to remote work, and I and many other people stopped going into the office and teaching my students in person. I did a study on this with a bunch of colleagues at MIT and elsewhere, and what we found was that before the pandemic, in the beginning of 2020, about one in six, a little over 15% of Americans were working remotely. When the pandemic hit, that grew steadily and hit 50%, roughly half of Americans working at home, so a complete transformation. And of course, it wasn't even, it wasn't like everybody did it. If you're an information worker, a professional, if you work mainly with data, then you're much more likely to work at home. If you're a manufacturing worker, working with other people or physical things, then it wasn't so easy to work at home, and instead, those people were much more likely to become laid off or unemployed. So it's been something that's had very disparate effects on different parts of the workforce. Do you think it's gonna be sticky in a sense that after vaccine comes out and the economy reopens, do you think remote work will continue? That's a great question. My hypothesis is yes, a lot of it will. Of course, some of it will go back, but a surprising amount of it will stay. I personally, for instance, I moved my seminars, my academic seminars to Zoom, and I was surprised how well it worked. So it works. Yeah, I mean, obviously, we were able to reach a much broader audience. So we have people tuning in from Europe and other countries, just all over the United States for that matter. I also actually found that it would, in many ways, is more egalitarian. We use the chat feature and other tools, and grad students and others who might've been a little shy about speaking up, we now kind of have more of ability for lots of voices, and they're answering each other's questions, so you kind of get parallel. Like if someone had a question about some of the data or a reference or whatever, then someone else in the chat would answer it. And the whole thing just became like a higher bandwidth, higher quality thing. So I thought that was kind of interesting. I think a lot of people are discovering that these tools that, thanks to technologists, have been developed over the past decade, they're a lot more powerful than we thought. I mean, of all the terrible things we've seen with COVID and the real failure of many of our institutions that I thought would work better, one area that's been a bright spot is our technologies. Bandwidth has held up pretty well, and all of our email and other tools have just scaled up kind of gracefully. So that's been a plus. Economists call this question of whether it'll go back a hysteresis. The question is like when you boil an egg, after it gets cold again, it stays hard. And I think that we're gonna have a fair amount of hysteresis in the economy. We're gonna move to this new, we have moved to a new remote work system, and it's not gonna snap all the way back to where it was before. One of the things that worries me is that the people with lots of followers on Twitter and people with voices, people that can, voices that can be magnified by reporters and all that kind of stuff, are the people that fall into this category that we were referring to just now, where they can still function and be successful with remote work. And then there is a kind of quiet suffering of what feels like millions of people whose jobs are disturbed profoundly by this pandemic, but they don't have many followers on Twitter. What do we, and again, I apologize, but I've been reading the rise and fall of the Third Reich, and there's a connection to the depression on the American side. There's a deep, complicated connection to how suffering can turn into forces that potentially change the world in destructive ways. So it's something I worry about, is what is this suffering going to materialize itself in five, 10 years? Is that something you worry about, think about? It's like the center of what I worry about. And let me break it down to two parts. There's a moral and ethical aspect to it. We need to relieve this suffering. I mean, I share the values of I think most Americans. We like to see shared prosperity or most people on the planet. And we would like to see people not falling behind, and they have fallen behind, not just due to COVID, but in the previous couple of decades, a median income has barely moved, depending on how you measure it. And the incomes of the top 1% have skyrocketed. And part of that is due to the ways technology has been used. Part of this has been due to, frankly, our political system has continually shifted more wealth into those people who have the powerful interest. So there's just, I think, a moral imperative to do a better job. And ultimately, we're all going to be wealthier if more people can contribute, more people have the wherewithal. But the second thing is that there's a real political risk. I'm not a political scientist, but you don't have to be one, I think, to see how a lot of people are really upset with their getting a raw deal, and they are going to, they wanna smash the system in different ways, in 2016 and 2018. And now, I think there are a lot of people who are looking at the political system, and they feel like it's not working for them, and they just wanna do something radical. Unfortunately, demagogues have harnessed that in a way that is pretty destructive to the country. And an analogy I see is what happened with trade. Almost every economist thinks that free trade is a good thing, that when two people voluntarily exchange, almost by definition, they're both better off if it's voluntary. And so generally, trade is a good thing. But they also recognize that trade can lead to uneven effects, that there can be winners and losers in some of the people who didn't have the skills to compete with somebody else, or didn't have other assets. And so trade can shift prices in ways that are averse to some people. So there's a formula that economists have, which is that you have free trade, but then you compensate the people who are hurt. And free trade makes the pie bigger. And since the pie is bigger, it's possible for everyone to be better off. You can make the winners better off, but you can also compensate those who don't win, and so they end up being better off as well. What happened was that we didn't fulfill that promise. We did have some more increased free trade in the 80s and 90s, but we didn't compensate the people who were hurt. And so they felt like the people in power reneged on the bargain, and I think they did. And so then there's a backlash against trade. And now both political parties, but especially Trump and company, have really pushed back against free trade. Ultimately, that's bad for the country. Ultimately, that's bad for living standards, but in a way I can understand that people felt they were betrayed. Technology has a lot of similar characteristics. Technology can make us all better off. It makes the pie bigger. It creates wealth and health, but it can also be uneven. Not everyone automatically benefits. It's possible for some people, even a majority of people, to get left behind while a small group benefits. What most economists would say, well, let's make the pie bigger, but let's make sure we adjust the system so we compensate the people who are hurt. And since the pie is bigger, we can make the rich richer, we can make the middle class richer, we can make the poor richer. Mathematically, everyone could be better off. But again, we're not doing that. And again, people are saying, this isn't working for us. And again, instead of fixing the distribution, a lot of people are beginning to say, hey, technology sucks, we've got to stop it. Let's throw rocks at the Google bus. Let's blow it up. Let's blow it up. And there were the Luddites almost exactly 200 years ago who smashed the looms and the spinning machines because they felt like those machines weren't helping them. We have a real imperative, not just to do the morally right thing, but to do the thing that is gonna save the country, which is make sure that we create not just prosperity, but shared prosperity. So you've been at MIT for over 30 years, I think. Don't tell anyone how old I am. Yeah, that's true, that's true. And you're now moved to Stanford. I'm gonna try not to say anything about how great MIT is. What's that move been like? What, it's East Coast to West Coast. Well, MIT is great. MIT has been very good to me, continues to be very good to me. It's an amazing place. I continue to have so many amazing friends and colleagues there. I'm very fortunate to have been able to spend a lot of time at MIT. Stanford's also amazing. And part of what attracted me out here was not just the weather, but also Silicon Valley, let's face it, is really more of the epicenter of the technological revolution. And I wanna be close to the people who are inventing AI and elsewhere. A lot of it is being invested at MIT for that matter in Europe and China and elsewhere, India. But being a little closer to some of the key technologists was something that was important to me. And it may be shallow, but I also do enjoy the good weather. I felt a little ripped off when I came here a couple of months ago, and immediately there are the fires, and my eyes were burning, the sky was orange, and there's the heat waves. And so it wasn't exactly what I'd been promised, but fingers crossed it'll get back to better. So maybe on a brief aside, there's been some criticism of academia and universities and different avenues. And I, as a person who's gotten to enjoy universities from the pure playground of ideas that it can be, always kind of try to find the words to tell people that these are magical places. Is there something that you can speak to that is beautiful or powerful about universities? Well, sure. I mean, first off, I mean, economists have this concept called revealed preference. You can ask people what they say, or you can watch what they do. And so obviously by reveal preferences, I love academia. I could be doing lots of other things, but it's something I enjoy a lot. And I think the word magical is exactly right. At least it is for me. I do what I love. Hopefully my dean won't be listening, but I would do this for free. It's just what I like to do. I like to do research. I love to have conversations like this with you and with my students, with my fellow colleagues. I love being around the smartest people I can find and learning something from them and having them challenge me. And that just gives me joy. And every day I find something new and exciting to work on. And a university environment is really filled with other people who feel that way. And so I feel very fortunate to be part of it. And I'm lucky that I'm in a society where I can actually get paid for it and put food on the table while doing the stuff that I really love. And I hope someday everybody can have jobs that are like that. And I appreciate that it's not necessarily easy for everybody to have a job that they both love and also they get paid for. So there are things that don't go well in academia, but by and large, I think it's a kinder, gentler version of a lot of the world. We sort of cut each other a little slack on things like, on just a lot of things. Of course, there's harsh debates and discussions about things and some petty politics here and there. I personally, I try to stay away from most of that sort of politics. It's not my thing. And so it doesn't affect me most of the time, sometimes a little bit maybe. But being able to pull together something, we have the digital economy lab. We get all these brilliant grad students and undergraduates and postdocs that are just doing stuff that I learned from. And every one of them has some aspect of what they're doing that's just, I couldn't even understand. It's like way, way more brilliant. And that's really, to me, actually, I really enjoy that, being in a room with lots of other smart people. And Stanford has made it very easy to attract those people. I just say, I'm gonna do a seminar or whatever, and the people come, they come and wanna work with me. We get funding, we get data sets, and it's come together real nicely. And the rest is just fun. It's fun, yeah. And we feel like we're working on important problems, you know, and we're doing things that, you know, I think are first order in terms of what's important in the world, and that's very satisfying to me. Maybe a bit of a fun question. What three books, technical, fiction, philosophical, you've enjoyed, had a big impact in your life? Well, I guess I go back to my teen years, and I read Sid Arthur, which is a philosophical book, and kind of helps keep me centered. By Herman Hest. Yeah, by Herman Hest, exactly. Don't get too wrapped up in material things or other things, and just sort of try to find peace on things. A book that actually influenced me a lot in terms of my career was called The Worldly Philosophers by Robert Heilbrenner. It's actually about economists. It goes through a series of different economists, written in a very lively form. And it probably sounds boring, but it did describe, whether it's Adam Smith, or Karl Marx, or John Maynard Keynes and each of them, sort of what their key insights were, but also kind of their personalities. And I think that's one of the reasons I became an economist, was just understanding how they grappled with the big questions of the world. So would you recommend it as a good whirlwind overview of the history of economics? Yeah, yeah, I think that's exactly right. It kind of takes you through the different things, and, you know, so you can understand how they reach, thinking some of the strengths and weaknesses. I mean, probably it's a little out of date now, it needs to be updated a bit, but, you know, you could at least look through the first couple hundred years of economics, which is not a bad place to start. More recently, I mean, a book I really enjoyed is by my friend and colleague Max Tegmark, called Life 3.0. You should have him on your podcast if you haven't already. It was episode number one. Oh my God. And he's back, he'll be back, he'll be back soon. Yeah, no, he's terrific. I love the way his brain works, and he makes you think about profound things. He's got such a joyful approach to life, and so that's been a great book, and I learn a lot from it, I think everybody, but he explains it in a way, even though he's so brilliant, that everyone can understand, that I can understand. You know, that's three, but let me mention maybe one or two others. I mean, I recently read More From Less by my sometimes co-author, Andrew McAfee. It made me optimistic about how we can continue to have rising living standards while living more lightly on the planet. In fact, because of higher living standards, because of technology, because of digitization that I mentioned, we don't have to have as big an impact on the planet, and that's a great story to tell, and he documents it very carefully. You know, a personal kind of self-help book that I found kind of useful, people, is Atomic Habits. I think it's, what's his name, James Clear. Yeah, James Clear. He's just, yeah, it's a good name, because he writes very clearly, and you know, most of the sentences I read in that book, I was like, yeah, I know that, but it just really helps to have somebody like remind you and tell you, and kind of just reinforce it, and that's what helps. So build habits in your life that you hope to have a positive impact, and don't have to make it big things. It could be just tiny little things. Exactly, I mean, the word atomic, it's a little bit of a pun, I think he says. You know, one, atomic means they're really small, and you take these little things, but also like atomic power, it can have like, you know, big impact. That's funny, yeah. The biggest ridiculous question, especially to ask an economist, but also a human being, what's the meaning of life? I hope you've gotten the answer to that from somebody. I think we're all still working on that one. But what is it? You know, I actually learned a lot from my son, Luke, and he's 19 now, but he's always loved philosophy, and he reads way more sophisticated philosophy than I do. I once took him to Oxford, and he spent the whole time like pulling all these obscure books down and reading them, and a couple of years ago, we had this argument, and he was trying to convince me that hedonism was the ultimate meaning of life, just pleasure seeking. Well, how old was he at the time? 17. Okay. But he made a really good intellectual argument for it too. Of course. But it just didn't strike me as right, and I think that while I am kind of a utilitarian, like I do think we should do the grace, good for the grace number, that's just too shallow, and I think I've convinced myself that real happiness doesn't come from seeking pleasure. It's kind of a little, it's ironic. Like if you really focus on being happy, I think it doesn't work. You gotta like be doing something bigger. I think the analogy I sometimes use is, you know, when you look at a dim star in the sky, if you look right at it, it kind of disappears, but you have to look a little to the side, and then the parts of your retina that are better at absorbing light can pick it up better. It's the same thing with happiness. I think you need to sort of find something other goal, something, some meaning in life, and that ultimately makes you happier than if you go squarely at just pleasure. And so for me, you know, the kind of research I do that I think is trying to change the world, make the world a better place, and I'm not like an evolutionary psychologist, but my guess is that our brains are wired not just for pleasure, but we're social animals, and we're wired to like help others, and ultimately, you know, that's something that's really deeply rooted in our psyche, and if we do help others, if we do, or at least feel like we're helping others, you know, our reward systems kick in, and we end up being more deeply satisfied than if we just do something selfish and shallow. Beautifully put. I don't think there's a better way to end it. Eric, you were one of the people when I first showed up at MIT that made me proud to be at MIT, so it's so sad that you're not at Stanford, but I'm sure you'll do wonderful things at Stanford as well. I can't wait till future books, and people should definitely read the other books. Well, thank you so much, and I think we're all part of the invisible college, as we call it. You know, we're all part of this intellectual and human community where we all can learn from each other. It doesn't really matter physically where we are so much anymore. Beautiful, thanks for talking today. My pleasure. Thanks for listening to this conversation with Eric Ben-Josselin, and thank you to our sponsors. Insera Watches, the maker of classy, well-performing watches. Four Sigmatic, the maker of delicious mushroom coffee. ExpressVPN, the VPN I've used for many years to protect my privacy on the internet. And Cash App, the app I use to send money to friends. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with Five Stars on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from Albert Einstein. It has become appallingly obvious that our technology has exceeded our humanity. Thank you for listening, and hope to see you next time.

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Garry Kasparov: Chess, Deep Blue, AI, and Putin | Lex Fridman Podcast #46

The following is a conversation with Garry Kasparov. He is considered by many to be the greatest chess player of all time. From 1986 until his retirement in 2005, he dominated the chess world, ranking world number one for most of those 19 years. While he has many historical matches against human chess players, in the long arc of history, he may be remembered for his match against the machine, IBM's Deep Blue. His initial victories and eventual loss to Deep Blue captivated the imagination of the world, of what role artificial intelligence systems may play in our civilization's future. That excitement inspired an entire generation of AI researchers, including myself, to get into the field. Garry is also a pro-democracy political thinker and leader, a fearless human rights activist, and author of several books, including How Life Imitates Chess, which is a book on strategy and decision making, Winter is Coming, which is a book articulating his opposition to the Putin regime, and Deep Thinking, which is a book on the role of both artificial intelligence and human intelligence in defining our future. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Garry Kasparov. As perhaps the greatest chess player of all time, when you look introspectively at your psychology throughout your career, what was the bigger motivator, the love of winning or the hatred of losing? Tough question. I have to confess, I never heard it before, which is, again, congratulations, it's quite an accomplishment. Losing was always painful. For me, it was almost like a physical pain because I knew that if I lost the game, it's just because I made a mistake. I always believed that the result of the game had to be decided by the quality of my play. Okay, you may say it sounds arrogant, but it helped me to move forward because I always knew that there was room for improvement. Was there the fear of the mistake? Actually, fear of mistake guarantees mistakes. And the difference between top players and the very top is that it's the ability to make a decision without predictable consequences. You don't know what's happening. It's just intuitively, I can go this way or that way. And there are always hesitations. People are like, you are just at the crossroad. You can go right, you can go left, you can go straight, you can turn and go back. And the consequences are just very uncertain. You have certain ideas what happens on the right or on the left, or just if you go straight, but it's not enough to make well-calculated choice. And when you play chess at the very top, it's about your inner strength. So I can make this decision, I will stand firm, and I'm not going to waste my time because I have full confidence that I will go through. Now, going back to the original question is, I would say neither. It's just it's love for winning, hate for losing. They were important elements, psychological elements. But the key element, it's the, I would say the driving force was always my passion for making a difference. It's just, I can move forward and I can always enjoy not just playing, but creating something new. Creating something new. How do you think about that? It's just finding new ideas in the openings, some original plan in the middle game. Actually, that helped me to make the transition from the game of chess where I was on the very top to another life where I knew I would not be number one. I would not be necessarily on the top, but I could still be very active and productive by my ability to make the difference by influencing people, say, joining the democratic movement in Russia or talking to people about human-machine relations. There's so many things where I knew my influence may not be as decisive as in chess, but still strong enough to help people to make their choices. So you can still create something new that makes a difference in the world outside of chess. But wait, you've kind of painted a beautiful picture of your motivations to chess, to create something new, to look for those moments of some brilliant new ideas. But were you haunted by something? So you make it seem like to be at the level you're at, you can get away without having demons, without having fears, without being driven by some of the darker forces. I mean, you sound almost religious, you know, darker forces, spiritual demons. I mean, do you have a call for a priest? That's what I'm guessing. Yeah. Now, let's go back to these crucial chess moments where I had to make big decisions. As I said, it was all about my belief from very early days that I can make all the difference by playing well or by making mistakes. So yes, I always had an opponent across the chessboard, opposite me. But no matter how strong the opponent was, whether just an ordinary player or another world champion like Anatoly Karpov, having all respect for my opponent, I still believe that it's up to me to make the difference. And I knew I was not invincible. I made mistakes. I made some blunders. And with age, I made more blunders. So I knew it. But it's still very much for me to be decisive factor in the game. I mean, even now, look, my latest chess experience was horrible. I mean, I played Fabio Caruana, this number two, number two, number three player in the world these days. We play this 960 with the so-called Fischer random chess, reshuffling pieces. Yeah, I lost very badly, but it's because I made mistakes. I mean, I had so many winning positions. I mean, 15 years ago, I would have crushed him. And while I lost, I was not so much upset. I mean, I know, as I said in the interview, I can fight any opponent, but not my biological clock. So it's fighting time is always a losing proposition. But even today at age 56, I knew that I could play great game. I couldn't finish it because I didn't have enough energy or just I couldn't have the same level of concentration. But in a number of games where I completely outplayed one of the top players in the world, I mean, it gave me a certain amount of pleasure. That is, even today, I haven't lost my touch. Not the same, you know, okay, the jaws are not as strong and the teeth are not as sharp, but I could get him just, you know, almost, you know, on the ropes. You still got it. Still got it. And it's, you know, and it's, I think it's my wife said it well. I mean, she said, look, Gary, it's somehow, it's not you just fighting your biological clock. It's just, you know, maybe it's a signal because, you know, the goddess of chess, since you spoke, right? Yeah. The goddess of chess, Keisha, maybe she didn't want you to win because, you know, if you could beat number two, number three player in the world, I mean, that's one of the top players who just recently played a world championship match. If you could beat him, that would be really bad for the game of chess. But just what people will say, oh, look, the game of chess, you know, it's not making any progress. The game is just, you know, it's totally devalued because, look, the guy coming out of retirement, you know, just, you know, winning games. Maybe that was good for chess, not good for you, but it's, look, I've been following your logic. We should always look for, you know, demons, you know, superior forces and other things that could, you know, if not dominate our lives, but somehow, you know, play a significant role in the outcome. Yeah. So the goddess of chess had to send a message. Yeah. Okay. So Gary, you should do something else. Time. Now for a question that you have heard before, but give me a chance. You've dominated the chess world for 20 years, even still got it. Is there a moment you said you always look to create something new? Is there games or moments where you're especially proud of in terms of your brilliance of a new creative move? You've talked about Mikhail Tal as somebody who was aggressive and creative chess player in your own game. Look, you mentioned Mikhail Tal. It's very aggressive, very sharp player, famous for his combinations and sacrifices, even called magician from Riga. So for his very unique style, but any world champion, you know, it's, yeah, was a creator. Some of them were so flamboyant and flash like Tal. Some of them were, you know, just, you know, less discerned at the chess board like Tigran Petrosyan, but every world champion, every top player brought something into the game of chess. And each contribution was priceless because it's not just about sacrifices. Of course, amateurs, they enjoy, you know, the brilliant games where pieces being sacrificed. It's all just, you know, it's all piece of hanging. And it's all of a sudden, you know, being material down, rook down or just, you know, queen down, the weaker side delivers the final blow and just, you know, mating opponent's king. But there are other kinds of beauty. I mean, it's a slow positional maneuvering, you know, looking for weaknesses and just gradually strangling your opponent and eventually delivering sort of a positional masterpiece. Yeah. So I think I made more difference in the game of chess than I could have imagined when I started playing. And the reason I thought it was time for me to leave was just, I mean, I knew that I was no longer in the position to bring the same kind of contribution, the same kind of new knowledge into the game. So, and going back, I could immediately look at my games against Anatoly Karpov. It's not just I won the match in 1985 and became world champion at age 22, but there were at least two games in that match. Of course, the last one, game 24, that was decisive game of the match, I won and became world champion. But also the way I won, it was a very sharp game and I found a unique maneuver that was absolutely new and it became some sort of just a typical now. Though just when the move was made on the board and put on display, a lot of people thought it was ugly. And another game, game 16 in the match, where I just also managed to outplay Karpov completely with black pieces, just paralyzing his entire army in its own camp. Technically or psychologically, it was a mix of both in game 16. Yeah, I think it was a big blow to Karpov. I think it was a big psychological victory for a number of reasons. One, the score was equal at a time and the world champion, by the rules, could retain his title in case of a tie. So, before game 16, we have nine games to go. And also it was some sort of a bluff because neither me nor Karpov saw the refutation of this opening idea. And I think it's just for Karpov, it was double blow because not that he lost the game, it was a triple blow. He lost the game, it was a brilliant game and I played impeccably after just this opening bluff. And then they discovered that it was a bluff. So, again, I didn't know, I was not bluffing. So, that's why it happens very often. Some ideas could be refuted. And it's just what I found out, and this is, again, going back to your spiritual theme is that you could spend a lot of time working. And when I say you could, it's in the 80s, in the 90s. It doesn't happen these days because everybody has a computer. You could immediately see if it works or it doesn't work. Machine shows your refutation in a split of a second. But many of our analysis in the 80s or in the 90s, they were not perfect simply because we're humans and you analyze the game, you look for some fresh ideas. And then just it happens that there was something that you missed because the level of concentration at the chessboard is different from one that when you analyze the game, just moving the pieces around. But somehow, if you spend a lot of time at the chessboard preparing, so in your studies, with your coaches, hours and hours and hours, and nothing of what you found had materialized on the chessboard. Somehow, these hours helped. I don't know why, always helped you. It's as if the amount of work you did could be transformed into some sort of spiritual energy that helped you to come up with other great ideas during the board. Again, even if there was no direct connection between your preparation and your victory in the game, there was always some sort of invisible connection between the amount of work you did, your dedication to actually to, and your passion to discover new ideas, and your ability during the game at the chessboard when the clock was ticking, we still had ticking clock, not digital, not digital clock at the time. So to come up with some brilliance. And I also can mention many games from the 90s. So obviously, all amateurs would pick up my game against Veselin Topalov in 1999 and V. Gonzay, again, because it was a brilliant game. The Black King traveled from its own camp to into White's camp across the entire board. It doesn't happen often, trust me, as you know, in the games of professional players, top professional players. So that's why visually, it was one of the most impressive victories. But I could bring to our attention many other games that were not so impressive for amateurs, not so beautiful, just sacrifice always beautiful, you sacrifice pieces. And then eventually you have so very few resources left, and you use them just to crush your opponent, basically, you have to make the king because you have almost nothing left at your disposal. But I, you know, I, up to the very end, get less and less, but still up to the very end, I always had games with some sort of, you know, interesting ideas and games that gave me great satisfaction. But I think it's what happened from 2005 up to these days was also a very, very big accomplishment, since, you know, I had to find myself to sort of relocate myself. Yeah, rechannel the creative energies. Exactly. And to find something where I feel comfortable, even confident that my participation still makes the difference. Beautifully put. So let me ask perhaps a silly question, but sticking on chess for just a little longer. Where do you put Magnus Carlsen, the current world champion in the list of all-time greats? In terms of style, moments of brilliance, consistency? It's a tricky question. You know, the moment you start ranking world champions, Yeah, you lose something? It's the, I think it's not fair because it's the, any new generation knows much more about the game than the previous one. So when people say, oh, Gary was the greatest, Fischer was the greatest, Magnus was the greatest, it disregards the fact that the great players of the past, whether Lasky or Capelplanc, Alokian, I mean, they knew so little about chess by today's standards. I mean, today, just any kid, you know, that spent a few years, you know, with his or her chess computer knows much more about the game simply just because you have access to this information. And it has been discovered generation after generation. We added more and more knowledge to the game of chess. It's about the gap between the world champion and the rest of the field. So it's the, now, if you look at the gap, then probably Fischer, you know, could be on top, but very short period of time, then you should also add a time factor. Yeah. I was on top, not as big as Fischer, but much longer. So, and also, unlike Fischer, I succeeded in beating next generation. Yeah. Here's the question. Yeah. Let's see if you still got the fire, speaking of the next generation, because you did succeed beating the next generation. Next, it's close. Okay. Anand, short, Anand, the sheer of, Kramnik is already 12 years younger. So that's a neck, that's, but still yet I, I competed with them and I just, I beat most of them and I was still dominant when I left at age 41. So back to Magnus. Magnus, I mean, consistency is phenomenal. The reason Magnus is, is on top and it's, seems unbeatable today. Magnus is, is a lethal combination of Fischer and Karpov, which is very, it's very unusual because Fischer style was very dynamic, just fighting to the last point, I mean, just using every resource available. Karpov was very different. It's just, he had an unparalleled ability to use the, every piece with a maximum effect, just its minimal resources always produce maximum effect. So now imagine that you merge these two styles. So it is, it's, it's like, you know, it's squeezing every stone for a drop of water, but, but doing it, you know, just, you know, for 50, 60, 70, 80 moves. I mean, Magnus could go on as long as Fischer with all his passion and energy, and at the same time being as meticulous and, and, and, and, and deadly as, as, as Karpov by just, you know, using every little advantage. So, and he has good, you know, very good health. It's important. I mean, physical conditions are, by the way, very important. So a lot of people don't recognize it. There are later studies shows that chess players burn thousands of calories during the game. So that puts him on the top of this field of the world champions. But again, it's, it's the discussion that is, I saw recently in internet, whether Garry Kasparov of his peak, let's say late eighties, could beat Magnus Carlsen today. I mean, it's totally irrelevant because Garry Kasparov in 1989, okay, played great chess, but still I knew very little about chess compared to Magnus Carlsen in 2019, who, by the way, learned from me as well. So that's why, yeah, I'm extremely cautious in making any judgment that involves, you know, time gaps. You ask, you know, soccer fans. So who is your favorite, Pelé, Maradona or Messi? Yeah. Who's your favorite? Messi. Messi. Why? Because... Maybe Maradona, maybe. No, because you're younger, but that's simple. Your instinctive answer is correct because you saw, you didn't see Maradona in action. I saw all of them in action. So that's why, but since, you know, when I was, you know, just following it, you know, just it's Pelé and Maradona, they were just, you know, they were big stars and it's Messi's already just, I was gradually losing interest in other things. So I remember Pelé in 1970, the final match, Brazil-Italy. So that's the first World Cup soccer I watched. So that's the, and actually my answer when I just, you know, because I was asked this question as well. So I say that it's just, while it's impossible to make a choice, I would still probably go with Maradona for a simple reason. The Brazilian team in 1970 could have won without Pelé. It was absolutely great. Still could have won, maybe, but it is, the Argentinian team in 1986 without Maradona would not be unified. So this is, and Messi, he still hasn't won a title. That's, that's, could argue for that for an hour, but you could say, if you ask Maradona, if you look in his eyes, especially let's say Garry Kasparov in 1989, he would have said, I was sure as hell would beat Magnus Carlsen. Yeah, just simply because- The confidence, the fire. Simply because, again, it's just, they saw me in action. So this, again, it's the age factor is important. Therefore, with the passion and energy and being equipped with all modern ideas, but again, then you make a very just important assumption that you could empower Garry Kasparov in 89 with all ideas that have been accumulated over 30 years. That would not be Garry Kasparov, that would be someone else. Because again, I belong to 1989. I was way ahead of the field and I beat Karpov several times in the world championship matches and I crossed 2,800, which by the way, if you look at the, in rating, which is just, it's, even today, so this is the rating that I retire. So this is, it's still, it's just, it's a top two, two, three. So that's, that's Karwan and Dink, it's about the same rating now. And I crossed 2,800 in 1990. We're just, you look at the inflation. When I crossed 2,800 in 1990, there was only one player in 2,700 category, Anatoly Karpov. Now we had more than 50. So just, when you see this, so if you add inflation, so I think my 2,851, it could probably, could be more valuable as Magnus 2,882, which was his highest rating. But anyway, again, too many hypotheticals. You're lost to IBM DBlue in 1997. In my eyes, that is one of the most seminal moments in the history. Again, I apologize for being romanticizing the notion, but in the history of our civilization, because humans, as a civilization, for centuries saw chess as, you know, the peak of what man can accomplish, of intellectual mastery, right? And that moment when a machine could beat a human being was inspiring to just an entire, anyone who cares about science, innovation, an entire generation of AI researchers. And yet, to you that loss, at least if reading your face, seemed like a tragedy, extremely painful, like you said, physically painful, why? When you look back at your psychology of that loss, why was it so painful? Were you not able to see the seminal nature of that moment? Or was that exactly why it was that painful? As I already said, losing was painful, physically painful. And the match I lost in 1997 was not the first match I lost to a machine. It was the first match I lost, period. That's... Oh, wow. Oh, wow. Right. That makes all the difference to me. First time I lost. Now, I lost, and the reason I was so angry that I just, I had suspicions that my loss was not just the result of my bad play. So, though I played quite poorly, just when you started looking at the games today, I made tons of mistakes. But I had all reasons to believe that there were other factors that had nothing to do with the game of chess. And that's why I was angry. But look, it was 22 years ago. It's more than the bridge. We can analyze this match and this is with everything you said. I agree with probably one exception. Is that considering chess as the sort of, as a pinnacle of intellectual activities, was our mistake. Because we just thought, oh, it's a game of the highest intellect. And it's just, you have to be so intelligent. And you could see things that the ordinary mortals could not see. It's a game. And all machines had to do in this game is just to make fewer mistakes, not to solve the game. Because the game cannot be solved. I mean, according to Koval Shannan, the number of legal moves is 10 to the 46th power. Too many zeros, just for any computer to finish the job, you know, in the next few billion years. But it doesn't have to. It's all about making fewer mistakes. And I think that's this match actually. And what's happened afterwards with other games, with Go, with Shogi, with video games. It's a demonstration that it's the machines will always beat humans in what I call closed systems. The moment you build a closed system, no matter how the system is called, chess, Go, Shogi, Dota, machines will prevail simply because they will bring down number of mistakes. Machines don't have to solve it. They just have to, the way they outplay us, it's not by just being more intelligent. It's just by doing something else. But eventually, it's just, it's capitalizing on our mistakes. And I think that's the way it's capitalizing on our mistakes. When you look at the chess machines ratings today, and compare this to Magnus Carlsen, it's the same as comparing Ferrari to Usain Bolt. The gap is, I mean, by chess standards is insane. 34, 3,500 to 2,800, 2,850 on Magnus. It's like difference between Magnus and an ordinary player from an open international tournament. It's not because machine understanding is better than Magnus Carlsen, but simply because it's steady. Machine has steady hand. And I think that is what we have to learn from 1997 experience, and from further encounters with computers and sort of the current state of affairs with AlphaZero, beating other machines. The idea that we can compete with computers in computers in so-called intellectual fields, it was wrong from the very beginning. By the way, the 1997 match was not the first victory of machines over- Over grandmasters. Over grandmasters. No, actually, I played against first decent chess computers from late 80s. So, I played with the prototype of Deep Blue called Deep Thought in 1989, two rapid chess games in New York. I won handily both games. We played against new chess engines like Fritz and other programs. And then it was Israeli program Junior that appeared in 1995. Right, right, right. I remember. Yeah. So, there were several programs. I lost a few games in Blitz. I lost one match against the computer chess engine in 1994, rapid chess. So, I lost one game to Deep Blue in 1996 match, the match I won. Some people tend to forget about it that I won the first match. Yes. But we made a very important psychological mistake thinking that the reason we lost Blitz matches, five minutes games, the reason we lost some of the rapid chess matches, 25 minutes chess, because we didn't have enough time. If you play a longer match, we will not make the same mistake. Nonsense. So, yeah, we had more time, but we still make mistakes. And machine also has more time. And machines will always be steady and consistent compared to humans' instabilities and inconsistencies. And today we are at the point where, yes, nobody talks about humans playing against machines. Now, machines can offer handicap to top players and still you know, will be favored. I think we're just learning that it's no longer human versus machines. It's about human working with machines. That's what I recognized in 1998, just after leaking my wounds and spending one year and just, you know, ruminating so what's happened in this match. And I knew that though we still could play against the machines. I had two more matches in 2003, playing both deep free and deep junior. Both matches ended as a tie. Though these machines were not weaker, at least, probably stronger than deep blue. And by the way, today, chess app on your mobile phone is probably stronger than deep blue. I'm not speaking about chess engines that are so much superior. And by the way, when you analyze games we played against deep blue in 1997 on your chess engine, they'll be laughing. And it also shows that's how chess changed because chess commentators, they'll look at some of our games like game four, game five, brilliant idea. Now you ask Stockfish, you ask Houdini, you ask Commodore, all the leading chess engines. Within 30 seconds, they will show you how many mistakes both Gary and deep blue made in the game that was trumpeted as a great chess match in 1997. Well, okay. So you've made an interesting, if you can untangle that comment. So now in retrospect, it was a mistake to see chess as the peak of human intellect. Nevertheless, that was done for centuries. So- By the way, in Europe, because you move to the far East, they will go, they had- Right, but games, games. Again, some of the games like board games. Yeah, I agree. So if I push back a little bit, so now you say that, okay, but it was a mistake to see chess as the epitome. And then now there's other things maybe like language, like conversation, like some of the things that in your view is still way out of reach of computers, but inside humans. Do you think, can you talk about what those things might be? And do you think just like chess that might fall soon with the same set of approaches, if you look at alpha zero, the same kind of learning approaches as the machines grow in size? No, no, it's not about growing in size. It's about, again, it's about understanding the difference between closed system and open-ended system. So you think that key difference, so the board games are closed in terms of the rules, the actions, the state space, everything is just constrained. You think once you open it, the machines are lost? Not lost, but again, the effectiveness is very different because machine does not understand the moment it's reaching territory of diminishing returns. To put it in a different way, machine doesn't know how to ask right questions. It can ask questions, but it will never tell you which questions are relevant. So it's like about the, it's a direction. So I think it's in human-machine relations we have to consider our role. And many people feel uncomfortable that the territory that belongs to us is shrinking. I'm saying, so what? Eventually we'll belong to the last few decimal points, but it's like having a very powerful gun and all you can do there is slightly alter the direction of the bullet, maybe 0.1 degree of this angle. But that means a mile away, 10 meters of target. So that's, we have to recognize that is a certain unique human qualities that machines in a foreseeable future will not be able to reproduce. And the effectiveness of this cooperation, collaboration depends on our understanding what exactly we can bring into the game. So the greatest danger is when we try to interfere with machine superior knowledge. So that's why I always say that sometimes you'd rather have, by reading this pictures in radiology, you may probably prefer an experienced nurse than, rather than having top professor, because she will not try to interfere with machines understanding. So it's very important to know that if machines knows how to do better things in 95%, 96% of territory, we should not touch it because it's happened. It's like in chess, recognize, they do it better. See where we can make the difference. You mentioned AlphaZero. I mean, AlphaZero, it's actually a first step into what you may call AI, because everything that's being called AI today, it's just, it's one or another variation of what Claude Shannon characterized as a brute force. It's a type A machine, whether it's Deep Blue, whether it's Watson, and all these things, the modern technologies that are being trumpeted as AI, it's still brute force. It's the, all they do, it's they do optimization. It's this, they are, they keep improving the way to process human generated data. Now, AlphaZero is the first step towards machine produced knowledge, which is, by the way, it's quite ironic that the first company that championed that was IBM. Oh, it's in backgammon. Interesting. Yes. You just, you should, you should, you should look at IBM. It's a new gammon. It's the, it's the scientist, he's still working at IBM. They had an early nineties. It's the, it's the, it's the program that played in all the AlphaZero types. So just trying to come up with own strategies, but because of success of Deep Blue, this project had been not abandoned, but just, it wasn't, it was put on calls. And now we just, it's, it's, it's, it's, it's, everybody talks about, about this, the machines generated knowledge. So as revolutionary, and it is, but there's still, you know, many open-ended questions. Yes. AlphaZero generates its own data. Many ideas that AlphaZero generated in chess were quite intriguing. So I, I, I looked at these games with, not just with interest, but with, you know, it's, it was quite exciting to learn how machine could actually, you know, juggle all the pieces and just play positions with a broken material balance, sacrificing material, always being ahead of other programs, you know, one or two moves ahead by, by foreseeing the consequences, not over calculating because machines, other machines were at least as powerful in calculating, but it's having this unique knowledge based on discovered patterns. After playing 60 million games. Almost something that feels like intuition. Exactly. But there's one problem. Now, a simple question. If, if AlphaZero faces superior point, let's say another powerful computer accompanied by a human who could help just to discover certain problems, because I already, I look at many AlphaZero games. I visited their lab, you know, spoke to Demis Kasabis at his team. And I, I know there's certain weaknesses there. Now, if these weaknesses are exposed, then the question is how many games will it take for AlphaZero to correct it? The answer is hundreds of thousands. Even if it keeps losing, it's this, because the whole system is based. So it's now, imagine, so this is, you can have a human by just making a few tweaks. So humans are still more flexible. And, and as long as we recognize what is, what is our role, where we can play sort of, so the most valuable part in this collaboration. So it's, it will help us to understand what are the next steps in human machine collaboration. Beautifully put. So let's talk about the thing that machines certainly don't know how to do yet, which is morality. Machines and morality. It's another question that, you know, just it's, it's, it's being asked all the time these days. And I, I think it's another phantom that is haunting a general public because it's just being fed with this, you know, illusions is that how can we avoid machines, you know, having bias, being prejudices. You cannot, because it's like looking in the mirror and complaining about what you see. If you have certain bias in the society, machine will, will just follow it. It's just, it's, it's, you know, you look at the mirror, you don't like what you see there. You can, you know, you can break it, you can try to distort it, or you can try to actually change something. Just by yourself. By yourself. Yes. So it's, it's very important to understand is this, is that you cannot expect machines to, to improve the yields of our society. And moreover, machines will simply, you know, just, you know, amplify. Yes. Yeah. But the thing is, people are more comfortable with other people doing injustice, with, with being biased. We're not comfortable with machines having the same kind of bias. So that's a, that's an interesting standard that we play some machines with autonomous vehicles. They have to be much safer with automated systems. Of course, of course, they're much safer. Statistically, they're much safer than, than. It's not of course. Why would they, it's not of course. It's, it's not given. Autonomous vehicles, you have to work really hard to make them safer. I, I, I think it just, it goes without saying, is the, the outcome of the, of this, I wouldn't call it competition, but comparison is very clear. But the problem is not about being, you know, safer. It's the 40,000 people or so every year died in car accidents in the United States. And it's, it's statistics. One accident with, with autonomous vehicle and it's front page of a newspaper. Yes. So it's, it's, again, it's about psychological. So it's, while people, you know, kill each other in car accidents because they make mistakes, they make more mistakes. For me, it's, it's, it's not a question. Of course, we make more mistakes because we're human. Yes. Machines also, and by the way, no machine will ever reach a hundred percent perfection. That's another, that's another important fake story that, that, that, that is being fed to the public. If machine doesn't reach a hundred percent performance is not safe. No. All you can ask any computer, whether it's, you know, playing chess or, or doing the stock market calculations or driving your autonomous vehicle, it's to make fewer mistakes. And yes, I know it's not, you know, it's not easy for us to accept because, ah, if, you know, if you have two humans, you know, colliding in their cars, okay, it's like, if one of, one of these cars is autonomous vehicle. And by the way, even if it's human's fault, terrible. How could you allow a machine to, to, to, to run without a driver at the wheel? So, you know, let's linger that for a second, that double standard, the way you felt with your first loss against Deep Blue, were you treating the machine differently than you would have a human? So what do you think about that difference between the way we see machines and humans? No, it's the, at that time, you know, for me, it was a match and that's why I was angry because I believe that the match was not, you know, fairly organized. So it's, it's, ah, definitely there weren't fair advantages for, for IBM and I want to play there another match, like a rubber match. So your anger or displeasure was aimed more like at the humans behind IBM versus the actual pure algorithm. Yes, absolutely, absolutely. Look, I mean, I, I knew at the time, and by the way, I was, objectively speaking, I was stronger at that time. So that's, that probably added to my anger because I knew I could beat the machine. Yeah. Yeah, so that's, and that's the, and that's, I lost, and I knew I was not well prepared. So, because they, I have to give them credit, they did some good work, ah, from 1996 and I, but I still could beat the, beat the machine. So I made too many mistakes. Also, this is the whole, it's this, the publicity around the match. So I, I underestimated the effect, you know, just it's, and, and being called the, you know, the, the, the brain's last stand, you know, it's okay. No, no, no pressure. Okay. Well, let me ask. Ah, so I was born also in the Soviet Union. What lessons do you draw from the rise and fall of the Soviet Union in the 20th century? When you just look at this nation that is now look, pushing forward into what Russia is. If you look at the long arc of history of the 20th century, what do we take away? What do we take away from that? I think the lesson of history is clear. Ah, undemocratic systems, totalitarian regimes, systems that are based on controlling their citizens and just, ah, every aspect of their life, not offering opportunities to, for private initiative, central planning systems, they doomed. They just, you know, they, they cannot be driving force for innovation. So they, in, in the history timeline, I mean, they could cause certain, you know, distortion of, of, of, ah, the concept of progress. Ah, they, by the way, they may call themselves progressive, but we know that is this, the damage that they caused to, to humanity is just, it's, it's, it's yet to be measured. But at the end of the day, they fail. They fail and it's, ah, and the end of the Cold War was a great triumph of the free world. It's not that the free world is perfect. It's very important to recognize the fact that, I always like to mention, you know, one of my favorite books, The Lord of the Rings, that the, there's no, there's no absolute good, but there is an absolute evil. Good, you know, comes in many forms, but we all, you know, it's being humans or being even, you know, humans from fairy tales or just some sort of mythical creatures. It's the, eh, you can always find, ah, spots on the sun. So this is, you're conducting war and just, and, and, and fighting for justice. There are always things that, you know, can be easily criticized and human history is the, is a never ending quest for perfection. Ah, but we know that there is absolute evil. We know it's, for me, it's now clear that it's, I mean, it's, nobody argues about Hitler being absolute evil, but I think it's very important to recognize Stalin was absolute evil. Communism caused more damage than any other ideology, ah, in the 20th century. And unfortunately, while we all know that fascism was condemned, but there was no Nuremberg for common communism. And that's why we could see, you know, still is the, ah, the successors of Stalin are feeling far more comfortable. And you, you as one of them. You highlight a few interesting connections actually between Stalin and Hitler. I mean, they're, they're in, in terms of the, ah, adjusting or clarifying the, the history of World War II, which is very interesting. Of course, we don't have time. So let me ask. You can ask it. I just, I just recently delivered a speech in Toronto, ah, at 80th anniversary of Molotov-Ribbentrop Pact. It's something that I believe, you know, just, you know, has must, must be taught in the schools that the World War II, ah, ah, had been started by two dictators by signing these, these, ah, criminal, criminal treaty collusion of two tyrants in August 1939 that led to the beginning of the World, World War II. And the fact is that eventually Stalin had no choice but to join allies because Hitler attacked him. So it just doesn't, you know, ah, ah, eliminate the fact that Stalin helped Hitler to start World War II. And he was one of the beneficiaries at early, at early stage by, ah, annexing, ah, part of Eastern Europe. And as a result of the World War II, he annexed almost entire Eastern Europe. And for many Eastern European nations, the end of the World War II was the beginning of, of communist occupation. So Putin, you've talked about as a man who stands between Russia and democracy, essentially today, you've been a strong opponent and critic of Putin. Let me ask again, how much does fear enter your mind and heart? So in 2007, there's this interesting comment from Oleg Kalugin, KGB general. He said that, I do not talk details. People who knew them are all dead now because they were vocal. I'm quiet. There's only one man who's vocal and he may be in trouble. World chess champion Kasparov. He has been very outspoken in his attacks on Putin. And I believe he's probably next on the list. So clearly your life has been, and perhaps continues to be in danger. How do you think about having the views you have, the ideas you have, being in opposition as you are in this kind of context when your life could be in danger? Ah, that's the reason I live in New York. So it's the, was not my first choice, but I knew I had to leave Russia at one point. And among other places, New York is the safest. Is it safe? No. I mean, it's just, it's the, I know what happens, what happened, what is happening with many of Putin's enemies. But at the end of the day, I mean, what can I do? I mean, it's, I, I could be very proactive by trying to change things I can influence, but here are a way of facts. I, I cannot stop doing what I've been doing for a long time. It's the right thing to do. I grew up, you know, with my family teaching me sort of the wisdom of Soviet dissidents, do what you must and so be it. I could try to be cautious by not traveling to certain places where, you know, my security could be at risk. There's so many invitations to speak at different locations in the world. And I have to say that many countries are just now, are not destinations that I can afford to travel. My mother still lives in Moscow. I meet her a few times a year. She was devastated when I had to leave Russia because since my father died in 1971, so she was 33 and she dedicated her entire life to her only son. But she recognized in just a year or so since I left Russia that it was the only chance for me to continue my normal life. So just to, I mean, to be relatively safe and to, to do what she taught me to do, to make the difference. Do you think you will ever return to Russia or let me ask a different way, when? Oh, I'm sure. It will be sooner than many people think because I think Putin's regime is facing insurmountable difficulties. And again, I read enough historical books to know that dictatorships, they, they end suddenly. It's just on Sunday, dictator feels comfortable. He believes he's popular on Monday morning. He's bust. The good news and bad news. I mean, the bad news is that I don't know when and how Putin rule ends. The good news, he also doesn't know. Okay. Well put. Let me ask a question that seems to preoccupy the American mind from the perspective of Russia. One, did Russia interfere in the 2016 US election government sanction and future to will Russia interfere in the 2020 US election? And what does that interference look like? It's very old. You know, we had such an intelligent conversation and, and you are ruining everything by asking such a stupid question. It's been going downhill the entire way. Yeah, but it's, it's, it's, it's, it's insulting for my intellect. Okay. Of course they did interfere. Of course they did absolutely everything to elect Trump. I mean, they said it many times. It is just, you know, I met enough KGB colonels in my life to tell you that, you know, just the way Putin looks at Trump. This is the way, looks, and I don't have to hear what he says, what Trump says, you know, just, I don't need to go through congressional investigations. The way Putin looks at Trump is the way the KGB officers looked at the assets. It's just, and following to 2020, of course they will do absolutely everything to help Trump to survive because I think the damage that Trump's reelections could cause to America and to the free world, it's just, it's beyond one's imagination. I think basically if Trump is reelected, he will ruin NATO because he's already heading in this direction, but now he's just, he's still limited by the reelection hurdles. If he's still in the office after November, 2020, okay, January, 2021, I don't want to think about it. My problem is not just Trump because Trump is basically, it's a symptom, but the problem is that I don't see, it's just, it's the, in American political horizon, politicians who could take on Trump for all damage that he's doing for the free world, not just things that happened, that went wrong in America. So there's the, it seems to me that the campaign, political campaign on the democratic side is fixed on certain important, but still secondary issues. Because when you have the foundation of the Republic in jeopardy, I mean, you cannot talk about healthcare. I mean, understand how important it is, but it's still secondary because the entire framework of American political life is at risk. And you have Vladimir Putin just, it's having, unfortunately, free hands by attacking America and other free countries. And by the way, we have so much evidence about Russia interfering in Brexit, in elections in almost every European country. And thinking that they will be shy of attacking America in 2020, now with Trump in the office, yeah, I think it's, yeah, it definitely diminishes the intellectual quality of our conversation. I do what I can. Last question. If you can go back, just look at the entirety of your life, you accomplished more than most humans will ever do. If you could go back and relive a single moment in your life, what would that moment be? There are moments in my life when I think about what could be done differently, but- No, experience happiness and joy and pride, just to touch once again. I know, I know, but it's the, look, I made many mistakes in my life. So I just, it's the, I know that at the end of the day, it's, I believe in the butterfly effect. So it's the, I knew moments where I could, moments where I could, now, if I'm there at that point in 89, in 93, pick up a year, I could improve my actions by not doing this stupid thing. But then how do you know that I will have all other accomplishments? Yeah, I just, I'm afraid that we just have to just follow this, if you may call wisdom before it's gump, it's the life is this, it's a box of chocolate and you don't know what's inside, but you have to go one by one. So it's the, I'm happy with who I am and where I am today. And I'm very proud, not only with my chess accomplishments, but that I made this transition. And since I left chess, I built my own reputation that had some influence on the game of chess, but it's not directly derived from the game. I'm grateful for my wife, who helped me to build this life. We actually married in 2005. It was my third marriage. That's why I said I made mistakes in my life. And by the way, I'm close with two kids from my previous marriages. So that's the, I managed to sort of to balance my life. And here, I live in New York. So we have our two kids born here in New York. It's new life and it's busy. Sometimes I wish I could, I could limit my engagement in many other things that are still taking time and energy, but life is exciting. And as long as I can feel that I have energy, I have strengths, I have passion to make the difference, I'm happy. I think that's a beautiful moment to end on. Gary, spasibo, thank you very much for talking today. Thank you.

https://youtu.be/8RVa0THWUWw

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Leonard Susskind: Quantum Mechanics, String Theory and Black Holes | Lex Fridman Podcast #41

The following is a conversation with Leonard Susskind. He's a professor of theoretical physics at Stanford University and founding director of Stanford Institute of Theoretical Physics. He is widely regarded as one of the fathers of string theory and in general, as one of the greatest physicists of our time, both as a researcher and an educator. This is the Artificial Intelligence Podcast. Perhaps you noticed that the people I've been speaking with are not just computer scientists, but philosophers, mathematicians, writers, psychologists, physicists, and soon other disciplines. To me, AI is much bigger than deep learning, bigger than computing. It is our civilization's journey into understanding the human mind and creating echoes of it in the machine. If you enjoy the podcast, subscribe on YouTube, give it five stars on iTunes, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Leonard Susskind. You worked and were friends with Richard Feynman. How has he influenced you, changed you as a physicist and thinker? What I saw, I think what I saw was somebody who could do physics in this deeply intuitive way. His style was almost to close his eyes and visualize the phenomena that he was thinking about and through visualization, outflank the mathematical, the highly mathematical and very, very sophisticated technical arguments that people would use. I think that was also natural to me, but I saw somebody who was actually successful at it, who could do physics in a way that I regarded as simpler, more direct, more intuitive. And while I don't think he changed my way of thinking, I do think he validated it. He made me look at it and say, yeah, that's something you can do and get away with. Practically, he didn't get away with it. So, do you find yourself, whether you're thinking about quantum mechanics or black holes or string theory, using intuition as a first step or a step throughout using visualization? Yeah, very much so, very much so. I tend not to think about the equations. I tend not to think about the symbols. I tend to try to visualize the phenomena themselves. And then when I get an insight that I think is valid, I might try to convert it to mathematics, but I'm not a natural mathematician. I'm good enough at it. I'm good enough at it, but I'm not a great mathematician. So for me, the way of thinking about physics is first intuitive, first visualization, scribble a few equations maybe, but then try to convert it to mathematics. Experience says that other people are better at converting it to mathematics than I am. And yet, you've worked with very counterintuitive ideas. So how do you- No, that's true, that's true. How do you visualize something counterintuitive? How do you dare? By rewiring your brain in new ways. Yeah, quantum mechanics is not intuitive. Very little of modern physics is intuitive. Intuitive, what does intuitive mean? It means the ability to think about it with basic classical physics, the physics that we evolved with throwing stones, or throwing stones, splashing water, or whatever it happens to be. Quantum physics, general relativity, quantum field theory are deeply unintuitive in that way. But after time and getting familiar with these things, you develop new intuitions. I always said you rewire. And it's to the point where me and many of my friends, I and many of my friends, can think more easily quantum mechanically than we can classically. We've gotten so used to it. I mean, yes, our neural wiring in our brain is such that we understand rocks and stones and water and so on. We sort of evolved for that. Evolved for it. Do you think it's possible to create a wiring of neuron-like state devices that more naturally understand quantum mechanics, understand wave function, understand these weird things? Well, I'm not sure. I think many of us have evolved the ability to think quantum mechanically to some extent. But that doesn't mean you can think like an electron. That doesn't mean, another example, forget for a minute quantum mechanics, just visualizing four-dimensional space or five-dimensional space or six-dimensional space, I think we're fundamentally wired to visualize three dimensions. I can't even visualize two dimensions or one dimension without thinking about it as embedded in three dimensions. If I want to visualize a line, I think of the line as being a line in three dimensions. Or I think of the line as being a line on a piece of paper with a piece of paper being in three dimensions. I never seem to be able to, in some abstract and pure way, visualize in my head the one dimension, the two dimension, the four dimension, the five dimensions, and I don't think that's ever gonna happen. The reason is, I think, our neural wiring is just set up for that. On the other hand, we do learn ways to think about five, six, seven dimensions. We learn ways, we learn mathematical ways, and we learn ways to visualize them, but they're different. And so, yeah, I think we do rewire ourselves. Whether we can ever completely rewire ourselves to be completely comfortable with these concepts, I doubt. So that it's completely natural. To a degree, it's completely natural. So I'm sure there's somewhat, you could argue, creatures that live in a two-dimensional space. Yeah, maybe there are. And, well, it's romanticizing the notion, of course, we're all living, as far as we know, in three-dimensional space, but how do those creatures imagine 3D space? Well, probably the way we imagine 4D, by using some mathematics and some equations and some tricks. Okay, so jumping back to Feynman just for a second, he had a little bit of an ego. Yes. Yes. Well, do you think ego is powerful or dangerous in science? I think both, both, both. I think you have to have both arrogance and humility. You have to have the arrogance to say, I can do this. Nature is difficult, nature is very, very hard. I'm smart enough, I can do it. I can win the battle with nature. On the other hand, I think you also have to have the humility to know that you're very likely to be wrong on any given occasion. Everything you're thinking could suddenly change. Young people can come along and say things you won't understand, and you'll be lost and flabbergasted. So I think it's a combination of both. You better recognize that you're very limited, and you better be able to say to yourself, I'm not so limited that I can't win this battle with nature. It takes a special kind of person who can manage both of those, I would say. And I would say there's echoes of that in your own work, a little bit of ego, a little bit of outside of the box, humble thinking. I hope so. So was there a time where you felt, you looked at yourself and asked, am I completely wrong about this? Oh yeah, about the whole thing or about specific things? The whole thing. What do you mean? Wait, which whole thing? Me and me and my ability to do this thing. Oh, those kinds of doubts. First of all, did you have those kinds of doubts? No, I had different kind of doubts. I came from a very working class background, and I was uncomfortable in academia for a long time. But there weren't doubts about my ability or my, they were, just the discomfort in being in an environment that my family hadn't participated in, I knew nothing about as a young person. I didn't learn that there was such a thing called physics until I was almost 20 years old. So I did have certain kind of doubts, but not about my ability. I don't think I was too worried about whether I would succeed or not. I never felt this insecurity, am I ever gonna get a job? That had never occurred to me that I wouldn't. Maybe you could speak a little bit to this sense of what is academia, because I too feel a bit uncomfortable in it. There's something I can't put quite into words what you have that's not, doesn't, if we call it music, you play a different kind of music than a lot of academia. How have you joined this orchestra? How do you think about it? I don't know that I thought about it as much as I just felt it. Thinking is one thing, feeling is another thing. I felt like an outsider until a certain age when I suddenly found myself the ultimate insider in academic physics. And that was a sharp transition, and I wasn't a young man, I was probably 50 years old. So you were never quite, it was a phase transition, you were never quite in the middle. Yeah, that's right, I wasn't. I always felt a little bit of an outsider. In the beginning, a lot an outsider. My way of thinking was different, my approach to mathematics was different, but also my social background that I came from was different. Now these days, half the young people I meet they're parents or professors. Right. Right, that was not my case. So yeah, but then all of a sudden at some point I found myself at the very much the center of, maybe not the only one at the center, but certainly one of the people in the center of a certain kind of physics. And all that went away, I mean it went away in a flash. So maybe a little bit with Feynman, but in general, how do you develop ideas? Do you work through ideas alone? Do you brainstorm with others? Oh, both, both, very definitely both. The younger time I spent more time with myself. Now, because I'm at Stanford, because I have a lot of ex-students and people who are interested in the same thing I am, I spend a good deal of time, almost on a daily basis, interacting, brainstorming as you said. It's a very important part. I spend less time probably completely self-focused and with a piece of paper and just sitting there staring at it. What are your hopes for quantum computers? So machines that are based on, that have some elements of leveraged quantum mechanical ideas. Yeah, it's not just leveraging quantum mechanical ideas. You can simulate quantum systems on a classical computer. Simulate them means solve the Schrodinger equation for them or solve the equations of quantum mechanics on a computer, on a classical computer. But the classical computer is not doing, is not a quantum mechanical system itself. Of course it is. Everything's made of quantum mechanics, but it's not functioning. It's not functioning as a quantum system. It's just solving equations. The quantum computer is truly a quantum system, which is actually doing the things that you're programming it to do. You want to program a quantum field theory. If you do it in classical physics, that program is not actually functioning in the computer as a quantum field theory. It's just solving some equations. Physically, it's not doing the things that the quantum system would do. The quantum computer is really a quantum mechanical system, which is actually carrying out the quantum operations. You can measure it at the end. It intrinsically satisfies the uncertainty principle. It is limited in the same way that quantum systems are limited by uncertainty and so forth. And it really is a quantum system. That means that what you're doing when you program something for a quantum system is you're actually building a real version of the system. The limits of a classical computer, classical computers are enormously limited when it comes to quantum systems. They're enormously limited because you probably heard this before, but in order to store the amount of information that's in a quantum state of 400 spins, that's not very many, 400 I can put in my pocket, 400 pennies in my pocket. To be able to simulate the quantum state of 400 elementary quantum systems, qubits we call them, to do that would take more information than can possibly be stored in the entire universe if it were packed so tightly that you couldn't pack any more in. 400 qubits. On the other hand, if your quantum computer is composed of 400 qubits, it can do everything 400 qubits can do. What kind of space, if you just intuitively think about the space of algorithms, that that unlocks for us. So there's a whole complexity theory around classical computers measuring the running time of things, and P, so on. What kind of algorithms, just intuitively, do you think it unlocks for us? Okay, so we know that there are a handful of algorithms that can seriously beat classical computers and which can have exponentially more power. This is a mathematical statement. Nobody's exhibited this in the laboratory. It's a mathematical statement. We know that's true, but it also seems more and more that the number of such things is very limited. Only very, very special problems exhibit that much advantage for a quantum computer, of standard problems. To my mind, as far as I can tell, the great power of quantum computers will actually be to simulate quantum systems. If you're interested in a certain quantum system and it's too hard to simulate classically, you simply build a version of the same system. You build a version of it, you build a model of it that's actually functioning as the system, you run it, and then you do the same thing you would do to the quantum system, you make measurements on it, quantum measurements on it. The advantage is you can run it much slower. You could say, why bother? Why not just use the real system? Why not just do experiments on the real system? Well, real systems are kind of limited. You can't change them, you can't manipulate them, you can't slow them down so that you can poke into them. You can't modify them in arbitrary kinds of ways to see what would happen if I change the system a little bit. I think that quantum computers will be extremely valuable in understanding quantum systems. At the lowest level, the fundamental laws. They're actually satisfying the same laws as the systems that they're simulating. That's right. Okay, so on the one hand, you have things like factoring. Factoring is the great thing of quantum computers, factoring large numbers. That doesn't seem that much to do with quantum mechanics. It seems to be almost a fluke that a quantum computer can solve the factoring problem in a short time. And those problems seem to be extremely special, rare, and it's not clear to me that there's gonna be a lot of them. On the other hand, there are a lot of quantum systems. Chemistry, there's solid state physics, there's material science, there's quantum gravity, there's all kinds of quantum field theory. And some of these are actually turning out to be applied sciences as well as very fundamental sciences. So we probably will run out of the ability to solve equations for these things. You know, solve equations by the standard methods of pencil and paper, solve the equations by the method of classical computers. And so what we'll do is we'll build versions of these systems, run them, and run them under controlled circumstances where we can change them, manipulate them, make measurements on them, and find out all the things we wanna know. So in finding out the things we wanna know about very small systems, right, is there something we can also find out about the macro level? About something about the function, forgive me, of our brain, biological systems? The stuff that's about one meter in size versus much, much smaller. Well, all the excitement is about, among the people that I interact with, is understanding black holes. Black holes. Black holes are big things. They are many, many degrees of freedom. There is another kind of quantum system that is big. It's a large quantum computer. And one of the things we've learned is that the physics of large quantum computers is in some ways similar to the physics of large quantum black holes. And we're using that relationship. Now you asked, you didn't ask about quantum computers, the systems, you didn't ask about black holes, you asked about brains. Yeah, about stuff that's in the middle of the two. It's different. So black holes are, there's something fundamental about black holes that feels to be very different than brains. Yes. And they also function in a very quantum mechanical way. Right. Okay. It is, first of all, unclear to me, but of course it's unclear to me. I'm not a neuroscientist. I have, I don't even have very many friends who are neuroscientists. I would like to have more friends who are neuroscientists. I just don't run into them very often. Among the few neuroscientists I've ever talked about about this, they are pretty convinced that the brain functions classically. That it is not intrinsically a quantum mechanical system or doesn't make use of the special features, entanglement, coherent superposition. Are they right? I don't know. I sort of hope they're wrong, just because I like the romantic idea that the brain is a quantum system. Yeah. But I think probably not. The other thing, big systems can be composed of lots of little systems, okay? Materials, the materials that we work with and so forth are, can be large systems, a large piece of material, but they're made out of quantum systems. Now, one of the things that's been happening over the last good number of years is we're discovering materials and quantum systems which function much more quantum mechanically than we imagine. Topological insulators, this kind of thing, that kind of thing. Those are macroscopic systems, but they, just superconductors, superconductors, have a lot of quantum mechanics in them. You can have a large chunk of superconductor, so it's a big piece of material. On the other hand, it's functioning and its properties depend very, very strongly on quantum mechanics. And to analyze them, you need the tools of quantum mechanics. If we can go on to black holes, and looking at the universe as an information processing system, as a computer, as a giant computer. It's a giant computer. What's the power of thinking of the universe as an information processing system? Or what is, perhaps its use, besides the mathematical use of discussing black holes and your famous debates and ideas around that, to human beings, or life in general, as information processing systems? So all systems are information processing systems. You poke them, they change a little bit, they evolve. All systems are information processing systems. So there's no extra magic to us humans? It certainly feels, consciousness, intelligence feels like magic. It sure does. Where does it emerge from? If we look at information processing, what are the emerging phenomena that come from viewing the world as an information processing system? Here is what I think. My thoughts are not worth much in this. If you ask me about physics, my thoughts may be worth something. If you ask me about this, I'm not sure my thoughts are worth anything. But as I said earlier, I think when we do introspection, when we imagine doing introspection and try to figure out what it is when we do, and we're thinking, I think we get it wrong. I'm pretty sure we get it wrong. Everything I've heard about the way the brain functions is so counterintuitive. For example, you have neurons which detect vertical lines. You have different neurons which detect lines at 45 degrees. You have different neurons. I never imagined that there were whole circuits which were devoted to vertical lines in the brain. Doesn't seem to be the way my brain works. My brain seems to work if I put my finger up vertically, or if I put it horizontally, or if I put it this way or that way. It seems to me it's the same circuits that are, it's not the way it works. The way the brain is compartmentalized seems to be very, very different than what I would have imagined if I were just doing psychological introspection about how things work. My conclusion is that we won't get it right that way. That, how will we get it right? I think maybe computer scientists will get it right. Eventually, I don't think they're anywhere near it. I don't even think they're thinking about it. But by computer, eventually we will build machines, perhaps, which are complicated enough, and partly engineered, partly evolved, maybe evolved by machine learning and so forth. This machine learning is very interesting. By machine learning, we will evolve systems, and we may start to discover mechanisms that have implications for how we think and for what this consciousness thing is all about. And we'll be able to do experiments on them and perhaps answer questions that we can't possibly answer by introspection. So that's a really interesting point. In many cases, if you look at even the string theory, when you first think about a system, it seems really complicated, like the human brain. And through some basic reasoning, in trying to discover fundamental, low-level behavior of the system, you find out that it's actually much simpler. Is that generally the process? And two, do you have that also hope for biological systems as well, for all the kinds of stuff we're studying at the human level? Of course, physics always begins by trying to find the simplest version of something and analyze it. Yeah, I mean, there are lots of examples where physics has taken very complicated systems, analyzed them, and found simplicity in them for sure. I said superconductors before. It's an obvious one. A superconductor seems like a monstrously complicated thing with all sorts of crazy electrical properties, magnetic properties, and so forth. And when it finally is boiled down to its simplest elements, it's a very simple quantum mechanical phenomenon called spontaneous symmetry breaking, which we, in other contexts, we learned about and we're very familiar with. So yeah, I mean, yes, we do take complicated things, make them simple, but what we don't wanna do is take things which are intrinsically complicated and fool ourselves into thinking that we can make them simple. We don't wanna make, I don't know who said this, but we don't wanna make them simpler than they really are, okay? Is the brain a thing which ultimately functions by some simple rules, or is it just complicated? In terms of artificial intelligence, nobody really knows what are the limits of our current approaches. You mentioned machine learning. How do we create human-level intelligence? It seems that there's a lot of very smart physicists who perhaps oversimplify the nature of intelligence and think of it as information processing, and therefore there doesn't seem to be any theoretical reason why we can't artificially create human-level or superhuman-level intelligence. In fact, the reasoning goes, if you create human-level intelligence, the same approach you just used to create human-level intelligence should allow you to create superhuman-level intelligence very easily, exponentially. So what do you think that way of thinking that comes from physicists is all about? I wish I knew, but there's a particular reason why I wish I knew. I have a second job. I consult for Google. Not for Google, for Google X. I am the senior academic advisor to a group of machine-learning physicists. Now, that sounds crazy because I know nothing about the subject. I know very little about the subject. On the other hand, I'm good at giving advice, so I give them advice on things. Anyway, I see these young physicists who are approaching the machine-learning problem. There is a real machine-learning problem, namely, why does it work as well as it does? Nobody really seems to understand why it is capable of doing the kind of generalizations that it does and so forth. And there are three groups of people who have thought about this. There are the engineers. The engineers are incredibly smart, but they tend not to think as hard about why the thing is working as much as they do how to use it, obviously. They've provided a lot of data. And it is they who demonstrated that machine-learning can work much better than you had any right to expect. The machine-learning systems are systems, the systems not too different than the kind of systems that physicists study. There's not all that much difference between quantum, in the structure of the mathematics, physically, yes, but in the structure of the mathematics, between a tensor network designed to describe a quantum system on the one hand and the kind of networks that are used in machine-learning. So there are more and more, I think, young physicists are being drawn to this field of machine-learning. Some very, very good ones. I work with a number of very good ones, not on machine-learning, but on having lunch. On having lunch? Right. Yeah. And I can tell you they are super smart. They don't seem to be so arrogant about their physics backgrounds that they think they can do things that nobody else can do. But the physics way of thinking, I think, will add great value to, or will bring value to the machine-learning. I believe it will. And I think it already has. At what time scale do you think predicting the future becomes useless? In your long experience in being surprised at new discoveries. Sometimes a day, sometimes 20 years. There are things which I thought we were very far from understanding, which practically in a snap of the fingers or a blink of the eye suddenly became understood, completely surprising to me. There are other things which I looked at and I said, we're not gonna understand these things for 500 years, in particular quantum gravity. The scale for that was 20 years, 25 years. And we understand a lot, and we don't understand it completely now by any means, but I thought it was 500 years to make any progress. It turned out to be very, very far from that. It turned out to be more like 20 or 25 years from the time when I thought it was 500 years. So if we may, can we jump around quantum gravity, some basic ideas in physics? What is the dream of string theory, mathematically? What is the hope? Where does it come from? What problem is it trying to solve? I don't think the dream of string theory is any different than the dream of fundamental theoretical physics altogether. Understanding a unified theory of everything. I don't like thinking of string theory as a subject unto itself, with people called string theorists who are the practitioners of this thing called string theory. I much prefer to think of them as theoretical physicists trying to answer deep fundamental questions about nature, in particular gravity, in particular gravity and its connection with quantum mechanics, and who at the present time find string theory a useful tool, rather than saying there's this subject called string theorists. I don't like being referred to as a string theorist. Yes, but as a tool, is it useful to think about our nature in multiple dimensions, the strings vibrating? I believe it is useful. I'll tell you what the main use of it has been up till now. Well, it has had a number of main uses. Originally, string theory was invented, and I know that I was there, I was right at the spot where it was being invented, literally, and it was being invented to understand hadrons. Hadrons are subnuclear particles, protons, neutrons, mesons, and at that time, the late 60s, early 70s, it was clear from experiment that these particles called hadrons could vibrate, could rotate, could do all the things that a little closed string can do, and it was and is a valid and correct theory of these hadrons. It's been experimentally tested, and that is a done deal. It had a second life as a theory of gravity, the same basic mathematics, except on a very, very much smaller distance scale. The objects of gravitation are 19 orders of magnitude smaller than a proton, but the same mathematics turned up, the same mathematics turned up. What has been its value? Its value is that it's mathematically rigorous in many ways and enabled us to find mathematical structures, mathematical structures which have both quantum mechanics and gravity. With rigor, we can test out ideas. We can test out ideas. We can't test them in the laboratory, that they're 19 orders of magnitude too small, the things that we're interested in, but we can test them out mathematically and analyze their internal consistency. By now, 40 years ago, 35 years ago, and so forth, people very, very much questioned the consistency between gravity and quantum mechanics. Stephen Hawking was very famous for it, rightly so. Now, nobody questions that consistency anymore. They don't because we have mathematically precise string theories which contain both gravity and quantum mechanics in a consistent way. So it's provided that certainty that quantum mechanics and gravity can coexist. That's not a small thing. It's a very big thing. It's a huge thing. Einstein would be proud. Einstein, he might be appalled. I don't know. He didn't like quantum mechanics very much, but he would certainly be struck by it. I think that may be, at this time, its biggest contribution to physics in illustrating almost definitively that quantum mechanics and gravity are very closely related and not inconsistent with each other. Is there a possibility of something deeper, more profound, that still is consistent with string theory but is deeper that is to be found? Well, you could ask the same thing about quantum mechanics. Is there something? Exactly. Yeah, yeah. I think string theory is just an example of a quantum mechanical system that contains both gravitation and quantum mechanics. So is there something underlying quantum mechanics? Perhaps something deterministic. Perhaps something deterministic. My friend, Gerard Etoft, whose name you may know, he's a very famous physicist. Dutch, not as famous as he should be, but. Hard to spell his name. It's hard to say his name. No, it's easy to spell his name. Apostrophe, he's the only person I know whose name begins with an apostrophe. And he's one of my heroes in physics. He's a little younger than me, but he's nevertheless one of my heroes. Etoft believes that there is some sub-structure to the world which is classical in character, deterministic in character, which somehow, by some mechanism that he has a hard time spelling out, emerges as quantum mechanics. I don't. The wave function is somehow emergent. The wave function, not just the wave function, but the whole mechan, the whole thing that goes with quantum mechanics, uncertainty, entanglement, all these things are emergent. So you think quantum mechanics is the bottom of the well? Is the... Here, I think, is where you have to be humble. Here's where humility comes. I don't think anybody should say anything is the bottom of the well at this time. I think we can reasonably say, or I can reasonably say, when I look into the well, I can't see past quantum mechanics. I don't see any reason for there to be anything beyond quantum mechanics. I think Etoft has asked very interesting and deep questions I don't like his answers. Well, again, let me ask, if we look at the deepest nature of reality, whether it's deterministic or, when observed, as probabilistic, what does that mean for our human level of ideas of free will? Is there any connection whatsoever from this perception, perhaps illusion of free will that we have, and the fundamental nature of reality? The only thing I can say is I am puzzled by that as much as you are. The illusion of it, the... The illusion of consciousness, the illusion of free will, the illusion of self. Does that connect to... How can a physical system do that? And I am as puzzled as anybody. There's echoes of it in the observer effect. Yeah. So do you understand what it means to be an observer? I understand it at a technical level. An observer is a system with enough degrees of freedom that it can record information, and which can become entangled with the thing that it's measuring. Entanglement is the key. When a system, which we call an apparatus or an observer, same thing, interacts with the system that it's observing, it doesn't just look at it, it becomes physically entangled with it. And it's that entanglement which we call an observation or a measurement. Now does that satisfy me personally as an observer? Yes and no. I find it very satisfying that we have a mathematical representation of what it means to observe a system. You are observing stuff right now. Yeah. At the conscious level. Right. Do you think there's echoes of that kind of entanglement in our macro scale? Yes, absolutely, for sure. We're entangled with everything, quantum mechanically entangled with everything in this room. If we weren't, then we would just, well, we wouldn't be observing it. But on the other hand, you can ask, do I really, am I really comfortable with it? And I'm uncomfortable with it in the same way that I can never get comfortable with five dimensions. My brain isn't wired for it. Are you comfortable with four dimensions? A little bit more because I can always imagine the fourth dimension is time. So the arrow of time, are you comfortable with that arrow? Do you think time is an emergent phenomena or is it fundamental to nature? That is a big question in physics right now. All the physics that we do, or at least that the people that I am comfortable with talking to, my friends, my friends. My friends, we all ask the same question that you just asked. Space, we have a pretty good idea is emergent and it emerges out of entanglement and other things. Time always seems to be built into our equations as just what Newton pretty much would have thought. Newton modified a little bit by Einstein would have called time. And mostly in our equations it is not emergent. Time in physics is completely symmetric, forward and backward. Right, symmetric. So you don't really need to think about the arrow of time for most physical phenomena. Most microscopic phenomena, no. It's only when the phenomena involve systems which are big enough for thermodynamics to become important, for entropy to become important. For a small system, entropy is not a good concept. And entropy is something which emerges out of large numbers. It's a probabilistic idea, it's a statistical idea, and it's a thermodynamic idea. Thermodynamics requires lots and lots and lots of little substructures. So it's not until you emerge at the thermodynamic level that there's an arrow of time. Do we understand it? Yeah, I think we understand better than most people think they understand. Most people say they think we understand it. Yeah, I think we understand it. It's a statistical idea. You mean like second law thermodynamics, entropy and so on? Yeah, yeah. Pick a pack of cards and you fling it in the air and you look what happens to it. It gets random. We understand it. It doesn't go from random to simple. It goes from simple to random. But do you think it ever breaks down? What I think you can do is in a laboratory setting, you can take a system which is somewhere intermediate between being small and being large and make it go backward. A thing which looks like it only wants to go forward because of statistical mechanical reasons, because of the second law. You can very, very carefully manipulate it to make it run backward. I don't think you can take an egg, a Humpty Dumpty who fell on the floor and reverse that. But you can, in a very controlled situation, you can take systems which appear to be evolving statistically toward randomness, stop them, reverse them and make them go back. What's the intuition behind that? How do we do that? How do we reverse it? You're saying a closed system. Yeah, pretty much closed system, yes. Did you just say that time travel is possible? No, I didn't say time travel is possible. I said you can make a system go backward. In time. You can make it go back. You can make it reverse its steps. You can make it reverse its trajectory. Yeah. How do we do it? What's the intuition there? Does it have, is it just a fluke thing that we can do at a small scale in the lab that doesn't have? What I'm saying is you can do it on a little bit better than a small scale. You can certainly do it with a simple small system. Small systems don't have any sense of the arrow of time. Atoms, atoms are, no sense of an arrow of time. They're completely reversible. It's only when you have, you know, the second law of thermodynamics is the law of large numbers. So you can break the law because it's not a deterministic law. You can break it, but it's hard. It requires great care. The bigger the system is, the more care, the more, the harder it is. You have to overcome what's called chaos. And that's hard. And it requires more and more precision. For 10 particles, you might be able to do it with some effort. For 100 particles, it's really hard. For 1,000 or a million particles, forget it. But not for any fundamental reason, just because it's technologically too hard to make the system go backward. So no time travel for engineering reasons. Oh, no, no, no, no. What is time travel? Time travel to the future, that's easy. You just close your eyes, go to sleep, and you wake up in the future. Yeah, yeah. A good nap gets you there, yeah. A good nap gets you there, right. What happens in reversing the second law of thermodynamics, the going backward in time, for anything that's human scale, is a very difficult engineering effort. I wouldn't call it time travel, because it gets too mixed up with what science fiction calls time travel. This is just the ability to reverse a system. You take the system, and you reverse the direction of motion of every molecule in it. That, you can do it with one molecule. If you find a particle moving in a certain direction, let's not say a particle, a baseball, you stop it dead, and then you simply reverse its motion. In principle, that's not too hard. And it'll go back along its trajectory in the backward direction. Just running the program backwards. Running the program backward. Yeah. If you have two baseballs colliding, well, you can do it, but you have to be very, very careful to get it just right. If you have 10 baseballs, really, really, or better yet, 10 billiard balls on an idealized frictionless billiard table. Okay, so you start the balls all on a triangle, right? And you whack them. Depending on the game you're playing, you either whack them or you're really careful, but you whack them. And they go flying off in all possible directions. Okay, try to reverse that. Try to reverse that. Imagine trying to take every billiard ball, stopping it dead at some point, and reversing its motion so that it was going in the opposite direction. If you did that with tremendous care, it would reassemble itself back into the triangle. Okay, that is a fact, and you can probably do it with two billiard balls, maybe with three billiard balls if you're really lucky. But what happens is as the system gets more and more complicated, you have to be more and more precise not to make the tiniest error, because the tiniest errors will get magnified, and you'll simply not be able to do the reversal. So yeah, but I wouldn't call that time travel. Yeah, that's something else. But if you think of it, it just made me think, if you think the unrolling of state that's happening as a program, if we look at the world, so the idea of looking at the world as a simulation, as a computer, but it's not a computer, it's just a single program. A question arises that might be useful. How hard is it to have a computer that runs the universe? Okay, so there are mathematical universes that we know about. One of them is called anti-de Sitter space, where we, and it's quantum mechanics, where I think we could simulate it in a computer, in a quantum computer. Classical computer, all you can do is solve its equations. You can't make it work like the real system. If we could build a quantum computer, a big enough one, a robust enough one, we could probably simulate a universe, a small version of an anti-de Sitter universe. Anti-de Sitter is a kind of a cosmology. So I think we know how to do that. The trouble is the universe that we live in is not the anti-de Sitter geometry, it's the de Sitter geometry. And we don't really understand its quantum mechanics at all. So at the present time, I would say we wouldn't have the vaguest idea how to simulate a universe similar to our own. You know, we could ask, could we build in the laboratory a small version, a quantum mechanical version, the collection of quantum computers entangled and coupled together, which would reproduce the phenomena that go on in the universe, even on a small scale. Yes, if it were anti-de Sitter space. No, if it's de Sitter space. Can you slightly describe de Sitter space and anti-de Sitter space? Yeah. What are the geometric properties of? They differ by the sign of a single constant called the cosmological constant. One of them is negatively curved, the other is positively curved. The anti-de Sitter space, which is the negatively curved one, you can think of as an isolated system in a box with reflecting walls. You could think of it as a system of quantum mechanical system, isolated in an isolated environment. De Sitter space is the one we really live in, and that's the one that's exponentially expanding. Exponential expansion, dark energy, whatever we want to call it. And we don't understand that mathematically. Do we understand? Not everybody would agree with me, but I don't understand. They would agree with me, they definitely would agree with me that I don't understand it. What about, is there an understanding of the birth, the origin, the Bing Bang? So, there's one thing with the other. No, no, there's theories. There are theories. My favorite is the one called eternal inflation. The infinity can be on both sides, on one of the sides and none of the sides. So, what's eternal infinity? Okay. Infinity on both sides. Oh, boy. Yeah, yeah. Why is that your favorite? Because it's the most, just mind-blowing? No. Because we want a beginning. No. Why do we want a beginning? In practice, there was a beginning, of course. In practice, there was a beginning. But could it have been a random fluctuation in an otherwise infinite time? Maybe. In any case, the eternal inflation theory, I think if correctly understood, would be infinite in both directions. How do you think about infinity? Oh, God. So, okay, of course you can think about it mathematically. I just finished this discussion with my friend, Sergey Brin. Yes. How do you think about infinity? I say, well, Sergey Brin is infinitely rich. How do you test that hypothesis? Okay. That's such a good line. Right. Yeah, so there's really no way to visualize some of these things. Like, like. Yeah, no, this is a very good question. Does physics have any, does infinity have any place in physics? Right. Right, and all I can say is, very good question. So, what do you think of the recent first image of a black hole visualized from the Event Horizon Telescope? It's an incredible triumph of science. In itself, the fact that there are black holes which collide is not a surprise. And they seem to work exactly the way they're supposed to work. Will we learn a great deal from it? I don't know, I can't, we might. But the kind of things we'll learn won't really be about black holes. Why there are black holes in nature of that particular mass scale and why they're so common may tell us something about the structure, evolution of structure in the universe. But I don't think it's gonna tell us anything new about black holes. But it's a triumph in the sense that you go back 100 years and it was a continuous development, general relativity, the discovery of black holes, LIGO, the incredible technology that went into LIGO. It is something that I never would have believed was gonna happen 30, 40 years ago. And I think it's a magnificent structure, magnificent thing, this evolution of general relativity, LIGO, high precision, ability to measure things on a scale of 10 to the minus 21. So, yeah. So you're just in awe that we, this path took us to this picture. Is it different? You know, you've thought a lot about black holes. How did you visualize them in your mind? And is the picture different than you realized it? No, it simply confirmed, you know, it's a magnificent triumph to have confirmed a direct observation that Einstein's theory of gravity at the level of black hole collisions actually works is awesome, it is really awesome. You know, I know some of the people who were involved in that. They're just ordinary people. And the idea that they could carry this out, I just, I'm shocked. Yeah, just these little homo sapiens. Yeah, just these little monkeys. Yeah, got together and took a picture of. Slightly advanced limers, I think. What kind of questions can science not currently answer but you hope might be able to soon? Well, you've already addressed them. What is consciousness, for example? You think that's within the reach of science? I think it's somewhat within the reach of science, but I think now I think it's in the hands of the computer scientists and the neuroscientists. Not a physicist. Perhaps at some point. But I think physicists will try to simplify it down to something that they can use their methods and maybe they're not appropriate. Maybe we simply need to do more machine learning on bigger scales, evolve machines. Machines not only that learn but evolve their own architecture as a process of learning, evolving architecture. Not under our control, only partially under our control, but under the control of machine learning. I'll tell you another thing that I find awesome. You know this Google thing that they taught computers how to play chess? Yeah, yeah. Okay, they taught computers how to play chess, not by teaching them how to play chess, but just having them play against each other. Against each other, self-play. Against each other. This is a form of evolution. These machines evolved. They evolved in intelligence. They evolved in intelligence without anybody telling them how to do it. They were not engineered. They just played against each other and got better and better and better. That makes me think that machines can evolve intelligence. What exact kind of intelligence, I don't know. But in understanding that better and better, maybe we'll get better clues as to what goes on in our own intelligence. Well, life and intelligence is, last question, what kind of questions can science not currently answer and may never be able to answer? Yeah. Yeah. Is there an intelligence out there that's underlies the whole thing? You can call them with a G word if you want. I can say, are we a computer simulation with a purpose? Is there an agent, an intelligent agent that underlies or is responsible for the whole thing? Does that intelligent agent satisfy the laws of physics? Does it satisfy the laws of quantum mechanics? Is it made of atoms and molecules? Yeah, there's a lot of questions. And I don't see, it seems to me a real question. It's an answerable question. Well, I don't know if it's answerable. The questions have to be answerable to be real. Some philosophers would say that a question is not a question unless it's answerable. This question doesn't seem to me answerable by any known method, but it seems to me real. There's no better place to end. Leonard, thank you so much for talking today. Okay, good.

https://youtu.be/s78hvV3QLUE

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Ray Dalio: Money, Power, and the Collapse of Empires | Lex Fridman Podcast #251

The following is a conversation with Ray Dalio, his second time on the podcast. He is a legendary investor, founder of Bridgewater Associates, author of a book I highly recommend called Principles, and also a new book called Principles for Dealing with a Changing World Order that looks at the geopolitics of today, especially US and China, through the lens of history, providing a fascinating model for the rise and fall of empires that can be applied to the analysis of our world today. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Ray Dalio. When you look at the history of the world, as you have done in your new book, Principles of Dealing with a Changing World Order, what is more important, more impactful, money or power? They go hand in hand. And they support each other and they compete with each other. Those who have money have power, a certain type of power. That power has to do with all that they can buy, but it also has the ability to influence those with political power. So, and so you see this throughout history, this symbiotic relationship. You know, for example, between the royal families, the nobility and the church. So you see that group of people supporting each other in various ways and then wrestling around with each other for the money and power among that group. So the dynamic that's quite classic is you could look at the parties in power back in, you know, the 16th, 17th centuries. You would look at royal families, nobles and the church, if you're in Europe. And then you would look at agricultural land and there was a certain dynamic. And that varies over time. It changes. As those people get thrown out and technology changes. So when we evolved, when the society evolved so that it would produce goods and services and you have something like the Industrial Revolution, the first Industrial Revolution, they have machines and you have the talent of people that are off the farms. And then you have a struggling for power. You see that power mix change. And so we don't see that same power mix anymore, but you still see the same dynamic. You see those with money dealing with those who have political power around those assets that are considered most valuable to particularly the productive assets that produce money. And political power is usually centered around nation state. So the major locus of power is the nations. Yes. In 1668, after 30 years of war, there was the development of nation states. Before then, we had, it was really the development of countries as we know it, that there were borders and that within those borders, those who were in those borders, those who had control got to control it. And there were not to be intrusions in those borders. And that's how we established the nation state. And then, of course, within each country, there is levels. There is a central level and then there is a typically a province or state level down below. And then there is a municipal level, so they each have different levels of power. And it's the coordination of those that determines how the country is run. You write that the quote, archetypal big cycle, governs the rising and declining empires and influences everything about them, including their currencies and markets. The most important three cycles are the ones you mentioned in the introduction. The long-term debt and capital market cycle, the internal order and disorder cycle, and the external order and disorder cycle. Can you describe this big cycle? There are two orders. There is an order by a, order I mean a system, how the system works. So, there's an internal order, that is the internal governance system and it's usually set out in a constitution or some agreements. And then there's the world order, how the world system. So, for example, in 1945, at the end of a war, which is basically a fight for determining the world order, the winners of the fight got together and created the world system as we now know it. In 1944, they created the Brenton Woods monetary system that determined the money, pretty much. And because the United States won and had 80% of the world's money, gold was money then, and it has 80% of the world's gold, and it was half the world economy and it was the great military power. The order was built around an American world order, so that the United Nations was in New York, the World Bank and the IMF were in Washington, and they built that new order. So, classically, you have a war to determine whose rules we're following, and then you have the new order being constructed. After that, there is usually a period of extended peace and prosperity. Peace suits prosperity, and so there's not... And the reason you have the peace is because no one wants to fight with the dominant power. You know you're going to lose, you've surrendered. There's been the surrendering. They carve up the world, they say what it's going to look like, who's going to control what. And then you come into that period of peace, and then prosperity, where then there's a working together. Usually, at that point, you've wiped out a lot of the debt, you've wiped out a lot of the issues, the class warfare and so on, and then there's good working together. So, those great periods, such as the Industrial Revolution in the late 1800s, or what we've experienced in the post-World War II period, are peaceful and prosperous periods led largely by the dominant world power. Over a period of time, since really 1500, and maybe before, but really 1500 when the Dutch invented capitalism, and what I mean by that, they invented the first capital markets, the first stocks and the first stock market, that since then capitalism has been an effective tool for building wealth because it got resources into the hands of inventive people. That's when we move from agriculture to the importance of inventiveness of people. They got resources, and then they built that prosperity. In that process of doing that, they create wealth gaps naturally. Those who make a lot of money make a lot more, and then those that don't. And it also produces opportunity gaps because, for example, those who earn a lot of money have that wealth. They have the power to educate their children in a way that others don't, and the gaps grow. And also the debts grow at that time. When they go around the world with their competitiveness, they earn a lot of money. So, for example, the Dutch, the Dutch Empire, learned how to build ships that would go around the world. A key ingredient of this improvement in this cycle is the improvement of education, and by education I mean the skills that come from education, but also civility, the ability to deal well together. So the Dutch invented ships that could go around the world, and they had military power, but they were also a very inventive society. 25% of the world's new inventions came from the Dutch. And so as they went around the world, they also brought their currency, and they brought their military. They needed the currency, they paid for things, and that currency, and then the more that happens, the more that becomes a reserve currency. And then they have their military, so they need their military strength, and so you see it evolve in all of those ways. But over a period of time, as they become more successful and more expensive, they become more expensive. And newer countries come along, like the UK, then learn to build ships from a lot the Dutch, and could do that less expensively. And also when they become more expensive, so less competitive, and also the work ethic begins to change. They believe that since they're richer, they can enjoy life more. They don't have to work quite as hard. And so you start to see the tilt. You start to see the development of the top. And when you have a world reserve currency, that allows you to borrow a lot of money, because those who want to save, want to hold your money, and that means that they'll lend you money, and so those countries get deeper into debt. So you see that they gradually lose their competitiveness, and they get themselves into financial circumstances, which are not good, and they have large wealth gaps, which set the stage for downturns. And when they have downturns, the first question is, do they have enough money? And traditionally, you know, money is resources. So you classically see that the coffers are bare, that they're spending more money than they are earning, and they run out of money in the coffers. And their granaries are empty, rather than stocked, so that they give them the buffer. And as that deteriorates, that worsens conditions. And if they have a rival power, that's also challenging them, they see greater internal conflict over wealth, and then they have the problems internally, and the problems externally, which usually results in an internal war, or an external war, that leads to the change in the, to the new world order. And to you, the Dutch Empire is a good example of that. The British, what are some of the key examples that you think about in the book, of this process that followed the big cycle? Well, the leading reserve currency empires, but it applies to all the empires, were the Dutch, the British, the American, and the Chinese. But you could follow the same pattern. In the book, it was very important for me to not just use words and concepts, because that's subjective. It was very important for me to use actual measurements. So as you see in the book, you can see every level of this. You can see where's the education level, what is the military power, each one of those, and you can see them back going over the 500 years. And so you can see the arcs and the composition of those arcs. And what you see is really, in most countries and most dynasties, you can see that, but you also can see through those numbers, the health of those countries. Today, there are statistics that are in the book that show what is the level of education, what is the level of economic output, what is the level of military strength, what is the level of a number of different measures of strength, so that you can then compare that. And I think that because there are objective measures of strength that you could see change, that shows the picture of where we are today. And I think one of the most important things about the book is that it allows people to monitor how those things are transpiring. I think for policy makers, are your policy makers doing a good job? And there's so much subjectivity in that. But I think it's very simple. If those lines on the chart are improving, if your health index is improving, then you're moving toward a better life. So that's what the book works like. Also, it was used to create a model for the future. In other words, there are cause-effect relationships. Everything that happens has reasons, causes that preceded it, that made it happen. And so by having all those in numbers, one can see the probabilities of certain things happening. So that's what you see in the book. It's not just Ray's interpretation. I didn't wanna make it Ray's interpretation because I don't know if I'm right. Yeah, so one of the fascinating things in the book, so you have to list these 18 measures. And there's like a little scorecard for the countries of the world today. So let's say US, China, and Europe. And what it was 20 years ago, and looking at the change from 20 years ago, and that's another indicator, the change itself to see where things are headed. Maybe can you comment on, from a score perspective, how is US and China doing? And in the 18 measures, what are some measures that stand out to you as particularly important to think about today for the United States, for China? Well, there are a number, financially, what you see in the United States is that we're borrowing a lot more money, creating a lot of debt, and we're printing a lot of money. And our capacity to do that is very much, is limited, first of all, because when there's a sale of a bond, when the government borrows more than it, borrows money because it spends more than it takes in, you have to sell a bond. And the world right now has a lot of US dollar denominated bonds because as the world's reserve currency, they sell, so on them. And they have very bad returns, negative real returns, negative real returns significantly, and so on. So that means that more bonds has to be sold than are bought. And that means that the Federal Reserve is faced with the choice of having to raise the interest rate to curtail borrowing, which slows the economy and hurts the markets, or by filling that difference and producing money, the debt monetization, which produces an inflation in goods, services, and financial assets. So in that regard, that's the United States' position. In China's case, its balance of payments is better. China has displaced the United States as the world's largest trading country. In other words, more exports to other countries. And as a result, it's economically competitive, but it doesn't have the world's reserve currency. It's a real blessing. So the United States has the world's reserve currency, but it is risking it because of this imbalance. So if you look at history, you see that those go slowly, but when they go eventually, they go quickly. So there's a risk of that financially. Then there's the issue of internal order. So I'm just giving you the major ones, but I'll get into some of the other ones too. Right now, there's a lot of internal conflict in the United States, which affects how well it works. In China, there's less internal conflict because it's a more autocratic state, but also they've created this bifurcation of what is political and what is economic in terms of producing that prosperity. So if you stay out of the politics, pretty much, and then you're seeing entrepreneurship, you're seeing the finances of new businesses and so on. And so that internal working, that's subject to different people's interpretations, whether they like it or not, but the internal conflict in terms of those kinds of measures is less. Sorry to pause on that for a second. So these measures, I guess you don't want to sort of romanticize any one measure or something like that, over-interpret any one measure, but is internal conflict always a bad thing? Is it a complicated calculation? Or do you kind of, the way we think about these measures that you've presented, we should be thinking like the higher, the better, the lower, the worse, or I mean, of course, depending on the measure. Well, in many cases, the conflict that produces the revolution produces revolutionary changes that lead to resolutions and lead to new starts. And so their short-term, a short-term civil war is a hellacious experience. And at the same time, it can be the transition to a new beginning. Also, there are different types of conflict. Competition, which makes things, makes everything better, is a productive conflict, whereas destructive conflicts are not good over the short time. So that's how those go. So within each measure, the story is complicated. Yeah, but my measures are sort of clear, meaning how much political conflict, how much social conflict. In other words, you can measure conflict, you can measure fighting, you can measure crime rates, you can measure lots of different ways of conflict. So the measures are a composite of different types of internal conflict. What are some other interesting measures, maybe if you can also mention, like for me in particular, interest is education and innovation. Yes, the classic cycle, the most important leading indicator is the quality of education. Most importantly, broad-based education drawn from the largest population because you can never tell who the talent is going to be, where they're gonna come from. So for example, if you look at the Chinese dynasties, the great Chinese dynasties and the Confucian approach, it was meritocratic of everybody could sit for exams and so on, broad base of drawing in the populations. And you see that if you go across societies because that draws on the largest number of population to get education. And it also, that creates a reality and a perception that the system is fair, equal opportunity, not just one of privilege. And that helps to create social stability. But education is not just education in understanding facts and so on, it is education in civility of how to behave together. And so if they're smart, they understand how to be productive because they work well together and they're productive. And then that leads to the next stage. You can see in the lines in the charts, I plotted these so that you could see in a typical cycle, you could see that education is the long leading indicator. And then you could see, as you mentioned, that what you see is inventiveness and technology measures then follow. And you see then also competitiveness and world markets follows. For example, in the early stages of a cycle, the industries that they go into tend to be very basic industry because they have cheap labor, something like textiles and simple manufactured goods and so on. But as the education rises, then they move up the value chain to greater technologies and so on, which raises incomes and raises productivity. So yes, those, and as you say, there are 18 different measures like that, but education and then civility and the inventiveness. So you see it reflected in who's inventing what. And that corresponds then who's trading with, who's a big trading country and where's the value of economic output and what are per capita incomes. They all follow those arcs. Yeah, like you said, the fascinating thing about your book, so there's philosophy, there's wisdom, but there's plots. Yeah, you can see it. So it's not just your opinion. It's kind of like you can interpret it any way you like, but you're just giving a lot of your own insights along with the numbers. If you were to look at the American nation, the American empire, and the trajectories looking into the future, given these measures, what is the trajectory that leads to the collapse of the American empire based on these measures? What are the concerning indicators? And if those break down further, what does that look like? Well, all of those indicators are concerning, maybe except for one, which is technology, the technology niche. Although even in that area, the United States is improving at a slower rate than is China for various advantages that they have there. They put out about eight times as many computer engineers, they have free data, and so on. But if you look at them, so the financial is a concern. The internal order, disorder, is a concern. Then if you look at education levels, the United States is losing its educational advantage. If you were to compare it with China, if you take general public education in the United States, it's deteriorated tremendously, even in comparison to developed countries. There are scores, PISA scores, and so on, and it's something like 38th in the world or something, and that was a big plunge, average public education. If you look at the best universities in the world, the United States is unique in having the best universities in the world, so there are these privileged spots that are excellent, uniquely excellent. So when you look at the comparison, education in China is improving rapidly, and the quantity is, a quantity of educated people in the areas that they're moving in is greater, and the resources that they're putting behind it is greater, and so you see the results are greater, but it's sort of along the lines that I'm dealing with. If you were to follow through in terms of actual productions, I think you know in terms of technologies, there are some areas that the United States is in a lead at the moment. There's some areas that China's in a lead, but China's gaining very quickly. When I first went to China, 1984, I would bring $10 calculators, and I gave them away as gifts to high-ranking people, and they thought they were miracle devices. Right now, in terms of areas like quantum computing and AI and many areas, you have a race going on, and so if you take the trajectory of the competitiveness, not just look at the current level, you have a situation where they're improving at a much faster rate. This is all good for the world if the world can get along, and the main thing I think is, how do you have a healthy world, and how do you have a strong economy, and how do you have a strong situation? Is be strong. The United States' war is with itself. That's the main war. You know, it's very simple in history. Be financially sound, earn more than you spend, and be strong in these ways, and pretty much everything will take care of itself. But you make it sound simple, of course, because there's a momentum when things degrade, when the education system degrades, when you start borrowing. I mean, all of these indicators, once they start going down, there's a momentum to it, so it's hard to reverse it. Right, and there are circumstances that you're then in. For example, indebtedness. It's politically desirable for those to borrow money and spend, because their constituencies only look at what they get. And when they get a lot, they don't pay attention to the balance sheet and how much debt is on the books. So it's always better to borrow, spend, and then leave the cleanup to the next guy. And so you inherit a lot. You inherited, as a new president enters in, or new legislators, they have a lot of debt, they have a broken down infrastructure, they don't have enough money to fix that. And so that's the lay of the land that the prior generations put you in, and there you are. And so that's right. It's difficult, because when you start to think, okay, what's healthy? Well, earn more than you spend. Well, that's not so easy, because, you know, what does that mean? Go earn more? I mean, okay, that's not so easy. Spend less? That isn't gonna work. So now what do you do? Okay, you have this debt that you then monetize, and that's why it's classic. So yes, that's why these cycles occur, because what has created before, what happened before created the lay of the land that is then increasingly difficult to deal with. So what can great leaders do in this moment? I mean, maybe, my sense is leadership is crucial here. So for example, to do very large projects and invest in the education system, that sort of try to fix the fundamentals, or maybe invest more and more into the innovation and the development of new technologies and so on. It feels like that just doesn't happen organically. So you have to have strong leaders that convince the populace of the importance of these ideas. Well, I completely agree with your list. What we have is a situation where everybody has their opinions, and they have to sort of get them exactly right, and they all fight with each other about whether their opinions. So the most important thing is that we become bipartisan so that we don't, and we get over our differences. I would have a bipartisan cabinet. I would draw upon members of both parties, the moderates, who are going to be able to work together. So as then we have one country, and then we deal with those in a means that works for the majority of the people in the middle rather than the polarity. I think our greatest risk is in not being able to do that. So I would say that's of paramount importance because we have the resources. Wealth, real wealth, and science, and everything has never been better than it is. But the notion is that it has to work for the majority of people, and we have to keep it being productive. So that group has got to calmly and knowledgeably work together so that they increase the size of the pie, and they create broad-based prosperity. So that is of paramount importance. Whatever they do, if they do it that way, I can say I'm happy about because that other alternative is the really scary alternative. So the scary alternative, the different ways it has evolved throughout history, some of it has led to wars. What are the future trajectories that lead to a potential war with China? Cold War or hot war? Is this something you think about? Is this something you're worried about? Yeah, I'd like to talk about both wars. So the war with China, as I say, there are five kinds of wars. There's a trade war, technology war, geopolitical influence war, capital war, and military war. As far as military war goes, I think it's only a Taiwan issue, but that's a big issue. And we could talk about that for a minute. But those others, they'll be rough competitions, and we'll have that type of evolution over a period of time. That's what that war looks like. Taiwan has been for a long time a sovereignty issue to China. And it has its roots in what's called the 100 years of humiliation. From the 1840s to 1949, foreign powers came in, took advantage of China. They had the Opium Wars and such times. And that represented the 100 years of humiliation. And Taiwan represents, is their sovereignty and their important thing. And 50 years ago, starting 50 years ago, there was an agreement that there is one China and Taiwan is part of China. And that there would be peaceful reunification. The peaceful reunification hasn't happened. And in their view, that's a very big issue. And so it's a big contentious issue. And that could produce a military war, could produce a military accident, it's a very tense situation. And if we had a military war, God help us, because of the capacity in all different new ways to inflict harm on each other. But anyway, that's that. If you don't have that military war, you'll have the competition between those other kinds of wars and whoever is strongest in those areas will win. Where do you put cyber war within the five? Well, cyber war is a military war. I'm assuming the type of cyber war that you're referring to is that which is used to inflict pain on the other party through cyber. So cyber wars, you'll see cyber war, you could see space war, you can see drone warfare, new types of warfare, not just the traditional and nuclear type of warfare. But you could see any of the above. Okay. What are the defining characteristics? What are the interesting things about Xi Jinping, the president of China, as a leader on the world stage? His father was a early leader. He was himself, in the Cultural Revolution at times, treated brutally. And during that period of time, it was very, very difficult. And he came up through the ranks and is a very intelligent man. When he first came to power, as you know, they have two five-year terms, and we're now coming to the end of the second of those five-year terms. When he first came to power, he felt that there should be a lot of reform, and reform meant moving to much more of a market and open economy. When that happened, him coming in, I had some contact with economic policy makers, but in the circumstances then, were that five major banks lent to state-owned enterprises and local governments with implied government guarantees. And so there was not control of that, and the movement to a more of a market economy, and the development of markets was a primary. And also, the dealing with the corruption issue. There was a lot of corruption prior to that, and that was viewed as an existential threat to the system. So that became the primary objective. And then as time progressed over those 10 years, there was a lot of changing in the world, their financial circumstances, opening many, many other markets, they particularly getting money to small and medium-sized enterprises, and developing a lending system, and then establishing controls on it. So right now, there's a vibrant capital markets. You can raise capital, you can be an entrepreneur, you can become a billionaire in the capital markets. And they developed the markets to be the second largest capital markets. At the same time, they had to deal with their rising debt issue, which they began to deal with really about four years ago, when the second term began. And then Liu He became the vice premier, responsible for that, and to deal with those issues. So you see right now that what's happening is the dealing with the real estate bubble. There was a development in real estate, a bubble, which produced a lot of unproductive lending. And Xi Jinping said, houses are meant to live in, not to speculate on. And so that was wasteful. So they established what they call three red lines, which are financial ratios, that the property developers had to live within. And that is then causing the adjustments that are going on now, which in my view are very healthy, because whenever there's bankruptcies and so on, the most in the public think, okay, that's a problem. It's in many cases really a cleaning up of bad debts and bad practices. And so that's what's going on. So that's, let's say, economically. At the same time, there is the changing relationships, the changing world order, the changing relationships with the United States and other countries, which is becoming much less cooperative and much more warlike, much more confrontational. Those two things, the domestic debt problem and the domestic, has led to what's called core, what they call core leadership, which means a leadership more around him that is less challenging, because they believe in history that during very difficult times, a more centrally controlled decision-making process lends itself better than to a more fragmented political contentious project. And that's basically what's going on now. You said it very eloquently, but you mean the leadership is surrounded by yes men and there's a lot of centralized control. That characterization is much more black and white than it really is. But it leans towards that direction. Like, for example, of the standing members of the Politburo, four are more allied to him, three are less so. You have to understand that it's kind of a collective leadership at the top. And then, of course, there's just jockeying for power in a highly political sense at the top. But no one leader can be successful against all those powers at the top. So it's very politically negotiating. It's very much more like if you put in the United States the Democrats and the Republicans and they had to be in the same government and they work it out, it's kind of something like that. And then, so that's that struggle, but it's an internal struggle. Where do you put the importance of some of these ideas at the founding of the United States? When then, now we're talking about it at the context of China, the freedom of speech freedoms. What China is doing with the central management of a lot of things, it's enabling a lot of growth, but it's also limiting people on the very basic level in terms of freedom, the kind of freedom that I think can lead to entrepreneurship, to starting new businesses, to having big dreams and chasing those dreams and then creating totally new things in whatever the space, maybe in technology, in business, in whatever. How important is that as a metric for society? Well, they have a view which is the idea of a dialectic which means that two things are at, that everything comes with pros and cons and two opposites exist. And you want the benefits of those two opposites and how do you deal with the benefits of those two opposites? So, let's say you want the capital markets because it gets money into the hands of the entrepreneurs who are motivated, they build fortunes, and that drives an economy to do very well. And at the same time, it produces the other problems, the wealth gaps, the other problems, then the debt cycle that we're talking about and so on. And Deng Xiaoping, how do you reconcile communism and the market economy and the capital markets? And he famously said, and it doesn't matter if it's a white cat or a black cat, just as long as it catches mice. In other words, if it works in making the country richer, then that becomes the objective and then they move that along. So, there are these conflicts. And one of the leaders described it to me as follows, because it's confusion and it goes back over a period of time. There's a hierarchy and it's an extension of the family, he described it. And he said, the United States is a country of individuals and individualism. And that is its vibrancy that we see. The individual rights to speak up, the individual protection of the individual, individual property rights and all of those things is of paramount importance. And we build our organization. That's why democracy is from the bottom up or even a company will get together and will be partners to prosper together. That is the American approach. He was describing that in China, it's an extension of the Confucian family, essentially. And so, it's almost like there's a hierarchy. And so, what they think about is the common good, not the individualism. So, for example, if they want a high-speed rail to go from one place to another, and that's best in the common good, then the individual protections that would stand in the way of doing that would be of secondary concern. So, that notion of controlling. So, for example, what they're doing with video games. They control what type of video games and how many hours a day kids can be on video games operating in that way because they believe that that's good for the society and that's very controlling. In the United States, I think probably most parents would say, leave it to me, and it's a matter between me and my kids. The same thing has to do with data. In other words, in the United States, who controls the data? Does the company control the data? Do you individually control the data? And so, the inclination would be to figure that out, but nobody would say that the government is going to control the data because of our inclination of really anti-government control. In China, it would be that the government will control the data because that's going to be best for the society, and it depends who you trust. So, that difference in philosophy is very much at the heart of that. As far as your question in terms of effectiveness, it really is, in China's case, it's how you balance the things, right? So, what they're attempting to do is to create a lot of freedom and creativity in areas that are not political, let's say. And so, you see a lot of entrepreneurship, you see a lot of product development, you see a lot of creativity happening in that way. So, the stereotype that you don't see creativity happening is an old stereotype, whereas a lot of creativity is certainly happening. And the system can work well if they can achieve that kind of balance. It's proven to have worked well. Since I started going there in 1984, per capita income, real per capita income, has increased by 26 times. The longevity rate has increased by 10 years. The poverty rate has fallen from 88% to less than 1% in terms of basics like starvation and things. And if you read history, Plato's Republic, he talks about the cycles, democracy and autocratic and the benevolent despot and all of that. Each has their own vulnerability. The vulnerability of democracy, which has been a remarkable, remarkable system, and I don't have to extol the benefits of it, but the vulnerability of it has always been the internal conflict that produces itself as anarchy. In World War II, four democracies chose to be autocracies because there was internal disorder and there was the belief, will somebody bring about order and get control of this situation? That was in Germany, Italy, Japan and Spain. They were parliamentary systems that turned themselves over to that. So both systems have vulnerabilities. I think the main thing that we need to think about is those vulnerabilities. Democracy is an amazing system because the adherence to the rules and the system and the checks and balances is quite amazing and it gives it a flexibility to change without civil wars. But there has to be the respect of the rules. And when you see something like they will not accept elections or they will not accept rules, history has shown when the causes that people are behind are more important to them than the system, the system is in jeopardy. So we have a situation that's very much like that in terms of, let's say, the 2024 elections. I believe that there's a very high chance that neither side will accept losing, for example. And so we have that kind of a situation. So one would hope that one could rise above the disagreements and rely on the system for resolving disagreements. Because if that doesn't happen, then we have our own chaos. So the kind of the trend that started in 2020, or I mean, I suppose it's been there, it's been growing. One representation of this internal disorder has been the growing trend of being skeptical about the results of the election. Well, it started before that. There was the emergence of populism before President Trump was elected. He was basically elected as a populist because there was a large percentage of the population that felt that the system didn't work for them. And he tapped into that. And he was largely elected as a populist leader, first populist leader in a developed country. And so populism began then. And that was a battle of one group against the other group. And so since then, it's been like that and it continued to grow. You've mentioned the vulnerability of democracy, the internal disorder is the vulnerability of democracy. What's the vulnerability of a system like China? Maybe one way to say is put China aside and look at history, look at Soviet Union. What's the vulnerability of a communist type system? Well, I'll call it both communist and autocratic. Depending on how much autocracy. Is that it lacks flexibility. It lacks the ability, but I should deal with them differently. In other words, there's the economic system. The economic system threatens motivation and productivity. So communism or socialism has to be done in a way where you can threaten productivity. Capitalism has, and what I mean by that, I mean free markets and capital markets have been an effective way of allocating resources and also creating the incentives and the resources, providing the resources for the inventiveness of new ideas. And so if I compare that, what the Chinese have done to a large extent is to recognize that and have made a move. That's why the seeming dialectic or the conflict between those two things exist. But anyway, that's it. As far as an autocratic system, rather than one man, one vote from the population up, the risks of the autocratic system is that there's enough discontent that arises, that the system doesn't have the flexibility and that rather than bending, it breaks. That's the big risk. The notion of trying to control a population if there's that rather than giving it the flexibility. So that would be the big risk of the autocratic system. What's the human, because you mentioned like the top gets bigger with the empires and you start taking things for granted. Is some of this just human nature? So the concern with China, with autocratic nations, the concern with the Third Reich, the Soviet Union, was that fundamentally at the individual level, the humans involved at the top, they start becoming, they're starting to lose touch with the reality in a way that no longer makes them, I guess that's the representation, the flexibility that you're referring to. Well, I mean, in a democracy, you could change. You can go as far left or as far right. You can change the leaders easily. And so the people don't become, they pretty much only have themselves to blame. And one of the problems of that is they may not choose the best leaders, but they have that flexibility. So vote and you get what you wanted. In the case of the autocratic, let's say leaders, and then the movement from democracies to autocracies, what you see normally that movement is that one of the systems is not working. Let's say the democracy is not effectively, everybody's arguing with each other and nobody's getting anything done. And like Mussolini, the trains are not running on time. And that would be the example. Geez, this place has gotten chaotic. Will somebody get to control? And then you get the autocratic, and then he's autocratic enough to boss people around. And then you follow those kinds of orders. And it's like maybe a CEO in a powerful company going around and that could work well or it could work badly. Most companies are run as like autocracies in a sense. There's the hierarchy and the command economy and that kind of thing. And that can work well or not. But then quite often when you get the populist autocratic, their personality is something that they wanna fight and they become more nationalistic and they tend to become more militaristic. And human nature at that stage lends itself to fighting. There's an arc here that when we think of a country and we say we, and we think of a country, it's not true, it's not like that. There are individuals who change. One generation dies and another generation comes along. And one of those arcs is that the ones who have been through war don't wanna go to war and are more happily willing to abide by whatever the rules are. As you get farther along into that cycle and you get a new generation and they forget about wars and the horrors of wars, then they want to fight. And so you're seeing right now the emergent of fight for right. And what that means is you see it internally. Fight, where are you, and fight for that thing. And they mean fight. And then externally, fight. Are you going to be the strong one who will fight and win? And that develops on both sides, this fight and win. And each side is cheering each other on into a war. But that comes by those who really have not experienced war because it comes in their part of their lifetime. Humans are fascinating. Humans are fascinating. And by the way, human nature has not changed over the thousands of years. So it's so interesting, because in doing this study, and it comes across in the study, it's like watching the same movie over and over again. You see the arc and you see it happen over and over again. The only things that seem to change are the clothes people wear and the technologies they use. -. Yeah, and then somebody probably will disagree with you about the clothes. Maybe there's also cycles within fashions. Maybe we're not even creative there. What do you make of Russia and Vladimir Putin? What do you think about Putin as a leader, as a human being on this world stage within the context of the cycles of empires? What do you think about? Well, Putin came to power at the failure of Russia's last order. So there was the end of communism, and there was the development of the market economy, the collapse of the Soviet Union. And at that time, he was appointed by Yeltsin, who was an alcoholic and had problems managing and was put into power. And the conditions in the Russia were, there was anarchy, there was no money. It had the classic end of cycle ingredients. It was broke, it was people were fighting with each other, it was in the anarchy, and that's when he came to power. And there were not institutions. The whole thing had collapsed, and it was not effective ministry of education, ministry of anything. And so the idea was that they needed 25 years of stability, and they needed a democracy, and they needed the improvement of capital markets. So he's been in that position as a, I guess I would call him a semi-autocratic leader in that from all indications, he would respect the democracy, and he's very popular. He's won democratic elections because he's been a strong leader, and he's brought peace and stability to Russia after the breakup of the Soviet Union. And he's a strong leader in pursuit of the country's interests in a way where Russia is not a significant economic power, but it is a significant military power. So the issues, and then there's a strong alliance between Russia and China now. So that's kind of the lay of the land. And then there are sensitivities. The Ukraine issue is a sensitivity because there are a lot of Russians who live in the Ukraine, and there's also the issue of NATO on their border. So there are those kinds of things, and he has military power, and he has a strong alliance with China. And I guess that's my best summary of what his position is. Strong leader, popular. These are not subjective interpretations. These are objective interpretations. Yeah, it's interesting just in this conversation, you're not sort of doing the usual criticism of any one particular system. You're looking at these systems from the perspective of history. You're just describing how they work. It's oftentimes when you talk about what Russia is today, or what the Soviet Union was, or what China is today, is you start to criticize, well, they do this kind of censorship, or they do this kind of, they limit freedoms in this kind of way. But you're just kind of describing this as a nation with ideas, what they think is right. This is how they hope to get it to work. This is why it's working. This is what's not working. Here's metrics that show that it's not working. I think that's a refreshing way to think about it. It's easy, though, I mean, you got some criticism saying that I think China's a strict parent. You know, some people criticize these countries for doing, so for violating human rights, I suppose there's some people that criticize the United States for violating human rights. But what are your thoughts on the world stage today about some of the behaviors of this government in terms of respecting the rights, the basic rights of human beings? You described accurately how I just tried to look at things in a non, I don't want to impute my values, on anybody, I mean, there are intolerable things, so I'm not saying there aren't intolerable things. But one of the great things of being an American here is that I grew up with all different nationalities having all different points of view and all different religions and all different ways of operating. And I've come to treasure the fact that that is, you know, what's their business is their business. And then the question is, where do you cross the line under what circumstances that others have got to do it my way? And then when you do it internationally, the issue of what is a sovereign state, you know, which, as I say, in the piece of Westphalia, and you have borders, and then when do you cross the line, that my way of doing things has got to be their way of doing things, or what are the various rights? And so that's a very delicate question, or a very difficult question. And we all have responsibilities to different parties, and we all have different levels of knowledge about those particular things. So for example, as an international investor, I have a responsibility to my investors. Those who run companies have a responsibility to theirs of how do they run that. So if you're taking Nike, or Snickers, and so on, and Americans can decide whether they wanna buy Chinese products or not buy Chinese products, we are all faced with those types of choices. So you have, what do you wanna do in your constituency, and you have your choices. And then beyond that, in many cases, the issues are quite complex, like there are geopolitical questions that enter into it. So, and then I believe that if you disconnect it, if all those entities, like myself, the businesses, doing business with China, disconnected, I think that that would be disastrous, economically disastrous, and it would also be, reduce the understanding that comes from working together, that helps to reduce wars. And so these are all complicated. So what we do is, and who makes it, my opinion matters the most. Why should it be my opinion that matters the most in making that decision? So I largely look at the government guidance that I get not only from my own government, but from the other governments, and I follow the rules. I'm in 40, we invest in 40 countries, and we wanna do that in the best way to provide the diversified portfolio, and we sort of need that. Every one of those countries has similar complexities. There are always one issue or another, and there's only so much that we really understand about all of those issues, so we rely largely on the guidance that we get. Yeah, you have to empathize and show respect to the culture of the place, the way things are done. You don't necessarily, the way you heal relationships between nations, like you said, you work together, and that requires kind of to listen maybe more than you talk, and I think people in the public sphere talk a lot about China without really listening, without understanding much about China. One of the things that makes me really sad because I know how to speak Russian, and I know how much is lost in translation, it makes me sad that I'll never really get to know the Chinese culture because I'll never really get to know the language, the literature, just talk to regular people. It's not just the government or officials or scientists, just regular folks, get the culture. I think if you don't understand the culture, just the basics of the human nature, what people love about their country, about their family, what kind of hopes they have, what kind of values they have, without that, you're not gonna be able to fully connect with them, and you have to do that first to have a chance of building a good world. I couldn't agree with you more. I was very lucky because, as I say, since 1984, so for more than half of my life, I've been going there, and the common people, and all sorts of people, and I've got to meet them. I don't speak the language, but a combination of through translators or them speaking English and being in situations, I had my son go to school, a local school, and we developed those kinds of understandings. I think that, but the not wanting to know the other perspective is the thing that's most scary. Like I'm right now in the middle, and all I wanna try to do is to help mutual understanding. You're right, if there were questions probing me, asking me, what is it? I'm not on one side or another. I don't wanna be on one side or another. I believe that each has their right within there to approach their different culture in their own way. So many ways you gave an example. If they're not doing harm to others. But that issue of trying to understand is so much better. That doesn't mean agree with. If you are wanting to out clever and out compete somebody, it still pays to understand what they're thinking. So to achieve understanding of what they're thinking, even if you wanna go to war with them, that understanding is the best thing to have. What we have now is a situation in which there's an enemy mentality, and that means that anything that seems to be like understanding, or conveying understanding, seems to mistakenly create the notion of I'm on their side in a war. And that's kind of a dangerous thing, because there's a momentum here to fight. Henry Kissinger praises your new book, and you thank him in it, in the dedication. What's your relationship like with him? What makes him interesting? Maybe what makes him controversial? What makes him such a central figure in history? First, most importantly, he's unique about seeing things through all the other's eyes. So if you were, it's like there's a chess game. I mean, I think geopolitics is like a chess game, but with multiple chess players playing the same game. So imagine there are six people around playing the chess game, and he could sit in each seat, and he could know how they see it, okay? And see it in a calm way of how they see it. He's unique in that way. He's 98 years old, and he's equally able to do that. And he has a background in which he's a historian, so he really understands history super terrifically. He doesn't understand economic history as much, so that's why, to some extent, we enjoy having a conversation, because he's interested in the economic piece he doesn't know, and I'm so interested in the geopolitical piece that I don't know as well. But anyway, he's able to do that, but not only a historian, but a practitioner. So when you go from an academic to a practitioner, who has that talent to see things through others' eyes in an objective way, and to be strategic rather than just tactical, that's a very special person, and that's why Henry is, to me, a very special person. Yeah, he's lived a fascinating life. Just all of the world events he's been involved in is fascinating, and like you said, that's such an interesting skill to have, to consider what are the concerns, the hope, the dreams, the fears of all the people at the table. What are they thinking? I find that people don't, once again, don't do that enough when it's the obvious thing you should be doing, whether it's business deals or political negotiation or geopolitical negotiation. I'm often surprised, again, sorry to go to the Russian thing because I hear Putin talk in Russian, and you start to infer certain intentions, like not the trivial stuff, like the human being. What is that human being hoping for himself, for his country, for his close in the circle, for the bigger, and I just see that that's often just lost in translation. I just see American leaders talking to Putin, and it's just not, there's not a connection. Absolutely, I know exactly what you're talking about. It has never failed that in my listening to a conversation, or even reading a speech, and you see then it reported, inevitably, the reporter picks some headline characterization that has very little to do with what was really happening, but might be a headline grabber that's at some kind of distortion, and there's a lack of understanding of really what's going on. If it's okay, let me ask you a couple questions about cryptocurrency. You've had a few opinions about Bitcoin over the years. What are your thoughts about Bitcoin today, its role in the global financial system and just in human society in general? Well, the evolution of Bitcoin over the years is one of the things that has influenced changes in my view. It has proven itself. Something like 10, 11 years ago, imagine the programming of this, and here's, you throw it out, and that's the idea. It has not been hacked. It has operated, it has built, it has come an amazing way over that 11 years to be maybe probably the most excited topic among a lot of people, and has been used and is now, has obtained the status of having imputed value. At the same time, it is one of those assets that is an alternative money. I think we're entering an era where there's going to be a competition of monies. Because of the printing of fiat money and the depreciated value, there will be a competition of monies, and Bitcoin is part of that competition, but there'll be many monies, not just crypto monies, but there'll be central bank crypto monies, but there'll be different kinds of monies. And even monies are things that you buy and sell. NFTs can become a money, a type of money. You own it and it's an investment, and you could say I'd rather own it than own Bitcoin. Has Ray Dalio bought any NFTs? Not yet, but only just because, I definitely wanna buy NFTs to just experience them. Like I think I should produce one, and I should. I should've asked that, have you minted an NFT? You probably should, just to know what it's like. Yeah, that's right. This stuff is happening. This stuff is real, and how it operates. But like all new real things, some are gonna go and some are gonna, it's like in the internet in the year 2000, pets.com could've been a great, but maybe pets.com doesn't make it, and who knows. That's the beauty of the competitive system that'll evolve and some things will be treasured and some things will be trashed. But when I look at it, I think we are in an environment of what is an alternative money. A money has two purposes, a medium of exchange and a storehold of wealth. And we are looking for, and it's portable. It's best if it's recognized in other countries. So gold is one of those. So I look at it as an alternative gold, but I look at a number of things as alternative gold. And I think that, and gold is still my favorite because of certain qualities. For example, you can't trace it. In Bitcoin, you can trace who owns it, where it's going and so on. Governments can have that ability to trace it and so on. A gold piece of coin, it's not connected. I think not connected has benefits, particularly in a world where maybe connections can be more risky. And then also gold has been for many thousands of years universally recognized as a source of money. And central banks, it's the third largest source of money in central bank reserves. And I don't think Bitcoin is going to serve those types of purposes and so on. So for various reasons, I prefer gold to the other, but it's a little bit part of my mix. But then you look at it, it hit, I think, 69,000 this year is the high Bitcoin hit. Do you think it's possible, you mentioned gold, do you think it's possible it reaches very high numbers, like one million that some people talk about? I don't think that's possible because the way I look at it is there's a certain amount of, certain amount of it. And there's a certain amount of gold. I'll use gold as a benchmark. The amount of it is worth about $1 trillion. Total crypto is about 2.2 trillion. But let's say Bitcoin, it's $1 trillion. If you take the amount of money that is in gold that is not used for jewelry purposes and not used by central banks, and I assume Bitcoin won't be used for jewelry purposes or central bank purposes, that amount in gold is about $5 trillion. So right now, if you were to have a portfolio that has gold and crypto, gold and Bitcoin, it's worth about 20% of the value of gold. Do I think it's going to be worth more than gold in terms of that mix? I don't think it'll be worth more than gold. But let's say it became worth as much as gold. I don't believe it will be. I think that 20% sounds kind of about right. I really don't know what the right answer is. And then there's the question of what is all of that pool of money, that let's say gold and gold equivalents relative to everything else. Does it go from, you know, let's call it six, seven, eight trillion to 16 trillion? Maybe it could double. It depends what it is in the world environment. But basically, if you use gold as a measure, there's no, it just makes no sense that it's going to be used that much more. Am I sure about that? I'm not sure about anything. But logically, it seems to me that there's a limitation on its price in relationship to other things that are like it. Let me ask for your deep financial analysis on a very important issue. I just talked a couple days ago with Elon Musk. He wants to put a literal Dogecoin on the moon. What are your thoughts about Dogecoin? And do you think it'll be the official currency? Maybe a reserve currency on the moon and on Mars? My reaction is, that's cute. I remember Elon, when he first got, he first got his money from PayPal. I think he said to me, it was, he got $180 million, $90 million. He decided to say, why aren't we going to outer space? And he wanted to take a spaceship that would be modified using Russian technology to put a plant and a watering can on the moon, or on Mars, I think it was. And he said, first life on Mars, or first life on that, as an inspiring notion. And so then there's always what's behind it. I have a lot of respect for Elon's ability to do other things behind it. And so I would take that as symbolic, and I'd be asking him what's behind it, what's next. And I'm also just on the topic of Dogecoin and memecoin, and there's some aspect of humor and lightheartedness that's really interesting about the way we communicate with ideas become viral, or how to captivate people with ideas. There's something about taking things too seriously that somehow slows it all down, and it's interesting. That's part of human nature somehow. So like humor is part of this whole thing. You've talked about the importance of writing ideas down. And you have a fascinating- Principles in particular. Principles. And you have this really nice thing in your book where you actually, I mean, there's such a brilliant way, sorry, you have such a brilliant way of highlighting which parts are extra important, and you make them bold. That's a brilliant idea. Let me just ask the high-level question of what's a good system for taking notes? Well, I find that almost everything happens over and over again. And we're in the blizzard of these things happening. And what I found is that if I'm making a decision that after I make the decision usually, or right at the time, if I pause and reflect, and I write my principle down, in other words, principle is sort of a recipe, what would I use to, how would I make that decision? And what are the criteria around it? I find that I make it much more clear, it becomes clearer, and it applies to the next thing that comes along, it'll be that way. Because everything happens over and over and over again. And I think people make the mistake of looking at just the one like it's the first one. I don't know, they have the first problem of this sort, or the first child, or whatever it is. And this has been happening plenty of times. And so if you have the principles, I found that that helped me think more clearly about it, and it helped me communicate better, like why? And so over the years, over the last 30 years or so, that's what I've done. I did it originally to communicate very well with the people I work with. I set up my company, and it was very important to have good communication. And then we could debate the principles, and so that's the process. I urge people to do that. There are many excellent decision makers, and I just wish that they wrote down their principles. So for example, we talk about Henry Kissinger, and his new book is gonna come out with a book on leadership. And don't just describe the leaders, describe then what about them were the essential elements to make a good leader under what circumstances. And so if we think about that, then also, then you begin to think in a principled way. And then when you start to think in a principled way, life becomes, it's so much easier to make decisions, and it's so much less confusing, because it's like coming up on a species, and you say, okay, well, what species is it? Not just another, it's a thing. No, what species is it, and how do I deal with that species effectively? And so that's what that is. And so I encourage people to write it down. I wish anybody who's successful wrote down their principles or their recipes for making those types of decisions. So the events of interest here happens over and over and over in similar ways, as you're looking for the patterns, and you're defining the process that's right to respond to those patterns, and you call that the principles. And that allows you to deal with the future effectively. So that codifies the lessons from the past to be able to deal with the future. What advice do you have for young folks today? In high school, in college, thinking about how to live, have a career they can be proud of, or maybe have a life they can be proud of? Know yourself, follow your passion, make your work and passion the same thing while considering the money part, because money will get you freedom and choice and be able to make that. But if you know yourself, feel the pull and pursue that passion. And along those lines, by the way, I found that using personality profile tests has been very helpful. I've used those for about 25 years for people to help to understand themselves and understand each other. So I created a free one that is called Principles U. It's online. It's had remarkable, loving people who've taken it, learn about themselves, but also you can put in somebody else and it'll tell you about your relationship with them. That's like 30 minutes, it's a quick discovery. But the main thing is to understand on your journey, your hero's journey, that you will have mistakes and you will have weaknesses and to understand those, not fight those, because by understanding mistakes, you will learn not to make mistakes again. I have a principle, which is pain plus reflection equals progress. And so that reflection is important to know yourself, know your pulls, know your weaknesses. And when you also know your weaknesses and the strengths of other people, there are people who have strengths where you're weak and you have strengths where they're weak. And to be able to work well together is the most effective way of achieving success. So yeah, it's that journey and there's a life arc and there's a journey and you wanna make it the best that you can make it. And it's like a video game. It has the challenges and the obstacles and the learning experiences and the temptations and all of that. And the maximizing learning to go where you wanna go to achieve the life you want is the most important. That's kind of maybe a long-winded way of saying it, but to learn, I think I'll try to say it simply. There's a five-step process. Step one is know your goals, know what you're going after. You could have almost anything you want, but you can't have everything you want. And so you have to prioritize. And you move in that direction. On the way to your goals, you're going to encounter your problems and your obstacles. So identifying, no, step two is understanding your problems and your obstacles, identify them. Step three is to diagnose them to get at the root cause of the problem. And that could be many root causes, but it could also be your weaknesses or weaknesses of others, but you have to be objective about them. Once you diagnose them, then you go to step four, which is to design a way to get around them. And then after you have that design, you implement that design. So you have to follow through and do it. And you do that, and that will then produce its new results, which should be better results. I call this kind of the looping process. It's the evolutionary looping process. And you just keep doing that, and you learn over a period of time, and you move in the direction that you want. Last question, and you only have one minute to answer it. You dedicate the book, quote, to my grandchildren and those of their generation who will be participants in the continuation of this story. May the force of evolution be with you. So let me ask, where's this force of evolution taking human civilization, and what in this story that evolution is writing gives you hope? Evolution is a direction toward improvement, and the greatest force is man's capacity to adapt and invent. And so you see in the charts in the book, you see that this upward movement, life expectancy, health, all the things that we think are better, you see there's a chart, and it shows that over a period of time, and you barely see the downturns from depressions and wars in that. That is the greatest power. Man's ability to invent and adapt is evolution, and that's the greatest power, and that is what gives me justifiable hope. And a continuation of that, like we mentioned with Elon, maybe we'll become a multi-planetary species. So not only will we keep creating amazing things here on Earth, we'll keep expanding out into the cosmos. My time horizon doesn't have me analyzing that yet, but I hope so, and I agree that that would be the natural trajectory. So I'm not gonna ask you for the best financial system on Mars. I think we'll focus on Earth for now. Ray, thank you so much for your brilliance, for the books you've written, for the works you've done, for the inspiration of millions. And thank you for spending your valuable time here with me today. Thank you. Thanks for listening to this conversation with Ray Dalio. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Ray Dalio himself. "'Every time you confront something painful, "'you are at a potentially important juncture in your life. "'You have the opportunity to choose "'healthy and painful truth, "'or unhealthy but comfortable delusion.'" Thank you for listening, and hope to see you next time.

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Neal Stephenson: Sci-Fi, Space, Aliens, AI, VR & the Future of Humanity | Lex Fridman Podcast #240

The following is a conversation with Neil Stevenson, a legendary science fiction writer exploring ideas in mathematics, science, cryptography, money, linguistics, philosophy, and virtual reality. From his early book, Snow Crash, to his new one called Termination Shock. He doesn't just write novels. He worked at the space company Blue Origin for many years, including technically being Blue Origin's first employee. He also was the chief futurist at the virtual reality company Magic Leap. This is the Lex Friedman Podcast. To support it, please check out our sponsors in the description. And now, here's my conversation with Neil Stevenson. You write both historical fiction, like World War II in Cryptonomicon, and science fiction, looking both into the past and the future. So let me ask, does history repeat itself? In which way does it repeat itself? In which way does it not? I'm afraid it repeats itself a lot. So I think human nature kind of is what it is. And so we tend to see similar behavior patterns emerging again and again. And so it's kind of the exception rather than the rule when something new happens. What role does technology play in the suppression or in revealing human nature? Well, the standards of living, life expectancy, all that have gotten incredibly better within the last, particularly the last hundred years. I mean, just antibiotics, modern vaccines, electrification, the internet. These are all improvements in most people's standard of living and health and longevity that exceed anything that was seen before in human history. So people are living longer, they're generally healthier, and so on. But again, we still see a lot of the same behavior patterns, some of which are not very attractive. So some of it has to do with the constraints on resources. Presumably with technology, you have less and less constraints on resources. So we get to maybe emphasize the better angels of our nature. And in so doing, does that not potentially fundamentally alter the experience that we have of life on earth? You know, until the last 10 or so years, I would have taken that view, I think. But people will find ways to be divisive and angry if it scratches a kind of psychological itch that they have got. And we used to look at the Weimar Republic, what happened in the economic collapse of Germany prior to the rise of Hitler, World War II, and kind of explain Hitler, at least partially, by just the misery that people were living in at that time. The economic collapse. Yeah, hyperinflation and unemployment and the decline in standard of living. And that sounds like a plausible explanation. But there are economic troubles now, for sure. We had the bank collapse in 2008. And there's stagnation in some people's standards of living. But it's hard to explain what we've seen in this country in the last few years, just strictly on the basis of people are poor and angry and sad. I think they want to be angry. So without being political in a divisive kind of way, can we talk about the lessons you can draw from World War II? This singular event in human history, it seems like. And yet, as you say, history rhymes, at the very least. Yeah. Being who I am, I tend to focus on the curious technological things that happened in conjunction with that war, which may not be where you want to go. Well, there are several things, and sorry to interrupt. So one in crypto, Namakan is more like the Alan Turing side of things, right? And then there's the outside of technology. First of all, there's the tools of war, which is a kind of technology. But then there's just like the human nature, the nature of good and evil. Yeah. Well, so one of the things that emerges from the war and from the extermination camps is that we were never allowed to have, you know, the kind of, you know, the kind of, you know, the kind of illusions anymore about human nature. So you have to learn that lesson to be an educated person. And you have to know that even in a supposedly, you know, enlightened, civilized society, people can become monsters quite easily. So that is for sure the big takeaway. Did you agree with Solzhenitsyn about, what is it, the line between good and evil runs through the heart of every man? Yeah. That all of us are capable? Great line. Yeah. Of evil? I read a good chunk of the Gulag Archipelago when I was a teenager, because my grandfather had it in his house, because he was one of these Americans who was obsessed with the Soviet Union and the Soviet threat and wanted people to be aware of some of what had happened. And so he had those books lying around and, you know, I would read them. And it's a similar kind of parallel story to what happened in Germany during the war, you know, this creation of this system of camps and oppression and lots of troubling behavior. To me, it's a story of how fear and desperation combined with a charismatic leader can lead to evil. But it's also a story of bravery, of love, of brotherhood and sisterhood, and and basically survival. You have like a man's search for meaning, which is the stories of the story of a man in a concentration camp, basically finding beauty in life, even under most extreme conditions. So to me, World War II is not necessarily a bleak view of human nature. It's a little moment of evil that revealed a much bigger good in humanity. So I'm not so sure that it leads me to a pessimistic view of the world, the fact that somebody like Hitler could happen, the fact that a lot of people could follow Hitler and get excited and maybe even love the hate of the other for some moment of time. I think that's all of us are capable of that, but I think all of us also have a capacity for good. And I think, I don't know what you think, but I think we have a greater desire for good than evil. And it seems like that's where technology is very useful, as a guide, as a helping hand. Okay. Can you give me an example, maybe? So I give you examples of futuristic technologies, and I can give you examples of current technologies. Current technologies, knowledge in the form of very basic knowledge, which is like Wikipedia, and search the original dream of Google, that I think is very much a success, which is making the world's information accessible at your fingertips. That kind of technology enables the natural, if this axiom, this assumption, that people want to do good is true, then letting them discover all of the information out there, false information and true information, all of it, and let them explore, that's going to lead to a better world, to better people. Futuristic technologies is, I personally, I mentioned to you offline, sort of love artificial intelligence. And so AI, that's an assistant, that's a guide, like a mentor to you, that you can, in the way that Google searches, but smarter, where you can help send it out and say, this is the direction in which I want to grow. Not authoritarian lecturing down from the algorithm of telling you, this is how you should grow, but almost the opposite, where you use it as an assistant, a servant in your journey towards knowledge. That sounds like an easy thing, but it's actually, from an AI perspective, very difficult. I mean, this is the theme of a book I wrote called The Diamond Age, which talks about a book that essentially does that. And I've been sort of watching people try to come at the problem of building that thing from different directions for, ever since the book came out, basically. And so I kind of have, although I haven't worked on it myself, I do get a sense of the level of difficulty in realizing that goal. So that book is in the 90s, so as Google is coming to be, is essentially, not Google, but the search engine, the initial search engine, and then which gave birth to Google, essentially, in contrast. Right. Yeah, yeah. That was still in the era of AltaVista and Ask Jeeves and multiple different search engines. And yeah, I'm pretty sure I had not heard of Google at that point. That would have been 95, 96. I think the book came out in 94. And then, of course, the social networks followed, which is another form of guidance through the space of information. Yeah. Well, what happens is that these things come along, and then people find ways to game them. And so I saw an interesting thread the other day pointing out that 20 years ago, if you had Googled Pythagorean theorem, chances are you would have been taken directly to a page explaining the Pythagorean theorem. If you do it now, you're probably going to, the top hits are going to be from somebody who's got an angle, who's got a scheme, right? They're like trying to sell you math tutoring, or they're working some kind of marketing plan on you. So the traditional engines become actually less useful over time for their original educational purpose. That doesn't mean that they can't, it shouldn't be replaced by newer and better ones. First of all, to defend the people with the angle, right? They're trying to find business models to fund oftentimes, which is funny you went with Pythagorean, like you went at math, those greedy bastards. Yeah, I know. But it's great. How can we monetize the Pythagorean theorem? Yeah. Well, I mean, education, right? Yeah. Education, right? It has to figure out like people who love math education, for example, love it purely, not purely, but very often love it for itself, for just teaching math. Yeah. But then they start, you know, when coming face to face with, for example, like the YouTube algorithm, they start to try to figure out, okay, how can I make money off of this? The primary goal is still that love of education, but they also want to make that love of education their full-time job. But I see that sort of that dance of humanity with the algorithms as it finds this kind of local pocket of optimality or sub-optimality, whatever. Yeah. It gets stuck in it. It's a pocket of some sort. But I see that pocket is way better than what we had before in the eighties, right? In the nineties before the internet. But like, and now we're now, this is also human nature. We start writing very eloquent articles about how this pocket is clearly a pocket, it's not very good. And we can imagine much better lands far beyond. But the reality is, it's better than before. And now we're waiting for- We have to escape from the local minimum. And you have to wait either for lone geniuses or for some kind of momentum of a group of geniuses that just say, enough is enough. I have an idea. This is how we get out. And it's too easy to be I think, partially because you can get a lot of clicks in your articles, being cynical about being in this pocket. And we were forever stuck in this pocket. And then coming up with this grandiose theory that humanity has finally, like it's collapsing, stuck forever, like a prison in this pocket. But reality, it's just clickbait articles and books until one curious ant comes up with the next pocket. Yeah. Tunnels through the barrier or gets enough energy to jump over the barrier. And eventually we'll be, as you've talked about, we'll colonize the solar system and then we'll be stuck in the solar system. And then people will say, well, we're screwed because when the sun energy runs out, there's no way to get to the next solar system. And so on. It goes on until we colonize the entirety of the observable universe. Yeah. I think getting out of the solar system is going to be a hard one. So can you, you mentioned this, can you elaborate why you think, back to sort of a serious question, why do you think it's hard to get outside of our solar system? It's just an energy calculator. I mean, you can do it slowly whenever you want. But the idea of getting there in one lifetime or multiple, a few lifetimes, is, requires huge amounts of energy to accelerate. And then as soon as you get halfway there, you need to expend an equal amount of energy to decelerate or you'll just go shooting by. And so that means carrying a lot of energy. And there's ideas like Yuri Milner, I think is still funding the idea to use laser propulsion to send something to another star system, a small object, but it'll have no way to slow down as far as I know. They never talk about that part. Like how do we slow down? Yeah. It's a quick flyby. You take a good picture, I guess. Yeah, you better take some good pictures on your way by. So, and that's great if it happens, I'm not knocking it. But the amount of energy that's needed is just staggering. And there's other issues like just how do you maintain an ecosystem for that long in isolation? How do you prevent people from going crazy? What happens if you hit something while traveling at a significant fraction of the speed of light? What about sort of some combination of expanding human lifespan, but also just good old fashioned, stable society on a spaceship? Yeah, yeah. The generation ship. Noah's Ark. Yeah, yeah. No, I think that's the only way. It would have to keep going for a long time. And they might get to where they're going and find a shitty solar system. We can try to do some advanced survey, but I mean, if you get there and all the planets in that solar system are just garbage planets, then it's kind of a big letdown for this like thousand year voyage that you've just been on, right? So, I mean, we have a pretty narrow range of parameters that we need to stay between in order to survive in terms of the gravitational field that we can deal with. So, that sets a bound on the size of the planet and what we need in the way of temperature and atmosphere and so on. So, when you look at all those complications, then basically building sort of exactly the environment we want out of available materials in this solar system starts to look a hell of a lot better. It's hard to make an economic argument, let's say, for making that journey. One of the things I like about the Expanse is the fact that the people who are trying to build the starship to go to the other solar system are doing it for religious reasons. I think that's the only reason that you would do it because economically it just makes more sense to build rotating cylindrical space habitats and make them perfect. Well, isn't everything done for religious reasons? Like, why do we exploration? Like, why do we go to the moon again and do the other things? What is JFK said, it's not because they're easy, but because they're hard. Isn't that kind of a religious reason? I knew a veteran of the Apollo program who once said that the Apollo moon landings were communism's greatest achievement. Yeah, so the conflict between nations is a kind of... Not exactly a religion, but it's what you're talking about. Well, it's a struggle for meaning. I mean, and that meaning isn't found in some kind of... It's hard to find meaning in mathematics. It's found in some kind of... in music and religion, whatever, art. I mean, some people do, but those are probably not enough of them to... Well, people that find meaning in mathematics, they usually find meaning between the lines nevertheless, not in the actual proving some kind of thing. Fair enough, yeah. So from a cost perspective, do you actually see a possible future where we're building these kind of generation ships and just... Why not launch them one a year out like wandering ants out into the galaxy? I have nothing against it. It's just, like I said, it's got a... The motivation to do it has to come from some kind of spiritual or kind of non-tangible calculus. So from a business model perspective, you don't think there's a business model there? No, no way. One of the many fascinating things you've done in your life, you were... At the very beginning, you were the person that convinced Jeff Bezos to start a spaceship company, a space company. You were there at Blue Origin for a few years in the beginning, working on alternate propulsion systems and, at least according to Wikipedia, alternate business models. Yeah, I mean, to go back to the first thing you said, Jeff Bezos is not a guy who required a lot of convincing. He'd been thinking about it since he was five years old, and it was an inevitability. But the idea that kind of got hatched in 1999 was to just do some advanced scouting work, explore the corners of the space of possibilities. And so that's what... That was Blue Operations LLC, which was the precursor to Blue Origin. And so it was a small staff of people that did that for a few years. And I think it was about 2003, 2004 that it swung decisively towards the direction it's been following ever since, which is using basically existing aerospace technologies and models to make chemical fueled rockets for space tourism. I believe, and I continue to believe, that the fact that we use chemical rockets is just an accident of history. It comes out of World War II. So until World War II, rockets are being built on a small scale by people like Robert Goddard. But then Hitler desperately wants to bomb London, but he can't quite reach it. And the Luftwaffe has been kind of neutralized. So he decides he's going to lob warheads into it with rockets, which is a terrible misallocation of resources. It's a terrible idea. So it only could have happened in a dictatorship controlled by a lunatic. But that's the situation that existed. So they built these rockets. That's the V2. And then it's just a complete coincidence that that war ends with atomic bombs being developed in a completely separate super weapon program. And so suddenly the existence of the bombs creates a demand for rockets that didn't exist before. Because if you've got atomic bombs, you need a way to deliver them. You can do it with bombers, but it's a lot better to just hurl them to the other side of the world on the top of a rocket. So suddenly rockets, which had gotten a boost because of Hitler's V2 program, got a much bigger boost during the 50s and 60s. And it is a complete, you're right, for some reason never thought of this. It is an accident of history that nuclear weapons are developed at a similar time. First of all, it's a complete coincidence that nuclear weapons are developed at a similar time. First of all, nuclear weapons didn't have to be developed at the same time as World War II. That's an accident in history. And the fact that, okay, so then Hitler started using rockets. That's an accident. Okay, that's fascinating. It's a fascinating set of coincidences. Yeah. And which is true of a lot of technologies, by the way. But by the time these rockets are kind of working, we've got hydrogen bombs that are so big and so devastating that nobody really wants to use them. But it turns out you can fit a capsule with a couple of people in it into the socket on the end of a missile that was made to hold a hydrogen bomb. Yeah. So we start doing that instead as a proxy for having a war. I'd love to be in the meeting where the first guy brought that up as an idea. It's probably a Russian. Why don't we strap a person to the rocket? Yeah. Yeah. Well, it probably was because they did it first, right? The Russians did it. And they had perhaps less respect for sort of safety protocols. Could be. They're a little bit more willing to sacrifice the life of an astronaut or to risk the life of an astronaut. Could be. Yeah. Yeah. This is basically the story of how, through all of this competition and because of these historical accidents, you know, trillions of R&D dollars and rubles were put into development of chemical rocket technology, which is, you know, now advanced to an incredibly high degree. But there's other ways to make things go really fast, which is all that rockets do. That's all orbit is. It's just going really fast. And because so many nerds are obsessed with space, people have been thinking about alternate schemes for as long as they've been thinking about rockets. And so one of the first things that I learned, kind of trying to explore new possibilities, was that I could put all of my brainpower to work and be creative as I could and invent some idea that I thought was new for making things go fast. And I would always find out that some guy in Russia or somewhere had thought the same idea up 50 years ago and figured out all the math. Yeah. You know. And so at a certain point, you give up on trying to invent completely new ideas and just go poking around trying to find those guys. So there's a number of ideas that we looked at. You know, some are crazier, some are less crazy. But the direction that that company eventually took was chemical rockets. Is there something you can comment on possible ideas? So first of all, I mean, you could use nuclear, so nuclear propulsion. Yeah. So that's, I mean, you've probably heard of Project Orion, which was Freeman Dyson and some of his collaborators had a scheme to power a large space vehicle by detonating atomic bombs behind it. And so one of the other people who was working at Blue Operations during this time was George Dyson, the son of Freeman. And so we knew all about Project Orion. And he found an old film that they'd shot on a beach in La Jolla of a prototype of this that was powered by like lumps of C4. So that was an idea. But for a private company, obtaining a large number of atomic bombs was probably out of scope. So there's more of a theoretical thing. There's a conceptually similar approach using lasers that Freeman worked on with Arthur Kantrowitz and some others, where you take a pulse blazer and you fire it at a vehicle that has a block of ice on the back. And the pulse hits the ice and flashes off a layer of steam that becomes plasma. And plasma is opaque because it conducts. And so being opaque, it then absorbs all of the energy from the laser pulse and gets really hot and just pushes on the back of the block of ice. And then you wait a moment for that to dissipate, and then you do it again. So it would just kind of vibrate its way. Like it sounds really violent, but Freeman said that if you were wearing like rubber-soled tennis shoes standing in this vehicle, you would just feel a mild vibration. So there your source of energy is on the ground and you're getting higher specific impulse than you could get by burning chemicals. Jordan Kerr and others worked on another laser system, the late Dr. Jordan Kerr, that just would heat up a heat exchanger by converging, many converging solid state lasers from the ground. And Kevin Parkin works on a works on a similar scheme that just uses microwaves to do that. We looked at tall towers. I spent a while looking kind of semi-seriously at giant bull whips. What's a bull whip? Just a whip. Just you have them here in Texas, right? Yeah, I understand. But how does that have to do with propulsion? If you think about it, a whip is an incredibly simple primitive object that can break the speed of sound. So it's unbelievable in a way that for thousands of years, people with no technology have been able to accelerate objects through the speed of sound, just through an architectural trick. Just the physics of a moving bend of material in a medium can do this. So that's the thing I still think about from time to time. You can use the same physics to make freestanding loops of chain or other flexible materials that just kind of stand up under their own physics. I mean, it's kind of awesome to imagine. So you imagine using the same kind of physics of a whip, but have at the end of it a spaceship. Yeah, that would detach at the moment of maximum velocity. Why not? Why wouldn't that? So part of my motivation in studying that was to ask that question. It was more almost a symbolic way of saying, look, there's all kinds of physics we haven't explored yet. It's no more crazy than the idea of chemical rockets. It's just that more money's gone into chemical rockets, right? Can I ask you a question on propulsion that's a little bit more out there? So I don't know if you've seen quite a lot of recent articles and reports and so on about UFOs, like the Tic-Tac aircraft. I keep seeing a lot of chatter about it, but I haven't gone deep into it. So the DOD released footage filmed by pilots, and there's a lot of reports about objects that moved in ways they haven't seen before that seem to defy the laws of physics, if we consider the aircraft that we have today. And so the reason I asked you that is because it kind of, to me, whatever the heck it is, it's inspiring for the possibilities of ideas for propulsion. If it's like secret projects from foreign nations, or it's physical phenomena that we don't yet understand, like ball lightning, all those kinds of things. Or if it is aliens or objects from an alien civilization, I most likely believe if it's an object from an alien civilization, it's gotta be a really dumb drone that just got lost. It's definitely not the pinnacle of intelligence. It's like some teenager's- Science fair experiment. Yeah, it just flew for a few centuries out and just landed, and then we humans are all really excited about this wild thing. I mean, what do you think about those, first of all, like the millions of reports of UFOs, right? There's some psychology there that's deeply cultural, but also the possibility of aliens having visited Earth. Yeah, I mean, I'd like to see some better pictures. For the reason I mentioned earlier, having to do with the difficulty of traveling between star systems, it's really hard for me to believe it's aliens. I just can't understand why you would go to all that trouble to transport something across light years and then do what these UFOs are allegedly doing. Like, how is that interesting? How does that justify the trip? So if you travel across those kinds of distances, you'd make a bigger splash? First of all, I would expect that the arrival of these things would be something we'd notice. It's got to decelerate into our solar system by- unless it got here really, really, really slowly. So I guess that's a possibility and just kind of snuck in. So at the end, we would detect some kind of footprint in terms of energy? You would think. So I actually think your idea of a science fair project gone bad is gone bad, you know, it makes more sense in that it would explain why if these things are alien technologies, they're just kind of hanging around our aircraft carriers for no particular reason, like not trying to communicate. Yeah. Can you imagine a scenario where aliens have visited Earth or are visiting Earth and we wouldn't notice it at all? Oh, sure. I mean, if they've got technology to get here, they've probably got technology to conceal the fact that- Oh, they're trying to conceal themselves. I meant more like they're not trying to conceal themselves, but we're just- our cognitive capabilities are like too limited and we are not thinking big enough. We're looking for little green men. We're looking for things that operate at a time scale that's human-like, you know, it's- Yeah, no, I love thinking about ideas like that. That's great science fiction novel fodder, you know, that the aliens are so different that we simply don't see them. I mean, is there, you know, in terms of language, do you think it would be difficult, not aliens visiting us, but traveling to other places to find a common language? You've written about the importance of language in intelligent civilizations. How difficult is the problem to bridge the gap between aliens and humans in terms of language so we're not lost in translation? Yeah, I mean, there's different takes on that depending on how biologically similar they are to us, you know. I mean, there's a school of thought that says basically advanced life has to be carbon-based for just reasons of chemistry. So right away, if you impose that limitation, then you're kind of assuming something that's starting to be biologically similar to us. So if they're about as big as we are and, you know, they kind of move around in space, you know, in a physical body the way we do, then there's probably a way to solve that communication problem. If they're, you know, like beings of pure energy from Star Trek or something like that, then it's a different story. Well, I love thinking about that kind of stuff too. I mean, you know, consciousness itself may be alien. I mean, it could be, like you said, beings of pure energy. I think of life as just complex systems and the kind of forms those complex systems can take seems to be much larger than the particular biological systems we see here on Earth. I have to ask a Twitter question about aliens. Are you ready? This is for Twitter. I'm ready. What would you expect from Twitter? Can humans have sex with aliens? Neil Stevenson. You can pass. I asked a language question. Can they communicate? Yeah. Can they fall in love before sex? That's how it works. So which question am I answering? The sex or the love? I mean, it depends what is more fundamental to relations across intelligent species. Yeah. I mean, you know, sex can mean a lot of things. So, I mean, if you're— Reproduction, right? In Star Trek, in classic Star Trek, you had to really suspend your disbelief to think that Spock was half Vulcan and half human, right? Because that's just not going to work DNA-wise. So if by sex you mean reproductive sex, then I would say no, unless you go to a panspermia kind of theory, which is that humans were seeded onto the planet as part of a galactic program of some sort. And then we're just returning home and hanging out with our old relatives. Distant cousins. Yeah. Yeah. But that doesn't seem plausible. We know that humans had sex with Neanderthals, with Denisovans. So you could think of them as aliens that came from our planet. So that's a kind of data point, I guess. But, you know, if you broaden your definition of sex to mean any kind of gratifying physical interaction, then sure. Right. Dancing. And that's how we get to love. And love can take many forms. Love can certainly take many forms. I have to ask you, in terms of space, just looking at where Blue Origin is, looking at where SpaceX is today, and maybe looking out 10, 20 years out from now, are you impressed of what's happening? We just saw William Shatner go up to space. Yeah, I was just watching his video this morning before I came here. Yeah. Are you impressed of where things stand today? Yeah. I mean, SpaceX in particular has done things that are just unbelievable. And I don't think anyone was anticipating 20 years ago, let's say, when this all started, just the speed with which they'd be able to rack up these incredible achievements. If you've kind of even seen a little bit of how the sausage is made, and sort of the difficulty of doing any kind of space travel, what they've achieved is just unbelievable. What about maybe a question about Elon Musk, even more than Jeff Bezos, he has a very kind of ambitious vision of this project that we're on as a species, of becoming a multi-planetary species, and becoming that quickly, as soon as possible, landing on Mars, colonizing Mars. What do you think of that project? There's two questions to ask. First, the question is, what do you think about the project of colonizing Mars? And second, what do you think about a human being who is so unapologetically ambitious at achieving the impossible, at what a lot of people would say is impossible? I think that colonizing Mars is the kind of goal that's easily stated. It's catchy, it's the kind of thing that can inspire people to get involved in a way that some other programs might not. So I think it's well chosen in that way. I have technical questions about, there's a problem of perchlorates on the surface of Mars that's gonna be big trouble, and there's radiation. This is known. What about business questions? Do you think, because you mentioned going outside of the solar system would best be done for religious reasons. What about colonizing Mars? Can you spin it into a business proposition? It's hard to think of a resource that's on Mars that could be brought back here cheaply enough to compete with stuff we could just dig out of the ground here or grow here. So I don't know if there is a business plan for that, or if it's just strictly, we're gonna go there and see what happens. Maybe again we need communism to get us going, to give us a reason, a little bit of the competition. Well, there's plenty of people who are sufficiently excited by the colonized Mars vision that they're willing to just go all in on it, even if there's not a business plan behind it. So I think it's well chosen. It's just I think it's probably the only approach to take. A lot of the, when white people came to this continent and started colonizing it, there was not a lot of coherent planning. What plans they did have turned out to be terrible plans. Trying to come up with plans that extend decades into the future is a waste of time. So do it for the kind of unexplainable love of the unknown, like the journey towards exploring the unknown and just kind of keep going. Yeah. Well, you saw it with Shatner and his reaction to the flight yesterday. He, for him, that trip was more than worth it just for these intangible reasons. What did he say? I haven't watched the video yet. He was trying to express, talking a lot about the moment where there was a lot of uncertainty about what was going to happen. Yeah. He was trying to express, talking a lot about the moment where suddenly you kind of rise above the thin blue blanket of the atmosphere and you're up into the blackness. That had a huge impact on him. So he was kind of, I wouldn't say groping for words, because he was pretty eloquent, but he was trying to express his feelings about that in a way that is pretty gripping to watch. So you've worked on this kind of stuff, we can go back to 10 years ago, you wrote an essay called Innovation Starvation. You worked on this kind of idea since then. Kind of looking at, maybe a little bit cynically, about our age today and our unwillingness to take on big, risky projects. So in the face of that, what do you think of people like Elon Musk? Because to me, people like that are inspiring and gives you hope in the face of a more kind of pessimistic perspective of our age. Yeah, well, he's clearly willing to tackle big, ambitious projects without a lot of soul searching or trying to make up his mind, right? He's just like, let's dig tunnels under cities, go. Step one, make a joke about it on Twitter, step two, actually do it. Yeah, yeah. And I mean, things have slowed down, our ability to build things at pace is a lot less than it was. And there's reasons for that. We're more concerned with safety and environmental impacts than people were when they were building some of the great public works projects of the mid 20th century. But we're at the point now where even just maintaining the stuff that we've got is such a huge project. And I think that's a big part of it. It's such a huge project that we need to put big resources into it and good minds into it. Or else we're going to be losing things that we take for granted. Do you think that there's a lot to be done in the digital space? That's, we mentioned sort of Wikipedia and knowledge. Don't you think there could be a lot of flourishing in the space of innovation, in terms of innovation in the digital space? Yeah, I mean, I'd like to see that. I think it's where a lot of the brainpower went during the last couple of generations, because people who might previously have been building rockets or other kinds of sort of hard technologies ended up instead going into programming computer science, which is understandable and great. We've got structural problems right now in the way social media works that are pretty severe. And so I certainly hope that we're not 10 years from now, that we're not exactly where we are today when it comes to that stuff. We need to move on. The beautiful thing about problems is they show you how not to do things. Yeah. And they give you, give opportunity to new ideas to flourish and to beat out the ideas of the old, which is a dream for me to see new social media. Yeah. That beats out the ways of the old. So I tend to, you perhaps agree that it's not, that it's impossible to do social media well. Oh, not at all. I mean, I listened to your interview with Jaron a couple of weeks ago, and I know Jaron, and we've talked about this. He went hard on me. He basically said, like, it's impossible. It is very nice. Well, the last time I kind of paid attention to Jaron's thoughts on it, he was thinking in terms of that basically there should be micropayments, such that if I, by clicking the like button on something, I'm essentially giving valuable intellectual property to Facebook or Twitter or whatever. It's not a very large amount of IP, but it's definitely a transfer of information that when they aggregate it is beneficial to them. So, and now I do remember that he, on his interview with you, was talking about, what, data unions or, yeah. Those are a lot of interesting ideas, but for me, the biggest disagreement was in the level of cynicism. He has a distrust and cynicism towards people in Silicon Valley being able to do these kinds of things. And I'm really, okay, when you have a large crowd of people that are doing things the wrong way, you should nevertheless maintain optimism, because what's important is to find the one person in that room that's going to do things the right way. Cynicism is going to completely silence out the whole room. So, he was saying, I've been here a long time. Oh, yeah. I've known, you know, I understand how these folks work. They think they're gods, and they know the right way to do things, and they will tell you the right way to do things. They'll tell you how to do those things, and that kind of hubris is going to always lead you astray when you are the one who's engineering the algorithms. And there's a lot of deep truth to that, because algorithms are powerful, and many people, when given power, do not do the best of things. I mean, most, what is it, the old Lincoln line, if you want to test a man's character, give him power. Yeah. Yes, but that doesn't mean that some people are not able to handle the power, that some people are not able to come up with good ideas that create better social media. Yeah, I didn't interpret Jaron's statements as being entirely cynical and hopeless. I mean, he's definitely raising, you know, issues of concern, but he wouldn't be out, you know, writing the books that he's written and talking about this stuff if he didn't think there was a way. If he didn't think there was hope, yeah. And part of it, as you probably know with Jaron, he just loves a good argument. Yeah. He just loves to have a little bit of fun. Well, I have to ask you about, I mean, we talked about taking all big, bold, risky ideas. So in your new book, Termination Shock, it's set here in Texas. Part of it is, yeah. Yeah. Most of it. Yeah. It's a great place to set it. So in it, the main character, TR McCooligan, a Texas billionaire, oil man, and truck stop magnate decides to solve climate change, to take on climate change by himself. So this is an interesting philosophical exploration of how to solve climate change from a perspective that's perhaps different than we've been thinking about. I wouldn't use the word solve, but let's say ameliorate the temporary effects. But please. Take on. Yeah. Take on the challenge. So it's very interesting, but as, so there's a gradual nature to this process. And I mean, just like in your book, the power of innovation is something that has saved us quite a few times in history. So what role does that play in this gradual process? Right. So ultimately we don't solve the problem until we get the CO2 out of the atmosphere. But that is going to take a while. We're still adding more. We haven't even started to reduce the amount. So. So there's two possibilities inside to reduce the amount that we're putting in the atmosphere. And two is removing what we got in the atmosphere. We have to do both. Right. And those are two different kind of efforts in terms of like what's involved. Because it stays up there. So I think just last week, China announced that they're going to try to level off their CO2 emissions in like 2030. So 2031, they'll only put as much CO2 into the atmosphere as they did in 2030, which is still a lot of CO2. In 2060, they're saying we'll be net zero. So if everyone in the world does that, and the PPM of CO2 in the atmosphere by then is say 450 parts per million, it'll stay at 450 parts per million until we take it out. And taking it out is hard. It's a big... It took us a long time. We had to empty out huge coal mines and oil reservoirs and burn all that stuff. We had to chop down forests and dig up peat bogs in order to create all of that CO2. And so we have to reverse all of those processes somehow in order to remove the CO2 and get it back down, hopefully into the 200 and some parts per million range where it used to be. So how about you get a single Texas billionaire to have a massive gun that blasts huge quantities of sulfur into the upper atmosphere? That's idea number one. This is called solar geoengineering. And we know that it's a possibility on a technical level, because volcanoes have been doing it forever. So many times in human history, we've seen a volcanic eruption that was followed by a global cooling trend that lasted for a couple of years. And one of these things happened, I think in the 60s or 70s in Indonesia. And the Australians sent a plane up into the stratosphere to take some samples of the plume. And when it came back down, the windscreen of the plane had sort of a deposit on it. So one of the Australian scientists licked it and reported that it was painfully acid. So that was our first kind of clue that what was being injected into the stratosphere was sulfur dioxide. And so we know, then Pinatubo came along in the 90s and did this experiment for us. So we know that sulfur in the stratosphere, it forms little spherical droplets of sulfuric acid after it combines with water. And those bounce back some of the sun's rays and reduce the amount of solar energy entering the troposphere, which is where we live. So we know that it works. And we also know that this stuff goes away after a couple of years. So it gradually washes out. And so it's not a permanent thing. Good news, bad news is, good news is it's not permanent. So if you don't like what's happening, you can just stop and wait a couple of years and you'll get back to where you started. And the bad news, if you're in favor of this kind of thing, is that you have to keep doing it forever. So this guy is one of those, he's read these papers, the TR, the character in the book, he knows all this. And all people who are familiar with climate science are, kind of know this, know this, it's a pretty well-established fact. And so he just decides he's going to take action unilaterally and do this. And so there's different ways to get the sulfur up there, but because it's Texas, he builds the biggest gun in the world. It's just six barrels pointed straight up and he begins firing shells loaded with sulfur into the stratosphere. And so the book is about not so much that as how people react to his doing that, what the political ramifications are around the world, because this is a extremely controversial idea and not everyone's on board with it. And even if you are willing to consider using a technological intervention, the fact is that it's going to have different effects on different parts of the world. So some areas may suffer more negatives than positives and they're not going to be happy. So what do you think, so in his case, in TR's case, he can get around getting permission from governments. If we were to look at us facing, outside of the story, us facing climate change, where do you think the solution will come from? Governments working together or from bold billionaire Texans? I'm pretty sure that this kind of intervention is never going to emerge from Western democracies. This kind of, sorry, government coordinate, which option? Solar geoengineering. Solar geoengineering. From a government, from a, like those are, I want to sort of the distinction, one is the idea, the technological idea you're talking about, but two is like who comes up with the idea and agrees on it, governments or individuals. Yeah. If this were to happen, I think it would be either an individual or more likely just a, some government somewhere that just decides it's in their interests to unilaterally do this. And you know, that's not me advocating it. It's just, it's so, it would be comparatively so cheap and easy to implement a solar geoengineering scheme that someone is probably going to do it once things get bad enough. But I don't think that governments will, or Western governments, just because they're not, well, we've seen what happened with vaccines, right? So, you know, getting people to take vaccinations or wear masks, you know, has turned out to be incredibly hard, even though it might save those people's lives. See, I blame, that's not Western, that's, I blame failure of leadership there, of leaders being, not coming off as authentic, not being inspiring, uniting, all those kinds of things. I think that's possible. I think it's just that we've gotten, the leaders we have right now aren't the right people because we've lived through kind of a long stretch of relatively comfortable times. And it feels like and it feels like unfortunate if you just look at history, that hard times make great leaders and easy times make like bureaucrats that are egotistical and greedy and not very interesting and not very bold. Yeah, no, I think that's fair. So, you know, we may be entering one of those interesting times, you know, of hardship in the Chinese curse sense. Yeah. So, so I could be wrong, but I mean, there have been some efforts to explore solar geoengineering. There was a plan to send up some balloons, high altitude balloons to take some measurements in Scandinavia that got squashed by objections from people who lived up there, who were just opposed to the whole program on principle. So we'll see a lot more of that. And it's going to be a hard program to advocate for just because I think people don't quite understand how much carbon dioxide is in the atmosphere and how far we are from even slowing down the rate that we're adding more to say nothing of bringing that number down. We're a long way out from that. Do you see in terms of portfolio of solutions, us becoming a multi-planetary species as part of that, as this also being a motivator for investing some percent of GDP into becoming a multi-planetary species? And what percent should that be, do you think? You know, in a indirect way, maybe, I mean, you know what people will say, which is the same argument that has been leveled against space exploration since the Apollo program, which is why don't we solve our problems here on earth before we spend money going into space. So I've never been a believer in that argument. I think there could be a sense in which the new perspective that could be obtained by thinking about, like if we're thinking about terraforming Mars, changing its atmosphere, making it more amenable to life and survival, you could see that maybe changing people's opinions about terraforming the earth. Yeah. There are some dangerous consequences to this particular idea of blasting software, of geoengineering. What do you make of sort of big, bold ideas that have, that are a double-edged sword? Are all ideas like this, all big ideas like this, they have a, they have the potential to have highly beneficial consequences and a potential to have highly destructive consequences? I wouldn't say all. I think, you know, going back to the, what we were talking about earlier, you know, how technology developed in the 50s and 60s, there was a period of time there when people maybe had unrealistic ideas about new technology and weren't sufficiently attentive to the possible downsides. So we got, and there's a reason why. I mean, there's, you know, in the mid-20th century, we saw, you know, antibiotics, we saw the polio vaccine, we saw just simple things like refrigerators in the home, you know. My grandmother, to her dying day, called the refrigerator the ice box because when she grew up, it was a box with ice in it. So you see all that change and it's largely for the benefit of people. And so if somebody comes along and says, hey, we're going to build nuclear reactors to make energy, or here's a new chemical called DDT that's going to kill mosquitoes, then it's easy to just buy into that and not be alert to the possible downsides. And of course, we know that the way that those early reactors were built and the way that the supply chain was built to create the fuel and deal with the waste was poorly thought out. And we're still dealing with the resulting problems at places like Hanford in the state of Washington. And we know that DDT, although it did kill a lot of insects, also had terrible effects on bird populations. So the kind of backlash that happened in the 70s that is still kind of going on is to sort of assume that everything is a double-edged sword and always to look for... We have to absolutely convince ourselves that the downside isn't going to come back and bite us before we can adopt any new technology. And I think the people are overly sensitized to that now. Yeah, it's funny. Depending on the technology, people are a little bit too terrified of certain technologies, like artificial intelligence is one. My sense is that the things that they're afraid of aren't the things that are likely going to happen in terms of negative things. It's probably impossible to predict exactly the unintended negative consequences. But what's also interesting is for AI as an example, people don't think enough about the positive things. I mean, the same is true with social media. It's very popular now for some reason to talk about all the negative effects of social media. We've immediately forgotten how incredible it is to connect across the world. There's a deep loneliness within all of us. We long to connect and social media, at least in part, enables that even in its current state. And all the negative things we see with social media currently are also in part just revealing the basics of human nature. It didn't make us worse, it's just bringing it to the surface. And step one of solving a problem is bringing it to the surface. The fact that there's a division, the fact that we're easily angered and upset, and all of that, the witch hunts, all those kinds of things, that's human nature. And it just reveals that allowing us to now work on it, it's therapy. And so that's another example of a technology that's just, we're not considering the positive effects now and in the future enough of. I have to ask about, there's a million things I can ask about, but virtual reality, I gotta ask you. You've thought about virtual reality, mixed reality quite a bit. What are the interesting trajectories you see for the proliferation of virtual reality or mixed reality in the next few years? Yeah, so I was at Magically for what, five years? With the best title of all time. Oh, thanks. Chief Futurist? Yeah. Yeah. And so I sort of had a little squad of people in Seattle doing what you might call content R&D. So we're trying to make content for AR, but because it's such a new medium, there's more of an engineering R&D project almost than a creative project. So it was fascinating to see everything that goes into making an AR system that runs. So an AR device, if it's really going to do AR, needs to be running SLAM in real time. And that alone is a big... So for people who don't know, first of all, virtual reality is creating an almost fully artificial world and putting you inside it. Augmented reality, AR, is taking the real world and putting stuff on top of that real world. And when you say SLAM, that means in real time, the device needs to be able to sense, accurately detect everything about that world sufficiently to be able to reconstruct the 3D structure of it so you can put stuff on the 3D structure of it so you can put stuff on top of it. And doing that in real time, presumably not just real time, but in a way that creates a pleasant experience for the human perception system is... Yeah, that's an engineering project. Right. Yeah, well said. And it's just one of the things that the system has to do. It's also tracking your eyes so it knows what you're looking at, how far away what you're looking at is. It's performing all those functions and it's got to keep doing that without burning up the CPU or depleting the battery unreasonably fast. And that's just table stakes. It's just the basic functions of the operating system. And then any content that you want to add has to sit on top of that. It's got to be rendered by the optics at a sufficiently low latency that it looks real and you don't get sick. So it's an amazing thing. And a magically shipped device that can do that in 2019. And they're about to ship the ML2. But I don't know any more about that than anyone else because I don't work there anymore. Does it still to some degree boil down to a killer app, a content question? Like you said, it's kind of a wide open space. Nobody knows exactly what's going to be the compelling thing. So doesn't a super compelling experience of some sort alleviate some of the need to alleviate some of the need for engineering perfection? Well, there's a base layer of engineering that you have to have no matter what. But you're certainly right that people like in the early days of video games put up with kind of low frame rate and what we would now call crappy graphics because they were having so much fun playing Doom or whatever. Even Tetris. Yeah. So for sure that's true. And so I was working on consumer facing content. There was a great team in Wellington, New Zealand that made a game called Dr. Groyd Broads Invaders that realized the potential of AR gaming in a way that I don't think anything else has before or since. And so that was definitely the strategy until April 2020, which is when the company decided to pivot to commercial industrial applications instead. And I haven't seen their financial projections, but I assume they had good reasons for making that strategic decision. It just means that it's no longer necessarily targeted at just end users who want to play a game or be entertained. But it's, you know. That to me from a sort of a dreamer, futurist perspective is heartbreaking because I don't know necessarily from in the VR space, but I see this kind of thing with robotics where to me, the future of robotics is consumer facing and a lot of great roboticists, Boston Dynamics and companies like that are focused on sort of industrial applications. Yeah. Because for financial business reasons. Yeah. No, I can see the parallels for sure. You know, we'll see. It was a fun project. You know, we worked on an app, for example, called Baby Goats, which just populated your room with Baby Goats. That seemed like a killer app right there. Well, we thought highly of the idea for sure. Yes. So, but because of the slam, the system knew, for example, here's a table, here's a little end table. We know the heights, we know how high our animated baby goat can jump. And so our engineers had to build a system for converting the slam primitives into game engine objects that the game, the AIs in the game could navigate around. So, and that ended up shipping as more of a dev kit or a sort of how to, a sample app than as a finished consumer facing. You mean the Baby Goat AI? Yeah. Yeah. That seems to me like a world I could entertain myself for hours just every day coming back home to see a Baby Goat. Yeah. I mean, it was an ambient kind of, it's not a thing that you would sit there and play like a video game. Just life. Yeah. Yeah. But now there's Baby Goats. I mean, what's the purpose of having dogs and cats in your life? Exactly. It's kind of ambient. They're not really helping you do anything, but it's enriching your life. You can go and play fetch or something for a while if you want, but you don't have to. Right. Yeah. So, we worked on that and a bigger project that was more of a storytelling in a fictional universe. The hardware is worth a look. There's still a belief, I just saw it this morning looking at Twitter, that the Magic Leap never shipped anything. But they've been, since 2019, you can go to their website and buy one of these devices anytime you want to spend the money. Yeah. And the new one is coming out, I think, in 2022, so in a few months. What do you think, looking out 50 years from now, what wins? Virtual reality, augmented reality, or physical reality? What wins? Meaning, like, what do people that have financial resources enjoy spending most of their time in? I've always been a fan of AR, and it's kind of an easy answer, because if you're wearing an AR device, you put a bag over your head, it becomes a VR device. If you block out what's really there, then all you're seeing is a VR. But you are, with AR, constrained to kind of operate in something that's similar to physical reality. With VR, you can go into fantastical worlds. True, true. So, there are still issues in those fantastical worlds with motion sickness, right? So, if your body is experiencing acceleration, your inner ear, that differs from what your eye thinks it's seeing, then you'll get sick, unless you're a very unusual person. So, it doesn't mean you can't do it, it's just a constraint that VR designers have to learn to work with. So, do you think it's possible that in the future, we're living mostly in a virtual reality world? Like, we become more and more detached from physical reality? For entertainment, maybe, for certain applications. I'm personally more, I mean, we have to make a distinction between what I would personally find interesting and what might win in the market. So, maybe some people, maybe lots of people would like to spend a huge amount of time in VR. I'm personally more interested in enhancing the experience that I have of the physical world, because the physical world's pretty cool, right? There's a lot to be said for moving around in the real world. Can I ask you, for you personally, to try to play devil's advocate, or to try to construct, to imagine a VR world where you and Neil Stephenson wouldn't want to stay? Not because the physical world all of a sudden became really bad, for some reason, like you're trying to escape it, but literally, it's just more enriching. In the same way, there's a glimmer in your eye when you said you enjoy the physical world. Double up on that glimmer for the virtual reality. Can you imagine such a world? Well, I'll give maybe an example that's a bridge, which is that I like making things. So, I like working in a machine shop and making objects with 3D printers or machines or whatever. So, I've had to learn how to get good at using a CAD program. There's many to choose from. I use one called Fusion 360. I can spend hours in that, trying to create, imagine and create the things I want to create. It's not virtual reality, exactly, but that whole time, my whole field of view is occupied by this monitor that's showing me a window into a three-dimensional space. I'm rotating things around. I'm imagining things. I'm making things. So, that is pretty close to being in virtual reality. Does that thing have to exist for you to experience true joy? Can you stay in Fusion 360 the whole time? Do you have to 3D print it and touch it? Yeah, I mean, that's my game. That's what I'm up to. But, you know, it happens that if you're building a virtual environment, if you're making a game level or creating a virtual set for a film or TV production, the thing that you're designing in the program may never physically exist. And in fact, it's preferable that it doesn't because the whole point of that is to make imaginary things that you couldn't build otherwise. So, I think lots of people spend a good chunk of their working hours in something that's pretty close to VR. It's just that currently the output device happens to be a rectangular object in front of them. You could replace that with a VR headset and they'd be doing the same stuff. There's all kinds of interfaces. For example, I enjoy listening to podcasts or audiobooks. Let's say actually podcasts because there's an intimate human connection in a podcast. It's one way, but you get to learn about the person you're listening to. And that's a real connection. And that's just audio. For a lot of people, that's just audio. And for me, that's just audio as a fan of people. And you kind of a little bit are friends with those people. Yeah. They're in your life. You're listening to them. Yeah. And I mean, they're as far away from real as it gets. There's not even a visual component. It's just audio. But they're as real. If I was on a desert island, my imagination, this thing works pretty good in terms of imagination. It creates a very beautiful world with just audio. Or even just reading books. Exactly. Reading books. Even more so with reading books. Because there's certain mediums which stimulate the imagination more. When you present less, the imagination works more. And that can create really enriching experiences. So I mean, to me, the question is, can you do some of the amazing things that make life amazing in virtual worlds? It seems to me the answer there is obviously yes. Even if I, like you, am attached to a lot of stuff in the physical world, I think I can very readily imagine coming up with some of the same magical experiences in the virtual world. Where you make friends and you can fall in love. Where the source of love in your life is to a much greater degree inside a virtual world. And then love means fulfillment, that means happiness, that's the thing you look forward to. And not some kind of dopamine rush type of love, but like long-lasting friendship. Yeah, yeah. It just depends on what is there in the way of applications, the content. And can it feed you those things? Can it give you those things? Can it give you, like in my example of using the CAD program, it gives me the ability to do something I enjoy, which is imagining things and making things in a particular way. But can we psychoanalyze you for a second? Sure. What exactly do you enjoy? Is there some component of you building the thing where you get to at least a little bit share with others? Like is there a human in the loop outside of you in that picture? Will anyone ever see it? Right. There's a source of your enjoyment, because I would argue that perhaps, like the turtles all the way down, when you get to the bottom turtle, it has to do with sharing with other humans. And if you can then put those humans inside the VR world, then you start to, then you can, okay, for example, you could do it in the physical world, the 3D printing, but you share it in the virtual world, and that's where the source of happiness is. I think, at least speaking for myself, I'm always thinking in terms of an audience. And at some level, I feel like I'm doing this for someone or communicating to someone, even if there's not a specific someone in mind. It could just be an abstract theoretical someone. And it's like another app I spend a lot of time in is Mathematica. Okay. Incredible app. Yeah. Yeah. And when I do a Mathematica notebook, if I'm trying to figure something out, I spend a lot of time typing. My stuff is just a huge blocks of text, just me thinking out loud, and then I'll spend some graphs and calculations and stuff. Because to me, that act of explaining things and commenting helps me understand what I'm doing. And there's kind of an audience, amorphous audience in mind. Yeah. Yeah. Like, I mean, most of this stuff nobody will ever see, and yet I'm creating it as if there were an audience that might read this stuff. Because I have to, that's a necessary constraint that helps me do a better job. What's the, this might be a tricky question to answer, what comes to mind as a particularly beautiful thing that you're proud of that you created inside Mathematica, visualization-wise, or something that just comes to memory, if it's possible to retrieve? So, the thing I've spent the most amount of time on is, I got obsessed a long time ago, was trying to tile the globe with hexagons. Yes. And... An actual globe? Well, any spherical... Any spherical, okay....object, yeah, but with an eye towards putting it on the Earth. And so, and have it be recursive. So, you can have hexagons within hexagons, which is hard, because, and probably a bad idea, because you can't tile a hexagon with smaller hexagons. They don't, they stick out. Got it. So, they're, oh, they stick out. So, there's a, can you do some kind of fractal hexagon situation? Yeah. Yeah. So, it's that, and people who know me are always, now make fun of me for this. So, they'll send me, if they see a picture with hexagons in it, they'll like send me a link, you know, to make fun of me. So, it's some... One of those people, Roger Penrose, or? I think Roger's a little above my level. Well, he's into hexagons as well, and tiling. Yeah. Yeah. So, I did a lot of that, and I thought, you know, it was pretty cool. But, there's some, like, surprisingly intractable problems that keep coming up. Like, you've always got to have some pentagons. Like, if you start with the icosahedron, which is equilateral triangles, which is a logical place to start, you can cover those with hexagons, but every vertex where the triangles come together is a pentagon, has to be a pentagon. Interesting. So, it's all hexagons, and then there's a pentagon at the intersections. Yeah. Yeah. Cool. How'd you figure that out? Is that a known fact? Well, it's just if you look at it, like, just by inspection. It's an obvious thing. Got it. Yeah. So, you can't make that go away. So, any system that you come up with to do this has got to have this exceptions built into it for those 12. You could have quintillions of hexagons, but you've still got to have 12 pentagons somewhere. So, I've blown a hell of a lot of time on that over the years. By the way, a lot of those kind of problems are very difficult to prove something about. Yeah. Yeah. Yeah. And I think Uber did it, because someone, one of my friends who knows of my interest in this and who likes to give me a hard time, sent me a link. This is a couple years ago to some code base that I think came out of Uber, where they had done this. You break down the whole surface of the earth into little hexagons. So, that was a real knife through the heart, but I'll probably come back to it someday. Is there something special about hexagons? Are you interested in all kinds of tiling? Well, I'm interested in all kinds of tiling, but I know my limitations as a math guy. So, hexagons are about my speed. Yeah. Just a sufficient amount of complexity. Yeah. Yeah. But no, tiling is a really interesting problem, both two and three dimensional. Tiling problems are fascinating, and they're one of those ancient puzzles that has attracted brainiacs for centuries. Let me ask you a little bit about AI. What are some likely interesting trajectories for the proliferation of AI in society over the next couple of decades? Do you think about this kind of stuff? I do not think about it a lot because it's a deep topic, and I don't consider myself super well informed about it. And AI seems to be a term that is applied to a lot of different things. So, I've messed around just a tiny little bit with neural nets, with what's it called? PCA, principal component analysis. So, I guess I tend to think in terms of granular bottom-up ideas rather than big picture top-down. Oh, got it. So, like very specific algorithms, like how are they going to, what problem are they going to solve in society such that it has a lot of big ripple effects? See, I mean, we could talk about a particular successful AI systems and success defined in different ways of recent years. So, one is the AI system, which is a very, very simple AI system. It is defined in different ways of recent years. So, one is language models with GPT-3. Most importantly, they're self-supervised, meaning they don't require much supervision from humans, which means they can learn by just reading a huge amount of content created by humans. So, read the internet and from that be able to generate text and do all kinds of things like that. It's possible they have a big enough neural network, it's going to be able to have conversations with humans based on just reading human language. That's an interesting idea. To me, the very interesting idea that people don't think about it as AI because they're kind of dumb currently is actual embodied robots. So, robotics like Boston Dynamics, I have downstairs and upstairs, legged robots. You know, the currently Boston Dynamics robots and most legged robots, most robots period are pretty dumb. Most of the challenges have to do with the actual, first of all, the engineering of making the thing work, getting a sensor suite that allows you to do the same things with Magic Leap, that base layer of like- Where is that stuff? Where am I? And what am I looking at? Yeah. I don't need to deeply understand my surroundings at a level of like, at a level beyond of what will hurt if I run into it. Yeah, yeah. But even that is hard. That's hard, but the thing that I think people don't, in the robotics space, explore enough is the human-robot interaction part of the picture, which is how it makes humans feel, how robots make humans feel. And I think that's going to have a very significant impact in the near future in society, which is the more you integrate AI systems of whatever form into society where humans are in contact with them regularly. So that could be embodied robotics, or that could be social media algorithms. I think that has a very significant impact. And people often think like, AI needs to be super smart to have an impact. I think it needs to be super integrated with society to have an impact. And more and more that's happening, even if they're dumb. Yeah. Yeah, no, I mean, a lot of my exposure to robots is that I'm associated with a combat robotics team, and I've been to a few BattleBots competitions. And that's not, like, in a lot of ways, that's pretty far from the kind of robotics you're talking about, because these robots are remote controlled. They're not autonomous. And so they're pretty simple. But it's interesting to watch people's emotional reactions to different robots. So there was one that was in the last year's season, the 2020 season, called Rusty, that was just, like, put together out of spare parts, and it looked kind of cute. And it became this huge crowd favorite, because you could see it was made of, like, salad bowls and, you know, random pieces of hardware that this guy had, like, scavenged from his farm. And so immediately, people kind of fell in love with this one particular robot, whereas they might, other robots might be like the bad guy in a, if you think of professional wrestling, you know, the heel and the baby face. So people do, for reasons that are hard to understand, form these emotional reactions. And we form narratives in the same way we do when we meet human beings. We tell stories about these objects, and they can be intelligent, and they can be biological, or they can be almost close to inanimate objects. Yeah. And that, to me, is kind of fascinating. And if robots choose to lean into that, it creates an interesting world. If they start using feedback loops to make themselves cuter. Not just cuter, but everything that humans do. Let's not speak harshly of robots. Humans do the same thing. Oh, no, I wasn't meaning it in a... But you're right. Humans, based on feedback, will change their appearance, their dress. Yes, I do this on Instagram all the time. How do I look cuter? That's the fundamental question I ask myself. Yeah. So why wouldn't a robot want to... It's like, oh, wow, people really don't like the quad mount machine gun on top of my turret. Maybe I should get rid of that, and people would feel more at ease. Or lean into it. Be proud of it. Proud of it. Like, you won't take my gun, whatever the saying is, from my dead cold hands. I mean, their personality, adding personality such that you can start to heal, you can start to weave narratives. I think that's a fascinating place where it... There's this feedback loop, like you said, where AI, especially when it's embodied, puts a mirror to ourselves. Just like other humans are close friends, they kind of teach us about ourselves. We teach each other, and through that process, grow close. And to me, it's so fascinating to expand the space of deep, meaningful interactions beyond just humans. That's the opportunity I see with robots and with AI systems. And that's why I don't like... My biggest problem with social media algorithms is the lack of transparency. It's not the existence of the algorithms. It's... Well, there's many things. One is the data. Data should be controlled by the individual, by people themselves. But also the lack of transparency in how the algorithms work. And change your perception of what's real, in hidden ways. In hidden ways. Like, you should be aware, just like when you take, I don't know, if you take psychedelics, you should be aware that you took the psychedelics. It shouldn't be a surprise. And second, you should become a student and a scholar, and there should be research done. There should be open conversation about how your perception has changed. And then you become your own guide in this world of altered perception. Because arguably, none of it is real. You get to choose the flavor of real. I mean, this is something you explore quite a bit. Do you, yourself, think that there is a bottom to it, where there is reality? There's a base layer of reality that physics can explore, and our human perception sort of layers stuff. Is there... Let's go to Plato. Is there such a thing as truth? I lean towards the Platonic view of things. So I believe that mathematical objects have a reality that it's not all made up by human minds. And I don't know where that reality comes from. I can't explain it. But I do think that mathematical objects are discovered and not invented. I did a lot of... Not a lot, but I did some reading of Husserl when I was writing Anathem. And he's a 20th century phenomenologist. And he's writing at the same time as scientists are starting to understand atoms and becoming aware that when we look at this table, it's really just a slab of almost entirely vacuum. And there's a very sparse arrangement of tiny, tiny little particles there occupying that space that interact with each other in such a way that our brains perceive this object. So that's kind of the beginnings of phenomenology. And his stuff is pretty hard to read. You really have to take it in small bites and go a little bit at a time. But he's trying to come to grips with these kinds of questions. How did you come to grips with it? Like, why does this table feel solid? Well, I mean, we're an evolved system that we have biological advantages in knowing where solid objects are. So we've got this system in our head that integrates our perceptions into this coherent view of things. One of the take-homes that I like from Husserl is the idea of intersubjectivity and the idea that the fundamental requirement for us to stay sane is for us to share our perceptions and have them ratified by other — they don't even have to be people — but that a prisoner in solitary confinement might domesticate a mouse or even insects because they perceive the same things that the prisoner perceives. And so convince him that he's not just hallucinating. Yeah, establish a consensus. Yeah. Just establish a consensus. But see, that doesn't mean any of it is real. You just establish a consensus. It could be very distant from something that's real in an engineering sense of real. Like, you could build it using physics. But I think that a valuable application for an AI robot would be just to do nothing except that. Consensus. It just sits there. And if you hear a door slam, you might turn to see what it is. If the robot at the same time turns to look at the door slam, it's ratifying your perception. But isn't that the basis of love? Is when the door slams, you both look, but for deeper things, you both hear the same music and others don't? I mean, isn't that what… Could… That's… by love, I mean depth of human connection. Yeah. Like, that's… or not… You arrive at similar reactions without having to explicitly communicate it. Yeah. But we could start with a robot that listens explicitly for the slam doors. Yeah. But no, I've… Or scary sounds. I can think of… so an example of this is, you know, when I went to college, you know, we'd be sitting at the cafeteria, you know, a bunch of people, you know, eating our dinner together that we had just met, let's say, you know. So a bunch of new people in your life and someone might make a funny remark or a not so funny remark or something would happen and you might then at that moment make eye contact with someone you didn't know at the other end of the table. And in that moment, you would realize this person is reacting, this person heard what I heard. They're reacting the way I reacted. Yeah. Nobody else appears to get the joke or to understand what just happened, but random strangers down there and I, we have this connection. Yeah. And then you build on that. So then the next time something happens, you automatically look at your new friend and they look back at you and before you know it, you know, you're hanging out together. Yeah. Because you know you've already established without even talking to each other that you're on the same wavelength. Yeah. It's seemingly so simple, but so powerful that it's establishing that you're on the same wavelength. Yeah. At some level. Yeah. There's no reason why you and a toaster can't have that. I'm just saying. No. Does this smell burn to you? Exactly. I think it's burn. If a toaster could just say that to you. Yeah. Yeah. Yeah. Cryptonomicon published in 1999, set in the late nineties and involves hackers who build essentially cryptocurrency. Bitcoin white paper came out in 2008. So I have to kind of ask from you looking at this layout of what's been happening in cryptocurrency, the evolution of this technology, how has it rolled out differently than you could have imagined in two ways? One, the technology itself and two, the human side of things, the human stories of the hackers and the financial folks and the powerful and the powerless, the human side of things. Yeah. Well, cryptonomicon is pre Bitcoin. It's pre Satoshi. It's pre blockchain, as you point out. So at that point, I was kind of reacting to what I was seeing among people like the Bay Area cypher punks in Berkeley. There was some, there was a branch here in Austin as well. And a lot of their thinking was so based on the idea that you would have to have a physical region of the earth that was free of government interference. You couldn't achieve that freedom by purely mathematical means on the network. You actually had to have a room somewhere with servers in it that a government couldn't come and meddle with. And so a lot of ideation happened around that view of things that there were efforts to figure out jurisdictions where this might work. There was a lot of interest for a while in Anguilla, which is a Caribbean island that had some unusual jurisdictional properties. There was Sea Land, which is a platform in the North Sea. And so there was a lot of effort that went into finding these physical locations that were deemed kind of safe. And that all goes away with blockchain. It's no longer necessary. And so that really changes the picture in a lot of ways because you no longer have, I mean, from a novelist point of view, the old system was a lot more fun to work with because it gives you a situation where hackers are wandering around in strange parts of the world, you know, trying to set up server rooms. So that's a great storytelling thing. There's still a little bit of that, right, in the modern world, but it's just there's several server rooms as opposed to one centralized one. Yeah. Yeah. And there is the, like, the new wrinkle is the need to do a lot of computation and to keep your GPUs from melting down. So people building things in Iceland or in shipping containers on the bottom of the ocean or whatever. So... But there's still governments involved and there's still, from a novelist perspective, interesting dynamics. With big governments like China and more sort of renegade governments from all over the world trying to contend with this idea of what to do in terms of control and power over these kinds of centers that do the mining of the cryptocurrency. Yeah. So we're in a stage now that kind of goes beyond the initial, like there's the stuff I was describing in Cryptonomicon had a little bit of air about it of the underpants gnomes in that, you know, we're going to build this system and then we'll make money somehow. But the intermediate step was left out. And that is, I think we're now sort of into that phase of the thing where Bitcoin, you know, blockchain exists, people know how it works. Bitcoin and other cryptocurrencies exist, people are using them. And it's sort of like, okay, what now? You know, where does this all lead? So... Do you have a sense of where it all leads? Like, is it possible that the set of technology kind of continues to have transformational effects on not just sort of finance, but who gets to have power in this world? So the decentralization of power. You know, big questions, right? So I guess there's a little bit of the cynic in me thinking that as soon as it becomes important enough, the existing banks and people in power are going to sort of control it. I guess an easy answer is that maybe it won't be a big change in the end. There's a utopian strain sometimes in the way people think about this that I'm not so sure about. There is a technological aspect to Bitcoin and other cryptocurrencies that make it a little easier to pull along the utopian thread. Because it's harder for governments to control Bitcoin. I mean, they have much fewer options. They can ban, they can make it illegal. It's more difficult. So technology here is on the side of the powerless, the voiceless, which is a very interesting idea. Of course, yes, it does have a utopian feel to it, but we have been making progress throughout human history. Maybe this is what progress looks like. There will be the powerful and the greedy and the bureaucrats that take advantage of it, skim off the top kind of thing. But maybe this does give more power to people that haven't had power before in a good way, like distributing power and enabling sort of greater resistance to sort of dictatorships and authoritarian regimes, that kind of thing. And also enabling all kinds of technologies, built on top of it. Ultimately, when you digitize money, money is a kind of speech, or it's a kind of mechanism of how humans interact. And if you make that digital, more and more of the world moves to the digital space. And then you can finally fully live in that virtual reality with the toaster. Yeah. In a lot of ways, I think in that realm of technology, that the money per se is one of the less interesting things you can do with it. So I think cryptographically enforceable contracts and organizations built on those, that seems to me like it's got more potential for change just because we do already have money. And although it's an old system, it's been digitized to a large extent by the stripes and the credit card companies of the world. And I also love the idea of connecting two smart contracts, connecting data, sort of making it more formal, it's like Mathematica, more structured, the integration of data, of weather data, of all kinds of data about the stuff in the world, so they can make contracts between people that's grounded in data. And that's actually getting closer to something like truth, because then you can make agreements based on actual data versus kind of perceptions of data. And if you can formalize, like distribute the power of who gets to tell the story, that's an interesting kind of resistance to, again, the powerful in the space of narrative. Yeah, David Brin has been saying for a while that the only way to settle arguments across the political divide is to make bets. So people can say, the election was stolen, or whatever controversial position they're taking, and they'll keep saying it until you wager real money on it. So maybe there's something there, if you could kind of turn that into a, put a user interface on that. Yeah, have a stake in your divisiveness, in your arguments. Right. Will Dogecoin take over the world? Twitter question. You know, I don't follow the different coins that much. So I don't, I mean, I hear about Dogecoin, and I've kind of followed the story of it. So the interesting aspect of Dogecoin is it, so in contrast to like Bitcoin and Ethereum, which are these serious implementations of cryptocurrency that seek to solve some of the problems that we're talking about with smart contracts and resist the banks and all those kinds of things, Dogecoin operates more in the space of memes and humor, while still doing some of the similar things. And it presents to the world sort of a question of whether memes, whether humor, whether narrative will go a long way in the future, like much farther than some kind of boring old grounded technologies, whether we'll be playing in the space of fun. Like once we built a base of comfort and stability, and like a robust system where everyone has shelter, everyone has food, and the basic needs covered, are we going to then operate in the space of fun? That's what I think about Dogecoin, because it seems like fun spreads faster than anything else. Fun of different kinds, and it can be bad fun, and it could be good fun. Yeah. And so it's a battle of good fun versus bad fun. It goes viral very quickly, when you post something that people find fun to. Yeah, and that's what Dogecoin represents. So there's like, so Bitcoin represents like financial, like serious financial instruments, and then Dogecoin represents fun. And it's interesting to watch the battle go on on the internet to see which wins. This is also like an open question to me of what is the internet? Because fun seems to prevail on the internet. And is that a fundamental property of the internet moving forward when you look 100 years out? Or is this a temporary thing that was true at the birth of the internet, and it's just true for a couple of decades until it fades away, and the adults take over and become serious again? Well, I think the adults took over initially, and then it was later on that people started using it for fun, frivolous things like memes. And I think that's pretty much unstoppable. Yeah. Because even people who are very serious, you know, enjoy sending around a funny picture or something that amuses them. Yeah, I personally think, we spoke about World War II, I think memes will save the world and prevent all future wars. You've been handwriting your work for the past 20 years since writing The Baroque Cycle. What are the pros and cons of handwriting versus typing? For me, I started it as an experiment when I started The Baroque Cycle, because I had noticed that sometimes if I was stuck having a hard time getting started, if I just picked up a pen and started writing, it was easy to go. So I just decided to keep with that. If it got in my way, I didn't like it, I could always just go back to the word processor, it'd be fine. But that never happened. So there's a certain security that comes from knowing that it's ink on paper and there's no operating system crash or software failure that can obliterate it. It's a slower output technique. And so a sentence or a paragraph spends a longer time in the buffer up here before it gets committed to paper, whereas I can type really fast. And so I can slam things out before I've really thought them through. So I think the first draft quality ends up being higher. And then editing, first draft of editing is just faster because instead of trying to move the cursor around or whatever, or hitting the backspace key, I can just draw a line through a word or a sentence or just around a whole paragraph and exit out. And in doing so, I very quickly created an edit, but I've also left behind a record of what the text was prior to the edit. Of course, all the digital versions have those quote unquote features, but their experience is experience is different. Is there a romance to just the physical, you know, the touch of the pen to the paper, doing what has been done for centuries? I think there is. I think there's a, just the simplicity of it and not having any intermediary technology beyond the pen and the paper is just very simple and clean. And so I've got a bunch of fountain pens and I started buying fancy paper from Italy a few years ago because I thought I would be more conservative with it, you know, but it still doesn't, it's still a trivial expenditure. So it doesn't really alter my habits very much. So all that said, once you do type stuff up, you use Emacs. Yeah. I use Emacs, obviously the superior editor. Of course. Let me just ask the ridiculous futuristic question, because Emacs has been around forever. Do you think in 100 years we will still have Emacs in Vim? Or like, pick a, let's say, 50, 100 years, 20 years. Yeah, no, I mean, whenever you're doing anything in Linux, you're spending a lot of time editing little config files and scripts and stuff. And you need to be able to pop in and out of editing those things. And it needs to work, like even if the windowing GUI is dead and all you've got is like a command line, to get out of that problem, you might need to enter an editor and alter a file. So I think on that level, there will always have to be sort of very simple, very simple, well, Emacs isn't very simple, but you know what I mean. There have to be basic editors that you can use from either the command line or a GUI, just for administering systems. Now, how widespread they'll be, there's a certain amount of, what's the story of the, there's the American folk tale of the hammer guy who drives the railroad spikes, John Henry, trying to keep up with the steam hammer. And eventually the steam hammer wins, because he can't drive the spikes fast enough. So there's a sense in which, there's a sense in which, Microsoft, who knows how much they've invested in code, Visual Studio or Apple with Xcode. So they've put huge amounts of money into enhancing their IDEs. And Emacs, in theory, can duplicate all of those features by, if you just have enough Linux hackers writing Emacs Lisp macros. But at some point, it's going to be hard to maintain that level of, to keep up feature for feature. The interesting thing about Emacs just is it lasted a long time. I think you've talked about, there's a certain, like, there's certain fads, certainly in the software engineering space. And it's interesting to think about technologies that sort of last for a very long time. And just kind of being in the, what is it? How do they get by? It's like the cockroaches of software, or the bacteria of software or something. Like this base thing that nobody, everybody's just became reliant on, and they just outlast everything else, and slowly, slowly adjust with the times, with a little bit of a delay, with a little bit of customization by individuals, kind of that. But they're always there in the shadows, and they outlast everybody else. And I wonder if that's, that might be the story for a lot of technologies, especially in the software space. Yeah, shell scripts, all that stuff. You can't run the modern world without a bunch of shell scripts, booting up machines and running things. So, that is going to be a hard thing to replace. And then tech for typesetting that you use, you said. For when I want to print it out, yeah, I just have some simple macros that I use. But then I have to, the publisher put their foot down, and they want it in Word format now. So, years ago, I wrote some macros to convert. And this time, what did I do? Copy-paste? No, I used regular expressions. So, I was to do italics in, you know, you put it in curly brackets, and you do backslash IT, and then you type what you want to type. And that's how you get italics in tech. So, you can create a regular expression that'll look for some text between curly brackets, preceded by backslash IT, and then instead convert that to italics. And Word will do that. Word, if you go deep enough into its search and replace UI... You can do regular expressions....is just reg-eps. Yeah. It's funny that you did that. I mean, I'm sure there's tools that help you with that kind of thing, but the task is sufficiently simple to where you can do a much better job than anybody else's tool can. Yeah, yeah. So... It's a fascinating process. It works fine for me, yeah. And it keeps you from messing around with formatting. Yeah. Like, oh, what if I put this chapter heading, you know, in, you know, a sans serif font? You know, it's just classic wanking. And so, those options are closed off in what I'm doing. Is there advice you could say, what does it take to write a great story? The power of good yarns, good narratives to pull people in is incredible. And I think my sort of amateur theory is that it's an evolutionary development. That if you're, you know, a cave person sitting around a fire in the Rift Valley a million years ago, if you can tell the story of how you escaped from the hyenas, or how Uncle Bob, you know, didn't escape from the hyenas, and if the people listening to you can take that in, and they can build that scenario in their heads, like a kind of virtual reality and see what you're describing, then you've just conferred an incredibly important advantage on the people who've heard that story. Yeah. Right? Yeah. And so, they know a bunch of stuff now about how to stay alive that they could not have learned in any other way. I mean, animals who don't have speech, though, they might warn each other, they might make a sound that says, danger, danger. But as far as we know, they can't tell more complicated stories. So, it's a part of us. Yeah, the collective intelligence seems to be one of the key characteristics of Homo sapiens. The ability to share ideas and hold ideas together in our minds, and storytelling is the fundamental aspect of that. Maybe even language itself is more fundamental. Yeah. Because the language is required to do the storytelling. Or maybe they evolve together, the language is required to do the storytelling. Or maybe they evolve together. Maybe they co-evolve. Yeah. So, I think that you've got to work with that. And I think sometimes it seems like in kind of literary circles that having a lot of plot is a little bit frowned upon as it's pulpy or it's exploitative. But for me, I don't have any compunctions whatsoever about that. I like stories that are grabby and fun and exciting to read. And once you've got one of those going, once you've got a good yarn going, that people will enjoy reading, then you're free to do whatever you want in the frame of that story. But if you don't have that, then you got nothing. What about having like, which you do, a technological scientific rigor, like to the accuracy and as much as possible. How does that add to Bob telling the story? Or telling the story about Bob around the campfire? Well, the main thing that it does is present little details that you might not have come up with on your own. So, if you're just sitting there freely imagining things, your brain probably isn't going to serve up the wealth of details and the resulting complications and surprises that the real world is constantly presenting us with. And so, in my case, if I'm trying to write a story that involves some technology like a rocket or orbital maneuvers or whatever, then delving into that story, or the details, eventually is going to turn up some weird, unexpected thing that gives me material to work with. But also subliminally readers who see that are going to be drawn in more because they're going to find that, oh, I didn't see that coming. You know, it's got some of the complexity and surprise value of the real world. Yeah, it does something. Alex Garland, director who wrote, directed Ex Machina. I think about AI movies and the more care you take in making it accurate, the more compelling the story becomes somehow. I'm not sure what that is. Maybe because it becomes more real to the people writing the story, maybe it just makes you a better writer. The key to any storytelling is getting the readers to suspend their disbelief. And there's all kinds of triggers and little tells that can break that. And once it's broken, it's really hard to get it back. A lot of times that's the end. Somebody will just close the book and not pick it up. I gotta ask you, you've answered this question, but I gotta ask you the most impossible question for an author to answer. But which Neil Stevenson book should one read first? So when people ask me that, I usually ask them what they like to read, right? Because, I mean, there's the best known one is probably Snow Crash, but that's a cyberpunk novel that's at the same time making fun of cyberpunk. So it's kind of got some layers to it that might not seem so funny if you don't have that, if you don't get the joke, right? So there's, I've written, as you point out, I've written historical novels. Some people like those, some people prefer those. So if that's what you like, then Cryptonomicon or the Baroque cycle is where you would start. If you like sort of techno thrillers that are set in a modern day setting but aren't science fiction-y per se, then Reamde is one of those. And Termination Shock is definitely one of those. So it just depends on what people like. When people a long time ago recommended I read Snow Crash, they said, it's Neil Stevenson's Light. It's the, like, if you don't want to be overwhelmed by the depth, like the rigor of a book, like that's a good introduction to the man. So essentially you're broken down by topics, but if you wanted to read all of them, what's a good introduction to the man? Because obviously these worlds are very different. The philosophies are very different. What's a good introduction to the human? People ask the same thing, Dostoevsky, people, right? It's a hard one to answer. Maybe Seveneves, because it's got big themes. It's about heavy, heavy things happening to the human race. But hopefully the story is told through a cast of characters that people can relate to, you know, and it moves along. So it does go kind of deep eventually on how rockets work and orbital mechanics and all that stuff, but people were able to get through it anyway. Or some people just skip over that. It's fine, you know. As an author, let me ask you, what books had a big impact on your life that you've read? Is there any that jumped to mind that you learned from as a writer, as a philosopher, as a mathematician, as an engineer? This is one of these questions where I always blank out and then when I'm walking out the door I'll remember 12 of them. So this is a random selection that doesn't represent the top? The top ones. Well, I mentioned, you know, Gulag Archipelago, that's kind of a hefty and dark, but and then it has a personal connection as well. Yeah, just, yeah. It's like where you found the book too. The time in your life, where you found it, who recommended it, that's also part of the story. Yeah, so there's definitely that. I circle back to Moby Dick a lot because we read it in a really great English class I had in high school and I came in with an oppositional stance because I thought that the teacher was going to try to talk me into having all kinds of highfalutin ideas about allegory and what does this mean, what's the symbolism, and it turned out that it turned out to be a lot more interesting and satisfying than that. What was the first powerful book you remember reading that like convinced you that this form could have depth? Was it Moby Dick? Was it like in high school? I'm trying to remember. Well, Moby Dick was definitely a big one. I mean, I used to read a lot of classics comics when I was, I don't know if you've seen these, it's a whole series of comic books that it was viral. You could, in the back of each comic book was an order form. You could check some boxes and fill out your address and mail it in and more would show up. But it was like, they would do the count of money. Christo, Moby Dick, Robert Louis Stevenson, Robinson Crusoe, all the sort of classic books were, they had put into comic book form. That's amazing. Yeah. Reading Moby Dick, if you're nine years old, is a tall order. There's some very complicated sentences in there and a lot of digressions. But if you're just looking at the comic books, like, holy shit, look at that whale. And ultimately the power of the story doesn't need the complicated words. It's all about the man and the whale. Yeah. So you could get kind of a grounding in a lot of classic works of literature without actually reading them, which is great when you're nine years old. So I read a lot of that stuff for sure. The annotated Sherlock Holmes. You mentioned David Dojda is an inspiration for some of your work. I mean, you've obviously done really a lot of research for the books you do. Roger Penrose. Do you remember a book that made you want to become a writer or a moment that made you become a writer? I think the answer I usually give is that when I was in fifth grade, one of my friends came to school one day, he was wearing leather shoes, like dress shoes. And I hated dress shoes because mine never fit. And so they were uncomfortable. I couldn't run. You know, they were cold. It was Iowa. So I kind of said, I remember very clearly thinking, okay, I don't like where this is going. Like, does this mean that next year all of the kids are going to be wearing leather shoes? So I need to find a job where I don't have to do that. So that was like the first time I thought about trying to find such a job, you know, being a writer. And then I just read a lot of just classic science fiction short stories and started trying to write some of my own. And they were just classic young adult stories like by Heinlein and the other classic names that you think of, but the Heinlein ones have stuck with me in a way that the others didn't. What's the greatest science fiction book ever written? Removing your work from consideration. Greatest? I'm loving torturing you right now. Greatest ever non-Stevenson. Do we include fantasy? Does it have to be science fiction? Oh, interesting. Fantasy. Hmm. I did not expect that twist. Well, for in a weird way, they're lumped together in people's minds, right? Yeah. They are, but there's also a boundary somehow. Yeah. I'm not sure what that is exactly. Nobody is. It's a mystery. So, I mean, if we do include it, then it's easily the Lord of the Rings. But, I mean, greatness is an interesting quality to try to define. And for me, a lot of the fun and the joy of such books is not in what you'd call greatness, but just storytelling. So, I was always a big fan of have space suit will travel. Which is a Heinlein young adult book. It's just a fun, good read. So, fun is a big component. Greatness is overrated. Well, I don't know if it's overrated, but it's just, you know, it might be underdefined. Let's put it that way. Have space suit will travel. Now I definitely have to read that one. Yeah. You mentioned Iowa. I was there a couple of times. I got to spend quite a bit of time with Dan Gable, with Tom Brands, who are wrestlers. Is it now wrestling, martial arts, part of your life, any part of your formation of who you are as a human being? I think so. It was a late thing for me, but growing up in Ames, growing up in Ames, Dan Gable was a few years older than me. And so, sometimes we would go to the arena at the university and watch wrestling meets. And this was before his Olympic career. So, everyone knew he was the star of that team, and that he was the best. But people didn't yet know that he was the greatest of all time. Gee, you saw Gable. So, that was part... It's funny. It feels like a small world that you would be in the same space as Dan Gable. Well, from 100 feet away, a little dot on the mat, trouncing his opponents, him and Chris Taylor. So, the other star was this 400-pound-plus guy named Chris Taylor, who also went to the Olympics. So, yeah, people... He was an athletic hero. And wrestling is... There's certain states like Oklahoma, Pennsylvania, Iowa, where wrestling is the sport, because those are states of small towns. And so, if you're a small town, if you're like Dan Gable, and you have to be on a football team with 20 other guys who are not Dan Gable, then no matter how good you are, your team might suck. But in a solo thing, you can go to the Olympics. So, we did a lot of wrestling in our gym classes in school, and I didn't like it. And I think partly it's just that it was so competitive, and the people who cared about it really cared about it a lot. And so, it was pretty tough. I didn't think I had the right body type. But then, after college, I was in Iowa City for a few years when he was coaching the wrestling team there. And he won nine championships out of 10 years during that time. So, he was both the greatest individual wrestler of all time and the greatest team coach. So, I've never met him, but he's kind of been in my sphere of awareness since I was... Kind of my whole life. And people would always tell stories about him. I think he got arrested once for some kind of, I don't know, minor offense in Ames. And so, he just basically stayed up all night. He was in this cage in the jail. He just stayed up all night doing pull-ups. Yeah, sounds about right. Yeah. And so, yeah. So, has that been... I mean, Iowa is such an interesting place in the world. I mean, wrestling is just part of that story. Is that somewhere in there? Does that resonate deeply with who you are? It was a formative thing for me growing up there, for sure. It's just a... Or at least used to be a very orderly place, high social capital, very minimal class differences. So, you'd have some people who would drive a Cadillac instead of a Chevy, but that was it. Those were the rich people. And a college town is always a different environment. Austin has some of this. So, it was a pretty kind of utopian, other than the weather and a few other things, environment to grow up in. The martial art I ended up doing is sword stuff, which is interesting because it uses a different feedback loop. So, if you're grappling, everything is through sense of touch. And your sense of touch is very old and simple. Like, earthworms don't even have eyes, but they can tell when they're being touched. So, it's very fast. It's very fast. And with a standoff art like boxing or some kinds of sword fighting, you're not touching the other person most of the time. Your visual system is doing something way more... It's doing slam and trying to figure out what the other person is up to. And so, that always fell more my speed. So, in Olympic style fencing, it doesn't start really until you're crossing blades with the other person. And now you're back to wrestling. You're feeling what they're doing. And it's all about that. But some of the older sword arts don't engage the blade that way. You stand off at range and then you make cutting attacks. And so, those are all processed visually. And I think I'm more of a slow thinker. So, it works for me better. I mean, it has the same... The artistry and the beauty of boxing, I suppose, just like you said, is like there's no contact and it's all processed visually. And I'm sure there's a dance of its own. Yeah. Yeah. That depends on the characteristic of a sword involved. Yeah. There's a set of stances and basic reactions that you try to learn that are thought to be defensible and safe or safer. And so, it tends to be a series of short engagements where you'll close in, you'll try out your idea and it works or it doesn't. And then you back off again. It's interesting to think about human history because martial arts, okay, that's a thing. But in terms of sword fighting, just the full range of humans that existed who mastered sword fighting or sought the mastery of sword fighting, just to imagine the thousands of people who... The heights they have achieved. Because the stakes are so incredibly high to be good. And it's the richest, most powerful people in those societies spending whatever it takes to get the best gear and the best training. Because you're right, everything depends on it. And it's still life and death. I mean, that's fascinating. And we perhaps have lost that forever with greater weapons. I mean, the artistry of sword fighting when it's life and death and you go into war, you have the Miyamoto Musashi's of the world. I don't know. There's a poetry to that, that there's a mastery to that that I don't know if we could achieve with any other kind of martial art. Well, one of the good... You were talking earlier about the good effects of the internet, social media that we sometimes overlook. And one of those is that there were all these isolated people around the world who were interested in this, who found each other and kind of created a network of people who help each other learn these things. So that doesn't mean that anyone is up to the level that you're talking about yet, but it is happening. And so there's a large number of old treatises, old written documents that have been dug up from libraries and people have been going over these and translating them from old dialects of Italian and German to make sense of them and learning how to do these techniques with different weapons. Actually, there's a guy here in Austin named Duman Stith who does African, historical African martial arts. Also, martial arts of enslaved Africans who would learn machete fighting techniques in the Caribbean, South America. He's probably within a mile of us. He's an amazing guy. That's awesome. I'm going to look him up. Can I ask you for advice? Can you give advice for young people, high school, college, undergrads, thinking about their career, thinking about life, how to live a life they can be proud of? You think quite a bit about what it's required to be innovative in this world. You think quite a bit about the future. So if somebody wanted to be a person that makes a big impact on the future, what advice would you give them? I think a big part of it is finding the thing that you will do happily and I don't want to say obsessively because that sounds like maybe it's pathological, but if you can find a thing that you'll sit down, you'll start doing it and hours later you kind of snap out of it, where did the time go? Then that's a really key discovery for anyone to make about themselves when they're young because if you don't have that, it's hard to figure out where you should put your energies. And so you might have the best intentions. You might say, I want world peace or whatever, but at the end of the day, what really matters is how do you spend your time and are you spending it in a way that's productive? Because it doesn't matter how smart you are or well-intentioned you are unless you've figured that out. And so it's finding that thing in which you can sort of, you naturally lose yourself in. The thing is, at least for me, there's a lot of things like that, but I first have to overcome the initial hump of really sucking at that thing. Like the fun starts a little bit after the first hump of really sucking and then you could suck just regularly. Yeah. So oftentimes people can give up too early, I think. I mean, that's true with mathematics for me. It's for a lot of people is if you just give it a chance to struggle. If you give yourself time to struggle, you'll find a way, you'll find the thing within that thing that you can lose track of time with. Yeah, that's a key detail that's an important thing to add to what I said, which is that this might not happen the first time you do a thing. Maybe it will, but you might have to climb that learning curve. And if there's pressures in your life that are making you feel bad about that, then it might prevent you from getting where you need to be. So there's some complexity there that can make this kind of non-obvious, but that's why we need good teachers. Another beneficial thing of the internet is YouTube and being able to learn things, how to do things on YouTube. The dude who made the YouTube video doesn't care how many times you hit pause and rewind. They're never going to roll their eyes and be impatient with you. And sometimes spending a huge amount of time on one video or one book, like making that the thing you just spent a huge amount of time on rereading, rereading, or re-watching, re-watching, that somehow really solidifies your love for that thing. And the depth of understanding you start to gain, and it's okay to stay with that. I used to think there's all these books out there, so I need to keep reading or keep reading. But then I realized, I think it was somewhere in college, where you could just spend your whole life with a single textbook. There's enough in that textbook to really, really stay. Yeah. Miesner, Thorne, and Wheeler, gravitation is one of those. Or another one is The Road to Reality by Roger Penrose, which is incredibly deep. And it starts with like two plus two equals four, and at the end, you're at the boundaries of physics. It's an amazing, amazing book. Let me ask you the big ridiculous question. Okay. Since you've pondered some big ridiculous questions in your work, what's the meaning of this whole thing? What's the meaning of life? Wow. Human life. Well, as far as I know, we're unique in the universe. There's no evidence that there's anything else in the universe that's as complicated as what's between our ears. Might be. You can't rule it out. So we appear to be pretty special. And so it's got to have something to do with that. And one of the reasons I like David Deutsch, in particular his book, The Beginning of Infinity, is that he talks about the power of explanations and the fact that most civilizations are static, that they've got a set of dogmas that they arrive at somehow, and they just pass those on from one generation to the next and nothing changes. But that huge changes have happened when people sort of follow whatever you want to call it, the scientific method or enlightenment. There's different ways of thinking about it, but basically explanatory, it's about the power of explanations and being able to figure out why things are the way they are. And that has created changes in our thinking and our way of life over the last few centuries that are explosive compared to anything that came before. And David sort of verges on classifying this as like a force of nature in its potential transformative power. If we keep going, if we figure out how to colonize the universe, like you were talking about earlier, how to spread to other star systems, then it is effectively a force of nature. This kind of drive to understand more and more and more, deeper and deeper and deeper, and to engineer stuff so that we can understand even more. Yeah. Yeah, it's the old, the universe created us to understand itself, maybe that's the whole purpose. Yeah. And it is an interesting, peculiar side effect of the way we've been created is we seem to be conscious beings, we seem to have little egos, we seem to be born and die pretty quickly. There's a bunch of drama. We're all within ourselves pretty unique and we fall in love and start wars and there's hate and all the full interesting dynamic of it. So it's not just about the individual people. Yeah. Somehow like the concert that we played together. Yeah, yeah. That's kind of interesting. There's a lot of peculiar aspects of that that I wonder if they're fundamental or just quirks of evolution. Whether it's death, whether it's love, whether all those things. I wonder if they're, from an engineering perspective, when we're trying to create that intelligent toaster that listens for the slam door and the smell of burning toast. Whether that toaster should be afraid of death and should fall in love just like we do. Neil, you're a fascinating human being. You've impacted the lives of millions of people. Well, thank you. It's a huge honor that you would spend your valuable time with me today. Thank you so much. Thank you for coming down to beautiful, hot Texas and thank you for talking today. It was a pleasure. I'm glad I came and did it. Thanks for listening to this conversation with Neil Stevenson. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Neil Stevenson himself in his novel, Snow Crash. The world is full of things more powerful than us, but if you know how to catch a ride, you can go places. Thanks for listening and hope to see you next time.

https://youtu.be/xAfdSak2fs8

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Michael Stevens: Vsauce | Lex Fridman Podcast #58

The following is a conversation with Michael Stevens, the creator of Vsauce, one of the most popular educational YouTube channels in the world, with over 15 million subscribers and over 1.7 billion views. His videos often ask and answer questions that are both profound and entertaining, spanning topics from physics to psychology. Popular questions include, what if everyone jumped at once? Or what if the sun disappeared? Or why are things creepy? Or what if the earth stopped spinning? As part of his channel, he created three seasons of Mind Field, a series that explored human behavior. His curiosity and passion are contagious and inspiring to millions of people. And so as an educator, his impact and contribution to the world is truly immeasurable. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it 5 stars on Apple Podcasts, support it on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode and never any ads in the middle that break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Brokerage services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App to support one of my favorite organizations called FIRST, best known for their FIRST Robotics and LEGO competitions. They educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating on Charity Navigator, which means the donated money is used to maximum effectiveness. When you get Cash App from the App Store, Google Play, and use code LEXPODCAST, you'll get $10 and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now, here's my conversation with Michael Stevens. One of your deeper interests is psychology, understanding human behavior. You've pointed out how messy studying human behavior is and that it's far from the scientific rigor of something like physics, for example. How do you think we can take psychology from where it's been in the 20th century to something more like what the physicists, theoretical physicists are doing, something precise, something rigorous? Well, we could do it by finding the physical foundations of psychology, right? If all of our emotions and moods and feelings and behaviors are the result of mechanical behaviors of atoms and molecules in our brains, then can we find correlations? Perhaps like chaos makes that really difficult and the uncertainty principle and all these things. We can't know the position and velocity of every single quantum state in a brain, probably. But I think that if we can get to that point with psychology, then we can start to think about consciousness in a physical and mathematical way. When we ask questions like, well, what is self-reference? How can you think about your self-thinking? What are some mathematical structures that could bring that about? There's ideas of, in terms of consciousness and breaking it down into physics, there's ideas of panpsychism where people believe that whatever consciousness is, is a fundamental part of reality. It's almost like a physics law. Do you think, what's your views on consciousness? Do you think it has this deep part of reality or is it something that's deeply human and constructed by us humans? Start nice and light and easy. Nothing I ask you today has actually proven answer, so we're just hypothesizing. So yeah, I mean, I should clarify, this is all speculation and I'm not an expert in any of these topics and I'm not God. But I think that consciousness is probably something that can be fully explained within the laws of physics. I think that our bodies and brains and the universe and at the quantum level is so rich and complex, I'd be surprised if we couldn't find a room for consciousness there. And why should we be conscious? Why are we aware of ourselves? That is a very strange and interesting and important question. And I think for the next few thousand years, we're going to have to believe in answers purely on faith. But my guess is that we will find that within the configuration space of possible arrangements of the universe, there are some that contain memories of others. Literally Julian Barber calls them time capsule states where you're like, yeah, not only do I have a scratch on my arm, but also this state of the universe also contains a memory in my head of being scratched by my cat three days ago. And for some reason, those kinds of states of the universe are more plentiful or more likely. When you say those states, the ones that contain memories of its past or ones that contain memories of its past and have degrees of consciousness? Just the first part, because I think the consciousness then emerges from the fact that a state of the universe that contains fragments or memories of other states is one where you're going to feel like there's time. You're going to feel like, yeah, things happened in the past. And I don't know what will happen in the future because these states don't contain information about the future. For some reason, those kinds of states are either more common, more plentiful, or you could use the anthropic principle and just say, well, they're extremely rare, but until you are in one or if you are in one, then you can ask questions like you're asking me on this podcast. Why questions? Yeah, it's like, why are we conscious? Well, because if we weren't, we wouldn't be asking why we were. You've kind of implied that you have a sense, again, hypothesis, theorizing that the universe is deterministic. What's your thoughts about free will? Do you think of the universe as deterministic in a sense that it's unrolling a particular, like it's operating under a specific set of physical laws and when you have set the initial conditions, it will unroll in the exact same way in our particular line of the universe every time? That is a very useful way to think about the universe. It's done us well. It's brought us to the moon. It's brought us to where we are today, right? I would not say that I believe in determinism in that kind of an absolute form or actually I just don't care. Maybe it's true, but I'm not going to live my life like it is. What in your sense, because you've studied kind of how we humans think of the world, what's in your view is the difference between our perception, like how we think the world is and reality? Do you think there's a huge gap there? Like we delude ourselves that the whole thing is an illusion, just everything about human psychology, the way we see things and how things actually are. All the things you've studied, what's your sense? How big is the gap between reality? Well, again, purely speculative. I think that we will never know the answer. We cannot know the answer. There is no experiment to find an answer to that question. Everything we experience is an event in our brain. When I look at a cat, I'm not even – I can't prove that there's a cat there. All I am experiencing is the perception of a cat inside my own brain. I am only a witness to the events of my mind. I think it is very useful to infer that if I witness the event of cat in my head, it's because I'm looking at a cat that is literally there and has its own feelings and motivations and should be pet and given food and water and love. I think that's the way you should live your life. But whether or not we live in a simulation on the brain in a vat, I don't know. Do you care? I don't really – well, I care because it's a fascinating question and it's a fantastic way to get people excited about all kinds of topics, physics, psychology, consciousness, philosophy. At the end of the day, what would the difference be? If you – The cat needs to be fed at the end of the day. Otherwise, it would be a dead cat. Right. But if it's not even a real cat, then it's just like a video game cat. And right, so what's the difference between killing a digital cat in a video game because of neglect versus a real cat? It seems very different to us psychologically. I don't really feel bad about, oh my gosh, I forgot to feed my Tamagotchi, right? But I would feel terrible if I forgot to feed my actual cats. So can you just touch on the topic of simulation? Do you find this thought experiment that we're living in a simulation useful, inspiring, or constructive in any kind of way? Do you think it's ridiculous? Do you think it could be true? Or is it just a useful thought experiment? I think it is extremely useful as a thought experiment because it makes sense to everyone, especially as we see virtual reality and computer games getting more and more complex. You're not talking to an audience in like Newton's time where you're like, imagine a clock that has mechanics in it that are so complex that it can create love. And everyone's like, no. But today, you really start to feel, man, at what point is this little robot friend of mine going to be like someone I don't want to cancel plans with? And so it's a great thought experiment of do we live in a simulation? Am I a brain in a vat that is just being given electrical impulses from some nefarious other beings so that I believe that I live on Earth and that I have a body and all of this? And the fact that you can't prove it either way is a fantastic way to introduce people to some of the deepest questions. So you mentioned a little buddy that you would want to cancel an appointment with. So that's a lot of our conversations. That's what my research is. It's artificial intelligence. I apologize, but you're such a fun person to ask these big questions with. Well, I hope I can give some answers that are interesting. Well, because of you've sharpened your brain's ability to explore some of the most, some of the questions that many scientists are actually afraid of even touching, which is fascinating. I think you're, in that sense, ultimately a great scientist through this process of sharpening your brain. Well, I don't know if I am a scientist. I think science is a way of knowing, and there are a lot of questions I investigate that are not scientific questions. On my field, we have definitely done scientific experiments and studies that had hypotheses and all of that. But not to be too precious about what does the word science mean, but I think I would just describe myself as curious, and I hope that that curiosity is contagious. So to you, the scientific method is deeply connected to science because your curiosity took you to asking questions. To me, asking a good question, even if you feel, society feels that it's not a question within the reach of science currently, to me, asking the question is the biggest step of the scientific process. The scientific method is the second part, and that may be what traditionally is called science, but to me, asking the questions, being brave enough to ask the questions, being curious and not constrained by what you're supposed to think is just true, what it means to be a scientist. It's certainly a huge part of what it means to be a human. If I were to say, you know what, I don't believe in forces. I think that when I push on a massive object, a ghost leaves my body and enters the object I'm pushing, and these ghosts happen to just get really lazy when they're around massive things, and that's why F equals MA. Oh, and by the way, the laziness of the ghost is in proportion to the mass of the object, so boom, proved me wrong. Every experiment, well, you can never find the ghost. And so none of that theory is scientific, but once I start saying, can I see the ghost, why should there be a ghost, and if there aren't ghosts, what might I expect, and I start to do different tests to see is this falsifiable, are there things that should happen if there are ghosts, or are there things that shouldn't happen, and do they, you know, what do I observe? Now I'm thinking scientifically. I don't think of science as, wow, a picture of a black hole. That's just a photograph. That's an image. That's data. That's a sensory and perception experience. Science is how we got that and how we understand it and how we believe in it and how we reduce our uncertainty around what it means. But I would say I'm deeply within the scientific community and I'm sometimes disheartened by the elitism of the thinking, sort of not allowing yourself to think outside the box. So allowing the possibility of going against the conventions of science, I think, is a beautiful part of some of the greatest scientists in history. I don't know. I'm impressed by scientists every day and revolutions in our knowledge of the world occur only under very special circumstances. It is very scary to challenge conventional thinking and risky because, let's go back to elitism and ego, right? If you just say, you know what, I believe in the spirits of my body and all forces are actually created by invisible creatures that transfer themselves between objects. If you ridicule every other theory and say that you're correct, then ego gets involved and you just don't go anywhere. But fundamentally, the question of, well, what is a force, is incredibly important. We need to have that conversation but it needs to be done in this very political way of like, let's be respectful of everyone and let's realize that we're all learning together and not shutting out other people. And so when you look at a lot of revolutionary ideas, they were not accepted right away. And Galileo had a couple of problems with the authorities and later thinkers, Descartes was like, all right, look, I kind of agree with Galileo but I'm going to have to not say that. I'll have to create and invent and write different things that keep me from being in trouble, but we still slowly made progress. Revolutions are difficult in all forms and certainly in science. Before we get to AI, on topic of revolutionary ideas, let me ask, on a Reddit AMA, you said that is the earth flat is one of the favorite questions you've ever answered. Speaking of revolutionary ideas. So your video on that, people should definitely watch, is really fascinating. Can you elaborate why you enjoyed answering this question so much? Yeah, well, it's a long story. I remember a long time ago, I was living in New York at the time, so it had to have been like 2009 or something. I visited the flat earth forums and this was before the flat earth theories became as sort of mainstream as they are. Sorry to ask the dumb question, forums, online forums. Yeah. Flat earth society, I don't know if it's.com or.org, but I went there and I was reading their ideas and how they responded to typical criticisms of, well, the earth isn't flat because what about this? And I could not tell, and I mentioned this in my video, I couldn't tell how many of these community members actually believe the earth was flat or were just trolling. And I realized that the fascinating thing is how do we know anything and what makes for a good belief versus a maybe not so tenable or good belief. And so that's really what my video about earth being flat is about. It's about, look, there are a lot of reasons. The earth is probably not flat, but a flat earth believer can respond to every single one of them. But it's all in an ad hoc way. And all of their rebuttals aren't necessarily going to form a cohesive, non-contradictory whole. And I believe that's the episode where I talk about Occam's razor and Newton's flaming laser sword. And then I say, well, you know what, wait a second, we know that space contracts as you move. And so to a particle moving near the speed of light towards earth, earth would be flattened in the direction of that particle's travel. So to them, earth is flat. Like we need to be really generous to even wild ideas because they're all thinking. They're all the communication of ideas. And what else can it mean to be a human? Yeah. And I think I'm a huge fan of the flat earth theory, quote unquote, in the sense that to me feels harmless to explore some of the questions of what it means to believe something, what it means to explore the edge of science and so on. It's because it's a harm, it's to me, nobody gets hurt whether the earth is flat or round, not literally, but I mean, intellectually when we're just having a conversation. That said, again, to elitism, I find that scientists roll their eyes way too fast on the flat earth. The kind of dismissal that I see to this even notion, they haven't like sat down and say, what are the arguments that are being proposed? And this is why these arguments are incorrect. So that should be something that scientists should always do, even to the most sort of ideas that seem ridiculous. So I like this, it's almost my test when I ask people what they think about flat earth theory to see how quickly they roll their eyes. Well, yeah, I mean, let me go on record and say that the earth is not flat. It is a three-dimensional spheroid. However, I don't know that and it has not been proven. Science doesn't prove anything. It just reduces uncertainty. Could the earth actually be flat? Extremely unlikely, extremely unlikely. And so it is a ridiculous notion if we care about how probable and certain our ideas might be. But I think it's incredibly important to talk about science in that way and to not resort to, well, it's true. It's true in the same way that a mathematical theorem is true. And I think we're kind of like being pretty pedantic about defining this stuff. But like, sure, I could take a rocket ship out and I could orbit earth and look at it and it would look like a ball, right? But I still can't prove that I'm not living in a simulation, that I'm not a brain in a vat, that this isn't all an elaborate ruse created by some technologically advanced extraterrestrial civilization. So there's always some doubt and that's fine. That's exciting. And I think that kind of doubt, practically speaking, is useful when you start talking about quantum mechanics or string theory. It helps, to me, that kind of little, adds a little spice into the thinking process of scientists. So, I mean, just as a thought experiment, your video kind of, okay, say the earth is flat, what would the forces when you walk about this flat earth feel like to the human? That's a really nice thought experiment to think about. Right, because what's really nice about it is that it's a funny thought experiment, but you actually wind up accidentally learning a whole lot about gravity and about relativity and geometry. And I think that's really the goal of what I'm doing. I'm not trying to convince people that the earth is round. I feel like you either believe that it is or you don't and that's, how can I change that? What I can do is change how you think and how you are introduced to important concepts like, well, how does gravity operate? Oh, it's all about the center of mass of an object. So right, on a sphere, we're all pulled towards the middle, essentially the centroid, geometrically, but on a disc, ooh, you're gonna be pulled at a weird angle if you're out near the edge. And that stuff's fascinating. Yeah, and to me, that particular video opened my eyes even more to what gravity is. It's just a really nice visualization tool of, because you always imagine gravity with spheres, with masses that are spheres. Yeah. And imagining gravity on masses that are not spherical, some other shape, but in here, a plate, a flat object is really interesting. It makes you really kind of visualize in a three-dimensional way the force of gravity. Even if a disc the size of earth would be impossible, I think anything larger than like the moon basically needs to be a sphere because gravity will round it out. So you can't have a teacup the size of Jupiter, right? There's a great book about a teacup in the universe that I highly recommend. I don't remember the author. I forget her name, but it's a wonderful book. So look it up. I think it's called Teacup in the Universe. Just to link on this point briefly, your videos are generally super, people love them, right? If you look at the sort of number of likes versus dislikes, this measure of YouTube, right, is incredible and as do I. But this particular flat earth video has more dislikes than usual. What do you, on that topic in general, what's your sense, how big is the community, not just who believes in flat earth, but sort of the anti-scientific community that naturally distrust scientists in a way that's not an open-minded way, like really just distrust scientists like they're bought by some, it's the kind of mechanism of some kind of bigger system that's trying to manipulate human beings. What's your sense of the size of that community? You're one of the sort of great educators in the world that educates people on the exciting power of science. So you're kind of up against this community. What's your sense of it? I really have no idea. I haven't looked at the likes and dislikes on the flat earth video. And so I would wonder if it has a greater percentage of dislikes than usual, is that because of people disliking it because they think that it's a video about earth being flat and they find that ridiculous and they dislike it without even really watching much, do they wish that I was more dismissive of flat earth theories? I know there are a lot of response videos that kind of go through the episode and are pro-flat earth, but I don't know if there's a larger community of unorthodox thinkers today than there have been in the past. And I just want to not lose them. I want them to keep listening and thinking. And by calling them all idiots or something, that does no good because how idiotic are they really? I mean, the earth isn't a sphere at all. We know that it's an oblate spheroid. And that in and of itself is really interesting. And I investigated that in which way is down, where I'm like, really, down does not point towards the center of the earth. It points in different direction depending on what's underneath you and what's above you and what's around you. The whole universe is tugging on me. And then you also show that gravity is non-uniform across the globe. Like if you, this is I guess thought experiment, if you build a bridge all the way across the earth and then just knock out its pillars, what would happen? Can you describe how it'd be like a very chaotic, unstable thing that's happening because gravity is non-uniform throughout the earth? Yeah. In small spaces, like the ones we work in, we can essentially assume that gravity is uniform, but it's not. It is weaker the further you are from the earth. And it also is going to be, it's radially pointed towards the middle of the earth. So a really large object will feel tidal forces because of that non-uniformness. And we can take advantage of that with satellites, right? Gravitational induced torque. It's a great way to align your satellite without having to use fuel or any kind of engine. So let's jump back to it. Artificial intelligence. What's your thought of the state of where we are at currently with artificial intelligence? And what do you think it takes to build human level or superhuman level intelligence? I don't know what intelligence means. That's my biggest question at the moment. And I think it's because my instinct is always to go, well, what are the foundations here of our discussion? What does it mean to be intelligent? How do we measure the intelligence of an artificial machine or a program or something? Can we say that humans are intelligent? Because there's also a fascinating field of how do you measure human intelligence? Of course. But if we just take that for granted, saying that whatever this fuzzy intelligence thing we're talking about, humans kind of have it. What would be a good test for you? So Turing developed a test that's natural language conversation. Would that impress you? A chat bot that you'd want to hang out and have a beer with for a bunch of hours or have dinner plans with? Is that a good test? Natural language conversation? Is there something else that would impress you? Or is that also too difficult to think about? I'm pretty much impressed by everything. I think that if- Roomba? If there was a chat bot that was incredibly, I don't know, really had a personality and I didn't, the Turing test, right? If I'm unable to tell that it's not another person, but then I was shown a bunch of wires and mechanical components and it was like, that's actually what you're talking to. I don't know if I would feel that guilty destroying it. I would feel guilty because clearly it's well-made and it's a really cool thing. It's like destroying a really cool car or something, but I would not feel like I was a murderer. So yeah, at what point would I start to feel that way? And this is such a subjective psychological question. If you give it movement or if you have it act as though, or perhaps really feel pain as I destroy it and scream and resist, then I'd feel bad. Yeah, it's beautifully put. And let's just say, act like it's a pain. So if you just have a robot that not screams, just like moans in pain, if you kick it, that immediately just puts it in a class that we humans, it becomes, it anthropomorphizes it. It almost immediately becomes human. So that's a psychology question as opposed to sort of a physics question. Right. I think that's a really good instinct to have. If the robot- Screams? Screams and moans, even if you don't believe that it has the mental experience, the qualia of pain and suffering, I think it's still a good instinct to say, you know what? I'd rather not hurt it. The problem is that instinct can get us in trouble because then robots can manipulate that. And there's different kinds of robots. There's robots like the Facebook and the YouTube algorithm that recommends the video and they can manipulate it in the same kind of way. Well, let me ask you just to stick on artificial intelligence for a second. Do you have worries about existential threats from AI or existential threats from other technologies like nuclear weapons that could potentially destroy life on earth or damage it to a very significant degree? Yeah, of course I do. Especially the weapons that we create. There's all kinds of famous ways to think about this. And one is that, wow, what if we don't see advanced alien civilizations because of the danger of technology? What if we reach a point, and I think there's a channel, Thotty2. Jeez, I wish I remembered the name of the channel. But he delves into this kind of limit of maybe once you discover radioactivity and its power, you've reached this important hurdle. And the reason that the skies are so empty is that no one's ever managed to survive as a civilization once they have that destructive power. And when it comes to AI, I'm not really very worried because I think that there are plenty of other people that are already worried enough. And oftentimes these worries are just, they just get in the way of progress. And they're questions that we should address later. And I think I talk about this in my interview with the self-driving autonomous vehicle guy as I think it was a bonus scene from the Trolley Problem episode. And I'm like, wow, what should a car do if this really weird contrived scenario happens where it has to swerve and save the driver but kill a kid? And he's like, well, what would a human do? And if we resist technological progress because we're worried about all of these little issues, then it gets in the way. And we shouldn't avoid those problems, but we shouldn't allow them to be stumbling blocks to advancement. So the folks like Sam Harris or Elon Musk are saying that we're not worried enough. So worry should not paralyze technological progress, but we're sort of marching, technology is marching forward without the key scientists, the developing the technology, worrying about the overnight having some effects that would be very detrimental to society. So to push back on your thought of the idea that there's enough people worrying about it, Elon Musk says there's not enough people worrying about it. So that's the kind of balance is, you know, it's like folks who really focus on non-nuclear deterrence are saying there's not enough people worried about nuclear deterrence, right? So it's an interesting question of what is a good threshold of people to worry about these? And if it's too many people that are worried, you're right, it'll be like the press would over report on it and there'll be technological, halt technological progress. If not enough, then we can march straight ahead into that abyss that human beings might be destined for with the progress of technology. Yeah. I don't know what the right balance is of how many people should be worried and how worried should they be, but we're always worried about new technology. You know, we know that Plato was worried about the written word. He's like, we shouldn't teach people to write because then they won't use their minds to remember things. There have been concerns over technology and its advancement since the beginning of recorded history. And so, you know, I think, however, these conversations are really important to have because again, we learn a lot about ourselves. If we're really scared of some kind of AI like coming into being that is conscious or whatever and can self replicate, we already do that every day. It's called humans being born. They're not artificial. They're humans, but they're intelligent and I don't want to live in a world where we're worried about babies being born because what if they become evil? Right. What if they become mean people? What if they're thieves? Maybe we should just like, what, not have babies born? Maybe we shouldn't create AI. It's like, you know, we will want to have safeguards in place in the same way that we know, look, a kid could be born that becomes some kind of evil person. But we have laws, right? And it's possible that with advanced genetics in general, be able to, you know, it's a scary thought to say that, you know, this, my child, if born would be, would have an 83% chance of being a psychopath, right? Like being able to, if it's something genetic, if there's some sort of, and what to use that information, what to do with that information is a difficult ethical. Yeah. I'd like to find an answer that isn't, well, let's not have them live. You know, I'd like to find an answer that is, well, all human life is worthy. And if you have an 83% chance of becoming a psychopath, well, you still deserve dignity and you still deserve to be treated well. You still have rights. At least at this part of the world, at least in America, there's a respect for individual life in that way. That's well, to me, but again, I'm in this bubble is a beautiful thing, but there's other cultures where individual human life is not that important, where a society, so I was born in Soviet Union, where the strength of nation and society together is more important than the, any one particular individual. So it's an interesting also notion, the stories we tell ourselves, I like the one where individuals matter, but it's unclear that that was what the future holds. Well, yeah. And I mean, let me even throw this out. Like what is artificial intelligence? How can it be artificial? I really think that we get pretty obsessed and stuck on the idea that there is some thing that is a wild human, a pure human organism without technology. But I don't think that's a real thing. I think that humans and human technology are one organism. Look at my glasses. Okay. If an alien came down and saw me, would they necessarily know that this is an invention, that I don't grow these organically from my body? They wouldn't know that right away. And the written word and spoons and cups, these are all pieces of technology. We are not alone as an organism. And so the technology we create, whether it be video games or artificial intelligence that can self replicate and hate us, it's actually all the same organism. When you're in a car, where do you end in the car begin? It seems like a really easy question to answer, but the more you think about it, the more you realize, wow, we are in this symbiotic relationship with our inventions. And there are plenty of people who are worried about it and there should be. But it's inevitable. And I think that even just us think of ourselves as individual intelligences may be silly notion because it's much better to think of the entirety of human civilization, all living organisms on earth as a single living organism, as a single intelligent creature, because you're right, everything's intertwined. Everything is deeply connected. So we mentioned Elon Musk, so you're a curious lover of science. What do you think of the efforts that Elon Musk is doing with space exploration, with electric vehicles, with autopilot, sort of getting into the space of autonomous vehicles, with boring under LA and Neuralink trying to communicate brain machine interfaces, communicate between machines and human brains? Well, it's really inspiring. I mean, look at the fandom that he's amassed. It's not common for someone like that to have such a following. And so it's- Engineering nerd. Yeah. So it's really exciting, but I also think that a lot of responsibility comes with that kind of power. So like if I met him, I would love to hear how he feels about the responsibility he has when there are people who are such a fan of your ideas and your dreams and share them so closely with you. You have a lot of power. And he didn't always have that. He wasn't born as Elon Musk. Well, he was, but well, he was named that later. But the point is that I want to know the psychology of becoming a figure like him. Well, I don't even know how to phrase the question right, but it's a question about what do you do when you're following, your fans become so large that it's almost bigger than you? And how do you responsibly manage that? And maybe it doesn't worry him at all, and that's fine too, but I'd be really curious. And I think there are a lot of people that go through this when they realize, whoa, there are a lot of eyes on me. There are a lot of people who really take what I say very earnestly and take it to heart and will defend me. And that can be dangerous and you have to be responsible with it. Both in terms of impact on society and psychologically for the individual, just the burden psychologically on Elon? Yeah, yeah. How does he think about that part of his persona? Well, let me throw that right back at you, because in some ways you're just a funny guy that's gotten a humongous following, a funny guy with a curiosity. You've got a huge following. How do you psychologically deal with the responsibility? In many ways, you have a reach in many ways bigger than Elon Musk. What is the burden that you feel in educating, being one of the biggest educators in the world where everybody's listening to you and actually everybody, most of the world that uses YouTube for educational material trusts you as a source of good, strong scientific thinking? It's a burden and I try to approach it with a lot of humility and sharing. I'm not out there doing a lot of scientific experiments. I am sharing the work of real scientists and I'm celebrating their work and the way that they think and the power of curiosity. But I want to make it clear at all times that, look, we don't know all the answers and I don't think we're ever going to reach a point where we're like, wow, and there you go. That's the universe. It's this equation, you plug in some conditions or whatever and you do the math and you know what's going to happen tomorrow. I don't think we're ever going to reach that point. But I think that there is a tendency to sometimes believe in science and become elitist and become, I don't know, hard, when in reality it should humble you and make you feel smaller. I think there's something very beautiful about feeling very, very small and very weak and to feel that you need other people. So I try to keep that in mind and say, look, thanks for watching. Vsauce is not, I'm not Vsauce, you are. When I start the episodes, I say, hey, Vsauce, Michael here. Vsauce and Michael are actually a different thing in my mind. I don't know if that's always clear, but yeah, I have to approach it that way because it's not about me. Yeah, so it's not even, you're not feeling responsibility. You're just sort of plugging into this big thing that is scientific exploration of our reality and you're a voice that represents a bunch, but you're just plugging into this big Vsauce ball that others, millions of others are plugged into. Yeah. So I try to encourage curiosity and responsible thinking and an embracement of doubt and being okay with that. So next week, talking to Christos Goudreau, I'm not sure if you're familiar who he is, but he's the VP of engineering, head of the quote unquote YouTube algorithm or the search and discovery. So let me ask first high level, do you have a question for him that if you can get an honest answer that you would ask, but more generally, how do you think about the YouTube algorithm that drives some of the motivation behind, no, some of the design decisions you make as you ask and answer some of the questions you do, how would you improve this algorithm in your mind in general? So just what would you ask him? And outside of that, how would you like to see the algorithm improve? Well, I think of the algorithm as a mirror. It reflects what people put in and we don't always like what we see in that mirror. From the individual mirror to the individual mirror to the society. Both. In the aggregate, it's reflecting back what people on average want to watch. And when you see things being recommended to you, it's reflecting back what it thinks you want to see. And specifically, I would guess that it's not just what you want to see, but what you will click on and what you will watch some of and stay on YouTube because of. I don't think that this is all me guessing, but I don't think that YouTube cares if you only watch like a second of a video as long as the next thing you do is open another video. If you close the app or close the site, that's a problem for them because they're not a subscription platform. They're not like, look, you're giving us 20 bucks a month no matter what. So who cares? They need you to watch and spend time there and see ads. So one of the things I'm curious about, whether they do consider longer term sort of develop you, your longer term development as a human being, which I think ultimately will make you feel better about using YouTube in the long term and allowing you to stick with it for longer. Because even if you feed the dopamine rush in the short term and you keep clicking on on cat videos, the eventually you sort of wake up like from a drug and say, I need to quit this. So I wonder how much you're trying to optimize for the long term. Because when I look at the, you know, your videos aren't exactly sort of no offense, but they're not the most clickable. They're both the most clickable and I feel I watched the entire thing and I feel a better human after I watched it. So like they're not just optimizing for the clickability. So my thought is, how do you think of it? And does it affect your own content? Like how deep you go, how profound you explore the directions and so on? I've been really lucky in that I don't worry too much about the algorithm. I mean, look at my thumbnails. I don't really go too wild with them. And with Minefield, where I'm in partnership with YouTube on the thumbnails, I'm often like let's pull this back. Let's be mysterious. Usually I'm just trying to do what everyone else is not doing. So if everyone's doing crazy Photoshop, what kind of thumbnails? I'm like, what if the thumbnails just align? Yeah. And what if the title is just a word? And I kind of feel like all of the Vsauce channels have cultivated an audience that expects that. And so they would rather Jake make a video that's just called stains than one called I explored stains. Shocking. Yeah. But there are other audiences out there that want that. And I think most people kind of want what you see the algorithm favoring, which is mainstream traditional celebrity and news kind of information. I mean, that's what makes YouTube really different than other streaming platforms. No one's like, what's going on in the world? I'll open up Netflix to find out. But you do open up Twitter to find that out. You open up Facebook. You can open up YouTube because you'll see that the trending videos are like what happened amongst the traditional mainstream people in different industries. That's what's being shown. And it's not necessarily YouTube saying we want that to be what you see. It's that that's what people click on. When they see Ariana Grande reads a love letter from like her high school sweetheart, they're like, I want to see that. And when they see a video from me that's got some lines in math and it's called law and causes, they're like, well, I mean, I'm just on the bus. Like I don't have time to dive into a whole lesson. So, you know, before you get super mad at YouTube, you should say, really, they're just reflecting back human behavior. Is there something you would improve about the algorithm? Knowing of course that as far as we're concerned, it's a black box, so we don't know how it works. Right. And I don't think that even anyone at YouTube really knows what it's doing. They know what they've tweaked, but then it learns. I think that it learns and it decides how to behave. And sometimes they're the YouTube employees are left going, I don't know, maybe we should like change the value of how much it worries about watch time and maybe it should worry more about something. I don't know. But I mean, I would like to see, I don't know what they're doing and not doing. Well, is there a conversation that you think they should be having just internally, whether they're having it or not? Is there something, should they be thinking about the long-term future? Should they be thinking about educational content and whether that's educating about what just happened in the world today, news or educational content, like what you're providing, which is asking big sort of timeless questions about how the way the world works. Well, it's interesting. What should they think about? Because it's called YouTube, not our tube. And that's why I think they have so many phenomenal educational creators. You don't have shows like Three Blue One Brown or Physics Girl or Looking Glass Universe or Up and Atom or Brain Scoop or I mean, I could go on and on. They aren't on Amazon Prime and Netflix and they don't have commissioned shows from those platforms. It's all organically happening because there are people out there that want to share their passion for learning, that want to share their curiosity. And YouTube could promote those kinds of shows more. But like, first of all, they probably wouldn't get as many clicks and YouTube needs to make sure that the average user is always clicking and staying on the site. They could still promote it more for the good of society. But then we're making some really weird claims about what's good for society because I think that cat videos are also an incredibly important part of what it means to be a human. I mentioned this quote before from Unumuno about, look, I've seen a cat like estimate distances and calculate a jump, you know, more often than I've seen a cat cry. And so things that play with our emotions and make us feel things can be cheesy and can feel cheap. But like, man, that's very human. And so even the dumbest vlog is still so important that I don't think I have a better claim to take its spot than it has to have that spot. It puts a mirror to us, the beautiful parts, the ugly parts, the shallow parts, the deep parts. You're right. But what I would like to see is, you know, I miss the days when engaging with content on YouTube helped push it into my subscribers timelines. It used to be that when I liked a video, say from Veritasium, it would show up in the feed on the front page of the app or the website of my subscribers. And I knew that if I liked a video, I could send it 100,000 views or more. That no longer is true. But I think that was a good user experience. When I subscribe to someone, when I'm following them, I want to see more of what they like. I want them to also curate the feed for me. And I think that Twitter and Facebook are doing that in also some ways that are kind of annoying. But I would like that to happen more. And I think we would see communities being stronger on YouTube if it was that way. Instead of YouTube going, well, technically, Michael liked this Veritasium video, but people are way more likely to click on Carpool Karaoke. So I don't even care who they are. Just give them that. Not say anything against Carpool Karaoke. That is a extremely important part of our society, what it means to be a human on earth. But I'll say it sucks. But a lot of people would disagree with you, and they should be able to see as much of that as they want. And I think even people who don't think they like it should still be really aware of it because it's such an important thing and such an influential thing. But yeah, I just wish that like new channels I discover and that I subscribe to, I wish that my subscribers found out about that. Because especially in the education community, a rising tide floats all boats. If you watch a video from Numberphile, you're just more likely to want to watch an episode from me, whether it be on Vsauce1 or Ding. It's not competitive in the way that traditional TV was, where it's like, well, if you tune into that show, it means you're not watching mine because they both air at the same time. So helping each other out through collaborations takes a lot of work. But just through engaging, commenting on their videos, liking their videos, subscribing to them, whatever, that I would love to see become easier and more powerful. So a quick and impossibly deep question, last question, about mortality. You've spoken about death as an interesting topic. Do you think about your own mortality? Yeah, every day. It's really scary. So what do you think is the meaning of life that mortality makes very explicit? So why are you here on earth, Michael? What's the point of this whole thing? What does mortality in the context of the whole universe make you realize about yourself? Just you, Michael Stevens. Well, it makes me realize that I am destined to become a notion. I'm destined to become a memory. And we can extend life. I think there's really exciting things being done to extend life, but we still don't know how to protect you from some accident that could happen, some unforeseen thing. Maybe we could save my connectome and recreate my consciousness digitally. But even that could be lost if it's stored on a physical medium or something. So basically, I just think that embracing and realizing how cool it is that someday I will just be an idea. And there won't be a Michael anymore that can be like, no, that's not what I meant. It'll just be what people – they have to guess what I meant. They'll remember me and how I live on as that memory will maybe not even be who I wanted to be. But there's something powerful about that and there's something powerful about letting future people run the show themselves. I think I'm glad to get out of their way at some point and say, all right, it's your world now. And you, the physical entity, Michael, have ripple effects in the space of ideas that far outlives you in ways that you can't control, but it's nevertheless fascinating to think. I mean, especially with you, you can imagine an alien species when they finally arrive and destroy all of us would watch your videos to try to figure out what were the questions that these people – But even if they didn't, I still think that there will be ripples. When I say memory, I don't specifically mean people remember my name and my birth date and there's a photo of me on Wikipedia. All that can be lost, but I still would hope that people ask questions and teach concepts in some of the ways that I have found useful and satisfying. Even if they don't know that I was the one who tried to popularize it, that's fine. But if Earth was completely destroyed, like burnt to a crisp, everything on it today, what would – the universe wouldn't care. Jupiter is not going to go, oh, no. And that could happen. So we do, however, have the power to launch things into space to try to extend how long our memory exists. And what I mean by that is we are recording things about the world and we're learning things and writing stories and all of this and preserving that is truly what I think is the essence of being a human. We are autobiographers of the universe and we're really good at it. We're better than fossils. We're better than light spectrum. We're better than any of that. We collect much more detailed memories of what's happening, much better data. And so that should be our legacy. And I hope that that's kind of mine too in terms of people remembering something or me having some kind of effect. But even if I don't, you can't not have an effect. That's the thing. This is not me feeling like I hope that I have this powerful legacy. It's like no matter who you are, you will. But you also have to embrace the fact that that impact might look really small and that's okay. One of my favorite quotes is from Tess of the D'Urbervilles and it's along the lines of the measure of your life depends on not your external displacement but your subjective experience. If I am happy and those that I love are happy, can that be enough? Because if so, excellent. I think there's no better place to end it, Michael. Thank you so much. It was an honor to meet you. Thanks for talking to me. Thank you. It was a pleasure. I hope you enjoyed this conversation with Michael Stevens and thank you to our presenting sponsor, Cash App. Download it. Use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, a STEM education nonprofit that inspires hundreds of thousands of young minds to learn, to dream of engineering our future. If you enjoyed this podcast, subscribe on YouTube, give it five stars on Apple Podcast, support it on Patreon or connect with me on Twitter. And now let me leave you with some words of wisdom from Albert Einstein. The important thing is not to stop questioning. Curiosity has its own reason for existence. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day. Thank you for listening and hope to see you next time.

https://youtu.be/3qMemn__kK8

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Noam Chomsky: Language, Cognition, and Deep Learning | Lex Fridman Podcast #53

The following is a conversation with Noam Chomsky. He's truly one of the great minds of our time and is one of the most cited scholars in the history of our civilization. He has spent over 60 years at MIT and recently also joined the University of Arizona, where we met for this conversation. But it was at MIT about four and a half years ago when I first met Noam. My first few days there, I remember getting into an elevator at Stata Center, pressing the button for whatever floor, looking up and realizing it was just me and Noam Chomsky riding the elevator. Just me and one of the seminal figures of linguistics, cognitive science, philosophy, and political thought in the past century, if not ever. I tell that silly story because I think life is made up of funny little defining moments that you never forget for reasons that may be too poetic to try and explain. That was one of mine. Noam has been an inspiration to me and millions of others. It was truly an honor for me to sit down with him in Arizona. I traveled there just for this conversation. And in a rare heartbreaking moment, after everything was set up and tested, the camera was moved and accidentally the recording button was pressed, stopping the recording. So I have good audio of both of us, but no video of Noam. Just the video of me and my sleep deprived but excited face that I get to keep as a reminder of my failures. Most people just listen to this audio version for the podcast, as opposed to watching it on YouTube. But still, it's heartbreaking for me. I hope you understand and still enjoy this conversation as much as I did. The depth of intellect that Noam showed and his willingness to truly listen to me, a silly looking Russian in a suit. It was humbling and something I'm deeply grateful for. As some of you know, this podcast is a side project for me where my main journey and dream is to build AI systems that do some good for the world. This latter effort takes up most of my time, but for the moment has been mostly private. But the former, the podcast, is something I put my heart and soul into. And I hope you feel that even when I screw things up. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode and never any ads in the middle that break the flow of the conversation. I hope that works for you. It doesn't hurt the listening experience. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcast, support it on Patreon, or simply connect with me on Twitter, Alex Friedman, spelled F-R-I-D-M-A-N. This show is presented by Cash App. The number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Brokerage services are provided by Cash App Investing, a subsidiary of Square, a member of SIPC. I'm excited to be working with Cash App to support one of my favorite organizations called the Digital Capital Fund. It's called The First, best known for their FIRST Robotics and LEGO competitions. They educate and inspire hundreds of thousands of students in over 110 countries, and have a perfect rating on Charity Navigator, which means the donated money is used to maximum effectiveness. When you get Cash App from the App Store, Google Play, and use code LEXPODCAST, you'll get $10, and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now, here's my conversation with Noam Chomsky. I apologize for the absurd philosophical question, but if an alien species were to visit Earth, do you think we would be able to find a common language or protocol of communication with them? There are arguments to the effect that we could, in fact, one of them was Marvin Minsky's. Back about 20 or 30 years ago, he performed a brief experiment with a student of his, Dan Bobrow. They essentially ran the simplest possible Turing machines, just free to see what would happen. And most of them crashed, either got into an infinite loop or stopped. The few that persisted essentially gave something like arithmetic. And his conclusion from that was that if some alien species developed higher intelligence, they would at least have arithmetic. They would at least have what the simplest computer would do. And in fact, he didn't know that at the time, but the core principles of natural language are based on operations which yield something like arithmetic in the limiting case and the minimal case. So it's conceivable that a mode of communication could be established based on the core properties of human language and the core properties of arithmetic, which maybe are universally shared. So it's conceivable. What is the structure of that language, of language as an internal system inside our mind versus an external system as it's expressed? It's not an alternative. It's two different concepts of language. Different. It's a simple fact that there's something about you, a trait of yours, part of the organism, you, that determines that you're talking English and not Tagalog, let's say. So there is an inner system. It determines the sound and meaning of the infinite number of expressions of your language. It's localized. It's not on your foot, obviously. It's in your brain. If you look more closely, it's in specific configurations of your brain. And that's essentially like the internal structure of your laptop, whatever programs it has are in there. Now, one of the things you can do with language, it's a marginal thing, in fact, is use it to externalize what's in your head. Actually, most of your use of language is thought, internal thought. But you can do what you and I are now doing. We can externalize it. Well, the set of things that we're externalizing are an external system. They're noises in the atmosphere. And you can call that language in some other sense of the word. But it's not a set of alternatives. These are just different concepts. So how deep do the roots of language go in our brain? Our mind? Is it yet another feature like vision, or is it something more fundamental from which everything else springs in the human mind? Well, in a way, it's like vision. There's something about our genetic endowment that determines that we have a mammalian rather than an insect visual system. And there's something in our genetic endowment that determines that we have a human language faculty. No other organism has anything remotely similar. So in that sense, it's internal. Now, there is a long tradition, which I think is valid, going back centuries to the early scientific revolution, at least, that holds that language is the core of human cognitive nature. It's the source. It's the mode for constructing thoughts and expressing them. That is what forms thought. And it's got fundamental creative capacities. It's free, independent, unbounded, and so on. And undoubtedly, I think the basis for our creative capacities and the other remarkable human capacities that lead to the unique achievements and not-so-great achievements of the species. The capacity to think and reason, do you think that's deeply linked with language? Do you think the way we, the internal language system is essentially the mechanism by which we also reason internally? It is undoubtedly the mechanism by which we reason. There may also be other, there are undoubtedly other faculties involved in reasoning. We have a kind of scientific faculty. Nobody knows what it is. But whatever it is that enables us to pursue certain lines of endeavor and inquiry and to decide what makes sense and doesn't make sense and to achieve a certain degree of understanding of the world, that uses language but goes beyond it. Just as using our capacity for arithmetic is not the same as having the capacity. The idea of capacity, our biology, evolution, you've talked about it defining, essentially, our capacity, our limit, and our scope. Can you try to define what limit and scope are? And the bigger question, do you think it's possible to find the limit of human cognition? Well, that's an interesting question. It's commonly believed, most scientists believe, that human intelligence can answer any question, in principle. I think that's a very strange belief. If we're biological organisms, which are not angels, then our capacities ought to have scope and limits, which are interrelated. Can you define those two terms? Well, let's take a concrete example. Your genetic endowment determines that you can have a male and visual system, arms and legs and so on, but it, and therefore, become a rich, complex organism. But if you look at that same genetic endowment, it prevents you from developing in other directions. There's no kind of experience which would yield the embryo to develop an insect visual system, or to develop wings instead of arms. So the very endowment that confers richness and complexity also sets bounds on what can be attained. Now, I assume that our cognitive capacities are part of the organic world, therefore they should have the same properties. If they had no built-in capacity to develop a rich and complex structure, we would have, understand nothing. Just as if your genetic endowment did not compel you to develop arms and legs, you would just be some kind of a random amoeboid creature with no structure at all. So I think it's plausible to assume that there are limits, and I think we even have some evidence as to what they are. So for example, there's a classic moment in the history of science. At the time of Newton, there was a, from Galileo to Newton, modern science, developed on a fundamental assumption, which Newton also accepted, namely that the world, the entire universe, is a mechanical object. And by mechanical, they meant something like the kinds of artifacts that were being developed by skilled artisans all over Europe, the gears, the levers, and so on. And their belief was, well, the world is just a more complex variant of this. Newton, to his astonishment and distress, proved that there are no machines, that there's interaction without contact. His contemporaries like Leibniz and Huygens just dismissed this as returning to the mysticism of the neo-scholastics. And Newton agreed. He said it is totally absurd. No person of any scientific intelligence could ever accept this for a moment. In fact, he spent the rest of his life trying to get around it somehow, as did many other scientists. That was the very criterion of intelligibility for, say, Galileo or Newton. Theory did not produce an intelligible world unless you could duplicate it in a machine. He showed you can't. There are no machines, any. Finally, after a long struggle, took a long time, scientists just accepted this as common sense. But that's a significant moment. That means they abandoned the search for an intelligible world. And the great philosophers of the time understood that very well. So, for example, David Hume, in his encomium to Newton, wrote that, who was the greatest thinker ever, and so on, he said that he unveiled many of the secrets of nature, but by showing the imperfections of the mechanical philosophy, mechanical science, he left us with, he showed that there are mysteries which ever will remain. And science just changed its goals. It abandoned the mysteries. It can't solve it. We'll put it aside. We only look for intelligible theories. Newton's theories were intelligible. It's just what they described wasn't. Well, Locke said the same thing. I think they're basically right. And if so, that showed something about the limits of human cognition. We cannot attain the goal of understanding the world, of finding an intelligible world. This mechanical philosophy, Galileo to Newton, there's a good case that can be made that that's our instinctive conception of how things work. So, if say infants are tested with things, if this moves, then this moves, they kind of invent something that must be invisible that's in between them that's making them move. Yeah, we like physical contact. Something about our brain seeks. Makes us want a world like that, just like it wants a world that has regular geometric figures. So, for example, Descartes pointed this out that if you have an infant who's never seen a triangle before, and you draw a triangle, the infant will see a distorted triangle, not whatever crazy figure it actually is. Three lines not coming quite together, or one of them a little bit curved, and so on. We just impose a conception of the world in terms of a perfect geometric object. It's now been shown that it goes way beyond that. That if you show on a tachistoscope, let's say a couple of lights shining, you do it three or four times in a row, what people actually see is a rigid object in motion, not whatever's there. We all know that from a television set, basically. So that gives us hints of potential limits to our cognition. I think it does, but it's a very contested view. If you do a poll among scientists, it's impossible we can understand anything. Let me ask, and give me a chance with this. So I just spent a day at a company called Neuralink, and what they do is try to design what's called the brain computer interface. So they try to do thousands readings in the brain, be able to read what the neurons are firing, and then stimulate back, so two-way. Do you think their dream is to expand the capacity of the brain to attain information, sort of increase the bandwidth at which we can search Google kind of thing? Do you think our cognitive capacity might be expanded, our linguistic capacity, our ability to reason might be expanded by adding a machine into the picture? It can be expanded in a certain sense, but a sense that was known thousands of years ago. A book expands your cognitive capacity. Okay, so this could expand it, too. But it's not a fundamental expansion. It's not totally new things could be understood. Well, nothing that goes beyond their native cognitive capacities. Just like you can't turn the visual system into an insect system. Well, I mean, the thought is perhaps you can't directly, but you can map. You could, but we know that without this experiment. You could map what a bee sees and present it in a form so that we could follow it. In fact, every bee scientist does that. But you don't think there's something greater than bees that we can map and then all of a sudden discover something, be able to understand a quantum world, quantum mechanics, be able to start to be able to make sense. Students at MIT study and understand quantum mechanics. But they always reduce it to the infant, the physical. I mean, they don't really understand. Oh, you don't, there's things, that may be another area where there's just a limit to understanding. We understand the theories, but the world that it describes doesn't make any sense. So, you know, the experiment, Schrodinger's cat, for example, can understand the theory, but as Schrodinger pointed out, it's an unintelligible world. One of the reasons why Einstein was always very skeptical about quantum theory. He described himself as a classical realist, in one's intelligibility. He has something in common with infants in that way. So, back to linguistics. If you could humor me, what are the most beautiful or fascinating aspects of language, or ideas in linguistics, or cognitive science that you've seen in a lifetime of studying language and studying the human mind? Well, I think the deepest property of language and puzzling property that's been discovered is what is sometimes called structure dependence. We now understand it pretty well, but it was puzzling for a long time. I'll give you a concrete example. So, suppose you say, the guy who fixed the car carefully packed his tools. That's ambiguous, he could fix the car carefully or carefully pack his tools. Suppose you put carefully in front. Carefully, the guy who fixed the car packed his tools. Then it's carefully packed, not carefully fixed. And in fact, you do that even if it makes no sense. So, suppose you say, carefully, the guy who fixed the car is tall. You have to interpret it as carefully he's tall. Even though that doesn't make any sense. And notice that that's a very puzzling fact because you're relating carefully not to the linearly closest verb, but to the linearly more remote verb. A linear closeness is an easy computation, but here you're doing a much more, what looks like a more complex computation. You're doing something that's taking you essentially to the more remote thing. It's now, if you look at the actual structure of the sentence, where the phrases are and so on, turns out you're picking out the structurally closest thing, but the linearly more remote thing. But notice that what's linear is 100% of what you hear. You never hear structure, can't. So, what you're doing is, and incidentally, this is universal, all constructions, all languages. And what we're compelled to do is carry out what looks like the more complex computation on material that we never hear. And we ignore 100% of what we hear and the simplest computation. By now there's even a neural basis for this that's somewhat understood. And there's good theories by now that explain why it's true. That's a deep insight into the surprising nature of language with many consequences. Let me ask you about a field of machine learning, deep learning. There's been a lot of progress in neural networks based, neural network based machine learning in the recent decade. Of course, neural network research goes back many decades. What do you think are the limits of deep learning, of neural network based machine learning? Well, to give a real answer to that, you'd have to understand the exact processes that are taking place. And those are pretty opaque. So it's pretty hard to prove a theorem about what can be done and what can't be done. But I think it's reasonably clear. I mean, putting technicalities aside, what deep learning is doing is taking huge numbers of examples and finding some patterns. Okay, that could be interesting. In some areas it is. But we have to ask here a certain question. Is it engineering or is it science? Engineering in the sense of just trying to build something that's useful. Or science in the sense that it's trying to understand something about elements of the world. So it takes a Google parser. We can ask that question. Is it useful? Yeah, it's pretty useful. You know, I use a Google translator. So on engineering grounds, it's kind of worth having, like a bulldozer. Does it tell you anything about human language? Zero. Nothing. And in fact, it's very striking. It's from the very beginning, it's just totally remote from science. So what is a Google parser doing? It's taking an enormous text, let's say the Wall Street Journal corpus, and asking how close can we come to getting the right description of every sentence in the corpus. Well, every sentence in the corpus is essentially an experiment. Each sentence that you produce is an experiment which is, am I a grammatical sentence? The answer is usually yes. So most of the stuff in the corpus is grammatical sentences. But now ask yourself, is there any science which takes random experiments which are carried out for no reason whatsoever and tries to find out something from them? Like if you're, say, a chemistry PhD student, you wanna get a thesis, can you say, well, I'm just gonna do a lot of, mix a lot of things together, no purpose, just, and maybe I'll find something. You'd be laughed out of the department. Science tries to find critical experiments, ones that answer some theoretical question. Doesn't care about coverage of millions of experiments. So it just begins by being very remote from science, and it continues like that. So the usual question that's asked about, say, a Google parser, is how well does it do, or some parser, how well does it do on a corpus? But there's another question that's never asked. How well does it do on something that violates all the rules of language? So for example, take the structure dependence case that I mentioned. Suppose there was a language in which you used linear proximity as the mode of interpretation. These deep learning would work very easily on that. In fact, much more easily than an actual language. Is that a success? No, that's a failure. From a scientific point of view, it's a failure. It shows that we're not discovering the nature of the system at all, because it does just as well, or even better, on things that violate the structure of the system. And it goes on from there. It's not an argument against doing it. It is useful to have devices like this. So yes, so neural networks are kind of approximators that look, there's echoes of the behavioral debates, right, behavioralism. More than echoes. Many of the people in deep learning say they've vindicated. Terry Sanyoski, for example, in his recent book says, this vindicates Skinnerian behaviors. It doesn't have anything to do with it. Yes, but I think there's something actually fundamentally different when the data set is huge. But your point is extremely well taken. But do you think we can learn, approximate that interesting complex structure of language with neural networks that will somehow help us understand the science? It's possible. I mean, you find patterns that you hadn't noticed, let's say, could be. In fact, it's very much like a kind of linguistics that's done, what's called corpus linguistics. When you, suppose you have some language where all the speakers have died out, but you have records. So you just look at the records and see what you can figure out from that. It's much better than, it's much better to have actual speakers where you can do critical experiments. But if they're all dead, you can't do them. So you have to try to see what you can find out from just looking at the data that's around. You can learn things. Actually, paleoanthropology is very much like that. You can't do a critical experiment on what happened two million years ago. So you're kind of forced just to take what data's around and see what you can figure out from it. Okay, it's a serious study. So let me venture into another whole body of work and philosophical question. You've said that evil in society arises from institutions, not inherently from our nature. Do you think most human beings are good, they have good intent? Or do most have the capacity for intentional evil that depends on their upbringing, depends on their environment, on context? I wouldn't say that they don't arise from our nature. Anything we do arises from our nature. And the fact that we have certain institutions, not others, is one mode in which human nature has expressed itself. But as far as we know, human nature could yield many different kinds of institutions. The particular ones that have developed have to do with historical contingency, who conquered whom, and that sort of thing. They're not rooted in our nature in the sense that they're essential to our nature. So it's commonly argued that these days that something like market systems is just part of our nature. But we know from a huge amount of evidence that that's not true. There's all kinds of other structures. It's a particular fact about a moment of modern history. Others have argued that the roots of classical liberalism actually argue that what's called sometimes an instinct for freedom, an instinct to be free of domination by illegitimate authority is the core of our nature. That would be the opposite of this. And we don't know. We just know that human nature can accommodate both kinds. If you look back at your life, is there a moment in your intellectual life or life in general that jumps from memory that brought you happiness, that you would love to relive again? Sure. Falling in love, having children. What about, so you have put forward into the world a lot of incredible ideas in linguistics, in cognitive science. In terms of ideas that just excites you when they first came to you, you would love to relive those moments. Well, I mean, when you make a discovery about something that's exciting, like say, even the observation of structure dependence and on from that, the explanation for it. But the major things just seem like common sense. So if you go back to take your question about external and internal language, you go back to say the 1950s, almost entirely language is regarded an external object, something outside the mind. It just seemed obvious that that can't be true. Like I said, there's something about you that determines you're talking English, not Swahili or something. But that's not really a discovery, that's just an observation which is transparent. You might say it's kind of like the 17th century, the beginnings of modern science, 17th century. They came from being willing to be puzzled about things that seemed obvious. So it seems obvious that a heavy ball of lead will fall faster than a light ball of lead. But Galileo was not impressed by the fact that it seemed obvious. So he wanted to know if it's true. He carried out experiments, actually thought experiments, never actually carried them out, which showed that it can't be true. And out of things like that, observations of that kind, why does a ball fall to the ground instead of rising, let's say? Seems obvious until you start thinking about it. Because why does steam rise? And I think the beginnings of modern linguistics, roughly in the 50s, are kind of like that, just being willing to be puzzled about phenomena that looked, from some point of view, obvious. And for example, a kind of doctrine, almost official doctrine of structural linguistics in the 50s was that languages can differ from one another in arbitrary ways, and each one has to be studied on its own without any presuppositions. In fact, there were similar views among biologists about the nature of organisms, that each one's, they're so different when you look at them that almost anything, you could be almost anything. Well, in both domains, it's been learned that that's very far from true. There are very narrow constraints on what could be an organism or what could be a language. But these are, that's just the nature of inquiry. Science in general, yeah, inquiry. So one of the peculiar things about us human beings is our mortality. Ernest Becker explored it in general. Do you ponder the value of mortality? Do you think about your own mortality? I used to when I was about 12 years old. I wondered, I didn't care much about my own mortality, but I was worried about the fact that if my consciousness disappeared, would the entire universe disappear? That was frightening. Did you ever find an answer to that question? No, nobody's ever found an answer, but I stopped being bothered by it. It's kind of like Woody Allen in one of his films, you may recall, he starts, he goes to a shrink when he's a child and the shrink asks him, what's your problem? He says, I just learned that the universe is expanding. I can't handle that. And then another absurd question is, what do you think is the meaning of our existence here, our life on Earth, our brief little moment in time? That's something we answer by our own activities. There's no general answer. We determine what the meaning of it is. The action determined the meaning. Meaning in the sense of significance, not meaning in the sense that chair means this, but the significance of your life is something you create. Noam, thank you so much for talking today. It was a huge honor. Thank you so much. Thanks for listening to this conversation with Noam Chomsky and thank you to our presenting sponsor, Cash App. Download it, use code LEXPODCAST, you'll get $10 and $10 will go to FIRST, a STEM education non-profit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future. If you enjoy this podcast, subscribe on YouTube, give it five stars on Apple Podcast, support on Patreon or connect with me on Twitter. Thank you for listening and hope to see you next time.

https://youtu.be/cMscNuSUy0I

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20,000 Push-ups and Pull-ups in 30 Days Challenge (featuring David Goggins)

A few days ago, I tweeted, I will do as many pushups and pull-ups next 30 days as this tweet gets likes, retweets, and comments. No number is too high. Bring it. It got 20,000. So thank you, internet friends, for the love and the suffering. It was probably about four or more times the amount that I was mentally preparing myself for. In the name of health, I decided to spread that around across multiple bodyweight exercises, including pushups and pull-ups, but also squats, ab rollers, and running. One mile of running equals 42 pushups. Flex math. And all happy with myself, I wrote to David Goggins asking for his advice, thoughts on this challenge. If you don't know David Goggins, he, to me, is one of the toughest, most inspiring humans on the planet. Retired Navy SEAL, ultra marathon runner, former record holder for the most pull-ups in 24 hours, author of the book Can't Hurt Me that I highly recommend, especially the audio book. Anyway, I asked him a few questions about this challenge, and he was kind enough to respond. I'll interleave the clips into the video. So the first thing I did is I explained to him the challenge and the way I spread it around across multiple bodyweight exercises, and just asked him for his thoughts about what I'm doing. Well I think it's a pretty good damn workout. But this is the issue right there, man. I believe that you told people on, I think it was Twitter, I'm not quite for sure, I think it was Twitter, that you would do pushups and pull-ups for the number of week retweets that you had. Now I'm hearing running, I'm hearing squats, I'm hearing, I am hearing pushups, I'm hearing pushups and pull-ups, I'm hearing all kinds of different other exercises. And you also told people that, guess what, bring it. No number's too high. But now you're other exercises, so that must mean that there is a number too high. So be careful what you wish for, my friend. So that being said, I would have stuck with the damn pushups and pull-ups, and challenge yourself to the umpteenth degree of pain and suffering, and that would have really taught you a humongous lesson about yourself and everything else. But what you have here is also amazing. But it's nothing compared to what you had previously talked about. There you have it. When David Goggins calls you out on your bullshit, you gotta step up. So I'm going to do what I originally promised, which is the 20,000 pushups and pull-ups. And on top of that, I'll do my best to do also the other bodyweight exercises, really for the sake of health. So we're talking about squats, ab rollers, and running. The whole goal I wanted to do here is something that's healthy, but still pushes me to my limits physically and mentally, and allows me to build up a habit of doing some efficient exercises every day. You know, something that takes less than an hour, but keeps me in pretty sharp, hard shape. That's what I'm going to do here. Certainly, with 20,000 pushups and pull-ups, that's a whole other level. I don't know what's going to happen, but I will learn something about myself for sure. So I want to mention some of the reasons, some of the motivations of why I'm doing this challenge. So first is, I didn't think too much about it. I just dived right in. I was actually just laying in bed and tweeted it out. I think some of the craziest, most fun, some of the most ambitious things we can take on in life sometimes can be just on a whim. So I'm decided on a whim, but I'm going to take it to completion. Also I wanted to do an exercise program that I've done often in the past that takes very little effort. So like being busy is not an excuse. It can take 20, 30 minutes a day just to get a hard workout in. You can do it at home. There's no excuse not to do it. The other thing is that travel is not an excuse because it's body weight. You can basically do it anywhere. You probably heard me talk a lot about it before, but I'm a huge believer in habits because habits remove the need for day-to-day motivations that can go up and down. I have a lot of research, work-related habits that are part of my life, but I wanted to get exercise as part of a daily routine in my life. I think especially in these times of the coronavirus and all the madness that's going on in the world, being healthy, making sure you're strengthening your immune system with good diet, good sleep, good exercise is really important for everybody. Everybody's kind of locked up and it's easy to slack on the exercise. I wanted to motivate others perhaps to join me on getting their exercise back on, getting back out there, getting a little bit of movement every single day. And also I wanted to harden up that muscle of doing a thing you don't want to do for that long period of time and getting it done. So I actually asked David, what should I do when things get tough? This is a good fucking question, man, because it's going to get fucking difficult. Day after day after day. That's the thing about what you're doing right now that's challenging is a lot of motherfuckers can sign up for the fucking one day event. A lot of people do. A lot of these CEOs, a lot of these people who don't want to suffer as a living, who don't want to suffer as making it a habit. What they do is they go out and they recruit these people to put them through a two day, three day fucking challenge. Anybody can do that shit because your mind can process two or three fucking days of suck. What you're doing, my friend, is going to be damn near a month of suck. So basically you're going to have a lot of days, especially in the morning time. The mornings when you wake up and your body says, go fuck yourself because I don't fucking feel like doing this today. And you're going to look at, because you're running six miles a day, I believe, which you know what's going to happen to your fucking ass is you're going to wake up in the morning and you're going to fucking do what I do. People think, oh, David Goggins just wakes the fuck up and he just gets his shit on. He gets his fuck ass. No, I don't. I don't get up and get after it. I look at my shoes sometimes for hours. I pass them. I go, I get stuff to drink. I go to the bathroom. I watch TV. I'll start doing some work and I look at those fucking shoes because why my body's saying go fuck yourself. So you have to be able to win the morning. You have to be able to not allow that to get too deep in your brain. And when things get really tough for you, when you're out there on like day 17 and your knees are hurting and your back is hurting, your shoulders are hurting, your elbow tendonitis and all kinds of shit going on, you got to start remembering your resume. A lot of people don't remember what the fuck they've accomplished in life. And at that time of suffering, you have to be able to fucking go through and pull up that fucking who the fuck I am resume and say, oh, for you, I'm sure you studied your fucking ass off for hours and days and years to get where you're at. I guarantee you did shit harder than this. And that's basically what you have to go back to. But it's hard to do because in that moment of suffering, all you can fucking think about is getting the fuck out of it. So you got to take that one second to pull yourself out of that suffering, to have a clear fucking thought. It's hard to have clear thoughts in the midst of extreme pain and suffering. Find that clear thought. Remind yourself of what you've been through back in the past, back in the day to get to where you're at today. So that's what I do is a counselor reminder. And then through that process, I guarantee you your mind and body will say, oh, we got this. We've we've been here before. Maybe not in that kind of pain and suffering, but we've been here before in the demons of your own mind. So that's the best reminder in the world. All right. So what I'm going to attempt, I'm going to do is 20,000 push ups and pull ups combined. And on top of that, I'm also going to do squats, ab rollers and run six miles every day. So the routine is this. Run six miles and then do 34 rounds of the following 15 push ups, five pull ups, five ab rollers and 10 squats just over and over 34 times a day. I might split it up three times a day. I might do it twice a day. I might do it just one in a day. My plan is to do the hardest one early on in the day, try to get as much done as possible, most likely about 14 rounds and then do another 10 and 10 later on in the day. The goal is for each round like that to take about two minutes. So for 34 rounds, that's 68 minutes. So the start is tomorrow, Wednesday, June 10th, going on for 30 days after that. So let me quickly do a round to give you a sense of the form and then talk about it. So there you have it. That's one round. The hope for that is to take about a minute and the total is two minutes. You get a break of about a minute between each session. Obviously good form is important. There's always going to be a keyboard warrior out there. I'm looking at you with some sweatpants in their mom's basement with Cheetos all over the place, way out of shape. Who's going to comment about the fact that the pushups aren't all the way down or aren't all the way up and the same with the pull-ups, so on and so forth. None of that matters. Good form in this case for a pushup and a pull-up is something that minimizes the risk of injury. I think this whole thing is a tough workout to be honest. Yesterday and the day before I did over 400, which was I was trying to see, is this even possible? Can I do 680 total pushups and pull-ups in a day? It seems like an insane number to me. I did 400 and it was tough, but doable. I think if 400 is doable, then 680 is too. I think I can certainly with a little bit of suffering do it for a few days. If I can be fortunate enough to avoid injury, the rest of the month is just mental. That's where the battle is. That's where all the good lessons are to be learned. I also asked David, by the way, there's a laptop over here, that's why I'm looking over here. I also asked David about the fact that some people might join in on this challenge in whatever capacity they can and what he recommends for me and for others to stay injury-free while still pushing their body and their mind to the limit. This challenge, you're going to get injured. If you don't have a good base, like for instance, if you don't do a lot of pull-ups, a lot of push-ups, what you do for both is you're utilizing these elbows, which you get tendonitis severely bad, and your shoulders. With the push-up, you're here, this is your hinge part. Yeah, you are using your chest, using your triceps, but this hinge is being used an awful lot, this elbow hinge. These shoulders are being used an awful lot. Even the pull-up motion is being used an awful lot. Basically, what happens is you're going to get injured. For a lot of you, I would definitely suggest doing a lot more squats, do a lot more abs, doing things like that. Even abs, you can injure abs, but going from zero to hero, you will have some injuries. You got this isom, try to get your body to recover as fast as possible, taking in proteins, taking in aminos, things like that, getting as much rest as you can, but you're going to get overused training issues with your body. That just comes with the, it's just nature of the beast. Like I said, those of you who start to get injured, start making those squats your go-to because your legs can handle so much. When I was doing the pull-up record, people wondered why that was so hard for me. First of all, I had a jacked up body when I was doing it, a very, I guess, out of alignment body, but your only contact point is your hands. There's been times in 200 mile races where I tore my quad, completely tore my quad. I was able to bandage it up and walk it out. I was able to walk 75 miles. That's the thing. Your legs can handle a lot of abuse, a lot of abuse. So when you start hurting, go to your legs. So there you have it. Don't use any kind of injury as an excuse to stop moving, stop exercising, just find an alternative exercise that doesn't hurt. I'm going to really try to stick to the push-up and pull-up and do everything I can to remain injury free. For me, a part of avoiding injury is stretching really well, also doing good warmup. For me, I'm doing the six mile run before doing the body weight exercises. Also, obviously, nutrition is important. Everybody has their own journey. I've dieted my whole life all kinds of ways, did combat sports my whole life, so cutting weight and performing optimally was always important. For me, whatever you think about it, the main diet that I've come to enjoy is either keto or carnivore, so primarily a meat-based diet, meat and fat, very low carb. So mostly for me, that just means ground beef, sometimes steak, and keto-friendly, low carb snacks here and there. Nutrition-wise, it's pretty basic, but I do take some stuff. So I take sodium in my food. So I put quite a bit of salt in there, magnesium. Also take fish oil in pill form, not much, like two or three fish oil pills a day and an emaldi vitamin. That's it. It would be, of course, awesome if other folks, if you decided to join in on this challenge at whatever level you want, it would just be fun to do pushups and pull-ups together or any kind of difficult exercise activity that will challenge you. Do it every single day. If you haven't ramped up to it, you haven't done it much, what I would recommend is to start very low to where almost you're comfortable and then increase it day by day to when you quickly become uncomfortable. But give your body time to adjust. That's really important. Again, the point here is to do a difficult exercise, but really is to do it for 30 days. And what I'm doing, and I hope you do as well, it's not just for 30 days. It's for 30 days you do something difficult, but you form that habit and you stick to it for months to come. Especially in these times, exercise is just so important for staying healthy and staying sane. So I'd love it if you joined in on the challenge. I'll have a spreadsheet linked in the description where I'll keep track of the reps that I'm doing on a daily basis just so you can follow along. You can also just copy that spreadsheet and use it for yourself to track your own numbers, share it with me on any of the social platforms. I'd love to see your progress. I'll also maybe go live on one of the platforms, Instagram, YouTube, on our Discord server, Twitter. I don't know. I don't know if there's interest in that. I'll be honest. I tried Instagram live a couple of days ago to work out, and it was a little weird for me to work out while other people watched, so I'm not sure. But maybe if there's interest, let me know. Maybe I can take a few questions about the challenge. I'll probably record video throughout the month and just publish it at the end. So with that, I'd like to thank David Goggins. I follow him on Instagram, and he's a constant reminder that I need to push myself to my limit mentally. I asked him, of course, whether he'd want to be a guest on the podcast. Let's see what he had to say. No problem, man. I love what you do. I've seen some of your work. You're an extremely intelligent guy, so your intelligence, and I see that you're willing to go the next mile. So you're willing to be a guy that is just not... All right, so for instance, I was in the military. They said, you better be real smart, or you better fucking be real hard. So I was the real hard guy, and I had to develop the smarts. I see that you're a really smart guy, and you're developing the hard. So I think that we can really have a good podcast together. It'd be a really interesting conversation. So there you have it. It's on. I think I'm recording this video, but most of this journey is quiet. It's on my own. It's with myself. It's a quiet journey of suffering. So yes, it's a way to get exercise back into my life, but it's really a chance to rediscover myself by doing something really, really difficult for a prolonged period of time. No matter what, I'll be a different, and I think a better human being on the other end. If you join me on this in your own parallel journey, great. Either way, stay healthy and stay hard.

https://youtu.be/xZlt2tqHd80

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Diana Walsh Pasulka: Aliens, Technology, Religion & the Nature of Belief | Lex Fridman Podcast #149

The following is a conversation with Diana Walsh-Pasulka, a professor of philosophy and religion at UNCW and author of American Cosmic, UFOs, Religion, and Technology. This book is one of the most fascinating explorations of the interconnected nature of technology, belief, and the mystery of alien intelligence. Quick mention of our sponsors, Element Electrolyte Drink, Grammarly Writing Plugin, Business Wars Podcast, and Cash App. So the choice is health, grammar, knowledge, or money. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. As a side note, let me say, as I did in the recent video on how many intelligent alien civilizations are out there, that the nature of alien life, intelligence, and how they might communicate with us humans is likely stranger than we imagine, and perhaps stranger than we can imagine. What is most fascinating to me is how the belief in the communication with such civilizations changes people's understanding of the world, and as Diana argues, the technology we create. Technological innovation itself seems to manifest the mythology in our collective intelligence that turns the seemingly impossible into reality in just a matter of years, through the belief of individual humans that carry out that innovation. The nature and power of this belief, in both technology and extraterrestrial intelligence, is mysterious and fascinating, perhaps holding the key to us humans understanding our own mind, our consciousness, and engineering versions of it in the machines we create. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcast, follow on Spotify, support it on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Diana Walsh-Basulka. You are a scholar of religious belief, or belief in general, so the fascinating question, what do you think is the difference between our beliefs and objective reality? What is real, period? Sure, what is real? Easy question. So first let me start with belief. So belief is generally, there are different definitions of belief just as there are different definitions of what is real. So for belief in my field, it would be attitudes toward something that dictate our actions. So we believe the sun is gonna rise tomorrow, therefore we act as if it will rise tomorrow. Beliefs can be wrong. For a long time, people believed, and actually some still do, that the earth was flat. Well, that's obviously an erroneous belief. So beliefs can be wrong. Now, the bigger question that philosophers ask is, is this belief accurate toward what we consider to be objective reality? So now let me go to objective reality. So what is real? I don't think we can actually obtain a correct understanding of what is real. And in that sense, I have to refer to a philosopher again, and that would be Immanuel Kant. So Immanuel Kant is one of the, he was basically in the 1750s, he wrote critiques of reason and things like that. So he said, well, if you're a philosopher or have any kind of understanding of Western history, you know who he is. He had this idea that we can actually never get to the thing in itself, okay? So he called that the noumenal, the thing in itself. He said, let's take this table, for instance, that you and I are talking across. So this thing is a table, you and I both know that, we assume it's real, we believe in it because we put our water on it and then our water stays on it, okay? However, can we know this thing in and of itself as a table? So that would be what he then would call the phenomenal. How do we know that that phenomena exists as we know it is, okay? How do we know? We use our faculties. So we use our senses and things like that. But again, even our senses can be wrong. So I've been on committees just recently, this year, last year, for hiring professors in my department who are philosophers. And we're hiring metaphysicians and people who are thinking about the nature of reality. And basically what I've learned from them, yeah, they're very- I'd love to attend those faculty talks. Metaphysics professors. What's funny is that for each one of them, I'm convinced each time. They all say different things, but they're so convincing. I'm like, yes, hire that one, right? Is it like historical philosophy at a particular time? No, no. What do they do? No, they're- Do they have an actual belief? They're practicing metaphysics? Metaphysicians, yes. So what they do is they come and they're usually excellent philosophers from Harvard or USC or whatever. They come and they give what's called a job talk. That's what philos- Every academic does a job talk in order to get a- They talk to us about a department about what they do. And so it so happens that we need a metaphysician and now we're hiring again for one. And so I've learned a lot about metaphysics in the last year and this is what I've learned. That they use physics as a basis for understanding what we can know about what is real. And what is real is really difficult to pin down. And so your question is, what is belief? Well, belief, does it correspond to reality? That's the question I would ask. And first, we don't even know what is real. So the table, they would say, how do we know that the table even exists? Well, how do we differentiate it from the floor, for example? So these are the questions that philosophers are asking. No one else's, of course. But philosophers are asking these questions and they have different answers for it. So I would say that it's very difficult to know what is real. And in fact, what I do usually is I paraphrase my friend and colleague, Brother Guy Consolmagno. He's a Jesuit priest, he's also an astronomer, and he's the director of the Vatican Observatory. And so he says this, he's a very smart person. He says, well, truth is a moving target. So basically, to know what is real out there, like gravity or something like that, you've got to approximate it. And as human beings, we have senses to tell us what, at least so we don't get hurt, we're not gonna fall off a building or something like that. We have eyes to see and things like that. So we can approximate what reality is, but we're never gonna get to it unless we develop better senses. And I think that that is what we are in the process of doing. We're developing better senses. We have telescopes, we have microscopes, we have extensions of ourselves, which are now called technology, and we can get to a better understanding of what reality is and what the objective world is, and therefore our beliefs can be honed. So we can get better beliefs, more accurate beliefs, but can we get beliefs that actually correspond to reality? Not in any precise way, but in approximate ways. So I hope that's not too big an answer to your question. Well, do you think beliefs in themselves can become reality? I mean, so you've now adapted the, in this little bit of a conversation, adapted the metaphysician view of reality, which is the physics. Yes. But we humans kind of operate in the space of ideas, very much so. Like we've kind of in the collective intelligence of human beings have come up with a set of ideas that persist in the minds of these many people, and they become quite strong and powerful. Like in terms of like impact on our lives, they can have sometimes more impact than this table does, than the physics. Yeah, I agree. And in that sense, is there some sense in which our beliefs are reality, even if they're not connected to the physics? Yes, even if they're not real, yeah. Even if, okay, so yes, absolutely. So our beliefs are tremendously, they create social effects, absolutely. There was a belief that, I'm gonna use this example. There was a belief back in the day, and we're talking about, when I say back in the day, I'm a historian, so I'm talking about like 1,000 years ago, right, that women had no souls, okay? So look, I don't know if human beings have souls. I can tell you this though, that if human beings have souls, probably animals do too. That's my own personal belief. That's not a professor belief there. But there was this belief among the Catholic magisterium, which runs Europe, that women had no souls, so they had to have this big meeting about it. Did women have souls? But that belief had consequences for women. I mean, women were treated and have been treated as if they didn't have souls. Okay, so there's- And the soul was really the essence of the human being. It was, it's called the animus, right? It's what is the essence of what is eternal, when women weren't eternal. Here's another example, okay? This is an example from my own research. All right, so there in the Catholic tradition, there's this idea of purgatory, hell, and heaven. And these are three destinations that people can go to when they die. And if you're great, you go to heaven automatically, and you're considered a saint. If you're okay, you go to purgatory, right? And you suffer for a time and then get back into heaven. If you're terrible, you go to hell, right? Okay, well, there was a place that the Catholics determined, and this was a belief for a long time, like a thousand years or more, and it was called limbo, all right? And limbo comes from the Latin, limbus, and it means edge. And it was either on the edge of hell or on the edge of heaven. No one really could determine which it was. No historians are like, well, this person says it was on the edge of heaven. Well, listen, this was a terrible, first of all, there is no limbo anymore. In 2007, Benedict, the then Pope, got rid of the idea that there was limbo, okay? So Catholics kind of went crazy because they didn't really know, they forgot that limbo existed, and they thought it was purgatory. And they said, how could you get rid of purgatory? But actually, he just got rid of this idea of limbo. Oh, so that's a distinct thing from purgatory. It was. And by the way, people should know that they have a book on purgatory that came before. American Cosmic, yes, I wrote a book on purgatory, yeah. Anyway, so limbo is a distinct thing from purgatory? Yeah, and the types of people who go to limbo happen to be virtuous pagans, okay? Like Socrates or somebody like that. And children who weren't baptized. So think of this. Think of for more than 1,000 years, mothers and fathers gave birth to babies who weren't baptized and couldn't be buried with their family in these burial, and then they couldn't be reunited with them in heaven. Think of the pain and suffering that that caused. And that was nothing. Limbo's nothing. Yet the belief in it caused untold suffering. And that's just a small example. And that was as real to them. It was absolutely real. I mean, the effects were real, let's put it that way. The place itself, not real. But the families themselves, do you think they really believed it? They totally believed it. As much as the table is real? Yes, I've read, but listen, we have trigger warnings today, right? So don't read this. It's gonna make you upset, okay? History, primary sources, no trigger warnings, okay? So you're going through somebody's diary from 1400, and you hear the suffering and pain that they went through. There were times in my research where I'd have to put my primary source down and just basically go outside and take a walk because it was so horrific. I knew it was true, because they wouldn't write something, they're not gonna write in their diary something that's not true, and it was horrible. So yes, these people went through untold suffering for nothing, because they had an erroneous belief. But they didn't know it was erroneous. So it was real to them. Yeah. So I don't know if you're familiar with Donald Hoffman. He has this idea that in terms of the distance we are from being able to know the reality, which is there, the physics reality, is we're actually really, really, really, really far away from that. Yeah. So I think his idea is that we're basically completely detached from it. Yes. What's your sense, how close are we to the reality? We'll talk about a bunch of ideas about our beliefs in technology and beyond, but in terms of what is actually real from a physical sense, how close are we to understanding that? Pretty far. I'm gonna use examples from what I do. Okay, so this idea that we're suspicious of what we actually think is real is not new, of course. It goes back a long time, thousands of years, in fact. And philosophers, I'm not actually technically a philosopher, but I was one. I'm a professor of religious studies. Yeah, but what do you introduce yourself at, like at a bar when the bartender asks, what do you do? I never tell people what I do, especially on airplanes. It's a bad idea. So generally, if they push, though, I say, I'm the chair of philosophy and religion, although I stepped down last year, so I'm no longer the chair. But I have a master's degree in philosophy, and I was a philosophy major, and I still study philosophy, so I integrate it into my research. All right, so this idea that we can't know, we're suspicious of what we know, it's called external world skepticism. That's the official philosophical name for it. Our faculties and our senses don't give us accurate perceptions of what is there, okay, especially at a quantum level or a molecular level. I mean, that's just obvious. So yeah, so I think that the person you mentioned is correct in that. I think we're far away from it. I think you're talking about our direct senses, but we have tools, measurement tools, from microscopes to all the tools of astronomy, cosmology, that gives us a sense of the big universe and also the sense of the very small. Do you think there's some other things that are completely sort of other dimensions, or there's ideas of panpsychism, that consciousness permeates all matter, that there's fundamental forces of physics we're not even aware of yet? Oh, absolutely. I do think, and this is why I write about technology, and I mean, that's actually what I specialize in is belief in technology with respect to religion. So in my opinion, thank goodness for technology, because where would we be without it? I mean, frankly, I think that it's, like Marshall McLuhan was the person who said, technology is like an extension of our senses, and I absolutely believe that to be true. I think that we're lucky that Prometheus gave us technology, okay, and that we use it, and we're making it better and better and better and better, and that makes us more efficient. It makes us more efficient as a species, and my point is that I think that our instruments, I mean, I don't want to be a religious technologist, but our instruments will save us. I mean, they're already making life better for us. You think it's important that they also help us understand reality more directly, more deeply? I think directly is better than deeply. I think directly, more directly, is probably a more accurate term for what you're trying to, I think, ask me. Can we actually, I mean, I think you're asking me that question that Kant basically was trying to get at, was can we know the thing in itself? Can we know that? Can we have some kind of intense knowing of it? It's almost mystical, and I would say that that's where religion comes in, okay? That's where we talk about religion, and if I may also go back to Immanuel Kant, this idea that he, just before he died, just as he died, he was working on, he did this critique of reason where basically he believed, he basically talks about can we know what's real? And he basically has this long, that question, can we know what's real? And then 1,000 pages later, no. I'll just give you the rundown, okay? So, okay, no. I'm just gonna be a little alert. Yeah, yeah, exactly. Then he does this other critique, and okay, so he does like three critiques. Then he does this critique of judgment, okay? Well, judgment is this other thing altogether, and I think that that's what you're getting at. So how do we know things? How can we know things really intensely and intimately? And I think that he thought that judgment was the idea that we can actually know the thing in itself, and he was working on that as he died, and then he never finished it. Hannah Arendt, another philosopher of the 20th century, took it up, took up the critique of judgment, and tried to finish it. Oh, why the word judgment? Because judgment, think about it. When you see a work of art, who judges that to be decent, okay? So there is a group of people who come to the decision that that's rotten, or that's pretty good. You know, like I noticed that you like to play guitar. Well, you choose music that I happen to like too, okay? So you and I both have a sense of judgment, just a sense. So he said there's a sense that some people have. Why do certain communities have a similar sense? What dictates that? And so he was working on that. He thought it had something to do with the knowledge, the intimate knowledge of the thing in itself. Yeah, so another philosopher that philosophers actually don't like at all, but religious studies people do is Martin Heidegger. So Martin Heidegger has some great essays. One is called, What is a Work of Art? And again, he gets to, you know, he talks about Van Gogh and Van Gogh's shoes. You know that picture, the painting Van Gogh's Shoes? It's really a really intense picture. It's just shoes. It's, you know, it's an amazing painting of shoes. And I think everybody can agree that's a cool picture of shoes, right? And so why? You know, the question is, why is that a cool picture of shoes? You know, what kind of knowledge are we accessing to determine that indeed that works, right? And in fact, we still like it. So basically the nature of knowledge and what does it represent? It can operate in the space of, that's detached from reality or can it ultimately represent reality? I guess that's the, is that the space of metaphysics? Is that the- Yeah, so what can we know is actually called epistemology. Epistemology. But metaphysics is- Intersect, I guess. Is basically what is the nature of reality. Right, and those intersect. Absolutely, yeah. A lot of things intersect in philosophy. We just have fancy names for them. Another non-philosopher that may be considered a philosopher since we're talking about reality is Ayn Rand and her philosophy of objectivism. What are your thoughts on her sense of taking this idea of reality, calling her philosophy objectivism, and kind of starting at the idea that you really could know everything and it's pretty obvious. And then from that, you can derive an ethics about how to live life. Like what is the good ethical life and all the virtue of selfishness, all that kind of stuff. So you talked to a lot of academic philosophers. So I'd be curious to see from the perspective of like, is she somebody that's taken seriously at all? Why is she dismissed, as I see from my distant perspective, by serious philosophers? And also like your own personal thoughts of like, is there some interesting bits that you find inspiring in her work or not? Okay, so Ayn Rand, I've had so many exceedingly intelligent students basically give me her books and basically say, please, Dr. Pasulka, read this book. And I'll tell them, yes, thank you. I've read this book before. And then when I engage in, let me put it this way, they're religious about Ayn Rand. Okay, so to them, Ayn Rand represents some type of way of life, right? Her objectivism. Now, why is she not taken seriously by philosophers in general? Well, let me put it this way. Philosophers in general tend to get pretty, I guess you could call it they're kind of scientists, but with words. I always call philosophy, when I describe it to someone who's gonna take a philosophy class, I say, it's basically math problems, like word math problems, okay? So that's basically what it is. So they take words very seriously and they're very formal. And definitions very seriously, yeah. So they all wanna get on the same page. So they're not, so there is no confusion. So for Ayn Rand to basically say you can know everything and establish ethics from that, I think philosophers automatically say no. Now, that doesn't mean I say no. In fact, we have at my university, a wonderful business school. And when you walk into the Dean of the Business School's office, Ayn Rand is everywhere. So it's, so I wanna say that not all academics are anti Ayn Rand. And in fact, I don't think philosophers are either, except that they don't teach Ayn Rand, okay? So in one sense, you could say that because they don't teach her, they're being exclusive in what they teach. Or very particular, perhaps is another way to put it. Yeah, it's hard to know where to place people like her because, you know, do you put Albert Camus as a philosopher? So I guess what's the good term for that? Like literary philosophers? Or whatever the term is, it's annoying to me that the academic philosophers get to own the word philosophy. Because like, it's just like people who think deeply about life, is what I think about as philosophy. And like, to me, it's like, all right. So I know Nietzsche is another person that's probably not respected in the philosophy circles because he is full of contradictions, full of- I love Nietzsche. Nietzsche's my favorite philosopher. Oh, really? Yes, I absolutely love Nietzsche. So he's definitely, you know, I love people that are full of ideas, even if they're full of contradictions, and Nietzsche is certainly that. Absolutely, yeah. And Ayn Rand is also that. I'm able to look past the obvious ego that's there on the page. And the fact that she actually has, in my view, a lot of wrong ideas. But there's a lot of interesting tidbits to pick up. And the same goes with Nietzsche. And I'm weirded out by the religious aspect here, on both the people who like worship Ayn Rand and people who completely dismiss her. I just kind of see it as, oh, can we just read a few interesting things and get inspired by it and move on? As opposed to- No. The problematic binary thing. Is there something you find about her work that's interesting to you, or her personality or any of that? Oh, I think she's fascinating. I don't dismiss her. She was a woman who reached a level of success with her mind at a time when that was difficult. So, I mean, she's definitely worth looking at for even that reason. But also, her idea, I guess part of the situation with Rand, first of all, I think that her work is, you have to, it's misinterpreted. Okay? And I think that's the same with Nietzsche. Like a lot of people think that, I mean, in fact, it is the case that Nietzsche's writing before the 20th century. So he's got the, you know, he's somewhat, his rhetoric is sexist and racist and, you know, of the time period, right? He was a educated philosopher of that time period. However, his books are amazing and Nietzsche's philosophy is incredible. And I think that, I think that's what you're saying about Rand too. And I agree. I mean, I think that we get caught up, I mean, likely we should, and we should contextualize these thinkers in the time period within which they are. We should not forgive their, you know, cause there were people during Nietzsche's time that were, you know, feminist and not racist and things like that. And, you know, so, but each has merit. I mean, I would say Nietzsche is, and you did ask me to talk about some of the books that made the largest impact on me. And Nietzsche's Gay Science is one of them. It's one of the best books ever, in my opinion. I do think Nietzsche was, I don't know about exactly sexist. He certainly was sexist, but it felt like he didn't get laid much in his life. No. It felt like he was extra sexist. I was like, his theories on women are like, all right. He's pretty angry. He seems frustrated. Yeah. I was like, all right, calm down, buddy. Oh, the fate of philosophers. I just ignore everything Nietzsche says about women. So can we talk about myth and religion a little bit? Yes. I mean, can we start at the beginning, which is like myths, how are they born? There's this collective intelligence amongst us human beings and we seem to create these beautiful ideas that captivate the minds of millions. How is such a myth born? Great question. Okay, so that brings us to terminology again. And in my field, we definitely, I think, try not to distinguish between religion, I guess this is gonna be controversial, I think, between religion and myth because we call other cultures, religions, myths, right? And then we call our myths, religions. And I guess myth has a bad connotation to it that it's not somehow real. Yeah. Now, what's interesting is that people like Plato, who lived thousands of years ago, 2,500 about, basically made this distinction himself within his own culture, which was Greek, right? So Plato is a very famous Greek philosopher. And he would say things like this. He would say that he would make a distinction between the reality of the one God or the one, he would call it, he didn't use the word God, but he's referencing a divinity, okay? And he believes in the soul, okay? So, but he would also say that the gods and goddesses of the Greeks are just myths. So even he would make that distinction. Again, he would say the population is not too bright, so they believe in these gods and goddesses. But he himself is talking to his students and he's basically talking about forms, so that seem to live in these other dimensions. Like this table, let's go back to this table that we're talking around right now. He would say that this table is the instantiation of the form table, and that there's this table that actually exists somewhere. It's this place where numbers exist, like the number two. Okay, so we use the number two mathematically, therefore it exists, but have you ever seen a real one? Have you ever seen the real two? No. No. Okay, so but where does it exist? So he says that tables, so he was also talking about things that he says are real, making a distinction between the people, and by the way, he got this from Socrates, his mentor, who was killed by Athens because he would say such things. People don't like to be told that what they believe in is not real, right? Yeah, by the way, his idea of the forms, it's just, you're just making me realize how incredible was that something like that was able to come up with that. I mean, that idea became a myth, the idea of forms, right, that permeated probably the most influential set of ideas in the history of philosophy, in the history of ideas. Yes, yeah, I mean, Plato, we know him for a reason, right? Yeah, so let's say that we're not, it's a gray area between religious and myth, and maybe not even. It is gray, yeah. So how's that idea with like little Plato start and permeate through all of society? Oh, how does it happen? Okay, so there are different ways that religions work. So a lot of people would call the UFO narrative today, and this is what I talk about in my book, like a myth, right, the UFO myth, but a lot of people believe in it, okay? So how do these things work? Well, what I did was I took, there's a, Anne Taves at UC Santa Barbara, she's a pretty well-known academic who studies religion, and she has this building block definition of religion, like it builds, okay? And so she says, there are no religious experiences or mythic experiences, there are experiences, and then they get interpreted as religious or mythic, okay? And so I use that with the UFO narrative. So I take, and I compare it to the religious narrative. So basically what happens, what happens is this, is that a person generally has a very intense experience. It could be with something that they see in the sky, a being that they see, like Moses in the burning bush or something like that. They tell other people, okay? And those other people believe them because they say, that guy, let's take you, okay, Alex. Okay, so you're playing some of your music, Jimi Hendrix shows up out of the blue. So Jimi Hendrix, who does electric church stuff, right? The electric church movement. So he shows up. I was, sorry, for a small attention. I'm not aware of, I apologize if I should be. I'm just, know how to play all of the songs. Electric church, is this a thing? Yeah, yeah, it's Jimi Hendrix's thing. Yeah. That was like a philosophy of his or what? Yes, yes, yes. So he thought he was, it was like a mission for him. Like he was a missionary and he was like doing the electric church. It was through his mission of music that he was actually impacting people spiritually. And I think you have to agree that his music is really spiritual, yeah. Wow, that's so cool to know that there's like a philosophy there. Yeah. I wonder if he's ever written anything. He's spoken about it many times. Interesting. I'm gonna have to actually do some research here. Wow, that adds another level of depth. That's awesome. Okay, so. Okay, so say Lex is playing one of his songs. He shows up. What's your favorite Hendrix song by the way? Oh, that's a hard one. I like Castles in the Sand. It's a sad one, but I like it. So I'm playing something and I show up. And all of a sudden, boom, just like Elvis does for people, Hendrix shows up, all right? And then you're amazed and he tells you something that's very, very significant. And he says, you need to tell other people this, okay? So then like, okay. I go on social media. Yes, and you start, and because people believe you and because you are a person of credibility, people believe you. And so all of a sudden a movement starts, okay? And it's the Hendrix movement. It's Hendrix two or something like that. We call it something, the next iteration of Hendrix, right? Hendrix lives, but he loses this vibration and only Lex can like, you know, can manifest this vibration, okay? So like, this is how religions start, you know, excuse your audience who are religious. I'm actually practicing Catholic. So this is how religion starts. They start with, first off, a contact experience. Not all of them, but a good portion of them. Some person has an experience that's transcendent, sacred to them. And they go and they tell other people. And then those people tell other people. And then something gets written about it, okay? And then it becomes, because it's a charismatic movement, people become affected by it. And if too many people are affected by it, an institution steps in and tries to control the narrative. So this is what you'd call the beginning of a religion or a myth, a very powerful myth. And so it's almost like a star, right? A star is born, okay? Yeah. When you say institution, do you mean some other organization that's already powerful? Yes. Someone to become overpowered by this new movement? Yes, absolutely. Is this usually governments? It's usually, yeah. So I have a couple of examples. I use the example of the Christian church in my book because I'm most familiar with the history of Christianity. And, you know, Christianity was started by this Jewish man. And it was a movement that, you know, he was a very powerful, charismatic person. Other people believed in him. And then his followers talked about him. And then, you know, usually early Christians before the 300s were generally people who were disenfranchised because he had a pretty radical idea that, you know, humans should have dignity. And this was pretty radical during that time. So women who didn't have dignity and, you know, slaves who didn't have dignity at the time converged to Christianity and drove. And so what happened was that all of a sudden it became this belief system that was undercurrent. And then Constantine, who was an elite, had an experience and made Christianity a state religion. By that time, there were different forms of Christianity, probably hundreds of them, well, most likely. And Constantine and the people who were powerful with him decided that their idea, this is the Council of Nicaea now, decided that there was one form, and they called it universal, the one form of Christianity, and this should be it. And so they kind of took out all the other denominations of Christianity and different forms of it. So you can see that a very, very powerful set of beliefs put a culture on fire, right? And so how did they, they had to deal with that fire somehow. And so they narrativized it. They decided, how do we interpret this? And they interpreted it as they wished, but that wasn't the only interpretation of Christianity. I have another example. I'm in a Catholic church a lot of times, and I'm gonna use the example of Faustina. She's a nun and she's Polish. And I think it was in the early 20th century, if not the 1800s, that she had a very powerful, many experiences actually of Jesus. And she saw Jesus with rays coming out of his heart. And basically she called this his divine mercy, and it became a devotion in Poland and it spread. The Catholic church was not into this at all, okay? And so they did everything they could to try to suppress Faustina's influence, which was growing and growing and growing and growing, okay? And so they were very successful in trying to keep her quiet, and she died, okay? Years later, John Paul II, Polish, sainted her and created the divine mercy devotion, which is worldwide now, and millions and millions of people. But do you see how they completely controlled it there? So fascinating that it just starts with a single, like you said, contact experience, and experience is the key word. Is your sense that those experiences are legitimate? So it's not somehow artificially constructed? Yeah, I think for the most part, they're legitimate experiences that people have. Why would someone wanna put themselves through what they go through? Why would Jesus wanna get crucified? I mean, that's a pretty nasty way to die. Why would Faustina bring this upon herself? The people that I meet who've said that they've seen UFOs, that most of them don't wanna be known because of the ridicule that goes along with it. So I honestly think that there are people who are maybe not stable and would like the attention, but for the most part, normal people don't want this attention. So you mentioned building blocks. You did mention the word God, or sort of the afterlife. Are those essential to the myth? So there's a contact experience. Is there some other aspects of myth and religion which makes them viral, which makes them spread and captivate the imagination of people? Yes, is there a pattern to them? I think that for each era, it's different. And people have, first, let's talk about the definition of religion, if that's okay. Because most people assume the definitions that we in the West are familiar with, which is that of Christianity, Islam, Judaism, monotheistic religions. And there are, that's not, I mean, those are just some religions. There are so many different types of religions. Some religions have no God at all. Zen Buddhism, for example, is a religion that asks you to take away your belief structures, like to kind of like, in fact, I would call that a Kantian-type religion, right? In that it's basically telling you to get rid of your concepts of what you think about things so that you can actually have the experience, like you were talking about earlier, of the thing in itself. And they call that satori. So there are people who believe, they try to, they call it meditation, Zen meditation. And it's fairly radical, actually. In some monasteries, I don't know if they still do this, but they'll whack you on the head if you appear to be not focusing and that kind of thing. They do things to basically take you away from your conceptions of reality and bring you into a state of all that is, which is what they call satori. And that has nothing to do with God. I like this religion. And anything that involves sticks and whacking in order for you to focus better, I'm gonna have to join a monastery. So, okay, so digging into definitions of religion. So what do you think is the scope that defines a religion? Oh, okay, so in my field, we have a few different definitions of religion, as you can imagine, just like philosophers have different definitions of what is real. So I take this definition, and it comes from John Livingston, and it's, religion is that set of beliefs and practices that is inspired by a transformative, what is perceived actually to be a transformative and sacred power. Can you say that again? Yeah, so religion is a set of, it's not just belief, it's also practices. It's both belief and practices, because you won't have the practices without the belief. So you have those together, okay? And it's inspired by what is perceived, because we don't know if it's real or not, what is perceived to be of sacred and transforming power. So perceived by the followers? Yeah. Is that related to the original sort of experience? No, no, well, it's perceived by the followers. That's a really good definition. So, and that's the governing idea, is that there's something of great power. Yes. Perceived to be of great power, to which you can connect yourself, either emotionally or intellectually somehow, in order to explore the world that is beyond your own capabilities. Yes. And is there communication also involved? Or- Generally. Yeah. Yeah. That's a great definition, okay. So within that falls everything that we've talked about so far, including technology and alien life and so on. Do you think ultimately religion is good for human civilization? Let me maybe phrase it differently, is what's religion good for? Okay, yeah, that's a great question. Thanks for asking that. Most people don't ask that. And I think it's the question to ask. Why do we still have religion? That's the question, right? Because scientists and others, scholars, humanists even, thought that there's this thing called the secularization thesis. And it's this idea that the more we progress rationally and we have better instruments for understanding our reality, the less religious we will be. But that's been found to be untrue. We're still very religious, okay? So why, why is it around? Well, it's adaptive in some way, in my opinion. Many people would not agree with me, but I kind of see it as an evolutionary adaptation. Now, think about religions, okay? Think about Christianity again, for one. Here comes this idea when you have this ruthless empire called the Roman Empire, which litters its roads with crucified bodies to let you know, don't mess with us, okay? All right. Here, all of a sudden, you have this guy saying, God is love, okay? All right, well, that's weird. Okay, so why? Why does this take off? Well, it takes off because we're becoming a colonial power. That means we're going into other countries, we're conquering them. We are, you know, how do we survive together as cultures that don't clash? Well, we have to have a belief structure that allows us to, and I think religions function that way, frankly. So religions help us, from Richard Dawkins' meme idea, it allows us to explore a space of ideas, and that in itself is the, so it's like evolution of ideas. And religion is a powerful tool for us to explore ideas. Because, you know, if I believe that men have souls. Do they? Yes, they do, okay. Wow. Wow. I'm still trying to figure that out. Well, I still, in terms of souls, do believe cats don't have souls, but we'll never be able to confirm that. Maybe if we get better instruments, you know, the soul instrument, you need to come up with that one, please. For cats? Yeah, not just for cats, but for all animals and people in general. For sure. You could put them in like a little, you know, soul machine and find out what's the status of their soul. That's funny. I hope we'll become a scientific discipline of consciousness and consciousness is in some sense connected to maybe what the meaning of the word soul used to be. And I think it's a fascinating open question, like what is consciousness and so on. Maybe we'll touch on in a little bit, but yeah, anyway, back to our- Religions being adaptive. I think that Christianity probably helped us become better people to each other as we moved into a more global society. And I also, it goes along with my book, which is basically making the argument that belief in non-human intelligence or ETs or UFOs, UAPs, whatever you want to call them, is a new form of religion. And how does that work with the scientific method? Do you think there's always this role of religion as being, in its broad definition of religion, as being a compliment to our sort of very rigorous empirical pursuit of understanding reality? Well, there's always going to be this coupling. We'll always redefine new eras of civilization of what that religion actually looks like. So you talk about technology and so on being the modern set of religious beliefs around that. So is that always going to, is religion always going to kind of cover the space of things we can't quite understand with science yet, but we still want to be thinking about? Oh, I see what you're saying. That's a great question. When you say religion, I would use the word religiosity because I think that we're moving out of the dogmatic types of religions into more of a, I hate to put it this way, but an X-Files type religion where we can say, I want to believe, or the truth is out there, but we don't know that it's out there or we don't know yet what it is, but we know it's out there. So there's this kind of built-in capacity for belief and something that we don't have evidence for yet. And that's a sort of faith. So I would say yes to that question, absolutely. I think it's adaptive in that way. We're moving into a new, I mean, heck, we've already moved into this culture. Most people have not caught up with it yet. I see that in the school systems, and I think that I'm hoping we can catch up fast because really it's moving faster than we are. So I mentioned to you offline that I'm finishing up on the rise and fall of the Third Reich. I'm not sure if you have anything in your exploration, interesting to say, but the use of religion by dictators or the lack of the use of religion by dictators, whether we're talking about Stalin, which is mostly secular. I apologize if I'm historically incorrect on this, but I believe it's secular. And Hitler, I think there's some controversy about how much religion played a role in his own personal life and in general, in terms of influencing the, using it to manipulate the public, but definitely the church played a role. Do you have a sense of the use of religion by governments to control the populations, by dictators, for example, or is that outside of your little explorations as a religious scholar? It's not outside of my framework, absolutely not. I think that it's done routinely. Propaganda is done routinely, especially, there's nothing more powerful than religion to get people to act, I think. I have, my mother's Jewish and my father was Roman Catholic, okay, from Irish extraction. And so both members, both great-grandparents came here under duress because they were being, what would you call it? There was an act of genocide on both sides, being done by other cultures, okay? So on the one hand, obviously we know about the Holocaust, okay, so they came, the great-grandparents came here to avoid that and they made it. On the other hand, there was an English genocide, we just have to say it, of the Irish. It was called a famine, but it wasn't one. It was a staged thing. And so millions of Irish left Ireland on coffin ships, is what they called them, because they usually wouldn't get here. Mine happened to get here, okay? So that's the context that I'm coming from. So in each case, for one thing, the Irish weren't considered, Catholics weren't considered, they were considered to be terrible. And there was a lot of anti-Catholic rhetoric here in the United States, which is kind of strange, because one of the, in fact, the most wealthy colonial family were the Carrolls in Maryland and they were Catholic. So when you look at the United States, at our history, and you see the separation of church and state, do you wanna know where that came from? That came from those guys. They convinced George Washington and Thomas Jefferson. I mean, they couldn't vote, yet they have their names on the constitution. Is that not a strange contradiction? So here you can see how propaganda works. There was anti-Catholic propaganda, there was anti-Jewish propaganda, and a lot of it was that these people weren't human, they weren't human beings. Another thing I'd like to say is that when the Irish did come here, they were a lot of times indentured servants. But that's terminology. What is an indentured servant? Slave. Pretty much. So in that sense, religion can be used- Derogatorily. Yeah, derogatorily as a useful grouping mechanism of saying this is the other. And it's powerful too, because behind it is a force of what people contend to be sacred, a sacred force. So it's up to God to decide who's, so you have to go along with what God says, of course. Well, that's basically, that's not the contact event. The contact event is usually some type of very specific, legitimate event that a person has with something that is non-human or considered divine. But when religions become narrativized, I would call it, by different institutions, that's when you're in danger of getting propaganda. You said Nietzsche, one of your favorite philosophers, he said famously, one of the many famous things he said, is that God is dead. Yes. What do you think he meant? Do you think he was right? Okay, good, I love this question. No one asks me about Nietzsche. I love Nietzsche. And I love Nietzsche. Okay, so first, actually, I do think, and I could be corrected and probably will be in all the comments. Well, first, Nietzsche, it's true, wasn't the first to say God is dead. I think Hegel said it, okay? No one reads Hegel. He's like so difficult to read that it's impossible. Same with Heidegger, as you mentioned. I love him, but yeah, he's really hard to read. So Nietzsche basically said God is dead. And let me give you the context for him saying that. He also said this. He said there was only one Christian. He died on the cross, okay? So he despised Christianity. And he said that- And the people who practice it. Absolutely, yeah. But again, he believed in Jesus. And he believed Jesus was, he didn't believe he was a divinity. He believed Jesus was a good man. And he died on the cross, okay? So he believed in the morality that's possible with Jesus. Yeah, he absolutely did. Yeah, he did. And Nietzsche basically was making a historical statement about God is dead. He said, and he was right. He was basically saying that in this, in the century in which he lived, and he died, I think, in 1900. Again, I could be wrong about that. So I just want to say that I believe he died in 1900. Okay, so he's writing in the 1800s. And he's basically saying God is dead and we killed him. Okay, so he's making a historical statement that at that point in time, with science just kind of getting better and industrialization happening, the idea of this thing beyond what we know as material reality is dead. So the substrate of Western civilization is dead. That's what Nietzsche is saying, if that makes sense. Yes. And he's basically says with that comes the Ubermensch, okay, which is the superhuman. And he says, there aren't many of them. He says, but they're gonna come. And he also talks about the philosophers of the future. And he's speaking and writing to them, is my belief. So he's basically telling you and me, because we're now the philosophers of his future. Yeah, he's basically telling us, this is what's happening now and look what it has done. He says, now everything is possible, all manner of terrible evil, because no one has the belief in God anymore. The belief that there is an afterlife, you asked about an afterlife. So with this kind of belief in a morality comes this belief, you can have morals without God, okay, people do. But what Christianity is this idea that you will reap what you sow. So if people don't believe that anymore, what will happen? And so that's what he's basically saying is that the basic anchor for Western society is now gone. Do you think he was right? Absolutely, absolutely right. But then again, what do you think if we brought him back to life and he read American Cosmic, your book, and he wrote, he tweeted about it, writing a review maybe for the, I don't know what they post, for New York Times, he'd be an editorial writer with a blue check mark on Twitter. What do you think he would say about this idea that you present that's a grander idea of religion than, you know. Like religiosity, like this new form. Yeah. Wouldn't that kind of reverse the idea that God is dead? Yeah, because it would bring up this idea of external intelligences that are not human, which is basically, a lot of religions talk about that. There are Bodhisattvas, there are angels, there are demons, you know, there's all these types of non-human intelligences that religion makes space for. So what I'm basically saying in American Cosmic is these new things are within the realm of UFOs and UAPs. So, no, I think that, well, I think Nietzsche would say that that's a progressive adaptation of religion, is what I would hope he would say. Nietzsche, however, is unpredictable, I think. I couldn't predict him. So I would say that it would be my hope that he would say this is an accurate representation of a move into a new type of religion. And it's adaptive, therefore progressive. He would probably be uncomfortable reading a book by a brilliant female professor. Who happens also to be short. I don't know if you read that. No. Yeah, oh, he said some pretty nasty things about short women. Oh my God. Yeah. Nietzsche, he should be canceled. No, no, please don't cancel Nietzsche. You have to take people in the context of their time. Although I'm pretty sure in his time he was also an asshole. He was. But assholes are people too. Okay. Just bad ones. You wrote the book American Cosmic, UFOs, Religion, Technology. What was the goal of writing this book? What maybe, we'll mention it, we have already mentioned it many times, but in this little space of a conversation, can you say maybe what is the key insight that you found that lingers with you to this day from the process, the long process of putting this book together? Sure. Just like with my book on purgatory, I went into the research thinking that it would be something that it was entirely not. It ended up being something completely different. And I think that's good. I think that people who do research are very excited actually when their research surprises them. So I was happily surprised by my purgatory book to learn that it was a place. And so I went into American Cosmic being a non-believer in UFOs entirely. And I came out being agnostic, okay? Kind of believer. Yeah. Yeah. So- But agnostic, sort of open to the mysteries of the world. Yes. And I didn't think that, first of all, I knew that the government was part of the situation. I just didn't know how much. And so I learned that quickly. And acclimated to it, accepted it. And noted that indeed, Horatio, the world is much more mysterious than we think it is. It's more mysterious. There are more mysteries in this life than your philosophy provides for. So as a sense, American Cosmic is about the mysteries of the modern life as encapsulated by the realm of technology and the realm of alien intelligences? Yes, I think that, I mean, I'd have to go off record as a professor and talk personally. As a person, I do think that there are mysteries of which we have an inkling. And if it's something as powerful as non-human intelligence, whether or not it's from another planet, extraterrestrial, or it happens to be from another dimension or something else, I think that this is going to get the attention of institutions of power. And indeed, I think that's what has happened. And although probably people have had interactions with these things, it appears to me historically, for a long time, as long as humans have existed, I would imagine that indeed, this is something that's quite powerful and could change the belief structures of our entire societies, our civilization, basically. So it's the same way that you're talking, the belief structures were strongly affected by religious beliefs throughout history, in the same way this has the potential. It serves as a source of concern for the powerful because it can have very significant effects on the populace. Huge effects, yes. Is there some broader understanding of how we should think about alien intelligences than like little green men? Yes. That you can maybe elaborate on and talk about? Yes, this comes directly out of my research in Catholic history. What I found was that, let's take for instance, this idea of an angel. Okay, so we all think we know what an angel looks like. Why? Well, we've been told what an angel looks like. We see what an angel looks like. Throughout history, people have painted angels and they all look pretty much the same. But actually, if you go to the primary sources on either in Hebrew or in Greek or in whatever language and in Latin, and you look at experiences that people have talked about, where they've written down their experiences about angels, angels don't at all look like what we think. They don't look like little cherubs with wings. They don't look like tall, strong, anthropomorphic, human looking things. They don't. They look really weird. And sometimes they don't look at all humanoid. They look like strange spinning things, right? With like eyes and things like that. They communicate telepathically with us. Okay, so what does that mean for the idea of extraterrestrials or what we consider to be aliens? Like, do you think that they're first, if we are, listen, I'm not the first to say this. If we're in contact with non-human intelligence, we're most likely in contact with its technology. Because think about us. Do we send human beings to Mars yet? Some people would say yes, but let's put that aside. So no, we don't. We use our technology. We send our rovers to Mars, okay? Okay, so if there's an extraterrestrial civilization, is it sending, are they coming by themselves? Are they coming to see us? Or are they sending their technology? Most likely, they either are technology or they are sending their technology. Yeah, there might be a gray area between what is technology and what the aliens are. Yeah. So put, you're saying like basically a robotic probe that would be the equivalent of us, our human civilization created technology. Way more advanced than what we could believe to be a probe, all right? It's kind of funny to think about like if whatever sort of extraterrestrial creations have visited Earth, that we're interacting with some like dumb, crappy drone technology. Yeah, it's true. And we're like, we're like building these like myths and so on from like an experience with some like crappy drone made by some crappy startup somewhere. That is correct. When the actual intelligence is like something much grander. Yeah, that's the more likely situation. That is correct. That's what I like to tell people. I'm like, no, it's probably a lot weirder than you think. Yeah, oh boy. So, but what forms can it possibly take? So like I really love this idea that I tend to be humble in the face of all that we don't know. And I tend to believe that the form alien life forms would take and the way they would communicate is much more likely to be of a form that we can't even comprehend or perhaps can't even perceive directly. So like, it could be in the space of, we don't understand most of how our mind works. It could be in the space of whatever the heck consciousness is. Like maybe consciousness itself is communication with aliens or like, I don't know. It could be just our own thoughts is actually the alien life forms communicating. Like, I know all of that sounds crazy, but I'm saying like, I'm just trying to come up with the craziest possible thing that doesn't make any sense that could very well be true. And you can't say it's not true because we don't understand basically anything about our mind. So it could be all of those things, everything from hallucinations, all the things that are explored through the different drugs that we've talked about in this podcast in general. Joe Rogan loves to talk about DMT and all those kinds of hallucinogenic drugs. All of it, including love and fear, all of those things that could be aliens communicating with us, memes on the internet. That could be, pretty sure humor is alien communication. No, I don't know. But is there some way that's helpful for you to think about beyond the little green men? Oh, absolutely. It accords exactly with how I think actually. So I'll explain. I liked in American Cosmic, I attained the status of full professor. So I was like, okay, I can pretty much write this book like I wanna do it. And I did. So I used a lot of quotes from cool artists like David Bowie. Okay, so David Bowie opens the book, okay? And he basically says, and so does Nietzsche, by the way, David Bowie and Nietzsche, boom, two awesome quotes right together. That's how I opened my book. No better opener. Yeah. Do you remember the quotes? Yeah, of course. So the first, the quote by David Bowie, and that's what I'm gonna concentrate on in response to what you just said, which I think is absolutely correct. David Bowie said, the internet is an alien life form. Okay, and if you've not seen David Bowie's interview where he says that, I highly recommend it. He's so brilliant. Okay, so David Bowie is actually quite brilliant about the idea of UFOs. He's also brilliant about the idea of technology, okay? And most people wouldn't think that, but I mean, he's pretty darn smart, okay? So, all right, so I started to think about it, and I also, early on in my research, met Jacques Vallée. Okay, so he's a technologist. He has a PhD in information technology from computer science, basically, from Northwestern, and he got that back in the day. You know, when I say back in the day, I'm not talking a thousand years ago. I'm talking like in the 60s, okay? So he's- Back when computer science wasn't really even a field that you can get a degree in. Yeah, he has a PhD in it, and he's French, he's from France, but he lives in Silicon Valley, and he worked on ARPANET, which is the proto-internet. He mapped Mars. He's also an astronomer. I mean, he's just this all-around brilliant guy, right? And he's also interested in UFOs, and most people take those two interests of his as separate interests, and I remember being at a very small conference and listening to him, being in awe, of course, because he's an awe-inspiring person, and then thinking, wait a minute, why do people compartmentalize those two things about him that are one and the same, okay? So when we talk about UFOs and UAPs and stuff, we have to talk about digital technology and things like that. Now, if we're going back to what I, so if I were to say what, if I were to believe in, and I, like I said earlier, I was agnostic, bordering on belief, most likely a believer, in this extraterrestrial, or not extraterrestrial, let me put it another way, non-human intelligence that's communicating with us. I'm gonna tell you how I think they communicate with us, and I go back to the Greeks again, okay? And the Greeks had this idea of muses, you know the muses? So, okay, so there are these things called muses, and we tend to think of them as metaphors, right? But what if they're not? What if they're actually non-human intelligence trying to communicate with us, but we're so stupid? We can't understand, like, so only people with, you know, in super amazing capacities, like poetic, creative, you know, intelligent, mathematical, whatever, you know, because they tend to do this symbolically, they tend to communicate with us in symbols form, and so music, you know, symbols, we've got math that are, you know, it's a symbolic language, and so what, so, okay, so muses are probably a good idea for me of what this would be. Now, would muses have spaceships, you know, or those things that we call physical counterparts to what they are? That's another question altogether. But if, you know, I, now, why would I think this? Because if you look at the history of our space programs, both Russian and American, you're gonna find some pretty weird stuff, pretty weird history there, Lex. So you wanna get an idea, go back to Tchaikovsky and read a little bit about what he has to say. If you look back at the history of our space programs, the viable space programs are both Russian and American, and each has an amazingly strange history because the founders of the calculations that got us up into space, the rocket scientists, basically, were doing some pretty weird rituals and doing religious things, right? They weren't necessarily, like, Jack Parsons on our side was out in the desert with people like L. Ron Hubbard and doing really intense rituals, believing that they were opening stargates and things like that, okay? And they were really doing that, okay? So then you go to the Russian side and they had a very specific non-dogmatic, according to Catholics or Orthodox Christianity, idea of what Christianity was, and they believed that they were interacting with angels, okay, non-human intelligences. So if you look back and you see muses, you know, you can contextualize them within this tradition. And so when I started to talk to people who were actually in the space program and who were in these programs that now the government has said, oh yeah, we do have these programs, they have the same belief structures. They believe that they were also in contact with these non-human intelligences and they were getting what they call downloads of information and creating, sometimes with Tyler D in my book, creating technologies that were real and they were selling them on NASDAQ for a lot of money, like, say, $100 million or something like that, undisclosed amounts. But a lot. And these things are viable technologies that we use now and they make our lives better and we progress as a species because of them. Now, that has nothing to do with the scientific method, as much as I know, as much as anybody's going to get angry at me for saying that, but, you know, sorry, those were strange encounters that created our ability to go into space. I don't know if they're real or not, but these people believe they were real. Right, so they have a power in actually having an impact in this world in inspiring humans to create technology, which enables us to do things we haven't been able to do before. Yeah. And I like how we're putting angels, alien life forms, aliens, and technology all in the non-human intelligence camp, which I really like that because that's very true. It's this other source of wisdom, intelligence, maybe a connection to the mysterious. Yes. I was really surprised by it. Can you speak a little bit more to the connection between aliens and technology that Jacques Vallée had in his own one individual mind that's very tempting to kind of separate as two separate endeavors. Why did you come to believe that they are one and the same, or at least part of the same intellectual journey? Thanks for asking that again, because nobody asks me that question, and it's central to my project. So Jacques was a huge influence, is a huge influence on me. He taught me a lot. He gave me access to some of his information that he keeps, but a lot of his information is actually there, out there for everyone to read. He has an academia.edu page, and he just, so he didn't have this, unfortunately, when I was doing my research in 2012 and 2013. So I had to go back and do microfiche type stuff. What I did was I began to read everything that he wrote, and he actually gave me a lot of his books too. And he told me, I remember, he dropped me off from, this is actually quite interesting if you'll allow me to tell you a little story. Please. Okay, and it also includes ayahuasca. So. Great. Every story that includes ayahuasca is a great story. Okay, so I was at a conference, and it was a small conference of very interesting people in California, on the Pacific Ocean. And Jacques was there. And this is actually, it opens my book. This is the book, this is the, I go, it's the preface to my book. I go on this ride, he takes me through Silicon Valley. I've lived there, right? My grandparents grew up in the same place that he raised his children in Belmont. And so, but we were there with Robbie Graham, who's a great ufologist in his own right, and film theorist. I highly recommend his work. So we were together, and he was taking us to San Francisco where I was gonna meet my brother, who was going to take me home. And so he took us on this long journey, and he talked to us. And as we got out of the car, he gave me several of his books. And one in particular, he gave me, and he said, read this first. That was like, okay, I definitely will read that first. Okay, so this is how the ayahuasca figures in. So we were, I didn't take it, nor have I taken it. Okay, so we were at this place in California, and Alex Gray and his wife were there, and they were talking about their experiences with psychedelics. You know, he's an amazing visionary artist, okay? So he believes that there's this place that you can enter, and he and his wife would enter this space with either ayahuasca or LSD or something like that. And they would not talk to each other, but they would be having the same exact experience. So they would, it was almost like having the same dream. Right? Okay, so somehow that whole event with Jacques there, and them talking about their experiences in these realms, of which religious studies people are quite familiar, by the way, because visionary experiences are what we study. So all of this seems super familiar to me. And I recognized that immediately that Jacques, that it hit me like, you know, very obvious that UFOs and these experiences and technology all seemed, they were all meshed together. And I knew that I had to take them. I knew I had to read everything Jacques ever wrote. And the best stuff he's written, by the way, is his little essays that he wrote in the 1970s, and they were peer reviewed essays about the beginning of the internet and how a lot of it was based on basically neural connection with the internet, like somehow psychic connection through the internet with others and things like that. So the brain is a biological neural network. There's this connection between visual neurons and so on. And that's what ultimately is able to have memories and has cognitive ability and is able to perceive the world and generate ideas. And those ideas are then spread on the internet, even from the very early days to other humans. So it gets injected or travels into the brains of other humans and that goes around in there and then spits out other stuff and it goes back and forth. So it's nice to think of the network that's in our mind, individual mind, as, I mean, very much, even deeply connected to the network that is the connection between humans through the internet. And so in that sense, Jacques saw the internet as this powerful, as a source of power and wisdom that is beyond our own. Exactly, that's external to us, like if you could call it autonomous AI, right? It's non-human intelligence in a sense, even though humans are a part of it. Yes, or we're invaded by it or whatever you wanna call it, okay. Yeah, whoever, right, it's the chicken and the egg, right. So if I can go on, I have lots of experience, things still, I'm not done with that. So this is where I come to this idea that we're in this space, we're in now a new space of religion, of religiosity. So what happens is then, and it's like a biosphere, and I'll talk about that in a minute. So Jacques takes us back, we get to San Francisco and my brother, who is your straight-laced person, army guy and everything like that, I get into his car and the first thing he tells me is, I took ayahuasca. And I was like, what? And he goes, it's gonna save humanity. Yeah. That's great. Yeah. As I mentioned to you offline, I talked to Matthew Johnson, he's a Hopkins professor and he's really a scholar of most, he's studied most drugs, he's also really deeply studied cocaine, all those stuff, negative effects, and he's focused on a lot of positive effects of the different psychedelics. It's kind of fascinating. So I'm very much interested in exploring the science of what these things do to the human mind and also personally exploring it. Although it's like this weird gray area, which he's masterful at, which is he's a professor at Johns Hopkins, one of the most prestigious universities in the world, and doing large scale studies of this stuff. And until he got a lot of money for these studies, even in Hopkins itself, there's not much respect. It's not even respect, it was like, people just didn't wanna talk about it as a legitimate field of inquiry. It's kind of fascinating how hesitant we are as a little human civilization to legitimize the exploration of the mysterious, of whatever the definition of the mysterious is for that particular period of time. So for us now, there's little groups of things. Like I would say consciousness in the space of computer science research is something that's still like, I don't know, maybe we'll let philosophers kick it around for a little longer. And then certainly extraterrestrial life forms in most formulations of that problem space is still the other. It's still the source of the mysterious, except maybe like SETI, which is like, how can we detect signals from far away alien intelligences that we'll be able to perceive? Yeah, and psychedelics is another one of those that's like, we're starting to see, okay, well, can we try to see if there's some medical applications of like helping you get, like he does studies of help you quit smoking or help you in some kind of treatment of some disease. And he's sneaking into that. I mean, it's like openly sneaking into it. He's doing studies on it of like, how can you expand the mind with these tools and what can the mind discover through psychedelics and so on? And we're like slowly creeping into the space of being able to explore these mysterious questions. But it's like, it sucks that sometimes a lot of people have to die, meaning, sorry, they have to age out. Like it's like faculty and people have a fixed set of ideas and they stick by them. And in order for new ideas to come in, then the young folks have to be born with an open mind, the possibility of those ideas, and then they have to become old enough and get A's in school and whatever to then carry those ideas forward. So, the acceptance of the exploration and the mysterious takes time. It's kind of sad. It is sad, I agree. Maybe to go into my source of passion, which is artificial intelligence. What's your sense about the possibility, like Pamela McCordick has this quote that I like. I talked to her a couple of years ago, or I guess already in this podcast, that artificial intelligence began with the ancient wish to forge the gods. So, do you think artificial intelligence may become the very kind of gods that were at the center of the religions of most of our history? Yeah, there's a lot there. So, I'm gonna start by addressing this idea of artificial intelligence being separate from human beings. So, I don't think that's actually, that might happen. Okay, I mean, it's already happened, but let's put it this way. Like you're talking about super artificial intelligence, like autonomous conscious artificial intelligence? Okay, yeah. Something with artificial consciousness. First of all, I think she's correct, okay? But also, there's an awesome quote. I'd also like to bring up this writer of fiction, actually. Ted Chiang, and one of his essays, he writes short essays. One of them was The Basis for the Movie Arrival, which if you haven't seen it, it's a really great movie about UFOs. It has a very creative way of proposing an idea of how they might be able to communicate. First of all, how they appear to us. Second of all, how they may be communicating with us humans. Exactly. The author, Ted Chiang, has a lot, I recommend his writings, his short stories. And one is very short, and it appeared in nature about 20 years ago, and it is called, I think it's called Eating the Crumbs from the Table or something like that. And it's basically this short essay, and I hate to do a spoiler here, but if you don't wanna know what it's about, don't listen right now. Yeah, spoiler alert. Yeah, okay, so this is what it's about. So basically, it's about human beings becoming two different species, okay? And one of them is created, they're called metahumans, and they start biohacking themselves with tech, okay? Sound familiar? So they do this, and they become metahumans and another species, right? And just kind of another fork, such that humans can barely understand them because they're so far removed. So in a sense, are they gods, right? No, they're metahumans, they're superhumans, they're enhanced humans, okay? I see that, hopefully, on the horizon, frankly. I hope so. Not that we have two species, but that we can use our technology or we can become so integrated with our technology that we can survive, okay? We can survive the radiation in space. We can't go places now because of the radiation in space. Perhaps we can develop our bodies such that we can survive the radiation in space. So there's this idea of these metahumans. Now, there's also this idea that technology is just another form of humans. We've created it, right? And so maybe it is bent on surviving, thereby using us kind of as a meme or a team. Some people are calling them teams now, these self-generating, they're replicating themselves through us, okay? I see that also, and I don't think that's terribly bad. Maybe it's just the way that we are evolving. It doesn't mean that, we're evolving all the time. We're taller than we used to be. We have different skills. So I don't see that as a bad thing. I think a lot of people see it as, if we're not how we are now, it's a tragedy. But it's not a tragedy. How we are now is actually a tragedy for most people alive. Yeah, and we might be evolving in ways we can't possibly perceive. Like you said, that humans have created Twitter, and Twitter may be changing us in ways that we can't even understand now currently. Like from a perspective, if you look at the entirety of the network of Twitter, that might be an organism that this, the organism understands what's happening from its level of perception. But we humans are just like the cells of the human body. We're interacting individually, but we're not actually aware of the big picture that's happening. And we naturally somehow, or whatever the force that's creating the entirety of this, whatever one version of it is, the evolutionary process, like biological evolution, whatever force that is, is just creating these greater and greater level of complexity. And maybe somehow other kinds of non-human intelligence are involved that we're calling alien intelligences. Yes. So just to step back, and we'll come back to AI, because I love the topic, but through American Cosmic and in general, you've interacted with much of the UFO community. You mentioned ufologists. By the way, is it ufologists, or is it ufologists? It's ufologists. Ufologists. Yeah. So first of all, what is a ufologist? And second of all, what have you learned about this community of ufologists, or also as you refer to them as the invisibles, or the members of the invisible college, or just in general, people who study UFOs from all the different kinds of groups that study UFOs? Sure. Generally, what I found is that they are, okay, so people who are interested in UFOs from being a kid and seeing some cool movie like Star Wars or something, and then they become interested and then they study it as best they can, UFOs or UAPs. They're generally an honest group of people who are using their tools. There are generally two types of them. There are those who believe in the nuts and bolts, like the physical craft, and they believe in that these are things from other planets, okay? So that's like the ETH hypothesis, you know. I'm sorry, ETH hypothesis. ETH is what we call it. Yeah, sorry about that. So this is like there's an actual spaceship, like something akin, but much more advanced than the rockets we use now. Yeah, they have advanced, yeah. Some kind of, not necessarily biological, but something like biological organisms that travel on these spaceships. So this would be like what, to you, the Stars Academy is trying to decipher. Like how do they do it? Maybe we could use that technology, the propulsion and things like that. They look at the rocket technology. Okay, so there are those. And then there are people who believe that it's more consciousness-based, okay? So these are your two types of ufologists who are known, and these are people who we know about. Then I found that there are people who are, quote-unquote, I call them the invisibles, because Jacques Vallée in the 70s, he and I think actually Alan Hynek, his colleague, quoted, this is a Francis Bacon thing, by the way. It goes back to the early modern time period when scientists could be killed for basically trying to go outside what the church or the government institution determined was dogma. And so they had to be really careful. So he called it the invisible college. So Hynek took that term and reused it, or what do you call it, repurposed it. So he repurposed it. So they were still talking to each other, though. So what I found to be the case was that there was a group of people who were scientists but were not on the internet. To people today, and students of mine in particular, and my own kids, actually, they think that you only exist if you're on the internet, or something only exists if it's on the internet, and that's, of course, untrue. And so what I found was that most people who are the most powerful people of our society and are doing things are not on the internet, and you're not gonna find any trace of them. So a lot of these people are what I call invisibles, people who are studying, at least their work is invisible. You might find them on the internet, but you're gonna find that they're part of the bowling league or something like that, right? You will not find that they are actually engaged in research about this topic, okay? And so I called them the invisibles because I was surprised to find them. And I thought, well, this is no longer the invisible college because these people are not even talking to each other. And that's why I reference this movie Fight Club. In it, you have an invisible, okay? And his name is Tyler Durden, and he's incredible. He does incredible things. He's like a person who should not exist, right? Because he does so many things that are amazing. And so I found a person like that, and I call, and he's a real person. He's partially on the internet, but nothing that he does around that topic of UFOs is on the internet. So I decided to call him Tyler D after Tyler Durden. And so these people, I've termed the UFO Fight Club because they work together, but they don't know, in fact, his boss doesn't know what he does. They don't talk to each other because you know the first rule of Fight Club. Same as the second, yeah. Exactly, yeah. You don't talk about Fight Club. No, you don't do it. Why do you have a sense that there's such a, I don't wanna say fear, but a principle of staying out of the limelight? I think there's something real. And I think that the use of it could be dangerous for people. Oh, sorry, you mean something real, like there's actual, what's the right terminology here to use? Alien technology, ideas about technology that are being explored, that are dangerous, have made public, that may become dangerous, have made public. So that's the word. You don't have to call it alien technology. You can call it ideas about alien technology because I don't know if it's actual alien technology or not, I honestly don't know. But I do know for a fact, because it's a historical fact, that Jack Parsons and Konstantin Tchaikovsky, who's Russian, believed in these things and believed that they were downloading this information. Whether or not they were, I don't, I mean, they definitely created the rocket technologies. That's true. How they did and whether their process was exactly what they said it was, I don't know. So this is the same thing today. So we've got some powerful technologies going on here. And of course we have a military, and we have a military for a reason. Almost every government who needs a military has one. And so they're going to keep these the way they should be kept, in my interpretation. I mean, think about it. Everybody accepts the fact that we have a military. Almost everybody does. Why are they so upset, then, that the military keeps secrets? Yeah, well, that's the nature of things. We can get into that whole thing. I tend to, I've spoken with the CTO, Lockheed Martin, on this. I obviously read and think about war a lot. It's such a difficult question, because this space, this particular space of technology, there's a gray area that I think is evolving over time. I think nuclear weapons change the game in terms of what should and shouldn't be secret. I think there's already technology that will enable us to destroy each other. And so there's some sense in which some technology should be made public. This is the same discussion between companies. Which part of your technology should you make public through, for example, academic publications and all that kind of stuff? Like how the Google search engine works, PageRank algorithm, or how the different deep learning, there's pretty vibrant machine learning research communities within Google, Facebook, and so on. And they release a lot of different ideas. It's an interesting question, like how dangerous is it to release some of the ideas? I think it's a gray area that's constantly changing. I do also think it's super interesting, I wonder if you could elaborate on it a little bit, that there's this gray area between what's actually real in terms of alien technology and the belief of it when held in the minds of really brilliant people, that they ultimately may produce the same kind of result in terms of being able to create new technologies that are human usable. Is there, in your mind, they're one and the same? Is like believing in alien craft and actually being in possession of an alien craft? I don't think they're the same, no. Belief is powerful, okay? In new age communities, people think thoughts are things, okay, that's been said. Thoughts are things, you can make them happen kind of thing, believe in them enough. It is true that if I believe I can run a 540 mile, I'll do it, okay, and I probably will do it, and I've done it before actually. Much younger, but I did it. So, but my coach is the one that instilled that belief in me, right? And so, but can I run like a one minute mile? No, okay? So I guess, does that answer your question? Like there's only so far belief goes in generating reality. Well, yeah, I mean, I guess that's what, just having listened to Jacques Vallee, it seemed like reality was not as important for the scientific exploration of the concept of alien technology. I could be wrong, but this is what I think Jacques is getting at. There are other ways to access places in reality other than what we consider to be physical. Right. That's what, there's consciousness, okay? So, like I said, so religious studies is, among other things, it's looking at visionary experiences, all right? So people do have visionary experiences. They did without drugs, you know, they did with drugs. They do with drugs. They do, many have them without drugs today. And oftentimes those visionary experiences correspond to each other. Now, how do we make sense of that? So, you know, do these places actually exist? In a sense, I think they do. And so I think that, you know, like let's take that very famous case of a Virgin Mary apparition in Fatima, where I think there was like a lot of people, thousands and thousands, if not like, I think 50,000 or something like that, a lot of people gathered to see what's now called the miracle of Fatima, which was the spinning of the sun. Well, a lot of people saw different things, but they all saw some kind of thing. Okay, so they all saw different things, but it was, something happened, okay? So I guess the question is, what are these places where we access non, what I'd call like non-physical realities, okay? Where we actually do get information. We get, like who could say that Jack Parsons didn't get information from doing these rituals and accessing these? We have to say that he actually did because we see the results of physical results. The same thing with Tyler. And that's why I put Tyler in this camp with this tradition with Jack Parsons. I say that Tyler is getting these, what he calls downloads, and you can see the results of them physically. He sells them on the Nasdaq. He makes millions of dollars from them. They help people. I've seen people who they've helped, okay? So. Do you think psychedelics that I just mentioned earlier have a possibility of going to these kind of, same kind of places of exploring ideas that are outside of our more commonplace understanding of the world? In my, yeah, I think so, absolutely. However, I think we have to be really careful about those because young people, or people in general, I should say, absolutely can get hurt by them. I mean, but we get hurt by alcohol. You know, we drive our cars and we kill each other. But psychedelics are really interesting because I know that within the history of our country, we have used psychedelics in various capacities for our military in order to try to stimulate ideas and access places and information that can't be accessed normally. This is all fact. Yeah, I talked to Matt for like four hours. So we ran out of time being able to talk. But I wanted to talk to him about MKUltra and Ted Kaczynski. There's so many mysterious things there. There's like layers of what's known or what's not known. It's fascinating. But I think what is interesting is psychedelics were used or were attempted to be used as tools of different kinds. That's the point. So like we think of technology as tools to enable us to do things. And that same way that psychedelics, like many drugs, could be used as tools, some more effective than others. Absolutely. I don't think what you, I'm not sure what you can do effectively with alcohol. Although somebody, I think somebody commented somewhere on social media that, I don't know why everyone gives, is so negative about alcohol. Because I think the person said that, it's given me some of the most incredible, it enabled me to let go and have some of the most incredible experiences with friends in my life. And it's true. We kind of sometimes say alcohol is dangerous. It can make you do horrible. But the reality is it's also a fascinating tool for letting go of trying to be somebody maybe that you're not and allowing you to be yourself fully in whatever crazy form that is. And allow you to have really deep and interesting experiences with those you love. So yeah, even alcohol can be used as an effective tool for exploring experiences and becoming, expanding your mind and becoming a better person. So, what the hell was I talking about? So yeah, so psychedelics and oh yeah, and MKUltra. Is there something interesting to say in our historical use of psychedelics? I mean, think about it. When did we start doing that? When did we start using those? That's true. It's quite a long time ago, right? But okay, but true. But when did our government start experimenting with them with us? Okay. Our government is the United States government. Yeah. Okay, so that happened in around the 1950s. Okay, after quote unquote, the 1940s, where we have 47 and we have this Roswell type stuff going on, okay, like crash sites and things like that. So I think that, I think there might be a correlation there. I don't know what it is, okay? But I do think- That's fascinating actually, yeah. There's a lot of interesting things started around that time period. Around that time period, yeah. Yeah, and so Aldous Huxley would say, we opened the doors of perception, okay? And what flew in? Oh man, that was beautifully put. It'd be interesting to get your opinions on certain more concrete sightings that are sort of monumental sightings of alien intelligences in the history, in the recent history. At least I'm aware of them. I'm not very much aware of this history, but the most recent one, I've spoken with David Fravor on this podcast. I really like him as a person. He's a fun guy, but also he's gotten a chance to, he's described his account of having an experience with what he and others now term the Tic Tac UFO. What do you think of that particular sighting, which has captivated the imagination of many in particular, because there's been videos released of it, of these UFOs, but I find the videos to be way too blurry and grainy to be of interest to me, the personally, to me, the most fascinating thing is the first person to comment from David and others about that experience. But what are your thoughts? Those videos have been out for a while, actually much, I think in the mid 2000s, they were out. But what you have is you have kind of like this corroboration from a group and also the New York Times involvement in 2017. My opinion about the Tic Tacs is that first, I believe the people who have had the experiences, I know some of them, like some of the radar people and things like that, they'd saw them, and they're not, I don't believe they're making it up. I do think that this is being used as a spin. And I'm just gonna say that. And the reason I think that is this, is because at the time it was released, I was still in touch with many people who were among the UFO Fight Club. And so they had intimate knowledge of these things. And the first thing they said was, we have satellites that can read the news on your phone when you're reading it. So we've got better footage than this, and this is not good footage at all. Therefore, they believe that it was authentic footage that had been doctored up. Now, why? I don't know why. So I honestly don't know if it's accurate or not. I mean, I believe the people, absolutely. But was this something out there to fool these people? Perhaps, I don't know. Is it spun? The people who I know who are part of the UFO Fight Club believed it was real, okay? And said, this is badly done, but real, okay? I see, but so there's some kind of, when you say spinning, there's some parties involved that are trying to leverage it from the- For funds, probably. For funds, for financial interest. Yeah, I think so. Nevertheless, it has inspired a conversation and just a lot of people in the world that there's something mysterious out there that we're not fully informed about. And I was certainly grateful that the New York Times ran the story right before my book came out. Well, see, but there's the financial interest that to me, as a person who doesn't give a damn about money, actually, I don't like money, except for when it's used in the context of a company to build cool things. But like, personally, I don't know. I find the financial interest side off-putting, especially when we're talking about the exploration of some of the most, like money is a silly creation of human beings. I agree. And it's used to provide temporary, like the unfortunate thing with money is that it helps you buy things that too easily allow you to forget the important things in life and also to forget the difficult aspects of life, to do the difficult intellectual work of being cognizant of your own mortality, of like fully engaging in life, in a life of reason to, of thinking deeply about the world, all those kinds of things. If you get like a nice car or something like that and just like, I don't know, all the different things you can do with money is it can make you forget that. Anyway, there's a long way to say that, yes, yes, it's very nice that it coincided nicely with the book, but also, I think it, I mean, like I said, I think it inspired quite a lot of people that, maybe there's a lot of things out there that we're, like it reminded a lot of people there's things out there we don't know about. Lex, I can agree with you on that, but can I push back on two things? Mm-hmm, just do it. Okay, all right. The first one is that I was happy to receive money from the book because of the New York Times article. That's absolutely false. So I published my book with Oxford, which is an academic press, and you don't get paid with an academic press, okay? So money was not it for me. What it was was recognition that my research was being validated, so, you know, because then people called me and said, well, maybe it's more than interesting. Okay, and they did, okay. The other thing about money is just as you say that, now, I agree with you, I'm upset about money too. I think there should be universal healthcare, a universal income, you know, I don't think people should be in poverty, especially because we are so wealthy as a species, frankly, okay, that said, think about this, if you don't have money, you can't have a life of the mind either, right? 100%, so I'm not espousing that like money's the devil. I just think that there is, money can be a drug, or I would compare it to like food or something like that, where like you really should have enough to nourish yourself, right? Yes, too much consumption. And too much can be a huge problem. So that's where I come from with money, and I'm just aware, I'm fortunate enough to have the skills and the health to be able to earn a living in whatever way, like I wish of having being in the United States, of being able to speak English, so at the very least I can work at McDonald's, and my standards are, I told Joe, I made a mistake, I told Joe Rogan that I've always had a few money, and people are like, oh, Lex was always rich, no, no, no, I was always broke. What I mean by I've always had a few money is like my standard of what it takes to have a few is always very little, I'm just happy with very little. But yes, it's true that money for many people, including for myself, it's just a different level for different people, is freedom. Freedom to think, freedom to pursue your passions. It just so happens, I am very fortunate that many of my passions often come with a salary, if I wished. I love programming, so even just working as a basic level software engineer would be a source of a lot of joy for me, and that happens in this modern world to come with a salary. So yeah, it's definitely true. I just mean that it can become a dangerous drug. So I'm glad you are in this pursuit that you are in for the love of knowledge, but it's true. Yeah, so. People should definitely buy your book. I won't be making money off of it. Oh yeah, this rocks, yeah. Absolutely. Maybe my next book. Yes. Yeah, your sense is there's something, as there's some groups of people that may be trying to leverage this for financial gains. And you know, probably good financial, I mean, they may have good reasons for this too. Like, okay, let's take the study of UFOs, okay? Maybe many people in government that decide who dole out the money, let's put it that way, they think UFOs aren't real. So they're not going to give these programs money. So how do these programs make money? They're gonna have to find a way to do it. So maybe that's how they do it, okay? So I. That's fascinating. This is a way to raise money for. Doing the research. Yeah, I think so. So let's take a step back to Roswell. We talked about it a little bit. What's your sense about that whole time? Roswell and just Area 51 and the sightings, and also the follow on mythology around those sightings. Of course. That's with us today. All right, so. Where do I get started? Well, I mean, it is a mythology here, right? The mythology of Roswell, it's very religious, like in the sense that there's a pilgrimage to Roswell people make, and they go to, there's a festival there as well, like a religious festival. You can get little kitschy stuff, like you can get at a religious festival there. So it's very much like a place of pilgrimage where a hierophany occurred. And a hierophany is basically contact with non-human intelligence, okay? So non-human intelligence is thought to have contacted humans or crashed at this place in Roswell, New Mexico. Now what's fascinating is that I begin my book by going out to a crash site in New Mexico. I have to get blindfolded with my, well, to tell you the truth, the story is that I'm with Tyler, who's an invisible, and he wants to show me a place in New Mexico where a crash happened. And he says that he thinks that I need to see physical evidence because I don't believe. And so I said, I'll go, but I'm gonna bring a friend of mine. And he said, no, you have to go alone. He goes, it's a place that is on government-owned property, and it's a no-fly zone. And when you go, you'll be blindfolded. And I said, I definitely need to bring a friend. So he said, well, who do you wanna bring? I just had met this university scientist. He's very well-known, and I call him James in my book. And I asked, and I had a feeling James would definitely wanna do this. And I asked James and he said, I'll go tomorrow, okay? So I suggested this to Tyler, and Tyler said, absolutely not, you know? And I thought, I know he's gonna look up James and he's gonna say yes, because if anybody can figure out what this material is that we're gonna go look for, it's gonna be James. He has the instruments. And so Tyler did, in fact, look him up and finally said, okay, I got, you can go. So we both head out there and we get blindfolded, and Tyler takes us out there. It takes about 40 minutes outside of a certain place in New Mexico. So in terms of Roswell, this is what I can say, is that according to Tyler, there were about seven crashes out in the 1940s in New Mexico in various places. We went to one of them, according to Tyler. At the time, I was completely an atheist with regard to anything that had to do with UFOs. So we were out there, we had specially configured metal detectors for these metals, and we did find these, okay? And they've since been studied by various scientists, material scientists, so forth. And I believe Jacques talked about, not those particular ones, but others on the Joe Rogan show. They're anomalies, so there are, scientists don't, I'm not a scientist, so I can't weigh in on whether, I just believe the people, these people I believe, because they're well-known scientists. What do you mean they're not anomalies? No, they are anomalous. Oh, anomalous in terms of the materials that are naturally occurring on Earth? Yes. Okay, so there's some kind of inklings of evidence that something happened in Roswell in terms of crashes of alien technology. Now, what else is there to the mythology? So there's some crashes, right? Yeah. I mean, that's kind of epic. It's pretty epic, yeah. And what else? What are we supposed to take away from this? Right, yeah, so it's weird. Okay, so there's this, okay, so in religious studies, like I said, we call it a hierophany, which is the meeting of a non-human intelligent thing, whatever it is, an angel, a god, whatever, a goddess, with, or an alien, with humans. And that's the place, okay? So the place is New Mexico. So New Mexico becomes folded into the mythology of this new religion, is what I call a new type of religion, of the UFO, and it becomes ground zero for this new mythology. Just like Mecca is the place where Muslims go, they have to go, right, at least once in their lives, it's a pilgrimage place now. So in my book, that's how I tell it. Now, what about Roswell in the public imagination? Obviously, according to Annie Jacobson, who's good, she's a great author, investigative journalist, she's written about Roswell too. I don't agree with all of what she comes up with, but part of it is that there's a lot of military stuff going on there that is classified, and there's a reason why you can't get in, and nor would you want to, right? So there's a lot of experimentation going on there. I don't believe that it has to do with ETs, frankly, but in the imaginations of Americans, Roswell is that place, but I went to a different place, and apparently there are several places in New Mexico. Now, strangely enough, I travel back to New Mexico at the very end chapter of my book, but I don't go there physically. I go there through the story of a Catholic nun who actually believes that she bi-located to New Mexico in the, gosh, in the 1600s. So she, yeah, it was very strange. And I was at the Vatican at the Space Observatory when I made that connection that she probably went to the very, well, she believed she went to this very place that I had gone. Can you elaborate on it a little bit? Like, what does it mean to go to that place? For her? Yeah, yeah, for her. I mean, so we're kind of breaking down the barrier between what it means to be at a place and time. Right, I agree with you. This is the field of religious studies. So, and again, I don't say it's true in my book. I just say it's a very strange coincidence that I'm at the Vatican Observatory. In fact, I'd finished my book, but while I was at the Vatican Observatory, I was there with Tyler, and we were looking at the records. They're called the trial records, but they're the canonization records of these two saints. Each was said to have done amazing things. One was Joseph of Cupertino, who levitated, okay? Or is said to have levitated. The other was Maria of Agrada from Spain. They're contemporaries in the 1600s, who was said to have been able to bilocate, which is to be in two places at once, okay? So this is a belief in Catholicism that certain very holy people can do these kinds of things, like levitate, which by the way, is also associated with UFO abductions. You know, people get levitated out of their beds and things like that. So we were sent there by a billionaire who was interested in levitation and bilocation. And since I could get in to the Vatican and I knew the director of the Vatican Observatory, both Tyler and I were able to go to the secret archives and look at the canonization records and then go to Castle Gandolfo, which is about an hour from the Vatican, where the first observatory, the space observatory of the Vatican is. The second one is in Arizona and it has a much larger telescope. So we went and Brother Guy gave me the keys to the archive. He said, look at anything you want. And I got to see a lot of stuff by Carl Sagan, by the way. I know you talked about, yeah, it was awesome. So they have a whole section on extraterrestrial, the search for extraterrestrial life. And they don't, by the way. How awesome is that? It was awesome, yeah. So we got to stay there. They have a scholar's quarters. And so they had two. And so Tyler stayed in one and I stayed in the other. And Brother Guy probably shouldn't have been so nice to me and given me the keys because when I got home, we were there for two weeks. When I got home, I got this frantic phone call from him and he basically said, Diana, he goes, do you remember where you put the original Kepler? And so I had this Kepler, right? And so I misplaced it. Luckily, I remembered where it went. I was like, oh gosh, thank goodness I found it. But he'll probably change the rules of the Vatican Observatory after my visit. So Maria is, she's actually in the history of our country in that she first wrote a cosmography of what she said was the spinning earth. And this was in the 1600s. And that's her first book. And she wrote that. And then she said that she was transported on the wings of angels to the new world. And she said that she met a culture of people and she basically told them about the faith of Catholicism. And then what happened was that the people that, and she described the fauna, she described the people and everything like that. And so there were actually missionaries there. And when they went to try to convert some of the people who already lived there, apparently they already knew a bunch of stuff. And they said, how did you know all this stuff? And they said, this lady in blue came and told us. And they said, did it look like this? And they showed them, they obviously didn't have a photograph, but they had a picture of a sister, a nun. And they say, yeah, she wore similar clothes, but she was much younger, right? And these guys thought that was weird. But when they went back to Spain, they found that this woman had been doing that in her mind, had been traveling. I mean, I don't know what to make of it. There's so many things that are sort of forcing you to kind of go outside of, you know, I'm of many minds. I have a very, most of my days spent with very rigorous scientific kind of things. And even engineering kind of things. And then I'm also open-minded. And just the entirety of the idea of extraterrestrial life forces you to think outside of conventional boundaries of thought, current scientific thought. Let's put it that way. And your story right now is certainly an example of that. It's freaking you out, that's okay. That's a nice way to put it. What are you, just another person that seems to be a key figure in this, in the mythology of this, is Bob Lazar. It'd be interesting. Maybe there's others you can tell me about. But Bob, who's also been on Joe Rogan, but his story has been told quite a bit. And he's got, I think he said that he witnessed some of the work being done on the spacecraft that was captured and so on, in order to try to reverse engineer some of the technology in terms of the propulsion and so on. What are your thoughts about his story, how it fits into the mythology of this whole thing and the broader ufologist community? Okay, so regarding Bob Lazar, with respect to his claims, again, I have no way to adjudicate whether or not he actually encountered this. I do have friends who are, and the people that I know who know his story, some know him, believe him. And they have said to me that the most important thing that they think he has said, in fact, one of them, I think made a meme out of it or something like that, was basically he said, maybe the public, I regret making it public, maybe the public isn't ready for this kind of information. And basically they've, they emphasize that to me and they emphasized it so much that they wanted me to know. So that is somewhat creepy to me. So I think, okay, this poor guy, Bob Lazar, so many people, this is what happens to people who have experiences like this. They're questioned, their reputations are put on the line. In some instances, their reputations are manipulated on purpose to make them look uncredible. To me, as a scientist, it's just inspiring that it kind of gives this kind of, I'm not even thinking of it, is there an actual spacecraft being hidden somewhere and studied and so on? I'm thinking of it like, I don't know, it's a thing that gives you a spark of a dream, as a reminder that we don't understand most of how this world works and then we can build technologies that aren't here today that will allow us to understand much more. And it's kind of like, almost like a feeling that it provides and it inspires and makes you dream. That's the way I see the Bob Lazar story. I don't necessarily, people ask me, because I'm at MIT, people ask me, did Bob Lazar actually go to MIT and so on? I don't know and I personally don't care. Like, that's not what's interesting to me about that story. To me, the myth is more interesting, not interesting actually, but inspiring. Yes, because inspiring, you're suggesting that the myth inspires you to create reality. Yes. Yeah, I think that's true. So even if it's like not real. It doesn't matter, does it? I mean, in some sense, just like you said, it does, in some sense, it doesn't. So a lot of people know how much I love 2001, Space Odyssey. So I got all these emails asking like, hey bro, do you know what's up with the monoliths in like the middle of the desert or whatever it was? I haven't been actually paying attention, I apologize. But you kind of mentioned offline that this is kind of cool and interesting. What do you make of these monoliths? And in general, are you a fan of 2001, Space Odyssey where monoliths showed up? Do you have any thoughts about either the science fiction, the mythology of it or the reality of it? Yes. Okay. No, okay. And please say more. Right. So first of all, Kubrick's films are not ever easy for me because they're so weird, right? And I don't actually enjoy watching them. But that doesn't- Work? Yeah, it doesn't take away from their incredible brilliance though and their visionary merit. So 2001, Space Odyssey is incredibly visionary. And of course, all those things that people say, I don't have to restate them. In terms of what I've, it's a subtext to my book, by the way, I didn't mean it to be, but it's almost a character in my book, 2001, Space Odyssey. And when the monoliths started to appear again, everything went crazy with my everything, internet, social media, phone, what's up, what's going on, right? Is this disclosure? And I thought, well, I'll tell you one thing, is it's, let's look at the timing of it. It's a cool, if it's an art, and then copy art and things like that, it's actually happening at a really interesting time when all of us are forced to go online. When all of us are forced, because of COVID, right? We're completely now invaded by the screen, or we're invading the screen. Like we're leaving, our infrastructure now is completely changed. So the monolith, basically, if art is supposed to show us life, it certainly has. If that's an art project, somebody did an awesome job with it. But apparently that monolith was there for a long time. I mean, that's the thing, it's been there for a couple of years. So they said, okay, all right. That said, if your audience is interested, I think the best theory about the meaning of the monolith is Robert Ager, or Robert Ayer, I think it's Robert Ager. He's got a website where he does analyses of films, and it's called collative learning, or collative learning. And he does the meaning of the monolith. Everyone should go look at that, because I fully agree with him. When I studied different meanings of the monolith in 2001, A Space Odyssey, I was fascinated. Okay, so what is this about? I accepted as soon as I listened to it, and watched it. So basically, he says that the monolith is, okay, can you pick up your phone here? What does that look like? What does that look like? What does that look like? What does that look like? Looks awfully a lot like a monolith. Yeah, okay, so basically that's what he was saying, was that Kubrick was basically, the monolith was technology, or the screen in particular. And he basically was saying that the cinema screen, we're being completely, and if you think about it, look at all this, we live in a screen culture. We have computer screens, iPhone screens, or phone screens, we have TV screens, everything is something, and now that COVID has come, we're forced to go into these screens, and we're forced to live a different material existence than we have lived before. So in my sense, I think that if it's an art project, it's a really good one for that. So I like that meaning of it, it's a screen, and a screen can take all kinds of forms. I mean, our perception system, in a sense, is a screen between reality and our mind. The screen of the computer is a screen. The virtual reality worlds that we might be one day living in, there will be an interface. I mean, ultimately, it's about the interface. That's interesting. It's an interface to another world of ideas. It's also a material change. It's a change in our material, I mean, when people talk about augmented reality, I say we already live in augmented reality, don't we? Because this isn't our grandparents' existence. Yeah, I sometimes, you have to pause and remind yourself how weirdly different this reality is than just even like, I mean, 30 years ago. The internet changed so much, and social media has changed so much about actually just the space of our thinking. Wikipedia changed so much about the offloading of our knowledge, the way we interact with knowledge. I mean, it offloaded our long-term memory about facts onto a digital format, so in a sense, it expanded our mind. It's kind of interesting. I'd be curious to see if he has just one interpretation. I wonder if there's others. I've corresponded with him, yes. So over the years, he and I have corresponded. And I told him, I said, look, I'm gonna be using this in my book, so I think you should read what I say. And he, of course, wanted to see it. So. What do you think about your book? Did he get it just to read it? Yeah, oh, yeah. So he is a non-believer in alien intelligence and UFOs, but he, and that's fine, but I still agree with him that the meaning of the monolith was the screen, but that doesn't mean the screen isn't like what David Bowie said, right? So it's not exclusive. So I could still use his theory, but differ from the conclusions. In terms of non-believer and believer, there's, when you say believer, you also are kind of implying this, that the idea that aliens have visited or have made direct contact with humans in some form. There's also the exploration and the idea of just alien intelligences out there in the universe. You know, the Drake equation, estimating how many intelligent civilizations may be out there, how many have ever existed, how many are about to communicate with us. I mean, when you just zoom out from our own little selfish perspective of Earth and look at the entirety, let's say the Milky Way galaxy, but maybe even the universe, does the idea that there are intelligent civilizations out there, something that you're excited about or something that you're terrified about? That's a good question. So basically, I would say I'm not so keen on it. I think that our relationship with technology, as it is and as I hope it will go, will help us survive, okay? I don't think we're equipped to do it as we stand now, but I think that if we can up our game or let's just put it this way, if technology is an extension of ourselves, which it actually is, it will help us because it'll probably be smarter than us, okay? It'll help us survive in the ways in which it determines best, okay? That said, if there are non-human intelligences out there and they have more advanced, you know, obviously technologies than us and they actually come, the history of human engagement with other cultures has not gone well for cultures that are less aggressive. So you see what I'm saying? Like, it's not a good idea. Well, I wonder where we stand, where humans stand in the full spectrum of aggression. Well, heck, where are we now, Lex? I mean, we're not too great here. We're still aggressing against each other. No, I know, but that will give us a benefit, right? Like, oh, you're saying, I thought, okay, I see. I just have a sense that there may be a lot of intelligences out there that are less aggressive because they've evolved past it. We can't assume that. No, I know we can't assume that, but like- If we can't assume it, then I'm gonna assume the worst. Well, that's, despite the fact that I'm Russian and think that life is suffering, I tend to assume, not the best, but I tend to assume that there is a best core to creatures, to people and to creatures that ultimately wins out. I think there's an evolutionary advantage to being good to other living creatures. And so ultimately, I think that if there's intelligent civilizations out there that prosper sufficiently to be able to travel across the great spans of space, that they've evolved past silly aggression, that it's more likely in my mind to be deeply cooperative. So like growth over destruction, like growth does not require destruction, I think. But if you see the universe as ultimately a place where it's highly constrained in resources that are necessary for traveling across space and time, then perhaps aggression is necessary in order to aggress against others that are desiring to get access to those resources. I don't know. I tend to try to be optimistic on that front. I think I'm emotionally optimistic and intellectually non-optimistic. Yeah, I guess I'm there with you. I tend to believe that the happiness and deep fulfillment in life is found in that emotional place. The intellectual place is really useful for building cool new technologies and ideas and so on. But happiness is in the emotional place. And there it pays off to be optimistic, I think. You said that technology might be able to save us. You know, that's also kind of optimistic too. It might kill us. There's, talking to you offline a little bit, there was a sense that we humans are facing existential risks, that it's not obvious that we will survive for long. Do you have, is there things that you worry about in terms of ways we may destroy ourselves or deeply damage the fabric of human civilization that technology may allow us to avoid or alleviate? Yes, I think that any, you can choose anything, actually, and it could destroy us. Okay, so, you know, pollution. You know, here we're in a pandemic, okay? A meteor, okay? So we can use technology, or the thing is is that we say we use technology, but actually that's not a correct way of putting it, in my opinion. So there is a term used by others, coined by somebody I don't know, and I'm sorry to not give credit where credit's due, but it's called technogenesis, and it's this idea, Heidegger actually had this idea, but he didn't use that term, and it's this idea that we co-evolve with technology, that we don't actually use it. Most people think it's like a tool we use, okay? Let's use technology to do this. Well, actually, when we engage with technology, we actually engage with it, and it engages back with us, and we engage with it. So it's this co-evolution that's happening, and in that sense, I think that as we create more autonomous, intelligent AI, it will help us survive, because if we co-evolve with it, it will need us as much as we need it, is my opinion. How that happens, or if that bears out to be true, we'll see, but I don't think the idea that we use technology is a correct way to put it. I think that technology is something so strange, the way it is today, like digital technology. I'm not talking about hammers or things like that, those kinds of tools, okay? Is technology is so far removed from that, and our environment is so now conditioned by our technology and the infrastructure we live within, the material structure. I think that it's going to, I don't think it's gonna be a Frankenstein. I think it's actually going, like a Mary Shelley type idea of technology. I think it's actually going to be more Promethean in the sense of, you know, think about it. We create children, and then we get old, and we rely upon our children to help us, okay? Well, I feel like that about technology. We've created, well, we've created it, right? And so it's kind of growing up now. Or maybe it's in its teenage years, and we'll see. What do you think about, in terms of this co-evolution of the work around brain-computer interfaces and maybe Neuralink and Elon, seeing Neuralink in particular as a, its long-term mission as a symbiosis with artificial intelligence. So like giving a greater bandwidth channel of communication between technology, AI systems, and the biological neural networks of our human mind. What do you think about this idea of connecting directly to the brain in AI systems? I mean, okay, I've listened to your podcast with Elon. I've listened to Elon before, very intelligent, obviously a super smart guy. I think this is already, I mean, not in the specific ways that he is doing it, but I think we are already doing that, okay? And I can give you some examples. And there are really trivial examples, but they do make the point, and this is one of them. So before I started this research on UFOs and UAPs and technology, I actually was looking at the effects of technology and in particular media on religion. And what I did was I was lucky to be asked to be a consultant for various movies. And one in particular I learned a lot from and that was The Conjuring. So I was a history consultant for The Conjuring. It happens to be my field, it's Catholic studies, right? And you've got these people who are real people and they're exercising demons and things like that. Okay, so I thought, wow, this is a great example for me. You know, I didn't do it for the money. It doesn't pay well, but I did it to learn, right? So I work closely with the screenwriters who I work with now all the time. I work with them all the time now. And what I found was this. I found that as the most interesting part of the creation of this movie was the editing process because they would use, it would go through editing and they would use test audiences. And a lot of the test audiences would be like, you know, there's like these things where they test their flicker rates and things like that, the eye flicker rates. And so, and when it goes really intense, they go to UC Irvine and they do this thing called cognitive consumption, which is basically, or I'm sorry, cognitive consumerism, where they basically hook test audiences up to EKGs and they read their brains and they figure out which scenes create the most- Arousal. Yeah, and so they cut out all the other scenes, okay? So what we're getting is we're getting like this drug. When we go to the movies or when we do video games or when we watch, we're literally physiologically responding to our technologies. So we're already there, we're already interfacing with them physiologically. So that's my example. Now, the kind of thing that he's doing, Musk is doing with Neuralink, I say, go for it. That's awesome, I hope he does it, you know? I'm fascinated, I want it to happen. Why do I want it to happen? Because I think that, well, first it's inevitable that it's going to happen. I also want to point out that Jacques Vallée was trying to get this done back in the 60s and the 70s. He was writing papers about, in fact, the ARPANET, the proto-internet, was called Augmentation of the Human Intellect. So we've been doing this for a while, okay? So props to Elon Musk, but we've been thinking about this for a good time. We've even been visioning it, okay? So there was a really interesting Jesuit priest who was French, Tellier de Chardin. I don't know if you know who he is. If not, he's fascinating. He was actually a soldier before he became a priest. And so he believed, he also saw what he called a biosphere. Now, this guy is talking in like the early 20th century, like the 1917, you know, that time period. And so basically he said and wrote about this thing called the noosphere. And he basically said, there will be a point when we merge with our technology and it's going to be somewhat like some kind of a biosphere. We have this atmosphere and then we have the stratosphere and it's gonna be this biosphere and we're all gonna be hooked into it mentally. So we'll be able to communicate in a way in which we don't communicate now. So, you know, that sounds so similar to the singularity. So after, I've read him many, many years ago, but when I read the Curtis Wiles book about the singularity, to me, it read just like religious language. Like it read like, you know, cause he, in fact, it's so much like revelation to me when I read it that I even assign it to my students in my classes. I'm like, this is it. You know, this is like a really great book of the singularity, you know, the coming singularity and this religious event, because it seems like it when he writes about it, he says, I felt it before I even understood it. You know? He, I mean, Kurzweil. Kurzweil, yeah, Kurzweil. I mean, what are your feelings about, not feelings, thoughts, feelings too, about the idea of the singularity? Do you think it's ultimately the thing that echoes throughout the history of ideas is this like moment of revelation, like this almost mythological religious moment, or is there something more physical to this idea of- Concrete. Concrete about the idea of, there'll come a point where our technology, there'll be like a phase shift between the basic fabric of like humanity, of how we interact, you know, how evolution brought us to be, these biological interaction, that our technology crosses some kind of line of capability that the world would be more technology than human to where it'll leave us behind. Sort of- Oh yeah, I don't think it's gonna leave us behind. I think it's gonna take us along. But it will be, I mean, I guess the idea of the singularity, first of all, isn't the idea of the singularity is like we can't possibly predict what's on the other side of the singularity. These are the senses like, this is like the world will be fundamentally transformed. Yes, okay, so right. And then it was, this was characterized in various movies like Lucy and stuff like that. Lucy being the first human that, right? So kind of replicating, this is gonna be the next iteration of humans is the singularity. I actually don't believe that, frankly. However, and the reason I don't believe it is because we're material beings and technology has to have a host. So we're not gonna become something super abstract. Like it's just impossible to do. There's nothing like that. Well, people will be listening to this podcast 100 years from now and laughing at it because they'll be all existing in a virtual reality. We'll be all information as opposed to material, meaning connected to some kind of concept of physical, physical reality. I don't even know the right words to use here. No, see, that's because there are none because there's no place from, there's no view from nowhere. There's no non-material, like we have thoughts, but they're connected to us, right? They're in our, you know, they're somehow, okay. As far as you know. Listen, platonic forms, I think, is about as, as, you know, close to what we're talking about as possible. Like this place where these things exist and then there's like a physical instantiation of it. No, but see, we're, the question is from the perspective of the platonic form, what does our physical world look like? You know what I'm saying? Like, you know, if, say you're a creature existing in a virtual reality, like if you grew up your whole life in a virtual reality game, like what is it, and somebody in that virtual reality world tells you that there actually exists this physical world and in fact, your own, you think you're in this virtual world, but it's actually, you're in a body and this is just your mind putting yourself and there's a piece of technology. Like, how will they be able to think of that physical world? Would they sound exactly like you just sounded a minute ago saying like, well, that's silly. Who cares if there's a physical world? It's the entirety of the perception and my memories and all of that is in this other realm of like information. It's just all just information. Why do I need some kind of weird meat bag to contain? So there's a great, again, I always return to something for your audience to read or you. There's a great, very short article online for free by David Chalmers, do you know him? He's the philosopher of consciousness. Yeah, interviewed him on this podcast, yeah. Yeah, yeah, he's cool. I used to, I was friends with his best friend for a while when I was in grad school. He probably has some weird friends. He does. He's a philosopher, okay? So. I like his fashion choice and his style too. Hang out with him a little bit, he's a great guy. Okay, so he wrote this article, which I use a lot. I love it because it's accessible to undergraduates and it's called Matrix as Metaphysics. And basically it's an answer to external world skepticism, which is basically how do we know there's an external world, right? How do we know that we're not in a matrix right now? And so basically he's using, he's also, he even references, he uses a religious reference even. He says, you could think of the matrix of the movie as a new, as the new book of Genesis for our new world, right? And I thought, yeah, that's absolutely correct because we don't know and we don't, we won't know for sure or for certain. Therefore, what we know is what is real to us. And so he goes through these scenarios and within philosophy is called, there's a, this is different from that, but it's like this brain in a vat, right? If you're a brain in a vat and some not so kind scientist is like recreating this world for you just to see, you know, and you think you're this awesome rockstar, right? And you're living this awesome existence, but you're actually just this brain in this vat, okay? But there's still a brain in a vat, okay? So his idea in the Matrix as Metaphysics kind of takes out the brain in a vat like this. I don't know if this is possible. So I've read critiques of this that, you know, what you're talking about is a non-dualism, like there's like, you know, or it's not necessarily a non-dualism. I just, I mean, information in and of itself has to have some kind of material component to it. I mean, it's that when taking it outside the realm of human beings, because dualism is kind of talking about humans in a sense, it's just possible to me that there could be creatures that exist in a very different form, perhaps rely on very different set of materials that may perhaps not even look like materials to us. Yes, I agree. Which is why like information, it could be even in computers, the information that's traveling inside a computer is connected to actual material movement. Right. Right, so like it is ultimately connected to material movement, but it's less and less about the material and more and more about the information. So I just mean that it's possible that- You think the singularity is basically like sloughing off our material existence? Well, I don't know. Because I can tell you that this has been the hope of philosophers and theologians forever. Yeah, well, I think we're living through a singularity. I don't think, I think this world, just like as you've said already, has been already transformed significantly and keeps continually being transformed. Yes. And we're just riding this big, beautiful wave of transformation and that's why it's both exciting and terrifying from a scientific perspective that like, we're so bad at predicting the future and the future is always so amazing in terms of the things it has brought us. I mean, I don't know if it always will be this exciting in terms of the rate of innovation, but it seems to be increasing still. And it's really exciting. It's exciting to- I think so too, yeah. It's terrifying because obviously we're building better and better tools for destroying ourselves. But I, on the optimistic side, believe that we also can build better and better tools to defend against all the ways we can destroy ourselves. And it's kind of this interesting race of innovation. Yeah. Books are great. Of course, the greatest book of all time, two of the greatest books of all time are yours. But besides those, what books, technical, fiction, or philosophical had an impact on your life or possibly you think others might want to read and get some insights from? And what ideas did you pick up from them? Great. Okay, I really enjoy Nietzsche. Okay, so anything by Nietzsche, Friedrich Nietzsche. He's a philosopher. I actually hated him when I first read him in my early 20s. That's like the opposite of most people's experience, right? They usually love him in their 20s and then they throw him to the curb. Later, yeah. I think he's totally misrepresented and misinterpreted. He grew on you. Well, it happened in one night. So, let me just describe it, because it's kind of funny. Yeah. It happened on New Year's. So I had friends when I was in my 20s and they kept telling me, you have to read Nietzsche, you have to read Nietzsche. And I tried, okay? But again, you know, no. I didn't like, I was not into how he described the philosophical concepts he was trying to get across. So, but they weren't giving up. I have very persistent friends. So, one of them gave me the Gay Science and I had it on my book stand and it was New Year's Eve. And I'm actually not a big part, I'm actually an introvert. I'm a geeky introvert, okay? So, I don't go out and party a lot. It was New Year's Eve, even that couldn't get me out to go party. So, I just wanted to go to bed. Yeah. And New Year's Eve hit and everybody went out and I was asleep and they woke me up. And I was like, darn, they woke me up. Eh, might as well read this book by Nietzsche. Okay, so I picked it up and lo and behold, I turned to a page that was exactly about, it was called Sanctus Januarius, which is basically St. January, and it was about New Year's Eve. And I thought, whoa, what a weird coincidence. And it was a really, it was also super Catholic. And it was a really beautiful little aphorism. It's actually a book of aphorisms, which are kind of religious, right? And so, it's religious, the genre is religious, let's put it that way, but he's not. So, basically he says, today's the day when people are supposed to make these resolutions, right? And he says, from here on out, I will never say no. I will only say yes, okay? I look away. If something's horrible, I'll just look away from it. I won't get angry at it. And then he also says, I will be like St. January. And St. January is actually the saint whose blood is in this place in Italy. I think it's in Italy. And every year it turns to blood again. So, it's like, it's desiccated, it's, you know. So, it's this miracle. He says, my blood is now, it flows again. And I was like, wow, that's really beautiful. And I said, and a strange coincidence because it just turned 12. So, it's like New Year's Eve. I pick up the book, I read this aphorism. I said, strange coincidence that. And then I turn the page and the page is about coincidences. And I was like, I shut it. And I thought, this is weird. And I felt like it was alive. I felt like the book was alive and Nietzsche was speaking to me, right? I had a like experience and engagement with Nietzsche. And so, after that, I couldn't put his stuff down. It was engaging, fascinating, everything. So, yeah, so that's one book, The Gay Science. What did you pick up from The Gay Science or from Nietzsche in general? Is there some ideas that just kind of. Yeah, yeah, the ideas basically that truth. He's got awesome one-liners. So, truth is a woman. So, okay, what does he mean by that? Truth is a woman. Basically, she's gonna lie to you. She looks real attractive, but she's not gonna tell you the truth. Oh, Nietzsche, yeah. So, okay, so basically, I'm not saying that that's true about women. I'm obviously a woman. So, basically, what he's saying is that truth is not, is like what I said, brother Guy said, it's a moving target, okay? We started this whole conversation with what's real, right? So, I should have just gone straight to Nietzsche. Haven't you heard truth is a woman? Okay, so truth is a woman. All right, so that, and also, and Foucault, this other philosopher, French philosopher, actually takes up this idea and creates his own framework called genealogy from it, so the genealogy of morals, so that we only believe certain things and we sediment them into truth. So, we say a truth told, who said that? Was it Lenin or Stalin? A truth told enough times, I mean, a lie told enough times becomes the truth. So, that's basically Nietzschean right there, okay? So, that's Nietzsche. So, Nietzsche also is a huge critic of Christianity, which I'm actually Catholic, I'm a practicing Catholic, so I appreciated his critique. I thought it was actually quite accurate. He's a critique of religion in general, and he's fascinating, and also, I find that his, he talks about altered states of consciousness, and he calls them elevated states, and I think through his book, you can actually experience elevated states, so yeah, Nietzsche. Thumbs up. So, what other book? Yeah, okay, so Hannah Arendt, she is a philosopher that not a lot of people know about, but she was a Jewish woman during the Holocaust, and she was interned at Bergen-Belsen, which was basically Auschwitz for women, and she escaped. She came to the United States, and she had worked with Heidegger, even though he's supposed to be anti-Semitic, and a Nazi, and everything, but they were lovers, okay? So, she comes out, and she's at Columbia University, and she teaches philosophy there, and she writes two books, which I'll recommend. One is called Eichmann in Jerusalem, where she attends the Nuremberg trials, and she basically makes this really astute observation about evil, and she says, Eichmann is one of the people who sent the Jews to the concentration camps who ran the trains, okay? And she said, the thing about Eichmann was that he didn't seem particularly evil. Actually, he seemed to be quite a nice guy. She said, what was interesting about him was he seemed incredibly thoughtless and stupid, and she said, and he used a lot of stereotypes, like memes. So, she actually wrote about memes before we had them, and now people just use memes, and they're actually used against us even. There's even a segment of warfare called memetic warfare, all right? So, memes are something that can sway a whole population of people. So, she wrote about memes before they were even in existence, and that's Eichmann in Jerusalem, and I think she also has some really amazing things to say about evil, is that when people remain thoughtless, she has another book called The Life of the Mind, which is gigantic, and I don't think anybody will read it, but frankly, it's one of the best books I've ever read, and I've read it many times. And basically, The Life of the Mind, in The Life of the Mind, she asks a very simple question. She says, why do people do bad things? Why are they evil? And what she says is she wonders if it's, she says that bad people sleep well at night, contrary to, you know how the saying, how do you sleep at night? Well, that's only because you're a good person that you're asking that question, because you actually have a conscience, and a conscience is this dual kind of, you fight with yourself about the consequences of your actions, and she says, bad people don't seem to have a conscience, so they actually sleep well at night. And so she goes through a whole history of philosophy about evil, and that's really a good one too, but I also have to recommend this one too. There's one more. So I know I recommended two, but just from the same philosopher. My friend Jeffrey Kripal, he's at Rice University, and he's in my field, religious studies. He's written several books. I mean, he's written a heck of a lot of books, let's put it that way, but I think his best book, or the one that impacted me the most, is called Authors of the Impossible. And his writing is very much like Nietzsche's writing, in the sense that it's almost as if he reaches out of the pages, and he grabs you, and he kind of slaps you around and says, think about this, you know, and you can't help but be changed after you've read it. And he's got a great chapter in there about Jacques Vallée. Oh, so he covers a bunch of different thinkers and authors that somehow are, what is it, renegade in some aspect, or revolutionary in some aspect. They're thinking the impossible. There's a great one he's written called Mutants and Mystics, where he talks about the comic strips, the, gosh, why can't I remember the name of the person, he just died, Stan Lee. He talks about the history of the comics by Stan Lee, and they're all paranormal. They all start off super paranormal, and it's fascinating. On the topic of Hannah Arendt. Yeah, Hannah Arendt. Hannah Arendt. So I haven't read her work, but I've vaguely touched upon sort of like commentary of her work, and it seems like some people think her work is dangerous in some aspect. I don't know if you can comment on why that is. It feels like similar with Ayn Rand, or something like that. Yeah. Where like this is, I should say not dangerous, but controversial. Yes, it is. Yes, they think it's controversial. This is the reason, I believe. I've heard of the controversy. The controversy is that she didn't, first of all, she is Jewish, and she did escape a concentration camp, and yet she's called, she's been called anti-Jewish. And I think part of that was that she basically was saying something that I believe, that a lot of normal people are like Eichmann, and evil things are done by people who just follow the rules, and they don't think about what they're doing. And that's one of the most pernicious forms of evil of our time. So we've talked quite a bit about the definitions of religion, and what are the different building blocks of religion. So one of the, I don't think we touched on, we did a little bit with the afterlife, but in a sense, I don't know if you're familiar with the Ernest Becker work, and all the philosophies around there about the fear of death, and how the fear of our own mortality, or awareness of our own mortality, and its fear is, in the case of Ernest Becker, is a significant component in the psychology in the way we humans develop our understanding of the world. So what are your thoughts in the context of religion, or maybe in the context of your own mind about the role of death in life, or fear of death in life? And are you afraid of death? We cover everything in this podcast. Every single topic is covered. Wow, okay. I so happen to have benefited, perhaps, from living with an older brother who seemingly had no fear of death while growing up, and he did everything, okay? So he was, he climbed mountains, he was a rock climber, he jumped out of airplanes. Of course, he had to be a Green Beret and go into the special forces where that type of thing is a requirement, right? And so because of that, I did a lot of things outside of my comfort zone, and which probably I shouldn't have done, and hope to goodness my kids don't do them, okay? Yeah. Okay, so do I fear death? I think about death a lot, actually. You may not know this about me, but in my field, I was the head, I was the co-chair of the death panel. It's called the death panel. There was like, it's the panel to think about death in religious studies, and I was that for many years. So you've thought about it a bit. A bit. Let's see, I think that people are a little too confident, I think, about life in general, that they're gonna kind of live all the time and not die. I happen to, I mean, I hate to say it, I'm super positive, and most people would consider me to be too happy almost, right? And so it's odd then that I spend a lot of time thinking about death, but I wonder if there's a connection there. Yeah. I'm happy to be alive, right? That's kind of what the thinking about death does, is it makes you appreciate the days that you do have. Yeah. It's a weird contrast. I tend to believe that the fact that this life ends gives each day a significant amount of meaning. So I don't know. It seems like an important feature of life. It's not like a bug. It seems like a feature that it ends, but it's a strange feature, because I wish it, like all the good stuff, you wish it wouldn't end. Well, you know what's interesting, Lex, and I do point this out to my students, because we cover, in a lot of the basic studies courses I teach, we cover all religions, or as many as we can, like the major religions. And so take Hinduism, for example. Now, this is an ancient religion, okay? So you and I are here talking about how we enjoy living and life and things like that. Well, the goal of Hinduism is basically never to get reincarnated again, is basically to not live, okay? And to get off Samsara, which is the wheel of life and death. Yeah. Escape the whole thing. Yeah, exactly. Think of that. Conditions are so different that you and I and my students are happy to be alive, but they're back in the day, you know, thousands of years ago, when they wrote, when they actually didn't write it, they spoke the Vedas, which were the sacred traditions of India. They wanted off. They didn't wanna come back. Life was terrible. That's what people don't have, the adequate understanding of history, that for the majority of people, life is really hard, right? And you and I are, and your audience, among the lucky. Yeah. We actually like life. We wanna live. We wanna live. Most of the time. Yeah, most of the time. What do you think the biggest, since we're covering every single possible topic, let me ask the biggest one, the unanswerable one, from the perspective of alien intelligence, or from the perspective of religious studies, or from the perspective of just Diana, what do you think is the meaning of this existence, of this life of ours? Yes, okay. So, all right, so. Well, of course I have to, my philosophical training as an undergrad always makes me think about, what's the assumption in your question? There's an assumption there. It's like, there is a meaning. Okay, that's the assumption. What do you mean by meaning? What do you mean by life? Yeah. Can you define the terms? No, no, but listen. Okay, I'll answer your question. I'm just gonna say that there's this assumption that we should have meaning to life, okay? Well, maybe we shouldn't. Maybe it's just all random, okay? However, I believe that it's not, and in my opinion, the meaning of life, in my opinion, is intrinsic. I enjoy living. I want to live. Sometimes I don't enjoy living, and when I don't enjoy living, I change my circumstances. So, it's intrinsic, and I think that certain things are intrinsic, and like love, love of your children is kind of, well, it's actually physiological, but it's also intrinsic. It's beautiful. You know, there's something about it that is intrinsically desirable. So, I think the meaning of life is like that, intrinsically desirable. So, it's something that just is born inside you based on what makes you feel good? No, that's hedonism. That's... So, but where do you place love? Love of your children. Yeah, so basically, love of your children, by the way, is not always easy because they do things that they shouldn't do. You have to discipline them. That's one of the worst things about parenthood, to me, is disciplining my children. I don't like to do that. I love them. So, a lot of things that I do that I feel are good are not easy. So, there's an intrinsic sense that, like, okay, let's take animals, okay? So, we have dogs and cats, okay? So, you might not, but I do. I told you about them. Can you share their names? If I share their names, I will share their names, okay? So, we have a cat, and it has red, fluffy hair, and so we called it Trump. Well, when we got our dog, we figured that it needed a companion, so we called it Putin. So, we have Trump and Putin. Those are the greatest pet names of all time. I'm sorry. And... I don't know. Maybe we'll be able to share a picture of your cat, because this is awesome. It is really cute, yeah. Very photogenic. I mean, is this something that's, whether we're talking about love or the intrinsic meaning, do you think that's something that's really special to humans? Or if there is intelligent alien civilizations out there, do you think that's something that they possess as well? Maybe in different forms? Like, whatever this thing that meaning is, this intrinsic drive that we have, do you think that's just a property of life, of some level of complexity? That we will see that everywhere in this universe? In my opinion, and this is just my opinion, I do think that it is, but I also think that it could take different forms. So if there is like, think of gravity, right? Gravity kind of like makes stuff stick to it, right? It attracts stuff. Well, what does love do? That does that too, right? So people who are, we call them charismatic. Charism, it means love. Charism means light and love. So a charismatic person is a person who attracts people to them, like the sun does, right? Like, you know? So I think that whatever this property is that's intrinsic is like gravity and most likely takes different forms in different types of life forms. Yeah, I can't wait until like Albert Einstein type of figure in the future will discover that love is in fact one of the fundamental forces of physics. That would be cool. Diana, this is one of the favorite conversations I've ever had. It's truly an honor to talk to you. And thank you so much for spending all this time with me. Absolutely, it's been fun. Thank you. Thanks for listening to this conversation with Diana Walsh-Basulka. And thank you to our sponsors, Element Electrolyte Drink, Grammarly Writing Plugin, Business Wars Podcast, and Cash App. So the choice is health, grammar, knowledge, or money. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you with some words from Carl Sagan. Somewhere, something incredible is waiting to be known. Thank you for listening and hope to see you next time.

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Eric Weinstein: Revolutionary Ideas in Science, Math, and Society | Lex Fridman Podcast #16

The following is a conversation with Eric Weinstein. He's a mathematician, economist, physicist, and the managing director of Thiel Capital. He coined the term, and you could say, is the founder of the intellectual dark web, which is a loosely assembled group of public intellectuals that include Sam Harris, Jordan Peterson, Steven Pinker, Joe Rogan, Michael Shermer, and a few others. This conversation is part of the Artificial Intelligence podcast at MIT and beyond. If you enjoy it, subscribe on YouTube, iTunes, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D. And now, here's my conversation with Eric Weinstein. Are you nervous about this? Scarce, you'll see. Okay. You mentioned Kung Fu Panda as one of your favorite movies. It has the usual profound master-student dynamic going on. So, who has been a teacher that significantly influenced the direction of your thinking and life's work? So, if you're the Kung Fu Panda, who was your Shifu? Oh, that's interesting because I didn't see Shifu as being the teacher. Who was the teacher? Oogway, Master Oogway, the turtle. Oh, the turtle, right. They only meet twice in the entire film, and the first conversation sort of doesn't count. So, the magic of the film, in fact, its point is that the teaching that really matters is transferred during a single conversation, and it's very brief. And so, who played that role in my life? I would say either my grandfather, Harry Rubin, and his wife, Sophie Rubin, my grandmother, or Tom Lehrer. Tom Lehrer? Yeah. In which way? If you give a child Tom Lehrer records, what you do is you destroy their ability to be taken over by later malware. And it's so irreverent, so witty, so clever, so obscene, that it destroys the ability to lead a normal life for many people. So, if I meet somebody who's usually really shifted from any kind of neurotypical presentation, I'll often ask them, are you a Tom Lehrer fan? And the odds that they will respond are quite high. Now, Tom Lehrer's Poisoning Pigeons in the Park, Tom Lehrer? That's very interesting. There are a small number of Tom Lehrer songs that broke into the general population, Poisoning Pigeons in the Park, The Element Song, and perhaps The Vatican Rag. So, when you meet somebody who knows those songs, but doesn't know- Oh, you're judging me right now, aren't you? Harshly. No, but you're Russian, so undoubtedly you know Nikolai Ivanovich Lobachevsky, that song. Yes, yeah. So, that was a song about plagiarism that was in fact plagiarized, which most people don't know, from Danny Kaye, where Danny Kaye did a song called Stanislavski of the Musky Arts. And so, Tom Lehrer did this brilliant job of plagiarizing a song about, and making it about plagiarism, and then making it about this mathematician who worked in non-Euclidean geometry. That was like giving heroin to a child. It was extremely addictive, and eventually led me to a lot of different places, one of which may have been a PhD in mathematics. And he was also at least a lecturer in mathematics, I believe, at Harvard, something like that. I just had dinner with him, in fact. When my son turned 13, we didn't tell him, but his bar mitzvah present was dinner with his hero, Tom Lehrer. And Tom Lehrer was 88 years old, sharp as a tack, irreverent and funny as hell. And just, you know, there are very few people in this world that you have to meet while they're still here, and that was definitely one for our family. So, that wit is a reflection of intelligence in some kind of deep way. Like, where, that would be a good test of intelligence, whether you're a Tom Lehrer fan. So, what do you think that is about wit, about that kind of humor, ability to see the absurdity in existence? Do you think that's connected to intelligence, or are we just two Jews on a mic that appreciate that kind of humor? No, I think that it's absolutely connected to intelligence. You can see it, there's a place where Tom Lehrer decides that he's going to lampoon Gilbert of Gilbert and Sullivan, and he's going to outdo Gilbert with clever, meaningless wordplay. And he has, forget the, well, let's see. He's doing Clementine as if Gilbert and Sullivan wrote it. And he says, that I missed her to pester, young sister, nay, mister, this mister to pester she tried. Pestering sisters of festering blister, you best to resist her, say I. The sister persisted, the mister resisted, I kissed her all loyalty slip. When she said I could have her, her sister's cadaver must surely have turned in its crypt. That's so dense, it's so insane that that's clearly, you know, maybe intelligence, because it's hard to construct something like that. If I look at my favorite Tom Lehrer lyric, you know, there's a perfectly absurd one, which is, once all the Germans were warlike and mean, but that couldn't happen again. We taught them a lesson in 1918, and they've hardly bothered us since then. Right? That is a different kind of intelligence. You know, you're taking something that is so horrific, and you're sort of making it palatable and funny and demonstrating also just your humanity. I mean, I think the thing that came through as Tom Lehrer wrote all of these terrible, horrible lines was just what a sensitive and beautiful soul he was, who was channeling pain through humor and through grace. I've seen throughout Europe, throughout Russia, that same kind of humor emerged from the generation of World War II. It seemed like that humor is required to somehow deal with the pain and the suffering that that war created. Well, you do need the environment to create the broad Slavic soul. I don't think that many Americans really appreciate Russian humor, how you had to joke during the time of, let's say, Article 58 under Stalin. You had to be very, very careful. The concept of a Russian satirical magazine like Krokodil doesn't make sense. So you have this cross-cultural problem that there are certain areas of human experience that it would be better to know nothing about. And quite unfortunately, Eastern Europe knows a great deal about them, which makes the songs of Vladimir Vysotsky so potent, the prose of Pushkin, whatever it is, you have to appreciate the depth of the Eastern European experience. And I would think that perhaps Americans knew something like this around the time of the Civil War, or maybe under slavery and Jim Crow, or even the harsh tyranny of the coal and steel employers during the labor wars. But in general, I would say it's hard for us to understand and imagine the collective culture unless we have the system of selective pressures that, for example, Russians were subjected to. Lex Dyson Yes. So if there's one good thing that comes out of war, it's literature, art, and humor, and music. Peter Oh, I don't think so. I think almost everything is good about war except for death and destruction. Lex Dyson Right. Without the death, it would bring the romance of it. The whole thing is nice. Peter Well, this is why we're always caught up in war. We have this very ambiguous relationship to it, is that it makes life real and pressing and meaningful, and at an unacceptable price, and the price has never been higher. Lex Dyson So to jump into AI a little bit, in one of the conversations you had, or one of the videos, you described that one of the things AI systems can't do, and biological systems can, is self-replicate in the physical world. Peter Oh, no, no. Lex Dyson In the physical world. Peter Well, yes, the physical robots can't self-replicate. But this is a very tricky point, which is that the only thing that we've been able to create that's really complex, that has an analog of our reproductive system, is software. Lex Dyson But nevertheless, software replicates itself, if we're speaking strictly for replication, in this kind of digital space. So I mean, just to begin, let me ask a question. Do you see a protective barrier or a gap between the physical world and the digital world? Peter Let's not call it digital. Let's call it the logical world versus the physical world. Lex Dyson Why logical? Peter Well, because even though we had, let's say, Einstein's brain preserved, it was meaningless to us as a physical object, because we couldn't do anything with what was stored in it at a logical level. And so the idea that something may be stored logically, and that it may be stored physically, are not necessarily, we don't always benefit from synonymizing. I'm not suggesting that there isn't a material basis to the logical world, but that it does warrant identification with a separate layer that need not invoke logic gates and zeros and ones. Lex Dyson And so connecting those two worlds, the logical world and the physical world, or maybe just connecting to the logical world inside our brain, Einstein's brain, you mentioned the idea of out, out intelligence. Peter Artificial out intelligence. Lex Dyson Artificial out intelligence. Peter Yes, this is the only essay that John Brockman ever invited me to write that he refused to publish in Edge. Lex Dyson Why? Peter Well, maybe it wasn't, it wasn't well written. But I don't know. Lex Dyson The idea is quite compelling. It's quite unique and new, at least from my view, stance point. Maybe you can explain it. Peter Sure. What I was thinking about is why it is that we're waiting to be terrified by artificial general intelligence, when in fact, artificial life is terrifying in and of itself, and it's already here. So in order to have a system of selective pressures, you need three distinct elements. You need variation within a population, you need heritability, and you need differential success. So what's really unique, and I've made this point, I think, elsewhere, about software is that if you think about what humans know how to build, that's impressive. So I always take a car, and I say, does it have an analog of each of the physiological systems? Does it have a skeletal structure? That's its frame. Does it have a neurological structure? It has an onboard computer, has a digestive system. The one thing it doesn't have is a reproductive system. But if you can call spawn on a process, effectively, you do have a reproductive system. And that means that you can create something with variation, heritability, and differential success. Now, the next step in the chain of thinking was, where do we see inanimate, non-intelligent life outwitting intelligent life? And I have two favorite systems, and I try to stay on them so that we don't get distracted. One of which is the Ofriz orchid, subspecies, or subclade, I don't know what to call it. Is it a type of flower? Yeah, it's a type of flower that mimics the female of a pollinator species in order to dupe the males into engaging, it was called pseudocopulation, with the fake female, which is usually represented by the lowest petal. And there's also a pheromone component to fool the males into thinking they have a mating opportunity. But the flower doesn't have to give up energy in the form of nectar as a lure, because it's tricking the males. The other system is a particular species of mussel, Lampicillus in the clear streams of Missouri. And it fools bass into biting a fleshy lip that contain its young. And when the bass see this fleshy lip, which looks exactly like a species of fish that the bass like to eat, the young explode and clamp onto the gills and parasitize the bass and also use the bass to redistribute them as they eventually release. Both of these systems, you have a highly intelligent dupe being fooled by a lower life form. And what is sculpting these convincing lures? It's the intelligence of previously duped targets for these strategies. So when the target is smart enough to avoid the strategy, those weaker mimics fall off. They have terminal lines, and only the better ones survive. So it's an arms race between the target species that is being parasitized getting smarter, and this other less intelligent or non-intelligent object getting as if smarter. And so what you see is that artificial general intelligence is not needed to parasitize us. It's simply sufficient for us to outwit ourselves. So you could have a program, let's say, one of these Nigerian scams that writes letters and uses whoever sends it Bitcoin to figure out which aspects of the program should be kept, which should be varied and thrown away. And you don't need it to be in any way intelligent in order to have a really nightmarish scenario of being parasitized by something that has no idea what it's doing. Lex. So you phrased a few concepts really eloquently. So let me try to, as a few directions this goes. So one, first of all, in the way we write software today, it's not common that we allow it to self-modify. Darrell Bock But we do have that ability now. Lex. We have the ability. It's- Darrell Bock Just not common. Lex. It's not just common. So your thought is that that is a serious worry if there becomes a- Darrell Bock But self-modifying code is available now. Lex. So there's different types of self-modification, right? There's personalization, you know, your email app, your Gmail is self-modifying to you after you log in or whatever, you can think of it that way. But ultimately, it's central, all the information is centralized. But you're thinking of ideas where you're completely, so this is a unique entity operating under selective pressures and it changes- Darrell Bock Well, you just, if you think about the fact that our immune systems don't know what's coming at them next, but they have a small set of spanning components. And if it's a sufficiently expressive system in that any shape or binding region can be approximated with the Lego that is present, then you can have confidence that you don't need to know what's coming at you because the combinatorics are sufficient to reach any configuration needed. Lex. So that's a beautiful thing, well, terrifying thing to worry about because it's so within our reach. What- Darrell Bock Whenever I suggest these things, I do always have a concern as to whether or not I will bring them into being by talking about them. Lex. So there's this thing from OpenAI, so next week I have to talk to the founder of OpenAI, this idea that their text generation, the new stuff they have for generating text is, they didn't want to bring it, they didn't want to release it because they're worried about the- Darrell Bock I'm delighted to hear that, but they're going to end up releasing it. Lex. Yes, so that's the thing. I think talking about it, well, at least from my end, I'm more a proponent of technology preventing, so further innovation preventing the detrimental effects of innovation. Darrell Bock Well, we're sort of tumbling down a hill at accelerating speed, so whether or not we're proponents or- Lex. It doesn't really matter. Darrell Bock It may not matter. Lex. Well, it may not. Darrell Bock Well, I do feel that there are people who've held things back and died poorer than they might have otherwise been. We don't even know their names. I don't think that we should discount the idea that having the smartest people showing off how smart they are by what they've developed may be a terminal process. I'm very mindful in particular of a beautiful letter that Edward Teller, of all people, wrote to Leo Zillard, where Zillard was trying to figure out how to control the use of atomic weaponry at the end of World War II. Teller, rather strangely, because many of us view him as a monster, showed some very advanced moral thinking, talking about the slim chance we have for survival and that the only hope is to make war unthinkable. I do think that not enough of us feel in our gut what it is we are playing with when we are working on technical problems. I would recommend to anyone who hasn't seen it a movie called The Bridge on the River Kwai about, I believe, captured British POWs who, just in a desire to do a bridge well, end up over collaborating with their Japanese captors. Well, now you're making me question the unrestricted open discussion of ideas in AI. I'm not saying I know the answer. I'm just saying that I could make a decent case for either our need to talk about this and to become technologically focused on containing it, or need to stop talking about this and try to hope that the relatively small number of highly adept individuals who are looking at these problems is small enough that we should, in fact, be talking about how to contain them. Well, the way ideas, the way innovation happens, what new ideas develop, Newton with calculus, whether if he was silent, the idea would emerge elsewhere. Well, in the case of Newton, of course, but in the case of AI, how small is the set of individuals out of which such ideas would arise? Well, the idea is that the researchers we know and those that we don't know, who may live in countries that don't wish us to know what level they're currently at are very disciplined and keeping these things to themselves. Of course, I will point out that there's a religious school in Kerala that developed something very close to the calculus, certainly in terms of infinite series in, I guess, religious prayer and rhyme and prose. So, it's not that Newton had any ability to hold that back and I don't really believe that we have an ability to hold it back. I do think that we could change the proportion of the time we spend worrying about the effects of what if we are successful rather than simply trying to succeed and hope that we'll be able to contain things later. Beautifully put. So, on the idea of intelligence, what form, treading cautiously as we've agreed as we tumbled down the hill, what form- Can't stop ourselves, can we? We cannot. What form do you see it taking? So, one example, Facebook, Google, do want to, I don't know a better word, you want to influence users to behave a certain way. And so, that's one kind of example of how intelligence is systems perhaps modifying the behavior of these intelligent human beings in order to sell more product of different kinds. But do you see other examples of this actually emerging in- Just take any parasitic system. Make sure that there's some way in which that there's differential success, heritability, and variation. And those are the magic ingredients. And if you really wanted to build a nightmare machine, make sure that the system that expresses the variability has a spanning set so that it can learn to arbitrary levels by making it sufficiently expressive. That's your nightmare. So, it's your nightmare, but it could also be, it's a really powerful mechanism by which to create, well, powerful systems. So, are you more worried about the negative direction that might go versus the positive? So, you said parasitic, but that doesn't necessarily need to be what the system converges towards. It could be, what is it? Well, parasitism, the dividing line between parasitism and symbiosis is not so clear. That's what they tell me about marriage. I'm still single, so I don't know. Well, yeah, we could go into that too, but no, I think we have to appreciate, you know, are you infected by your own mitochondria? Right. Right? Yeah. So, you know, in marriage, you fear the loss of independence, but even though the American therapeutic community may be very concerned about codependence, what's to say that codependence isn't what's necessary to have a stable relationship in which to raise children who are maximally case-selected and require incredible amounts of care because you have to wait 13 years before there's any reproductive payout, and most of us don't want our 13-year-olds having kids. It's a very tricky situation to analyze, and I would say that predators and parasites drive much of our evolution, and I don't know whether to be angry at them or thank them. Well, ultimately, I mean, nobody knows the meaning of life or what even happiness is, but there is some metrics. They didn't tell you? They didn't. That's why all the poetry and books are about, you know, there are some metrics under which you can kind of measure how good it is that these AI systems are roaming about. So, you're more nervous about software than you are optimistic about ideas of, yeah, self-replicating larceny. I don't think we've really felt where we are. You know, occasionally we get a wake-up. 9-11 was so anomalous compared to everything else we've experienced on American soil that it came to us as a complete shock that that was even a possibility. What it really was was a highly creative and determined R&D team deep in the bowels of Afghanistan, showing us that we had certain exploits that we were open to that nobody had chosen to express. I can think of several of those. These things that I don't talk about publicly that just seem to have to do with how relatively unimaginative those who wish to cause havoc and destruction have been up until now. But the great mystery of our time, of this particular little era, is how remarkably stable we've been since 1945, when we demonstrated the ability to use AI to do what we thought was provocative, when we demonstrated the ability to use nuclear weapons in anger. And we don't know why things like that haven't happened since then. We've had several close calls. We've had mistakes. We've had brinksmanship. And what's now happened is that we've settled into a sense that, oh, it'll always be nothing. It's been so long since something was at that level of danger that we've got a wrong idea in our head. And that's why when I went on the Ben Shapiro show, I talked about the need to resume above ground testing of nuclear devices, because we have people whose developmental experience suggests that when, let's say, Donald Trump and North Korea engage on Twitter, oh, it's nothing. It's just posturing. Everybody's just in it for money. There's a sense that people are in a video game mode, which has been the right call since 1945. We've been mostly in video game mode. It's amazing. So you're worried about a generation which has not seen any existential... We've lived under it. You see, you're younger. I don't know if, and again, you came from Moscow. Yeah. There was a TV show called The Day After that had a huge effect on a generation growing up in the US. And it talked about what life would be like after a nuclear exchange. We have not gone through an embodied experience collectively where we've thought about this. And I think it's one of the most irresponsible things that the elders among us have done, which is to provide this beautiful garden in which the thorns are cut off of the rose bushes and all of the edges are rounded and sanded. And so people have developed this totally unreal idea, which is everything's going to be just fine. And do I think that my leading concern is AGI or my leading concern is a thermonuclear exchange or gene drives or any one of these things? I don't know. But I know that our time here in this very long experiment here is finite because the toys that we've built are so impressive and the wisdom to accompany them has not materialized. And I think we actually got a wisdom uptick since 1945. We had a lot of dangerous skilled players on the world stage who nevertheless, no matter how bad they were, managed to not embroil us in something that we couldn't come back from. The Cold War. Yeah. And the distance from the Cold War. You know, I'm very mindful of, there was a Russian tradition actually, of on your wedding day, going to visit a memorial to those who gave their lives. Can you imagine this? Where you, on the happiest day of your life, you go and you pay homage to the people who fought and died in the battle of Stalingrad. I'm not a huge fan of communism, I gotta say, but there were a couple of things that the Russians did that were really positive in the Soviet era. And I think trying to let people know how serious life actually is, is the Russian model of seriousness is better than the American model. And maybe, like you mentioned, there was a small echo of that after 9-11. But we wouldn't let it form. We talk about 9-11, but it's 9-12 that really moved the needle. When we were all just there and nobody wanted to speak. We witnessed something super serious and we didn't want to run to our communities and our computers and blast out our deep thoughts and our feelings. And it was profound because we woke up briefly there. I talk about the gated institutional narrative that sort of programs our lives. I've seen it break three times in my life. One of which was the election of Donald Trump. Another time was the fall of Lehman Brothers when everybody who knew that Bear Stearns wasn't that important knew that Lehman Brothers met AIG was next. And the other one was 9-11. And so if I'm 53 years old and I only remember three times that the global narrative was really interrupted, that tells you how much we've been on top of developing events. We had the Murrow Federal Building explosion, but it didn't cause the narrative to break. It wasn't profound enough. Around 9-12, we started to wake up out of our slumber and the powers that be did not want to coming together. They, you know, the admonition was go shopping. And the powers that be was what is that force as opposed to blaming individuals? We don't know. So whatever that. Whatever that force is, there's a component of it that's emergent and there's a component of it that's deliberate. So give yourself a portfolio with two components. Some amount of it is emergent. But some amount of it is also an understanding that if people come together, they become an incredible force. And what you're seeing right now, I think, is there are forces that are trying to come together and there are forces that are trying to push things apart. And, you know, one of them is the globalist narrative versus the national narrative, where to the global globalist perspective, the nation's are bad things in essence, that they're temporary, they're nationalistic, they're jingoistic. It's all negative to people in the national, more in the national idiom. They're saying, look, this is where I pay my taxes. This is where I do my army service. This is where I have a vote. This is where I have a passport. Who the hell are you to tell me that because you've moved into some place that you can make money globally, that you've chosen to abandon other people to whom you have a special and elevated duty? And I think that these competing narratives have been pushing towards the global perspective from the elite and a larger and larger number of disenfranchised people are saying, hey, I actually live in a place and I have laws and I speak a language, I have a culture. And who are you to tell me that because you can profit in some faraway land, that my obligations to my fellow countrymen are so much diminished? So these tensions between nations and so on, ultimately you see being proud of your country and so on, which creates potentially the kind of things that led to wars and so on. Ultimately it is human nature and it is good for us for wake up calls of different kinds. Well, I think that these are tensions and my point isn't, I mean, nationalism run amok is a nightmare and internationalism run amok is a nightmare. And the problem is we're trying to push these pendulums to some place where they're somewhat balanced, where we have a higher duty of care to those who share our laws and our citizenship, but we don't forget our duties of care to the global system. I would think this is elementary, but the problem that we're facing concerns the ability for some to profit by abandoning their obligations to others within their system. And that's what we've had for decades. You mentioned nuclear weapons. I was hoping to get answers from you since one of the many things you've done as economics, and maybe you can understand human behavior, why the heck we haven't blown each other up yet, but okay, so we'll get back. I don't know the answer. Yes, it's a fast, it's really important to say that we really don't know. Mild uptick in wisdom. A mild uptick in wisdom. That's well, Steven Pinker, who I've talked with, has a lot of really good ideas about why, but nobody really. I don't trust his optimism. Listen, I'm Russian, so I never trust a guy who's that optimistic. No, no, no. It's just that you're talking about a guy who's looking at a system in which more and more of the kinetic energy, like war, has been turned into potential energy, like unused nuclear weapons. Wow, beautifully put. And now I'm looking at that system and I'm saying, okay, well, if you don't have a potential energy term, then everything's just getting better and better. Yeah, wow. That's beautifully put. Only a physicist could, okay. I'm not a physicist. Is that a dirty word? No, no. I wish I were a physicist. Me too. My dad's a physicist. I'm trying to live up to that probably for the rest of my life. He's probably going to listen to this too. So. He did. Yeah. So your friend, Sam Harris, worries a lot about the existential threat of AI, not in the way that you've described, but in the more. Well, he hangs out with Elon. I don't know Elon. So are you worried about that kind of, you know, about either robotic systems or, you know, traditionally defined AI systems essentially becoming super intelligent, much more intelligent than human beings and getting. Well, they already are. And they're not. When, when seen as a collective, you mean. Well, I mean, I can mean all sorts of things, but certainly many of the things that we thought were peculiar to general intelligence do not require general intelligence. So that's been one of the big awakenings that you can write a pretty convincing sports story from stats alone without needing to have watched the game. So, you know, is it possible to write lively prose about politics? Yeah, no, not yet. So we were sort of all over the map. One of the, one of the things about chess that you'll, there's a question I once asked on Cora that didn't get a lot of response, which was, what is the greatest brilliancy ever produced by a computer in a chess game, which was different than the question of what is the greatest game ever played. So if you think about brilliancies is what really animates many of us to think of chess as an art form. Those are those moves and combinations that just show such flair panache and soul. Computers weren't really great at that. They were great positional monsters. And, you know, recently we've started seeing brilliancies. And so. If your grandmasters have identified with alpha zero, that things were quite brilliant. Yeah. So that's, you know, that's an example of something. We don't think that that's AGI, but in a very restricted set, a set of rules like chess, you're starting to see poetry of a high order. And, and so I'm not, I don't like the idea that we're waiting for AGI. AGI is sort of slowly infiltrating our lives in the same way that I don't think a worm should be, you know, the C elegans shouldn't be treated as non-conscious because it only has 300 neurons. It maybe just has a very low level of consciousness because we don't understand what these things mean as they scale up. So am I worried about this general phenomena? Sure. But I think that one of the things that's happening is that a lot of us are fretting about this in part because of human needs. We've always been worried about the Golem, right? Well, the Golem is the artificially created life, you know, it's like Frankenstein. Yeah, sure. Character. It's a Jewish version and Frankenberg, Frankenstein. Yeah, that's makes sense. Right. So the, but we've always been worried about creating something like this and it's getting closer and closer and there are ways in which we have to realize that the whole thing is kind of the whole thing that we've experienced are the context of our lives is almost certainly coming to an end. And I don't mean to suggest that we won't survive. I don't know. And I don't mean to suggest that it's coming tomorrow. It could be 300, 500 years, but there's no plan that I'm aware of. If we have three rocks that we could possibly inhabit that are sensible within current technological dreams, the earth, the moon and Mars, and we have a very competitive civilization that is still forced into violence to sort out disputes that cannot be arbitrated. It is not clear to me that we have a long-term future until we get to the next stage, which is to figure out whether or not the Einsteinian speed limit can be broken. And that requires our source code. Our source code, the stuff in our brains to figure out what do you mean by our source code? The source code of the context, whatever it is that produces the quarks, the electrons, the neutrinos. Oh, our source code. I got it. So this is. You're talking about stuff that's written in a higher level language. Yeah, yeah, that's right. You're talking about the low level bits. Right. That's what is currently keeping us here. We can't even imagine, you know, we have harebrained schemes for staying within the Einsteinian speed limit. You know, maybe if we could just drug ourselves and go into a suspended state or we could have multiple generations of that. I think all that stuff is pretty silly, but I think it's also pretty silly to imagine that our wisdom is going to increase to the point that we can have the toys we have and we're not going to use them for 500 years. Speaking of Einstein, I had a profound breakthrough when I realized you're just one letter away from the guy. Yeah, but I'm also one letter away from Feinstein. It's well, you get to pick. Okay, so unified theory, you know, you've worked, you enjoy the beauty of geometry. Well, I don't actually know if you enjoy it. You certainly are quite good at it. I tremble before it. Tremble before it. If you're religious, that is one of the. I don't have to be religious. It's just so beautiful. You will tremble anyway. I mean, I just read Einstein's biography and one of the ways, one of the things you've done is try to explore a unified theory talking about a 14 dimensional observers that has the 4D space time continuum embedded in it. I'm just curious how you think and how philosophically at a high level about something more than four dimensions. How do you try to, what does it make you feel talking in the mathematical world about dimensions that are greater than the ones we can perceive? Is there something that you take away that's more than just the math? Well, first of all, stick out your tongue at me. Stick out your tongue at me. There was a sweet receptor and next to that were salt receptors and two different sides, a little bit farther back. There were sour receptors and you wouldn't show me the back of your tongue where your bitter receptor was. Show the good side always. Okay. That was four dimensions of taste receptors, but you also had pain receptors on that tongue and probably heat receptors on that tongue. So let's assume that you had one of each. That would be six dimensions. So when you eat something, you eat a slice of pizza and it's got some hot pepper on it, maybe some jalapeno. You're having a six dimensional experience, dude. Do you think we overemphasize the value of time as one of the dimensions or space? Well, we certainly overemphasize the value of time because we like things to start and end or we really don't like things to end, but they seem to. Well, what if you flipped one of the spatial dimensions into being a temporal dimension and you and I were to meet in New York City and say, well, where and when should we meet? Say, how about I'll meet you on 36th and Lexington at two in the afternoon and 11 o'clock in the morning? That would be very confusing. Well, so it's convenient for us to think about time, you mean? We happen to be in a delicious situation in which we have three dimensions of space and one of time and they're woven together in this sort of strange fabric where we can trade off a little space for a little time, but we still only have one dimension that is picked out relative to the other three. It's very much Gladys Knight and the Pips. So which one developed for who? Do we develop for these dimensions or did the dimensions or were they always there and it doesn't? Well, do you imagine that there isn't a place where there are four temporal dimensions or two and two of space and time or three of time and one of space? And then would time not be playing the role of space? Why do you imagine that the sector that you're in is all that there is? I certainly do not, but I can't imagine otherwise. I mean, I haven't done ayahuasca or any of those drugs that hope to one day, but doing ayahuasca, you could just head over to building two. That's where the mathematicians are. That's where they hang just to look at some geometry. We'll just ask about pseudo-Romanian geometry. That's what you're interested in. Okay, or you could talk to a shaman and end up in Peru. And then it's an extra money for that. You won't be able to do any calculations if that's how you choose to go about it. Well, a different kind of calculation, so to speak. Yeah, one of my favorite people, Edward Frankel, Berkeley professor, author of Love and Math, great title for a book, said that you were quite a remarkable intellect to come up with such beautiful original ideas in terms of unified theory and so on, but you were working outside academia. So one question in developing ideas that are truly original, truly interesting, what's the difference between inside academia and outside academia? When it comes to developing such ideas. Oh, it's a terrible choice. Terrible choice. So if you do it inside of academics, you are forced to constantly show great loyalty to the consensus and you distinguish yourself with small, almost microscopic heresies to make your reputation in general, and you have very competent people and brilliant people who are working together, who are, who form very deep social networks and have a very high level of behavior, at least within mathematics and at least technically within physics, theoretical physics. When you go outside, you meet lunatics and crazy people, madmen. And these are people who do not usually subscribe to the consensus position and almost always lose their way. And the key question is, will progress likely come from someone who is miraculously managed to stay within the system and is able to take on a larger amount of heresy that is sort of unthinkable, in which case that will be fascinating. Or is it more likely that somebody will maintain a level of discipline from outside of academics and be able to make use of the freedom that comes from not having to constantly affirm your loyalty to the consensus of your field? So you've characterized in ways that academia in this particular sense is declining. You posted a plot, the older population of the faculty is getting larger, the younger is getting smaller and so on. So which direction of the two are you more hopeful about? Well, the baby boomers can't hang on forever. First of all, in general true, and second of all, in academia. But that's really what this time is about. Is the baby boomers. We didn't, we're used to like financial bubbles that last a few years in length and then pop. The baby boomer bubble is this really long lived thing. And all of the ideology, all of the behavior patterns, the norms, for example, string theory is an almost entirely baby boomer phenomena. It was something that baby boomers were able to do because it required a very high level of mathematical ability. So you don't think of string theory as an original idea? Oh, I mean, it was original to Veneziano, probably is older than the baby boomers. And there are people who are younger than the baby boomers who are still doing string theory. And I'm not saying that nothing discovered within the large string theoretic complex is wrong. Quite the contrary, a lot of brilliant mathematics and a lot of the structure of physics was elucidated by string theorists. What do I think of the deliverable nature of this product that will not ship called string theory? I think that it is largely an affirmative action program for highly mathematically and geometrically talented baby boomer physics physicists so that they can say that they're working on something within the constraints of what they will say is quantum gravity. Now, there are other schemes, you know, there's like asymptotic safety. There are other things that you could imagine doing. I don't think much of any of the major programs, but to have inflicted this level of loyalty through a shibboleth. Well, surely you don't question X. Well, I question almost everything in the string program, and that's why I got out of physics. When you called me a physicist, it was a great honor. But the reason I didn't become a physicist wasn't that I fell in love with mathematics as I said, wow, in 1984, 1983, I saw the field going mad and I saw that mathematics, which has all sorts of problems, was not going insane. And so instead of studying things within physics, I thought it was much safer to study the same objects within mathematics. There's a huge price to pay for that. You lose physical intuition. But the point is that it wasn't a North Korean re-education camp either. Lex Dyson Are you hopeful about cracking open the Einstein unified theory in a way that has been really, really understanding whether this uniting everything together with quantum theory and so on? I mean, I'm trying to play this role myself to do it to the extent of handing it over to the more responsible, more professional, more competent community. So I think that they're wrong about a great number of their belief structures. But I do believe, I mean, I have a really profound love hate relationship with this group of people. Lex Dyson On the physics side. Oh, yeah. Because the mathematicians actually seem to be much more open-minded and. Well, they are and they aren't. They're open-minded about anything that looks like great math, right? They'll study something that isn't very important physics. But if it's beautiful mathematics, then they'll have, they have great intuition about these things. As good as the mathematicians are, and I might even intellectually at some horsepower level, give them the edge. The theoretical physics community is bar none the most profound intellectual community that we have ever created. It is the number one. There is nobody in second place as far as I'm concerned. Look in their spare time, in the spare time they invented molecular biology. Lex Dyson What was the origin of molecular biology? You're saying physics? Well, something like Francis Crick. I mean, a lot of the early molecular biologists. Lex Dyson Were physicists? Yeah. I mean, Schrodinger wrote, what is life? And that was highly inspirational. I mean, you have to appreciate that there is no community like the basic research community in theoretical physics. And it's not something I'm highly critical of these guys. I think that they would just wasted the decades of time with a near religious devotion to their misconception of where the problems were in physics. But this has been the greatest intellectual collapse ever witnessed within academics. Lex Dyson You see it as a collapse or just a lull? Peter T. Leeson Oh, I'm terrified that we're about to lose the vitality. We can't afford to pay these people. We can't afford to give them an accelerator just to play with in case they find something at the next energy level. These people created our economy. They gave us the Rad Lab and radar. They gave us two atomic devices to end World War II. They created the semiconductor and the transistor to power our economy through Moore's law. As a positive externality of particle accelerators, they created the World Wide Web. And we have the insolence to say, why should we fund you with our taxpayer dollars? No. The question is, are you enjoying your physics dollars? These guys signed the world's worst licensing agreement. And if they simply charged for every time you used a transistor or a URL or enjoyed the peace that they have provided during this period of time through the terrible weapons that they developed, or your communications devices, all of the things that power our economy, I really think came out of physics, even to the extent that chemistry came out of physics. And molecular biology came out of physics. So first of all, you have to know that I'm very critical of this community. Second of all, it is our most important community. We have neglected it. We've abused it. We don't take it seriously. We don't even care to get them to rehab after a couple of generations of failure. Right. No one. I think the youngest person to have really contributed to the standard model of theoretical level was born in 1936. Theoretical level was born in 1951. Right. Frank Wilczek. And almost nothing has happened that in theoretical physics after 1973, 74, that sent somebody to Stockholm for theoretical development, the predicted experiment. So we have to understand that we are doing this to ourselves. Now, with that said, these guys have behaved abysmally, in my opinion, because they haven't owned up to where they actually are, what problems they're really facing, how definite they can actually be. They haven't shared some of their most brilliant discoveries, which are desperately needed in other fields like gauge theory, which at least the mathematicians can share, which is an upgrade of the differential calculus of Newton and Leibniz. And they haven't shared the importance of renormalization theory, even though this should be standard operating procedure for people across the sciences dealing with different layers and different levels of phenomena. And by shared, you mean communicated in such a way that it disseminates throughout the different sciences. These guys are sitting, both theoretical physicists and mathematicians are sitting on top of a giant stockpile of intellectual gold. Right. They have so many things that have not been manifested anywhere. I was just on Twitter, I think I mentioned the Habermann switch pitch that shows the self-duality of the tetrahedron realized as a linkage mechanism. Now, this is like a triviality and it makes an amazing toy that's built a market, hopefully a fortune for Chuck Habermann. Well, you have no idea how much great stuff that these priests have in their monastery. So it's truly a love and hate relationship for you. Yeah. Well, it sounds like it's more on the love side. This building that we're in right here is the building in which I really put together the conspiracy between the National Academy of Sciences and the National Science Foundation through the government university industry research round table to destroy the bargaining power of American academics using foreign labor on microfiche in the base. Oh yeah. That was done here in this building. Isn't that weird? And I'm truly speaking with a revolutionary and a radical. No, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, no, at an intellectual level, I am absolutely garden variety. I'm just straight down the middle. The system that we are in this, this university is functionally insane. Harvard is functionally insane. And we don't understand that when we get these things wrong, the financial crisis made this very clear. There was a long period where every grownup, everybody with a tie who spoke in, you know, in baritone tones with the right degree at the end of their name, which was talking about how we banished volunteer volatility. We were in the great moderation. Okay. They were all crazy. And who was, who was right? It was like Nassim Taleb, right. Nouriel Roubini. Now what happens is, is that they claimed the market went crazy. But the market didn't go crazy. The market had been crazy. And what happened is, is that it suddenly went sane. Well, that's where we are with academics. Academics right now is mad as a hatter. And it's, it's absolutely evident. I can show you graph after graph. I can show you the internal discussions. I can show you the conspiracies. Harvard's dealing with one right now over its admissions policies for people of color who happened to come from Asia. All of this madness is necessary to keep the game going. What we're talking about, just, we're all around the topic of revolutionaries, is we're talking about the danger of an outbreak of sanity. Yeah. You're, you're the guy pointing out the elephant in the room here. And the elephant has no clothes. Is that how that goes? I was going to talk a little bit to Joe Rogan about this. We ran out of time. But I think you're, you have some, you, just listening to you, you could probably speak really eloquently to academia on the difference between the different fields. So you think there's a difference between science, engineering, and then the humanities in academia in terms of tolerance that they're willing to tolerate? So from my perspective, I thought computer science and maybe engineering is more tolerant to radical ideas. But that's perhaps innocent of me because I always, you know, all the battles going on now are a little bit more on the humanity side and gender studies and so on. Have you seen the American Mathematical Society's publication of an essay called Get Out the Way? I have not. What's the idea? The idea is that white men who hold positions within universities and mathematics should vacate their positions so that young black women can be able to get out of the way. And black women can take over something like this. That's in terms of diversity, which I also want to ask you about. But in terms of diversity of strictly ideas, do you think, because you're basically saying physics as a community has become a little bit intolerant to some degree to new radical ideas. Or at least you said that's changed a little bit recently, which is that even string theory is now admitting, OK, we don't look very promising in the short term. Right. So the question is what compiles, if you want to take the computer science metaphor, what will get you into a journal? Will you spend your life trying to push some paper into a journal or will it be accepted easily? What do we know about the characteristics of the submitter? And what gets taken up and what does not? All of these fields are experiencing pressure because no field is performing so brilliantly well that it's revolutionizing our way of speaking and thinking in the ways in which we've become accustomed. But don't you think even in theoretical physics, a lot of times, even with theories like string theory, you could speak to this, it does eventually lead to what are the ways that this theory would be testable? Yeah, ultimately, although, look, there's this thing about Popper and the scientific method that's a cancer and a disease in the minds of very smart people. That's not really how most of the stuff gets worked out. It's how it gets checked. Right. So there is a dialogue between theory and experiment. But everybody should read Paul Dirac's 1963 American, Scientific American article where he, you know, it's very interesting. He talks about it as if it was about the Schrodinger equation and Schrodinger's failure to advance his own work because of his failure to account for some phenomenon. The key point is that if your theory is a slight bit off, it won't agree with experiment, but it doesn't mean that the theory is actually wrong. But Dirac could as easily have been talking about his own equation in which he predicted that the electrons should have an antiparticle. And since the only positively charged particle that was known at the time was the proton, Heisenberg pointed out, well, shouldn't your antiparticle, the proton have the same mass as the electron? And doesn't that invalidate your theory? So I think that Dirac was actually being quite, potentially quite sneaky and talking about the fact that he had been pushed off of his own theory to some extent by Heisenberg. But look, we fetishized the scientific method and popper and falsification because it protects us from crazy ideas entering the field. So, you know, it's a question of balancing type one and type two error. And we're pretty, we were pretty maxed out in one direction. Luke Stevenson The opposite of that, let me say what comforts me sort of biology or engineering at the end of the day, does the thing work? Paul A You can test the crazies away. The crazy, well, see now you're saying, but some ideas are truly crazy and some are actually correct. Luke Stevenson So there's pre-correct, currently crazy. Paul A Yeah. Luke Stevenson Right. And so you don't want to get rid of everybody who's pre-correct and currently crazy. The problem is, is that we don't have standards in general for trying to determine who has to be put to the sword in terms of their career and who has to be protected as some sort of giant time suck pain in the ass who may change everything. Paul A Do you think that's possible, creating a mechanism of those select? Luke Stevenson Well, you're not going to like the answer, but here it comes. Paul A Oh, boy. Luke Stevenson It has to do with very human elements. We're trying to do this at the level of like rules and fairness. It's not going to work. Because the only thing that really understands this, you ever read the double helix? Paul A It's a book. Luke Stevenson Oh, you have to read this book. Not only did Jim Watson half discover this three dimensional structure of DNA, he was also one hell of a writer before he became an ass. That no, he's tried to destroy his own reputation. Paul A I knew about the ass. I didn't know about the good writer. Luke Stevenson Jim Watson is one of the most important people now living. And as I've said before, Jim Watson is too important a legacy to be left to Jim Watson. That book tells you more about what actually moves the dial. And there's another story about him, which I don't agree with, which is that he stole everything from Rosalind Franklin. I mean, the problems that he had with Rosalind Franklin are real, but we should actually honor that tension in our history by delving into it rather than having a simple solution. Jim Watson talks about Francis Crick being a pain in the ass that everybody secretly knew was super brilliant. And there's an encounter between Chargaff, who came up with the equimolar relations between the nucleotides, who should have gotten the structure of DNA and Watson and Crick. And, you know, he's talks about missing a shiver in the heartbeat of biology and stuff is so gorgeous. It just makes you tremble even thinking about it. Look, we know very often who is to be feared and we need to fund the people that we fear. The people who are wasting our time need to be excluded from the conversation. You see, and maybe we'll make some errors in both directions, but we have known our own people. We know the pains in the asses that might work out. And we know the people who are really just blowhards who really have very little to contribute most of the time. It's not 100%, but you're not going to get there with rules. Right. It's using some kind of instinct. I mean, to be honest, I'm going to make you roll your eyes for a second. But the first time I heard that there is a large community of people who believe the earth is flat actually made me pause and ask myself the question. Why would there be such a community? Yeah. Is it possible the earth is flat? So I had to like, wait a minute. I mean, then you go through a thinking process that I think is really healthy. It ultimately ends up being a geometry thing. I think it's an interesting thought experiment at the very least. Well, I do a different version of it. I say, why is this community stable? Yeah. That's a good way to analyze it. Well, interesting that whatever we've done has not erased the community. So, you know, they're taking a long shot bet that won't pan out. You know, maybe we just haven't thought enough about the rationality of the square root of two and somebody brilliant will figure it out. Maybe we will eventually land one day on the surface of Jupiter and explore it. Right. These are crazy things that will never happen. So much of social media operates by AI algorithms. You talked about this a little bit recommending the content you see. So on this idea of radical thought, how much should AI show you things you disagree with on Twitter and so on in a Twitter verse in the internet? I hate this question. Yeah. Yeah. Because you don't know the answer. No, no, no, no. Look, we've been, they've pushed out this cognitive Lego to us that will just lead to madness. It's good to be challenged with things that you disagree with. The answer is no, it's good to be challenged with interesting things with which you currently disagree, but that might be true. So I don't really care about whether or not I disagree with something or don't disagree. I need to know why that particular disagreeable thing is being pushed out. Is it because it's likely to be true? Is it because, is there some reason? Because I can write a computer generator to come up with an infinite number of disagreeable statements that nobody needs to look at. So please, before you push things at me that are disagreeable, tell me why. There is an aspect in which that question is quite dumb, especially because it's being used to almost very generically by these different networks to say, well, we're trying to work this out. But basically, how much do you see the value of seeing things you don't like, not you disagree with, because it's very difficult to know exactly what you articulated, which is the stuff that's important for you to consider that you disagree with. That's really hard to figure out. The bottom line is the stuff you don't like. If you're a Hillary Clinton supporter, you may not want to, it might not make you feel good to see anything about Donald Trump. That's the only thing algorithms can really optimize for currently. They really can't. No, they can do better. You think so? No, we're engaged in some moronic back and forth where I have no idea why people who are capable of building Google, Facebook, Twitter are having us in these incredibly low level discussions. Do they not know any smart people? Do they not have the phone numbers of people who can elevate these discussions? They do, but they're optimizing for a different thing and they're pushing those people out of those rooms. They're optimizing for things we can't see. And yes, profit is there. Nobody's questioning that. But they're also optimizing for things like political control or the fact that they're doing business in Pakistan. And so they don't want to talk about all the things that they're going to be bending to in Pakistan. So we're involved in a fake discussion. You think so? You think these conversations at that depth, they're happening inside Google. You don't think they have some basic metrics under user engagements? You're having a fake conversation with us, guys. We know you're having a fake conversation. I do not wish to be part of your fake conversation. You know how to cool these units. You know high availability like nobody's business. My Gmail never goes down, almost. So you think just because they can do incredible work on the software side with infrastructure, they can also deal with some of these difficult questions about human behavior, human understanding, human... You're not. You're not. I mean, I've seen the developers' screens that people have. I've seen the developers' screens that people take shots of inside of Google. And I've heard stories inside of Facebook and Apple. We're not... We're engaged. They're engaging us in the wrong conversations. We are not at this low level. Here's one of my favorite questions. Why is every piece of hardware that I purchase in tech space equipped as a listening device? Where's my physical shutter to cover my lens? We had this in the 1970s. The cameras that had lens caps, you know, how much would it cost to have a security model? Pay five extra bucks. Why is my indicator light software controlled? Why, when my camera is on, do I not see that the light is on by putting it as something that cannot be bypassed? Why have you set up all my devices at some difficulty to yourselves as listening devices? And we don't even talk about this. This thing is total fucking bullshit. Well, I hope... Wait, wait, wait. These discussions are happening about privacy. Is there a more difficult thing you're giving credit for? It's not just privacy. Yeah. It's about social control. We're talking about social control. Why do I not have controls over my own levers? Just have a really cute UI where I can switch, I can dial things, or I can at least see what the algorithms are. But you think that there is some deliberate choices being made here. There's emergence and there is intention. There are two dimensions. The vector does not collapse onto either axis. But the idea that anybody who suggests that intention is completely absent is a child. That's really beautifully put. And like many things you've said is going to make me... Can I turn this around slightly? Yeah. I sit down with you and you say that you're obsessed with my feed. I don't even know what my feed is. What are you seeing that I'm not? I was obsessively looking through your feed on Twitter because it was really enjoyable because there's the Tom Lehrer element, there's the humor in it. By the way, that feed is Eric R. Weinstein on Twitter. Eric R. Weinstein. Yeah. Seriously, why? Why did I find it enjoyable or what was I seeing? What are you looking for? Why are we doing this? What is this podcast about? I know you've got all these interesting people. I'm just some guy who's sort of a podcast guest. Sort of a podcast. You're not even wearing a tie. I mean, it's not even a serious interview. I'm not even wearing a tie. I'm searching for meaning, for happiness, for a dopamine rush, so short-term and long-term. And how are you finding your way to me? What is it? I don't honestly know what I'm doing to reach you. What I'm doing to reach you? Representing ideas which feel common sense to me and not many people are speaking. So it's kind of like the intellectual dark web folks, right? These folks, from Sam Harris to Jordan Peterson to yourself, are saying things where it's like, you're saying, look, there's an elephant. He's not wearing any clothes. And I say, yeah, yeah, let's have more of that conversation. That's how I'm finding you. I'm desperate to try to change the conversation we're having. I'm very worried we've got an election in 2020. I don't think we can afford four more years of a misinterpreted message, which is what Donald Trump was. And I don't want the destruction of our institutions. They all seem hell-bent on destroying themselves. So I'm trying to save theoretical physics. Trying to save the New York Times, trying to save our various processes. And I think it feels delusional to me that this is falling to a tiny group of people who are willing to speak out without getting so freaked out that everything they say will be misinterpreted and that their lives will be ruined through the process. I mean, I think we're in an absolutely bananas period of time, and I don't believe it should fall to such a tiny number of shoulders to shoulder this way. So I have to ask you, on the capitalism side, you mentioned that technology is killing capitalism, or it has effects that are not unintended, but not what economists would predict or speak of capitalism creating. I just want to talk to you about, in general, the effect of even then artificial intelligence or technology automation taking away jobs and these kinds of things, and what you think is the way to alleviate that, whether the Andrew Yang presidential candidate with universal basic income, UBI, what are your thoughts there? How do we fight off the negative effects of technology that- All right, you're a software guy, right? Yep. A human being is a worker, is an old idea. Yes. A human being has a worker, is a different object, right? Yes. So if you think about object-oriented programming, it's a different thing. It's a different concept, right? So if you think about object-oriented programming as a paradigm, a human being has a worker and a human being has a soul. We're talking about the fact that for a period of time, the worker that a human being has was in a position to feed the soul that a human being has. However, we have two separate claims on the value in society. One is as a worker and the other is as a soul, and the soul needs sustenance, it needs dignity, it needs meaning, it needs purpose. As long as your means of support is not highly repetitive, I think you have a while to go before you need to start worrying. But if what you do is highly repetitive and it's not terribly generative, you are in the crosshairs of for loops and while loops, and that's what computers excel at. Repetitive behavior, and when I say repetitive, I may mean things that have never happened through combinatorial possibilities, but as long as it has a looped characteristic to it, you're in trouble. We are seeing a massive push towards socialism because capitalists are slow to address the fact that a worker may not be able to make claims. A relatively undistinguished median member of our society still has needs to reproduce, needs to dignity, and when capitalism abandons the median individual or the bottom 10th or whatever it's going to do, it's flirting with revolution. And what concerns me is that the capitalists aren't sufficiently capitalistic to understand this. You really want to court authoritarian control in our society because you can't see that people may not be able to defend themselves in the marketplace because the marginal product of their labor is too low to feed their dignity as a soul. So my great concern is that our free society has to do with the fact that we are self-organized. I remember looking down from my office in Manhattan when Lehman Brothers collapsed and thinking, who's going to tell all these people that they need to show up at work when they don't have a financial system to incentivize them to show up at work? So my complaint is first of all, not with the socialists, but with the capitalists, which is you guys are being idiots. You're courting revolution by continuing to harp on the same old ideas that, well, you know, try harder, bootstrap yourself. Yeah, to an extent that works, to an extent. But we are clearly headed in a place that there's nothing that ties together our need to contribute and our need to consume. And that may not be provided by capitalism because it may have been a temporary phenomena. So check out my article on anthropic capitalism and the new gimmick economy. I think people are late getting the wake up call and we would be doing a better job saving capitalism from itself because I don't want this done under authoritarian control. And the more we insist that everybody who's not thriving in our society during their reproductive years in order to have a family is failing at a personal level. I mean, what a disgusting thing that we're saying. What a horrible message. Who the hell have we become that we've so bought into the Chicago model that we can't see the humanity that we're destroying in that process? And it's, I hate, I hate the thought of communism. I really do. My family has flirted with it decades past. It's a wrong, bad idea, but we are going to need to figure out how to make sure that those souls are nourished and respected and capitalism better have an answer. And I'm betting on capitalism, but I got to tell you, I'm pretty disappointed with my team. So you're still on the capitalism team. You just, uh, there's a theme here. Radical, radical capital, hyper capitalism. I want, I think hyper capitalism is going to have to be coupled to hyper socialism. You need to allow the most productive people to create wonders and you've got to stop bogging them down with all of these extra nice requirements. You know, nice is dead. Good has a future. Nice doesn't have a future because nice ends up with, with gulags. Damn, that's a good line. Okay. Last question. You tweeted today a simple, quite insightful equation saying, uh, imagine that every unit F of fame you picked up as stalkers and H haters. So I imagine S and H are dependent on your path to fame perhaps a little bit. Well, it's not as simple. I mean, people always take these things literally when you have like 280 characters to explain yourself. So you mean that that's not a mathematical, uh, no, there's no law. Okay. All right. So I put the word imagine because I still have a mathematician's desire for precision. Imagine that this were true. But it was a beautiful way to imagine that there is a law that has those variables in it and, uh, you've become quite famous these days. So how do you yourself optimize that equation with the peculiar kind of fame that you have gathered along the way? I want to be kinder. I want to be kinder to myself. I want to be kinder to others. I want to be able to have heart, compassion, or these things are really important. And I have a pretty spectrum-y kind of approach to analysis. I'm quite literal. I can go full Rain Man on you at any given moment. No, I can, I can. It's faculty of autism, if you like, and people are going to get angry because they want autism to be respected. But when you see me coding or you see me doing mathematics, I'm, you know, I speak with speech apnea. Uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh, uh. So I think, you know, we have to try to integrate ourselves and those tensions between, you know, it's sort of back to us as a worker and us as a soul. Many of us are optimizing one to the, at the expense of the other. And I struggle with social media and I struggle with people making threats against our families and I struggle with, um, just how much pain people are in. And if there's one message I would like to push out there, um, you're responsible. Everybody all of us, myself included, was struggling, struggle, struggle mightily because you, it's nobody else's job to do your struggle for you. Now, with that said, if you're struggling and you're trying and you're trying to figure out how to better yourself and where you failed and where you've let down your family, your friends, your workers, all this kind of stuff, give yourself a break. You know, if, if, if it's not working out, I have a lifelong relationship with failure and success. There's been no period of my life where both haven't been present in one form or another. And I do wish to say that a lot of times people think this is glamorous. I'm about to go do a show with Sam Harris. People are going to listen in on two guys having a conversation on stage. It's completely crazy. I'm always trying to figure out how to make sure that those people get maximum value and, and that's why I'm doing this podcast. You know, just give yourself a break. You owe us, you owe us your struggle. You don't owe your family or your coworkers or your lovers or your family members success. As long as you're in there and you're picking yourself up, recognize that this, this new situation with the economy that doesn't have the juice to sustain our institutions has caused the people who've risen to the top of those institutions to get quite brutal and cruel. Everybody is lying at the moment. Nobody's really a truth teller. Try to keep your humanity about you. Try to recognize that if you're failing, if things aren't where you want them to be and you're struggling and you're trying to figure out what you're doing wrong, which you could do, it's not necessarily all your fault. We are in a global situation. I have not met the people who are honest, kind, good, successful. Nobody that I've met is checking all the boxes. Nobody's getting all 10s. So I just think that's an important message that doesn't get pushed out enough. Either people want to hold society responsible for their failures, which is not reasonable. You have to struggle, you have to try. Or they want to say you're 100% responsible for your failures, which is total nonsense. Beautifully put. Eric, thank you so much for talking today. Thanks for having me, buddy.

https://youtu.be/2wq9x2QcZN0

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10 things I'm grateful for this Thanksgiving

Instead of saying some big things I'm grateful for this Thanksgiving, like family, friends, and life itself, let me give a list of seemingly insignificant things that popped into my head. I wrote them down that make me smile or just make me think. I think life is amazing because of such a collection of little things. So I thought it'd be fun to list a few. I'm thankful for the horse, Boxer, in the book Animal Farm by George Orwell, who had the motto, I will work harder, until his very last days. To me there's always been a kind of quiet heroism to the simplicity of that motto in the face of a fundamentally cruel world. I'm also thankful for love songs that are subtle, that look at the mundane, like Wonderful Tonight by Eric Clapton. I think a lot of great love songs are kind of over the top dramatic, and Wonderful Tonight is not. It's just admiring a moment of someone you love being beautiful once again in ways that have been many times before. And beautiful in a way that to me, so this is from my perspective, only a woman can be. Sort of admiring a beautiful dress and how glowing a person looks on a particular night. I'm also thankful for neural networks and deep learning for reigniting the big dream of artificial intelligence for me and I think for much of the world. Neural networks as they are, are probably not enough to achieve super intelligence, but I think the magic that's already there in neural networks, I think will be there in future AGI systems, whatever they end up looking like. Let's see, I'm also thankful for Granny Smith apples for being a source of happiness for me throughout my life, especially on some of the hard weight cuts I had to do for wrestling, for judo, for Jiu Jitsu tournaments. And now that I'm on a keto diet, it's a source of rare cheat meals where I just sneak in carbs. When you're on keto, carbs taste even better and apples is one of my favorite sources of carbs. I also probably have a bit of a love-hate relationship with apples because I don't know how to moderate them. I don't know how to eat just one apple. Okay, I'm also thankful for regular expressions, for being both powerful and painful, giving my sometimes OCD brain a chance to unlock the secret code behind language, if only for a brief moment of some seemingly insignificant task of parsing a file, a data file of some sort. I'm also thankful, as I probably said way too many times, for Mr. Fyodor Dostoevsky and especially for Prince Mishkin or the main character from The Idiot, which is a book by Dostoevsky. I think in particular what I've learned from Prince Mishkin is that loving the world simply is worth whatever trouble such an approach may, let's say, throw your way. Okay, this list is all over the place. I'm also thankful for, in general, the research process that's been part of my life for many years, many painful but glorious years. So the idea of going from the initial idea with colleagues to doing the different kinds of experiments to then writing it up with the elegant typography of LaTeX, submitting it to a conference or a journal, but conference is my favorite, especially in computer science, going through the revisions, and then finally attending the conference and presenting your work and having all the discussions over the work and then spurring on future ideas that you work on. I think the entirety of that process is magical and I've grown a lot from it. I'm truly thankful for having the opportunity to do it. It's one of the reasons I'm maintaining an affiliation and a position at MIT. I have regular conversations with friends and colleagues there, working on two papers currently still, even with all the things that are going on. I have so much love for this process and for MIT in general that I can't let it go. It's a big part of me and MIT is truly a special place. So it's a source of joy and I don't want to let go easily of things that bring me joy, even though so many things in this world do. Okay, I'm thankful for Mr. Dan Carlin's hardcore history and to be specific, the most memorable for me, there's a lot of great episodes, but the one that really got me was Painfultainment, which is a single standalone episode. It's so dark. It's so truly dark that more than the other episodes, I think it truly changed my view of human nature. And as is true with dark episodes of that kind or dark stories or philosophical ideas, it somehow empowered me, gave me more power to forgive my fellow human beings and forgive myself for the flaws that I have. This is a weird one. This list is just terrible. I'm thankful for mathematics and theoretical computer science in general. Speaking of things that bring me a lot of joy, it's just a constant source of unexpected beauty, both in algorithms or theorems. It's just, I don't know why, maybe it's the way my brain is. Maybe it's just human nature is something about the elegant beauty that can be only revealed through numbers is a source of happiness. And I'm thankful for having the brain and the opportunity to experience the beauty that's inherent to me in mathematics. Finally, I'm thankful for vodka, whiskey, and the worst of it, which is tequila for being a catalyst for some wild adventures. Some that I regretted at the time, but now truly can look back at with a big stupid smile on my face. I think that's 10. I gotta say, I appreciate all the love I've gotten over the past couple of years and I send it right back at you, many more fold. Happy Thanksgiving. I hope you have a good one.

https://youtu.be/ipQBP1wRFNM

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Jim Gates: Supersymmetry, String Theory and Proving Einstein Right | Lex Fridman Podcast #60

The following is a conversation with S. James Gates Jr. He's a theoretical physicist and professor at Brown University, working on supersymmetry, supergravity, and superstring theory. He served on former President Obama's Council of Advisors on Science and Technology, and he's now the co-author of a new book titled Proving Einstein Right, about the scientists who set out to prove Einstein's theory of relativity. You may have noticed that I've been speaking with not just computer scientists, but philosophers, mathematicians, physicists, economists, and soon much more. To me, AI is much bigger than deep learning, bigger than computing. It is our civilization's journey into understanding the human mind and creating echoes of it in the machine. That journey includes, of course, the world of theoretical physics and its practice of first principles mathematical thinking and exploring the fundamental nature of our reality. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on Apple Podcasts, follow on Spotify, support on Patreon, or simply connect with me on Twitter, at Lex Friedman, spelled F-R-I-D-M-A-N. If you leave a review on Apple Podcasts or YouTube or Twitter, consider mentioning ideas, people, topics you find interesting. It helps guide the future of this podcast. But in general, I just love comments that are full of kindness and thoughtfulness in them. This podcast is a side project for me, but I still put a lot of effort into it. So the positive words of support from an amazing community, from you, really help. I recently started doing ads at the end of the introduction. I'll do one or two minutes after introducing the episode and never any ads in the middle that can break the flow of the conversation. I hope that works for you and doesn't hurt the listening experience. I provide timestamps for the start of the conversations you may have noticed that you can skip to, but it helps if you listen to the ad and support this podcast by trying out the product or service being advertised. This show is presented by Cash App, the number one finance app in the App Store. I personally use Cash App to send money to friends, but you can also use it to buy, sell, and deposit Bitcoin in just seconds. Cash App also has a new investing feature. You can buy fractions of a stock, say $1 worth, no matter what the stock price is. Brokerage services are provided by Cash App Investing, a subsidiary of Square and member SIPC. I'm excited to be working with Cash App to support one of my favorite organizations called FIRST, best known for their FIRST Robotics and Lego competitions. They educate and inspire hundreds of thousands of students in over 110 countries and have a perfect rating on Charity Navigator, which means the donated money is used to maximum effectiveness. When you get Cash App from the App Store, Google Play, and use code LEXPODCAST, you'll get $10 and Cash App will also donate $10 to FIRST, which again is an organization that I've personally seen inspire girls and boys to dream of engineering a better world. And now here's my conversation with S. James Gates Jr. You tell a story when you were eight. You had a profound realization that the stars in the sky are actually places that we could travel to one day. Do you think human beings will ever venture outside our solar system? Wow, the question of whether humanity gets outside of the solar system, it's going to be a challenge. And as long as the laws of physics that we have today, are accurate and valid, it's going to be extraordinarily difficult. I'm a science fiction fan, as you probably know. So I love to dream of starships and traveling to other solar systems, but the barriers are just formidable. If we just kind of venture a little bit into science fiction, do you think the spaceships, if we are successful, that take us outside the solar system will look like the ones we have today? Or are fundamental breakthroughs necessary? In order to have genuine starships, probably some really radical views about the way the universe works are going to have to take place in our science. We could, with our current technology, think about constructing multi-generational starships where the people who get on them are not the people who get off at the other end. But even if we do that, the formidable problems actually are bodies, which doesn't seem to be conscious for a lot of people. Even getting to Mars is going to present this challenge, because we live in this wonderful home, has a protective magnetic magnetosphere around it. And so we're shielded from cosmic radiation. Once you leave this shield, there are some estimates that, for example, if you sent someone to Mars, with our technology, probably about two years out there without the shield, they're going to be bombarded. That means radiation, probably means cancer. So that's one of the most formidable challenges, even if we could get over the technology. Do you think, so Mars is a harsh place. Elon Musk, SpaceX, and the other big companies, Elon Musk, SpaceX, and other folks, NASA, are really pushing to put a human being on Mars. Do you think, again, forgive me for lingering in science fiction land for a little bit, do you think one day we may be able to colonize Mars? First, do you think we'll put a human on Mars? And then do you think we'll put many humans on Mars? So first of all, I am extraordinarily convinced we will not put a human on Mars by 2030, which is a date that you often hear in the public debate. What's the challenge there? What do you think? So there are a couple of ways that I could slice this, but the one that I think is simplest for people to understand involves money. So you look at how we got to the moon in the 1960s. It was about 10 year duration between the challenge that President Kennedy laid out and our successfully landing a moon. I was actually here at MIT when that first moon landing occurred. So I remember watching it on TV. But how did we get there? Well, we had this extraordinarily technical agency of the United States government, NASA. It consumed about 5% of the country's economic output. And so you say 5% of the economic output over about a 10 year period gets us 250,000 miles in space. Mars is about 100 times farther. So you have at least 100 times the challenge. And we're spending about 1 10th of the funds that we spent then as a government. So my claim is that it's at least 1,000 times harder for me to imagine us getting to Mars by 2030. And he had that part that you mentioned in the speech that I just have to throw in there of JFK, of we do these things not because they're easy, but because they're hard. That's such a beautiful line that I would love to hear a modern president say about a scientific endeavor. Well, one day we live and hope that such a president will arise for our nation. But even if, like I said, even if you fix the technical problems, the biological engineering that I worry most about. However, I'm going to go out on a limb here. I think that by 2090 or so, or 2100, should I say 120, I suspect we're going to have a human on Mars. Wow. So you think that many years out, first a few tangents. You said bioengineering is a challenge. What's the challenge there? So as I said, the real problem with interstellar travel, aside from the technology challenges, the real problem is radiation. And how do you engineer either an environment or a body, because we see rapid advances going on in bioengineering. How do you engineer either a ship or a body so that something, some person that's recognizably human will survive the rigors of interplanetary space travel? It's much more difficult than most people seem to take into account. So if we could linger on the 2090, 2100, 2120, sort of thinking of that kind of, you know, and let's linger on money. Okay. So Elon Musk and Jeff Bezos are pushing the cost, trying to push the cost down. I mean, this is, so do you have hope, as this actually a sort of a brilliant big picture scientist, do you think a business entrepreneur can take science and make it cheaper and get it out there faster? So bending the cost curve, you'll notice that has been an anchor. This is the simplest way for me to discuss this with people about what the challenge is. So yes, bending the cost curve is certainly critical if we're going to be successful. Now you ask about the endeavors that are out there now, sponsored by two very prominent American citizens, Jeff Bezos and Elon Musk. I'm disappointed actually in what I see in terms of the routes that are being pursued. So let me give you one example there. And this one is going to be a little bit more technical. So if you look at the kinds of rockets that both these organizations are creating, yes, it's wonderful, reusable technology to see a rocket go up and land on its fins, just like it did in science fiction movies when I was a kid. That's astounding. But the real problem is those rockets, the technology that we're doing now is not really that different than what was used to go to the moon. And there are alternatives, it turns out. There's an engine called a flare engine, which, so a traditional rocket, if you look at the engine, it looks like a bell, right? And then the flame comes out the bottom. But there is a kind of engine called a flare engine, which is essentially, when you look at it, it looks like an exhaust pipe on like a fancy car that's long and elongated. And it's a type of rocket engine that we know, we know if there's been preliminary testing, we know it works. And it also is actually much more economical because what it does is allow you to vary the amount of thrust as you go up in a way that you cannot do with one of these bell-shaped engines. So you would think that an entrepreneur might try to have the breakthrough to use flare nozzles, as they're called, as a way to bend the cost curve. Because as we keep coming back, that's going to be a big factor. But that's not happening. In fact, what we see is what I think of as incremental change in terms of our technology. So I'm not really very encouraged by what I personally see. So incremental change won't bend the cost curve. I don't see it. Just linger on the sci-fi for one more question. Sure. Do you think we're alone in the universe? Are we the only intelligent form of life? So there is a quote by Carl Sagan, which I really love when I hear this question. And I recall the quote, and it goes something like, if we're the only conscious life in the universe, it's a terrible waste of space. Because the universe is an incredibly big place. And when Carl made that statement, we didn't know about the profusion of planets that are out there. In the last decade, we've discovered over a thousand planets. And a substantial number of those planets are Earth-like in terms of being in the Goldilocks zone, as it's called. So in my mind, it's practically inconceivable that we're the only conscious form of life in the universe. But that doesn't mean they've come to visit us. Do you think they would look, do you think we'll recognize alien life if we saw it? Do you think it'd look anything like the carbon-based, the biological system we have on Earth today? It would depend on that life's native environment in which it arose. If that environment was sufficiently like our environment. There's a principle in biology and nature called convergence, which is that even if you have two biological systems that are totally separated from each other, if they face similar conditions, they tend to, nature will tend to converge on solutions. And so there might be similarities if this alien life form was born in a place that's kind of like this place. Physics appears to be quite similar, the laws of physics across the entirety of the universe. Do you think weirder things than we see on Earth can spring up out of the same kinds of laws of physics? From the laws of physics, I would say yes. First of all, if you look at carbon-based life, why are we carbon-based? Well, it turns out it's because of the way that carbon interacts with elements, which in fact is also a reflection on the electronic structure of the carbon nucleus. So you can look down the table of elements and say, well, gee, do we see similar elements? The answer is yes. And one that one often hears about in science fiction is silicon. So maybe there's a silicon-based life form out there if the conditions are right. But I think it's presumptuous of us to think that we are the template by which all life has to appear. Before we dive into beautiful details, let me ask a big question. What to you is the most beautiful idea, maybe the most surprising, mysterious idea in physics? The most surprising idea to me is that we can actually do physics. The universe did not have to be constructed in such a way that our, with our limited intellectual capacity, that is actually put together in such a way and that we are put together in such a way that we can, with our mind's eye, delve incredibly deeply into the structure of the universe. That to me is pretty close to a miracle. So there's simple equations, relatively simple, that can describe things, you know, the fundamental functions, that can describe everything about our reality. That's not, can you imagine universes where everything is a lot more complicated? Do you think there's something inherent about universes that simple laws are… Well, first of all, let me, this is a question that I encounter in a number of guides is, a lot of people will raise the question about whether mathematics is the language of the universe. And my response is, mathematics is the language that we humans are capable of using in describing the universe. It may have little to do with the universe, but in terms of our capacity, it's the microscope, it's the telescope through which we, it's the lens through which we are able to view the universe with the precision that no other human language allows. So could there be other universes? Well, I don't even know if this one looks like I think it does. But the beautiful, surprising thing is that physics, there are laws of physics, very few laws of physics, that can effectively compress down the functioning of the universe. Yes, that's extraordinarily surprising. I like to use the analogy with computers and information technology. If you worry about transmitting large bundles of data, one of the things that computer scientists do for us is they allow for processes that are called compression, where you take big packets of data and you press them down into much smaller packets, and then you transmit those and then unpack them at the other end. And so, it looks a little bit to me like the universe has kind of done us a favor. It's constructed our minds in such a way that we have this thing called mathematics, which then as we look at the universe teaches us how to carry out the compression process. A quick question about compression. Do you think the human mind can be compressed? The biology can be compressed. We talked about space travel. To be able to compress the information that captures some large percent of what it means to be me or you, and then be able to send that at the speed of light. Wow, that's a big question. And let me try to take it apart, unpack it into several pieces. I don't believe that wetware biology such as we are has an exclusive patent on intellectual consciousness. I suspect that other structures in the universe are perfectly capable of producing the data streams that we use to process, first of all, our observations of the universe and an awareness of ourself. I can imagine other structures can do that also. So, that's part of what you were talking about, which I would have some disagreement with. Consciousness. Yes. What's the most interesting part of- Consciousness? Of us humans? Is consciousness the thing- I think that's the most interesting thing about humans. And then you're saying that there's other entities throughout the universe. I can well imagine that the architecture that supports our consciousness, again, has no patent on consciousness. Just in case you have an interesting thought here, there's folks perhaps in philosophy called panpsychics that believe consciousness underlies everything. It is one of the fundamental laws of the universe. Do you have a sense that that could possibly fit into physics? I don't know the answer to that question. One part of that belief system is Gia, which is that there's a kind of conscious life force about our planet. And I've encountered these things before. I don't quite know what to make of them. I, my own life experience, and I'll be 69 in about two months, and I have spent all my adulthood thinking about the way that mathematics interacts with nature and with us to try to understand nature. And all I can tell you from all of my integrated experience is that there is something extraordinarily mysterious to me about our universe. This is something that Einstein said from his life experience as a scientist. And this mysteriousness almost feels like the universe is our parent. It's a very strange thing perhaps to hear a scientist say, but there are just so many strange coincidences that you just get a sense that something is going on. Lex Moffat Well, I interrupted you in terms of compressing what we're down to a consent at the speed of light. Darrell Bock Yes. So, the first thing is, I would argue that it's probably very likely that artificial intelligence ultimately will develop something like consciousness, something that for us would probably be indistinguishable from consciousness. So, that's what I meant by our biological processing equipment that we carry up here probably does not hold a patent on consciousness, because it's really about the data streams. I mean, that's, as far as I can tell, that's what we are. We are self-actuating, self-learning data streams. That to me is the most accurate way I can tell you what I've seen in my lifetime about what humans are at the level of consciousness. So, if that's the case, then you just need to have an architecture that supports that information processing. So, let's assume that that's true, that in fact, what we call consciousness is really about a very peculiar kind of data stream. If that's the case, then if you can export that to a piece of hardware, something metal, electronic, what have you, then you certainly will, ultimately that kind of consciousness could get to Mars very quickly. It doesn't have our problems. You can engineer the body. As I said, it's a ship or a body, you engineer one or both. Send it at a speed of light. Well, that one is a more difficult one, because that now goes beyond just a matter of having a data stream. It's now the preservation of the information in the data stream. And so, unless you can build something that's like a super, super, super version of the way the internet works, because most people aren't aware that the internet itself is actually a miracle. It's based on a technology called message packaging. So, if you could exponentiate message packaging in some way to preserve the information that's in the data stream, then maybe your dream becomes true. Can we, you mentioned with artificial intelligence, sort of us human beings not having a monopoly on consciousness. Does the idea of artificial intelligence systems, computational systems, being able to basically replacing us humans, scare you, excite you? What do you think about that? So, I'm going to tell you about a conversation I once had with Eric Schmidt. I was sitting at a meeting with him and he was a few feet away. And he turned to me and he said something like, you know, Jim, in maybe a decade or so, we're going to have computers that do what you do. And my response was not unless they can dream. Because there's something about the way that we humans actually generate creativity. It's somehow, I get this sense of my lived experience and watching creative people that somehow connected to the irrational parts of what goes on in our head. And dreaming is part of that irrational. So, unless you can build a piece of artificial intelligence that dreams, I have a strong suspicion that you will not get something that will fully be conscious by a definition that I would accept, for example. So, you mentioned dreaming. You've played around with some out there fascinating ideas. How do you think, and we'll start diving into the world of the very small ideas of supersymmetry and all that, in terms of visualization, in terms of how do you think about it? How do you dream of it? How do you come up with ideas in that fascinating, mysterious space? So, in my workspace, which is basically where I am charged with coming up on a mathematical palette with new ideas that will help me understand the structure of nature and hopefully help all of us understand the structure of nature. I've observed several different ways in which my creativity expresses itself. There's one mode which looks pretty normal, which I sort of think of as the Chinese water torture method. Just drop, drop, drop. You get more and more information, and suddenly it all congeals and you get a clear picture. And so, that's a kind of a standard way of working. And I think that's how most people think about the way technical people solve problems. That is kind of you accumulate this body of information, and at a certain point, you synthesize it, and then boom, there's something new. But I've also observed in myself and other scientists that there are other ways that we are creative. And these other ways to me are actually far more powerful. I first personally experienced this when I was a freshman at MIT, over in Baker House, right across the campus. And I was in a calculus course, 1801 is called at MIT. And calculus comes in two different flavors. One of them is called differential calculus. The other is called integral calculus. Differential calculus is the calculus that Newton invented to describe motion. It turns out integral calculus was probably invented about 1700 years earlier by Archimedes, but we didn't know that when I was a freshman. But so, that's what you study as a student. And the differential calculus part of the course was, to me, I wouldn't, how do I say this? It was something that by the drip, drip, drip method, you could sort of figure it out. Now, the integral part of calculus, I could memorize the formula. That was not the formula. That was not the problem. The problem was why, in my own mind, why do these formulae work? And because of that, when I was in the part of the calculus course where we had to do multiple substitutions to solve integrals, I had a lot of difficulty. I was emotionally involved in my education, because this is where I think the passion, emotion comes to. And it caused an emotional crisis that I was having these difficulties understanding the integral part of calculus. The why of it. The why. That's right, the why of it. Not the rote memorization of fact, but the why of it. Why does this work? And so, one night, I was over in my dormitory room in Baker House. I was trying to do a calculus problem set. I was getting nowhere. I got a terrific headache. I went to sleep and had this very strange dream. And when I awakened, I could do three and four substitutions and integrals with relative ease. Now, this to me was an astounding experience, because I had never before in my life understood that one's subconscious is actually capable of being harnessed to do mathematics. I experienced this, and I've experienced this more than once. So, this was just the first time why I remember it so. So, that's why when it comes to like really wickedly tough problems, I think that the kind of creativity that you need to solve them is probably the second variety, which comes somehow from dreaming. Do you think, again, I told you I'm Russian, so we romanticize suffering, but do you think part of that equation is the suffering leading up to that dreaming? So, the suffering is, I am convinced that this kind of creative, this second mode of creativity, as I like to call it, I'm convinced that this second mode of creativity is in fact, that suffering is a kind of crucible that triggers it, because the mind, I think, is struggling to get out of this. And the only way that you can actually get out of this is to actually solve the problem. And even though you're not consciously solving problems, something is going on. And I've talked about to a few other people, and I've heard other similar stories. And so, I guess the way I think about it is it's a little bit like the way that thermonuclear weapons work. I don't know if you know how they work, but a thermonuclear weapon is actually two bombs. There's an atomic bomb, which sort of does a compression, and then you have a fusion bomb that goes off. And somehow that emotional pressure, I think, acts like the first stage of a thermonuclear weapon. That's when we get really big thoughts. The analogy between thermonuclear weapons and the subconscious, the connection there is, at least visually, is kind of interesting. There may be, Freud would have a few things to say. Well, part of it is probably based on my own trajectory through life. My father was in the US Army for 27 years. And so, I started my life out on military basis. And so, a lot of probably the things that wander around in my subconscious are connected to that experience. I apologize for all the tangents, but... Well, you're doing it. But you're encouraging by answering the stupid questions. No, they're not stupid. So, your father was in the Army. What do you think about... Neil deGrasse Tyson recently wrote a book on interlinking the progress of science to sort of the aspirations of our military endeavors and DARPA funding and so on. What do you think about war in general? Do you think we'll always have war? Do you think we'll always have conflict in the world? I'm not sure that we're going to be able to afford to have war always. But strictly financially speaking? No, not in terms of finance, but in terms of consequences. So, if you look at technology today, you can have non-state actors acquire technology, for example, bioterrorism, whose impact is roughly speaking equivalent to what it used to take nations to impart on a population. I think the cost of war is ultimately... I think it's going to work a little bit like the Cold War. We survived 50, 60 years as a species with these weapons that are so terrible that they could have actually ended our form of life on this planet, but it didn't. Why didn't it? Well, it's a very bizarre and interesting thing, but it was called mutually assured destruction. And so, the cost was so great that people eventually figured out that you can't really use these things, which is kind of interesting because if you read the history about the development of nuclear weapons, physicists actually realized this pretty quickly. I think it was maybe Schrodinger who said that these things are not really weapons. They're political implements. They're not weapons because the cost is so high. And if you take that example and spread it out to the kind of technological development we're seeing now outside of nuclear physics, but I picked the example of biology, I could well imagine that there would be material science sorts of equivalents that across a broad front of technology, you take that experience from nuclear weapons. And the picture that I see is that it would be possible to develop technology that are so terrible that you couldn't use them because the costs are too high. And that might cure us. And many people have argued that actually it prevented, nuclear weapons have prevented more military conflict than... It certainly froze the conflict domain. It's interesting that nowadays it was with the removal of the threat of mutually assured destruction that other forces took over in our geopolitics. Do you have worries of existential threats of nuclear weapons or other technologies like artificial intelligence? Do you think we humans will tend to figure out how to not blow ourselves up? I don't know, quite frankly. This is something I've thought about. And I'm not, I mean, so I'm a spectator in the sense that as a scientist, I collect and collate data. So I've been doing that all my life and looking at my species. And it's not clear to me that we are going to avoid a catastrophic self-induced ending. Are you optimistic? Not as a scientist, but as a single specialist? I would say I wouldn't bet against us. Beautifully put. Let's dive into the world of the very small, if we could for a bit. What are the basic particles either experimentally observed or hypothesized by physicists? So as we physicists look at the universe, you can, first of all, there are two big buckets of particles. That is the smallest objects that we are able to currently mathematically conceive and then experimentally verify that these ideas have a sense of accuracy to them. So one of those buckets we call matter. These are things like electrons, things that are like quarks, which are particles that exist inside of protons. And there's a whole family of these things. There are in fact 18 quarks and apparently six electron-like objects that we call leptons. So that's one bucket. The other bucket that we see both in our mathematics as well as in our experimental equipment are what are a set of particles that you can call force carriers. The most familiar force carrier is the photon, the particle of light that allows you to see me. In fact, it's the same object that carries electric repulsion between like charges. From science fiction, we have the object called the graviton, which is talked about a lot in science fiction and Star Trek. But the graviton is also a mathematical object that we physicists have known about essentially since Einstein wrote his theory of general relativity. There are four forces in nature, fundamental forces. There is the gravitational force, its carrier is the graviton. There are three other forces in nature, the electromagnetic force, the strong nuclear force, and the weak nuclear force. And each one of these forces has one or more carriers. The photon is the carrier of the electromagnetic force. The strong nuclear force actually has eight carriers, they're called gluons. And then the weak nuclear force has three carriers, they're called the W plus, W minus, and Z bosons. So those are the things that both in mathematics and in experiments, by the way, the most precise experiments we're ever able, ever as a species able to conduct is about measuring the accuracy of these ideas. And we know that at least to one part in a billion, these ideas are right. So first of all, you've made it sound both elegant and simple, but is it crazy to you that there is force carriers? Like, is that supposed to be a trivial idea to think about? If we think about photons, gluons, that there's four fundamental forces of physics, and then those forces are expressed, there's carriers of those forces. Like, is that a kind of trivial thing? It's not a trivial thing at all. In fact, it was a puzzle for Sir Isaac Newton, because he's the first person to give us basically physics. Before Isaac Newton, physics didn't exist. What did exist was called natural philosophy. So discussions about using the methods of classical philosophy to understand nature, natural philosophy. So the Greeks, we call them scientists, but they were natural philosophers. Physics doesn't get born until Newton writes the Principia. One of the things that puzzled him was how gravity works, because if you read very carefully what he writes, he basically says, and I'm paraphrasing badly, but he basically says that someone who thinks deeply about this subject would find it inconceivable that an object in one place or location can magically reach out and affect another object with nothing intervening. And so it puzzled him. Does it puzzle you? Action at a distance? I mean, not as a physicist. It would, it would, except that I am a physicist, and we have long ago resolved this issue, and the resolution came about through a second-grade physicist. Most people have heard of Newton. Most people have heard of Einstein. But between the two of them, there was another extraordinarily great physicist, a man named James Clark Maxwell. And Maxwell, between these two other giants, taught us about electric and magnetic forces, and it's from his equations that one can figure out that there's a carrier called the photon. So this was resolved for physicists around 1860 or so. So what are bosons and fermions and hadrons? Elementary and composite. Sure. So earlier I said- Two buckets. You've got two buckets if you want to try to build the universe. You've got to start off with things on these two buckets. So you've got to have things, that's the matter, and then you have to have other objects that act on them to cause those things to cohere to fixed finite patterns, because you need those fixed finite patterns as building blocks. So that's the way our universe looks to people like me. Now, the building blocks do different things. So let's go back to these two buckets again. Let me start with a bucket containing the particle of light. Let me imagine I'm in a dusty room with two flashlights, and I have one flashlight which I direct directly in front of me, and then I have you stand over to say my left, and then we both take our flashlights and turn them on and make sure the beams go right through each other. And the beams do just that. They go right through each other. They don't bounce off of each other. The reason the room has to be dusty is because we want to see the light. The room dust wasn't there. We wouldn't actually see the light until it got to the other wall. So you see the beam because it's the dust in the air. But the two beams actually pass right through each other. They literally pass right through. They don't affect each other at all. One acts like the other, it's not there. The particle of light is the simplest example that shows that behavior. That's a boson. Now let's imagine that we're in the same dusty room, and this time you have a bucket of balls and I have a bucket of balls, and we try to throw them so that we get something like a beam, throwing them fast, right? If they collide, they don't just pass through each other, they bounce off of each other. Now that's mostly because they have electric charge, and electric charges, light charges repel. But mathematically, I know how to turn off the electric charge. If you do that, you'll find they still repel. And it's because they are these things we call fermions. So this is how you distinguish the things that are in the two buckets. They are either bosons or fermions. Which of them, and maybe you can mention the most popular of the bosons. The most recently discovered. It's like- The Higgs boson. Yeah, yeah. It's like when I was in high school and there was a really popular majorette. Her name is the Higgs particle these days. Can you describe which of the bosons and the fermions have been discovered, hypothesized, which have been experimentally validated, what's still out there? Sure. Right. So the two buckets that I've actually described to you have all been first hypothesized and then verified by observation, with the Higgs boson being the most recent one of these things. We haven't actually verified the graviton, interestingly enough. Mathematically, we have an expectation that graviton's like this, but we've not performed an experiment to show that this is an accurate idea that nature uses. So something has to be a carrier- For the force of gravity, exactly. Because that's- Can it be something way more mysterious than we... So when you say the graviton, would it be like the other particles, force carriers, or can it be something much more mysterious? In some ways, yes, but in other ways, no. It turns out that the graviton is also, if you look at Einstein's theory, he taught us about this thing he calls space-time, which is... If you try to imagine it, you can sort of think of it as kind of a rubber surface. That's one popular depiction of space-time. It's not an accurate depiction because the only accuracy is actually in the calculus that he uses, but that's close enough. So if you have a sheet of rubber, you can wave it. You can actually form a wave on it. Space-time is enough like that so that when space-time oscillates, you create these waves. These waves carry energy. We expect them to carry energy in quanta. That's what a graviton is. It's a wave in space-time. And so the fact that we have seen the waves with LIGO over the course of the last three years, and we've recently used gravitational wave observatories to watch colliding black holes and neutron stars and all sorts of really cool stuff out there. So we know the waves exist, but in order to know that gravitons exist, you have to prove that these waves carry energy in energy packets, and that's what we don't have the technology to do yet. And perhaps briefly jumping to a philosophical question, does it make sense to you that gravity is so much weaker than the other forces? No. You see, now you've touched on a very deep mystery about physics. There are a lot of such questions of physics about why things are as they are. And as someone who believes that there are some things that certainly are coincidences, like you could ask the same question about, well, why are the planets at the orbits that they are around the sun? The answer turns out there is no good reason. It's just an accident. So there are things in nature that have that character, and perhaps the strength of the various forces is like that. On the other hand, we don't know that that's the case, and there may be some deep reasons about why the forces are ordered as they are, where the weakest force is gravity, the next weakest force is the weak interaction, the weak nuclear force, then there's electromagnetism, there's a strong force. We don't really have a good understanding of why this is the ordering of the forces. Some of the fascinating work you've done is in the space of supersymmetry, symmetry in general. Can you describe, first of all, what is supersymmetry? Ah, yes. So you remember the two buckets I told you about, perhaps earlier, I said there are two buckets in our universe. So now I want you to think about drawing a pie that has four quadrants. So I want you to cut the piece of pie in fourths. So in one quadrant, I'm going to put all the buckets that we talked about that are like the electron and the quarks. In a different quadrant, I'm going to put all the force carriers. The other two quadrants are empty. Now, if you, I showed you a picture of that, you'd see a circle. There would be a bunch of stuff in one upper quadrant and stuff in others. And then I would ask you a question. Does that look symmetrical to you? No. No. And that's exactly right, because we humans actually have a very deeply programmed sense of symmetry. It's something that is part of that mystery of the universe. So how would you make it symmetrical? One way you could is by saying those two empty quadrants had things in them also. And if you do that, that's supersymmetry. So that's what I understood when I was a graduate student here at MIT in 1975, when the mathematics of this was first being born. Supersymmetry was actually born in the Ukraine in the late 60s, but we had this thing called the Iron Curtain, so we Westerners didn't know about it. But by the early 70s, independently, there were scientists in the West who had rediscovered supersymmetry. Bruno Zemino and Julius Vest were their names. So this was around 71 or 72 when this happened. I started graduate school in 73. So around 74, 75, I was trying to figure out how to write a thesis so that I could become a physicist the rest of my life. I had a great advisor, Professor James Young, who had taught me a number of things about electrons and weak forces and those sorts of things. But I decided that if I was going to have an opportunity to maximize my chances of being successful, I should strike it out in a direction that other people were not studying. And so as a consequence, I surveyed ideas that were being developed, and I came across the idea of supersymmetry. And the mathematics was so remarkable that it bowled me over. I actually have two undergraduate degrees. My first undergraduate degree is actually mathematics, and my second is physics, even though I always wanted to be a physicist. Plan A, which involved getting good grades, was mathematics. I was a mathematics major thinking about graduate school, but my heart was in physics. If we could take a small digression, what's to you the most beautiful idea in mathematics that you've encountered in this interplay between math and physics? It's the idea of symmetry. The fact that our innate sense of symmetry winds up aligning with just incredible mathematics, to me, is the most beautiful thing. It's very strange but true that if symmetries were perfect, we would not exist. And so even though we have these very powerful ideas about balance in the universe in some sense, it's only when you break those balances that you get creatures like humans and objects like planets and stars. So although they are a scaffold for reality, they cannot be the entirety of reality. So I'm kind of naturally attracted to parts of science and technology where symmetry plays a dominant role. And not just, I guess, symmetry, as you said, but the magic happens when you break the symmetry. The magic happens when you break the symmetry. Okay, so diving right back in, you mentioned four quadrants. Yes. Two are filled with stuff, two buckets. We've measured, yep. And then there's crazy mathematical thing, ideas for filling the other two. The other two. What are those things? Well, what are those things? So earlier, the way I described these two buckets is I gave you a story that started out by putting us in a dusty room with two flashlights. And I said, turn on your flashlight, I'll turn on mine, the beams will go through each other. And the beams are composed of force carriers called photons. They carry the electromagnetic force. And they pass right through each other. So imagine looking at the mathematics of such an object, which you don't have to imagine people like me do that. So you take that mathematics, and then you ask yourself a question. You see, mathematics is a palette. It's just like a musical composer is able to construct variations on a theme. Well, a piece of mathematics in the hand of a physicist is something that we can construct variations on. So even though the mathematics that Maxwell gave us about light, we know how to construct variations on that. And one of the variations you can construct is to say, suppose you have a force carrier for electromagnetism that behaves like an electron in that it would bounce off of another one. That's changing a mathematical term in an equation. So if you did that, you would have a force carrier. So you would say first it belongs in this force carrying bucket, but it's got this property of bouncing off like electrons. So you say, well, gee, wait, no, that's not the right bucket. So you're forced to actually put it in one of these empty quadrants. So those sorts of things, basically we give them a, so the photon mathematically can be accompanied by a photino. It's the thing that carries a force but has the rule of bouncing off. In a similar manner, you could start with an electron. And you say, okay, so write down the mathematics of an electron. I know how to do that. A physicist named Dirac first told us how to do that back in the late 20s, early 30s. So take that mathematics and then you say, let me look at that mathematics and find out what in the mathematics causes two electrons to bounce off of each other, even if I turn off the electrical charge. So I could do that. And now let me change that mathematical term. So now I have something that carries electrical charge, but if you take two of them, I'm sorry, if you turn their charges off, they'll pass through each other. So that puts things in the other quadrant. And those things we tend to call, we put the S in front of their name. So in the lower quadrant here, we have electrons. In this now newly filled quadrant, we have electrons. In the quadrant over here, we had quarks. Over here, we have squarks. So now we've got this balanced pie. And that's basically what I understood as a graduate student in 1975 about this idea of supersymmetry, that it was going to fill up these two quadrants of the pie in a way that no one had ever thought about before. So I was amazed that no one else at MIT found this an interesting idea. So it led to my becoming the first person in MIT to really study supersymmetry. This was 1975, 76, 77. And in 77, I wrote the first PhD thesis in the physics department on this idea because I was drawn to the balance. Drawn to the symmetry. So what does that, first of all, is this fundamentally a mathematical idea? So how much experimental, and we'll have this theme, it's a really interesting one when you explore the world of the small. And in your new book, talking about Approving Einstein, right, that we'll also talk about, there's this theme of kind of starting it, exploring crazy ideas first in the mathematics and then seeking for ways to experimentally validate them. Where do you put supersymmetry in that? It's closer than string theory. It has not yet been validated. In some sense, as you mentioned Einstein, so let's go there for a moment. In our book, Proving Einstein Right, we actually do talk about the fact that Albert Einstein in 1915 wrote a set of equations which were very different from Newton's equations in describing gravity. These equations made some predictions that were different from Newton's predictions. And it actually made three different predictions. One of them was not actually a prediction but a postdiction because it was known that Mercury was not orbiting the sun in the way that Newton would have told you. And so Einstein's theory actually describes Mercury orbiting in a way that it was observed as opposed to what Newton would have told you. So that was one prediction. The second prediction that came out of the theory of general relativity, which Einstein wrote in 1915, was that if you... So let me describe an experiment and come back to it. Suppose I had a glass of water and I filled the glass up and then I moved the glass slowly back and forth between our two faces. It would appear to me like your face was moving, even though you weren't moving. I mean, it's actually... And what's causing it is because the light gets bent through the glass as it passes from your face to my eye. So Einstein in his 1915 theory of general relativity found out that gravity has the same effect on light as that glass of water. It would cause beams of light to bend. Now, Newton also knew this, but Einstein's prediction was that light would bend twice as much. And so here's a mathematical idea. Now, how do you actually prove it? Well, you've got to watch... Yeah. Just a quick pause on that, just the language you're using. He found out... I can say he did a calculation. It's a really interesting notion that one of the most... One of the beautiful things about this universe is you can do a calculation and combine with some of that magical intuition that physicists have, actually predict what would be... What's possible to experimentally validate. That's correct. So he found out in the sense that there seems to be something here and mathematically it should bend... Gravity should bend light this amount. And so therefore that's something that could be potentially... And then come up with an experiment that could be validated. Right. And that's the way that actually modern physics, deeply fundamental modern physics, this is how it works. Earlier we spoke about the Higgs boson. So why did we go looking for it? The answer is that back in the late 60s, early 70s, some people wrote some equations and the equations predicted this. So then we went looking for it. So on supersymmetry for a second, there's these things called adinkra symbols, strange little graphs. You refer to them as revealing something like binary code, underlying reality. First of all, can you describe these graphs? What are they? What are these beautiful little strange graphs? Well, first of all, adinkras are an invention of mine together with a colleague named Michael Fox. In 2005, we were looking at equations. The story's a little bit more complicated and it'll take too long to explain all the details, but the Reader's Digest version is that we were looking at these equations and we figured out that all the data in a certain class of equations could be put in pictures. And the pictures, what do they look like? Well, they're just little balls. You have black balls and white balls. Those stand for those two buckets, by the way, that we talked about in reality. The white balls are things that are like particles of light. The black balls are like electrons. And then you can draw lines connecting these balls. And these lines are deeply mathematical objects. And there's no way for me to... I have no physical model for telling you what the lines are. But if you were a mathematician, I would do a technical phrase saying, this is the orbit of the representation of the action of the symmetry generators. Mathematicians wouldn't understand it. Nobody else in their right mind would. So let's not go there. But we figured out that the data that was in the equations was in these funny pictures that we could draw. And so that was stunning. But it also was encouraging because there are problems with the equations, which I had first learned about in 1979 when I was down at Harvard. I went out to Caltech for the first time and working with a great scientist by the name of John Schwartz. There are problems in the equations we don't know how to solve. And so one of the things about solving problems that you don't know how to solve is that beating your head against a brick wall is probably not a good philosophy about how to solve it. So what do you need to do? You need to change your sense of reference, your frame of reference, your perspective. So when I saw these funny pictures, I thought, gee, that might be a way to solve these problems with equations that we don't know how to do. So that was, for me, one of the first attractions is that I now had an alternative language to try to attack a set of mathematical problems. But I quickly realized that A, this mathematical language was not known by mathematicians, which makes it pretty interesting because now you have to actually teach mathematicians about a piece of mathematics because that's how they make their living. And the great thing about working with mathematicians, of course, is the rigor with which they examine ideas. So they make your ideas better than they start out. So I started working with a group of mathematicians, and it was in that collaboration that we figured out that these funny pictures had error-correcting codes buried in them. So- Can you talk about what are error-correcting codes? Sure. So the simplest way to talk about error-correcting codes is, first of all, to talk about digital information. Digital information is basically strings of ones and zeros. They're called bits. So now let's imagine that I want to send you some bits. Well, maybe I could show you pictures, but maybe it's a rainy day or maybe the windows in your house are foggy. So sometimes when I show you a zero, you might interpret it as a one. Or other times when I show you a one, you might interpret it as a zero. So if that's the case, that means when I try to send you this data, it comes to you in corrupted form. And so the challenge is, how do you get it to be uncorrupted? In the 1940s, a computer scientist named Hemming addressed the problem of how do you reliably transmit digital information? And what he came up with was a brilliant idea. The way you solve it is that you take the data that you want to send, the ones in your strings of ones and zeros, your favorite string, and then you dump more ones and zeros in, but you dump them in in a particular pattern. And this particular pattern is what a Hemming code is all about. So it's an error correcting code, because if the person at the other end knows what the pattern's supposed to be, they can figure out when one's got changed to zeros, zero's got changed to one. So it turned out that our strange little objects that came from looking at the equations that we couldn't solve, it turns out that when you look at them deeply enough, you find out that they're strict, that they have ones and zeros buried in them. But even more astoundingly, the ones and zeros are not there randomly. They are in the pattern of error correcting codes. So this was an astounding thing that when we first got this result and tried to publish it, it took us three years to convince other physicists that we weren't crazy. Eventually, we were able to publish it, I and this collaboration of mathematicians and other physicists. And so, ever since then, I have actually been looking at the mathematics of these objects, trying to still understand properties of the equations. And I want to understand the properties of equations because I want to be able to try things like electrons. So as you can see, it's just like a two step remove process of trying to get back to reality. So what would you say is the most beautiful property of these adinkra graphs, objects? What do you think, by the way, the word symbols, what do you think of them these simple graphs? Are they objects? For people who work with mathematics like me, our mathematical concepts are, we often refer to them as objects because they feel like real things. Even though you can't see them or touch them, they're so much part of your interior life that it is as if you could. So we often refer to these things as objects, even though there's nothing objective about them. And what does a single graph represent in space? So, okay, so the simplest of these graphs has to have one white ball and one black ball. That's that balance that we talked about earlier. Remember, we want to balance out the quadrants? Well, you can't do it unless you have a black ball and white ball. So the simplest of these objects looks like two little balls, one black, one white, connected by a single line. And what it's talking about is, as I said, a deep mathematical property related to symmetry. You've mentioned the error correcting codes, but is there a particular beautiful property that stands out to you about these objects that you just find? Yes. I mean, they're very early on in the development. Yes, there is. The craziest thing about these to me is that when you look at physics and try to write equations where information gets transmitted reliably, if you're in one of these super symmetrical systems with this extra symmetry, that doesn't happen unless there's an error correcting code present. So it's as if the universe says, you don't retransmit information unless there's something about an error correcting code. This to me is the craziest thing that I've ever personally encountered in my research. And it's actually got me to wondering, how this could come about? Because the only place in nature that we know about error correcting codes is genetics. And in genetics, we think it was evolution that causes error correcting codes to be in genomes. And so does that mean that there was some kind of form of evolution acting on the mathematical laws of the physics of our universe? This is a very bizarre and strange idea. And it's something I've wondered about from time to time since making these discoveries. Do you think such an evolution is possible? Do you think such an idea could be fundamental or is it emergent throughout all the different kinds of systems? I don't know whether it's fundamental. I probably will not live to find out. This is going to be the work of probably some future either mathematician or physicist to figure out what these things actually mean. We have to talk a bit about the magical, the mysterious string theory, super string theory. Sure. There's still maybe this aspect of it, which is there's still, for me, from an outsider's perspective, this fascinating heated debate on the status of string theory. Can you clarify this debate, perhaps articulating the various views and say where you land on it? So first of all, I doubt that I will be able to say anything to clarify the debate around string theory for a general audience. Part of the reason is because string theory has done something I've never seen theoretical physics do. It is broken out into consciousness of the general public before we're finished. You see, string theory doesn't actually exist because when we use the word theory, we mean a particular set of attributes. In particular, it means that you have an overarching paradigm that explains what it is that you're doing. No such overarching paradigm exists for string theory. What string theory is currently is an enormously large, mutually reinforcing collection of mathematical facts in which we can find no contradictions. We don't know why it's there, but we can certainly say that without challenge. Now, just because you find a piece of mathematics doesn't mean that this applies to nature. And in fact, there has been a very heated debate about whether string theory is some sort of hysteria among the community of theoretical physicists or whether it has something fundamental to say about our universe. We don't yet know the answer to that question. What those of us who study string theory will tell you are things like string theory has been extraordinarily productive in getting us to think more deeply, even about mathematics that's not string theory, but the kind of mathematics that we've used to describe elementary particles. There have been spinoffs from string theory, and this has been going on now for two decades almost, that have allowed us, for example, to more accurately calculate the force between electrons with the presence of quantum mechanics. This is not something you hear about in the public. There are other things that are being done, but they're not being done in the way that we hear about in the public. There are other similar things. That kind of property I just told you about is what's called weak-strong duality, and it comes directly from string theory. There are other things such as a property called holography, which allows one to take equations and look at them on the boundary of a space and then to know information about inside the space without actually doing calculations there. This has come directly from string theory. So there are a number of direct mathematical effects that we learn in string theory, but we take these ideas and look at math that we already know, and we find suddenly we're more powerful. This is a pretty good indication there's something interesting going on with string theory itself. So it's the early days of a powerful mathematical framework. That's what we have right now. What are the big, first of all, for most people probably, which as you said, most general public would know actually what string theory is, which is at the highest level, which is a fascinating fact. Well, string theory is what they do on the Big Bang Theory, right? One, can you maybe describe what is string theory, and two, what are the open challenges? So what is string theory? Well, the simplest explanation I can provide is to go back and ask what are particles, which is the question you first asked me. What's the smallest thing? Yeah, what's the smallest thing? So particles, one way I try to describe particles to people is start, I want you to imagine a little ball, and I want you to let the size of that ball shrink until it has no extent whatsoever, but it still has the mass of the ball. That's actually what Newton was working with when he first invented physics. He's the real inventor of the massive particle, which is this idea that underlies all of physics. So that's where we start. It's a mathematical construct that you get by taking a limit of things that you know. So what's a string? Well, in the same analogy, I would say, now I want you to start with a piece of spaghetti, so we all know what that looks like, and now I want you to let the thickness of the spaghetti shrink until it has no thickness. Mathematically, I mean, in words, this makes no sense, but mathematically, this actually works, and you get this mathematical object out. It has properties that are like spaghetti. It can wiggle and jiggle, but it can also move collectively like a piece of spaghetti. It's the mathematics of those sorts of objects that constitute string theory. And does the multidimensional, 11-dimensional, however many dimensional, more than four dimension, is that a crazy idea to you? Is that the stranger aspect of string theory to you? Not really, and also partly because of my own research. So earlier, we talked about these strange symbols that we've discovered inside the equations. It turns out that to a very large extent, adinkras don't really care about the number of dimensions. They kind of have an internal mathematical consistency that allows them to be manifest in many different dimensions. Since supersymmetry is a part of string theory, then this same property you would expect to be inherited by string theory. However, another little-known fact, which is not in the public debate, is that there are actually strings that are only four-dimensional. This is something that was discovered at the end of the 80s by three different groups of physicists working independently. I and my friend Warren Siegel, who were at the University of Maryland at the time, were able to prove that there's mathematics that looks totally four-dimensional, and yet it's a string. There was a group in Germany that used slightly different mathematics, but they found the same result. And then there was a group at Cornell who, using yet a third piece of mathematics, found the same result. So the fact that extra dimensions is so widely talked about in the public is partly a function of how the public has come to understand string theory and how the story has been told to them. But there are alternatives you don't know about. If we could talk about maybe experimental validation. You're the co-author of a recently published book, Proving Einstein Right, the human story of it, too, the daring expeditions that change how we look at the universe. Do you see echoes of the early days of general relativity in the 1910s to the more stretched out to string theory? I do. Or stretched out of that? I do. And that's one reason why I was happy to focus on the story of how Einstein became a global superstar. Earlier in our discussion, we went over his history where in 1915, he came up with this piece of mathematics, used it to do some calculations, and then made a prediction. But making a prediction is not enough. Someone's got to go out and measure. And so string theory is in that in-between zone. Now for Einstein, it was from 1915 to 1919. 1915, he makes the correct prediction. By the way, he made an incorrect prediction about the same thing in 1911, but he corrected himself in 1915. And by 1919, the first pieces of experimental observational data became available to say, yes, he's not wrong. And by 1922, the argument based on observation was overwhelming that he was not wrong. Can you describe what special and general relativity are just briefly? Sure. In the sense in what prediction Einstein made and maybe some or memorable moment from the human journey of trying to prove this thing right, which is incredible. Right. So I'm very fortunate to have worked with a talented novelist who wanted to write a book that coincided with a book I wanted to write about how science kind of feels if you're a person. Because it's actually people who do science, even though that may not be obvious to everyone. So for me, I wanted to write this book for a couple of reasons. I wanted young people to understand that these seeming alien giants that live before them were just as human as they are. They get married, they get divorced. They get married, they get divorced. They do terrible things. They do great things. They're people. They're just people like you. And so that part of telling the story allowed me to get that out there for both young people interested in the sciences as well as the public. But the other part of the story is I wanted to open up sort of what it was like. Now, I'm a scientist, and so I will not pretend to be a great writer. I understand a lot about mathematics, and I've even created my own mathematics that is kind of a weird thing to be able to do. But in order to tell the story, you really have to have an incredible master of the narrative. And that was my co-author, Kathy Pelletier, who is a novelist. So we formed this conjoined brain, I used to call us. She used to call us Professor Higgins and Eliza Doolittle. My expression for us is that we were a conjoined brain to tell this story. And it allowed, so what are some magical moments? To me, the first magical moment in telling the story was looking at Albert Einstein and his struggle. Because although we regard him as a genius, as I said, in 1911, he actually made an incorrect prediction about bending starlight. And that's actually what set the astronomers off. In 1914, there was an eclipse. And by various accidents of war and weather and all sorts of things that we talk about in the book, no one was able to make the measurement. If they had made the measurement, it would have disagreed with his 1911 prediction, because nature only has one answer. And so then you see how fortunate he was that wars and bad weather and accidents and transporting equipment stopped any measurements from being made. So he corrects himself in 1915, but the astronomers are already out there trying to make the measurement. So now he gives them a different number. And it turns out that's the number that nature agrees with. So it gives you a sense of this is a person struggling with something deeply. And although his deep insight led him to this, it is the circumstance of time, place, and accident through which we view him. And the story could have turned out very differently, where first he makes a prediction, the measurements are made in 1914, they disagree with his prediction. And so what would the world view him as? Well, he's this professor who made this prediction that didn't get it right. Yes? So the fragility of human history is illustrated by that story. And it's one of my favorite things. You also learn things like in our book, how eclipses and watching eclipses was a driver of the development of science in our nation when it was very young. In fact, even before we were a nation, it turns out there were citizens of this would-be country that were going out trying to measure eclipses. So some fortune, some misfortune affects the progress of science. Absolutely. Especially with ideas as, to me at least, if I put myself back in those days, as radical as general relativity is. First, can you describe, if it's okay, briefly, what general relativity is? And yeah, could you just take a moment of, yeah, put yourself in those shoes in the academic researcher, scientist of that time, and what is this theory? What is it trying to describe about our world? It's trying to answer the thing that left Isaac Newton puzzled. Isaac Newton says gravity magically goes from one place to another. He doesn't believe it, by the way. He knows that's not right. But the mathematics is so good that you have to say, well, I'll throw my qualms away because I'll use it. That's all we used to get a man from the Earth and the Moon was that mathematics. So I'm one of those scientists, and I've seen this, and if I thought deeply about it, maybe I know that Newton himself wasn't comfortable. And so the first thing I would hope that I would feel is, gee, there's this young kid out there who has an idea to fill in this hole that was left with us by Sir Isaac Newton. That would, I hope, would be my reaction. I have a suspicion. I'm kind of a mathematical creature. I was four years old when I first decided that science was what I wanted to do with my life. And so if my personality back then was like it is now, I think it's probably likely I would want to have studied his mathematics. What was a piece of mathematics that he was using to make this prediction? Because he didn't actually create that mathematics. That mathematics was created roughly 50 years before he lived. He's the person who harnessed it in order to make a prediction. In fact, he had to be taught this mathematics by a friend. So this is in our book. So putting myself in that time, I would want to, like I said, I think I would feel excitement. I would want to know what the mathematics is, and then I would want to do the calculations myself. Because one thing that physics is all about is that you don't have to take anybody's word for anything. You can do it yourself. It does seem that mathematics is a little bit more tolerant of radical ideas, or mathematicians, or people who find beauty in mathematics. All the white questions have no good answer, but let me ask. Why do you think Einstein never got the Nobel Prize for general relativity? He got it for the photoelectric effect. That is correct. Well, first of all, that's something that is misunderstood about the Nobel Prize in physics. The Nobel Prize in physics is never given for purely proposing an idea. It is always given for proposing an idea that has observational support. So he could not get the Nobel Prize for either special relativity nor general relativity because the provisions that Alfred Nobel left for the award prevent that. But after it's been validated, can he not get it then or no? Yes, but remember the validation doesn't really come until the 1920s. But that's why they invented the second Nobel Prize. I mean, Marie Curie, you can get a second Nobel Prize for one of the greatest theories in physics. So let's be clear on this. The theory of general relativity had its critics even up until the 50s. So if the committee had wanted to give the prize for general relativity, there were vociferous critics of general relativity up until the 50s. Einstein died in 1955. Yeah. What lessons do you draw from the story you tell in the book, from general relativity, from the radical nature of the theory to looking at the future of string theory? Well, I think that the string theorists are probably going to retrace this path, but it's going to be far longer and more torturous in my opinion. String theory is such a broad and deep development that in my opinion, when it becomes acceptable, it's going to be because of a confluence of observations. It's not going to be a single observation. And I have to tell you that, so I gave a seminar here yesterday at MIT, and it's on an idea I have about how string theory can leave signatures in the cosmic microwave background, which is astrophysical structure. And so if those kinds of observations are borne out, if perhaps other things related to the idea of supersymmetry are borne out, those are going to be the first powerful observationally based pieces of evidence that will begin to do what the Eddington expedition did in 1919. But that may take several decades. Do you think there will be Nobel Prizes given for string theory? No. Because decades. Because I think it will exceed normal human lifetimes. But there are other prizes that are given. I mean, there is something called the Breakthrough Prize. There's a Russian-American emigre named Yuri Milner, I believe his name, started this wonderful prize called the Breakthrough Prize. It's three times as much money as the Nobel Prize, and it gets awarded every year. And so something like one of those prizes is likely to be garnered at some point far earlier than a Nobel Award. Jumping around a few topics. While you were at Caltech, you've gotten to interact, I believe, with Richard Feynman, I have to ask. Yes, Richard Feynman, indeed. Do you have any stories that stand out in your memory of that time? I have a fair number of stories, but I'm not prepared to tell them. They're not all politically correct, shall we say. Let me just say, I'll say the following. Richard Feynman, if you've ever read some of the books about him, in particular, there's a book called Surely You're Joking, Mr. Feynman. There's a series of books that starts with Surely You're Joking, Mr. Feynman. And I think the second one may be something like What Do You Care What They Say, or something. I mean, the titles are all, there are three of them. When I read those books, I was amazed at how accurately those books portrayed the man that I interacted with. He was irreverent, he was fun, he was deeply intelligent, he was deeply human. And those books tell that story very effectively. Even just those moments, how did they affect you as a physicist? Well, one of the, well, it's funny because one of the things that, I didn't hear Feynman say this, but one of the things that is reported that he said is if you're in a bar stool as a physicist, and you can't explain to the guy on the bar stool next to you what you're doing, you don't understand what you're doing. And there's a lot of that that I think is correct, that when you truly understand something as complicated as string theory, when it's in its fully formed final development, it should be something you could tell to the person on the bar stool next to you. And that's something that affects the way I do science, quite frankly. It also affects the way I talk to the public about science. It's one of the sort of my mantras that I keep deeply, and try to keep deeply before me when I appear in public fora, speaking about physics in particular, and science in general. It's also something that Einstein said in a different way. He said, he had these two different formulations. One of them is, when the answer's simple, it's God speaking. And the other thing that he said was that what he did in his work was simply the distillation of common sense, that you distill down to something. And he also said, you make things as simple as possible, but no simpler. So all of those things, and certainly this attitude for me, first sort of seeing this was exemplified by being around Richard Feynman. So in all your work, you're always kind of searching for the simplicity, for the simple, clear. I am, ultimately. Ultimately, I am. You served on President Barack Obama's Council of Advisors in Science and Technology. For seven years, yes. For seven years with Eric Schmidt and several other brilliant people. Met Eric for the first time in 2009 when the council was called together. Yeah, I've seen pictures of you in that room. I mean, there's a bunch of brilliant people. It kind of looks amazing. What was that experience like, being called upon that kind of service? So let me go back to my father, first of all. I earlier mentioned that my father served 27 years in the US Army, starting in World War II. He went off in 1942, 43 to fight against the fascists. He was part of the supply corps that supplied General Patton as the tanks rolled across Western Europe, pushing back the forces of Nazism. To meet up with our Russian comrades who were pushing the Nazis, starting in Stalingrad. And the Second World War is actually a very interesting piece of history to know from both sides. Here in America, we typically don't, but I've actually studied history as an adult, so I actually know sort of the whole story. And on the Russian side, we don't know the Americans. We weren't taught the American side. I know, I know. I have many Russian friends, and we've had this conversation on many occasions. It's fascinating. But you know, like General Zhukov, for example, was something that you would know about, but you might not know about a Patton, but you're right. So, Georgi Zhukov, or Rokossovsky, I mean, there's a whole list of names that I've learned in the last 15 or 20 years looking at the Second World War. So... Your father was in the midst of that, probably one of the greatest wars in history. In the history of our species. And so, the idea of service comes to me essentially from that example. So, in 2009, when I first got a call from a Nobel Laureate, actually, in biology, Harold Farmis, was on my way to India, and I got this email message, and he said he needed to talk to me. And I said, okay, fine, we can talk. Got back to the States, I didn't hear from him. We went through several cycles of this, sending me messages, I want to talk to you, and then never contacted. And finally, I was on my way to give a physics presentation at University of Florida in Gainesville, and just had stepped off a plane, and my mobile phone went off, and it was Harold. And so, I said, Harold, why do you keep sending me messages that you want to talk, but you never call? And he said, well, I'm sorry, things have been hectic, and da-da-da-da-da. And then he said, if you were offered the opportunity to serve on the US President's Council of Advisors on Science and Technology, what would be your answer? Now, I was amused at the formulation of the question, because it's clear that there's a purpose of why the question is asked that way. But then, he made it clear to me he wasn't joking. And literally, one of the few times in my life, my knees went weak, and I had to hold myself up against a wall so that I didn't fall over. I doubt if most of us who have been the beneficiaries of the benefits of this country, when given that kind of opportunity, could say no. And I know I certainly couldn't say no. I was frightened out of my wits, because I had never—although I have—my career in terms of policy recommendations is actually quite long. It goes back to the 80s. But I had never been called upon to serve as an advisor to a president of the United States. And it was very scary, but I did not feel that I could say no, because I wouldn't be able to sleep with myself at night, saying that I chickened out or whatever. And so, I took the plunge, and we had a pretty good run. There are things that I did in those seven years, of which I'm extraordinarily proud. One of the ways I tell people is, if you've ever seen that television cartoon called Schoolhouse Rock, there's this one story about how a bill becomes a law. And I've kind of lived that. There are things that I did that have now been codified in U.S. law. Not everybody gets a chance to do things like that in life. What do you think is the—science and technology, especially in American politics—we haven't had a president who's an engineer or a scientist. What do you think is the role of a president like President Obama in understanding the latest ideas in science and tech? What was that experience like? Well, first of all, I've met other presidents besides President Obama. He is the most extraordinary president I've ever encountered. Despite the fact that he went to Harvard. When I think about President Obama, he is a deep mystery to me, in the same way, perhaps, that the universe is a mystery. I don't really understand how that constellation of personalities could—personality traits could come to fit within a single individual. But I saw them for seven years, so I'm convinced that I wasn't seeing fake news. I was seeing real data. He was just an extraordinary man. And one of the things that was completely clear was that he was not afraid and not intimidated to be in a room of really smart people. I mean, really smart people. That he was completely comfortable in asking some of the world's greatest experts, what do I do about this problem? And it wasn't that he was going to just take their answer, but he would listen to the advice. And he would listen to the answer, but he would listen to the advice. And that, to me, was extraordinary. As I said, I've been around other executives, and I've never seen one quite like him. He's an extraordinary learner, is what I observed, and not just about science. He has a way of internalizing information in real time that I've never seen in a politician before, even in extraordinarily complicated situations. Even scientific ideas. Scientific or non-scientific. Complicated ideas don't have to be scientific ideas. But I have, like I said, seen him in real time process complicated ideas with a speed that was stunning. In fact, he shocked the entire council. I mean, we were all stunned at his capacity to be presented with complicated ideas, and then to wrestle with them and internalize them, and then come back, more interestingly enough, come back with really good questions to ask. I've noticed this in the area that I understand more of artificial intelligence. I've seen him integrate information about artificial intelligence, and then come out with these kind of Richard Feynman-like insights. That's exactly right. And that's, as I said, those of us who have been in that position, it is stunning to see it happen because you don't expect it. Yeah. It takes what, for a lot of sort of graduate students, it takes like four years in a particular topic, and he just does it in a few minutes. He sees it very naturally. You've mentioned that you would love to see experimental validation of super-strength theory before you— Before I shuffle off this mortal coil. Which, the poetry of that reference made me smile when I saw it. You know, people actually misunderstand that because it's not what, it doesn't mean what we generally take it to mean colloquially, but it's such a beautiful expression. Yeah, it is. It's from the Hamlet, to be or not to be speech, which I still don't understand what that's about, but so many interpretations. Anyway, what are the most exciting problems in physics that are just within our reach of understanding and maybe solve the next few decades that you may be able to see? So, in physics, you limited it to physics. Physics, mathematics, this kind of space of problems that fascinate you. Well, the one that looks on the immediate horizon like we're going to get to is quantum computing. And that's gonna, if we actually get there, that's gonna be extraordinarily interesting. Do you think that's a fundamentally problem of theory, or is it now in the space of engineering? It's in the space of engineering. I was out at a Q station, as you may know, Microsoft has this research facility in Santa Barbara. I was out there a couple of months in my capacity as the vice president of American Physical Society. And I got, you know, I had some things that were like lectures and they were telling me what they were doing. And it sure sounded like they knew what they were doing and that they were close to major breakthroughs. Yeah, that's a really exciting possibility there. But back to Hamlet, do you ponder mortality, your own mortality? Nope. My mother died when I was 11 years old. And so, I immediately knew what the end of the story was for all of us. As a consequence, I've never spent a lot of time thinking about death. It'll come in its own good time. And sort of, to me, the job of every human is to make the best and the most of the time that's given to us in order not for our own selfish gain, but to try to make this place a better place for someone else. And on the why of life, why do you think we are? I have no idea. And I never even worried about it. For me, I have an answer, a local answer. The apparent why for me was because I'm supposed to do physics. But it's funny because there's so many other quantum mechanically speaking possibilities in your life, such as being an astronaut, for example. So, you know about that, I see. Well, like Einstein and the vicissitudes that prevented the 1914 measurement of starlight bending, the universe is constructed in such a way that I didn't become an astronaut, which would have, for me, I would have faced the worst choice in my life, whether I would try to become an astronaut or whether I would try to do theoretical physics. Both of these dreams were born when I was four years old simultaneously. And so, I can't imagine how difficult that decision would have been. The universe helped you out on that one. Not only in that one, but in many ones. It helped me out by allowing me to pick the right dad. Is there a day in your life you could relive because it made you truly happy? What day would that be, if you could just look back? Being a theoretical physicist is like having Christmas every day. I have lots of joy in my life. The moments of invention, the moments of ideas, revelation. Yes. The only thing that exceeds them are some family experiences, like when my kids were born and that kind of stuff, but they're pretty high up there. Well, I don't see a better way to end it, Jim. Thank you so much. It was a huge honor talking today. This worked out better than I thought. Glad to hear it. Thanks for listening to this conversation with S. James Gates Jr. And thank you to our presenting sponsor, Cash App. Download it and use code LEXPODCAST. You'll get $10 and $10 will go to FIRST, a STEM education non-profit that inspires hundreds of thousands of young minds to learn and to dream of engineering our future. If you enjoy this podcast, subscribe on YouTube, give it five stars on Apple Podcasts, support on Patreon, or connect with me on Twitter. And now let me leave you with some words of wisdom from the great Albert Einstein for the rebels among us. Unthinking respect for authority is the greatest enemy of truth. Thank you for listening and hope to see you next time.

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Tim Dillon: Comedy, Power, Conspiracy Theories, and Freedom | Lex Fridman Podcast #156

The following is a conversation with Tim Dillon, a stand-up comedian who is fearless in challenging the norms of modern day social and political discourse. Quick mention of our sponsors, NetSuite Business Management Software, Athletic Greens All-in-One Nutrition Drink, Magic Spoon Low Carb Cereal, BetterHelp Online Therapy, and Rev Speech Detect Service. So the choice is business, health, sanity, or transcripts. Choose wisely my friends, and if you wish, click the sponsor links below to get a discount at the support of this podcast. As a side note, let me say that I will continue talking to scientists, engineers, historians, mathematicians, and so on, but I will also talk to the people who Jack Kerouac called the mad ones in his book On The Road. That is one of my favorite books. He wrote, the only people for me are the mad ones. The ones who are mad to live, mad to talk, mad to be saved, desirous of everything at the same time. The ones who never yawn or say a commonplace thing, but burn, burn, like fabulous yellow Roman candles exploding like spiders across the stars. And in the middle, you see the blue center light pop, and everybody goes, ah. Some of these conversations will be a bit of a gamble, in that I have no idea how they will turn out, but I'm willing to risk it for a chance at a bit of an adventure. And I'm happy and honored that Tim, this time, wanted to take a chance as well. If you enjoy this thing, subscribe on YouTube, review it on Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with Tim Dillon. What would you like your tombstone to read? It's a good way to summarize the essence of a human being. I would like it to say, this has not been paid for. And I want my living relatives to struggle to pay for it, and I think I would like them to be hounded every day. I would like people to call and go, listen, we don't want to ever excavate a body, but we will, because this has not been paid for. I love the idea of leaving the world in lots of debt that other people have to deal with. And I know people that have done that, and I know people that have been in families where that's happened, where someone has to sit and just curse the sky, because they don't have a physical person anymore to be angry at, but they still have to deal with the decisions that person made. And that's deeply tragic, but that's always struck me as very funny. Well, it's a kind of immortality, the debt. If the debt lasts for a long time, the anger lasts for a long time, and then you're now immortal in the minds of many. You arouse emotion in the minds of many. My mother's best friend in the town I grew up in, her husband shot himself in the driveway, and my mother's friend never got a chance to just grieve, because he owed so much money, she would come over and go, I hate him. I fucking hate him. And it was just such an interesting thing to see somebody who... And her kids ended up getting angry at her for that, because they didn't understand why she would hate a guy who was clearly suffering. But she goes, he took the selfish way out, he fucked us. And it was always interesting for me to just remember that you can leave Earth and still be a problem. That's kind of a special person, so that's, I think, what I'd like my tombstone to read. Yeah, there's a show called Louis with Louis C. Cannon, if you watched it. Yes, I'm aware of it. There's this moment, I think, where an old guy's talking to Louis about, the best part about love is after you break up, and it's remembering that, like, remembering the good times and feeling that loss, the pain of that loss. The worst part about love is when you no longer feel that pain. The pain of losing somebody lasts longer, is more intense and lasts longer than the actual love. So his argument was like, the pain is what love really is. Wow. In the same way that anger, your tombstone, what arouses, will last longer. And that's deeply like a human thing. Like, why do we attach happiness to the way we should remember others? It could be just anger. I know so many people who will have deeply complicated feelings when... I did drugs for many years, so, and I spent time with some wild people. And their parents were also wild people. And some of their parents have done crazy things to them. And, you know, have created situations that were not productive for child rearing. And so I know that when those people die, it's going to be a very mixed bag. Like, there's going to be a lot of complex emotions, like, hey, we loved that guy. But also when we look back, he was a horrible father, a horrible husband. But he was fun. And we don't put enough stock in that, but there will be a push and pull. Yeah. And I'll be the one kind of bringing up like, hey, he was a lot of fun. He was a lot. Remember when he stuck us, you know, one of the things, this particular person I'm talking about, we were at a bar, me and my friend were there, we're having dinner, and his father, who was, you know, an alcoholic, you know, a guy that would go out every night, didn't work, you know, refused to work, would lie and say he was going to work, and then go to a bar. I mean, just a fun person. And we were sitting at this bar restaurant, and the bartender, we see his father walk up to the bartender and say, point at us, point at our table, and go, and put the thumbs up. And the bartender nodded. And then the father walked over to our table, and he said, listen, I just want to let you know, I just bought you dinner. And I looked at his son, I said, he's a pretty good guy. And then he climbed over the little fence down to the water, got in his little boat, it was a little cigarette boat, and he just drove away. And then about an hour later, we went, we said, I think that guy took care of the bill. But she said, well, go talk to the bartender. So we talked to the bartender. And he goes, he handed us a bill. And the bill was for like $1,000. And we said, wait a minute, what the hell's going on? And he goes, the guy that left an hour ago said you were going to take care of his bill. He's been drinking here all week. And we go, what are you talking about? And he goes, remember, he pointed at you, he put the thumbs up, and you guys waved? You remember that? And we went, yeah. And I just looked at my friend, and I went, you know, your dad is just, we're going to remember him for all kinds of reasons. But to you, he was fun. He was a lot of fun. He wasn't my dad. But I spent a lot of time with him. I was in two boating accidents with him. You know, two boating accidents. Alcohol involved, drugs involved? Yes, usually alcohol was involved when he left his house. And when he was at home as well. But I was in two boating accidents. And do you know how fun someone has to be to get in a second boating accident? Do you know what a good time someone has to be to get in a boat with them after you've already gotten in one wreck? Never get fooled again. What was that line? George Bush, never get fooled again. Right. Yeah, so if you're getting fooled again, you know, there's a reason for it. But he was a fun guy. He did have a death wish. The second boating accident, he grabbed me and said, you can't hang out with me anymore. And I said, why? He goes, I'm trying to kill myself. And I was like, oh. And then I understood that like, oh, the fun, under the fun lived a very destructive person who not only was destructive, but wanted to die. So speaking of fun people that want to die, I don't know if you're, we can go Hunter S. Thompson, but Charles Bukowski, I don't know if you're aware of the guy. I'm aware of him, sure. I've read some of his stuff. So his tombstone says, I just want to ask you a question about it. His tombstone says, don't try. Interesting. What do you think about that advice as a way to approach life? I think for many people, it's a good advice. Because the people that are going to try will do anyway. And the people that need to be told, there's a whole cottage industry now of motivational speakers and life coaches and gurus that tell people that they all have to own their own business and be their own boss and be a disruptor and get into industries. That's incredibly unrealistic for most people. Most people are not suited for that. And the Gary V's of the world that tell everybody that they should just hustle and grind and hustle and grind. They're very light on the specifics of what they should actually do. Yeah, I think a lot of people, that's not horrible advice to give to a lot of people. I think my generation got horrible advice from our parents, from our teachers. And that advice was follow your dreams. And nobody, and that was it, by the way. There was no like, what are your dreams? Are they realistic? What happens when they don't work out? Will your dreams make you happy? Are your dreams real? Do they exist on earth? Can you follow, anybody who follow your dreams, you can be anything you want to be. Horrible advice. Horrible advice. Worst advice you could ever give a generation of people, really, truly. I mean, think about it. If you were talking to somebody and you were trying to make them succeed, are there any two worse pieces of advice to give them than follow your dreams and you can be anything you want to be? Those to me are the two most destructive pieces of information I've ever heard. So let me push back because- Okay, that's fair. Many people do. So yeah, this is like a rigorous journalistic interview. Larry King, by the way, passed away today. So I'm taking over the- It's very sad. I'm carrying the- Very sad. R.M.E. King. Yeah. What was I even going to say? Oh, let me push back on the follow your dream thing is I come from an immigrant family where I was always working extremely hard at stuff, like in a stupid way. There's something about me that loves hitting my head against the wall over and over and over until either my head breaks or the wall breaks. Just like I love that dedication for no purpose whatsoever. It's like the mouse that's stuck in a cage or whatever. And everybody always told me, my family, the people around me, the epitome of what I could achieve is to be a stable job, the old lawyer, doctor, in my case it's like scientist and so on. But I had these dreams, I had this fire about I love robots and that nobody ever gave me permission to pursue those dreams. I know you're supposed to grab it yourself. Nobody's supposed to give you permission. But there's something about just people saying, fuck what everyone else thinks, like giving you permission, a parent or somebody like that saying, do your own thing. Go become an actor, go become, do the crazy thing you're not supposed to do, an artist, go build a company, quit school, all that kind of stuff. That's to push back against the, follow your dreams as bad advice. In mass, if you were to look at statistically how few people that works out for, I'm just, no, but let's be very honest. Be very honest. So I mean, like, yeah, if you're going to go be an actor, hey, I was broke for 10 years before I was making money as a comedian. I get it. I didn't need Gary Vanyerchuk to tell me to follow my thing, right? And here's the other thing. I was kind of funny and like, I was kind of, a lot of things were in my favor of being a comedian, right? I had this kind of crazy fucked up life. I had a lot of stories. I had exhausted, I was willing to fail. I had failed before. I was broke. I didn't care about being broke. I knew how to be broke. I was shameless to a degree. I would get on a stage night after night and be laughed at. I had a high threshold for being embarrassed. I had a high threshold for people thinking that I was a scumbag, right? And showing up at family parties and being like, yeah, I still really don't have a job. And I work at comedy clubs, kind of, and I get booked when I can. And I was you know, suited for it. There's this idea that people can just roam around the world injecting themselves into other things they have no aptitude for at all. And will that to happen? A small percentage of people might be able to do that. But the vast majority of people have something they might key into that they're meant to do. Like you loved robots, you love technology, and you found a place in that world where you thrive. But I think many people, a lot of people love robots, right? So a lot of people think everything you do is interesting. I think your shit is fascinating. I watch your podcast and I think it's very interesting. I have no place in your world. You know what I mean? I have no place in that world. I don't like remedial math. I don't like community college math. I think it's a waste of my time. What do you think about robot? Would you ever buy a robot for your home? Yes. What will it do? I'll be a companion, a friend. Oh yeah, I mean, I would like to start replacing friends and family with robots immediately. Okay. I mean, truly. Truly. I mean, I'm not even kidding. I would like to have a Thanksgiving with four robots. I'm dead serious. Are they into QAnon? When do the robots start going crazy? That's my question. It's like, how long do the robots live with me before they are also a problem and I got to replace them? You know what I mean? You're going to indoctrinate the robot. Yeah, the robot's going to call me like my aunt does and talk about coronavirus for an hour every morning and tell me everyone in America who's died of coronavirus. One of the things I enjoy in life is how terrified people like you, I'm a huge fan by the way, get a robot. Well, I'm concerned about AI completely getting rid of the need for human beings because human beings, I mean, you go out in the street and you go, so few of these people are necessary. Even now, even now you look at people and you go, they're hanging on by a thread, right? And you can just imagine how many jobs are going to get replaced, how many industries are going to be completely remade with AI and the pace of change worries me a little bit because we do a very bad job in this country of mitigation when we have problems. We don't do a great job. We did a not great job with COVID, right? We don't do a good job. It's just something we don't do well. We're good in booms and busts. We're good when it's good and we're actually, we kind of know how to kind of like, hey, we're bottomed out. We're like a gambling addict in this country. We like, we know what it feels like to be outside of an OTB at 9 a.m. drinking coffee and smoking cigarettes going, I'm going to build it back. And we know what it's like to win, but anything in between, it seems not that great. So to me, it feels like, are we going to be able to like help people that are displaced and that have their jobs taken by, I mean, do you not fear sort of a world where you have a lot of artificial intelligence replacing workers and then what happens? There's a lot of fears around artificial intelligence. One of them is yes, displacement of jobs, workers, that's technology in general. That's just any kind of new innovations, displaced jobs. I'm less worried about that. I'm more worried about other impacts of artificial intelligence. For example, the nature of our discourse, like social, the effects of algorithms on the way we communicate with each other, the spread of information, what that information looks like, the creation of silos, all that kind of stuff. I think that would just make worse the effects that the displacement of jobs has. I think ultimately, I have a hope that technology creates more opportunities than it destroys. I hope so too. So in that sense, AI to me is an exciting possibility. But the challenges this world presents will create divisions, will create chaos and so on. So I'm more focused on the way we deal as a society with that chaos, the way we talk to each other. That's huge. Creating the platform that's healthy for that. Now as a comedian, creator, whatever you want to call it, people that put out content, the gatekeepers are now algorithmic, right? So they are kind of almost AI ready. So if you are a person that puts out YouTube videos, podcasts, whatever you're doing, it used to be a guy in the back of the room with a cigar saying, I like you or get him out of here. Now it's an algorithm you barely understand. I've talked to people at YouTube, but I don't know if they understand the algorithm. They don't. They don't. And that's crazy. This is fascinating. Yeah, it's fascinating. Because I speak to people at YouTube and I go, hey man, what's going on here? One of my episode titles of my podcast was called Knife Fight in Malibu. It was about real estate. And it was because a realtor in Malibu, I was trying to get a summer rental, which I can't really afford, but I don't think that's a huge problem. I follow my dreams. So I called a realtor and she said, listen, she goes, I don't know what the government's saying, but she goes, it's a real knife fight out here. An old grizzled woman, real realtor, tan skin, cig out the mouth, driving a Porsche. It's a real knife fight out here. Her entire life had become real estate. Her soul had been hollowed out. Her kids hate her. No one's made her come in years, but she just loves heating kitchen floors and views. Fun. She's a demon from hell and we need them, truly. We're getting rid of them. It's not good. And she goes, it's a real knife fight out here. So we put that in the episode title. And of course, I guess some algorithm thought that we were showing people stabbing each other in Wendy's and we got demonetized. Did we get demonetized? We didn't get demonetized, but we lost like 80,000 views. We lost a lot of views because we were kicked out of whatever, we were just kicked out. And I was asking YouTube about it. They were kind of understanding it, but even the people that worked there didn't truly seem to understand the algorithm. So can you explain to me how that works where they barely know what's going on? No, they do not understand the full dynamics of the monster or the amazing thing that they've created. It's the amount of content that's being created is larger than anyone understands. This is huge. They can't deal with it. The teams aren't large enough to deal with it. There's special cases. So if you fall into the category of special cases, we can maybe talk about that, like a Donald Trump, where you actually have meetings about what to do with this particular account. But everything outside of that is all algorithms. They get reported by people and they get, like if enough people report a particular video, a particular tweet, it rises up to where humans look over it. But the initial step of the reporting and the rising up to the human supervision is done by algorithm and they don't understand the dynamics of that. Because we're talking about billions of tweets. We're talking about hundreds of thousands of hours of video uploaded every day. Now, the hilarity of it is that most of the YouTube algorithm is based on the title. That's crazy. And the description is a small contribution in terms of filtering, in terms of the knife fight situation. And that's all they can do. They don't have algorithms at all that are able to process the content of the video. So they try to also infer information based on if you're watching all of these QAnon videos or something like that, or Flat Earth videos, and you also watch, are really excitedly watching the whole knife fight in Malibu video, that says, that increases the chance that the knife fight is a dangerous video for society or something like that. Interesting. Wow. Based on their contribution. So people are watching something, because I watch QAnon and Flat Earth videos to ridicule them. Right. You know what I mean? I watch these videos and I make fun of them on my show. Yeah. But what's interesting is if I then go watch something else, I'm increasing the likelihood that that video is going to get looked at as potentially subversive or dangerous. Exactly. That's wild. So they make decisions about who you are as a human being, as a watcher, the visual user, based on the clusters of videos you're in. But those clusters are not manually determined, they're automatically clustered. It's so weird. We have titles where they got upset about, and I don't even understand. Like, we had a title that was so innocuous, in my opinion, and the title of the episode was called Bomb Disney World. And I was asking people to consider bombing Disney World, and YouTube got angry at that. So you don't know why. You can never understand why. You could have said Disney World is the bombs. Right. Right. It's just rearranging. That's what it probably meant. I wasn't saying to do it, but I was saying let's start thinking about plans to do... Not let's do it, but let's get in the mind. Let's change the conversation. I think it's very interesting, because as a comedian, you don't want to live in that world of worrying about algorithms. You don't want to worry about deplatforming and shadowbanning. I mean, all these conversations that I've had with other comedians about shadowbanning, I mean, it's hilarious. We all call each other, I think I'm being shadowbanned. Are you being shadowbanned? And nobody knew what that word was a month ago, I mean, a year ago. But everyone now is convinced that everything they do that isn't succeeding is being shadowbanned. So it's this new paranoia, this algorithmic paranoia now that we all kind of have, because there are genuine instances of people being taken out of an algorithm, you know, rightly or wrongly, however you want to believe. But then there are also things that just don't perform as well for a myriad of reasons. And then we're all saying like, well, they're against me, they're shutting me down, and you don't know if that's true or not, you know? What do you think about this moment in history, which was really troubling to me? We could talk about several troubling aspects, but one is Amazon removing Parler from AWS. To me, that was the most clearly troubling. It felt like it created a more dangerous world when the infrastructure on which you have competing medium of communications now puts its finger on the scale, now influences who wins and who loses. Absolutely, you're right. And what you're always told is like, if you don't like Twitter, create your own service. Or if you don't like something, you can do your own thing. And basically, because tech, you have to be in business with one of five companies, I think it's like Amazon, Facebook, Google, YouTube, and Twitter, whatever. I mean, Amazon puts everything on the cloud, Google and YouTube, it's all basically the SEO and the advertising, and you got to get your name out there, you don't want to be buried. Because you have to do business with those, it's a cartel of these companies, you understand it better than anybody, that you are prevented, truly. And I think, whatever you think about Parler, whatever you think about what people are saying on Parler, whatever you think about Alex Jones, whatever you thought about Milianopolis, the state has an interest in, and has always had an interest in crushing dissent. This is what the state has done. This is how they retain the power they have, by eliminating dissent where they can. Now, because you don't have three broadcast networks anymore, and a handful of newspapers that were all run, by the way, by people that had been either compromised or happily going with the program, and you have this wild west of the internet, people like me, people that make, I make funny content, that I hope is funny, but a lot of it is wild and crazy. I say a lot of wild and crazy things, they're very funny. I say a lot of wild and crazy things about powerful people. Yeah, you mock the powerful in there by bringing them down a notch. We'll probably talk about it, but humor is one of the tools to balance the powers in society. Well, sure. And to make people feel better about things, and to, you know, whatever the case may be, right? That's my goal, is to kind of like, hey, people have had a shitty day. If this video or podcast makes you laugh, that's great. I think that it was never going to stop at Alex Jones. Not that I think he should have been taken off everything the way he was, but this keeps going until we have sanitized all of social media. And what they really want it to be is what Instagram is kind of becoming, which is a marketplace of, you can just go and buy sneakers, go buy a sweatshirt, go buy jeans, go buy this, go buy that. And the idea of the free exchange of information seems to be the old internet, and it seems the new internet seems to be hyper, and I'm a capitalist, but this seems to be like hyper-capitalist in the sense of like, they only want you consuming things, and they don't want you thinking too much. And that seems to be where it's heading. I've even seen that with Instagram, where it's like, everything on Instagram is like, buy a sweatshirt. You know? And I'm like, all right, man. Hey, man, if I want a sweatshirt, I'll get it. Like, relax. You know? Just every ad seems to be encouraging consumption, but very few things seem geared towards, hey, let's have a dialogue, or let's—and not that Instagram was ever great for that, but like, if everything's geared now towards content on Instagram, a lot of it seems geared towards shopping. See, I don't know—that's an interesting point—I don't know if the consumerism that capitalism leads to is necessarily gets in the way of nuanced conversation. I feel like you could still sell Tim Dillon sweatshirts and have a difficult, nuanced conversation, or mock the current president, the previous president, mock the powerful, all that kind of stuff. Yeah, we try. We try to balance that. I mean— Do you have sweatshirts? We do. Are they on sale now, Fake Business? Yeah, they are. We do. Fake Business sweatshirt with the Enron logo, Fake Business. Because I do fake business all the time. It would be nice if we talk about Alex Jones, if you plug the sweatshirt during that conversation. Yeah, we'll do that. Absolutely. But what I tend to worry about with—I see social media and technology existing to flatten society. It makes people very boring. All of the experiences kids have right now are online. Many of their closest friendships are online. Their first relationships are online. The culture is very homogenous. And I think it's eliminating characters. It's eliminating interesting people. It's making people into AI. All of their tastes— Whoa, whoa, whoa, whoa, whoa. Yeah, yeah, yeah. AI could be Charles Bukowski as well. Let's not get crazy. It's not there yet, right? I mean, the $75,000 dog is not doing anything. So we're not there yet. Listen, I get why you like AI so much. I hate people too. And I'm very amenable to AI. And I agree with you. Listen, I think the future—we got to get everyone out of here. I'm with you on that. So don't think I'm— I love people. He's manipulating my mind and my— That's why the flash of light in your eyes when you talked about that dog was so much more than any person. And I get it, by the way. You're right. I love people, but if we could just— They're not exciting. If we could just use robots to kill most of them, I think that would be good for society. I'm with that too. But I think that social media flattens people. Flattening the personalities of characters. Flattening the personalities of people, man. And it's just—when's the last time—I like the idea of like—and somebody showing up to high school with a backpack and taking out an old CD and being like, hey man, here's this band you've never heard of that I love or whatever. You got to get into this. And I'm like—when I talk to young—I have friends that have younger brothers and everything. And I know that the dominant culture was always dominant. I'm not an idiot. But I feel like it's harder to be unique and original now because so much of what's promoted is just this way to kind of corral people into believing and thinking a certain set of ideals that's constantly shifting and evolving. And people are just caught up in that. And to me, it gets very boring very quickly. I hate being bored. And that's what it is. I don't know what to do with that because at the same time, podcasts are really popular. Long-form podcasts are really popular. That's true. And people are hungry for those kinds of conversations. There's a lot of dangerous ideas, quote-unquote, flowing, being spread around through podcasts, meaning just like debates. Correct. So that's still popular. So I don't know what to— I agree with you. That gives me hope, I guess. I hope so, too. And like I said, I look at the negative a lot because that's what I usually make fun of. But there's a lot of positive stuff happening, too. Let's talk a bit about Alex Jones. So you've gotten a chance to talk to him while you were on the Joe Rogan Experience. I've been on Alex's show. I've had Alex on my show. I've talked to Alex for three hours in front of—I guess it was maybe like 15 million people, right, on Joe's show. It was a really wild conversation. I think it was one of the coolest moments in broadcasting, clearly, that I've ever been a part of. But I think it goes in the lexicon of like, these are big podcasts. I think it's one of the biggest podcasts. A week before the election, Alex Jones. I'm really grateful that Joe gave me the opportunity to be there. And it was just an amazing conversation to watch. What was the shirt you wore, Julian Maxwell? Free Just Lane. It was a fun joke that no one in tech got because we all know how funny they are. But the tech writers, which is mainly blue-haired— I do not agree with the statement. They're mainly blue-haired people whose goal in life is to find things to give them orgasms. If you want to dye your hair blue, it's your choice. I respect it. Is it your choice? But at the end of the day, it's like, all the tech writers, a lot of people just—and I'm just maligning tech unfairly, but a lot of people that sense of humor were like, he's advocating for human trafficking. It's clearly a joke because we're coming off the Believe All Women. We're coming off that. And it's very funny to just say, Free Just Lane, hey man, Believe All Women. Our politics and our public sphere is so schizophrenic right now that when you point that out, people are going to be angry with you. But that was a fun shirt to wear. But on Alex, I was one of the people that found him really entertaining. The same kind of thing as with Bukowski, these kinds of personalities that are wild, crazy, full of ideas. They don't have to be grounded in truth at all, or they can be grounded in truth a little bit. He's just playing with ideas like a jazz musician, screaming sometimes. Obviously he has some demons. Sometimes he's super angry for no reason whatsoever. It's some weird thing that he's constructed in his own head. Sometimes he's super loving and peaceful, especially lately that I've heard him. I don't know if you've seen him with Michael Malice where he's doing—Malice was doing, like, telling Alex Jones, I love you, Alex. Just this loving kind of softness and kindness underneath it all. I don't know what to make of any of it. And then there's this huge number of people that tell me that Alex Jones is dangerous for society. So what do you do with that? Do you think he's dangerous for society? Do you think he is one of the sort of entertaining personalities of our time that shouldn't be suppressed or somewhere in between? I don't think that Alex per se is dangerous for society. I think the greater danger for society comes, again, from stifling all dissent, right? Like anybody with a voice that uses it, that critiques the government, and putting all of those people in a category and getting rid of them is incredibly dangerous, to me, more so. I think the biggest problem that Alex has ever had was when he questioned the Sandy Hook shooting. And that really was—because it really is this identifiable incident that you can look at where it did get away from him and a lot of his fans, who—the people that are attracted to conspiracy stuff, and I have some of those fans, some of them are really smart people, some of them are mentally unwell. A lot of them happen to be mentally unwell. So when you have a fan base of people where some of them are mentally unwell, and you are questioning tragic events, okay? And Alex was right about Epstein. He was right about a lot of things, and he's got no credit for that. And I understand that this piece—sometimes when you're right about 10 things and you're wrong about something, and the thing you're wrong about is so offensive to people, you're never going to get any credit for being right, even though you were right more than when you were wrong. The problem was a lot of his fans, who were crazy, stalked, harassed these families, and accused them of being actors, and accused them of faking their children's deaths. It was this horrific experience. And Alex is tied to that. Yeah. And how much he inspired that by what he did on his show, I don't know, because I haven't watched hours and hours of that particular thing, like the whole Sandy Hook thing. If you listen to him, he says, I really covered it, I kind of covered it and moved on. Other people go, no, he spent a long time on it. But that's the real danger of going into that territory over and over again, going everything's a false flag, or everything's fake. I think Alex has actually been kind of reasonable. He's resisted a lot of the politics of racial resentment on the alt-right, for example. He's resisted that. He's resisted the anti-Semitic currents of a lot of that politics, right? He's resisted a lot of the virulently anti-trans or anti-gay stuff. Now, he does dip his toe into the water of the culture wars, of course he does. But I've never really seen him – and I could be wrong about this – embrace white nationalism or identitarianism. I've never seen him really go anti-Semitic. I've never seen him take that route. When I grew up, and I would turn him on every now and then, he was talking about NAFTA, the WTO. He was talking about 9-11. He was talking about the World Trade Organizations and a lot of these big conferences, whether it was the Bilderberg Group, whether it was Bohemian Grove, which he infiltrated. And he was talking about, hey, here are the most powerful people in the world, and here's what they're doing, and here's how it affects you. And that was interesting to me, because no one else was really talking about it, except Alex Jones, occasionally Art Bell on WABC. You'd listen to him at night, right? I think Alex became very controversial when he decided to back Donald Trump. And then he has a considerable following and a considerable audience that he was then able to marshal in the direction of supporting Donald Trump. That was when the spotlight, because then he was talking to Trump, Trump did his show, Alex Jones just got bigger, right? And he blew up. That's the term, right? He blew up. He put out the good HBO special, whatever you want to call it. He has a hit song. He blew up. And then people started looking at the things that he was associated with. The Sandy Hook thing is a blemish on his record. I do believe he regrets it. But again, I do see the point of the families who are like, dude, fuck this guy forever. This is the worst thing I ever went through. It's a very tough... I understand the people that say that. I understand, and I understand the people that go, when you have tech companies that act in a coordinated manner to just get rid of someone, they don't have any way to defend themselves. It's a little terrifying when you think about that power being abused, and how wouldn't it be? Do you think he should not have been banned from all these platforms? I don't think... I do think that if you are a private company, right? I do think, and this is where you run into this problem. I don't know if these tech companies were government utilities, would that decrease people's likelihood of being banned? I don't know, right? So I understand the benefit of them being treated like public utilities and people thinking they have the right to a Twitter. I've never... I don't know. I have very little confidence. I mean, the government's trying to roll out a vaccine in California, and we vaccinated five people, I mean, in terms of what we need to do in the state, right? So maybe if it was a government utility, I do think someone like Alex Jones... There should be some process. So if you're going to get rid of someone, they should have a way to defend themselves. There should be more democratic process that you can go through than just being unilaterally taken off something. But like, then you run into the... Am I going to say that everyone deserves... No, if you're threatening or harassing people or threatening to kill them, publishing their private information, if you're committing crimes on these platforms, obviously the people that own these platforms are going to be like, we're not going to allow this to happen. So I understand that there is a line, right? There is some... People that say there's no line aren't really thinking. There is a line, there is a line. I just don't... That line seems to be moving all the time, and it seems to be a very hard thing to police. But I don't think you can remove a guy off everything, and then also, bank accounts won't give him debit cards or credit cards. I don't know if you talked to him about that. But there were financial institutions that were refusing to let him park his money there. So I mean, it really does get pretty terrifying pretty quickly. Probably without any transparency from those companies. So you're right, it feels like there should be a process of just having... For him to defend himself? I think there needs to be a process for people to defend themselves. Every day I wake up and I go, is something I said in a video going to get taken out of context? Is somebody going to get angry? Is somebody going to be... I say wild stuff, because that's what makes me laugh, that's what makes my friends laugh, and that's what makes my audience laugh. So I never ever... People, whatever political side you come down on, I think if you make your living speaking, it's always interesting to me if you are pro the deplatforming. That's odd. It's interesting to consider a kind of a jury context to where there's transparency about why your video about bombing Disney World might be taken down. It gets taken down, and then there is, it's almost like creating a little court case, a mini court case, and not in a legal sense, but in the public sphere. And then people should be able to have... You pick representatives of our current society and have a discussion about that and make a real vote. Jury locks himself up in a discussion. That kind of process might be necessary. Right now what happens is Twitter is completely... First of all, they're just mostly not aware of everything they're doing. There's too much stuff. But the stuff they're aware about, they make the decision and close doors, meetings, and without any transparency to the rest of the company, actually, but also transparency to the rest of the world. And then all they say is, we're making these decisions because the people, they use things like violence. So violence equals bad, and if this person is quote-unquote inciting violence, therefore that gives us enough reason to ban them without any kind of process. I mean, it's interesting. I'm torn in the whole thing. There's no transparency about it, but if Parler was indeed inciting violence, like if there was brewing of violence, potential violence where thousands of people might die because of some kind of riot, this is the scary thing about mob, about when a lot of people get together who are good people, like legitimately good people legitimately good people that love this country, that don't see enemies yet around them. But if they get excited together, and there's guns involved, and then some cop gets nervous and shoots one person, another person shoots the cop, and then there's a lot of shooting involved, and then it goes from five people dying in the Capitol to thousands of people dying in the Capitol. Well, in fairness to defend the people of the Capitol, they didn't shoot the cop, they bludgeoned him to death with a fire extinguisher. So I do want to just put that out as a defense of them. Listen, I'm sure there was some wild shit going on on Parler, and I think here's the problem, right? There's a lot of people that just want to go on these sites and say they want to kill everyone. And the problem is, at what point do you shut them all down? I think a lot of people are just living in a world where they're powerless. They don't have any political power. They don't have any economic power, right? They can't throw their money around. They don't have healthcare. Their job security isn't great. They might be living in a community that doesn't have the resources they would like it to have. They're not happy and thrilled. And then they have these sites where they can go on and just say, man, I'd like to fucking burn it all down. And distinguishing a guy blowing off steam and saying wild stuff from a genuine threat is a very hard thing to do. I've threatened to kill... I got banned from Airbnb. I threatened to kill the people that banned me comedically. Comedically. This is a joke. I'm not going to kill you. This is a joke, because I'm blowing off steam and I'm angry. Do you know how many people that my parents... My dad's like, I'm going to fucking kill this guy. My mom's like, I'm going to fucking kill... They were talking about each other. But none of it ever happened. But we should be... I think you have to create a space for people to threaten to overthrow the government as long as they don't violently do it. Does that make any sense? As long as they're not going to go hurt innocent people, what are you going to do? There's so many people out there that... That's why a lot of these things like 4chan, these sites, a lot of people going on there, they just want to say the most fucked up shit, because it's the thing that gives them... They can laugh or they can release steam. It is immature. It is stupid. It's not productive. But at the end of the day, if you're not going to give people health insurance, you got to give them something. It's like when someone in this country dies that everyone disagrees with, right? Political figure, media figure. A lot of people dance on their grave online. And then everyone, people goes... And the other side will always do it. If a conservative dies and everyone goes, great. Conservatives goes, this is grotesque. And then when RBG dies, they all have parties and the conservatives go, great. You have to let people in this country enjoy the deaths of their enemies. Yeah. You do, because they don't have much else. Again, if you gave them other things, you might say, guy, you can go get a knee operation. Why don't you stop? But if they're working for shit wages and you haven't figured out a way to treat them, treat their cancer diagnosis, and they don't... I mean, life, you got to derive pleasure from something, right? Yeah. It's an interesting point that anger is a good valve. If your life is suffering, that there's something very powerful about anger, but I still have hope that it doesn't have to be. I mean, that kind of channeling into anger that then becomes hate led us into a lot of troubles in human history. So, you have to be careful empowering people too much in that anger, especially... I think I understand why people were nervous about Parler, about Twitter and so on. Sure, yeah. Because all that shit talking about violence was now paired with, let's get together at this location. This was a new thing. It's not just being on whatever platform talking shit. It's saying, we're going to, in physical space, meet. And then everybody got... All these platforms got nervous. Well, what happens when all these shit talkers, all these angry people, they're just letting off steam, meet in a physical space? And there was probably overreach, almost definitely overreach, but I can understand why they were nervous about it. I agree. There doesn't seem to be... And this is when Trump got elected and when you have whatever you have, right? Whether you have riots in Portland and Seattle, where you have the Antifa people doing crazy things, you have the people storming the Capitol. There never seems to be a ton of an examination of why these ideas are becoming popular. Why are people so angry? What is leading people to this? Why are we here? What about their lives is to the point where they need to show up at these places? And obviously, there's always going to be people on the fringe. There'll always be the mentally unwell. There'll always be people that want to destroy society. But when you look at how popular large, long discredited things, whether it's fascism, totalitarian communism, all of these things are like, why are they back? Why are they back in a big way? And why are people so fed up with the status quo that they're finding solace in the most extreme discredited theories of how to run and operate societies, theories that have led to deaths of a lot of people. So to me, I'm like, if those people at the Capitol, yes, if they were going to work, if there's, you know, if they were able to go out and drink at Chili's, if they were able to get a fucking checkup, right, like, if their job paid a little bit better, and I'm not saying that this is all the reason, right? I'm sure that there's a lot of people there that are doing quite well, and they're still nuts. But like the anger and the rage that's boiling to the surface of this society, does it come from the fact that across the board, people in very different areas and with very different political beliefs feel like they are being fucked over, and there's nothing they can do about it. That's what the baseline to me, they look at the people that run the country and run the world, whether they're tech titans, the guys that you talked to, or whether they're people that run the government, whether they're people that run large banks, large media companies, the people that have created this kind of, you know, infrastructure that everyone lives in, these people are incredibly powerless. And when you push people to that point, logically, sadly, and unfortunately, the next thing does seem to be violence. Yeah, the thing that troubles me a lot is you said, nobody's asking why these beliefs are out there. But sometimes it's not even acknowledged that people are hurting people, are angry, just even acknowledging that all the conspiracy theories that are out there, acknowledging that they're out there, and then people are thinking about it and talking about it just because otherwise, so it's not acknowledged in this nuanced way. What happens is you say, okay, 70 million people are white supremacists. It's just throwing a kind of blanket statement. And of course, that gets them angrier, and makes them feel more powerless. And that, ultimately, that's what's been painful for me to see is that there's not an acknowledgement that most people are good. Right. And there's circumstances where it's just, you're pissed off. Right. Because you are powerless. I mean, most of us are powerless. You could fall in with a bad crowd. That's the thing. You can just fall in. Yeah. And it doesn't mean that there's not blame. You know, obviously, you have agency, you're a person. But the idea that you could be rehabilitated, you could do something stupid, or you could fall into a group of people that are... And then in a few years, you could go, what the fuck was I doing? I'm an ex-drug addict. I know what it's like to go from being one thing to being another thing. Right? I'm still a drug addict. If I were to use drugs right now or drink, I would still be addicted to them. Right? I mean, it's not something that I can ever change about myself, but I know what it's like to go from one thing to another thing. So when you look at racism, or whatever, ism, homophobia, misogyny, whatever you're looking at, anti-Semitism, and you go, that's a fixed condition where nobody's ever going to be able to change. Nobody's ever going to be able to be rehabilitated. Nobody's ever going to be able to reimagine themselves in a different way. To me, you're just, you're throwing away someone, and you're making them feel helpless and worthless. And that's going to lead to anti-social behavior that spills out into the vials. We don't have a very redemptive society. Right. That's a huge factor. We don't have a redemptive society. That's why I like OJ Simpson, because OJ Simp... Yes, he did a bad thing, supposedly. Allegedly, yeah. But he's very kind now on Twitter, and he makes very nice points about how we all have to get involved in the political process, and he's on golf courses. And I like watching people golf. I don't do it, but I like watching him do it. And he's like an elder statesman, because I remember him from The Naked Gun. And I choose to forgive him for whatever happened there, which I don't know. But I choose to forgive him really for... I mean, obviously, what they say is he cut his wife's head off. But I can look past that and redeem him, because he's very stable on Twitter, and he's a good... I see all these people going crazy on Twitter, and I'm like, there's maybe... OJ's lived a full life. I think there's a benefit to that. There's a benefit to living a full life. Yeah. How many of us have not at least tried to murder somebody in the past? 100%. Listen, OJ's had the highs and the lows, but he did it on his terms. And there's a real... It's like a Frank Sinatra song. Yeah, he did it my way. I mean, there's a benefit to that. And he seems like a very well-adjusted person now. So, I mean, I don't know. How is that a fact? But it is a fact, and that's an uncomfortable fact. Well, that's a strong case for forgiveness in one of the more extreme cases, I suppose. But yeah, there's not a process of forgiveness. It seems like people just take a single event from your, sometimes a single statement from your past, and use that as a categorical capture of the essence of this particular human being. So, murder might be a thing that you should get a timeout for. A little... Murder's bad. And let's just say that. Murder is not good. Well, I'm glad you make this definitive statement. It's a controversial... OJ's an interesting cat, because you're like, he's very stable on Twitter. He's very like, he's like, let's take a look at it, guys. We need more of his energy. That's what I'm trying to say. Yeah, yeah. I know, like, yes, it was bad. He killed the woman and the waiter. I was not for that. I wish he didn't do that. But the OJ Simpson trial was such a fun thing. Yeah, and like you said, we need more fun people in society. Well, we might. Speaking of fun people, your politics have been all over the place. I hope so. I hope so. Imagine someone whose politics weren't all over the place. It would seem odd. Right. In the 10 years that I've been politically conscious, just because I'm 35 and 20, no, I've probably been conscious for over two decades, but like, Democrats have become Republicans, Republicans become Democrats. I remember when Ann Coulter said we need to defend George W. Bush, when he said we need to go out and Christianize or modernize the Arab world, we need to democratize the Arab world. And then Ann Coulter backed Donald Trump. And all the right wing in America believed in nation building. They believed in going out and democratizing areas that might breed radical terrorists, whether it was Iraq or wherever you were going, toppling regimes and instituting new democratic norms in those countries. That was the right wing point of view when I grew up. Then the right wing switched to, we are going to be isolationists, we're going to take care of America, first and foremost, we're not going to go into other countries. And then the Democrats, who when I grew up were doves, and the right wing people were more hawkish, and the Democrats were like, the military solutions aren't the way. We need to have multilateral diplomatic coalitions to solve all the problems. Now, Rachel Maddow's like, let's nuke Russia every night on MSNBC. The Democrats are like, we need strong presence in Syria, we need a strong presence, we need to counter Putin all over the globe, we need to get... So they're more hawkish on things. So literally, I have watched two political parties literally flip. And it's crazy to watch. And in some sense, I've watched that as well, because when I first saw Barack Obama, I admired that he was against the war. This is whatever, maybe before he was a senator, he spoke out against the Iraq war. And then, you know, it doesn't feel like... It feels like his administration was more hawkish than dovish, in a sense, with all the drone attacks, with the sort of inability to pull back, or at least en masse, efficiently pull back from all the military involvement that we have all over the world. And just the language. What I think is interesting about that, what's interesting about Obama, because it's a very interesting study, is that presidents are controlled in very different ways, right? Presidents can be controlled by different factors, power factions within Washington. I think one of the reasons that Obama was maybe... He had a very close relationship with John Brennan, who was the CIA director. And Obama was very close with John Brennan. And Obama was very, I think, malleable to the extent that the CIA... And I've had CIA agents on my show, John Kiriakou, a guy who went to jail for exposing torture, was saying that, like, you get into the Oval Office, all of a sudden, you're having that presidential daily briefing every day, and the intelligence people come in, and they go, listen, man, I mean, there's going to be a terrorist attack on your watch if you don't do X, Y, and Z. They go, we have... They call it blue book information, which is five levels above top secret. And they go, hey, man, a guy in Iran at a cafe said he's blowing everything up next week. And it's the same thing as parlor. You don't know if it's true or not. But now the president's making a decision on, usually, a lot of uncorroborated intelligence that goes into a presentation for the president, where you're just terrified every day, and you don't want a terrorist attack on your watch. Now, so why are they getting all this information? Because a lot of the people in Washington have an interest in perpetual, constant, ongoing warfare, right? And there's a lot of financial gain to be had from that. So they're sneaking their information into the presentations that are going to the president, and then the president is now behaving and going, fuck, I don't want a bomb going off. We got to do what we got to do. And whatever version of that happens, that is really kind of what is happening. Whereas the presidents are being controlled by forces that are outside of the political sphere, but very much still in it, and they have a lot of power. That's what the deep state is. There's a lot of ridiculing Trump of going, oh, the deep state doesn't exist. It absolutely exists. There's been books about it written by liberal journalists. The deep state is only a term for unelected, largely, power factions in Washington, DC, that outlive any presidential administration. These are people that might work at the State Department. They might work at the Defense Department. These are people that are not always working officially in any government capacity. They might be private companies. They might be military contractors. They might be people at Boeing or Raytheon or General Dynamics. And they constitute a group of people that Trump kind of called the swamp, but Trump had really no interest in draining the swamp. He articulated these things, and this is what it is. You have a lot of interested parties that have budgets that they want, big budgets. Everybody wants a budget in Washington. What it is, they want money. And these are the people who really control presidents. So this idea that the president is the Beale-Endall has got to be smashed, which is why the horse race model of politics and being like, is it right wing? Is it left wing? Is it what team am I on? And what color am I wearing? It's very simplistic, but the reality is this is an empire. It's past its peak. We're in trouble. The United States is an empire past its peak. Yeah. I mean, that's just his – you could prove that case in court. Well, let's go to court right now. But I do love the more complex idea that there's just human beings who crave power and seek ways to attain that power through different ways. If you have Barack Obama or George Bush or Donald Trump, there's different attack vectors, different ways to attain that power, and then you can use that to leverage. And it probably doesn't have to be just in Washington, D.C. There's people who crave power all over the world. Of course. But where we are now in Los Angeles, these people are all good. LA. Studio executives are people that, from what I understand, they treat everyone fairly and they're nice. But D.C. is the bad guys, but out here in LA – West Coast. Everyone's lovely. So amidst this fun exploration in your mind through the political landscape that you've done over the past decade that you've been conscious politically, where does Donald Trump fit into this picture for you? Is – Great question. Well, he didn't, right? Because he wasn't political until four years ago, right? He got political very quickly before – I mean, he was always firing off crazy tweets about where Obama was born or whatever, but he got into politics very quickly, and then he became the president, right? So I knew him as Donald Trump, this crazy New York City character, the host of The Apprentice. I didn't think much about him. He was just constant. He was just this constant figure. I don't think much about Warren Buffett. I know Trump's like – he's married to a new showgirl all the time, and he's always opening another casino, and he's on TV. Wait, Warren Buffett, really? No, Trump. Trump. Oh, Trump, okay. But Warren Buffett is the opposite, right? Warren Buffett's been married for a million years, lives in a little house in Omaha. But that's what I associate Trump – I don't think about Warren Buffett. I don't think about these people. They're just guys that I've known forever that have like a – you associate certain things with them, right? And Trump, we always associate him with kind of vulgar, garish, new money, billionaire, married a lot, casinos, Miss Universe pageants. But again, but it makes perfect sense that he really was able to become president at the moment where we were about to have Hillary Clinton versus Jeb Bush. And I think Americans felt like this is – now the oligarchy is spitting right in our face. You're not even making it feel like there's an appearance of democracy. We have two crime families vowing for control of the country every four years. And then there was this rogue kind of upstart guy that was really about himself. Trump doesn't really care that much about the – I mean, really was summarized perfectly when he left, and he just said, hey, have a good life. That's what he said before he got on Andrews Air Force Base. If you watch his speech, he goes, hey, have a good life. That's what he really feel, like, hey, have a good life. I'm going to get on a plane right now and fly to a castle I own in Mar-a-Lago in Florida, and really I'm not going to think too much about you people outside of how I can get more attention in the future. Can I ask you like a therapy question? Yes. What is your favorite and least favorite quality of Donald Trump? So my least favorite quality of Donald Trump, I think, because there's a few of them, his lack of empathy, complete and total lack of empathy. I don't feel that he cares about human beings on any level, and I feel like that's maybe or should be a requirement, right? I mean, I don't think he cares. I think it's obvious that he doesn't care. I mean, he's saying like, they're in there, Mike Pence is in there, he knows that his people are going to try to get into a Capitol. I mean, those motherfuckers are not going to have jobs, they're going to go to federal prison, and he doesn't care. He doesn't care. As long as they're storming the Capitol to prove the point that he thinks he won the election, he has no concern for these people, his followers. He leads them lambs to the slaughter, right? So that's not a respectable quality. My favorite quality of Donald Trump is his willingness to call bullshit. So his willingness to call bullshit out. He doesn't play the game. When people say about Putin, Putin kills people, he goes, we kill a lot of people here too. He's willing and able to break the fourth wall and say things that no politician has ever said. He's willing to call out hypocrisy, of course not his own, but the media, the members of the political establishment, that's a laudable quality, it's an entertaining quality, right? We all like it. I'm like, this guy's saying something that a lot of people want said. That being said, it's coupled with no real work or action. So it's not coupled with anything behind it that he just wants to – we did an episode on my podcast once where it's like, essentially, he's like, criticizing the deep state, he wants a deeper state. He wants a deeper state, like he hired his daughter and her husband. I mean, this is not a guy that's interested in transparency and openness. He's a guy that would just prefer – he wants to run the mafia state. But he shakes up the norms of social discourse, political discourse, and that people are just hungry for that. Yes. But he got banned from Twitter, from all the different platforms. Do you think – is there an argument to be made for and against banning Trump? There's always arguments to be made for everything. A permanent ban seems to be an overreaction to me. He's the president of the United States. It also rearranges the power, like whether you like him or hate him, love him or hate him, he was the president. We've elevated Twitter as now more powerful than the president. It's like, do you want that to be long-term the salute, the reality? Like now Jack at Twitter is more powerful than the president of the United States. Is that a good paradigm going forward? I don't know. I'm not – listen, maybe give him a little timeout for a few days. I think a timeout – a little spanking, certainly. But I don't know if a permanent ban across the board on every social media – I mean, they banned him on Grindr. I mean, this is how hilarious it is, right? I mean, they banned him across the board on everything. I don't think he can get an Airbnb now. Neither can I. But like I don't think he can do anything. Again, I just – I look back and there's so many people. I have very smart, intelligent friends that go, yeah, but who cares? Yeah, but he's bad. Yeah, but blah, blah, blah. Yeah, but I don't like me, Lillianopolis. Yeah, but blah, blah, blah, blah, and I'm like, you have such faith. You have such faith that it's always going to be the people you dislike that are banned. It's always going to be the – it's never going to be you. Man, you have so much faith in the government. You have so much faith in tech oligarchs you've never met. You have so much faith in the security state that they're going to always make the right decisions and they're not going to penalize people that shouldn't be penalized. To me, I'm like, wow. I've never had that much faith in any human being ever, including myself. I wouldn't want that power. I would start deplatforming people that I hate. I would deplatform my aunt. You know what I mean? I would deplatform everyone I know. I mean, so it's such an insane power to give somebody. Who gets heard? Who gets to speak? Yeah, I'm worried about the effect it has on people like you actually. I agree. Of being – everybody's a little more nervous in what they say. Correct. And that is a big problem. Yes. Because then you're just like long-term unmasked like we were talking about. It has an effect where people just become more bland. Yeah, self-censorship, anxiety, all of these things go into it. We try to fight it. I try to fight it. I think I got to still do what makes me laugh, and what makes me laugh is often fucked up. And it's often – it's not always fucked up in a way that it's going to get me thrown off something, but I think pushing certain buttons is funny to me, so I got to keep doing that. Part of the problem is that so many of the lines are blurred. So you have comedians that are commentators, and commentators that are comedians, and politicians, and so it's harder to defend like, hey, I'm a comedian, leave me alone. That defense becomes harder when all of these lines are blurring. Everybody's kind of everything now. So people say to me, you should run for office, and they're serious, and I'm like, you're crazy. But they're serious. So the blurring of everything means that people aren't in their lanes as much, and that you go, well, this guy is dangerous because he's not just making a joke. He's doing something else, and he's using humor. And I'm like, I'm really not. I'm really just trying to make a joke. That's all. That's really what I'm trying to do. But I do think that because of the flattening, there's a lot of people out there that go, they take aim at humor, because they go, humor is where bad ideas can kind of start and flourish. But don't you, to put some responsibility on you, don't you think humor is a way to, that you are the modern, like, Jordan Peterson style intellectual? That humor is actually a tool of changing the zeitgeist, changing the social norms? It absolutely can be, but it also cannot be. I don't think it's any one thing, and I think there's a lot of pressure for a comedian. You can be funny and right. You can be funny and wrong. If your goal is to be right, you might end up being right and not funny. So the reality is, funny has to come first. There are brilliant people that have been funny and correct, according to people, right? But at the end of the day, people that put way too much faith in what comedy is, most of what comedy is, is people showing up to strip malls and telling jokes for an hour while people eat chicken fingers, and they all get drunk, and they laugh, and they feel a little bit better about their lives. That's really the majority of comedy. Then there's like 10 famous people that are really famous that do a version of that in an arena. But the amount of cultural power they have has always been greatly exaggerated. My uncles loved George Carlin, who was anti-military, industrial complex, anti-this, anti-that, and then they would go vote for Reagan, vote for Ronald Reagan. They didn't care. It doesn't really, it's not as powerful as you think. I wish it was. It feels good. It feels good for me to say, I am the new thing. It really isn't. It truly isn't. Comedians are the people that get on stage and say, we're fucked up. We're drug addicts. We're sex addicts. We're fat. We're gross. We can't manage our money. We can't stop eating. We can't stop fucking doing horrible things. We're liars. We're narcissists. We're scumbags. We're the people that get out and say that. Only a psychopath would look at us and go, show me the way. It's not- I disagree with you. Then I'm a psychopath. Well, and that's- That's another issue. I don't think, no pushback here. That's another issue. But you know what I'm saying. One, I don't because, I mean, I understand you using this as a psychological tool for yourself to give yourself freedom. Yes. But the reality is you are one of the rare comedians like a George Carlin who is, besides being funny- Yeah. When I hear things like that, I'm like, okay, you're being very sweet. But I agree. I understand what you're saying. I do stuff that hopefully makes you think. I hope that's what good comedy is. But I think I try to do that. But I also would hate to feel shackled to the idea of that I had to make a point and that point had to be correct. I think the best comedy makes fun of everything. It makes fun of both sides. And then there's a deeper truth about humanity revealed. But then what happens is people take that deeper truth and go, let's politicize it. But what does he mean? Is it the right or the left? And I'm like, I'm doing something that I think speaks to hopefully people on both sides for everybody because I'm making fun of people on the left and the right and in the center and people that don't care and people that do care. And I'm trying to figure out a way to do it. But then immediately anything of value in this culture right now is like, how do we politicize it? How do we put it in a box? So yes, I think comedy can produce a lot of inherently valuable things, reflective, thoughtful things. But then immediately, can it be put in this box where all of those things can be used politically? No. And like when they say like, comedy is a great way to speak truth to power. It is. But I don't know how much it changes things. I don't know how much a joke can dethrone a king. I know the idea is nice, but let's look at the practical applications. I mean, we had brilliant comics, Bill Hicks, George Carlin, Richard Price. We had people talk about so many problems in society, illustrate them, put a spotlight on them, and we still have them. They're worse now than they've ever been. That's not true. I think the society is better. So to push back, in my perspective, it's very possible that those voices were the exact reason we have the world today, which I do believe is actually, I mean, on the boring old measures of what makes a good world, which is, you know, the amount of violence in the world, the amount of opportunity, all those kinds of measures, even happiness, all of those things have been improving. Stephen Pinker gets a lot of shit for this, but he's really good at articulating how the data says pretty clearly that the world is getting better. And it's arguable that the freedoms we do enjoy currently are thanks to the comedic voices or the people who mock. So to me, it's possible that humor is the very thing that saves the world. Humor is the very thing that keeps, is the balance of power. It might, but I think a lot of the things that those guys criticize, whether it was militarism or the elites, the lying, the corruption, the bribery, that's still going on. And it's always going to go on, right? Because that's the nature of human beings. We call it out, we point it out, but we don't have a plan to change. It's not really our job. And I think that too much now is like, well, comedians should have a, like, I don't tell people who to vote for. Like, the idea that comedians went and told people who to vote for is, like, to me, is crazy. I understand, like, people have strong opinions, but, like, I believe I have a job. And my job is to make you laugh or whatever, maybe make you think, but, like, my job is not to tell you who to vote for. I mean, it's absurd. But see, the thing you do by the comedy, like, on your Twitter that people should definitely follow... I believe that, at Shem J. Dillon. I agree with you. Oh, on this point of... I agree with you wholeheartedly. That people should follow you. Yeah. Yeah. You give me freedom to think on my own. Well, thank you. Meaning, like, you're shaking things up to where I don't feel constrained about what I can think about. And what... Well, that's awesome. That... Thank you. So you're not telling me what to think. You're giving me the freedom to think. And that's what great comedy does is, you know, I don't often agree with George Carlin. He can get pretty political sometimes. But, you know, just the ability to do that, it's so rare. Podcasts do that too now. Like, there's certain people that can really just challenge you to, even when you disagree with them, to sort of be like, oh, it's okay to think about this kind of stuff. Yeah. And I appreciate that, because that's awesome. And I mean, that's great. And a guy like you is a brilliant guy. That's great. If I'm giving you the license to think, then, man, the world is completely fucked. But I'm happy about that. Yeah. No, it's... Well, you know... Speaking about the world being completely fucked, Alex Jones turned on QAnon. I know almost nothing... It's a very tough... They had a rough marriage. They fought it out for years. And eventually, we just knew someone was going to leave someone. Q left, tried to leave him a few months ago. Oh, so... Yeah. Q was staying at someone else's house. The car wasn't in the driveway. Yeah. Well, the thing about QAnon that makes it a lot of fun is it's kind of a make it up as you go along. I'm a drug addict, right? So often, my lies aren't planned. They're in the moment. A lot of what I do on the podcast, it's all in the moment. I'll have an idea of what I want to talk about, and I rant, and I go. And I've been stoned, and I show up at home, and my parents are like, what's going on? There was $50 on the mantel. Now it's not there. And I'm like, well... And I got to make something up on the spot, right? I've been... Are you drinking again? No, I'm not. And then you got to have a... Well, you were gone for two days. No one knows where you were. And somebody said you left your car. Well, I was... Well, this is... I was at a sales conference, and I left my car. I flew to Phoenix. I understand what that is. QAnon is an ever-evolving conspiracy theory where the events are happening in the past, in the present, and in the future. It's kind of hilarious. Every conspiracy theory is like Kennedy, something like that, that there's a lot of truth in that, or all truth. But at the end of the day, it's like you're looking back from 30,000 feet, analyzing little things that have already happened. QAnon's like... So I think Alex is kind of like, I'm a little tired of the constant evolving nature of that conspiracy theory. So he's not a fan of the jazz that is QAnon, so they're not... Because they're improvising. Correct. They're improvising. Alex is like, hey, man, I was on board a little bit, but at the end of the day, it's getting a little annoying, because it can turn on you. Eventually, you become part of the conspiracy. Alex is controlled opposition. That's what they'll say. Eventually, you... Because QAnon just eats things. So it's a conspiracy that just eats things. The minute you start to say, hey, man, maybe that's not... It just eats you and go, you're in on it. Everyone's in on it. Everyone's a satanic pedophile. Everybody. Everyone that questions it is eating children. And you go, wait a minute, that seems illogical. But now there's... There's not enough children. Now there's not enough. And I think QAnon's over now, unfortunately, because for these people, but I think fortunately for them, they're going to have to find a new hobby. But I think it's over now, because even the best QAnon people now are starting to go, hey, man, this might not be going down the way we thought. But they've literally gone as far as to say that Biden and Trump switched faces. Trump's actually still the president, except Biden's... You have to be a real moron now. You got to be real stupid now. It's at the end. It was cool when the Epstein stuff happened, QAnon was like, it was party at Q. And then when the Hunter Biden laptop stuff started to happen, they were like dancing, like it's time. And then Biden wins. And they're like, wait, whoa. And it's just like, it's the day after the party. QAnon, if you ever went to a party in high school or college, QAnon right now is the day after the party. You wake up, it's 12 noon, the sun is hitting you in the face, you're hungover, there's a stench of disgusting beer and cigarettes all over the house. You're like, what the fuck happened here? I got to get out of here and get a bacon, egg and cheese. That's what QAnon is. They got to sober up, get out of that house, get a bacon, egg and cheese and go, man, we were fucking whacked. We were high, dude. I thought Nancy Pelosi was eating children for four years, and that Donald Trump was going to put her in Guantanamo Bay. Wow. That was because I mean, it's interesting that people have to do that after the 60s. They're like, yeah, I just did a bunch of acid and I lived in a ranch in Malibu and fucked everyone I ever saw. And they're like, I thought that was the way the world was going to go. And I followed some shaman guy, some guru who just wanted to fuck me and 10 other people that were living there. And we did that for three years. Apparently, we never created the utopia we thought we were going to have. And now I'm back working here, you know, at Allstate Insurance, and we have great policies and we'd love you to come in the office and we can break them down for you. It all ends, folks, all the love, all the bullshit ends. But it's fun. They had so much fun. QAnon was hard to get mad at because they were this was all they had. Yeah. And they were they were quite good at it and they were good at it. And they and and it was a lot of desperate people. But they're also rich idiots. There's also like dumb, rich people. And those are like the saddest people in Q because it's like they should they have the resources to do other things. Yeah. But they just love Q. They're like, I'm just into this. I'm like, you're rich. Go do something. How incurious are you? Go to the Amazon. Go birdwatch. I don't know. But they're you know, so play golf. It's sad. But they're like done now. I mean, they're there. Oh, it's over. So you think this is the I think everything's ending. My whole thing is that Trump's out. QAnon's over. The quarantine is going to end. Everything's going to go back to something that's more recognizable. I think that. Are you optimistic about the 2021 and what? To a degree, in certain aspects, I have optimism. And then I have I have short term optimism and long term pessimism. Okay. Meaning that I think in the short term, things can get better. I think long term because there's so many forces that are out of our control that are evolving in ways I barely understand that are carving up society. It's going to be very tough long term to be completely optimistic, like, hey, it's going to be great. It's going to be good forever. But short term, I think, yeah, this quarantine will end. Things will get better. The economy will get a little better. The constant Trump craziness will die down a little bit. That's my hope. And people can go back to focusing on things that matter, which is, you know, the things that are near you and close to you. Yeah, the humans around you. The humans around you, not Nancy Pelosi. I have my I have uncles that talk about Nancy Pelosi. I'm like, you've never met her. You'll never meet her. Shut up. Yeah. And I have a belief that this kind of local love and kindness that you naturally can have for human beings that you actually know can be expanded at scale through the social networks that we use, that we build. Twitter is currently failing at that miserably. That would be great. But that's if we were able to increase the love through the social networks, that would be great. It feels very hard to. It's a worthy challenge. You've tweeted one of the underreported reasons conspiracy theories take hold is because some of them are true. What conspiracy theories do you believe that are sort of important for people to think about, would you say? Kennedy was not killed by a lone gunman with no connections to any other situation, government. I believe that JFK was removed from office by a group of people that had very different interests. But the question of like deep state. So these are powerful people that are able now to dictate through basically the threat of violence what the presidents, the surface powerful people in our society. Yeah. I mean, again, I want another investigation into 9-11, not because I think that George Bush pressed a button and made 9-11 happen, but because we invaded the country of Iraq. And then we, 15 out of 19 hijackers were from Saudi Arabia. There was tons of stuff in the 9-11 report that didn't make sense to anybody. There's tons of stuff about that day that I feel like we just don't know. Yeah, that's, sorry to interrupt. That's when I, my little aunt life touched upon conspiracy theory world and first learned about Alex Jones. Right. Because when 9-11 happened, it was very frustrating to me how poorly the reporting and the transparency around what exactly happened, who knew what, all that kind of basic information that you would hope the government would release, reveal, and use as like a lesson for how we prevent this. Instead, it felt like a lot of stuff was being hidden in order to manipulate some kind of machine that leads us to war. Yeah, that's fair to say. Yeah, I mean, I just don't feel like we've gotten the full story. I don't know what the full story is. I can't, I don't know what it is, but I don't feel like we've gotten the full story. Yeah, there are groups of powerful pedophiles, right? Whether they're in the Catholic church or they're in the government or wherever they are, they are able to cover things up that they do. They're able to silence people that try to out them in terms of like, disrupt their operations. That's true. QAnon has nuggets of truth. It just went crazy. Any conspiracy theory that involves the Knights Templar and also Chrissy Teigen is probably wrong. What's the Knights Templar? Well, it was just this group of Knights back in the day. It's that supposedly secret meetings and in every conspiracy, they talk about if you go deep enough, it's like the Knights Templar, the Rosicrucians, all of these secret groups throughout history, the Illuminati. And there's a thread that connects all of it. Oh, yes. It connects it all to David Spade. I mean, it's a little much. Well, how do you, if you're David Spade, defend yourself, by the way? You ignore it because it's hilarious. And I know David Spade. It's like, Hollywood's kind of boring. Yes, there are sex orgies. I'm not invited. I'm sure there's shit going on. Kids do get abused. Women get abused. Men get abused. I'll invite you to one. Please. We got the $75,000 dog and then we'll get one. But me and David Spade, we go out to sushi restaurants and you sit there and you listen to people complain. That's what a lot of it is. What a lot of Hollywood is, is deeply sad tragedy that people don't understand that some of it is nefarious and dark and there are problems and there are real power brokers here. It's a dark town, 100%. But the idea that everybody that lives here is in some wide ranging vast conspiracy isn't true. It ignores how humdrum, boring, deeply sad most people's lives are in Hollywood. And it ignores how sad fame is in general. Fame's a sad thing. Not always. But a lot of times, it's a sad thing. It's fleeting. It's ephemeral. It doesn't last. It separates you from other people. It's isolating. It can be traumatic depending on what's going on. Obviously, it's better than the alternative. If you're trying to be famous, it's better to be famous than not famous. I'll say that. But it's a mixed bag to a degree. There are things about it that aren't great. And Hollywood has a deep undercurrent of sadness of people that have not realized their dreams and people that have realized them. Both of those people- Like the people that win Olympic gold medals can sometimes suffer from depression. They've lost- Well, somebody said, and I forget who said it. It's a great quote. It's not mine. I think it's from a book or it might be from a TV show. Sometimes I quote something and they're like, that's from like Charlotte's Web. I'm like, oh. The two worst things are... Oh, I think it's from the movie Limitless. I'm like an idiot. But anyway, thanks for having me on. Tomorrow- I will not publish this. It's from the movie. And I think he says, the two worst things in the world are not... Oh, you know it's not from Limitless? I think it's from the movie where Nicolas Cage sold weapons. It was called Lord of War. It's a little better than Limitless. Anyway- That's a good movie. It's a great movie. He said, the two worst things in the world are not getting what you want and getting it. So the undercurrents of sadness that run through Hollywood are there are two rivers that converge and there are people that just never had it and people that have it and go, now what? And so it's a sad place, a tragic place. And there's a lot of... It's boring. That's what people don't realize. It's actually kind of boring. Well, life is kind of boring. Life is kind of boring. But there's also like... So I think QAnon is this way to make a lot of it seem like it's super exciting. And listen, I don't want to diminish the experiences of people who've been abused because there is a lot of horror here. But the whole QAnon thing was like everybody in everything is doing it and that's not true. Well, see, just to linger on that a little bit is Bill Gates, the conspiracy theories around Bill Gates bother me because this is me, dumb, naive Lex, thinks that Bill Gates did a lot of good for this world. First, by creating a company that empowered personal computers. And second, by donating a ton of money for treating malaria in Africa and all those kinds of things. And there's these huge amounts of conspiracies, I think, based on just replies to whatever Bill Gates does, anything. To me, the top replies should be about how inspiring that guy is to donate so much money. Well, I think that... I'm so sorry to... The thing I'm struggling with is if I'm Bill Gates, how do you behave differently? How do you show people that you're, if you're not, I don't know, doing creepy stuff that they're saying he's doing? Right. Well, I think part of it is that he's done some really good stuff, right? He's an innovative guy, he's on the vanguard of a lot of things, but he's also the antichrist. And I think that that is, you know, they're not mutually exclusive. He is the prince of darkness as well as some... No, here's my thing with Bill Gates. He's a Batman villain billionaire, meaning that he's not a villain, but he's got all this money, right? Here's the thing, and I love Mosk and all these guys, I know you love these guys. Listen, when you have the kind of money that these guys have, and you have the vision that they have, and they want society to look a certain way, and a lot of them are doing great things, people, they need to get better at the pushback. They need to get a little better. When somebody says, hey man, what's going on over there? Bill Gates needs to be a little better at going, here's what... Yeah. Because, you know, Bill Gates has the money. You know, I think he once he wanted to shoot a missile of dust at the atmosphere to help global warming, and a lot of scientists were like, hey man, that might not be the way to do it. But no one in history, like so few people in history have had the resources to even have that thought. That if you have the resources to have that thought, and you have designs on the way you want society to look, whether it's public health policy, vaccinations, whatever, you have to get a little better at dealing with legitimate critiques. And obviously you're not defending yourself against people that say you're the Antichrist, but you need to get a little better. And I feel like Bill Gates and some of those people at that level are like, ugh, PR is kind of beneath them. Yeah, they're terrible at it. They're terrible at it. They're terrible at it. Him and Zuckerberg are really bad at it. Zuckerberg's horrible at it. He seems especially bad at public. Yeah, and it makes me feel so bad because the problem with being a billionaire is you lose touch with reality if you're not careful. I think Elon is good at, at least so far, maintaining touch with reality. Not if you look at the name of his child, you can clearly see. Listen, I do like him, and I do think what he's done with Tesla, you know, my producer is a Tesla, and he never shuts up about it. And most people that have Teslas never shut up about them. And they think they're part of the development team at SpaceX. And I like that he's created a world where people can get excited about a $37,000 car and never shut the fuck up about it to the point where I have to threaten people with physical violence to get them to stop telling me about that their car drives itself. Maybe have a few less drinks and a few fewer Vicodin, and you can drive yourself. Have you thought about getting a Tesla? I've never thought about it. I don't like them. They're minimalist. I don't like, I want more. I want more. Get the Cybertruck. I'm just being a total trolling you about being a salesman. My producer wants a Cybertruck. I want a stagecoach. Old school stagecoach, horse thief shit. It's going back to that. I live in an area with a lot of horses. It's going back to like whipping a horse. I want an animal to shriek while I go by. You want more suffering in the world, not less. Oh, I think we need it. Okay, but I just don't like that billionaire is a bad word. Not every billionaire is a pedophile. I know, but the problem is a lot of, it's just, Epstein was very smart at just getting people at that house and taking photos of them. Nobody knew what they were doing, but it was one of those things where it's like, Epstein was the most social guy ever. Every photo he's like, hey. It's like everyone that's ever done anything in the world has been at that fucking island. Every human being is in a photo. It's just weird. It's funny, me and my friends get together. We don't ever take photos. Last night, a few people, it was my birthday yesterday. I'm 17. And my friends came over and we're just eating dinner. And we had a fun night. It was just four people that are over, nobody. Nobody ever thought, hey, I want to remember it. Let's take photos. I'm 36. But everything Epstein did, there's just photos of everybody. It's interesting. Do you think Jeffrey Epstein killed himself? No, I think he was killed by that guy that they put in his cell, that lunatic, who was that big muscled guy. I think he did it for money, kept his mouth shut. Money from whom do you think? Mossad, MI6, CIA, all three. So there's a lot of pressure from a lot of different powerful people. Probably Mossad, CIA more. I mean, it seems very clear that he was working in type of a honeypot intelligence operation. Ghislaine Maxwell's father was an Israeli super spy. Ghislaine Maxwell's working for Israeli intelligence. It would be odd to think. And of course, the CIA knows about everything that Israeli intelligence is doing with Americans. So I would think that it's a very cozy relationship with those two intelligence agencies. And I think if you ran it by anyone, I think if you ran it by French intelligence, they'd go, yeah, no, get him. I don't think there was any intelligence service in the world whose job is to protect the powerful people that live in their countries that was against him getting whacked. But do you think it's possible that he's just an evil person who is after manipulating people and also was a pedophile? No. So there's a bigger thing. No, it's factual that there's a bigger thing. Evil people don't get handed— Those are your facts, Tim Dillon. No, they're the facts of the case. You don't get handed a 65— Show me another evil guy who was handed a $65 million place by Les Wexner. Show me another evil guy that got that type of handshake deal where he was basically let off without anything after a judge had made a very sweetheart deal for him after he was accused of molesting a 14-year-old. Show me another evil guy that doesn't have that kind of backing, that has those type of friends, those connections, those type of properties. Show me multiple passports all over the world. So show me a guy without anyone backing him that's doing it. Why did they— So you think he's just an evil guy? So he's doing this for whom? It's his own just shits and giggles? He's just getting off on it? Human nature, yeah. Human nature, huh? It's human nature? $70 million limestone mansion. I'm being visibly mocked. Yeah. Is it human nature? And it's like poetry. I don't think it's human nature. I think they manipulated human nature, but I think they did it. I think Epstein was really just a functionary, and I think Just Lane was kind of a pimp, and Epstein was kind of a guy that made the money okay and hid money and things like that, and worked for a lot of powerful people. I don't believe in lone pedophiles anymore. I don't even believe that. If you're a pedophile, you're in a group. You know what I mean? Oh. You know? Whoa. I'm not even going there, but staying on Just Lane. So you believe there's some power in her. What do you think happens to her now? What are the different— Great question. I mean, I don't know what'll happen to her, but I imagine she'll get some type of deal, closed-door thing years from now when people don't really care about the case, and she'll serve some time in a very lax thing, or she'll be killed. I mean, again, it's like if she was doing what she was doing, which is, I believe, a fact, that she was compromising powerful people so that they could be blackmailed by the intelligence services of the US and Israel, probably—I don't see how she wasn't doing that. Someone's blackmailing—someone's using the photos and the tapes, right? Someone's using that against these people. Someone wants to control these people. Well, who and why? That's the real question. And I think the real question is, you want to exert control over congressmen and senators and presidents because they have the power to make decisions to affect the—but the CIA just works for a lot of very wealthy people. That's what the CIA—that's how the CIA started, right? It was lawyers, bankers. They're protecting financial interests of multinational corporations all over the world, overthrowing democratically elected governments, going in and doing subterfuge campaigns, encouraging terror. They were doing all kinds of crazy stuff. I don't see why that would change. I think that's who they still represent, and I think those people want certain policies and certain people pushed forward, and I think those people are controlled, and I think one of the ways to control people is their sexual problems, and that's the way they did it. I wish there was a way to—because everything you just said now is— Makes a lot of sense, doesn't it? I'm being indoctrinated on air. No, it was just a— You think Jeff Ramsey is just a fun, random guy who just wanted to make home movies of presidents? Well, you think I'm just some random guy? I'm just trying to sell myself as somebody who's friendly with the American audience? I believe you are backed by people that want people to be more comfortable with robot dogs. I believe that. I believe you're pushed to be the happy face of AI. Which is why I will edit this part out. They should have picked the happier face. No editing. Joe Rogan's rule, no editing. This is live. No, I mean, I wish there was a way for some of the conspiracy theories to prove that that's not the case. Like, what the CIA is—there is some possibility in my mind that institutions like the CIA and different kind of organizations are driven less by organized malevolence and more by just incompetence. Just bureaucracy being incompetent. I think that argument gets less and less persuasive when you look at all the things they've been able to do. It's very certain, just like you said, that there's a bunch of them that have done—there's some conspiracy theories that are dramatic and true. The question is, I wish there was a way to prove that some of them are not. And it's very difficult because so much is shrouded in mystery. One of the things I'm bothered by is when people accuse other athletes of using steroids, for example. And it's just, yes, a lot of people use steroids, but it sucks that people just don't believe you. There's some incredible athletes that look shredded, that look just incredible performers, and everybody just says that they're on steroids. They kind of assume— Yeah. I mean, and people accuse me all the time of being on performance-enhancing drugs and steroids. And it is hard, but what I remind them is it's—my appearance is a result of dedication. Hard work. It's hard work, diet, exercise, dedication. Are you on keto? I'm on keto. I'm doing a version of keto. You're keto, right? Yeah. So I'm doing a version of keto right now with bread. And it's—do you see what I mean? You carb up in order to be able— So it's keto with sugar. It's called keto plus sugar. And it's a good diet for—I grew up in the 90s when nobody ever lost weight, sadly, because every diet was like, you can eat what you want, just be accountable. No one even knew what that meant. So it would be like my mother being like, if you have chocolate chip pancakes, have a glass of water. Yeah. Just take a walk around the block. You can go to McDonald's three times a day. Just walk around the block. That's what my parents used to say. My mother would be like, just walk around the block. You're fine. Gonna have a cigarette? Walk 20 steps. Walk 20 steps back. It's exercise. So there's too many conspiracies out there. A lot of them aren't true. A lot of them are bitter, angry people trying to justify their own impotence, not being able to do anything in life. And they're like, the people that have done something in life, they're all nefarious. It's all—the car just tacked against me. That's 100% true. 100%. It attracts usually people that have not figured out a way to succeed or haven't succeeded on the level that they want you. But that also being true, there is a fair amount of fuckery going on and provable. And we just have to, I think, separate—know that these things are often inflated or not true, but know that sometimes they are true. Otherwise, it wouldn't exist. If there was nothing to JFK, if there was nothing to 9-11, if people felt like they were being dealt with honestly, this wouldn't exist. I mean, this exists because there are real questions that people have that don't get answered for whatever reason. And then the vacuum of the refusal to answer those questions, that information vacuum, is filled with people like Alex Jones, who are curious, and sometimes they're right, and sometimes they're horribly wrong, and sometimes they're all over the place. And good storytellers and people love stories. And then when there's an absence of actual real— Alex is a uniquely American person, like, very interesting. I don't know how many countries—like, how many people make a living as a conspiracy theorist, a good living, in other countries, right? It's very rare, right? I mean, it's very interesting. And he became—like, I know people that knew him when he was a kid, because I'd go to Austin and perform a lot. And he was a guy that would take a bullhorn and yell at cops because he thought D.W.I. checkpoints were unconstitutional. That's what he was doing in college. And he just went through—he was hated by the right. He was hated by the Bush people. He was hated by the—and he went from being this guy that was considered a leftist, even. Like, even though he was never a leftist, he was considered this enemy of mainstream conservatism. Like, he was not—and he was considered a guy that wasn't a patriot, wasn't this, wasn't that. And he just—like, he whines and whines, and ends up just being this confidant of a Republican president, a very divisive Republican president, and he becomes this populist and everything like that. It's really wild to watch that. But I mean, I do think he should retire eventually, just so we could get some, I don't know, it seems like a—it's a lot to keep doing. Well, I hope this world allows for Alex Jones to continue having a voice, because just like you said, he's a—you used the word fun, but really he shakes up the norms of our discourse. I do, too. I do think we need to put more value. I think entertainment, you know, we do need to say that there are people that should be allowed to have a voice for entertainment purposes. Right. And that's part of what Donald Trump, now that he's not the president, come on, let the guy, let him talk. Who do you think is the best comedian of all time? Oh, that's a great question. Greatest of all time. You mentioned Carlin, your uncle's liking Carlin. Well, Carlin is great. Carlin is really hard to argue with, but Chappelle is also really great. Louis C.K. is really great. I don't know that there's what Joan Rivers is great. I don't know, you smile at that. She's a beast of a comic. I'm not aware of her stand-up, actually. She's a beast of a comic. Ask Rogue and ask any of them. Kinnison's great. So what makes a great comic, do you think, in the history of comedy? Said something at the moment, in a way, found a way to communicate with people in the funniest possible way at that moment, and illustrated larger truths about life in what they did. And I think that guys like Louis and Chappelle and Pryor and Kinnison and Hicks, people like Joan Rivers have done that. And even modern people, people like Maria Bamford's an amazing comedian. It's just a different style of comedy, per se, but she's an amazing comedian. Cat Williams is an amazing comedian. He really is. Well, see, one of the things you kind of mentioned, the comedians you mentioned, they were kind of fearless in saying the difficult things that needs to be said. Cat Williams is more, I don't remember his comedy, but I think it's just more wild out there. Well, to an extent, but you can watch it. He's got stuff, he talks about stuff, he talks about race brilliantly, he talks about America brilliantly. No, I think there's a lot of stuff there. Of course, Chris Rock. Of Chris Rock, of course. It's so hard, you can't really pick one. You just gotta, there's a class of people that throughout the history of this business, which is not that long of a history, it's pretty much within the last century, that have been really influential. Sometimes it's style, the way they deliver things. Sometimes it's substance of how they, what they're saying, or sometimes it's just a style of what they're saying. I mean, and we're only talking about standup comedians, right? So there's a million great comedians. I mean, if we're going to talk about Jim Carrey and Adam Sandler and Chris Farley, I mean, these are brilliant. And those guys are bigger influences on comedy, I think, than standups, really, truly. So there's so many brilliant people in the business. Who was for you influential, just the early on? Hicks was influential, because I'd watch Bill Hicks and I'd be like, this guy's saying crazy shit on stage, and this is the only way he can get away with it, because it's so funny. And he was calling out the military industrial complex, and he was talking about the first Gulf War. I remember he said a joke that I heard, it made me sit up straight. He goes, he was in Canada, and he said, we had a war in the States. He was talking about the first Gulf War. And he said, I was in the unenviable position of being for the war, but against the troops. And to me, I love that joke. It was so funny to me. And I was like, oh, you can't get away with that anywhere other than standing on a stage. You could never say that in an office, really. And this was before it was like PC. And the other thing, I always knew that comedians had to say shit and have it be funny enough that you couldn't get away with it in polite society. That was the whole point. That was why it was a dark theater or a dark nightclub. That's why people had a few drinks. That's what the art form was. And that's why... So a guy like that was influential, because I started watching him. And then, of course, I loved SNL when I was a kid, and I would watch Chris Farley, and I would watch people like even John Belushi going back in the day, but I'd watch Adam Sandler and Will Ferrell and all these guys. I mean, there's so many funny people. But Bill Hicks was kind of funny. And then Patrice O'Neill was probably my favorite comedian, who's made me laugh more than anybody else. I think it was you, actually, that... Maybe on your podcast, we're talking about Patrice O'Neill, and that he was actually vicious to others. I think he was a little mean to other people, but he was very good to people he liked, I guess. I think he was like... I mean, he wasn't... And I've never met him. I have no inside info. But from what I've heard, he was like no nonsense guy, right? He just said what he wanted to say. But I think in terms of comedians, I don't know of anyone funnier than Patrice O'Neill, who said... In modern times, that said more about our society than him. I mean, he was just a brilliantly funny guy. On the radio, he was funny. On his specials, he was funny. Everywhere, he was funny. And there's something else to be said about the whole medium of comedians doing podcasts. Yeah. Because it unlocks a weird, special, new thing that changed everything. I mean, Rogan started with that. You're doing that. I think that's a whole other form of stand-ups, the ones that have a lot to say. Almost like we get to witness the process of the creation of the jokes, in a way, or the mind, the evolution of the mind behind the jokes. Yeah. Comedians relate to social media. Comedy is a performance-based medium. So, it's about getting up and doing it, getting up in a club, getting up in a theater, getting up in a bar, getting up wherever you can get up. And comedy, for years, was about performance. And then on the higher end, it was about movies and TV shows. But we were very slow to get on YouTube. We were very slow to adapt to technology. We were very slow to monetize anything we did on the internet. So, podcasting was a way for comics and funny people to get into that space, start earning money. And now, because of the pandemic, it's really become essential. And it helps you. And even without the pandemic, it was where people... It was how you were building a fan base. And that's like... But comics were very reticent to embrace social media at all, because they thought it was cheap, and they didn't like it. And they thought the people on it were idiots and were unfunny. And it was just a blatant... Whatever it was, whether it was a money grab, or it was just too commercial, and in a sense where they're like, hey, look at me. It was just goofy, right? And then comics, I think, got displaced, because all the YouTubers came in, and all the social media stars came in. And they really knocked comics off. Because now, people are much more... If you ask anyone under 30 who their favorite comedian is, they say David Dobrik. And there's nothing wrong with that. David's a funny guy. But what you... Not especially to me a ton, but that's okay. But he makes people laugh, so he's funny. But he's what people... That's a comedian now. So, comics got beat by other people coming into a digital space before they did, laying the groundwork and taking it over. And now, comics are just trying to stay alive. Even my podcast, which is... People really like it, thank God. And I love doing it. The Tim Dillon Show. Well, thank you. I was late. I've been podcasting for a long time, but really dedicating myself and putting the resources behind it, I was late to it. I was like, hey, I'm telling jokes on stage, which is great, but I should have been allocating more time to building an infrastructure online. And I wasn't doing it. And a lot of comics weren't doing it. Funny comics weren't doing it. Comics that should be doing it. And I think when the pandemic ends, a lot of comics will just keep doing live standup. But I will keep... Obviously, I'm going to go back on the road and do live standup, but I will keep doing this podcast and building digitally too. But you're also exploring ideas. You're doing short videos and so on. You're trying to look for different mediums of how to be funny. I want to be funny everywhere. I want to be funny everywhere. I love making things too. My producer, Ben Avery, is a brilliant editor and comedic mind, even though he's not a standup. He's able to... He understands funny. He understands what makes me funny. We're able to make these really... I mean, some of those videos, they're just brilliant little videos, even though they're tiny little videos. They're fucking as funny as anything. And it's not me. It's me working with somebody else to make something really great. And it's that relationship that's very important. Well, in some sense, the medium of a short video is a challenge, just like the medium of a short tweet. Of course. How to say something. I mean, whatever the flavor is of what's in your heart, what's in your mind, how to say it, whether the goal is funny or something, or just an expression, an idea. I think the whole thing that's important to us is that it's an extension of, really, like an extension of your friendship in a way. Are you guys laughing at it? Are you guys making each other laugh about this idea? And if that's the case, other people are going to laugh at it. I think so much of the old medium was like, everything was top-down. Okay, pitch me this idea. I pitch it to the showrunner. They pitch it to the network. They pitch it to this, to that, to the... Standards and practices, sales, and we got to go through everything. Now it's just like, are me and a few buddies, or even just one buddy, laughing at this idea? Does it captivate us? And do we see it visually? And also, a great line from Roseanne, a guy... Not Roseanne, but a guy that worked on Roseanne. The old Roseanne, the great one. He said, is it funny with the sound off? That's what we try to do. That's brilliant. Is it funny with the sound off? When you see me and the dumb things, or me and the Meghan McCain, or me and the thing, is it funny with the sound off? And if it's funny with the sound off, you have a good starting point. That's hilarious, because you... I would say you're one of the people... Because most people are not funny with the sound off, most comedians. You, Will Ferrell, is another example of that. There's something about when I click on one of your videos, it's funny, just like the first thing I see, just your face. Well, thank you. That's very sweet. But I mean, thank God. That's what we try to do, right? We're trying to be funny. So we're trying to be funny. Can we talk about love a little bit? Sure. So you came out of the closet as being gay when you were 25. Yeah, it was late. Very late. Very late. Before then... By today's standards. During and after, how has your view on love evolved? Interesting. It's so hard to say, because I'd like to make a very Disney-fied statement about like that you can't be in love secretively. You should be honest. Love should all be about honesty. But that's not true, right? There's people that are in love that are lying to everyone else, but they're deeply in love. I would love to say something like, honesty is an ingredient for love. But I don't know, maybe honesty with each other, but I think there's a lot of people in the world that aren't honest. My view on love is super important. I think that a lot of society in America is all about love. We don't tend to focus on other things in terms of friendship or sustainability of that. Because I think that a lot... I know a lot of people in relationships where it's like, I don't know, they're not... They love each other, but it's also a rock solid couple because they're very compatible in many other ways. They're friends. I see friendship and love as the same thing. There's parts of it that are, right? I look at it as like, there needs to be more than just that amazing chemistry or physical attraction that is this chemical thing that happens. There should be some underlying... Again, that's what I've observed as really long lasting successful relationships. Well, is there something about coming out that you took away that you remember as profound, insightful, and so on? Yes. It wasn't society, it was me. There were kids that were out in my high school that I waited years later to do it. That was no one's fault but my own. I was taking a cowardly way out and a lot of people... I could blame society or like, oh, I lived in a conservative area and I grew up in... You should take responsibility for your own decisions. If you're being cowardly, admit that you're being cowardly. That's what I took out of it. It's not society's fault that you chose to be a coward. Society will never be perfect. You have to be honest when you're ready to be honest or however you want to be honest, but it's not somebody... Too much now is it's everyone else's fault that you didn't make a hard choice or a hard decision. That's what I took out of it. Now, in retrospect, you see yourself as being afraid. Do you think at the time... Well, I wanted people to like me, which is the disease of humanity, is that we want to be liked. What happens is if you want people to like you and love you even, you want people to feel comfortable with you. And those were people like your family? Friends more. My family I could always throw in the street, but I'm kidding. I mean, but I am not. But my friends, my circle of friends, which were my family at the time, when you're 10th, 11th grade in high school, your friends are your family. You know what I mean? So you don't want to do anything that puts you on the outside of the circle. It's just thinking back to that fear. Is there things you're afraid of now that you're not doing? You're afraid to do? I'm afraid of all kinds of things. I'm afraid of not being good at my job, not being funny, letting people down, not putting out products that are good, whether it's the podcast every week or stand up or the videos. I'm afraid of... There's a ton of people that really enjoy what we do. So when you're in that position, you're nervous that you're going to start doing things that they don't like. So the new things you want to do, the evolution you want to do, you want to make sure you're evolving in the right way. You want to make sure that you're doing things that are consistent with why people liked you. But also, you don't want to put yourself in a box and limit what you can be going forward. So I had a talk with the CEO of NBC Universal once. I was doing some internal sketch for them. And I was playing a cab driver. And he was a... And he's not the current CEO, but he's a former CEO. And I said to him, what's the hardest part of running a corporation of this size? And he said something very interesting. He said, the hardest part is maximizing the current profit model of what you have at the same time, getting ready, getting the company ready for where it's going to be in five years. He said, those are often at odds. And that's the toughest thing. He goes, because I could just bang out everything I got to do right now. And we're going to make a lot of money doing this. But am I devoting enough resources into digital so that in five years, when that's where everything lives, are we competitive in that space? So as funny as I am now, hopefully to people and a lot of the things that I want to do now, I'm going, what groundwork am I not laying for three to five years down the road so that I can be adapting to the trends that are important then in terms of not so much comedic trends, but the technological trends? I should have done podcasting earlier. Should I have a bigger presence on TikTok? Should I have a bigger presence here? Should I be on Twitch? Should I be doing this? Should I be doing that? What am I not doing that I should be doing that I'll regret not doing? And those are the conversations I think I have in my own head all the time. And I guess there's parallels to coming out as gay or just parallels in career paths you're taking, all that. That's ultimately just fear. It's fear. It's the fear of... The best thing that happened in my career was that I came to LA. I didn't have an idea of what was going to happen. I met somebody who was really committed to making funny things, that we just wanted to be funny. No one would let us be funny. We didn't have Comedy Central letting us be funny. We didn't have HBO. We didn't have Netflix. We just had a garage and a phone in the beginning and then a camera and then a thing. And we just wanted to be funny. And that was the greatest risk really I took because I was like, well, I don't know what else is going to happen right now, but I just want to be funny. And funny saved my life. I mean, funny got me out of drugs. Funny probably got me out of the closet. Funny was the thing that I was able to do that made everything okay in my own head. So I was like, as long as I'm being funny, something good will happen. So we did that. And then something really cool happened, that we were able to do a lot of cool things. But that's what it is. It's fear that keeps you from being the better version of yourself. Your mom... I mean, you have so many complicated, fascinating parts of your story. But your mom, as you were growing up, suffered from mental illness, schizophrenia. Can you tell her story and how that relationship has changed over the years? Yeah, well, she was always eccentric and always, you know, the terms for schizophrenia in an Irish Catholic household where we didn't talk about anything were eccentric, fun. She's fun. There's a theme to this conversation. Unpredictable. She's a live wire. Any of the words you would use to describe somebody who's a fucking lunatic, but you wouldn't say that. Yeah. Thought they'd spin. Right. She started experiencing symptoms probably early on in her life, but she also, I think, started really manifesting them when I was in my mid-teens. So like 14, 13, 14 area. And she got really, really bad. And then I think she was institutionalized about 10 years ago, a little over 10 years ago. And she could really no longer live on her own. She was unable to go to work. She was unable to function. So I visit her when I can. Obviously, I'm not in New York. Whenever I go to New York, I visit her. She's aware of what I do, my career and everything like that. You know, she has good days and bad days, but mental illness is a thing. It's very tough. We don't talk about it as a society. People with mental problems don't get that much attention. We tend to think that they did something wrong or that they deserve it or that they are to be ignored. And we don't devote a lot of resources into it, which is unfortunate because then you have the junk gurus come in and go like, let's diagnose your mental illness off Instagram. And it's like, that's not the move. Yeah. Do you love her? I do. I do. I love her, but I also remember her that isn't her now. And when someone has mental illness that's severe, you make peace with their death before they die. Wow. Yeah. Because the part of them that you love and remember a lot of cases is not evident or obvious. Now, my mother is still a loving person that I love, but the fun, her ability to be present in the moment and to not, you know, that is lost with the progression of realness so that you still love her. And I mean, again, you know, your parents, you know, the time horizons you have with your parents are unknown. People don't know. I have friends that their parents were in their lives for their entire life. And I have friends whose parents were in their life but my mother was a very, she knew what I was. When I was a little kid, I was an actor. When I was like six to 12, my mother knew that I was a performer. She knew what I was and what I'd ultimately do. She recognized that in me. And when I said to her, I want to audition for shows, I want to be on stage, I want to be on this, I want to do this. She let me do it because she knew who I was and she didn't want to get in the way of me being a human being, a fully realized person at six. So that's probably the best thing a parent can do for a kid is let them be who they are. And my mother did that. So that, I mean, that's good. We ate too much fast food. There were negatives, but she did let me be who I was. Well, that's why you want to throw them out into the street. Yeah, sometimes. But coming to accept the mortality of her, I guess, identity as you remember it from childhood, I guess, identity as you remember it from childhood, do you ponder your own mortality? Are you afraid of death? I'm afraid of death. I don't like the idea of death, but I know it's happening. You know, I know it's going to happen eventually. I don't love it. You think about it? I think about, I want to do some good stuff that people can look back at. And I think I'm proud of the show where if people look back at the show, I don't know how comedy ages or whatever, but I think I put out a lot of stuff and I want to continue to put out stuff and I want to put out a few specials that people can look back at and go, oh, this guy was really funny in this really crazy, you know, he lived in the latter part of this century when all this shit was going on and he kind of made fun of it and he did something to make people's lives a little better just by having, you know, a few laughs, you know? What do you think about, this is something like in the podcast context, do you think you'll have just one or two or three shows out of thousands maybe that are like the truly special ones? That's probably the case. Or do you think it's an entirety of the body of work? I think people will take 10 minute clips from all different shows and put them together and- As a highlight? Yeah, like a highlight reel of just like, these are like the best things that he's ever done or the best rants he's ever had, the best things, whatever. So the legacy would be that this was an important voice in a very weird time of his life. I would hope that that's part of it and I hope that I continue to be in, you know, you say important, I say funny, but hopefully I continue to be a voice and that's what I think, when I think about death, I think about like, what did people come on earth to do? And I think I came, I think my main purpose on this planet, other than to experience whatever love or, you know, worthiness or whatever is to make, to entertain people. And there's a lot of people in comedy right now that are not entertainers and that's really the problem. But, and they got into comedy sort of the way that, you know, you can walk into the wrong store in a mall and then not realize you're in the wrong store and try on a bunch of clothes and then go, fuck, I wasted my whole afternoon. But I think I've always kind of been an entertainer and that's what I want to do. There's, unfortunately, sadly, a lot of people that look up to you. That is a horrible thing, but life is a nightmare. Yeah. If you were to give them advice, young folks, people in college, maybe even high school, but people in their twenties, about what to do with their life, whether it's career, whether it's just life in general, what would you say? Ignore everyone, make a few good friends, truly have honest conversations with yourself about your, when do you feel the most alive? When do you feel the most alive? Figure that out. When and how do you feel the most alive? Figure that out. Try to figure out a job or a career that can replicate that feeling. Don't listen to anyone. Don't listen to your parents. Don't listen to the gurus on the internet. Don't listen to me. Don't listen to anyone. Figure out, you know, where you feel the most alive. Where do you feel excited? Where does your pulse quicken? What do you feel matters? When you're in a situation, do you feel like it matters? What situation was that? What got you excited? What thing did you walk into where you looked around and were taken back and you're like, wow, this is amazing, and I'm filled with awe? If you can figure out a life where you can excite yourself, you might not use drugs or alcohol or a sex addiction or gambling or irresponsibility. You might not have to get your fucking kicks in very destructive places if you can get them in a productive place. You had a pretty weaving life that's full of mistakes and so on. Many mistakes. Are mistakes a bug or a feature? Do you recommend embrace the mistakes, make a bunch of them? Depends what they are, right? You've had the full spectrum. I've had a lot, but a lot of mine could have sunk me. They sound like fun when I talk about them, but they actually could have sunk me. They were all part of what made me funny, but I don't know. I would never tell anyone else to just light their life on fire and hope it works out on the other end. It would be pretty irresponsible. But hey, at the end of the day, it's like, you're gonna – I think one of my themes is that there's too much – we give the power – we think we have too – the power of choice has been elevated in our society to an unhealthy degree. I think you could get really good at something, but you're born with a certain aptitude. It might be to be a dealmaker. It might be to be an athlete. It might be to be an artist. It might be to be a romantic and just fall in and out of love, in and out of love, in and out of love. It might be to be a world traveler. But whatever you are, I think you are. I think that there's something about you that makes you something. If you can figure it out and then refine – you're not gonna be good at it per se, but if you're an athlete, it might not mean that you're going to be a great athlete in the history, but it might mean you're the best coach anyone's ever had or you're the person that builds a local scene for young athletes or whatever. If you are a really good dealmaker, it doesn't mean you're gonna be Warren Buffett, but it might mean you're somebody who enjoys making deals all the time and things like that. If you're an entertainer, it might mean that you are an entertainer. It might mean that you are in the world of entertainment because you love it so much that if you lack the skill set to really pursue it on a degree, you just wanna be – there's a thing inside of you that makes you what you are. I look at certain people and I go, you were born to be that thing. And the whole purpose is to find it. I was a juror on a murder trial in Long Island, and the woman who's the DA, I'm like, you were born to do this. You were born to put murderers away, and this guy killed the mother of his children. He was a bad guy, but I was like, you are really good at what you do. She has a strong belief in whatever her moral code is and what her justice and ethics are, and she wants to communicate that to people. She was very good at doing what she did. I don't know the facts of the case. I didn't really listen. He seemed guilty, so I just voted guilty. But I didn't really listen to her, but I heard the shape of her mouth was very bovine, like a cow, and it conferred a certain level of expertise that I enjoyed. Well, it's funny. I mean, you could see you're half joking. Yes, but I'm serious. You can often see that people just, they found their place. They found their role. They found their thing. They found their thing, and that's kind of the purpose of life. And once you are in a place that seems sticky, like the place that seems right, you know, that's one of the problems with the generation that you're speaking to, is there's always a feeling like I should keep exploring, keep exploring, but it's okay to stay in a place that you found that works. Yeah, and listen, sometimes the best place you'll find is when people are like, when did you feel really excited and alive? It's like doing nothing. You know? Like, that's the other thing. It's like, some people are going to be like, I feel really excited and alive, and I'm laying in my backyard in a hammock, and I just want to have the simplest life and not have to do much, and I don't like doing anything, and I love laying around and going, wow, the sky looks good today. Bill Gates goes, the sky looks good today. Let's shoot a missile into it. He wants to do shit, right? So it's like, in between that and nothing is you can find something. But in that process, for you personally, I mean, for me, and for others, I think there's a struggle. When you look in the, when Tim Dillon looks in the mirror, do you love yourself? Or do you hate yourself? Well, a lot of times I think I'm Amy Schumer, so I'm confused. I'm a detente with myself all the time. I don't love myself or hate myself. Addicts have a very bad problem where you can't just fall in love with yourself and you can't hate yourself. Both of them lead you to a negative place. You try to stay kind of even keel. I don't go like, hey, man, you put out a video, you got all these views, things are great, you sold a bunch of tickets, let's fucking go out. Like, maybe let's, hey, man, let's have that drink that you've been waiting for for 11 years. And I don't look at myself and go, you ate a burger yesterday, you're a piece of shit, you're horrible, you'll never get into the shape you want. I try not to get too low or too high. Both of them are not good from my particular mind. Okay. I got to ask, we kind of spoke about 2021 and you being potentially hopeful. Hopeful short term, cynical long term. Yeah. So let me ask, I forgot to ask, are you moving to Austin? I don't know. I mean, I don't think so immediately. I love Joe, I love what he's trying to do down there. I'm appreciative of everything that he's done for not only me, but for comedy in general. And I think as things happen in Austin and unfold, it's such a political answer, but as things unfold, I will consider it more and more. But I mean, I think I got another year in LA. So you've spoken so nicely about this magical place that is Los Angeles. LA is very funny. You think there's a place for comedy in LA? Oh yeah. There will always be a place for comedy in LA. So there's going to be a place for comedy in New York. I mean, the question is how thriving of a comedy scene is Austin going to be? And the Joe can probably make it one, but as of right now it isn't. So that would be him doing that. But the question is, there's a lot of people escaping Los Angeles, but I know better about New York. There's a lot of really brilliant people. Let them go. There's other people. This is the thing. This is the fear thing. It's like, no, but all the brilliant people are leaving. There'll be other people and they'll fill their shoes the way that they've done throughout history. And I think that New York and LA, listen, maybe in five to 10 years, they're not the two cities. It would be real rough in five years when this pandemic's over for people in Australia to go, dude, you got to go to America and you got to visit Charleston and Austin. Stop. Let's be adults here. Let's be adults. It's still going to be New York and LA for a while. LA is an absolute hellscape, but I don't think you're going to replace California with another place. And also everyone's making decisions now because we're literally in the midst of a pandemic we've never had before. We've never had this before. Joe loved California up until the pandemic. He had problems with it. We all have problems with it. There's a lot of benefits to being here. I think a lot of us made pretty bad decisions in 2020 because we're all locked up and stuck with our own thoughts. But so it's funny, there's parallels because I don't necessarily, you know, I'm obviously a fan of comedy, but I don't care where comics move. Sure. But there's a parallel move that's happening instead of decisions, which do influence my decision-making, which is where to start a business that's tech-centered. And that's more about the San Francisco, Silicon Valley, and there is a lot of people leaving there. And they're going to Austin. Well, Austin, there's a, I think, there's a bunch of different places. Phoenix, there's Denver. Austin will probably be a massive tech hub. Elon's there. It seems like it's all, everything about Austin says that it's going to be a massive tech hub. I just don't know if that means it'll be a massive comedy hub. It might. I don't know if those two can actually coexist. It's interesting because... Yeah, I think, you know, comedy suffered in New York and LA when everyone got super rich. Like, you know, it just wasn't as cool. It's still much more fun on the road. It's still more fun to perform for people that want and need to laugh in strip malls than it is to perform for hedge fund managers and with their dates and, you know, Instagram models in LA. It's just what it is. Comedy on the road is much more fun. So maybe in the spirit of that, Austin becomes, but you know, you know, if Austin is just colonized by tech bros and stuff like, yeah, I mean, sure, sure. It'll be fun and it'll be great. I think Joe's made LA a scene. So if anyone's going to make Austin a scene, it's Joe. Yeah, and I like the, on the Elon side, which is what I'm much more familiar with, the promise of the possibility of what that could become, because there's a lot of problems in Silicon Valley. And of course, it might be naive to think that just because it's like the grass is greener thing, which is just because the place where you come from has a lot of problems, doesn't mean you can just create a new place that's not going to have those. Yeah, there's homelessness in Austin. There are problems in Austin. I mean, I think that with, by the way, with the influx of very rich people to an area, sometimes that helps things, but sometimes it just makes things more polarizing and it puts a spotlight on those problems and makes those problems even bigger. Right? So, I mean, I don't know that it's necessarily, it's hard to predict. I just know that LA right now is funny. It's funny that there's 15 year old TikTokers making millions of dollars dancing in a house while the world burns. That is very funny. Well, it's for your style of humor, yes. The absurdity of the world. It's funny that no one cares about Hollywood starlets and actresses and actors and everyone goes, hey, fuck you, even though they've won three Academy Awards, they're all being replaced by just mediocre dancer 15 year olds. I mean, it's like, there's something hilarious about this city and it will burn in hell, but so will everything. So what are we talking about? Yeah, eventually the sun will die out and we will all be gone unless we colonize outside of our solar system. But I just sit here, I'm struggling with this because Boston, I'm currently at MIT, Boston doesn't feel like the right place to start a business in the tech sector. And so I'm choosing, I'm looking at San Francisco the way it is, and I'm looking at Austin. Oh, Austin, clearly. So it seems clear, but it's such a difficult thing to predict what a place will look like in 10 years, in 15 years, in 20 years. And it's so hard to predict if you'll like it or not until you're there. And you know, this is speaking to risk. There's not really a good reason for me to move anywhere. Right. There's not a good reason to do anything in life. Part of me wants to just fucking do it and whatever and see what happens. Do you like Boston? Do you like other things about Boston besides the tech thing? No. You like MIT? At MIT, that's the problem. But do you like the food in Boston? Do you eat food? I haven't eaten food or been outside for years. And I mean, that's probably the better version. But you're keto forever. You've been keto for a long time. Yeah, keto fasting for a long time. 15 years fasting, eating once or twice a day. I haven't. And no sugar ever. No like. No sugar. And no pasta ever. No bread ever. No pasta, no bread. No, except like, so my source of- You could kind of live anywhere because like, going out is such a big part of what city you live in. And like, you like the food there? Do you like the restaurants? Can you meet people? Whatever. But it's like, you really can just kind of- Yeah. So not married, no kids. Right. You have freedom. Me too. I have freedom. Yeah. And that's, we have the curse of too many choices. Right. That's the thing. We have too many choices. We don't have somebody else going, what about like, we don't have to justify our decisions to anyone. So we can just kind of like, let our minds run wild. So you just got to hone the instinct of just what feels right and just fucking do it. And that's it. I think Austin with Joe down there and Elon down there, Austin seems like a real no brainer move for you. To try. To try. Why the hell not? Why not? Why not? And then I think I should go to MIT. I mean, I think I should give those nerds a piece of my mind. Yeah. You should go to, I was in an Uber pool once with a kid from MIT and I was eating this thing from Bova's Bakery. I forget what it was. It was like a, it's so good. I don't know. You don't know Bova's Bakery, right? Yeah. It's in Boston. It's famous. And I was eating a thing and I was like covered in chocolate. This kid, like this little nerd, like this little like, you know, USB drive with feet was just staring at me and I just dropped them off at MIT and he like scurried away. Yeah. But that's a big school. Doesn't the NSA recruit out of there heavy? Like MIT, places like that. I can't, I can't speak to that. But what, this is a ridiculous question I sometimes ask myself when I'm alone. What is the meaning of life? Do you think about the big existential kind of why the hell we're here? It's a cosmic kind of joke, kind of in a weird way. Right. I mean, Joe said it the other day on maybe it was you saying that like, he was just like, you know, by the time you figure out what it is, you're out of here, you know, it's kind of interesting. Or you even start to figure out what it is. You're out of here. It's like, it's like, that's kind of funny. It's like, you don't get enough time to truly, I think the meaning of life is just like, at the end of the day, do you feel you, it was time well spent? Was it time well spent? That's, that's really what it is. If you look back, do you go, hey, it was time well spent. Like I pretty good ride. It was pretty good ride. I did. I did. I did a lot. I did a lot of things. I, I doing what you say is a part of it. I think if you say you're going to do something, maybe doing it. That seems to be extrapolating the meaning of life question to like, you know, what did you come here to do? I think it goes down deep of like, who are you and what do you want? And you know, what are you suited to do and what? It does seem that like the people who are most enlightened that I've ever met or read books by, they ultimately land on humor. Like they don't take shit seriously. They embrace the absurdity of it all and just kind of laugh at laugh at it in this kind of simple way. So it does seem that humor is like one of the fundamental truths of this. Yes. We're in. And some love, love, humor, humor can be love, right? People laughing that that sound is kind of like Carolyn Knapp, who wrote a book called drinking a love story, which is a really good book about drinking a love story. A really good book about not drinking, drinking and then not drinking. And she said the last you could understand things is love that you I think one of the last lines of the thing is like people talking about their experiences in life that that could be love, like, you know, laughter is love. Like, I feel like love and finding it wherever you could find it is why we're here. That's that connection. And laughter can be love and, you know, figuring out, you know, something that makes life better for a lot of people can be love, you know, whether it's a vaccine or a technological advancement or whatever, like, you know, all of those things, I think, can be that feeling. And I think that's what's important. It connects you to a larger frequency, you know? I don't think there's a better way to end it, Tim. I hope you're one of the voices, I truly believe that your legacy be one of the most important voices of our time, because you're fearless and challenging all the absurdity of the nonsense that of our social and political discourse. I hope you keep doing it. I'm a fan. I'm still a bit starstruck. So I'll stop it. Listen, I, I, I, I was your intellectual capacity, enjoying anything I do only underscores how truly fucked we are. But thank you very much. Yeah. Thank you for talking today. Thank you, brother. Thanks for listening to this conversation with Tim Dillon. And thank you to our sponsors, NetSuite Business Management Software, Athletic Greens All-in-One Nutrition Drink, Magic Spoon Low Carb Cereal, BetterHelp Online Therapy, and Rev Speech-to-Text Service. So the choice is business, health, sanity, or transcripts. Choose wisely, my friends. And if you wish, click the sponsor links below to get a discount and to support this podcast. And now let me leave you some words from George Carlin. Scratch any cynic and you will find a disappointed idealist. Thank you for listening and hope to see you next time.

https://youtu.be/8wYZjOzfTUk

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Michael Malice: Totalitarianism and Anarchy | Lex Fridman Podcast #200

The following is a conversation between me and Michael Malice. Michael is an author, anarchist, and simpleton, and I'm proud to call him my friend. He makes me smile, he makes me think, and he makes me wonder why I sound so sleepy all the time. And now, enjoy this conversation with Michael Malice in the Tupac Galova language that I'm increasingly certain I'll never quite able to get the hang of. So, comrade, if we lived on this farm, in the book Animal Farm, which animal would you most rather be? Would it be the pigs, the horses, the donkey Benjamin, the raven Moses, the humans, Mr. and Mrs. Jones, the dogs, or the sheep? I'm gonna go with the Milton answer, which is better to rule in hell than serve in heaven, right? It's better to rule in hell than serve in heaven. Yeah, so I would have to go with the pigs. So I guess I'd be a cop. At the very top, so the leader, the main pig, Napoleon versus like the... Snowballing the others. Yeah. I would say it's not... It's sure it's an allegory about the Russian Revolution, but I think Orwell's point was this is broader towards most totalitarian dictatorships. I mean, it could very easily be read as an indictment of Mussolini or Hitler or many of these others. I'm a huge George Orwell fan. One of the things that I think people on the right need to appreciate is the courage of many of these indisputably left-wing voices who were the strongest ones to take on totalitarian communism. And the three I could think of off the top of my head, who are all in my top 10 heroes of all time are Emma Goldman, Albert Camus, and Orwell being the third. Something that leftists like to throw in the face of people on the right who constantly invoke Orwell is that Orwell said, and I don't have the exact quote off the top of my head, but something to the effect of, every word I have written should be taken as a defense of democratic socialism against totalitarianism. So people like Truman was obviously very hardcore, in many ways, anti-communist. We like to parse things out. You're going to laugh, you're going to laugh into binary fashions that left good, right bad, or right good, left bad. But historically speaking, it does not fall away into these camps as easily as people would like. And I think it is important for those of us, it takes a lot more courage to fight the right from the right or to fight the left from the left, because in a sense, a lot of your countrymen or your fellow travelers are going to regard you as a traitor to the cause. So every chance I get, I will sing the praises of these three figures among others who not only, even if they hadn't done what they had done, just lived just amazing lives that all of us can learn from and admire and regard as somewhat a role model. So- What was the nature of their opposition to totalitarianism? Is it basically freedom? The value of freedom? Let's go through the three of them. So Emma Goldman, she was an early anarchist figure, we'll talk about her later, I'm sure. She got deported from the United States with her partner in crime, Alexander Berkman, literal crime, he tried to assassinate Frick, who was Andrew Carnegie's main man in the Pittsburgh steel mill strike. She got deported to the Soviet Union, and they're like, oh, you want socialism? Because at the time, the anarchists were regarded as socialist, go choke on it. And she's there, and she was watching in great horror, what was going on. And she actually went to Lenin's office, and she goes, this isn't what we're about. The revolution is about the individual and free speech, and everyone working together to further society. And he told her that, you know, free speech is a bourgeois contrivance. And regardless, you can't have these circumstances in the midst of a revolution. And when she left the Soviet Union, and you know, she went to Britain. And at the time, before the 1917, there was a lot of discussion among socialist circles about what would the revolution look like, right? Would there be the Bakunin anarchist model? Would there be the Marxist model? Obviously, the Bolsheviks ended up winning. But even then, it wasn't obvious, because there was the Bolsheviks and the Mensheviks. And what people, you know, you and I know what those words mean. But Bolsheviks were kind of funny, because Bolshe means bigger, and Menshe means smaller. The Mensheviks had the numbers. It was sarcastic that they were called Mensheviks, and the Bolsheviks were called Bolshe. And Lenin, you know, destroyed all his foes in a very merciless way, obviously. Beforehand, you know, there was the idea like, okay, we all these cockamamie ideas, we have to work together. You know, we don't know what's going to look like for the cause. Then as soon as he sees power, he's like, yeah, yeah, we're not doing that kind of pluralism anymore. This is going to be the right approach. So she left the Soviet Union, as did Berkman. She wrote a book that they titled, My Disillusionment with Russia. And I remember this one anecdote, which I'm going to discuss in the forthcoming book, where she goes to Britain, and the British were very red at the time, they really had something called the Fabian Society, which was the predecessor to the British Labour Party, which were like, all right, we're going to get rid of liberalism and have a socialist kind of nation. And she gave talks. And there was this one time where she gave a talk and she started and there was a standing ovation. By the time she was done, you could hear a pin drop, because she dared to look at these people in the face, something they'd been fighting for all their lives and saying, you know, we've been to the future and it works. And she's like, guys, this is worse than the czar. You know, people are under house arrest, you're not allowed to have, you know, newspapers are being shut down if they have heretical views, so on and so forth. And you know, she was just even more of a pariah than she had been previously. So she is, you know, deserves huge accolades in that regard. I brought her up and we're talking about with our conversation with Yaron Orwell, I think you don't need me to explain what he has done and continues to do to use fiction to demonstrate the horrors of a totalitarian state and Camus, who might be my all time, you know, great lighthouse, so to speak, in terms of being a man of conscience. You know, he joined the Communist Party. And for a lot of people in the States, you hear, oh, you joined the Communist Party. So I need to hear it's all you need to he was a communist, all you need to know, he joined the Communist Party, because they were the main ones fighting the fascists in France and other locations. And he took Nazism, as did many others, of course, very, very, very seriously. He wasn't some committed communist, but this was just his mechanism to take on, you know, be part of the underground in Vichy, France, and so on and so forth. So he had the quote, which is ascribed to him, which is kind of a misquote, Howard Zinn is the one who actually said it that it is a job of thinking people not to be on the side of the executioners. And he very much felt if you read his speech, when he won the Nobel Prize, I forget, in the 50s, where he goes, it's basically the job of writers to keep civilization from destroying himself. I don't think I'm ever going to be a man on the level of Camus and what he's accomplished. But I think that vision of it is the job of writers to be the conscience. And to point out, you know, this is the leftism at its best when you're giving voice to the voiceless, when you have the machine of the state, crushing and marginalizing people, and they might not be educated, literate, or have any power at all. He's the guy who's like, you are ruining humans, these humans matter. And I'm not going to let you look the other way, and act like you don't know what you're doing. So in this time, whether we look at the time of fascism, or we look at the fictional animal farm, what's the heroic action then? So Camus joined the Communist Party, there's a bunch of different heroic actions, some more heroic than others. Not just for the, you know, hero is the wrong word, in terms of like effectiveness. What's the effective action, I guess, is what I want to ask. As a writer, as a thinker, as somebody with a mind, what's the heroic action? That's a tricky question. Because a lot of times in the West, heroism is regarded as intertwined with martyrdom, right? So it's kind of this idea of like, you have to speak to, you know, Camus always talked about, let justice be done till the heavens fall. This is a common kind of motto among people with conscience, and that you have to do the right thing, even the consequences might not be what you like. And I think that is a good loose definition of heroism. So if you meet, I'll give you one example of heroism. This was on Twitter, and I really feel bad that I don't remember the guy's name. This was the line to Auschwitz, I believe it was. And you know, there's the Nazi guards keeping everyone along. And if you were certain, I think if you were under 12, they killed you or something, there was some age limit where some kids were killed or some were not, there was some circumstances. And he asked the mom how old this kid was. And she's like, he's 14. And she's like, No, he's 12. And she's like, No, he's nice 14. She goes, he's 12. And she realized what this Nazi was telling her even in that circumstance, and it ended up saving the kid's life. So I think heroism in this context, is defiance, and standing true to values of liberalism, humanism, and venerating the sanctity of human life. I think that and I think it's also important to pick your battles. I don't think if you know, he got on that Nazi over there gotten a bullhorn and said, Hey, this is the rules, blah, blah, blah, blah, blah, that's not going to help anyone do anything. So I do think, you know, people a lot of times attack me for my anarchist views. It's like, Oh, you know, would you call the police? Would you use the roads? Would you pay your income taxes? You know, I got an argument with Tim Poole, because there was that couple, I think, in it was that Missouri or Illinois when they had their guns, and they were being arrested, and they basically took a plea deal. And he said, you should have fought I go, it's a lot easier to say you should fight, but we don't know what circumstance someone is under. And what these totalitarian regimes did very, very well, as you know, is if you were a target, and they can't get through to you, that's fine, you have a family. So you can sit there, Lex, and gird your jaw, and you can stand up to all the torture. Cool. What are we gonna do about your wife? What about your mom? One thing Stalin did, he made it a law that kids up to 14 and up could get the death penalty for certain crimes. So after that, the rule was from the NKVD, if you were interrogating someone, they would have death warrants for the kid's child on the desk visible. So I'm interrogating you asking you to commit to I'm sorry, to admit to some crime that you're not committed. And those piece of paper, it's your it's you know, Svetlana, she's got a death warrant, you're gonna admit to any crime you want. So this is something Americans, this is even the case right now in North Korea, which I know you had Yomi Park on something I talked about a lot. Let's talk about instead of the hypothetical, but this is happening right now. On Earth, you can look at the map on Google. The great leader Kim Il Sung, the founder of North Korea said class enemies must be exterminated three generations. So North when people talk about individualism versus collectivism, Rick Santorum, former senator says the family is the basic unit of society unit, North Korea takes that seriously, the family is punished as a unit. So if someone does something wrong, three generations have to pay the price. And you often don't know who it is that got you all in trouble. There's not a trial. This to Western minds is something almost incomprehensible. It's a lot easier to be brave. When it's just your skin. There's something when it's when it's Yeah, when it's your child, your your loved ones, your every man becomes a coward. But also what bravery is there for me to write an essay for the Guardian to say I don't vote, there's no consequences to me, there's no possibility of consequences to me. This is the wonderful thing about living, excuse me, in a free country. It would take a lot of courage to be in the Soviet Union and say, I'm not going to vote. And what would that courage accomplish? Very little. So I think heroism in the sense of kind of the suicidal stuff and taking a stance with no consequence, it is a bit overrated. There is some aspect like the way I think about heroism is something like you said about the Nazi soldier, which is quietly privately in your own life, live the virtues that you want the rest of the world to live by. Yes. So like without writing about it is, is not as heroic as living it quietly. I'll give you a great example of this. I sometimes give talks on networking. And I tell the kids, if you know someone's in town and it's their birthday with nothing to do, take them out. And I say, I do this for selfish reasons. And everyone laughs. And I go, think about it this way. The guy who takes people out for their birthday is awesome. That could be you. Like you have that capacity to be that person and you're making that day feel special. They're going to remember for a long time. What's the cost? Dinner, 30 bucks, 25 bucks. So it's very disturbing to me how often people have opportunities to slightly move the needle and make things a bit better at almost no cost. And they just literally don't think in those terms. And one of the things Camus talked about, he's often described as a existentialist, which he did not like that term. He regarded himself as an absurdist is the idea that we're basically blank canvases. And this isn't something that is dangerous. This is enormous opportunity. And you have the ability to become the kind of man or woman that you admire and want to be. You don't have to be, I don't know, George Washington or one of these great heroes of all time. But everyone out there has the capacity to be a hero to their kids or to be a hero to maybe some... There's nursing homes and there's old people who are lonely. I think that you take in a dog that's on its last legs. These are little things. Terry Shepard does that a lot. I regard him as a hero. These are... Not Terry Shepard, I'm blanking on his name. These are things that people do that aren't heroic in the sense of Superman, but that I find admirable extremely and I think are very underrated because these people aren't championed. Is this some kind of weird, passive aggressive indirect way for you to tell me that I should take you out for your birthday on Monday? Is that why you gave that whole speech? That wasn't it at all. That was a joke, Michael. No, it was a failed joke. Nevertheless... There was no punchline. Without failure, we would not have triumph. Can we stick on the Camus absurdism versus existentialism? Sure. What do you think is the difference? In your ideas about anarchism too, it seems like you it seems like those are somehow intricately connected because existentialism is connected to freedom and freedom is connected to anarchism. Sure, but I mean, Sartre was a defender of the Soviet Union. He said explicitly about things like gulags, like even if it's true, we shouldn't talk about it. So, what people don't appreciate is how human beings can have contradictory ideas in their minds at the same time. So, one would think, okay, someone's a Democrat, they think ABC, therefore they can think DEF. People that have all sorts of contradictions and it's not at all clear and they'll have a clean conscience because the human mind is very sophisticated and is capable of doing this. So, Sartre, you would think he's this radical individualist, this sense of ultimate freedom, but he's defending the Soviet Union. Camus, on the other hand, would probably be, he was very much like a social Democrat. He didn't really talk about what politics should be so much as it shouldn't be. His essay, Reflections on the Guillotine, is one of the great masterpieces of all time, an attack on the death penalty, not in terms of no one's evil or it's wrong to kill murderers, but in terms of what does it do for a society. If you have someone who takes a person and locks them in a room and says, in two years I'm going to murder you, and you lock them for that, this is not someone we regard as moral. We regard this as someone who's a complete monster, but that's what the state does with the death penalty. And he challenges us to think, is this the kind of people we want to be? And again, he's saying, I'm not saying killing a murderer is wrong. I'm not saying evil is wrong. His entire career was dedicated to fighting the concept of evil. But are we the kind of people who want to be doing these things that in any other context we regard as torture or deprave? So I'm much more of a Camus person than a Sartre person. He was probably against war in that same way. So I don't, I have to admit, I don't know much about the political side of Camus. Well, and I don't think his political side is that interesting or relevant. What I find, sorry to interrupt you, what I find fascinating about Camus and what I think about on a daily basis from him is his insistence that you have to live a life based on conscience, that you have to be accountable to yourself when you put your head on the pillow at the end of the day and ask yourself, did I live a righteous life with integrity, true to my values? Did I not needlessly cause harm to innocent people? That kind of mindset. Did I, if someone is weak, am I using that as an opportunity to exploit them or to harm them? Or do I feel a bit of sympathy or empathy for this person because maybe they didn't have circumstances that were as beneficial as other people had? Well, how does that fit absurdism where everything is absurd, nothing has meaning, it really borders on nihilism? So he regards, his philosophy explicitly said is a response to nihilism and a attack on nihilism. He regards cynicism as the worst value people can have and I agree with him 100%. A lot of times people call me cynical online and I push back very, very hard because to be a, I had this quote in the New Right where I said, I'd rather be naive than a cynic because a cynic is a hopeless man who projects his hopelessness to the world at large. Camus, this is the metaphor I use and I find it very inspirational. I thought it was in his work but I guess I thought if I described it to him. There's two types of people. You imagine you go to a mountainside and you see a blank canvas on an easel standing in front of this mountainside. One people be like, why is this blank canvas here? What is this? What's going on here? And just be confused. Whereas the other type of person will be like, this is a blank canvas here in this beautiful countryside. What a great opportunity. I can paint this river. I could paint that bird. I could paint my friends or myself in the background. Infinite choices and this is a gift that I have been given. And I think that also ties very heavily into what I was, I went to yeshiva as a kid, which is Jewish school. What we were taught incessantly how to look at life is this beautiful gift that God has given you and that God wants you to be happy. He wants you to live to the fullest in a moral way. I remember the first time I went into a church and they were asking questions about the Jewish concept, the afterlife. They weren't familiar with Jewish thought. And it took me a second because I didn't really have answers. And then I remembered what we were taught, which is let's suppose you're at this banquet with the best chef on earth and the table is so heavy because you've got steaks and you've got chicken and you've got sushi and the wine's flowing and you've got your Dr. Pepper and Mr. Pibb and the store brand, everything you want. And you're looking around at this amazing bounty, right? And then you turn to this best chef on earth and you're like, oh, so what's for dessert? I mean, the offensiveness of that is just so insane. You have this eat the meal. I promise you if I could deliver this meal, the dessert's going to be okay. So this focus on the afterlife when we've been given this amazing gift on this earth is a very kind of different mindset from both the Jewish tradition as I'd been taught and the Camus mindset. Obviously, Camus was an atheist, didn't believe in an afterlife. But this concept that life is meaningless, but that means you have that opportunity to find value, to seek for truth, to seek for happiness. And Camus has this quote, it's ascribed to him, it's like a meme. I've never found the source, so maybe he doesn't really say it. But he says, maybe it's not about happy endings, maybe it's about the journey. And I think when you have that mindset, and as you and I, I think you and I both found this because neither of us when we were kids thought we'd be doing this, right? But now that we are really fortunate. Definitely this. Yeah. And definitely that. Yeah. But now that we're fortunate enough to do this and that we're blessed enough that there's people who find this of value and interest, and we could pay the rent doing this, there's not a day that goes by where I don't think you and I think this is pretty absurd. But it's also pretty wonderful. And as a consequence of us thriving, it also shows other people that happiness is possible on this earth. And I think cynicism is the lie. It's not just the worldview, it's a lie that happiness is not possible on this earth, or it's only possible if you sell your soul and you're a bad person, you screw other people over. I reject that in every aspect. As you said, my birthday is coming up. I've been feeling just a lot of really great things have been happening very, very recently. So it affects me very heavily emotionally, especially when I see the response it gives to the kids. So it's one thing to say, this is what I'm for. But when you can provide proof of concept that what you've been advocating does result in positive responses. I got a message from this kid who had tried to kill himself a year ago. And then he was like, look, I found your work, I found some other stuff. And now I realize I'm going to make something of myself. I was born in a meth house. I'm whatever 19, 20 years old, I should be in the garbage, but I'm going to try to be a standup because I have opportunity on this earth. Even if he fails as a standup, he's still such whatever he does, washing dishes, there's no shame in that. Is it so bad to have a crappy job and a girlfriend who you don't really like, but as compared to the alternative of like, I'm going to kill myself, this is heaven. Well, I think there's beauty to be discovered in all of it and all of those experiences. But at the same time, I often think about, I just recently reread The Idiot by Dostoyevsky. I often feel like the idiot. That's why when I say I'm an idiot, I often think about Prince Mishkin, that kind of idiot, which the world sees you as naive. I don't think he's naive. I don't think I'm naive, but I tend to see the good in people and the good in every moment. The world often is cynical. In fact, especially in what we do, often the intellectual is supposed to be cynical. This is very much an urban elite educated mindset where if you write a book about someone who's, let's suppose a drug addict or a prostitute, that has heft and that's valid. But if you're writing a book about a love story, two people fall in love and they're in roller coasters or carousels, that's less legitimate. I hate that. I hate that. I hate that so much because the message it gives to people is you have to choose between thriving and happiness and silliness and seriousness and depravity. I'm not saying that drug addicts and prostitutes are depraved, but basically their worldview is, unless it's dark and twisted, it doesn't really count as art. I despise that mindset, that subtext. So the internet and people around me often will call me naive because I don't know. I think the word they want is innocent, don't you think? But it's not that innocent. No, but innocent in that you genuinely in your heart, I know you fairly well at this point, believe that goodness is possible and that people can, if not be good, at least be better than they were yesterday. Even the word naive or the word innocent presumes that there's not wisdom in that, presumes that somehow that's, oh, isn't that beautiful to live that life of a child who sees the world with these bright eyes and is hopeful about the future, but just wait until they grow up and realize that reality is much harsher than they think. But that child might be wiser than all of the adults in the room. And don't you want to be, if the world is like that, don't you want to be the guy who takes it on and changes it for the better? Right? So it's like saying, well, cancer's everywhere, it's inevitable. Well, don't you want to be the one who says, not anymore, I'm here and I'm going to make that change and I can see it being better than it is now. So I think you and I have the same analysis of your worldview and I don't think that there is a good word for it. So I guess it's this idea of inherent benevolence might be, maybe wordy, but I think that's more accurate because you and I did not have such easy lives growing up, to put it mildly. You constantly talk about just horrific aspects of life. So to claim that you kind of don't know that they exist or you sleep on the rug is completely not accurate to your work and your mindset. Can we talk about World War II and the Soviet Union? Sure. So on Sunday, June 22nd, 1941, Hitler launched Operation Barbarossa, which was the surprise invasion of the Soviet Union. If I could read to you a few lyrics from a song that for some reason has stuck throughout my childhood. It was a famous song during that time. The song talks about Kiev, like that moment as part of that operation that Kiev was first bombed and it was announced on June 22nd. The song says at exactly four o'clock that the war has begun. For some reason, this song haunts me because the exactness of that time and this realization that at any moment you can have this thing happen to you in your own personal life. Maybe we had something like 9-11 happen where everything changes. It's just like haunting because it makes me think that at any moment something like that could happen that changes everything. I just think about normal life going on in Kiev at the time and then all of a sudden the bombs are dropping and they announce that the war has begun and you thought you were going to stay out of the war. This is something that is very intensely emotional for me because you and I are both Russian Jewish. To know that my grandparents and my great-grandma were told that the Nazis are coming and this was an address rehearsal and that if they get here, which they do, they did. Lvov is very Western Ukraine, that 100% you and all your relatives are going to be murdered. There's a monument now in Lvov where I'm from about this, but I don't think either of us can imagine what it's like to think that we're about minutes or whatever hours or there's just the Russian army standing between us and everyone we are related to are going to be murdered for no reason. What's the closure here? They evacuated a lot of people, but they didn't evacuate enough. To know that there is this force coming to 100% murder you, this isn't some kind of the TV news being hyperbolic. They're coming to kill you. If they get you, they will kill you. We all think about war like, oh, we hope America wins in Iraq, rah, rah. If America got their ass kicked in Vietnam, it's not really going to affect America in the sense that you're going to have the body bags and all the kids being killed. That's something that I'm not super in the rug, but no one in America thought the Vietnamese are going to come here and kill them. They were secure in their person. To have that sense of we've really need to win because if we don't win, we are 100%... We, they, the Russian army doesn't win. We are 100% all going to be slaughtered and often in not just a bullet to the head and in sadistic ways. It's something that to know that people who share my blood saw and went through is very hard for me to kind of wrap my head around. There's no possibility to delude yourself. Yeah, yeah, yeah. Because they would, as the song also talks about, but they would burn the factories. So it's basically saying, we're in the war now. This is- This is your life, yeah. This is our life now. You know how yesterday you were worried about, oh, I misplaced my pen. Where is it? It's like, yeah, this was paradise. Most of us are going to... Our life now is that most of us are going to die. And if we want to prevent all of us from dying, we have to fight. And we also can't sit down in some kind of weird desert island or plane crash situation and be like, let's decide between us who's going to be the first to die. Maybe the Titanic, right? They sat down and they were like women and children in the lifeboats. They had this rational agreement. You don't have those choices in a war. So it's something that I... It's just very chilling. And it's something I don't really have the emotional space to understand or grapple with. Obviously, I've been to North Korea. You can see it and so on and so forth. And you and I can't, or anyone listening to this, except for maybe on me and people like that, you can't imagine what that's like to live it. We can't imagine what it's like to live in those situations where it's not like before Hitler came, everyone's dancing around and having a great time. I mean, imagine what that life is like where your preference to Hitler is starving and waiting online for hours for bread and to have the secret police and your friend's attorney win and your phones are all tapped and you're a prisoner. But to you, this is infinitely better than the alternative. These are the choices that our family had to deal with. It's something that no matter how much you... It's like a... Let me put it in terms people can understand. You know what I mean? It's like your first bad breakup, right? That's a much simpler thing to wrap your head around because it's like if you've never had it, you can't really... But when you feel it, it's just so intense, but you can't tell someone what it's like. We could sit down for days and hours and have people tell us, but until it's the totality of your environment and your life and your mindset. I remember my grandma... She would talk about it like, when you're that hungry, all you're thinking about is bread. Yeah. Because your brain won't... Human beings, we evolved, we have instincts, whatever, and the mind is telling you food, food, food, food, food, food. And that there's kids thinking this and that they're not going to get the food. Yeah. And you imagine being a parent and your kids- Watching your kids without food and knowing they're not going to get the food. And the fact that this happened in North Korea in the 90s, I met a refugee and he had to watch his dad starve to death. And thank you. And we have no concept of what it's like. It's just like last night here in Austin, all the places were closed and I couldn't get my protein powder. And this is the extent of my suffering when it comes to food. There was a restaurant that I went to in Brooklyn where for some fakakta reason, they weren't serving sashimi, they only had sushi. So I had to have the rice and the carbs. To live a life where that is the extent of your food problems, as opposed to the choice is either Hitler killing you or being hungry 24-7. My grandma told this story of how they had a close call. It was her and her brother and her mom, my great grandma who passed. And I think there was either a helicopter overhead or something. And my great grandma jumped on top of my grandma's brother and not my grandma. So she basically did a Sophie's choice, my grandma's name is Sophia, and chose the brother. And this is something that she felt all her life that her mom had chosen her brother over her. But these little things that happen, these little decisions we have to make in war, there's a book I read called Five Chimneys, I think, this woman who was an Auschwitz survivor. And what she talked about, what people don't appreciate, it's not necessarily the slaughter and the torture, it's that there's no rhyme or reason to it. She talked about how they had a camp just for people from Czechoslovakia, and they were treated better than the Jews. And then one day, they just killed them all, right? And she's like, I still don't understand why they're giving them food and treating them well. And then the next day, they're all killed. And we will never get answers. And things like, she talks about how they decided to kill all the kids. And they didn't really, either for some reason, they didn't have the courage to or they wanted to be cruel. So instead of shooting them, they just kept walking in the snow until they all died. So it's things like this, that the fact that you and I dodged these bullets, and that we can be here and be doing this and running our mouths for a living, I think about it all the time. And it's just very disturbing to know, and I know you know this as well, that there's lots of places on earth where if people had a choice, they would kill us on sight and be proud of themselves for it. Yeah, I don't know what to make of the contrast of that. You were talking about the fact that you've been truly happy the last few weeks and months. There's been a lot of moments of happiness and joy. And that joy is built on a history of human suffering. Like in your roots, in your blood, is a lot of people that were tortured, that suffered, so that you could have this joy. And you have both the, you have the responsibility to truly be grateful for that joy. But it also shows that there's the happy ending, that it does end in a good note, that it does get infinitely, infinitely better. And that I think there's a, I don't like using the word responsibility, but there is an opportunity for those of us who did dodge that bullet to give testimony to these people, and more importantly, to give testimony to the people who are going through this now. So, one of the reasons I talk about North Korea so much, why I wrote Dear Reader, is because it's very easy. And this is human nature. I'm not condemning people. I think that's just how people are wired. When you see an Asian country with Asian people, and things are bad over there, I think in the West, it's like, oh, Asia, they're all crazy. They're wacky. They eat dogs or so on and so forth, some weird stereotype. And they think of them as kind of Martians. So, it's important for people who aren't of that kind of ancestry to kind of speak on behalf of these people, because it's very different how just people just naturally react when you have a Westerner talking about this. Instead of it becoming their, you know, them over there, it becomes, you know, this could have been us very easily. I have a friend, Peter Veyhansky, great dude. And I was showing him photos when I was in Pyongyang, and he goes, this looks like a Russian city with Asian people. It completely disturbed him. So, you know, that was one of the reasons I did go to North Korea, because that was as close as I would get to see what your family went through, to see what my family went through. And they're still living under this regime. And one of the things I fought very hard to do with Dear Reader, which I was successful in amazingly, and it just, I said, like, I could die now. Like, I feel like if you make, if you just move the needle a little bit, then you've kind of paid your due for your time here on this earth, to have it change from being a laughingstock, you know, and I think Team America did a good job. They made Kim Jong Il into a clown, and they made a joke of it. But you're going from nothing to jokes. At least now people are aware of it, that it exists, right? And then I, and many others, took it from a joke to like, guys, this is really, really, really bad. And none of us can even appreciate how bad it is. And I think now there is an understanding, other than a few people who are just looking at through a Trump lens and wanting Trump to fail, because Trump's an asshole, and that's fine, to be like, these poor people. And it's really unfortunate, because there's a segment of Western culture, who thinks that correctly, often when you're complaining about or discussing the plight of another country, that's just your prelude to war and an excuse to invade. Like the Kurds in Syria, you know, we're talking about, if we're not in Syria tomorrow, it's going to be another genocide, blah, blah, blah. I'm not saying, let's invade North Korea and things like that. All I'm saying is, you know, thank God that this isn't your life. I bring this up all the time. The woman who was my guide when I was there, I'm aware of what she's up to now. She's still, she's extremely rich by North Korean standards, but she'll never be in a position to buy medicine. She'll never be in a position to go on a vacation. Things that you and I just, you know, whatever, she can't go on the internet. She can't get an encyclopedia. She can't better herself as a person, other than through what the state allows, and meaning better yourself as a person in service to the state. So, I mean, it's also frustrating, because there's only so much that I can do as an individual. What's your takeaway about human nature from looking at North Korea and looking at how the rest of the world is looking at North Korea? I always, this is a great question, I think about it fairly often, I always say human beings are animals, right? When you say someone's an animal, it's like a slur, like he's like a beast. Animals are capable of enormous kindness, empathy, sympathy, you know, they look out for one another, groom one another. There's a thing with apes where they groom each other for parasites, and you're supposed, even if there are no parasites, they pretend there's parasites just to have that kind of bonding. You see infinite photos online of like cats raising puppies, because the puppy's mom died, things like this. That's part of being an animal. Part of being an animal is also just the most monstrous cruelty, killer whales, you know, there's this big PC move to not call them killer whales and just call them workers. They will murder blue whale pups, calves, excuse me, and play with them and not even eat them. So they just murder for the sake of fun. So there's and cats, you know, kill birds all the time, things like this. So it runs the whole gamut. And I think it's, I'm, you know, when you're on and I run your show, I don't think Lord of the Flies is accurate. I don't think Hobbes is how reality works when you're in that kind of state. But I think we've seen countless examples of human beings, especially when human beings have power over someone who's powerless, of allowing themselves to engage in not just harm, but cruelty. And that is something as Soviets, you and I are very painfully aware of it. It's not just about the oppression, which as bad enough as it is, it's that mediocre person with that little bit of power. And now they're standing between you and your daughter having medicine, and they love it to make you dance to be like, oh, you need me to get this medicine, make you go through hoops, because now they feel like for the first time in their life, they're in a position of strength and power. I think that is, in many ways, the more common nature of evil that what Hannah Arendt talks about the banality of evil, than someone who's like an SS guard, you're shooting someone in the head. Like that, I think we could all wrap our heads around to some extent, like, okay, I'm a military, it's not easy, I have to execute people pulling a trigger, you could kind of have this mental disconnect between the finger and the victim. But like that little day to day stuff, like, are you doing the right thing on a day to day basis that I think is far more common, and far more disturbing aspect in certain senses of the human psyche? Yeah, there's something especially disturbing about a weak man given power, and just abusing that power. There's something about not just weak, but like, mediocre at everything he does, or less than mediocre. A great example of this, which I'm also talking about in the next book is Ceausescu, who was the dictator of Romania. So, you know, the Cold War is still somewhat poorly understood in popular culture. But the different countries in the Second World, the Soviet bloc, some are more liberal than others, some are more sane than others. And Ceausescu, at first was one of the more Western friendly, more the free ones. Then he met the great leader Kim Il Sung from North Korea, and he had the idea to impose a personality cult on Romania. And it's the kind of things like forcing people to breed because he wanted to make people taller. I think he made like the biggest building in all of Europe, the People's Palace, but it was just for him. While there's no electricity, you know, elsewhere. But you look at this guy, Stalin's a badass, right? He was a bank robber. If you look at photos of him as a kid, he was a hunk. Lenin was clearly intellectual. These were powerful, Trotsky, these were powerful men with huge egos, huge force of personality. But you look at this Ceausescu guy, and you could, like, for example, on my driver's license, instead of my address, I'm like in my real address being like, 12345th Avenue, by mistake, it says 12345th Street, right? So you can imagine him being in the post office and me giving him my ID to get my package and him being baffled because this says street, this says Avenue instead of understand. And this, the look on his face, this dullard that you can see how, you know how sometimes I'm going to, can I curse? Fuck yes. Yeah. So if you know, like, if you're in the airport and you see someone and you look at them and an adult, and you think, okay, this person was born fucked up, just like on sight, like something's wrong with them. How are they traveling alone? You look at Ceausescu, you look at him, you're like, something's not right with this guy, not in the sense of like evil, but in the sense of he's a simpleton, right? And now he's in charge of this whole country, and everyone's taught to regard him as one of the great geniuses of all time. And it's this, the idea of this mediocre nobody, this guy would have in any other culture been accomplished nothing or would have had an honest job where he's like, okay, he works at the mail service, and he's bad at it. Okay, fine. He's not hurting anyone. And now as a result of this, he's responsible for mass death, secret police and incarceration. And, you know, one of the greatest things I've ever seen, which I'm sure many people see as well, if you go on YouTube, it's his speech. And it's the first time the crowd turns and his head kind of like, because they start booing him, which was unheard of. And, you know, he was shot with his dog faced wife, not that long after, it was just a great moment. But it's things like this, I agree with you that that mediocre weak person is now in a position of power over somebody else. And that sense of vindictiveness, like I'm going to feel strong for once in my life, but it's going to be at your expense. That I think is, you know, human nature, it's most primal. And every time I meet a person in this world, you're the first person to get me to cry on a fucking podcast. Fucking the robot gets me to cry, what the fuck is going on? Every time I meet a weird person, somebody, to me, heroism is also taking a risk to rebel against mediocrity. Yeah. Like in the most simplest of ways, like the license address, like taking a risk to break the little bit of rule that nobody will know about, to take that little bit of a leap of like that, that little protest against the bureaucracy. Well, like that Nazi guard where he just spoke out, he's like, Hey, lady, that's a big one. Oh, that's a big shirt. I mean, like literally at the line at Starbucks or something like that. Like even in the tiniest of ways, when I see people just like, it's almost like that little, like glimmer in their eye, a wink, like we're in this together, this there's, there's all this conformity all around us. That's at a different time could have been Nazi Germany, could have been a Stalinist Soviet union. We're in this together. We're going to rebel against that conformity by just, just taking the risk, that little bit of risk against mediocrity. I don't know. And that, and then once again, I see this in companies too. When I see the mediocrity, I see this, you know, I used to work at Google. I see it in Google. And when the companies grow, that mediocrity is overwhelming. The Peter principle, right? The Peter principle. Yeah. Yeah. My hope is that all of us have the possibility for that glimmer, that, that risk taking the, the leap of faith or whatever the heck that is the leap out of the ordinary, out of the conformity, out of the mediocrity. So this is where you and I disagree. I think most, a lot of people are not capable of that. They're accustomed to it. I don't know if they're not capable. No, I, I, my position, I understand your position. I'm disagreeing with it. I'm saying, I do not think they're capable. I think a lot of people effectively don't have souls. They do not have a conscience in this sense where they're going to look at an issue, bring their critical thinking and say, all right, I am going to do the right thing. Although I'm taking a risk. I don't think thinking is involved or is it just taking that leap there? There's something about that basic human spirit. Forget the thinking part. It's it, it's just saying like, I'll take that risk. They're taking that adventure. The same thing that got people to explore the seas, you know, that, that, uh, throughout human civilization, explore land, explore the oceans, like that, explore exploration. Like we've done stuff this way all this time. I'm going to take a leap. And that comes out of nowhere seemingly. But those people are the heroes, but I don't think that's universal. I've, there's, I'm going to use a very gauche example. There was a show called scare tactics, which was basically a candid camera, but they would scare people like they'd have vampires, whatever, and hidden camera and people's reactions. And so a lot of, but sometimes it, the prank didn't work out like they expected. So there was one where they were hiring the people who were the marks, you know, the contestants, so to speak, was we were hired to be a security guard. Okay. And you have to watch this, this factory overnight and you get paid. And what the setup was, some people were breaking out of the factory in the middle of the night, like in rags. And they were saying they were keeping us prisoner here, like blah, blah, and just watch the person reaction to this. And there was one security guard where they're, he basically forced them back into the building. And they're like, they're working us 24 seven. We're getting beaten. He's like, I'm here to do a job, get back in there. And you watch this and it never even enters his head to be like, something's wrong here. He was given his orders. He's following his orders. And to me, that is not uncommon. And that person, although they look like you and I, there's something essentially human missing with them. Now, very quickly, the reaction is, well, it's one step from there to Nazism. I don't think it's something that I'm not saying this person should be killed. But I'm just saying to expect that every human being has the capacity to have that defiance, especially at a cost to their own life. That I think is not realistic. But at the same time, I feel like an octopus on the eighth hand, it is those few of us, or if you want to include me in this, who do make these tiny little protests who look the other way when someone is hungry, who's stealing food from the supermarket. It's like, all right, I'm going to pretend I didn't see anything. Those little elements of heroism are what move humanity forward and demonstrate the validity of the human experience, whereas everyone else is kind of like scenery. I think almost everybody in the world can derive deep meaning and pleasure from having done those courageous acts. And I also think they have the capacity to do them, to discover that meaning and happiness. So you're the cynic, then why aren't they doing it? They haven't gotten a chance to, like I've never tried LSD or DMT. You haven't gotten the chance to try this amazing journey, which is taking the risk. That's nonsense. Because as you just said, two minutes ago, everyone has that chance every day to do the right thing. We have the chance to do a lot of things and we don't realize there's a lot of stuff right in front of our nose that we don't realize. You have to kind of wake up to it. Sometimes you need the catalyst. There needs to be some kind of thing that happens that wakes you up. The fact that most people don't take the small acts of rebellion doesn't mean they don't have the capacity to both do so and to derive a lot of meaning from it. Then it's a discussion about how to create societies that get more and more people to be free actors and free thinkers. That's the question. That probably leads us into a discussion of anarchism and so on. But I just think we are very young as a species. We're trying to figure out how to get ourselves to first be collaborative, but at the same time be free spirits. I think both of those are within human nature for most of us. I think another big concern is that there's enormous disincentives, and this is Michael Malice speaking, for human beings to be kind and for tenderness. I think, especially when you're young, when you're immature, a lot of times someone will reach out to you with kindness or vulnerability and you think it's funny to dunk their head underwater in a pool or something like that. When you get older, you look up. There's this one example of this. This was in the 90s. There was a woman. She became a stripper or something like that or whatever it was. She had this amazing body. She was just gorgeous. The show was, she was talking about how when she was in high school, she was bullied a lot. There was this football player. He messed with her every single day. At one day, she even threw pickles in her hair and her hair smelled like pickles and it was laughing at her. This really screwed her up. I mean, up to that show. They took her backstage and they brought out the football player. Now, he's a dad and a regular dude. He's like, do you know why you're here? He's like, no. They're like, oh, what were you like in high school? He's like, I was kind of a jock, bully, whatever. They brought her out. He didn't even remember her really. She just starts crying about the pickles and whatever. This is something that affected her for 20 years. I've never seen a clearer example of someone who wanted to kill themselves than this guy. The guilt on his face and he's looking at her and he's desperate to be like, what can I do to take your pain away, to make it better? He was just crippled by it because he knew there's nothing he could do. He knew he 100% did the wrong thing. He knew he did the wrong thing unthinkingly. You can imagine, I got to screw over this lady to feed my family. That's fine. But at the time, it meant nothing to him. Of course, he didn't remember. He was just paralyzed by this sense of crippling guilt. One of the reasons I always try to do the right thing isn't because I'm an inherently good person, which I do not think I am. I don't think anyone is inherently good, but because I will feel guilty about it for a very, very long time. Because if you do the wrong thing, this is a very Camus idea. If you do the wrong thing to a good person, that's really, really bad because what kind of person are you? In the same way that everyone can be that guy who takes someone out for their birthday, everyone has that ability for someone who did the wrong thing to someone who's a normal person. Do you want to be that guy as well? My friend, Bittstein, he's a big gold, excuse me, Bitcoin person. My biography, Ego and Hubris is like $500 now on eBay. It's hard to find. It came out in 2006. He had told me that you can get it on Torrent. It's downloadable. I'm like, oh, I thought if you're my friend, you'd want to buy it. At the time, it was not $500, I assure you. He goes, I did buy it. I'm just telling you that you could also get it for free, this information that you might want to use. I snapped at this kid who was doing right by me. I felt it just stuck in my head. I'm like, you're an ass. Then years later, I apologized. He had no memory of this at all. I'm glad to be able to reiterate the apology again. A lot of times, I'm extremely aggressive on Twitter and in other venues. I always try to, and maybe I fail, and that's my moral failing, always do it as a counterattack. If you're going to start going personal, if you're going to start being aggressive against an individual, I'm not going to necessarily hold back when I reciprocate. It's something that is very common on social media, but I don't think it is normal. Just because a lot of, this is, we're talking about the quiet little rebellion. Just because everyone else around you thinks it's okay to just go up to people and attack them in the most personal ways, imprompted because of their views, really just take a step back and realize what you're engaging with. Now, if that's the fight they want, then my Soviet cruelty could come out and that's why I don't drink because I do enjoy it. At the same time, be aware of what you're doing. Again, this goes back to Camus's sense that conscience really is what makes us human beings. That's the thing I was saying, I don't think most people think in terms of conscience. We are taught, this is that creeping cynicism that, oh, grow up. When you're an adult, you have to make sacrifices, blah, blah, blah. Even if I buy that for a second, which I don't, but if I have to make sacrifices sometimes, that doesn't mean it's okay for me to make a sacrifice of my values in this moment. If I have to maybe be at work and my boss is a jerk to me and calls me names, I have to be humiliated, but I got to put food on the plate, that doesn't mean it's okay later if I'm at a party and I'm just extremely offensive to someone for no reason. My own flavor of a little bit of rebellion. Sometimes I use the number two. You're very witty on Twitter. Thank you. Twitter likes mockery and wit. Counterattack, Twitter loves that, somebody who's skilled at it. My own flavor of a bit of rebellion is to say things very simply, bordering on cliche with authenticity and genuinely meaning the words I say, but knowing that those words would be, are easy to attack. Sometimes those attacks can hurt because people would just mock me. Sure. People don't like earnestness because they've been taught to be too cool for school. Yeah. There's this pressure for me to be sound way more sophisticated. Use bigger words, sometimes throw in a criticism of institutions or something like that. Almost as if I have a deep wisdom about the way the world is broken, but when you speak very simply about beautiful things in life, it's very easy to sound like you don't know what the hell you're talking about. Sure. And I stick by that. I don't know where that's going to end up, but it's like the idiot from Dostoevsky. It feels like that's the right thing, even if it hurts when I'm attacked for it. I do something similar sometimes, which is I'll have some innocuous comment about bubblegum. I mean, just it's not to be in political. And a lot of times people will respond to this paragraph of just invective about like blah, blah, blah, and then this, and you say this, and you're an ass, and just really trying to get at me. And in those situations, there are very specific circumstances, I will respond and I mean it every single time. I will say, I wish your parents had been kinder to you or your mom or your dad. Because if someone is some, even if I'm some idiot on Twitter, right, who's just talking about bubblegum, and this is your response. I'm not talking about politics where I can see how people get emotional. COVID, my grandma died, now you're talking about. And I realize this isn't about me. I'm someone you've never met, making some inane point about nothing. And you're getting agitated about this. It's clearly something else that's going on here. And someone taught you, someone had to teach you that this is how to respond in this very harsh way. And a lot of times they won't say anything or get deleted. And I hope every single time, there's no asterisk here, that they take a second and they realize that the way that they were talked to growing up was not acceptable, that they don't have to carry this forward, and that they don't have to be kind to me, I'm nobody to them. But take a second and ask if this is the kind of mindset you want to be, your norm, as opposed to a weapon you pull out of your pocket sometimes where it's warranted, or even when it's not warranted. I think there's a lot of those people out there, and we forget how hard it is for a lot of people to grow up, how they're trained from their parents or the single parent, that the only way they're going to get attention is by acting out, that when they do good things, it doesn't get comment. But if they do bad things, they got to smack upside their head. That I think is far more common than we realize. And that's such a, it's not even, it's not hitting the kid that's going to last, it's the pain is going to give five seconds. But when you're training this child, helpless child, is something that's really, really bad. I don't know if it always can be mapped to that. I always wonder about them, like what their motivations are. And I just kind of like whenever I think about them, I think only positively. And I don't even think about the childhood thing. I think, I don't know, I kind of imagine that all of us can go through that stage where we enjoy the derision of others. We go through stages of being- I enjoy the derision of others, but it has to be, you know, Billy, I'd have that quote, like, I like it when people are mean to me, I got to stop pretending to be nice. But like, what's the worst thing someone could say about you? You're not- what harm are you doing? Maybe your podcast is garbage and the people are- the conversations suck and the people are losers, okay? No, the main thing I would say is I'm way more popular than I deserve to be. What does deserve mean? The reality is there's people out there that just enjoy hating on others. And I don't fault them for it. Like, I don't even think of them as haters. I think of them as just people that in this particular part of their life are enjoying this activity of deriding others on the internet. I'm not sure what to do with that. I just don't want to- I don't want to allow myself to think badly of them, I guess, is the thing. I'm the one saying don't think badly of them. I'm saying that I don't think they're inherently bad people. I think that their thinking is screwed and that I'm steelmanning them. I'm saying, let's assume everything you're saying about Lex is true. This is an opportunity for you to outdo Lex. Like, it's- No, but are you saying they should stop hating? Because I'm saying like, maybe they shouldn't just keep- I don't believe in should, right? I'm an anarchist, but I'm saying is like, if this is your belief about Lex- Yeah. You know what it is? I made this comment in my book, The New Right, when people make fun of Andy Warhol and they're like, oh my God, he painted a soup can and now he became a millionaire. I could do this. Well, why don't you? Yeah. So basically, if I go up to you with a check and I say, I will give you a million dollars, you could see the check, you got to paint a soup can, what am I waiting for? So clearly there's a disconnect in their thinking between what they're perceiving and the reality. Because if it was as simple or as- maybe not simple, but as possible for them as they perceive it to be, why are they leaving comments instead of outdoing you? How great would it be for them to have your bigger audience and drive you into the ground? I don't know how that would work because it's not the NBA, but- No, but you want to point out- you do this too on Twitter. You want to point out the hypocrisy, the fraudulence of others, right? Sure, but what are you- you're not claiming anything other than this is- the following is a conversation between me and Michiki, whatever his name is, right? I got the voice down, dude. I got it down. I've been walking around my house doing my Lex impression. I've been leaking motor oil everywhere. Yeah, but yeah. I don't know. I don't know. I don't know what to make of it because I think there's a more general statement to be made. Like, I see Twitter this way too. When I read a tweet, I try to read it with like the best possible interpretation, meaning like, what is the wisdom in this tweet? Right? As opposed to what I think a large number of people- not a large number, but some fraction- try to see what is the worst possible interpretation of this tweet. And they want to destroy you for that worst interpretation. Like, they want to- there's people- I'm already aware of this with me and certainly with a lot of people. They're waiting for me to fail. They want me to be like- this guy talks about love all the time. They want me to be some dark, like, Bill Cosby type character. They want you to be in pain. Yeah. They want you to be in pain because they don't- Why? I'll tell you exactly why. Because this is why I'm so for being white-pilled and being for hope. Because if you are black-pilled, meaning if you think it's pointless, we're all done, you're just wasting your breath. If you have any counter examples to this thesis, if there's even a little bit of hope, your entire hypothesis falls through, right? So, it's kind of how, like, you have all these stories of people who are, like, painting swastikas who aren't Nazis, but just to show that, oh, there's all this Nazism, so I'm going to, you know, kind of force the conclusion. So, for them, when they see you thriving, you are, as a mediocre person with a crappy show, but you're demonstrating that people can succeed. This bothers them. So, you are- Anyone can succeed. That bothers them. Yeah. So, because then why haven't they? So, now, you're a counter to their worldview, and that is going to cause anxiety when you have data that contradicts other data in your worldview, in your mindset. This is a big issue for them. Yeah. So, anyone listening to this, they're annoyed by the look of my face. Remember that you could probably do way better than me, and you should. But also, what would you failing look like? Like, let's suppose this podcast went from whatever views you had to 100 views an episode. That's still success. You are talking to people you like, having conversations about important issues. You're having a good time. They're having a good time. How is that a failure? If I have dinner with a friend of mine, there's zero viewers, and we enjoy that time. That is the height of human success when you are sharing- Happiness. Happiness. Joy. Joy over love. So, what's the difference between joy and love, Michael Malice? I think joy is easier to attain. It's more common. You could share it with everyone. Give me an example of joy. What was a moment of joy for you recently? I could give you a great example of joy, and this is part in the absurdist mindset. I love having a bad meal at a restaurant, and you could see why. You go with your friend. It takes you 45 minutes to get seated. Okay, I'm starving. Waiter's not paying attention to you. They bring your water. It's got a hair in it. They get the food wrong. It comes out again. It's ripe, but it's cold. At a certain point, you're like, okay, I'm hungry. I'm living an anecdote. This is something that if you were at dinner, we could talk about this for years because how great is it that the worst thing that's happening to me is I got to wait an hour for this meal that's going to be cooked wrong, right? That to me is joy, is holding on to that idea that happiness and thriving are possible even when in the moment everything's going the wrong way. Doesn't every moment have the capacity to fill you with joy then? Yes, yes. So it's both the shitty moments and the good moments. Yes. But see, that's the way I usually talk about love is like I love life. Yes. And because life can generate everything, the pain, the loss, but also just like simple or complicated bliss, all of that. I just love all of that. And that because it fills me with a kind of, I guess, joy, but joy has a connotation that it's supposed to be somehow positive. Like you're supposed to be smiling. To me, you know, Man's Search for Meaning with Viktor Frankl, you know, just it's you're in the Holocaust, you're in a concentration camp, just having a little bit of food that you didn't expect you will have, or even just thinking about food. Or what about there's a kid there, you tell him a funny story and you crack him up. Yeah. Like you take away this child's pain for like five minutes. That is the height of joy. Yeah. So to me, like all of like life is like infinitely full of possibility for joy. Yes. And that's what I mean by love, because oftentimes like romantic love is what people think about when they think love. But to me, it's all like part of the same thing. And it's almost like love, romantic love or love with a friend, friendship is like you both notice each other. It's like dogs, they look at each other and then they look at the thing they're interested in. You both notice each other and that moment of joy. You share that moment of joy together. Yeah. Like the restaurant. The restaurant. Yeah. If you're both almost without conspiring, notice the absurdity of how shitty this meal is. And like that, again, that little glimmer of realization, that's what makes life beautiful. You mentioned your grandmother in Lvov. You were thinking of returning there. The plans got a little bit delayed, but what are you hoping from that trip of going back to Russia, going back to Ukraine? What do you hope to get out of it? But what do you think you will feel? A lot of things. First of all, I'm going with my buddy, Chris Williamson. He hosts the Modern Wisdom Podcast. He is one of my closest friends. We've never met. Oh, really? We've never met. He's in Britain. He's trying to get his ass over here to Austin. He's filling out his forms right now. He's too good looking. It's a crime. We call him... I call him Apollo and I'm Loki. So right away, you have a buddy comedy because we're going to film it. You have these two guys who on paper, you're very dissimilar, but we're very, very close. In which way are you similar? I think we're both very intense people, very strong emotionally. We're both very ambitious in the sense that not in terms of career, but we want to grab life by the short hairs kind of thing. We're just both like good experiences. Did he bench more than you? Oh yeah, he's... of course. I mean, the guy's jacked. He's just... Because you know, he's so good looking. He could be one of those guys who's mostly biceps. Oh no, no, no. If you look at... go to his Instagram, Chris Will X is his handle. It's head to toe. It's just sculpted. So he's perfect in every way. That's great. What flaws does he have? Because I need... He has bad taste in friends. And his accent is all crazy. He pronounces it, he's an underwear model. Now I spell it M-U-D-L. Just us two, British and American and just two different dudes. It's going to be a lot of fun. Although to be fair, as you know, I'm an underwear model now as well. Yeah, you're... So we're going to talk that in a second, maybe. But yeah, sheathunderwear.com. Yeah, this episode is brought to you by Sheath Underwear. Are we going to get some pictures eventually? I think we might be... Yes, I have them on my phone. We'll have them. We could share them right... You could slice it in right here. So to be able to go with someone who is a very close... I mean, we meet him, talk like every day, right? So to someone who generally cares about you, who's... He's very, very grounded, right? So a lot of times I'll have some concern and he's really good, and if you listen to his show, at slicing through the noise and being like, hold on a second, I can't do the accent yet. Have you considered A, B, and C? Because whenever I had this situation, this is what I did. So he's really good with that. So to have a... First of all, just two buddies on a trip is really a lot of fun. Second of all, I know that it's going to be very intense. So for you, you left Russia much later than I did. How old were you? 13. 13, right. So you remember it, I'm sure, very, very well. I left when I was one and a half, two. I don't remember it at all. To go to the streets where my family had to go through this stuff, to see the... They came to Lviv, they slaughtered all the Jews. I mean, to have that little memorial there that's there now, and to just look around and know yesterday, basically, they came here, they rounded everyone up. And also, from the other side, you had the Stalinists coming in and starving all the people. It's just to know that so much horror and death. There's this quote I saw once about a woman who went to Auschwitz, and she just made the comment, like, grass grows here. Because we think that when it comes to the nature of evil, that you're going to go there, there's going to be this pits of hell or whatever. There's birds. Robin's hopping around looking for the worms or whatever. They think it's perfectly nice. And you stand there to understand that so much suffering happened here or there is going to be very jarring. I know that it's going to be an issue because I speak Russian and not Ukrainian. And to speak Russian to Ukrainians is a big deal. So that's going to be a concern. I'm also worried about going to Russia because every Russian has this idea that even though they've just met you, they feel that they're in a position to tell you what you're doing wrong with your life, what you should be doing. If they're a cab driver, I have no tolerance for unsolicited advice on a basis at all. That's going to be horrible. They're going to be telling me I need to speak Russian better because you speak Russian like a dork. I'm not hearing it. I'm not interested in hearing it. So that I think, and also, given my upcoming book, The White Pill, and covering what happened back in the day under Stalinism and later, to see this was the Lubyanka, this was the basement where they would, you know, this is something that people might not realize. There's a superb film, The Death of Stalin, which is kind of does what I do with North Korea. You know, he puts a humorous spin on it. And then when you take a step back and you realize what they're actually saying, it's just like, it's very, very disturbing. How when Stalin was dying, he had a stroke. He's laying there in a pile of his own piss. He's unconscious. He be right before he died. He thought the doctors were all plotting against him. So they were being tortured to confess that they were trying to murder him. They had to get the doctors out of the torture chambers to attend to him. And they did it. So this kind of thing to like, go there like Red Square and see this is where it happened to see Lenin's body. Like this is the guy who Emma Goldman yelled at. It's going to be really, because I've worked so much in this space, jarring and intense and emotional. And as intense as it is for me sitting here talking to you about it, to see it and to see the faces and to see Cyrillic everywhere, other than Brighton Beach in Brooklyn, I'm sure it's going to do a huge number on me because as Western and as the Tupoi Mirikanyets, as the Russians will say I am, this is still where I came from. So no matter to see it face to face, I don't know how I'm going to react, but I don't think it's going to be like meh. You've assembled a number of essays from anarchist thinkers in a new book called the Anarchist Handbook. You mentioned Emma Goldman. What interesting things do these thinkers agree on and what do they disagree on? The anarchist handbook.com is the website. It covers from the 1790s to, I think my essay is the last one from 2014, which a friend of mine, who's a kind of a mediocre scientist is going to be reading for the audio book. Also podcast. Also podcast. I never, but it's not a podcast anyone would have heard of. It's like Tom Woods, but even worse. So what they all agreed on was the illegitimacy of government and also the malevolence of state actors and the consequences of governments. So they range in terms that most people would easily regard as either left or right wing, but it tackles the nature of government and also creates positive non-state alternatives from really many different angles. The slogan I have is the black flag, which is the traditional flag of anarchism. The black flag comes in many colors. So they were really all over the map in terms of what they're for, but their disagreement is about the nature of state and the nature of power. And it's very edifying because this is an ideology that's been in many ways swept under the rug. No one takes this seriously. Grow up. That I can allow people to sit down and read these essays and see for themselves just how beautiful this tapestry over the decades and centuries has been woven about people who genuinely believed in freedom as the most important and how to maximize that for a society. So maybe it's useful to talk about a few contrasting thinkers in there. Sure. So one is Leo Tolstoy. Oh yeah. Who I think not many people know is an anarchist. Yes. A Christian anarchist. Christian anarchist. Yeah. So he came to despise government for his deceit and his violence, but to him, the Christian principles of nonviolence, I think are important. Oh yeah. And it's kind of pacifist kind of mindset of, you know, it's better to someone to punch you than to punch them back. So he's in that way, at least I read he influenced MLK and Gandhi. What do you think about this flavor, color of the anarchist flag of nonviolence, nonviolent opposition? I will put the caveat that it bothers me when people bring up MLK because he's become so corporate and everyone just brings him up without knowing about him. One of the things that Martin Luther King did so very well was that he forced people to face the consequences of what they were putting forward. You want to be racist. You want to be for Jim Crow. You want to be for segregation. Okay. It's easy for you to do that from your living room. Now turn on your news and you see men and women in suits being attacked by dogs, being attacked by fire hoses and beaten by cops just so they could sit on the front of the bus. And now for a lot of people who were still racist, who were still had animus toward black people are watching this and it's going to be a lot harder to be like, I'm okay with this. I'm okay with human beings, even ones I regard as somehow bad or inferior to be beaten and attacked by trained dogs and they're not doing anything in response. That strikes to, I think, a very basic nature of, especially American, like, okay, whatever you're for, I'm not for people getting beaten and attacked when they're not really doing anything. So I think pacifism is something that's very easy to make fun of, but people don't underestimate how powerful it is for someone to say, you can do what you want to me. I'm not going to fight you back. I just want to live peacefully and have the same rights as you. And to say, screw you, you should get beaten. That's a hard pill for a lot of people to swallow. So I think he was really, and Gandhi, of course, as well, were excellent in that regard. There's a little bit of Machiavellianism to it. They've both been beatified in regard to saints, but their strategy worked very, very well for their purposes. So I think just all of us, when you see someone in this kind of Christian, I know you're Ron, obviously, it's nothing very highly Christianity, but if he's someone who's willing to take a punch and to say, you could do whatever you want to me, I'm not going to hurt somebody else, instinctively, and maybe this is kind of a hack, most people want to side with that guy, step in between and be like, oh, okay, let's take a step back, because whatever led to this is not tenable. We need to go back to the drawing board if the consequence is people are having these as a result of my decisions and actions. So I think that aspect of anarchism is very, very, in certain contexts, healthy and much smarter and more sophisticated than people give it credit for. And let's also point out that Tolstoy wrote War and Peace, and he wrote Anna Karenina. So this was not some naive or innocent, whatever word you want to use. He knew the nature of evil. He knew how bad things get. So he wasn't saying at all that human beings are inherently nice and kind. He was saying it's much more effective to not fight back and to force them to face that. I'll give you another example. I was on the show Trigonometry, and I was talking to the hosts, and one of them talked about how someone he knew had been the Gulag, or his mom was born the Gulag grandma. And after Stalin died and the Soviet Union liberalized and lots of the people in the Gulags were freed by Khrushchev and so on and so forth, I didn't know this, but many of the, or some, let's say some, of the guards of the Gulags killed themselves because they had genuinely believed that everyone in these camps was there for a reason. And when they found out that these people were completely innocent, didn't even have trials, and that they were the ones forcing them to work themselves to death and starve, they couldn't deal with that guilt. So when you are a pacifist or non-retaliatory, and you're forcing someone who's using force, look what you're doing. Look what you've become. For some people, some people don't care, like the guy in Scare Tactics, like I mentioned earlier, where for a lot of others, they're going to be like, okay, is this who I wanted to grow up to be? They will have that little flame of conscience that you and I talked about earlier. They will be like, how did I get to the point where there's this lady who wants to ride the bus, and she's lovely dressed, put together, and I have a, sending a dog on her? What kind of person am I? For some of those people, they're going to be like, okay, I can't be a part of this. I don't even understand the politics. I still am racist, but I'm not going to take part in this atrocity. Well, that was for him, from the individual perspective, perhaps he calls that Christian, but listening to that voice of conscience, like whatever that is in you, so for Tolstoy, it seems like anarchism, from the individual perspective, is silencing the rest of the world and listening to the, for him, probably God-given voice of conscience. And so that's what it means to live, embody anarchism. And to embody Christianity, I would think he would say. But he would see those as basically- Yes, correct. Yeah. So in terms of forms of government, the Christian government is one that's no government. Yeah, correct. What do you think about that as advice for an individual? Turn the other cheek. Do you think, I tend to believe that that's a really good way to live. I think it's very underrated, and this is me talking. I think a lot of times when someone, let's suppose you're having an argument, but you have to pick your battles, right? Let's suppose you're having a heated argument and someone says something very cruel to you, where you are tempted to double down and hit back twice as hard. But if it's someone who at all cares about you, where they're just in the moment and you just stop and you just say, did you hear what you just said to me? For some cases, that person will take a step back and be like, just like when I snapped at Michael at Bitstein years ago, I'd be like, wow, okay, this is bad. This is bad. I'm sorry. And it's kind of like they have to get to 10 before they control or delete, to use your language. Thank you. But for overflow, I appreciate that. And for some, they're going to just twist the knife. But I think this is a very useful technique. And also, you can also sleep well at night because you could be like, as much as this person tried to hurt me, I still didn't reciprocate. And yeah, I took that punch and it sucks, but at least I never said anything that I could feel guilty about. Exactly. Do you think that's ultimately a good way to implement anarchy in your personal life? Implementing anarchy in your personal life just means respecting people's boundaries. It means not forcing people to do things that they otherwise wouldn't want to do. I think you then have to take case by case. There's so many human interactions that are required for life. And there's tension and all those kinds of things. It's not always... Am I being naive or innocent? You're being so naive. Should I put the hat on? The hat's on the other head now. Well, I had to take off the hat because it's like Frodo with the ring. I was starting to feel powerful. I wanted to give you orders. I think there's ways of dealing with the tensions that are natural to human interactions that can't be simply... It's not as simple as saying you want to respect the freedom of others and the boundaries of others. It's like you both have to agree on stuff and work something out. And the mechanisms of that agreement, the game theory of that agreement requires different hacks and strategies. And the question is for an anarchist collective that's well-functioning, what kind of hacks, what kind of ways of behavior are more likely to be productive and not? That's almost like the question, do you want to turn the other cheek or do you want to stand your ground really firmly? When somebody is an asshole to you, you walk away. Or when somebody is an asshole to you, you turn the other cheek and give them a chance to rise to the best version of themselves and then find a common ground kind of thing. It's an open question of how to form those collectives when there's people with difficult childhoods and all that kind of stuff. Well, this also comes down to what is your relationship with this person? Is this out of character? If you and I got into a disagreement, all of a sudden you started getting very personal. First of all, I'd be very hurt, but then I'd be like, this is out of character for Lex. I'm sure I could be like, whoa, let's take a pause here. You're getting heated, I'm trying to work this out. What's going on here? And you get a meta conversation. But again, you and I have a relationship of mutual respect. So as opposed to if it was a stranger who just wants a piece of you, it's just like, you are coming at me not correct. I don't have to reciprocate in kind. I'm not going to shoot you, but I'm not going to pretend that you deserve respect when you're treating me with such contempt. I do defer, especially with people I know, because this is smart long-term game theory as well as the right thing to do. I do try to give them the benefit of the doubt at first, right? Because if you're going to go aggro, you can't go back. But you could always go from, let me hear them out, and then I could go aggro. So there's a big asymmetry there. Yeah. I don't think anyone has the answer to this question, is that the right strategy? To me, game theoretically, it seems the right strategy is to- Well, reciprocity is what game theory says is the right strategy. They did the prisoner's dilemma, and they found tit for tat is the one that's the most advantageous. So that's for when it's perfectly rational actors. But when you have, I mean, there's noise. There's, I think, benefit to just, even if they keep being shitty to you, still being nice to them for a while. Well, then there's the inverse where girls are turned off. Some people, like if you're in a relationship, and not just girls, but some people, when you're kind to them, they find you less attractive, right? That is kind of this weird, what am I supposed to do? You're only into me if I'm mean to you. I don't want to be mean, but then I'm getting punished for doing the right thing. That's another tricky one. I mean, this is nothing that necessarily has to do with anarchism so much as human beings are infinitely complex. We don't often know the backstory. For example, just yesterday, Jay, who's here, is one of my closest friends. I had a dinner with a bunch of people. I couldn't bring a plus four, so he wasn't invited. He didn't know the circumstances. He just thought we were having dinner without him. He was hurt. Once I spelled it out, he completely understood. I felt horrible because for me, to have any of my friends feel left out is just a very, very cruel thing. I felt bad, and I'm glad to apologize again publicly that that's ended up being the circumstances. A lot of times, we're also in Plato's cave. When you're dealing with somebody else, you have very, very limited information about their background and circumstances. That's why I will always, if it's someone I even have a little bit of a relationship with, try to give them the benefit of the doubt because I found, especially this comes from being a co-author. When you co-author books and you're walking in other people's shoes, you don't know a lot of the information. A lot of times, it's just a misunderstanding. But isn't that a fundamentally anarchist question of how we figure out this puzzle of human complexities in order to form voluntary collectives? We have to figure that out, how to make people feel good, how to make people- I agree. That's fair. I think not only anarchists have to think about this is my point, of course. But we have to think about it more than others do. Right. I feel like I should try to argue against anarchism at some point, out of love. Because people enjoy seeing me, what is it, when Ben Shapiro argues against a 20-year-old feminist- Ben Shapiro destroys high school students with facts and logic. This is this video of Michael Malice destroys a Marxist Russian communist pig. So anarchism as opposed to hierarchies. Well, that's left anarchism, anarcho-communism, yeah. The state. But there are many hierarchies that are not the state. We have a hierarchy here. This is your show. I'm differential to you. Right. But they're rigid hierarchies. Forced hierarchies is the- Forced hierarchies. Forced hierarchies. Okay. So do you think it's possible that humans, when left on their own accord, they form hierarchies naturally? Yes, inevitably, in my opinion. Inevitably. Which is why I disagree with the left anarchists. I think it's not a coherent thing to argue for non-hierarchical relationships, even in theory. It doesn't make sense to me. And I know the old-school anarchists will call me stupid or uninformed, but I've never been able to even wrap my head around this claim that you could have relationships without hierarchy. Right. So I guess there's a certain sense in which we're living in anarchism now. And I don't mean just because the nations, as you've said, are in anarchism relative to each other. But isn't the United States just a collective that was formed in anarchy? And this is just the collective that we're operating under, this hierarchy that was naturally formed. The United States was not naturally formed. It was formed by force and by fiat. But to your point, I stress this throughout the book. I always say this anarchism is not a location, it's a relationship. So yeah, you and I do have a hierarchy in that this is your show, but neither of us really has an authority over the other. I'm here voluntarily. You can kick me out if you want. I can leave it any way you want. Neither of us has the power to force the other to be in this relationship we've chosen. My lawyer, I defer to his judgment. He's not forcing me to do it. He gives me his advice and I could take it or leave it. Same with the doctor. So there is clearly who's in charge and who's not in charge, but they're not in a position to impose their will on everybody else. And you could very easily see John is Stephanie's lawyer and Stephanie is John's doctor. And in each of those contexts, one has this position of ostensible authority over the other. So anarchism is in fact not some utopian crazy thing. It is the norm of human relationships where you meet people, you're not necessarily equal. Someone's going to be taller, someone's going to be stronger, someone's smarter, wealthier with others, but you're not at all thinking, I am here and I could tell you what to do. And you are legally or morally obligated to follow my wishes. That is the basis of anarchism. So what way is the United States imposing by force something on you, do you think? If you leave your house, you will go to jail. My money being taken from you via taxation. Right. But don't you have the freedom to not operate under that? No, but that's like, yeah, like technically if someone comes up to you and mugs you and says your money or your life, you are making a choice. But what the anarchist argument is, they're not in a position to force you to make that choice. That is not morally binding, even though they have practically the power to force you into that dilemma. But you have the freedom to live under the United States or not. So even... I see. Yeah. The argument is if you don't like it, leave. Right. Not necessarily leave like geographically, but there's ways to live outside the force of the United States. There's ways, it's just very difficult to operate that way. But that's like saying you could outrun the mugger, which is true. But the issue is, does that mugger have the right to tell you at gunpoint, you either give me your money or I'm going to shoot you or secret plan C, you get to run away. Is that person a moral actor? And the anarchist answer is never. And the difference... Just one more thing. The anarchist view is the difference between that mugger and the government is only an air of legitimacy. Literally, they're morally identical. So is it possible that every hierarchy that gets big enough and successful enough such that it can monopolize a bunch of services it provides, isn't it always going to be amoral in your sense, the way the United States government is amoral? Well, I don't want to say just like the United States government is immoral because that implies the United States government is uniquely or especially immoral. I just want to clarify that because I know you didn't mean that and I don't want that to be the implication. Can you repeat the question? I'm sorry. So like won't every... Okay. So that's progressive economics. So the argument is in any market at a certain point, things tend to centralize and then that organization de facto can dictate price, can dictate so on and so forth. That is completely historical. If you look at any market, the trend is always towards decentralization, the music industry. When we were kids, there were four or five record labels. They were the ones who made all the songs that you're going to see in the Billboard Top 100 with a few exceptions. Now anyone can go to direct to market. If you look at TV stations, it went from CBS, NBC, ABC, then you got Fox, then you had cable, which is 100. Now you have satellite, which have sounds around the world and you have YouTube, which is literally infinite. So as technology improves and as wealth increases, which is a function of free enterprise, you are going to always have more and more choice, even within a monopoly. Coca-Cola, right? This is an example I used, I think, and then you're right. When we were kids, every terrible comedian would be like, oh, now they've got diet caffeine-free Coke. What's next? It's like, yeah, that's good. You want to have... What was his name? Kamin, the guy who invented the Segway. If you go... Dean Kamin. If you go into some restaurants right now, you will have those machines where you have like 80 kinds of Cokes and then you could have whatever flavor you want to add to it, grape, cherry, lemon, lime, so on and so forth. So in any field, you're going to have more and more competition. You're going to have less competition and less choices when the state gets involved because the state wants control. The state wants one big neck with one leash around it and that way it could just pull that dog in one direction or another. And you saw this last year with the lockdowns. Carol Roth wrote this amazing book called The War on Small Business and she talked about we have seen for the first time in history a massive wealth transfer from small and medium business towards organizations like Target and Amazon who made trillions of dollars last year, whereas mom and pop, which to me at least is like the acme of American achievement. You come to America, you have a fruit stand, a laundromat, you make socks, whatever it is, you're that unique artisan creating something special. They're the ones who didn't last, whereas Target and Amazon did. So when you have the state involvement, it will always be in favor of Jeff Bezos. And for the simple reason that it's going to be a lot easier for Jeff Bezos to get Nancy Pelosi and Mitch McConnell on the phone than it is for me making socks on Etsy. But your sense is that there'll be less and less over time, Jeff Bezos says, like whatever the industry will look at, there's a trend towards decentralization across all industries. And when I say decentralization, I just mean choice, right? So if you look at, again, networks, if you were in the 80s and you had a network just for LGBT issues, first of all, it's going to be complete heretical, that's not going to happen. And there's not going to be enough necessarily people identifies that to have an audience. Then there was something called Logo, they have that, and there's lots of other shows like that in this way. So more specific, look at websites. I'm positive that you and I, if we wanted to look up breeding guinea pigs, would find thousands of websites about different breeds and all this other stuff. 20 years ago, 30 years ago, you're going to have two books. And they're not going to be dynamic as these new breeds are developed. So at the same time, it does following on your argument, it does seem easier to move and immigrate from state to state within the United States and to other countries. Do you think that's a form of freedom that embodies anarchism, where you can resist the force of state by choosing where you live? To some extent, but the line people, some of these boomers will go at me on Twitter, if I'm going up to the police or something and be like, if you don't like America, get out of here. And I tell them, freedom means I do what I want, not what you want. Freedom means I don't have to move, you don't have to move. Free speech is a good example. It doesn't mean I have to be on Twitter, right? Twitter has the right to ban me. But what I'm saying is I'm saying something and you don't like it, too bad. You're the one who has to accommodate me because I have a right to do what I want with my person as long as I'm being peaceful. So I guess I'm trying to get to the difference between the state and what you would naturally want in anarchy, which is like a security company, all of those things, they will, as they become successful, start looking more and more like the state because you get to elect, you give them money, they have leaders. What's the difference between a government and a very successful service provider in anarchism? This gets a little confused in America because big companies necessarily are hand in hand with the government, ended up in bed with them. The answer to this question is a long, complicated one, and thankfully it's all in the Anarchist Handbook. There was an essay by Murray Rothbard who Dave Smith, this is the essay that converted Dave Smith, so maybe it's not as good as it could have been otherwise, called Anatomy of the State. And Murray Rothbard points out that state is the only agency in a country which gets its goods through force. The state is the only agency that is not a producer but inherently a parasite because it does not get its money voluntarily but through taxation and by imposing its values on a country. That is what makes a state uniquely different from, let's suppose, an Amazon or a Barnes & Noble or a Target. Jeff Bezos does not have the authority or the moral legitimacy to get an army and go into somebody's house, whereas Andrew Cuomo or Ron DeSantis, Donald Trump and Barack Obama certainly do. But is it possible that to reframe, so Jeff Bezos does if he hires a security force, also is it possible to reframe taxation as a form of payment? If it was done much better, if you could pay this collective that we call government in ways where you could pay for things that you care for, your money would be much more directly contributing to the things you care for. If you care for a service like healthcare, you'd be able to buy essentially insurance from the government. Why am I buying insurance from the government as opposed to insurance from an insurance company? What do you perceive as the difference between a tax and a price? Do you see the difference? Yes, I know on the surface level, I'm trying to get deeply to say there's a lot of similarities. But what I'm saying is there's one essential difference, which is taxes are imposed on you and you have no choice. Here's an example, my book, Ego and Hubris, my biography, it goes for $500 on eBay. Someone paid for it, some crazy person. People are showing me that it's on Amazon for $3,000, something like that. You could put a million for it. You could charge whatever price you want. The question is, is someone paying that 3,000 for it? Is someone paying that million for it? It's actually the buyer who establishes the price because the seller can put any price tag he wants, $80 trillion. But unless someone's paying that amount and clearing the market, that price has literally no real meaning. It's not an indicator of value or worth or market price. Taxation, on the other hand, is by fiat. I can decide it's fair that you, Lex, have to pay 40% and Joe has to pay 45%. Joe and Lex are in no position to be like, this price is too high. Not only is that money set just completely out of their hands, for people who are employees, it's taken out of their paychecks before they even see it. They don't have the choice to be like, you know what? I agree that the government has the right to pay taxation. Here's my check for 40%. It's going on. It's a completely different paradigm than you are when you're paying for price. The government provides a lot of services in the current system. Right, but there's no service the government provides that would not be provided better, more efficiently, and with more choices in a market. Well, that's a hypothesis. Very likely. I can demonstrate this to you very easily. I love it when you get flustered. This is what people like. It's so cute. Don't make me put on the hat again. The robot has the smoke coming out of his ears. What is price? Okay, so- I will tax love. People like, I think of the government as a kind of subscription service. No, no, that's the anarchist view. The anarchist view of private security would be a subscription service. So that's exactly correct. But everyone hates when you sign up to a gym and then you realize in the contract, it's very difficult to cancel that membership. And then they up the price. I mean, there's a lot of unpleasant things with a subscription service that then you can elect to go to another subscription service. Or you could go on Yelp and complain. And if there's enough people to do that, the gym will be receptive. Look at the power of Yelp versus the power of the vote. Well, we could talk about that too. So you're saying Yelp is more effective than voting. Yes. The thing is, I agree with you, but you take a further step. You say that Yelp is ethical and moral and voting is amoral. Or like not voting, but government is amoral. So it's not only is one more efficient than the other, you're saying like, because I would say government sucks at doing what it does and has gotten a lot better at it. And I believe it can keep getting better as it gets smaller and leverages companies more and more. But you're saying, no, no, no, government is fundamentally as an idea gets in the way of companies that should be doing those things anyway. Correct. Correct. I just think that companies, when you take away government, will start looking like government. Just because something looks like something does not mean it's the same. If someone puts out a yarmulke to fill in and they go to shul, they're not Jewish. Right. The basic objection you have with government, because you can leave, I apologize that this is that stupid Twitter cliche statement. Okay, sure. But your opposition to this idea of leaving the United States is that it's a lot of effort. Too much friction. That's not the option. The opposition is, in the introduction to the book, I say anarchism can be summed up in one sentence, you do not speak for me, everything else is application. So the claim that somebody I've never met or who I voted against, let's say, I hate Donald Trump, I despise him, I want Hillary Clinton to be president, too bad, Trump's your president, that's not what I want. The idea that this person can come on me and make any claims onto one second of my time, as opposed to trying to persuade me, that is something that I, an anarchist, regard as inherently evil and nonsensical. But to operate large organizations, like you see this with cryptocurrency, there's governance, you have to make difficult decisions. There's a block size wars for Bitcoin. Sure. So you will, there is a voting mechanism often with membership when you're subscription service. But see, the thing is, you're using these words and you're switching definitions, because like, if I go to a store, I can technically say I'm voting for Tropicana orange juice as opposed to another one. But to kind of say, oh, well, you're making a choice, therefore every choice is a vote. I don't, I think that that's something that the Venn diagram is not. No, I literally mean vote in this case, not money. Okay. There's some decisions like, should Bitcoin have increases block size? Okay. There's a bunch of different, they're called soft forks or hard forks. Oh, I'm not saying you should never vote. Like stockholders have to vote. Right, exactly. But there's no pretense. Here's, let's look at this. If you want to build robots, right? You would sit down with the company. You would, you guys would be like, we should do this kind of robot. You should do this kind of robot. The stockholders would have a vote or the board in proportion to their investment in the firm. Me who knows nothing about robots, I am the idea that I'm in a position to walk in and be like, this is what you should do is crazy and bizarre and wrong. Cause I'm not in an informed position. So what democracy does is it forces people who run businesses well to run businesses poorly by people who don't know how to run businesses at all. That's the, that's one of the many concerns. But you're saying that's the fundamental property of the state. I have a sense that the state could become as effective as what we think of as companies. I mean, that as This is why they can't because the state does not have access to data the way that firms do. And this is one of Ludwig von Mises' great points, what he called the calculation problem. If I'm looking at comic books, right? And I have detective comics. If detective comics 26 is a thousand and detective comics 28 is a thousand and detective comics 27 is 50,000. That is telling me that even if I don't know anything about comics, that detective comics 27 is either very, very scarce for some reason, or very, very desirable. It's the first appearance of Batman, whatever, but you don't need to know that to just look at this data and be like, okay, this is the market. Tell me something. If prices are set by the government, which the government is a monopoly, I have no way of picking those winners or losers. I don't have that data of supply and demand of an entire nation or a world of people making individual decisions and having price be dynamic and informing me as the organization where I should allocate my resources. So the price is a really strong signal that allows you to operate a voluntary collective where people get what they want and don't get what they don't want. And it tells me what to produce, what not to produce. And it also is great because if I see this podcasting industry, which didn't exist five years ago, and now these people are making bank, that tells me as someone who's an investor, okay, they're making 50% profit, whatever, 10% profit on their capital. In the plant industry, it's 2%. If I'm going to further my capital to this 10%, 10%, and that's going to lower the profit rate as that builds up. And that is how markets are regulated voluntarily. But the word government, I just think it's possible to have collectives that of human beings that represent others based on their voluntary... Yes, of course. You have private governance. Right, private governance. Any company, you can have a CEO, you can have a board of directors. Yeah. But then it starts to look very similar to me, a successful private governance mechanism at a scale of the United States starts looking a whole lot like the current government of the United States. Even Amazon, I don't think is anything close to the federal budget. Size-wise or budget-wise or power-wise. No. So you're saying it's not even state, it's almost like anything at that size. You want to keep things smaller. And markets are not going to combine to that level of the state because Jeff Bezos will never be in a position to tell everyone in America, I'm going to take 40% of your money before you even see it. That to me is actually unclear. We don't know that to be true, that Google or Amazon can't grow to the size. If you take away the US government, I'm not so sure that Amazon can't grow to the size of the US government. Okay. So worst case scenario is we're back where we started, right? That's not worst case scenario. But the concern is that Google is going to be the federal government? That's not the concern. I'm saying this is what it looks like when Google is the federal government. To me, the US government is our best attempt so far to have large-scale representation of people's interest. It really sucks, but it's our best attempt so far. And the question is how to improve it. If you take away the US government, I'm trying to see how do we improve on that scale of representation of people's interest. Let me give you one example that people could wrap their heads around very easily. I'm against government police monopoly. I'm for private security, right? You don't have to be an anarchist to understand this. Can everyone agree, or at least as a hypothesis, everyone can wrap their heads around, here's a big concern, 911, right? I've heard this 911 call. It's very chilling. There's a kid in a closet. His family's being murdered outside, right? He has to call 911. He's whispering. It's horrifying to hear. There's no reason why the number I call for my family's being murdered is the same number I call for the fire department, is the same number I call for an ambulance. What if instead it operated like Uber? You had buttons on your phone. If there's a real emergency, like someone's gun flyers, someone's being killed, you press this and it sends instead of the one police district, whatever company is nearby, you have a bunch of them and they're the ones who are going to come to your house to save you. People can wrap their heads around that very easily. That is one very clear way to go from having a government security monopoly towards having a more free enterprise system. When you apply that to pretty much anything, it doesn't become that complicated of an alternative. You're going to criticize this, but I believe the government, it's like the parenting thing we've talked about earlier, I think it creates a safe space for- I'm for safe spaces. I'm not going to laugh at you about that. I want people to be safe. But for a safe space for entrepreneurship. I believe that good government, hold on a second, give me a second. I'm sorry. I'm sorry. You're right. You're right. I'm sorry. I think government gives opportunity for companies to out-compete it. Yes. UPS, FedEx, 100%. Not a question. I believe you need to have government to give a chance for UPS, FedEx, for SpaceX, what was an X in there, to pop up. And then government will naturally back off from that place. But you need the innovators to step in and build the thing. You can't just- When has government ever backed off though? That never happens. Well, from FedEx and UPS, from SpaceX, from Amazon- Wait, wait, wait. Hold on. The US Postal Service still competes with FedEx and UPS. So here's the other thing. Not nearly- Not well, but they still exist. And the point is- They're dying. But UPS and FedEx are taxed. So not only they're paying for their own company, they're paying for this competitor. This is the essential difference. Imagine if you didn't have UPS. Excuse me, the federal government, no post office. So you had FedEx, you have DHL, you have US Post Service and many others. How about in this scenario, UPS has the capacity to take 20% of FedEx's DHL and courier's money and put in their own pocket and they never have to do anything in return. This is going to be an enormous advantage of UPS. And then when you add the addition that UPS is not necessarily going to be more efficient than the others, this is going to be a huge distortion in the market. Can you imagine if your podcast, you just automatically got 20% of the views of everybody else? I mean, would there be any incentive for you to be great? Or you could just sit in your laurels and do whatever you want, even more than now. It's hard to imagine more than now. That's because you're a robot and lack imagination. I think there just has to be, of course you can do it completely without government, but government... That's all I need to hear. Okay, that's all I need to hear. Show's over. Show's over. What's he going to do without government? The question is that safety net that's needed for entrepreneurship, that's needed for... I'm sorry to say, but I have a sense that there needs to be a bit of a safety net for freedom. I'm much more comfortable with saying you need a safety net for freedom than you need one for entrepreneurs. The beauty of markets is with your startup, if you have a startup and it completely fails, the only person who's screwed is you and your investors. If I'm a government and I make a startup, the entire society fails, like the Iraq War. If I have this cockamamie plan, everyone else doesn't have a choice. They are both funding it and sometimes even drafted or forced into it. The safety net, let's get back to the early anarchists. One of the things that I admire about them, the anarcho-communists, the old school left anarchists, is people don't remember what context they were in. They were in context without a welfare state. They're immigrating in huge numbers from Eastern Europe. You go to the Tenement Museum in New York, people are like 12 to a room. Kids are working in factories. They're either working in factories or they have to starve. It's not that their parents didn't love them, it's that the parents didn't have birth control, which was a felony. They also were in a position to put food on the table for their kids because they're uneducated and the jobs are paying nothing. You could understand why Emma Goldman, Alexander Berkman, Proudhon, and all these other figures were like, this is untenable. We see Carnegie with 80,000 mansions, whereas this lady whose husband died at age 30, who's never been to high school or even junior high school, has 10 kids. How is she going to put food on the table? It's not going to happen. You could understand why they would be like, all right, we need to seize this money and distribute it around the people. That makes a lot of sense. In a contemporary context where food is much cheaper, where shelter to some extent is more available, when medical care... We're so oblivious to how bad things were that we see things are bad now, so we assume that they were better than in some context. They were much, much worse there in many contexts. If you're going to make an argument for government, for me, the strongest argument is food stamps or free lunches for children, because I agree that would be very inefficient. It's going to probably make them obese because you're going to have Nabisco lobbying to make sure that if you're going to have this protein, you're not going to give the kids an Oreo, aren't you? These kids are poor. You want them to have some pleasure. That's going to have deleterious effects. If the choice is an inefficient government program and mass starvation, that is one where as an anarchist, I could easily see making the argument for that one. Even though I think very clearly private charity would be more efficient and distributed more effectively. But at that point, I don't really care about efficiency. If you're throwing out food to make sure these kids get fed, I don't care. Would engagement in military conflict be one of the biggest negative things about the state to you? Yeah, of course. War is the state at its worst. If we take away war- Or make it defensive instead of aggressive. Wouldn't that be a huge step forward? This is what drives me crazy. We're taught as kids in school that war is a last resort, and I agree with that. Yet, when you look at the corporate press, war is always the first response. These people do not talk about what war means. They'll show examples during the Bush years of soldiers coming home in caskets, which already is an unacceptable price in many cases for me. But they don't even pretend to care about the people overseas whose countries we've ransacked and lives we've ruined. It's just like, well, what are you going to do? Not ransack those countries. So that war to me is the state at its worst. See, I think that there is value from small government that doesn't engage in wars. I do think that the kind of collectives that you imagine functioning well would look like the best version of government that I imagine. Okay, great. What a great endorsement. Well, I see them as the same. Okay, fine. I think a lot of it is just terminology. I have no problem saying that I'm using the word anarchism incorrectly and to go for what you want. I have no problem with that or anything really, because like I said, life is beautiful. But nevertheless, you wrote the essay, Why I'm Not Going to Vote This Time or Ever. Yeah, Why I Won't Vote This Year or Any Other Year. Or Any Year. And the basic idea- I hope you do a better job reading it than you just read that title. I guess you'll take as many takes as necessary. I'll read it in Russian and then pay somebody to translate it. This isn't even Russian at all. He's just making up words. Where'd you find this guy? You get what you pay for. Yeah, exactly. This is anarchy. This is what you wanted. Yeah, like your basic summary is, let me see. If pressed, the simplest explanation I have for refusing to vote is this. I don't vote for the same exact reasons that I don't take communion. No matter how admirable he is or how much I agree with him, the Pope isn't the steward over my soul, nor is any president the leader of my life. This does not make me ignorant or evil any more than not being a Christian makes me ignorant or evil. If I need representation, I will hire the most qualified person to do so. Yeah. Isn't voting our current best developed way of hiring the most qualified person to represent you on some things? No, because if I have a lawyer and the lawyer screws up, I can fire him. If I vote for someone, I don't get who I want. I get for who my neighbors want. I get for who my neighbors want. So that makes no sense. Representation means I want you to speak for me, whereas voting is like, I kind of want you, but I'll take what I can get. And I'm going to take what I could get regardless. So what's the point? What in governance, again, that's what Bitcoin is. You want to be represented in deciding what to do, but once- Wait, Bitcoin isn't picking a person. They're not picking a president of Bitcoin. They're picking an idea. Yeah, it's more like a referendum. And to me, a referendum is much more coherent and defensible than it is voting for representative. Because if I'm voting for Joe Biden, I'm saying this person speaks to me for abortion, taxation, environmental policy, immigration, war, right? The odds that unless you're a complete NPC, that this one person will speak for you for everything and will deliver what he promised and has the power to deliver what he promised is not true. Whereas if I have Brexit, if I say I want Britain to remain part of the European Union to say yes or no question, that makes a lot more sense to me. But even that is not pure democracy because going back to the idea of the circulation of the elites, which James Burnham talked about, Pareto and Moscow and all them, you are still going to have someone telling you what you can and can't vote for and how these questions are framed. So in contradiction to what the left anarchists said, some element of hierarchy is always going to be inevitable. So listen, I agree with this aspect very much so that we should be voting for ideas and issues, not voting for leaders to represent us across the full spectrum of issues. It seems to make no sense. Okay, good. Yeah, this is great. But I do think there should be a leader. I do believe in voting for representatives to debate, to be communicators of ideas to us. But here's, let me, sorry to interrupt you, but you could have those two things. For example, wouldn't this be an improvement if they have that now? You have a referendum, do you want tax rate to be 30 or 40, whatever percent? You have the guy leading the campaign for 50, fight for 50. Then you have the lady leading the campaign for 40, fight for 40. They'll go out there, they can have debates, they can talk about the issue, but you're still not voting for one of them. You're voting for the issue. That makes much more sense to me. Then I'm going to vote for him and hope that he puts forward 50 and that depends on 99 other senators. Exactly. And but also, I mean, I do like the idea of voting for certain people to debate certain ideas. Yes, I think that's a major improvement. But the final vote should be based on the idea. So, okay, so agree. That would be nice to have plus no wars. And then you'll stop tweeting so aggressively. And to decriminalize things that don't hurt people. Drugs. Victimless crimes, drugs, especially prostitution is a big one. And this is me talking, Mr. All Cops Are Criminals. There is no one or maybe other than like abused children who needs access to the police other than sex workers. They're the ones who are the most likely to really put themselves in a dangerous situation. So they need to be able to call security because that's why they have pimps. Because you're a woman dealing with some strange dudes who are a lot of the time going to have weird kinks. You want to be able to be sure, even if you don't approve of prostitution, think it's horrible that she's not going to be raped and murdered and have no consequences. And if you're going to say, oh, well, she's a prostitute. She can't be raped. I just think for a second, if you're agreeing to sleep with somebody and then he starts choking you and being the crap out of you and saying it's now it's a dumb situation that is clearly beyond the pale of salt. And the same thing with drugs, heroin, cocaine, crack. The people that need help the most are the ones who are addicted to those drugs. But even the ones who need punishment. Let's suppose you think drug dealers should be in jail, right? It is very hard for me to say that someone who sells cocaine should be treated or in the same building as someone who rapes children or is a murderer. These are not similar types of evil, even if you believe that that drug dealer is an evil person. Yeah. I mean, there's an essay in there called by Alexander Berkman, who is Emma Goldman's partner on prisons and crime. And this is leftism at its best, forgetting the person is forgotten. And the fact that we have the world's largest prison population, the fact that so many people are just like, oh, you commit a crime, just put them in jail, throw away the key. At the very least, if you want to be totally immoral about it, it's expensive. And second of all, the concept that all criminals should be locked in a room together in these kind of largely inhuman conditions, and that's going to help people. I don't think that that's the ideal mechanism. Yeah, I tend to believe I usually don't speak so negatively about politicians, but I do think that politicians have done more evil in the war on drugs than did the people that are supposed to be the criminals in this picture. I'll give you another example of how this is the anarchist critique of power. Hunter Biden, and I'm not going to, I'm not making fun of him, not taking shots at him, he had an article in the New Yorker where he talks about when he was in LA, he was buying crack and there was a misunderstanding or like he left the crack pipe in the Hertz car and then blah, blah, blah, this issue. He's admitting to a felony in writing to a reporter, and I'm sure this was within the statute of limitations. There was no possibility he was going to have consequences. Kamala Harris, who was a cop, talked about when she was in college, she was smoking weed. And it's like, I don't begrudge you guys smoking your crack or smoking your weed, but for other people who are poor or maybe just had the short end of the stick, this is years of their life being destroyed. At the very least, even arrest is a traumatic situation. If you have a weed or cocaine or crack, you're arrested, that's really going to screw up. It's going to do a number on you being locked up. So to have that double standard to me is completely unacceptable. And that has nothing to do with a Republican or Democrat that George W. Bush was a coke head back in the day. He talks about overcoming his addiction, and I'm glad that he did. More power to him. But just to have this kind of, you know, it's just really kind of disturbing to me. And this is my anarchist brain, like how prevalent drug use is in college. There's that I think it was a joke on South Park, like there's a time and a place to try drugs and that's called college where people experiment. But all those college kids, which are going to become next generation's elite, don't really have that worry that if they get caught, then anything's going to happen to them. But that kid in the street who did not have that good upbringing, even if he's a piece of crap, like he's not going to have a different punishment. I think that's just really at his base on American. So in contrast to Tolstoy, let me ask you about Emma Goldman. You wrote that if anarchism believed in rulers, then Emma Goldman would be the undisputed queen. Yes. What ideas define her flavor of anarchism, would you say? Emma was really an old school radical. She was a radical among radicals. I don't know what ideas, I mean, what would ideas define her was anarchism, obviously. There's the violence. I mean, she was more open to the idea of violent opposition versus somebody like Tolstoy. Oh, sure. For sure. So basically Emma and Alexander Berkman, their mentor was someone named Johann Most. And Johann Most was a very early free speech, not very early, but he was a free speech concern because he published a pamphlet in Europe that was translated in the States about how to build dynamite. Because his idea was, all right, you have this oppressive government, this oppressive police force that use batons and bolts against us. The only way for us as the working class to level the playing field is through dynamite, and here's how you build it. So the question is, all right, is this something that could be allowed to be legal now that you're allowing the layman to, in his own house, build bombs? So Johann Most, basically they had a big parting of ways because when Alexander Berkman tried to assassinate Frick, Johann said, no, no, no, this is not something I'm for. And in fact, they thought with this assassination, this failed assassination, this would be the thing that fired off the revolution because you had the strike, the Pinkertons undervile, Pinkerton's getting killed, strikers are getting killed. This is what Marx predicted. They're going to light the spark and everything's going to come falling down. He ends up going to jail for 13 years instead, Alexander Berkman does. And then Goldman and Berkman had a big issue because when Leon Salgaz killed McKinley in 1901, it's kind of humorous in retrospect. He gets arrested and they're like, why'd you kill the president? He goes, I was radicalized by Emma Goldman. And she's like, oh, damn it. She's on the run. She's like, I don't even know this guy. Yeah. And she made the point about like, why is it worse than the president being killed and somebody else? We're all equal. And you would think if you're against capitalism, against the ruling class, this would be your first target. But Berkman, who went to jail, who tried to assassinate someone, he had said, McKinley, this is your villain. He's just a party hack. He's like a symptom of the times. This is foolish. And Goldman disagreed with him. She said it wasn't necessarily justified, but it may have done something that was defensible. So the three of them had their differences on the use of violence. And in fact, when she came back from Russia and was denouncing it in her book, My Disillusionment in Russia, My Third Disillusionment in Russia, the last chapter, she goes, look, I'm not saying I'm against violence. When there's the revolution comes, we're going to have to use force. She goes, but it's not the force of the state against the working class, against the masses. This is exactly what we're opposed to. This is a complete obscenity to our principles. So that was interesting. The fact that she was her periodical Mother Earth was a clearinghouse for many prominent ideas of the day that weren't anarchist, but were certainly radical. So she was a bit and also she was like tiny. She's like 5'1". So to have this little woman who was so feisty and talk back to Lenin, talk back to Lenin, what she took on Lenin, Woodrow Wilson, J. Edgar Hoover was the one who deported her. Someone who just and the thing is, you have to be careful because I think just like war, it's very easy to glamorize violence and to regard it as something admirable or heroic, like you're fighting for the cause. But if you take it out of the romanticism, you're like you're killing someone who had kids. You are killing someone with the family. You're making your if you're going to shoot someone, they're probably going to retaliate twice as hard. The violence sings its own song, and this is a very dangerous road you're going down. So you really need to be careful about what you're preaching here. And she kind of had this mixed feelings about it. But that is certainly not Emma Goldman and her best. Emma Goldman and her best was about the ultimate freedom of the individual, of caring about people who are desperately poor, who despised the corporate idea that we all had to be made cookie cutters and be interchangeable and all have to start work at the same time. And basically our entire lives slave for corporation that have nothing to show for it while they get wealthy and you have no opportunity for either productive work or creative work. So that I think the valorization of kind of the lowest of the low is something I find very admirable. There's a quote of hers, which I think even for those of us who are for property rights is anarchist left anarchism at its best, but she goes, go and ask for work. If they don't give you work, ask for bread. If they don't give you bread, take bread. So the idea that like if you're that poor and you're honestly trying to work and work isn't available and you steal food to keep alive, that you shouldn't feel guilt about it. I don't know that I would disagree with that. I think that there's something to be said at that point where it's just like, you know, if property rights come between that and mass starvation, it's going to be very hard for anyone to make the case for property rights. Now, my argument is when you have free enterprise, food becomes so plentiful that now obesity is an issue. But at the time she did not have, of course, have that data to access. Is there somebody you left out from the book that you thought about leaving in like some interesting figures? Yeah, there's a couple. So Chomsky would have been one, of course, because he's probably the biggest anarchist, one of the biggest anarchist thinkers in contemporary times. I was on the fence about Herbert Spencer because he's not an anarchist. Chris Williamson's reading the chapter for the book. He coined the term Survival of the Fittest and the chapter is called The Right to Ignore the State from his book, Social Statics. It was deleted from later editions, but people found it and reprinted it. And Randolph Bourne, he was an early progressive. He was the only one or one of the very few fighting against entering the Great War. And he had an essay called War is the Health of the State, which is basically about how states love war because it gives them an excuse to increase their power. And it's very hard to argue against increasing state power in a time of war. But since he was not himself an anarchist and there was plenty anti-war in there already, I didn't include him, but those would be the ones. Is there some people that you think the public would be surprised to learn that they are at least in part anarchist? Like I saw that Howard Zinn is supposed to be an anarchist. I mean, is there like just like Tolstoy is an anarchist. Is there some people like that that you think in our modern life that would be surprised to learn they're anarchist? I can't think of any off the top of my head. I mean, you could say Carl Hess, who was like Barry Goldwater's speechwriter from the 1964 campaign, but he's hardly a household name. I mean, I think a lot of people would not ascribe to that term, but are certainly informed with this complete distrust of all authority. Murray Rothbard had an essay, if I didn't include anatomy of the state, I was going to include this one. It's much, much shorter. And his question was, who are our allies and who are our enemies? And the point he made is there's lots of people who would call themselves anarchists who are of little use, whereas someone who is still like a minarchist or for government, but genuinely hates the question Rothbard had is if there's a button and you could press it, you would end the state. Would you press it so fast your finger would get a blister? Those are allies, even if they're somewhat of a minarchist. So I think that is kind of a better lens of looking at it. And I don't think anyone needs to really ascribe to anarchism as a whole ideology in so far as you're seeing right now, many people in certain fringe elements are just essentially or are decreasingly fringe and increasing mainstream elements are realizing that this idea that whatever the state does is somehow morally binding or legitimate is something that at least bears strong questioning. Sure. And I mean, I guess there's a lot of groups like the libertarians, for example, have some element of that. Oh, sure. For sure. Of harsh questioning of the ways of government. And also, I think what I love, I mean, if there's one issue where I would want people to have this kind of analysis, it is war. And it is like, OK, are you really sure? Because this is 100% going to result in a lot of people being killed, a lot of people being traumatized, a lot of people who are never going to recover, children, innocent people. Are you really sure this is the right thing to do? And I think a lot of times the answer is, well, it's the profitable thing to do. And that is, I think, again, government at its absolute most venal and worst. You, Michael Malice, in many ways are a New Yorker. Oh, yes. I'll give you one example. I don't know where Austin is on the map. No idea. Not even kidding. But does it even matter? It doesn't matter. But nevertheless, you've decided to move to Austin. Yes. Why do you think you're moving to Austin? Or why do you moving both to Austin and away from New York? This was one of the—I hate it when people talk like this, but I'm going to do it anyway. This was one of the hardest and easiest decisions of my life. It was hard because I've lived in New York since I was two. Other than college, it's the only home I've known. I know it intimately. I know all the cool spots. I love it with every fiber of my being, or I did. It was very much ingrained in my personality, my outlook about what cities can be and can't be and should be and shouldn't be. Deciding to move was not done. But when you see your crew, your chosen family, one by one whittling away, it's not easy. They all left. There's just a couple of us left in New York. And I don't see any mechanism by which New York is going to improve. Things are getting much worse all the time. It's just completely outrageous. Here, I would have a huge crew. I didn't realize how much cheaper real estate is than in New York. This is another way when you... So New Yorkers are the most provincial people on earth who are completely oblivious to the rest of the country. So for a long time, the argument was New York versus LA, right, for certain types of people. And they would say LA is cheaper in terms of rent. So New York, let's suppose the rent is 1,000, LA was 700, but you'd have to get a car. I'm like, this is kind of a wash. So I assumed Austin would be like 80% of New York prices. And I'm looking at these houses, and for like 700,000, you could get a house here that would cost like 3.5 million in New York. Yeah. So, and you could have a gun, and it's just like, I could have a yard, and I could have a dog, and I could have a three bedroom, and I could have aquariums and my weird plants. So to have all that, and it's just to have... I am very, very lucky that I have such a supportive crew. And they're also very smart, because they sat me down and they said, whatever excuse you have not to move here, we are going to make sure that doesn't count. Make sure that doesn't count, so my buddy Matt said, because I have a huge library, he goes, I will go to your house, and I will pack every single book you own myself, so you can get that as an excuse the other way. I don't know how to drive, and you do this, she's like, we're going to take driving lessons together. There goes that excuse. How do I find an apartment? They're like, we'll go with the realtor, and we'll take pictures for you, we'll report back, you could trust our judgment. And I'm like, that's very... I would do that. That sounds like fun, shopping for houses, I'd have to buy them. Then Matt, just yesterday, had the idea, goes, come here, rent a furnished apartment for a few months, you don't have the pressure of buying, and it's just, it's going to be an easy transition. The rent's not going to be anything compared to New York. I'm like, these are all very valid things. You're here, lots of other people. By the way, that's what this is. I made sure that's renting month to month. Oh, this is rental. This is rental. You didn't realize this. I thought you bought this. No, no, no. This is rental. We're going to talk. Why? I thought you bought it. No, it's rental. Well, I really value freedom. Who are you talking to? Have you heard of this thing, freedom? It's really great. But not everybody, the implementation of freedom is different for everybody. Of course. For me, I don't want to make a statement about others, I'll just speak for myself. I think when you buy a house, that is not just a wise financial decision or all those kinds of reasons that people have, investment, all those kinds of things. I think it's also a hit on your freedom because the positive way to frame that is you make it a home. Yes. Have a deep connection to it. But the negative way to frame it is you're now a little bit stuck there. Yeah. And you may stay there way longer than you should when much better opportunities for life come up. There's stages in life when you're not sure exactly what the future will hold. I would argue that's very often the case, basically at every stage in life. And I just want to make sure I maximize the freedom to embrace the most ambitious, the craziest, the wildest, the most beautiful opportunities that come by. You've actually brought this up because I said I really enjoyed the conversation with you and Yaron. Yeah. Like you talking to you and somebody else, I think you make a really significant effort. You've said this before, but it really is true and it stands in contrast to other folks who are also good conversations. You really make an effort for that person, like to meet the person. Oh, for sure. And you made me realize it's an art form, but it's also just a thing worth doing of putting in that effort and that leap of humanity to reach the people, whether you're talking to Dave Rubin or Alex Jones or Joe or me, just those are different human beings. Of course. And they've taken that leap. It's fascinating. I mean, how do you think about that? I'm a huge introvert as you are, I think. I feel very, very, very lucky that I get to get on a mic and run my mouth. And for some reason, people like this. So I know what it's like to have a good convo and I know what it's like to have a bad convo. So before I'll do a show, I will have some things I would want to talk about. And then I'll think about how to say them in an engaging way. So I do my homework in that regard. I'm also very good at, or I pride myself at, taking people who are cerebral or intellectual and making them a little bit silly, but also making them feel safe to be silly because I'm not going to be making a buffoon of them, that we're having fun as opposed to disrespecting the person. I think we all saw that with Yaron, who's very cerebral, very serious, but we were all cracking jokes and he was having a good time. And he knew even if I'm making fun of him to his face, it is coming from a place of kindness and he's in on the joke and we're all having fun. That is something I try to do as much as possible. I had an episode of my show a couple of weeks ago and someone who's been a friend of mine for a long time and someone I admire a lot, Elizabeth Spires, she was the founding member of Gawker, founding editor of Gawker. She's worked for the Observer for Jared Kushner. She's her resume second to none. And she was on my show and she was talking, her politics are pretty straightforward, like corporate journalist, blue pilled politics. And my audience was very upset that I wasn't pushing back or whatever. I'm like, my job, if someone is coming to a place where the audience is at least going to be somewhat hostile, is not to make her have negative consequences for doing something that she didn't need to do. My job is to make sure that the experience is a positive one for her as the host. So when I'm the guest, I always feel that my job is to make the host look good and make the host not feel like it's work. And the audience really likes that because instead of it being an interview or intense, it is a conversation. None of us know what's going to happen. So this is something I think about a fair amount and I try to apply and insofar as it succeeds successfully, I'm delighted and there's times when it's not successful and that's a shame, but all we could do is do our best. Yeah, I really enjoyed that conversation with her. I was surprised by the dislikes and all that kind of stuff. Well, one of the things I always talk about is I don't care what my friend's politics are. I care about if someone's, if I'm having a bad day, can I call them up and ask for advice? And Elizabeth has been there for me in the past. And then when I do it on a camera in front of mics, people freaking out, I'm like, I'm practicing what I preach. My, the relationships are more important than someone's political views and it's not hypocrisy at all to demonstrate that and not to push back. And there was great humor there. You're both a bit of trolls in very different ways, but nevertheless, that connection, the humor and the mutual respect and love that was all there. Of course, I adore her. Yeah, she was fascinating. You've talked to Alex Jones a couple of days ago. Sure, yeah. You've talked to him many times before, but you've had him on your podcast. This week, yeah. This week. I was kind of surprised that he mentioned that human animal hybrids was like the number, the main conspiracy that people should look into to open their eyes to the, you know, to the globalists, to all the conspiracies that are out there. Was that surprising to you? Um, no, because I came in there with questions and I was very focused on corralling him and having it be like kind of a coherent intellectual conversation. That was a really, really good. It was only an hour, but it was a very good conversation. Yeah, thank you. The response was overwhelmingly positive and I'm like, all right, I'm in a unique position because Alex, I met Alex, well, that's not true, but I was on Alex, with Alex on Tim Pool a couple of times. It was mayhem. It was anarchy. And I'm like, all right, let me get, but the thing is what people enjoyed is I was the one who was basically able to translate Alex's. He's obviously very performative. And a lot of times Alex will say things that are not really particularly controversial, but he'll say them in such a way that it sounds crazier than it is. You know, I think Joe's made this observation as well. So what I wanted to have him on, on my show is, all right, let's go through all these conspiracies, which have validity, which don't. And I knew if I asked him, because he's got a lot of historical knowledge, even if you think of a lot of it's nonsensical, let's sort out the wheat from the chaff, you know, because everyone has someone crazy in them. I have this expression, you take one red pill, not the whole bottle. You take the whole bottle of red pills, you assume literally everything in the media is a lie. That's just not a coherent position to have. Is the weather a lie when they tell you that the temperature is going to be wrong tomorrow? So that was fun to watch him go through that. And he felt bad because he felt incorrectly, in my opinion, that he was needlessly aggressive and disrespectful toward me on Tim. I didn't feel disrespected at all. It got heated, but I didn't take it personally. People have heated debates all the time. So I think he promised me he wouldn't interrupt and we'd be deferential, but that because he promised to be on his best behavior, that gave me an opportunity to address him seriously and not to bring the clown aspect out of him, which is easy to caricature him. My friend, Ethan Supley, who I'm sure people know, played a character based on him in The Hunt because Alex is this cartoon archetype. So it was really fun to get another side of him. And also it's just fun being on his show, just him being bombastic and just trying to be the calm voice of reason. And for once, the trickster was Apollo. Well, I like this thing he said before, and that's what makes me the most interested in Alex is the Nietzsche quote about the gazing into the abyss. I think he said on your show that he has become the abyss or something like that. I think that makes him fascinating that when you really take conspiracy theories seriously, the kind of effect it has on your mind, that to me is fascinating. Well, can I say one thing? The term conspiracy theory. If you ask any layman, it's like this. You say, do you like puppies? I hate them. Do you like baby dogs? Oh, they're the best, right? People, the human mind is capable of doing this. So if you ask people, do you think extremely powerful people often get together and manipulate data or rules in order to further their power and control and maintain it? I think 90 plus percent of people would be like, of course. Then you say, oh, so you believe in conspiracy theories? Oh, no, that's for crazy people. Those concepts are identical. Now, that term is used for people who are like, all right, there's conspiracies in government to experiment on people like Tuskegee. This is not in dispute. The CIA has unsealed things, Operation Mockingbird, so on and so forth. And at the same time, conspiracy theory applies to people who say 9-11 never happened and those are holograms. Now, it's the same word for both, but these are not at all equal truth claims and they do not at all have equal evidence to them. But it's very useful for powerful people to have that term in the zeitgeist because then I don't have to explain or defend. It's like only lunatics are going to look further on this. Do you really want to be a lunatic kid? And that takes care of the issue. Unfortunately, the same problem applies when language applies to a lot of other areas. 100 percent. That's the nature of language. Yeah. It's used not just to communicate, but to obfuscate. Obviously, that could be fixed by coming up with different words to label conspiracy theories that are much more likely to be true. Yeah, like power elite analysis is another, is basically a conspiracy theory. Well, this is the black pill versus white pill question with the abyss. Do you think thinking about these things can destroy the mind, can make you deeply cynical about the world? Yeah, because if you are thinking that you are not aware of or no one is aware of who's controlling things and that the level of their control, it gives you the sense of powerlessness and hopelessness. And my counter is the people in charge, one of the reasons I'm an anarchist, are nowhere near as smart and crafty as you think they are. And certainly maybe the ones completely in the shadow maybe are, but the ones who are in the public face most certainly are not, as social media has demonstrated. When you look at how senators and Harvard professors tweet, these are not intellects that you're in awe of, to put it mildly. So I think that kind of takes the bloom off the rose to a great extent. You mentioned that you've been doing a lot of amazing things, been truly joyful recently. Yeah. What, I don't know if you have a bucket list. Is there items on the bucket list you haven't done yet? Or are you pretty much satisfied and happy? And if you die today, if I murder you, you'll be happy? I could die today. Is there an item on the bucket list you want to get done? I don't, yeah. Deep sea submersible. That would be number one in a bucket list. Why? Because that's where all the most interesting zoology is. And to be in a place where virtually no human being has been and to see these God's mistakes in their natural environment. My friend coined that term, God's mistakes. If you look at deep sea creatures, you can imagine God making some animal being like, oh God, this is hideous. I'll just throw the bomb the other way. I was going to see this, so that would be my number one bucket list thing. I would say go to the White House as a guest would be a bucket list thing. Russia, go to Russia would be a bucket list thing. I want to go, these are secondary, like go to Eritrea would be a bucket list thing. I've got a long list of books I need to write. I don't know if that's really a bucket list per se. There's not a lot of things I want to do. There's not that much. What I'm at a point in my life is once you cross off certain things, you basically instead of driving the car, start surfing. And just amazing thing. I talked to you about this medical thing before we started. At a certain point, and I'm sure this happens to you because your platform is a lot bigger than mine, all sorts of things start coming your way that you never would have thought of. And you're like, this is pretty darn cool. And that's happening at an escalating rate. I'm at a point now where I get stopped every day by people. So that's going to be a weird thing for me to get adjusted to. Without exception, everyone who has ever stopped me on the street has been cool. And it's been a pleasant experience. There was one exception in an event where someone was genuinely on the spectrum and they didn't understand distance and you don't touch people. That's as bad as it got. So that is something that's going to be weird for me to have to deal with. Over the next couple of years, but it's the price you pay. And it's hardly a small price when people come up to you and say, you've made my life better. But it's just weird when you go in like, I was at the gym. And then someone tweets like, did I see you at the gym just now? It's kind of weird. And I'm sure it's the same for you when you're walking around and you don't think about it. But people know who you are. And you don't know who they are that you're being watched. Even though it's not malevolent, it's still just you don't get prepared for that. Michael, there will be two really big names that wanted to do this podcast, will do this podcast that I considered to do episode 200 with. But then I realized why the hell talk to somebody famous when I could talk to somebody I love that nobody knows or cares for. You just hit a random number generator. Yeah, just I listed all the Russians I know. And who is the easiest to get? Yeah, who's the most desperate for that stuff? He's got a shitty book out. We could talk about that for five minutes. This garbage cut and paste that he did. Yeah. Yeah. And it turned out okay, I think. Slightly above average. Michael, I love you. You're an incredible human being. It's an honor that you would talk to me and you'll be my friend. Thanks so much for doing this. The respect that I got when you asked me to do this podcast. You asked me to be the guest for the anniversary episode was similar to the respect when my two friends, Josh and Zoe, they were going to get married at City Hall. And they said, we want someone to witness it. They ask you. So it's one thing when people tell you they like you and respect you, which I had growing up. It's nothing when they show it. And this is something that I do not take lightly. And I hope no one takes lightly. And if someone does right by you and shows you respect, going back to kind of taking out for dinner, thank them. Buy them a candy bar. Buy them a soda. Do something to show that you don't take it for granted. Because I think what you and I both want to do is increase human kindness as much as possible. And I'm going to look at the camera. Be kind to yourself because a lot of you deserve it. Dasvidaniya. Thanks for listening to this conversation with Michael Malice. And thank you to Gala Games, Indeed, BetterHelp, and Masterclass. Check them out in the description to support this podcast. And now let me leave you with some words from Jack Kerouac that perhaps begins to explain the nature of and the reasons for my friendship with Mr. Michael Malice. The only people for me are the mad ones. The ones who are mad to live, mad to talk, mad to be saved, desirous of everything at the same time. The ones who never yawn or say a commonplace thing, but burn, burn like fabulous yellow Roman candles exploding like spiders across the stars. And in the middle, you see the blue center light pop and everybody goes, ah. Thank you for listening and hope to see you next time.

https://youtu.be/R5rNoV1Qy_Q

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Gustav Soderstrom: Spotify | Lex Fridman Podcast #29

The following is a conversation with Gustav Sordestrom. He's the Chief Research and Development Officer at Spotify, leading their product design, data technology, and engineering teams. As I've said before, in my research and in life in general, I love music, listening to it and creating it, and using technology, especially personalization through machine learning, to enrich the music discovery and listening experience. That is what Spotify has been doing for years, continually innovating, defining how we experience music as a society in a digital age. That's what Gustav and I talk about among many other topics, including our shared appreciation of the movie True Romance, in my view, one of the great movies of all time. This is the Artificial Intelligence Podcast. If you enjoy it, subscribe on YouTube, give it five stars on iTunes, support on Patreon, or simply connect with me on Twitter at Lex Friedman, spelled F-R-I-D-M-A-N. And now, here's my conversation with Gustav Sordestrom. Spotify has over 50 million songs in its catalog, so let me ask the all-important question. I feel like you're the right person to ask. What is the definitive greatest song of all time? It varies for me, personally. So you can't speak definitively for everyone? I wouldn't believe very much in machine learning if I did, right? Because everyone had the same taste. So for you, what is... you have to pick, what is the song? It's pretty easy for me. There is this song called You're So Cool, Hans Zimmer, soundtrack to True Romance. It was a movie that made a big impression on me and it's kind of been following me through my life. Actually, I had it play at my wedding. I sat with the organist and helped him play it on an organ, which was a pretty interesting experience. That is probably my, I would say, top three movie of all time. Yeah, it's just an incredible movie. Yeah, and it came out during my formative years. And as I've discovered in music, you shape your music taste during those years. So it definitely affected me quite a bit. Did it affect you in any other kind of way? Well, the movie itself affected me back then. It was a big part of culture. I didn't really adopt any characters from the movie, but it was a great story of love, fantastic actors. And, you know, really, I didn't even know who Hans Zimmer was at the time, but fantastic music. And so that song has followed me and the movie actually has followed me throughout my life. That was Quentin Tarantino, actually, I think, director of Produce Theater. So it's not Stairway to Heaven or Bohemian Rhapsody. Those are great. They're not my personal favorites, but I've realized that people have different tastes and that's a big part of what we do. Well, for me, I will have to stick with Stairway to Heaven. So 35,000 years ago, I looked this up on Wikipedia, flute-like instruments started being used in caves as part of hunting rituals, in primitive cultural gatherings, things like that. This is the birth of music. Since then, we had a few folks, Beethoven, Elvis, Beatles, Justin Bieber, of course, Drake. So in your view, let's start like high-level philosophical. What is the purpose of music on this planet of ours? I think music has many different purposes. I think there's certainly a big purpose, which is the same as much of entertainment, which is escapism and to be able to live in some sort of other mental state for a while. But I also think you have the opposite of escaping, which is to help you focus on something you are actually doing. So I think people use music as a tool to tune the brain to the activities that they are actually doing. And it's kind of like, in one sense, maybe it's the rawest signal. If you think about the brain as neural networks, it's maybe the most efficient hack we can do to actually actively tune it into some state that you want to be. You can do it in other ways. You can tell stories to put people in a certain mood. But music is probably very effective to get you to a certain mood very fast. You know, there's a social component historically to music, where people listen to music together. I was just thinking about this, that to me, and you mentioned machine learning, but to me personally, music is a really private thing. I'm speaking for myself. I listen to music. Almost nobody knows the kind of things I have in my library, except people who are really close to me. And they really only know a certain percentage. There's like some weird stuff that I'm almost probably embarrassed by. It's called the guilty pleasures. Everyone has the guilty pleasures. Hopefully they're not too bad. But for me, it's personal. Do you think of music as something that's social or as something that's personal? Or does it vary? So I think it's the same answer, that you use it for both. We've thought a lot about this during these 10 years at Spotify, obviously. In one sense, as you said, music is incredibly social. You go to concerts and so forth. On the other hand, it is your escape and everyone has these things that are very personal to them. So what we've found is that when it comes to... Most people claim that they have a friend or two that they are heavily inspired by and that they listen to. So I actually think music is very social, but in a smaller group setting, it's an intimate form of... It's an intimate relationship. It's not something that you necessarily share broadly. Now, at concerts, you can argue you do, but then you've gathered a lot of people that you have something in common with. I think this broadcast sharing of music is something we tried on social networks and so forth. It turns out that people aren't super interested in what their friends listen to. They're interested in understanding if they have something in common, perhaps, with a friend, but not just as information. Right. That's really interesting. I was just thinking of it this morning, listening to Spotify. I really have a pretty intimate relationship with Spotify, with my playlists. I've had them for many years now and they've grown with me together. There's an intimate relationship you have with a library of music that you've developed, and we'll talk about different ways we can play with that. Can you do the impossible task and try to give a history of music listening from your perspective, from before the internet and after the internet, and just everything leading up to streaming with Spotify? I'll try. It could be a 100-year podcast. I'll try to do a brief version. There are some things that I think are very interesting during the history of music, which is that before recorded music, to be able to enjoy music, you actually had to be where the music was produced, because you couldn't record it and time shift it. Creation and consumption had to happen at the same time, basically concerts. You either had to get to the nearest village to listen to music, and while that was cumbersome and it severely limited the distribution of music, it also had some different qualities, which was that the creator could always interact with the audience. It was always live. Also, there was no time cap on the music. I think it's not a coincidence that these early classical works are much longer than the Three Minutes. The Three Minutes came in as a restriction of the first wax disc that could only contain a three-minute song on one side. Actually, the recorded music severely limited the or put constraints. I won't say limit. I mean, constraints are often good, but it put very hard constraints on the music format. So you kind of said, instead of doing this opus of many tens of minutes or something, now you get three and a half minutes, because then you're out of wax on this disc. But in return, you get an amazing distribution. Your reach will widen. Just on that point real quick, without the mass scale distribution, there's a scarcity component where you kind of look forward to it. We had that, it's like the Netflix versus HBO Game of Thrones. You wait for the event because you can't really listen to it. So you look forward to it and then you derive perhaps more pleasure because it's more rare for you to listen to a particular piece. You think there's value to that scarcity? Yeah, I think that that is definitely a thing. And there's always this component of if you have something in infinite amounts, will you value it as much? Probably not. Humanity is always seeking some, is relative. So you're always seeking something you didn't have and when you have it, you don't appreciate it as much. So I think that's probably true. But I think that's why concerts exist. So you can actually have both. But I think net, if you couldn't listen to music in your car driving, that'd be worse. That cost would be bigger than the benefit of the anticipation, I think, that you would have. So, yeah, it started with live concerts. Then it's being able to, you know, the phonograph invented, right? You start to be able to record music. Exactly. So then you got this massive distribution that made it possible to create two things, I think. First of all, cultural phenomenons. They probably need distribution to be able to happen. But it also opened access to, you know, for a new kind of artist. So you started to have these phenomenons like Beatles and Elvis and so forth. That were really a function of distribution, I think. Obviously of talent and innovation, but there was also a technical component. And of course, the next big innovation to come along was radio, broadcast radio. And I think radio is interesting because it started not as a music medium. It started as an information medium for news. And then radio needed to find something to fill the time with so that they could honestly play more ads and make more money. And music was free. So then you had this massive distribution where you could program to people. I think those things, that ecosystem, is what created the ability for hits. But it was also a very broadcast medium. So you would tend to get these massive, massive hits, but maybe not such a long tail. In terms of choice, of everybody listening to the same stuff. Yeah. And as you said, I think there are some social benefits to that. I think, for example, there's a high statistical chance that if I talk about the latest episode of Game of Thrones, we have something to talk about. Just statistically, in the age of individual choice, maybe some of that goes away. So I do see the value of shared cultural components, but I also obviously love personalization. And so let's catch this up to the internet. So maybe Napster. Well, first of all, there's like MP3s, exactly, tapes, CDs. There was a digitalization of music with a CD, really. It was physical distribution, but the music became digital. And so they were files, but basically boxed software, to use a software analogy. And then you could start downloading these files. And I think there are two interesting things that happened. Back to music used to be longer before it was constrained by the distribution medium. I don't think that was a coincidence. And then really the only music genre to have developed mostly after music was a file again on the internet is EDM. And EDM is often much longer than the traditional music. I think it's interesting to think about the fact that music is no longer constrained in minutes per song or something. It's a legacy of an old distribution technology. And you see some of this new music that breaks the format. Not so much as I would have expected actually by now, but it still happens. So first of all, I don't really know what EDM is. Electronic dance music. You could say Avicii was one of the biggest in this genre. So the main constraint is of time. Something like three, four, five minute song. So you could have songs that were eight minutes, ten minutes and so forth. Because it started as a digital product that you downloaded. So you didn't have this constraint anymore. So I think it's something really interesting that I don't think has fully happened yet. We're kind of jumping ahead a little bit to where we are, but I think there's there's tons of format innovation in music that should happen now. That couldn't happen when you needed to really adhere to the distribution constraints. If you didn't adhere to that, you would get no distribution. So Björk, for example, the Icelandic artist, she made a full iPad app as an album. That's very expensive. Even though the app has great distribution, she gets nowhere near the distribution versus staying within the three minute format. So I think now that music is fully digital inside these streaming services, there is there is the opportunity to change the format again and allow creators to be much more creative without limiting their distribution ability. That's interesting that you're right. It's surprising that we don't see that taken advantage more often. It's almost like the constraints of the distribution from the 50s and 60s have molded the culture to where we want the three to five minute song than anything else. So we want the song as consumers and as artists. Because I write a lot of music and I never even thought about writing something longer than 10 minutes. It's really interesting that those constraints. Because all your training data has been three and a half minute songs. It's right. So digitization of data led to MP3s. Yes, I think you had this file then that was distributed physically. But then you had the components of digital distribution and then the internet happened. And there was this vacuum where you had a format that could be digitally shipped but there was no business model. And then all these pirate networks happened. Napster and in Sweden Pirate Bay which was one of the biggest. And I think from a consumer point of view which kind of leads up to the inception of Spotify. From a consumer point of view consumers for the first time had this access model to music where they could without kind of any marginal cost they could try different tracks. You could use music in new ways. There was no marginal cost. And that was a fantastic consumer experience to have access to all the music ever made. I think was fantastic. But it was also horrible for artists because there was no business model around it. So they didn't make any money. So the user need almost drove the user interface before there was a business model. And then there were these download stores that allowed you to download files. Which was a solution but it didn't solve the access problem. There was still a marginal cost of 99 cents to try one more track. And I think that that heavily limits how you listen to music. The example I always give is in Spotify a huge amount of people listen to music while they sleep. While they go to sleep and while they sleep. If that costed you 99 cents per three minutes you probably wouldn't do that. And you would be much less adventurous if there was a real dollar cost to exploring music. So the access model is interesting in that it changes your music behavior. You can be you can take much more risk because there's no marginal cost to it. Maybe let me linger on piracy for a second. Because I find especially coming from Russia piracy is something that's very interesting. To me, not me of course ever, but I have friends who have partook in piracy of music, software, TV shows, sporting events. And usually to me what that shows is not that they can actually pay the money. And they're not trying to save money. They're choosing the best experience. So what to me piracy shows is a business opportunity in all these domains. And that's where I think you're right. Spotify stepped in. Basically piracy was is an experience. You can explore, find music you like. And actually the interface of piracy is horrible. Because it's I mean it's bad metadata. Yeah, bad metadata, long download times, all kinds of stuff. And what Spotify does is basically first rewards artists and second makes the experience of exploring music much better. I mean the same is true I think for movies and so on. Piracy reveals in the software space for example I'm a huge user and fan of Adobe products. And there was much more incentive to pirate Adobe products before they went to a monthly subscription plan. And now all of the said friends that used to pirate Adobe products that I know now actually pay gladly for the monthly subscription. I think you're right. I think it's a sign of an opportunity for product development. And that sometimes there's a product market fit before there's a business model fit. In product development I think that that's a sign of it. In Sweden I think it was a bit of both. There was a culture where we even had a political party called the pirate party. And this was during the time when people said that information should be free. It was somehow wrong to charge for ones and zeros. So I think people felt that artists should probably make money somehow else. In concerts or something. So at least in Sweden it was part really social acceptance even at the political level. But that also forced Spotify to compete with free. Which I don't think would actually could have happened anywhere else in the world. The music industry needed to be doing bad enough to take that risk. And Sweden was like the perfect testing ground. It had government funded high bandwidth low latency broadband. Which meant that the product would work. And it was also there was no music revenue anyway. So they were kind of like I don't think this is going to work but why not. So this product is one that I don't think could have happened in America. The world's largest music market for example. So how do you compete with free? Because that's an interesting world of the internet where most people don't like to pay for things. So Spotify steps in and tries to yes compete with free. How do you do it? So I think two things. One is people are starting to pay for things on the internet. I think one way to think about it was that advertising was the first business model because no one would put a credit card on internet. Transactional with Amazon was the second. And maybe subscription is the third. And if you look offline subscription is the biggest of those. So that may still happen. I think people are starting to pay. But definitely back then we needed to compete with free. And the first thing you need to do is obviously to lower the price to free. And then you need to be better somehow. And the way that Spotify was better was on the user experience. On the actual performance. The latency of you know even if you had high bandwidth broadband it would still take you 30 seconds to a minute to download one of these tracks. So the Spotify experience of starting within the perceptual limit of immediacy about 250 milliseconds meant that the whole trick was it felt as if you had downloaded all of Pirate Bay. It was on your hard drive. It was that fast even though it wasn't. And it was still free. But somehow you were actually still being a legal citizen. That was the trick that Spotify managed to to pull off. So I've actually heard you say this or write this and I was surprised that I wasn't aware of it because I just took it for granted. You know whenever an awesome thing comes along you're just like oh of course it has to be this way. That's exactly right. That it felt like the entire world's libraries at my fingertips because of that latency being reduced. What was the technical challenge in reducing the latency? So there was a group of really really talented engineers. One of them called Ludwig Stregius. He wrote the actually from Gothenburg. He wrote the initial the uTorrent client which is kind of an interesting backstory to Spotify. You know that we have one of the top developers from BitTorrent clients as well. So he wrote uTorrent the world's smallest BitTorrent client. And then he was acquired very early by Daniel and Martin who founded Spotify. And they actually sold the uTorrent client to BitTorrent but kept Ludwig. So Spotify had a lot of experience within peer-to-peer networking. So the original innovation was a distribution innovation where Spotify built an end-to-end media distribution system up until only a few years ago. We actually hosted all the music ourselves. So we had both the server side and the client and that meant that we could do things such as having a peer-to-peer solution to use local caching on the client side because back then the world was mostly desktop. But we could also do things like hack the TCP protocols, things like Nagel's algorithm for kind of exponential back off or ramp up and just go full throttle and optimize for latency at the cost of bandwidth. And all of this end-to-end control meant that we could do an experience that felt like a step change. These days we actually are on GCP. We don't host our own stuff and everyone is really fast these days. So that was the initial competitive advantage. But then obviously you have to move on over time. And that was over 10 years ago, right? That was in 2008. The product was launched in Sweden. It was in a beta I think 2007. And it was on the desktop, right? So it was desktop only. There was no phone. There was no phone. The iPhone came out in 2008. But the App Store came out one year later I think. So the writing was on the wall but there was no phone yet. You've mentioned that people would use Spotify to discover the songs they like and then they would torrent those songs just so they can copy it to their phone. Just hilarious. Exactly. Not torrent, pirate. Seriously, piracy does seem to be like a good guide for business models. Video content. As far as I know, Spotify doesn't have video content. Well, we do have music videos and we do have videos on the service. But the way we think about ourselves is that we're an audio service. And we think that if you look at the amount of time that people spend on audio, it's actually very similar to the amount of time that people spend on video. So the opportunity should be equally big. But today it's not at all valued. Video is valued much higher. So we think it's basically completely undervalued. So we think of ourselves as an audio service. But within that audio service I think video can make a lot of sense. I think for when you're discovering an artist, you probably do want to see them and understand who they are. To understand their identity. You won't see that video every time. No. 90% of the time the phone is going to be in your pocket. For podcasters, you use video. I think that can make a ton of sense. So we do have video, but we're an audio service where think of it as we call it internally backgroundable video. Video that is helpful but isn't the driver of the narrative. I think also if you look at YouTube, the way people, there's quite a few folks who listen to music on YouTube. So in some sense YouTube is a bit of a competitor to Spotify. Which is very strange to me that people use YouTube to listen to music. They play essentially the music videos, right? But don't watch the videos and put it in their pocket. Well I think it's similar to to what's, strangely maybe it's similar to what we were for the piracy networks. Where YouTube for historical reasons have a lot of music videos. So you use, people use YouTube for a lot of the discovery part of the process I think. But then it's not a really good sort of quote-unquote mp3 player. Because it doesn't even background. Then you have to keep the app in the foreground. So so the consumption, it's not a good consumption tool, but it's a decently good discovery. I mean I think YouTube is fantastic product. And I use it for all kinds of purposes. That's true. If I were to admit something, I do use YouTube a little bit for the discovery, to assist in the discovery process of songs. And then if I like it, I'll I'll add it to Spotify. But that's okay. That's okay with us. Okay so sorry we're jumping around a little bit. So this kind of incredible, you look at Napster, you look at the early days of Spotify. How do you, one fascinating point is, how do you grow a user base? So you're there in Sweden, you have an idea. I saw the initial sketches that look terrible. How do you grow a user base from from a few folks to millions? I think there are a bunch of tactical answers. So first of all, I think you need a great product. I don't think you take a bad product and and market it to be successful. So you need a great product. But sorry to interrupt, but it's a totally new way to listen to music too. So it's not just, did people realize immediately that Spotify is a great product? I think they did. So back to the point of piracy, it was a totally new way to listen to music legally. But people had been used to the access model in Sweden and the rest of the world for a long time through piracy. So one way to think about Spotify, it was just legal and fast piracy. And so people have been using it for a long time. So they weren't alien to it. They didn't really understand how it could be legal because it would seem too fast and too good to be true. Which I think is a great product proposition if you can be too good to be true. But what I saw again and again was people showing each other, clicking the song, showing how fast it started and saying, can you believe this? So I really think it was about speed. Then we also had an invite program that was really meant for scaling because we hosted our own servers. We needed to control scaling. But that built a lot of expectation and I don't want to say hype because hype implies that it wasn't true. Excitement around the product. And we've replicated that when we launched in the US. We also built up an invite-only program for a lot of tactics. But I think you need a great product that solves some problem. And basically, the key innovation, there was technology, but on a meta level, the innovation was really the access model versus the ownership model. And that was tricky. A lot of people said that they wanted to own their music. They would never rent it or borrow it. But I think the fact that we had a free tier, which meant that you get to keep this music for life as well, helped quite a lot. So this is an interesting psychological point that maybe you can speak to. It was a big shift for me. It's almost like I had to go to therapy for this. I think I would describe my early listening experience, and I think a lot of my friends do, is basically hoarding music. It's like slowly, one song by one song, or maybe albums, gathering a collection of music that you love. And you own it. It's like often, especially with CDs or tape, you physically had it. And with Spotify, what I had to come to grips with, and it was kind of liberating actually, is to throw away all the music. I've had this therapy session with lots of people. And I think the mental trick is, so actually we've seen the user data when Spotify started. A lot of people did the exact same thing. They started hoarding as if the music would disappear. Almost the equivalent of downloading. And so we had these playlists that had limits of a few hundred thousand tracks, which no one will ever. Well, they do. Hundreds and hundreds and hundreds of thousands of tracks. And to this day, some people want to actually save, quote unquote, the entire catalog. But I think that the therapy session goes something like, instead of throwing away your music, if you took your files and you stored them in a locker at Google, it'd be a streaming service. It's just that in that locker, you have all the world's music now for free. So instead of giving away your music, you got all the music. It's yours. You could think of it as having a copy of the world's catalog there forever. So you actually got more music instead of less. It's just that you just took that hard disk and you sent it to someone who stored it for you. And once you go through that mental journey of like, still my files, they're just over there. And I just have 40 million of them, 50 million of them or something now. Then people are like, OK, that's good. The problem is, I think, because you paid us a subscription, if we hadn't had the free tier, where you would feel like, even if I don't want to pay anymore, I still get to keep them. You keep your playlist forever. They don't disappear even though you stop paying. I think that was really important. If we would have started as, you know, you can put in all this time, but if you stop paying, you lose all your work. I think that would have been a big challenge and was the big challenge for a lot of our competitors. That's another reason why I think the free tier is really important. That people need to feel the security that the work they put in, it will never disappear, even if they decide not to pay. I like it how you put the work you put in. I actually stopped even thinking of it that way. I just actually Spotify taught me to just enjoy music as opposed to what I was doing before, which is like in an unhealthy way, hoarding music. Which I found that because I was doing that, I was listening to a small selection of songs way too much to where I was getting sick of them. Whereas Spotify, the more liberating kind of approach is I was just enjoying. Of course, I listened to Stairway to Heaven over and over, but because of the extra variety, I don't get as sick of them. There's an interesting statistic I saw. Spotify has, maybe you can correct me, but over 50 million songs, tracks, and over 3 billion playlists. So 50 million songs and 3 billion playlists, 60 times more playlist songs. What do you make of that? Yeah, so the way I think about it is that from a statistician or machine learning point of view, you have all these, if you want to think about reinforcement learning, you have this state space of all the tracks and you can take different journeys through this world. I think of these as people helping themselves and each other creating interesting vectors through this space of tracks. And then it's not so surprising that across many tens of millions of atomic units, there will be billions of paths that make sense. And we're probably pretty quite far away from having found all of them. So kind of our job now is users, when Spotify started, it was really a search box that was for the time pretty powerful. And then I like to refer to this programming language called playlisting, where if you, as you probably were pretty good at music, you knew your new releases, you knew your back catalog, you knew your Star Way to Heaven, you could create a soundtrack for yourself using this playlisting tool that's like meta programming language for music to soundtrack your life. And people who were good at music, it's back to how do you scale the product. For people who are good at music, that wasn't actually enough. If you had the catalog and a good search tool, you can create your own sessions, you could create really good a soundtrack for your entire life. Probably perfectly personalized because you did it yourself. But the problem was most people, many people aren't that good at music. They just can't spend the time. Even if you're very good at music, it's gonna be hard to keep up. So what we did to try to scale this was to essentially try to build, you can think of them as agents, that this friend that some people had that helped them navigate this music catalog, that's what we're trying to do for you. But also there is something like 200 million active users on Spotify. So there, okay so from the machine learning perspective, you have these 200 million people plus they're creating, it's really interesting to think of a playlist as, I mean I don't know if you meant it that way, but it's almost like a programming language. It's or at least a trace of exploration of those individual agents, the listeners. And you have all this new tracks coming in. So it's a fascinating space that is ripe for machine learning. So is there, is it possible, how can playlists be used as data in terms of machine learning and to help Spotify organize the music? So we found in our data, not surprising that people who playlisted a lot, they retained much better, they had a great experience. And so our first attempt was to playlist for users. And so we acquired this company called Tunigo of editors and professional playlisters and kind of leveraged the maximum of human intelligence to help build kind of these vectors through the track space for people. And that broadened the product. Then the obvious next, and we used statistical means where they could see when they created a playlist, how did that playlist perform. They could see skips of the songs, they could see how the songs perform, and they manually iterated the playlist to maximize performance for a large group of people. But there were never enough editors to playlist for you personally. So the promise of machine learning was to go from kind of group personalization using editors and tools and statistics to individualization. And then what's so interesting about the the 3 billion playlists we have is, we ended, the truth is we lucked out. This was not a priority strategy as is often the case. It looks really smart in hindsight, but it was dumb luck. We looked at these playlists and we had some people in the company, a person named Eric Wernerzohn, who was really good at machine learning already back then in like 2007, 2008. Back then it was mostly collaborative filtering and so forth. But we realized that what this is, is people are grouping tracks for themselves that have some semantic meaning to them. And then they actually label it with a playlist name as well. So in a sense, people were grouping tracks along semantic dimensions and labeling them. And so could you use that information to find that that latent embedding? And so we started playing around with collaborative filtering and we saw tremendous success with it. Basically trying to extract some of these dimensions. And if you think about it, it's not surprising at all. It'd be quite surprising if playlists were actually random, if they had no semantic meaning. For most people, they group these tracks for some reason. So we just happened across this incredible data set where people are taking these tens of millions of tracks and group them along different semantic vectors. And the semantics being outside the individual users, so it's some kind of universal. There's a universal embedding that holds across people on this earth. Yes, I do think that the embeddings you find are going to be reflective of the people who playlist it. So if you have a lot of indie lovers who playlist, your embed is going to perform better there. But what we found was that yes, there were these latent similarities. They were very powerful. And it was interesting because I think that the people who playlisted the most initially were the so-called music aficionados who were really into music. And they often had a certain... their taste was often geared towards a certain type of music. And so what surprised us, if you look at the problem from the outside, you might expect that the algorithms would start performing best with mainstreamers first because it somehow feels like an easier problem to solve mainstream taste than really particular taste. It was the complete opposite for us. The recommendations performed fantastically for people who saw themselves as having very unique taste. That's probably because all of them playlisted and they didn't perform so well for mainstreamers. They actually thought they were a bit too particular and unorthodox. So we had the complete opposite of what we expected. Success within the hardest problem first and then had to try to scale to more mainstream recommendations. So you've also acquired Echo Nest that analyzes song data. So in your view, maybe you can talk about, so what kind of data is there from a machine learning perspective? There's a huge amount, we're talking about playlisting and just user data of what people are listening to, the playlist they're constructing, and so on. And then there's the actual data within a song, what makes a song, I don't know, the actual waveforms. How do you mix the two? How much value is there in each? To me it seems like user data is a romantic notion that the song itself would contain useful information, but if I were to guess, user data would be much more powerful. Playlist would be much more powerful. Yeah, so we use both. Our biggest success initially was with playlist data without understanding anything about the structure of the song. But when we acquired Echo Nest, they had the inverse problem. They actually didn't have any play data. They were a provider of recommendations, but they didn't actually have any play data. So they looked at the structure of songs sonically, and they looked at Wikipedia for cultural references and so forth, and did a lot of NLU and so forth. So we got that skill into the company and combined our user data with their content-based... So you can think of us, we were user-based and they were content-based in their recommendations, and we combined those two. And for some cases where you have a new song that has no play data, obviously you have to try to go by either who the artist is or the sonic information in the song or what it's similar to. So there's definitely value in both, and we do a lot in both, but I would say yes. The user data captures things that have to do with culture and the greater society that you would never see in the content itself. But that said, we have seen... We have a research lab in Paris, when we can talk more about that on kind of machine learning on the creator side, what it can do for creators, not just for the consumers. But where we looked at how does the structure of a song actually affect the listening behavior, and it turns out that there is a lot of... We can predict things like skips based on the song itself. We could say that maybe you should move that chorus a bit because your skip is going to go up here. There is a lot of latent structure in the music, which is not surprising because it is some sort of mind hack. So there should be structure. That's probably what we respond to. It just blew my mind actually from the creator perspective. So that's a really interesting topic that probably most creators aren't taking advantage of. So I've recently got to interact with a few folks, YouTubers, who are obsessed with this idea of what do I do to make sure people keep watching the video? And they look at the analytics of which point do people turn it off and so on. First of all, don't think that's healthy because you can do it a little too much. But it is a really powerful tool for helping the creative process. You just made me realize you could do the same thing for creation of music. So is that something you've looked into? Can you speak to how much opportunity there is for that? Yeah, I listened to the podcast with Zoroash and I thought it was fantastic and I reacted to the same thing where he said he posted something in the morning, immediately watched the feedback, where the drop-off was and then responded to that in the afternoon. Which is quite different from how people make podcasts, for example. I mean, the feedback loop is almost non-existent. So if we back out one level, I think actually both for music and podcasts, which we also do at Spotify, I think there's a tremendous opportunity just for the creation workflow. I think it's really interesting speaking to you because you're a musician, a developer and a podcaster. If you think about those three different roles, if you make the leap as a musician, if you think about it as a software tool chain, really, your DAW with the stems, that's the IDE, right? That's where you work in source code format with what you're creating. Then you sit around and you play with that and when you're happy you compile that thing into some sort of AAC or MP3 or something. You do that because you get distribution. There are so many run times for that MP3 across the world in car steers and stuff. So you kind of compile this executable and you ship it out in kind of an old-fashioned boxed software analogy. Then you hope for the best, right? But as a software developer, you would never do that. First you go on GitHub and you collaborate with other creators. Then you think it'd be crazy to just ship one version of your software without doing an A-B test, without any feedback loop. Issue tracking. Exactly. Then you would look at the feedback loops and try to optimize that thing. I think if you think of it as a very specific software tool chain, it looks quite arcane. The tools that a music creator has versus what a software developer has. So that's kind of how we think about it. Why wouldn't a music creator have something like GitHub where you could collaborate much more easily? We bought this company called Soundtrap which has a kind of Google Docs for music approach where you can collaborate with other people on the kind of source code format with stems. I think introducing things like AI tools there to help you as you're creating music, both in helping you put accompaniment to your music like drums or something, help you master and mix automatically, help you understand how this track will perform. Exactly what you would expect as a software developer. I think it makes a lot of sense. I think the same goes for a podcaster. I think podcasters will expect to have the same kind of feedback loop that Srirash has. Why wouldn't you? Maybe it's not healthy but... Sorry, I wanted to criticize the fact that you can overdo it because a lot of the... and we're in a new era of that. So you can become addicted to it and therefore what people say you become a slave to the YouTube algorithm. It's always a danger of a new technology as opposed to say if you're creating a song, becoming too obsessed about the intro riff to the song that keeps people listening versus actually the entirety of the creation process. It's a balance. Absolutely. But the fact that there's zero... I mean you're blowing my mind right now because you're completely right that there's no signal whatsoever, there's no feedback whatsoever on the creation process in music or podcasting almost at all. Are you saying that Spotify is hoping to help create tools to... not tools but... Not tools actually. Actually tools for creators. Absolutely. So we have... we've made some acquisitions the last few years around music creation. This company called Soundtrap which is a digital audio workstation but that is browser based and their focus was really the Google Docs approach. We can collaborate with people much more easily than you could in previous tools. So we have some of these tools that we're working with that we want to make accessible and then we can connect it with our consumption data. We can create this feedback loop where we could help you understand, we could help you create and help you understand how you will perform. We also acquired this other company within podcasting called Anchor which is one of the biggest podcasting tools. Mobile focused. So really focused on simple creation or easy access to creation but that also gives us this feedback loop and even before that we invested in something called Spotify for Artists and Spotify for Podcasters which is an app that you can download, you can verify that you are that creator and then you get things that software developers have had for years. You can see where if you look at your podcast for example on Spotify or a song that you released you can see how it's performing, which cities it's performing in, who's listening to it, what's the demographic breakup. So similar in the sense that you can understand how you're actually doing on the platform. So we definitely want to build tools. I think you also interviewed the head of research for Adobe and I think that's back to Photoshop that you like. I think that's an interesting analogy as well Photoshop I think has been very innovative in helping photographers and artists and I think there should be the same kind of tools for music creators where you could get AI assistance for example as you're creating music as you can do with Adobe where you can, I want a sky over here and you can get help creating that sky. The really fascinating thing is what Adobe doesn't have is a distribution for the content you create. So you don't have the data of if I create, if I, you know, whatever creation I make in Photoshop or Premiere I can't get like immediate feedback like I can on YouTube for example about the way people are responding and if Spotify is creating those tools that's a really exciting actually world. But let's talk a little about podcasts. So I have trouble talking to one person so it's a bit terrifying and kind of hard to fathom but on average 60 to 100,000 people will listen to this episode. Okay so it's intimidating. Yeah it's intimidating. So I hosted on Blueberry. I don't know if I'm pronouncing that correctly actually. It looks like most people listen to it on Apple Podcasts, Castbox and Pocketcast and only about a thousand listen on Spotify. Just my podcast. Right so where do you see a time when Spotify will dominate this? So Spotify is relatively new into this podcasting. Sorry yeah in podcasting. What's the deal with podcasting and Spotify? How serious is Spotify about podcasting? Do you see a time where everybody would listen to you know probably a huge amount of people, majority perhaps, listen to music on Spotify? Do you see a time when the same is true for podcasting? Well I certainly hope so. That is our mission. Our mission as a company is actually to enable a million creators to live off of their art and a billion people be inspired by it. And what I think is interesting about that mission is it actually puts the creators first even though it started as a consumer focused company and it says to be able to live off of their art not just make some money off of their art as well. So it's quite an ambitious project. And so we think about creators of all kinds and we kind of expanded our mission from being music to being audio a while back. And that's not so much because we think we made that decision. We think that decision was was made for us. We think the world made that decision. Whether we like it or not, when you put in your headphones you're going to make a choice between music and a new episode of your podcast or something else. We're in that world whether we like it or not and that's how radio works. So we decided that we think it's about audio. You can see the rise of audio books and so forth. We think audio is this great opportunity. So we decided to enter it and obviously Apple and Apple podcasts is absolutely dominating in podcasting and we didn't have a single podcast only like two years ago. What we did though was we looked at this and said can we bring something to this. We want to do this but back to the original Spotify we have to do something that consumers actually value to be able to do this. And the reason we've gone from not existing at all to being the quite a wide margin, the second largest podcast consumption, still wide gap to iTunes but we're growing quite fast. I think it's because when we looked at the consumer problem people said surprisingly that they wanted their podcasts and music in the same application. So what we did was we took a little bit of a different approach where we said instead of building a separate podcast app we thought is there a consumer problem to solve here because the others are very successful already and we thought there was in making a more seamless experience where you can have your podcast and your music in the same application. Because we think it's audio to you and that has been successful and that meant that we actually had 200 million people to offer this to instead of starting from zero. So I think we have a good chance because we're taking a different approach than the competition. And back to the other thing I mentioned about creators because we're looking at the end-to-end flow. I think there's a tremendous amount of innovation to do around podcast as a format. When we have creation tools and consumption I think we could start improving what podcasting is. I mean podcast is this opaque big like one two hour file that you're streaming which it really doesn't make that much sense in 2019 that it's not interactive, there's no feedback loops, nothing like that. So I think if we're gonna win it's gonna have to be because we build a better product for creators and for consumers. So we'll see but it's certainly our goal. We have a long way to go. Well the creators part is really exciting. You got me hooked there. It's the only stats I have. Blueberry just recently added the stats of whether it's listened to the end or not and that's like a huge improvement but that's still nowhere to where you could possibly go in terms of statistics. You just download the Spotify podcasters app and verify and then then you'll know where people dropped out in this episode. Oh wow okay. The moment I started talking. Okay I might be depressed by this but okay so one other question. The original Spotify for music and I have a question about podcasting in this line is the idea of albums. I have music aficionados, friends who are really big fans of music often really enjoy albums, listening to entire albums of an artist. Correct me if I'm wrong but I feel like Spotify has helped replace the idea of an album with playlists. So you create your own albums. It's kind of the way at least I've experienced music and I really enjoy it that way. One of the things that was missing in podcasting for me, I don't know if it's missing. I don't know. It's an open question for me but the way I listen to podcasts is the way I would listen to albums. So I take Joe Rogan Experience and that's an album and I listen you know I put that on and I listen one episode after the next and there's a sequence and so on. Is there room for doing what you did for music or doing what Spotify did for music but creating playlists sort of this kind of playlisting idea of breaking apart from podcasting from individual podcasts and creating kind of this interplay or have you thought about that space? It's a great question. So I think in in music you're right. Basically you bought an album so it was like you bought a small catalog of like 10 tracks right. It was again it was actually a lot of a lot of consumption. You think it's about what you like but it's based on the business model. You paid for this 10 track service and then you listen to that for a while and then when everything was flat priced you tended to listen differently. Now so I think the album is still tremendously important. That's why we have it and you can save albums and so forth and you have a huge amount of people who really listen according to albums and I like that because it is a creator format. You can tell a longer story over several tracks and so some people listen to just one track some people actually want to hear that whole story. Now in podcast I think I think it's different. You can argue that podcasts might be more like shows on Netflix. You have like a full season of Narcos and you're probably not going to do like one episode of Narcos and then one of House of Cards. Like you know there's a narrative there and you love the cast and you love these characters. So I think people will people love shows and I think they will they will listen to those shows. I do think you follow a bunch of shows at the same time so there's certainly an opportunity to bring you the latest episode of you know whatever the five six ten things that that you're into. But I think people are going to listen to specific hosts and love those hosts for a long time because I think there's something different with podcasts where this format of the experience of the audience is actually sitting here right between us. Whereas if you look at something on TV the audio actually would come from you would sit over there and the audio would come to you from both of us as if you were watching not as you were part of the conversation. So my experience is having listened to podcasts like yours and Joe Rogan is I feel like I know all of these people. They have no idea who I am but I feel like I've listened to so many hours of them. It's very different from me watching a TV show or an interview. So I think you fall in love with people and experience in a different way. So I think shows and hosts are going to be very very important. I don't think that's going to go away into some sort of thing where you don't even know who you're listening to. I don't think that's going to happen. What I do think is I think there's a tremendous discovery opportunity in podcasts because the catalog is growing quite quickly and I think podcasts is only a few like five six hundred thousand shows right now. If you look back to YouTube as another analogy for creators no one really knows if you would lift the lid on YouTube but it's probably billions of episodes and so I think the podcast catalog will probably grow tremendously because the creation tools are getting easier and then you're going to have this discovery opportunity that I think is really big. So a lot of people tell me that they love their shows but discovery in podcasts kind of suck. It's really hard to get into new show. They're usually quite long. It's a big time investment. So I think there's plenty of opportunity in the discovery part. Yeah for sure. A hundred percent. And even the dumbest. There's so many low-hanging fruit too. For example just knowing what episode to listen to first to try out a podcast. Exactly. Because most podcasts don't have an order to them. They can be listened to out of order and sorry to say some are better than others episodes. So some episodes of Joe Rogan are better than others and it's nice to know which you should listen to to try it out. And there's as far as I know almost no information in terms of like upvotes on how good an episode is. Exactly. So I think part of the problem is it's kind of like music. There isn't one answer. People use music for different things and there's actually many different types of music. There's workout music and there's classical piano music and focus music and and so forth. I think the same with podcasts. Some podcasts are sequential. They're supposed to be listened to in order. It's actually telling a narrative. Some podcasts are one topic kind of like yours but different guests. So you could jump in anywhere. Some podcasts actually have completely different topics and for those podcasts it might be that I want you know we should recommend one episode because it's about AI from someone but then they talk about something that you're not interested in the rest of the episode. So I think what we're spending a lot of time on now is just first understanding the domain and creating kind of the knowledge graph of how do these objects relate and how do people consume. I think we'll find that it's going to be different. I'm excited. Spotify is the first people I'm aware of that are trying to do this for podcasting. Podcasting has been like a wild west up until now. We want to be very careful though because it's been a very good wild west. I think it's this fragile ecosystem and we want to make sure that you don't barge in and say like oh we're gonna internetize this thing and you have to think about the the creators. You have to understand how they get distribution today, who listens to how they make money today, try to you know make sure that their business model works, that they understand. I think it's back to doing something to improving their product like feedback loops and distribution. So jumping back into terms of this fascinating world of recommender system and listening to music and using machine learning to analyze things. Do you think it's better to what currently, correct me if I'm wrong, but currently Spotify lets people pick what they listen to for the most part. There's a discovery process but you kind of organize playlists. Is it better to let people pick what they listen to or recommend what they should listen to? Something like Stations by Spotify that I saw that you're playing around with. Maybe you can tell me what's the status of that. This is a Pandora style app that just kind of as opposed to you select the music you listen to, it kind of feeds you the music you listen to. What's the status of Stations by Spotify? What's its future? The story of Spotify as we have grown has been that we made it more accessible to different audiences. Stations is another one of those where the question is some people want to be very specific. They actually want to hear Stairway to Heaven right now. That needs to be very easy to do. Some people or even the same person at some point might say I want to feel upbeat or I want to feel happy or I want songs to sing in the car. So they put in the information at a very different level and then we need to translate that into what that means musically. So Stations is a test to create like a consumption input vector that is much simpler where you can just tune it a little bit and see if that increases the overall reach. But we're trying to kind of serve the entire gamut of super advanced so-called music aficionados all the way to people who love listening to music but it's not their number one priority in life. They're not going to sit and follow every new release from every new artist. They need to be able to influence music at a different level. So you can think of it as different products and I think one of the interesting things to answer your question on if it's better to let the user choose or to play I think the answer is the challenge when machine learning kind of came along there was a lot of thinking about what does product development mean in a machine learning context. People like Andrew Ng for example when he went to Baidu he started doing a lot of practical machine learning, went from academia and he thought a lot about this and he had this notion that a product manager, designer, and engineer they used to work around this wireframe kind of describe what the product should look like or something to talk about. When you're doing like a chatbot or a playlist what are you going to say? Like it should be good? That's not a good product description. So how do you do that? And he came up with this notion that the test set is the new wireframe. The job of the product manager is to source a good test set that is representative of what like if you say like I want to play this that is Song Sissing in the car. The job of the product manager is to go and source like a good test set of what that means then you can work with engineering to have algorithms to try to produce that right. So we try to think a lot about how to structure product development for a machine learning age and what we discovered was that a lot of it is actually in the expectation and you can go two ways. Let's say that if you set the expectation with the user that this is a discovery product like Discover Weekly you're actually setting the expectation that most of what we show you will not be relevant. When you're in the discovery process you're going to accept that actually if you find one gem every Monday that you totally love you're probably going to be happy even though the statistical meaning one out of ten is terrible or one out of twenty is terrible from a user point of view because the setting was discovered is fine. Can I say to interrupt real quick I just actually learned about Discover Weekly which is a Spotify I don't know it's a feature of Spotify that shows you cool songs to listen to. Maybe I can do issue tracking. I couldn't find it on my Spotify app. It's in your library. It's in the library. It's in the list of live because I was like whoa this is cool I didn't know this existed and I tried to find it but. I will show it to you and feedback to our product team. There you go. But yeah so yeah sorry just to just to mention the expectation there is basically that you're going to discover new songs. Yeah so so then you can be quite adventurous in the recommendations you do but if you're but we have another product called Daily Mix which kind of implies that these are only going to be your favorites. So if you have one out of ten that is good and nine out of ten that doesn't work for you you're going to think it's a horrible product. So actually a lot of the product development we learned over the years is about setting the right expectations. So for Daily Mix you know algorithmically we would pick among things that feel very safe in your taste space. With Discover Weekly we go kind of wild because the expectation is most of this is not gonna. So a lot of that a lot of to answer your question there a lot of should you let the user pick or not it depends. We have some products where the whole point is that the user can click play put the phone in the pocket and it should be really good music for like an hour. We have other products where you probably need to say like no no save no no and it's very interactive. I see that makes sense and then the radio product the station's product is one of these like click play put in your pocket for hours. That's really interesting so you're thinking of different test sets of for different users and trying to create products that sort of optimize optimize for those test sets that represent a specific set of users. Yes I think one thing that I think is interesting is we invested quite heavily in editorial in people creating playlists using statistical data and that was successful for us and then we also invested in in machine learning and for the longest time you know within Spotify and within the rest of the industry there was always this narrative of humans versus the machine. Algo versus editorial and editors would would say like well if I had that data if I could see your playlisting history and I made a choice for you I would have made a better choice and they would have because they they understand they're much smarter than these algorithms. The human is incredibly smart compared to our algorithms. They can take culture into account and so forth. The problem is that they can't make 200 million decisions per hour for every user that logs in so the algo may be not as sophisticated but much more efficient. So there was this contradiction but then a few years ago we started focusing on this kind of human in the loop thinking around machine learning and we actually coined an internal term for it called algatorial the combination of algorithms and and editors where if we take a concrete example you think of the editor this paid expert that we have that's really good at something like soul, hip-hop, EDM something right there are two experts no one in the industry so they have all the cultural knowledge you think of them as the product manager and you say that let's say that you want to create a you think that there's a there's a product need in the world for something like songs to sing in the car or songs to sing in the shower I'm taking that example because it exists people love to scream songs in the car when they drive right yeah so you want to create that product then you have this product manager who's a musical expert they create they come up with a concept like I think this is a missing thing in in humanity like a playlist called songs to sing in the car they create the the framing the image the title and they create a test set of or they create a group of songs like a few thousand songs out of the catalog that they manually curate that are known songs that are great to sing in the car and they can take like through romance into account they understand things that our algorithms do not at all so they have this huge set of tracks then when we deliver that to you we look at your taste vectors and you get the 20 tracks that are songs to sing in the car in your taste so you have you have personalization and editorial input in the same process if that makes sense yeah it makes total sense and I have several questions around that this is a this is like fascinating okay so first it is a little bit surprising to me that the world expert humans are outperforming machines at specifying songs to sing in the car so maybe you could talk to that a little bit I don't know if you can put it into words but what is it how difficult is this problem uh of do you really uh I guess what I'm trying to ask is there how difficult is it to encode the cultural references uh the the context of the song the artists all all those things together can machine learning really not do that I mean I think machine learning is great at replicating patterns if you have the patterns but if you try to write me a spec of what songs greatest song to sing in the car definition is is it is it loud does it have many choruses should have been in movies it's it quickly gets incredibly complicated right yeah and and a lot of it may not be in the structure of the song or the title it could be cultural references because you know it was a history so so the definition problems quickly get and I think that was the that was the insight of Andrew Ng when he said the job of the product manager is to understand these things that that algorithms don't and then define what that looks like and then you have something to train towards right then you have kind of the test set and then so so today the editors create this pool of tracks and then we personalize you could easily imagine that once you have this set you could have some automatic exploration of the rest of the catalog because then you understand what it is and then the other side of it when machine learning does help is this taste vector how hard is it to construct a vector that represents the things an individual human likes this human preference so you can you know music isn't like it's not like amazon like things you usually buy music seems more amorphous like it's this thing that's hard to specify like what what is well you know if you look at my playlist what is the music that I love it's harder it seems to be uh much more difficult to specify concretely so how hard is it to build a taste vector it is very hard in the sense that you need a lot of data and i think what we found was that so it's not so it's not a stationary problem it changes over time um and so we've gone through the journey of if if um you've done a lot of computer vision obviously i've done a bunch of computer vision in in my past and we started kind of with the handcrafted heuristics for you know this is kind of in the music this is this and if you consume this you probably like this so we have we started there and we have some of that still then what was interesting about the playlist data was that you could find these latent things that wouldn't necessarily even make sense to you that could could even capture maybe cultural references because they co-occurred things that that wouldn't have uh appeared kind of mechanistically either in the content or so forth so um i think that um i think the core assumption is that there are patterns in in almost everything and if there are patterns these these embedding techniques are getting better and better now now as everyone else we're also using kind of deep embeddings where you can encode binary values and and so forth um and and what i think is interesting is is this process to try to find things that um that do not necessarily you wouldn't actually have have guessed so it is very hard in a in a in an engineering sense to find the right dimensions it's an incredible scalability problem to do for hundreds of millions of users and to update it every day but in but in theory um in theory embeddings isn't that complicated the fact that you try to find some principal components or something like that dimensionality reduction and so forth so the theory i guess is easy the practice is is very very hard and it's a it's a huge engineering challenge but fortunately we have some amazing both research and engineering teams in in this space yeah i guess the the question is all i mean it's similar i deal with it with the autonomous vehicle space is the question is how hard is driving and here is basically the question is of edge cases so embedding probably works not probably but i would imagine works well in a lot of cases so there's a bunch of questions that arise then so do song preferences does your taste vector depend on context like mood right so there's different moods and absolutely so how does that take in it and is it is it possible to take that as a consideration or do you just leave that as a interface problem that allows the user to just control it so when i'm looking for workout music i kind of specify it by choosing certain playlists doing certain search yeah so that's a great point it's back to the product development you could try to spend a few years trying to predict which mood you're in automatically when you open spotify or you create a tab which is happy and sad right and you're going to be right 100 of the time with one click now it's probably much better to let the user tell you if they're happy or sad or if they want to work out on the other hand if your user interface become 2000 tabs you're introducing so much friction so no one will use the product so then you have to get better so it's this thing where i think maybe it was i remember who coined it but it's called fault tolerant uis right you build a ui that is tolerant to being wrong and then you can be much less right in your in your in your algorithms so we you know we've had to learn a lot of that building the right ui that fits where the where the machine learning is and and a great discovery there which is which was by the teams during uh one of our hack days was this thing of taking discovery packaging it into a playlist and saying that these are new tracks that we think you might like based on this and setting the right expectation made it made it a great product so i think we have this benefit that for example tesla doesn't have that we can we can we can change the expectation we can we can build a fault tolerant setting it's very hard to be fault tolerant when you're driving at a you know 100 miles per hour or something and and we we have the luxury of being able to say that of being wrong if we have the right ui which gives us different abilities to take more risk so i actually think the self-driving problem is is much harder oh yeah for sure it's much less fun because people die exactly and since spotify uh it's such a more fun problem because failure will i mean failure is beautiful in a way it leads to exploration so it's a really fun reinforcement learning problem the worst case scenario is you get these wtf tweets like how the hell did i get this this song which is which is a lot better than the self-driving phase so what's the feedback that a user what's the signal that a user provides into the system so the the you mentioned skipping what is like the strongest signal is uh you didn't mention clicking like so so we have a few signals that are important obviously playing playing through so so one of the benefits of music actually even compared to podcast or or movies is the object itself is really only about three minutes so you get a lot of chances to recommend and the feedback loop is is every three minutes instead of every two hours or something so you actually get kind of noisy but but quite fast feedback and so you can see if people played through or if the which is you know the inverse of skip really that's an important signal on the other hand much of the consumption happens when your phone is in your pocket maybe you're running or driving or you're playing on a speaker and so you not skipping doesn't mean that you love that song it might be that it wasn't bad enough that you would walk up and skip so it's a noisy signal then then we have the equivalent of the like which is you saved it to your library that's a pretty strong signal of affection and then we have the more explicit signal of playlisting like you took the time to create a playlist you put it in there there's a very little small chance that if you took all that trouble this is not a really important track to you and then we understand also what other tracks it relates to so we have we have the playlisting we have the like and then we have the listening or skip and and you have to have very different approaches to all of them because they have different levels of of noise one one is very voluminous but noisy and the other is rare but you can you can probably trust it yeah it's interesting because uh i i think between those signals captures all the information you'd want to capture i mean there's a feeling a shallow feeling for me that there's sometimes that i'll hear a song that's like yes this is you know this was the right song for the moment but there's really no way to express that fact except by listening through it all the way yeah and maybe playing it again at that time or something yeah it there's no need for a button that says this was the best song i could have heard at this moment well we're playing around with that with kind of the thumbs up concept saying like i really like this just kind of talking to the algorithm it's unclear if that's the best way for humans to interact maybe it is maybe they should think of spotify as a person an agent sitting there trying to serve you and you can say like bad spotify good spotify right now the analogy we've had is more you shouldn't think of of us we should be invisible and the feedback is if you save it kind of you work for yourself you do a playlist because you think is great and we can learn from that it's kind of back to back to tesla how they kind of have this shadow mode they sit in what you drive we kind of took the same analogy we sit in what you playlist and then maybe we can we can offer you an autopilot where you can take over for a while or something like that and then back off if you say like that's not that's not good enough but but i think it's interesting to figure out what your mental model is if spotify is an ai that you talk to which i think might be a bit too abstract for for many consumers or if you still think of it as it's my music app but it's just more helpful and depends on the device it's running on which brings us to smart speakers so i have a lot of the spotify listening i do is on things that on devices i can talk to whether it's from amazon google or apple what's the role of spotify on those devices how do you think of it differently than on the phone or on the desktop there are a few things to say about the first of all it's incredibly exciting they're growing like crazy especially here in the in the in the us um and it's solving a consumer need that i think is is you can think of it as just remote interactivity you can control this thing from from from across the room and it may feel like a small thing but it turns out that friction matters to consumers being able to say play pause and so forth from across the room is is very powerful so basically you made you made the living room interactive now and uh what we see in our data is that the the number one use case for these speakers is music music and podcast so fortunately for us it's been important to these companies to have those use case covered so they want to spotify on this we have very good relationships with with with them um and we're seeing we're seeing tremendous success with them what what i think it's interesting about them is it's already working we we we kind of had this epiphany many years ago back when we started using sonos if you went through all the trouble of setting up your sonos system you had this magical experience where you had all the music ever made in your living room and and we we we made this assumption that the the home everyone used to have a cd player at home but they never managed to get their files working in the home having this network attached storage was too cumbersome for most consumers so we made the assumption that the home would skip from the cd all the way to streaming books where where you would get you would buy the steering and would have all the music built in that took longer than we thought but with the voice speakers that was the unlocking that made kind of the connected speaker happen in the home so so it really it really exploded and we saw this engagement that we predicted would happen what i think is interesting though is where it's going from now right now you think of them as voice speakers but i think if you look at google io for example they just added a camera to it where you know when the alarm goes off instead of saying hey google stop you can just wave your hand so i think they're going to think more of it as a as an agent or as a as an assistant truly an assistant and an assistant that can see you it's going to be much more effective than than a blind assistant so i i think these things will morph and we won't necessarily think of them as quote-unquote voice speakers anymore just as interactive access to the internet in the home but i still think that the biggest use case for those will be will be audio so for that reason we're investing heavily in it and we built our own nlu stack to be able to the the challenge here is how do you innovate in that world it's it's it lowers friction for consumers but it's also much more constrained there you have no pixels to play with in an in an audio only world it's really the vocabulary that is the interface so we started investing and playing around quite a lot with that trying to understand what the future will be of you speaking and gesturing and waving at your music and actually uh you're actually nudging closer to the autonomous vehicle space because from everything i've seen the level of frustration people experience upon failure of natural language understanding is much higher than failure in other contexts people get frustrated really fast so if you screw screw that experience up even just a little bit they give up really quickly yeah and and i think you see that in the data while while it's tremendously successful the most common interactions are play pause and you know next the things where if you compare it to taking up your phone unlocking it bringing up the app and skipping clicking skip yeah it was it was much lower friction but then uh for for longer more complicated things like can you find me that song people still bring up their phone and search and then play it on their speaker so we tried again to build a fault tolerant ui where for the more for the more complicated things you can still pick up your phone have powerful full keyboard search and then try to optimize for where there is actually lower friction and try to it's it's kind of like the test autopilot thing you have to be at the level where you're helpful if you're too smart and just in the way people are going to get frustrated and first of all i'm not obsessed with stairway to heaven it's just a good song but let me mention that as a use case because it's an interesting one i've literally told one of i don't want to say the name of the speaker because it'll when people are listening to it it'll make their speaker go off but i talk to the speaker and i say play stairway to heaven and every time it like not every time but a large percentage of the time it plays the wrong stairway to heaven it plays like some cover of the and that that part of the experience i actually wonder from a business perspective does spotify control that entire experience or no it seems like the nlu the the natural language stuff is controlled by the speaker and then spotify stays at a layer below that it's a good and complicated question some of which is dependent on the on the partner so it's hard to comment on the on the specifics but the question is the right one the challenge is if you can't use any other personalization i mean we know which stairway to heaven and and the truth is maybe for for one person it is exactly the cover that they want and they would be very frustrated if it plays i i think we i think we default to the right version but but you actually want to be able to do the cover for the person that just played the cover 50 times or spotify is just going to seem stupid so you want to be able to leverage the personalization but you have this stack where where you have the the asr and this thing called the n best list of the n best guesses here and then the person comes in at the end you actually want the personization to be here when you're guessing about what they actually meant so we're working with these partners um and it's a complicated it's a complicated thing where you want to you want to be able so first of all you want to be very careful with your users data you don't want to share your users data without their permission but you want to share some data so that their experience gets better so that these partners can understand enough but not too much and so forth so it's really the the trick is that it's it's like a business driven relationship where you're doing product development across companies together yeah which is which is really complicated but this is exactly why we built our own nlu so that we actually can make personalized guesses because this is the biggest frustration from a user point of view they don't understand about asrs and n best lists and and business deals they're like how hard can it be i've told this thing 50 times this version and still replace the wrong thing it can't it can't be hard so we try to take that user approach if the user the user is not going to understand the complications of business we have to solve it let's talk about sort of a complicated subject that i myself i'm quite torn about the idea sort of of um paying artists right i saw as of august 31st 2018 over 11 billion dollars were paid to rights holders so and further distributed to artists from spotify so a lot of money is being paid to artists first of all the whole time as a consumer for me when i look at spotify i'm not sure i'm remembering correctly but i think you said exactly how i feel which is this is too good to be true like when i started using spotify i assumed you guys would go bankrupt in like a month it's like this is too good a lot of people did it's like this is amazing uh so one question i have is sort of the bigger question how do you make money in this complicated world how do you deal with the relationship with record labels who are complicated uh these big you're essentially in have the task of herding cats but like rich and powerful cats and also have the task of paying artists enough and paying those labels enough and still making money in the internet space where people are not willing to pay hundreds of dollars a month so how do you navigate the space how do you navigate that's a beautiful description herding rich cats yeah i've never heard that before it is very complicated and i think certainly actually betting against spotify has been statistically a very smart thing to do just looking at the at the line of roadkill in music streaming services it's it's kind of i think if i had understood the complexity when i joined spotify unfortunately fortunately i didn't know enough about the the music industry to understand the complexities because then i would have made a more rational guess that it wouldn't work so you know ignorance is bliss but i think there have been a few distinct challenges i think as i said one of the things that made it work at all was that sweden and the nordics was a lost market so um they would you know there was there was no risk for labels to try this i don't think it would have worked if if the market was was healthy so so that was the initial condition then then we had this tremendous challenge with the model itself so now most people were pirating but for the people who bought a download or a cd the artists would get all the revenue for all the future plays then right so you got it all up front whereas the streaming model was like almost nothing day one almost nothing day two and then at some point this curve of incremental revenue would intersect with your day one payment and that took a long time to play out before before the music labels they understood that but on the artist side it took a lot of time to understand that actually if i have a big hit that is going to be played for for for many years this is a much better model because i get paid based on how much people use the product not how much they thought they would use it day one or so forth so it was a complicated model to get across and but time helped with that right and now now the revenues to the music industry actually are bigger again then you know it's gone through this incredible dip and now they're back up and so we're we're very you see proud of having having been a a part of that so there have been distinct problems i think when it comes to the to the labels we have taken the painful approach some of our competition at the time they kind of they kind of looked at other companies and said if we just if we just ignore the rights we get really big really fast we're going to be too big for the for the labels to kind of too big to fail they're not going to kill us we didn't take that approach we went legal from day one and we we negotiated and negotiated and negotiated it was very slow it's very frustrating we were angry at seeing other companies taking shortcuts and seeming to get away with it it was this this this game theory thing where over many rounds of playing the game this would be the right strategy and even though clearly there's a lot of frustrations at times during renegotiations there is this there is this weird trust where we have been honest and fair we've never screwed them they've never screwed us it's tenuous but there's this trust and like they know that if music doesn't get really big if lots of people do not want to listen to music i want to pay for it spotify has no business model so we actually are incredibly aligned right other companies not to be tensed but other companies have other business models where even if they may know music from no money for music they still be profitable companies but spotify won't so and i think the industry sees that we are actually aligned business wise so there is this this trust that allows us to to do product development even if it's scary um you know taking risks the free model itself was an incredible risk for the music industry to take that they should get credit for now some of it was that they had nothing to lose in sweden but frankly a lot of the labels also took risk and so i think we built up that trust with it with the i think uh herding of cats sounds a bit what's the word it sounds like uh dismissive of the cats dismissive no every cat mattered they're all beautiful and very important exactly they've taken a lot of risks and certainly it's been frustrating about it's not good yeah so it's it's it's really like playing it's it's game theory if you play the theory if you play the game many times then you can have the statistical outcome that you bet on and it feels very painful when you're in the middle of that thing i mean there's risk there's trust there's relationships from uh just having read the biography of steve jobs similar kind of relationship were discussed in itunes the idea of selling a song for a dollar was very uncomfortable for labels and exactly and there was no it was the same kind of thing it was trust it was game theory as as a lot of relationships that had to be built and uh it's really a terrifyingly difficult process that apple could go through a little bit because they could afford for that process to fail for spotify it seems terrifying because uh you can't initially i think a lot of it comes out comes down to you know honestly daniel and his tenacity in in negotiating which seems like an impossible it's a fun task because he was completely unknown and so forth but maybe that was also the reason that that it worked but i think uh yeah i think game theory is probably the best way to think about it you could straight go straight for this like nash equilibrium that someone is going to defect or or you played many times you try to actually go for the top left the corporation's sell is there any magical reason why spotify seems to have won this so a lot of people have tried to do what spotify tried to do and spotify has come out well so the answer is that there's no magical reason because i don't believe in magic but i think there are there are reasons um and i think some of them are that people have misunderstood a lot of what we actually do the actual the actual spotify model is very complicated they've looked at the premium model and said it seems like you can you can charge 9.99 for music and people are going to pay but that's not what happened actually when we launched the original mobile product everyone said they would never pay what happened was they started on the on the free product and then their engagement grew so much that eventually they said maybe it is worth 9.99 right it's uh it's your propensity to pay gross with your engagement so we have this super complicated business model where you operate two different business model advertising and premium at the same time and i think that is hard to replicate i have i struggle to think of other companies that run large-scale advertising and subscription products at the same time so i think the business model is actually much more complicated than people think it is and and so some people went after just the premium part without the free part and ran into a wall where no one wanted to pay some people went after just music music should be free just ads which doesn't give you enough revenue and doesn't work for the music industry so i think that combination is um it's kind of opaque from the outside so maybe i shouldn't say it here and reveal the secret but that that turns out to be harder to replicate than you would than you would think so there's a lot of brilliant business strategy here brilliance or luck probably more luck but it doesn't really matter it looks brilliant in retrospect so let's call it brilliant yeah when the books are written it'll be brilliant you've uh mentioned that your philosophy is to embrace change so how will the music streaming and music listening world change over the next 10 years 20 years you look out into the far future what do you think i think that music and for that matter audio podcasts audio books i think it's one of the few core human needs i think it there is no good reason to me why it shouldn't be at the scale of something like messaging or social networking i don't think it's a niche thing to listen to music or news or something so i think scale is obviously one of the things that i really hope for i think i hope that it's going to be billions of users i hope eventually everyone in the world gets access to all the world's music ever made so obviously i think it's going to be a much bigger business otherwise we we wouldn't be betting this big now if you if you look more at how it is consumed what i'm hoping is back to this analogy of the software tool chain where i think i sometimes internally i make this analogy to to text messaging text messaging was also based on standards in the in the area of mobile carriers you had the sms the 140 character 120 carat sms and it was great because everyone agreed on the standard so as a consumer you got a lot of distributions and interoperability but it was a very constrained format and and when the industry wanted to add pictures to that format to do the mms i looked it up and i think it took from the late 80s to early 2000s this is like a 15 20 year product cycle to bring pictures into that now once that entire value chain of creation and consumption got wrapped in one software stack within something like snapchat or whatsapp like the first week they added disappearing messages like then two weeks later they added stories like the pace of innovation when you're on one software stack and you can you can you can affect both creation and consumption i think it's going to be rapid so with these streaming services we now for the first time in history have enough i hope people on one of these services actually whether it's spotify or amazon or apple or youtube and hopefully enough creators that you can actually start working with the format again and and that excites me i think being able to change these constraints from 100 years that could really that could really do something interesting i don't i really hope it's not just going to be the iteration on on the same thing for the next 10 to 20 years as well yeah changing the creation of music or creation of audio creation of podcasts is a really fascinating possibility i myself don't understand what it is about podcasts that's so intimate it just is i listen to a lot of podcasts i think it touches on a human on a deep human need for connection that people do feel like they're connected to when they listen i don't understand what the psychology of that is but in this world is becoming more and more disconnected uh it feels like this is fulfilling a certain kind of need and uh empowering the creator as opposed to just the listener is really interesting that's this i'm really excited that you're working on yeah i think one of the things that is inspiring for our teams to work on podcast is exactly that whether you think like i like i probably do that it's something biological about perceiving to be in the middle of the conversation that makes you listen in a different way it doesn't really matter people seem to perceive it differently and uh there was this narrative for a long time that you know if you look at video everything kind of in the foreground it got shorter and shorter and shorter because of financial pressures and monetization and so forth and eventually at the end there's always like 20 seconds clip people just screaming something and and uh i'm really i feel really good about the fact that you you could have interpreted that as people have no attention span anymore they don't want to listen to things they're not interested in deeper stories like you know people are people are getting dumber but then podcast came along and it's almost like no no the need still existed once but maybe maybe it was the fact that you're not prepared to look at your phone like this for two hours but if you can drive at the same time it seems like people really want to dig deeper and they want to hear like the more complicated version so to me that is very inspiring that that podcast is actually long form it gives me a lot of hope for for humanity that people seem really interested in hearing deeper more complicated conversations this is uh i don't understand it it's fascinating so the majority for this podcast listen to the whole thing this whole conversation we've been talking for an hour and 45 minutes and somebody will i mean most people will be listening to these words i'm speaking right now you wouldn't have thought that 10 years ago with where the world seemed to go so that's very positive i think that's really exciting and empowering the creator in there is is really exciting uh last question you also have a passion for just mobile in general how do you see the smartphone world this the digital space of uh of smartphones and just everything that's on the move whether it's uh internet of things and so on changing over the next 10 years and so on i think that one way to think about it is that computing might be moving out of these um multi-purpose devices the computer we had in the phone into specific specific you know specific purpose devices and you know it will be ambient that you know at least in my home you just shout something at someone and there's always like one of these speakers close enough and so uh you start behaving differently it's as if you have the internet ambient ambiently around you and you can ask it things so i think computing will kind of get more integrated and we when we won't necessarily think of it as as a connected to a device in the same thing in in the same way that we do today i don't know the the path to that maybe we used to have these desktop computers and then we partially replaced that with the with the laptops and left you know we had desktop at home and at work and then we got these phones and we started leaving the the laptop at home for a while and maybe the maybe for stretches of time you're going to start using the watch and you can leave your your phone at home like for a run or something and you know we're on this progressive path where you i think what what is happening with the voice is that you haven't you haven't interact interaction paradigm that doesn't require as large physical devices so i definitely think there's a future where you can have your your airpods and and your watch and you can do a lot of computing and i i don't think it's going to be this binary thing i think it's going to be like many of us still have a laptop we just use it less and so you shift your your consumption over and i don't know about ar glasses and so forth i'm excited about i spent a lot of time in that area but i still think it's quite far away ar vr all yes vr is is happening and working i think the the recent oculus quest is quite impressive i think ar is further away at least that type of ar i think but i do think your phone or watch or glasses understanding where you are and maybe what you're looking at and being able to give you audio cues about that or you can say like what is this and it tells you what it is that i think might happen you know you use your your watch or your glasses as a as a mouse pointer on reality i think it might be a while before i might be wrong i hope i'm wrong i think it might be a while before we walk around with these big like lab glasses that project things i agree with you there's a it's actually really difficult when you have to understand the physical world enough to uh project onto it well i lied about the last question uh because i just thought of audio and my favorite topic which is the movie her do you think whether it's part of spotify or not we'll have i don't know if you've seen the movie her absolutely and uh their audio is the primary form of interaction and the connection with another entity that you can actually have a relationship with actually fall in love with based on voice alone audio alone do you how far do you think that's possible first of all based on audio alone to fall in love with somebody somebody or well yeah let's go with somebody just have a relationship based on audio alone and second question to that can we create an artificial intelligence system that allows one to fall in love with it and her him with you so this is my personal personal answer speaking for me as a person the answer is quite unequivocally yes on on both i think what we just said about podcasts and the feeling of being in the middle of a conversation if you could have an assistant where and we just said that feels like a very personal setting so if you walk around with these headphones and this thing you're speaking with this thing all over the time that feels like it's in your brain i think it's it's going to be much easier to fall in love with than something that would be on your screen i think that's entirely possible and then from the you can probably answer this better than me but from the concept of if it's going to be possible to build a machine that that can achieve that i think whether you whether you think of it as a if you can fake it the philosophical zombie that it assimilates it enough or it somehow actually is i think there's it's only question if you if you ask me about time i'd have to be a financier but if you say given some half infinite time absolutely i think it's just atoms and arrangement of information well i personally think that love is a lot simpler than people think so we started with true romance and ended in love i don't see a better place to end beautiful gustav thanks so much for talking today thank you so much it was a lot of fun it was fun

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